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dc.contributor.authorCOMERO Saraen_GB
dc.contributor.authorSERVIDA Diegoen_GB
dc.contributor.authorCAPITANI Luisaen_GB
dc.contributor.authorGAWLIK Bernden_GB
dc.date.accessioned2012-12-07T01:01:50Z-
dc.date.available2012-12-06en_GB
dc.date.available2012-12-07T01:01:50Z-
dc.date.created2012-10-15en_GB
dc.date.issued2012en_GB
dc.date.submitted2011-04-06en_GB
dc.identifier.citationJOURNAL OF GEOCHEMICAL EXPLORATION vol. 118 p. 30-37en_GB
dc.identifier.issn0375-6742en_GB
dc.identifier.urihttp://publications.jrc.ec.europa.eu/repository/handle/JRC64614-
dc.description.abstractStatistical methods are increasingly used for geochemical characterization of contaminated sites. The geochemical characteristics of the abandoned Coren del Cucì mine dump (Upper Val Seriana, Italy) were modelled by principal component analysis (PCA) and positivematrix factorization (PMF) of 56 soil samples analyzed for 11 elements and pH. PCA and PMF were used to investigate how different approaches deal with the preset type of data. PCA was performed on two data subsets—samples inside and outside the dump—recognized by cluster analysis. PMF was performed on the whole data set. However, a GIS-based approach was combined with PMF for better factor resolution. Three main principal components (PCs) were identified inside the dump: (i) the local ore mineralization; (ii) the background/regional metal content of rocks; and (iii) the variability of Cd. Two main PCs were obtained outside the dump: (i) the background/regionalmetal content of rocks; and (ii) the local ore elements. Five factors were determined by PMF: (i) two background geo-morphological characteristics of the area outside the dump; (ii) a source ofmineralization situated inside the waste disposal area; and (iii) two different geochemical anomaly zones. PMFwas found to be useful for estimating the number and composition of sources or processes that govern data characterized by heterogeneous behavior. In contrast to the application of PCA, no data pre-treatments procedures are needed to apply PMF.en_GB
dc.description.sponsorshipJRC.H.1-Water Resourcesen_GB
dc.format.mediumPrinteden_GB
dc.languageENGen_GB
dc.publisherELSEVIER SCIENCE BVen_GB
dc.relation.ispartofseriesJRC64614en_GB
dc.titleGeochemical characterization of an abandoned mine site: A combined positive matrix factorization and GIS approach compared with principal component analysisen_GB
dc.typeArticles in periodicals and booksen_GB
dc.identifier.doidoi:10.1016/j.gexplo.2012.04.003en_GB
JRC Directorate:Sustainable Resources

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