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Authors
Wu, Yu
Chen, Jinfang
Hong, Youwei
Zhuang, Mazhan
Lin, Yiling
Ji, Xiaoting
Lin, Ziyi
Zhang, Feng
Zhang, Keran
Liao, Dan
Zhang, Fuwang
Yu, Ruilian
Hu, Gongren
Chen, Jinsheng
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Funding
Funding for this research was provided by:
National Natural Science Foundation of China (42277091)
National Natural Science Foundation of China (U22A20578)
Natural Science Foundation of Fujian Province of China (2025J011481)
Natural Science Foundation of Xiamen (3502Z202474021)
the Fund of Key Laboratory of Global Change and Marine Atmospheric Chemistry, MNR (GCMAC2309)
STS Plan Supporting Project of the Chinese Academy of Sciences in Fujian Province (2023T3013)
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Article History
Received: 10 November 2024
Revised: 1 March 2026
Accepted: 23 March 2026
First Online: 8 April 2026
Declarations
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: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
: This manuscript has not been published elsewhere in any form or language (partially or in full). All authors agreed with the content and to submit an original paper entitled “Machine learning exploring the double high PM 2.5 and O 3 pollution in the southeast of China during 2018–2022”, which is expected to be published in Aerosol and Air Quality Research. All authors agree to publish an original paper entitled “Machine learning exploring the double high PM 2.5 and O 3 pollution in the southeast of China during 2018–2022” in Aerosol and Air Quality Research, if it is passed through peer reviews and accepted for publication.
