Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 25, issue 2
Articles | Volume 25, issue 2
https://doi.org/10.5194/acp-25-759-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-759-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 2
Research article
 | 
21 Jan 2025
Research article |  | 21 Jan 2025

Unleashing the potential of geostationary satellite observations in air quality forecasting through artificial intelligence techniques

Chengxin Zhang, Xinhan Niu, Hongyu Wu, Zhipeng Ding, Ka Lok Chan, Jhoon Kim, Thomas Wagner, and Cheng Liu

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Short summary
This research utilizes hourly air pollution observations from the world’s first geostationary satellite to develop a spatiotemporal neural network model for full-coverage surface NO2 pollution prediction over the next 24 hours, achieving outstanding forecasting performance and efficacy. These results highlight the profound impact of geostationary satellite observations in advancing air quality forecasting models, thereby contributing to future models for health exposure to air pollution.
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