REDD Methodological Module
“Estimation of emissions from market effects”
Version 1.0 - April 2009
I. SCOPE, APPLICABILITY AND PARAMETERS
Scope
This module allows for estimating GHG emissions caused by the market-effects leakage related
to extraction of wood for timber, fuel wood or charcoal in the baseline for carbon projects.
Applicability
This module is applicable for calculating market-effects leakage from REDD projects that reduce
levels of wood harvest substantially and permanently. The module should be used where
timber would be extracted before forest clearing in the baseline case, or where wood is
collected for fuel or charcoal production in the baseline case for sale in regional or national
markets. When REDD project activities result in reductions in harvests, it is likely that
production could shift to other areas of the country to compensate for the reduction.
Furthermore, when there is reduced timber production, the carbon stocks stored in harvested
wood products may decrease due to the implementation of the project activity.
Required conditions
•
The total volume to be extracted in the baseline must be known
Parameters
This module provides procedures to determine the following parameter:
Parameter
SI Unit
Description
LKMarketEffects
t-CO2-e
Net CO2 emissions due to market-effects leakage
1
II. PROCEDURE
1. Market-Effects Leakage Through Decreased Timber Harvest
Leakage due to market effects is equal to the emissions from logging that is displaced outside
the project area multiplied by a leakage factor:
(1)
Where:
LKMarketEffects
Total GHG emissions due to market- effects leakage; t CO2-e
LFME
Leakage factor for market-effects calculations; dimensionless
AL
Emissions from harvests displaced through implementation of carbon
project; t CO2-e
The leakage factor is determined by considering where in the country logging might be
increased as a result of the decreased supply of the timber caused by the project. If the areas
liable to be logged have a higher carbon stock than the project area it is likely that the
proportional leakage is higher and vice versa:
LFME
=0
if it can be demonstrated to the verifier that no market-effects
leakage will occur within national boundaries, e.g. if no new concessions
are being assigned AND annual extracted volumes cannot be increased
within existing national concessions AND illegal logging is absent (or de
minimis) in the host country.
LFME
= 0.4
if CBSL
=
NCS
(if CBSL ≤ NCS * 1.15 and ≥ NCS * 0.85)
LFME
= 0.7
if CBSL
<
NCS * 0.85
LFME
= 0.2
if CBSL
>
NCS * 1.15
Where:
LFME
Leakage factor for market-effects calculations; dimensionless
NCS
The mean national forest carbon stock; t CO2-e ha-1
CBSL
Mean carbon stock across strata in all pools in the baseline; t CO2-e ha-1
2
The mean carbon stock across all pools in the baseline is derived from the baseline modules
and involves area-weighting the stocks across the strata:
MB
∑ (C
C BSL =
BSL,i
* Ai )
i =1
(2)
MB
M B *∑ A
i =1
Where:
CBSL
Mean carbon stock across strata in all pools in the baseline; t CO2-e ha-1
CBSL,i
Carbon stock in all pools in the baseline in stratum i; t CO2-e ha-1 (see
Module BL-PL or Module BL-UP)
Ai
The area of stratum i in which logging is anticipated in the baseline
scenario; ha
i
1, 2, 3 …MB strata in the baseline scenario
MB
The total number of strata in the baseline scenario
The next step is to estimate the emissions associated with the displaced logging activity—this is
based on the total volume that would have been logged in the baseline in the project area
across strata and time periods:
∑
∑
,,,
(3)
Where:
AL
Emissions from harvests displaced through implementation of carbon
project; t CO2-e
CBSL,XB,i,t
Likely carbon emission due to displaced harvests in the baseline scenario
in at time t; t CO2-e
i
1, 2, 3 …MB strata in the baseline scenario
t
1, 2, 3, … t* years elapsed since the projected start of the REDD project
activity
The carbon emission due to the displaced logging has two components: the biomass carbon of
the extracted timber and the likely biomass carbon in the forest damaged in the process of
timber extraction:
,,, ,,, !
%%
" # ,,, "$ &
(4)
3
Where:
CBSL,XB,i,t
Likely carbon emission due to displaced harvests in the baseline scenario
in at time t; t CO2-e
VBSL,EX,j,t
Volume of timber projected to be extracted from within the project
boundary during the baseline in stratum i at time t; m3
Dmn
Mean wood density of commercially harvested species; t d.m.m-3
CF
Carbon fraction of biomass for commercially harvested species j; t C t
d.m.-1
LDF
Logging damage factor; t CO2-e m-3 (default 0.3663 t C m-3)
LDF default is only applicable to tropical forests. For other forest types a
value of LDF would have to be calculated based on statistically-based
measurements on extracted volumes and likely emissions caused by the
process of extraction
i
1, 2, 3 …MB strata in the baseline scenario
The logging damage factor (LDF) is a representation of the quantity of emissions that will
ultimately arise per unit of extracted timber (m3). These emissions arise from the noncommercial portion of the felled tree (the branches and stump) and trees incidentally killed
during tree felling. Conservatively logging roads, skid trails and logging decks are not included
here as the logging that is leaked is assumed in the majority of cases to become a small
proportion of a larger logging operation. The default value given here comes from the slope of
the regression equation between carbon damaged and volume extracted based on 534 logging
gaps measured by Winrock International in Bolivia, Belize, Mexico, the Republic of Congo, Brazil
and Indonesia (Annex 1).
2. Market Effects Leakage Through Decreased Harvest of Fuel Wood and Charcoal Sold
into Regional and/or National Markets
Leakage due to market effects is equal to the emissions from logging that is displaced outside
the project area multiplied by a leakage factor:
(5)
Where:
LKMarketEffects
Total GHG emissions due to market leakage effects; t CO2-e
4
LFME
Leakage factor for market effects calculations; dimensionless
AL
Emissions from harvests displaced through implementation of carbon
project; t CO2-e
The leakage factor is determined by considering where in the country harvest of fuel
wood/charcoal might be increased as a result of the decreased supply of the products caused
by the project. If the areas liable to be harvested have a higher carbon stock than the project
area it is likely that the proportional leakage is higher and vice versa:
= 0.4
LFME
if CBSL
=
NCS
(if CBSL ≤ NCS * 1.15 and ≥ NCS * 0.85)
LFME
= 0.7
if CBSL
<
NCS * 0.85
LFME
= 0.2
if CBSL
>
NCS * 1.15
Where:
LFME
Leakage factor for market effects calculations; dimensionless
NCS
The mean national forest carbon stock; t CO2-e ha-1
CBSL
Mean carbon stock across strata in trees in the baseline; t CO2-e ha-1
MB
∑ (C
C BSL =
BSL,i
* Ai )
i =1
(6)
MB
M B *∑ A
i =1
Where:
CBSL
Mean carbon stock across strata in all pools in the baseline; t CO2-e ha-1
CBSL,i
Carbon stock in all pools in the baseline in stratum i; t CO2-e ha-1
Ai
The area of stratum i in which harvesting is anticipated in the baseline
scenario; ha
i
1, 2, 3 …MB strata in the baseline scenario
5
The total number of strata in the baseline scenario
MB
C BSL,i = C BSL, AB _ tree,i + C BSL, BB _ tree,i + C BSL, DW ,i + C BSL, LI ,i + C BSL, SOC ,i
(7)
Where:
CBSL,i
Carbon stock in all pools in the baseline in stratum i; t CO2-e ha-1
CBSL,AB_tree,i
Carbon stock in aboveground biomass in the baseline in stratum i; t CO2-e ha-1
CBSL,BB_tree,i
Carbon stock in belowground biomass in the baseline in stratum i; t CO2-e ha-1
CBSL,DW,i
Carbon stock in dead wood in the baseline in stratum i; t CO2-e ha-1
CBSL,LI,i
Carbon stock in litter in the baseline in stratum i; t CO2-e ha-1
CBSL,SOC,i
Carbon stock in soil organic carbon in the baseline in stratum i; t CO2-e ha-1
Carbon pools excluded from the project can be accounted as zero. For the purpose of assigning
a baseline carbon stock it is conservative to exclude pools. At a minimum CAB_TREE should be
considered in all instances.
