LATVIA’S NATIONAL INVENTORY REPORTSEF (Standard Electronic Tables) for reporting of Kyoto units...

LATVIA’S NATIONAL INVENTORY REPORT 1990 – 2013

LATVIA’S NATIONAL INVENTORY

REPORT

Submission under UNFCCC

Common Reporting Formats (CRF) 1990 – 2013

2015


2

PREFACE

Latvia’s National Inventory under the United Nations Framework Convention on Climate Change (UNFCCC) and Regulation (EU) No 525/2013 of the European Parliament and of the

Council of 21 May 2013 on a mechanism for monitoring and reporting greenhouse gas emissions and for reporting other information at national and Union level relevant to climate change and repealing Decision No 280/2004/EC contains following parts:

1. Latvia’s National Inventory Report prepared using the reporting guidelines of UNFCCC (adopted by decision 24/CP.191);

2. CRF (Common Reporting Format) data tables for years 1990-2013 excluding KP-LULUCF data tables. The CRF tables are compiled with the UNFCCC CRF Reporter software (version 5.10.1).

3. SEF (Standard Electronic Tables) for reporting of Kyoto units (AAU, ERU, CER, t-CER, 1-CER, RMU) in registry 15.04.2015 and transfers of units during the year 2014.

According to Decision 13/CP.20 of the Conference of the Parties to the UNFCCC, CRF Reporter version 5.0.0 was not functioning in order to enable Annex I Parties to submit their CRF tables for the year 2015. In the same Decision, the Conference of the Parties reiterated

that Annex I Parties in 2015 may submit their CRF tables after 15/April, but no longer than the corresponding delay in the CRF Reporter availability. "Functioning" software means that

the data on the greenhouse emissions/removals are reported accurately both in terms of reporting format tables and XML format.

CRF reporter version 5.10 still contains issues in the reporting format tables and XML format

in relation to Kyoto Protocol requirements, and it is therefore not yet functioning to allow submission of all the information required under Kyoto Protocol.

Recalling the Conference of Parties invitation to submit as soon as practically possible, and

considering that CRF reporter 5.10 allows sufficiently accurate reporting under the UNFCCC (even if minor inconsistencies may still exist in the reporting tables, as per the Release Note

accompanying CRF Reporter 5.10), the present report is the official submission for the year 2015 under the UNFCCC. The present report is not an official submission under the Kyoto Protocol, even though some of the information included may relate to the requirements under

the Kyoto Protocol.

Authors:

Ministry of Environmental Protection and Regional Development of the Republic of Latvia (Agita Gancone), Latvian Environment, Geology and Meteorology Centre (Intars Cakars, Lauris Siņics, Ieva Sīle, Aiva Puļķe, Līga Rubene, Vita Ratniece), Institute of Physical

Energetics (Gaidis Klāvs, Larisa Gračkova), Latvian State Forest Research Institute "Silava" (Andis Lazdiņš, Aldis Butlers, Arta Bārdule, Ainārs Lupiķis), Latvia University of

Agriculture (Laima Bērziņa, Ritvars Sudars, Renāte Ondzule)

PART 1: ANNUAL INVENTORY SUBMISSION

INTRODUCTION Vita Ratniece Agita Gancone

1 http://unfccc.int/resource/docs/2013/cop19/eng/10a03.pdf#page=2


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TRENDS IN GREEN HOUSE GAS EMISSIONS Vita Ratniece Agita Gancone

ENERGY Ieva Sīle Gaidis Klāvs Larisa Gračkova

INDUSTRIAL PROCESSES AND PRODUCT USE Aiva Puļķe Vita Ratniece Līga Rubene

AGRICULTURE Laima Bērziņa Renāte Ondzule

LAND USE, LAND USE CHANGE AND FORESTRY Andis Lazdiņš Aldis Butlers Arta Bārdule Ainārs Lupiķis

WASTE Intars Cakars Lauris Siņics

RECALCULATIONS AND IMPROVEMENTS Vita Ratniece

PART 2: SUPPLEMENTARY INFORMATION REQUIRED UNDER ARTICLE 7,

PARAGRAPH 1

INFORMATION ON ACCOUNTING OF KYOTO UNITS Jeļena Lazdāne Mihalko Aiva Puļķe

INFORMATION ON CHANGES IN NATIONAL SYSTEM Vita Ratniece

INFORMATION ON CHANGES IN NATIONAL REGISTRY Jeļena Lazdāne Mihalko Aiva Puļķe

INFORMATION ON MINIMIZATION OF ADVERSE IMPACTS IN ACCORDANCE WITH

ARTICLE 3, PARAGRAPH 14 Agita Gancone


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ANNEXES

ANNEX 1: KEY CATEGORIES Vita Ratniece

ANNEX 2: ASSESSMENT OF UNCERTAINTY Vita Ratniece

ANNEX 3: OTHER DETAILED METHODOLOGICAL DESCRIPTIONS FOR INDIVIDUAL

SOURCE OR SINK CATEGORIES

Ieva Sīle, Gaidis Klāvs, Larisa Gračkova, Aiva Puļķe, Līga Rubene, Vita Ratniece, Andis Lazdiņš, Laima Bērziņa, Intars Cakars, Lauris Siņics ANNEX 4: THE NATIONAL ENERGY BALANCE FOR THE MOST RECENT INVENTORY

YEAR Ieva Sīle

ANNEX 5: DETAILED DISCUSSION OF METHODOLOGY AND DATA FOR

ESTIMATING CO2 EMISSIONS FROM FOSSIL FUEL COMBUSTION Ieva Sīle

ANNEX 6: OTHER Vita Ratniece


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Editing:

Aiva Eindorfa - Latvian Environment, Geology and Meteorology Centre (LEGMC)

Daiga Zute - Ministry of Agriculture, Forest Department

Ieva Līcīte - Ministry of Agriculture, Agriculture Department

Agita Gancone - Ministry of Environmental Protection and Regional Development of the Republic of Latvia, Climate Change Department

Helēna Rimša – Ministry of Environmental Protection and Regional Development of the Republic of Latvia, Climate Change Department

The Latvia’s inventory report as well as the CRF tables can be downloaded from address:

http://www.meteo.lv/

The contact person at Ministry of Environmental Protection and

Regional Development of the Republic of Latvia is:

Agita Gancone

Peldu street 25, Riga, LV – 1494, Latvia

E-mail: [email protected]

http://www.meteo.lv/

mailto:[email protected]


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CONTENT

PREFACE .................................................................................................................................. 2 LIST OF TABLES ................................................................................................................... 19

LIST OF FIGURES................................................................................................................. 26 UNITS AND ABBREVIATIONS............................................................................................ 29 EXECUTIVE SUMMARY ...................................................................................................... 31

ES.1 Background Information on GHG inventories and climate change ..................... 31

ES.1.1 Background information on climate change ................................................................. 31

ES.1.2 Background information on greenhouse gas inventories.............................................. 31

ES.2 Summary of National Emission and Removal-Related Trends ........................... 32

ES.2.1 GHG inventory .............................................................................................................. 32

ES.3 Overview of Source and Sink Category Emission Estimates and Trends .......... 36

ES.3.1 GHG inventory .............................................................................................................. 36

ES.4 Overview of Emission Estimates and Trends of Indirect GHG ............................ 37

PART 1: ANNUAL INVENTORY SUBMISSION................................................................. 40 1. INTRODUCTION........................................................................................................ 40

1.1 Background Information on Greenhouse Gas Inventories and Climate

Change... .............................................................................................................................. 40

1.1.1 Background information on climate change................................................................. 40

1.1.2 Background information on greenhouse gas inventories ............................................. 40

1.2 Description of the institutional national inventory arrangements ...................... 41

1.2.1 Overview of institutional, legal and procedural arrangements for compiling GHG inventory ................................................................................................................................... 41 1.2.2 Overview of inventory planning, preparation and management .................................. 44

1.2.3 Quality assurance, quality control and verification plan ............................................. 52 1.2.4 Quality Control procedures .......................................................................................... 54

1.2.4.1 Quality Assurance procedures ............................................................................................................ 54

1.2.4.2 Quality Control and Quality Assurance process improving the inventory ................................. 55

1.2.4.3 Documentation and Archiving............................................................................................................ 55

1.2.4.4 Verification activit ies ........................................................................................................................... 56

1.2.4.5 Treatment of confidentiality issues.................................................................................................... 57

1.2.5 Changes in national inventory arrangements since previous annual GHG inventory

submission................................................................................................................................. 58

1.3 Inventory preparation, data collection, processing and storage.......................... 58

1.3.1 GHG inventory.............................................................................................................. 58

1.4 Brief general description of methodologies and data sources used ..................... 59

1.4.1 GHG inventory.............................................................................................................. 59

1.5 Brief description of key categories ......................................................................... 61

1.5.1 GHG inventory.............................................................................................................. 61


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1.6 General uncertainty evaluation .............................................................................. 64

1.6.1 GHG inventory.............................................................................................................. 64

1.7 General assessment of completeness ...................................................................... 65

1.7.1 GHG inventory.............................................................................................................. 65

1.7.2 Completeness by timely coverage ................................................................................. 66

2. TRENDS IN GREENHOUSE GAS EMISSIONS ..................................................... 67

2.1 Description and interpretation of emission trends for aggregated greenhouse

gas emissions........................................................................................................................ 67

2.2 Description and interpretation of emission trends by gas.................................... 68

2.3 Description and interpretation of emission trends by category ........................... 69

2.3.1 Trends in ENERGY ....................................................................................................... 69

2.3.2 Trends in INDUSTRIAL PROCESSES AND PRODUCT USE..................................... 70 2.3.3 Trends in AGRICULTURE ........................................................................................... 71 2.3.4 Trends in LULUCF ....................................................................................................... 72

2.3.5 Trends in WASTE.......................................................................................................... 73

2.4 Description and interpretation of emission trends of indirect greenhouse gases

and SO2 ................................................................................................................................ 73

3. ENERGY (CRF 1) ....................................................................................................... 75

3.1 Overview of Sector ................................................................................................... 75

3.1.1 Quantitative overview ................................................................................................... 75 3.1.2 Description ................................................................................................................... 78

3.2 Fuel Combustion (CRF 1.A) ................................................................................... 83

3.2.1 Comparison of the sectoral approach with the reference approach (CRF 1.A (b), 1.A(c)) 87

3.2.1.1 Explanation of the difference .............................................................................................................. 89

3.2.1.2 Explanation of the fluctuations........................................................................................................... 92

3.2.1.3 Methodological issues.......................................................................................................................... 92

3.2.1.4 Time series consistency ....................................................................................................................... 94

3.2.1.5 Source-specific QA/QC and verification .......................................................................................... 94

3.2.2 International bunker fuels............................................................................................. 94

3.2.3 Feedstocks, reductants and other non-energy use of fuels (CRF 1.AD) ...................... 98 3.2.4 Energy Industries (CRF 1.A.1) ..................................................................................... 98

3.2.4.1 Source category description ................................................................................................................ 98

3.2.4.2 Methodological issues........................................................................................................................ 100

3.2.4.3 Uncertainties and time series consistency ...................................................................................... 107

3.2.4.4 Source-specific QA/QC and verification ........................................................................................ 108

3.2.4.5 Source-specific p lanned improvements .......................................................................................... 109

3.2.5 Manufacturing Industries and Construction (CRF 1.A.2) .......................................... 109

3.2.5.1 Source category description .............................................................................................................. 109



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3.2.6 Transport (CRF 1.A.3)................................................................................................ 119


3.2.6.2 Civil aviat ion (CRF 1.A.3.a)............................................................................................................. 121

3.2.6.3 Road transport (CRF 1.A.3.b)........................................................................................................... 124

3.2.6.4 Railways (CRF 1.A.3.c)..................................................................................................................... 134

3.2.6.5 Domestic Navigation (CRF 1.A.3.d) ............................................................................................... 136

3.2.6.6 Source specific recalculat ions........................................................................................................... 138

3.2.6.7 Source specific p lanned improvements........................................................................................... 138



3.2.7 Other Sectors (CRF 1.A.4).......................................................................................... 140






3.2.8 Other (CRF 1.A.5) ...................................................................................................... 148






3.3 Fugitive emissions from solid fuels and oil and natural gas (CRF 1.B) ............ 151

3.3.1 Fugitive emission from oil (CRF 1.B.2.a)................................................................... 152






3.3.2 Fugitive emissions from natural gas (CRF 1.B.2.b, CRF 1.B.2.c, CRF 1.B.2.d) ....... 155






3.4 CO2 Transport and Storage (CRF 1.C) ............................................................... 157

3.5 References ............................................................................................................... 157


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4. INDUSTRIAL PROCESSES AND PRODUCT USE (CRF 2)................................ 159

4.1 Overview of sector.................................................................................................. 159

4.1.1 Description ................................................................................................................. 161

4.2 Mineral industry (CRF 2.A).................................................................................. 163

4.2.1 Source category description ....................................................................................... 163 4.2.2 Cement Production (CRF 2.A.1) ................................................................................ 164





4.2.2.5 Source-specific recalcu lations .......................................................................................................... 170


4.2.3 Lime Production (CRF 2.A.2)..................................................................................... 170







4.2.4 Glass production (CRF 2.A.3) .................................................................................... 176







4.2.5 Ceramics (2.A.4.a) ...................................................................................................... 181







4.2.6 Other Process Uses of Carbonates (2.A.4.d).............................................................. 195


4.3 Chemical industry (CRF 2.B) ............................................................................... 195

4.3.1 Source category description ....................................................................................... 195

4.4 Metal industry (CRF 2.C) ..................................................................................... 195

4.4.1 Iron and Steel Production (CRF 2.C.1) ...................................................................... 195


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4.5 Non-energy products from fuels and solvent use (CRF 2.D) ............................. 201

4.5.1 Lubricant Use (CRF 2.D.1) ........................................................................................ 201






No recalculations were done in this sector. ...................................................................................................... 203

4.5.1.6 Source-specific improvements ......................................................................................................... 203

4.5.2 Paraffin Wax Use (CRF 2.D.2)................................................................................... 203







4.5.3 Other (CRF 2.D.3) ...................................................................................................... 205



4.5.3.3 Uncertainties and time series cons istency ...................................................................................... 210



4.6 Electronics industry (CRF 2.E) ............................................................................ 211

4.7 Product uses as OSD substitutes (CRF 2.F) ........................................................ 212

4.7.1 Refrigeration and Air Conditioning (CRF 2.F.1) ....................................................... 215

4.7.1.1 Domestic Refrigeration (CRF 2.F.1.b)............................................................................................ 215

4.7.1.1.1 Source category description ............................................................................................................215

4.7.1.1.2 Methodological issues .....................................................................................................................215

4.7.1.1.3 Uncertainties and time series consistency .......................................................................................218

4.7.1.1.4 Category specific QA/QC and verification ......................................................................................218

4.7.1.1.5 Category specific planned improvements ........................................................................................218

4.7.1.2 Commercial and Industrial Refrigeration (CRF 2.F.1.a, CRF 2.F.1.c) ..................................... 218




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4.7.1.3 Transport Refrigeration (CRF 2.F.1.d ) ........................................................................................... 221






4.7.1.4 Mobile and Stationary Air Conditioning (CRF 2.F.1.e, CRF 2.F.1.f) ....................................... 223






4.7.2 Foam Blowing Agents (CRF 2.F.2) ............................................................................ 225




4.7.2.4 Category specific QA/QC and verificat ion .................................................................................... 226

4.7.2.5 Category specific planned improvements ....................................................................................... 227

4.7.3 Fire Protection (CRF 2.F.3) ....................................................................................... 227






4.7.4 Aerosols (CRF 2.F.4.)................................................................................................. 228

4.7.4.1 Emissions from Metered Dose Inhalers (CRF 2.F.4.a) ................................................................ 228






4.8 OTHER PRODUCT MANUFACTURE AND USE (2.G) ................................. 230

4.8.1 Electrical Equipment (CRF 2.G.1) ............................................................................. 230






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4.8.2 N2O From Product Uses (CRF 2.G.3) ........................................................................ 231






4.8.3 Other (CRF 2.G.4) ...................................................................................................... 232






4.9 References ............................................................................................................... 234

5. AGRICULTURE (CRF 3) ......................................................................................... 236


5.2 Enteric Fermentation (CRF 3.A) .......................................................................... 240


5.2.2 Methodological issues ................................................................................................ 242 5.2.3 Uncertainties and time series consistency .................................................................. 247 5.2.4 Source-specific QA/QC and verification .................................................................... 247

5.2.5 Source-specific recalculations .................................................................................... 248 5.2.6 Source-specific planned improvements ...................................................................... 248

5.3 Manure Management (CRF 3.B) .......................................................................... 248

5.3.1 Source category description ....................................................................................... 248 5.3.2 Methodological issues ................................................................................................ 250

5.3.3 Uncertainties and time series consistency .................................................................. 256 5.3.4 Source-specific QA/QC and verification .................................................................... 256

5.3.5 Source-specific recalculations .................................................................................... 257 5.3.6 Source-specific planned improvements ...................................................................... 257

5.4 Agricultural Soils (CRF 3.D) ................................................................................ 257


5.4.3 Uncertainties and time series consistency .................................................................. 263 5.4.4 Source-specific QA/QC and verification .................................................................... 264 5.4.5 Source-specific recalculations .................................................................................... 264

5.4.6 Source-specific planned improvements ...................................................................... 264

5.5 Field Burning of Agricultural Residues (CRF 3.F)............................................. 264

5.6 Liming (CRF 3.G) .................................................................................................. 264

5.7 Urea Application (CRF 3.H) ................................................................................. 265

5.8 Other Carbon-containing Fertilizers (CRF 3.I) .................................................. 266


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5.9 Other (CRF 3.J)...................................................................................................... 266

6. LAND-USE, LAND-USE CHANGE AND FORESTRY (CRF 4)........................... 267


6.2 Land-use definitions and the classification systems used and their

correspondence to the LULUCF categories ................................................................... 277

6.3 Information on approaches used for representing land areas and on land-use

databases used for the inventory preparation................................................................ 278

6.4 Direct N2O emissions from managed soils (CRF 4 (IV)) .................................... 279


6.4.2 Information on approaches used for representing land areas and on land-use databases used for the inventory preparation ........................................................................ 279

6.4.3 Land-use definitions and the classification systems used and their correspondence to the LULUCF categories ......................................................................................................... 279 6.4.4 Methodological issues ................................................................................................ 279

6.4.5 Uncertainties and time-series consistency.................................................................. 280 6.4.6 Category-specific QA/QC and verification ................................................................ 280

6.4.7 Category-specific recalculations ................................................................................ 280 6.4.8 Category-specific planned improvements................................................................... 280

6.5 Indirect N2O emissions from managed soils (CRF 4 (IV)) ................................. 281

6.5.1 Source category description ....................................................................................... 281 6.5.2 Information on approaches used for representing land areas and on land-use

databases used for the inventory preparation ........................................................................ 281 6.5.3 Land-use definitions and the classification systems used and their correspondence to the LULUCF categories ......................................................................................................... 281

6.5.4 Methodological issues ................................................................................................ 281 6.5.5 Uncertainties and time-series consistency.................................................................. 282

6.5.6 Category-specific QA/QC and verification ................................................................ 282 6.5.7 Category-specific recalculations ................................................................................ 282 6.5.8 Category-specific planned improvements................................................................... 282

6.6 Forest land (CRF 4.A) ........................................................................................... 282


databases used for the inventory preparation ........................................................................ 287 6.6.3 Land-use definitions and the classification systems used and their correspondence to

the LULUCF categories ......................................................................................................... 288 6.6.4 Methodological issues ................................................................................................ 289

6.6.4.1 Forest land remain ing forest land..................................................................................................... 289

6.6.4.2 Land converted to forest land ........................................................................................................... 294

6.6.5 Uncertainties and time-series consistency.................................................................. 295


6.7 Cropland (CRF 4.B)............................................................................................... 297

6.7.1 Cropland remaining cropland (4.B.1) ........................................................................ 297


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6.7.1.2 Information on approaches used for representing land areas and on land-use databases used

for the inventory preparation............................................................................................................................... 299

6.7.1.3 Land-use definitions and the classification systems used and their correspondence to the

LULUCF categories.............................................................................................................................................. 299


6.7.1.5 Uncertainties and time-series consistency ...................................................................................... 301

6.7.1.6 Category-specific QA/QC and verificat ion .................................................................................... 302

6.7.1.7 Category-specific recalculat ions ...................................................................................................... 302

6.7.1.8 Category-specific p lanned improvements ..................................................................................... 302

6.7.2 Land converted to cropland ........................................................................................ 303


6.7.2.2 Information on approaches used for representing land areas and on land-use databases used

for the inventory preparation............................................................................................................................... 303







6.7.2.8 Category-specific p lanned improvements ..................................................................................... 306

6.8 Grassland (CRF 4.C) ............................................................................................. 306

6.8.1 Grassland remaining grassland ................................................................................. 306




6.8.1.3 Methodological data ........................................................................................................................... 307




6.8.1.7 Category-specific p lanned improvements ...................................................................................... 310

6.8.2 Land converted to grassland (4.C.2) .......................................................................... 310




6.8.2.3 Methodological data ........................................................................................................................... 311




6.8.2.7 Category-specific p lanned improvements ...................................................................................... 312

6.9 Wetlands (CRF 4.D)............................................................................................... 312



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6.9.2 Information on approaches used for representing land areas and on land-use

databases used for the inventory preparation ........................................................................ 313 6.9.3 Land-use definitions and the classification systems used and their correspondence to the LULUCF categories ......................................................................................................... 313

6.9.4 Methodological issues ................................................................................................ 313 6.9.5 Uncertainties and time-series consistency.................................................................. 314


6.10 Settlements (CRF 4.E) ........................................................................................... 315


6.10.2 Information on approaches used for representing land areas and on land-use databases used for the inventory preparation ........................................................................ 316 6.10.3 Land-use definitions and the classification systems used and their correspondence to

the LULUCF categories ......................................................................................................... 317 6.10.4 Methodological issues ................................................................................................ 317

6.10.4.1 Settlements remaining settlements .............................................................................................. 317

6.10.4.2 Land converted to settlements...................................................................................................... 318

6.10.5 Category-specific planned improvements................................................................... 320

6.10.6 Uncertainties and time-series consistency.................................................................. 320 6.10.7 Category-specific QA/QC and verification ................................................................ 320 6.10.8 Category-specific recalculations ................................................................................ 321

6.11 Other Land (CRF 4.F) ........................................................................................... 321

6.12 Biomass burning (CRF 4(V)) ................................................................................ 322

6.12.1 Source category description ....................................................................................... 322 6.12.2 Information on approaches used for representing land areas and on land-use databases used for the inventory preparation ........................................................................ 323

6.12.3 Land-use definitions and the classification systems used and their correspondence to the LULUCF categories ......................................................................................................... 324

6.12.4 Methodological issues ................................................................................................ 324

6.12.4.1 Forest wildfires ............................................................................................................................... 324

6.12.4.2 Grassland wildfires ........................................................................................................................ 325

6.12.4.3 Controlled fires in forests ............................................................................................................. 325

6.12.5 Uncertainties and time-series consistency.................................................................. 326 6.12.6 Category-specific QA/QC and verification ................................................................ 326

6.12.7 Category-specific recalculations ................................................................................ 326 6.12.8 Category-specific planned improvements................................................................... 327

6.13 Harvested wood products (CRF 4.G) ................................................................... 327


databases used for the inventory preparation ........................................................................ 327 6.13.3 Land-use definitions and the classification systems used and their correspondence to

the LULUCF categories ......................................................................................................... 328 6.13.4 Methodological issues ................................................................................................ 328 6.13.5 Uncertainties and time-series consistency.................................................................. 330

6.13.6 Category-specific QA/QC and verification ................................................................ 330


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6.13.7 Category-specific recalculations, if applicable, including changes made in response to

the review process................................................................................................................... 330 6.13.8 Category-specific planned improvements................................................................... 331

6.14 References ............................................................................................................... 331

7. WASTE (CRF 5) ........................................................................................................ 335


7.1.1 Quantitative overview ................................................................................................. 335 7.1.2 Description ................................................................................................................. 335

7.2 Solid Waste Disposal (CRF 5.A) ........................................................................... 337


7.2.3 Uncertainties and times series consistency ................................................................ 342 7.2.4 Source-specific QA/QC and verification .................................................................... 342 7.2.5 Source-specific recalculation ..................................................................................... 343

7.2.6 Source specific planned improvements....................................................................... 343

7.3 Biological treatment and solid waste (CRF 5.B) ................................................. 343

7.3.1 Composting (CRF 5.B.1) ............................................................................................ 343



7.3.1.3 Uncertainties and times series consistency..................................................................................... 344




7.3.2 Anaerobic Digestion at Biogas Facilities (CRF 5.B.2) .............................................. 345

7.4 Incineration and open burning of waste (CRF 5.C) ........................................... 345

7.4.1 Waste Incineration (CRF 5.C.1) ................................................................................. 345







7.4.2 Open Burning of Waste (CRF 5.C.2) .......................................................................... 349

7.5 Wastewater treatment and discharge (CRF 5.D)................................................ 349

7.5.1 Domestic Wastewater (CRF 5.D.1) ............................................................................ 349







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7.5.2 Industrial Wastewater (CRF 5.D.2)............................................................................ 356







7.5.3 Other (CRF 5.D.3) ...................................................................................................... 360







8. OTHER (CRF 6) ........................................................................................................ 362

9. INDIRECT CO2 AND NITROUS OXIDE EMISSIONS......................................... 363 10. RECALCULATIONS AND IMPROVEMENTS ...................................................... 364

10.1 Explanations and justifications for recalculations, including KP-LULUCF

inventory ............................................................................................................................ 364

10.1.1 GHG inventory............................................................................................................ 364

10.2 Implication for emission levels.............................................................................. 364

10.2.1 GHG inventory............................................................................................................ 364

10.3 Implications for emission trends, including time series’ consistency ................ 364

10.3.1 GHG inventory............................................................................................................ 364

10.4 Recalculations, including in response to the review process, and planned

improvements to the inventory ........................................................................................ 364

10.4.1 GHG inventory............................................................................................................ 364

PART 2: SUPPLEMENTARY INFORMATION REQUIRED UNDER ARTICLE 7,

PARAGRAPH 1 ..................................................................................................................... 377 11. INFORMATION ON ACCOUNTING OF KYOTO UNITS.................................... 377

11.1 Background information ....................................................................................... 377

11.2 Summary of information reported in the SEF tables ......................................... 377

11.3 Discrepancies and notifications ............................................................................ 377

11.3.1 List of discrepant transactions.................................................................................... 377 11.3.2 List of CDM notifications ........................................................................................... 377

11.3.3 List of non-replacements............................................................................................. 378 11.3.4 List of invalid units ..................................................................................................... 378 11.3.5 Actions and changes to address discrepancies........................................................... 378


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11.4 Publicly accessible information ............................................................................ 378

12. INFORMATION ON CHANGES IN NATIONAL SYSTEM ................................. 379 13. INFORMATION ON CHANGES IN NATIONAL REGISTRY ............................. 380 14. INFORMATION ON MINIMIZATION OF ADVERSE IMPACTS IN

ACCORDANCE WITH ARTICLE 3, PARAGRAPH 14 ..................................................... 383

14.1 Cross-border bilateral development assistance................................................... 383

14.2 Key instruments for climate change mitigation in Latvia .................................. 383

14.3 Conclusion .............................................................................................................. 384

14.4 REFERENCES....................................................................................................... 384

ANNEXES TO THE NATIONAL INVENTORY REPORT ................................................ 385

Annex 1 Key Categories ................................................................................................... 385

Annex 2: Assessment of Uncertainty............................................................................... 423

Annex 3: Other Detailed methodological descriptions for individual source or sink

categories ........................................................................................................................... 464

Annex 4: The national energy balance for the most recent inventory year ................ 488

Annex 5: Detailed discussion of methodology and data for estimating CO2 emissions

from fossil fuel combustion .............................................................................................. 492

Annex 6: Other................................................................................................................. 499


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LIST OF TABLES

Table 1.1 Institutions responsible for activity data and calculating emissions ......................... 45

Table 1.2 Inventory preparation plan for 2015 ......................................................................... 49

Table 1.3 Main data sources for activity data and emission values.......................................... 60

Table 1.4 Key categories in 2013 ............................................................................................. 61

Table 1.5 Uncertainties of 2013 emission estimates ................................................................ 65

Table 3.1 Consumption of energy resources in Latvia (TJ) ..................................................... 75

Table 3.2 Electricity production and consumption in Latvia (TJ) ............................................ 77

Table 3.3 Heat production and consumption in Latvia (TJ) ..................................................... 77

Table 3.4 GHG emissions from Energy sector in 1990–2013 (Gg) ......................................... 79

Table 3.5 Key categories in Energy sector in 2013 .................................................................. 82

Table 3.6 Reported emissions from fuel combustion in Latvia in 2013................................... 83

Table 3.7 Difference (%) between Sectoral and Reference approach data (PJ) and CO 2

emissions (Gg) .......................................................................................................................... 87

Table 3.8 Carbon emission factors (t/TJ) ................................................................................. 93

Table 3.9 Fuel consumption in international transport (TJ) ..................................................... 95

Table 3.10 Emission factors used in the calculation of emissions from International Bunkering .................................................................................................................................................. 97

Table 3.11 SO2 Emission factors used for diesel oil in the SO2 calculation of emissions International Bunkering ............................................................................................................ 98

Table 3.12 SO2 Emission factors used for RFO in the SO2 calculation of emissions

International Bunkering ............................................................................................................ 98

Table 3.13 Emissions from Energy industries (CRF 1.A.1) in 1990–2013 (Gg) ..................... 99

Table 3.14 Characteristics of liquid solid and solid biomass fuels and estimated CO2 emission

factors ..................................................................................................................................... 101

Table 3.15 Characteristics of natural gas and estimated CO2 emission factors...................... 102

Table 3.16 Characteristics of methane obtained from landfill gas and estimated CO2 emission factors ..................................................................................................................................... 104

Table 3.17 Characteristics of methane obtained from sludge gas and estimated CO 2 emission

factors ..................................................................................................................................... 104

Table 3.18 CH4, N2O, NOx, CO, NMVOC emission factors used in CRF 1.A.1. Energy

Industries (Gg/PJ) ................................................................................................................... 105

Table 3.19 Comparison of country specific and 2006 IPCC default CO2 emission factor values (Gg/PJ) .................................................................................................................................... 109

Table 3.20 Emissions from Manufacturing industries and construction (CRF 1.A.2) in 1990–2013 (Gg) ................................................................................................................................ 110

Table 3.21 CO2 emission factors, carbon content and NCV for municipal wastes by waste types (Gg/PJ) .......................................................................................................................... 112

Table 3.22 CO2 emissions from municipal waste non-biomass and biomass fractions by waste

types in 2008-2013 ................................................................................................................. 113


20

Table 3.23 CO2 emission factors, carbon content and NCV for industrial waste .................. 113

Table 3.24 CH4, N2O, NOx, NMVOC, CO emission factors (Gg/PJ) ................................... 115


Table 3.26 Summary of source category description, CRF 1.A.3.a ....................................... 122

Table 3.27 Fuel consumption in domestic civil aviation (TJ) ................................................ 123

Table 3.28 Emission factors used in the calculation of emissions from civil aviation........... 123

Table 3.29 GHG emissions in road transport by vehicle types (Gg CO2 eq) ......................... 124

Table 3.30 Summary of source category description, CRF 1.A.3.b ....................................... 127

Table 3.31 Activity data and sources used for emission calculation in road transport .......... 128

Table 3.32 Fuel consumption in road transport (TJ) .............................................................. 129

Table 3.33 Summary of source category description, CRF 1.A.3.c ....................................... 134

Table 3.34 Fuel consumption in railway (TJ)......................................................................... 135

Table 3.35 Emission factors used in the calculation of emissions from railway.................... 135

Table 3.36 Summary of source category description, CRF 1.A.3.d ....................................... 137

Table 3.37 Fuel consumption in domestic navigation (TJ) .................................................... 138

Table 3.38 Emission factors used in the calculation of emissions from navigation ............... 138

Table 3.39 Recalculations for Sub-category CRF 1.A.3 Transport........................................ 138

Table 3.40 Emissions from Other Sectors (CRF 1.A.4) in 1990–2013 (Gg) ......................... 140

Table 3.41 CH4, N2O, NOx, NMVOC, CO emission factors (Gg/PJ) .................................... 143

Table 3.42 CH4, N2O, NOx, NMVOC, CO emission factors for gasoline, diesel and RFO

(kg/Mg) ................................................................................................................................... 144


Table 3.44 Emissions from Other sources (CRF 1.A.5) in 1990–2013 (Gg) ......................... 148

Table 3.45 CO2, CH4, N2O, NOx, NMVOC, CO emission factors ........................................ 150

Table 3.46 Reported fugitive CO2, CH4, NMVOC emissions in Latvia in 1990-2013 (Gg) . 151

Table 3.47 Activity data used for NMVOC emission calculation in 1990–2013 (PJ) ........... 153

Table 3.48 Fugitive CH4, CO2 and NMVOC emissions from natural gas 1990-2013 (Gg)... 155

Table 3.49 Amounts of natural gas leaked in 1990-2013 (106 m3) ....................................... 156

Table 4.1 Reported GHG emissions from Industrial Processes and Product Use sector in

Latvia in 2013 ......................................................................................................................... 160

Table 4.2 Greenhouse gas emission trend in 1990–2013 (Gg CO2 eq) .................................. 161

Table 4.3 Emissions from 2.A Mineral Products in 1990–2013 (Gg) .................................... 163

Table 4.4 Average CaO content in clinker (%) and average CO2 emission factor in 1990–2013 (t CO2 / t clinker) .................................................................................................................... 167

Table 4.5 EFs for cement clinker production emission estimation (Gg/Gg) .......................... 167

Table 4.6 CKD correction factor in 1990–2013 ..................................................................... 168


21

Table 4.7 CO2 emissions from lime production in 1990–2013 (Gg)...................................... 170

Table 4.8 CO2 emission factors for limestone and dolomite use (t CO2/t raw material)........ 172

Table 4.9 Amount of produced lime in 1990–2013 (Gg) ....................................................... 174

Table 4.10 Limestone and dolomite use activity data in lime production (t CO2/t raw material)

................................................................................................................................................ 175

Table 4.11 NMVOC emissions from glass fibre and glass production in 1990–2013 (Gg) .. 177

Table 4.12 CO2 emissions from limestone, dolomite and soda ash use in glass fibre and glass production in 1990–2013 (Gg) .............................................................................................. 178

Table 4.13 Emission factors for materials use in glass production (t emissions / t product or

raw material) ........................................................................................................................... 179

Table 4.14 Activity data for raw materials use in glass production 1990-2013 (Gg) ............ 180

Table 4.15 CO2 emissions from tile production in 1995-2013 (Gg) ...................................... 181

Table 4.16 Activity data for tiles production in 1995-2013 (Gg) ........................................... 182

Table 4.17 Data and assumptions used for CO2 emission estimation for 1990-1992 ............ 183

Table 4.18 Data and assumptions used for CO2 emission estimation from 1st bricks production plant ........................................................................................................................................ 184

Table 4.19 Data and assumptions used for CO2 emission estimation from 2nd bricks production plant ...................................................................................................................... 186

Table 4.20 Data and assumptions used for CO2 emission estimation from 3rd bricks

production plant ...................................................................................................................... 188

Table 4.21 Data and assumptions used for CO2 emission estimation from 3rd bricks

production plant (continuation) .............................................................................................. 188

Table 4.22 Data and assumptions used for CO2 emission estimation from 4th bricks production plant ...................................................................................................................... 190

Table 4.23 Data and assumptions used for CO2 emission estimation from 5th bricks production plant ...................................................................................................................... 192

Table 4.24 Emissions from 2.C Metal Production in 1990–2013 (Gg) .................................. 196

Table 4.25 Data for estimation of CO2 emissions from steel production (tonnes) ................. 198

Table 4.26 Emission factors of metal production (t/t) ............................................................ 199

Table 4.27 CO2 emissions from lubricant use 1990-2013 (Gg).............................................. 201

Table 4.28 Activity data for lubricant use 1990-2013 ............................................................ 202

Table 4.29 CO2 emissions from paraffin wax use 1990-2013 (Gg) ....................................... 203

Table 4.30 Activity data from paraffin wax use 1990-2013 (Gg) .......................................... 204

Table 4.31 Data from Urea use 2006-2013 (Gg) .................................................................... 206

Table 4.32 Emission factors for asphalt roofing and Road paving in 1990–2013 ................. 210

Table 4.33 Total F-gases emissions under 2.F and 2.G sectors (1995-2013) (Gg CO2 eq) ... 214

Table 5.1 Greenhouse gas emissions (Gg CO2 eq.) in the agricultural sector, 1990–2013 .... 236

Table 5.2 Number of livestock (thousand heads), 1990–2013 ............................................... 238

Table 5.3 Sown area (thousand ha) of agricultural crops, 1990–2013 ................................... 239


22

Table 5.4 Sown area (thousand ha) of agricultural crops, 1990–2013 ................................... 240

Table 5.5 Reported emissions under the subcategory Enteric Fermentation.......................... 241

Table 5.6 Methane emissions (Gg) from Enteric Fermentation by livestock category, 1990–2013 ........................................................................................................................................ 241

Table 5.7 Default methane emission factors from Enteric Fermentation ............................... 242

Table 5.8 Average milk yield per cow (kg year-1) and fat content (%) .................................. 244

Table 5.9 The number (thousand heads) of non-dairy cattle by sub-categories in Latvia, 1990-2013 ........................................................................................................................................ 245

Table 5.10 Calculated gross energy (GE) intake (MJ day-1), 1990-2013 ............................... 246

Table 5.11 Calculated emission factors (kg CH4 head-1year-1) of methane emission from Enteric Fermentation, 1990-2013 ........................................................................................... 247

Table 5.12 Review of emission factors for enteric fermentation methane emissions ............ 248

Table 5.13 Reported emissions under the subcategory Manure Management ....................... 249

Table 5.14 Methane emissions (Gg) from Manure Management by livestock category 1990-

2013 ........................................................................................................................................ 249

Table 5.15 Nitrous oxide emissions (Gg) from Manure Management by livestock category,

1990-2013* ............................................................................................................................. 250

Table 5.16 Methane emission factors from Manure Management ......................................... 251

Table 5.17 Calculated emission factors (kg CH4 head-1year-1) used for estimation of methane

emission from manure management for dairy and non-dairy cattle, 1990-2013.................... 252

Table 5.18 Average N excretions (N, kg year-1) per head of animal ...................................... 254

Table 5.19 N excretion rates (kg N animal-1 yr-1) used in the estimates of N2O emissions for dairy and non-dairy cattle, 1990-2013 .................................................................................... 255

Table 5.20 Review of emission factors for methane emission calculation from manure

management ............................................................................................................................ 256

Table 5.21 Reported emissions under the subcategory Agricultural Soils ............................. 257

Table 5.22 Nitrous oxide emissions (Gg) from Managed Soils, 1990-2013 .......................... 258

Table 5.23 Nitrous oxide emissions (Gg) from N inputs to managed soils, 1990-2013 ........ 258

Table 5.24 Statistics of organic N fertilisers applied to soils ................................................. 260

Table 5.25 Default emission, volatilization and leaching factors for direct and indirect N 2O emissions calculation .............................................................................................................. 262

Table 5.26 Input values for direct nitrous oxide emission calculations from managed soils 263

Table 5.27 Consumed lime (t year-1) and calculated CO2 (Gg) emissions, 1990-1913 ........ 265

Table 5.28 Urea fertilisation (tonnes yr-1) statistics and calculated CO2 emissions (Gg), 1990-

2013 ........................................................................................................................................ 265

Table 6.1 Areas of IPCC land-use classes in 1990-2013, 1000 ha ......................................... 268

Table 6.2 Summary of aggregated GHG emissions in 1990-2013, Gg CO2 eq. annually...... 268

Table 6.3 Summary of land use change matrix ...................................................................... 269

Table 6.4 Land use change matrix .......................................................................................... 270


23

Table 6.5 LULUCF key categories......................................................................................... 277

Table 6.6 Summary of land use changes according to the NFI data ...................................... 278

Table 6.7 Tier 1 N2O emission/removal factors for drained organic soils in all land-use categories ................................................................................................................................ 279

Table 6.8 Distribution of drained, naturally dry and wet mineral and organic soils in Latvia's forests...................................................................................................................................... 283

Table 6.9 Annual increment of growing stock of trees on the forest land remaining forest, 1000 m3 ................................................................................................................................... 284

Table 6.10 Increment of growing stock of timber on the Land converted to forest ............... 285

Table 6.11 Updated figures of harvesting stock, in 1000 m3 .................................................. 285

Table 6.12 Total area of the land converted to forest ............................................................. 287

Table 6.13 Area of the land converted to forest more than 20 years ago ............................... 288

Table 6.14 Average periodic gross increment of living trees (m3 ha- 1 yr)........................... 290

Table 6.15 Wood density ........................................................................................................ 291

Table 6.16 Coefficients for calculation of above ground biomass from stem biomass .......... 291

Table 6.17 Average carbon stock in living biomass ............................................................... 291

Table 6.18 Average periodic mortality (m3 ha-1 yr.) .............................................................. 291

Table 6.19 Emission factors for rewetted organic soils, tonnes C ha-1 yr-1 ............................ 293

Table 6.20 Uncertainty of the forest land use data in 2013 .................................................... 295

Table 6.21 Area of Cropland .................................................................................................. 298

Table 6.22 Assumptions for calculation of carbon stock changes in living and dead biomass in

cropland .................................................................................................................................. 300

Table 6.23 Uncertainty of the cropland use data in 2013 ....................................................... 301

Table 6.24 Decision support table to estimate conversion of grassland, cropland and forest

land ......................................................................................................................................... 304

Table 6.25 Changes in calculations ........................................................................................ 306

Table 6.26 Relative stock changes for grassland management in mineral soils ..................... 308

Table 6.27 Assumptions for calculation of carbon stock changes in living and dead biomass in grassland ................................................................................................................................. 308

Table 6.28 Relative stock changes due to grassland management on mineral soils ............... 309

Table 6.29 Uncertainty of the grassland use data in 2013 ...................................................... 309

Table 6.30 Assumptions for calculation of carbon stock changes in living and dead biomass in wetlands .................................................................................................................................. 314

Table 6.31 Uncertainty of the wetland use data in 2013 ........................................................ 314

Table 6.32 Uncertainty of the settlements use data in 2013 ................................................... 320

Table 6.33 Burnt area of grassland in m² and ha .................................................................... 323

Table 6.34 Emission factor for each GHG (g kg¯¹ dry matter burnt) .................................... 325

Table 6.35: Emission factors for grassland's wildfires ........................................................... 325


24

Table 6.36 Emission factors (g kg-1 dry matter burnt) for various types of burning ............. 326

Table 6.37 HWP categories and their subcategories .............................................................. 328

Table 6.38 Assumptions for estimation of carbon stock in harvested wood products ........... 329

Table 6.39 Common coefficients to estimate balance between CO2 emissions and removals in

harvested wood products ........................................................................................................ 330

Table 7.1 Generated wastes in Latvia (Gg) ............................................................................ 337

Table 7.2 Reported emissions under subcategory Solid Waste Disposal on Land................. 337

Table 7.3 Estimated Disposed amounts from 1970 – 2002 .................................................... 338

Table 7.4 Disposed solid waste amounts from 2002-2013 (Gg) ............................................ 339

Table 7.5 Reported emissions under composting ................................................................... 343

Table 7.6 Composted waste amounts and emissions .............................................................. 344

Table 7.7 Reported emissions under category Waste Incineration......................................... 345

Table 7.8 Burned bodies in Riga crematorium ...................................................................... 346

Table 7.9 Default emission factors for CO2 emission calculation .......................................... 347

Table 7.10 Incinerated waste amounts without energy recovery ........................................... 347

Table 7.11 Emission factors for indirect gases ....................................................................... 348

Table 7.12 Emission factors for indirect gases from cremation ............................................. 348

Table 7.13 MCF values applied depending on type and level of treatment ........................... 351

Table 7.14 Activity data for calculation CH4 emissions from Domestic Waste Water Handling

sector ....................................................................................................................................... 351

Table 7.15 Calculation of CH4 emission from Domestic Waste Water Handling sector (2013)

................................................................................................................................................ 352

Table 7.16 Characteristics of sewage sludge in Latvia ........................................................... 352

Table 7.17 Calculation of CH4 emission from sewage sludge (2013).................................... 353

Table 7.18 Comparison of Latvian protein consumption data with data from neighbour countries (Lithuania and Estonia) ........................................................................................... 353

Table 7.19 Activity data for estimation emissions of N2O from Domestic Waste Water Handling sector ....................................................................................................................... 354

Table 7.20 Uncertainties for Domestic Waste Water Handling sector................................... 355

Table 7.21 Assumptions used for calculation of CH4 emissions from Industrial Waste Water Handling ................................................................................................................................. 357

Table 7.22 Activity data for calculation CH4 emissions from Industrial Waste Water Handling sector (amount of products, th. t/yr) ....................................................................................... 357

Table 7.23 Calculation example of emission of CH4 from Industrial Waste Water Handling

(2013)...................................................................................................................................... 358

Table 7.24 Activity data for calculation N2O emissions from Industrial Waste Water Handling

sector ....................................................................................................................................... 358

Table 7.25 Uncertainties for Industrial Waste Water Handling sector ................................... 359


25

Table 7.26 Activity data for calculation NMVOC emissions from Waste Water Handling

sector ....................................................................................................................................... 360

Table 10.1 Sector specific improvements needs of Latvia`s national GHG inventory .......... 365

Table 10.2 Response to the review process ............................................................................ 369


26

LIST OF FIGURES

Figure 1.1 The structure of Latvia`s National Inventory System ............................................. 42

Figure 1.2 Inventory Process .................................................................................................... 52

Figure 1.3 QA/QC activities of the inventory .......................................................................... 53

Figure 2.1 Latvia`s aggregated greenhouse gas emissions in 1990-2013 (Gg CO2 eq) ........... 67

Figure 2.2 Latvia`s greenhouse gas emissions by source 1990-2013 excluding LULUCF ..... 68

Figure 2.3 Trend in GHG emissions from Energy sector in 1990-2013 (Gg CO2 eq.) ............ 69

Figure 2.4 GHG emissions development in transport 1990 – 2013 (Gg CO2 eq.) ................... 70

Figure 2.5 Trend in GHG emissions from IPPU sector in 1990-2013 (Gg CO2 eq.) ............... 70

Figure 2.6 Trends of emissions by category within the sector, 1990-2013 (Gg, CO2 eq.)....... 71

Figure 2.7 Summary of the net emissions in LULUCF sector (Gg CO2 eq.) ........................... 72

Figure 2.8 Trend in GHG emissions from Waste sector in 1990-2013 (Gg CO2 eq.) .............. 73

Figure 2.9 Total indirect greenhouse gas emissions trend 1990-2013 (Gg) ............................. 74

Figure 3.1 Share of emissions in the Energy sector in 1990-2013 (%; Gg CO2 eq) ................ 79

Figure 3.2 GHG emissions from Energy sector 1990–2013 (Gg CO2 eq) ............................... 80

Figure 3.3 Total indirect GHG emissions from fuel combustion in 1990–2013 (Gg) ............. 82

Figure 3.4 Difference in fuel consumption of Liquid fuels between Reference and Sectoral Approach................................................................................................................................... 90

Figure 3.5 Difference in fuel consumption of Gaseous fuels between Reference and Sectoral Approach................................................................................................................................... 90

Figure 3.6 Difference in fuel consumption of Peat (including Peat briquettes) between

Reference and Sectoral Approach ............................................................................................ 91

Figure 3.7 Difference in consumption of Other fuels between Reference and Sectoral Approach................................................................................................................................... 91

Figure 3.8 Difference in consumption of Solid fuels between Reference and Sectoral Approach................................................................................................................................... 92

Figure 3.9 Emissions from International Bunkers (Gg CO2 eq.).............................................. 95

Figure 3.10 Loaded, unloaded cargo at ports in Latvia, thsd t ................................................. 96

Figure 3.11 Structure of loaded goods at ports in Latvia, thsd t. .............................................. 97

Figure 3.12 Loaded, unloaded cargo and served vessels at Riga port (2000 = 1) .................... 97

Figure 3.13 Fuel consumption in Energy Industries (CRF 1.A.1) for 1990-2013 (PJ) .......... 106

Figure 3.14 Fuel consumption in Main activity electricity and heat production (CRF 1.A.1.a) and average temperature in Latvia.......................................................................................... 107

Figure 3.15 Fuel consumption in Manufacturing industries and constructio n (CRF 1.A.2) for

1990-2013 (PJ)........................................................................................................................ 116

Figure.3.16 GHG emissions development in transport 1990 – 2013 ..................................... 119

Figure 3.17 GHG emissions in transport by sub-sectors in 2013 ........................................... 120

Figure 3.18 GHG emissions in transport sector by gases in 2013 .......................................... 120


27

Figure 3.19 Fuel consumption in transport by fuel type (2013) ............................................. 121

Figure 3.20 GHG emissions in civil aviation (Gg CO2 eq) .................................................... 121

Figure 3.21 Fuel consumption in domestic civil aviation (TJ) ............................................... 123

Figure 3.22 GHG emissions in road transport (Gg CO2 eq) ................................................... 124

Figure 3.23 CO2 emissions in road transport by vehicle types ............................................... 125

Figure 3.24 CH4 emissions in road transport by vehicle types ............................................... 126

Figure 3.25 N2O emissions in road transport by vehicle types............................................... 126

Figure 3.26 Development of Fuel consumption in road transport (TJ) .................................. 130

Figure 3.27 Distribution of passenger cars fleet by sub-classes ............................................. 130

Figure 3.28 Distribution of gasoline passenger cars fleet by layers ....................................... 131

Figure 3.29 Distribution of diesel oil passenger cars fleet by layers ...................................... 131

Figure 3.30 Distribution of light duty vehicles fleet by sub-classes....................................... 132

Figure 3.31 Distribution of light duty vehicles fleet by layers ............................................... 132

Figure 3.32 Distribution of heavy duty vehicles fleet by sub-classes .................................... 133

Figure 3.33 Distribution of heavy duty vehicles fleet by layers ............................................. 133

Figure 3.34 Development of GHG emissions in railway (Gg CO2 eq) .................................. 134

Figure 3.35 Development of fuel consumption in railway (TJ) ............................................. 135

Figure 3.36 GHG emission development in domestic navigation (Gg CO2 eq)..................... 136

Figure 3.37 Loaded, unloaded cargo and served vessels at Riga port (2000 = 1) .................. 136

Figure 3.38 Development of gasoline and diesel oil fuel consumption in domestic navigation ................................................................................................................................................ 137

Figure 3.39 Fuel consumption in Other sectors (CRF 1.A.4) for 1990-2013 (PJ) ................. 145

Figure 3.40 Fuel consumption in Other sectors (CRF 1.A.4) for stationary combustion and heating degree days in Latvia ................................................................................................. 146

Figure 3.41 Fugitive NMVOC emissions from oil products in 1990–2013 and retail price for gasoline in 1996-2013............................................................................................................. 152

Figure 4.1 GHG emissions from Industrial Processes and Product Use in 1990–2013 ......... 163

Figure 4.2 Emissions from Cement production in 1990–2013 (Gg) ...................................... 165

Figure 4.3 CO2 emission from limestone and dolomite use in lime and steel production in

1990–2013 (Gg) ...................................................................................................................... 171

Figure 4.4 Emissions from raw materials used in glass production 1990-2013 (Gg) ............ 176

Figure 4.5 NMVOC emissions from Solvent Use in 1990–2013 (Gg) .................................. 205

Figure 4.6 Emissions from asphalt roofing and road paving in 1990–2013 (Gg) .................. 206

Figure 4.7 NMVOC emissions from the different Solvent Use subsectors in 1990–2013 (Gg)

................................................................................................................................................ 207

Figure 4.8 HFC emissions from 2.F Product Uses as ODS Substitutes and HFC and SF6

emissions from 2.G Other Product Manufacture and Use (Gg CO2 eq)................................. 213

Figure 6.1 GHG emissions in forest land remaining forest .................................................... 286


28

Figure 6.2 GHG emissions in land converted to forest .......................................................... 286

Figure 6.3 Summary of GHG emissions in forest land .......................................................... 287

Figure 6.4 Emissions due to rewetting ................................................................................... 294

Figure 6.5 Summary of GHG emissions in cropland remaining cropland ............................. 298

Figure 6.6 Sample area used to estimate area of ditches in organic soils ............................... 301

Figure 6.7 Summary of GHG emissions from land converted to cropland ............................ 303

Figure 6.8 Summary of GHG emissions from grassland remaining grassland ...................... 307

Figure 6.9 Summary of GHG emissions from land converted to grassland ........................... 311

Figure 6.10 Summary of GHG emissions from wetlands....................................................... 313

Figure 6.11 Summary of GHG emissions from settlements remaining settlements ............... 316

Figure 6.12 Summary of GHG emissions from land converted to settlements ...................... 316

Figure 6.13 Assumption for average growing stock of living biomass in forest areas converted to settlements .......................................................................................................................... 319

Figure 6.14 Forest fires in Latvia in 2011-2013 (from yellow in 2011 to red in 2013) ......... 322

Figure 6.15 Aggregated emissions from biomass burning ..................................................... 323

Figure 6.16 Area of forest fires and biomass in burnt area .................................................... 324

Figure 6.17 Net emissions from HWP during period 1990-2013........................................... 327

Figure 7.1 Total GHG emissions from Waste sector 1990-2013 (Gg CO2 equivalents)........ 336

Figure 7.2 GHG Emissions in Waste subsectors 1990-2013 (Gg CO2 equivalents) .............. 336

Figure 7.3 Disposed waste amounts in Latvia (Gg) ............................................................... 340

Figure 7.4 Recovered CH4 from waste disposing (Gg) .......................................................... 340

Figure 7.5 CH4 emissions from waste disposing (Gg) ............................................................ 341

Figure 7.6 Total emissions from waste composting in CO2 equivalent (Gg) ......................... 344

Figure 7.7 CO2 emissions from Waste Incineration by waste type (Gg)................................ 346

Figure 7.8 Emissions from domestic Waste Water Handling sector (Gg CO2 eq.) ................ 350

Figure 7.9 Emissions from Industrial Waste Water Handling sector (Gg CO2 eq.) ............... 356


29

UNITS AND ABBREVIATIONS

t 1 tonne (metric) = 1 megagram (Mg) = 106 g

Mg 1 megagram = 106 g = 1 tonne (t)

Gg 1 gigagram = 109 g = 1 kilotonne (kt)

Tg 1 teragram = 1012 g = 1 megatonne (Mt)

TJ 1 terajoule = 1000 Gigajoule = 1012 J

AWMS - Animal waste management systems

CRF – Common Reporting Format

CSB – Central Statistical Bureau

EMEP/CORINAIR 2007 – Atmospheric emission inventory guidebook, Co-operative

Programme for Monitoring and Evaluation of the Long Range Transmission of Air Pollutants in Europe, The Core inventory of air emissions in Europe

EMEP/EEA 2013 - EMEP/EEA air pollutant emission inventory guidebook 2013 ETR – Emission trading registry

GHG – Greenhouse Gases

GDP – Gross domestic product

IPCC – Intergovernmental Panel on Climate Change

IPCC 1996 – Revised 1996 IPCC Guidelines for National Greenhouse gas Inventories (1997)

IPCC GPG 2000 - IPCC Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories (2000)

IPCC GPG LULUCF 2003 – IPCC Good Practice Guidance for land Use, Land – Use Change and Forestry (2003)

IPCC 2006 GUIDELINES – 2006 IPCC Guidelines for National Greenhouse Gas

Inventories

IPCC WETLANDS SUPPLEMENT - 2013 Supplement to the 2006 IPCC Guidelines for

National Greenhouse Gas Inventories: Wetlands

IPCC KP SUPPLEMENT - 2013 Revised Supplementary Methods and Good Practice Guidance Arising from the Kyoto Protocol

IPE – Institute of Physical Energetics

LEGMC – Latvian Environment, Geology and Meteorology Centre

LSIAE – Latvian State Institute of Agrarian Economics

LULUCF – Land Use, Land Use Change and Forestry

MoA - Ministry of Agriculture

MEPRD - Ministry of Environmental Protection and Regional Development

MoT - Ministry of Transport

NCV – Net calorific value

NIR – National inventory report


30

OECD - Organisation for Economic Co-operation and Development

REB – Regional Environment Boards

RTSD – Road Traffic Safety Department

SAM – State Agency of Medicines

SFRS – State Firefighting & Rescue Service

SFS – State Forest Service

UN – United Nations

UNFCCC – United Nations Framework Convention on Climate Change

ERT – Expert review team

EU – European Union

EU ETS – European Union Emission Trading Scheme

IPPC - Integrated Pollution Prevention Control

FMRL – Forest Management Reference Level


31

EXECUTIVE SUMMARY

ES.1 BACKGROUND INFORMATION ON GHG INVENTORIES AND CLIMATE CHANGE

ES.1.1 Background information on climate change

Latvia takes part in the global climate change mitigation process and together with many

other countries of the world signed the United Nations (UN) Framework Convention on Climate Change (UNFCCC) in Rio de Janeiro the UN Conference on Environment and

Development held in 1992. It entered into force on 21 March 1994. The Parliament of the Republic of Latvia (Saeima) ratified the UNFCCC on 23 February 1995. On May 30, 2002 the Parliament ratified the Kyoto Protocol. In accordance with the Kyoto Protocol Latvia,

individually or in a joint action with other country, should reach the level when aggregate anthropogenic CO2, CH4, N2O, HFC, PFC and SF6 emissions by the years 2008-2012 are 8%

below emission level in 1990.

The Latvia`s National Inventory Submission2 published in 2014 covers period from 1990-2012 and also shows that Latvia has reached the target of 8% emission reduction over the

period from 2008-2012 for the first commitment period under the Kyoto Protocol.

For the second commitment period of Kyoto Protocol until 2020 Latvia together with other

EU member states and Iceland has committed to achieve the joint target of emission reduction by 20% comparing to year 1990 under the 2009 climate and energy package3. The efforts of the reduction (reduction targets) are shared out as follows:

21% reduction compared to 2005 level for the emissions from sectors covered by the European Union Emission Trading Scheme (EU ETS); this goal is EU-wide and

defines that all EU ETS operators jointly reduce the total GHG emissions;

around 10% reduction compared to 2005 for other emitters (sectors and activit ies not

included in the EU ETS which are regulated by Effort Sharing Decision4 (EU ESD)). Member States have taken on binding annual targets for reducing their GHG

emissions from the sectors not covered by the EU ETS, such as housing, agriculture, waste and transport (excluding aviation). The national targets, covering the period 2013-2020, are differentiated according to Member States relative wealth. In

accordance with EU ESD Latvia’s national target is to limit emission growth to +17% above the 2005 level by 2020.

This latest submission includes data and information on the first year of the second commitment period of the Kyoto Protocol starting in 2013.

ES.1.2 Background information on greenhouse gas inventories

As a party to the UNFCCC and the Kyoto Protocol Latvia is required to produce and regularly

update national inventories of anthropogenic emissions by sources and removals by sinks of all greenhouse gases not controlled by Montreal Protocol from following sectors: Energy, Industrial Processes and Product Use, Agriculture, Land Use, Land Use Change and Forestry

and Waste.

2 http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/8108.php

3 http://ec.europa.eu/clima/policies/package/index_en.htm

4 http://ec.europa.eu/clima/policies/effort/index_en.htm

http://ec.europa.eu/clima/policies/package/index_en.htm


32

Latvia is a member of European Union since May, 2004 and Latvia’s climate change policy is

based on European Union climate policy therefore according to the Regulation (EU) No 525/2013 of the European Parliament and of the Council on a mechanism for monitoring and reporting GHG emissions and for reporting other information at national and Union level

relevant to climate change and repealing Decision No 280/2004/EC require to annually report information regarding their anthropogenic GHG emissions. Single national entity with overall

responsibility for the Latvia’s GHG inventory is the Ministry of Environmental Protection and Regional Development (MEPRD). The preparation of GHG inventory is collaborative work of different involved institutions.

This report contains the most updated information on anthropogenic emissions by sources and removals by sinks for the direct CO2, CH4, N2O, HFCs, PFCs, NF3, SF6 and indirect CO,

NOx, SO2, NMVOC greenhouse gases. Greenhouse gas inventory covers the years 1990-2013.

The GHG inventory is prepared according to the UNFCCC Decision 24/CP.195 Annex 1

reporting guidelines ―Guidelines for the preparation of national communications by Parties included in Annex I of the Convention, Part I: UNFCCC reporting guidelines on annual

greenhouse gas inventories on annual inventories‖ (UNFCCC Annex I inventory reporting guidelines) and tables of the common reporting format to implement the use of the 2006 IPCC Guidelines for National Greenhouse Gas inventories (2006 IPCC Guidelines). For the

preparation of the 2015 inventory submission CRF Reporter v 5.10.1 software has been used. Greenhouse gas inventory is compiled according to the methodologies recommended by the

IPCC.

ES.2 SUMMARY OF NATIONAL EMISSION AND REMOVAL-RELATED TRENDS

ES.2.1 GHG inventory

In 2013, Latvia's greenhouse gas emissions totalled 11025, 43 Gg CO2 eq. including indirect

CO2, excluding LULUCF. Latvia’s total GHG emissions without LULUCF in 2013 showed a decrease of 58.12% comparing to the base year. If compared to 2012 total GHG emissions

have decreased by 0.5% (Figure ES.1).

Figure ES .1 GHG emission time series for 1990–2013

5 http://unfccc.int/resource/docs/2013/cop19/eng/10a03.pdf#page=2


Table ES .1 a Aggregated GHG emissions by gases (1990 - 2001), Gg CO2 eq

GREENHOUSE GAS

EMISSIONS

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

CO2 eq (Gg)

CO2 emissions including net CO2

from LULUCF

19 539.34 17 787.49 14 097.51 11 805.81 10 307.09 9 059.01 9 133.74 8 604.93 8 227.86 7 643.66 7 012.42 7 428.51

CO2 emissions excluding net CO2 from LULUCF

9 756.92 7 753.70 2 633.77 1 203.70 -1 138.72 -1 369.62 -1 950.79 -822.74 -326.90 2 368.97 -1 092.84 -1 436.80

CH4 emissions including CH4 from LULUCF

3 995.93 3 939.44 3 371.15 2 555.02 2 360.44 2 337.68 2 272.27 2 227.07 2 129.99 1 985.65 1 995.39 2 086.22

CH4 emissions excluding CH4 from LULUCF

4 299.65 4 238.30 3 751.55 2 860.00 2 664.16 2 652.30 2 590.14 2 549.81 2 455.04 2 343.19 2 339.18 2 391.81

N2O emissions including N2O from LULUCF

2 649.10 2 487.69 1 991.80 1 512.56 1 353.18 1 219.75 1 225.95 1 229.66 1 187.54 1 116.67 1 133.07 1 230.08

N2O emissions excluding N2O

from LULUCF

3 228.30 3 071.88 2 590.46 2 107.94 1 953.71 1 827.86 1 838.79 1 846.86 1 808.83 1 745.63 1 763.86 1 861.50

HFCs NO,NA,NE NO,NA,NE NO,NA,NE NO,NA,NE NO,NA,NE 0.67 0.84 2.03 3.09 3.49 5.47 8.13

PFCs NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA

Unspecified mix of HFCs and

PFCs

NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA

SF6 NO,NA,NE NO,NA,NE NO,NA,NE NO,NA,NE NO,NA,NE 0.17 0.18 0.37 0.52 0.71 0.88 1.39

NF3 NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA

Total (without LULUCF) 26 184.37 24 214.61 19 460.45 15 873.39 14 020.70 12 617.28 12 632.97 12 064.06 11 549.00 10 750.18 10 147.24 10 754.33

Total (with LULUCF) 17 284.87 15 063.89 8 975.77 6 171.63 3 479.14 3 111.38 2 479.16 3 576.33 3 940.57 6 461.99 3 016.55 2 826.03

Total (without LULUCF, with indirect)

26 326.48 24 356.19 19 601.22 16 011.12 14 156.04 12 750.47 12 764.51 12 194.29 11 677.95 10 877.97 10 273.87 10 879.69

Total (with LULUCF, with

indirect)

17 426.98 15 205.47 9 116.54 6 309.35 3 614.48 3 244.57 2 610.70 3 706.57 4 069.53 6 589.78 3 143.18 2 951.39


34

Table ES .1 b Aggregated GHG emissions by gases (2002 - 2013), Gg CO2 eq

GREENHOUSE GAS EMISSIONS

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Change

from 1990

to latest

reported year (%)

CO2 eq (Gg)

CO2 emissions including net CO2 from LULUCF

7 454.85 7 639.71 7 647.62 7 733.03 8 234.41 8 557.09 8 127.83 7 392.13 8 478.49 7 734.62 7 414.61 7 276.02 -62.76

CO2 emissions excluding net CO2

from LULUCF 38.36 726.44 2 244.71 2 708.24 2 164.40 3 197.95 2 386.62 5 244.62 8 376.65 7 244.62 5 973.77 6 080.75 -37.68

CH4 emissions including CH4 from LULUCF

2 069.05 1 988.73 1 955.41 1 998.30 1 972.69 2 032.34 2 026.35 1 979.40 1 958.76 1 923.95 1 994.42 2 036.42 -49.04

CH4 emissions excluding CH4 from LULUCF

2 403.03 2 301.91 2 262.47 2 279.00 2 295.10 2 311.69 2 304.35 2 277.06 2 263.10 2 240.68 2 326.28 2 385.07 -44.53

N2O emissions including N2O from LULUCF

1 192.28 1 246.07 1 226.59 1 280.18 1 289.92 1 334.67 1 323.88 1 341.02 1 372.67 1 382.42 1 458.88 1 484.32 -43.97

N2O emissions excluding N2O from LULUCF

1 832.37 1 888.84 1 871.33 1 926.05 1 947.44 1 990.01 1 983.62 2 013.13 2 051.69 2 067.63 2 151.02 2 183.16 -32.37

HFCs 10.60 13.38 18.03 24.51 42.22 63.20 79.57 83.14 79.68 82.11 90.96 108.46


Unspecified mix of HFCs and


SF6 2.62 2.76 3.25 3.78 4.07 4.55 5.23 7.33 7.35 7.47 7.78 8.50

NF3 NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA NO,NA

Total (without LULUCF) 10 729.39 10 890.64 10 850.90 11 039.79 11 543.31 11 991.85 11 562.85 10 803.02 11 896.94 11 130.56 10 966.65 10 913.73 -58.32

Total (with LULUCF) 4 286.98 4 933.33 6 399.79 6 941.58 6 453.24 7 567.40 6 759.39 9 625.27 12 778.46 11 642.50 10 549.81 10 765.95 -37.71

Total (without LULUCF, with indirect)

10 853.03 11 013.12 10 972.17 11 160.46 11 664.32 12 105.69 11 680.38 10 913.13 12 011.12 11 244.09 11 078.53 11 025.43 -58.12

Total (with LULUCF, with indirect)

4 410.62 5 055.81 6 521.06 7 062.25 6 574.24 7 681.24 6 876.91 9 735.39 12 892.64 11 756.03 10 661.69 10 877.65 -37.58


35

Table ES .2 a Aggregated GHG emissions by sectors (1990 - 2000), Gg CO2 eq

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

1. Energy 19 258.46 17 744.53 14 461.67 12 355.03 10 797.79 9 546.94 9 614.55 9 050.72 8 637.88 8 001.91 7 383.68

2. Industrial processes and

Product Use 602.66 527.15 250.50 92.10 139.09 151.77 163.59 170.11 172.92 205.67 158.61

4. Agriculture 5 558.66 5 144.47 3 988.23 2 741.95 2 415.07 2 255.51 2 199.19 2 166.92 2 052.36 1 860.43 1 859.64

5. Land use, land use change

and forestry -8 899.50 -9 150.72 -10 484.68 -9 701.77 -10 541.56 -9 505.90 -10 153.82 -8 487.72 -7 608.42 -4 288.19 -7 130.69

6. Waste 764.59 798.46 760.05 684.32 668.75 663.06 655.64 676.30 685.83 682.18 745.31

7. Other NO NO NO NO NO NO NO NO NO NO NO

Total emissions (including

LULUCF) 17 284.87 15 063.89 8 975.77 6 171.63 3 479.14 3 111.38 2 479.16 3 576.33 3 940.57 6 461.99 3 016.55

Table ES .2 b Aggregated GHG emissions by sectors (2001 - 2013), Gg CO2 eq

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Change from

1990 to latest

reported year (%)

1. Energy 7 817.48 7 820.23 7 973.21 8 005.95 8 111.14 8 532.88 8 852.18 8 405.16 7 699.60 8 452.79 7 589.42 7 290.72 7 185.09 -62.69

2. Industrial processes and Product

Use 181.79 195.76 211.11 229.35 229.46 277.19 301.50 309.45 304.85 566.74 658.90 688.14 668.97 11.00

4. Agriculture 1 979.87 1 965.20 2 017.84 1 940.71 2 015.26 2 023.13 2 105.92 2 076.27 2 092.61 2 140.57 2 154.55 2 250.52 2 310.12 -58.44

5. Land use, land use change and

forestry -7 928.30 -6 442.41 -5 957.31 -4 451.11 -4 098.21 -5 090.07 -4 424.45 -4 803.46 -1 177.74 881.52 511.94 -416.84 -147.78 -98.34

6. Waste 775.20 748.21 688.47 674.89 683.93 710.12 732.25 771.97 705.96 736.84 727.69 737.27 749.54 -1.97

7. Other NO NO NO NO NO NO NO NO NO NO NO NO NO

Total emissions (including LULUCF) 2 826.03 4 286.98 4 933.33 6 399.79 6 941.58 6 453.24 7 567.40 6 759.39 9 625.27 12 778.46 11 642.50 10 549.81 10 765.95 -37.71


ES.3 OVERVIEW OF SOURCE AND SINK CATEGORY EMISSION ESTIMATES

AND TRENDS

ES.3.1 GHG inventory

The main sources of greenhouse gas emissions have been officially divided into the following sectors: Energy (CRF 1), Industrial processes and Product Use (CRF 2), Agriculture (CRF 3),

Land use, Land use change and Forestry (LULUCF CRF 4) and Waste (CRF 5). GHG emissions by sectors are shown in the Figure ES.2.

Figure ES .2 Latvia`s GHG emissions and removals by sectors 1990-2013 (Gg CO2 equivalent)

Figure ES .3 The composition of Latvian greenhouse gas emissions by sector in 2013 including indirect

CO2, excluding LULUCF

The Energy sector is the most significant source of GHG emissions with 65.2% share of the total emissions in the 2013. GHG emissions fluctuate in the latest years mainly due to the


37

economic trend, the energy supply structure and climate conditions. Total emissions in

Energy sector in 2013 decreased by 62.7% if compared to the base year. A large part of energy sector emissions comes from transport sector (39.3%). Transport emissions increased by 1.2% compared to year 2012. One of the critical factors influencing GHG emissions in

transport sector is the amount of consumed fuel.

Agriculture is the second most significant source of GHG emissions, with approximately

21.0% of Latvia’s total emissions. Emissions from agriculture include CH4, N2O emissions and CO2 emissions from liming and urea application. GHG emissions increased in 2013 by 2.6% compared to 2012 due to increase in livestock numbers (excepting goats and horses),

synthetic N fertilizer consumption, crop production and lime application to soils. The annual emissions have reduced approximately by 58.4% since 1990 due to decrease in agricultural

production. In 2013, given in CO2 equivalents, the N2O contributed 58.5%, CH4 contributed 40.7% of total GHG emission from the agricultural sector, remaining 0.8% refer to CO 2 emissions from liming and urea application.

Emissions from the Waste sector consist of CH4 and N2O emissions and have been increasing since 1990. In 2013, emissions were approximately 2.0% lower than in 1990, but

compared to 2012 emissions increased by 1.6%. Trend could be explained with changes in economic situation in Latvia. In 2013, emissions from the Waste sector were 749.54 Gg CO2 equivalents; it contributes 6.8% of total GHG emissions (excluding LULUCF).

The Industrial Processes and Product Use category contributes approximately 6.1% of the total GHG emissions. The emissions from industrial processes and product use (referred to as

non-energy related ones), include CO2, CH4, N2O and F-gases. The largest decrease in emissions occurred between years 1991 and 1993, when industry was going through a crisis. Emission fluctuations in product uses sectors are linked with the economic situation of the

country.

In the latest years emissions increased significantly due to overall increase in industrial

production processes. In 2013, emissions decreased by 2.8 %, compared to 2012 due to decrease activity data in sectors 2.A.1 Cement production (decrease of activity data 6.57%), 2.A.2 Lime production (69.7% decrease of activity data), 2.C.1 Iron and Steel Production

(decrease of activity data 76.9 % due to lower output from metal production plant (operating limited time per year), 2.D.3 Non-energy and product use (decrease of activity data 20.8%).

2.F. Product Uses as Substitutes for Ozone Depleting Substances (ODS) shows about 17,1% increase of actual emissions compared to 2012 due to increase of purchased F-gases amount in Commercial refrigeration and increasing number of passenger cars and trucks which caused

growth of emissions from Mobile Air-Conditioning.

Land use, Land use change and forestry (LULUCF) is a net sink in Latvia. In 2013, CO2

removals were -147.8 Gg CO2 eq compared to -8899.5 Gg CO2 eq in the base year that is approximately 98% less than in 1990, because of increase of harvesting rate and natural mortality in ageing forest. Most of the removals in the LULUCF sector come from forest

growth.

ES.4 OVERVIEW OF EMISSION ESTIMATES AND TRENDS OF INDIRECT GHG

Emissions from indirect GHGs are presented in Table ES.4.

Table ES .4. Indirect GHG emissions 1990-2013 (Gg)

NOx CO NMVOC SO2

1990 89.75 387.31 144.03 99.50

1991 82.71 354.09 139.99 80.51

1992 68.58 369.19 131.31 68.66


38

NOx CO NMVOC SO2

1993 60.82 337.08 123.47 64.46

1994 55.15 320.97 118.66 65.50

1995 50.61 296.57 115.75 47.82

1996 50.25 301.76 114.92 53.99

1997 48.41 274.49 110.56 42.10

1998 44.82 257.53 107.08 37.77

1999 43.76 257.83 104.26 29.52

2000 42.86 242.87 102.37 15.04

2001 45.50 241.65 105.09 11.56

2002 44.42 242.03 102.97 9.96

2003 45.93 233.06 101.87 8.21

2004 45.10 224.87 101.10 6.20

2005 43.59 204.59 100.03 6.30

2006 44.08 217.94 98.83 5.53

2007 44.35 188.06 94.54 5.24

2008 39.65 175.89 93.15 4.12

2009 36.19 191.93 92.13 3.76

2010 37.85 155.30 89.18 2.55

2011 32.88 158.35 88.24 2.27

2012 33.65 165.22 89.37 1.95

2013 33.59 149.19 87.70 1.46

In the period from 1990 to 2013 indirect GHG emissions have decreased: NOx by 62.6%, CO by 61.5% and NMVOC by 39.1%. Starting from 2001, slight fluctuations in NOx, NMVOC and CO emissions can be observed as a reason of increasing firewood consumption in

Residential sector as well as fuel consumption in Transport sector in particular years. SO2 emissions have decreased significantly from 1990 to 2013 by 98.5% as a reason of fuel switch

and approved legislation.

Figure ES .4 Indirect GHG emission by sector in 2013 (% of total indirect GHG emissions in sector)

In 2013, the most important sector producing indirect GHGs (including fugitive emissions) was Energy sector (including fugitive emissions). Fuel combustion in Energy sector causes

the largest part NOx emissions of (89.8% from total NOx emissions in 2013), but IPPU and Agriculture sectors make 4.5% and 5.4%, accordingly. Very small part of NOx emissions is produced in LULUCF sector – 0.3% from total NOx emissions). Almost all CO emissions

(94.4%) appear in Energy sector, mainly from fuel combustion in Residential and


39

Commercial/Institutional subsectors (74.5% from all emissions). A small part of CO

emissions come from LULUCF sector (3.8%) and IPPU sector (1.7%). The major part of SO 2

emissions (87.9%) comes from Energy sector (fuel combustion), but the other sulphur dioxide

emissions come from Industrial processes (Cement production and Iron and Steel production),

and a negligible part of SO2 comes also from Waste sector (Waste incineration). The largest amounts of NMVOC emissions are produced in IPPU sector (59.9%), mainly from solvent

use, and 31.3% from total NMVOC emissions in 2013 are produced in Energy sector (fuel combustion mainly in Residential sector). 8.4% of NMVOC emissions are produced in Agriculture sector, but the remaining 0.4% in Waste sector.

In Agriculture sector, CO and SO2 emissions, and in LULUCF sector, NMVOC and SO2 emissions do not appear.


40

PART 1: ANNUAL INVENTORY SUBMISSION

1. INTRODUCTION

1.1 BACKGROUND INFORMATION ON GREENHOUSE GAS INVENTORIES AND CLIMATE CHANGE

1.1.1 Background information on climate change

Latvia is a country by the Baltic Sea with total area of 64 573 km2 and there are 2 023 825

(2013) inhabitants6. Baltic coastline is approximately 498 km. Since the beginning of the previous century the forest area in Latvia has almost doubled reaching 3,260,000 ha7 (51%

from the total area of the country in 2014). Latvia lies in a temperate climate zone where active cyclone determines rapid changes in weather conditions (190-200 days per year). Annual mean precipitation is 600-700 mm. Main rocks in Latvia are clay, dolomite, sand,

gravel, limestone and gypsum.

The analysis of long-term climatological data series in Latvia has shown that the climate has

changed during last centuries. Air temperature has increased for the whole period of observations (from the 1795); however it has been more expressed during winter and spring and for the last decades. Increasing trends are evident in precipitation series for the cold

period, while the decreasing trends were found for summer and autumn seasons. Ice and snow cover period in Latvia became shorter during last decades. River discharge regime has been

subjected to major changes in relation to climate changes. Well expressed regular changes of high-water and low-water periods are evident. Seasonality indices have changed: increased values of growing degree days especially from the beginning of the 20 th century, decreased

number of frost days, reduced heating degree-days.

The climate change and climate variability have and will have a notable impact on inland and

sea hydro ecosystems as well as changes in vegetation. The increasing growth of aquatic vegetation in recent years has been related to climatic factors – higher mean temperature and earlier spring. The absence and lowering of the ice cover during winter’s causes the prolonged

growing season. There is a significant temporal gradient in vegetation dynamic from light nutrient-poor and species-poor forests to more nutrient-rich, more diverse species and closed

forests. This is evident that the future climate changes will have significant effect on natural and socio-economic systems in Latvia8.

1.1.2 Background information on greenhouse gas inventories

The Parliament of the Republic of Latvia ratified the United Nations Framework Convention

on February 23, 1995 and since March 23, 1995 Latvia is a Party to the Convention thus undertaking to implement series of international commitments. On May 30, 2002 the

Parliament also ratified the Kyoto Protocol. For the first commitment period of Kyoto protocol (2008-2012) Latvia had a commitment individually or in a joint action with other country to reach the level when aggregate anthropogenic CO2, CH4, N2O, HFC, PFC and SF6

are 8% below emission level in 1990. Previous GHG inventory shows that Latvia’s GHG emissions in 2012 are 58% below 1990 level. On 29 October 2002, The Cabinet of Ministers

of the Republic of Latvia approved the Strategy of Joint Implementation for 2002-2012 as

6 http://data.csb.gov.lv/pxweb/lv/Sociala/Sociala__ikgad__iedz__iedzskaits/IS0020.px/table/tableViewLayout1/?rxid=cdcb978c-22b0-416a-

aacc-aa650d3e2ce0 7 http://data.csb.gov.lv/pxweb/lv/lauks/lauks__ikgad__mezsaimn/MS010.px/table/tableViewLayout1/?rxid=cdcb978c-22b0-416a-aacc-

aa650d3e2ce0 8 Kļaviņš, M. Climate change in Latvia. University of Latvia.


41

defined in the Kyoto Protocol to the UN Framework Convention on Climate Change and

passed Regulations of the Cabinet of Ministers No. 653 ―On the Strategy of Joint Implementation (2002-2012) as defined in the Kyoto Protocol to the UN Framework Convention on Climate Change‖.

Latvia is a member of EU since May 2004 and Latvia’s climate change policy is based on Europe Union climate policy. The legislation act – Regulation No. 217 of Cabinet of

Ministers (27.03.2012.) determinates the institutions that are responsible for GHG inventory preparation.

Ministry of Environmental Protection and Regional Development (MEPRD), Climate Change

Department is responsible for the implementation and development of climate change mitigation and adaptation (and related) policies and measures. MEPRD is responsible for the

actions (coordination, implementation and development) to meet the international and EU emission reduction targets. MEPRD also coordinates the monitoring and reporting of GHG emission data.

As a party of the UNFCCC, Kyoto Protocol and European Union Latvia is required to produce and regularly update report on GHG emissions and removals. This report is the

annual submission of the Latvia to the UNFCCC and European Comission. It presents the GHG inventory, the process and the methods used for the compilation o f the inventory for 1990 to 2013. The structure of this NIR follows the ―Outline and general structure of the

national inventory report‖ (as included in appendix to the annex to decision 24/CP.19) prepared by UNFCCC.

1.2 DESCRIPTION OF THE INSTITUTIONAL NATIONAL INVENTORY ARRANGEMENTS

1.2.1 Overview of institutional, legal and procedural arrangements for compiling

GHG inventory

Latvian national GHG inventory system is designed and operated according to the guidelines

for national system under article 5, paragraph 1, of the Kyoto Protocol (Decision 20/CP.7) to ensure the transparency, consistency, comparability, completeness and accuracy of inventory.

Inventory activities include planning, preparation and management.

The inventory phases are:

collecting activity data;

selecting methods and emission factors appropriately;

estimating anthropogenic GHG emissions by sources and removals by sinks;

implementing uncertainty assessment;

implementing QA/QC activities.

A schematic model for the national system (NIS) is shown in Figure 1.1.

MEPRD Climate Change Department is responsible for the implementation and development

of climate change mitigation and adaptation (and related) policies and measures. MEPRD is responsible for the actions (coordination, implementation and development) to meet the

international and EU emission reduction targets. MEPRD also coordinates the monitoring and reporting of GHG emission data. MEPRD is single national entity with overall responsibility for the Latvian GHG inventory.


Figure 1.1 The structure of Latvia`s National Inventory System


The MEPRD Climate Change Department is responsible for:

Preparation of legal basis for maintaining the National System;

Informing the inventory compilers about requirements of the national system;

Overall coordination of GHG inventory process;

Final checking and approving of the GHG inventory before official submission to the

EC and UNFCCC;

Timely submission of GHG inventory to the UNFCCC and European Commission;

Formal agreements with inventory experts and for third part experts that evaluate quality assurance process;

Coordinating the work between the involved institutions, experts, European Commission and UNFCCC (including coordination of the UNFCCC inventory

reviews);

Keeping of archive of official submissions to UNFCCC and European Commission.

Latvian Environment, Geology and Meteorology Centre (LEGMC) is a governmental limited liability company and is responsible for:

collecting of activity data for Energy, Industrial Processes and Product Use and Waste

sectors (activity data are mainly collected from other institutions and LEGMC (Air and Climate division, Chemicals and Hazardous Waste division, Inland Waters

division) use them to calculate emissions);

preparation of the emission estimates for the Energy, Industrial Processes and Product

Use and Waste sectors;

preparation of QC procedures for relevant categories and documentation and archiving

of used materials for emission calculation;

LEGMC Air and Climate Division compile the final NIR using information from all

involved institutions as well as summarized emission data in CRF Reporter;

quality manager from LEGMC Air and Climate division perform the overall QC/QA

procedures for all sectors according to the QA/QC plan.

Calculations of removals and emissions for the LULUCF, KP-LULUCF sector were done by Latvian State Forest Research Institute "Silava" in collaboration with MoA. "Silava" is

responsible for collecting of activity data, preparation of the removals/emission estimates, preparation of QC procedures as well as documentation and archiving of used materials for

calculation.

Institute of Physical Energetic (IPE) calculates emissions for Transport sector. IPE is responsible for collecting of activity data, preparation of the emission estimates, preparation

of QC procedures as well as documentation and archiving of used materials for calculation.

Emissions from Agriculture sector were done by Latvia University of Agriculture in

collaboration with MoA. Latvia University of Agriculture is responsible for collecting of necessary activity data cooperating with Central Statistical Bureau (CSB), preparation of the emission estimates, preparation of QC procedures as well as documentation and archiving of

used materials for calculation.

The main data supplier for the Latvian GHG inventory is the CSB. Mainly MEPRD, LEGMC,

IPE, Latvia University of Agriculture contacted with CSB experts.


44

Institutions involved in the preparation of the national inventory report, are determined in the

CoM Regulations No. 217 (27.03.2012). For ensuring the continuity of the functions of the national system, the delegation contract is signed between the MEPRD and LEGMC. The delegation contract ensure the accomplishing of emission estimations and information

preparation in the Energy, Industrial Processes and Product use and Waste sectors for the inventory, as well as GHG inventory compilation and activities related to EU ETS.

Additionally there are agreements with ―Silava‖, IPE and Latvia University of Agriculture for emission estimations and information preparation accordingly for LULUCF, Transport and Agriculture sectors.

Before final GHG inventory are submitted to European Commission and UNFCCC secretariat it is forwarded to the involved ministries for review and approving. Based on received

comments inventory are corrected appropriate.

Several meetings (related Energy, LULUCF, Agriculture, Industrial Processes and Product Use, Waste) were held before and during preparation of inventory to discuss and agree on the

methodological issues, problems that have arisen and improvements that need to be implemented. There was discussion on the different problems that came up during the last

inventory preparation to find solutions how to improve the overall system.

The following issues for solving different problems and to improve cooperation between inventory experts and inventory compilers are:

Discussion on methodologies and possible changes in the future (implementation of the new 2006 IPCC Guidelines9);

Discussion on use of the CRF Reporter software versions (current version 5.10.1);

Discussion on QA/QC plan, available resources and possible improvements;

Discussion on data collection;

Agreement on recalculations;

Archiving system, updating and possible improvements;

Exchange of relevant information;

Reporting the conclusions from the meetings.

The detailed responsibilities of the institutions involved in preparing activity data and calculating emissions are summarized in the Table 1.1.

1.2.2 Overview of inventory planning, preparation and management

Inventory planning is one of the main stages in national GHG inventory management system

and all responsible institutions are involved in this process, which consists of:

establishing of national entity with overall responsibility for the national inventory;

assigning responsibilities for inventory preparation and management;

developing time schedule;

making arrangements to collect data from statistical agencies, companies, industry associations, etc.;

creating QA/QC plan;

9 http://www.ipcc-nggip.iges.or.jp/public/2006gl/


45

defining formal approval process within government;

developing review processes;

integrating continuous improvements.

Latvia’s national GHG inventory system is designed and operated according to the guidelines for national system under article 5, paragraph 1, of the Kyoto Protocol (Decision 20/CP.7) to

ensure the transparency, consistency, comparability, completeness and accuracy of inventories.

The inventory preparation plan is a part of the Latvia’s QA/QC plan and has to be followed by

all institutions defined in CoM Regulation No. 217 (27.03.2012)10. The inventory preparation plan is presented in Table 1.2 and responsible institutions are reflected in Table 1.1.

After the end of the annual reporting cycle in April, the institutions involved in inventory preparation start to plan for producing of the next annual inventory following received improvements and recommendations by ERT. Planning includes the identification of

improvements to be undertaken due to revised methodologies, updated activity data or emission factors and other relevant technical elements of inventory as well as addressing the

issues and recommendations in the review of the previous inventory submission.

Table 1.1 Institutions responsible for activity data and calculating emissions

CRF sectors Data Responsible institutions

Table 1.A(a) - Fuel Combustion Activities (Sectoral Approach)

Activity data CSB Environment and Energy Statistics Section, Road Traffic Safety Department

(RTSD)

Calculations LEGMC Air and Climate division, Institute of Physical Energetics (IPE)

Table 1.A(b) – CO2 from Fuel

Combustion Activities – Reference Approach

Activity data CSB Environment and Energy Statistics Section

Calculations LEGMC Air and Climate division

Table 1.A(d) – Feedstock’s and Non-

Energy Use of Fuels



Table 1.B.2. – Fugitive Emissions from

Oil and Natural Gas


Calculations LEGMC Air and Climate Division, JSC

―Latvijas Gāze‖

Table 1.D – International Bunkers and

Multilateral Operations



Table 2(I).A-E,G-H – Industrial Processes and Product Use

Activity data CSB Population Statistics Section

State Agency of Medicines;

Research of experts;

LEGMC ―2-AIR‖ and ―Chemical‖ databases

CSB Industrial Statistics Section

EU Emission Trading Scheme operators

Calculations LEGMC Chemicals and Hazardous Waste

Division, LEGMC Air and Climate division, EU

Emission Trading Scheme operators

Table 2(II) F – Industrial Processes -

HFCs, PFCs and SF6

Activity data CSB Population Statistics Section, Environment

and Energy Statistics Section

10

http://likumi.lv/doc.php?id=246033.


46


―Latvenergo‖ AS;


Annual reports by operators using F-gases

(reported to LEGMC)

Data from Chemicals Register (maintained by LEGMC)


Table 3.A – Agriculture, Enteric

Fermentation

Activity data CSB Agricultural Statistics Section

Calculations Latvia University of Agriculture

Table 3.B.1 - Agriculture, CH4

Emissions from Manure Management



Table 3.B.2 - Agriculture, N2O un

NMVOC Emissions from Manure

Management



Table 3.D - Agriculture, Agricultural

Soils

Activity data LEGMC database ―2-Water‖, Latvian State

Forest Research Institute "Silava"


Table 3 G Liming Activity data CSB


Table 3 H Urea application Activity data CSB


Table 4. A. Forest Land

Table 4. B. Cropland

Table 4. C. Grassland

Table 4. D. Wetlands

Table 4. E. Settlements

Table 4. F. Other Land

Activity data National Forest monitoring program (NFI)

Calculations Latvian State Forest Research Institute "Silava"

collaborated with Ministry of Agriculture

Table 4. B. Cropland – 4.B.1 Cropland

remaining Cropland

Activity data –

Area of organic soil

NFI, National studies and expert judgement

Calculations – Net carbon stock change in organic soils

Latvian State Forest Research Institute "Silava"

Table 4. C. Grassland – 4.C.1

Grassland remaining Grassland

Activity data - Area of organic

soil

National studies and expert judgment

Calculations – Net carbon

stock change in organic soils

National studies and expert judgment, Latvian

State Forest Research Institute "Silava"

Table 4. (V) Biomass Burning Activity data State Fire and Rescue Service of Latvia, State

forest service of Latvia


KP LULUCF Activity data State Fire and Rescue Service of Latvia, State

forest service of Latvia

National Forest monitoring program (NFI) National studies and expert judgement


Table 5 A - Waste, Solid Waste

Disposal on Land

Activity data LEGMC ―3-Waste‖ database, Methane recovery

installations

Calculations LEGMC Chemicals and Hazardous Waste Division


47


Table 5 B – Biological Treatment and

Solid Waste

Activity data CSB, LEGMC Chemicals and Hazardous Waste

Division

Calculations CSB, LEGMC Chemicals and Hazardous Waste Division

Table 5.B.1 – Composting Activity data LEGMC Chemicals and Hazardous Waste

Division


Division

Table 5 C – Incineration and open

Burning of Waste

Activity data LEGMC database ―3-Waste‖


Division

5.D Wastewater Treatment and

Discharge

Activity Data LEGMC ―2-Water‖ database, CSB statistics on

national population and production rates of

certain industries

Calculations LEGMC Inland Waters Division

Inventory management system includes 3 main stages – inventory planning, preparation and management.

The inventory preparation stage consists of:

Identification of key categories, which have a significant influence on a country’s total

inventory in terms of level or trend in emissions. In general, countries should focus on key categories for resources and improvements;

Selection of methods, emission factors and all necessary relevant information for

estimating anthropogenic GHG emissions by sources and removals by sinks;

Collection of activity data;

Managing recalculations from previous submissions taking into account updates of activity data by CSB, recommendations by ERT, suggestions from the third-part experts etc.

NIR compilation;

QA/QC plan implementation (include basic checks on entire inventory (Tier 1) and

more in-depth investigations into key sources (Tier 2);

Documentation.

The inventory management stage consists of:

Implementation of inventory review processes (e.g., expert review, public review);

Obtaining formal approval of final results and reporting within government;

Submission reporting to UNFCCC;

Making inventory information available to stakeholders and respond to information requests;

Archiving all documentation and results (The special centralised folder is created where experts can upload/download and store all files and information related to

inventory preparation);

Continuous improvement feedback.


48

Latvia prepares a NIR and Common Reporting Format (CRF) tables annually according to

requirements of the UNFCCC and the EU greenhouse gas monitoring mechanism. The 2015 submission contains estimates for the 1990- 2013. KP-LULUCF tables are not provided in this submission due to non-functioning CRF Reporter component related to KP-LULUCF

data tables.

The organizations of the preparation and reporting of Latvia’s greenhouse gas inventory and

the responsibilities of its different parts are detailed in Table 1.2.

All involved institutions to the GHG inventory system produce emission estimates according to Regulation of Cabinet of Ministers No.217 inter alias the UNFCCC reporting guidelines.

LEGMC is responsible for NIR compilation as well as emission data import in CRF reporter whereas MEPRD submits GHG inventory, including CRF tables to the UNFCCC Secretariat

and to the EC.


Table 1.2 Inventory preparation plan for 2015

Due to the problems with CRF Reporter functionality in 2015, timeline of this plan has been shift from annual inventory preparation plan timeline.

Element Activity Responsible performers Procedures Due date

To reconsider the changes

needed for the next year’s submission, taking into

account comments and recommendations made by the review team (ERT)

All institutions established by Regulation of Cabinet of

Ministers No.217 (Part II „National Inventory System‖, Paragraph 3)

All institutions involved in inventory preparation process to reconsider the changes

needed for the next year’s submission, taking into account comments and

recommendations made by the review team (ERT) and send to national inventory compiler for summarizing.

Middle of May

Additional meetings All institutions involved in GHG emissions and removals preparation

Additional meetings were organized for all sectors due to implementation of 2006 IPCC Guidelines, solving different problems regarding reviews, quality control activities etc.

January-February

Annual meeting

All institutions established by Regulation of Cabinet of

Ministers No.217 (Part II „National Inventory System‖, Paragraph 3)

All institutions involved in inventory preparation and approval process to participate in annual meeting where all issues related to 2015 submission were discussed.

30th September

Activity data and description Submission to LEGMC

EU Emission Trading Scheme (EU ETS) operators

EU ETS operators send to LEGMC activity data, CO2 emission factors, CO2 emissions

and descriptions as verified GHG report for enterprises involved in EU ETS annually for previous year.

LEGMC uses these data in GHG inventory for emission estimates in Energy and Industrial Processes sectors.

t ill 30th March

Operators

LEGMC (Air and Climate division, Chemicals and Hazardous Waste division, Inland

Waters Division) collects information for emission calculation for CRF2, CRF 3, CRF 6 in following databases:

―2-AIR‖ database;

―3-Waste‖;

―2-Water‖ databases;

Chemical Register.

Cement producer and Iron & Steel plant send additional information for detailed CO2 emission estimation according to national legislation.

t ill 15th June

t ill 1st October

Statistical bureau of Latvia (CSB)

CSB send to LEGMC activity data regarding Energy, Agriculture, and Industrial Processes sectors according to CoM Regulation No. 217.

Many of received and used activity data is available in CSB statistical databases: http://www.csb.gov.lv/dati/statistikas-datubazes-28270.html

till 1st October


50


State Firefighting & Rescue Service (SFRS)

SFRS send to LEGMC activity data - area of last years grass burning (ha). t ill 1st October

Ministry of Health

collaborating with State Agency of Medicines (SAM)

SAM sends to LEGMC activity data – data of imported metered dose inhalers containing

GHG (F gases subsector) and amount of used N2O for Anaesthesia (Solvent and other product use sector).

t ill 1st October

Emissions and descriptions Submission to MoA, MEPRD and LEGMC

Latvia University of

Agriculture collaborated with Ministry of Agriculture

Latvia University of Agriculture send to MEPRD and LEGMC report about emissions

from Agriculture, including information about used assumptions, activity data which was received from CSB.

till 1st March

Emissions and descriptions Submission to MEPRD and LEGMC

IPE according to agreement

with Ministry of Environmental Protection and Regional Development

IPE send to MEPRD and LEGMC report about emissions from Transport, including information about activity data, which was received from CSB.

till 1st March

JSC ―Latvijas Gāze‖ The only natural-gas transmission, storage, distribution, and sales operator in Latvia

sends the total fugitive emissions for previous year and short information of emission fluctuation according to national legislation.

till 1st October

CO2 removals and emissions, descriptions

Submission to MoA and MEPRD

Latvian State Forest Research

Institute (LSFRI) "Silava" collaborated with Ministry of Agriculture

LSFRI "Silava‖ send to MoA and MEPRD NIR relevant chapters, CRF about CO2

removals and emissions from LULUCF till 1

st March

CRF tables (XML) Compilation of the CRF

tables and QC by the LEGMC experts

LEGMC – Air and Climate

division, Chemicals and Hazardous Waste division, Inland Waters division.

LEGMC experts compile CRF tables, QC and send to MEPRD. till 1st October

CRF data

Draft NIR according to Regulation (EU) No 525/2013

CRF, NIR MEPRD - Climate Change Department

After corrections MEPRD send to EC CRF tables and draft short NIR through the Permanent Representation.

MEPRD uploaded CRF tables, XML and draft NIR in the EIONET CDR and electronically sent to EC notification about uploaded data.

30th June

Draft NIR MEPRD - Climate Change Department

According to the CoM Regulation No. 217, MEPRD send to involved institutions Draft NIR for comments and approving.

1st July

Draft NIR Involved institutions Involved institutions send to MEPRD comments about NIR 1st draft and approval. 1

st September

Quality control checks QC All institutions involved in inventory preparation process

Verification of national data in EC inventory and updates as necessary and response to

EC. Answers to the questions raised from EC, provide sectoral experts using EEA Review tool

1st September to 15

th October


51


(https://emrt.eea.europa.eu/2015) MEPRD approve provided answers from experts.

This process includes collaboration with involved institutions for preparing of response to EC.

Quality control checks QA Expert

Public

NIR was uploaded in the LEGMC home page for review. 1st July

Quality assurance QA Third part CRF and NIR for LULUCF were checked by third person not directly involved in the inventory preparation.

March/April

CRF data

NIR according to Regulation (EU) No 525/2013

CRF, NIR

MEPRD - Climate Change Department

MEPRD uploaded CRF tables, XML and draft NIR in the EIONET CDR.

30th October

NIR and emission data in CRF to UNFCCC

Inventory submission

MEPRD - Climate Change Department

MEPRD uploaded approved GHG inventory to UNFCCC portal. 15th November


1.2.3 Quality assurance, quality control and verification plan

The implementation of Quality Assurance and Quality Control (QA/QC) procedures in the

development of national GHG inventory is required by 2006 IPCC Guidelines.

According to CoM Regulation No. 217 (27.03.2012.) all institutions involved in inventory process are responsible for implementing QC procedures.

Mainly Tier 1 general inventory QC procedures outlined in Table 6.1 of 2006 IPCC Guidelines are used.

The legislation act determines:

the quality objectives for GHG inventory;

tasks and responsibilities of involved institutions;

QA/QC time schedule;

QA/QC plan that has been prepared to improve transparency, comparability, and completeness of GHG inventory. In the QA/QC plan quality control procedures to be

used before and during the compilation of GHG inventory are described.

check- lists and procedure descriptions for independent experts for quality assurance of

GHG inventory.

background for inventory improvement plan preparation activities.

Figure 1.2 shows the annual inventory process how the inventory is produced within the

national system.

Figure 1.2 Inventory Process

The result of quality depends on four main stages – planning, preparation, evaluation and

improvements and is ensured by inventory experts during compilation and reporting of inventory.


53

The inventory planning stage includes the setting of quality objectives and elaboration of the

QA/QC plan for the coming inventory preparation, compilation and reporting work. The main objective of Latvia’s GHG inventory system is to produce high quality GHG inventories.

The quality requirements set for the annual inventories – transparency, consistency,

comparability, completeness, accuracy, improvements and timelines. To ensure these inventory principles the following QA/QC activities of the inventory is done (Figure 1.3)

Figure 1.3 QA/QC activi ties of the inventory

The setting of quality objectives is based on the inventory principles taking into account the available resources.

The quality objectives for the 2015 inventory were the following:

Allocate sufficient resources for the implementation of the QA/QC plan especially

with regard to the QC activities performed by the inventory compilers preparing the NIR and CRF tables;

Allocate sufficient time and human resources to the final stages of the inventory

compilation process in which cross-sectoral work such as the key category analysis occurs, and enhance the QC procedures so that errors are avoided in future annual

submissions;

Strengthen the QC checks to adequately track any changes in the reporting between

the original submission and the successive resubmissions, if any, of the national inventory;

In order to ensure improvements:

All improvements promised in the NIR are carried out;

Feedback on reviews is systematic;

Inventory QC procedures meet requirements.

In order to ensure transparency:

transparent information is included in the NIR and CRF (including information regarding the used methodology, activity data and emissions in tables);

key words and indicators is used according to the IPCC guidelines;

recommendations of inventory reviews regarding transparency is taken into account as

far as possible;

documentation regarding quality control check is indicated;

a summary regarding the changes since the last inventory in relation to transparency is provided in the NIR.

In order to ensure consistency:

time series are consistent;

recommendations received during inventory review regarding consistency is taken into account after evaluation as far as possible;

information regarding consistency and recalculations is provided in the NIR;

an explanation for a decline or increase in emissions of time series is provided.


54

In order to ensure comparability:

methodologies and formats used in the inventory meet comparability requirements;

emissions and CO2 removal is localized and distributed according to the IPCC.

In order to ensure completeness:

emissions from all potential sources and gases is calculated;

recommendations of review – international experts – regarding improvements is taken into account as far as possible;

information regarding completeness is provided in the NIR;

all reasons for recalculations and reasons why a designation NE (not evaluated) and IE

(included elsewhere) is used instead of data is indicated;

In order to ensure accuracy:

Tier 2 or a higher method is used for the main sources as far as possible;

uncertainties are calculated and information is provided in the NIR;

a summary regarding changes in uncertainties and regarding improvements in comparison with the previous inventory is provided in the NIR.

In order to ensure timeliness:

inventory reports reach their recipient (EU / UNFCCC) within the set time.

1.2.4 Quality Control procedures

1.2.4.1 Quality Assurance procedures

The QA reviews are performed after the implementation of QC procedures to the finalised inventory. The inventory QA system comprises reviews to assess the quality of the inventory.

A basic review of the draft GHG emission and removal estimates and the draft report takes place before the final submissions to the EU and UNFCCC (January to March) by the

involved institutions on GHG inventory preparation process.

The draft of National inventory report (NIR) was sent to CSB, MoA, and MoT on 1st of July for checking and approving. According to Decision 13/CP.2011, the CRF version 5.0.0 was

considered as not functioning in order to enable Annex I Parties to submit their common reporting format tables for the year 2015 at allocated time. That’s why Annex I Parties in

2015 may submit their common reporting format tables after 15 April, but no longer than the corresponding delay in the CRF Reporter availability. According to previous mentioned the subsequent delays in reporting to European Commission (EC) have been expected and Draft

NIR and CRF tables according to Regulation (EU) No 525/2013 have been submitted only on 30th of June 2015. Consequently the Draft NIR and CRF tables were sent to involved

institutions for comments at the end of June.

UNFCCC review reports indicate the issues where inventory need the improvements and elaboration. The centralized review was taking place in Bonn, Germany from 1st till 6th of

September, 2014. During the review ERT formulated a number of recommendations relating to potential problems in some sectors of Latvia`s previous NIR. The ―Report on the individual

review of the annual submission of Latvia submitted in 2014‖12 was received on 13th of March, 2015. Responses to the recommendations provided in the review report (except KP

11

http://unfccc.int/resource/docs/2014/cop20/eng/10a03.pdf 12

http://unfccc.int/resource/docs/2015/arr/lva.pdf


55

LULUCF information) were elaborated in the Submission 2015 (Chapter 10 – Recalculations

and improvements).

The improvement plan for GHG inventory is compiled based on the findings of the UNFCCC, EC, internal reviews and recommendations from third part experts.

Quality Assurance (QA) activities include a planned system of review procedures conducted by personnel not directly involved in the inventory compilation/development process.

According to Regulation No. 217 MEPRD is responsible for ensuring QA procedures for GHG inventory.

Periodically all sectors are revised by third part experts. In previous submission energy, waste

and agriculture sectors were checked by personnel not directly involved in the inventory compilation. In 2015 submission LULUCF, LULUCF KP sectors were checked by

international third part reviewer. Results and recommendations in LULUCF sector are implemented in this submission in respective chapter 10, Table 10.2 Information regarding implementation of LULUCF KP recommendations will be included in next submission.

Within the project of EEA Financial Mechanism 2009-2014 Programme "National Climate Policy" quality control procedures for quality assurance of Industrial Proceses and Product

Use and LULUCF, KP sectors are still ongoing in 2015. Experience exchange seminars for previous mentioned sectors were held in the first half of 2015 as well as research devoted to improving the F-gases inventory is still continuing in 2015. Results are partially reflected in

this submission but entire information will be elaborated in next submissions.

1.2.4.2 Quality Control and Quality Assurance process improving the inventory

QA/QC procedures are an important component in the development of greenhouse gas emission inventory preparation. The basic aim of the QA/QC process is to ensure the quality

of the inventory and to contribute to the improvement of the inventory. Improving the submission during QA/QC process, the main findings and conclusions concerning the inventory quality and improvements needs to be considered and communicated into Latvia`s

GHG inventory system for making decisions concerning the annual inventory process and next inventory preparation.

The outcomes of the QA/QC process results in a reassessment of inventory or source category uncertainty estimates. For example, if data quality is found to be lower than previously thought and this situation cannot be rectified in the timeframe of the current inventory, the

uncertainty estimates are re-evaluated. Increased effort on QC results in improved emissions estimates and reduced uncertainties.

1.2.4.3 Documentation and Archiving

As part of general QC procedures, it is good practice to document and archive all information

that is used for emission estimates. Documentation has a significant role in the inventory quality management.

All institutions involved in GHG inventory preparation process are responsible for archiving

the collected data and estimated emissions.

Documentation system in CSB:

• Survey and calculations documentation system;

• Quality indicators documentation system;

• Thesaurus;


56

• 2 sub-systems – internal & external.

CSB a Document Storage System (ADS):

• In 2008, ADS was developed in the CSB;

• Starting with 2009, each year all fundamental processes performed for each statistical

survey as well as for calculations have to be described in detail;

• All quality indicators have to be described;

• ADS provides also a technical possibility to attach a number of supporting documents;

• ADS is made accessible for external users on the CSB website.

Revisions of data are defined as any changes to statistics that have already been published.

CSB uses integrated statistical data management system (ISDMS) for data processing. It is a metadata driven system based on metadata and standardisation of data processing, which in

essence does not require individual programming. This system is used for processing surveys of business (mainly) and social statistics. Data collected by means of questionnaires which are not included in the ISDMS are processed by the CSB using other especially developed data

processing applications. Detailed information is given in the Annex 6.

The expert organizations have archives located in their own facilities. Experts keep all

information (all disaggregated emission factors, activity data, and documentation about ho w these factors and data have been generated and aggregated for the preparation of the inventory) on the hard disks of the individual expert’s desktops.

Every annual inventory (CRF tables, XML, SQL Databases, NIR and Registry information) is archived.

Latvia has a centralized archiving system - all information (including corresponding letters, internal documentation on QA/QC procedures, external and internal reviews, documentation on annual key sources and key source identification, planned inventory impro vements) used

for inventory compilation are collected on the special server and the backup of data are made periodically. All information is archived at LEGMC. Common, password protected FTP

folder is used for information storage and exchange.

Printed copies of NIR are stored in LEGMC and MEPRD archives in May each year, after completion and submission of the inventory. All information is archived on CDs as well.

1.2.4.4 Verification activities

In the CSB data are verified in two data processing stages: on raw data level (processing of

individual information) and on aggregated data level (verifying prepared aggregates).

CSB uses several methods for data verification at the raw data level:

– arithmetical connections;

– logical connections;

– comparison with data of previous periods;

– mutual coherence verification with other statistical questionnaires;

– statistical registers and administrative data.

Aggregates are made and different groupings are formed from the raw data produced. CSB uses similar methods for verification of aggregates to ones, which are applied in the verification of raw data.


57

1.2.4.5 Treatment of confidentiality issues

For Latvia’s GHG Inventory mainly confidentiality is related to activity data provided to LEGMC by CSB. The data then is used for emission estimation and can’t be reported further.

If the data that could be considered as confidential is provided to LEGMC by production plan or other enterprise then the data is not considered as confidential and can be reported within

GHG Inventory.

Data of CSB

Legal, technical and administrative measures:

Legal:

―Law on State Statistics‖

―Law on State Information Systems‖

―Personal Data Protection Law‖

―Information Publicity Law‖.

Technical:

Physical Security (environmental (temperature fluctuations, etc.), technical (voltage reduction, etc.) and human factors (theft, deliberate or unintentional damages, etc.).

Logical Security (security measures provided by IT: user names and passwords, antivirus, firewalls etc.).

Administrative:

Information Security Management Coordination Council (ISMCC) ensure and implement in the CSB security policy, security means and principles of data storage, information

classification and confidentiality, principles of granting access rights.

Information Security Policy developed (2008).

CSB ensures confidentiality and protection of information supplied by the respondents, as well individual information received from other sources pursuant to the requirements of national legislation in force.

The CSB takes the necessary organisational, administrative and technical measures to ensure confidentiality.

Technical: described in internal regulations and procedures on security and use of Information Systems.

Organisational and administrative:

– ―Confidentiality Statement‖ signed by every employee, laying down the

personal data non-disclosure obligation;

– Confidentiality Council established to ensure that individual information possessed by the CSB is used for scientific and research purposes according to

the provisions of the Official Statistics Law and other legal acts and to deal with legally unregulated confidentiality issues.

– Handbook of statistical confidentiality developed (2009) that provides explanations of the methods used by the CSB for ensuring data confidentiality.


58

It is strictly determined in Law of Statistics what information could be provided to other

institutions even though the information is needed in emission estimation and reporting under international conventions. CSB can’t give the information of amount of production if one or two companies produce up to 95% from total market production in particular sector. Due to

small market of Latvia almost all industrial production data is classified as confidential with exception of food and drink sector where wine and sugar production data is classified as

confidential. LEGMC has interdepartmental agreement with CSB to receive confidential information for the emission estimation but these activity data has to be reported as ―C‖ in CRF Tables and in NIR.

Data of EU ETS

As all Latvia’s industrial processes sector’s companies are participating in EU ETS then data

from these companies can be obtained from their annual GHG report within compliance obligations within EU ETS. These activity data used emission factors and used emission estimation methodologies can be reported in NIR and in CRF Tables as the data of EU ETS

can’t be confidential and all companies’ annual GHG reports are published in LEGMC webpage.

ETR documentation

As no significant changes were done in Latvia’s ETR then ITL Initialization documentation wasn’t changed either.

1.2.5 Changes in national inventory arrangements since previous annual GHG

inventory submission

There are no changes to arrangements with institutions involved in the GHG inventory preparation. The agreements regarding responsibilities are maintained and continue to be in force according to the national legislation (Regulations of the Cabinet of Ministers No. 217

adopted on 27 March 2012 ―The National Inventory System of Greenhouse Gas Emission Units‖).

1.3 INVENTORY PREPARATION, DATA COLLECTION, PROCESSING AND STORAGE

1.3.1 GHG inventory

Each sector has an assigned one or more responsible sectoral experts who are responsible for

conformity with the relevant reporting guidelines, selection of appropriate methods and data sources and activity data collection, processing and updating of data.

For the Energy (excluding Transport), IPPU and Waste – data collection and emission estimation is done by LEGMC experts from Air and Climate Division, Chemicals and Hazardous Waste Division and Inland Waters Division.

For Transport activity data is collected and emissions are calculated by expert from Institute of Physical Energetics.

For Agriculture, data collection and emission estimations are done by Latvia University of Agriculture in collaboration with Ministry of Agriculture.

Land-use and land use change data and KP- LULUCF data are collected and

emissions/removals are calculated in Latvian State Forest Research Institute "Silava" in collaboration with Ministry of Agriculture and Latvia University o f Agriculture.


59

All experts responsible for data collection and processing in a particular sector are preparing

their data (activity data, emission factors) for import into CRF Reporter software. During the preparation of 2015 submission, all processes relevant to the GHG inventory have been restructured according to the 2006 IPCC Guidelines and the revised CRF tables.

1.4 BRIEF GENERAL DESCRIPTION OF METHODOLOGIES AND DATA SOURCES USED

1.4.1 GHG inventory

Latvia’s GHG emissions inventory is based on 2006 IPCC Guidelines for GHG inventories.

The main sources for emission factors are:

National studies for country specific parameters and emission factors (e.g. CO2

emission factors, aspects influencing SO2 emission factors, distribution of animal waste management systems, average N excretion and etc.);

2006 IPCC Guidelines;

2013 Supplement to the 2006 IPCC Guidelines for National Greenhouse Gas

Inventories: Wetlands (IPCC Wetlands Supplement);

2013 Revised Supplementary Methods and Good Practice Guidance Arising from the

Kyoto Protocol (IPCC KP Supplement);

EMEP/CORINAIR Guidebook 2007 and EMEP/EEA 2009;

EMEP/EEA air pollutant emission inventory guidebook 2013.

For 2015 NIR and CRF tables compilation the CRF Reporter version 5.10.1 was used. To

calculate GHG emissions, supplemental locally developed database in Excel format was used for all sectors except for Road Transport where COPERT IV was used.

Where data of bottom – up method were available and plants had reported estimated data

using plant specific emission factors and estimation methodologies for Energy sector, these data were used in the submission. If these data were not available, Tier 1 method from 2006

IPCC Guidelines was used to estimate emissions. Emissions for the whole country fuel consumption were estimated by adding up fuel consumption of individual sectors multiplied by appropriate emission factors.

Emissions from Road Transport sector were estimated by using COPERT IV model for 1990–2013 (Tier-2 method). Emissions for other transport sub-sectors were estimated according to

IPCC Tier 1 and Tier 2 methodologies (Tier 2 method for diesel oil CO2 emission calculation in railway and navigation and Tier 2 method for jet kerosene emission calculation in aviation (civil and international). Rest of emissions have been calculated by Tier 1 method).

Emissions from Industrial Processes and Product Use were estimated according to 2006 IPCC Guidelines, EMEP/CORINAIR 2007 Guidebook, EMEP/EEA 2009, EMEP/EEA air pollutant

emission inventory guidebook 2013 as well as using expert research and judgment about activity data and emission factors.

Emissions from Agriculture sector were estimated according to methodologies from 2006

IPCC Guidelines additionally using local researches related some parameters.

2006 IPCC Guidelines and IPCC Wetlands Supplement for CO2, CH4 and N2O emissions

from drained and rewetted soils were used to estimate emissions from LULUCF and KP-LULUCF sector.


60

2006 IPCC Guidelines were used to estimate emissions from Waste sector.

The Table 1.3 presents the main data sources used for activity data as well as information on actual calculations:

Table 1.3 Main data sources for activi ty data and emission values

Sector Data Sources for Activity Data Emission Calculation

Energy

Energy balance from Latvian Central Statistical Bureau (CSB);

IEA/ OECD – EUROSTAT – UNECE

Annual questionnaires;

LEGMC ―2-AIR‖ database;

Research of experts.

LEGMC Air and Climate division,

plant operators

Transport

Energy balance from Latvian CSB;

IEA/AIE – EUROSTAT – UNECE Annual questionnaires;

Data of Road Traffic safety Directorate;

Research of experts.

IPE according to agreement with the Ministry of

Environmental Protection and Regional Development

Industrial Processes

and Product Use

National production and sales statistics;

Direct information from enterprises

operating with pollutants;

Central Statistical Bureau;

Chemicals Register;

Assumptions by experts;


Research by experts;

LEGMC ―2-AIR‖ database

LEGMC Air and Climate division,

plant operators

LEGMC Chemicals and Hazardous Waste division

Agriculture

National agricultural statistics obtained

from CSB;

National studies.

Latvia University of Agriculture in collaboration with Ministry of Agriculture

LULUCF;

LULUCF KP

National forest inventory

State forest service

Ministry of Agriculture of Republic of

Latvia

Central Statistical Bureau

State Firefighting & Rescue Service

National studies and expert judgment

Latvian State Forest Research Institute "Silava" in

collaboration with Ministry of Agriculture and Latvia

University of Agriculture

Waste

Latvian Environment, Geology and

Meteorology Centre ―3-Waste‖ and ―2-

Water‖ databases;

Methane recovery installations;

CSB.

LEGMC Chemicals and Hazardous Waste division,

LEGMC Inland Waters Division


61

1.5 BRIEF DESCRIPTION OF KEY CATEGORIES

1.5.1 GHG inventory

This section provides an overview of key categories. The identification of key categories is described in the 2006 IPCC Guidelines Chapter 4: Methodological Choice and Identification of Key Categories.

Key sources are the emissions/removals, which have a significant influence on the total inventory in terms of the absolute level of emissions and the trend of emissions or both. Level

Assessment identify source category whose level has a significant effect on total national emissions. Trend Assessment identifies sources that are the key because of their contribution to the total trend of national emissions.

It is important to identify key source categories so that the resources available for inventory preparation may be prioritized and the best possible estimates prepared for the most

significant source categories.

IPCC methodologies offer two different methods for identifying key sources: Approach 1 and Approach 2. In the Approach 1 method, the emission sources are sorted according to their

contribution to emission level or trend. In the Approach 2 method, the relative uncertainties of the source categories are also taken into account. The key sources are the emission categories,

which represent together 95% of the inventory uncertainty if using level and trend assessment and 90% of the total value of the total trend assessment with uncertainty.

Both approaches are used to identify key sources for time period 1990-2013. The

identification is divided in two parts, key sources excluding LULUCF and key sources including LULUCF source categories. The starting point for the choice of source categories

with LULUCF is the list presented in the 2006 IPCC Guidelines, Chapter 4 Methodological Choice and Identification of Key Categories, Table 4.1. The base year for CO2, CH4, and N2O greenhouse gas emissions was 1990.

Summary of key categories is shown in Table 1.4. Key categories are identified by Approach 1 and Approach 2 in order to provide additional insight into the reasons why particular

categories are key (Table 1.4). Tables 4.2 and 4.3 of volume 1 of the 2006 IPCC Guidelines, including and excluding LULUCF are provided in Annex 1 of this submission.

Table 1.4 Key categories in 2013

IPCC category/Group Gas Identi fication

criteria

With

LULUCF

Without

LULUCF

1.A.1.a Public Electricity and Heat Production -

Solid Fuels

CO2 T1,T2 X X


Gaseous Fuels

CO2 L1, L2,T1,T2 X X

1.A.1.a Public Electricity and Heat Production - Peat CO2 T1


Liquid Fuels

CO2 T1,T2 X X

1.A.1.c Manufacture of So lid Fuels and Other

Energy Industries - Gaseous Fuels

CO2 L1 X

1.A.2.a Iron and Steel - Gaseous Fuels CO2 T1 X

1.A.2.c Chemicals - Liquid Fuels CO2 T1,T2 X X

1.A.2.d. Pulp, Paper and Print - Gaseous Fuels CO2 T1


62


criteria

With

LULUCF

Without

LULUCF

1.A.2.e Food Processing, Beverages and Tobacco -

Liquid Fuels

CO2 L1,T1,T2 X

1.A.2.e Food Processing, Beverages and Tobacco -

Gaseous Fuels

CO2 L1 X X

1.A.2.f Non-metallic Minerals - Liquid Fuels CO2 T1 X

1.A.2.f Non-metallic Minerals - Solid Fuels CO2 L1, L2,T1,T2 X X

1.A.2.f Non-metallic Minerals - Gaseous Fuels CO2 L1,T1 X X

1.A.2.f Non-metallic Minerals - Other Fossil Fuels CO2 L1 X X

1.A.2.g Other - Liquid Fuels CO2 L1,T1,T2 X X

1.A.2.g Other - Gaseous Fuels CO2 L1,T1 X X

1.A.3.b Road Transportation - Diesel Oil CO2 L1, L2,T1,T2 X X

1.A.3.b Road Transportation - Gasoline CO2 L1, L2,T1,T2 X X

1.A.3.b Road Transportation - LPG CO2 L1, L2,T1,T2 X X

1.A.3.c Railways - Liquid Fuels CO2 L1,T1 X X

1.A.4.a Commercial/Institutional - Gaseous Fuels CO2 L1,T1 X X

1.A.4.a Commercial/Institutional - Liquid Fuels CO2 L1,T1,T2 X X

1.A.4.a Commercial/Institutional - Solid Fuels CO2 L1,T1,T2 X

1.A.4.a Commercial/Institutional - Biomass Fuels CH4 L1,L2,T2 X

1.A.4.b Residential - Liquid Fuels CO2 L1 X X

1.A.4.b Residential - So lid Fuels CO2 L1,T1,T2 X

1.A.4.b Residential - Gaseous Fuels CO2 L1,T1 X X

1.A.4.b Residential - Biomass Fuels CH4 L1, L2,T1,T2 X X

1.A.4.c Agricu lture/Forestry/Fisheries - Liquid Fuels CO2 L1, L2,T1 X X

1.A.4.c Agricu lture/Forestry/Fisheries - Solid Fuels CO2 T2 X

1.A.4.c Agricu lture/Forestry/Fisheries - Gaseous

Fuels

CO2 L1, L2,T1,T2 X

1.B.2.b Natural Gas CH4 L1, L2 X X

2.A.1. Cement Production CO2 L1, L2,T1,T2 X X

2.A.2. Lime Production CO2 T1,T2 X

2.F.1. Refrigeration and air conditioning HFCs L1, L2 X X

3.A.1 Enteric Fermentation - Cattle CH4 L1, L2,T1,T2 X X

3.B.1.1 Manure Management - Cattle CH4 L1 X X

3.B.1.3 Manure Management - Swaine CH4 L1,L2,T1,T2 X

3.B.1.4 Manure Management - Other livestock CH4 T2 X

3.B.2.1 Manure Management - Cattle N2O L1,L2 X

3.B.5 Indirect N2O emissions from Manure

Management

N2O L1, L2 X

3.D.1. Direct N2O emissions from managed soils N2O L1, L2,T1,T2 X X

3.G. Liming CO2 T1,T2 X X


63


criteria

With

LULUCF

Without

LULUCF

4. G. Harvested wood products CO2 L1, L2, T1,T2 X

4.A.1 Forest Land remaining Forest Land – Carbon

stock change, liv ing biomass

CO2 L1, L2, T1,T2 X

4.A.1 Forest Land remaining Forest Land – Drained

organic soil

CO2 L1, L2, T1,T2 X

4.A.1 Forest Land remaining Forest Land – Carbon

stock change, dead wood

CO2 L1, T1,T2 X

4.A.1 Forest land remain ing forest land - Controlled

burning

CO2 L1,T1,T2 X

4.A.1. Forest land, Emissions and removals from

drainage and rewetting and other management of

organic and mineral soils

N2O L1, L2,T1,T2 X

4.A.1. Forest land, Emissions and removals from

drainage and rewetting and other management of

organic and mineral soils

CH4 L1, L2,T1,T2 X

4.A.2 Land converted to Forest Land – Carbon stock

change, grassland converted to forest land

CO2 L1,T1 X

4.A.2 Land Converted to Forest Land – grassland

converted to forest land, carbon stock change, dead

wood

CO2 L1 X

4.A.2 Land converted to Forest Land – grassland

converted to forest land, Drained organic soil

CO2 T2

4.B.1 Cropland remaining Cropland – Drained organic

soil

CO2 L1, L2,T1,T2 X

4.B.1 Land converted to Cropland – Carbon stock

change – dead organic matter

CO2 T1 x

4.B. Cropland remaining cropland, Emissions and

removals from drainage and rewetting and other

management of organic and mineral soils

CH4 L1 X

4.B.2 Land converted to Cropland – Drained organic

soil

CO2 L1, L2,T1,T2 X

4.B.2 Land converted to Cropland – Carbon stock

change, forest land converted to cropland

CO2 T1,T2 X

4.C.1 Grassland remain ing Grassland – Drained

organic soil

CO2 L1, L2,T1,T2 X

4.C.2 Land converted to Grassland – Drained organic

soil

CO2 L1, L2,T1,T2 X

4.C.2 Land converted to Grassland –Mineral soil CO2 L1,T1,T2 X

4.D.1. Wetlands, Peat extract ion from lands, organic

soils

CO2 L1,T1,T2 X

4.D.1 Wetlands remaining Wetlands – Carbon stock

change – living biomass

CO2 L1, L2,T1,T2 X

4.D.1 Wetlands remaining Wetlands – Carbon stock

change –organic soils

CO2 L1, L2,T1,T2 X


64


criteria

With

LULUCF

Without

LULUCF

4.E.1 Settlements remain ing Settlements – Carbon

stock change – living biomass

CO2 L1, L2,T1,T2 X

4.E.2 Land converted to Settlements – Carbon stock

change – living biomass

CO2 L1, L2,T1,T2 X

4.E.2 Land converted to Settlements – Carbon stock

change – dead organic matter

CO2 L1,T1 X

4.E.2 Land converted to Settlements – Organic soils CO2 L1, L2,T1,T2 X

4.E.2 Land converted to Settlements – Mineral soils CO2 L1,T1 X

4.E.2 Lands converted to settlements, Direct nitrous

oxide (N2O) emissions from n itrogen (N)

mineralizat ion/immobilization associated with

loss/gain of soil organic matter resulting from change

of land use or management of mineral soils

N2O T2 X

5.A.1. Managed Waste Disposal on Land CH4 L1, L2 X X

5.D.1 Domestic Wastewater CH4 L1,L2,T1 X X

5.D.2 Industrial Wastewater CH4 L1, L2,T2 X X

5.A.2. Unmanaged Waste Disposal Sites CH4 L1, L2,T1,T2 X X

1.6 GENERAL UNCERTAINTY EVALUATION

1.6.1 GHG inventory

This section provides an overview of the approach to uncertainty analysis for Latvia’s inventory. The mandatory reporting tables of analyses are provided in Annex 2.

The uncertainty estimates of the inventory 2015 has been done according to the Approach 1

method presented in 2006 IPCC Guidelines. The Approach 1 is based on emission estimates and uncertainty coefficients for activity data and emission factors.

In many cases uncertainty coefficients have been assigned based on default uncertainty estimates according to 2006 IPCC Guidelines or on expert judgment, because there is a lack of the information. For each source, the uncertainty for activity data and emission factors was

estimated and given in per cent.

Generally for activity data from CSB 2% uncertainty is used according to received

information from CSB.

The uncertainty calculation is based on Excel file, which is send to sectoral experts for updating annually.

The uncertainty analysis was done for the all sectors: Energy, Industrial Processes and Product Use, Agriculture, Waste and LULUCF. Uncertainties are estimated for direct

greenhouse gases, e.g. CO2, CH4, N2O and F-gases only.

In the annual meeting at the beginning of the inventory cycle the experts are advised to go through the uncertainty ranges of activity data and emissions factors in order to prioritize

inventory improvements. This year the uncertainty categories were reviewed and disaggregated according to 2006 IPCC Guidelines.


65

Uncertainties of 2013 emission estimates are reflected in Table 1.5. The overall uncertainty of

the inventory has improved since previous submission. Table 3.3 (with and without LULUCF) of volume 1 of the 2006 IPCC Guidelines is provided in Annex 2.

Table 1.5 Uncertainties of 2013 emission estimates

Uncertainty in total inventory % Trend uncertainty %

With LULUCF 55% 17%

Without LULUCF 11% 3%

The elaboration of uncertainty evaluation is still ongoing during the project ―European Economic Area Financial Mechanism 2009-2014 – ―National Climate Policy‖. Experience

exchange seminar is planned to take place at the end of October 2015. Within this seminar Latvian experts will gain experience from Norway colleagues regarding uncertainty estimation, evaluation and documentation. The aim of this project activity is to review current

uncertainty estimates and to undertake the Approach 2 uncertainty analysis. Results will be reflected into future submissions.

Detailed about uncertainty assessment is described under each subsector.

1.7 GENERAL ASSESSMENT OF COMPLETENESS

1.7.1 GHG inventory

Latvia has provided estimates for all significant IPCC source and sink categories according to

the detailed CRF classification. Estimates are provided for the following gases: CO 2, N2O CH4, F-gases (HFC, PFC, SF6 and NF3), NMVOC, NOx, CO and SO2. No additional sources

and sinks identified.

In accordance with the IPCC Guidelines, international aviation and marine bunker fuel emissions are not included in national totals.

The notation keys presented below are used to fill in the blanks in all the tables in the CRF. Notation keys used in the NIR are consistent with those reported in the CRF.

NE (not estimated):

―NE‖ is used for existing emissions by sources and removals by sinks of greenhouse gases that have not been estimated.

IE (included elsewhere):

―IE‖ is used for emissions by sources and removals by sinks of greenhouse gases that have

been estimated but included elsewhere in the inventory instead of the expected source/sink category.

NA (not applicable):

―NA‖ is used for activities in a given source/sink category that do not produce emissions or emissions are negligible.

C (confidential):

―C‖ is used for emissions that could lead to the disclosure of confidential information classified in the national legislation if reported at the most disaggregated level. In this case a

minimum of aggregation is required to protect business information.


66

1.7.2 Completeness by timely coverage

Both direct GHGs as well as indirect GHGs are covered by the Latvia’s inventory. A

complete set of CRF tables are provided for all years and the estimates are calculated in a consistent manner.


67

2. TRENDS IN GREENHOUSE GAS EMISSIONS

Detailed information on emission trends is provided in the description of IPCC sectors in

chapters 3-7 and in the CRF trend tables.

2.1 DESCRIPTION AND INTERPRETATION OF EMISSION TRENDS FOR AGGREGATED GREENHOUSE GAS EMISSIONS

The aggregated greenhouse gas emissions include gases defined in the Kyoto protocol – carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), sulphur hexafluoride (SF6),

hydrofluorocarbons (HFC), perfluorocarbons (PFC) and nitrogen trifluoride (NF3). The emission levels are presented in Gg of carbon dioxide equivalents.

Figure 2.1 Latvia`s aggregated greenhouse gas emissions in 1990-2013 (Gg CO2 eq)

As illustrated in Figure 2.1, Latvia’s GHG emissions have decreased considerably since the

1990-ties. This decrease influenced the economic situation in the country. In Latvia the transition period to market economy started after 1991. This process provoked essential changes in all sectors of national economy and resulted in the decrease of GHG emissions

after 1990.

For the first commitment period of Kyoto Protocol Latvia reached its emission limitation

target to limit it`s emissions between 2008 and 2012 by 8% of 1990 level.

Under the second commitment period of the Kyoto Protocol (2013–2020), Latvia contributes to achieving the EU quantified economy-wide emission reduction target of a 20% reduction in

emissions by 2020 compared with the 1990 base-year level. In Doha all EU 28 Member States decided to fulfil the GHG emission reduction commitments jointly so the 20% reduction

target now attributes to all EU Member States altogether.

The target for the EU and its Member States is formalized within the Climate and Energy Package of 2008 where the separate targets for the EU ETS and non-ETS emissions are

adopted. Latvia’s national target by 2020 for sectors outside the EU ETS allows the +17% increase of GHG emissions compared to 2005.


68

2.2 DESCRIPTION AND INTERPRETATION OF EMISSION TRENDS BY GAS

Carbon dioxide (CO2) is the main greenhouse gas causing the climate change. In 2013, CO2 emissions constitute 66.0% of Latvia’s total greenhouse gas emissions. In 2013, total CO2 emissions had decreased by approximately 62.8% since 1990.

The most important source of CO2 emissions (Gg) in 2013 was fossil fuel combustion – 90.8%, including Energy Industries – 28.6 %, Manufacturing Industries and Construction –

11.3 %; Transport – 41.3 %, Other sectors (Agriculture, Forestry, etc.) – 18.6 %.

Other anthropogenic emission sources of CO2 are Industrial Processes and Product Use – 7.5 % and Waste 0.01 %.

CO2 removals take place by green plants absorbing CO2 in the process of photosynthesis. In 2013, LULUCF in Latvia removed -147.78 Gg CO2 eq.

Main sources of CH4 emissions in Latvia are Enteric Fermentation of Livestock, Solid Waste Disposal Sites and Energy sector. Other important sources of CH4 emissions are leakage from natural gas pipeline systems and combustion of biomass. CH4 emissions in 2013 contribute

approximately 18.5 % of total GHG emissions (excluding LULUCF). The methane emissions (Gg) decreased by 49.0 % in 2013 since 1990.

Agricultural soils are the main source of N2O emissions in Latvia generating 83.6 % of all N2O emissions (Gg) in 2013. Other N2O emission sources are transport and biomass, combustion of liquid and other solid fuels in sectors of energy conversion and industry, waste

and sewage. Since 1990, total N2O emissions had decreased by 44.0 % in 2013, mainly due the decrease in the emissions from agriculture.

Emissions from HFCs and sulphur hexafluoride (SF6) consumption are reported for the period 1995-2013. Total HFCs emissions (Gg CO2 eq) increased in 2013 compared with 2012. SF6 emissions from electrical equipment contribute 8.50 Gg CO2 eq in 2013. Emissions of the

PFCs and NF3 does not occur (NO) in Latvia for all time series.

Emissions by sources are illustrated in the following Figure 2.2.

Figure 2.2 Latvia`s greenhouse gas emissions by source 1990-2013 excluding LULUCF


69

2.3 DESCRIPTION AND INTERPRETATION OF EMISSION TRENDS BY

CATEGORY

2.3.1 Trends in ENERGY

Figure 2.3 Trend in GHG emissions from Energy sector in 1990-2013 (Gg CO2 eq.)

There are two types of emission categories within Energy sector – fuel combustion, where emissions from Energy Industries (CRF 1.A.1), Manufacturing Industries and Construction (CRF 1.A.2), Transport (CRF 1.A.3), Other sector (CRF 1.A.4) and Other (military activities;

CRF 1.A.5) sector are produced, and fugitive emissions (CRF 1.B) where leakages from oil distribution and natural gas are occurring.

As it can be seen in Figure 2.3, the Energy sector (CRF 1.A, 1.B) is the most significant source of GHG emissions with 73.2% share of the total emissions in 1990 and 65.2% share in 2013. Most of Energy sector emissions (98.7% from total Energy emissions in 1990, and

98.6% in 2013) are produced by combusting fuels (CRF 1.A).

Emissions have decreased in all Energy subsectors – the largest decrease can be seen in

Manufacturing industries and Construction (CRF 1.A.2), where emissions in 1990-2013 have decreased by 79.7%. Also in Other sector (CRF 1.A.4) which includes Commercial/Institutional, Residential and Agriculture/Forestry/Fisheries the decrease in GHG

emissions is 74.1%, and in in Energy Industries GHG emissions have decreased by 68.8%. In Fugitive sector the decrease in GHG emissions is 59.2%.

After the decreasing in the period 1990 -1999, total GHG emissions from Transport (CRF 1.A 3) had the rapid growth in the period 2000 – 2007. Peak of GHG emissions in transport sectors have been recognized in 2007 when emissions exceeded 1990 level by 27%. The main

reason for this increasing of emissions was a sharp growth of economy and income of population resulting in rapid increasing of cars (mainly passenger cars).


70

Gg CO2 eq.

0

500

1000

1500

2000

2500

3000

3500

4000

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Figure 2.4 GHG emissions development in trans port 1990 – 2013 (Gg CO2 eq.)

Recession of the national economy was the major reason for decreasing of transport activities – decrease of passenger km by passenger cars and ton km by freight transport - and corresponding GHG emission decreasing in the time period 2008 – 2009. We can recognize

stability in GHG emission trend of transport sector in the last 3 years.

In 2013, total GHG emissions in the transport sector, compared 1990 level, have decreased by

6.7 %, however emissions have increased by 1.2% compare with 2012.

2.3.2 Trends in INDUSTRIAL PROCESSES AND PRODUCT USE

Figure 2.5 Trend in GHG emissions from IPPU sector in 1990-2013 (Gg CO2 eq.)

Figure 2.5 shows the GHG emission trend in IPPU sector. Data on emissions in IPPU sector are linked with the economic situation of the country as well as availability of statistical data.

The largest decrease in emissions occurred between 1990 and 1993 when industry was going


71

through a crisis. It has to be noted that in the beginning of 90ties during the countrywide

change in government system and national economy statistics was not well kept. Therefore there is lack of statistical data regarding industry during this time period or they are vague.

Since year 2000 and after the crisis in national economy of Russian Federation in 1999-2000

with whom Latvia has strength economic relations, GHG emissions from IPPU sector have increased from 158.61 Gg CO2 eq in 2000 to 309.45 Gg CO2 eq in 2008. It can be explained

with sharp development of Latvian industry when construction activities increased and industrial production of building materials also increased.

Due to Latvia’s economical features since 2007–2008 the industry development was slowing

down as the financing and real estate sectors started dominating in national economy. In 2009-2010 emissions increased in mineral industry sector due to cement production plant

switched the production technology and installations and increased its capacity by approximately 2.4 times.

Largest part of GHG emissions in the Industrial Processes and Product Use (IPPU) sector

constitute CO2 emissions from 2.A Mineral industry (82.2 % of total CO2 emissions from IPPU sector and 5.0% from total CO2 emissions in 2013). The second largest source is 2.F

Product Uses as ODS Substitutes causing 15.9% from all IPPU emissions and 1.0% from total GHG emissions in 2013. Considerably smaller are rest of IPPU emission sources – 2.G Other Product manufacture and use, 2.D Non energy products from fuels and solvents use and 2.C

Metal industry constituting together 1.9% from entire IPPU emissions in 2013.

Comparing with 2012 the emissions from IPPU sector in 2013 have decrease by about 2.8%

and mainly it can be explained with different production and services demand in external market.

2.3.3 Trends in AGRICULTURE

Agricultural GHG emissions in Latvia consist of CH4 emissions from enteric fermentation of

domestic livestock, CH4 and N2O emissions from manure management, N2O emissions from agricultural soils and CO2 emissions from liming and urea application. The trend of emissions

in CO2 eq. by category is presented in Figure 2.6. Generally emissions from the agricultural sector have declined by 58.4% compared to 1990, due to the decrease of livestock population, crop production and amounts of synthetic fertilizer consumption.

Figure 2.6 Trends of emissions by category within the sector, 1990-2013 (Gg, CO2 eq.)


72

In 2013, agriculture sector contributed 21.0% of the total GHG emissions originated in Latvia

or 2310.1 Gg CO2 eq. Emissions from agricultural soils contributed major share of the total emissions from the sector – 53.7%, enteric fermentation emissions was second largest source from the sector – 34.8%. The share of manure management emissions was evaluated as 10.7%

of total emissions in the sector, remaining 0.8% of emissions refer to liming and urea application. GHG emissions increased in 2013 by 2.6% comparing to 2012 due to increase of

livestock numbers (excepting goats and horses) with highest value for non-dairy cattle by +5.7%. Statistics also showed increase of synthetic N fertilizer consumption (+6.9%), sown area (+2.2%) and lime application to soils (+33.8%).

