A State of the Science Review of Wildfire-Specific Fine Particulate Matter Data Sources, Methods, and Models

Despite progress in reducing industrial air pollution, rising wildfire frequency and intensity, driven in part by climate change, pose significant health risks. Accurate estimates of wildfire-generated fine particulate matter with an aerodynamic diameter $<2.5\mu m$ (${\mathrm{PM}}_{2.5}$) are needed for advancing health research, policymaking, and environmental protection.

This review evaluates existing methodologies and data sources for estimating wildfire-generated ${\mathrm{PM}}_{2.5}$, aiming to improving accuracy and accessibility for health research, policy development, and environmental management strategies.

We conducted a systematic literature search across Medline, Scopus, Web of Science, Google Scholar, and Embase (January 2018 to March 2024) using keywords such as "${\mathrm{PM}}_{2.5}$ exposure," and "wildfire ${\mathrm{PM}}_{2.5}$." Studies were included if they were publicly available, focused on North America (primarily the US), and provided wildfire-attributable ${\mathrm{PM}}_{2.5}$ data. Of 2,757 articles identified, 418 full texts were screened, and 33 met inclusion criteria. Four studies offered wildfire-specific estimates of ${\mathrm{PM}}_{2.5}$, and one dataset was excluded due to accessibility issues, leaving three for analysis. We processed data using R (version R 4.3.1; R Development Core Team) at the ZIP code level for consistency and examined total and wildfire-specific ${\mathrm{PM}}_{2.5}$ estimates for California in 2010 (low fire activity) and 2018 (high fire activity), focusing on Los Angeles (densely monitored) and Modoc (no monitors) counties. Analyses included Pearson correlation, cross-correlation, and Granger causality to assess temporal relationships and consistency.

From the 33 studies included, three main estimation approaches emerged: chemical extraction, thresholding, and integration of satellite and fire-specific data (e.g., smoke plumes and fire perimeters). Most studies combined ground-based monitor data, satellite-derived aerosol optical depth, and explanatory data like meteorology and land use. The three public datasets indicated that in California, wildfire-specific ${\mathrm{PM}}_{2.5}$ contributed 11.2%-36.9% of total ${\mathrm{PM}}_{2.5}$ in 2010 and 13.7%-21.2% in 2018 with stronger agreement in 2018. Correlations were stronger in Modoc County (no monitors) (0.44-0.51 in 2010; 0.79-0.88 in 2018) than in Los Angeles County (densely populated area, 20 EPA monitors, where correlations ranged from 0.19-0.21 in 2010 and 0.54-0.79 in 2018). Overall, the datasets estimating total ${\mathrm{PM}}_{2.5}$ were more consistent than wildfire-specific ${\mathrm{PM}}_{2.5}$ estimates.

We offer a review of current data sources used for wildfire-specific ${\mathrm{PM}}_{2.5}$ estimation and compare publicly available datasets. As expected, the contribution of wildfire smoke to overall ${\mathrm{PM}}_{2.5}$ increased with wildfire activity. However, limited publicly available datasets hinder comprehensive comparisons and generalizations for health research and outcomes. https://doi.org/10.1289/EHP15672.