PS-AFOLU
F-V Methodology
Revegetation of degraded land
July 2012
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 2
July 2012
Table of contents:
1
2
3
4
5
Sources: ................................................................................................................................... 3
Summary: ................................................................................................................................. 3
Definitions: .............................................................................................................................. 3
Applicability: ............................................................................................................................ 4
Eligibility................................................................................................................................... 4
Project Type .............................................................................................................................................. 4
Historic Land Use ...................................................................................................................................... 5
6
7
8
Project Definition ..................................................................................................................... 6
Demonstration of additionality ............................................................................................... 8
Baseline Emissions ................................................................................................................... 8
8.1 Determine the Baseline Scenario(s) .................................................................................................... 8
8.2 Stratification........................................................................................................................................ 8
8.3 Baseline net GHG emissions/removals ............................................................................................... 9
8.4 Project GHG removals/emissions ..................................................................................................... 10
8.5 Leakage ............................................................................................................................................. 15
8.6 Net project GHG emission reductions/removals .............................................................................. 16
8.7 Estimation of uncertainty ................................................................................................................. 16
8.8 Calculation of PS Credits ................................................................................................................... 19
9
Monitoring ............................................................................................................................. 19
9.1 Monitoring of project implementation ............................................................................................. 19
9.2 Sampling design ................................................................................................................................ 20
9.3 Data and parameters available at validations (default or possibly measured one time) ................. 21
9.4 Data and parameters monitored ...................................................................................................... 21
Annex A: Tools for estimation of carbon pools and sources ........................................................ 22
Tool Ctree: Estimation of carbon stocks and change in carbon stocks of trees ............................. 23
Tool CNT-Woody: Estimation of carbon stocks and changes in carbon stocks of non-tree woody
biomass ......................................................................................................................................... 45
Tool CHE: Estimation of carbon stocks and changes in carbon stocks of herbaceous biomass .... 59
Tool CDW: Estimation of carbon stocks and change in carbon stock in dead wood ..................... 70
Tool CLI: Estimation of carbon stocks and change in carbon stock in litter .................................. 85
Tool CWP: Estimation of carbon stock and carbon stock changes in wood products ................... 93
Tool CSOC: Tool for estimation of change in soil organic carbon stocks ...................................... 101
Tool N2O: Estimation of direct and indirect oxide emission from nitrogen fertilization............ 108
Tool: Grazing GHG Emissions: CH4 emissions due to enteric fermentation and N2O from manure
and urine deposited on grassland soils....................................................................................... 114
Tool: Leakage emissions from CH4 and N2O emissions as result of grazing animals.................. 125
Annex B - Guidance on Estimating biomass in living trees at the start of the project activity .. 138
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 3
July 2012
1
1 Sources:
2
3
This methodology refers to the latest CDM approved versions of the following tools, procedures,
guidelines and guidances:
4
5

Guidelines on conservative choice and application of default data in estimation of the net
anthropogenic GHG removals by sinks;
6
7

Tool for the identification of degraded or degrading lands for consideration in implementing
A/R CDM project activities;
8
9

Combined tool to identify the baseline scenario and demonstrate additionality in A/R CDM
project activities;
10

Tool for testing significance of GHG emissions in A/R CDM project activities;
11
12

Estimation of non-CO2 GHG emissions resulting from burning of biomass attributable to an
A/R CDM project activity”;
13

Estimation of GHG emissions related to fossil fuel combustion in CDM AR project activities.
14
15

Estimation of the increase in GHG emissions attributable to displacement of pre-project
agricultural activities in A/R CDM project activity;
16
2 Summary:
17
18
19
20
21
This methodology is applied to estimate the GHG removals resulting from activities that increase the
carbon stocks in non-forested degraded lands through direct planting of seeds or seedlings or humanassisted natural regeneration, resulting in vegetation structure either above or below the CDM People’s
Republic of China (PRC) definition of forest. The project activity may or may not result in the
displacement of pre-project grazing activities.
22
23
The estimation of GHG emission sources and pools are calculated through the use of Tools found in the
Annex of the Methodology and CDM AR approved tools.
24
3 Definitions:
25
For the purpose of this methodology, the following specific definitions apply:
26
27
Non-tree woody vegetation: Ligneous vegetation that does not meet the definition of a tree as set forth
by this methodology.
28
Herbaceous vegetation: Non-tree non-ligneous vegetation
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 4
July 2012
29
30
Tree: Single or multi-stemmed ligneous vegetation with a minimum tree height at maturity of 2 m in
situ.
31
4 Applicability:
32
33
34
35
This methodology is applicable to forestation and vegetation increase project activities that are
implemented on degraded lands. The CDM A/R “Tool for the identification of degraded or degrading
lands for consideration in implementing CDM A/R project activities” shall be applied for demonstrating
that lands are degraded or degrading.
36
The conditions under which the methodology is applicable are:
37
38
(a) The project activity is implemented on lands where the most likely baseline land
management is the continuation of the existing or historical baseline land management;
39
40
41
42
(b) The forestation and vegetation increase project activity is implemented on degraded lands,
which are expected to remain degraded or to continue to degrade in the absence of the
project, hence the land cannot be expected to revert to a non-degraded state without
human intervention;
43
44
45
(c) If at least a part of the project activity is implemented on organic soils, drainage of these
soils is not allowed and not more than 10% of their area may be disturbed as result of soil
preparation for planting;
46
(d) The land does not fall into wetland1 category;
47
(e) Flooding irrigation is not allowed;
48
5 Eligibility
49
50
51
52
53
54
55
56
Project Type
This methodology is applicable to project activities categorized as Forestation and Vegetation Increase
(F-V) in the Panda Standard AFOLU Specification. Although baseline land use under the F-V category can
vary, the baseline land use must be a continuation of historical and/or existing land management due to
the applicability conditions of this methodology. Under this category, to be eligible all parcels included in
F-V project activities must not meet the definition of forest as set forth by the PRC Designated National
Authority (DNA) at the project start date. Project participants shall provide evidence that each parcel is
eligible for an F-V project activity by demonstrating the following conditions.
1
“Wetlands”, “settlements”, “cropland” and “grassland” are land categories as defined in the Good Practice
Guidance for Land Use, Land-use Change and Forestry (IPCC, 2003).
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 5
July 2012
57
58
Demonstrate that the land at the moment the project starts does not contain forest by providing
transparent information that:
59
60
61
1. Vegetation on the land is below the forest thresholds (tree crown cover or equivalent stocking
level, tree height at maturity in situ, minimum land area) adopted for the definition of forest by
PRC under decisions CDM 16/CMP.1 and 5/CMP.1 as communicated by the respective DNA; and
62
63
2. All young natural stands and all plantations on the land are not expected to reach the minimum
crown cover and minimum height chosen by PRC to define forest; and
64
65
3. The land is not temporarily unstocked, as a result of human intervention such as harvesting or
natural causes.
66
67
In order to demonstrate the conditions 1-3, project participants shall provide information that reliably
discriminates between forest and non-forest land according to the PRC definition of a forest, inter alia:
68
(a) Aerial photographs or satellite imagery complemented by ground reference data; or
69
(b) Land use or land cover information from maps or digital spatial datasets; or
70
71
(c) Ground based surveys (land use or land cover information from permits, plans, or information
from local registers such as cadastre, owners’ registers, or other land registers).
72
73
74
If options (a), (b), and (c) are not available/applicable, project participants shall submit a written
testimony which was produced by following a Participatory Rural Appraisal (PRA) methodology2 or a
standard Participatory Rural Appraisal (PRA) as practised in PRC.
75
Historic Land Use
76
77
78
79
80
The project proponent must provide documented evidence of the historic land use management within
the project’s geographic boundaries over the 10 years prior to the start date. If the land use
management within the project’s geographic boundary has changed within the last 10 years, the project
proponent must demonstrate that land management change did not occur in pursuit of emissions
crediting. Documented evidence of historic land use management changes could include:
81

Land use management records
82

Field surveys
2
Participatory rural appraisal (PRA) is an approach to the analysis of local problems and the formulation of
tentative solutions with local stakeholders. It makes use of a wide range of visualization methods for group-based
analysis to deal with spatial and temporal aspects of social and environmental problems. This methodology is, for
example, described in: Chambers R (1992): Rural Appraisal: Rapid, Relaxed, and Participatory. Discussion Paper
311, Institute of Development Studies, Sussex.; Theis J, Grady H (1991): Participatory rapid appraisal for
community development. Save the Children Fund, London.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 6
July 2012
83

Data and feedback from stakeholders
84

Information from other appropriate sources, including Participatory Rural Appraisal (PRA)
85
86
If land use management changes were brought about by legal requirements such as national or sectoral
policies, they shall not be considered to have been made in the pursuit of emissions crediting.
87
6 Project Definition
88
89
In the Project Form, the project proponent shall define the temporal and spatial boundaries of the
project as delineated in the PS-AFOLU Specification.
90
91
92
93
The emission sources and associated GHGs included in or excluded from accounting are shown in the
below table. Any one of these sources can be neglected, i.e. accounted as zero, if the application of the
most recent version of the CDM “Tool for testing significance of GHG emissions in project activities”
leads to the conclusion that the emission source is insignificant.
94
Table 1 Emission sources and GHGs included or excluded from accounting
Sources
Gas
CO2
Burning of woody
biomass
Included/
excluded
Excluded
CH4
Included
N2O
Included
Fertilizer emissions
N2O
Included
Fossil Fuel Combustion
CO2
Included
Water Inundation
CH4
Excluded
Justification/Explanation
Carbon stock decreases due to burning are accounted
as a change in carbon stock.
Burning of woody biomass for the purpose of site
preparation or as part of forest management can lead
to significant levels of emissions of methane.
Burning of woody biomass for the purpose of site
preparation or as part of forest management can lead
to significant levels of emissions of nitrous oxide.
Application of fertilizers can lead to significant levels of
nitrous oxide emissions.
Use of machinery in the project can lead to significant levels
of carbon dioxide emissions.
Under the applicability conditions of this methodology,
methane emissions from flooding irrigation are not
expected to increase.
95
The carbon pools included in or excluded from accounting are shown in Table 1.
96
Table 2 Carbon pools accounted for in project boundary
Carbon pools
Above-ground Tree
biomass
Below-ground Tree
Accounted for
Yes
Justification / Explanation
Yes
Below-ground biomass stock is expected to increase due
Major carbon pool subjected to project activity
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 7
July 2012
Carbon pools
biomass
Above-ground NonTree biomass
Below-ground NonTree biomass
Dead wood
Accounted for
Forest floor (litter)
Yes
(alternatively No)
Soil organic carbon
(SOC)
Yes (alternatively No, if the
project is implemented on
organic soils or if
ploughing/ ripping/
scarification attributable
to the project activity
continues beyond the initial
five-year period)
Yes (alternatively No, if no
timber is harvested from
trees in the project)
Harvested Wood
Products
Yes
Yes
Yes
(alternatively No)
Justification / Explanation
to the implementation of the project activity
Major carbon pool subjected to project activity
Below-ground biomass stock is expected to increase due
to the implementation of the project activity
This stock may change (when compared to baseline) due
to implementation of the project activity. The
methodology provides an approach for accounting for
this pool, but it also allows for exclusion of the dead
wood carbon pool if transparent and verifiable
information can be provided that carbon stocks in dead
wood in the baseline scenario can be expected to
decrease more or increase less, relative to the project
scenario.
This stock may change (when compared to baseline) due
to implementation of the project activity. The
methodology provides an approach for accounting for
this pool, but it also allows for exclusion of the litter
carbon pool if transparent and verifiable information can
be provided that carbon stocks in litter in the baseline
scenario can be expected to decrease more or increase
less, relative to the project scenario.
Under applicability conditions of this methodology,
carbon stocks in this pool is likely to increase in the
project compared to the baseline. However, the
methodology also provides the conservative choice of
not accounting for changes in carbon stock in the pool.
This stock may increase (when compared to
baseline) due to implementation of the project
activity. The methodology provides an
approach for accounting for this pool, but it
allows also for exclusion of the wood products
pool
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 8
July 2012
97
7 Demonstration of additionality
98
99
100
To determine additionality for each project activity, the latest version of the CDM tool ‘Combined Tool
to identify the baseline scenario and demonstrate the additionality in project activities3’ shall be
implemented.
101
8 Baseline Emissions
102
103
104
105
8.1 Determine the Baseline Scenario(s)
106
107
A Baseline Agent can be identified through documentation showing that such an entity has legally
recognized control over specific parcels.
108
109
110
111
112
113
114
Where a specific (known) entity cannot be identified, the most likely type or ‘class of baseline agents’
shall be determined. The selection of a ‘class of agent’ must be demonstrated with historical records
showing that the identified class of agent is the most common agent undergoing activities in the project
region that are identical to the project’s baseline scenario. Where multiple classes of baseline agents
exist in the project region, stratification of the project area into spatially discrete categories that reflect
distinct classes of agents shall be performed. Identify the baseline scenario and demonstrate
additionality
115
116
117
To determine the baseline scenario for each project activity and class of baseline agent, the latest
version of the CDM tool ‘Combined Tool to identify the baseline scenario and demonstrate the
additionality in project activities’ shall be implemented4.
118
119
120
8.2 Stratification
121
122
123
Strata shall reflect biophysical and land-management parameters such as soil type, elevation,
precipitation regime, temperature, slope and aspect, vegetation composition, land use history, and land
use management.
124
125
Different stratifications may be required for the baseline and project scenarios in order to achieve
optimal accuracy of the estimates of net GHG removals by sinks.
As stated in PS-AFOLU, the Baseline Agent is the entity responsible for the activities that would occur
under the baseline scenario. The Baseline Agent may be either a known entity or a type or class of
entity.
Where the project area is not homogeneous, stratification should be carried out to improve the
accuracy and precision of emission reduction and removal estimates.
3
4
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 9
July 2012
126
8.3 Baseline net GHG emissions/removals
127
128
129
The baseline net GHG removals by sinks is the sum of the changes in carbon stocks in the selected
carbon pools within the project boundary that would have occurred in the absence of the forestation
and vegetation increase project activity.
130
Under the applicability conditions of this methodology:
131
132
133
134
135

It is expected that the baseline non-woody aboveground and belowground vegetation, dead
wood and litter carbon pools will not show a permanent net increase. It is therefore
conservative to assume that the sum of the changes in the carbon stocks of non-woody
aboveground and belowground non-woody vegetation, dead wood and litter carbon pools is
zero for all strata in the baseline scenario;
136
137
138

Since carbon stock in soil organic carbon (SOC) is unlikely to increase in the baseline, the
change in carbon stock in SOC may be conservatively assumed to be zero for all strata in the
baseline scenario.
139
Therefore the baseline net GHG removals by sinks will be determined as:
t*
140
C BSL   CTREE _ BSL,t  C NT W OODY _ BSL,t  N 2 O fertilizer_ BSL,t  CH 4,enteric _ BSL,t  N 2 O grazing _ BSL,t
(1)
t 1
141
where:
 C BSL
Baseline net GHG removals by sinks; t CO2-e
C TREE _ BSL,t
Sum of the carbon stock changes in above-ground and below-ground biomass of
trees in the baseline in year t; t CO2-e
Sum of the carbon stock changes in above-ground and below-ground biomass of
non-tree woody vegetation in baseline in year t; t CO2-e
Sum of N2O emissions as a result of nitrogen application within project boundary
in baseline in year t; t CO2-e
Sum of CH4 emissions as a result of enteric fermentation within project boundary
in the baseline in year t; t CO2-e
Sum of N2O emissions as a result of manure and urine deposited on grassland soil
during grazing within the project boundary in the baseline, at year t; t CO2-e
1, 2, 3, … t* years elapsed since the start of the project activity
C NT W OODY _ BSL,t
∆𝑁2 𝑂𝑓𝑒𝑟𝑡𝑖𝑙𝑖𝑧𝑒𝑟_𝐵𝑆𝐿,𝑡
CH 4,enteric _ BSL,t
N 2 O grazing, BSL,t
t
142
143
144
145
146
The changes in tree carbon stocks in the baseline shall be estimated using the Tool in the Annex:
“Estimation of carbon stocks and change in carbon stocks of trees ” or the latest version of the CDM
Tool: “Estimation of carbon stocks and change in carbon stocks of trees and shrubs in A/R CDM project
activities”.5
5
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 10
July 2012
147
148
149
150
151
The changes in non-tree woody biomass stocks in the baseline shall be estimated using the Tool in the
Annex: “Estimation of carbon stocks and change in carbon stocks of non-tree woody vegetation” or the
latest version of the CDM Tool: “Estimation of carbon stocks and change in carbon stocks of trees and
shrubs in A/R CDM project activities”.6
152
153
It is always conservative to exclude estimation of N2O emissions from fertilizer or grazing and CH4
emissons from grazing in the baseline. Therefore, it is allowable to assume:
154
155
∆𝑁2 𝑂𝑓𝑒𝑟𝑡𝑖𝑙𝑖𝑧𝑒𝑟_𝐵𝑆𝐿,𝑡 = 0
(2)
156
CH 4,enteric _ BSL,t  0
(3)
157
N 2 O grazing, _ BSLt  0
(4)
158
159
160
161
However, where emissions are expected to be significant, emissions in the baseline can be estimated
using the Tools: “Estimation of N2O emission from nitrogen fertilization Tool” and “Grazing GHG
Emissions: CH4 emissions due to enteric fermentation and and N2O from manure and urine deposited on
grassland soils”.
162
8.4 Project GHG removals/emissions
163
164
165
166
167
The actual net GHG removals by sinks shall be estimated using the equations in this section. When
applying these equations for the ex ante calculation of actual net GHG removals by sinks, Project
Proponents shall provide estimates of the values of those parameters that are not available before the
start of the project. Project Proponents should retain a conservative approach in making these
estimates.
168
The actual net GHG removals by sinks shall be calculated as:
169
C ACTUAL  C P  GHG E _ PROJ
170
where:
(5)
C ACTUAL
Actual net GHG removals by sinks; t CO2-e
CP
Sum of the changes the carbon stock in the selected carbon pools within the project
boundary; t CO2-e
Increase in non-CO2 GHG emissions within the project boundary as a result of the
implementation of the project activity; t CO2-e
GHG E _ PROJ
6
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 11
July 2012
171
8.4.1 Estimation of changes in the carbon stocks
172
173
The verifiable changes in carbon stocks in the selected carbon pools within the project boundary are
estimated using the following equation:
174
C P   C P ,t
t*
(6)
t 1
175
where:
CP
Sum of the changes in carbon stock in all selected carbon pools in stratum i, since start of
the project; t CO2-e
Change in carbon stock in all selected carbon pools in the project scenario, in year t;
t CO2-e
1, 2, 3, … t* years elapsed since the start of the project activity; yr
C P ,t
t
176
177
178
Change in carbon stock in all selected carbon pools, in year t, is calculated as:
C P ,t  CTREE _ PROJ ,t  C NT W OODY _ PROJ ,t  C HE _ PROJ ,t
 C DW _ PROJ ,t  C LI _ PROJ ,t  C SOC _ PROJ ,t  CW P _ PROJ ,t
where:
∆CP,t
CTREE _ PROJ ,t
C NT W OODY _ PROJ ,t
C HE _ PROJ ,t
C DW _ PROJ ,t
C LI _ PROJ ,t
C SOC _ PROJ ,t
CW P _ PROJ ,t
t
179
180
181
(7)
Change in carbon stock in all selected carbon pools in the project scenario, in
year t; t CO2-e
Change in carbon stock in above-ground and below-ground biomass of trees in
the project scenario, in year t; t CO2-e
Change in carbon stock in non-tree woody vegetation biomass in the project
scenario, in year t; t CO2-e
Change in carbon stock in herbaceous vegetation biomass in the project scenario,
in year t; t CO2-e
Change in carbon stock in the dead wood carbon pool in the project scenario, in
year t; t CO2-e
Change in carbon stock in the litter carbon pool in the project scenario, in year t; t
CO2-e
Change in carbon stock in the soil organic carbon pool in the project scenario, in
year t; t CO2-e
Change in carbon stock in the wood products carbon pool in the project scenario,
in year t; t CO2-e
1, 2, 3, … t* years elapsed since the start of the project activity
Estimating change in carbon stock in tree biomass
It is conservative to assume that the change in carbon stocks in tree biomass is equal to zero in some or
all stratum in the project scenario.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 12
July 2012
182
183
184
To estimate the change in tree biomass, the Tool in the Annex: “Estimation of carbon stocks and change
in carbon stocks of trees” or the latest version of the CDM Tool: “Estimation of carbon stocks and
change in carbon stocks of trees and shrubs in A/R CDM project activities” 7 shall be used.
185
186
187
Within this methodology, ex ante estimation of such change can be based on existing data sources.
However, documentation must be provided to display that such estimates are applicable to the
conditions and activities to take place within the project boundary.
188
189
190
191
192
Ex post estimation of tree biomass must be based on actual measurements carried out on trees in
sample plots. Sample plots must be created within each stratum where changes in tree biomass are
accounted. The size and dimensions of such permanent plots may vary dependent on the spatial
distribution of trees planted. The location of such permanent sample plots shall be determined using
unbiased methods.
193
194
195
Non-tree woody vegetation
It is conservative to assume that the change in carbon stocks in non-tree biomass is equal to zero in
some or all stratum in the project scenario.
196
197
198
199
To estimate the change in non-tree woody biomass, the Tool in the Annex:“Estimation of carbon stocks
and change in carbon stocks of non-tree woody vegetation” or the latest version of the CDM Tool:
“Estimation of carbon stocks and change in carbon stocks of trees and shrubs in A/R CDM project
activities” 8 shall be used.
200
201
202
203
204
205
Within this methodology, ex ante estimation of such change can be estimated using the default method
provided. Ex post estimation of non-tree woody biomass must be based on actual measurements in nonpermanent sample plots. Sample plots must be created within each stratum where changes in non-tree
woody vegetation are accounted. The size and dimensions of such plots may vary dependent on the
method used. The location of such sample plots shall be determined using unbiased methods and may
or may not be positioned in association with tree permanent sample plots.
206
207
208
Herbaceous vegetation
It is conservative to assume that the change in carbon stocks in herbaceous biomass is equal to zero in
some or all stratum in the project scenario.
209
210
For ex ante estimates, the changes in carbon stocks of herbaceous vegetation shall be conservatively
neglected.
211
212
213
For ex post estimates, to estimate the change in herbaceous vegetation, the Tool “Estimation of carbon
stocks and change in carbon stocks of non-woody vegetation” shall be used. Ex post estimation of
herbaceous biomass must be based on actual measurements in non-permanent sample plots. Sample
7
8
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 13
July 2012
214
215
216
217
218
plots field data collection must take place within each stratum where changes in herbaceous vegetation
are accounted. The size and dimensions of such plots may vary dependent on the method used. The
location of such sample plots shall be determined using unbiased methods and may or may not be
positioned in association with tree permanent sample plots. The sample plot locations must not be
protected from any project activities.
219
220
221
Dead wood
It is conservative to assume that the change in carbon stocks in dead wood biomass is equal to zero in
some or all stratum in the project scenario.
222
223
To estimate the change in dead wood biomass, the Tool in the Annex: “Estimation of carbon stocks and
change in carbon stocks of dead wood” shall be used.
224
225
226
227
228
229
Within this methodology, ex ante estimation of such change can be estimated using the default method
provided or can be conservatively neglected. Ex post estimation may use one of the methods provided
in the tool. Ex post estimation of deadwood biomass must be based on actual field measurements.
Measurements must take place within each stratum where changes in deadwood are accounted. The
location of such field measurements shall be determined using unbiased methods and may or may not
be positioned in association with tree permanent sample plots.
230
231
232
Litter
It is conservative to assume that the change in carbon stocks in litter biomass is equal to zero in some or
all stratum.
233
234
To estimate the change in litter biomass, the Tool in the Annex: “Estimation of carbon stocks and change
in carbon stocks of litter” shall be used.
235
236
237
238
239
240
241
Within this methodology, ex ante estimation of such change can be estimated using the default method
provided or can be conservatively neglected. Ex post estimation may use one of the methods provided
in the tool. Ex post estimation of litter must be based on actual measurements in non-permanent
sample plots. Sample plots must be created within each stratum where changes in litter are accounted.
The size and dimensions of such plots may vary dependent on the method used. The location of such
sample plots shall be determined using unbiased methods and may or may not be positioned in
association with tree permanent sample plots.
242
243
244
Soil Organic Carbon
To estimate the change in soil carbon, the Tool in the Annex: “Estimation of change in soil organic
carbon stocks” shall be used.
245
246
247
248
Within this methodology, ex ante estimation of such change can be conservatively neglected. Ex post
estimation shall used the method provided in the tool. Ex post estimation of soil must be based on
actual measurements in non-permanent sample points. Sample points must be created within each
stratum where changes in soil are accounted. The location of such sample points shall be determined
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 14
July 2012
249
250
using unbiased methods and may or may not be positioned in association with tree permanent sample
plots or other carbon sampling plots.
251
It is conservative to assume that the change in soil organic carbon is equal to zero in some or all stratum.
252
Non-CO2 GHG emissions
253
254
The increase in GHG emissions as a result of the implementation of the proposed project activity within
the project boundary can be estimated as:
255
GHG E _ PROJ   E BIOMASS _ BURN _ PROJ ,t  N 2 O fertilizer_ PROJ ,t  ETFC _ PROJ ,t  CH 4,enteric _ PROJ ,t  N 2Ograzing _ PROJ , t
t*
t 1
256
257
(8)
where:
GHG E _ PROJ
Increase in GHG emissions as a result of the implementation of the proposed
project activity within the project boundary; t CO2-e
E BIOMASS _ BURN _ PROJ ,t
Emission of non-CO2 GHGs resulting from burning of biomass and forest fires
within the project boundary, in year t; t CO2-e
N 2 O fertilizer_ PROJ ,t
Annual N2O emissions as a result of nitrogen application in the project scenario
time t; t CO2-e. yr-1
ETFC _ PROJ ,t
CO2 emissions from fossil fuel combustion in the project scenario, during the
year t; t CO2-e
CH 4,enteric _ PROJ ,t
N 2 O grazing, PROJ ,t
Sum of CH4 emissions as a result of enteric fermentation within project
boundary in the project scenario in year t; t CO2-e
Sum of N2O emissions as a result of manure and urine deposited on grassland
soil during grazing within the project boundary in the project scenario, at year t;
t CO2-e
t
1, 2, 3, … t* years elapsed since the start of the project activity
258
259
It is never conservative to neglect GHG emissions in the project scenario.
260
261
262
Biomass Burning
The CDM approved tool: “Estimation of non-CO2 GHG emissions resulting from burning of biomass
attributable to an A/R CDM project activity”9 shall be used to estimate emissions from biomass burning.
9
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 15
July 2012
263
E BIOMASS _ BURN _ PROJ ,t  GHG E ,t
(9)
264
E BIOMASS _ BURN _ PROJ ,t
GHG E ,t
Emission of non-CO2 GHGs resulting from burning of biomass and forest fires
within the project boundary, in year t; t CO2-e
CDM tool output parameter: Emission of non-CO2 GHGs resulting from burning
of biomass and forest fires within the project boundary, in year t; t CO2-e
265
266
267
268
Fertilizer application
To estimate emission from fertilizer, emissions can be estimated using the Tool in the Annex:
“Estimation of N2O emission from nitrogen fertilization Tool”10.
269
270
271
272
273
274
275
Fossil fuel combustion
Project Proponents shall use the CDM Tool: “Estimation of GHG emissions related to fossil fuel
combustion in CDM AR project activities”11 to estimate fossil fuel emission. Fossil fuel combustion
associated with the transport of inputs to the project site and implementation of project activities are
included. As allowed by the CDM Tool, the estimation of GHG emissions related to transportation
outside the project boundary only the distance up to the first point of commuting is taken into
consideration.
276
ETFC _ PROJ ,t   ETFC ,i ,t
M
(10)
i
ETFC _ PROJ ,t
ETFC ,i ,t
i
t
CO2 emissions from fossil fuel combustion in the project scenario during the year t;
t CO2-e
CO2 emissions from fossil fuel combustion resulting from stratum i during the year
t; t CO2-e
1, 2, 3, … M strata in the baseline scenario
1, 2, 3, … t* years elapsed since the start of the project activity
277
278
279
280
281
282
CH4 emissions due to enteric fermentation and N2O from manure and urine deposited on grassland
soils
To estimate CH4 emissions as a result of enteric fermentation and N2O emissions as a result of manure
and urine deposited on grassland soil during grazing Project Proponents shall use the tool “CH4
emissions due to enteric fermentation and N2O from manure and urine deposited on grassland soils”.
283
284
285
8.5 Leakage
Leakage resulting from the displacement of pre-project agricultural activities shall be calculated using
the CDM AR Tool: “Estimation of the increase in GHG emissions attributable to displacement of pre10
11
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 16
July 2012
286
287
project agricultural activities in A/R CDM project activity”12 and the tool “Leakage emissions from CH4
and N2O emissions as result of grazing animals”.
288
Therefore, leakage is estimated as follows:
t*
289
LK   LK AGRIC,t LK CH 4,enteric,t  LK N 2O , grazing,t
(11)
t 1
290
where:
LK
Total GHG emissions due to leakage; t CO2-e
LK AGRIC,t
Leakage due to the displacement of agricultural activities in year t, as calculated in
the tool “Estimation of the increase in GHG emissions attributable to displacement
of pre-project agricultural activities in A/R CDM project activity”; t CO2-e
LKCH 4 , enteric, t
Leakage emission from CH4 as a result of enteric fermentation, in year t; t CO2e
LK N 2Ograzing, t
Total leakage from N2O emissions as a result of manure and urine deposition, at
year t; t CO2e
291
292
293
294
295
8.6 Net project GHG emission reductions/removals
The net anthropogenic GHG removals by sinks is the actual net GHG removals by sinks minus the
baseline net GHG removals by sinks minus leakage, therefore, the following general formula can be used
to calculate the net anthropogenic GHG removals by sinks of an project activity (CFV-PS), in t CO2-e.
296
C FV  PS  C ACTUAL  C BSL  LK
297
where:
298
299
300
C FV  PS
Net anthropogenic GHG removals by sinks; t CO2-e
C ACTUAL
Actual net GHG removals by sinks; t CO2-e
CBSL
Baseline net GHG removals by sinks; t CO2-e
LK
Total GHG emissions due to leakage; t CO2-e
(12)
8.7 Estimation of uncertainty
Estimated carbon emissions and removals arising from AFOLU activities have uncertainties associated
with the measures/estimates of: area or other activity data, carbon stocks, biomass growth rates,
12
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 17
July 2012
301
302
303
expansion factors, and other coefficients. It is assumed that the uncertainties associated with the
estimates of the various input data are available, either as default values given in IPCC Guidelines
(2006), IPCC GPG-LULUCF (2003), expert judgement, or estimates based on sound statistical sampling.
304
305
306
307
Alternatively, (indisputably) conservative estimates can also be used instead of uncertainties, provided
that they are based on verifiable literature sources or expert judgement. In this case the uncertainty is
assumed to be zero. However, this module provides a procedure to combine uncertainty information
and conservative estimates resulting in an overall ex-post project uncertainty.
308
Uncertainty shall be estimated for all pools and sources accounted for in the methodology.
309
8.7.1 Assessment of uncertainty in baseline emissions and removals in project
310
To assess uncertainty across all pools and sources:
311
Uncertainty should be expressed as the 95% confidence interval as a percentage of the mean.
U
* EBSL, SS1   U BSL, SS 2 * EBSL, SS 2   ...  U BSL, SSn * EBSL, SSn 
2
2
2
312
Uncertaint y BSL,SS, 
313
Where:
314
315
UncertaintyBSL,SS
Percentage uncertainty in the combined carbon stocks and greenhouse gas
sources in the baseline case; %
316
317
318
319
UBSL,SSn
Percentage uncertainty (expressed as 95% confidence interval as a percentage
of the mean where appropriate) for carbon stocks and greenhouse gas sources
in the baseline case (1,2…n represent different carbon pools and/or GHG
sources); %
320
321
322
323
EBSL,SSn
Carbon stock or GHG sources (e.g. trees, down dead wood, soil organic carbon,
emission from fertilizer addition, emission from biomass burning etc.) (1,2…n
represent different carbon pools and/or GHG sources) in the baseline case; t
CO2-e
BSL, SS1,
EBSL, SS1  EBSL, SS 2  ...  EBSL, SSn
(13)
324
325
8.7.2 Assessment of uncertainty ex-post in the with-project scenario
326
Uncertainty should be expressed as the 95% confidence interval as a percentage of the mean.
327
328
Uncertaint y P 
U
* EP , SS1   U P , SS 2 * EP , SS 2   ...  U P , SSn * EP , SSn 
2
P , SS1
2
EP , SS1  EP , SS 2  ...  EP , SSn
2
(14)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 18
July 2012
329
Where:
330
331
UncertaintyP
Uncertainty in the combined carbon stocks and greenhouse gas sources in the
with-project case; %
332
333
334
335
UP,SSn
Percentage uncertainty (expressed as 95% confidence interval as a percentage
of the mean where appropriate) for carbon stocks, greenhouse gas sources and
leakage emissions in the with-project case (1,2…n represent different carbon
pools and/or GHG sources); %
336
337
338
339
EP,SSn
Carbon stock or GHG sources (e.g. trees, down dead wood, soil organic carbon,
emission from fertilizer addition, emission from biomass burning) (1,2…n
represent different carbon pools and/or GHG sources) in the with-project case; t
CO2-e
340
8.7.3 Calculate total error in the PS project activity
341
342
343
Calculation of leakage is conservative in all instances and therefore uncertainty is not considered here.
Total project uncertainty is therefore equal to the combined uncertainty in baseline and with-project
estimates:
344
C PS _ ERROR  Uncertaint y BSL  Uncertaint y P
345
Where:
346
CPS_ERROR
Total uncertainty for project activity; %
347
Uncertaint yBSL
Total uncertainty in baseline scenario; %
348
UncertaintyP
Total uncertainty in the with-project scenario; %
2
2
(15)
349
350
351
352
353
354
8.7.4 Implications for project accounting
The allowable uncertainty under this methodology is ±15 of the mean at the 95% confidence interval.
Where this precision level is met then there is no deduction for uncertainty. If the 95% confidence
interval is greater than 15% of the mean the reportable amount must include an Uncertainty Deduction.
The adjusted value to account for uncertainty shall be calculated as:
355
356
Adjusted _ C FV  PS ,t  C FV  PS ,t * 100%  C PS _ ERROR  15% 
357
Where:
358
359
Adjusted_ CFV-PS,t
(16)
Cumulative total net GHG emission reductions at time t adjusted to account for
uncertainty; t CO2-e
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 19
July 2012
360
CFV-PS,t
Cumulative total net GHG emission reductions at time t; t CO2-e
361
CPS_ERROR
Total uncertainty for REDD project activity; %
362
363
364
8.8 Calculation of PS Credits
365
PSt  Adjusted _ C FV  PS ,t2  Adjusted _ C FV  PS ,t1  BufferTOTAL
366
Where:
367
PSt
Number of PS Units at time t = t2 - t1; PS
368
369
Adjusted_CFV-PS,t2
Cumulative total net GHG emissions reductions at time t2 adjusted to account
for uncertainty; t CO2-e
370
Adjusted_CFV-PS,t1
Cumulative total net GHG emissions reductions at time t1; t CO2-e
371
BufferTOTAL
Total permanence risk buffer withholding; t CO2-e
To calculate the number of Panda Standard (PS) Credits for the monitoring period T = t2 –t1, this
methodology uses the following equation:


