Wildfire, prescribed burn, and agricultural burn smoke PM2.5 estimates for CA, WA, and OR 2014-2020
Data files
May 17, 2024 version files 24.90 MB
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PM25_AG_2014_2020.nc4
7.38 MB
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PM25_RX_2014_2020.nc4
8.09 MB
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PM25_WF_2014_2020.nc4
9.43 MB
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README.md
1.78 KB
Abstract
Wildfires, prescribed burns, and agricultural burns all impact ambient air quality across the Western U.S.; however, little is known about how communities across the region are differentially exposed to smoke from each of these fire types. To address this gap, we quantify smoke exposure stemming from wildfire, prescribed, and agricultural burns across Washington, Oregon, and California from 2014-2020 using a fire type-specific biomass burning emissions inventory and the GEOS-Chem chemical transport model. We examine fire type-specific PM2.5 concentration by race/ethnicity, socioeconomic status, and in relation to the Center for Disease Control’s Social Vulnerability Index. Overall, population average PM2.5 concentrations are greater from wildfires than from prescribed and agricultural burns. While we found limited evidence of exposure disparities among sub-groups across the full study area, we did observe disproportionately higher exposures to wildfire-specific PM2.5 exposures among Native communities in all three states and, in California, higher agricultural burn-specific PM2.5 exposures among lower socioeconomic groups. We also identified, for all three states, areas of significant spatial clustering of smoke exposures from all fire types and increased social vulnerability. These results provide a first look at the differential contributions of smoke from wildfires, prescribed burns, and agricultural burns to PM2.5 exposures among demographic subgroups, which can be used to inform more tailored exposure reduction strategies across sources.
README: Fire type-specific smoke PM2.5
https://doi.org/10.5061/dryad.w0vt4b90g
We estimate daily PM2.5 exposure from wildfire, prescribed, and agricultural burns across WA, OR, and CA during 2014-2020, using biomass burning estimates from the Fire INventory from NCAR (FINN) and the GEOS-Chem chemical transport model. We first ran a global simulation at 4° x 5° resolution with 72 vertical levels to generate boundary conditions, followed by a nested grid simulation for the 11 western states at 0.25° x 0.3125° resolution. To estimate wildfire, prescribed burn, and agricultural burn-specific PM2.5 concentrations, we completed four model scenarios using different combinations of emissions inventories: 1) no biomass burning emissions (background only), 2) background plus only wildfire emissions, 3) background plus only prescribed burning emissions, and 4) background plus only agricultural burning emissions. Background sources refer to non-fire emissions sources, which in the western U.S. are primarily industry, transportation, energy production, sea salt, and dust (Park et al. 2004; Chow and Watson 2002; Prather 2009; Hadley 2017; Chmielewski 2011). We calculated wildfire-specific PM2.5 concentrations as the difference between scenarios 1 and 2, prescribed burn-specific emissions as the difference between scenarios 1 and 3, and agricultural burn emissions as the difference between scenarios 1 and 4. These files contain surface-level daily fire-type specific PM2.5 estimates. These files contain surface-level daily fire-type specific PM2.5 estimates from wildfire, prescribed burns, and agricultural burns.
Variables:
- PM2.5 (µg/m3)
- Time (days since 2014-01-01)
Recommended software: R, Python