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Development of land use regression models for PM2.5, PM2.5 absorbance, PM10 and PMcoarse in 20 European study areas : results of the ESCAPE project

Eeftens, M. and Beelen, R. and de Hoogh, K. and Bellander, T. and Cesaroni, G. and Cirach, M. and Declercq, C. and Dedele, A. and Dons, E. and de Nazelle, A. and Dimakopoulou, K. and Eriksen, K. T. and Falq, G. and Fischer, P. and Galassi, C. and Grazuleviciene, R. and Heinrich, J. and Hoffmann, B. and Jerrett, M. and Keidel, D. and Korek, M. and Lankki, T. and Lindley, S. and Madsen, C. and Molter, A. and Nador, G. and Nieuwenhuijsen, M. J. and Nonnemacher, M. and Pedeli, X. and Raaschou, Nielsen and Patelarou, E. and Quass, U. and Ranzi, A. and Schindler, C. and Stempfelet, M. and Stephanou, E. G. and Sugiri, D. and Tsai, M. and Yli-Tuomi, T. and Varro, M. J. and Vienneau, D. and von Klot, S. and Wolf, K. and Brunekreef, B. and Hoek, G.. (2012) Development of land use regression models for PM2.5, PM2.5 absorbance, PM10 and PMcoarse in 20 European study areas : results of the ESCAPE project. Environmental science & technology, Vol. 46, H. 20. pp. 11195-11205.

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Official URL: http://edoc.unibas.ch/dok/A6094128

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Abstract

ABSTRACT: Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM2.5, PM2.5 absorbance, PM10 and PMcoarse were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g. traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R2) was 71% for PM2.5 (range across study areas 35%-94%). Model R2 was higher for PM2.5 absorbance (median 89%, range 56-97%) and lower for PMcoarse (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R2 was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R2 results were on average 8-11% lower than model R2. Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Environmental Exposures and Health
UniBasel Contributors:Tsai, Ming and Schindler, Christian and Keidel, Dirk
Item Type:Article, refereed
Article Subtype:Research Article
Bibsysno:Link to catalogue
Publisher:American Chemical Soc.
ISSN:0013-936X
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:19 Jul 2013 07:44
Deposited On:19 Jul 2013 07:43

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