2.3.4 Trends in LULUCF

Net aggregated emissions in LULUCF sector considerably increased since 1990 due to growth of economic activity in forest sector and due to conversion of forest lands to

settlements and croplands. Although the increment of living biomass in forest land remaining forest and afforested land is still larger than the carbon losses due to commercial felling and natural mortality, the gap between gains and losses is decreasing, causing reduction of the net

removals of CO2 in forest land. Hence the total growing stock of living biomass is still increasing in forest lands. Major changes took place also in cropland and wetland sectors due

to implementation of the new guidelines (2006 IPCC Guidelines and IPCC Wetlands Supplement). Summary of the net emissions excluding harvested wood products is shown in Figure 2.7.

Figure 2.7 Summary of the net emissions in LULUCF sector (Gg CO2 eq.)

Absolute increase of the net annual GHG emissions in LULUCF sector in 2013 if compared

to 1990 is 8751.72 Gg CO2 e., mostly because of increase of emissions in forest lands (by 11166.14 Gg CO2 e. between 1990 and 2013). Emissions increased also in settlements – by

948.85 Gg CO2 eq. between 1990 and 2013. In cropland, grassland and wetlands emissions decreased by, respectively 536.10, 643.05 and 211.79 Gg CO2 eq. annually between 1990 and 2013. Reduction of emissions in cropland is caused by conversion of cropland to grassland.

Net decrease of annual removals in LULUCF sector in 2013 in compare to 1990 is 98 %.


73

2.3.5 Trends in WASTE

GHG emissions from Waste sector have been fluctuated from 1990-2013. Fluctuations in total

GHG emissions in waste sector could be explained with changes of economic situation in last 20 years (Figure 2.8).

Figure 2.8 Trend in GHG emissions from Waste sector in 1990-2013 (Gg CO2 eq.)

Some industry sectors were almost closed in the middle of 90-ties. Emissions from Biological

treatment of solid waste and Incineration and open burning of waste are very small in comparison to 5.A. and 5.D. In 2013, emissions were approximately 1.97 % lower than in 1990. In 2012, emissions from

the Waste sector were 749.54 Gg CO2 equivalents; it contributes about 6.8% of total GHG emissions (excluding LULUCF).

2.4 DESCRIPTION AND INTERPRETATION OF EMISSION TRENDS OF INDIRECT GREENHOUSE GASES AND SO2

The emissions trends of the indirect greenhouse gases, sulphur dioxide, nitrogen oxides, carbon monoxide and non-methane volatile organic compounds, are presented in Figure 2.9.


74

Figure 2.9 Total indirect greenhouse gas emissions trend 1990-2013 (Gg)

In 2013, the sulphur dioxide emissions were 1.46 Gg from which 87.7% originated in the Energy sector and 12.2% from Industrial Processes. Since 1990 to 2013 the total SO2

emissions have decreased by 98.5%. The reduction is mainly due to use of fuels with lower content of sulphur as well as fuel switching from solid and liquid types of fuel to natural gas and biomass.

Nitrogen oxides were generated generally in the Energy sector (89.8%) and 4.5% in the Industrial Processes. In 2013, the total emissions were 33.59 Gg. The Transport sector was

responsible for 48.7% of the total NOx emissions. The total NOx emissions have decreased by 62.6% from 1990 to 2013. Generally the reduction is due to decrease of total fuel consumption that was caused by transformation of national economy as well as energy

efficiency and control measures and also solid fuels and heavy liquid fuels replacement with natural gas and biomass fuels.

In 2013, Carbon monoxide emissions were 149.19 Gg, originated generally in the Energy sector (94.4%). Residential sector generates the biggest part of the total CO emissions – 74.5%. The CO emission trend shows a decrease of emissions for period 1990 – 2013 by

61.5%.

In 2013, total emissions of Non-methane volatile organic compounds were 87.70 Gg from

which 59,9% generates in Industrial Processes and Product Use (mainly from Non-energy products from fuels and solvent use which constitute 58.3% from total NMVOC emissions in 2013) and 31.3 % comes from Energy sector (Residential stationary plants).


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3. ENERGY (CRF 1)

3.1 OVERVIEW OF SECTOR

3.1.1 Quantitative overview

Both the imported (natural gas, liquid gas, oil and oil products, coal) and local fuels (wood, peat, hydro resources) are used in the Energy sector in Latvia (Table 3.1). Mainly the imported fuels (natural gas and heavy oil) are used in heat generation. Smaller boiler houses

burn local fuel (wood) and coal as well.

Table 3.1 Consumption of energy resources in Latvia (TJ)

1990 1995 2000 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Energy

consumption 301611 171390 144322 163544 166388 168204 175809 179210 171566 167721 175955 165148 166854 167128

Shale oil NO 79 2440 315 118 157 118 118 79 39 39 79 39 NO

Liquefied

petroleum gas

3689 1548 2140 2368 2505 2550 2687 2414 2186 2003 2103 2414 3279 3840

Gasoline and

aviation gasoline

26796 18128 14831 15214 15346 15126 16753 18299 16672 13941 12667 11926 10146 9282

Jet kerosene 3067 1166 1123 1685 2074 2463 2852 3414 4105 4297 4926 4925 5012 5185

Other kerosene

648 432 43 NO NO NO NO NO NO NO NO NO NO NO

Diesel oil

(oven fuel inclusive)

43000 17166 20693 29063 31188 32887 36371 41343 39133 36500 38994 35268 35182 36222

Residual fuel

oil 63092 36134 9460 4547 3735 3167 2152 1624 1096 1421 1069 735 568 194

Petroleum

coke NO NO NO 956 1088 429 627 132 NO 165 627 NO NO NO

Other liquids 2637 712 2553 1381 1088 209 1088 963 795 711 1005 NO NO 42

Liquid fuels,

total 142929 75365 53283 55529 57142 56988 62648 68307 64066 59077 61430 55347 54226 54765

Coal 26098 7172 2761 2648 2570 3146 3409 4248 4248 3409 4378 4509 3645 2906

Peat briquettes

867 403 31 NO NO NO NO 1 1 6 6 3 4 4

Coke 290 211 290 161 188 188 161 107 134 134 80 80 161 52

Oil shale 28 NO NO NO NO NO NO NO NO NO NO NO NO NO

Solid fuels, total

27283 7786 3082 2809 2758 3334 3570 4356 4383 3549 4464 4592 3810 2962

Peat 3286 3838 2452 915 90 80 70 90 90 30 100 40 30 80

Natural gas 99653 42279 45635 56408 55785 56852 58892 56922 55814 51381 61313 54034 50806 50269

Wood and

wood

products

27581 42102 39695 46969 49434 49396 49748 48706 46018 52591 45646 46901 52503 53106

Charcoal NO NO NO NO 30 60 30 45 210 240 210 240 268 210

Bioethanol NO NO NO NO NO NO 43 NO 1 108 350 318 279 264

Biodiesel NO NO NO NO NO 107 60 73 82 73 808 749 659 631

Landfill gas NO NO NO 162 242 251 259 271 290 323 331 349 347 371

Other biogas NO NO NO NO NO NO NO NO NO NO 61 465 1629 2141

Sewage sludge gas

NO 20 44 54 97 113 95 100 99 125 143 125 131 119

Straws NO NO NO NO NO NO 11 16 14 29 60 43 38 58


76

1990 1995 2000 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Biomass,

total 27581 42122 39739 47185 49803 49927 50247 49211 46714 53489 47609 49190 55854 56901

Used oils 879 NO NO 409 497 848 263 234 263 117 95 88 58 29

Used tires NO NO 131 290 313 174 119 90 81 20 107 424 313 517

Municipal

wastes NO NO NO NO NO NO NO NO 155 57 838 1433 1756 1605

Other fuels,

total 879 NO 131 699 810 1022 382 324 499 195 1040 1945 2127 2151

Oil products have an important place in the Latvian energy resource market; their market share is about 33% in 2013, including heavy fuel – residual fuel oil and shale oil. The residual

fuel oil consumption has a significant decrease - in 1990 it was 21% from total fuel consumption, but in 2013 it is 0.1%. The essential decrease of heavy oil share in energy balance is explained with increase of costs due to increasing fuel costs because of

implementation of the EU Directive 1999/32/EC prescribing that sulphur content of heavy oil shall not exceed 1%. The biggest part from liquid fuel consumption contributes to gasoline

and diesel oil with approximately 83% from total liquid fuel consumption in 2013 where gasoline is mostly consumed in transport sector and only a small part is used in off- roads. Diesel oil consumption divides by combusted in transport sector – 74.3%, and combusted in

stationary combustion installations – 25.7% from total diesel oil consumption. The total consumption of liquid fuels in 2013 has decreased by 62% since 1990.

Total share of solid fuels in national market is quite low – approximately 2%. The solid fuel consumption in last years is stable although the consumption had decreased by 89% since 1990. A decrease in solid fuel consumption can be seen in 2008-2009 due to global economic

crisis. However, from 2009 to 2011 it increased by 29% that can mainly be explained with an increase of coal consumption, but in years 2011-2013 there can be seen a decrease in solid

fuel consumption by 35% due to reduced use of coal.

Peat is a local fuel quite widely used in Latvia in early 1990-ties with 1.09% of total energy consumption. However, nowadays amounts of peat used have decreased and have reached

0.05% of total share in 2013.

The largest consumers of natural gas are combined heat and power plant, and heat generation

enterprises as well as industrial enterprises. Natural gas has a stable place in total fuel consumption where its share is 33% in 1990 and 30% in 2013. Natural gas consumption has decreased by 50% in 1990-2013. Recent years until 2011 the consumption of natural gas had

an increasing trend – from 2009 to 2010 it increased even by 19%, but in 2010-2013 there can be seen a decrease of natural gas consumption by 18%.

Biomass fuels are wood and wood products, straw, charcoal and biofuels. In the total fuel consumption the share of firewood and other wood products is quite substantial and has reached its peak with 32% in recent years, comparing with 1990 when firewood consumption

was only about 9% from total energy consumption. In 2010-2013 wood and wood products’ use increased reaching 32% of all fuels consumed.

In latest years liquid and gaseous biofuels are becoming more popular and their consumption from 0.28% in 2005 has reached 2.11% in 2013 from total fuel consumption. In latest years also such biomass fuels as straws are used, and it has an increasing trend with fluctuations,

especially in 2010-2011, which can mainly be explained with significant temperature differences in winter.

There are also used tires and municipal wastes consumed in the latest years, and the most significant increase can be observed in 2011 – comparing with 2010 the consumption of other


77

fuels has increased by 97% and reached 1.12% from total share. However, in 2012-2013 the

increase of other fuels consumed was not as rapid as in previous year, and the increase in particular fuels’ use in 2013 was about 3%, comparing with 2012, and the share of total fuel amount consumed was 1.27% in 2013. Also used oils are reported as other fuels, however,

this fuel type has a decreasing trend.

Hydroelectric power plants (HPP) and combined heat and power plants (CHP) produce part of

the electrical power, while part is imported (Table 3.2, Table 3.3). Volume of electricity generation directly depends on the through-flow of the river Daugava. Also the import of electricity from Russia, Estonia and Lithuania has a quite substantial role in the electricity

supply.

Table 3.2 Electricity production and consumption in Latvia (TJ)

Production

Own use

and

losses

Import Export

Final consumption

CRF

1.A.2

CRF

1.A.3

CRF

1.A.4 TOTAL

1990 16186 6883 25700 12798 11484 918 17550 29952

1995 10573 6372 9529 1408 5130 677 10267 16074

2000 10163 5202 7589 1159 5159 547 10411 16117

2001 10210 5688 8424 1645 5562 623 10314 16499

2002 8906 5188 10217 1764 5494 518 11563 17575

2003 8330 5065 9616 137 5778 490 12456 18724

2004 11369 4975 9839 2290 5882 500 13072 19454

2005 12139 4767 10278 2545 6120 533 13972 20625

2006 9878 4522 10116 1087 6332 540 15242 22114

2007 10030 4194 17870 7070 6538 504 16740 23782

2008 11405 4198 16715 7643 6066 497 17298 23861

2009 12625 4032 15333 9378 5421 436 16114 21971

2010 12848 4626 14303 11160 5724 453 16197 22374

2011 10649 4133 14432 9950 6012 446 15829 22287

2012 13756 3636 17766 11678 7175 464 17015 24653

2013 10915 3556 18018 13140 6509 446 16719 23674

Table 3.3 Heat production and consumption in Latvia (TJ)

Production Own use and losses Final consumption

CRF 1.A.2 CRF 1.A.4 TOTAL

1990 99439 15171 32929 51339 84268

1995 46112 7156 1969 36987 38956

2000 31867 6815 659 24393 25052

2001 33937 7038 641 26258 26899

2002 33048 6541 630 25877 26507

2003 33516 6409 626 26481 27107

2004 31093 6174 608 24311 24919

2005 31144 5886 684 24574 25258

2006 30056 5454 634 23968 24602

2007 28685 4911 554 23220 23774

2008 26402 4010 356 22036 22392

2009 26308 4099 298 21911 22209


78

Production Own use and losses Final consumption

CRF 1.A.2 CRF 1.A.4 TOTAL

2010 28662 4590 387 23685 24072

2011 25000 4104 268 20628 20896

2012 26857 4464 259 22134 22393

2013 26249 4551 479 21219 21698

Types of fuels used for combustion in Latvia:

Liquid fuels are mainly imported from Latvia’s neighbouring countries – Lithuania, Belarus,

Russian Federation, Norway and others and consist of:

shale oil;

liquefied petroleum gas;

motor gasoline and aviation gasoline;

kerosene type jet fuel;

other kerosene;

gasoline type jet fuel;

motor diesel oil and heating gas oil;

residual fuel oil;

other liquids;

petroleum coke.

Solid fuels consist of coal and coke imported from Commonwealth of Independent States (countries of former Union of Soviet Socialist Republics), as well as local fuel – peat briquettes – that are mainly produced inside country but not imported;

Peat is 100% produced inside of the country;

Gaseous fuels (natural gas) are 100% imported from Russian Federation;

Biomass fuels:

solid biomass – wood and other wood products, charcoal, straw, is mainly produced

and used inside of the country,

methane obtained from biogas that is 100% produced inside of the country – landfill gas that is used since 2002 when first landfill started to collect and combust biogas

with energy recovery, and sludge gas that is combusted with energy recovery since 1993 in one sewage purification plant, and also other biogases from anaerobic

fermentation,

liquid biofuels – biogasoline and biodiesel, which are mainly imported from Latvia’s

neighbourhood countries.

Other fuels are municipal wastes and industrial wastes – used tires, collected by and combusted in cement production plant in Latvia, as well as used oils.

3.1.2 Description

As it can be seen in the Figure 3.1, the share of subsectors in the Energy sector has changed, especially in 1.A.3 Transport sector, 1.A.4 Other sectors and 1.A.1. Energy industries and

these changes are explained in the corresponding sub-chapters.


79

Figure 3.1 Share of emissions in the Energy sector in 1990-2013 (% ; Gg CO2 eq)

In 1990 the biggest share of GHG emissions was held by Energy industries with 32.7% as well as Other sectors with 30.8% from all emissions produced in Energy sector. 20.5% of emissions were produced also in Manufacturing industries and construction sector, and the

smallest share of emissions was held by Transport sector with only 15.9%. Emissions in military sector (1.A.5) were not produced until 1996.

However, starting from 1990, the share of Transport emissions have constantly grown, reaching 38.1% in 2005. Since then, the Transport sector have been the largest emissions’ producer in Energy sector, which can be generally explained with the increase of population’s

income and growth of economy and also with restrictions related with use of fossil fuels in stationary combustion.

In 2013, the biggest share of GHG emissions in Energy sector is held by Transport sector with 39.9% of total Energy sector’s GHG emissions. The second largest subsector with 27.4% share is Energy Industries, and a quite significant part of emissions – 21.4% – is produced

within 1.A.4 Other sectors (small combustion in commercial and residential subsectors). Emissions from Military sector (1.A.5) have a 0.1% share from Energy emissions.

Table 3.4 GHG emissions from Energy sector in 1990–2013 (Gg)

A Fuel combustion B Fugitive emissions from fuels Aggregate GHGs

CO2 CH4 N2O CH4 CO2 CO2, CH4, N2O

Gg Gg Gg CO2 equivalent

1990 18 556.80 12.21 0.50 9.90 0.0115 19 010.87

1995 8 905.56 13.35 0.37 7.92 0.0092 9 349.05

2000 6 852.82 11.23 0.33 6.03 0.0070 7 233.03

2001 7 251.76 12.44 0.36 5.84 0.0073 7 671.39

2002 7 251.93 12.19 0.37 6.10 0.0074 7 667.66

2003 7 417.36 12.71 0.40 4.76 0.0055 7 854.13

2004 7 436.70 13.09 0.42 4.71 0.0055 7 888.07

2005 7 528.48 13.04 0.41 5.33 0.0062 7 977.95

2006 7 999.20 12.69 0.41 3.82 0.0044 8 437.35

2007 8 315.68 12.62 0.41 3.92 0.0046 8 754.11

2008 7 896.70 11.66 0.39 4.03 0.0047 8 304.46


80

A Fuel combustion B Fugitive emissions from fuels Aggregate GHGs

CO2 CH4 N2O CH4 CO2 CO2, CH4, N2O

Gg Gg Gg CO2 equivalent

2009 7 168.96 12.80 0.39 3.81 0.0044 7 604.47

2010 7 992.44 10.40 0.36 3.66 0.0043 8 361.18

2011 7 152.43 10.45 0.38 2.52 0.0044 7 526.39

2012 6 808.90 11.25 0.41 3.18 0.0049 7 211.11

2013 6 705.76 10.32 0.40 4.04 0.0080 7 084.09

Decrease of emissions depends on economic and social situation in the beginning and ending

of the 90-ties. The emissions are decreasing from 1990 to 2013 with some fluctuations in between. Since 2000, fuel consumption as well as emissions from fuel combustion increased

due to development of national economy (Table 3.4).

GHG emissions from the Energy sector in the latest years (since 2000) are fluctuating with a peak point in 2007 that is explained with an increase of national economy (Figure 3.2). GHG

emissions in the Energy sector increased by 19.9% in 2000-2007. In the second half of 2008, a recession in national economy started caused by the crisis. That is the main reason why all

GHG emissions in Energy sector decreased by 13% in 2007-2009. Starting with 2010, total GHG emissions increased again by 9.8% compared with 2009 as consumption of fuel increased, too, because of the relatively warm winter – in 2009 the number of heating degree

days13 was 4184, while in 2010 – 4671. However, the emissions decreased again by 10.2% in 2011 comparing with 2010 because of warm weather – the number of HDD was 3989. In

2012 fuel consumption decreased even more as well as the amount of GHG emissions produced – by 3.9% from 2011 level, however, the number of HDDs was considerably larger (HDD = 4385), which could be explained with better heat insulation in buildings. In 2013, the

emissions were by 1.4% lower than in 2012, and also the number of HDDs was lower.

Figure 3.2 GHG emissions from Energy sector 1990–2013 (Gg CO2 eq)

13

Heating degree day (HDD) is a proxy for the energy demand needed to heat a home or a business; it is derived from measurements of outside air temperature. The heating requirements for a given structure at a specific location are considered to be to some degree proportional to the number of HDD at that location. HDD are defined relative to a base temperature (18°C, according to EUROSTAT), the outside temperature below which a building is assumed to need heating (http://www.eea.europa.eu/data-and-

maps/indicators/heating-degree-days-1).


81

In CRF 1.A.1 Energy industries sector the decrease in emissions 2008-2009 can be explained

with the crisis in national economy caused by global financial crisis, also the winter in 2009 was quite warm, therefore in 2009 GHG aggregated emissions in 1.A.1 were 2.6% less than in 2008, but in 2010 an increase of emissions by 20.5% in Energy industries was observed,

mostly because of the ending of the global crisis and also the average temperature in winter was lower than in year 2009. As year 2011 was warmer than previous year, the fuel

consumption, as well as the emissions decreased by 7.9% if compared with year 2010. However, the average temperature in 2012 was less than in 2011, but the amounts of consumed energy resources continued to decrease as well as the emissions which decreased

by 10.3% comparing to 2011. In 2013 the emissions in Energy industries increased by 3.8%, if compared with 2012.

The decrease of industrial production in Manufacturing industries (CRF 1.A.2) was influenced by economic situation when development of national economy was made in financial and real estate sectors but the import dominated over export. Increase of costs and

prices as well as total inflation led to a total decrease of local industry. Therefore the GHG emissions from CRF 1.A.2 sector decreased by 19.6% in 2008-2009, but in 2010 emissions

increased by 21.6% as fuel consumption increased. In year 2011 the emissions decreased by 17.8% that can be explained with great reconstructions in the enterprise ―Liepājas Metalurgs‖ under 1.A.2.a sector where the fuel consumption decreased significantly. In year 2012

comparing to year 2011 the GHG emissions increased by 6.3% mainly due to intensified steel melting in „Liepājas Metalurgs‖. However, in 2013, there can be seen a decrease in 1.A.2.

emissions by 17.6% which is also related with activities in ―Liepājas Metalurgs‖, which went bankrupt at particular year.

For Transport sector (CRF 1.A.3) emissions decreased from 2008 to 2009 by 12.4% that was

influenced by sharp increase of fuel price and economy crisis. Decrease is also explained with improvement of car park in country, where old cars were replaced with new ones. Starting

from 2010 growth of emissions from transport sector is observed by 2.1% comparing to 2009, although in year 2011 the emissions decreased again and comparing with year 2010 the decrease was 11%. The decrease in emissions can be seen also in 2011-2012 by 3.5%, but in

2013 the emissions have increased by 1.2%.

The emissions in CRF 1.A.4 Other sectors are constantly decreasing since 1990, with

fluctuations in emissions in the time scale which mostly depend on the temperatures in winter. In 2013 comparing with 2012, the emissions have decreased by 3.9%. Overall, since 1990 the emissions in 1.A.4. sector have decreased by 74.1%.

The emissions in 1.A.5 Other have decreased by 12% in 2012-2013, and it is not related neither with financial circumstances nor weather conditions.

Decrease of methane fugitive emissions can be explained with a constant improvement of natural gas supply infrastructure.


82

Figure 3.3 Total indirect GHG emissions from fuel combustion in 1990–2013 (Gg)

In 2013, the largest part of indirect emissions contributes CO then NMVOC and NOx

emissions (Figure 3.3). Most CO and NMVOC emissions come from wood combustion in the Residential sector while the largest share of NOx emissions comes from Transport sector.

The biggest decrease is observed in SO2 emissions where emissions decreased from 95.93 Gg

in 1990 to 1.28 Gg in 2013. It is explained with changes in type of fuels combusted in Energy sector as well as with implementation of national legislations for sulphur content in liquid

fuels used for transport.

The indirect emissions in general are lower in 2013 if compared to 2012: CO emissions have decreased by 10.1%, NMVOCs have decreased by 7.4%, NOx emissions have decreased by

0.5%, but the greatest decrease in emissions can be seen in SOx – 18.9% which can be explained with an increased amounts of biomass burned comparing with previous year.

Key categories

Key categories reported in Table 3.5 are estimated without taking LULUCF sector into account by using Tier 1 estimation level. Tier 1 approach for determinatio n of the key source

is used by incorporating category uncertainty estimates developed under Tier 1 uncertainty analysis.

Table 3.5 Key categories in Energy sector in 2013

Key categories of emissions and removals Gas

Criteria used for key

source identification

Level Trend

1.A.1 Fuel combustion - Energy Industries - Liquid Fuels CO2

x

1.A.1 Fuel combustion - Energy Industries - Gaseous Fuels CO2 x x

1.A.1 Fuel combustion - Energy Industries - Peat CO2

x

1.A.2 Fuel combustion - Manufacturing Industries and Construction -

Liquid Fuels CO2 x x


Solid Fuels CO2 x x


Gaseous Fuels CO2 x x


Other Fossil Fuels CO2

x

1.A.3.b Road Transportation CO2 x x


83

Key categories of emissions and removals Gas

Criteria used for key

source identification

Level Trend

1.A.3.c Railways CO2 x

1.A.4 Other Sectors - Liquid Fuels CO2 x x

1.A.4 Other Sectors - So lid Fuels CO2 x x

1.A.4 Other Sectors - Gaseous Fuels CO2 x x

1.A.4 Other Sectors - Biomass CH4 x x

3.2 FUEL COMBUSTION (CRF 1.A)

Emissions from fuel combustion comprise all in-country fuel combustion, including point sources, transport and other fuel combustion. Emissions from fuel combustion in the Energy sector are divided into following subcategories:

1.A.1 Energy Industries;

1.A.2 Manufacturing Industries and Construction;

1.A.3 Transport – road transport, civil aviation, railways and domestic navigation;

1.A.4 Other Sectors (Commercial/Institutional, Residential,

Agriculture/Forestry/Fisheries);

1. A.5 Other (Not elsewhere specified) – military transport.

Reported greenhouse gas emissions are listed in Table 3.6.

Table 3.6 Reported emissions from fuel combustion in Latvia in 2013

Source Fuel Type Emissions

CO2 CH4 N2O NOx CO NMVOC SO2

1.A.1 Energy Industries

a. Public Electricity and Heat Production

Liquid Fuels √ √ √ √ √ √ √

Solid Fuels √ √ √ √ √ √ √

Peat √ √ √ √ √ √ √

Gaseous Fuels √ √ √ √ √ √ NO

Biomass √ √ √ √ √ √ NO

Other Fuels NO NO NO NO NO NO NO

b. Petroleum Refin ing

Liquid Fuels NO NO NO NO NO NO NO

Solid Fuels NO NO NO NO NO NO NO

Peat NO NO NO NO NO NO NO

Gaseous Fuels NO NO NO NO NO NO NO

Biomass NO NO NO NO NO NO NO


c. Manufacture of So lid Fuels and Other Energy Industries








84



1.A.2 Manufacturing Industries and Construction

a. Iron and Steel







b. Non-Ferrous Metals







c. Chemicals



Peat √ √ √ √ √ √ √




d. Pulp, Paper and Print







e. Food Processing, Beverages and Tobacco







f. Non-metallic minerals






Other Fuels √ √ √ √ √ √ √

g. Other


85





Peat √ √ √ √ √ √ √




1.A.3 Transport

a. Civil Aviat ion

Aviation Gasoline √ √ √ √ √ √ √

Jet Kerosene √ √ √ √ √ √ √

b. Road Transportation

Gasoline √ √ √ √ √ √ √

Diesel Oil √ √ √ √ √ √ √

LPG √ √ √ √ √ √ √

Other Liquid Fuels √ √ √ √ √ √ √

Gaseous Fuels NA NA NA NA NA NA NA

Biomass √ √ √ NO NO NO NO


c. Railways




Biomass √ √ √ √ √ √ √

Other Fuels NA NA NA NA NA NA NA

d. Navigation

Residual Oil (Residual

Fuel Oil) NO NO NO NO NO NO NO

Gas/Diesel Oil √ √ √ √ √ √ √

Gasoline √ √ √ √ √ √ √

Other Liquid Fuels NA NA NA NA NA NA NA

Gaseous Fuels NA NA NA NA NA NA NA



e. Other Transportation






1.A.4 Other Sectors

a. Commercial/Institutional





86






b. Residential







c. Agricu lture/Forestry/Fisheries







1.A.5 Other

a. Stationary







b. Mobile – Military navigation and aircrafts







CO2 emissions from fuel combustion were 6705.76 Gg (including Transport sector) in 2013 and accounted 92.2% of the total CO2 emissions.

CH4 emissions from fuel combustion were 10.32 Gg (including Transport sector) in 2013 that makes 12.7% of total CH4 emissions. The biggest part of CH4 emissions contributes to Other

sectors – 9.33 Gg.

N2O emissions from fuel combustion were 0.40 Gg (including Transport sector) and accounted 8.1% of the total N2O emissions in 2013.


87

3.2.1 Comparison of the sectoral approach with the reference approach (CRF 1.A

(b), 1.A(c))

Reference approach (RA) is carried out using import, export, production and stock change

data as well as data of fuel consumption in international aviation and international marine reported as bunkering from the CSB online database where Energy balance is available.

Difference between CO2 emissions estimated with RA and SA for liquid fuels is quite high –

from 3.94% in 1995 to -18.64% in 2010 (Table 3.7). Difference for solid fuels is smaller - 0.60% in 1992 to -0.01% in 1995. Difference for gaseous fuels fluctuates from 5.34% in 1993

to 0.37% in 2005. For other fuels the fluctuations are a bit higher – from 2.58% in 2006 to -8.26% in 2013.

Table 3.7 Difference (% ) between Sectoral and Reference approach data (PJ) and CO2 emissions (Gg)

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

Fuel consumption - Liquid fuels

SA 138.39 123.94 103.92 96.87 91.09 74.33 80.21 68.90 67.76 63.13 52.05

RA 139.86 123.14 104.18 96.56 93.12 77.01 78.65 67.48 66.46 55.13 44.99

Diff., % 1.06 -0.64 0.25 -0.33 2.22 3.60 -1.95 -2.05 -1.91 -12.68 -13.58

CO 2 emissions - Liquid fuels

SA 10272.41 9184.73 7702.74 7181.04 6781.17 5523.57 5976.97 5111.69 5020.72 4670.44 3814.53

RA 10431.23 9134.49 7725.98 7177.64 6947.01 5741.20 5876.94 5015.92 4948.82 4135.76 3324.28

Diff., % 1.55 -0.55 0.30 -0.05 2.45 3.94 -1.67 -1.87 -1.43 -11.45 -12.85

Fuel consumption - Solid fuels

SA 26.30 22.62 18.89 17.20 12.36 7.38 7.01 5.89 4.44 3.90 3.05

RA 26.42 22.73 19.00 17.26 12.36 7.38 7.01 5.89 4.45 3.90 3.05

Diff., % 0.44 0.50 0.60 0.36 0.01 -0.01 0.03 0.01 0.07 0.04 0.06

CO 2 emissions - Solid fuels

SA 2492.07 2140.89 1788.41 1629.48 1172.35 701.01 665.86 561.47 423.79 372.90 292.06

RA 2502.91 2151.66 1799.14 1635.33 1172.45 700.97 666.06 561.51 424.11 373.07 292.24

Diff., % 0.44 0.50 0.60 0.36 0.01 -0.01 0.03 0.01 0.08 0.05 0.06

Fuel consumption - Gaseous fuels

SA 98.43 97.76 70.20 45.20 33.62 41.30 35.22 43.12 42.22 40.44 44.96

RA 99.65 100.47 72.23 47.58 34.62 42.28 36.22 44.15 43.25 41.44 45.74

Diff., % 1.24 2.77 2.89 5.28 2.98 2.36 2.84 2.39 2.44 2.47 1.72

CO 2 emissions - Gaseous fuels

SA 5399.39 5362.40 3922.07 2525.61 1863.43 2285.06 1965.95 2404.37 2357.14 2252.13 2490.55

RA 5469.25 5513.98 4037.67 2660.35 1919.97 2340.84 2023.14 2463.54 2416.42 2309.39 2535.12

Diff., % 1.29 2.83 2.95 5.34 3.03 2.44 2.91 2.46 2.51 2.54 1.79

Fuel consumption - Peat

SA 3.22 3.24 3.85 3.62 3.37 3.84 3.50 3.47 2.45 1.36 2.39

RA 3.29 3.27 3.86 3.66 3.37 3.84 3.50 3.47 2.46 1.37 2.45

Diff., % 2.18 0.68 0.26 0.86 0.02 0.07 0.05 0.08 0.45 0.71 2.52

CO 2 emissions - Peat

SA 328.50 333.01 395.57 372.95 347.99 395.92 360.29 357.78 252.88 140.49 248.21

RA 337.34 336.22 397.72 376.89 348.52 396.74 361.06 358.52 254.32 141.62 254.67


88

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

Diff., % 2.69 0.96 0.55 1.06 0.15 0.21 0.21 0.21 0.57 0.80 2.60

Fuel consumption - O ther fuels

SA 0.88 IE,NO IE,NO IE,NO IE,NO IE,NO IE,NO IE,NO IE,NO 0.03 0.09

RA 0.88 NO NO NO NO NO NO NO NO 0.03 0.09

Diff., % 0 IE,NO IE,NO IE,NO IE,NO IE,NO IE,NO IE,NO IE,NO 0 0

CO 2 emissions - O ther fuels

SA 64.46 NO NO NO NO NO NO NO NO 3.04 10.86

RA 64.43 IE,NO IE,NO IE,NO IE,NO IE,NO IE,NO IE,NO IE,NO 3.04 10.85

Diff., % 0.05 IE,NO IE,NO IE,NO IE,NO IE,NO IE,NO IE,NO IE,NO 0.07 0.07

Continuation of Table 3.7

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Fuel consumption - Liquid fuels

SA 52.28 52.07 53.97 55.31 54.74 60.03 65.05 60.14 54.94 56.70 50.59 49.40 49.77

RA 47.99 44.00 48.86 45.16 42.23 54.19 59.51 55.66 47.02 46.06 43.76 47.37 47.09

Diff., % -8.19 -15.50 -9.47 -18.34 -22.86 -9.74 -8.52 -7.45 -14.42 -18.77 -13.49 -4.11 -5.40

CO 2 emissions - Liquid fuels

SA 3818.74 3807.08 3958.28 4055.78 3997.28 4383.90 4740.97 4380.27 4010.03 4152.28 3684.00 3590.59 3613.02

RA 3530.47 3241.14 3603.40 3725.25 3615.59 3980.39 4358.52 4080.54 3432.98 3378.11 3209.58 3483.25 3454.97

Diff., % -7.55 -14.87 -8.97 -8.15 -9.55 -9.20 -8.07 -6.84 -14.39 -18.64 -12.88 -2.99 -4.37

Fuel consumption - Solid fuels

SA 3.90 3.17 2.81 2.76 3.33 3.57 4.35 4.36 3.54 4.46 4.59 3.81 2.96

RA 3.90 3.17 2.81 2.76 3.33 3.57 4.36 4.38 3.54 4.46 4.59 3.81 2.96

Diff., % 0.06 0.05 0.04 0.04 0.04 0.03 0.00 0.60 0.00 0.00 0.00 0.00 0.03

CO 2 emissions - Solid fuels

SA 372.71 303.15 267.62 263.13 317.60 339.52 413.30 413.71 336.82 422.73 435.10 362.35 280.50

RA 372.93 303.32 267.74 263.25 317.73 339.63 413.32 416.21 336.84 422.72 435.12 362.36 280.58

Diff., % 0.06 0.06 0.04 0.05 0.04 0.03 0.00 0.60 0.01 0.00 0.00 0.00 0.03

Fuel consumption - Gaseous fuels

SA 52.25 53.50 55.67 55.25 56.69 58.63 56.59 55.48 50.74 61.04 53.53 50.30 49.99

RA 53.16 54.07 56.41 55.79 56.85 58.89 56.92 55.81 51.38 61.31 54.03 50.81 50.54

Diff., % 1.74 1.07 1.33 0.97 0.29 0.45 0.59 0.61 1.26 0.44 0.95 1.00 1.10

CO 2 emissions - Gaseous fuels

SA 2889.47 2960.08 3075.07 3055.18 3133.27 3242.42 3129.73 3066.38 2807.04 3372.02 2956.18 2772.75 2710.99

RA 2941.79 2993.20 3118.30 3087.14 3144.77 3259.63 3150.21 3086.54 2844.60 3389.23 2985.93 2802.61 2742.48

Diff., % 1.81 1.12 1.41 1.05 0.37 0.53 0.65 0.66 1.34 0.51 1.01 1.08 1.16

Fuel consumption - Peat

SA 1.25 1.01 0.67 0.08 0.08 0.07 0.09 0.05 0.03 0.05 0.04 0.03 0.06

RA 1.25 1.01 0.91 0.09 0.08 0.07 0.09 0.09 0.04 0.11 0.04 0.03 0.08

Diff., % 0.06 0.00 35.80 13.75 1.12 1.14 0.83 78.08 38.46 135.56 0.00 0.00 31.25

CO 2 emissions - Peat

SA 129.24 104.39 69.91 8.31 8.32 7.29 9.37 5.30 2.66 4.64 4.45 3.51 6.62

RA 129.41 104.46 95.00 9.46 8.42 7.38 9.45 9.45 3.70 10.98 4.45 3.51 8.73

Diff., % 0.13 0.07 35.89 13.83 1.19 1.21 0.90 78.30 39.13 136.53 0.08 0.08 31.85


89

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Fuel consumption - O ther fuels

SA 0.55 1.03 0.62 0.97 0.35 0.35 0.3 0.4 0.16 0.5 0.75 0.88 1.12

RA 0.55 1.03 0.62 0.97 0.35 0.35 0.3 0.4 0.16 0.5 0.75 0.88 1.12

Diff., % 0 0 0 -0.14 0.1 0 0 0 -0.01 0 0 0 0

CO 2 emissions - O ther fuels

SA 41.6 77.25 46.48 54.3 72 26.07 22.3 31.05 12.41 40.77 72.7 79.71 94.63

RA 42.37 78.3 47.39 55.21 73.07 26.74 22.81 31.37 12.43 41.63 66.7 88.85 90.77

Diff., % 1.86 1.37 1.96 1.68 1.49 2.58 2.3 1.06 0.09 2.09 -8.26 11.47 -4.08

The biomass consumption in the comparison is not included as this type of fuel is assumed as CO2 neutral and CO2 emissions from biomass combustion are taken into account in the CO2

emission estimation from Energy sector.

Amount of used tires combusted in cement production plant is reported as Other fuels as well

as municipal wastes combusted in the same cement production plant. According to 2006 IPCC Guidelines, used oils are also reported under Other fuels.

3.2.1.1 Explanation of the difference

Energy balance

In the Annual questionnaires, as well as in CSB online database statistical differences,

distribution losses and interproduct transfer are reported for certain fuels, whereas in the RA table only stock changes are possible to input. These data are not taken into account and not

put in stock changes’ cells of CRF Reporter RA tables. Therefore the difference for liquid fuels and peat and is quite significant for many years, for example, losses for peat are quite visible. To improve the transparency of reporting, the statistical differences, distribution

losses, as well as interproduct transfers for the whole time series are presented in Annex 4.

CSB estimates total consumption data by taking production, import, export, international

bunkering and stock changes data into account. Final consumption data is estimated by taking into account sectoral consumption data reported by fuel consumers excluding reported distribution losses data. Transformation and Energy sectors are not included in final

consumption data. For several fuel types difference between these two estimation approaches is reported as statistical difference that is quite significant for some fuel types – diesel oil,

gasoline, residual fuel oil. For peat amount of distribution losses is also quite significant but this amount is not taken into account in RA reporting.

CSB reports the amount of fuel that was used in interproduct transfer but this amount is not

reported in RA tables therefore the consumption of fuel in RA tables is reported although the fuel was not consumed in Latvia, for example, for other kerosene in 2004-2008.


90

The changes larger than 5% between fuel consumption in RA and SA are explained below for

each fuel type.

Figure 3.4 Difference in fuel consumption of Liquid fuels between Reference and Sectoral Approach

The difference between fuels varies from -5% to 5% until 1998, and with up to -25.12% difference in 2005 (Figure 3.4). The differences after 1998 can be generally explained with statistical differences in diesel oil energy balance which are not taken into account when

calculating Reference Approach, and also with interproduct transfers of RFO, shale oil, jet fuel and kerosene. In 1999, there are also large statistical differences in gasoline consumption

(-6.38 PJ).

Figure 3.5 Difference in fuel consumption of Gaseous fuels between Reference and Sectoral Approach


91

The differences in natural gas consumption between both approaches are mainly due to

distribution losses that occur every year (Figure 3.5).

Figure 3.6 Difference in fuel consumption of Peat (including Peat briquettes) between Reference and

Sectoral Approach

Among all fuel types, for peat and peat briquettes the differences are the most remarkable. It

is because in the recent years there are significant losses of peat reported by CSB, for example, in 2003, there are 241 TJ reported by CSB as peat losses, and it can be clearly seen in difference of Sectoral and Reference approaches - while the total consumption according to

Reference Approach is 914 TJ, within Sectoral Approach only 673 TJ are reported. The same applies to years 2008-2011 and 2013, where losses of peat are around 10-60 TJ.

Figure 3.7 Difference in consumption of Other fuels between Reference and Sectoral Approach

The differences for Other fuels are not larger than ±5%, therefore not analysed.


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Figure 3.8 Difference in consumption of Solid fuels between Reference and Sectoral Approach

The differences for solid fuels are not larger than ±5% therefore not analysed.

3.2.1.2 Explanation of the fluctuations

Fluctuations of emissions estimated with Sectoral and Reference Approach are more or less

equal. All fuels had decreased in 1990-1995 due to continued changes of national economy structure, inflation and collapse of national industry. Still in 1995-1996 the government

adopted strict rules to cut back the inflation and downward of industry so the fuel consumption since 1995-1996 also was restructured. Since 1996 the natural gas consumption is increasing but other fuel consumption are increasing only after 2000 – after crisis in

national economy of neighbourhood Russian Federation and due to development of national economy that was prepared for joining European Union. In the recent years there can be seen

the influence of global economic crisis in 2007-2009 and a recovery after that in 2010-2013 with a decreasing trend of emissions.

3.2.1.3 Methodological issues

2006 IPCC Guidelines Reference approach for the CO2 emission estimations and comparison of CO2 emissions were used. CRF Reporter software developed by experts from UNFCCC

was used to report emission data. Annual import, export, production, international bunkers and stock changes data divided by fuel types are put in the RA tables of CRF Reporter as well

as carbon emission factor and coefficient of fraction of carbon oxidized.

Generally emissions are calculated by multiplying fuel consumption with country specific, plant specific or IPCC default carbon EF taking into account fraction of carbon oxidized.

Carbon emission factors were estimated by taking into account net calorific values and the molecular weight ratio of the carbon and CO2. Net calorific values of the fuels are taken from

Energy Balance prepared by CSB. The fuel consumers reported the NCV of the used fuels to CSB according to national legislation that obliges the enterprises that do any fuel use activities report it to CSB. The consumption of fuels is taken from CSB online database due

to more precise data as in Annual Questionnaires, therefore, in order to improve transparency of the reporting, it was decided to use data from Energy Balance instead of Annual


93

Questionnaires. The NCV from natural gas has been taken from the enterprise ―Latvijas

Gāze‖ which reports NCVs of natural gas consumed to LEGMC every year.

For peat, gasoline, diesel oil, RFO, shale oil, jet fuel, kerosene, wood, used oils and natural gas carbon emission factor is assumed as country specific. For several fuels NCV changes

once in whole time series in 2003-2004 or 2002-2003 but for natural gas and municipal wastes NCV and also carbon emission factor changes for every year in whole time series.

NCV and CEF of other liquid fuels changes in every year in time series are explained with the fluctuation of other oil fuel structure (biogasoline, biodiesel, other liquid biofuels – bioethanol). Municipal wastes structure also influenced carbon emission factor change in

2008-2013.

Table 3.8 Carbon emission factors (t/TJ)

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Peat 28.925 28.925 28.925 28.925 28.925 28.925 28.925 28.925 28.925 28.925 28.925 28.925 28.925 28.925 28.925 28.925

Gasoline 18.893 18.893 18.893 18.893 18.893 18.906 18.906 18.906 18.906 18.906 18.906 18.906 18.906 18.906 18.906 18.906

Diesel oil 20.400 20.400 20.400 20.400 20.400 20.400 20.400 20.400 20.400 20.400 20.400 20.400 20.400 20.400 20.400 20.400

RFO 21.113 21.113 21.113 21.113 21.113 21.113 21.113 21.113 21.113 21.113 21.113 21.113 21.113 21.113 21.113 21.113

Shale oil 21.047 21.047 21.047 21.047 21.047 21.047 21.047 21.047 21.047 21.047 21.047 21.047 21.047 21.047 21.047 21.047

LPG 17.126 17.126 17.126 17.126 17.126 17.126 17.126 17.126 17.126 17.126 17.126 17.126 17.126 17.126 17.126 17.126

Jet fuel 19.718 19.718 19.718 19.718 19.718 19.713 19.713 19.713 19.713 19.713 19.713 19.713 19.713 19.713 19.713 19.713

Kerosene 19.715 19.715 19.715 NO NO NO 19.711 19.715 19.715 19.715 19.715 19.715 19.715 19.715 19.715 19.715

Wood 30.015 30.015 30.015 30.015 30.015 30.015 30.015 30.015 30.015 30.015 30.015 30.015 30.015 30.015 30.015 30.015

Used oils 20.012 20.012 20.012 20.012 20.012 28.659 28.659 28.659 28.659 28.659 28.659 28.659 28.659 28.659 28.659 28.659

Natural gas 15.173 15.167 15.157 15.136 15.155 15.148 15.146 15.139 15.144 15.142 15.140 15.141 15.161 15.158 15.120 15.120

Landfill

gas, sludge gas, other

biogas

NO 13.953 13.953 13.953 13.953 13.953 13.953 13.953 13.953 13.953 13.953 13.953 13.953 13.953 13.953 13.953

Industrial waste

NO NO 23311 23.31 23.311 23.311 23.311 21.787 21.787 21.787 23.787 23.787 17.104 19.884 18.925 19.998

Municipal

waste (non-biomass)

NO NO NO NO NO NO NO NO NO NO 23.882 23.241 25.075 29.623 32.051 23.463

Petroleum coke

26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600

Anthracite 26.800 26.800 26.800 26.800 26.800 26.800 26.800 26.800 26.800 26.800 26.800 26.800 26.800 26.800 26.800 26.800

Peat

briquettes 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600 26.600

Waste oils 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000

Straw 27.300 27.300 27.300 27.300 27.300 27.300 27.300 27.300 27.300 27.300 27.300 27.300 27.300 27.300 27.300 27.300

Charcoal 30.500 30.500 30.500 30.500 30.500 30.500 30.500 30.500 30.500 30.500 30.500 30.500 30.500 30.500 30.500 30.500

Oil shale 29.100 NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Coal 25.800 25.800 25.800 25.800 25.800 25.800 25.800 25.800 25.800 25.800 25.800 25.800 25.800 25.800 25.800 25.800

Coke 29.200 29.200 29.200 29.200 29.200 29.200 29.200 29.200 29.200 29.200 29.200 29.200 29.200 29.200 29.200 29.200

Other oil 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000

Biogasoline, biodiesels

NO NO NO NO NO NO NO 19.300 19.300 19.300 19.300 19.300 19.300 19.300 19.300 19.300

Other

liquid biofuels

NO NO NO NO NO NO NO 21.700 21.700 21.700 21.700 21.700 21.700 21.700 21.700 21.700

Carbon emission factors for petroleum coke, anthracite, peat briquettes, waste oils, straw,

charcoal, oil shale, coal, coke, other oil, biogasoline, biodiesels and other liquid biofuels taken


94

from 2006 IPCC Guidelines were used (Table 3.8). Carbon emission factor for industrial

wastes (used tires) was estimated based on CO2 emission factor reported by cement production plant within EU ETS.

3.2.1.4 Time series consistency

Time series of the estimated emissions are consistent and complete because the same

methodology, emission factors and data sources are used for sectors for all years in time series. Emissions from all sectors are estimated or reported as not occurring / not applicable therefore there are no ―not estimated‖ sectors.

3.2.1.5 Source-specific QA/QC and verification

The best way to check RA data is to compare them with SA data that is done already in CRF

Reporter. The difference between these two emission estimation and reporting methodologies has to be double-checked and explained.

There are several ways to do the checks of the activity data:

Energy sector data is taken from the Energy Balance that CSB, and it has the internal QA/QC procedures based on mathematical model and analysis to avoid logic

mistakes.

Data of RA are verified by CSB within National Inventory System Quality assurance

process and in case of inconsistency of data reported in NIR and in CRF with the data in Energy balance of CSB and data reported to EUROSTAT by CSB all the

information of data mismatch is reported to LEGMC. After that Energy sector’s sectoral expert check all again the reported data and incorporate necessary changes in CRF and in NIR. If the sectoral expert doesn’t agree with reported data mismatch and

considers that no changes are necessary the information of this is again sent to CSB with detailed explanation.

Estimated CO2 emissions are checked:

By comparing the emissions estimated with Reference Approach and Sectoral

approach. All significant differences (more than 5%) are double-checked. Difference has to be explained and agreed with CSB. This verification step is done for total fuel combustion sector.

By comparing used carbon emission factor with CO2 emission factors used in Sectoral Approach.

3.2.2 International bunker fuels

International bunkers cover international aviation and navigation according to the 2006 IPCC Guidelines. Emissions from international aviation and navigation are not included into national total emissions. Taking into consideration the fact that ports in Latvia are focused on

transit cargo transport, navigation activities have big fluctuations and depend on neighbouring countries’ economical and international trading activities and competitiveness of Latvian

ports’ with other neighbouring ports in Baltic Sea. At the same time emissions from aviation are more stable, and recent trend depicts a persistent increase. In 2013, total GHG emissions of International Bunkering (see Figure 3.9), compared to 2012 level has decreased by 0.9%.

In different subsectors various changes have taken place in 2013. In international aviation the GHG emissions have increased by 3.5%, whereas in the international navigation it has

decreased by 3.0 %.


95

CO2 eq.

0

200

400

600

800

1000

1200

1400

1600

1800

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Figure 3.9 Emissions from International Bunkers (Gg CO2 eq.)

Data about international bunker fuel consumption is provided by CSB (Table 3.9). CSB split

of fuel for national and international navigation/aviation is based on EUROSTAT and IEA guidelines on data collection. Defined approach about energy consumption allocation for international and national navigation/aviation fully is in line with the defined criteria in 2006

IPCC Guidelines and IPCC GPG 2000 (for more details see ―Energy Statistics Manual‖, IEA, EUROSTAT (2005)). In Latvia case there are no situations when international

marine/aviation transport departs from port in Latvia and stops in port in Latvia to drops and picks up passengers or freight and then departs to final destination in other country. Therefore implemented data collections of fuel consumption in international and national

navigation/aviation fully ensure a correct allocation between national and international mode.

To provide the consistent allocation of fuel consumption between domestic and international

mode in the navigation and aviation, CSB each month co llects and summarises the information which is submitted by every one of enterprises which perform fuel bunkering. For this purpose the particular statistical report format is elaborated in which the enterprises have

to fill in the data regarding amount of fuel sold respectively in domestic and international navigation and aviation.

Table 3.9 Fuel consumption in international transport (TJ)14

Aviation Navigation

Jet Kerosene Diesel Oil RFO

1990 3067.2 5013.8 14737.8

1995 1080.0 1104.7 5156.2

2000 1123.2 339.9 0.0

2001 1123.2 4249.0 3938.2

2002 1166.4 3611.7 4993.8

2003 1685.2 3101.8 4750.2

2004 2031.0 3186.8 5278.0

2005 2463.0 3824.1 7064.4

2006 2765.0 2761.9 5481.0

2007 3371.0 2506.9 4953.2

2008 4062.0 1912.1 6699.0

14

CSB. Annual Eurostat Energy Questionnaire, 2013


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Aviation Navigation

Jet Kerosene Diesel Oil RFO

2009 4278.0 2591.9 8850.8

2010 4907.0 2932.0 7592.0

2011 4926.0 3171.0 5806.0

2012 4984.0 3697.0 6374.0

2013 5142.0 3148.0 6658.0

CO2 emissions in the international navigation are affected by the fuel consumption, which depends on several factors:

On the one hand it is affected by the port activity indicators (loaded, unloaded cargo). As shown in Figure 3.10, the total loaded and unloaded cargo volume in 2013 has increased by nearly 24% compared to 2001. At the same time the structure of the

cargo handled (see Figure 3.11) has changed. The main changes have affected the oil transhipment, whose share of cargo handled has decreased from 18.7% to 0.2%. At the

same time, the coal share of the total cargo volume handled has increased from 9.7% to 37.3 %.

On the other hand, fuel consumption is affected by the number of vessels serviced in

ports. As shown in Figure 3.12, in spite of the rapid increase in the volume of cargo at the port of Riga, the number of serviced ships has remained almost unchanged. The

main reason for this trend is the increase in the gross tonnage of vessels. The most significant increase was registered in the average tanker gross tonnage, but also in

other cargo carrier groups (container, dry bulk carriers). All this confirms the fact that the cargo owners continue to optimize transport costs including fuel costs and try to use larger vessels where possible.

Figure 3.10 Loaded, unloaded cargo at ports in Latvia, ths d t


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Figure 3.11 Structure of loaded goods at ports in Latvia, ths d t.

0

0,5

1

1,5

2

2,5

3

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

loaded,unloaded cargo

served vessels

Figure 3.12 Loaded, unloaded cargo and served vessels at Riga port (2000 = 1)

The implemented emission factors for emission calculation from international navigation are

shown in Table 3.10.

Table 3.10 Emission factors used in the calculation of emissions from International Bunkering

CO2 CH4 N2O NOx CO NMVOC

Gg/PJ Gg/PJ Gg/PJ Gg/PJ Gg/PJ Gg/PJ

Diesel oil 74.0 0.004 0.03 1.8475 0.1742 0.0659

RFO 76.6 0.005 0.002 1.9532 0.1822 0.0665

The methodology used for calculation of emissions from international aviation corresponds to the 2006 IPCC Guidelines Tier 2 where the amount of LTO/cruises is crucial. Emissions from

international navigation are calculated in pursuance with 2006 IPCC Guidelines Tier 1.

The relevant emission factors are taken from different sources. All of the international aviation and navigation emission factors (CO2, CH4 and N2O) are derived from the 2006 IPCC

Guidelines while the remaining factors – from EMEP/EEA 2013 (for determination of SO2 EF country-specific sulphur content is applicable) (see Table 3.11 and Table 3.12).


98

Table 3.11 SO2 Emission factors used for diesel oil in the SO2 calculation of emissions International

Bunkering

Diesel oil Fuel

content NCV

EF

(Gg/PJ)

1990-2002 0.2 42.49 0.094

2003-2004 0.05 42.49 0.024

2004-2007 0.2 42.49 0.094

2008-2011 0.1 42.49 0.047

Table 3.12 SO2 Emission factors used for RFO in the SO2 calculation of emissions International

Bunkering

RFO Fuel

content NCV

EF

(Gg/PJ)

1990-2007 2.8 40.6 1.352

2007-2012 1.5 40.6 0.74

3.2.3 Feedstocks, reductants and other non-energy use of fuels (CRF 1.AD)

There are no emissions produced in this sector. Emissions from non-energy use of paraffin waxes, lubricants, bitumen and white spirits are included in CRF 4 – Industrial processes and product use sector.

3.2.4 Energy Industries (CRF 1.A.1)

3.2.4.1 Source category description

CRF 1.A.1 Energy Industries sector includes emissions from fuel combustion in point sources

in energy and heat production. According to 2006 IPCC Guidelines, emissions from autoproducers (undertakings which generate electricity/heat wholly or partly for their own use, as an activity that supports their primary activity) are assigned to the sector where they

were generated and not under CRF 1.A.1.

Emissions from combustion installations with NACE 2 codes 35.11 and 35.30 are reported in

CRF 1.A.1.a sector. There are no petroleum refineries in Latvia; therefore in CRF 1.A.1.b notation key „NO‖ is used. CRF 1.A.1 sector also includes the emissions from on-site use of fuel in the energy production facilities and emissions from manufacturing of solid fuels (peat

briquettes and charcoal production plants) – these emissions are reported under 1.A.1.c Manufacture of solid fuels and other energy industries sector.

In submission 2015, the CRF subsector 1.A.1. was split into subsectors which are in line with 2006 IPCC Guidelines/CRF Reporter structure. The GHG emissions were reported under following ones:

1. A.1. Energy industries:

1. A.1.a. Public electricity and heat production:

• 1.A.1.a.i Electricity generation; • 1.A.1.a.ii Combined heat and power generation;

• 1.A.1.a.iii Heat plants;

1. A.1.c. Manufacture of solid fuels and other energy industries:

• 1. A.1.c.i Manufacture of solid fuels.


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Table 3.13 Emissions from Energy industries (CRF 1.A.1) in 1990–2013 (Gg)

CO2 CH4 N2O

GHG (CO2,

CH4, N2O) NOx CO NMVOC SO2

Gg Gg CO2 eq. Gg

1990 6201.22 0.19 0.038 6217.15 10.54 2.61 0.22 36.28

1991 5692.55 0.17 0.033 5706.81 9.65 2.56 0.21 29.42

1992 4861.46 0.15 0.031 4874.39 8.34 2.09 0.17 26.77

1993 3939.64 0.14 0.030 3951.90 7.07 1.48 0.13 28.20

1994 3712.96 0.15 0.032 3726.19 6.92 1.28 0.13 32.15

1995 3391.71 0.12 0.026 3402.54 6.25 1.39 0.12 22.77

1996 3511.75 0.15 0.030 3524.56 6.54 1.32 0.13 28.54

1997 3275.72 0.19 0.032 3289.98 6.10 1.70 0.14 19.40

1998 3338.13 0.21 0.035 3354.03 6.11 1.75 0.15 20.33

1999 2919.47 0.19 0.030 2933.20 5.24 1.61 0.13 15.58

2000 2474.11 0.15 0.024 2485.18 4.40 1.56 0.12 7.10

2001 2421.19 0.17 0.025 2432.76 4.37 1.75 0.13 5.14

2002 2317.01 0.18 0.026 2329.19 4.23 1.75 0.13 4.86

2003 2246.23 0.20 0.028 2259.58 4.15 1.86 0.14 3.52

2004 2056.91 0.20 0.026 2069.73 3.78 1.78 0.13 2.10

2005 2047.02 0.17 0.023 2058.12 4.05 1.73 0.12 2.20

2006 2073.74 0.19 0.025 2085.85 3.86 1.85 0.13 1.23

2007 1944.72 0.19 0.024 1956.65 4.50 1.74 0.12 1.25

2008 1917.50 0.18 0.024 1929.12 3.43 1.73 0.12 0.75

2009 1866.76 0.18 0.024 1878.48 3.29 1.68 0.12 0.75

2010 2249.56 0.20 0.027 2262.58 3.54 2.02 0.14 0.78

2011 2071.47 0.19 0.025 2083.53 3.14 1.87 0.13 0.35

2012 1855.35 0.22 0.029 1869.28 3.05 1.85 0.13 0.35

2013 1918.68 0.32 0.043 1939.40 3.51 2.25 0.16 0.25

CO2 emissions from CRF 1.A.1 sector have a decreasing trend with a few fluctuations from which the most recent is in 2010 (Table 3.13). Since 1990, CO2 emissions have decreased by 69.1% (biomass emissions excluded). In the beginning of 90-ties the decrease of CO2

emissions is explained with economic crisis caused by changes of political and social situation in the country when national economy was completely reorganized. Decrease in the

end of 90-ties is explained with economic crisis in Russian Federation with whom Latvia has close economic collaboration. Although heat and electricity production for population use were influenced by 2008-2009 crisis in national economy in smaller level than industrial

production the emissions were decreasing as population was using less electricity and residential sector switched from central district heating to individual heating. Also, the

continued decrease of emissions can be explained with higher standards of physical characterization of fuels and fuel switching to the fuels with lower costs and emissions – natural gas and biomass. In recent years, an increase of CO2 emissions in 2010 can be

explained with extremely cold winter, and the decrease in 2011 – with much warmer one, which remarkably influenced the amounts of fuel used for heating. Since 2010 up to year

2013, the emissions of CO2 have decreased by 14.7%.

Nevertheless, for CH4 and N2O emissions there can be seen an increase in recent years, starting from 2011, due to increased use of liquid solid and biomass fuel consumption. Since


100

2011 up to year 2013 the increase in CH4 and N2O emissions was 71.2% and 72.4%,

respectively. If compared with decreasing CO2 emissions, the increase in CH4 and N2O emissions is because of biomass use – as it is considered as CO2 neutral, it does not take place in CO2 balance, however, it is accounted in CH4 and N2O emissions.

Indirect GHG emissions from CRF 1.A.1 Energy Industries were estimated as well. SO2 had the biggest decrease by 99.3% in 1990–2013. It can be explained with fuel switching from

coal, peat and heavy fuel oils to natural gas and biomass from what sulphur dioxide emissions are not emitted. Also a strict national legislation was approved to improve the quality of used liquid fuels in country. NOx emissions have also decreased by 66.7% in 1990-2013, NMVOC

emissions – by 25%, and CO emissions – by 14.7%. The decrease can also be explained with fuel switch from solid ones to natural gas and biomass, which have lower emission factors.


2006 IPCC Guidelines’ Tier 2 method was used to estimate CO2 emissions from fuel

combustion as country specific parameters were used to estimate CO2 emission factor. However, for some fuels there are no country-specific emission factors, therefore 2006 IPCC Tier 1 method using default emission factors was used. 2006 IPCC Guidelines’ Tier 1 method

was used to calculate CH4 and N2O emissions from the CRF 1.A.1 sector.

As sludge gas consists approximately 35-44% of non-combustible components such as CO2

sulphur and others and 56-65% of sludge gas is combustible, methane emissions from biogas were calculated only by taking into account the methane part of biogas. It means that under the biogas fuel the combustion of methane is reported. As methane is obtained from sludge it

is considered as biomass combustion, hence CO2 neutral. Therefore Tier 2 method from 2006 IPCC Guidelines were used to calculate CO2 emissions from methane obtained from sludge

gas as plant specific parameters were used to estimate CO2 emissions from methane obtained from sludge gas.

Calculation of all emissions from fuel combustion is done with Excel databases developed by

the experts from LEGMC. The general method for emission data preparation was used:

qBEFEm

where:

Em – total emissions (Gg)

EF – estimated or default emission factor (t/TJ)

Bq – amount of fuel in thermal units (TJ)

NOx and SO2 emission data of 2005-2013 from combined heat and power plants as well as heat production only plants are taken from database ―2-AIR‖ where enterprises that do any pollution activity and have A, B or C category pollution permits report their emission data,

therefore these data are plant specific. Other indirect GHGs (CO, NMVOC) are calculated using Tier 1 method.

Emission factors and other parameters


National studies for country specific parameters and emission factors;

Data from only natural gas supplier company of natural gas physical characteristics;

2006 IPCC Guidelines;

EMEP/EEA 2013.

Country specific emission factors were used to calculate carbon dioxide (CO2) and sulphur dioxide (SO2) emissions.


101

CO2 emission factors

In 2004 a research by a local expert was made regarding CO2 emission factors for Latvia in concern with IPCC 1996 and used fuel type of physical characteristics. National expert assessed indices that influences CO2 emission factor and calculated CO2 emission factor in the

research ―Methodological instructions for CO2 emissions determination‖ (Annex 2). This research was made considering United Nations framework convention of climate change

recommendations of Intergovernmental Panel of Climate Change and physical characterizations of types of fuels used in Latvia.

Solid and liquid fuels and solid biomass

For calculating CO2 emission factors for liquid and solid fuels following equation15 was used:

where:

EFCO2 – emission factor for CO2 (kg CO2/MJ)

Qzd – net calorific value of fuel (MJ/kg (m

3))

Cd – carbon content in fuel (%)

MCO2 – molecule weight for CO2 – 44. 0098 (g/mcl)

MC – molecule weight for C – 12.011 (g/mcl)

For submission 2015 CO2 emission factors for certain types of fuels were recalculated according to CSB reported information of NCV changes in time period. NCV value was obtained from fuel consumers that have to report the used amount data and other fuel

information to CSB within annual reporting (Table 3.14).

Table 3.14 Characteristics of liquid solid and solid biomass fuels and estimated CO2 emission factors

Fuel type

Carbon

content in

working mass

of fuel (Cd) %

NCV (Qzd),

GJ/t Oxidation factor

Emission factor

with oxidation

factor (EF CO2),

t/TJ

Peat Wd=40% 29.07 10.05 0.98 103.8664

Motor gasoline (for

off-roads) 83.13

44 (1990-2002)

43.97 (2003-2013) 0.99

68.5347

68.5815

Diesel oil 86.68 42.49 0.99 74.0010

RFO 85.72 40.6 0.99 76.5881

Shale oil 82.82 39.35 0.99 76.3477

LPG 77.99 45.54 0.995 62.4366

Jet fuel 85.18 43.2 (1990-2002)

43.21 (2003-2013) 0.99

71.5252

71.5087

Other kerosene 85.17

43.2 (1990-2000)

43.21 (2004)

43.2 (2005-2013)

0.99 71.5168 (Qz

d 43.2)

71.5003 (Qzd 43.21)

Used oils 83.77 41.86 0.99 72.5930

Wood

Wd = 55% 20.11 6.7 0.98 107.7789

15

―Guidance manual for CO2 emission estimations (Developed in accordance with UNFCCC and IPCC recommendations and physical

characteristics of fuels used in Latvia)‖


102

For some fuels default CO2 emission factors from 2006 IPCC Guidelines, Volume 2, Chapter

2 Stationary combustion, Table 2.2, were taken due to unavailability of country specific data:

• coal – 94.6 Gg/PJ; • coke – 107 Gg/PJ;

• peat briquettes – 97.5 Gg/PJ; • biodiesel – 70.8 Gg/PJ;

• straws – 100 Gg/PJ; • waste oils – 73.3 Gg/PJ.

Natural gas

For calculating CO2 emission factor for natural gas following equation16 was used:

where:

EFCO2 – emission factor for CO2 (Gg/1000m3)


MCO2 – molecule weight for CO2 – 44.0098 (g/mcl)

Mc – molecule weight for C – 12.011 (g/mcl)

ρ – natural gas density – for transition from density to mass units (t/1000m3)

Data of carbon content and natural gas density for all years in 1990-2013 were obtained from only natural gas supplier JSC ―Latvijas Gāze‖ that collects/measures these data by themselves. NCV values to calculate data further in energy units were taken from CSB.

Table 3.15 Characteristics of natural gas and estimated CO2 emission factors

Carbon content in

working mass of fuel (Cd)

%

Oxidation factor

(p)

Natural gas density

(ρ)

t/1000m3

Emission factor with

oxidation factor

(EF CO2)

Gg/1000m3

1990 74.33 0.995 0.6867 1.8703

1991 74.33 0.995 0.6867 1.8703

1992 74.36 0.995 0.6923 1.8863

1993 74.15 0.995 0.6965 1.8924

1994 74.04 0.995 0.6914 1.8757

1995 74.26 0.995 0.6889 1.8745

1996 74.3 0.995 0.6859 1.8673

1997 74.39 0.995 0.6845 1.8658

1998 74.35 0.995 0.6857 1.8680

1999 74.31 0.995 0.6841 1.8627

2000 74.32 0.995 0.6879 1.8733

2001 74.36 0.995 0.6876 1.8735

2002 74.36 0.995 0.6858 1.8686

2003 74.38 0.995 0.6851 1.8672

2004 74.39 0.995 0.6839 1.8641

2005 74.4 0.995 0.6835 1.8633

16

―Guidance manual for CO2 emission estimations (Developed in accordance with UNFCCC and IPCC recommendations and physical

characteristics of fuels used in Latvia)‖


103

Carbon content in

working mass of fuel (Cd)

%

Oxidation factor

(p)

Natural gas density

(ρ)

t/1000m3

Emission factor with

oxidation factor

(EF CO2)

Gg/1000m3

2006 74.39 0.995 0.6838 1.8639

2007 74.38 0.995 0.6828 1.8609

2008 74.38 0.995 0.6833 1.8622

2009 74.37 0.995 0.686 1.8694

2010 74.42 0.995 0.6855 1.8692

2011 74.43 0.995 0.6856 1.8698

2012 74.31 0.995 0.6855 1.8665

2013 74.34 0.995 0.6884 1.8751

Landfill gas

There are five landfills in Latvia that are collecting biogas from landfills – one landfill is collecting and combusting biogas since 2002 second from 2003 third from 2004. Fourth landfill started to combust biogas with energy recovery only in 2008, but fifth – from 2013.

As landfills were not able to provide information of carbon content percentage in working mass of fuel constant methane value was used instead and was estimated basing on moll mass

of components. Following equation17 was used to calculate this methane number:

100)(

HC

Cd

MM

MC

where:


Mc – molecule weight for C – 12.011 (g/mcl)

MH – H molecule weight (1.008 g/mcl)

100 – estimat ion of percentage

For calculation of CO2 emission factor of methane obtained from landfill gas, an equation basically the same as for natural gas was used, although methane carbon content, density and NCV from scientific literature was used18. The same assumption refers to other biogas.

where:



3))


MCO2 – molecule weight for CO2 – 44. 0098 (g/mcl)

MC – molecule weight for C – 12.011 (g/mcl)

17

―Guidance manual for CO2 emission estimations (Developed in accordance with UNFCCC and IPCC recommendations and physical characteristics of fuels used in Latvia)‖

18 http://dolgikh.com/index/0-31

http://dolgikh.com/index/0-31


104

Table 3.16 Characteristics of methane obtained from landfill gas and estimated CO2 emission factors

Amount of

methane in

landfill gas (% )

Default carbon

content in working

mass of methane

(Cd)

%

NCV of

methane

(Qzd)

TJ/1000m3

Oxidation

factor

(p)

Natural gas

density

(ρ)

t/1000m3

Emission factor

with oxidation

factor

(EF CO2)

kg/GJ

50% 74.867543% 35.88 0.995 0.6687 50.870474

Sludge gas

The CO2 emission factor estimated below is estimated for pure methane that is obtained from

collected sludge gas.

As wastewater treatment plant was not able to provide the information of carbon content

percentage in working mass of fuel, a constant carbon content in methane was used estimated basing on moll mass of components. Following equation was used for calculations:

100)(

HC

Cd

MM

MC


Mc – molecule weight for C – 12011 (g/mcl)

MH – H molecule weight (1.008 g/mcl)

100 – estimat ion of percentage

For calculation of CO2 emission factor of methane obtained from sludge gas the same equation as for natural gas was used.

NCV numbers of methane obtained from sludge gas that is combusted with energy recovery for all years are obtained from wastewater treatment plant (Table 3.17).

Table 3.17 Characteristics of methane obtained from sludge gas and estimated CO2 emission factors

Amount of

methane in

sludge gas (% )

Default carbon content

in working mass of

methane

(Cd)

%

NCV of

methane

(Qzd)

TJ/1000m3

Oxidation

factor

(p)

Natural gas

density

(ρ)

t/1000m3

Emission factor

with oxidation

factor

(EF CO2)

kg/GJ

56-65% 74.867543% 35.88 0.995 0.6687 50.870474

SO2 emission factors

SO2 emissions factors were calculated by equation taken from EMEP/EEA 2013 and were

calculated by national expert considering physical characterizations of types of fuels used in Latvia and national and international legislation. Percentage amount of sulphur content in used fuels is taken from national database ―2-AIR‖ where polluters report the sulphur content

data for certain types of fuels (Annex 2).

Emission factors for SO2 are calculated by using following equation:

100

100

100

10010

1

1002 6 nr

Q

s

where:

EF – emission Factor (kg/TJ) 2 – SO2 / S (kg/kg) s – sulphur content in fuel (%)


105

r – retention of sulphur in ash (%) Q – net calorific value (TJ/kt) 10

6 – (unit) conversion factor

n – efficiency of abatement technology and/or reduction efficiency (%).

Other emission factors

The default CH4 and N2O emission factors used in estimation of emission were taken from

2006 IPCC Guidelines, Volume 2, Chapter 2 Stationary combustion, Table 2.2.

Emission factors for NOx, NMVOC and CO were taken from EMEP/EEA 2013, 1.A.1 Energy industries, Table 3-2 (coal, coke), Table 3-3 (peat, peat briquettes), Table 3-4 (natural gas,

LPG, sludge gas), Table 3-5 (RFO), Table 3-6 (liquid fuels, including biodiesel). Emission factors used for 2015 Submission are listed in Table 3.18 below.

Table 3.18 CH4, N2O, NOx, CO, NMVOC emission factors used in CRF 1.A.1. Energy Industries (Gg/PJ)

CH4 N2O NOx NMVOC CO

Diesel o il 0.003 0.0006 0.065 0.0008 0.0162

RFO 0.003 0.0006 0.142 0.0023 0.0151

LPG 0.001 0.0001 0.089 0.0026 0.039

Jet fuel 0.003 0.0006 0.065 0.0008 0.0162

Other kerosene 0.003 0.0006 0.065 0.0008 0.0162

Other liquid 0.003 0.0006 0.065 0.0008 0.0162

Shale oil 0.003 0.0006 0.065 0.0008 0.0162

Coal 0.001 0.0015 0.209 0.001 0.0087

Coke 0.001 0.0015 0.209 0.001 0.0087

Peat briquettes 0.001 0.0015 0.247 0.0014 0.0087

Peat 0.001 0.0015 0.247 0.0014 0.0087

Natural gas 0.001 0.0001 0.089 0.0026 0.039

Wood 0.030 0.0040 0.081 0.00731 0.09

CH4 from sludge gas 0.001 0.0001 0.089 0.0026 0.039

Landfill gas 0.001 0.0001 0.089 0.0026 0.039

Other biogas 0.001 0.0001 0.089 0.0026 0.039

Biodiesel 0.003 0.0006 0.065 0.0008 0.0162

Straws 0.030 0.0040 0.081 0.00731 0.09

Waste oils 0.030 0.0040 0.065 0.0008 0.0162

Activity data

Mainly emissions from fuel combustion are calculated using fuel consumption data from the

national Energy Balance, prepared by CSB. In previous submissions the Annual Questionnaires sent to EUROSTAT were used, but after an internal third party review in 2014 an expert’s conclusion was to use Energy Balance, if possible, to ensure more precise data. As

in the EUROSTAT tables fuel consumption mainly is in natural units (kt, millions m3) therefore net calorific values provided by CSB were used to calculate fuel consumption into

terajoules. However, there were differences between Annual Questionnaires’ and Energy Balance data due to rounding and conversion of units, therefore it was decided to use Energy Balance data with accuracy up to 1 TJ (instead of Annual Questionnaire accuracy 1 kt). Data

on fuel consumption in CRF 1.A.1 sector are presented in Annex 3, Table 1.

The CSB data collection system is based on detailed compulsory survey 2-EK (annual). Form

2-EK ―Survey on acquisition and consumption of energy resources‖ is collected from about 5000 enterprises and organizations (with all kind of economic activity) that are included in the lists of suppliers of statistical information.


106

Approximately 5000 respondents – all enterprises of the local governments regardless their

number of employees and other enterprises employing 80 and more persons – were surveyed. Enterprises and organizations employing less than 80 persons were surveyed by the random sampling and afterwards the acquired results were extrapolated. 2–EK represents the basic

tool for creating energy balances at a country level.

The amounts of methane from landfill gas combusted are taken from Waste expert, therefore

are consistent with numbers of recovered amounts of landfill gas in Waste sector. The amounts of methane from sludge gas combusted are consistent with numbers of gas, recovered from Wastewater handling sector.

In Figure 3.13 there can be seen fuel consumption by fuel types in 1990-2013 in Energy Industries sector. The largest amounts of fuel types consumed are gaseous fuels in the whole

time series and liquid fuels in the beginning of 1990-ties. The amounts of biomass consumed are slightly increasing, while the consumption of solid fuels and peat has sharply decreased.

Figure 3.13 Fuel consumption in Energy Industries (CRF 1.A.1) for 1990-2013 (PJ)

The biggest decrease in time period 1990–2013 for the two sub-sectors of 1.A.1 Energy industries sector was for liquid fuel due to significant decrease of fuel consumption in 1.A.1.a

subsector by 98.8%. It is explained with fuel switching processes when liquid fuels were switched to cheaper fuels. Also a stronger legislation contributed fue l switch to the type of fuels with lower level of emissions. It also explains why consumption of solid fuels

decreased. However, since 2007, the consumption of solid fuels has increased that is explained with the increase of coal consumption in CRF 1.A.1.a subsector by 304% in 2006-

2013. The increase of solid fuel consumption was promoted by increase of oil price in world when coal combustion became cheaper than combustion of residual fuel oil, diesel oil and natural gas.

Consumption of biomass fuel has increased by 2.4 times in 1990–2013. Solid biomass is a local fuel and has lower costs therefore liquid and solid fuels were replaced with biomass and

natural gas.


107

Figure 3.14 Fuel consumption in Main activi ty electricity and heat production (CRF 1.A.1.a) and average

temperature in Latvia

As it can be seen in Figure 3.14 the fuel consumption in 1.A.1.a sector can be related with the heating degree days with an exception of 1990-ties when Soviet Union collapsed and

reorganizations took place in Latvia. However, for time period from 1997 to 2002 there can be seen that in years where energy consumption reduced, the HDD were also reduced. Years

2006-2008 had quite high average temperature therefore the fuel consumption for combined heat plants and heat plants for heat production decreased as there was not any need of high heat production amounts, but in 2009-2010 the average temperature was lower and the use of

fuel consumption increased. However, in year 2011 the fuel consumption decreased because of a relatively warm winter, and in year 2012 the consumption of fuel continued to decrease

despite the fall of average temperature, which could be explained with better heat insulation in houses therefore less heat needed to be produced. In 2013 the fuel consumption increased, however, HDD were less than in 2012.

3.2.4.3 Uncertainties and time series consistency

Uncertainty in activity data of fuel combustion in 1.A.1 sector is ±2% in 2013. CSB gives

approximately 2% statistical sample error for statistical data. According to CSB, as data are obtained using information given by respondents, this number is a variation coefficient which

characterizes selection of respondents. Total variation coefficient for energy balance is within 2-3%. In Latvia all fossil fuels (oil, natural gas and coal) are imported and import and export statistics are fairly accurate.

Uncertainty of activity data for solid biomass combustion was assigned as 5% because biomass activity data were collected by CSB with questionnaires sent by enterprises

consumed biomass. Also, according to 2006 IPCC Guidelines, Volume 2, Chapter 1, pg. 1.19, biomass data are generally more uncertain than other data in national energy statistics, because a large fraction of the biomass may be part of the informal economy, and the trade in

these type of fuels is frequently not registered in the national energy statistics and balances. That was a reason for higher uncertainty for biomass than for other fuel types. Uncertainty of

sludge gas stationary combusted in enterprises covered by 1.A.1 Energy Industries sector was assumed rather low – 2% because the combusted fuel amount is obtained directly from wastewater treatment plant that has precise measurement equip ment for accounting of

combusted fuel. Still the methane percentage amount in combusted sludge gas is given


108

approximately, therefore final uncertainty of combusted sludge gas is assumed as 5%. The

same applies to landfill gas.

CO2 emission factor was estimated according physical characterization of used fuels in country basing on average NCV reported by fuel consumers and carbon content, hence the

uncertainty for liquid fuels was assigned as quite low – about 10%. As emission factors for solid fuels were taken from 2006 IPCC Guidelines, the uncertainty was assumed 20%.

Emission factor uncertainty for peat and peat briquettes was assumed 15% because peat emission factor is country specific, but emission factor for peat briquettes is taken from 2006 IPCC Guidelines. CO2 emission factor for natural gas was assumed rather low – as 5%

because annual plant specific fuel data is used to estimate emission factor.

CH4 and N2O emission factors used in estimation of emissions were taken according to 2006

IPCC Guidelines, Volume 2, Chapter 2 Stationary combustion, Table 2.12., which provides the range of default values for uncertainties. The uncertainty both for CH4 and N2O EFs was assigned as uncertainties used in previous submissions – 50%.

Time series of the estimated emissions are consistent and complete because the same methodology, emission factors and data sources are used for sectors for all years in time

series. Emissions from all sectors are estimated or reported as not occurring / not applicable, therefore there are no ―not estimated‖ sectors.


All documentation and information received for inventory purposes are archived in FTP folder. All findings are documented by using check- lists, available on Regulations of the

Cabinet of Ministers No. 217 adopted on 27 March 2012 ―The National Inventory System of Greenhouse Gas Emission Units‖.

Activity data verification

All sources of energy data are presented in the corresponding NIR chapter (3.2.4.2 Methodological issues) as well as disaggregated data at the finest level possible are presented

in the corresponding Annex. Data completeness has been explained in the previous subchapter.

Activity data have been checked at the data provider – Central Statistical Bureau, which has its own internal QA/QC procedures based on mathematic model and analysis to avoid logic mistakes. When activity data have been received, the sectoral expert responsible for the

emission estimation and reporting are comparing all data changes with the previous inventory, and all changes are explained in the corresponding subchapter. All fluctuations or changes in

NCVs are double checked and agreed with CSB.

All activity data used in Sectoral Approach are also compared with activity data used in Reference Approach estimations. All significant differences (±5%) are explained in the

corresponding subchapter.

Emission factor verification

For country-specific CO2 emission factors, the sources of the calorific values, carbon content and oxidation factors, as well as these values are provided in 3.2.4.2Methodological issues.

Country specific CO2 values for year are compared with default ones available on 2006 IPCC

Guidelines, Volume 2, Chapter 2 Stationary combustion, Table 2.2. Whether country specific CO2 emission factor is or is not in the confidence interval, can be seen in Table 3.19.


109

Table 3.19 Comparison of country specific and 2006 IPCC default CO2 emission factor values (Gg/PJ)

Lower CS Upper LV ETS

Gasoline 67.50 71.18 73.00

Diesel oil 72.60 74.00 74.80 74.75

RFO 75.50 76.59 78.80 77.36

LPG 61.60 62.44 65.60 62.75

Jet fuel 69.70 71.51 74.40

Other kerosene 70.80 71.50 73.70

Other liquid 72.20 72.59 74.40

Shale oil 67.80 76.35 79.20 74.75

Peat 100.00 103.87 108.00 105.99

Natural gas 54.30 54.23 58.30 55.44

Wood 95.00 107.78 132.00

Sludge gas 46.20 50.87 66.00

Landfill gas 46.20 50.87 66.00

Other biogas 46.20 50.87 66.00

Only natural gas country specific CO2 emission factor is outside of confidence interval given by 2006 IPCC Guidelines. Main reasons are different carbon content in fuel, as well as different NCVs.

Emission verification:

To verify the CO2 emissions, logical mistakes are checked by checking the time series of the

activity data, emission factors and emissions consistency to display all significant and illogical changes in the activity data and emissions. The emissions for indirect GHGs in the database are cross-checked with emissions reported within Convention on Long-range

Transboundary Air Pollution (CLRTAP) for verification purposes.

CO2 emissions are compared with emissions in Reference Approach estimations, and all

significant differences (±5%) are explained in the corresponding subchapter.

3.2.4.5 Source-specific planned improvements

No improvements are planned to be done until the next submission.

3.2.5 Manufacturing Industries and Construction (CRF 1.A.2)


CRF 1.A.2 Manufacturing industries and construction sector includes emissions from fuel combustion in combustion installations for industrial production including emissions from off–road. CRF 1.A.2 sector also includes the emissions from on-site use of fuel in the

industrial production facilities (autoproducers) – these emissions are reported under particular sub-sectors of CRF 1.A.2 according to 2006 IPCC Guidelines.

According to 2006 IPCC Guidelines, Volume 2, Chapter 2 Stationary combustion, Table 2.1., emissions arising from off- road and other mobile machinery in industry should be broken out as a separate subcategory. These emissions are calculated together from all gasoline use in

particular subsectors (Chemicals, Wood and wood products, Construction) within CRF 1.A.2. It also ensures the consistency between CLRTAP and UNFCCC data.


110

In Submission 2015, the CRF subsector CRF 1.A.2 Manufacturing industries was split into

subsectors which are in line with 2006 IPCC Guidelines/CRF Reporter structure:

1.A.2.a Iron and steel;

1.A.2.b Non-ferrous metals;

1.A.2.c Chemicals;

1.A.2.d Pulp, paper and print;

1.A.2.e Food processing, beverages and tobacco;

1.A.2.f Non-metallic minerals;

1.A.2.g Other:

• 1.A.2.g.i Manufacturing of machinery; • 1.A.2.g.ii Manufacturing of transport equipment;

• 1.A.2.g.iii Mining (excluding fuels) and quarrying; • 1.A.2.g.iv Wood and wood products; • 1.A.2.g.v Construction;

• 1.A.2.g.vi Textile and leather; • 1.A.2.g.vii Off-road vehicles and other machinery;

• 1.A.2.g.viii Other.

Table 3.20 Emissions from Manufacturing industries and construction (CRF 1.A.2) in 1990–2013 (Gg)

CO2 CH4 N2O

Aggregate GHGs

(CO2, CH4, N2O) NOx CO NMVOC SO2

Gg Gg CO2 eq. Gg

1990 3889.62 0.22 0.030 3903.90 17.59 19.21 3.14 24.45

1991 2935.87 0.12 0.019 2944.40 12.30 6.96 1.69 15.21

1992 2492.18 0.11 0.017 2499.80 10.50 6.74 1.52 14.09

1993 2159.26 0.13 0.021 2168.98 10.05 7.78 1.77 14.56

1994 1960.11 0.13 0.022 1969.95 9.62 6.29 1.63 15.84

1995 1909.08 0.14 0.022 1919.02 9.64 4.26 1.52 15.19

1996 1865.84 0.15 0.023 1876.30 9.38 5.78 1.72 14.71

1997 1818.00 0.15 0.023 1828.40 9.20 5.04 1.65 14.22

1998 1589.62 0.15 0.023 1600.11 7.70 5.04 1.71 10.93

1999 1441.60 0.14 0.022 1451.63 6.87 4.20 1.59 8.89

2000 1177.84 0.12 0.018 1186.11 4.92 3.53 1.38 4.43

2001 1078.32 0.16 0.022 1089.00 3.82 4.07 1.74 2.26

2002 1125.46 0.16 0.022 1135.98 3.67 4.21 1.68 1.65

2003 1132.98 0.15 0.020 1142.68 3.72 3.67 1.59 1.31

2004 1149.31 0.19 0.026 1161.78 3.75 5.20 2.10 0.81

2005 1153.03 0.22 0.031 1167.80 3.51 6.28 2.36 1.06

2006 1223.89 0.24 0.033 1239.63 3.95 7.21 2.66 1.18

2007 1216.41 0.20 0.029 1230.25 3.79 7.10 2.37 1.19

2008 1112.86 0.22 0.031 1127.57 3.41 7.30 2.45 0.78

2009 887.11 0.29 0.040 906.22 3.24 7.51 3.09 0.56

2010 1078.96 0.35 0.049 1102.35 3.83 8.68 3.58 0.83

2011 878.52 0.41 0.058 905.91 3.18 9.63 4.02 0.75

2012 931.37 0.47 0.066 962.65 3.51 10.65 4.52 0.70

2013 761.10 0.48 0.066 792.96 3.21 10.17 4.67 0.47


111

Emissions from CRF 1.A.2 significantly decreased in 1990 to 2001, which can be explained

with recession of Soviet Union and following reformations and reorganizations within Latvia after that. Since 2001, the emissions started to increase until 2006, because of development in national economy and industry, as well as growing demand of industrial production and

increasing welfare of inhabitants (Table 3.20). Growth in GHG emissions in the given time period were caused by increased amounts of coal and natural gas consumed. Decrease of

emissions in 2006-2008 were influenced by the features of national economy development when in-country industrial production already started to diminish due to increasing costs of the production and dominance of imported products. Crisis in national economy in the second

part of 2008 also caused a significant decrease in total emissions. The increasing amounts of solid biomass consumption also caused a drop in CO2 emissions. The crisis in national

economy caused by global financial crisis in 2008-2009 influenced quite significant decrease of GHG emissions by 20%. The crisis and development of EU ETS influenced biomass consumption for 2008-2009 in 1.A.2 sector – its amounts were growing, while amounts of

almost all other fuels decreased. In 2010-2013 the emissions are fluctuating due to reconstructions in 2011-2012 in the largest steel producer ―Liepājas Metalurgs‖. As it

replaced its furnace to electric one, the emissions decreased, however, in 2013 due to several reasons it initiated bankruptcy, therefore the amounts of production decreased significantly.

Due to the essential increase of biomass consumption non-CO2 emissions increased in 2009-

2013: CH4 emissions increased by 69%, while N2O emissions increased by 65.4%.

Also indirect GHG emissions from CRF 1.A.2 sector were estimated. In this sector almost all

indirect emissions have decreased: NOx emissions have decreased by 81.7%, CO emissions – by 47.1%, and SO2 emissions have a decrease by 98.1% in 1990–2013. The decrease in emissions is explained with fuel switching to natural gas and biomass from what sulphur

dioxide emissions are not emitted, and there are less NOx and CO emissions from these fuels comparing with solid and liquid fuels. However, NMVOC emissions have an increasing trend

and have increased by 48.6% since 1990 due to very high emission factors for biomass comparing with other fuels.


Methods


combustion as country specific parameters were used to estimate CO2 emission factor. However, for some fuels there are no country-specific emission factors, therefore 2006 IPCC

Tier 1 method using default emission factors was used. 2006 IPCC Guidelines’ Tier 1 method was used to calculate CH4 and N2O emissions from the CRF 1.A.2 sector.


the experts from LEGMC.

The general method for emission data preparation was used:

qBEFEm

where:







112



EU ETS reports (for used tires and municipal waste);

IPCC 2006 Guidelines;

EMEP/EEA 2013.

Country specific emission factors were used to calculate carbon dioxide (CO2) and sulphur dioxide (SO2) emissions.


CO2 emission factors for CRF 1.A.2 Manufacturing Industries and Construction sector are

estimated with the same equations and using the same method as for CRF 1.A.1 Energy industries sector with the exception for industrial waste and municipal waste that are not combusted in CRF 1.A.1 sector.

For some fuels default CO2 emission factors from 2006 IPCC Guidelines, Volume 2, Chapter 2 Stationary combustion, Table 2.3, were taken due to unavailability of country specific data:

• other liquid fuels – 73.3 Gg/PJ; • coal – 94.6 Gg/PJ; • coke – 107 Gg/PJ;

• anthracite – 98.3 Gg/PJ; • oil shale – 107 Gg/PJ;

• petroleum coke – 97.5 Gg/PJ • peat briquettes – 97.5 Gg/PJ; • biodiesel – 70.8 Gg/PJ;

• straws – 100 Gg/PJ; • waste oils – 73.3 Gg/PJ.

Municipal waste

CO2 emission factors of municipal wastes combusted in cement production plants are taken from plant’s annual GHG report within EU ETS for 2008-2013. This CO2 emission factors

are estimated at the plant by using plant specific data about combustion installation as well as net calorific value and carbon content measured and obtained in the plant laboratory. 2006

IPCC Guidelines state to separate non-biomass and biomass parts of the municipal wastes. It has been done in Submission 2015 as follows: CO2 emissions to be reported to EU ETS have been taken from 2008-2012 for non-biomass part, because for EU ETS only non-biomass CO2

emissions have to be reported. The emission factors given in the reports are for whole emissions and it is possible to calculate the emission factor for non-biomass fraction. The

emission factors for total CO2 emissions and for non-biomass fraction are provided in Table 3.21.

Table 3.21 CO2 emission factors, carbon content and NCV for municipal wastes by waste types (Gg/PJ)

2008 2009 2010 2011 2012 2013

Total CO2 EF, Gg/PJ

Ecofuel 1 85.19 82.81

Ecofuel 2 120.95 82.69 113.22 95.24 85.98

Fossil CO2 EF, Gg/PJ

Ecofuel 1 44.16 43.03

Ecofuel 2 71.01 35.11 27.99 32.42 38.69

C content, %

Ecofuel 1 54.4 53.1

Ecofuel 2 54.4 49.1 54.0 54.0 41.3


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2008 2009 2010 2011 2012 2013

NCV, TJ/kt

Ecofuel 1 22.779 23.514

Ecofuel 2 17.416 19.594 18.232 16.852 17.615

Biomass content, %

Ecofuel 1 48.16 48.04

Ecofuel 2 58.70 57.54 75.28 65.96 41.33

For estimating biomass emissions the following equation was used:

where:

Ebiomass – CO2 emissions from b iomass fraction (Gg);

Etotal – total CO2 emissions (Gg);

Enon-biomass - CO2 emissions from biomass fraction (Gg);

The calculated results for total CO2 emissions from municipal wastes, as well as from biomass and non-biomass fraction can be found in Table 3.22.

Table 3.22 CO2 emissions from municipal waste non-biomass and biomass fractions by waste types in

2008-2013

2008 2009 2010 2011 2012 2013

Fossil CO2 emissions, Mg

Ecofuel 1 6856 2284.54

Ecofuel 2

304.63 26440 37606 54948 60808.06

Biomass CO2 emissions, Mg

Ecofuel 1 6369.748 2112.17

Ecofuel 2

214.25 35835.33 114499.41 106457.61 74320.97

Total CO2 emissions, Mg

Ecofuel 1 13225.75 4396.71

Ecofuel 2

518.88 62275.33 152105.41 161405.61 135129.03

Industrial waste

Emission factors for CO2 emission estimation for industrial waste – used tires, neutralised

polluted soil, waste wood, fluffy tyre, wood processing residues and shredded rubber – combusted in CRF 1.A.2.f Non-metallic minerals (cement production) for years 1999–2013 are taken from GHG emission reports that plant submitted under EU ETS (Table 3.23). These

CO2 emission factors are estimated at the plant by using plant specific data about combustion installation as well as net calorific value and carbon content measured and obtained in the

plant laboratory. Also for this fuel type biomass and non-biomass emissions have been calculated, as this fuel contains biomass.

Table 3.23 CO2 emission factors, carbon content and NCV for industrial waste

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Total CO2 EF, Gg/PJ

Used tyres 82.756 82.756 82.756 82.756 82.756 82.756 79.44 79.44 79.44 85 85 85 85 85 85

NPS 79.43 80.602

Waste wood 117.6


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1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Fluffy tyres 81.13 81.13 87.01

Wood processing residues

135.3 130.35

Shredded

rubber 81.13

Fossil CO2 EF, Gg/PJ

Used tyres 60.9 60.9 60.9 60.9 60.9 60.9 60.9 60.9 60.9 60.9 60.9 60.9 60.9 60.9 60.9

NPS

Waste wood 15.88

Fluffy tyres 27.01 17.93 30.45

Wood processing

residues

37.58 41.47

Shredded rubber

41.22

C content, %

Used tyres 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87

NPS 30.52 32.99

Waste wood 42.30

Fluffy tyres 63.10 63.10 68.76

Wood

processing residues

20.11 20.11

Shredded rubber

75.10

NCV (TJ/kt)

Used tyres 26.21 26.21 26.21 26.21 26.21 26.21 26.21 26.21 26.21 26.21 26.21 26.21 26.21 26.21 26.21

NPS 14.3 14.999

Waste wood 13.181

Fluffy tyres 28.5 42.937 28.961

Wood processing residues

12.569 12.114

Shredded rubber

31.315

Biomass content, %

Used tyres 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28

NPS 17 30

Waste wood 87

Fluffy tyres 67 78 65

Wood processing

residues

72 68

Shredded rubber

49

For estimating biomass emissions, the above mentioned equation for municipal waste was

used.

Since 2005 the cement production plant is participating in EU Emission trading scheme therefore estimated CO2 EF is verified by accredited verifiers and approved by Regional

Environmental Board.

SO2 emission factors

SO2 emission factors for all fuels, except industrial and municipal wastes, in CRF 1.A.2 Manufacturing Industries and Construction sector are estimated with the same equations and using the same method as for CRF 1.A.1 Energy industries sector.

For industrial and municipal wastes SO2 emission factors are taken from EMEP/EEA 2013, Chapter 5.C.1.b, Table 3-1 (0.0047 kg/Mg) and Chapter 5.C.1.a, Table 3-1 (0.087 kg/Mg).


List of other emission factors can be seen in Table 3.24.

The default CH4 and N2O emission factors are taken from 2006 IPCC Guidelines, Volume 2,

Chapter 2 Stationary combustion, Table 2.3. Gasoline emission factors are used for CH4 and


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N2O emission estimation from off-roads (2006 IPCC Guidelines, Volume 2, Chapter 3 Mobile

combustion, Table 3.3.1.). As there is no information about distribution between 2-stroke and 4-stroke engines, it was assumed that 25% of consumed gasoline is combusted in 2-stroke engines, while 75% - in 4-stroke engines. Such assumption has been made, based on Danish

data which are presented in EMEP/EEA 2013 for air pollutants’ calculations.

NOx, CO and NMVOC emission factors used in estimation of emission were taken from

EMEP/EEA 2013, Chapter 1.A.2, Tables 3-2 to 3-5, with an exception of oil shale which has been taken from Estonian inventory as country specific. For industrial wastes and municipal wastes NOx, CO and NMVOC emission factors are taken from EMEP/EEA 2013, Chapter

5.C.1.b, Table 3-1 and Chapter 5.C.1.a, Table 3-1 (Table 3.24).

Table 3.24 CH4, N2O, NOx, NMVOC, CO emission factors (Gg/PJ 19)

CH4 N2O NOx NMVOC CO

Gasoline 2-stroke 0.130 0.0004 2.765 242.197 620.793

4-stroke 0.050 0.0020 7.117 17.602 770.368

Diesel oil 0.003 0.0006 0.513 0.030 0.070

RFO 0.003 0.0006 0.513 0.030 0.070

LPG 0.001 0.0001 0.074 0.023 0.029

Jet fuel 0.003 0.0006 0.513 0.030 0.070

Other kerosene 0.003 0.0006 0.513 0.030 0.070

Other liquid 0.003 0.0006 0.513 0.030 0.070

Petroleum coke 0.003 0.0006 0.513 0.030 0.070

Waste oils 0.030 0.0006 0.513 0.030 0.070

Shale oil 0.003 0.0006 0.513 0.030 0.070

Coal 0.000 0.0015 0.173 0.089 0.931

Coke 0.001 0.0015 0.173 0.089 0.931

Anthracite 0.001 0.0015 0.173 0.089 0.931

Oil shale 0.001 0.0015 0.110 0.050 0.087

Peat briquettes 0.001 0.0015 0.173 0.089 0.931

Peat 0.002 0.0015 0.173 0.089 0.931

Natural gas 0.001 0.0001 0.074 0.023 0.029

Wood 0.030 0.0040 0.091 0.300 0.570

Other biogas 0.001 0.0001 0.074 0.023 0.029

Biodiesel 0.003 0.0006 0.513 0.030 0.070

Industrial wastes (used tires) 0.030 0.0040 0.870 7.400 0.070

Municipal wastes 0.030 0.0040 1.071 0.0059 0.041

Waste oils 0.030 0.0040 0.513 0.030 0.070

Activity data

Mainly emissions from fuel combustion are calculated using fuel consumption data from the national Energy Balance, prepared by CSB. The data collection system for CRF 1.A.2 sector

is the same as for CRF 1.A.1 sector. Data on fuel consumption in 1.A.2 sector are presented in ANNEX A.3.1.

Autoproducers data prepared by CSP are taken into account into the calculation of the

emissions from CRF 1.A.2 sector according to 2006 IPCC Guidelines.

19

For indirect GHGs for gasoline, industrial and municipal waste – kg/Mg


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Only gasoline combustion is reported as off- roads in CRF 1.A.2 sector. It is sure that diesel

oil is also consumed as off- roads but for now it is not possible for CSB and LEGMC to divide the consumption between fuel combusted stationary and filled in technological vehicles. Due to that all diesel oil reported in the sector is estimated as combusted stationary.

Figure 3.15 Fuel consumption in Manufacturing industries and construction (CRF 1.A.2) for 1990-2013

(PJ)

The most of fuel types with an exception of biomass and other fossil fuels have decreased in 1990-2013 (Figure 3.15). Liquid fuels have the biggest decrease in time period by 91%. It is

explained with fuel switching processes when liquid fuels were replaced with other cheaper fuels. Also stronger legislation contributed fuel replacement to the type of fuels with lower

level of emissions. Decrease of natural gas reflects the total decrease of industrial production if comparing with 1990.

The consumption of solid fuels (mainly coal) has been decreasing in 1990-2004 with an

exception of 1993-1994, mainly due to increased use of coal in Construction and Textiles and Leather sectors. Solid fuels consumption was growing rapidly by 4.4 times since 2004 until

2008 because of the growth in national economy, and decreased in 2009 by 30% due to global crisis. However, starting from 2009, the consumption of solid fuels grew by 54% until year 2012. The increase of solid fuel consumption was promoted by the increase of oil price

overall the world when coal combustion was cheaper than combustion of residual fuel oil and diesel oil. The increase in Latvia is also explained with the development of mineral production sector – cement production – where coal is consumed. In 2013 there can be seen a

drop in solid fuel consumption – in Non-metallic minerals sector the consumption decreased by 32%, and in Iron and Steel sector by 76% because o f bankruptcy of the largest steel

producing company, which was mentioned in 3.2.5.2 Methodological issues.

After the crisis in the beginning of 90-ties natural gas consumption steadily increased with some small exceptions due to fuel replacement processes and development of national

economy.

Consumption of biomass fuel has increased very significantly – by 2.1 times in 1990–2013

with some fluctuations in 2000-2008. Lower costs of solid and liquid biomass, free and large availability of the fuel in-country as well as development of EU ETS were the main reasons for liquid and solid fuels’ replacement with biomass and natural gas.


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Consumption of used tires and municipal wastes in Mineral production (information taken

from „CEMEX‖, the only company which combusts used tires and municipal waste for energy purposes) reported as other fossil fuels had increased in 1999-2013 by 5.7 times and continue to increase year by year. Comparing with 2010, the consumption of wastes has

increased by 1.3 times in 2013. The increase was influenced by intensified cement production that was caused by increased demand of construction materials and sharp development of

construction sector. In other fossil fuels also used oils are reported, and the amounts of this fuel are fluctuating over years with a decreasing trend in recent years.


Uncertainty in activity data of fuel combustion in 1.A.2 sector is ±2% in 2013. CSB gives approximately 2% statistical sample error for statistical data. According to CSB, as data are

obtained using information given by respondents, this number is a variation coefficient which characterizes selection of respondents. Total variation coefficient for energy balance is within

2-3%. In Latvia all fossil fuels (oil, natural gas and coal) are imported and import and export statistics are fairly accurate.

Uncertainty of activity data for solid biomass combustion was assigned as 15% because

biomass activity data were collected by CSB with questionnaires sent by enterprises consumed biomass. Also, according to 2006 IPCC Guidelines, Volume 2, Chapter 1, pg. 1.19,

biomass data are generally more uncertain than other data in national energy statistics, because a large fraction of the biomass may be part of the informal economy, and the trade in these type of fuels is frequently not registered in the national energy statistics and balances.

Uncertainty of other fuels consumption – municipal and industrial wastes used in mineral production is assumed also low – 2% as the activity data is obtained from only one producer

within EU ETS therefore the data is verified by accredited verifier and Regional Environmental Board.

CO2 emission factor was estimated according physical characterization of used fuels in

country basing on average NCV reported by fuel consumers and carbon content so uncertainty for liquid fuels was assigned as quite low about 10%. The same uncertainty level was

assigned for peat. However, for combustion of solid fuels and other fossil fuels (waste oils) the uncertainty of CO2 emission factor was assigned higher to 20% because CO2 emission factor of anthracite, coal and coke was taken from 2006 IPCC Guidelines. CO2 emission

factor for natural gas was assumed rather low as 5% because plant specific fuel data is used to estimate emission factor.

CO2 emission factors for industrial and municipal waste are assumed as 2% as were determined in accredited laboratory of cement production company.

CH4 and N2O emission factor used in estimation of emissions was taken according to 2006

IPCC Guidelines, Volume 2, Chapter 2 Stationary combustion, Table 2.12., which provides the range of default values for uncertainties. The uncertainty both for CH4 and N2O EFs was

assigned as uncertainties used in previous submissions – 50%.

Time series of the estimated emissions are consistent and complete because the same methodology emission factors and data sources are used for sectors for all years in time series.

Emissions from all sectors are estimated or reported as not occurring/not applicable therefore there are no ―not estimated‖ sectors.


118







Activity data have been checked at the data provider – Central Statistical Bureau, which has

its own internal QA/QC procedures based on mathematic model and analysis to avoid logic mistakes. When activity data have been received, the sectoral expert responsible for the

emission estimation and reporting are comparing all data changes with the previous inventory, and all changes are explained in the corresponding subchapter. All fluctuations or changes in NCVs are double checked and agreed with CSB.




For country-specific CO2 emission factors, the sources of the calorific values, carbon content

and oxidation factors, as well as these values are provided in 3.2.4.2 Methodological issues.


Guidelines, Volume 2, Chapter 2 Stationary combustion, Table 2.2. Whether country specific CO2 emission factor is or is not in the confidence interval can be seen in Table 3.25.



Gasoline 67.50 71.18 73.00

Diesel oil 72.60 74.00 74.80 74.75

RFO 75.50 76.59 78.80 77.36

LPG 61.60 62.44 65.60 62.75

Jet fuel 69.70 71.51 74.40


Other liquid 72.20 72.59 74.40

Shale oil 67.80 76.35 79.20 74.75

Peat 100.00 103.87 108.00 105.99

Natural gas 54.30 54.23 58.30 55.44

Wood 95.00 107.78 132.00

Sludge gas 46.20 50.87 66.00

Landfill gas 46.20 50.87 66.00

Other biogas 46.20 50.87 66.00

Only natural gas country specific CO2 emission factor is outside of confidence interval given by 2006 IPCC Guidelines. Main reasons are different carbon content in fuel, as well as

different NCVs.


119


To verify the CO2 emissions, logical mistakes are checked by checking the time series of the activity data, emission factors and emissions consistency to display all significant and illogical changes in the activity data and emissions. The emissions for indirect GHGs in the

database are cross-checked with emissions reported within CLRTAP for verification purposes.

CO2 emissions are compared with emissions in Reference Approach estimations, and all significant differences (±5%) are explained in the corresponding subchapter.



3.2.6 Transport (CRF 1.A.3)


This section describes GHG emissions resulting from transport fuel combustion. In 2013, this source category was responsible for approximately 25.6% of total GHG emissions in Latvia,

reaching 2827 Gg (see Figure.3.16).

0

500

1000

1500

2000

2500

3000

3500

4000

19

90

19

95

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

Road transport Railways Navigation Civil aviation

Gg CO2 eq

Figure.3.16 GHG emissions development in transport 1990 – 2013

Emissions from Transport (CRF 1.A 3) include all domestic transport sectors: civil aviation, road transport, railways, domestic navigation and other mobile sources (which are not

included in other sectors).

In 2013, total GHG emissions in the transport sector, compared 1990 level, have decreased by 6.7 %. Peak of GHG emissions in transport sectors have been recognized in 2007 when

emissions exceeded 1990 level by 27%.

The road transport constitutes a convincing majority of the total GHG emissions in the

transport sector. In 2013, it gave 90.04 % of total emissions but the next largest emission source is railway – 8.83 % (see Figure 3.17).

CO2 emissions constitute nearly 97% of the total GHG emissions in the transport sector and

they are key sources in road transport and railway (Figure 3.18).


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Figure 3.17 GHG emissions in transport by sub-sectors in 2013

CO2

98,1%

CH4

0,2%

N2O

1,8%

Figure 3.18 GHG emissions in transport sector by gases in 2013

One of the critical factors influencing CO2 emission is the amount and type of the consumed

fuel. In 2013, total fuel consumption in the transport sector, compared to 2012 level, has increased by 1.3 %. In different subsectors various changes have taken place in 2013. In domestic civil aviation the fuel consumption has increased by more than 50%, whereas in the

railway transport it has decreased by 8.8 %. In the road transport the fuel consumption has increased by 1.9 %, but in domestic navigation it has increased approximately 2 times.

In total, road transport consumes about 91.1%, railway – about 7.9% and domestic civil aviation and domestic navigation – the remaining share of fuel.

Diesel oil is the major fuel type in the transport sector and it constitutes 69.2 %, and is

followed by gasoline – 22.6 %, but LPG constitutes 6.1% and biofuels (biodiesel and bioethanol) 2.0% of the total fuel consumption in the transport sector (see Figure 3.19). A

share of biofuels has decreased from 2.1% in year 2012 up to 2.0% in year 2013. It is in place a sharp increasing of LPG consumption in road transport. LPG consumption has increased by 27.4% in 2013 compared to 2012. Biofuel mainly is used in road transport but small portion is

consumed in rail transport as well.


121

Figure 3.19 Fuel consumption in trans port by fuel type (2013)

3.2.6.2 Civil aviation (CRF 1.A.3.a)

In Latvia the share of civil aviation flights, excluding international flights, is comparatively small. Therefore the fuel consumption and thus also the volume of GHG emissions is

comparably small, constituting mere 0.12% of GHG emissions from transport sector in year 2013 (Figure 3.20). In aviation emissions are calculated for aviation gasoline and jet kerosene. The aviation gasoline is mainly used by small-sized propeller planes but jet kerosene is used

by airplanes with turbofan and turbo prop engines.

Figure 3.20 GHG emissions in civil aviation (Gg CO2 eq)

In Latvia, there are four airports for commercial aviation, of which the largest is the Riga International Airport. Considering that local commercial flights are very dependent on the

strategy of local state owned airline company (airBaltic); the number of flights, fuel consumption and emission amount are quite unsteady over the years. As it can be seen, after the state owned (99.8% of shares) local airline company had aborted domestic commercial

flights in year 2009, fuel consumption had decreased dramatically in 2009. Today the main


122

activities in civil aviation relates with private flights. Economic recovery starting in Latvia in

2011 has fostered activity and fuel consumption in civil aviation. The results from the carried out additional analyses indicate no evidence of any certain trend in gasoline and jet fuel consumption.

Methods

When calculating emissions from civil aviation, two approaches have been applied. 2006

IPCC Guidelines Tier 1 method has been applied when estimating emissions from aviation gasoline for all gases. When calculating emissions from jet kerosene Latvia uses Tier 1 to estimate emissions of CO2 and SO2, and Tier 2 to estimate CH4, N2O and all other gases.

Using Tier 2 approach, emissions for LTO (landing/take off) and cruise are calculated individually. Separate emission factors are provided for LTO and Cruise activities. Prior to

the emission calculation, representative aircraft type was chosen, for which the fuel consumption and emission data exist in the EMEP database (EMEP/EEA emission inventory guidebook — 2013).

1. Total Emissions = LTO Emissions + Cruise Emissions

2. LTO Emissions = Number of LTOs * Emission Factor of LTOs

3. LTO Fuel Consumption = Number of LTOs * Fuel Consumption per LTO

4. Cruise Emissions = (Total Fuel Consumption – LTO Fuel Consumption) * EF Cruise

The summary of the latest key category assessment, methods and EF used is presented in

Table 3.26.

Table 3.26 Summary of source category description, CRF 1.A.3.a

CRF Gas Method EF All sources

estimated

1.A.3.a CO2 T1 D Yes

CH4 T1,T2 D Yes

N2O T1, T2 D Yes

T1 Tier 1; T2 Tier 2; D Default.

Activity data

The data about fuel consumption (see Table 3.27) in aviation is derived from the CSB. CSB has started to collect data as of year 2006. For the time period 1990 – 2005 the data for fuel

consumption is used from the study (―Evaluation of fuel consumption for domestic aviation and navigation‖, FEI, 2004). For 2004 onwards, the air flight statistics is provided by the Riga

and Liepaja airports.


123

Figure 3.21 Fuel consumption in domestic civil aviation (TJ)

Table 3.27 Fuel consumption in domestic civil aviation (TJ)

Jet kerosene Gasoline

1990 0.8 0.2

1995 5.4 1.1

2000 18.8 4.0

2001 21.4 4.6

2002 23.7 5.1

2003 25.5 5.4

2004 43.0 5.7

2005 38.0 6.0

2006 12.8 6.4

2007 14.8 8.4

2008 34.5 5.4

2009 2.3 1.7

2010 2.1 4.0

2011 2.0 7.0

2012 24.0 7.0

2013 43.0 4.0

Emission factors

Default EFs of LTO and cruise (jet kerosene) for civil aviation is used (2006 IPCC Guidelines and EMEP/EEA emission inventory guidebook – 2013).

Table 3.28 Emission factors used in the calculation of emissions from civil aviation


Gg/PJ Gg/PJ Gg/PJ Gg/PJ Gg/PJ Gg/PJ Gg/PJ

Aviation gasoline 70.0 0.0005 0.002 0.25 0.1 0.05 0.023


124

3.2.6.3 Road transport (CRF 1.A.3.b)

The road transport constituted 90.04 % of GHG emissions in the transport sector in 2013. After the rapid growth in the period 2000 – 2007 (see Figure 3.22), emissions in 2009 have

sharply decreased. The main reason was a sharp decrease of fuel consumption in the road transport in 2009. It decreased by 12.8 %, compared to 2008 level. The major reason for this

tendency was recession of the national economy and decrease of transport activities – decrease of passenger km by passenger cars and ton km by freight transport. The road transport is widely used in the local transportation and also for providing cross-border

transportation. The freight road transport approximately constitutes 40% (2013) of the total freight in the country (traffic of goods in ton-km). The share has increased by 3.8 %, compared with year 2012. In the freight road transport the inland freight constitutes

approximately 90% of gross – timber products, food products, household goods and building materials are dominant. Fuel consumption in road transport has increased by 1.9% in year

2013 compare with 2012. In different fuels various changes have taken place in 2013 compare with 2012. Gasoline consumption has decreased by 9.3% points and biofuel consumption has decreased by 0.7 % points, whereas diesel fuel consumption has increased by 4.8% points and

LPG consumption even by 27.4% points (see Figure 3.26).

Figure 3.22 GHG emissions in road transport (Gg CO2 eq)

Road transport includes five vehicle categories: Passenger cars, Buses, Heavy duty-vehicles

(HDV), Light duty-vehicles (LDV) and Mopeds & Motorcycles. In time period 1990 – 2013, essential changes have taken place in the structure of GHG emissions created by the road

transport (see Table 3.29). Gasoline has previously been the most common fuel used for road transports, but in 2013 the amount of diesel used for road traffic is 2.7 times more as gasoline and the emissions of CO2 from diesel surpassed the emissions of CO2 from gasoline as from

2001. In 2013, the gasoline consumption emissions created by passenger cars were less than of 1990

level, while the diesel oil fuel consumption created by the emissions of passenger cars have increased several times. The emissions of Light-duty vehicles (LDV) and heavy-duty vehicles (HDV) gasoline consumption have decreased, but the emissions of diesel oil fuel

consumption have essentially increased. Table 3.29 GHG emissions in road trans port by vehicle types (Gg CO2 eq)

Passenger Cars LDV HDV

Gasoline Diesel Gasoline Diesel Gasoline Diesel

1990 1132 43 161 55 424 525

1995 926 36 91 39 261 440


125

Passenger Cars LDV HDV

2000 864 119 48 78 145 660

2001 953 253 44 101 115 835

2002 958 285 37 117 95 879

2003 974 359 32 122 83 908

2004 1001 448 28 130 66 930

2005 993 521 24 129 55 1003

2006 1111 621 23 147 49 1113

2007 1225 767 22 178 43 1251

2008 1118 767 19 179 35 1159

2009 937 706 16 169 20 1000

2010 852 746 15 184 17 1116

2011 789 669 15 190 16 852

2012 666 679 17 236 13 761

2013 603 730 16 250 12 776

Trend

2013/1990 (% ) -47 1594 -90 358 -97 48

Trend

2013/2012 (% ) -10 8 -6 6 -10 2

Figure 3.23 CO2 emissions in road transport by vehicle types

CO2 emissions are directly fuel-use dependent and, in this way, the development in the emissions reflects a trend in the fuel consumption. As shown in Figure 3.23, the most

important emissions source for the road transport is passenger cars and HDV vehicles followed by LDV, buses and motorcycles. Share of CO2 emissions from passenger cars was 57.7%, HDV and buses 31.4% and LDV 10.8% in year 2013. In 2013, CO2 emissions in road

transport, compared to 2012 level have increased by 1.9 %.


126

Figure 3.24 CH4 emissions in road transport by vehicle types

CH4 emissions present consistent decrease trend within the whole period (see Figure 3.24). In 2013, CH4 emissions in road transport, compared to 2012 level have decreased by 5.9 %. The

majority of CH4 emissions from the road transport come from gasoline passenger cars (53%). The substantial emission drop from 2001 onwards is explained by the sharp penetration of

EURO3 and EURO4 passenger cars into the Latvia fleet and additionally in years 2009 - 2013 with decreasing of gasoline consumption by passenger cars.

Figure 3.25 N2O emissions in road transport by vehicle types

In 2013, N2O emissions in road transport, compared to 2012 level have increased by 2.4 %. Taking into account that N2O emission rates are largely dependent from implemented combustion and emission control technologies, different factor interaction characterises the

trend of N2O changes.

To analyse the trend of N2O emission at first the significance of different emission sources

should be clearly identified. The passenger cars (Figure 3.25) contribute 69.3%, LDV 10.8% and HDV and busses 19.8% of total N2O emission in Latvia’s road transport. Thus the N20 emission trend is mainly determined by the change in the technologies and fuel used by

passenger cars.


127

Regarding total N20 emission created by the fleet of Latvia passenger cars, gasoline fuelled

passenger cars contribute slightly above 37%, the rest is emitted by diesel fuelled passenger cars. Important, in the period after year 2005 the average N2O emission factor (t/TJ) for gasoline fuelled passenger cars has tendency to decrease due to change in the relative share of

EURO3 and EURO4 cars and EURO5 cars. The N20 emission factor (g/km) of gasoline fuelled passenger cars of the EURO 1 and EURO 2 classes is more than twice higher

compared to the factor of gasoline fuelled passenger cars of the EURO3 and EURO4 classes. The mileage share in 2013, calculated by summing the shares of EURO3 and EURO4 and EURO5 gasoline passenger cars, has increased almost twice – from 29.5% to 56.2% of the

total gasoline passenger cars mileage, compared to year 2005.

At the same time, one can see the opposite trend in the group of diesel passenger cars. The

N2O emission factor (g/km) of EURO3 and EURO4 and EURO5 diesel passenger cars is per about 60% higher than the emission factor for EURO1 and EURO2 diesel passenger cars. Thus, due to the significant rise of the mileage share of EURO3 and EURO4 and EURO5 cars

– from 24% (year 2005) up to 59.4% (year 2013) of the total diesel passenger cars mileage, the average N2O emission factor (t/TJ) for diesel passenger cars has also slightly increased.

Methods

For road transport, the detailed methodology is used to make annual estimates of the Latvian emissions, as described in the 2006 IPCC Guidelines and EMEP/EEA emission inventory

guidebook – 2013. The actual calculation is made with a COPERT IV model. COPERT IV provides factors for fuel consumption and for all exhaust emission components which are

included in the national inventory. For several reasons, COPERT IV is regarded as the most appropriate source of road traffic fuel consumption and emission factors. First of all, very few Latvia’s emission measurements exist, so data are too scarce to support emission calculations

on a national level. Secondly, the COPERT model is regularly updated with new experimental findings from European research programmes and, apart from updated fuel-use and emission

factors, the use of COPERT IV by many European countries ensures a large degree of cross-national consistency in reported emission results.

In COPERT IV, fuel consumption and emission simulation can be made for operationally hot

engines, taking into account gradually tighten emission standards and emission degradation due to catalyst wear. Furthermore, the emission effects of cold-start and evaporation are

simulated. Estimation of evaporative emissions of hydrocarbons and the inclusion of cold start emission effects are dealt with in the Latvian inventory by using LEGMA meteorological input data for ambient temperature variations during months; the distribution of evaporate

emissions in the driving modes are used default by COPERT IV model.

Corresponding to the COPERT IV fleet classification, all vehicles in the Latvia fleet are

grouped into vehicle classes, subclasses and layers. The layer classification is a further division of vehicle sub-classes into groups of vehicles with the same average fuel consumption and emission behaviour, according to EU emission legislation levels.

Trip-speed dependent basis factors for fuel consumption and emissions are implemented. The fuel consumption and emission factors used in the Latvia inventory are taken from the

COPERT IV model. The summary of the methods and EF used is presented in Table 3.30.

Table 3.30 Summary of source category description, CRF 1.A.3.b


estimated

1.A.3.b CO2 T2 CS Yes

CH4 T2 D (COPERT model) Yes

N2O T2 D (COPERT model) Yes T2 Tier 2; CS Country Specific; D Default.


128

To calculate CO2 emissions from lubrication oil using in car’s engines in road transport it is

calculated amount of oil, which the oil film developed on the inner cylinder walls. This oil film further is exposed to combustion and is burned along with the fuel. A calculation of lubricant oil consumption for engine operation has been performed using a typical oil

consumption factors for different vehicle types, fuel used and vehicle age (see Table 3-28 EMEP Emission inventory Guidebook 2013). Based on this calculated lubricant oil

consumption and using default EF (2006 IPCC Guidelines) CO2 emissions for lubricant oil burning for engine operation has been calculated.

For estimating CO2 emissions from use of urea-based additives in catalytic converters (non-

combustive emissions), it is used equation from 2006 IPCC Guidelines:

12

44

60

12 PurityActivityEmission

where:

Emissions - CO2 Emissions from urea-based additive in catalytic converters (Gg CO2);

Activity - amount of urea-based additive consumed for use in catalytic converters (Gg);

Purity - the mass fraction (= percentage divided by 100) of urea in the urea-based additive;

12/60 - conversion from urea to carbon;

44/12 - conversion from carbon to CO2.

In calculations, it is assumed that 75% of the HDV (starting with Euro IV class and later) the urea-based additives are used in catalytic converters. The activity level is 3 percent of diesel

consumption by the HDV. Thirty two and half percent is taken as default purity. Estimated CO2 emissions are reported in the IPPU sector (CRF 2).

Activity data

As a basis for model input information CSB and LR Road Traffic Safety Directorate (RTSD) data is used. CSB data have been used considering the fuel consumption, RTSD collected and

published data have been used considering stock of road transport in Latvia. Total mileage data for passenger cars, light duty trucks, heavy duty trucks and buses produced by the RTSD

is used for the years 1996-2012. The summary of the data sources used in emission calculation for road transport are presented in Table 3.31.

Table 3.31 Activity data and sources used for emission calculation in road transport

Activi ty data Source of activi ty data Remarks

Fuel consumption Calculated consumption

by COPERT IV model

Calibrated with national statistics. Deviation

less than 0,15%

Number of cars Road Traffic Safety

Directorate

For calcu lation it is used number of cars with

permission to participate in traffic

Number of cars

by fuel and

vehicle type

Road Traffic Safety

Directorate and expert

calculation

Based on available data cars are grouped by

fuel type, engine power, age and vehicle

categories according to emission control

system

Distance travelled

by cars by fuel

and vehicle type

Road Traffic Safety

Directorate expert

calculation

Based on an average data by cars classes it is

modelled by fuel type, engine power, age and

vehicle categories

Emission factors National specific for

CO2 emissions,

COPERT emission

factors for CH4 and N2O

CO2 emission factors are based on carbon

content in fuel.

1990 – 1999 EF for unleaded gasoline is 68.6;

2000 - onwards EF gasoline is 71.18

1990 – onwards EF d iesel oil 74.0


129

General information about activity data is presented in Figure 3.27 (number of cars and their

split by sub-classes and layers). Before emission calculation COPERT IV model was calibrated to be consistent with actual fuel consumption (energy statistics see Table 3.32). Deviation between fuel consumption in COPERT model and statistics is less than 0.1%. Thus

we can say that all emission calculation is based on fuel consumption amount.

Table 3.32 Fuel consumption in road transport (TJ)

Gasoline, TJ Diesel oil, TJ LPG, TJ

Natural gas,

TJ

Biofuel

(biodiesel

and

bioethanol),

TJ

1990 24217 8326 592 305 NO

1995 17994 6884 91 33 NO

2000 14520 11471 865 68 NO

2001 15268 15930 866 101 NO

2002 14960 17168 865 68 NO

2003 14950 18609 956 68 NO

2004 15038 20222 1047 68 NO

2005 14730 22180 1093 68 107

2006 16313 25240 1184 68 138

2007 17852 29485 1093 67 71

2008 16269 28256 956 33 83

2009 13586 25154 865 4 173

2010 12308 27449 988 1 1102

2011 11432 22945 1184 NO 844

2012 9697 22465 1859 NO 742

2013 8794 23539 2368 NO 737

As seen in Figure 3.26, the fuel consumption has essentially changed in the time period 1990 – 2012. The gasoline consumption from the highest consumption in 1990 has decreased till

1999, reaching the lowest consumption and after six year stabilisation the increase was seen in 2006 and 2007. Consumption of gasoline had decreased in 2013 by 9.3% points compare with year 2012. Whereas the diesel fuel consumption starting from 1997 has increased all the time

till 2007. While it decreased in 2008 and 2009. Diesel fuel consumption has increased in 2013 by 4.8% compare with year 2012. It was in place substantial LPG consumption increasing in

year 2011 and 2012 in road transport.


130

Figure 3.26 Development of Fuel consumption in road transport (TJ)20

The vehicle numbers per passenger cars sub-class and layers are shown in Figure 3.27.

Figure 3.27 Distribution of passenger cars fleet by sub-classes

Analysing the development of the passenger car fleet in the time period 1990 – 2013 (Figure 3.28, Figure 3.29), following features can be noted:

Cars with a gasoline engine of a capacity > 2.0l constitute the major part;

Cars with a gasoline engine of a capacity < 1.4l during the whole period have small

changes and its constitute approximately 7% in year 2013;

As of 2000, the number of cars with diesel engines, both, < 2.0l and > 2.0l, grow rapidly and its share is 45.3% from the toral number of passenger cars in 2013;

As of 2005, in the car fleet with a gasoline engine, the number of EIRO 3 and EIRO 4 cars grow rapidly. In 2013 a share of EURO3 and EURO 4 and EURO 5 cars constitute

21%;

20

LPG, natural gas and biofuel on right axes


131

As of 2005, in the car fleet with a diesel engine, the number of EURO 4 and EURO 5

cars grow rapidly. In 2013 a share of EURO 4 and EURO 5 cars constitute 27%;.

Figure 3.28 Distribution of gasoline passenger cars fleet by layers

Figure 3.29 Distribution of diesel oil passenger cars fleet by layers

Analysing the development of LDV fleet (Figure 3.30, Figure 3.31) in the following time period, major features can be noted as follows:

As of 1996, the number of cars with a gasoline engine decreases;

As of 2000, the number of cars with a diesel engine rapidly increases. In 2013 a share of diesel cars is 92% ;

As of 2005, the number of EURO 4 and EURO 5 cars increases. In 2013 a share of EURO 4 and EURO 5 cars constitute 30%;


132

Figure 3.30 Distribution of light duty vehicles fleet by sub-classes

Figure 3.31 Distribution of light duty vehicles fleet by layers

The vehicle numbers per HDV sub-classes and layers are presented in Figure 3.32 and Figure 3.33. Analysing the development of HDV fleet in the following time period, major features

can be noted as follows:

As of 2000, the number of cars with a gasoline engine rapidly decreases. A share of gasoline cars has decreased from 33% to 4.4 % corresponding years 2000 and 2013;

As of 2000, the number HDV cars with tonnage 14-34 t and a diesel engine starts to increase;

As of 2000, average age reduction of cars takes place gradually. In 2013 a share of EURO IV and EURO V cars constitute 27.5%.


133

Figure 3.32 Distribution of heavy duty vehicles fleet by sub-classes

Figure 3.33 Distribution of heavy duty vehicles fleet by layers

Emission factors

CO2 emissions in COPERT IV model were calculated, using country-specific CO2 emission factor that are calculated based on the information available on the C and H content in fuel.

Country specific EF for CO2 emission calculation (gasoline, diesel oil) in road transport is used:

1990 – 2013 EF diesel oil 74.0 kg/GJ (―Guidance Manual for CO2 emission

estimations‖ (2004) see Annex 2 of NIR);

1990 – 1999 EF for unleaded gasoline is 68.6 kg/GJ (―Guidance Manual for CO2

emission estimations‖ (2004) see Annex 2 of NIR); Taking into account recommendations of ERT about necessity to investigate EF for gasoline (due to big difference in comparison with other countries ’), Ministry of Environmental

Protection and Regional development funded research ―Research on carbon content in transport fuels‖ in year 2012. The research on C content in fuels carried out in 2012 quantified

C and H content in gasoline. For gasoline the C content is 86.3%, further it is calculated NCV for gasoline (43.97 MJ/kg) and estimated CO2 emission factor in accordance


134

Requirements from the IPCC 2006 Guidelines. Based on the results of this research, CO2 EF

of gasoline has been calculated - 71.18 kg/GJ. Although quantification of C and H content in gasoline has been performed for fuel with a requirement for gasoline quality which is in force from 01.01.2009, the updated CO2 EF is implemented for emissions calculation 2000-2013

because only unleaded gasoline is used starting from year 2000. Rest of emission factors comes from the COPERT IV model.

3.2.6.4 Railways (CRF 1.A.3.c)

In 2013, the fuel consumption in railway constituted 8.8 % of GHG emissions from the total

GHG emissions in transport. Freight transport has a dominant role in railway. The railway transport accomplishes approximately 60% (2013) of the total freight transport in Latvia (traffic of goods in ton-km) and the transit transport traffic is dominant. In 2009 and 2010,

transported freight along the railway and therefore the diesel consumption has a slightly decreased, compared to 2008 level. Due to dependence on transit transport of goods from

Russia fuel consumption has decreased by approximately 8.8% in 2013 compare with year 2012. It resulting in decreasing of GHG emission by 10.1% in 2013 compared to 2012 level. Emission calculation in railway transport includes railway transport operated by diesel

locomotives.

Railway related fuel consumption is key sources for CO2 emissions (Figure 3.34). In 2013,

total GHG emissions in railway, compared to 1990 level have decreased by 57.9 %.

Figure 3.34 Development of GHG emissions in railway (Gg CO2 eq)

Methodological issues

Methods

When calculating emissions from railway, 2006 IPCC Guidelines Tier 1 and Tier 2 methods have been applied. The summary of the latest key category assessment, methods and EF used

is presented in Table 3.33.

Table 3.33 Summary of source category description, CRF 1.A.3.c


estimated

1.A.3.c CO2 T2 CS Yes

CH4 T1 D Yes

N2O T1 D Yes T1 Tier 1; T2 Tier 2; CS Country Specific; D Default.


135

Activity data

The data about diesel oil consumption in railway are derived from the CSB. Development of diesel oil consumption is presented in Figure 3.35 and Table 3.34. As we see, starting from year 2010 a small portion of biodiesel is used in railway.

Figure 3.35 Development of fuel consumption in railway (TJ)

Table 3.34 Fuel consumption in railway (TJ)

Diesel oil Biodiesel

1990 7181 NO

1995 3229 NO

2000 2762 NO

2001 2847 NO

2002 2974 NO

2003 3399 NO

2004 3484 NO

2005 3484 NO

2006 3059 NO

2007 3314 NO

2008 3314 NO

2009 3102 NO

2010 2804 35

2011 3144 91

2012 3357 63

2013 3017 48

Emission factors

Country specific EF for CO2 emissions is used (―Guidance Manual for CO2 emission estimations‖ (2004) see Annex 2 of NIR). Rest of emission factors comes from 2006 IPCC

Guidelines and EMEP/EEA 2013 (Table 3.35).

Table 3.35 Emission factors used in the calculation of emissions from railway


Gg/PJ Gg/PJ Gg/PJ Gg/PJ Gg/PJ Gg/PJ Gg/PJ

Diesel oil 74 0.00415 0.0286 1.2332 0.251823 0.10943

0,02353

(2003-2004)

0,09414 (1990-2007)

0.04707

(2008-2013)


136

3.2.6.5 Domestic Navigation (CRF 1.A.3.d)

In 2013, fuel consumption in navigation was responsible for 1.0% of GHG emissions from total GHG emissions in transport.

Although Latvia has several ports, domestic navigation that providing transport of freight or passengers among local ports is not developed. Major activities in ports deal with

international freight transport. In domestic navigation, the emissions are calculated for miscellaneous vessels (tugs, barges, towboats, and icebreakers), recreational crafts and personal boats (Figure 3.36).

Figure 3.36 GHG emission development in domestic navigation (Gg CO2 eq)

Fuel consumption and CO2 emissions trend in domestic navigation mainly depends from international (import, export) cargo activities in ports (cargo turnover and number of vessels

served in ports). During the period 2006-2013 international cargo turnover in ports has increased by approximately 18% and number of served vessels by approximately 10% points.

This increasing trend of activity partly explains fuel consumption increasing. On the other hand, fuel consumption is affected by the number of vessels serviced in ports. As shown in Figure 3.37, in spite of the rapid increase in the volume of cargo at the port of Riga, the

number of serviced ships has remained almost unchanged. The main reason for this trend is the increase in the gross tonnage of vessels. The most significant increase was registered in

the average tanker gross tonnage, but also in other cargo carrier groups (container, dry bulk carriers).

0

0,5

1

1,5

2

2,5

3

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

loaded,unloaded cargo

served vessels

Figure 3.37 Loaded, unloaded cargo and served vessels at Riga port (2000 = 1)


137

Other additional factor which makes impact to fuel consumption in domestic navigation is

weather conditions. This we can definitely see for year 2010 and 2011 when air temperature was low and sea was covered by ice. An ice breaker operated many months to ensure operation of ports in year 2010 and 2011. This has made an impact to fuel consumption in

years 2010 and 2011.

Before GHG emission calculation is performed CSB is asked to check and further confirm

fuel consumption in sector if fluctuation is more than 20% points compare to the previous year.

Methodological issues

Methods

When calculating emissions from navigation, IPCC 2006 Guidelines Tier 1 and Tier 2 method

has been applied. Country specific CO2 EF is used for emission calculation from diesel fuel consumption. The summary of the latest key category assessment, methods and EF used is presented in Table 3.36.

Table 3.36 Summary of source category description, CRF 1.A.3.d


estimated

1.A.3.d CO2 T1,T2 CS; D Yes

CH4 T1 D Yes

N2O T1 D Yes T1 Tier 1; T2 Tier 2; CS Country Specific; D Default.

Activity data

The data about diesel oil consumption and gasoline consumption in domestic navigation are

derived from the CSB. CSB have started to collect data about diesel oil consumption and gasoline consumption in domestic navigation respectively from year 2006 and 2010. For the

time period 1990 – 2005 and 1990 – 2009 correspondingly for diesel oil and gasoline consumption it is used data evaluation method from the study (―Evaluation of fuel consumption for domestic aviation and navigation‖, FEI, 2004). Development of fuel

consumption in domestic navigation is presented in Figure 3.38 and Table 3.37.

Diesel oil consumption has increased approximately 2 times in year 2013 compare with year

2012.

Figure 3.38 Development of gasoline and diesel oil fuel consumption in domestic navigation


138

Table 3.37 Fuel consumption in domestic navigation (TJ)

Diesel oil Gasoline

1990 11 2

1995 6 3

2000 6 3

2001 6 3

2002 6 4

2003 6 4

2004 6 4

2005 5 4

2006 4 4

2007 43 5

2008 85 5

2009 170 4

2010 212 3

2011 212 3

2012 170 3

2013 340 4

Emission factors

Default EFs for navigation is used (2006 IPCC Guidelines and EMEP/EEA 2013, Table 3.38).

Table 3.38 Emission factors used in the calculation of emissions from navigation

CO2, t/TJ CH4, t/TJ N2O, t/TJ

Gasoline 69.3 0.0473 0.000296

Diesel oil 74.0 0.004 0.003

3.2.6.6 Source specific recalculations

The following recalculations and improvements of the emission inventories have been made in the transport sector since the emission reporting in 2014. (Table 3.39).

Table 3.39 Recalculations for Sub-category CRF 1.A.3 Transport

Sub-category Recalculation Improvements

Road transport (CRF A.3.b) CO2 emissions for 2000-

2008 have been

recalculated

Recalcu lations have been done due to

implementation of updated Country

specific EF for gasoline for t ime series

2000-2008 (71.18 instead 68.6).

Railway (CRF A.3.c) CH4; N2O and NOx

emissions 1990-2012

Recalcu lations have been done due to

implementation of updated EF (2006 IPCC

Guidelines and EMEP/EEA 2013).

3.2.6.7 Source specific planned improvements

No improvements are planned for the sector.


Activity data about fuel consumption in transport sector is mainly ava ilable from 1990 and

they are provided by CSB. Considering that CSB gives approximately 2% statistical sample


139

error for statistical data uncertainty in activity data of fuel consumption in transport is ±2% in

2013. Before GHG emission calculation is performed CSB is asked to check and further confirm fuel consumption in sector if fluctuation is more than 20% points compare to the previous year.

CO2 emission factor was estimated according physical characterization of used fuels in country based on average NCV reported by fuel consumers and carbon content so uncertainty

was assigned as quite low about 10%. Default CH4 and N2O emission factors used in estimation of emissions was taken from 2006 IPCC Guidelines, so uncertainty was assigned 50 %.

In order to maintain consistency with the time-series the estimation procedures have been developed as described above (chapter 1.6.). However, due to the fact that some of the

estimations are not based on activity data but on other factors as LTO cycles in civil aviation sector, a certain degree of uncertainty exists. In road transport one important basic parameter for the COPERT IV model is vehicle-km, which is calculated through another model. This

second model is based on the mileage driven by the vehicle noted at time of TA (annual inspection/testing of the vehicle) at Road Traffic Safety Directorate. If it is in place sharp

changing of some external factors impacted fuel consumption, for example economy recession, fuel price or energy tax, it will not be shown as clea rly in the development of vehicle mileage as in statistics on fuel consumption.

To ensure time series consistency any recalculation related with model version updating is realized for all time period. Linear interpolation has been implemented only for cases when

activity data fluctuation does not take place.


QA/QC check is performed according to 2006 IPCC Guidelines. Latvia’s national inventory QA/QC plan is ruled in national legislation and approved by Cabinet of Ministers.

All Tier 1 general inventory level QC procedures listed in chapter 1.2. applicable to this sector

are used. These measures are implemented every year during the transport sector inventory. In addition, the consumption of every type of fuel in the last year is checked and compared with

previous years. If large variations are discovered for certain fuels, responsible CSB staff is contacted for an explanation.

Estimated emissions verification:

1. All estimations of the emissions done for a transport sector are checked on the logical mistakes by checking the time series of the activity data, emission factors and

emissions consistency to display all significant and illogic changes in the activity data and emissions.

2. Emissions are checked using time series consistency check for the EF estimated in

CRF Reported. EFs are calculated per fuel, substance and CRF-code and checked against the emission factors to make sure that no calculation errors have occurred

when emissions were computed. The calculated air transport emissions have been compared and verified with Eurocontrol’s emission data for 2008-2010. The calculated activity data for fuel consumption of LTO and cruise mode and emissions

were comparable and very close to those estimated by Eurocontrol.

3. For road transport a checking is done on less aggregated level than CRF reported.

Non CO2 EF changes that are higher than 10% in time series are double-checked and reasonable explanation for IEF changes has to be found.


140

Each expert reviewer has to check and fill in QC form for each category taking into account

criteria given in QA/QC plan approved in national legislation. Potential errors and inconsistencies are documented in the special form and corrections are made if necessary. The QC measures have been implemented concerning used activity data, implemented Guidelines,

methods and EF. Form then is sent to National Inventory Compiler and archived.

Additional QA/QC checks for Tier2 methodology

For emission calculation in road transport additional QA/QC check approach has implemented. QC activities are realised with emission data and activity data QC. It is assessed that implemented default EF from COPERT IV model are applicable to national

circumstances because model comprises all necessary technologies. Country specific EFs for CO2 are calculated based on 2006 IPCC Guidelines methodology. Activity data (fuel

consumption, total number of vehicles) provider CSB has the internal QA/QC procedures based on mathematical model and analysis to avoid logic mistakes. To ensure QA procedure expert from Road traffic and safety Directorate is asked to make peer review about the main

assumption implemented in emission calculation.

3.2.7 Other Sectors (CRF 1.A.4)


CRF 1.A.4 Other sectors include emissions from the small combustion of fuels in Commercial/Institutional, Residential sectors and Agriculture/Forestry/Fisheries. In addition,

emissions from mobile machinery used in Commercial, Residential and Agriculture and Forestry sectors are included here as off- road. Also emissions from autoproducers are included in relevant sectors of CRF 1.A.4 – according to 2006 IPCC Guidelines these

emissions have to be reported in sectors producing them.

