Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 25, issue 21
Articles | Volume 25, issue 21
https://doi.org/10.5194/acp-25-14205-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-14205-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 21
Research article
 | 
30 Oct 2025
Research article |  | 30 Oct 2025

Differentiation of primary and secondary marine organic aerosol with machine learning

Baihua Chen, Lu Lei, Emmanuel Chevassus, Wei Xu, Ling Zhen, Haobin Zhong, Lin Wang, Chunshui Lin, Ru-Jin Huang, Darius Ceburnis, Colin O'Dowd, and Jurgita Ovadnevaite

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Short summary
This study uses machine learning to separate marine primary organic aerosol (POA) and secondary organic aerosol (SOA) from 1 decade of high-resolution data. POA averages 51 % of marine organic aerosols annually, peaking at 63 % in summer. A support vector regression model, validated via fuzzy clustering and Monte Carlo simulations, identifies seasonal patterns of POA linked to biological activity. We found diverse impacts of marine POA and SOA on the aerosol hygroscopicity and mixing state.
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