ࡱ> tVlj h q` 0-= bjbjqPqP  ::r%000|$ *Y^ 4.DDLе(TTTTTTT$[h<^:CT$$$CT^^DDDX$x.^DDT$TcT$vDR s+Rt\uX0*YuJ v^p'v^$^v^$NF R CTCTd$$$*Y$$$$$$5Y/$Y^^^^^ Approved afforestation and reforestation baseline and monitoring methodology AR-AM0004 Reforestation or afforestation of land currently under agricultural use (Version 04) Source This methodology is based on the draft CDM-AR-PDD Reforestation around Pico Bonito National Park, Honduras, whose baseline study, monitoring and verification plan and project design document were prepared by the Fundacin Parque Nacional de Pico Bonito (FUPNAPIB), Ecologic Development Fund, Winrock International, USAID MIRA and the World Bank (BioCarbon Fund). For more information regarding the proposal and its consideration by the Executive Board please refer to case ARNM0019: Reforestation around Pico Bonito National Park, Honduras on < HYPERLINK "http://cdm.unfccc.int/methodologies/ARmethodologies/approved_ar.html" http://cdm.unfccc.int/methodologies/ARmethodologies/approved_ar.html>. Section I. Summary and applicability of the baseline and monitoring methodologies Selected baseline approach from paragraph 22 of the CDM A/R modalities and procedures Existing or historical, as applicable, changes in carbon stocks in the carbon pools within the project boundary. Applicability This methodology is applicable to the following project activities: Afforestation or reforestation of degraded land, which is subject to further degradation or remains in a low carbon steady state, through assisted natural regeneration, tree planting, or control of pre-project grazing and fuel-wood collection activities (including in-site charcoal production); The project activity can lead to a shift of pre-project activities outside the project boundary, e.g. a displacement of agriculture, grazing and/or fuel-wood collection activities, including charcoal production. The conditions under which the methodology is applicable are: Lands to be afforested or reforested are degraded and the lands are still degrading or remain in a low carbon steady state; Site preparation does not cause significant longer-term net decreases of soil carbon stocks or increases of non-CO2 emissions from soil; Carbon stocks in soil organic carbon, litter and dead wood can be expected to further decrease due to soil erosion and human intervention or increase less in the absence of the project activity, relative to the project scenario; Flooding irrigation is not permitted; Soil drainage and disturbance are insignificant, so that non CO2-greenhouse gas emissions from these types of activities can be neglected; The A/R CDM project activity is implemented on land where there are no other on-going or planned A/R activities (no afforestation/reforestation in the baseline). Selected carbon pools Table A: Selected carbon pools Carbon PoolsSelected Justification / ExplanationAbove-groundYesMajor carbon pool subjected to the project activityBelow-groundYesMajor carbon pool subjected to the project activityDead woodNoConservative approach under applicability conditionLitterNoConservative approach under applicability conditionSoil organic carbonNoConservative approach under applicability conditionSection II. Baseline methodology description Project boundary The project boundary geographically delineates the afforestation or reforestation project activity under the control of the project participants. The A/R CDM project activity may contain more than one discrete area of land. Each discrete area of land shall have a unique geographical identification. It shall be demonstrated that each discrete area of land to be included in the boundary is eligible for an A/R CDM project activity. PPs shall apply the latest version of the tool Procedures to demonstrate the eligibility of lands for afforestation and reforestation CDM project activities as approved by the Executive Board. The latest version of Guidance on the application of the definition of project boundary to A/RCDM project activities (available at: < HYPERLINK "http://cdm.unfccc.int/Reference/Guidclarif/index.html" http://cdm.unfccc.int/Reference/Guidclarif>) may be applied in identification of areas of land planned for an A/R CDM project activity. The project boundary includes emissions sources and gases as listed in Table B. Table B: Gases considered from emissions by sources other than resulting from changes in carbon pools SourcesGasIncluded/ excludedJustification / ExplanationBurning of biomassCO2NoHowever, carbon stock decreases due to burning are accounted as a carbon stock change CH4YesNon-CO2 gas emitted from biomass burningN2ONoPotential emission is negligibly smallEligibility of land This methodology uses the latest version of the mandatory tool: Procedures to define the eligibility of lands for afforestation and reforestation project activities approved by the CDM Executive Board to demonstrate land eligibility within the project boundary. Ex ante stratification If the project activity area is not homogeneous, stratification should be carried out to improve the accuracy and the precision of biomass estimates. Different stratifications may be required for the baseline and project scenarios in order to achieve optimal accuracy of the estimates of net GHG removal by sinks. For estimation of baseline net GHG removals by sinks, or estimation of actual net GHG removals by sinks, strata should be defined on the basis of parameters that are key entry variables in any method (e.g., growth models or yield curves/tables) used to estimate changes in biomass stocks: For baseline net GHG removals by sinks. It will usually be sufficient to stratify according to area of major vegetation types because baseline removals for degraded (or degrading) land are expected to be small in comparison to project removals; For actual net GHG removals by sinks. The ex ante estimations shall be based on the project planting/management plan. The ex post stratification shall be based on the actual implementation of the project planting/management plan. The expost stratification may be affected by natural or anthropogenic impacts if they are able to add variability to growth pattern in the project area, e.g., local fires (see SectionIII.2). Further subdivision of the project strata to represent spatial variation in the distribution of the baseline or the project biomass stocks/removals is not usually warranted. However, factors impacting growth (e.g., soil type) might be useful for ex post stratification if their variability in the project area is large. For ex ante and ex post stratification, PPs may optionally make use of remote sensing data acquired close to the time the project commences and/or close to the time of occurrence of natural or anthropogenic impacts if such impacts add variability to growth pattern in the project area. Note: In the equations used in this methodology, the letter i is used to represent a stratum and the letter m for the total number of strata. Procedure for selection of most plausible baseline scenario The baseline scenario is determined by the following steps: Step 1: Demonstrate that the proposed A/R CDM project activity meets the conditions under which the proposed methodology is applicable, and that baseline approach 22(a) can be used. Step 2: Define the project boundary as described in Section II.2 above. Step 3: Analyze historical land use, local and sectoral land-use policies or regulations and land use alternatives. Analyse the historical and existing land-use/land-cover changes in the context of the socio-economic conditions prevailing within the boundary of the proposed A/R CDM project activity and identify key factors that influence the land-use/land-cover changes over time, using multiple sources of data including archives, maps or satellite images of land use/cover data prepared before 31.12.1989 (reforestation) or at least 50 years old (afforestation) and before the start of the proposed A/R CDM project activity, supplementary field investigation, land-owner interviews, as well as studies and data collected from other sources; Show that historical and current land-use/land-cover change has led to progressive degradation of the land over time including a decrease or steady state at a reduced level of the carbon stocks in the carbon pools. Provide indicators of land degradation and carbon stock decrease/steady state that can be verified and sustain the choice of these indicators using appropriate and credible sources of information, such as scientific literature and studies or data collected in the project area or similar areas; The historical degradation feature can be indicated by: Vegetation degradation. For example: The land was forest at time points in the past and non-forest at more recent time points; There was a forest at time points in the past, but attempts to re-establish the forest through seeding have failed; There was higher crown cover of non-tree vegetation at time points in the past and lower crown cover at more recent time points. Soil degradation. For example: Lower soil erosion at time points in the past than in more recent time points; Higher soil organic matter content at time points in the past than in more recent time points; Less desertification at time points in the past than in more recent time points. These indicators do not represent all cases of land degradation but are appropriate for the proposed methodology. Other indicators may be used. Identify and briefly describe national, local and sectoral land-use policies or regulations adopted before 11 November 2001 that may influence land-use/land-cover change and demonstrate that they do not influence the areas of the proposed A/R CDM project activity (e.g., because the policy does not target this area, or because there are barriers to the policy implementation in this area, etc). If the policies (implemented before 11November2001) significantly impact the project area, then the baseline scenario cannot be degraded land and this methodology cannot be used any further; Identify alternative land uses including alternative future public or private activities on the degraded lands including any similar A/R activity or any other feasible land development activities, that are not in contradiction with the identified local, national and/or sectoral land-use policies and regulations and that could be implemented within the boundary of the proposed A/R CDM project activity. In doing so, use land records, field surveys, data and feedback from stakeholders, and other appropriate sources; Demonstrate that land-use/land-cover within the boundary of the proposed A/R CDM project activity would not change and/or lead to further degradation and carbon stock decrease in absence of the proposed project activity, e.g., by assessing the relative attractiveness of alternative land uses in terms of benefits to the local economy and communities subsistence, consulting with stakeholders for existing and future land use, and identifying barriers for alternative land uses. If the analyses above indicate for the baseline land use that the land area within the boundary of the proposed A/R CDM project activity is likely to change its current status (i.e. degraded and/or subject to further degradation), then this methodology is not applicable. However, if the analysis shows that a change can only occur as a result of the implementation of the proposed A/R CDM activity, continue with the next step. Step 4: Stratify the A/R CDM project area as explained in Section II.3 above. Step 5: Determine the baseline land-use/land-cover scenario for each stratum. Analyse the possibility of self-encroachment of trees under the current conditions by, e.g.: Survey and identification of trees growing on site; Identification of on-site or external seed pools/sources that may result in natural regeneration; Identification of the possibility of seed sprout and growth into trees with the potential height, crown cover and area crossing the threshold values used in the national definition of forest, under the current conditions. If no, or only sparse, natural regeneration with no potential to become a forest can be identified, continue with Section II. REF _Ref138324845 \r \h  \* MERGEFORMAT  5 below. Otherwise, the proposed A/R CDM project activity is not different from the baseline scenario. Estimation of baseline net GHG removals by sinks Baseline strata without trees or woody perennials The baseline net greenhouse gas removals by sinks is the sum of the changes in carbon stocks in the carbon pools within the project boundary that would have occurred in the absence of an A/R CDM project activity. As per the conditions under which the proposed methodology is applicable (described in Section I. REF _Ref138258060 \r \h  \* MERGEFORMAT  2), lands to be afforested or reforested are degraded lands, either abandoned or subjected to pre-project grazing activity or agricultural crop activity, with vegetation having area, crown cover and tree high values below the thresholds used in the national definition of forest, and the lands are still degrading or remaining in a low carbon steady state. For this reason, in all baseline strata where: No growing trees or woody perennials exist; and No trees or other woody perennials will start to grow at any time during the crediting period; or No trees or other woody perennials will reach the threshold for the national definition of forest due to ongoing cutting and burning cycles that are part of shifting cultivation systems; The baseline net greenhouse gas removals by sinks are expected to be negative due to ongoing degradation. For these strata the methodology conservatively assumes that baseline net greenhouse gas removals by sinks is zero: CBSL = 0 for all t* d" tcp ( AUTONUMLGL \e ) where: CBSLBaseline net greenhouse gas removals by sinks; t CO2-et*Number of years elapsed since the start of the A/R project activity; yrtcpYear at which the first crediting period ends; yrThis baseline methodology accounts for above-ground and below-ground biomass only. Therefore, for all strata that do not satisfy the conditions listed above, the baseline net greenhouse gas removals by sinks can be calculated by: CBSL = CB,LB ( AUTONUMLGL \e ) where: CBSLBaseline net greenhouse gas removals by sinks; t CO2-e CBLB Baseline sum of the changes in living biomass carbon stocks (above- and below-ground); tCO2-e Note: Following the guidance contained in paragraph 35 in the report of the EB 42 meeting the living biomass does not contain the biomass of herbaceous vegetation. Note: In this methodology equation 2 is used to estimate baseline net greenhouse gas removals by sinks for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which baseline net greenhouse gas removals by sinks are estimated. Estimation of CBLB (changes in living biomass carbon stocks in the baseline)  EMBED Equation.3  ( AUTONUMLGL \e ) where: CBLB Baseline sum of the changes in living biomass carbon stocks (above- and below-ground); tCO2-e CB,ikt Baseline annual carbon stock change in living biomass for stratum i, stand model k, timet; t CO2-e. yr-1i1, 2, 3, mBL baseline stratak1, 2, 3, K stand modelt1, 2, 3, t* years elapsed since the start of the A/R CDM project activityTo be symmetric, equation 3 will be used for both the baseline and the actual net GHG removals by sinks, the subscript k referencing stand model is included. Stand model is the term used for stratum within the project. For the ex ante baseline estimation k = 0. For those strata without growing trees, or with trees and non-tree vegetation as part of an agricultural cycle that are not accumulating carbon due to the predictable cutting and burning, "CB,ikt = 0. For those strata with a few growing trees, "CB,ikt is estimated using one of following two methods that can be chosen based on the availability of data. Method 1 (Carbon gain-loss method)  EMBED Equation.3  ( AUTONUMLGL \e ) where: "Cikt Annual carbon stock change in living biomass for stratum i, for stand modelk, timet; tCO2-e yr-1"CG,ikt Annual increase in carbon stock due to biomass growth for stratumi, for stand modelk, time t; t CO2-e yr-1"CL,ikt Annual decrease in carbon stock due to biomass loss for stratum i, for stand modelk, timet; t CO2-e yr-1 Note: This methodology conservatively assumes that "CL,ikt = 0 for the baseline scenario.  EMBED Equation.3  ( AUTONUMLGL \e ) where: "CG,ikt Annual increase in carbon stock due to biomass growth for stratum i, for stand modelk, timet; t CO2-e. yr-1Aijt Area of stratum i, for stand model k, at time t; hectare (ha)CTOTAL,ikt Annual average increment rate in total biomass in units of dry matter for stratumi for stand model k, time t; t d.m. ha-1 yr-1 Note: The area of a stratum i planted with species j has a time notation because depending on baseline land-use/land-cover projections stand models k may appear at different dates within the same stratum. As well, GTOTALikt can be estimated as a constant annual average value. The baseline net greenhouse gas removals by sinks can be calculated by:  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: CTOTAL,ikt Annual average increment rate in total biomass for stratum i for stand modelk, timet; td.m. ha-1 yr-1 Gw,ijt Average annual above-ground biomass increment for stratum i, speciesj, at timet; td.m.ha-1 yr-1Rj Root-shoot ratio appropriate to increments for species j; dimensionlessCFjThe carbon fraction for species j; t C (t d.m.)-1Iv,ijt Average annual increment in merchantable volume for stratum i, species j; m3 ha-1 yr-1Dj Basic wood density for species j; t d.m. m-3BEF1,j Biomass expansion factor for conversion of annual net increment (including bark) in merchantable volume to total above-ground biomass increment for species j; dimensionlessNote: GTOTALikt can be estimated as a constant annual average value; Care should be taken that the root-shoot ratio may change as a function of the above-ground biomass present at time (t) (see IPCC GPG, 2003, Annex 3.A1, Table 3A1.8); Ivijt is estimated as current annual increment CAI. The mean annual increment MAI in the forestry jargon can only be used if its use leads to conservative estimates. Method 2 (stock change method)  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \* Arabic \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: "Cikt Annual carbon stock change in living biomass for stratum i, for stand modelk, timet; tCO2-e. yr-1Cikt Carbon stock in living biomass for stratum i, stand model k, time t; t CCikt2 Total carbon stock in living biomass for stratum i, species j, calculated at time t=t2; t CCikt1 Total carbon stock in living biomass for stratum i, species j, calculated at time t=t1; t CT Number of years between times t2 and t1 (T = t2 - t1)AiktArea of stratum i, for stand model k, at time t; hectare (ha)CAB,ijtCarbon stock in above-ground biomass for stratum i, species j, at time t; t CCBB,ijt Carbon stock in below-ground biomass for stratum i, species j, at time t; t CVijt Average merchantable volume of stratum i, species j, at time t; m3 ha-1Dj Basic wood density of species j; t d.m. m-3 merchantable volumeBEF2,j Biomass expansion factor for conversion of merchantable volume to above-ground tree biomass for species j; dimensionlessRj Root-shoot ratio for species j; dimensionlessNote: Stratification criteria shall include age classes so that Vijt should have low variances within stratumi, speciesj and timet. An alternative way of estimating CAB,ijt is to use allometric equations which are also considered to be good practice by the IPCC.  EMBED Equation.3  ( AUTONUMLGL \e ) where: CAB,ijtCarbon stock in above-ground biomass for stratum i, species j, at timet; t CAiktArea of stratum i, stand model k, at time t; hectare (ha)nTRijtNumber of trees in stratum i, species j, at time t; dimensionless ha-1CFjCarbon fraction for species j, t C (t d.m.)