National Institute for Environmental Studies (NIES) Tomoko Hasegawa, Shinichiro Fujimori, Kiyoshi Takahashi and Toshihiko Masui Hasegawa, T., Fujimori, S., Takahashi, K., Masui, T., 2015. Scenarios for the risk of hunger in the twenty-first century using Shared Socioeconomic Pathways. Environmental Research Letters 10, 014010. Artic Article URL e URL http:/ http://iop opscience.io science.iop.or org/ g/1748-9326/10/1/014010 1748-9326/10/1/014010 The 20 th AIM international workshop, Tsukuba, January 23-24, 2015 1
Introduction Background • Climate change would increase the number of malnourished children. • The climate impacts strongly depend on population and GDP. – Based on the SRES and CMIP3 ; Need updated. – Only population and GDP were considered; other socioeconomic indicators could be considered. • A new interdisciplinary scenario framework (SSP+RCP) has recently been designed for climate change research. • Scenarios for various fields (e.g. water use) have been developed based on SSPs. – No scenarios for risk of hunger consistent with SSPs have been developed. 2
Introduction Objectives 1. Develop 21 st ‐ century scenarios for the risk of hunger consistent with SSPs as a baseline of climate impact research on agriculture 2. Identify the elements strongly affecting future risk of hunger • 7 socioeconomic indicators were considered: – Population, demographic change, GDP, equality of food distribution, crop yields, irrigation area, land productivity of livestock and wood products 3
Method Shared Socioeconomic Pathways Low population growth; high economic growth; Rapid population growth; high human Moderate economic growth; development; low low levels of education and governance; environmental awareness. Regionalization; low environmental awareness. A mixed world, with rapid technological Low population growth; development in high income high economic growth; countries. In other regions, high levels of education development proceeds and governance; slowly. Inequality remains globalization, international high. cooperation, technological development, and Based on O’Neill et al. (2014) environmental awareness. 4
Method AIM/CGE (Computable General Equilibrium) Demand curve Supply curve Economic model Price • Fundamental idea: • supply = demand, • balanced by price mechanism • Population & income growth � Increase in food demand Quantity � Increase in food price Domestic distribution of food energy (FAO,2008) � Producers: increase in production (cropland expansion, yield growth) � Consumers: decrease in consumption; shift to less expensive goods 5
Method Parameters related to food and hunger Parameters: Population, demographic change Each parameters were GDP determined from the Equality of food distribution adaptation viewpoint Crop yield Irrigation area Land productivity of livestock and wood products Income elasticity of food demand Price elasticity of land use change Price elasticity of trade AIM/CGE Endogenous variables: Food consumption Meat consumption Land use (Cropland, pasture, forest) 6 Hasegawa et al. 2015
Method Parameters related to food and hunger Parameters: Population, demographic change GDP Equality of food distribution Three approaches for assuming Crop yield parameters Irrigation area 1. Based on observed data Land productivity of livestock and wood products (Stylized fact) Income elasticity of food demand 2. Based on existing studies Price elasticity of land use change 3. Assumed in line with SSP Price elasticity of trade storylines if neither were available. AIM/CGE Endogenous variables: Food consumption Meat consumption Land use (Cropland, pasture, forest) 7
Method Comparison with observed data : the improved equality of food distribution with income growth Inequality 0.45 observed data (2005) Coefficient of variation (CV) of the domestic − distribution of dietary energy consumption = ⋅ 0.134 Optimistic 0.6894 y x 0.4 − = ⋅ = 0.109 2 Median y 0.6531 x (Observed data; R 0.61) 0.35 − = ⋅ 0.054 Pessimistic 0.4609 y x 0.3 Pessimistic 0.25 0.2 Intermediate Optimistic 0.15 0.1 Equality 0 20000 40000 60000 80000 GDP per capita [US$, 2005] 8 Hasegawa et al. 2015
