Background: 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.

Objectives: 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 PM_2.5.

Methods: Three 2-week PM_2.5 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.

Results: 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 ( R ² = 0.35). The LUR models included estimated regional background OP, local traffic, and large-scale urbanity with explained variance ( R ²) of 0.60 for OP^DTT and 0.67 for OP^ESR. OP^DTT and OP^ESR model predictions were moderately correlated ( R ² = 0.44). OP model predictions were moderately to highly correlated with predictions from a previously published PM_2.5 model ( R ² = 0.37–0.52), and highly correlated with predictions from previously published models of traffic components ( R ² > 0.50).

Conclusion: 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 PM_2.5 models offer the potential to investigate which metric is the strongest predictor of health effects.

Citation: 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

Address correspondence to A. Yang, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, the Netherlands. Telephone: 31 30 274 3316. E-mail: Aileen.Yang@rivm.nl

We thank K. Meliefste, who was involved in the monitoring campaign.

This study was funded by the RIVM Strategic Research Program (SOR).

The authors declare they have no actual or potential competing financial interests.

Received: 3 July 2014 Accepted: 31 March 2015 Advance Publication: 3 April 2015 Final Publication: 1 November 2015

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