-1fi(DBHt,Ht)Allometric equation linking above-ground biomass of living trees (d.m. ha-1) to mean diameter at breast height (DBH) and possibly mean tree height (H) for speciesj; dimensionlessNote: Mean DBH and H values should be estimated for stratumi, speciesj, at timet using a growth model or yield table that gives the expected tree dimensions as a function of tree age. The allometric relationship between above-ground biomass and DBH and possibly H is a function of the species considered. To be conservative, this methodology does not account for living biomass losses due to harvesting and mortality in the baseline scenario and does account for them in the project scenario. Therefore when using method 2 for the baseline (and make its use consistent with the assumption "CL,ij = 0 made in equation 4 of method 1), Vijt shall not consider volume reductions due to harvesting and mortality. For the choice of methods there is no priority, and it will mainly depend on the kind of parameters available. Vijt and Iv,itj shall be estimated based on number of trees and national/local growth curve/table that is usually covered by national/local forestry inventory. Dj, BEF1,j, BEF2,j, CFj and Rj are regional and species specific and shall be chosen with priority from higher to lower order as follows: Existing local and species specific; National and species specific (e.g. from national GHG inventory); Species specific from neighboring countries with similar conditions. Sometimes (c) might be preferable to (b); this case shall be substantiated in the PDD; Globally species specific (e.g. GPG-LULUCF). If none of the above works, then start again from a), but replace species specific with similar species (e.g., shape of trees, broadleaved vs. deciduous etc). When choosing from global or national databases because local data are limited, it shall be confirmed with any available local data that the chosen values for the baseline are not a significant underestimate of the baseline net removals by sinks, as far as can be judged. Local data used for confirmation may be drawn from the literature and local forestry inventory. Additionality This methodology uses the latest version of the Tool for the demonstration and assessment of additionality in afforestation and reforestation CDM project activities approved by the CDMExecutive Board. Ex ante actual net GHG removal by sinks The actual net greenhouse gas removals by sinks represent the sum of the verifiable changes in carbon stocks in the carbon pools within the project boundary, minus the increase in greenhouse emissions by sources measured in CO2 equivalents within the project boundary that are a result of the implementation of an A/R CDM project activity. Therefore, CACTUAL = CP,LB - GHGE ( AUTONUMLGL \e ) where: CACTUAL Actual net greenhouse gas removals by sinks; t CO2-eCP,LB Sum of the changes in living biomass carbon stocks (above- and below-ground); tCO2eGHGE Sum of the increases in GHG emissions by sources within the project boundary as a result of the implementation of an A/R CDM project activity; t CO2-eNote: This methodology equation 13 is used to estimate actual net greenhouse gas removals by sinks for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated. Estimation of actual CP,LB (changes in living biomass carbon stocks in the project scenario) In general, the changes in living biomass stocks in the project can be given by:  EMBED Equation.3  ( AUTONUMLGL \e ) where: CP,LB Sum of the changes in living biomass carbon stocks (above- and below-ground); tCO2-eCP,LB TSum of the changes in living tree biomass carbon stocks (above- and below-ground); tCO2-e EbiomasslossDecrease in the carbon stock in the living biomass carbon pools of non-tree woody vegetation in the year of site preparation, up to time t*; t CO2-eTreatment of pre-existing vegetation Given the conditions under which the proposed methodology is applicable (described in Section I.3), pre-existing carbon stocks in the living biomass are most likely not significant (< 2% of the anticipated actual net GHG removals by sinks). The methodology nevertheless considers the two following possible situations: The carbon stocks in the living biomass of pre-existing non-tree and tree vegetation are not significant: Carbon stock changes in the living biomass of pre-existing non-tree and tree vegetation are not included in the ex ante calculation of actual carbon stock changes, regardless if the pre-existing non-tree and tree vegetation is left standing or is harvested; If the pre-existing vegetation is burned for land preparation before planting, non-CO2 emissions are estimated from the total above-ground biomass (details in Section2 below) and included in the calculation of actual net GHG removal by sinks if they are significant (> 2% of actual net GHG removals by sinks); To be conservative the biomass of the pre-existing vegetation would be set as the maximum biomass over the slash and burn/fallow cycle. The carbon stocks in the living biomass of pre-existing non-tree and tree vegetation are significant. If the carbon stocks in the living biomass of pre-existing vegetation are likely to represent more than 2% of the anticipated actual net GHG removals by sinks, the following methodology procedure is applied: If the baseline is shifting agriculture or another form of agriculture/fallow cycle, a conservative approach of setting the baseline stock to be equal to the maximum stock over the cycle should be used. It is assumed all this stock will disappear in the year of site preparation. The stocks are assumed to be burned: Non-CO2 emissions are calculated from the carbon stock in the above-ground biomass of non-tree and tree vegetation (details in Section 6.2 below); 100% carbon stock loss in the above-ground and below-ground biomass is assumed and estimated using equation 15 for both the non-tree component and the young trees. Otherwise if for land preparation before planting non-tree and tree vegetation is burned (and not harvested) then: Non-CO2 emissions are calculated from the carbon stock in the above-ground biomass of non-tree and tree vegetation (details in Section 7.2.2 below); 100% carbon stock loss in the above-ground and below-ground biomass is assumed and estimated using the methods outlined in equation 16 ff. below for the tree component and equation 15 for the non-tree component. Or, if the tree vegetation is partially or totally harvested before burning then: The carbon stock decrease in the harvested above-ground and below-ground tree biomass is estimated using the methods outlined below; The above-ground biomass of the harvested trees is subtracted from the total above-ground biomass estimate used for the calculation of non-CO2 emissions from burning; Carbon stock changes in the living biomass (above-ground and below-ground) of pre-existing trees that are left standing are not included in the ex ante calculation of actual carbon stock changes. This is a conservative assumption because the trees will continue to grow. Ex post these trees will be measured in the monitoring plots; any change in the carbon stocks in these trees due to growth or mortality will be duly accounted. All existing non-tree vegetation is assumed to disappear in the year of site preparation, to account for slash and burn or future competition from planted trees. This is a conservative assumption because there will be some non-tree vegetation in the project scenario. Some vegetation may re-grow even if all non-tree vegetation is removed during the site preparation (overall site burning). The carbon stock decrease is estimated as follows:  EMBED Equation.3  ( AUTONUMLGL \e ) where: EbiomasslossDecrease in the carbon stock in the living biomass carbon pools of non-tree vegetation in the year of site preparation, up to time t*; t CO2-eAiktArea of stratum i, stand model k, time t; haBpre,iktAverage pre-existing stock non-tree pre-project biomass on land to be planted before the start of a proposed A/R CDM project activity for baseline stratumi, stand modelk, timet; t d.m. ha-1CFpreThe carbon fraction of dry biomass in pre-existing vegetation, t C (t d.m.)-1i1, 2, 3, mBL strata in the baselinek1, 2, 3, KP stand models in the project scenariot1, 2, 3, t* years elapsed since the start of the A/R project activityTreatment of trees For clarification, trees refer to all woody biomass that occurs as a result of the A/R project. The methodology and equations for estimating ex ante actual changes in the living biomass carbon stocks are similar to the ones used for the estimation of baseline changes in the living biomass carbon stocks, with the following main differences: Harvesting and mortality are taken into account; Baseline strata (defined based on pre-existing vegetation, among others) differ for the project implementation (based on type of baseline stratum where activity takes place, stand model and possibly cohorts of the same stand model); Stand models are different as defined in Step 2 of Section II.2.  EMBED Equation.3  ( AUTONUMLGL \e ) where: CP,LB Sum of the changes in living biomass carbon stocks in the project scenario (above- and below-ground); t CO2-e CLB,ikt Annual carbon stock change in living biomass for stratum i, stand modelk, timet; tCO2eyr-1 i1, 2, 3, & mBL strata in the baselinek1, 2, 3, & K stand models in the project scenariot1, 2, 3, & t* years elapsed since the start of the A/R project activityAnnual carbon stock changes in the living biomass (CLB,ikt) are estimated using one of the two methods described in Section II. REF _Ref138324845 \w \h  \* MERGEFORMAT  5. In addition: Method 1 (Carbon gain-loss method) The following equations shall be used to calculate the average annual decrease in carbon stocks due to biomass loss for stratumi, stand modelk and timet ("CL,ikt)  EMBED Equation.3  ( AUTONUMLGL \e ) where: CL,ikt Average annual decrease in carbon stocks due to biomass loss for stratumi, stand modelk, timet; t CO2-e yr-1Lhr,ikt Annual carbon loss due to commercial harvesting for stratum i, stand modelk, timet; tCO2-e yr-1Lfw,ikt Annual carbon loss due to fuel wood gathering for stratum i, species j, time t; CO2-e yr-1Lot,ikt Annual natural losses (mortality) of carbon for stratum i, species j, time t; CO2-e yr-1and:  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: Lhr,ikt Annual carbon loss due to commercial harvesting for stratum i, stand modelk, timet; tCO2-e yr-1Lfw,ikt Annual carbon loss due to fuel wood gathering for stratum i, speciesj, timet; CO2eyr-1Lot,ikt Annual natural losses (mortality) of carbon for stratum i, species j, time t; CO2-e yr-1j1,2,3,J tree speciesHijtAnnually extracted merchantable volume for stratum i, species j, time t; m3 ha-1 yr-1 Dj Wood density for species j; t d.m. m-3 merchantable volumeBEF2,j Biomass expansion factor for converting merchantable volumes of extracted round wood to total above-ground biomass (including bark) for stratum i, speciesj, timet; dimensionlessCFj Carbon fraction of dry matter for species j; t C (t d.m.)-1FGijtAnnual volume of fuel wood harvesting for stratum i, species j, time t; m3 ha-1 yr-1AiktArea of stratum i, stand model k, at time t; hectare (ha)AdistiktForest areas affected by disturbances in stratum i, stand model k, time t; ha yr-1Bw,ijt Average above-ground biomass stock for stratum i, species j, time t; t d.m. ha-1 Mijt% Mortality caused by disturbance in stratum i, species j, time t; dimensionlessNote: The time notation t is given here assuming that in most cases project participants are able to define a harvesting schedule (volumes and years of harvesting as per Step 2 in Section II.2). The use of a constant average annual harvesting volume should be used only under particular circumstances and should be justified in the PDD. This methodology allows for the assumption of no disturbances in the ex ante estimation of actual net GHG removals by sinks, which implies that Adistikt is set as zero and therefore Lot,ikt = 0. This assumption can be made in project circumstances where expected disturbances (e.g. fire, pest and disease outbreaks) are of low frequency and intensity, and therefore difficult to predict. However, the factor Adistikt should be estimated when natural tree mortality due to competition and/or disturbances is likely to cause significant carbon losses. In such cases, Adistikt can be estimated as an average annual percentage of Aikt to express a yearly mortality percentage due to competition (usually between 0% and 2% of Aikt) or disturbances. Method 2 (stock change method) The  stand models as defined in Section II. REF _Ref138757208 \w \h  \* MERGEFORMAT  3, Step 2 shall be developed and presented in the PDD in a way that the values of Vikjt (average merchantable volume of stratum i, speciesj, stand modelk, at timet) used in equation 10 represent the actual average merchantable volume of stratumi, speciesj, stand modelk, at timet after deduction of harvested volumes and mortality:  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: Vikt1 Average merchantable volume of stratum i, stand model k, at time t = t1; m3 ha-1Vikt2 Average merchantable volume of stratum i, stand model k, at time t = t2; m3 ha-1MfikTMortality factor = percentage of Vikt1 died during the period T; dimensionlessIv,ijT Average annual net increment in merchantable volume for stratum i, species j during the period T; m3 ha-1 yr-1HijTAverage annually harvested merchantable volume for stratum i, speciesj, during the periodT; m3 ha-1 yr-1 FGijTAverage annual volume of fuel wood harvested for stratum i, speciesj, during the period T; m3 ha-1 yr-1T Number of years between times t2 and t1 (T = t2 - t1)AdistijT Average annual area affected by disturbances for stratum i, speciesj, during the periodT; ha yr-1AijTAverage annual area for stratum i, species j, during the period T; ha yr-1j1,2,3Jk tree species in stand model kThe choices of methods and parameters shall be used in the same ways as described in Section II. REF _Ref138324845 \w \h  \* MERGEFORMAT  5. Estimation of GHGE (increase in GHG emissions by sources within the project boundary as a result of the implementation of an A/R CDM project activity) An A/R CDM project activity may increase GHG emissions, in particular CO2, CH4 and N2O. The list below contains factors that may be attributable to the increase of GHG emissions: Emissions of greenhouse gases by biomass burning from site preparation (slash and burn activity). The increase in GHG emissions as a result of the implementation of the proposed A/R CDM project activity within the project boundary can be estimated by:  EMBED Equation.3  ( AUTONUMLGL \e ) where: GHGE Increase in GHG emissions as a result of the implementation of the proposed A/RCDM project activity within the project boundary; tCO2eEBiomassBurn Increase in GHG emission as a result of biomass burning within the project boundary; tCO2-eNote: In this methodology equation 23 is used to estimate the increase in GHG emissions for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated. 7.2.1 Estimation of EBiomassBurn (GHG emissions from biomass burning) Slash and burn occurs traditionally in some regions during site preparation before planting and/or replanting, and this practice results in CO2 and non-CO2 emissions. Based on revised IPCC 1996 Guideline for LULUCF, this type of emissions can be estimated (whenever double counting of carbon stock losses is avoided) as follows.  EMBED Equation.3  ( AUTONUMLGL \e ) where: EBiomassBurn Total GHG emission from biomass burning in slash and burn; tCO2eEBiomassBurn,CO2 CO2 emission from biomass burning in slash and burn; t CO2-eEBiomassBurn, CH4 CH4 emission from biomass burning in slash and burn; t CO2-eand:  EMBED Equation.3  ( AUTONUMLGL \e ) where: EBiomassBurn,CO2 CO2 emission from biomass burning in slash and burn; t CO2-eAB,ikt_sb Area of slash and burn for stratum i, stand model k, time t; haBikt Average above-ground biomass stock before burning for stratumi as determined for the respective baseline stratum, stand model k, time t; t d.m. ha-1PBBikt Average proportion of biomass burnt for stratum i, stand modelk, timet; dimensionlessCE Average biomass combustion efficiency (IPCC default = 0.5); dimensionlessCF Carbon fraction (IPCC default = 0.5); t C (t d.m.)-1i 1, 2, 3, SPS strata of the project activityk1, 2, 3, K stand models in the project scenariot1, 2, 3, t* years elapsed since the start of the A/R project activityEmissions of non-CO2 gases are given by:  EMBED Equation.3  ( AUTONUMLGL \e ) where: EBiomassBurn,CO2 CO2 emission from biomass burning in slash and burn; t CO2-eEBiomassBurn, CH4 CH4 emission from biomass burning in slash and burn; t CO2-eERCH4Emission ratio for CH4 (IPCC default value = 0.012); t CO2-e/t CGWPCH4 Global Warming Potential for CH4 (= 21 for the first commitment period); tCO2e./t CH4The combustion efficiencies CE may be chosen from Table 3.A.14 of IPCC GPG-LULUCF. If no appropriate combustion efficiency can be used, the IPCC default of 0.5 should be used. The nitrogen-carbon ratio (N/C ratio) is approximated to be about 0.01. This is a general default value that applies to leaf litter, but lower values would be appropriate for fuels with greater woody content, if data are available. Emission factors for use with above equations are provided in Tables 3.A.15 and 3.A.16 of IPCC GPG-LULUCF. Leakage Leakage (LK) represents the increase in GHGs emissions by sources which occurs outside the boundary of an A/R CDM project activity which is measurable and attributable to the A/R CDM project activity. According to the guidance provided by the Executive Board, leakage also includes the decrease in carbon stocks which occurs outside the boundary of an A/R CDM project activity which is measurable and attributable to the A/R CDM project activity (see EB 22, Annex 15). There are three sources of the leakage covered by this methodology: Carbon stock decreases caused by displacement of pre-project agricultural crops, grazing and fuel-wood collection activities; Carbon stock decreases caused by the increased use of wood posts for fencing.  EMBED Equation.3  ( AUTONUMLGL \e ) Note: In this methodology, equation 27 is used to estimate leakage for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated. Estimation of LKActivityDisplacement (leakage due to activity displacement) The land planned for A/R CDM activities may be subjected to agricultural activities, grazing and fuel-wood collection. Thus, as the result of the project activity, these pre-project activities may be temporarily or permanently displaced from within the project boundary to areas outside the project boundary. The displacement may result in leakage if new agricultural or grazing areas are obtained by converting stocked areas, particularly forests, to new areas for agricultural or grazing activities or if the displaced fuel-wood collection results in degradation or deforestation of forests and devegetation of other lands. For project activities involving grazing, if net livestock is not increased, CO2 emissions resulting from fodder consumption and CH4 emissions from enteric fermentation in displaced domestic livestock do not represent an overall net increase of GHG emissions attributable to the A/R CDM project activity because they would occur in the without project scenario. These sources can be excluded from the leakage calculations. Taking into account the above, leakage due to activity displacement is estimated as follows:  EMBED Equation.3  ( AUTONUMLGL \e ) where: LKActivityDisplacement Leakage due to activity displacement; t CO2-e LKconversionLeakage due to conversion of forest to non-forest; t CO2-eLK fuel-woodLeakage due to the displacement of fuel-wood collection; t CO2-eEstimation of LKconversion (Leakage due to conversion of lands) As a result of the A/R CDM project activity, agricultural activities may be displaced permanently or temporarily outside the project boundary. This activity shifting or activity displacement may result in leakage in the immediate years after the start of the project activity when activities are displaced to areas outside the project boundary. LKconversion occurs in two ways: Conversion for grazing; and Conversion for cropland. Therefore:  EMBED Equation.3  ( AUTONUMLGL \e ) where: LKconv-graz Leakage resulting from the conversion for grazingLKconv-crop Leakage resulting from the conversion for croplandEstimation of LKconv-graz (Leakage due to conversion of land to grazing land) Depending on the specific project circumstances, the entire pre-project animal population, or a fraction of it, may have to be displaced permanently, or temporarily, outside the project boundary. This displacement of animal populations may result in leakage. However, leakage due to conversion of land to grazing land is not attributable to the A/R CDM project activity if the conversion of land to grazing land occurs 5 or more years after the last measure taken to reduce animal populations in the project area. The type and schedule of the measures to be taken to control animal grazing in the project areas should therefore be described in the AR-CDM-PDD and its implementation monitored. Where pre-project grazing activities exist, it is necessary to estimate the pre-project animal population from different livestock groups in the project area. This can be done by interviewing the animal owners in the project area or, by interviewing a sample of them in case of multiple landowners or by conducting a Participatory Rural Appraisal (PRA). Other sources of information, such as local animal census data, may also be used. As animal numbers may fluctuate over time, it is recommended to calculate the average animal population of the 5 to 10 years time period preceding the starting date of the A/R CDM project activity.  EMBED Equation.3  ( AUTONUMLGL \e ) where: NaBLAverage pre-project number of animals from the different livestock groups that are grazing in the project area; dimensionlesssNaBL Sampled pre-project number of animals from the different livestock groups that are grazing in the project area; dimensionless SFRPAgaFraction of total project area sampled for animal grazing; dimensionlessGiven the conditions under which this methodology is applicable (see Section I.3), particularly the applicability of baseline approach 22(a), the methodology assumes that the estimated historical or current animal population size (NaBL) will remain constant over the entire crediting period. Based on the planned afforestation or reforestation establishment schedule and the prescribed management, the periods of time from which grazing should be excluded from different parcels to be planted can be specified. This planning should be used to estimate the animal population that will be displaced each year outside the project boundary.  