Development of Land Use Regression Models for Particle Composition in Twenty Study Areas in Europe

de Hoogh, Kees; Wang, Meng; Adam, Martin; Badaloní, Chiara; Beelen, Rob; Birk, Matthias; Cesaroni, Giulia; Cirach, Marta; Declercq, Christophe; Dėdelė, Audrius; Dons, Evi; de Nazelle, Audrey; Eeftens, Marloes; T. Eriksen, Kirsten; Eriksson, Charlotta; Fischer, Paul; Gražulevičienė, Regina; Gryparis, Alexandros; Hoffmann, Barbara; Jerrett, Michael; Katsouyanni, Klea; Iakovides, Minas; Lanki, Timo; Lindley, Sarah; Madsen, Christian; Mölter, Anna; Mosler, Gioia; Nádor, Gizella; Nieuwenhuijsen, Mark; Pershagen, Göran; Peters, Annette; C. Phuleria, Harish; Probst‐Hensch, Nicole; Raaschou‐Nielsen, Ole; Quaß, Ulrich; Ranzi, Andrea; G. Stephanou, Euripides; Sugiri, Dorothea; E. Schwarze, Per; Tsai, Ming‐Yi; Yli‐Tuomi, Tarja; János Varró, Mihály; Vienneau, Danielle; Weinmayr, Gudrun; Brunekreef, Bert; Hoek, Gerard

doi:10.1021/es400156t

Public

Development of Land Use Regression Models for Particle Composition in Twenty Study Areas in Europe

Published in Environmental Science & Technology • May 7, 2013

Authors:

Kees de Hoogh

Meng Wang

Martin Adam

Abstract

Land Use Regression (LUR) models have been used to describe and model spatial variability of annual mean concentrations of traffic related pollutants such as nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM). No models have yet been published of elemental composition. As part...

Subject

Particulates

Environmental chemistry

Environmental science

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