harnessing the carbon market to sustain ecosystems and alleviate poverty draft redd methodology...
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Harnessing the carbon market to sustain ecosystems and alleviate poverty
Draft REDD Methodology
BioCarbon Fund
Workshop, February 5 – 8, 2008
History and Plan2007:• 1st Draft• Reviewers: Ben de Jong, Bernhard Schlamadinger, Tim
Pearson + Comments from Andrea Garcia and Marc Steiniger
2008:• January: 2nd Draft• February: Comments from WB colleagues
Finalized 2nd Draft• March: 2nd round of comments by reviewers• June: 3rd draft submitted to VCS?
Existing guidanceIPCC (www.ipcc.ch):• Revised 1996 GL for National GHG Inventories. • 2003 GPG for Land Use, Land Use-Change, and Forestry .• 2006 GL for National GHG Inventories, Vol. 4, Agriculture, Forestry
and Other land Uses (AFOLU).
Winrock International (www.winrock.org):• Reducing GHG Emissions from Deforestation and Degradation in
Developing Countries: a Sourcebook of Methods and Procedures for Monitoring, Measuring and Reporting.
• Land Use, Land Use Change and Forestry Projects.
Voluntary Carbon Standard (www.v-c-s.org):• Guidance for Agriculture, Forestry and Other Land Use Projects
Issues
• Insufficient policy guidance on critical methodological issues:– Definitions (forest, deforestation, degradation)– Project and Baseline Emissions– Emissions from land-use after deforestation– Leakage (types, attribution, assessment)– Etc.
• Components of a baseline– Quantity– Location– Carbon stock changes
Applicability conditions
(a) Only “gross deforestation”.
(b) Deforestation agents, drivers and underlying causes can be identified.
(c) Deforestation and forest degradation agents are bound to a certain region and cannot migrate beyond that region.
(d) Information on forest cover and forest status before the start of the project activity is available for at least two points in time.
(e) Information on land use-use and land-cover on deforested land before the start of the project activity is available.
Step 1. Define the boundaries of the proposed REDD project activity: spatial, temporal, carbon pools and sources of greenhouse gas emissions.
Step 4. Project the quantity of future deforestation and forest degradation
Step 3. Analyze agents, drivers and underlying causes of deforestation and forest degradation
Step 5. Project the location of future deforestation and forest degradation by analyzing the spatial correlation between historical land-use and land-cover change and biogeophysical and socioeconomic factors (vicinity to roads, slope, population density, etc.)
Step 7. Estimate the expected baseline carbon stock changes and non-CO2 emissions.
Step 2. Analyze historical land-use and land-cover change in the reference region during the past 10-15 years and project potential forest regeneration.
Approach a: Linear projection. Deforestation and forest degradation are linearly projected from observed historical trends.
Approach c: Corridor. Deforestation and forest degradation are projected as a likelihood corridor to reflect uncertainty.
Step 6. Project future baseline activity data (the land-use and land-cover change component of the baseline) by combining the results of steps 2, 4 and 5.
Step 10. Calculate the expected ex ante net anthropogenic GHG emission reductions.
Step 8. Estimate the expected actual carbon stock changes and non-CO2 emissions.
Step 9. Estimate the expected leakage carbon stock changes and non-CO2 emissions.
Approach b: Multiple regression. Deforestation and forest degradation are projected using multiple regression.
Select the applicable baseline approach and justify the choice.
Step 1. Define the boundaries of the proposed REDD project activity: spatial, temporal, carbon pools and sources of greenhouse gas emissions.
Step 4. Project the quantity of future deforestation and forest degradation
Step 3. Analyze agents, drivers and underlying causes of deforestation and forest degradation
Step 5. Project the location of future deforestation and forest degradation by analyzing the spatial correlation between historical land-use and land-cover change and biogeophysical and socioeconomic factors (vicinity to roads, slope, population density, etc.)
Step 7. Estimate the expected baseline carbon stock changes and non-CO2 emissions.
Step 2. Analyze historical land-use and land-cover change in the reference region during the past 10-15 years and project potential forest regeneration.
