국소환경 모델을 이용한 초미세먼지(PM2.5) 노출 기여율 평가
Evaluation of PM2.5 Exposure Contribution Using a Microenvironmental Model
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Background: Since people move through microenvironments rather than staying in one place, they may be exposed to both indoor and outdoor PM2.5 concentrations. Objectives: The aim of this study was to assess the exposure level of each sub-population group and evaluate the contribution rate of the major microenvironments. Methods: Exposure scenarios for sub-population groups were constructed on the basis of a 2019 Time-Use survey and the previous literature. A total of five population groups were classified and researchers wearing MicroPEM simulated monitoring PM2.5 exposure concentrations in real-time over three days. The exposure contribution for each microenvironment were evaluated by multiplying the inhalation rate and the PM2.5 exposure concentration levels. Results: Mean PM2.5 concentrations were 33.0 µg/m3 and 22.5 µg/m3 in Guro-gu and Wonju, respectively. When the exposure was calculated considering each inhalation rate and concentration, the home showed the highest exposure contribution rate for PM2.5. As for preschool children, it was 90.8% in Guro-gu, 94.1% in Wonju. For students it was 65.3% and 67.3%. For housewives it was 98.2% and 95.8%, and 59.5% and 91.7% for office workers. Both regions had higher exposure to PM2.5 among the elderly compared to other populations, and their PM2.5 exposure contribution rates were 98.3% and 94.1% at home for Guro-gu and Wonju, respectively. Conclusions: The exposure contribution rate could be dependent on time spent in microenvironments. Notably, the contribution rate of exposure to PM2.5 at home was the highest because most people spend the longest time at home. Therefore, microenvironments such as home with a higher contribution rate of exposure to PM2.5 could be managed to upgrade public health.
Abstract
Background: Since people move through microenvironments rather than staying in one place, they may be exposed to both indoor and outdoor PM2.5 concentrations. Objectives: The aim of this study was to assess the exposure level of each sub-population group and evaluate the contribution rate of the major microenvironments. Methods: Exposure scenarios for sub-population groups were constructed on the basis of a 2019 Time-Use survey and the previous literature. A total of five population groups were classified and researchers wearing MicroPEM simulated monitoring PM2.5 exposure concentrations in real-time over three days. The exposure contribution for each microenvironment were evaluated by multiplying the inhalation rate and the PM2.5 exposure concentration levels. Results: Mean PM2.5 concentrations were 33.0 µg/m3 and 22.5 µg/m3 in Guro-gu and Wonju, respectively. When the exposure was calculated considering each inhalation rate and concentration, the home showed the highest exposure contribution rate for PM2.5. As for preschool children, it was 90.8% in Guro-gu, 94.1% in Wonju. For students it was 65.3% and 67.3%. For housewives it was 98.2% and 95.8%, and 59.5% and 91.7% for office workers. Both regions had higher exposure to PM2.5 among the elderly compared to other populations, and their PM2.5 exposure contribution rates were 98.3% and 94.1% at home for Guro-gu and Wonju, respectively. Conclusions: The exposure contribution rate could be dependent on time spent in microenvironments. Notably, the contribution rate of exposure to PM2.5 at home was the highest because most people spend the longest time at home. Therefore, microenvironments such as home with a higher contribution rate of exposure to PM2.5 could be managed to upgrade public health.
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