(17)
372
373
374
375
376
377
The final net emission reduction can be reported as the mean if precision is calculated to be within ±15%
of the mean at 95% confidence across the entire Project Boundary and not only within a Carbon Pool,
stratum, or Project Activity. If the 95% confidence interval is greater than 15% of the mean the
reportable amount must include an Uncertainty Deduction. The Uncertainty Deduction shall be equal to
the calculated % of the mean represented by the confidence interval minus the allowable 15%.
378
The Buffer is determined by a risk assessment conducted using the Panda Standard Risk Analysis Tool.
379
9 Monitoring
380
381
382
383
384
All data collected as part of monitoring should be archived electronically and be kept at least for
two years after the end of the last crediting period. One hundred percent of the data should be
monitored unless indicated otherwise in the tables below. All measurements should be conducted
according to relevant standards. In addition, the monitoring provisions in the tools referred to in this
methodology apply.
385
9.1 Monitoring of project implementation
386
Information shall be provided, and recorded in the PS Project Form to establish that:
387
388
(a) The geographic coordinates of the project boundary (and any stratification inside the
boundary) are established, recorded and archived;
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 20
July 2012
389
390
391
392
393
394
(b) Commonly accepted principles of forest inventory and management in the host country are
implemented. In absence of these, standard operating procedures (SOPs) and quality
control/quality assurance (QA/QC) procedures for inventory operations, including field data
collection and data management, shall be identified, recorded and applied. Use or
adaptation of SOPs available from published handbooks, or from the IPCC GPG LULUCF
2003, is recommended;
395
396
(c) The vegetation planting and management plan, together with a record of the plan as
actually implemented during the project, shall be available for validation and/or verification.
397
9.2 Sampling design
398
399
400
401
402
403
Vegetation activities that do not meet the PRC criteria for forest thresholds may result in a
heterogeneous arrangement of different planting formations across the landscape such as live fences,
areas of dispersed and evenly distributed or non-evenly distributed trees and non-tree woody
vegetation, and patches of vegetation that do not meet forest thresholds. Sample plots should be of an
appropriate size and shape for the configuration of vegetation in the stratum, and every part of the
stratum should have an equal probability of being sampled.
404
405
406
407
408
Stratification of the project area into relatively homogeneous units can either increase the measuring
precision without increasing the cost unduly, or reduce the cost without reducing measuring precision
because of the lower variance within each homogeneous unit. Project Proponents should present in the
PS Project Form an ex ante stratification of the project area or justify the lack of it. The number and
boundaries of the strata defined ex ante may change during the crediting period (ex post).
409
9.2.1 Precision requirements
410
411
The targeted precision level for biomass estimation across the project area is ±15% of the mean at a 95%
confidence level.
412
413
414
Project Proponents may use the latest version of the approved CDM AR tool “Calculation of the number
of sample plots for measurements within project activities” to determine the sample size and allocation
of sample plots among strata.
415
9.2.2 Updating of strata
416
The ex post stratification shall be updated because of the following reasons:
417
418

Unexpected disturbances occurring during the crediting period (e.g. due to fire, pests or
disease outbreaks), affecting differently various parts of an originally homogeneous stratum;
419
420

Land management activities (cleaning, planting, thinning, harvesting, coppicing, rereplanting) that are implemented in a way that affects the existing stratification.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 21
July 2012
421
Established strata may be merged if reasons for their establishing have disappeared.
422
9.3 Data and parameters available at validations (default or possibly
measured one time)
423
424
Parameters are listed within the Tools applied.
425
426
427
428
In choosing key parameters or making important assumptions based on information that is not specific
to the project circumstances, such as in use of existing published data, Project Proponents should retain
a conservative approach: that is, if different values for a parameter are equally plausible, a value that
does not lead to over-estimation of net anthropogenic GHG removals by sinks should be selected.
429
430
9.4 Data and parameters monitored
431
432
433
434
435
436
When applying all relevant equations provided in this methodology for the ex ante calculation of net
anthropogenic GHG removals by sinks, Project Proponents shall provide transparent estimations for the
parameters that are monitored during the crediting period. These estimates shall be based on
measured or existing published data where possible and Project Proponents should retain a
conservative approach: that is, if different values for a parameter are equally plausible, a value that
does not lead to over-estimation of net anthropogenic GHG removals by sinks should be selected.
Parameters are listed within the Tools applied.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 22
July 2012
Annex A: Tools for estimation of carbon pools and sources
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 23
July 2012
1
2
Tool Ctree: Estimation of carbon stocks and change in carbon stocks of
trees
3
4
5
Source
6
Assumptions
7
This tool makes the following assumptions:
Tool is based off of the CDM A/R Methodological Tool “Estimation of carbon stocks and change in
carbon stocks of trees and shrubs in A/R CDM project activities” (Version 02.1.0)13
8
(a)
9
10
Linearity of biomass growth for trees
Growth of biomass in trees may be assumed to proceed on average at an approximately
constant rate between two points in time at which biomass is estimated.
11
(b)
12
13
14
Appropriateness of root-shoot ratios
Root-shoot ratios appropriate for estimation of below-ground biomass from aboveground biomass under forest/continuous-cover conditions are appropriate for all trees
within the project boundary.
15
Parameters
16
This tool provides procedures to determine the following parameters:
17
18
Table 3: Parameters determined
Parameter
SI Unit
Description
CTREE ,t
t CO2-e
Carbon stock in tree biomass within the project boundary at a given
point of time in year t
CTREE , t
t CO2-e
Change in carbon stock in tree biomass within the project boundary
in year t
19
While applying this tool in a methodology, the following notation should be used:
20
In the baseline scenario:
13
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 24
July 2012
21
CTREE _ BSL,t for CTREE ,t
22
CTREE _ BSL,t for CTREE , t
23
In the project scenario:
24
CTREE _ PROJ ,t for CTREE ,t
25
CTREE _ PROJ , t for CTREE , t
26
27
28
29
30
31
32
33
34
35
36
Methods
37
38
39
40
41
42
43
44
45
46
47
48
49
50
1. Carbon stock in tree biomass is estimated on the basis of one or more tree biomass strata.
2. For the purpose of this tool, the term species also implies a group of species when a biometric
parameter (e.g. biomass expansion factor, root-shoot ratio, basic wood density, carbon fraction) or a
model (e.g. allometric equation, volume table) is applicable to more than one species.
3. Carbon stock and change in carbon in trees is estimated by applying one of the following methods,
each applicable under its specific conditions.
a. Stock change method;
This method is applicable when temporary sample plots are used. Under this method, first
the carbon stock in trees at a point of time is estimated and then the change in carbon stock
in a year is calculated on the basis of two successive stocks.
b. Increment method;
This method is applicable when permanent sample plots are used and are remeasured on
successive verifications. Under this method, first the change in carbon stock between two
successive verifications is estimated and then the carbon stock at a given point of time in a
year is calculated on the basis of the change in carbon stock and the previous value of
carbon stock at a given point of time.
c. Default method;
This method is applicable only for estimation of carbon stock and change in carbon stock in
trees in the baseline when any of the methods (a) and (b) above cannot be applied for lack
of data, or when the mean tree crown cover in the baseline is less than 20% of the threshold
crown cover reported by the host Party under paragraph 8 of the annex to decision 5/CMP.1
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 25
July 2012
51
52
4. For additional information on approaches to estimate living tree biomass in the field see “Annex B
Guidance on Estimating biomass in living trees at the start of the project activity”.
53
54
55
56
Method 1: Stock change Method
Under stock change method carbon stock in trees within the project boundary is estimated at the time
of verification. Change in carbon stock in trees between two successive verifications is calculated as the
difference between the two estimated stocks
57
58
59
M1 Step 1 Estimation of biomass stock in trees
Biomass of trees of species j per unit area in stratum i at a given point of time in year t is calculated on
the basis of one or more tree dimensions (e.g. diameter, basal area, height).
60
The tree dimensions are obtained using one of the following procedures:
61
62
(a) For ex ante estimation, the tree dimensions are taken from existing data sources such as
yield tables, tree growth curves, or tree growth models;
63
64
65
66
67
68
69
(b) For ex post estimation, the tree dimensions are obtained from field measurements.
Measurements are carried out on all the trees in sample plots laid down in each stratum using
either representative random or systematic sampling. Number of sample plots and their
allocation to different strata required for a targeted precision may be calculated using the CDM
tool “Calculation of the number of sample plots for measurements within A/R CDM project
activities”. In exceptional situations, measurements may be carried out on all the trees in a
stratum where trees are few and scattered out.
70
Tree dimensions are converted to tree biomass by applying one of the following methods:
71
(a) Biomass expansion factor (BEF) method;
72
(b) Allometric equation method.
73
M1 Step 1a Estimation of tree biomass using BEF method
74
75
76
77
Under this method volume tables or volume equations are used to convert tree dimensions to stem
volume of trees. Stem volume of trees is converted to above-ground tree biomass using basic wood
density and biomass expansion factors, and the above-ground tree biomass is expanded to total tree
biomass using root-shoot ratios. Thus, biomass of trees of species j in sample plot p is estimated as:
78
BTREE , j , p ,i ,t  VTREE , j , p ,i ,t  D j  BEF2, j  (1  R j )
79
where:
BTREE , j , p ,i ,t
VTREE , j , p ,i ,t
(18)
Biomass of trees of species j in sample plot p of stratum i at a point of time in
year t; t d.m.
Stem volume of trees of species j in sample plot p of stratum i at a point of time
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 26
July 2012
Dj
Rj
Biomass expansion factor for conversion of stem biomass to above-ground tree
biomass, for tree species j; dimensionless
Root-shoot ratio for tree species j; dimensionless
J
P
I
t
1, 2, 3, … tree species in plot p
1, 2, 3, … sample plots in stratum i
1, 2, 3, … tree biomass estimation strata within the project boundary
1, 2, 3, … years counted from the start of the project activity
BEF2 , j
80
81
in year t, estimated by using the tree dimension(s) as entry data into a volume
table or volume equation; m3
Basic wood density of tree species j; t d.m. m-3
The volume table or volume equation applicable to a species is selected from the following sources (the
most preferred source being listed first):
82
83
(a) Existing data applicable to local situation (e.g.
conditions);
represented by similar ecological
84
(b) National data (e.g. from national forest inventory or national GHG inventory);
85
(c) Data from neighbouring countries with similar conditions;
86
(d) Globally applicable data.
87
While applying Equation (1), it is ensured that the parameters VTREE, j , p , i , t and BEF2 , j are compatible,
88
i.e. both are based either on over-bark volume or on under-bark volume. If VTREE , j , p , i , t is obtained from
89
a volume table or volume equation giving under-bark volume (i.e. commercial volume, rather than gross
90
stem volume), and the biomass expansion factor BEF2 , j is based on over-bark volume (or vice versa),
91
92
93
then a bark correction factor is applied. For the purpose of applying this correction, volume of bark is
assumed to be 15% of the volume of the wood (i.e. the under-bark volume), unless transparent and
verifiable information can be provided to justify a different value.
94
M1 Step 1b Estimation of tree biomass using allometric method
95
96
97
Under this method allometric equations are used to convert tree dimensions to above-ground biomass
of trees and the above-ground tree biomass is expanded to total tree biomass using root-shoot ratios.
Thus, biomass of trees of species j in sample plot p is calculated as:
98
BTREE, j , p ,i ,t  f j ( DBH t , H t )  (1  R j )
(19)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 27
July 2012
99
where:
Rj
Biomass of trees of species j in sample plot p of stratum i at a given point of
time in year t; t d.m.
Sum of above-ground biomass of trees of species j in sample plot p of stratum i
at a given point of time in year t calculated using allometric function returning
total above-ground tree biomass on the basis of tree dimensions as entry data;
t d.m.
Alternatively, other approaches allowing estimation of tree biomass per
hectare (e.g. using a relascope) may be applied to calculate the total aboveground biomass of trees of species j in sample plot p of stratum i at a given
point of time in year t
Root-shoot ratio for tree species j; dimensionless
J
P
I
t
1, 2, 3, … tree species in plot p
1, 2, 3, … sample plots in stratum i
1, 2, 3, … tree biomass estimation strata within the project boundary
1, 2, 3, … years counted from the start of the project activity
BTREE , j , p ,i ,t
f j ( DBH t , H t )
100
101
102
The allometric equations applicable to a tree species or a group of tree species are selected using the
same procedure as prescribed for selection of volume tables or volume equations in paragraphs 12 and
13 above.
103
104
M1 Step 2 Estimation of the total tree biomass within the project boundary
1. Tree biomass in sample plot p of stratum i is estimated as follows:
105
BTREE , p ,i ,t   BTREE , j , p ,i ,t
(20)
j
106
where:
BTREE , p ,i ,t
BTREE , j , p ,i ,t
J
P
I
t
107
2.
108
bTREE , p ,i ,t 
Tree biomass in sample plot p in stratum i at a given point of time in year t;
t d.m.
Biomass of trees of species j in sample plot p of stratum i at a given point of
time in year t; t d.m.
1, 2, 3, … species in plot p
1, 2, 3, … sample plots in stratum i
1, 2, 3, … strata used for tree biomass estimation within the project boundary
1, 2, 3, … years counted from the start of the project activity
Tree biomass per hectare in plot p in stratum i is estimated as follows:
BTREE , p ,i ,t
Ap ,i
(21)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 28
July 2012
109
where:
BTREE , p ,i ,t
Tree biomass per hectare in sample plot p in stratum i at a given point of time in
year t; t d.m. ha-1
Tree biomass in sample plot p in stratum i at a given point of time in year t; t d.m.
Ap , i
Area of sample plot p in stratum i; ha
P
I
t
1, 2, 3, … sample plots in stratum i
1, 2, 3, … tree biomass estimation strata within the project boundary
1, 2, 3, … years counted from the start of the project activity
bTREE, p , i ,t
110
3.
Mean tree biomass per hectare in stratum i and its variance are estimated as follows:
ni
111
b
p 1
bTREE,i ,t 
TREE , p , i , t
 ni