EMBED Equation.3  ( AUTONUMLGL \e ) where: Naoutside,t Number of animals displaced outside the project area at year t; dimensionlessNaBL Average number of animals from the different livestock groups that are grazing in the project area under the baseline scenario; dimensionlessNaAR,tNumber of animals allowed in the project area under the proposed A/R CDM project activity at year t; dimensionlessCase 1: NaBL < NaAR,t Leakage due to the displacement of animal grazing can be set as zero if the number of animals allowed in the project area under the proposed A/R CDM project is more than the average number of animals from the different livestock groups that are grazing in the project area under the baseline scenario. Lconv-graz = 0, if NaBL < NaAR,t ( AUTONUMLGL \e ) This situation can only occur if the planned A/R CDM project activity produces more fodder than the baseline activity. Case 2: NaBL > NaAR,t If the planned A/R CDM project activity produces less fodder than the baseline activity then, the animal populations will be displaced outside the project boundary due to the implementation of the A/R CDM project activity. These animals can be relocated in three different types of grazing areas: Existing grazing land areas under the control of the animal owners that are either sub-utilized or that have a potential to be managed for higher fodder production. These areas may be managed in a way that would provide sufficient fodder to feed the entire displaced animal population and prevent leakage. Any such measures have to be described in the PDD and subjected to monitoring. Such measures may not cause a significant increase in GHG emissions; New grazing land areas under the control of the animal owners, to be obtained from conversion of other land-uses to grazing land. This conversion is a source of leakage that should be estimated ex ante and monitored ex post; Unidentifiable grazing land areas, not under the control of the animal owners, which can either already exist or have to be established by converting other land-uses to new grazing land. This is typically the case when the animals are sold as a consequence or the implementation of the A/R CDM project activity. The total area of grazing land in which the displaced animal population will be maintained can be estimated as follow: GLA = EGL + NGL + XGL ( AUTONUMLGL \e ) where: GLA Total grazing land area outside the project boundary needed to feed the displaced animal populations; haEGLTotal existing grazing land area outside the project boundary that is under the control of the animal owners (or the project participants) and that will receive part of the displaced animal populations, up to time t*, haNGLTotal new grazing land area outside the project boundary to be converted to grazing land that is under the control of the animal owners (or the project participants) and that will receive another part of the displaced animal populations, up to time t*; haXGLTotal unidentifiable grazing land area outside the project boundary that will receive the remaining part of displaced animal populations, e.g. when the pre-project animal owners decide to sell the animals, up to time t*; haThe following steps are required: Step 1: Collect data on type of domestic species, their owners, population size, and number of months per annum during which animals from the different species are present in different discrete parcels of the area to be afforested or reforested. If several parcels of land are to be planted, collect these data from a sample. The sample size should not be less than 10% of the randomly selected parcels or 30 parcels. Estimate the annual biomass consumption of the animals over the project area to be planted as follows:  EMBED Equation.3  ( AUTONUMLGL \e ) where: CL PA,tAnnual animal biomass consumption over the project area to be planted at time t; td.m.yr-1pParcel index (P = total number of parcels); dimensionlessanAnimal type index (An = total number of animal types); dimensionlessDBIj Daily biomass intake by animal type j; kg d.m. head-1 day-1npgt Number of individual animals from the livestock group g at parcel p at time t; dimensionlessagpNumber of months per annum during which animals from the livestock group g are present at parcel p; dimensionless30 Average number of days in month; dimensionlessSFRPAgaFraction of total project area sampled for animal grazing; dimensionlessFor data on daily biomass intake, preferably use local data or applicable data from the scientific literature. For default data on daily biomass intake by animal see Table C. Step 2: Interview the owners of the animal populations identified in Step 1 to identify: Na: the total number of animals from the different livestock groups that are grazing in the project area (or in the sampled discrete parcels); dimensionless; Nas: the number of animals from the different livestock groups that the animal owners intend to sell as a consequence of the project implementation. Selling may be due to insufficient land under the control of the animal owners outside the project boundary; dimensionless; EGL: the existing grazing land areas outside the project boundary that are under the control of the animal owners and that will be used to maintain part of the displaced animal populations; ha. These areas shall be specified in the AR-CDM-PDD and subject to monitoring; Table C: Approximate values of daily biomass intake (d.m. dry mass) for different types of animals Animal Type Developed / DevelopingDaily Feed Intake (MJ head-1 day-1)Daily Biomass Intake (kg d.m. head-1 day-1)Sheep Developed Countries 202.0Developing Countries 131.3Goats Developed Countries 141.4Developing Countries 141.4Mules/Asses Developed Countries 606.0Developing Countries 606.0Sources: Feed intake from Crutzen et al. (1986). NGL: the new grazing land areas outside the project boundary that are under the control of the animal owners and that will be converted to grass-land to maintain another part of the displaced animal populations; ha. These areas shall be specified in the ARCDMPDD and subject to monitoring. Step 3: Estimate the number of animals that can be displaced in EGL-areas: Interview local experts and the owners of EGL areas about maximum population and number of months per annum during which animals of the type displaced can be present in these areas. Using equation 34, calculate the maximum annual biomass that these grazing areas can produce for animal feeding (CLmax); Collect data on domestic species, their population, and number of months per annum during which animals from different species are already present in different discrete parcels of the areas identified in Step 2. Using equation 34, calculate the annual biomass that these grazing areas are currently producing for animal feeding (CLcurrent). The average number of animals already present in the EGL areas selected for monitoring shall be specified in the ARCDMPDD (NaEGl,t=1); Determine if the EGL areas are sufficient for feeding the entire population of displaced animals; If: (CLmax - CLcurrent)EGL e" CL PA Then: Leakage due to activity displacement is set as zero (e.g. LKconversion = 0) and no further assessment of LKconversion will be necessary; If: (CLmax - CLcurrent)EGL < CL PA Then: Additional grazing areas will be required to feed the displaced animals. Calculate the number of displaced animals that can be maintained in EGL areas as follows: Average annual biomass consumed by one average animal:  EMBED Equation.3  ( AUTONUMLGL \e ) Number of animals that can be displaced in EGL:  EMBED Equation.3  ( AUTONUMLGL \e ) Step 4: Estimate the number of animals that can be displaced in NGL-areas: Interview local experts and the owners of these areas about maximum population and number of months per annum during which animals can be present in these areas after conversion to grazing land - for each type of animal species. Using equation35 calculate the maximum annual biomass that these areas to be converted to grazing lands can produce for animal feeding (CLmax); Do sub-step b) as in Step 1, but for the NGL area. The average number of animals already present in the NGL areas selected for monitoring shall be specified in the ARCDM-PDD (NaNGL,t=1); Determine if the NGL areas are sufficient for feeding the population of displaced animals that cannot be maintained in EGL areas: If: (CLmax - CLcurrent)EGL + (CLmax - CLcurrent )NGL e" CL PA Then: NGL areas are sufficient and no animals will have to be displaced to unidentifiable areas, and XGL can be set as zero; If: (CLmax - CLcurrent)EGL + (CLmax - CLcurrent )NGL < CL PA Then: NGL areas are insufficient, and some animals will have to be displaced to unidentifiable areas. Do sub-step d) as in Step 1, but for NGL areas. Step 5: Estimate the number of animals that will have to be displaced to unidentifiable areas and estimate XGL: Determine the number of animals to be displaced to unidentifiable areas using the following conservative decision rule: If: Nas e" (Na - dNaEGL + dNaNGL) Then: dNaXGL = Nas If: Nas < (Na - dNaEGL + dNaNGL) Then: dNaXGL = (Na - dNaEGL + dNaNGL) Calculate XGL using the following equation:  EMBED Equation.3  ( AUTONUMLGL \e ) where: XGLTotal unidentified grazing land area outside the project boundary that will receive the remaining part of displaced animal populations, e.g. when the pre-project animal owners decide to sell the animals, up to time t*; haATotal project area; haNa Total number of animals from the different livestock groups that are grazing in the project area; dimensionlessdNaXGLTotal number of animals to be displaced to unidentifiable areas; dimensionless Step 6: Estimate leakage due to displacement of grazing activities as follows: LKconv-graz = LKNGL + LKXGL ( AUTONUMLGL \e ) where: LKconv-grazLeakage due to conversion of non-grassland to grassland; t CO2-eLKNGLLeakage due to conversion of non-grassland to grassland in NGL areas under the control of the animal owners; t CO2-e LKXGLLeakage due to conversion of non-grassland to grassland in unidentified XGL areas; t CO2-eEstimation of LKNGL Stratify NGL areas in categories of land-use/land-cover that are significantly different in terms of carbon stock (e.g., crop-land, fallow land, mature forest); Estimate the mean carbon stocks in the five carbon pools (from IPCC GPGLULUCF, literature or original measurements) of each NGL stratum. In the case of the soil organic carbon pool, always subtract from the estimate in the NGL strata the estimated mean carbon stock in the soil organic carbon pool of the project area (from IPCC GPG-LULUCF, literature or original measurements). This is not necessary for dead wood and litter, because in the project area, under the applicability conditions of this methodology, these pools have very small carbon stocks; If a significant proportion of the above-ground biomass in the NGL strata is merchantable timber volume, estimate the biomass of this volume (trough field measurements); Subtract from the total above-ground biomass in the NGL strata the biomass of the harvested timber and any woody biomass that is likely to be used as fuel-wood or for charcoal production; Assume that the remaining above-ground biomass will be 100% burned, which will result in emissions of non-CO2 gases. If no estimates of harvested timber volume and/or fuel wood biomass are made, assume that all above-ground biomass will be burned. This assumption is conservative because the fraction of biomass that burns is always less than 100%; Estimate LKNGL as follows:  EMBED Equation.3  ( AUTONUMLGL \e ) where: LKNGLLeakage due to conversion of non-grassland to grassland; t CO2-englt Total area converted to grassland at time t; haCNGLac t Mean carbon stock including above and below-ground biomass of the NGL area converted to grassland at time t; CO2-eWBht Fraction of total above-ground biomass harvested as timber and as fuel-wood at time t (not burned); dimensionlessEacBiomassBurntTotal non-CO2 emissions from biomass burning in land converted to grazing land at time t (calculated from 100% of the above-ground biomass); t CO2-e. These can be calculated using equation 23Calculate the average aLKNGL per displaced animal in NGL areas as follows:  EMBED Equation.3  ( AUTONUMLGL \e ) where: aLKNGLAverage leakage due to conversion of non-grassland to grassland per displaced animal in NGL areas; t CO2-e animal-1LKNGLLeakage due to conversion of non-grassland to grassland; t CO2-e dNaNGL Total number of animals to be displaced to NGL areas; dimensionless Estimation of LKXGL As it is not possible to identify land-use/land-cover in XGL areas, this methodology conservatively assumes that these areas are covered by mature forests and that these forests will be converted to grazing land; Estimate the mean carbon stocks in the five carbon pools (from IPCC GPGLULUCF, literature or original measurements) of mature forests in the country or region where the grazing animals will most likely be sold. In the case of the soil organic carbon pool, always subtract from the estimate in the XGL areas the estimated mean carbon stock in the soil organic carbon pool of the project area (from IPCC GPG-LULUCF, literature or original measurements). This is not necessary for dead wood and litter, because in the project area, under the applicability conditions of this methodology, these pools have very small carbon stocks; Estimate the likely percentage of above-ground biomass that is likely not to be burned (from literature or original studies). If no justifiable assumption can be made regarding this percentage, assume 100% of biomass burning; Estimate LKXGL as follows:  EMBED Equation.3  ( AUTONUMLGL \e ) where: LKXGLLLeakage due to conversion of unidentifiable-land to grassland; tCO2exglt Total unidentifiable area converted to grassland at time t; haCXGLac t Mean carbon stock including above and below-ground biomass of the XGL area converted to grassland at time t; CO2-eWBht Fraction of total above-ground biomass not-burned at time t (not burned); dimensionlessEacBiomassBurntTotal non-CO2 emissions from biomass burning in unidentifiable land converted to grazing land at time t (assuming 100% burning of above-ground biomass); tCO2-e. These can be calculated using equation 23Calculate the average aLKXGL per displaced animal in XGL areas as follows:  EMBED Equation.3  ( AUTONUMLGL \e ) where: aLKXGLAverage leakage due to conversion of non-grassland to grassland per displaced animal in XGL areas; t CO2-e animal-1LKXGLLeakage due to conversion of non-grassland to grassland; t CO2-e dNaXGL Total number of animals to be displaced to XGL areas; dimensionlessEstimation of LKconv-crop (Leakage due to conversion of land to crop land, based on area of conversion) Activity shifting or activity displacement may result in leakage immediately after the start of the project activity when activities are displaced to areas outside the project boundary. However, leakage due to conversion of land is not attributable to the AR CDM project activity if the conversion of land occurs 5 or more years after the displacement of the activity to areas outside the project boundary. The type and schedule of measures to be taken to prevent the conversion of land outside the project boundary should therefore be described in the AR-CDM-PDD and its implementation monitored. Alternative methodologies are presented for analyses at the household or at the community level (the household analysis is only appropriate where continued ownership or occupation of land parcels can be shown). For the household level analysis, over the five-year period, 10 % of the randomly selected displaced households (or a minimum of randomly selected 30 households) will be tracked with respect to their land use. For the community level analysis, the land use of randomly selected 10 % of the communities (or a minimum of 10 communities) displaced or partially displaced by project activities will be tracked, with 10% of randomly selected households (or a minimum of 10 randomly selected households) in each community sampled to determine the area of unidentifiable conversion in the five years after the start of displacement from project area. The community level analysis allows for communities of differing sizes. LKconv-crop=CSAD CSb ( AUTONUMLGL \e ) where: LKconv-cropLeakage resulting from the conversion for croplandCSADLocally derived carbon stock (including all five eligible carbon pools); tCO2eha1) of area of land on which activities shifted; t CO2-e ha-1CSbCarbon stock of baseline; t CO2-e ha-1Case 1: CSAD < CSb Leakage due to displacement for cropland can be set as zero if the carbon stock on the land to which crops are displaced is less than the carbon stock from which they originated under the baseline scenario. Lconv-crop = 0, if CSAD < CSb ( AUTONUMLGL \e ) Case 2: CSAD > CSb However, if activities are displaced to land with higher stocks, then a leakage debit should be taken by the project. Carbon stock decreases through biomass losses will be calculated by multiplying the area of land conversion by the carbon stock. Land holdings are broken down into two types: Land holdings with areas of geographically identifiable land conversion outside the project boundary. The area of identifiable land converted by a sampled displaced household or community is multiplied by the mean carbon stock of the land strata type prior to conversion. If the previous land strata type is unknown, the strata with the highest carbon stock will be used; Land holdings with areas of geographically unidentifiable land conversion outside the project boundary. This may be due to migration of households to unknown locations or any other circumstance that causes the location of the households converted land to be unknown. Where the land households convert is unidentifiable, leakage GHG emissions is conservatively assumed equal to the area of land from which the household was displaced multiplied by a conservative value for regional forest biomass stock. Household level Step 1: Randomly select households to be sampled (10% of all households or a minimum of 30 households), e.g by selecting them systematically from a list of all households listed in alphabetic order. Step 2: Measure area of cropland within project boundaries each sampled household will be displaced from. Step 3: Interview sampled household to determine total area of cropland owned by each household that is planted (TACPh), and the land cover class (CSi) of the area (IAChi) and that each household intends to convert. Step 4: Estimate the carbon stock in each land cover stratum using methods detailed in IPCC GPGLULUCF chapter 4.3, including all pools. Step 5: Determine the mean conservative forest biomass stock for the project region ( EMBED Equation.3 ) for application to unidentified areas. Step 6: Calculate the leakage using the following equations:  EMBED Equation.3  ( AUTONUMLGL \e ) and:  EMBED Equation.3  ( AUTONUMLGL \e ) where: LKconv-cropLeakage due to conversion of land to cropland attributable to displacement (activity shifting); t CO2-eIAChiIdentifiable areas converted by household hh in stratum i; hectaresTACPhTotal area of cropland planted that is owned by household h; hectareshh1,2,3.Hh households; dimensionlessi1,2,3.I strata; dimensionlessCSiLocally derived carbon stock of identified lands (including all the five eligible carbon pools) of stratum i; t CO2-e. ha-1 EMBED Equation.3 Locally derived average carbon stock of unidentified lands (including all the five eligible carbon pools); t CO2-e. ha-1SFSampling factor of household; dimensionlessTNHHTotal number of households using project lands in baseline; dimensionlessSHHSampled households, number of households sampled for LKconv-crop; dimensionlessCommunity level For the community based estimate, one calculates the leakage per community using an equation similar to equation 45 and then one sums over the communities based on area. Step 1: Record the number of communities occupying land inside the project boundary. Randomly select 10% of the communities (or a minimum of 10 communities) to be sampled. Step 2: Measure total area of cropland within project boundaries from which pre-project activities in each sampled community will be displaced (TACPc). Step 3: Calculate the number of households within each selected community (TNHHc). Step 4: Randomly select 10% of households (or a minimum of 10 households) to be sampled within selected communities, e.g by selecting them systematically from a list of all households listed in alphabetic order. Step 5: Interview community members to estimate the area of identifiable land that each sampled community will convert due to displacement of pre-project activities (IAChc). Step 6: Classify the estimated area of identifiable land that may be converted within the community into a pre-conversion land cover stratum. Step 7: Estimate the carbon stock (including all 5 carbon pools) in each land cover stratum using methods detailed in IPCC GPG-LULUCF chapter 4.3 (CSi). Step 8: Determine the mean conservative forest biomass stock for the project region ( EMBED Equation.3 ) for application to unidentified areas; Step 9: Calculate the leakage using the following equations:  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: LKconv-cropLeakage due to conversion of land to cropland attributable to displacement (activity shifting); t CO2-eLKconv-crop,cLeakage due to conversion of land to cropland attributable to displacement (activity shifting) in community c; t CO2-eTACPTotal area of land on which pre-project activities were displaced due to project activities; hectaresTACPcTotal area of land on which pre-project activities were displaced due to project activities in community c; hectaresIAChciIdentifiable areas converted of stratum i by household hh in community c; hectaresCSiLocally derived carbon stock (including all the five eligible carbon pools) of stratumi; t CO2-e ha-1 EMBED Equation.3 Locally derived average carbon stock of unidentified lands (including all the five eligible carbon pools); t CO2-e ha-1TNHHcTotal number of households using project lands in baseline in community c; dimensionlessSHHcSampled households in community c, number of households sampled for leakage by activity shifting; dimensionlessSFcSampling factor for community c; dimensionlessc1,2,3C, communities; dimensionlessi1,2,3.I, strata; dimensionlesshh1,2,3, Hhc, households in community c; dimensionlessEstimation of LK fuel-wood (Leakage due to displacement of fuel-wood collection) Depending on the specific project circumstance, all pre-project fuel-wood collection activities (including in-site charcoal production), or a fraction of them, may have to be displaced permanently, or temporarily, outside the project boundary. Where pre-project fuel-wood collection and/or charcoal production activities exist, it is necessary to estimate the pre-project consumption of fuel-wood in randomly selected different discrete parcels or (subareas) within the project area. This can be done by interviewing households or implementing a Participatory Rural Appraisal (PRA). Where several discrete parcels are present in the project area, sampling techniques can be used. Others sources of information, such as local studies on fuel-wood consumption and/or charcoal production may also be used. Average data from the 5 to 10 years time period preceding the starting date of the AR CDM project activity should be used whenever possible.  