Advancing new metrics for wildfire smoke exposure: Case study in Alaska to bridge public health, climate adaptation, and fire management

For this study, researchers developed a historical air quality dataset for Alaska using a hybrid approach that integrates GEOS-Chem atmospheric modeling with ground-based data to estimate daily wildfire-attributable PM2.5 at a 0.625°×0.5° resolution from 2003–2020. We aggregated these estimates by census tract and derived metrics to quantify long-term wildfire smoke exposure, then combined these estimates with social vulnerability data to identify populations disproportionately affected. Alaskans experienced an average of 3.5 million person-days of moderate and >800,000 person-days of dense smoke exposure annually. In years when over 2 million acres burned, 86–98% of census tracts recorded at least one day of moderate smoke, and up to 73% experienced heavy smoke.

Northern Interior Alaska had over 300 cumulative days of poor air quality (~10% of summer days) over the 18-year period, with smoke waves lasting as long as 43 days. Tracts identified as having high smoke exposure and high smoke vulnerability were generally in rural Interior Alaska; however, urban tracts in Interior and Southcentral were also identified. High-exposure census tracts had statistically greater proportions of housing cost-burdened residents and women of childbearing age. This study highlights the need to move beyond traditional fire metrics and adopt measures that better capture the full scope of human exposure. This approach provides a framework for assessing health risks and integrating public health into climate adaptation and fire management especially in wildfire-prone regions where observations are sparse.