1. Overlaps of AQ and climate policy – global modelling perspectives David Stevenson Institute of Atmospheric and Environmental Science School of GeoSciences The University of Edinburgh Thanks to: Ruth Doherty (Univ. Edinburgh) Dick Derwent (rdscientific) Mike Sanderson, Colin Johnson, Bill Collins (Met Office) Frank Dentener, Peter Bergamaschi, Frank Raes (JRC Ispra) Markus Amann, Janusz Cofala, Reinhard Mechler (IIASA) NERC and the Environment Agency for funding

2. Material mainly from 2 current publications: The impact of air pollutant and methane emission controls on tropospheric ozone and radiative forcing: CTM calculations for the period 1990-2030 Dentener et al (2004) Atmos. Chem. Phys. Disc. (currently open for discussion on the web) Impacts of climate change and variability on tropospheric ozone and its precursors Stevenson et al (2005) Faraday Discussions (upcoming discussion meeting at Leeds in April)

3. Rationale Regional-global scale AQ legislation has implications for climate forcing – quantify these for current and possible future policies (use 2 very different models to try and reduce model uncertainty) Climate change will influence AQ – use coupled climate-chemistry model to identify potentially important interactions

4. Modelling Approach Global chemistry-climate model: STOCHEM- HadAM3 (also some results from TM3+others) Three transient runs: 1990 → 2030, following different emissions/climate scenarios: 1. Current Legislation (CLE) Assumes full implementation of all current legislation 2. Maximum Feasible Reductions (MFR) Assumes full implementation of all available current emission reduction technology 3. CLE + climate change For 1 and 2, climate is unforced, and doesn’t change. For 3, climate is forced by the is92a scenario, and shows a global surface warming of ~1K between 1990 and 2030.

5. STOCHEM-HadAM3 Global Lagrangian chemistry-climate model Meteorology: HadAM3 + prescribed SSTs GCM grid: 3.75° x 2.5° x 19 levels CTM: 50,000 air parcels, 1 hour timestep CTM output: 5° x 5° x 9 levels Detailed tropospheric chemistry − CH 4 -CO-NO x -hydrocarbons (70 species) − includes S chemistry Interactive lightning NO x, C 5 H 8 from veg. these respond to changing climate ~3 years/day on 36 processors (SGI Altix)

6. Global NO x emissions Figure 1. Projected development of IIASA anthropogenic NO x emissions by SRES world region (Tg NO 2 yr -1 ). CLE SRES A2 MFR

7. Global CO emissions Figure 2 Projected development of IIASA anthropogenic CO emissions by SRES world region (Tg CO yr -1 ). CLE SRES A2 MFR

8. Global CH 4 emissions Figure 3: Projected development of IIASA anthropogenic CH 4 emissions by SRES region (Tg CH 4 yr -1 ). CLE SRES A2 MFR

9. Figure 4. Regional emissions separated for sources categories in 1990, 2000, 2030-CLE and 2030-MFR for NO x [Tg NO 2 yr -1 ] Regional NO x emissions 1990 2000 2030 CLE 2030 MFR

10. Surface O 3 (ppbv) 1990s

11. BAU Change in surface O 3, CLE 2020s-1990s >+10 ppbv India +2 to 4 ppbv over N. Atlantic/Pacific A large fraction is due to ship NO x CLE

12. CLE Surface Annual Mean O 3 2020s-1990s TM3 (top) and STOCHEM (bottom) Figure 13. Decadal averaged ozone volume mixing ratio differences [ppbv] comparing the 2020s and 1990s for (a) TM3 CLE and STOCHEM CLE.

13. Surface ΔO 3 2030CLE–2000 (NB July) 18 Models from IPCC-ACCENT intercomparison

14. MRFBAU Change in surface O 3, MFR 2020s-1990s Up to -10 ppbv over continents

15. Figure 13(b) Decadal averaged ozone volume mixing ratio differences [ppbv] comparing the 2020s and 1990s for TM3 MFR and STOCHEM MFR MFR Surface Annual Mean O 3 2020s-1990s TM3 (top) and STOCHEM (bottom)

16. Surface ΔO 3 2030MFR–2000 (NB July) 18 Models from IPCC-ACCENT intercomparison

17. CH 4,  CH4 & OH trajectories 1990-2030 CLE CLEcc

18. If the world opts for MFR over CLE, net reduction in radiative forcing of 0.2-0.3 W m -2 for the period 2000-2030 Methane controls are the most effective for RF

19. Part 1 Summary Co-benefits for both AQ and climate from some emissions controls Methane offers the best opportunity (also CO and NMVOCs) NO x controls (alone) benefit AQ, but probably worsen climate forcing (via OH and CH 4 ) (Similarly for SO 2 ) AQ policies influence climate – this study gives a quantitative assessment Use of many models shows results are quite consistent

20. ΔO 3 from climate change Warmer temperatures & higher humidities increase O 3 destruction over the oceans But also a role from increases in isoprene emissions from vegetation & changes in lightning NO x 2020s CLEcc- 2020s CLE

21. Zonal mean ΔT (2020s-1990s)

22. Zonal mean H 2 O increase 2020s- 1990s

23. Zonal mean change in convective updraught flux 2020s-1990s

24. C 5 H 8 change 2020s (climate change – fixed climate)

25. Lightning NOx change 2020s (climate change – fixed climate) More lightning in N mid-lats Less, but higher, tropical convection No overall trend in Lightning NOx emissions HadCM3 Amazon drying

26. Zonal mean PAN decrease 2020s (climate change – fixed climate) Increased PAN thermal decomposition, due to increased T Colder LS

27. Zonal mean NO x change 2020s (climate change – fixed climate) Increased PAN decomposition Increased N mid-lat convection and lightning Less tropical convection and lightning

28. Zonal mean O 3 budget changes 2020s (climate change – fixed climate)

29. Zonal mean O 3 decrease 2020s (climate change – fixed climate)

30. Zonal mean OH change 2020s (climate change – fixed climate) Complex function: F(H2O, NOx, O3, T,…)

31. Influence of climate change on O 3 – 4 IPCC ACCENT models

32. Part 2 Summary Climate change will introduce feedbacks that modify air quality These include: – More O3 destruction from H2O – More stratospheric input of ozone – More isoprene emissions from vegetation – Changes in lightning NOx – Increases in sulphate from OH and H2O2 – Wetland CH4 emissions (not studied here) – Changes in stomatal uptake? (``) These are quite poorly constrained – different models show quite a wide range of response: large uncertainties