Work

Advancing Aerosol Chemistry with Machine Learning: A Short Review

Year: 2025

Type: article

Source: ACS ES&T Air

DOI: 10.1021/acsestair.5c00001

Authors: Ying Wang, Wei Xu, Haobin Zhong, Baihua Chen, Lin Yang, Lin Wang, Jingye Ren, Jing Duan, Chunshui Lin, Ru-Jin Huang

Institutions: Chinese Academy of Sciences, Beijing Normal University, Institute of Earth Environment, State Key Laboratory of Earth Surface Processes and Resource Ecology, Institute of Urban Environment, Jiaxing Nanhu University

Language: English

Topic: Atmospheric chemistry and aerosols

Subfield: Atmospheric Science

Field: Earth and Planetary Sciences

Domain: Physical Sciences

Open Access status: closed

Funders: National Natural Science Foundation of China, Chinese Academy of Sciences, National Key Research and Development Program of China, State Key Laboratory of Loess and Quaternary Geology

Awards: G3070953474, G3187080897, G3535806154, G4326816878, G7696740189

OpenAlex ID: W4415902379

FWCI: 1.344

Cites: 164

Cited by: 3

Related to: