Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 21, issue 12
Articles | Volume 21, issue 12
https://doi.org/10.5194/acp-21-9719-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-9719-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 21, issue 12
Research article
 | Highlight paper
 | 
29 Jun 2021
Research article | Highlight paper |  | 29 Jun 2021

Disparities in particulate matter (PM10) origins and oxidative potential at a city scale (Grenoble, France) – Part 2: Sources of PM10 oxidative potential using multiple linear regression analysis and the predictive applicability of multilayer perceptron neural network analysis

Lucille Joanna S. Borlaza, Samuël Weber, Jean-Luc Jaffrezo, Stephan Houdier, Rémy Slama, Camille Rieux, Alexandre Albinet, Steve Micallef, Cécile Trébluchon, and Gaëlle Uzu

Viewed

Total article views: 6,643 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
5,052 1,490 101 6,643 471 83 136
  • HTML: 5,052
  • PDF: 1,490
  • XML: 101
  • Total: 6,643
  • Supplement: 471
  • BibTeX: 83
  • EndNote: 136
Views and downloads (calculated since 10 Feb 2021)
Cumulative views and downloads (calculated since 10 Feb 2021)

Viewed (geographical distribution)

Total article views: 6,643 (including HTML, PDF, and XML) Thereof 6,637 with geography defined and 6 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 24 Dec 2025
Download
Short summary
With an enhanced source apportionment obtained in a companion paper, this paper acquires more understanding of the spatiotemporal associations of the sources of PM to oxidative potential (OP), an emerging health-based metric. Multilayer perceptron neural network analysis was used to apportion OP from PM sources. Results showed that such a methodology is as robust as the linear classical inversion and permits an improvement in the OP prediction when local features or non-linear effects occur.
Read more
Share
Altmetrics
Final-revised paper
Preprint