• A Corrigendum to this article was published on 16 October 2017

This article has been updated


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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Change history

  • 16 October 2017

    In the version of this Letter originally published, the first row of Table 1, 'Base results', contained errors. These errors have been corrected in the online versions of this Letter.


  1. 1.

    et al. Long-term ozone exposure and mortality. N. Engl. J. Med. 360, 1085–1095 (2009).

  2. 2.

    et al. Extended follow-up and spatial analysis of the American Cancer Society study linking particulate air pollution and mortality. Respir. Rep. Health Eff. Inst. 140, 5–114 (2009).

  3. 3.

    , , & Chronic exposure to fine particles and mortality: an extended follow-up of the Harvard Six Cities Study from 1974 to 2009. Environ. Health Perspect. 120, 965–970 (2012).

  4. 4.

    et al. An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure. Environ. Health Perspect. 122, 397–403 (2014).

  5. 5.

    et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) Ch. 11 (IPCC, Cambridge Univ. Press, 2013).

  6. 6.

    , & Air quality and climate connections. J. Air Waste Manag. Assoc. 65, 645–685 (2015).

  7. 7.

    et al. Chemistry and the linkages between air quality and climate change. Chem. Rev. 115, 3856–3897 (2015).

  8. 8.

    , & Human mortality effects of future concentrations of tropospheric ozone. C. R. Geosci. 339, 775–783 (2007).

  9. 9.

    et al. Global health and economic impacts of future ozone pollution. Environ. Res. Lett. 4, 044014 (2009).

  10. 10.

    et al. Variation in estimated ozone-related health impacts of climate change due to modeling choices and assumptions. Environ. Health Perspect. 120, 1559–1564 (2012).

  11. 11.

    et al. Global premature mortality due to anthropogenic outdoor air pollution and the contribution of past climate change. Environ. Res. Lett. 8, 034005 (2013).

  12. 12.

    et al. The effect of future ambient air pollution on human premature mortality to 2100 using output from the ACCMIP model ensemble. Atmos. Chem. Phys. 16, 9847–9862 (2016).

  13. 13.

    et al. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): overview and description of models, simulations and climate diagnostics. Geosci. Model Dev. 6, 179–206 (2013).

  14. 14.

    et al. Tropospheric ozone changes, radiative forcing and attribution to emissions in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Atmos. Chem. Phys. 13, 3063–3085 (2013).

  15. 15.

    , , , & Impacts of 21st century climate change on global air pollution-related premature mortality. Climatic Change 121, 239–253 (2013).

  16. 16.

    et al. Climate change, ambient ozone, and health in 50 US cities. Climatic Change 82, 61–76 (2007).

  17. 17.

    et al. Potential impact of climate change on air pollution-related human health effects. Environ. Sci. Technol. 43, 4979–4988 (2009).

  18. 18.

    , & Impact of climate change on ambient ozone level and mortality in Southeastern United States. Int. J. Environ. Res. Public Health 7, 2866–2880 (2010).

  19. 19.

    , , & Modeling of regional climate change effects on ground-level ozone and childhood asthma. Am. J. Prev. Med. 41, 251–257 (2011).

  20. 20.

    et al. The geographic distribution and economic value of climate change-related ozone health impacts in the United States in 2030. J. Air Waste Manag. Assoc. 65, 570–580 (2015).

  21. 21.

    et al. Impact of climate change on ozone-related mortality and morbidity in Europe. Eur. Respir. J. 41, 285–294 (2013).

  22. 22.

    et al. The representative concentration pathways: an overview. Climatic Change 109, 5–31 (2011).

  23. 23.

    et al. Pre-industrial to end 21st century projections of tropospheric ozone from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Atmos. Chem. Phys. 13, 2063–2090 (2013).

  24. 24.

    et al. Radiative forcing in the ACCMIP historical and future climate simulations. Atmos. Chem. Phys. 13, 2939–2974 (2013).

  25. 25.

    et al. Effect of climate change on surface ozone over North America, Europe, and East Asia. Geophys. Res. Lett. 43, 3509–3518 (2016).

  26. 26.

    , & An increase in aerosol burden and radiative effects in a warmer world. Nat. Clim. Change 6, 269–274 (2016).

  27. 27.

