1. Climate Change and Poverty Conference February 10, 2015 The impact of climate change on costs of food and its impact on poverty at subnational scale Anne Biewald Hermann Lotze-Campen, Ilona Otto, Nils Brinckmann, Susanne Rolinski, Benjamin Bodirsky, Isabelle Weindl, Alexander Popp, Hans- Joachim Schellnhuber

2. 2 Methodology

3. 3 Combining three data sets: 1.Spatially explicit model based indicators: biophysical yield, production amount, costs of food 2.Spatially explicit hunger index 3.Spatially explicit population

4. 4 Methodology Combining three data sets: Spatially explicit model based indicators: biophysical yield, production amount, costs of food Spatially explicit hunger index Spatially explicit population Where are how many and what kind of poor people affected by CC impacts on agricultural production?

5. 5 Structure of the presentation Hunger index Model description Scenarios Results

6. 6 The Hunger Index

7. 7 The spatially explicit hunger index (SEHI) is calculated based on child undernourishment, child underweight and infant mortality for the year 2000 (FAO 2015, CIESIN et al., 2005b). 2000

8. 8 Projection of the spatially explicit hunger index to the year 2030 for SSP4 and SSP5. 2030

9. 9 Model description

10. 10 MAgPIE (Model of agricultural production and its impact on the environment) Cost minimization ~ 60.000 grid cells (1000 aggregated clusters) 10 economic regions 13 crops, 5 livestock activities international trade Demography Income and diet Food demand, production costs Socioeconomic inputs Cereals Oilseeds Pulses Sugar beets Crop yields Land & Water constraints Climate change (GCM) LPJ (50x50 km grid) Biophysical inputs (LPJmL) Bioenergy Lotze-Campen et al. 2008 MAgPIE Land use pattern

11. 11 Scenarios

12. 12 Representative Concentration Pathways

13. 13 Socio-economic Pathways (SSPs)

14. 14 Relevant SSP specifications for MAgPIE SSP4SSP5 MNASASSSAMNASASSSA Population in developing countries HighLow Kcal per capita in developing countries LowHigh Regional food crop demand High About equal Low About equal Trade liberalizationTrade restrictedTrade liberalized MNA: Middle East and North Africa SAS: South Asia SSA: Sub-Saharan Africa

15. 15 What kind of world will be affected by climate change?

16. 16 What kind of world will be affected by climate change? CC SSP4 No CC SSP4 No CC SSP5 CC SSP5

17. 17 The agricultural indicators

18. 18 Yields Difference in biophysical yields (CC – noCC), 2030. MNA: Middle East and North Africa SAS: South Asia SSA: Sub-Saharan Africa

19. 19 Difference in production (CC – noCC) year 2030 Production SSP4 SSP5

20. 20 Difference in production (CC – noCC) year 2030 Production SSP4 SSP5

21. 21 Area Trade Regional specific processes to react to CC impacts: MNA

22. 22 SSP4 + SSP5: increase of yields Area Trade Yield after optimization Regional specific processes to react to CC impacts: MNA

23. 23 Regional specific processes to react to CC impacts: SAS SSP4: expand agricultural land SSP5: increase in imports, decrease exports TradeArea

24. 24 Regional specific processes to react to CC impacts: SSA SSP4: expand agricultural land SSP5: increase imports, decrease exports TradeArea

25. 25 Costs of food Difference in costs of food (CC-noCC), 2030. SSP5 SSP4 Costs of food

26. 26 Processes which lead to a change in COF

27. 27 The agricultural vulnerability indicator

28. 28 Differences in the CC impacts on costs of food (COF) combined with the projected hunger index. SSP4 SSP5 2030 Hunger Index Cost of Food

29. 29 Spatially explicit population SSP4 SSP5

30. 30 SSP4SSP5 Hunger index SeriousAlarming Extremely Alarming SeriousAlarming Extremely Alarming SSA Serious2052242816483 High914026160 Extremely high 1381163320 Impact of CC on costs of food Affected people in Mio. by changes of COF in the different hunger index categories for Sub-Saharan Africa

31. 31 Thank you! biewald@pik-potsdam.de

32. 32 Quantified SSP specifications for MAgPIE Model parameters (SSP indications) Implementation SSP 4Implementation SSP 5 SSAMNASASSSAMNASAS Population in Mio people in 2030 1396511205412405082025 Kcal per capita in 2030 (GDP) 253132452621270733942763 Demand for food crops in Peta Joule in 2030 (population/ GDP) 446224607013419121007088 Share of livestock products in the diet in 2030 (GDP) 0.090.145 0.14 0.100.145 0.14 Trade liberalization (Globalization) Starting from 2010 trade barriers are relaxed by 10% percent per decade for developed regions, but are kept constant for developing regions considered here. Starting from 2010 trade barriers are relaxed by 10% percent per decade globally. Livestock intensification (Technology) SlowFast Nutrient efficiency (Technology) HighMedium

33. 33 Affected people by change in COF in the different hunger index categories Affected people by change in COF and hunger index in Mio SSP4 SSP5 LMSAEA LMSA SSA PI142114423440 321324101350 NI122961576 135331750 SI32220522428 222616483 HI009140 0526160 EI07138116 8113320 MNA PI17181100 5045000 NI00310 03010 SI00000 184000 HI09000 95351100 EI8728521420 111714220 SAS PI0724470 01648200 NI0157020 4681300 SI097672283 621261030 HI0757310 124150400 EI049410 044200

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36. 36 Modelling processes leading to a change of production patterns and resulting changes in costs of food Regional food demand is exogenously given and constant A decrease of yields and irrigation water can be compensated through: 1.Imports 2.Increase of production Production can be increased by: a) Expanding agricultural area b) Investing in irrigation infrastructure or c) Investing in R&D leading to higher yields