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Michigan Tech Research Institute


In response to increasing wildfire risks, California plans to expand the use of prescribed fire. We characterized the anticipated change in health impacts from exposure to smoke under a future fire-management scenario relative to a historical period (2008–2016). Using dispersion models, we estimated daily fine particulate matter (PM2.5) emissions from hypothetical future prescribed fires on 500,000-acres classified as high priority. To evaluate health impacts, we calculated excess daily cardiorespiratory emergency department visit rates attributed to all-source PM2.5, distinguishing the portion of the burden attributed to prescribed fire. The total burden was differentiated by fire type and by smoke strata-specific days to calculate strata-specific burden rates, which were then applied to estimate the burden in the future scenario. This analysis suggests that the exposure to prescribed fire smoke, measured as the number of persons exposed per year, would be 15 times greater in the future. However, these exposures were associated with lower concentrations compared to the historical period. The increased number of exposure days led to an overall increase in the future health burden. Specifically, the northern, central, and southern regions experienced the largest burden increase. This study introduces an approach that integrates spatiotemporal exposure differences, baseline morbidity, and population size to assess the impacts of prescribed fire under a future scenario. The findings highlight the need to consider both the level and frequency of exposure to guide strategies to safeguard public health as well as aid forest management agencies in making informed decisions to protect communities while mitigating wildfire risks.

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©2024 The Authors. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA. Publisher’s version of record:

Publication Title

Earth's Future

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Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


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