Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 25, issue 23
Articles | Volume 25, issue 23
https://doi.org/10.5194/acp-25-17275-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-17275-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 23
Research article
 | 
02 Dec 2025
Research article |  | 02 Dec 2025

Optimizing CCN predictions through inferred modal aerosol composition – a boreal forest case study

Rahul Ranjan, Maura Dewey, Liine Heikkinen, Lauri R. Ahonen, Krista Luoma, Paul Bowen, Tuukka Petäjä, Annica M. L. Ekman, Daniel G. Partridge, and Ilona Riipinen

Viewed

Total article views: 6,055 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
3,738 1,881 436 6,055 706 521 463
  • HTML: 3,738
  • PDF: 1,881
  • XML: 436
  • Total: 6,055
  • Supplement: 706
  • BibTeX: 521
  • EndNote: 463
Views and downloads (calculated since 08 May 2025)
Cumulative views and downloads (calculated since 08 May 2025)

Viewed (geographical distribution)

Total article views: 6,055 (including HTML, PDF, and XML) Thereof 5,954 with geography defined and 101 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Saved (final revised paper)

Latest update: 28 Oct 2026
Download
Short summary
We use multi-year measurements of cloud condensation nuclei (CCN) at a boreal forest site to inversely infer size-resolved aerosol chemical composition. We find that inorganic species are more enriched in the larger end (accumulation mode) of the sub-micron aerosol population while organics often dominate the smaller end (Aitken mode). Our approach demonstrates the potential of long-term CCN measurements to infer size-resolved chemical composition of sub-micron aerosol.
Read more
Share
Altmetrics
Final-revised paper
Preprint