In submission 2015, the CRF subsector 1.A.4. Other sectors were split into subsectors which

are in line with 2006 IPCC Guidelines/CRF Reporter structure:

1.A.4.a Commercial/Institutional:

• 1.A.4.a.i Stationary combustion; • 1.A.4.a.ii Off-road vehicles and other machinery;

1.A.4.b Residential:

• 1.A.4.b.i Stationary combustion; • 1.A.4.b.ii Off-road vehicles and other machinery;

1.A.4.c Agriculture/Forestry/Fishing: • 1.A.4.c.i Stationary combustion;

• 1.A.4.c.ii Off-road vehicles and other machinery; • 1.A.4.c.iii Fishing.

Table 3.40 Emissions from Other Sectors (CRF 1.A.4) in 1990–2013 (Gg)

CO2 CH4 N2O

Aggregate

GHGs (CO2,

CH4, N2O)

NOx CO NMVOC SO2

Gg Gg CO2 eq. Gg

1990 5535.58 11.00 0.163 5859.15 21.19 160.97 22.59 34.16

1991 5648.04 12.53 0.178 6014.49 23.67 156.34 23.17 31.58

1992 4005.76 11.29 0.166 4337.51 18.33 139.32 20.97 25.44

1993 3350.58 12.05 0.169 3702.06 16.62 146.53 22.10 20.86

1994 2347.99 11.94 0.161 2694.53 13.04 144.15 21.85 16.10


141

CO2 CH4 N2O

Aggregate

GHGs (CO2,

CH4, N2O)

NOx CO NMVOC SO2

Gg Gg CO2 eq. Gg

1995 1564.12 12.51 0.171 1927.75 10.65 140.10 22.39 8.33

1996 1585.29 12.84 0.176 1958.65 10.78 147.70 23.36 9.10

1997 1343.94 12.17 0.165 1697.46 8.77 138.83 22.06 6.76

1998 1153.96 11.33 0.155 1483.47 7.42 132.61 20.97 4.83

1999 1136.28 11.15 0.154 1460.81 8.39 128.42 20.53 3.32

2000 1050.76 10.46 0.145 1355.42 7.94 125.14 19.73 2.22

2001 1209.82 11.56 0.158 1545.71 8.77 137.65 21.59 2.60

2002 1182.77 11.34 0.155 1512.52 8.14 133.18 21.07 1.79

2003 1268.75 11.88 0.163 1614.37 9.30 140.47 22.23 1.57

2004 1318.31 12.25 0.168 1674.60 9.28 141.86 22.65 1.37

2005 1292.72 12.25 0.167 1648.66 8.79 144.30 22.86 1.46

2006 1354.01 11.89 0.162 1699.68 8.65 140.27 22.23 1.20

2007 1370.96 11.88 0.162 1716.28 8.17 137.65 22.00 0.82

2008 1292.32 10.99 0.149 1611.51 7.39 134.11 20.93 0.54

2009 1279.73 12.09 0.164 1630.69 7.53 148.02 23.06 0.48

2010 1458.28 9.61 0.131 1737.65 7.34 115.06 18.08 0.62

2011 1355.77 9.64 0.132 1636.01 7.28 120.47 18.61 0.61

2012 1278.47 10.36 0.141 1579.62 7.19 124.90 19.65 0.35

2013 1247.42 9.33 0.128 1518.63 6.96 111.14 17.60 0.40

GHG emissions in CRF 1.A.4 sector decreased by 76.9% in 1990-2000 due to reorganizations in the country after the collapse of Soviet Union, as mentioned in previous chapters (Table

3.40). Since 2000 GHG emissions started to grow due to thrive in national economy, and increased by 26.6% in until 2007. During economic crisis in 2008-2009 the emissions

decreased by 5% from 2007, and increased in the following two years because of recovery in economy. However, in the recent years – 2012 and 2013 the GHG emissions decreased by 3.4% and 7.2% comparing with 2011 level – in 2012 a lot more biomass was used, and the

use of solid fuels decreased significantly, whereas in 2013 gaseous fuels were used less than in 2012, and also the consumption of biomass reduced. There can also be seen a trend that if

the average temperature comparing with previous year has increased, CO2 emissions are less and vice versa.

CH4 and N2O emissions shows the biomass consumption trend – in 2012 the increase in

emissions was 7.5% and 7.3%, respectively, comparing with 2011, and in 2013 there can be seen a decrease in CH4 and N2O emissions by 10% and 9.6%, comparing with 2012.

Indirect GHG emissions from CRF 1.A.4 Other sectors were estimated as well. SO2 had the biggest decrease by 98.8% in 1990–2013. It can be explained with fuel switching from coal, peat and heavy fuel oils to natural gas and biomass from what sulphur dioxide emissions are

not emitted. Also a strict national legislation was approved to improve the quality of used liquid fuels in country. NOx emissions have also decreased by 67.1% in 1990-2013, NMVOC

emissions – by 22.1%, and CO emissions – by 31%. The decrease can also be explained with fuel switch from solid ones to natural gas and biomass, which have lower emission factors.


142


Methods


combustion as country specific parameters were used to estimate CO2 emission factor. However, for some fuels there are no country-specific emission factors, therefore 2006 IPCC

Guidelines Tier 1 method using default emission factors was used. 2006 IPCC Guidelines’ Tier 1 method was used to calculate CH4 and N2O emissions from the CRF 1.A.4 sector.


the experts from LEGMC.

The general method for emission data preparation was used:

qBEFEm

where:








IPCC 2006 Guidelines;

EMEP/EEA 2013. Country specific emission factors were used to calculate carbon dioxide (CO2) and sulphur

dioxide (SO2) emissions.


CO2 emission factors for CRF 1.A.4 Other sectors are estimated with the same equations and

using same methods as for CRF 1.A.1 Energy industries sector, including calculation methods and assumptions for landfill gas and other biogas as in CRF 1.A.1 sector.

For some fuels default CO2 emission factors from 2006 IPCC Guidelines, Volume 2, Chapter 2 Stationary combustion, Table 2.4, were taken due to unavailability of country specific data:

• other liquid fuels – 73.3 Gg/PJ;

• coal – 94.6 Gg/PJ; • biodiesel – 70.8 Gg/PJ;

• straws – 100 Gg/PJ; • charcoal – 112 Gg/PJ; • waste oils – 73.3 Gg/PJ.

For CRF 1.A.4.c.iii Fishing default CO2 emission factors were taken from 2006 IPCC Guidelines, Volume 2, Chapter 3 Mobile combustion, Table 3.5.2:

• diesel oil – 74.1 Gg/PJ; • residual fuel oil – 77.4 Gg/PJ.


143

SO2 emissions factors

SOx emission factors for CRF 1.A.4 Other sectors are estimated with the same equations and using same method as for CRF 1.A.1 and CRF 1.A.2 sectors.


The default CH4 and N2O emission factors are taken from 2006 IPCC Guidelines, Volume 2, Chapter 2 Stationary combustion, Table 2.3. NOx, CO and NMVOC emission factors used in

estimation of emission were taken from EMEP/EEA 2013, Chapter 1.A.4 Small combustion, Tables 3-3 to 3-6 (CRF 1.A.4.b.i), Tables 3-7 to 3-10 (CRF 1.A.4.a.i, 1.A.4.c.i).

List of other emission factors can be seen in Table 3.41.

Table 3.41 CH4, N2O, NOx, NMVOC, CO emission factors (Gg/PJ)

CH4

N2O

NOx NMVOC CO

1.A.4.a 1.A.4.b,

1.A.4.c

1.A.4.a,

1.A.4.c 1.A.4.b

1.A.4.a,

1.A.4.c 1.A.4.b

1.A.4.a,

1.A.4.c 1.A.4.b

Diesel o il 0.010 0.010 0.0006 0.513 0.051 0.03 0.001 0.066 0.057

RFO 0.010 0.010 0.0006 0.513 0.051 0.03 0.001 0.066 0.057

LPG 0.005 0.005 0.0001 0.074 0.051 0.023 0.001 0.029 0.026

Jet fuel 0.010 0.010 0.0006 0.513 0.051 0.03 0.001 0.066 0.057

Other kerosene 0.010 0.010 0.0006 0.513 0.051 0.03 0.001 0.066 0.057

Other liquid 0.010 0.010 0.0006 0.513 0.051 0.03 0.001 0.066 0.057

Waste oils 0.300 0.300 0.0040 0.513 0.051 0.03 0.03 0.066 0.057

Shale oil 0.010 0.010 0.0006 0.513 0.051 0.03 0.001 0.066 0.057

Coal 0.010 0.300 0.0015 0.173 0.110 0.089 0.484 0.931 4.600

Peat briquettes 0.010 0.300 0.0015 0.173 0.110 0.089 0.484 0.931 4.600

Peat 0.010 0.300 0.0015 0.173 0.110 0.089 0.484 0.931 4.600

Natural gas 0.005 0.005 0.0001 0.074 0.051 0.023 0.002 0.029 0.026

Wood 0.300 0.300 0.0040 0.091 0.080 0.300 0.600 0.570 4.000

CH4 from landfill gas 0.005 0.005 0.0001 0.074 NO 0.023 NO 0.029 NO

Other biogas 0.005 0.005 0.0001 0.074 NO 0.023 NO 0.029 NO

Straws 0.300 0.300 0.0040 0.091 0.080 0.300 0.600 0.570 4.000

Biodiesel 0.010 0.010 0.0006 0.513 NO 0.03 NO 0.07 NO

Charcoal 0.200 0.300 0.0040 NO 0.080 NO 0.600 NO 4.000

Gasoline emission factors are used for CH4 and N2O emission estimation from off- roads

(2006 IPCC Guidelines, Volume 2, Chapter 3 Mobile combustion, Table 3.3.1.). As there is no information about distribution between 2-stroke and 4-stroke engines, it was assumed that 25% of consumed gasoline is combusted in 2-stroke engines, while 75% - in 4-stroke engines.

Such assumption has been made, based on Danish data which are presented in EMEP/EEA 2013 for air pollutants’ calculations. The emission factors for indirect GHGs were taken from

Chapter 1.A.4. Non-road mobile sources and machinery. NOx, CO and NMVOC emission factors used in estimation of emission were taken from EMEP/EEA 2013, Chapter 1.A.4 Non-road mobile sources and machinery, Table 3-1.

Also diesel oil and residual fuel oil consumed in Fisheries sector was assumed as consumed by fishing ships and the emission factors were taken from 2006 IPCC Guidelines, Volume 2,

Chapter 3 Mobile combustion, Table 3.5.2. Emission factors for indirect GHGs are taken from EMEP/EEA 2013, Chapter 1.A.3.d., Table 3-1.


144

Emission factors for gasoline consumed in offroads and d iesel oil and residual fuel oil

consumed in Fisheries are presented in Table 3.42.

Table 3.42 CH4, N2O, NOx, NMVOC, CO emission factors for gasoline, diesel and RFO (kg/Mg21

)

Gasoline Diesel RFO

2-stroke 4-stroke

CH4

1.A.4.a.ii 0.18 0.12

NO NO 1.A.4.b.ii 0.18 0.12

1.A.4.c.ii 0.17 0.08

1.A.4.c.iii NO NO 0.007 0.007

N2O

1.A.4.a.ii

0.0004 0.002 NO NO 1.A.4.b.ii

1.A.4.c.ii

1.A.4.c.iii NO NO 0.002 0.002

NOx

1.A.4.a.ii

2.765 7.117 NO NO 1.A.4.b.ii

1.A.4.c.ii

1.A.4.c.iii NO NO 78.5 79.3

NMVOC

1.A.4.a.ii

242.197 17.602 NO NO 1.A.4.b.ii

1.A.4.c.ii

1.A.4.c.iii NO NO 2.8 2.7

CO

1.A.4.a.ii

620.739 770.368 NO NO 1.A.4.b.ii

1.A.4.c.ii

1.A.4.c.iii NO NO 7.4 7.4

Activity data

Mainly emissions from fuel combustion are calculated using fuel consumption data from the national Energy Balance, prepared by CSB. The data collection system for CRF 1.A.4 sector is the same as for CRF 1.A.1 and CRF 1.A.2 sectors. Data on fuel consumption in 1.A.4

sector are presented in ANNEX A.3.1.

Autoproducers data prepared by CSP are taken into account into the calculation of the

emissions from CRF 1.A.4 sector according to 2006 IPCC Guidelines.

Only gasoline combustion is reported as off- roads in CRF 1.A.4 sector. It is sure that diesel oil is also consumed as off- roads but for now it is not possible for CSB and LEGMC to divide

the consumption between fuel combusted stationary and fil led in technological vehicles. Due to that all diesel oil reported in the sector is estimated as combusted stationary.

In CRF 1.A.4.c.iii Fishing it is assumed, that diesel oil and residual fuel oil is consumed by fishing vessels.

21 For CH4 and N2O – Gg/PJ


145

Figure 3.39 Fuel consumption in Other sectors (CRF 1.A.4) for 1990-2013 (PJ)

The biggest decrease in 1990-2013 was for solid fuel consumption – 95.7% and liquid fuels

consumption – 69.5% (Figure 3.39). It is explained with fuel switching processes when solid and liquid fuels were replaced with cheaper fuels. Also stronger legislation contributed fuel

switching to the type of fuels with a lower level of emissions.

Since 1990 biomass dominates as a fuel in CRF 1.A.4 sector. The biggest part of solid biomass consumption goes to Residential sector where biomass is the main fuel in small

capacity burning installations. Consumption of biomass fuel has increased by 17% in 1990–2013 in Other sectors. However, it can be seen that the amounts of biomass have been

fluctuating over recent years which can be explained with temperature fluctuations during winter.

Since 1997 gaseous fuel consumption was constantly increasing until 2007, because it had

lower costs to and liquid and solid fuels were replaced with natural gas as a fuel. The increase in fuel consumption in CRF 1.A.4 Other sectors is strongly linked to decrease in fuel

consumption in CRF 1.A.1 Energy industries when central heating supply consumers switched to individual heating supply. In the recent years a decreased consumption in natural gas is observed, which was influenced by increasing costs of natural gas.


146

Figure 3.40 Fuel consumption in Other sectors (CRF 1.A.4) for stationary combustion and heating degree

days in Latvia

As it can be seen in Figure 3.40, fuel consumption in 1.A.4 sector is related with changes in

temperature – in years where heating degree days are more, the amounts of consumed fuel are also larger, especially it can be seen in 1994-2003 and in the most recent years. In 2008 there

was considerably low amount of HDDs, and also the fuel consumed was less than in 2007. However, in 2009-2010 the correlation between HDDs and consumption is less visible because of impact of global crisis, which clearly affected the Residential sector. In 2011-2013

there can be seen a correlation in HDDs and fuel consumption – in 2012 the number of HDDs was by 9.9% higher than in 2011, and the amounts of fuel consumed were by 5% more. In

2013 the number of HDDs was by 7% less, and also fuel consumed was by 7% less than in 2012.


Uncertainty in activity data of fuel combustion in 1.A.4 sector is ±2% in 2013. CSB gives approximately 2% statistical sample error for statistical data. According to CSB, as data are

obtained using information given by respondents, this number is a variation coefficient which characterizes selection of respondents. Total variation coefficient for energy balance is within

2-3%. In Latvia all fossil fuels (oil, natural gas and coal) are imported and import and export statistics are fairly accurate.

Uncertainty of activity data for solid biomass combustion was assigned as 5% because

biomass activity data were collected by CSB with questionnaires sent by enterprises consumed biomass. As fuel consumption in CRF 1.A.4.b Residential sector is obtained only

every 5 years using questionnaire and data are extrapolated until the next survey, therefore the uncertainty of all fuel consumption in residential sector is assumed 15%. According to 2006 IPCC Guidelines, Volume 2, Chapter 1, pg. 1.19, biomass data are generally more uncertain

than other data in national energy statistics, because a large fraction of the biomass may be part of the informal economy, and the trade in these type of fuels is frequently not registered

in the national energy statistics and balances. Uncertainty of landfill gas stationary combusted in enterprises covered by 1.A.4 Other sectors was assumed rather low – 2% because the combusted fuel amount is obtained directly from landfill plant that has precise measurement

equipment for accounting of combusted fuel. Still the methane percentage amount in combusted landfill gas is given approximately, therefore final uncertainty of biomass fuels is

assumed as 5%.


147

CO2 emission factor was estimated according physical characterization of used fuels in

country basing on average NCV reported by fuel consumers and carbon content, hence the uncertainty for liquid fuels was assigned as quite low – about 10%. The same level of uncertainty was assigned for solid fuels. CO2 emission factor for natural gas was assumed

rather low – as 5% because annual plant specific fuel data is used to estimate emission factor.

CH4 and N2O emission factor used in estimation of emissions was taken according to 2006

IPCC Guidelines, Volume 2, Chapter 2 Stationary combustion, Table 2.12., which provides the range of default values for uncertainties. The uncertainty both for CH4 and N2O EFs was assigned as uncertainties used in previous submissions – 50%.


series. Emissions from all sectors are estimated or reported as not occurring / not applicable, therefore there are no ―not estimated‖ sectors.







Activity data have been checked at the data provider – Central Statistical Bureau, which has its own internal QA/QC procedures based on mathematic model and analysis to avoid logic mistakes. When activity data have been received, the sectoral expert responsible for the






For country-specific CO2 emission factors, the sources of the calorific values, carbon content and oxidation factors, as well as these values are provided in 3.2.4.2 Methodological issues.


Guidelines, Volume 2, Chapter 2 Stationary combustion, Table 2.2. Whether country specific CO2 emission factor is or is not in the confidence interval, can be seen in Table 3.43.



Gasoline 67.50 71.18 73.00

Diesel oil 72.60 74.00 74.80 74.75

RFO 75.50 76.59 78.80 77.36

LPG 61.60 62.44 65.60 62.75


148


Jet fuel 69.70 71.51 74.40


Other liquid 72.20 72.59 74.40

Shale oil 67.80 76.35 79.20 74.75

Peat 100.00 103.87 108.00 105.99

Natural gas 54.30 54.23 58.30 55.44

Wood 95.00 107.78 132.00

Sludge gas 46.20 50.87 66.00

Landfill gas 46.20 50.87 66.00

Other biogas 46.20 50.87 66.00

Only natural gas country specific CO2 emission factor is outside of confidence interval given by 2006 IPCC Guidelines. Main reasons are different carbon content in fuel, as well as different NCVs.


To verify the CO2 emissions, logical mistakes are checked by checking the time series of the

activity data, emission factors and emissions consistency to display all significant and illogical changes in the activity data and emissions. The emissions for indirect GHGs in the database are cross-checked with emissions reported within CLRTAP for verification

purposes.

CO2 emissions are compared with emissions in Reference Approach estimations, and a ll

significant differences (±5%) are explained in the corresponding subchapter.



3.2.8 Other (CRF 1.A.5)


Under the CRF 1.A.5.b Other Mobile sources emissions from liquid fuels – aviation gasoline, diesel oil and jet kerosene, used in military aircrafts and ships are reported. These emissions appear since 1996 (Table 3.44).

Table 3.44 Emissions from Other sources (CRF 1.A.5) in 1990–2013 (Gg)

CO2 CH4 N2O

Aggregate

GHGs

(CO2,

CH4,

N2O)

NOx CO NMVOC SO2

Gg Gg CO2

eq. Gg

1990 NE NE NE NE NE NE NE NE







149

CO2 CH4 N2O

Aggregate

GHGs

(CO2,

CH4,

N2O)

NOx CO NMVOC SO2

Gg Gg CO2

eq. Gg

1996 0.19 1.36E-06 5.45E-06 0.19 2.48E-04 0.07 1.18E-03 1.86E-05

1997 0.10 6.82E-07 2.73E-06 0.10 1.24E-04 0.04 5.89E-04 9.29E-06

1998 0.19 1.36E-06 5.45E-06 0.19 2.48E-04 0.07 1.18E-03 1.86E-05

1999 0.15 1.08E-06 4.31E-06 0.15 1.96E-04 0.06 9.30E-04 1.47E-05

2000 0.14 9.67E-07 3.87E-06 0.14 1.76E-04 0.05 8.35E-04 1.32E-05

2001 0.17 1.19E-06 4.75E-06 0.17 2.16E-04 0.06 1.03E-03 1.62E-05

2002 6.88 5.32E-04 1.87E-04 6.95 0.14 0.54 0.013 2.17E-03

2003 6.16 4.61E-04 1.68E-04 6.22 0.12 0.55 0.013 1.93E-03

2004 9.63 7.86E-04 2.61E-04 9.73 0.21 0.57 0.016 2.24E-03

2005 7.62 5.53E-04 2.08E-04 7.70 0.14 0.75 0.017 1.85E-03

2006 7.51 5.27E-04 2.05E-04 7.59 0.14 0.83 0.018 1.79E-03

2007 2.84 1.12E-04 7.85E-05 2.87 0.03 0.70 0.012 7.97E-04

2008 3.41 1.58E-04 9.40E-05 3.44 0.04 0.73 0.013 8.62E-04

2009 5.34 3.55E-04 1.46E-04 5.39 0.09 0.67 0.014 1.34E-03

2010 7.87 6.17E-04 2.14E-04 7.95 0.16 0.58 0.015 1.89E-03

2011 7.22 5.71E-04 1.96E-04 7.29 0.15 0.51 0.013 1.73E-03

2012 7.33 5.61E-04 1.99E-04 7.40 0.15 0.60 0.014 1.78E-03

2013 6.45 4.56E-04 1.76E-04 6.51 0.12 0.69 0.015 1.61E-03

Emissions from this sector are not influenced by the changes in national economy or in the economy of Latvia’s trade partners, but still the emissions are decreasing since 2004.

However, in the recent years until 2012 there has been an increase of fuel consumption, according to data given by CSB. In 2013 the GHG emissions decreased by 12% comparing

with 2012.


Methods

2006 IPCC Guidelines’ Tier 1 method was used to calculate GHG emissions from the 1.A.5.b Other Mobile source sector.

Calculation of all emissions from fuel combustion is done with Excel databases developed by experts from LEGMC.

The general method for preparing inventory data was used:

qBEFEm

where:






150

Default emission factors for direct GHGs from Military aircrafts are taken from 2006 IPCC

Guidelines, Volume 2, Chapter 3 Mobile combustion, Table 3.5.2 and Table 3.6.4 (Table 3.45).

Indirect GHGs emission factors were taken from EMEP/EEA 2013. Country specific

emission factors were used to calculate sulphur dioxide (SO2) emissions.

Table 3.45 CO2, CH4, N2O, NOx, NMVOC, CO emission factors22

CO2 CH4 N2O NOx NMVOC CO

Aviation gasoline 69.3 0.0005 0.002 4 19 1200

Diesel oil 74.1 0.007 0.002 78.5 2.8 7.4

Jet fuel 71.5 0.0005 0.002 4 19 1200


Uncertainty in activity data of fuel combustion in sectors CRF 1.A.5.b is ±2% in 2013 because official statistical information from CSB is used.

Emission factors used for emission estimation were taken from 2006 IPCC Guidelines. For

diesel oil the uncertainty for CO2 emission factor, according to these Guidelines, Volume 2, Chapter 3 Mobile combustion, Section 3.5.1.7, is 2%, but for CH4 and N2O it is much higher -

about 50%. For aviation gasoline and jet fuel, the uncertainty for CO2 emission factor, according to 2006 IPCC Guidelines, Volume 2, Chapter 3 Mobile combustion, Section 3.6.1.7, is 5%, but for CH4 and N2O it is assumed that the uncertainty is very high – 100%.


series.


All documentation and information received for inventory purposes are archived in FTP folder. All findings are documented by using check- lists, available on Regulations of the Cabinet of Ministers No. 217 adopted on 27 March 2012 ―The National Inventory System of

Greenhouse Gas Emission Units‖.


All sources of energy data are presented in the corresponding NIR chapter (3.2.8.2 Methodological issues) as well as disaggregated data at the finest level possible are presented in the corresponding Annex. Data completeness has been explained in the previous

subchapter.

Activity data have been checked at the data provider – Central Statistical Bureau, which has

its own internal QA/QC procedures based on mathematic model and analysis to avoid logic mistakes. When activity data have been received, the sectoral expert responsible for the emission estimation and reporting are comparing all data changes with the previous inventory,

and all changes are explained in the corresponding subchapter. All fluctuations or changes in NCVs are double checked and agreed with CSB.

All activity data used in Sectoral Approach are also compared with activity data used in Reference Approach estimations. All significant differences (±5%) are explained in the corresponding subchapter.

22

Units for GHGs are in Gg/PJ, for indirect GHGs in kg/Mg.


151


As all emission factors are taken from 2006 IPCC Guidelines, no additional verification procedures have been performed.

Emission verification

To verify the CO2 emissions, logical mistakes are checked by checking the time series of the activity data, emission factors and emissions consistency to display all significant and

illogical changes in the activity data and emissions. The emissions for indirect GHGs in the database are cross-checked with emissions reported within CLRTAP for verification purposes.

CO2 emissions are compared with emissions in Reference Approach estimations, and a ll significant differences (±5%) are explained in the corresponding subchapter.



3.3 FUGITIVE EMISSIONS FROM SOLID FUELS AND OIL AND NATURAL GAS (CRF 1.B)

Under the 1.B Fugitive emissions category CO2, CH4 and NMVOC emissions from operations

with natural gas and light liquid fuels are reported (Table 3.46).

Table 3.46 Reported fugitive CO2, CH4, NMVOC emissions in Latvia in 1990-2013 (Gg)

CO2 CH4

Aggregate GHGs

(CO2, CH4) NMVOC

Gg Gg Gg CO2 eq. Gg

1990 0.0115 9.90 247.59 4.18

1991 0.0111 9.54 238.49 3.88

1992 0.0101 8.70 217.43 3.59

1993 0.0097 8.32 207.94 3.45

1994 0.0094 8.13 203.20 3.35

1995 0.0092 7.92 197.89 3.19

1996 0.0089 7.63 190.68 3.10

1997 0.0083 7.12 177.96 2.88

1998 0.0079 6.83 170.75 2.75

1999 0.0076 6.51 162.79 2.63

2000 0.0070 6.03 150.64 2.48

2001 0.0073 5.84 146.09 2.47

2002 0.0074 6.10 152.57 2.52

2003 0.0055 4.76 119.08 2.12

2004 0.0055 4.71 117.87 2.11

2005 0.0062 5.33 133.19 2.28

2006 0.0044 3.82 95.53 1.91

2007 0.0046 3.92 98.07 2.72

2008 0.0047 4.03 100.70 2.50

2009 0.0044 3.81 95.13 2.44


152

CO2 CH4

Aggregate GHGs

(CO2, CH4) NMVOC

Gg Gg Gg CO2 eq. Gg

2010 0.0043 3.66 91.61 2.35

2011 0.0044 2.52 63.03 1.40

2012 0.0049 3.18 79.61 1.44

2013 0.0080 4.04 101.01 1.71

It is possible to get data from hard coal transportation via railways but it is assumed that no GHG emissions are generated during this activity. Only particulate matters emissions are

estimated from coal transportation in Latvia.

There are lasting peat mining and manufacturing traditions in Latvia. As stated in 2006 IPCC

Guidelines, Volume 4 Agriculture, Forestry and Other Land Use, Chapter 1 Introduction, with current state of scientific knowledge, it is possible to provide methods for estimating CO2 and N2O emissions associated with management of peatlands, and CO2 from conversion

to wetlands by flooding. However, according to 2006 IPCC Guidelines, Volume 4, Chapter 7 Wetlands, all on-site sources of greenhouse gas emissions should be reported under AFOLU

Wetlands category regardless of the end-use of peat.

There are no coal mines in Latvia and therefore no fugitive emissions from mining processes occur.

3.3.1 Fugitive emission from oil (CRF 1.B.2.a)


CRF sector 1.B.2.a Oil includes NMVOC emissions from refined oil products storage and

distribution. There are no oil refineries in Latvia; therefore NMVOC emissions from gasoline distribution only were calculated for 1990–2013.

Figure 3.41 Fugitive NMVOC emissions from oil products in 1990–2013 and retail price for gasoline in

1996-2013

Decrease of NMVOC emissions in whole time series can be generally explained with

increasing costs of gasoline therefore it was used less. In 2005-2007 there can be seen a rise in


153

emissions which can be explained with economic growth and prosperity, however, in 2008

due to global crisis, the use of gasoline, as well as NMVOC emissions decreased, and continued to decrease after that because of rapid increase in retail price. Since 1990 the NMVOC emissions have decreased by 65%.


Methods

EMEP/EEA 2013 Tier 1 methodology is used to estimate fugitive NMVOC emissions from operations with gasoline in 1990–2013. It uses the general equation, where emissions are

obtained by multiplying the total amount of gasoline sold with the emission factor.

Emission factors

NMVOC emission factor – 2 kg/Mg oil – for emission from gasoline distribution was taken

from EMEP/EEA 2013, Chapter 1.B.2.a.v Distribution of oil products, Table 3-1.

Activity data

Activity data for NMVOC emission calculation was used from CSB Energy Balance (Table 3.47).

Table 3.47 Activity data used for NMVOC emission calculation in 1990–2013 (PJ)

1990 26.796

1991 22.616

1992 21.692

1993 21.032

1994 20.108

1995 18.128

1996 17.908

1997 16.456

1998 15.400

1999 14.872

2000 14.831

2001 15.535

2002 15.228

2003 15.214

2004 15.346

2005 15.126

2006 16.753

2007 18.299

2008 16.672

2009 13.941

2010 12.667

2011 11.926

2012 10.146

2013 9.282


154


Activity data for fugitive emissions from operations with gasoline were taken from CSB and uncertainty was assumed as very low for about 2% as statistical frame mistake. Uncertainty

for emission factor is assumed as 100%, according to 2006 IPCC Guidelines, Vo lume 2, Chapter 4 Fugitive emissions, Table 4.2 (refined product distribution).

Time series of the NMVOC emissions are consistent for whole time series, where amounts of gasoline sold are taken from CSB online database, and emission factors – from EMEP/EEA 2013 Guidelines.

Time series of the estimated emissions are consistent and complete because the same methodology emission factors and data sources are used for sectors for all years in time series. Emissions from all sectors are estimated or reported as not occurring / not applicable therefore

there are no ―not estimated‖ sectors.





All sources of energy data are presented in the corresponding NIR chap ter (3.2.8.2 Methodological issues) as well as disaggregated data at the finest level possible are presented


Activity data have been checked at the data provider – Central Statistical Bureau, which has its own internal QA/QC procedures based on mathematic model and analysis to avoid logic mistakes. When activity data have been received, the sectoral expert respo nsible for the




As all emission factors are taken from EMEP/EEA 2013, no additional verification

procedures have been performed.

Emission verification

To verify the NMVOC emissions, logical mistakes are checked by checking the time series of the activity data, emission factors and emissions consistency to display all significant and illogical changes in the activity data and emissions. The emissions are also cross-checked

with emissions reported within CLRTAP for verification purposes.




155

3.3.2 Fugitive emissions from natural gas (CRF 1.B.2.b, CRF 1.B.2.c, CRF

1.B.2.d)


CO2, CH4 and NMVOC emissions from operations with natural gas a re reported in the following sub-sectors CRF 1.B.2.b Natural gas sector:

1.B.2.b.i Venting;

1.B.2.b.iii All other:

• 1.B.2.b.iii 4 Transmission and storage; • 1.B.2.b.iii 5 Distribution; • 1.B.2.b.iii 6 Other (includes leakage at industrial plants and power stations and

leakage at residential and commercial sectors) •

Table 3.48 Fugitive CH4, CO2 and NMVOC emissions from natural gas 1990-2013 (Gg)

CO2 CH4

Aggregate GHGs

(CO2, CH4) NMVOC

Gg Gg Gg CO2 eq. Gg

1990 0.0115 9.90 247.59 2.97

1991 0.0111 9.54 238.49 2.86

1992 0.0101 8.70 217.43 2.60

1993 0.0097 8.32 207.94 2.49

1994 0.0094 8.13 203.20 2.43

1995 0.0092 7.92 197.89 2.37

1996 0.0089 7.63 190.68 2.28

1997 0.0083 7.12 177.96 2.13

1998 0.0079 6.83 170.75 2.05

1999 0.0076 6.51 162.79 1.95

2000 0.0070 6.03 150.64 1.80

2001 0.0073 5.84 146.09 1.76

2002 0.0074 6.10 152.57 1.83

2003 0.0055 4.76 119.08 1.43

2004 0.0055 4.71 117.87 1.41

2005 0.0062 5.33 133.19 1.60

2006 0.0044 3.82 95.53 1.14

2007 0.0046 3.92 98.07 1.89

2008 0.0047 4.03 100.70 1.74

2009 0.0044 3.81 95.13 1.81

2010 0.0043 3.66 91.61 1.77

2011 0.0044 2.52 63.03 0.86

2012 0.0049 3.18 79.61 0.98

2013 0.0080 4.04 101.01 1.28

The emissions have a decreasing trend in 1990-2013 with the reduction of GHGs by 59%. There are few years where the emissions increased, and in all cases the increase is related with repair works and modernisation of existing pipeline system. In 2013, there can be seen a rise

in emissions by 10% comparing with 2012, and it also can be explained with repair works in pipeline system. However, a detailed information about length of pipelines, materials used for

the distribution network, pressure conditions, flow rates etc. is not possible to obtain due to


156

confidentiality issues because ―Latvijas Gāze‖ is the only company in Latvia which

distributes natural gas.


Methods

LEGMC are receiving data about CH4 emissions from the natural gas holding company

―Latvijas Gāze‖ for the time period 1990–2013, Consequently company ―Latvijas Gāze‖ calculates emissions by itself, using data of natural gas density and other physical parameters, and measures the content of methane and other chemical compounds in natural gas, therefore

it is assumed as Tier 2 method, using country-specific data and calculations.

LEGMC has methodological material, which describes how the amounts of natural gas leaked are calculated. The methodology is translated in English and a brief essence of methods is

available on Annex 3.

Activity data

CH4 emissions are obtained from the holding company ―Latvijas Gāze‖ and the activity data (millions m3) are provided in Table 3.44 below.

Table 3.49 Amounts of natural gas leaked in 1990-2013 (106 m3)

1.B.2.b.i

Venting

1.B.2.b.iii 4

Transmission

and storage

1.B.2.b.iii 5

Distribution

1.B.2.b.iii 6

Other Total

1990 5.61 0.13 0.69 12.44 18.87

1991 5.38 0.13 0.69 11.98 18.17

1992 4.83 0.13 0.59 10.92 16.47

1993 4.58 0.13 0.69 10.44 15.85

1994 4.46 0.13 0.69 10.21 15.48

1995 4.32 0.13 0.69 9.94 15.08

1996 4.13 0.13 0.69 9.58 14.53

1997 3.80 0.13 0.69 8.94 13.56

1998 3.63 0.11 0.69 8.58 13.01

1999 3.42 0.11 0.69 8.18 12.40

2000 3.11 0.11 0.69 7.57 11.48

2001 0.30 0.10 0.69 10.03 11.14

2002 0.98 0.10 0.69 9.86 11.63

2003 1.09 0.10 0.69 7.20 9.07

2004 1.56 0.09 0.69 6.63 8.98

2005 3.25 0.09 0.69 6.12 10.15

2006 1.80 0.08 0.69 4.71 7.28

2007 1.76 0.07 0.69 4.95 7.47

2008 2.44 0.07 0.69 4.48 7.67

2009 1.78 0.06 0.69 4.71 7.25

2010 1.64 0.06 0.69 4.59 6.98

2011 1.77 0.05 0.69 1.70 4.21

2012 1.34 0.05 0.69 3.35 5.43

2013 1.09 0.04 0.69 4.06 5.89


157


The level of uncertainty was determined by natural gas distributing company „Latvijas Gāze‖. The uncertainty both for activity data (gas amounts) and CH4, CO2 and NMVOC emissions

from gas venting and natural gas leakages in gas distribution and transmission systems, as well as in gas storage facility is assigned as quite low – 10%, as these were estimated by only

enterprise operated with natural gas in Latvia – ―Latvijas Gāze‖ by methodology developed for enterprise. However, for other leakage (CRF 1.B.2.b.iii 6) the uncertainty for the emissions is assumed as 35%.

Emissions from all sectors are estimated or reported as not occurring / not applicable therefore there are no ―not estimated‖ sectors.


―Latvijas Gāze‖, that reports fugitive CH4 emissions from the operations with natural gas,

estimates CH4 and CO2 emissions according to methodology prepared especially for the organization that is internationally verified and approved by the Environment State Bureau. Underground storage ―Inčukalns‖ also has an ISO standard and all the information obtaining

procedures are controlled and verified.



3.4 CO2 TRANSPORT AND STORAGE (CRF 1.C)

There is no CO2 captured and further storaged in Latvia. There is a research done to find the potential sites for CO2 geological storage in Latvia within international project ―Assessing European Capacity for Geological Storage of Carbon Dioxide‖ (EU GeoCapacity) 23,24. Latvia

has a storage potential in local structures in the Cambrian water-saturated sandstone. In one of such geological structures, an underground storage of natural gas was established already in

1968 – the Inčukalns natural gas storage. For modelling the potential costs, the largest CO 2 source in Latvia in 2005 from EU ETS was taken, and as potential storages were selected the two largest ones. The modelling results demonstrated that the efficiency of the establishment

of CO2 storages there is too low. The unsatisfactory results are associated with the inefficient injection of small volumes of CO2 in the storages, and the cost of the establishment of

infrastructure is quite high, and the expenditure is unfounded with the low level of CO 2 injection.

3.5 REFERENCES

2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 2 Energy:

• Chapter 2 Stationary combustion;

• Chapter 3 Mobile combustion; • Chapter 4 Fugitive emissions.

23

http://www.co2geonet.com/NewsData.aspx?IdNews=44&ViewType=Old&IdType=18

24 http://meteo.lv/fs/CKFinderJava/userfiles/files/Geologija/Potential%20sites.pdf


158

2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4

Agriculture, Forestry and Other Land Use :

• Chapter 1 Introduction;

• Chapter 4 Wetlands.

EMEP/EEA air pollutant emission inventory guidebook 2013, Part B: sectoral

guidance, Volume 1 Energy, 1A Combustion, 1B Fugitive emissions from fuels:

• 1.A.1 Energy industries; • 1.A.2 Manufacturing industries and construction;

• 1.A.3.a Aviation; • 1.A.3.d Navigation (shipping);

• 1.A.4 Small combustion; • 1.A.4 Non-road mobile sources and machinery; • 1.B.2.a.v Distribution of oil products;

EMEP/EEA air pollutant emission inventory guidebook 2013, Part B: sectoral guidance, Volume 5 Waste:

• 5.C.1.a Municipal waste incineration; • 5.C.1.b Industrial waste incineration including hazardous waste and sewage

sludge.

Metodiskie norādījumi CO2 emisiju noteikšanai, izstrādāti, ievērojot ANO Vispārējās konvencijas ―Par klimata pārmaiņām‖, Klimata pārmaiņu starpvaldību padomes

(IPCC) rekomendācijas un Latvijā pielietotā kurināmā fizikālās īpašības. Riga, 2004.

Физико-химические свойства природного газа: http://dolgikh.com/index/0-31

CSB. Annual Eurostat Energy Questionnaire, 2014.

Annual Energy data, CSB, 2014:

http://data.csb.gov.lv/pxweb/lv/vide/vide__ikgad__energetika/?tablelist=true&rxid=cdcb978c-22b0-416a-aacc-aa650d3e2ce0

EU ETS data:

• 2005-2007: http://www.meteo.lv/lapas/uznemumi-kuriem-izsniegtas-

siltumnicefekta-gazu-emisijas-atlaujas-?id=1255&nid=574 • 2008.-2012: http://www.meteo.lv/lapas/uznemumi-kuriem-izsniegtas-

siltumnicefekta-gazu-emisijas-atlaujas-2-pe?id=1253&nid=575

• 2013-2020: http://www.vvd.gov.lv/atlaujas-un- licences/seg-atlaujas/

Average temperature data in 1990-2013, LEGMC.

Average retail prices of selected commodity (gasoline): http://data.csb.gov.lv/pxweb/en/ekfin/ekfin__ikgad__PCI/PC0030_euro.px/table/table

ViewLayout1/?rxid=cdcb978c-22b0-416a-aacc-aa650d3e2ce0

Nulle, U., Nulle, I. Potential sites for CO2 geological storage in Latvia. LEGMC.

Available on: http://meteo.lv/fs/CKFinderJava/userfiles/files/Geologija/Potential%20sites.pdf

CO2GeoNet brochure "What does CO2 geological storage really mean?" :

http://www.co2geonet.com/NewsData.aspx?IdNews=44&ViewType=Old&IdType=18, http://www.co2geonet.com/UserFiles/file/Rowena/Latvia_final%20protected.pdf

http://dolgikh.com/index/0-31



http://www.meteo.lv/lapas/uznemumi-kuriem-izsniegtas-siltumnicefekta-gazu-emisijas-atlaujas-?id=1255&nid=574

http://www.meteo.lv/lapas/uznemumi-kuriem-izsniegtas-siltumnicefekta-gazu-emisijas-atlaujas-?id=1255&nid=574

http://www.meteo.lv/lapas/uznemumi-kuriem-izsniegtas-siltumnicefekta-gazu-emisijas-atlaujas-2-pe?id=1253&nid=575


http://www.vvd.gov.lv/atlaujas-un-licences/seg-atlaujas/

http://data.csb.gov.lv/pxweb/en/ekfin/ekfin__ikgad__PCI/PC0030_euro.px/table/tableViewLayout1/?rxid=cdcb978c-22b0-416a-aacc-aa650d3e2ce0

http://data.csb.gov.lv/pxweb/en/ekfin/ekfin__ikgad__PCI/PC0030_euro.px/table/tableViewLayout1/?rxid=cdcb978c-22b0-416a-aacc-aa650d3e2ce0

http://meteo.lv/fs/CKFinderJava/userfiles/files/Geologija/Potential%20sites.pdf

http://www.co2geonet.com/NewsData.aspx?IdNews=44&ViewType=Old&IdType=18

http://www.co2geonet.com/UserFiles/file/Rowena/Latvia_final%20protected.pdf


159

4. INDUSTRIAL PROCESSES AND PRODUCT USE (CRF 2)


Sources of emissions from Industrial Processes and Product Use are shown in Table 4.1.

Mineral Products (CRF 2.A)

o Cement Production (clinker production) (CRF 2.A.1) o Lime Production (as non-marketed lime for steel production in Iron & Steel

production plant) and limestone and dolomite use in lime production (CRF

2.A.2) o Glass Production (CRF 2.A.3)

Raw materials use in glass production – potash, fluorspar and witherite; Limestone and dolomite use in glass production; NMVOCs and indirect CO2 from glass fibre production;

Soda ash use in glass production. o Other Process Uses of Carbonates (CRF 2.A.4)

Ceramics (Bricks and tiles production) (CRF 2.A.4.a) Other ( reported NOx and NMVOC emissions from clinker production)

(CRF 2.A.4.d)

Metal Production (CRF 2.C) o Iron and Steel Production (CRF 2.C.1)

CO2 emissions from use of crude iron as raw material; CH4 and indirect GHG emissions from total iron and steel production; CO2 emissions from limestone and dolomite use in steel production;

Non-energy products from fuels and solvent use (CRF 2.D) o Lubricant Use (CRF 2.D.1)

o Paraffin Wax Use (CRF 2.D.2) o Other (CRF 2.D.3)

Solvent use; Road paving with asphalt; Asphalt roofing;

Urea use;

Other Production (CRF 2.H)

NMVOC emissions from food and drink production (2.H.1): CO2 emissions from limestone use in sugar production for time period

2005-2006 (2.H.1); SO2 emissions from Pulp and Paper production for time period 1990 –

1996 (2.H.2);

Product uses as ODS substitutes (CRF 2.F) o Refrigeration and Air Conditioning (CRF 2.F.1)

Commercial Refrigeration (CRF 2.F.1.a) Domestic Refrigeration (CRF 2.F.1.b) Industrial Refrigeration (CRF 2.F.1.c)

Transport Refrigeration (CRF 2.F.1.d) Mobile Air-Conditioning (CRF 2.F.1.e)

o Foam Blowing Agents (CRF 2.F.2) Closed Cells (CRF 2.F.2.a)

o Fire Protection (CRF 2.F.3)

o Aerosols (CRF 2.F.4) Metered Dose Inhalers (CRF 2.F.4.a)


160

Other product manufacture and use (CRF 2.G)

o Electrical Equipment (CRF 2.G.1) o N2O From Product Uses (CRF 2.G.3)

o Other (CRF 2.G.4) Production of Shoes

Emissions from the Chemical Industry (CRF 2.B), Electronics Industry (CRF 2.E) and Other

(CRF 2.H) sectors are not occurring in Latvia. Indirect CO2 emissions were estimated from NMVOC emissions in glass fibre production and

Solvent use sub-sector and reported directly in table CRF 2.Industrial Processes and Product use.

Table 4.1 Reported GHG emissions from Industrial Processes and Product Use sector in Latvia in 2013

Source Emissions

CO2 CH4 N2O HFCs PFCs SF6 NF3 NOx CO NMVOC SO2

2.A Mineral Products

1. Cement Production √ √ √ √ √

2. Lime Production √ NE NE NE NE NE NE

3. Glass Production √ NE NE √ NE

Production of Glass (Use of

fluorspar) √ NE NE

NE NE NE NE

Production of Glass (Use of potash)

NO NO NO

NO NO NO NO

Production of Glass (Use of white rite)

NO NO NO

NO NO NO NO

Production of Glass Fibre √ NE NE NE NE √ NE

4.Other Process Uses of Carbonates

4.a Ceramics

Production of bricks √ NE/NO NE/NO NE/NO NE/NO NE/NO NE/NO

Production of t iles √ NE NE NE NE NE NE

B. Chemical Industry

1. Ammonia Production NO NO NO NO NO NO NO

2. Nitric Acid Production NO NO

3. Adipic Acid Production NO NO NO NO NO

4.Caprolactam, Glyoxal and Glyoxylic Acid Production

NO NO NO

NO NO

5. Carbide Production NO NO NO NO NO NO NO

6.Titanium Dioxide Production NO NO NO NO NO NO NO

7. Soda Ash Production NO NO NO NO NO NO

8. Petrochemical and Carbon Black Production

NO NO

NO NO NO NO

9.Fluorochemical Production NO NO NO NO NO NO NO NO NO NO

10.Other NO NO NO NO NO NO

C. Metal Production

1. Iron and Steel Production √ NO NA √ √ √ √

2. Ferroalloys Production NO NO NO NO NO NO NO

3. Aluminium Production NO NO NO NO NO NO NO NO

4. Magnesium Production NO NO NO NO NO NO NO NO NO NO NO

5.Lead Production NO NO NO NO NO NO NO

6.Zinc Production NO NO NO NO NO NO NO

7.Other NO NO NO NO NO NO NO

D. Non-energy Products from Fuels and Solvent Use

1.Lubricant Use √

2. Paraffin Wax Use √

3. Other

Solvent Use √ √

Road paving with asphalt √ NE NE √ NE

Asphalt roofing √ NE √ √ NA


161

Source Emissions

CO2 CH4 N2O HFCs PFCs SF6 NF3 NOx CO NMVOC SO2

Urea use √ NA NA NA NA

E. Electronics Industry

1. Integrated Circuit or Semiconductor

NO NO NO NO

2. TFT Flat Panel Display NO NO NO NO

3. Photovoltaics NO NO NO NO

4. Heat Transfer Fluid

5. Other NO NO NO NO

F. Product Uses as ODS Substitutes

1 Refrigeration and Air Conditioning

√ NO

2. Foam Blowing Agents (Closed Cells)

√ NO

3. Fire Protection √ NO

4. Aerosols ( Metered Dose Inhalers)

√ NO

5. Solvents NO NO

6. Other applications

NO NO

G. Other Product Manufacture and Use

1. Electrical Equipment √ NO

2. SF6 and PFCs from Other

Product Use NO NO

3. N2O from Product Uses (Medical Applications)

√

4. Other (Production of Shoes) √

H. Other

1.Pulp & Paper NO NO NO NO NO NO NO

2.Food and beverages industry NA NA NA NA NA √ NA

4.1.1 Description

Industrial processes GHG emissions contribute 6.1% of the total anthropogenic GHG

emissions in Latvia in 2013. The most important emission source of the Industrial Processes and Product use in 2013 is CO2 emissions from Mineral products and HFCs emissions from

Consumption of halocarbons and SF6.

Table 4.2 Greenhouse gas emission trend in 1990–2013 (Gg CO2 eq)

Year Total 2.A Mineral Products

2.C Metal Production

2.D Non-

Energy Products from Fuels and

Solvent

2.F

Product Uses as ODS Substitutes

2.G Other Product Manufacture and Use 2.H. Other

Gg CO2 eq

CO2 CO2 CH4 CO2 HFCs HFCs SF6 N2O CO2

1990 602.66 589,20 12,82 0,07 0,58 NO, NE NO, NA, NE NO, NA, NE 0,005 NO, NA

1991 527,15 518,03 8,70 0,05 0,37 NO, NE NO, NA, NE NO, NA, NE 0,005 NO, NA




1995 151,77 146,11 4,43 0,03 0,35 0,27 0,40 0,17 0,004 NO, NA

1996 163,59 158,69 3,48 0,04 0,36 0,41 0,42 0,18 0,005 NO, NA


162

Year Total 2.A Mineral Products

2.C Metal Production

2.D Non-

Energy Products from Fuels and

Solvent

2.F

Product Uses as ODS Substitutes

2.G Other Product Manufacture and Use 2.H. Other

Gg CO2 eq

CO2 CO2 CH4 CO2 HFCs HFCs SF6 N2O CO2

1997 170,11 159,31 7,99 0,06 0,33 1,59 0,45 0,37 0,005 NO, NA

1998 172,92 160,38 8,50 0,06 0,38 2,58 0,50 0,52 0,004 NO, NA

1999 205,67 193,30 7,71 0,06 0,39 3,26 0,23 0,71 0,004 NO, NA

2000 158,61 143,39 8,42 0,06 0,39 4,69 0,78 0,88 0,003 NO, NA

2001 181,79 163,77 8,04 0,06 0,39 6,62 1,52 1,39 0,008 NO, NA

2002 195,76 174,47 7,60 0,06 0,40 8,63 1,97 2,62 0,006 NO, NA

2003 211,11 182,32 12,16 0,07 0,43 11,00 2,37 2,76 0,006 NO, NA

2004 229,35 194,36 12,90 0,07 0,73 14,88 3,15 3,25 0,006 NO, NA

2005 229,46 183,31 12,35 0,07 0,59 20,91 3,60 3,78 0,003 4,85

2006 277,19 212,83 12,56 0,07 0,69 38,18 4,04 4,07 0,011 4,73

2007 301,50 218,10 14,57 0,07 1,01 58,13 5,06 4,55 0,004 NO, NA

2008 309,45 214,80 8,73 0,07 1,06 73,75 5,81 5,23 0,004 NO, NA

2009 304,85 203,91 9,56 0,06 0,86 77,73 5,41 7,33 0,004 NO, NA

2010 566,74 467,36 11,28 0,07 1,00 73,49 6,19 7,35 0,004 NO, NA

2011 658,90 567,56 0,72 0,02 1,02 77,59 4,51 7,47 0,005 NO, NA

2012 688,14 585,36 2,87 0,10 1,06 88,34 2,62 7,78 0,005 NO, NA

2013 668.97 549.95 0,96 0,02 1,08 106,62 1,84 8,50 0,005 NO, NA

Data on emissions in the Industrial Processes and Product Use sector are linked with the

economic situation of the country as well as availability of statistical data. The largest decrease in emissions occurred between 1990 and 1993 (Figure 4.1, Table 4.2) when industry

was going through a crisis.

It has to be noted that in the beginning of 90ties during the countrywide change in government system and national economy statistics was not well kept. Therefore there is lack

of statistical data regarding industry during this time period or they are vague. The data extrapolation was carried out for the sectors where possible although the extrapolation is

almost impossible to do due to different circumstances – changes and total restructuring of national economy when industrial development wasn’t predictable and explainable.

Since year 2000 and after the crisis in national economy of Russian Federation in 1999-2000

with whom Latvia has strength economic relations, GHG emissions fro m Industrial Processes sector have increased by 90.01% in 2000-2007. It is explained with sharp development of

Latvian industry when construction activities increased and industrial production of building materials also increased.


163

Figure 4.1 GHG emissions from Industrial Processes and Product Use in 1990–2013

(Gg CO2 eq.)

4.2 MINERAL INDUSTRY (CRF 2.A)

4.2.1 Source category description

2.A Mineral Products sector is main source of GHG emissions in Industrial Processes and Product Use sector. At the moment the most important for non-energy CO2 emission sources from Mineral products sector are cement, limestone use in glass and metal production and

lime production.

CO2 emissions are strongly influenced by economic situation in country. Emission curve

reflects economic crisis in time period 1991–1993 after changes in national economy in country when significant amount of industrial producers stop their activities and large former Soviet Union market broke down (Table 4.3). Also radical decreases of CO2 emissions from

1999 to 2000 are influenced by economic crisis in neighbourhood Russian Federation with whom Latvia had strong foreign trade linkage.

Table 4.3 Emissions from 2.A Mineral Products in 1990–2013 (Gg)

CO2

NOx CO NMVOC SO2 2.A 2.A.1 2.A.2 2.A.3 2.A.4.a

1990 589.198 370.804 148.857 0.352 69.185 0.902 NO,NA,NE 0.154 3.409

1995 146.111 91.068 40.660 3.399 10.984 0.237 NO,NA,NE 0.040 0.896

2000 143.387 86.334 36.848 5.813 14.391 0.226 NO,NA,NE 0.038 0.853

2005 183.312 134.456 32.223 5.675 10.958 0.358 NO,NA,NE 0.061 1.354

2006 212.832 168.588 30.371 2.673 11.201 0.446 NO,NA,NE 0.076 1.686

2007 218.102 170.734 30.210 4.398 12.761 0.457 NO,NA,NE 0.078 1.725


164

CO2

NOx CO NMVOC SO2 2.A 2.A.1 2.A.2 2.A.3 2.A.4.a

2008 214.797 167.479 28.424 3.992 14.902 0.452 NO,NA,NE 0.077 1.706

2009 203.907 176.178 21.795 2.576 3.358 0.549 NO,NA,NE 0.030 1.739

2010 467.363 428.873 28.592 4.433 5.465 0.483 0.805 0.008 0.070

2011 567.558 555.135 0.661 4.280 7.481 0.934 1.731 0.011 0.374

2012 585.356 572.334 1.761 3.730 7.531 1.464 3.506 0.011 0.321

2013 549.946 537.644 0.275 2.977 9.865 1.497 2.580 0.011 0.167

Due to Latvia’s economical features since 2007–2008 the industry development was slowing down as the financing and real estate sectors started dominating in national economy. In 2009-2010 emissions from 2.A.1 Cement production increased as cement production plant

switched the production technology and installations and increased its capacity by approximately 2.4 times. In 2013 there are decreased produced amount of clinker about

6.57%. Under sector 2.A Mineral products there are included NMVOC emissions from glass fibre production. Also SO2, NOx and NMVOC emissions from cement production are reported. Indirect CO2 emissions were estimated from NMVOC emissions in 2.A.3 sector

from glass fibre production. NOx, CO and NMVOC emissions from cement production are reported in 2.A.4.d Other sector due to structure of CRF Reporter software when it is not

possible to report NOx, CO and NMVOC emissions in 2.A.1 Cement Production sector.

4.2.2 Cement Production (CRF 2.A.1)


CO2, NOx, NMVOC and SO2 emissions are estimated for Cement production sector. The emission curve represent the total situation in national economy when the big decrease happened in the beginning of the 90ties due to changes in national economy, domestic market

and production demand. CO2 emissions had decreased by 95.57% in 1990-1993. Increase of emissions in 2000-2007 about 97.76 % represents the development of construction sector and

development of external market. Still in 2009 new production plant with dry process kiln production technology was erected and the old one where the wet process kiln technology was used was closed in the middle of the year. And as the old production plant was set to closing

no active cement kiln dust recovery occurred and all cement kiln dust was collected and transported to landfill for storage. Therefore amount of cement kiln dust and CKD/clinker

ratio increased sharply in 2009-2013 that affected CO2 (Figure 4.2).


165

Figure 4.2 Emissions from Cement production in 1990–2013 (Gg)

All emissions except NMVOC increased in 2008-2009 when CO2 increased by 5.19%, SO2 –

by 1.95%. NOx emissions increased quite sharp by 21.51% that is explained with the emission factor of NOx for new production plant using dry process kiln that is higher than emission factor for NOx in old production plant using wet technology. NMVOC emissions decreased

by 61.22% that is also explained with the emission factor for new production plant that is lower than for the old production plant’s wet kiln process technology.

Starting from 2010 fully dry process kiln is used in cement production. For 2009 both kiln processes- dry and wet was used in cement production. Previously (1990 – 2009 partly) only wet process kiln was used in cement production. Due to increasing activity for cement clinker

production in 2010 there are obviously decreased amount of SOx emissions. From year 2009 to 2010 SOx emissions are decreased about 95.95% due to changing technology of cement

clinker production from wet to dry process kiln. As resources there are used tyres a nd lube oil which consists sulphur compounds, all necessary for producing clinker. NOx are decreased about 11.98% but these data are not representative due to new technology started to work with

full capacity only in July on 2nd half of year 2010 and fully in 2011. Starting with 2010 there are increased emissions from 2.A.1 sector due to increasing of activity in cement production

comparing with previous years. CO2 emissions for time period 2009-2012 are increased about 166% due to new technology were active. In 2013 there are decreased produced clinker amount about 6.57% and CO2 emissions about 6.06%. Production of cement clinker is

depending on the demand in internal and external market.


Methods

Tier 2 method from 2006 IPCC Guidelines was used to estimate clinker production data from

final cement production amount when clinker / cement ratio for different types of cement is known as well as for CO2 emission factor and emission estimation. CO2 emissions from clinker production are estimated using following equation from 2006 IPCC Guidelines

equation 2.225 :

CO2 Emissions= Mcl ×EFcl × CFckd

where:

CO2 Emissions- emissions of CO2 from cement production, tonnes

25 http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol3.html, Mineral industry emissions, p 2.9

http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol3.html


166

Mcl – weight (mass) of clinker produced, tonnes

EFcl – emission factor for clinker, tonnes CO2 /tonne clinker. This clinker emission factor (EFcl ) is not corrected

for CKD.

CFckd – emissions correction factor for CKD, dimensionless

Tier 2 approach from EMEP/CORINAIR 2007 was used to calculate NOx, NMVOC, SO 2 emissions from cement production taking into account produced amount of clinker in wet and dry process kiln and technology based EFs.

Emission factors

CO2 emission factor

CO2 emission factor is calculated for all years in time series 1990–2013 according to CaO content in used limestone that is measured in laboratory of cement production facility (Table 4.4). LEGMC is able to use all laboratory measurements data from cement production plant

even if it is not accredited and certified as requested in EU ETS MRG so CaO content in limestone is available to estimate CO2 emission factor for clinker. These emission factors will

correspond to Tier 2 emission factor estimations from 2006 IPCC Guidelines as CO2 emissions from Cement Production sector.

CO2 emission factor is calculated using equation 2.4 from 2006 IPCC Guidelines 26 taken into

account country-specific data on CaO content of clinker and the fraction of CaO that was derived from a carbonate source (generally CaCO3):

EFclc = (0.785 × CaO content)×CKDcorrection

where:

EFclc – clinker production EF (Gg/Gg)

0.785 – molecular weight ration of CO2 to CaO in the raw material (CaCO3)

CaO – CaO content (weight fraction) in produced clinker (%)

CKDcorrection – correction factor for cement kiln dust

CKD correction factor is calculated using equation 2.5 from 2006 IPCC Guidelines:

CFckd =1+(Md/Mcl)×Cd×Fd×(EFc/EFcl)

where:

CFckd- emissions correction factor for CKD, d imensionless

Md- weight of CKD not recycled to the kiln, tonnes

Mcl- weight of clinker produced, tonnes

Cd- fraction of original carbonate in the CKD (i.e., before calcination), fract ion

Fd – fraction calcination of the orig inal carbonate in the CKD, fraction

EFc – emission factor for the carbonate (2006 IPCC Guidelines Chapter 2 Table 2.1), tonnes CO2 /tonne

carbonate

EFcl -emission factor for clinker uncorrected for CKD ( i.e., 0.51 tonnes CO2/ tonne clinker), tonnes CO2/ tonne

clinker

26

http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol3.html , Mineral industry emissions ,p 2.12



167

Table 4.4 Average CaO content in clinker (% ) and average CO2 emission factor in 1990–2013 (t CO2 / t

clinker)

Average

CaO

content

(%)

CO2 EF

without

CKD

factor

CKD

correction

factor

CO2 EF

with CKD

factor

1990 64.60 0.507 1.094 0.555

1995 64.06 0.503 1.031 0.518

2000 64.41 0.506 1.021 0.516

2005 64.41 0.506 1.002 0.507

2006 64.75 0.508 1.003 0.510

2007 64.06 0.503 1.004 0.505

2008 63.72 0.500 1.001 0.501

2009 65.27 0.512 1.008 0.517

2010 65.24 0.512 1.003 0.514

2011 64.34 0.505 1.004 0.507

2012 64.30 0.505 1.004 0.507

2013 64.65 0.508 1.004 0.510

For year 1996–2005 average CaO content data of years 1995 and 2006 was used in emissions

calculation since data for average CaO content in produced clinker for years 1996–2003 was not available in cement production plant. Also information from plant that average CaO content of years where data is available could be used was received.

CaO content data are requested to cement production plant. CO2 emission factor is used according to information on CaO content in produced clinker provided by plant.

Indirect GHG emission factors

As the EFs for NOx, NMVOC and SO2 are not available in EMEP/EEA 201327 (marked as ―Not Estimated‖) the EFs from EMEP/CORINAIR 2007 28 were used as these emissions are

emitted in the production according to cement production plant. Till 2010 the EFs were divided for dry and wet process kiln used (Table 4.5). Starting with 2010 there are reported

NOx and SO2 emissions as plant-specific data that are detected automatically from dry process production plant. Only NMVOC emissions are estimated using provided EFs below taken from EMEP/CORINAIR 2007 mentioned in (Table 4.5) for both technologies.

Table 4.5 EFs for cement clinker production emission estimation (Gg/Gg)

NOx NMVOC SO2

wet process kiln 0.00135 0.00023 0.0051

dry process kiln 0.00175 0.00001 0.0051

Activity data

The produced clinker is not weighted in cement production plant but produced clinker is estimated from final produced amount of cement clinker. As plant produce many types of cement, clinker activity data are estimated taking into account different cement type and

27

http://www.eea.europa.eu/publications/emep-eea-guidebook-2013 , Mineral products (pages 12-13) 28

http://www.eea.europa.eu/publications/EMEPCORINAIR5/B3311vs2.4.pdf (pages 12-13)

http://www.eea.europa.eu/publications/emep-eea-guidebook-2013

http://www.eea.europa.eu/publications/EMEPCORINAIR5/B3311vs2.4.pdf


168

multiplying it with cement/clinker ratio and also mass balance of cement, clinker and used

additives in cement production. Cement production activity data from plant is available according to cement producer annual EU ETS GHG report (European Union Emission Trading System Greenhouse Gas Report that must be submitted by EU ETS operators

annually till 15th of March to State Environmental Service Regional Environmental Board for approval of verified emissions in previous year).

Alternative of activity data if clinker production data is not available (as plant has non-stop production process) is to use cement clinker data and estimate this amount back to clinker production data. In the cement production plant it is done for the EU ETS annual reporting by

taking into account clinker and cement ratio for the particular types of produced cement. Activity data of cement and clinker is plant- specific data reported from cement clinker plant.

Final clinker data is known to using plant mass balance approach calculate in two steps:

1) Clinker production = ((cement export – cement stock changes) * clinker/cement ratio)) - clinker export – clinker stock changes ;

2) Produced clinker = used clinker + clinker export – clinker import + clinker stock change.

Approach (1) is used for each produced cement type to calculate produced clinker amount that is produced in respective plant.

CaO content is measured in the cement production companies and CO2 EF for produced

clinker is estimated according to equation 2.4 from 2006 IPCC Guidelines 29. As it stated by cement producer and verified by ISO accredited verifiers the cement kiln dust is weighted at

the plant before the transportation outside the company for the storage.

Due to changing of technology there are produced 2.4 times more clinker in 2010 as in previous year. It is explained with new dry process kiln technology and increasing capacity

of clinker production plant. Full capacity of dry process cement clinker production has caused the increase of CO2 from Industrial processes and Product Use sector starting from 2010.

Cement clinker are produced for internal use but mainly for export.

Table 4.6 CKD correction factor in 1990–2013

Produced

clinker

(Gg)

Produced

cement

kiln dust

(Gg)

CKD /

clinker

ratio (% )

Corrected

CKD /

clinker

ratio (% )

1990 668.50 175.49 26.25 0.094

1995 175.69 15.00 8.54 0.031

2000 167.18 10.00 5.98 0.021

2005 265.40 1.53 0.58 0.002

2006 330.65 2.89 0.87 0.003

2007 338.31 3.35 0.99 0.004

2008 334.46 0.99 0.30 0.001

2009 340.99 8.08 2.37 0.008

2010 834.94 7.02 0.84 0.003

2011 1095.23 10.87 0.99 0.004

2012 1129.11 13.29 1.18 0.004

2013 1054.95 12.43 1.18 0.004

29

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169

As it can be seen in (Table 4.6) the plant specific data resulted in a higher CKD ratio

(26.25%) in 1990, while the CKD in 2008 is much lower (0.30%). Still to ensure comparability, as required by the IPCC GPG 2000 and also reflect the national circumstances, Latvia uses the maximum permissible good practice guidance limit of CKD – 6-8% where the

plant specific data exceeds 8% for the calculation of CO2 emissions from cement production. CKD ratio was changed to 8% that is maximum permissible good practice guidance limit of

CKD (6%–8%) although official statistical data resulted in different CKD ratio.

According to cement production plant the CKD amount is weighted before it is sent to disposal site. The amount of weighted CKD as well as procedures of all data obtaining is

verified by the accredited verifier within EU ETS. According to Verification Company all production facilities as well as data obtaining and storage was inspected at the production

company personally by the lead verificator. All verification reports also are publicly available till 2012 through LEGMC ETR web page http://www.meteo.lv/lapas/uznemumi-kuriem-izsniegtas-siltumnicefekta-gazu-emisijas-atlaujas-2-pe?id=1253&nid=575, after responsible

for such information publication is State Environmental Service of Latvia - http://www.vvd.gov.lv/izsniegtas-atlaujas-un-licences/seg-atlaujas/ , internal verification

documentation is confidential. The cement clinker is produced only from limestone and CKD amount changes due to production technology. For the years 2005-2008 CKD has decreased due to improvement of used technology.


Uncertainty of cement production data is assumed as 10% as clinker production data is

estimated from final cement production data because produced clinker is not weighted separately before the final cement mixture is produced.

CO2 emission factor for 2.A.1 sector is estimated based on plant specific data of used limestone characterizations so average uncertainty of 5% is assumed.


methodology, emission factors and data sources are used for sectors for all years. GHG emissions from the sector are estimated or reported as not occurring / not applicable therefore

there are no ―not estimated‖ sectors.

All industrial production data used in emission estimation from 2.A Mineral Products sector is taken from the annual GHG reports that industrial producers submit within EU ETS.

According to EU ETS legislation all GHG reports have to be verified by the ISO accredited verifiers that checks that all reported information – activity data, CO2 emission factors,

estimated emissions as well as estimation methodology, is correct and corresponds to certain requirements from the legislation. Cement and lime production facilities certify that all additional information for CO2 emission estimation is true verified. Regional Environmental

Board also checks the annual GHG reports and compares the data in the reports with the data reported by the enterprise to database ―2-AIR‖ and to CSB.

Time series consistency was checked by verifying IEF, AD and emission changes and attention was paid to important changes that increase/decrease that are explained in NIR.


QA/QC check is performed with Tier2 method from 2006 IPCC Guidelines.

Emissions are checked using time series consistency check for the IEF estimated in CRF

Reporter and all IEF changes - in time series are double-checked and reasonable explanation for IEF changes has to be found under each subsector source category description.

http://www.meteo.lv/lapas/uznemumi-kuriem-izsniegtas-siltumnicefekta-gazu-emisijas-atlaujas-2-pe?id=1253&nid=575,%20after

http://www.meteo.lv/lapas/uznemumi-kuriem-izsniegtas-siltumnicefekta-gazu-emisijas-atlaujas-2-pe?id=1253&nid=575,%20after

http://www.vvd.gov.lv/izsniegtas-atlaujas-un-licences/seg-atlaujas/


170

Quality control check list is filled for each category taking into account criteria given in

QA/QC plan approved in national legislation. All findings were documented and introduced in GHG inventory. All corrections are archived.

Plant specific CO2 emission factors and Tier2 CO2 emission estimation methodology is used.

Tier 2 methodology is used to estimate CO2 emissions from cement production using plant specific data of CaO content in used limestone and Tier2 methodology from 2006 IPCC

Guidelines.

Cement, cement kiln dust production data and estimated clinker production data is taken from plant’s annual GHG reports within EU ETS. According to legislation the GHG reports are

verified by accredited verifiers and then checked and approved by Regional Environmental Boards. The data reported in CRF tables and in NIR is also verified by CSB.

CaO content data is reported to LEGMC by cement production plant and is determined in plant’s laboratory according to plant’s internal procedures.

Checks performed pursuant to Article 7(1)(l) of Regulation (EU) No 525/2013 are done to

comparing EU ETS data with GHG inventory emissions. EU ETS registry administrators has an Excel file containing a list of all operators participating in EU ETS and those verified

emissions that are compared with ITL (International Transaction Log) records. Such consistency checks are done in all IPPU sectors.

4.2.2.5 Source-specific recalculations

In this sector there are made recalculations in all time series taking into account correction factor for CO2 emissions calculation of clinker production. CO2 emissions from clinker

production are estimated using 2006 IPCC Guidelines equation 2.2.


No improvements are planned for this sector.

4.2.3 Lime Production (CRF 2.A.2)


Under this sector CO2 emissions from lime production in Iron & Steel production are reported as these emissions are estimated based on total produced quicklime (CaO) data and limestone

and dolomite use in one lime production plant. In iron & steel production facility lime necessary for steel smelting in open hearth furnaces is produced only from limestone in vertical shaft kiln. The plant reports their non-marketed

quicklime production data for 2005-2013 within EU ETS so the estimated emissions as well as used activity data and emission factors are taken from plant’s annual GHG report (Table

4.7).

Table 4.7 CO2 emissions from lime production in 1990–2013 (Gg)

In steel

production

In lime

production

1990 30.24 118.62

1995 30.24 10.42

2000 32.56 4.28

2005 30.37 1.85


171

In steel

production

In lime

production

2006 29.07 1.31

2007 28.63 1.58

2008 26.54 1.89

2009 21.36 0.44

2010 28.05 0.54

2011 0.12 0.54

2012 1.40 0.36

2013 0.00 0.27

As for most of Latvia’s economy sectors the emissions in 2008-2009 have decreased significantly due to the economic crisis. In 2010, emissions have increased due to increasing

activity data of produced lime that are used for glass and metal production. There are increased emissions from lime production due to overall increasing of activity in Ind ustrial

processes. In 2011 emissions of produced lime that are used for metal production are decreased due to changing technology of metal production as plant switched on steel production in EAF (Electric arc furnace) only and operation of this plant was partially

suspended due to reconstruction.

In latest years there are trend to decrease CO2 emissions from subsector 2.A.2 due to

reconstruction mentioned above and due to fact that plant are not operating a full year.

Figure 4.3 CO2 emission from limestone and dolomite use in lime and steel production in 1990–2013 (Gg)30

As it can be seen in Figure 4.3 the CO2 emissions from dolomite use in lime production plant as well as dolomite and limestone use in steel production are continuously decreasing since

the beginning of 90ties due to recession of overall national economy. In 2013 there are not used anymore dolomite in steel production and limestone in lime production. There are used very small amount of limestone in steel production and lime production plant are still using

the dolomite as raw material.

30

dolomite use (steel production), limestone use (steel production), dolomite use (lime production), on secondary axis


172


Methods

CO2 emissions from lime production in steel production plant are estimated with Tier 1

method based on total produced quicklime data and default emission factor.

EM = EF × AD

where:

EM – CO2 emissions from quicklime production (Gg)

EF – default EF according to IPCC GPG 2000 (tCO2/t lime) and MRG

AD – quicklime production data (Gg)

CO2 emissions from Lime production in two direct lime production plants are calculated

basing on data of carbonates – dolomite and limestone use. Purity factor from IPCC GPG 2000 is taken into account in estimation of CO2 emissions from dolomite use in lime

production calculation. CO2 emissions from limestone use in lime production processes are estimated with Tier 2 method based on plant specific activity data and default IPCC 1996 emission factors. Tier 3 method is used in CO2 emission from dolomite use in lime production

processes estimation as plant specific activity data as well as plant specific CO2 emission factors are used in estimation.

Emission factors

Default CO2 emission factor from IPCC GPG 2000 was used by steel production plant as per tonne of high calcium quicklime – 0.785 tCO2/t lime31. Lime in the particular plant is

produced only from limestone.

Emission factors of limestone and dolomite use in steel production are default ones taken

from IPCC 1996 (Table 4.8).

Table 4.8 CO2 emission factors for limestone and dolomite use (t CO2/t raw material)

1990–2013

Limestone use in steel and lime production 0.440

Dolomite use in steel production 0.477

Plant specific CO2 emission factor for dolomite use in lime production

The used CO2 emission factor of dolomite use in Lime production is considered as plant specific as CaO and CaO*MgO content is taken into account.

According to laboratory measurements made in only lime producer plant in Latvia average content of dolomite is:

CaCO3 – 51.83%;

MgCO3 – 40.80%;

SiO2; Fe2O3; Al2O3 – 5.88%;

Others – 1.49%.

31

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173

According to laboratory data:

average content of water in dolomite is 5.24%;

average content of water in produced lime is 0%;

average content of CO2 in lime is 16.99%;

average content of dolomite (dry) is 94.76% or 947.6 kg dolomite.

947.6 kg dolomite contains:

491.14 kg CaCO3 (51.86%)

386.62 kg MgCO3 (40.80%)

55.72 kg SiO2; Fe2O3; Al2O3 (5.88%)

14.12 kg Others (1.49%)

947.6 kg dolomite complete decomposes and pullulates:

491.14 kg CaCO3 × 0.440 (emission factor) = 216.10 kg CO2

386.62 kg MgCO3 × 0.522 (emission factor) = 201.82 kg CO2.

Oxides capture:

491.14 kg CaCO3 × 0.560 (emission factor) = 275.04 kg CaO

(or 491.14 kg CaCO3 – 216.10 kg CO2 = 275.04 kg CaO)

386.62 kg MgCO3 × 0.478 (emission factor) = 184.80 kg MgO

(or 386.62 kg MgCO3 – 201.82 kg CO2 = 184.80 kg MgO)

216.10 kg CO2 + 201.82 kg CO2 + 275.04 kg CaO + 184.80 kg MgO = 877.76 kg

947.6 kg – 877.76 kg = 69.84 kg ballast

Lime is made (theoretical):

275.04 kg CaO + 184.80 kg MgO + 69.84 kg ballast = 529.69 kg lime

CO2 content in lime is 16.99% (practical):

529.69 kg lime – 83.01%

Lime is made (practical):

638.09 kg lime + CO2 – 100%

CO2 content in lime is:

638.09 kg lime + CO2 – 529.69 kg lime = 108.41 kg CO2

CO2 emissions (1 tonne complete decomposition) pullulate:

216.10 kg CO2 + 201.82 kg CO2 – 108.41 kg MgO = 309.51 kg CO2

0.3095 t CO2 proceed from practical decomposition of 1 tonne of dolomite.

Average content of water (5.24%) in used dolomite is taken into account when CO2 emission

factor is estimated:


174

CO2 EF dolomite use in lime production = 309.51 kg CO2 × 94.76% = 0.29329167 t CO2 / t dolomite.

Activity data

In this sector there are gathered activity data from two facilities of lime production and one plant of steel production.

Activity data were taken from industrial production plants. Industrial producers are participants of the EU ETS and the GHG reports of these enterprises have to be freely

available according to EU ETS regulations. The GHG reports of EU ETS operators are published on LEGMC home page (http://www.meteo.lv/lapas/uznemumi-kuriem-izsniegtas-siltumnicefekta-gazu-emisijas-atlaujas-2-pe?id=1253&nid=575) (Table 4.9).

Table 4.9 Amount of produced lime in 1990–2013 (Gg)

In steel

production

In lime

production

1990 10.452 214.225

1995 10.452 19.208

2000 13.416 7.894

2005 17.097 20.435

2006 11.758 14.116

2007 12.939 15.510

2008 14.842 17.283

2009 8.851 9.581

2010 16.325 17.211

2011 0.002 0.888

2012 0.541 1.099

2013 0.000 0.496

For years 1995-2004 the iron production plant reported their activity data additionally after the information request letter. Due to lack of official data it was decided to use year’s 1995 activity data for emission estimation for 1990-1995.

Changes of national economy and whole data exchange system in early 90ties were the reason why many data is lost even in production plants. Still to improve CO2 emission estimation

activity data of first year’s data available was used to estimate emissions for the prior years, for example, for Iron & Steel production plant year 2005 data was used to estimate the emissions for 1990-2004.

Activity data fluctuates in whole time series. Biggest decrease occurs in the beginning of 1990ties as a consequence of changes in structure of country’s national economy.

In 2010 activity data are increased by 23.03% due to overall increasing of activity in all

industrial sector. Exception is limestone use in steel production. Activity of lime production are still decreasing in 2011-2013 due to changes of steel production technology that are

described in plant GHG permit. In 2011, there is overall decreasing of total emissions from lime production about 74.12 % due to changes of steel production technology as plant switched on steel production in EAF (Electric arc furnace) only and operation of this plant

was partially suspended due to reconstruction. As it seen in Table 4.10 in latest years there are overall decrease of activity in sector 2.A.2.




175

Table 4.10 Limestone and dolomite use activity data in lime production (t CO2/t raw material)

Do

lom

ite u

se (

steel

pro

du

cti

on

)

Lim

est

on

e u

se (

steel

pro

du

cti

on

)

Do

lom

ite u

se (

lim

e

pro

du

cti

on

)

Lim

est

on

e u

se (

lim

e

pro

du

cti

on

)

1990 33.00 14.30 404.442 NO

1995 33.00 14.30 35.535 NO

2000 33.00 14.30 14.604 NO

2005 29.71 6.33 6.303 NO

2006 30.49 12.02 4.452 NO

2007 30.40 9.02 3.776 1.078

2008 26.25 5.38 0.95 3.654

2009 22.39 8.47 1.15 0.229

2010 28.11 4.15 1.32 0.349

2011 0.25 0.00 1.32 0.35

2012 1.55 0.54 0.73 0.323

2013 0.00 0.00 0.94 0.000


Although according to IPCC GPG 2000 the uncertainty of non-marketed lime production data could reach 100% and more32 it is assumed that the uncertainty of activity data for non-marketed lime production data is 2.A.2 sector is assumed as 2% as only one plant specific

data verified by accredited verifier and approved by Regional Environmental Board is used.

As default emission factors for lime production from IPCC GPG 2000 as well as MRG are

used and the uncertainty is assumed 50% due to unavailability of the plant specific data of produced lime and due to the fact that this is default emission factor for quicklime production.


methodology, emission factors and data sources are used for sectors for all years in time series. All other GHG emissions except CO2 emission are not relevant and could not be

reported in CRF.

Time series consistency was checked by verifying IEF, AD and emission changes and attention was paid to important increase/decrease that are explained in NIR.


QA/QC check is performed with Tier1 method from IPCC GPG 2000.

Activity data, CO2 emission factor and estimated emissions are taken from the annual GHG reports that steel production plant submit within EU ETS.

According to EU ETS legislation all GHG reports have to be verified by the ISO accredited verifiers that checks that all reported information is correct and corresponds to certain requirements from the legislation. Steel production facility certifies that all additional

32

http://www.ipcc-nggip.iges.or.jp/public/gp/english/3_Industry.pdf (page 3.23)

http://www.ipcc-nggip.iges.or.jp/public/gp/english/3_Industry.pdf


176

information for CO2 emission estimation is verified. Regional Environmental Boards also

checks the annual GHG reports and approves the report if everything reported is correct.

Emissions are checked using time series consistency check for the IEF estimated in CRF Reported and all IEF changes in time series are double-checked and reasonable explanation

for IEF changes has to be found under each subsector source category description.

The QC form has been filled in for each category taking into account criteria given in QA/QC

plan approved in national legislation. Form then is archived.

Checks performed pursuant to Article 7(1)(l) of Regulation (EU) No 525/2013 are done to comparing EU ETS data with GHG inventory emissions. EU ETS registry administrators has

an Excel file containing a list of all operators participating in EU ETS and those verified emissions that are compared with ITL (International Transaction Log) records. Such

consistency checks are done in all IPPU sectors.


No recalculations have been done for the sector.


No improvements are planned for the sector.

4.2.4 Glass production (CRF 2.A.3)


In this sector CO2 emissions from use of additional raw materials used in glass production plants – fluorspar, potash and witherite (barium carbonate), are reported, as well as NMVOC

emissions from glass production and glass fibre production reported by production facilities. CO2 emissions from glass fibre production processes are estimated from NMVOC emissions due to lack of CO2 emission factors and activity data to CO2 emissions directly.

Figure 4.4 Emissions from raw materials used in glass production 1990-2013 (Gg)33

Use of potash as well as NMVOC emissions from glass production stopped in 2005 when the glass production plant ended its activity although the use of raw materials in last years of this

glass production plant increased sharply. Use of witherite is occurring only in 2005-2007 in

33

Emissions from use of potash on primary axis


177

glass production manufacturing plant but in 2008 and 2009 the plant has suspended it activity.

Since 2005 NMVOC emissions are still emitted but in smaller amounts from glass fiber production (Figure 4.4).

NMVOC emissions for time period 1997-2013 were taken from national database ―2-AIR‖

where glass fiber production plant reported its emissions divided by NMVOC sub-type (Table 4.11). For time period 1990-1996 only butyl acetate data is available from glass fiber

production company’s application for GHG permit within EU ETS. For year 2005, also glass production company had reported its NMVOC emissions (these emissions are reported together under Glass production sector in CRF Reporter) but since then glass production is

not operating therefore NMVOC emissions from glass production are reported only for 2005.

Table 4.11 NMVOC emissions from glass fibre and glass production in 1990–2013 (Gg)

Aceto

ne

Bu

tyla

ceta

te

Aceti

c a

cid

Fo

rmald

eh

yd

e

Iso

pro

pan

ol

(iso

pro

py

l)

Meth

ano

l (m

eth

yl

alc

oh

ol)

Meth

an

e

Kero

sen

e

Pro

pan

e (

pro

py

l

alc

oh

ol)

Fo

rmic

acid

tota

l N

MV

OC

in

gla

ss f

ibre

pro

du

cti

on

tota

l N

MV

OC

in

gla

ss p

ro

du

cti

on

tota

l N

MV

OC

(G

g)

1990 NO 0.001 NO NO NO NO NO NO NO NO 0.00128 NO 0.00128

1995 NO 0.002 NO NO NO NO NO NO NO NO 0.00158 NO 0.00158

2000 0.140 0.664 0.294 0.066 NO NO NO 1.570 NO NO 0.00273 NO 0.00273

2005 NO 1.493 0.909 0.107 0.276 0.084 NO 0.659 1.200 0.233 0.00496 0.00642 0.01138

2006 NO 1.486 0.960 0.101 0.360 0.232 NO 0.094 1.274 0.188 0.00469 NO 0.00469

2007 NO 1.315 1.704 NO 1.722 2.414 NO NO 5.920 NO 0.01307 NO 0.01307

2008 NO 0.968 1.548 NO 1.599 2.173 NO NO 5.810 NO 0.01210 NO 0.01210

2009 NO 1.172 0.402 NO 1.071 0.401 NO NO 6.715 NO 0.00976 NO 0.00976

2010 NO 1.684 1.673 NO 1.355 2.613 NO NO 6.712 NO 0.01404 NO 0.01404

2011 NO 1.622 1.908 NO 2.351 2.873 NO NO 6.640 NO 0.01539 NO 0.01539

2012 NO 1.908 NO NO 2.873 NO NO NO NO NO 0.00478 NO 0.00478

2013 NO 0.205 0.935 NO NO NO NO NO 1.429 NO 0.00257 NO 0.00257

The sharp decrease of limestone use in glass production plant in 1997 and accordingly the CO2 emissions is explained with changes in plant’s structure as since 1997 the plant is Joint Stock Company and overall changes in production technology.

The economic crisis is obviously reflecting in CO2 emissions from limestone, dolomite and soda ash use in mineral production (Table 4.12). Also the increase of taxes influences the

ability of industrial producers to invest in future development. In 2010 there are increased CO2 emissions from limestone about 72% comparing with previous year due to increasing activity in all industrial sector. It is explained with fact that Latvia is almost over economic

crisis. In latest years there are tend to decrease emissions of limestone use in glass production. From 2011 to 2013 there are decreased CO2 emissions about 30.43%. In 2012 plant didn’t

used acetic acid, methanol and propane. In 2013 emissions from NMVOC used in glass fibre production are increased about 100.7% comparing with 1990 when only butylacetate was used as raw material.


178

Table 4.12 CO2 emissions from limestone, dolomite and soda ash use in glass fibre and glass production in

1990–2013 (Gg)

From

limestone

use

From

Dolomite

use

From

soda ash

use

1990 0.352 NO NO

1995 1.947 0.809 0.643

2000 2.698 1.372 1.743

2005 3.111 0.996 1.554

2006 2.196 NO 0.466

2007 4.355 NO 0.037

2008 3.992 NO NO

2009 2.575 NO NO

2010 4.432 NO NO

2011 4.279 NO NO

2012 3.729 NO NO

2013 2.977 NO NO


Methods

Default methodology was used to estimate emissions when activity data is multiplied with emission factor. CO2 emission factors used to estimate emissions from raw materials use in glass production are plant specific and taken from plants annual GHG reports within EU ETS

(Table 4.11). NMVOC emissions for time period 1997-2013 are taken from national database ―2-AIR‖ where both glass production and glass fibre production companies report their

emissions. NMVOC emissions for 1990-1996 are estimated only for butylacetate use that glass fibre production company reported in its application for GHG permit during the implementation of ETS in Latvia.

CO2 emissions from limestone and dolomite use and soda ash use in glass production are estimated with Tier 2 method basing on plant- specific activity data and default IPCC 1996

emission factors.

Indirect CO2 emissions from glass fibre production processes were estimated according to 2006 IPCC Guidelines provided methodology and explanation of indirect CO2 emission

estimation basing on carbon conversion factor and average default carbon content amount. CO2 emission factors are not provided in emission estimation methodology and it wouldn’t be

possible to obtain activity data for direct CO2 emission estimation.

For the CO2 emission estimation NMVOC emissions were taken as activity data and CO2 emissions were estimated using carbon conversion factor.

NMVOCEFE COCO 22

where:

ECO2 – CO2 emissions (Gg)

EFCO2 – estimated CO2 emission factor


179

NMVOC – NMVOC emissions (Gg)

Emission factors

CO2 emission factors for emission from additional raw materials use in glass production processes were taken from reports of glass production plants submitted within EU ETS

implementation and from applications to GHG permits. These are plant specific emission factors. Emission factors of limestone and dolomite use in production of glass as well soda

ash use in glass production are default ones taken from IPCC 1996 (Table 4.13).

Table 4.13 Emission factors for materials use in glass production (t emissions / t product or raw material)

1990 – 2013

Fluorspar use 0.0017

Potash use 0.32

Barium carbonate (witherite) use 0.223

Butylacetate use (NMVOC)34 1.0

Limestone use 0.440

Dolomite use 0.477

Soda ash use 0.415

For CO2 emission from glass fibre production estimation 80% of carbon content conversion factor. According to 2006 IPCC Guidelines 35, indirect emissions of CO2 from atmospheric

oxidation of emitted NMVOC are to be included in the national emission inventory. The average amount of carbon in NMVOC is assumed to be 80%36. The default carbon content

conversion factor of 2006 IPCC Guidelines that is 60% was assumed as too low.

The CO2 emission factor was estimated using following equation:

011.120098.44%802

COEF

Where:

EFCO2 – CO2 emission factor (Gg/Gg)

80% – the average amount of carbon in NMVOC

44.0098 / 12.011 – carbon dioxide and carbon molmass ratio

This leads to an emission factor for indirect CO2 release of 2.931299642 kg CO2/kg NMVOC.

Activity data

Amount of raw materials used in glass production is quite small and fluctuates in whole time

series. Although use of potash increased sharply in 2004-2005, the use stopped in 2005 due to closure of glass production plant (Table 4.14).

34

For emission estimation only for year 1990-1996, since 1997 the plant reported data from national database ―2-AIR‖ is used 35

http://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/1_Volume1/V1_7_Ch7_Precursors_Indirect.pdf (page 7.6) 36

Basing of the most often used average carbon conversion factor

http://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/1_Volume1/V1_7_Ch7_Precursors_Indirect.pdf


180

Table 4.14 Activity data for raw materials use in glass production 1990-2013 (Gg)

Use of

potash

(Gg)

Use of

fluors par

(Gg)

Use of

barium

carbonate

(Gg)

Use of

butylacetate

(Gg)

Use of

dolomite

(Gg)

Use of

limestone

(Gg)

Soda

ash use

(Gg)

1990 NO NO NO 0.0013 NO 0.8000 NO

1995 NO 0.1158 NO 0.0016 1.6970 4.4253 1.5489

2000 NO 0.0840 NO NO 2.8750 6.1326 4.2002

2005 0.0376 0.2652 0.0115 NO 2.0880 7.0701 3.7435

2006 0.0198 0.2221 0.0209 NO NO 4.9910 1.1219

2007 0.0088 0.2013 0.0096 NO NO 9.8988 0.0902

2008 NO 0.2552 NO NO NO 9.0725 NO

2009 NO 0.4084 NO NO NO 5.8530 NO

2010 NO 0.6222 NO NO NO 10.0721 NO

2011 NO 0.5912 NO NO NO 9.7261 NO

2012 NO 0.6390 NO NO NO 8.4749 NO

2013 NO NO NO NO NO 6.7657 NO

Activity data fluctuates in whole time series. Biggest decrease occurs in the beginning of 1990ties as a consequence of changes in structure of country’s national economy. Dolomite

use in glass production ended in 2005 as glass production plant stopped its activity. The total amount of raw material used was affected by the closing of glass production plant and

suspending of activity of another glass production plant.

In 2008-2013, only use of fluorspar in glass fibre production plant is occurring as other two glass production plants or either stopped its activity or suspended it.


The uncertainty of activity data for this sector is assumed as 2% as plant specific reported data

is used. Accredited verifiers and Latvia’s Regional Environmental Boards verify the activity data reported in production plant’s annual GHG reports within EU ETS so the activity data is

adequately verified.

As default emission factors for limestone, dolomite and soda ash use are used the uncertainty is assumed 50%.

CO2 emission factor for this sector are taken from glass production plant so the uncertainty could be assumed as quite low. Still the estimation of the emission factor can’t be adequately

verified so the uncertainty is assumed as quite high – 70%.


series. All emissions with exception of CO2 emissions for use of fluorspar and potash as well as NMVOC emissions for glass fibre production are not estimated due to lack of estimation

methodology.



181



Activity data, CO2 emission factors and estimated emissions from glass production plants are

taken from the annual GHG reports that plants submit within EU ETS. All GHG reports are verified by the ISO accredited verifiers that checks that all reported information is correct and

corresponds to certain requirements from the legislation. Regional Environmental Boards also check the annual GHG reports and approves the report if everything reported is correct.


comparing EU ETS data with GHG inventory emissions. EU ETS registry administrators has an Excel file containing a list of all operators participating in EU ETS and those verified emissions that are compared with ITL (International Transaction Log) records. Such

consistency checks are done in all IPPU sectors.


No recalculation has been done for the sector.


No improvements are planned.

4.2.5 Ceramics (2.A.4.a)


Bricks production has strong traditions in Latvia as production plants operate many decades, for example in bricks production plant ―LODE‖ the brick production was started in 1964. Still

from 5 now operating bricks production plants only two were operating up to 1990, there is no information if the other companies were working for time period 1990-1993 what is not

covered by GHG permit application requirements.

According to ERT team recommendation on 2015 there are reported bricks emissions in one line in CRF.

For now it is known that only plants 1 and 5 were operating in time period 1990-1993 so the indicator IE was previously used for both these plants in time period 1990-1993. As it was not

possible to obtain the data for raw materials used in Bricks production companies No 1 and 5, there wasn't possible to estimate the emissions using the same methodology as for 1993-2008 and follow the consistency. Therefore the CO2 emissions were estimated only using total

produced bricks amount for 1990-1993 for these two plants. And after 1993 it was possible to increase methodology level and estimate CO2 emissions for each plant separately.

There is only one tiles production plant in Latvia and CO2 emissions from use of clay in tile production process in 1995-2013 are reported in this sector. The tiles production plant is participant of EU ETS so the data from plant’s annual GHG reports is available for inventory.

Table 4.15 CO2 emissions from tile production in 1995-2013 (Gg)

CO2

emissions

(Gg)

1990 NO

1995 0.163


182

CO2

emissions

(Gg)

2000 0.208

2005 0.135

2006 0.140

2007 0.179

2008 0.042

2009 0.229

2010 0.200

2011 0.279

2012 0.483

2013 0.535

Emissions are decreasing since 2003 with some fluctuation due to decrease of activity of tiles production plant. (Table 4.15). Still in 2009 the CO2 emissions have increased approximately 4 times as the building and construction sector again became active. In 2010 activity of tile

production is decreased for about 12.66%. From 2010-2013 activity of tile production is increased about 167.5% due to demand of such production in market.


Default methodology was used to estimate emissions when activity data is multiplied with

emission factor but the CO2 emission factor – 0.08794 (t CO2/t dry clay), used to estimate emissions from clay use in tiles production are taken from MRG. 37

Amount of used clay in tiles production is taken from only tiles production plant in Latvia

(Table 4.16).

Table 4.16 Activity data for tiles production in 1995-2013 (Gg)

Use of clay

in tiles

production

(Gg)

1990 NO

1995 2.034

2000 2.594

2005 1.685

2006 1.748

2007 2.242

2008 0.525

2009 2.861

2010 2.497

2011 3.484

2012 6.033

2013 6.684

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183

Estimation of CO2 emission factor in bricks production plants is rather complicated and based

on physical and chemical characteristics of raw materials and type o f activity data for estimations of emissions.

CO2 emission estimation for 1990-1992

For years 1990-1992 no plant specific data is available from bricks production plants so CO2 emission estimation for these 3 years is done based on final produced bricks amount if

average weight of one brick is known.

According to statistical information average weight of one brick is 3.9kg and according to plant data average produced bricks / used clay ratio is 1.25.

Then if final amount of produced bricks is know it is possible to determine approximate clay consumption (Table 4.17). In CO2 emission estimation emission factor 0.047 tCO2/t used clay

is used.

Table 4.17 Data and assumptions used for CO2 emission estimation for 1990-1992

1990 1991 1992

produced bricks (pieces) 471800000 546423000 259918000

average weight of one brick (kg) 3.9 3.9 3.9

produced bricks (tonnes) 1840020 2131049.7 1013680.2

average produced bricks / used clay ratio 1.25 1.25 1.25

used clay (Gg) 1472.016 1704.84 810.9442

CO2 emission factor of used clay tCO2/t used clay 0.047 0.047 0.047

CO2 emissions (Gg) 69.1848 80.1275 38.1144

CO2 emissions are estimated differently in Latvia’s five bricks production plants as well as estimation methodology differs because it was possible to use higher tier of emission

estimation in last years due to availability of necessary activity data and laboratory measures of used raw materials.

1st bricks production plant

During the revision of 1st bricks production plant’s application to GHG permit, annual GHG reports for 2005-2009 it was stated that the plant has changed used CO2 emission estimation

methodology 3 times:

1. CO2 emission for time period 1993-2004 was estimated by using used clay as an activity data and CO2 emission factor for used clay – 0.047 tCO2/t used clay. The

particular emission factor is determined for total used clay data when clay characterizations are not known. CO2 emissions are determined by ignition loses of

clay: in 1000° C – 4.7% of instant CO2 is emitted).

2. For 2005-2007 the plant is using calculation method B – alkali earth oxides, from the MRG when calculation is based on the content of the CaO, MgO and other (earth)

alkali.

3. For years 2008-2012 plant is using the calculation method A – carbon input, from the

MRG when calculation is based on the carbon input on each of the relevant raw materials. Tier 1 emission factors from the MRG corresponding particular method are used when conservative value of 0.2 tonnes CaCO3 (0.08794 tonnes of CO2) per tonne

of dry clay is applied for the calculation of the emission factor instead of results of analyses.


184

First bricks production plant’s used methodology for CO2 emission estimation in whole time

series is inconsistent as methodology is changed several times and for 2008 estimation methodology is again switched from Tier2 to Tier1 and default average CO2 emission factor is used.

Methods

The CO2 emissions in whole time period was calculated by using calculation method B –

alkali earth oxides, from the MRG when calculation is based on the content of the CaO, MgO and other (earth) alkali38.

According to bricks production plant’s reported information the following equation to

estimate CO2 emissions was used:

CFEFADADCO MgOCaOraw ,2

where:

CO2 – total CO2 emissions from bricks production (Gg)

ADraw – activity data of used raw materials – clay (Gg)

ADCaO,MgO – CaO and MgO content in used raw materials (%)

EF – CO2 emission factor of CaO and MgO (Gg/Gg)

CF – conversion factor

Emission factors

CO2 emission factors for CaO and MgO – 0.785 and 1.092 for tonne CO2 per tonne of oxide respectively, were taken from MRG39 (Table 4.18).

Activity data

As MgO and CaO content data was not available for years 1993-2004 so the data reported in bricks production plant’s GHG report for 2005 was used: MgO content – 4.9%, CaO content

– 11.6%.

As for years 2008-2009 different emission estimation methodology is used and MgO and CaO data is not available content data of 2006-2007 was used also to estimate emissions for 2008-

2012: MgO content – 2.9%, CaO content – 10.26%.

Table 4.18 Data and assumptions used for CO2 emission estimation from 1st

bricks production plant

Use

of

cla

y (

Gg

)

Mg

O c

on

ten

t (%

)

CaO

co

nte

nt

(%)

Mg

O a

mo

un

t (G

g)

CaO

am

ou

nt

(Gg

)

Mg

O C

O2 E

F (

tCO

2/t

ox

ide)

CaO

CO

2 E

F (

tCO

2/t

ox

ide)

CO

2 e

mis

sio

ns

(Gg

)

Av

era

ge C

O2 E

F (

tCO

2/t

ox

ides)

1990 NO NO NO NO NO NO NO NO NO

1995 2.700 4.90% 11.60% 0.132 0.313 1.092 0.785 0.390 0.876

2000 4.800 4.90% 11.60% 0.235 0.557 1.092 0.785 0.694 0.876

2005 5.257 4.90% 11.60% 0.258 0.610 1.092 0.785 0.760 0.876

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185

Use

of

cla

y (

Gg

)

Mg

O c

on

ten

t (%

)

CaO

co

nte

nt

(%)

Mg

O a

mo

un

t (G

g)

CaO

am

ou

nt

(Gg

)

Mg

O C

O2 E

F (

tCO

2/t

ox

ide)

CaO

CO

2 E

F (

tCO

2/t

ox

ide)

CO

2 e

mis

sio

ns

(Gg

)

Av

era

ge C

O2 E

F (

tCO

2/t

ox

ides)

2006 6.245 2.90% 10.26% 0.181 0.641 1.092 0.785 0.701 0.853

2007 7.745 2.90% 10.26% 0.225 0.795 1.092 0.785 0.869 0.853

2008 3.880 2.90% 10.26% 0.113 0.398 1.092 0.785 0.435 0.853

2009 2.268 2.90% 10.26% 0.066 0.233 1.092 0.785 0.254 0.853

2010 1.922 2.90% 10.26% 0.056 0.197 1.092 0.785 0.216 0.853

2011 1.698 2.90% 10.26% 0.049 0.174 1.092 0.785 0.191 0.853

2012 1.670 2.90% 10.26% 0.048 0.171 1.092 0.785 0.187 0.853

In 2013 1st bricks production plant is not operating anymore.

2nd bricks production plant

CO2 emissions for 2nd bricks production plant is recalculated only for year 2008 in

comparison with plant’s annual GHG report. For 1999-2008 the plant is using the same emission estimation methodology but for year 2008 average default emission factor from MRG is used. As this emission factor is Tier1 emission factor but for previous years Tier2

emission factors are used it was decided to recalculate emissions for 2008.

The plant was closed at the end of 2008 and wasn’t operated in 2009 due to company’s

reorganization when production plant using old obsolete installations were closed and all production was transferred to other modern production facilities.

Methods

Calculation method A – carbon input, from the MRG40 is used in plant’s emission estimation for its application for GHG permit as well for reporting of annual CO2 emission:

33332 MgCOMgCOrawCaCOCaCOraw EFADADEFADADCO

where:

CO2 – CO2 emissions from 2nd

bricks production plant (Gg)

ADraw – activity data of used clay (Gg)

ADCaCO3 – CaCO3 content in used clay (%)

EFCaCO3 – CaCO3 emission factor (Gg/Gg)

ADMgCO3 – MgCO3 content in used clay (%)

EFMgCO3 – MgCO3 emission factor (Gg/Gg)

Emission factors

Default CO2 emission factors from the MRG for the CaCO3 and MgCO3 are used. CO2

emission factor for CaCO3 is 0.44 tCO2/t CaCO3 and CO2 emission factor for MgCO3 is 0.522 tCO2/t MgCO3.

40




186

Activity data

The content of CaCO3 and MgCO3 are determined in plant laboratories or stated in mineral deposits passport.

Activity data carbonate is CaCO3, MgCO3 or other alkali earth or alkali carbonates

amount that is used during the reporting period input (clay). Carbonate mass is estimated using clay consumption amount and results of clay content measurement with maximal

allowable process uncertainty of ± 2.5% (Table 4.19).

Table 4.19 Data and assumptions used for CO2 emission estimation from 2nd

bricks production plant

1990 1995 2000 2005 2006 2007 2008

Use of clay (Gg) NO NO 16.37 22.983 28.559 37.203 13.975

MgCO3 content (%) NO NO 5.00% 10.98% 9.56% 9.52% 9.50%

CaCO3 content (%) NO NO 9.00% 13.06% 13.15% 13.10% 13.10%

MgCO3 amount (Gg) NO NO 0.819 2.523 2.729 3.542 1.328

CaCO3 amount (Gg) NO NO 1.473 3.002 3.756 4.874 1.831

MgCO3 CO2 EF (tCO2/t oxide) NO NO 0.522 0.522 0.522 0.522 0.522

CaCO3 CO2 EF (tCO2/t oxide) NO NO 0.440 0.440 0.440 0.440 0.440

CO2 emissions (Gg) NO NO 1.076 2.638 3.077 3.993 1.500

Average CO2 EF (tCO2/t oxides) NO NO 0.469 0.477 0.475 0.475 0.474

As it was mentioned the plant wasn’t operated in 2009 and it is approved that most likely the plant will not be reopened again.

3rd bricks production plant

CO2 emission that 3rd plant is estimated for 1998-2004 in its application for GHG permit

during the implementation of ETS in Latvia by using the methodology that is not in line with IPCC Guidelines. Still in the application the plant had reported the MgO and CaO content data in used dry clay so the emissions were recalculated using the available activity data.

The CO2 emissions from particular bricks production plant was recalculated for 2008 and 2009 as the methodology use was stated as consistent only in 1998-2007 although the

methodology was changed in 2005. The methodology was changed from one approach – alkali earth oxides, to other approach – carbon input because the carbon input laboratory measurement data is available since 2005. As both methodologies are appropriate and both

are assumed as Tier2 therefore the methodology change was considered as acceptable.

Still for years 2008-2009 lower tier emission factor from MRG41 – a conservative value of 0.2

tonnes CaCO3 (corresponding to 0,08794 tonnes of CO2) per tonne of dry clay, was used to estimate CO2 emissions. The plant indicates that the lower tier use is acceptable within EU ETS as the plant is low emission producer.

Methods

For 1998-2004 the plant is using calculation method B – alkali earth oxides, from the MRG

when calculation is based on the content of the CaO, MgO and other (earth) alkali.

According to bricks production plant’s reported information the following equation to estimate CO2 emissions was used:

CFEFADADCO MgOCaOraw ,2

41




187

where:



ADCaO,MgO – CaO and MgO content in used raw materials (%)

EF – CO2 emission factor of CaO and MgO (Gg/Gg)


The plant for time period 2005-2007 is using the calculation method A – carbon input, from

the MRG when calculation is based on the carbon input on each of the relevant raw materials. As it was mentioned above the plant in using different methodology again for 2008-2009 so the data was recalculated using the emission estimation method as for 2005-2007. Following

equation from MRG is used to estimate emissions for 2005-2012:

33332 MgCOMgCOrawCaCOCaCOraw EFADADEFADADCO

where:

CO2 – CO2 emissions from 3rd


ADraw – activity data of used clay (Gg)





Emission factors

CO2 emission factors for CaO and MgO – 0.785 and 1.092 for tonne CO2 per tonne of oxide respectively, were taken from MRG42 (Table 4.2.17).

CO2 emission factors for CaCO3 and MgCO3 – 0.44 and 0.522 for tonne CO2 per tonne of carbonates respectively, were taken from MRG43 to recalculate the emissions (Table 4.20,

Table 4.21).

Activity data

For 1998-2004 emission estimation MgO and CaO content is used. According to mineral

passport of State Geology Service’s quarry ―Progress‖ alkali earth oxides – MgO and CaO, contents are 8.03% and 3.02% respectively.

For years 2005-2007 emission estimation the contents of CaCO3 and MgCO3 are determined in plant laboratories or stated in mineral deposits passport and are 12.79% and 10.75% respectively. As for year 2008-2009 the carbonates input percentage amount is not known the

data of 2005-2007 was used (Table 4.20, Table 4.21).

According to production plant’s application for GHG permit and annual GHG reports activity

data of used raw materials is estimated using following equation:

MADAD clayraw 1

where:

ADraw – activity data of used raw materials – dray clay (Gg)

ADclay – amount of used clay (Gg)

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188

M – moisture content of clay in bricks pressing process (%)

For year 2005-2013 the activity data was estimated by using following equation from bricks production plant’s GHG report:

avbulkraw MADAD

where:


ADbulk – amount of dried bulk materials (p ieces)

Mav – average mass with 0% moisture content (Gg)

The activity data was estimated by plant randomly taking 10 examples of production from drying tunnels dried after that till 0% moisture content and weighted. After that average mass

of production is estimated. So for year 2005-2013 the used clay is reported already with 0% moisture content.

The used raw materials – used clay, were estimated by taking into account the moisture

content of the clay.

Table 4.20 Data and assumptions used for CO2 emission estimation from 3rd bricks production plant

1990 1995 2000

use of clay (Gg) NO NO 10.25

moisture content (%) NO NO 17.00%

used raw materials - dry clay (Gg) NO NO 8.51

MgO content (%) NO NO 8.03%

CaO content (%) NO NO 3.02%

MgO amount (Gg) NO NO 0.683

CaO amount (Gg) NO NO 0.257

MgO CO2 EF (tCO2/t oxide) NO NO 1.092

CaO CO2 EF (tCO2/t oxide) NO NO 0.785

CO2 emissions (Gg) NO NO 0.95

Average CO2 EF (tCO2/t oxides) NO NO 1.008

Table 4.21 Data and assumptions used for CO2 emission estimation from 3rd bricks production plant

(continuation)

use

of

cla

y (

Gg

)

Mg

CO

3 c

on

ten

t

(%)

CaC

O3 c

on

tent

(%)

Mg

CO

3 a

mo

un

t

(Gg

)

CaC

O3 a

mo

un

t

(Gg

)

Mg

CO

3 C

O2 E

F

(tC

O2/t

ox

ide)

CaC

O3 C

O2 E

F

(tC

O2/t

ox

ide)

CO

2 e

mis

sio

ns

(Gg

)

Av

era

ge C

O2 E

F

(tC

O2/t

ox

ides)

2005 29.891 10.75% 12.79% 3.213 3.823 0.522 0.440 3.359 0.477

2006 22.316 10.75% 12.79% 2.399 2.854 0.522 0.440 2.508 0.477

2007 23.854 10.75% 12.79% 2.564 3.051 0.522 0.440 2.681 0.477

2008 77.687 10.75% 12.79% 8.351 9.936 0.522 0.440 8.730 0.477

2009 19.814 10.75% 12.79% 2.13 2.534 0.522 0.440 2.230 0.477

2010 32.513 10.75% 12.79% 3.495 4.158 0.522 0.440 3.650 0.477

2011 38.914 10.75% 12.79% 4.183 4.977 0.522 0.440 4.370 0.477

2012 40.698 10.75% 12.79% 4.375 5.205 0.522 0.440 4.570 0.477

2013 49.705 10.75% 12.79% 5.343 6.357 0.522 0.440 5.586 0.477


189

4th bricks production plant

The CO2 emission estimation from 4th bricks production plant is rather complicated due to allowed approach in Latvia that Latvia’s ETS operator can use diffe rent methodology for every year to estimate their CO2 emissions.

After the review of 4th bricks production plant’s application for GHG permit during ETS implementation in Latvia and the plant’s annual GHG reports in 2005-2008 the plant’s used

methodology for CO2 emission estimation in time series is inconsistent as methodology is changed four times during whole time series:

1. CO2 emission for time period 2000-2004 was estimated by using used clay (with

moisture content 23%) as an activity data and CO2 emission factor for used clay – 0.0658 tCO2/t used clay. Then CO2 emission factor for dry clay is estimated by

reducing it by 23% that gives emission factor – 0.050666 tCO2/t used clay.

2. The plant for year 2005 is using the calculation method A – carbon input, from the MRG when calculation is based on the carbon input on each of the relevant raw

materials. The content of CaCO3 and MgCO3 are determined in plant laboratories or stated in mineral deposits passport. Default CO2 emission factors from the MRG for

the CaCO3 and MgCO3 are used.

3. For years 2006 and 2007 the plant is using calculation method B – alkali earth oxides, from the MRG when calculation is based on the content of the CaO, MgO and other

(earth) alkali.

4. For year 2008 plant is using the same calculation method A as for year 2005– carbon

input, from the MRG when calculation is based on the carbon input on each of the relevant raw materials. Still Tier 1 emission factors from the MRG corresponding particular method are used when conservative value of 0.2 tonnes CaCO3 (0.08794

tonnes of CO2) per tonne of dry clay is applied for the calculation of the emission factor instead of results of analyses.

So to make emission estimation more consistent CO2 emissions from 4th bricks production plant was recalculated:

1. for years 2000-2004 were recalculate by using the CaCO3 and MgCO3 content data

reported by plant in its application for GHG permit when ETS was implemented in Latvia – CaCO3 – 11.48%, and MgCO3 – 1.8%, and using emission factors from

MRG.

2. For year 2006-2007 the CaCO3 and MgCO3 content data were estimated from MgO and CaO content data corresponding molar mass of MgO, CaO and CO2.

3. For year 2008 the same CaCO3 and MgCO3 content data as for 2007 was used in emission estimation as other information was not available (Table 4.22).

Methods

As bricks production plant is constantly changing used methodology to estimate their annual CO2 emissions within ETS requirements, the emissions were recalculated using the most

appropriate approach for the best result. As the CaCO3 and MgCO3 content data was available for 2000-2004 and then for 2005 but MgO and CaO content data was available for 2006-2007

it was decided to estimate CO2 emissions using Calculation A method – carbon input from MRG44.

The following equation was used to estimate CO2 emissions from 4th bricks production plant:

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190

33332 MgCOMgCOclayCaCOCaCOclay EFADADEFADADCO

where:

CO2 – CO2 emissions from 4th


ADclay – activity data of used clay (Gg)





Emission factors

CO2 emission factors for CaCO3 and MgCO3 – 0.44 and 0.522 for tonne CO2 per tonne of carbonates respectively, were taken from MRG45 to recalculate the emissions.

Activity data

The plant reported that amount of carbonates (CaCO3 and MgCO3) in used clay is estimated

according to chemical content of clay that was determined in Institute of Silicate Materials. For years 2005 the CaCO3 and MgCO3 content is taken from production plant’s annual GHG report. For years 2006-2007 CaCO3 and MgCO3 data was estimated by taking into account

used clay content data and its estimation parameters available from bricks production plant. For year 2008 that particular data was no available so the percentage amount of carbonates of

year 2007 was used (Table 4.22).

According to production plant’s application for GHG permit and annual GHG reports activity data of used raw materials is estimated using following equation:

tenisitechippingsbulkavbulkraw MMmoistureMMADAD 100/

where:



Mav – average mass (Gg)

Mbulk – mass of dried bulk materials loaded in furnace

moisture/100 – average moisture content of clay (%)

Mchippings – mass of dried scobs (Gg)

Mtenisite – mass of tenisite (granulated burnt defectives of ceramics) (Gg)

Mass of chippings wasn’t taken into account as it is biomass and is assumed as CO2 neutral.

Mass of tenisite – granulated burnt defectives of previously made ceramics that is folded into mass of clay to improve lasting of final production, is not taken into account as it is secondary

process and during repeated burning the CO2 emissions are not emitted.

Table 4.22 Data and assumptions used for CO2 emission estimation from 4th bricks production plant

1990 1995 2000 2005 2006 2007 2008

use of clay (Gg) NO NO 9.000 25.246 29.826 34.166 27.329

MgCO3 content (%) NO NO 1.80% 6.47% 6.47% 6.67% 6.67%

CaCO3 content (%) NO NO 11.48% 14.62% 14.62% 13.71% 13.71%

45




191

MgCO3 amount (Gg) NO NO 0.162 1.634 1.929 2.28 1.824

CaCO3 amount (Gg) NO NO 1.033 3.691 4.361 4.684 3.747

MgCO3 CO2 EF (tCO2/t oxide) NO NO 0.522 0.522 0.522 0.522 0.522

CaCO3 CO2 EF (tCO2/t oxide) NO NO 0.440 0.440 0.440 0.440 0.440

CO2 emissions (Gg) NO NO 0.539 2.477 2.926 3.251 2.601

Average CO2 EF (tCO2/t oxides) NO NO 0.451 0.465 0.465 0.467 0.467

In year 2009 the bricks production plant is not operating due to economic crisis that affected

construction sector in Latvia where demand of the production sharply decreased. Still the non-operation of particular plant is assumed only temporary and it is prospective that plant will be operating again.

5th bricks production plant

In the bricks production plant’s application for GHG permit during the implementation of

ETS in Latvia in 2005 the CO2 emission for time period 1993-2004 was estimated by using used clay as an activity data and CO2 emission factor for used clay – 0.047 tCO2/t used clay. After the review of the GHG report it was stated that plant is using the total used clay data as

activity data instead of using particular CaO and MgO data even the MgO and CaO content is determined in Riga Technical University Institute of Silicate Materials for the clay used in

particular plant. The plant’s used an unknown source CO2 EF for time series 1993-2004 so plant’s reported data were recalculated according to available information and using the methodology from plant’s latest reported annual GHG reports.

Methods

The particular bricks production plant is using Calculation method B – alkali earth oxides,

from MRG46. According to MRG calcination of CO2 is calculated based on the amounts of ceramics produced and the CaO, MgO and other (earth) alkali oxide contents of the ceramics.

Following equation from bricks production plant’s annual GHG reports within EU ETS was

used to estimate CO2 emissions.

where:



ADCaO,MgO% / 100 – CaO and/or MgO content in used raw materials (%)

EF – CO2 emission factor of CaO and/or MgO (Gg/Gg)


For some years in bricks production also CaCO3 was used as additive to clay for yellow

bricks production. Following equation from plant’s annual GHG reported was used to estimate CO2 emissions from CaCO3 use:

CFEFADADCO additiveraw 785.11002

where:

46




192

CO2 – total CO2 emissions from additive use (Gg)


ADadditive% / 100 – CaO content in used raw materials (%)

1.785 – factor to estimate CaO from used CaCO3 data

EF – CO2 emission factor of CaO (Gg/Gg)


In latest years 2008-2013 the CO2 emissions were estimated for different bulks of used clay

so CaO and MgO content data for these bulks differs. Therefore the CO2 emissions were estimated separately. (Table 4.23)

Table 4.23 Data and assumptions used for CO2 emission estimation from 5th bricks production plant

Use

of

clay

(G

g)

MgO

conte

nt (%

)

CaO

conte

nt (%

)

MgO

am

ount (G

g)

CaO

am

ount (G

g)

MgO

CO

2 E

F (

tCO

2/t o

xid

e)

CaO

CO

2 E

F (

tCO

2/t o

xid

e)

CaC

O3 (

additiv

e) (

Gg)

CO

2 e

mis

sion

s (G

g)

Aver

age

CO

2 E

F (

tCO

2/t o

xid

es)

1990 NO NO NO NO NO NO NO NO NO NO

1995 107.38 1.43% 10.39% 1.536 11.152 1.092 0.785 0.000 10.431 0.822

2000 112.50 1.43% 10.39% 1.609 11.683 1.092 0.785 0.000 10.928 0.822

2005 88.29 0.39% 1.75% 0.344 1.545 1.092 0.785 0.000 1.589 0.841

2006 94.44 0.39% 1.75% 0.368 1.653 1.092 0.785 0.342 1.849 0.841

2007 80.90 0.36% 1.47% 0.291 1.189 1.092 0.785 1.218 1.787 0.845

2008 26.32 1.23% 0.32% 0.324 0.084 1.092 0.785 0.000 1.594 1.029

28.33 1.35% 0.41% 0.382 0.116 1.092 0.785 1.020

28.82 1.26% 0.38% 0.363 0.110 1.092 0.785 1.021

13.21 1.09% 0.25% 0.144 0.033 1.092 0.785 1.035

2009 1.05 1.09% 0.25% 0.011 0.003 1.092 0.785 0.000 0.647 1.035

21.02 1.07% 0.27% 0.225 0.057 1.092 0.785 1.030

22.05 1.16% 0.27% 0.256 0.060 1.092 0.785 1.034

1.19 1.12% 0.23% 0.013 0.003 1.092 0.785 1.040

2010 0.82 1.12% 0.23% 0.009 0.002 1.092 0.785 1.019 1.396 1.040

21.05 1.23% 0.26% 0.259 0.055 1.092 0.785 1.038

21.15 1.13% 0.24% 0.239 0.051 1.092 0.785 1.038

20.80 1.16% 0.28% 0.241 0.058 1.092 0.785 1.032

2011 17.72 1.12% 0.23% 0.198 0.041 1.092 0.785 2.875 2.638 1.040

26.51 1.23% 0.26% 0.326 0.069 1.092 0.785 1.038

25.05 1.13% 0.24% 0.283 0.060 1.092 0.785 1.038

24.07 1.16% 0.28% 0.279 0.067 1.092 0.785 1.032

2012 21.17 1.12% 0.23% 0.237 0.049 1.092 0.785 2.465 2.287 1.040

20.83 1.23% 0.26% 0.256 0.054 1.092 0.785 1.038

18.59 1.13% 0.24% 0.210 0.045 1.092 0.785 1.038

21.41 1.16% 0.28% 0.248 0.060 1.092 0.785 1.032


193

Use

of

clay

(G

g)

MgO

conte

nt (%

)

CaO

conte

nt (%

)

MgO

am

ount (G

g)

CaO

am

ount (G

g)

MgO

CO

2 E

F (

tCO

2/t o

xid

e)

CaO

CO

2 E

F (

tCO

2/t o

xid

e)

CaC

O3 (

additiv

e) (

Gg)

CO

2 e

mis

sion

s (G

g)

Aver

age

CO

2 E

F (

tCO

2/t o

xid

es)

2013 20.75 1.02% 0.25% 0.212 0.052 1.092 0.785 5.863 3.744 1.032

20.28 1.22% 0.39% 0.247 0.079 1.092 0.785 1.018

18.48 1.20% 0.30% 0.222 0.055 1.092 0.785 1.031

20.60 1.20% 0.03% 0.247 0.006 1.092 0.785 1.085

Emission factors

CO2 emission factors for CaO and MgO – 0.785 and 1.092 for tonne CO2 per tonne of oxide respectively, were taken from MRG47. In plant’s application to GHG permit unknown source

emission factor was used so the data for 1993-2004 was recalculated using emission factor from MRG.

Activity data

According to production plant’s application for GHG permit and annual GHG reports activity data of used raw materials is estimated using following equation:

100/moistureMMADAD bulkavbulkraw

where:



Mav – average mass (Gg)

Mbulk – mass of dried bulk materials

moisture/100 – content of moisture (%)

Content of CaO and MgO in used clay is determined in independent certified laboratory taking analysis of used clay. Used additives – CaCO3 (limestone flour) is weighted in

production plant before addition to clay.

For years 1993-2004 the CaO and MgO content was unknown as such laboratory measurements were not done before EU ETS implementation requirements. The CaO and

MgO content data was determined only in the end of 2003. This part icular amount was then used for all years in time period 1993-2004 as other data was not available.


The uncertainty of activity data for this sector is assumed as 2%. The activity data reported in

production plant’s annual GHG reports within EU ETS is verified by accredited verifiers and Latvia’s Regional Environmental Boards so the activity data is adequately verified.

47




194

CO2 emission factors used in emission calculation from tiles production are the default from

MRG so the uncertainty of emission factors is assumed as 50%.


series. Only CO2 emissions from tiles production are estimated. Other emissions are not estimated due to lack of official emission estimation methodology and emission factors.

The uncertainty of activity data for the bricks production sector is assumed as 10% although the plants’ reported data is used. Plants are used several emission estimation methodologies and for some historical years the reported data seems to be less reliable.

CO2 emission factors used in emission calculation from bricks and tile production are the default from Monitoring and Reporting Guidelines within EU ETS so the uncertainty of

emission factors is assumed as 50%.

For years 1990-1992 and 1993-2008 two different emission estimation methodologies are used still the time series is assumed as consistent as for 1990-1992 default Tier1 methodology

is used but for 1993-2008 already plant specific emission estimation methodology assumed as Tier2 level is used.

For time period 1993-2008 two different methodologies are used for 3rd bricks production plant so that could lead to inconsistent time series although it is assumed that these are plant specific data and there is no need to recalculate them with using default emission factors or

average carbonates content data.

Only CO2 emissions from bricks production are estimated. Other emissions are not estimated

due to lack of official emission estimation methodology and emission factors.



Activity data, CO2 emission factor and estimated emissions are taken from the annual GHG

reports that tiles production plant submit within EU ETS.

CO2 emission factors for tiles production are taken from MRG and are the default ones

therefore there is no need to re-check correctness of emission factors.



QA/QC plan approved in national legislation. All findings were documented and introduced in GHG inventory. All corrections are archived.

Plant specific CO2 emission factors and Tier 2 CO2 emission estimation methodology

Tier2 methodology is used to estimate CO2 emissions from bricks production using plant specific data of used clay characteristics – amount of carbonates, percentage division of

carbonates and Tier2 methodology from IPCC GPG 2000.

Activity data is taken from plants reported annual GHG reports within EU ETS. All GHG

reports are verified by the ISO accredited verifiers that checks that all reported information is correct and corresponds to certain requirements from the legislation. Regional Environmental Boards also checks the annual GHG reports and approves the report if everything reported is

correct.

CO2 emission factors are taken from MRG and are the default ones therefore there is no need

to re-check correctness of emission factors.


195

All estimations of the emissions done in the LEGMC also are checked on the logical mistakes

by checking the time series of the activity data, emission factors and emissions consistency to display all significant and illogic changes in the activity data and emissions.


comparing EU ETS data with GHG inventory emissions. EU ETS registry administrators has an Excel file containing a list of all operators participating in EU ETS and those verified

emissions that are compared with ITL (International Transaction Log) records. Such consistency checks are done in all IPPU sectors.


No recalculation has been done for the sector.


According to in country review in September of 2013 the ERT recommends Latvia to report

aggregated brick production emissions in one line in the CRF table to avoid misunderstanding as incomplete reporting for a single plant, and in the meanwhile include plant-specific estimates in the NIR for the sake of transparency. On submission 2015 there are made some

technical updates in CRF under sector 2.A.4.a Ceramics following to ERT recommendations and all emissions from bricks production are reported in aggregated manner.

4.2.6 Other Process Uses of Carbonates (2.A.4.d)


There is no other process use of carbonates in Latvia. Under sector 2.A.4.d Other there are

reported NOx, CO and NMVOC emissions from cement production as there is not technically possible to report in CRF software these emissions under 2.A.1 Cement production sector.

4.3 CHEMICAL INDUSTRY (CRF 2.B)


Although there are strong traditions of the chemical industry in Latvia there are nonchemical industry production processes listed in 2006 IPCC Guidelines or EMEP/EEA 2013 that generate GHG emissions.

The biggest part of chemical industry is medicine production and then small part of paints and varnishes production.

In sector 2.B.10.a there are calculated particular matters from phosphate fertilizers but these emissions are not reported under Climate convention as GHGs.

4.4 METAL INDUSTRY (CRF 2.C)

4.4.1 Iron and Steel Production (CRF 2.C.1)


CO2 emissions from crude iron as input material in iron and steel production in open-heart

furnaces as well as crude iron used in electric arc furnaces are included in the inventory


196

according to 2006 IPCC Guidelines excluding scrap metal use in crude steel production. The

indirect GHG emission sources are also included under iron and steel production.

Table 4.24 Emissions from 2.C Metal Production in 1990–2013 (Gg)

CO2 CH4 NOx CO NMVOC SO2

1990 12.8161 0.0028 2.8050 0.0006 0.0110 0.0880

1995 4.4285 0.0014 1.4246 0.0003 0.0056 0.0447

2000 8.4212 0.0025 2.5515 0.0005 0.0100 0.0800

2005 12.3471 0.0028 2.8272 0.0006 0.0111 0.0887

2006 12.5617 0.0028 2.8282 0.0006 0.0111 0.0887

2007 14.5692 0.0028 2.8466 0.0006 0.0112 0.0893

2008 8.7255 0.0027 2.7054 0.0005 0.0106 0.0849

2009 9.5601 0.0022 2.2463 0.0004 0.0088 0.0705

2010 11.2761 0.0027 2.7300 0.0005 0.0107 0.0856

2011 0.7160 0.0008 0.0218 0.0002 0.0077 0.0101

2012 2.8725 0.0042 0.1087 0.0008 0.0385 0.0502

2013 0.9554 0.0010 0.0251 0.0002 0.0089 0.0116

Biggest decrease occurred in time period 1990–1992 due to changes in Latvia’s national economy (Table 4.24). Decrease of CO2 emissions in 1990–1996 also occurred due to

decrease of used crude iron in open-hearth furnaces (OHF) as CO2 emissions are estimated only from crude iron use excluding used scrap metal part. It is explained with modification of production process when biggest part of primary and final steel products is produced by

smelting of scrap metal.

CO2 emissions increased almost twice in 2002–2003 when amount of used crude iron

increased but amount of used scrap metal remains in same level. Final amount of steel products produced in only metal industry facility fluctuates in small range in latest years. After going through a crisis in 2008-2009, there are increased all emissions from Metal

production in 2010. In 2011 there are sharply decrease of emissions due to changing technology of metal production, so also decreased amount of steel produced in electric arc

furnaces (EAF) (about 75.11%) and mass of steel produced in OHF (about 68.67 %). Since mid-2011 the OHF is not used in this company (the installations are dismantled). At the end of 2010 installation was dismantled and new one was set up. In 2011 plant was working only

4 months. All crude steel is produced from scrap metal only in EAF. In 2011-2013 there are produced all amount of crude steel in EAF only and plant wasn’t operated a full year but only

5-7 month in a year.


IPCC 1996, IPCC GPG 2000 Tier2, EMEP/CORINAIR 2009 and EMEP/EEA 2013 are used to calculate direct and indirect GHG emissions from the 2.C.1 Steel Production sector. There is only one Iron & Steel production plant in Latvia that produces crude steel by melting crude

iron and not only by melting scrap metals. The plant is participant of EU ETS and submits their annual GHG reports to LEGMC. It is possible to obtain more accurate and complete

activity data and emission factors from enterprise that is involved in the emission trading system. Till Submission 2008 CO2 emissions from plant’s GHG reports were taken to report emissions from crude steel production.

After the In-country review 2007 the CO2 emissions were completely recalculated according to IPCC GPG 2000 as methodology of CO2 emission estimation from Monitoring and


197

Reporting Guidelines48 within EU ETS didn’t correspond to production technology used in

plant.

Calculation of all emissions from processes is done with Excel databases developed by experts from LEGMC. CRF Reporter software developed by experts from UNFCCC was used

to report emission data.

CO2 emission estimations from crude steel production

Methods

IPCC GPG 2000 Tier2 method is based on estimation of carbon losses through the production processes when remaining carbon is emitted to air.

CO2 emissions were estimated only from crude iron used. In steel production plant mostly steel is produced by melting scrap metal that doesn't produce CO2 emissions by leaking

carbon. The only amount of total produced steel is reported by steel production company that means that the total amount of steel produced by using crude iron and melting scrap metal is known. Therefore it is needed to estimate the crude steel amount that is produced only by

using crude iron and that caused CO2 emissions. This amount is then used as activity data.

Following equation from IPCC GPG 2000 is used to calculate CO2 emissions from steel

production:

EAFin Produced Steel of MassfactorEmission

12/44Steel Crude in theCarbon of Mass

- Production Steel Crudefor usedIron Crude in theCarbon of Mass

EAF

+)

(=Emissions steelcrude

According to information reported by steel producer:

Average carbon content of crude iron using in steel production is 3 – 4% in 1990-

2006, 4% for 2007, 2009-2013 and 3% for 2008;

Average carbon content of produced steel is 0.1 – 0.4% for 1990-2006, 0.3% for

2007-2008 and 0.2% for 2009-2013.

Carbon emitted from consumed electrodes in electric arc furnaces has to be taken into account. These emissions are estimated by multiplying emission factor with mass of steel

produced in electric arc furnaces.

Emission factors

Till 2008 there were used default emission factor- 1.5 kg carbon per tonne of steel and after there are used data reported by steel production plant. There are used as far as possible plant provided activity data and emission factors and as possible applicable higher tier method

according to available data.

Activity data

For year 1990-2006 the used amount of raw materials in different types of production installations – open-hearth furnaces and electric arc furnaces was known as CSB reported the data to LEGMC even though the data could be confidential. Total produced amount of crude

steel was known without division into particular production installations. So it was necessary to divide amount of crude steel produced in open-hearth furnaces and in electric arc furnaces.

These amounts are estimated by using amount of raw materials used in open-hearth furnaces and electric arc furnaces (used raw materials in different furnaces related to total used raw

48




198

materials) and the same percentage is related to amount of produced steel. Accordingly

amount of steel produced in open-hearth furnaces and in electric arc furnaces is divided from total produced crude steel.

For years 2007-2008 the total produced crude steel amount divided by used production

technologies was reported by plant but the plant couldn’t report the used raw materials divided by production technologies. The steel producer reported that it’s not possible to divide

these two amounts, as plant doesn’t do it.

So the used raw material amount in 2007-2009 was divided by the same percentage raw material divided in 2006:

99.59% of total used scrap metals were used in open hearth furnaces;

95.52% of total used crude iron were used in open hearth furnaces.

Since large amount of scrap metals is used in crude steel production it is necessary to exclude this amount from total crude steel amount and to estimate only the amount of crude steel in

what production crude iron was involved. It is estimated by using crude iron / scrap metal ratio since amounts of used scrap metal in openhearth furnaces and used crude iron in the

same furnaces are known. Then this ratio number is multiplied with amount of steel produced in openheart furnaces to estimate amount of crude steel produced directly from crude iron.

Coke in crude steel production process is used as reducing agent to decrease the carbon

content in final produced crude steel. The coke is combusted in production process and emissions from coke use is reported in 1.A.2.a Iron & Steel sector of Energy sector. Data for

CO2 emission estimations are given in Table 4.25 below.

Table 4.25 Data for estimation of CO2 emissions from steel production (tonnes)

Cru

de

stee

l p

rod

uct

ion

(t)

% m

ass

of

stee

l p

rodu

ced

in

OH

F

Ma

ss o

f st

eel

pro

du

ced

in

OH

F(t

)

Use

d s

crap

met

al i

n o

pen

hea

rt

furn

aces

in

ste

el p

rod

uct

ion

(t)

Cru

de

iro

n u

sed

in o

pen

hea

rt

furn

aces

(t)

Cru

de

iro

n/s

crap

met

al r

atio

% m

ass

of

stee

l p

rodu

ced

in

EA

F

Ma

ss o

f st

eel

pro

du

ced

in

EA

F(t

)

Am

ou

nt

of

cru

de

stee

l in

wh

at

pro

du

ctio

n c

rud

e i

ron

wh

ere

inv

olv

ed(t

)

Car

bo

n c

on

tent

in

cru

de

iron

Car

bo

n c

on

tent

in

cru

de s

teel

Use

1.5

kg

per

ton

ne

EA

F f

or

2%

cru

de

iro

n

Co

nv

ersi

on

fac

tor

CO

2 (

Gg

)

1990 550000 98.74% 543074 537227 107732 20.05% 1.26% 6926 110293 3.50% 0.25% 0.0015 3.664 12.952

1995 279326 98.72% 275747 285015 37086 13.01% 1.28% 3579 36346 3.50% 0.25% 0.0015 3.664 4.477

2000 500292 99.23% 496434 503123 70637 14.04% 0.77% 3858 70240 3.50% 0.25% 0.0015 3.664 8.477

2005 554345 98.94% 548472 527950 104010 19.70% 1.06% 5873 109210 3.50% 0.25% 0.0015 3.664 12.461

2006 554546 98.90% 548419 531026 105769 19.92% 1.10% 6127 110454 3.50% 0.25% 0.0015 3.664 12.682

2007 558156 99.76% 556814 463940 109248 23.55% 0.24% 1342 131434 4.00% 0.30% 0.0015 3.664 14.603

2008 530462 99.34% 526964 492450 88319 17.93% 0.66% 3498 95136 3.00% 0.30% 0.0018 3.664 8.777

2009 440458 99.90% 440016 413058 68784 16.65% 0.10% 442 73347 4.00% 0.20% 0.0064 3.664 9.555

2010 535301 99.79% 534168 476868 81340 17.06% 0.21% 1133 91307 4.00% 0.20% 0.0061 3.664 11.283

2011 167624 NO NO NO NO 1.81% 100.00% 167624 167624 4.00% 0.20% 0.0018 3.664 0.716

2012 836431 NO NO NO NO 1.49% 100.00% 836431 836431 4.00% 0.20% 0.0014 3.664 2.873

2013 193190 NO NO NO NO 1.40% 100.00% 193190 193190 4.00% 0.20% 0.0030 3.664 0.955

CH4 and indirect GHG emission estimations from crude steel production

Methods


199

The CH4, NMVOC, CO, NOx and SO2 emissions from iron and steel production are

calculated at the LEGMC based on activity data from the CSB and steel production plant according to EMEP/CORINAIR 2007 and EMEP/EEA 2013 emission factors.

Emission factors

Emission factors of methane and indirect GHG emissions are taken from EMEP/CORINAIR 2007 methodology (Table 4.26).

Table 4.26 Emission factors of metal production (t/t)

CH4 NOx CO NMVOC SO2

Iron and Steel Production

In open

hearth

furnace

0.000005 0.0051 0.000001 0.00002 0.00016

In electric

arc furnace 0.000005 0.00013 0.0017 0.000046 0.00006

Emission factors for NOx, NMVOC and SO2 emissions are taken from EMEP/EEA 2013 according to methodology for estimations of emissions from processes in open-hearth

furnaces, where 95% of total steel production is produced till 2010 and for electric arc furnace starting from year 2011.

It has to be noted that for CH4, NMVOC, CO, NOx and SO2 emissions estimations total produced crude steel data is used but for CO2 emission estimation only crude steel produced from crude iron is taken into account and reported in CRF Reporter.


Only one enterprise operates in iron and steel industry category in Latvia and this facility

reports data of production and raw materials used in production processes. Still used raw materials data divided by technological processes aren’t available and are estimated by using

approximate percentage. So the uncertainty of activity data of iron and steel industry is assumed 25%.

CO2 emission factor is estimated according to plant specific data reported by steel producer

using IPCC GPG 2000 equations so the uncertainty of CO2 emission factor is assumed as 5%.

Uncertainty of CH4 emission factor taken from EMEP/CORINAIR 2007 methodologies is

assigned as 10% so it is apposite for open-hearth furnaces – technology mainly used in facility operated in iron and steel industry in Latvia till 2010. After there are produced all steel in electric arc furnaces.


series. GHG emissions from all sectors are estimated or reported as not occurring / not applicable therefore there are no ―not estimated‖ sectors.

Time series consistency was checked by verifying IEF, AD and emission changes and

attention was paid to important increase/decrease that are explained in NIR.


200


QA/QC check is performed with Tier1 method from 2000 IPCC GPG.



Quality control check list is filled for each category taking into account criteria given in QA/QC plan approved in national legislation. All findings were documented and introduced in GHG inventory. All corrections are archived.

Plant specific CO2 emission factors and Tier2 CO2 emission estimation methodology

Tier2 methodology is used to estimate CO2 emissions from steel production using plant specific data and Tier2 methodology from IPCC GPG.

All the activity data required in CO2 emission estimation IPCC GPG is reported by steel production plant to LEGMC within National legislation.

All estimations of the emissions done in the LEGMC also are checked on the logical mistakes by checking the time series of the activity data, emission factors and emissions consistency to display all significant and illogic changes in the activity data and emissions.

Checks performed pursuant to Article 7(1)(l) of Regulation (EU) No 525/2013 are done to comparing EU ETS data with GHG inventory emissions. EU ETS registry administrators

have an Excel file containing a list of all operators participating in EU ETS and those verified emissions that are compared with ITL (International Transaction Log) records. Such consistency checks are done in all IPPU sectors.


Latvia produces steel from crude iron and scrap metal using open hearth furnaces (OHFs) and electric arc furnaces (EAFs). Latvia has used equation 3.6B of the IPCC good practice guidance, which requires knowledge of the mass of crude iron input to the furnace and of the

mass of crude steel produced from the crude iron out of the furnace. In response to a question raised by the ERT during the review, Latvia confirmed that some crude iron is used for steel-

making in the EAFs, but because the two inputs required by the IPCC methodology (mass of crude iron used and mass of steel produced from crude iron) are not known for EAFs, the CO2 emissions from EAFs have not been estimated. The ERT considers that the exclusion of crude

iron in EAFs in the estimation of CO2 emissions from production of steel constitutes a potential underestimation of emissions in this category. Latvia submitted revised estimates

and the ERT considers that the revised estimates have resolved the issue. The revised emission estimates increased the CO2 emissions from the category metal production by 4.8 per cent (1.52 Gg CO2 eq) for the entire first commitment period (2008–2012).




201

4.5 NON-ENERGY PRODUCTS FROM FUELS AND SOLVENT USE (CRF 2.D)

4.5.1 Lubricant Use (CRF 2.D.1)


Under this category there are reported lubricant consumption as feedstocks in Latvia.

Emissions from lubricant is reported as „CO2 not emitted‖ because it is assumed that CO2

emissions is captured and not emitted to the air.

Consumption and emissions of lubricants are reported in sector 2.D.1 for all years in time

series 1990-2013 (Table 4.27).

