Leveraging High-ResolutionSatellite-Derived NO₂ Estimates to Evaluate NO₂ Exposure Representativenessand Socioeconomic Disparities

Research has typically estimated NO₂ concentrations over several kilometers; thus, NO₂ data at finer spatial resolution remain limited. This study used tropospheric NO₂ data from the TROPOspheric Monitoring Instrument (TROPOMI) and traffic-related land use parameters to estimate long-term average NO₂ concentrations at a spatial resolution of 500 m in South Korea from 2018 to 2022. Our satellite-land use hybrid regression model showed reasonably high predictability with a cross-validation <i>R</i>² of 0.81, mean absolute error of 2.28 ppb and root mean squared error of 2.85 ppb. Leveraging these high-resolution data, we assessed the representativeness of ground monitors for population exposure by comparing population-weighted NO₂ concentrations from estimated and measured data. Across 17 metropolitan cities and provinces, the ratios of population-weighted estimated to measured NO₂ ranged from 0.62 to 1.12, with the ratio of 1 exhibiting the most representative monitoring networks. We further investigated disproportionate NO₂ exposures based on socioeconomic status, revealing that NO₂ exposures were consistently higher in local districts with higher socioeconomic status because of the unique historical backgrounds of rapid economic development and urban infrastructure design in South Korea. Using high-resolution NO₂ data can lead to more comprehensive and precise exposure assessments, enhancing public health and regulatory applications.