IAMC November 12, 2012 Consistent Analysis of Different Scenarios of Climate Stabilization and Sustainable Development Keigo Akimoto, Kenichi Wada, Fuminori Sano, Ayami Hayashi, Takashi Homma, Junichiro Oda, Miyuki Nagashima, Kohko Tokushige, and Toshimasa Tomoda Research Institute of Innovative Technology for the Earth (RITE)
Background and Objective 2 The world is facing various issues to be solved in many of which are related to sustainable development. It is really important to achieve such multiple objectives with well-balanced priorities, in order to improve our well-being in the future. Consistent analyses for climate change and other sustainable development challenges are required to seek better future including considerations of different conditions among countries. This study presents consistent and quantitative analyses for climate change and sustainable development.
Overview of ALPS* Models, Assessed Indicators and Scenarios * ALPS: ALternative Pathways toward Sustainable development and climate stabilization
Relationships among Models for Consistent Scenario Analysis 4 Assessment of food access Socio-economy Population, GDP Assessment of population living in poverty Mid-term world energy and economic model: DEARS (until 2050) Energy Assessment of energy security (until 2050) Assessment of food security Ultra-long-term energy and macroeconomic model: DNE21 Mid-term world energy and mitigation measures assessment model: DNE21+ (until 2050) Food, water resource, land use GHGs excluding energy-related CO2 Assessment model for GHGs excluding energy-related CO2 Climate change Simplified climate change model: MAGICC6 Assessment models for food demand/supply, water resource and land use change Grid-based estimation of climate change: using results from MIROC3.2 Assessment of water stress Impacts of global warming Estimation model for economic damages from global warming (developed by Nordhaus) Assessment model for biodiversity (Impacts on terrestrial ecosystem and ocean acidification) Assessment model for health impact
Overview of the Module for Assessments of Food Demand/Supply, Water and Land-use 5 Population Per-capita GDP Climate* 1 Food demand Management factor Yield Slope Soil Water availability Energy model etc. Land required for food crop production Land cover: Arable land, Forests, etc. Water demand: Domestic water, Industrial water, etc. Irrigation water Water withdrawals grids river basins 32 regions Agro-land use model Population distribution Water-stressed basin (Annual water withdrawalsto-availability ratio 0.4) Water-stressed population *1: Grid-based climate scenarios were estimated based on pattern scaling method, integrating data on GMT rise and AOGCMs projection.
Energy Assessment Model: DNE21+ 6 Linear programming model (minimizing world energy system cost) Evaluation time period: 2000-2050 Representative time points: 2000, 2005, 2010, 2015, 2020, 2025, 2030, 2040, 2050 World divided into 54 regions Large area countries are further divided into 3-8 regions, and the world is divided into 77 regions. Bottom-up modeling for technologies both in energy supply and demand sides (200-300 specific technologies are modeled.) Primary energy: coal, oil, natural gas, hydro&geothermal, wind, photovoltaics, biomass and nuclear power Electricity demand and supply are formulated for 4 time periods: instantaneous peak, peak, intermediate and off-peak periods Interregional trade: coal, crude oil, natural gas, syn. oil, ethanol, hydrogen, electricity and CO2 Existing facility vintages are explicitly modeled. - The model has detailed information in regions and technologies enough to analyze sectoral approach. - Consistent analyses among regions and sectors can be conducted.
Assessed Major Indicator 7 Category Economic and poverty Agriculture, land-use, and biodiversity Water Energy Income (GDP per capita) Indicator People living in poverty (including impacts of climate change and mitigation measures) Food access (amount of food consumption per GDP) (including impacts of climate change and mitigation measures) Energy access (access to grid electricity; People relying on the traditional use of biomass for cooking) Agriculture land area (including impacts of climate change) Food security (amount of food imports per GDP) (including impacts of climate change and mitigation measures) People living under water stress (including impacts of climate change) Sustainable energy use (cumulative fossil fuel consumption) Energy use efficiency (primary energy consumption per capita and per GDP) Energy security (share of total primary energy consumption accounted for by oil and gas imports with country risks) Climate change Economic impact of mitigation measures (marginal abatement cost (carbon price) and GDP loss) Global mean temperature change Aggregated economic impact of climate change
Assumed Scenarios 8 ALPS core scenarios Scenarios for macro-level and socio-economic conditions in the long term Scenario A: Medium technological progress scenario Scenario B: High technological progress scenario Scenarios for emission reduction levels ALPS-Baseline ALPS-CP6.0 ALPS-CP4.5 ALPS-CP3.7 ALPS-CP3.0 Climate change policy scenarios I:Pluralistic society scenario II:Climate policy prioritized scenario III: Energy security prioritized scenario
Assumed Socioeconomic Scenarios
ALPS Per-capita GDP Scenarios (Global Average, Baseline) 10 60 SRES A1 IPCC Range in SRES Per-capita GDP (Thousand 2000USD) 50 40 30 20 10 ALPS-Scenario B SRES A2 SRES B1 SRES B2 Range in ALPS ALPS-Scenario A 0 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Note: GDP of SRES scenarios are adjusted to the price in 2000 from that in 1990.
