Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 19, issue 7
Articles | Volume 19, issue 7
https://doi.org/10.5194/amt-19-2575-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-2575-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 7
Research article
 | 
17 Apr 2026
Research article |  | 17 Apr 2026

Leveraging machine learning to enhance aerosol classification using Single-Particle Mass Spectrometry

Jose A. Perez Chavez, Maria A. Zawadowicz, Joseph Wilkins, and Christopher Blaszczak-Boxe

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Short summary
In this study, we leverage the power of machine learning to develop classifiers using a comprehensive dataset of SPMS spectra. These classifiers enable automatic differentiation of aerosol particles based on their chemistry and size, facilitating more accurate and efficient aerosol classification. Our results show increased accuracy when including unlabeled data in a semi-supervised framework.
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