The next step is to estimate the emissions associated with the displaced harvesting activity—
this is based on the total volume that would have been logged in the baseline in the project
area across strata and time periods:
∑
∑
,,,
(8)
Where:
AL
Emissions from harvesting displaced through implementation of carbon
project; t CO2-e
CBSL,XB,t
Likely carbon emission due to displaced harvests in the baseline scenario
in at time t; t CO2-e
Ai
The area of stratum i in which harvesting of fuel wood and/or production
of charcoal is anticipated in the baseline scenario; ha
i
1, 2, 3 …MB strata in the baseline scenario
t
1, 2, 3, … t* years elapsed since the projected start of the REDD project
activity
The carbon emission due to displaced harvests is calculated from the volume that would likely
be extracted in the baseline scenario:
6
,, '(, !
%%
$ &
(9)
Where:
CBSL,XB,i,t
Likely carbon emission due to displaced harvests in the baseline scenario
in at time t; t CO2-e
VBSL,FW ,t
The mean annual per capita consumption of fuel wood and/or production
of charcoal in the baseline period (see Module BL-DFW); m3 yr-1
Dmn
Mean wood density of commercially harvested species; t d.m.m-3
CF
Carbon fraction of biomass for commercially harvested species j; t C t-1
d.m.
t
1, 2, 3, … t* years elapsed since the projected start of the REDD project
activity
7
III. DATA AND PARAMETERS NOT MONITORED (DEFAULT OR MEASURED ONE TIME)
Data / parameter:
Ai,
Data unit:
ha
Used in equations:
2,6
Description:
The area of stratum i
Source of data:
Analysis of Remote Sensing data and/or legal records and/or survey
information for lands owned or controlled or previously owned or
controlled by the baseline agent of deforestation
Measurement
procedures (if any):
Any comment:
Data / parameter:
CF
Data unit:
t C t d.m.-1
Used in equations:
4,9
Description:
Carbon fraction of dry matter
Source of data:
Default value 0.47 t C t-1 d.m. can be used, or species specific values from
the literature (e.g. IPCC 2006 INV GLs AFOLU Chapter 4 Table 4.3)
Measurement
procedures (if any):
Any comment:
Data / parameter:
Dmn
Data unit:
t d.m.m-3
Used in equations:
4,9
Description:
Mean wood density of commercially harvested species
Source of data:
The source of data shall be chosen with priority from higher to lower
preference as follows:
(a) Averaged national and commercial species-specific (e.g. from
National GHG inventory);
(b) Averaged commercial species-specific from neighboring countries
with similar conditions. Sometimes (b) may be preferable to (a).
(c) Averaged regional commercial species-specific (e.g. Table 4.13 IPCC
8
National Guidance for Greenhouse Gas Inventories AFOLU Section).
(d) Regional average (0.58 t d.m.m-3- tropical Africa; 0.60 t d.m.m-3tropical America; 0.57 d.m.m-3- tropical Asia) from Brown, S. 1997.
Estimating Biomass and Biomass Change of Tropical Forests: a Primer.
For the Food and Agriculture Organization of the United Nations. Rome,
1997. FAO Forestry Paper - 134. ISBN 92-5-103955-0.
Measurement
procedures (if any):
Any comment:
Data / parameter:
LDF
Data unit:
t CO2-e m-3
Used in equations:
4
Description:
Factor for calculating the biomass of dead wood created during logging
operations per cubic meter extracted
Source of data:
Default value of 0.3663 t CO2-e m-3 from 534 logging gaps measured by
Winrock International in Bolivia, Belize, Mexico, the Republic of Congo,
Brazil and Indonesia may be used (cf. Annex 1).