ALPS Global Population Scenarios 11 Population 人口 (100 ( 億人 million ) people) 160 140 120 100 80 60 40 20 UN2008 High UN2008 Middle UN2008 Low SRES A2 (IIASA1996 High) ALPS-Scenario A Range in UN2008 ALPS-Scenario B Range in SRES SRES B2 (UN1998 middle) IIASA2007 (10-90 percentile) Range in ALPS SRES A1/B1 (IIASA1996 Low) 0 1950 1975 2000 2025 2050 2075 2100 High per-capita GDP will induce low population. Scenario A: medium population, Scenario B: low population
ALPS Global Food Demand Scenarios 12 35,000 30,000 2005-2050: +1.0%/yr (per-cap consumption: +0.2%/yr) 2050-2100: +0.1%/yr (per-cap consumption: +0.0%/yr) Food demand (Tcal/day) 25,000 20,000 15,000 10,000 5,000 1960 1990-2005:+1.5%/yr (per-cap consumption: +0.2%/yr) 1970 1980 1990 2000 2010 2005-2050: +0.8%/yr (per-cap consumption: +0.2%/yr) 1961-1990:+2.5%/yr (per-cap consumption: +0.7%/yr) 2020 2030 2040 2050 2050-2100: -0.3%/yr (per-cap consumption: +0.0%/yr) 2060 2070 2080 2090 2100 ALPS-A ALPS-B FAO(2006) The effects of population decrease on food demands are larger than those of per-capita income increase. Hence, the global food demands in Scenario B are smaller than those in Scenario A.
GHG Emission Outlook and Emission Reduction Scenarios ー Baseline, CP6.0, CP4.5, CP3.7, CP3.0 ー
ALPS CO2 Emission Scenarios 14 120 100 ALPS B-Baseline ALPS A-Baseline ALPS A-CP6.0 CO2 emission (GtCO2eq/yr) 80 60 40 20 ALPS A-Baseline ALPS A-CP4.5 ALPS A-CP3.7 ALPS A-CP3.0 ALPS B-Baseline RCP8.5 RCP6.0 0 RCP4.5-20 1990 2010 2030 2050 2070 2090 2110 2130 2150 RCP3PD Note: CO2 emissions including those from industrial processes and LULUCF RCP (Representative Concentration Pathway): IPCC new scenario
Global Mean Temperature Rise 15 7 Surface temperature relative to pre-industrial (K) 6 5 4 3 2 1 ALPS A-Baseline ALPS A-CP6.0 ALPS A-CP4.5 ALPS A-CP3.7 ALPS A-CP3.0 RCP8.5 RCP6.0 RCP4.5 RCP3PD 0 1990 2010 2030 2050 2070 2090 2110 2130 2150 Note: Equilibrium climate sensitivity is assumed to be 3 C, which is a most likely value. The maximum global mean temperature change relative to the pre-industrial level is about 2 C (1.94 C) for the ALPS CP3.0.
Assessments of Sustainable Development Indicators
Agriculture Land Area 17 Required area for food productions to meet food demands Required area for food productions (Year 2000=100) 140 120 100 80 60 40 20 0 A-Reference(w.o. adaptations of changes in varieties of crop and planting) A-Baseline A-CP6.0 A-CP4.5 A-CP3.7 A-CP3.0 B-Baseline 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 The additional required area for crop productions will be about 20% in 2050 under Scenario A-Baseline. The area in the case of climate stabilization at a low level will be smaller than that of the baseline. However, socioeconomic conditions, such as population, will have larger effects on the required area.
