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Land use regression models for ultrafine particles in six european areas
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 3848417
Author(s) van Nunen, Erik; Vermeulen, Roel; Tsai, Ming-Yi; Probst-Hensch, Nicole; Ineichen, Alex; Davey, Mark; Imboden, Medea; Ducret-Stich, Regina; Naccarati, Alessio; Raffaele, Daniela; Ranzi, Andrea; Ivaldi, Cristiana; Galassi, Claudia; Nieuwenhuijsen, Mark; Curto, Ariadna; Donaire-Gonzalez, David; Cirach, Marta; Chatzi, Leda; Kampouri, Mariza; Vlaanderen, Jelle; Meliefste, Kees; Buijtenhuijs, Daan; Brunekreef, Bert; Morley, David; Vineis, Paolo; Gulliver, John; Hoek, Gerard
Author(s) at UniBasel Probst Hensch, Nicole
Tsai, Ming-Yi
Ineichen, Alex
Imboden, Medea
Ducret-Stich, Regina
Year 2017
Title Land use regression models for ultrafine particles in six european areas
Journal Environmental Science and Technology
Volume 51
Number 6
Pages / Article-Number 3336-3345
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.
Publisher American Chemical Society
ISSN/ISBN 0013-936X ; 1520-5851
edoc-URL http://edoc.unibas.ch/55446/
Full Text on edoc No
Digital Object Identifier DOI 10.1021/acs.est.6b05920
PubMed ID http://www.ncbi.nlm.nih.gov/pubmed/28244744
ISI-Number WOS:000397477900025
Document type (ISI) Journal Article
 
   

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29/03/2024