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Development of Predictive Model for Annual Mean Radon Concentration for Assessment of Annual Effective dose of Radon Exposure

라돈 노출 유효선량 평가를 위한 연간 평균 라돈 농도 예측모델 개발

  • Lee, Cheolmin (Department of Chemical & Biological Engineering, Seokyeong University) ;
  • Kang, Daeyong (Department of Humanities and Social Medicine, Ajou University School of Medicine) ;
  • Koh, Sangbaek (Department of Preventive Medicine, Wonju College of Medicine, Yonsei University) ;
  • Cho, Yongseog (Korea Radon Association) ;
  • Lee, Dajeong (Korea Radon Association) ;
  • Lee, Sulbee (Korea Radon Association)
  • 이철민 (서경대학교 화학생명공학과) ;
  • 강대용 (아주대학교 의과대학 인문사회의학교실) ;
  • 고상백 (연세대학교 원주의과대학 예방의학교실) ;
  • 조용석 (한국 라돈 협회) ;
  • 이다정 (한국 라돈 협회) ;
  • 이슬비 (한국 라돈 협회)
  • Received : 2016.05.23
  • Accepted : 2016.08.09
  • Published : 2016.08.31

Abstract

This research, sponsored by the Korean Ministry of Environment in 2014, was the first epidemiological study in Korea that investigated the health impact assessment of radon exposure. Its purpose was to construct a model that calculated the annual mean cumulative radon exposure concentrations, so that reliable conclusions could be drawn from environment-control group research. Radon causes chronic lung cancer. Therefore, the long-term measurement of radon exposure concentration, over one year, is needed in order to develop a health impact assessment for radon. Hence, based on the seasonal correction model suggested by Pinel et al.(1995), a predictive model of annual mean radon concentration was developed using the year-long seasonal measurement data from the National Institute of Environmental Research, the Korea Institute of Nuclear Safety, the Hanyang University Outdoor Radon Concentration Observatory, and the results from a 3-month (one season) survey, which is the official test method for radon measurement designated by the Korean Ministry of Environment. In addition, a model for evaluating the effective annual dose for radon was developed, using dosimetric methods. The model took into account the predictive model for annual mean radon concentrations and the activity characteristics of the residents.

Keywords

References

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