A PM10 chemically characterized nation-wide dataset for Italy. Geographical influence on urban air pollution and source apportionment.

Autor: Pietrodangelo A; C.N.R. Institute of Atmospheric Pollution Research, Monterotondo St., Rome 00015, Italy. Electronic address: pietrodangelo@iia.cnr.it., Bove MC; Ligurian Regional Agency for Environmental Protection (ARPAL), Genoa 16149, Italy., Forello AC; Department of Physics, University of Milan and INFN-Milan, 20133 Milan, Italy., Crova F; Department of Physics, University of Milan and INFN-Milan, 20133 Milan, Italy., Bigi A; Department of Engineering 'Enzo Ferrari', University of Modena and Reggio Emilia, Modena 41125, Italy., Brattich E; Department of Physics and Astronomy 'Augusto Righi', University of Bologna, Bologna 40126, Italy., Riccio A; Department of Science and Technology, University of Naples Parthenope, Naples 80143, Italy., Becagli S; Department of Chemistry 'Ugo Schiff', University of Florence, Sesto Fiorentino, Florence 50019, Italy., Bertinetti S; Department of Chemistry, University of Turin, 10125 Turin, Italy., Calzolai G; National Institute of Nuclear Physics (INFN), Sesto Fiorentino, Florence 50019, Italy., Canepari S; Department of Environmental Biology, Sapienza University of Rome, 00185 Rome, Italy., Cappelletti D; Department of Chemistry, Biology and Biotechnology, University of Perugia, 06123 Perugia, Italy., Catrambone M; C.N.R. Institute of Heritage Science, Milan 20125, Italy., Cesari D; C.N.R. Institute of Atmospheric Sciences and Climate, ISAC-CNR, Lecce 73100, Italy., Colombi C; Regional Agency for Environmental Protection of Lombardy (ARPA Lombardia), Milan 20124, Italy., Contini D; C.N.R. Institute of Atmospheric Sciences and Climate, ISAC-CNR, Lecce 73100, Italy., Cuccia E; Regional Agency for Environmental Protection of Lombardy (ARPA Lombardia), Milan 20124, Italy., De Gennaro G; Department of Biology, University of Bari 'Aldo Moro', Bari 70121, Italy., Genga A; Department of Biological and Environmental Sciences and Technologies DISTeBA, University of Salento, Lecce 73100, Italy., Ielpo P; C.N.R. Institute of Atmospheric Sciences and Climate, ISAC-CNR, Lecce 73100, Italy., Lucarelli F; Department of Physics and Astrophysics, University of Florence and INFN-Florence, Sesto Fiorentino, Florence, 50019, Italy., Malandrino M; Department of Chemistry, University of Turin, 10125 Turin, Italy., Masiol M; Department of Environmental Science, Informatics and Statistics, University Ca' Foscari, 30172 Mestre-Venezia, Italy., Massabò D; Department of Physics, University of Genoa and INFN-Genoa, 16146 Genoa, Italy., Perrino C; C.N.R. Institute of Atmospheric Pollution Research, Monterotondo St., Rome 00015, Italy., Prati P; Department of Physics, University of Genoa and INFN-Genoa, 16146 Genoa, Italy., Siciliano T; Department of Mathematics and Physics 'Ennio De Giorgi', University of Salento, Lecce 73100, Italy., Tositti L; Department of Chemistry 'Giacomo Ciamician', University of Bologna, Bologna, 40126, Italy., Venturini E; Department of Industrial Chemistry 'Toso Montanari', University of Bologna, Bologna 40126, Italy., Vecchi R; Department of Physics, University of Milan and INFN-Milan, 20133 Milan, Italy.
Jazyk: angličtina
Zdroj: The Science of the total environment [Sci Total Environ] 2024 Jan 15; Vol. 908, pp. 167891. Date of Electronic Publication: 2023 Oct 16.
DOI: 10.1016/j.scitotenv.2023.167891
Abstrakt: Urban textures of the Italian cities are peculiarly shaped by the local geography generating similarities among cities placed in different regions but comparable topographical districts. This suggested the following scientific question: can different topographies generate significant differences on the PM 10 chemical composition at Italian urban sites that share similar geography despite being in different regions? To investigate whether such communalities can be found and are applicable at Country-scale, we propose here a novel methodological approach. A dataset comprising season-averages of PM 10 mass concentration and chemical composition data was built, covering the decade 2005-2016 and referring to urban sites only (21 cities). Statistical analyses, estimation of missing data, identification of latent clusters and source apportionment modeling by Positive Matrix Factorization (PMF) were performed on this unique dataset. The first original result is the demonstration that a dataset with atypical time resolution can be successfully exploited as an input matrix for PMF obtaining Country-scale representative chemical profiles, whose physical consistency has been assessed by different tests of modeling performance. Secondly, this dataset can be considered a reference repository of season averages of chemical species over the Italian territory and the chemical profiles obtained by PMF for urban Italian agglomerations could contribute to emission repositories. These findings indicate that our approach is powerful, and it could be further employed with datasets typically available in the air pollution monitoring networks.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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