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M. Amann, W. Sch öpp, J. Cofala, G. Klaassen

M. Amann, W. Sch öpp, J. Cofala, G. Klaassen. The RAINS-GHG Model Approach Work in progress. Introduction of GHGs into RAINS. Task: Develop cost curves for GHGs (CO 2 , CH 2 , N 2 O, CFC, HFC, SF 6 ) in addition to SO 2 , NO x , VOC, NH 3 , PM, (BC, CO)

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M. Amann, W. Sch öpp, J. Cofala, G. Klaassen

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  1. M. Amann, W. Schöpp, J. Cofala, G. Klaassen The RAINS-GHG Model Approach Work in progress

  2. Introduction of GHGs into RAINS Task: • Develop cost curves for GHGs (CO2, CH2, N2O, CFC, HFC, SF6) in addition to SO2, NOx, VOC, NH3, PM, (BC, CO) • Country-by-country, medium-term up to 2030 Challenges: • How to capture linkages in emissions, controls, impacts, and instruments? • How to model structural changes?

  3. Traditional RAINS optimization • Decision variables: segments of pollutant-specific cost curves • No interaction between pollutants • Cost curves fixed for given energy structure, no structural change possible

  4. New decision variables Decision variables:Amounts of economic activities controlled by a given abatement measure k (acti,k) • Each technical measure represented as a variable For each activity class i: Σ acti * effj = total activity • Derived from an exogenous baseline scenario • E.g., demand for useful energy (transport volume) • Kept constant in RAINS calculations

  5. Emission- and cost calculation Emission calculation: Σ acti,j *emission factori,j,l = total emissionsl • For each pollutant l • Emission factors include effects of controls • Captures multi-pollutant effects of individual measures Cost calculation: Σ acti,j *cost coeffi = total costs • Cost coefficients describe costs for each technology, not allocated to a specific pollutant • Serves as objective function in optimization

  6. Efficiency improvements and fuel substitution Efficiency improvements: eff > 1 inΣ acti * eff = total activity . or: Σ acti + sav = total activity Fuel substitution (e.g., coal  gas): • Decision variable fs: Σ acti * eff + fs = total coal use Σ acti * eff - fs = total gas use Costs and applicability limits derived from sensitivity runs of full energy model!

  7. Environmental constraints Air quality: Σ emissions i * transfer functionik target levelk • For each receptor k • For deposition, air quality, health effects, etc. • Simultaneous constraints for multiple effects Greenhouse gases (l): Σ emissions il * Xl emission ceiling • For each country or groups of countries • For each GHGs or a basket of GHGs • Xl : weighting factor (GWP) or function (radiative forcing)

  8. Carbon trading Between countries: Σ actbuy *emission factorCO2 - trade  total CO2,buyΣ actsell *emission factorCO2 + trade  total CO2,sell • Also possible for other GHGs/basket of GHGs Buying C from the world market: Σ actbuy *emission factorCO2 - trade  total CO2,buy Σ other costs +trade * C price = total costs Pollution taxes: Σ other costs +Σemissionsl * taxl = total costs

  9. Costs and benefits Simplifications: • Temporal aspects (reflected by constraints) • Substitution options (reflected by constraints) Gains: • Capture full interaction between pollutants • Allow systematic exploration of co-benefits • Enables full integrated assessment of air pollution and climate change Requirements: • Link to full energy model to derive limits • Embed in long-term energy/climate scenarios

  10. A multi-pollutant/multi-effect problem

  11. Conclusions • Work in progress • Building, as far as possible, on reviewed RAINS databases and UNFCCC information • Cooperation with climate modelling community welcome • Methodology and implementation to be completed by late 2004 • Further workshops at IIASA to discuss details and review progress

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