EMBED Equation.3  ( AUTONUMLGL \e ) where: FGBLAverage pre-project annual volume of fuel-wood gathering in the project area; m3 yr-1sFGBL Sampled average pre-project annual volume of fuel-wood gathering in the project area; m3 yr-1SFRPAfwFraction of total area or households in the project area sampled; dimensionlessGiven the conditions under which this methodology is applicable (see Section I.3), particularly the applicability of baseline approach 22(a), the methodology assumes that the estimated historical or current fuel-wood consumption and/or charcoal production (FGBL) will remain constant over the entire crediting period. Based on the planned afforestation or reforestation establishment schedule and the prescribed management, the periods of time from which fuel-wood collection and/or charcoal production should be excluded from the considered sample discrete areas as well as the amounts of fuel-wood produced in the different stands through thinning, coppicing and harvesting can be specified. This planning should be used to estimate the amount of fuel-wood and/or charcoal that may have to be obtained each year from sources outside the project boundary.  EMBED Equation.3  ( AUTONUMLGL \e ) where: FGoutside,tVolume of fuel-wood gathering displaced outside the project area at year t; m3 yr-1FGBL Average pre-project annual volume of fuel-wood gathering in the project area; m3yr1FGAR,tVolume of fuel-wood gathering allowed/planned in the project area under the proposed AR CDM project activity; m3 yr-1Leakage due to displacement of fuel-wood collection can be set as zero (LK fuel-wood = 0) under the following circumstances: FGBL < FGAR,t; LK fuel-wood < 2% of actual net GHG removals by sinks (See EB 22, Annex 15). In all other cases, leakage due to displacement of fuel-wood collection shall be estimated as follow (IPCC GPG-LULUCF - Equation 3.2.8):  EMBED Equation.3  ( AUTONUMLGL \e ) FGt = FGoutside,t FGNGL, t ( AUTONUMLGL \e ) where: LK fuel-woodLeakage due to displacement of fuel-wood collection up to year t*; t CO2-eFGtVolume of fuel-wood gathering displaced in unidentified areas; m3 yr-1FGoutside,t Volume of fuel-wood gathering displaced outside the project area at year t; m3 yr-1FGNGL,tVolume of fuel-wood gathering in NGL areas and supplied to pre-project fuel-wood collectors and/or charcoal producers; m3 yr-1DAverage basic wood density; t d.m. m-3 (See IPCC GPG-LULUCF, Table 3A.1.9)BEF2Biomass expansion factor for converting volumes of extracted round wood to total above-ground biomass (including bark); dimensionless Table 3A.1.10CFCarbon fraction of dry matter (default = 0.5); t C (t d.m.)-1Ex ante net anthropogenic GHG removal by sinks 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 A/R CDM project activity (CARCDM), in t CO2-e:  EMBED Equation.3  ( AUTONUMLGL \e ) where: CAR-CDMNet anthropogenic greenhouse gas removals by sinks; t CO2-eCACTUAL Actual net greenhouse gas removals by sinks (equation 13); t CO2-eCBSL Baseline net greenhouse gas removals by sinks (equation 1 or 2); t CO2-eLK Leakage (27); t CO2-eNote: In this methodology equation 55 is used to estimate net anthropogenic GHG removals by sinks for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated. This is done because project emissions and leakage are permanent, which requires to calculate their cumulative values since the starting date of the A/R CDM project activity. Calculation of tCERs and lCERs To estimate the amount of CERs that can be issued at time t*= t2 (the date of verification) for the monitoring period T = t2 t1, this methodology uses the EB approved equations, which produce the same estimates as the following: tCERs = CAR-CDM,t2 ( AUTONUMLGL \e ) lCERs = CAR-CDM,t2 - CAR-CDM,t1 ( AUTONUMLGL \e ) where: tCERsNumber of units of temporary Certified Emission ReductionslCERsNumber of units of long-term Certified Emission ReductionsCAR-CDM,t2Net anthropogenic greenhouse gas removals by sinks, as estimated for t* = t2; t CO2-eCAR-CDM,t1Net anthropogenic greenhouse gas removals by sinks, as estimated for t* = t1; t CO2-eUncertainties and conservative approach: To help reduce uncertainties in the accounting of emissions and removals, this methodology uses whenever possible the proven methods from the GPG-LULUCF, GPG-2000, and the IPCCs Revised 2006 Guidelines. As well, tools and guidance from the CDM Executive Board on conservative estimation of emissions and removals are also used. Despite this, potential uncertainties still arise from the choice of parameters to be used. Uncertainties arising from, for example, biomass expansion factors (BEFs) or wood density, would result in uncertainties in the estimation of both baseline net GHG removals by sinks and the actual net GHG removals by sinks - especially when global default values are used. It is recommended that PPs identify key parameters that would significantly influence the accuracy of estimates. Local values that are specific to the project circumstances should then be obtained for these key parameters, whenever possible. These values should be based on: Data from well-referenced peer-reviewed literature or other well-established published sources; or National inventory data or default data from IPCC literature that has, whenever possible and necessary, been checked for consistency against available local data specific to the project circumstances; or In the absence of the above sources of information, expert opinion may be used to assist with data selection. Experts will often provide a range of data, as well as a most probable value for the data. The rationale for selecting a particular data value should be briefly noted in the CDMARPDD. For any data provided by experts, the CDMAR-PDD shall also record the experts name, affiliation, and principal qualification as an expert (e.g., that they are a member of a country's national forest inventory technical advisory group) as well as a 1-page summary CV for each expert consulted, included in an annex. In choosing key parameters or making important assumptions based on information that is not specific to the project circumstances, such as in use of default data, PPs should select values that will lead to an accurate estimation of net GHG removals by sinks, taking into account uncertainties. If uncertainty is significant, PPs should choose data such that it tends to under-estimate, rather than over-estimate, net GHG removals by sinks. Data needed for ex ante estimations Data/ParametersDescriptionsVintageData sources and geographical scaleHistorical land use/cover dataDetermining baseline approach, Demonstrating eligibility of landEarliest possible up to nowLocalPublications, government, interviewLand use/cover mapDemonstrating eligibility of land, stratifying land areaBefore 1990 and most recent dateRegional, localForestry inventorySatellite imageSame as above cell1989/1990 and most recent dateLocale.g. LandsatLandform mapStratifying land areamost recent date1:10000Local governmentSoil mapStratifying land areamost recent date1:10000Local government and institutional agenciesNational and sectoral policiesAdditionality considerationBefore 11 Nov. 2001National and sectoralLocal government UNFCCC, EB and AR-WG decisions - reports1997 up to nowInternationalUNFCCC websiteIRR, NPV cost benefit ratio, or unit cost of serviceIndicators of investment analysisMost recent dateLocalCalculation (if any, depends on the way of additionality analysis)Investment costsIncluding land purchase or rental, machinery, equipments, buildings, fences, site and soil preparation, seedling, planting, weeding, pesticides, fertilization, supervision, training, technical consultation, etc. that occur in the establishment periodMost recent date, taking into account market riskLocalLocal statistics, published data and/or survey (if any, depends on the way of additionality analysis)Operations and maintenance costsIncluding costs of thinning, pruning, harvesting, replanting, fuel, transportation, repairs, fire and disease control, patrolling, administration, etc.Most recent date, taking into account market riskLocalLocal statistics, published data and/or survey (if any, depends on the way of additionality analysis)Transaction costsIncluding costs of project preparation, validation, registration, monitoring, etc.Most recent dateNational and internationalDOERevenuesThose from timber, fuel-wood, non-wood products, with and without CER revenues, etc.Most recent date, taking into account market riskNational and localLocal statistics, published data and/or survey (if any, depends on the way of additionality analysis)12/44Ration of molecular weights of carbon and CO2; dimensionlessGlobal defaultIPCC16/12Ration of molecular weights of CH4 and carbon; dimensionlessGlobal defaultIPCC30Average number of days in month; dimensionless44/12Ratio of molecular weights of CO2 and carbon; dimensionlessGlobal defaultIPCC44/28Ratio of molecular weights of N2O and nitrogen; dimensionlessGlobal defaultIPCCanAnimal type index (An = total number of animal types; dimensionlessProjectEstimated ex ante, monitored ex postATotal project area; haMost updatedProjectEstimated ex ante, monitored ex postAB,ikt_sbArea of slash and burn in stratum i, stand model k, time t; haProjectEstimated ex ante, monitored ex postAdistiktForest areas affected by disturbances in stratum i, stand model k, time t; ha yr-1Most updatedStratum and speciesEstimated ex ante, monitored ex postAdistikT Average annual area affected by disturbances for stratum i, stand model k, during the period T; ha yr-1Most updatedStratum and speciesEstimated ex ante, monitored ex postagpl Number of months per annum during which animals from the livestock group g are present at parcel p; dimensionlessMost updatedProjectEstimated ex ante, monitored ex postAikt Area of stratum i, stand model k, at time t; hectare (ha)Most updatedStratum and speciesEstimated ex ante, monitored ex postAikt_sb Area of slash and burn for stratum i, stand model k, time t; haMost updatedStratum and speciesEstimated ex ante, monitored ex postAikTAverage annual area for stratum i, stand model k, during the period T; ha yr-1Most updatedStratum and speciesEstimated ex ante, monitored ex postaLKNGLAverage leakage due to conversion of non-grassland to grassland per displaced animal in NGL areas; t CO2-e. animal-1Most updatedProjectCalculated aLKXGLAverage leakage due to conversion of non-grassland to grassland per displaced animal in XGL areas; t CO2-e. animal-1Most updatedProjectCalculated BEF1,j Biomass expansion factor for conversion of annual net increment (including bark) in merchantable volume to total above-ground biomass increment for species j; dimensionlessGlobal default to localGPG-LULUCF, national GHG inventory, local surveyBEF2Biomass expansion factor for converting volumes of extracted round wood to total above-ground biomass (including bark); dimensionless Table 3A.1.10Global default to localGPG-LULUCF, national GHG inventory, local surveyBEF2,ijt Biomass expansion factor for converting merchantable volumes of extracted round wood to total above-ground biomass (including bark) for stratum i, species j, time t; dimensionlessGlobal default to localGPG-LULUCF, national GHG inventory, local surveyBikt Average above-ground biomass stock before burning for stratum i, stand model k, time t; t d.m. ha-1Global default to localGPG-LULUCF, national GHG invenory, local surveyBpre,iktAverage pre-existing stock on land to be planted before the start of a proposed A/R CDM project activity for baseline stratum i, stand model k, time t; t d.m. ha-1Most updatedGlobal default to localGPG-LULUCF, national GHG inventory, local surveyBw,ijt Average above-ground biomass stock for stratum i, species j, time t; t d.m. ha-1 Most updatedLocalNational GHG inventory, local surveycCommunity index (C=total number of communities); dimensionlessProjectEstimated ex ante, monitored ex postCAB,ijtCarbon stock in above-ground biomass for stratum i, species j, at time t; t CLocal and species specificCalculatedCNGLac t Mean carbon stock including above and below-ground biomass of the NGL area converted to grassland at time t; CO2-e.Regional, local defaultEstimated ex anteCXGLac t Mean carbon stock including above and below-ground biomass of the XGL area converted to grassland at time t; CO2-e.Regional, local defaultEstimated ex anteCACTUAL Actual net greenhouse gas removals by sinks; t CO2-e.Project specificCalculatedCAR-CDMNet anthropogenic greenhouse gas removals by sinks; t CO2-e.Project specificCalculatedCAR-CDM,t1Net anthropogenic greenhouse gas removals by sinks, as estimated for t* = t1; t CO2-e.Project specificCalculatedCAR-CDM,t2Net anthropogenic greenhouse gas removals by sinks, as estimated for t* = t2; t CO2-e.Project specificCalculatedCBB,ijt Carbon stock in below-ground biomass for stratum i, species j, at time t; t CLocal and species specificCalculatedCBSL Baseline net greenhouse gas removals by sinks; t CO2-e.Project specificCalculatedCE Average biomass combustion efficiency; dimensionlessGlobal and national defaultIPCC GPG-2000, national GHG inventoryCFj Carbon fraction for species j; t C (t d.m.)-1Global default to localGPG-LULUCF, national GHG inventoryCFpreCarbon fraction of dry biomass in pre-existing vegetation, t C (t d.m.)-1Global default to localGPG-LULUCF, national GHG inventoryCikt Total carbon stock in living biomass for stratum i, stand model k, calculated at time t; t CStratumCalculatedCSiLocally derived carbon stock (including all five eligible carbon pools) of stratum i; tCO2e. ha-1Most updatedProjectCalculated  EMBED Equation.3 Locally derived average carbon stock of unidentified lands (including all the five eligible carbon pools); t CO2-e. ha-1Most updatedProjectCalculated CTOTAL,ikt Average annual increment rate in total carbon stock in stratum i, stand model k, time t; t of CO2 ha-1.yr-1StratumCalculatedDAverage basic wood density; t d.m. m-3 (See IPCC GPG-LULUCF, Table 3A.1.9)Global default to localGPG-LULUCF, national GHG inventoryDBHTree diameter at breast height; cmProject specificMeasuredDBIj Daily biomass intake by animal type j; kg d.m. head-1 day-1Global default to localEstimated ex anteDj Basic wood density for species j; t d.m. m-3 (See IPCC GPG-LULUCF, Table 3A.1.9)Global default to localGPG-LULUCF, national GHG inventory, local surveydNaEGLNumber of animals that can be displaced in EGL areas; dimensionlessMost updatedProjectEstimated ex ante, measured ex postdNaNGLNumber of animals that can be displaced in NGL areas; dimensionlessMost updatedProjectEstimated ex ante, measured ex postdNaXGLNumber of animals to be displaced in XGL areas; dimensionlessMost updatedProjectEstimated ex ante, measured ex postEacBiomassBurntTotal non-CO2 emissions from biomass burning in land converted to grazing land at time t (calculated from 100% of the above-ground biomass); t CO2-e.Most updatedProjectCalculatedEBiomassBurn Total increase in non-CO2 emission as a result of biomass burning within the project boundary; t CO2-e.Most updatedProjectCalculatedEBiomassBurn, CH4 CH4 emission from biomass burning in slash and burn; t CO2-e.Most updatedProjectCalculatedEBiomassBurn, N2O N2O emission from biomass burning in slash and burn; t CO2-e.Most updatedProjectCalculatedEBiomassBurn,CO2 CO2 emission from biomass burning in slash and burn; t CO2-e.Most updatedProjectCalculatedEbiomasslossDecrease in the carbon stock in the living biomass carbon pools of non-tree vegetation in the year of site preparationMost updatedProjectCalculatedEGLTotal existing grazing land area outside the project boundary that is under the control of the animal owners (or the project participants) and that will receive part of the displaced animal populations, up to time t*; haProjectEstimated ex anteEiEmission/removal estimate for source/sink iERCH4Emission ratio for CH4 (IPCC default value = 0.012)Global defaultIPCC default value = 0.012ERN2O Emission ratio for N2O (IPCC default value = 0.007)Global defaultIPCC default value = 0.007FGAR,tVolume of fuel-wood gathering allowed/planned in the project area under the proposed AR-CDM project activity; m3 yr-1ProjectEstimated ex ante, measured ex postFGBLAverage pre-project annual volume of fuel-wood gathering in the project area; m3 yr-1ProjectEstimated ex anteFGijtAnnual volume of fuel wood harvesting for stratum i, species j, time t; m3 ha-1 yr-1StratumEstimated ex ante, monitored ex postFGijTAverage annual volume of fuel wood harvested for stratum i, species j, during the period T; m3 ha-1 yr-1StratumEstimated ex ante, monitored ex postFGNGL,tVolume of fuel-wood gathering in NGL areas and supplied to pre-project fuel-wood collectors and/or charcoal producers; m3 yr-1ProjectEstimated ex ante and ex postFGoutside,tVolume of fuel-wood gathering displaced outside the project area at year t; m3 yr-1ProjectEstimated ex ante and ex postFGtVolume of fuel-wood gathering displaced in unidentified areas; m3 yr-1ProjectEstimated ex ante and ex postfi(DBHt,Ht) An allometric equation linking above-ground biomass of living trees (d.m ha-1) to mean diameter at breast height (DBH) and possibly mean tree height (H) for species j; dimensionlessNational, local, species specificForestry inventory, published data, local surveyGHGE Sum of the increases in GHG emissions by sources within the project boundary as a result of the implementation of an A/R CDM project activity; t CO2-e. Project specificCalculatedGLA Total grazing land area outside the project boundary needed to feed the displaced animal populations; haProjectEstimated ex anteGTOTAL,ijt Annual average increment rate in total biomass in units of dry matter for stratum i, speciesj, time t; t d.m ha-1 yr-1 Most recentGlobal default to localGPG-LULUCF, national and local forestry inventoryGw,ijt Average annual above-ground biomass increment for stratum i, species j, time t; t d.m ha-1 yr-1Global default to localGPG-LULUCF, national GHG inventoryGWPCH4 Global Warming Potential for CH4 GlobalIPCC default = 21GWPN2OGlobal Warming Potential for N2OGlobal defaultIPCC default = 310hhHousehold index (Hh = total number of households); dimensionlessProjectEstimated ex ante, monitored ex post HHctotal number of households in community c; dimensionlessProjectEstimated ex ante, monitored ex post HTree height; mProjectEstimated to measured ex ante, measured ex postHijtAnnually extracted merchantable volume for stratum i, species j, time t; m3 ha-1 yr-1 Local/standEstimated ex ante, monitored ex postHijTAverage annually harvested merchantable volume for stratum i, species j, during the period T; m3 ha-1 yr-1 Local/standEstimated ex ante, monitored ex posti Stratum index for both baseline strata and the strata of the project scenarioProjectEstimated ex ante, monitored ex postIAChiIdentifiable areas converted in stratum i by household hh; hectaresMost updatedProjectCalculated IAChicIdentifiable Areas Converted in stratum i by household hh in community c; hectaresMost updatedProjectCalculated Iv,ijt Average annual increment in merchantable volume for stratum i, species j, time t; m3 ha-1 yr-1Local/standEstimated ex anteIv,ijT Average annual net increment in merchantable volume for stratum i, species j during the period T; m3 ha-1 yr-1Local/standEstimated ex antejSpecies representing a specific stand model (J = total species)ProjectEstimated ex antekStand model consisting of one or several species (K = total stand models)lCERsNumber of units of long-term Certified Emission ReductionsProjectCalculatedLfw,ijt Annual carbon loss due to fuel wood gathering for stratum i, species j, time t; CO2-e. yr-1Local/standEstimated ex ante, monitored ex postLhr,ijt Annual carbon loss due to commercial harvesting for stratum i, species j, time t; t CO2-e. yr-1Local/standEstimated ex ante, monitored ex postLK Total project leakage ; t CO2-e.ProjectCalculatedLK fuel-woodLeakage due to the displacement of fuel-wood collection; t CO2-e.ProjectCalculatedLKActivityDisplacementLeakage due to activity displacement; t CO2-e. ProjectCalculatedLKconversionLeakage due to conversion of land for grazing or cropland; t CO2-e.ProjectCalculatedLKconv-grazLeakage resulting from conversion of land for grazing; t CO2-e.ProjectCalculated LKconv-cropLeakage resulting from conversion of land for cropland; t CO2-e.ProjectCalculated LKconv-crop,cLeakage resulting from conversion of land for cropland in community c; t CO2-e.ProjectCalculated LKNGLLeakage due to conversion of non-grassland to grassland in NGL areas under the control of the animal owners; t CO2-e. ProjectCalculatedLKXGLLeakage due to conversion of non-grassland to grassland in unidentified XGL areas; t CO2-e. ProjectCalculatedLot,ijt Annual natural losses (mortality) of carbon for stratum i, species j, time t; CO2-e. yr-1Local/standCalculatedMfijTMortality factor = percentage of Vijt1 died during the period T; dimensionlessLocal/standEstimatedmBLTotal baseline stratamPSTotal strata in project scenarioNaTotal number of animals from the different livestock groups that are grazing in the project area (or in the sampled discrete areas); dimensionlessProjectEstimated-measuredNaAR,tNumber of animals allowed in the project area under the proposed AR-CDM project activity at year t; dimensionlessProjectEstimated ex ante, monitored ex postNaBLAverage pre-project number of animals from the different livestock groups that are grazing in the project area; dimensionlessProjectEstimated ex anteNaEGL,t=1Average number of animals present in the EGL areas selected for monitoring at project start; dimensionlessProjectEstimated ex ante, monitored ex postNaNGL,t=1Average number of animals present in the NGL areas selected for monitoring at project start; dimensionlessProjectEstimated ex ante, monitored ex postNaoutside,tNumber of animals displaced outside the project area at year t; dimensionlessProjectEstimated ex ante, monitored ex postNasNumber of animals from the different livestock groups that the animal owners intend to sell as a consequence of the project implementation; dimensionlessProjectEstimated ex ante, monitored ex postN/C ratioNitrogen-carbon ratio; dimensionlessGlobalIPCCNGLTotal new grazing land area outside the project boundary to be converted to grazing land that is under the control of the animal owners (or the project participants) and that will receive another part of the