Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 18, issue 20
Articles | Volume 18, issue 20
https://doi.org/10.5194/amt-18-5763-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-5763-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 20
Research article
 | 
24 Oct 2025
Research article |  | 24 Oct 2025

Machine learning-based downscaling of aerosol size distributions from a global climate model

Antti Vartiainen, Santtu Mikkonen, Ville Leinonen, Tuukka Petäjä, Alfred Wiedensohler, Thomas Kühn, and Tuuli Miinalainen

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Short summary
Global climate models, commonly used for climate predictions, struggle at capturing local-scale variations in air quality. We have used measurements of ultrafine particles (UFPs), a less understood air pollutant with potentially significant health implications, for training machine learning models that can substantially reduce the inaccuracy in UFP concentrations predicted by a climate model. This approach could aid epidemiological studies of ultrafine particles by extending exposure records.
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