2
ni *  bTREE , p ,i ,t    bTREE , p ,i ,t 
p 1
 p 1

si2 
ni * (ni  1)
ni
112
113
2
(23)
where:
Mean tree biomass per hectare in stratum i at a given point of time in year t;
t d.m. ha-1
Tree biomass per hectare in sample plot p in stratum i at a given point of time in
year t; t d.m. ha-1
Number of sample plots in stratum i
bTREE , i ,t
bTREE, p , i ,t
ni
Variance of mean tree biomass per hectare in stratum i at a given point of time in
year t; (t d.m. ha-1)2
si2
114
115
(22)
ni
4.
Mean tree biomass per hectare within the project boundary and its variance are estimated as
follows:
M
116
bTREE ,t   wi * bTREE ,i ,t
(24)
si2
  wi *
i 1
ni
(25)
i 1
117
s
2
bTREE
M
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 29
July 2012
118
where:
ni
Mean tree biomass per hectare within the project boundary at a given point of
time in year t; t d.m. ha-1
Ratio of the area of stratum i to the sum of areas of biomass estimation strata;
dimensionless
Mean tree biomass per hectare in stratum i at a given point of time in year t;
t d.m. ha-1
Variance of mean tree biomass per hectare within the project boundary at a
given point of time in year t; (t d.m. ha-1)2
Variance of mean tree biomass per hectare in stratum i at a given point of time in
year t; (t d.m. ha-1)2
Number of sample plots in stratum i
M
Number of tree biomass estimation strata within the project boundary
bTREE ,t
wi
bTREE , i ,t
sb2TREE
si2
119
5.
Margin of error of the mean tree biomass per hectare within the project boundary is estimated as:
120
ebTREE  tVAL * sbTREE
121
where
ebTREE
tVAL
sbTREE
(26)
Margin of error of the mean tree biomass per hectare within the project
boundary; t d.m. ha-1
Two-sided Student’s t-value for: (i) degrees of freedom equal to n – M, where n is
total number of sample plots within the project boundary, and M is the total
number of tree biomass estimation strata; and (ii) the confidence level required
by the methodology applying this tool (e.g. 90% or 95%); dimensionless
E.g.: Two-sided Student’s t-value for a probability value of 10% (which implies a
90% confidence level) and 45 degrees of freedom can be obtained in Excel
spreadsheet as “=TINV(0.10,45)” which returns a value of 1.6794
Square root of the variance of mean tree biomass per hectare in stratum i at a
given point of time in year t (i.e. the standard error of the mean); t d.m. ha-1
122
1. If ebTREE / bTREE ,t *100% is greater than the maximum allowable relative margin of error of the mean
123
124
125
126
127
128
prescribed in the methodology, then additional sample plots are installed. The number of sample
plots for the required allowable relative margin of error of the mean may be calculated using the
tool “Calculation of the number of sample plots for measurements within A/R CDM project
activities” with the data on stratum level variance estimated in Equation (6).
2. Mean tree biomass within the project boundary at a given point of time in year t is estimated as
follows:
129
BTREE ,t  A  bTREE ,t
(27)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 30
July 2012
130
where
BTREE ,t
Mean tree biomass within the project boundary at a given point of time in year t;
t d.m.
A
Sum of areas of the biomass estimation strata within the project boundary; ha
bTREE ,t
Mean tree biomass per hectare within the project boundary at a given point of
time in year t; t d.m. ha-1
131
132
3. Finally, carbon stock in tree biomass within the project boundary at a given point of time in year t is
estimated as follows:
133
CTREE,t 
134
where
44
 BTREE,t  CFTREE
12
CTREE ,t
BTREE ,t
CFTREE
(28)
Carbon stock in tree biomass within the project boundary at a given point of time
in year t; t CO2-e
Mean tree biomass within the project boundary at a given point of time in year t;
t d.m.
Carbon fraction of tree biomass; t C t d.m.-1
A default value of 0.50 is used unless transparent and verifiable information can
be provided to justify a different value
135
M1 Step 3 Estimation of change in carbon stock in trees ( CTREE )
136
137
138
1. The rate of change of tree biomass over a period of time is calculated assuming a linear growth.
Therefore, the rate of change in carbon stock in tree biomass over a period of time is calculated as
follows:
139
dCTREE, (t1 ,t 2 ) 
140
where:
dCTREE , ( t1 ,t 2 )
CTREE,t 2
CTREE,t 2  CTREE,t1
T
(29)
Rate of change in carbon stock in tree biomass within the project boundary during the
period between a point of time in year t1 and a point of time in year t2; t CO2-e yr-1
Carbon stock in tree biomass within the project boundary at a point of time in year t2;
t CO2-e
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 31
July 2012
CTREE ,t1
T
Carbon stock in tree biomass within the project boundary at a point of time in year t1;
t CO2-e
Time elapsed between two successive estimations (T=t2 – t1); yr
141
2. For the first verification, the variable CTREE ,t1 in Equation (12) is assigned the value of carbon stock
142
in the pre-project tree biomass, that is: CTREE , t1  CTREE _ BSL for the for the first verification, where
143
144
145
146
t1 = 1 and t2 = “year of first verification”.
3. Change in carbon stock in tree biomass within the project boundary in year t (t1  t  t2) is calculated
as follows:
147
CTREE,t  dCTREE, (t1 ,t 2 )  1year for t1  t  t2
148
where:
(30)
CTREE , t
Change in carbon stock in tree biomass within the project boundary in year t; t CO2-e
dCTREE , (t1 ,t 2 )
Rate of change in carbon stock in tree biomass within the project boundary during the
period between a point of time in year t1 and a point of time in year t2; t CO2-e yr-1
149
150
151
152
153
Method 2 Increment Method
Increment method is used when trees in the same sample plots are measured on two successive
verifications. Individual trees are identified and biomass increment of each tree between two
successive verifications is estimated. If a tree measured at the time of the earlier verification cannot
be found at the time of the later verification (i.e. the tree is missing or is dead), then its biomass on the
154
155
later verification is recorded as zero. If a new trees is found at the time of the later verification, then
its biomass at the time of earlier verification is recorded as zero.
156
The tree dimensions are obtained using one of the following procedures:
1
157
158
(a) For ex ante estimation, the tree dimensions are taken from existing data sources such as
yield tables, tree growth curves, or tree growth models;
159
160
161
162
163
164
165
(b) For ex post estimation, the tree dimensions are obtained from field measurements.
Measurements are carried out on all the trees in sample plots laid down in each stratum using
either representative random or systematic sampling. Number of sample plots and their
allocation to different strata required for a targeted precision may be calculated using the CDM
tool “Calculation of the number of sample plots for measurements within A/R CDM project
activities”. In exceptional situations, measurements may be carried out on all the trees in a
stratum where trees are few and scattered out.
166
Tree dimensions are converted to tree biomass by applying one of the following methods:
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 32
July 2012
167
(a) Biomass expansion factor (BEF) method;
168
(b) Allometric equation method.
169
170
171
M2 Step 1 Estimation of change in carbon stock in trees
1. Biomass of an individual tree l of species j in sample plot p is estimated as follows:
172
BTREE ,l , j , p ,i ,t  VTREE ,l , j , p ,i ,t  D j  BEF2, j  (1  R j )
173
174
(31)
Or
BTREE ,l , j , p ,i ,t  f j ( DBH t , H t )  (1  R j )
(32)
175
176
where:
BTREE,l , j , p ,i ,t
Biomass of individual tree l of species j in sample plot p of stratum i at a point
of time in year t; t d.m.
VTREE ,l , j , p ,i ,t
Stem volume of individual tree l of species j in sample plot p of stratum i at a
point of time in year t, estimated by using the tree dimension(s) as entry data
into a volume table or volume equation; m3
Dj
Basic wood density of tree species j; t d.m. m-3
BEF2 , j
Biomass expansion factor for conversion of stem biomass to above-ground tree
biomass, for tree species j; dimensionless
Rj
Root-shoot ratio for tree species j; dimensionless
f j ( DBH t , H t )
Sum of above-ground biomass of trees of species j in sample plot p of stratum i
at a given point of time in year t calculated using allometric function returning
total above-ground tree biomass on the basis of tree dimensions as entry data;
t d.m.
Alternatively, other approaches allowing estimation of tree biomass per
hectare (e.g. using a relascope) may be applied to calculate the total aboveground biomass of trees of species j in sample plot p of stratum i at a given
point of time in year t
j
1, 2, 3, … tree species in plot p
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 33
July 2012
P
1, 2, 3, … sample plots in stratum i
I
1, 2, 3, … tree biomass estimation strata within the project boundary
t
1, 2, 3, … years counted from the start of the project activity
177
178
179
180
2. Change in biomass of an individual tree l of species j in sample plot p of stratum i between two
successive verifications is estimated as follows:
181
BTREE ,l , j , p ,i ,(t1,t 2)  BTREE ,l , j , p ,i ,t 2  BTREE ,l , j , p ,i ,t1
182
where:
BTREE ,l , j , p ,i ,(t1,t 2 )
Change in biomass of tree l of species j in sample plot p of stratum i between
the earlier verification carried out at time t1 and the later verification carried
out at time t2; t d.m.
BTREE,l , j , p ,i ,t 2
Biomass of tree l of species j in sample plot p of stratum i at time t2; t d.m.
BTREE , j , p ,i ,t1
Biomass of tree l of species j in sample plot p of stratum i at time t1; t d.m.
l
1, 2, 3, ... trees of species j in plot p
j
1, 2, 3, … species in plot p
p
1, 2, 3, … sample plots in stratum i
i
1, 2, 3, … strata used for tree biomass estimation within the project boundary
t
1, 2, 3, … years counted from the start of the project activity
183
184
185
3. Change in tree biomass in plot p in stratum i is estimated as follows:
186
BTREE , p ,i ,(t1,t 2 )   BTREE ,l , j , p ,i ,(t1,t 2 )
j
187
(33)
(34)
l
where:
BTREE , p ,i ,(t1,t 2 )
Change in tree biomass in sample plot p of stratum i between the earlier
verification carried out at time t1 and the later verification carried out at time
t2; t d.m.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 34
July 2012
188
189
BTREE ,l , j , p ,i ,(t1,t 2 )
Change in biomass of tree l of species j in sample plot p of stratum i between
the earlier verification carried out at time t1 and the later verification carried
out at time t2; t d.m.
l
1, 2, 3, ... trees of species j in plot p
j
1, 2, 3, … species in plot p
p
1, 2, 3, … sample plots in stratum i
i
1, 2, 3, … strata used for tree biomass estimation within the project boundary
t
1, 2, 3, … years counted from the start of the project activity
4. Change in tree biomass per hectare in plot p in stratum i is estimated as follows
190
bTREE ,i ,(t1,t 2 ) 
191
where:
bTREE ,i ,(t1,t 2 )
BTREE , p ,i ,(t1,t 2 )
192
193
194
BTREE , p ,i ,(t1,t 2 )
A p ,i
(35)
Change in tree biomass per hectare in sample plot p of stratum i between the
earlier verification carried out at time t1 and the later verification carried out at
time t2; t d.m. ha-1
Change in tree biomass in sample plot p of stratum i between the earlier
verification carried out at time t1 and the later verification carried out at time t2;
t d.m..
Ap , i
Area of sample plot p in stratum i; ha
p
1, 2, 3, … sample plots in stratum i
i
1, 2, 3, … tree biomass estimation strata within the project boundary
t
1, 2, 3, … years counted from the start of the project activity
5. Mean change in tree biomass per hectare in stratum i and variance of the change in tree biomass
per hectare in the stratum are estimated as follows
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 35
July 2012
 b
TREE , p ,i ,( t1,t 2 )
195
bTREE,i ,(t1,t 2) 
p
 ni

