BACKGROUND, AIM, AND SCOPE: This study developed an integrated approach to identify pollutant sources of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) of workers based on their blood contents. MATERIALS AND METHODS: We first measured blood PCDD/F contents of sinter plant workers and residents living near the plant. By comparing those blood indicatory PCDD/Fs found for residents with those for sinter plant workers, exposure-related blood indicatory PCDD/Fs were identified for each selected worker. We then measured PCDD/F concentrations of four different sinter plant workplaces and three different ambient environments of the background. By comparing those airborne indicatory PCDD/Fs found for ambient environments with those for sinter plant workplaces, exposure-related airborne indicatory PCDD/Fs for each workplace were obtained. Finally, by matching exposure-related blood indicatory PCDD/Fs with exposure-related airborne indicatory PCDD/Fs, all suspected pollutant sources were identified for each selected worker. RESULTS: Poor Pearson correlations were found between workers' blood contents and their corresponding PCDD/F exposures. Significant differences were found in the top three blood indicatory PCDD/Fs among the selected workers. By matching exposure-related blood indicatory PCDD/Fs with exposure-related airborne indicatory PCDD/Fs, two to three suspected pollutant sources were identified for each selected worker. DISCUSSION: The poor Pearson correlation found between workers' airborne PCDD/Fs exposures and their blood contents was because workers' blood PCDD/Fs contents were contributed not only by workers' occupational exposures, but also by other exposure sources and exposure routes. The difference in blood indicatory PCDD/Fs among the selected workers were obviously due to the intrinsic differences in their time/activity patterns in the involved workplaces. While workers used a dust respirator to perform their jobs, gas phase exposure-related airborne indicatory PCDD/Fs played an important role on identifying suspected pollutant sources. But if a dust respirator was not used, the gas + particle phase exposure-related airborne indicatory PCDD/Fs would become the key factor for identifying suspected pollutant sources. CONCLUSIONS: The developed integrated approach could identify all suspected pollutant sources effectively for selected workers based on their blood contents. The identified pollutant sources were theoretically plausible since they could be verified by examining workers' time/activity patterns, their status in using dust respirators, and the concentrations of PCDD/Fs found in the selected workplace atmospheres. RECOMMENDATIONS AND PERSPECTIVES: The developed technique can be used to identify possible pollutant sources not only for workers but also for many other exposure groups associated with various emission sources and exposure routes in the future.
BACKGROUND, AIM, AND SCOPE: This study developed an integrated approach to identify pollutant sources of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) of workers based on their blood contents. MATERIALS AND METHODS: We first measured blood PCDD/F contents of sinter plant workers and residents living near the plant. By comparing those blood indicatory PCDD/Fs found for residents with those for sinter plant workers, exposure-related blood indicatory PCDD/Fs were identified for each selected worker. We then measured PCDD/F concentrations of four different sinter plant workplaces and three different ambient environments of the background. By comparing those airborne indicatory PCDD/Fs found for ambient environments with those for sinter plant workplaces, exposure-related airborne indicatory PCDD/Fs for each workplace were obtained. Finally, by matching exposure-related blood indicatory PCDD/Fs with exposure-related airborne indicatory PCDD/Fs, all suspected pollutant sources were identified for each selected worker. RESULTS: Poor Pearson correlations were found between workers' blood contents and their corresponding PCDD/F exposures. Significant differences were found in the top three blood indicatory PCDD/Fs among the selected workers. By matching exposure-related blood indicatory PCDD/Fs with exposure-related airborne indicatory PCDD/Fs, two to three suspected pollutant sources were identified for each selected worker. DISCUSSION: The poor Pearson correlation found between workers' airborne PCDD/Fs exposures and their blood contents was because workers' blood PCDD/Fs contents were contributed not only by workers' occupational exposures, but also by other exposure sources and exposure routes. The difference in blood indicatory PCDD/Fs among the selected workers were obviously due to the intrinsic differences in their time/activity patterns in the involved workplaces. While workers used a dust respirator to perform their jobs, gas phase exposure-related airborne indicatory PCDD/Fs played an important role on identifying suspected pollutant sources. But if a dust respirator was not used, the gas + particle phase exposure-related airborne indicatory PCDD/Fs would become the key factor for identifying suspected pollutant sources. CONCLUSIONS: The developed integrated approach could identify all suspected pollutant sources effectively for selected workers based on their blood contents. The identified pollutant sources were theoretically plausible since they could be verified by examining workers' time/activity patterns, their status in using dust respirators, and the concentrations of PCDD/Fs found in the selected workplace atmospheres. RECOMMENDATIONS AND PERSPECTIVES: The developed technique can be used to identify possible pollutant sources not only for workers but also for many other exposure groups associated with various emission sources and exposure routes in the future.