Approach a: Linear projection. Deforestation and forest degradation are linearly projected from observed historical trends.
Approach c: Corridor. Deforestation and forest degradation are projected as a likelihood corridor to reflect uncertainty.
Step 6. Project future baseline activity data (the land-use and land-cover change component of the baseline) by combining the results of steps 2, 4 and 5.
Step 10. Calculate the expected ex ante net anthropogenic GHG emission reductions.
Step 8. Estimate the expected actual carbon stock changes and non-CO2 emissions.
Step 9. Estimate the expected leakage carbon stock changes and non-CO2 emissions.
Approach b: Multiple regression. Deforestation and forest degradation are projected using multiple regression.
Select the applicable baseline approach and justify the choice.
Ex ante methodology steps
Ex ante methodology steps
Ex ante = before validation
Ex ante = before validation
Ex post methodology steps
Ex post methodology steps
Step 1. Define the boundaries of the proposed REDD project activity: spatial, temporal, carbon pools and sources of greenhouse gas emissions.
Step 3. Analyze agents, drivers and underlying causes of deforestation and forest degradation
Step 2. Analyze historical land-use and land-cover change in the reference region during the past 10-15 years and project potential forest regeneration.
Step 11. Project monitoring.
Step 13. Adjustment of the baseline for future crediting periods.
Step 12. Ex post calculation of net anthropogenic GHG emssion reduction
Ex post = during project implementation
Ex post = during project implementation
Step 1. Define the boundaries of the proposed REDD project activity.
1.1 Spatial boundaries
1.2 Temporal boundaries
1.3 Carbon pools
1.4 Sources of emissions and GHG
Reference region
= Forest to be protected / managed
= Area where pre-project activities could be displaced
= Domain from which information on DD agents, drivers and rates is extracted and projected.
Step 1. Define the boundaries of the proposed REDD project activity.
1.1 Spatial boundaries
Leakage belt
Project area
Step 1. Define the boundaries of the proposed REDD project activity.
1. 2 Temporal boundaries
time
Project start Project end
End of 1st crediting period and start of 2nd crediting period
End of 2st crediting period and start of 3rd crediting period
min 20
max 100 yrs
max 10
yrs
Start of the historical reference period
End of the historical reference period
10-15
yrs
Step 1. Define the boundaries of the proposed REDD project activity.
1. 3 Carbon pools
1. Above-ground biomass• Trees• Non-Trees
2. Below-ground biomass
3. Dead wood• Standing• Lying• Wood products
4. Litter
5. Soil organic carbon
Selection criteria:
• Principle of conservadurism.
• Expected magnitude of carbon stock change.
• Cost
Could be different carbon pools depending on the land-use/land-cover change category.
Trees Dead Wood
Soil Carbon
Non-treeVegetation
WoodProducts
Before Deforestation
After Deforestation
Car
bo
n S
tock
(Brown et al., 2007)
(Brown et al., 2007)
Car
bo
n S
tock
time
Trees
Non-Tree Vegetation
Dead Wood
Soil Carbon
Harvested wood
Step 1. Define the boundaries of the proposed REDD project activity.
1.4 Sources of emissions and GHG
Under the REDD activity scenario:
GHG emissions that would occur in the baseline are avoided.
GHG emissions due to project activities are likely to occur.
GHG emissions due to leakage are likely to increase.
• Conservatively ignore them.• Can count non-CO2
emissions from forest fire.
• Reasonably assume that project emissions are less than baseline emissions ignore.
• Leakage prevention measures and activity displacement may lead to significant GHG emissions consider.
Step 1. Define the boundaries of the proposed REDD project activity.
1.4 Sources of emissions and GHG
Source GHG Comment
Forest fires CH4 and N2O Avoided baseline emission
Fertilization N2O Leakage prevention measures
Enteric fermentation
CH4 Leakage prevention measures
Manure management
CH4 and N2O Leakage prevention measures
• Non-significant sources are omitted• Significance is tested using the EB-CDM approved tool
Step 2. Analysis of historical Land-Use and Land-Cover Change.
