Affordable Access

Publisher Website

Measuring long-term exposure to wildfire PM2.5 in California: Time-varying inequities in environmental burden.

Authors
  • Casey, Joan A1, 2
  • Kioumourtzoglou, Marianthi-Anna1
  • Padula, Amy3
  • González, David J X4, 5
  • Elser, Holly6
  • Aguilera, Rosana7
  • Northrop, Alexander J8
  • Tartof, Sara Y9
  • Mayeda, Elizabeth Rose10
  • Braun, Danielle11, 12
  • Dominici, Francesca11
  • Eisen, Ellen A5
  • Morello-Frosch, Rachel4, 5
  • Benmarhnia, Tarik7
  • 1 Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY 10032.
  • 2 Department of Environmental and Occupational Health, University of Washington School of Public Health, Seattle, WA 98195.
  • 3 Department of Obstetrics, Gynecology and Reproductive Sciences, Program on Reproductive Health and the Environment, University of California San Francisco, San Francisco, CA 94143.
  • 4 Department of Environmental Policy, Science, and Management, University of California, Berkeley, CA 94720.
  • 5 Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA 94704.
  • 6 Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104.
  • 7 Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA 92037.
  • 8 Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032.
  • 9 Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA 91101.
  • 10 Department of Epidemiology, University of California Los Angeles Fielding School of Public Health, Los Angeles, CA 90095.
  • 11 Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA 02115.
  • 12 Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215.
Type
Published Article
Journal
Proceedings of the National Academy of Sciences
Publisher
Proceedings of the National Academy of Sciences
Publication Date
Feb 20, 2024
Volume
121
Issue
8
Identifiers
DOI: 10.1073/pnas.2306729121
PMID: 38349877
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM2.5) concentrations differ from relatively smoothly varying total PM2.5. Thus, we introduced a conceptual model for computing long-term wildfire PM2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM2.5 exposure based on intermittent and extreme daily wildfire PM2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM2.5 < 5 μg/m3; 2) days with non-zero wildfire PM2.5; 3) mean wildfire PM2.5 during peak exposure week; 4) smoke waves (≥2 consecutive days with <15 μg/m3 wildfire PM2.5); and 5) mean annual wildfire PM2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM2.5 metrics using mixed-effects models. Averaged 2006 to 2020, we detected little difference in exposure by CES score or racial/ethnic composition, except for non-Hispanic American Indian and Alaska Native populations, where a 1-SD increase was associated with higher exposure for 4/5 metrics. CES or racial/ethnic × year interaction term models revealed exposure disparities in some years. Compared to their California-wide representation, the exposed populations of non-Hispanic American Indian and Alaska Native (1.68×, 95% CI: 1.01 to 2.81), white (1.13×, 95% CI: 0.99 to 1.32), and multiracial (1.06×, 95% CI: 0.97 to 1.23) people were over-represented from 2006 to 2020. In conclusion, during our study period in California, we detected disproportionate long-term wildfire PM2.5 exposure for several racial/ethnic groups.

Report this publication

Statistics

Seen <100 times