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Assessing urban mortality from wildfires with a citizen science network

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Abstract

Assessment of exposure and mortality attributable to air pollution is one of the most important tasks to inform strategies for mitigation and prevention of the negative effects of degraded air quality. While the vast majority of studies rely on either satellite data or sparse (and expensive) monitoring networks and focus on global- or regional-scale assessments, emerging low-cost citizen science networks are a new source of information that can be used to provide more detailed estimates at urban scale, thereby refining previous estimates and providing spatially resolved information at census tract resolution. In this work, we demonstrate how a citizen science network, validated with a reference air pollution station, provides sensibly different (and spatially resolved) estimates of air pollution levels and associated exposure/mortality than assuming constant air pollution across the analyzed urban area. Specifically we focus on the extreme pollution episode of the 2020 California wildfires that significantly impacted the city of San Francisco. We estimate that during the wildfires, degraded air quality was responsible for an increase between 2 and 4% of the baseline mortality in the same city over the time period of study (August 19, 2020 to September 30, 2020).

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Data availability

The datasets analyzed during the current study are available at www.purpleair.com for the low-cost sensors and at www.epa.gov/outdoor-air-quality-data/download-daily-data for the EPA measurement.

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  1. Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA

    Peng Shen & Stefano Castruccio

  2. Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN, USA

    Paola Crippa

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Shen, P., Crippa, P. & Castruccio, S. Assessing urban mortality from wildfires with a citizen science network. Air Qual Atmos Health 14, 2015–2027 (2021). https://doi.org/10.1007/s11869-021-01072-0

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