Articles | Volume 26, issue 1
https://doi.org/10.5194/acp-26-635-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-635-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Jan 2026
Research article |
| 14 Jan 2026
Deciphering isoprene variability across dozen of Chinese and overseas cities using deep transfer learning
Song Liu
College of carbon Neutrality Future Technology, Sichuan University, Chengdu 610065, China
Xiaopu Lyu
CORRESPONDING AUTHOR
Department of Geography, Hong Kong Baptist University, Hong Kong 000000, China
Fumo Yang
College of carbon Neutrality Future Technology, Sichuan University, Chengdu 610065, China
Zongbo Shi
School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK
Xin Huang
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Tengyu Liu
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Hongli Wang
State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, 200233, China
Mei Li
College of Environment and Climate, Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China
Jian Gao
Chinese Research Academy of Environmental Sciences, Beijing 100012, China
Nan Chen
Research Centre for Complex Air Pollution of Hubei Province, Wuhan 430078, China
Guoliang Shi
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
Institute of Tropical and Marine Meteorology, China Meteorological Administration, Guangzhou, China
Chenglei Pei
Guangzhou Sub-branch of Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510006, China
Chengxu Tong
School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK
Xinyi Liu
College of carbon Neutrality Future Technology, Sichuan University, Chengdu 610065, China
Li Zhou
College of carbon Neutrality Future Technology, Sichuan University, Chengdu 610065, China
Alex B. Guenther
Department of Earth System Science, University of California, Irvine, California, USA
College of carbon Neutrality Future Technology, Sichuan University, Chengdu 610065, China
Data sets
Global Vegetation Greenness (NDVI) from AVHRR GIMMS-3G+, 1981-2022 (Version 1) J. E. Pinzon et al. https://doi.org/10.3334/ORNLDAAC/2187
ERA5-Land hourly data from 1950 to present H. Hersbach et al. https://doi.org/10.24381/cds.e2161bac
Short summary
We studied the invisible gas isoprene, which trees and vehicles release into the air and which can worsen urban smog. Using advanced computer learning trained on measurements from many cities, we uncovered how temperature, sunlight, and city greening shape isoprene levels. Comparing Hong Kong and London, we found climate warming boosts isoprene and future ozone pollution, but strong cuts in anthropogenic emission could limit this impact.
We studied the invisible gas isoprene, which trees and vehicles release into the air and which...
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