Satellite-Based Long-Term Spatiotemporal Trends in Ambient NO₂ Concentrations and Attributable Health Burdens in China From 2005 to 2020.

ABSTRACT: Despite the recent development of using satellite remote sensing to predict surface NO₂ levels in China, methods for estimating reliable historical NO₂ exposure, especially before the establishment of NO₂ monitoring network in 2013, are still rare. A gap-filling model was first adopted to impute the missing NO₂ column densities from satellite, then an ensemble machine learning model incorporating three base learners was developed to estimate the spatiotemporal pattern of monthly mean NO₂ concentrations at 0.05° spatial resolution from 2005 to 2020 in China. Further, we applied the exposure data set with epidemiologically derived exposure response relations to estimate the annual NO₂ associated mortality burdens in China. The

SUBMITTER: Huang K 

PROVIDER: S-EPMC10190124 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature