M. Amann, W. Schöpp, 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) Country-by-country, medium-term up to 2030 Challenges: How to capture linkages in emissions, controls, impacts, and instruments? How to model structural changes?

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

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

Emission- and cost calculation Emission calculation: Σ act i,j * emission factor i,j,l = total emissions l –For each pollutant l –Emission factors include effects of controls –Captures multi-pollutant effects of individual measures Cost calculation: Σ act i,j * cost coeff i = total costs –Cost coefficients describe costs for each technology, not allocated to a specific pollutant –Serves as objective function in optimization

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

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

Carbon trading Between countries: Σ act buy * emission factor CO2 - trade  total CO 2, buy Σ act sell * emission factor CO2 + trade  total CO 2, sell –Also possible for other GHGs/basket of GHGs Buying C from the world market: Σ act buy * emission factor CO2 - trade  total CO 2, buy Σ other costs + trade * C price = total costs Pollution taxes: Σ other costs + Σ emissions l * tax l = total costs

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

A multi-pollutant/multi-effect problem

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