Mathematical Advancement of General Chlorine Bulk Decay Model

作     者：Shaoying Qi Jinfeng Lu 

作者机构：Department of Civil & Environmental EngineeringUniversity of Illinois at Urbana-Champaign College of Environmental Science and EngineeringNankai University Key Laboratory of Pollution Processes and Environmental Criteria (Nankai University)Ministry of Education 

出 版 物：《Journal of Harbin Institute of Technology(New Series)》 (哈尔滨工业大学学报（英文版）)

年 卷 期：2017年第24卷第4期

页      面：9-17页

学科分类：08[工学] 0815[工学-水利工程] 

基　　金：Sponsored by the National Key Research and Development Program of China(Grant No.2016YFC0400707) National Science and Technology Major Project of the Ministry of Science and Technology of China(Grant No.2015ZX07203-007) National Natural Science Foundation of China(Grant No.31601834) Natural Science Foundation of Tianjin(Grant No.14JCYBJC22900) 

主　　题：chlorine residual potable water natural organic matter decay model 

摘      要：An accurate chlorine bulk decay model is needed to ensure that potable water meets the microbial and the chemical safeties at the treatment plant and throughout the distribution. Among the mathematical models available,the general second-order chlorine bulk decay model( GBDM) is the most fundamentally *** of the GBDM,however,has been hindered by its numerous fictive parameters and lack of an analytical solution. This theoretical work removes the two obstacles. The GBDM is solved through transformation and integration. The analytical solution provides deep insights into the GBDM and facilitates the parameterization and sensitivity analysis. The background natural organic matter( NOM) is characterized with the probabilistic distribution of functional groups. It reveals that the mean of the function group distribution is correlated with the initial chlorine decay rate coefficient( κ_0). A simple formula is developed to determine κ_0 directly from the initial chlorine decay. The theoretical treatment reduces the fictive parameters to a minimum. For the common lognormal distribution,the GBDM needs only three parameters,well defined as initial chlorine demand X_0,median rate coefficient km,and heterogeneity index σ. For more complicated scenarios,composite distributions are constructed through superposition of individual distributions. A highlighted example is to predict chlorine decay in blends of different waters. With the theoretical and mathematical advancement here,the GBDM can be applied effectively to any reactive background matter in any reaction systems.