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Attributing human mortality from fire PM2.5 to climate change

Nature Climate Change volume 14, pages 1193–1200 (2024)Cite this article

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An Author Correction to this article was published on 25 October 2024

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Abstract

Climate change intensifies fire smoke, emitting hazardous air pollutants that impact human health. However, the global influence of climate change on fire-induced health impacts remains unquantified. Here we used three well-tested fire–vegetation models in combination with a chemical transport model and health risk assessment framework to attribute global human mortality from fire fine particulate matter (PM2.5) emissions to climate change. Of the 46,401 (1960s) to 98,748 (2010s) annual fire PM2.5 mortalities, 669 (1.2%, 1960s) to 12,566 (12.8%, 2010s) were attributed to climate change. The most substantial influence of climate change on fire mortality occurred in South America, Australia and Europe, coinciding with decreased relative humidity and in boreal forests with increased air temperature. Increasing relative humidity lowered fire mortality in other regions, such as South Asia. Our study highlights the role of climate change in fire mortality, aiding public health authorities in spatial targeting adaptation measures for sensitive fire-prone areas.

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Fig. 1: Global fire PM2.5, its mortality and ACC.
Fig. 2: The ACC of fire emissions and their risk in the 2010s.
Fig. 3: Regional ACC of fire mortality.
Fig. 4: Spatial model agreements in the 2010s.
Fig. 5: The relation between ACC of fire mortality and ACC of relative humidity or air temperature during the 1960s to 2010s.

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Data availability

Input data (climate and socio-economic forcing and the burnt area in the factual and counterfactual simulations) are available from the ISIMIP data repository (https://data.isimip.org/). Topographic data for making global map were from MathWorks and we used MATLAB R2024a for creating all figures. Intermediate and output data used in this analysis are available at the repository in both MATLAB array and NetCDF formats77. Source data are provided with this paper.

Code availability

All code to reproduce the analysis and figures is available via Zenodo at https://doi.org/10.5281/zenodo.13231638 (ref. 77).

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Acknowledgements

C.Y.P., K.T. and S.F. were supported by the Environment Research and Technology Development Fund (JPMEERF20241001) of the Environmental Restoration and Conservation Agency of Japan. C.Y.P. was supported by JSPS KAKENHI grant no. JP24H01530. S.F. and T.J. were supported by the Sumitomo Electric Industries Group CSR Foundation. C.B. was funded by the Met Office Climate Science for Service Partnership Brazil project which is supported by the Department for Science, Innovation & Technology. H.H. was supported by United States Department of Energy, Office of Science (Lab Directed Res & Dev (LDRD) 29IN290162:80941). PNNL is operated for DOE by Battelle Memorial Institute under contract DE-ACO5-76RL01830. M.M. was supported by the German Federal Ministry of Education and Research under the research projects QUIDIC (01LP1907A) and is based on work from COST Action CA19139 PROCLIAS (process-based models for climate impact attribution across sectors), supported by COST (European Cooperation in Science and Technology; https://www.cost.eu). S.H. was supported by the Max Planck Tandem group programme. D.K.L. was supported by the Korea Environment Industry & Technology Institute through the ‘Climate Change R&D Project for New Climate Regime’ funded by the Korea Ministry of Environment (2022003570004).

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Authors and Affiliations

  1. National Institute for Environmental Studies, Tsukuba, Japan

    Chae Yeon Park, Kiyoshi Takahashi & Junya Takakura

  2. Department of Environmental Engineering, Graduate School of Engineering, Kyoto University, Kyoto, Japan

    Shinichiro Fujimori & Thanapat Jansakoo

  3. Met Office Hadley Centre, Exeter, UK

    Chantelle Burton & Eleanor Burke

  4. Pacific Northwest National Laboratory, Atmospheric, Climate, and Earth Sciences Division, Richland, WA, USA

    Huilin Huang

  5. Department of Earth and Environmental Sciences, Dalhousie University, Halifax, Nova Scotia, Canada

    Sian Kou-Giesbrecht

  6. Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Potsdam, Germany

    Christopher P. O. Reyer & Matthias Mengel

  7. International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

    Fang Li

  8. Facultad de Ciencias Naturales, Universidad del Rosario, Bogotá, Colombia

    Stijn Hantson

  9. College of Agriculture and Life Science, Seoul National University, Seoul, Republic of Korea

    Dong Kun Lee

  10. College of Science and Engineering, Ritsumeikan University, Kusatsu, Japan

    Tomoko Hasegawa

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Contributions

C.Y.P. contributed to analysis and writing. K.T., S.F., C.P.O.R. and M.M. contributed to the design of the study. T.J., C.B., H.H., S.K.-G. and E.B. ran the atmospheric model or fire–vegetation model simulations and contributed data. F.L., S.H. and C.B. coordinated the fire sector in ISIMIP with the support of C.P.O.R. J.T., D.K.L. and T.H. contributed to statistical analysis and reviewed the paper.

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Correspondence to Chae Yeon Park.

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Extended data

Extended Data Fig. 1 Fire organic carbon emissions from three fire-vegetation models.

Annual total organic carbon (OC) emissions from three fire models (a, CLASSIC; b, SSiB4; and c, JULES) and observation-based reference data (GFED4.1 s [Global Fire Emissions Database version 4.1] for 1997–2019 (d) and together with GFAS [CAMS Global Fire Assimilation System] for 2003–2019 (e)). OC is the predominant particulate carbon from fire. Three fire-vegetation models (a, b, and c) have two simulation results (factual simulation (1) and counterfactual simulation (2)) and the attribution of climate change (ACC) (3). JULES considered fires in both cropland and pastureland as agricultural fires, while CLASSIC considered only fires in cropland.

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Park, C.Y., Takahashi, K., Fujimori, S. et al. Attributing human mortality from fire PM2.5 to climate change. Nat. Clim. Chang. 14, 1193–1200 (2024). https://doi.org/10.1038/s41558-024-02149-1

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