@article{3006167,
    title = "Development of land use regression models for particle composition in twenty study areas in Europe",
    author = "De Hoogh, K. and Wang, M. and Adam, M. and Badaloni, C. and Beelen, R. and Birk, M. and Cesaroni, G. and Cirach, M. and Declercq, C. and Dědelě, A. and Dons, E. and De Nazelle, A. and Eeftens, M. and Eriksen, K. and Eriksson, C. and Fischer, P. and Gražulevičieně, R. and Gryparis, A. and Hoffmann, B. and Jerrett, M. and Katsouyanni, K. and Iakovides, M. and Lanki, T. and Lindley, S. and Madsen, C. and Mölter, A. and Mosler, G. and Nádor, G. and Nieuwenhuijsen, M. and Pershagen, G. and Peters, A. and Phuleria, H. and Probst-Hensch, N. and Raaschou-Nielsen, O. and Quass, U. and Ranzi, A. and Stephanou, E. and Sugiri, D. and Schwarze, P. and Tsai, M.-Y. and Yli-Tuomi, T. and Varró, M.J. and Vienneau, D. and Weinmayr, G. and Brunekreef, B. and Hoek, G.",
    journal = "Environmental science and technology",
    year = "2013",
    volume = "47",
    number = "11",
    pages = "5778-5786",
    issn = "0194-0287",
    doi = "10.1021/es400156t",
    keywords = "Elemental compositions;  Land use regression;  Land-use regression models;  Particle composition;  Particulate Matter;  Spatial variability;  Traffic variables;  Traffic-related pollutants, Land use;  Nickel;  Nitrogen oxides;  Regression analysis;  Zinc, Silicon, copper;  element;  iron;  nickel;  potassium;  silicon;  sulfur;  vanadium;  zinc, annual variation;  chemical composition;  health impact;  land use;  project assessment;  regression analysis;  spatial variation;  traffic emission, article;  concentration (parameters);  Europe;  land use;  land use regression model;  particulate matter;  regression analysis;  traffic, Air Pollution;  Copper;  Europe;  Geographic Information Systems;  Models, Theoretical;  Nickel;  Nitrogen Dioxide;  Nitrogen Oxides;  Particulate Matter;  Potassium;  Regression Analysis;  Silicon;  Sulfur;  Vanadium;  Zinc, Europe",
    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 of the ESCAPE project, we measured the elemental composition in both the PM10 and PM2.5 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 PM2.5 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 PM2.5 performed poorest with R2 under 50%. The LUR models are used to estimate exposures to elemental composition in the health studies involved in ESCAPE. © 2013 American Chemical Society."
}