Leveraging High-Resolution Satellite-Derived NO₂ Estimates to Evaluate NO₂ Exposure Representativeness and Socioeconomic Disparities.

ABSTRACT: 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 R² 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 NO_2</

SUBMITTER: Kim NR 

PROVIDER: S-EPMC11866924 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature