Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Wildfire smoke exposure and mortality burden in the USA under climate change

Nature volume 647, pages 935–943 (2025)Cite this article

Subjects

Abstract

Wildfire activity has increased in the USA and is projected to accelerate under future climate change1,2,3. However, our understanding of the impacts of climate change on wildfire activity, smoke and health outcomes remains highly uncertain because of the difficulty of modelling the causal chain from climate to wildfire to air pollution and health. Here we quantify the mortality burden in the USA due to wildfire smoke fine particulate matter (PM2.5) under climate change. We construct an ensemble of statistical and machine learning models that link climate to wildfire smoke PM2.5 and empirically estimate smoke PM2.5–mortality relationships using data on all recorded deaths in the USA. We project that smoke PM2.5 could result in 71,420 excess deaths (95% confidence interval: 34,930–98,430) per year by 2050 under a high-warming scenario (shared socioeconomic pathway scenario 3-7.0, SSP3-7.0)—a 73% increase relative to the estimated 2011–2020 average annual excess deaths from smoke. Cumulative excess deaths from smoke PM2.5 could reach 1.9 million between 2026 and 2055. We find evidence for mortality impacts of smoke PM2.5 that last up to 3 years after exposure. When monetized, climate-driven smoke deaths result in economic damages that exceed existing estimates of climate-driven damages from all other causes combined in the USA4,5. Our research suggests that the health impacts of climate-driven wildfire smoke could be among the most important and costly consequences of a warming climate in the USA.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Research methodology.
Fig. 2: Projected wildfire emissions under future climate change scenarios.
Fig. 3: Wildfire emissions increase observed smoke PM2.5 concentrations in the neighbouring and downwind areas.
Fig. 4: Population exposure to wildfire smoke PM2.5 increases by two to threefold under future climate scenarios.
Fig. 5: Mortality impacts of wildfire smoke PM2.5 and estimated mortality due to smoke PM2.5 under future climate scenarios.

Similar content being viewed by others

Data availability

Data needed to replicate results and main text figures are available in a public repository at Zenodo92 (https://doi.org/10.5281/zenodo.16855665), except for county-level mortality data for low-population counties, which were obtained through application to the National Center for Health Statistics. Although we cannot share the full mortality data that we used in the analysis, we released a dataset that allows replication of our smoke–mortality model using public mortality data derived from CDC WONDER.

Code availability

R code to replicate results and main text figures is available at Zenodo92 (https://doi.org/10.5281/zenodo.16855665).

References

  1. Abatzoglou, J. T. & Williams, A. P. Impact of anthropogenic climate change on wildfire across western US forests. Proc. Natl Acad. Sci. USA 113, 11770–11775 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Diffenbaugh, N. S., Konings, A. G. & Field, C. B. Atmospheric variability contributes to increasing wildfire weather but not as much as global warming. Proc. Natl Acad. Sci. USA 118, e2117876118 (2021).

  3. Jones, M. W. et al. Global and regional trends and drivers of fire under climate change. Rev. Geophys. 60, e2020RG000726 (2022).

  4. Hsiang, S. et al. Estimating economic damage from climate change in the United States. Science 356, 1362–1369 (2017).

    Article  CAS  PubMed  Google Scholar 

  5. Technical Documentation on the Framework for Evaluating Damages and Impacts (FrEDI) (EPA, 2023).

  6. Iglesias, V., Balch, J. K. & Travis, W. R. U. S. fires became larger, more frequent, and more widespread in the 2000s. Sci. Adv. 8, eabc0020 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  7. McClure, C. D. & Jaffe, D. A. US particulate matter air quality improves except in wildfire-prone areas. Proc. Natl Acad. Sci. USA 115, 7901–7906 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. O’Dell, K., Ford, B., Fischer, E. V. & Pierce, J. R. Contribution of wildland-fire smoke to US PM2.5 and its influence on recent trends. Environ. Sci. Technol. 53, 1797–1804 (2019).

    Article  PubMed  Google Scholar 

  9. Childs, M. L. et al. Daily local-level estimates of ambient wildfire smoke PM2.5 for the contiguous US. Environ. Sci. Technol. https://doi.org/10.1021/acs.est.2c02934 (2022).