Method Comparison with observed data : increased meat consumption with income growth (1980 ‐ 2009) observed data 800 = ⋅ − 60.0 ln 399.8 y x Optimistic Meat ‐ based calorie intake [kcal/day/cap] 700 = ⋅ − = 2 Medium 87.8 ln 545.3(Observed data; 0.57) y x R Pessimistic = ⋅ − Pessimistic 130 ln 833.0 y x 600 500 Intermediate 400 300 Optimistic 200 100 0 0 20000 40000 60000 80000 income [US$/person] 9 Hasegawa et al. 2015
The 21 st ‐ century Scenarios of risk of hunger Results using SSPs Land use change 12000 10000 Food crops Land use [Mha] 8000 Population at risk of hunger Pasture 6000 Grassland 900 4000 Managed forest Population at risk of hunger 800 2000 Primary forest 700 SSP3 0 SSP1 SSP2 SSP3 SSP4 SSP5 600 SSP4 2005 2100 [million] 500 Food consumption per capita 400 300 4000 SSP1 SSP2 Carolie intake [kcal /person/day] 3500 200 SSP5 3000 100 2500 SSP1 0 2000 SSP2 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 1500 SSP3 SSP4 1000 SSP5 500 0 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 10 Hasegawa et al. 2015
Method Decomposition analysis What strongly affects future risk of hunger? • Change in hunger risk was decomposed into three factors; Change Inequality of Food Population in pop. at ＋ ＋ ＋ Residual = food consumption growth risk of distribution hunger ＊ See discussion paper for more detail @http://www.nies.go.jp/social/dp/dpindex.html. 11
Result Factors affecting future hunger risk (global, at 2005 level) 1000 1000 1000 c) SSP3 b) SSP2 a) SSP1 Change in population at risk of Change in population at risk of Change in population at risk of 500 500 500 hunger [million] hunger [million] hunger [million] 0 0 0 ‐ 500 ‐ 500 ‐ 500 ‐ 1000 ‐ 1000 ‐ 1000 ‐ 1500 ‐ 1500 ‐ 1500 2005 2020 2035 2050 2065 2080 2095 2005 2020 2035 2050 2065 2080 2095 2005 2020 2035 2050 2065 2080 2095 1000 1000 d) SSP4 e) SSP5 Change in population at risk of Change in population at risk of residual 500 500 hunger [million] hunger [million] per ‐ capita calorie 0 0 (domestic production) inequality of food distribution ‐ 500 ‐ 500 population ‐ 1000 ‐ 1000 ‐ 1500 ‐ 1500 net change 2005 2020 2035 2050 2065 2080 2095 2005 2020 2035 2050 2065 2080 2095 • Population, inequality of food distribution causes large differences in hunger risk among SSPs 12 Hasegawa et al. 2015
Regional population at risk of hunger and its factors (SSP3, 2100 ） 21st ‐ century risk of hunger differs among SSPs • Regional distribution depends greatly on population growth, equality in food • distribution and increase in food consumption Regions with greater population • The most pessimistic scenario ( SSP3 ) growth face higher risk of hunger. North Brazil China Africa Former Rest of Soviet South Union America 900 Rest of Southeast Population at risk of hunger 800 Africa, Asia Rest of SSP3 700 39% Asia, 16% 600 Middle India, SSP4 East [million] 500 23% 400 500 residual 300 Change in population at risk of SSP2 SSP1 200 250 trade 100 SSP5 hunger [million] 0 0 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 per ‐ capita calorie ‐ 250 ‐ 500 inequality of food distribution population (Relative to 2005) Hasegawa et al. in review
Result & discussion Comparison of the population at risk of hunger with existing studies 1200 • Lines: this study Pop. at risk of hunger in • this study was lower than • Dots: existing studies 1000 in existing studies. Population at risk of hunger [million] Improvements in food 800 • distribution equality was considered in this study SSP3 600 whereas it was not for SSP4 existing studies. 400 � Inequality of food • SSP2 distribution influences 200 SSP1 long ‐ term assessments A1 SSP5 of hunger risk. A2 0 B1 B2 1990 2020 2050 2080 14 Hasegawa et al. 2015
Conclusion Conclusion We developed scenarios for hunger risk in the 21 st century using SSPs. Factors affecting future hunger risk were investigated. • Risk of hunger without climate change in the 21 st century differed among SSPs • Factors influencing the future reduction of hunger risk were population, inequality of food distribution, and per ‐ capita food consumption. • Inequality of food distribution greatly influences long ‐ term assessments of hunger risk. 15
Thank you for your attention! Acknowledgments This research was supported by the Environment Research and Technology Development Fund (2–1402) of the Ministry of the Environment, Japan, and the climate change research program of the National Institute for Environmental Studies. 16
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