M. Amann, W. Sch

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, CH4, 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 variablesAmounts of economic
  activities controlled by a given abatement
  measure k (acti,k)
• Each technical measure represented as a variable
• For each activity class i
• S acti effj total activity
• Derived from an exogenous baseline scenario
• E.g., demand for useful energy (transport volume)
• Kept constant in RAINS calculations

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Emission- and cost calculation

• Emission calculation
• S 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
• S 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 gt 1 in S acti eff total activity
• . or S acti sav total
  activity
• Fuel substitution (e.g., coal ? gas)
• Decision variable fs
• S acti eff fs total coal use
• S acti eff - fs total gas use
• Costs and applicability limits derived from
  sensitivity runs of full energy model!

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Environmental constraints

• Air quality
• S 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)
• S 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)

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Carbon trading

• Between countries S actbuy emission factorCO2
  - trade ? total CO2,buyS actsell emission
  factorCO2 trade ? total CO2,sell
• Also possible for other GHGs/basket of GHGs
• Buying C from the world market
• S actbuy emission factorCO2 - trade ? total
  CO2,buy
• S other costs trade C price total costs
• Pollution taxes
• S other costs S emissionsl taxl total
  costs

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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

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A multi-pollutant/multi-effect problem
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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