Abstract
BackgroundThere 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.ObjectiveOur 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.MethodsKriged 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.ResultsThere 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.ConclusionsThere 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.
Highlights
There is increasing concern regarding the potential adverse health effects of air pollution, hazardous air pollutants (HAPs)
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
In 1971, the Clean Air Act was established under which National Ambient Air Quality Standards (NAAQS) were created to regulate ambient air concentrations of these six criteria pollutants [1]
Summary
There is increasing concern regarding the potential adverse health effects of air pollution, hazardous air pollutants (HAPs). There has been concern regarding the potential adverse human health effects of ozone, sulfur dioxide, nitrogen oxides, carbon monoxide, particulates, and lead. The potential for human exposure to benzene is well established, but quantifying exposure for populationbased epidemiologic studies is problematic and requires immense resources. For this reason, researchers studying the health effects of ambient air levels of benzene often rely on proxy measures of exposure. Previous studies that have used kriging to map air pollution levels include: sulfur dioxide in Instanbul, Turkey [5], ozone in Atlanta [6,7] and northern Georgia [8], and particulates across the entire U.S [9] and in Beijing, China [10]. Kriging has been used in a range of epidemiologic studies of criteria pollutants to examine exposures to NO2 among pregnant women in Spain [11] as well as associations between: particulates and ozone and mortality in Los Angeles [12], particulates and mortality in Hamilton, Ontario, Canada [13], particulates and ectopy in the U.S [9], CO, NO2, CO2 and preterm birth in Korea [14], ozone and pediatric asthma exacerbation in Atlanta [6], and particulates and low birth weight in Korea [15]
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