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The air pollution benefits of low severity fire
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Abstract
Larger and more frequent wildfire events in Western North America in recent years have resulted in extensive human and environmental damage, and are reversing decades of air quality improvements. Fuels treatments, including the use of prescribed fire, can reduce the extent and severity of future wildfires, but air quality trade-offs resulting from application of these treatments -- more initial smoke from prescribed burning in hopes of less smoke from future wildfire -- remain poorly quantified. Using two decades of high-resolution satellite-derived measurements of fire severity and fire smoke particulate matter across California, we assess the causal effect of low-severity wildfire -- a proxy for prescribed burning -- on subsequent wildfire activity and air quality, with particular attention to whether low-severity fire also reduces subsequent fire risk in surrounding unburned areas. We find that locations "treated" with low severity fire see an immediate 92% reduction in the probability of very high severity wildfires in the same location, with detectable reductions in high-severity fire risk lasting up to a decade and detectable up to 5 km from the treated locations. We estimate that the future benefits of low-severity fuel "treatments", in terms of reduced smoke from severe fires, substantially outweigh the costs of the smoke produced in the initial treatment fires, with benefit-cost ratios that exceed six after a decade even under a high discount rate (< 6%). Benefits and costs rise roughly linearly with the amount of area treated. We estimate that a policy of 500 thousand acres of low-severity treatments per year in CA, sustained for a decade, would have reduced cumulative smoke PM2.5 concentrations by roughly 23% by the end of the period. These results suggest that substantial expansion of limited current prescribed burned acreage could have meaningful air quality benefits.
DOI
https://doi.org/10.31223/X52M9N
Subjects
Environmental Studies, Forest Sciences, Remote Sensing
Keywords
wildfires, prescribed fires, remote sensing, causal inference
Dates
Published: 2025-07-02 10:35
Last Updated: 2025-07-03 05:32
License
CC-By Attribution-NonCommercial-NoDerivatives 4.0 International
Additional Metadata
Conflict of interest statement:
None
Data Availability (Reason not available):
Data and code available upon request
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