2.1 Select data sources
2.2 Define land-use/land-cover classes
2.3 Define LULC-change categories
2.4 Prepare LULC and LULC-change maps and LULC-change matrices
2.5 Assess map accuracy
2.6 Prepare a methodological annex
Step 2. Analysis of historical Land-Use and Land-Cover Change.
2.1 Select data sources
• Prefer existing LU/LC and LU/LC-change maps if they are already approved by the national authority and/or independently validated.
• Unclassified remotely sensed data (medium resolution – Landsat, Spot).
• Ground-truth data (high resolution remotely sensed data and/or field data).
Step 2. Analysis of historical Land-Use and Land-Cover Change.
2.2 Define land-use / land-cover classes
• Consistent with IPCC classes:- Forest Land - Wetland- Cropland - Settlement- Grassland - Other land
• Consult National GHG inventory for the definitions.
• Subdivide, as necessary, to build homogeneous carbon stock density classes.
Time
tCO2e ha-1
Undisturbed Forest
Initial degradation
Intermediate degradation
Advanced degradation
Forest Degradation
Forest Non- Forest
Carbon Density Classes
Degradation
tCO2e ha-1
TimeRecovered
ForestInitial
successionIntermediate succession
Advancedsuccession
Forest Plantation or Succession
ForestNon-Forest
Carbon stock enhancement(“Regeneration”)
Carbon Density Classes
Step 2. Analysis of historical Land-Use and Land-Cover Change.
2.3 Define LU/LC-change categories
Describe class transitions in case of degradation and carbon stock enhancement (= “ Forest Regeneration”).
Intact forest Cropland
Grassland
Wetland
Settlement
Other Land
Forest Land Non-Forest LandForest Regeneration
Forest Degradation
DeforestationDegraded forest
Managed forest
Non-Forest Degraded
ForestClass X
Forest
Non-Forest ForestClass X
Forest Regeneration
Class ANon-Forest
Degraded Forest
Class X
Forest Regeneration
Class B
Forest Regeneration
Class A
Degraded Forest Class X
Forest Regeneration
Class B
Regeneration (C-stock
enhancement)
Degradation Deforestation
Forest Regeneration
Class A
Forest Regeneration
Class B
Forest Regeneration
Class C
Forest Regeneration
Class D
Regeneration (C-stock
enhancement)
Degradation Deforestation
Forest Class X
Degraded Forest
Class Y
Possible class transitions during one crediting periodPossible class transitions during one crediting period
Step 2. Analysis of historical Land-Use and Land- Cover Change.
2.3 Prepare LU/LC and LU/LC-change maps and LU/LC-change matrices
• Forest cover benchmark map• Past and current LU/LC• Past LU/LC change• Potential forest regeneration map
2.5 Assess map accuracy
2.6 Prepare a methodological annex
Step 3. Analysis of agents, drivers, underlying causes and chain of events
3.1 Agents• Who is deforesting / degrading?
3.2 Drivers:• What drives the agents to cut the trees?
(a) Spatial variables (predisposing factors)(b) Economic and social variables.
3.3 Underlying causes:• Ultimate reasons explaining the drivers.
3.4 Chain of events:• Relationships between agents.• Typical sequence of events leading to
deforestation or degradation.
Step 4. Project the quantity of future deforestation and forest degradation
4.1 Analysis of remaining forest area that is suitable for conversion to non-forest use and logging activities
4.2 Selection of the baseline approach
4.3 Quantitative projection of future deforestation and forest degradation
Step 4. Project the quantity of future deforestation and forest degradation
4.1 Analysis of remaining forest area that is suitable for conversion to non-forest use and logging activities
Time
DD rates are likely to decrease once only “sub-optimal” areas remain available.
DD rates should decrease once only “marginal” areas remain available.
DD rates should be zero once no suitable area remains available.
DD rates are likely to continue at the historical level as long as “optimal” areas are available.Ha yr-1
Step 4. Project the quantity of future deforestation and forest degradation
4.2 Selection of the baseline approach
(a) Linear projection: Future deforestation and degradation is linearly projected from past trends.
