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Scenarios For Differentiating Commitments : A quantitative analysis

Scenarios For Differentiating Commitments : A quantitative analysis. EU Expert Group on Further Action Berlin, May 14, 2003 Odile Blanchard, LEPII-EPE (Previously IEPE). Overview. Possible elements and options of a climate protection architecture

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Scenarios For Differentiating Commitments : A quantitative analysis

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  1. Scenarios For Differentiating Commitments :A quantitative analysis EU Expert Group on Further Action Berlin, May 14, 2003 Odile Blanchard, LEPII-EPE (Previously IEPE)

  2. Overview • Possible elements and options of a climate protection architecture • Differentiated commitment scenarios : objectives, methodology, assumptions • Comparative results • Implementation issues • Conclusion

  3. Designing a Climate Protection Architecture:Possible Elements and Options • Legal Nature of Commitments • Binding • Non-Binding • Mixture • Type of GHG Limitation Commitment • Tax • PAMs (e.g., harmonized PAMs; SD-PAMs) • Targets (e.g., fixed, dynamic, dual) • Approach to Differentiating Commitments • Pledge-based (e.g., Kyoto-style) • Principle-based (e.g., Brazilian Proposal, equal per capita) • Timing and Triggers • By existing or new Annex • Coverage and Scope of Actions - Different gases and/or sectors

  4. Designing a Climate Protection Architecture:Possible Elements and Options Continued… • Market-Based Mechanisms • Int’l emissions trading • CDM • Sector-CDM • Financial and Technology Commitments • Funding for adaptation/impacts compensation • Funding for clean energy development • Accountability Mechanisms • Measurement, reporting, and review of commitments • Compliance system • Overall Environmental Objective • UNFCCC Article 2 • More specific (e.g., keep 450 CO2 eq. option open)

  5. Building on the Kyoto Protocol: Options for Protecting the Climate 1. Introduction: An Architecture for Climate Protection 2. Continuing Kyoto: Emission Caps in DCs? 3. Sustainable Development Policies and Measures 4. Evolving to a Sector-Based CDM 5. Dual-Intensity Targets:Reducing Uncertainty 6. Learning from the Argentine Voluntary Commitment 7. The Brazilian Proposal onRelative Responsibility 8. Equal Per Capita Entitlements 9. Differentiated Commitment Scenarios: Quantitative Analysis 10. Conclusion: Building and Effective and Fair Climate Protection Architecture

  6. 9. Differentiated Commitment ScenariosObjectives • Illustrate the formalization of a few emission allocation proposals, 2010-2030 • For each allocation scenario, quantitatively assess : - the emission allowances distributed across countries - the emission reduction costs - the impacts of trade

  7. 9. Differentiated Commitment ScenariosMethodology • Set an intermediate (2030) environmental goal, compatible with a long term CO2 concentration target of 450-550 ppmv : 9.4 GtC in 2030 • Define 3 worldwide scenarios: - Per Capita Convergence scenario - Relative Responsibility scenario • Emissions-Intensity Target scenario • POLES model and ASPEN software

  8. Why stabilization below 10 GtC by 2030 ? Fossil fuel CO2 emissions from mitigation scenarios for 550ppmv stabilization IPCC TAR WGIII

  9. Why stabilization below 10 GtC by 2030 ? Fossil fuel CO2 emissions from 76 post- SRES stabilization scenarios IPCC TAR WGIII

  10. Tools developed at IEPE • POLES(Prospective Outlook on Long-term Energy Systems): a world simulation energy model, partial equilibrium, 38 countries/regions. Main outputs : • energy supply, demand, price projections to 2030 • GHG emission marginal abatement curves (MAC) by regions/countries • ASPEN (Analyse des Systemes de Permis d’Emission Negociables), computes : • GHG emission allocations based on the allocation rule chosen ; • emission permit price and trade flows, for any permit market

  11. Quantitative assessments:2010 and 2030 assumptions • 2010 CO2 world emissions : 7.8 GtC (+38 % /1990), resulting from : • Annex 1 : comply with KP commitment, except USA, Eastern Europe • USA : Feb 14, 2002 “Bush Adm. Rule” (-18 % emission intensity over 10 years) • Eastern Europe: BAU emissions (to avoid “hot air”) • Non-Annex 1: BAU emissions • 2030 BAU world emissions : almost 12 GtC (+ 111% /1990)

  12. Emissions per capita scenario : assumptions • Convergence year: 2050, at 0.95 tC/cap. • Transition period : 2011-2049 with a yearly carbon budget to allocate (resource sharing) • 2010-2030 yearly global CO2emissions budget calculated on a linear basis to reach 9.4 GtC in 2030. 2030-2040: global emissions stabilization at 9.4 GtC • 2040-2050: -1%/y global emissions reduction • Using one of GCI’s proposed equations for convergence

