Development of land use regression models for particle composition in 20 study areas in Europe

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

doi:10.1021/es400156t

Development of land use regression models for particle composition in 20 study areas in Europe

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

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Land Use Regression (LUR) models have been used to describe/model spatial variability of annual mean concentrations of traffic related pollutants like 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), sulphur (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 (R2) with a large variability between areas. Traffic variables were the dominant predictors, reflecting non-tailpipe 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.

Original language	English
Pages (from-to)	5778−5786
Number of pages	9
Journal	Environmental Science and Technology
Volume	47
Issue number	11
DOIs	https://doi.org/10.1021/es400156t
Publication status	Published - 2013

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de Hoogh, K., Wang, M., Adam, M., Badaloni, C., Beelen, R., Birk, M., Cesaroni, G., Cirach, M., Declercq, C., Dėdelė, A., Dons, E., de Nazelle, A., Eeftens, M., Eriksen, K. T., Eriksson, C., Fischer, P., Gražulevičienė, R., Gryparis, A., Hoffmann, B., ... Hoek, G. (2013). Development of land use regression models for particle composition in 20 study areas in Europe. Environmental Science and Technology, 47(11), 5778−5786. https://doi.org/10.1021/es400156t

@article{2468a3bdd8b445259ca4a2f495f19fc6,

title = "Development of land use regression models for particle composition in 20 study areas in Europe",

abstract = "Land Use Regression (LUR) models have been used to describe/model spatial variability of annual mean concentrations of traffic related pollutants like 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), sulphur (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 (R2) with a large variability between areas. Traffic variables were the dominant predictors, reflecting non-tailpipe 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.",

author = "{de Hoogh}, Kees and Meng Wang and Martin Adam and Chiara Badaloni and Rob Beelen and Matthias Birk and Giulia Cesaroni and Marta Cirach and Christophe Declercq and Audriaus Dėdelė and Evi Dons and {de Nazelle}, Audrey and Marloes Eeftens and Eriksen, {Kirsten Thorup} and Charlotta Eriksson and Paul Fischer and Regina Gra{\v z}ulevi{\v c}ienė and Alexandros Gryparis and Barbara Hoffmann and Michael Jerrett and Klea Katsouyanni and Minas Iakovides and Timo Lanki and Sarah Lindley and Christian Madsen and Anna M{\"o}lter and Gioia Mosler and Gizella N{\'a}dor and Nieuwenhuijsen, {Mark J.} and G{\"o}ran Pershagen and Annette Peters and Harish Phuleria and Nicole Probst-Hensch and Ole Raaschou-Nielsen and Ulrich Quass and Andrea Ranzi and Stephanou, {Euripides G.} and Dorothea Sugiri and Per Schwarze and Ming-Yi Tsai and Tarja Yli-Tuomi and Varr{\'o}, {Mih{\'a}ly J.} and Danielle Vienneau and Gudrun Weinmayr and Bert Brunekreef and Gerard Hoek",

year = "2013",

doi = "10.1021/es400156t",

language = "English",

volume = "47",

pages = "5778−5786",

journal = "Environmental Science and Technology",

issn = "0013-936X",

publisher = "American Chemical Society",

number = "11",

}

de Hoogh, K, Wang, M, Adam, M, Badaloni, C, Beelen, R, Birk, M, Cesaroni, G, Cirach, M, Declercq, C, Dėdelė, A, Dons, E, de Nazelle, A, Eeftens, M, Eriksen, KT, Eriksson, C, Fischer, P, Gražulevičienė, R, Gryparis, A, Hoffmann, B, Jerrett, M, Katsouyanni, K, Iakovides, M, Lanki, T, Lindley, S, Madsen, C, Mölter, A, Mosler, G, Nádor, G, Nieuwenhuijsen, MJ, Pershagen, G, Peters, A, Phuleria, H, Probst-Hensch, N, Raaschou-Nielsen, O, Quass, U, Ranzi, A, Stephanou, EG, Sugiri, D, Schwarze, P, Tsai, M-Y, Yli-Tuomi, T, Varró, MJ, Vienneau, D, Weinmayr, G, Brunekreef, B & Hoek, G 2013, 'Development of land use regression models for particle composition in 20 study areas in Europe', Environmental Science and Technology, vol. 47, no. 11, pp. 5778−5786. https://doi.org/10.1021/es400156t

TY - JOUR

T1 - Development of land use regression models for particle composition in 20 study areas in Europe

AU - de Hoogh, Kees

AU - Wang, Meng

AU - Adam, Martin

AU - Badaloni, Chiara

AU - Beelen, Rob

AU - Birk, Matthias

AU - Cesaroni, Giulia

AU - Cirach, Marta

AU - Declercq, Christophe

AU - Dėdelė, Audriaus

AU - Dons, Evi

AU - de Nazelle, Audrey

AU - Eeftens, Marloes

AU - Eriksen, Kirsten Thorup

AU - Eriksson, Charlotta

AU - Fischer, Paul

AU - Gražulevičienė, Regina

AU - Gryparis, Alexandros

AU - Hoffmann, Barbara

AU - Jerrett, Michael

AU - Katsouyanni, Klea

AU - Iakovides, Minas

AU - Lanki, Timo

AU - Lindley, Sarah

AU - Madsen, Christian

AU - Mölter, Anna

AU - Mosler, Gioia

AU - Nádor, Gizella

AU - Nieuwenhuijsen, Mark J.

AU - Pershagen, Göran

AU - Peters, Annette

AU - Phuleria, Harish

AU - Probst-Hensch, Nicole

AU - Raaschou-Nielsen, Ole

AU - Quass, Ulrich

AU - Ranzi, Andrea

AU - Stephanou, Euripides G.

AU - Sugiri, Dorothea

AU - Schwarze, Per

AU - Tsai, Ming-Yi

AU - Yli-Tuomi, Tarja

AU - Varró, Mihály J.

AU - Vienneau, Danielle

AU - Weinmayr, Gudrun

AU - Brunekreef, Bert

AU - Hoek, Gerard

PY - 2013

Y1 - 2013

N2 - Land Use Regression (LUR) models have been used to describe/model spatial variability of annual mean concentrations of traffic related pollutants like 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), sulphur (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 (R2) with a large variability between areas. Traffic variables were the dominant predictors, reflecting non-tailpipe 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.

AB - Land Use Regression (LUR) models have been used to describe/model spatial variability of annual mean concentrations of traffic related pollutants like 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), sulphur (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 (R2) with a large variability between areas. Traffic variables were the dominant predictors, reflecting non-tailpipe 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.

U2 - 10.1021/es400156t

DO - 10.1021/es400156t

M3 - Article

C2 - 23651082

SN - 0013-936X

VL - 47

SP - 5778−5786

JO - Environmental Science and Technology

JF - Environmental Science and Technology

IS - 11

ER -

Development of land use regression models for particle composition in 20 study areas in Europe

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