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

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

doi:10.5194/acp-25-17275-2025

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

Supplement

https://doi.org/10.5194/acp-25-17275-2025-supplement

Data sets

rahulranjanaces/Inverse-closure: inverse-closure (Version 0) R. Ranjan https://doi.org/10.5281/zenodo.17243563

rahulranjanaces/DREAM-MCMC: Inverse-closure using DREAM-MCMC (DREAM-MCMC) M. Dewey https://doi.org/10.5281/zenodo.17243685

Cloud Condensation Nuclei observation data (2016--2020) for the study 'Optimizing CCN predictions through inferred modal aerosol composition -- a boreal forest case study' L. Ahonen et al. https://doi.org/10.5281/zenodo.17277646

Model code and software

rahulranjanaces/Inverse-closure: inverse-closure (Version 0) R. Ranjan https://doi.org/10.5281/zenodo.17243563

rahulranjanaces/DREAM-MCMC: Inverse-closure using DREAM-MCMC (DREAM-MCMC) M. Dewey https://doi.org/10.5281/zenodo.17243685

Download

Article (3775 KB)
Full-text XML

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.