2
ni *  bTREE, p ,i ,(t1,t 2)    bTREE, p ,i ,(t1,t 2) 
p 1
 p 1


ni * (ni  1)
ni
196
s2 ,i
197
where:
bTREE, i ,(t1,t 2)
bTREE , p ,i ,( t1,t 2 )
198
199
200
(36)
ni
2
(37)
Mean change in tree biomass per hectare in stratum i between the earlier
verification carried out at time t1 and the later verification carried out at time t2;
t d.m. ha-1
Tree biomass per hectare in sample plot p in stratum i between the earlier
verification carried out at time t1 and the later verification carried out at time t2;
t d.m ha-1
ni
Number of sample plots in stratum i
s2 ,i
Variance of change in tree biomass per hectare in stratum i between the earlier
verification carried out at time t1 and the later verification carried out at time t2;
(t d.m. ha-1)2
6. Mean change in tree biomass per hectare within the project boundary and its variance are
estimated as follows:
M
bTREE ,t   wi * bTREE ,i ,(t1,t 2 )
201
(38)
i 1
203
M
s 2 ,i
i 1
ni
s 2bTREE   wi *
202
(39)
where:
bTREE ,t
Mean change in tree biomass per hectare within the project boundary between
the earlier verification carried out at time t1 and the later verification carried out
at time t2; t d.m. ha-1
wi
Ratio of the area of stratum i to the sum of areas of biomass estimation strata;
dimensionless
bTREE ,i ,(t1,t 2 )
Mean change in tree biomass per hectare in stratum i between the earlier
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 36
July 2012
verification carried out at time t1 and the later verification carried out at time t2;
t d.m. ha-1
s2bTREE
s2 ,i
204
205
206
Variance of mean change in tree biomass per hectare within the project
boundary between the earlier verification carried out at time t1 and the later
verification carried out at time t2; (t d.m. ha-1)2
Variance of change in tree biomass per hectare in stratum i between the earlier
verification carried out at time t1 and the later verification carried out at time t2;
(t d.m. ha-1)2
ni
Number of sample plots in stratum i
M
Number of tree biomass estimation strata within the project boundary
i
1, 2, 3, . tree biomass estimation strata within the project boundary
7. Margin of error of the mean change in tree biomass per hectare within the project boundary is
estimated as:
207
ebTREE  tVAL * sbTREE
208
where
ebTREE
tVAL
(40)
Margin of error of the mean change in tree biomass per hectare within the
project boundary between the earlier verification carried out at time t1 and the
later verification carried out at time t2; t d.m. ha-1
Two-sided Student’s t-value for: (i) degrees of freedom equal to n – M, where n is
Total number of sample plots within the project boundary, and M is the total
number of tree biomass estimation strata; and (ii) the confidence level required
by the methodology applying this tool (e.g. 90% or 95%); dimensionless
E.g.: Two-sided Student’s t-value for a probability value of 10% (which implies a
90% confidence level) and 45 degrees of freedom can be obtained in Excel
spreadsheet as “=TINV(0.10,45)” which returns a value of 1.6794
s bTREE
209
Square root of the variance of mean change in tree biomass per hectare within
the project boundary between the earlier verification carried out at time t1 and
the later verification carried out at time t2 (i.e. the standard error of the mean);
t d.m. ha-1
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 37
July 2012
ebTREE / btree(t1,t 2) *100% must be less
210
8. The relative margin of error of the mean calculated as
211
212
213
214
than or equal to the maximum allowable relative margin of error of the mean prescribed in the
methodology.
9. Change in tree biomass within the project boundary between the earlier verification carried out at
time t1 and the later verification carried out at time t2 is estimated as follows:
215
BTREE,(t1,t 2)  A  bTREE,(t1,t 2)
216
where
(41)
BTREE,t
Change in tree biomass within the project boundary between the earlier
verification carried out at time t1 and the later verification carried out at time t2;
t d.m.
A
Sum of areas of the biomass estimation strata within the project boundary; ha
bTREE,(t1,t 2)
217
218
Mean change in tree biomass per hectare within the project boundary between
the earlier verification carried out at time t1 and the later verification carried out
at time t2; t d.m. ha-1
10. Change in carbon stock in tree biomass within the project boundary between the earlier verification
carried out at time t1 and the later verification carried out at time t2 is estimated as follows:
219
CTREE,(t1,t 2) 
220
where
CTREE,(t1,t 2)
BTREE ,(t1,t 2 )
CFTREE
44
 BTREE,(t 2,t1)  CFTREE
12
(42)
Change in carbon stock in tree biomass within the project boundary between the
earlier verification carried out at time t1 and the later verification carried out at
time t2; t CO2-e
Change in tree biomass within the project boundary between the earlier
verification carried out at time t1 and the later verification carried out at time t2;
t d.m.
Carbon fraction of tree biomass; t C t d.m.-1
A default value of 0.50 is used unless transparent and verifiable information can
be provided to justify a different value
221
222
M2 Step 2 Estimation of carbon stock in trees
1. Rate of change of carbon stock in trees between the years t2 and t1 is estimated as follows:
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 38
July 2012
223
dCTREE,(t1 ,t2 ) 
224
where:
CTREE,(t1,t 2)
T
(43)
dCTREE , (t1 ,t 2 )
Rate of change in carbon stock in tree biomass within the project boundary during the
period between a point of time in year t1 and a point of time in year t2; t CO2-e yr-1
CTREE,(t1,t 2)
Change in carbon stock in tree biomass within the project boundary between the earlier
verification carried out at time t1 and the later verification carried out at time t2; t CO2-e
T
Time elapsed between two successive estimations (T=t2 – t1); yr
225
226
2. Carbon stock in tree biomass within the project boundary at a point of time in year t falling between
t1 and t2 is estimated as follows:
227
CTREE,t  CTREE,t 1  dCTREE,(t1 ,t2 )  1year
228
where:
CTREE ,t
CTREE,t 1
dCTREE , (t1 ,t 2 )
(44)
Carbons stock in tree biomass within the project boundary at a point of time in year t;
t CO2-e
Carbons stock in tree biomass within the project boundary at a point of time in
year t . 1; t CO2-e
Rate of change in carbon stock in tree biomass within the project boundary during the
period between a point of time in year t1 and a point of time in year t2; t CO2-e yr-1
229
230
Method 3 Default methods for estimation of C stock and change in C stock in trees in baseline
231
232
233
234
This method is applicable only for estimation of carbon stock and change in carbon stock in trees in the
baseline when any of the methods above cannot be applied for lack of data, or when the mean tree
crown cover in the baseline is less than 20% of the threshold crown cover reported by the host Party
under paragraph 8 of the annex to decision 5/CMP.1
235
Carbon stock and change in carbon stock in trees in the baseline are estimated as follows:
236
CTREE _ BSL,i 
44
 CFTREE _ BSL  BFOREST  (1  RTREE _ BSL )  CCTREE _ BSL,i  ABSL,i
12
(45)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 39
July 2012
237
CTREE _ BSL,i 
238
where:
44
 CFTREE _ BSL  BFOREST  (1  RTREE _ BSL )  CCTREE _ BSL,i  ABSL,i
12
(46)
CTREE _ BSL,i
Carbon stock in living trees in the baseline, in baseline stratum i; t CO2-e. Baseline
strata are delineated on the basis of tree crown cover
CFTREE _ BSL
Default carbon fraction of tree biomass in the baseline; dimensionless. A default
value of 0.50 may be used, t C (t.d.m.)-1
BFOREST
Default above-ground biomass content in forest in the region/country where the
project is located; t d.m. ha-1
RTREE _ BSL
Default root-shoot ratio for the trees in the baseline; dimensionless. A default value
of 0.25 may be used
CCTREE _ BSL, i
Crown cover of trees in the baseline, in baseline stratum i, expressed as a fraction
(e.g. 10% crown cover implies CCTREE _ BSL, i =0.10)
CTREE _ BSL,i
Average annual change in carbon stock in tree biomass in the baseline; t CO2-e yr-1
BFOREST
Default average annual increment of above-ground biomass in forest in the
region/country where the project is located; t d.m. ha-1 yr-1
ABSL,i
Area of stratum i in the baseline, delineated on the basis of crown cover; ha
239
Parameter Tables
240
Data and parameters not monitored
Data / Parameter:
BEF2,j
Data unit:
Used in equations:
Description:
Dimensionless
Biomass expansion factor for conversion of stem biomass to aboveground biomass for tree species j
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 40
July 2012
Source of data:
Comments:
The source of data shall be selected, in order of preference, from the
following: (a) Local sources of species-specific data; (b) National
sources of species-specific data (e.g. national forest inventory or
national GHG inventory); (c) Species-specific data from neighbouring
countries with similar conditions; (d) Globally available data applicable
to the species; (e) IPCC default values (e.g. Table 3A.1.10 of IPCC GPGLULUCF 2003). (Although the BEFs in Table 3A.1.10 apply to biomass,
the dimensionless factors can be equally applied for wood volume
expansions.)
BEFs in IPCC literature and national inventory are usually applicable to
closed canopy forest. If applied to individual trees growing in an open
field it is recommended that the selected BEF be increased by 30%
Data / Parameter:
BFOREST
Data unit:
t d.m. ha-1
Used in equations:
Description:
Default above-ground biomass content in forest in the region/country
where the project is located
Source of data:
The source of data shall be selected, in order of preference, from the
following: (a) Regional/national inventories e.g. national forest
inventory, national GHG inventory; (b) Inventory from neighbouring
countries with similar conditions; (c) Globally available data applicable
to the project site or to the region/country where the site is located
(e.g. latest data from FAO); (d) IPCC default values from Table 3A.1.4 of
IPCC GPG-LULUCF 2003
Data / Parameter:
∆BFOREST
Data unit:
t d.m. ha-1 yr-1
Used in equations:
Description:
Source of data:
Default average annual increment in above-ground biomass in forest in
the region/country where the project is located
The source of data shall be selected, in order of preference, from the
following: (a) Regional/national inventories e.g. national forest
inventory, national GHG inventory; (b) Inventory from neighbouring
countries with similar conditions; (c) Globally available data applicable
to the project site or to the region/country where the site is located
(e.g. latest data from FAO); (d) IPCC default values from Table 3A.1.5 of
IPCC GPG-LULUCF 2003
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 41
July 2012
Comments:
(i) Trees biomass may reach a steady state, when biomass growth
becomes zero or insignificant – either because of biological maturity of
trees or because the rate of anthropogenic biomass extraction from
the area is equal to the rate of biomass growth. Therefore, this
parameter should be taken to be zero after the year in which tree
biomass in baseline reaches a steady state. The year in which tree
biomass in baseline reaches steady-state is taken to be the 20th year
from the start of the CDM project activity, unless transparent and
verifiable information can be provided to justify a different value. (ii)
When land is subjected to periodic slash-and-burn practices in the
baseline, the average tree biomass is constant, and hence value of this
parameter is set equal to zero.
Data / Parameter:
Dj
Data unit:
t d.m. m-3
Used in equations:
Description:
Source of data:
Basic wood density for species j
The source of data, in order of preference, shall be any of the
following: (a) National and species-specific data (e.g. from national
GHG inventory); (b) Species-specific data from neighbouring countries
with similar conditions; (c) Globally available species-specific data (e.g.
Table 3A.1.9 IPCC GPG-LULUCF 2003)
Data / Parameter:
Rj
Data unit:
Used in equations:
Description:
Source of data:
Dimensionless
Root-shoot ratio for species j
The source of data, in order of preference, shall be any of the
following: (a) Existing local species-specific data; (b) National speciesspecific data (e.g. national forest inventory or national GHG inventory);
(c) Species-specific data from neighbouring countries with similar
conditions; (d) Globally available species-specific data. If none of the
above sources are available, then the value of Rj may be calculated as
R = exp[-1.085+0.9256*ln(A)]/A, where A is above-ground biomass (t
d.m. ha-1) [Source: Table 4.A.4 of IPCC GPG-LULUCF 2003]
241
242
Data and parameters monitored
Data / Parameter:
Ai
Data unit:
Used in equations:
Ha
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 42
July 2012
Description:
Source of data:
Measurement procedures:
Monitoring frequency:
QA/QC procedures:
Area of stratum i
Field measurement
Standard operating procedures (SOPs) prescribed under national forest
inventory are applied. In absence of these, SOPs from published
handbooks, or from the IPCC GPG LULUCF 2003, may be applied.
Delineation of strata boundaries should preferably be done in such
way that it can be easily migrated to a Geographical Information
System (GIS) which facilitates integration of data from different
sources (including GPS coordinates and remotely sensed data)
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In the absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
Data / Parameter:
Ap,i
Data unit:
Used in equations:
Description:
Source of data:
Measurement procedures:
Ha
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
Sample plot location is registered with a GPS and marked on the
project map
Comments:
Area of sample p in stratum stratum i
Field measurement
Standard operating procedures (SOPs) prescribed under national forest
inventory are applied. In absence of these, SOPs from published
handbooks, or from the IPCC GPG LULUCF 2003, may be applied
Data / Parameter:
CCTREE_BSL,i
Data unit:
Used in equations:
Description:
Dimensionless
Source of data:
Field measurement
Crown cover of trees in the baseline, in baseline stratum i, expressed
as a fraction (e.g. 10% crown cover implies CCTREE_BSL,I =0.10)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 43
July 2012
Measurement procedures:
Monitoring frequency:
QA/QC procedures:
Data / Parameter:
Data unit:
Used in following equations:
Description:
Source of data:
Measurement procedures (if
any):
Considering that the biomass in trees in the baseline is smaller
compared to the biomass in trees in the project, a simplified method of
measurement may be used for estimating tree crown cover. Ocular
estimation of tree crown cover may be carried out or any other
method such as the line transect method or the relascope method may
be applied
NA
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
DBH
cm or any unit of length
Usually the diameter at breast height of the tree; but it could be any
other diameter or dimensional measurement (e.g. basal diameter,
root-collar diameter, basal area, etc.) applicable for the model or data
source used
Field measurements in sample plots. For ex ante estimations, DBH
values should be estimated using a growth curve, a growth model, or a
yield table that gives the expected tree dimensions as a function of
tree age
Standard operating procedures (SOPs) prescribed under national forest
inventory are applied. In absence of these, SOPs from published
handbooks, or from the IPCC GPG LULUCF 2003, may be applied
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In the absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
Data / Parameter:
Data unit:
Used in equations:
Description:
Source of data:
H
m or any other unit of length
Height of tree
Field measurements in sample plots. For ex ante estimations, H values
should be estimated using a growth curve, a growth model, or a yield
table that gives the expected tree dimensions as a function of tree age
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 44
July 2012
Measurement procedures (if
any):
Standard operating procedures (SOPs) prescribed under national forest
inventory are applied. In the absence of these, SOPs from published
handbooks, or from the IPCC GPG LULUCF 2003, may be applied
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
Models used may be based on total tree height (top height) or height
of stem (clear bole height). The relevant height should be
measured/estimated and used
Comments:
Data / Parameter:
Data unit:
Used in equations:
Description:
T
Year
Source of data:
Measurement procedures:
Comments:
Recorded time
N/A
If the two successive estimations of carbon stock in trees are carried
out at different points of time in year t2 and t1, (e.g. in the month of
April in year t1 and in the month of September in year t2), then a
fractional value shall be assigned to T
Time period elapsed between two successive estimations of carbon
stock in trees and shrubs
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 45
July 2012
2
Tool CNT-Woody: Estimation of carbon stocks and changes in carbon stocks
of non-tree woody biomass
3
Source
4
5
6
7
Tool is based off of the CDM A/R Methodological Tool “Estimation of carbon stocks and change in
carbon stocks of trees and shrubs in A/R CDM project activities” (Version 02.1.0) and the VCS Approved
Methodology “VMD0001 Estimation of carbon stocks in the above- and belowground biomass in live tree
and non-tree pools (CP-AB), v1.0”.14
8
Assumptions
9
This tool makes the following assumptions:
1
10
(c)
11
12
13
Linearity of biomass growth for non-tree woody vegetation
Growth of biomass in non-tree woody vegetation may be assumed to proceed on
average at an approximately constant rate between two points in time at which biomass
is estimated.
14
(d)
15
16
17
Appropriateness of root-shoot ratios
Root-shoot ratios appropriate for estimation of below-ground biomass from aboveground biomass under forest/continuous-cover conditions are appropriate for all nontree woody vegetation within the project boundary.
18
Parameters
19
This tool provides procedures to determine the following parameters:
20
21
Table 4: Parameters determined
Parameter
SI Unit
Description
C NT W OODY,t
t CO2-e
Carbon stock in non-tree woody vegetation biomass within the
project boundary at a given point of time in year t
C NT W OODY,t
t CO2-e
Change in carbon stock in non-tree woody vegetation biomass
within the project boundary in year t
14
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 46
July 2012
22
While applying this tool in a methodology, the following notation should be used:
23
In the baseline scenario:
24
C NT W OODY BSL,t for C NT W OODY,t
25
C NT W OODY BSL,t for C NT W OODY,t
26
In the project scenario:
27
C NT W OODY _ PROJ ,t for C NT W OODY,t
28
C NT W OODY _ PROJ ,t for C NT W OODY,t
29
30
31
Methods
Carbon stock in non-tree woody biomass is estimated on the basis of the biomass in one or more strata.
32
Non-tree woody aboveground biomass pool includes trees smaller than the minimum tree size
measured in the tree biomass pool, all shrubs, and all other non-herbaceous live vegetation.
33
34
35
Step 1 Estimation of carbon stock in non-tree woody biomass using one of following methods
The carbon stock in non-tree woody vegetation is estimated by applying one of the following methods.
The default method can only be used in baseline calculations although the other two methods may be
36
used. The other two methods require field measurements.
37
Method 1 Default Method
38
1.
Non-tree woody vegetation biomass per hectare (
B NT W OODY,i ,t
) is estimated as follows:
39
40
41
(a) For those areas where the non-tree woody vegetation crown cover is less than 5%, the nontree woody vegetation biomass per hectare is considered negligible and hence accounted as
zero;
42
43
(b) For those areas where the non-tree woody vegetation crown cover is 5% or more, non-tree
woody vegetation biomass per hectare is estimated as follows:
44
45
B NT W OODY,i ,t = BDR SF * BFOREST * CC NT W OODY,i ,t
(47)
where:
B NT W OODY,i ,t
Non-tree woody vegetation biomass per hectare in non-tree woody
vegetation density stratum i, at a given point of time in year t; t d.m. ha1
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 47
July 2012
BDR SF
Ratio of non-tree woody vegetation biomass per hectare in land having
a non-tree woody vegetation crown cover of 1.0 and default aboveground biomass content per hectare in forest in the region/country
where the project is located; dimensionless
BFOREST
Default above-ground biomass content in forest in the region/country
where the project is located; t d.m. ha-1
CC NT W OODY,i ,t
Crown cover of non-tree woody vegetation in non-tree woody
vegetation biomass stratum i at a given point of time in year t
expressed as a fraction; dimensionless
46
47
48
49
50
2. Carbon stock in non-tree woody vegetation biomass is estimated for each non-tree woody
vegetation biomass stratum delineated on the basis of non-tree woody vegetation crown cover.
Once the area within the project boundary has been stratified on the basis of non-tree woody
vegetation crown cover, carbon stock in non-tree woody vegetation biomass within the project
boundary at a given point of time in year t is calculated as:
51
C NT W OODY,default,i ,t 
52
where:
44
 CFS  1  RS   ANT W OODY,i ,t  B NT W OODY,i ,t
12
(48)
C NT W OODY,default,i ,t
Carbon stock in non-tree woody vegetation biomass using the default method
within the project boundary at a given point of time in stratum i, in year t; t CO2-e
CFS
Carbon fraction of non-tree woody vegetation biomass; dimensionless
IPCC default value of 0.50 is used.
RS
Root-shoot ratio for non-tree woody vegetation; dimensionless
ANT W OODY,i ,t
Area of non-tree woody vegetation biomass stratum i at a given point of time in
year t; ha
B NT W OODY,i ,t
Non-tree woody vegetation biomass per hectare in non-tree woody vegetation
biomass stratum i at a given point of time in year t; t d.m. ha-1
I
1, 2, 3, … non-tree woody vegetation biomass strata delineated on the basis of nontree woody vegetation crown cover
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 48
July 2012
t
1, 2, 3, … years counted from the start of the project activity
53
54
Method 2 Sampling Frame Method
55
56
57
In a stratum where non-tree vegetation is spatially variable, large frames should be used (e.g. 12 m radius circle). Where non-tree vegetation is homogeneous, smaller frames can be used (e.g.
30 cm radius).
58
59
60
61
62
63
Generally, the frame is placed at a randomly or systematically selected GPS point or tree plot.
At each location, all vegetation originating from inside the frame is cut at the base and
weighed. One representative subsample of the cut material is weighed to obtain its wet mass.
The collected subsample is taken to a laboratory, oven dried and weighed to determine the dry
mass. The wet to dry ratio of the subsample is then used to estimate the dry mass of the
original sample.
64
65
66
67
The mean carbon stock in belowground biomass per unit area is estimated based on field
measurements of aboveground parameters. Root to shoot ratios are coupled with the
aboveground biomass estimate to calculate belowground from aboveground biomass. An
appropriate root to shoot ratio for non-tree biomass must be chosen.
68
69
To estimate the mean carbon stock per unit area in the aboveground and below non-tree
biomass for each stratum:
70
C AB _ nontree_ sample,i  
71
C BB _ nontree_ sample,i  C AB _ nontree_ sample,i * R
72
Where:
73
74
CAB_nontree_sample,i
Carbon stock in aboveground non-tree vegetation in sampling plot in
strata i from sample method; t C ha-1
75
76
CAB_,nontree_sample,sfp,i
Carbon stock in aboveground non-tree vegetation in sample plot sfp in
stratum i from sampling frame method; kg d.m.
77
78
CBBB_nontree_sample,i
Carbon stock in belowground non-tree vegetation in sampling plot in
strata i from sample method; t C ha-1
79
R
Root to shoot ratio; t root t C -1 shoot t C
80
CFj
Carbon fraction of dominant non-tree vegetation j; t C t d.m.-1
81
Asfpi
Area of non-tree sampling plot s fp in stratum i; ha
82
sfp
1, 2, 3 … SFPi sample plots in stratum i
SFPi
C AB _ nontree_ sample,sfp,i
sfp1
Asfp,i
* CF
(49)
(50)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 49
July 2012
83
i
1, 2, 3 … M strata
84
85
Method 3 Allometric Equation Method:
86
87
88
89
This method may be used for shrubs, bamboo, or other vegetation types where individuals can
be clearly delineated. Sample plots shall be non-permanent and may be placed in association
with tree plots or in another unbiased systematic or random distribution within the project
area.
90
91
92
93
94
1. Select or develop an appropriate allometric equation (if possible species-specific, or if not
from a similar species).
2. Estimate carbon stock in aboveground biomass for each individual l in the sample plot r
located in stratum i using the selected or developed allometric equation:
S
95
Ni ,r
C AB _ nontreeallometric,i , r   f j (vegatationparameters) * CF j
(51)
j 1 l 1
96
97
Where:
98
99
CAB_nontree_allometric,i,r
Carbon stock in aboveground biomass of non-tree sample plot r in
stratum i from allometric equation method; t C
100
CFj
Carbon fraction of biomass for species j; t C t-1 d.m.
101
102
103
fj(vegetation parameters )
104
i
1, 2, 3, …M strata
105
r
1, 2, 3, …R non-tree allometric method sample plots in stratum i
106
j
1, 2, 3 … S species
107
l
1, 2, 3, … Ni,r sequence number of individuals in sample plot r in stratum i
108
t
0, 1, 2, 3 …t* years elapsed since start of the REDD project activity
109
3. Calculate the mean carbon stock in aboveground and belowground biomass for each stratum:
110
111
112
113
The mean carbon stock in belowground biomass per unit area is estimated based on field
measurements of aboveground parameters. Root to shoot ratios are coupled with the
aboveground biomass estimate to calculate belowground from aboveground biomass. An
appropriate root to shoot ratio for non-tree biomass must be chosen.
Aboveground biomass from allometric equation for species j
linking parameters such as stem count, diameter of crown, height,
or others ; t. d.m. individual-1
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 50
July 2012
114
Ri
C AB _ nontree_ allometric,r ,i
r 1
Ari
115
C AB _ nontree_ allometric,i  
116
C BB _ nontree_ allometric,i  C AB _ nontree_ allometric,i * R
(52)
(53)
117
118
Where:
119
120
CAB_nontree_allometric,i
Mean aboveground biomass carbon stock in stratum i from allometric
equation method; t C ha-1
121
122
CAB_nontree_allometric,r,i
Carbon stock in aboveground biomass of non-tree sample plot r of
stratum i from non-tree allometric sample plots, t C
123
Ari
Area of non-tree allometric method sample plot in stratum i; ha
124
125
CBB_nontree_allometric,i
Mean belowground biomass carbon stock in stratum i from allometric
equation method, t C ha-1
126
R
Root to shoot ratio; t root d.m. t-1 shoot d.m.
127
r
1, 2, 3 …R non-tree allometric method sample plots in stratum i
128
i
1, 2, 3 … M strata
129
130
Step 2 Estimate total carbon stocks in non-tree woody vegetation
131
132
133
134
Calculate the carbon stock in aboveground non-tree biomass for the project activity boundary
by multiplying by the area of the stratum and adding the mean carbon stock calculated using
the various methods.
Where:
135
C NT Woodysample,t 
44
*  (C ABnontreesample,i ,t  C BBnontreesample,i ,t ) * Area NT Woodysample,i ,t
12 i
136
137
(54)
C NT W oodyallometric,t 
44
*  (C ABnontreeallometric,i ,t  C BBnontreeallometric,i ,t ) * Area NT allometric sample,i ,t
12 i
138
139
(55)
C NT W oody,t  C NT W oody sample,t  C NT W oody allometric,t  C NT W oody default,t
(56)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 51
July 2012
140
141
CNT-Woody,t
Mean non-tree woody biomass carbon stock, at time t; t CO2e ha-1
142
143
CNT-Woody-sample,t
Mean non-tree woody biomass carbon stock from sample frame method,
at time t; t CO2e ha-1
144
145
CNT_Woody_allometric,t
Mean non-tree woody biomass carbon stock from allometric equation
method, at time t; t CO2e ha-1
146
147
CNT_Woody_default,t
Mean non-tree woody biomass carbon stock from default method, at
time t; CO2e C ha-1
148
149
CAB_nontree-sample,i
Aboveground biomass carbon stock in non-tree vegetation in stratum i at
time t, t C
150
151
CAB_nontree-allometric,i
Aboveground biomass carbon stock in non-tree vegetation in stratum i at
time t, t C
152
153
AreaNT-Woody-sample,i,t
Area of plantings of non-tree woody vegetation sampled using sampling
frame method in stratum i at time t; ha
154
155
AreaNT-Woody-allometric,i,t Area of plantings of non-tree woody vegetation sampled using allometric
method in stratum i at time t; ha
156
157
i
158
Step 3 Estimation of change in carbon stocks in non-tree woody vegetation
159
160
1.
161
dC NT W OODY,(t1 ,t2 ) 
162
where:
1, 2, 3 … M strata
The rate of change of non-tree woody vegetation biomass over a period of time is estimated as
follows:
C NT W OODY,t2  C NT W OODY,t1
T
(57)
dC NT W OODY,(t1 ,t2 )
Rate of change in carbon stock in non-tree woody vegetation biomass within the
project boundary during the period between a point of time in year t1 and a point
of time in year t2; t CO2-e yr-1
C NT W OODY,t 2
Carbon stock in non-tree woody vegetation biomass within the project boundary at
a point of time in year t2; t CO2-e
C NT W OODY,t1
Carbon stock in non-tree woody vegetation biomass within the project boundary at
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 52
July 2012
a point of time in year t1; t CO2-e
Time elapsed between two successive estimations (T=t2 – t1); yr
T
For the first verification, the variable C NT W OODY,t1 in the above equation is assigned the value of
163
2.
164
165
carbon stock in the pre-project non-tree woody vegetation biomass, that is:
C NT W OODY,t1  C NT W OODY _ BSL for the for the first verification, where t1 = 1 and t2 = “year of first
166
verification”.
167
168
3.
Change in carbon stock in non-tree woody vegetation biomass within the project boundary in
year t (t1  t  t2) is calculated as follows:
169
C NT W OODY,t  dC NT W OODY,(t1 ,t2 )  1year for t1  t  t2
170
where
(58)
C NT W OODY,t
Change in carbon stock in non-tree woody vegetation biomass within the project
boundary in year t; t CO2-e
dC NT W OODY,(t1 ,t2 )
Rate of change in carbon stock in non-tree woody vegetation biomass within the
project boundary during the period between a point of time in year t1 and a point
of time in year t2; t CO2-e yr-1
171
Parameter Tables
172
Data and parameters not monitored
Data / Parameter:
BDRSF
Data unit:
Used in equations:
Description
Dimensionless
Source of data:
A default value of 0.10 should be used unless transparent and verifiable
information can be provided to justify a different value
Data / Parameter:
RS
Data unit:
Used in equations:
Description:
Dimensionless
Ratio of biomass per hectare in land having a shrub crown cover of 1.0
and biomass per unit area in a fully stocked forest in the region/country
where the project is located
Root-shoot ratio for shrubs
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 53
July 2012
Source of data:
The source of data, in order of preference, shall be any of the following:
(a) Existing local species-specific data; (b) National species-specific data
(e.g. national forest inventory or national GHG inventory); (c) Speciesspecific data from neighbouring countries with similar conditions;
(d) Globally available species-specific data. If none of the above sources
are available, then a default value of 0.40 may be used [Source: Table
4.4 of 2006 IPCC Guidelines for National Greenhouse Gas Inventories]
Data / parameter:
fj(vegetation parameters )
Data unit:
t. d.m. individual-1
Used in equations:
Description:
Source of data:
Allometric equation for non-tree species l linking parameters such as
stem count, diameter of crown, height, or others to aboveground
biomass of an individual
Whenever available, use allometric equations that are species-specific or
group of species-specific, provided the equations have been derived
using a wide range of diameters and heights, based on datasets that
comprise at least 30 individuals. Project participants may create project
location specific equation where appropriate.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 54
July 2012
Measurement procedures (if
any):
It is necessary to verify the applicability of existing equations used.
Allometric equations can be verified either by: 1. Review of source data
from which equation was derived and confirmation that the source data
is representative of the species and conditions in the project and covers
the range of potential sizes. Or 2. Destructive Sampling · Selecting at
least five individuals covering the range of sizes existing, and felling and
weighing the aboveground biomass to determine the total (wet) mass of
the stem and branch components; · Extracting and immediately
weighing subsamples from each of the wet stem and branch
components, followed by oven drying at 70oC to determine dry biomass;
· Determining the total dry weight of each individual from the wet
weights and the averaged ratios of wet and dry weights of the stem and
branch components. If the biomass of the harvested individual is within
±10% of the mean values predicted by the selected allometric equation,
and is not biased, then mean values from the equation may be used.
Otherwise, the equation must be re-parameterized to conform to the
validation data before using, or another equation selected. To create a
new allometric equation: Follow guidance in: Pearson, T., Walker, S. and
Brown, S. 2005. Sourcebook for Land Use, Land-Use Change and Forestry
Projects. Winrock International and the World Bank Biocarbon Fund.
