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Options for Mitigation in Agriculture
The document provides an overview of options for greenhouse gas mitigation in agriculture. It discusses: 1) Agriculture contributes significantly to global emissions and reductions are necessary to meet climate targets. Many mitigation practices are compatible with sustainable development goals. 2) Key greenhouse gases from agriculture include methane, nitrous oxide, and carbon dioxide. Soils can also store carbon. 3) Common mitigation practices discussed include alternate wetting and drying of rice fields, livestock management improvements, efficient fertilizer use, agroforestry, and reducing food loss and waste. 4) The EX-ACT tool is introduced as a way to estimate and compare emissions between baseline and project scenarios to identify mitigation opportunities in agriculture
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Options for Mitigation in Agriculture
- 1. ADB Training 9-11October, 2018,Tokyo Options for Mitigation in Agriculture Lini Wollenberg, CCAFS Low emissions agriculture
- 2. Why mitigation inagriculture? 1. Significant • 10-12% of global emissions • Agriculture contributes on average 35% of developing countries’ total emissions 2. Necessary Reductions in other sectors will not be enough to achieve 2 °C and 1.5 °C targets 3. Possible Many practices are compatible with SDGs, hence the possibility of “low emissions development” Mercator Institute Roe et al. 2017
- 3. (1) Agriculture emits3 key greenhouse gases (GHGs) Methane (CH4) Nitrous oxide (N2O) Carbon dioxide (CO2)
- 4. And can storecarbon in plants and soil Above-ground and below- ground biomass Grassland Soil organic carbon Organic carbon
- 5. Units: tons CO2equivalent/yr Oneton of carbon equals 3.67 tons of carbon dioxide CO2e Global warming potential over 100 years • CO2: 1 • CH4: 25x • N2O: 298X 2) Global net CO2e is what matters to the climate
- 6. 3) Two keymetrics for emissions • CO2e per ha • CO2e per kg - “Emissions Intensity” - “Yield-scaled emissions” Used for adding up or comparing emissions for a given area of land Used to show the GHG efficiency of a food product or supply chain. Also called:
- 7. 4) Mitigation isa reduction in emissions Reductions are measured relative to the previous land use or supply chain emissions The reference can be a base year or baseline. A baseline is a projection into the future showing business-as-usual (BAU) emissions. 0 5 10 15 20 25 2015 2016 2017 2018 2019 BAU emissions Reduced emissions GHGemissionstCO2e Reduction in emissions using baseline = 15 tCO2e Base year Increase in emissions of 5 tCO2e
- 8. AFOLU Emissions: agriculture,forestry & land use Agriculture produces GHG emissions of 5.4 GtCO2e/yr (IPCC)
- 9. • Paddy rice- alternate wetting and drying (AWD) • Livestock systems - improving feeding, animal and herd management; pasture management • Cereal crops- building soil organic matter, e.g. through integrated soil fertility management; nutrient efficiency through technologies such as urea deep placement; BNI in crops • Perennial crops- transitioning from annual crops or degraded land to agroforestry, forestry or grassland Existing mitigation options in agriculture • Avoided conversion of high carbon landscapes (forests, peatlands, mangroves, grasslands) • Reduced food loss and waste- storage, packaging, waste recycling • Supply chain energy use – fertilizer production, cooling, transportation • Dietary shifts- shift to low emissions food products, e.g. beef to chicken
- 10. Water management inpaddy rice: Alternate wetting and drying • Reduces CH4 emissions up to 38%. Also reduces fossil fuel use, lodging and pests • Issues: requires farmer control over irrigation, uneven incentives for water-level management, increased weeding, N2O, difficult to verif • IRRI information hub: ghgmitigation.irri.org/
- 11. • Livestock intensification reducesemissions intensity up to 20X for beef, 300X for dairy • Improve digestibility of feed • Reduce numbers of animals 0.00 50.00 100.00 150.00 200.00 250.00 300.00 350.00 400.00 450.00 7.50 8.50 9.50 10.50 11.50 methane-kgCO2/kgproteinproduced metabolisable energy (MJ/kg DM) developed developing BRICS Pastoralist farmers in Chad Herrero et al. 2013, PNAS Livestock intensification US, EU intensive cattle production • Issues: absolute emissions increase, cost of improved feed, cultural barriers, emissions from land use change and feed production, other environmental impacts • Resource: Tackling Climate Change through Livestock www.fao.org/docrep/018/i3437e/i3437e00.htm
- 12. Efficient use ofnitrogen fertilizer • Increasing NUE from 19 to 75%, decreases emissions intensity by 56% (12.7 to 7.1 g N2O-N/kg N uptake) • Increase efficiency of N fertilizer uptake by plants, e.g. timing, rates, deep placement, microdosing • Issues: most smallholder farmers only use small amounts of N, so absolute emissions will increase. • Resource: Site-specific nutrient management https://ccafs.cgiar.org/publications/site-specific-nutrient-management- implementation-guidance-policymakers-and-investors#.W7ZgSC-ZPEY
- 13. Soil carbon sequestration •Agriculture is the major driver of soil carbon loss • But soil C can be managed: e.g. reduced burning, legume intercropping, agroforestry, compost, manure, deep-rooted plants. • Issues: finite, reversible, ambitious potentials, competition for biomass inputs, insufficient other nutrients, MRV costs and detectable changes only after ~20 years.
