Development of Land Use Regression Models for PM2.5, PM2.5 Absorbance, PM10 and PMcoarse in 20 European Study Areas; Results of the ESCAPE Project

Eeftens, Marloes; Beelen, Rob; de Hoogh, Kees; Bellander, Tom; Cesaroni, Giulia; Cirach, Marta; Declercq, Christophe; Dėdelė, Audrius; Dons, Evi; de Nazelle, Audrey; Dimakopoulou, Konstantina; T. Eriksen, Kirsten; Falq, Grégoire; Fischer, Paul; Galassi, Claudia; Gražulevičienė, Regina; Heinrich, Joachim; Hoffmann, Barbara; Jerrett, Michael; Keidel, Dirk; Korek, Michal; Lanki, Timo; Lindley, Sarah; Madsen, Christian; Mölter, Anna; Nádor, Gizella; Nieuwenhuijsen, Mark; Nonnemacher, Michael; Pedeli, Xanthi; Raaschou‐Nielsen, Ole; Patelarou, Evridiki; Quaß, Ulrich; Ranzi, Andrea; Schindler, Christian; Stempfelet, Morgane; G. Stephanou, Euripides; Sugiri, Dorothea; Tsai, Ming‐Yi; Yli‐Tuomi, Tarja; János Varró, Mihály; Vienneau, Danielle; von Klot, Stephanie; Wolf, Kathrin; Brunekreef, Bert; Hoek, Gerard

doi:10.1021/es301948k

Public

Development of Land Use Regression Models for PM2.5, PM2.5 Absorbance, PM10 and PMcoarse in 20 European Study Areas; Results of the ESCAPE Project

Published in Environmental Science & Technology • Sep 10, 2012

Authors:

Marloes Eeftens

Rob Beelen

Kees de Hoogh

Abstract

Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM(2.5), PM(2.5) absorbance, PM(10), and PM(coar...

Subject

Environmental science

Regression analysis

Explained variation

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