57pp. Available at: http://www.winrock.org/Ecosystems/files/WinrockBioCarbon_Fund_Sourcebook-compressed.pdf
Any comment:
173
174
175
Data and parameters monitored
Data / Parameter:
Ai
Data unit:
Used in equations:
Description:
Source of data:
Ha
Area of stratum i
Field measurement
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 55
July 2012
Measurement procedures:
Standard operating procedures (SOPs) prescribed under national forest
inventory are applied. In absence of these, SOPs from published
handbooks, or from the IPCC GPG LULUCF 2003, may be applied.
Delineation of strata boundaries should preferably be done in such way
that it can be easily migrated to a Geographical Information System (GIS)
which facilitates integration of data from different sources (including
GPS coordinates and remotely sensed data)
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed under
national forest inventory are applied. In the absence of these, QA/QC
procedures from published handbooks, or from the IPCC GPG LULUCF
2003, may be applied
Data / Parameter:
Aspf,i,t
Data unit:
Used in equations:
Description:
Source of data:
Measurement procedures:
Ha
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed under
national forest inventory are applied. In absence of these, QA/QC
procedures from published handbooks, or from the IPCC GPG LULUCF
2003, may be applied
Comments:
Sample plot location is registered with a GPS and marked on the project
map
Data / parameter:
Asf
Data unit:
m-2
Used in equations:
Description:
Source of data:
Measurement procedures (if
any):
Area of non-tree sampling plot s fp in stratum
Field measurement
Standard operating procedures (SOPs) prescribed under national forest
inventory are applied. In absence of these, SOPs from published
handbooks, or from the IPCC GPG LULUCF 2003, may be applied
Area of one sampling frame
Recording and archiving size of sampling frame plot
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 56
July 2012
Monitoring frequency:
QA/QC procedures:
Any comment:
Data / parameter:
Data unit:
Used in equations:
Description:
Source of data:
Measurement procedures (if
any):
Monitoring frequency:
QA/QC procedures:
Any comment:
Monitoring must occur at least every ten years for baseline renewal.
Where carbon stock enhancement is included monitoring shall occur at
least every five years
Shall be known ex-ante.
Ar
Hectares
Total area of all non-tree allometric method sample plots in stratum i
Recording and archiving size of non-tree allometric method sample plot
Monitoring must occur at least every ten years for baseline renewal.
Where carbon stock enhancement is included monitoring shall occur at
least every five years
Where carbon stock estimation occurs only for determination of the
baseline this parameter shall be known ex-ante. Where part of project
monitoring, ex-ante the number and area of sample plots shall be
estimated based on projected sample effort relative to projections of
growth and emissions.
Data / Parameter:
ANT-WOODY,i,t
Data unit:
Used in equations:
Description:
Source of data:
Measurement
Ha
procedures:
Monitoring frequency:
QA/QC procedures:
Area of shrub biomass stratum i at a given point of time in year t
Field measurement
Standard operating procedures (SOPs) prescribed under national forest
inventory are applied. In absence of these, SOPs from published
handbooks, or from the IPCC GPG LULUCF 2003, may be applied
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed under
national forest inventory are applied. In absence of these, QA/QC
procedures from published handbooks, or from the IPCC GPG LULUCF
2003, may be applied
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 57
July 2012
Data / Parameter:
CCSHRUB,I,t
Data unit:
Used in equations:
Description:
Dimensionless
Source of data:
Measurement procedures:
Field measurement
Considering that the biomass in shrubs is smaller than the biomass in
trees, a simplified method of measurement may be used for estimating
shrub crown cover. Ocular estimation of crown cover may be carried out
or any other method such as the line transect method or the relascope
method may be applied
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed under
national forest inventory are applied. In absence of these, QA/QC
procedures from published handbooks, or from the IPCC GPG LULUCF
2003, may be applied
Comments:
(a) When land is subjected to periodic slash-and-burn practices in
baseline, an average shrub crown cover equal to default value of 0.5 is
used in Equation (11) unless transparent and verifiable information can
be provided to justify a different value; (b) Ex ante estimation of shrub
crown cover at a time other than the start of the project is carried out
with the following considerations in view: (i) Shrub crown cover is
assumed to remain at the pre-project level unless transparent and
verifiable information can be provided to justify a different rate of
change;. (ii) When land is abandoned, shrubs may encroach such land
and shrub crown cover may reach its maximum default value of 0.6 over
a period of 20 years from the year in which the land is abandoned. If the
year in which the land is abandoned is not known, then an average
crown cover of 0.30 is assumed at the start of the project
Data / Parameter:
Data unit:
Used in equations:
Description:
T
Year
Source of data:
Measurement procedures
Recorded time
N/A
Crown cover of shrubs in shrub biomass stratum i at a given point of time
in year t
Time period elapsed between two successive estimations of carbon stock
in trees and shrubs
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 58
July 2012
Comments:
If the two successive estimations of carbon stock in trees are carried out
at different points of time in year t2 and t1, (e.g. in the month of April in
year t1 and in the month of September in year t2), then a fractional value
shall be assigned to T
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 59
July 2012
1
2
3
Tool CHE: Estimation of carbon stocks and changes in carbon stocks of
herbaceous biomass
4
Assumptions
5
6
7
1.
This tool assumes that the non-woody biomass pool includes all live herbaceous vegetation.
Vegetation measured in the tree or non-tree woody biomass pool must be excluded from all
measurements of herbaceous biomass.
8
9
10
2.
Change of biomass in non-woody biomass may be assumed to proceed, on average, at an
approximately constant rate between two points of time at which the biomass is estimated.
11
Parameters
12
This tool provides procedures to determine the following parameters:
Parameter
SI Unit
Description
C HE ,t
t CO2-e
Carbon stock in herbaceous vegetation within the project boundary
at a given point of time in year t; t CO2-e
C HE ,t
t C yr-1
Rate of change in carbon stock in herbaceous, for the period
between year t1 and year t2; t CO2-e
13
While applying this tool in a methodology, the following notation should be used:
14
In the project scenario:
15
C HE , PROJ ,t for C HE ,t
16
C HE _ PROJ ,t for C HE ,t
17
18
19
20
Methods
21
For ex post estimates, the carbon stock estimates must be based on yearly field measurements.
For ex ante estimates, the carbon stocks and the changes in carbon stocks of herbaceous vegetation
may be conservatively neglected.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 60
July 2012
22
23
24
25
The expected long-term average carbon stocks in the herbaceous biomass vegetation under the project
scenario must be conservatively estimated. The estimated change in carbon stocks in non-woody
vegetation cannot exceed the difference between the carbon stocks at the start of the project and the
long term average.
26
27
Step 1 Create estimated long-term average carbon stock in non-woody biomass vegetation
under project scenario
28
29
30
31
32
1.
A conservative estimate of the long-term average carbon stocks in non-woody biomass must be
created for each stratum. Such conservative estimates must be based on published literature of
herbaceous biomass stocks over at least a ten year time frame under similar management
regime as the project scenario. Alternatively, it is allowable to demonstrate an indisputably
conservative estimate of long-term average carbon stocks.
33
34
2.
This can be calculated based on published estimates of aboveground herbaceous biomass stocks
and a root to shoot ratio:
35
C HE  AB,i ,long  term  C HE  AB,i , LT * Ai
(59)
36
C HE  BB,i ,long  term  C HE  AB,i ,long  term * R
(60)
37
C HE ,i ,longerm  C HE  AB,i ,longterm  C HE  BB,i ,longterm
(61)
38
39
Where:
C HE , i ,longeterm
Conservatively estimated long-term carbon stock in herbaceous vegetation in
stratum i; t CO2-e
C HE  AB,,i ,longterm
Conservatively estimated long-term carbon stock in aboveground herbaceous
vegetation in stratum i; t CO2-e
C HE  BB, p ,i ,longterm
Conservatively estimated long-term carbon stock in belowground herbaceous
vegetation in stratum i; t CO2-e
C HE  AB,i , LT
Conservative estimate of long-term carbon stock in herbaceous vegetation in
stratum i based on literature; t CO2-e ha-1
R
Root to shoot ratio; t root t C -1 shoot t CO2-e
Ai
Area of stratum i; ha
I
1, 2, 3, … biomass estimation strata within the project boundary
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 61
July 2012
40
41
Step 2 Estimation of carbon stock in non-woody biomass vegetation
42
43
44
45
46
47
48
49
50
51
3.
For ex post estimates of actual herbaceous biomass in the project scenario, field sampling must
take place every year. The herbaceous carbon stock in a given year is assumed to be the average
of the biomass at the highest and lowest biomass points. Sampling must take place to coincide
with the periods of lowest and highest carbon stocks in herbaceous vegetation in order to
account for natural and anthropogenic influences on the herbaceous vegetation and to eliminate
seasonal effects. It is conservative to assume the lowest carbon stocks equal zero, in which case
field sampling is only required at the period of highest stocks. Alternatively the Project
Proponents may plan field sampling to coincide with the period of lowest carbon stocks in
herbaceous vegetation and conservatively assume the lowest carbon stock for herbaceous
vegetation.
52
53
54
55
56
57
58
4.
For estimating carbon stock in herbaceous vegetation, four herbaceous vegetation samples are
collected from each non-permanent sample plot, using a sampling frame which is placed in four
randomly selected positions within the sample plot. The four samples are well mixed into one
composite sample and its wet weight is taken. A sub-sample taken from the composite sample is
weighed, oven dried, and weighed again to determine its dry weight. The dry-to-wet weight
ratio of the sub-sample is calculated and used for estimating the dry weight of the composite
herbaceous vegetation sample.
59
60
5.
Carbon stock in aboveground herbaceous vegetation biomass in plot p at the highest and lowest
biomass point in year t is then calculated as:
61
C HE  AB, p ,i ,tlow 
A p ,i
44
 CFHE 10 *
 B HE _ W ET, high, p ,i ,t  DWR HE , p ,i
12
4 * a p ,i
(62)
62
C HE  AB, p ,i ,thigh 
A p ,i
44
 CFHE  10 *
 B HE _ W ET,low, p ,i ,t  DWR HE , p ,i
12
4 * a p ,i
(63)
63
where:
C HE  AB, p ,i ,t ,low
Carbon stock in aboveground herbaceous vegetation in plot p in stratum i in year t
at lowest biomass point in the year; t CO2-e (Parameter can be conservatively
assumed to equal zero)
C HE  AB, p ,i ,t , high
Carbon stock in aboveground herbaceous vegetation in plot p in stratum i in year t
at highest biomass point in the year; t CO2-e
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 62
July 2012
CFHE
Carbon fraction of dry biomass in herbaceous vegetation; dimensionless (IPCC
default value15 of 0.50 is used)
B HE _ W ET, high, p ,i
Wet weight of the composite herbaceous vegetation sample collected from plot p
of stratum i at highest biomass point in year t; kg
B HE _ W ET,low, p ,i
Wet weight of the composite herbaceous vegetation sample collected from plot p
of stratum i at lowest biomass point in year t; kg
DWR HE , p ,i
Dry-to-wet weight ratio of the herbaceous vegetation sub-sample collected from
plot p in stratum i; dimensionless
Note: It is acceptable to determine this ratio for three randomly selected sample
plots in a stratum and then apply the average ratio to all plots in that stratum.
64
65
66
67
68
A p ,i
Total area of sample plots in stratum i; ha
a p ,i
Area of sampling frame for plot p in stratum i; m2
I
1, 2, 3, … biomass estimation strata within the project boundary
P
1, 2, 3, … sample plots in stratum i
t
1, 2, 3, … years elapsed since the start of the project activity
6.
Carbon stock in herbaceous vegetation in stratum i in year t is then calculated as the carbon
stock averaged between the lowest and highest biomass points :
C HE , i ,t , high 
C HE , i ,t ,low 
C HE  AB, i ,t 
Ai
A p ,i
C
Ai
A p ,i
C
HE  AB , p ,i ,t , high
HE  AB , p ,i ,t ,low
(65)
p
C HE  AB, p ,i ,t ,low  C HE  AB, p ,i ,t ,high
2
69
15
(64)
p
IPCC GPG for LULUCF, 2003, page 3.35, section 3.2.1.2.1.1 Choice of Method
(66)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 63
July 2012
70
C HE  BB,i ,t  C HE  AB,i ,t * Ri
(67)
71
C HE ,i ,t  C HE  AB,i ,t  C HE  BB,i ,t
(68)
72
73
74
75
76
where
C HE , i ,t
Carbon stock in herbaceous vegetation in stratum i in year t; t CO2-e
C HE  AB,,i ,t
Aboveground biomass carbon stock in herbaceous vegetation in stratum i in
year t; t CO2-e
C HE  BB, p ,i ,t
Belowground biomass carbon stock in herbaceous vegetation in stratum i in
year t; t CO2-e
C HE  AB, p ,i ,t ,low
Carbon stock in aboveground herbaceous vegetation in plot p in stratum i in
year t at lowest biomass point in the year; t CO2-e (Parameter can be
conservatively assumed to equal zero)
C HE  AB, p ,i ,t , high
Carbon stock in aboveground herbaceous vegetation in plot p in stratum i in
year t at highest biomass point in the year; t CO2-e
Ai
Area of stratum i; ha
Ap , i
Area of sample plots in stratum i; ha
Ri
Root to shoot ratio for stratum i; t root t C -1 shoot t CO2-e
P
1, 2, 3, … sample plots in stratum i
I
1, 2, 3, … biomass estimation strata within the project boundary
t
1, 2, 3, … years elapsed since the start of the project activity
7.
If the estimated actual carbon stocks in herbaceous vegetation biomass in stratum i in year t are
greater than the long term average, then it shall be assumed:
C HE ,i ,t  C HE ,i ,longerm
77
78
where
(69)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 64
July 2012
C HE , i ,t
Carbon stock in herbaceous vegetation in stratum i in year t; t CO2-e
C HE , i ,longeterm
Conservatively estimated long-term carbon stock in herbaceous vegetation in
stratum i; t CO2-e
79
80
81
82
8.
Finally, the carbon stock in herbaceous vegetation biomass within the project boundary in year t
is calculated by summing up C HE , i ,t over all the strata, that is:
C HE ,t   C HE ,i ,t
(69)
i
83
where:
C HE ,t
Carbon stock in herbaceous vegetation within the project boundary in year t; t CO2e
C HE , i ,t
Carbon stock in herbaceous vegetation in stratum i in year t; t CO2-e
I
1, 2, 3, … biomass estimation strata within the project boundary
t
1, 2, 3, … years elapsed since the start of the project activity
84
Step 3 Estimation of change in carbon stocks in non-woody vegetation
85
86
87
1.
The rate of change of herbaceous vegetation biomass over a period of time is calculated
assuming a linear change. Therefore, the rate of change in carbon stock in herbaceous
vegetation over a period of time is calculated as:
88
dC HE ,i ,( t1 ,t 2 ) 
89
where:
C HE ,i ,t 2  C HE ,i ,t1
T
(70)
dC HE ,i ,(t1,t 2 )
Rate of change in the herbaceous vegetation carbon pool in stratum i (averaged over
a monitoring period); t CO2-e yr–1
C HE,i ,t
Biomass of herbaceous vegetation in stratum i at time t; t CO2-e
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 65
July 2012
T
Number of years between monitoring time t2 and t1 (T = t2 – t1); yr
t
1, 2, 3, … t* years elapsed since the start of the project activity
Change in carbon stock in herbaceous vegetation in year t (t1  t  t2) is then calculated as:
90
2.
91
C HE ,i ,t  dC HE ,i ,(t1 ,t 2 )  1year
(71)
92
C HE,t   C HE,i ,t
(72)
i
93
94
where:
C HE ,t
Change in carbon stock in herbaceous vegetation in project boundary, in year t; t
CO2-e
C HE ,i ,t
Change in carbon stock in herbaceous vegetation in stratum i, in year t; t CO2-e
dC HE ,i ,(t1 ,t2 )
Rate of change in carbon stock in herbaceous vegetation in stratum i, for the period
between year t1 and year t2; t CO2-e yr-1
I
1, 2, 3, … biomass estimation strata within the project boundary
95
Parameter Tables
96
Data and parameters not monitored
Data / Parameter:
CFHE
Data unit:
Used in equations:
Description:
t C t-1 d.m.
Carbon fraction of dry biomass in herbaceous vegetation;
dimensionless
Source of data:
IPCC default value of 0.5 t C t-1 d.m. may be used
Data / Parameter:
Ri
Data unit:
Used in equations:
Description:
Dimensionless
Root-shoot ratio for stratum i
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 66
July 2012
Source of data:
The source of data, in order of preference, shall be any of the
following: (a) Existing local species-specific data; (b) National
species-specific data (e.g. national forest inventory or national GHG
inventory); (c) Species-specific data from neighbouring countries
with similar conditions; (d) Globally available species-specific data. If
none of the above sources are available, then the value of Rj may be
calculated as R = exp[-1.085+0.9256*ln(A)]/A, where A is aboveground biomass (t d.m. ha-1) [Source: Table 4.A.4 of IPCC GPGLULUCF 2003]
97
98
Data and parameters monitored
Data / Parameter:
Ai
Data unit:
Used in equations:
Description:
Source of data:
Measurement procedures
Ha
Monitoring frequency:
QA/QC procedures:
Every 5 years since start of project activitiy
Quality control/quality assurance (QA/QC) procedures prescribed under
national forest inventory are applied. In the absence of these, QA/QC
procedures from published handbooks, or from the IPCC GPG LULUCF
2003, may be applied
Data / Parameter:
ap,i
Data unit:
m2
Used in equations:
Description:
Area of herbaceous biomass sampling frame used in plot p in stratum i
Source of data:
Measurement procedures:
Monitoring frequency:
Area of stratum i
Field measurement
Standard operating procedures (SOPs) prescribed under national forest
inventory are applied. In absence of these, SOPs from published
handbooks, or from the IPCC GPG LULUCF 2003, may be applied.
Measurement
Standard operating procedures (SOPs) prescribed under national forest
inventory are applied. In absence of these, SOPs from published
handbooks, or from the IPCC GPG LULUCF 2003, may be applied
Bi-annually every year since start of project activitiy
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 67
July 2012
QA/QC procedures:
Quality control/quality assurance (QA/QC) procedures prescribed under
national forest inventory are applied. In absence of these, QA/QC
procedures from published handbooks, or from the IPCC GPG LULUCF
2003, may be applied
Comments:
Often a herbaceous biomass sampling frame of 0.50 m2 is used
Data / Parameter:
BHE_WET,high,p,i
Kg
Data unit:
Used in equations:
Description:
Source of data:
Measurement procedures:
Wet weight of the composite herbaceous vegetation sample collected
from plot p of stratum i at highest biomass point of the year t
Field measurements in sample plots.
Documentation must be presented to demonstrate sampling occurring
during time of high biomass.
Standard operating procedures (SOPs) prescribed under national forest
inventory are applied. In absence of these, SOPs from published
handbooks, or from the IPCC GPG LULUCF 2003, may be applied
As described above, four herbaceous vegetation samples are collected
from each non-permanent sample plot, using a sampling frame which is
placed in four randomly selected positions within the sample plot. The
four samples are well mixed into one composite sample and its wet
weight is taken. A sub-sample taken from the composite sample is
weighed, oven dried, and weighed again to determine its dry weight.
The dry-to-wet weight ratio of the sub-sample is calculated and used for
estimating the dry weight of the composite herbaceous vegetation
sample.
Monitoring frequency:
QA/QC procedures:
Annually every year since start of project activitiy
Quality control/quality assurance (QA/QC) procedures prescribed under
national forest inventory are applied. In the absence of these, QA/QC
procedures from published handbooks, or from the IPCC GPG LULUCF
2003, may be applied
Data / Parameter:
Data unit:
Used in equations:
Description:
BHE_WET,low,p,i
Kg
Source of data:
Wet weight of the composite herbaceous vegetation sample collected
from plot p of stratum i at lowest biomass point of the year t
Field measurements in sample plots.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 68
July 2012
Measurement procedures:
Documentation must be presented to demonstrate sampling occurring
during time of lowest biomass.
Standard operating procedures (SOPs) prescribed under national forest
inventory are applied. In absence of these, SOPs from published
handbooks, or from the IPCC GPG LULUCF 2003, may be applied
As described above, four herbaceous vegetation samples are collected
from each non-permanent sample plot, using a sampling frame which is
placed in four randomly selected positions within the sample plot. The
four samples are well mixed into one composite sample and its wet
weight is taken. A sub-sample taken from the composite sample is
weighed, oven dried, and weighed again to determine its dry weight.
The dry-to-wet weight ratio of the sub-sample is calculated and used for
estimating the dry weight of the composite herbaceous vegetation
sample.
Monitoring frequency:
QA/QC procedures:
Annually every year since start of project activitiy
Quality control/quality assurance (QA/QC) procedures prescribed under
national forest inventory are applied. In the absence of these, QA/QC
procedures from published handbooks, or from the IPCC GPG LULUCF
2003, may be applied
Data / Parameter:
Data unit:
Used in equations:
Description:
T
Year
Source of data:
Measurement procedures:
Comments:
Recorded time
N/A
If the two successive estimations of carbon stock are carried out at
different points of time in year t2 and t1, (e.g. in the month of April in
year t1 and in the month of September in year t2), then a fractional value
shall be assigned to T
Data / Parameter:
DWRHE,p,i
Dimensionless
Data unit:
Used in equations:
Description:
Source of data:
Time period elapsed between two successive estimations of carbon
stock
Dry-to-wet weight ratio of the herbaceous biomass (dry weight/wet
weight)
Laboratory measurement of field samples
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 69
July 2012
Measurement procedures:
herbaceous biomass samples shall be collected and well mixed into one
composite sample at the same time of year in order to account for
natural and anthropogenic influences on the herbaceous biomass
accumulation and to eliminate seasonal effects. A subsample from the
composite sample of herbaceous biomass is taken, oven dried and
weighed to determine the dry weight.
Monitoring frequency:
QA/QC procedures:
Bi-annually every year since start of project activitiy
Data / Parameter:
C HE  AB,i , LT
Data unit:
Used in equations:
Description:
t CO2-e ha-1
Source of data:
Published literature. Must be based on average annual aboveground
carbon stocks of herbaceous biomass over at least ten years of data.
The estimatese must be based on field measurements at both high and
low biomass and consider the average
Conservative estimate of long-term carbon stock in aboveground
herbaceous vegetation in stratum i based on literature;
May be updated over time as new data sources become available.
Documentation must be presented to demonstrate that land use
management of published data is similar to project scenario.
Alternatively, an indisputably conservative estimate may be used.
Measurement procedures:
Monitoring frequency:
QA/QC procedures:
Prior to each verficiation event.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 70
July 2012
1
2
Tool CDW: Estimation of carbon stocks and change in carbon stock in
dead wood
3
4
5
Source
6
Assumptions
7
This tool makes the following assumption:
This tool is based on the CDM A/R Tool “Estimation of carbon stocks and change in carbon stocks in
dead wood and litter in project activities” (Version 01.1.0)16.
8
(a) Linearity of change of biomass in deadwood over a period of time:
9
10
Change of biomass in deadwood may be assumed to proceed, on average, at an
approximately constant rate between two points of time at which the biomass is estimated.
11
(b) Appropriateness of root-shoot ratios:
12
13
Root-shoot ratios appropriate for estimation of below-ground biomass from above-ground
biomass of living trees are also appropriate for dead trees.
14
15
Parameters
16
This tool provides procedures to determine the following parameters:
Parameter
SI Unit
Description
C DW , t
t CO2-e
Carbon stock in dead wood within the project boundary at a given
point of time in year t
C DW , t
t CO2-e
Change in carbon stock in dead wood within the project boundary
in year t
17
While applying this tool in a methodology, the following notation should be used:
18
In the project scenario:
19
C DW _ PROJ , t for C DW , t
16
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 71
July 2012
20
CDW _ PROJ ,t for C DW , t
21
Methods
22
Step 1 Estimation of carbon stock in dead wood
23
24
25
26
27
1.
Carbon stock in dead wood is estimated on the basis of the same strata, and the same sample
plots, which are used for the purpose of estimation of living tree biomass. However, Project
Proponents applying this tool may use a different stratification for the purpose of estimation of
carbon stock in dead wood if transparent and verifiable information can be given for justification
of such a choice.
28
29
2.
Two methods are offered for estimation of carbon stock in dead wood: a measurement-based
method and a conservative default-based approach
30
Method 1: Measurement approach to estimation of carbon stock in dead wood (CDW)
31
32
33
For the purpose of this tool a biometric parameter (such as bole shape/form factor, biomass expansion
factor, root-shoot ratio, basic wood density, carbon fraction, etc) applicable to a species may also be
applied to a group of species having similar biometric characteristics.
34
35
For the purpose of this tool an allometric equation or volume table applicable to a species may also be
applied to a group of species having similar allometric characteristics.
36
37
M1.1. Biomass of dead wood of species j in sample plot p in stratum i at a given point of time in year t is
calculated separately for the following three types of dead wood:
38
39
a. Standing dead wood trees: Dead trees which have lost only leaves and twigs
and some branches.
40
b. Standing dead wood stumps: Dead trees which have lost most of branches
41
c. Lying dead wood.
42
M1.1.a. Standing dead wood
43
M1.1.a.1 Measure dead tree biomass
44
45
46
For all dead trees measurement of tree dimensions (i.e. diameter and/or height) are carried out in
sample plots laid down in each stratum. In exceptional situations, measurements may be carried out on
all such dead trees in the stratum where trees are few and scattered out.
47
48
Tree dimensions (i.e. diameter and/or height as measured) are converted to dead wood biomass in
standing dead trees by applying one of the following two methods:
49
a. The biomass expansion factor (BEF) method; or
50
b. The allometric method.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 72
July 2012
51
Estimation of standing dead tree biomass using BEF method
52
53
54
55
56
Under this method volume tables (or volume functions/curves) are used to convert tree dimensions to
stem volume of trees. Stem volume of trees is converted to above-ground tree biomass using basic
wood density and biomass expansion factors and the above-ground tree biomass is expanded to total
tree biomass using root-shoot ratios. Thus, dead wood biomass in standing dead trees of species j in
sample plot p is calculated as:
57
BDW S _ TREE , j , p ,i ,t  D j  BEF2, j  (1  R j )  VTREE , j ( DBH k , H k )   k
K
(73)
k 1
58
where:
BDW S _ TREE , j , p ,i ,t
VTREE , j ( DBH k , H k )
DBH k
Hk
k
Dj
Rj
Biomass expansion factor for conversion of stem biomass to above-ground
tree biomass, for species j; dimensionless
Root-shoot ratio for tree species j; dimensionless
J
K
P
I
t
1, 2, 3, … tree species in plot p
1, 2, 3, … dead trees of species j in plot p in stratum i
1, 2, 3, … sample plots in stratum i
1, 2, 3, … biomass estimation strata within the project boundary
1, 2, 3, … years elapsed since the start of the project activity
BEF2 , j
59
60
Biomass of dead wood in dead trees of species j in sample plot p of
stratum i at a point of time in year t; t d.m.
Stem volume of the kth dead tree of species j in plot p of stratum i as
returned by the volume function for species j using the tree dimension(s)
as entry data; m3
Diameter of the kth dead tree of species j in plot p of stratum i at a point of
time in year t; metre or any other unit of length used by the volume
function
Height of the kth dead tree of species j in plot p of stratum i at a point of
time in year t; metre or any other unit of length used by the volume
function
Biomass reduction factor for the kth dead tree, depending upon its category
according to paragraph 11(a) or 11(b); dimensionless
Basic wood density of species j; t d.m. m-3
The volume table (or volume function) applicable to a species or a group of species shall be selected
from the following sources (the most preferred source being listed first):
61
(e) Existing local data;
62
(f) National data (e.g. from national forest inventory or national GHG inventory);
63
(g) Data from neighbouring countries with similar conditions;
64
(h) Globally available data.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 73
July 2012
65
Estimation of standing dead tree biomass using allometric method
66
67
68
Under this method allometric equations are used to convert tree dimensions to above-ground biomass
of trees and the above-ground tree biomass is expanded to total tree biomass using root-shoot ratios.
Thus, dead wood biomass in standing dead trees of species j in sample plot p is calculated as:
69
BDW S _ TREE , j , p ,i ,t  (1  R j )   f j ( DBH k , H k )   k
K
(74)
k 1
70
where:
Rj
Biomass of dead wood in standing dead trees of species j in sample plot p
of stratum i at a point of time in year t; t d.m.
Above-ground biomass of the kth dead tree of species j in sample plot p of
stratum i returned by the allometric function for species j using the tree
dimension(s) as entry data; t d.m.
Biomass reduction factor for the kth dead tree
For dead trees which have lost only leaves and twigs ,  k = 0.97517. For
dead trees which have lost leaves, twigs and small branches (diameter < 10
cm).  k = 0.8018.
Root-shoot ratio for tree species j; dimensionless
J
K
P
I
t
1, 2, 3, … tree species in plot p
1, 2, 3, … dead trees of species j in plot p in stratum i
1, 2, 3, … sample plots in stratum i
1, 2, 3, … biomass estimation strata within the project boundary
1, 2, 3, … years elapsed since the start of the project activity
BDW S _ TREE , j , p ,i ,t
f j ( DBH k , H k )
k
71
72
The allometric equation applicable to a species shall be selected in the same manner which applies to
selection of volume tables explained in paragraph 15 above.
73
M1.1.a.2 Estimation of carbon stock in standing dead wood in dead trees
74
75
In both the BEF method and the allometric method, the carbon stock in dead wood biomass in standing
dead trees of species j in sample plot p of stratum i is calculated as follows:
76
CDW S _ TREE , j , p ,i , t 
77
where:
17
18
44
 CFj  BDW S _ TREE , j , p ,i ,t
12
Adapted from IPCC GPG-LULUCF 2003: p. 4.105, section 4.3.3.5.3 DEAD ORGANIC MATTER
Ibid.
(75)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 74
July 2012
CDW S _ TREE , j , p ,i ,t
CFj
BDW S _ TREE , j , p ,i ,t
J
P
I
t
Carbon stock in dead wood in standing dead trees of species j in sample
plot p in stratum i at a given point of time in year t; t CO2-e
Carbon fraction of tree biomass of species j; dimensionless
Biomass of dead wood in standing dead trees of species j in sample plot p
of stratum i at a point of time in year t; t d.m.
1, 2, 3, … tree species in plot p
1, 2, 3, … sample plots in stratum i
1, 2, 3, … biomass estimation strata within the project boundary
1, 2, 3, … years elapsed since the start of the project activity
78
M1.1.b Estimation of carbon stock in standing dead wood in tree stumps
79
80
1. Each dead tree stump in a sample plot is categorized into a decay class as: (i) Sound; (ii)
Intermediate; or (iii) Rotten, on the basis of a machete test19.
81
82
83
84
85
86
2. A density reduction factor is assigned to each of the decay classes, which is to be multiplied by the
basic wood density of the species of the stump to obtain its estimated wood density. The following
default values20 of the density reduction factors for the three decay classes are used, unless Project
Proponents have more specific data available with them: for the decay class (i) Sound, the density
reduction factor = 1.00; for the decay class (ii) Intermediate, the density reduction factor = 0.80; for
the decay class (iii) Rotten, the density reduction factor = 0.45.
87
88
3. For each dead tree stump of height less than 4 m the mid-height diameter is measured. For each
dead tree stump of height 4 m and above, the diameter at breast height (DBH) is measured.
89
4. For stumps of height more than 4 m, the mid-height diameter of the stump is estimated21 as:
90
DMID _ STUMP
91
where


