This work focused on the oxidative potential (OP) of the water-soluble fraction of PM2.5 collected at an industrial suburban site, near a biogas plant in the South of Italy. The study aimed also to estimate the contribution of PM2.5 sources to the measured OP. The measurement campaign was performed between 30/01/2018 and 28/03/2018, collecting 48 PM2.5 samples. The daily PM2.5 samples were chemically analysed for evaluating the concentrations of elemental and organic carbon, the main water-soluble ions, the main metals. The OP was evaluated with the Dithiothreitol (DTT) assay. The acquired dataset was analysed in order to identify the principal PM2.5 sources and to evaluate their impact to the OPDTT using two approaches: the first included DTTnormalized with the sampled air volume (DTTV) in the input of the receptor model PMF5, the second used a multi-linear regression between PMF outputs and DTTV for estimating the source contributions to OPDTT.

Source apportionment of PSource apportionment of PM2.5 and of its oxidative potential in an industrial suburban site in South Italyand of its oxidative potential in an industrial suburban site in South Italy

Daniela Cesari;Eva Merico;Fabio Massimo Grasso;Stefano Decesari;Franco Belosi;Francesco Manarini;Paola De Nuntiis;Matteo Rinaldi;Andrea Gambaro;Elisa Morabito;Daniele Contini
2020

Abstract

This work focused on the oxidative potential (OP) of the water-soluble fraction of PM2.5 collected at an industrial suburban site, near a biogas plant in the South of Italy. The study aimed also to estimate the contribution of PM2.5 sources to the measured OP. The measurement campaign was performed between 30/01/2018 and 28/03/2018, collecting 48 PM2.5 samples. The daily PM2.5 samples were chemically analysed for evaluating the concentrations of elemental and organic carbon, the main water-soluble ions, the main metals. The OP was evaluated with the Dithiothreitol (DTT) assay. The acquired dataset was analysed in order to identify the principal PM2.5 sources and to evaluate their impact to the OPDTT using two approaches: the first included DTTnormalized with the sampled air volume (DTTV) in the input of the receptor model PMF5, the second used a multi-linear regression between PMF outputs and DTTV for estimating the source contributions to OPDTT.
2020
PM2.5; source apportionment; oxidative potential; industrial site
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/420152
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