Carbon Accounting Tools
              for
Sustainable Land Management




                        1
     Carbon Accounting Tools
                for
  Sustainable Land Management


Anass Toudert, Ademola Braimoh, Martial Bernoux, Maylina St-Louis, Manar
      Abdelmagied, Louis Bockel, Adriana Ignaciuk, and Yuxuan Zhao




                                                                           2
Contents
Acknowledgments ........................................................................................................................................................9

Acronyms.................................................................................................................................................................... 10

Executive Summary ................................................................................................................................................... 12

1.       Introduction ...................................................................................................................................................... 17

2.       Sustainable land management and carbon benefits ...................................................................................... 19
     2.1     Sustainable land management defined .......................................................................................................... 19
     2.2     Carbon benefits of SLM projects ................................................................................................................... 20
     2.3     Methodology for the study ............................................................................................................................. 21

3.       Screening of carbon accounting tools ............................................................................................................. 23
     3.1 Carbon tools identification and characterization ............................................................................................. 23
        3.1.1 Availability and geographical coverage .................................................................................................... 24
        3.1.2 Activities scope ......................................................................................................................................... 25
        3.1.3 Data requirements ..................................................................................................................................... 27
        3.1.4 Time and skills requirements .................................................................................................................... 27
        3.1.5 Conclusion and remarks ............................................................................................................................ 28

4. Short-listed tools for comparative analysis.......................................................................................................... 32
     4.1 Detailed description of short-listed tools .......................................................................................................... 32
        4.1.1 Carbon Benefits Project Modeling Tools .................................................................................................. 32
        4.1.2 Agence Française de Développement Carbon Footprint Tool .................................................................. 33
        4.1.3 Agriculture, Forestry, and Other Land Use Carbon Calculator (AFOLU Carb) ....................................... 35
        4.1.4 Carbon Assessment Tool for Afforestation and Reforestation .................................................................. 36
        4.1.5 Cool Farm Tool ......................................................................................................................................... 37
        4.1.6 Climate Change, Agriculture, and Food Security Mitigation Options Tool (CCAFS-MOT) ................... 38
        4.1.7 Ex-Ante Carbon-Balance Tool .................................................................................................................. 39
     4.2 Detailed characterization of the short-listed tools............................................................................................ 40
        4.2.1 Assessing GHG consequences of projects ................................................................................................ 40
        4.2.2 Intergovernmental Panel on Climate Change methods ............................................................................. 41
        4.2.3 Accounting for climate and soil ................................................................................................................ 42
        4.2.4 GHG scope ................................................................................................................................................ 43
        4.2.5 Uncertainties ............................................................................................................................................. 44
        4.2.6 Presentation of GHG assessment results and shortlisted tools .................................................................. 45
        4.2.7 Overall comments and conclusion ............................................................................................................ 46

5. Application of the Short-Listed Tools to GEF Development Projects .............................................................. 47

Desk study analysis .................................................................................................................................................... 49
     5.1 Belarus-Forestry Development Project (FDP) ................................................................................................. 49
        5.1.1 Detailed project analysis per activity for the Belarus Forestry Development Project ............................... 50
           5.1.1.1 Afforestation/reforestation (initial land use: perennial cropland) .................................................... 50
           5.1.1.2 Forest management and degradation (forest fire management) ....................................................... 51
              5.1.1.2.1 Inputs and investments (electricity, gasoil, wood consumption, and irrigation) ....................... 52
        5.1.2 Project carbon balance .............................................................................................................................. 52
     5.2 Brazil, GEF Rio Grande do Sul Biodiversity .................................................................................................... 52


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    5.2.1 Detailed project analysis per activity for the Brazil GEF Rio Grande do Sul Biodiversity Project .......... 53
       5.2.1.1 Grassland management ..................................................................................................................... 53
    5.2.2 Project carbon balance .............................................................................................................................. 54
5.3 Brazil, Caatinga Conservation and Sustainable Management Project............................................................. 54
   5.3.1 Detailed project analysis per activity for the Brazil Caatinga Conservation and Sustainable Management
   Project ................................................................................................................................................................ 55
      5.3.1.1 Afforestation/reforestation (ILU: grassland) .................................................................................... 55
      5.3.1.2 Annual crops development (ILU: degraded land) ............................................................................. 56
      5.3.1.3 Perennial crops development (ILU: degraded land) ......................................................................... 57
   5.3.2 Project carbon balance .............................................................................................................................. 57
5.4 Burkina Faso, Third Phase Community Based Rural Development Project .................................................... 57
   5.4.1 Detailed project analysis per activity for Burkina Faso Third Phase Community Based Rural
   Development Project .......................................................................................................................................... 58
      5.4.1.1 Deforestation (Final land use: grassland) ........................................................................................ 58
      5.4.1.2 Forest management and degradation ................................................................................................ 59
   5.4.2 Project carbon balance .............................................................................................................................. 59
5.5 Burundi, Sustainable Coffee Landscape Project............................................................................................... 59
   5.5.1 Detailed project analysis per activity for the Burundi Sustainable Coffee Landscape Project.................. 60
      5.5.1.1 Afforestation/reforestation (ILU: set aside land) .............................................................................. 60
      5.5.1.2 Perennial crops improvement............................................................................................................ 61
      5.5.1.3 Forest management and degradation ................................................................................................ 61
   5.5.2 Project carbon balance .............................................................................................................................. 62
5.6 China, Guangxi Integrated Forestry Development and Conservation Project ................................................. 62
   5.6.1 Detailed project analysis per activity for Guangxi Integrated Forestry Development and Conservation
   Project ................................................................................................................................................................ 63
      5.6.1.1 Afforestation (ILU: set aside and grassland) .................................................................................... 63
5.7 China, Shanghai Agricultural and Non-point Pollution Reduction Project ..................................................... 64
   5.7.1 Detailed project analysis per activity for Shanghai Agricultural and Non-Point Pollution Reduction
   Project ................................................................................................................................................................ 65
      5.7.1.1 Livestock ............................................................................................................................................ 65
   5.7.2 Project carbon balance .............................................................................................................................. 66
5.8 Costa Rica, Biodiversity Conservation in Cacao Agroforestry ........................................................................ 66
   5.8.1 Detailed project analysis per activity for Costa Rica Biodiversity Conservation in Cacao Agroforestry
   Project ................................................................................................................................................................ 67
      5.8.1.1 Afforestation activities (ILU: set aside land)..................................................................................... 67
      5.8.1.2 Perennial crops improvement............................................................................................................ 68
   5.8.2 Project carbon balance .............................................................................................................................. 68
5.9 Ethiopia, Country Program for Sustainable Land Management (ECPSLM).................................................... 69
   5.9.1 Detailed project analysis per activity for ECPSLM .................................................................................. 70
      5.9.1.1 Afforestation activities (ILU: set aside land and degraded land)...................................................... 70
      5.9.1.2 Annual cropland improvement .......................................................................................................... 71
      5.9.1.3 Grassland management ..................................................................................................................... 71
      5.9.1.4 Forest management and degradation ................................................................................................ 72
      5.9.1.5 Inputs and Investments (electricity, irrigation, buildings, and roads construction) .......................... 72
   5.9.2 Project carbon balance .............................................................................................................................. 72
5.10 Guinea, Community-based Land Management Project .................................................................................. 72
   5.10.1 Detailed project analysis per activity for the Guinea Community-based Land Management Project ..... 74
      5.10.1.1 Deforestation activities (FLU: set aside land and annual cropland) .............................................. 74
      5.10.1.2 Annual cropland improvement ........................................................................................................ 74
      5.10.1.3 Perennial cropland development (ILU: annual crops).................................................................... 75
      5.10.1.4 Forest management and degradation (forest fire management) ..................................................... 75
   5.10.2 Project carbon balance ............................................................................................................................ 76


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5.11 Jordan, Integrated Ecosystem Management in the Jordan Rift Valley ........................................................... 76
   5.11.1 Detailed project analysis per activity for the Jordan Integrated Ecosystem Management in the Jordan
   Rift Valley Project ............................................................................................................................................. 77
      5.11.1.1 Grassland development (ILU: set aside land) ................................................................................. 77
5.12 Mali, Natural Resources Management in a Changing Climate ...................................................................... 78
   5.12.1 Detailed project analysis per activity for the Mali Natural Resources Management in a Changing
   Climate Project................................................................................................................................................... 79
      5.12.1.1    Deforestation (FLU: grassland) ................................................................................................. 79
      5.12.1.2 Afforestation activities (ILU: set aside land and degraded land).................................................... 80
      5.12.1.3 Annual cropland improvement ........................................................................................................ 80
      5.12.1.4 Grassland management ................................................................................................................... 81
   5.12.2 Project carbon balance ............................................................................................................................ 82
5.13 Moldova, Agriculture Competitiveness Project .............................................................................................. 82
   5.13.1 Detailed project analysis per activity for the Moldova Agriculture Competitiveness Project................. 83
      5.13.1.1 Annual cropland improvement ........................................................................................................ 83
      5.13.1.2 Perennial cropland improvement .................................................................................................... 84
5.14 Morocco, GEF Social and Integrated Agriculture (ASIMA) .......................................................................... 85
   5.14.1 Detailed project analysis per activity for the Morocco GEF Social and Integrated Agriculture (ASIMA)
   ........................................................................................................................................................................... 86
       5.14.1.1 Perennial cropland development (ILU: degraded land) ................................................................. 86
       5.14.1.2 Annual cropland improvement ........................................................................................................ 87
       5.14.1.3 Livestock .......................................................................................................................................... 88
5.15 Serbia, Contribution of Sustainable Forest Management to a Low Emission and Resilient Development
Project..................................................................................................................................................................... 88
   5.15.1 Detailed project analysis per activity for the Serbia Contribution of Sustainable Forest Management to a
   Low Emission and Resilient Development Project ............................................................................................ 89
      5.15.1.1 Afforestation/reforestation (ILU: grassland, set aside land, and degraded land)........................... 89
      5.15.1.2          Deforestation (FLU: set aside land)........................................................................................... 90
      5.15.1.3 Forest management and degradation .............................................................................................. 91
   5.15.2 Project carbon balance ............................................................................................................................ 91
5.16 Turkey, Sustainable land Management and Climate-Friendly Agriculture .................................................... 91
   5.16.1 Detailed project analysis per activity for the Turkey Sustainable Land Management and Climate-
   Friendly Agriculture Project .............................................................................................................................. 92
      5.16.1.1 Annual cropland improvement ........................................................................................................ 92
      5.16.1.2 Forest management and degradation .............................................................................................. 93
      5.16.1.3 Grassland management ................................................................................................................... 93
   5.16.2 Project carbon balance ............................................................................................................................ 94
5.17 Chile, Sustainable Land Management Project................................................................................................ 94
   5.17.1 Key project activities acting on GHG ..................................................................................................... 95
      5.17.1.1 Aysen Cohaique site ........................................................................................................................ 95
      5.17.1.2 Combarbalá site .............................................................................................................................. 95
      5.17.1.3 Ohiggins - Litueche site ................................................................................................................... 96
      5.17.1.4 Araucania - Los Sauces (previously purto saaverda) ...................................................................... 96
   5.17.2 Detailed project analysis per activity for the Chile Sustainable Land Management and Climate-Friendly
   Agriculture Project ............................................................................................................................................. 97
      5.17.2.1 Afforestation activities (ILU: degraded land and grassland) .......................................................... 98
      5.17.2.2 Grassland management ................................................................................................................... 99
      5.17.2.3 Forest management and degradation .............................................................................................. 99
   5.17.3 Project carbon balance .......................................................................................................................... 100
      5.17.3.1 EX-ACT analysis ........................................................................................................................... 100
      5.17.3.2 CBP analysis ................................................................................................................................. 100
   5.17.4 Conclusion ............................................................................................................................................ 101



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    5.18 Tunisia, Second Natural Resources Management Project ............................................................................ 101
       5.18.1 Key project activities acting on GHG ................................................................................................... 102
          5.18.1.1 Médenine sites ............................................................................................................................... 102
             Afforestation activities ............................................................................................................................ 102
             Grassland management .......................................................................................................................... 102
             Annual crops........................................................................................................................................... 103
             Perennial crops ...................................................................................................................................... 103
          5.18.1.2 C.R.D.A Kasserine......................................................................................................................... 104
             Grassland management development ..................................................................................................... 104
             Perennial crops development and improvements ................................................................................... 104
          5.18.1.3 C.R.D.A Jendouba ......................................................................................................................... 104
             Grassland management and development .............................................................................................. 104
             Perennial crops development and improvement ..................................................................................... 104
             Livestock activities: C.R.D.A Médenine, Kasserine, and Jendouba ....................................................... 105
             Inputs and investments: C.R.D.A Médenine, Kasserine, and Jendouba ................................................. 105
             Fertilizer use ........................................................................................................................................... 105
       5.18.2 Detailed project analysis per activity for the Tunisia GEF Second Natural Resources Management
       Project .............................................................................................................................................................. 106
          5.18.2.1 Afforestation activities (ILU: degraded land) ............................................................................... 106
          5.18.2.2 Annuals cropland development and improvement ......................................................................... 107
          5.18.2.3 Perennial cropland development (ILU: set aside)......................................................................... 108
          5.18.2.4 Grassland management and development ..................................................................................... 108
          5.18.2.5 Livestock ........................................................................................................................................ 109
          5.18.2.6 Inputs and investments (fertilizers, irrigation, and agricultural buildings) .................................. 109
       5.18.3 Project carbon balance .......................................................................................................................... 109
          5.18.3.1 EX-ACT analysis ........................................................................................................................... 110
       5.18.4 Conclusion ............................................................................................................................................ 110

6. Discussion: Overall performance of the suitable tools ..................................................................................... 113
    6.1 Review of the detailed characterization of suitable tools................................................................................ 113
    6.2 Tools coverage and performance relative to SLM activities ........................................................................... 114
       6.2.1 Afforestation and reforestation activities ................................................................................................ 114
       6.2.2 Deforestation activities............................................................................................................................ 115
       6.2.3 Forest management ................................................................................................................................. 115
       6.2.4 Annual cropland ...................................................................................................................................... 115
       6.2.5 Perennial cropland................................................................................................................................... 116
       6.2.6 Grassland management ........................................................................................................................... 116
       6.2.7 Livestock ................................................................................................................................................. 117
       6.2.8 Inputs management (fertilizers and pesticides) ....................................................................................... 117
       6.2.9 Investments ............................................................................................................................................. 117
       6.2.10 Versatility of the tools ........................................................................................................................... 117
    6.3 Comparison of results between tools .............................................................................................................. 119
       6.3.1 Results analysis ....................................................................................................................................... 121
    6.4 Multicriteria GHG tool selector for SLM Projects ......................................................................................... 122

7. Conclusions and recommendations .................................................................................................................... 123

Annex: Detailed Results of Carbon Balance Appraisals ...................................................................................... 126

References ................................................................................................................................................................ 133




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FIGURES
Figure E1: Step-by-step process for selecting a GHG calculator…………………………………………………....16
Figure 1: Components of the SLM-CCMC Project ..................................................................................................... 18
Figure 2: Carbon balance per component and per tool (Forestry Development Project, Belarus) .............................. 50
Figure 3: Carbon balance per component and per tool (BR GEF Rio Grande do Sul Biodiversity, Brazil) ................ 53
Figure 4: Carbon balance per component and per tool (Caatinga Conservation and Sustainable Management Project,
Brazil) .......................................................................................................................................................................... 55
Figure 5: Carbon balance per component and per tool (Third Phase Community Based Rural Development Project,
Burkina Faso) .............................................................................................................................................................. 58
Figure 6: Carbon balance per component and per tool (Sustainable Coffee Landscape Project, Burundi) ................. 60
Figure 7: Carbon balance per component and per tool (Guangxi Integrated Forestry Development and Conservation
Project, China) ............................................................................................................................................................. 63
Figure 8: Carbon balance per component and per tool (Shanghai Agricultural and Non-point Pollution Reduction
Project, China) ............................................................................................................................................................. 65
Figure 9: Carbon balance per component and per tool (Biodiversity Conservation in Cacao Agroforestry, Costa
Rica) ............................................................................................................................................................................ 67
Figure 10: Carbon balance per component and per tool (Country Program for SLM, Ethiopia)................................. 69
Figure 11: Carbon balance per component and per tool (Community-based Land Management Project, Guinea)..... 73
Figure 12: Carbon balance per component and per tool (Integrated Ecosystem Management in the Jordan Rift
Valley, Jordan) ............................................................................................................................................................ 77
Figure 13: Carbon balance per component and per tool (Natural Resources Management in a Changing Climate,
Mali) ............................................................................................................................................................................ 79
Figure 14: Carbon balance per component and per tool (Agriculture Competitiveness Project, Moldova) ................ 83
Figure 15: Carbon balance per component and per tool (GEF Social and Integrated Agriculture, Morocco)............. 86
Figure 16: Carbon balance per component and per tool (Contribution of Sustainable Forest Management to a Low
Emission and Resilient Development, Serbia)............................................................................................................. 89
Figure 17: Carbon balance per component and per tool (Sustainable land Management and Climate-Friendly
Agriculture, Turkey) .................................................................................................................................................... 92
Figure 18: Carbon balance per component and per tool (Sustainable Land Management Project, Chile) .................. 98
Figure 19: Carbon balance per component and per tool (Second Natural Resources Management, Tunisia) ........... 106
Figure 20: Step-by-step process for selecting a GHG calculator ............................................................................... 122
Cover photo: Kate Evans/CIFOR

TABLES
Table E1: Activity scope of GHG tools………………………………………………………………………………14
Table E2: Data, Time and Skills requirements of the tools…………………………………………………………..15
Table 1: SLM approaches and technologies ................................................................................................................ 20
Table 2: Website, developer, and geographical coverage of the carbon accounting tools ........................................... 24
Table 3: Activity scope for the tools............................................................................................................................ 26
Table 4: Data, time, and skills requirements of the tools ............................................................................................. 27
Table 5: Prescreening results of 10 tools ..................................................................................................................... 28
Table 6: Detailed information on the three unsuitable tools ........................................................................................ 30
Table 7: Selected tools and carbon credit .................................................................................................................... 41
Table 8: Tools comparison based on the IPCC GHG accounting approaches and carbon pools ................................. 42
Table 9: Sources, sinks, and SLM activities accounted for by each tool ..................................................................... 44
Table 10: Uncertainty and leakage accounting in the carbon accounting tools ........................................................... 45
Table 11: Results types provided by the carbon accounting tools ............................................................................... 46
Table 12: List of projects selected for the study .......................................................................................................... 47
Table 13: Definition of activity-categories considered in line with IPCC’s and FAO’s definitions............................ 48
Table 14: Carbon balance results for the Mali Natural Resources Management in a Changing Climate Project ........ 82
Table 15: Carbon balance results for Agriculture Competitiveness Project. ............................................................... 85
Table 16: Temperate continental forest carbon sequestration potential within the biomass ........................................ 95
Table 17: Woodland forest carbon sequestration potential within the biomass and dead wood .................................. 95
Table 18: Subtropical steppe forest carbon sequestration potential within the biomass .............................................. 96
Table 19: Subtropical steppe forest carbon sequestration within the biomass ............................................................. 96
Table 20: Broadleaved forest carbon sequestration potential within the biomass ....................................................... 96


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Table 21: Subtropical dry forest carbon sequestration within the biomass.................................................................. 96
Table 22: Subtropical humid forest carbon sequestration potential within the biomass .............................................. 97
Table 23: Afforestation/reforestation scenarios within the project’s three sites .......................................................... 97
Table 24: Forestry rehabilitation scenarios within the project’s three sites ................................................................. 97
Table 25: Grassland management scenarios within the project’s three sites ............................................................... 97
Table 26: Afforestation activities PRGN2 project-species above-ground net volume growth .................................. 102
Table 27: Grassland management activities, Médenine............................................................................................. 103
Table 28: Annual crops development and improvement activities, Médenine .......................................................... 103
Table 29: Growth rates for olives and orchards up to 20 years (tC/ha/year) ............................................................. 104
Table 30: Livestock management activities for the three sites .................................................................................. 105
Table 31: Infrastructures development PRNG2 project............................................................................................. 105
Table 32: Afforestation activities .............................................................................................................................. 110
Table 33: Grassland management (C.R.D.A Médenine) ........................................................................................... 110
Table 34: Annuals crops management and development........................................................................................... 111
Table 35: Perennial crops management and development ......................................................................................... 111
Table 36: Data, time, and skills requirements of the suitable tools ........................................................................... 113
Table 37: Analysis type, IPCC GHG accounting approaches, GHG, carbon pools, uncertainty and leakage accounted
for by the suitable tools ............................................................................................................................................. 114
Table 38: Tools and frequency of SLM activities assessed ....................................................................................... 114
Table 39: Recommended tools per land use activity ................................................................................................. 118
Table 40: Recommended tools when considering land use change scenarios ........................................................... 119
Table 41: Comparison of results: Desk study, Tier 1 methodology versus in-depth analysis, Tier 2 methodology .. 120




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Acknowledgments
This report drew from contributions from a range of experts working on agriculture and climate
change. We thank everyone who contributed to its richness and multidisciplinary outlook. The
work was led by Ademola Braimoh from the World Bank and Louis Bockel from the Food and
Agriculture Organization of the United Nations (FAO) who developed the concepts and provided
overall guidance to the team. The report was written by Anass Toudert from FAO with
contributions from Martial Bernoux, Maylina St-Louis, Manar Abdelmagied, and Adriana
Ignaciuk. The work was completed under the overall supervision of Jurgen Voegele and Mark
Cackler.

We acknowledge the support of colleagues from the United Nations Environment Program:
Mohamed Sessay, Gemma Shepherd, Adamou Bouhari, Patrick Mmayi, Maarten Kappelle,
Peninah Wairimu-Kihuha, Joyce Ngugi and Florence Kahiro. We also thank Mohamed Bakarr,
Ulrich Apel, Pascal Andre Claude Martinez, and Manuela Ravina da Silva (GEF).

We also acknowledge the comments from Eleanor Milne, Mark Easter and Keith Paustian of
Colorado State University whose insight greatly enriched the study. The support provided during
field work is also acknowledged. We thank Javier Cano Martín and Angelo Sartori (Corporación
Nacional Forestal, Chile), Afef Ben Abda, Lamia Jemmeli (Director, Ministry of Agriculture,
Water Resources and Fisheries, Tunisia), and Chokri Walha (Regional Coordinator, Ministry of
Agriculture, Hydraulic Resources and Fisheries, Tunisia), Ryan Zuniga (FAO), and Stavros
Papageorgiou, and Anatol Gobjila (World Bank).

The contributions of Xiaoyue Hou and Yu Huan (World Bank) to the e-learning module
accompanying the report are also acknowledged.




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Acronyms
AFD-CFT      Agence Française de Développement Carbon Footprint Tool
AFOLU        Agriculture, Forestry, and Other Land Use
CAT-AR       Carbon Assessment Tool for Afforestation and Reforestation
CATIE        Centro Agronómico Tropical de Investigación y Enseñanza
CAT-SFM      Carbon Assessment Tool for Sustainable Forest Management
CBP          Carbon Benefits Project
CCAFS-MOT    Climate Change, Agriculture, and Food Security Mitigation Options Tool
CDM          Clean Development Mechanism
CFT          Cool Farm Tool
CONAF        Chilean National Forestry Corporation
COP21        Conference of the Parties to the UN Framework Convention on Climate Change
CSU          Colorado State University
DA           Detailed Assessment
DNDC         De Nitrification-De Composition Model
EF           Emission Factor
EX-ACT       Ex-Ante Carbon-Balance Tool
FAO          Food and Agriculture Organization of the United Nations
FLU          Final Land Use
GEF          Global Environment Facility
GEO          Global Environment Objective
GHG          Greenhouse Gas
GZAR         Guangxi Zhuang Autonomous Region
HFC          Hydrofluorocarbon
ILU          Initial Land Use
IPA          Integrated Participatory Approach
IPCC         Intergovernmental Panel on Climate Change
IPCC-GNGGI   Intergovernmental Panel on Climate Change Guidelines for National
             Greenhouse Gas Inventories
IPCC-GPG     Intergovernmental Panel on Climate Change Good Practice Guidance for Land
LULUCF       Use, Land-Use Change and Forestry
LCA          Life Cycle Analysis
M&E          Monitoring and Evaluation
MAT          Mean Annual Temperature
NPP          Net Primary Production
PDP          Participatory Development Plan
PFC          Perfluorocarbon
SA           Simple Assessment
SF 6         Sulphur Hexafluoride


                                                                                     10
SLM        Sustainable Land Management
SLM-CCMC   Sustainable Land Management and Climate Change Mitigation Co-Benefits
SOC        Soil Organic Carbon
TARAM      Tool for Afforestation and Reforestation Approved Methodologies
USAID      U.S. Agency for International Development
VGSSM      Voluntary Guidelines for Sustainable Soil Management




                                                                                   11
Executive Summary
    1) At the 21st Conference of the Parties to the UN Framework Convention on Climate Change
       (COP21) in Paris, in December 2015, 195 countries negotiated a binding agreement to limit
       global warming below 2°C compared to pre-Industrial levels, and to pursue efforts to limit
       the temperature increase to 1.5°C. As global absolute greenhouse gas (GHG) emissions
       continue to increase, COP21 raised the sense of urgency and called for more ambitious
       mitigation actions. In the case of carbon dioxide (CO 2 ), the leading GHG contributing to
       temperature change, limiting the temperature increase to 1.5°C and 2°C by 2050 and 2070,
       respectively, would necessitate a net-zero CO 2 emissions scenario.

    2) Agriculture, Forestry, and Other Land Use (AFOLU) sector is unique among economic
       sectors because its mitigation potential derives from both an enhancement of removals of
       GHGs and a reduction of emissions through management of land and livestock. The
       AFOLU sector is responsible for just under a quarter (approximately 10–12 GtCO 2 eq per
       year) of global anthropogenic GHG emissions, mainly due to deforestation and agricultural
       emissions from livestock, soil, and nutrient management. AFOLU emissions could change
       substantially in transformational pathways, given the high mitigation potential from
       agriculture, forestry, and bioenergy. Mitigation options in the AFOLU sector, therefore,
       need to be assessed, as far as possible, for their potential impact on all other services
       generated by land.

    3) We cannot fix what we do not measure, which is why quantifying greenhouse gas (GHG)
       emissions from agricultural landscapes is a necessary step for climate-smart agriculture
       (CSA) 1 and sustainable land management (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-emission development, assessing product supply chains, certifying
       sustainable agriculture practices, and informing consumers on the carbon footprint of their
       choices (Olander et al. 2013).

    4) This report compares the relative performance of available GHG accounting tools for SLM,
       defined as the implementation of land use systems and management practices that enable
       humans to maximize the economic and social benefits from land while maintaining or
       enhancing the ecosystem services that land resources provide. The report seeks to answer


1
  Climate-smart agriculture (CSA) is an integrated approach that aims to address the interlinked challenges of food
security and climate change by sustainably increasing agricultural productivity to support equitable increases in farm
incomes, food security, and development; adapting and building resilience of agricultural and food systems to
climate change at multiple levels; and reducing greenhouse gas (GHG) emissions from agriculture.



                                                                                                                   12
   questions such as which carbon assessment tools are available and under what conditions
   they are best applicable for assessing SLM GHG footprint.

5) The first step in the study identified the following 10 commonly used carbon accounting
   tools for further analysis:
       • Carbon Benefits Project Simple and Detailed Assessment tools developed by the
           GEF-funded ‘Carbon Benefits Project’ (CBP SA and DA)
       • Agence Française de Développement Carbon Footprint Tool (AFD-CFT)
       • Forest Carbon Calculator (U.S. Agency for International Development [USAID]
           Agriculture, Forestry, and Other Land Use [AFOLU] Carbon Calculator)
       • Carbon Assessment Tool for Afforestation and Reforestation (CAT-AR)
       • Carbon Assessment Tool for Sustainable Forest Management (CAT-SFM)
       • Climate Change, Agriculture, and Food Security Mitigation Options Tool (CCAFS-
           MOT)
       • Cool Farm Tool (CFT)
       • DeNitrification-DeComposition Model (DNDC)
       • Ex-Ante Carbon-Balance Tool (EX-ACT)
       • Tool for Afforestation and Reforestation Approved Methodologies (TARAM)

6) The tools were mapped within the wide range of potential carbon sequestration and GHG
   emission reduction activities, thereby developing a resource for managers of SLM projects
   to choose the most appropriate tool under different contexts. The study went beyond desk
   exercise and includes running the tools on real datasets from 18 Global Environment
   Facility (GEF) projects spreading across 16 countries representing a wide range of
   ecosystems. Many of these countries are highly dependent on the production and exports of
   agricultural goods and face a range of climate change-related challenges. The analyses
   were user-driven, to understand the underlying peculiarities of each tool and their
   differences, thereby enabling the users to make an informed choice on the suitable GHG
   calculator(s) under specific contexts.

7) The study indicates that many advanced tools have been developed, the methodologies
   applied by the tools are relatively similar, and tool developers align their methodology with
   the IPCC guidelines. The tools are moderately data, skills, and time-demanding and offer
   many additional functions including carbon footprint, socioeconomic analysis, and multiple
   area analysis. The methodologies on which the tools are based are transparent and detailed
   in guidance documents.

8) GHG assessment can be implemented for different reasons, depending on stakeholders and
   local context. Tools should be able to compare a “without project” scenario to a “with-
   project” situation. They should also consider pertinent issues like improving productivity
   and rural livelihoods, restoring degraded lands and afforestation/reforestation and forest
   management. A useful tool should also account for all possible mitigation options: carbon
   conservation, sequestration and emissions reduction, and emissions from different land


                                                                                             13
         covers associated with SLM activities. The screening of the GHG tools in terms of
         activities scope, that is, the extent to which they can handle a wide range of SLM activities
         indicate that two tools: CBP and EX-ACT are the most versatile, able to address GHG
         emissions from non-vegetative surfaces to cropland, grassland and forest cover. CAT-AR,
         CAT-SFM and TARAM are the least versatile, reflecting the fact that the tools were
         specifically developed to address the forest sector (Table E1).

                                                                              Table E1: Activity scope of GHG tools




                                                                                                      Perennial production
                                                                                                       Field trees, hedges,
                        Temperate crops




                                                           Rice cultivation
                                          Tropical crops




                                                                                                                                                  Settlements 2
                                                                                                          agroforestry




                                                                                                                                                                  Other land 3
                                                                                                           vineyards)
                                                                              Grassland




                                                                                                           (orchards,
                                                                                          Livestock




                                                                                                                                       Wetlands
                                                                                                                              Forest
                                                                                                                                                                                 Score
No.         Tool                                                                                                                                                                         Assessment Ratings
                                                                                                                                                                                  (%)




    1       CBP         x                 x                x                  x           x            x          x           x        x          x               no             91            ++++
    2    AFD-CFT        x                 x                no                 x           x            no         no          x        no         x               x              73            +++
    3     AFOLU         x                 x                x                  x           x            x          x           x        no         no              no             73            +++
    4    CAT-AR         no                no               no                 no          no           no         no          x        no         no              no              9             +
    5    CAT-SFM        no                no               no                 no          no           no         no          x        no         no              no              9             +
    6     CCAFS         x                 x                x                  x           x            x          x           no       no         no              no             64            +++
    7       CFT         x                 x                x                  no          x            x          x           no       no         no              no             55            +++
    8      DNDC         x                 x                x                  x           x            no         x           no       no         no              no             55            +++
    9     EX-ACT        x                 x                x                  x           x            x          x           x        x          x               x              100           ++++
    10    TARAM         no                no               no                 no          no           no         no          x        no         no              no              9             +

    x means the tool meets the criterion; no means the tool does not. Score is the number of activities out of 11 for which a tool is
                                    suitable, expressed in percent. Ratings are assigned as follows:
                                                     0 % <Tool score ≤ 25 %  +
                                                    25 % < Tool score ≤ 50%  ++
                                                   50 % < Tool score ≤ 75 %  +++
                                                      Tool score > 75 %  ++++

     9) Data for GHG appraisals are typically sourced during project identification up to appraisal.
        One of the main challenges include how to consider the heterogeneity of production
        systems and biological processes involved in GHG emissions; and up-scaling from the
        farm to a landscape assessment, all of which have implications for data needs (Colomb,
        2013) 4. At plot scale and farm scale, technical data are easily available and can be provided
        directly by farmers. At the regional scale, data inventory often needs to be obtained from
        statistical databases or expert knowledge leading to an increase in uncertainties.



2
  Settlements: This category includes all developed land, including transportation infrastructure and human
settlements of any size, unless they are already included under other categories. This should be consistent with
national definitions
3
  Other land: which includes areas with bare soil, rock, and ice, in addition to all land areas that do not fall into the
other five land-use categories including degraded lands.
4
 Colomb V, Touchemoulin O, Bockel L, Chotte J L, Martin S, Tinlot M and Bernoux M 2013 Selection of
appropriate calculators for landscape-scale greenhouse gas assessment for agriculture and forestry Environ. Res.
Lett. Vol 8 (1) 015029



                                                                                                                                                                                                          14
    10) 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 (Table E2). 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
        evaluations.

                           Table E2: Data, Time and Skills requirements 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 <Time necessary ≤ 10 min  ++++    ++++ to +; from basic skills
                         ++++ to +; from low data
    (modified from                                    10 min <Time necessary≤ 20 min  +++          requirements to
                      requirements to medium/ high/
    Colomb, 2013) 5                                    20 min <Time necessary≤30 min  ++     /medium/high/very high skills
                        very high data requirements
                                                           Time necessary > 30 min  +               requirements


    11) The accuracy of the different quantification methods is classified in three tiers, Tier 1
        methods being the least accurate. The accuracy of the method depends on the emission
        factors (EFs) and the project activity data used. Region-specific EFs and activity data are
        more accurate than country-specific EFs and should preferably be used. Nevertheless, other
        context-specific aspects should be considered to provide the users with tools that are
        comprehensible, standardized, robust, and applicable to SLM projects.

    12) The report also shows that the completeness aspect is key in comparing the tools: GHG
        assessments are not always reported for all relevant categories of sources and sinks and
        GHGs. Some tools cover only some land use activities whereas other tools cover almost all
        land use activities. Furthermore, scope definitions vary and the number and type of GHGs
        covered differ across tools. As such, it is recommended to extend the scope of the
        calculators while restricting the data, skills, and time needed and increasing their accuracy.
        For international dissemination of these tools, their availability in different languages is
        crucial.



5
 Colomb V, Touchemoulin O, Bockel L, Chotte J L, Martin S, Tinlot M and Bernoux M 2013 Selection of
appropriate calculators for landscape-scale greenhouse gas assessment for agriculture and forestry Environ. Res.
Lett. submitted



                                                                                                                         15
13) The accuracy of a tool depends mainly on the data that feed into it. Thus, it depends on data
    availability at the local level, on the one hand, and on support of the users and advice on
    how to find data, on the other. All tools offer the option to specify Tier 2 values, country-
    specific EFs. Desk studies analysis based on project documentation is often lacking
    comprehensive and reliable datasets for the compilation of GHG assessment, which will
    decrease the level of uncertainty. Data collection and quality assurance at the local level is
    therefore recommended.
14) The suggested process for selecting a suitable calculator(s) is based on the characteristics of
    each calculator. Users should select tools according to more specific criteria, helped by the
    tables provided in this report.

                   Figure E1: Step-by-step process for selecting a GHG calculator




                                                                                                16
1.         Introduction
    15) Agriculture is intrinsically linked to climate, with most agricultural technologies having
        direct or indirect climate links. Agriculture and the patterns of land use change (LUC) 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; FAO et al. 2017; IPCC 2001; Lobell et al. 2008).

