Ground-level ozone and fine particulate matter (PM 2.5) are associated with premature human mortality1,2,3,4; their future concentrations depend on changes in emissions, which dominate the near-term5, and on climate change6,7. Previous global studies of the air-quality-related health effects of future climate change8,9 used single atmospheric models. However, in related studies, mortality results differ among models10,11,12. Here we use an ensemble of global chemistry–climate models13 to show that premature mortality from changes in air pollution attributable to climate change, under the high greenhouse gas scenario RCP8.5 (ref. 14), is probably positive. We estimate 3,340 (−30,300 to 47,100) ozone-related deaths in 2030, relative to 2000 climate, and 43,600 (−195,000 to 237,000) in 2100 (14% of the increase in global ozone-related mortality). For PM 2.5, we estimate 55,600 (−34,300 to 164,000) deaths in 2030 and 215,000 (−76,100 to 595,000) in 2100 (countering by 16% the global decrease in PM 2.5-related mortality). Premature mortality attributable to climate change is estimated to be positive in all regions except Africa, and is greatest in India and East Asia. Most individual models yield increased mortality from climate change, but some yield decreases, suggesting caution in interpreting results from a single model. Climate change mitigation is likely to reduce air-pollution-related mortality.
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This research was funded by NIEHS grant no. 1 R21 ES022600-01, a fellowship from the Portuguese Foundation for Science and Technology, and by a Dissertation Completion Fellowship from The Graduate School (UNC—Chapel Hill). We thank K. Yeatts (Gillings School of Global Public Health, UNC—Chapel Hill), C. Mathers (WHO), P. Speyer (IHME), and A. Henley (Davis Library Research & Instructional Services, UNC—Chapel Hill). The work of D.B. and P.C.-S. was funded by the US Dept. of Energy (BER), performed under the auspices of LLNL under Contract DE-AC52-07NA27344, and used the supercomputing resources of NERSC under contract no. DE-AC02-05CH11231. R.M.D., I.A.M. and D.S.S. acknowledge ARCHER supercomputing resources and funding under the UK Natural Environment Research Council grant: NE/I008063/1. G.Z. acknowledges the NZ eScience Infrastructure, which is funded jointly by NeSI’s collaborator institutions and through the MBIE’s Research Infrastructure programme. G.A.F. has received funding from BEIS under the Hadley Centre Climate Programme contract (GA01101) and from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 641816 (CRESCENDO). D.T.S. and G.F. acknowledge the NASA High-End Computing Program through the NASA Center for Climate Simulation at Goddard Space Flight Center for computational resources.
About this article
Air Quality, Atmosphere & Health (2018)