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Comparing land use regression and dispersion modelling to assess residential exposure to ambient air pollution for epidemiological studies
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
ID 2714325
Author(s) de Hoogh, Kees; Korek, Michal; Vienneau, Danielle; Keuken, Menno; Kukkonen, Jaakko; Nieuwenhuijsen, Mark J.; Badaloni, Chiara; Beelen, Rob; Bolignano, Andrea; Cesaroni, Giulia; Pradas, Marta Cirach; Cyrys, Josef; Douros, John; Eeftens, Marloes; Forastiere, Francesco; Forsberg, Bertil; Fuks, Kateryna; Gehring, Ulrike; Gryparis, Alexandros; Gulliver, John; Hansell, Anna L.; Hoffmann, Barbara; Johansson, Christer; Jonkers, Sander; Kangas, Leena; Katsouyanni, Klea; Künzli, Nino; Lanki, Timo; Memmesheimer, Michael; Moussiopoulos, Nicolas; Modig, Lars; Pershagen, Göran; Probst-Hensch, Nicole; Schindler, Christian; Schikowski, Tamara; Sugiri, Dorothee; Teixidó, Oriol; Tsai, Ming-Yi; Yli-Tuomi, Tarja; Brunekreef, Bert; Hoek, Gerard; Bellander, Tom
Author(s) at UniBasel Eeftens, Marloes
Künzli, Nino
Probst Hensch, Nicole
Schindler, Christian
Schikowski, Tamara
Tsai, Ming-Yi
Year 2014
Title Comparing land use regression and dispersion modelling to assess residential exposure to ambient air pollution for epidemiological studies
Journal Environment international : a journal of environmental science, risk and health
Volume 73
Pages / Article-Number 382-92
Keywords Land use regression, Dispersion modelling, Air pollution, Exposure, Cohort
Mesh terms Air Pollutants, analysis; Air Pollution; Environmental Exposure; Epidemiologic Studies; Female; Humans; Least-Squares Analysis; Models, Theoretical
Abstract Land-use regression (LUR) and dispersion models (DM) are commonly used for estimating individual air pollution exposure in population studies. Few comparisons have however been made of the performance of these methods.; Within the European Study of Cohorts for Air Pollution Effects (ESCAPE) we explored the differences between LUR and DM estimates for NO2, PM10 and PM2.5.; The ESCAPE study developed LUR models for outdoor air pollution levels based on a harmonised monitoring campaign. In thirteen ESCAPE study areas we further applied dispersion models. We compared LUR and DM estimates at the residential addresses of participants in 13 cohorts for NO2; 7 for PM10 and 4 for PM2.5. Additionally, we compared the DM estimates with measured concentrations at the 20-40 ESCAPE monitoring sites in each area.; The median Pearson R (range) correlation coefficients between LUR and DM estimates for the annual average concentrations of NO2, PM10 and PM2.5 were 0.75 (0.19-0.89), 0.39 (0.23-0.66) and 0.29 (0.22-0.81) for 112,971 (13 study areas), 69,591 (7) and 28,519 (4) addresses respectively. The median Pearson R correlation coefficients (range) between DM estimates and ESCAPE measurements were of 0.74 (0.09-0.86) for NO2; 0.58 (0.36-0.88) for PM10 and 0.58 (0.39-0.66) for PM2.5.; LUR and dispersion model estimates correlated on average well for NO2 but only moderately for PM10 and PM2.5, with large variability across areas. DM predicted a moderate to large proportion of the measured variation for NO2 but less for PM10 and PM2.5.
Publisher Elsevier
ISSN/ISBN 0160-4120
Full Text on edoc No
Digital Object Identifier DOI 10.1016/j.envint.2014.08.011
PubMed ID
ISI-Number WOS:000345540700043
Document type (ISI) Journal Article

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