    16) Climate change poses a major challenge to the agricultural sector due to the dependence of
        agriculture on climate and the complex role it plays in rural, social, and economic contexts
        (Hatfield et al. 2011). According to the FAO (2002), the rising incidence of weather
        extremes will have increasingly negative impacts on crop productivity, especially if
        occurring at sensitive stages in crop life cycles (National Climate Assessment 2014). The
        Intergovernmental Panel on Climate Change (IPCC), in its fifth assessment report, predicts
        that climate change will affect food security substantially by the mid-21st century.

    17) Yet climate-smart agriculture and sustainable land management practices such as
        reforestation, improved water management, integrated soil fertility management,
        conservation agriculture, agroforestry, better rangeland management can be major sinks,
        presenting opportunities to mitigate climate change by removing substantial volumes of
        carbon from the atmosphere and sequestering them in soils and plant tissues.

    18) 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).

    19) 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. 6 This report documents efforts of a study under the Sustainable Land Management
        and Climate Change Mitigation Co-benefits (SLM-CCMC) project financed by the Global
        Environment Facility (GEF) to create an environment which will make it easier for land
        management project managers to realize the climate change co-benefits of climate-smart

6
    Within the current study, the terms ‘tools’ and ‘calculators’ are used interchangeably.



                                                                                                  17
         agriculture and sustainable land management practices. 7 The project has 3 components
         (Figure 1): 1) Training and outreach for Carbon Benefit Project (CBP) tools; 2)
         Enhancement of existing CBP tools set and 3) Comparative analysis of C accounting tools
         (Figure 1).

                                Figure 1: Components of the SLM-CCMC Project




    20) This report covers Component 3 implemented by the World Bank with support from the
        FAO and the Colorado State University. It compares the relative performance of available
        GHG accounting calculators for SLM, and answers questions such as which carbon
        assessment tools are available and under what conditions they are best applicable for
        assessing SLM GHG emissions. The overall goal is to provide users with helpful
        information for choosing the most appropriate calculator in each case, and to highlight
        major methodological differences between the calculators. Commonly used GHG tools are
        mapped within the wide range of potential carbon sequestration and GHG emission
        reduction activities, thereby developing a resource for the Global Environment Facility
        (GEF) and other managers of SLM projects to choose the most appropriate tool. The
        analysis goes beyond desk study and includes running the tools on real datasets from 18
        GEF projects and builds on existing reviews and online tools (Colomb et al. 2013; Denef et
        al. 2011; Milne et al, 2013; World Bank 2012a).




7
    https://www.thegef.org/project/sustainable-land-management-and-climate-change-mitigation-co-benefits-slm-ccmc




                                                                                                              18
2.         Sustainable land management and carbon benefits
2.1        Sustainable land management defined

    21) 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.

    22) 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.

    23) There is increasing scientific evidence on the potential advantages and co-benefits
        associated with adopting SLM technologies and practices, including the protection of
        biodiversity and securing the quantity and quality of soil and water resources in the long
        term. Recognizing that there is no overarching solution to land degradation and low
        productivity, the selection of appropriate SLM practices should be site specific to ensure
        appropriate targeting of the root causes. Therefore, SLM technologies for a specific project
        area should be based on the qualities and characteristics of the local land resources; the
        SLM requirements of land use to be pursued; and the socioeconomic context and priorities
        of land users. While SLM should target the impact at the landscape level, technologies and
        practices are usually based on gaining incremental improvements within the land use
        production system by integrating local practices that will result in several benefits,
        including:
          • Improved plant management (for example, higher yields, good vegetative cover, and
              reduced rain impact); 8
          • Improved soil and nutrient management (for example, higher organic matter levels;
              integrated plant nutrition, improved soil structure, and good rooting conditions);
          • Improved rainwater management (for example, reduced runoff, increased infiltration,
              and improved soil moisture conditions); and
          • Reduced risk to production systems, people, and assets.




8
    Annual and perennial crops, grasses, and other herbaceous pasture species, trees, and shrubs.



                                                                                                    19
 24) 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)

2.2    Carbon benefits of SLM projects

 25) SLM has the potential to deliver carbon benefits in three important ways (World Bank,
    2012b):
      • The first is through carbon conservation, in which the large volumes of carbon stored
         in natural forests, grasslands, and wetlands remain stored as carbon stocks.
         Conserving this terrestrial carbon represents a ‘least-cost opportunity’ in terms of
         climate change adaptation and mitigation and is essential to increasing the resilience
         of agricultural ecosystems.
      • The second is through carbon sequestration, in which the growth of agricultural and
         natural biomass actively removes carbon from the atmosphere and stores it in soil by
         increasing soil organic carbon (SOC) and biomass (both above and below the ground).
      • The third is through the reduction of GHG emissions that emanate from agricultural
         production, including those emissions that result from land use change (LUC) in
         which carbon stocks become carbon sources as agricultural production expands into
         natural ecosystems. The potential and magnitude of each of these benefits depend on



                                                                                                             20
                the baseline conditions and on the local environmental, socioeconomic, and cultural
                conditions.

    26) Understanding the potential for SLM technologies and practices to mitigate GHG
        emissions in the agriculture sectors requires cost-effective tools that can assess total-system
        carbon benefits. Estimates of this potential should consider the full GHG balance, including
        possible combinations of different activities and practices that could affect the net climate
        change mitigation potential. Such tools should be comprehensible, standardized, robust,
        and applicable to SLM projects, policies, and strategies. In the last few years, several
        carbon accounting tools have been developed following different approaches to meet the
        needs of various users.

2.3        Methodology for the study

    27) This study is designed to compare the relative performance of available GHG accounting
        tools 9 and help potential users select the most appropriate tool(s) for an SLM project’s
        GHG assessment. It seeks to answer questions such as which carbon assessment calculators
        are available and under what conditions they are best applicable for assessing the SLM
        GHG emissions.

    28) To facilitate the different activities of targeting climate change mitigation in agriculture,
        decision makers can currently choose from a wide range of available GHG tools. Many
        tools have been developed for assessing GHG emissions from SLM activities in the last
        few years. 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. Each tool is characterized by certain competitive advantages and is
        often the first methodological choice with regard to its own field of specialization.

    29) The tools selection builds on the outcome of Colomb et al. (2012, 2013) studies and the
        documentation provided with each calculator. Six prescreening criteria were applied:
        availability, geographical coverage, activities scope, data requirements, time requirements,
        and skills requirements. Out of the 10 prescreened tools, the 7 tools with the highest global
        screening scores were selected for the comparative analysis and, therefore, for real project
        datasets’ evaluation. The short-listed tools were further explored in terms of how they can
        be used; types of activities considered; GHG assessment boundary; carbon pools, sources,
        and sinks; associated GHG emissions; and other relevant criteria. The testing of the tools
        goes beyond a desk exercise and includes running the tools on real datasets from GEF
        projects. Eighteen SLM projects were identified and analyzed using the seven short-listed
        tools. Two projects were subject to field data collection and are used as case studies for an
        in-depth assessment of each tool.


9
    In this report, the terms ‘tools’ and ‘calculators’ are used interchangeably.



                                                                                                    21
30) Based on the tools’ scope and the IPCC GHG accounting approaches, 51 activities were
    assessed and eight main SLM activities were identified. The selected projects represent the
    implementation of land use systems and management practices across a wide spectrum of
    SLM technologies. Countries were selected to represent a range of ecosystems (for
    example, tropical, temperate, and semi-arid) and agro-ecological zones representing five
    regions (Africa, Middle East and North Africa, Latin America and the Caribbean, Eastern
    Europe and Central Asia, and Europe). Results obtained by project/activity were analyzed
    and discussed. Standard deviation was used to measure variation or dispersion between
    values in a set of results data, providing an indication of how far the tools’ individual
    responses to a set of data vary or ‘deviate’ from the mean. Critical variables were identified,
    which allowed conclusions to be drawn on the relative transparency, completeness, and
    consistency of each tool.




                                                                                                22
3.     Screening of carbon accounting tools
3.1 Carbon tools identification and characterization

 31) 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. The first step in this analysis identified the following carbon
     accounting tools for further analysis:
         • Carbon Benefits Project Simple and Detailed Assessment tools developed by the
             GEF-funded ‘Carbon Benefits Project’ (CBP SA and DA)
         • Agence Française de Développement Carbon Footprint Tool (AFD-CFT)
         • Forest Carbon Calculator (U.S. Agency for International Development [USAID]
             Agriculture, Forestry, and Other Land Use [AFOLU] Carbon Calculator)
         • Carbon Assessment Tool for Afforestation and Reforestation (CAT-AR)
         • Carbon Assessment Tool for Sustainable Forest Management (CAT-SFM)
         • Climate Change, Agriculture, and Food Security Mitigation Options Tool (CCAFS-
             MOT)
         • Cool Farm Tool (CFT)
         • DeNitrification-DeComposition Model (DNDC)
         • Ex-Ante Carbon-Balance Tool (EX-ACT)
         • Tool for Afforestation and Reforestation Approved Methodologies (TARAM)

 32) 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.
     Each tool is characterized by certain competitive advantages and is often the first
     methodological choice with regard to its own field of specialization.

 33) To facilitate a more informed tool selection, the tools selection builds on the outcome of
     Colomb et al. (2012, 2013) studies by applying the following six prescreening criteria:
      • Availability. This criterion allows us to evaluate whether the tool and its technical
          guidelines are freely accessible online (see Table 2).
      • Geographical coverage. This criterion allows us to evaluate the geographical context,
          that is, the continental regions where the tools are mostly applicable. (See Table 2).
      • Activities scope. This allows us to evaluate to what extent the tools can handle a wide
          range of SLM activities (see Table 3).
      • 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 a developing country context (see
          Table 4).


                                                                                                 23
       •   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 (see Table 4).
       •   Skills requirements. This indicates the extent to which skills needed for the analysis
           exceed what we consider 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 presented in this report are agronomic, forestry,
           or SLM skills (see Table 4).

3.1.1 Availability and geographical coverage

 34) All the 10 tools screened are readily available online and offer technical guidance for users.
     Table 2 shows the website, developer, and geographic coverage of each tool. The tools are
     web or Excel-based, are freely available on the Internet and can be downloaded directly or
     accessed through e-mail requests from the developers. Tool descriptions are usually
     generated on the website, and sometimes include case study applications. While most of the
     tools were developed in countries with industrial agricultural systems, researchers and
     users have been able to adapt them to development projects in countries where agriculture
     and SLM are key priorities.

          Table 2: Website, developer, and geographical coverage of the carbon accounting tools
                                                                                         Geographical
No.     Tool                    Website                         Developer
                                                                                       zone/application
 1    AFD-       http://www.afd.fr/lang/en/home/projet Agence Française de         World
      CFT        s_afd/changement_climatique/Liens_u Développement (France)        All climates
                 tiles_climat/4861736956
 2    AFOLU      http://www.afolucarbon.org/           USAID, Winrock              World
      Carb                                             International (United       All climates
                                                       States)
 3    CAT-AR http://www.worldbank.org/en/search? World Bank                        World
                 q=CAT-AR+                                                         All climates
                 percent28Carbon+Assessment+Tool+
                 for+Afforestation+and+Reforestation
                 percent29
 4    CAT-       http://documents.worldbank.org/curat  World Bank                  World
      SFM        ed/en/392001468331049999/pdf/9036                                 All climates
                 80WP0Box380tingguidanceforestry.p
                 df
 5    CBP        www.carbonbenefitsproject.org         GEF/United Nations          World
                                                       Environment Programme /     All climates
                                                       Colorado State University
                                                       (CSU)
 6    CCAFS- https://ccafs.cgiar.org/mitigation-       CGIAR CCAFS                 World
      MOT        option-tool-                                                      All climates
                 agriculture#.V717mU19670


                                                                                                          24
                                                                                             Geographical
No.     Tool                   Website                           Developer
                                                                                           zone/application
 7    CFT        https://www.coolfarmtool.org/           Unilever and researchers at   World
                                                         the University of Aberdeen    All climates
 8    DNDC       http://www.dndc.sr.unh.edu/             Institute for the Study of    United States, but has
                                                         Earth, Oceans, and Space,     been adapted to other
                                                         University of New             parts of the world
                                                         Hampshire (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.cf   World Bank Carbon             World
                 m?Page=BioCF&FID=9708&ItemID            Finance Unit                  All climates
                 =9708&ft=DocLib&CatalogID=4496
                 9

3.1.2 Activities scope

 35) GHG assessment can be implemented for different reasons, depending on the stakeholders
     and the local context. There is a need for carbon accounting tools that are capable of cross
     comparing ‘without-project’ and ‘with-project’ scenarios while at the same time addressing
     pertinent issues such as improving agricultural productivity, strengthening the resilience of
     rural livelihoods, and restoring degraded land resources. Furthermore, a useful tool should
     also account for all possible mitigation options: carbon conservation, sequestration, and
     emission reduction.

 36) According to the IPCC, GHG emissions reporting is addressed along the following six land
     use categories:
     • Forestland. This category includes all land with woody vegetation consistent with
         thresholds used to define forestland in the national GHG inventory. It also includes
         systems with a vegetation structure that currently falls below but in situ, could
         potentially reach the threshold values used by a country to define the forestland
         category.
     • Cropland. This category includes cropped land, including rice fields, and agroforestry
         systems where the vegetation structure falls below the thresholds used for the forestland
         category.
     • Grassland. This category includes rangelands and pasture land that are not considered
         cropland. It also includes systems with woody vegetation and other non-grass
         vegetation such as herbs and brushes that fall below the threshold values used in the
         forestland category. The category also includes all grassland from wild lands to
         recreational areas as well as agricultural and silvi-pastoral systems, consistent with
         national definitions.
     • Wetlands. This category includes areas of peat extraction and land that is covered or
         saturated by water for all or part of the year (for example, peatland) and that does not
         fall into the forestland, cropland, and grassland or settlements categories. It includes




                                                                                                            25
               reservoirs as a managed subdivision and natural rivers and lakes as unmanaged
               subdivisions.
          •    Settlements. This category includes all developed land, including transportation
               infrastructure and human settlements of any size, unless they are already included under
               other categories. This should be consistent with national definitions.
          •    Other land. This category includes areas with bare soil, rock, and ice, in addition to all
               land areas that do not fall into the other five land use categories including degraded
               lands.

     37) The scope of activities of the tools is indicated in Table 3, ranging from ability to assess
         GHG emissions from non-vegetative surfaces to cropland, grassland, and forest cover. The
         CBP and EX-ACT were identified as the most versatile tools capable of addressing most, if
         not all, land use activities. The least versatile tools identified where the CAT-AR, CAT-
         SFM, and TARAM, because they were developed to address the forestry sector.

                                                                                   Table 3: Activity scope for the tools
                                                                                                       Perennial production
                                                                                                        Field trees, hedges,
                         Temperate crops




                                                            Rice cultivation
                                           Tropical crops




                                                                                                                                                   Settlements 10


                                                                                                                                                                    Other land 11
                                                                                                           agroforestry


                                                                                                            vineyards)
                                                                               Grassland




                                                                                                            (orchards,
                                                                                           Livestock




                                                                                                                                        Wetlands
                                                                                                                               Forest
                                                                                                                                                                                    Score
No.           Tool                                                                                                                                                                          Assessment Ratings
                                                                                                                                                                                     (%)




 1           CBP         x                 x                x                  x           x            x          x           x        x          x                no              91            ++++
 2        AFD-CFT        x                 x                no                 x           x            no         no          x        no         x                x               73            +++
 3         AFOLU         x                 x                x                  x           x            x          x           x        no         no               no              73            +++
 4        CAT-AR         no                no               no                 no          no           no         no          x        no         no               no               9             +
 5        CAT-SFM        no                no               no                 no          no           no         no          x        no         no               no               9             +
 6         CCAFS         x                 x                x                  x           x            x          x           no       no         no               no              64            +++
 7           CFT         x                 x                x                  no          x            x          x           no       no         no               no              55            +++
 8          DNDC         x                 x                x                  x           x            no         x           no       no         no               no              55            +++
 9         EX-ACT        x                 x                x                  x           x            x          x           x        x          x                x               100           ++++
 10        TARAM         no                no               no                 no          no           no         no          x        no         no               no               9             +

     x means the tool meets the criterion; no means the tool does not. Score is the number of activities out of 11 for which a tool is
                                     suitable, expressed in percent. Ratings are assigned as follows:
                                                      0 % <Tool score ≤ 25 %  +
                                                     25 % < Tool score ≤ 50%  ++
                                                    50 % < Tool score ≤ 75 %  +++
                                                       Tool score > 75 %  ++++




10
   Settlements: This category includes all developed land, including transportation infrastructure and human
settlements of any size, unless they are already included under other categories. This should be consistent with
national definitions
11
   Other land: which includes areas with bare soil, rock, and ice, in addition to all land areas that do not fall into the
other five land-use categories including degraded lands.




                                                                                                                                                                                                             26
3.1.3 Data requirements

  38) Data for GHG appraisals is typically sourced during the project identification phase
      through the project appraisal process. The main challenges for the data needs of GHG
      assessments of SLM projects is the heterogeneity of production systems and biological
      processes involved in GHG emissions and the scaling-up of assessments from the farm to
      landscape level (Colomb et al. 2013). At plot and farm scale, technical data are more
      readily available and can be generated directly by farmers, while at the regional scale, data
      often need to be obtained from a statistical database or through expert knowledge, often
      increasing uncertainties.

3.1.4 Time and skills requirements

  39) Seven out of ten tools have moderately low data requirements. CAT-AR requires a high
      amount of data, while CAT-SFM and DNDC are notably higher in their data requirements
      (Table 4). The time required for analysis, given the availability of data, varies from ‘very
      short’ for the CCAFS-MOT to ‘very long’ for the DNDC, CBP, EX-ACT, and TARAM
      tools. There is close correlation between time and skills requirements for GHG analysis
      using the tools. Tools that are relatively highly skill-demanding, that is, they require more
      than the basic skills previously mentioned for assessments, correspondingly require more
      time to perform GHG evaluations.

                          Table 4: Data, time, and skills requirements of the tools
No.       Tool           Data requirements              Time requirements               Skills requirements
 1    AFD-CFT                 +++                                 ++                             +
 2    AFOLU Carb              +++                                +++                           +++
 3    CAT-AR                   ++                                +++                            ++
 4    CAT-SFM                   +                                 ++                             +
 5    CBP                     +++                                  +                             +
      CCAFS-
 6                            +++                               ++++                         ++++
      MOT
7     CFT                     +++                               +++                           +++
8     DNDC                      +                                  +                            +
9     EX-ACT                  +++                                ++                            ++
10    TARAM                   +++                                  +                            +
                                                 0 min < Time necessary ≤ 10 min
                                                  ++++
                      ++++ to +; from low data                                        ++++ to +; from basic
Legend                                           10 min < Time necessary ≤ 20
                      requirements to                                                 skills requirements to
(modified from                                   min  +++
                      medium/high/very high                                           medium/high/very high
Colomb et al. 2013)                              20 min < Time necessary ≤ 30
                      data requirements                                               skills requirements
                                                 min  ++
                                                 Time necessary > 30 min  +




                                                                                                               27
3.1.5 Conclusion and remarks

  40) All the tested tools are readily available online and have technical guidance. CBP and EX-
      ACT are identified as the most versatile by nature because they cover all land use activities.
      CAT-AR, CAT-SFM, and TARAM are the least versatile, reflecting the fact that the tools
      were specifically developed to address the forestry sector. Seven tools have moderately
      low-data requirements, one (CAT-AR) requires high amounts of data, while CAT-SFM and
      DNDC have very high data requirement.

  41) The overall prescreening results are presented in Table 5. Four criteria were considered in
      the final ratings, as there is no significant difference among the tools in terms of
      availability and geographic coverage. CCAFS-MOT achieved the highest rating of 81
      percent. It can handle many activities, and it is relatively low in data, time, and skills
      requirements. AFOLU Carb and CFT each received a global screening score of 75 percent,
      followed by EX-ACT with a score of 69 percent and CBP with a score of 62 percent. Five
      tools (CBP, AFD-CFT, CAT-SFM, DNDC, and TARAM) are highly skill-demanding, with
      the implication that more training may be required for users. Alternatively, developers
      could explore the possibility of simplifying the tools to encourage a larger number of users.
      The most time-demanding tools identified are the CBP, DNDC, and TARAM because the
      data and skills requirements are high.

                                    Table 5: Prescreening results of 10 tools

                     Activities        Data                 Time                Skills           Global screening
No.       Tool
                      scope        requirements         requirements         requirements           scorea (%)
 1    AFD-CFT           +++              +++                   ++                   +                    56
      AFOLU
 2                      +++              +++                  +++                +++                     75
      Carb
 3    CAT-AR               +              ++                  +++                  ++                    50
 4    CAT-SFM              +               +                   ++                   +                    31
 5    CBP              ++++              +++                     +                 ++                    62
      CCAFS-
 6                      +++              +++                ++++                 +++                     81
      MOT
 7    CFT               +++              +++                  +++                +++                     75
 8    DNDC              +++                +                     +                  +                    38
 9    EX-ACT           ++++              +++                   ++                  ++                    69
10 TARAM                   +             +++                     +                  +                    37
Note: a. Global prescreening score is the number of points (+) out of a maximum of 16, expressed in percentage.

  42) Apart from the activities scope, the DNDC scored low on all other screening criteria. The
      DNDC is simulation model based, lacking the interface (automated web or Excel)
      characteristic of most other tools. In addition to its highly demanding time and skills
      requirements, the CAT-SFM’s primary focus on assessing the net anthropogenic GHG
      removals by sinks and emissions in forest management activities gives it a limited activities
      scope.




                                                                                                                  28
43) Out of the 10 prescreened tools, 7 tools with the highest global screening scores were
    selected for the comparative analysis. In descending order of score, the selected tools are
    CCAFS-MOT, AFOLU Carb, CFT, EX-ACT, CBP Tools, AFD-CFT, and CAT-AR. More
    detailed information on the three tools with the lowest ratings are presented in Table 6.




                                                                                            29
                                                Table 6: Detailed information on the three unsuitable tools
   Tools                         CAT-SFM                                              DNDC                                             TARAM
              CAT-SFM closely follows the Guidance for           DNDC tool can be used for predicting crop         TARAM is an Excel-based spreadsheet that
              AFOLU Projects by the Voluntary Carbon             growth, soil temperature and moisture             facilitates the estimation of ex ante emission
              Standard (VCS Association 2008) to assess the      regimes, soil carbon dynamics, nitrogen           reductions either Temporary Certified
              net anthropogenic GHG removals by sinks and        leaching, and emissions of trace gases            Emission Reductions (tCERs) or Long
              emissions by sources resulting from forest         including N 2 O, nitric oxide (NO), nitrogen      Certified Emission Reductions (lCERs)
General       management activities.                             (N 2 ), ammonia (NH 3 ), CH 4 , and CO 2 .        according to the steps prescribed in the A/R
Information   Assessment level: Site level                       Assessment level: Site level                      methodologies.
              Geographical coverage: Global                      Geographical coverage: United States.
              Practices covered: Forest Management               Practices covered: Mainly crops; can              Assessment level: Site level
              GHG covered: CO 2 , N 2 O, and CH 4                quantify emissions from a variety of specific     Geographical coverage: Global
                                                                 crop management practices.                        Practices covered: Forest Management,
                                                                 GHG covered: CO 2 , N 2 O, and CH 4               afforestation and reforestation activities.
                                                                                                                   GHG covered: CO 2 , N 2 O, and CH 4
              •   Description and number of stands,               •   Daily temperature and precipitation          • Methodology applicable to the proposed
                  measurement units, and project year             •   Soil bulk density, texture, organic               Clean Development Mechanism (CDM)-
              •   Baseline, management activities                     carbon content, pH                                AR project activity
                  (application of fertilizers, liming             •   Farming practices (for example, crop         • Description of stands (tree and woody
                  application, thinning and harvesting, solid         type and rotation, tillage, fertilization,        species)
                  and paper wood products, wood to be                 manure amendment, irrigation, flooding,      • Baseline stratum and project activities
Data input
                  burned, fossil fuel consumption within the          grazing, and weeding)                             (stratum, sub-stratum, plot location,
                  forest stand)                                                                                         number of trees, diameter at breast
              •   Project activity (use of fertilizers, liming,                                                         height, tree height, wood density,
                  thinning, and harvesting, paper wood                                                                  biomass expansion factor, root-shoot
                  products, wood to be burned)                                                                          ratio, merchantable volume, fuel use,
              •   Leakage and key default values                                                                        fertilizer use, area of biomass burned)
                                                                                                                   • Leakage and key default values
              •   Carbon stocks (tCO 2 eq): this encompasses      •   Daily dynamics in the simulation run tab     • Ex ante net anthropogenic GHG
                  all stand models and every year, and the        •   Annual results per hectare in the results         removals by sinks
                  carbon contained in (above-ground and               tab: crop production (kg C per ha per        • Anticipated volume of carbon credits
                  below-ground) woody vegetation, in                  year), N balance (kg N per ha per year),
                  (above-ground and below-ground) pre-                C balance (kg C per ha per year), water
Data Output
                  existing trees and woody vegetation and in          balance (mm per year), and GHG
                  solid wood and paper products                       emissions (kg CO 2 eq per ha per year)
              •   Sum of changes in carbon stocks, above-
                  ground and below-ground (tCO 2 eq)
              •   Losses, above-ground and below-ground
                  (tCO 2 eq)



                                                                                                                                                               30
   Tools                            CAT-SFM                                           DNDC                                          TARAM
                •   Emissions (tCO 2 eq) from use of fossil fuel,
                    from liming and fertilization, from burning
                    and decay of wood and wood products in all
                    stand models
                •   The CAT-SFM does not consider fire              •   The tool can be used for predicting crop   •   The TARAM Tool was designed by the
                    occurrence resulting in forest degradation          growth, soil temperature and moisture          World Bank team as a self-explaining
                    and focuses only on the forest management-          regimes, soil carbon dynamics, nitrogen        tool suitable Afforestation/Reforestation
                    oriented projects.                                  leaching, and emissions of trace gases.        approved methodologies. It starts by
                •   The need for detailed data makes the use of     •   The tool is not adapted to estimate GHG        choosing a methodology from the
Potential use
                    the tool a challenge (fertilization, liming         emissions from agricultural development        approved and available methodologies’
of the tool
                    application, thinning and harvesting, solid         projects, where we mostly compare a            list and the model automatically adapts
                    and paper wood products, fossil fuel                baseline scenario to a ‘with-project’          all the worksheets to each
                    consumption within the forest stand, and so         scenario.                                      methodology’s particularities.
                    on).                                            •   The geographical coverage is limited to
                                                                        the United States.




                                                                                                                                                              31
4. Short-listed tools for comparative analysis
4.1 Detailed description of short-listed tools

 44) The carbon accounting tools that are short-listed for evaluation of real project datasets are
     described in terms of how they can be used, types of activities considered, GHG
     assessment boundary, carbon pools, sources, and sinks, associated GHG emissions, and
     other relevant criteria.

4.1.1 Carbon Benefits Project Modeling Tools

 45) The CBP modeling tools were developed by CSU with several partners and were released
     in March 2012. The tools are applicable to any land use/management project and can be
     applied globally for ex ante and ex post analysis and project tracking. The system has three
     options:
       • The Simple Assessment (SA) is an online tool based on the IPCC method. It requires
           users to choose land management information from prepopulated menus and uses
           default IPCC factors.
       • The Detailed Assessment (DA), also an online tool, is based on the IPCC method, but
           it allows users to enter their own project-specific information and emission factors
           (EFs).
       • The Dynamic Modeling option, which is the Century Ecosystem Model linked to a
           GIS, has to be downloaded from the web. Expertise in GIS and ecosystem modeling
           is needed to use this option.

 46) The SA and DA are designed to work on areas from a few hectares to approximately 10
     million hectares. The Dynamic Modeling option has been used at the landscape to
     subnational scale but can be applied at any scale if data are available. The CBP SA and DA
     were specifically designed for project accounting in GEF projects. GEF projects tend to be
     at landscape scale, often including multiple land uses, land management systems, and
     smallholdings that can have a mix of livestock and cropping systems. The CBP SA and DA
     were also specifically designed to deal with heterogeneous situations where an overall
     GHG balance is required. This is achieved by allowing the user to define multiple points or
     polygons in the system and then describe land cover, use, and management for ‘baseline’
     and ‘project’ scenarios. Furthermore, due to the landscape scope of the tools, they can also
     work to operate at a transboundary level, targeting projects and activities in more than one
     country.

 47) In terms of relevance to smallholder farmer groups, the SA can be used with the sort of
     activity data that a land management project is likely to have and, as an online tool, only
     requires an Internet connection. Users choose land management options from prepopulated
     lists. For the DA (also an online tool), users can build their own crop/forest/grass
     management systems. Local datasets and measurements can be used to improve estimates,


                                                                                               32
     so that costs and expertise associated with field sampling can apply, although users are
     encouraged to use existing local data if available (for example, from journal publications
     and PhD thesis). Both the SA and the DA tools are available in English, Spanish, French,
     Russian, Portuguese, and Chinese, with Amharic to be added.

 48) The toolkit covers all ecosystems classified in the IPCC GHG Inventory Methods for
     AFOLU (IPCC 2006). It covers emissions of all three major GHGs (CO 2 , CH 4 , and N 2 O)
     from all sources covered by the IPCC method and carbon stock changes associated with all
     carbon pools. Non-land-use emissions are not dealt with.

 49) The output of the assessment is a spatially explicit net GHG balance expressed in CO2
     equivalents. The system produces a PDF summary report and detailed Excel file reports
     that can be used in a GIS. Results are broken down by land use, land management, climate
     region, soil type, source, and sub-source categories for each geographic area that the user
     defines, in addition to giving a total for the entire area. Results are therefore spatially
     explicit, allowing multiple land use and management situations across heterogeneous
     landscapes to be analyzed at the same time. All results are accompanied by an estimate of
     uncertainty made using the IPCC error propagation method. In the DA, users can modify
     the model emission or carbon stock factors and adjust the uncertainty associated with their
     own project-specific factors.

 50) The tools are focused on use in mixed landscapes where net GHG accounting is required
     for a range of land use and land management situations. They cover all the land use
     categories given by the IPCC (forests, agroforestry, trees - outside of forests, in settlements
     and savannas), croplands (including agroforestry integrated with croplands and
     perennial/woody crops, such as tree fruits and nuts), grasslands, and wetlands. Carbon
     stocks covered include SOC and above- and below-ground woody biomass (litter and dead
     wood are not covered but are in the process of being added to the tool).

 51) The system can be used to address issues of leakage by defining additional ‘leakage’
     polygons or points and adjusting the final total to account for emissions from these areas.
     The CBP DA has the flexibility to be used in a way that is compatible with regulatory
     markets and voluntary market standards. It has not yet been reviewed or directly approved
     by any market or standard, but there are plans to do so under the ongoing GEF project
     (SLM-CCMC).

4.1.2 Agence Française de Développement Carbon Footprint Tool

 52) The AFD-CFT was developed by the AFD in 2007 and has been used since for ex ante
     GHG assessments of all its operations. The AFD-CFT’s accounting method uses a project’s
     or an activity’s operational data to estimate its GHG emissions. A carbon footprint
     calculation is created by making an inventory of a project’s activities. The quantities are
     entered into a spreadsheet that directly computes each item’s emissions in CO 2 equivalents
     (CO 2 eq) through a scientifically determined ‘EF’ embedded in the spreadsheet. As it

                                                                                                 33
   multiplies the activity’s ‘observable’ physical data values by this EF, the spreadsheet
   instantly converts each physical value into its CO 2- eq using tons as a unit of measure.
   Tools can be used by any land use/management project and are freely available from the
   website.

53) The outputs of the assessment include emission estimates forCO 2 , which results primarily
    from combusting fossil fuels and from producing aluminium, steel, cement, and glass; CH 4 ,
    which results from burning and/or decomposing biomass (organic material) and from
    producing and/or refining gasoline and natural gas; N 2 O, which results from incinerating
    solid waste, spreading fertilizers, and/or various transportation means; hydrofluorocarbons
    (HFCs), which occur as a by-product of industrial processes making insulation,
    refrigeration and air conditioning; perfluorocarbons (PFCs), which occur as a by-product of
    aluminium production; and sulphur hexafluoride (SF 6 ), which is used for insulation and
    current interruption in electricity transmission and distribution equipment and electronic
    systems.

54) The emissions are separated into two distinct categories according to the project’s phase—
    construction versus operation—and further sub-categories, as follows:

     Project ‘Construction Phase’ emission sources:
     • Clearing: deforestation
     • Construction materials: production of cement, steel, metals, and so on
     • Construction energy consumption: fuel and electricity used during construction

     Project ‘Operating Phase’ emission sources:
     • Fuel consumption: Combustion of fossil fuels.
     • Electricity/heat consumption.
     • Other process emissions: Includes non-energy-producing processes, especially
        decarbonation from cement clinker production, CH 4 released from mining and dam
        reservoirs, mechanization of organic waste and wastewater, N 2 O released by
        spreading fertilizer or from industrial gases, particularly coolants.
     • Purchase of goods and services: Includes the production of products consumed due to
        the project’s activity, especially metals, plastics, glass, paper and cardboard, and
        chemical and agricultural products.
     • Freight: Moving commodities, inputs and/or finished products by road, rail, air, or
        ocean.
     • Passenger transport.
     • Waste and wastewater.
     • Land use: Changing how land is used, resulting in emissions from biomass and soil.
     • Utilization: People’s use of utilities and infrastructure and/or factories or other
        buildings. This includes the mix of their use of transportation, electricity, fuels,
        products, and so on, and their waste-end of life: disposing of built or produced objects.



                                                                                              34
 55) The AFD-CFT calculation is compatible with the definition of ‘Scopes’ 1, 2, and 3 in the
     GHG Protocol:
      • Scope 1. Direct sources. GHG emissions, from sources directly related to a project’s
          activity, for example, combustion
      • Scope 2. Electricity. Indirect GHG emissions, from the generation of purchased
          electricity and/or heat needed for the project’s activity
      • Scope 3. Other indirect sources. GHG emissions, from the production of materials
          purchased from other parties and used in the project’s activity, for example,
          production and/or extraction of purchased materials, waste disposal, and use of sold
          products and services

 56) The calculation of GHG emissions resulting from a project covers the project’s entire
     lifetime, which is determined by the AFD-CFT. The project lifetime includes both the
     construction and operating phases. If building the project will generate negligible emissions,
     its construction phase is not included in the accounting. If the project’s construction proves
     emissive, by default, the AFD-CFT uses one-year durations. In the operating phase, for
     ease of comparison, standardized lifetimes for each type of project are suggested depending
     on the type of activities; the AFD-CFT user can change them on a case-by-case basis as
     needed and the annual GHG emissions are determined by dividing the project’s total
     lifetime (construction + operation) emissions by the total lifetime of the project.

 57) A project’s carbon footprint calculation is presented in terms of emissions generated during
     the construction phase in tCO 2 eq and emissions generated or abated annually during the
     operating phase in tCO 2 eq per year. To aggregate data and compare different projects, the
     values for the construction and/or operating phases are added to show the average annual
     emissions over the project’s lifetime. No discount rate is applied to annual emissions.

4.1.3 Agriculture, Forestry, and Other Land Use Carbon Calculator (AFOLU Carb)

 58) AFOLU Carb was developed by Winrock International, in collaboration with the USAID
     Global Climate Change team, to give USAID an easy way to mainstream its agency wide
     results indicator of CO 2 emission reductions and removals into its work. The tool,
     developed in 2007 and updated since, was designed to estimate emission reductions and
     removals from agriculture/forestry related USAID project activities that directly have an
     impact on how land is used or managed. The tool comprises six online and freely available
     calculators that cover forest protection, forest management, afforestation/reforestation,
     agroforestry, cropland management, and grazing land management. The calculators can
     also produce reports on above-ground forest biomass carbon, peat carbon, and soil carbon.

