Diffuse Air Emissions in E-PRTR · 2019-07-26 · maps of different spatial scaleand corresponding...

Thomas Gauger:

Overview on data compilation and gridding

"Diffuse Air Emissions in E-PRTR" DG Environment (No 070307/2009/548773/SER/C4)

E-PRTR Expert Group Meeting on emission releases from diffuse sources

Brussels, Belgium22 October 2010

Thomas Gauger, Institute of Navigation, Universität Stuttgart (INS)[email protected]


data needed for mapping/gridding:

• emission data:

- (sub-)sectoral national emission totals per pollutant

• proxy data:

- statistical data for regionalisation of emission activities

- geo reference data for spatial allocation

data compilation and gridding diffuse air emissions

maps of different spatial scale and corresponding interpretation levels:


high resolution gridding of diffuse air emissions in 5 x 5km² grid resolution (regional to local scale)

additional high resolution information is needed when ‘scale down’ procedures are applied:



general methodology for the spatial distribution of emissions:

source: B. Thiruchittampalam 2010, modified

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griddedsmall scale

annual emission

emission data &emission sources

geo referenced (spatial) statistics

spatial allocation(grid attributes)

mapping(geo database)

data abstraction data attribution spatial distribution mapping result

source: B. Thiruchittampalam 2010, modified

spatial allocation of emission data to a high resolution grid using GIS technique:


Target spatial resolution and georeference:5x5 km² grid cell layers in WGS84:EPSG

Pollutants [units: Gg]CO - Carbon monoxide SO2 - Sulphur dioxideCO2 - Carbon dioxide NOX - Nitrogen oxidesNH3 - Ammonia PM10 - Particulates (≤10 µm)

Emissions from diffuse sources- transport activities: on-road transport, national and international shipping, and domestic aviation- stationary commercial and residential combustion, - industrial releases from Annex 1 of the E-PRTR Regulation below the capacity thresholds (Annex 1)and release thresholds (Annex 2) of the Regulation and

- agricultural activities (NH3, PM10)

Coverage and data (on land, 31 countries, and sea)- EU27 member states [AT, BE, BG, CY, CZ, DK, EE, FI, FR, DE, GR, HU, IE, IT, LT, LV, LU, MT, NL, PL, PT, RO, SK, SI, ES, SE, UK]

- EFTA countries [CH, LI, NO, IS]

+ Sea (national and international shipping routes)

other standards & references- NFR_02/NFR_08 and/or CRF emission sector structure reference (CLRTAP and UNFCCC) - NUTS country geo code standard reference (regions, country territories)- VLIZ and EAA maritime boundaries and territorial water

spatial distribution of diffuse emissions in Europe –definitions and data compilation

source: http://ec.europa.eu/eurostat/ramon/nuts/home_regions_en.html

nomenclature of territorial units for statistics, NUTS, and the statistical regions of Europe:

spatial distribution of diffuse emissions in Europe –definitions and data compilation: proxy data


Main proxy datasets for spatial distribution:

- CORINE LAND COVER land use data: CLC2000/CLC2006/CLCCH1990 (100x100m², 250x250m², 1x1km²)

- EUROSTAT statistical data on animal density, population, employees, traffic (aviation, ports) etc.

- SEDAC and CIESCIN data on population

- GISCO data on ports and airports

- TREMOVE, TRANS-TOOLS, VNF and OSM data on traffic networks (roads/rivers), traffic volume

- APMoSPHERE data on international shipping

- USGS, MROS and other data sets for allocation of industrial processes and energy production

spatial distribution of diffuse emissions in Europe –definitions and data compilation: main proxy data

spatial distribution of diffuse emissions in Europe –technical data model defining and linking different data used

source: B. Thiruchittampalam 2010

12

Landcover data(different sources)

landcover type „Industrial or commercial units“

Number of employees by activity branches

(NUTS 3)

1 km x 1km Grid for EU(ArcGIS 9.3)

Georeferenced maps –NUTS levels(ArcGIS 9.3)

regional GIS data

basic vector grid

CORINEland cover

dataEUROSTAT

data etc.