Table 4.27 CO2 emissions from lubricant use 1990-2013 (Gg)

CO2

emissions

(Gg)

1990 0.571

1995 0.337

2000 0.308

2005 0.381

2006 0.381

2007 0.381

2008 0.367

2009 0.220

2010 0.205

2011 0.279

2012 0.323

2013 0.308


Emission factors

CO2 emissions are calculated according to Tier1 method and emission factors as well as default carbon content are taken from the2006 IPCC Guidelines. Carbon content for lubricant is 20.0 kg/GJ as default one taken from 2006 IPCC Guidelines Volume 2 Energy Chapter 1

Table 1.3.

Net calorific value (NCV) for lubricants is 41.86 TJ/103 t and are reported in energobalance

from Central Statistical Bureau of Latvia.

CO2 emissions are calculated using 2006 IPCC Guidelines equation 5.2:

CO2 Emissions = LC×CCLubricant×ODULubricant×44/12

Where:

CO2 emissions= CO2 Emissions from lubricants, tonne CO2

LC= Total lubricant consumption, TJ

CCLubricant=carbon content of lubricants (default), tonneC/TJ (=kg/ C/TJ)

ODU Lubricant =ODU(Oxidised during use) factor (based on default composition of oil and grease)fraction


202

44/12= mass ratio of CO2/C

Activity data

Activity data prepared by CSB and reported to EUROSTAT in EUROSTAT Annual

Questionnaire formats were used.

Lubricants are mainly used in transport sector. According to Transport sector expert the

percentage amount of lubricants that are combusted in mobile vehicles system was estimated. Approximately 99.7% in 2010-2013 from total lubricants consumption are used as feedstocks and therefore 99.7% of carbon is reported as stored. Only 0.3% of total lubricant consumption

is assumed as combusted and the emissions for the activity are included in Road Transport sector.

Table 4.28 Activity data for lubricant use 1990-2013

Consumption

of lubricants

(TJ)

Net calorific

value for

lubricants

(TJ/103 t)

1990 1632.54 41.86

1995 962.78 41.86

2000 879.06 41.86

2005 1088.36 41.86

2006 1088.36 41.86

2007 1088.36 41.86

2008 1046.5 41.86

2009 627.9 41.86

2010 586.04 41.86

2011 795.34 41.86

2012 920.92 41.86

2013 879.06 41.86


The default ODU factor for lubricant is taken from 2006 IPCC Guidelines and is very uncertain so that uncertainty of this factor is assumed as 50 %.

The carbon content coefficients is taken from 2006 IPCC Guidelines and are based on two studies of the carbon content and heating value of lubricants, from which an uncertainty range of about 3%.

Activity data are taken from CSB of Latvia and uncertainty are assumed as 2%.


QA/QC check is performed according to 2006 IPCC Guidelines. There are compared the amounts discarded, recovered and combusted in Transport sector with total consumption

figures in the calculation to check the internal consistency data and ODU factors if they are used in the calculation of different source categories across sectors.


203


No recalculations were done in this sector.

4.5.1.6 Source-specific improvements

No specific improvements are planned in this sector.

4.5.2 Paraffin Wax Use (CRF 2.D.2)


Under this category there are reported paraffin wax consumption as feedstocks in Latvia. Paraffin wax mainly are used in chemical substances and chemical production as well as

plastic, rubber and furniture production. Emissions from paraffin wax is reported as „CO2 not emitted‖ because it is assumed that CO2 emissions is captured and not emitted to the air.

Consumption and emissions of paraffin wax are reported in sector 2.D.2 for all years in time series 1990-2013. (Table 4.29)

Table 4.29 CO2 emissions from paraffin wax use 1990-2013 (Gg)

CO2

emissions

(Gg)

1990 NO

1995 NO

2000 0.044

2005 0.117

2006 0.088

2007 0.088

2008 0.073

2009 0.103

2010 0.161

2011 0.103

2012 0.088

2013 0.132


Emission factors

CO2 emissions are calculated according to Tier1 method and emission factors as well as

default carbon content are taken from the 2006 IPCC Guidelines. Carbon content for paraffin wax is 20.0 kg/GJ as default one taken from 2006 IPCC Guidelines Volume 2 Energy Chapter

1 Table 1.3.

Net calorific value (NCV) for lubricants is 41.86 TJ/103 t and is reported in Energy Balance from Central Statistical Bureau of Latvia.

CO2 emissions are calculated using 2006 IPCC Guidelines equation 5.4:

CO2 Emissions = PW×CCWax×ODUWax×44/12


204

Where:

CO2 emissions= CO2 Emissions from waxes, tonne CO2

LC= Total wax consumption, TJ

CCWax=carbon content of paraffin wax (default), tonneC/TJ (=kg/ C/TJ)

ODU Wax=ODU(Oxid ised during use) factor for paraffin wax, fract ion

44/12= mass ratio of CO2/C

Activity data

Activity data prepared by CSB and reported to EUROSTAT in EUROSTAT Annual Questionnaire formats were used. Data from statistics about paraffin wax consumption are available only from 1999.

Table 4.30 Activity data from paraffin wax use 1990-2013 (Gg)

Consumption

of paraffin

wax (TJ)

Net calorific

value for

paraffin wax

(TJ/103t)

1990 NO 41.86

1995 NO 41.86

2000 125.58 41.86

2005 334.88 41.86

2006 251.16 41.86

2007 251.16 41.86

2008 209.3 41.86

2009 293.02 41.86

2010 460.46 41.86

2011 293.02 41.86

2012 251.16 41.86

2013 376.74 41.86


The default ODU factor for paraffin wax are taken from 2006 IPCC Guidelines and are very uncertain due to depends on specific-country conditions and policies that uncertainty of this factor are assumed as 100 %.

The carbon content coefficient is taken from 2006 IPCC Guidelines and uncertainty range is about 5%.

Activity data are taken from CSB of Latvia and uncertainty are assumed as 2%.


QA/QC check is performed according to 2006 IPCC Guidelines. There are compared the amounts discarded, recovered and combusted with total consumption figures in the

calculation to check the internal consistency data and ODU factors if they are used in the calculation of different source categories across sectors.


205


No recalculations were done in this sector.


No specific improvements are planned in this sector.

4.5.3 Other (CRF 2.D.3)


This chapter describes emissions from Solvent Use, Road paving with asphalt and Asphalt roofing sector under Other (CRF 2.D.3).

Solvent Use

Use of solvents and products containing solvents results in emissions of non-methane volatile

organic compounds (NMVOC) which are regarded as an indirect greenhouse gases as it over a period of time will oxidize into CO2 when emitted to the atmosphere. Solvent Use sector was the largest pollution source of NMVOC emissions in Latvia in 2013

and it covered over 58.3% (50.81 Gg) from the total Latvia’s NMVOC emissions (Figure 4.5).

Figure 4.5 NMVOC emissions from Solvent Use in 1990–2013 (Gg)

Decrease in NMVOC emissions in the period 1990-2001 has occurred mostly due to the industry going through a crisis. There are not observe fluctuations from 2002 till 2006. At the

end of 2008 the world was struck by the economic crisis which also affected the Solvent Use sector in Latvia. There is stability in trends of NMVOC emissions from Solvent Use sector in

later years. For instance, emissions of NMVOC have decreased by 0.16 %, from 50.89 Gg NMVOC in 2012 to 50.81 Gg NMVOC in 2013.

Road paving with asphalt (2.D.3.b) and Asphalt roofing (2.D.3.c)

In this sector emissions from construction materials production as well as Road paving activities are reported.

According to CSB information the biggest part of NMVOC and CO2 occurs during road paving with asphalt. Just small part of all bitumen mixtures are used in asphalt roofing sector.


206

Figure 4.6 Emissions from asphalt roofing and road paving in 1990–2013 (Gg)49

The emissions from these two particular sectors are constantly increasing since the beginning of 90ties. Slight emission decrease in 1999-2000 is explained with the change of percentage

that is used to divide activity data used in roofing and road paving. The sharp emission increase in 2003-2004 is explained with Latvia’s accession to EU in the May of 2004 before

and after what the road paving works were very active. As it is explained previous there are tend to increase CO2 emissions from road paving and asphalt roofing activity in 2010. In 2011 and 2012 there are increased amount of activity data used for road paving and asphalt roofing

about 58.08% and 6.99% respectively. In 2013 there are decreased overall activity of bitumen use in industrial processes about 20.81% and it depends on financial resources that are

assigned directly to this sector for road paving or asphalt roofing (Figure 4.6).

Urea use

Urea are used as catalyst in fuel consumption and calculated under 1.A.3 Transport sector but emissions are reported under 2.D Non- energy Products from Fuels and Solvent Use (Table

4.31).

Table 4.31 Data from Urea use 2006-2013 (Gg)

Urea

co

nsu

mp

tio

n

(Gg

)

CO

2 e

mis

sio

ns

(Gg

)

1990 NO NO

1995 NO NO

2000 NO NO

2005 NO NO

2006 2.006 0.133

2007 2.007 0.419

2008 2.008 0.497

2009 2.009 0.471

2010 2.01 0.563

49

Emissions from road paving with asphalt on secondary axis


207

Urea

co

nsu

mp

tio

n

(Gg

)

CO

2 e

mis

sio

ns

(Gg

)

2011 2.011 0.521

2012 2.012 0.528

2013 2.013 0.538


Solvent Use

Methodologies for estimating NMVOC emissions can be found in EMEP/EEA air pollutant emission inventory guidebook 2013. In EMEP/EEA guidebook subcategory `Other solvent

and product use` of the Selected Nomenclature for sources of Air Pollution (SNAP) and is subdivided into subcategories. These subcategories accordance with EMEP/EEA guidebook

are:

SNAP 0601: Coating applications (Including such activities as paints and varnishes from decorative, industrial and other coating applications);

SNAP 0602: Degreasing, Dry cleaning (Degreasing includes cleaning products from water-insoluble substances such as grease, fats, oils waxes and tars. Dry cleaning

refers to any process to remove contamination from furs, leather, down leathers, textiles or other objects made of fibres using organic solvents);

SNAP 0603: Chemical products (Including the processing of polyester, PVC, foams

and rubber, manufacture of paints, inks, glues and adhesives and finishing of textile);

SNAP 0604: Domestic solvent use including fungicides; Printing and Other solvent

and product use (Including such activities as `enduction` (i.e. coating) of glass wool and mineral, printing industry, fat and oil extraction, uses of glues and adhesives, wood preservation, domestic use (other than paint application) and vehicle underseal

treatment and vehicle dewaxing).

Figure 4.7 NMVOC emissions from the di fferent Solvent Use subsectors in 1990–2013 (Gg)


208

In 2013 the biggest subcategory was Domestic solvent use including fungicides; Printing and

Other solvent and product use subsector (82.1% or 41.73 Gg NMVOC) (Figure 4.7). Coating applications constituted 10.9% or 5.55 Gg NMVOC and Chemical products – 6.9% or 3.5 Gg NMVOC emissions under Solvent Use sector. Degreasing and Dry Cleaning constitutes a

small amount of whole SNAP 0602.

From the 1990ties till 2005 statistics for Solvent Use was not well kept due to the country-

wide changes in governmental system and national economy. For 2006-2013 all activity data was obtained from the Chemical Register (CR) at Ltd. Latvian Environment, Geology and Meteorology Centre (except Chemical products (SNAP 0603)). In the CR data of imported

and produced amount of chemical products containing NMVOCs is collected together with the percentage of a particular NMVOC in imported or produced products. It is assumed that

the NMVOC containing products imported in the country in a particular year are utilized in the same year as the data of the actual use is not available or is confidential. In the CR information on a particular year, amount of produced and imported chemicals (ton), NACE

code, trade name, chemical name, CAS number and concentration (from … till %) is provided.

The average content of NMVOC in NMVOC containing product is calculated by arithmetic average and is presented in mass percentage. The percentage content is used as NMVOC emission factor. NMVOC emissions (Gg) from Solvent Use sector were calculated for the

time series 1990-2013 using the equation below.

ENMVOC = EFNMVOC AD where:

ENMVOC – non-methane volatile organic compounds emissions from solvents and other

production use (Gg);

EFNMVOC – emission factor is assumed as the average percentage of a particular NMVOC in

NMVOC containing product;

AD – activity data from the Chemical Register, Gg.

Statistics for Chemical products (SNAP 0603) also was not well kept from the 1990ties till 2003 due to the country wide changes in governmental system and national economy. For 2004-2013 all NMVOC emissions data is obtained directly from database ―2-Air‖ at Ltd.

Latvian Environment, Geology and Meteorology Centre. ―2-AIR‖ is database where enterprises (that do any pollution activity and have category A, B, or C polluting activity)

report their emissions data; it is approximately 3000 enterprises in total every year. From these approximately 3000 enterprises data is used only from the enterprises that produced NMVOC emissions according to the EMEP/EEA air pollutant emission inventory guidebook

2013. The enterprises have been reporting their produced NMVOC emissions dividing in a particular NMVOC. Activity data for time period 2004-2013 reported by enterprises is not

available as these data is not required to be reported and could be assumed as confidential.

To obtain a comparable data in time series for years where statistics was not well kept NMVOC emissions were calculated using the same methodology as for years 2006-2013 (for

Chemical products: 2004-2013). Assuming that base year for NMVOC emissions is year 2006 (for Chemical products: 2004), NMVOC emissions for years where statistics was not well

kept were calculated proportionally, taking into account the number of inhabitants provided


209

by the Central Statistical Bureau50. Therefore Implied emission factor (IEF) depends on the

amount of NMVOC containing products in particular year (activity data varies year to year).

Indirect CO2 eq (Gg) emissions from Solvent Use sector were calculated from NMVOC emissions for the time series 1990-2013 using the equation below:

EmissionsCO2 = EmissionsNMVOC Percent carbon in NMVOCs by mass

44.0098/12.011

It was assumed that the average carbon content is 60% by mass for all categories under the sector of Solvent Use sector in accordance with the 2006 IPCC Guidelines. As described in

the Guidelines, the used fossil carbon content fraction of NMVOC is based on limited and published national analyses of speciation profile.


EMEP/EEA 2013 Tier1 was used to estimate NMVOC emissions from the 2.D.3.b Road paving with asphalt and 2.D.3.c Asphalt roofing. According to CSB the biggest part of

bitumen mixtures amount is used for road paving. Only small part is used for roofing activities (Table 4.32).

NMVOC emissions are estimated using simpler default methodology:

ENMVOC = ADbitumen × EFNMVOC

where:

ENMVOC – NMVOC emissions (Gg)

ADbitumen – bitumen and bitumen mixtures used in CRF 2.D.3.b and 2.D.3.c activit ies (Gg)

EFNMVOC –NMVOC emission factor (Gg/Gg)

Indirect CO2 emissions from asphalt roofing and road paving with asphalt activities were estimated according to 2006 IPCC Guidelines provided methodology and explanation of

indirect CO2 emission estimation basing on carbon conversion factor and average default carbon content amount.

For the CO2 emission estimation NMVOC emissions were taken as activity data and CO2 emissions were estimated using carbon conversion factor.

NMVOCEFE COCO 22

where:

ECO2 – CO2 emissions (Gg)

EFCO2 – estimated CO2 emission factor

NMVOC – NMVOC emissions (Gg)

Emission factors

For CO2 emission estimation 80% of carbon content conversion factor are used. According to

2006 IPCC Guidelines 51 indirect emissions of CO2 from atmospheric oxidation of emitted NMVOC are included in the national emission inventory. The average amount of carbon in

50

http://data.csb.gov.lv/pxweb/lv/Sociala/Sociala__ikgad__iedz__iedzskaits/IS0020.px/table/tableViewLayout1/?rxid=cdcb978c-22b0-416a-aacc-aa650d3e2ce0

51 http://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/1_Volume1/V1_7_Ch7_Precursors_Indirect.pdf (page 7.6)

http://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/1_Volume1/V1_7_Ch7_Precursors_Indirect.pdf


210

NMVOC is assumed as 80%52. The default carbon content conversion factor from 2006 IPCC

Guidelines that is 60% was assumed as too low.

So the CO2 emission factor was estimated using following equation:

011.120098.44%802

COEF

where

EFCO2 – CO2 emission factor (Gg/Gg)

80% – the average amount of carbon in NMVOC

44.0098 / 12.011 – carbon dioxide and carbon molmass ratio

This leads to an emission factor for indirect CO2 release of 2.931299642 kg CO2/kg NMVOC.

Default CO and NMVOC emission factors are taken from EMEP/EEA 2013.53,54 Due to lack

of the technology use information Tier1 EFs were used (Table 4.32).

Table 4.32 Emission factors for as phalt roofing and Road paving in 1990–2013

CO2

(t CO2/t NMVOC)

CO (Gg/Gg)

NMVOC (Gg/Gg)

Asphalt Roofing 2.93 0.0000095 0.00013

Road Paving with Asphalt 2.93 NE 0.000016

Urea use

Description of methodology to calculate CO2 emissions from Urea use are reported under sector 1.A.3 Transport.


Solvent use

Uncertainty of available activity data for Solvent Use was ±2% by expert judgment in 2013.

Emission factor uncertainty is assumed to be ± 20% accordance with EMEP/EEA guidebook 2013, 2.D Other solvent and product use. Time series consistency was ensured by using one

method for all time series.


Uncertainty of activity data for estimations of CO2 emissions from 2.D.3.c Asphalt roofing

sector and 2.D.3.b Road paving with asphalt sector is assumed rather low as CSB data of used bitumen mixtures are used and the percentage of 2006 IPCC Guidelines is used to divide

bitumen use for roofing and paving activities. Still as it is not clearly known how much of the total bitumen is used for asphalt paving and for asphalt roofing (bitumen use in construction sector) the uncertainty is assumed as at least 20%.

The CO2 emission factors for 2.D.3.b and 2.D.3.c sectors are assumed as high as 70% because default emission factors are used and CO2 emissions are estimated from NMVOC emissions.

The uncertainty of indirect emission factors for these two sectors taken from EMEP/EEA 2013 as Tier1 EFs is assumed as high as 50% as the default emission factors are used.

52 Basing of the most often used average carbon conversion factor 53 http://www.eea.europa.eu/publications/emep-eea-emission-inventory-guidebook-2009/part-b-sectoral-guidance-chapters/2-industrial-

processes/2-a-mineral-industry/2-a-5-asphalt-roofing.pdf (page 7) 54 http://www.eea.europa.eu/publications/emep-eea-emission-inventory-guidebook-2009/part-b-sectoral-guidance-chapters/2-industrial-

processes/2-a-mineral-industry/2-a-6-road-paving-with-asphalt.pdf (page 9)

http://www.eea.europa.eu/publications/emep-eea-emission-inventory-guidebook-2009/part-b-sectoral-guidance-chapters/2-industrial-processes/2-a-mineral-industry/2-a-5-asphalt-roofing.pdf

http://www.eea.europa.eu/publications/emep-eea-emission-inventory-guidebook-2009/part-b-sectoral-guidance-chapters/2-industrial-processes/2-a-mineral-industry/2-a-5-asphalt-roofing.pdf

http://www.eea.europa.eu/publications/emep-eea-emission-inventory-guidebook-2009/part-b-sectoral-guidance-chapters/2-industrial-processes/2-a-mineral-industry/2-a-6-road-paving-with-asphalt.pdf

http://www.eea.europa.eu/publications/emep-eea-emission-inventory-guidebook-2009/part-b-sectoral-guidance-chapters/2-industrial-processes/2-a-mineral-industry/2-a-6-road-paving-with-asphalt.pdf


211


methodology, emission factors and data sources are used for sectors for all years in time series. NOx, CO and SO2 emissions are not estimated due to lack of estimation methodology and official emission factors.



Solvent use

QA/QC check is performed with Tier1 method from EMEP/EEA guidebook 2013, 2.D Other solvent and product use.



Quality control check list is filled for each category taking into account criteria given in QA/QC plan approved in national legislation. All findings were documented and introduced in GHG inventory. All corrections are archived in centralized archiving system (common FTP

folder).

Road paving with asphalt (2.D.3.b) and Asphalt roofing (2.D.3.c).

Activity data used in NMVOC and CO2 emissions from asphalt roofing and road paving with asphalt was reported by CSB in Annual Questionnaire tables. Bitumen data used in emission estimation and reported in NIR are verified by CSB. Data also is compared to the data

reported in 1A(d) sector.

CSB has the internal QA/QC procedures based on mathematical model and analysis to avoid

logic mistakes.

The activity data used in estimations is repeatedly verified by CSB energy experts by checking the data input in data estimation database and reported in the NIR.

All estimations of the emissions done in the LEGMC also are checked on the logical mistakes by checking the time series of the activity data, emission factors and emissions consistency to

display all significant and illogic changes in the activity data and emissions.

The QC form has been filled in for each category taking into account criteria given in QA/QC plan approved in national legislation. Form then is archived.


Solvent use

No improvements are planned under Solvent Use sector.


No improvements are planned under Road paving with asphalt and Asphalt roofing sector.

4.6 ELECTRONICS INDUSTRY (CRF 2.E)

In accordance with 2006 IPCC Guidelines Parties are requested to estimate emissions from

Electronics industry which includes manufacturing of integrated circuit of semiconductors, TFT flat panel displays, photovoltaics and heat transfer fluids.


212

There is one enterprise in Latvia which manufactures liquid crysta l displays (LCDs) and 3D

products for industrial, professional, medical and defence applications. Directly contacting with the company there was received an information that they don`t use the NF3 in their technology as well as they haven`t planned to use it in the future.

Other types of equipment listed in 2006 IPCC Guidelines under this subsector are not being manufactured in Latvia thus relevant categories are marked as ―NO‖ in CRF tables.

4.7 PRODUCT USES AS ODS SUBSTITUTES (CRF 2.F)

This category covers emissions from hydrofluorocarbons (HFC), perfluorocarbons (PFC), sulphur hexafluoride (SF6) (hereinafter F-gases). Latvia has ratified Convention for the

Protection of the Ozone Layer (Vienna, 1985) and it’s Protocol on Substances Depleting the Ozone Layer (Montreal, 1987). These documents are aimed to take out the circulation of

completely halogenated alkanes (CFC-11, CFC-12, CFC-113, and CFC-114), partly halogenated alkanes (CFC-22, CFC-21) and halons, and to substitute them with alternative substances – F gases.

The usage of products which substitute OSDs and SF6 in Latvia mainly depends on import. F-gases are imported either in bulk by trade or for domestic consumption (new equipment filling

up, refilling of equipment) or in already filled equipment.

The first basic investigation on Latvia`s consumption of F gases was carried out in 2004. In the framework of the project ―SF6, HFC and PFC emission inventory in Latvia 1995-2003‖ 55

the areas and users of HFC, PFC and SF6 gases in Latvia were identified and initial activity data was obtained. The sources of emissions (in accordance with IPCC 1996 methodology)

and availability of activity and consumption data were assessed. This information was used for elaboration of questionnaire forms which were sent to 120 enterprises operating with F – gases. As the response from the enterprises was relatively low (about 28%), the expert had

also find other ways to collect necessary data (i.e. use activity data from CSB, do the extrapolation etc.).

According to Regulation of the European Parliament and of the Council No 842/2006 on certain fluorinated greenhouse gases Latvia has adopted Regulations on special restrictions and prohibitions regarding activities with ozone-depleting substances and fluorinated

greenhouse gases (Regulation No.563 of the Cabinet of Ministers of Latvia)56. According to Regulation No.563 any company, institution, or organization using ozone layer depleting

substances, each year till the 31st of March shall submit a statement on ozone layer depleting substances and fluorinated greenhouse gases used in the reporting year to the Latvian Environment, Geology and Meteorology Centre (LEGMC). The new Regulation No 517/2014

of the European Parliament and of the Council of 16 April 2014 on fluorinated greenhouse gases which repeals Regulation No 842/2006 has entered into force starting from 2015.

According to Regulations No. 563 350 operators reported data of their operations with F-gases which was used for F-gases emission estimation for submission 2015 per year 2013.

According to Regulations No. 575 of Cabinet of Ministers of the Republic of Latvia on

accounting order and database of chemical substances and mixtures (29th of June 2010) 57 the LEGMC maintains the Chemicals Register. Data from Register is used annua lly for emission

estimations from F-gases containing foams.

55

Project report ―SF6, HFC and PFC emission inventory in Latvia 1995-2003‖, Riga 2004 56http://likumi.lv/ta/id/233736-noteikumi-par-ipasiem-ierobezojumiem-un-aizliegumiem-attieciba-uz-darbibam-ar-ozona-slani-noardosam-

vielam-un-fluoretam-siltumn...

57 http://likumi.lv/doc.php?id=212619


213

The calculation of emissions under 2.F, 2.G.1 and 2.G.4 subsectors which covers F-gases was

carried out for following gases: HFC–23, HFC–32, HFC–125, HFC–134a, HFC–143a, HFC–152, HFC-245fa, HFC-365mfc, HFC–227ea and SF6.

The 2.F and partially 2.G category includes HFC emissions from refrigeration and air

conditioning equipment (CRF 2.F.1), foam blowing agents (CRF 2.F.2), fire protection (CRF 2.F.3), metered dose inhalers (CRF 2.F.4.a), other sources (emissions from shoes containing

HFC-134a (CRF 2.G.4)) and SF6 emissions from electrical equipment (switchgears) (CRF 2.G.1).

There is no production of HFCs in Latvia. Emissions of the PFCs and NF3 does not occur

(NO) in Latvia for all time series at all.

According to the UNFCCC Decision 2/CMP.8 each Party with a quantified emission

limitation and reduction commitment inscribed in the third column of Annex B to the Kyoto Protocol, as contained in annex I to decision 1/CMP.8, shall submit to the secretar iat an initial report to facilitate the calculation of its assigned amount pursuant to Article 3, paragraphs

7bis, 8 and 8bis, of the Kyoto Protocol for the second commitment period. The initial report also shall contain the information regarding identification of its selected base year for NF3

(nitrogen trifluoride). Latvia has chosen 1995 as base year for NF3 emission reporting.

The emissions of F-gases (under CRF sectors 2.F and 2.G) are linearly increasing since 1995 from 0.85 Gg CO2 eq. in 1995 to 116.96 Gg CO2 eq. in 2013. The mayor part of F-gases

emissions constitutes 2.F.1 Refrigeration and Air Conditioning (87.9%). The second largest emission source is use of electrical equipment under 2.G.1 Electrical Equipment subcategory

which is responsible for 7.3% of total F-gases emissions in 2013. Additionally 3.0% from F-gases emissions comes from 2.F.4. Aerosols (metered dose inhalers) and 1.6% from 2.G.4. Other (Production of shoes) in 2013 (Figure 4.8, Table 4.33).

Figure 4.8 HFC emissions from 2.F Product Uses as ODS Substitutes and HFC and S F6 emissions from

2.G Other Product Manufacture and Use (Gg CO2 eq)


Table 4.33 Total F-gases emissions under 2.F and 2.G sectors (1995-2013) (Gg CO2 eq)

Year 2.F 2.F.1 2.F.1.a 2.F.1.b 2.F.1.c 2.F.1.d 2.F.1.e 2.F.2 2.F.3 2.F.4 2.G.1 2.G.4.

Product Uses as

Substitut

es for ODS

Refrigeration and Air

Conditioning

Commercial Refrigeration

Domestic Refrigeration

Industrial Refrigeration

Transport Refrigeration

Mobile Air conditioning

Foam blowing agents

Fire Protection

Aerosols Electrical

equipment Other

Applications (Shoes)

1995 0.27 0.27 NO, NE 0.03 NO,NE 0.22 0.02 NO,NE NO,NE NO,NE 0.17 0.40

2000 4.69 3.46 0.08 0.07 NO,NE 0.04 3.27 NO,NE NO,NE 1.24 0.88 0.78

2001 6.62 4.87 0.19 0.08 NO,NE 0.08 4.52 NO,NE 0.02 1.73 1.39 1.52

2002 8.63 6.58 0.27 0.09 NO,NE 0.10 6.12 NO,NE 0.02 2.03 2.62 1.97

2003 11.00 9.03 0.37 0.12 NO,NE,IE 0.33 8.22 0.003 0.04 1.93 2.76 2.37

2004 14.88 12.83 0.96 0.14 NO,NE,IE 0.11 11.63 0.059 0.08 1.91 3.25 3.15

2005 20.91 18.69 0.71 0.17 NO,NE,IE 0.21 17.61 0.036 0.05 2.13 3.78 3.60

2006 38.18 35.60 9.24 0.19 NO,NE,IE 0.15 26.01 0.182 0.02 2.39 4.07 4.04

2007 58.13 55.21 18.38 0.21 NO,NE,IE NO,IE 36.62 0.112 0.05 2.77 4.55 5.06

2008 73.75 70.69 27.69 0.23 NO,NE,IE NO,IE 42.77 0.001 0.08 2.98 5.23 5.81

2009 77.73 74.81 30.66 0.24 NO,NE,IE NO,IE 43.92 0.000 0.11 2.80 7.33 5.41

2010 73.49 70.63 29.67 0.25 NO,IE NO,IE 40.71 0.001 0.14 2.72 7.35 6.19

2011 77.59 74.71 29.91 0.26 NO,IE NO,IE 44.54 0.001 0.17 2.71 7.47 4.51

2012 88.34 85.58 35.11 0.28 NO,IE NO,IE 50.20 0.001 0.21 2.55 7.78 2.62

2013 106.62 102.86 46.12 0.29 NO,IE NO,IE 56.45 0.001 0.24 3.52 8.50 1.84


4.7.1 Refrigeration and Air Conditioning (CRF 2.F.1)

The calculation of actual emissions is done according to the IPCC 2006 Guidelines.

Refrigeration and Air Conditioning Systems are responsible for about 85.8% of the Latvia`s F-gas emissions. The main subsectors are:

Domestic Refrigeration (fridges and freezers in households);

Commercial Refrigeration (refrigerators for supermarkets, shops etc.);

Transport Refrigeration (refrigerated vehicles);

Industrial Refrigeration (refrigeration units in industries);

Stationary Air Conditioning (heat pumps and room air-conditioning systems);

Mobile Air Conditioning (AC systems in passenger cars, trucks and buses).

4.7.1.1 Domestic Refrigeration (CRF 2.F.1.b)

4.7.1.1.1 Source category description This category includes all refrigeration units (fridges and freezers) for domestic use. As there is no production of such equipment in Latvia, emissions could be estimated taking into

account data on imported units which are charged and used within the country. In domestic refrigeration the HFC-134a is used as refrigerant and as a foam insulating gas.

4.7.1.1.2 Methodological issues HFC-134a emissions from domestic refrigerators and freezers are estimated by using IPCC

2006 Guidelines Tier 2a – Emission-factor approach. According to the methodology, refrigerant emissions at a reporting year can be calculated separately for each stage of life of

the equipment. These emissions come from:

Echarge, t – emissions related to the refrigerant charge: connection and disconnection of the refrigerant container and the new equipment to be charged;

Elifetime,t – annual emissions from the banks of refrigerants during operation (fugitive emissions and ruptures) and servicing;

Eend-of-life,t – emissions at system disposal.

Equation 7.10 from IPCC 2006 Guidelines was used to sum up all the emissions from

domestic refrigeration occurring during the lifetime of the equipment:

Etotal,t = EContainers,t + ECharge,t + ELifetime,t

The basic data for HFC-134a emission estimation from domestic refrigerators and freezers are:

1. number of inhabitants in Latvia – data was taken from CSB database „Resident population at the beginning of the year‖58;

2. number of households in Latvia – data was taken from CSB database „Total number

of households and the average size of a household‖59.

58

http://data.csb.gov.lv/pxweb/en/Sociala/Sociala__ikgad__iedz__iedzskaits/IS0020.px/table/tableViewLayout1/?rxid=a79839fe-11ba-4ecd-8cc3-4035692c5fc8

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3. percentage of households using refrigerators and freezers – for 1996, 2001, 2006 and 2010 years data was taken from CSB database „Number of electrical appliances used in dwellings and average age of appliances‖. 60 Data obtained with questionnaires of

households made every five years.

4. percentage of refrigerators and freezers charged with HFC-134a were determined by

experts during report ―SF6, HFC and PFC emission inventory in Latvia 1995-2003‖.

As percentage of the domestic refrigerating equipment containing HFC-134a was obtained during the preparation of the report ―SF6, HFC and PFC emission inventory in Latvia 1995-

2003‖ is known only for 1999-2003, data for historical years prior this time period was extrapolated. Data for 2004-2008 was calculated assuming the average increase of 4%, due to

improvement of wellbeing of population and the requirements of European Union. It is assumed that the percentage of the refrigerators containing HFC-134a is increasing as previously used chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs) is now

prohibited since Latvia has undertook the obligations of the European Union in 2004. In 2009-2013 the increase of percentage amount of domestic refrigerators containing HFC-134a

is assumed lower – 3%.

HFC-134a from charging of domestic refrigerators and freezers

There are no manufacturing companies in Latvia and all domestic refrigerators and freezers are imported.

Activity data for emission estimation from recharging of domestic refrigerators and freezers

are number of freezing equipment units containing HFC-134a used in households. According to responses on the questionnaires submitted to report ―SF6, HFC and PFC emission inventory

in Latvia 1995-2003‖ average amount of HFC-134a used in charging of domestic freezing equipment is 176.25g and charging is made once in lifetime (15 years) – average after 7.5 years. That gives approximate annual amount of HFC-134a charged that is estimated with

equation from 2006 IPCC Guidelines:

HFCCharged,t = R ×n/f where:

HFCcharged – amount of HFC-134a charged in year t (tonnes);

R – amount of refrigerators and freezers charged with HFC-134a (units);

n – average equipment lifet ime (years);

f – amount of HFC-134a charged once in lifetime of equipment

After the in-country review in 12th – 17th October 2009 it was suggested to use average

lifetime 15 years just for early years in time period but for the latest years use shorter lifetime period. So it was assumed to use 15 years lifetime factor for years 1995-2000 but for time

period 2001-2013 lifetime factor used in emission estimation is assumed as 10 years. As regards to the charging it was assumed that from 2001-2013 it is accomplished average after 5 years.

According to 2006 IPCC Guidelines average 0.6% of HFC-134a used in charging is emitted during charging process.61

Equation from 2006 IPCC Guidelines for charging emissions estimation:

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2006 IPCC Guidelines for National Greenhouse Gas Inventories: Emissions of Fluorinated Substitutes for Ozone Depleting Substances (Volume 3) Industrial Processes and Product Use, p.7.52

http://en.wikipedia.org/wiki/Chlorofluorocarbons

http://en.wikipedia.org/wiki/Hydrochlorofluorocarbons


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ECharged,t = Mt × k/100 where:

Echarged – emissions during system manufacture/assembly in year (kg)

Mt – amount of HFC-134a charged into a new equipment in year (kg);

k – charging losses (%)

HFC-134a from stocks of domestic refrigerators and freezers

Amount of HFC-134a in stocks is estimated according to data from CSB. Approximate

amount of HFC-134a stored in domestic refrigerators and freezers was estimated based on CSB data on number of households and number of inhabitants as well as assumptions made according to the previous F-gases research.

According to 2006 IPCC Guidelines average percentage of losses during operation is 0.3% of the total quantity banked in the stock.62

Equation from 2006 IPCC Guidelines for emissions estimation from equipment lifetime:

Elifetime,t = Bt× x/100 where:

Elifetime – amount of HFC emitted during system operation in year (kg)

Bt – amount of HFC banked in existing systems in year (kg);

x – annual emission rate (%)

HFC-134a from disposal of domestic refrigerators and freezers

The activity data for emission estimation is impossible to obtain as the data of HFC-134a

charged in new equipment in time period 1980-1992 is needed. It isn’t possible to obtain this data as basic statistical information for activity data estimation is necessary. Still according to

research made for report ―SF6, HFC and PFC emission inventory in Latvia 1995-2003‖ the percentage of all freezing domestic equipment in 1995 is quite low as 5%. So for years 1980-1992 the percentage amount is assumed as low as 0-1%. As well as amount of freezing

equipment in households is assumed as rather low in this time period. So it was assumed that disposal emissions for time period 1995-2004 is negligible and notation key ―NA‖ for these

years for disposal emissions is used.

Law on Waste Management63 (adopted in 28.10.2010) according to what ―electrical and electronic equipment manufacturers shall ensure the waste collection, adoption, processing,

reuse, recycling, recovery and disposal using the best available techniques‖64 stipulates the order of environmentally safe liquidation of substances from electric and electronic equipment

that includes chlorofluorocarbons (cryofluorane, CFC), hydrochlorofluorocarbons (HCFC) or hydrofluorocarbons (HFC), hydrocarbons (HC) and deliver them to particular treatment facilities. According to previous mentioned Law it is assumed that there are no disposal

emissions from domestic and commercial refrigerators and freezers since 2005. The main aspect of choosing ―0‖ emissions from disposal is that collected electric and electronic

equipment is not disposed in Latvia. All the equipment is collected and transported to other countries for recycling or disposing. So the notation key ―NO‖ is used for domestic refrigeration sector emissions for 2005-2013.

62 2006 IPCC Guidelines for National Greenhouse Gas Inventories: Emissions of Fluorinated Substitutes for Ozone Depleting Substances

(Volume 3) Industrial Processes and Product Use, p.7.52 63

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4.7.1.1.3 Uncertainties and time series consistency

Uncertainty for Domestic refrigeration could arise to 75% according to expert judgement.

Also uncertainty of emission factors for HFCs is assumed as 75%. Combined emission uncertainty was estimated using Approach 1 of the 2006 IPCC Guidelines.

Time series of the estimated emissions are consistent because the same methodology,

emission factors and data sources are used for sectors for all years in time series.

4.7.1.1.4 Category specific QA/QC and verification QA/QC check is performed according to 2006 IPCC Guidelines. All information on activity data and emission calculations are stored and archived in the common FTP folder. All

findings are documented using check- lists which are archived and documented in centralized archiving system (common FTP folder).

All estimations of the emissions done in the LEGMC are checked on the logical mistakes by checking the time series of the activity data, emission facto rs and emissions consistency to display all significant and illogic changes in the activity data and emissions.

Quality control check list is filled for each category taking into account criteria given in QA/QC plan approved in national legislation. All findings were documented and introduced

in GHG inventory.

Quality manager from LEGMC has checked the data between CRF and NIR to ensure the consistency as well as QC actions were done in CRF in purpose to double check if all sub-

applications are covered.

As from 2015 according to 2006 IPCC Guidelines the Industrial Processes and Solvent and

Other Product Use sectors have merged in one sector – Industrial Processes and Product Use, the order for data input in CRF Reporter and completion of relevant NIR subchapters for three experts responsible of IPPU sector has been set up in the instruction. Preparation of such

instruction for each sector has been determined with national legislation (Regulation of Cabinet of Ministers No. 217) and it is planned to update it every year before the start of a

new inventory cycle. Additionally internal inventory preparation plan has set up for LEGMC experts to ensure consistency in sectors where more than one responsible expert are involved. Also it was done to promote inventory preparation in a timely manner.

4.7.1.1.5 Category specific planned improvements Within the EEA Financial Mechanism 2009-2014 Programme "National Climate Policy " it is planned to ensure detailed quality control procedures for quality assurance of Industrial process sector. It is also planned to perform F-gases research to significantly improve the

process of obtaining the activity data and country specific emission factors as well as decrease uncertainties. Results will be reflected into next submission.

4.7.1.2 Commercial and Industrial Refrigeration (CRF 2.F.1.a, CRF 2.F.1.c)

4.7.1.2.1 Source category description Activity data for emission calculation are taken from annual reports by F-gases operators according to Regulation (EC) No. 842/2006 and national legislation No.56365 ―Regulations of

ozone depleting substances and fluorinated greenhouse gases that are freezing agents‖ operators (merchants and other institutions) which perform activities with ozone depleting substances or F-gases annually shall report to LEGMC the following information:

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Name of the substance;

Amount of substance at the beginning of the year;

Imported amount;

Exported amount;

Charged amount in freezing equipment units;

Recycled amount;

Regenerated amount;

Disposed amount;

Amount of substance at the end of the year.

360 operators reported data of their operation with F-gases for submission 2015 per year 2013. For historical years activity data were obtained from questionnaires done within ―SF6, HFC and PFC emission inventory in Latvia 1995-2003‖. For 2004-2005 activity data were

obtained from enterprises that responded on data request letters sent by LEGMC. For 2006-2013 data were obtained from reporting within previously mentioned regulation act.

4.7.1.2.2 Methodological issues 2006 IPCC Guidelines were used to estimate emissions from commercial and industrial

freezing equipment.

F-gases from charging of commercial and industrial refrigeration

There are no manufacturing companies in Latvia and all refrigerators and freezers used in commercial and industrial refrigeration are imported.

Activity data for emission calculations is obtained from operators who have reported data of their operations with F-gases in 2013. Information reported by operators includes amounts of F-gases in bulk and in blends.

Average 3.5% of HFC-134a used in charging is emitted during charging process according to 2006 IPCC Guidelines.66 For time period 2006-2013 average 1.5% of HFC-134a charged into

refrigerators is assumed as emitted into air. ―Regulation on substances that deplete the ozone layer and certain fluorinated greenhouse gases‖ was adopted in the second part of 2011. As it regulates the activities with F-gases and sets out limitations for these activities it is assumed

that more accurate operations with F-gases are taken since the regulations have entered into force.

Equation from 2006 IPCC Guidelines for charging emissions estimation:

ECharged, t = Mt × k/100 where:




F-gases from stocks of commercial and industrial refrigeration

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Activity data for emission calculations is obtained from operators who have reported data of their operations with F-gases in 2013. Information reported by operators includes amounts of F-gases in bulk and in blends.

According to 2006 IPCC Guidelines average percentage of losses during operation varies from 1-35% but it was assumed average 15% losses for commercial refrigerators used in

Latvia as stand-alone commercial applications are used in commercial refrigerating sector. This percentage is used for time period 1998-2005. For time period 2006-2013 average 8% of HFC-134a stored in stocks is assumed as emitted into air. ―Regulation on substances that

deplete the ozone layer and certain fluorinated greenhouse gases‖ was adopted in the second part of 2011 as is regulating the activities with F-gases and set out limitations for these

activities. So it is assumed that more accurate operations with F-gases are taken.

Equation from 2006 IPCC Guidelines for emission estimation stocks:

Elifetime, t = Bt × x / 100 where:

Elifetime – amount of emissions during equipment operation (t)

Bt – amount of F-gases held in stocks in year t (tonnes);

x – losses during operation period (%)

F-gases from disposal of commercial and industrial refrigeration

From 1990-2004 emissions from disposal of commercial and industrial refrigeration are not estimated due to lack of statistical data of collected and disposed refrigerants and data of

collected/not collected freezing agents in refrigeration equipment. Since 2005 according to ―Law on Waste Management‖67 (adopted in 28.10.2010) the F-gases remained in electronic

and electric equipment have to be collected and transferred to waste treatment facilities for liquidation or to waste processors for regeneration. The F-gases amount of recycled, regenerated and destroyed equipment is known for time period 2006-2010. These amounts are

very negligible. As the amount of F-gases have to be collected before the disposal of the refrigeration equipment and the collection has to be done according to rules without any

possible leakage, it is assumed that the emissions from collection of the amount of F-gases destroyed or recycled after that are not occurring (NO).

According to previously mentioned it is assumed that there are no disposal emissions from

commercial and industrial refrigeration equipment since 2005. So the notation key ―NO‖ is used in CRF Reporter for 2005-2013.


Activity data for HFCs is obtained from reports of enterprises operated with F-gases therefore

it is assumed that uncertainty could arise to 75%. Also uncertainty of emission factors for HFCs is assumed as 75%. Combined emission uncertainty was estimated using Approach 1 of

the 2006 IPCC Guidelines.

Time series of the estimated emissions are consistent because the same methodology, emission factors and data sources are used for sectors for all years in time series.

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4.7.1.2.4 Category specific QA/QC and verification

QA/QC is performed according to 2006 IPCC Guidelines. More detailed description can be

found under chapter 4.7.1.1.4.

4.7.1.2.5 Category specific planned improvements Within the EEA Financial Mechanism 2009-2014 Programme "National Climate Policy " it is planned to ensure detailed quality control procedures for quality assurance of Industrial

process sector. It is also planned to perform F-gases research to significantly improve the process of obtaining the activity data and country specific emission factors as well as decrease uncertainties. Results will be reflected into next submission.

4.7.1.3 Transport Refrigeration (CRF 2.F.1.d)

4.7.1.3.1 Source category description This group includes refrigerated road vehicles. There is no production o f refrigeration units in Latvia so emissions occur from stocks and from disposal.

During the preparation of the report ―SF6, HFC and PFC emission inventory in Latvia 1995-2003‖ transport enterprises and auto services were questioned. According to the respo nses

only negligible amount of HFCs is used in railways and water transport. Small amount of HFC-23 is filled into refrigerating equipment in ships. Reported HFC-134a and HFC-125 is filled into mobile refrigerators used in road transport.

According to ―Regulation on substances that deplete the ozone layer and certain fluorinated greenhouse gases‖ F-gases operators that charge and own the mobile refrigerating equipment

have to report the amount of used F-gases since 2006. These operators use F-gases as freezing agents.

4.7.1.3.2 Methodological issues

F-gases from charging of transport refrigeration

For historical years 1990-2006 it is almost impossible to obtain necessary data of F-gases used for charging of mobile refrigerators as enterprises didn’t have particular accounting and

mainly enterprises served not only mobile refrigerators, but also stationary refrigeration equipment and stationary and mobile air conditioning equipment. So these enterprises have only total charged amount of HFCs. And also enterprises that own mobile refrigerators didn`t

service their equipment. Till year 2006 there weren’t any rules that enterprises which operate with F-gases have to report used amounts.

For years 2007-2013 it is very difficult or almost impossible to exclude the amount charged in transport refrigeration equipment from all F-gases amounts reported by F-gases operators because operators haven't such aggregated accounting within national regulation. Amount of

F-gases charged in transport refrigeration reported under 2.F.1.a Commercial Refrigeration sector. Consequently notation key ―IE‖ is used for reporting in CRF Reporter from 2006-2013

under 2.F.1.d Transport Refrigeration.

F-gases from stocks of transport refrigeration

For historical years 1990-2006 the amount of F-gases in operating transport refrigeration

systems is estimated by using the information of road transport and ships refrigeration equipment reported by enterprises within preparation of report ―SF6, HFC and PFC emission

inventory in Latvia 1995-2003‖. Enterprises reported the amount of transport refrigerators they own, type of F-gases filled in it and amount of refrigerators used.

Equation from 2006 IPCC Guidelines for emission estimation from stocks:


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Average emission factor for stocks emissions is 15% for time period 1995-2005, since 2006 8% leakage factor is used because of adopting ―Regulation on substances that deplete the ozone layer and certain fluorinated greenhouse gases‖ 68

For later years 2007-2013 the amount of F-gases in operating transport refrigeration equipment is reported by enterprises according to national legislation which establishes that

any company, institution, or organization using ozone layer depleting substances, shall submit a statement on ozone layer depleting substances used in the reporting year to LEGMC. Operators are not required to report the NACE code of their activities and consequently it's

very difficult to exclude the enterprises operating as freight carriers from whole list of enterprises reporting their activities with F-gases. Consequently from year 2007 till 2013 the

amount of F-gases used in transport refrigeration and emissions from stocks are reported under 2.F.1.a Commercial Refrigeration sector and the notation key ―IE‖ is used for reporting in CRF Reporter under 2.F.1.d Transport Refrigeration.

F-gases from disposal of transport refrigeration

For historical years 1990-2005 emissions from disposal of transport refrigeration systems are

not possible to estimate due to the lack of statistical data (reported as ―NE‖ in CRF Reporter).

According to ―Law on Waste Management‖69 the F-gases remained in electronic and electric

equipment have to be collected and transferred to waste treatment facilities for liquidation or to waste processors for regeneration (outside of Latvia). According to previous mentioned Law it is assumed that there are no disposal emissions from transport refrigerators since 2005.

So the notation key ―NO‖ is used in CRF Reporter for emissions from disposal of transport refrigeration equipment from 2005 till 2013.


Activity data for HFCs is obtained from reports of enterprises operated with F-gases therefore

it is assumed that uncertainty could arise to 75%. Also uncertainty of emission factors for HFCs is assumed as 75%. Combined emission uncertainty was estimated using Approach 1 of




QA/QC is performed according to 2006 IPCC Guidelines. More detailed description can be found under chapter 4.7.1.1.4.

4.7.1.3.5 Category specific planned improvements

Within the EEA Financial Mechanism 2009-2014 Programme "National Climate Policy " it is

planned to ensure detailed quality control procedures for quality assurance of Industrial

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4.7.1.4 Mobile and Stationary Air Conditioning (CRF 2.F.1.e, CRF 2.F.1.f)

4.7.1.4.1 Source category description

According to ―Regulation on substances that deplete the ozone layer and certain fluorinated greenhouse gases‖ F-gases operators that charge the mobile and also own stationary air

conditioning equipment shall report the amount of used and stored F-gases. Emissions under this subcategory are estimated using activity data reported by operators which use F-gases as

conditioning agents.

4.7.1.4.2 Methodological issues

2006 IPCC Guidelines were used to estimate emissions from stationary and mobile air conditioners.

HFC-134a from charging of mobile and stationary air conditioning

For historical years 1995-2006 it is almost impossible to obtain precise data of F-gases used

for charging of stationary or mobile air conditioners as enterprises didn’t have particular accounting and majority of enterprises serve refrigerating and conditioning equipment together. So these enterprises have only total charged amount of HFCs. Until year 2006 there

weren’t any rules for enterprises which operate with F-gases to report used amounts.

For years 2007-2013 it is very difficult or almost impossible to exclude the amount charged in

stationary and mobile air conditioning equipment from amount reported by F-gases operators within national regulation as charged in freezing and conditioning equipment because operators haven't such aggregated accounting.

So the amount of F-gases charged in stationary and mobile air conditioners and emissions from charging are reported under 2.F.1.a Commercial Refrigeration sector and the notation

key ―IE‖ is used for reporting in CRF Reporter.

HFC-134a from stocks of stationary and mobile air conditioning

The amount of F-gases in stationary air conditioning equipment (stocks) is reported by

enterprises within national legislation. Operators don't have to report the equipment type where F-gases are stored and it's very difficult to exclude the enterprises reporting F-gases

filled in their stationary air conditioning equipment from total F-gases reported as stocks of enterprise.

HFC-134a emissions from mobile air conditioning are estimated by using 2006 IPCC

Guidelines and default percentage amounts. The basic data for HFC-134a emission estimation from mobile air conditioners (MACs):

1. data obtained from CSB database „Number of registered road vehicles‖ 70. The amount of passenger cars and trucks manufactured after 1995 obtained by Road Traffic Safety Directorate were used in emission estimates;

2. percentage of cars filled with HFCs – taken from report ―SF6, HFC and PFC emission inventory in Latvia 1995-2003‖;

Percentage of cars filled with HFCs according to project report is 20% for passenger cars and 50% for trucks. This percentage is used for time period 1995-2000.

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The fleet age is constantly improving when in 2002 only 2.13% of the total registered in country passenger cars manufacturing year was higher than year 2000, in 2005 this percentage was 5.99% but in year 2008 21.64% of total registered passenger cars were younger than year

2000 (manufacturing year). In 2009 22.51% of the total registered passenger cars have higher manufacturing year than 2000, but 11% have higher manufacturing year than 2005.

According to previous mentioned it can be assumed that in year 2000 the percentage of passenger cars equipped with MACs filled with F-gases is higher than 20% and it percentage has to increase year by year. The expert judgement is – starting from year 2000 the percentage

of passenger cars with manufacturing year higher than 1995 equipped with F-gases filled MACs are constantly increasing and reaches 44% in year 2013. The same percentage increase

has to be applied for trucks when percentage of trucks equipped with MACs increase from 50% in 2000 to 74.2% in 2013.

According to 2006 IPCC Guidelines average percentage of losses during operation lifetime is

15% of the total quantity banked in the stock.71






HFC-134a from disposal of stationary and mobile air conditioning

According 2006 IPCC Guidelines for emission estimation from disposal of stationary and

mobile air conditioners, the amount of F-gases charged in particular historical years is needed. It means that data for amount of F-gases charged in the eighties and nineties is needed. It is impossible to obtain data of these years.

During the project for the ―SF6, HFC and PFC emission inventory in Latvia 1995-2003‖ it was assumed that approximate 8% of total MACs are disposed every year. Average lifetime

factor for MACs is 12 years.72 According to assumption it is possible to estimate amount of F-gases remained in MACs after the disposal every year by multiplying amount of MACs disposed with the approximate amount of F-gases remained in one amount. It is assumed that

approximate 40% of F-gases filled in MACs is remained after the lifetime of MACs.

HFC remained = MAC total × m × HFC fill × r where:

HFCremained – amount of F-gases remained in MACs after their lifet ime in year (t)

MACtotal – total amount of MACs in passenger cars and trucks (pieces)

M – amount of MACs disposed (%)

HFCfill – amount of F-gases filled in one MAC of passenger car or truck

R – amount of F-gases remained in one MAC (%)

71

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It is assumed that 100% of F-gases remained in MACs after their lifetime. For disposal emission estimation the default values from 2006 IPCC Guidelines were used. 73

Equation from 2006 IPCC Guidelines for emission estimation from disposal of MACs:

Eend-of-life,t = Mt-d× p/100 × (1-ƞrec,d/100) where:

Eend-of-life,t– amount of emissions from system disposal (t)

Mt-d– amount of HFCs charged into domestic refrigerators and freezers in year (t -n) (t)

P – residual charge of HFC in equipment being disposed of expressed in % of full charge (%)

ƞrec,d – recovery efficiency at disposal

4.7.1.4.3 Uncertainties and time series consistency Activity data for HFCs is obtained from reports of enterprises operated with F-gases therefore it is assumed that uncertainty could arise to 75%. Also uncertainty of emission factors for HFCs is assumed as 75%. Combined emission uncertainty was estimated using Approach 1 of






4.7.1.4.5 Category specific planned improvements

Within the EEA Financial Mechanism 2009-2014 Programme "National Climate Policy " it is planned to ensure detailed quality control procedures for quality assurance of Industrial process sector. It is also planned to perform F-gases research to significantly improve the

process of obtaining the activity data and country specific emission factors as well as decrease uncertainties. Results will be reflected into next submission.

4.7.2 Foam Blowing Agents (CRF 2.F.2)


In this sector HFCs are emitted only from the use of imported foams containing F-gases.

There is no production of foams in Latvia.

Although the activity in building sector in previous years has radically increased, emission estimations can be done starting from 2002 due to the lack of activity data of imported and

used building foams or foams used in windows manufacturing as well as lack of data on foams containing F-gases.

Data of imported foams divided by particular foam type is obtained from Chemicals Register maintained by LEGMC where all companies operating with products containing chemicals have to report their data on import/export and production amounts of chemical substances. No

export and production data is reported to the Chemicals Register therefore only imported amount can be obtained. So only emissions from use of foams and disposal emissions after

foam have been used – emissions from products left in foam packaging, containers etc.

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The imported amount of foams is obtained from Chemicals Register where companies that

import products containing specific chemicals have to report their data.

Although it can be assumed that not all foams imported in country in particular year are used in the same year, the import data is used to estimate actual emissions as there is no available

information on amounts sold.

Compounds that are being used in foams are HFC-245fa, HFC-365mcf, HFC-227ea, HFC –

134a and HFC 152a. It is assumed that all the foams imported are closed cells foams (used in insulation applications) according to NACE classification. The data on foams imported as well as the average percentage of F gas in the foams were obtained from Chemicals Register.

The emission calculations were done according to 2006 IPCC Guidelines Tier 1a method using activity data on imported foams and default emission factors – first year losses 10% of

the original HFC charge/year, annual losses 4.5% of the original HFC charge/year 74.

Equation from 2006 IPCC Guidelines for emissions from closed-cell foam in year was used:

Emissions t = M × EF FYL + Bank t × EF AL

where:

Emissions t = emissions from closed-cell foam in year t, tonnes

EF FYL = first year loss emission factor, fraction 10%

Bank t = HFC charge b lown into closed-cell foam manufacturing between year t and year t-n, tonnes

EF AL = annual loss emission factor, fraction

n = product lifetime of closed-cell foam

t = current year

(t-n) = the total period over which HFCs used in foams could still be present

For decommissioning losses estimation the manufacturing and/or processing of foams data in historical years have to be obtained. The product lifetime of foam is 20 years. Therefore it is necessary to obtain the data of the years prior 1989. As in that time Latvia was part of Soviet

Union the specific data was not collected as well as it is believable that the foam blowing did not occur in country or it occur in very negligible amounts. Therefore decommissioning losses

for foams use are assumed as not applicable (NA).


Uncertainty for Foam blowing products could arise to 75% according to expert judgement. Also uncertainty of emission factors for HFCs is assumed as 75%. Combined emission

uncertainty was estimated using Approach 1 of the 2006 IPCC Guidelines.


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4.7.2.5 Category specific planned improvements

Within the EEA Financial Mechanism 2009-2014 Programme "National Climate Policy " it is

planned to ensure detailed quality control procedures for quality assurance of Industrial process sector. It is also planned to perform F-gases research to significantly improve the process of obtaining the activity data and country specific emission factors as well as decrease

uncertainties. Results will be reflected into next submission.

4.7.3 Fire Protection (CRF 2.F.3)


Emissions from fire extinguishing are problematic to estimate due to the fact that there is only statistical information of the registered fire extinguishing equipment (pieces) in Latvia done

by State Fire and Rescue Service. Type of substance used in equipment isn’t registered.


HFC-227ea from charging of fire extinguishing equipment

During the preparation of the report ―SF6, HFC and PFC emission inventory in Latvia 1995-

2003‖ it was found out that there is no manufacturing of fire extinguishers containing F-gases. 19 enterprises were questioned including only manufacturer of fire extinguishers. According to responses received a little amount of fire extinguishers are filled with F-gases. Only 2

enterprises reported the amount of HFC-227ea in their installed equipment in particular year and amount of HFC-227ea held in stocks (containers) of fire extinguishing equipment. It was

reported that no charging was done for the installed equipment. Fire extinguishers were installed already filled with F-gases and there weren’t any necessity to recharge them. Therefore only emissions from stocks were calculated.

HFC-227ea from stocks of fire extinguishing equipment

Amount of F-gases in annually installed equipment and amount held in containers is used as

activity data for emission estimations from stocks. It is assumed that 2% from total stocks is emitted during equipment operations annually according to 2006 IPCC Guidelines 75.

For 2007-2013 emission estimation data of year 2006 was used as no response was received on sent questionnaires. In purpose to improve the accuracy of the estimates and avoid potential underestimation of emissions, for 2007-2013 emissions were calculated assuming

the average increasing amount of HFC-227ae installed in fire extinguishers per year. Activity data from years 2003-2006 increases averagely about 0.486 tonnes per year, so this amount

was used for extrapolation of activity data for later years.






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HFC-227ea from disposal of fire extinguishing equipment

In year 2006 one enterprise reported the amount of HFC-227ea disposed. It was assumed that

only 5% is emitted from the disposal as in 2006 new national regulation for the operation with F-gases and for the dangerous waste treatment was adopted.

Equation from 2006 IPCC Guidelines for disposal emissions estimation:

Eend-of-life,t = Mt-d× p/100 × (1-ƞrec,d/100) where:

Eend-of-life,t– amount of emissions from system disposal (t)

Mt-d– amount of HFCs charged into domestic refrigerators and freezers in year (t -n) (t)

P – residual charge of HFC in equipment being disposed of expressed in % of full charge (%)

ƞrec,d – recovery efficiency at disposal


Uncertainty for Fire protection equipment could arise to 75% according to expert judgement. Also uncertainty of emission factors for HFCs is assumed as 75%. Combined emission







Within the EEA Financial Mechanism 2009-2014 Programme "National Climate Policy " it is planned to ensure detailed quality control procedures for quality assurance of Industrial


4.7.4 Aerosols (CRF 2.F.4.)

4.7.4.1 Emissions from Metered Dose Inhalers (CRF 2.F.4.a)

4.7.4.1.1 Source category description During the project within preparation of the report ―SF6, HFC and PFC emission inventory in Latvia 1995-2003‖ Latvia’s enterprises producing household and professional cleaning agents

and disinfectants were questioned. The enterprises stated that in the production of aerosols F-gases are not used in Latvia. It means that all aerosols used in Latvia are imported. It is very difficult to collect the data of imported aerosols as it is necessary to divide HFCs containing

aerosols from others. It is almost impossible to get the information from all households and importers of industrial aerosols in Latvia. Central Custom Service only registers all imported

aerosols with one custom code not dividing them by type or by substances containing. Also since Latvia is in Schengen zone only imported amount from Third Countries is registered.


229

So only the aerosols used in medicine for asthmatics are estimated and reported under this sector. During the project for the preparation of the report ―SF6, HFC and PFC emission inventory in Latvia 1995-2003‖ amount of inhalers contained HFC–134a were clarified as

well as average amount of HFC-134a filled in one inhaler divided by the type of medicine. All the inhalers are imported as no inhalers for asthmatics are produced in Latvia.

4.7.4.1.2 Methodological issues For years 1998-2006 data of imported inhalers reported by importers of medical preparations

was used as activity data. From 2007 till 2013 data for emission estimations annually is obtained by State Agency of Medicines of Latvia. All importers of the medical preparations

shall report the imported and sold amount of medicines so these data are very precise.

It is possible to estimate total amount of HFC-134a used in metered dose inhalers in particular year as the imported amount of inhalers containing HFC-134a and an average amount of

HFC-134a filled in each type of inhalers is known.

Equation for total amount HFC-134a used as medical preparation:

HFC sold = Σ MDI sold × HFC filled where:

HFCsold – total amount of HFC sold/imported in country (t)

MDIsold – amount of sold/imported particular type of metered dose inhalers containing F-gases (pieces)

HFCfilled – amount of HFCs filled in part icular type of inhaler (t)

According to 2006 IPCC Guidelines 50%76 leakage from metered dose inhalers sold in particular year and 50% from inhalers sold in year before particular year is assumed.

Equation from 2006 IPCC Guidelines for metered dose inhalers emissions:

Emissionst = St × EF + St-1 × (1-EF) where:

Emissionst = emissions in year t, tonnes

St – quantity of HFC and PFC contained in aerosol products sold in year t, tonnes

St-1 – quantity of HFC and PFC contained in aerosol products sold in year t -1, tonnes

EF = emission factor (=fraction of chemical emitted during the first year), fraction

4.7.4.1.3 Uncertainties and time series consistency Uncertainty for Metered dose aerosols could arise to 75% according to expert judgement. Also uncertainty of emission factors for HFCs is assumed as 75%. Combined emission




4.7.4.1.4 Category specific QA/QC and verification QA/QC is performed according to 2006 IPCC Guidelines. More detailed description can be found under chapter 4.7.1.1.4.

76



230

4.7.4.1.5 Category specific planned improvements Within the EEA Financial Mechanism 2009-2014 Programme "National Climate Policy " it is

planned to ensure detailed quality control procedures for quality assurance of Industrial process sector. It is also planned to perform F-gases research to significantly improve the process of obtaining the activity data and country specific emission factors as well as decrease


4.8 OTHER PRODUCT MANUFACTURE AND USE (2.G)

4.8.1 Electrical Equipment (CRF 2.G.1)


There is only one enterprise where huge amount of SF6 is used in commutation and control installations. Installations are not produced in Latvia and the old equipment without fill of the

SF6 was dismantled at the beginning of nineties. Only starting from 1992 new equipment was gradually installed. Since 1992, it uses small amount of SF6 in electrical equipment, but since

1995 used amount is increasing.

Enterprise imports equipment already filled with SF6. There is no manufacturing of the electric equipment containing SF6 in Latvia, therefore only emissions from charging and

operating were estimated using amount of SF6 in newly installed equipment as activity data.


For emission estimations the Tier1 default emission factor method from 2006 IPCC Guidelines was used. Emissions are estimated by multiplying default regional emission factor

(for Europe) by amount of SF6 used in equipment in enterprise. Starting from 2015 the equipment was divided into the sealed pressure electrical equipment (MV switchgear) and

closed pressure electrical equipment (HV switchgear) containing the SF6 due to the different emission factors for each of these installations. For HV switchgears 2.6 %, but for MV switchgears 0.2% emission factor was used.

Equation from 2006 IPCC Guidelines for emission estimation from charging:

ECharged, t = Mt × k /100 where:




SF6 emissions from stocks of electrical equipment







231

SF6 from disposal of electrical equipment

Lifetime of used equipment is 30 years and no equipment was dismantled yet.

Still for years 2003-2013 enterprise report the emergency leakage from electrical equipment. As amount of SF6 emergency leaked is known it is reported as 100% emissions and is reported as disposal emissions.


As there is only one facility in the country which uses SF6 in their technology and reports the

data on SF6 usage directly to LEGMC, it is assumed that data used for emission estimation under this subcategory is more precise. Uncertainty of activity data for SF6 from electrical

equipment is assumed as ±2% for AD, but EF uncertainty could arise up to 30% according to the 2006 IPCC Guidelines.

Combined emission uncertainty was estimated using Approach 1 of the 2006 IPCC

Guidelines.







process sector. It is also planned to perform F-gases research to significantly improve the process of obtaining the activity data and country specific emission factors as well as decrease


4.8.2 N2O From Product Uses (CRF 2.G.3)


The N2O emissions under CRF 2.G.3 produce N2O from product uses: Medical applications. N2O emissions from anaesthesia formed a negligible part of total GHG emissions in Latvia. In 2013 these emissions totalled 0.005 Gg CO2 eq.


N2O emissions from medical applications were estimated taking into account the amount of

N2O sold. According to the 2006 IPCC Guidelines, it was assumed that 100% of N2O sold for anaesthesia was emitted to the air, therefore activity data is equal to estimated emissions. The

data on the N2O sales was available since 1995. Activity data was provided by the State Agency of Medicines of Latvia. The estimation of emissions is based on the assumption that all used N2O is emitted to the atmosphere in the same year when it is produced or imported in

Latvia.

To obtain a comparable data in time series for years 1990-1994 assume that base year for

NMVOC emissions is year 1995, N2O emissions for years 1990-1994 were calculated


232

proportionally, taking into account the number of inhabitants provided by the Central Statistical Bureau77.


Uncertainty of available activity data under CRF 2.G.3 sub-sector was ±2% in 2013. Emission factor uncertainty is assumed to be 2%. Time series consistency was ensured by using one

method for all time series.


QA/QC check is performed with Tier1 method from EMEP/EEA guidebook 2013.


by checking the time series of the activity data, emission factors and emissions consistency to

display all significant and illogic changes in the activity data and emissions.


QA/QC plan approved in national legislation. All findings were documented and introduced in GHG inventory. All corrections are archived in centralized archiving system (common FTP

folder).


No improvements are planned under CRF 2.G.3.

4.8.3 Other (CRF 2.G.4)


Other source of HFC-134a emissions is production and use of shoes whose soles are filled with HFC-134a. Manufacturing of shoes (shoe soles) containing HFC-134a occurred in 1995-2002. After 2002 only HFC-134a emissions from stocks and disposal is emitted.


Activity data for emission estimation is taken from CSB databases about produced imported and exported amount of shoes78

Assumptions and default leakage factors from Danish project ―The Greenhouse gases: HFCs,

PFCs and SF6‖ since no researches of F-gases use under this category Latvia was done. 79

HFC-134a emissions from manufacturing of shoes containing F-gases

The manufacturing of shoe soles containing HFC-134a occurred in Latvia in 1995-2002. The amount of produced shoes (shoe soles) is obtained by CSB. According to Danish project 80 it was assumed that 5% of all shoes with plastic, rubber and leather soles contain polyether

containing 8 g of HFC-134a per shoe.

77

http://data.csb.gov.lv/pxweb/lv/Sociala/Sociala__ikgad__iedz__iedzskaits/IS0020.px/table/tableViewLayout1/?rxid=cdcb978c-22b0-416a-aacc-aa650d3e2ce0

78http://data.csb.gov.lv/Selection.aspx?px_tableid=atirdz\Detaliz%C4%93ta+statistika\8+z%C4%ABmju+l%C4%ABmen%C4%AB\2012_i

mp_8.px&px_language=en&px_type=PX&px_db=atirdz&rxid=cdcb978c-22b0-416a-aacc-aa650d3e2ce0 79

http://www2.mst.dk/common/Udgivramme/Frame.asp?http://www2.mst.dk/udgiv/publications/2009/978-87-7052-962-4/html/bred01_eng.htm

80 http://www2.mst.dk/udgiv/publications/2009/978-87-7052-962-4/pdf/978-87-7052-963-1.pdf




233

Total amount of HFC-134a used for manufacturing of shoe soles can be estimated by using equation:

HFC filled = Sh produced × d HFC × HFCsh where:

HFCfilled – total amount of HFC-134a used in manufacturing of shoes (t)

Shproduced – amount of produced shoes (pieces)

dHFC – amount of shoes containing HFC-134a (%)

HFCsh – amount of HFC-134a filled in one shoe sole (t)

Danish default leakage factor for HFC-134a emitted during manufacturing is 15%.

The HFC-134a emissions from manufacturing of shoe soles can be estimated by using

equation:

E production = HFC filled × k where:

Eproduction – HFC-134a emissions from shoe manufacturing (t)

HFCfilled – total amount of HFC used in manufacturing of shoes (t)

k – leakage from shoes production (%)

HFC-134a emissions from stocks in shoes containing F-gases

In whole period 1995-2013 amount of imported shoes in Latvia is increasing.

The amount of imported and exported as well as produced shoes (shoe sole) is obtained by CSB. According to previous mentioned Danish project it was assumed that 5% of all shoes

with plastic, rubber and leather soles contain polyether containing 8 g of HFC-134a per shoe.

Total amount of HFC-134a held in stocks in shoe soles can be estimated by using equation:

HFC stocks = HFC filled + HFC imported – HFC exported where:

HFCstocks – total amount of HFC-134 held in stocks in shoe soles and used in country in particular year (t)

HFCfilled – total amount of HFC-134a filled in shoes during manufacture of shoes (t)

HFCimported – total amount of HFC-134a imported in shoes (t)

HFCexported – total amount of HFC-134a exported in shoes (t)

Danish default leakage factor for HFC-134a emitted during lifetime is 4.5% (lifetime is 3 years) or 1.5% annually.

The HFC-134a emissions from stocks held in shoe soles can be estimated by using equation:

E stocks = HFC stocks × x where:

Estocks – HFC-134a emissions from shoe lifetime (t)

HFCstocks – total amount of HFC-134 held in stocks in shoe soles and used in country in particular year (t)

x – leakage from using of shoes during its lifetime (%)


234

HFC-134a emissions from disposal of shoes containing F-gases

According to Danish project average lifetime of shoes is 3 years. It means that form HFC-134a emission estimation the amount of HFC-134a remained in shoe soles after their lifetime

in year-3 has to no known. As CSB doesn’t have so old data the approximate amount back to year 1992 is extrapolated taken into account the amount curve in 1995-2000.

Total amount of HFC-134a left in shoe soles after their lifetime ends can be estimated by using equation:

HFC remained = HFC stocks × (1-x) where:

HFCremained – total amount of HFC-134a remained in shoes after their lifetime in year-3

(t)

(1-x) – percentage amount of HFC left in shoes (%)

For the emission estimation from disposal default Danish emission factor 71.5% is used as

some part of shoes are destroyed in incineration and thereby not released as emissions.

The HFC-134a emissions from disposal of shoe soles can be estimated by using equation:

E disposal = HFC remained × Q where:

Edisposal – total amount of HFC-134a emissions from disposal

HFCremained – total amount of HFC-134a remained in shoes after their lifetime in year-3

(t)

Q – leakage from d isposal (%)


Uncertainty could arise to 75% according to expert judgement. Also uncertainty of emission factors for HFCs is assumed as 75%. Combined emission uncertainty was estimated using

Approach 1 of the 2006 IPCC Guidelines.







process sector. It is also planned to perform F-gases research to significantly improve the process of obtaining the activity data and country specific emission factors as well as decrease


4.9 REFERENCES

IPCC 2006. 2006 IPCC Guidelines for National Greenhouse Gas Inventories.

Hayama: IPCC and IGES. http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.htm.


235

EMEP/EEA air pollutant emission inventory guidebook 2013

Register of Chemical Substances and Chemical Mixtures;

Database "2-Air";

Data from State Agency of Medicines;

Data from Central Statistical Bureau.


236

5. AGRICULTURE (CRF 3)


Emissions of greenhouse gases (GHG) from agriculture sector in Latvia include: 1) emission of methane (CH4) from enteric fermentation of domestic livestock and

manure management; 2) emission of nitrous oxide (N2O) from manure management and managed soils;

3) emission of carbon dioxide (CO2) from lime and urea application.

Emissions from managed soils include direct nitrous oxide emissions (application of synthetic nitrogen (N) fertilizer; animal manure, compost, sewage sludge and other organic fertilizers;

urine and dung N deposited by grazing animals on pasture, range and paddock ; N in crop residues, as well as cultivation of organic soil in croplands and grasslands and N

mineralisation associated with loss of soil organic matter resulting from change of land use or management of mineral soils and indirect nitrous oxide emissions (atmospherics deposition, nitrogen leaching and run-off).

Rice cultivation (3 C) and savannas (3 E) are not typical for Latvia; therefore these categories are reported as ―NO‖ in CRF tables. Legislative measures and agricultural residue

management practices prohibit agricultural residues burning on fields, therefore a notation key ‖NO‖ is used in CRF tables under the category Field Burning of Agricultural Residues

(3 F). The calculation of emissions is based on 2006 IPCC Guidelines methodology. Detailed

information about methods is provided under each subcategory.

In 2013, agriculture sector contributed 2310.1 Gg CO2 eq. which made up 21.0% of total

national emissions and it was the second largest source of GHG emissions in Latvia. Nitrous oxide emissions constituted 58.5% (1351.7 Gg CO2 eq.) and methane emissions resulted in 40.7% (940.5 Gg CO2 eq.) of total GHG emissions from agricultural sector. Remaining 0.8%

(17.9 Gg CO2 eq.) of total GHG emissions were made up of lime and urea usage. 85.4% of total agriculture sector methane emissions resulted from enteric fermentation and 14.6% -

from manure management. The largest part (91.8%) of total nitrous oxide emissions resulted from direct- indirect emissions of managed soils, only 8.2% of total nitrous oxide emissions related to manure management.

In 2013, GHG emissions from agriculture sector in Latvia increased by 2.6% comparing with 2012. However, annual emissions have been reduced by 58.4% since 1990 due to decrease in the number of livestock, nitrogen fertilizers etc. (Table 5.1).

Table 5.1 Greenhouse gas emissions (Gg CO2 eq.) in the agricultural sector, 1990–2013

Year CH4 N2O CO2 Total

1990 2690.5 2489.0 379.1 5558.7

1991 2575.6 2330.3 238.6 5144.5

1992 2099.4 1851.3 37.5 3988.2

1993 1351.0 1387.0 4.0 2741.9

1994 1179.5 1233.1 2.5 2415.1

1995 1155.9 1097.6 2.0 2255.5

1996 1096.9 1100.8 1.5 2199.2

1997 1060.6 1105.0 1.3 2166.9

1998 984.6 1064.4 3.4 2052.4

1999 857.4 999.6 3.5 1860.4

2000 837.1 1016.3 6.2 1859.6

2001 878.8 1098.9 2.2 1979.9


237

Year CH4 N2O CO2 Total

2002 874.8 1070.3 20.1 1965.2

2003 871.1 1119.6 27.1 2017.8

2004 841.0 1097.3 2.5 1940.7

2005 863.8 1148.5 3.0 2015.3

2006 868.4 1151.9 2.9 2023.1

2007 903.6 1195.8 6.5 2105.9

2008 874.9 1195.4 6.0 2076.3

2009 869.2 1214.9 8.5 2092.6

2010 881.4 1253.1 6.1 2140.6

2011 885.5 1256.5 12.5 2154.5

2012 909.5 1325.0 16.1 2250.5

2013 940.5 1351.7 17.9 2310.1

Share of total % in 2013 40.7% 58.5% 0.8% 100.0%

2013 versus 2012 +3.5% +2.0% +10.9% +2.6%

Some interannual variation of emissions, which can be noticed from the time series, was mainly caused by fluctuation in activity data among the years due to the changes in number of animals, which had been significantly affected by economical situation in the country, as well

as agricultural policy. Methane and nitrous oxide emissions from manure management were affected by the fluctuation in the number of animals and the proportion of manure managed in

different manure management systems which vary depending on animal species. Nitrous oxide emissions from managed soils generally were affected by the numbers describing management of organic soils, amount of synthetic fertilizers consumption, number of animals

and crop yields, which have large variation among the years.

Emissions from agriculture noticeably decreased in the beginning of 90`s after the Soviet

system and large state or collective farms collapses. However, in the recent years it is possible to observe a slight increase of sown area, consumption of synthetics N-fertilizers, non-dairy, sheep, swine and poultry numbers. State efforts to improve animal manure management

systems (MMS) and expansion of anaerobic digester production in the largest farms is the main reason that reduces the increase of emissions from manure management in the last years.

In the last years, farming in Latvia turns to liquid slurry management system according to closing of small farms and reflection to the trend to this management system in developed countries, however liquid slurry produces more methane and results in increase of this type of

emissions.

Number of cattle, sheep, swine, goats, horses, poultry, rabbits and fur-bearing animals’

population, as well as data on milk production and fat content in milk are obtained from the Central Statistical Bureau (CSB) of Latvia Database and statistical yearbooks . Similarly to the number of domestic livestock, also statistical information about amounts of synthetic

fertilizer N application and crop production is obtained from the CSB database. The distribution of different manure management systems is adopted from national studies on two

periods:

1) 1990-1999 according to assumptions made by Latvian State Institute of Agrarian Economics81 (LSIAE, 2005);

2) 2000-2012 according to research activities and developed methodology provided by Latvia University of Agriculture82.

81

Latvian State Institute of Agrarian Economics. http://www.lvaei.lv/lv/ 82

Rivža P. u.c. Lauksaimniecības rādītāju prognoze 2015. un 2020. gadam. Latvijas Republikas Zemkopības ministrija. Latvijas Lauksaimniecības universitāte. 2011

http://www.lvaei.lv/lv/


238

Statistical information about livestock number in Latvia is included in Table 5.2. Number of fur-bearing animals is not available for 1990-1992 and 1995, therefore interpolation and extrapolation is used to fill in the gaps of time series.

Table 5.2 Number of livestock (thousand heads), 1990–2013

Year Dairy

Cattle

Non-

dairy

Cattle

Sheep Swine Goats Horses Poultry Rabbits

Fur-

bearing

animals

1990 535.1 904.2 164.6 1401.1 5.4 30.9 10321.1 194.0 260.2

1991 531.4 851.5 183.7 1246.5 6.1 30.0 10395.1 223.0 260.2

1992 481.7 662.6 164.7 866.5 6.4 28.4 5438.3 198.5 260.2

1993 351.0 326.9 114.0 481.8 6.3 26.2 4123.7 162.8 260.2

1994 311.9 238.9 86.3 500.7 7.4 26.8 3699.6 154.5 221.0

1995 291.9 245.2 72.2 552.8 8.9 27.2 4198.3 152.5 213.5

1996 274.6 234.8 55.5 459.6 8.4 25.8 3790.7 134.3 205.9

1997 262.8 214.1 40.7 429.9 8.9 23.3 3550.7 93.4 88.6

1998 242.1 192.3 29.4 421.1 10.5 22.0 3208.8 97.6 55.2

1999 205.6 172.8 27.0 404.9 8.1 19.0 3236.9 72.3 84.0

2000 204.5 162.2 28.6 393.5 10.4 19.9 3104.6 110.9 97.2

2001 209.1 175.6 29.0 428.7 11.5 19.6 3621.2 150.4 117.7

2002 204.6 183.5 31.5 453.2 13.2 18.5 3882.0 141.6 116.3

2003 186.3 192.3 39.2 444.4 15.0 15.4 4002.6 149.2 119.4

2004 186.2 184.9 38.6 435.7 14.7 15.5 4049.5 135.5 143.5

2005 185.2 200.0 41.6 427.9 14.9 13.9 4092.3 97.9 141.7

2006 182.4 194.7 41.3 416.8 14.3 13.6 4488.1 92.9 182.8

2007 180.4 218.3 53.9 414.4 13.0 13.0 4756.8 96.4 181.4

2008 170.4 209.8 67.1 383.7 12.9 13.1 4620.5 57.4 197.5

2009 165.5 212.7 70.7 376.5 13.2 12.6 4828.9 43.9 164.4

2010 164.1 215.4 76.8 389.7 13.5 12.0 4948.7 33.5 167.0

2011 164.1 216.5 79.7 375.0 13.4 11.5 4417.9 39.3 183.7

2012 164.6 228.5 83.6 355.2 13.3 10.9 4910.9 37.3 231.6

2013 165.0 241.5 84.8 367.5 12.6 10.7 4985.8 38.9 231.6

2013

versus

2012

+0.2% +5.7% +1.4% +3.5% -5.3% -1.8% +1.5% +4.3% 0.0%

Latvian livestock industry has been influenced by historical events and economic situation. Particularly significant changes in the livestock industry began in 1992 after the restoration of

Latvian independence when most of big farms went into liquidation. Since the Soviet Union had a planned economy, most of the output of livestock products was carried out in other

Soviet republics. Reorientation of livestock product export to Western markets was more difficult in terms of market saturation. Latvian farmers were forced to reduce production levels of milk, meat and egg. Consequently, livestock numbers declined most rapidly in 1990-

1994 in all sectors, except for goat farming. In the case of stud-farms – all the above-mentioned social and economic changes lead to eliminating of stud-farms, the horses were

sold, only the strongest stud-farms continued to work. Starting from 2004, according to Latvia accession to the European Union, the number of livestock has stabilized. The increase of production indicators was characteristic for beef cattle, sheep, goat and poultry industries.

Dairy farming is one of the most important branches of agriculture in Latvia. Number of dairy cows in Latvia is relatively stable, with a tendency to a slight increase in the last years. In

2013, 165 thousand dairy cows were registered and an average milk yield per cow reached 5508 kg, showing the highest value since 1990. Since 2009, the number of large farms has increased, while small farms have been closed, however dairy farms in Latvia are

characterized by a low herd size in comparison with other European countries.


239

Statistical surveys are the source of data on crop production in commercial companies, private farms and individual merchants. Fluctuations in activity data is observed due to economical situation in the country. Since 2007, two sugar factories have stopped their activity therefore

no data is presented further. Agricultural statistics data fulfil criteria are determined by the EU and requirements are determined in the legislative acts. The Project Documentation System

(ADS) is established at CSB. It is a quality metadata system for internal and external users. There are methodological descriptions of all statistical surveys and calculations. Annual samples are made up as stratified simple samples. Holdings are selected b y economic size

(standard output – SO) and type of farming. Standard output is a standard indicator characterizing the economic activity of agricultural holding, i.e., value acquired from one

hectare of agricultural crops or one livestock head (unit), estimated at prices of the corresponding region and expressed in EUR. A Total standard output characterises the economic size of the holding in monetary terms. Farms with SO >= 50000 EUR are included

for 100% statistical surveys; farms with 2000 EUR<SO < 50000 EUR are selected by economic size and type of farming. Sample size for annual sample (Crop and Animal survey)

includes 5.1 thousand holdings. Small holdings with SO < 2000 EUR are not included in annual Crop and Animal surveys, but information for these holdings is estimated using experts’ method. For this estimation CSB uses information from Agricultural Censuses and

surveys of small farms, which are organized between Censuses. Crop and livestock statistics quality reports are available on CSB web page83;84.

Statistical information about crop production in Latvia for calculation of nitrous oxide emissions is included in Table 5.3 and Table 5.4. Data about sown area of mixed cereals and pulses (1990-1997) and oil flax (1990-1999) are not available; therefore data for filling gaps

in the time series are extrapolated from the closest numbers. Other statistical data are included in relevant subchapters.

Table 5.3 Sown area (thousand ha) of agricultural crops, 1990–2013

Year Wheat Barley Triticale Oats Rye Buckwheat Mixed

cereals Rape Pulses

Mixed

cereals

and

pulses

1990 141.5 306.6 1.1 82.4 130.7 0.1 12.7 1.9 10.5 20.4

1991 71.5 397.4 2.6 92.7 69.2 0.1 13.7 0.7 9.0 20.4

1992 128.6 347.0 3.3 69.4 131.4 0.1 13.5 1.3 6.7 20.4

1993 169.1 270.3 6.8 48.5 187.6 0.1 6.2 1.7 2.8 20.4

1994 94.6 264.1 3.1 54.0 62.7 0.1 5.3 2.2 2.8 20.4

1995 109.6 195.9 2.7 45.6 40.4 0.1 6.8 1.1 3.0 20.4

1996 149.2 176.4 1.7 53.6 56.4 0.1 6.8 0.8 3.6 20.4

1997 152.3 188.7 2.8 59.1 62.5 0.6 11.0 0.4 4.7 20.4

1998 150.9 165.9 5.3 59.7 57.7 1.7 13.6 1.2 6.8 20.4

1999 146.0 142.7 5.8 47.2 47.2 2.3 7.9 6.5 2.5 10.4

2000 158.1 130.6 5.9 45.5 54.8 6.2 5.3 6.9 2.1 7.4

2001 166.8 124.0 13.0 55.2 55.8 10.6 4.1 8.4 3.2 7.3

2002 153.5 132.1 15.5 47.1 42.3 10.5 3.4 18.4 2.5 5.9

2003 167.8 129.2 19.1 49.4 44.2 6.5 2.9 25.9 2.9 5.8

2004 169.9 123.5 17.1 56.7 45.1 9.7 3.3 54.3 2.6 5.9

2005 187.4 145.9 13.3 58.0 39.3 10.4 3.7 71.4 2.2 5.9

2006 215.1 149.8 11.3 62.9 42.8 14.0 4.9 83.2 1.4 6.3

2007 224.6 139.7 12.4 62.4 57.5 10.7 3.0 99.2 1.6 4.6

2008 256.6 123.9 13.8 66.2 59.0 10.4 2.7 82.6 1.6 4.3

2009 285.7 94.6 13.1 60.6 59.0 10.1 2.5 93.3 2.5 5.0

83

http://www.csb.gov.lv/sites/default/files/quality_report_on_annual_crop_statistics_2010_0.pdf 84

http://www.csb.gov.lv/sites/default/files/quality_report_on_livestock_and_meat_statistics_2010_0.pdf

http://www.csb.gov.lv/sites/default/files/quality_report_on_annual_crop_statistics_2010_0.pdf

http://www.csb.gov.lv/sites/default/files/quality_report_on_livestock_and_meat_statistics_2010_0.pdf


240

Year Wheat Barley Triticale Oats Rye Buckwheat Mixed

cereals Rape Pulses

Mixed

cereals

and

pulses

2010 307.6 91.1 12.1 63.3 34.6 8.2 3.6 110.6 2.7 6.3

2011 311.3 94.7 9.9 59.3 28.4 9.5 3.8 121.3 3.8 7.6

2012 354.7 85.2 13.3 62.0 37 11.7 3.8 117.5 4.6 8.4

2013 371.8 82.3 14.2 62.4 29.1 10.6 1.2 128.2 7.0 8.2

Table 5.4 Sown area (thousand ha) of agricultural crops, 1990–2013

Year

Sugar

beet

Fodder

roots Potatoes

Maize

for

silage

and

forage

Crops

for

green

feed

and

silage

Perennial

grass

Grasslands

and

pastures

Fibre

flax Oil flax

1990 14.7 37.0 80.3 44.8 73.9 664.0 847.7 11.9 0.3

1991 14.6 39.4 82.2 39.5 84.9 679.6 844.2 8.8 0.3

1992 24.8 36.5 96.9 24.8 56.7 598.6 843.4 7.6 0.3

1993 12.1 29.6 87.7 9.2 31.4 536.0 825.1 0.6 0.3

1994 12.0 26.2 80.4 2.7 20.9 540.6 803.4 1.5 0.3

1995 9.5 19.8 75.3 0.6 17.8 374.7 800.5 1.4 0.3

1996 10.0 17.3 78.7 1.2 11.6 398.4 798.1 1.3 0.3

1997 10.9 14.9 69.6 0.5 13.2 389.7 738.0 1.6 0.3

1998 16.3 13.1 58.8 0.5 12.8 392.7 677.9 2.2 0.3

1999 15.5 9.1 50.1 0.7 12.0 383.1 617.7 2.0 0.3

2000 12.7 9.0 51.3 1.2 11.4 347.2 605.7 1.6 0.3

2001 14.1 9.6 55.1 1.0 8.4 304.4 611.3 1.4 0.4

2002 15.9 7.5 53.6 1.2 7.2 335.1 610.3 2.1 0.1

2003 14.4 7.1 54.6 1.7 9.9 282.9 613.1 2.1 0.1

2004 13.8 5.6 48.9 2.9 9.9 302.3 620.9 2.7 0.1

2005 13.5 3.8 45.1 2.9 8.7 360.6 628.9 2.2 0.2

2006 12.7 2.8 45.1 3.5 11.4 425.8 636.8 1.5 0.2

2007 0.3 2.3 40.3 5.1 11.1 427.1 641.0 1.4 0.1

2008 NO 0.9 37.8 5.9 8.2 413.1 648.1 0.4 0.2

2009 NO 0.7 30 9.8 7.2 413.7 659.4 0.1 0.2

2010 NO 0.9 30.1 7.1 6.3 387.3 625.2 0.0 1.1

2011 NO 0.8 29.7 11.3 5.7 370.8 651.2 0.1 1.4

2012 NO 0.6 28.2 20.6 10.6 351.4 656.4 0.6 0.3

2013 NO 0.3 27.3 20.4 7.7 356.7 663.4 0.2 0.1

5.2 ENTERIC FERMENTATION (CRF 3.A)


Methane (CH4) is emitted as a by-product of the normal livestock digestive process, in which microbes resident in the animals’ digestive system ferment the feed consumed by the animal. This fermentation process is also known as enteric fermentation85. Ruminant livestock (cattle,

sheep and goats) are primary source of methane emissions. The amount of enteric methane emitted is driven primarily by the number and size of domestic animals, the type of digestive

system, and the type and amount of feed consumed 86. Latvia reports emissions from cattle (including dairy cows), sheep, swine, goats, horses, rabbits, and fur-bearing animals (Table 5.5). Emission from poultry enteric fermentation has not been estimated. According to 2006

IPCC Guidelines methodology for enteric fermentation calculation from poultry is not

85

IPCC GPG, 2000 86

2006 IPCC Guidelines


241

developed. Methane emission from poultry is calculated below in the Manure management category.

Table 5.5 Reported emissions under the subcategory Enteric Fermentation

CRF Source Emissions reported

3.A 1 Cattle Dairy / Non-Dairy Cattle CH4

3.A 2 Sheep CH4

3.A 3 Swine CH4

3.A 4 Other – Buffalo NO

3.A 4 Other – Camels NO

3.A 4 Other – Deer NE

3.A 4 Other – Goats CH4

3.A 4 Other – Horses CH4

3.A 4 Other – Mules and asses NO

3.A 4 Other – Poultry NE

3.A 4 Other – Rabbits CH4

3.A 4 Other – Fur-bearing animals CH4

Cattle are the largest source of enteric methane emissions (95.2% from total enteric fermentation methane emissions) in Latvia. In 2013, dairy cattle produced 64.1% and non-dairy cattle –31.1% of methane emissions. Emissions from sheep formed 2.1%, from swine –

1.7%, from horses – 0.6%, and from goats – 0.2% of the total emissions from enteric fermentation. In 2013, total methane emissions from enteric fermentation of do mestic

livestock increased by 1.11 Gg or 3.6%, comparing with 2012. This is caused by the increase of the number of all livestock, except goats and horses. Since 1990, generally due to the evident fall of the number of livestock, methane emissions decreased by 64.7% (Table 5.6).

Table 5.6 Methane emissions (Gg) from Enteric Fermentation by livestock category, 1990–2013

Year Dairy

cattle

Non-

dairy

cattle

Sheep Swine Goats Horses Rabbits

Fur-

bearing

animals

Total,

CH4

1990 52.92 34.21 1.32 2.10 0.03 0.56 0.11 0.03 91.28

1991 51.52 32.22 1.47 1.87 0.03 0.54 0.13 0.03 87.80

1992 44.85 25.07 1.32 1.30 0.03 0.51 0.12 0.03 73.22

1993 32.60 12.37 0.91 0.72 0.03 0.47 0.10 0.03 47.23

1994 29.67 9.04 0.69 0.75 0.04 0.48 0.09 0.02 40.78

1995 28.34 9.28 0.58 0.83 0.04 0.49 0.09 0.02 39.67

1996 27.24 8.96 0.44 0.69 0.04 0.46 0.08 0.02 37.94

1997 27.16 8.13 0.33 0.64 0.04 0.42 0.06 0.01 36.79

1998 25.37 7.29 0.24 0.63 0.05 0.40 0.06 0.01 34.04

1999 21.53 6.51 0.22 0.61 0.04 0.34 0.04 0.01 29.30

2000 21.55 6.09 0.23 0.59 0.05 0.36 0.07 0.01 28.95

2001 22.39 6.44 0.23 0.64 0.06 0.35 0.09 0.01 30.21

2002 21.69 6.86 0.25 0.68 0.07 0.33 0.08 0.01 29.98

2003 21.02 7.43 0.31 0.67 0.08 0.28 0.09 0.01 29.88

2004 20.39 6.92 0.31 0.65 0.07 0.28 0.08 0.01 28.72

2005 20.69 7.50 0.33 0.64 0.07 0.25 0.06 0.01 29.56

2006 20.68 7.53 0.33 0.63 0.07 0.24 0.05 0.02 29.55

2007 20.84 8.57 0.43 0.62 0.07 0.23 0.06 0.02 30.84

2008 20.05 8.35 0.54 0.58 0.06 0.24 0.03 0.02 29.87

2009 19.67 8.52 0.57 0.56 0.07 0.23 0.03 0.02 29.65

2010 19.71 8.73 0.61 0.58 0.07 0.22 0.02 0.02 29.96

2011 19.79 8.85 0.64 0.56 0.07 0.21 0.02 0.02 30.15

2012 20.14 9.38 0.67 0.53 0.07 0.20 0.02 0.02 31.03

2013 20.59 10.02 0.68 0.55 0.06 0.19 0.02 0.02 32.14

Share of

total %

in 2013

64.1% 31.1% 2.1% 1.7% 0.2% 0.6% 0.1% 0.1% 100.0%


242

Year Dairy

cattle

Non-

dairy

cattle

Sheep Swine Goats Horses Rabbits

Fur-

bearing

animals

Total,

CH4

2013

versus

2012

+2.3% +6.8% +1.4% +3.5% -5.3% -1.8% +4.3% 0.0% +3.6%

5.2.2 Methodological issues

The Tier 1 approach relies on default emissions factors. For Tier 1 methodology countries are required to collect data on number of animals for each livestock category. The Tier 2 approach is more complex because it draws upon country-specific information on animal and

feed characteristics. The Tier 2 approach is recommended to estimate methane emissions for countries with large cattle and sheep populations.

Emissions from enteric fermentation of domestic livestock in Latvia have been calculated by using the IPCC Tier 1 and Tier 2 methodologies presented in the 2006 IPCC Guidelines. Methane emissions from enteric fermentation for sheep, swine, goats, horses, rabbits and fur-

bearing animals have been calculated with the IPCC Tier 1 methodology by multiplying the number of the animals in each category with the IPCC default emission factor of the

respective livestock category as shown in 2006 IPCC Guidelines87:

where:

Emissions = methane emissions from Enteric Fermentation, Gg CH4 yr-1

;

EF(T) = emission factor for the defined livestock population, kg CH4 head-1

yr-1

;

N(T) = the number of head of livestock species / category T in the country;

T = species/category of livestock.

The default emission factors as for developed countries according to 2006 IPCC Guidelines88

were used to calculate methane emissions from enteric fermentation for sheep, swine, goats, horses, rabbits and fur-bearing animals (Table 5.7). As default IPCC or national emission

factors for rabbits and fur-bearing animals are not available, the Norwegian89 emission factor for fur-bearing animals and Russian90 emission factor for rabbits were used for emission calculations similarly by experience of the neighbouring countries.

Table 5.7 Default methane emission factors from Enteric Fermentation

Livestock category EF (kg CH4 head-1

yr-1

)

Sheep 8

Swine 1.5

Goats 5

Horses 18

Rabbits 0.59

Fur-bearing animals 0.1

87

2006 IPCC Guidelines. Volume 4, Chapter 10, Equation 10.19, page 10.28 88

2006 IPCC Guidelines. Volume 4, Chapter 10, Table 10.10, page 10.28 89

Greenhouse gas emission in Norway 1990-2011, National inventory report, 2013, p. 238, Table 6.3 90

Национальный доклад о кадастре антропогенных выбросов из источников и абсорбции поглотителями парниковых газов не регулируемых Монреальским протоколом за 1990-2011 г. Москва, 2013. Часть 1, C. 175, Taблица 6.5


243

The Tier 2 methodology has been used for cattle, because emissions from cattle make up the biggest part of total agricultural sector methane emissions. With the Tier 2 methodology methane emissions have been calculated as in the Tier 1 methodology mentioned above, but

the emission factors (EF) for dairy cattle and non-dairy cattle hve been calculated according to 2006 IPCC Guidelines methodology represented as91:

where:

EF = emission factor, kg CH4 head-1

yr-1

;

GE = gross energy intake, MJ head-1

day-1

;

Ym = methane conversion factor, per cent of gross energy in feed converted to methane (d efault values in table

10.12, page 10.30 from 2006 IPCC Guidelines);

The factor 55.65 (MJ/kg CH4) is the energy content of methane.

For cattle, the gross energy intake (GE) has been calculated according to 2006 IPCC Guidelines92:

where:

GE = gross energy, MJ day-1

;

NEm = net energy required by the animal for maintenance, MJ day-1

;

NEa = net energy for animal activity, MJ day-1

;

NEl = net energy for lactation, MJ day-1

;

NEwork = net energy for work, MJ day-1

;

NEp = net energy required for pregnancy, MJ day-1

;

REM = ratio of net energy available in a diet for maintenance to digestible energy consumed;

NEg = net energy needed for growth, MJ day-1

;

REG = ratio of net energy available for growth in a diet to digestible energy consumed;

DE%= digestible energy expressed as a percentage of gross energy.

The equations for calculating NEm (Equation 10.3, 2006 IPCC Guidelines), NEa (Equation 10.4, 2006 IPCC Guidelines), NEl (Equation 10.8, 2006 IPCC Guidelines), NEp

(Equation 10.13, 2006 IPCC Guidelines), NEg (Equation 10.6, 2006 IPCC Guidelines), REM (Equation 10.14, 2006 IPCC Guidelines) and REG (Equation 10.15, 2006 IPCC Guidelines)93 are:

91



2006 IPCC Guidelines. Volume 4, Chapter 10, Equation 10.3-10.15, page 10.15-10.21


244

where:

Cfi = maintenance coefficient (default values used94

);

Weight = animal weight, kg;

Ca = coefficient corresponding to animals feeding situation (default values used)95

;

Milk = amount of milk produced, kg of milk day-1

;

Fat = fat content of milk, % by weight;

Cpregnancy = Pregnancy coefficient (default values used96

);

BW = the average live body weight (BW) of the animals in the population, kg;

MW = the mature live body weight of an adult female in moderate body condition, kg;

WG = the average daily weight gain of the animals in the population, kg day-1

;

C = a coefficient with a value of 0.8 for females, 1.0 for castrates and 1.2 for bulls;

REM = ratio of net energy available in a diet for maintenance to digestible energy consumed;

REG= ratio of net energy available for growth in a diet to digestible energy consumed;

DE% = digestible energy, %.

When using NEp to calculate GE, the NEp estimate must be weighted by the portion of the mature females that actually go through gestation in a year. According to animal breeding

specialist calculations based on data of Agricultural Data Centre Republic of Latvia Register, 83% of the NEp value is used in the GE equation.

Methane conversion factor (Ym) of zero is assumed for juveniles consuming only milk (2006

IPCC Guidelines, p.10.30). In Latvia, it was supposed that calves feed milk and milk substitute no longer than of age 3 months. Therefore it was assumed that methane conversion

rate of young cattle less than 1 year old is 4.9%. The rate was estimated as three fourths of Ym 6.5% for all cattle, based on an assumption that for calves between 0 and 3 months Ym is 0%.

Feed digestibility (DE) 65% is used in calculations according to the average value represented in Table 10.2 in the 2006 IPCC Guidelines, because detailed information on feed digestibility

are not available in the country yet.

The calculation of GE is strongly based on the milk production and fat content in milk. Trends about milk production and fat content in milk are presented in Table 5.8.

Values of milk fat content for 1990-1997 are derived by extrapolation based on an assumption that fat content in milk was around 3.5% in 1990; all other information comes from CSB of

Latvia.

Table 5.8 Average milk yield per cow (kg year-1

) and fat content (% )

Year Average milk yield Fat content

1990 3437 3.50

1991 3205 3.58

1992 2793 3.67

1993 2741 3.75

94



2006 IPCC Guidelines. Volume 4, Chapter 10, Table 10.7, page 10.20


245

Year Average milk yield Fat content

1994 2923 3.84

1995 3074 3.92

1996 3237 4.01

1997 3585 4.09

1998 3733 4.06

1999 3754 4.00

2000 3898 4.08

2001 4055 4.08

2002 3958 4.08

2003 4261 4.11

2004 4251 4.17

2005 4364 4.25

2006 4492 4.26

2007 4636 4.31

2008 4822 4.29

2009 4892 4.31

2010 4998 4.29

2011 5064 4.22

2012 5250 4.16

2013 5508 4.08

In Latvian inventory livestock category cattle consists of dairy cattle and non-dairy cattle. Calculating methane emissions from enteric fermentation, dairy cattle are not divided into smaller sub-categories. A non-dairy cattle category for the period 1990-2013 consists of seven

sub-categories according to the records in a database of CSB of Latvia:

Young cattle less than 1 year old:

calves for slaughter ;

heifers and bulls for breeding ;

Young cattle from 1 to 2 years old:

bulls;

heifers; Mature non-dairy cattle 2 years old and over:

bulls;

heifers;

other cows. Missing data or no available data are extrapolated mathematically. The total numbers of

non-dairy cattle by sub-categories are presented in Table 5.9.

Table 5.9 The number (thousand heads) of non-dairy cattle by sub-categories in Latvia, 1990-2013

Year

Young cattle less

than 1 year old

Young cattle from

1 to 2 years old

Mature non-dairy cattle

2 years old and over

calves for

slaughter

heifers and

bulls for

breeding

bulls heifers bulls heifers other cows

1990 142.6 382.6 83.0 219.6 12.0 54.3 10.1

1991 134.3 360.3 78.2 206.8 11.3 51.2 9.6

1992 104.5 280.4 60.8 160.9 8.8 39.8 7.4

1993 51.6 138.3 30.0 79.4 4.3 19.6 3.7

1994 37.7 101.1 21.9 58.0 3.2 14.4 2.7

1995 38.7 103.8 22.5 59.5 3.2 14.7 2.8

1996 37.1 97.3 22.9 56.4 3.3 15.0 2.8

1997 37.1 86.6 20.6 50.1 2.6 13.8 3.3

1998 28.2 81.1 16.1 49.8 1.6 12.7 2.8

1999 27.3 73.3 17.0 42.5 1.1 9.5 2.1


246

Year

Young cattle less

than 1 year old

Young cattle from

1 to 2 years old



calves for

slaughter

heifers and

bulls for

breeding


2000 24.7 73.2 13.5 38.1 0.8 9.8 2.1

2001 68.6 43.4 18.1 30.9 1.7 10.4 2.5

2002 64.7 46.0 20.2 40.1 1.1 8.7 2.7

2003 64.3 44.8 24.4 42.3 1.5 11.2 3.8

2004 63.5 46.9 15.9 40.7 1.7 11.6 4.6

2005 60.4 58.5 14.8 44.8 1.6 11.9 8.0

2006 52.5 55.0 15.1 47.8 1.8 13.1 9.5

2007 52.7 62.2 15.4 57.1 1.2 14.6 15.2

2008 49.2 59.2 12.1 54.1 2.6 20.8 12.7

2009 52.1 55.4 13.1 53.7 3.0 19.9 15.6

2010 51.2 54.0 13.6 54.0 3.2 20.3 18.7

2011 50.4 53.5 11.7 55.0 3.1 20.9 22.0

2012 52.6 55.8 12.2 57.9 3.5 21.0 25.6

2013 53.0 56.3 14.3 61.0 4.3 23.4 29.2

Results of gross energy intake (GE) calculation for dairy and non-dairy cattle from enteric fermentation are summarized in Table 5.10.

Table 5.10 Calculated gross energy (GE) intake (MJ day-1

), 1990-2013

Year Dairy

cows

Young cattle less than

1 year old

Young cattle from 1 to

2 years old

Mature non-dairy cattle 2 years and

over

calves for

slaughter

heifers

and bulls

for

breeding


1990 232.0 77.8 86.2 150.1 109.6 180.3 130.7 139.4

1991 227.4 77.8 86.2 150.1 109.6 180.3 130.7 139.4

1992 218.4 77.8 86.2 150.1 109.6 180.3 130.7 139.4

1993 217.9 77.8 86.2 150.1 109.6 180.3 130.7 139.4

1994 223.1 77.8 86.2 150.1 109.6 180.3 130.7 139.4

1995 227.7 77.8 86.2 150.1 109.6 180.3 130.7 139.4

1996 232.7 77.8 86.2 150.1 109.6 180.3 130.7 139.4

1997 242.4 77.5 86.2 150.1 109.6 181.4 130.7 139.4

1998 245.8 77.5 86.2 150.1 109.6 181.4 130.7 139.4

1999 245.6 77.5 86.2 150.1 109.6 181.4 130.7 139.5

2000 247.2 79.0 87.9 151.4 110.6 183.0 131.9 142.1

2001 251.1 78.7 88.4 151.1 110.3 182.5 131.7 142.2

2002 248.7 79.0 87.9 151.3 110.7 181.4 131.3 142.3

2003 264.6 79.0 87.9 151.4 110.5 182.9 131.8 142.1

2004 256.9 79.0 87.9 150.7 110.4 182.8 131.7 142.3

2005 262.0 79.0 87.9 150.8 110.1 182.2 131.9 142.1

2006 265.9 79.0 87.9 150.3 109.8 181.6 132.1 142.2

2007 270.9 79.0 87.9 150.1 109.6 181.3 132.5 142.2

2008 276.0 79.0 87.9 150.0 109.6 181.3 133.1 142.2

2009 278.7 79.0 87.9 149.7 109.4 180.9 133.4 142.2

2010 281.7 79.0 87.9 149.3 109.0 180.4 133.5 142.1

2011 282.8 79.1 88.1 149.9 109.0 180.4 134.0 142.4

2012 287.0 79.1 88.1 148.8 108.7 180.3 134.3 142.4

2013 292.7 78.3 87.1 147.6 107.9 178.2 133.8 140.9

Results of emission factors calculation for dairy and non-dairy cattle from enteric fermentation are summarized in Table 5.11.


247

Table 5.11 Calculated emission factors (kg CH4 head-1

year-1

) of methane emission from Enteric

Fermentation, 1990-2013

Year Dairy

cows

Young cattle less than

1 year old

Young cattle from 1 to

2 years old

Mature non-dairy cattle 2 years old

and over

calves for

slaughter

heifers

and bulls

for

breeding


1990 98.9 24.9 27.5 64.0 46.7 76.9 55.7 59.4

1991 97.0 24.9 27.5 64.0 46.7 76.9 55.7 59.4

1992 93.1 24.9 27.5 64.0 46.7 76.9 55.7 59.4

1993 92.9 24.9 27.5 64.0 46.7 76.9 55.7 59.4

1994 95.1 24.9 27.5 64.0 46.7 76.9 55.7 59.4

1995 97.1 24.9 27.5 64.0 46.7 76.9 55.7 59.4

1996 99.2 24.9 27.5 64.0 46.7 76.9 55.7 59.4

1997 103.4 24.8 27.6 64.0 46.7 77.3 55.7 59.4

1998 104.8 24.8 27.6 64.0 46.7 77.3 55.7 59.4

1999 104.7 24.8 27.6 64.0 46.7 77.3 55.7 59.5

2000 105.4 25.3 28.1 64.6 47.1 78.0 56.2 60.6

2001 107.1 25.2 28.3 64.4 47.0 77.8 56.1 60.6

2002 106.0 25.3 28.1 64.5 47.2 77.3 56.0 60.7

2003 112.8 25.3 28.1 64.5 47.1 78.0 56.2 60.6

2004 109.5 25.3 28.1 64.2 47.1 77.9 56.2 60.7

2005 111.7 25.3 28.1 64.3 46.9 77.7 56.2 60.6

2006 113.4 25.3 28.1 64.1 46.8 77.4 56.3 60.6

2007 115.5 25.3 28.1 64.0 46.7 77.3 56.5 60.6

2008 117.7 25.3 28.1 64.0 46.7 77.3 56.7 60.6

2009 118.8 25.3 28.1 63.8 46.6 77.1 56.9 60.6

2010 120.1 25.3 28.1 63.7 46.5 76.9 56.9 60.6

2011 120.6 25.3 28.2 63.9 46.5 76.9 57.1 60.7

2012 122.3 25.3 28.2 63.4 46.4 76.9 57.3 60.7

2013 124.8 25.1 27.9 62.9 46.0 76.0 57.0 60.1

5.2.3 Uncertainties and time series consistency

The uncertainty associated with livestock population varies widely depending on the source, but according to 2006 IPCC Guidelines should be known within +20%. However, according to received information from CSB of Latvia, uncertainty of activity data describing numbers

of livestock could be 2-3%. Generally, the uncertainty of activity data provided by CSB of Latvia is set as 2%. 2006 IPCC Guidelines declare that emission factors estimated using the

Tier 1 method are unlikely to be known more accurately than +30% and may be uncertain to +50%. Tier 2 method is likely to be in the order of +20%97.

According to the assumptions above, emission factors estimated using the Tier 1 method is set

to be uncertain of 40%, but uncertainty of emission factors estimated by the Tier 2 is set as 20%.

5.2.4 Source-specific QA/QC and verification

Activity data check. Livestock data were checked by an inventory compiler. Livestock age

sub-groups data that were collected by extrapolating are compared with statistical data of CSB to achieve correct total numbers. Data collection methods are documented in agriculture

sector inventory compilers data base for GHG inventory purposes.

97

2006 IPCC Guidelines. Volume 4, Chapter 10, page 10.33


248

Review of emission factors. Country-specific emission factors derived with Tier 2 method are cross-checked against the IPCC defaults. Results of comparison of emission factors for methane emission from enteric fermentation of dairy cows and non-dairy cattle are shown

below (Table 5.12):

Table 5.12 Review of emission factors for enteric fermentation methane emissions

Category Source EF (kg CH4 head-1

year-1

)

Dairy cows Latvia, Tier 2, 2013 125.0


(Western Europe)98

117.0

Non-dairy cattle Latvia, Tier 2, 2013 (average) 44.0


(Western Europe)58

57.0

Latvia uses higher emission factor for dairy cows based on a different feeding situation that is

not totally characterized as stall fed (set for Tier 1). Also digestibility used for calculations of emission coefficient is lower (65% against 70% for Tier 1). In average enteric fermentation methane emission factor for non-dairy cattle is lower than IPCC default, caused mainly by

different feeding situation (pasture, range and paddock corresponds with 35.8% for non-dairy cattle in Latvia).

5.2.5 Source-specific recalculations

For 2015 submission the main recalculations of methane emissions for the period 1900-2013 are done based on the implementation of 2006 IPCC Guidelines methodology. Emissions from non-dairy livestock are calculated within seven age subcategories, comparing to

previous submission. Also two new animal categories as rabbits and fur-bearing animals are included in the inventory.

5.2.6 Source-specific planned improvements

Elaboration of methodology to expand calculations on swine age subgroups is planned for the

next inventory.

5.3 MANURE MANAGEMENT (CRF 3.B)


The emission sources cover management of manure from domestic livestock. Latvia reports methane (CH4) and nitrous oxide (N2O) emissions from cattle (including dairy cows), sheep, swine (including market and breeding swine), horses, goats and poultry (including layers and

broilers and others), as well as rabbits and fur-bearing animals (Table 5.13). When organic matter in livestock manure decomposes in anaerobic environment, methanogenic bacteria

produce methane. The amount of methane produced from manure depends on a livestock type and diet, special feeding and digestibility of food, as well as waste management system. The nitrous oxide estimated in this section is the N2O produced during the storage and treatment

of manure before it is applied to land. Production of nitrous oxide during storage and treatment of animal wastes occurs via combined nitrification-denitrification of nitrogen in

animal waste.

98



249

Table 5.13 Reported emissions under the subcategory Manure Management


3.B 1 Cattle Dairy / Non-Dairy Cattle CH4, N2O

3.B 2 Sheep CH4, N2O

3.B 3 Swine CH4, N2O

3.B 4 Other – Buffalo NO

3.B 4 Other – Camels NO

3.B 4 Other – Deer NE

3.B 4 Other – Goats CH4, N2O

3.B 4 Other – Horses CH4, N2O

3.B 4 Other – Mules and asses NO

3.B 4 Other – Poultry CH4, N2O

3.B 4 Other – Rabbits N2O

3.B 4 Other – Fur-bearing animals N2O

Methane emissions from manure management have decreased by 66.5% over the time period 1990-2013 (Table 5.14). In 2013, methane emissions from manure management of domestic

livestock increased by 0.13 Gg or 2.5% compared with 2012.

Table 5.14 Methane emissions (Gg) from Manure Management by livestock category 1990-2013

Year Dairy

Cattle

Non-

dairy

Cattle

Sheep Swine Goats Horses Poultry Rabbits

Fur-

bearing

animals

Total CH4

1990 2.66 1.33 0.03 8.98 0.0007 0.05 3.09 0.0155 0.18 16.34

1991 2.59 1.26 0.03 7.98 0.0008 0.05 3.12 0.0178 0.18 15.22

1992 2.26 0.98 0.03 5.62 0.0008 0.04 1.63 0.0159 0.18 10.76

1993 1.64 0.48 0.02 3.24 0.0008 0.04 1.19 0.0130 0.18 6.81

1994 1.49 0.35 0.02 3.28 0.0010 0.04 1.05 0.0124 0.15 6.40

1995 1.43 0.36 0.01 3.52 0.0012 0.04 1.05 0.0122 0.15 6.57

1996 1.37 0.35 0.01 2.88 0.0011 0.04 1.13 0.0107 0.14 5.94

1997 1.37 0.32 0.01 2.73 0.0012 0.04 1.11 0.0075 0.06 5.63

1998 1.28 0.28 0.01 2.67 0.0014 0.03 1.03 0.0078 0.04 5.34

1999 1.08 0.25 0.01 2.55 0.0011 0.03 1.01 0.0058 0.06 5.00

2000 1.57 0.29 0.01 2.48 0.0014 0.03 0.08 0.0089 0.07 4.54

2001 1.68 0.32 0.01 2.72 0.0015 0.03 0.09 0.0120 0.08 4.94

2002 1.59 0.33 0.01 2.87 0.0017 0.03 0.10 0.0113 0.08 5.01

2003 1.56 0.36 0.01 2.82 0.0020 0.02 0.10 0.0119 0.08 4.97

2004 1.56 0.34 0.01 2.77 0.0019 0.02 0.10 0.0108 0.10 4.92

2005 1.64 0.38 0.01 2.73 0.0019 0.02 0.10 0.0078 0.10 4.99

2006 1.84 0.41 0.01 2.66 0.0019 0.02 0.11 0.0074 0.12 5.19

2007 1.90 0.48 0.01 2.65 0.0017 0.02 0.12 0.0077 0.12 5.30

2008 1.92 0.47 0.01 2.45 0.0017 0.02 0.11 0.0046 0.13 5.12

2009 1.93 0.50 0.01 2.41 0.0017 0.02 0.12 0.0035 0.11 5.11

2010 1.99 0.53 0.01 2.50 0.0018 0.02 0.12 0.0027 0.11 5.30

2011 2.06 0.54 0.02 2.39 0.0017 0.02 0.11 0.0031 0.12 5.27

2012 2.18 0.59 0.02 2.26 0.0017 0.02 0.12 0.0030 0.16 5.35

2013 2.17 0.65 0.02 2.34 0.0016 0.02 0.12 0.0031 0.16 5.48

Share

of total

% in

2013

39.6% 11.8% 0.3% 42.7% 0.0% 0.3% 2.3% 0.1% 2.9% 100.0%

2013

versus

2012

-0.3% +9.6% +1.4% +3.4% -5.3% -1.8% +1.5% +4.3% 0.0% +2.5%


250

In 2013, total nitrous oxide emissions (including direct and indirect emissions) reached 0.37 Gg. Direct nitrous oxide emissions decreased by 61.0% over the time period 1990-2013 (Table 5.15). In 2013, direct emissions from manure management increased by 0.01 Gg or

4.5% compared to 2012. The fluctuation of emissions is related to the variation of animal numbers, as well as changes in the distribution of livestock manure management systems

(MMS). Similarly indirect nitrous oxide emissions decreased by 66.5% over the time period 1990-2013, showing the tendency to increase by 0.01 Gg or 4.3% in the last inventory year comparing with 2012 (Table 5.15).

Table 5.15 Nitrous oxide emissions (Gg) from Manure Management by livestock category, 1990-2013*

Year Dairy

Cattle

Non-dairy

Cattle

Sheep Swine Goats Horse

s

Poultr

y Rabbits

Fur-

bearing

animal

s

Total direct,

N2O

Total indirect,

N2O

1990 0.25 0.17 0.004 0.05 0.000 0.006 0.04 0.01 0.02 0.55 0.48

1991 0.25 0.16 0.005 0.05 0.000 0.005 0.04 0.01 0.02 0.53 0.46

1992 0.22 0.12 0.004 0.03 0.000 0.005 0.02 0.01 0.02 0.43 0.37

1993 0.16 0.06 0.003 0.02 0.000 0.005 0.02 0.01 0.02 0.29 0.23

1994 0.14 0.04 0.002 0.02 0.000 0.005 0.01 0.01 0.01 0.25 0.20

1995 0.14 0.05 0.002 0.02 0.000 0.005 0.01 0.01 0.01 0.25 0.20

1996 0.13 0.04 0.002 0.02 0.000 0.005 0.01 0.01 0.01 0.23 0.19

1997 0.13 0.04 0.001 0.02 0.000 0.004 0.01 0.01 0.01 0.21 0.18

1998 0.12 0.04 0.001 0.02 0.000 0.004 0.01 0.01 0.00 0.20 0.16

1999 0.10 0.03 0.001 0.01 0.000 0.003 0.01 0.00 0.01 0.17 0.14

2000 0.12 0.02 0.001 0.01 0.000 0.004 0.01 0.01 0.01 0.19 0.15

2001 0.13 0.03 0.001 0.01 0.000 0.004 0.01 0.01 0.01 0.20 0.16

2002 0.12 0.03 0.001 0.02 0.000 0.003 0.01 0.01 0.01 0.20 0.16

2003 0.12 0.03 0.001 0.02 0.000 0.003 0.01 0.01 0.01 0.20 0.16

2004 0.12 0.03 0.001 0.02 0.000 0.003 0.01 0.01 0.01 0.19 0.16

2005 0.12 0.03 0.002 0.02 0.001 0.003 0.01 0.01 0.01 0.20 0.16

2006 0.12 0.03 0.002 0.01 0.001 0.003 0.01 0.01 0.01 0.20 0.16

2007 0.12 0.04 0.002 0.01 0.001 0.002 0.02 0.01 0.01 0.21 0.17

2008 0.12 0.04 0.003 0.01 0.001 0.002 0.01 0.00 0.01 0.20 0.16

2009 0.11 0.04 0.003 0.01 0.001 0.002 0.02 0.00 0.01 0.20 0.16

2010 0.11 0.04 0.003 0.01 0.001 0.002 0.01 0.00 0.01 0.20 0.15

2011 0.11 0.04 0.003 0.01 0.001 0.002 0.01 0.00 0.01 0.20 0.15

2012 0.12 0.04 0.003 0.01 0.001 0.002 0.01 0.00 0.02 0.20 0.15

2013 0.12 0.05 0.003 0.01 0.001 0.002 0.01 0.00 0.02 0.21 0.16

Share

of total % in

2013

54.8% 22.9% 1.6% 5.7% 0.4% 0.9% 5.4% 1.2% 7.1% 100.0% -

2013

versus 2012

-0.7% +19.7% +1.4% -4.8% -5.3% -1.8% +29.3% +4.3% 0.0% +4.5% +4.3%

*emissions from pasture not included, they are reported under 3.D Managed soils


The 2006 IPCC Guidelines include two tiers to estimate emissions from livestock manure. The Tier 1 approach requires livestock population data by animal species/category and

climate region in order to estimate emissions. The Tier 2 approach requires detailed information on animal characteristics and the manner in which manure is managed; it is

encouraged to be used for countries where a particular livestock species/category represents a significant share of emissions. The process of developing Tier 2 emission factors involves


251

determining the mass of volatile solids excreted by the animals (VS, in kg) along with the maximum methane producing capacity for the manure (Bo, in m3 kg of VS). In addition, a methane conversion factor (MCF) that accounts for the influence of climate on methane

production must be obtained for each manure management system.

Methane emissions from manure management for sheep, swine (divided as market and

breeding swine), goat, horse, poultry (divided as layers and broilers and others), rabbits and fur-bearing animals were calculated by using Tier 1 methodology by multiplying the number of the animals with the default emission factor for each animal category according to the 2006

IPCC Guidelines99:

where:

CH4 Manure = CH4 emissions from manure management, for a defined population, Gg CH4 yr-1

EF(T) = emission factor for the defined livestock population, kg CH4 head-1 yr-1;

N(T) = the number of head of livestock species / category T in the country;


Emission factors for Tier 1 methodology calculations were chosen as for cool climate region and are represented in Table 5.16. The original source of default emission factors is 2006

IPCC Guidelines100.

Table 5.16 Methane emission factors from Manure Management

Animal category EF (kg head-1

year-1

)

Sheep 0.19

Goats 0.13

Horses 1.56

Market swine 6

Breed ing swine 9

Layers (dry manure) 0.03

Layers (liqu id manure) 1.2

Bro ilers and others 0.02

Rabbits 0.08

Fur-bearing animals 0.68

For dairy cattle and non-dairy cattle the Tier 2 approach was used for estimating methane emissions from manure management systems as dairy cattle’s represent a significant share of

total emissions from agriculture sector. This method requires detailed information on animal characteristics and the manner in which manure is managed. Methane emission factors for cattle were determined from the 2006 IPCC Guidelines101:

where:

EF(T) = annual CH4 emission factor for livestock category T, kg CH4 animal

-1 yr

-1;

VS(T) = daily volatile solid excreted for livestock category T, kg dry matter animal

-1 day

-1;

Bo(T) = maximum methane producing capacity for manure produced by livestock category T, m3 CH4 kg

-1of VS

excreted (0.24 for dairy cattle and 0.17 for non-dairy cattle);

99


2006 IPCC Guidelines. Volume 4, Chapter 10, Tables 10.15 and 10.16, page 10.40-10.41 101

2006 IPCC Guidelines. Volume 4, Chapter 10, Equation 10.23, page 10.41


252

MCF(S,k) = methane conversion factors for each manure management system by climate region k, % (Solid

Storage – 2%, Liquid Storage (with crust) – 10%, Pasture/Range/Paddock – 1%;Anaerobic Digester – 0% as

represented in table 10.17, page 10.44, 2006 IPCC Guidelines);

MS(T,S,k) = fraction of livestock category manure handled using manure management system in climate region k,

dimensionless;

0.67 = conversion factor of m3 CH4 to kilograms CH4;

365 = basis for calculating annual VS production, days yr-1

.

Default methane conversion factor (MCF) values for manure management systems, as well as methane producing capacities B0 (0.24 for dairy cows and 0.17 for other cattle) are used in

Latvia’s National Greenhouse Gas Inventory.

Daily volatile solid (VS) excretion rate (per day on a dry-matter weight basis) was estimated

as represented in the 2006 IPCC Guidelines102:

where:

VS = volatile solid excretion per day on a dry-organic matter basis, kg VS day-1

;

GE = gross energy intake, MJ day-1

;

DE% = digestibility of the feed in percent (65%);

(UE • GE) = urinary energy expressed as fraction of GE (0.04•GE are considered as urinary energy);

ASH = the ash content of manure calculated as a fraction of the dry matter feed intake (0.08);

18.45 = conversion factor for dietary GE per kg of dry matter (MJ kg-1

).

Results of calculation of the country specific methane emissions factors from manure

management are included in Table 5.17.

Table 5.17 Calculated emission factors (kg CH4 head-1

year-1

) used for estimation of methane emission

from manure management for dairy and non-dairy cattle, 1990-2013

Year Dairy

cows

Young cattle less

than 1 year old

Young cattle from

1 to 2 years old



calves for

slaughter

heifers

and bulls

for

breeding


1990 4.98 1.01 1.14 2.40 1.76 2.99 2.09 1.84

1991 4.88 1.01 1.14 2.40 1.76 2.99 2.09 1.84

1992 4.69 1.01 1.14 2.40 1.76 2.99 2.09 1.84

1993 4.68 1.01 1.14 2.40 1.76 2.99 2.09 1.84

1994 4.79 1.01 1.14 2.40 1.76 2.99 2.09 1.84

1995 4.89 1.01 1.14 2.40 1.76 2.99 2.09 1.84

1996 4.99 1.01 1.14 2.40 1.76 2.99 2.09 1.84

1997 5.20 1.02 1.14 2.42 1.77 2.91 2.09 1.84

1998 5.27 1.02 1.14 2.41 1.76 2.94 2.09 1.84

1999 5.27 1.02 1.14 2.42 1.77 2.92 2.10 1.83

2000 7.68 0.95 1.05 3.64 2.66 4.37 3.14 1.71

2001 8.04 0.96 1.03 3.92 2.86 4.75 3.36 1.70

2002 7.77 0.95 1.05 3.69 2.53 5.61 3.59 1.70

2003 8.39 0.95 1.05 3.67 2.68 4.45 3.16 1.71

2004 8.39 0.95 1.05 4.34 2.76 4.54 3.25 1.69

2005 8.88 0.95 1.05 4.14 3.03 5.03 3.58 1.71

2006 10.07 0.95 1.05 4.56 3.32 5.50 3.96 1.70

2007 10.52 0.95 1.05 4.70 3.44 5.71 4.11 1.70

2008 11.24 0.95 1.05 4.71 3.45 5.71 4.15 1.70

2009 11.69 0.95 1.05 4.98 3.63 6.00 4.38 1.70

2010 12.14 0.95 1.05 5.30 3.84 6.40 4.66 1.70

102



253

Year Dairy

cows

Young cattle less

than 1 year old

Young cattle from

1 to 2 years old



calves for

slaughter

heifers

and bulls

for

breeding


2011 12.54 0.94 1.05 5.65 3.95 6.59 4.76 1.69

2012 13.24 0.94 1.05 5.82 4.16 6.68 5.10 1.69

2013 13.16 0.98 1.09 5.73 4.16 6.86 5.09 1.76

The 2006 IPCC Guidelines methodology was used for estimating nitrous oxide (N2O) emissions from manure management by multiplying the total amount of N excretion (from all

animal species/categories) in each type of manure management system by an emission factor for that type of manure management system. Emissions are then summed over all manure

management systems. Direct nitrous oxide emissions (kg N2O yr-1) from manure management have been calculated by using 2006 IPCC Guidelines103:

where:

N2O D(mm) = direct N2O emissions from Manure Management in the country, kg N2O yr-1

;

N(T) = number of head of livestock species/category T in the country;

Nex(T) = annual average N excretion per head of species/category T in the country, kg N animal-1

yr-1

;

MS(T,S) = fraction of total annual nitrogen excretion for each livestock species/category T that is managed in

manure management system in the country, dimensionless;

EF3(S) = emission factor for direct N2O emissions from manure management system S in the country, kg N2O-N kg-1 N in

manure management system;

S = manure management system;


The amount of nitrogen excreted annually per animal has been divided among different manure management systems and multiplied with the IPCC default emission factor for each

manure management system. The manure management systems (S) reported in the inventory are:

liquid system;

solid storage;

pasture range and paddock;

anaerobic digester.

Following emission factors for direct nitrous oxide emissions from manure management were implemented: EF3 = 0.005 for liquid manure/slurry with natural crust cover; EF3 = 0.005 for solid storage; EF3 = 0 for pasture/range/paddock; EF3 = 0 for digester (2006 IPCC

Guidelines104). Data about the distribution of animal manure management systems (MMS) according to the national studies are available in Appendix A.3.4. Nitrous oxide emissions

from pasture are calculated under manure management, but are reported under category Urine and dung deposited by grazing animals in CRF 3.D.

Data of N excretion during the year per each livestock category used for the inventory are

country specific and are obtained from national studies105. IPCC default annual average

103 2006 IPCC Guidelines. Volume 4, Chapter 10, Equation 20.25, page 10.54 104


Fertiliser Recommendations for Agricultural Crops (2013) Ed.A. Karklins and A.Ruza. Jelgava:LLU, 55 p.


254

nitrogen excretion was used for rabbits and fur-bearing animals106. All mentioned values are represented in Table 5.18.

Table 5.18 Average N excretions (N, kg year-1

) per head of animal

Livestock category 1990-2004 2005-2013

Sheep 6 13

Market swine 4 4

Breed ing swine 9 9

Goats 6 13

Horses 46 47

Layers 0.6 0.6

Bro ilers and others 0.3 0.3

Rabbit 8.1 8.1

Fur - bearing animals 8.34 8.34

Values about annual N excretion (Nex(T)) per animal for dairy cattle and non-dairy cattle were calculated according to IPCC Tier 2 methodology107:

where:

Nex (T) = annual N excretion rates, kg N animal-1

yr-1

;

Nintake (T) = the annual N intake per head of animal of species/category T , kg N animal-1

yr-1

;

Nretention(T) = fraction of annual N intake that is retained by animal of species/category T, dimensionless.

The daily N intake per animal head of species/category is calculated as108:

where:

N intake (T) = daily N consumed per animal of category T, kg N animal-1

day-1

;

GE = gross energy intake of the animal, MJ animal-1

day1;

18.45 = conversion factor for dietary GE per kg of dry matter, MJ kg-1

;

CP% = percent crude protein in diet, input (16% used for calculations);

6.25 = conversion from kg of dietary protein to kg of dietary N, kg feed protein (kg N-1

).

The daily N retention per animal head of species/category is estimated as109:

where:

N retention(T) = daily N retained per animal of category T, kg N animal-1

day-1

;

Milk = milk production, kg animal-1

day-1

(dairy cows only);

Milk PR% = percent of protein in milk, calculated as [1.9 + 0.4 %Fat];

6.38 = conversion from milk protein to milk N, kg Protein (kg N)-1

;

WG = weight gain, input for each livestock category, kg day-1

;

268 and 7.03 = constants;

NEg = net energy for growth, MJ day-1

;

6.25 = conversion from kg dietary protein to kg dietary N, kg Protein (kg N)-1

.

106






255

Calculated values of N excretion (Nex(T)) per animal for dairy cattle and non-dairy cattle are represented in Table 5.19.

Table 5.19 N excretion rates (kg N animal-1

yr-1

) used in the estimates of N2O emissions for dairy and non-

dairy cattle, 1990-2013

Year Dairy

cows

Young cattle less

than 1 year old

Young cattle from

1 to 2 years old



calves for

slaughter

heifers

and bulls

for

breeding


1990 100 29 34 67 48 88 63 67

1991 98 29 34 67 48 88 63 67

1992 96 29 34 67 48 88 63 67

1993 96 29 34 67 48 88 63 67

1994 97 29 34 67 48 88 63 67

1995 99 29 34 67 48 88 63 67

1996 100 29 34 67 48 88 63 67

1997 103 29 34 67 48 88 63 67

1998 104 29 34 67 48 88 63 67

1999 104 29 34 67 48 88 63 67

2000 104 30 35 68 49 89 63 68

2001 105 30 35 68 49 89 63 68

2002 104 30 35 68 49 88 63 68

2003 109 30 35 68 49 89 63 68

2004 106 30 35 67 49 89 63 68

2005 108 30 35 67 49 89 63 68

2006 109 30 35 67 48 88 63 68

2007 111 30 35 67 48 88 64 68

2008 112 30 35 67 48 88 64 68

2009 113 30 35 67 48 88 64 68

2010 114 30 35 67 48 88 64 68

2011 115 30 35 67 48 88 64 68

2012 116 30 35 66 48 88 64 69

2013 118 30 35 66 47 87 64 68

The indirect nitrous oxide emissions from volatilisation of N in forms of NH3 and NOx from

manure management are estimated as:

N2O G(mm) = (N volatilization−MMS • EF4) where:

N2OG(mm) = indirect N2O emissions due to volatilization of N from Manure Management in the country, kg N2O yr-1

;

Nvolatilization-MMS = amount of manure nitrogen that is lost due to volatilisation of NH3 and NOx, kg N yr-1

;

EF4 = emission factor for N2O emissions from atmospheric deposition of nitrogen on soils and water surfaces,

kg N2O-N (kg NH3-N + NOx-N volatilised)-1

; default value 0.01 kg N2O-N (kg NH3-N +NOx-N volatilised)-1

is

used.

The indirect nitrous emissions from leaching and runoff of N from manure management

systems are estimated as:

N2O L(mm) = (N leaching −MMS • EF5) where:

N2OL(mm) = indirect N2O emissions due to leaching and runoff from Manure Management in the country, kg N2O yr-1

;

Nleaching-MMS = amount of manure nitrogen that leached from manure management systems, kg N yr-1

;

EF5 = emission factor for N2O emissions from nitrogen leaching and runoff, kg N2O-N/kg N leached and runoff

(default value 0.0075 kg N2O-N (kg N leaching/runoff)-1

.


256

The amount of manure nitrogen that is lost due to volatilisation of NH3 and NOx, and that leaches into soil and/or runs off during solid storage of manure at outdoor areas or in feedlots is fully derived from 2006 IPCC Guidelines, Equations 10.26 and 10.28110.


The uncertainty of the manure management system usage data depends on the characteristics of each country's livestock industry and how information on manure management is collected.

2006 IPCC Guidelines show that for one type of management system, the uncertainty associated with management system usage data can be 10% or less. However, for countries where there is a wide variety of management systems, the uncertainty range in management

system usage data can be much higher, in the range of 25% to 50%, depending on the availability of reliable and representative survey data that differentiates animal populations by

system usage111. For Latvia uncertainty of 25% is set. The uncertainty range for the default emission factors is estimated to be +30%. Improvements achieved by Tier 2 methodologies are evaluated to reduce uncertainty ranges in the emission factors to +20%. IPCC expert

judgment shows that uncertainty ranges for the default N excretion rates are estimated at about +50%112. Latvia uses country specific values, therefore uncertainty for N excretion rates

are reduced to 25%.


Activity data check. General QC procedures including quality checks related to calculations, data processing, completeness, and documentation were used during the inventory. Defined

manure management systems in the inventory is consistent with definitions that are presented in 2006 IPCC Guidelines Table 10.18113. Latvia uses country specific methodology to determine distribution of manure management systems that is available in scientific

literature114.

Review of emission factors. Country-specific emission factors were compared with IPCC

defaults. Emission factors were chosen as for cool climate region by average annual temperature ≤10°C. Data in Table 5.20 shows that Latvia uses lower emission factors than IPCC defaults.

Table 5.20 Review of emission factors for methane emission calculation from manure management

Category Source EF (kg CH4 head-1

year-1

)

Dairy cows Latvia, Tier 2, 2013 13.2


(Western Europe)115

21

Non-dairy cattle Latvia, Tier 2, 2013(average) 3.6


(Western Europe)75

6

Default emission coefficients are represented based on an assumption that liquid storage systems are commonly used for cattle manure and limited cropland is available for spreading

manure, however in Latvia liquid systems are not dominated for cattle. In 2013, a liquid system for dairy-cows was accounted as 27.6% of all manure management systems, but for

non-dairy cattle the share of liquid systems reached only 21.4%. Liquid systems also are not

110 2006 IPCC Guidelines. Volume 4, Chapter 10, Equation 10.26 and 10.28, page 10.54, 10.56



113 2006 IPCC Guidelines. Volume 4, Chapter 10, Table 10.18, page 10.49

114 Priekulis J., Āboltiņš A. (2015) Calculation Methodology for Cattle Manure Management Systems Based on the 2006 IPCC Guidelines .

Proceedings of the 25th NJF Congress Nordic View to Sustainable Rural Development. Riga, pp.274-280 115



257

typical for young cattle less than 1 year old and for suckling cows. Usually, solid storages and pasture, range and paddock is used as a manure management system that is associated with low MCF values, consequently leading to smaller emissions amounts.

Latvia uses country specific nitrogen excretion rates116, according to the latest research results. Calculated and measured nitrogen excretion rates are compared with other countries

inventory data and default factors. No significant differences were found for rates used for inventory that are within the range of values reported in other EU countries.


For 2015 submission, recalculations of methane emissions for period 1900-2013 are done

based on implementation of 2006 IPCC Guidelines. Emissions from non-dairy livestock are calculated within seven age subcategories, comparing to the previous submission, swine and

poultry are divided in two subgroups. Also two new animal categories as rabbits and fur-bearing animals are included in the inventory.


Updating of manure management systems distribution data, according to the new

methodology developed by scientists according to manure management systems explanations in 2006 IPCC Guidelines to determine manure management systems specific for Latvia. Especially, manure management systems distribution data should be updated for the period

1990-1999.

5.4 AGRICULTURAL SOILS (CRF 3.D)


In the 2006 IPCC Guidelines, direct and indirect emissions of nitrous oxide from managed soils are estimated separately. The following N sources are included in the inventory for estimating direct nitrous oxide emissions from managed soils:

synthetic N fertilizers (FSN);

organic N applied as a fertilizer (e.g., animal manure, compost, sewage sludge,

rendering waste) (FON);

urine and dung N deposited on pasture, range and paddock by grazing animals (FPRP);

N in crop residues (above-ground and below-ground), including from N-fixing crops and from forages during pasture renewal (FCR);

drainage/management of organic soils (i.e., Histosols) (FOS). Indirect N2O emissions from managed soils are determined for volatilization and leaching

processes. Indirect nitrous oxide emissions included in the inventory are reported in Table 5.21.

Table 5.21 Reported emissions under the subcategory Agricultural Soils


3.D 1.1 Inorganic N fert ilizers N2O

3.D 1.2.a Animal manure applied to soils N2O

3.D 1.2.b Sewage sludge applied to soils N2O

3.D 1.2.c Other organic fertilizer applied to soils N2O

3.D 1.3 Urine and dun deposited on soils N2O

116

Fertiliser Recommendations for Agricultural Crops (2013) Ed.A. Karklins and A.Ruza. Jelgava:LLU, 55 p.


258


3.D 1.4 Crop residues N2O 3.D 1.5 Cult ivation of organic soils N2O 3.D 2.1 Atmospheric deposition N2O 3.D 2.2 Nitrogen leach ing and run-off N2O

Nitrous oxide emission from managed soils was 4.16 Gg in 2013. In general, emission has decreased in 2013 by 43.2% comparing with 1990. The main reason for that was decreasing of all livestock numbers that affected the amount of nitrogen excreted annually to soil and low

consumption of fertilizers. However, in 2013 nitrous oxide emission increased by 0.07 Gg or 1.8% comparing with 2012 (Table 5.22). The main reason of the increase of emission in the

latest years is the growing demand of synthetic fertilizers. In 2013, total nitrous oxide emission from managed soils originated as 85.4% from direct sources. Indirect nitrous oxide emission from volatilization formed 4.8% and from leaching – 9.9% of total emission.

