Estimation of Adaptation Cost and Risk Toshihiko Masui Izumi Kubota, Azusa Okagawa, Shinichiro Fujimori, Tomoko Hasegawa ICA-RUS/CCRP-PJ2 International Workshop 2013 Tokyo, Japan December 5, 2013
Overall of this sub-theme • Collection of data and information on adaptation cost in global scale, and Meta analysis – Assessment of risk of adaptation. • Socio-economic scenario development – based on SSPs – A part of Scenario Task Group, and providing scenarios to other teams. • Development of integrated assessment model reflecting climate change impact & adaptation and mitigation. – Model intercomparison among S-10-4.
Impact and Adaptation (2) First-level Second-level Third-level category Adaptive measures category category Agriculture Grains, fruit Improvement of tolerance and avoidance of high temperatures Livestock farming Livestock, fodder Avoidance of high temperatures and migration to Food sector more suitable locations Fisheries Migratory fish, coastal Adaptation to changes in ecosystems and fish, aquaculture movement to more suitable locations Water supply Securing of reservoirs and groundwater use Water demand measures Improvement of efficiency Water Water environment management Measures against eutrophication and salt water Flood control measures Forest ecosystemsNatural forests, planted Revision of sanctuaries Natural forests, community ecosystems woodland (vegetation Coastal Oceans, freshwater, tidal Reduction of environmental load and riparian /land) ecosystems flats forest preservation Source: Research Committee on Global Warming Effects and Adaptation (MOE, 2012)
Impact and Adaptations (1) First-level Second-level Third-level category Adaptive measures category category Changes in land use Changes in land Development of buffer zones/dykes, changes in use/architectural styles architectural styles Disaster Enhancement of Information provision and Development of evacuation routes, disaster prevention disaster prevention support drills and coastal systems sector Monitoring Observation Summer heat Public health guidance Health Infectious diseases Vaccination, improvement of sanitation Safe living Houses, inhabited areas Strengthening/movement of buildings Healthy living Heat, water environment Heat stroke measures, maintenance of health Economically Heat, diet Use of weather derivatives, development of National/ affluent living new industries urban life Comfortable living Heat Renovation and pest extermination Culture Ecosystems Tree planting and preservation Source: Research Committee on Global Warming Effects and Adaptation (MOE, 2012) Update this table using IPCC AR5.
Constraints on adaptations Constraints/obstacles • Physical/ecological • Technological • Economic/financial • Social/cultural • Institutional • Information/recognition • Human resource development Source: Research Committee on Global Warming Effects and Adaptation (MOE, 2012)
Adaptation risks Risks for human society • Risks associated with cost burden (adoption expenses, development expenses) • Development potential as an industry • Risks associated with changes in land use • Risks associated with changes in local infrastructure • Risks associated with growth in energy demand Risks for ecosystems • Impact on ecosystems of selective breeding and changes in tree species, etc. • Risks associated with ecosystem changes Source: Research Committee on Global Warming Effects and Adaptation (MOE, 2012)
Estimation of adaptation costs in global scale literatur Estimation method Results on adaptation cost notes e Assumptions Adaptation fields Annual cost (bil. $) ratio to GDP Temperature change: 2-3 ℃ 9 － 41 World Additional investment to fields - US$ at 2000price Bank with climate risk (2006) World Definition of adaptation Public hardware actions All area US$ at 2005 price Bank costs (2010) additional costs Infrastructure Rainy season Rainy season Baseline ( ＮＣＡＲ scenario) ( ＮＣＡＲ scenario) Coastal area defined by sector 89.5 － 101.8 0.22 － 0.12% (2010 － Water supply and river GHG scenario flood 49) IPCC SRES A2 Agriculture Climate scenario Fishery Dry season Dry season NCAR 、 CISRO Human health (CISRO scenario) (CISRO scenario) 2010 － 2050 0.17 － 0.11% (2010 － Time period Forestry & ecosystem 76.8 － 88.3 49) Adaptation level Extreme events recovery to the level