5x5km² grid (EU27 & EFTA4,

land & sea)

NUTS (level 0/1/2/3)

proxy - data

input data and databases

Intersection: 5km x 5km grid with the maps for the different NUTS-levels for each country

Visualisation: Number of employees by activity branches on NUTS 3

Visualisation: Landcover data (CORINE 2000/2006, Global Land Cover)

Zonal statistics procedure(calculate the landcover types in

each gid cell/polygon)

spatial calculation

intersection: 5km x 5km grid ∩ NUTS 3 level

mappingactivity on NUTS 3

mapping: sector specific land cover data

zonal statistics:land cover classes per grid cell

high resolutionemission maps of diffuse sources

MySQL calculationspatial distribution

Regionalisation of the emission values on NUTS 3 level –

based on the number of employees by activity branches

Spatial distribution of the Emission valeus

from NUTS 3 level to 5 km x 5 km grid cell

based on the share of the landcover type

„Industrial and commercial“

within each grid cell/polygon

regionalisation

of emission values on NUTS 3 level

spatial distribution

of emission values

to 5 km x 5 km grid cells

using fractions of land cover class

general concept for spatial distribution of diffuse emissions


mapping and high resolution gridding of diffuse air emissions

mapping result

source: M. Usbasich 2010, modified


data abstraction: data abstraction: emission data and emission sources emission data and emission sources

real world object groups are differentiated into GIS objects; real world object groups are differentiated into GIS objects; data retrieval is carried outdata retrieval is carried out

national total emission data are abstracted (differentiated) into point, line, and area sources

- facility, network, and area definition for each sector/source category is carried out- the respective geo-referenced statistical data are retrieved- data analysis on quality (completeness and actuality) is carried out

spatial allocation of emission data on a small scale (high resolution) grid using GIS (1)

data abstraction: facility, network, area definition for sector/source categories

all sector/source categories are differentiated into point, line, and polygon features before allocation and representation in target grid cells is carried out-------------------------------------------------------------------------------------------Geographic features

Point sources: a point source can be any emission represented by x and y coordinates. This should represent the main point of emission (i.e. a stack on an industrial site).

Area sources:this is a description given to a source that exhibits diffuse characteristics. For example, sources that are too numerous or small to be individually identified as point sources or from which emissions arise over a large area. This could include forests, residential areas and administrative/commercial activities within urban areas. Area sources as polygons: area polygons are often used to represent data attributed to administrative or other types of boundaries (data collection boundaries, site boundaries and other non-linear or regular geographical features).

Line source:a description given to a source that exhibits a line type of geography, e.g. a road, railway, pipeline or shipping lane, etc. Line sources are represented by vectors with a starting node and an end node specifying an x,y location for each. Line source features can also contain vertices that define curves between the start and end reference points.

[Text from EMEP/EEA emission inventory guidebook 2009, (p 5-7)]


[Figures: Wickert 2001]


overlay, intersect: overlay, intersect: spatial allocation of geo referenced (spatial) statistic data spatial allocation of geo referenced (spatial) statistic data on emission sourceson emission sources

differentiated objects (emission source) data:differentiated objects (emission source) data:GIS data input and storage is carried outGIS data input and storage is carried out

point, line, polygon emission source objects are attributed to raster cell layers with common [ID], and [NUTS code] primary attribute values;the spatial distribution of (proxy) objects within grid cells is derived

- facility, network, and area allocation data processing consists of -- data input into GIS -- transformation into standard projection -- allocation into basic high resolution grid layer

(linking basic grid cell IDs as 1st level grid cell attributes)



Spatial distribution of diffuse emissions in Europe

• Mapping domain and basic data

Spatial resolution and georeference:5x5 km² grid in CGS ERTS LAEA[converted into WGS84, EPSG:4326]

Attributes: � Grid_CODE ID of 5x5km² grid cells

ID: 1, (…), 2.408.448 (1x1km² grid: 1, (…), 60.221.200)

Coverage and data (31 countries, land & sea areas):- EU27 member states:

AT, BE, BG, CY, CZ, DK, EE, FI, FR, DE, GR, HU, IE, IT,

LT, LV, LU, MT, NL, PL, PT, RO, SK, SI, ES, SE, UK

- EFTA4 countries:CH, LI, NO, IS

+ Sea: international shipping routes, territorial waters (coastal shipping)

other standards & references- NUTS country geo code standard reference

for EU27 and EFTA4 countries- VLIZ and EAA territorial water, maritime boundaries

overlay and intersection of layers for gridding: spatial allocation (and distribution) of (proxy) objects within grid cells---------------------------------------------------------------------------------------------------------------