Table 5.22 Nitrous oxide emissions (Gg) from Managed Soils, 1990-2013

Year N2O direct

emission

N2O indirect emission

from atmos pheric

deposition

N2O indirect

emission from

leaching and run-off

Total

1990 6.02 0.47 0.84 7.33

1991 5.64 0.43 0.76 6.83

1992 4.56 0.32 0.54 5.41

1993 3.57 0.20 0.35 4.13

1994 3.23 0.17 0.29 3.68

1995 2.89 0.14 0.21 3.24

1996 2.92 0.13 0.22 3.27

1997 2.95 0.13 0.23 3.32

1998 2.87 0.13 0.22 3.21

1999 2.73 0.11 0.20 3.04

2000 2.74 0.12 0.21 3.07

2001 2.93 0.14 0.25 3.32

2002 2.86 0.13 0.24 3.23

2003 2.99 0.14 0.27 3.40

2004 2.93 0.14 0.26 3.33

2005 3.06 0.15 0.29 3.50

2006 3.06 0.15 0.29 3.50

2007 3.16 0.16 0.31 3.64

2008 3.17 0.16 0.32 3.65

2009 3.22 0.17 0.33 3.72

2010 3.32 0.18 0.36 3.85

2011 3.33 0.18 0.36 3.87

2012 3.50 0.19 0.40 4.09

2013 3.55 0.20 0.41 4.16

Share of total % in 2013 85.4% 4.8% 9.9% 100.0%

2013 versus 2012 +1.5% +4.3% +3.5% +1.8%

In 2013, managed organic soils formed the major part of total direct emissions (44.7%),

following by emission from synthetic fertilizers (30.9%), urine and dung deposited on pasture (8.2%), crop residues (8.2%), animal manure applied to soils (7.7%), and other organic N additions applied to soils (Table 5.23).

Table 5.23 Nitrous oxide emissions (Gg) from N inputs to managed soils, 1990-2013

Year FSN

FON

(animal

manure)

FON

(sludge)

FON

(other) FPRP FCR FOS

1990 2.06 0.69 0.00 0.00 1.24 0.33 1.69

1991 1.77 0.67 0.00 0.00 1.19 0.32 1.70


259

Year FSN

FON

(animal

manure)

FON

(sludge)

FON

(other) FPRP FCR FOS

1992 1.04 0.56 0.00 0.00 1.00 0.28 1.69

1993 0.62 0.38 0.00 0.00 0.63 0.24 1.69

1994 0.46 0.33 0.00 0.00 0.54 0.21 1.69

1995 0.18 0.32 0.00 0.00 0.52 0.18 1.69

1996 0.23 0.30 0.00 0.00 0.50 0.20 1.68

1997 0.30 0.28 0.00 0.00 0.48 0.21 1.67

1998 0.31 0.25 0.00 0.00 0.44 0.19 1.67

1999 0.30 0.22 0.00 0.00 0.38 0.16 1.66

2000 0.36 0.25 0.00 0.00 0.31 0.17 1.66

2001 0.50 0.26 0.02 0.00 0.32 0.18 1.65

2002 0.43 0.26 0.02 0.00 0.32 0.18 1.64

2003 0.59 0.26 0.01 0.00 0.32 0.17 1.64

2004 0.55 0.25 0.01 0.00 0.31 0.18 1.63

2005 0.64 0.26 0.01 0.00 0.32 0.21 1.63

2006 0.67 0.26 0.01 0.00 0.31 0.19 1.62

2007 0.72 0.27 0.01 0.00 0.33 0.22 1.61

2008 0.75 0.26 0.00 0.00 0.31 0.25 1.60

2009 0.82 0.25 0.01 0.00 0.31 0.25 1.59

2010 0.94 0.25 0.01 0.01 0.30 0.22 1.59

2011 0.94 0.25 0.01 0.00 0.31 0.24 1.59

2012 1.02 0.26 0.01 0.01 0.31 0.31 1.59

2013 1.10 0.27 0.01 0.01 0.29 0.29 1.58

FSN = synthetic N fertilizer, FON = organic N additions, FPRP = urine and dang N deposited on pasture , FCR = N in crop residues, FOS = managed organic soil in grassland and cropland.


For estimation of nitrous oxide emissions from managed soils the Tier 1 methodology was

used. Direct nitrous oxide emissions from agricultural soils have been calculated using the following equation according to 2006 IPCC Guidelines117 :

where:

where:

N2ODirect –N = annual direct N2O–N emissions produced from managed soils, kg N2O–N yr-1

;

N2O–NN inputs = annual direct N2O–N emissions from N inputs to managed soils, kg N2O–N yr-1

;

N2O–NOS = annual direct N2O–N emissions from managed organic soils, kg N2O–N yr-1

;

N2O–NPRP = annual direct N2O–N emissions from urine and dung inputs to grazed soils, kg N2O–N yr-1

;

FSN = annual amount of synthetic fertiliser N applied to soils, kg N yr-1

;

FON = annual amount of animal manure, compost, sewage sludge and other organic N additions applied to soils, kg N yr-1

;

FCR = annual amount of N in crop residues (above-ground and below-ground), including N-fixing crops, and

from forage/pasture renewal, returned to soils, kg N yr-1

;

FOS = annual area of managed/drained organic soils in grasslands and croplands, ha

FPRP = annual amount of urine and dung N deposited by grazing animals on pasture, range and paddock, kg N yr-1

;

EF1 = emission factor for N2O emissions from N inputs, kg N2O–N kg-1

N input;

EF2 = emission factor for N2O emissions from drained/managed organic soils, kg N2O–N ha-1

yr-1

;

117



260

EF3PRP = emission factor for N2O emissions from urine and dung N deposited on pasture, range and paddock by

grazing animals, kg N2O–N/kg N input.

Data of annual amount of synthetic fertiliser N applied to soils (Table 5.26) are provided by

CSB of Latvia. Data on annual area of managed organic crop and grassland soils are provided by Latvian State Forest Research Institute ―Silava‖ (Table 5.26). N mineralised in mineral soils as a result of soil C loss through change in land use or management are not evaluated in

this category, but are explained in Chapter 6.4.

Applied organic N fertiliser (FON) is calculated using methodology represented in 2006 IPCC

Guidelines118. This includes applied to soils animal manure, sewage, compost, as well as other organic amendments of regional importance to agriculture:

where:

FON = total annual amount of organic N fertiliser applied to soils other than by grazing animals, kg N yr-1

.

FAM = annual amount of animal manure N applied to soils, kg N yr-1

;

FSEW = annual amount of total sewage N that is applied to soils, kg N yr-1

;

FCOMP = annual amount of total compost N applied to soils, kg N yr-1

;

FOOA = annual amount of other organic amendments used as fertiliser, kg N yr-1

.

Data on amount of sewage sludge applied to managed soils are provided by State Ltd Latvian Environment, Geology and Meteorology Centre, other data of organic N fertiliser applied to soils are obtained from CSB. Amounts of sewage composts are not included in calculations.

Other organic amendments used as fertiliser mainly refer to digesters. Amount of nitrogen in sewage sludge, digester and composts are calculated based on sewage sludge application in

agriculture research results done by Latvia University of Agriculture scientists ,119 other research projects 120 and expert judgement.

Statistics of different types of organic N fertilisers applied to soils are limited in Latvia.

Available data is represented in Table 5.24.

Table 5.24 Statistics of organic N fertilisers applied to soils

Year

Sewage sludge applied to

managed soils, t dry

matter

Composts applied to

managed soils, thousand t

Other organic N (digester) applied

to managed soils thousand t

2001 30946.7 NO NO

2002 22513.9 NO NO

2003 9230.89 NO NO

2004 7683.7 NO NO

2005 6545.5 NO NO

2006 8936.4 NO NO

2007 8131.6 NO NO

2008 5255.2 NO NO

2009 6686.9 NO NO

2010 9306.5 95.5 3.7

2011 8759.5 39.9 6.1

2012 7472.6 62.2 82.5

2013 7479.2 40.4 289.9

118


Gemste, I., Vucāns, A. (2010) Notekūdeņu dūņas. Jelgava, LLU, 276 lpp. 120

Litiņa I. (2013) Digestāta kā mēslošanas līdzekļa efektivitātes novērtējums kukurūzas sējumā. Zinātniski praktiskā konference

LAUKSAIMNIECĪBAS ZINĀTNE VEIKSMĪGAI SAIMNIEKOŠANAI . Jelgava, LLU, 206-209 lpp.


261

Animal manure nitrogen (FAM) emits from agricultural soil through manure application to fields as an organic fertilizer. Calculation of emissions from nitrogen input through application of animal manure is done according to 2006 IPCC Guidelines121:

where:


;

NMMS Avb = amount of managed manure N available for soil application, feed, fuel or construction, kg Nyr-1

;

FracFEED = fraction of managed manure used for feed;

FracFUEL = fraction of managed manure used for fuel;

FracCNST = fraction of managed manure used for construction.

Acquired results of FAM are represented in Table 5.26.Total annual amount of managed manure N available for soil application (FMMS_Avb) is determined by 2006 IPCC Guidelines

(Chapter 10.5.4) according to the directions of estimation of N lost from manure management systems to final application on managed soils. Calculations are done by fully adopted IPCC methodology (2006 IPCC Guidelines, Volume 4, Chapter 10, Equation 10.34, p.10.65).

Total annual amount of managed manure N available for soil application is determined under CRF category 3B and is represented in Table 5.26.

The term FPRP refers to the annual amount of N deposited on pasture, range and paddock soils by grazing animals. The term FPRP is estimated using 2006 IPCC Guidelines from the number of animals in each livestock species/category T(N (T)), the annual average amount of N

excreted by each livestock species/category T (Nex(T)), and the fraction of this N deposited on pasture, range and paddock soils by each livestock species/category T (MS(T,PRP))

122:

Total annual amount of N deposited on pasture, range and paddock soils by grazing animals is determined under CRF category 3B and is represented in Table 5.26.

The annual production of residue N (FCR) is estimated using 2006 IPCC Guidelines Tier 1

methodology123:

where:

FCR = annual amount of N in crop residues (above and below ground), including N-fixing crops, and from

forage/pasture renewal, returned to soils annually, kg N yr-1

;

Crop(T) = harvested annual dry matter yield for crop T, kg d.m. ha-1

;

Area(T) = total annual area harvested of crop T, ha yr-1

;

Area burnt (T) = annual area of crop T burnt, ha yr-1

;

Cf = combustion factor;

FracRenew (T) = fraction of total area under crop T;

RAG(T) = ratio of above-ground residues dry matter to harvested yield for crop T;

NAG(T) = N content of above-ground residues for crop T, kg N (kg d.m.)-1

;

FracRemove(T) = fraction of above-ground residues of crop T removed annually for purposes such as feed, bedding

and construction, kg N (kg crop-N)-1

;

RBG(T) = ratio of below-ground residues to harvested yield for crop T, kg d.m. (kg d.m.)-1

;

NBG(T) = N content of below-ground residues for crop T, kg N (kg d.m.)-1

;

T = crop or forage type.

121





262

There are no annual area burnt included in calculations, It is estimated that approximately 20% of above-ground residues of all main crops (wheat, outs, barley and rye) and 80% of rape are removed annually for purposes such as feeding, bedding and construction.

Correction factor to estimate dry matter yields (Crop(T)) is determined as124:

where:

Crop(T) = harvested dry matter yield for crop T, kg d.m. ha-1

;

Yield Fresh(T) = harvested fresh yield for crop T, kg fresh weight ha-1

;

DRY = dry matter fraction of harvested crop T, kg d.m. (kg fresh weight)-1

.

All calculations on annual amount of N in crop residues are done based on default factors represented in 2006 IPCC Guidelines125. Calculated values are available in Table 5.26.

The nitrous oxide emissions from atmospheric deposition of N volatilised from managed soil

are estimated using 2006 IPCC Guidelines126:

where:

N2O(ATD)-N = annual amount of N2O–N produced from atmospheric deposition of N volatilised from managed

soils, kg N2O–N yr-1

;


;

FracGASF = fraction of synthetic fertiliser N that volatilises as NH3 and NOx, kg N volatilised (kg of N applied)-1

;

FON = annual amount of managed animal manure, compost, sewage sludge and other organic N additions

applied to soils, kg N yr-1

;

FPRP = annual amount of urine and dung N deposited by grazing animals on pasture, range and paddock, kg N

yr-1

;

FracGASM = fraction of applied organic N fertiliser materials (FON) and of urine and dung N deposited by

grazing animals (FPRP) that volatilises as NH3 and NOx, kg N volatilised (kg of N applied or deposited)-1

;

EF4 = Emission factor for N2O emissions from atmospheric deposition of N on soils and water surfaces, kg N2O-

N/kg NH3-N and NOx-N emitted.

The N2O emission from nitrogen loss from agricultural soils through leaching and runoff is estimated as shown in 2006 IPCC Guidelines127

:

where:

N2O(L)–N = annual amount of N2O–N produced from leaching and runoff, kg N2O–N yr-1

;

FCR = amount of N in crop residues (above- and below-ground), including N-fixing crops, and from

forage/pasture renewal, kg N yr-1

;

FSOM = annual amount of N mineralised in mineral soils, kg N yr-1

;

FracLEACH-(H) = Fraction of N input that is lost through leaching and runoff, kg N (kg of N additions)-1

;

EF5 = emission factor for N2O emissions from N leaching and runoff, kg N2O–N (kg N leached and runoff)-1

.

All emission coefficients and fractions for estimation direct and indirect emissions estimation from managed soils are summarized in Table 5.25.

Table 5.25 Default emission, volatilization and leaching factors for direct and indirect N2O emissions

calculation

Factor Value Uncertainty range

EF1 for N additions from mineral fert ilizers, organic amendments

and crop residues [kg N2O–N (kg N)-1

] 0.01 0.003 - 0.03

124






263

Factor Value Uncertainty range

EF2 CG, Temp for temperate organic crop and grassland soils

(kgN2O–N ha-1

) 8 24

EF3PRP , CPP for cattle (dairy, non dairy ), poultry and pigs

[kg N2O–N (kg N) -1

] 0.02 0.007 - 0.06

EF3PRP , SO for cattle (dairy, non dairy), poultry and pigs

[kg N2O–N (kg N) -1

] 0.01 0.003 - 0.03

EF4 [N volatilization and re-deposition], kg N2O–N [kg NH3–N +

NOX–volatilized] 0.010 0.002 - 0.05

EF5 (leaching/runoff), kg N2O–N [kg N leaching/runoff] 0.0075 0.0005 -0.025

FracGASF (Volatilizat ion from synthetic fertilizer), (kg NH3–N +

NOx–N) [kg N applied] –1

0.10 0.03 - 0.3

FracGASM (Volatilization from all organic N fertilizers applied ,

and dung and urine deposited by grazing animals), [kg NH3–N +

NOx–N] [kg N applied or deposited] –1

0.20 0.05 - 0.5

FracLEACH-(H),N losses by leaching/runoff [kg N ] 0.30 0.1 - 0.8

Table 5.26 Input values for direct nitrous oxide emission calculations

from managed soils

Year FSN Fos FAM F PRP, CPP F PRP, SO FCR

1990 131400000 134698 44071934 38764439 1154150 21215221

1991 112400000 134852 42821879 37328264 1183650 20172658

1992 66000000 134687 35519679 31235823 1098650 17513578

1993 39700000 134571 24161839 19739697 917801 15510392

1994 29000000 134356 21063748 16737893 863965 13631796

1995 11500000 134116 20530478 16237434 841163 11166742

1996 14500000 133673 19323455 15547322 764653 12987857

1997 19400000 133194 17515142 14959598 669883 13659941

1998 19600000 132753 16074797 13771277 614829 12349370

1999 19000000 132348 14178229 11850712 532623 10229137

2000 23000000 131858 15644288 9578801 579380 10540297

2001 31600000 131367 18305980 9838107 575900 11140060

2002 27600000 130807 17685591 10026617 562660 11325644

2003 37500000 130369 16701116 10009573 522320 11016642

2004 35200000 129879 16393317 9513842 521920 11601038

2005 40900000 129315 16559736 9809305 709240 13412721

2006 42700000 128732 17111887 9429846 697510 12129181

2007 46100000 128130 17557671 9967578 776620 14282755

2008 47500000 127509 16771666 9464918 881540 15675956

2009 51900000 126850 16486902 9315324 899040 15642000

2010 59500000 126450 16964256 9201568 933690 14243144

2011 59800000 126310 16634005 9259304 944170 15138250

2012 65200000 126167 17539376 9306459 960100 19534483

2013 69700000 126028 18375504 8845230 962030 18543329


;

FOS = annual area of managed/drained organic soils in grasslands and croplands, ha


;

FPRP CPP = annual amount of urine and dung N deposited by grazing cattle, swine and poultry on pasture, kg N yr-1

;

FPRP SO = annual amount of urine and dung N deposited by grazing other animals on pasture, kg N yr-1

;

FCR = annual amount of N in crop residues (above and below ground), including N-fixing crops, kg N yr-1

.


The uncertainty of activity data is set to 2%. The uncertainty of the default emission factors reaches +50%.


264


A complete coverage of the direct and indirect N2O emissions from managed land requires estimation of emissions for all anthropogenic inputs and activities (F SN, FON, FCR, FPRP, FSOM and FOS), that is done in the inventory. N excretion data are consistent with those used for the

manure management systems source category. National crop produc tion and synthetic fertilizer consumption statistics is compared to FAO. CSB of Latvia shows efforts to reduce

differences between national statistics and FAO data. All calculations mostly are done according to Tier 1, fluctuations in time series should be explained by fluctuations of statistical data, showing that agricultural production numbers in Latvia are highly variable. As

production levels are strongly associated with support of famers from state, situation on agriculture products market, agricultural products price changes, local demand of agricultural

products and other.


Recalculations are done according to the implementation of 2006 IPCC Guidelines methodology.


Development of the country specific values for FracLEACH-(H) to estimate N losses by leaching/runoff. Development of the country specific data for crop residue statistics, because similar research projects in Latvia show differences between IPCC crop residues statistics and

country specific numbers.

5.5 FIELD BURNING OF AGRICULTURAL RESIDUES (CRF 3.F)

Notation key – NO is used for reporting field burning of agricultural residues in Latvia. Legislative measures and agricultural residue management practices prohibit field burning o f agricultural residues. This is explained by Latvian Administrative Violations Code Section

179 Violation of Fire Safety Regulations.

5.6 LIMING (CRF 3.G)

Liming is used to reduce soil acidity and improve plant growth in managed systems, particularly agricultural lands and managed forests. Adding carbonates to soils in the form of lime (e.g., calcic limestone (CaCO3), or dolomite (CA Mg(CO3)2) leads to CO2 emissions as

the carbonate limes dissolve and release bicarbonate (2HCO3-), which evolves into CO2 and

water (H2O). CO2 using Tier 1 emissions from additions of carbonate limes to soils are

estimated with a formula from 2006 IPCC Guidelines128:

where:

CO2–C Emission = annual C emissions from lime application, tonnes C yr-1

;

M = annual amount of calcic limestone (CaCO3) or dolomite (CA Mg(CO3)2), tonnes yr-1

;

EF = emission factor, tonne of C (tonne of limestone or dolomite) -1

.

Emission factors (EF) are 0.12 for limestone and 0.13 for dolomite. The uncertainty of them is

50%. Statistical data in Latvia provides information on overall consumption of liming

128



265

material. Therefore EF 0.13 is implemented for determination of CO2 emissions from liming. Activity data and calculated emissions are represented in Table 5.27.

Table 5.27 Consumed lime (t year-1) and calculated CO2 (Gg) emissions, 1990-1913

Year Annual amount of consumed liming material CO2 emission

1990 779200 371.42

1991 486700 231.99

1992 70600 33.65

1993 3500 1.67

1994 1600 0.76

1995 2700 1.29

1996 1400 0.67

1997 400 0.19

1998 4700 2.24

1999 4900 2.34

2000 10200 4.86

2001 700 0.33

2002 32900 15.68

2003 53800 25.64

2004 2200 1.05

2005 3300 1.57

2006 3000 1.43

2007 10700 5.10

2008 6000 2.86

2009 8700 4.15

2010 4300 2.05

2011 17400 8.29

2012 21600 10.30

2013 28900 13.78

2013 versus

2012 +33.8% +33.8%

5.7 UREA APPLICATION (CRF 3.H)

CO2 emissions from urea fertilisation are estimated with the following equation from 2006

IPCC Guidelines129:

where:

CO2–C Emission = annual C emissions from urea application, tonnes C yr-1

;

M = annual amount of urea fertilisation, tonnes urea yr-1

;

EF = emission factor, tonne of C (tonnes of urea)-1

.

Emission factor (EF) of 0.20 for urea application emissions is used for calc ulations. The

default 50% of uncertainty is applied, activity data uncertainty is evaluated as 2%. CSB of Latvia data of urea application is available from 2007. FAO data for 2002 and 2003 is also

available. Data for all other years are derived by extrapolation of available statistical values. Table 5.28 represents activity data and estimated CO2 emissions from urea fertilisation.

Table 5.28 Urea fertilisation (tonnes yr-1) statistics and calculated CO2 emissions (Gg), 1990-2013

Year Annual amount of urea fertilization CO2 emissions

1990 10512 7.71

1991 8992 6.59

129



266

Year Annual amount of urea fertilization CO2 emissions

1992 5280 3.87

1993 3176 2.33

1994 2320 1.70

1995 920 0.67

1996 1160 0.85

1997 1552 1.14

1998 1568 1.15

1999 1520 1.11

2000 1840 1.35

2001 2528 1.85

2002 6078 4.46

2003 1942 1.42

2004 1943 1.42

2005 1944 1.43

2006 1945 1.43

2007 1946 1.43

2008 4323 3.17

2009 5930 4.35

2010 5459 4.00

2011 5798 4.25

2012 7901 5.79

2013 5558 4.08

2013 versus 2012 -29.7% -29.7%

5.8 OTHER CARBON-CONTAINING FERTILIZERS (CRF 3.I)

There is no data on other carbon-containing fertilizers use in Latvia. Notation key – NO is used.

5.9 OTHER (CRF 3.J)

There is no information on other sources in Latvia. Notation key – NO is used.


267

6. LAND-USE, LAND-USE CHANGE AND FORESTRY (CRF 4)


This category comprises CO2 emissions and removals arising from Land Use, Land Use Change and Forestry (LULUCF). This sector is important in Latvia's GHG balance due to the

fact that more than half of the country area is covered with forests and due to long history of sustainable forest management which secured that the increment of woody biomass in Latvia

is considerably above the average level in Europe (respectively, 5.3 m3 ha-1 and 4.3 m3 ha-1 in 2010130). According to data provided by National statistical forest inventory (NFI) total forest area (including afforested lands) in 2013 was 3325580 ha (52 % of the total country area).

Total area of land converted to forest from 1990 to 2013 is 204.28 kha. Twenty years transition period is considered for land use changes, therefore area of historical forest lands is

increasing during recent years, but area of lands converted to forest is decreasing, because area converted to forest until 1993 (including) is now reported as forest land remaining forest. The same approach is applied to conversion of cropland to grassland. Conversion of forest

land to other land use categories in 2010-2013 is calculated using the extrapolation method, assuming that conversion of forest land to cropland and to settlements follows to a linear

regression based on data from 1990 to 2009.

Category Other lands consist of degraded areas. No removals or emissions are reported under this category, as it is not managed by definition and does not contain considerable amount of

organic carbon.

Latvia reports carbon stock changes and GHG emissions from forest land, wetland, cropland

and grassland. In the forest land category removals and emissions associated with living biomass and soil were estimated using mixed approach of Tier 1 and Tier 2 and country specific activity data, like increment and harvesting figures, mortality rate in forests, wood

density values, BEFs, carbon stock in biomass, as well as the land use information. Calculations were done by Latvian State Forest Research Institute ―Silava‖ (LSFRI Silava)

with support of Ministry of Agriculture of Republic of Latvia (MoA). Emissions from organic soils (cropland, grassland, forest land), controlled burning (forest land) and wildfires (forest land and grassland) were estimated using Tier 1 and Tier 2 methods and country specific

activity data. Emissions due to conversion of forest land to other land use categories (living and dead wood, litter and soil carbon pools) were introduced in 2011. Currently in forest land converted to other land use categories, living biomass, dead wood and litter are reported using

instant oxidation method. Estimation of conversion of land use from cropland to grassland was introduced in 2011 to represent land use changes associated with reduction of area of

cropland. Carbon stock changes are reported using research data demonstrating difference of carbon stock in cropland and grassland131.

Emissions of GHG due to forest fires in LULUCF sector in this report are calculated using

data about areas of forest fires provided by the State forest service (SFS).

This is the second year when Latvia reported harvested wood products (HWP) pool using data

which were obtained during elaboration of the Forest management reference level (FMRL).

The areas of IPCC land-use categories and Latvia's official land area are given in Table 6.1. Slight changes are applied to the whole cycle due to harmonization of the country area.

130

EUROSTAT – Forest Area and Forest Increment and Felling data sets. 131

Lazdiņš, Atbalsts Klimata Pētījumu Programmai (starpziņojums Par 2012. Gada Darba Uzdevumu Izpildi), Atbalsts Klimata Pētījumu Programmai (starpziņojums Par 2012. Gada Darba Uzdevumu Izpildi).


268

Table 6.1 Areas of IPCC land-use classes in 1990-2013, 1000 ha132

Year Total

country

area

Forest

land

Cropland Grassland Settlement

s

Wetland Other

land

1990 6 457.30 3 168.56 1 842.24 755.01 238.82 448.35 4.32

1991 6 457.30 3 174.97 1 837.27 752.97 239.41 448.35 4.32

1992 6 457.30 3 179.04 1 833.98 751.61 240.01 448.35 4.32

1993 6 457.30 3 185.57 1 828.93 749.53 240.60 448.35 4.32

1994 6 457.30 3 192.65 1 823.50 747.29 241.19 448.35 4.32

1995 6 457.30 3 200.04 1 817.85 744.96 241.78 448.35 4.32

1996 6 457.30 3 210.13 1 810.36 741.89 242.26 448.35 4.32

1997 6 457.30 3 220.12 1 802.95 738.84 242.73 448.35 4.32

1998 6 457.30 3 227.86 1 797.12 736.44 243.20 448.35 4.32

1999 6 457.30 3 238.67 1 789.13 733.16 243.67 448.35 4.32

2000 6 457.30 3 247.70 1 782.39 730.39 244.15 448.35 4.32

2001 6 457.30 3 259.79 1 773.20 726.61 245.04 448.35 4.32

2002 6 457.30 3 268.30 1 766.53 723.87 245.92 448.35 4.32

2003 6 457.30 3 277.47 1 759.41 720.94 246.81 448.35 4.32

2004 6 457.30 3 288.49 1 750.97 717.47 247.70 448.35 4.32

2005 6 457.30 3 299.88 1 742.26 713.90 248.59 448.35 4.32

2006 6 457.30 3 311.64 1 733.30 710.21 249.48 448.35 4.32

2007 6 457.30 3 323.77 1 724.07 706.43 250.36 448.35 4.32

2008 6 457.30 3 336.27 1 714.58 702.53 251.25 448.35 4.32

2009 6 457.30 3 334.13 1 714.93 701.68 253.82 448.42 4.32

2010 6 457.30 3 331.99 1 715.29 700.82 256.39 448.49 4.32

2011 6 457.30 3 329.85 1 715.64 699.96 258.96 448.56 4.32

2012 6 457.30 3 327.71 1 715.99 699.11 261.53 448.64 4.32

2013 6 457.30 3 325.58 1 716.34 698.25 264.10 448.71 4.32

Net emissions of aggregated GHG (CO2, CH4 and N2O) in LULUCF sector in 2013 were -147,78 Gg of CO2 equivalents (Table 6.2). Aggregated net removals of the GHG reduced by 98 % in 2013 compared to 1990.

Table 6.2 Summary of aggregated GHG emissions in 1990-2013, Gg CO2 eq. annually

Year Forest land Cropland Grassland Wetlands Settlements LULUCF

1990 -14385.35 3377.31 917.59 1247.34 109.82 -8899.5

1991 -15182.18 3412.00 888.42 1776.72 116.93 -9150.72

1992 -15565.73 3436.52 865.05 597.51 124.83 -10484.68

1993 -14819.68 3464.03 835.22 284.46 135.63 -9701.77

132

Based on the NFI data.


269

Year Forest land Cropland Grassland Wetlands Settlements LULUCF

1994 -15298.11 3488.27 803.48 417.59 143.59 -10541.56

1995 -13896.21 3511.42 771.29 427.19 153.42 -9505.9

1996 -13932.42 3197.11 735.25 410.84 124.76 -10153.82

1997 -11404.56 3198.21 699.24 460.11 130.43 -8487.72

1998 -10001.69 3198.54 670.7 358.63 138.51 -7608.42

1999 -6774.47 3201.69 631.15 812.74 146.18 -4288.19

2000 -9234.82 3199.41 598.41 584.93 153.19 -8899.5

2001 -10301.73 3167.98 555.72 666.62 307.31 -9150.72

2002 -9127.11 3163.43 525.03 1029.24 322.39 -10484.68

2003 -8506.64 3162.55 491.55 880.38 337.18 -9701.77

2004 -7096.53 3160.7 450.35 887.38 351.43 -10541.56

2005 -6903.03 3156.72 408.51 1120.34 365.79 -9505.9

2006 -8066.51 3152.14 370.82 1365.2 379.36 -10153.82

2007 -7545.16 3144.65 287.45 722.18 329.31 -8487.72

2008 -8591.46 3140.14 242.87 1106.28 344.05 -7608.42

2009 -4932.54 2893.26 233.62 981.13 870.77 -4288.19

2010 -2327.91 2870.71 223.29 1021.62 919.14 -7130.69

2011 -2529.6 2860.88 240.97 1023.4 956.06 511.94

2012 -3530.79 2851.2 258.73 991.1 1015.24 -416.84

2013 -3219.21 2841.21 274.54 1035.55 1058.67 -147.78

Area of organic soils in croplands and grasslands is updated according to the inventory of

historical data about farmlands implemented in 2009 133. Area of cropland and grassland in LULUCF reporting is synchronized with Agriculture reporting, including recalculation of cultivated organic soils. It is considered that all forest land, grassland, cropland and

settlements are managed. Detailed land use change matrices are provided in Table 6.4; summary – in Table 6.3.

Emissions from drained organic and mineral soils are calculated using default emission factors and national activity data. Information about area of drained mineral and organic soils in forest land is taken from the NFI (total area of forest types on drained soils).

Table 6.3 Summary of land use change matrix

Changes To

Forest land

To

Cropland

To

Grassland

To

Settlements

To

Wetland

To

Other land

1990 3 165.92 1 840.33 760.16 238.23 448.35 4.32

From Forest

land

20.91 0.00 23.71 0.00 0.00

From Cropland 0.00 146.65 0.84 0.00 0.00

From Grassland 204.28 0.00 12.70 0.00 0.00

133

L.U. Consulting, ―Augšņu un reljefa izejas datu sagatavošana un Eiropas Komisijas izstrādāto augsnes un reljefa kritēriju mazāk

labvēlīgo apvidu noteikšanai piemērošanas simulācija (Projekta kopsavilkuma ziņojums)‖ (Elaboration of soil and terrain data and simulation of application of the criteria elaborated by the European Commission for identification of less valuable regions (Summary of the project report)), Latvijas Republikas Zemkopības Ministrija, 2010.


270

Changes To

Forest land

To

Cropland

To

Grassland

To

Settlements

To

Wetland

To

Other land

From

Settlements

0.00 2.60 8.42 1.69 0.00

From Wetland 0.00 0.00 0.00 1.33 0.00

From Other land 0.00 0.00 0.00 0.00 0.00

2013 3 325.58 1 716.34 698.25 264.10 448.71 4.32

Table 6.4 Land use change matrix

Changes To

Forest land

To

Cropland

To

Grassland

To

Settlements

To

Wetland

To

Other land

Land use change 1989-1990

1989 3 165.92 1 840.33 760.16 238.23 448.35 4.32

From Forest

land

1.91 0.59

From Cropland 0.00

From Grassland 5.14

From

Settlements

From Wetland

From Other land


1990 3 168.56 1 842.24 755.01 238.82 448.35 4.32

From Forest

land

1.91 0.59

From Cropland 6.87

From Grassland 8.91

From

Settlements

From Wetland

From Other land


1991 3 174.97 1 837.27 752.97 239.41 448.35 4.32

From Forest

land

1.91 0.59

From Cropland 5.20

From Grassland 6.56

From

Settlements

From Wetland

From Other land



271

Changes To

Forest land

To

Cropland

To

Grassland

To

Settlements

To

Wetland

To

Other land

1992 3 179.04 1 833.98 751.61 240.01 448.35 4.32

From Forest

land

1.91 0.59

From Cropland 6.95

From Grassland 9.03

From

Settlements

From Wetland

From Other land


1993 3 185.57 1 828.93 749.53 240.60 448.35 4.32

From Forest

land

1.91 0.59

From Cropland 7.34

From Grassland 9.58

From

Settlements

From Wetland

From Other land

1994 3 192.65 1 823.50 747.29 241.19 448.35 4.32

From Forest

land

1.91 0.59

From Cropland 7.56

From Grassland 9.89

From

Settlements

From Wetland

From Other land


1995 3 200.04 1 817.85 744.96 241.78 448.35 4.32

From Forest

land

0.79 0.47

From Cropland 8.27

From Grassland 11.35

From

Settlements

From Wetland

From Other land


1996 3 210.13 1 810.36 741.89 242.26 448.35 4.32

From Forest 0.79 0.47


272

Changes To

Forest land

To

Cropland

To

Grassland

To

Settlements

To

Wetland

To

Other land

land

From Cropland 8.21


From

Settlements

From Wetland

From Other land


1997 3 220.12 1 802.95 738.84 242.73 448.35 4.32

From Forest

land

0.79 0.47

From Cropland 6.61

From Grassland 9.01

From

Settlements

From Wetland

From Other land


1998 3 227.86 1 797.12 736.44 243.20 448.35 4.32

From Forest

land

0.79 0.47

From Cropland 8.78


From

Settlements

From Wetland

From Other land


1999 3 238.67 1 789.13 733.16 243.67 448.35 4.32

From Forest

land

0.79 0.47

From Cropland 7.53


From

Settlements

From Wetland

From Other land


2000 3 247.70 1 782.39 730.39 244.15 448.35 4.32

From Forest

land

0.69 0.89


273

Changes To

Forest land

To

Cropland

To

Grassland

To

Settlements

To

Wetland

To

Other land

From Cropland 9.89


From

Settlements

From Wetland

From Other land


2001 3 259.79 1 773.20 726.61 245.04 448.35 4.32

From Forest

land

0.69 0.89

From Cropland 7.35


From

Settlements

From Wetland

From Other land


2002 3 268.30 1 766.53 723.87 245.92 448.35 4.32

From Forest

land

0.69 0.89

From Cropland 7.82


From

Settlements

From Wetland

From Other land


2003 3 277.47 1 759.41 720.94 246.81 448.35 4.32

From Forest

land

0.69 0.89

From Cropland 9.13


From

Settlements

From Wetland

From Other land


2004 3 288.49 1 750.97 717.47 247.70 448.35 4.32

From Forest

land

0.69 0.89

From Cropland 9.39


274

Changes To

Forest land

To

Cropland

To

Grassland

To

Settlements

To

Wetland

To

Other land


From

Settlements

From Wetland

From Other land


2005 3 299.88 1 742.26 713.90 248.59 448.35 4.32

From Forest

land

0.69 0.89

From Cropland 9.65


From

Settlements

From Wetland

From Other land


2006 3 311.64 1 733.30 710.21 249.48 448.35 4.32

From Forest

land

0.69 0.89

From Cropland 9.92


From

Settlements

From Wetland

From Other land


2007 3 323.77 1 724.07 706.43 250.36 448.35 4.32

From Forest

land

0.69 0.89

From Cropland 10.18


From

Settlements

From Wetland

From Other land


2008 3 336.27 1 714.58 702.53 251.25 448.35 4.32

From Forest

land

2.14

From Cropland 0.17

From Grassland 2.54


275

Changes To

Forest land

To

Cropland

To

Grassland

To

Settlements

To

Wetland

To

Other land

From

Settlements

0.52 1.68 0.34

From Wetland 0.27

From Other land


2009 3 334.13 1 714.93 701.68 253.82 448.42 4.32

From Forest

land

2.14

From Cropland 0.17

From Grassland 2.54

From

Settlements

0.52 1.68 0.34

From Wetland 0.27

From Other land


2010 3 331.99 1 715.29 700.82 256.39 448.49 4.32

From Forest

land

2.14

From Cropland 0.17

From Grassland 2.54

From

Settlements

0.52 1.68 0.34

From Wetland 0.27

From Other land


2011 3 329.85 1 715.64 699.96 258.96 448.56 4.32

From Forest

land

2.14

From Cropland 0.17

From Grassland 2.54

From

Settlements

0.52 1.68 0.34

From Wetland 0.27

From Other land


2012 3 327.71 1 715.99 699.11 261.53 448.64 4.32

From Forest

land

2.14

From Cropland 0.17

From Grassland 2.54

From 0.52 1.68 0.34


276

Changes To

Forest land

To

Cropland

To

Grassland

To

Settlements

To

Wetland

To

Other land

Settlements

From Wetland 0.27

From Other land

2013 3 325.58 1 716.34 698.25 264.10 448.71 4.32

CO2 emissions from mineral soil due to conversion of forest land to other land use categories are estimated using Equation 2.25 of the 2006 IPCC Guidelines. Research data134 were used to estimate carbon losses due to conversion from forest land to cropland on mineral soils; the

same factors of emission as for cropland on organic soil were used for converted organic soil. Default transition period of 20 years is assumed in calculations according to the 2006 IPCC

Guidelines, except for conversion of grassland to forest land, where two forest rotation periods (150 years) were considered. Data about carbon stock in soil and litter in forest soil are taken as averages from the results of international forest soil inventory project BioSoil135.

Average stock of dead wood in forests is estimated from the NFI database 136.

Knowledge about dynamics of dead wood in forest lands is insufficient, both in terms of

mortality factors and decay periods, because forest management principles were significantly changed since 1990, for instance, in the 80ths it was a common practice to debark stumps and to incinerate harvesting residues to reduce risk of distribution of pests. Nowadays this practice

is not used any more in state forests and in very limited amount – in private forests. Instead of that collection of residues for biofuel production becomes more common. Comparison of

different sources of information about dead wood (NFI and reports to the Timber Committee137) demonstrates constant increase of dead wood stock in forests during the last decade; however, it could be result of several extreme weather events. Mortality factors

excluding extreme events were elaborated in 2012 on the base of the NFI data (sample plots measured in 2006 and 2012) for the FMRL calculations 138.

Estimates of emissions from drained forest soils are supplemented with calculation of N 2O emissions from organic soils. Emissions of CO2 from drained organic soils are calculated using default emission factors of the IPCC Wetlands Supplement (2.6 tonnes C ha-1 annually

in forest land, 7.9 tonnes C ha-1 in cropland, 6.1 tonnes C ha-1 in grassland and 2.8 tonnes C ha-1 in peatlands).

The key categories in LULUCF sector in 2013 in Latvia are summarised in Table 6.5. The most significant key category is Forest land remaining forest land. Harvested wood products included into the inventory in 2013 are also a key category by level of net emissions.

134

Andis Lazdiņš et al., ―Temporary Carbon Stock Changes in Forest Soil in Latvia,‖ in Abstracts of International Baltic Sea Regional

Scientific Conference (presented at the Interdisciplinary Research for Higher Socioeconomic Value of Forests, Riga: LSFRI Silava, 2013), 51–52; Andis Lazdiņš, Arta Bārdule, and Jeļena Stola, ―Preliminary Results of Evaluation of Carbon Stock in Historical Cropland and Grassland,‖ in Abstracts of International Baltic Sea Regional Scientific Conference (presented at the Interdisciplinary Research for Higher Socioeconomic Value of Forests, Riga: LSFRI Silava, 2013), 56–57.

135 Arta Bārdule et al., ―Forest soil characteristic in Latvia according results of the demonstration project BioSoil (Latvijas meža augsņu

īpašību raksturojums demontrācijas projekta BioSoil rezultātu skatījumā),‖ Mežzinātne | Forest Science 20 (53) (2009): 105–124; Andis Lazdiņš et al., Mežsaimniecisko Darbību Ietekmes Uz Siltumnīcas Efektu Izraisošo Gāzu Bilanci Pētījuma Programmas Izstrāde Pārskats par pirmā etapa izpildi (Salaspils: LVMI Silava, 2010).

136 http://www.silava.lv/userfiles/file/2010%20nov%20MRM_visi%20mezi_04-08g.xls

137 FAO Forestry Department, Global forest resources assessment 2010. Country report - Latvia (Rome: Forestry Department, Food and

Agriculture Organization of the United Nations, 2010); FAO, State of the world’s forests 1997 (Rome: FAO, 1997); FAO Forestry Department, Global Forest Resources Assessment 2000, FAO Forestry Paper (Food and Agriculture Organization of the United

Nations, 2000). 138

Lazdiņš, Donis, and Strūve, Latvijas Meža Apsaimniekošanas Radītās Ogļskābās Gāzes (CO) Piesaistes Un Siltumnīcefekta Gāzu (SEG) Emisiju References Līmeņa Aprēķina Modeļa Izstrāde.

http://www.silava.lv/userfiles/file/2010%20nov%20MRM_visi%20mezi_04-08g.xls


277

Table 6.5 LULUCF key categories

No Key categories of emissions and removals GHG Identi fication criteria

level trend

1. 4.A.1 Forest Land Remain ing Forest Land CO2 X X

2. 4.A.2 Land Converted to Forest Land CO2 X X

3. 4.B.1 Cropland Remaining Cropland CO2 X X

4. 4.B.2 Land Converted to Cropland CO2 X X

5. 4.C.1 Grassland Remaining Grassland CO2 X

6. 4.C.2 Land Converted to Grassland CO2 X X

7. 4.D.1.1 Peat Extract ion Remaining Peat Extract ion CO2 X

8. 4.D.1.3 Other Wetlands Remain ing Other Wetlands CO2 X

9. 4.E.2 Land Converted to Settlements CO2 X X

10. 4.G Harvested Wood Products CO2 X X

11. 4(II). Emissions and removals from drainage and rewetting

and other management of organic and minera l soils

CO2 X X


and other management of organic and mineral soils

CH4 X X


and other management of organic and mineral soils

N2O X X

The sector reporting was considerably updated in 2013 due to development of national GHG reporting and projection tool for LULUCF sector and implementation of results of several

scientific studies. The most important improvements in this report are imp lementation of country specific wood density values, carbon stock in different fractions of biomass, BEFs, as

well as recalculation of losses due to commercial harvesting and natural mortality in forests. Gains and losses in living and dead biomass are reported for grassland and settlements, where NFI provides sufficient data to report dynamics of carbon stock in biomass.

6.2 LAND-USE DEFINITIONS AND THE CLASSIFICATION SYSTEMS USED AND THEIR CORRESPONDENCE TO THE LULUCF CATEGORIES

Forest is land of a minimum area of 0.1 ha with potential tree crown cover of more than 20 % and with the potential of trees to reach a minimum height of 5 m at maturity. The cropland refers to the area of arable land, including orchards and extensively managed arable lands.

The grassland category consists of lands used as pastures, as well as glades and bush- land which do not fit to forest definition, vegetated areas on non-forest lands complying to forest

definition where land use type can be easily switched back to grassland without legal requirement of transformation of the land use, but except grassland used in forage production and extensively managed cropland. Wetlands category includes all inland water bodies,

swamps and mires, flood- lands and alluvial lands.

The information about area of all land use categories since 2009 comes from the NFI.

Information about grassland, cropland, wetlands and other lands provided by the State land service (SLS) and Central statistical bureau (CSB) are used for reference – to estimate potential errors in the NFI data as well as to estimate the area of cropland and grassland in


278

1990. Conversion of cropland to grassland is estimated using remote sensing method comparing vegetation index in the NFI sample plots listed as cropland or grassland 139.

6.3 INFORMATION ON APPROACHES USED FOR REPRESENTING LAND

AREAS AND ON LAND-USE DATABASES USED FOR THE INVENTORY PREPARATION

Spatial approach is used to represent area of forest land, grassland, cropland, wetlands, settlements and other lands. Activity data are provided by the National forest inventory (NFI)140. Source data of the inventory (about 16000 plots representing 400 ha each) are used

in calculations of land use and land use changes, as well as drainage and rewetting of forest land. The NFI data are adopted to the harmonized country area for the whole reporting period

and to land use categories used in the GHG inventory. Two cycles of the NFI (2004-2008 and 2009-2013) are used in the GHG inventory.

Research data (LANDSAT images based remote sensing studies) are used to identify forest

and woody areas converted to cropland to settlement as well as extensively managed croplands, like organic farms, where considerable area of arable land is set aside for a longer

time period and can be reported by the NFI teams as grassland or forest land, depending from structure of vegetation.

Land use changes since completion of the 2nd NFI cycle are reported on the base of the field

measurement data; however, 10 years transition period is applied to the measurement data (described in details in Table 9.24 for conversions of cropland and grassland) to avoid

overestimation of the land use changes, especially in farmlands and due to conversion to forest land and conversion of forest land.

Summary of land use changes (change of the land use code in the NFI database) according to

comparison of the 1st and 2nd NFI cycle is shown in Table 6.6.

Table 6.6 Summary of land use changes according to the NFI data

Status Initial

land use

Final land use Total

cropland settlement

s

forest wetlands grassland

Uncertain

areas

cropland 4 345 84 653 88 998

settlement

s

8 950 8 950

forest 8 782 8 197 37 482 54 461

wetlands 132 11 722 3 033 14 887

grassland 145 511 55 561 5 433 206 506

Total 154 425 80 578 13 631 125 168 373 802

Land use

changes

2009-2013

cropland 836 836

settlement

s

2 596 1 686 8 420 12 702

forest 10 689 10 689

wetlands 1 329 1 329

grassland 12 701 12 701

Total 2 596 25 555 1 686 8 420 38 257

139

Lazdiņš and Zariņš, Vēsturiskās (1990. Gada) Apsaimniekoto Aramzemju Platības Noteikšana Un Līdz 2009. Gadam Notikušo Aramzemju Platības Izmaiņu Novērtēšana.

140 Source –

http://www.silava.lv/userfiles/file/Meza%20statistiska%20inventarizacija/Kopsavilkumi%202014%20I%20cikls%20(2).xlsx; http://www.silava.lv/userfiles/file/Meza%20statistiska%20inventarizacija/Kopsavilkumi%202014%20II%20cikls%20(2).xlsx


279

6.4 DIRECT N2O EMISSIONS FROM MANAGED SOILS (CRF 4 (IV))


Direct N2O emissions from drainage of organic soils are estimated for forest lands, croplands, grasslands, settlements and wetlands land-use categories. Direct N2O emissions

corresponding to land-use change from N mineralisation associated with loss of soil organic matter from change of land use or management are estimated for land-use change to croplands

and settlements on mineral soils.


databases used for the inventory preparation

Information on approaches used for representing land areas and on land-use databases used for the inventory preparation are described in following chapters characterizing land use

changes.

6.4.3 Land-use definitions and the classification systems used and their

correspondence to the LULUCF categories

Land use definitions described in following chapters on forest land, cropland, grass land, settlement and wetland are used.


Direct emissions of N2O due to drainage of organic soils are calculated according equation No. 1 (Equation 2.7 of the IPCC Wetlands Supplement).

N 2 O−N OS=[(FOS,CG,Temp⋅EF 2CG,Temp)+(F OS,F,Temp,NR⋅EF 2F,Temp,NR)] ;where

N 2 O−N OS=Annual direct N 2 O−N emissions frommanaged /drained organic soil ,

kg N 2 O−N yr−1

FOS= Annual areaof managed /drained organic soils , ha.The subscripts CG , F ,Temp , NR

refer tocropland and grassland , forest land ,temperate and nutrient rich ,respectively.

EF 2=Emission factor for N 2 O emissions fromdrained /managed organic soils ,

kg N 2 O – N ha−1

yr−1

(1)

Activity data consist of areas of land remaining in a land-use category and land converted to other land-use category on drained organic soils. Data of annual area of drained organic soil

are taken from the NFI. Default N2O emission factors for drained organic soils are shown in Table 6.7 according Table 2.5 of the IPCC Wetlands Supplement.

Table 6.7 Tier 1 N2O emission/removal factors for drained organic soils in all land-use categories

Land-use category Climate/

vegetation zones

Emission factor (kg

N2O-N ha-1

yr-1

)

95% Confidence interval

Forest land, drained Temperate 2.8 -0.57 6.1

Cropland, drained Boreal and

temperate

13 8.2 18

Grassland, deep-

drained, nutrient-

rich

Temperate 8.2 4.9 11

Peatland managed

for ext raction

Boreal and

temperate

0.3 -0.03 0.64


280

N2O emissions from land converted to another land-use category on drained organic soils are calculated in the same way as emissions from land remaining in a land-use category.

Direct N2O emissions from N inputs to managed soils and from N mineralisation resulted

from loss of soil organic C stocks in mineral soils due to land-use change are estimated by Tier 1 methodology using equation No. 2 (equation 11.1 of 2006 IPCC Guidelines):

N 2 O−N N inputs=F SOM∗EF1 ; where

N 2 O−N N inputs−annual direct N 2 O−N emissions fromN inputs tomanaged

soils , kg N 2 O−N yr−1

EF1−emission factor for N mineralised frommineral soil asa result of loss

of soil carbon ,kg N 2 O−N (kg N )−1

(2)

The equation No. 2 is supplemented by equation 11.8 from 2006 IPCC Guidelines (equation

No.4 in the NIR). Default emission factor for N mineralised from mineral soil as a result of loss of soil carbon (0.01 kg N2O-N (kg N)-1) from table 11.1 is used. For estimation of annual amount of N mineralised in mineral soils as a result of loss of soil carbon due to land use

change to cropland default C:N ratio (15) for soil organic matter from 2006 IPCC Guidelines is utilized. As there is no fixed default emission factors for settlements provided by IPCC

guidelines, default emission factors of croplands land-use category are applied, C:N ratio for soil organic matter applied based on expert judgement is 15, and annual carbon losses in organic soil in settlements are reported using emissions factor from cropland – 5 tonnes C ha-

1 yearly (2006 IPCC Guidelines), assuming that peat is not completely removed during the conversion.

6.4.5 Uncertainties and time-series consistency

Uncertainty of soil nitrogen (N2O) emissions are estimated according to data obtained within

the scope of the international forest soil monitoring project BioSoil and values provided in the 2006 IPCC Guidelines. Uncertainty ranges of emission factors for N2O emissions from

drained organic are listed in Table 9.7.

Uncertainty range of emission factor for N mineralised from mineral soil as a result of loss of soil carbon is 0.003-0.03 kg N2O-N (kg N)-1. Uncertainty range of C:N ratio of the soil

organic matter for land-use change is 10-30.

6.4.6 Category-specific QA/QC and verification

QA/QC procedures include double check of area affected by the land use change and soil CO 2

emissions – under calculation of land use changes and during calculation of N2O emissions.

6.4.7 Category-specific recalculations

In previous inventory direct N2O emissions from mineral soil due to land use category changes were not estimated, no recalculations are done. Recalculations for N2O emissions

from drained organic soils are based on changes in methodology due to implementation of the IPCC Wetlands Supplement.

6.4.8 Category-specific planned improvements

N2O emissions might be considerable part of emissions from wetlands, therefore, it is

necessary to develop method for estimation impact of drainage on N2O emissions, and it is important to be able to separate wetlands on organic soils (high N2O emissions) and mineral

soils (low N2O emissions).


281

6.5 INDIRECT N2O EMISSIONS FROM MANAGED SOILS (CRF 4 (IV))


Indirect N2O emissions corresponding to land-use change from N mineralisation associated with loss of soil organic matter from change of land use or management are estimated for

land-use change to croplands and settlements on mineral soils.



Information on approaches used for representing land areas and on land-use databases used for the inventory preparation are described in fo llowing chapters characterizing land use

changes.



Land use definitions described in following chapters on forest land, cropland, grassland, settlement and wetland are used.


Indirect N2O emissions corresponding to land-use change from N mineralisation associated with loss of soil organic matter from change of land use or management are estimated for

land-use change to croplands and settlements on mineral soils. Indirect N2O emissions from organic soils are not calculated, because 2006 IPCC Guidelines does not include such a methodology.

Indirect N2O emissions from land use change to cropland are calculated according to 2006 IPCC Guidelines. Amount of N2O-N emissions produced from leaching and run-off as a result

from land use change to cropland are estimated by Tier 1 methodology using equation 11.10 (equation No. 3 in the NIR).

N 2 O(L)−N =F SOM∗FracLEACH-H∗EF5 ;where

N 2 O(L)−N−annual amount of N 2 O−N produced from leaching and runoff

of N additions to managed soils where leaching/runoff occurs , kg N2O−N yr

−1

FracLEACH-( H)− fraction of all N added to/mineralised in managed soils in

regions where leaching/runoff occurs that is lost through leaching and runoff ,

kg N (kg of N additions)−1

EF5−emission factor for N 2 O emissions from leaching and runoff,

kg N 2 O−N (kg N leached and runoff)−1

)

(3)

It is supplemented by equation 11.8 from 2006 IPCC Guidelines (equation No. 4 in the NIR).

icmatteresoilorganNratioofth:CR

tonnesCusetype,orlandoilcarbonfuallossofsaverageannΔC

N. kg ,management or use land in chenge throught carbon soilof loss of

result a as soilsmineral in dmineralise N of amount annual net theF

where1000;R

1ΔC=F

Mineral

SOM

MineralSOM

(4)

For estimation of annual amount of N mineralised in mineral soils as a result of leaching/run-

off associated with loss of soil carbon through land use change to cropland, default C:N ratio (15) for soil organic matter from 2006 IPCC Guidelines is utilized. Carbon losses are


282

calculated according to the Tier 1 method of the 2006 IPCC Guidelines. Default values of fraction of all N added to/mineralised in managed soils due to leaching and run-off (0.3 kg N (kg of N additions)-1) and emission factor for N2O emissions from N leaching and run-off

(0.0075 kg N2O-N (kg N leached and run-off)-1) are taken from table 11.3 of 2006 IPCC Guidelines.

Indirect N2O emissions from land use change to settlements are also reported using the 2006 IPCC Guidelines Tier 1 method. Amount of N2O-N emissions produced from leaching and run-off as a result from land use change to settlements are estimated by Tier 1 methodology

using equation 11.10 supplemented by equation 11.8 from 2006 IPCC Guidelines. For estimation of annual amount of N mineralised in mineral soils as a result of leaching/run-off

associated with loss of soil carbon thorough land use change to settlements, C:N ratio 15 for soil organic matter based on expert judgement is utilized. Tier 1 method of the 2006 IPCC Guidelines (loss of 20 % of soil carbon in land converted to settlement) is used to

estimate carbon stock changes. Default values of fraction of all N added to mineralised in managed soils due to leaching and run-off (0.3 kg N (kg of N additions)-1) and emission factor

for N2O emissions from N leaching and run-off (0.0075 kg N2O-N (kg N leached and run-off)-1) are taken from table 11.3 of 2006 IPCC Guidelines.


Uncertainty range of C:N ratio of the soil organic matter for land-use change from Forest

Land or Grassland to Cropland is 10-30 %. Uncertainty range of fraction of all N added to/mineralised in managed soils in regions where leaching/run-off occurs that is lost through

leaching a run-off is 0.1-0.8 kg N (kg of N additions-1). Uncertainty range of emission factor for N2O emissions from N leaching and run-off according to 2006 IPCC Guidelines is 0.0005-0.025 kg N2O-N (kg N leached and run-off-1).


QA/QC procedures include double check of area affected by the land use change and soil CO 2 emissions – under calculation of land use changes and during calculation of N2O emissions.


In previous inventory indirect N2O were not estimated, no recalculations are done.


Information on land use changes, particularly, d istribution of organic and mineral soil and losses of carbon due to land use changes should be estimated. Country specific C/N ratio will be introduced after completion of the agriculture soil monitoring project141.

6.6 FOREST LAND (CRF 4.A)


There are 2 key source and sink categories in forest land in Latvia – CO2 in Forest Land

remaining Forest Land and CO2 in Land converted to Forest Land, excluding 3 key source categories (CO2, CH4 and N2O) under Emissions and removals from drainage and rewetting

141

EEA grants program funded Project No. 2014/88 Augsnes oglekļa krājumu novērtēšana aramzemē un pļavās (Evaluation of soil carbon stock in perennial grassland and cropland).


283

and other management of organic and mineral soils which are now evaluated separately in the CRF reporter.

The estimation of the area of forest land is based on the NFI142. Forest Land is divided in two

categories: forest land remaining forest land and land converted to forest land. Removals and emissions are reported in the category forest land remaining forest and land converted to

forest. The calculation is done separately for land remaining forest land and converted to forest more than 20 years ago.

The NFI and research data are used to estimate time series for areas and gross increment.

Mortality data are calculated on the base of the NFI data and mortality factors, considering linear correlation between the modelled mortality in 2009-2013 and actual mortality data for

the whole period143. Distinction between forest land remaining forest land and areas converted to forest land is made according to the age of dominant species in forests on afforested land – if age of dominant species was less than zero in 1990, it is considered as land converted to

forest, in other cases it is considered as forest land remaining forest land.

Carbon stock changes in above and below ground living and dead biomass are reported in the

submission. Decay factor for dead wood including harvesting residues not incinerated on-site is considered 20 years. Changes of organic carbon in litter and soil organic matter in naturally dry and wet soils are assumed to be zero according to research data on carbon stock in forest

soil in 2006 and 2012144.

Carbon stock changes are reported separately on naturally dry and wet mineral and organic

soils and drained mineral and organic soils. Soils are considered organic as defined in the NFI: a soil is classified as organic if the organic layer (H horizon) is at least 20 cm deep. Distribution of the forest site types according to the NFI is shown in Table 6.8.Conversion of

forest stands on drained mineral or organic soil to naturally wet soil is reported as rewetting.

Table 6.8 Distribution of drained, naturally dry and wet mineral and organic soils in Latvia's forests

Year Forest at the

end of year,

1000 ha

Forest on

dry mineral

soils, 1000

ha

Forest on

drained

mineral

soils, 1000

ha

Forest on

wet mineral

soils, 1000

ha

Forest on

drained

organic

soils, 1000

ha

Forest on

wet organic

soils, 1000

ha

1990 3168.56 1544.29 611.32 306.77 433.1 273.08

1991 3174.97 1550.65 611.88 306.52 433.06 272.86

1992 3179.04 1554.98 612.41 306.27 432.73 272.65

1993 3185.57 1560.74 613.29 306.37 432.74 272.43

1994 3192.65 1567.39 614.52 306.12 432.39 272.22

1995 3200.04 1573.42 615.97 305.88 432.76 272

1996 3210.13 1581.21 617.16 306.87 433.1 271.79

1997 3220.12 1590.35 617.98 307.01 433.1 271.68

1998 3227.86 1597.29 618.49 307.23 433.28 271.57

1999 3238.67 1608.33 618.65 307.11 433.12 271.46

2000 3247.7 1616.28 619.45 307.68 432.94 271.35

2001 3259.79 1627 620.99 307.44 433.11 271.24

2002 3268.3 1634.31 621.69 307.64 433.56 271.11

2003 3277.47 1643.24 621.73 307.49 434.04 270.97

2004 3288.49 1653.57 623.59 307.36 433.15 270.83

2005 3299.88 1664.12 624.51 307.38 433.18 270.7

2006 3311.64 1675.05 625.41 307.4 433.22 270.56

142

http://www.silava.lv/userfiles/file/2010%20nov%20MRM_visi%20mezi_04-08g.xls 143

Lazdiņš, Donis, and Strūve, Latvijas Meža Apsaimniekošanas Radītās Ogļskābās Gāzes (CO2) Piesaistes Un Siltumnīcefekta Gāzu (SEG) Emisiju References Līmeņa Aprēķina Modeļa Izstrāde (Elaboration of calculation model for evaluation of GHG emissions and

CO2 removals due to forest management). 144

Lazdiņš et al., ―Temporary Carbon Stock Changes in Forest Soil in Latvia‖; Lazdiņš et al., Mežsaimniecisko Darbību Ietekmes Uz Siltumnīcefekta Gāzu Emisijām Un CO₂ Piesaisti Novērtējums (pārskats Par 2012. Gada Darba Uzdevumu Izpildi).


284

Year Forest at the

end of year,

1000 ha

Forest on

dry mineral

soils, 1000

ha

Forest on

drained

mineral

soils, 1000

ha

Forest on

wet mineral

soils, 1000

ha

Forest on

drained

organic

soils, 1000

ha

Forest on

wet organic

soils, 1000

ha

2007 3323.77 1686.33 626.32 307.43 433.27 270.42

2008 3336.27 1697.98 627.22 307.46 433.32 270.29

2009 3334.13 1689.52 643.64 304.39 436.65 259.92

2010 3331.99 1681.05 660.06 301.33 439.99 249.55

2011 3329.85 1672.59 676.48 298.26 443.33 239.19

2012 3327.71 1664.13 692.9 295.2 446.67 228.82

2013 3325.58 1655.66 709.32 292.13 450.01 218.45

The carbon stock change in living biomass is estimated with the default method of the 2006 IPCC Guidelines – carbon uptake and release of the living biomass correspond to the mean gross annual increment of forest growing stock, annual harvesting of trees and decay due to

natural mortality.

Considerable part of non-CO2 emissions is associated with incineration of harvesting residues

in clear-cuts. The activity data for this calculation was based on an outdated study until 2010145. Now a questionnaire for private forest owners on utilization of harvesting residues is used146. According to this questionnaire in 2005-2009 about 7 % of residues were left for

incineration and in 2010-2013 – 4.13 % of the residues were incinerated.

The time series for annual increment of growing stock of trees on a forest land remaining

forest are given in Table 6.9 and in the land converted to forest – in Table 6.10.

The total drain of trees is very much affected by commercial felling. The demand for timber products was low at the beginning of the 1990s; therefore, felling was also at a low level and

the carbon stock of trees was high. The felling stock increased during 1990s and reached top average in early 2000s. Updated figures147 of felling, including biofuel gathering, are shown

in Table 6.11.

The Land converted to forest land provides relatively small net increment of growing stock of trees – about 0.22 mill. m3 in 2013. Taking into account that these forests are generally young

stands, no emissions from commercial felling are considered. Areas afforested 20 years ago (in 1990-1993) are reported under the forest land remaining forest land category.

Table 6.9 Annual increment of growing stock of trees on the forest land remaining forest, 1000 m3

Year Aspen Grey alder

Birch Spruce Black alder

Oak, ash Other Pine Total

1990 3736.61 2062.14 7854.37 4071.82 1690.34 285.14 539.04 6434.72 26674.17

1991 3733.66 2060.51 7848.16 4068.6 1689 284.92 538.61 6429.64 26653.1

1992 3730.7 2058.88 7841.96 4065.38 1687.67 284.69 538.18 6424.56 26632.03

1993 3727.75 2057.25 7835.75 4062.17 1686.33 284.47 537.76 6419.47 26610.96

1994 3810.81 2218.59 7983.41 4658.27 1851.8 292.3 477.45 6487.57 27780.2

1995 3807.79 2216.83 7977.08 4654.58 1850.34 292.07 477.07 6482.43 27758.19

1996 3806.27 2215.94 7973.89 4652.72 1849.6 291.95 476.88 6479.83 27747.07

1997 3804.74 2215.05 7970.69 4650.85 1848.85 291.84 476.69 6477.23 27735.95

1998 3803.22 2214.16 7967.5 4648.99 1848.11 291.72 476.5 6474.64 27724.83

1999 3426.18 2283.12 7858.19 5390.23 1891.66 279.41 461.49 6668.29 28258.56

2000 3424.81 2282.2 7855.04 5388.07 1890.9 279.3 461.3 6665.61 28247.22

2001 3423.09 2281.06 7851.1 5385.36 1889.96 279.15 461.07 6662.27 28233.05

2002 3421.37 2279.91 7847.15 5382.66 1889.01 279.01 460.84 6658.92 28218.88

2003 3419.65 2278.76 7843.21 5379.95 1888.06 278.87 460.61 6655.58 28204.7

145

Leonards Līpiņš, ―Assessment of wood resources and efficiency of wood utilization (Koksnes izejvielu resersu un to izmantošan as efektivitātes novērtējums)‖ (LLU, 2004), http://www.zm.gov.lv/index.php?sadala=258&id=803.

146 Lazdiņš, A., Lazdiņa, D., 2013. Meža ugunsgrēku un mežizstrādes atlieku dedzināšanas radītās siltumnīcefekta gāzu emisijas Latvijā

(Greenhouse gas emissions in Latvia due to incineration of harvest ing residues and forest fires), in: Referātu Tēzes. Presented at the Latvijas Universitātes 71. zinātniskā konference ―Ģeogrāfija, ģeoloģija, vides zinātne‖, Latvijas Universitāte, Rīga, pp. 133–137.

147 Values updated according to results of the second NFI cycle.


285

Year Aspen Grey

alder

Birch Spruce Black

alder

Oak, ash Other Pine Total

2004 2366.58 2420.19 6836.27 5250.14 1495.14 301.54 377.78 7573.02 26620.68

2005 2365.39 2418.97 6832.84 5247.5 1494.39 301.39 377.59 7569.21 26607.3

2006 2364.2 2417.76 6829.4 5244.86 1493.64 301.24 377.4 7565.4 26593.91

2007 2363.01 2416.54 6825.96 5242.22 1492.89 301.09 377.22 7561.6 26580.53

2008 2361.82 2415.32 6822.52 5239.58 1492.14 300.94 377.03 7557.79 26567.14

2009 2716.12 2170.11 6518.1 5318.52 1537.02 387.98 234.48 6363.69 25246.02

2010 2718.73 2172.19 6524.35 5323.62 1538.5 388.35 234.7 6369.8 25270.25

2011 2724.61 2176.89 6538.46 5335.14 1541.83 389.19 235.21 6383.58 25324.9

2012 2728.45 2179.96 6547.68 5342.66 1544 389.74 235.54 6392.58 25360.6

2013 2734.43 2184.74 6562.04 5354.38 1547.39 390.6 236.06 6406.6 25416.23

Table 6.10 Increment of growing stock of timber on the Land converted to forest148

Year Net increment, m³ Stem biomass,

1000 tonnes

Crown biomass,

1000 tonnes

Below-ground

biomass, 1000

tonnes

Total biomass,

1000 tonnes

1990 136.26 0.06 0.02 0.02 0.09

1991 591.29 0.24 0.07 0.08 0.39

1992 1411.27 0.58 0.18 0.18 0.94

1993 2695.88 1.11 0.34 0.35 1.8

1994 4534.9 1.86 0.58 0.59 3.03

1995 7000.64 2.87 0.9 0.91 4.68

1996 10188.99 4.18 1.31 1.32 6.81

1997 14169.39 5.82 1.82 1.83 9.47

1998 18937.42 7.77 2.43 2.45 12.65

1999 24587.02 10.06 3.22 3.2 16.48

2000 31143.82 12.74 4.08 4.06 20.88

2001 38721.87 15.84 5.08 5.05 25.96

2002 47310.79 19.35 6.2 6.17 31.72

2003 56931.64 23.28 7.46 7.42 38.17

2004 67663.64 27.47 8.96 8.83 45.26

2005 79574.63 32.31 10.54 10.38 53.23

2006 92725.06 37.65 12.28 12.1 62.03

2007 107173.99 43.51 14.2 13.98 71.69

2008 122980.02 49.93 16.29 16.04 82.27

2009 139819.05 56.82 18.68 18.28 93.78

2010 157508.09 64.01 21.04 20.59 105.64

2011 175955.85 71.5 23.5 23 118.01

2012 195099.01 79.28 26.06 25.51 130.85

2013 214889.12 87.32 28.71 28.09 144.12

Table 6.11 Updated figures of harvesting stock, in 1000 m3

Year Total excluding

deforestation

Aspen Grey

alder

Birch Spruce Black

alder

Oak,

ash

Other Pine

1990 6297.55 568.35 405.01 1827.46 1355.42 109.19 24.32 0.01 2007.79

1991 5531.97 499.26 355.78 1605.3 1190.64 95.92 21.36 0.01 1763.71

1992 5056.33 456.33 325.19 1467.27 1088.27 87.67 19.53 0.01 1612.06

1993 5991.69 540.75 385.34 1738.7 1289.59 103.89 23.14 0.01 1910.28

1994 7217 651.33 464.15 2094.27 1553.31 125.13 27.87 0.01 2300.93

1995 8672.69 782.71 557.77 2516.69 1866.62 150.37 33.49 0.01 2765.04

1996 8519.11 768.85 547.89 2472.12 1833.56 147.71 32.9 0.01 2716.07

1997 11239.43 1014.36 722.84 3261.52 2419.05 194.88 43.41 0.01 3583.36

1998 12632.65 1140.1 812.44 3665.81 2718.91 219.03 48.79 0.02 4027.55

1999 16925.69 1527.54 1088.54 4911.59 3642.9 293.47 65.36 0.02 5396.26

2000 13855.7 1269.63 666.58 4099.53 3867.38 0 50.45 0 3902.15

2001 13037.03 1235.76 593.86 3613.68 3394.98 233.06 34.57 0 3931.13

2002 14090.92 1399.42 816.16 3979.92 3512.58 223.99 40.51 0 4118.34

2003 14599.66 1473.65 996.39 3944.79 3300.02 231.89 48.93 0 4604

2004 13542.74 1282.88 1075.65 3795.57 2934.95 246.67 45.72 0 4161.3

2005 14209.18 847.32 839.85 3597.28 3705.24 261.3 83.08 0 4875.1

148

Andis Lazdiņš and Juris Zariņš, ―Elaboration and integration into National greenhouse gas inventory report matrices of land use changes of areas belonging to Kyoto protocol article 3.3 and 3.4 activities (Report on research work contracted by the Ministry of Environment of republic of Latvia)‖ (LVMI Silava, 2010).


286

Year Total excluding

deforestation

Aspen Grey

alder

Birch Spruce Black

alder

Oak,

ash

Other Pine

2006 12340.08 1180.35 860.65 3561.31 2380.31 255.29 52.55 0 4049.62

2007 12752.59 1178.77 1076.25 3854.25 2548.87 254.88 64.54 0.19 3774.86

2008 11287.94 990.28 894.22 3294.99 1982.87 256.93 46.12 0 3822.53

2009 13512.24 1214 767.53 3959.2 2155.57 254.86 55.14 0 5105.93

2010 16349.84 1424.07 1036.82 5710.6 2397.14 374.76 56.47 0 5349.99

2011 16021.22 1427.85 1247.55 4373.28 2738.8 280.85 83.37 10.64 5858.88

2012 14769.69 1170.11 4402.3 1257.07 2372.49 219.03 57.44 10.81 5280.43

2013 14685.05 1188.45 4311.92 1305.46 2413.89 285.54 76.3 9.63 5093.86

The aggregated net emissions from forest land remaining forest were -3615.14 Gg of CO2 eq.

in Latvia in 2013 (Figure 6.1), excluding removals in harvested wood products and emissions from drainage and rewetting of organic soils (respectively -2141.52 and 764.12 Gg CO2, Table 6.17. The most of the emissions are associated with commercial felling. The net

emissions from land converted to forest excluding emissions from drainage and rewetting of organic soils in 2013 were -368.19 Gg CO2 eq. (Figure 6.2). Total emissions from forest lands,

excluding harvested wood products in 2013 were -3219.21 Gg CO2 eq. (Figure 6.3).

Figure 6.1 GHG emissions in forest land remaining forest

Figure 6.2 GHG emissions in land converted to forest


287

Figure 6.3 Summary of GHG emissions in forest land

In case of on-site incineration of harvesting residues during commercial harvesting, all emissions also are applied to the forest land remaining forest land category, because no

commercial felling takes place in young stands (younger than 20 years) on land converted to forest land.



Forest land area and deforested area was estimated in 2009 using remote sensing approach –

vegetation index were estimated in all the NFI points, including those outside forest lands in satellite image (LANDSAT) series from 1990, 1995 and 2000 to identify points where vegetation index permanently changed from values characteristic for forest lands to the one's

characteristic for settlements, grassland and cropland.

Source data are provided by the NFI. The same rules are applied to the forest land remaining

forest and land converted to forest. The last category is identified by the age of dominant tree species in the NFI category afforested lands – if age of the stand was above zero in 1990, it is reported under the Forest land remaining forest category, and otherwise it stays in the

converted land category. Recalculation of age of forest marked as forests growing on farmlands is the reason, why area of managed forest increased since 1990. The total area of

the Land converted to forest is shown in Table 6.12 and Table 6.13. In 2010 it start to reduce, because area afforested in 1990-1993 in the convention reporting is reported under the forest land remaining forest land category.

Table 6.12 Total area of the land converted to forest

Year Land converted

to forest at the

end of year,

1000 ha

forest on dry

mineral soils,

1000 ha

forest on

drained mineral

soils, 1000 ha

forest on wet

mineral soils,

1000 ha

forest on

drained organic

soils, 1000 ha

1990 5.14 3.77 0.67 0.35 0.35

1991 14.06 11.34 1.71 0.35 0.66

1992 20.62 16.89 2.72 0.35 0.66

1993 29.65 23.87 4.08 0.69 1.01

1994 39.23 31.73 5.8 0.69 1.01

1995 49.12 38.98 7.73 0.69 1.72


288

Year Land converted

to forest at the

end of year,

1000 ha

forest on dry

mineral soils,

1000 ha

forest on

drained mineral

soils, 1000 ha

forest on wet

mineral soils,

1000 ha

forest on

drained organic

soils, 1000 ha

1996 60.47 47.98 9.4 0.69 2.4

1997 71.72 57.74 10.46 0.95 2.57

1998 80.73 65.29 11.22 1.29 2.93

1999 92.8 76.95 11.62 1.29 2.94

2000 103.09 85.51 12.66 1.99 2.93

2001 116.76 96.84 14.45 2.19 3.28

2002 126.85 104.92 15.45 2.54 3.94

2003 137.6 114.62 15.8 2.54 4.63

2004 150.2 125.72 17.96 2.56 3.95

2005 163.16 137.04 19.18 2.74 4.2

2006 176.5 148.73 20.39 2.92 4.46

2007 190.21 160.78 21.6 3.1 4.73

2008 204.28 173.2 22.81 3.28 4.99

2009 204.28 173.2 22.81 3.28 4.99

2010 199.14 169.43 22.14 2.93 4.64

2011 190.22 161.86 21.1 2.93 4.33

2012 183.66 156.31 20.09 2.93 4.33

2013 174.63 149.33 18.73 2.59 3.98

Table 6.13 Area of the land converted to forest more than 20 years ago

Year Land

converted to

forest > 20

years ago,

1000 ha

forest on dry

mineral soils,

1000 ha

forest on

drained

mineral soils,

1000 ha

forest on wet

mineral soils,

1000 ha

forest on

drained

organic soils,

1000 ha

2010 5.14 3.77 0.67 0.35 0.35

2011 14.06 11.34 1.71 0.35 0.66

2012 20.62 16.89 2.72 0.35 0.66

2013 29.65 23.87 4.08 0.69 1.01



Forest under LULUCF reporting is land of a minimum area of 0.1 ha with potential tree crown cover of more than 20 % and with the potential of trees to reach a minimum height of

5 m at maturity. Young natural stands and all plantations established for the forestry purposes, which have to reach a crown density of 20 % or tree height of 5 m are considered under forest

land; as well as the areas normally forming part of the forest area, which are temporarily unstocked as a result of human intervention or natural causes, but which are expected to revert to forest. For linear formations, a minimum width of 20 m is applied. Area estimates are

derived from the NFI data149.

149

http://www.silava.lv/userfiles/file/2010%20nov%20MRM_visi%20mezi_04-08g.xls


289


6.6.4.1 Forest land remaining forest land

Calculations of carbon stock changes and GHG emissions in forest lands are based on activity

data provided by the NFI (area, living biomass and dead wood) and Level I forest monitoring data (soil organic carbon). National statistics (State forest service) are used to estimate forest fires and commercial felling related emissions and removals. The calculation of GHG

emissions and CO2 removals in historical forest lands is based mainly on research report ―Elaboration of the model for calculation of the CO2 removals and GHG emissions due to

forest management‖150 and factors and coefficients elaborated within the scope of the research program on impact of forest management on GHG emissions and CO2 removals151.

Changes of the carbon stock and GHG emissions are estimated according to the Tier 2

methods with country specific data. Default method (the carbon loss to be subtracted from the carbon removals for the reporting year) is used in calculations of removals and emissions of

CO2 in living biomass.

Methodologies for estimation of carbon stock changes and GHG emissions are considerably improved; they are now merged together into the ―Forest data modelling tool‖, which is

complex spreadsheet. Separate versions (with different input data) are elaborated for the UNFCCC and the Kyoto protocol reporting. In future these tools will be merged to simplify

calculations. The tool is still under development, current working version can be downloaded from the website ―Land use, land use change and forestry sector in Latvia‖152.

The concept of the ―Forest data modelling tool‖:

land use and land use change data are elaborated separately to simplify tool structure, the connection is organized as linked tables;

main input data – area under different growth and management conditions, species composition, gross annual increment, mortality per area, harvesting rate and species composition and others;

calculations are done on annual basis using periodic (5 years period) and annual input data;

historical data (1990-2004) – backward calculation on the base of the NFI data; for 1970-1989 research data and expert judgements are utilized;

all modules in the spreadsheet are merged together following to the forest management cycle (from growth to decay);

the tool combines all land use and land use change categories.

Content of the tool (separate calculation sheets):

living biomass (annual increment of living biomass, summary of growing stock and characteristics of biomass);

mortality (natural reduction of number of living trees, estimation of decay of harvesting residues, calculation of dynamics of carbon stock in dead biomass);

150

Lazdiņš, A., Donis, J., Strūve, L., 2012. Latvijas meža apsaimniekošanas radītās ogļskābās gāzes (CO2) piesaistes un siltumnīcefekta gāzu (SEG) emisiju references līmeņa aprēķina modeļa izstrāde (Elaboration of the model for calculation of the CO2 removals and

GHG emissions due to forest management) ( No. 5.5-9.1-0070-101-12-91). LVMI Silava, Salaspils. Lazdiņš, A., Donis, J., Strūve, L., 2012b. Latvia’s national methodology for reference level of forest management activities (English summary).

151 Lazdiņš et al., Mežsaimniecisko Darbību Ietekmes Uz Siltumnīcefekta Gāzu Emisijām Un CO₂ Piesaisti Novērtējums (pārskats Par

2013. Gada Darba Uzdevumu Izpildi). 152

https://sites.google.com/site/lvlulucf/activity/nir-1990-2011/Meza%20apsaimniekosana%20%28FMRL%2020120730%29.ods?attredirects=0&d=1


290

commercial harvesting (input to the harvested wood products, losses in above-ground and below-ground biomass);

harvested wood products (carbon stock change in locally originated and consumed harvested wood products);

emissions from soils (CO2, CH4 and N2O from drained organic soils and CH4, DOC,

CO2 emissions from rewetted soils in forest land and wetlands);

fire (emissions of CO2, CH4 and N2O due to incineration of harvesting residues and

wildfires);

conversion from forests (as a land use change to estimate area of managed forests);

afforestation (carbon stock change in living biomass, dead wood and litter);

cropland (emissions from soil, carbon stock change in living and dead biomass);

grassland (emissions from soil, carbon stock change in living and dead biomass,

wildfires);

conversion of farmland (emissions or removals in soil);

settlements (carbon stock change in soil, living and dead biomass);

managed wetlands (emissions from soil, carbon stock change in living and dead

biomass).

Module for estimation of the gross annual increment of living biomass:

increment figures on the base of the NFI (Table 6.14);

historical recalculations (before 2004) were done together with mortality rate (Table 6.18) estimations in 2011 and 2012 153;

species, age of stands and dimensions specific gross increment equations for the most common tree species (values specific for birch are used for other tree species);

species specific wood densities (Table 6.15) different BEFs (Table 6.16);

average carbon stock in biomass is provided in Table 6.17.

Table 6.14 Average periodic gross increment of living trees (m3 ha- 1 yr)

Species 1970-1993 1994-1998 1999-2003 2004-2008 2009-2013

Aspen 15.96 16.33 14.72 10.19 10.76

Grey alder 7.04 7.60 7.84 8.33 7.16

Birch 8.64 8.81 8.69 7.58 7.38

Spruce 7.44 8.54 9.91 9.67 9.30

Black alder 10.77 11.84 12.12 9.60 8.56

Oak, ash 6.30 6.48 6.21 6.71 6.25

Other species 8.74 7.77 7.53 6.18 6.28

Pine 7.00 7.08 7.30 8.30 7.56

153

Jānis Donis, Latvijas Meža Resursu Ilgtspējīgas, Ekonomiski Pamatotas Izmantošanas Un Prognozēšanas Modeļu Izstrāde (Salaspils:

LVMI Silava, 2011), http://www.zm.gov.lv/doc_upl/MAF2011_S82.pdf; Lazdiņš, Donis, and Strūve, Latvijas Meža Apsaimniekošanas Radītās Ogļskābās Gāzes (CO2) Piesaistes Un Siltumnīcefekta Gāzu (SEG) Emisiju References Līmeņa Aprēķina Modeļa Izstrāde.


291

Table 6.15 Wood density154

Species Density, tonnes m-3

Aspen 0.40

Grey alder 0.41

Birch 0.47

Spruce 0.36

Black alder 0.41

Oak, ash 0.41

Other s pecies (mostly Salix sp.) 0.41

Pine 0.38

Table 6.16 Coefficients for calculation of above ground biomass from stem biomass155

Species Stem biomass to crown biomass Stem biomass to below-ground biomass

Aspen 1.22 0.28

Grey alder 1.45 0.34

Birch 1.19 0.29

Spruce 1.58 0.43

Black alder 1.45 0.28

Oak, ash 1.45 0.18

Other s pecies 1.45 0.27

Pine 1.27 0.31

Table 6.17 Average carbon stock in living biomass156

Species C, kg in tonne of dry biomass157

Aspen 508

Grey alder 522

Birch 521

Spruce 528

Black alder 522

Oak, ash 522

Other s pecies 522

Pine 531

Mortality and decay:

species specific coefficients of mortality (Table 6.18) not dependant on size of tree

(dominant or undergrowth trees), depend on the age of stand and average dimensions of trees;

calculations on the base of NFI using backward calculation for 5 years period, assuming equal rate of commercial thinning in the 90ths;

20 years decomposition period (mortality since 1970 considered as emissions);

constant mortality values considered for periods before 1990.

Table 6.18 Average periodic mortality (m3 ha

-1 yr.)

158

Species 1970-1993 1994-1998 1999-2003 2004-2008 2009-2013

Aspen 1.64 1.95 1.97 1.92 2.44

Grey alder 0.3 0.33 0.36 0.48 2.16

Birch 1.59 1.67 1.58 1.43 1.8

Spruce 1.61 1.76 1.94 2.05 2.49

154

Lazdiņš et al., Mežsaimniecisko Darbību Ietekmes Uz Siltumnīcefekta Gāzu Emisijām Un CO₂ Piesaisti Novērtējums (pārskats Par 2013. Gada Darba Uzdevumu Izpildi).

155 Ibid.

156 Ibid.

157 Dried at 105

oC temperature.

158 Lazdiņš et al., Mežsaimniecisko Darbību Ietekmes Uz Siltumnīcefekta Gāzu Emisijām Un CO₂ Piesaisti Novērtējums (pārskats Par

2013. Gada Darba Uzdevumu Izpildi); Lazdiņš, Donis, and Strūve, Latvijas Meža Apsaimniekošanas Radītās Ogļskābās Gāzes (CO) Piesaistes Un Siltumnīcefekta Gāzu (SEG) Emisiju References Līmeņa Aprēķina Modeļa Izstrāde.


292

Species 1970-1993 1994-1998 1999-2003 2004-2008 2009-2013

Black alder 1.3 1.42 1.47 1.64 2.14

Oak, ash 2.29 2.66 2.67 2.87 4.01

Other species 0.75 0.66 0.67 0.77 2.31

Pine 1.16 1.24 1.38 1.48 1.38

Commercial felling:

dominant species specific harvesting data since 1970 (1990-2011 Central statistical bureau, 1970-1989 research papers159);

decomposition of crown and underground biomass – 20 years; species specific wood densities and different BEFs for coniferous and deciduous trees (Table 6.15 and Table

6.16).

The methodology for harvested wood products is based on Rüter, S., 2011 160. More detailed description follows in further chapters.

Emissions from drained soils are reported – 2.6 tonnes C ha-1 and 2.8 kg N2O-N ha-1 (IPCC Wetlands Supplement) annually from organic soils.

Methodology for calculation of emissions due to wildfires and incineration of harvesting residues is described in following chapters. Incineration of harvesting residues is going down in Latvia and in 2012-2014 LSFRI Silava had opportunity to collect information about

incineration of harvesting residues in private forests. According to results of the questionnaire about 15 % of harvesting residues were left for incineration in 2005-2009 in private forests

and 7 % in 2010-2013. In state forests, that contribute to about 50 % of harvesting stock no harvesting residues are left for incineration.

Area of organic soils in the forest lands is reported according to structure of distribution of the

forest stand types. Total area of organic soils as well as total area of forests were updated according to research data on land use structure according to the NFI161.

New project is implemented in 2014 to estimate carbon stock change in organic forest soil due to establishment of drainage system162. The empiric material is collected in experimental trials established in early 60ths. According to the study results no soil carbon losses take place due

to drainage of organic soil in comparison to naturally wet site; however, more experimental data are necessary to extrapolate these results to the whole area of Latvia.

Drained organic soil in forest land is source of CH4 emissions. CH4 emissions are calculated by equation 2.6 in IPCC Wetlands Supplement (equation No. 5 in the NIR).

CH 4_organic=A∗((1−Frac ditch)∗EF CH _4_land +Fracditch∗EFCH _4_ditch); where

CH 4_organic−annual CH 4 loss fromdrained organic soils , kgCH 4 yr−1

A− land area of drained organic soils ina land−use category , ha

EFCH _ 4_land−emission factor for direct CH 4 emissions fromdrained organic

soils , kgCH 4 ha−1

yr−1

EFCH _ 4_ditch

−emission factor for CH4emissions fromdrainage ditches ,kg CH

4ha

−1yr

−1

Fracditch− fraction of the total area of drained organic soil which is ocupied by ditches(5)

159

Zigurds Saliņš, Mežs - Latvijas Nacionālā Bagātība (Jelgava: Jelgavas tipogrāfija, 2002); Zigurds Saliņš, Meža izmantošana Latvijā: stāvoklis, perspektīvas (Jelgava [Latvia]: LLU Meza izmantosanas katedra, 1999).

160 Projection of Net Emissions from Harvested Wood Products in European Countries, Johann Heinrich von Thünen Institute, Hamburg.

161 Lazdiņš and Zariņš, ―Elaboration and integration into National greenhouse gas inventory report matrices of land use changes of areas

belonging to Kyoto protocol article 3.3 and 3.4 activities (Report on research work contracted by the Ministry of Environment of republic of Latvia).‖

162 Andis Lazdiņš, Aldis Butlers, and Ainārs Lupiķis, ―Case Study of Soil Carbon Stock Changes in Drained and Afforested Transitional

Bog,‖ in Foresst Ecosystems and Its Management: Towards Understanding the Complexity (presented at the 9th Baltic theriological conference, Ilgas: Latvian State Forest Research Institute ―Silava,‖ 2014); Andis Lazdiņš and Ainārs Lupiķis, Hidrotehniskās Meliorācijas Ietekme Uz CO Emisijām Mežaudzēs Uz Susinātām Augsnēm (Salaspils, 2014), Salaspils.


293

The CH4 emission factor for organic soils of drained forest land (table 2.3 and table 2.4 in the IPCC Wetlands Supplement) is 2.5 kg CH4 ha-1 yr-1 and emission factor for drainage ditches is 217 kg CH4 ha-1 yr-1. Data for fraction of drainage ditches of total drained area on organic

soils is obtained by evaluation fraction of ditches in state managed forest lands to all drained forest organic soils.

GHG emissions from rewetted organic soils are estimated according to the Tier 1 methods. CO2 emissions are calculated using equation 3.3:

CO2−C rewetted org soil=CO2−Ccomposite+CO 2−C DOC ; where

CO2−C rewetted org soil−CO2−C emissions/ removals fromrewetted organic soils , tonnesC yr−1

CO2−Ccomposite−CO 2−C emissions /removals fromthe soil and non−treevegetation ,

tonnesC yr−1

CO2−C DOC−off −site CO2−C emissions fromdissolved organic carbonexported

fromrewetted organic soils ,tonnes C yr−1

(6)

complemented by equations 3.4 and 3.5 of the IPCC Wetlands Supplement.

CO2−C composite=∑c ,n

(A∗EFCO 2); where

Ac,n−areaof rewetted organic soils∈climate zone c and nitrient status n ,ha

EFCO2c,n

−CO2−C emission factor for rewetted organic soils in climate zonec ,nutrient status n ,

tonnes C ha−1

yr−1

(7)

CO2−C DOC=∑c

(A∗EF DOC_REWETTED); where

Ac−areaof rewetted organic soils in climate zone c , ha

EFDOC_rewetted, c

−CO2−C emission factor fromDOC exported fromrewetted organic soils

in climate zone c ,tonnes C ha−1

yr−1

(8)

Emission factors for CO2-C (0.5 tonnes CO2-C ha-1 yr-1) and DOC (0.24 tonnes

CO2-C ha-1 yr-1) are taken from tables 3.1 and 3.2 of the IPCC Wetlands Supplement. N2O emissions from rewetted organic soils according to Tier 1 method are assumed to be negligible and are not estimated, CH4 emissions are calculated applying Tier 1 method using

equation 3.7 of the IPCC IPCC Wetlands Supplement (equation No. 9). Default emission factor (216 kg CH4-C ha-1 yr-1) from table 3.3 was used (Table 6.19).

CH 4−C rewetted org soil =

∑c,n

(A∗EFCH 4 soil)c ,n

1000; where

CH 4−C rewetted org soil−CH 4−C emissions /removals fromrewetted organic soils , tonnes C yr−1

Ac,n−area of rewetted organic soilsin climate zone c and nutrient status n ,ha

EFCH 4 soil

−emission factor fromrewetted organic soils in climate zone c and nutrient status n ,

kg CH4−C ha

−1yr

−1

(9)

Table 6.19 Emission factors for rewetted organic soils, tonnes C ha-1

yr-1

No GHG Emission factor

1 CO2 0.5

2 CH4 0.216

Rewetting is reported under forest land – conversion of forests on drained organic soils to forest on naturally wet soil. The conversion is usually approved by changes in ground vegetation and groundwater table during the site visits. Total rewetted area according to

comparison of the NFI data is 10 kha. It is assumed, that the rewetting was linear and 2 kha of forests were rewetted every year from 2009 to 2013. Total emissions due to rewetting in 2013

approached to 100 Gg CO2 eq. (Figure 6.4).


294

Figure 6.4 Emissions due to rewetting

6.6.4.2 Land converted to forest land

In section lands converted to forest land all categories except grasslands converted to forest land are noted as NO because other conversions do not take place in practice. Grasslands

converted to forest land are estimated using spatial approach – analysis of the NFI data about forests on former farmland (land being cropland and grassland before 1990) which was afforested after 1990. Areas where trees did not reach 2 cm diameter at breast height were

excluded from estimation and reported under grassland category to avoid reporting of extensively managed farmlands under forest land category. The year of afforestation of every

single NFI plot selected for analysis was determined by subtraction of age of stand fro m a year when field measurements were done.

Gains in living biomass on afforested lands are estimated using interpolation (stock change

method assuming that the increment structure in areas afforested in different periods is similar)163. Weighted average wood density for a particular year in forest land remaining

forest is used to convert stem volume to biomass. Similarly, average carbon stock in living biomass and BEFs characteristic for particular year were applied to calculation. 2015 is the second year, when, both, carbon stock change in living biomass in land remaining forest and

land converted to forest is calculated using Tier 2 method.

Losses of living biomass in afforested lands are noted as NO because no commercial felling

takes place in these stands (the smallest commercially and legally valuable harvesting age is 30 years for grey alder).

Emissions from organic soils in afforested lands were calculated using the same approach as

for emissions from drained organic soils on lands remaining forest.

This is the second year when dead wood and litter are reported as sink categories in afforested

lands. It is assumed that average stock of dead wood, and consequently in litter in historical forest lands and afforested lands becomes equal at certain stand age. The assumption is based on the NFI field measurements considering that increment of the dead wood stock in

163

L.U. Consulting, ―Augšņu un reljefa izejas datu sagatavošana un Eiropas Komisijas izstrādāto augsnes un reljefa kritēriju mazā

labvēlīgo apvidu noteikšanai piemērošanas simulācija (Projekta kopsavilkuma ziņojums)‖ (Elaboration of soil and terrain data and simulation of application of the criteria elaborated by the European Commission for identification of less valuable regions (Summary of the project report)), Latvijas Republikas Zemkopības Ministrija, 2010.


295

afforested areas will follow linear regression and will reach values characteristic for the forest land within 150 years.

It is assumed in the calculation, that dead wood stock in afforested lands will reach

1.1 tonnes C ha-1 within 150 years. Values of average carbon stock in dead wood in 1990-2013 were used in calculation. Similarly, weighted average above-ground and below-ground

biomass expansion factors and carbon content in living biomass for a particular year obtained in living biomass calculations are used to convert stem biomass to the total biomass.

Average carbon stock in litter is 12.1 tonnes C ha-1 according to the BioSoil project forest soil

inventory data164. Considering the same transformation period of 150 years, average increment of carbon stock in the litter carbon pool is 0.08 tonnes C ha-1.

No removals in soil are reported due to conversion to forest land, because there are no scientific evidences of increase of carbon stock in soil after afforestation. The project started in 2012 on comparison of carbon stock in historical cropland and grassland shows no

difference in carbon stock between grassland, recently afforest land and historical forest land in the upper soil layer (0-40 cm)165; however, there are evidences of statistically significant

carbon stock changes in deeper soils layers after afforestation166.


Uncertainties are estimated on the base the NFI and expert judgement. Uncertainty of soil carbon (CO2) emissions are estimated according to data obtained within the scope of the

international forest soil monitoring project BioSoil and values provided in the IPCC Wetlands Supplement. The uncertainty of CO2 emission factor according to IPCC guidelines in organic

soil is 90 %.

The uncertainty of area (Table 6.20) is estimated as standard error of proportion (equation No. 10).

Table 6.20 Uncertainty of the forest land use data in 2013

Land use category Number of NFI

plots

Share of NFI

plots

Standard error

of proportion

Forest land 8322 52% 2%

forest land remaining forest land 7885 49% 2%

drained organic soil 1116 7% 6%

land converted to forest land 437 3% 9%

drained organic soil 10 - 72%

Uncertainty of annual increment of growing stock of trees in forest lands is 0.9 %, uncertainty of increment on afforested lands 16 %. Uncertainties calculated according to 2006

IPCC Guidelines, Volume 1, Chapter 3 as twice the relative standard error. For harvesting stock, uncertainty according to forest regulations is 10 %. BEFs utilized in calculations

according to expert judgement have uncertainty level of 0.9-2.0 % for different species, 0.8 % in average according to the study results. Combined category uncertainty is calculated according to 2006 IPCC Guidelines TIER 1 – SIMPLE PROPAGATION OF ERRORS.

164 Bārdule et al., ―Forest soil characteristic in Latvia according results of the demonstration project BioSoil (Latvijas meža augsņu

īpašību raksturojums demontrācijas projekta BioSoil rezultātu skatījumā).‖ 165 Andis Lazdiņš, Atbalsts Klimata Pētījumu Programmai (starpziņojums Par 2012. Gada Darba Uzdevumu Izpildi) (Salaspils: LVMI

Silava, 2012), https://sites.google.com/site/lvlulucf/research-projects/atbalstsklimatapetijumuprogrammaistarpzinojumspar2012gadarezultatiem.

166 R. Kasparinskis et al., ―Long term impact of afforestation on soil morphology and properties, Lauksaimniecības zemju apmežošanās ilgtermiņa ietekme uz augsnes morfoloģiju un īpašībām,‖ Forest science no. 24(57) p. 17–40 (2011), http://agris.fao.org/agris-search/search/display.do?f=2012%2FLV%2FLv1203.xml%3BLV2012000112.


296

95 % confidence interval for CH4 emission factor for drained organic soil of forest land is 0.6-5.7 kg CH4 ha-1 yr-1. Uncertainty range of CH4 emission factor for drainage ditches in drained forest land is 41-393 kg CH4 ha-1 yr-1.

Uncertainty range of CO2-C emission factor for rewetted organic soils is -0.71-+1.71 tonnes CO2-C ha-1 yr-1. Uncertainty range of CO2-C emission factor from DOC exported from

rewetted organic soils is 0.14-0.36 tonnes CO2-C ha-1 yr-1. 95% range of CH4-C emission factor from rewetted organic soils is 0-856 kg CH4-C ha-1 yr-1.


Quality control procedures listed in 2006 IPCC Guidelines Chapter 4.4.3 were implemented

for all calculations, including elaboration of country specific BEFs, wood density and carbon content factors.

The NFI data have gone through the following QC measures:

field gauges and instruments were checked and calibrated;

new instruments were tested to find possible differences in measurement results

compared with the old ones;

before field surveying, field personnel has had a training period to ascertain that

observers are able to use the equipment correctly, that observers do measurements and classifications correctly and that the guidelines and instructions are understood

correctly;

verification measurements were carried out during field seasons;

field data are checked by evaluation if all sample plots are measured, no required information is missing (if missing entries are found, they are completed and re-

measurement is done, if necessary), the compatibility between data variables is checked using logical controls;

calculated results are compared with the results of previous inventories. If

considerable or unexpected changes are found, reasons for the changes were clarified and explained.

Work on improvement of tree height and timber equations used in calculations in the NFI and development of verification tools continues therefore changes in the input data provided by

the NFI are possible.

The NFI team applies quality guidelines and QA/QC measures to the all work stages. Documentation is in Latvian with brief descriptions of NFI methods and measurements in

English167.

The data based on forest statistics were produced by the LSFRI Silava 168. Data descriptions

are available including the applied definitions, methods of data compilation, reliability and comparability. It was confirmed that all data used in this section cover whole land area of Latvia.

167

Zemkopības ministrija, ―Meža statistiskās inventarizācijas veikšanas un mežaudzes sekundāro parametru aprēķināšanas metodika (instrukcija Nr. 10 no 17.03.2004.)‖ (Latvijas Republikas Zemkopības ministrija, 2004),https://sites.google.com/site/lvlulucf/literature/MSI_metodika_Instrukcija_%282004%29.pdf?attredirects=0&d=1; LSFRI

Silava, ―Methods utilized to recalculate historical forest increment data‖ (LSFRI Silava, 2007), https://sites.google.com/site/lvlulucf/literature/Recalculationsofhystoricalremovals2007.pdf?attredirects=0&d=1.

168 http://www.silava.lv/userfiles/file/2010%20nov%20MRM_visi%20mezi_04-08g.xls


297


The major improvement of the inventory was the application of updated country specific information on annual increment, mortality and felling stock. Major changes are also applied to the inventory due to conversion to the 2006 IPCC Guidelines in calculations, like indirect

N2O emissions and GHG emissions due to rewetting. Minor changes are introduced in calculations of GHG emissions due to incineration of biomass. Land use and land use changes

are recalculated according to results of the 2nd NFI cycle.


The most important planned improvements:

estimation of decay period for dead wood (harvesting residues and below-ground

biomass, planned to complete until report 1990-2014);

estimation of carbon stock changes in drained organic soils in forest lands (2015);

estimation of transition period for dead wood and litter carbon stock in afforested lands (2015-2018);

development of production version of EPIM tool, including instantaneous calculation of uncertainties, broader representation of land use change options and closer

integration of Kyoto protocol and the UNFCCC reporting;

improvement and simplification of structure of land use change calculation tool,

including uncertainty estimates.

6.7 CROPLAND (CRF 4.B)

6.7.1 Cropland remaining cropland (4.B.1)


Cropland remaining cropland is a key source category of CO2 emissions. Under the cropland's category emissions from organic soils (CO2, N2O and CH4), living and dead woody biomass

(CO2) are reported. Net aggregated emissions from cropland remaining cropland were 2567.26 Gg of CO2 eq. in 2013 (excluding 117.75 Gg of CO2 eq. emissions from drained

organic soils, Figure 6.5.


298

Figure 6.5 Summary of GHG emissions in cropland remaining cropland

The total area of croplands is estimated using the approach described further in chapter

Category-specific recalculations and following to research results. Updated values split into cropland remaining cropland and cropland converted less and more than 20 years ago are

shown in Table 6.21.

There is statistically significant increase of volume of growing stock of trees in cropland. In previous reports it was not included in calculations because of too high uncertainties of the

increment. After completion of the 2nd round of the NFI, the stock change method can be applied to characterize biomass of living trees in cropland on the base of stock changes during

5 years period.

Table 6.21 Area of Cropland

Cropland, 1000

ha

Land remaining cropland Land converted to cropland

organic soil other soils organic soil other soils

1990 1842.2 95.3 1745.0 0.3 1.7

1991 1837.3 95.3 1738.1 0.5 3.3

1992 1834.0 95.0 1733.3 0.8 4.9

1993 1828.9 94.7 1726.6 1.0 6.6

1994 1823.5 94.3 1719.6 1.3 8.2

1995 1817.9 94.0 1712.4 1.6 9.9

1996 1810.4 93.6 1704.6 1.7 10.6

1997 1803.0 93.1 1696.8 1.8 11.2

1998 1797.1 92.7 1690.6 1.9 11.9

1999 1789.1 92.4 1682.2 2.0 12.6

2000 1782.4 91.9 1675.1 2.1 13.3

2001 1773.2 91.5 1665.6 2.2 13.9

2002 1766.5 91.0 1658.8 2.3 14.5

2003 1759.4 90.6 1651.3 2.4 15.1

2004 1751.0 90.2 1642.6 2.5 15.7

2005 1742.3 89.8 1633.7 2.6 16.3

2006 1733.3 89.3 1624.5 2.7 16.9

2007 1724.1 88.8 1615.1 2.8 17.5

2008 1714.6 88.3 1605.4 2.9 18.1

2009 1714.9 87.7 1605.8 2.9 18.6

2010 1715.3 87.7 1607.5 2.6 17.4

2011 1715.6 88.0 1609.0 2.3 16.3

2012 1716.0 88.2 1610.5 2.1 15.2

2013 1716.3 89.0 1612.0 1.8 14.1


299

6.7.1.2 Information on approaches used for representing land areas and on land-use


Remote sensing (LANDSAT satellite image analysis) based research data 169 are used to update cropland area based on frequency of changes of vegetation index and characterization

of the particular piece of land in other databases. Area of cropland considerab ly increased and area of grasslands decreased, when research data were applied, in comparison to the original

NFI data, because extensively managed farmlands (biological farms and grassland utilized in forage production) are reported under cropland category as well as lands, which at least once per 10 years have value of vegetation index typical for cropland.

6.7.1.3 Land-use definitions and the classification systems used and their correspondence to the LULUCF categories

The cropland refers to the area of arable land, including orchards and extensively managed arable lands. The area is reported by the NFI and updated by the remote sensing based

research data. Information provided by the Central statistical bureau (CSB) and Rural development service (RDS) is used to evaluate modelling results and assumptions utilized in the NFI data analysis. The total area of farmland (cropland and grassland) is equal according

to the NFI and RDS, but share of cropland is higher in recalculated NFI data, because of the extensively managed arable land. Cropland also includes animal feeding glades, which

according to national land use classification belong to forest land.


Activity data for calculations are provided by research project170 (area of organic soils). Area of land remaining cropland is estimated using remote sensing based research data 171 on the base of

the NFI. Area of organic soils in farmland according to summaries of land surveys is

5.18 ± 0.5 %. This value characterizes area of cropland before 1990, because it is based on field measurements completed in 60ths, 70ths and early 80ths. It is assumed that share of organic

soil in cropland remaining cropland, cropland converted to grassland, grassland converted to cropland and grassland remaining grassland is equal. Minor changes are introduced by conversion of forest land on organic soil to cropland and grassland. Therefore, the area of

organic soil in cropland is linearly correlating with the total area of cropland. In 2013 according to this estimation there were 88.48 kha of organic soil in cropland remaining

cropland and 1.82 kha in land converted to cropland. The study data on distribution of organic

169

Lazdiņš, A. (2011). Harmonization of land use matrix in Latvia according to requirements of international greenhouse gas reporting system - extending outputs of National Forest inventory program. Proceedings of 6th Internationasl Scientific Conference Students

on Their Way to Science, Jelgava, Maj 27 2011. p 10. Jelgava: Latvia University of Agriculture, Faculty of Social Sciences, Faculty of Engineering, Forest Faculty; Lazdiņš, A., Āboliņa, L., Zariņš, J., Jansons, J., Razma, Ģ. & Donis, J. (2010). Mežu zemes izmantošanas maiņas matricas izstrādāšana un integrēšanu nacionālajā siltumnīcefekta gāzu inventarizācijas pārskatā par Kioto

protokola 3.3 un 3.4 pantā minētajiem pasākumiem . Salaspils; Lazdiņš, A. & Zariņš, J. (2010). Elaboration and integration into National greenhouse gas inventory report matrices of land use changes of areas belonging to Kyoto protocol article 3.3 and 3.4 activities (Report on research work contracted by the Ministry of Environment of republic of Latvia). LVMI Silava; Lazdiņš, A. & Zariņš, J. (2012). Vēsturiskās (1990. gada) apsaimniekoto aramzemju platības noteikšana un līdz 2009. gadam notikušo aramzemju

platības izmaiņu novērtēšana. Salaspils. (2/27.01); Lazdiņš and Zariņš, Vēsturiskās (1990. Gada) Apsaimniekoto Aramzemju Platības Noteikšana Un Līdz 2009. Gadam Notikušo Aramzemju Platības Izmaiņu Novērtēšana; Lazdiņš et al., Atbalsts Klimata Pētījumu Programmai (Pārksats Par Projekta 2013. Gada Darba Uzdevumu Izpildi); Lazdiņš and Čugunovs, Oglekļa Dioksīda (CO) Piesaistes Un Siltumnīcefekta Gāzu (SEG) Emisiju Un Zemes Lietojuma Veida Ietekmes Novērtējums Intensīvi Un Ekstensīvi

Kultivētās Aramzemēs, Daudzgadīgos Zālājos Un Bioloģiski Vērtīgos Zālājos. 170

L.U. Consulting, ―Augšņu un reljefa izejas datu sagatavošana un eiropas komisijas izstrādāto augsnes un reljefa kritēriju mazā labvēlīgo apvidu noteikšanai piemērošanas simulācija (Projekta kopsavilkuma ziņojums).‖

171 Lazdiņš and Čugunovs, Oglekļa Dioksīda (CO) Piesaistes Un Siltumnīcefekta Gāzu (SEG) Emisiju Un Zemes Lietojuma Veida

Ietekmes Novērtējums Intensīvi Un Ekstensīvi Kultivētās Aramzemēs, Daudzgadīgos Zālājos Un Bioloģiski Vērtīgos Zālājos; Lazdiņš and Zariņš, Vēsturiskās (1990. Gada) Apsaimniekoto Aramzemju Platības Noteikšana Un Līdz 2009. Gadam Notikušo Aramzemju Platības Izmaiņu Novērtēšana.


300

soil show that only about 2.2 % of farmlands are located on organic soil, including 1.0 % of cropland and 2.9 % of grassland; however, this study does not demonstrate, what are the driving forces of reduction of area of cropland on organic soil – if it is land use change or

decomposition of organic layer driven phenomena172.

Carbon stock change in living and dead woody biomass is based on activity data provided by

the NFI. The biomass increment is used in calculations before 2009 and stock change method is applied for calculations in 2009-2013 assuming linear increment of carbon stock in cropland. Carbon stock in living and dead biomass is calculated using the same coefficients as

in calculations of carbon stock changes in forested land. All conversion factors for estimation of carbon in biomass are developed domestically173.

Net carbon stock changes in mineral soil in cropland are reported as not occurring because no significant changes in management systems took place since 1990 and according to Tier 1 method of the 2006 IPCC Guidelines Chapter 5174 the carbon stock changes in mineral soil

should be reported in case of changes in management practice.

The assumptions used in EPIM tool for estimation of carbon stock change in living and dead

biomass are shown in Table 6.22, default 20 years decay period is considered for dead wood.

Table 6.22 Assumptions for calculation of carbon stock changes in living and dead biomass in cropland

Year Cropland

with

woody

vegetation,

1000 ha

Gross increment of

living biomass

Wood

density,

kg m¯³

Natural

mortalit

y, m³

ha¯¹

BEFs Carbon

content,

kg ton-1

mill. m³ m³ ha¯¹ stem to

crown

stem to

below-

ground

1990 2.34 0.01 2.52 0.41 0.48 0.31 0.31 523

1991 2.34 0.01 2.52 0.41 0.48 0.31 0.31 523

1992 2.34 0.01 2.52 0.41 0.48 0.31 0.31 523

1993 2.34 0.01 2.52 0.41 0.48 0.31 0.31 523

1994 2.65 0.01 2.52 0.41 0.49 0.31 0.32 523

1995 2.65 0.01 2.52 0.41 0.49 0.31 0.32 523

1996 2.65 0.01 2.52 0.41 0.49 0.31 0.32 523

1997 2.65 0.01 2.52 0.41 0.49 0.31 0.32 523

1998 2.65 0.01 2.52 0.41 0.49 0.31 0.32 523

1999 2.65 0.01 2.52 0.41 0.5 0.32 0.32 523

2000 2.65 0.01 2.52 0.41 0.5 0.32 0.32 523

2001 2.65 0.01 2.52 0.41 0.5 0.32 0.32 523

2002 2.65 0.01 2.52 0.41 0.5 0.32 0.32 523

2003 2.65 0.01 2.52 0.41 0.5 0.32 0.32 523

2004 2.65 0.01 2.52 0.41 0.54 0.33 0.32 524

2005 2.65 0.01 2.52 0.41 0.54 0.33 0.32 524

2006 2.65 0.01 2.52 0.41 0.54 0.33 0.32 524

2007 1.45 0.01 6.19 0.41 1.34 0.33 0.32 524

2008 1.45 0.01 6.19 0.41 1.34 0.33 0.32 524

2009 1.45 0.01 6.19 0.41 1.42 0.33 0.32 524

2010 1.45 0.01 6.19 0.41 1.42 0.33 0.32 524

2011 1.45 0.01 6.19 0.41 1.42 0.33 0.32 524

2012 1.46 0.01 6.1 0.41 1.4 0.33 0.32 524

2013 1.46 0.01 6.19 0.41 1.82 0.33 0.32 524

CO2 emissions from drained organic soils in croplands were calculated using IPCC Wetlands Supplement Tier 1 method. Emission factor – 7.9 tonnes C ha-1 annually.

172

Lazdiņš et al., Atbalsts Klimata Pētījumu Programmai (Pārksats Par Projekta 2013. Gada Darba Uzdevumu Izpildi). 173

Andis Lazdiņš et al., Mežsaimniecisko Darbību Ietekmes Uz Siltumnīcefekta Gāzu Emisijām Un CO₂ Piesaisti Novērtējums (pārskats Par 2013. Gada Darba Uzdevumu Izpildi) (Salaspils, 2013), Salaspils.

174 Section 5.2.3.1 Choice of Method, Tier 1.


301

Drained organic soil in cropland is source of CH4 emissions. CH4 emissions are calculated by equation 2.6 in the IPCC Wetlands Supplement. The emission factor for organic soils (table 2.3 and table 2.4 in the IPCC Wetlands Supplement) is 0±2.8 kg CH4 ha-1 yr-1 (cropland,

drained) and emission factor for drainage ditches 1165±830 kg CH4 ha-1 yr-1 (deep – drained cropland); respectively, only CH4 emissions from ditches are calculated. Drainage systems on

organic soils are considered. Area of ditches is considered equally proportional to area of drained organic soil in cropland. High resolution satellite images were used to estimate coverage of ditches in organic soils – 30 randomly selected drainage systems overlapping

with former or current peat extraction sites (Figure 6.6) and obtained value (0.3 km ha-1) was extrapolated to all organic soils.

Figure 6.6 Sample area used to estimate area of ditches in organic soils

6.7.1.5 Uncertainties and time-series consistency

Uncertainty of area estimates is provided in Table 6.23.

Table 6.23 Uncertainty of the cropland use data in 2013


plots

Share of NFI

plots

Standard error

of proportion

Cropland 4295 27% 3%

cropland remaining cropland 4255 26% 3%

organic soil 221 1% 13%

land converted to cropland 40 0% 32%


The uncertainty of CO2 emission factor for organic soil is determined according to the IPCC Wetlands Supplement. According to Table 5.5 of the 2006 IPCC Guidelines the uncertainty of impact factor for different management practices applied in croplands is 12 % for long term

cultivating. No uncertainty is considered for full tillage and medium input (impact factor – 1). Uncertainty of CH4 emission factor for drainage ditches is 0.81 % (Table 2.4 in the IPCC

Wetlands Supplement).

Consistency of time series of calculations is secured by use of the NFI data for the cropland and grassland area and the NFI based remote sensing analysis for land use changes. The

estimation of area of organic soil represents situation before 1990. Area of cropland on organic soil might be overestimated; however, more accurate digitalised data of historical soil

maps are expected in the Agricultural soil mapping project, which will be completed at the end of 2015.


302

6.7.1.6 Category-specific QA/QC and verification

The QA/QC plans for the cropland category includes the QC measures based on the IPCC

(2006 IPCC Guidelines, Chapter 5.4.3, tier 1 based QA/QC). The QA/QC procedures are implemented during every inventory. Potential errors and inconsistencies are documented and corrections are made if necessary. Land use, as well as carbon stock in living and dead

biomass related QA/QC procedures are implemented within the scope of the standard NFI procedure by re-measuring of 20 % of all sample plots. Training of the NFI field teams takes

place every spring before starting the field works.

6.7.1.7 Category-specific recalculations

The most significant change in cropland is application of the default emission factor for drained organic soil – 7.9 tonnes C ha-1 yearly. This change increased emissions from organic soil in cropland by 790 % in compare to IPCC GPG LULUCF (2003) and by 63 % in

compare to previously calculated values (2006 IPCC Guidelines). Emission factor for long term cultivating in croplands has been changed from 0.71 to 0.69; however, it does not affect

carbon stock estimates in cropland remaining cropland.

This is the 1st year when carbon stock change in living and dead biomass is included in cropland remaining cropland. These pools, however have only minor impact on the net

emissions from cropland. The net carbon stock change in living and dead biomass carbon pool is 2.61 Gg C in 2013, which accounts for less than 1 % of the net GHG emissions from

cropland remaining cropland.

Considerable changes in the net GHG emissions take place due to calculation of CH4 emissions from drainage ditches on drained organic soil in croplands. CH4 emissions from

ditches in 2013 are 117.75 Gg CO2 eq.

6.7.1.8 Category-specific planned improvements

There are several improvements proposed for the following inventories:

updated area of organic soil in cropland according to the NFI study started in 2012175;

the same values of share of organic soil will be used for land converted to cropland. Logarithmic regression will be used in time series to reduce share of organic soil in

cropland before 1990 (5.18 %) to the actual value;

updated CO2 emissions from organic soil considering area changes and recent findings

in Nordic and Baltic countries, particularly, doctoral thesis by Jüri-Ott Salm ―Emission of greenhouse gases CO2, CH4, and N2O from Estonian transitional fens and ombrotrophic bogs: the impact of different land-use practice‖176.

updated N2O emissions due to disturbances using emphyrical data on carbon stock changes in soil;

Tier 1 methodology to estimate carbon stock changes in cropland considering changes of cropping practices since 1970.

175

Lazdiņš, A., 2012. Atbalsts klimata pētījumu programmai (starpziņojums par 2012. gada darba uzdevumu izpildi) ( No. 020512/S68).

LVMI Silava, Salaspils. 176

Salm, J.O., 2012. Emission of greenhouse gases CO2, CH4, and N2O from Estonian transitional fens and ombrotrophic bogs: the impact of different land-use practice (Doctoral thesis). Tartu Ülikooli Kirjastus, Tartu.


303

6.7.2 Land converted to cropland


CO2 is a key category of emissions in land converted to cropland. Emissions from soil, living

and dead biomass due to conversion to cropland are reported in the GHG inventory. The net GHG emissions from land converted to croplands in 2013 (excluding emissions from drainage of organic soils) were 156.28 Gg CO2 eq. (Figure 6.7).

Figure 6.7 Summary of GHG emissions from land converted to cropland

All lands converted to cropland less than 20 years ago are reported in this category. The land converted to cropland more than 20 years ago are reported under cropland remaining cropland

category. The most of the land converted to cropland is forest land. Other types of land use changes have minor impact.

6.7.2.2 Information on approaches used for representing land areas and on land-use databases used for the inventory preparation

Remote sensing and NFI sample plots based research data are used to estimate forest land converted to cropland177. Other land use categories converted to cropland are estimated since 2009, when the 2nd cycle of the NFI was started in Latvia; however, there are no evidences of

conversion of considerable area of other land use categories to cropland since 1990 due to the fact that the area of cropland continuously decreased until 2008. Later according to the NFI

data it is stabilizing; however, it is complicated to identify, if returning to conventional agricultural practice are occasional cases or it is continuous process. Therefore, there is 5 years delay period (between 2 NFI cycles) to approve land use change from grassland to

cropland or opposite, as well as afforestation and conversion of forest land to grassland.

177

Lazdiņš and Zariņš, ―Elaboration and integration into National greenhouse gas inventory report matrices of land use changes of areas belonging to Kyoto protocol article 3.3 and 3.4 activities (Report on research work contracted by the Ministry of Environment of

republic of Latvia)‖; Lazdiņš, ―Harmonization of Land Use Matrix in Latvia according to Requirements of International Greenho use Gas Reporting System - Extending Outputs of National Forest Inventory Program‖; Zariņš, Meža Statistiskās Inventarizācijas Parauglaukumu Mērījumu Interpolācijas Projekts, Izmantojot Satelītu Uzņēmumu Analīzes Iespējas (pāskats Par Meža Attīstības Fonda Pasūtīto Pētījumu); Lazdiņš et al., Mežu Zemes Izmantošanas Maiņas Matricas Izstrādāšana Un Integrēšanu Nacionālajā

Siltumnīcefekta Gāzu Inventarizācijas Pārskatā Par Kioto Protokola 3.3 Un 3.4 Pantā Minētajiem Pasākumiem; Lazdiņš and Zariņš, Vēsturiskās (1990. Gada) Apsaimniekoto Aramzemju Platības Noteikšana Un Līdz 2009. Gadam Notikušo Aramzemju Platības Izmaiņu Novērtēšana.


304

6.7.2.3 Land-use definitions and the classification systems used and their correspondence to the LULUCF categories

The decision support tree was elaborated in 2013 to simplify identification of land use changes in cropland, grassland and forest land using the NFI data analysis (Table 6.24). The identification of land use changes according to this approach takes 10 years. Considering that

there are still some unsolved issues, like interpretation of merged sectors of the NFI plots with different initial land use and distribution of biomass located on converted sites, it is proposed

to combine automated evaluation and following manual quality assurance.

Table 6.24 Decision support table to estimate conversion of grassland, cropland and forest land

First NFI 2004-2008 Second NFI 2005-2013 Third NFI 2014-2019 Fifth NFI 2020-2024

Initial land use –

grassland

Whole plot or sector is

ploughed – no land use

change marked


ploughed – ploughed

area is marked as

cropland since second

NFI


ploughed – the area

remains cropland

No signs of ploughing –

the area remains

cropland


the area remains

grassland



remains grassland


the area remains

grassland


the area remains

grassland



remains grassland


ploughed – ploughed

area is marked as

cropland since third NFI


the area remains

grassland


the area remains

grassland



remains grassland


the area remains

grassland


Transition period for all land use changes is considered 20 years; respectively, land converted

to cropland in 1990 is reported under the cropland remaining cropland category in 2010. Land use changes to cropland in 1990-2008 are estimated using remote sensing based evaluation of

vegetation index. The same data are used to identify extensively managed cropland, initially reported under grassland remaining grassland category.

Area of organic soil in land converted to cropland is calculated using different approach than

in cropland remaining cropland. Instead of using proportion of area of organic soil in the final land use category, the values characteristic for initial land use are applied. Respectively, if share of organic soil in forest land remaining forest in 1990 is 22 %, it is considered, that area

of organic soil in forest land converted to cropland in 1990 is 22 %178.

Unlike to cropland remaining cropland carbon stock change in living biomass in forest land

converted to cropland is calculated as losses in living biomass due to felling of trees, considering average carbon stock in living biomass in forest land remaining forest in a

178

Lazdiņš, Bārdule, and Stola, ―Preliminary Results of Evaluation of Area of Organic Soils in Arable Lands in Latvia.‖


305

particular year. Losses in dead wood are reported similarly, as loss of average carbon stock in dead wood in a particular year. Carbon stock in litter is considered as constant value 12.14 ± 2.8 tonnes C ha-1 according to the BioSoil project results in fertile stand types

(Hylocomiosa, Oxalidosa, Myrtilloso-sphagnosa, Myrtillosoi-polytrichosa, Myrtillosa mel., Mercurialosa mel.). Instant oxidation method is applied to living biomass, dead wood and

litter carbon pools.

Carbon stock changes in mineral soil are estimated using Equation 2.25 of the 2006 IPCC Guidelines. Impact factors for calculations of the carbon stock change under different

management activities are taken from Table 5.5 in 2006 IPCC Guidelines:

FLU 0.69 (Long-term cultivated, Temperate moist);

FMG 1.00 (Full tillage, Temperate dry and wet);

FI 1.00 (Medium input, all).

The initial carbon stock in mineral forest soil at 0-30 cm depth (reference C stock) is

82.6 ± 7.8 tonnes ha-1 according to the forest soil monitoring project BioSoil179. Forest stand types similar to agricultural lands are selected to calculate average carbon stock in forest soil

(Hylocomiosa, Oxalidosa, Myrtilloso-sphagnosa, Myrtillosoi-polytrichosa, Myrtillosa mel., Mercurialosa mel.). Initial carbon stock at 0-30 cm depth in grassland is considered 77 ± 6.9 tonnes ha-1. The carbon stock in forest land converted to cropland after transition

period of 20 years according to the Equation 2.25 is 57 tonnes C ha-1 at 0-30 cm depth; respectively, reduction of carbon stock in mineral soils is 25.6 tonnes ha-1 or 1.3 tonnes C ha-1

annually. The carbon stock in grassland converted to cropland after transition period of 20 years according to the Equation 2.25 is 52.7 tonnes C ha-1 at 0-30 cm depth; respectively, reduction of carbon stock in mineral soils is 23.7 tonnes ha-1 or 1.2 tonnes C ha-1 annually.

In organic soil of forest land and grassland converted to cropland the factor for cropland remaining cropland (7.9 tonnes C ha-1 annually) is used to estimate carbon stock changes.

The same approach as for cropland remaining cropland is used to calculate CH4 emissions from drainage ditches.


Uncertainty of area estimates is provided in Table 9.23. Uncertainty of average carbon stock in litter in forests is 23 %, uncertainty of carbon stock in mineral soil in forest land at 0-30 cm

is 9 %, uncertainty of dead wood stock in forests is 2 %, uncertainty of carbon stock in dead wood according to the expert judgement is 30 %; the combined uncertainty of carbon stock in

dead wood is 31 %. Uncertainties for CH4 emissions and carbon stock changes in mineral soil are the same as for cropland remaining cropland.


The same approach as in cropland remaining cropland is applied. A part of remote sensing data (10 %) was evaluated manually during the remote analysis to estimate uncertainty of the

automatic classification of vegetation index.

179

Lazdiņš et al., Mežsaimniecisko Darbību Ietekmes Uz Siltumnīcefekta Gāzu Emisijām Un CO₂ Piesaisti Novērtējums (pārskats Par 2013. Gada Darba Uzdevumu Izpildi).


306


Factors for carbon stock in forest soil, litter and land use factor for calculation of carbon stock

changes in mineral soil due to conversion to cropland are changed, as well as factor for calculation of emissions from organic soil (Table 6.25).

Table 6.25 Changes in calculations

Factor 2014

submission

2015

submission

Explanation

Carbon stock in mineral forest

soil

124.2 82.6 ERT recommendation to use

data from fertile soil

Carbon stock in litter in forest land

20.9 12.1 ERT recommendation to use data from fertile soil

FLU for cropland on mineral soil

0.71 0.69 2006 IPCC Guidelines

Carbon stock change in organic soil in cropland

3.74 5 2006 IPCC Guidelines


Area of organic soil might be overestimated in land converted to cropland, significantly increasing emissions due to conversion of forest land to cropland and grassland to cropland. Field measurement based information on organic soils is necessary to improve accuracy of

estimates of the emissions.

6.8 GRASSLAND (CRF 4.C)

6.8.1 Grassland remaining grassland


The grassland’s category is a key source of CO2 emissions from organic soil. Total area of

grassland in Latvia in 2013 was 698.25 kha, including 562.20 kha of grassland remaining grassland. Grassland remaining grassland is divided into mineral and organic soils. Area of the grassland is estimated using research data180 on the base of remote sensing data analysis.

The net emissions from grassland remaining grassland were 600.68 Gg CO2 eq. (excluding 60.48 Gg CO2 eq. emissions from drained organic soils) in Latvia in 2013 (Figure 6.8). The

CO2 removals are reported in living and dead biomass in forest lands not fulfilling criteria of forest definition. The most of the emissions are associated with organic soils.

180

Lazdiņš and Čugunovs, Oglekļa Dioksīda (CO2) Piesaistes Un Siltumnīcefekta Gāzu (SEG) Emisiju Un Zemes Lietojuma Veida Ietekmes Novērtējums Intensīvi Un Ekstensīvi Kultivētās Aramzemēs, Daudzgadīgos Zālājos Un Bioloģiski Vērtīgos Zālājos.


307

Figure 6.8 Summary of GHG emissions from grassland remaining grassland

Grassland remaining grassland is divided into mineral (95% of total area of grassland

remaining grassland) and organic (5% of total area of grassland remaining grassland) soils. It is assumed that mineral soils are neither a source nor sink of CO2. It could be changed depending on management level (degraded or improved) in grasslands; however, according to

the expert judgement the inventory team considered that all grasslands are managed in way that there are no degraded or improved grasslands. The judgement is based on the fact that

husbandry production in Latvia decreased considerably since 1990, but area of pastures and grasslands is increased. This fact demonstrates extensive use of former pastures and lands used in fodder production before 1990. This type of management systems is not associated

with decrease of carbon stock in soil. Organic soils are considerable source of CO2 emissions. Organic soils and drainage ditches in grasslands are reported as a source of methane also as it

is recommended in the IPCC Wetlands Supplement chapter 2.

6.8.1.2 Land-use definitions and the classification systems used and their correspondence

to the LULUCF categories

The category consists of lands used as pastures, as well as glades and bush- land which do not fit to forest definition, including vegetated areas on non-forest lands complying to forest

definition where land use type can be easily switched back to grassland without legal requirement of transformation of the land use, but except grassland used in forage production

and extensively managed cropland. In the Latvia's GHG reporting non-forest lands with average diameter of trees at the breast height less than 2 cm are reported under grassland's category. No removals or emissions associated with living or dead biomass are reported for

these lands to avoid overestimation of CO2 removals.

6.8.1.3 Methodological data

Area of the grassland is estimated using research data 181 on the base of remote sensing data analysis. Information about area of organic agricultural soils is obtained from final report of

L.U. consulting project (5.18 % ± 11 % of total area of farmlands)182. These figures are based

181

Lazdiņš and Čugunovs, Oglekļa Dioksīda (CO2) Piesaistes Un Siltumnīcefekta Gāzu (SEG) Emisiju Un Zemes Lietojuma Veida

Ietekmes Novērtējums Intensīvi Un Ekstensīvi Kultivētās Aramzemēs, Daudzgadīgos Zālājos Un Bioloģiski Vērtīgos Zālājos. 182

L.U. Consulting, ―Augšņu un reljefa izejas datu sagatavošana un eiropas komisijas izstrādāto augsnes un reljefa kritēriju mazā labvēlīgo apvidu noteikšanai piemērošanas simulācija (Projekta kopsavilkuma ziņojums).‖


308

on soil mapping data and characterizes situation before 1990 (data utilized in calculation were obtained from the 60ths to early 80ths).

Woody biomass increment figures for 2004-2013 are taken from the NFI, but for the historical

data results of recalculation of increment of living biomass in grassland are considered183. Mortality factors are taken directly from forest land remaining forest assuming that mortality

in grassland is equal to average mortality (in percent of increment of living biomass) in forest land in a particular year. Decay period for dead wood is considered 20 years according to 2006 IPCC Guidelines.

The assumptions for biomass calculations used in EPIM tool are shown in Table 6.26 default 20 years decay period is considered for dead wood.

Table 6.26 Relative stock changes for grassland management in mineral soils

Factor Level Climate regime IPCC default Uncertainty

Land use All All 1.0 NA

Management Nominally managed (non-

degraded)

All 1.0 NA

Management Moderately degraded

grassland

Temperate /

Boreal

0.95 ± 13%

Management Severely degraded All 0.7 ± 40%

Management Improved grassland Temperate /

Boreal

1.14 ± 11%

Input (applied only to

improved grassland)

Medium All 1.0 NA


improved grassland)

High All 1.11 ± 7%

The calculations are done in EPIM tool, which is still in development stage; therefore some

calculations, like emissions from organic soils are not fully implemented and should be done manually. The assumptions used in EPIM tool are shown in Table 6.27, default 20 years decay period is considered for dead wood.

Table 6.27 Assumptions for calculation of carbon stock changes in living and dead biomass in grassland

Year Grassland

with woody

vegetation,

1000 ha

Gross increment of

living biomass

Wood

density,

kg m¯³

Natural

mortalit

y, m³

ha¯¹

BEFs Carbon

content,

kg tonne-

1


crown

stem to

below-

ground

1990 19.13 0.02 0.97 0.41 0.18 0.31 0.31 523

1991 19.44 0.02 0.95 0.41 0.18 0.31 0.31 523

1992 19.75 0.02 1 0.41 0.19 0.31 0.31 523

1993 20.07 0.02 0.99 0.41 0.19 0.31 0.31 523

1994 20.38 0.02 0.99 0.41 0.19 0.31 0.32 523

1995 20.69 0.02 0.97 0.41 0.19 0.31 0.32 523

1996 21 0.02 0.96 0.41 0.19 0.31 0.32 523

1997 21.32 0.02 0.96 0.41 0.19 0.31 0.32 523

1998 21.63 0.02 0.94 0.41 0.19 0.31 0.32 523

1999 21.94 0.02 0.98 0.41 0.2 0.32 0.32 523

2000 22.26 0.02 0.97 0.41 0.19 0.32 0.32 523

2001 22.57 0.02 0.96 0.41 0.19 0.32 0.32 523

2002 22.88 0.02 0.94 0.41 0.19 0.32 0.32 523

2003 23.19 0.02 0.93 0.41 0.19 0.32 0.32 523

2004 23.51 0.02 0.92 0.41 0.2 0.33 0.32 524

2005 23.82 0.02 0.91 0.41 0.2 0.33 0.32 524

2006 24.13 0.02 0.89 0.41 0.19 0.33 0.32 524

2007 23.54 0.05 2.12 0.41 0.46 0.33 0.32 524

2008 23.54 0.05 2.12 0.41 0.46 0.33 0.32 524

183

Jansons, Methods Utilized to Recalculate Historical Forest Increment Data.


309

Year Grassland

with woody

vegetation,

1000 ha

Gross increment of

living biomass

Wood

density,

kg m¯³

Natural

mortalit

y, m³

ha¯¹

BEFs Carbon

content,

kg tonne-

1


crown

stem to

below-

ground

2009 23.54 0.05 2.12 0.41 0.49 0.33 0.32 524

2010 23.54 0.05 2.12 0.41 0.49 0.33 0.32 524

2011 23.54 0.05 2.12 0.41 0.49 0.33 0.32 524

2012 23.65 0.04 1.88 0.41 0.43 0.33 0.32 524

2013 23.84 0.05 1.93 0.41 0.57 0.33 0.32 524

The emission factor of drained organic soils is considered to be 6.1 tonnes C ha-1 yearly

according to IPCC 2013.

Emission factors for CH4 emissions from drained organic soil and drainage ditches are respectively 16 kg and 1165 kg CH4 yearly according to tables 2.3 and 2.4 in IPCC 2013.

Total area of drainage ditches is estimated by using the same approach as explained in cropland. Ditch density on organic soils is assumed to be 0.045 ha ha-1.

Default coefficients on impact of different management regime on carbon emissions from 2006 IPCC Guidelines chapter 6, Table 6.2 are used to calculate carbon stock changes in mineral soil (Table 6.28). Combined impact factor for carbon stock changes in mineral soil is

equal to 1 (land use – all, management – non-degraded, input – medium).

Table 6.28 Relative stock changes due to grassland management on mineral soils

Factor Level Climate regime IPCC default Uncertainty

Land use All All 1.0 NA

Management Nominally managed (non-

degraded)

All 1.0 NA

Management Moderately degraded

grassland

Temperate /

Boreal

0.95 ± 13%

Management Severely degraded All 0.7 ± 40%

Management Improved grassland Temperate /

Boreal

1.14 ± 11%


improved grassland)

Medium All 1.0 NA


improved grassland)

High All 1.11 ± 7%

N2O and CH4 emissions from biomass burning are calculated according to methodology described in chapter Biomass burning.



Table 6.29 Uncertainty of the grassland use data in 2013


plots

Share of NFI

plots

Standard error

of proportion

Grassland 1747 11% 4%

grassland remaining grassland 1407 9% 5%


land converted to grassland 340 2% 11%


The uncertainty estimate for the CO2 emission factor for organic soils is 20 % according to the Table 2.1 in the IPCC Wetlands Supplement.

Uncertainties for emission factors used in calculation of CH4 emissions from organic grasslands and drainage ditches are 85 % and 81 % according to Table 2.3 and Table 2.4 in the IPCC Wetlands Supplement.


310

The time series of emissions from grasslands is consistent; however, overestimation is possible due to lack of knowledge about current area and distribution of organic soils. Recent studies shows that area of organic soils in grassland is less than 1.5 %184; however more

accurate information will be available at the end of 2015.


The QA/QC plans for the Grassland's category includes the QC measures based on the IPCC (2006 IPCC Guidelines, Chapter 6.4.3, Tier 1 approach). These measures are implemented

every year during the inventory. Potential errors and inconsistencies are documented and corrections are made if necessary. The files and documents used in preparation of the inventory are archived annually and back-up copies are made weekly.


Major changes occurred due to change of CO2 emission factor for organic soils. Emission

factor is changed from 1.6 Gg CO2-C ha-1 yr-1 to 6.1 Gg CO2-C ha-1 yr-1.

Changes have appeared in total estimates on net emissions due to including of CH4 emission

from organic soils in estimates. Previously it was considered that methane emissions are negligible and can be ignored. But latest studies in Estonia have approved significant methane emissions from organic soils in grasslands including also emissions from drainage ditches.

Net CH4 emissions are 60.48 Gg CO2 eq. yr-1.


It is planned to improve reporting for ditch area in organic soil in next years. Now we have very limited knowledge about organic soils and drainage ditches in grasslands. In the end of

2015 new NFI inventory data and results about organic soils in grassland will be available and on the basis of the NFI inventory it will be possible to specify reporting.

6.8.2 Land converted to grassland (4.C.2)


This category is key source of CO2 removals due to sequestration of carbon in mineral soil after conversion of cropland to grassland. Under this category all lands converted to grassland

less than 20 years ago185 are reported and the total area is estimated to be 135.69 kha in 2013.

All categories of land use change to grassland, except cropland to grassland, are reported as

NO, because there are no evidences of such conversions. Conversion from cropland to grassland takes place due to abandonment of cropland. Grassland is reported in the managed lands category.

184

Andis Lazdiņš et al., Atbalsts Klimata Pētījumu Programmai (Pārksats Par Projekta 2013. Gada Darba Uzdevumu Izpildi) (Salaspi ls, 2013), Salaspils; Andis Lazdiņš, Atbalsts Klimata Pētījumu Programmai (starpziņojums Par 2012. Gada Darba Uzdevumu Izpildi) (Salaspils, 2012), Salaspils, https://sites.google.com/site/lvlulucf/research-

projects/atbalstsklimatapetijumuprogrammaistarpzinojumspar2012gadarezultatiem. 185

Lazdiņš and Zariņš, ―Elaboration and integration into National greenhouse gas inventory report matrices of land use changes of areas belonging to Kyoto protocol article 3.3 and 3.4 activities (Report on research work contracted by the Ministry of Environment of republic of Latvia)‖; Lazdiņš, ―Harmonization of Land Use Matrix in Latvia according to Requirements of International Greenhouse

Gas Reporting System - Extending Outputs of National Forest Inventory Program‖; Lazdiņš and Čugunovs, Oglekļa Dioksīda (CO2) Piesaistes Un Siltumnīcefekta Gāzu (SEG) Emisiju Un Zemes Lietojuma Veida Ietekmes Novērtējums Intensīvi Un Ekstensīvi Kultivētās Aramzemēs, Daudzgadīgos Zālājos Un Bioloģiski Vērtīgos Zālājos.


311

Increase of the area of organic soils is associated with conversion of cropland to grassland during the 90ths and during the last decade. Opposite process – reduction of area of grassland – took place due to afforestation (both natural expansion of forest and planting) of farmlands.

Net GHG emissions in land category land converted to grassland excluding emissions from drained organic soil in 2013 were -394.79 Gg CO2 eq. (Figure 6.9). Increase of removals of

CO2 in land converted to grassland after 2001 is associated with removals of CO2 in soil.

Figure 6.9 Summary of GHG emissions from land converted to grassland

6.8.2.2 Land-use definitions and the classification systems used and their correspondence

to the LULUCF categories

The category of grassland is defined already on grassland remaining grassland. Main difference in definition between grassland remaining grassland and land converted to

grassland is that under category of land converted to grassland all grasslands are counted where land use change have occurred in last 20 years.

6.8.2.3 Methodological data

Carbon stock changes in mineral soils in cropland converted to grassland are reported as net

removals, because there are research evidences, that carbon stock in grasslands in average at 0-30 cm depth is significantly higher than in cropland186 and the difference is 23.7 tonnes C ha-1. These data are based on comparison of 80 NFI sample plots and will be

updated in future by continuous monitoring of carbon stock change in soil.

Methane emissions from ditches on organic soils have been included in estimates also for

lands converted to grasslands and it is calculated with the same approach as grassland remaining grassland.


Uncertainty of area estimates is provided in Table 6.29. Uncertainties of emissions and carbon stock change factors are described in chapters characterizing grassland remaining grassland.

186

Lazdiņš, Bārdule, and Stola, ―Preliminary Results of Evaluation of Carbon Stock in Historical Cropland and Grassland‖; Lazdiņš et al., Atbalsts Klimata Pētījumu Programmai (Pārksats Par Projekta 2013. Gada Darba Uzdevumu Izpildi) .


312


QA/QC procedures are described in chapters characterizing grassland remaining grassland.


Carbon stock changes in soil are recalculated due to application of different initial carbon

stock values in cropland and different factor of carbon stock changes in organic soil.


Country specific data are necessary to estimate carbon stock changes according to the soil mapping data, as well as to estimate share of organic soil in land converted to grassland.

