Department of Environmental Engineering Sciences, Engineering School of Sustainable Infrastructure & Environment (ESSIE), University of Florida, P.O. Box 116450, Gainesville, FL 32611-6450, USA.
Department of Environmental Engineering Sciences, Engineering School of Sustainable Infrastructure & Environment (ESSIE), University of Florida, P.O. Box 116450, Gainesville, FL 32611-6450, USA.
J Environ Manage. 2015 Feb 1;149:253-62. doi: 10.1016/j.jenvman.2014.10.014. Epub 2014 Nov 15.
There are over 100 models that have been developed for predicting trihalomethanes (THMs), haloacetic acids (HAAs), bromate, and unregulated disinfection byproducts (DBPs). Until now no publication has evaluated the variability of previous THM and HAA models using a common data set. In this article, the standard error (SE), Marquardt's percent standard deviation (MPSD), and linear coefficient of determination (R(2)) were used to analyze the variability of 87 models from 23 different publications. The most robust models were capable of predicting THM4 with an SE of 48 μg L(-1) and HAA6 with an SE of 15 μg L(-1), both achieving R(2) > 0.90. The majority of models were formulated for THM4. There is a lack of published models evaluating total HAAs, individual THM and HAA species, bromate, and unregulated DBPs.
已经开发出了超过 100 种模型来预测三卤甲烷（THMs）、卤乙酸（HAAs）、溴酸盐和未受管制的消毒副产物（DBPs）。到目前为止，还没有任何出版物使用通用数据集评估以前的 THM 和 HAA 模型的可变性。在本文中，标准误差（SE）、马夸特的百分标准偏差（MPSD）和线性确定系数（R（2））用于分析 23 种不同出版物中的 87 种模型的可变性。最稳健的模型能够以 48μg/L 的 SE 预测 THM4，以 15μg/L 的 SE 预测 HAA6，两者的 R（2）均大于 0.90。大多数模型都是为 THM4 制定的。缺乏评估总 HAAs、个别 THM 和 HAA 物种、溴酸盐和未受管制的 DBPs 的已发表模型。