displaced animal populations, up to time t*; haProjectEstimated ex antenglt Total area converted to grassland at time t; haProjectEstimated ex antenpgt Number of individual animals from the livestock group g at parcel p at time t; dimensionlessProjectEstimated ex antenTRijtNumber of trees in stratum i, species j, at time t; dimensionless ha-1ProjectEstimated ex ante, monitored ex postpParcel index (P = total number of parcels); dimensionlessIndexPBBikt Average proportion of biomass burnt for stratum i, stand model k, time t; dimensionlessGlobal and national defaultIPCC GPG-2000, national GHG inventoryRj Root-shoot ratio appropriate to increments for species j; dimensionlessGlobal default to localGPG-LULUCF, national GHG inventory, local surveySFSampling factor; dimensionlessProjectCalculated ex anteSFcSampling factor of community c; dimensionlessProjectCalculated ex antesFGBL Sampled average pre-project annual volume of fuel-wood gathering in the project area; m3 yr-1ProjectEstimated ex ante and ex postSFRPAfwFraction of total area or households in the project area sampled for fuel-wood; dimensionlessProjectDefined ex anteSFRPAgaFraction of total area or households in the project area sampled for grazing animals; dimensionlessProjectDefined ex anteSFREGLFraction of total EGL areas sampled; dimensionlessProjectDefined ex anteSFRNGLFraction of total NGL areas sampled; dimensionlessProjectDefined ex anteSHHSampled households, number of households sampled for LKconv-crop; dimensionlessProjectDefined ex anteSHHcSampled households in community c, number of households sampled for LKconv-crop; dimensionlessProjectDefined ex antesNaBL Sampled pre-project number of animals from the different livestock groups that are grazing in the project area; dimensionless ProjectEstimated ex antet1, 2, 3, t* years elapsed since the start of the A/R CDM project activityProjectEstimated ex ante, monitored ex postT Number of years between times t2 and t1 (T = t2 - t1)ProjectEstimated ex ante, monitored ex postt*Number of years elapsed since the start of the A/R project activity; yrTACPTotal Area of Cropland Planted by the project; hectaresMost updatedProjectCalculated TACPcTotal area of cropland planted that is owned by community c; hectaresMost updatedProjectCalculated TACPhTotal area of cropland planted that is owned by household hh; hectaresMost updatedProjectCalculated tCERsNumber of units of temporary Certified Emission ReductionsProjectCalculatedtcpYear at which the first crediting period ends; yrTNHHTotal number of households using project lands in baseline; dimensionlessMost updatedProjectCalculated TNHHcTotal number of households using project lands in baseline in community c; dimensionlessMost updatedProjectCalculated Vijt Average merchantable volume of stratum i, species j, at time t; m3 ha-1Local and species specificForestry inventory, yield table, local surveyVijt1 Average merchantable volume of stratum i, species j, at time t = t1; m3 ha-1Local and species specificForestry inventory, yield table, local surveyVijt2 Average merchantable volume of stratum i, species j, at time t = t2; m3 ha-1Local and species specificForestry inventory, yield table, local surveyWBht Fraction of total above-ground biomass harvested as timber and as fuel-wood at time t (not burned); dimensionlessDefined ex anteEstimated ex ante and ex postXGLTotal unidentifiable grazing land area outside the project boundary that will receive the remaining part of displaced animal populations, e.g. when the pre-project animal owners decide to sell the animals, up to time t*; haProjectEstimated ex ante and ex postxgltTotal unidentifiable area converted to grassland at time t; haProjectEstimated ex ante, monitored ex postCavAverage annual biomass consumed by one average animal; t d.m.yr-1ProjectEstimated ex ante"CG,ikt Annual increase in carbon stock due to biomass growth for stratum i, stand model k, time t; t CO2-e. yr-1ProjectEstimated ex ante, monitored ex postCikt Annual carbon stock change in living biomass for stratum i, stand model k, time t; t CO2-e. yr-1.ProjectEstimated ex ante, monitored ex post"CL,ikt Annual decrease in carbon stock due to biomass loss for stratum i, stand model k, time t; t CO2-e. yr-1 ProjectEstimated ex anteCL PA,tAnnual animal biomass consumption over the project area to be planted at time t; t d.m.yr-1ProjectEstimated ex anteCLcurrentCurrent annual biomass that the grazing areas can produce for animal feeding; t d.m.yr-1ProjectEstimated ex anteCLmaxMaximum annual biomass that the grazing areas can produce for animal feeding; td.m.yr1ProjectEstimated ex anteOther information None. Section III: Monitoring methodology description The proposed new methodology proposes methods for monitoring the following elements: The proposed A/R CDM project activity including the project boundary, forest establishment, and forest management activities; Actual net GHG removals by sinks including changes in carbon stock in above-ground biomass and below-ground biomass, increase in GHG emissions within the project boundary due to site preparation, transportation, thinning and logging and nitrogen fertilization; Leakage due to displacement of agricultural crops, grazing and fuel-wood collection activities; A Quality Assurance/Quality Control plan, including field measurements, data collection verification, data entry and archiving, as an integral part of the monitoring plan of the proposed A/R CDM project activity, to ensure the integrity of data collected. The baseline net GHG removals by sinks are assumed to be constant due to acceptance of the baseline approach 22 (a) in the related baseline methodology. The proposed monitoring methodology stratifies the project area based on local climate, existing vegetation, site class and tree species to be planted with the aid of land use/cover maps, satellite images, soil map, GPS and/or field survey. The proposed methodology uses permanent sample plots to monitor carbon stock changes in living biomass pools. The methodology first determines the number of plots needed in each stratum/sub-stratum to reach the targeted precision level of (10% of the mean at the 90% confidence level. GPS located plots ensure the measuring and monitoring consistently over time. Monitoring project boundary and project implementation: Monitoring of project implementation includes: Monitoring of the project boundary; Monitoring of forest establishment; Monitoring of forest management. The corresponding methodology procedures are outlined below. Monitoring of the boundary of the proposed A/R CDM project activity This is meant to demonstrate that the actual area afforested or reforested conforms with the afforestation or reforestation area outlined in the PDD. The following activities are foreseen: Field surveys concerning the project boundary within which the A/R activity has occurred, site by site; Measuring geographical positions (latitude and longitude of each corner polygon sites) using GPS; Checking whether the afforested/reforested areas are consistent with the eligible areas as defined in the CDM-AR-PDD; If afforestation/reforestation activities fall outside of the project boundary as defined in the CDM-AR-PDD, these lands shall not be accounted as a part of the A/R CDM project activity; Input the measured geographical positions into the GIS system and calculate the implemented area of each stratum and stand; The development of the tree cover shall be monitored periodically all through the crediting period, including through remote sensing as applicable. If tree cover is affected by natural hazards (forest fires, plagues, etc.) or human interventions (harvesting, deforestation) beyond average regional damage levels, location; area of the deforested land and carbon losses shall be identified. These areas shall be treated as separate strata. Similarly, if the planting on certain lands within the project boundary fails these lands will be documented; Monitoring of forest establishment. To ensure that the planting quality conforms to the practice described in AR-CDM-PDD and is well implemented, the following monitoring activities shall be conducted in the first three years after planting: Confirm that site and soil preparations are implemented based on practice documented in PDD. If pre-vegetation is removed, e.g., slash and burn of pre-existing vegetation, emissions associated shall be accounted for (described in section below); Survey and check that species and planting for each stratum are in line with the PDD; Document and justify any deviation from the planned forest establishment. Monitoring of forest management Forest management practices are important drivers of the GHG balance of the project, and thus must be monitored. Practices to be monitored include: Cleaning and site preparation measures: date, location, area, biomass removed and other measures undertaken; Planting: date, location, area, tree species (establishment of the stand models); Thinning: date, location, area, tree species, thinning intensity, volumes or biomass removed; Harvesting: date, location, area, tree species, volumes or biomass removed; Coppicing: date, location, area, tree species, volumes or biomass removed; Fuel wood collection: date, location, area, tree species, volumes or biomass removed; Checking and confirming that harvested lands are re-planted, re-sowed or coppiced as planned and/or as required by forest law; Checking and ensuring that good conditions exist for natural regeneration if harvested lands are allowed to regenerate naturally; Monitoring of disturbances: date, location, area (GPS coordinates and remote sensing, as applicable), tree species, type of disturbance, biomass lost, implemented corrective measures, change in the boundary of strata and stands. Stratification and sampling for ex post calculations The number and boundaries of the strata defined ex ante using the methodology procedure outlined in Section II.2 may change during the crediting period (ex post). For this reason, strata should be monitored periodically. If a change in the number and area of the project strata occurs, the sampling framework should be adjusted accordingly. The methodology procedures for monitoring strata and defining the sampling framework are outlined below. Monitoring of strata 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 participants should present in the AR-CDM-PDD an ex ante stratification of the project area using the methods outlined in Section II.2 and build a geo-referenced spatial data base in a GIS platform for each parameter used for stratification of the project area under the baseline and the project scenario. This geo-referenced spatial database shall be updated periodically due to the following reasons: Unexpected disturbances occurring during the crediting period (e.g. due to fire, pests or disease outbreaks), affecting differently different parts of an originally homogeneous stratum or stand; Forest management (cleaning, planting, thinning, harvesting, coppicing, re-replanting) may be implemented at different intensities, dates and spatial locations than originally planned in the PDD; Eligible land areas as defined in the AR-CDM-PDD not yet under the control of the project participant at the start of the project activity have become under the control of the project participants (see Section II.1, point c); Two different strata may be similar enough to allow their merging into one stratum. If one of the above occurs, ex post stratification may be required. The possible need for ex post stratification shall be evaluated at each monitoring event and changes in the strata should be reported to the DOE for verification. Monitoring of strata and stand boundaries shall be done using a Geographical Information System (GIS), which allows for integrating data from different sources (including GPS coordinates and remote sensing data). The monitoring of strata and stand boundaries is critical for a transparent and verifiable monitoring of the variable Aikt (area of stratum i, stand model k, at time t), which is of outmost importance for an accurate and precise calculation of net anthropogenic GHG removals by sinks. Sampling framework The sampling framework, including sample size, plot size, plot shape and plot location should be specified in the CDM-AR-PDD. Definition of the sample size and allocation among strata Permanent sampling plots will be used for sampling over time to measure and monitor changes in carbon stocks. Permanent sample plots are generally regarded as statistically efficient in estimating changes in forest carbon stocks because typically there is high covariance between observations at successive sampling events. However, it should be ensured that the plots are treated in the same way as other lands within the project boundary, e.g., during site and soil preparation, weeding, fertilization, irrigation, thinning, etc., and should not be destroyed over the monitoring interval. Ideally, staff involved in management activities should not be aware of the location of monitoring plots. Where local markers are used, these should not be visible. The number of sample plots is estimated as dependent on accuracy and costs. It is assumed that the following parameters are from pre-project estimates (e.g. results from a pilot-study) or literature data: ATotal size of all strata (A), e.g. the total project area; haAi Size of each stratum (=  EMBED Equation.3  where tcr is the end of the crediting period); hak1, 2, 3, KP stand models in the project scenarioAiktArea of stratum i, stand model k, time t; haAPSample plot size; hastiStandard deviation for each stratum i; dimensionlessCiCost of establishment of a sample plot for each stratum i; e.g. US$QApproximate average value of the estimated quantity Q, (e.g. wood volume); e.g. m3 ha-1DLPDesired level of precision (e.g. 10%); dimensionlessThen:  EMBED Equation.3  ;  EMBED Equation.3  ;  EMBED Equation.3  ( AUTONUMLGL \e ) where: NMaximum possible number of sample plots in the project areaNiMaximum possible number of sample plots in stratum i EAllowable error With the above information, the sample size (number of sample plots to be established and measured) can be estimated as follows:  EMBED Equation.3  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: n Sample size (total number of sample plots required) in the project areaniSample size for stratum ii1, 2, 3, mSP project scenario (ex post) strataz/2 Value of the statistic z (normal probability density function), for  = 0.1 (implying a 90% confidence level)When no information on costs is available or the costs may be assumed as constant for all strata, then:  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) It is possible to reasonably modify the sample size after the first monitoring event based on the actual variation of the carbon stocks determined from taking the n samples. Sample plot size The plot area a has major influence on the sampling intensity and time and resources spent in the field measurements. The area of a plot depends on the stand density. Therefore, increasing the plot area decreases the variability between two samples. According to Freese (1962), the relationship between coefficient of variation and plot area can be denoted as follows:  EMBED Equation.3  ( AUTONUMLGL \e ) where a1 and a2 represent different sample plot areas and their corresponding coefficient of variation (CV). Thus, by increasing the sample plot area, variation among plots can be reduced permitting the use of small sample size at the same precision level. Usually, the size of plots is between 100 m2 for dense stands and 1000 m2 for open stands. Plot location To avoid subjective choice of plot locations (plot centers, plot reference points, movement of plot centers to more convenient positions), the permanent sample plots shall be located systematically with a random start, which is considered good practice in IPCC GPG-LULUCF. This can be accomplished with the help of a GPS in the field. The geographical position (GPS coordinate), administrative location, stratum and stand, series number of each plots shall be recorded and archived. Also, it is to be ensured that the sampling plots are as evenly distributed as possible. For example, if one stratum consists of three geographically separated sites, then it is proposed to: Divide the total stratum area by the number of plots, resulting in the average area represented by each plot; Divide the area of each site by this average area per plot, and assign the integer part of the result to this site. e.g., if the division results in 6.3 plots, then 6 plots are assigned to this site, and 0.3 plots are carried over to the next site, and so on. Monitoring frequency Monitoring interval depends on the variability in carbon stocks and the rate of carbon accumulation, i.e., the growth rate of trees as of living biomass. Although the verification and certification shall be carried out every five years after the first verification until the end of the crediting period (paragraph32 of decision 19/CP.9), monitoring interval may be less than five years. However, to reduce the monitoring cost, the monitoring intervals shall coincide with verification time, i.e., five years of interval. Logically, one monitoring and verification event will take place close to the end of the first commitment period, e.g. in the second half of the year 2012. Project participants shall determine the first monitoring time, taking into account: The growth rate of trees and the financial needs of the project activity: the later the date of the first verification, the higher will be the amount of net anthropogenic GHG removals by sinks but the lower the financial net present value of a CER; Harvesting events and rotation length: The time of monitoring and subsequent verification and certification shall not coincide with peaks in carbon stocks based on paragraph 12 of Appendix B in decision 19/CP.9. Measuring and estimating carbon stock changes over time The growth of individual trees on plots shall be measured at each monitoring event. Pre-existing (baseline) trees should conservatively and consistently with the baseline methodology not be measured and accounted for. Although non-tree vegetation such as herbaceous plants, grasses, and shrubs can occur, usually with biomass less than 10 percent, there is also non-tree vegetation on degraded lands and the baseline scenario has assumed the zero stock change for this non-tree biomass. Therefore, non-tree vegetation will not be measured and accounted. The omission of non-tree biomass makes the monitoring conservative. Even if the initial site preparation results in a removal of non-tree biomass, there is no risk to over-estimate the removals. The carbon stock changes in living biomass on each plot are then estimated through Biomass Expansion Factors (BEF) method or allometric equations method. Monitoring GHG emissions by sources increased as results of the A/R CDM project activity An A/R CDM project activity may increase GHG emissions, in particular CO2, CH4 and N2O. The list below contains factors that may result in an increase of GHG emissions: Emissions of greenhouse gases from biomass burning for site preparation (slash and burn activity). Changes in GHG emissions caused by these practices can be estimated by monitoring activity data and selecting appropriate emission factors. Calculation of ex post baseline net GHG removals by sinks, if required The baseline carbon stock changes do not need to be monitored after the project is established, because the accepted baseline approach 22(a) assumes continuation of existing changes in carbon pools within the project boundary from the time of project validation. However, if the project participants choose a renewable crediting period, relevant data necessary for determining the renewed baseline, including net greenhouse gas removals by sinks during the crediting period, shall be collected and archived to determine whether the baseline approach and baseline scenario are still valid or have to be updated. Reasons for a possible need for updating may include: National, local and sectoral policies that may influence land use in the absence of the proposed A/R CDM project activity; Technical progresses that may change the baseline approach and baseline scenario; Climate conditions and other environmental factors that may change to such a degree as to significantly change the successional and disturbance processes or species composition, resulting in, e.g., improved climate conditions and/or available seed source would make the natural regeneration possible that is not expected to occur for the current baseline scenario; Significant changes of political, social and economic situation, making baseline approach and the projection of baseline scenario unreasonable; Existing barriers that may be removed, for instance: Removal of existing investment barriers: Local farmers (communities) can afford the high establishment investment in the early stage or have chance to get commercial loans from banks for the reforestation activity; Removal of existing technological barriers: Local farmers (communities) get knowledge and skills for producing high quality seedling, successful tree planting, controlling forest fire, pest and disease, and etc.; Removal of existing institutional barriers (e.g., well-organized institutional instruments to integrate separate households and address technological and financial barriers). Market that may change the alternative land use, e.g., significant price rising of wood and non-woody products would make the degraded land economically attractive in the absence of the proposed A/R CDM project activity; Check that the baseline net GHG removals by sinks are not under-estimated before the crediting period can be renewed using control plots. The carbon stock changes in the baseline scenario can be estimated by measuring carbon stock in the above-ground biomass on control plots respectively at the initial stage and at the end of the crediting period. The control plots shall be established outside the project boundary and serve as proxy and accurately reflect the development of the degraded lands in the absence of the project activity. Measuring the carbon stock change in above-ground biomass is sufficient for the purpose of baseline scenario checking. Data to be collected and archived for the estimation of baseline net GHG removals by sinks Table D: Data to be collected and archived for the estimation of baseline net GHG removals by sinks ID numberData VariableSource of dataData UnitMeasured (m), calculated (c), estimated (e)Recording frequencyProportion of data monitoredComment2.3.01National, local and sectoral policies that may influence land use in the absence of the proposed A/R CDM project activityVariousn.a.CollectedStart and end of the crediting periodAs complete as possible2.3.02Natural and anthropogenic factors influencing land use, land cover and natural regenerationVariousn.a.CollectedStart and end of the crediting periodAs complete as possible2.3.03Stratum IDStratification mapAlpha numeric20 years100%Stratum identification for baseline scenario checking2.3.04Carbon stock in above-ground biomass at the end of the crediting periodCalculated based on baseline plot measurementt CO2-e. yr-1cEnd of the crediting period100% of baseline plotsCalculated based on baseline plot measurement for different strata/sub-strata2.3.05Carbon stock in above-ground biomass at the start of the crediting periodCalculated based on baseline plot measurementt CO2-e. yr-1cStart of the crediting period100% of baseline plotsCalculated based on baseline plot measurement for different strata/sub-strata2.3.06Baseline carbon stock change in above-ground biomassCalculated t CO2-e. yr-1c20 years100%Calculated  Calculation of ex post actual net GHG removal by sinks The actual net greenhouse gas removals by sinks represent the sum of the verifiable changes in carbon stocks in the carbon pools within the project boundary, minus the increase in GHG emissions measured in CO2 equivalents by the sources that are increased as a result of the implementation of an A/R CDM project activity, while avoiding double counting, within the project boundary, attributable to the A/R CDM project activity. The calculations can be performed annually or periodically according to the monitoring plan. Therefore: CACTUAL = CLB  GHGE ( AUTONUMLGL \e ) where: CACTUAL Actual net greenhouse gas removals by sinks; t CO2-e CLB Sum of the changes in living biomass carbon stocks (above- and below-ground); tCO2e GHGE Sum of the increases in GHG emissions by sources within the project boundary as a result of the implementation of an A/R CDM project activity; tCO2e Note: In this methodology equation 66 is used to estimate actual net greenhouse gas removal by sinks for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated. The stock change method should be used to determine annual or periodical values.  