  10. Zhang, D. et al. Wildland fires worsened population exposure to PM2.5 pollution in the contiguous United States. Environ. Sci. Technol. 57, 19990–19998 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Reid, C. E. et al. Critical review of health impacts of wildfire smoke exposure. Environ. Health Perspect. 124, 1334–1343 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Gould, C. F. et al. Health effects of wildfire smoke exposure. Annu. Rev. Med. https://doi.org/10.1146/annurev-med-052422-020909 (2023).

  13. Chen, G. et al. Mortality risk attributable to wildfire-related PM2.5 pollution: a global time series study in 749 locations. Lancet Planet. Health 5, e579–e587 (2021).

    Article  MathSciNet  PubMed  Google Scholar 

  14. Li, Y. et al. Dominance of wildfires impact on air quality exceedances during the 2020 record‐breaking wildfire season in the United States. Geophys. Res. Lett. 48, e2021GL094908 (2021).

  15. Burke, M. et al. The contribution of wildfire to PM2.5 trends in the USA. Nature https://doi.org/10.1038/s41586-023-06522-6 (2023).

  16. Zhuang, Y., Fu, R., Santer, B. D., Dickinson, R. E. & Hall, A. Quantifying contributions of natural variability and anthropogenic forcings on increased fire weather risk over the western United States. Proc. Natl Acad. Sci. USA 118, e2111875118 (2021).

  17. Zhong, Q., Shen, G., Wang, B., Ma, J. & Tao, S. Climate-driven escalation of global PM2.5 health burden from wildland fires. Environ. Sci. Technol. 59, 3131–3142 (2025).

    Article  CAS  PubMed  Google Scholar 

  18. Westerling, A. L. Increasing western US forest wildfire activity: sensitivity to changes in the timing of spring. Philos. Trans. R. Soc. Lond. B 371, 20150178 (2016).

  19. Law, B. E. et al. Anthropogenic climate change contributes to wildfire particulate matter and related mortality in the United States. Commun. Earth Environ. 6, 336 (2025).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Radeloff, V. C. et al. Rapid growth of the US wildland-urban interface raises wildfire risk. Proc. Natl Acad. Sci. USA 115, 3314–3319 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Balch, J. K. et al. Warming weakens the night-time barrier to global fire. Nature 602, 442–448 (2022).

    Article  CAS  PubMed  Google Scholar 

  22. Hessilt, T. D. et al. Future increases in lightning ignition efficiency and wildfire occurrence expected from drier fuels in boreal forest ecosystems of western North America. Environ. Res. Lett. 17, 054008 (2022).

    Article  Google Scholar 

  23. Abatzoglou, J. T., Juang, C. S., Williams, A. P., Kolden, C. A. & Westerling, A. L. Increasing synchronous fire danger in forests of the western United States. Geophys. Res. Lett. 48, e2020GL091377 (2021).

  24. Wang, S. S.-C., Leung, L. R. & Qian, Y. Projection of future fire emissions over the contiguous US using explainable artificial intelligence and CMIP6 models. J. Geophys. Res. 128, e2023JD039154 (2023).

  25. Brown, P. T. et al. Climate warming increases extreme daily wildfire growth risk in California. Nature 621, 760–766 (2023).

    Article  CAS  PubMed  Google Scholar 

  26. Lam, Y. F., Fu, J. S., Wu, S. & Mickley, L. J. Impacts of future climate change and effects of biogenic emissions on surface ozone and particulate matter concentrations in the United States. Atmos. Chem. Phys. 11, 4789–4806 (2011).

    Article  CAS  Google Scholar 

  27. Yue, X., Mickley, L. J., Logan, J. A. & Kaplan, J. O. Ensemble projections of wildfire activity and carbonaceous aerosol concentrations over the western United States in the mid-21st century. Atmos. Environ. 77, 767–780 (2013).

    Article  CAS  Google Scholar 

  28. Sarangi, C. et al. Projected increases in wildfires may challenge regulatory curtailment of PM2.5 over the eastern US by 2050. Atmos. Chem. Phys. 23, 1769–1783 (2023).

    Article  CAS  Google Scholar 

  29. Liu, J. C. et al. Future respiratory hospital admissions from wildfire smoke under climate change in the Western US. Environ. Res. Lett. 11, 124018 (2016).

    Article  Google Scholar 

  30. Ford, B. et al. Future fire impacts on smoke concentrations, visibility, and health in the contiguous United States. Geohealth 2, 229–247 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Neumann, J. E. et al. Estimating PM2.5-related premature mortality and morbidity associated with future wildfire emissions in the western US. Environ. Res. Lett. 16, 035019 (2021).