H STUMP

 0.57  DBH  
 H STUMP  H DBH 
0.80
for H STUMP > 4 m
DMID _ STUMP
Mid-height diameter of the dead tree stump; m
DBH
Diameter at breast height of the dead tree stump; m
H STUMP
Height of the stump; m
H DBH
Height above ground level at which DBH is measured; m
19
(76)
The stump wood is struck with a machete—if the blade bounces off it is sound; if it enters slightly into the wood,
is it intermediate; and if it causes the wood to fall apart, it is rotten. IPCC GPG LULUCF 2003, section 4.3.3.5.3
DEAD ORGANIC MATTER
20
Adapted from Harmon, M. E. and J. Sexton. (1996) Guidelines for Measurements of Woody Detritus in Forest
Ecosystems. US LTER Publication No. 20. US LTER Network Office, University of Washington, Seattle, WA,
USA.
21
Adapted from Ormerod, D W, 1973. A simple bole model. Forestry Chronicle. 49:136-138.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 75
July 2012
92
5. Carbon stock in dead wood in dead tree stumps of species j in plot p is calculated as:
93
CDW S _ STUMP, j , p ,i ,t 
94
where:
2
44

 CFj  D j  (1  R j )   DMID _ STUMP, k  H k   k
12
4 k
(77)
CFj
Carbon stock in dead wood in dead tree stumps of species j in sample
plot p in stratum i at a given point of time in year t; t CO2-e
Carbon fraction of tree biomass of species j; dimensionless
Dj
Basic wood density of species j; t d.m. m-3
Rj
Root-shoot ratio for tree species j; dimensionless
DMID _ STUMP, k
Mid-height diameter of the kth dead tree stump of species j in plot p in
stratum i at a given point of time in year t; m
Height of the kth dead tree stump of species j in plot p in stratum i at a
given point of time in year t; m
Density reduction factor applicable to the kth dead tree stump of species j
in plot p in stratum i at a given point of time in year t; dimensionless
1, 2, 3, … tree species in plot p
1, 2, 3, … dead trees of species j in plot p in stratum i
1, 2, 3, … sample plots in stratum i
1, 2, 3, … biomass estimation strata within the project boundary
1, 2, 3, … years elapsed since the start of the project activity
CDW S _ STUMP, j , p ,i ,t
Hk
k
J
K
P
I
t
95
96
M1.1.c. Estimation of carbon stock in lying dead wood
97
98
99
100
1. Lying dead wood is estimated by using line transect method (Harmon and Sexton, 1996).22 Two
transect lines, of total length of at least 100 m,23 approximately orthogonally bisecting each other at
the centre of the plot are established and the diameter of each piece of lying dead wood (with
diameter ≥10 cm) intersecting a transect line is measured.
101
102
2. Each piece of dead wood is assigned to one of three decay classes and each of the three decay
classes are assigned a density reduction factor as explained in paragraphs 19 and 20 above.
103
104
3. Based on these measurements and categorization into decay classes, carbon stock in lying dead
wood of species j in plot p is calculated as:
22
Harmon, M. E. and J. Sexton. (1996) Guidelines for Measurements of Woody Detritus in Forest Ecosystems. US
LTER Publication No. 20. US LTER Network Office, University of Washington, Seattle, WA, USA.
23
If parcel area does not allow for the required length in two lines, then more than two lines are permissible.
However, where lines are obliged to run in parallel they should be separated by at least 20m.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 76
July 2012
105
C DW L, j , p ,i ,t 
106
where:
44
2 N
 CF j  D j 
  Dn   n
12
8L n 1
CFj
Carbon stock in lying dead wood of species j in sample plot p in stratum i at a
given point of time in year t; t CO2-e
Carbon fraction of tree biomass of species j; dimensionless
Dj
Basic wood density of species j; t d.m. m-3
L
Sum of the lengths of the transect lines approximately orthogonally bisecting
each other at the centre of the plot p; m
Diameter of the nth piece of lying dead wood intersecting a transect line; cm
C DW L, j , p ,i ,t
Dn
n
Density reduction factor applicable to the nth piece of lying dead wood
intersecting a transect line; dimensionless
1, 2, 3, … tree species in plot p
1, 2, 3, … sample plots in stratum i
1, 2, 3, … biomass estimation strata within the project boundary
1, 2, 3, … years elapsed since the start of the project activity
j
p
i
t
107
4. The carbon stock in dead wood in a stratum is then calculated as:
108
CDW , i ,t 
109
(78)
Ai
Ap ,i
 C
DWS _ TREE , j , p , i ,t
p
 CDWS _ STUMP, j , p ,i ,t  CDWL, j , p ,i ,t 
(79)
j
where:
CDW , i ,t
Carbon stock in dead wood in stratum i at a given point of time in year t;
t CO2-e
Ai
Total area of stratum i; ha
Ap , i
Total area of sample plots in stratum i; ha
CDW S _ TREE, j , p ,i ,t
Carbon stock in dead wood in standing dead trees of species j in sample
plot p in stratum i at a given point of time in year t; t CO2-e
CDW S _ STUMP, j , p ,i ,t
Carbon stock in dead wood in dead tree stumps of species j in sample
plot p in stratum i at a given point of time in year t; t CO2-e
CDW L, j , p ,i ,t
Carbon stock in lying dead wood of species j in sample plot p in stratum i
at a given point of time in year t; t CO2-e
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 77
July 2012
j
1, 2, 3, … tree species in plot p
p
1, 2, 3, … sample plots in stratum i
I
1, 2, 3, … biomass estimation strata within the project boundary
t
1, 2, 3, … years elapsed since the start of the project activity
110
111
5. Finally, the carbon stock in dead tree biomass within the project boundary at a given point of time in
year t is calculated by summing up CDW , i , t over all the strata, that is:
112
CDW ,t   CDW ,i ,t
(80)
i
113
where:
CDW ,t
Carbon stock in dead wood within the project boundary at a given point of
time in year t; t CO2-e
CDW , i ,t
Carbon stock in dead wood in stratum i at a given point of time in year t;
t CO2-e
i
1, 2, 3, … biomass estimation strata within the project boundary
t
1, 2, 3, … years elapsed since the start of the project activity
114
115
116
Method 2 Default method for estimation of carbon stock in dead wood (CDW)
117
118
If Project Proponents do not wish to make sampling based measurements for estimation of C stock in
dead wood, they may use the default method described here.
119
120
For all strata where this default method is to be used, the change in carbon stock in dead wood is
estimated as:
121
C DW ,t   C TREE ,i ,t * DF DW 
i
122
where:
(9)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 78
July 2012
CDW ,t
Carbon stock in dead wood within the project boundary at a given point of
time in year t; t CO2-e
CTREE , i ,t
Carbon stock in trees in stratum i at a point of time in year t; t C
DFDW
Default factor for the relationship between carbon stock in dead wood and
carbon stock in trees; %
I
1, 2, 3, … biomass estimation strata within the project boundary
t
1, 2, 3, … years elapsed since the start of the project activity
123
124
Step 2 Estimation of change in carbon stocks in dead wood pool
125
126
127
The rate of change of dead wood biomass over a period of time is calculated assuming a linear change
(see assumptions under Section I). Therefore, the rate of change in carbon stock in dead wood over a
period of time is calculated as:
128
dCDW , (t1 ,t 2 ) =
129
where:
CDW ,t 2  CDW ,t1
(10)
T
dCDW , (t1 ,t 2 )
Rate of change in carbon stock in dead wood within the project boundary during the
period between a point of time in year t1 and a point of time in year t2; t CO2-e yr-1
C DW ,t 2
Carbon stock in dead wood within the project boundary at a point of time in year t2; t
CO2-e
CDW ,t1
Carbon stock in dead wood within the project boundary at a point of time in year t1; t
CO2-e
T
Time elapsed between two successive estimations (T=t2 – t1); yr
130
Change in carbon stock in dead wood within the project boundary in year t (t1  t  t2) is given by:
131
CDW ,t  dCDW , (t1 ,t 2 )  1year for t1  t  t2
132
where:
(11)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 79
July 2012
C DW , t
Change in carbon stock in dead wood within the project boundary in year t; t CO2-e
dCDW , (t1 ,t 2 )
Rate of change in carbon stock in dead wood within the project boundary during the
period between a point of time in year t1 and a point of time in year t2; t CO2-e yr-1
133
134
Parameter Tables
135
Data and parameters not monitored
Data / Parameter:
BEF2,j
Data unit:
Used in equations:
Description:
Dimensionless
Source of data:
The source of data shall be selected, in order of preference, from the
following:(a) Local sources of species-specific data; (b) National
sources of species-specific data (e.g. national forest inventory or
national GHG inventory); (c) Species-specific data from neighbouring
countries with similar conditions; (d) Globally available data
applicable to the species; (e) IPCC default values (e.g. Table 3A.1.10
of IPCC GPG-LULUCF 2003) (Although the BEFs in Table 3A.1.10
apply to biomass, the dimensionless factors can be equally applied
for wood volume expansions.)
Comments:
BEFs in IPCC literature and national inventory are usually applicable
to closed canopy forest. If applied to individual trees growing in an
open field it is recommended that the selected BEF be increased by
30%
Data / Parameter:
CFj
Data unit:
t C t-1 d.m.
Used in equations:
Description:
Carbon fraction of tree biomass for species j
Biomass expansion factor for conversion of stem biomass to aboveground biomass for tree species j
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 80
July 2012
Source of data:
The source of data, in order of preference, shall be the following:
(a) National level species-specific data (e.g. from national GHG
inventory); (b) Species-specific data from neighbouring countries
with similar conditions; (c) Globally available species-specific data
(e.g. IPCC GPG-LULUCF 2003); d) The IPCC default value of 0.5 t C t-1
d.m.
Data / Parameter:
Dj
Data unit:
t d.m. m-3
Used in equations:
Description:
Source of data:
1, 4, 5
Basic wood density for species j
The source of data, in order of preference, shall be any of the
following: (a) National and species-specific data (e.g. from national
GHG inventory); (b) Species-specific data from neighbouring
countries with similar conditions; (c) Globally available speciesspecific data (e.g. Table 3A.1.9 IPCC GPG-LULUCF 2003)
Data / Parameter:
DFDW
Data unit:
Used in equations:
Description:
%
Source of data:
Defaults conservatively derived from Delaney et al. 1997[1], Smith et
al.[2], Glenday 2008[3], Keller et al. 2004[4], Eaton and Lawrence
2006[5], Krankina and Harmon 1995[6], and Clark et al 2002[7].
[1] Delaney, M., Brown, S., Lugo, A.E., Torres-Lezama, A. and Bello
Quintero, N. 1997. The distribution of organic carbon in major
components of forests located in five life zones of Venezuela.
Journal of Tropical Ecology 13: 697-708; [2] Smith, James E.; Heath,
Linda S.; Skog, Kenneth E.; Birdsey, Richard A. 2006. Methods for
Calculating Forest Ecosystem and Harvested Carbon with Standard
Estimates for Forest Types of the United States. Forest Service,
Northeastern Research Station, General Technical Report NE-343.
216 p; [3] Glenday, J. 2008. Carbon storage and emissions offset
potential in an African dry forest, the Arabuko-Sokoke Forest, Kenya.
Envion. Monit. Assess 142: 85-95; [4] Keller, M., Palace, M., Asner,
G., Pereira Jr, R. and Silva, JNM. 2004. Coarse woody debris in
undisturbed and logged forests in eastern Brazilian Amazon. Global
Change Biology 10: 784-795 [5] Eaton, J.M. and Lawrence, D. 2006.
Woody debris stocks and fluxes during succession in a dry tropical
Default factor for the relationship between carbon stock in dead
wood and carbon stock in trees
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 81
July 2012
forest. Forest Ecology and Management 232: 46-55; [6] Krankina,
O.N., Harmon, M.E., 1995. Dynamics of the dead wood carbon pool
in northwestern Russian boreal forests. Water Air Soil Pollut.
82,227–238; [7] Clark, D.B., Clark, D.A., Brown, S., Oberbauer, S.F.,
Veldkamp, E., 2002.Stocks and flows of coarse woody debris across a
tropical rain forest nutrient and topography gradient. Forest Ecol.
Manage. 5646, 1–112.
Biome
TROPICAL
TROPICAL
TROPICAL
TROPICAL
TEMPERATE/BOREAL
Data / Parameter:
Rj
Data unit:
Used in equations:
Description:
Source of data:
Dimensionless
Elevation
<2000m
<2000m
<2000m
>2000m
All
Precipitation
DFDW
<1000 mm/yr
2%
1000-1600 mm/yr
1%
>1600 mm/yr
6%
All
7%
All
8%
Root-shoot ratio for species j
The source of data, in order of preference, shall be any of the
following: (a) Existing local species-specific data; (b) National
species-specific data (e.g. national forest inventory or national GHG
inventory); (c) Species-specific data from neighbouring countries
with similar conditions; (d) Globally available species-specific data. If
none of the above sources are available, then the value of Rj may be
calculated as R = exp[-1.085+0.9256*ln(A)]/A, where A is aboveground biomass (t d.m. ha-1) [Source: Table 4.A.4 of IPCC GPGLULUCF 2003]
136
137
Data and parameters monitored
Data / Parameter:
Ai
Data unit:
Used in equations:
Description:
Source of data:
Measurement procedures
Ha
Area of stratum i
Field measurement
Standard operating procedures (SOPs) prescribed under national
forest inventory are applied. In absence of these, SOPs from
published handbooks, or from the IPCC GPG LULUCF 2003, may be
applied.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 82
July 2012
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In the absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
Data / Parameter:
Ap,i
Data unit:
Used in equations:
Description:
Source of data:
Measurement procedures:
Ha
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
Data / Parameter:
Data unit:
Used in equations:
Description:
DBH
cm or any unit of length as specified
Source of data:
Measurement procedures (if
any):
Field measurements in sample plots.
Standard operating procedures (SOPs) prescribed under national
forest inventory are applied. In absence of these, SOPs from
published handbooks, or from the IPCC GPG LULUCF 2003, may be
applied
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In the absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
Total area of sample plots in stratum i
Field measurement
Standard operating procedures (SOPs) prescribed under national
forest inventory are applied. In absence of these, SOPs from
published handbooks, or from the IPCC GPG LULUCF 2003, may be
applied
Diameter at breast height of a tree. For the purpose of Equations (1)
and (2), DBH could be any other diameter or dimensional
measurement (e.g. basal diameter, root-collar diameter, basal area,
etc.) applicable for the model or data source used
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 83
July 2012
Data / Parameter:
Dn
Data unit:
Used in equations:
Description:
cm
Source of data:
Measurement procedures:
Field measurements along transect lines in sample plots
Standard operating procedures (SOPs) prescribed under national
forest inventory are applied. In absence of these, SOPs from
published handbooks, or from the IPCC GPG LULUCF 2003, may be
applied
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In the absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
Data / Parameter:
Data unit:
Used in equations:
Description:
Source of data:
Measurement procedures (if
any):
H
m or any other unit of length as specified
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
Data / Parameter:
Data unit:
Used in equations:
Description:
T
Year
Source of data:
Recorded time
Diameter of the nth piece of lying dead wood intersecting a transect
line
Height of tree
Field measurements in sample plots.
Standard operating procedures (SOPs) prescribed under national
forest inventory are applied. In the absence of these, SOPs from
published handbooks, or from the IPCC GPG LULUCF 2003, may be
applied
Time period elapsed between two successive estimations of carbon
stock
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 84
July 2012
Measurement procedures:
Comments:
N/A
If the two successive estimations of carbon stock are carried out at
different points of time in year t2 and t1, (e.g. in the month of April in
year t1 and in the month of September in year t2), then a fractional
value shall be assigned to T
Data / Parameter:
DMID_STUMP,k
m
Data unit:
Used in equations:
Description:
Mid-height diameter of the kth dead tree stump of species j in plot p
in stratum i at a given point of time in year t
Source of data:
Measurement procedures (if
any):
Field measurements in sample plots.
Standard operating procedures (SOPs) prescribed under national
forest inventory are applied. In the absence of these, SOPs from
published handbooks, or from the IPCC GPG LULUCF 2003, may be
applied
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
Data / Parameter:
Data unit:
Used in equations:
Description:
L
m
Source of data:
Measurement procedures (if
any):
Monitoring frequency:
QA/QC procedures:
Sum of the lengths of the transect lines approximately orthogonally
bisecting each other at the centre of the plot p; m
Field measurements in sample plots.
Standard operating procedures (SOPs) prescribed under national
forest inventory are applied. In the absence of these, SOPs from
published handbooks, or from the IPCC GPG LULUCF 2003, may be
applied
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 85
July 2012
1
Tool CLI: Estimation of carbon stocks and change in carbon stock in litter
2
3
4
Source
5
Assumptions
6
This tool makes the following assumption:
This tool is based on the CDM A/R Tool “Estimation of carbon stocks and change in carbon stocks in
dead wood and litter in A/R CDM project activities” (Version 01.1.0)24.
7
Linearity of change of biomass in litter over a period of time:
8
9
Change of biomass in litter may be assumed to proceed, on average, at an approximately
constant rate between two points of time at which the biomass is estimated.
10
Parameters
11
This tool provides procedures to determine the following parameters:
Parameter
SI Unit
Description
C LI ,t
t CO2-e
Carbon stock in litter within the project boundary at a given point
of time in year t
CLI ,t
t CO2-e
Change in carbon stock in litter within the project boundary in year
t
12
While applying this tool in a methodology, the following notation should be used:
13
In the project scenario:
14
CLI _ PROJ ,t for C LI ,t
15
C LI _ PROJ , t for CLI ,t
16
Methods
17
18
19
Carbon stock in litter can either be based on the same strata used to estimate tree biomass or Project
Proponent may use alternative stratification if transparent and verifiable information can be given for
justification of such a choice.
24
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 86
July 2012
20
Step 1 Estimation of carbon stock in litter
21
22
Two methods are offered for estimation of carbon stock in litter: a measurement-based method and a
conservative default-based approach.
23
Method 1 Measurement approach to estimation of carbon stock in litter (CLI)
24
25
26
27
28
29
1.
For estimating carbon stock in litter, four litter samples are collected from each sample plot,
using a sampling frame which is placed in four randomly selected positions within the plot. The
four samples are well mixed into one composite sample and its wet weight is taken. A subsample taken from the composite sample is weighed, oven dried, and weighed again to
determine its dry weight. The dry-to-wet weight ratio of the sub-sample is calculated and used
for estimating the dry weight of the composite litter sample.
30
2.
Carbon stock in litter biomass in plot p is then calculated as:
31
CLI , p ,i ,t 
32
where:
A
44
 CFLI  10 * p ,i  BLI _ W ET, p ,i  DWRLI , p ,i
12
4 * a p ,i
(81)
CLI , p ,i , t
Carbon stock in litter in plot p in stratum i; t CO2-e
CFLI
Carbon fraction of dry biomass in litter; dimensionless (IPCC default value25 of 0.37
is used)
BLI _ W ET, p ,i
Wet weight of the composite litter sample collected from plot p of stratum i; kg
DWR LI , p ,i
Dry-to-wet weight ratio of the litter sub-sample collected from plot p in stratum i;
dimensionless
Note: It is acceptable to determine this ratio for three randomly selected sample
plots in a stratum and then apply the average ratio to all plots in that stratum.
A p ,i
Total area of sample plots in stratum i; ha
a p ,i
Area of sampling frame for plot p in stratum i; m2
I
1, 2, 3, … biomass estimation strata within the project boundary
25
IPCC GPG for LULUCF, 2003, page 3.35, section 3.2.1.2.1.1 Choice of Method
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 87
July 2012
P
1, 2, 3, … sample plots in stratum i
t
1, 2, 3, … years elapsed since the start of the project activity
33
3.
34
CLI , i ,t 
35
36
37
38
Carbon stock in litter in stratum i is then calculated as:
Ai
Ap ,i
C
LI , p , i , t
(82)
p
where
C LI , i ,t
Carbon stock in litter in stratum i at a given point of time in year t; t CO2-e
Ai
Area of stratum i; ha
Ap , i
Area of sample plots in stratum i; ha
CLI , p ,i , t
Carbon stock in litter in plot p in stratum i; t CO2-e
P
1, 2, 3, … sample plots in stratum i
I
1, 2, 3, … biomass estimation strata within the project boundary
t
1, 2, 3, … years elapsed since the start of the project activity
4.
Finally, the carbon stock in litter biomass within the project boundary at a given point of time in
year t is calculated by summing up C LI , i , t over all the strata, that is:
CLI ,t   CLI ,i ,t
i
(83)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 88
July 2012
39
where:
C LI ,t
Carbon stock in litter within the project boundary at a given point of time in year t;
t CO2-e
C LI , i ,t
Carbon stock in litter in stratum i at a given point of time in year t; t CO2-e
I
1, 2, 3, … biomass estimation strata within the project boundary
t
1, 2, 3, … years elapsed since the start of the project activity
40
Method 2 Default method for estimation of carbon stock in litter (CLI)
41
42
If Project Proponents do not wish to make sampling based measurements for estimation of C stock in
litter, they may use the default method described in this section.
43
44
For all strata where this default method is to be used, the change in carbon stock in litter is estimated
as:
45
C LI ,t   CTREE ,i ,t * DFLI 
(84)
i
46
where:
C LI ,t
Carbon stock in litter within the project boundary at a given point of time
in year t; t CO2-e
CTREE , i ,t
Carbon stock in trees in stratum i at a point of time in year t; t C
DF LI
Default factor for the relationship between carbon stock in litter and
carbon stock in trees; %
I
1, 2, 3, … biomass estimation strata within the project boundary
t
1, 2, 3, … years elapsed since the start of the project activity
47
Step 2 Estimation of change in carbon stock in litter
48
49
50
The rate of change of litter biomass over a period of time is calculated assuming a linear change (see
assumptions under Section I). Therefore, the rate of change in carbon stock in litter over a period of
time is calculated as:
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 89
July 2012
51
dC LI , ( t1 ,t 2 ) =
52
where:
CLI ,t 2  CLI ,t1
(85)
T
dC LI , ( t1 ,t 2 )
Rate of change in carbon stock in litter within the project boundary during the period
between a point of time in year t1 and a point of time in year t2; t CO2-e yr-1
C LI ,t 2
Carbon stock in litter within the project boundary at a point of time in year t2; t CO2-e
C LI ,t1
Carbon stock in litter within the project boundary at a point of time in year t1; t CO2-e
T
Time elapsed between two successive estimations (T=t2 – t1); yr
5. Change in carbon stock in litter within the project boundary in year t (t1  t  t2) is given
by:
53
54
55
CLI ,t  dCLI , (t1 ,t 2 )  1year for t1  t  t2
56
where:
(86)
CLI ,t
Change in carbon stock in litter within the project boundary in year t; t CO2-e
dC LI , ( t1 ,t 2 )
Rate of change in carbon stock in litter within the project boundary during the period
between a point of time in year t1 and a point of time in year t2; t CO2-e yr-1
57
58
Parameter Tables
59
Data and parameters not monitored
Data / Parameter:
CFLI
Data unit:
t C t-1 d.m.
Used in equations:
Description:
Source of data:
Carbon fraction of litter biomass
IPCC default value of 0.37 t C t-1 d.m. may be used
Data / Parameter:
DFDW
Data unit:
Used in equations:
%
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 90
July 2012
Description:
Default factor for the relationship between carbon stock in litter and
carbon stock in trees
Source of data:
Defaults conservatively derived from Delaney et al. 1997, Smith et
al., Glenday 2008, Keller et al. 2004, Eaton and Lawrence 2006,
Krankina and Harmon 1995, and Clark et al 2002.
Biome
TROPICAL
TROPICAL
TROPICAL
TROPICAL
TEMPERATE/BOREAL
60
Data / Parameter:
Rj
Data unit:
Used in equations:
Description:
Source of data:
Dimensionless
Elevation
<2000m
<2000m
<2000m
>2000m
All
Precipitation
DFLI
<1000 mm/yr
4%
1000-1600 mm/yr 1%
>1600 mm/yr
1%
All
1%
All
4%
Root-shoot ratio for species j
The source of data, in order of preference, shall be any of the
following: (a) Existing local species-specific data; (b) National
species-specific data (e.g. national forest inventory or national GHG
inventory); (c) Species-specific data from neighbouring countries
with similar conditions; (d) Globally available species-specific data. If
none of the above sources are available, then the value of Rj may be
calculated as R = exp[-1.085+0.9256*ln(A)]/A, where A is aboveground biomass (t d.m. ha-1) [Source: Table 4.A.4 of IPCC GPGLULUCF 2003]
Data and parameters monitored
Data / Parameter:
Ai
Data unit:
Used in equations:
Description:
Source of data:
Measurement procedures
Ha
Monitoring frequency:
Every five years since the year of the initial verification
Area of stratum i
Field measurement
Standard operating procedures (SOPs) prescribed under national
forest inventory are applied. In absence of these, SOPs from
published handbooks, or from the IPCC GPG LULUCF 2003, may be
applied.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 91
July 2012
QA/QC procedures:
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In the absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
Data / Parameter:
ap,i
Data unit:
m2
Used in equations:
Description:
Source of data:
Measurement procedures:
Area of litter sampling frame used in plot p in stratum i
Measurement
Standard operating procedures (SOPs) prescribed under national
forest inventory are applied. In absence of these, SOPs from
published handbooks, or from the IPCC GPG LULUCF 2003, may be
applied
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
Comments:
Often a litter sampling frame of 0.50 m2 is used
Data / Parameter:
BLI_WET,p,i
Data unit:
Used in equations:
Description:
Kg
Source of data:
Measurement procedures:
Field measurements in sample plots.
Standard operating procedures (SOPs) prescribed under national
forest inventory are applied. In absence of these, SOPs from
published handbooks, or from the IPCC GPG LULUCF 2003, may be
applied
Monitoring frequency:
QA/QC procedures:
Every five years since the year of the initial verification
Quality control/quality assurance (QA/QC) procedures prescribed
under national forest inventory are applied. In the absence of these,
QA/QC procedures from published handbooks, or from the IPCC GPG
LULUCF 2003, may be applied
Data / Parameter:
T
Wet weight of the composite litter sample collected from plot p of
stratum i; kg
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 92
July 2012
Data unit:
Used in equations:
Description:
Year
Source of data:
Measurement procedures:
Comments:
Recorded time
N/A
If the two successive estimations of carbon stock are carried out at
different points of time in year t2 and t1, (e.g. in the month of April in
year t1 and in the month of September in year t2), then a fractional
value shall be assigned to T
Data / Parameter:
DWRLI,p,i
Dimensionless
Data unit:
Used in equations:
Description:
Source of data:
Measurement procedures:
Monitoring frequency:
QA/QC procedures:
Time period elapsed between two successive estimations of carbon
stock
Dry-to-wet weight ratio of the litter (dry weight/wet weight)
Laboratory measurement of field samples
Litter samples shall be collected and well mixed into one composite
sample at the same time of year in order to account for natural and
anthropogenic influences on the litter accumulation and to eliminate
seasonal effects. A subsample from the composite sample of litter is
taken, oven dried and weighed to determine the dry weight.
Every five years since the year of the initial verification
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 93
July 2012
1
2
Tool CWP: Estimation of carbon stock and carbon stock changes in wood
products
3
4
Source
5
Parameters
Tool is based on the ACR Methodology “Afforestation and Reforestation of Degraded Land”.26
Parameter
SI Unit
Description
CW P,t
t CO2-e
Carbon stock in wood products, in year t; t CO2e
CW P,t
t CO2-e
Change in carbon stock in dead wood within the project boundary
in year t; t CO2-e yr-1
6
While applying this tool in a methodology, the following notation should be used:
7
In the project scenario:
8
CW P _ PROJ ,t for CW P,t
9
CW P _ PROJ ,i ,t for CW P,i ,t
10
11
Methods
12
13
Wood products may be excluded from the project as this carbon stock is considered to be zero
in the baseline scenario and omission is thus always conservative.
14
15
Step 1 Estimation of carbon stock in wood products
This method is based on the methods set out by Winjum et al (1998)27.
16
Step 1.1 Calculate extracted biomass
17
18
Calculate the biomass of the total volume extracted from the start of the project to date from
within the project boundary (if necessary convert volumes in ft3 to m3 by multiplying by 0.0283):
26
27
http://www.americancarbonregistry.org/carbon-accounting/afforestation-and-reforestation-of-degraded-lands
Winjum, J.K., Brown, S. and Schlamadinger, B. 1998. Forest harvests and wood products: sources and
sinks of atmospheric carbon dioxide. Forest Science 44: 272-284
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 94
July 2012
EXCW P,i ,t ,ty   Vex ,i ,h,ty, j * D j * CFj 
H PS S PS
19
(87)
h 1 j 1
20
where:
EXCW P,i ,t ,ty
The summed stock of extracted biomass carbon from stratum i up to year t by
class of wood product ty; t C
Vex ,i ,h ,ty, j
The volume of timber extracted from stratum i during harvest h by species j and
wood product class ty; m3
Dj
Basic wood density of species j; t d.m. m-3
CFj
Carbon fraction of biomass for tree species j; t C t-1 d.m. (IPCC default value = 0.5
t C t-1 d.m.)
h
1, 2, 3 …HPS number of harvests since the start of the project activity up to year t.
j
1, 2, 3 … SPS tree species in the baseline scenario
ty
Wood product class – defined here as sawnwood, wood-based panels, other
industrial roundwood, paper and paper board, and other
i
1, 2, 3, … MPS strata in the project scenario
t
1, 2, 3, … t* years elapsed since the start of the project activity
21
22
Step 1.2 Calculate Wood Waste fraction
23
24
25
Winjum et al 1998 indicate that the proportion of extracted biomass that is oxidized (burning or
decaying) from the production of commodities to be equal to 19% for developed countries, 24%
for developing countries.
26
WW is therefore equal to:
27
WWi ,t  EXCW P,i ,t ,ty * wf
28
where:
WWi,t
(88)
Wood waste. The fraction of biomass extracted from stratum i up to year t
immediately emitted through mill inefficiency; t C
EXCW P,i ,t ,ty
The summed stock of extracted biomass carbon from stratum i up to year t by
class of wood product ty; t C
ty
Wood product class – defined here as sawnwood (s), wood-based panels (w),
other industrial roundwood (oir), paper and paper board (p), and other (o)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 95
July 2012
wf
Wood waste fraction – 0.19 for developed countries, 0.24 for developing
countries; t C t C-1
I
1, 2, 3, … MPS strata in the project scenario
t
1, 2, 3, … t* years elapsed since the start of the AR ACR project activity
29
Step 1.3 Calculate Short-lived Fraction
30
31
Winjum et al 1998 give the following proportions for wood products with short-term (<5 yr) uses
(applicable internationally):
32
33
34
35
Sawnwood
Woodbase panels
Other industrial roundwood
Paper and Paperboard
36
37
The methodology makes the assumption that all other classes of wood products are 100%
oxidized within 5 years.
38
SLF is therefore equal to:
39
SLFi ,t  EXCW P,i ,t ,ty  WWi ,t * slp
40
41
where:
SLFi,t
0.2
0.1
0.3
0.4
(89)
Fraction of wood products extracted from stratum i up to year t that will be emitted
to the atmosphere within 5 years of timber harvest; t C
EXCW P,i ,t ,ty
The summed stock of extracted biomass carbon from stratum i up to year t by
class of wood product ty; t C
WWi,t
Wood waste. The fraction of biomass extracted from stratum i up to year t
immediately emitted through mill inefficiency; t C
Slp
Short-lived proportion - 0.2 for sawnwood, 0.1 for woodbase panels, 0.3 for other
industrial roundwood, 0.4 for paper and paperboard and 1 for other; t C t C-1
Ty
Wood product class – defined here as sawnwood (s), wood-based panels (w),
other industrial roundwood (oir), paper and paper board (p), and other (o)
i
1, 2, 3, … MPS strata in the project scenario
T
1, 2, 3, … t* years elapsed since the start of the project activity
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 96
July 2012
42
43
44
45
Step 1.4 Calculate additional oxidized fraction (OF)
Winjum et al 1998 gives annual oxidation fractions for each class of wood products split by forest region
(boreal, temperate and tropical). This methodology projects these fractions over 95 years to give the
additional proportion that is oxidized between the 5th and 100th years after initial harvest (Table 5):
46
47
Table 5 Proportion of remaining wood products oxidized between 5 and 100 years after initial harvest by wood product class
and forest region Wood Product Class
Wood Product Class
Boreal
Temperate
Tropical
Sawnwood
0.36
0.60
0.84
Woodbase panels
0.60
0.84
0.97
Other industrial
roundwood
0.84
0.97
0.99
Paper and paperboard
0.36
0.60
0.99
48
49
OF is therefore equal to:
50
OFi ,t  EXCW P,i ,t ,ty  WWi ,t   SLFi ,t * fo
51
where:
(90)
OFi,t
Fraction of wood products extracted from stratum i up to year t that will be emitted to
the atmosphere between 5 and 100 years of timber harvest; t C
EXCW P,i ,t ,ty
The summed stock of extracted biomass carbon from stratum i up to year t by class of
wood product ty; t C
WWi,t
Wood waste. The fraction of biomass extracted from stratum i up to year t immediately
emitted through mill inefficiency; t C
SLFi,t
Fraction of wood products extracted from stratum i up to year t that will be emitted to
the atmosphere within 5 years of timber harvest; t C
fo
Fraction oxidized – see Table 3 for defaults; t C t C-1
Ty
Wood product class – defined here as sawnwood (s), wood-based panels (w), other
industrial roundwood (oir), paper and paper board (p), and other (o)
I
1, 2, 3, … MPS strata in the project scenario
T
1, 2, 3, … t* years elapsed since the start of the AR ACR project activity
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 97
July 2012
52
Step 1.5 Calculate carbon stocks in wood products from stratum i
53
54
55
56
57
58
Calculate the proportion of extracted timber that remains sequestered after 100 years. Instead of
tracking annual emissions through retirement, burning and decomposition, the methodology calculates
the proportion of wood products that have not been emitted to the atmosphere 100 years after harvest
and assumes that this proportion is permanently sequestered. Default factors listed below are derived
from Winjum et al.199828. Alternatively, Project Proponents may use specific factors in equations 25e to
25h from local, regional or national sources that can be validated by peer-reviewed literature.
59
CWP,i ,t 
 EXC
ty
WP,i ,t ,ty
 WWi ,t   SLFi ,t   OFi ,t 
(91)
s ,w,oir, p ,o
60
where:
CW P,i ,t
Carbon stock in wood products from stratum i up to year t; t C
EXCW P,i ,t ,ty
The summed stock of extracted biomass carbon from stratum i up to year t
by class of wood product ty; t C
WWi,t
Wood waste. The fraction of biomass extracted from stratum i up to year t
immediately emitted through mill inefficiency; t C
SLFi,t
Fraction of wood products up to year t that will be emitted to the
atmosphere within 5 years of timber harvest; t C
OFi,t
Fraction of wood products up to year t that will be emitted to the
atmosphere between 5 and 100 years of timber harvest; t C
ty
Wood product class – defined here as sawnwood (s), wood-based panels (w),
other industrial roundwood (oir), paper and paper board (p), and other (o)
i
1, 2, 3, … MPS strata in the project scenario
t
1, 2, 3, … t* years elapsed since the start of the AR ACR project activity
61
62
Step 1.6 Sum carbon stocks in wood products across strata
63
64
Finally, the carbon stock in wood products biomass within the project boundary at a given point of time
in year t is calculated by summing up CW P,i ,t over all the strata. If harvesting boundaries extend across
65
66
stratum boundaries, harvest volumes should be allocated to each stratum proportionally to the area
harvested in each stratum and documentation thereof presented for verification.
28
Winjum, J.K., Brown, S. and Schlamadinger, B. 1998. Forest harvests and wood products: sources and
sinks of atmospheric carbon dioxide. Forest Science 44: 272-284
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 98
July 2012
67
CW P,t 
68
where:
44
 CW P,i,t
12 i
(92)
CW P,t
Carbon stock in wood products within the project boundary at a given point of time
in year t; t CO2-e
CW P,i ,t
Carbon stock in wood products in stratum i at a given point of time in year t; t C
I
1, 2, 3, … biomass estimation strata within the project boundary
t
1, 2, 3, … years elapsed since the start of the project activity
69
70
Step 2 Estimation of change in wood products carbon stock
71
72
73
The change in carbon stock in wood products is estimated on the basis of harvested volume and ratios
of long-term wood products of time in year t1 and again at a point of time in year t2 for each stratum.
The rate of change of carbon stock in wood products is calculated as:
74
CW P,t 
75
where:
76
CW P,t2  CW P,t1
T
(93)
CW P,t
Rate of change in long-term wood products, averaged for the period between year t1
and year t2; t CO2-e yr-1
CW P,t 2
Carbon stock in wood products, up to year t2; t CO2-e
CW P,t1
Carbon stock in wood products, up to year t1; t CO2-e
T
Time elapsed between two successive estimations (T=t2 – t1); yr
I
1, 2, 3, … MPS strata in the project scenario
T
1, 2, 3, … t* years elapsed since the start of the AR ACR project activity
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 99
July 2012
77
Parameter Tables
78
Data and parameters not monitored
Data / Parameter:
IV,j,t
Data unit:
Used in equations:
Description:
Source of data:
m3 ha-1 yr-1
Average annual increment in stem volume of species j, in year t
The source of data, in order of preference, shall be the following:
(a) Existing local and species or group of species-specific tree growth
data or local volume tables; (b) National and species or group of
species-specific tree growth data or standard volume tables (e.g. from
national forest inventory or national GHG inventory); (c) Species or
group of species-specific tree growth data or volume tables from
neighbouring countries with similar conditions; (d) Globally available
data applicable to species or group of species
Measurement procedures:
Comments:
N/A
IV,j,t is estimated as the “current annual increment – CAI”. The “mean
annual increment” – often abbreviated as MAI in the forestry
inventories– can only be used if its use leads to conservative
estimates.
The values read from tables if expressed on the per unit of area basis
will usually apply to fully stocked forest. Thus, they should be
corrected to be applicable in the baseline conditions, e.g. by
multiplication by the fraction of tree crown cover or fraction of
number of stems in the baseline stratum of interest (other ways of
correction may be proposed by project proponents)
Data / Parameter:
OFi,t,SLFi,t,WWi,t
Data unit:
Used in equations:
Description:
tC
Source of data:
OFi,t = Fraction of wood products extracted from stratum i up to year
t that will be emitted to the atmosphere between 5 and 100 years
after production; SLFi,t = Fraction of wood products extracted from
stratum i up to year t that will be emitted to the atmosphere within 5
years of production; WWi,t = Fraction of biomass extracted from
stratum i up to year t effectively emitted to the atmosphere during
production.
The source of the data is the published paper of Winjum et al. 1998:
Winjum, J.K., Brown, S. and Schlamadinger, B. 1998. Forest harvests
and wood products: sources and sinks of atmospheric carbon dioxide.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 100
July 2012
Measurement procedures:
Comments:
79
Forest Science 44: 272-284
N/A
Data / Parameter:
Rj
Data unit:
Used in equations:
Description:
Source of data:
Dimensionless
Measurement procedures:
Comments:
N/A
Root-shoot ratio for species or group of species j
The source of data, in order of preference, shall be any of the
following: (a) Existing local and species or group of species-specific
data; (b) National and species or group of species-specific data (e.g.
national forest inventory or national GHG inventory); (c) Species or
group of species-specific data from neighbouring countries with
similar conditions; (d) Globally available data applicable to species or
group of species growing under similar conditions or similar forest
type. If none of the above sources are available, then the value of Rj
may be calculated as B/A where B = exp[-1.085+0.9256*ln(A)], where
A is above-ground biomass (t d.m. ha-1) and B is below-ground
biomass (t d.m. ha-1) [Source: Table 4.A.4 of IPCC GPG-LULUCF 2003]
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 101
July 2012
1
Tool CSOC: Tool for estimation of change in soil organic carbon stocks
2
3
4
Applicability
This tool is applicable when the areas of land, the baseline scenario, and the project activity
meet the following conditions:
5
a. The areas of land to which this tool is applied
6
i.
Do not fall into wetland29 category; or
7
8
ii.
Do not contain organic soils as defined in “Annex A: glossary” of the IPCC GPG LULUCF
2003;
9
10
Parameters
This tool provides procedures to determine thefollowing parameters:
11
12
Table 6: Parameters determined
Parameter
SI Unit
Description
C SOC,t
t CO2-e
Soil organic carbon within the project boundary at a given point of
time in year t
C SOC ,t
t CO2-e
Change in SOC stock within the project boundary in year t
13
14
While applying this tool in a methodology, the following notation should be used:
15
In the project scenario:
16
C SOC _ PROJ ,t for C SOC,t
17
C SOC _ PROJ ,t for C SOC ,t
18
29
“Wetlands”, “settlements”, “cropland” and “grassland” are land categories as defined in the Good Practice
Guidance for Land Use, Land-use Change and Forestry (IPCC, 2003).
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 102
July 2012
19
Methods
20
21
Step 1 Estimation of soil organic carbon stock
22
Measurements of initial stocks must take place within 2 years of the project start date, for
simplicity referred to here as stocks at t=0.
23
The procedure to be followed in the measurement of soil organic carbon is outlined below.
26
Strata employed for soil organic carbon will conform to the same strata employed for all other
included pools. To estimate the carbon stock in soil organic carbon per unit area for sample plot
sp, stratum i, at time t:
27
C SOC, sp,i ,t  C SOCsample, sp,i ,t * BD sample, sp,i ,t * Dep sample, sp,i ,t *100
28
Where:
29
CSOCsp,i,t
Carbon stock in soil organic carbon for sample plot sp, stratum i, at time
t; t C ha-1
CSOCsample,sp,i,t
Soil organic carbon content of the sample in sample plot sp, stratum i, at
time t; determined in the laboratory in g C/100 g soil (fine fraction <2
mm)
BDsample,sp,i,t
Bulk density of fine (<2 mm) fraction of mineral soil in sample plot sp,
stratum i, at time t ; determined in the laboratory in g fine fraction cm-3
total sample volume
Depsample,sp,i,t
Depth to which soil sample is collected in sample plot sp in stratum i at
time t; cm
39
sp
1, 2, 3 … Pi sample plots in stratum i
40
i
1, 2, 3 … M strata
41
t
0, 1, 2, 3 … years elapsed since the start of the project activity
42
To estimate the mean carbon stock in soil organic carbon, converted to carbon dioxide
equivalents, per unit area for stratum i, at time t:
24
25
30
31
32
33
34
35
36
37
38
43
44
C SOC,i ,t
 pi


