Greenhouse Gas Accounting for Sustainable Land Management Quick Guidance for Users 1|P age Greenhouse Gas Accounting for Sustainable Land Management Quick Guidance for Users Anass Toudert, Ademola Braimoh, Martial Bernoux, Maylina St-Louis, Manar Abdelmagied, Louis Bockel, Adriana Ignaciuk, and Yuxuan Zhao 2|P age Abstract Agriculture, and the patterns of land use change that are associated with it, have a high environmental footprint and contribute to climate change, as the sector accounts for about one-quarter of anthropogenic greenhouse gas (GHG) emissions globally. However, improved land management practices can play an important role in mitigating GHG emissions by removing substantial volumes of carbon from the atmosphere and sequestering them in soils and plant tissues. We can’t fix what we do not measure, which is why quantifying greenhouse gas emissions is a necessary step for climate-smart agriculture and sustainable land management. Greenhouse gas accounting can provide the numbers and data that are important to decision making in adopting less carbon-intensive practices, guiding low-emissions development, assessing product supply chains, certifying sustainable agriculture practices, and informing consumers on the carbon footprint of their choices. This Quick Guidance on Greenhouse Gas Accounting for Sustainable Land Management provides an overview of SLM activities subject to greenhouse gas appraisal, guidance in the selection of tools, data needs for the application and final use of the greenhouse gas accounting tools It complements the more comprehensive Carbon Accounting Tools for Sustainable Land Management report, and it is targeted at leading resource managers and project developers to proficiency in the independent use of greenhouse gas accounting tools. 3|P age Contents Abstract ........................................................................................................................................................................3 1. Introduction ........................................................................................................................................................5 2. SLM and their Activity Categories for GHG Assessment ..............................................................................7 3. Selection of tools .................................................................................................................................................9 4. Data collection and scenario building ............................................................................................................. 11 5. The final carbon balance ................................................................................................................................. 16 References .................................................................................................................................................................. 17 Annexes ....................................................................................................................................................................... 18 Annex 1: Availability and geographical coverage of 10 commonly used GHG calculators ................................... 18 Annex 2: Data, Time and Skills requirement of the tools........................................................................................ 19 Annex 3: Multicriteria GHG tool selector for SLM projects .................................................................................. 20 Annex 4: Recommended tools per land use activity ................................................................................................ 22 Annex 5: Recommended tools when considering Land Use Change scenarios ..................................................... 23 Annex 6: Detailed description of the tools most suitable for SLM project ............................................................. 24 Carbon Benefits Project Modeling Tools ........................................................................................................... 24 Agence Française de Développement Carbon Footprint Tool ........................................................................... 25 Agriculture, Forestry and Other Land Use Carbon Calculator ......................................................................... 27 Carbon Assessment Tool for Afforestation and Reforestation ........................................................................... 28 Ex-Ante Carbon-Balance Tool ........................................................................................................................... 29 FIGURES Figure 1: Building development scenarios for GHG Accounting ................................................................................ 11 Figure 2: The Final Carbon Balance ............................................................................................................................ 16 Figure A2.1: Step-by-step process for selecting a GHG calculator ............................................................................. 21 Cover photo: Kate Evans/CIFOR TABLES Table 1: SLM approaches and technologies ..................................................................................................................7 Table 2: Definition of activity-categories in line with IPCC’s and FAO’s definitions ..................................................8 Table 3: Examples of Tier 1 activity data ................................................................................................................. 