UNSW Water Research Centre, School of Civil & Environmental Engineering, University of New South Wales, NSW 2052, Australia.
School of Mathematics & Statistics, University of New South Wales, NSW 2052, Australia.
Water Res. 2017 Feb 1;109:144-154. doi: 10.1016/j.watres.2016.11.008. Epub 2016 Nov 3.
Chlorine disinfection of biologically treated wastewater is practiced in many locations prior to environmental discharge or beneficial reuse. The effectiveness of chlorine disinfection processes may be influenced by several factors, such as pH, temperature, ionic strength, organic carbon concentration, and suspended solids. We investigated the use of Bayesian multilayer perceptron (BMLP) models as efficient and practical tools for compiling and analysing free chlorine and monochloramine virus disinfection performance as a multivariate problem. Corresponding to their relative susceptibility, Adenovirus 2 was used to assess disinfection by monochloramine and Coxsackievirus B5 was used for free chlorine. A BMLP model was constructed to relate key disinfection conditions (CT, pH, turbidity) to observed Log Reduction Values (LRVs) for these viruses at constant temperature. The models proved to be valuable for incorporating uncertainty in the chlor(am)ination performance estimation and interpolating between operating conditions. Various types of queries could be performed with this model including the identification of target CT for a particular combination of LRV, pH and turbidity. Similarly, it was possible to derive achievable LRVs for combinations of CT, pH and turbidity. These queries yielded probability density functions for the target variable reflecting the uncertainty in the model parameters and variability of the input variables. The disinfection efficacy was greatly impacted by pH and to a lesser extent by turbidity for both types of disinfections. Non-linear relationships were observed between pH and target CT, and turbidity and target CT, with compound effects on target CT also evidenced. This work demonstrated that the use of BMLP models had considerable ability to improve the resolution and understanding of the multivariate relationships between operational parameters and disinfection outcomes for wastewater treatment.
在环境排放或有益再利用之前,许多地方都采用生物处理废水的氯消毒法。氯消毒过程的有效性可能受到多种因素的影响,例如 pH 值、温度、离子强度、有机碳浓度和悬浮固体。我们研究了使用贝叶斯多层感知器(BMLP)模型作为有效和实用的工具,用于编译和分析游离氯和单氯胺病毒消毒性能作为一个多变量问题。根据相对易感性,使用腺病毒 2 评估单氯胺的消毒效果,使用柯萨奇病毒 B5 评估游离氯的消毒效果。构建了一个 BMLP 模型,以将关键消毒条件(CT、pH 值、浊度)与这些病毒在恒定温度下的观察对数减少值(LRV)相关联。事实证明,这些模型对于在氯(氨)化性能估计中纳入不确定性以及在操作条件之间进行插值非常有价值。可以使用该模型执行各种类型的查询,包括确定特定 LRV、pH 值和浊度组合的目标 CT。同样,可以为 CT、pH 值和浊度的组合得出可实现的 LRV。这些查询为目标变量生成了概率密度函数,反映了模型参数的不确定性和输入变量的可变性。对于这两种消毒类型,消毒效果都受到 pH 值的极大影响,其次是浊度。在 pH 值和目标 CT 之间以及浊度和目标 CT 之间观察到非线性关系,并且还证明了对目标 CT 的复合效应。这项工作表明,使用 BMLP 模型具有相当大的能力来提高对操作参数和废水处理消毒效果之间多变量关系的分辨率和理解。