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CCAFS Low emissions development (LED) activities funded by USAID

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Presentation by Lini Wollenberg, Low Emissions Development Flagship Leader at USAID offices in Washington
September 24 2018

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CCAFS Low emissions development (LED) activities funded by USAID

  1. 1. Lini Wollenberg, CCAFS Low Emissions Development Flagship September 24, 2018 An update on CCAFS LED Activities funded by USAID
  2. 2. Stock-taking Tracking NDC commitments https://cgspace.cgiar.org/handle/10568/73255
  3. 3. USAID support 2016-2018 Towards implementation of mitigation • Scholarship program for graduate students to quantify emissions in food loss and waste • Livestock MRV  Tier 2  RUMINANT model • Agroforestry MRV 3. CLIFF-GRADS Fellowships 1. MRV 2. NDC support Feasibility and investment assessments • Vietnam • Kenya
  4. 4. 1 MRV of Livestock emissions Collaboration with UNIQUE Forestry, GRA and FAO • Review of MRV practices: report and workshop (2017)* • Compilation of practices, in progress (to be completed 2018) • MRV Resource Platform (2018) • Activity gap filling guidance, workshop (2018)* and report (2019) *USAID supporrted
  5. 5. Why improve MRV of livestock emissions? • 92 developing countries included livestock emissions in their NDCs • Yet most developing countries use Tier I approaches that generally do not capture mitigation • Most countries are still designing MRV for mitigation of livestock emissions Source: Wilkes et al. 2017
  6. 6. 1.1. Review of country practices (2018) 1. What are current MRV practices for livestock emissions? 2. What are the barriers and opportunities for improvement? Reviewed data for 140 developing countries; conducted interviews with 20+ countries Wilkes et al. 2017 French and Spanish versions also available
  7. 7. Survey results on IPCC criteria for MRV: Transparency, consistency, comparability, completeness and accuracy (TCCCA) • Moderate transparency: Only 99 reported activity data used, 117 reported emissions factors used. • Completeness– Good for CH4 (139 parties reported enteric fermentation, 134 manure management CH4); moderate for N20 (115 parties manure and 116 for soil). • Good comparability- all used IPCC guidelines • Moderate consistency: 82 used consistent time series, 37 parties were inconsistent. 21 reported one year only • Low accuracy - 119 out of 140 developing countries (85%) used Tier I For Tier 2 users, 16 parties did not update emission factors; only 5 used updated emission factors 89 parties - no analysis of uncertainty
  8. 8. Activity data: Gaps and mixed data sources Wilkes et al. 2017
  9. 9. Chile Colombia Ethiopia Indonesia Philippines Vietnam Human resource allocation to inventory work   Institutional structures for inventory related research   Weak links with national data providers (e.g. statistics agencies)     Lack of data on diverse farm conditions   Limited capacities for Tier 2 research   Sustainability of finance for inventory agencies  Finance for activity data collection or emission research     Practical constraints to inventory improvement
  10. 10. 1.2 Activity Data: expert workshop Hague July 2018 • Shifting to Tier 2 requires regularly updated activity data that most developing countries do not yet collect • Demand for guidance for NDC and MRV developers on practical methods for estimating activity information
  11. 11. Country needs for activity data What? • Tier 2 and NDCs, but basic Tier 1 data gaps also exist (e.g. population stocks, age bands) • Definitions / characterization of systems • Core variables: population, live weight, weight gain, milk yield,diet, manure management systems • Dynamic and relevant to developing country conditions: - Regularly updated activity data for different production systems - Reflect reduced emissions (BAU scenarios) - Seasonality Guide to be completed by June 2019.
  12. 12. • RUMINANT will allow Colombia to use separate emission factors for different livestock production systems, which emit according to their productivity and efficiency. • This allows the inventory to capture mitigation effects, which is necessary for MRV of Colombia’s livestock NAMA. • By moving to an advanced inventory methodology, Colombia has achieved the level of MRV rigor necessary to attract climate finance for its NAMA. 1.3 Use of RUMINANT model to estimate methane emissions from livestock in Colombia (1) Photo: N Palmer, CIAT
  13. 13. • The RUMINANT model is a “Tier 3” approach to estimate methane (CH4) from enteric fermentation in livestock. • RUMINANT was validated for CH4 emissions from livestock in the tropical lowlands (Cauca Valley) for seven diets. • Good correlation observed between measured (polytunnel) and RUMINANT CH4 estimates. Use of RUMINANT model to estimate methane emissions from livestock in Colombia (2) Comparison between measured enteric methane emissions (solid circles) to those simulated by RUMINANT model (open circles).
