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Land use regression models for ultrafine particles in six european areas

van Nunen, Erik and Vermeulen, Roel and Tsai, Ming-Yi and Probst-Hensch, Nicole and Ineichen, Alex and Davey, Mark and Imboden, Medea and Ducret-Stich, Regina and Naccarati, Alessio and Raffaele, Daniela and Ranzi, Andrea and Ivaldi, Cristiana and Galassi, Claudia and Nieuwenhuijsen, Mark and Curto, Ariadna and Donaire-Gonzalez, David and Cirach, Marta and Chatzi, Leda and Kampouri, Mariza and Vlaanderen, Jelle and Meliefste, Kees and Buijtenhuijs, Daan and Brunekreef, Bert and Morley, David and Vineis, Paolo and Gulliver, John and Hoek, Gerard. (2017) Land use regression models for ultrafine particles in six european areas. Environmental Science and Technology, 51 (6). pp. 3336-3345.

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Official URL: http://edoc.unibas.ch/55446/

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Abstract

Long-term ultrafine particle (UFP) exposure estimates at a fine spatial scale are needed for epidemiological studies. Land use regression (LUR) models were developed and evaluated for six European areas based on repeated 30 min monitoring following standardized protocols. In each area; Basel (Switzerland), Heraklion (Greece), Amsterdam, Maastricht, and Utrecht ("The Netherlands"), Norwich (United Kingdom), Sabadell (Spain), and Turin (Italy), 160-240 sites were monitored to develop LUR models by supervised stepwise selection of GIS predictors. For each area and all areas combined, 10 models were developed in stratified random selections of 90% of sites. UFP prediction robustness was evaluated with the intraclass correlation coefficient (ICC) at 31-50 external sites per area. Models from Basel and The Netherlands were validated against repeated 24 h outdoor measurements. Structure and model R(2) of local models were similar within, but varied between areas (e.g., 38-43% Turin; 25-31% Sabadell). Robustness of predictions within areas was high (ICC 0.73-0.98). External validation R(2) was 53% in Basel and 50% in The Netherlands. Combined area models were robust (ICC 0.93-1.00) and explained UFP variation almost equally well as local models. In conclusion, robust UFP LUR models could be developed on short-term monitoring, explaining around 50% of spatial variance in longer-term measurements.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Chronic Disease Epidemiology > Genetic Epidemiology of Non-Communicable Diseases (Probst-Hensch)
03 Faculty of Medicine > Departement Public Health > Sozial- und Präventivmedizin > Genetic Epidemiology of Non-Communicable Diseases (Probst-Hensch)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH)
UniBasel Contributors:Probst Hensch, Nicole and Tsai, Ming and Ineichen, Alex and Imboden, Medea and Ducret-Stich, Regina
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:American Chemical Society
ISSN:0013-936X
e-ISSN:1520-5851
Note:Publication type according to Uni Basel Research Database: Journal article
Identification Number:
Last Modified:09 Oct 2017 07:42
Deposited On:09 Oct 2017 07:42

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