| Summary: | 碩士 === 輔仁大學 === 公共衛生學系碩士班 === 96 === Epidemiological studies have suggested that particulate air pollution was an importance factor for respiratory diseases, where stationary ambient monitoring data were used to estimate the concentrations for individual’s residence area. In fact, personal exposures to air pollutants might differ from corresponding outdoor concentrations due to personal activities and home characteristics.The object of this study was to investigate the correlation between ambien concentrations and personal exposures to particulate air pollutions.
The study measured personal and ambient particle levels for college students in Taichung metropolitan area by using two personal multipollutant samplers (ChemPass® Personal Sampling System), monitoring for five consecutive days. Additionally, information of personal time-activity diary and housing diary was collected to identify personal pollution sources during the sampling period. From January 3, 2007 to March 9, 2007, 7 college students were recruited to participate the study. After excluding the samples with problems, a total of 29 sampling days were counted in the final analysis.
Results showed that subjects spent most of their time at bedroom (71.6%). The second most common microenvironment was non-residential indoor environment (21.3%). The least percentage of all-day activities happened at home, but not in bedroom (1.5%), and inside vehicles (0.9%).The mean ambient and personal PM10 concentrations were 82.80 (± 31.71) μg/m3and 72.38 (±21.74) μg/m3, PM2.5-10 were 20.31 (± 11.83) μg/m3 and 15.91(± 10.86) μg/m3, PM2.5 were 64.04 (± 28.02) μg/m3 and 56.47 (± 20.74) μg/m3, particulate sulfate were 10.19 (± 4.34) μg/m3 and 9.00 (± 3.86) μg/m3, particulate nitrate were 6.37 (± 4.88) μg/m3 and 4.36 (± 3.03 ) μg/m3, respectively. Results found that personal exposures were generally lower than ambient for PM10, PM2.5-10, PM2.5, particulate sulfate and particulate nitrate.
The Spearman’s correlation coefficients between ambient and personal exposures nitrate were the strongest for particulate (rs =0.925, p<0.01), followed by PM2.5 (0.923, p<0.01), particulate sulfate (0.799, p<0.01), and PM10 (0.758, p<0.01). The correlation between personal PM2.5-10 exposures and corresponding ambient concentrations were the weakest. Finally, showed data analysis that personal particulate nitrate and PM2.5 exposures were significantly influenced by ambient concentrations, while personal PM2.5-10 exposures were influenced by specific activities. Match with time-activity diary analysis, personal PM10, PM2.5, PM nitrate and PM sulfate exposures were influenced by ambient concentration for college students in Taichung metropolitan area.
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