노출평가 방법론에 대한 과거와 현재, 그리고 미래
Review of Exposure Assessment Methodology for Future Directions
1
조회
0
다운로드
2
인용
0
참고문헌
키워드
초록
Public interest has been increasing the focus on the management of exposure to pollutants and the related health effects. This study reviewed exposure assessment methodologies and addressed future directions. Exposure can be assessed by direct (exposure monitoring) or indirect approaches (exposure modelling). Exposure modelling is a cost-effective tool to assess exposure among individuals, but direct personal monitoring provides more accurate exposure data. There are several population exposure models: stochastic human exposure and dose simulation (SHEDS), air pollutants exposure (APEX), and air pollution exposure distributions within adult urban population in Europe (EXPOLIS). A South Korean population exposure model is needed since the resolution of ambient concentrations and time-activity patterns are country specific. Population exposure models could be useful to find the association between exposure to pollutants and adverse health effects in epidemiologic studies. With the advancement of sensor technology and the internet of things (IoT), exposure assessment could be applied in a real-time surveillance system. In the future, environmental health services will be useful to protect and promote human health from exposure to pollutants.
Abstract
Public interest has been increasing the focus on the management of exposure to pollutants and the related health effects. This study reviewed exposure assessment methodologies and addressed future directions. Exposure can be assessed by direct (exposure monitoring) or indirect approaches (exposure modelling). Exposure modelling is a cost-effective tool to assess exposure among individuals, but direct personal monitoring provides more accurate exposure data. There are several population exposure models: stochastic human exposure and dose simulation (SHEDS), air pollutants exposure (APEX), and air pollution exposure distributions within adult urban population in Europe (EXPOLIS). A South Korean population exposure model is needed since the resolution of ambient concentrations and time-activity patterns are country specific. Population exposure models could be useful to find the association between exposure to pollutants and adverse health effects in epidemiologic studies. With the advancement of sensor technology and the internet of things (IoT), exposure assessment could be applied in a real-time surveillance system. In the future, environmental health services will be useful to protect and promote human health from exposure to pollutants.
참고문헌 (28)
- Lioy PJ, "Assessing total human exposure to contaminants. A multidisciplinary approach", Environ Sci Technol, 24(7), pp.938~945 (1990)
- Nieuwenhuijsen M, "New developments in exposure assessment: the impact on the practice of health risk assessment and epidemiological studies", Environ Int, 32(8), pp.996~1009 (2006)
- "Quality Assurance Air Monitoring Site Search"[URL]
- "AirKorea"[URL]
- Burke JM, "A population exposure model for particulate matter: case study results for PM(2.5) in Philadelphia, PA", J Expo Anal Environ Epidemiol, 11(6), pp.470~489 (2001)
- Klepeis NE, "The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants", J Expo Anal Environ Epidemiol, 11(3), pp.231~252 (2001)
- 이현수, "직장인의 시간활동 양상 평가", 한국산업보건학회지, 20(2), pp.102~110 (2010), 한국산업보건학회
- Yang W, "Determinants of residential indoor and transportation activity times in Korea", J Expo Sci Environ Epidemiol, 21(3), pp.310~316 (2011)
- 양원호, "한국인의 평일 및 주말의 국소환경 시간활동 양상", 한국실내환경학회지, 6(4), pp.267~274 (2009), 한국실내환경학회
- 황윤형, "평일 시간활동패턴을 활용한 도시 인구의 유사노출집단 분류", 한국환경보건학회지, 42(6), pp.353~364 (2016), 한국환경보건학회
- Lee S, "Seasonal differences in determinants of time location patterns in an urban population: a large population-based study in Korea", Int J Environ Res Public Health, 14(7), pp.672~ (2017)
- 류현수, "한국 학생들의 시간활동 양상 평가", 한국환경보건학회지, 44(2), pp.143~152 (2018), 한국환경보건학회
- Lim S, "Personal exposures to PM2.5 and their relationships with microenvironmental concentrations", Atmos Environ, 47, pp.407~412 (2012)
- Hwang Y, "Contribution of microenvironments to personal exposures to PM10 and PM2.5 in summer and winter", Atmos Environ, 175, pp.192~198 (2018)
- Guak S, "A model for population exposure to PM2.5: identification of determinants for high population exposure in Seoul", Environ Pollut, 285, pp.117406~ (2021)
- LangstaffJE, "Health and Environmental Impacts Division" (2017), U.S. Environmental Protection Agency
- Johnson TR, "A multipollutant evaluation of APEX using microenvironmental ozone, carbon monoxide, and particulate matter (PM2.5) concentrations measured in Los Angeles by the exposure classification project", Cogent Environ Sci, 4, pp.1453022~ (2018)
- Kruize H, "Description and demonstration of the EXPOLIS simulation model: two examples of modeling population exposure to particulate matter", J Expo Anal Environ Epidemiol, 13(2), pp.87~99 (2003)
- Hänninen O, "EXPOLIS simulation model: PM2.5 application and comparison with measurements in Helsinki", J Expo Anal Environ Epidemiol, 13(1), pp.74~85 (2003)
- Valari M, "EXPLUME v1.0: a model for personal exposure to ambient O3 and PM2.5", Geosci Model Dev, 13, pp.1075~1094 (2020)
- 김윤지, "센서를 이용한 이산화탄소와 미세먼지의 장기간 시간적인 변이를 활용한 어린이집의 실내환경수준 평가", 한국환경보건학회지, 43(4), pp.267~272 (2017), 한국환경보건학회
- Guak S, "Prediction models using outdoor environmental data for real-time PM10 concentrations in daycare centers, kindergartens, and elementary schools", Build Environ, 187, pp.107371~ (2021)
- Kim T, "A new analytical method for the classification of time-location data obtained from the global positioning system (GPS)", J Environ Monit, 14(8), pp.2270~2274 (2012)
- Zhao Y, "Fine particulate matter exposure and renal function: a populationbased study among pregnant women in China", Environ Int, 141, pp.105805~ (2020)
- Lim CC, "Mapping urban air quality using mobile sampling with low-cost sensors and machine learning in Seoul", South Korea. Environ Int, 131, pp.105022~ (2019)
- Wu TG, "Identifying low-PM2.5 exposure commuting routes for cyclists through modeling with the random forest algorithm based on lowcost sensor measurements in three Asian cities", Environ Pollut, 294, pp.118597~ (2022)
- 김기철, "실내 환경 정보와 재실자의 반응", 대한건축학회논문집, 29(07), pp.229~237 (2013), 대한건축학회
- National Institute of Environmental Research, "Planning of Environmental Health 100+ Services" (2013), National Institute of Environmental Research