13 Table 4: Checklist for identifying project relevant modules.......................................................................................... 15 4|P age 1. Introduction Agriculture, and the patterns of land use change that are associated with it, have a high environmental footprint and contribute to climate change, as the sector accounts for about one- quarter of anthropogenic greenhouse gas (GHG) emissions globally. At the same time, agriculture is strongly influenced by weather and climate (Battisti and Naylor 2009; IPCC 2001; Lobell et al. 2008). However, climate change can offer new opportunities for productive and sustainable land management (SLM) practices, such as reforestation, improved water management, integrated soil fertility management, conservation agriculture, agroforestry, improved rangeland management, and others because of changing biophysical or market conditions. Improved land management practices can play an important role in mitigating GHG emissions by removing substantial volumes of carbon from the atmosphere and sequestering them in soils and plant tissues. We cannot fix what we do not measure. Systematic assessments are required to make targeted decisions and, therefore, ensure food security. The quantification of GHG emissions and carbon sequestration is a necessary step for SLM. GHG accounting can provide the numbers and data that are key for informed decision making. It can help identify management practices and opportunities that reduce GHG emissions while also providing improved food security, more resilient production systems, and better rural livelihoods. In practical terms, GHG emissions data can support farmers in adopting less carbon-intensive practices, guiding low-emissions development, assessing product supply chains, certifying sustainable agriculture practices, and informing consumers on the carbon footprint of their choices (Olander et al. 2013). Many tools have been developed for assessing GHG emissions from SLM in the last few years. Denef et al. (2012) classify these tools as calculators, protocols, guidelines, and models. 1 This document provides users with helpful information for choosing the most appropriate tool for a given project. It complements the full report on comparative analysis of Carbon Accounting Tools for Sustainable Land Management. 2 The primary use of this guidance note is in project design. Development practitioners who need to estimate the GHG-balance of SLM investment proposals in the agriculture, forestry and land use sector are therefore the principal intended audience. The main target users should be involved during the project design stage and pursue the objective of aligning ex- ante program and project documents in accordance with the results obtained from the GHG appraisal. This guidance note is divided into 5 sections, including this introduction. Section 2 briefly explains SLM activities which are the prime subject of GHG analysis. Section 3 provides guidance on the selection of GHG accounting tools and how to utilize them as part of the project document design process. Section 4 discusses data types and collection and scenario 1 In this guidance note, the terms ‘tools’ and ‘calculators’ are used interchangeably. 2 For more detailed information, a glossary of terms and the complete bibliography, please refer to the full report Carbon Accounting Tools for Sustainable Land Management 5|P age building, while Section 5 concludes with carbon-balance appraisal and how using GHG accounting tools serves this purpose. 6|P age 2. SLM and their Activity Categories for GHG Assessment According to the UN Earth Summit of 1992, SLM is “the use of land resources, including soils, water, animals, and plants, for the production of goods to meet changing human needs, while simultaneously ensuring the long-term productive potential of these resources and the maintenance of their environmental functions.” It entails the implementation of land use systems and management practices that enable humans to maximize the economic and social benefits from land (soil, water, and air) while maintaining or enhancing the ecosystem services that land resources provide. SLM practices include technologies and approaches that aim to increase land quality to enhance productivity and, at the same time, protect the natural resource base through economically viable and socially acceptable solutions. These technologies include agronomic, vegetative, structural, and management measures, such as new seed varieties, terracing, forestation, reduced tillage, micro-irrigation, fertilizer placement approaches, and livestock-feeding schedules. Databases such as the World Overview of Conservation Approaches and Technologies (WOCAT), TerrAfrica, the World Bank SLM Sourcebook, and the Voluntary Guidelines for Sustainable Soil Management (VGSSM) provide comprehensive recommendations and examples of SLM practices. A non-exhaustive list of SLM practices can be found in table 1. Table 1: SLM approaches and technologies SLM practices SLM approaches SLM technologies Land use regimes Agronomic and vegetative measures Structural measures • Watershed plans • Intercropping • Terraces and other physical measures (for • Community land • Natural regeneration