  32. Stowell, J. D. et al. Asthma exacerbation due to climate change-induced wildfire smoke in the Western US. Environ. Res. Lett. 17, 014023 (2021).

    Article  Google Scholar 

  33. Wang, S. S.-C., Qian, Y., Leung, L. R. & Zhang, Y. Interpreting machine learning prediction of fire emissions and comparison with FireMIP process-based models. Atmos. Chem. Phys. 22, 3445–3468 (2022).

    Article  CAS  Google Scholar 

  34. Ye, X. et al. Evaluation and intercomparison of wildfire smoke forecasts from multiple modeling systems for the 2019 Williams Flats fire. Atmos. Chem. Phys. 21, 14427–14469 (2021).

    Article  CAS  Google Scholar 

  35. Carter, T. S. et al. How emissions uncertainty influences the distribution and radiative impacts of smoke from fires in North America. Atmos. Chem. Phys. 20, 2073–2097 (2020).

    Article  CAS  Google Scholar 

  36. Xie, Y., Lin, M. & Horowitz, L. W. Summer PM2.5 pollution extremes caused by wildfires over the western United States during 2017–2018. Geophys. Res. Lett. 47, e2020GL089429 (2020).

  37. Qiu, M. et al. Evaluating chemical transport and machine learning models for wildfire smoke PM2.5: implications for assessment of health impacts. Environ. Sci. Technol. https://doi.org/10.1021/acs.est.4c05922 (2024).

  38. Southworth, E. K. et al. The influence of wildfire smoke on ambient PM2.5 chemical species concentrations in the contiguous US. Environ. Sci. Technol. https://doi.org/10.1021/acs.est.4c09011 (2025).

  39. Heft-Neal, S. et al. Emergency department visits respond nonlinearly to wildfire smoke. Proc. Natl Acad. Sci. USA 120, e2302409120 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Xie, Y. et al. Tripling of western US particulate pollution from wildfires in a warming climate. Proc. Natl Acad. Sci. USA 119, e2111372119 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Rennert, K. et al. Comprehensive evidence implies a higher social cost of CO2. Nature 610, 687–692 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. van der Werf, G. R. et al. Global fire emissions estimates during 1997–2016. Earth Syst. Sci. Data 9, 697–720 (2017).

    Article  Google Scholar 

  43. Ma, Y. et al. Long-term exposure to wildland fire smoke PM2.5 and mortality in the contiguous United States. Proc. Natl Acad. Sci. USA 121, e2403960121 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Zhang, D., Xi, Y., Boffa, D. J., Liu, Y. & Nogueira, L. M. Association of wildfire exposure while recovering from lung cancer surgery with overall survival. JAMA Oncol. 9, 1214–1220 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Elser, H. et al. Wildfire smoke exposure and incident dementia. JAMA Neurol. 82, 40–48 (2025).

    Article  PubMed  Google Scholar 

  46. Carleton, T. et al. Valuing the global mortality consequences of climate change accounting for adaptation costs and benefits. Q. J. Econ. 137, 2037–2105 (2022).

    Article  Google Scholar 

  47. Grillakis, M. et al. Climate drivers of global wildfire burned area. Environ. Res. Lett. 17, 045021 (2022).

    Article  Google Scholar 

  48. Abatzoglou, J. T. et al. Projected increases in western US forest fire despite growing fuel constraints. Commun. Earth Environ. 2, 227 (2021).

    Article  Google Scholar 

  49. Connolly, R. et al. Mortality attributable to PM2.5 from wildland fires in California from 2008 to 2018. Sci. Adv. 10, eadl1252 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Park, C. Y. et al. Future fire-PM2.5 mortality varies depending on climate and socioeconomic changes. Environ. Res. Lett. 19, 024003 (2024).

    Article  Google Scholar 

  51. Deryugina, T., Heutel, G., Miller, N. H., Molitor, D. & Reif, J. The mortality and medical costs of air pollution: evidence from changes in wind direction. Am. Econ. Rev. 109, 4178–4219 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Weichenthal, S. et al. How low can you go? Air pollution affects mortality at very low levels. Sci. Adv. 8, eabo3381 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Rao, K., Williams, A. P., Diffenbaugh, N. S., Yebra, M. & Konings, A. G. Plant-water sensitivity regulates wildfire vulnerability. Nat. Ecol. Evol. 6, 332–339 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Schollaert, C. L. et al. Quantifying the smoke-related public health trade-offs of forest management. Nat. Sustain. 7, 130–139 (2023).

