Applying Satellite-Derived PM_2.5 Data to Policy-Relevant Air Quality Metrics

Area of Science:

• Environmental Science
• Remote Sensing
• Public Health

Background:

• The American Lung Association (ALA) annually grades U.S. air quality using EPA data.
• Many counties lack regulatory monitors, limiting ALA assessments.
• Satellite-derived data offers a potential solution for assessing air quality in unmonitored areas.

Purpose of the Study:

• To evaluate satellite-derived fine particulate matter (PM2.5) data as a method to support ALA air quality assessments.
• To compare PM2.5 county-level indicators derived from satellite data with ground-based monitor results.
• To assess the feasibility of using satellite data for grading unmonitored counties.

Main Methods:

• Compared two satellite-derived PM2.5 datasets against ground-based monitor data.
• Allocated satellite data to U.S. counties using three different methods.
• Assessed agreement based on concentration values, rankings, and passing/failing the ALA benchmark (9.0 μg/m³).

Main Results:

• A 90th percentile approach for satellite PM2.5 showed moderate agreement (spatial correlation coefficient of 0.76) with ground monitors.
• Most unmonitored counties "pass" the ALA benchmark.
• 63 unmonitored counties were identified as "failing" the benchmark using satellite data.

Conclusions:

• Satellite-derived PM2.5 data can supplement ground-based monitoring for air quality assessments.
• Improved analysis methods for satellite data can enhance its utilization in air quality evaluations.
• Space-based data has the potential to broaden the scope of air quality monitoring globally.