Applying Satellite-Derived PM2.5 Data to Policy-Relevant Air Quality Metrics

Abstract

Since 2000, the American Lung Association (ALA) has published an annual “State of the Air” report, which assigns grades and ranks United States (U.S.) cities and counties based on data from regulatory monitors reported to the Environmental Protection Agency (EPA). We evaluate satellite-derived gridded data sets for fine particulate matter (PM_2.5), as a possible method to support the ALA assessment in counties without regulatory monitors. Our analysis compares two publicly available, annual average, satellite-derived gridded PM_2.5 data sets, allocated to U.S. counties using three different methods. Assigning the 90th percentile gridded value of PM_2.5 within a county as the county-level indicator yields moderately strong agreement between ground-based monitor PM_2.5 results and satellite-derived PM_2.5 results, with a spatial correlation coefficient of 0.76 for 8 years of Washington University global (WashU GL) data. This agreement is evaluated with respect to concentration values, rankings, and the definition of counties as “passing” or “failing” the ALA annual PM_2.5 benchmark of 9.0 μg/m³ (the 2024 EPA National Ambient Air Quality Standard for annual PM_2.5). While most unmonitored counties are “passing” the ALA benchmark, we identify 63 counties that would be classified as “failing” if satellite-based data were used to assign ALA grades. Improving methods to analyze satellite-derived data for comparison with monitor-based metrics can support broader utilization of space-based data in the U.S. and globally.