of trees or other example, soil bunds, stone bunds, and bench use plans vegetation terraces) • Grazing • Agroforestry • Flood control and drainage measures (for agreements, • Afforestation and reforestation example, rock catchments’ water harvesting, closures, and so • No tillage cut-off drains, vegetative waterways, stone- on • Mulching and crop residue paved waterways, flood water diversion, • Soil and water • Crop rotation and so on) conservation • Fallowing • Water harvesting, runoff management, and zones • Composting/green manure small-scale irrigation (for example, shallow • Vegetation • Integrated pest management wells/boreholes, micro ponds, underground corridors cisterns, percolation pits, ponds, spring • Vegetative strip cover development, roof water harvesting, river • Contour planting bed dams, stream diversion weir, farm dam, • Revegetation of rangelands tie ridges, inter-row water harvesting, half- • Integrated crop-livestock systems moon structures, and so on) • Woodlots • Gully control measures (for example, stone • Live fencing check dams, brushwood check dams, gully • Alternatives to wood fuel cut/reshaping and filling, gully revegetation, • Sand dune stabilization and so on) 7|P age The first step in GHG accounting for SLM is to determine the activity categories of agriculture, forestry and other land use sectors affected by the project (Table 2). The activity categories in turn will allow the user to select the appropriate GHG accounting tool and modules within the tool. Table 2: Definition of activity-categories in line with IPCC’s and FAO’s definitions Activities Definition Afforestation/reforestation Refers to the artificial establishment of forest on lands that previously did not carry forest within living memory, while reforestation is defined as the artificial establishment and natural regeneration of forest on lands that carried forest before. Deforestation Refers to the change of land cover with depletion of tree crown cover to less than 10 percent. Changes within the forest class (for example, from closed to open forest) that negatively affect the stand or site—and, in particular, lower the production capacity—are termed forest degradation. Forest management Refers to the reductions in the productive capacity of the forest. For each activity, the initial state of the forest and its expected final states (without project and with project) were identified. It includes directly human-induced change (for example, because of improved silviculture), indirect influences (for example, nitrogen or CO 2 fertilization), and natural causes (including natural successional processes). Within this study, two main categories of forest management were identified: fire forest management and forest management and degradation (biomass loss). Annual cropland Refers to lands covered with temporary broadleaf or grass-type crops that are harvested at the completion of the growing season, then remain idle until replanted. Two categories were identified for annual crops: newly implemented systems after land conversion of other land use systems and annual systems that remain annual systems. Perennial cropland Refers to lands covered with temporary broadleaf or grass-type crops that are harvested at the completion of the growing season, then remain idle until replanted. Two categories were identified for perennial crops: newly implemented systems after land conversion of other land use systems and perennial systems that remain perennial systems. Grassland management Refers to lands with herbaceous types of cover, typically graminoids. Tree and shrub cover is less than 10 percent. Two categories were identified for grassland systems: newly implemented systems after land conversion of other land use systems and grassland systems that remain grassland systems. Livestock Refers to a broad sense to cover all grown animals regardless of age, location, or purpose of breeding. Six main categories of livestock are fixed: dairy cattle, other cattle, buffalo, sheep, swine (market), swine (breeding), goats, camels, horses, mules, asses, poultry, deer, and alpacas. Inputs Refers to the use of agricultural chemicals, N fertilizer in non-upland rice systems (that is, flooded rice systems), sewage, and organic fertilizers in farm operations and based on projects activities. Investments Refers to electricity consumption, fuel consumption, installation of irrigation systems, and building of infrastructure. 8|P age 3. Selection of tools GHG calculators have been developed through different approaches, targets, and objectives, suitable for a defined geographic coverage. To facilitate the different activities of targeting climate change mitigation in agriculture, decision makers can today choose from a wide range of available GHG tools. These tools differ in their main objectives—reflected in different data needs, geographical scope, and coverage along the value chain as well as their regional and subsector specificity. To facilitate a more informed tool selection, six prescreening criteria are usually applied (Colomb et al. 2012, 2013): 3 1) Availability. This criterion allows users to evaluate whether the tool and its technical guidelines are freely accessible online (see Annex 1). 2) Geographical coverage. This criterion allows users to evaluate the geographical context, that is, the continental regions where the tools are mostly applicable. 3) Activities scope. This allows users to evaluate to what extent the tools can handle a wide range of SLM activities. 4) Data requirements. This refers to the data that the GHG analysis is based on. This may be data available to the user before the evaluation begins, or intermediate data that are generated during the analysis. Data requirements are assessed in terms of qualitative and quantitative information (for example, state of degraded forests) and the relative accessibility of the data, especially in the context of low income countries. 5) Time requirements. This refers to the time it takes for the user to successfully conduct an analysis. Note, however, that it may be difficult to precisely estimate the amount of time necessary for each tool or assessment, as this depends on the skills of the evaluator, level of accuracy, reliability, and data availability. 6) Skills requirements. This indicates the extent to which skills needed for the analysis exceed what is considered basic evaluation skills. Such basic skills include the ability to reason logically and conduct basic GHG analysis, gather information through interviews and other qualitative methods, and write reports and present results. Without appropriate skills, impractical or inappropriate methodology may be selected, resulting in misleading conclusions. The special skills needed for conducting the different types of efficiency analyses are agronomic, forestry, or SLM skills. Application of the prescreening criteria to ten commonly used GHG calculators (Annex 2) indicates that seven out of the 10 tools have moderately low data requirements, one (CAT-AR) requires high amounts of data, while CAT-SFM and DNDC are notably extreme in their very high data requirements. The time required for analysis given the availability of data varies from “very short” for CCAFS mitigation tool to “very long” for DNDC, CBP, EX-ACT and TARAM. There is close correlation between time and skill requirements for GHG analysis using the tools. Tools that are relatively highly skill-demanding, that is, require more than the basic skills, correspondingly require more time to perform GHG appraisals. 3 For more information on how the criteria were applied to ten commonly used GHG calculators, please refer to the full report Carbon Accounting Tools for Sustainable Land Management 9|P age Following prescreening, the suggested process for selecting a suitable GHG tool(s) is based on the characteristics of each calculator (Annex 3). These characteristics include the ability of the calculator to account for the range of SLM activities, changes in land use, different GHGs, the need for spatially explicit results, uncertainties, and leakages associated with the project. Users should select tools according to these more specific criteria, helped by the tables provided in Annexes 4 and 5. 10 | P a g e 4. Data collection and scenario building Depending on the specific project, data collection and GHG analysis is only necessary in the modules relevant to the project. The main data needs occur only in the focal areas of the project. Rather than choosing modules according to project type, the modules are chosen with respect to project impacts, that is, what is affected by the project. This flexibility allows for the adequate consideration of multi-segment projects and leads the project designer to think of possible indirect impacts on in-directly impacted areas, e.g. increased pressure for deforestation or grassland degradation. Scenario building enables designers to make projections about the impacts that a prospective project or intervention is most likely to have, and to compare this With- Project Scenario to the alternative business-as-usual Without-Project Scenario in which the project never took place. This ex-ante evaluation of two alternative theoretical scenarios requires data on a real-world baseline situation – something which is very familiar to ex-ante economic analysis in general. Baseline scenario building begins with the Initial Situation of land use and management practices in the project area, given in the following figure as xo, using the example of a project that is designed to increase the amount of cropland that is cultivated using improved nutrient management. Developing the alternative scenarios over two time periods, the With-Project Scenario projects an increase in the improved fertilized area to x 2 hectares, while the Without-Project Scenario forecasts a proportionately smaller increase in area to x 1 hectares Figure 1: Building development scenarios for GHG Accounting 11 | P a g e GHG accounting typically differentiates between two time periods. The implementation phase defines the period in which active project activities are carried out and lasts from t 0 until t 1 (Figure 1). Thereby the period covered by the analysis does not necessarily end with the termination of the active project intervention. Even after the point that a new equilibrium in land use and practices is reached in t 1 further changes may occur, for instance changes in soil carbon content or in biomass, that are extended results of the intervention following the lifespan of the intervention itself. This period defines the capitalization phase which lasts from t 1 until t 2 . The difference in activity data between With- and Without-Project scenarios serves then later as the input data for calculating the carbon-balance of the project. Data are needed concerning all