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This project investigates the utility of satellite remote sensing to improve the identification and monitoring of air quality nonattainment areas under the National Ambient Air Quality Standards (NAAQS). Nonattainment designations—triggered when pollution levels exceed daily or annual thresholds—are critical for initiating regulatory interventions to reduce emissions and protect public health. However, these designations often rely on ground-based air monitoring networks that are spatially limited, leaving gaps in coverage across broad geographic areas.
To address this limitation, the study utilizes NOAA’s GOES Advanced Baseline Imager (ABI) PM2.5 product, a high-temporal resolution satellite dataset capable of providing surface-level fine particulate matter concentrations across the continental United States. GOES-derived PM2.5 data are processed to generate both 24-hour exceedance estimates and annual average concentrations, enabling a more robust comparison against the NAAQS criteria for short-term and long-term exposure. Geospatial analysis techniques are used to overlay satellite-derived PM2.5 data with state and county boundaries, enabling the identification of areas potentially at risk for nonattainment designation.
Satellite-based PM2.5 estimates are validated using data from the EPA’s Air Quality System (AQS) and are further used to interpolate pollutant concentrations in areas without sufficient monitoring infrastructure. By incorporating both daily and annual metrics, this approach enhances the ability to detect exceedance patterns and track long-term air quality trends. The integration of satellite observations into nonattainment assessments provides a scalable method to supplement traditional monitoring networks, improve spatial coverage, and support regulatory decision-making related to State Implementation Plans (SIPs). The findings demonstrate the value of remote sensing as a complementary tool in modern air quality management and compliance assessment.