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Differences in the Estimation of Wildfire-Associated Air Pollution by Satellite Mapping of Smoke Plumes and Ground-Level Monitoring

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  • Raj P. Fadadu

    (Joint Medical Program, University of California Berkeley School of Public Health and University of California San Francisco School of Medicine, Berkeley, CA 94704, USA
    Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, CA 94704, USA)

  • John R. Balmes

    (Joint Medical Program, University of California Berkeley School of Public Health and University of California San Francisco School of Medicine, Berkeley, CA 94704, USA
    Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, CA 94704, USA
    Department of Medicine, University of California San Francisco, San Francisco, CA 94143, USA)

  • Stephanie M. Holm

    (Department of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
    Division of Epidemiology, School of Public Health, University of California Berkeley, Berkeley, CA 94704, USA
    Western States Pediatric Environmental Health Specialty Unit, San Francisco, CA 94143, USA)

Abstract

Wildfires, which are becoming more frequent and intense in many countries, pose serious threats to human health. To determine health impacts and provide public health messaging, satellite-based smoke plume data are sometimes used as a proxy for directly measured particulate matter levels. We collected data on particulate matter <2.5 μm in diameter (PM 2.5 ) concentration from 16 ground-level monitoring stations in the San Francisco Bay Area and smoke plume density from satellite imagery for the 2017–2018 California wildfire seasons. We tested for trends and calculated bootstrapped differences in the median PM 2.5 concentrations by plume density category on a 0–3 scale. The median PM 2.5 concentrations for categories 0, 1, 2, and 3 were 16, 22, 25, and 63 μg/m 3 , respectively, and there was much variability in PM 2.5 concentrations within each category. A case study of the Camp Fire illustrates that in San Francisco, PM 2.5 concentrations reached their maximum many days after the peak for plume density scores. We found that air pollution characterization by satellite imagery did not precisely align with ground-level PM 2.5 concentrations. Public health practitioners should recognize the need to combine multiple sources of data regarding smoke patterns when developing public guidance to limit the health effects of wildfire smoke.

Suggested Citation

  • Raj P. Fadadu & John R. Balmes & Stephanie M. Holm, 2020. "Differences in the Estimation of Wildfire-Associated Air Pollution by Satellite Mapping of Smoke Plumes and Ground-Level Monitoring," IJERPH, MDPI, vol. 17(21), pages 1-9, November.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:21:p:8164-:d:440196
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    References listed on IDEAS

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    1. Jia Coco Liu & Loretta J. Mickley & Melissa P. Sulprizio & Francesca Dominici & Xu Yue & Keita Ebisu & Georgiana Brooke Anderson & Rafi F. A. Khan & Mercedes A. Bravo & Michelle L. Bell, 2016. "Particulate air pollution from wildfires in the Western US under climate change," Climatic Change, Springer, vol. 138(3), pages 655-666, October.
    2. Chenchen Wang & Yifan Tu & Zongliang Yu & Rongzhu Lu, 2015. "PM 2.5 and Cardiovascular Diseases in the Elderly: An Overview," IJERPH, MDPI, vol. 12(7), pages 1-11, July.
    3. JinSoo Park & Sungroul Kim, 2020. "Machine Learning-Based Activity Pattern Classification Using Personal PM 2.5 Exposure Information," IJERPH, MDPI, vol. 17(18), pages 1-11, September.
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    1. Raj P. Fadadu & Katrina Abuabara & John R. Balmes & Jon M. Hanifin & Maria L. Wei, 2023. "Air Pollution and Atopic Dermatitis, from Molecular Mechanisms to Population-Level Evidence: A Review," IJERPH, MDPI, vol. 20(3), pages 1-21, January.

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