 59) The tool uses a tiered approach (Tier 1 and 2) where data requirements are minimal, but if
     more detailed information is available, it allows users to override default data to produce
     more refined estimates. Under the Tier 1 approach, the generation of CO 2 impact estimates
     generally only requires that users enter the area of the activity and the geographic location


                                                                                                35
     of the project activity. Under the Tier 2 approach, data input options allow users to generate
     more refined estimates by overriding defaults and entering project-specific information.

 60) The calculators use different methods with an underlying database derived from extensive
     literature reviews and the IPCC 2006 Guidelines for AFOLU (IPCC 2006). In terms of
     application at the landscape scale, the database also houses information at the
     administrative level, which can vary greatly depending on the country and region you are
     working in.

 61) An estimate of uncertainty is not provided with the output, and the developers are very
     clear in stating that the calculators are not designed to produce the level of accuracy needed
     for carbon financing. The AFOLU Carb provides a management effectiveness rating that is
     used as a measure of the success of project activities in terms of preventing GHG emissions
     or increasing removals from LUC activities, which could be used to predicate carbon
     leakage. The output gives the carbon change in CO 2 eq per activity type, administrative unit,
     and project.

4.1.4 Carbon Assessment Tool for Afforestation and Reforestation

 62) The CAT-AR was developed by the Tropical Agricultural Research and Higher Education
     Center (under Spanish acronym, Centro Agronómico Tropical de Investigación y
     Enseñanza (CATIE) in Costa Rica) for the World Bank as part of the ‘Pilot Program for
     Assessment of GHG Intensity of Core Development Activities.’ The tool consists of an
     Excel file and is free to download from the World Bank website.

 63) The CAT-AR is a simplified version of the ‘Tool for ex-ante estimation of forestry CERs’,
     or TARAM, an Excel-based tool developed jointly by the Bio Carbon Fund (World Bank)
     and CATIE to facilitate the application of the approved methodologies for afforestation and
     reforestation CDM project activities. CAT-AR therefore closely follows the CDM
     approach for GHG accounting of afforestation and reforestation projects. In situations
     where there is a lack of project-specific data, CAT-AR can provide indicative results by
     applying default values (Tier 1) from the 2003 Intergovernmental Panel on Climate Change
     Good Practice Guidance for Land Use, LUC and Forestry (IPCC-GPG LULUCF) and the
     2006 Intergovernmental Panel on Climate Change Guidelines for National Greenhouse Gas
     Inventories (IPCC-GNGGI).

 64) The CAT-AR tool considers afforestation and reforestation activities. Afforestation is
     defined as the direct human-induced conversion of land that has not been forested for a
     period of at least 50 years to forested land through planting, seeding, and/or the human-
     induced promotion of natural seed sources. Reforestation is defined as the direct human-
     induced conversion of non-forested land to forested land through planting, seeding, and/or
     the human-induced promotion of natural seed sources on land that was forested but that has
     been converted to non-forested land.



                                                                                                36
 65) The GHG assessment boundary includes four components: the geographic area where the
     project activities take place, the time frame of the assessment, the carbon pools considered,
     and the sources and sinks of associated GHG.

 66) With the CAT-AR tool, the GHG emissions/removals are assessed within both the discrete
     site(s) where the afforestation and reforestation project are located and the site(s) of the
     project boundary where GHG emissions/removals increase/decrease due to the project
     activity. The tool allows the user to monitor ex ante annual carbon stocks, changes in
     carbon stocks, and GHG emissions/removals up to a maximum of 30 years. It also takes
     four carbon pools: above-ground and below-ground trees and woody biomass, as well as
     above-ground and below-ground non-woody biomass. SOC and wood products are not
     included.

 67) The tool outputs include calculations of the CO 2 removals from biomass growth, CO 2
     emissions from consumption of fossil fuels (diesel or gasoline) for management purposes
     and from liming (CaCO 3 and CaMg(CO 3 ) 2 ), CH 4 released by burning of pre-existing trees
     and woody vegetation as well as non-woody vegetation for site preparation, N 2 O emissions
     from the use of organic and synthetic fertilizers and from the burning of pre-existing trees
     and woody vegetation as well as non-woody vegetation for site preparation.

 68) In addition to emissions/removals of GHGs, the CAT-AR considers two sources of leakage:
     fuel consumption out of the project boundary (transport of inputs and of staff for plantation
     and management, and of products) and emissions due to activity displacement outside the
     project boundary. The net anthropogenic GHG removals from the AR project are defined
     as the project net GHG removals by sinks minus the baseline net GHG removals by sinks
     minus the leakage. Both cumulative and yearly increments are shown in CAT-AR results.

4.1.5 Cool Farm Tool

 69) The CFT was developed to be a decision support tool for farmers to help them gain a better
     understanding of the sources and sinks of agricultural GHGs in their production practices.
     The main emphasis of the tool is on arable land, although livestock and woody perennial
     crops are included. The intended users of the tool are multinational or national food and
     beverage companies, farmers, cooperatives, and development and other organizations that
     work with farmers. The tool was developed by Unilever, the University of Aberdeen, and
     the Sustainable Food Laboratory. The first version was released in early 2010, with
     subsequent versions released in early 2011 and a new version in May 2012. The tool is
     Excel based and uses standardized software available in most countries with an
     accompanying online questionnaire available in English and Spanish. The tool itself is
     available only in English, although there are plans to make it available in more languages,
     starting with Spanish.

 70) The tool has global applicability because it uses equations, either based on modifications of
     the IPCC approach or on other sources in the literature (Hillier et al. 2011). It comprises

                                                                                               37
     many sub-models dealing with arable crops, woody perennial crops, livestock and LUC to
     or from grassland, arable land, and forest. GHG emissions include CO 2 , CH 4 , and N 2 O
     resulting from soil disturbance, fertilizer use, resident nitrogen, crop residue management,
     pesticide use, livestock production, and LUC. Additionally, the tool covers carbon stock
     changes in soil and biomass resulting from management changes. Emissions from on-site
     electricity use, fertilizer and pesticide production, and transport (for inputs and of the final
     product) are also included. The output of net GHG emissions is calculated in CO 2 eq in
     tables, graphs, and charts, broken down by emissions sources and sinks.

 71) The output is not spatially explicit, as it is for individual agricultural products. The tool
     does not assess uncertainty and the authors state that the tool is not intended as a carbon
     market access mechanism, but it can provide a screen for carbon market opportunities
     because it can be used to run ‘what if’ scenarios.

 72) Leakage and permanence is only addressed in relation to above-ground tree and non-tree
     biomass. Although the tool was originally designed to be used for individual products, it
     can be used at other scales if the details of all the products produced on those scales are
     known.

 73) There are plans to develop a web-based version of the tool to improve the transparency,
     scalability, user guidance, and user interface. There are also plans to enable integration of
     CFT into other supply chain GHG and life cycle analysis (LCA) resources used by private
     companies, commercial service providers, and public interest organizations. The CFT was
     recently accepted by the GHG metric working group for the Stewardship Index for
     Specialty Crops and will be recommended to the Coordinating Council.

4.1.6 Climate Change, Agriculture, and Food Security Mitigation Options Tool (CCAFS-MOT)

 74) The CCAFS-MOT was developed by the University of Aberdeen and the CGIAR Research
     Program on CCAFS, with support from USAID and the U.S. Department of Agriculture, to
     provide fast and accessible information on mitigation options for agriculture. The tool
     suggests mitigation options that are well suited to the production system, soils, and climatic
     conditions of the farm. The suggestions are based on empirical models and data from over
     a dozen different research studies.

 75) As an Excel-based tool, the CCAFS-MOT brings together several empirical models to
     estimate GHG emissions in rice, cropland, and livestock systems and to provide
     information about the most effective mitigation options. The tool allows for management-
     relevant GHG assessments to be made with relatively little effort and the estimation of
     GHG emissions from various crops (for example, barley, maize, and sugarcane), crop
     groups (for example, vegetables and legumes), and livestock production in different regions.
 76) The tool is intended as a decision-support tool for policy advisers and extension services
     around the world and is widely contextualized, promoted, and disseminated, enabling
     national decision makers to prioritize low-emission initiatives. The outputs of the tool are

                                                                                                  38
        estimates of emissions in terms of total GHG emitted in kilograms of CO 2 equivalent per
        hectare (kg CO 2 eq per ha) and in terms of GHG intensity, that is, kg of CO 2 equivalent per
        unit of product (kg CO 2 eq per unit). Users choose management practices. The aim of the
        tool is to accommodate a range of users from an introductory to an advanced level,
        depending on objectives and issues such as time, existing knowledge, or data available.

     77) Leakage and permanence are not addressed. The tool calculates the GHG emissions
         (emissions per hectare and per yield) due to current management practices and provides a
         ranked list of different management options to reduce emissions. The options are ranked by
         emissions estimates (total GHGs emitted in kilograms of CO 2 eq 12 per hectare and in terms
         of GHG emissions intensity), which helps compare the potential impact of each option.

4.1.7 Ex-Ante Carbon-Balance Tool

     78) EX-ACT was developed by the FAO to provide anyone developing agriculture and forestry
         projects (more particularly, program officers, funding agencies, and ministries) with a tool
         to estimate the impact of projects on GHG emissions and carbon sequestration (Bernoux et
         al. 2010). The tool consists of an Excel file and is free to download from the FAO website.

     79) The tool was developed using the IPCC Guidelines for National Greenhouse Gas
         Inventories (IPCC 2006) in conjunction with other methodologies and reviews of default
         coefficients (Lal 2006; Smith et al. 2008). This makes the tool globally applicable. It
         assesses the impact of agriculture and forestry activities on carbon stock changes per unit
         of land and CH 4 and N 2 O emissions in tCO 2 eq per hectare per year. The tool covers all
         GHG emissions linked with LULUCF activities covered by the 2006 IPCC Guidelines
         (IPCC 2006) plus some additional sources.

     80) EX-ACT is applicable to development projects in the areas of crop management, SLM,
         agroforestry, grassland restoration, production intensification, and livestock management.
         The tool covers the following sources and activities:
           • Deforestation/afforestation/reforestation
           • Annual and perennial cropland management
           • Flooded rice management practices
           • Livestock and dairy (enteric CH 4 and CH 4 from manure)
           • Nutrient management (liming, fertilizers, pesticides, and herbicides)
           • Energy consumption inputs and farm machinery (electricity and fuel)



12
  CO2 equivalent: It is a quantity to express the relative impact on the radiative forcing, that is, on the global
warming, of a substance (mostly GHGs) compared to that of CO2 and is calculated using the Global Warming
Potentials (GWPs). GWPs are measurements of the relative radiative effect of a given substance compared to that of
CO2, over a specific period. For instance, the official values for CDM of CH4) are set to 21 (meaning that 1 kg of
CH4 is as effective, in terms of radiative forcing, as 21 kg of CO2) and to 310 for N2O, based on a secular time scale.



                                                                                                                    39
 81) Furthermore, the tool covers emissions associated with carbon stock changes during land
     use conversion; biomass or residue burning; flooded rice cultivation; organic soils;
     livestock production; and inputs of lime, fertilizer, and manure. The tool also provides
     comprehensive coverage of non-land-use emissions associated with agriculture, such as
     those from the production, transport, storage, and transfer of agricultural chemicals and
     emissions from energy use and infrastructure (electricity and fuel consumption associated
     with buildings and irrigation system construction and maintenance).

 82) The output is not spatially explicit, but it provides a carbon balance resulting from project
     activities (for example, what would happen above a baseline scenario). This is
     accompanied by a rough estimate of uncertainty (rounded up to the nearest 10 percent),
     which is calculated using the method given in the IPCC 2006 Guidance (IPCC 2006).

 83) Issues of leakage are not addressed specifically, but they could be addressed by adjusting
     input information. Permanence is not addressed, but the uncertainty results could be used to
     highlight categories where problems of permanence might arise. No analysis of social or
     economic impacts is included, although the tool output has been used to feed into an
     economic analysis using the Marginal Abatement Cost Curves (Bockel et al. 2012). Tier 1
     EFs are supplied, with the option for users to input their own data. Overall, the tool requires
     a fair amount of detailed information.

4.2 Detailed characterization of the short-listed tools

 84) This section focuses on the ability of the seven short-listed tools to perform specific tasks,
     including (a) assessment of GHG consequences of SLM projects, (b) consideration of IPCC
     methods, (c) accounting for climate and soil in GHG evaluation, (d) GHG scope, and (e)
     treatment of uncertainties. This detailed characterization should help users understand and
     interpret the possible response while running the tools on real datasets from GEF and other
     SLM projects.

4.2.1 Assessing GHG consequences of projects

 85) The availability of approved carbon assessment methodologies is crucial for carbon
     crediting. These methodologies are the blueprints used to design, verify, and operate carbon
     projects. They document the protocol for quantifying carbon emissions and removals and
     include guidelines for identifying baseline scenario and assessing additionality in all carbon
     pools relevant to the project.

 86) Carbon calculators for project evaluation can be split into two subcategories—carbon
     market-oriented and non-carbon market-oriented tools—each one tailored for a different
     type of projects. For example, carbon market-oriented tools assume that a project is being
     run primarily for carbon mitigation benefits or with a heavy mitigation focus, whereas non-
     carbon market-oriented tools are often aimed at projects that have a primary focus on
     carbon co-benefits associated with the planned activities. The carbon calculators should

                                                                                                 40
     account for all possible mitigation options, including carbon storage. The type of
     calculators determines the level of expertise expected to use the tool.

 87) Tools focusing on carbon crediting schemes have been applied in countries where
     agriculture is subjected to carbon credits or with potential CDM projects. Tools not
     focusing on carbon crediting schemes usually account for all possible mitigation options,
     especially carbon storage. These tools aim to provide information for project managers,
     stakeholders, and donors.

 88) Table 7 indicates that, of the short-listed tools, only one is specifically designed for carbon
     crediting (the CAT-AR). Despite this, there may be opportunities for further developing
     some of the tools to meet the requirements for voluntary or other carbon markets, through
     the integration of specific carbon assessment methodologies.

                              Table 7: Selected tools and carbon credit
  No.          Tool               Focus on Carbon Credit               Not focused on Carbon Credit
   1     AFD-CFT                                                                     x
   2     AFOLU Carb                                                                  x
   3     CAT-AR                               x
   4     CBP                                                                         x
   5     CCAFS-MOT                                                                   x
   6     CFT                                                                         x
   7     EX-ACT                                                                      x

4.2.2 Intergovernmental Panel on Climate Change methods

 89) The IPCC oversees the review and compilation of all studies on climate change and has
     published guidelines and good practice references for GHG accounting (IPCC 2006). These
     guidelines are referenced in all the short-listed GHG accounting tools. GHG accounting
     using the IPCC methodology can be carried out at three levels:
       • Tier 1 corresponds to accounting for large areas, with average EFs provided for large
          ecoregions of the world.
       • Tier 2 is similar but uses state- or region-specific data, with more accurate EFs and
          carbon stock changes when available.
       • Tier 3 is very detailed, applying biophysical models of GHG processes that were
          developed at the country or regional level and which are different from those
          recommended by the IPCC, but which have been demonstrated to improve
          predictions of GHG emission assessments.

 90) For emissions of CO 2 from energy consumption and all nitrous oxide (N 2 O) and methane
     (CH 4 ) emissions, the generic approach considers multiplying an activity data (which can be
     land area, animal numbers, mass unit, or fuel quantity) by its specific EF for each source.
     For non-energy-related CO 2 emissions or removals, most calculations, except otherwise
     specified, use an approach with a stock difference method. The stock difference method



                                                                                                      41
      calculates emissions or removals as the change over time of carbon stocks for the different
      pools.

 91) The IPCC methods are based on five carbon pools—above-ground biomass, below-ground
     biomass, litter, deadwood, and soil carbon. Six out of the seven tools account for above-
     ground and soil carbon, but the CCAFS-MOT and CFT tools do not account for below-
     ground, litter, and deadwood. The CBP, AFD-CFT, and AFOLU Carbon Calculator
     (AFOLU Carb) do not account for litter and deadwood. EX-ACT is the only tool
     accounting for all five carbon pools.
       Table 8: Tools comparison based on the IPCC GHG accounting approaches and carbon pools
                   IPCC Tier Gain-loss and stock     Above-    Below-             Dead
No.      Tool                                                           Litter                SOC
                   used (1, 2)  difference methods   ground    ground             wood
 1    AFD-CFT           x                X              x         x                            x
 2    AFOLU             x                               x         x                            x
      Carb
 3    CAT-AR            x                X              x         x
 4    CBP               x                X              x         x                            x
 5    CCAFS-            x                               x                                      x
      MOT
 6    CFT               x                               x                                      x
 7    EX-ACT            x                X              x         x       x         x          x

4.2.3 Accounting for climate and soil

 92) In many SLM activities, emissions depend on the local environment, especially soil and
     climate conditions. These parameters have an especially strong impact on N 2 O emissions
     (nitrification-denitrification processes) and carbon storage potential. The potential carbon
     sequestration is controlled primarily by pedological factors that set the physicochemical
     maximum limit to storage of carbon in the soil. Such factors include soil texture and clay
     mineralogy, depth, bulk density, aeration, and proportion of coarse fragments.

 93) The attainable carbon sequestration is set by factors that limit the input of carbon to the soil
     system. The net primary production (NPP)—the rate of photosynthesis minus autotrophic
     respiration—is the major factor influencing the attainable sequestration and is modified by
     above-ground versus below-ground carbon allocation. Land management practices that
     increase carbon input through increased NPP tend to increase the attainable level of carbon
     sequestration. Adequately accounting for soil emissions is therefore crucial. For instance,
     soil N 2 O accounts for some 40 percent of agricultural emissions at the global level, and soil
     carbon storage/destocking is the highest carbon sink potential with the ability to store or
     release the equivalent of several years of global emissions (Baumert, Herzog, and Pershing
     2005). Soil carbon turnover varies from a few weeks to several thousand years depending
     on the carbon pool.

 94) Climate has both direct and indirect effects on attainable sequestration. The decomposition
     rate of organic matter increases with temperature but decreases with increasingly anaerobic
     conditions. The actual carbon sequestration is determined by land management factors that


                                                                                                    42
    reduce carbon storage such as erosion, tillage, residue removal, and drainage. Theoretically,
    the potential soil carbon sequestration capacity is equivalent to the cumulative historical
    carbon loss. Despite this, only 50 percent to 66 percent of this capacity is attainable through
    the adoption of SLM practices.

 95) At the regional and local scales, the climate is usually quite homogenous. Special care is
     needed, however, when working on islands or mountainous territories where sub-regional
     climates can differ significantly within short distances. On the other hand, management
     practices can have a strong impact on microclimates, affecting their biophysical processes
     involved in GHG emissions, including volatilization. Emissions factors and GHG tools do
     not usually have sufficient accuracy to consider the impact of microclimates on soils
     emissions.

 96) Soil heterogeneity can also be very high, especially concerning carbon content, which is
     strongly affected by cropping management practices. Thus, for limiting uncertainties from
     soil emissions, the field scale approach seems more appropriate than farm scale or regional
     scale. To consider soil and climate parameters on emissions, three options are possible:
       • User-defined data
       • Use of national/regional averages
       • Use of the geographic information system (GIS) approach

 97) The most accurate data are obtained through the description of soil and climate using key
     parameters such as temperature, rainfall, carbon content, bulk density, and texture. These
     data should be obtained from multiple samplings to reduce uncertainty, with minimum
     sample size provided by literature depending on the parameter required (Post et al. 2001).

4.2.4 GHG scope

 98) This review indicates the lack of homogeneity among the tools in terms of the GHG
     accounting scope. Indeed, different tools account for different sources (for example, some
     include energy, some infrastructure and transport, some N-fixing plant emissions, some soil
     carbon dynamics, and so on) and all are designed for different purposes and are context-
     specific. This lack of homogeneity markedly impedes direct comparison of results from
     different calculators. For a better interpretation of results, users need to apply
     standardization based on average emission per hectare for cereal crops or livestock that is
     seldom provided by guides to users.

 99) Only five out of the seven short-listed tools collectively account for CO 2 , N 2 O, and CH 4 .
     The AFD-CFT and AFOLU Carb do not account for N 2 O. Additionally, the AFOLU Carb
     does not account for CH 4 (see Table 9). The differences in scope can strongly affect the
     results of cross-comparison of tools, especially if some calculators account for carbon soil
     sequestration and others do not. However, in most situations, GHG tools account for
     hotspots of GHG emissions and variation in scope have a rather limited impact on the


                                                                                                 43
      results as indicated by studies comparing several GHG calculators under similar
      circumstances (Soil Association Producer Support; FAO 2010). The Life Cycle Assessment
      studies indicate that the agricultural production stage represents the major stage for GHG
      emissions in the product life cycle of most foods (Roy et al. 2009; Virtanen et al. 2010;
      Weber and Matthews 2008); therefore, transport (if not by air), processing, and packaging
      (except for glass and tins) are not hotspots of GHG emissions in food production.
                         Table 9: Sources, sinks, and SLM activities accounted for by each tool
                                     Analysis
                         GHG                                              SLM activities
                                       type




                                                                                                                                                  (afforestation/deforestation)
                                                                                     Rangeland/grazing land




                                                                                                                                                     Land use management




                                                                                                                                                                                                            Investment and inputs
                                                                                                                                                                                  Forest management
                                                                                                                          Agroforestry
                                                                      Horticulture



                                                                                                              Grassland
                                                           Cropland




                                                                                                                                                                                                                                    Livestock
No.     Tool
                                       Ex ante

                                                 Ex post




                                                                                                                                         Forest




                                                                                                                                                                                                      LUC
                          N2O
                  CO 2



                                CH 4




  1   AFD-        x no x            x     x    Limited x        x    x    x    no        x        no      x    x    no
      CFT
  2 AFOLU x no no                   x    no      no      no x no          x    no        no     Limited no no no
      Carb
  3 CAT-          x    x     x      x     x      no      no no no no no Limited                   no      x    x    no
      AR
  4 CBP           x    x     x      x     x       x       x     x    x    x     x        x         x      x    x     x
  5 CCAFS- x           x     x      x    no       x       x     x    x   no no           no       no      x no x
      MOT
  6 CFT           x    x     x      x    no       x       x no no no no                  no       no      no no x
  7 EX-           x    x     x      x     x       x       x     x    x    x     x        x         x      x    x     x
      ACT
x means the tool meets the criteria, Limited means it partially does meet the criteria, while no means it does not.
x means the tool meets the criterion, Limited means it partially does meet the criterion, while no means it does not.

4.2.5 Uncertainties

  100) Global uncertainty in GHG assessment results from three sources: uncertainties in
     activity data (inventory), uncertainty due to year-to-year variability in climate and
     management factors, and uncertainty in EFs (characterization) (Gibbons, Ramsden, and
     Blake 2006). Uncertainties can be very high for the agricultural sector, depending on the
     emission process considered. Some tools account for uncertainties, while others do not.
     Table 10 indicates that only CBP and EX-ACT quantify uncertainties in their GHG
     evaluation. Five out of the seven tools account for leakage, the CFT tool at least partially.

  101) At the farm scale, uncertainty can be caused by the inventory as data tends to be directly
     provided by farmers. At the landscape or regional scale, data are based on statistical
     average or expert knowledge, introducing large uncertainties. Because GHG tools do not
     assess inventory uncertainties, users should be aware of them and factor them into decision


                                                                                                                                                                                                                                     44
      making. However, evaluating the impact of these uncertainties is often quite difficult. One
      way to reduce them is to go through an iterative process that ensures high accuracy for
      activities with a strong impact on the outcome, such as the number of cattle or the quantity
      of nitrogen fertilizers.

 102) Year-to-year uncertainty can be reduced using average climatic data and management
    practices over several years. Intra annual climate variability interfering with management
    practices also induces uncertainties, but as GHG tools provide results per year, there is
    virtually no way of addressing this. For example, due to different climatic conditions, for
    the same amount of nitrogen, nitrification-denitrification rates may be higher in some years
    than others. Only biophysical models with daily or monthly pace could account for such
    detailed differences. Moving from Tier 1 to Tier 3 IPCC approach reduces these
    uncertainties.

 103) In interpreting results, the high level of uncertainty occurring in agriculture and forestry
    activities should be mentioned, especially when comparing two projects or two areas.
    Information on the causes of the uncertainties can be very important. The acceptable level
    of uncertainty depends on the data being considered and the goal of the GHG assessment.
    At the landscape level, information is generally more generic than at the farm level; thus, a
    higher uncertainty level is acceptable.

              Table 10: Uncertainty and leakage accounting in the carbon accounting tools
                                                   Quantitative value of
No.      Tool       No value for uncertainty                                            Leakage
                                                   uncertainty provided
 1    AFD-CFT                  x                                                           x
 2    AFOLU                    x                                                           x
      Carb
 3    CAT-AR                   x
 4    CBP                                                    x                             x
 5    CCAFS-                   x
      MOT
 6    CFT                      x                                                        Partially
 7    EX-ACT                                                 x                             x

4.2.6 Presentation of GHG assessment results and shortlisted tools

 104) The results are expressed in different units. They can be expressed in ton CO 2 equivalent,
    such as tCO 2 eq per year, tCO 2 eq per project (several years), tCO 2 eq per ha per year, and
    tCO 2 eq per kg of products. The results might also be expressed in net value (emission –
    storage) or provide both values. Users must be careful to distinguish between tons of
    carbon and tons of CO 2 (1 ton of CO 2 is 3.67 times a ton of carbon). Some calculators
    provide results only for one situation, while others provide the value for the baseline
    scenario (also known as a business-as-usual scenario) and with-project situation (project
    scenario).




                                                                                                    45
                   Table 11: Results types provided by the carbon accounting tools
                                                      GHG/project with             Other results (only
                             GHG/product ex:
No.     Tool      GHG/ha                          comparison between several         GHG for full
                             GHG/ kg grain)
                                                           scenarios                farm/territory)
 1    AFD-CFT        x                                         x
 2    AFOLU          x                                                                     x
      Carb
 3    CAT-AR         x
 4    CBP            x                                         x                            x
 5    CCAFS-         x               x                                                      x
      MOT
 6    CFT            x               x                                                      x
 7    EX-ACT         x               x                         x

4.2.7 Overall comments and conclusion

 105) Except for the CAT-AR tool, the tested GHG accounting tools are not specifically
    designed for a carbon market. All the tools follow the IPCC and stock difference methods.
    The carbon pools considered within each calculator vary; however, all short-listed
    calculators account for above-ground and SOC. Only the EX-ACT tool accounts for all the
    five carbon pools.

 106) All calculators account for soil and climate differences and for the main GHG sources
    and emissions and can identify hotspots (except emissions from LUC that are often
    ignored). As for the GHG coverage, only five out of the seven short-listed tools account for
    CO 2 , N 2 O, and CH 4 collectively. Five out of the seven tools account for leakage, one of
    them at least partially. Only CBP and EX-ACT quantify uncertainties in their GHG
    evaluation.

 107) While interpreting the results, it is necessary to consider the different objectives of each
    tool as they reflect the different areas of focus, methodologies, GHG scope, uncertainties
    along the analysis, and leakage. Each tool is characterized by certain competitive
    advantages and is often the first methodological choice regarding its own field of
    specialization. These differences concerning methodologies and scope have a significant
    impact on results. The main challenges with landscape assessments is how to consider the
    heterogeneity of production systems analyzed and the uncertainty of biological processes
    involved in GHG emissions. Therefore, it is impossible to do a straight comparison
    between the tools. Detailed analyses would be needed to evaluate precisely the variability
    of results from the tools. Ultimately the choice of tool will depend on the specific needs of
    the user.

 108) It is recommended that the user pays attention to the GHG scope accounted for and the
    uncertainties associated with results if major differences are observed when interpreting
    results obtained from the application of various calculators to GEF development projects.



                                                                                                         46
5. Application of the Short-Listed Tools to GEF Development
Projects
 109) Climate change will have a major impact on agricultural production, comparative
    advantages, and trade flows. A greater divergence between regions in terms of agricultural
    output is likely. For the most part, countries in the tropics and subtropical zones, mostly
    developing economies, are expected to lose in terms of agricultural production whereas
    countries in temperate zones, mostly developed economies, are expected to gain. In the
    absence of adoption of sustainable agricultural intensification and other climate-smart
    agricultural practices, these regional differences could have huge implications on GHG
    emissions.

 110) This report is intended to help potential users select the most appropriate tool for an SLM
    project’s GHG assessment. Comparing the use of the short-listed GHG assessment tools to
    assess the GHG footprint of SLM operations entails mapping the tools within the wide
    range of potential carbon sequestration and GHG emission reduction activities. So far, the
    short-listed tools have been used for a range of operations worldwide and by various
    partner organizations, including the World Bank, FAO, and AFD.

 111) The testing of the tools goes beyond a desk analysis and includes running the tools on
    real datasets from GEF projects. Eighteen SLM projects (Table 12) were identified and
    analyzed using the seven short-listed tools. Two projects were subject to field data
    collection and are used as case studies for an in-depth assessment of each tool. The selected
    projects represent the implementation of land use systems and management practices across
    a wide spectrum of SLM technologies, with the aim of improving plant management and
    rainwater management and reducing risks to production systems, people, and assets. Based
    on the tools’ scope and the IPCC GHG accounting approaches, 51 activities were assessed
    and eight main SLM activities were identified (Table 13). The full results of the assessment
    are provided within annex 1.

 112) The study includes 16 countries (Belarus, Brazil, Burkina Faso, Burundi, Chile, China,
    Costa Rica, Ethiopia, Guinea, Jordan, Mali, Moldova, Morocco, Serbia, Tunisia, and
    Turkey), representing five regions (Africa, Middle East and North Africa, Latin
    America and the Caribbean, Eastern Europe and Central Asia, and Europe). Many of these
    countries are highly dependent on the production and exports of agricultural goods and they
    are facing a range of climate change-related challenges.

                           Table 12: List of projects selected for the study
      Project                                                                               GEF
No.              Country   Region                            Project name
        ID                                                                                   ID
 1    P147760   Belarus    ECA       Forestry Development Project                           6947
 2    P086341   Brazil     LCR       BR GEF Rio Grande do Sul Biodiversity                  2450
 3    P070867   Brazil     LCR       Caatinga Conservation and Management – Mata Branca –   2450
                                     (GEF)



                                                                                              47
       Project                                                                                                   GEF
No.                  Country       Region                             Project name
         ID                                                                                                       ID
 4     P130568      Burkina        AFR       Sustainable Land and Forestry Management Project                    5187
                    Faso
 5     P127258      Burundi        AFR       Sustainable Coffee Landscape Project                                4631
 6     P087318      China          EAP       Guangxi Integrated Forestry Development and Conservation            2634
                                             Project
 7     P090376      China          EAP       GEF Shanghai Agricultural and Non-point Pollution                   3223
                                             Reduction
 8     P061315      Costa Rica     LCR       Sustainable Cacao Production in Southeastern Costa Rica              979
                                             (GEF-MSP)
 9     P090789      Ethiopia       AFR       ET Sustainable Land Management (ECPSLM)                             4630
10     P081297      Guinea         AFR       Community-based Land Management Project                             1877
11     P075534      Jordan         MNA       Integrated Ecosystem Management in the Jordan Rift Valley           1214
                                             GEF
12     P129516      Mali           AFR       Natural Resources Management in a Changing Climate in               5270
                                             Mali
13     P118518      Moldova        ECA       Moldova Agriculture Competitiveness Project                         4630
14     P129774      Morocco        MNA       Morocco Social and Integrated Agriculture                           5292
15     P635621      Serbia         EUR       Contribution of Sustainable Forest Management to a Low              9089
                                             Emission and Resilient Development
16     P613134      Turkey         ECA       Sustainable Land Management and Climate-Friendly                    4583
                                             Agriculture Project
17     P085621      Chile          ECA       Sustainable Land Management Project                                 4140
18     P112568      Tunisia        MNA       Second Natural Resources Management Project                         3669

       Table 13: Definition of activity-categories considered 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, as a result of
                            improved silviculture), indirect influences (for example, nitrogen or CO2 fertilization),
                            and natural causes (including natural successional processes). Within this study two
                            main categories of forest management were identified: forest fire 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.


                                                                                                                     48
        Activities                                             Definition
Livestock               Refers in a broad sense 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             Refer to electricity consumption, fuel consumption, installation of irrigation systems,
                        and building of infrastructure.


     Desk study analysis
5.1 Belarus-Forestry Development Project (FDP)

  113) The development objective of the project is to enhance the sustainable management of
     forestry assets in targeted project areas, through increasing silvicultural thinning and
     improving afforestation and reforestation capacity, thereby providing enhanced
     employment opportunities while continuing to provide global public goods. The project has
     three components:
       • Component 1: Improvement of silviculture and the sustainability of forest
           management
       • Component 2: Improvement of forest fire prevention, monitoring, detection, and
           suppression
       • Component 3: Capacity building for sustainable forest management

  114) Based on the scope and applicability of the tools, the activities under Components 1 and 2
     of the project were assessed. The results of the carbon balance obtained by the tools (see
     annex 1) are summarized in Figure 2. The analyses comprise the improvement of forest
     nurseries for afforestation and reforestation, the use of woody biomass from logging
     residues from final and selective fillings, and the improvement of forest fire management.




                                                                                                               49
         Figure 2: Carbon balance per component and per tool (Forestry Development Project, Belarus)
                     0
                          EX-ACT      CBP       AFOLU      AFD CFT    CAT-AR       CCAFS    CFT
                -20000
                                                 Carb
                -40000
                -60000
                -80000
               -100000
               -120000
               -140000
               -160000
               (tCO2eq/year        Inputs & Investments
                                   Degradation and management (forest degradation)
                                   Land Use Changes (Afforestation) on perennial


     115) The analysis considers the following set of information, determined as the minimum
        information required to carry out a GHG analysis:
          • Country/continental region: Belarus/Eastern Europe
          • Climate and moisture regime: Cool temperate moist
          • Dominant regional soil type: Sandy soils
          • Duration of the project implementation: 5 years and duration of analysis (also referred
             to as accounting period) set to 20 years 13

     116) While some calculations might not require all the above information, they might also
        require information on the moisture regime and the Mean Annual Temperature (MAT) of
        the project area.

5.1.1 Detailed project analysis per activity for the Belarus Forestry Development Project

5.1.1.1 Afforestation/reforestation (initial land use: perennial cropland)

     117) Based on the sources, sinks, and SLM activities accounted for by the tools, five tools
        (EX-ACT, CBP Simple Assessment [SA], AFD-CFT, AFOLU Carb, and CAT-AR) were
        appropriate for analyzing the afforestation activities (see Table 9). Because the activity
        analysis was conducted following the Tier 1 methodology, the default coefficients
        generated by the tools were used. The mean and standard deviation are respectively
        −6,727.6 tCO 2 eq per year and 1,890.8 tCO 2 eq per year, and the 95 percent confidence
        interval of the mean is estimated at between −5,070 and −8,384 tCO 2 eq per year.

13
   The accounting period is defined within as the sum of the implementation phase and the capitalization phase.
These values are set at minimum 20 years used either in IPCC 1996 or 2006 Guidelines and are gathered from a
large compilation of observations and long-term monitoring.



                                                                                                                  50
 118) Except for the CAT tool, all the results generated by the tools were situated within this
    estimated range. The analysis suggests that even if the project is not implemented, some
    forest plantation would be developed (baseline scenario). However, the CAT tool only
    considers afforestation with project implementation. Thus, the estimated carbon balance
    using CCAFS-MOT and CFT was calculated separately (with- and without- project
    scenarios) for the sake of comparison. In addition, the CAT tool considers cropland and
    grassland as baselines for land use activities.

