Articles | Volume 23, issue 2
https://doi.org/10.5194/acp-23-1511-2023
https://doi.org/10.5194/acp-23-1511-2023
Research article
 | 
26 Jan 2023
Research article |  | 26 Jan 2023

Ground-level gaseous pollutants (NO2, SO2, and CO) in China: daily seamless mapping and spatiotemporal variations

Jing Wei, Zhanqing Li, Jun Wang, Can Li, Pawan Gupta, and Maureen Cribb

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Latest update: 13 Dec 2024
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Short summary
This study estimated the daily seamless 10 km ambient gaseous pollutants (NO2, SO2, and CO) across China using machine learning with extensive input variables measured on monitors, satellites, and models. Our dataset yields a high data quality via cross-validation at varying spatiotemporal scales and outperforms most previous related studies, making it most helpful to future (especially short-term) air pollution and environmental health-related studies.
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