Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 19, issue 2
Articles | Volume 19, issue 2
https://doi.org/10.5194/amt-19-421-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-421-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 2
Research article
 | 
20 Jan 2026
Research article |  | 20 Jan 2026

Retrieval of aerosol composition from spectral aerosol optical depth and optical properties using a machine learning approach

Denghui Ji, Xiaoyu Sun, Christoph Ritter, and Justus Notholt

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Short summary
We have developed a new method that uses machine learning to analyse aerosols by combining different instruments measuring at different wavelengths. This method can identify the composition of these aerosols faster and more accurately. We tested it using ground-based data. Our results show that this method can help monitor air quality and better understand the impact of aerosols on the climate.
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