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
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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

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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.
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