- 14. Agroforestry • Global reviewshows maximum carbon increases in -Plant biomass in improved fallows: 11 tC/ha/yr -Soil C in silvopastoral systems: 4 tC/ha/yr • Issues: finite, reversible, can conflict with crops, classification as forestry or agriculture, trees on farms often not counted due to scale Feliciano et al. 2018 https://doi.org/10.1016/j.agee.2017.11.032
- 15. Reduce food lossand waste in supply chains Nash et al. 2017 • 10-20% reduction of emissions based on assessment of Feed the Future projects in Asia • Issues: Reduces emissions intensity, but not necessarily total emissions; lack of available data Product Country % Food loss and waste Without project With project Reduction Dairy (cattle) Bangladesh 17 7 10 Maize Cambodia 30 10 20 Bitter gourd " 30 10 20 Cucumber " 30 10 20 Eggplant " 30 10 20 Long bean " 30 10 20 Rice (irrigated) " 20 5 15
- 16. ADB projects andsome mitigation options ADB project examples Location Activity GHG mitigation opportunities HP, India Horticulture LUC C storage in above- ground biomass FLW reduction Storage and transportation? Mongolia Vegetable production LUC N-fertilizer efficiency FLW reduction Cold storage and transportation Tajikistan Dairy LUC Livestock FLW reduction Cold storage and transportation
- 17. 10/23/2018 17 Landscape transitions Crop transitions Rice crops Crops (non rice)Fertilizer Livestock - 4.7M TotalAnnualtCO2e Land use change Agricultural practice improvements Increased emissions Reduced emissions/ increased C sequestration (1,865,626) (905,776) (433,447) (616,320) (32,068) (819,848 ) 435,313 1,723,672 2.1 M Mitigation benefits of USAID’s agricultural development portfolio https://ccafs.cgiar.org/blog/greenhouse-gas-emission-analyses-nine-agricultural-development-projects-reveal- mitigation#.WqrhAGbMzEY 25developmentprojects,15countries,3continents.
