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

This article has been updated

Abstract

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.

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Acknowledgements

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.

Author information

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.

Affiliations

  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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Contributions

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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DOI

https://doi.org/10.1038/nclimate3354

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