Food Access Indicator (Amounts of food consumption per GDP) 18 Food Access Index [amounts of food consumptions/gdp] (US.Y2000=100) 300 250 200 150 100 50 686 916 1315 651 655 715 745 754 359 Bioenergy and forestation effects w.o. Bioenergy and forestation effects Vulnerable 0 A-baseline A-CP6.0 A-CP4.5 A-CP3.7 A-CP3.0 A-baseline A-CP6.0 A-CP4.5 A-CP3.7 A-CP3.0 A-baseline A-CP6.0 A-CP4.5 A-CP3.7 A-CP3.0 A-baseline A-CP6.0 A-CP4.5 A-CP3.7 A-CP3.0 A-baseline A-CP6.0 A-CP4.5 A-CP3.7 A-CP3.0 A-baseline A-CP6.0 A-CP4.5 A-CP3.7 A-CP3.0 A-baseline A-CP6.0 A-CP4.5 A-CP3.7 A-CP3.0 A-baseline A-CP6.0 A-CP4.5 A-CP3.7 A-CP3.0 2000 2050 2100 2000 2050 2100 2000 2050 2100 2000 2050 2100 China India Sub-saharan Africa L. America Vulnerabilities of food access will decrease in most countries and regions in the long-term under any emission scenarios, because future incomes are expected to increase in the future. Global warming impacts on food productions are relatively small compared with the effects of income increase. Global warming counter-measures of large scale of forestation and bioenery use slightly increase vulnerabilities of food access.
People Living under Water Stress 19 Population under water stress (million) 1,200 1,000 800 600 400 200 0 2000 2050 A-Base 2050 A-CP3.0 2050 B-Base 2100 A-Base 2100 A-CP3.0 2100 B-Base 2000 2050 A-Base 2050 A-CP3.0 2050 B-Base 2100 A-Base 2100 A-CP3.0 2100 B-Base 2000 2050 A-Base 2050 A-CP3.0 2050 B-Base 2100 A-Base 2100 A-CP3.0 2100 B-Base 2000 2050 A-Base 2050 A-CP3.0 2050 B-Base 2100 A-Base 2100 A-CP3.0 2100 B-Base 2000 2050 A-Base 2050 A-CP3.0 2050 B-Base 2100 A-Base 2100 A-CP3.0 2100 B-Base North Africa, Middle East Southwest Africa China India Other South Asia Water stress: annual water withdrawal-to-availability ratio 0.4 People under water stress will increase in many Asian countries mainly due to population increase. GHG emission cuts will not contribute to the mitigation of the stress. The water stress decreases after 2050 in the Scenario B mainly due to population decrease.
CO2 marginal abatement cost ($/tco2) 600 500 400 300 200 100 CO2 Marginal Abatement Cost for Different Stabilization Levels 0 2000 2020 2040 2060 2080 2100 ALPS A-CP6.0 ALPS A-CP4.5 ALPS A-CP3.7 ALPS A-CP3.0 IEA WEO2011 New Policy (EU) IEA WEO2011 450 (US) Note: The costs until 2050 are estimated by DNE21+, and those after 2050 are estimated by DNE21. 20 High marginal abatement costs are estimated after 2040 particularly for CP3.0. even if all the countries make the coordinated efforts (uniform marginal abatement cost) and the least cost mitigation measures are achieved.
CO2 Marginal Abatement Cost (Comparisons of Scenarios A and B) 400 21 CO2 marginal abatement cost (US2000$/tCO2) 350 300 250 200 150 100 50 0 2010 2020 2030 2040 2050 A-CP3.0 A-CP3.7 A-CP4.5 A-CP6.0 B-CP3.0 B-CP3.7 B-CP4.5 B-CP6.0 The baseline emission in Scenario B which is assumed to have higher GDP is larger than that in Scenario A. However, the marginal abatement cost in Scenario B is lower than that in Scenario A under deeper emission reductions such as CP3.0, CP3.7, because there are larger area for forestation and bioenergy productions due to population decreases, higher technology improvement, and electrification ratio.
