Food, poverty and climate change mitigation, including land use perspectives
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Presentation by Lini Wollenberg (CCAFS) at Wageningen University And Research Centre, June 2016 Focus on increasing food security in the face of climate change while also reducing climate impacts
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Food, poverty and climate change mitigation, including land use perspectives
- 1. Lini Wollenberg, CCAFS Low emissions agriculture Land Use Perspectives and Climate Change Mitigation, WUR 2016 Food, poverty and climate change mitigation
- 2. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part
- 3. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part
- 4. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part Why bother to mitigate agricultural emissions? …especially if we have to solve food and climate vulnerability problems at the same time?
- 5. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part CGIAR Research Program on Climate Change Agriculture and Food Security (CCAFS) Mission: Increasing food security in the face of climate change while also reducing climate impacts Includes adapatation and mitigation • 15 CGIAR centers • 200 + scientists in 20+ countries • Plus partner organizations, including Wageningen University
- 6. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part LivestockPlus (CIAT, ICRAF) Nitrogen fertilizer efficiency and N2O estimates (CIMMYT, WUR) Avoided deforestation and cattle (CIFOR) Low emissions development pathways for livestock (ILRI) Mitigation priorities in rice-dominated landscapes (IRRI) CCAFS low emissions development: major thematic areas Food loss and laste (WUR, IFPRI) Global Sustainable livestock intensification (WUR)
- 7. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part I. Reasons to mitigate GHG emissions in agriculture
- 8. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part Agricultural GHG emissions matter globally
- 9. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image partAgricultural emissions are also significant within countries Agriculture contributes an average of 30% of national emissions -42 countries ≥ 50% -89 countries ≥ 20% (Data based on National Communications, Richards et al. 2015)
- 10. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part Livestock intensification • Improve digestibility of feed • Reduce numbers of animals • Reduces emissions intensity up to 20X for beef, 300X for dairy (without considering LUC, feed) 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 Mitigation can be a development co-benefit: 1. Livestock GHG efficiency EU, USA
- 11. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part 2. Nitrogen Use Efficiency • Increase efficiency of N fertilizer uptake by plants, e.g. timing, rates, deep placement, microdosing • Increasing NUE from 19 to 75%, decreases emissions intensity by 56% (12.7 to 7.1 g N2O-N/kg N uptake) Groenigen et al. n.d.
- 12. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part 3. Water use efficiency • Alternate wetting and drying can reduce water use by 30% and CH4 emissions up to 38% and reduce fossil fuel use • More than 200 studies, although mostly in China, Japan and Philippines.
- 13. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part LED Example: Sustainable Cattle Intensification in Brazil Sustainable intensification programs produced 18% lower GHG emissions/kg beef compared to neighboring farms not in the programs. Practices: reduced slaughter age and increased stocking rates Sampled 44 cattle farmers and emissions activity data from 41 farms in Mato Grosso, Amazonas, Rondonia, and Pará; 18 interviewed cattle farmers participated in one of four national projects on sustainable intensification, Guedes-Pinto et al. 2016 Cattle farm survey sites (Bogaerts et al. 2016)
- 14. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part CEREALS - ADVANCE II GHANA Reduced tillage, crop residue burning reduction, nutrient management, AWD • Yield increases of 51% - 149% • AWD in rice - reduced emissions 43% • Reduced burning and residue increased SOM • Post-harvest losses reduced from 30 to 10% Emissions intensity decreased § Maize 117% § Soybean 267% § Irrigated rice 66% LED EXAMPLE: Feed the Future USAID Program Nash et al. 2016
- 15. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image partDemand for mitigation in agriculture: - 119 countries have agriculture in their mitigation NDC. - 64% are developing countries UNFCCC
- 16. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part II. Why mitigation in agriculture might be difficult
- 17. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part Tier 1 emissions factors may be misleading Over-prediction of emissions using default emission factors • 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
- 18. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part Smallholders contribute ~32% of agricultural emissions Country (ranked by emissions from smallholder agriculture) Agricultural emissions Mt CO2e/yr % land under smallholders Smallholder agricultural emissions Mt CO2e/yr China 818 98% 804 India 647 44% 287 Indonesia 156 55% 86 Ethiopia 89 60% 54 Bangladesh 75 69% 51 Tanzania 44 88% 39 Pakistan 134 15% 21 Egypt 28 58% 16 Colombia* 59 28% 16 Nepal 21 69% 14 Philippines 51 25% 13 Myanmar 64 19% 12 Sum of top 12 2186 1413 Agriculture sector emissions by smallholder agriculture in top emitting non-Annex I countries 4X the agricultural emissions of the EU or US 7% come from top 3 countries Proportion of land under smallholdings: • Data available for only 61 countries • Old, ranging from 1993 to 2011. Vermeulen and Wollenberg 2015
- 19. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part Need for incentives for farmers and those who advise and fund them Sustainable cattle initiatives in Brazil Cattle producers joined initiatives primarily to increase production and reduce production costs • Also to learn new practices, access innovations, interest in sustainability • Only a few found new markets or earned higher prices. Despite strong regulations and finance, barriers persist: • cost of changing farm practices, 100,000-300,000 Brazilian reais • insufficient technical assistance or capacity, and • difficulty in complying with legal standards
- 20. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part III. How much can mitigation practices contribute to the 2 °C policy target?
