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Deciphering isoprene variability across dozen of Chinese and overseas cities using deep transfer learning.

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Title: Deciphering isoprene variability across dozen of Chinese and overseas cities using deep transfer learning.
Authors: Liu, Song1, Lyu, Xiaopu2 xiaopu_lyu@hkbu.edu.hk, Yang, Fumo1, Shi, Zongbo3, Huang, Xin4, Liu, Tengyu4, Wang, Hongli5, Li, Mei6, Gao, Jian7, Chen, Nan8, Shi, Guoliang9, Zou, Yu10, Pei, Chenglei11, Tong, Chengxu3, Liu, Xinyi1, Zhou, Li1, Guenther, Alex B.12, Wang, Nan1 nan.wang@scu.edu.cn
Source: Atmospheric Chemistry & Physics. 2026, Vol. 26 Issue 1, p635-646. 12p.
Database: Environment Complete
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  Data: Deciphering isoprene variability across dozen of Chinese and overseas cities using deep transfer learning.
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  Data: <searchLink fieldCode="JN" term="%22Atmospheric+Chemistry+%26+Physics%22">Atmospheric Chemistry & Physics</searchLink>. 2026, Vol. 26 Issue 1, p635-646. 12p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eih&AN=191076225
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        Value: 10.5194/acp-26-635-2026
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        Text: English
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              Text: 2026
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