Geo-STO3Net: A Deep Neural Network Integrating Geographical Spatiotemporal Information for Surface Ozone Estimation
Author:
Affiliation:
1. Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, China
2. Department of Land Surveying and Geo-Informatics, Hong Kong Polytechnic University, Hong Kong, SAR, China
Funder
Zhejiang Provincial Natural Science Foundation of China
Fundamental Research Funds for the Provincial Universities of Zhejiang
National Natural Science Foundation of China
Hong Kong Polytechnic University
Science and Technology Innovation 2025 Major Project of Ningbo City
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/36/10354519/10414127.pdf?arnumber=10414127
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1. A large ozone-circulation feedback and its implications for global warming assessments
2. Impact of ground-level ozone exposure on sleep quality and electroencephalogram patterns at different time scales
3. The impacts of ambient ozone pollution on China's wheat yield and forest production from 2010 to 2021
4. Increases in surface ozone pollution in China from 2013 to 2019: anthropogenic and meteorological influences
5. First long-term surface ozone variations at an agricultural site in the North China Plain: Evolution under changing meteorology and emissions
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