title: 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.
  
  
  OBJECTIVE
  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).
  
  
  CONCLUSIONS
  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.
  
  
  BACKGROUND
  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.
authors.affiliation: National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
authors.forename: Aileen
authors.initials: A
authors.lastname: Yang
authors.forename: Meng
authors.initials: M
authors.lastname: Wang
authors.forename: Marloes
authors.initials: M
authors.lastname: Eeftens
authors.forename: Rob
authors.initials: R
authors.lastname: Beelen
authors.forename: Evi
authors.initials: E
authors.lastname: Dons
authors.forename: Daan L A C
authors.initials: DL
authors.lastname: Leseman
authors.forename: Bert
authors.initials: B
authors.lastname: Brunekreef
authors.forename: Flemming R
authors.initials: FR
authors.lastname: Cassee
authors.forename: Nicole A H
authors.initials: NA
authors.lastname: Janssen
authors.forename: Gerard
authors.initials: G
authors.lastname: Hoek
mesh_terms: D000393:Air Pollutants / Q000032:analysis; D000397:Air Pollution / Q000032:analysis*; D001530:Belgium; D002947:Cities; D004229:Dithiothreitol / Q000032:analysis*; D004578:Electron Spin Resonance Spectroscopy; D004784:Environmental Monitoring / Q000379:methods*; D040362:Geographic Information Systems; D009426:Netherlands; D010084:Oxidation-Reduction; D052638:Particulate Matter / Q000032:analysis* / Q000737:chemistry*; D012044:Regression Analysis; D001335:Vehicle Emissions / Q000032:analysis
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter; D001335:Vehicle Emissions; D004229:Dithiothreitol
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