 119) The tools with GHG balance within the estimated range of results are the EX-ACT tool,
    CBP SA, AFOLU Carb, and AFD-CFT. The AFOLU Carb estimates a carbon balance
    value further away from the mean value. This could be explained by the fact that the
    AFOLU Carb is not based on the gain-loss and stock difference methods, and therefore,
    does not compute emissions or removals as the change over time of carbon stocks for the
    different pools (Table 8). The differences between the EX-ACT, CBP SA, and AFD-CFT
    tools are minor: EX-ACT and CBP SA have a 5.34 percent difference, EX-ACT and AFD-
    CFT a 4.19 percent difference, and CBP SA and AFD-CFT a 1.15 percent difference.

 120) Based on this analysis, the three tools, EX-ACT, CBP, and AFD-CFT, are suitable for
    afforestation GHG analysis when considering perennial cropland as the initial land use
    (ILU) and when afforestation activities are carried out with and without the project
    implementation.

5.1.1.2 Forest management and degradation (forest fire management)

 121) Based on the sources, sinks, and SLM activities accounted for by the tools, three tools
    (EX-ACT, CBP SA, and AFOLU Carb) were used to analyze forest management and
    degradation activities (see Table 9). Because the activities analysis was conducted
    following the Tier 1 methodology, the default coefficients generated by the tools were used.

 122) The difference between the results obtained from EX-ACT and CBP SA was small.
    Although the AFOLU Carb tool considers the fire impact, the difference in results is
    explained by the suggested default Forest Carbon Stock value, which is the average of the
    above- and below-ground forest carbon stock in the tree pool (Table 8). The difference in
    results between the EX-ACT, AFOLU Carb, and CBP SA tools are minor: EX-ACT and
    CBP have a 1.36 percent difference, EX-ACT and AFOLU Carb a 1.4 percent difference,
    and CBP and AFOLU Carb a 1.5 percent difference. This difference could be explained by
    the fact the CBP SA does not consider fire occurrence lower than 1 percent, and the activity
    suggests that the fire impact (percent burnt) will be reduced from 0.2 percent without the
    project implementation to 0.1 percent yearly with the project implementation. Based on this
    analysis, the three tools—EX-ACT, CBP, and AFOLU Carb—are suitable for GHG
    analysis of forest fire management.




                                                                                             51
5.1.1.2.1 Inputs and investments (electricity, gasoil, wood consumption, and irrigation)

 123) Based on the sources, sinks, and SLM considered by the tools, only EX-ACT and AFD-
    CFT were used to analyze energy consumption (see Table 9). Because the activity analysis
    was conducted following the Tier 1 methodology, the default coefficients generated by the
    tools were used. A minimal difference was observed among the results, owing to the
    similarities in the EFs used by the tools. The AFD-CFT, however, does not account for
    GHG emissions caused by irrigation infrastructures.
 124) Based on this analysis, the two tools—EX-ACT and AFD-CFT—are suitable for the
    GHG analysis of electricity, fuel consumption, and wood consumption, while EX-ACT
    also estimates emissions related to irrigation systems.

5.1.2 Project carbon balance

 125) Based on the sources, sinks, and SLM activities, the EX-ACT is the only tool capable of
    assessing the full range of GHG consequences associated with the Belarus Forest
    Development Project. The estimated carbon balance is −2,786,149 tCO 2 eq for the entire
    duration of the analysis (20 years) or −0.2 tCO 2 eq per hectare per year.

5.2 Brazil, GEF Rio Grande do Sul Biodiversity

 126) The project development objective is to promote the conservation and restoration of
    biodiversity in the grassland ecosystem in the Rio Grande do Sul's territory by
    mainstreaming biodiversity conservation within forestry, agriculture, and livestock
    productive landscapes. The project has three components:
      • Component 1: On-Farm Biodiversity Mainstreaming
      • Component 2: Biodiversity Management
      • Component 3: Project Management

 127) Based on the scope and applicability of the tools, the activities of Component 1 were
    assessed. The results of the carbon balance obtained are summarized in Figure 3. The
    analyses focus on the rationalization of land conversion processes by promoting the
    adoption of biodiversity conservation practices in the main productive systems of the
    grasslands. As a result, moderately degraded grassland is brought under enhanced
    biodiversity conservation.




                                                                                           52
  Figure 3: Carbon balance per component and per tool (BR GEF Rio Grande do Sul Biodiversity, Brazil)



           0
                    EX-ACT    CBP      AFOLU Carb    AFD CFT     CAT-AR       CCAFS        CFT
     -50,000

    -100,000

    -150,000

    -200,000

    -250,000

    -300,000

    (tCO2eq/year)


 128) The analysis considers the following set of information, determined as the minimum
    information required to carry out a GHG analysis:
      • Country/continental region: Brazil/South America
      • Climate and moisture regime: Tropical wet
      • Dominant regional soil type: Low activity clay soils
      • Duration of the project implementation: 5 years and duration of analysis set to 20
         years

 129) While some calculations might not require all the above information, others might also
    require the moisture regime and the MAT.

5.2.1 Detailed project analysis per activity for the Brazil GEF Rio Grande do Sul Biodiversity
Project

5.2.1.1 Grassland management

 130) Based on the sources, sinks, and SLM activities considered by the tools, four tools (EX-
    ACT, AFOLU Carb, CBP SA, and AFD-CFT) were used to analyze grassland management
    activities (see Table 9). Because the activity analysis was conducted following the Tier 1
    methodology, the default coefficients generated by the tools were used. The mean and
    standard deviation are respectively −235,641 tCO 2 eq per year and 11,509.8 tCO 2 eq per
    year. The 95 percent confidence interval of the mean is between −224,361 and −246,920
    tCO 2 eq per year.

 131) All the results generated by the tools are situated within this estimated range. Minimal
    differences were observed within the results. These differences were mainly due to the use



                                                                                                        53
     of different IPCC GHG accounting approaches and carbon pools (Table 8), and
     uncertainties associated with the Tier 1 methodology. For example, the AFD-CFT tool
     calculates the default soil carbon stock changes based on a set of IPCC questions, whereas
     the AFOLU Carb provides estimated values for relative stock change factors.

 132) The differences in results between the tools varies: EX-ACT and CBP have a 0.62
    percent difference, EX-ACT and AFD-CFT a 5.55 percent difference, EX-ACT and
    AFOLU Carb a 33 percent difference, CBP and AFD-CFT a 28 percent difference, CBP
    and AFOLU Carb a 32 percent difference, and AFD-CFT and AFOLU Carb a 4 percent
    difference.

5.2.2 Project carbon balance

 133) The total estimated carbon balance for the Brazil, BR GEF Rio Grande do Sul
    Biodiversity Project ranges between −1.06 and −1.17 tCO 2 per hectare per year.

5.3 Brazil, Caatinga Conservation and Sustainable Management Project

 134) The project's global environmental objective and its development objective are the same:
    contributing to the preservation, conservation, and sustainable management of the
    biodiversity of the Caatinga in the states of Bahia and Ceara, while improving the quality
    of life of its inhabitants, through the introduction of sustainable development practices. The
    project has two components:
      • Component 1: Institutional and Policy Support for Integrated Ecosystem Management
      • Component 2: Promotion of Integrated Ecosystem Management Practices

 135) Based on the scope and applicability of the tools, the activities in Component 2 were
    assessed. The results of the carbon balance obtained by the tools are summarized in Figure
    4. The analyses focus on (a) promoting Integrated Ecosystem Management Practices, (b)
    supporting the implementation of cost-effective and replicable Integrated Ecosystem
    Management practices at the local level to ensure sustainability of conservation efforts, and
    (c) preventing land degradation in the Caatinga Biome.




                                                                                               54
Figure 4: Carbon balance per component and per tool (Caatinga Conservation and Sustainable Management
                                           Project, Brazil)
      0
            EX-ACT           CBP        AFOLU Carb      AFD CFT         CAT-AR        CCAFS                CFT
  -5,000

 -10,000

 -15,000

 -20,000

 -25,000

 -30,000

 -35,000

 -40,000
  tCO2eq/year        Land Use Changes (Afforestation)    Agriculture (Annual)    Agriculture (Perennial)


 136) The analysis considers the following set of information, determined as the minimum
    information required to carry out a GHG analysis:
      • Country/continental region: Brazil/South America
      • Climate and moisture regime: Tropical wet
      • Dominant regional soil type: Low activity clay soils
      • Duration of the project implementation: 5 years and duration of analysis set to 20
         years

 137) While some calculations might not require all the above information, others might also
    require the moisture regime and the MAT.

5.3.1 Detailed project analysis per activity for the Brazil Caatinga Conservation and Sustainable
Management Project

5.3.1.1 Afforestation/reforestation (ILU: grassland)

 138) Based on the sources, sinks, and SLM activities accounted for by the tools, five tools
    (EX-ACT, CBP SA, AFD-CFT, AFOLU Carb, and CAT-AR) were used to analyze
    afforestation activities (see Table 9). Because the activity analysis was conducted following
    the Tier 1 methodology, the default coefficients generated by the tools were used. The
    mean and standard deviation are respectively −32,363.2 tCO 2 eq per year and 6,374.8
    tCO 2 eq per year, with 95 percent confidence interval of the mean between −26,775 and
    −37,951 tCO 2 eq per year.




                                                                                                                 55
 139) The project information suggests that afforestation activities would take place on
    grassland (initial land use [ILU]). All the results generated by the tools are situated within
    this estimated range. The AFOLU Carb provides a value further away from the mean value.
    This is explained by the fact that the AFOLU Carb does not consider the land use change
    and therefore, does not compute emissions related to soil carbon losses.

 140) The differences in results between the EX-ACT, CBP SA, and CAT-AR tools are minor:
    EX-ACT and CBP SA have a 1.6 percent difference, EX-ACT and CAT-AR a 0.88 percent
    difference, and CBP SA and CAT-AR a 0.8 percent difference. The difference in results
    between these tools and the AFD-CFT is higher: EX-ACT and AFD-CFT have a 15 percent
    difference, AFD-CFT and CBP SA a 13 percent difference, and AFD-CFT and CAT-AR a
    14 percent difference. Based on this analysis, the four tools—EX-ACT, CBP, AFD-CFT,
    and CAT-AR—are suitable for the afforestation GHG analysis when considering grassland
    as ILU.

5.3.1.2 Annual crops development (ILU: degraded land)

 141) Based on the sources, sinks, and SLM activities accounted for by the tools, six tools (EX-
    ACT, AFOLU, CBP SA, AFD-CFT, CCAFS-MOT, and CFT) were used to analyze annual
    cropland activities (see Table 9). The primary activity focused on developing annual crops
    in degraded areas. Because the analysis was conducted following the Tier 1 methodology,
    the default coefficients generated by the tools were used. The mean and standard deviation
    are respectively −593.1 tCO 2 eq per year and 565.6 tCO 2 eq per year, with the 95 percent
    confidence interval of the mean between −1,043 and −136 tCO 2 eq per year.

 142) Except for the CCAFS-MOT and the AFOLU Carb, all the results generated by the tools
    are situated within this estimated range. The CCAFS-MOT tool does not consider all land
    use changes (only forest to grassland, arable to grassland, and grassland to arable) and has
    limited management options. Similarly, the AFOLU Carb does not consider all
    management practices (only tillage and inputs management) and land use changes.
    Although the CFT tool results are within the expected range, the tool does not provide a
    comparison of with and without the project scenarios, so an estimation of the carbon
    balance using the CCAFS-MOT and CFT tools was calculated separately (with and without
    the project scenarios) for the sake of comparison.

 143) Only three tools—EX-ACT, CBP SA, and AFD-CFT—out of the six tools that have
    annual crops as an activity scope were able to estimate the mitigation benefit of this activity.
    The differences in results between the EX-ACT, CBP SA, and AFD-CFT tools are minor:
    EX-ACT and CBP SA have a 10 percent difference, EX-ACT and AFD-CFT a 9.4 percent
    difference, and CBP SA and AFD-CFT a 1 percent difference. This difference could be
    explained by the fact that the AFD-CFT and CBP SA tools do not consider degraded land




                                                                                                 56
      as an ILU. 14 Based on this analysis, the EX-ACT tool is suitable for GHG analysis of
      annual cropland development when considering degraded land as ILU.
5.3.1.3 Perennial crops development (ILU: degraded land)

     144) Based on the sources, sinks, and SLM activities accounted for by the tools, three tools
        (EX-ACT, CBP SA, and AFD-CFT) were used to analyze perennial activities (see Table 9).
        Because the activity analysis was conducted following the Tier 1 methodology, the default
        coefficients generated by the tools were used. The standard deviation is estimated at 2,049
        tCO 2 eq per year and the mean at −6,687.6 tCO 2 eq per year. The 95 percent confidence
        interval of the mean is between −8,717 and −1,215 tCO 2 eq per year.

     145) Although the AFOLU Carb tool includes cropland management within its activity scope
        (Table 9), it does not differentiate between perennial and annual crops and was therefore
        not considered in this case. Except for the AFD-CFT, all the tools generated results within
        the estimated range. The AFD-CFT tool estimates a carbon balance value
        further away from the mean value.

     146) The difference in results between the EX-ACT, CBP SA, and AFD-CFT tools varies:
        EX-ACT and CBP have a 13 percent difference, EX-ACT and AFD-CFT a 96 percent
        difference, and CBP and AFD-CFT an 86 percent difference. This could be explained by
        the different ILUs considered while running the calculations (degraded land for EX-ACT,
        abandoned cropland for AFD-CFT, and severely degraded grassland for the CBP SA).
        Based on this analysis, EX-ACT is suitable for GHG analysis of perennial cropland
        development when considering degraded land as ILU.

5.3.2 Project carbon balance

     147) The total estimated carbon balance for the Brazil, Caatinga Conservation and Sustainable
        Management Project ranges between −18.6 and −16.2 tCO 2 eq per hectare per year.

5.4 Burkina Faso, Third Phase Community Based Rural Development Project

     148) The development objective of the project is to enhance the capacity of rural communities
        and decentralized institutions for the implementation of local development plans that
        promote sustainable land and natural resources management and productive investments at
        commune level. The project has five components:
          • Component 1: Strengthening capacity for decentralized rural development
          • Component 2: Implementation of the rural land legislation and enhancement of local
             dispute resolution mechanisms
          • Component 3: Local and regional investments

14
  The CBP DA could be used by replacing the severely degraded grassland carbon stock values with degraded land
corresponding values based on the IPCC methodology.



                                                                                                            57
       •   Component 4: Sustainable land and forestry management
       •   Component 5: Project management, monitoring, and evaluation

 149) Based on the scope and applicability of the tools, the activities in Component 4 were
    assessed. The results of the carbon balance obtained by the tools are summarized in Figure
    5. The analyses focus on promoting community-based sustainable land and forestry
    management practices to reduce pressure on natural resources from competing land uses.

 Figure 5: Carbon balance per component and per tool (Third Phase Community Based Rural Development
                                        Project, Burkina Faso)
                   0
                           EX-ACT        CBP      AFOLU   AFD CFT      CAT-AR   CCAFS   CFT
                                                  Carb
             -2,000


             -4,000


             -6,000


             -8,000


            -10,000


            -12,000
             tCO2eq/year            Management and degradation (forest degradation)
                                    Land Use Changes (Deforestation)


 150) The analysis considers a set of information determined as the minimum information
    required to carry out a GHG analysis as follows:
   • Country/continental region: Burkina Faso/Africa
   • Climate and moisture regime: Tropical dry
   • Dominant regional soil type: Low activity clay soils
   • Duration of the project implementation: 5 years and duration of analysis set to 20 years

 151) While some calculations might not require all the above information, others might also
    require the moisture regime and the MAT.

5.4.1 Detailed project analysis per activity for Burkina Faso Third Phase Community Based
Rural Development Project

5.4.1.1 Deforestation (Final land use: grassland)

 152) Based on the sources, sinks, and SLM activities accounted for by the tools, three tools
    (EX-ACT, CBP SA, and AFOLU Carb) were used to analyze deforestation activities (see
    Table 9). Because the analysis was conducted following the Tier 1 methodology, the


                                                                                                  58
         default coefficients generated by the tools were used. The mean and standard deviation are
         respectively −7,423.5 tCO 2 eq per year and 203.8 tCO 2 eq per year, with the estimated 95
         percent confidence interval of the mean between −7,623 and −7,223 tCO 2 eq per year.

     153) All the tools provided results within this calculated range. The AFOLU Carb generated
        a value further away from the mean value. This can be explained by the fact that the
        AFOLU Carb is not based on the gain-loss and stock difference methods (Table 8) and
        therefore, does not compute emissions related to land use change.

     154) The differences in results between the EX-ACT, CBP SA, and AFOLU Carb tools are
        minor: EX-ACT and CBP have a 5 percent difference, EX-ACT and AFOLU Carb a 3
        percent difference, and CBP SA and AFOLU Carb a 2 percent difference. Based on this
        analysis, the three tools—EX-ACT, CBP and AFOLU Carb—are suitable for deforestation
        GHG analysis when considering grassland as final land use (FLU).

5.4.1.2 Forest management and degradation

     155) Based on the sources, sinks, and SLM activities accounted for by the tools, two tools
        (EX-ACT and CBP SA) were used to analyze forest management activities (see Table 9).
        Because the analysis was conducted following the Tier 1 methodology, the default
        coefficients generated by the tools were used. The AFOLU Carb tool is not considered
        within the analysis; although it considers forest protection activities, it does not consider
        the biomass losses that are not due to deforestation or illegal logging. The difference in
        results between the tools is minor (6.2 percent). 15 Based on this analysis, the EX-ACT and
        CBP tools are suitable for forest management GHG analysis.

5.4.2 Project carbon balance

     156) For the overall project results, the CBP and EX-ACT tools provide relatively close results
        (0.08 tCO 2 eq per year of difference). The uncertainty level for the CBP tool, (38 percent) is
        higher than that of EX-ACT (20 percent). Had the CBP DA been used instead of the SA,
        uncertainty could have been lowered substantially by using site-specific EFs.

5.5 Burundi, Sustainable Coffee Landscape Project

     157) The development objective of the project is to pilot sustainable land and water
        management practices in the coffee landscape of Burundi. The project has four components:
          • Component 1: Sustainable coffee landscape management
          • Component 2: Addressing pollution point sources in coffee washing stations
          • Component 3: Diversification of livelihoods
          • Component 4: Knowledge and learning
15
     Using Tier 2 coefficients instead of Tier 1 methodology/coefficients could decrease the difference further.



                                                                                                                   59
 158) Based on the scope and applicability of the tools, the activities in Component 1 were
    assessed. The results of the carbon balance obtained by the tools are summarized in Figure
    6. The analyses focus on the promotion of sustainable land and water management,
    agroforestry, and shade grown coffee cultivation, as well as conservation activities in one
    protected area.

  Figure 6: Carbon balance per component and per tool (Sustainable Coffee Landscape Project, Burundi)
                 0
                      EX-ACT      CBP       AFOLU        AFD CFT   CAT-AR   CCAFS   CFT
             -2,000
                                             Carb
             -4,000

             -6,000

             -8,000

            -10,000

            -12,000

            -14,000

            -16,000

              tCO2eq/year      Degradation and Management (forest degradation)
                               Agriculture (Perennial)
                               Land Use Changes (Afforestation)


 159) The analysis considers a set of information determined as the minimum information
    required to carry out a GHG analysis as follows:
      • Country/continental region: Burundi/Africa
      • Climate and moisture regime: Tropical mountain moist
      • Dominant regional soil type: Low activity clay soils
      • Duration of the project implementation: 4 years and duration of analysis set to 20
          years

 160) While some calculations might not require all the above information, others might also
    require the moisture regime and the MAT.

5.5.1 Detailed project analysis per activity for the Burundi Sustainable Coffee Landscape Project

5.5.1.1 Afforestation/reforestation (ILU: set aside land)

 161) Based on the sources, sinks, and SLM activities accounted for by the tools, five tools
    (EX-ACT, CBP SA, AFD-CFT, AFOLU, and CAT-AR) were used to analyze afforestation
    activities (see Table 9). Because the analysis was conducted following the Tier 1
    methodology, the default coefficients generated by the tools were used. The mean and
    standard deviation are respectively −5,163.2 tCO 2 eq per year and 324.4 tCO 2 eq per year


                                                                                                        60
     with the 95 percent confidence interval of the mean between −4,878 and −5,447 tCO 2 eq
     per year.

 162) The range of expected results allows us to observe the differences between the tools
    while analyzing afforestation activities. These differences are explained by the fact that the
    AFOLU tool does not account for the gain-loss and stock difference methods (Table 8) and
    therefore, does not compute emissions or removals as the change over time of carbon
    stocks for the different pools.

 163) The differences in results between the EX-ACT, AFD-CFT, and CAT-AR tools are minor:
    EX-ACT and AFD-CFT have a 3 percent difference, EX-ACT and CAT-AR a 1 percent
    difference, and AFD-CFT and CAT-AR a 3 percent difference. The difference between the
    CAT-AR, CBP SA, AFD-CFT, and EX-ACT tools is explained by the fact that the analysis
    used Tier 1 methodology, and the absence of set aside land as ILU for the CBP SA tool.
    Based on this analysis, the three tools—CAT-AR, AFD-CFT, and EX-ACT—are suitable
    for afforestation GHG analysis when considering set aside land as ILU. It should be noted
    that the CBP DA could also be used by replacing the severely degraded grassland carbon
    stock values with corresponding values for set aside land based on the IPCC methodology.

5.5.1.2 Perennial crops improvement

 164) Based on the sources, sinks, and SLM activities accounted for by the tools, four tools
    (EX-ACT, CBP SA, AFD-CFT, and CFT) were used to analyze perennial improvements
    (see Table 9). The results, however, are equal to zero. This is explained by the absence of
    Tier 2 values in the tools to describe the improved system (improved shaded coffee in our
    case).

 165) All the four tools are suitable for GHG analysis of perennial improvements. Using Tier 2
    values is recommended in such activity analysis; therefore, the CBP DA, rather than SA,
    should be used. Further analysis using the Tier 2 methodology will help understand and
    highlight the different characteristics between each of the tools.

5.5.1.3 Forest management and degradation

 166) Based on the sources, sinks, and SLM activities accounted for by the tools, two tools
    (EX-ACT and CBP SA) were used to analyze forest management activities (see Table 9).
    The AFOLU Carb tool is not considered within the analysis; although it considers forest
    protection activities, it does not consider the biomass losses that are not due to
    deforestation or illegal logging. Because the analysis was conducted following the Tier 1
    methodology, the default coefficients generated by the tools were used. The difference in
    results between the tools is 12 percent. Based on this analysis, the EX-ACT and CBP tools
    are suitable for forest management GHG analysis.




                                                                                               61
5.5.2 Project carbon balance

 167) For the overall project results, only the CBP and EX-ACT tools cover the appropriate
    areas of the project GHG appraisal and provide relatively similar results (−0.2 tCO 2 eq per
    year difference). The uncertainty level is higher for the CBP tool at 51 percent, while the
    EX-ACT results are accompanied by an uncertainty level of 37 percent. Overall uncertainty
    depends on the uncertainty levels given to different factors by the IPCC and can be reduced
    in both CBP and EX-ACT by moving to a Tier 2 analysis (where the user supplies some of
    their own factors).

5.6 China, Guangxi Integrated Forestry Development and Conservation Project

 168) The overall project development objective is to improve the effectiveness of forest
    management and institutional arrangements in timber production, watershed protection, and
    nature reserves management in selected areas of the Guangxi Zhuang Autonomous Region
    (GZAR). The project has four components:
      • Component 1: Expanding timber plantations by financing
      • Component 2: Increasing ecological forest cover
      • Component 3: Strengthening management of nature reserves
      • Component 4: Enhancing institutional and management capacity to implement an
         integrated institutional and management capacity-building program knowledge and
         learning

 169) Based on the scope and applicability of the tools, the activities in Component 1 were
    assessed. The results of the carbon balance obtained by the tools are summarized in Figure
    7. The analyses focus on expanding timber plantations and enlarging four central nurseries
    including setting up tissue culture plant, seedling shed, and irrigation.




                                                                                             62
   Figure 7: Carbon balance per component and per tool (Guangxi Integrated Forestry Development and
                                     Conservation Project, China)

                    0
                         EX-ACT    CBP     AFOLU    AFD CFT   CAT-AR   CCAFS      CFT
              -500,000
                                            Carb
            -1,000,000

            -1,500,000

            -2,000,000

            -2,500,000

            -3,000,000

            -3,500,000

            -4,000,000

            -4,500,000
             tCO2eq/year


 170) The analysis considers a set of information determined as the minimum information
    required to carry out a GHG analysis as follows:
      • Country/continental region: China/Asia continental
      • Climate and moisture regime: Warm temperate moist
      • Dominant regional soil type: High activity clay soils
      • Duration of the project implementation: 6 years and duration of analysis set to 20
          years

 171) While some calculations might not require all the above information, others might also
    require the moisture regime and the MAT.

5.6.1 Detailed project analysis per activity for Guangxi Integrated Forestry Development and
Conservation Project

5.6.1.1 Afforestation (ILU: set aside and grassland)

 172) Based on the sources, sinks, and SLM activities accounted for by the tools, five tools
    (CAT-AR, CBP SA, AFD-CFT, AFOLU Carb, and EX-ACT) were used to analyze
    afforestation activities (see Table 9). Because the analysis was conducted following the
    Tier 1 methodology, the default coefficients generated by the tools were used. The standard
    deviation is estimated at 504,468 tCO 2 eq per year and the mean at −3,402,056.2 tCO 2 eq
    per year. The 95 percent confidence interval of the mean is between −2,959,869 and
    −3,844,242 tCO 2 eq per year.

 173) The range of expected results allows us to observe the differences between results while
    analyzing afforestation activities. These differences are explained by the fact that the


                                                                                                      63
        AFOLU Carb tool does not consider the gain-loss and stock difference methods (Table 8)
        and therefore, does not compute emissions related to land use change.

     174) The differences in results between the EX-ACT, CBP, AFD-CFT, and CAT-AR tools
        varies: EX-ACT and CBP have a 97 percent difference, EX-ACT and AFD-CFT a 20
        percent difference, EX-ACT and CAT-AR a 30 percent difference, CBP and AFD-CFT an
        82 percent difference, CBP and CAT-AR a 72 percent difference, and AFD-CFT and CAT-
        AR a 10 percent difference. The difference between the CAT-AR, CBP SA, AFD-CFT, and
        EX-ACT tools could be explained by the fact that Tier 1 methodology was applied, the
        absence of set aside land as ILU for the CBP SA tool, and the difference in the sources and
        sinks accounted for by the tools, and SLM activities considered by the tools (Tables 8 and
        9).

     175) Based on this analysis, the four tools—CAT-AR, AFD-CFT, CBP, and EX-ACT—are
        suitable for afforestation GHG analysis when considering grassland as ILU, while, the
        three tools—EX-ACT, CAT-AR, and AFD-CFT—are suitable when considering set aside
        land as the ILU. 16

5.7 China, Shanghai Agricultural and Non-point Pollution Reduction Project

     176) The objective of the project is to demonstrate effective and innovative pollution reduction
        activities in Shanghai's rural areas to reduce the rural and agricultural pollution load
        (especially nutrients) in the surface water flowing to the East China Sea. The project has
        four components:
          • Component 1: Livestock waste management technology demonstration
          • Component 2: Wetland demonstration for pollution reduction
          • Component 3: Integrated agricultural pollution reduction techniques
          • Component 4: Project management and dissemination

     177) Based on the scope and applicability of the tools, the activities in Component 1 were
        assessed. The results of the carbon balance obtained by the tools are summarized in Figure
        8. The analyses focus on the integration of livestock and agricultural waste management on
        large-scale and medium-scale farms. Within the analysis, we assume that cattle and swine's
        methane (CH 4 ) emissions from enteric fermentation and manure management are reduced
        by half with the project implementation.




16
  The CBP DA could be used by replacing the severely degraded grassland carbon stock values with corresponding
values for set aside land based on the IPCC methodology.



                                                                                                           64
   Figure 8: Carbon balance per component and per tool (Shanghai Agricultural and Non-point Pollution
                                      Reduction Project, China)

                 0
                       EX-ACT     CBP   AFOLU Carb AFD CFT    CAT-AR    CCAFS      CFT
             -1,000

             -2,000

             -3,000

             -4,000

             -5,000

             -6,000

             -7,000

             tCO2eq/year



 178) The analysis considers a set of information determined as the minimum information
    required to carry out a GHG analysis as follows:
      • Country/continental region: China/Asia continental
      • Climate and moisture regime: Warm temperate moist
      • Dominant regional soil type: Low activity clay soils
      • Duration of the project implementation: 5 years and duration of analysis set to 20
          years

  179) While some calculations might not require all the above information, others might also
      require the moisture regime and the MAT.
5.7.1 Detailed project analysis per activity for Shanghai Agricultural and Non-Point Pollution
Reduction Project

5.7.1.1 Livestock

 180) Based on the sources, sinks, and SLM activities accounted for by the tools, four tools
    (EX-ACT, CBP DA, CCAFS-MOT, and CFT) were used to analyze livestock management
    activities (see Table 9). However, only two tools—EX-ACT and CBP DA—can estimate
    the total carbon balance, because these tools give the user the option of using Tier 2 values
    for livestock. The CFT tool does not allow the user to enter Tier 2 values for livestock;
    therefore, it is not possible to compare the with- and without-project GHG balance.
    Additionally, neither the CFT nor the CCAFS-MOT tool provides the user with options to
    analyze potential mitigation achieved through the improvement of feeding practices,
    manure management, and energy consumption.


                                                                                                        65
     181) The difference in results between the EX-ACT and CBP DA tools is minor (1 percent).
        Based on this analysis, the EX-ACT 17 and CBP tools are suitable for livestock GHG
        analysis using Tier 2 methodology.

5.7.2 Project carbon balance

     182) The overall project result ranges between −0.51 and −0.55 tCO 2 per head per year. The
        uncertainty level is quite similar between the two tools—21 percent for the CBP tool and
        20 percent for the EX-ACT tool.

5.8 Costa Rica, Biodiversity Conservation in Cacao Agroforestry

     183) The rationale of the project is to improve the management of cacao-based poor
        indigenous small-farms according to both ecological and organic productive principles to
        ensure conservation and sustainable use of plant and animal diversity and provide a
        sustainable source of family income. The overall objective of the project is to promote and
        maintain on-farm biodiversity while improving livelihoods of organic cacao producers
        (indigenous, Latin mestizos, and Afro Caribbean groups) in the Talamanca-Caribbean
        corridor in Costa Rica. The project has four components:
          • Component 1: Promotion and Conservation of On-Farm Biodiversity
          • Component 2: Production, Certification & Marketing of Biodiversity-Friendly,
              Organic Products
          • Component 3: Strengthening Farmers and Producers Organizations
          • Component 4: Biodiversity and Monitoring

     184) Based on the scope and applicability of the tools, the activities in Component 1 were
        assessed. The results of the carbon balance obtained by the tools are summarized in Figure
        9. The analyses focus on rehabilitation planning of cocoa plantations.




17
  For users who wish to use detailed Tier 2 (for example, refined EFs on enteric fermentation) a link is provided by
the EX-ACT tool to the FAO GLEAM-I tool.



                                                                                                                  66
  Figure 9: Carbon balance per component and per tool (Biodiversity Conservation in Cacao Agroforestry,
                                             Costa Rica)
                  0
                           EX-ACT      CBP    AFOLU Carb AFD CFT    CAT-AR       CCAFS       CFT
             -1,000

             -2,000

             -3,000

             -4,000

             -5,000

             -6,000

             -7,000

             -8,000
             tCO2eq/year
                                Land Use Changes (Afforestation)   Agriculture (perennial)



 185) The analysis considers a set of information determined as the minimum information
    required to carry out a GHG analysis as follows:
      • Country/continental region: Costa Rica/Central America
      • Climate and moisture regime: Tropical moist
      • Dominant regional soil type: Low activity clay soils
      • Duration of the project implementation: 6 years and duration of analysis set to 20
          years

 186) While some calculations might not require all the above information, others might also
    require the moisture regime and the MAT.

5.8.1 Detailed project analysis per activity for Costa Rica Biodiversity Conservation in Cacao
Agroforestry Project

5.8.1.1 Afforestation activities (ILU: set aside land)

 187) Based on the sources, sinks, and SLM activities accounted for by the tools, five tools
    (CAT-AR, CBP SA, AFD-CFT, AFOLU Carb, and EX-ACT) were used to analyze
    afforestation activities (see Table 9). Because the analysis was conducted following the
    Tier 1 methodology, the default coefficients generated by the tools were used. The standard
    deviation is estimated at 428 tCO 2 eq per year and the mean at −2,338.8 tCO 2 eq per year
    with a significance level of 0.05 (CI = 95 percent, 1.960 standard error of the mean).
    Therefore, the range of results for afforestation activities should be between −1,963 and
    −2,714 tCO 2 eq per year.




                                                                                                      67
     188) The range of expected results allows us to observe the differences between the tools
        while analyzing afforestation activities. These differences are explained by the fact that the
        AFOLU Carb does not consider the gain-loss and stock difference methods (Table 8) and
        therefore, does not compute emissions or removals as change over time of carbon stocks
        for the different pools. The difference in results between the EX-ACT, CBP, AFD-CFT,
        and CAT-AR tools varies: EX-ACT and CBP have a 14 percent difference, EX-ACT and
        AFD-CFT a 25 percent difference, EX-ACT and CAT-AR a 6 percent difference, CBP and
        AFD-CFT a 39 percent difference, CBP and CAT-AR a 7 percent difference, and AFD-
        CFT and CAT-AR a 32 percent difference. The difference between the CAT-AR, CBP SA,
        AFD-CFT, and EX-ACT tools could be explained by the use of the Tier 1 methodology
        and the absence of set aside land as ILU for the CBP SA tool.

     189) Based on this analysis, the three tools—CAT-AR, AFD-CFT, and EX-ACT—are suitable
        for afforestation GHG analysis when considering set aside land as the ILU change. 18

5.8.1.2 Perennial crops improvement

     190) Based on the sources, sinks, and SLM activities accounted for by the tools, three tools
        (EX-ACT, CBP DA, and AFD-CFT) were used to analyze perennial activities (see Table 9).
        The analysis consists of improving perennial crops management practices. To follow the
        Tier 2 methodology, the default Tier 1 coefficients were replaced to describe the initial and
        final (after improvements) above-ground growth rate (t C per ha per year), both to
        characterize the type of vegetation and the biomass growth. The mean and standard
        deviation are respectively −4,827 tCO 2 eq per year and 23.38 tCO 2 eq per year with the 95
        percent confidence interval of the mean between −4,800 and −4,853 tCO 2 eq per year.

     191) All the results generated by the tools were situated within this estimated range. The
        differences in results between the EX-ACT, CBP, and AFD-CFT tools are minor: EX-ACT
        and CBP have a 2 percent difference, EX-ACT and AFD-CFT a 2 percent difference, and
        CBP and AFD-CFT a 5 percent difference.

     192) Based on this analysis, the three tools—EX-ACT, CBP, and AFD-CFT—are suitable for
        perennial crops improvement GHG analysis using Tier 2 coefficients.

5.8.2 Project carbon balance

     193) For the overall project results, the AFD-CFT, CBP DA, and EX-ACT tools cover the
        appropriate areas of the project GHG appraisal by providing relatively close results (0.62
        tCO 2 eq per ha per year of difference between the two extreme results −5.28 (CBP) and
        −5.9 (AFD-CFT) tCO 2 eq per ha per year) to the estimated carbon count. The uncertainty

18
  The CBP DA could be used by replacing the severely degraded grassland carbon stock values with corresponding
values for set aside land based on the IPCC methodology.



                                                                                                            68
      level is higher for the CBP tool, at 62 percent, while the EX-ACT results are accompanied
      by an uncertainty level of 27 percent.