(b) Modeling approach: Future deforestation and degradation is projected using multiple regression techniques (requires sufficient data points).
(c) Corridor approach:Future deforestation and degradation is projected as an average of the historical rate. The 90% confidence interval of the mean is calculated to determine a “corridor” of likely baseline deforestation and forest degradation.
Variable DD
Observed Projected
Approach b: Modeling approach
Monitoring and ex post adjustment (dynamic baseline)
time
ha
Constant DDDecreasing DDIncreasing DD
Observed ProjectedObserved Projected Observed Projected
Approach a: Linear projection
time
ha
time
ha
time
ha
Variable DD
Observed Projected
Approach c: Corridor approach
90% CI
time
ha
50% credit
0 credit
Full credit
Step 4. Project the quantity of future deforestation and forest degradation
4.3 Quantitative projection of future deforestation and forest degradation
Year Deforestation (ha) Degradation (ha)1
2
3
4
5
6
7
8
…
Project end
Step 5. Project the location of future deforestation and forest degradation
Distance to roads
Distance to roads
Deforestation in year 1
Deforestation in year 2
Deforestation in year 3
Deforestation in year …
Suitability
Road
Road
Step 5. Project the location of future deforestation and forest degradation
5.1 Create driver maps from spatial variables.
5.2 Create suitability maps for deforestation and for degradation.
5.3 Select the most accurate suitability map for deforestation and for degradation.
5.4 Locate future deforestation and forest degradation.
Slope Vicinity to roads
Logging areasLand allocation projects
Suitability Map
Spatial variables Driver Maps
CATIE Study in Costa Rica (1996-2006)
Ex post correlation with actual deforestation: r = 0.91 (p < 0.001)
Step 4
Step 5
Deforested Potential
Degradation Mapyear 1
Category 1 of Categorized
Potential Degradation Map
Area that would be degraded in
year 1
DeforestedPotential
Degradation Mapyear 2
Area that would be degraded in
year 2
Category 2 of Categorized
Potential Degradation Map
Deforested Potential
Degradation Mapyear 3
Area that would be degraded in
year 3
Category 3 of Categorized
Potential Degradation Map
Continue
Categorized Potential
Degradation. Map
In case that degradation is taken into account…
Step 5. Project the location of future deforestation and forest degradation
At the end of Step 5 we have:
Initial LU/LC Cover Map
Potential Forest Regeneration Map
Potential Deforestation Map
Potential Forest Degradation Map
From step 2
From step 2
From step 5
From step 5
Step 6. Project future land-use and land-cover change
6.1 Identification of LU/LC-change categories in “forest land remaining forest land”
• Forest degradation
• Forest regeneration (= carbon stock enhancement)
6.2 Identification of LU/LC-change categories in “forest land converted to non-forest land”.
• Deforestation
LU/LC-Map year 0
Potential Deforestation
year 1
Deforested LU/LC-Map
year 1
Potential Degradation
year 1 Deforested & Degraded LU/LC-Map
year 1
Potential Regeneration
year 1
D&D & Regenerated LU/LC-Map
year 1
Potential Degradation
year 2
Potential Deforestation
year 2
Deforested LU/LC-Map
year 2
Deforested & Degraded LU/LC-Map
year 2
Potential Regeneration
year 2
D&D & Regenerated LU/LC-Map
year 2
LU/LC-Map year 1
Continue with all future years
Step 2
Step 5
Step 6
6.1 Identification of LU/LC-change categories in “forest land remaining forest land”
Forest land remaining forest land: Forest Degradation
Project year
Forest A to
Degraded Forest A1
Forest B to
Degraded Forest B1
Forest C to
Degraded Forest C1
Degraded Forest A1
to Degraded Forest A2
Degraded Forest B1
to Degraded Forest B2
Degraded Forest B1
to Degraded Forest B2
Degraded Forest A2
to Degraded Forest A3
Degraded Forest B2
to Degraded Forest B3
Etc. (as
needed) Total
ha ha ha ha ha ha ha ha ha ha
1
2
3
…
n
Total crediting period
Total project duration
6.1 Identification of LU/LC-change categories in “forest land remaining forest land”
Degradation and carbon stock enhancement (“regeneration”).
