Leveraging High-Resolution Satellite-Derived NO<sub>2</sub> Estimates to Evaluate NO<sub>2</sub> Exposure Representativeness and Socioeconomic Disparities
Na Rae Kim, Hyung Joo Lee
Abstract
High Resolution Image Download MS PowerPoint Slide Research has typically estimated NO 2 concentrations over several kilometers; thus, NO 2 data at finer spatial resolution remain limited. This study used tropospheric NO 2 data from the TROPOspheric Monitoring Instrument (TROPOMI) and traffic-related land use parameters to estimate long-term average NO 2 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 R 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 NO 2 concentrations from estimated and measured data. Across 17 metropolitan cities and provinces, the ratios of population-weighted estimated to measured NO 2 ranged from 0.62 to 1.12, with the ratio of 1 exhibiting the most representative monitoring networks. We further investigated disproportionate NO 2 exposures based on socioeconomic status, revealing that NO 2 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 NO 2 data can lead to more comprehensive and precise exposure assessments, enhancing public health and regulatory applications.