6.9 WETLANDS (CRF 4.D)


Wetlands remaining wetlands is a key source category of CO2 emissions due to commercial peat extraction and emissions of CO2 from drained soil. According to the 2006

IPCC Guidelines wetlands include land that is covered or saturated by water for all or part of the year and that does not fall into the forest land, cropland, and grassland or settle ment categories. Total area of wetlands (448.71 kha) is reported according to the research results,

including 27.0 kha of peatlands drained for peat extraction (Table 3a.3.3 of the IPCC GPG LULUCF 2003).

Latvia reports CO2 emissions associated only with industrial peat extraction in this category. The rest of the area of wetlands is not managed and CO2 emissions are not calculated, exception is area with woody vegetation located adjacent to water courses, water body or

swamps and which does not fit to definition of forest land category (Table 9.30). According to the Table 3a.3.3 of the IPCC GPG LULUCF 2003 the default value for area of industrial peat-

lands in Latvia is 27 kha; using extraction rate method calculations result in 3 kha in 2013. Taking into account considerable annual fluctuations in peat production, more conservative default method is used in calculations.

Aggregated emissions from industrial peatlands are equal for the whole time series due to lack of data about status of industrial peat-lands prepared for extraction 20-40 years ago.

However, there are no evidences of new industrial peatlands prepared for peat extraction after 1990; therefore, the risk of underestimation of emissions do not exist. N2O contributes to about 7 % of net emissions from peat-lands. Removals in this category are reported in living

and dead biomass.

The net GHG emissions in wetlands in 2013 were 1035.55 Gg CO2 eq. (Figure 6.10). The

most of the emissions are associated with commercial peat production for horticulture.


313

Figure 6.10 Summary of GHG emissions from wetlands



Spatial approach is used to represent area of wetlands. Activity data are provided by the

NFI187. No changes in land use are considered since 1990.



Wetlands category includes all inland water bodies (rivers, ponds, lakes), swamps (constantly

wet areas where height of trees cannot reach more than 5 m in height and ground vegetation consists mostly of sphagnum and different sword grasses), flood-lands (small areas) and alluvial lands (larger flood- lands).


Activity data – area of peatlands prepared for extraction, is taken from TABLE 3a.3.3 188 of the IPCC GPG LULUCF 2003. Emission factor for carbon stock changes (2.8 tonnes C ha-1 yr-1) due to drainage is taken from IPCC Wetlands Supplement 189. Carbon content in air dry

peat (0.45 tonnes C per tonne of peat) is considered according to Table 7.5 of 2006 IPCC Guidelines 190. Moisture of peat reported in national statistics is considered 40 %.

Off-site CO2-C emissions associated to the horticultural (non-energy) use of peat extracted and removed are reported using instant oxidation method. Off-site emissions from peat used for energy are reported in the Energy Sector (1.A.1. Energy industries, 1.A.2. Manufacturing

industries and construction and 1.A.4. Other sectors), and is therefore not included here.

CH4 emissions from drained organic soils are calculated according to methodology applied in

drained forests on organic soil. As drainage of wetlands in national conditions is occurring

187 Lazdiņš, ―Harmonization of land use matrix in Latvia according to requirements of international greenhouse gas reporting syst em -

extending outputs of National Forest inventory program.‖

188 Estimates of peatland areas and use for tier 1 in 1000 hectares

189 EMISSION FACTORS FOR CO2–C AND ASSOCIATED UNCERTAINTY FOR LANDS MANAGED FOR PEAT

EXTRACTION, BY CLIMATE ZONE 190

CONVERSION FACTORS FOR CO2–C FOR VOLUME AND WEIGHT PRODUCTION DATA


314

only in territories for peat extraction default emission factors for drained organic soil (6.1 kg CH4 ha-1 yr-1) and drainage ditches (542 kg CH4 ha-1 yr-1) for peat extraction are utilized. Density of ditches is considered 0.07 ha per 1 ha of peatland.

The calculations are done in EPIM tool, which is still in development stage; therefore some calculations, like emissions from organic soils are not fully implemented and should be done

manually. The assumptions used in EPIM tool are shown in Table 6.30, default 20 years decay period is considered for dead wood.

Table 6.30 Assumptions for calculation of carbon stock changes in living and dead biomass in wetlands

Year Wetlands

with

woody

vegetation,

1000 ha

Gross increment of

living biomass

Wood

density,

kg m¯³

Natural

mortalit

y, m³

ha¯¹

BEFs Carbon

content,

kg tonne-

1


crown

stem to

below-

ground

1990 189.25 0.06 0.33 0.41 0.06 0.31 0.31 523

1991 191.55 0.07 0.37 0.41 0.07 0.31 0.31 523

1992 193.42 0.08 0.41 0.41 0.08 0.31 0.31 523

1993 194.24 0.08 0.42 0.41 0.08 0.31 0.31 523

1994 195.72 0.09 0.44 0.41 0.09 0.31 0.32 523

1995 196.29 0.09 0.45 0.41 0.09 0.31 0.32 523

1996 197.92 0.09 0.46 0.41 0.09 0.31 0.32 523

1997 199.26 0.09 0.46 0.41 0.09 0.31 0.32 523

1998 201.05 0.09 0.47 0.41 0.09 0.31 0.32 523

1999 201.2 0.09 0.47 0.41 0.09 0.32 0.32 523

2000 202.54 0.1 0.47 0.41 0.09 0.32 0.32 523

2001 203.12 0.1 0.47 0.41 0.09 0.32 0.32 523

2002 204.27 0.1 0.47 0.41 0.09 0.32 0.32 523

2003 205.96 0.1 0.47 0.41 0.09 0.32 0.32 523

2004 206.59 0.1 0.46 0.41 0.1 0.33 0.32 524

2005 206.71 0.1 0.46 0.41 0.1 0.33 0.32 524

2006 210.16 0.1 0.46 0.41 0.1 0.33 0.32 524

2007 97.62 0.18 1.85 0.41 0.4 0.33 0.32 524

2008 97.62 0.18 1.85 0.41 0.4 0.33 0.32 524

2009 97.62 0.18 1.85 0.41 0.43 0.33 0.32 524

2010 97.62 0.18 1.85 0.41 0.43 0.33 0.32 524

2011 97.62 0.18 1.85 0.41 0.43 0.33 0.32 524

2012 97.62 0.17 1.73 0.41 0.4 0.33 0.32 524

2013 97.62 0.17 1.79 0.41 0.53 0.33 0.32 524


Uncertainty level of CO2 emission factor is assumed as 95 %191. Uncertainty of area estimates

is provided in Table 6.31.

Table 6.31 Uncertainty of the wetland use data in 2013


plots

Share of NFI

plots

Standard error

of proportion

Wetlands 1123 7% 6%

wetlands remaining wetlands 1119 7% 6%

drained soil 68 0% 24%

land converted to wetlands 4 0% 135%

Uncertainty range of emission factors for drained organic soil and drainage ditches are 1.6-11 kg ha-1 yr-1 and 102-981 kg CH4 ha-1 yr-1.

191

According to log-normal distribution.


315

Complete consistency of the time-series is secured by use of the same data source for estimation of area and emissions for the whole time period. Emissions associated with peat extraction might be considerably overestimated because this industry is reduced during last

decades and area of peat-lands prepared for extraction is reduced too. However, there are no statistically verifiable data about technical status of peat quarries therefore default values of

activity data based on situation before 1990 are used in calculations.


Quality control procedures named in 2006 IPCC Guidelines were done, particularly, data about peat extraction were compiled from different sources (national statistics and Union of

peat producers) as well as emission factors provided by different authors were compared.


Area of wetlands is updated due to harmonization of the country area in the whole reporting period. Carbon stock changes in living biomass and dead wood are reported according to the

methodology applied in the forest land remaining forest.


Non-CO2 GHG might be considerable part of emissions from wetlands, therefore, it is

necessary to develop method for estimation impact of ditches and other types of wetlands on N2O and CH4 emissions. Considering growth of peat extraction for energy purposes from abandoned peatlands and forests on wet organic soils, it is important to be able to calculate

impact of drainage on non-CO2 emissions as well as to be able to separate wetlands on organic soils (high N2O emissions) and mineral soils (low N2O emissions). Wetlands are one

of the priorities in further development of GHG inventory in LULUCF sector in Latvia.

6.10 SETTLEMENTS (CRF 4.E)


Land converted to settlements is a key source of CO2 emissions according to trend and level

assessment due to losses in carbon stock in living biomass, dead wood, litter and soil carbon pool. The role of conversion of forest land to settlements is increasing with a growth of economic activity and road construction in rural regions, because more than half of the

country area is covered by forests, so that any new constructions are always associated with conversion of forest lands. Conversion of abandoned farmlands at the same time is more

intensive; however, young forests on farmlands cannot fully compensate emissions due to the conversion of forest lands.

Under the settlements category emissions from soils, litter, living and dead biomass due to

conversion of land use type are reported. In 2013 removals in living and dead biomass in settlements are reported using the NFI data on increment of growing stock in settlements,

which is represented mostly by overgrowing of roadsides, power lines and other infrastructure. Net emissions from settlements remaining settlements in 2013 were -97.94 Gg CO2 (Figure 6.11). However, removals in woody vegetation and dead biomass were

compensated by emissions due to land use change (land converted to settlements category). Net emissions from land converted to settlements in 2013 were 1156.61 Gg CO2 eq. (Figure

6.12). Total area of settlements in 2013 was 264.10 kha, including 227.90 kha of settlements remaining settlements since 1990.


316

Figure 6.11 Summary of GHG emissions from settlements remaining settlements

Figure 6.12 Summary of GHG emissions from land converted to settlements

The total area of settlements is estimated according to the information provided by the NFI. According to the expert estimation, increase of area of settlements during last 20 years

occurred due to conversion of forest land. Increase of area of settlements (deforestation) is generally associated with road construction. All roads, including forest roads are reported in

the settlements category; therefore, the deforested area is considerably higher than official statistics, where forest roads are not reported as deforested area and still belong to forest land.



Spatial approach is used to represent area of settlements. Activity data are provided by the

NFI. Area of land converted to settlements before 2004 is estimated using LANDSAT satellite images within the scope of the project ―Elaboration and integration into National


317

greenhouse gas inventory report matrices of land use changes of areas belonging to Kyoto protocol article 3.3 and 3.4 activities‖192.



According to the 2006 IPCC Guidelines settlements include all developed land, like

residential, transportation, commercial, and production (commercial, manufacturing) infrastructure of any size, unless it is already included under other land-use categories, for instance, in forest lands (parks and green parts of forests). According to national definitions

updated for the GHG reporting, settlements mean:

land under buildings including yards and gardens as well as land necessary to maintain

and to access those buildings;

land under roads including buffer zones;

forest infrastructure excluding ditches and other wetlands, but including seed orchards, forest nurseries and fire-breaks;

other infrastructure – buffer zones of industrial networks, quarries etc.


6.10.4.1 Settlements remaining settlements

Area of land remaining settlements is assumed constant until 2009 (227.90 kha) according to the NFI data, including 0.32 kha of organic soils. In 2010-2013 areas converted to settlements

in 1990-1993 are reported under settlements remaining settlements).

The CO2 removals are reported for living and dead biomass categories in settlements remaining settlements based on the NFI data. Removals are reported based on weighted (by

area) gross increment, mortality factors, BEFs, carbon content and wood density in a particular year in forest land remaining forest. For emissions from dead wood pool in

settlements remaining settlements 20 years transition period is considered. Age of woody vegetation on settlements is counted backwards and as soon as age of trees reach ―0‖, it is considered, that there is no more vegetation and no increment calculations are done. EPIM

tool is used in calculations.

Emissions from soils in settlements remaining settlements are calculated according 2006

IPCC Guidelines Tier 1 method. It is assumed that inputs equal outputs so that settlement mineral soil C stocks do not change in settlements remaining settlements. Emissions from organic soils in settlements remaining settlements are calculated using equation 2.26 in 2006

IPCC Guidelines (equation No. 11). If soils are drained and the peat is not removed, the emissions are calculated using emission factors for cultivated organic soils, due to deep

drainage in settlements similar to cropland. Annual emission factor (EF) for cultivated organic soils in cool temperate climatic temperature regime is 5.0 tonnes C ha-1 yr-1 (2006 IPCC Guidelines, Table 5.6).

192

Lazdiņš and Zariņš, ―Elaboration and integration into National greenhouse gas inventory report matrices of land use changes of areas belonging to Kyoto protocol article 3.3 and 3.4 activities (Report on research work contracted by the Ministry of Environment of republic of Latvia).‖


318

LOrganic=∑c

( A⋅EF )c , where

LOrganic=annual carbon loss from drained organic soils , tonnesC yr-1

;

A=land areaof drained organic soils in climate type c , ha ;

EF=emission factor for climate type c ,tonnes C ha-1

yr-1

.

(10)

CH4 emissions from drained organic soils in settlements are estimated by the same methodology as described under chapter cropland remaining cropland, by using the same emission factors, because cropland land-use category has the closest national conditions of

drained organic soils to settlements land-use category.

6.10.4.2 Land converted to settlements

Area of land converted to settlements is estimated by evaluation of vegetation index of the NFI points (23 thousand plots across the country) in series of satellite images produced in

1990, 1995 and 2000. Final land use was considered according to empiric data obtained during field visits (2004-2008). Points, where the vegetation index permanently changed from forest to non-forest land were marked as potentially deforested. Then logical selection was

used to separate those points where removal of woody vegetation is not associated with land use change (for instance, cleaning of roadsides outside forest lands and buffer zones of

railways) or changes in vegetation index were not permanent (for instance, forest in 1990, non-forest in 1995, forest in 2000 and settlement with woody vegetation in 2004-2008 according to the NFI), and the rest of points, mostly forest roads, were noted as deforested.

Linear regression based on remote sensing data was used to elaborate prognosis for conversion of forest land to other land uses in 2004-2008. NFI data are used to estimate land

converted to settlements in 2009-2013.

Area of land converted to settlement since 1990 is estimated using satellite image analysis. Total area of land converted to settlements in 2013 is 36.21 kha.

The emissions (losses in carbon pools) are reported under category forest land converted to settlements. Carbon stock changes associated with commercial felling, including removal of

woody vegetation on forest infrastructure (roadsides, ditches etc.) are reported considering that losses in living biomass are equal to average growing stock in forest land remaining forest in a particular year. Similarly, dead wood stock in forest land remaining forest in a

particular year is considered as carbon losses from dead wood due to conversion of forest land to settlements. Instant oxidation method is considered for living and dead wood carbon pools.

Carbon stock changes in dead biomass are reported using instant oxidation method considering that all dead biomass converts to emissions in the year of the land use change. Average carbon stock in dead biomass (12.14 tonnes C ha-1 in litter and 6.0 tonnes C ha-1 in

dead wood) is used in calculations. Carbon stock in dead wood in converted land is considered to be equal to average carbon stock in dead biomass in forest land remaining forest

land in a year of the conversion.

Losses due to commercial felling in forest areas converted to settlements are reported considering that the losses are equal to average growing stock of living biomass in forest land

remaining forest in the year of conversion (BEFs, carbon content and wood density are considered as weighted (Figure 6.13) by total biomass distribution between species) averages

in a particular year of conversion.


319

Figure 6.13 Assumption for average growing stock of living biomass in forest areas converted to

settlements

The total change in soil C stocks for land converted to settlements is computed using equation 2.24 in 2006 IPCC Guidelines, which combines the change in soil organic C stocks for

mineral soils and organic soils. Change in soil organic C stocks is estimated for mineral soils with land-use conversion to settlements using Equation 2.25 in 2006 IPCC Guidelines

(equation No. 12). Emission from mineral soil due to land use change to settlements that is paved over is reported according to average carbon stock in forest mineral soil, assuming that carbon accumulated in upper 30 cm (82.6 tonnes C ha-1) partially turns into emissions within

20 years (0.8 tonnes C h-1 annually). The impact factor (FLU x FMG x FI) is 0.8.

ΔC Mineral=(SOC 0−SOC (0-T))

D

SOC=∑c , s , i

(SOC REFc,s,i⋅FLUc,s,i⋅F MGc,s,i⋅F Ic,s,i⋅Ac,s,i) , where

ΔC Mineral=annual change in carbon stocks inmineral soils , tonnesC yr-1

;

SOC 0=soil organiccarbon stock in the last year of an inventorytime

period , tonnesC ;SOC (0-T)=soil organiccarbon stock at the beginning of the inventorytime

period , tonnesC ;

D=time dependence of stock change factorswhich is the default time period fortransition betweenequilibrium SOC values , yr ;c=represents the climate zones ;

s=the soil types ;i= the set of management systems that are present∈a country ;

SOC REF=the reference carbonstock , tonnes C ha-1

;

F LU=stock change factor for land−use systems or sub-system for a particular

land−use , dimensionless ;F MG=stock change factor for management regime ,dimensionless ;

F I=stock change factor for input of organic matter , dimensionless ;

A=land areaof the stratum being estimated ,ha.

(11)


320

Land converted to settlements on organic soils within the inventory time period is treated the same as settlements remaining settlements. Carbon losses are computed using equation 2.26 in 2006 IPCC Guidelines.


Lack of knowledge about distribution of settlements with vegetation coverage and without it leads to overestimation of soil emissions, because all settlements are considered as loosing

soil carbon, in spite certain area is continuing to sequestrate carbon (like buffer zones around roads); therefore it is important to elaborate method to calculate proportion of settlements with and without vegetation coverage and different methods for calculation of soil carbon

losses in these areas. It is planned to use satellite images with high resolution in several pilot areas (representing different economic activity and dominant type of vegetation) in this study.

In spite of ability to calculate carbon stock changes in living and dead biomass since 2004, historical figures cannot be easily restored. It is planned to use high resolution satellite images to evaluate dynamics of carbon stock in living biomass in certain pilot areas since 1990 and to

extrapolate obtained results to all NFI plots to avoid potential overestimation of removals of CO2 in living biomass.



Table 6.32 Uncertainty of the settlements use data in 2013


plots

Share of NFI

plots

Standard error

of proportion

Settlements 661 4% 7%

settlements remaining settlements 570 4% 8%

land converted to settlements 91 1% 21%


Uncertainty of average carbon stock in litter in forests is 6.1 %, uncertainty of carbon stock in soil layer 0-30 cm is 15.6 %, uncertainty of dead wood stock in forests is 1.7 %, and

uncertainty of carbon stock in dead wood is 30 %. Combined uncertainty of carbon stock in dead wood is 30 %. Combined uncertainty of carbon stock change is 14.6 %.

Consistency of time series is secured by using the same activity data (NFI) for the whole

period. Extrapolation is used to elaborate prognosis of deforestation for 2009.

Uncertainty of annual carbon stock change factor (EF) for cultivated organic soils in cool

temperate climatic temperature regime is ± 90 % (IPCC Wetlands Supplement).

Uncertainties of emission factors for estimation of CH4 emissions from drained organic soils are indicated under chapter Cropland.


The QA/QC plans for the settlements' category include the QC measures based on the 2006 IPCC Guidelines. Specific QA/QC checks across the settlements methodology were done.

Potential errors and inconsistencies are documented and corrections are made if necessary. The files and documents used in preparation of the inventory are archived annually and back-up copies are made weekly.


321


Area of settlements is updated due to harmonization of the country area in the whole reporting period. Calculation of carbon stock in settlements (areas covered with trees, but not complying with thresholds of forest land definition, like roadside buffer zones) is

implemented into the inventory after completion of the most of measurements in the 2nd cycle of the NFI, demonstrating that settlements are net sink of CO2 removals in living biomass.

The removals are calculated according to the average increase of growing stock depending on the age of woody vegetation for the period before 2004, on the base of actual data for the period between 2004 and 2008 (the 1st NFI cycle) and on the basis of the 2nd cycle of the NFI

in 2009-2013. BEFs, wood density and carbon content values applied to forest land are used for settlements too.

Losses in living biomass are calculated as mortality rate applying average mortality rate (percentage of increment) in forest land in a particular year to gross increment of living biomass. Losses in dead biomass are reported as decomposition of dead wood applying 20

years transition period.

Minor changes in area converted to settlement due to implementation of the EPIM tool and

harmonization of the country area in the whole reporting period.

Major changes are applied to calculation of GHG emissions due to conversion of forest land to settlements; losses in living biomass are calculated using instant oxidation method

according to average growing stock of living biomass in forest land in a particular year. Losses in dead biomass are calculated using instant oxidation method according to average

growing stock of dead biomass in a particular year and average stock of litter in forest land in the whole period.

Annual carbon loss from drained organic soils (peat is not removed) in land converted to

settlements is calculated according equation 2.26 in 2006 IPCC Guidelines. Annual emission factor (EF) for cultivated organic soils in cool temperate climatic temperature regime is 5.0 tonnes C ha-1 yr-1 (IPCC Wetlands Supplement).

Annual carbon loss from mineral soils in land converted to settlements is calculated separately according equation 2.25 in 2006 IPCC Guidelines. Losses in mineral soil are reported

considering that carbon stock in soil in upper 30 cm layer will be lost within 20 years and assuming that 20 % of the soil carbon relative to the previous land use will be lost as a result of disturbance, removal or relocation. Country specific input data on average carbon stock in

forest soil is considered.

6.11 OTHER LAND (CRF 4.F)

According to the IPCC GPG LULUCF 2003 other lands are territories without vegetation like rocks, glaciers as well as the rest of unmanaged lands which are not included in other land use categories. According to the national land use statistics other lands include unmanaged lands,

wetlands and settlements (1 459.3 mill. ha in 2008). Instead of the official statistics since 2009 the NFI is used to estimate area of other lands. It is assumed that other lands are dunes

not covered by woody vegetation. Total area of these lands is considered constant for the whole reporting period (4.3 kha). No GHG emissions or CO2 removals are reported in this category.


322

6.12 BIOMASS BURNING (CRF 4(V))


This source category includes greenhouse gas emissions (CO2, CH4, N2O) and other emissions (NOx and CO) from biomass burning on forest land comprising wildfires and

controlled burning, as well as wildfires in grassland. The area statistics on forest wildfires are compiled by the State forest service and they are based on information given by the local

units.

Figure 6.14 shows that the most of forest fires are located around large cities and roads. The situation is similar every year.

Figure 6.14 Forest fires in Latvia in 2011-2013 (from yellow in 2011 to red in 2013)

Wildfires in grasslands are more common in south eastern part of the country and around

Riga. Concentration of wildfires in the south-east correlates with area of abandoned farmlands.

Emissions from biomass burning are represented by incineration of harvesting residues during forest logging operations. The information until 2004 was based on the study and for the 2004-2013 the information source is changed to questionnaire of private forest owners and

state forest management company. This switch leads to reduction of emissions in 2005.

Total aggregated emissions from biomass burning (wildfires and controlled burning in forest

lands and wildfires in grasslands) in 2013 were 126.9 Gg of CO2 eq. (Figure 6.15).


323

Figure 6.15 Aggregated emissions from biomass burning



Area of forest wildfires in time period between 1990 and 2013 is provided by the SFS, area of grassland burning is provided by the State fire safety service (SFSS), cartographic

information about location of wildfires in grasslands since 2005 is provided by the Rural Support Service. Total area of burnt grassland is shown inTable 6.33. For 1990-1992 no

statistical information exists. It was decided to use average burnt area of fo llowing 5 years period for 1990-1992 instead of notification key NO. Area of forest fires and biomass in burnt area is shown in Figure 6.16.

Table 6.33 Burnt area of grassland in m² and ha

Year Area, ha

1993 21

1994 98

1995 526

1996 1 224

1997 576

1998 1 255

1999 2 685

2000 2 262

2001 4 800

2002 11 547

2003 14 335

2004 6 717

2005 2 027

2006 25 806

2007 4 048

2008 1 170

2009 4 462

2010 2 495

2011 1 618

2012 1 872

2013 1 885

Total 91 429


324

Figure 6.16 Area of forest fires and biomass in burnt area



Biomass burning occurs in forest land and grassland. Taking into account that wetlands (swamps) belong to forest land according to national land use definitions, emissions

associated with wildfires in wetlands cannot be separated and are reported under fo rest lands remaining forests. No evidences of forest fires or grassland wildfires are found in land converted to forest in the NFI plots having special forest land category – burnt forest;

therefore it is considered that no forest fires takes place in affo rested area. The approach used in the Latvia's GHG inventory (reporting emissions under land use categories according to

national statistics) secures that emissions from biomass burning are not overlapping.


Tier 1 and 2 methods of calculation provided in the 2006 IPCC Guidelines were utilized. Emissions from any type of fires were calculated using equation 2.27 of the 2006 IPCC

Guidelines:

L fire=A∗M B∗C f∗Gef∗10−3

;where

L fire−amount of greenhouse gas emissions from fire, tonnes of each GHG e.g. CH 4 , N 2 O , etc . ;

A=area burnt, ha ;

MB=mass of fuel available for combustion, tonnes ha

−1. This includes biomass, ground litter

and dead wood. When Tier 1 methods are used then litter and dead wood pools are assumed

zero, except where there is a land-use change;

C f =combustion factor, dimensionless;

Gef =emission factor, g kg−1

dry matter burnt.(12)

6.12.4.1 Forest wildfires

Amount of burned biomass is considered according to average growing stock of living

biomass, dead wood and litter in a particular year. Combustion efficiency or fraction of


325

biomass combusted (dimensionless) is considered 0.45 according to Table 2.6 of 2006 IPCC Guidelines 193. Factors of emissions are shown in Table 6.34.

Table 6.34 Emission factor for each GHG (g kg¯¹ dry matter burnt)

Gas CH4 CO N2O NOx CO2

Emission factor 6.1±2.2 78±31 0.06 1.1±0.6 1550±95

6.12.4.2 Grassland wildfires

Emissions from wildfires in grassland were calculated using equation 2.27 of the 2006 IPCC

Guidelines. Mass of available fuel in grassland's fires – 2.1 t dm ha-1 (Table 2.4 of 2006 IPCC Guidelines 194), fraction of the biomass combusted 0.74 (Table 2.6 of 2006 IPCC Guidelines

195). Factors of emissions for grassland fires are shown in Table 6.35.

Table 6.35: Emission factors for grassland's wildfires196

No Gas Factor, g kg-1

dry matter burnt

1. CO 65±20

2. CH4 2.3±0.9

3. NOx 3.9±2.4

4. N2O 0.21±0.10

6.12.4.3 Controlled fires in forests

Emissions from controlled fires were calculated considering average stock of harvesting residues (BEF for conversion of stem biomass to above-ground biomass), which considerably

increased due to increase of estimates of harvesting stock. Factors of emissions are shown in Table 6.34. The following assumptions have been made for burnt harvesting residues calculation:

1990 to 2000 – 50 % of harvesting residues are left for incineration and 67 % of the left residues are incinerated, the rest are left to decay;

2001 to 2004 – 30 % of harvesting residues are left for incineration and 67 % of the left residues are incinerated, the rest are left to decay;

2005 to 2009 – 7 % of harvesting residues are left for incineration and 100 % of the left residues are burnt on-site; the rest of the residues are left for decay or extracted for

bioenergy production.

starting from 2010 – 4 % of harvesting residues are left for incineration and 100 % of

the left residues are burnt on-site; the rest of the residues are left for decay or extracted for bioenergy production.

CO2 emissions are calculated only from wildfires taking into account that carbon located in

harvesting residues is already reported as losses in living biomass. Incinerated residues are extracted from removals in dead wood.

193

Combustion factor values (proportion of prefire biomass consumed) for fires in a range of vegetation types. 194

Fuel (dead organic matter plus live biomass) biomass consumption values for fires in a range of vegetation types. 195

Combustion factor values (proportion of prefire biomass consumed) for fires in a range of vegetation types. 196

IPCC 2006 Table 2.5 Emission factors (g kg-1

dry matter burnt) for various types of burning.


326


Uncertainty in activity data (area) for biomass burning is estimated at ± 10 % based on expert judgement. Uncertainty concerning combustion efficiencies in combined is ± 10 % according to the expert judgement. Uncertainties in emission factors are based on the 2006 IPCC

Guidelines default values.


Quality control procedures named in 2006 IPCC Guidelines were done. Possible overlapping in emission/removal estimation with other sources has been checked as far as it is possible on

the base of existing data. Land areas of wildfires and controlled burning were reviewed with latest statistics. It was confirmed that all data used in this section cover whole land area of

Latvia.


Major changes were applied to this category due to utilization of improved data on harvesting residues and available biomass in forest wildfires. Area of forest wildfires as well as data of

biomass in burnt areas starting from 2011 is updated. Information about burning of harvesting residues is evaluated by forest owner's questionnaires.

Emissions from any type of fires were recalculated using equation 2.27 of the 2006 IPCC Guidelines. Improved fuel (dead organic matter plus live biomass) biomass consumption value for fires in grassland according to 2006 IPCC Guidelines Table 2.4, combustion factor

values according to 2006 IPCC Guidelines Table 2.6 and emission factors for various types of burning according to 2006 IPCC Guidelines Table 2.5 are used.

Utilized fuel biomass consumption value for wildfires in grassland is 2.1 t dry matter ha-1

(previously 2.4 t dry matter ha-1 according Table 3.4.2 of IPCC GPG LULUCF 2003).

Combustion factor value for wildfire in temperate forests is 0.45 (previously 0.34 according

to Table 3A.1.12 of IPCC GPG LULUCF 2003, boreal forests). Combustion factor value for post logging slash burn in temperate forests is 0.62 (previously 0.33 according to Table

3A.1.12 of IPCC GPG LULUCF 2003, boreal forests). Combustion factor value for wildfires in grasslands (all savannah grasslands, early dry season burns) is 0.74 (previously 0.50). Comparison of previously used emission factors according to IPCC GPG LULUCF 2003

Table 3A.1.16 and improved Table 6.36.

Table 6.36 Emission factors (g kg-1 dry matter burnt) for various types of burning

Category References CH4 CO N2O NOx CO2

Forest fires IPCC GPG LULUCF 2003

Table 3A.1.16, Kaufman

et al. (1992)

7.1 112 0.11 0.7 1531

Biofuel

burning

2006 IPCC Guidelines Table

2.5, Andreae and Merlet

(2001)

6.1±2.2 78±31 0.06 1.1±0.6 1550±95

Moist-

infertile

grassland

IPCC GPG LULUCF 2003

Table 3A.1.16, Scholes (1995)

2 59 0.10 4 1498

Savannah

and

grassland

2006 IPCC Guidelines Table

2.5, Andreae and Merlet

(2001)

2.3±0.9 65±20 0.21±0.1

0

3.9±2.4 NO


327


A new methodology on estimation of incineration efficiency in forest fires will be elaborated and different types of forest fires will be separated to account the GHG emissions more accurate. Information provided by the State forest service will be used with higher level of

accuracy by splitting different types of forest fires and following activities in the forest stands to avoid double reporting of harvested wood extracted in sanitary felling after forest fires.

Burning of harvesting residues will be evaluated by forest owner’s questionnaires.

6.13 HARVESTED WOOD PRODUCTS (CRF 4.G)


The category harvested wood products is a key source of CO2 removals. Increase of removals

in the harvested wood products during the last decade is associated with increase of harvesting rate and implementation of more advanced timber processing technologies.

Net emissions due to production of the harvested wood products are calculated according to

methodology in IPCC 2013.

The net emissions in harvested wood category in 2013 were -2142 Gg CO2. The net emissions

during the reporting period are shown in Figure 6.17. CO2 emissions due to roundwood production in deforested land is reported using instantaneous oxidation method.

Figure 6.17 Net emissions from HWP during period 1990-2013



The calculation is based on harvesting statistics collected by the State forest service,

production statistics by the Forest industry association, FAO and EUROSTAT. Linkage with land area used in the commercial felling is secured through the State forest service stand wise forest inventory system, where all commercial harvesting activities are recorded.

Only locally harvested wood is accounted in estimates.


328



Forested land is considered to be an ecosystem in all stages of its development, dominated by

trees the height of which at the particular location may reach at least 5 metres and the present or potential projection of the crown of which is at least 20 percent of the area occupied by the

forest stand197.

Deforestation is the direct human induced conversion of forest land to non-forested land. This definition is given in the IPCC KP Supplement 198.

Classification of HWP is made on the basis of IPCC KP Supplement according to table 2.8.1IPCC KP Supplement (Table 6.37).

Table 6.37 HWP categories and their subcategories

HWP category HWP subcategory

Sawn wood Coniferous sawnwood

Non-coniferous sawnwood

Wood-based panels Hardboard (HDF)

Insulating board (Other board, LDF)

Fibreboard compressed

Medium-density fibreboard (MDF)

Particle board

Plywood

Veneer sheets

Paper and paperboard -


The net emissions from the harvested wood products are calculated according to the methodology elaborated by S. Rüter, 2011. The methodology corresponds to Tier 2 for HWP in IPCC KP Supplement for HWP. Three main HWP groups are used in calculations –

sawnwod, wood based panels and paper and paperboard with more detailed division on products in Table 6.38.

The proportion is calculated by equation No. 14 to estimate share of harvesting stock extracted due to deforestation and is used to calculate share of domestic industrial roundwood by equation. The data to calculate proportion is obtained from Central statistical bureau of

Latvia and is collected by the State forest service. This proportion is applied to HWP to estimate how much HWP could be produced from wood obtained in deforested areas. Instant

oxidation is applied to the proportion of HWP potentially produced from the wood obtained in deforested areas.

IRW P (i)=(1−D∗M

avg

MH total

)∗IRW total (i ); where

IRW P(i)= production of industrial roundwood excluding roundwood fromdeforested area in

year i ,Gg C yr−1

;

D=annual deforested area , ha ;

Mavg

=average growing stock incountry , m3ha

−1;

MHtotal

=total harvested stock volume ,m3;

IRW total (i )=total industrial domestic roundwood production.

(13)

197

Legislation of the Republic of Latvia. Law on forests. http://likumi.lv/doc.php?id=2825 198

IPCC 2014, 2013 Revised Supplementary methods and Good Practice Guidance Arising from the Kyoto protocol, Hiraishi, T., Krug, T., Tanabe K., Srivastava N., Baasansuren, J., Fukuda, M. and Troxler, T. G. (eds) Published: IPCC, Switzerland.


329

Historical data on production, import and export of HWP as well as share of different types of the products are used in calculation. The coefficients and numeric values used in calculation are default conversion factors recommended in IPCC KP Supplement (Table 2.8.1) and are

provided in Table 6.38 and Table 6.39. Input data in calculation are extrapolated to 1900. Net emissions due to decay of harvesting residues are reported separately considering 20 years

transition period for above and below ground biomass. Instant oxidation is considered for the firewood assortment.

Table 6.38 Assumptions for estimation of carbon stock in harvested wood products

HWP categories Density (oven dry mass over air

dry volume), Mg m-3

C conversion factor (per air

dry volume), C m-3

Sawnwood – Coniferous 0.450 0.225

Sawnwood – Non-Coniferous 0.560 0.280

Veneer sheets 0.505 0.253

Plywood 0.542 0.267

Particle board 0.596 0.269

Hardboard 0.788 0.335

MDF (Medium density fibreboard) 0.691 0.295

Fibreboard compressed 0.739 0.315

Insulating board 0.159 0.075

- oven dry mass over air dry

mass, Mg Mg-1

per air dry mass, Mg C Mg-1

Paper and paperboard (aggregate) 0.900 0.386

Share of locally originated wood in harvested wood products is calculated using equation No. 15.

f IRW (i)=IRW P( i)−IRW EX (i)

IRW P(i)+IRW(IM )

( I )−IRW EX (i);where

f IRW (i)=share of industrial roundwood for the domestic production of HWP originating

from domestic forests in year i ;

IRW P(i)= production of industrial roundwood excluding roundwood from

deforested area in year i, Gg C yr−1

;

IRW EX (i)=export of industrial roundwood in year i , Gg C yr−1

;

IRW( IM )

( I )=import of industrial roundwood in year i , Gg C yr−1

.

(14)

Organic carbon in harvested wood products originated from local wood is calculated using equation No. 16.

CHWP= f IRW (i)∗HWP D ;where

CHWP=organic carbon in domestically produced HWP excluding HWP

from wood produced in deforested area, Gg C yr−1

;

HWP D=Domestical production of HWP ,Gg C yr−1

.

(15)

The rate of the CO2 emissions and removals in harvested wood products is calculated using equations No. 17 and 18.


330

C (i+1)=e−k∗C (i)+[

1−e−k

k]∗inflow(i); where

C (i+1)=annual carbon stock ,Gg C yr−1

;

e=exponential constant ;

k=decay constant for each HWP category ,units yr−1

;

C (i)=carbon stock∈ particular category at the begining of year i ,Gg C ;

inflow (i)=the inflow tothe particular HWP category during year i ,Gg C yr−1

;

k=ln (2)

HL; where

HL=the number of years it takes to lose one-half of the material currently

in the pool, yr

(16)

ΔC(i)=C (i+1)−C (i);where

ΔC (i)=carbonstock changeof the HWPcategory during year i ,Gg C yr−1

. (17)

Table 6.39 Common coefficients to estimate balance between CO2 emissions and removals in harvested

wood products

Factors Numeric value

Common coefficients

e 2.718282

ln(2) 0.6931

Assortment s pecific coefficients:

Assortment Sawnwood Platewood Pulpwood

HL 35 25 2

k 0.02 0.03 0.35

e-k

0.98 0.97 0.71

k=1−ln (2)

H∗L

0.99 0.99 0.85

The equations of calculation of the harvested wood products are included into the National tool for calculation of the net emissions due to forest management as separate module.


Uncertainty level of the activity data for the whole time series is assumed 15 % in 1990-2013.


Harvesting rate and production of harvested wood products used in the calculations is compared with other data sources, particularly statistics collected by the Latvia Forest industry federation.

6.13.7 Category-specific recalculations, if applicable, including changes made in

response to the review process

Minor recalculations have been done due to the changes in conversion factors in Table 9.38. Double counting of emissions (as instant oxidation under land converted from forest to other

land use categories and as emissions from HWP) is avoided by applying proportion principle to estimation of HWP originated due to commercial felling and conversion of forest land.


331


Impact factors of more detailed species composition on structure of assortments will be included into the calculations in the next inventory.

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37. Salm, J.O., 2012. Emission of greenhouse gases CO2, CH4, and N2O from Estonian transitional fens and ombrotrophic bogs: the impact of different land-use practice (Doctoral thesis). Tartu Ülikooli Kirjastus, Tartu.

38. Zariņš, J. Meža Statistiskās Inventarizācijas Parauglaukumu Mērījumu Interpolācijas Projekts, Izmantojot Satelītu Uzņēmumu Analīzes Iespējas (pārskats Par Meža

Attīstības Fonda Pasūtīto Pētījumu);

39. Zemkopības ministrija, ―Meža statistiskās inventarizācijas veikšanas un mežaudzes sekundāro parametru aprēķināšanas metodika (instrukcija Nr. 10 no 17.03.2004.)‖

(Latvijas Republikas Zemkopības ministrija;

40. Zigurds Saliņš, Mežs - Latvijas Nacionālā Bagātība (Jelgava: Jelgavas tipogrāfija,

2002); Zigurds Saliņš, Meža izmantošana Latvijā: stāvoklis, perspektīvas (Jelgava [Latvia]: LLU Meža izmantošanas katedra, 1999).


335

7. WASTE (CRF 5)


7.1.1 Quantitative overview

Waste management has acquired prior significance in the environmental protection policy as one of the instruments for sustainable use of natural resources. The main directions in the

waste management are the development of the construction of polygons and collecting system for non–hazardous municipal waste and the development of system for the collection and treatment of hazardous waste. At the moment 11 non-hazardous waste polygons and two

polygons for hazardous waste got A category permit according to IPPC directive. Biogas collection and use for energy production from biodegradable wastes and sludge is set as one

of priorities in Latvia.

Main activity data sources for GHG emissions calculations in Waste sector are databases199 ―3-Wastes‖, ―2-Water‖ and data from CSB.

Data on hazardous waste in Latvia have been collected and compiled by LEGMC since 1997, but data on municipal (non-hazardous) waste since 2001. Until then the waste volume was

determined on the basis of separate pilot projects and the assessments and projections by waste management experts.

Since 2002, databases about hazardous and municipal wastes are combined in one database

―3-Wastes‖. Data in this database are taken from State Statistical survey about wastes, which occurs annually.

Statistical survey about wastes must fill all enterprises, which have permits on polluting activities (A and B category) and all enterprises, which have permits on waste management operations. To estimate disposed waste amounts in preliminary years; data about population

and Gross domestic product (GDP) are taken from CSB.

―2-Water‖ database was developed by LEGMC as well. Data of water abstraction and use,

wastewater treatment and discharge have been collected since 1991 in the frame of state statistical survey ―2 – Water‖. State statistical survey ―2-Water‖ must be reported by all enterprises which have issued permits on water use, water resources use or mineral deposits

quarry use, or IPPC permit. Both LEGMC "2-Water" and CSB data are used as activity data for emission calculation - CSB and "2-Water" data for CH4 emission from Domestic Waste

Water Handling and Sewage Sludge, N2O emission from Industrial Waste Water Handling and NMVOC emission, and CSB for CH4 emission from industrial waste water handling and N2O from Domestic Waste Water Handling.

7.1.2 Description

GHG emissions from Waste sector have been fluctuated from 1990-2013. In 2013, emissions were approximately 1,97 % lower than in 1990. In 2013, emissions from the Waste sec tor

were 749,54 Gg CO2 equivalents; it contributes about 6,8 % of total GHG emissions (excluding LULUCF).

199

http://parissrv.lvgmc.lv/public_reports

http://parissrv.lvgmc.lv/public_reports


336

Figure 7.1 Total GHG emissions from Waste sector 1990-2013 (Gg CO2 equivalents)

Fluctuations in total GHG emissions in waste sectors could be explained with changes of

economic situation in last 20 years (Figure 7.1). Some industry sectors were almost closed in the middle of 90-ties. Biggest influence to total emission trend gives GHG emissions from

Waste water handling.

Figure 7.2 GHG Emissions in Waste subsectors200 1990-2013 (Gg CO2 equivalents)

Emissions from Waste Incineration (WI) and Composting (Comp.) in las t year’s, when

emissions from these sectors were calculated, are very small in comparison with other sectors – Solid waste disposal (SWD) and Waste water handling (WWH) (Figure 7.2).

According to the information from LEGMC201 the total generated amount of waste are shown

in Table 7.1.

200

Biological treatment of solid waste and Incineration and burning of waste on secundary axis


337

Table 7.1 Generated wastes in Latvia (Gg)

Year Municipal (all non-

hazardous) wastes Hazardous wastes Total

2006 1420.46 54.372 1474.832

2007 1386.57 41.605 1428.175

2008 1368.79 46.400 1415.160

2009 1033.91 55.563 1089.473

2010 1131.404 55.089 1186.493

2011 1535.057 58.476 1593.533

2012 1799.440 85.121 1884.561

2013 1902.007 109.23 2011.237

N2O is emitted as the release from sewage purification system and waste incineration.

Data on CO2 and N2O emissions from waste incineration are available only since 1999.

Emissions are estimated from 1990, data on incinerated amount 1990 – 1998 are extrapolated according to waste amounts. Calculation of indirect GHG emissions from cremation is shown in Section 7.4.1.1. Emissions from waste incineration with energy recovery are counted under

energy sector.

CH4 and N2O are emitted from waste composting. Data available only from 2003, when

composting facilities start to report within state statistical survey about wastes composting. For emission calculations 2006 IPCC Guidelines and default factors were used.

7.2 SOLID WASTE DISPOSAL (CRF 5.A)


Methane emission is calculated from SWD (Table 7.2). It is main GHG source from waste sector in Latvia. Compare to year 2012, emissions of CH4 in 2013 decrease due to higher CH4 recovery rate. Compare to year 1990 CH4 emissions increase by 6 Gg due to First order decay

calculation method.

Table 7.2 Reported emissions under subcategory Solid Waste Disposal on Land


5.A 1 Managed Waste Disposal on Land CH4, NMVOC

5.A 2 Unmanaged Waste disposal Sites CH4, NMVOC

5.A 3 Other Not occurring

To estimate CH4 emissions with First Order Decay (Tier2) method from landfills, time series for disposed waste amounts till 1970 was developed. The base year for disposed amount

estimation is 1996, when research202 about biggest landfills was done. All calculations are done according to 1996 year amount. In that research total generated solid municipal waste

amount is estimated as 2 379 829 m3. It is assumed that outstanding part of these wastes is going to landfills. Amount of disposed tons are calculated - 2 379 829 m3*0.2 = 475 965 tons. Waste amounts 1997 – 2001 was estimated like equal growth between 1996 and 2002

amount. Amounts 1970 – 1995 were estimated according to GDP and population changes.

201

http://www.meteo.lv/public/28759.html 202

―Research about solid waste management in Latvia‖, 1998, Ltd GEO Consultants


338

Value of waste density (0.2 t/m3) is taken from Latvian Environment agency (2002) ―Handbook in use of factors for inventory of municipal waste in transition from volume to a unit of weight‖203.

Table 7.3 Estimated Disposed amounts from 1970 – 2002

Year Population

Disposed

solid waste

amount

(Gg)

GDP/inha

bitant

(LVL -

2000

prices)

Disposed

wastes

from

urban

areas

(Gg)

Disposed

wastes

from

rural

areas

(Gg)

1970 2351903 409.59 1230 249.95 159.65

1971 2368671 419.60 1286.4 260.15 159.45

1972 2385439 429.60 1342.8 266.35 163.25

1973 2402207 439.61 1399.2 276.95 162.65

1974 2418975 449.61 1455.6 283.25 166.36

1975 2435744 459.62 1512 294.15 165.46

1976 2452512 469.62 1568.4 300.56 169.06

1977 2469280 479.62 1624.8 311.76 167.87

1978 2486048 489.63 1681.2 318.26 171.37

1979 2502816 499.63 1737.6 332.18 167.46

1980 2508728 508.59 1794 335.67 172.92

1981 2514640 517.55 1850.4 348.50 169.05

1982 2529255 527.35 1906.8 353.32 174.02

1983 2543870 537.15 1963.2 365.26 171.89

1984 2558486 546.94 2019.6 371.92 175.02

1985 2573101 556.74 2076 384.15 172.59

1986 2587716 572.04 2169.4 393.01 179.03

1987 2607822 587.87 2262.8 405.63 182.24

1988 2627928 603.70 2356.2 416.55 187.15

1989 2648034 619.53 2449.6 430.06 189.47

1990 2668140 635.36 2543 439.97 195.39

1991 2634628 599.65 2324.6 415.62 184.02

1992 2601116 563.93 2106.2 389.90 174.03

1993 2567604 528.22 1887.8 362.42 165.80

1994 2534092 492.50 1669.4 339.96 152.54

1995 2500580 456.79 1451 314.36 142.43

1996 2469531 475.96 1600 326.98 148.98

1997 2444912 506.30 1693.75 347.36 158.94

1998 2420789 536.64 1787.5 368.00 168.64

1999 2399248 566.98 1881.25 387.30 179.68

2000 2377383 597.32 1975 406.73 190.59

2001 2364254 627.66 2149 426.81 200.85

2002 2345768 658.00 2304

Figures in bold is primary data from National statistics204 (Table 7.3). All other years are estimated according to these figures. Disposed amount are estimated according to GDP

and population changes. Population amounts for year 1971 -1978, 1982 – 1985, 1987 – 1988, 1991 – 1994 are calculated according to available amounts in nearest years. GDP data from 1970 – 1979 are estimated like the same decrease from 1985 - 1980.

203

http://www.lvgmc.lv/fs/CKFinderJava/userfiles/files/Vide/Atkritumi/statistika/Rokasgramata_atkr_faktori.pdf 204

Statistical Yearbook of Latvia 2004, CSB, 2005


339

Landfills from 1970 – 2001 are estimated as unmanaged205. Disposed amount are divided between rural and urban areas, according population proportion between these areas. Methane correction factors (MCF) for CH4 emissions calculations in urban areas (deep sites -

0.8) and rural areas (shallow sites - 0.4) are used.

Data about waste disposal on land for 2002 - 2013 are taken from database ―3-Wastes‖

(Table 7.4). Starting from year 2002, according to data base information, biggest sites could be estimated as managed sites (polygons) and MCF-1 is starting to use. For each year (2002-2013) in polygons disposed amount are determine according to disposing site profile from ―3-

Wastes‖ data base.

Table 7.4 Disposed solid waste amounts from 2002-2013 (Gg)

Year

Total disposed

solid waste

amount

Disposed in

polygons (MCF-

1)

Disposed in

deep

unmanaged

sites (urban

area, MCF-0.8)

Disposed in

shallow

unmanaged

sites (rural

area, MCF-0.4)

2002 658.0 217.46 303.97 136.57

2003 578.9 207.74 256.07 115.05

2004 631.7 282.84 240.71 108.15

2005 610.9 370.43 165.89 74.53

2006 670.0 454.39 148.78 66.84

2007 775.1 553.27 153.09 68.78

2008 704.8 566.89 95.12 42.74

2009 637.5 549.5 60.71 27.28

2010 605.4 586.9 12.73 5.72

2011 548.7 543.5 2.6 2.6

2012 529.5 525.568 1.98 1.98

2013 534.2 534.2 0 0

According to information in landfill research, number of active waste disposal sites decreased from 558 in 1997 to 12 in 2013. All calculations are done for unsorted wastes, because 95% of disposed wastes are reported as unsorted.

According to Waste management plan 2013 – 2020, in Latvia operates 11 waste disposing polygons, all other waste disposal sites are planned to close. In 2013 – 11 solid

waste polygons operates, all these sites are estimated as managed. When this plan will be realized, data collection about disposed municipal wastes amounts and its composition will become more accurate. Disposed solid waste amounts in Latvia are shown in Figure 7.3.

205 ―Degradable organic carbon in disposed wastes‖, 2011, Ltd Virsma


340

Figure 7.3 Disposed waste amounts in Latvia (Gg)

Since October 2002, CH4 recovery from landfills are in progress. For 2010 only in four waste facilities (SIA Getlini EKO, SIA Liepajas RAS, SIA ZAAO Daibe, SIA Zemgale Eko) CH4

recovery was realized. In SIA Getlini EKO polygon methane was collected from old waste disposing area and from new waste disposing cells, which is specially build for waste

disposing with biogas collection. In SIA Liepajas RAS methane collection also is developed in old landfill Skede and in new polygon Kivites. In SIA ZAAO polygon Daibe methane collection was started in the middle of 2009. In SIA Zemgale Eko polygon Brakski methane is

started to collect in year 2013. In total 6.92 Gg of CH4 was collected and recovered in 2013. Recovered methane amount is presented in Figure 7.4.

Figure 7.4 Recovered CH4 from waste dis posing (Gg)


341

According to Latvia’s Waste Management plan 2013-2020, CH4 recovery from landfills is one of priorities in waste management. CH4 emission from waste disposing in SWD sites is presented in Figure 7.5.

Figure 7.5 CH4 emissions from waste disposing (Gg)


2006 IPCC Guidelines (Tier 2) method is used for CH4 emissions calculation and is based on equations:

where: Lo – potential annual methane emission (Gg);

MSWL - annual MSW landfilled (Gg);

MCF – CH4 correction factor, depend of waste disposal site type;

Managed sites – 1

Deep unmanaged sites - 0.8

Shallow unmanaged sites - 0.4

DOC – degradable organic carbon (0.17);

DOCF – fraction of DOC dissimilated (0.6);

F – fraction of CH4 landfill gas (0.5);

R – recovered CH4 (Gg);

CH4 – methane real emission;

A – normalisation factor A=(1-e-k)/k

k- methane generation coefficient (1/y) (0.05);

x – calculation starting year;

t – inventory year;

R (t) – methane recovery in year t;

Lo CH4 potential emission= MSWL *MCF * DOC * DOCF * F * 16/12

CH4 year emission (t) = [CH4 (t) – R(t)] *(1 – OX)

CH4 generated in year t (Gg/yr) = ∑x [ (A*k*MSWL(x)*Lo(x))*e-k(t-x)

]


342

OX – oxidation factor (default 0)

3 separate calculations are done for 3 types of landfills:

1. polygons (MCF-1), 2. deep unmanaged sites (MCF-0.8) 3. shallow unmanaged sites (MCF-0.4)

Total methane emission is counted together from 3 values.

Fraction of CH4 in landfill gas is estimated as 0.5 according to information, which is received

from methane collection enterprises. Methane collection enterprises provide information about collected methane amount and also about methane concentration in landfill gas. Methane concentration is mutable, it diversifies from 0.47 – 0.54 depending on time frame

and weather conditions.

DOC value is used as 0.17, according to research what is carried out in Latvia (―Degradable

organic carbon in disposed wastes‖, 2011, Ltd Virsma). All other factors are default from IPCC guidelines.

7.2.3 Uncertainties and times series consistency

To calculate CH4 emissions from SWD many emission factors are used. According to 2006

IPCC Guidelines for each factor uncertainty is estimated as:

DOC – 20%;

DOCf – 30%;

MCF – 10%;

CH4 fraction F – 5%;

k – 40%.

22222

. kFMCFDOCfDOCEFuncert

Combined uncertainty for emission factors from SWD is 52%.

Uncertainty for activity data is estimate as 20 %. For all years same methodology and

coefficients for calculation are used (Tier 2). Amount of disposed wastes are estimated in different ways for time period since 1970. There are no other possibilities for Latvia, because waste statistics are available only from 2002.


QA/QC procedure for waste disposing is done. Mistakes, found in emission calculation during QA/QC procedure, were corrected within this submission. Time series consistency check for IEF on 10% changes was done.

Disposed waste amount from year 2002 is taken from waste data base ―3-Wastes‖. Data in this data base are checked and approved by Regional Environmental Boards.

National factor of DOC is determined in national research ―Degradable organic carbon in disposed wastes‖, 2011, Ltd Virsma. Research is available in QA/QC documentation.

Distribution between managed and unmanaged also is described in ―Degradable

organic carbon in disposed wastes‖, 2011, Ltd Virsma.


343

Information about CH4 recovery is taken directly from polygon reports. These reports are collected and checked by LEGMC every year. Report is published in LEGMC website every year. Information about distribution between flaring and energy recovery is described.

In Latvia case it is impossible correctly estimate distribution of CH4 recovery between managed and unmanaged sites, because old landfill and new disposing cell are located in one

site. Collected CH4 is counted together, but that does not affect final CH4 emissions.

7.2.5 Source-specific recalculation

No specific recalculations are done.

7.2.6 Source specific planned improvements

Estimation of MCF will be done for Latvia landfills for all time series. It is planned to make

an efforts within the programme ―European Economic Area Financial Mechanism 2009-2014 – ―National Climate Policy‖ to improve MCF uses. Improvement will be undertaken for next submission.

7.3 BIOLOGICAL TREATMENT AND SOLID WASTE (CRF 5.B)

7.3.1 Composting (CRF 5.B.1)


Under Composting 5.B.1 sector emissions from waste composting are calculated, Composting is set as one of priorities in waste treatment in Latvia. For composting biological degradable

wastes are useful. In Latvia these are mostly ―park - garden‖ and ―food production‖ wastes. Composting in private households was very popular for many years, but about these activities no correct data or estimation about composted waste amounts. Data become available since

2003, when waste treatment companies start waste composting and get IPPC permits on this activity.

Table 7.5 Reported emissions under composting


5.B.1. Compost production CH4, N2O

From composting CH4 and N2O emissions are calculated according 2006 IPCC Guidelines. In previous IPCC Guidelines was not provided emission factors for composting. Data about

composted amounts are taken from ―3-Waste‖ database. In year 2011 was increase of composted amounts in composting enterprises.


344

Figure 7.6 Total emissions from waste composting in CO2 equivalent (Gg)


2006 IPCC Guidelines are used for composting calculations. Composted waste amount is multiplied by emission factor. Composted waste amount is taken from ―3-Waste‖ database,

R3 - Recycling/reclamation of organic substances that are not used as solvents (including composting and other biological transformation processes), recovery operation for determination of composted amounts was used. Not all amounts, which classified under

recovery as R3, are composted. To determine composted amount, each enterprise, which reports with recovery operations R3, working profile must be taken in account.

Default emission factors for composting were used from 2006 IPCC Guidelines:

1. 4 g CH4/ kg composted wastes;

2. 0.3 g N2O/ kg composted wastes.

Table 7.6 Composted waste amounts and emissions

Year Composted amount (Gg) CH4 emission (Gg) N2O emission (Gg)

2003 2.224 0.008896 0.0006672

2004 7.905 0.031620 0.0023715

2005 6.564 0.026256 0.0019692

2006 11.698 0.046792 0.0035094

2007 9.416 0.037664 0.0028248

2008 9.282 0.037128 0.0027846

2009 15.11 0.06044 0.004533

2010 18.55 0.0742 0.005565

2011 23.699 0.094796 0.0071097

2012 17.62 0.07048 0.005286

2013 14.367 0.05747 0.00431

7.3.1.3 Uncertainties and times series consistency

Emission factor uncertainties are calculated according range, which is published in IPCC

Guidelines 2006 Volume 5, Chapter 4, For N2O range is 0.06 – 0.6, for CH4 0.03 – 8, Uncertainty for N2O emission factor is 90%, for CH4 – 100%, Activity data uncertainty is

estimated as 20%, Time series for composting begins in 2003, for previous years data are not


345

available, because industrial composting do not happening in Latvia, Composting in private garden occurs all time in Latvia, but there is no any estimation available on these amounts.


Composted wastes amounts are taken from waste data bases. Data in this data bases are checked and approved by Regional Environmental Boards.


No recalculations.


New waste recovery classification in Latvia comes in force in 2013. Determination of composting will be more precise, because special R code will be used for composting.

It is planned to make an efforts within the programme ―European Economic Area Financial

Mechanism 2009-2014 – ―National Climate Policy‖ to improve this section. Research about composted amounts in households and country specific emissions factors for composting will

be realized in year 2015.

7.3.2 Anaerobic Digestion at Biogas Facilities (CRF 5.B.2)

Anaerobic Digestion at biogas facilities occurs in Latvia. All emissions are counted under energy sector because all biogas are used for energy production.

7.4 INCINERATION AND OPEN BURNING OF WASTE (CRF 5.C)

7.4.1 Waste Incineration (CRF 5.C.1)


Data on amount of waste incinerated in Latvia can be found in databases that are created and maintained by LEGMC. Data on hazardous waste incineration are available starting 1999. In the hazardous waste data base there is a separate entry for 1997-2001 on the amount of

incinerated waste. Starting 2002 the database also contains entries for recovery (R) and disposal (D) of waste, which is consistent with the EU legislation.

Table 7.7 Reported emissions under category Waste Incineration


5.C 1 Biogenic (cremation) SO2, NMVOC, CO, NOx

5.C 2 Other – non biogenic (industrial and hospital wastes) CO2, N2O, SO2, NMVOC, CO,

NOx

Currently there are no large amounts of waste being incinerated in Latvia without energy recovery. The main source of emissions is attributed to the hazardous and clinical waste

incineration. The amounts of incinerated clinical waste are registered in the hazardous waste database (from 2002 in ―3-Waste‖ data base) as Health service for humans and animals as

well as related research waste. The rest of the incinerated waste from hazardous waste database is considered as hazardous (industrial) wastes.

In 2001 large increase of emissions are shown, because one enterprise reported huge amount

of incinerated wastes, but another year’s amount is much smaller. Incinerated amounts for


346

years 1990 – 1998 is extrapolated according to average value of incinerated amount for years 2002 – 2013 what is attributed to disposed wastes value.

In latest years incinerated amount of waste decrease due to hazardous waste incineration

facility do not work in full capacity and some of them are closed. CO2 emissions from Waste Incineration are presented in Figure 7.7.

Figure 7.7 CO2 emissions from Waste Incineration by waste type (Gg)

Data about burned bodies available from Riga crematorium since 1994, and calculations of its emissions are being made in accordance with the EMEP/EEA guidebook 2013 methodology. The crematorium is being under operation since December 22nd, 1994. The main gases

emitted during cremation are SOx, NOx, CO, and NMVOC, and all of them have to be reported in the inventory as indirect GHG. These amounts are counted in Incinerated Biogenic

Waste sector (Table 7.8).

Table 7.8 Burned bodies in Riga crematorium

Year Burned bodies

1994 54

1995 564

1996 819

1997 817

1998 869

1999 982

2000 1127

2001 1297

2002 1293

2003 1389

2004 1391

2005 1529

2006 1630

2007 1959

2008 2227

2009 1977

2010 2102

2011 2158


347

Year Burned bodies

2012 1970

2013 2000


According to the 2006 IPCC Guidelines emissions of CO2 and N2O have to be calculated from the Waste Incineration. CH4 emissions in well- functioning incinerators are usually very

small. The CH4 emissions are particularly relevant for open burning. Usually CO2 emissions are substantially larger than emissions of N2O. Emissions from waste incineration without energy production are considered under the Waste sector, while emissions from waste

incineration with energy production are considered under the Energy sector.

CO2 emissions were calculated using following 2006 IPCC Guidelines equation:

CO2 emissions = i[SWix x CF i x FCF i x OXi x 44/12] Gg/year,

where:

i = waste type (hazardous waste, clinical waste);

SWi = amounts of type i waste incinerated. (Gg/year);

CFi = carbon contents in the type i waste;

FCFi = fossil carbon contents in the type i waste;

OXi = oxidation factor of type i waste;

44/12 = conversion of C into CO2

There are no national factors for carbon and fossil carbon amounts in each type of waste; therefore default factors from the 2006 IPCC Guidelines were used (Table 7.9).

Table 7.9 Default emission factors for CO2 emission calculation

Clinical waste Hazardous waste

C contents in waste (CCW) 0.6 0.5

Fossil C contents in waste (FCF) 0.4 0.9

Oxidation factor (OX) 100% 100%

N2O emissions from Waste incineration are calculated according to 2006 IPCC Guidelines Volume 5 Table 5.6. Factor 100 (g N2O/ t waste) is used. This factor is determined for

Industrial waste in wet weight. Latvia’s incinerated hazardous wastes are mostly used oils, solvents and other liquids. Clinical wastes are not dried before burning. The same factor also is used for clinical wastes N2O emissions calculation.

Table 7.10 Incinerated waste amounts without energy recovery

Year

Hazardous

waste (Gg)

Clinical

waste

(Gg)

Total

(Gg)

1990 0.429082 0.116729 0.545812

1991 0.404964 0.110168 0.515131

1992 0.380845 0.103606 0.484451

1993 0.356726 0.097045 0.453771

1994 0.332607 0.090484 0.423091

1995 0.308488 0.083922 0.39241

1996 0.321434 0.087444 0.408878

1997 0.341924 0.093018 0.434942

1998 0.362414 0.098592 0.461006

1999 0.34721 0.20142 0.54863

2000 0.69028 0.05641 0.74669

2001 1.31927 0.21331 1.53258


348

Year

Hazardous

waste (Gg)

Clinical

waste

(Gg)

Total

(Gg)

2002 0.165643 0.032247 0.19789

2003 0.201813 0.040607 0.24242

2004 0.210125 0.112325 0.32245

2005 0.215127 0.102127 0.317254

2006 0.78616 0.26189 1.04805

2007 0.5405 0.350861 0.891361

2008 0.29975 0.012361 0.312111

2009 0.200 0.011663 0.211663

2010 0.200 0.012843 0.212843

2011 0.0063 0.37883 0.38513

2012 0 0.36691 0.36691

2013 0 0.48572 0.48572

Indirect gases (NMVOC, CO, SO2, NOx) are calculated from waste incineration according to EMEP/EEA emission inventory guide book 2013 (Table 7.11).

Table 7.11 Emission factors for indirect gases

Clinical wastes (kg/Mg) Hazardous waste (kg/Mg)

NMVOC 0.7 7.4

CO 0.19 0.07

SO2 0.24 0.047

NOx 2.3 0.87

Cremation

Indirect GHG emissions from cremation were calculated by multiplying the number of bodies

burned with the corresponding emission factor. Calculations were based on emission factors given by the EMEP/EEA emission inventory guide book 2013 (Table 7.12).

Table 7.12 Emission factors for indirect gases from cremation

Indirect GHG Emission factor (kg/body)

NMVOC 0.013

CO 0.140

SO2 0.113

NOx 0.825


Emission factors uncertainty for CO2 is estimated as 40%, according 2006 IPCC Guidelines, because no correct information on carbon content in incinerated wastes is known. Uncertainty

for N2O emission factor is 100%. Uncertainty for activity data is estimate as 20 %.


QA/QC procedure for waste incineration is done. Inconsistencies between years were not found. Incinerated wastes amounts are taken from waste data bases. Data in this data bases are

checked and approved by Regional Environmental Boards.


349


Firstly emissions estimated for years 1990 – 1998.


No planned improvements.

7.4.2 Open Burning of Waste (CRF 5.C.2)

Open burning of wastes is reported as NE (Not estimated). There are no any data available about burned wastes amounts in households.

7.5 WASTEWATER TREATMENT AND DISCHARGE (CRF 5.D)

7.5.1 Domestic Wastewater (CRF 5.D.1)


The emission sources cover handling of collected and uncollected domestic waste water for

CH4 from both waste water and sewage sludge and N2O emissions from human sewage.

In most cases urban waste water is treated in aerobic systems in Latvia. However, the accurate

breakdown of amount aerobic and anaerobic processes during treatment of municipal waste water is unknown.

Therefore, data on type of treatment plant and its treatment level is available within national

database ―2-Water‖, and all the treatment plants is distributed by their type and level of treatment.

Totally, taking into account of recovered CH4 as well, emissions from Domestic Waste Water Handling sector made 64.8 Gg CO2 eq. in 2013 (Figure 7.8), what makes decrease of 70.9% in comparison to emissions of 1990 and increase of 12.7% in comparison to emissions of

2012.


350

Figure 7.8 Emissions from domestic Waste Water Handling sector (Gg CO2 eq.)


Calculation of CH4 emission from Domestic Waste Water Handling is based on amount of

BOD5 (biochemical oxygen demand, 5-day test) produced by national population. However, different methane conversion factors (MCFs) are applied depending of type and level of treatment of certain treatment plant. Mechanically treated load are calculated, using maximum

value of MCF. Data on treatment type and level of certain waste water treatment plant serving certain number of population is available in national data base ―2-Water‖206, collecting

treatment plant- level data on water abstraction and use, treatment and discharge. Distribution of national population by type and level of waste water treatment was extrapolated for period, uncovered by water statistics (1990-1999).

IPCC default formula (2006 IPCC Guidelines, chapter 6.2.2 „Domestic Wastewater‖) was used for calculation of CH4 emission from Domestic Waste Water Handling sector. However,

distribution of national population by treatment type and level is used instead of distribution of national population by income level.

RSTOWEFUEmissionsCHi

ii

)()(4

where

CH4Emissions – CH4 emissions in the inventory year, kg CH4/yr

TOW – total organics in waste water in inventory year, kg BOD/yr

S – organic component removed as sludge in inventory year, kg BOD/yr

Ui – degree of national population receiving certain waste water treatment type and level, % i –waste water treatment type and level (well-managed biological, poor-managed biological, non-biological and no collection

and no treatment)

EFi – emission factor for each treatment type fraction, kg CH4/kg BOD

R – amount of CH4 recovered in inventory year, kg CH4/yr

ioi MCFBEF

206

http://parissrv.lvgmc.lv/public_reports/#viewType=water2reports

http://parissrv.lvgmc.lv/public_reports/#viewType=water2reports


351

where: EFi – emission factor for each treatment type fraction, kg CH4/kg BOD i –waste water treatment type and level (well-managed biological, poor-managed biological, non-biological and no collection and no treatment)

Bo – maximum CH4 producing capacity, kg CH4/kg BOD MCFi – methane correction factor for each treatment type and level

365001.0* IBODPTOW where TOW – total organics in waste water in inventory year, kg BOD/yr P – country population in inventory year, persons BOD – country-specific per capita BOD in inventory year, g/person/day

I – correction factor for additional industrial BOD discharged into sewers CH4 emissions from anaerobic sewage sludge were calculated using default formula from

„Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories: Reference Manual‖; chapter 6.3.5 „Methodology for Estimating Emissions from Wastewater Handling‖.

In this case IPCC Guidelines 1996 were used because 2006 IPCC Guidelines do not provide methodology to estimate emissions from anaerobic sewage sludge.

EFTOSSM

where: SM – total CH4 emission from sewage sludge, kg CH4 TOS – total organic content of sludge, kg COD/yr EF – emission factor for sludge, kg CH4/kg COD

Methane Conversion Factors (MCFs) were applied depending of treatment type and level. 2006 IPCC Guidelines were used as source of MCF values; however, expert judgment was

performed to choose values applicable for Latvian conditions (Table 7.13).

Table 7.13 MCF values applied depending on type and level of treatment

Treatment type and level MCF

Biological treatment with secondary or higher treatment level 0

Biological treatment with treatment level lower than secondary 0.3

Mechanical and chemical treatment 0.8

No treatment 0.5

Organic load – 60 g of BOD per person per day – is determined by national legislation (Cabinet Regulation No. 34 "Regulations regarding Discharge of Polluting Substances into

Water" (22.01.2002)).

Activity data, used for calculation of CH4 emissions from domestic waste water are summarized in the following Table 7.14.

Table 7.14 Activity data for calculation CH4 emissions from Domestic Waste Water Handling sector

Year Population

receiving well-managed biological

treatment

Population

receiving poor-managed

biological

treatment

Population

receiving non-biological

treatment

Population

receiving no treatment

Amount of

anaerobic sludge, t/y

Amount of

recovered CH4, Gg/y

1990 1 459 034 410 363 69 301 729 442 19 015 0

1995 1 367 407 384 592 64 949 683 633 13 529 0.370

2000 1 300 038 365 644 61 749 649 952 7 368 0.822

2001 1 270 609 278 967 49 339 754 469 15 990 1.019

2002 1 289 321 278 202 49 793 703 640 15 642 1.565

2003 1 575 889 94 710 45 001 583 790 13 036 1.001

2004 1 467 826 75 390 45 452 687 852 20 673 1.817

2005 1 448 202 81 142 45 670 674 710 15 791 2.103

2006 1 444 229 89 402 44 336 649 907 10 010 1.779

2007 1 454 319 76 439 40 303 637 779 8 587 1.855

2008 1 234 846 167 828 34 800 754 336 13 199 1.837

2009 1 361 893 124 583 20 963 655 395 11 465 2.326


352

Year Population

receiving well-

managed biological

treatment

Population

receiving poor-

managed

biological treatment

Population

receiving non-

biological

treatment

Population

receiving no

treatment

Amount of

anaerobic

sludge, t/y

Amount of

recovered

CH4, Gg/y

2010 1 263 152 140 283 30 281 686 788 11 464 2.666

2011 1 464 082 90 866 26 955 488 468 11 136 2.337

2012 1 406 166 106 105 33 715 498 827 6 295 2.447

2013 1 416 897 93 661 29 343 483 924 9 614 2.225

Example of methane emission calculation from 2013 is shown in a following Table 7.15.

Table 7.15 Calculation of CH4 emission from Domestic Waste Water Handling sector (2013)

Treatment

type

Population,

persons

Total DC

(Gg

BOD/yr)

DC WW

w/o

sludge

(Gg BOD/yr)

Correction

factor for

additional

industrial discharges of

BOD into a

sewer

Maximum

CH4

producing

capacity Bo,

kg CH4/kg

BOD

MCF Emission

factor

Emission

(Gg of

CH4)

Well

managed

biological

1 416 897 31.030 28.756 1.25 0.6 0 0 0

Poor managed

biological

93 661 2.051 1.901 1.25 0.6 0.3 0.18 0.410

Non-biological

29 343 0.643 0.596 1.25 0.6 0.8 0.48 0.342

No

treatment 483 924 10.598 9.821 1 0.6 0.5 0.3 2.823

Total: 2 023 825 44.322 41.074 3.575

Some amount of sewage sludge is treated or stored in anaerobic conditions in Latvia, causing formation of CH4.

Assumptions regarding sewage sludge are shown in Table 7.16.

Table 7.16 Characteristics of sewage sludge in Latvia

Characteristic Value

Average content of dry solids in sludge, %* 14**

Average content of COD in dry solids, % 43***

Average content of N in dry solids, % 52****

*Is used to estimate content of dry solids for years where statistic data are not available (1998 -2002)

**”Notekūdeņu dūņas un to izmantošana” („Sewage Sludge and Disposal of it”), Gemste I., Vucāns A., Jelgava,

2002.

***Average data of 1996

****”Notekūdeņu dūņas” (“Sewage Sludge”), Gemste I., Vucāns A., Jelgava, 2007.

Extrapolation was used to estimate amount of sewage sludge produced and treated anaerobically for period 1990 – 1997, where statistic data were not available. Based on

statistics available (1998 – 2008), assumption was made the part of anaerobically treated sludge is 53%. Emissions from sludge, used as fertilizer in agriculture or disposed in landfills, are reported under according sectors in different chapters of this NIR.

Data on recovery of CH4 from waste water handling are plant specific data from treatment plant ―Daugavgrīva‖, operated by largest Latvian water supply and waste water Treatment

Company ―Rīgas ūdens‖. Recovery of CH4 is also performed by its daughter company ―Rigens‖, starting from 2002. 2.225 Gg of methane was recovered from waste water handling in 2013. Recovered amount of CH4 is being used as fuel in the cogeneration plant, and

emissions from it are reported under the Energy sector. It is assumed, that content of the CH4 in the recovered biogas by volume is 70%, and density of CH4 is 0.6687 kg/m3.

Example of CH4 emission calculation from sewage sludge is shown in Table 7.17.


353

Table 7.17 Calculation of CH4 emission from sewage sludge (2013)

Total DC sludge (Gg

COD/yr)

Emission factor for sludge (kg CH4/ kg

COD)

Emission of sludge (Gg CH4)

4.969 0.25 1.242

Thus, total CH4 emission from domestic waste water handling and sewage sludge in 2013 is

3.575 + 1.242 – 2.225 = 2.592 Gg of CH4.

Calculation of emissions of N2O from Domestic Waste Water handling is based on amount of

nitrogen, generated from the protein consumption by national population. Number of national population is taken from national statistics (CSB) while country specific value of protein consumption (83.7 g/person/day or 30.551 kg/person/yr) is obtained from national food

consumption research207, accessible on internet site:

http://www.lvaei.lv/?lang=1&menu=51&itemid=94.

Unfortunately, no annual data of protein consumption are available, therefore one constant value is used for entire timeline.

When compared with similar data from Latvian neighbour countries (Lithuania and Estonia),

Latvian data shows consistent value (Table 7.18).

Table 7.18 Comparison of Latvian protein consumption data with data from neighbour countries

(Lithuania and Es tonia)

Country g/person/day kg/person/yr

Latvia 83.7 30.551

Lithuania 77.4…78.1* 28.251…28.507**

Estonia 101* 36.865**

*Data taken from Lithuanian and Estonian NIRs (2010)

**Recalculated for comparison

Amount of N2O emission from Domestic Waste Water Handling is calculated according to

„2006 IPCC Guidelines for National Greenhouse Gas Inventories‖; chapter 6.3.1 „Methodological issues‖ (2006 IPCC Guidelines).

28

442 EffluentEffluentEmissions EFNON

where

N2OEmissions – N2O emission in inventory year, kg N2O/yr NEffluent – Nitrogen in the effluent discharged to aquatic environment EFEffluent – Emission factor for N2O emissions from discharged waste water, kg N2O-N/kg N

SludgeCOMINDCONNONNPREffluent NFFFoteinPN )Pr(

where

NEffluent – Total annual amount of nitrogen in waste water effluent, kg N/yr P – National population Protein – Annual per capita protein consumption, kg/pers/y FNPR – Fraction of nitrogen in protein, kg N/kg protein

FNON-COM – Factor for non-consumed protein added to waste water FIND-COM – Factor for industrial and commercial co-discharged protein into a sewer system NSludge – Nitrogen removed with sludge, kg N/y

207

By Latvian State Institute of Agrarian Economy

http://www.lvaei.lv/?lang=1&menu=51&itemid=94


354

Default value for nitrogen fraction in protein – 0.16 kg N/kg protein – is used in calculation. Default IPCC value for emission factor – 0.005 kg N2O-N/kg N – was used as well. Both values were taken from 2006 IPCC Guidelines.

A small amount of N2O is emitted during the release from the sewage system. The calculations gives emission 0.021 Gg of N2O (2013).

N2O emissions from centralized waste water treatment processes are estimated as well.

PlantCOMINDPlantPlants EFFTPON 2

where

N2OPlants – Total N2O emissions from plants in the inventory year, kg N2O/y

P – Human population TPlant – Degree of utilization of modern, centralized treatment plants, % FIND-COM – Fraction of industrial and commercial co-discharged protein EFPlant – Emission factor, g N2O/pers/y

Waste water treatment plants, providing tertiary treatment (i.e. removal of nitrogen of

phosphorus), are considered to be in compliance with requirements for ―modern, centralized treatment plants‖. Degree of their utilization is estimated based on number of national population, provided with such treatment. National waste water database ―2-Water‖ provides

according statistical data (starting from 2000). Constant value of 3% was used for years, previous to 2000.

Activity data for estimation emissions of N2O from Domestic Waste Water Handling sector are shown in the following table Table 7.19.

Table 7.19 Activity data for estimation emissions of N2O from Domestic Waste Water Handling sector

Year Population Amount of sludge

produced, t/y

Degree of utilization of modern, centralized treatment

plants, %

1990 2 668 140 36 115 3.0

1995 2 500 580 25 695 3.0

2000 2 377 383 18 234 0.1

2001 2 353 384 23 153 4.9

2002 2 320 956 21 467 7.6

2003 2 299 390 29 278 4.3

2004 2 276 520 36 164 8.9

2005 2 249 724 28 877 8.4

2006 2 227 874 23 942 9.2

2007 2 208 840 23 259 9.3

2008 2 191 810 19 263 12.0

2009 2 162 834 22 346 14.5

2010 2 120 504 21 395 16.4

2011 2 070 371 19 728 18.2

2012 2 044 813 18 064 17.8

2013 2 023 825 20 733 17.4

Default values from 2006 IPCC Guidelines are used for fraction of industrial and commercial co-discharged protein and emission factor (correspondingly, 1.25 and 3.2 g N2O/pers/y).

Estimation gives emission of 0.001 Gg of N2O from this subsector in 2013. Thus, total emission of N2O from Domestic Waste Water Handling was 0.021 + 0.001 = 0.022 Gg of

N2O what makes increase of 68.3% in comparison with emissions of 1990 and decrease of 18.5% in comparison with emissions of 2012.


355


The following uncertainties were used for Domestic Waste Water Handling sector for activity

data and emission factors:

Table 7.20 Uncertainties for Domestic Waste Water Handling sector

Emission Activi ty data Emission factor

CH4 10% 30%*

N2O 10% 30%*

*30% - default uncertainty from 2006 IPCC Guidelines

Time series show continuous decrease of emissions in the entire timeline. Main reason of this decrease is recovery of CH4, implementation of more and better treatment plants also can be

observed, but its effect on decrease of emission is limited.

Inconsistencies in data (for example, potential outlier in 2008) can be explained with quality

of activity data. Although data collection system on population, receiving certain grade of waste water treatment is generally well-designed and allows to collect data on plant level, the actual data quality still largely depends on competence of person in enterprise, responsib le for

reporting these data.


Following procedures of quality assurance and quality control were carried out:

Statistic data of national population, served by certain treatment type and level, as well

as amount of sludge produced and disposed are collected through annual state statistical survey ―2-Water‖. In frames of this survey, enterprises, performing

collection and treatment of waste water, submit their data using online database. Reported data are checked by Latvian State Environment Service, whose environment inspectors approve reports or return them to submitters for correcting of data;

Units of measurement were checked during comparison with results of previous reports;

Number of national population was cross-checked with activity data, used in others sectors (solvents and waste disposal);

Amount of CH4 recovery from sewage sludge was checked by comparing data from Energetic sector on amount of sludge gas burned in waste water treatment facility;

Protein consumption data were compared with values from neighbour countries of Latvia – Lithuania and Estonia (Table 7.18);

Comments in CRF tables were checked in process of entering data of calculation and recalculation results in CRF tables.


All emission data were recalculated in Domestic Waste Water Handling sector, due to both

methodology change (transition to 2006 IPCC Guidelines) and adjustment of activity data.




356

7.5.2 Industrial Wastewater (CRF 5.D.2)


Industrial Waste Water Handling is responsible for CH4 and N2O emissions. Fluctuations of

methane emission from Industrial Waste Water Handling are connected with fluctuatio ns of amount of production produced. Significant decrease in methane emission in period 1993 – 1999 is due to decrease of economic activity after collapse of Soviet Union. Emission of N2O,

produced by Industrial Waste Water Handling, is negligible, giving ~ 0.1% of emission in this sector in 2013 (Figure 7.9).

Figure 7.9 Emissions from Industrial Waste Water Handling sector (Gg CO2 eq.)


Emissions of CH4 from Industrial Waste Water Handling is calculated from amount of total organic product (expressed as COD – chemical oxygen demand) and total nitrogen in waste

water, generated in certain branches of industry (mostly food-processing industry).

IPCC default formula („2006 IPCC Guidelines for National Greenhouse Gas Inventories‖;

chapter 6.2.3 „Industrial Wastewater‖ - 2006 IPCC Guidelines) was used for calculation of CH4 emission from Industrial Waste Water Handling sector.

i

iiiiEmissions REFSTOWCH )(4

where

CH4Emissions – CH4 emissions in inventory year, kg CH4/yr TOWi – total organically degradable material in industrial waste water from industry i in inventory year, kg COD/yr i – industrial sector

Si – organic component removed with sludge in the inventory year, kg COD/yr EFi – emission factor for industry i, kg CH4/kg COD Ri – amount of CH4 recovered in inventory year, kg CH4

ioi MCFBEF

where

EFi – emission factor for each industry i, kg CH4/kg COD i – each type of industry


357

Bo – maximum CH4 producing capacity, kg CH4/kg COD MCFi – methane correction factor for each type of industry

iiii CODWPTOW

where

TOWi – total organically degradable material for industry i, kg COD/yr

i – industrial sector Pi – total industrial product for industry i, t /yr Wi – waste water generated for each type of industry, m

3/t product

CODi – industrial degradable organic component in waste water, kg COD/m3

Activity data (amount of certain industrial products) was taken from national statistics – data base of Latvian Central Statistics Bureau. Default IPCC value 0.25 kg CH4/kg COD was used

for maximum methane producing capacity, as it is recommended in 2006 IPCC Guidelines. Amount on generation of waste water per certain type of product and organic component in

that waste water were taken as default values from 2006 IPCC Guidelines.

Plant specific survey was performed during 2012, to obtain MCF values for certain industries. The average weighted MCF for each industry were estimated depending of level of

contribution of said industry in terms of amount of waste water generated and its fate (level of treatment or transfer to certain urban waste water treatment plant).

Assumptions for all relevant industries are summarized in a Table 7.21.

Table 7.21 Assumptions used for calculation of CH4 emissions from Industrial Waste Water Handling

Industry type Generation of waste water, m3/t of

product*

Organic component in waste

water, kg COD/m3*

Weighted

MCF value**

Milk 7 2.7 0.10

Meat 13 4.1 0.15

Fish 13 2.5 0.05

Beer 6.3 2.9 0.04

Fruits and vegetables 20 5 0.13

Sugar 11 3.2 0.50

Paper and pulp 162 9 0.30

Plastics 0.6 3.7 0.14

Organic chemicals 67 3 0.03

*Assumptions used from 2006 IPCC Guidelines

**rounded to 2 decimal positions

Organic component removed with sludge and amount of recovered CH4 under this sector is assumed to be 0 – both values are estimated and taken into account under the Domestic Waste

Water Handling sector.

Activity data, used for calculation of CH4 emissions from domestic waste water are summarized in the following table Table 7.22.

Table 7.22 Activity data for calculation CH4 emissions from Industrial Waste Water Handling sector

(amount of products, th. t/yr)

Year Milk Meat Fish Beer Fruits and

vegetables

Sugar Paper

and pulp

Plastics Organic

chemicals

1990 1 188 324 335 9 0 31 37 0 0

1995 353 99 114 66 0 29 1.5 0 0

2000 407 125 147 94 47 63 22 18 12

2001 416 97 161 100 52 56 23 23 14

2002 380 98 133 121 58 77 27 30 15

2003 436 119 109 138 57 75 31 35 16

2004 784 109 126 133 55 67 30 27 16

2005 810 77 151 130 57 71 34 29 5

2006 295 73 126 142 48 60 38 30 5

2007 240 148 75 141 50 0 43 33 4


358

Year Milk Meat Fish Beer Fruits and

vegetables

Sugar Paper

and pulp

Plastics Organic

chemicals

2008 270 168 130 130 52 0 39 24 26

2009 230 147 107 0 44 0 30 0 0

2010 197 120 56 153 27 0 38 0 0

2011 183 121 60 150 18 0 42 0 0

2012 194 125 67 140 18 0 44 0 0

2013 225 122 73 134 19 0 46 0 0

Example of CH4 emission calculation from Industrial Waste Water Handling is provided in a table Table 7.23.

Table 7.23 Calculation example of emission of CH4 from Industrial Waste Water Handling (2013)

Product

name

Amount of

production,1

000 t/yr

Amount of

waste water

per

production

unit, m3/t

Amount of

waste

water, 1000

m3/yr

Conc.of

COD in

waste

water,

kg/m3

Load of

COD,

t/yr

Max.CH4

prod.

capacity,

kg CH4/ kg

COD

MCF Emission

of CH4,

t/yr or

Mg/yr

a b c = a*b d e = c*d f g h = e*f*g Milk 225 7 1 574 2.7 4 249 0.25 0.10 107 Meat 122 13 1 591 4.1 6 524 0.25 0.15 243 Fish 73 13 950 2.5 2 376 0.25 0.05 29 Sugar 0 11 0 3.2 0 0.25 0.5 0 Beer 134 6.3 847 2.9 2 456 0.25 0.04 25 Fruits and

vegetables 19 20 379 5 1 895 0.25 0.13 59

Paper and

pulp 46 162 7 468 9 67 214 0.25 0.30 5 041

Plastics 0 0.6 0 3.7 0 0.25 0.14 0 Organic chemicals

0 67 0 3 0 0.25 0.03 0

Thus, total emission of CH4 from Industrial Waste Water treatment in 2013 was 5.505 Gg of CH4 what makes 0.4% increase if compared to emission of 1990 and 5.3% increase if

compared with emission of 2012.

N2O emission from Industrial Waste Water Handling was calculated, using Tier 1 method from 2006 IPCC Guidelines, chapter 6.3.1 ―Nitrous Oxide Emissions from Wastewater.‖.

Calculation is based on load of nitrogen in the industrial waste water:

61028

44 EFNWM ef

where WM – total emission of N2O from industrial waste water handling in Gg N2O

Nef – load of nitrogen, kg/yr EF – emission factor, kg N2O-N/kg N

IPCC default value (0.005 kg N2O-N/kg N) from 2006 IPCC Guidelines was used for calculation. Activity data, used for calculation of N2O emissions from Industrial Waste Water Handling,

are summarized in Table 7.24.

Table 7.24 Activity data for calculation N2O emissions from Industrial Waste Water Handling sector

Year Load of N in industrial waste water, t/yr

1990 1 000

1995 480

2000 165

2001 452

2002 350

2003 272

2004 297


359

Year Load of N in industrial waste water, t/yr

2005 230

2006 147

2007 162

2008 70

2009 149

2010 101

2011 92

2012 43

2013 60

N2O emission from Industrial Waste Water Handling is negligible – 0.0005 Gg/yr (i.e. 0.474 Mg/yr (2013)) what makes decrease of 94.0% if compared to emissions of 1990 and increase

of 41.3% if compared to emission of 2012.


The following uncertainties were used for Industrial Wastewater Handling sector for activity data and emission factors (Table 7.25):

Table 7.25 Uncertainties for Industrial Waste Water Handling sector

Emission Activity data Emission factor

CH4 2%* 30%**

N2O 10% 30%**

*frame uncertainty of CSB

**default uncertainty from 2006 IPCC Guidelines

Time series of emissions are inconsistent, since Industrial Waste Water Handling is significant source of CH4 emissions and amount of production, which is activity data for it,

varies a lot from year to year. Decrease of emissions from Industrial Waste Water Handling in period 1992 – 2001 can also be explained by decrease of national economic activity after collapse of Soviet Union in 1991.

Fluctuations of activity data and emissions of N2O from Industrial Waste Water are even worse, however its effect on total emissions from this sector is not significant, because of

small amount of N2O emitted.


Following procedures of quality assurance and quality control were carried out:

Statistic data of nitrogen load in waste water (including industrial waste water) are

collected through annual state statistical survey ―2-Water‖. In frames of this survey, enterprises, performing collection and treatment of waste water, submit their data using online database. Reported data are checked by Latvian State Environment

Service, whose environment inspectors approve reports or return them to submitters for correcting of data;

Units of measurement were checked during comparison with results of previous reports;

Comments in CRF tables were checked in process of entering data of calculation and recalculation results in CRF tables.


Entire timeline was recalculated for emissions of CH4 due to adjustment of activity data.


360



7.5.3 Other (CRF 5.D.3)


Data of LEGMC shows there were 238 mio m3 of waste water discharged in Latvia (2013).

Most of national population (76%, 2013) is served by urban waste water collecting and treatment. Certain amount of NMVOC is produced from Waste Water Handling sector.


Emissions of NMVOC was calculated and using default EMEP emission factor from „EEA Emission Inventory Guidebook 2013‖ was used for this calculation – 15 mg of NMVOC per

m3 of waste water produced, what gives 3.57 Mg/yr of NMVOC (2013). It makes decrease of 60.3% if compared to emission of 1990 and increase of 1.7% if compared to emission of

2012.

Activity data, used for this calculation, are summarized in the following table (Table 7.26):

Table 7.26 Activity data for calculation NMVOC emissions from Waste Water Handling sector

Year Amount of waste water produced, mio m3

1990 600

1995 357

2000 257

2001 244

2002 243

2003 229

2004 211

2005 226

2006 196

2007 210

2008 191

2009 226

2010 222

2011 241

2012 234

2013 238


No specific issues.


Statistic data of amount of waste water produced and discharged are collected through annual state statistical survey ―2-Water‖. In frames of this survey, enterprises,

performing collection and treatment of waste water, submit their data using online database. Reported data are checked by Latvian State Environment Service, whose environment inspectors approve reports or return them to submitters for correcting of

data;

Units of measurement were checked during comparison with results of previous

reports.


361


Emissions were recalculated for years 2008 – 2010 and 2012 due to adjustment of activity

data.


No planned improvements.


362

8. OTHER (CRF 6)

Latvia does not report any emissions under the Other sector.


363

9. INDIRECT CO2 AND NITROUS OXIDE EMISSIONS

Indirect CO2 emissions were estimated from NMVOC emissions in glass fibre production and Solvent use. Information reported in Chapter 4. Industrial Processes and Product Use (CRF 2).

Latvia does not report indirect nitrous oxide emissions from other than the agriculture and LULUCF sectors.


364

10. RECALCULATIONS AND IMPROVEMENTS

10.1 EXPLANATIONS AND JUSTIFICATIONS FOR RECALCULATIONS, INCLUDING KP-LULUCF INVENTORY

10.1.1 GHG inventory

The changes in inventory since the previous submission to the UNFCCC were done according

to:

Implementation of 2006 IPCC Guidelines;

Recommendations by ERT during Centralized review (2014);

Suggestions from the third part experts not directly involved in the preparation of

national inventory;

Corrections of activity data by CSB and corrections of input mistakes.

10.2 IMPLICATION FOR EMISSION LEVELS


See section 10.1.

10.3 IMPLICATIONS FOR EMISSION TRENDS, INCLUDING TIME SERIES’

CONSISTENCY


See section 10.1.

10.4 RECALCULATIONS, INCLUDING IN RESPONSE TO THE REVIEW PROCESS, AND PLANNED IMPROVEMENTS TO THE INVENTORY


The development of the GHG inventory aims to improve the calculation and reporting of the

inventory. The improvement plan is discussed and approved by all experts and organizations involved in GHG inventory preparation process.

Many improvements of next and future GHG inventories are planned within the project of

EEA Financial Mechanism 2009-2014 Programme "National Climate Policy ":

- ) development of an integrated database for climate change and air quality data

aggregation. The development of the database will result in enhanced data quality, workflow optimization and facilitation of report submissions;

-) preparation of research studies for GHG inventory improving (for example,

Promoting sustainable land management through creation of a digital soil database; analyze bovine intestinal fermentation processes (methane release); evaluate agricultural fertilizer-

related processes and activities; estimation of soil carbon stock in cropland and grassland);

- ) ensuring QA/QC evaluation for land use, land use change and forestry and industrial processes sectors;


365

- ) conferences, training seminars and other experience-sharing events carried out to increase the capacity of Latvian inventory experts (already took place in 2015, results partially reflected into this submission, final results planned to be implemented into next

submission).

The Table 10.1 shows the sector specific improvements needs for the forthcoming

inventories. More detailed information about planned improvements can be found under sectoral chapters.

Table 10.1 Sector s pecific improvements needs of Latvia`s national GHG inventory

CRF

category Planned improvement Tentative

time

schedule

Progress

General Develop an integrated database for climate

change and air quality data aggregation

and preparation of GHG inventory (NIR)

and other reports to different international institutions;

2016

Will be done starting from 2016

Submission.

General Increase capacity of the Latvian inventory

experts (conferences, training seminars

and other experience-sharing events

carried out to increase the capacity of

Latvian inventory experts) accordingly the quality of the inventory will be improved.

2015-2016

Train ing seminars and

experience sharing events

already took place in 2014 and

2015 within the project of EEA

Financial Mechanism 2009-

2014 Programme ―National

Climate Policy ―. Quality

improvements partially

implemented into 2015

Submission. Entire results will

be implemented into next submission.

General Improve uncertainty of the inventory

implementing Tier 2 approach (Monte Carlo model)

2015-2016

Planned into second half of 2015

within the project of EEA


2014 Programme ―National

Climate Policy ―. Results will be

implemented into next

submission.

Energy

Update CO2 methodology for fuels. From

2016

From 2016 Planned to be carried

out in 2016.

IPPU/F-

gases

Elaborate F-gases reporting – improve AD

obtaining, develop country specific

emission factors, improve QA/QC procedures of F-gases inventory

2015-2017

Started in 2015 within the

project of EEA Financial

Mechanism 2009-2014

Programme ―National Climate

Policy ―. Results will be implemented next submissions.

Agriculture overview

Establish a modelling tool integrating

climate changes and perform a data

analysis of SEG emission estimation

methodology in Agriculture.

Analyse the release of methane from cattle

enteric fermentation processes, evaluate

the processes related to manure

management and activities, develop

modelling programs for agricultural emission evaluation and projection.

From 2015

Improvement planned within the


Mechanism 2009-2014


Policy ―. Will be done starting

from 2015 Submission.

Agriculture

3.A.1

Perform research activities for usage a Tier

2 method for the estimation of CH4 2016

Partially done within the project

of EEA Financial Mechanism


366

CRF


time

schedule

Progress

Enteric

fermentation emissions from enteric fermentation of

cattle sub-categories and swine sub-

categories.

2009-2014 Programme

―National Climate Po licy‖

Taking into account restricted

financial resources; the

methodology will be updated

only for cattle. Regarding swine,

it is planned to investigate

theoretical possibility to move to Tier 2.

Agriculture3.A.2.

Manure

management

Improve data on animal waste

management systems to improve Tier 2

calculations and time series consistency.

2015-2016

Planned for the next

submissions within the project

of EEA Financial Mechanism

2009-2014 Programme

―National Climate Po licy‖

Agriculture 3.A.2.

Manure

management

Provide exp lanations regarding to manure

management systems’ methodology.

Particularly, the source of activity data and

assumptions of anaerobic digester for all

types of livestock could be provided.

Reassessment of manure management

systems distribution could be done,

particularly pasture season length (days),

taking into account statistical data: the

share of number of livestock per holding,

data of manure storage facilit ies obtained

in Agricu ltural Census and surveys,

technology changes of breeding and

different keeping of sub-categories of non-

dairy cows and swine.

2015-2016

The description of assessment of

manure management systems is

already prepared by Prof.

J.Priekulis. The scientific

publication in English available

starting from 2015 Submission.

Will be implemented into next

submission.

Agriculture

3.D

Developing of country specific values for

FracLEACH-(H) to estimate N losses by

leaching/runoff. Developing of country

specific data for crop residue statistics,

because similar research projects in Latvia

show differences between IPCC crop

residues statistics and country specific

numbers. However, results should be

future evaluated and approved by experts

from agriculture sector.

2016

Will be implemented into next

submission.

LULUCF -

overview

Evaluation of carbon stock changes in

croplands and grasslands. 2015

Improvement planned within the


Mechanism 2009-2014


Policy ―.

LULUCF Direct and

Indirect N2O

emissions from

managed

soils

N2O emissions might be considerable part

of emissions from wetlands, therefore, it is

necessary to develop method for

estimation impact of drainage on N2O

emissions, and it is important to be able to

separate wetlands on organic soils (high

N2O emissions) and mineral soils (low

N2O emissions). Information on land use

changes, particularly, distribution of

organic and mineral soil and losses of

2016-2020

Demonstration project

application for LIFE+ progra m

―LIFE Restore - Support tools

for sustainable and responsible

management and re-use of

degraded peatlands in Latvia‖

proposed in 2015.


367

CRF


time

schedule

Progress

carbon due to land use changes should be

estimated. Country specific C/N ratio will

be introduced after completion of the agriculture soil monitoring project.

LULUCF 4.A Forest

Land

Estimation of decay period for dead wood

(harvesting residues and below-ground

biomass, planned to complete until report

1990-2014);

2015

Research project on this issue is

completed, implementation

stage is proposed in 2015.

Estimation of carbon stock changes in

drained organic soils in forest lands

(2015);

2016

Pilot study is completed and

implementation of the research

is started; preliminary data will

be available at the end of 2015.

Estimation of transition period for dead

wood and litter carbon stock in afforested

lands (2015-2018);

2017

The project work plan is

elaborated, the implementation

is proposed to 2017.

Development of production version of

EPIM tool, including broader

representation of land use change,

integration of land use change and GHG

calculation modules and integration of

Kyoto protocol and the UNFCCC reporting modules.

2015

Structural improvements of the

model are defined; technical

work and quality assurance will

be implemented in 2015 for

reporting 1990-2014.

LULUCF 4.B.1

Cropland

remaining

cropland

Updated area of organic soil in cropland

according to the NFI study started in 2012 and soil mapping project.

2016-2020

Temporary results will be

available in 2016 after

complet ion of soil mapping

project, all NFI p lots on former

and currently used cropland and

grassland will be visited until

2020.

Updated CO2 emissions from organic soil

considering area changes and recent

findings in Nordic and Balt ic countries,

particularly, doctoral thesis by Jüri-Ott

Salm ―Emission of greenhouse gases CO2,

CH4, and N2O from Estonian transitional

fens and ombrotrophic bogs: the impact of

different land-use practice‖.

2016-2020

Demonstration project

application for LIFE+ program

―LIFE Restore - Support tools

for sustainable and responsible

management and re-use of

degraded peatlands in Latvia‖

proposed in 2015.

Carbon losses and updated N2O emissions

due to disturbances using emphyrical data on carbon stock changes in soil

2016-2020

According to availability on data

carbon stock changes in organic

soils converted to cropland or

grassland from forest land or

wetland. The work plan is

elaborated and will be

implemented in line with

relevant activities in GHG

inventory improvement.

Tier 3 methodology to estimate carbon

stock changes in cropland considering changes of cropping practices since 1970.

2016

It is proposed to implement

Yasso model in forest land and

cropland to obtain informat ion

on carbon stock changes in soil.

LULUCF 4.B.2 Land

converted to

Area of organic soil might be

overestimated in land converted to 2016

The new estimates will be based

on soil mapping project which


368

CRF


time

schedule

Progress

cropland cropland. Field measurement based

informat ion on organic soils is necessary

to improve accuracy of estimates of the emissions.

has to be completed in 2015.

LULUCF 4.C

Grasslands

Improvement of reporting for ditch area in

organic soil. Now the estimates are based

on limited knowledge about organic soils

and drainage ditches in grasslands. The

updated information will be based on NFI

data, soil mapping data and digital GIS

informat ion on drainage systems.

2016

Soil mapping project has to be

completed to start estimation of

area of drainage ditches on

organic soils.

LULUCF

4.B., 4.C.

Land, Aggregate

Sources and

Non-CO2

Emissions

Sources on Land

Create a dig ital database of soils

digitalising availab le soil maps.

From 2015

Planned to implement in next

submissions. Improvement

planned within the project of

EEA Financial Mechanism

2009-2014 Programme

―National Climate Po licy ―.

LULUCF

3.D.4.

Wetlands

Develop method for estimat ion impact of

ditches and other types of wetlands on N2O

and CH4 emissions.

2016-2020

Planned to implement in next

submissions. Demonstration

project application for LIFE+

program ―LIFE Restore -

Support tools for sustainable and

responsible management and re-

use of degraded peatlands in Latvia‖ proposed in 2015

LULUCF

4.B.5. Settlements

Utilizat ion of high resolution satellite

images to evaluate dynamics of carbon

stock in living biomass in certain pilot

areas since 1990 and to extrapolate

obtained results to all NFI plots to avoid

potential overestimation of removals of

CO2 in liv ing biomass.

2016-2020 Planned to implement in next

submissions.

LULUCF 4

(V) Biomass

Burning

A new methodology on estimation of

incineration efficiency in forest fires will

be elaborated and different types of forest

fires will be separated to account the GHG

emissions more accurate. Information

provided by the State forest service will be

used with higher level of accuracy by

splitting different types of forest fires and

following activities in the forest stands to

avoid double reporting of harvested wood

extracted in sanitary felling after forest

fires. Burning of harvesting residues will

be evaluated by forest owner’s questionnaires.

2017

The work plan is elaborated for

implementation to obtain data for fo llowing inventories.

LULUCF

4.G Harvested

Wood

Products

Impact factors of more detailed species

composition on structure of assortments

for reporting and projections of HWP in

reference level.

2016-2017

Will be included into the

calculations in the next inventory.

Waste 5.A Solid Waste

Disposal

Estimation of MCF will be done for Latvia

landfills for all time series. 2015-2016

It is planned to make an efforts

within the programme


369

CRF


time

schedule

Progress

―European Economic Area


2014 – ―Nat ional Climate

Policy‖ to improve MCF uses.

Improvement will be undertaken

for next submission.

Waste 5.B.1

Composting New waste recovery classification in

Latvia comes in force in 2013.

Determination of composting will be more

precise, because special R code will be

used for composting.

It is planned to make an efforts within the

programme ―European Economic Area

Financial Mechanism 2009-2014 –

―National Climate Policy‖ to improve this

section. Research about composted

amounts in households and country

specific emissions factors for composting

will be realized in year 2015.

2015-2016

It is planned to organize the

pilot project within the

programme ―European

Economic Area Financial

Mechanism 2009-2014 –

―National Climate Policy‖.

Improvement will be undertaken

for next submission.

Response to the previous reviews was prepared according to recommendations by ERT during

centralized review in 2014 and recommendations by third part reviewers (Table 10.2).

Table 10.2 Res ponse to the review process

Sector CRF Category/Iss

ue

Review Recommendation Review

Report/Paragrap

h

LV Response (status of

implementation)

Chapter/Section

in the

NIR

Cross-

cutting QA/QC

Allocate sufficient resources for

the implementation of the QA/QC plan, but especially with regard to

the QC activities performed by

the inventory compilers preparing

the NIR and CRF tables.

FCCC/ARR/2014/LVA DRAFT,

para 14

Additional QA/QC improving activities (training seminars and

experience sharing events) took

place in 2014 and continue in 2015 within the project of EEA Financial

Mechanism 2009-2014 Programme

―National Climate Policy ―. Quality

improvements partially implemented

into 2015 Submission. Entire results will be implemented into next

submission.

Chapter 1.2.3

Inventory

preparation

Report the key categories in accordance with the IPCC good

practice guidance, and

consistently report the results in

the NIR and the CRF tables.


para 16

Key categories reported in accordance with the 2006 IPCC

Guidelines and IPCC Wetlands

Supplement for CO2, CH4 and N2O

emissions from drained and rewetted soils. Results reflected consistently

between NIR & CRF

Chapter

1.5

Inventory

preparation

Allocate sufficient time and human resources to the final

stages of the inventory compilation process in which

cross-sectoral work such as the

key category analysis occurs, and

enhance the QC procedures so

that errors are avoided in future

annual submissions.


para 16

Additional QA/QC improving activities (training seminars and

experience sharing events) took

place in 2014 and continue in 2015 within the project of EEA Financial

Mechanism 2009-2014 Programme

―National Climate Policy ―. Quality

improvements partially implemented

into 2015 Submission. Entire results will be implemented into next

submission.

Chapter

1.2.3


370

Sector

CRF Category/Iss

ue

Review Recommendation

Review Report/Paragrap

h


implementation)

Chapter/Section

in the

NIR

Inventory

preparation

Report the uncertainties associated with the total national

emission estimates based on

formula 6.4 of the IPCC good

practice guidance.


para 18

Uncertainty estimations in process. Will be reported in accordance with

the 2006 IPCC Guidelines (Volume

1, Chapter 3, Table 3.2) based on

formula 3.1 (corresponding to the IPCC GPG formula 6.4 which was

recommended by ERT).

NIR – Chapter

1.6 (Will

be

updated)

Inventory

management

Correct the error in the reporting

of emissions from consumption of

halocarbons and SF6

FCCC/ARR/2014/

LVA DRAFT,

para 22

The new 2006 IPCC Guidelines

have been used for calculation of

emissions from 2.F. Product uses for OSD Substitutes and 2.G. Other

Product Manufacture and Use

(correspondingly to IPCC GPG –

2.F Consumption of HFCs & SF6).

As it was explained in response to ERT during centralized review in

2014 error in the reporting of

emissions from consumption of

halocarbons and SF6 was not the

potential problem raised by ERT during the review and emissions

were not recalculated due to that

reason. Error was the technical

problem with xml files during the

multifold import/export process within the CRF during review

process.

The error has been resolved in 2015

submission.

Chapter

4.8.1

Inventory

management

Strengthen the QC checks to adequately track any changes in

the reporting between the original

submission and the successive

resubmissions, if any, of the

national inventory.


para 22

QC was strengthened in a following way – LEGMC has prepared and annually will update instructions for

inventory preparation. Especially in

those sectors where more than one

responsible expert is involved, the

clear order for experts for data input

and NIR preparation is explained.

Chapter

1.2.3

Energy General

Include the results of the implementation of the

recommendations from the

external independent review

conducted in 2014


para 30

Implemented in 2015 submission.

Included in all relevant subsectors

Chapter

3.2

General

Perform further activities to reduce the relatively high

uncertainty values for categories

where the provision of data and associated uncertainties are of a

good quality


para 31

Implemented in 2015 submission. Uncertainties looked through and

corrected for activity data, CO2 EF

Chapters 3.2.4.3,

3.2.5.3.,

3.2.7.3,

3.2.8.3

Reference

and sectoral

approaches

Use both the Eurostat data and the IEA data to conduct QC of the

CRF tables, in order to ensure consistency between the data sets

and provide a clear explanation of

any differences

FCCC/ARR/2014/

LVA DRAFT,

para 34

More detailed analysis will be on the

next Submission.


371

Sector

CRF Category/Iss

ue



h


implementation)

Chapter/Section

in the

NIR

International

bunker fuels

Include relevant transport statistics to increase the

transparency of the information

provided on the emission trends

of international transport activities for aviation and

navigation


para 35

Additional statistics about international navigation are included

to increase the transparency on the

emission trends and to provide

additional explanation

Chapter

3.2.2

Stationary and mobile

combustion: all fuels –

CO2

More regularly update the analysis of NCVs for the fuels

used


para 37

All NCVs are taken from CSB on-line database or Annual

Questionnaires

Chapter

3.2.1.3

Stationary and mobile combustion:

all fuels –

CO2

Verify the parameters used with the measured values and reported

parameters under the EU ETS


para 37

Emission factors for CO2 compared with ones in 2006 IPCC and CS

values

Chapters 3.2.4.4,

3.2.5.4.,

3.2.7.4

Stationary combustion:

other fuels –

CO2

Apply annually updated CO2 EFs for the combustion of used tyres

in the cement industry that could

be obtained from the annual EU

ETS report


para 38

All emission factors are taken

directly from EU ETS reports

Chapter

3.2.5.2

Oil and natural gas:

gaseous fuels

– CH4

Include more detailed background information to explain the

improvements undertaken in the

distribution network to clarify the

reasons for the emissions

reduction in this category


para 41

More detailed information is not available due to confidentiality

issues

Chapter

3.3.2.1

Stationary combustion –

all fuels –

CO2

Use CSB Energy Balance data 3rd part internal

review

CSB Energy Balance data used as AD source instead of Annual

Questionnaires to improve data

accuracy.

Chapter

3.2.4.2


all fuels –

CO2

Use the data from CSB to provide the consistency between activity

data (e.g. NCV for natural gas

consumption).

3rd part internal

review

Data used now corresponds both with EU ETS and CSB data (natural

gas CO2 EF)

Chapter

3.2.4.2


Charcoal and peat

briquettes

production

Assess the fuel flow through charcoal and peat briquettes

production process

3rd part internal

review

Fuel flow is assessed and the

emissions are recalculated

Chapter

3.4.2


372

Sector

CRF Category/Iss

ue



h


implementation)

Chapter/Section

in the

NIR


liquid fuels –

CO2

Double check the activity data

from military activities to avoid

double counting.

3rd part internal

review

Data are checked for 1.A.5.b sector and subtracted from 1.A.4.a sector

to avoid double counting

Chapter

3.2.8.1

Industrial

processes and other

product

use

General

Implement the capacity-building project to achieve better time-

series consistency in the emission

estimates


para 46

Under IPPU the F-gases research has started in 2015 in purpose to

improve AD obtaining, develop

country specific emission factors; improve QA/QC procedures of F-

gases inventory as well as to achieve

better time-series consistency in the

emission estimates. Will be

implemented into next submission.

Cement production –

CO2

Include a clearer description of the method used to estimate

clinker production


para 47

Description of method used to estimate clinker production is

updated.

Chapter

4.2.2.2


CO2

Provide information on the sources of data used to estimate

clinker production using the mass

balance approach


para 47

Information on the sources of data used to estimate clinker production

using the mass balance approach

Chapter

4.2.2.2


CO2

Provide the correct values of the average calcium oxide content for

the entire time series and

strengthen the implementation of

QC checks to avoid discrepancies between the NIR and the CRF

tables


para 48

Correct values of the average calcium oxide content for the time

series are presented in Table 4.4.

Chapter

4.2.2.2

Iron and steel

production –

CO2

Make efforts to acquire accurate and complete information

regarding the amounts of carbon in the different material streams

entering and leaving the process

FCCC/ARR/2014/

LVA DRAFT,

para 50

Emissions from Iron&Steel production are recalculated

according to ERT recommendations

and provided method taking into account the same percentage of

material streams entering and

leaving the process. Explanation are

available,

Chapter

4.4.1.5

Iron and steel production –

CO2

Verify the closure of the input–output carbon mass balance of the

process


para 50

Emissions from Iron&Steel production are recalculated

according to ERT recommendations and provided method taking into

account the same percentage of

material streams entering and

leaving the process.

Chapter

4.4.1.5

Other mineral

products:

CO2, CH4

and N2O

Report the aggregated brick production emissions in one line

in CRF table 2(I)


para 51

On submission 2015 there are reported in CRF aggregated

emissions of bricks production

under sector 2.A.4.a Ceramics.

Chapter

4.2.6.


373

Sector

CRF Category/Iss

ue



h


implementation)

Chapter/Section

in the

NIR

Solvent and other product

use – N2O

Use the notation key ―NE‖ to report N2O emissions from fire

extinguishers and aerosol cans


para 52

In 2015 submission N2O emissions from fire extinguishers and aerosol

cans have not been calculated and

reported. There are no statistical

data available to estimate these emissions however these emissions

are assumed to be negligible.

Agriculture QA/QC

Further strengthen the QA/QC procedures to eliminate any

inconsistencies between the NIR

and the CRF tables


para 56

QA/QC was strengthened in a following way – responsible expert

for QA/QC checks is involved in

inventory preparation process. One

expert is responsible for calculations, but other – for NIR

preparation and QC.

Chapters

5.2.4.,

5.3.4,

5.4.4.

Enteric fermentation

– CH4

Include a clearer explanation of the choice of parameter value for

length of pasture season (tp)


para 58

Scientific publication is prepared that explains calculation

methodology for manure

management systems, including determination of pasture length

according to 2006 IPCC Guidelines.

Reference is provided in NIR.

Chapter

5.3.4.

Enteric

fermentation

– CH4

Correct the inconsistency between CRF table 4.A and the NIR in the

reporting of the pregnancy

coefficient (Cpregnancy) and improve the transparency in the

reporting of the parameters used

to estimate these emissions

FCCC/ARR/2014/

LVA DRAFT,

para 59

Explanation is provided in NIR.

Chapter

5.2.2.

Agricultural

soils – N2O

Report on the progress made towards implementing the tier 2

methodology


para 63

Development of Tier 2 for estimation of indirect N2O emissions

true leaching and run-off is involved in activities of scientific project: National Research Programme ―The

value and dynamic of Latvia’s

ecosystems under changing climate

(EVIDEnT). Sub-project 3.2. ―Analysis of GHG emissions from

agricultural sector and economic

assessment of GHG emissions

mitigation measures‖.

LULUCF

Forest land remaining

forest land –

CO2

Include in the NIR the additional information on artificial removal

of trees that was provided to the

ERT


para 69

The annual felling stock is determined combining 2 data

sources – State forest register harvesting reports and National

forest inventory data on losses of

growing stock due to artificial

activities. The obtained data are

verified by unofficial timber industry statistics. The principle of

calculation of felling stock is

provided in chapters on

methodological issues in forest land

remaining forest land.

Chapter

7.6.4.1

Forest land remaining

forest land –

CO2

Provide a more detailed description of the estimates for

the annual growing stock

increments and the estimation of

mortality rates


para 70

More detailed information on

calculation of annual increment and mortality is provided in chapters on

methodological issues in forest land

remaining forest land as well as

chapters on recalculations in forest

land remaining forest land.

Chapter

7.6.1

7.6.4


374

Sector

CRF Category/Iss

ue



h


implementation)

Chapter/Section

in the

NIR

Forest land remaining forest land –

CO2

Report the carbon stock changes estimated for each of the carbon

pools in the NIR, indicating how

these values were estimated,

taking into consideration any deviations observed from the

default values provided in the

IPCC good practice guidance for

LULUCF

FCCC/ARR/2014/

LVA DRAFT,

para 71

Since this year the methodology is changed to 2006 IPCC Guidelines

and IPCC Wetlands Supplement; methodologies are described in

details in relevant chapters of the

National inventory report.

Chapter

7.6.1

7.6.4

Land converted to

forest land –

CO2

Include the additional information provided to the ERT justifying

that all pools under all land-use

categories, except for grassland converted to forest land, are not a

source of GHG emissions

FCCC/ARR/2014/

LVA DRAFT,

para 72

The information on GHG emissions due to land use changes is updated;

emissions from organic soils in lands converted to forest land and

grassland are calculated according to

methodologies provided in the IPCC

Wetlands Supplement. Other land

use change categories are updated according to the newest data

provided by the NFI. The

information on applied

methodologies is provided in

relevant chapters on methodologic

issues.

Chapters 7.6.4.2,

7.7.2.4, 7.7.2.7,

7.8.2.3,

7.8.2.6

7.10.4.2.

Cropland remaining

cropland –

CO2

Provide transparent information on the use of the notation key

―NO‖ to report the changes in

carbon stocks for the living

biomass pool by demonstrating that the statistical difference is not

significant, or provide estimates

at least using a tier 1 approach as

an interim measure


para 74

The carbon stock changes in mineral soils in cropland remaining cropland

are a part of improvement plan. The

methodologic solution proposed in pilot studies on carbon stock

changes is to use Yasso model for

mineral soils.

Land converted to

cropland –

CO2

Indicate under which category the losses of carbon in living biomass

corresponding to forest land converted to cropland are

reported and demonstrate that the

losses of carbon stock in the

living biomass pool under forest

land converted to cropland are not

omitted


para 76

Detailed description on

methodologic approach in calculation of losses of carbon in

living biomass due to conversion to

cropland is provided in description

of methodologic issues under

chapter land converted to cropland

Chapters7.7.2.4,

7.7.2.7

Land converted to

cropland –

CO2

Estimate and report the changes in carbon stock for 2012 instead

of using the notation key ―IE‖


para 76

Carbon stock changes due to conversion of forest land to cropland

are reported using instant oxidation

method, respectively, if there are no

land use changes from forest land to cropland, there are no carbon stock

changes in living biomass. Notation

key is changed to NO

Chapters

7.7.2.4,

7.7.2.7

Land

converted to cropland –

CO2

Estimate the losses of carbon

stock in dead organic matter for 2012 and report them under forest

land converted to cropland

FCCC/ARR/2014/

LVA DRAFT,

para 77

Carbon stock changes in dead wood due to conversion of forest land to

cropland are reported using instant

oxidation method, respectively, if there are no land use changes from

forest land to cropland, there are no

carbon stock changes in dead wood.

Notation key is changed to NO


375

Sector

CRF Category/Iss

ue



h


implementation)

Chapter/Section

in the

NIR

Grassland remaining

grassland –

CO2

Include in the NIR the additional information provided to the ERT

that the application of lime and

dolomite takes place only on

cropland and perennial grassland and the associated reporting of

these emissions under cropland


para 78

Lime application is reported according to 2006 IPCC Guidelines

under agriculture sector, therefore,

there is no need for additional

explanation under LULUCF sector

Chapter

5.6

Grassland remaining

grassland –

CO2

Clarify, based on data from the NFI, whether carbon stock

changes in dead biomass occur


para 79

Carbon stock changes in dead biomass due to mortality of trees are

reported in relevant CRF tables and

calculation method is provided in relevant chapter of the National

inventory report.

Chapters 7.6.4,

7.6.7

Settlements

remaining settlements –

CO2

Correct the inconsistency between the estimated and reported values of carbon stock changes in dead

organic matter and the

information provided in the NFI


para 80

Recalculations are done and results reported in relevant CRF tables, methodological issues are reported

under relevant chapters of National

inventory report

Chapters 7.10.4

7.10.8

Waste General

Provide explanations in the NIR for all categories that have been

recalculated


para 83

Explanation provided.

General

Implement the results of the

programme "European Economic Area Financial Mechanism

Programme 2009–2014‖ –

―National Climate Policy‖, which

involves a number of

improvements for the waste

sector


para 85

Results are not implemented yet,

because project is still going.

Solid waste disposal on

land – CH4

Provide in the NIR the sources of information for the methods used

for estimating waste density


para 86

Density is taken form methodology (http://www.lvgmc.lv/fs/CKFinderJa

va/userfiles/files/Vide/Atkritumi/stat

istika/Rokasgramata_atkr_faktori.pd

f), which have many data sources.

Chapter

7.2

Solid waste

disposal on

land – CH4

Include in the NIR the information provided to the ERT

on the comparatively higher emissions from unmanaged solid

waste disposal sites

FCCC/ARR/2014/

LVA DRAFT,

para 87

From year 1970 – 2002 all waste disposal are categorized as

unmanaged. Only from 2002 waste

polygons are started to estimate as managed. That is logical according

to First oder decay method -

emissions from unmanaged are

higher because occurs many years.

Chapter

7.2

Solid waste disposal on

land – CH4

Include in the NIR the

information provided to the ERT on CH4 recovery from

unmanaged solid waste disposal

sites


para 88

Correct distribution of CH4 recovery between managed and unmanaged

sites is not possible, because old landfills and new polygons have

common collecting system and

accounting is dome together for all

collected CH4.

http://www.lvgmc.lv/fs/CKFinderJava/userfiles/files/Vide/Atkritumi/statistika/Rokasgramata_atkr_faktori.pdf





376

Sector

CRF Category/Iss

ue



h


implementation)

Chapter/Section

in the

NIR

Waste incineration –

CO2, CH4

and N2O

Estimate and report these

emissions for the full time series


para 90

Estimation of incinerated amounts back to year 1990 is done and

emissions calculated. CH4 emissions

are not calculated, default emissions

factors not applicable for Latvia.

Chapter

7.4.1

Waste incineration – CO2, CH4

and N2O

Include in the NIR more substantive information on the nature and amounts of hazardous

waste incinerated

FCCC/ARR/2014/

LVA DRAFT,

para 91

Latvia does not have such more precise information about waste

incineration. Data from year 1999 is only about amounts - not about

waste incinerator types.

Chapter

7.4.1

Other (composting)

– CH4 and

N2O

Estimate and report these emissions for the entire time

series


para 92

It will be done for next submission.

Chapter

7.3.1


377

PART 2: SUPPLEMENTARY INFORMATION REQUIRED UNDER ARTICLE 7, PARAGRAPH 1

11. INFORMATION ON ACCOUNTING OF KYOTO UNITS

11.1 BACKGROUND INFORMATION

The standard electronic format tables are included in the submission for the fifth time (see

―RREG1_LV_2014.xlsx‖ attached to the submission). The SEF tables include information on

the AAU, ERU, CER, t-CER, l-CER and RMU in the Latvia’s registry on 31.12.2014 as well as information on transfers of the units in 2014 to and from other Parties of the Kyoto Protocol.

11.2 SUMMARY OF INFORMATION REPORTED IN THE SEF TABLES

At the beginning of the 2014 there were 66 330 176 AAUs, 418 607 ERUs, 322 904 CERs in

the National holding accounts and 5 324 ERUs, 16 107 CERs were held in entity holding accounts. At the beginning of 2014 10 499 146 EUAs and 848 191 CERs and 49 013 ERUs were stored in Retirement account.

At the end of 2014 66 332 433 AAUs, 418 607 ERUs, 322 904 CERs were left in National holding accounts and 21 550 CERs and 5 317 ERUs were held in the entity holding accounts.

10 499 146 EUAs_AAUs, 49 013 ERUs and 848 191 CERs were left in Latvia’s national retirement account during compliance period at the beginning of 2014 and therefore these allowances are also stored in Retirement account.

The registry did not contain any RMUs, t-CERs or l-CERs and no units were in the Article

3.3/3.4 net source cancellation accounts and the t-CER and l-CER replacement accounts.

Total of Kyoto protocol units 76 831 579 AAUs, 472 937 ERUs, 1 192 645 CERs were stored in the ETR accounts at the end of 2014.

Latvia’s assigned amount is 119 182 130 tonnes CO2 eq.

Full details are available in the SEF tables.

11.3 DISCREPANCIES AND NOTIFICATIONS

11.3.1 List of discrepant transactions

No discrepant transactions rejected and / or terminated with the response codes that are considered to be a discrepancy for the purpose of the reporting occurred in 2014 in Latvia’s ETR.

No transactions in Latvia’s ETR were cancelled or terminated.

11.3.2 List of CDM notifications

CDM notifications – reversal of storage notifications, non-certification notifications were received in the reporting period 2014.

The report ―R3: List of CDM notifications‖ is reported empty.


378

11.3.3 List of non-replacements

No non-replacement occurred during reporting period 2014.

It was considered not to report ―R4: List of non-replacements‖ report as the non-replacement list is empty.

11.3.4 List of invalid units

There weren’t any invalid units in Latvia’s ETR in the reporting period from 1st January 2014

to 31st December 2014.

The report ―R5: List of invalid units‖ is reported empty.

11.3.5 Actions and changes to address discrepancies

There weren’t any discrepant transactions that were not terminated and / or cancelled in

Latvia’s ETR during reporting period 2014.

As cancelled and terminated transactions in 2014 were not considered discrepant according to

DES no specific actions to correct any problems were necessary.

11.4 PUBLICLY ACCESSIBLE INFORMATION

The information required to be publicly accessible by the decisions 13/CMP/1 is available in

the user interface of the Latvia’s ETR – http://www.meteo.lv/en/lapas/submission-under-

unframework-of-climate-change-convention-conference-?id=1476&nid=646 as well as in the

webpage http://ec.europa.eu/environment/ets/account.do?languageCode=lv.

http://www.meteo.lv/en/lapas/submission-under-unframework-of-climate-change-convention-conference-?id=1476&nid=646

http://www.meteo.lv/en/lapas/submission-under-unframework-of-climate-change-convention-conference-?id=1476&nid=646

http://ec.europa.eu/environment/ets/account.do?languageCode=lv


379

12. INFORMATION ON CHANGES IN NATIONAL SYSTEM

No changes in National system were made since previous submission.


380

13. INFORMATION ON CHANGES IN NATIONAL REGISTRY

The following changes to the national registry of Latvia have therefore occurred in 2014.

Reporting Item Description

15/CMP.1 annex II.E paragraph 32.(a)

Change of name or contact

1) Jeļena Lazdane-Mihalko

Authorised Representative 1

Latvian Environment, Geology and Meteorology Centre

Address: Maskavas street 165, Riga, LV-1019, Latvia

Tel.: +371 67032015

e-mail: [email protected]

2) Aiva Puļķe


Latvian Environment, Geology and Meteorology Centre

Address: Maskavas street 165, Riga, LV-1019, Latvia

Tel.: +371 67032015


3) Helena Rimša


Ministry of Environmental Protection and Regional Development of the Republic of Latvia

Address: Peldu street 25, Riga, LV-1494, Latvia

Tel.:+371 67026508


No changes of name or contact in the registry following 32(a) during the reported period and previous period. In

previous LATVIA’S NATIONAL INVENTORY REPORT there was incorrect description. The Authorised

Representatives was changed by places, no information about the third Authorised Representative was added, but there was no changes in the registry.

15/CMP.1 annex II.E paragraph 32.(b)

Change regarding cooperation arrangement

No change of cooperation arrangement occurred during the reported period.





381


15/CMP.1 annex II.E paragraph 32.(c)

Change to database structure or the capacity of national registry

An updated diagram of the database structure is attached as Annex A.

Versions of the CSEUR released after 6.1.7.1 (the production version at the time of the last Chapter 14

submission) introduced changes in the structure of the database.

These changes were limited and only affected EU ETS

functionality. No change was required to the database and application backup plan or to the disaster recovery plan.

No change to the capacity of the national registry occurred during the reported period.

15/CMP.1 annex II.E paragraph 32.(d)

Change regarding conformance

to technical standards

Changes introduced since version 6.1.7.1 of the national registry were limited and only affected EU ETS functionality.

However, each release of the registry is subject to both regression testing and tests related to new functionality.

These tests also include thorough testing against the DES and were successfully carried out prior to the relevant major release of the version to Production (see Annex B).

Annex H testing was carried out in February 2015 and the test report is provided as part of this submission.

No other change in the registry's conformance to the technical standards occurred for the reported period.

15/CMP.1 annex II.E paragraph 32.(e)

Change to discrepancies

procedures

No change of discrepancies procedures occurred during the reported period.

15/CMP.1 annex II.E paragraph 32.(f)

Change regarding security

No change of security measures occurred during the reporting period.

15/CMP.1 annex II.E paragraph 32.(g)

Change to list of publicly available information

No change to the list of publicly available information occurred during the reporting period.

15/CMP.1 annex II.E paragraph 32.(h)

Change of Internet address

No change of the registry internet address occurred during the reporting period.


382


15/CMP.1 annex II.E paragraph 32.(i)

Change regarding data integrity measures

No change of data integrity measures occurred during the reporting period.

15/CMP.1 annex II.E paragraph 32.(j)

Change regarding test results

Changes introduced since version 6.1.7.1 of the national registry were limited and only affected EU ETS

functionality. Both regression testing and tests on the new functionality were successfully carried out prior to release of the version to Production. The site acceptance test was

carried out by quality assurance consultants on behalf of and assisted by the European Commission; the report is

attached as Annex B.

Annex H testing was carried out in February 2015 and the test report is provided as part of this submission.


383

14. INFORMATION ON MINIMIZATION OF ADVERSE IMPACTS

IN ACCORDANCE WITH ARTICLE 3, PARAGRAPH 14

Latvia as Annex 1 country provides following information how Latvia is striving, under Article 3, paragraph 14, minimize adverse social, environmental and economic impacts on

developing countries in accordance with the guidelines for the preparation of the information required under Article 7 of the Kyoto Protocol (Decision 15/CMP.1, paragraph 24).

14.1 CROSS-BORDER BILATERAL DEVELOPMENT ASSISTANCE

In 2013 Latvia contributed to development assistance with 17. 9 mil. EUR, 90% of which was distributed through multilateral channels (UN agencies, EU etc.). The rest 10% was disbursed

to specific targets of that year, including support to regional development of Moldova. In 2013 Moldova’s regional development was broadened to the country-wide scale on the basis

of 2012 project ―Support to Moldova’s North Regional Development Agency and Regional Development Council with the Updating of Regional Development Strategy‖, which was reported in Latvia’s National Inventory Report 1990-2012.

The project aimed to improve the capacity of employees of Moldova’s Regional Development Council to create the Strategy of Regional Development 2010-2016, in particular developing

perspective enterprises. Project was implemented by experts of the Ministry of Environmental Protection and Regional Development of the Republic of Latvia, financed by the Ministry of Foreign of Affairs of the Republic of Latvia. During the project, research on business

environment and perspective development directions were done. Recommendations given by Latvian experts on regional development were based on experience of Latvia. Total cost of

the project was EUR 14 229. The project did not specify business sectors; however taking into consideration the EU Sustainable Development Strategy, Latvia implements its commitments in such way that minimize adverse effects to Moldova and other developing countries.

14.2 KEY INSTRUMENTS FOR CLIMATE CHANGE MITIGATION IN LATVIA

Biofuel policy

Although Latvia does not have comprehensive bilateral development assistance network, there are several other ways within Latvia and within the European Union framework, which

we believe have a great potential on minimizing adverse impacts on developing countries. One such instrument is the EU directives: 2009/28/EC on the promotion of the use of energy

from renewable resources and 2003/30/EC on the promotion of the use of biofuels or other renewable fuels for transport. Since 2009 5% biofuel additive to fossil fuels is compulsory. Experts of the Ministry of Economics in 2013 have concluded that the most beneficial

scenario is to grow biofuel crops in Latvia, which excludes competition between food and biofuel cash crops in developing countries.

The Energy Strategy 2030 of Latvia

In March 2013 ―Long-Term Energy Strategy 2030 of Latvia – Competitive Energy for the Society‖ (the Energy Strategy 2030) was approved by the Cabinet of Ministers. It has already

been outlined in the Sustainable Development Strategy of Latvia 2030 (the Strategy) and the Guidelines for the Development of Energy Sector for 2007-2016 (the Guidelines) and it

corresponds to the EU Energy Strategy 2030. The Energy Strategy 2030 envisages increase of renewable energy resources (RER) by 50%. The main renewable energy source according to the Guidelines is hydropower. The Energy Strategy 2030 sets comprehensive long-term action


384

plan to ensure safe supply of energy, increased use of RER and improving energy performance of public and industrial buildings.

Financial instruments

Climate Change Financial Instrument (CCFI) and Cohesion Fund (CH) are two main financial instruments for implementing projects of the use of RER and increasing energy efficiency in

public and industrial buildings. In 2013 EUR 7.4 million from CCFI was allocated for implementing 21 projects for applying technologies using RER for production of hea t energy and electricity. Regarding the aim to increase energy performance in order to reduce

greenhouse gas emissions (GHG) two clusters of projects were implemented in 2013: for industrial buildings and education institution buildings.

To make investments in technological industrial equipment to improve energy performance of industrial buildings 11 projects financed by CCFI have been implemented under the CCFI tender ―Complex Solutions for Reducing Greenhouse Gas Emissions‖ with total amount of

EUR 2 million. At the same time 31 projects financed by the CCFI (EUR 6 million) were applied to improve energy efficiency of education institution buildings.

14.3 CONCLUSION

Since submission of 2014 limited changes in the activities minimizing adverse impacts have occurred. Significant changes in reducing fiscal incentives, tax exemptions, subsidies in GHG

emitting sectors and amendments of regulations have not been made. However, the approval of the Energy Strategy 2030 and available financial instruments are essential tools for climate

change mitigation.

Latvia due to its size and share in international trade does not have any significant impact on developing countries and yet effort is put to maintain it and develop in a sustainable way.

14.4 REFERENCES

- Ecologic Institute and eclareon. 2014. Assessment of climate change policies in the

context of the European Semester. Country Report: Latvia. http://ec.europa.eu/clima/policies/g-gas/progress/docs/lv_2014_en.pdf

- EU. 2006. EU Sustainable Development Strategy.

- Ministry of Economics. 2013. Informatīvais ziņojums par situāciju biodegvielu ražošanas nozarē.

- Ministry of Economics. 2013. Informative Report. Long-Term Energy Strategy of Latvia 2030 – Competitive Energy for the Society.

