Methodology and applications of the RAINS air pollution integrated assessment model Markus Amann International Institute for Applied Systems Analysis (IIASA)

Contents Cost-effectiveness analysis The RAINS concept Key methodologies and results

Cost-effectiveness needs integration Economic development Emission generating activities (energy, transport, agriculture, industrial production, etc.) Emission characteristics Emission control options Costs of emission controls Atmospheric dispersion Environmental impacts (health, ecosystems) Systematic approach to identify cost-effective packages of measures

The RAINS integrated assessment model for air pollution Energy/agricultural projections Emissions Emission control options Atmospheric dispersion Health and environmental impacts Costs Driving forces

The RAINS multi-pollutant/multi-effect framework PMSO 2 NO x VOCNH 3 Health impacts: PM  O 3  Vegetation damage: O 3  Acidification  Eutrophication 

System boundaries Driving forces of air pollution (energy use, transport, agriculture) are driven by other issues, and have impacts on other issues too. Critical boundaries: Greenhouse gas emissions and climate change policies (GAINS!) Agricultural policies Other air pollution impacts on water and soil (nitrogen deposition over seas, nitrate in groundwater, etc.) Quantification of AP effects where scientific basis is not robust enough (economic evaluation of benefits)

Policy analysis with the RAINS cost-effectiveness approach Energy/agricultural projections Emissions Emission control options Atmospheric dispersion Health and environmental impacts Costs Environmental targets OPTIMIZATION Driving forces

Per-capita costs NEC1999 Scenario H1

The cost-effectiveness approach Decision makers Decide about Ambition level (environmental targets) Level of acceptable risk Willingness to pay Models help to separate policy and technical issues: Models Identify cost-effective and robust measures: Balance controls over different countries, sectors and pollutants Regional differences in Europe Side-effects of present policies Maximize synergism with other air quality problems Search for robust strategies

RAINS policy applications UN ECE Convention on Long-range Transboundary Air Pollution: –Second Sulphur Protocol 1994 –Gothenburg Multi-pollutant Protocol 1999 European Union –Acidification Strategy 1997 –National Emission Ceilings 1999 –Clean Air For Europe 2005 –Revision of National Emission Ceilings 2007 China –National Acid Rain policy plan 2004 –Multi-pollutant/multi-effect clean air policy 2007 National RAINS implementations –Netherlands, Italy, Finland

Review of RAINS methodology and input data Scientific peer review of modelling methodology in 2004 Bilateral consultations with experts from Member States and Industry on input data –For CAFE: : 24 meeting with 107 experts –For NEC review: 2006: 28 meetings with > 100 experts The RAINS model is accessible online at

Criteria for aggregation of emission sources RAINS applies six criteria: Importance of source (>0.5 percent in a country) Possibility for using uniform activity rates and emission factors Possibility of establishing plausible forecasts of future activity levels Availability and applicability of “similar” control technologies Availability of relevant data

Calculating emissions i,j,k,mCountry, sector, fuel, abatement technology E i,y Emissions in country i for size fraction y AActivity in a given sector ef “ Raw gas ” emission factor eff m,y Reduction efficiency of the abatement option m XImplementation rate of the considered abatement measure

Land-based emissions CAFE baseline “with climate measures”, EU-25

RAINS cost estimates are country- and technology-specific Technology-specific factors: Investments Demand for labour, energy, by-products Lifetime of equipment Removal efficiency Country-specific factors: Prices for labour, energy, by-products, etc. Applicability General factors: Interest rate

An example cost curve for SO 2

Scope for further technical emission reductions CAFE baseline “with climate measures”, EU-25

Source-receptor relationships for PM2.5 derived from the EMEP Eulerian model for primary and secondary PM PM2.5 j Annual mean concentration of PM2.5 at receptor point j ISet of emission sources (countries) JSet of receptors (grid cells) p i Primary emissions of PM2.5 in country i s i SO 2 emissions in country i n i NO x emissions in country i a i NH 3 emissions in country i α S,W ij, ν S,W,A ij, σ W,A ij, π A ij Linear transfer matrices for reduced and oxidized nitrogen, sulfur and primary PM2.5, for winter, summer and annual

Estimating the loss of life expectancy in RAINS Approach Endpoint: –Loss in statistical life expectancy –Related to long-term PM2.5 exposure, based on cohort studies Life tables provide baseline mortality for each cohort in each country For a given PM scenario: Mortality modified through Cox proportional hazard model using Relative Risk (RR) factors from literature From modified mortality, calculate life expectancy for each cohort and for entire population

Input to life expectancy calculation Life tables (by country) Population data by cohort and country, Urban/rural population in each 50*50 km grid cell Air quality data: annual mean concentrations –PM2.5 (sulfates, nitrates, ammonium, primary particles), excluding SOA, natural sources –50*50 km over Europe, rural + urban background –for any emission scenario Relative risk factors

Loss in life expectancy attributable to fine particles [months] Loss in average statistical life expectancy due to identified anthropogenic PM2.5 Calculations for 1997 meteorology CAFE baseline Maximum technical Current legislation emission reductions

Five stages in dynamic acidification modelling Important time factors: Damage delay time Recover delay time

Excess acid deposition to forests Percentage of forest area with acid deposition above critical loads, Calculation for 1997 meteorology CAFE baseline Maximum technical Current legislation emission reductions

Excess nitrogen deposition threatening biodiversity Percentage of ecosystems area with nitrogen deposition above critical loads Calculation for 1997 meteorology CAFE baseline Maximum technical Current legislation emission reductions

Vegetation-damaging ozone concentrations AOT40 [ppm.hours]. Critical level for forests = 5 ppm.hours Calculations for 1997 meteorology CAFE baseline Maximum technical Current legislation emission reductions

Optimized emission reductions for EU-25 of the CAFE policy scenarios [2000=100%]

%10%20%30%40%50%60%70%80%90%100% Health improvement (Change between baseline and maximum measures) Annual Cost €Millions Costs for reducing health impacts from fine PM Analysis for the EU Clean Air For Europe (CAFE) programme

Courtesy of Les White %10%20%30%40%50%60%70%80%90%100% Health improvement (Change between baseline and maximum measures) Annual Cost €Millions RAINS cost-effectiveness approach Equal technology approach Cost savings from the RAINS approach Estimates presented by Concawe

Emission control costs of the CAFE policy scenarios

The critical question on uncertainties in the policy context Not: What is the confidence range of the model results? But: Given all the shortcomings, imperfections and the goals, how can we safeguard the robustness of the model results? Conventional scientific approaches for addressing uncertainties do either not provide policy-relevant answers or are too complex to implement. For practical reasons alternative approach required

In RAINS, uncertainties addressed through (1) Model construction (2) Identification of potential biases (3) Target setting (4) Sensitivity analyses

Uncertainties of intermediate results 95% confidence intervals SO 2 NO x NH 3 Emissions±13 % ±15 % Deposition± % Critical loads excess (area of protected ecosystems) -5% %

Probability for protecting ecosystems Gothenburg Protocol 2010

More advanced methods for treating uncertainties could be developed … But: Are Parties ready to put increased effort into providing and, subsequently, agreeing upon the data needed for such an analysis? Would Parties be prepared to follow abatement strategies derived with such a method, i.e., to pay more for strategies that yield the same environmental improvements but with a higher probability of attainment?