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A national crowdsourced network of low-cost fine particulate matter and aerosol optical depth monitors: results from the 2021 wildfire season in the United States

Fine particulate matter (PM 2.5 ) is a leading contributor to premature death, disease, and environmental degradation globally. Wildfire smoke is a primary source of air pollution in the United States. However, reference-grade ground monitors are cost prohibitive to deploy at the spatial scales need...

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Bibliographic Details
Published in:Environmental science: atmospheres 2023-10, Vol.3 (1), p.1563-1575
Main Authors: Wendt, Eric A, Ford, Bonne, Cheeseman, Michael, Rosen, Zoey, Pierce, Jeffrey R, Jathar, Shantanu H, L'Orange, Christian, Quinn, Casey, Long, Marilee, Mehaffy, John, Miller-Lionberg, Daniel D, Hagan, David H, Volckens, John
Format: Article
Language:English
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Summary:Fine particulate matter (PM 2.5 ) is a leading contributor to premature death, disease, and environmental degradation globally. Wildfire smoke is a primary source of air pollution in the United States. However, reference-grade ground monitors are cost prohibitive to deploy at the spatial scales needed to assess the variability of wildfire smoke. In many regions lacking adequate monitoring, health impact assessments and epidemiological studies on smoke may rely on satellite-based instruments, which estimate PM 2.5 based on Aerosol Optical Depth (AOD). However, AOD measurements may not capture surface-level impacts; thus, measurements in under-monitored regions are necessary to interpret satellite observations. While low-cost PM 2.5 sensors have been deployed at large scales, these sensors typically lack AOD measurement capability. In prior work, we designed the Aerosol Mass and Optical Depth (AMODv2) sampler, which can simultaneously measure PM 2.5 (optical and gravimetric filter-based) and AOD. In this work, we distributed AMODv2s to volunteers at 31 locations in the contiguous United States, forming a nationwide network for the summer of 2021. A majority of our network was successful, with 86.6% of sampling periods resulting in a valid sample. We found our AOD sensors agreed closely with nearby (
ISSN:2634-3606
2634-3606
DOI:10.1039/d3ea00086a