title: Kriged and modeled ambient air levels of benzene in an urban environment: an exposure assessment study.
abstract: BACKGROUND
  There is increasing concern regarding the potential adverse health effects of air pollution, particularly hazardous air pollutants (HAPs). However, quantifying exposure to these pollutants is problematic.
  
  
  OBJECTIVE
  Our goal was to explore the utility of kriging, a spatial interpolation method, for exposure assessment in epidemiologic studies of HAPs. We used benzene as an example and compared census tract-level kriged predictions to estimates obtained from the 1999 U.S. EPA National Air Toxics Assessment (NATA), Assessment System for Population Exposure Nationwide (ASPEN) model.
  
  
  METHODS
  Kriged predictions were generated for 649 census tracts in Harris County, Texas using estimates of annual benzene air concentrations from 17 monitoring sites operating in Harris and surrounding counties from 1998 to 2000. Year 1999 ASPEN modeled estimates were also obtained for each census tract. Spearman rank correlation analyses were performed on the modeled and kriged benzene levels. Weighted kappa statistics were computed to assess agreement between discretized kriged and modeled estimates of ambient air levels of benzene.
  
  
  RESULTS
  There was modest correlation between the predicted and modeled values across census tracts. Overall, 56.2%, 40.7%, 31.5% and 28.2% of census tracts were classified as having 'low', 'medium-low', 'medium-high' and 'high' ambient air levels of benzene, respectively, comparing predicted and modeled benzene levels. The weighted kappa statistic was 0.26 (95% confidence interval (CI) = 0.20, 0.31), indicating poor agreement between the two methods.
  
  
  CONCLUSIONS
  There was a lack of concordance between predicted and modeled ambient air levels of benzene. Applying methods of spatial interpolation for assessing exposure to ambient air pollutants in health effect studies is hindered by the placement and number of existing stationary monitors collecting HAP data. Routine monitoring needs to be expanded if we are to use these data to better assess environmental health risks in the future.
authors.affiliation: Division of Epidemiology and Disease Control, University of Texas School of Public Health, Houston, TX 77030, USA.
authors.forename: Kristina W
authors.initials: KW
authors.lastname: Whitworth
authors.forename: Elaine
authors.initials: E
authors.lastname: Symanski
authors.forename: Dejian
authors.initials: D
authors.lastname: Lai
authors.forename: Ann L
authors.initials: AL
authors.lastname: Coker
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D001554:Benzene / Q000032:analysis*; D003627:Data Interpretation, Statistical; D004784:Environmental Monitoring / Q000379:methods*; D062665:Epidemiological Monitoring; D015386:Hazardous Substances / Q000032:analysis; D008956:Models, Chemical; D018709:Statistics, Nonparametric; D013781:Texas / Q000453:epidemiology
chemical_list: D000393:Air Pollutants; D015386:Hazardous Substances; D001554:Benzene