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

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• 作者：Kees de Hoogh ; Meng Wang ; Martin Adam ; Chiara Badaloni ; Rob Beelen ; Matthias Birk ; Giulia Cesaroni ; Marta Cirach ; Christophe Declercq ; Audrius D臈del臈 ; Evi Dons ; Audrey de Nazelle ; Marloes Eeftens ; Kirsten Eriksen ; Charlotta Eriksson ; Paul Fischer ; Regina Gra啪ulevi膷ien臈 ; Alexandros Gryparis ; Barbara Hoffmann ; Michael Jerrett ; Klea Katsouyanni ; Minas Iakovides ; Timo Lanki ; Sarah Lindley ; Christian Madsen ; Anna M枚lter ; Gioia Mosler ; Gizella N谩dor ; Mark Nieuwenhuijsen ; G枚ran Pershagen ; Annette Peters ; Harisch Phuleria ; Nicole Probst-Hensch ; Ole Raaschou-Nielsen ; Ulrich Quass ; Andrea Ranzi ; Euripides Stephanou ; Dorothea Sugiri ; Per Schwarze ; Ming-Yi Tsai ; Tarja Yli-Tuomi ; Mih谩ly J. Varr贸 ; Danielle Vienneau ; Gudrun Weinmayr ; Bert Brunekreef ; Gerard Hoek
• 刊名：Environmental Science & Technology (ES&T)
• 出版年：2013
• 出版时间：June 4, 2013
• 年：2013
• 卷：47
• 期：11
• 页码：5778-5786
• 全文大小：561K
• 年卷期：v.47,no.11(June 4, 2013)
• ISSN：1520-5851

文摘

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 (NO_x) and particulate matter (PM). No models have yet been published of elemental composition. As part of the ESCAPE project, we measured the elemental composition in both the PM₁₀ and PM_2.5 fraction sizes at 20 sites in each of 20 study areas across Europe. LUR models for eight a priori selected elements (copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)) were developed. Good models were developed for Cu, Fe, and Zn in both fractions (PM₁₀ and PM_2.5) explaining on average between 67 and 79% of the concentration variance (R²) with a large variability between areas. Traffic variables were the dominant predictors, reflecting nontailpipe emissions. Models for V and S in the PM₁₀ and PM_2.5 fractions and Si, Ni, and K in the PM₁₀ fraction performed moderately with R² ranging from 50 to 61%. Si, NI, and K models for PM_2.5 performed poorest with R² under 50%. The LUR models are used to estimate exposures to elemental composition in the health studies involved in ESCAPE.