因为越来越需要平衡病原体控制和消毒副产品的健康风险 （DBP）在供水系统中，公用事业单位必须仔细检查并优化其消毒 实践。作者提供了一个简单的机械模型来预测总三卤甲烷（TTHM） 以及根据氯需求生成的九种卤乙酸（HAA9）的总和。为了评估这一点 通过建模方法，DBP中使用了八种密苏里地表水（原水和明矾处理） 形成和氯衰变动力学研究。采用平行一级反应模型对模型进行拟合 氯衰变数据和模型系数用于预测THM和HAA的形成。 通过拟合DBP动力学数据，获得了TTHMs和HAA9的产率系数。平均而言， 所有受试未经处理的地表水的TTHM和HAA9产量系数约为40 ug TTHM/mg 分别消耗Cl2和25微克HAA9/mg Cl2。在受到明矾凝结的水中 平均TTHM和HAA9产量系数分别为30 ug TTHM/mg Cl2和17 ug HAA9/mg Cl2 分别消费。本研究中引入的DBP预测模型提供了一个简单的， 通过关注氯需求来评估处理方案的可靠依据。这个模型可以 易于根据当地条件进行校准。包括23个参考文献、表格和图表。

Because of an increasing need to balance health risks for pathogen control and disinfection byproduct (DBP) formation in water supplies, utilities are forced to closely examine and optimize their disinfection practices. The authors provide a simple mechanistic model to predict total trihalomethane (TTHM) and the sum of nine haloacetic acids (HAA9) formation based on chlorine demand. To evaluate this modeling approach, eight Missouri surface waters (raw and alum-treated) were used in DBP formation and chlorine decay kinetic studies. A parallel first-order reaction model was used to fit the chlorine decay data, and the model coefficients were used to predict THM and HAA formation. Yield coefficients for TTHMs and HAA9 were obtained from fitting the DBP kinetic data. On average, the TTHM and HAA9 yield coefficients for all raw surface waters tested were about 40 ug TTHM/mg Cl2 and 25 ug HAA9/mg Cl2 consumed, respectively. In waters subjected to alum coagulation, the average TTHM and HAA9 yield coefficients were 30 ug TTHM/mg Cl2 and 17 ug HAA9/mg Cl2 consumed, respectively. The DBP predictive model introduced in this study provided a simple, reliable basis to evaluate treatment options by focusing on chlorine demand. This model can be readily calibrated to local conditions. Includes 23 references, tables, figures.