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Development of prediction models of chlorine bulk decay coefficient by rechlorination in water distribution network

상수도 공급과정 중 재염소 투입에 따른 잔류염소농도 수체감소계수 예측모델 개발

  • Jeong, Bobae (Department of Environmental Engineering, University of Seoul) ;
  • Kim, Kibum (Department of Environmental Engineering, University of Seoul) ;
  • Seo, Jeewon (Department of Environmental Engineering, University of Seoul) ;
  • Koo, Jayong (Department of Environmental Engineering, University of Seoul)
  • 정보배 (서울시립대학교 환경공학과) ;
  • 김기범 (서울시립대학교 환경공학과) ;
  • 서지원 (서울시립대학교 환경공학과) ;
  • 구자용 (서울시립대학교 환경공학과)
  • Received : 2018.11.16
  • Accepted : 2019.01.08
  • Published : 2019.02.15

Abstract

This study developed prediction models of chlorine bulk decay coefficient by each condition of water quality, measuring chlorine bulk decay coefficients of the water and water quality by water purification processes. The second-reaction order of chlorine were selected as the optimal reaction order of research area because the decay of chlorine was best represented. Chlorine bulk decay coefficients of the water in conventional processes, advanced processes before rechlorination was respectively $5.9072(mg/L)^{-1}d^{-1}$ and $3.3974(mg/L)^{-1}d^{-1}$, and $1.2522(mg/L)^{-1}d^{-1}$ and $1.1998(mg/L)^{-1}d^{-1}$ after rechlorination. As a result, the reduction of organic material concentration during the retention time has greatly changed the chlorine bulk decay coefficient. All the coefficients of determination were higher than 0.8 in the developed models of the chlorine bulk decay coefficient, considering the drawn chlorine bulk decay coefficient and several parameters of water quality and statistically significant. Thus, it was judged that models that could express the actual values, properly were developed. In the meantime, the chlorine bulk decay coefficient was in proportion to the initial residual chlorine concentration and the concentration of rechlorination; however, it may greatly vary depending on rechlorination. Thus, it is judged that it is necessary to set a plan for the management of residual chlorine concentration after experimentally assessing this change, utilizing the methodology proposed in this study in the actual fields. The prediction models in this study would simulate the reduction of residual chlorine concentration according to the conditions of the operation of water purification plants and the introduction of rechlorination facilities, more reasonably considering water purification process and the time of chlorination. In addition, utilizing the prediction models, the reduction of residual chlorine concentration in the supply areas can be predicted, and it is judged that this can be utilized in setting plans for the management of residual chlorine concentration.

Keywords

References

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