edoc

Spatial variation and land use regression modeling of the oxidative potential of fine particles

Yang, Aileen and Wang, Meng and Eeftens, Marloes and Beelen, Rob and Dons, Evi and Leseman, Daan L. A. C. and Brunekreef, Bert and Cassee, Flemming R. and Janssen, Nicole A. H. and Hoek, Gerard. (2015) Spatial variation and land use regression modeling of the oxidative potential of fine particles. Environmental Health Perspectives, 123 (11). pp. 1187-1192.

[img] PDF - Published Version
314Kb

Official URL: http://edoc.unibas.ch/42084/

Downloads: Statistics Overview

Abstract

Oxidative potential (OP) has been suggested to be a more health-relevant metric than particulate matter (PM) mass. Land use regression (LUR) models can estimate long-term exposure to air pollution in epidemiological studies, but few have been developed for OP.; We aimed to characterize the spatial contrasts of two OP methods and to develop and evaluate LUR models to assess long-term exposure to the OP of PM2.5.; Three 2-week PM2.5 samples were collected at 10 regional background, 12 urban background, and 18 street sites spread over the Netherlands/Belgium in 1 year and analyzed for OP using electron spin resonance (OP(ESR)) and dithiothreitol (OP(DTT)). LUR models were developed using temporally adjusted annual averages and a range of land-use and traffic-related GIS variables.; Street/urban background site ratio was 1.2 for OP(DTT) and 1.4 for OP(ESR), whereas regional/urban background ratio was 0.8 for both. OP(ESR) correlated moderately with OP(DTT) (R2 = 0.35). The LUR models included estimated regional background OP, local traffic, and large-scale urbanity with explained variance (R2) of 0.60 for OP(DTT) and 0.67 for OP(ESR). OP(DTT) and OP(ESR) model predictions were moderately correlated (R2 = 0.44). OP model predictions were moderately to highly correlated with predictions from a previously published PM2.5 model (R2 = 0.37-0.52), and highly correlated with predictions from previously published models of traffic components (R2 > 0.50).; LUR models explained a large fraction of the spatial variation of the two OP metrics. The moderate correlations among the predictions of OP(DTT), OP(ESR), and PM2.5 models offer the potential to investigate which metric is the strongest predictor of health effects.; Yang A, Wang M, Eeftens M, Beelen R, Dons E, Leseman DL, Brunekreef B, Cassee FR, Janssen NA, Hoek G. 2015. Spatial variation and land use regression modeling of the oxidative potential of fine particles. Environ Health Perspect 123:1187-1192; http://dx.doi.org/10.1289/ehp.1408916.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Former Units within Swiss TPH > Exposure Science (Tsai)
UniBasel Contributors:Eeftens, Marloes
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:National Institute of Environmental Health Sciences
ISSN:0091-6765
e-ISSN:1552-9924
Note:Publication type according to Uni Basel Research Database: Journal article -- Reproduced with permission from Environmental Health Perspectives
Language:English
Identification Number:
Last Modified:31 Aug 2017 08:57
Deposited On:21 Apr 2016 11:53

Repository Staff Only: item control page