Application of multivariate statistical methods for groundwater physicochemical and biological quality assessment in the context of public health

dc.contributor.author	Παπαϊωάννου, Άγγελος	el
dc.contributor.author	Μαυρίδου, Αθηνά	el
dc.contributor.author	Χατζηχριστοδούλου, Χρήστος	el
dc.contributor.author	Παπαστεργίου, Παναγιώτης	el
dc.contributor.author	Παππά, Όλγα	el
dc.date.accessioned	2015-04-30T19:17:59Z
dc.date.available	2015-04-30T19:17:59Z
dc.date.issued	2015-04-30
dc.identifier.uri	http://hdl.handle.net/11400/9340
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://link.springer.com/article/10.1007%2Fs10661-009-1217-x	en
dc.subject	Φυσικοχημική ποιότητα του πόσιμου νερού
dc.subject	βιολογικη ποιότητα πόσιμου νερού
dc.subject	Ανάλυση κατά συστάδες
dc.subject	Διαχωριστική ανάλυση
dc.subject	Παραγοντική ανάλυση
dc.subject	Physicochemical drinking water quality
dc.subject	Biological drinking water quality
dc.subject	Cluster analysis
dc.subject	Discriminant analysis
dc.subject	Factor analysis
dc.title	Application of multivariate statistical methods for groundwater physicochemical and biological quality assessment in the context of public health	en
heal.type	journalArticle
heal.classification	Υγεία
heal.classification	Χημεία
heal.classification	Health
heal.classification	Chemistry
heal.classificationURI	N/A-Υγεία
heal.classificationURI	N/A-Χημεία
heal.classificationURI	http://zbw.eu/stw/descriptor/16635-5
heal.classificationURI	http://skos.um.es/unescothes/C00568
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh85027250
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh85038374
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh85046817
heal.contributorName	Δοβρίκη, Ελένη	el
heal.contributorName	Ρήγας, Ιωάννης	el
heal.identifier.secondary	DOI: 10.1007/s10661-009-1217-x
heal.language	en
heal.access	campus
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Επαγγελμάτων Υγείας και Πρόνοιας. Τμήμα Ιατρικών Εργαστηρίων	el
heal.publicationDate	2010-11
heal.bibliographicCitation	Papaioannou, A., Mavridou, A., Hadjichristodoulou, C., Papastergiou, P., Pappa, Ο. et al. (2010) Application of multivariate statistical methods for groundwater physicochemical and biological quality assessment in the context of public health. Monitoring and Assessment. 170 (1-4), pp.87-97. Available from: http://link.springer.com [Accessed 30/04/2015]	en
heal.abstract	Three representative areas (lowland, semi-mountainous, and coastal) have been selected for the collection of drinking water samples, and a total number of 28 physical, chemical, and biological parameters per water sample have been determined and analyzed. The mean values of the physical and chemical parameters were found to be within the limits mentioned in the 98/83/EEC directive. The analysis of biological parameters shows that many of the water samples are inadequate for human consumption because of the presence of bacteria. Cluster analysis (CA) first was used to classify sample sites with similar properties and results in three groups of sites; discriminant analysis (DA) was used to construct the best discriminant functions to confirm the clusters determined by CA and evaluate the spatial variations in water quality. The standard mode discriminant functions, using 17 parameters, yielded classification matrix correctly assigning 96.97% of the cases. In the stepwise mode, the DA produced a classification matrix with 96.36% correct assignments using only ten parameters (EC, Cl − , NO3 − , HCO3 − , CO3 − 2, Ca + 2, Na + , Zn, Mn, and Pb). CA and factor analysis (FA) are used to characterize water quality and assist in water quality monitoring planning. CA proved that two major groups of similarity (six subclusters) between 17 physicochemical parameters are formed, and FA extracts six factors that account for 66.478% of the total water quality variation, when all samples’ physicochemical data set is considered. It is noteworthy that the classification scheme obtained by CA is completely confirmed by principal component analysis.	en
heal.journalName	Environmental Monitoring and Assessment	el
heal.journalType	peer-reviewed
heal.fullTextAvailability	true