Grid_code ID with NUTS code attribution

_______________________________________________________________________________________example: point source attribution to grid cell(s)

object � grid representation

NUTS layer target grid layer{overlay, intersect}:

grid cell ID NUTS codes attributed


emission source locality �

emission source locality can beattributed in terms of e.g.an index (ID) for point sources,grid area fraction for area sources,or grid fraction for line sources,respectively.


zonal fractions: zonal fractions: spatial allocation of data (as grid attributes)spatial allocation of data (as grid attributes)

data transformation, query, and analysis is carried outdata transformation, query, and analysis is carried out

- gridded weighting factors are calculated and attributed to grid cells[relative (proxy) object fraction of NUTS total per grid cell]

- gridded proxy data layers are generated (2nd level grid cell attributes)


grid cell ID�

�grid cell attributes

grid cell ID�


zonal fractions: gridded proxy data layers are generated:“gridded weighting factors” are calculated and attributed to all grid cells[“relative (proxy) object fraction of NUTS total” per grid cell]----------------------------------------------------------------------------------------------------------------


[Figure: Wickert 2001]

grid cell ID�


α = 1

α = 0.3

α = 0.65

relative (proxy) object fraction of NUTS total emission per cell(e.g. percentage of national total emission) is calculated in and attributed to the respective proxy grid layers using informationon locality of sources and geospatial statistics (proxy data)

zonal fractions: gridded proxy data layers are generated“gridded weighting factors” are calculated and attributed to all grid cells[“relative (proxy) object fraction of NUTS total” per cell]; ----------------------------------------------------------------------------------------------------------------


where: • i: is a specific geographic feature (emitting objects);

• emissionix: is the emissions attributed to a specific geographical feature (e.g. a grid, line, point or administrative boundary) within the spatial surrogate dataset x;

• emissiont: is the total national emission for a sector to be distributed across the national area using the (x) surrogate spatial dataset;

• valueix – jx are the surrogate data values of each of the specific geographical features within the spatial surrogate dataset x.


model result:model result:emission mapping, emission geo database is generatedemission mapping, emission geo database is generated

- emission per grid cell is calculated using “gridded weighting factors”[total NFR/CRF per sector · “fraction of NUTS total” per cell]

- gridded emission data layers are generated (final cell attributes)


model result: emission (density) is calculated using “gridded weighting factors”[total NFR/CRF per sector · “fraction of NUTS total” per cell]; gridded emission data layers are generated (final cell attributes)----------------------------------------------------------------------------------------------------------------


where: • i: is a specific geographic feature (emitting objects);

• emissionix: is the emissions attributed to a specific geographical feature (e.g. a grid, line, point or administrative boundary) within the spatial surrogate dataset x;

• emissiont: is the total national emission for a sector to be distributed across the national area using the (x) surrogate spatial dataset;

• valueix – jx are the surrogate data values of each of the specific geographical features within the spatial surrogate dataset x.

model result: emission (density) is calculated using “gridded weighting factors”[total NFR/CRF per sector · “fraction of NUTS total” per cell]; gridded emission data layers are generated (final cell attributes)----------------------------------------------------------------------------------------------------------------agricultural emissions of NH3, Germany (fictive example for illustration):


500kt


- Gridded European high resolution maps of diffuse emissions of NOX, SO2, PM10, CO and CO2 are calculated covering 31 EU27 and EFTA4 countries and the surrounding sea

- Emissions from diffuse sources include:- on-road transport, national and international shipping, and domestic aviation- stationary commercial and residential combustion - diffuse industrial releases- agricultural activities (NH3, PM10)

- The methodological approach is based on up-to-date state of the scientific and technical knowledge including improvements in terms of maximum elaborateness, actuality, and accuracy on the whole European scale

conclusions

Thank You for Your attention!


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Diffuse Air Emissions in E-PRTR · 2019-07-26 · maps of different spatial scaleand corresponding...

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