- 18. Feasibility Case 1:Developing an investment plan for AWD in Vietnam Comprehensive, comparative analysis of potentially viable LED practices and their supporting interventions within the rice supply chain Geographic suitability Barriers Incentives, enabling conditions Costs, benefits and risk analysis 1. Domestic investment plan for AWD and mid-season drainage 2. Outline for international investment proposal for AWD Policy gap analysis Identification of policy levers to incentivize adoption Quantification of investment needed Identification of international funding sources Investment plan for AWD Prioritize interventions, identify instruments to encourage large- scale adoption Slides courtesy of Tran Van The
- 19. Business case forAWD in Vietnam - 5,000.00 10,000.00 15,000.00 20,000.00 An Giang Kien Giang Soc Trang Average Costs (1000 VND/ha/season) AWD None - 10,000.00 20,000.00 30,000.00 An Giang Kien Giang Soc Trang Average Net benefit (1000 VND/ha/season) AWD None 30,000.00 35,000.00 40,000.00 45,000.00 An Giang Kien Giang Soc Trang Average Revenue (1000 VND/ha/season) AWD None
- 20. Suitability maps formitigation practices and planning finance
- 21. Key points 1. Manyoptions: Opportunities for mitigation occur via agricultural practices, land use change, supply chain or shifts in diet preferences Best practices for mitigation: - Seek absolute reductions where possible (e.g. AWD) - Elsewhere at least improve GHG efficiency (emission intensity) - Offset emissions with C sequestration - Work at all scales 2. Agricultural development can yield significant climate change mitigation co-benefits 3. Actions are already being taken to plan and implement mitigation at large scales where net benefits occur
- 22. CCAFS Flagship LowEmission Development https://ccafs.cgiar.org/flagships/low-emissions-development Thank you! Lini.wollenberg@uvm.edu ccafs.cgiar.org
- 23. Feasibility Case 2:Private drone companies help scaling out of technologies for better N fertilizer management • 3 drone companies delivering N recommendations to maize farmers in Mexico using NDVI from their drones and an algorithm. • Farmers are willing to pay for this service (approx. 3 USD / ha per flight). • N saving of ca. 60 – 70 kgN/ha
- 24. ADB Training 9-11October, 2018,Tokyo An introduction to the EX-ACT Tool Lini Wollenberg, CCAFS Low emissions agriculture
- 25. What is theEX-ACT Tool? Ex-Ante Carbon Balance Tool developed by FAO • Compares net emissions with and without a project • Intended for planning, not assessment or verification How does it work? • A set of linked Microsoft Excel sheets • Structured as 8 modules reflecting land use and management practices • Compares baseline, project and BAU scenarios • Covers emissions and C sequestration, in CO2e/ha/yr • Uses IPCC default (Tier 1) or user can specify region-specific emission values (Tier 2) • Available in 4 languages • Simple supply chain calculation possible
- 26. On-line course availableon World Bank Site • https://olc.worldbank.org/content/estimating-ghg-emissions-and- carbon-sequestration-agriculture-forestry-and-other-land-use-ex
- 27. Estimating emissions Emissions =Activity x Emissions Factor IPCC default EF’s are based on global or regional average values Ex. Nitrous Oxide = Annual amount of synthetic fertilizer N applied to soils, kg N yr-1 x 1% Guidance from IPCC 1996 and 2006 guidelines:
- 28. Tier 1 EmissionFactors Default emission factor provided by the IPCC. Usually regional or global. Tier 2 Emission Factors More complex and country-specific emission factor. Not usually available in low income countries. Tier 3 Emission Factors Most complex, often modeled. See also the IPCC Emissions Factor Database https://www.ipcc- nggip.iges.or.jp/EFDB/ Example of IPCC Tier 1 defaults in Good Practice Guidelines Tiers: Specificity of estimates
- 29. Poor accuracy ofGHG calculators using Tier 1 emissions Comparison of Cool Farm Tool and Ex-Act Tool results against measurements in tropical agriculture. Default emission factors lead to over-prediction of emissions. • Dashed line is a 1:2 line; data points above this line represent an overestimation by a factor of 2 or more. • Solid line is a 1:1 line; data points above this line represent an over- estimation of GHG emissions by the calculator. Richards et al. 2016 https://dx.doi.org/10.1038/srep26279
- 30. Calculators using TierI emissions don’t even predict well whether emissions have increased or decreased 30 Richards et al. 2016 https://dx.doi.org/10.1038/srep26279 Change in GHG emissions due to an intervention Incorrect calculator predictions (opposite direction of change than measured observations) EX-ACT underestimated emissions in a significant number of cases
- 31. 1. Complete “Description”module Using EX-ACT Download: www.fao.org/tc/exact/carbon-balance-tool-ex-act. Total time period should not be less than 20 years if carbon sequestration is expected.