    Article  Google Scholar 

  55. Dickinson, G. N. et al. Health risk implications of volatile organic compounds in wildfire smoke during the 2019 FIREX‐AQ campaign and beyond. Geohealth 6, e2021GH000546 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Gao, Y. et al. Wildfire-related PM2.5 and cardiovascular mortality: a difference-in-differences analysis in Brazil. Environ. Pollut. 347, 123810 (2024).

    Article  CAS  PubMed  Google Scholar 

  57. Gao, Y. et al. Wildfire-related PM2.5 and cause-specific cancer mortality. Ecotoxicol. Environ. Safety 285, 117023 (2024).

    Article  CAS  PubMed  Google Scholar 

  58. Kelp, M., Burke, M., Qiu, M., Liu, T. & Diffenbaugh, N. Effect of recent prescribed burning and land management on wildfire burn severity and smoke emissions in the western United States. AGU Adv. 6, e2025AV001682 (2025).

    Article  Google Scholar 

  59. Burke, M. et al. Exposures and behavioural responses to wildfire smoke. Nat. Hum. Behav. 6, 1351–1361 (2022).

    Article  PubMed  Google Scholar 

  60. van Donkelaar, A. et al. Monthly global estimates of fine particulate matter and their uncertainty. Environ. Sci. Technol. 55, 15287–15300 (2021).

    Article  PubMed  Google Scholar 

  61. Buch, J., Williams, A. P., Juang, C. S., Hansen, W. D. & Gentine, P. SMLFire1.0: a stochastic machine learning (SML) model for wildfire activity in the western United States. Geosci. Model Dev. 16, 3407–3433 (2023).

    Article  Google Scholar 

  62. Mesinger, F. et al. North American regional reanalysis. Bull. Am. Meteorol. Soc. 87, 343–360 (2006).

    Article  Google Scholar 

  63. Xia, Y. et al. Continental-scale water and energy flux analysis and validation for North American Land Data Assimilation System project phase 2 (NLDAS-2): 2. Validation of model-simulated streamflow. J. Geophys. Res. 117, D03109 (2012).

  64. Mitchell, K. E. et al. The multi‐institution North American Land Data Assimilation System (NLDAS): utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. J. Geophys. Res. 109, 2003JD003823 (2004).

    Article  Google Scholar 

  65. Commission for Environmental Cooperation (CEC), North American Land Change Monitoring System, Canada Centre for Remote Sensing (CCRS), U.S. Geological Survey (USGS), Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO), Comisión Nacional Forestal (CONAFOR), Instituto Nacional de Estadística y Geografía (INEGI). North American Environmental Atlas – Land Cover 2015 30m, edn 4.0. https://www.cec.org/north-american-environmental-atlas/land-cover-30m-2015-landsat-and-rapideye/ (2024).

  66. Pullabhotla, H. K., Zahid, M., Heft-Neal, S., Rathi, V. & Burke, M. Global biomass fires and infant mortality. Proc. Natl Acad. Sci. USA 120, e2218210120 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Qiu, M., Ratledge, N., Azevedo, I. M. L., Diffenbaugh, N. S. & Burke, M. Drought impacts on the electricity system, emissions, and air quality in the western United States. Proc. Natl Acad. Sci. USA 120, e2300395120 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Huang, X. et al. Smoke-weather interaction affects extreme wildfires in diverse coastal regions. Science 379, 457–461 (2023).

    Article  CAS  PubMed  Google Scholar 

  69. Urbanski, S. Wildland fire emissions, carbon, and climate: emission factors. For. Ecol. Manage. 317, 51–60 (2014).

    Article  Google Scholar 

  70. Jen, C. N. et al. Speciated and total emission factors of particulate organics from burning western US wildland fuels and their dependence on combustion efficiency. Atmos. Chem. Phys. 19, 1013–1026 (2019).

    Article  CAS  Google Scholar 

  71. Liang, Y. et al. Emissions of organic compounds from western US wildfires and their near-fire transformations. Atmos. Chem. Phys. 22, 9877–9893 (2022).