without climate damages Discount rate 0 UNFCCC Definition of adaptation Infrastructure 8-130 - US$ at 2005 price (2007) costs 1.2(A1B) 、 1.1(B1) Coastal area additional costs 11(A1B) 、 9(B1) Water supply Baseline Agriculture 14 defined by sector Forestry & Fishery GHG scenario Human health 4-5 IPCC SRES A1B, B1,IS92a Natural ecosystem 12-22 Time period 2010 － 2030 Agrawala. Definition of adaptation cost Coastal area - DICE Cost is estimated S., et al. under optimal investment to reduce damages Agriculture 0.28% in 2100 (OECD) adaptation and no Baseline Human health mitigation. (2010) defined by model Resident & ecosystem WITCH Climate model other vulnerable market 0.19% in 2100 AD-DICE, AD-RICE, AD- Non-market WITCH Extreme events at NPV 2005 － 2100 Time period Discount rate 3% Taking into account adaptation related to flow, stock & capacity
Urgent! • We need more information about adaptation cost! • If you know new data, information, report, ..., please introduce to us! – Global – National – Local
Our concept of impact/adaptation modeling Detailed process results from Ecosystem other teams Coastal area Agriculture (food) GHG CGE model In order to input to CGE, Temperature increase <Economic activity> process/information should be simplified. Water Health Damage Mitigation Impact Adaptation
Climate change impact and adaptation assessment on food consumption utilizing a new scenario framework Center for Social & Environmental Systems Research, National Institute for Environmental Studies T. Hasegawa, S. Fujimori, S. Yonghee, K. Takahashi, T. Masui and A. Tanaka Hasegawa T., Fujimori S., Shin Y., Takahashi K., Masui T. and A. Tanaka, Climate change impact and adaptation assessment on food consumption utilizing a new scenario framework, Environmental Science and Technology , accepted. 10
Background Introduction • Climate change(CC) impacts on agriculture & food systems • Several approaches have been taken • Existing studies – Not quantifying effects of adaptation measures – Based on SRES, not RCPs & SSPs – Based on climate data of CMIP3, not CMIP5 • Aim – Analyze CC impacts on food consumption and risk of hunger by using RCPs & SSPs based on multi-GCM scenarios. – Quantify effects of adaptation measures 11
Method 気候モデル Scenario settings 社会経済 気候条件 条件 作物モデル 作物収量変化 Socio-economic conditions 世界 CGE モデル Optimistic Middle Pessimistic エネルギー・削減費用 農業・食料 SSP1 SSP2 SSP3 • エネルギー需給 • 食料需給 土地利用 • バイオ作物生産 • 栄養不足人口 変化 Climate conditions • 炭素価格 • 所得低下 NoCC Present climate condition assumed With CC RCP2.6 RCP4.5 with/without adaptation in low or middle income countries RCP6.0 RCP8.5 Adaptation measures: ◦ change in crop variety & planting dates ◦ industrial countries: available World GDP World GDP World population World Population 200000 “RCP”: Representative Concentration Pathway 15000 SSP1 SSP1 “SSP”: Shared Socioeconomic Pathway bil 2005 US$/year 150000 SSP2 Mil number 10000 SSP2 100000 SSP3 SSP3 5000 50000 0 0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 12 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
Method Modeling framework Climate model Socioeconomic Climate condition condition (RCP2.6/4.5/6.0/8.5 (SSP1-3) /NoCC) • population • Crop model GDP • Consumer Change in preference Model crop yield Exogenous variables Year: 2005-2050 Climate Endogenous Global CGE model World17regions change variables impact Energy & mitigation cost Agriculture & food • • Energy supply & Food supply & demand demand Land use • • Bio-crop production Population at risk • Carbon price of hunger • Income loss 13
Method Representative Concentration Pathway • CGE model: Emission constraints • GAEZ crop model: climate condition 14
Method 気候モデル Global change in climate conditions 社会経済 気候条件 条件 作物モデル 作物収量変化 Temperature Precipitation 世界 CGE モデル エネルギー・削減費用 農業・食料 • エネルギー需給 • 食料需給 土地利用 • バイオ作物生産 • 栄養不足人口 変化 • 炭素価格 • 所得低下 Solar radiation 15
• Change in crop yield due to CC is calculated M-GAEZ Change in yield [%] (NoCC=100) -100 100 150 200 -50 50 0 Change in crop yield due to CC in 2050 EU25 Oceania Japan Canada United States (RCP8.5, HadGEM2ES) Rest of Europe Crop yields Turkey China India Brazil Former Soviet Union Southeast Asia Rest of Asia Rest of South America Middle East North Africa Rest of Africa 16
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