5.9 Ethiopia, Country Program for Sustainable Land Management (ECPSLM)

 194) The objective of the proposed program is to conserve and restore landscapes of global
    and national ecological, economic, and social importance through the adoption of SLM
    policies, practices, and technologies. The four initial indicative components of the program
    or packages of activities to be developed under the program are the following:
      • Component 1: Institutional strengthening
      • Component 2: Actions on the ground to scale up SLM
      • Component 3: Land Monitoring System
      • Component 4: Program Coordination and Management

 195) Based on the scope and applicability of the tools, the activities in Component 2 were
    assessed. The results of the carbon balance obtained by the tools are summarized in Figure
    10. The analyses focus on scaling up SLM through the provision of financial and technical
    support to implement on a wider scale, with on-the-ground results, appropriate best
    practices, and technologies selected by the intended beneficiaries.

       Figure 10: Carbon balance per component and per tool (Country Program for SLM, Ethiopia)
   500,000

         0
                 EX-ACT             CBP      AFOLU Carb     AFD CFT       CAT-AR        CCAFS           CFT
  -500,000

 -1,000,000

 -1,500,000

 -2,000,000

 -2,500,000

 -3,000,000

 -3,500,000

          Land Use Changes (Afforestation)                  Agriculture (Annual)
          Agriculture (Perennial)                           Grassland and Livestock (Grassland management)
          Degradation and Management (forest degradation)   Inputs & Investments



 196) The analysis considers a set of information determined as the minimum information
    required to carry out a GHG analysis as follows:


                                                                                                              69
          •   Country/continental region: Ethiopia/Africa
          •   Climate and moisture regime: Tropical dry
          •   Dominant regional soil type: High activity clay soils
          •   Duration of the project implementation: 5 years and duration of analysis set to 20
              years

     197) While some calculations might not require all the above information, others might also
        require the moisture regime and the MAT.

5.9.1 Detailed project analysis per activity for ECPSLM

5.9.1.1 Afforestation activities (ILU: set aside land and degraded land)

     198) Based on the sources, sinks, and SLM activities accounted for by the tools, five tools
        (CAT-AR, CBP SA, AFD-CFT, AFOLU Carb, and EX-ACT) were used to analyze
        afforestation activities (see Table 9). Because the analysis was conducted following the
        Tier 1 methodology, the default coefficients generated by the tools were used. The mean
        and standard deviation are respectively −3,402,056.2 tCO 2 eq per year and 259,244 tCO 2 eq
        per year, with the 95 percent confidence interval of the mean between −929,309 and
        −1,383,786 tCO 2 eq per year.

     199) The range of expected results allows us to observe the differences between the tools
        while analyzing afforestation activities. Several factors could contribute to this, including
        that the AFOLU Carb does not consider the gain-loss and stock difference methods (Table
        8) and therefore, does not compute emissions related to land use change.

     200) The differences in results between the EX-ACT, CBP, AFD-CFT, and CAT-AR tools
        varies: EX-ACT and CBP have a 3 percent difference, EX-ACT and AFD-CFT a 29
        percent difference, EX-ACT and CAT-AR a 22 percent difference, CBP and AFD-CFT a
        25 percent difference, CBP and CAT-AR an 18 percent difference, and AFD-CFT and
        CAT-AR a 7 percent difference. Furthermore, the difference between the CAT-AR, CBP
        SA, AFD-CFT, and EX-ACT tools could be explained by the fact that the Tier 1
        methodology and the absence of set aside land and degraded land as ILU for the CBP SA
        and of degraded land for the AFD-CFT.

     201) Based on this analysis, the three tools—CAT-AR, AFD-CFT, and EX-ACT—are suitable
        for afforestation GHG analysis when considering set aside land as ILU. 19 The EX-ACT
        tool is also suitable for afforestation GHG analysis when considering degraded land as ILU
        change.


19
  The CBP DA could be used by replacing the severely degraded grassland carbon stock values with set aside and
degraded land corresponding values based on the IPCC methodology.



                                                                                                           70
5.9.1.2 Annual cropland improvement

 202) Based on the sources, sinks, and SLM activities accounted for by the tools, six tools (EX-
    ACT, AFOLU Carb, CBP SA, AFD-CFT, CCAFS-MOT, and CFT) were used to analyze
    annual cropland activities (see Table 9). Because the analysis was conducted following the
    Tier 1 methodology, the default coefficients generated by the tools were used. The standard
    deviation is estimated at 159,745 tCO 2 eq per year and the mean at −3,402,056.2 tCO 2 eq
    per year with a significance level of 0.05 (CI = 95 percent, 1.960 standard error of the
    mean). Therefore, the range of results for annual cropland activities should be between
    −288,854 and −544,500 tCO 2 eq per year.

 203) Except for the CBP and EX-ACT, all the results generated by the other tools were
    situated within a range of −270,000 and −370,000 tCO 2 eq per year. However, the results
    generated by the CCAFS-MOT, CFT, AFOLU Carb, and AFD-CFT tools did not cover all
    the improved management options expressed within the project document. For instance,
    using the CCAFS-MOT, we assume that the entire area of annual crops will be subject to
    improvement by halting residue burning and promoting zero tillage, while the project
    suggests that the annual crops improvements are improved agronomic practices, no tillage,
    water management, and manure application. Further, the CCAFS-MOT and CFT tools do
    not account for the gain-loss and stock difference carbon accounting. For the sake of
    comparison, the estimated carbon balance using the two tools (CCAFS-MOT and CFT
    tools) was calculated separately (without- and with-project scenarios).

 204) The six tools have annual crops as an activity scope and can estimate the mitigation
    potential of this activity. However, due to the abovementioned limitations, the use of the
    AFD-CFT, AFOLU Carb, CCAFS-MOT, and CFT tools is not recommended. The
    difference in results between the EX-ACT and CBP tools is significant (68 percent). Based
    on this analysis, the two tools—EX-ACT and CBP—are suitable for annual crops’ GHG
    analysis when considering improved practices scenarios.

5.9.1.3 Grassland management

 205) Based on the sources, sinks, and SLM activities accounted for by the tools, four tools
    (EX-ACT, AFOLU Carb, CBP SA, and AFD-CFT) were used to analyze grassland
    management activities (see Table 9). Because the analysis was conducted following the
    Tier 1 methodology, the default coefficients generated by the tools were used. The mean
    and standard deviation are respectively −363,371 tCO 2 eq per year and 20,268 tCO 2 eq per
    year, with the 95 percent confidence interval of the mean between −333,508 and −383,233
    tCO 2 eq per year.

 206) All the results generated by the tools were situated within this estimated range. The
    differences in the results generated by the tools were mainly due to the use of different
    IPCC GHG accounting approaches and carbon pools (Tables 8 and 10). For example, the


                                                                                             71
     AFD-CFT tool calculates the default soil carbon stock changes based on a set of IPCC
     criteria, whereas, the AFOLU Carb provides estimated values for relative stock change
     factors based on the project location.

 207) The difference in results between the tools varies: EX-ACT and CBP have a 10 percent
    difference, EX-ACT and AFD-CFT a 12 percent difference, EX-ACT and AFOLU Carb a
    33 percent difference, CBP and AFD-CFT a 1 percent difference, CBP and AFOLU Carb a
    23 percent difference, and AFD-CFT and AFOLU Carb a 23 percent difference.

5.9.1.4 Forest management and degradation

 208) Based on the sources, sinks, and SLM activities accounted for by the tools, two tools
    (EX-ACT and CBP SA) were used to analyze forest management and degradation activities
    (see Table 9). Since the analysis was conducted following the Tier 1 methodology, the
    default coefficients generated by the tools were used. The AFOLU Carb tool is not
    considered within the analysis; although it considers forest protection activities, it does not
    consider the biomass losses that are not due to deforestation or illegal logging. The
    difference in results between the EX-ACT and CBP tools is relatively small (6.2 percent).
    Based on this analysis, the two tools—EX-ACT and CBP—are suitable for forest
    management GHG analysis.

5.9.1.5 Inputs and Investments (electricity, irrigation, buildings, and roads construction)

 209) Based on the sources, sinks, and SLM activities accounted for by the tools, two tools
    (EX-ACT and AFD-CFT) were used to analyze inputs and investments activities (see Table
    9)—in the project’s case, electricity, irrigation, buildings, and roads. Because the analysis
    was conducted following the Tier 1 methodology, the default coefficients generated by the
    tools were used. The difference in results is explained by the tools’ different coverage of
    the activities. Based on this analysis, the EX-ACT and AFD-CFT tools are suitable for the
    electricity, buildings, and roads construction GHG analysis, while EX-ACT also can be
    used to analyze activities related to the installation of new irrigation infrastructure.

5.9.2 Project carbon balance

 210) For the overall project results, the EX-ACT tool covers the aspects of the project GHG
    appraisal. The estimated carbon balance is −66,317,269 tCO 2 eq for the entire duration of
    the analysis (20 years) or 3 tCO 2 per ha per year. The uncertainty level is 39 percent.

5.10 Guinea, Community-based Land Management Project

 211) The development objective of the project is to reduce land degradation through the
    integration of SLM practices into the overall development planning process of communities
    and local governments in selected pilot sub-watersheds. The global objective of the project
    is to pilot sustainable and replicable approaches to the prevention and mitigation of the


                                                                                                72
   causes and negative impacts of land degradation on the structure and functional integrity of
   ecosystems. The project has three components:
     • Component 1: Local Investment Fund
     • Component 2: Capacity Building for Local Development
     • Component 3: Project Management, Coordination, and Monitoring and Evaluation

212) Based on the scope and applicability of the tools, the activities in Component 1 were
   assessed. The results of the carbon balance obtained by the tools are summarized in Figure
   11. The analyses focus on enhancing SLM focused investments and supporting the
   demonstration of practices that would reduce land degradation.

Figure 11: Carbon balance per component and per tool (Community-based Land Management Project,
                                            Guinea)
         0
                 EX-ACT   CBP       AFOLU Carb       AFD CFT   CAT-AR        CCAFS   CFT
    -50,000


   -100,000


   -150,000


   -200,000


   -250,000


   -300,000
   tCO2eq/year             Degradation and Management (forest degradation)
                           Agriculture (Perennial)
                           Agriculture (Annual)
                           Land Use Changes (Deforestation)



213) The analysis considers a set of information determined as the minimum information
   required to carry out a GHG analysis as follows:
     • Country/continental region: Guinea/Africa
     • Climate and moisture regime: Tropical moist
     • Dominant regional soil type: Low activity clay soils
     • Duration of the project implementation: 8 years and duration of analysis set to 20
         years

214) While some calculations might not require all the above information, others might also
   require the moisture regime and the MAT.




                                                                                                 73
5.10.1 Detailed project analysis per activity for the Guinea Community-based Land Management
Project

5.10.1.1 Deforestation activities (FLU: set aside land and annual cropland)

     215) Based on the sources, sinks, and SLM activities accounted for by the tools, three tools
        (EX-ACT, CBP SA, and AFOLU Carb) were used to analyze deforestation activities (see
        Table 9). Because the analysis was conducted following the Tier 1 methodology, the
        default coefficients generated by the tools were used. The standard deviation is estimated at
        11,083 tCO 2 eq per year and the mean at −91,180 tCO 2 eq per year with a significance level
        of 0.05 (CI = 95 percent, 1.960 standard error of the mean). Therefore, the range of results
        for deforestation activities should be between −80,318 and −102,042 tCO 2 eq per year.

     216) All the tools provided results within this calculated range. The AFOLU Carb generated
        a value further away from the mean value. This is explained by the fact that the AFOLU
        Carb does not account for the gain-loss and stock difference methods, and therefore, does
        not compute emissions or removals as the change over time of carbon stocks for the
        different pools.

     217) The differences in results between the tools varies: 20 EX-ACT and CBP have a 10
        percent difference, EX-ACT and AFOLU Carb a 14 percent difference, and CBP SA and
        AFOLU Carb a 24 percent difference. Based on this analysis, the three tools—EX-ACT,
        CBP, and AFOLU Carb—are suitable for deforestation GHG analysis when considering
        annual cropland as the FLU.

5.10.1.2 Annual cropland improvement

     218) Based on the sources, sinks, and SLM activities accounted for by the tools, six tools (EX-
        ACT, CBP SA, AFD-CFT, AFOLU Carb, CCAFS-MOT, and CFT) were used to analyze
        annual cropland activities (see Table 9). Since the analysis was conducted following the
        Tier 1 methodology, the default coefficients generated by the tools were used. The mean
        and standard deviation are respectively −10,154 tCO 2 eq per year and 2,286 tCO 2 eq per
        year. The 95 percent confidence interval of the mean is between −8,325 and −11,983
        tCO 2 eq per year.

     219) Except for the CBP SA and EX-ACT, all the results generated by the tools were situated
        within this range. However, the results generated by the CCAFS-MOT, CFT, AFOLU Carb,
        and AFD-CFT tools are underestimated and do not cover all the improved management
        options expressed within the project document. For instance, using the CCAFS-MOT, we
        assume that the entire area of annual crops will be subject to improvement by stopping the
        residue burning and incorporating zero tillage. Furthermore, the CCAFS-MOT and CFT

20
     Using the Tier 2 methodology/coefficients, instead of Tier 1, could further decrease the difference.



                                                                                                            74
     tools do not provide a comparison of with and without the project scenario. The estimated
     carbon balance using the two tools (CCAFS-MOT and CFT tools) was calculated
     separately (without and with the project scenarios) for the sake of comparison.

 220) The six tools have annual crops as an activity scope and can estimate the mitigation
    potential of this activity. However, due to the abovementioned limitations, the use of the
    AFD-CFT, AFOLU Carb, CCAFS-MOT, and CFT tools is not recommended. The
    differences in results between the EX-ACT and CBP tools is 31 percent. Based on this
    analysis, the two tools—EX-ACT and CBP—are suitable for annual crops GHG analysis
    when considering improved practices scenarios.

5.10.1.3 Perennial cropland development (ILU: annual crops)

 221) Based on the sources, sinks, and SLM activities accounted for by the tools, three tools
    (EX-ACT, CBP SA, AFD-CFT) were used to analyze perennial activities (see Table 9).
    Although the AFOLU Carb tool includes cropland management within its activity scope, it
    was not used because it does not differentiate between perennial and annual crops (Table 9).
    Because the analysis was conducted following the Tier 1 methodology, the default
    coefficients generated by the tools were used. The standard deviation is estimated at 2,621
    tCO 2 eq per year and the mean at −107,022 tCO 2 eq per year with a significance level of
    0.05 (CI = 95 percent, 1.960 standard error of the mean). Therefore, the range of results for
    perennial cropland development activities should be between −81,328 and −132,715
    tCO 2 eq per year.

 222) All the results generated by the tools were situated within this estimated range. The AFD-
    CFT tool estimated a carbon balance value further away from the mean value. Furthermore,
    the differences in results between the tools varies: EX-ACT and CBP have a 15 percent
    difference, EX-ACT and AFD-CFT a 42 percent difference, and CBP SA and AFD-CFT a
    27 percent difference. Based on this analysis, the three tools—EX-ACT, CBP, and AFD-
    CFT—are suitable for perennial development GHG analysis when considering annual
    cropland as ILU change.

5.10.1.4 Forest management and degradation (forest fire management)

 223) Based on the sources, sinks, and SLM activities accounted for by the tools, three tools—
    EX-ACT, CBP SA, and AFOLU Carb—were used to analyze forest management and
    degradation activities (see Table 9). The analysis was conducted following the Tier 1
    methodology, and as such, the default coefficients generated by the tools were used.

 224) Although the AFOLU Carb tool takes into account the fire impact, the difference in
    results is explained by the suggested default Forest Carbon Stock value, which is the
    average of the above- and below-ground forest carbon stock in the tree pool (Table 8). The
    differences in results between the tools varies: EX-ACT and CBP have a 9 percent


                                                                                              75
     difference, EX-ACT and AFOLU Carb a 13 percent difference, and CBP SA and AFOLU
     Carb a 3.94 percent difference. This difference could be explained by the fact the CBP does
     not consider fire occurrence lower than 1.0 percent, and the activity suggests that the fire
     impact (percent burnt) will be reduced from 0.2 percent to 0.1 percent yearly with the
     project implementation. Based on this analysis, the three tools—EX-ACT, CBP, and
     AFOLU Carb—are suitable for GHG analysis of forest fire management.

5.10.2 Project carbon balance

 225) For the overall project results, the scope of the CBP and EX-ACT tools covers the
    appropriate areas for the overall objectives of the project. Both tools provided relatively
    similar results within the range of 0.2 tCO 2 eq per year difference. Despite this, the
    uncertainty level is higher for the EX-ACT tool at 44 percent, while the CBP results are
    accompanied by an uncertainty level of 37 percent.

5.11 Jordan, Integrated Ecosystem Management in the Jordan Rift Valley

 226) The development objective of the Jordan Rift Valley project is to apply the principles of
    integrated ecosystem management to the existing land use master plan of the Jordan Rift
    Valley and establish a network of well-managed protected areas that meets local ecological,
    social, and economic needs. The project has five components:
      • Component 1: Assessment and Planning for Integrated Ecosystem Management
      • Component 2: Development of a network of biodiversity conservation sites
      • Component 3: Integrated Assessments of Climate Change Impacts on Biodiversity
          Conservation
      • Component 4: Strengthening sustainable financing mechanisms
      • Component 5: Project management, coordination, and M&E

 227) Based on the scope and applicability of the tools, the activities in Component 2 were
    assessed. The results of the carbon balance obtained by the tools are summarized in Figure
    12. The analyses focus on developing a network of biodiversity conservation sites,
    embodying the principles of integrated ecosystem management.




                                                                                              76
 Figure 12: Carbon balance per component and per tool (Integrated Ecosystem Management in the Jordan
                                         Rift Valley, Jordan)

                 0
                      EX-ACT     CBP     AFOLU    AFD CFT   CAT-AR    CCAFS      CFT
                                          Carb
            -50,000


           -100,000


           -150,000


           -200,000


           -250,000


           -300,000
            tCO2eq/year



 228) The analysis considers a set of information determined as the minimum information
    required to carry out a GHG analysis as follows:
      • Country/continental region: Jordan/Middle East
      • Climate and moisture regime: Warm temperate dry
      • Dominant regional soil type: High activity clay soils
      • Duration of the project implementation: 6 years and duration of analysis set to 20
          years

 229) While some calculations might not require all the above information, others might also
    require the moisture regime and the MAT.

5.11.1 Detailed project analysis per activity for the Jordan Integrated Ecosystem Management in
the Jordan Rift Valley Project

5.11.1.1 Grassland development (ILU: set aside land)

 230) Based on the sources, sinks, and SLM activities accounted for by the tools, three tools
    (EX-ACT, CBP SA, and AFD-CFT) were used to analyze grassland development activities
    (see Table 9). Since the activity analysis was conducted following the Tier 1 methodology,
    the default coefficients generated by the tools were used. The activity consists of
    developing grassland on set aside land.

 231) The differences in the results generated by the tools are mainly due to the difference in
    the EFs and carbon stock change values associated with the Tier 1 methodology. For
    instance, the CBP SA does not take ‘set aside land’ as an ILU. Thus, it was replaced by
    severely degraded grassland. The difference in results between EX-ACT and AFD-CFT is


                                                                                                   77
        minor (9 percent difference). Based on this analysis, the EX-ACT and AFD-CFT tools are
        suitable for grassland development GHG analysis when considering set aside land as the
        ILU. 21

5.12 Mali, Natural Resources Management in a Changing Climate

     232) The project development objective is to secure the ecological integrity of the sites as
        globally important ecological corridors and migratory flyways, through a combination of
        integrated land use planning, ecologically appropriate and nature-based socioeconomic
        development, and biodiversity protection and management. The project has four
        components:
          • Component 1: Knowledge management, Governance, and Communication
          • Component 2: Scaling-up Sustainable land management practices
          • Component 3: Diversification of local livelihoods
          • Component 4: Project coordination, monitoring, and evaluation

     233) Based on the scope and applicability of the tools, the activities in Component 2 were
        assessed. The results of the carbon balance obtained by the tools are summarized in Figure
        13. The analyses focus on (a) scaling up SLM practices, (b) improving the sustainable use
        of biodiversity resources in the targeted areas, (c) reversing the reduction of forest coverage,
        and (d) strengthening the resilience of rural producers' assets in the targeted areas and
        communities to climate change challenges.




21
  The CBP DA could be used by replacing the severely degraded grassland carbon stock values with corresponding
values for set aside land based on the IPCC methodology.



                                                                                                            78
  Figure 13: Carbon balance per component and per tool (Natural Resources Management in a Changing
                                           Climate, Mali)
       0
                EX-ACT     CBP      AFOLU Carb      AFD CFT        CAT-AR         CCAFS   CFT

  -50,000



 -100,000



 -150,000



 -200,000



 -250,000                               Land Use Changes (Deforestation)
  tCO2eq/year                           Land Use Changes (Afforestation)
                                        Agriculture (Annual)
                                        Grassland and Livestock (Grassland management)


 234) The analysis considers a set of information determined as the minimum information
    required to carry out a GHG analysis as follows:
      • Country/continental region: Mali/Africa
      • Climate and moisture regime: Tropical dry
      • Dominant regional soil type: High activity clay soils
      • Duration of the project implementation: 5 years and duration of analysis set to 20
          years

 235) While some calculations might not require all the above information, others might also
    require the moisture regime and the MAT.

5.12.1 Detailed project analysis per activity for the Mali Natural Resources Management in a
Changing Climate Project

5.12.1.1Deforestation (FLU: grassland)

 236) Based on the sources, sinks, and SLM activities accounted for by the tools, three tools
    (EX-ACT, CBP SA, and AFOLU Carb) were used to analyze deforestation activities (see
    Table 9). Because the analysis was conducted following the Tier 1 methodology, the
    default coefficients generated by the tools were used. The standard deviation is estimated at
    6,593.9 tCO 2 eq per year and the mean at −36,567.75 tCO 2 eq per year with a significance
    level of 0.05 (CI = 95 percent, 1.960 standard error of the mean). Therefore, the range of
    results for deforestation activities should be between −30,105 and −43,029 tCO 2 eq per year.



                                                                                                     79
     237) Except for the CBP SA, all the tools generated results within this estimated range. The
        AFOLU Carb generated a value further away from the mean value, which can be explained
        by the fact that the AFOLU Carb does not account for the gain-loss and stock difference
        methods (Table 8) and therefore, does not compute emissions or removals as the change
        over time of carbon stocks for the different pools.

     238) The differences in results between the EX-ACT, CBP, and AFOLU Carb tools varies:
        EX-ACT and CBP have a 54 percent difference, EX-ACT and AFOLU Carb a 14 percent
        difference, and CBP and AFOLU Carb a 66 percent difference. Using the Tier 2
        coefficients instead of Tier 1 methodology could further decrease the difference. Based on
        this analysis, the three tools—EX-ACT, CBP, and AFOLU Carb—are suitable for
        deforestation GHG analysis when considering grassland as the FLU.

5.12.1.2 Afforestation activities (ILU: set aside land and degraded land)

     239) Based on the sources, sinks, and SLM activities accounted for by the tools, five tools
        (EX-ACT, CBP SA, AFOLU Carb, AFD-CFT, and CAT-AR) were used to analyze
        afforestation activities (see Table 9). Because the analysis was conducted following the
        Tier 1 methodology, the default coefficients generated by the tools were used. The mean
        and standard deviation are respectively −6,608.6 tCO 2 eq per year and 2,366 tCO 2 eq per
        year, with 95 percent confidence interval of the mean between −4,534 and −8,682 tCO 2 eq
        per year.

     240) Except for the AFOLU Carb tool, all the results generated by the tools are situated within
        this estimated range. The AFOLU Carb tool does not account for the gain-loss and stock
        difference methods, and therefore, does not compute emissions or removals as the change
        over time of carbon stocks for the different pools (Table 8). The differences in results
        between the EX-ACT, CBP, AFD-CFT, and CAT-AR tools varies: EX-ACT and CBP have
        a 54 percent difference, EX-ACT and AFD-CFT a 19 percent difference, and CBP and
        AFD-CFT a 71 percent difference. The differences observed between the CAT-AR, CBP
        SA, AFD-CFT, and EX-ACT tools could be explained by the fact that Tier 1
        methodology/coefficients, different GHG accounting approaches, and carbon pools were
        applied in the analyses (Table 8).

     241) Based on this analysis, the three tools—CAT-AR, AFD-CFT, and EX-ACT—are suitable
        for afforestation GHG analysis when considering set aside land as ILU, while, the EX-ACT
        tool is suitable for afforestation GHG analysis when considering degraded land as ILU. 22

5.12.1.3 Annual cropland improvement


22
  The CBP DA could be used by replacing the severely degraded grassland carbon stock values with corresponding
values for set aside land and degraded land based on the IPCC methodology.



                                                                                                           80
 242) Based on the sources, sinks, and SLM activities accounted for by the tools, six tools (EX-
    ACT, CBP SA, AFD-CFT, AFOLU, CCAFS-MOT, and CFT) were used to analyze annual
    cropland activities (see Table 9). The activity consists of improving management practices
    of annual crops. The analysis was conducted following the Tier 1 methodology; therefore,
    the default coefficients generated by the tools were used. The mean and standard deviation
    are respectively −3,402,056.2 tCO 2 eq per year and 159,745 tCO 2 eq per year. The
    estimated confidence interval of the mean is between −288,854 and −544,500 tCO 2 eq per
    year.

 243) Except for the CBP SA and EX-ACT tools, all the results generated by the tools were
    situated within a range of −2,383 and −2,499 tCO 2 eq per year. However, the results
    generated by the CCAFS-MOT, CFT, AFOLU Carb, and AFD-CFT tools were
    underestimated as they did not reflect all the improved management options expressed
    within the project document. For instance, using the CCAFS-MOT, we assume that the
    entire area of annual crops will be subject to improvement by stopping the residue burning
    and incorporating zero tillage, while the project suggests that the annual crops
    improvements are improved agronomic practices, nutrient management, residue
    management, and manure application. Further to this, the CCAFS-MOT and CFT tools are
    not based on gain-loss and stock difference methods (Table 8). The estimated carbon
    balance using the two tools (CCAFS-MOT and CFT tools) was calculated separately
    (without and with the project scenarios) for the sake of comparison. As for the AFOLU
    Carb tool, it considers only two improvements, the tillage (full, reduced, and no-till) and
    inputs (low, medium, high with and without manure), to describe the improved
    management options for annual cropland.

 244) The six tools have annual crops as an activity scope and can estimate the mitigation
    potential of this activity. However, due to the abovementioned limitations, the use of the
    AFD-CFT, AFOLU Carb, CCAFS-MOT, and CFT tools is not recommended. The
    differences in results between the EX-ACT and CBP tools is high (70 percent). Based on
    this analysis, the two tools, EX-ACT and CBP, are suitable for annual crops GHG analysis
    when considering improved practices scenarios.

5.12.1.4 Grassland management

 245) Based on the sources, sinks, and SLM activities accounted for by the tools, four tools
    (EX-ACT, CBP SA, AFOLU Carb, and AFD-CFT) were used to analyze grassland
    management activities (see Table 9). Because the analysis was conducted following the
    Tier 1 methodology, the default coefficients generated by the tools were used. The mean
    and standard deviation are respectively −156,784 tCO 2 eq per year and 11,546 tCO 2 eq per
    year with 95 percent confidence interval of the mean between −145,468 and −168,100
    tCO 2 eq per year.




                                                                                             81
     246) All the results generated by the tools were situated within this estimated range. The
        difference in the results generated is mainly due to the difference in the EFs and carbon
        stock change values associated with the Tier 1 methodology. For example, the AFD-CFT
        tool calculates the default soil carbon stock changes based on a set of IPCC criteria,
        whereas the AFOLU Carb provides estimated values for relative stock change factors
        (Table 8).

     247) The differences in results between the EX-ACT, CBP, AFD-CFT, and AFOLU tools
        varies: EX-ACT and CBP have a 6 percent difference, EX-ACT and AFD-CFT a 20
        percent difference, EX-ACT and AFOLU Carb a 2 percent difference, CBP and AFD-CFT
        a 14 percent difference, CBP and AFOLU Carb an 8 percent difference, and AFD-CFT and
        AFOLU Carb a 22 percent difference. Based on this analysis, the four tools—EX-ACT,
        CBP, AFD-CFT, and AFOLU Carb—are suitable for grassland management GHG
        analysis. 23

5.12.2 Project carbon balance

     248) For the overall project results, four tools—the CBP, EX-ACT, AFD-CFT, and AFOLU
        Carb—have a scope that covers all project activities. The tools provide relatively close
        results (see Table 14). The uncertainty level for the CBP tool equals 32 percent, while the
        EX-ACT results are accompanied by an uncertainty level of 48 percent due to the use of
        Tier 1 methodology.
Table 14: Carbon balance results for the Mali Natural Resources Management in a Changing Climate Project
            Tools
                                  EX-ACT               CBP           AFOLU Carb            AFD CFT
          (tCO 2 eq)
Total                            −4,065,339        −4,110,680         −4,300,499           −3,618,000
Total per year                    −203,267          −205,534           −215,025             −180,900
Per hectare                          −34              −34.7             −36.3                −30.6
Per hectare per year                −1.72             −1.74             −1.82                −1.53

5.13 Moldova, Agriculture Competitiveness Project

     249) The development objective of the Agriculture Competitiveness Project for Moldova is to
        enhance the competitiveness of the country’s agrofood sector by supporting the
        modernization of the food safety management system, facilitating market access for
        farmers, and mainstreaming agro-environmental and SLM practices. The project has five
        components:
          • Component 1: Enhancing food safety management
          • Component 2: Enhancing market access potential
          • Component 3: Enhancing land productivity through sustainable land management
          • Component 4: Project management

23
  It should be noted that the specific value of organic carbon present in soils should be generated for the AFOLU
Carb tool.



                                                                                                                    82
       •   Component 5: Compensatory sales support grants

 250) Based on the scope and applicability of the tools, the activities in Component 3 were
    assessed. The results of the carbon balance obtained by the tools are summarized in Figure
    14. The analyses focus on enhancing land productivity through SLM, supporting activities
    to mainstream SLM practices and technologies, and rehabilitating anti-erosion shelterbelts.

  Figure 14: Carbon balance per component and per tool (Agriculture Competitiveness Project, Moldova)
                 0
                      EX-ACT     CBP       AFOLU       AFD CFT    CAT-AR       CCAFS   CFT
                                            Carb
             -5,000


            -10,000


            -15,000


            -20,000


            -25,000

             tCO2eq/year        Agriculture (Annual)     Agriculture (Perennial)



 251) The analysis considers a set of information determined as the minimum information
    required to carry out a GHG analysis as follows:
      • Country/continental region: Moldova/Eastern Europe
      • Climate and moisture regime: Warm temperate moist
      • Dominant regional soil type: High activity clay soils
      • Duration of the project implementation: 5 years and duration of analysis set to 20
          years

 252) While some calculations might not require all the above information, others might also
    require the moisture regime and the MAT.

5.13.1 Detailed project analysis per activity for the Moldova Agriculture Competitiveness
Project

5.13.1.1 Annual cropland improvement

 253) Based on the sources, sinks, and SLM activities accounted for by the tools, six tools (EX-
    ACT, AFOLU Carb, CBP SA, AFD-CFT, CCAFS-MOT, CFT) were used to analyze
    annual cropland activities (see Table 9). Because the analysis was conducted following the
    Tier 1 methodology, the default coefficients generated by the tools were used. The activity

                                                                                                        83
     consists of improving management practices of annual crops. The mean and standard
     deviation are respectively −9,056 tCO 2 eq per year and 5,674 tCO 2 eq per year with the 95
     percent confidence interval of the mean between −4,516 and −13,596 tCO 2 eq per year.

 254) Except for the CBP SA and EX-ACT tools, all the results generated by the other tools
    were situated within a range of −2,383 and −2,499 tCO 2 eq per year. However,
    underestimation occurs for CCAFS-MOT, CFT, AFOLU Carb, and AFD-CFT and do not
    reflect all the improved management options cited in the project document. For instance,
    using the CCAFS-MOT, we assume that the entire area of annual crops will be subject to
    improvement by stopping the residue burning and incorporating zero tillage, while the
    project suggests that the annual crops improvements are improved agronomic practices,
    nutrient management, residue management, and manure application. Furthermore, the
    CCAFS-MOT and CFT tools do not provide a comparison of with and without the project
    scenarios. The estimated carbon balance using the two tools (CCAFS-MOT and CFT tools)
    was calculated separately (without and with the project scenarios) for the sake of
    comparison. As for the AFOLU Carb tool, it considers only two improvements, the tillage
    (full, reduced, and no-till) and inputs (low, medium, high with and without manure), to
    describe the improved management options for annual cropland.

 255) The six tools have annual crops as an activity scope and can estimate the mitigation
    potential of this activity. However, due to the abovementioned limitations, the use of the
    AFD-CFT, AFOLU Carb, CCAFS-MOT, and CFT tools is not recommended. The
    difference in results between the EX-ACT and CBP tools is high (31 percent). Based on
    this analysis, the two tools—EX-ACT and CBP—are suitable for annual crops GHG
    analysis when considering improved practices scenarios.

5.13.1.2 Perennial cropland improvement

 256) Based on the sources, sinks, and SLM activities accounted for by the tools, three tools
    (EX-ACT, CBP DA, and AFD-CFT) were used to analyze perennial activities. The activity
    analysis consists of improving perennial crops management practices. To follow the Tier 2
    methodology, the default Tier 1 coefficients were replaced to describe the initial and final
    (after improvements) above-ground growth rate (tC per ha per year). This was done to
    characterize both the type of vegetation and the biomass growth.

 257) The difference in results generated by the tools is minor: EX-ACT and CBP DA have a
    5.0 percent difference, AFD-CFT and CBP DA a 6.0 percent difference, and EX-ACT and
    AFD-CFT a 0.5 percent difference. Based on this analysis, the three tools—EX-ACT, CBP
    DA, and AFD-CFT—are suitable for perennial improvements GHG analysis when
    considering set aside land as the ILU.

5.13.2 Project carbon balance




                                                                                             84
 258) The project objectives’ scope is covered by three tools—the CBP, EX-ACT, and AFD-
    CFT. The tools provided relatively close results (see Table 15). The uncertainty level for
    the CBP tool equals 40 percent, while an uncertainty level of 46 percent accompanies the
    EX-ACT results.

              Table 15: Carbon balance results for Agriculture Competitiveness Project.
        Carbon Balance
                                         EX-ACT                    CBP                  AFD-CFT
           (tCO 2 eq)
             Total                       −397,955                −412,320               −300,000
         Total per year                 −19,897.76             −16,216.00              −15,000
           Per hectare                    −39.80                −41.232                  −30
       Per hectare per year                −1.99                  −2.06                  −1.5


5.14 Morocco, GEF Social and Integrated Agriculture (ASIMA)

 259) The project development objective is to increase the implementation of land and
    biodiversity conservation measures in selected projects directed at small farmers located in
    targeted marginal areas in the project area. The project has two components:
   • Component 1: Development of the capacities of public and private institutions on land
      and biodiversity conservation
   • Component 2: Transfer of land and biodiversity conservation measures among small
      farmers

 260) Based on the scope and applicability of the tools, the activities in Component 2 were
    assessed. The results of the carbon balance obtained by the tools are summarized in Figure
    15. The analyses focus on promoting land and biodiversity conservation measures in
    specific agri-food chains typical of marginal areas.




                                                                                                   85
 Figure 15: Carbon balance per component and per tool (GEF Social and Integrated Agriculture, Morocco)
       0
                EX-ACT          CBP        AFOLU Carb       AFD CFT     CAT-AR         CCAFS         CFT
  -50,000

 -100,000

 -150,000

 -200,000

 -250,000

 -300,000

 -350,000

 -400,000
 tCO2eq/year

            Land Use Changes (Agrforestry) + Agriculture (perennial)   Agriculture (Annual)    Livestock



 261) The analysis considers a set of information determined as the minimum information
    required to carry out a GHG analysis as follows:
      • Country/continental region: Morocco/Africa
      • Climate and moisture regime: Warm temperate dry
      • Dominant regional soil type: High activity clay soils
      • Duration of the project implementation: 5 years and duration of analysis set to 20
          years

 262) While some calculations might not require all the above information, others might also
    require the moisture regime and the MAT.

5.14.1 Detailed project analysis per activity for the Morocco GEF Social and Integrated
Agriculture (ASIMA)

5.14.1.1 Perennial cropland development (ILU: degraded land)

 263) Based on the sources, sinks, and SLM activities accounted for by the tools, three tools
    (EX-ACT, CBP SA, and AFD-CFT) were used to analyze perennial activities (see Table 9).
    Because the activity analysis was conducted following the Tier 1 methodology, the default
    coefficients generated by the tools were used.

 264) The difference in results between the tools varies: EX-ACT and CBP SA have a 36
    percent difference, EX-ACT and AFD-CFT a 0.82 percent difference, and CBP and AFD-


                                                                                                           86
        CFT a 35.5 percent difference. The high difference in results provided by the CBP SA tool
        could be explained by the uncertainty related to the Tier 1 methodology as well as the
        consideration of severely degraded grassland instead of degraded land as ILU for the CBP
        SA.

     265) Based on this analysis, the EX-ACT is a suitable tool for perennial cropland development
        GHG analysis when considering degraded land as ILU. 24

5.14.1.2 Annual cropland improvement

     266) Based on the sources, sinks, and SLM activities accounted for by the tools, six tools (EX-
        ACT, CBP SA, AFD-CFT, AFOLU Carb, CCAFS-MOT, and CFT) were used to analyze
        annual cropland activities (see Table 9). The activity consists of improving the
        management practices of annual crops. Because the analysis was conducted following the
        Tier 1 methodology, the default coefficients generated by the tools were used. The mean
        and standard deviation are respectively −4,123.5 tCO 2 eq per year and 2,074 tCO 2 eq per
        year with the 95 percent confidence interval of the mean between −2,463 and −5,783
        tCO 2 eq per year.

     267) Except for the CBP SA and EX-ACT, all the results generated by the tools were situated
        within this range. However, the results generated by the CCAFS-MOT, CFT, AFOLU Carb,
        and AFD-CFT tools are underestimated and do not reflect all the improved management
        options expressed within the project document. For instance, using the CCAFS-MOT, we
        assume that the entire area of annual crops will be subject to improvement by stopping
        residue burning and incorporating zero tillage, while the project suggests that the annual
        crops improvements are improved agronomic practices, no tillage, water management, and
        manure application. Furthermore, the CCAFS-MOT and CFT tools do not provide a
        comparison of with and without the project scenario and do not account for the gain-loss
        and stock difference methods. The estimated carbon balance using the two tools (CCAFS-
        MOT and CFT tools) was calculated separately (without and with the project scenarios) for
        the sake of comparison. As for the AFOLU Carb tool, it considers only two improvements,
        the tillage (full, reduced, and no-till) and inputs (low, medium, high with and without
        manure), to describe the improved management options for annual cropland.

     268) The six tools have annual crops as an activity scope and can estimate the mitigation
        potential of this activity. However, due to the abovementioned limitations, the use of the
        AFD-CFT, AFOLU Carb, CCAFS-MOT, and CFT tools is not recommended. The
        difference in results between the EX-ACT and CBP tools is high (30 percent).



24
  The CBP and AFD tools default values should be replaced with corresponding carbon stock values for degraded
land based on the IPCC methodology.



                                                                                                          87
     269) Based on this analysis, the EX-ACT and CBP are suitable for annual crops GHG analysis
        when considering improved practices scenarios.


5.14.1.3 Livestock

     270) Based on the sources, sinks, and SLM activities accounted for by the tools, five tools
        (EX-ACT, CBP, CCAFS-MOT, AFOLU Carb, and CFT) were used to analyze livestock
        management activities (see Table 9). The activity consists of improving the management
        practices of livestock. Because the analysis was conducted following the Tier 1
        methodology, the default coefficients generated by the tools were used. However, as the
        analysis required more technical mitigation options, 25 only the EX-ACT and AFOLU Carb
        tools were able to generate an estimate of the total carbon balance for the livestock
        activities. The AFOLU Carb and CBP SA tools consider the number of livestock without
        any technical mitigation options, therefore, the carbon balance is 0 tCO 2 eq. The CBP DA
        tool does allow the user to input their own factors associated with technical mitigation
        options, but the DA was not used in this analysis. The CFT also has a few limiting factors,
        including no opportunity for the user to insert Tier 2 values and to compare with and
        without project scenarios. However, the CFT and CCAFS-MOT tools do provide the user
        with options on feeding practices, manure management, and energy consumption.

     271) Based on this analysis, the analysis found that the EX-ACT tool is the most suitable for
        livestock GHG analysis when considering technical mitigation options (feeding practices,
        specific agents, and breeding practices) and the CBP DA can also be used if the user has
        their own EF data. 26

5.15 Serbia, Contribution of Sustainable Forest Management to a Low Emission and
Resilient Development Project

     272) The project aims to promote SFM practices among the actors of the public and private
        sector, strengthening their capacities of mainstreaming biodiversity conservation and
        management of carbon stocks into forest management planning and implementation. The
        project components are the following:
       • Component 1: Enabling environment for multifunctional sustainable forest management
       • Component 2: Multifunctional forest management
       • Component 3: Monitoring, evaluation, and lessons dissemination

25
   Methane emissions are affected by a number of factors including the animal traits (for example, age, bodyweight,
and genetics) and environmental parameters (for example, temperature) but also feed quality. Therefore, mitigation
options would have to address those last drivers. Smith et al. (2008) reviewed the mitigation potentials linked mostly
with animal and feed factors and reported that they could be categorized more precisely into improved feeding
practices, use of specific agents or dietary additives, and longer-term management changes and animal breeding.
26
   For users who wish to use detailed Tier 2 (for example, refined EFs on enteric fermentation) a link is provided by
the EX-ACT tool to the FAO GLEAM-I tool.



                                                                                                                   88
 273) Based on the scope and applicability of the tools, the activities in Component 2 were
    assessed. The results of the carbon balance obtained by the tools are summarized in Figure
    16. The analyses focus on increasing forest area under sustainable and multifunctional
    forest management to enhance carbon sequestration.
Figure 16: Carbon balance per component and per tool (Contribution of Sustainable Forest Management to a
                            Low Emission and Resilient Development, Serbia)
      40,000
      20,000
            0
                  EX-ACT     CBP       AFOLU Carb      AFD CFT      CAT-AR       CCAFS     CFT
     -20,000
     -40,000
     -60,000
     -80,000
    -100,000
    -120,000

    tCO2eq/year                Degradation and Management (forest degradation)
                               Land Use Changes (Deforestation)
                               Land Use Changes (Afforestation)



 274) The analysis considers a set of information determined as the minimum information
    required to carry out a GHG analysis as follows:
      • Country/continental region: Serbia/Western Europe
      • Climate and moisture regime: Warm temperate moist
      • Dominant regional soil type: Low activity clay soils
      • Duration of the project implementation: 4 years and duration of analysis set to 20
          years

 275) While some calculations might not require all the above information, others might also
    require the moisture regime and the MAT.

5.15.1 Detailed project analysis per activity for the Serbia Contribution of Sustainable Forest
Management to a Low Emission and Resilient Development Project

5.15.1.1 Afforestation/reforestation (ILU: grassland, set aside land, and degraded land)

 276) Based on the sources, sinks, and SLM activities accounted for by the tools, five tools
    (EX-ACT, CBP SA, AFOLU Carb, AFD-CFT, and CAT-AR) were used to analyze the
    afforestation activities (see Table 9). Because the analysis was conducted following the
    Tier 1 methodology, the default coefficients generated by the tools were used. The standard
    deviation is estimated at 22,519 tCO 2 eq per year and the mean at −56,868.6 tCO 2 eq per


                                                                                                     89
     year with a significance level of 0.05 (CI = 95 percent, 1.960 standard error of the mean).
     Therefore, the range of results for afforestation activities should be between −37,129 and
     −76,607 tCO 2 eq per year.

 277) Except for the AFOLU Carb tool, all the results generated by the tools were situated
    within this estimated range. This is explained by the fact that the AFOLU Carb does not
    account for the gain-loss and stock difference methods and therefore, does not compute
    emissions or removals as the change over time of carbon stocks for the different pools
    (Table 8). The difference in results between the EX-ACT, CBP, AFD-CFT, and CAT-AR
    tools varies: EX-ACT and CBP have a 5.35 percent difference, EX-ACT and AFD-CFT a
    10 percent difference, EX-ACT and CAT-AR a 28 percent difference, CBP and AFD-CFT
    a 37 percent difference, CBP and CAT-AR a 54 percent difference, and AFD-CFT and
    CAT-AR a 17 percent difference. It is recommended to use the CBP DA to replace the
    grassland EFs by the corresponding values for the set aside and degraded land.

 278) Based on this analysis, the four tools—CAT-AR, EX-ACT, CBP, and AFD-CFT—are
    suitable for afforestation GHG analysis when considering grassland as ILU. The CAT-AR,
    EX-ACT, and AFD-CFT for afforestation GHG analysis when considering set aside land as
    ILU. The EX-ACT for afforestation GHG analysis when considering degraded land as ILU.

5.15.1.2Deforestation (FLU: set aside land)

 279) Based on the sources, sinks, and SLM activities accounted for by the tools, three tools
    (EX-ACT, CBP SA, and AFOLU Carb) were used to analyze deforestation activities (see
    Table 9). Because the analysis was conducted following the Tier 1 methodology, the
    default coefficients generated by the tools were used. The standard deviation is estimated at
    7,684 tCO 2 eq per year and the mean at −19,835 tCO 2 eq per year with a significance level
    of 0.05 (CI = 95 percent, 1.960 standard error of the mean). Therefore, the range of results
    for deforestation activities should be between 12,304 and 27,366 tCO 2 eq per year.

 280) All the tools provided results within this calculated range. The AFOLU Carb provides
    a value further away from the mean value. This is explained by the fact that the AFOLU
    Carb does not apply the gain-loss and stock difference methods, and therefore, does not
    compute emissions or removals as the change over time of carbon stocks for the different
    pools (Table 8).

 281) Based on this analysis, the difference in results between tools is minor and could be
    explained by the fact that different IPCC GHG accounting approaches and carbon pools
    apply for the tools. Using the Tier 2 methodology/coefficients instead of the Tier 1 could
    further decrease the difference. The difference in results between the EX-ACT, CBP, and
    AFOLU Carb tools varies: EX-ACT and CBP have a 33 percent difference, EX-ACT and
    AFOLU Carb a 36 percent difference, and CBP and AFOLU Carb a 67 percent difference.



                                                                                              90
     282) Based on this analysis, the two tools—EX-ACT and AFOLU Carb—are suitable for
        deforestation GHG analysis when considering set aside land as the FLU. 27

5.15.1.3 Forest management and degradation

     283) Based on the sources, sinks, and SLM activities accounted for by the tools, three tools
        (EX-ACT, CBP, and AFOLU Carb) were used to analyze forest degradation activities (see
        Table 9). Because the analysis was conducted following the Tier 1 methodology, the
        default coefficients generated by the tools were used. The difference in results between the
        tools is minor (8 percent).

     284) Based on this analysis, the EX-ACT and CBP tools are suitable for forest management
        GHG analysis.

5.15.2 Project carbon balance

     285) For the overall project results, the CBP and EX-ACT tools cover all project activities.
        The tools provide close results (0.02 tCO 2 eq per hectare per year). The uncertainty level
        for the CBP tool equals 26 percent, while the EX-ACT results are accompanied by an
        uncertainty level of 39 percent.

5.16 Turkey, Sustainable land Management and Climate-Friendly Agriculture

     286) The project objective is to improve sustainability of agriculture and forest land use
        management through the diffusion and adoption of low-carbon technologies with win-win
        benefits in land degradation, climate change, and biodiversity conservation and increase
        farm profitability and forest productivity. The project has three components:
          • Component 1: Rehabilitation of Degraded Forest and Rangeland
          • Component 2: Climate-Smart Agriculture
          • Component 3: Enhanced enabling environment for sustainable land management

     287) Based on the scope and applicability of the tools, the activities in Components 1 and 2
        were assessed. The results of the carbon balance obtained by the tools are summarized in
        Figure 17. The analyses focus on rehabilitating degraded forest and rangelands and
        improving management practices and climate-smart agriculture techniques applied across
        productive landscapes.




27
  The CBP DA could be used by replacing the severely degraded grassland carbon stock values with corresponding
values for set aside land based on the IPCC methodology.



                                                                                                            91
Figure 17: Carbon balance per component and per tool (Sustainable land Management and Climate-Friendly
                                         Agriculture, Turkey)
                   0
                        EX-ACT      CBP       AFOLU     AFD CFT    CAT-AR     CCAFS   CFT
                                               Carb
              -50,000


             -100,000


             -150,000


             -200,000


             -250,000

              tCO2eq/year        Grassland and Livestock (Grassland management)
                                 Degradation and Management (forest degradation)
                                 Agriculture (Annual)



 288) The analysis considers a set of information determined as the minimum information
    required to carry out a GHG analysis as follows:
      • Country/continental region: Turkey/Asia continental
      • Climate and moisture regime: Warm temperate dry
      • Dominant regional soil type: High activity clay soils
      • Duration of the project implementation: 5 years and duration of analysis set to 20
          years

 289) While some calculations might not require all the above information, others might also
    require the moisture regime and the MAT.

5.16.1 Detailed project analysis per activity for the Turkey Sustainable Land Management and
Climate-Friendly Agriculture Project

5.16.1.1 Annual cropland improvement

 290) Based on the sources, sinks, and SLM activities accounted for by the tools, six tools (EX-
    ACT, CBP SA, AFD-CFT, AFOLU Carb, CCAFS-MOT, and CFT) were used to analyze
    annual cropland activities (see Table 9). The activity consists of improving the
    management practices of annual crops. Because the analysis was conducted following the
    Tier 1 methodology, the default coefficients generated by the tools were used. The standard
    deviation is estimated at 21,293 tCO 2 eq per year and the mean at −36,711.5 tCO 2 eq per
    year with a significance level of 0.05 (CI = 95 percent, 1.960 standard error of the mean).
    Therefore, the range of results for annual cropland activities should be between −19,673
    and −53,749 tCO 2 eq per year.



                                                                                                    92
 291) Except for the CBP SA and EX-ACT tools, all the tools generated results within this
    estimated range. However, the results generated by the CCAFS-MOT, CFT, AFOLU Carb,
    and AFD-CFT tools are underestimated and do not reflect all the improved management
    options expressed within the project document. For instance, using the CCAFS-MOT, we
    assume that the entire area of annual crops will be subject to improvement by stopping the
    residue burning and incorporating zero tillage, while the project suggests that the annual
    crops improvements are improved agronomic practices, no tillage, and manure application.
    Further, the CCAFS-MOT and CFT tools are not based on gain-loss and stock difference
    methods. The estimated carbon balance using the two tools (CCAFS-MOT and CFT) was
    calculated separately (without and with the project scenarios) for the sake of comparison.
    As for the AFOLU Carb tool, it considers only two improvements, the tillage (full, reduced,
    and no-till) and inputs (low, medium, high with and without manure), to describe the
    improved management options for annual cropland.

 292) The six tools have annual crops as an activity scope and can estimate the mitigation
    potential of this activity. However, due to the abovementioned limitations, the use of the
    AFD-CFT, AFOLU Carb, CCAFS-MOT, and CFT tools is not recommended. The
    difference in results between the EX-ACT and CBP tools is minor (8 percent). Based on
    this analysis, the two tools—EX-ACT and CBP—are suitable for annual crops GHG
    analysis when considering improved practices scenario.

5.16.1.2 Forest management and degradation

 293) Based on the sources, sinks, and SLM activities accounted for by the tools, two tools
    (EX-ACT and CBP SA) were used to analyze forest degradation activities (see Table 9).
    Because the analysis was conducted following the Tier 1 methodology, the default
    coefficients provided by the tools were used. The AFOLU Carb tool is not included within
    the analysis; although it considers forest protection activities, it does not consider the
    biomass losses that are not due to deforestation or illegal logging. The difference in results
    between the EX-ACT and CBP tools is high (30 percent). Based on this analysis, the EX-
    ACT and CBP tools are suitable for forest management GHG analysis.

5.16.1.3 Grassland management

 294) Based on the sources, sinks, and SLM activities accounted for by the tools, four tools
    (EX-ACT, CBP SA, AFOLU Carb, and AFD-CFT) were used to analyze grassland
    management activities (see Table 9). Because the analysis was conducted following the
    Tier 1 methodology, the default coefficients provided by the tools were used. The mean
    and standard deviation are respectively −109,991.5 tCO 2 eq per year and 11,669 tCO 2 eq per
    year with the 95 percent confidence interval of the mean between −98,555 and −121,427
    tCO 2 eq per year.




                                                                                               93
     295) All the results generated by the tools were situated within this estimated range. The
        differences in the results provided by the tools are mainly due to the different EFs and
        carbon stock change values associated with the Tier 1 methodology. The AFD-CFT tool,
        for example, calculated the default soil carbon stock changes based on a set of IPCC
        questions, whereas the AFOLU Carb provided estimated values for relative stock change
        factors instead.

     296) The differences in results between the tools varies: EX-ACT and CBP have a 13 percent
        difference, EX-ACT and AFD-CFT a 6 percent difference, EX-ACT and AFOLU Carb a
        15 percent difference, CBP and AFD-CFT a 19 percent difference, CBP and AFOLU Carb
        a 3 percent difference, and AFD-CFT and AFOLU Carb a 22 percent difference.

     297) Based on this analysis, the four tools—EX-ACT, CBP, AFOLU Carb, and AFD-CFT—
        are suitable for grassland management GHG analysis with the Tier 1 methodology. 28

5.16.2 Project carbon balance

     298) For the overall project results, the CBP and EX-ACT cover all project activities. The
        tools generated close results (0.3 tCO 2 eq per hectare per year) with an uncertainty level
        estimated at 19 percent for the CBP tool and 47 percent for the EX-ACT tool.

5.17 Chile, Sustainable Land Management Project

     299) The project's Global Environment Objective (GEO) is to develop a national framework
        for SLM to combat land degradation, mainstream biodiversity into national policies, and
        protect forest carbon assets. The main project beneficiaries will be (a) the rural poor,
        including indigenous communities, whose lands are degraded or threatened and can benefit
        from improvements in soil conservation and improved sustainability of production systems;
        (b) private sector producers; (c) civil society benefitting from an improved landscape that
        incorporates water, soil, biodiversity, carbon, and other intangibles as values; and (d) native
        biodiversity in global priority hotspots.

     300) The executing agency is the Chilean National Forestry Corporation (CONAF), which will
        also manage procurement and share responsibility for financial management. The land area
        targeted, where SLM practices will be applied to reduce land degradation, is about 100,000
        ha. This includes 25,000 ha of new sites managed outside protected areas, 3,464 ha of
        restored/afforested areas, and 57,250 ha of forest areas brought under forest management
        plans.

     301) The National SLM framework approach will be piloted in four geographic regions that
        are globally and nationally recognized as priority areas for conservation, including: (a) the
28
     The specific value suitable for organic carbon present in soils should be provided for the AFOLU Carb.



                                                                                                              94
     Central Andean Dry Puna, (b) the Chilean Mattorral, (c) the Winter Rainfall Forest -
     Valdivian Temperate Rainforest, and (d) the Patagonian Andes Nothofagus forests and
     steppe. A total of five strategic pilot areas, were identified during preparation, one in each
     of the ecological regions, except for the Chilean Mattoral region, which has two sites. SLM
     will be carried out on intervention area through subprojects on individual or community
     landholdings in cooperation and agreement with producers in the five pilot areas.

5.17.1 Key project activities acting on GHG

 302) Based on the scope and applicability of the tools, afforestation, forest management, and
    grassland management activities were assessed on a total area of 123,095 ha. The results of
    the carbon balance obtained by the tools are summarized in Figure 18. The project area is
    subject to the improvement of land management practices, forest restoration and
    afforestation, and forest areas brought under forest management plans. The project targets
    four regions in Chile.

5.17.1.1 Aysen Cohaique site

 303) Without the project implementation, (a) 6 ha of degraded land would remain degraded
    and none of the afforestation activities would take place; (b) 130 ha of subtropical humid
    forest would remain in a state like the initial state of degradation, that is, moderately
    degraded; and (c) 4 ha of grassland would remain moderately degraded.

 304) With the project implementation, the afforestation/restoration activities will take place
    and the degraded area will be replaced with 6 ha of temperate continental forest, and 130 ha
    of the woodland will be improved from 40 percent biomass lost to 10 percent biomass lost.
    The forest management scenario is accompanied by an improvement of grassland
    management practices on 4 ha. The forest characteristics in the intervention areas are
    summarized in Tables 16 and 17.

        Table 16: Temperate continental forest carbon sequestration potential within the biomass
Growth rates for systems up to 20 years (tC/ha/year) Growth rates for systems after 20 years (tC/ha/year)
    Above-ground                 Below-ground            Above-ground                 Below-ground
         5.25                         1.52                    5.25                         1.52

       Table 17: Woodland forest carbon sequestration potential within the biomass and dead wood
      Above-ground (tC/ha)                   Below-ground (tC/ha)                Dead wood (tC/ha)
               115.6                                  33.5                               8.3

5.17.1.2 Combarbalá site

 305) Without the project implementation, (a) 30 ha of degraded grassland would remain
    degraded and none of the afforestation activities would take place, (b) 60 ha of severely
    degraded grassland would remain severely degraded, and (c) 130 ha of subtropical steppe
    forest would pass from 40 percent biomass lost to 60 percent biomass lost.

                                                                                                       95
 306) With the project implementation, the afforestation/restoration activities will take place,
    the degraded grassland area will be replaced by 30 ha of subtropical steppe forest, and 200
    ha of subtropical steppe forest will pass from 40 percent biomass lost to 20 percent biomass
    lost. The forest management scenario is accompanied by an improvement of grassland
    management practices on 60 ha. The forest characteristics in the intervention areas are
    summarized in Tables 18 and 19.

          Table 18: Subtropical steppe forest carbon sequestration potential within the biomass
Growth rates for systems up to 20 years (tC/ha/year)  Growth rates for systems after 20 years (tC/ha/year)
    Above-ground                 Below-ground             Above-ground                 Below-ground
          1.9                         0.56                      1.9                         0.56

               Table 19: Subtropical steppe forest carbon sequestration within the biomass
               Above-ground (tC/ha)                                   Below-ground (tC/ha)
                       37.6                                                   10.9

5.17.1.3 Ohiggins - Litueche site

 307) Without the project implementation, (a) 125 ha of degraded land would remain degraded
    and none of the afforestation activities would take place, (b) 20 ha of moderately degraded
    pasture would remain the same as compared to the initial state of degradation, and (c) 550
    ha of subtropical dry forest would pass from 60 percent biomass lost to 80 percent biomass
    lost.

 308) With the project implementation, the afforestation/restoration activities will take place
    and the degraded land area will be replaced with 30 ha of broadleaved forest, and 550 ha of
    subtropical dry forest will be improved from 60 percent biomass lost to 40 percent biomass
    lost. This improved forest management scenario is accompanied by an improvement of
    grassland management practices on 20 ha. The forest characteristics in the intervention
    areas are summarized in Tables 20 and 21.

              Table 20: Broadleaved forest carbon sequestration potential within the biomass
Growth rates for systems up to 20 years (tC/ha/year)  Growth rates for systems after 20 years (tC/ha/year)
    Above-ground                 Below-ground             Above-ground                 Below-ground
          1.9                         0.56                      1.9                        0.56

                 Table 21: Subtropical dry forest carbon sequestration within the biomass
               Above-ground (tC/ha)                                   Below-ground (tC/ha)
                       57.8                                                   16.8

5.17.1.4 Araucania - Los Sauces (previously purto saaverda)

 309) Without the project implementation, none of the afforestation will take place, and the
    235-ha subject to restoration activities will remain degraded land. With the project



                                                                                                        96
      implementation, the afforestation/restoration activities will take place, and thus the
      degraded land area will be replaced with 235 ha of subtropical humid forest. The forest
      characteristics are summarized in Tables 22.

          Table 22: Subtropical humid forest carbon sequestration potential within the biomass
Growth rates for systems up to 20 years (tC/ha/year) Growth rates for systems after 20 years (tC/ha/year)
    Above-ground                 Below-ground            Above-ground                 Below-ground
          5.3                         1.5                      5.3                         1.5


  310) As per the overall project activities, Tables 23 to 25 summarize the main rehabilitated
     forestlands and grasslands.

                 Table 23: Afforestation/reforestation scenarios within the project’s three sites
                              Type of vegetation that                                      Area that will be
           Sites                                             Previous land use
                                 will be afforested                                         afforested (ha)
Aysen Cohaique              Subtropical humid forest      Degraded land                            6
Combarbalá                  Subtropical steppe            Grassland                                30
Ohiggins - Litueche         Subtropical dry forest        Degraded land                           125
Araucania - Los Sauces      Subtropical humid forest      Degraded land                           235
                                                                     Total area (ha)              396

                  Table 24: Forestry rehabilitation scenarios within the project’s three sites
                                                          Degradation level of the vegetation
                                                                 (percent of biomass lost)            Area (ha)
        Sites
                                                                        Without
                            Type of vegetation         Initial state                With project
                                                                        project
Aysen Cohaique         Subtropical humid forest             40             40              10            130
Combarbalá             Subtropical steppe                   40             60              30            220
Ohiggins - Litueche    Subtropical dry forest               60            80              40             550
                                                                                    Total area (ha)      900

                  Table 25: Grassland management scenarios within the project’s three sites
                                      Degradation level of the vegetation                      Area (ha)
Type of vegetation                                                                        Start-Without-
                        Initial state    Without project            With project
                                                                                          With
Aysen Cohaique        Moderate          Moderate             Improved with inputs                  4
Combarbalá            Severe            Severe               Improved without inputs              60
Ohiggins - Litueche   Moderate          Moderate             Improved without inputs              20
                                                                          Total area (ha)         84

The average above-ground biomass of the grassland dominant species is 4.7 tC per ha.

5.17.2 Detailed project analysis per activity for the Chile Sustainable Land Management and
Climate-Friendly Agriculture Project

  311) Based on the scope and applicability of the tools, the activities were assessed. The results
     of the carbon balance obtained by the tools are summarized in Figure 18.




                                                                                                               97
      Figure 18: Carbon balance per component and per tool (Sustainable Land Management Project, Chile)
                     0
                          EX-ACT     CBP     AFOLU Carb AFD CFT       CAT-AR        CCAFS   CFT
                 -2,000
                 -4,000
                 -6,000
                 -8,000
                -10,000
                -12,000
                -14,000
                -16,000

                                   Grassland and Livestock (Grassland management)
                                   Degradation and Management (forest degradation)
                                   Land Use Changes (Afforestation)


5.17.2.1 Afforestation activities (ILU: degraded land and grassland)

     312) Based on the sources, sinks, and SLM activities accounted for by the tools, five tools
        (CAT-AR, CBP SA, AFD-CFT, AFOLU Carb, and EX-ACT) were used to analyze
        afforestation activities (see Table 9). The activity analysis was conducted following the
        Tier 2 methodology; therefore, default coefficients were replaced with country-/region-
        specific coefficients. The mean and standard deviation are respectively −9,864.2 tCO 2 eq
        per year and 1,366 tCO 2 eq per year, with 95 percent confidence interval between –8,666
        and –11,062 tCO 2 eq per year.

     313) Except for the AFOLU Carb, all the results generated by the tools were situated within
        this range. This is explained by the fact that the AFOLU Carb does not apply the gain-loss
        and stock difference methods (Table 8), and therefore, does not compute emissions or
        removals as the change over time of carbon stocks for the different pools. The difference in
        results between the EX-ACT, CBP, AFD-CFT, and CAT-AR tools is minor: EX-ACT and
        CBP have a 1.5 percent difference, EX-ACT and AFD-CFT a 3 percent difference, EX-
        ACT and CAT-AR a 0.34 percent difference, CBP and AFD-CFT a 1.4 percent difference,
        CBP and CAT-AR a 1.4 percent difference, and AFD-CFT and CAT-AR a 2 percent
        difference.

     314) Based on this analysis, the four tools—CAT-AR, CBP, AFD-CFT, and EX-ACT—are
        suitable for afforestation GHG analysis when considering grassland as ILUs. 29 While the
        EX-ACT is suitable when considering degraded land as the ILU.


29
     The use of CBP DA assessment is recommended.



                                                                                                          98
5.17.2.2 Grassland management

     315) Based on the sources, sinks, and SLM activities accounted for by the tools, four tools
        (EX-ACT, AFOLU Carb, CBP SA, and EX-ACT) were used to analyze grassland
        management activities (see Table 9). The activity analysis was conducted following the
        Tier 2 methodology; therefore, default coefficients were replaced with country-/region-
        specific coefficients. The standard deviation is estimated at 13.6 tCO 2 eq per year and the
        mean at −220.25 tCO 2 eq per year with a significance level of 0.05 (CI = 95 percent, 1.960
        standard error of the mean). Therefore, the range of results for grassland management
        activities should be between −208 and −233 tCO 2 eq per year.

     316) A minor difference was observed within the results. The difference in the results
        generated by the tools was mainly due to the use of different IPCC GHG accounting
        approaches and carbon pools (Table 8). For example, the AFD-CFT tool calculates the
        default soil carbon stock changes based on a set of IPCC questions, whereas the AFOLU
        Carb provides estimated values for relative stock change factors.

     317) The difference in results between the tools are minor: EX-ACT and CBP have a 7 percent
        difference, EX-ACT and AFD-CFT a 11 percent difference, EX-ACT and AFOLU Carb a
        6 percent difference, CBP and AFD-CFT a 3 percent difference, CBP and AFOLU Carb a
        0.9 percent difference, and AFD-CFT and AFOLU Carb a 4 percent difference.

     318) Based on this analysis, the four tools—EX-ACT, CBP, AFD-CFT, and AFOLU Carb—
        are suitable for grassland management GHG analysis using a Tier 2 methodology. 30

5.17.2.3 Forest management and degradation

     319) Based on the sources, sinks, and SLM activities accounted for by the tools, two tools
        (EX-ACT and the CBP SA) were used to analyze forest management activities (see Table
        9). The activity analysis was conducted following the Tier 2 methodology; therefore,
        default coefficients were replaced with country-/region-specific coefficients. The AFOLU
        Carb tool is not considered within the analysis; although it considers forest protection
        activities, it does not consider the biomass losses that are not due to deforestation or illegal
        logging. On the impact of forest management and degradation, only the CBP and EX-ACT
        tools allow for the use of Tier 2 coefficients to describe the states of degradation. The
        difference in results between the EX-ACT and CBP tools is minor (0.65 percent). Based on
        this analysis, the EX-ACT and CBP tools are suitable for forest management GHG analysis.



30
  The specific values for the soil carbon sequestration were not modified, which explains the small variability
within the results.



                                                                                                                  99
5.17.3 Project carbon balance

 320) Based on the sources, sinks, and SLM activities accounted for by the tools, two tools
    (EX-ACT and CBP) were capable of analyzing the overall project activities (see Table 9).
    The following paragraphs focus on a detailed description of the results obtained using tools
    that allow an estimate of the overall project activities results in terms of GHG emissions.

5.17.3.1 EX-ACT analysis

 321) The project carbon balance presented in this section was assessed with the EX-ACT tool
    to provide a detailed GHG results distribution between all activities affected by the project.
    It provides results both for the 20 years duration of a typical project GHG appraisal and per
    year. The results per ha are also included.

 322) Baseline EX-ACT Assumptions. The EX-ACT analysis takes into account the specific
    environmental features (soil and climate types) of each case study. Soil and climate
    information is needed to determine the coefficients used in the analysis. Average climates
    considered in the analysis are warm temperate. The moisture regime was classified as dry,
    and the dominant soil type was classified as high activity clay. The implementation phase
    of the SLM project was specified as 2 years, followed by an estimated capitalization phase
    of 18 years.

 323) According to the EX-ACT calculation, the SLM project could have a climate mitigation
    potential of roughly −300 ktCO 2 eq reduced/fixed on 20 years (direct impact), primarily
    through afforestation/reforestation activities (−206 ktCO 2 eq) and rehabilitation of degraded
    forests (−90 ktCO 2 eq). This project could fix around 13 tons of CO 2 eq per hectare per year.
    The uncertainty level with the EX-ACT tool is 20 percent.

5.17.3.2 CBP analysis

 324) The project’s carbon balance provided in this section was analyzed with the CBP tool to
    provide a detailed GHG results distribution between all activities affected by the project. It
    provides results for the six years duration of a typical project GHG implementation phase
    and per year.

 325) Baseline CBP Assumptions. The CBP analysis considers specific environmental
    features for the land use climate zones of each case study. The coefficients used in the
    analysis were completed with the Tier 2 values. Because the CBP tool does not consider
    degraded land as a land use category, we consider the ILU as annual cropland with a
    carbon stock of 1 tC per ha and soil carbon stock is set to 12.5 tC per ha.




                                                                                               100
 326) The CBP tool allowed for simultaneous calculations of emissions generated by activities
    (afforestation activities and the forest management and degradation activities) and
    emissions generated by the grassland management.

 327) According to CBP calculations, the SLM project could have a mitigation impact of
    roughly −300 tCO 2 eq reduced/fixed on 20 years (direct impact) or 10.98 tCO 2 eq per
    year per hectare, mostly through afforestation/reforestation activities and the rehabilitation
    of degraded forests. The uncertainty level with the CBP is 19 percent.

5.17.4 Conclusion

 328) The SLM project aims to provide a GHG mitigation impact ranging between −15,010 and
    −15,163.1 tCO 2 eq per year on 1,380 ha (an average of −10.88 and 10.99 tCO 2 eq per year).
 329) On the impact of afforestation and forest and grassland management, only the CBP and
    EX-ACT tools generated results using Tier 2 coefficients, both to characterize the type of
    vegetation and the reduction of standing stock on remaining forests.

 330) At a global level, both the CBP and EX-ACT tools provided relatively close results, with
    roughly a 1.01 percent difference. The EX-ACT had an uncertainty level of 20 percent as
    compared to the CBP’s 26 percent uncertainty level.

5.18 Tunisia, Second Natural Resources Management Project

 331) The project's GEO is to improve the living conditions of rural communities in the project
    areas in terms of access to basic infrastructure and services, sustainably increase income,
    and improve natural resource management practices by fostering an integrated approach to
    community-based development. There are three components to the project.
      • Component 1: Support to Participatory Development Plan (PDP) investments.
          This component will contribute to the project development objective by supporting
          the financing of investments within the PDPs framework, which reflects the priority
          needs of local communities in the project target areas.
      • Component 2: Support to the development of treated wastewater use for
          agriculture. The objective of this component is to support the National Program for
          Wastewater Reuse through the transfer of treated wastewater from the Greater Tunis
          area toward the interior of the country (south of the Tunisian Dorsal). In these areas,
          demand for water is high and treated wastewater will help increase yields on
          agricultural land, reduce fluctuations in agricultural production, and enhance
          adaptation to climate variability and change.
      • Component 3: Institutional strengthening and awareness raising. The objective of
          this component is to support the mainstreaming of the Integrated Participatory
          Approach (IPA) in rural development in the three governorates of Jendouba,
          Kasserine, and Medenine through institutional strengthening and capacity building of
          target groups involved in project implementation. The component will also support


                                                                                              101
              the implementation of a monitoring and evaluation (M&E) system for project
              activities and for safeguards and communication and sensitization on SLM and
              environmental issues.

5.18.1 Key project activities acting on GHG

     332) Based on the scope and applicability of the tools, crops management, grassland
        management, livestock, and creation of rural tracks and irrigation infrastructures activities
        were assessed on a total area of 21,877.5 ha. The implementation phase is seven years. The
        project area is subject to the improvement of land management practices, forest restoration
        and afforestation, and forest areas brought under forest management plans. The project
        targets three regions in Tunisia.

5.18.1.1 Médenine sites

Afforestation activities

     333) The project aims at developing beekeeping activities by distributing more than 20,000
        hives and combating desertification by planting honey-bearing trees mainly Eucalyptus
        camaldulensis. Without the project implementation, 53 ha of afforestation will take place.
        With the project implementation, the afforestation/restoration activities will take place on
        90 ha. Thus, the degraded land area will be replaced with 47 ha of forest. The forest
        characteristics are summarized in Table 26.

         Table 26: Afforestation activities PRGN2 project-species above-ground net volume growth
                                                 Wood          Above-ground net      Above-ground net
                     Biomass expansion                 32                     33
     Species                                   density    t     volume growth          volume growth
                           factor 31
                                                dm/m3              m3/ha/year           t dm/ha/year
Eucalyptus
                             1.30                0.40                22.50                  11.7
camaldulensis

Grassland management

     334) About 750 ha of grassland in Médenine sites are described as severely degraded. Without
        the project implementation, no further improvements are observed as compared to the
        initial state of degradation. With the project implementation, 750 ha of grassland would be
        subject to improved management practices without input use. The main dominant species is
        Sulla (Hedysarum coronarium). The grassland management is summarized in Table 27.




31
   Temperate Conifers: Spruce-fir, see IPCC GPG-LULUCF Table 3A.1.10.
32
   See IPCC 2006 Guidelines, V4. Table 4.13.
33
   See IPCC 2006 Guidelines, V4. Table 4.11A.



                                                                                                        102
                            Table 27: Grassland management activities, Médenine
                Grazing     Area    State of the grassland at  Future state of the          Above-ground
     Sites
                species     (ha)          project start             grassland             biomass (tdm/ha) 34
C.R.D.A                                                       Improved without
              Sulla         750 Severely degraded                                                6.59
Médenine                                                      inputs
Annual crops

     335) With the project implementation, 3,051 ha of annual crops will be managed, improved,
        and developed. The annual cropland activities target both annual full field and greenhouse
        crops, both irrigated and non-irrigated crops. About 3,750 ha of annual crops are managed
        with improved agricultural management practices, improved seeds and varieties, crop
        rotation, nutrient management, and no tillage residue retention. No improved management
        practices would be carried out without the project implementation and the crop residues
        would continue to be burnt. The targeted areas are as follows:

                  Table 28: Annual crops development and improvement activities, Médenine
     Type of annual vegetation system     Area (ha)           Previous Land Use                   Practices
                                         Irrigated                     400 ha                  Degraded land
Development of annual crops full field                             200 ha legumes              Set aside
                                         Non-irrigated
                                                           200 ha cereals: wheat and barley    Set aside
                                         Tomato                         1.5 ha                 Degraded land
Development of annual crops in           Pepper                          1 ha                  Degraded land
greenhouses                              Cucumber                       1.5 ha                 Degraded land
                                         Melon                          0.5 ha                 Degraded land

                                         Irrigated                    1,250 ha                 Annual crops
Improved existing annual crops
(tomato, pepper, cucumber, and melon)
                                         Non-irrigated                1,000 ha                 Annual crops



Perennial crops

     336) To improve the livelihoods of local households, the project plans on planting tree crops
        on a total area of 10,200 ha of set aside land through an agroforestry approach in Médenine
        sites. In addition, the project aims to improve the management practices on 1,530 ha of
        land (1,500 ha of olives and 30 ha of orchards) through improved nutrient management.
        Without the project implementation, no plantation and improvement practices would take
        place. The perennial trees characteristics are summarized in Table 29.



34
  Diversités phénotypique et moléculaire des micro-symbiotes du Sulla du nord (Hédysarum Coronarium L.) et
sélection de souches rhizobiales efficientes“. SD Fitouri.



                                                                                                             103
                    Table 29: Growth rates for olives and orchards up to 20 years (tC/ha/year)
                                                     Growth rates for perennial systems (tC/ha/year)
            Perennial trees
                                                      Above-ground                       Below-ground
Olives (Proietti et al. 2016)                             3.33                                 0.87
Orchards (Scandellari et al. 2017)                        2.45                                 1.10




5.18.1.2 C.R.D.A Kasserine

Grassland management development

     337) The development of new pasture areas within private courses is one of the targeted
        project activities. With the project implementation, 442 ha of alfa (Stipa tenacissima),
        wormwood (Artemisia vulgaris), and rosemary (Rosmarinus officinalis) species would be
        planted on set aside land. The assumption is made that those species have on average an
        above-ground biomass similar to the Sulla species, 1.9 tC per ha.

Perennial crops development and improvements

     338) To improve the livelihoods of local households, the project plans on planting olive trees
        (2,200 ha) and orchards (95 ha) on a total area of 2,295 ha of set aside land through an
        agroforestry approach. Without the project implementation, no trees will be planted. The
        weighted average above-ground biomass growth is 3.24 tC per ha per year and 0.89 tC per
        ha per year for the below-ground biomass.

5.18.1.3 C.R.D.A Jendouba

Grassland management and development

     339) The project aims to develop new pasture areas in both forest and private courses. With
        the project implementation, 40 ha of sulla (Hedysarum coronarium) species would be
        planted on set aside land (forest courses) and 2,000 ha on private courses on set aside land
        and degraded land. Without the project implementation, no new pasture area would be
        developed. The default values are used to describe the grassland species characteristics in
        warm temperate region. 35

Perennial crops development and improvement



35
     See IPCC 2006 Guidelines, Chapter 6 Grassland.



                                                                                                        104
  340) The project intends to plant olive trees (1,500 ha) and grenadier trees (26 ha) on a total
     area of 1,526 ha of set aside land. Without the project implementation, no trees will be
     planted.

Livestock activities: C.R.D.A Médenine, Kasserine, and Jendouba

  341) With the project implementation, 164,103 heads of sheep and goats would be distributed
     in the three targeted areas. The project also targets the improvement of the breeding
     practices and the enhancement of veterinary monitoring. The livestock activities are
     summarized in Table 30.

                         Table 30: Livestock management activities for the three sites
                              C.R.D.A                 C.R.D.A                    C.R.D.A
                             Médenine                Kasserine                  Jendouba                Total
     Type of                                                Future
                                   Future with                                         Future with
    livestock          Start                      Start      with          Start                      With the
                                     project                                             project
                                                            project                                   project
                         Number of heads          Number of heads           Number of heads
Sheep                 45,000         51,700      40,320     42,420          —              —           94,120
Goats                 45,000         51,750      17,280     18,180          30             53          69,983
                            Improvements breeding practices and feeding practices
Sheep                60 percent    100 percent     —          —         60 percent     100 percent

Inputs and investments: C.R.D.A Médenine, Kasserine, and Jendouba

  342) With the project implementation, a total area of 2,976 ha will be rehabilitated through
     improved water management practices and will benefit from the installation of 2,894 ha of
     trickle irrigation, a sprinkler system on 82 ha and the installation of 40 irrigation basins
     equivalent to 62,400 m2 of agricultural building (concrete). Without the project
     implementation, no additional irrigation system would be installed. With the project
     implementation, 167.4 km of rural roads for medium traffic (asphalt) would be
     rehabilitated.

                             Table 31: Infrastructures development PRNG2 project
                                        Achievements                      Type of irrigation
                                                                            infrastructure
   Activities           C.R.D.A            C.R.D.A           C.R.D.A                                  Total
                                                                               installed
                       Médenine           Jendouba           Kasserine   (sprinkler, drip ...)
                          11 ha             187 ha            2,696 ha   Trickle                     2,894 ha
                          57 ha              25 ha               —       Solid roll sprinkle          82 ha
                    Private
Irrigated areas
                    equipment by                                         Irrigation basin (30
                                              —                  —                                   1,200 m3
                    water basins: 40                                     m3)
                    Units
Creation of rural
                         51 km            61.8 km            54.6 km       Asphalting tracks         167.4 km
tracks

Fertilizer use



                                                                                                              105
 343) In contrast to the project activities, it was identified that fertilizers would be applied to
    achieve the desired productivity targets. Thus, the yearly quantities used, with the project
    implementation, are 70,172.5 kg of Nitrogen (N), 185,985 kg of phosphorus (P 2 O 5 ), and
    173,470 kg of potassium (K 2 O). The manure application is 47,592.5 tons. Without the
    project implementation, no fertilizers would be used (Table 33).



5.18.2 Detailed project analysis per activity for the Tunisia GEF Second Natural Resources
Management Project

 344) Based on the scope and applicability of the tools, the activities were assessed. The results
    of the carbon balance obtained by the tools are summarized Figure 19.

 Figure 19: Carbon balance per component and per tool (Second Natural Resources Management, Tunisia)

  50,000



       0
             EX-ACT        CBP          AFOLU Carb         AFD CFT          CAT-AR            CCAFS   CFT


  -50,000



 -100,000



 -150,000



 -200,000



 -250,000                Inputs & Investments (Fertlizer, irrigation and agricultral buildings)
                         Livestock
                         Grassland (Grassland management)
                         Agriculture (Perennial)
                         Agriculture (Annual)
                         Land Use Changes (Afforestation)


5.18.2.1 Afforestation activities (ILU: degraded land)



                                                                                                            106
     345) Based on the sources, sinks, and SLM activities accounted for by the tools, five tools
        (CAT-AR, CBP DA, AFD-CFT, AFOLU Carb, and EX-ACT) were used to analyze
        afforestation activities (see Table 9). The activity analysis was conducted following the
        Tier 2 methodology; therefore, default coefficients were replaced with country-/region-
        specific coefficients. The mean and standard deviation are respectively −631.6 tCO 2 eq per
        year and 66 tCO 2 eq per year. The estimated 95 percent confidence interval of the mean is
        between −573 and −689 tCO 2 eq/year.

     346) Except for the AFOLU Carb, all the results generated by the tools were situated within
        this range. This is explained by the fact that the AFOLU tool does not apply the gain-loss
        and stock difference methods (Table 8) and therefore, does not compute emissions or
        removals as the change over time of carbon stocks for the different pools. The difference in
        results between the EX-ACT, CBP, AFD-CFT, and CAT-AR tools is minor: EX-ACT and
        CBP have a 2.4 percent difference, EX-ACT and AFD-CFT a 0.8 percent difference, EX-
        ACT and CAT-AR a 2.9 percent difference, CBP and AFD-CFT a 3 percent difference,
        CBP and CAT-AR a 4 percent difference, and AFD-CFT and CAT-AR a 1 percent
        difference.

     347) Based on this analysis, the four tools—CAT-AR, CBP, AFD-CFT, and EX-ACT—are
        suitable for afforestation GHG analysis when considering degraded land as ILU (degraded
        land). 36

5.18.2.2 Annuals cropland development and improvement

     348) Based on the sources, sinks, and SLM activities accounted for by the tools, six tools (EX-
        ACT, CBP DA, AFD-CFT, AFOLU Carb, CCAFS-MOT, and CFT) were used to analyze
        annual cropland activities. The activity consists of developing annual crops in degraded and
        set aside areas through improved management practices. The activity analysis was
        conducted following the Tier 2 methodology; therefore, default coefficients were replaced
        with country or region-specific coefficients. The mean and standard deviation are
        respectively 833 tCO 2 eq per year and 565.6 tCO 2 eq per year, and the 95 percent
        confidence interval of the mean is between −2,283 and −3,618 tCO 2 eq per year.

     349) Other than the CCAFS-MOT and AFOLU Carb tools, all the results provided by the tools
        were situated within this range. This is explained by the fact that the CCAFS-MOT tool
        does not consider all the land use changes (only forest to grassland, and arable or grassland
        to arable or grassland) and has limited management options. Similarly, the AFOLU Carb
        does not consider all the management practices (only tillage and inputs management) and
        land use changes.



36
     The use of CBP DA assessment is recommended.



                                                                                                 107
 350) For annuals crop development: The difference in results between the EX-ACT, CBP,
    and AFD-CFT tools for annual cropland development are as follows: EX-ACT and CBP
    have a 5 percent difference, EX-ACT and AFD-CFT a 12 percent difference, and CBP and
    AFD-CFT a 14 percent difference. The difference could be explained by the fact that the
    AFD-CFT tool does not consider degraded land as ILU. For the AFD-CFT, the set aside
    land was considered instead to be Cropland - Set aside (<20 years),
    Temperate/Boreal/Tropical, moist/wet.

 351) For annuals crop improvement: The difference in results between the EX-ACT and
    CBP tools is 5 percent.

 352) Based on this analysis, the three tools—EX-ACT, CBP, and AFD-CFT—are suitable for
    annual crops GHG analysis when considering management improvements scenarios, while,
    the two tools—EX-ACT and CBP—are suitable for annual crops GHG analysis when
    considering improved practices scenarios.

5.18.2.3 Perennial cropland development (ILU: set aside)

 353) Based on the sources, sinks, and SLM activities accounted for by the tools—three tools
    (EX-ACT, CBP DA, and AFD-CFT) were used to analyze perennial activities (see Table 9).
    The activity analysis was conducted following the Tier 2 methodology; therefore, default
    coefficients provided by the tools were replaced to describe the baseline and with project
    above-ground growth rate (tC per ha per year) both to characterize the type of vegetation
    and the improvement of the biomass growth. The mean and standard deviation are
    respectively at −180,820 tCO 2 eq per year and 12,789 tCO 2 eq per year. The 95 percent
    confidence interval of the mean is between −166,348 and −195,293 tCO 2 eq per year.

 354) All the results generated by the tools were situated within this range. The EX-ACT, CBP,
    and CAT-AR tools provided similar results: EX-ACT and CBP DA have a 7 percent
    difference, EX-ACT and AFD-CFT a 14 percent difference, and CBP and AFD-CFT a 6
    percent difference.

 355) Based on this analysis, the three tools—EX-ACT, CBP DA, and AFD-CFT—are suitable
    for GHG analysis of perennial cropland development when considering set aside land as
    the ILU and when using Tier 2 methodology.

5.18.2.4 Grassland management and development

 356) Based on the sources, sinks, and SLM activities accounted for by the tools, four tools
    (EX-ACT, AFOLU Carb, CBP SA, and AFD-CFT) were used to analyze grassland
    management and grassland development activities (see Table 9). The activity analysis was
    conducted following the Tier 2 methodology; therefore, the default coefficients were
    replaced with country-/region-specific coefficients. The mean and standard deviation are


                                                                                          108
     respectively −220.25 tCO 2 eq per year and 7,134 tCO 2 eq per year, with the 95 percent
     confidence interval of the mean lying between −6,144 and −20,127 tCO 2 eq per year.

 357) All the results provided by the tools were situated within this range, except for the
    AFOLU Carb. The difference in results between the EX-ACT, CBP, and AFD-CFT tools is
    minor: EX-ACT and CBP have a 3 percent difference, EX-ACT and AFD-CFT a 6 percent
    difference, and CBP and AFD-CFT a 3 percent difference.

  358) Based on this analysis, the three tools—EX-ACT, CBP, and AFD-CFT—are suitable for
      GHG analysis of grassland management and development using Tier 2 methodology.
5.18.2.5 Livestock

 359) Based on the sources, sinks, and SLM activities accounted for by the tools, four tools
    (EX-ACT, CBP, CCAFS-MOT, and CFT) were used to analyze livestock management
    activities (see Table 9). However only two tools, EX-ACT and CBP DA, were able to
    estimate the total carbon balance as the analysis considered Tier 2 values. The AFOLU
    Carb tool does not consider the Tier 2 values for livestock and therefore, the result is zero;
    no difference before and after the project. The CFT does not allow the user to enter Tier 2
    values, and the calculation to compare two situations is not possible. However, both the
    CFT and CCAFS-MOT tools provide the user with options on mitigation options including
    feeding practices, manure management, and energy consumption.
 360) The difference in results between the EX-ACT and CBP DA tools is minor (0.84 percent).
    Based on this analysis, the two tools—EX-ACT and CBP—are suitable for livestock GHG
    analysis using the Tier 2 methodology.

5.18.2.6 Inputs and investments (fertilizers, irrigation, and agricultural buildings)

 361) Based on the sources, sinks, and SLM activities accounted for by the tools, two tools
    (EX-ACT and AFD-CFT) were used to analyze energy consumption (see Table 9). The
    activity analysis was conducted following the Tier 1 methodology; therefore, default
    coefficients provided by the tools were used. There was a minor observable difference
    between the results. The AFD-CFT does not consider irrigation infrastructure and fertilizer
    use. Thus, the EX-ACT tool was the most suitable for GHG analysis of the fertilizers,
    irrigation, and agricultural buildings, while the AFD-CFT estimated only emissions related
    to agricultural building construction.

5.18.3 Project carbon balance

 362) Based on the sources, sinks, and SLM activities accounted for by the tools, only one tool
    (EX-ACT) covered the appropriate areas of GHG appraisal (see Table 9). The following
    paragraphs focus on a detailed description of the results obtained using tools that allow an
    estimate of the overall project activities’ results in terms of GHG emissions.




                                                                                              109
5.18.3.1 EX-ACT analysis

  363) The project carbon balance provided in this section was analyzed with the EX-ACT tool
     to provide a detailed GHG results distribution between all activities affected by the project.
     It provides results both for the whole 20 years duration of a usual project GHG appraisal
     and per year. Results per ha are provided in the following paragraphs.

  364) Baseline EX-ACT Assumptions: The EX-ACT analysis considers the specific
     environmental features (soil and climate types) of each case study. Soil and climate
     information are needed to determine the coefficients used in the analysis. Average climates
     considered in the analysis are warm temperate. The moisture regime was classified as dry,
     and the dominant soil type was classified as high activity clay. The implementation phase
     of second Natural Resources Management Project was specified as 7 years followed by an
     estimated capitalization phase of 13 years.

  365) The Sustainable Land Management Project could have a climate mitigation impact of
     roughly −4,100 ktCO 2 eq reduced/fixed on 20 years (direct impact) mostly through
     perennials development activities (−3,800 ktCO 2 eq) and rehabilitation and development of
     grassland (−300 ktCO 2 eq). This project could fix around 9.5 tons of CO 2 eq per year per
     hectare. The uncertainty level with the EX-ACT tool is 21 percent.

5.18.4 Conclusion

  366) The Second Natural Resources Management project aims to provide a GHG mitigation
     impact of −206,770 tCO 2 eq per year on 21,877.5 hectares. The project, which targets crops
     management, grassland management, livestock, and creation of rural tracks and irrigation
     infrastructures activities, is within the range of a series of SLM projects. At a global level,
     only the EX-ACT tool covers all the project activities, coming in at an uncertainty level of
     about 21.2 percent. Tables 32 to 35 summarize the project activities.

                                        Table 32: Afforestation activities
                                                                                       Afforested area
                                                             ILU
            Type of forest vegetation                                         Without
                                                         (pre-project)                        With project (ha)
                                                                             project (ha)
Eucalyptus gomfocephala and Eucalyptus
                                                       Degraded land             53                   90
camaldulensis

                          Table 33: Grassland management (C.R.D.A Médenine)
                  Grazing        Area      State of the grassland at project              Future state of the
    Sites
                  species        (ha)                    start                                grassland
C.R.D.A
               Sulla              750        Severely degraded                        Improved without inputs
Médenine




                                                                                                                110
                           Table 34: Annuals crops management and development
                                             Previous                                        Average amount of
     Type of annual
                              Area (ha)        Land          Practices                    fertilizer and pesticide
    vegetation system
                                                Use                                             used (kg / ha)
                                                                                        40 t/ha of manure + 50
                                              Degraded     Zero tillage + nutrient
               Irrigated        400 ha                                                  kg/ha of N + 120 kg/ha of
                                              land         management
                                                                                        P 2 O 5 + 120 kg/ha of K 2 O
Annual crops                                               Zero tillage + nutrient
                            200 ha legumes    Set aside                                 1 ton per ha of manure
full field                                                 management
               Not
                            200 ha cereals:
               irrigated
                              wheat and       Set aside    Zero tillage                 —
                                barley
                                                           Improved seeds and           40 t/ha of manure + 50
                                              Degraded
               Tomato           1.5 ha                     varieties + nutrient         kg/ha of N + 120 kg/ha of
                                              land
                                                           management                   P 2 O 5 + 120 kg/ha of K 2 O
                                                           Improved seeds and           25 t/ha of manure + 40
                                              Degraded
               Pepper            1 ha                      varieties + nutrient         kg/ha of N + 110 kg/ha of
Annual crops                                  land
                                                           management                   P 2 O 5 + 100 kg/ha of K 2 O
in
                                                           Improved seeds and           30 t/ha of manure + 30
greenhouses                                   Degraded
               Cucumber         1.5 ha                     varieties + nutrient         kg/ha of N + 100 kg/ha of
                                              land
                                                           management                   P 2 O 5 + 90 kg/ha of K 2 O
                                                           Improved seeds and           25 t/ha of manure + 50
                                              Degraded
               Melon            0.5 ha                     varieties + nutrient         kg/ha of N + 90 kg/ha of
                                              land
                                                           management                   P 2 O 5 + 90 kg/ha of K 2 O
Annual crops                                               Improved seeds and           25 t/ha of manure + 40
                                              Annual
existing and   Irrigated       1,250 ha                    varieties + crop rotation    kg/ha of N + 110 kg/ha of
                                              crops
improved                                                   + nutrient management        P 2 O 5 + 100 kg / ha of K 2 O
(tomato,                                                   No tillage + improved
pepper,        Not                            Annual       agronomic practices
cucumber                       1,000 ha                                                 —
               irrigated                      crops
and melon)
                                                                          47,592.5 t/ha of manure
                                                                          70,172.5 kg/ha of N
Total area                     3,051 ha       Total Fertilizers
                                                                          185,985 kg/ha of P 2 O 5
                                                                          173,470 kg/ha of K 2 O

                         Table 35: Perennial crops management and development
      Sites           Type of perennial vegetation system    Previous Land Use                     Area (ha)
                   Improved tree crops      Olives          —                                        1,500
                                            Grenadiers      —                                         30
C.R.D.A
                                            Olives          Grassland                               10,000
Médenine           Newly planted tree
                                            200 ha: almond                                      200 ha: almond
                   crops                                    Grassland
                                            and fig tree                                          and fig tree
                   Improved tree crops
                                            —               —                                          —
C.R.D.A
Jendouba           Newly planted tree         Olives               Set aside                         1,500
                   crops                      Grenadiers           Annual crops                       26
                   Improved tree crops        —                    —                                  —
C.R.D.A                                       Olives               Set aside                         2,200
                   Newly planted tree
Kasserine                                     Apple tree           Set aside                          45
                   crops
                                              Almond               Set aside                          50
                                                           Total                       15,551 ha




                                                                                                                 111
112
6. Discussion: Overall performance of the suitable tools
 367) This study compares GHG Accounting Tools for SLM. It examines the tools’
    performance, GHG coverage, suitability per SLM activities, and comparability of results.
    To confirm, reduce, or eliminate the tools activities scope, mapping the tools within the
    wide range of potential carbon sequestration and GHG emission reduction activities is
    crucial. Critical variables identified contributed to conclusions on the relative transparency,
    completeness, and consistency of each tool. These conclusions are summarized in the
    detailed characterization of the tools and in the analysis of tools coverage and performances
    per activity. The analysis found that it is important to assess tool coverage and results per
    SLM activity to judge their ability to measure GHG emissions from non-vegetative
    surfaces to cropland, grassland, and forest cover.

6.1 Review of the detailed characterization of suitable tools

 368) Only five out of seven short-listed tools were identified as suitable for a wide range of
    SLM GHG assessment: AFOLU Carb, AFD-CFT, CAT-AR, CBP, and EX-ACT. The data,
    time and skill requirements are shown in Table 36, as there is no difference among the tools
    in terms of availability and geographic coverage. All calculators account for soil and
    climate differences and have relatively moderate data, time, and skills requirements, with
    the implication that more training may be required for users.

 369) Concerning GHG coverage, only three out of the five suitable tools account for CO 2 ,
    N 2 O, and CH 4 collectively. Except for the CAT-AR tool, each tool accounts for leakage.
    Only CBP and EX-ACT quantify uncertainties in their GHG evaluation. Except for the
    CAT-AR tool, the tested GHG accounting tools are not specifically designed for carbon
    markets. All the tools follow the IPCC and stock difference methods. The carbon pools
    considered within each calculator vary; however, all short-listed calculators account for
    above-ground and below-ground biomass.

                   Table 36: Data, time, and skills requirements of the suitable tools
No.   Tool            Data requirements                Time requirements               Skills requirements
 1    AFD-CFT                 +++                              ++                                 +
 2    AFOLU Carb              +++                             +++                               +++
 3    CAT-AR                   ++                             +++                                ++
 4    CBP                     +++                             +++                                 +
 5    EX-ACT                  +++                              ++                                ++
                                              0 min < Time necessary ≤ 10 min
                                               ++++
                   + +++to +; from low data                                         ++++ to +; from basic
                                              10 min < Time necessary ≤ 20 min
                   requirements to                                                  skills requirements to
Legend                                         +++
                   medium/high/very high                                            medium/high/very high
                                              20 min < Time necessary ≤ 30 min
                   data requirements                                                skills requirements
                                               ++
                                              Time necessary > 30 min  +




                                                                                                        113
  Table 37: Analysis type, IPCC GHG accounting approaches, GHG, carbon pools, uncertainty and leakage
                                   accounted for by the suitable tools
                                 IPCC GHG
             Analysis
                                 accounting                                             GHG                            Carbon pools
              type
                                 approaches



                                 IPCC Tier used (1, 2)

                                                           Gain-loss and Stock
                                                           difference methods




                                                                                                        Above-ground

                                                                                                                       Below-ground




                                                                                                                                                           Soil Carbon
  Tool                                                                                                                                                                   Uncertainty   Leakage




                                                                                                                                               Dead wood
             Ex ante

                       Ex post




                                                                                                                                      Litter
                                                                                         N2O
                                                                                 CO 2



                                                                                               CH 4
AFD-                              x                                                                                                                                          no
             x     x     x               x    no     x                                                   x             x              no       no          x                             x
CFT
AFOLU                             x                                                                                                   no       no                            no
             x    no     x               x    no no                                                      x             x                                   x                             x
Carb
CAT-AR       x     x     x        x      x     x     x                                                   x             x              no       no          no                no          x
CBP          x     x     x        x      x     x     x                                                   x             x                                    x                 x          x
EX-ACT       x     x     x        x      x     x     x                                                   x             x              x        x            x                 x          x
x means the tool meets the criteria, no means it does not

6.2 Tools coverage and performance relative to SLM activities

  370) Table 38 summarizes the suitable tools with respect to the prevalence of SLM activities
     in the GEF projects. The circumstances under which the tools are suitable are discussed in
     the following paragraphs.

                                                         Table 38: Tools and frequency of SLM activities assessed
      SLM activity                                              Frequency                     GHG accounting tools suitable
Afforestation                                                                    10                   EX-ACT, CBP, AFD-CFT, AFOLU Carb, and CAT-AR
Deforestation                                                                    4                    EX-ACT, CBP, AFOLU Carb, and CAT-AR
Forest management                                                                8                    EX-ACT, CBP, and AFOLU Carb
Perennial crops                                                                  9                    EX-ACT, CBP, AFD-CFT, and CFT
Annual crops                                                                     8                    EX-ACT, CBP, AFD-CFT, AFOLU, CCAFS, and CFT
Grassland management                                                             7                    EX-ACT, CBP, AFOLU Carb, and AFD-CFT
Livestock                                                                        2                    EX-ACT and CBP
Inputs (Fertilizers and
                                                                                 1                    EX-ACT and AFD-CFT
Pesticides)
Investments                                                                      4                    EX-ACT and AFD-CFT

6.2.1 Afforestation and reforestation activities

  371) Ten afforestation activities were identified and assessed across the GEF projects (Table
     38). Four tools—EX-ACT, CBP, AFD-CFT and CAT-AR—are judged suitable for
     afforestation GHG balance analysis. Depending on the ILU, the following GHG calculators
     are recommended for both Tier 1 and Tier 2 methodologies:


                                                                                                                                                                                             114
       •   The EX-ACT tool, when the ILU is annual cropland, perennial cropland, flooded
           rice, grassland, set aside land, degraded land, other land, wetlands or settlements.
       •   The CBP tool, when the ILU is annual cropland, perennial cropland, flooded rice,
           grassland, or settlements.
       •   The AFD-CFT tool, when the ILU is annual cropland, perennial cropland, set aside
           land, grassland, other land, or settlements.
       •   The CAT-AR tool, when the ILU is cropland or grassland.
       •   EX-ACT, CBP, and AFD-CFT tools when afforestation activities are carried out in
           the baseline/business as usual scenario.

6.2.2 Deforestation activities

 372) Four deforestation activities were identified and assessed (Table 38). Three tools, EX-
    ACT, CBP, and AFD-CFT, are judged suitable for the deforestation GHG balance analysis.
    Depending on the FLU, the following GHG calculators are recommended for both Tier 1
    and Tier 2 methodologies:
      • The EX-ACT tool, when the FLU is annual cropland, perennial cropland, flooded
         rice, grassland, set aside land, degraded land, other land, wetlands, or settlements
      • The CBP tool, when the FLU is annual cropland, perennial cropland, flooded rice,
         grassland, or settlements
      • The AFD-CFT tool, when the FLU is annual cropland, perennial cropland, set aside
         land, grassland, other land, or settlements

6.2.3 Forest management

 373) Eight forest management activities were identified and assessed (Table 38). Within this
    study, two forest management categories were identified for GHG balance analysis: forest
    fire management and forest management and degradation (Table 13). Depending on the
    type of forest management activities, the following GHG calculators are recommended for
    both Tier 1 and Tier 2 methodologies:
      • The EX-ACT, CBP, and AFOLU Carb tools, for forest fire management GHG
          analysis
      • The EX-ACT and CBP tools, for all forest management GHG analysis.

6.2.4 Annual cropland

 374) Eight annual crops activities were identified and assessed (Table 38). Within this study,
    two annual crops categories were identified for GHG balance analysis: newly implemented
    systems after land conversion (LUC) and annual systems that remain annual systems
    (Table 13).

 375) For newly implemented systems and depending on the ILU, the following GHG
    calculators are recommended for both Tier 1 and Tier 2 methodologies:


                                                                                           115
           •    The EX-ACT tool, when the ILU is forestland, perennial cropland, flooded rice,
                grassland, set aside land, degraded land, other land, wetlands, or settlements
           •    The CBP tool, when the ILU is forestland, perennial cropland, flooded rice,
                grassland, or settlements
           •    The AFD-CFT tool, 37 when the ILU is forestland, perennial cropland, set aside land,
                grassland, other land, or settlements

     376) For GHG analysis of annual systems that remain annual systems, the EX-ACT and CBP
        tools are recommended when considering improved management practices scenario for
        both Tier 1 and Tier 2 methodologies.

6.2.5 Perennial cropland

     377) Nine perennial crops activities were identified and assessed (Table 38). Within this study,
        two perennial crops categories were identified for GHG balance analysis: newly
        implemented systems after land conversion (LUC) and perennial systems that remain
        perennial systems (Table 13). For both categories, the following tools are recommended for
        both Tier 1 and Tier 2 methodologies:
          • The EX-ACT tool, 38 when the ILU is forestland, annual cropland, flooded rice,
             grassland, set aside land, degraded land, other land, wetlands, or settlements
          • The CBP tool, when the ILU is forestland, annual cropland, perennial cropland,
             flooded rice, or settlements
          • The AFD-CFT tool,32 when the ILU is forestland, cropland, set aside land, grassland,
             other land, or settlements

6.2.6 Grassland management

     378) Seven grassland activities were identified and assessed (Table 38). Within this study, two
        grassland categories were identified for GHG balance analysis: newly implemented systems
        after land conversion (LUC) and grassland systems that remain grassland systems (Table
        13).

     379) For newly implemented grassland systems and depending on the ILU, the following GHG
        calculators are recommended for both Tier 1 and Tier 2 methodologies:
          • The EX-ACT tool, when the ILU is forestland, annual cropland, perennial cropland,
              flooded rice, set aside land, degraded land, other land, wetlands, or settlements.
          • The CBP tool, when the ILU is forestland, annual cropland, perennial cropland, or
              other land. The CBP DA is recommended for the analysis as default coefficients
              could be replaced to describe the set aside and degraded land EFs and carbon stocks
              values.
37
     Restricted agricultural management practices.
38
     The tool is suitable for perennial crops improvement.



                                                                                                 116
          •   The AFD-CFT tool, when the ILU is forestland, annual cropland, perennial cropland,
              set aside land, other land, or settlements.

     380) For GHG analysis of grassland systems that remain grassland systems, the EX-ACT,
        CBP, AFOLU Carb, and AFD-CFT tools are recommended when considering improved
        management practices for both Tier 1 and Tier 2 methodologies.

6.2.7 Livestock

     381) Two grassland activities were identified and assessed (Table 38). Based on the analysis
        results, the use of the EX-ACT tool is recommended for livestock GHG analysis when
        considering technical mitigation options (feeding practices, specific agents, and breeding
        practices). 39

6.2.8 Inputs management (fertilizers and pesticides)

     382) Only one fertilizer management activity was identified and assessed (Table 38). Based on
        the analysis results, the use of the EX-ACT tool is recommended for GHG balance analysis
        (N 2 O emissions from managed soils, CO 2 emissions from lime and urea application).
     383) No pesticides management activities were identified. However, the use of the EX-ACT
        tool is recommended for GHG balance analysis of pesticides management.

6.2.9 Investments

     384) Four investments activities were identified and assessed (Table 38). Within this study the
        GHG emissions covered by the ‘investments’ are (a) GHG emissions associated with
        electricity consumption, (b) GHG emissions associated with fuel consumption, (c) GHG
        emissions associated with installation of irrigation systems, and (d) GHG emissions
        associated with building of infrastructure (Table 13). Depending on the investments
        activities, the following tools are recommended for both Tier 1 and Tier 2 methodologies:
          • The EX-ACT tool, when considering GHG emissions related to electricity and fuel
              consumption, irrigation system construction, or agricultural building activities.
          • The AFD-CFT tool, when considering GHG emissions related to electricity and
              infrastructure and agricultural building construction.

6.2.10 Versatility of the tools

     385) Table 39 identifies the EX-ACT, CBP, and AFD-CFT tools as the most versatile tools
        capable of addressing most land use activities. The least versatile tools are the CAT-AR

39
  For users intending to use detailed Tier 2 (for example, refined EFs on enteric fermentation), a link is provided by
the EX-ACT tool to the FAO GLEAM-I tool. The CBP DA could be used to add in livestock EFs.




                                                                                                                  117
      and AFOLU Carb because they were developed to address specific SLM activities. Table
      39 also demonstrates that most calculators account for land use change (that is, a change
      from one land use category to another—forestland, cropland, grassland, flooded, other land,
      degraded land). Table 40 highlights the recommended tools (EX-ACT, CBP, and/or AFD-
      CFT) when considering different land use change scenarios.

