Department of Geography and Environmental Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA.
Environ Sci Technol. 2010 Feb 15;44(4):1232-9. doi: 10.1021/es9028606.
Statistical models are developed for bromine incorporation in the trihalomethane (THM), trihaloacetic acids (THAA), dihaloacetic acid (DHAA), and dihaloacetonitrile (DHAN) subclasses of disinfection byproducts (DBPs) using distribution system samples from plants applying only free chlorine as a primary or residual disinfectant in the Information Collection Rule (ICR) database. The objective of this study is to characterize the effect of water quality conditions before, during, and post-treatment on distribution system bromine incorporation into DBP mixtures. Bayesian Markov Chain Monte Carlo (MCMC) methods are used to model individual DBP concentrations and estimate the coefficients of the linear models used to predict the bromine incorporation fraction for distribution system DBP mixtures in each of the four priority DBP classes. The bromine incorporation models achieve good agreement with the data. The most important predictors of bromine incorporation fraction across DBP classes are alkalinity, specific UV absorption (SUVA), and the bromide to total organic carbon ratio (Br:TOC) at the first point of chlorine addition. Free chlorine residual in the distribution system, distribution system residence time, distribution system pH, turbidity, and temperature only slightly influence bromine incorporation. The bromide to applied chlorine (Br:Cl) ratio is not a significant predictor of the bromine incorporation fraction (BIF) in any of the four classes studied. These results indicate that removal of natural organic matter and the location of chlorine addition are important treatment decisions that have substantial implications for bromine incorporation into disinfection byproduct in drinking waters.
统计模型是为信息收集规则（ICR）数据库中仅使用自由氯作为主消毒剂或残留消毒剂的水厂中的分配系统样品中三卤甲烷（THM）、三卤乙酸（THAA）、二卤乙酸（DHAA）和二卤乙腈（DHAN）类消毒副产物（DBP）的溴化作用开发的。本研究的目的是描述水质条件在处理前后对分配系统中溴化作用进入 DBP 混合物的影响。贝叶斯马尔可夫链蒙特卡罗（MCMC）方法用于模拟单个 DBP 浓度，并估计用于预测每个四个优先 DBP 类别的分配系统 DBP 混合物中溴化作用分数的线性模型的系数。溴化作用模型与数据吻合良好。跨 DBP 类别的溴化作用分数的最重要预测因子是碱度、特定紫外吸收（SUVA）和氯添加第一点的溴化物与总有机碳比（Br:TOC）。分配系统中的自由氯残留、分配系统停留时间、分配系统 pH 值、浊度和温度仅对溴化作用有轻微影响。溴化物与应用氯（Br:Cl）的比值不是四个研究类别的溴化作用分数（BIF）的重要预测因子。这些结果表明，去除天然有机物和氯的添加位置是重要的处理决策，对饮用水中消毒副产物的溴化作用有重大影响。
