Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 17, issue 23
Articles | Volume 17, issue 23
https://doi.org/10.5194/amt-17-6945-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-6945-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 23
Research article
 | 
11 Dec 2024
Research article |  | 11 Dec 2024

Merging holography, fluorescence, and machine learning for in situ continuous characterization and classification of airborne microplastics

Nicholas D. Beres, Julia Burkart, Elias Graf, Yanick Zeder, Lea Ann Dailey, and Bernadett Weinzierl

Viewed

Total article views: 2,025 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,650 320 55 2,025 127 58 83
  • HTML: 1,650
  • PDF: 320
  • XML: 55
  • Total: 2,025
  • Supplement: 127
  • BibTeX: 58
  • EndNote: 83
Views and downloads (calculated since 20 Dec 2023)
Cumulative views and downloads (calculated since 20 Dec 2023)

Viewed (geographical distribution)

Total article views: 2,025 (including HTML, PDF, and XML) Thereof 2,025 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 31 Oct 2025
Download
Short summary
We tested a method to identify airborne microplastics (MPs), merging imaging, fluorescence, and machine learning of single particles. We examined whether combining imaging and fluorescence data enhances classification accuracy compared to using each method separately and tested these methods with other particle types. The tested MPs have distinct fluorescence, and a combined imaging and fluorescence method improves their detection, making meaningful progress in monitoring MPs in the atmosphere.
Read more
Share