Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 18, issue 23
Articles | Volume 18, issue 23
https://doi.org/10.5194/amt-18-7297-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-7297-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 23
Research article
 | 
02 Dec 2025
Research article |  | 02 Dec 2025

Laser-Induced Fluorescence coupled with Machine Learning as an effective approach for real-time identification of bacteria in bioaerosols

Alejandro Fontal, Sílvia Borràs, Lídia Cañas, Sofya Pozdniakova, and Xavier Rodó

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Short summary
Monitoring airborne microbes is crucial for health and ecosystems, but often slow and expensive. We adapted an existing instrument, Rapid-E, using Laser-Induced Fluorescence and machine learning, for rapid, field-deployable bacterial identification. Our system successfully detected bacteria and showed promise in distinguishing various species. This faster approach improves environmental monitoring and helps safeguard public health by quickly spotting potential microbial threats in the air.
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