- 21. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part According to integrated assessment modeling, e.g. IMAGE
- 22. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part 1 GtCO2e mitigation needed annually in agriculture by 2030 (11-18% reduction) Agriculture will need to limit GHG emissions to 6-8 GtCO2e (out of all-sector total of 26 GtCO2e) by 2030
- 23. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part Feasible? Selected mitigation practices compatible with food production • Cropland management • Grazing land management • Livestock Not • Rewetting peatlands • Cropland set aside IPCC AR5 Table 11.2
- 24. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part Calculated mitigation with global data sets 1. Bottom-up technology-by-technology estimates (Smith 2007, 2008, University of Aberdeen, IPCC) $20 tCO2 2. Production efficiency gains (trade and location, production system) using integrated assessment modeling (Havlík 2014, IIASA) $20, $50 tCO2
- 25. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part Contributions of mitigation scenarios compared to the 2°C mitigation goal for agriculture 0.21 0.40 0.92 1.19 1.23 0.0 0.5 1.0 1.5 Mitigation (GtCO2e/yr) RCP2.6 (IMAGE) (2) GCAM2.6 (3) MESSAGE2.5 (4) Technical practices USD20/t (8) GLOBIOM USD20/t (9) 1 GtCO2e/yr mitigation to stay within 2° C
- 26. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part 0.76 0.31 1.71 1.77 2.00 1.37 4.31 1.20 0 1 2 3 4 5 Livestock supply chains Decrease food waste Shift dietary patterns Avoided deforestation by agriculture Soil carbon Mitigation (GtCO2e/yr) A more comprehensive goal fo agriculture-related land use could be up to 4-6 GtCO2e/yr or ~21% of the mitigation needed across all sectors
- 27. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part 27SAI - GRA
- 28. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part Summary of pros and cons for meeting food and climate needs • Agriculture is probably needed to meet 2°C target • Major source of emissions and mitigation globally and nationally • Mitigation options already exist • Mitigation options contribute to other SDGs, e.g., food security, poverty reduction, and sustainable production • Integrated approach to land use necessary for accounting • Difficult to quantify; poor estimates in developing world • Transactions costs of reaching smallholders • Technical and policy options insufficient for 2 degree goal • Lack of direct incentives tied to mitigation alternatives • Political sensitivity and opposition (BRICS) Pros Cons
- 29. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part Go for the 2° goal? 1. Not mitigating in agriculture will increase the cost of mitigation in other sectors or reduce the feasibility of meeting the 2°C goal. - Compare investment options in nuanced way. 2. Mitigation must be part of sustainable agriculture and land use vision, regardless of 2°C goal 3. Align technical support, finance, MRV for agriculture, forestry and other land uses in both supply chains and public sector jurisdictions.
- 30. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part
- 31. The image part with relationship ID rId24 was not found in the file. The image part with relationship ID rId24 was not found in the file. The image part CCAFS data and tools on website • CSA guide and database • Climate wizard • Downscaled climate data • Mitigation options tool • Agronomic trial information • Household surveys (baseline, IMPACT)