  13. Emissions per capita scenarioConvergence equation • Country’s annual emissions share: Sy = Sy-1 - (Sy-1 - Py)*exp(-a*(1-t)) Sy : emissions share in year y Py : population share in year y a: convergence coefficient (= 4) t : elapsed time ratio between starting year (2011, t = 0 ) and convergence year (2050, t = 1) • Country’s annual emissions entitlement: share Sy multiplied by the global CO2 emissions budget of year y • Source: adapted from GCI

  14. Relative responsibility scenario : assumptions • Brazilian-type approach : reductions sharing • 2010-2030 yearly global CO2 emissions budget: same as for Per capita convergence scenario • 2010-2030 yearly global CO2 emission reductionsrelative to BAU • Distribution of the yearly reductions among ALL countries, based on relative responsibility • CO2 cumulative emissions from 1900 • Responsibility of a country: ratio of cumulative emissions of the country/world cumulative emissions • 2011-2015 relative responsibility: refers to 2005 ratio 2016-2020 to 2010; 2021-2025 to 2015 BAU; 2026-2030 to 2020 BAU.

  15. Relative responsibility scenario : calculating emission reductions, an example • 2030 global CO2 reductions: BAU - Emission Budget= 11.981 - 9.4 = 2.581GtC • 2030 US relative responsibility : US CO2 cumulative emissions 1900-2020: 111.3 GtC World CO2 cumulative emissions 1900-2020: 421 GtC US 2030 responsibility ratio: 111.3 / 421 = 26.43 % • US 2030 emission reductions relative to BAU : 2.581 * 26.43 % = 0.682 GtC = 682 MtC

  16. Emissions-Intensity Target scenario: assumptions • 2030 global CO2 emissions target: still 9.4 GtC • Approach based on relative changes of em / GDP (no absolute figures for em/GDP) ; country specific • Various simulations carried out to reach the 9.4 GtC target • Simulation used: • Annex I improve CO2/GDP by 2 % yearly from BAU trend ; • Non-Annex I : 0.5 % improvement from BAU trend

  17. Results: Comparing Emission Allowances • All scenarios meet the near-term environmental goal • In all scenarios, more stringent emission limitations in Annex I than in Non-Annex I countries • 2030 emission allowances above 1990 levels for all Non-Annex I countries • In the Per Cap Convergence scenario, some Non-Annex I countries would have allowance surpluses relative to their BAU emissionprojections in 2030

  18. Results : comparing emission allowancesReduction (–) or increase (+) in 2030 emissions relative to 1990 (%)

  19. Results: Comparing Emission Allowances Distribution of CO2 Emissions allowances

  20. Results: Comparing Emission Allowances Per capita CO2 emission allowances

  21. Results: Comparing Costs and Trade • Across all scenarios, higher emission reduction costs in Annex I than in Non-Annex I • Trade: all countries benefit from trade ; typically, Annex I countries are buyers; Non-Annex I countries are sellers • Highest volume of trade and highest gains from trade in the Per CapitaConvergence scenario

  22. Results :Comparing impacts of trading

  23. Implementation issues : Per capita convergence • Principle-based : egalitarian • What long-term environmental goal (“emission budget”) ? What yearly contraction path ? What level of convergence? • Emissions trading is essential • Does not account much for national circumstances • Acceptability : low for Annex I, high for Non-Annex I • Variants : more acceptable but more complex (e.g. Aslam’s proposal : fixed minimum per capita level + variable per capita portion related to country-specific circumstances)

  24. Implementation issues : Relative responsibility • Principle-based : polluter pays • Choice of indicator of responsibility:how far down the causal chain of global warming ? • Data challenges: • Consensus on distant past CO2-energy related figures ? • Data for CO2 from land-use change, non-CO2 GHGs? Sensitivity analyses. • Acceptance of Annex I responsibility for pre-1990 emissions ? • Bringing developing countries on board : • Delay participation (thresholds: GDP/cap, non-Annex I responsibility vs Annex I) • Reductions relative to a dynamic baseline • Responsibility principle for Annex I, other basis for non-Annex I commitments

  25. Implementation issues : Emissions-intensity targets • Pledge-based target: as many targets as countries ; choice of adjustment form of GHG emissions to GDP changes, need for capacity building • Additional data set : GDP • GDP measure : domestic currency • Emission intensity targets expressed in rates of change, rather than absolute terms • Emissions trading: after compliance period ; or allow trade during commitment period (GDP projections and commitment period reserve)

  26. Conclusion (1): Scenarios for differentiating commitments • Reaching 550 ppmv stabilization of CO2 concentrations by 2100 requires stringent reductions in the near-term, particularly by Annex I countries • Emission allowances and emission reduction costs vary for each country across the 3 scenarios • Helpful information for countries to shape their negotiating position • Extension of work: exempt some countries from emission limitations ; mix approaches

  27. Conclusion (2): options for climate protection • No proposal can satisfy the interests and concerns of all countries • Design of a menu of near-term options to build confidence and capacity… - Stronger leadership of developed countries in emission reductions - Multiple options : enhanced participation in emission reductions - But potentially insufficient to address climate change over the LT • … coupled to a principled, long-term framework - To combat bargaining power of pledged-based commitments - To avoid the complexity of multiple options - Could include a more definite environmental objective

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