Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 24, issue 12
Articles | Volume 24, issue 12
https://doi.org/10.5194/acp-24-7261-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-7261-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 24, issue 12
Research article
 | 
26 Jun 2024
Research article |  | 26 Jun 2024

Unveiling the optimal regression model for source apportionment of the oxidative potential of PM10

Vy Dinh Ngoc Thuy, Jean-Luc Jaffrezo, Ian Hough, Pamela A. Dominutti, Guillaume Salque Moreton, Grégory Gille, Florie Francony, Arabelle Patron-Anquez, Olivier Favez, and Gaëlle Uzu

Viewed

Total article views: 1,088 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
815 212 61 1,088 85 34 40
  • HTML: 815
  • PDF: 212
  • XML: 61
  • Total: 1,088
  • Supplement: 85
  • BibTeX: 34
  • EndNote: 40
Views and downloads (calculated since 19 Feb 2024)
Cumulative views and downloads (calculated since 19 Feb 2024)

Viewed (geographical distribution)

Total article views: 1,088 (including HTML, PDF, and XML) Thereof 1,093 with geography defined and -5 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 20 Nov 2024
Download
Short summary
The capacity of particulate matter (PM) to generate reactive oxygen species in vivo is represented by oxidative potential (OP). This study focuses on finding the appropriate model to evaluate the oxidative character of PM sources in six sites using the PM sources and OP. Eight regression techniques are introduced to assess the OP of PM. The study highlights the importance of selecting a model according to the input data characteristics and establishes some recommendations for the procedure.
Read more
Altmetrics
Final-revised paper
Preprint