  14. 14. 2. MRV of Agroforestry IPCC guidelines note that trees outside forests “should be included when they are a significant component of total changes in biomass stocks”(IPCC 1996, 5.13). • Yet agroforestry is often difficult to detect due to small land areas, unclear or overlapping institutional mandates, multiple land use classifications, and a lack of dedicated programs to build capacity or collect data. . Review Methods • Review of UNFCCC documents NCs (N=147), NDCs (N=147) REDD+ strategies (N=73) and NAMAs (N=264). • Interviews of key informants in 12 countries.
  15. 15. Agroforestry MRV- country needs Key findings • 40% of developing countries (59/147) proposed agroforestry in NDCs. • Highest interest in Africa (71%),then Americas (34%), Asia (21%) and Oceania (7%). • 71% (105/147) National Communications mentioned agroforestry or interventions that could include agroforestry. • 79% (42/53) countries with REDD+ explicitly included agroforestry in REDD+ efforts Source: Rosenstock et al. in press
  16. 16. Agroforestry MRV- reporting (1) 1. Countries overwhelmingly use Tier 1 approaches to quantify carbon stocks and carbon stock changes in the LULUCF sector (84%, 95/113 countries’ NCs) 2. Only 18 countries reported using some Tier 2 approaches. 3. REDD+ countries often use a mix of tiers when estimating forest carbon baselines 4. Representation of land uses at appropriate resolution is a precondition for the application of more accurate carbon stock change estimate
  17. 17. 5. Agroforestry that meets forest definitions more likely to be captured in reporting. • Relatively few countries provided a quantitative estimate of the carbon in non-forest trees in the inventory. 16 countries gave a quantitative estimate of either: • the number of trees (e.g. 300,000 trees in Nepal to 405,104,918 trees in Niger) or • the areal extent of trees outside forests (e.g. 250 ha in Nauru to 2.2 million ha in Tunisia). 6. Agroforestry in GHG inventory reports, still overall lacking • elaboration of woody biomass types and • presentation of subcategories of land-use types and GHG removal sources in supplementary tables. Agroforestry MRV- reporting (2)
  18. 18. Constraints and enabling conditions for MRV of agroforestry Rosenstock et al. In press.
  19. 19. Agroforestry MRV: National case studies in Vietnam and Colombia  Developed estimates of C benefits of agroforestry and costs for implementation for Vietnam’s revision of the Nationally Developed Contribution (final revision scheduled March 2019).  In Colombia, defined a pathway for integrating and monitoring tree- based systems, with a specific focus on agroforestry, under the developing Forestry NAMA. With the Colombia Ministry of Environment (MADS) and IDEAM (the institute responsible for GHG MRV).  Made technical recommendations for trees on farms definitions and technical input for the construction and definition of categories  Piloted use of cost-effective way to identify lands including agroforestry using ‘Collect Earth’ (cheap, crowd sourced, Google Earth Engine) in both Vietnam and Colombia. Results were positive, but challenges remain.