    Article  CAS  Google Scholar 

  72. Jaffe, D. A. et al. Wildfire and prescribed burning impacts on air quality in the United States. J. Air Waste Manag. Assoc. 70, 583–615 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Achtemeier, G. L. Measurements of moisture in smoldering smoke and implications for fog. Int. J. Wildland Fire 15, 517 (2006).

    Article  Google Scholar 

  74. Shen, L., Mickley, L. J. & Murray, L. T. Influence of 2000–2050 climate change on particulate matter in the United States: results from a new statistical model. Atmos. Chem. Phys. 17, 4355–4367 (2017).

    Article  CAS  Google Scholar 

  75. Westervelt, D. M. et al. Quantifying PM2.5-meteorology sensitivities in a global climate model. Atmos. Environ. 142, 43–56 (2016).

    Article  CAS  Google Scholar 

  76. Mickley, L. J., Jacob, D. J., Field, B. D. & Rind, D. Effects of future climate change on regional air pollution episodes in the United States. Geophys. Res. Lett. 31, L24103 (2004).

  77. Barnes, E. A. & Fiore, A. M. Surface ozone variability and the jet position: Implications for projecting future air quality. Geophys. Res. Lett. 40, 2839–2844 (2013).

    Article  CAS  Google Scholar 

  78. Turner, A. J., Fiore, A. M., Horowitz, L. W. & Bauer, M. Summertime cyclones over the Great Lakes Storm Track from 1860–2100: variability, trends, and association with ozone pollution. Atmos. Chem. Phys. 13, 565–578 (2013).

    Article  Google Scholar 

  79. NCHS. Multiple Cause of Death 1999–2020. National Vital Statistics System (CDC, 2023).

  80. Wei, Y. et al. Exposure-response associations between chronic exposure to fine particulate matter and risks of hospital admission for major cardiovascular diseases: population based cohort study. Brit. Med. J. 384, e076939 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  81. Hsiang, S. Climate econometrics. Annu. Rev. Resour. Econ. 8, 43–75 (2016).

    Article  Google Scholar 

  82. Di, Q. et al. Air pollution and mortality in the Medicare population. N. Engl. J. Med. 376, 2513–2522 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Pope, C. A., Coleman, N., Pond, Z. A. & Burnett, R. T. Fine particulate air pollution and human mortality: 25+ years of cohort studies. Environ. Res. 183, 108924 (2020).

    Article  CAS  PubMed  Google Scholar 

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

  85. Hoek, G. et al. Long-term air pollution exposure and cardio- respiratory mortality: a review. Environ. Health 12, 43 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. NCHS. Multiple Cause of Death 1999–2020 on CDC WONDER Online Database, Released 2021: Data Compiled from Data Provided by the 57 Vital Statistics Jurisdictions Through the Vital Statistics Cooperative Program (CDC, 2021); https://wonder.cdc.gov/mcd.html.

  87. O’Dell, K. et al. Estimated mortality and morbidity attributable to smoke plumes in the United States: not just a western US problem. Geohealth 5, e2021GH000457 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  88. US Census Bureau. National Population Projections Tables: Main Series (2023).

  89. Berlin Rubin, N. & Wong-Parodi, G. As California burns: the psychology of wildfire- and wildfire smoke-related migration intentions. Popul. Environ. 44, 15–45 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  90. McConnell, K. et al. Rare and highly destructive wildfires drive human migration in the U.S. Nat. Commun. 15, 6631 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. EPA Report on the Social Cost of Greenhouse Gases: Estimates Incorporating Recent Scientific Advances (EPA, 2023).

  92. Qiu, M. et al. Data and code for ‘Wildfire smoke exposure and mortality burden in the USA under climate change’. Zenodo https://doi.org/10.5281/zenodo.16855665 (2025).

Download references

Acknowledgements

We thank A. Wilson for helping process mortality data; Y. Ma and K. Chen for sharing their smoke mortality estimates for comparison; A. van Donkelaar for helping with dataset of total PM2.5 concentrations; seminar participants at Stanford University, Harvard University and the Brookhaven National Laboratory for comments; and the Keck Foundation for funding. M.Q. acknowledges the support from the planetary health fellowship at Stanford’s Center for Innovation in Global Health, and Minghua Zhang faculty career catalyst award from Stony Brook University. M.L.C. was supported by an Environmental Fellowship at the Harvard University Center for the Environment. R.J. acknowledges support for this work from NIH grant R01HD104835 and the Ruth L. Kirschstein National Research Service Award grant 5T32HS026128-07. N.S.D. acknowledges support from Stanford University. Some of the computing for this project was performed on the Stanford Sherlock cluster, and we thank Stanford University and the Stanford Research Computing Center for providing computational resources and support that contributed to these research results. NCEP North American Regional Reanalysis (NARR) data were provided by the NOAA PSL from their website (https://psl.noaa.gov).