Forest strata converted to non-forest land
Project year
Forest A Forest B Forest C Degraded Forest A1
Degraded Forest B1
Degraded Forest C1
Degraded Forest A2
Degraded Forest B2
etc. (as
needed) Total
ha ha ha ha ha ha ha ha ha ha
1
2
3
…
n
Total crediting period
Total project duration
6.1 Identification of LU/LC-change categories in “forest land remaining forest land”
Deforestation.
Step 6. Project future land-use and land-cover change
6.2 Identification of LU/LC-change categories in “forest land converted to non-forest land”.
Three methods are available to do this projection:
(1) Historical LULC-change;
(2) Suitability modeling; and
(3) Ex post observations (dynamic baseline).
Non-forest land uses that would be established on deforested forest land
Project year
Grassland A
Grassland B
Grassland C
Cropland A
Cropland B
Cropland C
Wetland A
Wetland B Etc. (as
needed) Total
ha ha ha ha ha ha ha ha ha ha
1
2
3
…
n
Total crediting period
Total project duration
6.2 Identification of LU/LC-change categories in “forest land converted to non-forest land”.
Step 7. Estimate the expected baseline carbon stock changes and non-CO2 emissions.
7.1 Estimation of the average carbon stock density of each LU/LC class.
7.2 Estimation of non-CO2 emissions from forest fires (if applicable).
7.3 Calculation of Emission Factors.
7.4 Calculations of carbon stock changes due to forest degradation and regeneration.
7.5 Calculation of carbon stock changes (and non-CO2 emissions) due to deforestation.
7.6 Estimation of total baseline carbon stock changes and non-CO2 emissions (CBASELINE)
Average carbon stock
in the "from" class Average carbon stock
in the "to" class Emission Factor
(Average carbon stock change)
CAB CBB CDW CL CSOC CAB CBB CDW CL CSOC CAB CBB CDW CL CSOC
LULC-change category tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
Forest A to Grass Land Forest B to Grass Land Forest C to Grass Land Forest A to Crop Land Forest B to Crop Land
Deforestation
Forest C to Crop Land Forest A to Forest B Forest B to Forest C
Regeneration
Forest C to Forest A Forest B to Forest A
Degradation Forest C to Forest B
LU/LC-change category
Deg
Reg
Def
7.3 Calculation of Emission Factors.
Emission Factor Activity
data Carbon stock change
CAB CBB CDW CL CSOC CAB CBB CDW CL CSOC Total
LULC-change category tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
ha tCO2e tCO2e tCO2e tCO2e tCO2e tCO2e
Forest A to Forest B Forest B to Forest C
Regeneration
Forest C to Fores A Forest B to Forest A
Degradation Forest C to Forest B
Total for year (year)
7.4 Calculations of carbon stock changes due to forest degradation and regeneration.
Average carbon stock density Activity
data Total carbon stock
CAB CBB CDW CL CSOC CAB CBB CDW CL CSOC Total
LULC-class tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
tCO2e ha-1
ha tCO2e tCO2e tCO2e tCO2e tCO2e tCO2e
Forest A Forest B Forest Land
Forest C Total for
Forest Land
Crop Land non-Forest Land Grass Land
Total for non-Forest Land
Carbon stock change =
Total for non-Forest Land
minus Total for
Forest Land (year)
7.5 Calculation of carbon stock changes due to deforestation.
Deforestation Forest Degradation Forest Regeneration Total Carbon Stock
Changes
Total non-CO2 Emissions
from Biomass Burning
Total
CA
B
CB
B
CD
W
CL
CSO
C
Tot
al
CA
B
CB
B
CD
W
CL
CSO
C
Tot
al
CA
B
CB
B
CD
W
CL
CSO
C
Tot
al
CA
B
CB
B
CD
W
CL
CSO
C
Tot
al
GH
GA
B
GH
GD
W
GH
GL
Tot
al
CB
ASE
LIN
E
Project year
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
tCO
2e
1 2 3 4 … n
Total crediting period
Total project duration
7.6 Estimation of total baseline carbon stock changes and non-CO2 emissions (CBASELINE)
Step 8. Estimate the expected actual carbon stock changes.
• Estimations are based on planned project activities.
• The expected level of “activity data” is reported in tables similar to the previous ones.
• The numbers of reduced activity data for “degradation” and “deforestation” and the underlying assumptions must be explained and justified.
• If specific measures are undertaken to enhance carbon stocks in “regeneration” forest classes, the Potential Forest Regeneration Map must be adjusted accordingly .
Step 9. Estimation of expected leakage: carbon stock changes and non-CO2
emissions (CLEAKAGE)
measuresLKntDisplacemeLEAKAGE EEC
animalsLKionfertilizatLKmeasuresLK GHGGHGE ,,
EDisplacement = (CBASELINE - CACTUAL) * X%
Assumptions about attributability of different types of leakage
• Attributable to a REDD project activity are:– Activity displacement. – Emissions from measures implemented to prevent activity
displacement.
• Not attributable are:– Positive leakage (consistently with CDM). – Market effects:
• Project can not control markets and market actors, but government can• Market effects are attributable to governments• If market effects are not controlled by governments and carbon prices,
DD will continue.
CBASELINE CACTUAL CLEAKAGE CREDD CREDD Total
carbon stock
changes
Total permanent
GHG emissions
Total carbon stock
changes
Total permanent
GHG emissions
Total carbon stock
changes
Total permanent
GHG emissions
Total carbon stock
changes
Total permanent
GHG emissions
Total
Project year tCO2e tCO2e tCO2e tCO2e tCO2e tCO2e tCO2e tCO2e tCO2e
1 2
3 4
… n
Total cred.
period
Total project
duration
Step 10. Calculate the expected ex ante net anthropogenic GHG emission reductions.
LEAKAGEACTUALBASELINEREDD CCCC
Ex post methodology steps
Ex post methodology steps
Step 1. Define the boundaries of the proposed REDD project activity: spatial, temporal, carbon pools and sources of greenhouse gas emissions.
Step 3. Analyze agents, drivers and underlying causes of deforestation and forest degradation
Step 2. Analyze historical land-use and land-cover change in the reference region during the past 10-15 years and project potential forest regeneration.
Step 11. Project monitoring.
Step 13. Adjustment of the baseline for future crediting periods.
Step 12. Ex post calculation of net anthropogenic GHG emssion reduction
Step 11. Project monitoring.
11.1 Project implementation:• Measures to reduce deforestation and forest
degradation; • Measures to enhance carbon stocks; and • Measures to reduce the risk of leakage.
11.2 Land-use and land-cover change in the reference region, project area and leakage belt
11.3 Driver variables used to estimate the quantity and location of future deforestation and forest degradation
11.4 Carbon stocks
Step 12. Calculation of ex post net anthropogenic GHG emission reductions
LEAKAGEACTUALBASELINEREDD CCCC
Ex ante projection
Ex post measured
Ex post measured
Step 13. Adjustment of the baseline projections for future crediting periods
13.1 Adjustment of the land-use / land-cover change component of the baseline
13.2 Adjustment of the carbon stock-change component of the baseline
?BBB
timeT1 T2 T3 T4t-2 t-1 t1 t2t0
T3: 4 x A
A
A
A
A
T1: 1 x B
T1: 1 x A
A
B
T2: 3 x A
T2: 2 x B
A
A
A
BB
13.1 Adjustment of the land-use / land-cover change component of the baseline
T2: (PA+LKB)/RR = 2/3
T3: (PA+LKB)/RR= ?/4
T3: 2/3 = ?/4? = 2/3*4 = 2.6
Reference Region
Project Area and Leakage Belt
13.2 Adjustment of the carbon stock-change component of the baseline
• Measure and adjust, as necessary, the estimated average carbon stock density of LU/LC classes
• Adjust emission factors