Alternately a region or project-specific value may be calculated and
justified to the validator.
Measurement
procedures (if any):
Any comment:
Data / parameter:
NCS
Data unit:
t CO2-e / ha.
Used in equations:
Indirectly in equations 1,5
Description:
The mean national forest carbon stock
Source of data:
The appropriate national value may be taken from Table 4.7 of 2006 IPCC
Guidelines for National Greenhouse Gas Inventories
Measurement
procedures (if any):
Any comment:
9
IV. TERMS ORIGINATING IN OTHER MODULES
Data / parameter:
CBSL,AB,tree,i
Data unit:
t CO2-e ha-1
Used in equations:
7
Description:
Carbon stock in aboveground biomass in trees in the baseline in stratum i
Module parameter
originates in:
CP-A
Any comment:
Data / parameter:
CBSL,BB,tree,i
Data unit:
t CO2-e ha-1
Used in equations:
7
Description:
Carbon stock in belowground biomass in trees in the baseline in stratum i
Module parameter
originates in:
CP-B
Any comment:
Data / parameter:
CBSL,i
Data unit:
t CO2-e ha-1
Used in equations:
2,6,7
Description:
Carbon stock in all pools in the baseline in stratum i
Module parameter
originates in:
BL-PL
and
BL-UP
Any comment:
Data / parameter:
CBSL,DW,i
Data unit:
t CO2-e ha-1
Used in equations:
7
Description:
Carbon stock in dead wood in the baseline in stratum i
10
Module parameter
originates in:
CP-W
Any comment:
Data / parameter:
CBSL,LI,i
Data unit:
t CO2-e ha-1
Used in equations:
7
Description:
Carbon stock in litter in the baseline in stratum i
Module parameter
originates in:
CP-L
Any comment:
Data / parameter:
CBSL,SOC,i
Data unit:
t CO2-e ha-1
Used in equations:
7
Description:
Carbon stock in soil organic carbon in the baseline in stratum i
Module parameter
originates in:
CP-S
Any comment:
Data / parameter:
VBSL,EX,i,t
Data unit:
m3
Used in equations:
4
Description:
Volume of timber projected to be extracted from within the project
boundary during the baseline in stratum i at time t
Module parameter
originates in:
CP-W
Any comment:
Data / parameter:
VBSL,FW,t
Data unit:
m3 yr-1
Used in equations:
9
11
Description:
The mean annual per capita consumption of fuel wood and/or
production of charcoal in the baseline period
Module parameter
originates in:
BL-DFW
Any comment:
12
V. ANNEX 1
Dead Wood Created (t C)
35
y = 0.3663x
R² = 0.70
30
25
20
15
10
5
0
0
10
20
30
40
50
60
70
80
Volume (m3)
Methods used by Winrock can be referenced in the following reports to USAID:
Deliverable 9:
Use of Aerial Digital Imagery to measure the impact of selective
logging on carbon stocks of tropical forests in Republic of Congo
Deliverable 10:
Quantification of carbon benefits in conservation project activities
through spatial modeling: Republic of Congo as a case study
Deliverable 13a:
as a case study
Impact of logging on carbon stocks of forests: Chihuahua, Mexico
Deliverable 17:
Amazon as a case study
Impact of logging on carbon stocks of forests: The Brazilian
Deliverable 21:
Use of aerial digital imagery to measure the impact of selective
logging on carbon stocks of tropical forest in Brazilian Amazon
Impact of selective logging on carbon stocks of tropical forests in
Deliverable 24:
East Kalimantan, Indonesia
Under Carbon and Co-Benefits from Sustainable Land-Use Management project: Cooperative
Agreement No. EEM-A-00-03-00006-00
And in the following manuscript being prepared for peer-reviewed publication:
Pearson, TRH and Brown, S. 2009. Impact of selective logging on the carbon stocks of tropical
forests: case studies from Belize, Bolivia, Brazil, Indonesia, Mexico and the Republic of Congo.
13