Articles | Volume 18, issue 5
https://doi.org/10.5194/essd-18-2999-2026
https://doi.org/10.5194/essd-18-2999-2026
Data description article
 | 
05 May 2026
Data description article |  | 05 May 2026

Improved global daily nitrogen dioxide concentrations from 2005 to 2023 derived using a deep learning approach

Jiangshan Mu, Chenliang Tao, Yuqiang Zhang, Zhou Liu, Yingnan Zhang, Na Zhao, Bin Luo, Qionghui Zhou, Qingzhu Zhang, Hongliang Zhang, and Likun Xue

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Short summary
Nitrogen dioxide is a common air pollutant that varies strongly across space and time, yet consistent global information has been limited. We developed a new global dataset that describes daily nitrogen dioxide levels from 2005 to 2023 by combining satellite observations, weather data, and ground measurements using artificial intelligence. The dataset reveals long-term changes and regional patterns and provides a reliable resource for future air quality research.
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