                                                                                    Table 39: Recommended tools per land use activity

                                                                                                                                                                            SLM activities

                                                                     Forest                                          Annual                                                  Perennial                                                                                                                                 Inputs, energy, and
                                                                                                                                                                                                                                           Grassland
                                                                   management                                         crops                                                    crops                                                                                                                                     infrastructure
                   Afforestation/reforestation*




                                                                                                                                                                                                                                                                                             Inputs (fertilizers and pesticides)
                                                                                                                                                                              Perennial crops development*

                                                                                                                                                                                                             Perennial crops improvement
                                                                                                                     Annual crops development*

                                                                                                                                                 Annual crops improvement




                                                                                                                                                                                                                                            Grassland development*

                                                                                                                                                                                                                                                                     Grassland improvement
                                                                                             Forest management and
                                                                    Fire forest management




                                                                                                                                                                                                                                                                                                                                   Electricity consumption
                                                  Deforestation*




                                                                                                                                                                                                                                                                                                                                                                                Irrigation systems
                                                                                                                                                                                                                                                                                                                                                             Fuel consumption
No.     Tool




                                                                                                                                                                                                                                                                                                                                                                                                     Infrastructure
                                                                                                   degradation




                                                                                                                                                                                                                                                                                                                                                                                                                      Score
                                                                                                                                                                                                                                                                                                                                                                                                                       (%)




     AFD-                   no        no                                                                         60
 1               x x                           x    no    x      x      x      x     no x no no x
     CFT
     AFOLU            no              no      no no      no      no     no           no no no no no              13
 2              no           x                                                 x
     Carb
 3 CAT-AR x no              no        no      no no      no      no     no     no no no no no no                 6
 4 CBP           x x         x         x       x     x    x      x      x      x     no no no no no              66
 5 EX-ACT x x                x         x       x     x    x      x      x      x     x     x    x    x    x     100
Note: *The choice of the appropriate tool is conditioned by the different land uses considered when considering
LUC scenarios.
 x means the tool meets the criterion; no means the tool does not. Score is the number of activities out of 15 for which a tool is
                                                 suitable, expressed in percent.




                                                                                                                                                                                                                                                                                                                                                                                                                       118
                 Table 40: Recommended tools when considering land use change scenarios

    ILU                                                               Set
                           Annual    Perennial               Flooded       Degraded Other
              Forestland                         Grassland           aside                Settlements
                            crops      crops                   rice          land   land
                                                                     land
   FLU
                                                                      AFD-
                           AFD-
                                     AFD-CFT     AFD-CFT              CFT
                           CFT
                                     CAT-AR      CAT-AR               CAT-            EX-   CBP
Forestland                 CAT-AR                            EX-ACT          EX-ACT
                                     CBP         CBP                  AR              ACT   EX-ACT
                           CBP
                                     EX-ACT      EX-ACT               EX-
                           EX-ACT
                                                                      ACT
                                                                      AFD-
              AFD-CFT                AFD-CFT     AFD-CFT
Annual                                                                CFT             EX-   CBP
              CBP                    CBP         CBP         EX-ACT          EX-ACT
crops                                                                 EX-             ACT   EX-ACT
              EX-ACT                 EX-ACT      EX-ACT
                                                                      ACT
                                                                      AFD-
              AFD-CFT      AFD-                  AFD-CFT
Perennial                                                             CFT             EX-     CBP
              CBP          CFT CBP               CBP         EX-ACT          EX-ACT
crops                                                                 EX-             ACT    EX-ACT
              EX-ACT       EX-ACT                EX-ACT
                                                                      ACT
                           AFD-                                       AFD-
              AFD-CFT             AFD-CFT
                           CFT                                        CFT             EX-     CBP
Grassland     CBP                 CBP                        EX-ACT          EX-ACT
                           CBP                                        EX-             ACT    EX-ACT
              EX-ACT              EX-ACT
                           EX-ACT                                     ACT

Flooded                                                               EX-             EX-
              EX-ACT       EX-ACT EX-ACT         EX-ACT                      EX-ACT          EX-ACT
rice                                                                  ACT             ACT

                           AFD-
Set aside     AFD-CFT             AFD-CFT        AFD-CFT                              EX-
                           CFT                               EX-ACT          EX-ACT          EX-ACT
land          EX-ACT              EX-ACT         EX-ACT                               ACT
                           EX-ACT

Degraded                                                              EX-             EX-
              EX-ACT       EX-ACT EX-ACT         EX-ACT      EX-ACT                          EX-ACT
land                                                                  ACT             ACT

              CBP          CBP    CBP            CBP                  EX-
Other land                                                   EX-ACT          EX-ACT          EX-ACT
              EX-ACT       EX-ACT EX-ACT         EX-ACT               ACT

              CBP          CBP    CBP            CBP                  EX-             EX-
Settlements                                                  EX-ACT          EX-ACT
              EX-ACT       EX-ACT EX-ACT         EX-ACT               ACT             ACT


6.3 Comparison of results between tools

  386) The comparability of the assessment results depends on the land use activity as each tool
     has its own purpose. There is no widely accepted international standard or protocol for
     GHG assessment and monitoring at the local level yet. In the absence of any such standard,
     all the short-listed calculators have used the IPCC methodology for national inventories as
     a guideline. As such, the accuracy of a tool largely depends on the IPCC methods used and
     the data that feed into it. The Tier 1 methods are based on least accurate methods, Tier 2
     methods are more accurate methods, where EFs and carbon stock changes are available.



                                                                                                  119
      The Tier 3 methods are very detailed, where biophysical models of GHG processes that are
      developed at the country or regional level are available.

  387) This raises the question as to whether the desk study analysis based on project documents
     and Tier 1 methods disposes of comprehensive and reliable datasets for the compilation of
     GHG assessment. Table 41 compiles differences in results between tools for both analysis:
     the desk study using Tier 1 methodology and the in-depth analysis using Tier 2
     methodology. All the SLM activities, besides deforestation and forest fire management,
     were assessed under both desk study and in-depth analysis. For both activities, and to
     complete the analysis, default values were substituted by Tier 2 coefficients to describe the
     type of vegetation and their associated carbon stock values.

       Table 41: Comparison of results: Desk study, Tier 1 methodology versus in-depth analysis, Tier 2
                                                 methodology
                                                                          Desk study            In-depth
                    Activities                           Tools          analysis, Tier 1    analysis, Tier 2
                                                                         methodology         methodology
                                                  CBP & EX-ACT                  +                   +
                                                  AFD-CFT & EX-
                                                                                +                   +
                                                  ACT
                                                  CAT-AR & EX-
                                                                                +                   +
*Afforestation/reforestation                      ACT
                                                  AFD-CFT & CBP               +++                   +
                                                  CAT-AR & CBP                  +                   +
                                                  AFD-CFT & CAT-
                                                                              +++                   +
                                                  AR
                                                  CBP & EX-ACT               ++++                  ++
                                                  AFOLU Carb &
Deforestation                                                                 +++                   +
                                                  EX-ACT
                                                  AFOLU Carb &
                                                                             ++++                  ++
                                                  CBP
                                                  EX-ACT & CBP                 ++                   +
                                                  AFOLU Carb &
                                                                              +++                   +
Forest           Forest fire management           EX-ACT
management                                        AFOLU Carb &
                                                                              +++                   +
                                                  CBP
                 Forest management                CBP & EX-ACT                 ++                   +
                                                  CBP & EX-ACT                 ++                   +
                                                  AFD-CFT & EX-
Annual           Annual cropland development                                   ++                  ++
                                                  ACT
Cropland
                                                  AFD-CFT & CBP                ++                   +
                 Annual cropland improvement      CBP & EX-ACT               ++++                   +
                                                  CBP & EX-ACT                +++                  ++
                                                  AFD-CFT & EX-
                                                                             ++++                  ++
                 Perennial cropland development   ACT
                                                  AFD-CFT & CBP
Perennial                                                                    ++++                  ++
                                                  SA
cropland
                                                  CBP & EX-ACT                           +
                                                  EX-ACT & AFD-
                 Perennial cropland improvement*                                         +
                                                  CFT
                                                  CBP & AFD-CFT                          +



                                                                                                         120
                                                                              Desk study            In-depth
                    Activities                             Tools            analysis, Tier 1     analysis, Tier 2
                                                                             methodology          methodology
                                                    CBP & EX-ACT                  ++                   ++
                                                    AFD-CFT & EX-
                                                                                  +++                 ++
                                                    ACT
                                                    AFOLU Carb &
                                                                                  +++                 ++
                                                    EX-ACT
                 Grassland management
                                                    AFD-CFT & CBP                 +++                  +
Grassland
                                                    AFOLU Carb
                                                                                  +++                  +
                                                    &CBP
                                                    AFD-CFT &
                                                                                  +++                  +
                                                    AFOLU Carb
                                                    AFD-CFT & EX-
                 Grassland development                                             ++                  +
                                                    ACT
Livestock                                           CBP & EX-ACT                    +                  +
                                                    AFD-CFT & EX-
Inputs and infrastructures                                                                   +**
                                                    ACT
                                                          0 percent < results difference ≤ 5 percent  +
                                                         5 percent < results difference ≤ 10 percent  ++
Legend
                                                        10 percent < results difference ≤ 20 percent  +++
                                                             results difference > 20 percent  ++++
Note:
*The analysis was conducted following Tier 2 methodology with default Tier 1 coefficients replaced to describe the
initial and final (after improvements) above-ground growth rate (tC per ha per year)
** A minimal difference was observed among the results, owing to the similarities in investment and input EFs used
by the tools.

6.3.1 Results analysis

  388) The most versatile results differences were observed within the desk study analysis. This
     is explained mainly by the use of the Tier 1 accounting approach and the type of carbon
     pools taken into account by each tool. The highest result differences (more than 20 percent)
     were observed when analyzing deforestation, perennial cropland development, and annual
     cropland improvement activities. The less versatile results differences (less than 20 percent)
     were associated with afforestation/reforestation, forest management, annual cropland
     development, perennial cropland improvement, livestock, and inputs and infrastructures
     GHG accounting assessment.

  389) For the in-depth analysis, including data collected at the local level in Tunisia and Chile
     provided more accuracy than the desk study analysis. The differences in results decreased
     significantly (to less than 10 percent) when the data collected reflected more detailed
     descriptions of the projects’ activities and their associated EFs and carbon stock values.

  390) The uncertainty level furthermore validates the different results as the degree of
     uncertainty was estimated at less than 21 percent within the in-depth analysis, compared to
     higher uncertainty levels when running a desk study analysis (for example, 62 percent,
     Biodiversity Conservation in Cacao Agroforestry Project in Costa Rica).



                                                                                                              121
      6.4 Multicriteria GHG tool selector for SLM Projects

        391) Following the analyses, we present in this section a set of criteria for selecting a tool for a
           given SLM project. The three-step process also reflects the characteristics and purpose of
           the tool (Figure 20).
             • Step 1: Choose the land use activity (afforestation, deforestation, forest management,
                 annual cropland, perennial cropland, grassland, flooded rice, wetlands, inputs, energy,
                 and infrastructure) (Table 39).
             • Step 2: If any LUC activity is foreseen, choose ILU and FLU. (Table 40).
             • Step 3: Consider other criteria as needed to recommend the appropriate GHG tool(s)
                 (for example, the GHGs [CO 2 , N 2 O, CH 4 ], the IPCC GHG accounting approaches,
                 the need for multiple areas to be analyzed simultaneously, carbon pools, the need for
                 spatially explicit results, uncertainties, and leakages, and so on) (Table 37). Note that
                 additional requirements can be used to reduce the selection to one or two calculators.
                           Figure 20: Step-by-step process for selecting a GHG calculator
                                                              Aim
                                   GHG Accounting Tools for Sustainable Land Management



                                                Geographical zone/application
                                                  World, all climates and soils


Predefined

                                                     Data, Time and Skills
                                                            Medium




                                                 1. Land use activity (Table 39)
                                       (Afforestation, deforestation, forest management,        Land Use
                                        annual crops, perennial crops, grassland, flooded
                                       rice, wetlands, inputs, energy, and infrastructure)




                                                       2. LUC (Table 40)                      Ye           No
                                                         (ILU and FLU)



                                                      3. GHG, Carbon pools
                                                          Uncertainty
                                                           Leakage
                                                           (Table 37)




                                                                                                        122
7. Conclusions and recommendations
 392) Climate change poses a major challenge to the agricultural sector due to the dependence
    of agriculture on climate and the complex role it plays in rural, social, and economic
    contexts (Hatfield et al. 2011). According to the FAO (2002), the rising incidence of
    weather extremes will have increasingly negative impacts on crop productivity, especially
    if occurring at sensitive stages in crop life cycles (National Climate Assessment 2014).
    Furthermore, the IPCC, in its fifth assessment report, predicts that climate change will
    affect food security by the mid-21st century. However, climate change can offer new
    opportunities for productive and SLM practices. 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.

 393) Systematic assessments are required to make informed decisions, and therefore, tackle
    climate-induced vulnerability and food insecurity. 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.
    Estimates of this potential should consider the full GHG balance, including possible
    combinations of different activities and practices that could affect the net climate change
    mitigation potential.

 394) This study has shown that many advanced tools have been developed, the main
    methodological approaches and challenges of GHG accounting have been highlighted, and
    an analytical framework for the selection of the appropriate carbon accounting tools for
    SLM activities has been presented. The analysis was user driven to understand the
    underlying particularities of each tool and their differences and enable the user to make the
    final choice on the GHG calculator(s). In general, the methodologies applied by the tools
    are relatively similar and all tool developers align their methodology with the IPCC
    guidelines. The tools are moderately data, skills, and time demanding and offer many
    additional functions (carbon footprint, socioeconomic analysis, and so on). The
    methodologies on which the tools are based are transparent and detailed in guidance
    documents.

 395) The accuracy of the different quantification methods is classified in three tiers, Tier 1
    methods being the least accurate methods. The accuracy of the method depends on the EFs
    and the activity data used. Region-specific EFs and activity data are more accurate than
    country-specific EFs and should preferably be used. Nevertheless, other aspects should be
    considered to provide the users with tools that are comprehensible, standardized, robust,
    and applicable to SLM projects.




                                                                                             123
     396) This study clearly shows that the completeness aspect is key in comparing the tools:
        GHG assessments are not always reported for all relevant categories of sources and sinks
        and GHGs. Some tools cover only some land use activities whereas other tools cover
        almost all land use activities. Furthermore, scope definitions vary and the number and type
        of GHG covered differ across tools. As such, it is recommended to extend the scope of the
        calculators while restricting the data, skills, time needed, and increasing their accuracy.
        For the international dissemination of these tools, their availability in different languages is
        of crucial importance.

     397) The accuracy of a tool depends mainly on the data that feed into it. Thus, it depends on
        data availability at the local level, on the one hand, and on support of the users and advice
        on how to find data, on the other. All tools offer the option to specify Tier 2 values,
        country-specific EFs. Desk studies analysis based on project documentation is often
        lacking comprehensive and reliable datasets for the compilation of GHG assessment, which
        will increase/decrease the level of certainty/uncertainty. Data collection and quality
        assurance at the local level is therefore recommended.

     398) It is important to bear in mind that the main question is not whether a calculator is
        suitable. On the contrary, most actors would welcome any development toward greater
        tools completeness and accuracy. A recent FAO publication 40 encourages the development
        of new tools and the dissemination of existing tools to assist with the analysis of, and the
        planning for, the impacts of climate change and new national reporting requirements. In
        this prospect, advocacy for large-scale climate finance to be funnelled into the sectors
        where investment can lay the groundwork for the paradigm shift is needed to achieve the
        future we want.




40
     FAO Strategy on Climate Change, available at http://www.fao.org/3/a-i7175e.pdf




                                                                                                    124
125
Annex: Detailed Results of Carbon Balance Appraisals

          GE                            Component
Project         Countr
           F             Project name    s of the                  Review by activity and by GHG Tool (in tCO 2 -e/Year)
  ID              y
          ID                              project
                                                                                AFOLU                                 CCA
                                           Tools       EX-ACT        CBP                    AFD CFT      CAT-AR                CFT
                                                                                 Carb                                  FS
                                        Land Use
                                        Changes
                                        (Afforestati    -7227       -7,624       -7,879       -9,537       -3,371      N/A     N/A
                                        on) on
                                        perennial
                                        Degradatio
                                        n and
                                        managemen
                                                        -8801       -8,922       -7,622        N/A          N/A        N/A     N/A
                                        t (forest
                          Forestry      degradation
P1477     694   Belaru
                         Developmen     )
 60        7      s
                          t Project                        -
                                        Inputs &
                                                       123279.0      N/A          N/A        -123,284       N/A        N/A     N/A
                                        Investments
                                                          33
                                                           -                                    -
                                           Total                   -330,920    -152,441                   -67,425          -    -
                                                       2,786,149                            2,656,404
                                         Total per
                                                       -139,307     -16,546      -7,622      -132,820      -3,371          -    -
                                           year
                                                           -
                                        Per hectare    3.603330        -           -            -3           -             -    -
                                                          261
                                        Per hectare
                                                          0            -           -           -0.2          -             -    -
                                         per year
                                                                                AFOLU                                 CCA
                                           Tools       EX-ACT        CBP                    AFD CFT      CAT-AR                CFT
                                                                                 Carb                                  FS
                                        Grassland
                                        and
                                        Livestock
                                                       -227,027    -225,620    -162,645      -170,000       N/A        N/A     N/A
                                        (Grassland
                         BR GEF Rio     managemen
P0863     245             Grande do     t)
                Brazil
 41        0                 Sul                           -           -           -            -
                         Biodiversity      Total                                                             -             -    -
                                                       4,540,540   4,512,400   3,252,900    3,400,000
                                         Total per
                                                       -227,027    -225,620    -162,645      -170,000        -             -    -
                                           year
                                        Per hectare     -21.22       -21.1       -27.47       -28.71         -             -    -
                                        Per hectare
                                                         -1.06       -1.1        -1.37        -1.44          -             -    -
                                         per year
                                                                                AFOLU                                 CCA
                                           Tools       EX-ACT        CBP                    AFD CFT      CAT-AR                CFT
                                                                                 Carb                                  FS
                                        Land Use
                                        Changes
                                                        -28,032     -24,509     -34,194      -42,800      -39,281      N/A     N/A
                                        (Afforestati
                           Caatinga
                                        on)
                         Conservation
P0708     245                and        Agriculture
                Brazil                                   -544        -475         -42          -200         N/A       -1,684   -304
 67        0              Sustainable   (Annual)
                         Management
                            Project     Agriculture
                                                        -8,357      -7,306        N/A         -2,900        N/A        N/A     -197
                                        (Perennial)
                                           Total       -738,642    -645,810    -684,720      -918,000     -785,615         -    -
                                         Total per
                                                        -36,932     -32,291     -34,236      -45,900      -39,281          -    -
                                           year




                                                                                                                                126
                                       Per hectare     -371.2      -324.5         -        -461.31       -        -      -
                                       Per hectare
                                                        -18.6       -16.2         -        -23.07        -        -      -
                                        per year



                                                                              AFOLU                              CCA
                                          Tools       EX-ACT        CBP                   AFD CFT     CAT-AR           CFT
                                                                               Carb                               FS



                          GGW:         Land Use
                       Community       Changes
                       based Rural                     -7,225      -7,668      -7,511      -7,290       N/A      N/A    N/A
                                       (Deforestati
                       Developmen      on)
                       t Project 3rd
P1305   518   Burkin    Phase with     Manageme
 68      7    a Faso    Sustainable    nt and
                         Land and      degradation
                                                       -2,491      -2,652       N/A         N/A         N/A      N/A    N/A
                         Forestry      (forest
                       Management      degradation
                        in Burkina     )
                           Faso           Total       -194,323    -206,401    -150,214    -145,800       -        -      -
                                        Total per
                                                       -9,716      -10,320     -7,511      -7,290        -        -      -
                                          year
                                       Per hectare      -13         -14         -10         -10          -        -      -
                                       Per hectare
                                                         -1          -1          -1          -1          -        -      -
                                        per year
                                                                              AFOLU                              CCA
                                          Tools       EX-ACT        CBP                   AFD CFT     CAT-AR           CFT
                                                                               Carb                               FS
                                       Land Use
                                       Changes
                                                       -4,765      -5,441      -5,463      -4,900      -4,746    N/A    N/A
                                       (Afforestati
                                       on)
                                       Agriculture
                                                       -43,986     -63,260      N/A        -56,000      N/A      N/A   -4,048
                                       (Perennial)
                                       Degradatio
                       Watershed       n and
P1272   463   Burun    App to Sust     Manageme
                                                       -4,112      -3,614      -5,890       N/A         N/A      N/A    N/A
 58      1     di        Coffee        nt (forest
                       Production      degradation
                                       )
                                                                                                                         -
                                                          -           -                       -
                                          Total                               -227,060                -94,910          80965.
                                                      1,057,260   1,266,004               1,218,000
                                                                                                                         8
                                                                                                                         -
                                        Total per
                                                       -52,863     -63,300     -11,353     -60,900     -4,746          4048.2
                                          year                                                                    -      9
                                       Per hectare      -171        -21.7         -        -612.06       -
                                       Per hectare
                                                        -8.5        -1.1          -         -30.6        -
                                        per year
                                                                              AFOLU                              CCA
                                          Tools       EX-ACT        CBP                   AFD CFT     CAT-AR           CFT
                                                                               Carb                               FS
                                       Land Use
                         Guangxi                                                                          -
                                       Changes            -           -           -           -
                        Integrated                                                                    3,564,79   N/A    N/A
                                       (Afforestati   2,620,688   7,641,060   3,771,511   3,200,000
                         Forestry                                                                        2
P0873   263                            on)
              China    Developmen
 18      4
                           t and                          -           -           -           -           -
                       Biodiversity       Total       52,413,76   152,821,2   75,430,22   64,000,00   71,295,8    -      -
                       Conservation                       7          00           0           0          49
                                                                                                          -
                                        Total per         -           -           -           -
                                                                                                      3,564,79    -      -
                                          year        2,620,688   7,641,060   3,771,511   3,200,000
                                                                                                         2




                                                                                                                         127
                                                                                 -           -           -
                                      Per hectare     -244.92     -714.1     636.9988    540.4720    602.0846     -        -
                                                                               599         686          13
                                      Per hectare
                                                      -12.25       -35.7      -31.85      -27.02      -30.1       -        -
                                       per year
                                                                             AFOLU                              CCA
                                         Tools       EX-ACT        CBP                   AFD CFT     CAT-AR              CFT
                                                                              Carb                               FS
                        Shanghai      Livestock       -5,394      -5,862        0          N/A         N/A       N/A       0
                       Agricultural
                                         Total       -107,888    -117,240        -           -          -         -        0
                        and Non-
P0903   322
              China       point        Total per
 76      3                                            -5,394      -5,862         -           -          -         -        0
                        Pollution        year
                        Reduction
                         Project      Per hectare      -34          0            -           -          -         -        0
                                      Per hectare
                                                       -1.7         0            -           -          -         -        0
                                       per year
                                                                             AFOLU                              CCA
                                         Tools       EX-ACT        CBP                   AFD CFT     CAT-AR              CFT
                                                                              Carb                               FS
                                      Land Use
                                      Changes                                                            -
                                                      -2,548      -2,207      -2,850      -3,300                 N/A      N/A
                                      (Afforestati                                                   2,389.29
                                      on)
                         Project      Agriculture
                       Biodiversity                   -4,708      -4,840       N/A        -4,600       N/A       N/A      N/A
P0613         Costa                   (perennial)
        979               cacao                                                                                   -
 15           Rica                                                                                                          -
                       agroforestry      Total       -145,116    -140,940     -57,000    -158,000    -47,786    34,68
                        Costa Rica                                                                                       34,684
                                                                                                                  4
                                       Total per
                                                      -7,256      -7.047      -2,857      -7,900      -2,390    -1,734   -1,734
                                         year
                                      Per hectare      -109       -105.6       -43         -118        -36       -26      -26
                                      Per hectare
                                                        -5         -5.28        -2          -6          -2        -1       -1
                                       per year
                                                                             AFOLU                              CCA
                                         Tools       EX-ACT        CBP                   AFD CFT     CAT-AR              CFT
                                                                              Carb                               FS
                                      Land Use
                                                                                                         -
                                      Changes            -           -                       -
                                                                             -783,933                1,348,05    N/A      N/A
                                      (Afforestati   1,079,287   1,121,464               1,450,000
                                                                                                        6
                                      on)
                                                                                                                  -        -
                                      Agriculture
                                                     -659,046    -324,000    -572,747    -274,000      N/A      301,6    368,66
                                      (Annual)
                                                                                                                 05        6
                                                                                                                           -
                                      Agriculture        -
                                                                 -986,632      N/A       -410,000      N/A       N/A     543,00
                                      (Perennial)    1,017,526
                                                                                                                           0
                         Country
                       Program for    Grassland
P0907   463   Ethiop   Sustainable    and
 89      0      ia        Land        Livestock
                                                     -342,098    -380,000    -481,386    -380,000      N/A       N/A      N/A
                       Management     (Grassland
                       (ECPSLM)       managemen
                                      t)

                                      Degradatio
                                      n and
                                      Manageme
                                                      -78,794     -73,850    -134,367      N/A         N/A       N/A      N/A
                                      nt (forest
                                      degradation
                                      )
                                      Inputs &
                                                     101,665       N/A         N/A        3,600        N/A       N/A      N/A
                                      Investments
                                                         -           -           -           -           -
                                         Total       66,317,26   57,718,91   36,761,32   49,560,00   26,961,1     -        -
                                                         9           0           3           0          20




                                                                                                                           128
                                                                      -
                                        Total per         -                       -           -
                                                                  2,885,945                              -        -        -
                                          year        3,315,863               1,838,066   2,478,000
                                                                     .50
                                       Per hectare      -59.7       -51.9         -           -          -        -        -
                                       Per hectare
                                                         -3         -2.6          -           -          -        -        -
                                        per year
                                                                              AFOLU                             CCA
                                          Tools       EX-ACT        CBP                   AFD CFT     CAT-AR             CFT
                                                                               Carb                              FS
                                       Land Use
                                       Changes
                                                       -88,541     -98,530     -76,650    -101,000     N/A       N/A      N/A
                                       (Deforestati
                                       on)
                                       Agriculture
                                                       -13,921     -10,081     -10,081     -11,000     N/A      -9,500   10,500
                                       (Annual)
                                       Agriculture
                                                      -138,151    -118,728      N/A        -90,000     N/A       N/A     75,200
                                       (Perennial)
                       Community-      Degradatio
P0812   187                            n and
              Guinea   based Land
 97      7                             Manageme
                       Management                      -13,756     -15,168     -15,778      N/A        N/A       N/A      N/A
                                       nt (forest
                                       degradation
                                       )
                                                          -           -           -           -
                                          Total                                                          -        -        -
                                                      5,087,380   4,850,140   1,734,620   4,040,000
                                                                      -
                                        Total per
                                                      -254,369    242,507.0    -86,731    -202,000       -        -        -
                                          year
                                                                      0
                                       Per hectare     -102.2       -97.4         -           -          -        -        -
                                       Per hectare
                                                        -5.1        -4.9          -           -          -        -        -
                                        per year
                                                                              AFOLU                             CCA
                                          Tools       EX-ACT        CBP                   AFD CFT     CAT-AR             CFT
                                                                               Carb                              FS
                                       Land Use
                                       Change
                                       ( set aside
                                       land           -214,679     -85,697      N/A       -175,000     N/A       N/A      N/A
                         Integrated    converted
                        Ecosystem      to
P0755   121                            grassland)
              Jordan   Management
 34      4                                                -           -                       -
                       in the Jordan      Total                                   -                      -        -        -
                        Rift Valley                   4,293,575   1,713,940               3,500,000
                                        Total per
                                                      -214,679     -85,697        -       -175,000       -        -        -
                                          year
                                       Per hectare     -118.9       -47.5         -         -96.9        -        -        -
                                       Per hectare
                                                        -5.9        -2.4          -         -4.85        -        -        -
                                        per year
                                                                              AFOLU                             CCA
                                          Tools       EX-ACT        CBP                   AFD CFT     CAT-AR             CFT
                                                                               Carb                              FS
                                       Land Use
                                       Changes
                         Natural                       -37,175     -21,317     -42,779     -45,000     N/A       N/A      N/A
                                       (Deforestati
                        Resources      on)
P1295   527            Management
               Mali
 16      0                 in a        Land Use
                        Changing       Changes
                         Climate                       -1,218      -5,738      -10,780     -9,344     -11,300    N/A      N/A
                                       (Afforestati
                                       on)
                                       Agriculture
                                                       -2,383      -8,499      -5,040      -6,500      N/A      -1,003   -1,226
                                       (Annual)




                                                                                                                           129
                                       Grassland
                                       and
                                       Livestock
                                                      -158,833    -169,980    -156,426    -195,900     N/A       N/A      N/A
                                       (Grassland
                                       managemen
                                       t)
                                                          -           -           -           -
                                          Total                                                          -        -        -
                                                      3,992,189   4,110,680   4,300,499   4,818,000
                                        Total per
                                                      -199,609    -205,534    -215,025    -240,900       -        -        -
                                          year
                                       Per hectare      -34         -70.4       -36.3       -40.7        -        -        -
                                       Per hectare
                                                        -1.7        -3.5        -1.8         -2          -        -        -
                                        per year
                                                                              AFOLU                             CCA
                                          Tools       EX-ACT        CBP                   AFD CFT     CAT-AR             CFT
                                                                               Carb                              FS
                                                                                                                  -
                                       Agriculture
                                                       -5,682      -15,189     -5,504      -5,200      N/A      3314.    -4051
                                       (Annual)
                                                                                                                 34
                                       Agriculture
                                                       -4,811      -5,427       N/A        -5,000      N/A       N/A     -3598
                                       (Perennial)
                       Agriculture
P1185   463   Moldo                                       -
                       Competitive
 18      0     va                         Total       209,855.0   -412,320    -110,080    -204,000       -        -        -
                       ness Project
                                                          2
                                        Total per         -           -
                                                                               -5,504      -10,200       -        -        -
                                          year        10,492.75   15,189.00
                                       Per hectare     -20.99      -41.232      -25.5       -20.4        -        -        -
                                       Per hectare
                                                        -1.05      -2.0616      -1.3        -1.02        -        -        -
                                        per year
                                                                              AFOLU                             CCA
                                          Tools       EX-ACT        CBP                   AFD CFT     CAT-AR             CFT
                                                                               Carb                              FS
                                       Land Use
                                       Changes
                                       (Agrforestr
                                                      -373,063    -258,335      N/A       -370,000     N/A       N/A      N/A
                                       y) +
                                       Agriculture
                                       (perennial)
                       GEF Social
                          and          Agriculture
P1297   529   Moroc                                    -4,772      -3,254      -7,965      -2,500      N/A      -2,432   -3,818
                       Integrated      (Annual)
 74      2     co
                       Agriculture
                        (ASIMA)        Livestock        -33          0         -1,238       N/A        N/A       N/A      N/A
                                                          -           -                       -
                                          Total                               -184,060                   -        -        -
                                                      7,557,368   5,231,783               7,450,000
                                        Total per
                                                      -377,868    -261,589     -9,203     -372,500       -        -        -
                                          year
                                       Per hectare      -130        -89.7         -           -          -        -        -
                                       Per hectare
                                                        -6.5        -4.5          -           -          -        -        -
                                        per year
                                                                              AFOLU                             CCA
                                          Tools       EX-ACT        CBP                   AFD CFT     CAT-AR             CFT
                       Contribution                                            Carb                              FS
                             of
                                       Land Use
                        Sustainable
                                       Changes
                          Forest                       -65,434     -86,124     -24,674     -58,900    -49,211    N/A      N/A
                                       (Afforestati
P6356   908            Management
              Serbia                   on)
 21      9               to a Low
                         Emission
                                       Land Use
                       and Resilient
                                       Changes
                       Developmen                      21,466      29995       14,881      13,000      N/A       N/A      N/A
                                       (Deforestati
                              t
                                       on)




                                                                                                                          130
                                      Degradatio
                                      n and
                                      Manageme
                                                      -54,246      N/A         N/A         N/A        N/A     N/A   N/A
                                      nt (forest
                                      degradation
                                      )
                                                         -           -
                                         Total                               -195,869    -918,000      -       -     -
                                                     1,964,280   2,322,380
                                       Total per
                                                      -98,214    -116,119     -9,793      -45,900      -       -     -
                                         year
                                      Per hectare      -16       -23.2238        -           -         -       -     -
                                      Per hectare
                                                       -0.8      -1.16119        -           -         -       -     -
                                       per year




                                                                             AFOLU                            CCA
                                         Tools       EX-ACT        CBP                   AFD CFT     CAT-AR         CFT
                                                                              Carb                             FS




                                      Agriculture
                                                      -19,743     -21,545     -26,966     -30,000     N/A     N/A   N/A
                                      (Annual)
                                      Degradatio
                                      n and
                                      Manageme
                        Sustainable                   -43,682     -59,145      N/A         N/A        N/A     N/A   N/A
                                      nt (forest
                           land       degradation
P6131   458            Management     )
              Turkey
 34      3             and Climate-
                         Friendly     Grassland
                        Agriculture   and
                                      Livestock
                                                     -103,398    -118,290    -121,278     -97,000     N/A     N/A   N/A
                                      (Grassland
                                      managemen
                                      t)
                                                         -           -           -           -
                                         Total                                                         -       -     -
                                                     3,336,460   3,979,588   2,964,880   2,540,000
                                                                     -
                                       Total per
                                                     -166,823    198,979.4   -148,244    -127,000      -       -     -
                                         year
                                                                     0
                                      Per hectare      -33.4       -39.8         -           -         -       -     -
                                      Per hectare
                                                       -1.7         -2           -           -         -       -     -
                                       per year
                                                                             AFOLU                            CCA
                                         Tools       EX-ACT        CBP                   AFD CFT     CAT-AR         CFT
                                                                              Carb                             FS
                                      Land Use
                                      Changes
                                                      -10,340     -8,684      -11,145     -8,171     -7,801   N/A   N/A
                                      (Afforestati
                                      on)
                                      Degradatio
                       Sustainable    n and
P0856   414               Land        Manageme
              Chile                                   -7,611      -6,423       N/A         N/A        N/A     N/A   N/A
 21      0             Management     nt (forest
                         Project      degradation
                                      )

                                      Grassland
                                      and
                                      Livestock
                                                       -208        -56         -222        233        N/A     N/A   N/A
                                      (Grassland
                                      managemen
                                      t)




                                                                                                                    131
                                       Total       -363,184    -303,269    -227,333    -158,771       -         -       -
                                     Total per                     -
                                                    -18,159                 -11,367     -7,939        -         -       -
                                       year                    15,163.50
                                    Per hectare       -3          -3           -           -          -         -       -
                                    Per hectare
                                                     -0.1        -0.2          -           -          -         -       -
                                     per year
                                                                           AFOLU                              CCA
                                       Tools       EX-ACT        CBP                   AFD CFT     CAT-AR             CFT
                                                                            Carb                               FS
                                    Land Use
                                                                                                                -       -
                                    Changes
                                                   -111,322     -70,968     -67,888     -93,200    -118,663   118,0   118,06
                                    (Afforestati
                                                                                                               67       7
                                    on)
                                    Agriculture
                                                   -106,487    -168,740      N/A       -132,900      N/A      N/A      N/A
                                    (Perennial)

                                    Grassland
                                    and
                                    Livestock
                                                    -7,838      -14,667     -3,523      -4,400       N/A      N/A      N/A
                                    (Grassland
                                    managemen
                        TUN GEF     t)
                         Second
P1125   366   Tunisi
                         Natural
 68      9      a                   Inputs &
                        Resources
                       Management   Investments
                                    (constructio
                                    n of              12         N/A         N/A         N/A         N/A      N/A      N/A
                                    irrigation
                                    systems on
                                    4,000 ha)

                                                       -           -           -           -
                                       Total                                                          -         -       -
                                                   4,512,700   5,087,500   1,428,220   4,610,000
                                                                   -
                                     Total per
                                                   -225,635    254,375.0    -71,411    -230,500       -         -       -
                                       year
                                                                   0
                                    Per hectare     -179.4      -202.3         -           -          -         -       -
                                    Per hectare
                                                      -9         -10.1         -           -          -         -       -
                                     per year




                                                                                                                        132
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