- 32. 2. Build scenarios Threescenarios required 1. Start: Initial conditions 2. Without: Baseline showing expected conditions without the project (business-as- usual) 3. With: Conditions with project intervention
- 33. 2. Build scenarios(cont) “With” scenario (with project) Identify expected changes Identify dynamic of changes over time • “Without” scenario (baseline) Defined as would have happened without the project. This is what EX-ACT compares project results against. Options: − No change from initial conditions (simplest, and likely to be most common) − Extrapolation of past trends − Modeling of future trends
- 34. 3. Choose relevantmodules to complete
- 35. 4. Collect activitydata for each land use and practice, for each scenario Estimate areas (ha) of land use change and changes in management practices • Can use expert judgement, project planning documents, national statistics, focus groups, primary data collection etc. Quality affects results. • Most time consuming stage, especially to produce relevant scenarios
- 36. Example of module:Land use change (LUC) Navigation bar for modules Data entry required in light blue cells; not all cells must be completed
- 37. Land use change(cont): Deforestation
- 38. Example of module:Annual crops Areas continuously managed as annuals. Enter names of additional cropping systems. Areas converted to annuals: Prefilled based on Land Use module Dynamics of intervention: immediate (default), linear or exponential
- 39. Remember • Complete Descriptionand then only relevant modules • Provide data for all three scenarios (start, without, with project), remembering that some land uses will be relevant to only one scenario (e.g. baseline or project) • Normal for many cells or modules to be left blank • Scroll down and across so you don’t miss modules, links, etc. See user guidelines: http://www.fao.org/tc/exact/user-guidelines/en/ Quick, complete and technical guidance available
- 40. CO2e Reminder: Global netCO2e is what matters Be careful about project “leakage,” increases in emissions elsewhere
- 41. Tips • “Help” tabprovides soil, climate and ecological zone classifications; see additional resources here by scrolling to the right • Additional information and options are located throughout the tool in the form of orange buttons: e.g. look-up tables, value chain calculations, uncertainty information, land use change matrix • All calculations are based on IPCC guidance, so you can look up assumptions if not available in Ex-Act documents. Example of assumption: Changes in carbon sequestration are calculated over 20-year time period and annualized. • In some cases FAO can “unlock” pages for you if you need to customize calculations
- 42. EX-ACT Exercise (20minutes) • Working in teams of 2-3 people, complete description module and one to two other modules • Can make up data, but try to be realistic Identify 1. Net change in emissions/ha/yr as a result of your project 2. Uncertainty of your estimate 3. Largest contributing: Source of emissions (“component”): Type of GHG: 4. Resulting emissions intensity (or at least where the calculation option appears) 5. Value chain results (or at least where calculation option appears)
- 43. Relevant EX-ACT links •EX-ACT home page: http://www.fao.org/tc/exact/ex-act-home/en/ • EX-ACT tool Version 7: http://www.fao.org/fileadmin/templates/ex_act/excel/EX-ACT- v7.2.xlsx • Quick guide: http://www.fao.org/3/a-i8075e.pdf • Comprehensive user guide: http://www.fao.org/fileadmin/templates/ex_act/pdf/Technical_guideli nes/EX-ACTUserManuaFinal_WB_FAO_IRD.pdf • Translations and other guidance: http://www.fao.org/tc/exact/user- guidelines/en/ • World Bank on-line course https://olc.worldbank.org/content/estimating-ghg-emissions-and- carbon-sequestration-agriculture-forestry-and-other-land-use-ex
- 44. CCAFS Flagship LowEmission Development https://ccafs.cgiar.org/flagships/low-emissions-development Thank you! Lini.wollenberg@uvm.edu ccafs.cgiar.org
- 45. Negative emissions neededto limit warming below 1.5 or 2 °C Roe et al. 2017 How Improved Land Use Can Contribute to the 1.5°C Goal of the Paris Agreement
- 46. IPCC emissions factorsand uncertainty levels Emissions source Range of emissions factors for developing country (warm wet/warm moist conditions) Unit Uncertainty/error for Tier 1 emissions factors Biomass C storage 12 to 228 t C/ha/yr 6-126% Biomass C loss with harvest 9 to 50 t C/ha every 5 - 8 years 75% Relative stock change in soil C 0.48 to 144 t C/ha/yr 26% (7 - 61%) Land conversion 1.8 to 10 t C/ha/yr 75% N2O fertilizer 0.01 kg N2O-N/kg N .003 - .30 CH4 Paddy rice 1.3* kg CH4/ha/day 62-169% CH4 Enteric fermentation - dairy cattle 46 to 72 kg CH4/ha/day 30-50% CH4 Enteric fermentation -other cattle 27 to 56 kg CH4/ha/day 30-50% CH4 Enteric fermentation -other 1 to 55 kg CH4/ha/day 30-50% CH4 manure 1 to 2 kg CH4/head/year 30% N2O urine 0.32 to 1.57 kg N/1000Kg animal mass/day 50% *if scaling factors used, ranges from 0.35 to 1.34
