2016
DOI: 10.1016/j.chemosphere.2015.11.094
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Spatial distribution and potential sources of trace elements in PM10 monitored in urban and rural sites of Piedmont Region

Abstract: The results on elemental composition of aerosol (PM10) sampled during 2011 in Piedmont region (Italy) are interpreted using meteorological data, Enrichment Factors (EF), chemometric processing by Principal Component Analysis (PCA), Factor Analysis (FA) and Hierarchical Cluster Analysis (HCA).Daily concentrations of about 30 elements were measured using HR-ICP-MS in five monitoring sites. A clear seasonal pattern, with higher concentrations in autumn and winter, was observed, particularly in the urban sites. Le… Show more

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Cited by 48 publications
(12 citation statements)
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“…The mean concentrations were comparable to other urban sites in Campania (South Italy) such as Naples [27] or to other urban Italian sites [35].…”
Section: Pm 10 Mass Concentrationssupporting
confidence: 52%
“…The mean concentrations were comparable to other urban sites in Campania (South Italy) such as Naples [27] or to other urban Italian sites [35].…”
Section: Pm 10 Mass Concentrationssupporting
confidence: 52%
“…The urban enrichment of PM 10 observed here has also been demonstrated previously when comparing urban PM 10 with rural locations [ Hueglin et al ., ; Padoan et al ., ; Röösli et al ., ; Yin and Harrison , ] and suburban locations [ Hueglin et al ., ; Wei et al ., ]. These variations were mostly attributed to enhanced anthropogenic activities in city areas such as soil resuspension by moving traffic [ Hueglin et al ., ; Padoan et al ., ; Wei et al ., ].…”
Section: Resultsmentioning
confidence: 99%
“…A unique advantage of the PMF algorithm is that the model considers the measurement uncertainties corresponding to the observed data to weigh the data points, and thus output the source profiles that can well represent the real characteristics. Of course, Principal Component Analysis (PCA) related methods (e.g., Padoan et al [57]) are also useful for the source apportionment analyses. In this study, we used EPA (Environmental Protection Agency) PMF 3.0 to identify and apportion possible sources to the observed metal elements.…”
Section: Pmf Analysismentioning
confidence: 99%