- Ministry of Foreign Affairs. 2014. Latvia’s contribution to development assistance.

http://www.mfa.gov.lv/en/policy/development-co-operation/latvia-s-contribution-to-development-assistance

- Ministry of Foreign Affairs. Latvijas attīstības sadarbības politika. 2015. http://www.mfa.gov.lv/arpolitika/attistibas-sadarbiba/latvijas-attistibas-sadarbibas-politika

http://ec.europa.eu/clima/policies/g-gas/progress/docs/lv_2014_en.pdf



http://www.mfa.gov.lv/arpolitika/attistibas-sadarbiba/latvijas-attistibas-sadarbibas-politika

http://www.mfa.gov.lv/arpolitika/attistibas-sadarbiba/latvijas-attistibas-sadarbibas-politika


385

ANNEXES TO THE NATIONAL INVENTORY REPORT

ANNEX 1 KEY CATEGORIES

A.1.1 Spreadsheet for the Approach 1 analysis for year 2013 – level assessment with

LULUCF

IPCC category/Group Gas Base year emissions or removals

Year 2013 emissions or removals

Absolute value of 2013 emissions

Activity data uncertainty

Emission factor / estimation

parameter uncertainty

Level assessment

Cumulative total of Level assessment

4.A.1 Forest Land remaining Forest Land – Drained organic soil

CO2 4125.54896 4252.175208 4252.175208 0.06 1.11 0.126575414 12.66%

4.A.1 Forest Land remaining Forest Land – Carbon stock change, living biomass

CO2 -19499.28721 -4136.117297 4136.117297 0.025 0.123120693 24.97%

4.A.1 Forest Land remaining Forest Land – Carbon stock change, dead wood

CO2 77.30730333 -3801.986511 3801.986511 0.02 0.11317455 36.29%

4.B.1 Cropla nd remaining Cropland – Drained organic soil

CO2 2761.36609 2576.809411 2576.809411 0.13 0.9 0.07670444 43.96%

4. G. Harvested wood products CO2 -166.3561979 -2141.522557 2141.522557 0.15 0 0.063747163 50.33%

1.A.1.a Public Electricity and Heat Production - Gaseous Fuels

CO2 2644.318679 1789.305004 1789.305004 0.02 0.05 0.053262627 55.66%

1.A.3.b Road Transportation - Diesel Oil CO2 616.1359677 1741.886302 1741.886302 0.02 0.5 0.051851104 60.84%

3.D.1. Direct N2O emissions from managed soils

N2O 2183.630811 1240.469649 1240.469649 0.02 0.5 0.036925327 64.54%

4.D.1. Wetlands, Peat extraction from lands, organic soil s

CO2 1016.928 917.4083375 917.4083375 0.24 1.58 0.027308691 67.27%

3.A.1 Enteric Fermentation - Cattle CH4 2178.340191 765.2269298 765.2269298 0.02 0.2 0.022778675 69.54%

4.C.1 Grassland remaining Grassland – Drained organic soil

CO2 874.7530284 651.3619279 651.3619279 0.23 0.9 0.019389231 71.48%

1.A.3.b Road Transportation - Gasoli ne CO2 1723.750448 625.9575 625.9575 0.02 0.5 0.018633012 73.35%

4.E.2 Land converted to Settlements – Carbon stock change – living biomass

CO2 113.1222033 594.71159 594.71159 1.69 0.017702908 75.12%

4.A.1. Forest land, Emissions and removals from drainage and rewetting and other management of organic and mineral soils

N2O 567.8831994 590.0496563 590.0496563 0.07 1.87 0.017564135 76.87%

4.C.2 Land converted to Grassland –Mineral

soil

CO2 -0.003061255 -560.4792382 560.4792382 0.11 0.016683906 78.54%

2.A.1. Cement Production CO2 370.8039966 537.6437303 537.6437303 0.1 0.05 0.016004157 80.14%

5.A.2. Unmanaged Waste Disposal Sites CH4 392.8311633 346.2876433 346.2876433 0.2 0.52 0.010308019 81.17%

1.A.4.c Agriculture/Forestry/Fisheries -

Liquid Fuels

CO2 695.0757089 317.4303672 317.4303672 0.02 0.1069 0.009449018 82.12%

4.D.1 Wetlands remaining Wetlands – Carbon stock change –organic soils

CO2 277.2 277.2 277.2 0.24 1.58 0.008251472 82.94%

4.A.2 Land converted to Forest Land – Carbon stock change, grassland converted to forest land

CO2 -0.174093333 -276.7873533 276.7873533 0.15 0.008239189 83.77%

1.A.4.a Commercial/Institutional - Gaseous Fuels

CO2 274.4466477 242.7711156 242.7711156 0.02 0.05 0.00722662 84.49%

4.E.2 Land converted to Settlements –

Carbon stock change – dead organic matter

CO2 45.01128341 238.3274994 238.3274994 0.21 0.007094346 85.20%

1.A.4.b Residential - Gaseous Fuels CO2 219.6011945 231.3293677 231.3293677 0.02 0.05 0.006886031 85.89%

1.A.3.c Railways - Liquid Fuels CO2 531.37994 223.258 223.258 0.02 0.05 0.006645769 86.55%

5.A.1. Managed Waste Disposal on Land CH4 0 186.6154068 186.6154068 0.2 0.52 0.005555021 87.11%

1.A.4.b Residential - Biomass Fuels CH4 150.075 181.2375 181.2375 0.1 0.5 0.005394936 87.65%


386

IPCC category/Group Gas Base year emissions or

removals

Year 2013 emissions or

removals

Absolute value of 2013

emissions

Activity data

uncertainty

Emission factor /

estimation parameter uncertainty

Level assessment

Cumulative total of Level

assessment

4.E.2 Land converted to Settlements –

Organic soils

CO2 3.765666667 173.7967198 173.7967198 0.62 0.9 0.005173444 88.16%

4.D.1 Wetlands remaining Wetlands – Carbon stock change – living biomass

CO2 -65.31052 -161.4256967 161.4256967 2.24 0.004805193 88.65%

1.A.4.b Residential - Liquid Fuels CO2 329.9110639 154.26032 154.26032 0.02 0.1 0.0045919 89.10%

4.C.2 Land converted to Grassland – Drained organic soil

CO2 0.000861458 147.8708275 147.8708275 0.52 0.9 0.004401703 89.54%

1.A.3.b Road Transportation - LPG CO2 36.95737306 147.8567316 147.8567316 0.02 0.5 0.004401283 89.98%

1.A.4.a Commercial/Institutional - Liquid Fuels

CO2 1007.294341 142.1295097 142.1295097 0.02 0.1 0.0042308 90.41%

5.D.2 Industrial Wastewater CH4 137.025 137.625 137.625 0.02 0.3 0.004096713 90.82%


CH4 56.17169761 130.5862744 130.5862744 0.07 1.02 0.00388719 91.21%

1.A.2.f Non-metallic Minerals - Solid Fuels CO2 16.4292 122.8854 122.8854 0.02 0.2 0.003657956 91.57%

1.A.2.g Other - Liqui d Fuels CO2 795.7039841 122.1484903 122.1484903 0.02 0.1 0.00363602 91.94%

4.B. Cropla nd remaining cropland, Emissions and removals from drainage and rewetting and other management of organic and mineral soils

CH4 125.0939765 117.6632261 117.6632261 0.13 0.71 0.003502507 92.29%

4.E.1 Settlements remaining Settlements – Carbon stock change – living biomass

CO2 -48.28378424 -105.6971782 105.6971782 2.1 0.003146311 92.60%

1.A.2.g Other - Gaseous Fuels CO2 524.168965 104.6567463 104.6567463 0.02 0.05 0.00311534 92.91%

2.F.1. Refrigeration and air conditioning HFCs 0 102.8615524 102.8615524 0.75 0.75 0.003061902 93.22%

4.E.2 Land converted to Settlements – Mineral soils

CO2 1.399567031 100.4322263 100.4322263 0.21 0.002989588 93.52%

1.A.2.e Food Processi ng, Beverages and Tobacco - Gaseous Fuels

CO2 174.2220665 98.04113849 98.04113849 0.02 0.05 0.002918412 93.81%

1.A.2.f Non-metallic Minerals - Other

Fossil Fuels

CO2 0 92.50516 92.50516 0.02 0.02 0.002753621 94.08%

4.B.2 Land converted to Cropland – Drained organic soil

CO2 12.166 85.162 85.162 1.3 0.9 0.002535036 94.34%

4.A.1 Forest land remaining forest land - Controlled bur ning

CO2 256.17754 83.34388 83.34388 0.92 0.06 0.002480915 94.59%

1.B.2.b Natural Gas CH4 177.238 82.3568 82.3568 0.3115 0.01 0.002451533 94.83%

1.A.2.f Non-metallic Minerals - Gaseous Fuels

CO2 314.4838285 72.88013835 72.88013835 0.02 0.05 0.002169439 95.05%

3.B.1.1 Manure Management - Cattle CH4 99.92910799 70.54136894 70.54136894 0.25 0.2 0.00209982 95.26%

4.A.2 Land Converted to Forest Land – grassland converted to forest land, carbon stock change, dead w ood

CO2 -1.729127891 -68.69365758 68.69365758 0.09 0.002044819 95.46%

5.D.1 Domestic Wastewater CH4 222.8 64.8 64.8 0.1 0.3 0.001928916 95.66%

4.A.2 Land Converted to Forest Land – grassland converted to forest land, carbon

stock change, litter

CO2 -1.525469 -60.602861 60.602861 0.09 0.001803978 95.84%

4.C. Grassland, Emissions and removals from drainage and rewetting and other management of organic and mineral soils

CH4 66.19807613 60.48292143 60.48292143 0.06 0.6 0.001800408 96.02%

3.B.1.3 Manure Management - Swaine CH4 224.4975 58.4925 58.4925 0.25 0.3 0.001741159 96.19%


Gaseous Fuels

CO2 778.5312078 57.80522878 57.80522878 0.02 0.5 0.001720701 96.36%

1.A.1.c Manufacture of Solid Fuels and Other Energy Industries - Gaseous Fuels

CO2 44.69904433 50.37622658 50.37622658 0.02 0.05 0.00149956 96.51%

1.A.4.b Residential - Solid Fuels CO2 605.8184 50.138 50.138 0.02 0.2 0.001492469 96.66%

3.B.2.1 Manure Management - Cattle N2O 124.5366808 49.48558332 49.48558332 0.25 0.2 0.001473048 96.81%

4.E.2 Lands converted to settlements, Direct

nitrous oxide (N2O) emissions from nitrogen (N) mineralization/immobilization associated with loss/gain of soil organic matter

N2O 0.910566118 49.34129338 49.34129338 0.87 0.7 0.001468753 96.96%


387


removals


removals


emissions

Activity data

uncertainty

Emission factor /


Level assessment


assessment

resulting from change of land use or

management of mineral soils

1.A.4.a Commercial/Institutional - Solid Fuels

CO2 1410.784936 49.0974 49.0974 0.02 0.2 0.001461493 97.10%

4.B.2 Land converted to Cropland –Mineral soil

CO2 6.98223392 48.54695124 48.54695124 0.32 0.001445108 97.25%

3.B.5 Indirect N2O emissions from Manure Management

N2O 142.1423263 47.57185732 47.57185732 0.02 0.5 0.001416082 97.39%

4.C.1 Grassland remaining Grassland –

Carbon stock change – living biomass

CO2 -19.17968712 -41.72134122 41.72134122 0.61 0.001241928 97.51%

1.A.1.a Public Electricity and Heat Production - Solid Fuels

CO2 218.053 40.1104 40.1104 0.02 0.2 0.001193975 97.63%

1.A.4.a Commercial/Institutional - Biomass Fuels

CH4 39.135 39.52177273 39.52177273 0.05 0.5 0.001176453 97.75%

4.A.2 Land converted to Forest Land – grassland converted to forest land, Drained organic soil

CO2 3.355733333 37.895 37.895 0.72 1.11 0.001128029 97.86%

1.A.2.e Food Processing, Beverages and Tobacco - Liquid Fuels

CO2 798.2058686 33.22587 33.22587 0.02 0.1113 0.000989042 97.96%

4.D.1 Wetlands remaining Wetlands – Carbon stock change – dead organic matter

CO2 -13.80987667 -29.95736333 29.95736333 0.06 0.000891747 98.05%

1.A.2.a Iron and Steel - Gaseous Fuels CO2 234.4643123 29.87868767 29.87868767 0.02 0.05 0.000889405 98.14%

1.A.4.b Residential - Biomass Fuels N2O 23.85192 28.75998 28.75998 0.1 0.5 0.000856105 98.22%

4.D.1. Wetlands, Peat extraction from lands, organic soils

CH4 28.53444375 28.53444375 28.53444375 0.24 0.8 0.000849391 98.31%

1.A.3.c Railways - Liquid Fuels N2O 61.20060747 26.122382 26.122382 0.02 0.5 0.000777591 98.39%

4.C.2. Lands converted to grasslands, Direct nitrous oxide (N2O) emissions from nitrogen (N) mineralization/immobilization associated with loss/gain of soil organic matter

resulting from change of land use or management of mineral soils

N2O 0.000147896 25.3866853 25.3866853 0.68 0.37 0.000755691 98.46%

1.A.3.d Domestic Naviagtion - Diesel Oil CO2 0.8332289 25.16 25.16 0.02 0.05 0.000748943 98.54%

4.B.2 Land converted to cropland, Direct nitrous oxide (N2O) emissions from nitrogen (N) mineralization/immobilization associated

with loss/gain of soil organic matter resulting from change of land use or management of mineral soils

N2O 3.15132616 22.5734702 22.5734702 1.31 0.73 0.000671949 98.60%

1.A.2.f Non-metallic Minerals - Liquid Fuels CO2 273.5769252 21.97829728 21.97829728 0.02 0.1 0.000654233 98.67%

1.A.2.c Chemicals - Gaseous Fuels CO2 23.42449305 20.87712296 20.87712296 0.02 0.05 0.000621454 98.73%

1.A.1.c Manufacture of Solid Fuels and Other Energy Industries - Liquid Fuels

CO2 24.7792529 18.87025524 18.87025524 0.02 0.1 0.000561715 98.79%

1.B.2.c Venting and Flaring CH4 70.344325 18.642 18.642 0.1 0.01 0.00055492 98.84%

4.A.1. Forest land, Emissions and removals from drainage and rewetting and other


CO2 0 18.39 18.39 0.72 0.25 0.000547419 98.90%

3.A.2 Enteric Fermentation - Sheep CH4 32.92 16.96 16.96 0.02 0.4 0.000504852 98.95%

1.A.1.a Public Electricity and Heat Production - Liquid Fuels

CO2 3049.621305 15.86030086 15.86030086 0.02 0.1 0.000472117 99.00%

4.E.1 Settlements remaining Settlements –

Drained organic soils

CO2 0 15.32483431 15.32483431 0.08 0.9 0.000456178 99.04%

1.A.2.g Other - Biomass Fuels N2O 0.455344 15.2293496 15.2293496 0.05 0.5 0.000453335 99.09%

3.A.3 Enteric Fermentation - Swine CH4 52.54125 13.78125 13.78125 0.02 0.4 0.000410229 99.13%

3.G. Liming CO2 371.4186667 13.7756667 13.7756667 0.02 0.5 0.000410063 99.17%

1.A.3.b Road Transportation - Diesel Oil N2O 5.593827044 13.09045627 13.09045627 0.02 0.5 0.000389666 99.21%

1.A.1.a Public Electricity and Heat Production - Biomass Fuels

N2O 0.519712 11.01384 11.01384 0.05 0.5 0.000327851 99.24%

4.E.1 Settlements remaining Settlements – Carbon stock change – dead organic matter

CO2 -6.108421479 -10.78459125 10.78459125 0.08 0.000321027 99.27%


388


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Level assessment


assessment

3.B.2.4 Manure Management - Other

livestock

N2O 22.04902 9.58666 9.58666 0.25 0.3 0.000285368 99.30%

1.A.2.g Other - Biomass Fuels CH4 0.2865 9.58215 9.58215 0.05 0.5 0.000285234 99.33%

2.A.4. Other process uses of carbonates CO2 69.184752 9.050385865 9.050385865 0.02 0.5 0.000269405 99.36%

1.A.2.a Iron and Steel - Solid Fuels CO2 5.671 8.7096 8.7096 0.02 0.2 0.000259261 99.38%



CO2 -4.28449168 -8.708601291 8.708601291 0.05 0.000259231 99.41%

1.A.2.c Chemicals - Liquid Fuels CO2 276.6786727 8.55381336 8.55381336 0.02 0.1 0.000254623 99.43%

2.G.1. Electrical equipment SF6 0 8.50315813 8.50315813 0.02 0.3 0.000253115 99.46%

4.B.1 Cropland remaining Cropland – Carbon stock change – living biomass

CO2 -6.134341743 -8.205353949 8.205353949 3.5 0.000244251 99.48%

4.A.1 Forest land remaining forest land - Controlled burning

CH4 25.2045 8.2 8.2 0.92 0.36 0.000244091 99.51%

3.B.1.4 Manure Management - Other livestock

CH4 83.38555 7.57375 7.57375 0.25 0.3 0.000225449 99.53%

3.A.4 Enteric Fermentation - Other livestock CH4 18.092 7.542775 7.542775 0.02 0.4 0.000224527 99.55%

1.A.2.b Non-Ferrous Metals - Gaseous Fuels CO2 0 7.483228491 7.483228491 0.02 0.05 0.000222755 99.58%


CH4 0.327 6.940298662 6.940298662 0.05 0.5 0.000206593 99.60%

5.D.1 Domestic Wastewater N2O 3.929726 6.612322 6.612322 0.1 0.3 0.00019683 99.62%

1.A.5.b Mobile - Liquid Fuels CO2 0 6.447874167 6.447874167 0.02 0.5 0.000191935 99.64%


N2O 6.219856 6.292871419 6.292871419 0.05 0.5 0.000187321 99.65%

1.A.2.d. Pulp, Paper and Print - Gaseous Fuels

CO2 149.4154681 5.585308222 5.585308222 0.02 0.05 0.000166259 99.67%

1.A.2.g Other - Solid Fuels CO2 27.263264 4.73 4.73 0.02 0.2 0.000140799 99.69%

1.A.3.b Road Transportation - Gasoline N2O 13.07410741 4.586290942 4.586290942 0.02 0.5 0.000136521 99.70%

1.A.3.b Road Transportation - Lubricants CO2 3.4629 4.33188 4.33188 0.1 0.5 0.000128948 99.71%

5.C.1 Waste Incineration N2O 4.847024532 4.313387888 4.313387888 0.2 1 0.000128398 99.72%

1.A.1.a Public Electricity and Heat Production - Peat

CO2 142.826737 4.15465786 4.15465786 0.02 0.15 0.000123673 99.74%

3.H. Urea Application CO2 7.7088 4.075866667 4.075866667 0.2 0.05 0.000121327 99.75%

1.A.4.b Residential - Solid Fuels CH4 48.03 3.975 3.975 0.02 0.5 0.000118325 99.76%


N2O 3.793114286 3.793114286 3.793114286 0.24 1.12 0.00011291 99.77%


Biomass Fuels

CH4 9.15 3.627804811 3.627804811 0.05 0.5 0.00010799 99.78%

3.B.2.3 Manure Management - Swaine N2O 15.35892 3.60282 3.60282 0.25 0.3 0.000107246 99.79%

2.F.4. Aerosols HFCs 0 3.52216298 3.52216298 0.75 0.75 0.000104845 99.80%

4.E.2 Settlements remaining Settlements,

Direct nitrous oxide (N2O) emissi ons from nitrogen (N) mineralization/immobilization associated with loss/gain of soil organic

matter resulting from change of land use or management of mineral soils

N2O 3.2207095 3.2207095 9.58716E-05 99.81%

1.A.3.a Domestic Aviation - Jet kerosene CO2 0.054819072 3.107107044 3.107107044 0.02 0.5 9.24899E-05 99.82%

1.A.3.d Domestic Naviagtion - Diesel Oil N2O 0.1006644 3.0396 3.0396 0.02 0.5 9.04804E-05 99.83%

4.A.1 Forest land remaining forest land -

wildfires

CH4 2.466906545 3.018876526 3.018876526 0.37 0.36 8.98635E-05 99.84%


389


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2.A.3. Glass production CO2 0.352 2.976908 2.976908 0.02 0.6 8.86143E-05 99.85%

4 (IV) Indirect nitrous oxide (N2O) emissions from managed soils

N2O 0.16057137 2.97600236 2.97600236 8.85873E-05 99.86%

1.A.3.b Road Transportation - LPG N2O 0.163685304 2.463208388 2.463208388 0.02 0.5 7.33229E-05 99.87%

1.A.4.c Agriculture/Forestry/Fisheries - Solid Fuels

CO2 102.28152 2.4596 2.4596 0.02 0.5 7.32154E-05 99.87%

1.A.3.b Road Transportation - Gasoline CH4 17.15516309 2.455797158 2.455797158 0.02 0.5 7.31022E-05 99.88%

1.A.2.e Food Processing, Beverages and Tobacco - Solid Fuels

CO2 103.071464 2.365 2.365 0.02 0.2 7.03995E-05 99.89%

1.A.2.e Food Processing, Beverages and Tobacco - Other Fossil Fuels

CO2 0 2.1257 2.1257 0.02 0.2 6.32762E-05 99.89%

1.A.2.c Chemicals - Peat CO2 0 2.07732893 2.07732893 0.02 0.1 6.18363E-05 99.90%

2.G.4. Other HFCs 0 1.835685463 1.835685463 0.75 0.75 5.46432E-05 99.91%

5.B.1. Composting CH4 0 1.4367 1.4367 0.2 1 4.27666E-05 99.91%

4.B.1 Cropland remaining Cropland – Carbon stock change – dead organic matter

CO2 -1.368079328 -1.339381629 1.339381629 0.03 3.98697E-05 99.91%

1.A.2.f Non-metallic Minerals - Other Fossil

Fuels

N2O 0 1.294887885 1.294887885 0.02 0.5 3.85452E-05 99.92%

5.B.1. Composting N2O 0 1.2844098 1.2844098 0.2 0.9 3.82333E-05 99.92%

1.A.4.b Residential - Liquid Fuels CH4 0.868375 1.270375 1.270375 0.02 0.5 3.78155E-05 99.93%

1.A.4.c Agriculture/Forestry/Fisheries - Liquid Fuels

CH4 5.99375 1.250225 1.250225 0.02 0.5 3.72157E-05 99.93%

1.A.3.b Road Transportation - Diesel Oil CH4 1.108041461 1.116917573 1.116917573 0.02 0.5 3.32475E-05 99.93%

1.A.2.f Non-metallic Minerals - Biomass Fuels

N2O 0.008344 1.056180881 1.056180881 0.05 0.5 3.14396E-05 99.94%

3.B.2.2 Manure Management - Sheep N2O 1.32908 1.03108 1.03108 0.25 0.3 3.06924E-05 99.94%

1.A.1.a Public Electricity and Heat

Production - Gaseous Fuels

N2O 1.4367772 0.9833106 0.9833106 0.02 0.5 2.92704E-05 99.94%


N2O 2.95616 0.96254 0.96254 0.92 2.86521E-05 99.94%

2.C.1 Iron and Steel Production CO2 12.81611267 0.955378707 0.955378707 0.05 0.25 2.8439E-05 99.95%


N2O 2.908143856 0.911925296 0.911925296 0.02 0.5 2.71455E-05 99.95%


CH4 1.20535 0.824925 0.824925 0.02 0.5 2.45557E-05 99.95%

1.A.2.f Non-metallic Minerals - Other Fossil Fuels

CH4 0 0.814736505 0.814736505 0.02 0.5 2.42524E-05 99.95%

1.A.3.b Road Transportation - LPG CH4 0.124565463 0.801443483 0.801443483 0.02 0.5 2.38567E-05 99.96%

1.A.4.a Commercial/Institutional - Liquid

Fuels

CH4 3.495 0.74775 0.74775 0.02 0.5 2.22584E-05 99.96%


CH4 0.00525 0.66454334 0.66454334 0.05 0.5 1.97816E-05 99.96%

1.A.4.c Agriculture/Forestry/Fisheries - Biomass Fuels

N2O 1.45424 0.588801467 0.588801467 0.05 0.5 1.7527E-05 99.96%

1.A.2.f Non-metallic Minerals - Solid Fuels N2O 0.07599 0.580653 0.580653 0.02 0.5 1.72844E-05 99.97%


CH4 0.6255 0.559625 0.559625 0.02 0.5 1.66585E-05 99.97%

2.D.3.d Urea Use CO2 0 0.537788082 0.537788082 0.2 0.1 1.60085E-05 99.97%

1.A.2.e Food Processing, Beverages and Tobacco - Biomass Fuels

N2O 0.271776 0.5352974 0.5352974 0.05 0.5 1.59343E-05 99.97%

1.A.4.b Residential - Gaseous Fuels CH4 0.5005 0.53325 0.53325 0.02 0.5 1.58734E-05 99.97%


390


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5.C.1 Waste Incineration CO2 0.810707594 0.4274336 0.4274336 0.2 0.4 1.27235E-05 99.97%

3.B.1.2 Manure Management - Sheep CH4 0.78185 0.4028 0.4028 0.25 0.3 1.19902E-05 99.97%

1.A.2.g Other - Peat CO2 0 0.39 0.39 0.02 0.1 1.16092E-05 99.98%


N2O 2.411706848 0.358718096 0.358718096 0.02 0.5 1.0678E-05 99.98%

4.A.1 Forest land remaining forest land -

wildfires

N2O 0.289234682 0.3539509 0.3539509 0.37 1.05361E-05 99.98%

1.A.1.c Manufacture of Solid Fuels and Other Energy Industries - Biomass Fuels

N2O 0 0.352832 0.352832 0.05 0.5 1.05028E-05 99.98%

1.A.4.b Residential - Liquid Fuels N2O 0.4500694 0.343223288 0.343223288 0.02 0.5 1.02168E-05 99.98%


CH4 0.171 0.336825 0.336825 0.05 0.5 1.00263E-05 99.98%

1.A.3.c Railways - Liquid Fuels CH4 0.745009038 0.31799375 0.31799375 0.02 0.5 9.46579E-06 99.98%

1.A.3.b Road Transportation - Biomass N2O 0 0.307472263 0.307472263 0.02 0.5 9.15259E-06 99.98%

2.D.1 Lubricant Use CO2 0.571307104 0.3071332 0.3071332 0.02 0.25 9.1425E-06 99.98%

1.A.2.g Other - Liquid Fuels N2O 2.149772 0.297218048 0.297218048 0.02 0.5 8.84735E-06 99.98%

1.A.3.a Domestic Aviation - Aviation Gasoline CO2 0.011005031 0.28 0.28 0.02 0.5 8.33482E-06 99.98%

1.A.3.d Domestic Naviagtion - Gasoline CO2 0.172771761 0.2772 0.2772 0.2 0.05 8.25147E-06 99.99%

2.A.2. Lime Production CO2 148.8573814 0.274894634 0.274894634 0.02 0.5 8.18285E-06 99.99%

1.A.2.c Chemicals - Biomass Fuels N2O 0 0.24953815 0.24953815 0.05 0.5 7.42806E-06 99.99%

2.F.3. Fire Protection HFCs 0 0.2369598 0.2369598 0.75 0.75 7.05363E-06 99.99%

1.A.4.b Residential - Solid Fuels N2O 2.862588 0.23691 0.23691 0.02 0.5 7.05215E-06 99.99%

1.A.4.a Commercial/Institutional - Solid

Fuels

N2O 6.66618252 0.231993 0.231993 0.02 0.5 6.90579E-06 99.99%


CH4 0 0.222 0.222 0.05 0.5 6.60832E-06 99.99%


CH4 8.109 0.195 0.195 0.02 0.5 5.80461E-06 99.99%

1.A.2.g Other - Liquid Fuels CH4 2.26531 0.194025 0.194025 0.02 0.5 5.77558E-06 99.99%


N2O 1.030335 0.189528 0.189528 0.02 0.5 5.64172E-06 99.99%

4.C.1 Grassland remaining Grassland, wildfires

N2O 0.05399279 0.183306897 0.183306897 0.1 0.48 5.45654E-06 99.99%


CH4 0.049609866 0.168426759 0.168426759 0.1 0.39 5.0136E-06 99.99%

1.A.2.c Chemicals - Biomass Fuels CH4 0 0.157344085 0.157344085 0.05 0.5 4.6837E-06 99.99%

5.D.2 Industrial Wastewater N2O 2.341428614 0.141334546 0.141334546 0.1 0.3 4.20714E-06 99.99%


N2O 0.1491192 0.1334146 0.1334146 0.02 0.5 3.97138E-06 99.99%


Gaseous Fuels

CH4 1.774375 0.13325 0.13325 0.02 0.5 3.96648E-06 99.99%

2.D.2 Paraffin wax use CO2 0 0.132 0.132 0.02 0.5 3.92927E-06 99.99%


Fuels

CH4 3.72829 0.12975 0.12975 0.02 0.5 3.8623E-06 100.00%

1.A.4.b Residential - Gaseous Fuels N2O 0.1193192 0.1271268 0.1271268 0.02 0.5 3.78421E-06 100.00%

1.A.2.d. Pulp, Paper and Print - Biomass

Fuels

N2O 0 0.115624 0.115624 0.05 0.5 3.4418E-06 100.00%


391


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1.A.2.d. Pulp, Paper and Print - Biomass

Fuels

CH4 0 0.07275 0.07275 0.05 0.5 2.16556E-06 100.00%


N2O 1.87891384 0.057812 0.057812 0.02 0.5 1.7209E-06 100.00%

1.A.2.g Other - Gaseous Fuels N2O 0.28480456 0.057514 0.057514 0.02 0.5 1.71203E-06 100.00%

1.A.2.e Food Processing, Beverages and Tobacco - Gaseous Fuels

N2O 0.09466268 0.0538784 0.0538784 0.02 0.5 1.60381E-06 100.00%

1.A.2.f Non-metallic Minerals - Liquid Fuels N2O 0.64092648 0.0531036 0.0531036 0.02 0.5 1.58075E-06 100.00%

2.D.3.b Road paving with asphalt CO2 0.001463305 0.052980255 0.052980255 0.2 0.6 1.57707E-06 100.00%

1.A.5.b Mobile - Liquid Fuels N2O 0 0.052371989 0.052371989 0.02 0.5 1.55897E-06 100.00%

1.A.2.g Other - Gaseous Fuels CH4 0.23893 0.04825 0.04825 0.02 0.5 1.43627E-06 100.00%

2.D.3.c Asphalt roofing CO2 0.002972338 0.047829397 0.047829397 0.2 0.6 1.42375E-06 100.00%


N2O 0.05379496 0.045594 0.045594 0.02 0.5 1.35721E-06 100.00%


CH4 0.079415 0.0452 0.0452 0.02 0.5 1.34548E-06 100.00%

1.A.2.f Non-metallic Minerals - Gaseous

Fuels

N2O 0.1708732 0.0400512 0.0400512 0.02 0.5 1.19221E-06 100.00%

1.A.2.a Iron and Steel - Solid Fuels N2O 0.023691 0.037548 0.037548 0.02 0.5 1.1177E-06 100.00%


N2O 7.1626684 0.0371308 0.0371308 0.02 0.5 1.10528E-06 100.00%


N2O 0 0.034568 0.034568 0.02 0.5 1.02899E-06 100.00%

1.A.3.d Domestic Naviagtion - Diesel Oil CH4 0.001126 0.034 0.034 0.02 0.5 1.01209E-06 100.00%


CH4 0.14335 0.0336 0.0336 0.02 0.5 1.00018E-06 100.00%

1.A.3.b Road Transportation - Lubricants N2O 0.02384 0.03278 0.03278 0.1 0.5 9.75769E-07 100.00%

1.A.2.f Non-metallic Minerals - Solid Fuels CH4 0.00425 0.032475 0.032475 0.02 0.5 9.6669E-07 100.00%

1.A.4.c Agriculture/Forestry/Fisheries - Gaseous Fuels

N2O 0.423011 0.0317668 0.0317668 0.02 0.5 9.45609E-07 100.00%

1.A.3.a Domestic Aviation - Jet kerosene N2O 0.000453151 0.028884544 0.028884544 0.02 0.5 8.59812E-07 100.00%


N2O 0.024287 0.0276842 0.0276842 0.02 0.5 8.24082E-07 100.00%


CH4 0.78871 0.026525 0.026525 0.02 0.5 7.89575E-07 100.00%

2.C.1 Iron and Steel Production CH4 0.06875 0.02414875 0.02414875 0.1 0.25 7.18841E-07 100.00%


CH4 0.020375 0.023225 0.023225 0.02 0.5 6.91344E-07 100.00%

1.A.2.g Other - Solid Fuels N2O 0.12419448 0.02235 0.02235 0.02 0.5 6.65297E-07 100.00%

1.A.2.f Non-metallic Minerals - Liquid Fuels CH4 0.268845 0.022275 0.022275 0.02 0.5 6.63065E-07 100.00%


CH4 0 0.02175 0.02175 0.02 0.5 6.47437E-07 100.00%

1.A.3.b Road Transportation - Biomass CH4 0 0.020267227 0.020267227 0.02 0.5 6.03299E-07 100.00%

1.A.3.c. Railway Biomass Fuels N2O 0 0.0200256 0.0200256 0.02 0.5 5.96106E-07 100.00%

1.A.1.c Manufacture of Solid Fuels and

Other Energy Industries - Liquid Fuels

CH4 0.02314 0.019125 0.019125 0.02 0.5 5.69298E-07 100.00%


N2O 0.615519 0.01788 0.01788 0.02 0.5 5.32238E-07 100.00%

1.A.2.a Iron and Steel - Gaseous Fuels N2O 0.127395 0.0164198 0.0164198 0.02 0.5 4.88772E-07 100.00%


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Production - Liquid Fuels

CH4 3.00505 0.015625 0.015625 0.02 0.5 4.65113E-07 100.00%

1.A.3.b Road Transportation - Lubricants CH4 0.02475 0.01425 0.01425 0.1 0.5 4.24183E-07 100.00%

1.A.2.a Iron and Steel - Gaseous Fuels CH4 0.106875 0.013775 0.013775 0.02 0.5 4.10043E-07 100.00%


N2O 0.4832964 0.011622 0.011622 0.02 0.5 3.45955E-07 100.00%

1.A.2.c Chemicals - Gaseous Fuels N2O 0.01272758 0.011473 0.011473 0.02 0.5 3.41519E-07 100.00%

1.A.5.b Mobile - Liquid Fuels CH4 0 0.011410463 0.011410463 0.02 0.5 3.39658E-07 100.00%


N2O 0.47777148 0.011175 0.011175 0.02 0.5 3.32649E-07 100.00%


CH4 0.057625 0.0106 0.0106 0.02 0.5 3.15532E-07 100.00%

1.A.2.c Chemicals - Gaseous Fuels CH4 0.0106775 0.009625 0.009625 0.02 0.5 2.86509E-07 100.00%

1.A.2.c Chemicals - Peat N2O 0 0.00894 0.00894 0.02 0.5 2.66119E-07 100.00%

1.B.2.b Natural Gas CO2 0.008686 0.006516 0.006516 0.3115 0.01 1.93963E-07 100.00%

2.G.3. N2O from product uses N2O 0.004768 0.005364 0.005364 0.02 0.02 1.59671E-07 100.00%

1.A.3.d Domestic Naviagtion - Gasoline CH4 0.00295205 0.004739595 0.004739595 0.2 0.5 1.41085E-07 100.00%

1.A.2.b Non-Ferrous Metals - Gaseous Fuels N2O 0 0.0041124 0.0041124 0.02 0.5 1.22415E-07 100.00%

1.A.2.c Chemicals - Liquid Fuels N2O 0.65129688 0.0040826 0.0040826 0.02 0.5 1.21528E-07 100.00%

1.A.3.a Domestic Aviation - Jet kerosene CH4 0.000009504 0.00355575 0.00355575 0.02 0.5 1.05845E-07 100.00%

1.A.2.b Non-Ferrous Metals - Gaseous Fuels CH4 0 0.00345 0.00345 0.02 0.5 1.02697E-07 100.00%

1.A.2.c Chemicals - Liquid Fuels CH4 0.273195 0.003425 0.003425 0.02 0.5 1.01953E-07 100.00%

1.A.2.d. Pulp, Paper and Print - Gaseous

Fuels

N2O 0.08118414 0.0030694 0.0030694 0.02 0.5 9.13675E-08 100.00%


CH4 0.0681075 0.002575 0.002575 0.02 0.5 7.66506E-08 100.00%

1.A.3.a Domestic Aviation - Aviation Gasoline N2O 9.36998E-05 0.002384 0.002384 0.02 0.5 7.0965E-08 100.00%

1.A.2.a Iron and Steel - Solid Fuels CH4 0.001325 0.0021 0.0021 0.02 0.5 6.25112E-08 100.00%

1.A.2.g Other - Peat N2O 0 0.001788 0.001788 0.02 0.5 5.32238E-08 100.00%

1.B.2.c Venting and Flaring CO2 0.002806 0.001476 0.001476 0.1 0.01 4.39364E-08 100.00%

1.A.3.c. Railway Biomass Fuels CH4 0 0.00132 0.00132 0.02 0.5 3.92927E-08 100.00%

1.A.2.g Other - Solid Fuels CH4 0.006946 0.00125 0.00125 0.02 0.5 3.7209E-08 100.00%


CH4 0.034425 0.001 0.001 0.02 0.5 2.97672E-08 100.00%

1.A.2.c Chemicals - Peat CH4 0 0.001 0.001 0.02 0.5 2.97672E-08 100.00%

1.A.2.e Food Processing, Beverages and

Tobacco - Solid Fuels

CH4 0.026721 0.000625 0.000625 0.02 0.5 1.86045E-08 100.00%

1.A.3.d Domestic Naviagtion - Gasoline N2O 0.000219506 0.000352182 0.000352182 0.2 0.5 1.04835E-08 100.00%

1.A.2.g Other - Peat CH4 0 0.0001 0.0001 0.02 0.5 2.97672E-09 100.00%

1.A.3.a Domestic Aviation - Aviation Gasoline CH4 1.96519E-06 0.00005 0.00005 0.02 0.5 1.48836E-09 100.00%


Production - Other fossil fuels

CO2 3.0786 0 0 0.02 0.2 0 100.00%


393


removals


removals


emissions

Activity data

uncertainty

Emission factor /


Level assessment


assessment



CH4 0.0315 0 0 0.02 0.5 0 100.00%

1.A.1.a Public Electricity and Heat Production - Other fossil fuels

N2O 0.050064 0 0 0.02 0.5 0 100.00%

1.A.1.c Manufacture of Solid Fuels and Other Energy Industries - Solid Fuels

CO2 0 0 0 0.02 0.2 0 100.00%


CO2 0 0 0.05 0.1 0 100.00%

1.A.1.c Manufacture of Solid Fuels and

Other Energy Industries - Peat

CO2 73.83865681 0 0 0.02 0.1 0 100.00%


CH4 0 0 0 0.02 0.5 0 100.00%

1.A.1.c Manufacture of Solid Fuels and Other Energy Industries - Peat

CH4 0.0177725 0 0 0.02 0.5 0 100.00%


N2O 0 0 0 0.02 0.5 0 100.00%


N2O 0.3177723 0 0 0.02 0.5 0 100.00%

1.A.2.a Iron and Steel - Liquid Fuels CO2 93.25228881 0 0 0.02 0.1 0 100.00%

1.A.2.a Iron and Steel - Biomass Fuels CO2 0 0 0 0.05 0.1 0 100.00%

1.A.2.a Iron and Steel - Peat CO2 0 0 0 0.02 0.1 0 100.00%

1.A.2.a Iron and Steel - Other fossil fuels CO2 61.3521 0 0 0.02 0.2 0 100.00%

1.A.2.a Iron and Steel - Liquid Fuels CH4 0.091425 0 0 0.02 0.5 0 100.00%

1.A.2.a Iron and Steel - Biomass Fuels CH4 0 0 0 0.05 0.5 0 100.00%

1.A.2.a Iron and Steel - Peat CH4 0 0 0 0.02 0.5 0 100.00%

1.A.2.a Iron and Steel - Other fossil fuels CH4 0.62775 0 0 0.02 0.5 0 100.00%

1.A.2.a Iron and Steel - Liquid Fuels N2O 0.2179572 0 0 0.02 0.5 0 100.00%

1.A.2.a Iron and Steel - Biomass Fuels N2O 0 0 0 0.05 0.5 0 100.00%

1.A.2.a Iron and Steel - Peat N2O 0 0 0 0.02 0.5 0 100.00%

1.A.2.a Iron and Steel - Other fossil fuels N2O 0.997704 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Liquid Fuels CO2 0 0 0 0.02 0.1 0 100.00%

1.A.2.b Non-Ferrous Metals - Solid Fuels CO2 0 0 0 0.02 0.2 0 100.00%

1.A.2.b Non-Ferrous Metals - Biomass Fuels CO2 0 0 0 0.05 0.1 0 100.00%

1.A.2.b Non-Ferrous Metals - Peat CO2 0 0 0 0.02 0.1 0 100.00%

1.A.2.b Non-Ferrous Metals - Liquid Fuels CH4 0 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Solid Fuels CH4 0 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Biomass Fuels CH4 0 0 0 0.05 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Peat CH4 0 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Liquid Fuels N2O 0 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Solid Fuels N2O 0 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Biomass Fuels N2O 0 0 0 0.05 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Peat N2O 0 0 0 0.02 0.5 0 100.00%


394


removals


removals


emissions

Activity data

uncertainty

Emission factor /


Level assessment


assessment

1.A.2.d. Pulp, Paper and Print - Liquid Fuels CO2 15.54739345 0 0 0.02 0.1 0 100.00%

1.A.2.d. Pulp, Paper and Print - Solid Fuels CO2 2.692316 0 0 0.02 0.2 0 100.00%

1.A.2.d. Pulp, Paper and Print - Peat CO2 0 0 0 0.02 0.1 0 100.00%

1.A.2.d. Pulp, Paper and Print - Liquid Fuels CH4 0.015225 0 0 0.02 0.5 0 100.00%

1.A.2.d. Pulp, Paper and Print - Solid Fuels CH4 0.0007115 0 0 0.02 0.5 0 100.00%

1.A.2.d. Pulp, Paper and Print - Peat CH4 0 0 0 0.02 0.5 0 100.00%

1.A.2.d. Pulp, Paper and Print - Liquid Fuels N2O 0.0362964 0 0 0.02 0.5 0 100.00%

1.A.2.d. Pulp, Paper and Print - Solid Fuels N2O 0.01272162 0 0 0.02 0.5 0 100.00%

1.A.2.d. Pulp, Paper and Print - Peat N2O 0 0 0 0.02 0.5 0 100.00%

1.A.2.e Food Processing, Beverages and Tobacco - Peat

CO2 0 0 0 0.02 0.1 0 100.00%


CH4 0 0 0 0.02 0.5 0 100.00%


Tobacco - Peat

N2O 0 0 0 0.02 0.5 0 100.00%

1.A.2.f Non-metallic Minerals - Peat CO2 0 0 0 0.02 0.1 0 100.00%

1.A.2.f Non-metallic Minerals - Peat CH4 0 0 0 0.02 0.5 0 100.00%

1.A.2.f Non-metallic Minerals - Peat N2O 0 0 0 0.02 0.5 0 100.00%

1.A.2.g Other - Other Fossil Fuels CO2 0 0 0 0.02 0.2 0 100.00%

1.A.2.g Other - Other Fossil Fuels CH4 0 0 0 0.02 0.5 0 100.00%

1.A.2.g Other - Other Fossil Fuels N2O 0 0 0 0.02 0.5 0 100.00%

1.A.3.b Road Transportation - Gaseous

Fuels

CO2 17.6165255 0 0 0.02 0.5 0 100.00%

1.A.3.b Road Transportation - Gaseous Fuels

CH4 0.7015 0 0 0.02 0.5 0 100.00%


N2O 0.27267 0 0 0.02 0.5 0 100.00%

1.A.4.a Commercial/Institutional - Peat CO2 66.54499789 0 0 0.02 0.1 0 100.00%

1.A.4.a Commercial/Institutional - Other Fossil Fuels

CO2 0 0 0 0.02 0.2 0 100.00%

1.A.4.a Commercial/Institutional - Peat CH4 0.168 0 0 0.02 0.5 0 100.00%


CH4 0 0 0 0.02 0.5 0 100.00%

1.A.4.a Commercial/Institutional - Peat N2O 0.2955862 0 0 0.02 0.5 0 100.00%


N2O 0 0 0 0.02 0.5 0 100.00%

1.A.4.b Residential - Peat CO2 42.27150449 0 0 0.02 0.1 0 100.00%

1.A.4.b Residential - Other Fossil Fuels CO2 0 0 0 0.02 0.2 0 100.00%

1.A.4.b Residential - Peat CH4 3.1875 0 0 0.02 0.5 0 100.00%

1.A.4.b Residential - Other Fossil Fuels CH4 0 0 0 0.02 0.5 0 100.00%

1.A.4.b Residential - Peat N2O 0.1860712 0 0 0.02 0.5 0 100.00%

1.A.4.b Residential - Other Fossil Fuels N2O 0 0 0 0.02 0.5 0 100.00%


395


removals


removals


emissions

Activity data

uncertainty

Emission factor /


Level assessment


assessment

1.A.4.c Agriculture/Forestry/Fisheries - Peat CO2 3.0225 0 0 0.02 0.5 0 100.00%

1.A.4.c Agriculture/Forestry/Fisheries - Other Fossil Fuels

CO2 0 0 0 0.02 0.5 0 100.00%

1.A.4.c Agriculture/Forestry/Fisheries - Peat CH4 0.2325 0 0 0.02 0.5 0 100.00%


CH4 0 0 0 0.02 0.5 0 100.00%

1.A.4.c Agriculture/Forestry/Fisheries - Peat N2O 0.013857 0 0 0.02 0.5 0 100.00%


N2O 0 0 0 0.02 0.5 0 100.00%

2.D.3. Solvent Use CO2 0 0 0 0.02 0.2 0 100.00%

2.F.2 Foam blowing agents HFCs 0 0 0 0.75 0.75 0 100.00%

4.B.2 Land converted to Cropland – Carbon stock change, forest land converted to cropland

CO2 364.39865 0 0 0.45 0 100.00%

4.B.1 Land converted to Cropland – Carbon stock change – dead organic matter

CO2 111.6529333 0 0 0.32 0 100.00%

Total 17284.8703 10765.94797 33594.00593 40.448 132.3882 1 317.1713851

A.1.2 Spreadsheet for the Approach 1 analysis for year 2013 – level assessment without

LULUCF


removals


removals

ABS Year 2013 emissions or

removals




Level assessment

Cumulative total of LA


CO2 2644.318679 1789.305004 1789.305004 0.02 0.05 0.163949971 16.39%

1.A.3.b Road Transportation - Diesel Oil

CO2 616.1359677 1741.886302 1741.886302 0.02 0.5 0.159605103 32.36%

3.D.1. Direct N2O emissions from

managed soils

N2O 2183.630811 1240.469649 1240.469649 0.02 0.5 0.113661429 43.72%


1.A.3.b Road Transportation - Gasoline

CO2 1723.750448 625.9575 625.9575 0.02 0.5 0.05735507 56.47%


5.A.2. Unmanaged Waste Disposal

Sites

CH4 392.8311633 346.2876433 346.2876433 0.2 0.52 0.031729554 64.57%


Liquid Fuels

CO2 695.0757089 317.4303672 317.4303672 0.02 0.1069 0.029085427 67.48%


CO2 274.4466477 242.7711156 242.7711156 0.02 0.05 0.022244568 69.70%



5.A.1. Managed Waste Disposal on Land

CH4 0 186.6154068 186.6154068 0.2 0.52 0.017099148 75.58%





CO2 1007.294341 142.1295097 142.1295097 0.02 0.1 0.013023006 81.31%



396


removals


removals


removals




Level assessment


1.A.2.f Non-metallic Minerals - Solid Fuels

CO2 16.4292 122.8854 122.8854 0.02 0.2 0.011259711 83.69%

1.A.2.g Other - Liquid Fuels CO2 795.7039841 122.1484903 122.1484903 0.02 0.1 0.01119219 84.81%


2.F.1. Refrigeration and air

conditioning

HFCs 0 102.8615524 102.8615524 0.75 0.75 0.009424971 86.72%


CO2 174.2220665 98.04113849 98.04113849 0.02 0.05 0.008983288 87.61%


CO2 0 92.50516 92.50516 0.02 0.02 0.008476039 88.46%

1.B.2.b Natural Gas CH4 177.238 82.3568 82.3568 0.3115 0.01 0.007546167 89.22%


CO2 314.4838285 72.88013835 72.88013835 0.02 0.05 0.006677842 89.88%

3.B.1.1 Manure Management - Cattle

CH4 99.92910799 70.54136894 70.54136894 0.25 0.2 0.006463546 90.53%


3.B.1.3 Manure Management -

Swaine

CH4 224.4975 58.4925 58.4925 0.25 0.3 0.005359535 91.66%


Gaseous Fuels

CO2 778.5312078 57.80522878 57.80522878 0.02 0.5 0.005296562 92.19%


CO2 44.69904433 50.37622658 50.37622658 0.02 0.05 0.00461586 92.65%


3.B.2.1 Manure Management - Cattle

N2O 124.5366808 49.48558332 49.48558332 0.25 0.2 0.004534252 93.56%


CO2 1410.784936 49.0974 49.0974 0.02 0.2 0.004498684 94.01%


N2O 142.1423263 47.57185732 47.57185732 0.02 0.5 0.004358902 94.45%


CO2 218.053 40.1104 40.1104 0.02 0.2 0.003675225 94.82%


CH4 39.135 39.52177273 39.52177273 0.05 0.5 0.003621291 95.18%


CO2 798.2058686 33.22587 33.22587 0.02 0.1113 0.003044411 95.48%

1.A.2.a Iron and Steel - Gaseous Fuels

CO2 234.4643123 29.87868767 29.87868767 0.02 0.05 0.002737717 95.76%



1.A.3.d Domestic Naviagtion - Diesel Oil

CO2 0.8332289 25.16 25.16 0.02 0.05 0.002305354 96.49%

1.A.2.f Non-metallic Minerals - Liquid Fuels

CO2 273.5769252 21.97829728 21.97829728 0.02 0.1 0.002013822 96.69%



CO2 24.7792529 18.87025524 18.87025524 0.02 0.1 0.001729039 97.06%




CO2 3049.621305 15.86030086 15.86030086 0.02 0.1 0.001453244 97.53%



3.G. Liming CO2 371.4186667 13.7756667 13.7756667 0.02 0.5 0.001262233 97.92%


397


removals


removals


removals




Level assessment



N2O 5.593827044 13.09045627 13.09045627 0.02 0.5 0.001199449 98.04%


N2O 0.519712 11.01384 11.01384 0.05 0.5 0.001009173 98.14%


N2O 22.04902 9.58666 9.58666 0.25 0.3 0.000878404 98.23%


2.A.4. Other process uses of carbonates

CO2 69.184752 9.050385865 9.050385865 0.02 0.5 0.000829266 98.40%



2.G.1. Electrical equipment SF6 0 8.50315813 8.50315813 0.02 0.3 0.000779125 98.64%


CH4 83.38555 7.57375 7.57375 0.25 0.3 0.000693966 98.70%

3.A.4 Enteric Fermentation - Other livestock

CH4 18.092 7.542775 7.542775 0.02 0.4 0.000691127 98.77%

1.A.2.b Non-Ferrous Metals -

Gaseous Fuels

CO2 0 7.483228491 7.483228491 0.02 0.05 0.000685671 98.84%


CH4 0.327 6.940298662 6.940298662 0.05 0.5 0.000635924 98.91%


1.A.5.b Mobile - Liquid Fuels CO2 0 6.447874167 6.447874167 0.02 0.5 0.000590804 99.03%


N2O 6.219856 6.292871419 6.292871419 0.05 0.5 0.000576602 99.08%


CO2 149.4154681 5.585308222 5.585308222 0.02 0.05 0.000511769 99.13%


1.A.3.b Road Transportation -

Gasoline

N2O 13.07410741 4.586290942 4.586290942 0.02 0.5 0.000420231 99.22%

1.A.3.b Road Transportation - Lubricants

CO2 3.4629 4.33188 4.33188 0.1 0.5 0.00039692 99.26%

5.C.1 Waste Incineration N2O 4.847024532 4.313387888 4.313387888 0.2 1 0.000395226 99.30%


CO2 142.826737 4.15465786 4.15465786 0.02 0.15 0.000380682 99.34%

3.H. Urea Application CO2 7.7088 4.075866667 4.075866667 0.2 0.05 0.000373462 99.37%



CH4 9.15 3.627804811 3.627804811 0.05 0.5 0.000332408 99.44%


Swaine

N2O 15.35892 3.60282 3.60282 0.25 0.3 0.000330118 99.48%

2.F.4. Aerosols HFCs 0 3.52216298 3.52216298 0.75 0.75 0.000322728 99.51%

1.A.3.a Domestic Aviation - Jet kerosene

CO2 0.054819072 3.107107044 3.107107044 0.02 0.5 0.000284697 99.54%


N2O 0.1006644 3.0396 3.0396 0.02 0.5 0.000278512 99.57%

2.A.3. Glass production CO2 0.352 2.976908 2.976908 0.02 0.6 0.000272767 99.59%

1.A.3.b Road Transportation - LPG N2O 0.163685304 2.463208388 2.463208388 0.02 0.5 0.000225698 99.62%


CO2 102.28152 2.4596 2.4596 0.02 0.5 0.000225368 99.64%


CH4 17.15516309 2.455797158 2.455797158 0.02 0.5 0.000225019 99.66%


CO2 103.071464 2.365 2.365 0.02 0.2 0.0002167 99.68%


398


removals


removals


removals




Level assessment



CO2 0 2.1257 2.1257 0.02 0.2 0.000194773 99.70%

1.A.2.c Chemicals - Peat CO2 0 2.07732893 2.07732893 0.02 0.1 0.000190341 99.72%

2.G.4. Other HFCs 0 1.835685463 1.835685463 0.75 0.75 0.0001682 99.74%

5.B.1. Composting CH4 0 1.4367 1.4367 0.2 1 0.000131642 99.75%


N2O 0 1.294887885 1.294887885 0.02 0.5 0.000118648 99.76%

5.B.1. Composting N2O 0 1.2844098 1.2844098 0.2 0.9 0.000117688 99.77%

1.A.4.b Residential - Liquid Fuels CH4 0.868375 1.270375 1.270375 0.02 0.5 0.000116402 99.79%


CH4 5.99375 1.250225 1.250225 0.02 0.5 0.000114555 99.80%


CH4 1.108041461 1.116917573 1.116917573 0.02 0.5 0.000102341 99.81%


N2O 0.008344 1.056180881 1.056180881 0.05 0.5 9.67755E-05 99.82%


Sheep

N2O 1.32908 1.03108 1.03108 0.25 0.3 9.44755E-05 99.83%


N2O 1.4367772 0.9833106 0.9833106 0.02 0.5 9.00985E-05 99.84%

2.C.1 Iron and Steel Production CO2 12.81611267 0.955378707 0.955378707 0.05 0.25 8.75392E-05 99.84%


N2O 2.908143856 0.911925296 0.911925296 0.02 0.5 8.35577E-05 99.85%


CH4 1.20535 0.824925 0.824925 0.02 0.5 7.5586E-05 99.86%


CH4 0 0.814736505 0.814736505 0.02 0.5 7.46525E-05 99.87%



CH4 3.495 0.74775 0.74775 0.02 0.5 6.85146E-05 99.88%


CH4 0.00525 0.66454334 0.66454334 0.05 0.5 6.08906E-05 99.89%


N2O 1.45424 0.588801467 0.588801467 0.05 0.5 5.39505E-05 99.89%


N2O 0.07599 0.580653 0.580653 0.02 0.5 5.32039E-05 99.90%

1.A.4.a Commercial/Institutional -

Gaseous Fuels

CH4 0.6255 0.559625 0.559625 0.02 0.5 5.12772E-05 99.90%

2.D.3.d Urea Use CO2 0 0.537788082 0.537788082 0.2 0.1 4.92763E-05 99.91%


N2O 0.271776 0.5352974 0.5352974 0.05 0.5 4.90481E-05 99.91%



3.B.1.2 Manure Management - Sheep

CH4 0.78185 0.4028 0.4028 0.25 0.3 3.69077E-05 99.93%

1.A.2.g Other - Peat CO2 0 0.39 0.39 0.02 0.1 3.57348E-05 99.93%


Liquid Fuels

N2O 2.411706848 0.358718096 0.358718096 0.02 0.5 3.28685E-05 99.93%

1.A.1.c Manufacture of Solid Fuels and Other Energy Industries -

Biomass Fuels

N2O 0 0.352832 0.352832 0.05 0.5 3.23292E-05 99.94%



CH4 0.171 0.336825 0.336825 0.05 0.5 3.08625E-05 99.94%



399


removals


removals


removals




Level assessment


1.A.3.b Road Transportation - Biomass

N2O 0 0.307472263 0.307472263 0.02 0.5 2.8173E-05 99.95%



1.A.3.a Domestic Aviation - Aviation

Gasoline

CO2 0.011005031 0.28 0.28 0.02 0.5 2.56558E-05 99.96%

1.A.3.d Domestic Naviagtion - Gasoline

CO2 0.172771761 0.2772 0.2772 0.2 0.05 2.53992E-05 99.96%

2.A.2. Lime Production CO2 148.8573814 0.274894634 0.274894634 0.02 0.5 2.5188E-05 99.96%

1.A.2.c Chemicals - Biomass Fuels N2O 0 0.24953815 0.24953815 0.05 0.5 2.28646E-05 99.96%

2.F.3. Fire Protection HFCs 0 0.2369598 0.2369598 0.75 0.75 2.17121E-05 99.97%



N2O 6.66618252 0.231993 0.231993 0.02 0.5 2.1257E-05 99.97%

1.A.1.c Manufacture of Solid Fuels

and Other Energy Industries - Biomass Fuels

CH4 0 0.222 0.222 0.05 0.5 2.03414E-05 99.97%

1.A.4.c Agriculture/Forestry/Fisheries - Solid

Fuels

CH4 8.109 0.195 0.195 0.02 0.5 1.78674E-05 99.97%



N2O 1.030335 0.189528 0.189528 0.02 0.5 1.7366E-05 99.98%

1.A.2.c Chemicals - Biomass Fuels CH4 0 0.157344085 0.157344085 0.05 0.5 1.44171E-05 99.98%



N2O 0.1491192 0.1334146 0.1334146 0.02 0.5 1.22245E-05 99.98%


CH4 1.774375 0.13325 0.13325 0.02 0.5 1.22094E-05 99.98%

2.D.2 Paraffin wax use CO2 0 0.132 0.132 0.02 0.5 1.20949E-05 99.98%


CH4 3.72829 0.12975 0.12975 0.02 0.5 1.18887E-05 99.99%


1.A.2.d. Pulp, Paper and Print -

Biomass Fuels

N2O 0 0.115624 0.115624 0.05 0.5 1.05944E-05 99.99%

1.A.2.d. Pulp, Paper and Print - Biomass Fuels

CH4 0 0.07275 0.07275 0.05 0.5 6.66592E-06 99.99%


N2O 1.87891384 0.057812 0.057812 0.02 0.5 5.29718E-06 99.99%


1.A.2.e Food Processing, Beverages

and Tobacco - Gaseous Fuels

N2O 0.09466268 0.0538784 0.0538784 0.02 0.5 4.93676E-06 99.99%


N2O 0.64092648 0.0531036 0.0531036 0.02 0.5 4.86576E-06 99.99%


1.A.5.b Mobile - Liquid Fuels N2O 0 0.052371989 0.052371989 0.02 0.5 4.79873E-06 99.99%




N2O 0.05379496 0.045594 0.045594 0.02 0.5 4.17768E-06 99.99%


CH4 0.079415 0.0452 0.0452 0.02 0.5 4.14157E-06 99.99%


400


removals


removals


removals




Level assessment



N2O 0.1708732 0.0400512 0.0400512 0.02 0.5 3.6698E-06 99.99%



N2O 7.1626684 0.0371308 0.0371308 0.02 0.5 3.40221E-06 99.99%


and Tobacco - Other Fossil Fuels

N2O 0 0.034568 0.034568 0.02 0.5 3.16739E-06 99.99%


CH4 0.001126 0.034 0.034 0.02 0.5 3.11534E-06 99.99%


CH4 0.14335 0.0336 0.0336 0.02 0.5 3.07869E-06 99.99%


N2O 0.02384 0.03278 0.03278 0.1 0.5 3.00356E-06 100.00%


CH4 0.00425 0.032475 0.032475 0.02 0.5 2.97561E-06 100.00%


N2O 0.423011 0.0317668 0.0317668 0.02 0.5 2.91072E-06 100.00%


N2O 0.000453151 0.028884544 0.028884544 0.02 0.5 2.64663E-06 100.00%


and Other Energy Industries - Gaseous Fuels

N2O 0.024287 0.0276842 0.0276842 0.02 0.5 2.53664E-06 100.00%


CH4 0.78871 0.026525 0.026525 0.02 0.5 2.43043E-06 100.00%



CH4 0.020375 0.023225 0.023225 0.02 0.5 2.12805E-06 100.00%



CH4 0.268845 0.022275 0.022275 0.02 0.5 2.04101E-06 100.00%


CH4 0 0.02175 0.02175 0.02 0.5 1.9929E-06 100.00%


CH4 0 0.020267227 0.020267227 0.02 0.5 1.85704E-06 100.00%

1.A.3.c. Railway Biomass Fuels N2O 0 0.0200256 0.0200256 0.02 0.5 1.8349E-06 100.00%

1.A.1.c Manufacture of Solid Fuels and Other Energy Industries - Liquid

Fuels

CH4 0.02314 0.019125 0.019125 0.02 0.5 1.75238E-06 100.00%


N2O 0.615519 0.01788 0.01788 0.02 0.5 1.6383E-06 100.00%


N2O 0.127395 0.0164198 0.0164198 0.02 0.5 1.50451E-06 100.00%


CH4 3.00505 0.015625 0.015625 0.02 0.5 1.43168E-06 100.00%


CH4 0.02475 0.01425 0.01425 0.1 0.5 1.3057E-06 100.00%


CH4 0.106875 0.013775 0.013775 0.02 0.5 1.26217E-06 100.00%


N2O 0.4832964 0.011622 0.011622 0.02 0.5 1.0649E-06 100.00%


1.A.5.b Mobile - Liquid Fuels CH4 0 0.011410463 0.011410463 0.02 0.5 1.04551E-06 100.00%


N2O 0.47777148 0.011175 0.011175 0.02 0.5 1.02394E-06 100.00%


Production - Solid Fuels

CH4 0.057625 0.0106 0.0106 0.02 0.5 9.71254E-07 100.00%


1.A.2.c Chemicals - Peat N2O 0 0.00894 0.00894 0.02 0.5 8.19152E-07 100.00%



401


removals


removals


removals




Level assessment




CH4 0.00295205 0.004739595 0.004739595 0.2 0.5 4.34278E-07 100.00%

1.A.2.b Non-Ferrous Metals - Gaseous Fuels

N2O 0 0.0041124 0.0041124 0.02 0.5 3.7681E-07 100.00%



CH4 0.000009504 0.00355575 0.00355575 0.02 0.5 3.25805E-07 100.00%


CH4 0 0.00345 0.00345 0.02 0.5 3.16116E-07 100.00%



N2O 0.08118414 0.0030694 0.0030694 0.02 0.5 2.81242E-07 100.00%


CH4 0.0681075 0.002575 0.002575 0.02 0.5 2.35941E-07 100.00%

1.A.3.a Domestic Aviation - Aviation Gasoline

N2O 9.36998E-05 0.002384 0.002384 0.02 0.5 2.18441E-07 100.00%


1.A.2.g Other - Peat N2O 0 0.001788 0.001788 0.02 0.5 1.6383E-07 100.00%


1.A.3.c. Railway Biomass Fuels CH4 0 0.00132 0.00132 0.02 0.5 1.20949E-07 100.00%



CH4 0.034425 0.001 0.001 0.02 0.5 9.16277E-08 100.00%

1.A.2.c Chemicals - Peat CH4 0 0.001 0.001 0.02 0.5 9.16277E-08 100.00%


and Tobacco - Solid Fuels

CH4 0.026721 0.000625 0.000625 0.02 0.5 5.72673E-08 100.00%


N2O 0.000219506 0.000352182 0.000352182 0.2 0.5 3.22696E-08 100.00%

1.A.2.g Other - Peat CH4 0 0.0001 0.0001 0.02 0.5 9.16277E-09 100.00%


CH4 1.96519E-06 0.00005 0.00005 0.02 0.5 4.58139E-09 100.00%


CO2 3.0786 0 0 0.02 0.2 0 100.00%


CH4 0.0315 0 0 0.02 0.5 0 100.00%


N2O 0.050064 0 0 0.02 0.5 0 100.00%


and Other Energy Industries - Solid Fuels

CO2 0 0 0 0.02 0.2 0 100.00%


CO2 73.83865681 0 0 0.02 0.1 0 100.00%


CH4 0 0 0 0.02 0.5 0 100.00%


CH4 0.0177725 0 0 0.02 0.5 0 100.00%


and Other Energy Industries - Solid Fuels

N2O 0 0 0 0.02 0.5 0 100.00%


N2O 0.3177723 0 0 0.02 0.5 0 100.00%

1.A.2.a Iron and Steel - Liquid Fuels CO2 93.25228881 0 0 0.02 0.1 0 100.00%

1.A.2.a Iron and Steel - Biomass Fuels

CO2 0 0 0 0.05 0.1 0 100.00%

1.A.2.a Iron and Steel - Peat CO2 0 0 0 0.02 0.1 0 100.00%


402


removals


removals


removals




Level assessment


1.A.2.a Iron and Steel - Other fossil fuels

CO2 61.3521 0 0 0.02 0.2 0 100.00%

1.A.2.a Iron and Steel - Liquid Fuels CH4 0.091425 0 0 0.02 0.5 0 100.00%


CH4 0 0 0 0.05 0.5 0 100.00%

1.A.2.a Iron and Steel - Peat CH4 0 0 0 0.02 0.5 0 100.00%


CH4 0.62775 0 0 0.02 0.5 0 100.00%

1.A.2.a Iron and Steel - Liquid Fuels N2O 0.2179572 0 0 0.02 0.5 0 100.00%


N2O 0 0 0 0.05 0.5 0 100.00%

1.A.2.a Iron and Steel - Peat N2O 0 0 0 0.02 0.5 0 100.00%


N2O 0.997704 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Liquid Fuels

CO2 0 0 0 0.02 0.1 0 100.00%

1.A.2.b Non-Ferrous Metals - Solid

Fuels

CO2 0 0 0 0.02 0.2 0 100.00%

1.A.2.b Non-Ferrous Metals - Biomass Fuels

CO2 0 0 0 0.05 0.1 0 100.00%

1.A.2.b Non-Ferrous Metals - Peat CO2 0 0 0 0.02 0.1 0 100.00%


CH4 0 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Solid Fuels

CH4 0 0 0 0.02 0.5 0 100.00%


CH4 0 0 0 0.05 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Peat CH4 0 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Liquid

Fuels

N2O 0 0 0 0.02 0.5 0 100.00%


N2O 0 0 0 0.02 0.5 0 100.00%


N2O 0 0 0 0.05 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Peat N2O 0 0 0 0.02 0.5 0 100.00%

1.A.2.d. Pulp, Paper and Print - Liquid Fuels

CO2 15.54739345 0 0 0.02 0.1 0 100.00%

1.A.2.d. Pulp, Paper and Print - Solid Fuels

CO2 2.692316 0 0 0.02 0.2 0 100.00%

1.A.2.d. Pulp, Paper and Print - Peat

CO2 0 0 0 0.02 0.1 0 100.00%


Liquid Fuels

CH4 0.015225 0 0 0.02 0.5 0 100.00%


CH4 0.0007115 0 0 0.02 0.5 0 100.00%


CH4 0 0 0 0.02 0.5 0 100.00%


N2O 0.0362964 0 0 0.02 0.5 0 100.00%


N2O 0.01272162 0 0 0.02 0.5 0 100.00%


N2O 0 0 0 0.02 0.5 0 100.00%


CO2 0 0 0 0.02 0.1 0 100.00%


and Tobacco - Peat

CH4 0 0 0 0.02 0.5 0 100.00%


N2O 0 0 0 0.02 0.5 0 100.00%

1.A.2.f Non-metallic Minerals - Peat CO2 0 0 0 0.02 0.1 0 100.00%


403


removals


removals


removals




Level assessment


1.A.2.f Non-metallic Minerals - Peat CH4 0 0 0 0.02 0.5 0 100.00%

1.A.2.f Non-metallic Minerals - Peat N2O 0 0 0 0.02 0.5 0 100.00%

1.A.2.g Other - Other Fossil Fuels CO2 0 0 0 0.02 0.2 0 100.00%

1.A.2.g Other - Other Fossil Fuels CH4 0 0 0 0.02 0.5 0 100.00%

1.A.2.g Other - Other Fossil Fuels N2O 0 0 0 0.02 0.5 0 100.00%


CO2 17.6165255 0 0 0.02 0.5 0 100.00%


CH4 0.7015 0 0 0.02 0.5 0 100.00%


N2O 0.27267 0 0 0.02 0.5 0 100.00%

1.A.4.a Commercial/Institutional - Peat

CO2 66.54499789 0 0 0.02 0.1 0 100.00%


CO2 0 0 0 0.02 0.2 0 100.00%


Peat

CH4 0.168 0 0 0.02 0.5 0 100.00%


CH4 0 0 0 0.02 0.5 0 100.00%


N2O 0.2955862 0 0 0.02 0.5 0 100.00%


N2O 0 0 0 0.02 0.5 0 100.00%

1.A.4.b Residential - Peat CO2 42.27150449 0 0 0.02 0.1 0 100.00%

1.A.4.b Residential - Other Fossil Fuels

CO2 0 0 0 0.02 0.2 0 100.00%

1.A.4.b Residential - Peat CH4 3.1875 0 0 0.02 0.5 0 100.00%

1.A.4.b Residential - Other Fossil

Fuels

CH4 0 0 0 0.02 0.5 0 100.00%

1.A.4.b Residential - Peat N2O 0.1860712 0 0 0.02 0.5 0 100.00%


N2O 0 0 0 0.02 0.5 0 100.00%

1.A.4.c Agriculture/Forestry/Fisheries - Peat

CO2 3.0225 0 0 0.02 0.5 0 100.00%


CO2 0 0 0 0.02 0.5 0 100.00%


CH4 0.2325 0 0 0.02 0.5 0 100.00%


CH4 0 0 0 0.02 0.5 0 100.00%


N2O 0.013857 0 0 0.02 0.5 0 100.00%


Other Fossil Fuels

N2O 0 0 0 0.02 0.5 0 100.00%

2.D.3. Solvent Use CO2 0 0 0 0.02 0.2 0 100.00%

2.F.2 Foam blowing agents HFCs 0 0 0 0.75 0.75 0 100.00%

Total 26184.37109 10913.72564 10913.72564 15.663 111.6882 1 268.2296467


404

A.1.3 Spreadsheet for the Approach 1 analysis for year 2013 – trend assessment with LULUCF

IPCC category/Group Gas Base year

emissions or removals

Year 2013


Activity

data uncertainty

Emission

factor / estimation parameter uncertainty

Trend

assessment

Contribution

to trend

Cumulative

total of contribution to trend

4.A.1 Forest Land remaining Forest Land – Carbon stock change, living biomass

CO2 -19499.28721 -4136.117297 0.025 0.4634 0.254779143 0.254779143

4.A.1 Forest Land remaining Forest Land – Carbon stock change, dead wood

CO2 77.30730333 -3801.986511 0.02 0.2227 0.1224777 37.73%

4. G. Harvested wood products CO2 -166.3561979 -2141.522557 0.15 0 0.1179 0.064828372 44.21%


CO2 3049.621305 15.86030086 0.02 0.1 0.1090 0.059919931 50.20%

4.A.1 Forest Land remaining Forest Land – Drained organic soil

CO2 4125.54896 4252.175208 0.06 1.11 0.0973 0.053524378 55.55%

1.A.3.b Road Transportation - Diesel Oil CO2 616.1359677 1741.886302 0.02 0.5 0.0786 0.043203614 59.87%

4.B.1 Cropland remaining Cropland – Drained organic soil

CO2 2761.36609 2576.809411 0.13 0.9 0.0496 0.027258487 62.60%


CO2 1410.784936 49.0974 0.02 0.2 0.0480 0.026391106 65.24%


4.C.2 Land converted to Grassland –Mineral soil

CO2 -0.003061255 -560.4792382 0.11 0.0324 0.017829486 68.90%

4.E.2 Land converted to Settlements – Carbon stock change – living biomass

CO2 113.1222033 594.71159 1.69 0.0303 0.016677144 70.57%


CO2 1007.294341 142.1295097 0.02 0.1 0.0281 0.015436971 72.11%


CO2 798.2058686 33.22587 0.02 0.1113 0.0268 0.014758504 73.59%

1.A.3.b Road Transportation - Gasoline CO2 1723.750448 625.9575 0.02 0.5 0.0259 0.014241487 75.01%


CO2 778.5312078 57.80522878 0.02 0.5 0.0247 0.013586774 76.37%





CO2 1016.928 917.4083375 0.24 1.58 0.0164 0.00903474 80.48%

4.A.2 Land converted to Forest Land – Carbon stock change, grassland converted to forest

land

CO2 -0.174093333 -276.7873533 0.15 0.0160 0.008801503 81.36%



N2O 567.8831994 590.0496563 0.07 1.87 0.0137 0.007518317 82.11%

4.B.2 Land converted to Cropland – Carbon stock change, forest land converted to cropland

CO2 364.39865 0 0.45 0.0131 0.007220108 82.84%


3.G. Liming CO2 371.4186667 13.7756667 0.02 0.5 0.0126 0.006920979 84.23%

4.E.2 Land converted to Settlements – Carbon stock change – dead organic matter

CO2 45.01128341 238.3274994 0.21 0.0122 0.006689653 84.90%

4.E.2 Land converted to Settlements – Organic soils

CO2 3.765666667 173.7967198 0.62 0.9 0.0099 0.005454079 85.45%


1.A.2.f Non-metallic Minerals - Liquid Fuels CO2 273.5769252 21.97829728 0.02 0.1 0.0086 0.004721431 86.44%

4.C.2 Land converted to Grassland – Drained

organic soil

CO2 0.000861458 147.8708275 0.52 0.9 0.0086 0.004703939 86.91%


CO2 2644.318679 1789.305004 0.02 0.05 0.0082 0.004526135 87.36%



405


removals


removals

Activity data

uncertainty

Emission factor /


Trend assessment

Contribution to trend

Cumulative total of

contribution to trend


Fuels

CO2 314.4838285 72.88013835 0.02 0.05 0.0071 0.003912699 88.15%


CO2 -65.31052 -161.4256967 2.24 0.0070 0.003841107 88.54%


N2O 2183.630811 1240.469649 0.02 0.5 0.0069 0.003805046 88.92%



Liquid Fuels

CO2 695.0757089 317.4303672 0.02 0.1069 0.0067 0.003674206 89.65%

1.A.2.f Non-metallic Minerals - Solid Fuels CO2 16.4292 122.8854 0.02 0.2 0.0065 0.003583614 90.01%


4.C.1 Grassland remaining Grassland – Drained organic soil

CO2 874.7530284 651.3619279 0.23 0.9 0.0062 0.003388491 90.69%

4.D.1 Wetlands remaining Wetlands – Carbon stock change –organic soils

CO2 277.2 277.2 0.24 1.58 0.0060 0.003325705 91.03%

5.A.2. Unmanaged Waste Disposal Sites CH4 392.8311633 346.2876433 0.2 0.52 0.0059 0.003232381 91.35%

4.E.2 Land converted to Settlements – Mineral soils

CO2 1.399567031 100.4322263 0.21 0.0058 0.003167144 91.67%



CO2 218.053 40.1104 0.02 0.2 0.0055 0.003044488 91.97%



CH4 56.17169761 130.5862744 0.07 1.02 0.0055 0.00304114 92.27%


2.A.2. Lime Production CO2 148.8573814 0.274894634 0.02 0.5 0.0053 0.00294068 92.87%



CO2 149.4154681 5.585308222 0.02 0.05 0.0051 0.002782807 93.43%


CO2 142.826737 4.15465786 0.02 0.15 0.0049 0.00269777 93.70%


4.B.2 Land converted to Cropland – Drained organic soil

CO2 12.166 85.162 1.3 0.9 0.0045 0.002468056 94.20%


CO2 256.17754 83.34388 0.92 0.06 0.0044 0.002424567 94.44%

4.E.1 Settlements remaining Settlements – Carbon stock change – living biomass

CO2 -48.28378424 -105.6971782 2.1 0.0044 0.002405676 94.68%



CO2 274.4466477 242.7711156 0.02 0.05 0.0042 0.002285033 95.15%

4.B.1 Land converted to Cropland – Carbon stock change – dead organic matter

CO2 111.6529333 0 0.32 0.0040 0.002212265 95.37%

4.A.2 Land Converted to Forest Land –

grassland converted to forest land, carbon stock change, dead wood

CO2 -1.729127891 -68.69365758 0.09 0.0039 0.002150971 95.59%


CO2 103.071464 2.365 0.02 0.2 0.0036 0.001967 95.78%


CO2 102.28152 2.4596 0.02 0.5 0.0035 0.001948339 95.98%

4.A.2 Land Converted to Forest Land – grassland converted to forest land, carbon stock change, litter

CO2 -1.525469 -60.602861 0.09 0.0035 0.001897628 96.17%

1.A.2.a Iron and Steel - Liquid Fuels CO2 93.25228881 0 0.02 0.1 0.0034 0.001847679 96.35%



4.E.2 Lands converted to settlements, Direct nitrous oxide (N2O) emissions from nitrogen (N) mineralization/immobilization associated

N2O 0.910566118 49.34129338 0.87 0.7 0.0028 0.001551567 96.84%


406


removals


removals

Activity data

uncertainty

Emission factor /


Trend assessment


Cumulative total of


with loss/gain of soil organic matter resulting

from change of land use or management of mineral soils


CO2 73.83865681 0 0.02 0.1 0.0027 0.001463021 96.98%


CH4 83.38555 7.57375 0.25 0.3 0.0026 0.001411251 97.12%

4.B.2 Land converted to Cropland –Mineral soil

CO2 6.98223392 48.54695124 0.32 0.0026 0.001405995 97.26%

1.A.4.a Commercial/Institutional - Peat CO2 66.54499789 0 0.02 0.1 0.0024 0.001318507 97.40%


N2O 142.1423263 47.57185732 0.02 0.5 0.0024 0.001303054 97.53%

4.B. Cropland remaining cropland, Emissions and removals from drainage and rewetting and other management of organic and

mineral soils

CH4 125.0939765 117.6632261 0.13 0.71 0.0023 0.001264432 97.65%

1.A.2.a Iron and Steel - Other fossil fuels CO2 61.3521 0 0.02 0.2 0.0022 0.001215616 97.77%

4.A.2 Land converted to Forest Land – grassland converted to forest land, Drained organic soil

CO2 3.355733333 37.895 0.72 1.11 0.0021 0.001138998 97.89%

2.A.4. Other process uses of carbonates CO2 69.184752 9.050385865 0.02 0.5 0.0020 0.001082906 98.00%

4.C.1 Grassland remaining Grassland – Carbon stock change – living biomass

CO2 -19.17968712 -41.72134122 0.61 0.0017 0.000947186 98.09%


1.B.2.b Natural Gas CH4 177.238 82.3568 0.3115 0.01 0.0016 0.000891878 98.27%

1.A.4.b Residential - Peat CO2 42.27150449 0 0.02 0.1 0.0015 0.000837557 98.35%


4.C.2. Lands converted to grasslands, Direct nitrous oxide (N2O) emissions from nitrogen (N) mineralization/immobilization associated with loss/gain of soil organic matter resulting

from change of land use or management of mineral soils

N2O 0.000147896 25.3866853 0.68 0.37 0.0015 0.000807579 98.52%


1.A.3.d Domestic Naviagtion - Diesel Oil CO2 0.8332289 25.16 0.02 0.05 0.0014 0.000783862 98.67%


CO2 44.69904433 50.37622658 0.02 0.05 0.0013 0.000716875 98.75%

4.D.1 Wetlands remaining Wetlands – Carbon stock change – dead organic matter

CO2 -13.80987667 -29.95736333 0.06 0.0012 0.000679356 98.81%

4.B.2 Land converted to cropland, Direct nitrous oxide (N2O) emissions from nitrogen (N) mineralization/immobilization associated with loss/gain of soil organic matter resulting from change of land use or management of mineral soils

N2O 3.15132616 22.5734702 1.31 0.73 0.0012 0.000655651 98.88%

4.C. Grassland, Emissions and removals from drainage and rewetting and other management of organic and mineral soils

CH4 66.19807613 60.48292143 0.06 0.6 0.0011 0.000612405 98.94%



CH4 39.135 39.52177273 0.05 0.5 0.0009 0.000481826 99.05%





1.A.3.b Road Transportation - Gaseous Fuels CO2 17.6165255 0 0.02 0.5 0.0006 0.00034905 99.25%

4.D.1. Wetlands, Peat extraction from lands,

organic soils

CH4 28.53444375 28.53444375 0.24 0.8 0.0006 0.000342342 99.29%


407


removals


removals

Activity data

uncertainty

Emission factor /


Trend assessment


Cumulative total of



Production - Biomass Fuels

N2O 0.519712 11.01384 0.05 0.5 0.0006 0.000340067 99.32%


CO2 174.2220665 98.04113849 0.02 0.05 0.0006 0.000333183 99.35%

1.A.2.d. Pulp, Paper and Print - Liquid Fuels CO2 15.54739345 0 0.02 0.1 0.0006 0.000308052 99.39%

1.A.3.b Road Transportation - Diesel Oil N2O 5.593827044 13.09045627 0.02 0.5 0.0006 0.000305589 99.42%



1.A.3.b Road Transportation - Gasoline CH4 17.15516309 2.455797158 0.02 0.5 0.0005 0.000261786 99.50%


CH4 25.2045 8.2 0.92 0.36 0.0004 0.000238544 99.52%

2.C.1 Iron and Steel Production CO2 12.81611267 0.955378707 0.05 0.25 0.0004 0.000223544 99.54%

4.E.1 Settlements remaining Settlements – Carbon stock change – dead organic matter

CO2 -6.108421479 -10.78459125 0.08 0.0004 0.000222041 99.57%


CH4 0.327 6.940298662 0.05 0.5 0.0004 0.0002143 99.59%


4.C.1 Grassland remaining Grassland – Carbon stock change – dead organic matter

CO2 -4.28449168 -8.708601291 0.05 0.0003 0.00019214 99.63%

3.B.2.3 Manure Management - Swaine N2O 15.35892 3.60282 0.25 0.3 0.0003 0.000189708 99.65%



CH4 8.109 0.195 0.02 0.5 0.0003 0.000154467 99.68%


N2O 7.1626684 0.0371308 0.02 0.5 0.0003 0.000140738 99.69%

4.B.1 Cropland remaining Cropland – Carbon stock change – living biomass

CO2 -6.134341743 -8.205353949 3.5 0.0003 0.000139478 99.71%



N2O 22.04902 9.58666 0.25 0.3 0.0002 0.00013191 99.73%


N2O 6.66618252 0.231993 0.02 0.5 0.0002 0.000124702 99.75%

3.A.4 Enteric Fermentation - Other livestock CH4 18.092 7.542775 0.02 0.4 0.0002 0.000118525 99.76%

1.A.3.b Road Transportation - Gasoline N2O 13.07410741 4.586290942 0.02 0.5 0.0002 0.000113152 99.77%



CO2 24.7792529 18.87025524 0.02 0.1 0.0002 0.000109316 99.79%

1.A.3.a Domestic Aviation - Jet kerosene CO2 0.054819072 3.107107044 0.02 0.5 0.0002 9.77548E-05 99.80%

1.A.3.d Domestic Naviagtion - Diesel Oil N2O 0.1006644 3.0396 0.02 0.5 0.0002 9.46989E-05 99.81%

4 (IV) Indirect nitrous oxide (N2O) emissions from managed soils

N2O 0.16057137 2.97600236 0.0002 9.14888E-05 99.82%

2.A.3. Glass production CO2 0.352 2.976908 0.02 0.6 0.0002 8.77247E-05 99.83%


CH4 5.99375 1.250225 0.02 0.5 0.0001 7.89875E-05 99.84%

1.A.4.a Commercial/Institutional - Biomass

Fuels

N2O 6.219856 6.292871419 0.05 0.5 0.0001 7.69454E-05 99.84%

1.A.3.b Road Transportation - LPG N2O 0.163685304 2.463208388 0.02 0.5 0.0001 7.51145E-05 99.85%


Fuels

CH4 3.72829 0.12975 0.02 0.5 0.0001 6.97439E-05 99.86%


408


removals


removals

Activity data

uncertainty

Emission factor /


Trend assessment


Cumulative total of


1.A.3.b Road Transportation - Lubricants CO2 3.4629 4.33188 0.1 0.5 0.0001 6.91895E-05 99.87%


CH4 9.15 3.627804811 0.05 0.5 0.0001 6.58909E-05 99.87%

1.A.4.b Residential - Peat CH4 3.1875 0 0.02 0.5 0.0001 6.31564E-05 99.88%


CO2 3.0786 0 0.02 0.2 0.0001 6.09986E-05 99.88%

1.A.4.c Agriculture/Forestry/Fisheries - Peat CO2 3.0225 0 0.02 0.5 0.0001 5.98871E-05 99.89%


CH4 3.00505 0.015625 0.02 0.5 0.0001 5.90443E-05 99.90%

1.A.2.d. Pulp, Paper and Print - Solid Fuels CO2 2.692316 0 0.02 0.2 0.0001 5.33449E-05 99.90%


4.A.1 Forest land remaining forest land - wildfires

CH4 2.466906545 3.018876526 0.37 0.36 0.0001 4.71555E-05 99.91%


N2O 3.793114286 3.793114286 0.24 1.12 0.0001 4.55079E-05 99.92%


CH4 3.495 0.74775 0.02 0.5 0.0001 4.54622E-05 99.92%


5.C.1 Waste Incineration N2O 4.847024532 4.313387888 0.2 1 0.0001 4.11765E-05 99.93%



N2O 2.411706848 0.358718096 0.02 0.5 0.0001 3.63737E-05 99.94%


N2O 1.87891384 0.057812 0.02 0.5 0.0001 3.53893E-05 99.94%


N2O 0.008344 1.056180881 0.05 0.5 0.0001 3.34331E-05 99.94%



Gaseous Fuels

CH4 1.774375 0.13325 0.02 0.5 0.0001 3.09182E-05 99.95%


N2O 2.908143856 0.911925296 0.02 0.5 0.0001 2.86118E-05 99.95%


N2O 2.95616 0.96254 0.92 0.0001 2.7953E-05 99.95%

1.A.4.b Residential - Liquid Fuels CH4 0.868375 1.270375 0.02 0.5 0.0000 2.32064E-05 99.96%

3.H. Urea Application CO2 7.7088 4.075866667 0.2 0.05 0.0000 2.30819E-05 99.96%



CH4 0.00525 0.66454334 0.05 0.5 0.0000 2.10359E-05 99.96%

1.A.2.a Iron and Steel - Other fossil fuels N2O 0.997704 0 0.02 0.5 0.0000 1.97683E-05 99.97%

1.A.2.f Non-metallic Minerals - Solid Fuels N2O 0.07599 0.580653 0.02 0.5 0.0000 1.69657E-05 99.97%

4.B.1 Cropland remaining Cropland – Carbon stock change – dead organic matter

CO2 -1.368079328 -1.339381629 0.03 0.0000 1.55006E-05 99.97%


Tobacco - Liquid Fuels

CH4 0.78871 0.026525 0.02 0.5 0.0000 1.47835E-05 99.97%


N2O 1.030335 0.189528 0.02 0.5 0.0000 1.43857E-05 99.97%

1.A.3.b Road Transportation - Gaseous Fuels CH4 0.7015 0 0.02 0.5 0.0000 1.38994E-05 99.97%

1.A.3.b Road Transportation - Diesel Oil CH4 1.108041461 1.116917573 0.02 0.5 0.0000 1.35761E-05 99.97%



409


removals


removals

Activity data

uncertainty

Emission factor /


Trend assessment


Cumulative total of


1.A.2.a Iron and Steel - Other fossil fuels CH4 0.62775 0 0.02 0.5 0.0000 1.24381E-05 99.98%


N2O 0.271776 0.5352974 0.05 0.5 0.0000 1.16436E-05 99.98%


N2O 0.615519 0.01788 0.02 0.5 0.0000 1.1627E-05 99.98%

1.A.2.f Non-metallic Minerals - Liquid Fuels N2O 0.64092648 0.0531036 0.02 0.5 0.0000 1.10099E-05 99.98%


Biomass Fuels

N2O 1.45424 0.588801467 0.05 0.5 0.0000 1.00835E-05 99.98%


N2O 0.4832964 0.011622 0.02 0.5 0.0000 9.20621E-06 99.98%


N2O 0.47777148 0.011175 0.02 0.5 0.0000 9.11096E-06 99.98%

1.A.3.a Domestic Aviation - Aviation Gasoline CO2 0.011005031 0.28 0.02 0.5 0.0000 8.6891E-06 99.98%


N2O 0.423011 0.0317668 0.02 0.5 0.0000 7.3709E-06 99.99%


CH4 0.171 0.336825 0.05 0.5 0.0000 7.32667E-06 99.99%


3.B.2.2 Manure Management - Sheep N2O 1.32908 1.03108 0.25 0.3 0.0000 6.46587E-06 99.99%


N2O 0.3177723 0 0.02 0.5 0.0000 6.29626E-06 99.99%

1.A.4.a Commercial/Institutional - Peat N2O 0.2955862 0 0.02 0.5 0.0000 5.85667E-06 99.99%

4.A.1 Forest land remaining forest land - wildfires

N2O 0.289234682 0.3539509 0.37 0.0000 5.52879E-06 99.99%


CH4 0.6255 0.559625 0.02 0.5 0.0000 5.40886E-06 99.99%

1.A.3.b Road Transportation - Gaseous Fuels N2O 0.27267 0 0.02 0.5 0.0000 5.40262E-06 99.99%

1.A.3.d Domestic Naviagtion - Gasoline CO2 0.172771761 0.2772 0.2 0.05 0.0000 5.39482E-06 99.99%



N2O 0.05399279 0.183306897 0.1 0.48 0.0000 4.76142E-06 99.99%


1.A.2.f Non-metallic Minerals - Liquid Fuels CH4 0.268845 0.022275 0.02 0.5 0.0000 4.61823E-06 99.99%

1.A.4.c Agriculture/Forestry/Fisheries - Peat CH4 0.2325 0 0.02 0.5 0.0000 4.6067E-06 99.99%


CH4 0.049609866 0.168426759 0.1 0.39 0.0000 4.37491E-06 99.99%

1.A.2.a Iron and Steel - Liquid Fuels N2O 0.2179572 0 0.02 0.5 0.0000 4.31855E-06 99.99%


1.A.4.b Residential - Peat N2O 0.1860712 0 0.02 0.5 0.0000 3.68677E-06 99.99%

1.A.4.a Commercial/Institutional - Peat CH4 0.168 0 0.02 0.5 0.0000 3.32871E-06 100.00%



N2O 1.4367772 0.9833106 0.02 0.5 0.0000 2.81238E-06 100.00%

3.B.1.2 Manure Management - Sheep CH4 0.78185 0.4028 0.25 0.3 0.0000 2.67782E-06 100.00%




CH4 1.20535 0.824925 0.02 0.5 0.0000 2.35938E-06 100.00%


410


removals


removals

Activity data

uncertainty

Emission factor /


Trend assessment


Cumulative total of



Fuels

N2O 0.1708732 0.0400512 0.02 0.5 0.0000 2.11156E-06 100.00%

1.A.2.a Iron and Steel - Gaseous Fuels N2O 0.127395 0.0164198 0.02 0.5 0.0000 2.00184E-06 100.00%


1.A.2.a Iron and Steel - Liquid Fuels CH4 0.091425 0 0.02 0.5 0.0000 1.81147E-06 100.00%


Fuels

CH4 0.14335 0.0336 0.02 0.5 0.0000 1.77144E-06 100.00%



1.A.2.a Iron and Steel - Gaseous Fuels CH4 0.106875 0.013775 0.02 0.5 0.0000 1.6794E-06 100.00%




N2O 0.08118414 0.0030694 0.02 0.5 0.0000 1.51092E-06 100.00%



N2O 0.1491192 0.1334146 0.02 0.5 0.0000 1.28947E-06 100.00%


CH4 0.0681075 0.002575 0.02 0.5 0.0000 1.26755E-06 100.00%

1.A.3.d Domestic Naviagtion - Diesel Oil CH4 0.001126 0.034 0.02 0.5 0.0000 1.05927E-06 100.00%


N2O 0.050064 0 0.02 0.5 0.0000 9.91956E-07 100.00%

1.A.2.f Non-metallic Minerals - Solid Fuels CH4 0.00425 0.032475 0.02 0.5 0.0000 9.48862E-07 100.00%

1.A.3.a Domestic Aviation - Jet kerosene N2O 0.000453151 0.028884544 0.02 0.5 0.0000 9.09875E-07 100.00%



CH4 0.057625 0.0106 0.02 0.5 0.0000 8.04569E-07 100.00%


1.A.2.d. Pulp, Paper and Print - Liquid Fuels N2O 0.0362964 0 0.02 0.5 0.0000 7.19168E-07 100.00%


CH4 0.034425 0.001 0.02 0.5 0.0000 6.50277E-07 100.00%


CH4 0.0315 0 0.02 0.5 0.0000 6.24133E-07 100.00%


1.A.3.b Road Transportation - Lubricants N2O 0.02384 0.03278 0.1 0.5 0.0000 5.70413E-07 100.00%


Tobacco - Solid Fuels

CH4 0.026721 0.000625 0.02 0.5 0.0000 5.09561E-07 100.00%


N2O 0.024287 0.0276842 0.02 0.5 0.0000 3.99452E-07 100.00%


N2O 0.05379496 0.045594 0.02 0.5 0.0000 3.84522E-07 100.00%

1.A.1.c Manufacture of Solid Fuels and Other

Energy Industries - Peat

CH4 0.0177725 0 0.02 0.5 0.0000 3.5214E-07 100.00%


CH4 0.020375 0.023225 0.02 0.5 0.0000 3.35111E-07 100.00%

1.A.2.d. Pulp, Paper and Print - Liquid Fuels CH4 0.015225 0 0.02 0.5 0.0000 3.01665E-07 100.00%

1.A.4.c Agriculture/Forestry/Fisheries - Peat N2O 0.013857 0 0.02 0.5 0.0000 2.74559E-07 100.00%

1.A.2.d. Pulp, Paper and Print - Solid Fuels N2O 0.01272162 0 0.02 0.5 0.0000 2.52063E-07 100.00%


411


removals


removals

Activity data

uncertainty

Emission factor /


Trend assessment


Cumulative total of



Tobacco - Gaseous Fuels

N2O 0.09466268 0.0538784 0.02 0.5 0.0000 1.61684E-07 100.00%


CH4 0.02314 0.019125 0.02 0.5 0.0000 1.499E-07 100.00%


CH4 0.079415 0.0452 0.02 0.5 0.0000 1.35641E-07 100.00%

1.A.3.a Domestic Aviation - Jet kerosene CH4 0.000009504 0.00355575 0.02 0.5 0.0000 1.12925E-07 100.00%




1.A.3.d Domestic Naviagtion - Gasoline CH4 0.00295205 0.004739595 0.2 0.5 0.0000 9.22812E-08 100.00%


1.A.3.a Domestic Aviation - Aviation Gasoline N2O 9.36998E-05 0.002384 0.02 0.5 0.0000 7.39815E-08 100.00%


1.A.3.b Road Transportation - Lubricants CH4 0.02475 0.01425 0.1 0.5 0.0000 3.70802E-08 100.00%


1.A.2.d. Pulp, Paper and Print - Solid Fuels CH4 0.0007115 0 0.02 0.5 0.0000 1.40975E-08 100.00%


1.A.3.d Domestic Naviagtion - Gasoline N2O 0.000219506 0.000352182 0.2 0.5 0.0000 6.85411E-09 100.00%

1.A.3.a Domestic Aviation - Aviation Gasoline CH4 1.96519E-06 0.00005 0.02 0.5 0.0000 1.55162E-09 100.00%


CO2 0 0 0.02 0.2 0 100.00%

1.A.1.c Manufacture of Solid Fuels and Other

Energy Industries - Biomass Fuels

CO2 0 0.05 0.1 0 100.00%


CH4 0 0 0.02 0.5 0 100.00%


CH4 0 0.222 0.05 0.5 0 100.00%


N2O 0 0 0.02 0.5 0 100.00%


N2O 0 0.352832 0.05 0.5 0 100.00%

1.A.2.a Iron and Steel - Biomass Fuels CO2 0 0 0.05 0.1 0 100.00%

1.A.2.a Iron and Steel - Peat CO2 0 0 0.02 0.1 0 100.00%

1.A.2.a Iron and Steel - Biomass Fuels CH4 0 0 0.05 0.5 0 100.00%

1.A.2.a Iron and Steel - Peat CH4 0 0 0.02 0.5 0 100.00%

1.A.2.a Iron and Steel - Biomass Fuels N2O 0 0 0.05 0.5 0 100.00%

1.A.2.a Iron and Steel - Peat N2O 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Liquid Fuels CO2 0 0 0.02 0.1 0 100.00%

1.A.2.b Non-Ferrous Metals - Solid Fuels CO2 0 0 0.02 0.2 0 100.00%

1.A.2.b Non-Ferrous Metals - Gaseous Fuels CO2 0 7.483228491 0.02 0.05 0 100.00%

1.A.2.b Non-Ferrous Metals - Biomass Fuels CO2 0 0 0.05 0.1 0 100.00%


412


removals


removals

Activity data

uncertainty

Emission factor /


Trend assessment


Cumulative total of


1.A.2.b Non-Ferrous Metals - Peat CO2 0 0 0.02 0.1 0 100.00%

1.A.2.b Non-Ferrous Metals - Liquid Fuels CH4 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Solid Fuels CH4 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Gaseous Fuels CH4 0 0.00345 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Biomass Fuels CH4 0 0 0.05 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Peat CH4 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Liquid Fuels N2O 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Solid Fuels N2O 0 0 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Gaseous Fuels N2O 0 0.0041124 0.02 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Biomass Fuels N2O 0 0 0.05 0.5 0 100.00%

1.A.2.b Non-Ferrous Metals - Peat N2O 0 0 0.02 0.5 0 100.00%

1.A.2.c Chemicals - Peat CO2 0 2.07732893 0.02 0.1 0 100.00%

1.A.2.c Chemicals - Biomass Fuels CH4 0 0.157344085 0.05 0.5 0 100.00%

1.A.2.c Chemicals - Peat CH4 0 0.001 0.02 0.5 0 100.00%

1.A.2.c Chemicals - Biomass Fuels N2O 0 0.24953815 0.05 0.5 0 100.00%

1.A.2.c Chemicals - Peat N2O 0 0.00894 0.02 0.5 0 100.00%

1.A.2.d. Pulp, Paper and Print - Peat CO2 0 0 0.02 0.1 0 100.00%


CH4 0 0.07275 0.05 0.5 0 100.00%

1.A.2.d. Pulp, Paper and Print - Peat CH4 0 0 0.02 0.5 0 100.00%


N2O 0 0.115624 0.05 0.5 0 100.00%

1.A.2.d. Pulp, Paper and Print - Peat N2O 0 0 0.02 0.5 0 100.00%


CO2 0 0 0.02 0.1 0 100.00%


CO2 0 2.1257 0.02 0.2 0 100.00%


CH4 0 0 0.02 0.5 0 100.00%


CH4 0 0.02175 0.02 0.5 0 100.00%


Tobacco - Peat

N2O 0 0 0.02 0.5 0 100.00%


N2O 0 0.034568 0.02 0.5 0 100.00%

1.A.2.f Non-metallic Minerals - Peat CO2 0 0 0.02 0.1 0 100.00%


Fuels

CO2 0 92.50516 0.02 0.02 0 100.00%

1.A.2.f Non-metallic Minerals - Peat CH4 0 0 0.02 0.5 0 100.00%


Fuels

CH4 0 0.814736505 0.02 0.5 0 100.00%

1.A.2.f Non-metallic Minerals - Peat N2O 0 0 0.02 0.5 0 100.00%


Fuels

N2O 0 1.294887885 0.02 0.5 0 100.00%


413


removals


removals

Activity data

uncertainty

Emission factor /


Trend assessment


Cumulative total of


1.A.2.g Other - Peat CO2 0 0.39 0.02 0.1 0 100.00%

1.A.2.g Other - Other Fossil Fuels CO2 0 0 0.02 0.2 0 100.00%

1.A.2.g Other - Peat CH4 0 0.0001 0.02 0.5 0 100.00%

1.A.2.g Other - Other Fossil Fuels CH4 0 0 0.02 0.5 0 100.00%

1.A.2.g Other - Peat N2O 0 0.001788 0.02 0.5 0 100.00%

1.A.2.g Other - Other Fossil Fuels N2O 0 0 0.02 0.5 0 100.00%

1.A.3.b Road Transportation - Biomass CH4 0 0.020267227 0.02 0.5 0 100.00%

1.A.3.b Road Transportation - Biomass N2O 0 0.307472263 0.02 0.5 0 100.00%

1.A.3.c. Railway Biomass Fuels CH4 0 0.00132 0.02 0.5 0 100.00%

1.A.3.c. Railway Biomass Fuels N2O 0 0.0200256 0.02 0.5 0 100.00%


CO2 0 0 0.02 0.2 0 100.00%

1.A.4.a Commercial/Institutional - Other

Fossil Fuels

CH4 0 0 0.02 0.5 0 100.00%


N2O 0 0 0.02 0.5 0 100.00%

1.A.4.b Residential - Other Fossil Fuels CO2 0 0 0.02 0.2 0 100.00%

1.A.4.b Residential - Other Fossil Fuels CH4 0 0 0.02 0.5 0 100.00%

1.A.4.b Residential - Other Fossil Fuels N2O 0 0 0.02 0.5 0 100.00%


CO2 0 0 0.02 0.5 0 100.00%


CH4 0 0 0.02 0.5 0 100.00%


Other Fossil Fuels

N2O 0 0 0.02 0.5 0 100.00%

1.A.5.b Mobile - Liquid Fuels CO2 0 6.447874167 0.02 0.5 0 100.00%

1.A.5.b Mobile - Liquid Fuels CH4 0 0.011410463 0.02 0.5 0 100.00%

1.A.5.b Mobile - Liquid Fuels N2O 0 0.052371989 0.02 0.5 0 100.00%

2.D.2 Paraffin wax use CO2 0 0.132 0.02 0.5 0 100.00%

2.D.3. Solvent Use CO2 0 0 0.02 0.2 0 100.00%

2.D.3.d Urea Use CO2 0 0.537788082 0.2 0.1 0 100.00%

2.F.1. Refrigeration and air conditioning HFCs 0 102.8615524 0.75 0.75 0 100.00%

2.F.2 Foam blowing agents HFCs 0 0 0.75 0.75 0 100.00%

2.F.3. Fire Protection HFCs 0 0.2369598 0.75 0.75 0 100.00%

2.F.4. Aerosols HFCs 0 3.52216298 0.75 0.75 0 100.00%

2.G.1. Electrical equipment SF6 0 8.50315813 0.02 0.3 0 100.00%

2.G.4. Other HFCs 0 1.835685463 0.75 0.75 0 100.00%


CO2 0 18.39 0.72 0.25 0 100.00%

4.E.1 Settlements remaining Settlements –

Drained organic soils

CO2 0 15.32483431 0.08 0.9 0 100.00%


414


removals


removals

Activity data

uncertainty

Emission factor /


Trend assessment


Cumulative total of


4.E.2 Settlements remaining Settlements,

Direct nitrous oxide (N2O) emissi ons from nitrogen (N) mineralization/immobilization associated with loss/gain of soil organic

matter resulting from change of land use or management of mineral soils

N2O 3.2207095 0 100.00%

5.A.1. Managed Waste Disposal on Land CH4 0 186.6154068 0.2 0.52 0 100.00%

5.B.1. Composting CH4 0 1.4367 0.2 1 0 100.00%

5.B.1. Composting N2O 0 1.2844098 0.2 0.9 0 100.00%

Total 17284.8703 10765.94797 40.448 132.3882 1.8187 1.0000 316.5135

A.1.4 Spreadsheet for the Approach 1 analysis for year 2013 – trend assessment without LULUCF

IPCC category/Group Gas Base year emissions or removals

Year 2013 emissions or removals


Emission factor / estimation parameter

uncertainty

Trend Uncertainty


Cumulative total of contribution to trend


CO2 616.136 1741.886 0.02 0.5 0.05948263 0.226473 22.65%


CO2 3049.621 15.8603 0.02 0.1 0.0421656 0.160541 38.70%



CO2 2644.319 1789.305 0.02 0.05 0.032882 0.125194 51.22%


CO2 1410.785 49.0974 0.02 0.2 0.01787294 0.068049 58.03%



managed soils

N2O 2183.631 1240.47 0.02 0.5 0.0178799 0.068076 70.86%


CO2 798.2059 33.22587 0.02 0.1113 0.00989926 0.03769 74.63%


CO2 1007.294 142.1295 0.02 0.1 0.00857342 0.032642 77.89%


CO2 778.5312 57.80523 0.02 0.5 0.0086619 0.032979 81.19%



5.A.2. Unmanaged Waste Disposal Sites

CH4 392.8312 346.2876 0.2 0.52 0.00803228 0.030582 89.17%


3.G. Liming CO2 371.4187 13.77567 0.02 0.5 0.00467219 0.017789 91.19%




Gaseous Fuels

CO2 274.4466 242.7711 0.02 0.05 0.00564457 0.021491 97.61%



CO2 16.4292 122.8854 0.02 0.2 0.00457567 0.017421 101.25%




CO2 1723.75 625.9575 0.02 0.5 0.00029778 0.001134 103.96%


CO2 273.5769 21.9783 0.02 0.1 0.00297867 0.011341 105.09%


415


removals


removals




Trend Uncertainty


Cumulative total of contribution

to trend



2.A.2. Lime Production CO2 148.8574 0.274895 0.02 0.5 0.0020777 0.007911 108.01%

1.A.2.f Non-metallic Minerals -

Gaseous Fuels

CO2 314.4838 72.88014 0.02 0.05 0.00156176 0.005946 108.60%


CO2 149.4155 5.585308 0.02 0.05 0.00187784 0.00715 109.32%


CO2 142.8267 4.154658 0.02 0.15 0.00184135 0.007011 110.02%


CO2 218.053 40.1104 0.02 0.2 0.00149051 0.005675 110.59%


CO2 103.0715 2.365 0.02 0.2 0.00135359 0.005154 111.10%


CO2 102.2815 2.4596 0.02 0.5 0.0013388 0.005097 111.61%

1.A.2.a Iron and Steel - Liquid Fuels CO2 93.25229 0 0.02 0.1 0.00130832 0.004981 112.11%


1.A.1.c Manufacture of Solid Fuels and Other Energy Industries - Gaseous

Fuels

CO2 44.69904 50.37623 0.02 0.05 0.00134314 0.005114 112.95%


CO2 73.83866 0 0.02 0.1 0.00103595 0.003944 113.34%




CO2 66.545 0 0.02 0.1 0.00093362 0.003555 114.44%


CO2 695.0757 317.4304 0.02 0.1069 0.00266318 0.01014 115.46%

3.B.1.4 Manure Management - Other

livestock

CH4 83.38555 7.57375 0.25 0.3 0.00087367 0.003326 115.79%


CO2 61.3521 0 0.02 0.2 0.00086076 0.003277 116.12%


CO2 174.2221 98.04114 0.02 0.05 0.00139017 0.005293 116.65%


CO2 0.833229 25.16 0.02 0.05 0.00097234 0.003702 117.02%


CH4 39.135 39.52177 0.05 0.5 0.00099668 0.003795 117.39%


CO2 69.18475 9.050386 0.02 0.5 0.00061669 0.002348 117.63%


1.A.4.b Residential - Peat CO2 42.2715 0 0.02 0.1 0.00059307 0.002258 118.16%





N2O 142.1423 47.57186 0.02 0.5 0.00013366 0.000509 119.16%



N2O 0.519712 11.01384 0.05 0.5 0.00042347 0.001612 119.51%

1.A.3.b Road Transportation - Diesel

Oil

N2O 5.593827 13.09046 0.02 0.5 0.0004335 0.001651 119.68%



416


removals


removals




Trend Uncertainty



to trend



CO2 24.77925 18.87026 0.02 0.1 0.00039038 0.001486 120.06%

1.B.2.b Natural Gas CH4 177.238 82.3568 0.3115 0.01 0.00073443 0.002796 120.34%



CO2 17.61653 0 0.02 0.5 0.00024716 0.000941 120.51%


CH4 0.327 6.940299 0.05 0.5 0.00026685 0.001016 120.61%



Liquid Fuels

CO2 15.54739 0 0.02 0.1 0.00021813 0.00083 120.77%




Gasoline

CH4 17.15516 2.455797 0.02 0.5 0.00014464 0.000551 121.00%

2.C.1 Iron and Steel Production CO2 12.81611 0.955379 0.05 0.25 0.00014244 0.000542 121.06%


N2O 6.219856 6.292871 0.05 0.5 0.00015886 0.000605 121.12%



CH4 8.109 0.195 0.02 0.5 0.00010614 0.000404 121.24%


CO2 0.054819 3.107107 0.02 0.5 0.00012075 0.00046 121.28%


N2O 0.100664 3.0396 0.02 0.5 0.00011747 0.000447 121.33%



N2O 7.162668 0.037131 0.02 0.5 9.9039E-05 0.000377 121.37%


CO2 3.4629 4.33188 0.1 0.5 0.00012084 0.00046 121.41%

2.A.3. Glass production CO2 0.352 2.976908 0.02 0.6 0.00011149 0.000424 121.45%

3.B.2.3 Manure Management - Swaine N2O 15.35892 3.60282 0.25 0.3 7.4574E-05 0.000284 121.48%


N2O 6.666183 0.231993 0.02 0.5 8.4452E-05 0.000322 121.51%


1.A.3.b Road Transportation - LPG N2O 0.163685 2.463208 0.02 0.5 9.4042E-05 0.000358 121.62%

5.C.1 Waste Incineration N2O 4.847025 4.313388 0.2 1 0.0001007 0.000383 121.66%



CH4 3.72829 0.12975 0.02 0.5 4.7233E-05 0.00018 122.16%

1.A.4.b Residential - Peat CH4 3.1875 0 0.02 0.5 4.472E-05 0.00017 122.18%


CO2 3.0786 0 0.02 0.2 4.3192E-05 0.000164 122.20%


CO2 3.0225 0 0.02 0.5 4.2405E-05 0.000161 122.21%


CH4 5.99375 1.250225 0.02 0.5 3.5194E-05 0.000134 122.23%



CH4 3.00505 0.015625 0.02 0.5 4.1549E-05 0.000158 122.24%


CO2 2.692316 0 0.02 0.2 3.7773E-05 0.000144 122.26%


417


removals


removals




Trend Uncertainty



to trend


N2O 0.008344 1.056181 0.05 0.5 4.1191E-05 0.000157 122.27%

1.A.4.b Residential - Solid Fuels N2O 2.862588 0.23691 0.02 0.5 3.0896E-05 0.000118 122.28%

1.A.4.b Residential - Liquid Fuels CH4 0.868375 1.270375 0.02 0.5 3.7502E-05 0.000143 122.30%


Gasoline

N2O 13.07411 4.586291 0.02 0.5 4.054E-06 1.54E-05 122.30%

3.H. Urea Application CO2 7.7088 4.075867 0.2 0.05 5.1258E-05 0.000195 122.32%

5.D.2 Industrial Wastewater N2O 2.341429 0.141335 0.1 0.3 2.7322E-05 0.000104 122.33%

1.A.2.g Other - Liquid Fuels CH4 2.26531 0.194025 0.02 0.5 2.4194E-05 9.21E-05 122.34%

1.A.3.b Road Transportation - LPG CH4 0.124565 0.801443 0.02 0.5 2.9598E-05 0.000113 122.35%


N2O 1.878914 0.057812 0.02 0.5 2.41E-05 9.18E-05 122.36%


CH4 3.495 0.74775 0.02 0.5 1.9789E-05 7.53E-05 122.37%


Biomass Fuels

CH4 0.00525 0.664543 0.05 0.5 2.5917E-05 9.87E-05 122.38%


CH4 1.108041 1.116918 0.02 0.5 2.8138E-05 0.000107 122.39%


N2O 2.411707 0.358718 0.02 0.5 1.9806E-05 7.54E-05 122.40%



CH4 1.774375 0.13325 0.02 0.5 1.9683E-05 7.49E-05 122.47%

1.A.2.g Other - Liquid Fuels N2O 2.149772 0.297218 0.02 0.5 1.8537E-05 7.06E-05 122.47%


N2O 0.07599 0.580653 0.02 0.5 2.1644E-05 8.24E-05 122.48%

3.B.2.2 Manure Management - Sheep N2O 1.32908 1.03108 0.25 0.3 2.168E-05 8.25E-05 122.49%


N2O 0.271776 0.535297 0.05 0.5 1.7123E-05 6.52E-05 122.50%


N2O 0.997704 0 0.02 0.5 1.3998E-05 5.33E-05 122.50%


N2O 22.04902 9.58666 0.25 0.3 6.5598E-05 0.00025 122.53%


N2O 1.436777 0.983311 0.02 0.5 1.83E-05 6.97E-05 122.53%

1.A.4.b Residential - Gaseous Fuels CH4 0.5005 0.53325 0.02 0.5 1.3834E-05 5.27E-05 122.54%


CH4 1.20535 0.824925 0.02 0.5 1.5353E-05 5.85E-05 122.54%


and Tobacco - Liquid Fuels

CH4 0.78871 0.026525 0.02 0.5 1.0028E-05 3.82E-05 122.55%


N2O 2.908144 0.911925 0.02 0.5 5.1347E-06 1.95E-05 122.55%


CH4 0.6255 0.559625 0.02 0.5 1.3112E-05 4.99E-05 122.55%


CH4 0.7015 0 0.02 0.5 9.842E-06 3.75E-05 122.56%


CO2 0.011005 0.28 0.02 0.5 1.0797E-05 4.11E-05 122.56%

1.A.2.c Chemicals - Liquid Fuels N2O 0.651297 0.004083 0.02 0.5 8.978E-06 3.42E-05 122.57%


CH4 0.171 0.336825 0.05 0.5 1.0774E-05 4.1E-05 122.57%

1.A.2.a Iron and Steel - Other fossil

fuels

CH4 0.62775 0 0.02 0.5 8.8073E-06 3.35E-05 122.57%


N2O 1.030335 0.189528 0.02 0.5 7.0429E-06 2.68E-05 122.58%


N2O 0.615519 0.01788 0.02 0.5 7.9364E-06 3.02E-05 122.58%


418


removals


removals




Trend Uncertainty



to trend


N2O 0.640926 0.053104 0.02 0.5 6.9152E-06 2.63E-05 122.58%


CO2 0.172772 0.2772 0.2 0.05 8.4176E-06 3.2E-05 122.58%


N2O 0.483296 0.011622 0.02 0.5 6.3261E-06 2.41E-05 122.59%


and Tobacco - Solid Fuels

N2O 0.477771 0.011175 0.02 0.5 6.266E-06 2.39E-05 122.59%


CH4 9.15 3.627805 0.05 0.5 1.3513E-05 5.15E-05 122.59%

1.A.4.b Residential - Liquid Fuels N2O 0.450069 0.343223 0.02 0.5 7.1094E-06 2.71E-05 122.60%


N2O 0.423011 0.031767 0.02 0.5 4.6924E-06 1.79E-05 122.60%


N2O 0.317772 0 0.02 0.5 4.4583E-06 1.7E-05 122.60%


N2O 0.295586 0 0.02 0.5 4.147E-06 1.58E-05 122.60%


N2O 0.27267 0 0.02 0.5 3.8255E-06 1.46E-05 122.60%

1.A.2.c Chemicals - Liquid Fuels CH4 0.273195 0.003425 0.02 0.5 3.6989E-06 1.41E-05 122.61%


CH4 0.2325 0 0.02 0.5 3.262E-06 1.24E-05 122.61%

1.A.2.a Iron and Steel - Liquid Fuels N2O 0.217957 0 0.02 0.5 3.0579E-06 1.16E-05 122.61%


CH4 0.268845 0.022275 0.02 0.5 2.9007E-06 1.1E-05 122.61%

5.C.1 Waste Incineration CO2 0.810708 0.427434 0.2 0.4 5.3432E-06 2.03E-05 122.61%

1.A.4.b Residential - Peat N2O 0.186071 0 0.02 0.5 2.6106E-06 9.94E-06 122.61%

1.A.4.b Residential - Gaseous Fuels N2O 0.119319 0.127127 0.02 0.5 3.298E-06 1.26E-05 122.61%

3.B.1.2 Manure Management - Sheep CH4 0.78185 0.4028 0.25 0.3 4.7846E-06 1.82E-05 122.61%


N2O 0.149119 0.133415 0.02 0.5 3.1259E-06 1.19E-05 122.62%


CH4 0.168 0 0.02 0.5 2.357E-06 8.97E-06 122.62%

2.D.1 Lubricant Use CO2 0.571307 0.307133 0.02 0.25 3.9969E-06 1.52E-05 122.62%

1.A.2.g Other - Gaseous Fuels N2O 0.284805 0.057514 0.02 0.5 1.7464E-06 6.65E-06 122.62%

2.D.3.b Road paving with asphalt CO2 0.001463 0.05298 0.2 0.6 2.0516E-06 7.81E-06 122.62%

1.A.2.g Other - Gaseous Fuels CH4 0.23893 0.04825 0.02 0.5 1.4651E-06 5.58E-06 122.62%

2.D.3.c Asphalt roofing CO2 0.002972 0.047829 0.2 0.6 1.829E-06 6.96E-06 122.62%

1.A.2.a Iron and Steel - Liquid Fuels CH4 0.091425 0 0.02 0.5 1.2827E-06 4.88E-06 122.62%

1.A.2.a Iron and Steel - Gaseous Fuels N2O 0.127395 0.01642 0.02 0.5 1.1451E-06 4.36E-06 122.62%


CH4 0.001126 0.034 0.02 0.5 1.314E-06 5E-06 122.62%


N2O 0.170873 0.040051 0.02 0.5 8.3089E-07 3.16E-06 122.62%

1.A.2.a Iron and Steel - Gaseous Fuels CH4 0.106875 0.013775 0.02 0.5 9.6069E-07 3.66E-06 122.62%


N2O 0.081184 0.003069 0.02 0.5 1.019E-06 3.88E-06 122.62%

1.A.2.f Non-metallic Minerals - Solid

Fuels

CH4 0.00425 0.032475 0.02 0.5 1.2105E-06 4.61E-06 122.62%

1.A.2.g Other - Solid Fuels N2O 0.124194 0.02235 0.02 0.5 8.6831E-07 3.31E-06 122.62%


N2O 0.000453 0.028885 0.02 0.5 1.1233E-06 4.28E-06 122.62%


419


removals


removals




Trend Uncertainty



to trend

1.A.2.a Iron and Steel - Solid Fuels N2O 0.023691 0.037548 0.02 0.5 1.1362E-06 4.33E-06 122.63%


CH4 0.14335 0.0336 0.02 0.5 6.9706E-07 2.65E-06 122.63%


CH4 0.068108 0.002575 0.02 0.5 8.5483E-07 3.25E-06 122.63%


and Other Energy Industries - Liquid Fuels

N2O 0.053795 0.045594 0.02 0.5 1.0285E-06 3.92E-06 122.63%


N2O 0.02384 0.03278 0.1 0.5 9.4759E-07 3.61E-06 122.63%


N2O 0.050064 0 0.02 0.5 7.0239E-07 2.67E-06 122.63%


N2O 0.024287 0.027684 0.02 0.5 7.4201E-07 2.83E-06 122.63%


N2O 1.45424 0.588801 0.05 0.5 2.6258E-06 1E-05 122.63%


N2O 0.036296 0 0.02 0.5 5.0924E-07 1.94E-06 122.63%


CH4 0.020375 0.023225 0.02 0.5 6.2249E-07 2.37E-06 122.63%


N2O 0.094663 0.053878 0.02 0.5 7.7913E-07 2.97E-06 122.63%



CH4 0.057625 0.0106 0.02 0.5 3.939E-07 1.5E-06 122.63%


CH4 0.034425 0.001 0.02 0.5 4.4387E-07 1.69E-06 122.63%


CH4 0.0315 0 0.02 0.5 4.4194E-07 1.68E-06 122.63%



CH4 0.079415 0.0452 0.02 0.5 6.5363E-07 2.49E-06 122.63%


CH4 0.026721 0.000625 0.02 0.5 3.5045E-07 1.33E-06 122.63%


CH4 0.02314 0.019125 0.02 0.5 4.2335E-07 1.61E-06 122.63%

1.A.3.c Railways - Liquid Fuels CH4 0.745009 0.317994 0.02 0.5 1.9847E-06 7.56E-06 122.63%


CH4 0.017773 0 0.02 0.5 2.4935E-07 9.49E-07 122.63%


CH4 0.015225 0 0.02 0.5 2.1361E-07 8.13E-07 122.63%

1.A.2.c Chemicals - Gaseous Fuels N2O 0.012728 0.011473 0.02 0.5 2.7015E-07 1.03E-06 122.63%


N2O 0.013857 0 0.02 0.5 1.9441E-07 7.4E-07 122.63%


N2O 0.012722 0 0.02 0.5 1.7848E-07 6.8E-07 122.63%

1.A.2.c Chemicals - Gaseous Fuels CH4 0.010678 0.009625 0.02 0.5 2.2664E-07 8.63E-07 122.63%

2.C.1 Iron and Steel Production CH4 0.06875 0.024149 0.1 0.25 2.0074E-08 7.64E-08 122.63%


CH4 0.02475 0.01425 0.1 0.5 2.1009E-07 8E-07 122.63%


CH4 9.5E-06 0.003556 0.02 0.5 1.3894E-07 5.29E-07 122.63%


CH4 0.002952 0.00474 0.2 0.5 1.4395E-07 5.48E-07 122.63%

2.G.3. N2O from product uses N2O 0.004768 0.005364 0.02 0.02 1.429E-07 5.44E-07 122.63%

1.B.2.b Natural Gas CO2 0.008686 0.006516 0.3115 0.01 1.3298E-07 5.06E-07 122.63%


Gasoline

N2O 9.37E-05 0.002384 0.02 0.5 9.1926E-08 3.5E-07 122.63%

3.A.4 Enteric Fermentation - Other livestock

CH4 18.092 7.542775 0.02 0.4 4.1177E-05 0.000157 122.65%

1.A.2.g Other - Solid Fuels CH4 0.006946 0.00125 0.02 0.5 4.8563E-08 1.85E-07 122.65%


420


removals


removals




Trend Uncertainty



to trend

1.A.2.a Iron and Steel - Solid Fuels CH4 0.001325 0.0021 0.02 0.5 6.3544E-08 2.42E-07 122.65%

1.B.2.c Venting and Flaring CO2 0.002806 0.001476 0.1 0.01 1.836E-08 6.99E-08 122.65%


CH4 0.000712 0 0.02 0.5 9.9823E-09 3.8E-08 122.65%

1.A.3.d Domestic Naviagtion -

Gasoline

N2O 0.00022 0.000352 0.2 0.5 1.0695E-08 4.07E-08 122.65%


CH4 1.97E-06 0.00005 0.02 0.5 1.928E-09 7.34E-09 122.65%


CO2 0 0 0.02 0.2 0 122.65%


CH4 0 0 0.02 0.5 0 122.65%


CH4 0 0.222 0.05 0.5 0 122.65%

1.A.1.c Manufacture of Solid Fuels and Other Energy Industries - Solid

Fuels

N2O 0 0 0.02 0.5 0 122.65%


N2O 0 0.352832 0.05 0.5 0 122.65%

1.A.2.a Iron and Steel - Biomass Fuels CO2 0 0 0.05 0.1 0 122.65%

1.A.2.a Iron and Steel - Peat CO2 0 0 0.02 0.1 0 122.65%

1.A.2.a Iron and Steel - Biomass Fuels CH4 0 0 0.05 0.5 0 122.65%

1.A.2.a Iron and Steel - Peat CH4 0 0 0.02 0.5 0 122.65%

1.A.2.a Iron and Steel - Biomass Fuels N2O 0 0 0.05 0.5 0 122.65%

1.A.2.a Iron and Steel - Peat N2O 0 0 0.02 0.5 0 122.65%


CO2 0 0 0.02 0.1 0 122.65%


CO2 0 0 0.02 0.2 0 122.65%


CO2 0 7.483228 0.02 0.05 0 122.65%


CO2 0 0 0.05 0.1 0 122.65%

1.A.2.b Non-Ferrous Metals - Peat CO2 0 0 0.02 0.1 0 122.65%


CH4 0 0 0.02 0.5 0 122.65%


Fuels

CH4 0 0 0.02 0.5 0 122.65%


CH4 0 0.00345 0.02 0.5 0 122.65%


CH4 0 0 0.05 0.5 0 122.65%

1.A.2.b Non-Ferrous Metals - Peat CH4 0 0 0.02 0.5 0 122.65%


N2O 0 0 0.02 0.5 0 122.65%


N2O 0 0 0.02 0.5 0 122.65%


N2O 0 0.004112 0.02 0.5 0 122.65%


Biomass Fuels

N2O 0 0 0.05 0.5 0 122.65%

1.A.2.b Non-Ferrous Metals - Peat N2O 0 0 0.02 0.5 0 122.65%

1.A.2.c Chemicals - Peat CO2 0 2.077329 0.02 0.1 0 122.65%

1.A.2.c Chemicals - Biomass Fuels CH4 0 0.157344 0.05 0.5 0 122.65%


421


removals


removals




Trend Uncertainty



to trend

1.A.2.c Chemicals - Peat CH4 0 0.001 0.02 0.5 0 122.65%

1.A.2.c Chemicals - Biomass Fuels N2O 0 0.249538 0.05 0.5 0 122.65%

1.A.2.c Chemicals - Peat N2O 0 0.00894 0.02 0.5 0 122.65%

1.A.2.d. Pulp, Paper and Print - Peat CO2 0 0 0.02 0.1 0 122.65%


CH4 0 0.07275 0.05 0.5 0 122.65%

1.A.2.d. Pulp, Paper and Print - Peat CH4 0 0 0.02 0.5 0 122.65%


N2O 0 0.115624 0.05 0.5 0 122.65%

1.A.2.d. Pulp, Paper and Print - Peat N2O 0 0 0.02 0.5 0 122.65%


CO2 0 0 0.02 0.1 0 122.65%


CO2 0 2.1257 0.02 0.2 0 122.65%


and Tobacco - Peat

CH4 0 0 0.02 0.5 0 122.65%


CH4 0 0.02175 0.02 0.5 0 122.65%


N2O 0 0 0.02 0.5 0 122.65%


N2O 0 0.034568 0.02 0.5 0 122.65%

1.A.2.f Non-metallic Minerals - Peat CO2 0 0 0.02 0.1 0 122.65%


CO2 0 92.50516 0.02 0.02 0 122.65%

1.A.2.f Non-metallic Minerals - Peat CH4 0 0 0.02 0.5 0 122.65%


Fossil Fuels

CH4 0 0.814737 0.02 0.5 0 122.65%

1.A.2.f Non-metallic Minerals - Peat N2O 0 0 0.02 0.5 0 122.65%


N2O 0 1.294888 0.02 0.5 0 122.65%

1.A.2.g Other - Peat CO2 0 0.39 0.02 0.1 0 122.65%

1.A.2.g Other - Other Fossil Fuels CO2 0 0 0.02 0.2 0 122.65%

1.A.2.g Other - Peat CH4 0 0.0001 0.02 0.5 0 122.65%

1.A.2.g Other - Other Fossil Fuels CH4 0 0 0.02 0.5 0 122.65%

1.A.2.g Other - Peat N2O 0 0.001788 0.02 0.5 0 122.65%

1.A.2.g Other - Other Fossil Fuels N2O 0 0 0.02 0.5 0 122.65%


CH4 0 0.020267 0.02 0.5 0 122.65%


N2O 0 0.307472 0.02 0.5 0 122.65%

1.A.3.c. Railway Biomass Fuels CH4 0 0.00132 0.02 0.5 0 122.65%

1.A.3.c. Railway Biomass Fuels N2O 0 0.020026 0.02 0.5 0 122.65%


CO2 0 0 0.02 0.2 0 122.65%


Other Fossil Fuels

CH4 0 0 0.02 0.5 0 122.65%


N2O 0 0 0.02 0.5 0 122.65%


CO2 0 0 0.02 0.2 0 122.65%


422


removals


removals




Trend Uncertainty



to trend


CH4 0 0 0.02 0.5 0 122.65%


N2O 0 0 0.02 0.5 0 122.65%


CO2 0 0 0.02 0.5 0 122.65%

1.A.4.c Agriculture/Forestry/Fisheries

- Other Fossil Fuels

CH4 0 0 0.02 0.5 0 122.65%


N2O 0 0 0.02 0.5 0 122.65%

1.A.5.b Mobile - Liquid Fuels CO2 0 6.447874 0.02 0.5 0 122.65%

1.A.5.b Mobile - Liquid Fuels CH4 0 0.01141 0.02 0.5 0 122.65%

1.A.5.b Mobile - Liquid Fuels N2O 0 0.052372 0.02 0.5 0 122.65%

2.D.2 Paraffin wax use CO2 0 0.132 0.02 0.5 0 122.65%

2.D.3. Solvent Use CO2 0 0 0.02 0.2 0 122.65%

2.D.3.d Urea Use CO2 0 0.537788 0.2 0.1 0 122.65%

2.F.1. Refrigeration and air conditioning

HFCs 0 102.8616 0.75 0.75 0 122.65%

2.F.2 Foam blowing agents HFCs 0 0 0.75 0.75 0 122.65%

2.F.3. Fire Protection HFCs 0 0.23696 0.75 0.75 0 122.65%

2.F.4. Aerosols HFCs 0 3.522163 0.75 0.75 0 122.65%

2.G.1. Electrical equipment SF6 0 8.503158 0.02 0.3 0 122.65%

2.G.4. Other HFCs 0 1.835685 0.75 0.75 0 122.65%

5.A.1. Managed Waste Disposal on

Land

CH4 0 186.6154 0.2 0.52 0 122.65%

5.B.1. Composting CH4 0 1.4367 0.2 1 0 122.65%

5.B.1. Composting N2O 0 1.28441 0.2 0.9 0 122.65%

input data input data input data Note A

input data Note A

END

Total 25568.24 9171.839 15.643 111.1882 0.26264746 1 326.936876


ANNEX 2: ASSESSMENT OF UNCERTAINTY

A.2.1 Approach 1 uncertainty analysis for year 2013 including LULUCF



Year 2013


Activity

data uncertainty

Emission

factor / estimation

parameter

uncertainty

Combined

uncertainty

Contribution

to variance by category in

year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national

emissions

introduced by

emission factor / estimation

parameter

uncertainty

Uncertainty in trend

in national emissions introduced by activity

data uncertainty

Uncertainty

introduced into the trend

in total

national

emissions


CO2 3049.621305 15.86030086 2% 10% 0.1020 0.0000 0.1088 0.0009 0.0109 0.0000 0.000118337



CO2 218.053 40.1104 2% 20% 0.2010 0.0000 0.0055 0.0023 0.0011 0.0001 1.23029E-06



CO2 2644.318679 1789.305004 2% 5% 0.0539 0.0001 0.0082 0.1035 0.0004 0.0029 8.74175E-06


CO2 142.826737 4.15465786 2% 15% 0.1513 0.0000 0.0049 0.0002 0.0007 0.0000 5.41582E-07



CO2 3.0786 0 2% 20% 0.2010 0.0000 0.0001 0.0000 0.0000 0.0000 4.92272E-10



CH4 3.00505 0.015625 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0001 0.0000 2.88271E-09


CH4 0.057625 0.0106 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 5.35571E-13



CH4 1.20535 0.824925 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.42516E-12



CH4 0.327 6.940298662 5% 50% 0.5025 0.0000 0.0004 0.0004 0.0002 0.0000 3.87806E-08


CH4 0.034425 0.001 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.49661E-13



CH4 0.0315 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.22108E-13



N2O 7.1626684 0.0371308 2% 50% 0.5004 0.0000 0.0003 0.0000 0.0001 0.0000 1.63782E-08


424


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /

estimation parameter

uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty


in national emissions

introduced by activity data uncertainty

Uncertainty

introduced

into the trend in total

national

emissions


N2O 1.030335 0.189528 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.71219E-10



N2O 1.4367772 0.9833106 2% 50% 0.5004 0.0000 0.0000 0.0001 0.0000 0.0000 9.12927E-12



N2O 0.519712 11.01384 5% 50% 0.5025 0.0000 0.0006 0.0006 0.0003 0.0000 9.76556E-08


N2O 0.615519 0.01788 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.11785E-10



N2O 0.050064 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 8.13638E-13


and Other Energ y Industries - Liquid

Fuels

CO2 24.7792529 18.87025524 2% 10% 0.1020 0.0000 0.0002 0.0011 0.0000 0.0000 1.34873E-09


and Other Energ y Industries - Solid Fuels

CO2 0 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 0


and Other Energ y Industries - Gaseous Fuels

CO2 44.69904433 50.37622658 2% 5% 0.0539 0.0000 0.0013 0.0029 0.0001 0.0001 1.10445E-08

1.A.1.c Manufacture of Solid Fuels and Other Energ y Industries - Biomass

Fuels

CO2 0 5% 10% 0.1118 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.1.c Manufacture of Solid Fuels and Other Energ y Industries - Peat

CO2 73.83865681 0 2% 10% 0.1020 0.0000 0.0027 0.0000 0.0003 0.0000 7.07898E-08


and Other Energ y Industries - Liquid

Fuels

CH4 0.02314 0.019125 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.95595E-14


and Other Energ y Industries - Solid

Fuels

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


and Other Energ y Industries - Gaseous

CH4 0.020375 0.023225 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 9.43032E-14


425


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions

Fuels


and Other Energ y Industries - Biomass

Fuels

CH4 0 0.222 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 4.20643E-11


and Other Energ y Industries - Peat

CH4 0.0177725 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.02536E-13


and Other Energ y Industries - Liquid Fuels

N2O 0.05379496 0.045594 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.27827E-13


and Other Energ y Industries - Solid Fuels

N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.1.c Manufacture of Solid Fuels and Other Energ y Industries - Gaseous

Fuels

N2O 0.024287 0.0276842 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.33992E-13

1.A.1.c Manufacture of Solid Fuels and Other Energ y Industries - Biomass

Fuels

N2O 0 0.352832 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 1.06254E-10


and Other Energ y Industries - Peat

N2O 0.3177723 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.27802E-11

1.A.2.a Iron and Steel - Liquid Fuels CO2 93.25228881 0 2% 10% 0.1020 0.0000 0.0034 0.0000 0.0003 0.0000 1.12905E-07

1.A.2.a Iron and Steel - Solid Fuels CO2 5.671 8.7096 2% 20% 0.2010 0.0000 0.0003 0.0005 0.0001 0.0000 3.79191E-09

1.A.2.a Iron and Steel - Gaseous Fuels CO2 234.4643123 29.87868767 2% 5% 0.0539 0.0000 0.0067 0.0017 0.0003 0.0000 1.15264E-07

1.A.2.a Iron and Steel - Biomass Fuels CO2 0 0 5% 10% 0.1118 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.a Iron and Steel - Peat CO2 0 0 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 0


fuels

CO2 61.3521 0 2% 20% 0.2010 0.0000 0.0022 0.0000 0.0004 0.0000 1.95492E-07

1.A.2.a Iron and Steel - Liquid Fuels CH4 0.091425 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.71338E-12


426


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions

1.A.2.a Iron and Steel - Solid Fuels CH4 0.001325 0.0021 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.37149E-15

1.A.2.a Iron and Steel - Gaseous Fuels CH4 0.106875 0.013775 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.33264E-12

1.A.2.a Iron and Steel - Biomass Fuels CH4 0 0 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.a Iron and Steel - Peat CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


fuels

CH4 0.62775 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.27924E-10

1.A.2.a Iron and Steel - Liquid Fuels N2O 0.2179572 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.54214E-11

1.A.2.a Iron and Steel - Solid Fuels N2O 0.023691 0.037548 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.38457E-13

1.A.2.a Iron and Steel - Gaseous Fuels N2O 0.127395 0.0164198 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.31436E-12

1.A.2.a Iron and Steel - Biomass Fuels N2O 0 0 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.a Iron and Steel - Peat N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


fuels

N2O 0.997704 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.23134E-10


Fuels

CO2 0 0 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 0


Fuels

CO2 0 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.b Non-Ferrous Metals - Gaseous

Fuels

CO2 0 7.483228491 2% 5% 0.0539 0.0000 0.0004 0.0004 0.0000 0.0000 6.18529E-10

1.A.2.b Non-Ferrous Metals - Biomass

Fuels

CO2 0 0 5% 10% 0.1118 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.b Non-Ferrous Metals - Peat CO2 0 0 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 0


Fuels

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Fuels

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.b Non-Ferrous Metals - Gaseous CH4 0 0.00345 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 9.99157E-15


427


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions

Fuels

1.A.2.b Non-Ferrous Metals - Biomass

Fuels

CH4 0 0 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.b Non-Ferrous Metals - Peat CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Fuels

N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Fuels

N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.b Non-Ferrous Metals - Gaseous

Fuels

N2O 0 0.0041124 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.41967E-14


N2O 0 0 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.b Non-Ferrous Metals - Peat N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.c Chemicals - Liquid Fuels CO2 276.6786727 8.55381336 2% 10% 0.1020 0.0000 0.0095 0.0005 0.0009 0.0000 8.97692E-07

1.A.2.c Chemicals - Gaseous Fuels CO2 23.42449305 20.87712296 2% 5% 0.0539 0.0000 0.0004 0.0012 0.0000 0.0000 1.49782E-09

1.A.2.c Chemicals - Peat CO2 0 2.07732893 2% 10% 0.1020 0.0000 0.0001 0.0001 0.0000 0.0000 1.55992E-10

1.A.2.c Chemicals - Liquid Fuels CH4 0.273195 0.003425 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.3263E-11

1.A.2.c Chemicals - Gaseous Fuels CH4 0.0106775 0.009625 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 7.65142E-15

1.A.2.c Chemicals - Biomass Fuels CH4 0 0.157344085 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 2.11305E-11

1.A.2.c Chemicals - Peat CH4 0 0.001 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 8.39451E-16

1.A.2.c Chemicals - Liquid Fuels N2O 0.65129688 0.0040826 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.34944E-10

1.A.2.c Chemicals - Gaseous Fuels N2O 0.01272758 0.011473 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.08716E-14

1.A.2.c Chemicals - Biomass Fuels N2O 0 0.24953815 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 5.31474E-11

1.A.2.c Chemicals - Peat N2O 0 0.00894 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.70919E-14


CO2 15.54739345 0 2% 10% 0.1020 0.0000 0.0006 0.0000 0.0001 0.0000 3.13868E-09


428


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions


CO2 2.692316 0 2% 20% 0.2010 0.0000 0.0001 0.0000 0.0000 0.0000 3.76488E-10


Gaseous Fuels

CO2 149.4154681 5.585308222 2% 5% 0.0539 0.0000 0.0051 0.0003 0.0003 0.0000 6.41067E-08

1.A.2.d. Pulp, Paper and Print - Peat CO2 0 0 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 0


CH4 0.015225 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 7.5248E-14

1.A.2.d. Pulp, Paper and Print - Solid

Fuels

CH4 0.0007115 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.64335E-16


Gaseous Fuels

CH4 0.0681075 0.002575 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.32857E-12


Biomass Fuels

CH4 0 0.07275 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 4.51725E-12

1.A.2.d. Pulp, Paper and Print - Peat CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Liquid Fuels

N2O 0.0362964 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.27669E-13

1.A.2.d. Pulp, Paper and Print - Solid

Fuels

N2O 0.01272162 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 5.2537E-14


Gaseous Fuels

N2O 0.08118414 0.0030694 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.88771E-12


Biomass Fuels

N2O 0 0.115624 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 1.14105E-11

1.A.2.d. Pulp, Paper and Print - Peat N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0



CO2 798.2058686 33.22587 2% 11% 0.1131 0.0000 0.0268 0.0019 0.0030 0.0001 8.91917E-06


CO2 103.071464 2.365 2% 20% 0.2010 0.0000 0.0036 0.0001 0.0007 0.0000 5.11842E-07



CO2 174.2220665 98.04113849 2% 5% 0.0539 0.0000 0.0006 0.0057 0.0000 0.0002 2.66557E-08


429


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions


CO2 0 0 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 0



CO2 0 2.1257 2% 20% 0.2010 0.0000 0.0001 0.0001 0.0000 0.0000 6.17066E-10



CH4 0.78871 0.026525 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.8072E-10


CH4 0.026721 0.000625 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.14705E-13



CH4 0.079415 0.0452 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.06842E-14


and Tobacco - Biomass Fuels

CH4 0.171 0.336825 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 4.6286E-11


CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0



CH4 0 0.02175 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.97113E-13



N2O 1.87891384 0.057812 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0000 0.0000 1.0356E-09


N2O 0.47777148 0.011175 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.86399E-11



N2O 0.09466268 0.0538784 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.93894E-14


and Tobacco - Biomass Fuels

N2O 0.271776 0.5352974 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 1.16899E-10


N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0



N2O 0 0.034568 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.0031E-12

1.A.2.f Non-metallic Minerals - Liquid

Fuels

CO2 273.5769252 21.97829728 2% 10% 0.1020 0.0000 0.0086 0.0013 0.0009 0.0000 7.38376E-07


430


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions


CO2 16.4292 122.8854 2% 20% 0.2010 0.0000 0.0065 0.0071 0.0013 0.0002 1.73946E-06


Gaseous Fuels

CO2 314.4838285 72.88013835 2% 5% 0.0539 0.0000 0.0071 0.0042 0.0004 0.0001 1.40766E-07

1.A.2.f Non-metallic Minerals - Peat CO2 0 0 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 0


CO2 0 92.50516 2% 2% 0.0283 0.0000 0.0054 0.0054 0.0001 0.0002 3.43701E-08


Fuels

CH4 0.268845 0.022275 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.76373E-11


Fuels

CH4 0.00425 0.032475 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 7.47303E-13


Gaseous Fuels

CH4 0.14335 0.0336 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.59781E-12


Biomass Fuels

CH4 0.00525 0.66454334 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 3.73297E-10

1.A.2.f Non-metallic Minerals - Peat CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Fossil Fuels

CH4 0 0.814736505 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 5.57224E-10


Fuels

N2O 0.64092648 0.0531036 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.00241E-10


Fuels

N2O 0.07599 0.580653 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.38908E-10


Gaseous Fuels

N2O 0.1708732 0.0400512 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.69113E-12


N2O 0.008344 1.056180881 5% 50% 0.5025 0.0000 0.0001 0.0001 0.0000 0.0000 9.42941E-10

1.A.2.f Non-metallic Minerals - Peat N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Fossil Fuels

N2O 0 1.294887885 2% 50% 0.5004 0.0000 0.0001 0.0001 0.0000 0.0000 1.40754E-09


431


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions

1.A.2.g Other - Liquid Fuels CO2 795.7039841 122.1484903 2% 10% 0.1020 0.0000 0.0216 0.0071 0.0022 0.0002 4.7039E-06

1.A.2.g Other - Solid Fuels CO2 27.263264 4.73 2% 20% 0.2010 0.0000 0.0007 0.0003 0.0001 0.0000 2.01536E-08

1.A.2.g Other - Gaseous Fuels CO2 524.168965 104.6567463 2% 5% 0.0539 0.0000 0.0128 0.0061 0.0006 0.0002 4.40821E-07

1.A.2.g Other - Peat CO2 0 0.39 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 5.4982E-12

1.A.2.g Other - Other Fossil Fuels CO2 0 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.g Other - Liquid Fuels CH4 2.26531 0.194025 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0000 0.0000 1.2393E-09

1.A.2.g Other - Solid Fuels CH4 0.006946 0.00125 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 7.92331E-15

1.A.2.g Other - Gaseous Fuels CH4 0.23893 0.04825 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 8.46937E-12

1.A.2.g Other - Biomass Fuels CH4 0.2865 9.58215 5% 50% 0.5025 0.0000 0.0005 0.0006 0.0003 0.0000 7.55321E-08

1.A.2.g Other - Peat CH4 0 0.0001 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 8.3945E-18

1.A.2.g Other - Other Fossil Fuels CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.g Other - Liquid Fuels N2O 2.149772 0.297218048 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0000 0.0000 9.08382E-10

1.A.2.g Other - Solid Fuels N2O 0.12419448 0.02235 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.53304E-12

1.A.2.g Other - Gaseous Fuels N2O 0.28480456 0.057514 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.20338E-11

1.A.2.g Other - Biomass Fuels N2O 0.455344 15.2293496 5% 50% 0.5025 0.0000 0.0009 0.0009 0.0004 0.0001 1.90796E-07

1.A.2.g Other - Peat N2O 0 0.001788 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.68368E-15

1.A.2.g Other - Other Fossil Fuels N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Gasoline

CO2 0.011005031 0.28 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.26403E-11

1.A.3.a Domestic Aviation - Jet

kerosene

CO2 0.054819072 3.107107044 2% 50% 0.5004 0.0000 0.0002 0.0002 0.0001 0.0000 7.92758E-09


Gasoline

CH4 1.96519E-06 0.00005 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.99745E-18


kerosene

CH4 0.000009504 0.00355575 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.05783E-14


432


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions


N2O 9.36998E-05 0.002384 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.54099E-15


kerosene

N2O 0.000453151 0.028884544 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.86791E-13


Gasoline

CO2 1723.750448 625.9575 2% 50% 0.5004 0.0008 0.0259 0.0362 0.0129 0.0010 0.000168425


Oil

CO2 616.1359677 1741.886302 2% 50% 0.5004 0.0066 0.0785 0.1008 0.0393 0.0029 0.001550453

1.A.3.b Road Transportation - LPG CO2 36.95737306 147.8567316 2% 50% 0.5004 0.0000 0.0072 0.0086 0.0036 0.0002 1.30986E-05