Author information

Authors and Affiliations

  1. School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, USA

    Minghao Qiu

  2. Program in Public Health, Stony Brook University, Stony Brook, NY, USA

    Minghao Qiu

  3. Doerr School of Sustainability, Stanford University, Stanford, CA, USA

    Minghao Qiu, Makoto Kelp, Jeff Wen, Noah S. Diffenbaugh & Marshall Burke

  4. Center for Innovation in Global Health, Stanford University, Stanford, CA, USA

    Minghao Qiu & Renzhi Jing

  5. Center on Food Security and the Environment, Stanford University, Stanford, CA, USA

    Jessica Li, Sam Heft-Neal & Marshall Burke

  6. School of Public Health, University of California San Diego, La Jolla, CA, USA

    Carlos F. Gould

  7. Woods Institute for the Environment, Stanford University, Stanford, CA, USA

    Renzhi Jing

  8. Department of Health Policy, School of Medicine, Stanford University, Stanford, CA, USA

    Renzhi Jing

  9. Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA

    Marissa L. Childs

  10. School of Public Policy and International Affairs, Princeton University, Princeton, NJ, USA

    Yuanyu Xie

  11. National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory, National Oceanic and Atmospheric Administration, Princeton, NJ, USA

    Meiyun Lin

  12. Department of Epidemiology and Population Health, School of Medicine, Stanford University, Stanford, CA, USA

    Mathew V. Kiang

  13. National Bureau of Economic Research, Cambridge, MA, USA

    Marshall Burke

Authors
  1. Minghao Qiu
    View author publications

    Search author on:PubMed Google Scholar

  2. Jessica Li
    View author publications

    Search author on:PubMed Google Scholar

  3. Carlos F. Gould
    View author publications

    Search author on:PubMed Google Scholar

  4. Renzhi Jing
    View author publications

    Search author on:PubMed Google Scholar

  5. Makoto Kelp
    View author publications

    Search author on:PubMed Google Scholar

  6. Marissa L. Childs
    View author publications

    Search author on:PubMed Google Scholar

  7. Jeff Wen
    View author publications

    Search author on:PubMed Google Scholar

  8. Yuanyu Xie
    View author publications

    Search author on:PubMed Google Scholar

  9. Meiyun Lin
    View author publications

    Search author on:PubMed Google Scholar

  10. Mathew V. Kiang
    View author publications

    Search author on:PubMed Google Scholar

  11. Sam Heft-Neal
    View author publications

    Search author on:PubMed Google Scholar

  12. Noah S. Diffenbaugh
    View author publications

    Search author on:PubMed Google Scholar

  13. Marshall Burke
    View author publications

    Search author on:PubMed Google Scholar

Contributions

M.Q. and M.B. designed the study. M.Q. led the smoke projection modelling with inputs from all of the authors. M.Q., J.L. and R.J. led the statistical and machine learning modelling of fire emissions. M.Q., S.H.-N., C.F.G. and M.L.C. led the health impacts analysis. M.Q. and M.B. led the writing of the manuscript. M.Q., J.L., C.F.G., R.J., M.K., M.L.C., J.W., Y.X., M.L., M.V.K., S.H.-N., N.S.D. and M.B contributed to interpretation of results and reviewed the manuscripts.

Corresponding authors

Correspondence to Minghao Qiu or Marshall Burke.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature thanks Joan Casey, Lulu Chen, Gaige Kerr, Scott Weichenthal, Xiao Wu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Future smoke contribution from different fire regions.

Source-receptor matrix of the contributions from fire emissions from the five source regions (x-axis) to population-weighted smoke PM2.5 concentrations in nine receptor regions across the contiguous US (y-axis). The plot shows the contributions in 2046–2055 averaged over all GCMS under the SSP3-7.0 scenario.

Extended Data Fig. 2 Historical and projected dry matter (DM) emissions.

Historical annual average emissions in 2001–2021 and projected annual emissions (2046–2055) under the SSP3-7.0 scenario in the eastern US (top), Canada and Alaska (middle), and Mexico (bottom). Projected emissions are first stochastically downscaled from regional emissions predictions and then averaged over 40 simulated downscaling estimates.

Extended Data Fig. 3 Illustration of the stochastic downscaling approach using the western US as an example.

Historical annual average emissions in 2001–2021 from GFED4s, and projected annual emissions averaged between 2046–2055 under the SSP3-7.0 scenario at the grid level. The “static” panel shows the results derived from the static downscaling method, which applies a common ratio to the historical emission pattern to match the future projected emissions. The “stochastic” panel shows our main stochastic downscaling method, which generates the same total emissions as the static method regionally but allows for the possibility that grids that have never burned could burn. Projected emissions are first stochastically downscaled from regional emissions predictions and then averaged over 40 simulated downscaling estimates (six are shown here for the illustration purpose).

Extended Data Fig. 4 Estimated annual excess deaths due to smoke PM2.5 using alternative exposure-response functions.

Panel A: results estimated using alternative smoke-mortality models (averaged over 2011–2020). In addition to our main model (grey bar), we estimate a model that uses the public mortality data from CDC WONDER, a model that additionally includes year 2020 in the regressions, a model that follows similar specification from Ma et al., 2024 (i.e. a monthly model with alternative bin specifications and 12-month moving average of smoke PM2.5 concentration), and models which calculates the number of months or the number of days in a year that fall in different smoke bins to represent different temporal aggregations. The bars show mean values of bootstrapped estimates, and the whiskers show bootstrapped 95% confidence intervals (500 bootstraps). Panel B: results estimated using published exposure-response functions that link total PM2.5 to mortality. Note the results here are estimated using lag 0 model and all-ages group, to match earlier work.

Extended Data Fig. 5 Cumulative effects of smoke on mortality across different lag years.

Panel A: aggregated coefficients for each smoke bin across different lag years, representing the cumulative effects of smoke exposure on mortality in the same year and subsequent years. Panel B: estimated mortality due to annual smoke PM2.5 under historical (2011–2020) and future scenarios (2046–2055). The plot shows the same-year mortality due to smoke (in the case of lag 0), and cumulative mortality (lag 0-1,…,lag 0-4). The bars show mean values of bootstrapped estimates, and the whiskers show bootstrapped 95% confidence intervals (500 bootstraps). We report results from “lag 0-1” model as our main estimates.

Extended Data Fig. 6 Estimated excess deaths due to smoke PM2.5 under the historical, SSP1-2.6, and SSP3-7.0 scenarios due to annual smoke exposure (lag 0-1).

The top panels show estimates at the county level. The bottom panels show estimates at the state level.

Extended Data Fig. 7 Uncertainty in projected annual smoke PM2.5 concentration (Panel A) and mortality (Panel B).

The red dashed line shows the main estimate. The solid bar shows the 10th and 90th percentile, and the black line shows the 2.5th and 97.5th percentile. Uncertainty from “climate projection” is calculated using the percentiles of 28 GCMs. Uncertainty from “climate-fire model” and “fire-smoke model” is calculated using bootstrap procedures performed on the climate-fire and fire-smoke models. Uncertainty from “emission downscaling” shows the range of smoke and mortality estimated across 40 different downscaling estimates. Uncertainty from “smoke-mortality function” is calculated using bootstrap procedures performed on the smoke-mortality response functions. The combined uncertainty is quantified using a Monte-Carlo simulation approach, where we randomly sample 500 combinations of GCMs, climate-fire models, downscaling estimates, and fire-smoke models, and smoke-mortality functions.

Extended Data Table 1 Estimated past and future population-weighted average smoke PM2.5, and smoke contribution to total PM2.5 (i.e. smoke PM2.5/total PM2.5) at the state level
Full size table
Extended Data Table 2 Empirically estimated exposure-response function of smoke PM2.5 on mortality rate across three age groups (all ages, 65 and up, under 65)
Full size table
Extended Data Table 3 Estimated annual excess deaths due to exposure to wildfire smoke by state
Full size table

Supplementary information

Supplementary Information

Supplementary Tables 1–11, Supplementary Figs. 1–12 and Supplementary References.

Reporting Summary

Peer Review File

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qiu, M., Li, J., Gould, C.F. et al. Wildfire smoke exposure and mortality burden in the USA under climate change. Nature 647, 935–943 (2025). https://doi.org/10.1038/s41586-025-09611-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41586-025-09611-w

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing