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 was written by Borlaza, Lucille Joanna S.;Weber, Samuel;Jaffrezo, Jean-Luc;Houdier, Stephan;Slama, Remy;Rieux, Camille;Albinet, Alexandre;Micallef, Steve;Trebluchon, Cecile;Uzu, Gaelle. And the article was included in Atmospheric Chemistry and Physics in 2021.HPLC of Formula: 76-54-0 This article mentions the following:
The oxidative potential (OP) of particulate matter (PM) measures PM capability to potentially cause anti-oxidant imbalance. Due to the wide range and complex mixture of species in particulates, little is known about the pollution sources most strongly contributing to OP. A 1-yr sampling of PM10 (particles with an aerodynamic diameter below 10) was performed over different sites in a medium-sized city (Grenoble, France). An enhanced fine-scale apportionment of PM10 sources, based on the chem. composition, was performed using the pos. matrix factorization (PMF) method and reported in a companion paper. OP was assessed as the ability of PM10 to generate reactive oxygen species (ROS) using three different acellular assays: dithiothreitol (DTT), ascorbic acid (AA), and 2,7-dichlorofluorescein (DCFH) assays. Using multiple linear regression (MLR), the OP contributions of the sources identified by PMF were estimated Conversely, since atm. processes are usually non-linear in nature, artificial neural network (ANN) techniques, which employ non-linear models, could further improve estimates Hence, the multilayer perceptron anal. (MLP), an ANN-based model, was addnl. used to model OP based on PMF-resolved sources as well. This study presents the spatiotemporal variabilities of OP activity with influences by season-specific sources, site typol. and specific local features, and assay sensitivity. Overall, both MLR and MLP effectively captured the evolution of OP. The primary traffic and biomass burning sources were the strongest drivers of OP in the Grenoble basin. There is also a clear redistribution of source-specific impacts when using OP instead of mass concentration, underlining the importance of PM redox activity for the identification of potential sources of PM toxicity. Finally, the MLP generally offered improvements in OP prediction, especially for sites where synergistic and/or antagonistic effects between sources are prominent, supporting the value of using ANN-based models to account for the non-linear dynamics behind the atm. processes affecting OP of PM10. In the experiment, the researchers used many compounds, for example, 2′,7′-Dichloro-3′,6′-dihydroxy-3H-spiro[isobenzofuran-1,9′-xanthen]-3-one (cas: 76-54-0HPLC of Formula: 76-54-0).
2′,7′-Dichloro-3′,6′-dihydroxy-3H-spiro[isobenzofuran-1,9′-xanthen]-3-one (cas: 76-54-0) belongs to benzofurans derivatives. Benzofuran derivatives are one of the most important oxygen-containing heterocycles. Benzofurans are stable towards alkali and readily polymerize on treatment with sulfuric acid, due to which they are useful for the preparation of low cost chemically relatively inert resins.HPLC of Formula: 76-54-0
Referemce:
Benzofuran – Wikipedia,
Benzofuran | C8H6O – PubChem