1C SOC,sp,i ,t  44
 sp

 * * Ai

pi  12




(94)
(95)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 103
July 2012
45
Where:
46
CSOC,i,t
Carbon stock in soil organic carbon for stratum i, at time t; t CO2-e
47
Ai
Area of stratum i; ha
48
CSOCsp,i,t
Carbon stock in soil organic carbon for sample plot sp, stratum i, at time t;
t C ha-1
50
sp
1, 2, 3 … Pi sample plots in stratum i
51
i
1, 2, 3 … M strata
52
t
0, 1, 2, 3 … years elapsed since the start of the project activity
53
44/12
Ratio of molecular weight of CO2 to carbon, t CO2-e t C-1
49
54
55
56
57
Step 2 Estimation of change in soil organic carbon
The change in carbon stocks may be estimated by repeated sampling. Non-permanent sampling
locations must be used.
58
Carbon stock changes in the project are estimated using the stock change method:
59
C SOC,t    C SOC,i ,t
60
C SOC,i ,t 
M
(96)
i 1
C SOC,i ,t  C SOC,i ,t  x
x
(97)
61
62
Where:
63
ΔCSOC,i,t
Annual net carbon stock change in soil for stratum i, at time t; t CO2-e yr-1
64
CSOC,i,t
Mean carbon stock in soil for stratum i, at time t; t CO2-e
65
CSOC,i,t-1
Mean carbon stock in soil for stratum i, at time t= t-x; t CO2-e
66
i
1, 2, 3 …M strata within the project boundary
67
t
0, 1, 2, 3, … t years elapsed since the start of the project activity
68
69
70
x
number of years prior to t the previous inventory was conducted
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 104
July 2012
71
Parameter Tables
72
Data and parameters not monitored
73
74
Data and parameters monitored
Data / Parameter:
BDsample,sp,i,t
Data unit:
g cm-3
Used in equations:
Description:
87
Bulk density of fine (< 2 mm) fraction of mineral soil per unit volume
of sample in g cm-3; bulk density equals the oven dry weight of the
fine fraction (< 2 mm) of the soil core divided by the core volume
Field sampling and laboratory determination
Source of data:
Measurement procedures:
For bulk density determination, samples (cores) of known volume are
collected in the field and oven dried to a constant weight at 105 oC
(for a minimum of 48 hours). The total sample is then weighed, then
any coarse rocky fragments (>2 mm) are sieved and weighed
separately.
The bulk density of the soil core is estimated as:
BD sampl e 
ODW  RF
CV
Where:
=
Bulk density of the < 2mm fraction, in grams per cubic
BDsample
centimeter (g/cm3)
ODW =
Oven dry mass total sample in grams
CV
=
Core volume in cm3
RF
=
Mass of coarse fragments (> 2 mm) in grams
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 105
July 2012
Note that volume includes coarse (>2mm) fragments. Because coarse
rocky fragments occupy space in the soil profile in which carbon is not
stored, discounting this volume as in traditional bulk density
calculations would overestimate soil carbon stocks when applied to a
volume that does not distinguish between coarse and fine fractions.
Further guidance is provided in the IPCC 2003 GPG-LULUCF and in:
Nelson, D.W., and L.E. Sommers. 1982. Total carbon, organic carbon,
and organic matter. p. 539–580. In A.L. Page et al. (ed.) Methods of
soil Analysis. Part 2. 2nd ed. Agron. Monogr. 9. ASA and SSSA,
Madison, WI.
Monitoring frequency:
Pearson, T., Walker, S. and Brown, S. 2005. Sourcebook for Land Use,
Land-Use Change and Forestry Projects. Winrock International and the
World Bank Biocarbon Fund. 57pp. Available at:
http://www.winrock.org/Ecosystems/files/WinrockBioCarbon_Fund_Sourcebook-compressed.pdf
At least every 10 years since the year of initial verification
Comments:
Data / Parameter:
CSOCsample,sp,i,t
Data unit:
Used in equations:
Description:
g C/100 g soil (fine fraction <2 mm)
87
Soil organic carbon of the sample in sample plot sp, stratum i, at time
t; determined in the laboratory in g C/100 g soil (fine fraction <2 mm)
Field sampling and laboratory determination
Source of data:
Measurement procedures:
For soil carbon determination, an aggregate sample (e.g. from 4
systematically-distributed cores) is collected from within a sample
plot in the field, thoroughly mixed and sieved through a 2 mm sieve.
The prepared sample is analyzed for percent organic carbon using
either dry combustion using a controlled-temperature furnace (e.g.
LECO CHN-2000, LECO RC-412 multi-carbon analyzer, or equivalent),
dichromate oxidation with heating, or Walkley-Black method.
Further guidance is provided in the IPCC 2003 GPG-LULUCF and in
Nelson, D.W., and L.E. Sommers. 1982. Total carbon, organic carbon,
and organic matter. p. 539–580. In A.L. Page et al. (ed.) Methods of
soil Analysis. Part 2. 2nd ed. Agron. Monogr. 9. ASA and SSSA,
Madison, WI.
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 106
July 2012
Monitoring frequency:
Comments:
Data / Parameter:
Data unit:
Used in equations:
Description:
Source of data:
Measurement procedures:
Pearson, T., Walker, S. and Brown, S. 2005. Sourcebook for Land Use,
Land-Use Change and Forestry Projects. Winrock International and the
World Bank Biocarbon Fund. 57pp. Available at:
http://www.winrock.org/Ecosystems/files/WinrockBioCarbon_Fund_Sourcebook-compressed.pdf
At least every 10 years since the year of initial verification
Monitoring frequency:
Comments:
Depsample
Cm
87
Depth in cm to which soil sample is collected
Core dimensions recorded in the field
Depth of sampling for soil organic carbon is centered on the upper soil
horizons where root biomass and organic matter inputs are
concentrated, depending on soil type and ecosystem, typically
between 20 cm and 100 cm. Depth of soil sampling employed in
inventories is held constant for the duration of the project.
Depsample
Cm
Data / Parameter:
CFs
Data unit:
Used in equations:
t C t dry soil-1
91
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 107
July 2012
Description:
Mean carbon fraction of soil type s
Source of data:
Measurement procedures:
Field sampling and laboratory determination
A minimum of 20-30 representative samples of each soil type s that
will be added to the project area must be taken.
Samples are oven dried (70° C) to a constant weight in the laboratory.
The prepared sample is analysed for precent organic carbon using
either dry combustion using a controlled-temperature furnace (e.g.
LECO CHN-2000, LECO RC-412 multi-carbon analyser, or equivalent),
dichromate oxidation with heating, or Walkley-Black method.
For each soil type s either:


