Three policy scenarios for CAFE Markus Amann, Janusz Cofala, Chris Heyes, Zbigniew Klimont, Wolfgang Schöpp, Fabian Wagner Three policy scenarios for CAFE
Assumptions CAFE baseline “with climate measures” for 2020 Agricultural projections without CAP reform Further measures for road emissions taken Meteorology of 1997
Costs for reducing the four effects between CLE and MTFR *) excluding costs for road sources
Targets selected for the optimization Ambition level CLE Low Medium High MTFR Years of life lost due to PM2.5 (EU-wide, million YOLLs) 137 110 104 101 96 Acidification (country-wise gap closure on cumulative excess deposition) 0% 55% 75% 85% 100% Eutrophication (country-wise gap closure on cumulative excess deposition) Ozone (country-wise gap closure on SOMO35) 60% 80% 90%
Emission control costs for three ambition levels for the four targets *) excluding costs for road sources
Effects in 2000 and for CAFE medium ambition 2020 PM Eutrophication Ozone Acid, forests Acid, lakes Acid, semi-nat.
Optimized emission reductions for EU-25 of the D23 scenarios [2000=100%]
Costs per pollutant for EU-25 on top of CLE
Measures taken in the D23 medium ambition scenario SO2 Low sulphur coal Low sulphur heavy fuel oil Flue gas desulphurization NOx Combustion modifications Selective non-catalytic and catalytic reduction NOx reduction from light- and heavy-duty diesel vehicles PM High efficiency dedusters New boiler types in the residential sector Good housekeeping measures on oil boilers Low sulphur fuels for (national) sea traffic
Measures taken in the D23 medium ambition scenario VOC Control of fugitive losses in organic chemical industry Switch emulsion bitumen in road paving Paint application (coatings) Stage II Liquid fuel production (improved flare and reduction of fugitive losses) Ammonia Application of pig and cattle manures with low ammonia application measures Substituting ammonium nitrate by urea Covers on manure storage for pigs and cattle Changes in feeding strategies
Distribution of costs [€/person/year] *) excluding costs for road sources
Distribution of physical benefits Medium ambition scenario % point improvements in total European effect indicators*), sum over four effects *) between CLE and MTFR
Sensitivity analyses How would measures for ships change the outcomes? Are emission reductions in the joint optimization driven by health or ecosystems targets? How would alternative health impact theories change the results? How would national energy and agricultural projections change the optimization outcome?
With “medium ambition” measures for ships Sensitivity analysis 1: With medium ambition measures for ships [million €] Without ship measures With “medium ambition” measures for ships Costs for land-based sources Costs for ships Total costs Cost difference Low ambition 5953 5813 28 5841 -140 Medium ambition 10709 10522 10550 -159 High ambition 14882 14582 14556 -326
Sensitivity analysis 2: Are PM or ecosystems targets driving? *) excluding costs for road sources
Sensitivity analysis 2: Are PM or ecosystems targets driving?
Sensitivity analysis 3: Uncertainties in PM health impact theories Alternative hypothesis: “Secondary inorganic aerosols do not contribute to health impacts, all PM effects are related to primary PM2.5 emissions” Sensitivity study: Achieve same relative improvement in mortality estimated for CLE based on “primary PM only” theory – or, expressed alternatively: Reduce primary PM2.5 concentrations by the same percentage as total PM2.5 would be reduced in reference case Two optimization runs: Health only Multi-effect optimization
PM fractions associated with health impacts Natural Sec organics Nitrates Sulfates Carbon Primary non-carbon Standard RAINS approach Sensitivity case WHO advice Primary anthrop. particles Secondary anthrop. particles
Sensitivity analysis 3: Control costs for alternative impact theories
Sensitivity analysis 3: Reductions of “Primary PM only” case vs Sensitivity analysis 3: Reductions of “Primary PM only” case vs. Standard approach, joint optimization
Sensitivity analysis 4: Implications of national energy and agricultural projections National energy and agricultural projections available for 10 countries However, these do not comply with Kyoto obligations Two questions: How would optimization results (“emission ceilings”) change based on the national projections? What about the feasibility/costs of emission ceilings, if the underlying projection does not materialize? Approach: Joint optimization with national projections for same target setting rules (gap closures and relative YOLL improvement recalculated for new CLE/MTFR)
CO2 emissions in 2020 of national and PRIMES energy projections, relative to 2000 40% 60% 80% 100% 120% 140% Belgium Denmark Finland France Italy Portugal Sweden UK Czech Republic Slovenia With climate measures No further climate measures National projection
Sensitivity analysis 4: Costs of optimized scenarios, CAFE baseline vs Sensitivity analysis 4: Costs of optimized scenarios, CAFE baseline vs. national projections Billion €/year *) excluding costs for road sources
Sensitivity analysis 4: SO2 emissions, CAFE baseline vs Sensitivity analysis 4: SO2 emissions, CAFE baseline vs. national projections Emissions in 2000 = 100%
Conclusions Three cases calculated for three ambition levels: costs of 6, 11 and 15 billion €/year For targets on PM, eutrophication, acidification and ozone Resulting emission reductions are cost-effective and have equitable distributions of costs and physical benefits Findings from sensitivity analyses: Control of ship emissions decrease overall costs Optimization driven by health and ecosystems targets Multi-effect optimization increases robustness against uncertainties in health impact mechanisms Robustness against national energy projections needs further attention (and more robust national projections!)