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M. Amann G. Klaassen, R. Mechler, J. Cofala, C. Heyes International Institute for Applied Systems Analysis (IIASA) Modelling synergies and trade-offs between.

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Presentation on theme: "M. Amann G. Klaassen, R. Mechler, J. Cofala, C. Heyes International Institute for Applied Systems Analysis (IIASA) Modelling synergies and trade-offs between."— Presentation transcript:

1 M. Amann G. Klaassen, R. Mechler, J. Cofala, C. Heyes International Institute for Applied Systems Analysis (IIASA) Modelling synergies and trade-offs between mitigation of GHGs and air pollution with the RAINS model

2 Linkages between air pollution and climate Air pollutants have radiative forcing: Ozone controls serve air quality and climate concerns Aerosols/PM damage human health and influence climate Environmental impacts of CC and AP are interlinked Synergies and trade-offs in emission controls

3 A multi-pollutant/multi-effect framework extended to GHGs PMSO 2 NO x VOCNH 3 CO 2 CH 4 N2ON2O CFCs HFCs SF 6 Health impacts: PM  O 3  Vegetation damage: O 3  Acidification  Eutrophication  Radiative forcing: - direct  - via aerosols  - via OH 

4 Introducing GHGs into RAINS Develop cost curves for GHGs (CO 2, CH 4, N 2 O, HFC, PFC, SF 6 ) in addition to SO 2, NO x, VOC, NH 3, PM, (BC, CO) Country-by-country, medium-term up to 2030 Include structural changes as means for emission controls Capture synergies and trade-offs

5 CO 2 control options in the power sector Shift from  to  GasHydro Bio- mass Wind onshore Wind offshore Solar PV Other renew. Carbon capture Brown coalxxxxxxx Hard coalxxxxxxxx Heavy fuel oil xxxxxxx Natural gasxxxxxx

6 CO 2 cost curve Germany, power sector, 2020

7 Options to control CH 4 TechnologyCost (€/tCH4) TechnologyCost (€/tCH 4 ) Paper recycling-1750 Further gas use in gas extraction 7 Improved feeding-1231 Housing adaptation15 Increased gas flaring-377 Alternative rice strains45 Improved I&M for gas distribution -200 Digestion66 Gas use in oil extract.-187 Integrated waste water systems100 Recovery in coal mines-67 Doubling leak control1203 Gas use in gas extraction -57 Waste diversion1438 Ban of agricultural waste burning 0 Replace gray cast iron network2378 Propionate precursors4250

8 CH 4 cost curve France, 2020

9 First preliminary results

10 Data and assumptions Latest RAINS energy- & cost data For EU-25, excluding Cyprus and Malta (EU-23) For 2020

11 Reference case (REF) CAFE “without climate measures” energy projections for 2020 Air pollution control according to recent EU legislation (NEC Directive, LCP Directive, Auto-Oil, etc.)

12 Scenario 1: Fuel-shift CO 2 control in the power sector Cost-effective fuel shift measures to reduce CO 2 emissions in the power sector by 15 % Subject to exogenous electricity demand

13 Fuel shifts applied to reduce CO 2 emissions

14 CO 2 [Mt ] NO x [kt] SO 2 [kt] PM2.5 [kt] Changes in emissions compared to REF, EU-23 -40 -30 -20 -10 0 10 20 30 Fuel-shiftMulti-gasBio-fuel -80 -70 -60 -50 -40 -30 -20 -10 0 10 Fuel-shiftMulti-gasBio-fuel -250 -200 -150 -100 -50 0 Fuel-shiftMulti-gasBio-fuel -250 -200 -150 -100 -50 0 Fuel-shiftMulti-gasBio-fuel

15 Differences in premature deaths (cases/year, compared to REF) -4000 -3000 -2000 -1000 0 1000 Fuel-shiftMulti-gasBio-fuel

16 Emission control costs (billion €/yr, compared to REF) Control ofFuel-shift scenario CO 2 +3.5 CH 4 0 GHGs+3.5 SO 2 -1.4 NO x -0.3 PM-0.6 Air pollutants-2.3 Total+1.2

17 Scenario 2: Multi-gas Multi-GHG control In each country, the equivalent CO 2 reductions of the Fuel-shift scenario are achieved with CO 2 and CH 4 controls

18 CH 4 reduction measures applied in the Multi-gas scenario

19 Fuel shifts applied in the Fuel-shift and Multi-gas scenarios

20 CO 2 [Mt ] NO x [kt] SO 2 [kt] PM2.5 [kt] Changes in emissions compared to REF, EU-23 CH 4 -40 -30 -20 -10 0 10 20 30 Fuel-shiftMulti-gasBio-fuel -80 -70 -60 -50 -40 -30 -20 -10 0 10 Fuel-shiftMulti-gasBio-fuel -250 -200 -150 -100 -50 0 Fuel-shiftMulti-gasBio-fuel -250 -200 -150 -100 -50 0 Fuel-shiftMulti-gasBio-fuel CH 4

21 Differences in premature deaths (cases/year, compared to REF) -4000 -3000 -2000 -1000 0 1000 Fuel-shiftMulti-gasBio-fuel

22 Emission control costs (billion €/yr, compared to REF) Control ofFuel-shiftMulti-gas CO 2 +3.5+2.1 CH 4 0-1.2 GHGs+3.5+0.9 SO 2 -1.4-1.2 NO x -0.3-0.2 PM-0.6-0.4 Air pollutants-2.3-1.8 Total+1.2-0.9

23 Scenario 3: Bio-fuels Increased biomass use in households Shift to biomass use for domestic heating: 10% of light fuel oil is replaced by biomass

24 CO 2 [Mt ] NO x [kt] SO 2 [kt] PM2.5 [kt] Changes in emissions compared to REF, EU-23 CH 4

25 Differences in premature deaths (cases/year, compared to REF)

26 Emission control costs (billion €/yr, compared to REF) Control ofBio-fuel scenario CO 2 +0.6 CH 4 0 GHGs+0.6 SO 2 -0.1 NO x 0 PM0 Air pollutants-0.1 Total0.5

27 Further work Finalization of cost curves for other GHGs Optimization tool: –Separate and joint optimization of emission controls for air pollutants and GHGs: –With constraints (targets) for air quality –With constraints (targets) for radiative forcing/GWP –Simulation of emission trading, emission taxes Implementation for developing countries

28 Conclusions (1) Important synergies and trade-offs exist between air pollution control and GHG mitigation Integration can maximize synergies and avoid trade-offs To be truly cost-effective, climate policies have to account for cost savings of reducing traditional air pollutants - both for industrialized and developing countries

29 Conclusions (2) Multi-pollutant/multi-effect/multi-scale strategies: offer more flexibility and increased potential for economic efficiency harness multiple benefits of measures when costs are increasing connect global long-term climate objectives with concrete local near-term benefits


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