Monitoring frequency:
Comments:
75
76
If the 90% confidence interval is equal to or less than 10% of
the mean, the mean carbon fraction is applied.
If the 90% confidence interval is greater than 10% of the
mean, the higher 90% confidence bound of the mean is
applied.
At least every 10 years since the year of initial verification
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 108
July 2012
1
2
Tool N2O: Estimation of direct and indirect oxide emission from nitrogen
fertilization
3
4
5
Source
6
Parameters
Tool is based on the CDM AR Methodological Tool “Estimation of direct oxide emission from nitrogen
fertilization” (Version 01)30.
Parameter
SI Unit
Description
N 2 O fertilizer,t
t CO2-e
N2O emission as a result of nitrogen fertilization within project
boundary, in year t
N 2 O fertilizer,t
t CO2-e
Change in N2O emissions as a result of nitrogen fertilization within
project boundary, in year t
7
While applying this tool in a methodology, the following notation should be used:
8
In the baseline scenario:
9
N 2 O fertilizer, _ BSLi,t for N 2 O fertilizer,i ,t
10
N 2 O fertilizer, BSL,t for N 2 O fertilizer,t
11
In the project scenario:
12
N 2 O fertilizer,i ,t for N 2 O fertilizer,i ,t
13
N 2 O fertilizer,t for N 2 O fertilizer,t
14
15
16
17
18
19
Methods
This tool can be used for both ex ante and ex post estimation of the nitrous oxide emissions from
nitrogenous fertilizer application within the boundary of the project activity. For ex post estimation
purposes, activity data (quantities and nitrogen content of synthetic and organic nitrogen fertilizers) are
monitored. As Project Proponents may use various types of fertilizers, it is important to identify and
record the fertilizer types applied and their nitrogen content.
30
http://cdm.unfccc.int/methodologies/ARmethodologies/approved
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 109
July 2012
20
21
The total N2O emissions due to fertilizer use is equal to the sum of direct N2O emissions and indirect N2O
emissions:
22
N 2 O fertilizer,t  N 2Odirect, fertilizer, t  N 2Oindirect, fertilizer, t
(98)
23
24
25
The direct nitrous oxide emissions from nitrogen fertilization can be estimated using equations as
follows:
26
N 2 Odirect, fertilizer,t   N 2 Odirectfertilizer,t
27
N 2 Odirect, fertilizer,t   N 2 Odirect, fertilizer,i ,t
(100)
28
N 2 Odirect, fertilizer,i ,t  ( FSN ,i ,t  FON ,i ,t ) * EF1 * MW N 2O * GWPN 2O
(101)
29
FSN ,i ,t   M SFs,i ,t * NCSFs * (1  FracGASF )
t*
(99)
t 1
m
i 1
S
(102)
s
30
O
FON ,i ,t   M OFo,i ,t * NCOFo * (1  FracGASM )
(103)
o
31
32
where:
N 2 Odirect, fertilizer,t Sum of the direct N2O emissions as a result of nitrogen application; t CO2-e
N 2 Odirect, fertilizer,i ,t
Direct N2O emission as a result of nitrogen application within the project boundary,
in year t; t-CO2-e
i
1, 2, 3, … M strata
FSN,i,t
Mass of synthetic fertilizer nitrogen applied adjusted for volatilization as NH3 and
NOX, t-N in stratum i in year t
Mass of organic fertilizer nitrogen applied adjusted for volatilization as NH3 and
NOX, t-N in stratum i in year t year t
Mass of synthetic fertilizer type s applied, tonne in stratum i in year t
Mass of organic fertilizer type o applied, tonne in stratum i in year t
Emission Factor for emissions from N inputs, tonne-N2O-N (t-N )-1
(IPCC default = 1% may be used when location specific factors are unavailable)
Fraction that volatilises as NH3 and NOX for synthetic fertilizers, dimensionless (IPCC
FON,i,t
MSFs,i,t
MOFo,i,t
EF1
FracGASF
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 110
July 2012
FracGASM
MWN2O
GWPN2O
NCSFs
NCOFo
S
O
t
default = 0.1 may be used)
Fraction that volatilises as NH3 and NOX for organic fertilizers, dimensionless
(IPCC default = 0.2 may be used)
Ratio of molecular weights of N2O and N (44/28), , tonne-N2O-N (t-N )-1
Global Warming Potential for N2O, kg-CO2-e (kg-N2O)-1 (IPCC default = 310)
Nitrogen content of synthetic fertilizer type s applied, g-N (100 g fertilizer)-1
Nitrogen content of organic fertilizer type o applied, g-N (100 g fertilizer) -1
Number of synthetic fertilizer types
Number of organic fertilizer types
1, 2, 3, . years elapsed since the start of the project activity
33
34
35
The indirect nitrous oxide emissions from nitrogen fertilization can be estimated using equations as
follows:
36
N 2 Oindirect, fertilizer,t   N 2 Oindirect, fertilizer,t
37
N 2 Oindirect, fertilizer,t   N 2 Oindirect, fertilizer,i ,t
(105)
38
N 2 Oindirect, fertilizer,i ,t  ( FSN ,i ,t * FracGASF  F ON ,i ,t * FracGASM ) * EF4 * MW N 2O * GWPN 2O
(106)
t*
t 1
(104)
m
39
40
i 1
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 111
July 2012
41
where:
N 2 Oindirect, fertilizer,t Sum of the indirect N2O emissions as a result of nitrogen application in year t; t
CO2-e
N 2 Oindirect, fertilizer,i ,t
i
Indirect N2O emission as a result of nitrogen application within the project
boundary, in stratum i in year t; t-CO2-e
1, 2, 3, … M strata
FSN,i,t
Mass of synthetic fertilizer nitrogen applied adjusted for volatilization as NH3 and
NOX, t-N in stratum i in year t
FON,i,t
Mass of organic fertilizer nitrogen applied adjusted for volatilization as NH3 and
NOX, t-N in stratum i in year t year t
FracGASF
Fraction that volatilises as NH3 and NOX for synthetic fertilizers, dimensionless
(IPCC default = 0.1 may be used)
FracGASM
Fraction that volatilises as NH3 and NOX for organic fertilizers, dimensionless
(IPCC default = 0.2 may be used)
MWN2O
GWPN2O
t
Ratio of molecular weights of N2O and N (44/28), , tonne-N2O-N (t-N )-1
Global Warming Potential for N2O, kg-CO2-e (kg-N2O)-1 (IPCC default = 310 may be
used)
1, 2, 3, ... years elapsed since the start of the project activity
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 112
July 2012
1
Parameter Tables
2
Data and parameters not monitored
Data / Parameter:
GWPN2O
Data unit:
kg CO2 / kg N2O
Used in equations:
Description:
Global Warming Potential of N2O
Source of data:
IPCC Second Assessment report
Comments:
IPCC Second Assessment report lists as: GWPN2O=310
Data / Parameter:
EF1
Data unit:
t-N2O-N (t-N input)-1
Used in equations:
Description:
Source of data:
Comments:
Emission Factor for emissions from N inputs
Country-specific data, IPCC, Volume 4 Table 11.1
Data unit:
Used in equations:
Description:
FracGASF
Dimensionless
Source of data:
The fraction that volatilises as NH3 and NOX for
synthetic fertilizers
Comments:
Country-specific data, IPCC, Volume 4 Table 11.3
Data / Parameter:
FracGASM
Dimensionless
Data unit:
Used in equations:
Description:
The fraction that volatilises as NH3 and NOX for organic
fertilizers
Source of data:
Country-specific data, IPCC, Volume 4 Table 11.3
Data / Parameter:
NCSFi
Data unit:
g-N (100 g fertilizer)-1
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 113
July 2012
Used in equations:
Description:
Source of data:
Nitrogen content of synthetic fertilizer type i applied
Producers of synthetic fertilizer purchased and used. If
producers do not provide data of nitrogen content, the
nitrogen content should be determined by qualified lab.
Data / Parameter:
NCOFo
Data unit:
g-N (100 g fertilizer)-1
Used in equations:
Description:
Source of data:
Nitrogen content of organic fertilizer type o applied
Producers of organic fertilizer purchased and used. If
producers do not provide data of nitrogen content, the
nitrogen content should be determined by qualified lab.
3
4
Data and parameters monitored
Data / Parameter:
Data unit:
Used in equations:
Description:
Source of data:
Measurement procedures (if any):
Monitoring frequency:
Comments:
Data / Parameter:
Data unit:
Used in equations:
Description:
Source of data:
Measurement procedures (if any):
Monitoring frequency:
Comments:
5
MSFi,t
t
Mass of synthetic fertilizer type i applied in year t
Record of synthetic fertilizer purchased and used
Keep record of quantities purchased and used
Continuous monitoring of all fertlizer applied
MOFj,t
t
Mass of organic fertilizer type j applied in year t
Record of organic fertilizer purchased and/or used
Keep record of quantities purchased and/or used
Continuous monitoring of all fertlizer applied
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 114
July 2012
1
2
Tool: Grazing GHG Emissions: CH4 emissions due to enteric fermentation
and N2O from manure and urine deposited on grassland soils
3
4
5
Source
6
Parameters
Tool is based on 2006 IPCC Guidelines for Natural Greenhouse Gas Inventories31 and VCS proposed
Methodology for Sustainable Grassland Management (SGM) Version 1.
Parameter
SI Unit
Description
CH 4 ,enteric,t
t CO2-e
CH4 emission as a result of enteric fermenation within project
boundary, in year t
CH 4,enteric,t
t CO2-e
Change in CH4 emission as a result of enteric fermenation within
project boundary, at year t
N 2 O grazing,t
t CO2-e
N2O emissions as a result of manure and urine deposited on
grassland soil during grazing, in year t
N 2 O grazing,t
t CO2-e
Change in N2O emissions as a result of manure and urine
deposited on grassland soil during grazing, at year t
7
While applying this tool in a methodology, the following notation should be used:
8
In the baseline scenario:
9
CH 4 ,enteric_ BSL,t for CH 4 ,enteric,t
10
CH 4,enteric _ BSLt for CH 4,enteric,t
11
N 2 O grazing_ BSL,t for N 2 O grazing,t
12
N 2 O grazing_ BSL,t for N 2 O grazing,t
31
http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 115
July 2012
13
In the project scenario:
14
CH 4 ,enteric_ PROJ,t for CH 4 ,enteric,t
15
CH 4,enteric _ PROJ ,t for CH 4,enteric,t
16
N 2 O grazing_ PROJ ,t for N 2 O grazing,t
17
N 2 O grazing_ PROJ ,t for N 2 O grazing,t
18
19
20
21
22
23
24
25
26
Methods
This tool can be used for baseline and project ex ante and project ex post estimation of the emissions
from grazing within the boundary of the project activity. It can also be used to estimate emissions taking
place outside the project boundary as a result of project activities. For ex post estimation purposes,
activity data (population of different livestock types, grazing periods, livestock weight) are monitored.
The methods employed are based on methods presented in the 2006 IPCCC Guidelines for National
Greenhouse Gas Inventories. The emissions from grazing are broken down into two main sources. The
first is the emissions from enteric fermentation and the second is emissions taking place when manure
and urine are deposited on the project boundary during grazing.
27
28
29
30
31
Methane emissions from enteric fermentation
Methane emissions from enteric fermentation in the baseline and project scenario are based on the
number of livestock, emissions per head of livestock, and an estimate of the fraction of the year
livestock spend within the project boundary
32
Methane emissions from enteric fermentation are calculated as:
t*
33
CH 4,enteric   CH 4,enteric,t
(107)
t 1
L
34
CH 4 ,enteric,t  GWPCH 4 *  EFCH 4, L * LPL _ adj,t  1000
(108)
L 1
35
36
M
H L ,i ,t
i 1
Hours t
LPL _ adj,i ,t   LPL,i ,t *
(109)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 116
July 2012
37
where:
CH 4,enteric,t
Change in CH4 emission as a result of enteric fermentation within project boundary,
at year t; t CO2e
CH 4 ,enteric,t
CH4 emission as a result of enteric fermentation within project boundary, in year t; t
CO2e
GWPCH4
Global Warming Potential of CH4; kg CO2 kg CH4-1
EFCH4,enteric,L
Emission Factor due to enteric fermentation per head of livestock type L per year; kg
CH4 head-1 year-1
LPL_adj,t
Adjusted population of livestock type L, in year t; head of livestock
LPL,I,t
Population of livestock type L in stratum i , in year t; head of livestock
HL,t
Average number of hours per year livestock type L located within stratum i at time t;
hours
Hourst
Total number of hours in the year t
L
I
T
1, 2, 3, … L livestock types
1,2,3, …M stratum within project boundary
1, 2, 3, … years elapsed since the start of the project activity
38
39
40
41
Nitrous oxide emissions from manure and urine deposition
Both direct and indirect emissions from manure and urine deposited on the soil during grazing are
accounted for.
t*
42
N 2 O grazing,t   N 2 O grazing,t
43
N 2 O grazing,t  N 2 O grazing,indirect,t  N 2 O grazing, direct,t
t 1
(110)
(111)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 117
July 2012
44
where:
N 2 O grazing,t
Change in total N2O emissions as a result of manure and urine deposition, at year t; t
CO2e
N 2 O grazing,t
Total N2O emissions as a result of manure and urine deposition, at year t; t CO2e
N 2 O grazing,indirect,t Total indirect N2O emissions as a result of manure and urine deposition, at year t; t
CO2e
N 2 O grazing, direct,t
Total direct N2O emissions as a result of manure and urine deposition, at year t; t
CO2e
t
1, 2, 3, … years elapsed since the start of the project activity
45
46
47
48
49
The direct and indirect N2O emissions from manure and urine deposited on the project boundary is
calculated using methods described in the 2006 IPCC Guidelines for National Greenhouse Gas
Inventories. Values for many parameters listed may be drawn from site or region specific data or where
data are unavailable, IPCC default data. See parameter tables for values.
L
50
N 2 O grazing,direct,t   FPRP,adj,t * EF3 PRP, L *
L 1
L
51
N 2 O grazing,indirect,t   FPRP,adj,t * FracGASM , L * EF4 *
L 1
M
52
44
* GWPN 2O
28
FPRP,adj,i ,t   LPL,i ,t * H L,i ,t * WL *
i 1
44
* GWPN 2O
28
Nex L
* 1000 * 1  FracGASM , L 
(1000 * 24)
(112)
(113)
(114)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 118
July 2012
53
where:
N 2 O grazing, direct,t
Total direct N2O emissions as a result of manure and urine deposition, at year t; t
CO2e
N 2 O grazing,indirect,t Total indirect N2O emissions as a result of manure and urine deposition, at year t; t
CO2e
FPRP,adj,t
Annual amount of urine and dung N deposited by grazing animals on project
boundary soils during grazing, adjusted for volatilization as NH3 and NOx at time t; t N
EF3PRP,L
Emission factor for N2O from urine and dung N deposited by livestock type L on
project boundary soils; kg N2O-N (kg N input)-1
EF4
Emission factor for N2O for atmospheric deposition of manure N on soils and water
surfaces within the project boundary; kg N2O-N (kg N input)-1
GWPN2O
Global Warming Potential of N2O; kg CO2 kg N2O-1
LPL,I,t
Population of livestock type L in stratum i at time t
WL
Average weight of livestock type L at time t; kg head-1
NexL
HL,I,t
Nitrogen excretion; kg 1000 kg-1 animal mass day-1
Average number of hours per year an individual of livestock type L located within
stratum i at time t; hours
Fraction of volatilization from dung and urine deposited by grazing animals as NH3
FRACGASM,L
and NOx; kg N volatilized (kg of N deposited)-1
l
t
1, 2, 3, … L livestock types
1, 2, 3, …t years elapsed since the start of the project activity
54
55
56
Parameter Tables
57
Data and parameters not monitored
Data / Parameter:
GWPCH4
Data unit:
kg CO2 / kg CH4
Used in equations:
Description:
Global Warming Potential of CH4
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 119
July 2012
Source of data:
IPCC Second Assessment report
Comments:
IPCC Second Assessment report lists as: GWPCH4=21
Data / Parameter:
EFCH4,enteric,L
Data unit:
kg CH4 head-1 year-1
Used in equations:
Description:
Emission Factor from enteric emissions per head of livestock type L per year
Comments:
Country or site specific data. Where specific data is not available, may use IPCC
2006 default values from tables 10.10 and 10.11
See section below for IPCC values
Data / Parameter:
EF3PRP,L
Data unit:
Used in equations:
kg N2O–N (kg N)-1
Source of data:
Description:
Emission factor for N2O from urine and dung N deposited by live stock type L
on project boundary soils
Source of data:
Country or site specific data. Where specific data is not available, may use IPCC
2006 default values from tables 11.1. EF3PRP,CPP should be used for cattle (dairy,
non-dairy, and buffalo), poultry and pigs. EF3PRP,SO should be used for sheep and
other animals.
Comments:
IPCC 2006 values: EF3PRP,CPP = 0.02 EF3PRP,SO = 0.01
Data / Parameter:
EF4
Data unit:
kg N2O-N (kg N input)-1
Used in equations:
Description:
Emmision factor for N2O for atmospheric deposition of manure N on soils and
water surfaces within the project boundary
Source of data:
Country or site specific data. Where specific data is not available, may use IPCC
2006 default values from tables 11.3
Comments:
IPCC 2006 EF4 = 0.010
Data / Parameter:
GWPN2O
Data unit:
kg CO2 kg N2O-1
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 120
July 2012
Used in equations:
Description:
Global Warming Potential of N2O
Source of data:
IPCC Second Assessment Report
Comments:
IPCC Second Assessment report lists as: GWPN2O=310
Data / Parameter:
NexL
Data unit:
kg 1000 kg-1 animal mass day-1
Used in equations:
Description:
Comments:
Nitrogen excretion
Country or site specific data. Where specific data is not available, may use IPCC
2006 default values from tables 10.19
See IPCC 2006 tables below
Data / Parameter:
FRACGASM,L
Data unit:
kg N volatilized (kg of N deposited)-1
Source of data:
Used in equations:
Description:
Fraction of volatilization from dung and urine deposited by grazing animals as
NH3 and NOx
Source of data:
Country or site specific data. Where specific data is not available, may use IPCC
2006 default values from table 11.3
Comments:
IPCC 2006 value: FRACGASM=0.20
Data / Parameter:
Hourst
Data unit:
Hours
Used in equations:
Description:
Source of data:
Measurement
procedures (if any):
Monitoring
frequency:
Comments:
58
Total number of hours in year t
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 121
July 2012
59
Data and parameters monitored
Data / Parameter:
LPL,i,t
Data unit:
Used in equations:
Description:
Source of data:
Head livestock
Measurement
procedures (if any):
Monitoring frequency:
Population of livestock of livestock type L in stratum i, at time t
Field measurements
Population of livestock by type may come from records or via a PRA.
Number of livestock shall be assumed to be constant in the baseline. Where
sampling takes place sampling must result in a precision of equal or less
than 15% of the mean at the 95% confidence interval
Every five years since the year of initial verification. In the baseline, the
number of livestock shall assumed to be constant for the baseline period.
Comments:
Data / Parameter:
WL,t
Data unit:
Used in equations:
Description:
kg head-1
Source of data:
Measurement
procedures (if any):
Monitoring frequency:
Average weight of livestock type L, at time t
Field measurements, written documentation, or data from peer reviewed
scientific literature relavent to the project area (eg similar environmental
and grazing conditions).
Where field measurements are used, average weight of livestock by type
may come from records or via direct measurements. Where sampling takes
place, sampling must result in a precision of equal or less than 15% of the
mean at the 95% confidence interval.
Every five years since the year of initial verification. In the baseline, the
weight of each livestock type shall assumed to be constant for the baseline
period.
Comments:
Data / Parameter:
HL,I,t
Data unit:
Used in equations:
Hours
Description:
Source of data:
Average number of hours per year an individual of livestock type L is located
within stratum i at time t; hours
Field sampling
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 122
July 2012
Measurement
procedures (if any):
Monitoring frequency:
Shall be based on direct measurement and monitoring. Shall be based on a
sum of hours a livestock animal spent each month of the year within
stratum i. The estimate of hours within stratum i may be based on
estimates of average number of hours livestock spent within stratum per
day, average number of days livestock spent within stratum for a given
month. Sampling must result in a precision of equal or less than 15% of the
mean at the 95% confidence interval.
Where HL,I,baseline > HLi,,t in the project case, it must be conservatively assumed
that HL,i,t = HL,i,baseline
Every five years since the year of initial verification. In the baseline, the
average grazing hours shall assumed to be constant for the baseline period.
Comments:
60
61
62
63
IPCC Default tables
Table 7 IPCC 2006, Chapter 10, Table 10.10, providing default values for EFCH4,enteric,L
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 123
July 2012
64
65
66
Table 8 IPCC 2006, Chapter 10, Table 10.19, providing default values for NexL
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 124
July 2012
67
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 125
July 2012
1
2
Tool: Leakage emissions from CH4 and N2O emissions as result of grazing
animals
3
4
5
6
Source
7
Parameters
Tool is based on 2006 IPCC Guidelines for Natural Greenhouse Gas Inventories32 and “Tool: Grazing GHG
Emissions: CH4 emissions due to enteric fermentation and N2O from manure and urine deposited on
grassland soils”.
Parameter
SI Unit
Description
LK CH 4, enteric,t
t CO2-e
Leakage emissions from CH4 emission as a result of enteric
fermentation, in year t
LKCH 4, enteric, t
t CO2-e
Total leakage CH4 emission as a result of enteric fermentation, at
year t; at year t
LK N2Ograzing,t
t CO2-e
N2O emissions as a result of manure and urine deposited on
grassland soil during grazing, in year t
LKN 2Ograzing, t
t CO2-e
Total leakage from direct N2O emissions as a result of manure and
urine deposition, at year t; at year t
8
9
Methods
10
11
12
Hours of Grazing outside Project Boundary
As a result of project activities, the amount of grazing taking place outside the project boundary may
change, thus potentially increasing methane and nitrous oxide emissions outside the project boundary.
13
14
However, additionally, as result of project activities, the population of livestock may decrease because
animals are sold or slaughtered.
15
16
If the average population of a livestock type in the baseline (LPL,BASELINE ) is greater than in the project
scenario (LPL,t) then the population of livestock that is either sold to entities not involved in the project
32
http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 126
July 2012
17
18
19
activities or slaughtered may be estimated. The number hours of ‘livestock hours’ this equates to is then
estimated based on the population and the average number of hours per year spent by that livestock
type in the baseline scenario (HL,i,BSL).
20
H LP , L ,t   LPL ,i ,t * H L ,i ,t
M
(115)
i 1
21
M
22
H Sold , L ,t   LPL ,i , Sold * H L ,i , BSL
(116)
i 1
23
where:
HLP,L,t
Total number hours livestock type L spent within project boundary, in year t; hours
LPL,I,t
Population of livestock type L in stratum i , in year t; head of livestock
HL,t
Total number of hours per year livestock type L located within stratum i at time t;
hours
HSOLD,L,t
Estimated number of hours livestock of type L that have been sold or slaughtered
that would have grazed within the project boundary in each year since the start of
the project; hours
HL,i,BSL
Total number of hours per year individual of livestock type L is located within
stratum i in each year in the baseline scenario; hours
LPL,i,sold
Population of livestock type L in stratum i, sold or slaughtered at a result of project
activities; head of livestock
L
I
T
1, 2, 3, … L livestock types
1,2,3, …M stratum within project boundary
1, 2, 3, …t years elapsed since the start of the project activity
24
25
26
The number of hours of grazing that are assumed to be occurring outside the project boundary as a
result of the project is then estimated as:
27
H LK , L ,t  H L , BSL  H Sold, L ,t  H LP , L ,t
(117)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 127
July 2012
28
where:
HLK,L,t
Total livestock grazing assumed to occur outside project boundary as a result of the
project for livestock type L, in year t; hours
HL,BSL
Total hours per year livestock type L located inside project boundary each year in the
baseline scenario at time t; hours
HSOLD,L,t
Estimated number of hours of livestock type L that have been sold or slaughtered
that would have grazed within the project boundary in each year since the start of
the project; hours
HLP,L,t
Total number hours livestock type L spent within project boundary, in year t; hours
L
I
T
1, 2, 3, … L livestock types
1,2,3, …M stratum within project boundary
1, 2, 3, …t years elapsed since the start of the project activity
29
30
31
32
Leakage methane emissions from enteric fermentation
Leakage from methane emissions from enteric fermentation is based on the number of hours each
livestock type is assumed to be grazing outside the project boundary as a result of the project.
33
Methane emissions from enteric fermentation are calculated as:
t*
34
LK CH 4 , enteric   LK CH 4 , enteric,t
(118)
t 1
L
35
LKCH 4 , enteric, t  GWPCH 4 *  EFCH 4, L * LPLK , L _ adj,t  1000
(119)
L 1
36
37
LPLK , L _ adj,it 
H LK , L,t
Hours t
(120)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 128
July 2012
38
where:
LKCH 4, enteric, t
Total leakage CH4 emission as a result of enteric fermentation, at year t; t CO2e
LKCH 4 , enteric, t
Leakage emission from CH4 as a result of enteric fermentation, in year t; t CO2e
GWPCH4
EFCH4,enteric,L
Global Warming Potential of CH4; kg CO2 kg CH4-1
Emission Factor due to enteric fermentation per head of livestock type L per year; kg
CH4 head-1 year-1
LPLKL_adj,t
Adjusted population of livestock type L grazing outside project boundary as result of
project, in year t; head of livestock
HLK,L,t
Total livestock grazing assumed to occur outside project boundary as a result of the
project for livestock type L, in year t; hours
Hourst
Total number of hours in the year t
L
I
T
1, 2, 3, … L livestock types
1,2,3, …M stratum within project boundary
1, 2, 3, … years elapsed since the start of the project activity
39
40
41
42
Leakage nitrous oxide emissions from manure and urine deposition
Both direct and indirect emissions from manure and urine deposited on the soil during grazing are
accounted for.
t*
43
LK N 2Ograzing,t   LK N 2Ograzing,t
44
LK N 2Ograzing,t  LK N 2OLK , grazing,indirect,t  LK N 2Ograzing, direct,t
t 1
(121)
(122)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 129
July 2012
45
where:
LKN 2Ograzing, t
Leakage emissions in total N2O emissions as a result of manure and urine deposition,
at year t; t CO2e
LK N 2Ograzing, t
Total leakage from N2O emissions as a result of manure and urine deposition, at year
t; t CO2e
LK N 2Ograzing, indirect, t
Total leakage from indirect N2O emissions as a result of manure and urine
deposition, at year t; t CO2e
LK N 2Ograzing, direct, t
Total leakage from direct N2O emissions as a result of manure and urine deposition,
at year t; t CO2e
t
1, 2, 3, … years elapsed since the start of the project activity
46
47
48
49
50
The direct and indirect N2O emissions from manure and urine deposited outside the project boundary is
calculated using methods described in the 2006 IPCC Guidelines for National Greenhouse Gas
Inventories. Values for many parameters listed may be drawn from site or region specific data or where
data are unavailable, IPCC default data. See parameter tables for values.
51
LK N 2Og ra zin g, d irect,t   FPRP, LK , adj, L ,t * EF3 PRP, L *
L
L 1
L
44
* GWPN 2O
28
52
LK N 2Ograzing,indirect,t   FLK , PRP, adj, L ,t * FracGASM , L * EF4 *
53
FLK , PRP, adj, L,t  H LK , L,t *WL *
L 1
44
* GWPN 2O
28
Nex L
*1000 * 1  Frac GASM , L 
(1000 * 24)
(123)
(124)
(125)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 130
July 2012
54
where:
LK N 2Ograzing, direct, t
Total leakage from direct N2O emissions as a result of manure and urine deposition,
at year t; t CO2e
LK N 2Ograzing, indirect, t
Total leakage from indirect N2O emissions as a result of manure and urine
deposition, at year t; t CO2e
FLK,PRP,adj,L,t
Annual amount of urine and dung N deposited by grazing animals outside of project
boundary soils during grazing as a result of the project, by livestock L, in year t;
adjusted for volatilization as NH3 and NOx; t N
EF3PRP,L
Emission factor for N2O from urine and dung N deposited by livestock type L; kg N2ON (kg N input)-1
EF4
Emission factor for N2O for atmospheric deposition of manure N on soils and water
surfaces; kg N2O-N (kg N input)-1
GWPN2O
Global Warming Potential of N2O; kg CO2 kg N2O-1
HLK,L,t
Total livestock grazing assumed to occur outside project boundary as a result of the
project for livestock type L, in year t; hours
WL
Average weight of livestock type L at time t; kg head-1
NexL
FRACGASM,L
Nitrogen excretion; kg 1000 kg-1 animal mass day-1
Fraction of volatilization from dung and urine deposited by grazing animals as NH3
and NOx; kg N volatilized (kg of N deposited)-1
l
t
1, 2, 3, … L livestock types
1, 2, 3, …t years elapsed since the start of the project activity
55
56
57
Parameter Tables
58
Data and parameters not monitored
Data / Parameter:
GWPCH4
Data unit:
kg CO2 / kg CH4
Used in equations:
Description:
Global Warming Potential of CH4
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 131
July 2012
Source of data:
IPCC Second Assessment report
Comments:
IPCC Second Assessment report lists as: GWPCH4=21
Data / Parameter:
EFCH4,enteric,L
Data unit:
kg CH4 head-1 year-1
Used in equations:
Description:
Emission Factor from enteric emissions per head of livestock type L per year
Comments:
Country or site specific data. Where specific data is not available, may use IPCC
2006 default values from tables 10.10 and 10.11
See section below for IPCC values
Data / Parameter:
EF3PRP,L
Data unit:
Used in equations:
kg N2O–N (kg N)-1
Source of data:
Description:
Emission factor for N2O from urine and dung N deposited by live stock type L
on project boundary soils
Source of data:
Country or site specific data. Where specific data is not available, may use IPCC
2006 default values from tables 11.1. EF3PRP,CPP should be used for cattle (dairy,
non-dairy, and buffalo), poultry and pigs. EF3PRP,SO should be used for sheep and
other animals.
Comments:
IPCC 2006 values: EF3PRP,CPP = 0.02 EF3PRP,SO = 0.01
Data / Parameter:
EF4
Data unit:
kg N2O-N (kg N input)-1
Used in equations:
Description:
Emmision factor for N2O for atmospheric deposition of manure N on soils and
water surfaces within the project boundary
Source of data:
Country or site specific data. Where specific data is not available, may use IPCC
2006 default values from tables 11.3
Comments:
IPCC 2006 EF4 = 0.010
Data / Parameter:
GWPN2O
Data unit:
kg CO2 kg N2O-1
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 132
July 2012
Used in equations:
Description:
Global Warming Potential of N2O
Source of data:
IPCC Second Assessment Report
Comments:
IPCC Second Assessment report lists as: GWPN2O=310
Data / Parameter:
NexL
Data unit:
kg 1000 kg-1 animal mass day-1
Used in equations:
Description:
Comments:
Nitrogen excretion
Country or site specific data. Where specific data is not available, may use IPCC
2006 default values from tables 10.19
See IPCC 2006 tables below
Data / Parameter:
FRACGASM,L
Data unit:
kg N volatilized (kg of N deposited)-1
Source of data:
Used in equations:
Description:
Fraction of volatilization from dung and urine deposited by grazing animals as
NH3 and NOx
Source of data:
Country or site specific data. Where specific data is not available, may use IPCC
2006 default values from table 11.3
Comments:
IPCC 2006 value: FRACGASM=0.20
Data / Parameter:
Hourst
Data unit:
Hours
Used in equations:
Description:
Source of data:
Measurement
procedures (if any):
Monitoring
frequency:
Comments:
59
Total number of hours in year t
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 133
July 2012
60
Data and parameters from other Tools:
Data / Parameter:
LPL,i,t
Data unit:
Used in equations:
Description:
Head livestock
Source of data:
Population of livestock of livestock type L in stratum i, at time t
Tool Grazing GHG Emissions: CH4 emissions due to enteric fermentation and
N2O from manure and urine deposited on grassland soils
Measurement
procedures (if any):
Monitoring frequency:
Comments:
Data / Parameter:
WL,t
Data unit:
kg head-1
Used in equations:
Description:
Average weight of livestock type L, at time t
Source of data:
Tool Grazing GHG Emissions: CH4 emissions due to enteric fermentation and
N2O from manure and urine deposited on grassland soils
Measurement
procedures (if any):
Monitoring frequency:
Comments:
Data / Parameter:
HL,I,t
Data unit:
Used in equations:
Hours
Description:
Source of data:
Average number of hours per year livestock type L located within stratum i
at time t; hours
Tool Grazing GHG Emissions: CH4 emissions due to enteric fermentation and
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 134
July 2012
N2O from manure and urine deposited on grassland soils
Measurement
procedures (if any):
Monitoring frequency:
Comments:
61
62
Data and parameters monitored:
Data / Parameter:
LPL,i,sold
Data unit:
Used in equations:
Head livestock
Description:
Source of data:
Population of livestock type L in stratum i, sold or slaughtered at a result of
project activities; head of livestock
Field measurements or documentation
Measurement
procedures (if any):
Population of livestock by type may come from records or via a PRA.
Monitoring frequency:
Comments:
63
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 135
July 2012
64
65
66
IPCC Default tables
Table 9 IPCC 2006, Chapter 10, Table 10.10, providing default values for EFCH4,enteric,L
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 136
July 2012
67
68
69
Table 10 IPCC 2006, Chapter 10, Table 10.19, providing default values for NexL
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 137
July 2012
70
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 138
July 2012
2
Annex B - Guidance on Estimating biomass in living trees at the start of the
project activity
3
4
5
The below text provides guidance on methods that may be used to estimate the biomass of living trees
prior to the initiation of project activities. Such information may then be used to estimate what changes
in tree biomass would have taken place in the baseline scenario.
6
Carbon stock in living trees in strata i at the start of the project activity is calculated as follows:
7
CTREE _ BSL,i  BTREE _ BSL,i * CFTREE _ BSL
8
where:
1
9
(126)
CTREE _ BSL,i
Above and belowground carbon stock in living trees in the baseline at the start of
the project activity in strata i; t C
BTREE _ BSL,i
Biomass of living trees in the baseline at the start of the project in strata i; t dry
matter (d.m.)
CFTREE _ BSL
Carbon fraction of dry matter for living tree biomass in baseline; t C t-1 d.m.
The biomass of living trees in the baseline at the start of the project activity in each stratum ( BTREE _ BSL,i
10
11
) is estimated using any one of the following methods (a, b, or c):
12
Method a. Estimation based on existing data
13
14
15
16
If published data is available from which biomass content per unit area for the project area can be
estimated, the data may be used provided that the estimated value of biomass content per unit area
does not underestimate biomass in the project area. In this case, the biomass of living trees in the
baseline at the start of the project activity is calculated as:
17
BTREE _ BSL,i  BDTREE _ BSL,i * ATREE _ BSL,i
(127)
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 139
July 2012
18
where:
BTREE _ BSL,i
Above and belowground biomass of living trees in the baseline at the start of the
project activity in strata i; t d.m.
BDTREE _ BSL,i
Above and belowground tree biomass content per unit area of strata i (obtained
from published literature); t d.m. ha-1
ATREE _ BSL,i
Area of land within the project boundary in strata i where living trees are standing
at the start of the project activity; ha
19
20
Method b. Complete inventory of trees
21
22
23
24
25
If the trees in the baseline are few and scattered out, all the trees may be inventoried and dimensional
measurements (such as diameter or height or both) may be carried out on them. Follow one of
methods described in the Tool: Estimation of carbon stocks and change in carbon stocks of trees to
estimate the biomass of each tree. Biomass of living trees in the baseline at the start of the project is
then calculated as:
26
BTREE _ BSL,i   BTREE ,k
n
(128)
k 1
27
where:
BTREE _ BSL,i
Above and belowground biomass of living trees in the baseline at the start of the
project activity in strata i; t d.m.
BTREE,k
biomass of the kth tree as estimated from dimensional measurements; t d.m.
N
Total number of living trees in the baseline at start of the project activity
28
29
Method c. Inventory of trees in sample plots
30
31
32
33
34
If the number of trees in the baseline scenario is too large for a complete inventory to be carried out,
sample plots are laid out and dimensional measurements are carried out on the trees in these sample
plots. Follow one of methods described in Tool: Estimation of carbon stocks and change in carbon
stocks of trees to estimate the biomass of each tree. The biomass of living trees in the baseline at the
start of the project activity is then calculated as:
PS-AFOLU - F-V Methodology: Revegetation of Degraded Lands 140
July 2012
35
 Ai
BTREE _ BSL,i   
i  APLOT ,i
36
where:
BTREE _ BSL,i
Ai
APLOT ,i
BTREE ,i , p
i
37

B
p TREE,i, p 

(129)
Biomass of living trees in the baseline at the start of the project activity in strata i; t
d.m.
Area of baseline stratum i within the project boundary at start of the project activity;
ha
Area of sample plots in baseline stratum i where dimensional measurements are
carried out on the trees; ha
Biomass of living trees in plot p of baseline stratum i as estimated from dimensional
measurements; t d.m.
1, 2, 3, … Baseline strata