- 47. Agricultural greenhouse gassources and sinks Percent of agricultural emissions (IPCC AR4 2007)
- 48. Sources: Bernoux etal. 2012 Scale: + indicates <1 day, ++++ indicates >1 month Geographi c scope Intended scale of calculation Time and data requiremen ts User input EFs Scenarios Uncertain ty estimates EX-ACT World Landscape + Yes Initial, BAU, project Yes, for EFs Cool Farm Tool World Farm ++ In excel versio n Yes, with different tool runs No USAID AFOLU Calculator Developing countries Landscape + No In different runs No ALU World Landscape ++++ Yes No Entered by user Carbon benefits project World Landscape +++ Yes Initial, BAU, project Yes
- 49. Precision example: N2O calculationmethodology EX-ACT IPCC default 1% of applied N or user-defined Cool Farm Tool Bouwman model: accounts for N-rate*Fertilizer type interaction, crop type, soil texture, SOC, soil drainage, soil pH, climate type USAID AFOLU Calculator IPCC default EFs, specific to fertilizer type ALU IPCC default EFs Carbon benefits project Range: IPCC Tier 1 defaults or user-defined
- 50. Ex-Act calculates throughcapitalization phases. Build scenarios (cont)
Editor's Notes
- #2 What are the most important terrestrial carbon sinks? What might be the most efficient terrestrial carbon sinks for managing climate change mitigation? What might be the best manageable sinks? What are good and realizable approaches/ management options for those sinks? What are cost-efficient approaches? What are relevant financing options and mechanisms? What are practically applicable MRV options? What should be policy priorities for managing of terrestrial carbon sinks for climate change mitigation? How is the climate change mitigation objective for terrestrial carbon sinks aligned with country policies and Intended Nationally Determined Contributions (INDCs)? What are the challenges to align the climate change mitigation objective for terrestrial carbon sinks with other development priorities such as biodiversity conservation, improving agricultural productivity, increasing food security, eliminating poverty, etc.? Forests as terrestrial carbon sinks: Conservation of forests including IFL Forest management Afforestation/Reforestation Soils as terrestrial carbon sinks: Preservation and restoration of peat soils and grasslands Restoration of degraded soils and avoidance of soil degradation Agricultural land management and agro-ecological approaches (conservation agriculture, agroforestry, etc.) (Other Intertwining concepts and landscape approaches (e.g. forest landscape restoration)) Scientifically based overview of terrestrial carbon sinks and their potential MRV (measuring, reporting and verification) system for terrestrial carbon sinks and connected challenges
- #3 49Gt CO2e 2010 global emissions (chk) needs to go down to 42 by 2030. GCB target: The target assumes an allowable emissions budget of 6.15–7.78 GtCO2e yr 1 for agriculture in 2030 (Table 1). The goal represents an 11–18% reduction relative to the scenarios’ respective 2030 business-as-usual baselines. The goal would contribute ~4–5% of the 26 GtCO2e yr 1 in mitigation needed across all sectors in 2030 to achieve the 2 °C limit; business-as-usual emissions for all sectors in the same year are ~68 GtCO2e As a target for 2030, this is a near-term goal only. The scenarios show that the contribution of agriculture would need to increase in 2050 to 2.51 GtCO2e (IMAGE) and 2.63 GtCO2e yr 1 (GCAM), reaching a maximum of 2.91 GtCO2e yr 1 in 2070–2080 using IMAGE and 4.20 GtCO2e yr 1 in 2100 using GCAM
- #6 One simple indicator: global CO2 in gigatons, gG, Tg, etc. Estimating mitigation that is meaningful for climate change requires more than metrics. Requires a systematic approach to assess emissions per ha and additionality and leakage: e.g., baselines (historical, averages across multiple years, projections); GWP is IPCC official number for 2013 to 2020 Duration in atmosphere CO2 lasts 1000s yrs N2O 100 yrs CH4, 10 yrs
- #7 Usually in tons or kg
- #9 5.4Gt CO2e/yr annual emissions
- #11 (also called intermittent flooding/drainage, single/multiple drainage) The practice of AWD on the farm n At about two weeks after transplanting, the field is left to dry out until the water level is at 15 cm below the soil surface. Then, the field is flooded again to a water depth of approximately 3–5 cm before draining again. This irrigation scheme is repeated except during flowering time, when the field is maintained at a flooded water depth of 3–5 cm. The number of drainages and the number of days that the field is non-flooded will vary. n A drainage level of 15 cm is called “safe AWD” because this level will not cause a yield decline (see Further Reading). Farmers monitor the water level in the field using a field water tube—a 30-cm length of 15-cm diameter plastic pipe or bamboo, with drilled holes, which is sunk into the rice field until 10 cm of it protrudes above soil level. This has been effective in assuring farmers that the rice plant is accessing water even when there is no standing water in the field. Once AWD has become established, the tube is often dispensed with and farmers base the decision to irrigate on soil monitoring. n Proper leveling of rice fields is necessary to ensure that no areas are excessively dry or wet, which could adversely affect yields. Laser landleveling may be appropriate in some farming systems. n Weed management is important, as periods of drying can encourage weed growth. Maintaining flooded conditions until around 2 weeks after transplanting discourages the growth of weeds while the rice plant becomes established. AWD technology can reduce the number of irrigations significantly compared with the farmers’ practice, thereby lowering irrigation water consumption by 25% and, in some cases, reducing fuel consumption for pumping water by 30 liters per hectare.
- #14 – estimated total global loss of 133 Gt C (488 Gt CO2e) (Sanderman et al. 2017)
- #15 In t CO2, average is ~ 18 t CO2 for average AGB in tropics, 8 t CO2 for soil average Rule of thumb: ½ biomass is carbon Average increase in carbon - tropical climate -Plant biomass: 4.85 tC/ha/yr -Soil C: 2.23 tC/ha/yr
- #18 Turning to mitigation, We can also ask whether intensification and increasing productivity can achieve mitigation goals, CCAFS, working with FAO, examined the mitigation co-benefits of IFAD and USAID’s agricultural investment portfolios. This figure shows the USAID analysis, for 25 diverse agricultural development projects and several dozens of practices across 15 countries in 3 continents. You can see that across the entire portfolio,blue is negative emissions, yellow is positive, that ag investments resulted in substantial net mitigation co-benefits, 2.6 MtCO2e/yr. Looking at interventions across categories you can see that the major source of emissions was livestock and secondarily fertilizer use, but that this was offset by land use change and rice and crop management. So current trajectories of agricultural development can yield substantial mitigation co-benefits, especially when considered at the larger portfolio level. That is the good news… ****** Landscape and crop transitions 1) Landscape transitions- Within the agricultural development projects, project interventions focused on both avoided land conversion (avoided change from forest) and active land conversion (agricultural or degraded lands changed to forest). 2) Crop transitions- This area include transitions to perennial crops or agroforestry. Also transitions from flooded rice systems to other crops such as wheat. Transitions land into irrigated rice. (Check why 5802 in positive) Management practice improvements 1) Rice crops- AWD, UDP, Short Duration Rice 2) Crops- Soil, manure, and water management improvements- also includes crop residue burning reduction and perennial management. 3) Fertilizer- increases and decreases 4) Livestock- herd size management, feed quality and breeding improvements. Grassland increases. With better feeding practices and increases in cow weight comes increased emissions.
- #19 CCAFS is now collaborating with a number of countries, including Vietnam, Colombia and Kenya to implement their NDCs. Vietnam for example, according to their NDC plans to implement alternate wetting and drying or mid season drainage in 1.7 mil ha We are supporting comparative analysis of options for reducing emissions and the development of an investment plan to provide the basis both for policy change and investment in scale-out (at the national level) and submission of proposals for climate finance. In Kenya we supported similar work. In Columbia we have supported modeling emissions usingthe RUMINANT model and the development of better emission factors. Important lessons are being learned from these experiences that we hope can inform NDCs and pave the way for other countries to also be successful.
