Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 17, issue 13
Articles | Volume 17, issue 13
https://doi.org/10.5194/amt-17-4137-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-4137-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 13
Research article
 | 
15 Jul 2024
Research article |  | 15 Jul 2024

Retrieval and analysis of the composition of an aerosol mixture through Mie–Raman–fluorescence lidar observations

Igor Veselovskii, Boris Barchunov, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Mikhail Korenskii, Gaël Dubois, William Boissiere, and Nikita Kasianik

Viewed

Total article views: 719 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
543 130 46 719 33 36
  • HTML: 543
  • PDF: 130
  • XML: 46
  • Total: 719
  • BibTeX: 33
  • EndNote: 36
Views and downloads (calculated since 12 Feb 2024)
Cumulative views and downloads (calculated since 12 Feb 2024)

Viewed (geographical distribution)

Total article views: 719 (including HTML, PDF, and XML) Thereof 725 with geography defined and -6 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 13 Aug 2024
Download
Short summary
The paper presents a new method that categorizes atmospheric aerosols by analyzing their optical properties with a Mie–Raman–fluorescence lidar. The research specifically looks into understanding the presence of smoke, urban, and dust aerosols in the mixtures identified by this lidar. The reliability of the results is evaluated using the Monte Carlo technique. The effectiveness of this approach is successfully demonstrated through testing in ATOLL, an observatory influenced by diverse aerosols.
Read more