Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/15377
Title: Development of Land Use Regression Models for Particle Composition in Twenty Study Areas in Europe
Authors: de Hoogh, Kees
Wang, 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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