  20. 20. 3. Support for Countries’ NDCs Feasibility of rice LED options and 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
  21. 21. 3.1. Policy gap analysis o In policy development & implementation: Ambitious targets and limited financial resources (domestic, international support, private); especially for infrastructure, irrigations system; o Linkages and collaboration: Poor linkages in policies (inter-regional linkages, multidisciplinary; project to project); o Capacity building: Limited knowledge, readiness from local and private stakeholders in GHG reduction (LEDs); o Economic benefits vs social, environment and politic benefits: Low benefits and low or no support for private sector rice production o Performance and scaling: Good performance/test but lack esources for replication o Land tenure and large farm model: Slow moving land use policy for rice for investment 3. Results Slides courtesy of Tran Van The
  22. 22. 3.2. Policy levers for AWD in rice production 3. Results GHG mitigation on rice production GHG mitigation project (3119/BNN- KHCN, 2011) National green growth strategy and action plan ( 1393/QD- TTg, 2014) Action plan to response to climate change in agriculture (819/QĐ-BNN- KHCN, 2016) INDC (2015) Plan to implement NDC in agriculture (7028/BNN- KHCN, 2016) Restruc- tured rice project (1898/QD- BNN, 2016) AWD YY N N YYY Y YY SRI YY N N YYY Y YY ICM YY Y Y YYY Y Y MSD N N N YYY N - Compost YY Y Y YYY Y - Reduced nitrogen by SA YY N N YYY Y Y Biochar Y N N YYY Y - Slides courtesy of Tran Van The
  23. 23. 2.3. CBA on AWD in MRD 3. Results - 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
  24. 24. 4. Support for Countries’ NDCs Feasibility of livestock LED options and investment plan in Kenya and Ethiopia (Ericksen, using Dickhoefer et al., 2014)
  25. 25. Improving feed quality to reduce emissions intensities: Improvements in feed quality to increase productivity • Supplemental fodder from improved forage species – Mixed crop-livestock. (26-28% reductions in emission intensities for lactating cattle Opio et al 2016) • Supplemental feeding with concentrates –dairy (20- 27% reductions in dairy, Opio et al.) • Managed grazing – extensive pastoral (similar to improved feed quality?) • Analyzed profits to be made at farm level, based upon data collected from field visits with farmers in five counties. • Evaluated requirements for investment in a project to support yield positive returns over a five-year time span Source: Polly Ericksen, ILRI and John Kashangaki, SBA Africa Ltd 2018
  26. 26. Summary of findings: change in milk yield and monthly profit margin County Milk production per cow (kg/litres) with fodder Change in daily milk yield Profit margins with fodder intervention (KES) Change in monthly profit margins Worst case Best case Worst case Best case Murang’a 7 20 186% 16,158 33,558 108% Nyeri 6 15 150% 16,383 23,883 46% Uasin Gishu 6 15 150% 9,043 22,223 146% Kiambu 12 22 83% 53,267 63,800 20% Nyandarua 5 13 160% 7,625 23,158 204% Average 7.2 17 146% 20,495 3,325 105% Source: Polly Ericksen, ILRI and John Kashangaki, SBA Africa Ltd 2018
  27. 27. Estimated project costs
  28. 28. Fodder production can generate greater revenue and reduce emissions • Both milk yields and profit margins improve • GHG emissions intensities can reduce • 8 to 24% (FAO and NZAGGRC) or up to 0.46 metric tons CO2 equivalent with conservative adoption rates. • Brandt et al suggests reductions up to 26- 31%, if combine forages with concentrates Source: Polly Ericksen, ILRI and John Kashangaki, SBA Africa Ltd 2018
  29. 29. Call for Food Loss and Waste Proposals https://ccafs.cgiar.org/sites/default/files/career/attachments/CLIFF- GRADS%20call%20for%20applications%20FLW%202018-2019%20final_0.pdf
  30. 30. Conclusions: Where are countries in preparedness for mitigation? (1) MRV 1. MRV systems for livestock and agroforestry are moderate to weak, but seem to be heading in the right direction  Livestock emissions accuracy is a concern, but many moving to Tier 2. Sensitivity to pasture feeds’ mitigation impact is possible with Tier 3. N2O needs attention.  Agroforestry- increasingly visible, especially on forest lands; trees on farms are gap. Address resolution of scale as precondition for activity and emission factor data. Guidance needed??  Some countries are ahead, so learning can be accelerated with exchange. Need multi-country leadership 2. Biggest need is access to activity data: linkages among statistical systems is essential; remote sensing; crowdsourcing; include supply chains. 3. UNFCCC reporting drives institutional incentives for action, and institutional actors are clear. Strong impact pathway. 4. Need for multiple country leadership
  31. 31. Conclusions: Where are countries in preparedness for mitigation? (2) Feasibility and investment planning 1. Strong evidence for profitability and incentives for both AWD in rice and improved livestock fodder; although returns relative to other sectors not analysed. 2. But business and investment cases are messy, based on limited data and understanding, no consistent method 3. Feasibility and investment were highly focused spatially in intensive production areas, suggesting these might also be focal areas for MRV and investment case development. 4. Impact pathway is less clear given need for multiple actors and ministries; complex and competitive climate finance environment, gap between research and implementation. How to strengthen this?
  32. 32. https://ccafs.cgiar.org/flagships/low-emissions-development https://ccafs.cgiar.org/our-work/capacity-enhancement#.W5bZ1i2B3EY CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) Thank you!
  33. 33. Interventions to reduce emissions intensities • Manure management • Biodigesters for methane capture – (zero grazing) dairy • Manure storage in covered heaps – mixed crop-livestock
  34. 34. Interventions to reduce emissions intensities • Improved animal husbandry • Reduce chronic disease burden of intestinal parasites – all systems • Reduce age at slaughter – pastoral systems
  35. 35. Cross Cutting Themes • Degree of market orientation is major precondition for upgrading • Even with market orientation, low milk prices inhibit investment in upgrading • Small land size as major limitation • Low trust and accountability of input services
  36. 36. Improved Forages • Barriers  Low availability of land (B) – paddocks?  Diversified cropping strategies (M, I?)  Low accessibility of improved planting material (M) • Potential incentives?  Field trials to improve farmer awareness  Investments to stimulate fodder seed  Financial evaluation of specialization vs diversification • NB: AI and dairy meal become more attractive when basal diet improves
  37. 37. Biodigestors • Barriers  High upfront cost (M)  Maintenance requirements (I)  Slurry transport (B) • Incentives  Household energy source (direct benefit)  Improved household health (direct benefit)  Farmer innovation on slurry transport  ?
  38. 38. Managed Grazing in Rangelands • Barriers  Require high institutional governance capacity (O)  Expansive landscape commitment (O,B)  Long time horizon to see substantial carbon sequestration effects (B) • Incentives  Improve market access to drive intensification  Couple with improved herd management and health
  39. 39. Interventions to reduce emissions intensities • Improvements in Feed Quality to increase productivity • Supplemental fodder from improved forage species – Mixed crop-livestock • Supplemental feeding with concentrates – dairy • Managed grazing – extensive pastoral
  40. 40. Interventions to reduce emissions intensities • Manure management • Biodigesters for methane capture – (zero grazing) dairy • Manure storage in covered heaps – mixed crop-livestock
  41. 41. Interventions to reduce emissions intensities • Improved animal husbandry • Reduce chronic disease burden of intestinal parasites – all systems • Reduce age at slaughter – pastoral systems
  42. 42. Domestic investment plan for AWD Policy gap analysis Quantification of investment needed Consultation with finance experts; Identification of international funding sources Feasibility analysis on AWD (separated study): • Geographic suitability • Barriers to adoption • Identify incentives and enabling conditions to encourage large-scale adoption Identification of policy levers to incentivize adoption Analysis of costs, benefits and risks 2. Methodology
  43. 43. 2. Methodology Province AWD Convention An Giang 40 20 Kien Giang 40 20 Soc Trang 40 20 Total 120 60 Costs and benefits determination Field data collection CBA application Cost efficiency calculation MAC Estuimated abatement rate of GHG (tCO2eha-1) Potential scale analysis (ha) Estumated abatement optential of GHG (M. tCO2e) Reculate cost effectives (CE) and abatement potential Sensitive analysis and scenario (low, medium and high) Sample taken from field survey MAC applied to determine cost of GHG reduction on rice RRA and PRA for data collection SWOT, bottleneck analysis Slides courtesy of Tran Van The
  44. 44. 6 4 Argentina • 8 agro-ecological and climatic regions • Breeding and fattening systems identified/region • Production systems modeled (activity, diet, reproduction and production) • Aggregate results cross-checked against regional, census and agricultural production data. Bolivia • 3 climatic regions (altiplano, valles and tropics) • Cattle and sheep sub-classes (e.g. dairy cattle, non-dairy cattle, young cattle and oxen) using expert opinion in region. • Data on feed rations, apparent digestibility of forage and feed and other production data (e.g. milk yields, live weights)/region obtained from publications or government agencies. Diverse structures for Tier 2 classification
  45. 45. RECOMMENDATIONS 6 5 1. Consider updated Tier 2 approaches using activity and livestock production data that reflect changing livestock systems and their productivity 2. Improve synergies among statistical systems, other livestock data systems and MRV 3. Share country experiences on priorities for livestock MRV system development 4. Develop methods for addressing gaps in activity data

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