An introductionto the monitoring of

forestry carbon sequestration projects

Developing Forestry and Bioenergy Projects within CDM

EcuadorMarch, 2004

Igino M. Emmer PhDFace Foundation

F orestsA bsorbingC arbon dioxideE mission

The Netherlandsarea: 5.000 hastart: March 1992

Czech-RepublicKRNAP/NPSarea: 14.000 hastart: October 1992

Sabah-MalaysiaInfaproarea: 14.000 hastart: July 1992

EcuadorProfaforarea: 75.000 hastart: June 1993 Uganda

UNP-Facearea: 27.000 hastart: August 1994

Overview of the Face projects

Contents

• Introduction

• Basic principles of carbon monitoring in forests

Introduction

What is carbon monitoring in forests?

Forest carbon monitoring quantifies changes in carbon stocks in various carbon pools of the forestby repeated measurement

Why carbon monitoring?- Transparency and credibility- Verification (see project cycle)- Compliance versus voluntary

• COP 9

• IPCC GPG LULUCF

• Large versus small-scale projects

Monitoring plan

• Contents (CDM EB):- GHG baseline and with-project- Archiving- Nature and quality of methodologies- Remedial measures for negative

impacts

• This introduction: carbon monitoring in CDM AR

Good Practice

• Intergovernmental Panel on Climate Change Good Practice Guidance for Land Use, Land Use Change and Forestry- Revised 1996 IPCC Guidelines for

National Greenhouse Gas Inventories

- National inventories and projects

• Winrock International and others

Basic principles of carbon monitoring

• First considerations for planning

• Data requirements

• Tools for data collection

• Carbon calculations

• Leakage, risks and uncertainties

First considerations for planning

• Greenhouse gasses involved

• Baseline versus with-project scenario

• Required frequency

• Availability of expertise

• Costs

Greenhouse gasses involved

• CO2 (1 CO2e)

• CH4 (23 CO2e)

• N2O (296 CO2e)

Baseline versus with-project scenario

• Baseline may become counterfactual

• Plot selection

• Modelling

Required frequency

• Lomax: lowest cost/effort, maximum result

• Carbon monitoring vs research

• CDM AR: 5-year intervals

• Just before verification

• Statistics- Stock changes versus variability

Stock changes versus variability

Project design: COProject design: CO22 Uptake Over TimeUptake Over Time

0

100

200

300

400

500

0 10 20 30 40 50 60 70 80

Time (years)

Sh

ort

to

ns

CO

2 /

acre

1

High variability + small average change:large sample size

Measurement year

2002 2012

Car

bon

co

nten

t (un

it)

Pre-defined precision and accuracy

• Precision: e.g. measuring a stem diameter

• Accuracy: assessing the carbon stored in the forest

Can be found in the IPCC GPG LULUCF

Availability of expertise: fields

• Forestry, terrain knowledge

• Sampling design and statistics

• Logistics

• Supervision and quality control

Costs

• Labour intensive, time consuming: may easily become expensive

• Lomax- Pre-monitoring intelligence- Pilot sampling

• Relation with market price of CO2e

(end of considerations)

Data requirement

• 50% of biomass is carbon (C)

• Carbon pools- Above-ground biomass- Below-ground biomass- Soil carbon- Litter

Pools to be involved

• In principle all carbon pools within the project boundary must be considered

• Only if transparent and verifiable information is provided, pools that are shown not to be a source may be excluded from the monitoring

Above-ground biomass

1 .3 m1 .3 m

1 .3 m1 .3 m

1 .3 m

1 d ia m e te rs t

2 d ia m e te rnd

1 .3 m1 .3 m

tw o m easurem ents

Above-ground biomass

allometric biomass regression equation:

B = a + b * D2 * H

where

B: biomass (kg)

D: stem diameter (cm) at breast height (1.3 m)

H: total height (m)

a-b: regression parameters from the data, depending on tree species and site conditions

Below-ground biomass

• Average below-ground to above-ground ratio for tropical, boreal and temperate forest (IPCC) = 0.26

• Varying little among latitudes (boreal-temperate-tropical) or soil texture

• IPCC guidelines: ‘given the lack of standard methods and the time-consuming nature of monitoring below-ground biomass in forests, it is good practice to estimate below-ground biomass from either estimated aboveground biomass based on various equations or from locally derived data’

Soil carbon

A general formula for calculating soil organic carbon:

 

SOC = [SOC] * BulkDensity * Volume * (1-CoarsFragments)

 

where

SOC: soil carbon stock (Mg C/ha)

[SOC]: concentration of soil carbon (g C/kg)

BulkDensity (Mg/m3)

CoarseFragments: fraction in %

Tools for data collection

Good monitoring depends on

• An adequate land classification scheme

• An appropriate spatial and temporal resolution

• A proper standard for precision and accuracy

• A transparent methodology

• Measures to assure consistency and availability over time

Remote sensing

• Air photography

• Satellite imagery

• Radar

Ground-based surveys; sampling design

• Ground-based surveys require field visits for measuring selected attributes

• The way these attributes are measured in terms of ‘how many times’ and ‘where’ is the sampling design

• The sampling design must- prevent any bias in measurements- allow for efficient execution of the work- allow for independent verification

Sampling design

• Complete enumeration

• Simple random sampling

• Systematic sampling

• Stratified random sampling

Precision, Accuracy, Lomax

Sampling unit

• Plot (permanent or temporary)

• Pre-defined constant area (tonnes C/ha)

• Permanent plots:- Better quantification of stock

changes- Independent verification

Sample grid

Sample size versus precision level

Equipment

Carbon calculations

• Carbon stocks

• Sample size

• Time intervals

Other issues

• Leakage- Monitoring within project

boundaries

• Risks and uncertainties- Assessment- Mitigation