EMBED Equation.3  ( AUTONUMLGL \e ) where: CP,LB Sum of the changes in living biomass carbon stocks (above- and below-ground); tCO2-eCP,LB TSum of the changes in living tree biomass carbon stocks (above- and below-ground); tCO2-eEbiomasslossDecrease in the carbon stock in the living biomass carbon pools of non-tree vegetation in the year of site preparation, up to time t*; t CO2-e (as per equation 15)Estimation of changes in the carbon stocks The carbon stock changes in pools of soil organic carbon, litter and dead wood are ignored in this methodology, thus, the verifiable changes in carbon stock equal to the carbon stock changes in above-ground biomass and below-ground biomass within the project boundary, estimated using the following methods and equations:  EMBED Equation.3  ( AUTONUMLGL \e ) where: CP,LB Sum of the changes in living biomass carbon stocks (above- and below-ground); tCO2-e CP,ikt Annual carbon stock change in living biomass for stratum i, stand model k, time t; tCO2eyr-1i 1, 2, 3, & Sps strata of the project activity k1, 2, 3, & K stand modelst1, 2, 3, & t* years elapsed since the start of the A/R project activityand  EMBED Equation.3  ( AUTONUMLGL \e ) where: "CP,ikt Annual carbon stock change in living biomass for stratum i, stand model k, time t; tCO2-e. yr-1"CAB,ikt Annual carbon stock change in above-ground biomass for stratum i, stand model k, timet; tC yr-1"CBB,ikt Annual carbon stock change in below-ground biomass for stratum i, stand model k, timet; tC yr-1The mean change in carbon stocks in above-ground biomass and below-ground biomass per unit area are estimated based on field measurements on permanent plots. Two methods are available: Biomass Expansion Factors (BEF) method and Allometric Equations method. BEF Method Step 1: Measure the diameter at breast height (DBH, at 1.3 m above-ground) and preferably height of all the trees in the permanent sample plots above a minimum DBH. The minimum DBH varies depending on tree species and climate, for instance, the minimum DBH may be as small as 2.5 cm in arid environments where trees grow slowly, whereas it could be up to 10 cm for humid environments where trees grow rapidly (IPCC GPG-LULUCF). Step 2: Estimate the volume of the commercial component of trees based on locally derived equations, then sum for all trees within a plot and express as volume per unit area (e.g., m3/ha). It is also possible to combine Step 1 and Step 2 if there are field instruments (e.g. relascope) that measure volume of each tree directly. Step 3: Choose BEF and root-shoot ratio: The BEF and root-shoot ratio vary with local environmental conditions, species and age of trees, the volume of the commercial component of trees. These parameters can be determined by either developing a local regression equation or selecting from national inventory, Annex 3A.1 Table 3A.1.10 of IPCC GPG LULUCF, or from published sources. If a significant amount of effort is required to develop local BEFs and root-shoot ratios, involving, for instance, harvest of trees, then it is recommended not to use this method but rather to use the resources to develop local allometric equations as described in the allometric method below (refers to Chapter 4.3 in IPCC GPG LULUCF). If that is not possible either, national species specific defaults are for BEF and R can be used. Since both BEF and the root-shoot ratio are age dependent, it is desirable to use age-dependent equations. Stem-wood volume can be very small in young stands and BEF can be very large, while for old stands BEF is usually significantly smaller. Therefore using average BEF value may result in significant errors for both young stands and old stands. It is preferable to use allometric equations, if the equations are available, and as a second best solution, to use age-dependent BEFs (but for very young trees, multiplying a small number for stemwood with a large number for the BEF can result in significant error). Step 4: Converting the volume of the commercial component of trees into carbon stock in above-ground biomass and below-ground biomass via basic wood density, BEF root-shoot ratio and carbon fraction, given by:  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: MCAB,ijt Mean carbon stock in above-ground biomass per unit area for stratum i, species j, timet; t C ha-1MCBB,ijt Mean carbon stock in below-ground biomass per unit area for stratum i, species j, timet; tC ha-1MVijt Mean merchantable volume per unit area for stratum i, species j, time t; m3 ha-1Dj Volume-weighted average wood density; t d.m. m-3 merchantable volumeBEFj Biomass expansion factor for conversion of biomass of merchantable volume to above-ground biomass; dimensionlessCFj Carbon fraction; IPCC default value = 0.5; t C (t d.m.)-1Rj Root-shoot ratio; dimensionlessStep 5: The total carbon stock in living biomass for stratum i, species j, time t is calculated from the area for stratum i, species j, time t and the mean carbon stocks in above-ground biomass and below-ground biomass per unit area, as follows:  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: "CAB,ijt Annual carbon stock change in above-ground biomass for stratum i, species j, time t; tCyr1"CBB,ijt Annual carbon stock change in below-ground biomass for stratum i, species j, time t; tCyr1Aijt Area of stratum i, species j, at time t; hectare (ha)Note: The area of a stratum i planted with species j in stand model k has a time notation because stands with species j will be established (planted) at different dates. MCAB,ijt Mean carbon stock in above-ground biomass per unit area for stratum i, species j, time t; tC ha-1 MCBB,ijt Mean carbon stock in below-ground biomass per unit area for stratum i, species j, time t; tC ha-1 Step 6: The change in carbon stock in living biomass over time is given by:  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: "CAB,ikt Annual carbon stock change in above-ground biomass for stratum i, stand model k, timet; t C yr-1"CBB,ikt Annual carbon stock change in below-ground biomass for stratum i, stand model k, timet; t C yr-1CAB,ijt2 Carbon stock in above-ground biomass for stratum i, species j, calculated at time t = t2; tC CAB,ijt1 Carbon stock in above-ground biomass for stratum i, species j, calculated at time t = t1; tCCBB,ijt2 Carbon stock in below-ground biomass for stratum i, species j, calculated at time t = t2; tC CBB,ijt1 Carbon stock in below-ground biomass for stratum i, species j, calculated at time t = t1; tC T Number of years between monitoring time t2 and t1 (T = t2 t1); yearsjSpecies j (J = total number of species)Allometric method Step 1: Measure the diameter at breast height (DBH, at 1.3 m above ground) and possibly, depending on the form of the equation, height of all the trees in the permanent sample plots above a minimum DBH. The minimum DBH varies depending on tree species and climate, for instance, the minimum DBH may be as small as 2.5 cm in arid environments where trees grow slowly, whereas it could be up to 10 cm for humid environments where trees grow rapidly (IPCC GPG-LULUCF). When first measured all trees should be tagged to permit the tracking of individual trees in plots through time. Where a tree has died, been harvested or can not be found then the biomass at time t2 should be made equal to zero to give the requisite deduction. Step 2: Choose or establish appropriate allometric equations.  EMBED Equation.3  ( AUTONUMLGL \e ) where: TBABj Above-ground biomass of a tree; kg tree-1 fj(DBH,H) An allometric equation for species j linking above-ground tree biomass (kg tree-1 ) to diameter at breast height (DBH) and possibly tree height (H) measured in plots for stratum i, species j, time tThe allometric equations are preferably local-derived and species-specific. When allometric equations developed from a biome-wide database, such as those in Annex 4A.2, Tables 4.A.1 and 4.A.2 of IPCC GPG LULUCF, conservative estimates shall be ensured. The respective procedures and assumptions have to be described in the monitoring plan of the PDD. Also generic allometric equations can be used, as long as it can be proven that they underestimate carbon sequestration. Step 3: Estimate carbon stock in above-ground biomass per tree using selected allometric equations applied to the tree measurements in Step 1  EMBED Equation.3  ( AUTONUMLGL \e ) where: TCABCarbon stock in above-ground biomass per tree; kg C tree-1 TBABjAbove-ground biomass of a tree of species j; kg tree-1 CF Carbon fraction (IPCC default value = 0.5); t C (t d.m.)-1Step 4: Calculate the increment of above-ground biomass carbon accumulation at the tree level. Calculate by subtracting the biomass carbon at time 2 from the biomass carbon at time 1 for each tree.  EMBED Equation.3  ( AUTONUMLGL \e ) where: TCABjTCarbon stock change in above-ground biomass per tree of species j between two monitoring events; kg C tree-1TCABj,t2Carbon stock change in above-ground biomass per tree of species j at monitoring event t2; kg C tree-1TCABj,t1Carbon stock change in above-ground biomass per tree of species j at monitoring event t1; kg C tree-1Step 5: Calculate the increment in above-ground biomass carbon per plot on a per area basis. Calculate by summing the change in biomass carbon per tree within each plot and multiplying by a plot expansion factor which is proportional to the area of the measurement plot. This is divided by 1,000 to convert from kg to t.  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: PCAB,ijTPlot level carbon stock change in above ground biomass in stratum i, species j, between two monitoring events; t C ha-1TCABjTCarbon stock change in above-ground biomass per tree of species j between two monitoring events; kg C tree-1XFPlot expansion factor from per plot values to per hectare valuesAPPlot area; m2trTree (TR = total number of trees in the plot)Step 6: Calculate mean carbon stock change within each stratum. Calculate by averaging across plots in a stratum or stand:  EMBED Equation.3  ( AUTONUMLGL \e ) where: MCABikTMean carbon stock change in above-ground biomass in stratum i, stand model k, between two monitoring events; t C ha-1.PCABijTPlot level mean carbon stock change in above-ground biomass in stratum i, species j, between two monitoring events; t C ha-1.plPlot number in stratum i, species j; dimensionlessPLikTotal number of plots in stratum i, stand model k; dimensionlessjSpecies j (J = total number of species)Step 7: Estimate carbon stock in below-ground biomass using root-shoot ratios and above-ground carbon stock and apply Steps 4 and 5 to below-ground biomass.  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: TCBBjCarbon stock in below-ground biomass per tree of species j; kg C tree-1TCABjCarbon stock in above-ground biomass per tree of species j as calculated in Step 1; kgC tree-1RjRoot-shoot ratio appropriate to increments for species j; dimensionlessTCBBjTCarbon stock change in below-ground biomass per tree of species j between two monitoring events; kg C tree-1PCBB, ijTPlot level carbon stock change in below-ground biomass of species j between two monitoring events; t C ha-1XFPlot expansion factor from per plot values to per hectare values (see equation 80); dimensionlesstrTree (TR = total number of trees in the plot)MCBBikTMean carbon stock change in below-ground biomass for stratum i, stand model k, between two monitoring events; t C ha-1PCBBikTPlot level carbon stock change in below-ground biomass for stratum i, stand model k, between two monitoring events; t C ha-1 pl = plot number in stratum i, stand model k; dimensionlessPLikTotal number of plots in stratum i, stand model k; dimensionlessStep 8: Calculate the annual carbon stock change by dividing the carbon changes between two monitoring events by the number of years between monitoring events.  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: "MCAB,ikt Annual mean carbon stock change in above-ground biomass for stratum i, stand model k, at year t; t C ha-1 yr-1 "MCBB,ikt Annual mean carbon stock change in below-ground biomass for stratum i, stand model k, at year t; t C ha-1 yr-1 MCABikTMean carbon stock change in above-ground biomass for stratum i, stand model k, between two monitoring events; t C ha-1 yr-1 MCBBikTMean carbon stock change in below-ground biomass for stratum i, stand model k, between two monitoring events; t C ha-1 yr-1 TNumber of years between two monitoring events which in this methodology is 5 yearsStep 9: The annual carbon stock change in living biomass for each stratum i, species j, stand modelk, at timet is calculated from the area of each stratum i, species j, stand model k, at time t and the annual mean carbon stock change in above-ground biomass and below-ground biomass per unit area, given by:  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: AiktArea of stratum i, stand model k, at time t; hectare (ha) "CAB,ikt Changes in carbon stock in above-ground biomass for stratum i, stand model k, at time t; tC yr-1 "CBB,ikt Changes in carbon stock in below-ground biomass for stratum i, stand model k, at time t; tC yr-1 "MCAB,iktAnnual mean carbon stock change in above-ground biomass for stratum i, stand model k, at year t; t C ha-1 yr-1 "MCBB,iktAnnual mean carbon stock change in below-ground biomass for stratum i, stand model k, at year t; t C ha-1 yr-1 Note that stand models will most often be one of the strata, and therefore will be included as such rather than as a separate consideration. Estimation of the increase in emissions The increase in GHG emission as a result of the implementation of the proposed A/R CDM project activity within the project boundary can be estimated by:  EMBED Equation.3  ( AUTONUMLGL \e ) where: GHGE Increase in GHG emission as a result of the implementation of the proposed A/RCDM project activity within the project boundary; t CO2-eEBiomassBurn Increase in GHG emission as a result of biomass burning within the project boundary; tCO2-eNote: In this methodology equation 90 is used to estimate the increase in GHG emission for the period of time elapsed between project start (t = 1) and the year t = t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated. 5.2.1 Estimation of EBiomassBurn (GHG emissions from biomass burning) Slash and burn or removal of pre-existing vegetation occurs traditionally in some regions during site preparation before planting and/or replanting, this would result in CO2 and non-CO2 emissions. Step 1: Estimating the above-ground biomass stock per unit area before slash and burn or removal. To be conservative this methodology requires that the highest biomass over slash and burn cycles be applied as the baseline and for calculation of emissions from biomass burning. The degraded land or logged land is usually dominated by young trees/seedling, herbaceous plants and shrubs. . A small frame (either circular or square), usually encompassing about 0.5-1.0 m2 or less, is used to aid this task. The material inside the frame is cut to ground level and weighed. Well-mixed samples are then collected and oven dried to determine dry-to-wet matter ratios. These ratios are then used to convert the entire sample to oven-dry matter. For shrubs and young trees left, destructive harvesting techniques can also be used to measure the above-ground biomass. An alternative approach is to use allometric equations for the trees and shrubs. As long as the trees are larger than the defined minimum diameter for the equation, equations used elsewhere in the project can be applied. For smaller trees it is advised to harvest them with the herbaceous vegetation. If the shrubs are large, it is possible to develop local shrub allometric equations based on variables such as crown area and height or diameter at base of plant or some other relevant variable (e.g., number of stems in multi-stemmed shrubs). The equations would then be based on regressions of biomass of the shrub versus some logical combination of the independent variables. The independent variable or variables would then be measured in the sampling plots (Refers to Chapter 4.3 in IPCC GPG LULUCF). Step 2: Estimating mean proportion of biomass burnt (or harvested) and emission factors. The proportion of biomass burnt can be estimated by sampling after burning. The combustion efficiencies may be chosen from Table 3.A.14 of IPCC GPG-LULUCF. If no appropriate combustion efficiency can be used, the IPCC default of 0.5 should be used. The nitrogen-carbon ratio (N/C ratio) is approximated to be about 0.01. This is a general default value that applies to leaf litter, but lower values would be appropriate for fuels with greater woody content, if data are available. Emission factors for use with above equations are provided in Tables 3.A 15 and 3.A.16 of IPCC GPGLULUCF. Step 3: Estimating of GHG emissions resulted from the slash and burn based on revised IPCC 1996 Guideline for LULUCF and IPCC GPG-LULUCF:  EMBED Equation.3  ( AUTONUMLGL \e ) where: EBiomassBurn Total GHG emission from biomass burning in slash and burn; t CO2-eEBiomassBurn,CO2 CO2 emission from biomass burning in slash and burn; t CO2-eEBiomassBurn, CH4 CH4 emission from biomass burning in slash and burn; t CO2-eand:  EMBED Equation.3  ( AUTONUMLGL \e ) where: Aikt_sb Area of slash and burn for stratum i, stand model k, time t; haBikt Average above-ground biomass stock before burning for stratum i, stand modelk, time t; t d.m. ha-1PBBikt Average proportion of biomass burnt for stratum i, stand model k, time t; dimensionlessCE Average biomass combustion efficiency (IPCC default = 0.1); dimensionlessCF Carbon fraction (IPCC default = 0.5); t C (t d.m.)