TROPOMI Satellite Data Reshape NO₂ Air Pollution Land-Use Regression Modeling Capabilities in the United States.

ABSTRACT: Nitrogen dioxide (NO₂) pollution is associated with adverse health effects, but its spatial variability between ground monitors is poorly characterized. NO₂ column observations from the Tropospheric Monitoring Instrument (TROPOMI) have unprecedented spatial resolution and high accuracy over the globe. Land-use regression (LUR) models predict surface-level NO₂ with relevance for epidemiological and environmental justice studies. We use TROPOMI NO₂ columns in a land use regression (LUR) model to improve surface NO₂ concentration estimates over the United States. The TROPOMI LUR predictions have improved correlation with ground monitors (Adj. R ² = 0.72) and bias (Mean Bias, MB = 14.2%) compared with an existing LUR usin

SUBMITTER: Nawaz MO 

PROVIDER: S-EPMC11833862 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature