Dataset Information

Spatial Variation and Land Use Regression Modeling of the Oxidative Potential of Fine Particles.

ABSTRACT:

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 PM2.5.

Methods

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.

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) (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).

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 PM2.5 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.

SUBMITTER: Yang A

PROVIDER: S-EPMC4629740 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Publications

Spatial Variation and Land Use Regression Modeling of the Oxidative Potential of Fine Particles.

Yang Aileen A Wang Meng M Eeftens Marloes M Beelen Rob R Dons Evi E Leseman Daan L A C DL Brunekreef Bert B Cassee Flemming R FR Janssen Nicole A H NA Hoek Gerard G

Environmental health perspectives 20150403 11

<h4>Background</h4>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.<h4>Objectives</h4>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.<h4>Methods</h4>Three 2-week PM2.5 samples were co ...[more]

PMID: 25840153

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Dataset Information

Spatial Variation and Land Use Regression Modeling of the Oxidative Potential of Fine Particles.

Background

Objectives

Methods

Results

Conclusion

Citation

Publications

Spatial Variation and Land Use Regression Modeling of the Oxidative Potential of Fine Particles.

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