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Title: | Development of Land Use Regression Models for Particle Composition in Twenty Study Areas in Europe | Authors: | de Hoogh, Kees WANG, Xi-Meng Adam, Martin Badaloni, Chiara Beelen, Rob Birk, Matthias Cesaroni, Giulia Cirach, Marta Declercq, Christophe Dedele, Audrius DONS, Evi de Nazelle, Audrey Eeftens, Marloes Eriksen, Kirsten Eriksson, Charlotta Fischer, Paul Grazuleviciene, Regina Gryparis, Alexandros Hoffmann, Barbara Jerrett, Michael Katsouyanni, Klea Iakovides, Minas Lanki, Timo Lindley, Sarah Madsen, Christian Moelter, Anna Mosler, Gioia Nador, Gizella Nieuwenhuijsen, Mark Pershagen, Goran Peters, Annette Phuleria, Harisch Probst-Hensch, Nicole Raaschou-Nielsen, Ole Quass, Ulrich Ranzi, Andrea Stephanou, Euripides Sugiri, Dorothea Schwarze, Per Tsai, Ming-Yi Yli-Tuomi, Tarja Varro, Mihaly J. Vienneau, Danielle Weinmayr, Gudrun Brunekreef, Bert Hoek, Gerard |
Issue Date: | 2013 | Publisher: | AMER CHEMICAL SOC | Source: | ENVIRONMENTAL SCIENCE & TECHNOLOGY, 47 (11), p. 5778-5786 | 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 PM2.5) explaining on average between 67 and 79% of the concentration variance (R-2) 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 R-2 ranging from 50 to 61%. Si, NI, and K models for PM2.5 performed poorest with R-2 under 50%. The LUR models are used to estimate exposures to elemental composition in the health studies involved in ESCAPE. | Notes: | [de Hoogh, Kees; Mosler, Gioia; Vienneau, Danielle] Univ London Imperial Coll Sci Technol & Med, Dept Epidemiol & Biostat, MRC HPA Ctr Environm & Hlth, London, England. [Wang, Meng; Beelen, Rob; Eeftens, Marloes; Brunekreef, Bert; Hoek, Gerard] Univ Utrecht, Inst Risk Assessment Sci, NL-3508 TD Utrecht, Netherlands. [Adam, Martin; Eeftens, Marloes; Phuleria, Harisch; Probst-Hensch, Nicole; Tsai, Ming-Yi; Vienneau, Danielle] Swiss Trop & Publ Hlth Inst, Dept Epidemiol & Publ Hlth, Basel, Switzerland. [Adam, Martin; Eeftens, Marloes; Phuleria, Harisch; Probst-Hensch, Nicole; Tsai, Ming-Yi; Vienneau, Danielle] Univ Basel, Basel, Switzerland. [Badaloni, Chiara; Cesaroni, Giulia] Lazio Reg Hlth Serv, Dept Epidemiol, Rome, Italy. [Birk, Matthias] HMGU Inst Epidemiol I, Neuherberg, Germany. [Cirach, Marta; de Nazelle, Audrey; Nieuwenhuijsen, Mark] Ctr Res Environm Epidemiol CREAL, Barcelona, Spain. [Cirach, Marta; de Nazelle, Audrey; Nieuwenhuijsen, Mark] Hosp del Mar, Res Inst, IMIM, Barcelona, Spain. [Cirach, Marta; de Nazelle, Audrey; Nieuwenhuijsen, Mark] CIBERESP, Madrid, Spain. [Declercq, Christophe] French Inst Publ Hlth Surveillance, St Maurice, France. [Dedele, Audrius; Sugiri, Dorothea] Vytautas Magnus Univ, Kaunas, Lithuania. [Dons, Evi] VITO MRG Flemish Inst Technol Res, Environm Risk & Hlth Unit, Mol, Belgium. [Dons, Evi] Hasselt Univ, Diepenbeek, Belgium. [de Nazelle, Audrey] Univ London Imperial Coll Sci Technol & Med, Ctr Environm Policy, London, England. [Eriksen, Kirsten; Raaschou-Nielsen, Ole] Danish Canc Soc, Res Ctr, Copenhagen, Denmark. [Eriksson, Charlotta; Pershagen, Goran] Karolinska Inst, Inst Environm Med, S-10401 Stockholm, Sweden. [Fischer, Paul] Natl Inst Publ Hlth & Environm, Ctr Environm Hlth, NL-3720 BA Bilthoven, Netherlands. [Gryparis, Alexandros; Katsouyanni, Klea] Univ Athens, Sch Med, Dept Hyg Epidemiol & Med Stat, Athens 11528, Greece. [Grazuleviciene, Regina; Hoffmann, Barbara; Weinmayr, Gudrun] Univ Dusseldorf, IUF Leibniz Res Inst Environm Med, D-40225 Dusseldorf, Germany. [Jerrett, Michael] Univ Calif Berkeley, Sch Publ Hlth, Berkeley, CA 94720 USA. [Iakovides, Minas; Stephanou, Euripides] Univ Crete, Environm Chem Proc Lab, Iraklion, Greece. [Lanki, Timo; Yli-Tuomi, Tarja] Natl Inst Hlth & Welf, Dept Environm Hlth, Kuopio, Finland. [Lindley, Sarah] Univ Manchester, Sch Environm & Dev Geog, Manchester, Lancs, England. [Madsen, Christian] Norwegian Inst Publ Hlth, Div Epidemiol, Oslo, Norway. [Moelter, Anna] Univ Manchester, Ctr Occupat & Environm Hlth, Manchester, Lancs, England. [Nador, Gizella; Varro, Mihaly J.] Natl Inst Environm Hlth, Dept Environm Epidemiol, Budapest, Hungary. [Peters, Annette] HMGU Inst Epidemiol II, Neuherberg, Germany. [Quass, Ulrich] IUTA Inst Energie & Umwelttech eV, Air Qual & Sustainable Nanotechnol, Duisburg, Germany. [Ranzi, Andrea] ARPA Emilia Romagna, Reg Reference Ctr Environm & Hlth, Modena, Italy. [Schwarze, Per] Norwegian Inst Publ Hlth, Div Environm Med, Oslo, Norway. [Tsai, Ming-Yi] Univ Washington, Dept Environm & Occupat Hlth Sci, Seattle, WA 98195 USA. [Brunekreef, Bert] Univ Med Ctr Utrecht, Julius Ctr Hlth Sci & Primary Care, Utrecht, Netherlands. c.dehoogh@imperial.ac.uk | Keywords: | Engineering, Environmental; Environmental Sciences | Document URI: | http://hdl.handle.net/1942/15377 | ISSN: | 0013-936X | e-ISSN: | 1520-5851 | DOI: | 10.1021/es400156t | ISI #: | 000320097400035 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2014 |
Appears in Collections: | Research publications |
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