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Air pollution sources apportionment in a french urban site

hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierQuality control and dynamic reliability [CQFD]
dc.contributor.authorCHAVENT, Marie
hal.structure.identifierCentre d'Etudes Nucléaires de Bordeaux Gradignan [CENBG]
dc.contributor.authorGUÉGAN, Hervé
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierQuality control and dynamic reliability [CQFD]
dc.contributor.authorKUENTZ, Vanessa
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorPATOUILLE, Brigitte
hal.structure.identifierQuality control and dynamic reliability [CQFD]
hal.structure.identifierGroupe de Recherche en Economie Théorique et Appliquée [GREThA]
dc.contributor.authorSARACCO, Jérôme
dc.date.issued2007
dc.identifier.issn2152-372X
dc.description.abstractEnThe development of air quality control strategies is a wide preoccupation for human health. In order to achieve this purpose, air pollution sources have to be accurately identified and quantified. This case study is part of a scientific project initiated by the French ministry of Ecology and Sustainable Development. Measurements of chemical composition data for particles have been realized on a French urban site. The work presented in this paper splits into two main steps. In the first one, the identification of the sources profiles has been reached thanks to Principal Component Analysis (PCA), followed by a rotation technique. Then, in the second step, a receptor modelling approach (using Positive Matrix Factorization as estimation method) allows to evaluate the apportionment of the sources. The results from these two statistical methods have enabled to characterize and apportion five sources of fine particulate emission.
dc.language.isoen
dc.publisherSociété Française de Statistique
dc.title.enAir pollution sources apportionment in a french urban site
dc.typeArticle de revue
dc.subject.halStatistiques [stat]/Applications [stat.AP]
dc.subject.halStatistiques [stat]/Méthodologie [stat.ME]
bordeaux.journalCase Studies in Business, Industry and Government Statistics
bordeaux.page119-129
bordeaux.volume1
bordeaux.issue2
bordeaux.peerReviewedoui
hal.identifierhal-00273137
hal.version1
hal.popularnon
hal.audienceNon spécifiée
dc.subject.itPollution data
dc.subject.itPrincipal Component Analysis (PCA)
dc.subject.itPositive Matrix Factorization (PMF)
dc.subject.itrotation
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-00273137v1
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