Conclusion
Conclusion 23 Climate change is a dangerous issue. Emission reductions are surely required. But there are not only synergy effects between climate change and other sustainable development issues but also exist trade-offs, e.g., food access, under deep emission reductions, according to our study. Balanced climate target and balanced measures across climate change and many other sustainable development issues including climate change adaptations are required. Some indicators are strongly affected by socioeconomic changes rather than global warming impacts. Socioeconomic conditions expecting high emissions in BaU do not necessarily expect high mitigation costs for deep emission reductions. Distribution issues within countries and regions will be important for sustainable development. Distribution issues should be more focused in future works.
Appendix
Overview of the GHG Assessment Model (2 Models and 1 Scenario) 25 1. DNE 21+ Model Non-Energy CO2 2. Non-CO2 GHG Emissions Scenario Assessment Model Assessment model for energy-related CO2 emissions 54 regions in the world Bottom-up modeling (200-300 specific technologies are modeled) Projection module for non-energy CO2 emissions 54 regions in the world Estimations of sectoral non-energy CO2 emissions to be consistent with GDP and production activities Assessment model for the 5 non-co2 GHG emissions (CH4, N2O, HFCs, PFC, SF6) 54 regions in the world The methodology is similar to the USEPA assessment Estimates of the 6 GHG emissions, emission reduction costs and potentials, and specific cost-effective measures for emission reductions Note: LULUCF is excluded for the estimates.
Region divisions of DNE21+ 26
Technology Descriptions in DNE21+ (1/2) 27 Fossil fuels Coal Oil (conventional, unconv.) Gas (conventional, unconv.) Unit production cost Cumulative production Renewable energies Hydro power & geothermal Wind power Photovoltaics Biomass Unit supply cost Annual production Nuclear power Energy conv. processes (oil refinery, coal gasification, bioethanol, gas reforming, water electrolysis etc.) Electric Power generation CCS Industry Iron & steel Cement Paper & pulp Chemical (ethylene, propylene, ammonia) Aluminum Solid, liquid and gaseous fuels, and electricity <Top-down modeling> Transport vehicle Solid, liquid and gaseous fuels, and electricity <Top-down modeling> Residential & commercial Refrigerator, TV, air conditioner etc. Solid, liquid and gaseous fuels, and electricity <Top-down modeling>
Technology Descriptions in DNE21+ (2/2) An Example for High Energy Efficiency Process in Iron & Steel Sector 28 Coal for steel sector 24.1 GJ 23.8 GJ 22.5 GJ Type III: Current coke oven Recycling of waste plastics and tires 0.25 GJ Waste plastics and tires 0.25 GJ Type IV: Next-generation coke oven Blast furnace, sintering furnace, BF, BOF, casting, and hot rolling Type III and IV: High-eff. Intersection (Sophisticated steelmaking process with many energy saving facilities including CDQ, TRT, COG and LDG recovery) (Larger scale capacity plant) Electricity 455 kwh 91 kwh Utility 4.1 GJ Electricity (grid) Carbon capture from BFG Process gases recovery 8.6 GJ 111 kwh Steel product derived from BOF steel 1 ton of crude steel equivalent for each type Power generation facility 0.98 GJ Compressed CO 2 0.60 tco 2 Heavy oil BF: blast furnace, BOF: basic oxygen furnace, CDQ: Coke dry quenching, TRT: top-pressure recovery turbine, COG: coke oven gas, LDG: oxygen furnace gas
ALPS GDP Scenarios (Global, Baseline, MER) 29 400 SRES A1 RCP3PD(2.6) Range in SRES 350 ALPS Scenario B SRES B1 Range in RCP GDP (Trillion 2000USD) 300 250 200 150 100 RCP4.5 SRES B2 SRES A2 Range in ALPS RCP8.5 RCP6.0 50 ALPS Scenario A 0 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Note: GDP of SRES scenarios are adjusted to the price in 2000 from that in 1990. GDPs of SRES A1 and B1 are much higher than the ALPS assumptions. The GDP of Scenario A is close to that of RCP8.5 and RCP6.0; the GDP of Scenario B is close to that of RCP4.5.
Regional GDP PPP : Scenario A 30 L. America 8% Other Asia 7% India 4% Other Annex I 10% China 6% Africa 4% Japan 9% 1990 Other Non- Annex I 5% EU15 23% EU27(+12) 3% L. America 8% Other Asia 8% US 21% India 6% Other Non- Annex I 6% L. America 10% Other Asia 10% India 9% Africa 7% 2020 China 19% Africa 4% Other Non- Annex I 5% US 20% China 15% Other Annex I 2005 Japan 6% EU15 19% EU27(+12) 2% US 14% EU15 14% EU27(+12) 2% Japan 4% Other Annex I 5% Other Non- Annex I 6% Africa 10% L. America 9% Other Asia 11% India 12% 2050 China 22% US 12% EU15 9% EU27(+12) 1% Japan 3% Other Annex I 5%
Per-capita Food Demand Scenarios 31 Food demand (kcal/day/cap) Minimum required calorie in developing country average (1825 kcal) 4500 4000 3500 3000 2500 2000 1500 100 1000 10000 100000 GDP per capita (US 2000 $) Solid line: historical, dashed line: future scenarios The increase in food insecurity is not a result of poor crop harvests but because high domestic food prices, lower incomes and increasing unemployment have reduced access to food by the poor. (FAO, 2009) Food demand (kcal/capita/day) 3,200 3,100 3,000 2,900 2,800 2,700 2,600 2,500 2,400 2,300 2,200 1960 United States Western Europe Japan China Indonesia India Belarus,Estonia et al. Brazil South East Africa 1970 1980 1990 2000 2010 Scenario A Global average 2020 2030 2040 2050 2060 2070 2080 2090 2100 ALPS-A ALPS-B FAO(2006)
ALPS Scenarios for Atmospheric CO2 Concentration 32 1500 CO2 concentration (ppm) 1300 1100 900 700 500 300 1990 2010 2030 2050 2070 2090 2110 2130 2150 ALPS A-Baseline ALPS CP6.0 ALPS CP4.5 ALPS CP3.7 ALPS CP3.0 RCP8.5 RCP6.0 RCP4.5 RCP3PD Note: only CO2
CO2 Equivalent Concentration Trajectory 33 1500 Concentratins incl. all forcing agents (ppm CO2eq.) 1300 1100 900 700 500 ALPS A-Baseline ALPS A-CP6.0 ALPS A-CP4.5 ALPS A-CP3.7 ALPS A-CP3.0 RCP8.5 RCP6.0 RCP4.5 RCP3PD 300 1990 2010 2030 2050 2070 2090 2110 2130 2150 There are differences in CO2 equivalent concentration between RCP3PD and ALPS CP3.0 due to differences in estimates of CH4 and N2O emission reduction potentials. There are differences in CO2 equivalent concentration between RCP4.5 and ALPS CP4.5 due to differences in estimates of baseline emissions of F-gases.
Aggregated Warming Damages 34 GDP loss due to climate change impacts 7.0% 6.0% 5.0% 4.0% 3.0% 2.0% 1.0% 0.0% 2000 2050 2100 2150 A-Baseline (Global) China India Other Asia A-CP6.0 (Global) A-CP4.5 (Global) A-CP3.7 (Global) A-CP3.0 (Global) China India Other Asia Aggregated global warming damages proposed by Nordhaus, 2010 D(t) GDP Base (t) = a 1T(t) + a 2 (T(t)) a 3 GDP Base : Baseline GDP; T(t): Global mean temperature; a1, a2: coefficients for 12 regions, a3:2.0
CO2 Emission reductions by Region (Only energy-related CO2 emissions) 35 Energy-related CO2 emissions and reductions [GtCO2/yr] 60 50 40 30 20 10 AI-CP4.5 10% 6% 12% 8% 8% Energy-related CO2 emissions and reductions [GtCO2/yr] 60 50 40 30 20 10 AI-CP3.7 19% 10% 24% 13% 12% 0 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 0 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Energy-related CO2 emissions and reductions [GtCO2/yr] 60 50 40 30 20 10 AI-CP3.0 24% 12% 27% 17% 15% Other Non-OECD Other OME India China Other OECD USA CO2 emissions Note 1: All numbers of the emission reduction ratio are represented by the rate in total emission reductions in 2050 in the case of CP3.0. Note 2: The reduction effects are represented as those relative to the baseline emissions. 0 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
CO2 Emission reductions by Sector and Technology 36 CO2 emissions and reductions (GtCO2/yr) 70 60 50 40 30 20 10 AI-CP4.5 6% 3% 9% 9% 5% 13% CO2 emissions and reductions (GtCO2/yr) 70 60 50 40 30 20 10 AI-CP3.7 13% 6% 12% 12% 6% 10% 14% CO2 emissions and reductions (GtCO2/yr) 0 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 70 60 50 40 30 20 AI-CP3.0 10 0 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 14% 12% 13% 10% 9% 13% 13% 0 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Power: CCS Power: renewables Power: nuclear power Power: efficiency improvement & fuel switching among fossil fuels Other energy conversion Residential & commercial Transportation Industry Int. marine & aviation bunker Industrial process CO2 emission reductions from LULUCF CO2 emissions Note 1: All numbers of the emission reduction ratio are represented by the rate in total emission reductions in 2050 in the case of CP3.0. Note 2: The reduction effects are represented as those relative to the baseline emissions. Some of the sectors, e.g., transportation sector, greatly reduce emissions even in Baseline.