-1 EMBED Equation.3  ( AUTONUMLGL \e ) where: 12/44 Ration of molecular weights of carbon and CO2; dimensionless16/12 Ration of molecular weights of CH4 and carbon; dimensionlessERCH4Emission ratio for CH4 (IPCC default = 0.012); t CO2-e./t C GWPCH4Global Warming Potential for CH4 (IPCC default = 21 for the first commitment period); t CO2-e/t CH Data to be collected and archived for actual net GHG removals by sinks Table E: Data to be collected and archived for actual net GHG removals by sinks ID numberData VariableSource of dataData unitMeasured (m) calculated (c) estimated (e)Recording frequencyProportion of data monitoredComment2.1.1.01DLPDesired level of precision (e.g. 10%)%DefinedBefore the start of the project100%For the purpose of QA/QC and measuring and monitoring precision control2.1.2.02PBBiktAverage proportion of biomass burnt for stratum i, stand model k, time tMeasured after slash and burnDimensionlessmAnnually100%Sampling survey after slash and burn2.1.1.03PLIDSample plot ID (1,2,3,pl, )Project and plot map, GISAlpha numericDefinedBefore the start of the project100%Numeric series ID will be assigned to each permanent sample plot2.1.1.04PLikTotal number of plots in stratum i, stand model kField measurementDimensionlessm5-year100%2.1.1.05RjRoot-shoot ratioLocal-derived, national inventory,Dimensionlesse5 year100% of sampling plotsLocal-derived and species-specific value have the priority2.1.1.0616/12Ratio of molecular weights of CH4 and carbon; Universal constantDimensionlessUniversal constant2.1.1.0744/12Ratio of molecular weights of carbon and CO2; dimensionlessUniversal constantDimensionlessUniversal constant2.1.1.0844/28Ratio of molecular weights of N2O and nitrogen; dimensionlessUniversal constantDimensionlessUniversal constant2.1.1.09Confidence level (e.g. 90%)AR-CDM-PDD%DefinedBefore the start of the project100%For the purpose of QA/QC and measuring and monitoring precision control2.1.1.10ATotal size of all strata (A), e.g. the total project areaGIS or/and GPSHectaresmBefore the start of the project and adjusted thereafter every 5-year100%2.1.1.11AiArea of each stratumGIS or/and GPSHectaresmBefore the start of the project and adjusted thereafter every 5-year100%2.1.1.13AiktArea of stratum i, stand model k, at time t; GIS or/and GPSHectaresmYearly100%Measured for different strata and stands2.1.1.14AB,ikt_sbArea of slash and burn in stratum i, stand model k, at time t MeasurementHectaresmYearly100%Measured for different strata and stands2.1.1.15APSample plot areaField measurementm2m5-year100%2.1.1.16BEFBiomass expansion factor (BEF)Local-derived, national inventory, IPCC GPG LULUCFDimensionlesse5 year100% of sampling plotsLocal-derived and species-specific value have the priority (IPCC default in LULUCF GPG 2003, Table 3A.1.10)2.1.1.17BijtAverage above-ground biomass stock before burning for stratum i, species j, timetField measurementt d.m. ha-1mBefore burningSample plots2.1.1.18N/C ratioNitrogen/carbon ratioLiteratureDimensionlesseOnce per species or group of speciesIPCC default value (0.01) is used if no appropriate value2.1.1.19CAB,ijtCarbon stock in above-ground biomass for stratumi, species j, time tCalculationst Cc5-year100%2.1.1.20CACTUALActual net greenhouse gas removals by sinks;Calculationst CO2-e.c5-year100%2.1.1.21CBB,ijtCarbon stock in below-ground biomass for stratumi, species j, time tCalculationst Cc5-year100%2.1.1.22CEAverage biomass combustion efficiencyGPG LULUCF, National inventoryDimensionlesseBefore the start of the project100%IPCC default value (0.5) is used if no appropriate value2.1.1.23CFCarbon fractionLocal, national, IPCCt C (t d.m.)-1eOnce per crediting periodLocal-derived and species-specific value have the priority (IPCC default = 0.5)2.1.1.24CFjCarbon fraction of species jLocal, national, GPG for LULUCF IPCCt C (t d.m.)-2eOnce per species100% of species or species groupLocal-derived and species-specific value have the priority (IPCC default = 0.5)2.1.1.25CiCost of establishment of a sample plot for each stratum iMeasurementUS$ or local currencym5-years100%2.1.1.28DBHDiameter at breast height of living and standing dead treesPlot measurementcm (living/dead)m5 year100% trees in plotsMeasuring at each monitoring time per sampling method2.1.1.29DjWood density of species jLocal-derived, national inventory, IPCC GPG LULUCFt d.m. m-3e5 year100% of sampling plotsLocal-derived and species-specific value have the priority2.1.1.30DAverage wood densityLocal-derived, national inventory, IPCC GPG LULUCFt d.m. m-3e5 year100% of sampling plotsLocal-derived and species-specific value have the priority2.1.1.31EAllowable errorCalculationsDepends on the variable calculatedc5-year100% of the variables2.1.1.32EBiomassBurnIncrease in GHG emission as a result of biomass burning within the project boundaryCalculationst CO2-e.c5-year100%2.1.1.33EBiomassBurn, CH4CH4 emission from biomass burning in slash and burnCalculationst CO2-e.c5-year100%2.1.1.34EBiomassBurn, N2ON2O emission from biomass burning in slash and burnCalculationst CO2-e.c5-year100%2.1.1.35EBiomassBurn,CO2CO2 emission from biomass burning in slash and burnCalculationst CO2-e.c5-year100%2.1.1.40ERN20Emission ratio for N2OLiteratureDimensionlesseYearly(IPCC default = 0.007)2.1.1.41ERCH4Emission ratio for CH4 LiteratureDimensionlesseYearly(IPCC default = 0.012)2.1.1.42fj(DBH,H)Allometric equation for species j linking above-ground tree biomass (kg tree-1 ) to diameter at breast height (DBH) and possibly tree height (H) measured in plots for stratum i, speciesj, time tLiterature and/or field measurementskg tree-1m-e-cOnce per speciesfor all major species or group of speciesUse local/global equations validated for local conditions2.1.1.46GHGEIncrease in GHG emission as a result of the implementation of the proposed A/R CDM project activity within the project boundary Calculationst CO2-ec5-year100%2.1.1.47GWPCH4Global Warming Potential for CH4IPCC literature - EB decisionseOnce per commitment period (IPCC default = 21)2.1.1.48GWPN2OGlobal Warming Potential for N2O IPCC literature - EB decisionseOnce per commitment period(IPCC default = 310)2.1.1.49HijtAnnually harvested volume and fuel wood for stratum i, species j, at time t Harvesting statisticsm3cAnnually100% standsAnnually recorded2.1.1.50iIDStratum iD (1, 2, 3, mSP project scenario (ex post) strata)Stand map, GISAlpha numericDefinedAt stand establishment100%Each stand has a particular year to be planted under each stratum2.1.1.51IDiktStand IDStand map, GISAlpha numericDefinedAt stand establishment100%Each stand has a particular year to be planted under each stratum2.1.1.52lat/longPlot locationProject and plot map and GPS locating, GISm5 years100%Using GPS to locate before start of the project and at time of each field measurement2.1.1.53MCAB,ijtMean carbon stock in above-ground biomass per unit area for stratum i, species j, time tCalculationst C ha-1c5-year100%2.1.1.54MCBB,ijtMean carbon stock in below-ground biomass per unit area for stratum i, species j, time tCalculationst C ha-1c5-year100%2.1.1.55MVijtMean merchantable volume per unit area for stratum i, species j, time tm3 ha-1m35 year100% of sampling plotsCalculated from 2.1.1.13 and possibly 2.1.1.15 using local-derived equations, or directly measured by field instrument2.1.1.56NMaximum possible number of sample plots in the project area CalculationsDimensionlessc5-years100%2.1.1.57nSample size (total number of sample plots required) in the project area CalculationsDimensionlessc5-years100%2.1.1.58NiMaximum possible number of sample plots in stratum i CalculationsDimensionlesscBefore the start of the project and adjusted thereafter every 5-year100%2.1.1.59niSample size for stratum i CalculationsDimensionlesscBefore the start of the project and adjusted thereafter every 5-year100%Calculated for each stratum 2.1.1.64nTRPLiktNumber of trees in the sample plotPlot measurementNumberm5 years100% trees in plotsCounted in plot measurement2.1.1.66DLPDesired level of precision (e.g. 10%)%DefinedBefore the start of the project100%For the purpose of QA/QC and measuring and monitoring precision control2.1.1.67PBBiktProportion of biomass burntMeasured after slash and burnDimensionlessmAnnually100%Sampling survey after slash and burn2.1.1.68PBBiktAverage proportion of biomass burnt for stratum i, stand model k, time tField estimates or literatureDimensionlesseBefore burningSample plotsUsed for estimating numbers of sample plots of each stratum and stand, as necessary2.1.1.69PLIDSample plot ID (1, 2, 3, pl, )Project and plot map, GISAlpha numericDefinedBefore the start of the project100%Numeric series ID will be assigned to each permanent sample plot2.1.1.70PLikTotal number of plots in stratum i, stand model kField measurementDimensionlessm5-year100%2.1.1.71RjRoot-shoot ratioLocal-derived, national inventoryDimensionlesse5 year100% of sampling plotsLocal-derived and species-specific value have the priority2.1.1.72stiStandard deviation for each stratum i; dimensionlesseAt each monitoring event100%Used for estimating numbers of sample plots of each stratum and stand, as necessary2.1.1.73TBABjAbove-ground biomass of a treeCalculationskg dry matter tree-1c5-year100%2.1.1.74TCABjCarbon stock in above-ground biomass per tree of species jCalculationskg C tree-1c5-year100%2.1.1.75tIDAge of plantation (1, 2, 3, years)GISyearmAt stand establishment100%Counted since the planted year2.1.1.76trIDTree ID (1, 2, 3, tr TR = total number of trees in the plot)Field measurementDimensionlessm5-year100%2.1.1.77XFPlot expansion factor from per plot values to per hectare values )CalculationsDimensionlessc5-year100%2.1.1.78z/2Value of the statistic z (normal probability density function), for  = 0.1 (implying a 90% confidence level)Statistic bookDimensionlessm5-years0%2.1.1.79"CAB,ijtAnnual carbon stock change in above-ground biomass for stratum i, species j, time t; Calculationst C yr-1c5-year100%2.1.1.80"CAB,iktAnnual carbon stock change in above-ground biomass for stratum i, stand model k, time t; Calculationst C yr-1c5-year100%2.1.1.81"CBB,ijtAnnual carbon stock change in below-ground biomass for stratum i, species j, time t; Calculationst C yr-1c5-year100%2.1.1.82"CBB,iktAnnual carbon stock change in below-ground biomass for stratum i, stand model k, time t; Calculationst C yr-1c5-year100%2.1.1.83CLB,iktAnnual carbon stock change in living biomass for stratum i, stand modelk, time tCalculationst CO2-e. yr-1c5-year100%2.1.1.84CP,LBSum of the changes in living biomass carbon stocks (above- and below-ground)Calculationst CO2-ec5-year100%2.1.1.85MCABikTMean carbons stock change in above-ground biomass stratum i, stand model k, between two monitoring eventsCalculationst C ha-1c5-year100%2.1.1.86MCABiktMean carbons stock change in above-ground biomass stratum i, stand model k, between two monitoring eventsCalculationst C ha-1c5-year100%2.1.1.87MCBB,iktMean carbons stock change in below-ground biomass stratum i, stand model kCalculationst C ha-1c5-year100%2.1.1.88MCBBikTMean carbons stock change in below-ground biomass stratum i, stand model k, between two monitoring eventsCalculationst C ha-1c5-year100%2.1.1.89PCAB,ijTPlot level mean carbon stock change in above-ground biomass ins stratum i, species j between two monitoring eventsCalculationst C ha-1c5-year100%2.1.1.90PCBB,ijTPlot level mean carbon stock change in above-ground biomass in stratum i, species j between two monitoring eventsCalculationst C ha-1c5-year100%2.1.1.91TCABjtCarbon stock change in above-ground biomass per tree of species j in year tCalculationskg C tree-1c5-year100%2.1.1.92TCABjTCarbon stock change in above-ground biomass per tree of species j between two monitoring eventsCalculationskg C tree-1c5-year100%2.1.1.93TCBBjtCarbon stock change in below-ground biomass per tree of species j in year t Calculationskg C tree-1c5-year100%2.1.1.94TCBBjTCarbon stock change in below-ground biomass per tree of species j between two monitoring events Calculationskg C tree-1c5-year100% Leakage For the type of A/R CDM project activity to which this methodology applies, leakage shall be estimated as follows:  EMBED Equation.3  ( AUTONUMLGL \e ) Note: In this methodology equation 95 is used to estimate leakage for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated. Estimation of LKActivityDisplacement (leakage due to activity displacement) Leakage due to activity displacement is estimated as follows:  EMBED Equation.3  EMBED Equation.3  EMBED Equation.3  ( AUTONUMLGL \e ) EMBED Equation.3  where: LKActivityDisplacement Leakage due to activity displacement; t CO2-eLKconversionLeakage due to conversion of forest to non-forest; t CO2-eLK fuel-woodLeakage due to the displacement of fuel-wood collection; t CO2-eAs a result of the A/R CDM project activity, agricultural activities may be displaced permanently or temporarily outside the project boundary. This activity shifting or activity displacement may result in leakage in the immediate years after the start of the project activity when activities are displaced to areas outside the project boundary. LKconversion occurs in two ways: Conversion for grazing; Conversion for cropland. Therefore:  EMBED Equation.3  ( AUTONUMLGL \e ) where: LKconv-graz Leakage resulting from the conversion for grazing LKconv-crop Leakage resulting from the conversion for croplandEstimation of LKconv-graz (Leakage due to conversion of land to grazing land) Leakage due to conversion of land to grazing land is not attributable to the A/R CDM project activity if the conversion of land to grazing land occurs 5 years after the last measure taken to reduce animal populations in the project area. Monitoring of leakage due to the conversion of land to grazing land is therefore necessary only up to the fifth year after the last measure taken to reduce animal populations in the project area. Step 1: Monitor the grazing control measures specified in the AR-CDM-PDD. This is necessary to establish the actual date of the last measure taken to control animal grazing. Monitoring of leakage due to conversion of land to grazing land will not be necessary 5 years after this date because any conversion of land to grazing land would not be reasonably attributable to the A/R CDM project activity. Step 2: For each verification period, estimate the average animal population size present in the project area to estimate the number of animals displaced outside the project boundary. Monitoring can be done by periodically surveying the project area or a randomly selected sample of discrete areas as part of the project area and by interviewing the animal owners.  EMBED Equation.3  ( AUTONUMLGL \e ) where: Naoutside,tNumber of animals displaced outside the project area at year t; dimensionlessNaBL Ex ante estimated pre-project number of animals from the different livestock groups that would be grazing in the project area under the baseline scenario; dimensionless. This estimate is fixed for the entire crediting period and is specified in the ARCDMPDDNaAR,tMonitored number of animals present in the project area at year t; dimensionlessIf: NaBL < NaAR,t then, it can be assumed that the AR-CDM project activity has not displaced grazing animal populations. Leakage due to conversion of land to grazing land can be set as zero (LKconversion = 0) and no further monitoring step is needed; NaBL > NaAR,t then it is necessary to monitor the animal populations in the EGL areas specified in the AR-CDM-PDD. Step 3: For each verification period, estimate the average animal population size displaced in the EGL areas specified in the AR-CDM-PDD by periodically surveying these areas and interviewing their owners.  EMBED Equation.3  ( AUTONUMLGL \e ) where: dNaEGLtNumber of animals displaced in EGL areas at time t; dimensionlessNaEGL,tNumber of animals present in the sampled EGL areas at time t; dimensionlessNaEGL,t=1Number of animals present in the sampled EGL areas at time t=1, as specified in the AR-CDM-PDD; dimensionlessSFREGLFraction of sampled EGL areas sampled with respect to total, as specified in the AR-CDM-PDD; dimensionlessIf: NaBL < (NaAR,t + dNaEGL,t) then, it can be assumed that the animal populations displaced due to the AR CDM project activity have not occasioned leakage due to conversion of land to grazing land (LKconversion = 0) and no further monitoring step is needed; NaBL > (NaAR,t + dNaEGL,t) then it is necessary to monitor the animal populations in the NGL areas specified in the AR-CDM-PDD. Step 4: For each verification period, estimate the average animal population size displaced in the NGL areas specified in the AR-CDM-PDD by periodically surveying these areas and interviewing their owners.  EMBED Equation.3  ( AUTONUMLGL \e ) where: dNaNGLtNumber of animals displaced in NGL areas at time t; dimensionlessNaNGL,tNumber of animals present in the sampled NGL areas at time t; dimensionlessNaNGL,t=1Number of animals present in the sampled NGL areas at time t = 1, as specified in the AR-CDM-PDD; dimensionlessSFRNGLFraction of sampled NGL areas sampled with respect to total, as specified in the ARCDMPDD; dimensionlessIf: NaBL < (NaAR,t + dNaEGL,t + dNaNGL,t) then, it can be assumed that AR-CDM project activity has not displaced animal population to unidentified areas and leakage due to conversion of non-grassland to grassland in unidentified XGL areas can be set as zero (LKXGL= 0); NaBL > (NaAR,t + dNaEGL,t+ dNaNGL,t) then it is necessary to estimate the animal populations displaced in XGL areas as follows:  EMBED Equation.3  ( AUTONUMLGL \e ) Step 5: Estimate leakage due to displacement of grazing activities as follows: LKconv-graz = LKNGL + LKXGL ( AUTONUMLGL \e ) where: LKNGLLeakage due to conversion of non-grassland to grassland in NGL areas under the control of the animal owners; t CO2-eLKXGLLeakage due to conversion of non-grassland to grassland in unidentified XGL areas; tCO2-e Estimation of LKNGL  EMBED Equation.3  ( AUTONUMLGL \e ) where: LKNGLLeakage due to conversion of non-grassland to grassland in NGL areas; t CO2-edNaNGLtnumber of animals displaced in NGL areas at time t as estimated in Step 4; dimensionlessaLKNGLAverage leakage due to conversion of non-grassland to grassland per displaced animal in NGL areas as estimated ex ante in the AR-CDM-PDD; t CO2-e. animal-1Estimation of LKXGL  EMBED Equation.3  ( AUTONUMLGL \e ) where: LKXGLLeakage due to conversion of non-grassland to grassland in XGL areas; t CO2-edNaXGLtNumber of animals displaced in XGL areas at time t as estimated in Step 4; dimensionlessaLKXGLAverage leakage due to conversion of non-grassland to grassland per displaced animal in XGL areas as estimated ex ante in the AR-CDM-PDD; t CO2-e animal-1Estimation of LKconv-crop (Leakage due to conversion of land to crop land, based on area of conversion) Leakage through land conversion due to activity displacement should be monitored through sampling the households and communities displaced from land by the project. However, leakage due to conversion of land is not attributable to the A/R CDM project activity if the conversion of land occurs 5 or more years after the displacement of the activity to areas outside the project boundary. Leakage estimation includes monitoring households with identifiable areas of land conversion and conservatively applying a deforestation area to households with unidentifiable areas of land conversion. The type and schedule of measures to be taken to prevent conversion of land outside the project boundary should be described in the AR-CDM-PDD and its implementation monitored. LKconv-crop=CSAD CSb ( AUTONUMLGL \e ) where: CSADLocally derived carbon stock (including all the five eligible carbon pools; t CO2-e. ha-1) of area of land on which activities shifted; t CO2-e ha-1CSbCarbon stock of baseline; t CO2-e ha-1Case 1: CSAD < CSb Leakage due to displacement for cropland can be set as zero if the carbon stock on the land to which crops are displaced is less than the carbon stock from which they originated under the baseline scenario. Lconv-crop = 0, if CSAD < CSb ( AUTONUMLGL \e ) Case 2: CSAD > CSb Step 0: Determine if leakage analysis will take place at the household or community level. Household level analysis should only take place in project areas where households have clear land ownership or tenure. Household level T0: Before start of project activities Step 1: Record the number of households occupying land inside the project boundary (TNHH). Randomly select 10% of the households (or a minimum of 30) to be sampled. Step 2: Measure area of land within project boundaries each sampled household will be displaced from due to project activities (TACPh). T1: Return one year after activity displacement and record land conversion outside project area Step 3: Classify sampled households as either having identifiable or unidentifiable converted lands. Households which have moved from the area or which cannot be found should be placed in the unidentifiable households category. Step 4: Measure area of identifiable land each household has converted since displacement of pre-project activities (IAChi). Step 5: Classify each area of identifiable converted land into a pre-conversion land cover stratum. Step 6: Measure the carbon stock (including all 5 pools) in each land cover stratum using methods from IPCC GPG-LULUCF chapter 4.3. Step 7: Determine the mean conservative forest biomass stock for the project region ( EMBED Equation.3 ), if no mean regional stock data exists, use mean national stock reported in IPCC GPG-LULUCF (Table3A.1.4). Step 8: Calculate the leakage using the following equations:  EMBED Equation.3  ( AUTONUMLGL \e ) and:  EMBED Equation.3  ( AUTONUMLGL \e ) where: LKconv-cropLeakage due to conversion of land to cropland attributable to displacement (activity shifting); t CO2-eIAChiIdentifiable areas converted by household hh in stratum i; hectaresTACPhTotal area of cropland planted that is owned by household hh; hectareshh1,2,3.Hh households; dimensionlessi1,2,3.I strata; dimensionlessCSiLocally derived carbon stock of identified lands (including all the five eligible carbon pools) of stratum i; t CO2-e ha-1 EMBED Equation.3 Locally derived average carbon stock of unidentified lands (including all five eligible carbon pools); t CO2-e ha-1SFSampling factor of household; dimensionlessTNHHTotal number of households using project lands in baseline; dimensionlessSHHsampled households, number of households sampled for LKconv-crop; dimensionlessT5: Return after five years and record land conversion outside project area by repeating Steps 3-8. Community level T0: Before start of project activities: Step 1: Record the number of communities occupying land inside the project boundary. Randomly select 10 % of the communities (or a minimum of 10 communities) to be sampled. Step 2: Measure total area of cropland within project boundaries from which pre-project activities in each sampled community will be displaced (TACPc). Step 3: Calculate the total number of households within each selected community (TNHHc). Step 4: Randomly select 10 % of households (or a minimum of 10 households) to be sampled within selected communities. T1: Return one year after activity displacement and record land conversion outside project area: Step 5: Interview community members to estimate the area of identifiable land that each sampled community will convert due to displacement of pre-project activities (IAChc). Step 6: Classify the estimated area of identifiable land that may be converted within the community into a pre-conversion land cover stratum. Step 7: Estimate the carbon stock (including all 5 pools) in each land cover stratum using methods detailed in IPCC GPG-LULUCF chapter 4.3 (CSi). Step 8: Determine the mean conservative forest biomass stock for the project region ( EMBED Equation.3 ) for application to unidentified areas. Step 9: Calculate the leakage using the following equations:  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e )  EMBED Equation.3  ( AUTONUMLGL \e ) where: LKconv-cropLeakage due to conversion of land to cropland attributable to displacement (activity shifting); t CO2-eLKconv-crop,cLeakage due to conversion of land to cropland attributable to displacement (activity shifting) in community c; t CO2-eTACPTotal area of land on which pre-project activities were displaced due to project activities; hectaresTACPcTotal area of land on which pre-project activities were displaced due to project activities in community c; hectaresIAChciIdentifiable areas converted of stratum i by household hh in community c; hectaresCSiLocally derived carbon stock (including all eligible carbon pools) of stratum i; tCO2e.ha-1 EMBED Equation.3 Locally derived average carbon stock of unidentified lands (including all five eligible carbon pools); t CO2-e. ha-1TNHHcTotal number of households using project lands in baseline in community c; dimensionlessSHHcSampled households in community c, number of households sampled for leakage by activity shifting; dimensionlessSFcSampling factor for community c; dimensionlessc1,2,3C, communities; dimensionlessi1,2,3.I, strata; dimensionlesshh1,2,3, Hhc, households in community c; dimensionlessEstimation of LK fuel-wood (Leakage due to displacement of fuel-wood collection) Step 1: For each verification period, estimate the average fuel-wood collection in the project area to estimate the volume of fuel-wood gathering displaced outside the project boundary. Monitoring can be done by periodically interviewing households, through a Participatory Rural Appraisal (PRA) or field-sampling.  