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The Role of Asia in Mitigating Climate Change: Results from the Asia Modeling Exercise Kate Calvin, Leon Clarke, Volker Krey, Geoff Blanford, Jiang Kejun,

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Presentation on theme: "The Role of Asia in Mitigating Climate Change: Results from the Asia Modeling Exercise Kate Calvin, Leon Clarke, Volker Krey, Geoff Blanford, Jiang Kejun,"— Presentation transcript:

1 The Role of Asia in Mitigating Climate Change: Results from the Asia Modeling Exercise Kate Calvin, Leon Clarke, Volker Krey, Geoff Blanford, Jiang Kejun, Mikiko Kainuma, Elmar Kriegler, Gunnar Luderer, P.R. Shukla International Energy Workshop 2012 Cape Town, South Africa June 21, 2012 PNWD-SA-9886

2 Goals of AME  Objective: to better articulate the role of Asia in addressing climate change.  Goal: To bring together global modelers that commonly participate in efforts to explore international policy architectures with regional modelers and experts with Asia-specific knowledge, understanding, data, and analysis.  Method: A coordinated modeling exercise that attempts to link these communities to provide more effective modeling and analysis of Asia within a global context.

3 Participants  26 Participating Models  Australia (GTEM)  Canada (TIAM-World)  China (China MARKAL, IAMC, IPAC, PECE),  EU (GEM-E3, IMAGE, MESSAGE, POLES-IPTS, REMIND, TIMES-VTT, WITCH)  India (GCAM-IIM)  Japan (AIM-CGE, AIM-Enduse, DNE21+, GRAPE, MARIA- 23)  Korea (KEI-Linkages)  Nepal (Nepal MARKAL)  United States (EPPA, GCAM, iPETS, MERGE, Phoenix)

4 The Models  Models differ with respect to:  Regional scope (Global, China only, Nepal Only)  Time horizon (through 2100, through 2050)  Degree of foresight (myopic, intertemporally optimizing)  Underlying structure (market-equilibrium, cost minimization)  Sectoral coverage (Energy only, Energy & Agriculture/Land-Use, Full Economy)  Emissions included (CO 2 only, Kyoto gases only, all species)  Climate representation (No representation, GHG concentrations only, all radiative forcing agents)

5 Exercise Design  Six Core Scenarios:  Baseline  3 CO 2 price paths These scenarios were used to link between the global and regional models.

6 Exercise Design  Six Core Scenarios:  Baseline  3 CO 2 price paths  2 Stabilization paths (global models only)  550 CO 2 -e stabilization (total forcing)  450 CO 2 -e overshoot (total forcing)  For models without all forcing agents, we provided exogenous paths that they could use.

7 Exercise Design  Six Core Scenarios:  Baseline  3 CO 2 price paths  2 Stabilization paths (global models only)  All policies are first-best (immediate accession, economy-wide CO 2 prices/constraints)  No harmonized variables in the core scenarios

8 Variation in AME Baselines Median and Range Across Models in 2100

9 Exercise Design  We created several subgroups, which allowed us to explore different aspects of the scenarios more in depth.  Subgroup topics:  Base Year Data  Baseline Scenarios  Urban/Rural development  Technology and Technical Change  Global and Regional Mitigation Efforts  National Policies and Measures  Low Carbon Societies

10 Exercise Design  We created several subgroups, which allowed us to explore different aspects of the scenarios more in depth.  Subgroup topics:  Base Year Data  Baseline Scenarios  Urban/Rural development  Technology and Technical Change  Global and Regional Mitigation Efforts  National Policies and Measures  Low Carbon Societies

11 RESULTS

12 Base Year Data Deviation from UN 2010 Deviation from WB

13 Base Year Data

14 Deviation from UN 2010 Deviation from WB

15 Base Year Data Deviation from IEA Deviation from CDIAC

16 Base Year Data  Key findings:  There are some good reasons why base year data differs across models. Examples include:  Differences in region definition  Differences in data sources  Differences in modeled base year  Differences in calibration method  While differences in base year data do affect future growth projections, differences in assumed growth rates have a much larger impact on the future.

17 Baseline Scenarios

18 Japan Taiwan Korea Malaysia Model projections 1990 – 2005 data EIA projection Baseline Scenarios PC TPE = 1% PC TPE = 2% PC TPE = 3%PC TPE = 4%PC TPE = 5% PC TPE = -1% PC TPE = 0% PC TPE = -2% Average Growth Rates in China, 2005 – 2020 with comparison to Asian history

19 Baseline Scenarios Average Growth Rates in China, 2005 – 2020

20 Baseline Scenarios  Key findings:  Models differ in their projections of economic growth, energy intensity, and carbon intensity  Differences in underlying growth assumptions result in a factor of 2 difference in Chinese CO 2 emissions across models in 2020  Models with similar emissions levels may achieve them in very different ways  The models do not span the full uncertainty range. This is merely the range of modelers’ “best guesses.”

21 Variation in AME Policy Case Median and Range Across Models in 2100 Assumes a carbon price of $30/tCO 2 in 2020, rising at 5% p.a.

22 Global & Regional Mitigation Global Marginal Abatement Cost Curves, 2005 – 2050

23 Global & Regional Mitigation Fossil fuel & industrial CO 2 emissions in 2050, relative to baseline

24 Global & Regional Mitigation Fossil fuel & industrial CO 2 emissions reductions in 2050, relative to world

25 Electricity Generation by model, region, and fuel in 2050 in $30/tCO 2 Scenario Technology

26 Global & Region Mitigation  Key findings:  Models differ significantly in the amount of mitigation achieved for a particular carbon price  Some regions show less mitigation than others, regardless of the model considered  Differences in mitigation are due to a variety of factors, including:  Differences in baseline emissions levels  Differences in model flexibility  Differences in technology cost and availability

27 Technology  Key findings:  Models show a wide variety of future energy systems across time and scenarios.  Variation is due to differences in assumed technology cost, resource availability, etc.  While there is some variation across regions within a model due to resource constraints, many models tend to “favor” certain technologies.

28 Other Analyses  Urban/Rural Development:  Analyzed the effect of urbanization on energy use and emissions  Finding: Urbanization has an effect on solid fuel consumption, but may not strongly influence total CO 2 emissions  National Policies & Measures:  Compared results from the models to Copenhagen pledges and MEF/G8 goals  Finding: Stringency of Copenhagen pledges varies across regions, and to a lesser extent across models  Low Carbon Societies:  Assessed policies and measures needed to implement 2 degree scenarios

29 Summary  The Asia Modeling Exercise brought together more than 20 energy-economy and integrated assessment models.  These models ran a set of coordinated scenarios.  We focused our analysis of the results on Asian regions.  We analyzed results across a variety of dimensions, including base year data, baselines, global & regional mitigation, technology, and national policies & measures.  We find that models differ significantly across a number of variables, reflecting uncertainty in the future evolution of the world’s economy and energy system. However, there were some robust results across models.

30 THANK YOU!


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