Lubricants

CO2 3.4629 4.33188 10% 50% 0.5099 0.0000 0.0001 0.0003 0.0001 0.0000 5.21462E-09


Gaseous Fuels

CO2 17.6165255 0 2% 50% 0.5004 0.0000 0.0006 0.0000 0.0003 0.0000 1.00742E-07


Gasoline

CH4 17.15516309 2.455797158 2% 50% 0.5004 0.0000 0.0005 0.0001 0.0002 0.0000 5.66833E-08


Oil

CH4 1.108041461 1.116917573 2% 50% 0.5004 0.0000 0.0000 0.0001 0.0000 0.0000 1.55744E-10

1.A.3.b Road Transportation - LPG CH4 0.124565463 0.801443483 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.40164E-10


Lubricants

CH4 0.02475 0.01425 10% 50% 0.5099 0.0000 0.0000 0.0000 0.0000 0.0000 1.47303E-14


Gaseous Fuels

CH4 0.7015 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.59748E-10


Biomass

CH4 0 0.020267227 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.44813E-13


N2O 13.07410741 4.586290942 2% 50% 0.5004 0.0000 0.0002 0.0003 0.0001 0.0000 1.0643E-08


N2O 5.593827044 13.09045627 2% 50% 0.5004 0.0000 0.0006 0.0008 0.0003 0.0000 7.76769E-08

1.A.3.b Road Transportation - LPG N2O 0.163685304 2.463208388 2% 50% 0.5004 0.0000 0.0001 0.0001 0.0001 0.0000 4.6817E-09


433


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions


N2O 0.02384 0.03278 10% 50% 0.5099 0.0000 0.0000 0.0000 0.0000 0.0000 3.40976E-13


Gaseous Fuels

N2O 0.27267 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.41354E-11


Biomass

N2O 0 0.307472263 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 7.9361E-11

1.A.3.c Railways - Liquid Fuels CO2 531.37994 223.258 2% 5% 0.0539 0.0000 0.0062 0.0129 0.0003 0.0004 2.30492E-07

1.A.3.c Railways - Liquid Fuels CH4 0.745009038 0.31799375 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.81167E-11

1.A.3.c. Railway Biomass Fuels CH4 0 0.00132 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.46266E-15

1.A.3.c Railways - Liquid Fuels N2O 61.20060747 26.122382 2% 50% 0.5004 0.0000 0.0007 0.0015 0.0003 0.0000 1.22247E-07

1.A.3.c. Railway Biomass Fuels N2O 0 0.0200256 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.36641E-13


Gasoline

CO2 0.172771761 0.2772 20% 5% 0.2062 0.0000 0.0000 0.0000 0.0000 0.0000 2.08159E-11


CO2 0.8332289 25.16 2% 5% 0.0539 0.0000 0.0014 0.0015 0.0001 0.0000 6.77575E-09


CH4 0.00295205 0.004739595 20% 50% 0.5385 0.0000 0.0000 0.0000 0.0000 0.0000 1.30567E-14

1.A.3.d Domestic Naviagtion - Diesel

Oil

CH4 0.001126 0.034 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 9.30911E-13


Gasoline

N2O 0.000219506 0.000352182 20% 50% 0.5385 0.0000 0.0000 0.0000 0.0000 0.0000 7.20579E-17

1.A.3.d Domestic Naviagtion - Diesel

Oil

N2O 0.1006644 3.0396 2% 50% 0.5004 0.0000 0.0002 0.0002 0.0001 0.0000 7.44017E-09


Liquid Fuels

CO2 1007.294341 142.1295097 2% 10% 0.1020 0.0000 0.0281 0.0082 0.0028 0.0002 7.92681E-06


Solid Fuels

CO2 1410.784936 49.0974 2% 20% 0.2010 0.0000 0.0480 0.0028 0.0096 0.0001 9.20033E-05


CO2 274.4466477 242.7711156 2% 5% 0.0539 0.0000 0.0042 0.0140 0.0002 0.0004 2.00977E-07


434


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions


CO2 66.54499789 0 2% 10% 0.1020 0.0000 0.0024 0.0000 0.0002 0.0000 5.7496E-08


Other Fossil Fuels

CO2 0 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 0


CH4 3.495 0.74775 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0000 0.0000 1.71051E-09


CH4 3.72829 0.12975 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0001 0.0000 4.02219E-09


Gaseous Fuels

CH4 0.6255 0.559625 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.50298E-11


Biomass Fuels

CH4 39.135 39.52177273 5% 50% 0.5025 0.0000 0.0009 0.0023 0.0004 0.0002 2.18098E-07


Peat

CH4 0.168 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 9.16218E-12


Other Fossil Fuels

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Liquid Fuels

N2O 2.411706848 0.358718096 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0000 0.0000 1.09435E-09


Solid Fuels

N2O 6.66618252 0.231993 2% 50% 0.5004 0.0000 0.0002 0.0000 0.0001 0.0000 1.28587E-08


Gaseous Fuels

N2O 0.1491192 0.1334146 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.42256E-12


Biomass Fuels

N2O 6.219856 6.292871419 5% 50% 0.5025 0.0000 0.0001 0.0004 0.0001 0.0000 5.55835E-09


Peat

N2O 0.2955862 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.83628E-11


N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.4.b Residential - Liquid Fuels CO2 329.9110639 154.26032 2% 10% 0.1020 0.0000 0.0030 0.0089 0.0003 0.0003 1.51517E-07

1.A.4.b Residential - Solid Fuels CO2 605.8184 50.138 2% 20% 0.2010 0.0000 0.0189 0.0029 0.0038 0.0001 1.43301E-05


435


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions

1.A.4.b Residential - Gaseous Fuels CO2 219.6011945 231.3293677 2% 5% 0.0539 0.0000 0.0055 0.0134 0.0003 0.0004 2.18077E-07

1.A.4.b Residential - Peat CO2 42.27150449 0 2% 10% 0.1020 0.0000 0.0015 0.0000 0.0002 0.0000 2.32014E-08


Fuels

CO2 0 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.4.b Residential - Liquid Fuels CH4 0.868375 1.270375 2% 50% 0.5004 0.0000 0.0000 0.0001 0.0000 0.0000 4.49632E-10

1.A.4.b Residential - Solid Fuels CH4 48.03 3.975 2% 50% 0.5004 0.0000 0.0015 0.0002 0.0008 0.0000 5.63091E-07

1.A.4.b Residential - Gaseous Fuels CH4 0.5005 0.53325 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.18197E-11

1.A.4.b Residential - Biomass Fuels CH4 150.075 181.2375 10% 50% 0.5099 0.0001 0.0051 0.0105 0.0025 0.0015 8.64279E-06

1.A.4.b Residential - Peat CH4 3.1875 0 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0001 0.0000 3.29822E-09


CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.4.b Residential - Liquid Fuels N2O 0.4500694 0.343223288 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.62561E-12

1.A.4.b Residential - Solid Fuels N2O 2.862588 0.23691 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0000 0.0000 2.00029E-09

1.A.4.b Residential - Gaseous Fuels N2O 0.1193192 0.1271268 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.3768E-12

1.A.4.b Residential - Biomass Fuels N2O 23.85192 28.75998 10% 50% 0.5099 0.0000 0.0008 0.0017 0.0004 0.0002 2.17125E-07

1.A.4.b Residential - Peat N2O 0.1860712 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.12393E-11


Fuels

N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


- Liquid Fuels

CO2 695.0757089 317.4303672 2% 11% 0.1088 0.0000 0.0067 0.0184 0.0007 0.0005 7.79655E-07


- Solid Fuels

CO2 102.28152 2.4596 2% 50% 0.5004 0.0000 0.0035 0.0001 0.0018 0.0000 3.13853E-06


- Gaseous Fuels

CO2 778.5312078 57.80522878 2% 50% 0.5004 0.0000 0.0247 0.0033 0.0123 0.0001 0.000152515


- Peat

CO2 3.0225 0 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0001 0.0000 2.96559E-09


436


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions


CO2 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


- Liquid Fuels

CH4 5.99375 1.250225 2% 50% 0.5004 0.0000 0.0001 0.0001 0.0001 0.0000 5.16312E-09


- Solid Fuels

CH4 8.109 0.195 2% 50% 0.5004 0.0000 0.0003 0.0000 0.0001 0.0000 1.97294E-08


CH4 1.774375 0.13325 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0000 0.0000 7.90496E-10


- Biomass Fuels

CH4 9.15 3.627804811 5% 50% 0.5025 0.0000 0.0001 0.0002 0.0001 0.0000 3.81024E-09


- Peat

CH4 0.2325 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.75479E-11


- Other Fossil Fuels

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


- Liquid Fuels

N2O 2.908143856 0.911925296 2% 50% 0.5004 0.0000 0.0001 0.0001 0.0000 0.0000 6.79143E-10


N2O 0.4832964 0.011622 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 7.00826E-11


- Gaseous Fuels

N2O 0.423011 0.0317668 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.49276E-11


- Biomass Fuels

N2O 1.45424 0.588801467 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 8.98765E-11


N2O 0.013857 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.23331E-14


N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.5.b Mobile - Liquid Fuels CO2 0 6.447874167 2% 50% 0.5004 0.0000 0.0004 0.0004 0.0002 0.0000 3.49002E-08

1.A.5.b Mobile - Liquid Fuels CH4 0 0.011410463 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.09295E-13

1.A.5.b Mobile - Liquid Fuels N2O 0 0.052371989 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.30247E-12


437


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions

1.B.2.b Natural Gas CO2 0.008686 0.006516 31% 1% 0.3117 0.0000 0.0000 0.0000 0.0000 0.0000 2.75793E-14

1.B.2.b Natural Gas CH4 177.238 82.3568 31% 1% 0.3117 0.0000 0.0016 0.0048 0.0000 0.0021 4.40594E-06

1.B.2.c Venting and Flaring CO2 0.00 0.001476 10% 1% 0.1005 0.0000 0.0000 0.0000 0.0000 0.0000 1.45863E-16

1.B.2.c Venting and Flaring CH4 70.344325 18.642 10% 1% 0.1005 0.0000 0.0015 0.0011 0.0000 0.0002 2.3476E-08

2.A.1. Cement Production CO2 370.8039966 537.6437303 10% 5% 0.1118 0.0000 0.0177 0.0311 0.0009 0.0044 2.0137E-05

2.A.2. Lime Production CO2 148.8573814 0.274894634 2% 50% 0.5004 0.0000 0.0053 0.0000 0.0027 0.0000 7.14936E-06

2.A.3. Glass production CO2 0.352 2.976908 2% 60% 0.6003 0.0000 0.0002 0.0002 0.0001 0.0000 9.18704E-09

2.A.4. Other process uses of carbonates CO2 69.184752 9.050385865 2% 50% 0.5004 0.0000 0.0020 0.0005 0.0010 0.0000 9.69821E-07

2.C.1 Iron and Steel Production CO2 12.81611267 0.955378707 5% 25% 0.2550 0.0000 0.0004 0.0001 0.0001 0.0000 1.03454E-08

2.C.1 Iron and Steel Production CH4 0.06875 0.02414875 10% 25% 0.2693 0.0000 0.0000 0.0000 0.0000 0.0000 1.11975E-13

2.D.1 Lubricant Use CO2 0.571307104 0.3071332 2% 25% 0.2508 0.0000 0.0000 0.0000 0.0000 0.0000 7.48885E-13

2.D.2 Paraff in wax use CO2 0 0.132 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.46266E-11

2.D.3.b Road paving with asphalt CO2 0.001463305 0.052980255 20% 60% 0.6325 0.0000 0.0000 0.0000 0.0000 0.0000 4.01842E-12

2.D.3.c Asphalt roofing CO2 0.002972338 0.047829397 20% 60% 0.6325 0.0000 0.0000 0.0000 0.0000 0.0000 3.15981E-12

2.D.3. Solvent Use CO2 0 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 0

2.D.3.d Urea Use CO2 0 0.537788082 20% 10% 0.2236 0.0000 0.0000 0.0000 0.0000 0.0000 8.7123E-11


conditioning

HFCs 0.00 102.8615524 75% 75% 1.0607 0.0001 0.0060 0.0060 0.0045 0.0063 5.9761E-05

2.F.2 Foam blowing agents HFCs 0.00 0.0014292 75% 75% 1.0607 0.0000 0.0000 0.0000 0.0000 0.0000 1.15371E-14

2.F.3. Fire Protection HFCs 0.00 0.2369598 75% 75% 1.0607 0.0000 0.0000 0.0000 0.0000 0.0000 3.17147E-10

2.F.4. Aerosols HFCs 0.00 3.52216298 75% 75% 1.0607 0.0000 0.0002 0.0002 0.0002 0.0002 7.00697E-08

2.G.1. Electrical equipment SF6 0.00 8.50315813 2% 30% 0.3007 0.0000 0.0005 0.0005 0.0001 0.0000 2.19743E-08

2.G.3. N2O from product uses N2O 0.004768 0.005364 2% 2% 0.0283 0.0000 0.0000 0.0000 0.0000 0.0000 8.47181E-17


438


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions

2.G.4. Other HFCs 0.00 1.835685463 75% 75% 1.0607 0.0000 0.0001 0.0001 0.0001 0.0001 1.9033E-08

3.A.1 Enteric Fermentation - Cattle CH4 2178.340191 765.2269298 2% 20% 0.2010 0.0002 0.0342 0.0443 0.0068 0.0013 4.83019E-05

3.A.2 Enteric Fermentation - Sheep CH4 32.92 16.96 2% 40% 0.4005 0.0000 0.0002 0.0010 0.0001 0.0000 7.49757E-09

3.A.3 Enteric Fermentation - Swine CH4 52.54125 13.78125 2% 40% 0.4005 0.0000 0.0011 0.0008 0.0004 0.0000 1.92693E-07

3.A.4 Enteric Fermentation - Other

livestock

CH4 18.092 7.542775 2% 40% 0.4005 0.0000 0.0002 0.0004 0.0001 0.0000 7.58665E-09

3.B.1.1 Manure Management - Cattle CH4 99.92910799 70.54136894 25% 20% 0.3202 0.0000 0.0005 0.0041 0.0001 0.0014 2.09115E-06

3.B.2.1 Manure Management - Cattle N2O 124.5358736 49.48502171 25% 20% 0.3202 0.0000 0.0016 0.0029 0.0003 0.0010 1.1301E-06

3.B.1.2 Manure Management - Sheep CH4 0.78185 0.4028 25% 30% 0.3905 0.0000 0.0000 0.0000 0.0000 0.0000 7.00169E-11

3.B.2.2 Manure Management - Sheep N2O 1.32908 1.03108 25% 30% 0.3905 0.0000 0.0000 0.0001 0.0000 0.0000 4.57243E-10

3.B.1.3 Manure Management - Swaine CH4 224.4975 58.4925 25% 30% 0.3905 0.0000 0.0047 0.0034 0.0014 0.0012 3.42383E-06

3.B.2.3 Manure Management - Swaine N2O 15.35892 3.60282 25% 30% 0.3905 0.0000 0.0003 0.0002 0.0001 0.0001 1.61438E-08


CH4 83.38555 7.57375 25% 30% 0.3905 0.0000 0.0026 0.0004 0.0008 0.0002 6.16809E-07


N2O 22.04902 9.58666 25% 30% 0.3905 0.0000 0.0002 0.0006 0.0001 0.0002 4.3631E-08

3.B.5 Indirect N2O emissions from

Manure Management

N2O 142.1423263 47.57185732 2% 50% 0.5004 0.0000 0.0024 0.0028 0.0012 0.0001 1.40984E-06


managed soils

N2O 2183.630811 1240.469649 2% 50% 0.5004 0.0033 0.0069 0.0718 0.0035 0.0020 1.60621E-05

3.G. Liming CO2 371.4186667 13.7756667 2% 50% 0.5004 0.0000 0.0126 0.0008 0.0063 0.0000 3.95914E-05

3.H. Urea Application CO2 7.7088 4.075866667 20% 5% 0.2062 0.0000 0.0000 0.0002 0.0000 0.0001 4.45274E-09

4.A.1 Forest Land remaining Forest

Land – Carbon stock change, living biomass

CO2 -19 499.29 -4136.117297 3% 0.0250 0.0001 0.4686 0.2393 0.0000 0.0085 7.15754E-05


Land – Carbon stock change, dead

CO2 77.31 -3801.986511 2% 0.0200 0.0000 0.2227 0.2200 0.0000 0.0062 3.87061E-05


439


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions

wood


Land – Drained organic soil

CO2 4 125.55 4252.175208 6% 111% 1.1116 0.1928 0.0971 0.2460 0.1078 0.0209 0.01205516

4.A.2 Land converted to Forest Land –

Carbon stock change, grassland

converted to forest land

CO2 -0.17 -276.7873533 15% 0.1500 0.0000 0.0160 0.0160 0.0000 0.0034 1.15391E-05

4.A.2 Land Converted to Forest Land –

grassland converted to forest land, carbon stock change, dead wood

CO2 -1.73 -68.69365758 9% 0.0900 0.0000 0.0039 0.0040 0.0000 0.0005 2.55868E-07

4.A.2 Land Converted to Forest Land – grassland converted to forest land,

carbon stock change, litter

CO2 -1.53 -60.602861 9% 0.0900 0.0000 0.0035 0.0035 0.0000 0.0004 1.99145E-07

4.A.2 Land converted to Forest Land –

grassland converted to forest land,

Drained organic soil

CO2 3.36 37.895 72% 111% 1.3231 0.0000 0.0021 0.0022 0.0023 0.0022 1.02703E-05

4.A.1 Forest land remaining forest land

- Controlled burning

CO2 256.18 83.34388 92% 6% 0.9220 0.0001 0.0044 0.0048 0.0003 0.0063 3.94269E-05



CH4 25.2045 8.2 92% 36% 0.9879 0.0000 0.0004 0.0005 0.0002 0.0006 4.0537E-07



N2O 2.95616 0.96254 92% 0.9200 0.0000 0.0001 0.0001 0.0000 0.0001 5.24942E-09


- wildf ires

CH4 2.466906545 3.018876526 37% 36% 0.5162 0.0000 0.0001 0.0002 0.0000 0.0001 9.30521E-09


- wildf ires

N2O 0.289234682 0.3539509 37% 0.3700 0.0000 0.0000 0.0000 0.0000 0.0000 1.14812E-10

4.A.1. Forest land, Emissions and

removals from drainage and rewetting

and other management of organic and

mineral soils

CO2 0 18.39 72% 25% 0.7622 0.0000 0.0011 0.0011 0.0003 0.0011 1.24436E-06


440


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions

4.A.1. Forest land, Emissions and removals from drainage and rewetting


mineral soils

CH4 56.17169761 130.5862744 7% 102% 1.0224 0.0002 0.0055 0.0076 0.0056 0.0007 3.23831E-05

4.A.1. Forest land, Emissions and

removals from drainage and rewetting


mineral soils

N2O 567.8831994 590.0496563 7% 187% 1.8713 0.0105 0.0137 0.0341 0.0256 0.0034 0.000664769

4.B.1 Cropland remaining Cropland –


CO2 -6.134341743 -8.205353949 350% 3.5000 0.0000 0.0003 0.0005 0.0000 0.0023 5.52114E-06

4.B.1 Cropland remaining Cropland – Carbon stock change – dead organic

matter

CO2 -1.368079328 -1.339381629 3% 0.0300 0.0000 0.0000 0.0001 0.0000 0.0000 1.08081E-11

4.B.1 Cropland remaining Cropland –


CO2 2761.36609 2576.809411 13% 90% 0.9093 0.0474 0.0495 0.1491 0.0445 0.0274 0.002735492

4.B.2 Land converted to Cropland –

Carbon stock change, forest land

converted to cropland

CO2 364.39865 0 45% 0.4500 0.0000 0.0131 0.0000 0.0000 0.0000 0



CO2 111.6529333 0 32% 0.3200 0.0000 0.0040 0.0000 0.0000 0.0000 0


Mineral soil

CO2 6.98223392 48.54695124 32% 0.3200 0.0000 0.0026 0.0028 0.0000 0.0013 1.61555E-06



CO2 12.166 85.162 130% 90% 1.5811 0.0002 0.0045 0.0049 0.0040 0.0091 9.83686E-05

4.B. Cropland remaining cropland, Emissions and removals from drainage

and rewetting and other management

of organic and mineral soils

CH4 125.0939765 117.6632261 13% 71% 0.7218 0.0001 0.0023 0.0068 0.0016 0.0013 4.2316E-06


441


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions

4.B.2 Land converted to cropland, Direct nitrous oxide (N2O) emissions

from nitrogen (N)

mineralization/immobilization

associated with loss/gain of soil organic matter resulting from change of land

use or management of mineral soils

N2O 3.15132616 22.5734702 131% 73% 1.4997 0.0000 0.0012 0.0013 0.0009 0.0024 6.61149E-06

4.C.1 Grassland remaining Grassland – Carbon stock change – living biomass

CO2 -19.17968712 -41.72134122 61% 0.6100 0.0000 0.0017 0.0024 0.0000 0.0021 4.33585E-06


Carbon stock change – dead organic

matter

CO2 -4.28449168 -8.708601291 5% 0.0500 0.0000 0.0003 0.0005 0.0000 0.0000 1.26921E-09



CO2 874.7530284 651.3619279 23% 90% 0.9289 0.0032 0.0062 0.0377 0.0055 0.0123 0.000180974

4.C.2 Land converted to Grassland –Mineral soil

CO2 -0.003061255 -560.4792382 11% 0.1100 0.0000 0.0324 0.0324 0.0000 0.0050 2.5445E-05

4.C.2 Land converted to Grassland –


CO2 0.000861458 147.8708275 52% 90% 1.0394 0.0002 0.0086 0.0086 0.0077 0.0063 9.88603E-05

4.C. Grassland, Emissions and removals from drainage and rewetting


mineral soils

CH4 66.19807613 60.48292143 6% 60% 0.6030 0.0000 0.0011 0.0035 0.0007 0.0003 5.3469E-07

4.C.1 Grassland remaining Grassland,

wildf ires

CH4 0.049609866 0.168426759 10% 39% 0.4026 0.0000 0.0000 0.0000 0.0000 0.0000 1.15278E-11

4.C.1 Grassland remaining Grassland,

wildf ires

N2O 0.05399279 0.183306897 10% 48% 0.4903 0.0000 0.0000 0.0000 0.0000 0.0000 1.95261E-11

4.C.2. Lands converted to grasslands,

Direct nitrous oxide (N2O) emissions

from nitrogen (N)

mineralization/immobilization associated with loss/gain of soil organic

matter resulting from change of land


N2O 0.000147896 25.3866853 68% 37% 0.7741 0.0000 0.0015 0.0015 0.0005 0.0014 2.29024E-06


442


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions


CO2 -65.31052 -161.4256967 224% 2.2400 0.0011 0.0070 0.0093 0.0000 0.0296 0.000875264

4.D.1 Wetlands remaining Wetlands –

Carbon stock change – dead organic

matter

CO2 -13.80987667 -29.95736333 6% 0.0600 0.0000 0.0012 0.0017 0.0000 0.0001 2.16276E-08

4.D.1 Wetlands remaining Wetlands –

Carbon stock change –organic soils

CO2 277.2 277.2 24% 158% 1.5981 0.0017 0.0060 0.0160 0.0096 0.0054 0.000120924

4.D.1. Wetlands, Peat extraction from

lands, organic soils

CO2 1016.928 917.4083375 24% 158% 1.5981 0.0185 0.0164 0.0531 0.0259 0.0180 0.000997718


CH4 28.53444375 28.53444375 24% 80% 0.8352 0.0000 0.0006 0.0017 0.0005 0.0006 5.62029E-07

4.D.1. Wetlands, Peat extraction from

lands, organic soils

N2O 3.793114286 3.793114286 24% 112% 1.1454 0.0000 0.0001 0.0002 0.0001 0.0001 1.41401E-08

4.E.1 Settlements remaining

Settlements – Carbon stock change – living biomass

CO2 -48.28378424 -105.6971782 210% 2.1000 0.0004 0.0044 0.0061 0.0000 0.0182 0.00032981

4.E.1 Settlements remaining

Settlements – Carbon stock change – dead organic matter

CO2 -6.108421479 -10.78459125 8% 0.0800 0.0000 0.0004 0.0006 0.0000 0.0001 4.98293E-09

4.E.1 Settlements remaining Settlements – Drained organic soils

CO2 0 15.32483431 8% 90% 0.9035 0.0000 0.0009 0.0009 0.0008 0.0001 6.46776E-07

4.E.2 Land converted to Set tlements –


CO2 113.1222033 594.71159 169% 1.6900 0.0087 0.0303 0.0344 0.0000 0.0822 0.006762138



CO2 45.01128341 238.3274994 21% 0.2100 0.0000 0.0122 0.0138 0.0000 0.0041 1.67681E-05


Mineral soils

CO2 1.399567031 100.4322263 21% 0.2100 0.0000 0.0058 0.0058 0.0000 0.0017 2.97771E-06

4.E.2 Land converted to Set tlements – Organic soils

CO2 3.765666667 173.7967198 62% 90% 1.0929 0.0003 0.0099 0.0101 0.0089 0.0088 0.000157421


443


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions

4.E.2 Lands converted to settlements, Direct nitrous oxide (N2O) emissions

from nitrogen (N)

mineralization/immobilization

associated with loss/gain of soil organic matter resulting from change of land


N2O 0.910566118 49.34129338 87% 70% 1.1166 0.0000 0.0028 0.0029 0.0020 0.0035 1.62371E-05

4.E.2 Settlements remaining Settlements, Direct nitrous oxide (N2O)

emissions from nitrogen (N)

mineralization/immobilization associated with loss/gain of soil organic

matter resulting from change of land


N2O 3.2207095 0.0000 0.0000 0.0002 0.0002 0.0000 0.0000 0

4. G. Harvested wood products CO2 -166.3561979 -2141.522557 15% 0% 0.1500 0.0009 0.1179 0.1239 0.0000 0.0263 0.000690758

4 (IV) Indirect nitrous oxide (N2O)

emissions from managed soils

N2O 0.16057137 2.97600236 0.0000 0.0000 0.0002 0.0002 0.0000 0.0000 0

5.A.1. Managed Waste Disposal on Land

CH4 0 186.6154068 20% 52% 0.5571 0.0001 0.0108 0.0108 0.0056 0.0031 4.08439E-05

5.A.2. Unmanaged Waste Disposal

Sites

CH4 392.8311633 346.2876433 20% 52% 0.5571 0.0003 0.0059 0.0200 0.0031 0.0057 4.14497E-05

5.B.1. Composting CH4 0 1.4367 20% 100% 1.0198 0.0000 0.0001 0.0001 0.0001 0.0000 7.46146E-09

5.B.1. Composting N2O 0 1.2844098 20% 90% 0.9220 0.0000 0.0001 0.0001 0.0001 0.0000 4.91434E-09

5.C.1 Waste Incineration CO2 0.810707594 0.4274336 20% 40% 0.4472 0.0000 0.0000 0.0000 0.0000 0.0000 5.21391E-11

5.C.1 Waste Incineration N2O 4.847024532 4.313387888 20% 100% 1.0198 0.0000 0.0001 0.0002 0.0001 0.0001 1.05898E-08

5.D.1 Domestic Wastewater CH4 222.8 64.8 10% 30% 0.3162 0.0000 0.0043 0.0037 0.0013 0.0005 1.92899E-06

5.D.1 Domestic Wastewater N2O 3.929726 6.612322 10% 30% 0.3162 0.0000 0.0002 0.0004 0.0001 0.0001 8.1517E-09

5.D.2 Industrial Wastewater CH4 137.025 137.625 2% 30% 0.3007 0.0000 0.0030 0.0080 0.0009 0.0002 8.73881E-07

5.D.2 Industrial Wastewater N2O 2.341428614 0.141334546 10% 30% 0.3162 0.0000 0.0001 0.0000 0.0000 0.0000 5.23857E-10

Total 17284.8695 10765.9488 0.2982 0.0285


444


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in

national emissions

introduced by


parameter

uncertainty




Uncertainty

introduced


national

emissions

Total Uncertainties Uncertainty in total

inventory %:

55% Trend uncertainty %: 17%

A.2.2 Approach 1 uncertainty analysis for year 2013 (excluding LULUCF)



Year 2013


Activity

data uncertainty

Emission

factor / estimation

parameter

uncertainty

Combined

uncertainty

Contribution

to variance by category in

year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national emissions

introduced by

emission factor /


uncertainty

Uncertainty in trend in

national emissions introduced by activit y

data uncertainty

Uncertainty

introduced into the trend in

total national

emissions


CO2 3049.621305 15.86030086 2% 10% 0.1020 0.0000 0.0479 0.0006 0.0048 0.0000 2.29276E-05

1.A.1.a Public Electricity and

Heat Production - Solid Fuels

CO2 218.053 40.1104 2% 20% 0.2010 0.0000 0.0019 0.0015 0.0004 0.0000 1.5226E-07


Heat Production - Gaseous Fuels

CO2 2644.318679 1789.305004 2% 5% 0.0539 0.0001 0.0262 0.0683 0.0013 0.0019 5.45393E-06


CO2 142.826737 4.15465786 2% 15% 0.1513 0.0000 0.0021 0.0002 0.0003 0.0000 1.00642E-07


Heat Production - Other fossil

fuels

CO2 3.0786 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 9.60601E-11


Heat Production - Liquid Fuels

CH4 3.00505 0.015625 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 5.57849E-10


CH4 0.057625 0.0106 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.57833E-14


445


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national

emissions introduced by

emission factor /


uncertainty


national emissions

introduced by activit y data uncertainty

Uncertainty

introduced into

the trend in total national

emissions


CH4 1.20535 0.824925 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.87255E-11


Heat Production - Biomass Fuels

CH4 0.327 6.940298662 5% 50% 0.5025 0.0000 0.0003 0.0003 0.0001 0.0000 1.72317E-08


Heat Production - Peat

CH4 0.034425 0.001 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.49718E-14

1.A.1.a Public Electricity and Heat Production - Other fossil

fuels

CH4 0.0315 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.28548E-14


N2O 7.1626684 0.0371308 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0001 0.0000 3.16953E-09


Heat Production - Solid Fuels

N2O 1.030335 0.189528 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.10305E-11


Heat Production - Gaseous Fuels

N2O 1.4367772 0.9833106 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 5.50236E-11


N2O 0.519712 11.01384 5% 50% 0.5025 0.0000 0.0004 0.0004 0.0002 0.0000 4.33935E-08


Heat Production - Peat

N2O 0.615519 0.01788 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.07711E-11


Heat Production - Other fossil fuels

N2O 0.050064 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.5877E-13

1.A.1.c Manufacture of Solid

Fuels and Other Energy Industries - Liquid Fuels

CO2 24.7792529 18.87025524 2% 10% 0.1020 0.0000 0.0003 0.0007 0.0000 0.0000 1.47975E-09

1.A.1.c Manufacture of Solid Fuels and Other Energy

Industries - Solid Fuels

CO2 0 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 0


Industries - Gaseous Fuels

CO2 44.69904433 50.37622658 2% 5% 0.0539 0.0000 0.0012 0.0019 0.0001 0.0001 6.63569E-09


446


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions


Industries - Peat

CO2 73.83865681 0 2% 10% 0.1020 0.0000 0.0012 0.0000 0.0001 0.0000 1.3814E-08


Industries - Liquid Fuels

CH4 0.02314 0.019125 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.31977E-14


Fuels and Other Energy

Industries - Solid Fuels

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0




CH4 0.020375 0.023225 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 7.97732E-14



Industries - Biomass Fuels

CH4 0 0.222 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 1.833E-11



Industries - Peat

CH4 0.0177725 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.00085E-14


Fuels and Other Energy Industries - Liquid Fuels

N2O 0.05379496 0.045594 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.98214E-13


Fuels and Other Energy Industries - Solid Fuels

N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0



N2O 0.024287 0.0276842 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.13347E-13


Industries - Biomass Fuels

N2O 0 0.352832 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 4.63012E-11



Industries - Peat

N2O 0.3177723 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.39661E-12

1.A.2.a Iron and Steel - Liquid CO2 93.25228881 0 2% 10% 0.1020 0.0000 0.0015 0.0000 0.0001 0.0000 2.20326E-08


447


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions

Fuels

1.A.2.a Iron and Steel - Solid

Fuels

CO2 5.671 8.7096 2% 20% 0.2010 0.0000 0.0002 0.0003 0.0000 0.0000 2.43794E-09


CO2 234.4643123 29.87868767 2% 5% 0.0539 0.0000 0.0026 0.0011 0.0001 0.0000 1.78234E-08


CO2 0 0 5% 10% 0.1118 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.a Iron and Steel - Peat CO2 0 0 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.a Iron and Steel - Other

fossil fuels

CO2 61.3521 0 2% 20% 0.2010 0.0000 0.0010 0.0000 0.0002 0.0000 3.81484E-08

1.A.2.a Iron and Steel - Liquid Fuels

CH4 0.091425 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 5.29478E-13

1.A.2.a Iron and Steel - Solid Fuels

CH4 0.001325 0.0021 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 8.78619E-16

1.A.2.a Iron and Steel - Gaseous

Fuels

CH4 0.106875 0.013775 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.45472E-13

1.A.2.a Iron and Steel - Biomass

Fuels

CH4 0 0 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.a Iron and Steel - Peat CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


fossil fuels

CH4 0.62775 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.49627E-11

1.A.2.a Iron and Steel - Liquid

Fuels

N2O 0.2179572 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.00926E-12

1.A.2.a Iron and Steel - Solid

Fuels

N2O 0.023691 0.037548 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.80889E-13

1.A.2.a Iron and Steel - Gaseous

Fuels

N2O 0.127395 0.0164198 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.90868E-13

1.A.2.a Iron and Steel - Biomass

Fuels

N2O 0 0 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 0


448


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions

1.A.2.a Iron and Steel - Peat N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


fossil fuels

N2O 0.997704 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.30552E-11


CO2 0 0 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 0


CO2 0 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 0


Gaseous Fuels

CO2 0 7.483228491 2% 5% 0.0539 0.0000 0.0003 0.0003 0.0000 0.0000 2.6953E-10


Biomass Fuels

CO2 0 0 5% 10% 0.1118 0.0000 0.0000 0.0000 0.0000 0.0000 0


Peat

CO2 0 0 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 0


Liquid Fuels

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Solid Fuels

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Gaseous Fuels

CH4 0 0.00345 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.35393E-15


CH4 0 0 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.b Non-Ferrous Metals - Peat

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Liquid Fuels

N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Solid Fuels

N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Gaseous Fuels

N2O 0 0.0041124 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.18634E-15


Biomass Fuels

N2O 0 0 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 0


449


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions

1.A.2.b Non-Ferrous Metals - Peat

N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.c Chemicals - Liquid Fuels CO2 276.6786727 8.55381336 2% 10% 0.1020 0.0000 0.0041 0.0003 0.0004 0.0000 1.6631E-07

1.A.2.c Chemicals - Gaseous Fuels

CO2 23.42449305 20.87712296 2% 5% 0.0539 0.0000 0.0004 0.0008 0.0000 0.0000 9.58933E-10

1.A.2.c Chemicals - Peat CO2 0 2.07732893 2% 10% 0.1020 0.0000 0.0001 0.0001 0.0000 0.0000 6.79751E-11

1.A.2.c Chemicals - Liquid Fuels CH4 0.273195 0.003425 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.44772E-12

1.A.2.c Chemicals - Gaseous

Fuels

CH4 0.0106775 0.009625 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 9.87162E-15

1.A.2.c Chemicals - Biomass

Fuels

CH4 0 0.157344085 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 9.20782E-12

1.A.2.c Chemicals - Peat CH4 0 0.001 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.658E-16

1.A.2.c Chemicals - Liquid Fuels N2O 0.65129688 0.0040826 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.60683E-11

1.A.2.c Chemicals - Gaseous Fuels

N2O 0.01272758 0.011473 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.40262E-14

1.A.2.c Chemicals - Biomass Fuels

N2O 0 0.24953815 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 2.31595E-11

1.A.2.c Chemicals - Peat N2O 0 0.00894 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.9236E-14


CO2 15.54739345 0 2% 10% 0.1020 0.0000 0.0002 0.0000 0.0000 0.0000 6.12474E-10


CO2 2.692316 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 7.34664E-11


Gaseous Fuels

CO2 149.4154681 5.585308222 2% 5% 0.0539 0.0000 0.0022 0.0002 0.0001 0.0000 1.17541E-08


Peat

CO2 0 0 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 0


Liquid Fuels

CH4 0.015225 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.46836E-14


450


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions


CH4 0.0007115 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.20676E-17


Gaseous Fuels

CH4 0.0681075 0.002575 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.42956E-13


Biomass Fuels

CH4 0 0.07275 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 1.96844E-12


Peat

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Liquid Fuels

N2O 0.0362964 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 8.34535E-14


Solid Fuels

N2O 0.01272162 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.02519E-14


N2O 0.08118414 0.0030694 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.45207E-13


N2O 0 0.115624 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 4.97224E-12


Peat

N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.e Food Processing,

Beverages and Tobacco - Liquid Fuels

CO2 798.2058686 33.22587 2% 11% 0.1131 0.0000 0.0114 0.0013 0.0013 0.0000 1.62065E-06


Beverages and Tobacco - Solid Fuels

CO2 103.071464 2.365 2% 20% 0.2010 0.0000 0.0016 0.0001 0.0003 0.0000 9.6145E-08

1.A.2.e Food Processing, Beverages and Tobacco - Gaseous

Fuels

CO2 174.2220665 98.04113849 2% 5% 0.0539 0.0000 0.0010 0.0037 0.0000 0.0001 1.35724E-08


CO2 0 0 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 0


Beverages and Tobacco - Other

Fossil Fuels

CO2 0 2.1257 2% 20% 0.2010 0.0000 0.0001 0.0001 0.0000 0.0000 2.68893E-10


451


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions

1.A.2.e Food Processing, Beverages and Tobacco - Liquid

Fuels

CH4 0.78871 0.026525 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.33034E-11

1.A.2.e Food Processing, Beverages and Tobacco - Solid

Fuels

CH4 0.026721 0.000625 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.02962E-14


Beverages and Tobacco - Gaseous

Fuels

CH4 0.079415 0.0452 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 5.57661E-14


Beverages and Tobacco - Biomass

Fuels

CH4 0.171 0.336825 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 2.65404E-11


Beverages and Tobacco - Peat

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Beverages and Tobacco - Other Fossil Fuels

CH4 0 0.02175 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.73046E-13

1.A.2.e Food Processing, Beverages and Tobacco - Liquid

Fuels

N2O 1.87891384 0.057812 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.91836E-10

1.A.2.e Food Processing, Beverages and Tobacco - Solid

Fuels

N2O 0.47777148 0.011175 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.28825E-11


Beverages and Tobacco - Gaseous

Fuels

N2O 0.09466268 0.0538784 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 7.9236E-14


Beverages and Tobacco - Biomass

Fuels

N2O 0.271776 0.5352974 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 6.70312E-11


Beverages and Tobacco - Peat

N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Beverages and Tobacco - Other Fossil Fuels

N2O 0 0.034568 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.37111E-13


452


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions


CO2 273.5769252 21.97829728 2% 10% 0.1020 0.0000 0.0035 0.0008 0.0004 0.0000 1.24121E-07


Solid Fuels

CO2 16.4292 122.8854 2% 20% 0.2010 0.0000 0.0044 0.0047 0.0009 0.0001 8.0316E-07


Gaseous Fuels

CO2 314.4838285 72.88013835 2% 5% 0.0539 0.0000 0.0022 0.0028 0.0001 0.0001 1.85447E-08


Peat

CO2 0 0 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 0


Other Fossil Fuels

CO2 0 92.50516 2% 2% 0.0283 0.0000 0.0035 0.0035 0.0001 0.0001 1.49771E-08


Liquid Fuels

CH4 0.268845 0.022275 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.93971E-12


CH4 0.00425 0.032475 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.44974E-13


CH4 0.14335 0.0336 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.50637E-13


Biomass Fuels

CH4 0.00525 0.66454334 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 1.6319E-10


Peat

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Other Fossil Fuels

CH4 0 0.814736505 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.42816E-10


Liquid Fuels

N2O 0.64092648 0.0531036 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.67077E-11


Solid Fuels

N2O 0.07599 0.580653 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.10286E-10


Gaseous Fuels

N2O 0.1708732 0.0400512 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.56121E-13


N2O 0.008344 1.056180881 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 4.12215E-10

1.A.2.f Non-metallic Minerals - N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


453


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions

Peat


Other Fossil Fuels

N2O 0 1.294887885 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.13349E-10

1.A.2.g Other - Liquid Fuels CO2 795.7039841 122.1484903 2% 10% 0.1020 0.0000 0.0080 0.0047 0.0008 0.0001 6.57194E-07

1.A.2.g Other - Solid Fuels CO2 27.263264 4.73 2% 20% 0.2010 0.0000 0.0003 0.0002 0.0001 0.0000 2.59319E-09

1.A.2.g Other - Gaseous Fuels CO2 524.168965 104.6567463 2% 5% 0.0539 0.0000 0.0043 0.0040 0.0002 0.0001 5.99983E-08

1.A.2.g Other - Peat CO2 0 0.39 2% 10% 0.1020 0.0000 0.0000 0.0000 0.0000 0.0000 2.3959E-12

1.A.2.g Other - Other Fossil Fuels CO2 0 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.g Other - Liquid Fuels CH4 2.26531 0.194025 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.05239E-10

1.A.2.g Other - Solid Fuels CH4 0.006946 0.00125 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 9.88665E-16

1.A.2.g Other - Gaseous Fuels CH4 0.23893 0.04825 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 9.63693E-13

1.A.2.g Other - Biomass Fuels CH4 0.2865 9.58215 5% 50% 0.5025 0.0000 0.0004 0.0004 0.0002 0.0000 3.332E-08

1.A.2.g Other - Peat CH4 0 0.0001 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.65799E-18

1.A.2.g Other - Other Fossil Fuels CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.2.g Other - Liquid Fuels N2O 2.149772 0.297218048 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.30852E-10

1.A.2.g Other - Solid Fuels N2O 0.12419448 0.02235 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.16071E-13

1.A.2.g Other - Gaseous Fuels N2O 0.28480456 0.057514 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.36928E-12

1.A.2.g Other - Biomass Fuels N2O 0.455344 15.2293496 5% 50% 0.5025 0.0000 0.0006 0.0006 0.0003 0.0000 8.41671E-08

1.A.2.g Other - Peat N2O 0 0.001788 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.16944E-15

1.A.2.g Other - Other Fossil Fuels N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.3.a Domestic Aviation -

Aviation Gasoline

CO2 0.011005031 0.28 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.77497E-11


kerosene

CO2 0.054819072 3.107107044 2% 50% 0.5004 0.0000 0.0001 0.0001 0.0001 0.0000 3.47989E-09


454


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions


CH4 1.96519E-06 0.00005 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 8.84878E-19


kerosene

CH4 0.000009504 0.00355575 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.61467E-15

1.A.3.a Domestic Aviation -

Aviation Gasoline

N2O 9.36998E-05 0.002384 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.01166E-15


kerosene

N2O 0.000453151 0.028884544 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.01227E-13


Gasoline

CO2 1723.750448 625.9575 2% 50% 0.5004 0.0008 0.0035 0.0239 0.0018 0.0007 3.57345E-06


Diesel Oil

CO2 616.1359677 1741.886302 2% 50% 0.5004 0.0064 0.0567 0.0665 0.0284 0.0019 0.000807345

1.A.3.b Road Transportation - LPG

CO2 36.95737306 147.8567316 2% 50% 0.5004 0.0000 0.0051 0.0056 0.0025 0.0002 6.42235E-06


CO2 3.4629 4.33188 10% 50% 0.5099 0.0000 0.0001 0.0002 0.0001 0.0000 3.58974E-09


Gaseous Fuels

CO2 17.6165255 0 2% 50% 0.5004 0.0000 0.0003 0.0000 0.0001 0.0000 1.96586E-08


Gasoline

CH4 17.15516309 2.455797158 2% 50% 0.5004 0.0000 0.0002 0.0001 0.0001 0.0000 8.04293E-09


Diesel Oil

CH4 1.108041461 1.116917573 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.57931E-10


LPG

CH4 0.124565463 0.801443483 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.05595E-10


Lubricants

CH4 0.02475 0.01425 10% 50% 0.5099 0.0000 0.0000 0.0000 0.0000 0.0000 1.1567E-14


Gaseous Fuels

CH4 0.7015 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.11726E-11


CH4 0 0.020267227 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.50256E-13

1.A.3.b Road Transportation - N2O 13.07410741 4.586290942 2% 50% 0.5004 0.0000 0.0000 0.0002 0.0000 0.0000 2.96131E-10


455


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions

Gasoline


Diesel Oil

N2O 5.593827044 13.09045627 2% 50% 0.5004 0.0000 0.0004 0.0005 0.0002 0.0000 4.24077E-08

1.A.3.b Road Transportation - LPG

N2O 0.163685304 2.463208388 2% 50% 0.5004 0.0000 0.0001 0.0001 0.0000 0.0000 2.09859E-09


N2O 0.02384 0.03278 10% 50% 0.5099 0.0000 0.0000 0.0000 0.0000 0.0000 2.21618E-13


Gaseous Fuels

N2O 0.27267 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.70969E-12


Biomass

N2O 0 0.307472263 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.45824E-11

1.A.3.c Railways - Liquid Fuels CO2 531.37994 223.258 2% 5% 0.0539 0.0000 0.0001 0.0085 0.0000 0.0002 5.81709E-08

1.A.3.c Railways - Liquid Fuels CH4 0.745009038 0.31799375 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.38345E-13

1.A.3.c. Railway Biomass Fuels CH4 0 0.00132 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.37369E-16

1.A.3.c Railways - Liquid Fuels N2O 61.20060747 26.122382 2% 50% 0.5004 0.0000 0.0000 0.0010 0.0000 0.0000 9.33577E-10

1.A.3.c. Railway Biomass Fuels N2O 0 0.0200256 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.46695E-13


Gasoline

CO2 0.172771761 0.2772 20% 5% 0.2062 0.0000 0.0000 0.0000 0.0000 0.0000 9.11938E-12


CO2 0.8332289 25.16 2% 5% 0.0539 0.0000 0.0009 0.0010 0.0000 0.0000 2.98357E-09


CH4 0.00295205 0.004739595 20% 50% 0.5385 0.0000 0.0000 0.0000 0.0000 0.0000 7.11132E-15


Diesel Oil

CH4 0.001126 0.034 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.11308E-13


Gasoline

N2O 0.000219506 0.000352182 20% 50% 0.5385 0.0000 0.0000 0.0000 0.0000 0.0000 3.92528E-17


Diesel Oil

N2O 0.1006644 3.0396 2% 50% 0.5004 0.0000 0.0001 0.0001 0.0001 0.0000 3.28732E-09


456


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions


Liquid Fuels

CO2 1007.294341 142.1295097 2% 10% 0.1020 0.0000 0.0106 0.0054 0.0011 0.0002 1.1476E-06


Fuels

CO2 1410.784936 49.0974 2% 20% 0.2010 0.0000 0.0206 0.0019 0.0041 0.0001 1.6929E-05

1.A.4.a

Commercial/Institutional -

Gaseous Fuels

CO2 274.4466477 242.7711156 2% 5% 0.0539 0.0000 0.0049 0.0093 0.0002 0.0003 1.28855E-07

1.A.4.a

Commercial/Institutional - Peat

CO2 66.54499789 0 2% 10% 0.1020 0.0000 0.0011 0.0000 0.0001 0.0000 1.12198E-08

1.A.4.a

Commercial/Institutional - Other

Fossil Fuels

CO2 0 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.4.a


Liquid Fuels

CH4 3.495 0.74775 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.83934E-10

1.A.4.a

Commercial/Institutional - Solid

Fuels

CH4 3.72829 0.12975 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0000 0.0000 7.39632E-10

1.A.4.a


Gaseous Fuels

CH4 0.6255 0.559625 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.29453E-11

1.A.4.a

Commercial/Institutional - Biomass Fuels

CH4 39.135 39.52177273 5% 50% 0.5025 0.0000 0.0009 0.0015 0.0004 0.0001 2.07817E-07

1.A.4.a


CH4 0.168 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.78787E-12

1.A.4.a

Commercial/Institutional - Other Fossil Fuels

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.4.a

Commercial/Institutional - Liquid Fuels

N2O 2.411706848 0.358718096 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.52547E-10


457


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions


Fuels

N2O 6.66618252 0.231993 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0000 0.0000 2.36456E-09


Gaseous Fuels

N2O 0.1491192 0.1334146 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.87243E-12

1.A.4.a


Biomass Fuels

N2O 6.219856 6.292871419 5% 50% 0.5025 0.0000 0.0001 0.0002 0.0001 0.0000 5.28171E-09

1.A.4.a


N2O 0.2955862 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 5.53459E-12

1.A.4.a

Commercial/Institutional - Other

Fossil Fuels

N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.4.b Residential - Liquid

Fuels

CO2 329.9110639 154.26032 2% 10% 0.1020 0.0000 0.0006 0.0059 0.0001 0.0002 3.18583E-08

1.A.4.b Residential - Solid Fuels CO2 605.8184 50.138 2% 20% 0.2010 0.0000 0.0077 0.0019 0.0015 0.0001 2.39109E-06

1.A.4.b Residential - Gaseous

Fuels

CO2 219.6011945 231.3293677 2% 5% 0.0539 0.0000 0.0053 0.0088 0.0003 0.0002 1.33692E-07

1.A.4.b Residential - Peat CO2 42.27150449 0 2% 10% 0.1020 0.0000 0.0007 0.0000 0.0001 0.0000 4.52751E-09

1.A.4.b Residential - Other

Fossil Fuels

CO2 0 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 0


Fuels

CH4 0.868375 1.270375 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.02797E-10

1.A.4.b Residential - Solid Fuels CH4 48.03 3.975 2% 50% 0.5004 0.0000 0.0006 0.0002 0.0003 0.0000 9.38757E-08

1.A.4.b Residential - Gaseous

Fuels

CH4 0.5005 0.53325 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.87609E-11

1.A.4.b Residential - Biomass

Fuels

CH4 150.075 181.2375 10% 50% 0.5099 0.0001 0.0045 0.0069 0.0023 0.0010 6.09391E-06

1.A.4.b Residential - Peat CH4 3.1875 0 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0000 0.0000 6.43601E-10


458


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions


CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Fuels

N2O 0.4500694 0.343223288 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 8.96945E-12

1.A.4.b Residential - Solid Fuels N2O 2.862588 0.23691 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.33473E-10

1.A.4.b Residential - Gaseous Fuels

N2O 0.1193192 0.1271268 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.20296E-12

1.A.4.b Residential - Biomass

Fuels

N2O 23.85192 28.75998 10% 50% 0.5099 0.0000 0.0007 0.0011 0.0004 0.0002 1.53254E-07

1.A.4.b Residential - Peat N2O 0.1860712 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 2.19319E-12


N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0


Liquid Fuels

CO2 695.0757089 317.4303672 2% 11% 0.1088 0.0000 0.0011 0.0121 0.0001 0.0003 1.30373E-07


Solid Fuels

CO2 102.28152 2.4596 2% 50% 0.5004 0.0000 0.0015 0.0001 0.0008 0.0000 5.88392E-07

1.A.4.c

Agriculture/Forestry/Fisheries -

Gaseous Fuels

CO2 778.5312078 57.80522878 2% 50% 0.5004 0.0000 0.0102 0.0022 0.0051 0.0001 2.59223E-05

1.A.4.c


Peat

CO2 3.0225 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 5.78694E-10

1.A.4.c


Other Fossil Fuels

CO2 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.4.c


Liquid Fuels

CH4 5.99375 1.250225 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 5.69728E-10

1.A.4.c


CH4 8.109 0.195 2% 50% 0.5004 0.0000 0.0001 0.0000 0.0001 0.0000 3.6986E-09


459


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions

Solid Fuels

1.A.4.c


Gaseous Fuels

CH4 1.774375 0.13325 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.34066E-10

1.A.4.c


Biomass Fuels

CH4 9.15 3.627804811 5% 50% 0.5025 0.0000 0.0000 0.0001 0.0000 0.0000 1.08585E-10

1.A.4.c


Peat

CH4 0.2325 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.42423E-12

1.A.4.c

Agriculture/Forestry/Fisheries - Other Fossil Fuels

CH4 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.4.c

Agriculture/Forestry/Fisheries - Liquid Fuels

N2O 2.908143856 0.911925296 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 3.38306E-11


Solid Fuels

N2O 0.4832964 0.011622 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.31381E-11


Gaseous Fuels

N2O 0.423011 0.0317668 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 7.61959E-12

1.A.4.c


Biomass Fuels

N2O 1.45424 0.588801467 5% 50% 0.5025 0.0000 0.0000 0.0000 0.0000 0.0000 2.63778E-12

1.A.4.c


Peat

N2O 0.013857 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.21634E-14

1.A.4.c


Other Fossil Fuels

N2O 0 0 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 0

1.A.5.b Mobile - Liquid Fuels CO2 0 6.447874167 2% 50% 0.5004 0.0000 0.0002 0.0002 0.0001 0.0000 1.52081E-08


460


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions

1.A.5.b Mobile - Liquid Fuels CH4 0 0.011410463 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 4.76266E-14

1.A.5.b Mobile - Liquid Fuels N2O 0 0.052371989 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 1.00332E-12

1.B.2.b Natural Gas CO2 0.008686 0.006516 31% 1% 0.3117 0.0000 0.0000 0.0000 0.0000 0.0000 1.2019E-14

1.B.2.b Natural Gas CH4 177.238 82.3568 31% 1% 0.3117 0.0000 0.0003 0.0031 0.0000 0.0014 1.91983E-06

1.B.2.c Venting and Flaring CO2 0.00 0.001476 10% 1% 0.1005 0.0000 0.0000 0.0000 0.0000 0.0000 6.35641E-17

1.B.2.c Venting and Flaring CH4 70.344325 18.642 10% 1% 0.1005 0.0000 0.0004 0.0007 0.0000 0.0001 1.01541E-08

2.A.1. Cement Production CO2 370.8039966 537.6437303 10% 5% 0.1118 0.0000 0.0146 0.0205 0.0007 0.0029 8.96706E-06

2.A.2. Lime Production CO2 148.8573814 0.274894634 2% 50% 0.5004 0.0000 0.0024 0.0000 0.0012 0.0000 1.39108E-06

2.A.3. Glass production CO2 0.352 2.976908 2% 60% 0.6003 0.0000 0.0001 0.0001 0.0001 0.0000 4.21616E-09


CO2 69.184752 9.050385865 2% 50% 0.5004 0.0000 0.0008 0.0003 0.0004 0.0000 1.42837E-07

2.C.1 Iron and Steel Production CO2 12.81611267 0.955378707 5% 25% 0.2550 0.0000 0.0002 0.0000 0.0000 0.0000 1.76058E-09

2.C.1 Iron and Steel Production CH4 0.06875 0.02414875 10% 25% 0.2693 0.0000 0.0000 0.0000 0.0000 0.0000 1.88625E-14

2.D.1 Lubricant Use CO2 0.571307104 0.3071332 2% 25% 0.2508 0.0000 0.0000 0.0000 0.0000 0.0000 5.44205E-13

2.D.2 Paraff in wax use CO2 0 0.132 2% 50% 0.5004 0.0000 0.0000 0.0000 0.0000 0.0000 6.37369E-12

2.D.3.b Road paving with asphalt CO2 0.001463305 0.052980255 20% 60% 0.6325 0.0000 0.0000 0.0000 0.0000 0.0000 1.76761E-12

2.D.3.c Asphalt roofing CO2 0.002972338 0.047829397 20% 60% 0.6325 0.0000 0.0000 0.0000 0.0000 0.0000 1.40669E-12

2.D.3. Solvent Use CO2 0 0 2% 20% 0.2010 0.0000 0.0000 0.0000 0.0000 0.0000 0

2.D.3.d Urea Use CO2 0 0.537788082 20% 10% 0.2236 0.0000 0.0000 0.0000 0.0000 0.0000 3.79648E-11


conditioning

HFCs 0.00 102.8615524 75% 75% 1.0607 0.0001 0.0039 0.0039 0.0029 0.0042 2.60415E-05

2.F.2 Foam blowing agents HFCs 0.00 0.00 75% 75% 1.0607 0.0000 0.0000 0.0000 0.0000 0.0000 5.02742E-15

2.F.3. Fire Protection HFCs 0.00 0.2369598 75% 75% 1.0607 0.0000 0.0000 0.0000 0.0000 0.0000 1.382E-10

2.F.4. Aerosols HFCs 0.00 3.52216298 75% 75% 1.0607 0.0000 0.0001 0.0001 0.0001 0.0001 3.05336E-08


461


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions

2.G.1. Electrical equipment SF6 0.00 8.50315813 2% 30% 0.3007 0.0000 0.0003 0.0003 0.0001 0.0000 9.57551E-09

2.G.3. N2O from product uses N2O 0.004768 0.005364 2% 2% 0.0283 0.0000 0.0000 0.0000 0.0000 0.0000 4.02245E-17

2.G.4. Other HFCs 0.00 1.835685463 75% 75% 1.0607 0.0000 0.0001 0.0001 0.0001 0.0001 8.29385E-09

3.A.1 Enteric Fermentation - Cattle

CH4 2178.340191 765.2269298 2% 20% 0.2010 0.0002 0.0054 0.0292 0.0011 0.0008 1.86951E-06

3.A.2 Enteric Fermentation -

Sheep

CH4 32.92 16.96 2% 40% 0.4005 0.0000 0.0001 0.0006 0.0000 0.0000 2.78359E-09


Swine

CH4 52.54125 13.78125 2% 40% 0.4005 0.0000 0.0003 0.0005 0.0001 0.0000 1.56006E-08


Other livestock

CH4 18.092 7.542775 2% 40% 0.4005 0.0000 0.0000 0.0003 0.0000 0.0000 6.63856E-11


Cattle

CH4 99.92910799 70.54136894 25% 20% 0.3202 0.0000 0.0011 0.0027 0.0002 0.0010 9.55914E-07


Cattle

N2O 124.5358736 49.48502171 25% 20% 0.3202 0.0000 0.0001 0.0019 0.0000 0.0007 4.46793E-07


CH4 0.78185 0.4028 25% 30% 0.3905 0.0000 0.0000 0.0000 0.0000 0.0000 3.03572E-11


N2O 1.32908 1.03108 25% 30% 0.3905 0.0000 0.0000 0.0000 0.0000 0.0000 2.23707E-10


Swaine

CH4 224.4975 58.4925 25% 30% 0.3905 0.0000 0.0013 0.0022 0.0004 0.0008 7.85272E-07


Swaine

N2O 15.35892 3.60282 25% 30% 0.3905 0.0000 0.0001 0.0001 0.0000 0.0000 3.39479E-09


Other livestock

CH4 83.38555 7.57375 25% 30% 0.3905 0.0000 0.0010 0.0003 0.0003 0.0001 1.07438E-07


Other livestock

N2O 22.04902 9.58666 25% 30% 0.3905 0.0000 0.0000 0.0004 0.0000 0.0001 1.67763E-08

3.B.5 Indirect N2O emissions

from Manure Management

N2O 142.1423263 47.57185732 2% 50% 0.5004 0.0000 0.0004 0.0018 0.0002 0.0001 5.2324E-08


462


emissions or

removals

Year 2013

emissions or

removals

Activity

data

uncertainty

Emission

factor /


uncertainty

Combined

uncertainty

Contribution

to variance by

category in year x

Type A

sensitivity

Type B

sensitivity

Uncertainty in

trend in national


emission factor /


uncertainty


national emissions


Uncertainty

introduced into


emissions


N2O 2183.630811 1240.469649 2% 50% 0.5004 0.0032 0.0126 0.0474 0.0063 0.0013 4.15161E-05

3.G. Liming CO2 371.4186667 13.7756667 2% 50% 0.5004 0.0000 0.0054 0.0005 0.0027 0.0000 7.2508E-06

3.H. Urea Application CO2 7.7088 4.075866667 20% 5% 0.2062 0.0000 0.0000 0.0002 0.0000 0.0000 1.94112E-09

5.A.1. Managed Waste Disposal

on Land

CH4 0 186.6154068 20% 52% 0.5571 0.0001 0.0071 0.0071 0.0037 0.0020 1.77981E-05

5.A.2. Unmanaged Waste

Disposal Sites

CH4 392.8311633 346.2876433 20% 52% 0.5571 0.0003 0.0070 0.0132 0.0036 0.0037 2.71314E-05

5.B.1. Composting CH4 0 1.4367 20% 100% 1.0198 0.0000 0.0001 0.0001 0.0001 0.0000 3.25141E-09

5.B.1. Composting N2O 0 1.2844098 20% 90% 0.9220 0.0000 0.0000 0.0000 0.0000 0.0000 2.14147E-09

5.C.1 Waste Incineration CO2 0.810707594 0.4274336 20% 40% 0.4472 0.0000 0.0000 0.0000 0.0000 0.0000 2.31883E-11

5.C.1 Waste Incineration N2O 4.847024532 4.313387888 20% 100% 1.0198 0.0000 0.0001 0.0002 0.0001 0.0000 9.84051E-09

5.D.1 Domestic Wastewater CH4 222.8 64.8 10% 30% 0.3162 0.0000 0.0011 0.0025 0.0003 0.0003 2.25854E-07

5.D.1 Domestic Wastewater N2O 3.929726 6.612322 10% 30% 0.3162 0.0000 0.0002 0.0003 0.0001 0.0000 4.52359E-09

5.D.2 Industrial Wastewater CH4 137.025 137.625 2% 30% 0.0031

5.D.2 Industrial Wastewater N2O 2.341428614 0.141334546 10% 30% 0.3162 0.0000 0.0000 0.0000 0.0000 0.0000 9.20137E-11

Total 26184.3703 10913.7265 0.0114 0.0010

Total Uncertainties Uncertainty

in total

inventory %:

11% Trend uncertainty %: 3%


463


ANNEX 3: OTHER DETAILED METHODOLOGICAL DESCRIPTIONS FOR INDIVIDUAL SOURCE OR SINK CATEGORIES

A.3.1 Energy (excluding Transport sector)

Sulphur content

Fuel 90-95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13

Diesel 0.200 0.200 0.200 0.200 0.050 0.050 0.050 0.050 0.050 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035

RFO 2.000 2.000 2.122 2.097 2.005 2.078 1.983 1.922 1.972 1.452 1.292 1.030 1.184 0.888 0.613 1.418 1.086 1.100 1.100

Gasoline 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015

Jet fuel 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050

Other liquids 0.551 0.551 0.551 0.564 0.523 0.428 0.417 0.300 0.253 0.215 0.211 0.229 0.268 0.183 0.146 0.146 0.146 0.146 0.146

LPG 0.200 0.200 0.200 0.200 0.150 0.150 0.150 0.014 0.013 0.014 0.013 0.011 0.020 0.020 0.005 0.005 0.005 0.005 0.005

Shale oil 1.000 1.000 1.000 1.000 0.800 0.735 0.834 0.800 0.833 0.850 0.850 0.800 0.825 0.833 0.800 0.800 0.800 0.800 0.800

Coal 1.800 1.800 1.467 1.368 1.064 0.896 0.871 0.729 0.626 0.646 0.726 0.644 0.494 0.318 0.324 0.325 0.374 0.330 0.343

Coke 1.800 1.200 0.600 0.400 0.400 0.400 0.400 0.400 0.400 0.400 0.400 0.400 0.400 0.400 0.400 0.400 0.400 0.400 0.400

Oil shale 0.700

Peat 0.300 0.300 0.280 0.219 0.205 0.237 0.215 0.273 0.265 0.254 0.271 0.245 0.217 0.116 0.210 0.170 0.170 0.170 0.170

SO2 EF (Gg/PJ)

Fuel 90-95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13

Diesel 0.094 0.094 0.094 0.094 0.024 0.024 0.024 0.024 0.024 0.016 0.016 0.016 0.016 0.016 0.016 0.016 0.016 0.016 0.016

RFO 0.966 0.966 1.024 1.012 0.968 1.003 0.957 0.928 0.952 0.701 0.624 0.497 0.572 0.429 0.296 0.685 0.524 0.531 0.531

Gasoline 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007

Jet fuel 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023

Other liquids 0.263 0.263 0.263 0.269 0.250 0.205 0.199 0.143 0.121 0.103 0.101 0.109 0.128 0.087 0.070 0.070 0.070 0.070 0.070

LPG 0.088 0.088 0.088 0.088 0.066 0.066 0.066 0.006 0.006 0.006 0.006 0.005 0.009 0.009 0.002 0.002 0.002 0.002 0.002

Shale oil 0.508 0.508 0.508 0.508 0.407 0.374 0.424 0.407 0.424 0.432 0.432 0.407 0.419 0.424 0.407 0.407 0.407 0.407 0.407

Coal 1.138 1.138 0.928 0.865 0.673 0.567 0.551 0.461 0.430 0.443 0.498 0.442 0.339 0.218 0.222 0.223 0.257 0.227 0.256

coke 1.229 0.819 0.410 0.273 0.273 0.273 0.273 0.269 0.269 0.269 0.269 0.269 0.269 0.269 0.269 0.269 0.269 0.269 0.269

Oil shale 1.370

Peat 0.507 0.507 0.474 0.370 0.347 0.400 0.364 0.462 0.448 0.429 0.458 0.414 0.367 0.196 0.354 0.288 0.288 0.288 0.288 Notes:

Gasoline – due to legislation Shale oil – average amount fro m database Nr. 2-Air

Peat – average amount fro m database Nr. 2-Air

Coal - average amount fro m database Nr. 2-Air and additional calculated average amount by periods Diesel oil – due to legislation


465

Fuel consumption in Energy sector (stationary combustion), TJ

1.A.1 Energy Industries

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

1.A.1.a. Public Electricity and Heat Production

Liquid Fuels 40098 20266 6350 5065 4821 3406 2843 2153 1299 1219 693 1031 705 593 492 211

Diesel o il 5524 85 127 42 42 42 42 42 42 43 43 16 15 25 127 94

RFO 32561 20016 5279 4425 4425 3207 2801 2111 1218 1137 650 1015 690 568 365 113

LPG 46 NO NO NO NO NO NO NO NO NO NO NO NO NO NO 4

Other liquid 1967 126 NO 126 NO NO NO NO NO NO NO NO NO NO NO NO

Shale oil NO 39 944 472 354 157 NO NO 39 39 NO NO NO NO NO NO

Solid Fuels 2305 1395 371 398 285 209 210 183 105 341 446 472 419 419 513 424

Coal 2305 1395 371 398 285 209 210 183 105 341 446 472 419 419 513 424

Peat 1377 2703 1970 1125 995 653 60 40 20 20 20 10 10 9 NO 40

Peat 1346 2626 1970 1125 995 653 60 40 20 20 20 10 10 9 NO 40

Peat briquettes 31 77 NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Natural gas 48214 23163 27996 32633 31691 33199 31499 32434 34242 32043 31845 30739 37812 34664 30895 32997

Biomass 436 1063 3232 3668 4164 4687 4648 4222 4817 4755 4635 4499 5322 5164 7104 10870

Wood 436 1045 3191 3617 4097 4644 4570 4132 4741 4675 4556 4390 5120 4635 5793 9198

Sludge gas NO 18 41 51 67 43 78 90 76 80 79 100 114 100 105 97

Landfill gas NO NO NO NO NO NO NO NO NO NO NO 9 18 22 22 14

Other biogas NO NO NO NO NO NO NO NO NO NO NO NO 61 355 1145 1561

Biodiesel NO NO NO NO NO NO NO NO NO NO NO NO 8 52 39 NO

Straws NO NO NO NO NO NO NO NO NO NO NO NO 1 NO NO NO

Waste oils 42 NO NO 42 42 29 88 29 NO NO NO 29 29 3 NO NO

1.A.1.c. Manufacture of Solid Fuels and Other Energy Industries

Liquid Fuels 339 253 1550 170 212 170 212 212 212 170 212 163 213 255 170 255

Diesel o il 212 212 127 170 212 170 212 212 212 170 212 163 213 255 170 255

RFO 81 41 NO NO NO NO NO NO NO NO NO NO NO NO NO NO

LPG 46 NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Jet fuel NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Other liquid NO NO 1423 NO NO NO NO NO NO NO NO NO NO NO NO NO

Solid Fuels NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Coal NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Peat 711 727 381 105 10 10 10 20 10 9 NO NO NO NO NO NO

Natural gas 815 944 807 877 806 875 872 872 939 570 805 497 875 943 977 929


466

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Wood NO NO NO 272 242 558 558 242 272 273 273 457 233 330 229 296

Waste oils NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

1.A.2 Manufacturing Industries and Construction

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

1.A.2.a. Iron and Steel

Liquid Fuels 1219 705 1172 1042 963 963 963 126 963 963 917 792 1006 NO NO NO

Diesel o il 42 NO 42 NO NO NO NO 42 NO NO NO NO 1 NO NO NO

RFO 1177 203 NO NO NO NO NO NO NO NO 122 81 NO NO NO NO

Other liquid NO 502 1130 963 963 963 963 84 963 963 795 711 1005 NO NO NO

Shale oil NO NO NO 79 NO NO NO NO NO NO NO NO NO NO NO NO

Solid Fuels 53 158 264 264 241 134 188 161 134 107 134 134 106 107 345 84

Coal NO NO NO NO NO NO NO NO NO NO NO NO 26 27 102 26

Coke 53 158 264 264 241 134 188 161 134 107 134 134 80 80 161 58

Anthracite NO NO NO NO NO NO NO NO NO NO NO NO NO NO 82 NO

Natural gas 4275 2360 3904 4058 3898 3969 4026 4125 4091 4118 3821 3395 3838 1180 1449 551

Waste oils 837 NO NO 42 NO NO NO 526 NO NO NO NO NO NO NO NO

1.A.2.b. Non-Ferrous Metals

Liquid Fuels NO NO NO 42 NO NO NO NO NO NO NO NO NO 2 3 NO

Diesel o il NO NO NO 42 NO NO NO NO NO NO NO NO NO 2 3 NO

Solid Fuels NO NO NO NO NO NO NO NO NO NO NO NO NO 2 1 NO

Coal NO NO NO NO NO NO NO NO NO NO NO NO NO 2 1 NO

Natural gas NO NO 168 190 269 302 269 203 204 201 134 101 135 168 168 NO

Biomass NO NO NO NO NO NO NO NO NO NO NO NO NO NO 1 NO

Biodiesel NO NO NO NO NO NO NO NO NO NO NO NO NO NO 1 NO

1.A.2.c. Chemicals

Liquid Fuels 3643 4547 122 164 162 122 NO NO NO NO 124 126 94 131 154 137

Diesel o il 127 NO NO NO NO NO NO NO NO NO 43 85 85 85 17 NO

RFO 3127 4547 122 122 162 122 NO NO NO NO 81 41 9 NO NO NO

LPG NO NO NO NO NO NO NO NO NO NO NO NO NO 46 137 137

Other kerosene 389 NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Other liquid NO NO NO 42 NO NO NO NO NO NO NO NO NO NO NO NO

Solid Fuels NO NO NO NO NO NO NO NO NO NO NO NO NO 1 NO NO

Coal NO NO NO NO NO NO NO NO NO NO NO NO NO 1 NO NO

Peat NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO 20


467

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Natural gas 427 1090 317 269 278 308 405 442 480 381 513 518 606 404 371 385

Biomass NO 7 47 46 29 19 47 29 59 74 188 130 188 188 282 262

Wood NO 7 47 46 29 19 47 29 56 72 187 127 187 169 210 208

Biodiesel NO NO NO NO NO NO NO NO 3 2 1 3 1 1 NO NO

Other biogas NO NO NO NO NO NO NO NO NO NO NO NO NO 18 72 54

Waste oils NO NO NO NO NO NO NO NO NO NO 29 NO NO NO NO NO

1.A.2.d. Pulp, Paper and Print

Liquid Fuels 203 81 NO NO NO NO NO NO NO NO NO NO 3 14 6 NO

Diesel o il NO NO NO NO NO NO NO NO NO NO NO NO 3 14 6 NO

RFO 203 81 NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Solid Fuels 28 56 NO 28 28 26 26 26 26 NO NO NO NO NO NO NO

Coal 28 56 NO 28 28 26 26 26 26 NO NO NO NO NO NO NO

Natural gas 2724 101 101 135 134 168 167 202 235 201 201 101 101 101 68 103

Biomass NO 87 23 13 20 20 20 27 20 16 7 163 156 108 102 97

Wood NO 87 23 13 20 20 20 27 20 16 7 163 156 108 102 97

1.A.2.e. Food Processing, Beverages and Tobacco

Liquid Fuels 10547 4693 2970 1651 1442 1034 873 912 916 669 420 586 566 376 500 475

Diesel o il 3229 552 552 467 340 340 340 297 255 213 212 212 170 85 121 170

RFO 7105 4060 1745 975 893 609 406 406 447 325 122 244 285 121 203 81

LPG 46 NO NO 46 46 46 46 46 91 91 46 91 72 91 137 182


Other kerosene NO NO 43 NO NO NO NO NO NO NO NO NO NO NO NO NO

Other liquid 167 42 NO 84 84 NO 42 84 84 NO NO NO NO NO NO 42

Shale oil NO 39 630 79 79 39 39 79 39 40 40 39 39 79 39 NO

Solid Fuels 1069 309 140 140 141 158 105 132 106 79 79 52 52 16 27 25

Coal 911 256 114 114 114 131 105 105 79 79 79 52 52 16 27 25

Coke 158 53 26 26 27 27 NO 27 27 NO NO NO NO NO NO NO

Peat NO NO NO NO NO NO NO NO NO NO NO NO 3 NO NO NO

Peat briquettes NO NO NO NO NO NO NO NO NO NO NO NO 3 NO NO NO

Natural gas 3177 3065 2607 2775 2985 2764 3238 3149 3249 2684 2370 1930 1919 1886 1819 1808

Biomass 228 327 450 800 842 719 916 1034 772 701 394 488 339 360 536 452

Wood 228 327 450 800 842 719 916 1034 772 701 394 483 333 360 535 449

Biodiesel NO NO NO NO NO NO NO NO NO NO NO 5 6 NO 1 NO

Other biogas NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO 3

Waste oils NO NO NO NO 42 88 88 88 88 117 88 30 29 56 29 29

1.A.2.f. Non-metallic minerals


468

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Liquid Fuels 3585 2562 1521 482 358 1367 1209 764 920 379 207 293 864 298 291 297

Diesel o il 127 84 42 42 42 42 42 255 212 127 127 128 237 298 291 297

RFO 3289 2436 731 162 NO NO NO 41 NO 81 41 NO NO NO NO NO

LPG NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO


Other liquid 126 42 NO 42 NO 251 NO NO 42 NO NO NO NO NO NO NO

Petroleum coke NO NO NO NO 198 956 1088 429 627 132 NO 165 627 NO NO NO

Shale oil NO NO 748 236 118 118 79 39 39 39 39 NO NO NO NO NO

Solid Fuels 170 114 28 28 28 26 26 682 1127 1809 1888 1285 1757 2136 1910 1299

Coal 142 114 28 28 28 26 26 682 1127 1809 1888 1285 1757 2136 1910 1299

Oil shale 28 NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Peat NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Natural gas 5734 1282 808 1821 2352 1884 1845 2381 1878 1979 1782 942 1010 977 1280 1344

Biomass 7 94 61 82 111 184 139 144 169 165 152 94 521 1076 1188 886

Wood 7 94 24 12 17 102 50 95 135 139 77 67 10 3 23 NO

Wastes (biomass fraction) NO NO 37 70 94 82 89 49 34 26 75 27 511 1073 1165 886

Other Fossil Fuels NO NO 94 385 824 442 429 300 202 153 255 74 404 664 819 1086

Waste oils NO NO NO 209 586 234 205 175 117 88 117 29 NO NO NO NO

Industrial wastes (used tires) NO NO 94 176 238 208 224 125 85 65 58 15 84 331 242 379

Municipal wastes NO NO NO NO NO NO NO NO NO NO 80 30 320 332 577 707

1.A.2.g. Other

Liquid Fuels 10551 4156 1790 1300 1041 931 1233 1064 1276 1832 1408 1149 967 1477 1695 1667

Gasoline 880 44 44 44 69 44 88 88 88 88 88 44 44 44 44 44

Diesel o il 2039 849 848 806 849 805 975 806 1060 1657 1275 1105 863 1301 1559 1529

RFO 7632 3086 813 366 123 82 82 82 82 41 NO NO 41 41 NO NO

LPG NO 91 46 NO NO NO 46 46 46 46 45 NO 19 91 92 94


Other kerosene NO 86 NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Other liquid NO NO NO 84 NO NO 42 42 NO NO NO NO NO NO NO NO

Petroleum coke NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Shale oil NO NO 39 NO NO NO NO NO NO NO NO NO NO NO NO NO

Solid Fuels 278 170 84 56 56 52 52 104 130 79 26 26 26 47 27 50

Coal 199 170 84 56 56 52 52 104 130 79 26 26 26 47 27 50

Coke 79 NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Oil shale NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Peat NO 15 NO NO NO NO 10 NO NO NO NO NO 11 2 2 4


469

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Peat briquettes NO 15 NO NO NO NO NO NO NO NO NO NO 1 NO NO 4

Peat NO NO NO NO NO NO 10 NO NO NO NO NO 10 2 2 NO

Natural gas 9557 2115 1968 2335 2922 3334 3208 3177 3258 3318 3014 2275 2928 2862 2797 1930

Biomass 382 1899 2152 2985 2485 2449 3673 4350 5442 4459 5132 7793 9116 10547 12107 12778

Wood 382 1899 2152 2985 2485 2449 3673 4350 5442 4459 5132 7793 9115 10547 12051 12776

Biodiesel NO NO NO NO NO NO NO NO NO NO NO NO 1 NO 2 2

Landfill gas NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Other biogas NO NO NO NO NO NO NO NO NO NO NO NO NO NO 54 NO

Waste oils NO NO NO 42 NO NO NO NO NO NO NO 29 29 29 29 NO

1.A.4 Other Sectors

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

1.A.4.a. Commercial/Institutional

Liquid Fuels 13453 2890 1715 1928 1818 2207 2167 1860 2289 1902 1596 1586 1619 1397 1859 1939

Gasoline 44 NO 88 77 46 44 44 44 44 44 44 44 44 88 44 88

Diesel o il 8116 1189 1020 1190 1317 1530 1657 1275 1700 1657 1360 1393 1418 1251 1713 1755

RFO 4953 1177 528 528 325 284 244 365 365 40 80 41 41 2 NO NO

LPG 46 91 NO 91 46 182 137 137 137 137 91 91 99 54 98 96

Jet fuel NO 86 NO NO NO NO 43 NO 43 24 21 17 17 2 4 NO

Other kerosene 43 346 NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Other liquid 251 NO NO 42 84 167 42 NO NO NO NO NO NO NO NO NO

Shale oil NO NO 79 NO NO NO NO 39 NO NO NO NO NO NO NO NO

Solid Fuels 14913 2903 1565 1536 1423 1338 1285 1049 1075 1075 918 735 1023 891 354 519

Coal 14913 2903 1565 1536 1423 1338 1285 1049 1075 1075 918 735 1023 891 354 519

Peat 672 114 31 15 NO 10 NO 20 40 61 31 16 1 32 32 NO

Peat briquettes 511 62 31 15 NO NO NO NO NO 1 1 6 1 3 4 NO

Peat 161 52 NO NO NO 10 NO 20 40 60 30 10 NO 29 28 NO

Natural gas 5004 2328 3054 3347 4103 4278 4680 4598 4851 5676 5679 5415 5623 5055 4952 4477

Biomass 5218 8282 4991 5497 5709 5965 6894 6737 6651 7253 4995 4826 5054 4398 5547 5721

Wood 5218 8282 4991 5497 5663 5803 6652 6485 6381 6966 4691 4482 4680 3997 5163 5217

Landfill gas NO NO NO NO 46 162 242 251 259 271 290 314 314 327 326 357

Other biogas NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO 49

Straws NO NO NO NO NO NO NO NO 11 16 14 29 57 43 24 44

Biodiesel NO NO NO NO NO NO NO NO NO NO NO NO 4 31 34 54

Waste oils NO NO NO 42 126 58 117 29 58 29 29 NO 8 NO NO NO


470

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

1.A.4.b. Residential

Liquid Fuels 4908 1402 1443 1441 1441 1398 1443 1577 1621 1438 1393 2025 2237 2229 2236 2237

Gasoline NO NO 132 132 132 132 132 220 264 264 264 264 264 264 263 264

Diesel o il 1912 127 127 170 170 127 127 127 127 127 127 850 1062 1062 1062 1062

RFO 41 NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

LPG 2869 1275 1184 1139 1139 1139 1184 1230 1230 1047 1002 911 911 903 911 911


Solid Fuels 6404 1821 512 1338 854 787 787 944 813 813 813 813 1049 944 577 530

Coal 6404 1821 512 1338 854 787 787 944 813 813 813 813 1049 944 577 530

Peat 425 252 10 NO NO NO NO NO NO NO NO NO 20 NO NO NO


Peat 131 20 10 NO NO NO NO NO NO NO NO NO 20 NO NO NO

Natural gas 4004 4181 2659 3001 3293 3667 3958 4193 4326 4587 4693 4304 5219 4480 4481 4266

Biomass 20010 30003 28227 30518 30078 31850 32073 32234 31195 30433 30168 33667 25036 26144 27823 24195

Wood 20010 30003 28227 30518 30078 31850 32043 32174 31165 30388 30108 33607 24974 26084 27764 24105

Charcoal NO NO NO NO NO NO 30 60 30 45 60 60 60 60 59 90

Straws NO NO NO NO NO NO NO NO NO NO NO NO 2 NO NO NO

1.A.4.c. i, ii Agriculture/Forestry/Fisheries

Liquid Fuels 7706 2759 2551 2644 2650 2847 3061 3316 3783 4038 3700 3827 4053 4258 3958 4003

Gasoline 1628 88 44 11 17 44 44 44 44 44 NO NO NO 88 88 88

Diesel o il 4886 2549 2507 2592 2592 2762 3017 3272 3739 3994 3654 3782 4037 4122 3824 3867

RFO 934 122 NO 41 41 41 NO NO NO NO NO NO 3 3 NO NO

LPG 46 NO NO NO NO NO NO NO NO NO 46 45 13 45 46 48


Other liquid 126 NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Solid Fuels 1081 456 85 113 113 78 78 52 52 52 52 26 26 26 52 26

Coal 1081 456 85 113 113 78 78 52 52 52 52 26 26 26 52 26

Peat 31 25 NO NO NO NO NO NO NO NO NO NO NO NO NO NO


Peat NO 10 NO NO NO NO NO NO NO NO NO NO NO NO NO NO

Natural gas 14195 641 505 712 702 850 1014 841 806 764 587 521 977 808 1044 1066

Biomass 1220 358 590 546 508 506 607 552 534 713 324 722 569 500 727 1002

Wood 1220 358 590 546 508 506 607 552 534 713 324 722 568 361 299 460

Other biogas NO NO NO NO NO NO NO NO NO NO NO NO NO 91 358 474

Straws NO NO NO NO NO NO NO NO NO NO NO NO NO NO 14 14

Biodiesel NO NO NO NO NO NO NO NO NO NO NO NO 1 48 56 54


471

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

1.A.4.c. iii Fishing

Diesel o il 1275 1402 935 1147 807 1232 1062 892 722 510 425 340 425 467 297 297

RFO 487 365 244 203 203 203 203 162 41 NO NO NO NO NO NO NO

1.A.5 Other

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Gasoline NO NO 1.935 2.374 1.540 2.155 2.858 2.374 5.716 0.967 5.408 1.121 0.224 NO NO NO

Diesel o il NO NO NO NO 74.570 64.542 110.941 77.119 73.125 14.277 20.650 49.033 86.684 80.264 78.662 63.459

Jet fuel NO NO NO NO 17.496 17.154 16.938 24.327 23.722 24.000 20.957 22.728 19.980 17.785 20.974 24.414


472

A.3.2. Energy: CO2 reference approach and comparison with sectoral approach

Table 1 Reference Approach estimations (TABLE 1.A(b))

FUEL TYPES Unit Production Imports Exports International Stock

change Apparent

Conver

sion

NCV/

GCV

Apparent Carbon

emission Carbon Carbon Net carbon Fraction of Actual CO2

bunkers consumpti

on factor consumption factor content

stored[C

excluded] emissions carbon emissions

(TJ/Uni

t) (TJ) (t C/TJ) (kt) (kt C) ((kt) C) oxidized ((kt) CO2)

Liquid fossil

Primary fuels

Crude oil TJ NO NO NO NO NO NO NCV NO NO NO NO NO NO NO

Orimulsion TJ NO NO NO NO NO NO NCV NO NO NO NO NO NO NO

Natural gas liquids TJ NO NO NO NO NO NO NCV NO NO NO NO NO NO NO

Secondary fuels Gasoline TJ 9 903.00 886.00 NO 44.00 8 973.00 1.00 NCV 8 973.00 18.91 169.64 NO 169.64 0.99 615.81

Jet kerosene TJ 5 920.00 778.00 5 142.00 -43.00 43.00 1.00 NCV 43.00 19.71 0.85 NO 0.85 0.99 3.08

Other kerosene TJ 43.00 43.00 NO NO 0.00 1.00 NCV 0.00 19.72 0.00 NO 0.00 0.99 0.00

Shale oil TJ 118.00 118.00 NO 0.00 1.00 NCV 0.00 21.05 0.00 NO 0.00 0.99 0.00

Gas/diesel oil TJ 58 939.00 21 372.00 3 148.00 425.00 33 994.00 1.00 NCV 33 994.00 20.40 693.48 NO 693.48 0.99 2 517.34

Residual fuel oil TJ 6 852.00 NO 6 658.00 NO 194.00 1.00 NCV 194.00 21.11 4.10 NO 4.10 0.99 14.87

Liquefied petroleum gases (LPG)

TJ 8 530.00 4 736.00 -46.00 3 840.00 1.00 NCV 3 840.00 17.13 65.76 NO 65.76 1.00 239.92

Ethane TJ NO NO NO NO NO NCV NO NO NO NO NO NO NO

Naphtha TJ NO NO NO NO NO NCV NO NO NO NO NO NO NO

Bitumen TJ 3 097.00 NO -84.00 3 181.00 1.00 NCV 3 181.00 22.00 69.98 69.98 0.00 0.99 0.00

Lubricants TJ 1 841.00 919.00 NO 42.00 880.00 1.00 NCV 880.00 20.00 17.60 1.00 16.60 1.00 60.88

Petroleum coke TJ NO NO NO NO 1.00 NCV NO 26.60 NO NO NO 1.00 NO

Refinery feedstocks TJ NO NO NO NO NO NCV NO NO NO NO NO NO NO

Other oil TJ 167.00 167.00 -42.00 42.00 1.00 NCV 42.00 20.00 0.84 NO 0.84 1.00 3.08

Other liquid fossil NO NO NO NO NO

Liquid fossil totals 51 147.00 1 022.25 70.98 951.27 3 454.97

Solid fossil Primary fuels Anthracite (3) TJ NO 109.73 27.43 54.87 27.43 1.00 NCV 27.43 26.80 0.74 NO 0.74 1.00 2.70

Coking coal TJ NO NO NO NO NO NO NCV NO NO NO NO NO NO NO

Other bituminous coal TJ NO 2 748.27 164.57 NO -294.87 2 878.57 1.00 NCV 2 878.57 25.80 74.27 NO 74.27 1.00 272.31

Sub-bituminous coal TJ NO NO NO NO NO NO NO NCV NO NO NO NO NO NO NO

Lignite TJ NO NO NO NO NO NO NCV NO NO NO NO NO NO NO

Oil shale and tar sand TJ NO NO NO NO NO NO NCV NO NO NO NO NO NO NO

Secondary fuels BKB(4) and patent fuel TJ NO NO NO NO NO NCV NO NO NO NO NO NO NO

Coke oven/gas coke TJ 26.00 NO -26.00 52.00 1.00 NCV 52.00 29.20 1.52 NO 1.52 1.00 5.57


473

FUEL TYPES Unit Production Imports Exports International Stock

change Apparent

Conver

sion

NCV/

GCV

Apparent Carbon

emission Carbon Carbon Net carbon Fraction of Actual CO2

bunkers consumption

factor consumption factor content stored[C excluded]

emissions carbon emissions

(TJ/Unit)

(TJ) (t C/TJ) (kt) (kt C) ((kt) C) oxidized ((kt) CO2)

Coal tar TJ NO NO NO NO NO NCV NO NO NO NO NO NO NO

Other solid fossil NO NO NO NO NO

Solid fossil to tals 2 958.00 76.52 NO 76.52 280.58

Gaseous fossil Natural gas (dry ) TJ NO 58 423.00 NO 7 879.00 50 544.00 1.00 NCV 50 544.00 14.87 751.71 NO 751.71 1.00 2 742.48

Other gaseous fossil

NO NO NO NO NO

Gaseous fossil totals

50 544.00 751.71 NO 751.71 2 742.48

Waste (non-biomass fraction) TJ NO IE IE NO IE IE,NO IE NCV IE,NO IE IE,NO IE IE,NO IE IE,NO

Other fossil fuels

1 115.32 24.76 NO 24.76 90.77

Waste oils TJ 29.00 NO NO NO 29.00 1.00 NCV 29.00 20.00 0.58 NO 0.58 1.00 2.13

Industrial waste TJ NO 301.82 4.02 -81.25 379.05 1.00 NCV 379.05 20.00 7.58 NO 7.58 1.00 27.80

Municipal waste TJ NO 717.77 14.42 -3.91 707.26 1.00 NCV 707.26 23.46 16.59 NO 16.59 1.00 60.85

Peat TJ 104.00 42.00 42.00 NO 20.00 84.00 1.00 NCV 84.00 28.93 2.43 NO 2.43 0.98 8.73

Total 105 848.32 1 877.66 70.98 1 806.69 6 577.52

Biomass total

57 757.37 1 658.68 NO 1 658.68 5 965.20

Solid biomass TJ 73 335.00 1 752.00 27 194.00 -5 061.00 52 954.00 1.00 NCV 52 954.00 30.01 1 589.36 NO 1 589.36 0.98 5 711.67

Liquid biomass TJ 2 598.02 862.00 2 373.02 -71.63 1 158.63 1.00 NCV 1 158.63 19.85 22.99 NO 22.99 1.00 84.31

Gas biomass TJ 2 609.33 NO NO NO 2 609.33 1.00 NCV 2 609.33 13.95 36.41 NO 36.41 1.00 132.83

Other non-fossil fuels (biogenic waste)

TJ NO 1 017.07 19.34 -37.68 1 035.41 1.00 NCV 1 035.41 9.59 9.92 NO 9.92 1.00 36.39


474

Table 2 Comparison of CO2 emissions from fuel combustion (1.A(c))

FUEL TYPES REFERENCE APPROACH SECTORAL APPROACH(1) DIFFERENCE(2)

Apparent energy

consumption

Apparent energy consumption (excluding non-energy use,

reductants and feedstocks)

CO2 emissions Energy

consumption CO2 emissions

Energy

consumption CO2 emissions

(PJ) (PJ) (kt) (PJ) (kt) (%) (%)

Liquid fuels (excluding international bunkers) 51.15 47.09 3 454.97 49.77 3 613.02 -5.40 -4.37

Solid fuels (excluding international bunkers) 2.96 2.96 280.58 2.96 280.50 0.03 0.03

Gaseous fuels 50.54 50.54 2 742.48 49.99 2 710.99 1.10 1.16

Other fossil fuels 1.12 1.12 90.77 1.12 94.63 0.00 -4.08

Peat 0.08 0.08 8.73 0.06 6.62 31.25 31.85

Total 105.85 101.79 6 577.52 103.90 6 705.76 -2.04 -1.91


475

A.3.3 Transport

Road Transport

Distribution of road transport fleet by subsectors and layers, year 2013

Subsector

Technology

Population

Mileage,

km/year on

vehicle

Passenger Cars

Gasoline <1,4 l ECE 15/00-01 306 1620

Gasoline <1,4 l ECE 15/02 394 1980

Gasoline <1,4 l ECE 15/03 820 2700

Gasoline <1,4 l ECE 15/04 3947 3600

Gasoline <1,4 l PC Euro 1 - 91/441/EEC 6016 5500

Gasoline <1,4 l PC Euro 2 - 94/12/EEC 5646 10130

Gasoline <1,4 l PC Euro 3 - 98/69/EC Stage2000 7446 12758

Gasoline <1,4 l PC Euro 4 - 98/69/EC Stage2005 9942 14520

Gasoline <1,4 l PC Euro 5 - EC 715/2007 2699 19000

Gasoline 1,4 - 2,0 l ECE 15/00-01 2721 1170

Gasoline 1,4 - 2,0 l ECE 15/02 3265 1494

Gasoline 1,4 - 2,0 l ECE 15/03 3810 2430

Gasoline 1,4 - 2,0 l ECE 15/04 26486 3600

Gasoline 1,4 - 2,0 l PC Euro 1 - 91/441/EEC 36012 7200

Gasoline 1,4 - 2,0 l PC Euro 2 - 94/12/EEC 45124 12000

Gasoline 1,4 - 2,0 l PC Euro 3 - 98/69/EC Stage2000 26392 16000

Gasoline 1,4 - 2,0 l PC Euro 4 - 98/69/EC Stage2005 26359 17500

Gasoline 1,4 - 2,0 l PC Euro 5 - EC 715/2007 4611 22155

Gasoline >2,0 l ECE 15/00-01 449 1620

Gasoline >2,0 l ECE 15/02 471 2250

Gasoline >2,0 l ECE 15/03 641 2700

Gasoline >2,0 l ECE 15/04 2714 4228

Gasoline >2,0 l PC Euro 1 - 91/441/EEC 7113 9900

Gasoline >2,0 l PC Euro 2 - 94/12/EEC 11540 14400

Gasoline >2,0 l PC Euro 3 - 98/69/EC Stage2000 9878 17741

Gasoline >2,0 l PC Euro 4 - 98/69/EC Stage2005 8770 20740

Gasoline >2,0 l PC Euro 5 - EC 715/2007 957 21975

Diesel <2,0 l Conventional 14569 10000

Diesel <2,0 l PC Euro 1 - 91/441/EEC 26728 11000

Diesel <2,0 l PC Euro 2 - 94/12/EEC 32570 12500

Diesel <2,0 l PC Euro 3 - 98/69/EC Stage2000 35315 14500

Diesel <2,0 l PC Euro 4 - 98/69/EC Stage2005 31197 18500

Diesel <2,0 l PC Euro 5 - EC 715/2007 7394 22000

Diesel >2,0 l Conventional 5438 12000

Diesel >2,0 l PC Euro 1 - 91/441/EEC 13339 13000

Diesel >2,0 l PC Euro 2 - 94/12/EEC 22461 17000

Diesel >2,0 l PC Euro 3 - 98/69/EC Stage2000 27483 18360

Diesel >2,0 l PC Euro 4 - 98/69/EC Stage2005 24996 19000

Diesel >2,0 l PC Euro 5 - EC 715/2007 3397 23000

LPG Conventional 8500 15000

LPG PC Euro 1 - 91/441/EEC 8141 19500

LPG PC Euro 2 - 94/12/EEC 11013 20525

LPG PC Euro 3 - 98/69/EC Stage2000 7250 21900


476

Subsector

Technology

Population

Mileage,

km/year on

vehicle

LPG PC Euro 4 - 98/69/EC Stage2005 5121 22900

LPG PC Euro 5 - EC 715/2007 661 24620

Light Duty Vehicles


LPG LD Euro 1 - 93/59/EEC 121 30369

LPG LD Euro 2 - 96/69/EEC 246 31000

LPG LD Euro 3 - 98/69/EC Stage2000 114 33727

LPG LD Euro 4 - 98/69/EC Stage2005 186 43374

LPG LD Euro 5 - 2008 Standards 97 47984

Gasoline <3,5t Conventional 195 17000

Gasoline <3,5t LD Euro 1 - 93/59/EEC 230 18000

Gasoline <3,5t LD Euro 2 - 96/69/EEC 455 19000

Gasoline <3,5t LD Euro 3 - 98/69/EC Stage2000 376 21500

Gasoline <3,5t LD Euro 4 - 98/69/EC Stage2005 737 28400

Gasoline <3,5t LD Euro 5 - 2008 Standards 189 31000

Diesel <3,5 t Conventional 2304 25000

Diesel <3,5 t LD Euro 1 - 93/59/EEC 5512 25000

Diesel <3,5 t LD Euro 2 - 96/69/EEC 8659 26000

Diesel <3,5 t LD Euro 3 - 98/69/EC Stage2000 9017 28000

Diesel <3,5 t LD Euro 4 - 98/69/EC Stage2005 7905 34000

Diesel <3,5 t LD Euro 5 - 2008 Standards 2729 38000

Heavy Duty Trucks


LPG HD Euro I - 91/542/EEC Stage I 45 24400

LPG HD Euro II - 91/542/EEC Stage II 71 26000

Gasoline >3,5 t Conventional 1027 18500

Gasoline >3,5 t HD Euro I - 91/542/EEC Stage I 94 18640

Gasoline >3,5 t HD Euro II - 91/542/EEC Stage II 86 18644

Gasoline >3,5 t HD Euro III - 2000 Standards 13 25057

Rigid <=7,5 t Conventional 1133 20400

Rigid <=7,5 t HD Euro I - 91/542/EEC Stage I 634 20411

Rigid <=7,5 t HD Euro II - 91/542/EEC Stage II 665 20411

Rigid <=7,5 t HD Euro III - 2000 Standards 521 27431

Rigid <=7,5 t HD Euro IV - 2005 Standards 290 40071

Rigid <=7,5 t HD Euro V - 2008 Standards 128 42079

Rigid 7,5 - 12 t Conventional 582 20600

Rigid 7,5 - 12 t HD Euro I - 91/542/EEC Stage I 282 20603

Rigid 7,5 - 12 t HD Euro II - 91/542/EEC Stage II 355 20603

Rigid 7,5 - 12 t HD Euro III - 2000 Standards 310 28929

Rigid 7,5 - 12 t HD Euro IV - 2005 Standards 144 38291

Rigid 7,5 - 12 t HD Euro V - 2008 Standards 64 36565

Rigid 12 - 14 t Conventional 157 20700

Rigid 12 - 14 t HD Euro I - 91/542/EEC Stage I 123 20702

Rigid 12 - 14 t HD Euro II - 91/542/EEC Stage II 57 20702

Rigid 12 - 14 t HD Euro III - 2000 Standards 22 23111

Rigid 12 - 14 t HD Euro IV - 2005 Standards 27 29129

Rigid 12 - 14 t HD Euro V - 2008 Standards 17 31534




477

Subsector

Technology

Population

Mileage,

km/year on

vehicle























Rigid >32 t Conventional 16 38400

Rigid >32 t HD Euro I - 91/542/EEC Stage I 20 38400

Rigid >32 t HD Euro II - 91/542/EEC Stage II 50 38400

Rigid >32 t HD Euro III - 2000 Standards 82 53000

Rigid >32 t HD Euro IV - 2005 Standards 67 74000

Rigid >32 t HD Euro V - 2008 Standards 23 78000

Articulated 14 - 20 t Conventional 476 29500

Articulated 14 - 20 t HD Euro I - 91/542/EEC Stage I 529 29500

Articulated 14 - 20 t HD Euro II - 91/542/EEC Stage II 904 29550

Articulated 14 - 20 t HD Euro III - 2000 Standards 759 38000

Articulated 14 - 20 t HD Euro IV - 2005 Standards 1119 52000

Articulated 14 - 20 t HD Euro V - 2008 Standards 436 57000













Buses

Urban Buses Conventional 8 29840

Urban Buses HD Euro I - 91/542/EEC Stage I 1 29840


478

Subsector

Technology

Population

Mileage,

km/year on

vehicle

Urban Buses HD Euro II - 91/542/EEC Stage II 17 29840

Urban Buses Midi <=15 t Conventional 323 32567

Urban Buses Midi <=15 t HD Euro I - 91/542/EEC Stage I 130 32567

Urban Buses Midi <=15 t HD Euro II - 91/542/EEC Stage II 271 32567

Urban Buses Midi <=15 t HD Euro III - 2000 Standards 467 43891

Urban Buses Midi <=15 t HD Euro IV - 2005 Standards 570 56098

Urban Buses Midi <=15 t HD Euro V - 2008 Standards 220 52520

Coaches Standard <=18 t Conventional 301 47805

Coaches Standard <=18 t HD Euro I - 91/542/EEC Stage I 164 47805

Coaches Standard <=18 t HD Euro II - 91/542/EEC Stage II 239 47805

Coaches Standard <=18 t HD Euro III - 2000 Standards 221 59027

Coaches Standard <=18 t HD Euro IV - 2005 Standards 145 62020

Coaches Standard <=18 t HD Euro V - 2008 Standards 55 69080

Coaches Articulated >18 t Conventional 43 47805

Coaches Articulated >18 t HD Euro I - 91/542/EEC Stage I 90 47805

Coaches Articulated >18 t HD Euro II - 91/542/EEC Stage II 226 47805

Coaches Articulated >18 t HD Euro III - 2000 Standards 262 59027

Coaches Articulated >18 t HD Euro IV - 2005 Standards 66 62020

Coaches Articulated >18 t HD Euro V - 2008 Standards 8 69080

Mopeds

<50 cm³ Conventional 176 1000

<50 cm³ Mop - Euro I 1371 1150

<50 cm³ Mop - Euro II 10886 1150

Motorcycles

2-stroke >50 cm³ Conventional 1066 1100

2-stroke >50 cm³ Mot - Euro I 1153 1620

2-stroke >50 cm³ Mot - Euro II 481 1620

2-stroke >50 cm³ Mot - Euro III 1099 1620

4-stroke <250 cm³ Mot - Euro III 425 400

4-stroke 250 - 750 cm³ Conventional 868 1400

4-stroke 250 - 750 cm³ Mot - Euro I 1336 2030

4-stroke 250 - 750 cm³ Mot - Euro II 606 2030

4-stroke 250 - 750 cm³ Mot - Euro III 1440 2440

4-stroke >750 cm³ Conventional 536 1800

4-stroke >750 cm³ Mot - Euro I 767 2030

4-stroke >750 cm³ Mot - Euro II 337 2030

4-stroke >750 cm³ Mot - Euro III 1015 2440


479

A.3.4 Industrial Processes Sector

Table 1 HFC–134a estimation from domestic refrigeration

1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Number o f inhabitants 2485056 2367550 2337170 2310173 2287955 2263122 2238799 2218357 2200325 2177322 2141669 2097555 2059709 2034319 2012647

Number o f households (units) 967600 921700 909000 904100 895100 884600 879500 872000 868700 857200 837100 825600 817000 822000 823300

Amount of households (%) 39% 39% 39% 39% 39% 39% 39% 39% 39% 39% 39% 39% 40% 40% 41%

Number o f re frigerators in

households (units) 837942 815151 808101 817306 822597 826216 834646 840608 838296 828055 809476 799181 791673 797340 799424

Amount of re frigerators in

households (%) 87% 88% 89% 90% 92% 93% 95% 96% 97% 97% 97% 97% 97% 97% 97%

Number o f freezers in households

(units) 21287 28388 29997 40504 50663 60507 112048 80224 76011 71148 65712 61094 56782 53430 49810

Amount of freezers in households

(%) 2% 3% 3% 4% 6% 7% 13% 9% 9% 8% 8% 7% 7% 7% 6%

Refrigerators and freezers containing HFC-134a (%)

5% 13% 15% 18% 22% 26% 30% 34% 38% 42% 45% 48% 51% 54% 57%

Number o f re frigerators containing HFC-134a (units)

41897 105970 121215 147115 180971 214816 250394 285807 318552 347783 364264 383607 403753 430564 455672

Number o f freezers containing

HFC-134a (units) 1064 3690 4500 7291 11146 15732 33614 27276 28884 29882 29571 29325 28959 28852 28392

HFC-134a in refrigerators (140 g)

(kg) 5865.59 14835.76 16970.12 20596.12 25335.98 30074.28 35055.11 40012.94 44597.32 48689.65 50996.97 53704.95 56525.45 60278.90 63794.06

HFC-134a in freezers (140 g) (kg) 149.01 516.67 629.94 1020.69 1560.41 2202.44 4706.03 3818.66 4043.80 4183.48 4139.88 4105.54 4054.20 4039.31 3974.81

HFC-134a in stocks (t) 6.01 15.35 17.60 21.62 26.90 32.28 39.76 43.83 48.64 52.87 55.14 57.81 60.58 64.32 67.77

HFC-134a charging one in a lifetime for re frigerators – (176.25

g) (kg)

3.57 9.02 6.88 8.35 10.27 12.19 14.21 16.22 18.07 19.73 20.67 21.76 22.91 24.43 25.85

HFC-134a charging one in a

lifetime for freezers – (176.25 g)

(kg)

0.09 0.31 0.26 0.41 0.63 0.89 1.91 1.55 1.64 1.70 1.68 1.66 1.64 1.64 1.61


480

1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

HFC-134a charged 0.00 0.01 0.01 0.01 0.01 0.01 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.03 0.03

HFC-134a leakage during charging

of re frigerators (0.6%) (kg) 0.02 0.05 0.04 0.05 0.06 0.07 0.09 0.10 0.11 0.12 0.12 0.13 0.14 0.15 0.16

HFC-134a leakage during charging

of freezers (0.6 %) (kg) 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01

HFC-134a fro m charging (t) 0.0000 0.0001 0.0000 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0002 0.0002

HFC-134a leakage fro m stocks in refrigerators containing HFC-134a

(0.3%) (kg) 17.60 44.51 50.91 61.79 76.01 90.22 105.17 120.04 133.79 146.07 152.99 161.11 169.58 180.84 191.38

HFC-134a leakage fro m stocks in

freezers containing HFC-134a

(0.3%) (kg)

0.45 1.55 1.89 3.06 4.68 6.61 14.12 11.46 12.13 12.55 12.42 12.32 12.16 12.12 11.92

HFC-134a fro m stock (t) 0.02 0.05 0.05 0.06 0.08 0.10 0.12 0.13 0.15 0.16 0.17 0.17 0.18 0.19 0.20

HFC-134a leakage after disposal (80%60%) (kg)

NE NA NA NA NA NA NO NO NO NO NO NO NO NO NO

HFC-134a leakage after disposal

(80%60%) (kg) NE NA NA NA NA NA NO NO NO NO NO NO NO NO NO

Table 2 HFC–134a emission estimation from commercial and industrial refrigeration

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Amount of HFC-134a used in installation of new equipment (t) 0.0800 0.0211 0.1118 0.2330 0.3532 0.5850 0.6639 0.3765 6.8653 4.8303 6.6466 7.0848 8.7729 3.8173 8.3482 22.1426

Amount of HFC-134a used for charging (t) 0.0108 0.1420 0.1810 0.2233 0.5878 0.6982 0.3738 0.7360 IE IE IE IE IE IE IE IE

Amount of gas is manufactured equipment (t) - 0.03 - - 0.0202 0.0136 - - - - - - - - - -

Total amount of HFC-134a charged (t) 0.0908 0.1931 0.2928 0.4563 0.9612 1.2968 1.0377 1.1125 6.8653 4.8303 6.6466 7.0848 8.7729 3.8173 8.3482 22.1426

Leakage fro m charging (%) 15% 15% 15% 15% 15% 15% 15% 15% 8% 8% 8% 8% 8% 8% 8% 8%

HFC-134a held in stocks (t) 0.0908 0.2231 0.3128 0.7748 1.0352 1.4044 2.1133 2.4695 30.7908 25.9109 43.0996 61.6263 46.6234 17.0610 48.4359 56.4426

Leakage fro m stocks (%) 3.50% 3.50% 3.50% 3.50% 3.50% 3.50% 3.50% 3.50% 1.50% 1.50% 1.50% 1.50% 1.50% 1.50% 1.50% 1.50%

HFC-134a emissions from charging (t) 0.0032 0.0068 0.0102 0.0160 0.0336 0.0454 0.0363 0.0389 0.1030 0.0725 0.0997 0.1063 0.1316 0.0573 0.1252 0.3321

HFC-134a emissions from stocks (t) 0.0136 0.0335 0.0469 0.1162 0.1553 0.2107 0.3170 0.3704 2.4633 2.0729 3.4480 4.9301 3.7299 1.3649 3.8749 4.5154

HFC-134a fro m disposal - - - - - - - NO NO NO NO NO NO NO NO NO


481

Table 3 HFC–32 emission estimation from commercial and industrial refrigeration

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Amount of HFC-32 used in installation of new equipment (t)

NE NE 0.4846 1.5818 1.3011 1.6591 2.0065 2.7336 3.1901 2.5703

Amount of HFC-32 used for charging (t)

0.046 IE IE IE IE IE IE IE IE IE

Total amount of HFC-32 charged (t) 0.0460 - 0.4846 1.5818 1.3011 1.6591 2.0065 2.7336 3.1901 2.5703

Leakage from charging (%) 15% 15% 8% 8% 8% 8% 8% 8% 8% 8%

HFC-32 held in stocks (t) 0.4837 0.0184 1.1819 2.9121 5.5460 11.6342 6.7596 4.9438 3.5141 5.3435

Leakage from stocks (%) 3.50% 3.50% 1.50% 1.50% 1.50% 1.50% 1.50% 1.50% 1.50% 1.50%

HFC-32 emissions from charging (t) 0.0016 - 0.0073 0.0237 0.0195 0.0249 0.0301 0.0410 0.0479 0.0386

HFC-32 emissions from stocks (t) 0.0726 0.0028 0.0945 0.2330 0.4437 0.9307 0.5408 0.3955 0.2811 0.4275

HFC-32 from disposal - NO NO NO NO NO NO NO NO NO


2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Amount of HFC-125 used in installation of new equipment (t)

- 0.0660 8.2509 6.4119 12.1509 14.7358 19.1665 22.5163 21.0095 22.7562


0.0931 IE IE IE IE IE IE IE IE IE

Total amount of HFC-125 charged (t)

0.0931 0.0660 8.2509 6.4119 12.1509 14.7358 19.1665 22.5163 21.0095 22.7562




HFC-125 emissions from charging (t)

0.0033 0.0023 0.1238 0.0962 0.1823 0.2210 0.2875 0.3377 0.3151 0.3413

HFC-125 emissions from

stocks (t) 0.0937 0.0129 0.5778 1.7260 2.6730 3.5479 2.8187 3.1549 2.5868 5.0546

HFC-125 from disposal - NO NO NO NO NO NO NO NO NO


2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Amount of HFC-143 used in installation of new equipment

(t) NO 0.0780 9.0183 5.6805 12.5648 13.5303 18.9081 23.1855 19.5919 18.2122

Amount of HFC-143 used for

charging (t) 0.0510 IE IE IE IE IE IE IE IE IE

Total amount of HFC-143 charged (t)

0.0510 0.0780 9.0183 5.6805 12.5648 13.5303 18.9081 23.1855 19.5919 18.2122




HFC-143 emissions from charging (t)

0.0018 0.0027 0.1353 0.0852 0.1885 0.2030 0.2836 0.3478 0.2939 0.2732

HFC-143 emissions from stocks (t)

0.0131 0.0117 0.5466 1.8740 2.5625 1.9427 2.5845 3.0766 3.9399 4.0283

HFC-143 from disposal NO NO NO NO NO NO NO NO NO NO


2006 2007 2008 2009 2010 2011 2012 2013

Amount of HFC-152 used in installation of new

0.012267 - - - - - 2.976 0.72


482

2006 2007 2008 2009 2010 2011 2012 2013

equipment (t)


IE IE IE IE IE IE IE IE

Leakage from charging

(%)

8% 8% 8% 8% 8% 8% 8% 8%

HFC-152 held in stocks (t) 0.1110061 0.0744925 0.0379789 0.0024739 0.000546 0.0017979 1.1536601 0.7212181

Leakage from stocks (%) 1.50% 1.50% 1.50% 1.50% 1.50% 1.50% 1.50% 1.50%

HFC-152 emissions from

charging (t)

0.0002 NO NO NO NO NO 0.00001547 NO

HFC-152 emissions from stocks (t)

0.0089 0.0060 0.0030 0.0002 0.00004 0.000143832 0.09229 0.05770

Table 7 HFC– 23 emission estimation from commercial and industrial refrigeration

2008 2009 2010 2011 2012 2013

Amount of HFC-23 used in installation of new equipment (t) 0.0012 NO NO NO 0.57209 0.126923

Leakage from charging (%) 8% 8% 8% 8% 8% 8%

HFC-23 held in stocks (t) 0.011 0.02336 0.05732 0.0442 0.05056 0.61192

Leakage from stocks (%) 1.50% 1.50% 1.50% 1.50% 1.50% 1.50%

HFC-23 emissions from charging (t) 0.0000 NO NO NO 0.0007 0.001903845

HFC-23 emissions from stocks (t) 0.0009 0.0019 0.0046 0.0036 0.0047 0.0489536

HFC-23 from disposal NO NO NO NO NO NO

Table 8 HFC–134a emission estimation from transport refrigeration

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Amount of HFC-134a held in stocks (t) 0.0308 0.0913 0.2898 0.2598 0.3093 0.4580 0.5622 0.5440 IE IE

Leakage from stocks (%) 15% 15% 15% 15% 15% 15% 15% 8% 8% 8%

Emissions from stocks (t) 0.0046 0.0137 0.0435 0.0390 0.0464 0.0687 0.0843 0.0435 IE IE

Table 9 HFC–23 emission estimation from transport refrigeration

1995 1996 1997 1998 1999 2000 2001 2002 2003

Amount of HFC-23 held in stocks (t) 0.1000 0.0240 0.0500 0.1800 0.0900 0.0100 0.0100 0.0200 0.1200

Leakage from stocks (%) 15% 15% 15% 15% 15% 15% 15% 15% 15%

Emissions from stocks (t) 0.0150 0.0036 0.0075 0.0270 0.0135 0.0015 0.0015 0.0030 0.0180

Table 10 HFC–125 emission estimation from transport refrigeration

2004 2005 2006

Amount of HFC-125 held in stocks (t) 0.0133 0.1704 0.3274

Leakage from stocks (%) 15% 15% 8%

Emissions from stocks (t) 0.0020 0.0256 0.0262


483

Table 11 HFC – 134a emission estimation from mobile air conditioning equipment

1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Passenger cars with manufacturing year >1995

384 30730 41049 55166 73510 103917 151705 230926 324774 371591 376123 392265 403791 435907 472549

Trucks with

manufacturing year >1995

35 12724 15164 17714 20875 25955 36693 46068 57906 63271 60436.5 33835 41263 48445 55761

Passenger cars equipped with MACs (%)

20% 20% 23% 26% 29% 31% 33% 35% 36% 38% 0.3936458

0.4069791

42% 43% 44%

Trucks equipped with MACs (%)

50.0% 50.0% 53.3% 56.2% 58.7% 60.9% 62.9% 64.7% 66.4% 67.9% 69.4% 70.7% 71.9% 73.1% 74.2%

Passenger cars

equipped with MACs (pieces)

76.8 6146 9578.1 14448.2 21090.4 32123.5 49930.2 80202.6 118210.0 140966.8 148059.2 159643.7 169381.9 187982.2 209034.4

Trucks equipped with MACs (pieces)

17.5 6362 8087.466 9953.693 12251.87 15809.89 23084.49 29820.35 38447.90 42984.06 41921.52 23920.63 29687.87 35425.10 41394.45

Amount of HFC-134a in passenger cars (kg)

61 4917 7662 11559 16872 25699 39944 64162 94568 112773 118447 127715 135506 150386 167228

Amount of HFC-134a in trucks (kg)

21 7634 9705 11944 14702 18972 27701 35784 46137 51581 50306 28705 35625 42510 49673

Total amount of HFC-134a in cars (t)

0.082 12.551 17.367 23.503 31.575 44.671 67.646 99.947 140.705 164.354 168.753 156.420 171.131 192.896 216.901

Leakage from stocks

(%)

15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15%

HFC-134a emission

from stocks (t)

0.012 1.883 2.605 3.525 4.736 6.701 10.147 14.992 21.106 24.653 25.313 23.463 25.670 28.934 32.535

Disposed MACs from passenger cars in year (piece)

6 492 766 1156 1687 2570 3994 6416 9457 11277 11845 12771 13551 15039 16723

Disposed MACs from trucks in year (piece)

1 509 647 796 980 1265 1847 2386 3076 3439 3354 1914 2375 2834 3312

F-gases remained in one MAC (%)

40% 40% 40% 40% 40% 40% 40% 40% 40% 40% 40% 40% 40% 40% 40%

Remained f-gases in

annually disposed MACs (kg)

2.638 401.638 555.758 752.097 1010.385 1429.463 2164.658 3198.289 4502.569 5259.338 5400.103 5005.430 5476.191 6172.669 6940.827

Leakage from disposal (%)

100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

HFC-134a disposal emissions (t)

0.003 0.402 0.556 0.752 1.010 1.429 2.165 3.198 4.503 5.259 5.400 5.005 5.476 6.173 6.941


484

Table 14 HFC–227ea emission estimation from fire extinguishing equipment

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Amount of HFC-

227ea in installed equipment (t)

0.2435 0.2435 0.6085 1.232 0.793 0.2775 0.7635 1.2495 1.7355 2.2215 2.7075 3.1935 3.6795

Amount of HFC-

227ea held in containers (t)

195.5 195.5 195.5 195.5 195.5 195.5 195.5 195.5 195.5 195.5 195.5 195.5 195.5

Leakage from installed equipment (%)

5% 5% 5% 5% 5% 5% 5% 5% 5% 5% 5% 5% 5%

Emission from stocks (t)

9.78718 9.78718 9.80543 9.83660 9.81465 9.78888 9.81318 9.83748 9.86178 9.88608 9.91038 9.93468 9.95898


485

A.3.5 Agriculture

Distribution of liquid manure management system in agriculture sector,

1990-2013 (share)

LIQUID

SYSTEM

Dairy

Cattle

Non-

dairy

Cattle

Sheep Goats Horses Swine Poultry Rabbits

Fur-

bearing

animals

1990 0.035 0.021 NO NO NO 0.460 0.390 NO NO

1991 0.035 0.021 NO NO NO 0.460 0.390 NO NO

1992 0.035 0.021 NO NO NO 0.460 0.390 NO NO

1993 0.035 0.021 NO NO NO 0.460 0.390 NO NO

1994 0.035 0.021 NO NO NO 0.460 0.390 NO NO

1995 0.035 0.021 NO NO NO 0.460 0.390 NO NO

1996 0.035 0.021 NO NO NO 0.460 0.390 NO NO

1997 0.035 0.021 NO NO NO 0.460 0.390 NO NO

1998 0.035 0.021 NO NO NO 0.460 0.390 NO NO

1999 0.035 0.021 NO NO NO 0.460 0.390 NO NO

2000 0.123 0.086 NO NO NO 0.425 NO NO NO

2001 0.133 0.095 NO NO NO 0.485 NO NO NO

2002 0.125 0.088 NO NO NO 0.548 NO NO NO

2003 0.13 0.091 NO NO NO 0.600 NO NO NO

2004 0.14 0.098 NO NO NO 0.656 NO NO NO

2005 0.153 0.107 NO NO NO 0.694 NO NO NO

2006 0.195 0.137 NO NO NO 0.774 NO NO NO

2007 0.205 0.144 NO NO NO 0.801 NO NO NO

2008 0.225 0.155 NO NO NO 0.808 NO NO NO

2009 0.238 0.167 NO NO NO 0.818 NO NO NO

2010 0.251 0.186 NO NO NO 0.832 NO NO NO

2011 0.265 0.193 NO NO NO 0.841 NO NO NO

2012 0.283 0.209 NO NO NO 0.853 NO NO NO

2013 0.276 0.214 NO NO NO 0.794 NO NO NO

Distribution of solid manure management system in agriculture sector,

1990-2013 (share)

SOLID

STORAGE

Dairy

Cattle

Non-

dairy

Cattle


Fur-

bearing

animals

1990 0.565 0.527 0.575 0.575 0.493 0.540 0.610 1 1

1991 0.565 0.527 0.575 0.575 0.493 0.540 0.610 1 1

1992 0.565 0.527 0.575 0.575 0.493 0.540 0.610 1 1

1993 0.565 0.527 0.575 0.575 0.493 0.540 0.610 1 1

1994 0.565 0.527 0.575 0.575 0.493 0.540 0.610 1 1

1995 0.565 0.527 0.575 0.575 0.493 0.540 0.610 1 1

1996 0.565 0.527 0.575 0.575 0.493 0.540 0.610 1 1

1997 0.565 0.527 0.575 0.575 0.493 0.540 0.610 1 1

1998 0.565 0.527 0.575 0.575 0.493 0.540 0.610 1 1

1999 0.565 0.527 0.575 0.575 0.493 0.540 0.610 1 1


486

SOLID

STORAGE

Dairy

Cattle

Non-

dairy

Cattle


Fur-

bearing

animals

2000 0.614 0.366 0.400 0.700 0.500 0.538 0.915 1 1

2001 0.608 0.362 0.400 0.700 0.500 0.482 0.921 1 1

2002 0.612 0.365 0.400 0.700 0.500 0.424 0.923 1 1

2003 0.609 0.364 0.400 0.700 0.500 0.375 0.926 1 1

2004 0.602 0.361 0.400 0.700 0.500 0.322 0.929 1 1

2005 0.593 0.359 0.400 0.700 0.500 0.286 0.931 1 1

2006 0.563 0.345 0.400 0.700 0.500 0.212 0.932 1 1

2007 0.556 0.342 0.400 0.700 0.500 0.186 0.933 1 1

2008 0.542 0.338 0.400 0.700 0.500 0.178 0.936 1 1

2009 0.533 0.333 0.400 0.700 0.500 0.169 0.938 1 1

2010 0.521 0.325 0.400 0.700 0.500 0.156 0.655 1 1

2011 0.509 0.311 0.400 0.700 0.500 0.147 0.560 1 1

2012 0.503 0.304 0.400 0.700 0.500 0.134 0.522 1 1

2013 0.490 0.358 0.400 0.700 0.500 0.105 0.665 1 1

Distribution of pasture, range and paddock as manure management system in

agriculture sector, 1990-2013 (share)

PASTURE

RANGE AND

PADDOCK

Dairy

Cattle

Non-

dairy

Cattle


Fur-

bearing

animals

1990 0.400 0.452 0.425 0.425 0.507 NO NO NO NO

1991 0.400 0.452 0.425 0.425 0.507 NO NO NO NO

1992 0.400 0.452 0.425 0.425 0.507 NO NO NO NO

1993 0.400 0.452 0.425 0.425 0.507 NO NO NO NO

1994 0.400 0.452 0.425 0.425 0.507 NO NO NO NO

1995 0.400 0.452 0.425 0.425 0.507 NO NO NO NO

1996 0.400 0.452 0.425 0.425 0.507 NO NO NO NO

1997 0.400 0.452 0.425 0.425 0.507 NO NO NO NO

1998 0.400 0.452 0.425 0.425 0.507 NO NO NO NO

1999 0.400 0.452 0.425 0.425 0.507 NO NO NO NO

2000 0.263 0.548 0.600 0.300 0.500 0.037 0.085 NO NO

2001 0.259 0.543 0.600 0.300 0.500 0.033 0.079 NO NO

2002 0.263 0.547 0.600 0.300 0.500 0.028 0.077 NO NO

2003 0.261 0.545 0.600 0.300 0.500 0.025 0.074 NO NO

2004 0.258 0.541 0.600 0.300 0.500 0.022 0.071 NO NO

2005 0.254 0.534 0.600 0.300 0.500 0.020 0.069 NO NO

2006 0.242 0.518 0.600 0.300 0.500 0.014 0.068 NO NO

2007 0.239 0.514 0.600 0.300 0.500 0.013 0.067 NO NO

2008 0.233 0.507 0.600 0.300 0.500 0.014 0.064 NO NO

2009 0.228 0.500 0.600 0.300 0.500 0.013 0.062 NO NO

2010 0.223 0.486 0.600 0.300 0.500 0.012 0.045 NO NO

2011 0.218 0.492 0.600 0.300 0.500 0.011 0.040 NO NO

2012 0.205 0.483 0.600 0.300 0.500 0.011 0.038 NO NO

2013 0.200 0.416 0.600 0.300 0.500 0.008 0.035 NO NO


487

Distribution of other management systems in agriculture sector,

1990-2013 (share)

OTHER,

Digester

Dairy

Cattle

Non-

dairy

Cattle


1990 NO NO NO NO NO NO NO NO



















2009 0.001 NO NO NO NO NO NO NO

2010 0.005 0.003 NO NO NO NO 0.300 NO

2011 0.008 0.004 NO NO NO 0.001 0.400 NO

2012 0.009 0.004 NO NO NO 0.002 0.440 NO

2013 0.034 0.012 NO NO NO 0.093 0.300 NO


488

ANNEX 4: THE NATIONAL ENERGY BALANCE FOR THE MOST RECENT INVENTORY YEAR

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NCV 39.35 45.54 43.97 43.21 43.21 43.2 42.49 40.6 41.86 41.86 41.86 41.86 41.86 29.23 24.06 10.05 15.49 26.79 34.41 27.98 17.05 30 0.03 0.04 19.03 20.49 19.02 14.4

Production 101 3 73277 71 2456 323 102 2270 58

Recycled products 29 29 84 85

Imports 86069 118 8530 9903 43 5920 43 55791 194 42 1841 3097 380 167 2858 42 26 58423 1692 308 1807 60 271 320

Imported for bunkering 9806 3148 6658

Exports 29062 118 4736 886 43 778 43 21372 919 0 167 192 42 26924 270 74 2225

Bunkering 9806 3148 6658

Interproduct transfers

Stock changes -299 46 -44 43 -425 -42 84 -3 42 240 -21 1 26 -7879 5061 -68 -4 80

Statistical difference 2537 309 2228 -275

Gross energy consumption 59274 3840 9282 5185 36222 194 42 880 3181 377 42 29 2906 80 4 52 50269 53106 392 1824 -210 264 631 323 102 2270 58

Transformation -232 -12 -107 -113 -485 -40 -34648 -11811 300 -189 -102 -2074 -29

electricity plants -144

public CHP -111 -9 -102 -409 -40 -29315 -4476 -18 -102 -1655

autoproducer CHP -860 -636 -171 -419

public heat plants -100 -4 -85 -11 -15 -3682 -4578

autoproducer heat plants -21 -8 -13 -61 -791 -1381 -29

production of peat briquettes


489

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charcoal production -596 300

Energy sector 255 255 929

Losses 1 20 275

Final consumption 58787 3828 9282 5185 35860 81 42 880 3181 377 42 29 2420 20 4 52 14417 41295 392 1824 90 264 631 134 196 29

Transport 44084 2368 8798 5185 26896 837 0 264 521

international air transport 5142 5142

domestic air transport 47 4 43

road transport 35454 2368 8794 23539 753 0 264 473

rail transport 3101 3017 84 48

inland shipping 340 340

pipeline transport

Industry and construction 6203 411 44 1996 81 42 3181 377 42 29 1406 20 4 52 5987 12880 392 1824 2 6

manufacture of metals 32 52 551

manufacture of chemicals and chemical products

179 137 42 20 378 208 6

manufacture of other fabricated metal products

138

manufacture of other non-

metallic mineral products 297 297 1299 1342 392 1824 0


490

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manufacture of transport

equipment 42 42 69 0

machinery 4 241 91

mining and quarrying 382 382 69 0

manufacture of food products,

beverages and tobacco 504 182 170 81 42 29 25 1686 429 0

manufacture of paper and paper products

103 97

manufacture of wood and of products of wood and cork

470 46 298 126 619 11722 0

construction 4036 46 44 765 3181 25 447 155 2

manufacture of textiles 25 275 0

manufacture of other products 293 42 251 69 178

Other sectors 8500 1049 440 6968 43 1014 8430 28415 90 108 134 190 29

other consumers - commercial and public sector

1921 91 88 1742 458 3510 3860 54 134 15

households 2237 911 264 1062 530 4266 24105 90


491

Oil

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s

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etr

ol

Petr

ol ty

pe j

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fuel

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pe j

et

fuel

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fuel

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aw

crop and animal production,

hunting and related service activities; forestry and logging

4043 46 88 3867 42 26 654 443 54 190 14

fishing 299 1 0 297 1 7


492

ANNEX 5: DETAILED DISCUSSION OF METHODOLOGY AND DATA FOR ESTIMATING CO2 EMISSIONS FROM FOSSIL FUEL COMBUSTION

Guidance manual for CO2 emission estimations

(Developed in accordance with UNFCCC and IPCC recommendations

and physical characteristics of fuels used in Latvia)

V.Bergmanis

Riga 2004


493

Annotation

The report is done in accordance with conditions of contract No. 15 of 17 May 2004. Guidance manual of CO2 emissions from stationary fuel combustion installations estimations

is developed in accordance to requirements from IPCC Guidelines. It means that according to developed guidance, CO2 emissions from every object could be determined using physical

characteristics of combusted fuel and amount of consumed fuel. In case such physical characteristics are not available, average estimated data for types of fuels used in Latvia could be used (Table 1).

Following additional information are given:

capacity of combustion installations,

particle content of fuel,

concept of heat of combustion and use of it in estimations

discretion in composition of thermal balance of combustion installation that provide better

understanding of combustion installations operations and processes that generate CO 2 emissions.

The report is developed to help enterprises that operate with combustion installations, Regional Environmental Boards (REB) and environment experts calculate CO2 emission from stationary fuel combustion.


494

Introduction

Guidance for practical determination of CO2 emission factors in the case of:

combusted type of fuel and physical qualities of it;

combusted amount of fuel,

is developed for enterprises to fulfil the requirements of national legislation (Cabinet of

Ministers Regulations ―About taxes of natural resources‖ and Cabinet of Ministers Regulation No. 555).

Stationary combustion installations are divided in:

boiler units – generation of electricity and heat for public utilities;

technological equipment combustion installations that are divided in:

installations where flue gases directly do not collide with produced products (mainly food industry – bread baking, malt drying;

Installations where flue gases directly collide with produced products (construction materials

and metal production).

In point 1 and 2.1 mentioned installations emission thresholds of noxious products are

determined and guidance of CO2 emission estimations could be used. In other cases technological specific of production should be taken into account.

Mathematical expression of CO2 emission determination given in first chapter is used in

specified calculation using data from fuel certificates and combusted amount of fuels. In cases when data from fuel certificates are not available (carbon content and net calorific value of

fuel), CO2 emission factors (Table 1) that are estimated using mathematical expression, IPCC Guidelines and average values of physical qualities of fuels used in Latvia are used.

In CO2 emission determination it is assumed that all carbon stored in fuel transforms into CO2

in combustion process. Practically part of carbon (depends on type of fuel, type of furnaces, maintenance conditions of boiler units) doesn’t burn fully and forms CO that transforms into

CO2 in length of time (approximately 48 h).

Consequently enterprise operating combustion installation and permit chemically incomplete combustion (q3) has to consume bigger amount of fuel to obtain necessary amount if heat and

therefore bigger amount of CO2 is generated.

Part of fuel did not participate in combustion processes. This part is composed by non-

combusted fuel (carbon) that is discharged from combustion installation with ashes, slag and soot. Non-combusted part of fuel is accounted as mechanically incomplete combustion losses q4 in thermal balance of combustion installation. These loses are rather big if solid fuels –

coal, peat, are combusted (ashes, slag), smaller – if liquid fuels are combusted (soot) and minimal – if gaseous fuels are combusted. For gaseous fuels q4 is technological losses

(maintenance of installations and safe work requirements provision) that are gas- fittings leakage in units processes to avoid possible explosions. In leakage process other greenhouse effect gas – methane, is emitted to atmosphere.

Brief discretion in particle content of organic fuel, relevance between fuel working, dry and combusted volumes, gross and net calorific values and suggestions in what cases previously

mentioned relevancies could be used in estimations are given in the report.


495

1. CO2 emission estimations for combusted organic fuels (guidance manual)

In combustion of organic fuels process carbon (C) in fuel connects with air oxygen as a result carbon dioxide (CO2) is made. In case of chemically incomplete combustion also carbon

monoxide (CO) is made that in approximately 48 h time connects with air oxygen and transforms in CO2.

To estimate CO2 emissions, it is necessary to know:

combusted type of fuel;

amount of combusted fuel Bn;

carbon content (Cd %) in working mass of fuel;

net calorific values of working mass of fuel (Qzd, MJ/kg (m3)).

Easier way to estimate CO2 emissions is to calculate emission factor (E) and consumed

amount of fuel (Bq) marked in heat amount units (MJ, GJ, TJ…. / time period). For E and Bq estimation necessary data is collected from fuel certificates (Quality note) or analyse data and accounting of combusted fuels.

For emission factor calculation following relevance is used:

6413,36100

10002

2

d

z

d

C

d

z

CO

d

COQ

C

MQ

MCEF

where:



3))


MCO2 – molecule weight for CO2 – 44, 0098 (g/mcl)

Mc – molecule weight for C – 12,011 (g/mcl)

1000 – switching from MJ to GJ

100 – percentage determination

Heat amount generated into furnaces with fuel is estimated:

d

znq QBB

where:

Bn – consumption of fuel in natural units in time period, tn (103

m3)

CO2 emissions in time period are estimated:

qCO BECO 22

where:

CO2 – estimated emissions, kg (t)

ECO2 – calculated emission factor, kg/GJ (t/TJ);

Bq - heat amount generated into furnaces with fuel, GJ (TJ).

Practically all amount of fuel input in furnaces doesn’t take part in combustion process. Part

of non-combusted fuels is discharged from furnace with ashes, soot and slag. These are so-called mechanically incomplete combustion losses. That’s why oxidation factor p has to be taken into account in CO2 emission estimations.

Oxidation factor:

100

100 4qp

Practically CO2 emissions:


496

pE=E2

COCO

,

2

If data from fuel certificates are not available, average data summarized in Table 1 could be

used in CO2 emission estimations. Data reported in table are estimated by using average data from fuel certificates of fuels used in Latvia and suggestions from IPCC Good Practice

Guidance and Uncertainty Management in National Greenhouse Gas Inventories.


497

Table 1 Carbon content in organic fuels working masses, net calorific values and CO2 emission factor

Type of fuel

Carbon content

Cd

%

NCV (Qzd)

MJ/kg

Emission factor without

oxidation factor (E CO2)

kg/GJ

Oxidation factor

(p)

Emission factor with oxidation

factor (EF CO2)

kg/GJ

Wood, Wd = 55% 20,11 6,70

* 109,98 0,98 107,78

Peat, Wd = 40% 29,07 10,05 106,07 0,98

** 103,95

Residual fuel oil 85,72 40,60 77,43 0,99 76,65

Diesel o il, liquid oven fuel 86,68 42,49 74,81 0,99 74,06

Motor gasoline (for off-roads****

) 83,13 43,97 69,33 0,99 68,64

Natural gas 51,54 33,66***

55,54 0,995 55,26

LPG 77,99 45,54 62,80 0,995 62,49

Shale oil 82,82 39,35 76,19 0,99 75,43

Coke 63,87 26,79 88,43 0,98 85,68

Lubricants 83,77 41,86 73,33 0,99 72,60

Other kerosene 85,17 43,20 72,30 0,99 71,58

Jet fuel 85,18 43,21 72,29 0,99 71,57 * for wood – Qz

d ir TJ/1000m

3

** for electricity production p = 0,99

*** natural gas – Qz

d is MJ/m

3

**** off roads – vehicles not involved in traffic, for example, asphalt pavers, and other commercial and household technological equipment, fo r example, grass rollers


498

Emission factor values (EnCO2) that are determined for natural unit of consumed amount of

fuel – t, (1000 m3) could be used equally in CO2 emission estimations. These values are reported in Table 2.

Table 2 CO2 emission factors for natural units of organic fuel

Type of fuel En

CO2, kg/t (1000 m3)

Coal 2417

Wood, Wd = 55% 722

Peat, Wd = 40% 1044

Residual fuel oil 3110 Diesel oil, liquid oven fuel 3144

Motor gasoline (for off-roads) 3016

Natural gas 1879

LPG 2844

Shale oil 2968

Coke 2294

Lubricants 3039

Other kerosene 3090

Jet fuel 3089

Following relevance for very approximate (control) CO2 emission estimations could be used:

0366413,0100

2

d

n

C

CO

d

n

k CBM

MCBE

where:

Bn – consumed natural units amount of fuels, t (1000 m3)

Cd – carbon content in working mass of fuel, %

Note: CO2 emissions of renewable energy resources are not estimated. Emission factors given in Table 1.1 and Table 1.2

could be used as comparative values.

4. Explanation and suggestions

1. In IPCC methodology it is determined that in each country all available data have to be

used in estimation of CO2 emission factors for different fuel types and only when these data aren’t available data from methodology could be used. It was taken into account when CO 2

emission factors for fuels used in Latvia were estimated.

2. Country’s average CO2 emission factors are estimated using actual data of fuel consumption and types [L1 chapter 1.2.1]. These data are obtained by Central Statistical

Bureau of Latvia. Also in L1 it is stated that only part of fuel consumption used for acquisition of Energy has to be taken into account instead of the part that is used in

technological processes. In the same chapter it is stated that amount of all combusted fuel types has to be estimated by using the same output measures. In the energy balance prepared by Central Statistical Bureau fuel consumption is estimated by using net calorific value of

working volume of each particular type of fuel Qzd, but for natural gas – gross calorific value

Qa (it is recommendation of EUROSTAT). It has to be taken into account in estimation of

total country’s CO2 emissions.

3. In total amount of CO2 emissions leakage of gas (ventilation and technological losses) in the extraction fields of coal-gas aren’t taken into account. It is referable to the exploitation of

natural gas utilization equipment. Oxidation coefficient for the gaseous fuels is used in the estimation of CO2 emissions. Leakage of gas is accounted as fugitive CH4 emissions.

5. In cases if net calorific values of fuels Qzd aren’t available but only Qa data it is possible to

use average values in the estimation [L1]:

for liquid and solid fuels Qzd ~ 0, 95 Qa

for gaseous fuels Qzd ~ 0,9 Q


ANNEX 6: OTHER

Additional information on CSB Integrated Statistical Data Management System (ISDMS)

ISDMS contents:

Following business application software modules are covering and supporting all phases of the statistical data processing:

Core metadata base module – the key part of the system ensures metadata collection and storage, defines all entire system processes starting from data collection and ending with output reports preparation. All System software modules are linked with the Core Metadata

module.

Registers module – ensure system users with the full range of respondents data.

Data entry and validation module – generates date entry and validation applications, executes validation and data editing processes and storage clean data sets in the Micro Data Base.

Web based data collection module – ensures electronic data collection via Web.

Data aggregation module – ensures data aggregation on different conditions and storage of the aggregated data sets in the Macro Data Base.

Data analysis module – via micro data export to MS Excel and/or Access ensures data analysis processes, MS OLAP tools are available for data analysis as well.

Data dissemination module – ensures data storage for publication at CSB web.

User’s administration module – administrates user roles and rights.

ISDMS advantages:

Standardized data entry, processing and storage procedures => process oriented data processing.

Centralized processing and storage of all types of statistical data, including metadata, by using data warehouse technologies and OLAP tools.

The system is connected to Business Register => direct respondent basic data retrieval and updating.

Special import and export procedure is created for data exchange with other systems.

A link with PC Axis is created for electronic data dissemination.

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