EMBED Equation.3  ( AUTONUMLGL \e ) where: FGoutside,tVolume of fuel-wood gathering displaced outside the project area at year t; m3 yr-1FGBL Average pre-project annual volume of fuel-wood gathering in the project area estimated ex ante and specified in the AR-CDM-PDD; m3 yr-1FGAR,tVolume of fuel-wood gathered in the project area according to monitoring results; m3yr-1Step 2: In the NGL areas specified in the AR-CDM-PDD for monitoring of displaced animal grazing, monitor the volume of fuel-wood gathering that is supplied to pre-project fuel-wood collectors and/or charcoal producers (FGNGL,t ). Step 3: Leakage due to displacement of fuel-wood collection can be set as zero (LK fuel-wood = 0) under the following circumstances: FGBL < FGAR,t; LK fuel-wood< 2% of actual net GHG removals by sinks (See EB 22, Annex 15). If one of the above assumptions was made in the AR-CDM-PDD, it is necessary to monitor FGARt and/or FGNGLt to prove that the assumption is still valid. In all other cases, leakage due to displacement of fuel-wood collection shall be estimated as follow (IPCC GPG-LULUCF - Equation 3.2.8):  EMBED Equation.3  ( AUTONUMLGL \e ) FGt = FGoutside,t FGNGL, t ( AUTONUMLGL \e ) where: LK fuel-woodLeakage due to displacement of fuel-wood collection up to year t*; t CO2-eFGtVolume of fuel-wood gathering displaced in unidentified areas; m3 yr-1FGoutside,tVolume of fuel-wood gathering displaced outside the project area at year t as per Step 1; m3 yr-1FGNGL,tMonitored volume of fuel-wood gathering in NGL areas and supplied to pre-project fuel-wood collectors and/or charcoal producers as per Step 2; m3 yr-1DAverage basic wood density; t d.m. m-3 (See IPCC GPG-LULUCF - Table3A.1.9)BEF2Biomass expansion factor for converting volumes of extracted round-wood to total above-ground biomass (including bark); dimensionless Table 3A.1.10CFCarbon fraction of dry matter (default = 0.5); t C (t d.m.)-144/12Ratio of molecular weights of carbon and CO2; dimensionless Data to be collected and archived for leakage Table F: Data to be collected and archived for leakage ID numberData VariableSource of dataData unitMeasured (m) calculated (c) estimated (e)Recording frequencyProportion of data monitoredComment3.1.0144/12Ration of molecular weights of carbon and CO2; dimensionlessUniversal constantDimensionlessUniversal constant3.1.02aLKNGLAverage leakage due to conversion of non-grassland to grassland per displaced animal in NGL areas AR-CDM-PDDt CO2 -e. animal-1c - eEx ante in AR-CDM-PDDSFRNGLEx ante estimate in the AR-CDM-PDD3.1.03aLKXGLAverage leakage due to conversion of non-grassland to grassland per displaced animal in XGL areas AR-CDM-PDDt CO2 -e. animal-1c - eEx ante in AR-CDM-PDDEx ante estimate in the AR-CDM-PDD3.1.05BEF2Biomass expansion factor (BEF)Local-derived, national inventory, IPCC GPG LULUCFDimensionlesse5 year100% of sampling plotsLocal-derived and species-specific value have the priority (IPCC default in LULUCF GPG 2003, Table3A.1.10)3.1.06cCommunity index (C=total number of communities)DimensionlessDefinedYears 0, 1 and 53.1.07CFjCarbon fraction of dry matter of species jLiterature, own studiest C (t d.m.)-1eOnce per species or group of species100%Local/national data or IPCC default (= 0.5)3.1.08CSiLocally derived carbon stock of identified lands (including all five eligible carbon pools) of stratum iField measurementt CO2-e. ha-1mYears 0, 1 and 53.1.09 EMBED Equation.3 Locally derived average carbon stock of unidentified lands (including all five eligible carbon pools)Field measurementt CO2-e. ha-1mYears 0, 1 and 53.1.11DjWood density of species jLocal-derived, national inventory, IPCC GPG LULUCFt d.m. m-3e5 year100% of sampling plotsLocally derived and species-specific value have the priority3.1.12dNaEGLtNumber of animals displaced in EGL areas at time t CalculationsDimensionlesscYearly100%3.1.13dNaNGLtNumber of animals displaced in NGL areas at time t as estimated in Step4CalculationsDimensionlesscYearly100%3.1.14dNaXGLtnumber of animals displaced in XGL areas at time t as estimated in Step4CalculationsDimensionlesscYearly100%3.1.17FGAR,tVolume of fuel-wood gathered in the project area according to monitoring resultsField samplingm3 yr--1mYearlySFRPAfw3.1.18FGBLAverage pre-project annual volume of fuel-wood gathering in the project area estimated ex ante and specified in the ARCDMPDDAR-CDM-PDDm3 yr--1c - eEx ante in AR-CDM-PDDEx ante estimate in the AR-CDM-PDD3.1.19FGNGL,tMonitored volume of fuel-wood gathering in NGL areas and supplied to pre-project fuel-wood collectors and/or charcoal producers as per Step 2Field measurementsm3 yr--1mYearlySFRNGL3.1.20FGoutside,tVolume of fuel-wood gathering displaced outside the project area at year t as per Step 1Calculationsm3 yr--1cYearly100%3.1.21FGtVolume of fuel-wood gathering displaced in unidentified areasCalculationsm3 yr--1cYearly100%3.1.24hhHousehold index (Hh=total number of households)DefinedYears 0, 1 and 53.1.25iStrata index (S=total number of strata)DimensionlessDefinedYears 0, 1 and 53.1.26IAChiIdentifiable areas converted by household hh in stratum IField measurementhamYears 0, 1 and 510% or at least 30 households3.1.27IAChciIdentifiable areas converted of stratum i, by household hh in community cField measurementhamYears 0, 1 and 510% or at least 30 households3.1.29LKTotal project leakageCalculationst CO2-e.cYearly100%3.1.30LK fuel-woodLeakage due to the displacement of fuel-wood collectionCalculationst CO2-e.cYearly100%3.1.31LKActivityDisplacementLeakage due to activity displacementCalculationst CO2-e.cYearly100%3.1.32LKconversionLeakage due to conversion of forest to non-forest; tCO2-e.Calculationst CO2-e.cYearly100%3.1.33LKconv-grazLeakage resulting from the conversion for grazingCalculationst CO2-e.cYearly3.1.34LKconv-cropLeakage resulting from the conversion for croplandCalculationt CO2-e.cYears 0, 1 and 510% or at least 30 households or 10% of communities (or at least 10), 10% of households per community or at least 103.1.35LKconv-crop,cLeakage due to conversion of land to cropland attributable to displacement (activity shifting) in community cCalculationt CO2-e.cYears 0, 1 and 510% of communities (or at least 10), 10% of households per community or at least 103.1.37LKNGLLeakage due to conversion of non-grassland to grassland in NGL areasCalculationst CO2-e.cYearly100%3.1.42LKXGLLeakage due to conversion of non-grassland to grassland in XGL areas Calculationst CO2-e.cYearly100%3.1.43NaAR,tMonitored number of animals present in the project area at year tField measurementsDimensionlessmYearlySFRPAga3.1.44NaBLEex ante estimated pre-project number of animals from the different livestock groups that would be grazing in the project area under the baseline scenario AR-CDM-PDDDimensionlesseEx ante in AR-CDM-PDDSFRPAgaThis estimate is fixed for the entire crediting period and is specified in the AR-CDM-PDD3.1.45NaEGL,tNumber of animals present in the sampled EGL areas at time tField measurementsDimensionlessmYearlySFREGL3.1.46NaEGL,t=1Number of animals present in the sampled EGL areas at time t=1, as specified in the AR-CDM-PDDAR-CDM-PDDDimensionlessc - eEx ante in AR-CDM-PDDEx ante estimate in the AR-CDM-PDD3.1.47NaNGL,tNumber of animals present in the sampled NGL areas at time tField measurementsDimensionlessmYearlySFRNGL3.1.48NaNGL,t=1Number of animals present in the sampled NGL areas at time t=1, as specified in the AR-CDM-PDDAR-CDM-PDDDimensionlessc - eEx ante in AR-CDM-PDDEx ante estimate in the AR-CDM-PDD3.1.49Naoutside,tNumber of animals displaced outside the project area at year tCalculationsDimensionlesscYearly100%3.1.52SFSampling factor of household hhCalculationsDimensionlesscYears 0, 1 and 510% or at least 30 households3.1.53SFcSampling factor of household cCalculationsDimensionlesscYears 0, 1 and 510% or at least 30 households3.1.54SFREGLFraction of sampled EGL areas sampled with respect to totalCDM-AR-PDDDimensionlessDefined using statistical criteriaEx ante in AR-CDM-PDDEx ante estimate in the AR-CDM-PDD3.1.55SFRNGLFraction of sampled NGL areas sampled with respect to totalCDM-AR-PDDDimensionlessDefined using statistical criteriaEx ante in AR-CDM-PDDEx ante estimate in the AR-CDM-PDD3.1.56SFRPFraction of sampled project areas sampled fencing postsCDM-AR-PDDDimensionlessDefined using statistical criteriaEx ante in AR-CDM-PDDEx ante estimate in the AR-CDM-PDD3.1.57SFRPAfwFraction of sampled project areas sampled for fuel-wood collectionCDM-AR-PDDDimensionlessDefined using statistical criteriaEx ante in AR-CDM-PDDEx ante estimate in the AR-CDM-PDD3.1.58SFRPAgaFraction of sampled project areas sampled for grazing animalsCDM-AR-PDDDimensionlessDefined using statistical criteriaEx ante in AR-CDM-PDDEx ante estimate in the AR-CDM-PDD3.1.59SHHSampled households, number of householdsField measurementDimensionlessDefinedYear 010% or at least 30 households3.1.60SHHcSampled households in community cField measurementDimensionlessDefinedYear 010% of communities (or at least 10), 10% of households per community or at least 103.1.61TACPTotal area of land on which pre-project activities were displaced due to project activitiesField measurementhamYear 010% or at least 30 households3.1.62TACPcTotal area of cropland planted that is owned by community cField measurementhamYear 010% of communities (or at least 10), 10% of households per community or at least 103.1.63TACPhTotal area of cropland planted that is owned by household hhField measurementhamYear 010% or at least 30 households3.1.64TNHHTotal number of households using project lands in baselineField measurementDimensionlessDefinedYear 010% or at least 30 households3.1.65TNHHcTotal number of households inc community c using project lands in baselineField measurementDimensionlessDefinedYear 010% of communities (or at least 10), 10% of households per community or at least 10 Ex post net anthropogenic GHG removal by sinks 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 A/R CDM project activity (CARCDM), in t CO2-e:  EMBED Equation.3  ( AUTONUMLGL \e ) where: CAR-CDMNet anthropogenic greenhouse gas removals by sinks; 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sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH h*CJaJmH nH sH tH $ByCyIyyyyyMDDDDD $$Ifa$kd5$$Ifl4  rL# t0  64 laf4yyyhzizqzzMDDDDD $$Ifa$kd$$Ifl4  rL# t0  64 laf4 zazbzezgzhzizqz{zzzzzzzzzzzzzzzz{ {{{𶢶~jWGW𶢶h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nHsH tH$h*6CJ]aJmH nHsH tH h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH !h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH zzzzzz{MDDDDD $$Ifa$kd$$Ifl4  rL# t0  64 laf4{{{{{{\{]{`{b{c{d{l{v{}{{{{{{{{{{{{{{ɵqq[qGGɵq'h*h*6CJaJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH !h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*h*CJmH nH sH tH $h*h*CJaJmH nH sH tH {{{c{d{l{{MDDDDD $$Ifa$kd$$Ifl4  rL# t0  64 laf4{{{N|O|q||MDDDDD $$Ifa$kdy$$Ifl4  rL# t0  64 laf4{{=|>|||||||<}=}_}`}d}e}}}}}}}}}}H~J~S~V~Z~\~f~h~޽ˆu޽ˆd޽ˆS!h*CJ]aJmH nH sH tH !h*6CJaJmH nH sH tH !h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJaJmH nH sH tH !h*CJH*aJmH nH sH tH |||B}C}T}_}MDDDDD $$Ifa$kdJ$$Ifl4  rL# t0  64 laf4_}`}e}}}}}MDDDDD $$Ifa$kd $$Ifl4  rL# t0  64 laf4}}}o~{~~~MDDDDD $$Ifa$kd $$Ifl4  rL# t0  64 laf4h~k~m~~~~~~~ &(+-jknqsѾ𗇗vѾeѾe!h*CJH*aJmH nH sH tH !h*CJ]aJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH !h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH "~~~./GjMDDDDD $$Ifa$kd!$$Ifl4  rL# t0  64 laf4jksMDDDDD $$Ifa$kd"$$Ifl4  rL# t0  64 laf4MDDDDD $$Ifa$kd_#$$Ifl4  rL# t0  64 laf4@AIoMDDDDD $$Ifa$kd0$$$Ifl4  rL# t0  64 laf4ISZfmoprstǀӀڀ܀݀ހ߀ѾѾwdTh*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*6CJH*aJmH sH  h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH h*CJaJmH nH sH tH !h*6CJaJmH nH sH tH h*6CJaJmH sH opt܀MDDDDD $$Ifa$kd%$$Ifl4  rL# t0  64 laf4܀݀߀'MDDDDD $$Ifa$kd%$$Ifl4  rL# t0  64 laf4 &'(),-`bklstwx{}ڻqځځ```M$h*h*CJaJmH nH sH tH !h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH !h*6CJaJmH nH sH tH h*CJaJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH '(-MDDDDD $$Ifa$kd&$$Ifl4  rL# t0  64 laf4!$&5?FRYZ[\]^Ƃ҂قǴ}mmm\m\m\mǴm}m!h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*h*CJmH nH sH tH $h*h*CJaJmH nH sH tH 'h*h*6CJaJmH nH sH tH $()5ZMDDDDD $$Ifa$kdt'$$Ifl4  rL# t0  64 laf4Z[^ڂMDDDDD $$Ifa$kdE($$Ifl4  rL# t0  64 laf4قڂۂނ $FGJMuwÃăɃʃ˃ ϴϴϴϴϴo\L\\h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH h*CJaJmH nH sH tH h*CJaJmH sH h*6CJH*aJmH sH h*6CJaJmH sH  h*h*CJmH nH sH tH $h*h*CJaJmH nH sH tH ڂۂ%2:FMDDDDD $$Ifa$kd)$$Ifl4  rL# t0  64 laf4FGNƒMDDDDD $$Ifa$kd)$$Ifl4  rL# t0  64 laf4ƒÃ˃*+7IMDDDDD $$Ifa$kd*$$Ifl4  rL# t0  64 laf4"$')AHIJKPQR؄߄˺˺˺˩˛td˺˺˺˩˛dh*CJaJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH !h*6CJaJmH nH sH tH !h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH !h*CJ]aJmH nH sH tH #IJR„΄MDDDDD $$Ifa$kd+$$Ifl4  rL# t0  64 laf4#$,>MDDDDD $$Ifa$kdZ,$$Ifl4  rL# t0  64 laf4"#$6=>?Astυ()34;<@θΧΙΙsΙ_ssss'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH !h*6CJaJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH h*CJaJmH nH sH tH !h*6CJaJmH nH sH tH >?AMDDDDD $$Ifa$kd+-$$Ifl4  rL# t0  64 laf4ЅхمMDDDDD $$Ifa$kd-$$Ifl4  rL# t0  64 laf4JKW|MDDDDD $$Ifa$kd.$$Ifl4  rL# t0  64 laf4@ADGIWaht{|}~†Æ͆ΆՆֆ܆ͼͩq]J:JJJh*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH !h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH !h*CJ]aJmH nH sH tH !h*CJH*aJmH nH sH tH |}MDDDDD $$Ifa$kd/$$Ifl4  rL# t0  64 laf4܆݆9:RSUͼͩq^N@qh*CJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH !h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH !h*CJ]aJmH nH sH tH !h*CJH*aJmH nH sH tH >?GRMDDDDD $$Ifa$kdo0$$Ifl4  rL# t0  64 laf4RS`MDDDDD $$Ifa$kd@1$$Ifl4  rL# t0  64 laf4U_`͇· _`xy{ȷpȷpȷcTh*6CJH*aJmH sH h*6CJaJmH sH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH !h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH ·MDDDDD $$Ifa$kd2$$Ifl4  rL# t0  64 laf4 demxMDDDDD $$Ifa$kd2$$Ifl4  rL# t0  64 laf4xyňƈΈڈMDDDDD $$Ifa$kd3$$Ifl4  rL# t0  64 laf4Ĉڈۈ݈#$'=>@KLⵧⵧⵧxd'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*6CJH*aJmH sH h*6CJaJmH sH h*CJmH nH sH tH h*CJaJmH nH sH tH h*CJH*aJmH sH h*CJaJmH nHsH tHh*CJaJmH sH !h*6CJaJmH nH sH tH ڈۈ()1=MDDDDD $$Ifa$kd4$$Ifl4  rL# t0  64 laf4=>LMDDDDD $$Ifa$kdU5$$Ifl4  rL# t0  64 laf4/08CMDDDDD $$Ifa$kd&6$$Ifl4  rL# t0  64 laf4)*/0CDFIJÊĊŊ ͼͦ͘qͼͦ͘qͼ`!h*CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH !h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH "CDJMDDDDD $$Ifa$kd6$$Ifl4  rL# t0  64 laf4Ŋ ,7MDDDDD $$Ifa$kd7$$Ifl4  rL# t0  64 laf4 78:=>Q[_`e|}‹ËċƋNj޺pހހ޺\p޺\p޺'h*6CJH*]aJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH !h*CJH*aJmH nH sH tH !78>MDDDDD $$Ifa$kd8$$Ifl4  rL# t0  64 laf4‹MDDDDD $$Ifa$kdj9$$Ifl4  rL# t0  64 laf4‹ËNjMDDDDD $$Ifa$kd;:$$Ifl4  rL# t0  64 laf4MDDDDD $$Ifa$kd ;$$Ifl4  rL# t0  64 laf4!+2>EFʺo_L8L8L'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH h*CJaJmH nHsH tH$h*6CJ]aJmH nHsH tH'h*6CJH*]aJmH nHsH tHh*CJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH h*CJaJmH nHsH tH$h*6CJ]aJmH nH sH tH $h*6CJ]aJmH nHsH tH!FMDDDDD $$Ifa$kd;$$Ifl4  rL# t0  64 laf4FGLʍˍӍMDDDDD $$Ifa$kd<$$Ifl4  rL# t0  64 laf4FGIKLɍʍˍݍ[\dȵn`M9'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH !h*6CJaJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nHsH tH$h*6CJ]aJmH nHsH tH h*h*CJmH nH sH tH [\dMDDDDD $$Ifa$kd=$$Ifl4  rL# t0  64 laf4dnu%,-.0ȵ~nXnE$h*6CJ]aJmH nHsH tH*h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH -MDDDDD $$Ifa$kdP>$$Ifl4  rL# t0  64 laf4-.:MDDDDD $$Ifa$kd!?$$Ifl4  rL# t0  64 laf409:wxTUVȵlXlXlG4ȕ$h*6CJ]aJmH nHsH tH h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH h*CJaJmH nHsH tH$h*6CJ]aJmH nHsH tHh*CJaJmH nHsH tH$h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nHsH tHUV^MDDDDD $$Ifa$kd?$$Ifl4  rL# t0  64 laf4V^ho{ĐŐːېőƑؑߑݸq^M^<!h*6CJaJmH nH sH tH !h*>*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH h*CJaJmH nH sH tH MDDDDD $$Ifa$kd@$$Ifl4  rL# t0  64 laf4ŐőƑΑMDDDDD $$Ifa$kdA$$Ifl4  rL# t0  64 laf4 2MDDDDD $$Ifa$kdeB$$Ifl4  rL# t0  64 laf4*123479op{}ԒՒߒ˺q`˧q`˧!h*6CJaJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH !h*CJH*aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH %239MDDDDD $$Ifa$kd6C$$Ifl4  rL# t0  64 laf4 .MDDDDD $$Ifa$kdD$$Ifl4  rL# t0  64 laf4 &-./1?@klstwz{𶢶~n]nO~;'h*6CJH*]aJmH nH sH tH h*CJmH nH sH tH !h*6CJaJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH !h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH ./1klrsMDDDDD $$Ifa$kdD$$Ifl4  rL# t0  64 laf4st|ԓՓMDDDDD $$Ifa$kdE$$Ifl4  rL# t0  64 laf4{|ÓēԓՓTUefҔͷͩoͷͩbQEQh*CJaJmH sH !h*6CJaJmH nH sH tH h*6CJaJmH sH $h*6CJH*aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH ef~MDDDDD $$Ifa$kdzF$$Ifl4  rL# t0  64 laf4ҔӔ۔MDDDDD $$Ifa$kdKG$$Ifl4  rL# t0  64 laf4!5<=>ACDEƵթ▂o\L;!h*CJH*aJmH nHsH tHh*CJaJmH nHsH tH$h*6CJ]aJmH nH sH tH $h*6CJH*aJmH nHsH tH'h*6CJH*]aJmH nHsH tH$h*6CJ]aJmH nHsH tHh*CJaJmH sH !h*6CJaJmH nH sH tH h*6CJH*aJmH sH h*6CJaJmH sH h*CJmH nH sH tH h*CJaJmH nH sH tH !"*=MDDDDD $$Ifa$kdH$$Ifl4  rL# t0  64 laf4=>EʕMDDDDD $$Ifa$kdH$$Ifl4  rL# t0  64 laf4•ɕʕ˕Εҕӕ012BϹϦnZG7Ϲh*CJaJmH nHsH tH$h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nHsH tH$h*6CJ]aJmH nHsH tH h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH !h*CJH*aJmH nHsH tHh*CJaJmH nHsH tHʕ˕ӕ12:JMDDDDD $$Ifa$kdI$$Ifl4  rL# t0  64 laf4BIJKNRSȖϖЖіԖזؖ   #$%(+,>A^_`pwxyнpн_pн_p!h*6CJaJmH nHsH tH*h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nHsH tH$h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nHsH tH$h*6CJ]aJmH nHsH tHh*CJmH nH sH tH h*CJaJmH nH sH tH !h*6CJaJmH nH sH tH %JKSЖMDDDDD $$Ifa$kdJ$$Ifl4  rL# t0  64 laf4Жіؖ  $MDDDDD $$Ifa$kd`K$$Ifl4  rL# t0  64 laf4$%,_`hxMDDDDD $$Ifa$kd1L$$Ifl4  rL# t0  64 laf4xy}͗Η֗MDDDDD $$Ifa$kdM$$Ifl4  rL# t0  64 laf4y}̗ޗ  02;J\cdehjklǶǨǶǨp]Mh*CJaJmH nHsH tH$h*6CJ]aJmH nH sH tH !h*CJH*aJmH nHsH tH'h*6CJH*]aJmH nHsH tH$h*6CJ]aJmH nHsH tHh*CJmH nH sH tH !h*6CJaJmH nH sH tH h*CJaJmH nH sH tH h*6CJH*aJmH sH h*CJaJmH sH h*6CJaJmH sH KLTdMDDDDD $$Ifa$kdM$$Ifl4  rL# t0  64 laf4delMDDDDD $$Ifa$kdN$$Ifl4  rL# t0  64 laf4 TU]gnzݶݨr_K_K_: h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH !h*6CJaJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nHsH tH TU]MDDDDD $$Ifa$kduO$$Ifl4  rL# t0  64 laf4řMDDDDD $$Ifa$kdFP$$Ifl4  rL# t0  64 laf4řϙ֙5679:ɹɹݹ||kX𹣹Jh*CJmH nH sH tH $h*6CJ]aJmH nH sH tH h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJaJmH nH sH tH 6789MDDDDD $$Ifa$kdQ$$Ifl4  rL# t0  64 laf49:?wMDDDDD $$Ifa$kdQ$$Ifl4  rL# t0  64 laf4:>?vٚښ   GISuv{|˛̛͛ϛЛ⹦m⹦Ym'h*6CJH*]aJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH h*6CJH*aJmH sH h*CJaJmH sH h*CJaJmH nH sH tH h*6CJaJmH sH "MDDDDD $$Ifa$kdR$$Ifl4  rL# t0  64 laf4 TaiuMDDDDD $$Ifa$kdS$$Ifl4  rL# t0  64 laf4uv|˛MDDDDD $$Ifa$kd[T$$Ifl4  rL# t0  64 laf4˛̛ЛMDDDDD $$Ifa$kd,U$$Ifl4  rL# t0  64 laf4 UbjvMDDDDD $$Ifa$kdU$$Ifl4  rL# t0  64 laf4  Tvw{|}ŜƜ՜%'01;>?ŷŕp]M]]]h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH !h*CJH*aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*6CJH*aJmH sH h*CJmH nH sH tH h*CJaJmH nH sH tH h*CJaJmH sH !h*6CJaJmH nH sH tH h*6CJaJmH sH vw}֜MDDDDD $$Ifa$kdV$$Ifl4  rL# t0  64 laf4FGbMDDDDD $$Ifa$kdW$$Ifl4  rL# t0  64 laf4?@CEFGʝ˝՝ڝ۝ݝޝߝ/01567^`ijty޺o_oooo޺o_oooh*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH !h*CJH*aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH !h*CJH*aJmH nH sH tH %/MDDDDD $$Ifa$kdpX$$Ifl4  rL# t0  64 laf4/07ΞMDDDDD $$Ifa$kdAY$$Ifl4  rL# t0  64 laf4yz|}~ΞϞОўԞ՞֞*+HIQXYȷȷȡȓo_ȡN!h*6CJaJmH nH sH tH h*CJaJmH nH sH tH !h*CJH*aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH !h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH ΞϞ֞HIYwMDDDDD $$Ifa$kdZ$$Ifl4  rL# t0  64 laf4Ycjovwx{|ʠޠȵqq[qȵG'h*6CJH*]aJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH !h*>*CJaJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH wx|ʠMDDDDD $$Ifa$kdZ$$Ifl4  rL# t0  64 laf4MDDDDD $$Ifa$kd[$$Ifl4  rL# t0  64 laf4ġܡv׮yfR?y$h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH h*CJaJmH nH sH tH h*h*CJmH nH sH tH 'h*h*6CJaJmH nH sH tH $h*h*CJaJmH nH sH tH *h*CJOJQJ^JaJmH nH sH tH h*CJaJmH nH sH tH h*6CJaJmH sH h*CJaJmH sH |~MDDDDD $$Ifa$kd\$$Ifl4  rL# t0  64 laf4vz|~¢ĢƢJNhlxz޷ީo_ooooN=!h*CJ]aJmH nH sH tH !h*CJH*aJmH nH sH tH h*CJaJmH nH sH tH $h*6CJ]aJmH nH sH tH 'h*6CJH*]aJmH nH sH tH $h*6CJ]aJmH nH sH tH 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