    , , & Modeling the effect of temperature on ozone-related mortality. Ann. Appl. Stat. 8, 1728–1749 (2014).

  28. 28.

    , & Does particulate matter modify the association between temperature and cardiorespiratory diseases? Environ. Health Perspect. 114, 1690–1696 (2006).

  29. 29.

    et al. Co-benefits of global greenhouse gas mitigation for future air quality and human health. Nat. Clim. Change 3, 885–889 (2013).

  30. 30.

    et al. in Climate Change 2014: Impacts, Adaptation, and Vulnerability (eds Field, C. B. et al.) 709–754 (IPCC, Cambridge Univ. Press, 2014).

  31. 31.

    et al. RCP 8.5—A scenario of comparatively high greenhouse gas emissions. Climatic Change 109, 33–57 (2011).

  32. 32.

    et al. Global air quality and climate. Chem. Soc. Rev. 41, 6663–6683 (2012).

  33. 33.

    et al. Projections of global health outcomes from 2005 to 2060 using the International Futures integrated forecasting model. Bull. World Health Organ. 89, 478–486 (2011).

  34. 34.

    et al. Historical emissions of black and organic carbon aerosol from energy-related combustion, 1850–2000. Glob. Biogeochem. Cycles 21, GB2018 (2007).

  35. 35.

    , , & Uncertainty analysis of emissions estimates in the RAINS integrated assessment model. Environ. Sci. Policy 8, 601613 (2005).

  36. 36.

    et al. Anthropogenic sulfur dioxide emissions: 1850–2005. Atmos. Chem. Phys. 11, 1101–1116 (2011).

  37. 37.

    et al. Evolution of anthropogenic and biomass burning emissions of air pollutants at global and regional scales during the 1980–2010 period. Climatic Change 109, 163–190 (2011).

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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.

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Author notes

    • Raquel A. Silva

    Present address: Oak Ridge Institute for Science and Education at US Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.


  1. Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina 27599, USA

    • Raquel A. Silva
    •  & J. Jason West
  2. NCAR Earth System Laboratory, National Center for Atmospheric Research, Boulder, Colorado 80307, USA

    • Jean-François Lamarque
  3. Nicholas School of the Environment, Duke University, Durham, North Carolina 27710, USA

    • Drew T. Shindell
  4. Department of Meteorology, University of Reading, Reading RG6 6BB, UK

    • William J. Collins
  5. NASA Goddard Institute for Space Studies and Columbia Earth Institute, New York, New York 10025, USA

    • Greg Faluvegi
  6. Met Office Hadley Centre for Climate Prediction, Exeter EX1 3P, UK

    • Gerd A. Folberth
  7. NOAA Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey 08540, USA

    • Larry W. Horowitz
    •  & Vaishali Naik
  8. National Institute for Environmental Studies, Tsukuba, Ibaraki 305-8506, Japan

    • Tatsuya Nagashima
  9. National Centre for Atmospheric Science, University of Reading, Reading RG6 6BB, UK

    • Steven T. Rumbold
  10. Earth and Environmental Science, Graduate School of Environmental Studies, Nagoya University, Nagoya 464-8601, Japan

    • Kengo Sudo
  11. Research Institute for Applied Mechanics, Kyushu University, Fukuoka 816-8580, Japan

    • Toshihiko Takemura
  12. Lawrence Livermore National Laboratory, Livermore, California 94551, USA

    • Daniel Bergmann
    •  & Philip Cameron-Smith
  13. School of GeoSciences, University of Edinburgh, Edinburgh EH9 3FF, UK

    • Ruth M. Doherty
    • , Ian A. MacKenzie
    •  & David S. Stevenson
  14. GAME/CNRM, Meteo-France, CNRS—Centre National de Recherches Meteorologiques, Toulouse 31057, France

    • Beatrice Josse
  15. National Institute of Water and Atmospheric Research, Wellington 6021, New Zealand

    • Guang Zeng


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J.J.W., J.-F.L., D.T.S. and R.A.S. conceived the study. All other co-authors conducted the model simulations. R.A.S. processed model output and estimated human mortality. R.A.S. and J.J.W. analysed results. R.A.S. and J.J.W. prepared the manuscript and all co-authors commented on it.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to J. Jason West.

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