People Living in Poverty 37 People living in poverty (millions) 1800 1600 1400 1200 1000 800 600 400 Both mitigation costs and residue damages considered Europe and Former Soviet Union Latin America Sub-Sahara Africa Middle east and North Africa Other Asia India China 200 0 C V C V C V C V C V C V C V C V C V baseline CP4.5 CP3.0 baseline CP4.5 CP3.0 baseline CP4.5 CP3.0 2000 2030 2050 2100 Note: Constant and variant international poverty lines are adopted by using the poverty thresholds of income at constant 1.25$/day ( C ) and at 1.25-2.83$/day affected by oil price increase ( V ), respectively. People living in poverty will decrease drastically in the future, particularly in Asian regions. However, if the poverty threshold increases due to global social conditions, the decrease will be smaller. The people in CP3.0 will be slightly higher than in other emission scenarios.
People Living under Water Stress 38 200 180 160 140 120 100 80 60 40 20 0 2000 2010 2020 2030 2040 2050 2060 Population living under water stress (Year 2000=100) 2070 2080 2090 2100 A-Baseline A-CP6.0 A-CP4.5 A-CP3.7 A-CP3.0 B-Baseline People under water stress will increase in the world mainly due to population increase and be about 80% increase relative to the 2000 level. GHG emission cuts will not contribute to the mitigation of the stress. The water stress decreases after 2050 in the Scenario B mainly due to population decrease.
Ocean Acidification 39 8.1 Change in ph 8 ph 7.9 A-Baseline A-CP6.0 7.8 A-CP4.5 A-CP3.7 A-CP3.0 7.7 2000 2050 2100 2150 Saturation state of Aragonite (N60 ) 1.8 Aragonite which consists of CaCO3 is undersaturated after 2100 in N60 sea under Baseline emissions. Ω (Aragonite) 1.6 1.4 1.2 1 0.8 A-Baseline 0.6 A-CP6.0 0.4 A-CP4.5 0.2 A-CP3.7 A-CP3.0 0 2000 2050 2100 2150
Analyses on Energy Access and Energy Security
Modern Energy Access: Electricity 41 Without access to electricity (%) 2009 ALPS-A, 2050 - Access to electricity will improve in many Asian countries, while it is still a challenging issue in 2050 only for some countries.
Modern Energy Access: Traditional biomass use 42 Without modern cooking facilities (%) [People relying on the traditional use of biomass for cooking (%)] 2009 ALPS-A, 2050 - Traditional biomass use for cooking harms healths and avoids economic activities. The use in Asian countries will reduce toward 2050, but will be a challenging issue even in 2050 for some countries
Assessment of Energy Security For Different levels of concentration 43 10,000 2000 Vulnerable Energy security index 7,500 5,000 2,500 2050 A-Baseline 2050 A-CP4.5 2050 A-CP3.0 0 US W. Europe Japan China India and S. Asia ESI = coil TPES i ( ) + ( ) 2 gas 2 r S r S i i, oil c TPES i i i, gas Share of imported oil in TPES Political risks of region i Dependence on region i ESI : energy security index, TPES: total primary energy supply Note: index based on IEA, 2007 While the energy security index of Japan decreases (less vulnerable) for CP3.0, that of China, India increases (more vulnerable) for deeper emission reductions due to increase in imported gas shares.