- #20 Investment plan for AWD should be implemented for 900 thousand hectares, contribute in 10.97 million tCO2e, produced added net benefit of 8,540 billion VND (371.36 million US$/yr.) as compared to conventional rice cultivation in 2030. 2017-2018 data and analysis
- #24 Adresses rate, not timing source or placement
- #25 What are the most important terrestrial carbon sinks? What might be the most efficient terrestrial carbon sinks for managing climate change mitigation? What might be the best manageable sinks? What are good and realizable approaches/ management options for those sinks? What are cost-efficient approaches? What are relevant financing options and mechanisms? What are practically applicable MRV options? What should be policy priorities for managing of terrestrial carbon sinks for climate change mitigation? How is the climate change mitigation objective for terrestrial carbon sinks aligned with country policies and Intended Nationally Determined Contributions (INDCs)? What are the challenges to align the climate change mitigation objective for terrestrial carbon sinks with other development priorities such as biodiversity conservation, improving agricultural productivity, increasing food security, eliminating poverty, etc.? Forests as terrestrial carbon sinks: Conservation of forests including IFL Forest management Afforestation/Reforestation Soils as terrestrial carbon sinks: Preservation and restoration of peat soils and grasslands Restoration of degraded soils and avoidance of soil degradation Agricultural land management and agro-ecological approaches (conservation agriculture, agroforestry, etc.) (Other Intertwining concepts and landscape approaches (e.g. forest landscape restoration)) Scientifically based overview of terrestrial carbon sinks and their potential MRV (measuring, reporting and verification) system for terrestrial carbon sinks and connected challenges
- #26 Developed by WB, FAO and IRD
- #29 http://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/4_Volume4/V4_05_Ch5_Cropland.pdf
- #30 https://dx.doi.org/10.1038/srep26279 We do have emission factors based on data from temperate areas, but those aren’t great for the tropics Because of this dearth of information, most developing countries quantify ag emissions using Tier 1 emissions factors, which are calibrated to data from developed temperate countries, with conditions dissimilar to the actual conditions in the tropics This gives us an inaccurate picture of actual emissions or mitigation potentials in tropical developing countries What we found is that the calculators tend to overestimate emissions- EX-ACT was only slightly more likely to overestimate as to underestimate emissions (54% of cases) Comparison between measured and calculator-predicted soil fluxes for N2O, CH4, and the net balance (CO2e). The solid line is a 1:1 line; data points above this line represent an over-estimation of GHG emissions by the calculator. The dashed line is a 1:2 line; data points above this line represent an overestimation by a factor of 2 or more.
- #31 Change in GHG balance between control and alternative management practices (e.g. continuous flooding vs. multiple drainage in rice). Points in the upper right and lower left quadrants represent cases where the calculator predicted the same direction of change as observed in the field study. Points in the lower right and upper left quadrants represent cases where the calculator predicted the opposite direction of change as observed in the field study.
- #32 One reason for using implementation and capitalization phases in EX-ACT is to enable 20 year phase for accounting for C accumulation
- #34 Most projects will have only 2 scenarios: baseline (initial conditions) and project
- #36 Data collection using expert judgement, project documents, key respondents, observation or resources in Ex-Act
- #39 See http://www.fao.org/fileadmin/templates/ex_act/pdf/Technical_guidelines/EX-ACTUserManuaFinal_WB_FAO_IRD.pdf for more detail
- #41 One simple indicator: global CO2 in gigatons, gG, Tg, etc. Estimating mitigation that is meaningful for climate change requires more than metrics. Requires a systematic approach to assess emissions per ha and additionality and leakage: e.g., baselines (historical, averages across multiple years, projections); GWP is IPCC official number for 2013 to 2020 Duration in atmosphere CO2 lasts 1000s yrs N2O 100 yrs CH4, 10 yrs
- #43 Discussion Comprehensive, but very coarse High sensitivity to parameters Data quality only as good as your input Where can you find Tier 2 inputs? Time consuming to do input Cannot compare more than one project Limited number of zones N-fixing plants or residue N not included; cannot leave residues on field
- #47 Numbers need checking High variability, nonadditive effects and uncertainties of 10 to 150% (compared to 10-15% for CO2 from fossil fuels)
- #49 CBP provides a range of modules: simple assessment (only requires knowing land use changes) Detailed assessment module (requires specific information on crop/grass/forest species and systems, improved emission factors, Resources and facilities for field sampling and lab analysis) Dynamic modeling option (requires use of GIS and data for model paramaterization) CBP can provide both ex-ante and ex-post analysis