Process-level simulation of chemical composition, size distribution and cloud condensation nuclei of secondary organic aerosol from <i>α</i>-pinene ozonolysis

Song, Zhen; Zhang, Chenqi; Shen, Hongru; Ma, Hao; Pullinen, Iida; Zhao, Defeng

doi:10.5194/acp-26-2769-2026

Articles | Volume 26, issue 4

https://doi.org/10.5194/acp-26-2769-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-26-2769-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 26, issue 4

Research article

|

24 Feb 2026

Research article |

| 24 Feb 2026

Process-level simulation of chemical composition, size distribution and cloud condensation nuclei of secondary organic aerosol from α-pinene ozonolysis

Zhen Song, Chenqi Zhang, Hongru Shen, Hao Ma, Iida Pullinen, and Defeng Zhao

Supplement

https://doi.org/10.5194/acp-26-2769-2026-supplement

Data sets

Process-level simulation of chemical composition, size distribution and cloud condensation nuclei of secondary organic aerosol from α-pinene ozonolysis Zhen Song et al. https://doi.org/10.5281/zenodo.17539325

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Short summary

Secondary organic aerosol (SOA) can act as cloud condensation nuclei (CCN) and influence global cloud formation. This study modeled CCN and chemical composition, aerosol size and hygroscopicity (κ) of SOA using a model treating every single step. We evaluated the model ability and limitations in simulated chemical composition, κ, particle size distribution and CCN as a potential benchmark model and found that the accurate simulation of SOA size and κ is essential for reliable CCN prediction.