those areas in which change is observed between project start and end of the capitalization phase due to project implementation as well as in those areas where such alterations are actively prevented because of project implementation, for instance through prevented deforestation. In addition to more generic Tier 1 data (table 3), more detailed Tier 2 data can be selectively applied to increase resolution and the confidence level of projected results. A tier level of analysis represents a level of methodological complexity to estimate greenhouse gas emissions following the definition in NGGI-IPCC-2006. Tier 1 methods rely on default values and require a lower level of detail, while Tier 2 methods require regional specific carbon stock values and emission coefficients, implying higher precision and the need for more sophisticated data. 12 | P a g e Table 3: Examples of Tier 1 activity data Description module - Sub-continent - Dominant regional soil type Obliga tory - Type of climate - Project duration - Moisture regime Land use change module Deforestation Only if project related - Forest type and size - Final land use after conversion - Area deforested - Burning during conversion? Afforestation & reforestation - Type of current land use - Burning during conversion? - Type of future forest Other land use change - Type of current land use - Burning during conversion? - Type of future land use Crop production module Annual systems - Current and future planted crop area - Practices of residue burning? (by type of crop) - Crop management practices Perennial systems - Current and future planted crop area - Practices of residue burning? (by type of crop) Irrigated rice - Specifications of water management practices Grassland and livestock module Grassland - Current and future grassland area by state of - Practices of grassland burning? degradation Livestock - Type and number of livestock - Feeding and breeding practices Land degradation module Forest degradation - Dynamic of forest degradation / rehabilitation - Occurrence of forest fires? by forest type and size Degradation of organic soils (peatland) - Vegetation type and size concerned by - Area affected by peat extraction drainage of organic soils Input an investment module Agricultural inputs - Weight of agricultural inputs by type Energy consumption - Quantity of electricity, liquid and gaseous fuel, and wood consumed Building of infrastructure - Size of area with newly established irrigation infrastructure or buildings (by type) 13 | P a g e Besides offering the option to use Tier 1 default values, some GHG accounting tools encourage users to substitute default values with more location-specific Tier 2 data that lead to lower uncertainty levels in the estimation. Tier 2 data involves location-specific variables that offer specifications on the carbon content and stock changes in all five carbon pools as well as the emission factors for selected practices. Some examples of Tier 2 data include: • Above and below ground biomass levels and changes for forestland • Soil carbon content • Rates of soil carbon sequestration on various land uses • Amount of biomass burnt during land conversion and crop residue management • Nitrous oxide and methane emissions from manure management • Emissions from enteric fermentation • Emissions associated with the construction of agricultural, road and building infrastructure The collection of Tier 2 data is especially advised for core project components that are expected to be larger sources or sinks of GHGs. This logic may be understood as a good practice leading to a reasonable combination of Tier 2 and Tier 1 data. The checklist in Table 4 allows users determine the modules that apply to their project. 14 | P a g e Table 4: Checklist for identifying project relevant modules Carbon-balance Impact Relevant Project Main Impact Area Module(s) to fill intervention YES NO A Reduced emissions of carbon dioxide A1 Reduction in rate of deforestation Land use change A2 Reduction in forest degradation Land degradation A3 Adoption of improved cropland management Crop production A4 Introduction of renewable energy and energy-saving Investments technologies B Reduced emissions of methane and nitrous oxide POSITIVE (SINK) B1 Improved animal production Livestock B2 Improved management of livestock waste Livestock B3 More efficient management of irrigation water in rice Crop production B4 Improved nutrient management Crop production, Livestock C Carbon sequestration C1 Conservation farming practices Crop production C2 Improved forest management practices Land use change C3 Afforestation and reforestation Land use change C4 Adoption of agroforestry Crop production C5 Improved grassland management Grassland C6 Restoration of degraded land Land use change D Increased emissions of methane, nitrous oxide and carbon dioxide D1 Increased livestock production Livestock D2 Increased irrigated rice production Crop production D3 Increased fertilizer use and over-fertilization Inputs NEGATIVE (SOURCE) D4 Production, transportation, storage and transfer of Inputs agricultural chemicals Investments D5 Increased electricity consumption Investments D6 Increased fuel consumption Investments D7 Installation of irrigation systems Investments D8 Building of infrastructure E Decreased carbon stocks E1 Increased deforestation & timber logging Land use change E2 Increased land degradation (forests, croplands, grassland) Land degradation, E3 Cropland expansion Grassland E4 Residue burning, deep tillage, … Land use change Crop production 15 | P a g e 5. The final carbon balance In estimating the final carbon balance, only the modules that are directly impacted by project activities should be filled. The main data needs occur only in the focal areas of the project and project team should ensure that sufficient data required by the tool is collected. It is normal that many data entry cells will not be used if some modules do not apply to the project. It is also essential that information is entered on changes occurring With-Project vis-a-vis Without-Project situation. The specific agro-ecological conditions and activity data in the GHG accounting tool modules lead to the calculation of GHG emissions and carbon stock changes. The comparison of the net emissions from With-Project and Without-Project scenarios constitutes the marginal difference in GHG emissions and carbon sequestration due to project implementation which defines the overall carbon balance. Figure 2: The Final Carbon Balance 16 | P a g e References Battisti, D. S., and R. L. Naylor. 2009. “Historical Warnings of Future Food Insecurity with Unprecedented Seasonal Heat.” Science 323 (5911): 240–244. DOI: 10.1126/science.1164363. Bernoux, M., G. Branca, A. Carro, L. Lipper, G. Smith, and L. Bockel. 2010. “Ex-ante Greenhouse Gas Balance of Agriculture and Forestry Development Programs.” Scientia Agricola 67 (1): 31– 40. http://dx.doi.org/10.1590/S0103-90162010000100005 Bockel, L., P. Sutter, O. Touchemoulin, and M. Jönsson. 2012. “Using Marginal Abatement Cost Curves to Realize the Economic Appraisal of Climate Smart Agriculture Policy Options [online].” EasyPol Module 116. Food and Agriculture Organization of the United Nations. http://www.fao.org/3/a-bq866e.pdf Colomb, V.,O. Touchemoulin, L. Bockel, J. L. Chotte, S. Martin, M. Tinlot, and M. Bernoux. 2013. “Selection of Appropriate Calculators for Landscape-Scale Greenhouse Gas Assessment for Agriculture and Forestry.” Environmental Research Letters 8 (1). https://doi.org/10.1088/1748- 9326/8/1/015029 Colomb, V., M. Bernoux, L. Bockel, J. L. Chotte, S. Martin, M. Tinlot, and O. Touchemoulin. 2012. ‘’ Review of GHG Calculators in Agriculture and Forestry Sectors: A Guideline for Appropriate Choice and Use of Landscape Based Tools. http://www.fao.org/fileadmin/templates/ex_act/pdf/ADEME/Review_existingGHGtool_V F_UK4.pdf Denef, K., K. Paustian, S. Archibeque, S. Biggar, and D. Pape. 2012. Report of Greenhouse Gas Accounting Tools for Agriculture and Forestry Sectors. Interim report to USDA under Contract No. GS23F8182H. [online]. https://www.usda.gov/oce/climate_change/techguide/Denef_et_al_2012_GHG_Account ing_Tools_v1.pdf FAO (Food and Agriculture Organization). 2010. Comparing Results of Carbon Balance Appraisal Using On-going Bio-Carbon Fund Projects [online]. 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Naylor. 2008. “Prioritizing Climate Change Adaptation Needs for Food Security in 2030.” Science 319 (5863): 607–610. DOI:10.1126/science.1152339 Olander, L., E. Wollenberg, F. Tubiello, and M. Herold. 2013. “Advancing Agricultural Greenhouse Gas Quantification.” Environmental Research Letters, 8 pp (1). https://doi.org/10.1088/1748- 9326/8/1/011002 Smith, P., D. Martino, Z. Cai, D. Gwary, H. Janzen, P. Kumar, B. McCarl, S. Ogle, F. O'Mara, and C. Rice. 2008. “Greenhouse Gas mitigation in Agriculture.” Philosophical Transactions of the Royal Society B: Biological Sciences 363 (1492): 789–813. DOI: 10.1098/rstb.2007.2184. 17 | P a g e Annexes Annex 1: Availability and geographical coverage of 10 commonly used GHG calculators Geographical No. Tool Website Developer zone/application 1 AFD-CFT http://www.afd.fr/lang/en/home/projets_a Agence Française de World fd/changement_climatique/Liens_utiles_c Développement All climates limat/4861736956 (France) 2 AFOLU http://www.afolucarbon.org/ USAID, Winrock World Carb International (United All climates States) 3 CAT-AR http://www.worldbank.org/en/search?q=C World Bank World AT-AR+ All climates percent28Carbon+Assessment+Tool+for +Afforestation+and+Reforestation percent29 4 CAT-SFM http://documents.worldbank.org/curated/e World Bank World n/392001468331049999/pdf/903680WP0 All climates Box380tingguidanceforestry.pdf 5 CBP www.carbonbenefitsproject.org GEF/United Nations World Environment All climates Programme/CSU 6 CCAFS- https://ccafs.cgiar.org/mitigation-option- CGIAR CCAFS World MOT tool-agriculture#.V717mU19670 All climates 7 CFT https://www.coolfarmtool.org Unilever and World researchers at the All climates University of Aberdeen 8 DNDC http://www.dndc.sr.unh.edu Institute for the Study United States, but of Earth, Oceans, and has been adapted to Space, University of other parts of the New Hampshire world (United States) Temperate climate to a large extent 9 EX-ACT http://www.fao.org/tc/exact/ex-act- FAO World home/en All climates 10 TARAM https://wbcarbonfinance.org/Router.cfm? World Bank Carbon World Page=BioCF&FID=9708&ItemID=9708 Finance Unit All climates &ft=DocLib&CatalogID=44969 18 | P a g e Annex 2: Data, Time and Skills requirement of the tools No. Tool Data requirements Time requirements Skills requirements 1 CBP +++ + ++ 2 AFD-CFT +++ ++ + 3 AFOLU +++ +++ +++ 4 CAT-AR ++ +++ ++ 5 CAT-SFM + ++ + 6 CCAFS +++ ++++ ++++ 7 CFT +++ +++ +++ 8 DNDC + + + 9 EX-ACT +++ ++ ++ 10 TARAM +++ + + Legend 0 min