Australian Rivers Institute, School of Environment and Science, Griffith University, Southport, Qld 4222, Australia.
The University of Queensland, Advanced Water Management Centre, Brisbane, Qld 4072, Australia; Catalan Institute for Water Research (ICRA), Technological Park of the University of Girona, 17003, Spain.
Sci Total Environ. 2018 Nov 1;640-641:31-40. doi: 10.1016/j.scitotenv.2018.05.280. Epub 2018 May 28.
Parallel factor (PARAFAC) analysis of fluorescence excitation-emission matrices (EEMs) was used to investigate the organic matter and DBP formation characteristics of untreated, primary treated (enhanced coagulation; EC) and secondary treated synthetic waters prepared using a Suwannee River natural organic matter (SR-NOM) isolate. The organic matter was characterised by four different fluorescence components; two humic acid-like (C1 and C2) and two protein-like (C3 and C4). Secondary treatment methods tested, following EC treatment, were; powdered activated carbon (PAC), granular activated carbon (GAC), 0.1% silver-impregnated activated carbon (SIAC), and MIEX® resin. Secondary treatments were more effective at removing natural organic matter (NOM) and fluorescent DBP-precursor components than EC alone. The formation of a suite of 17 DBPs including chlorinated, brominated and iodinated trihalomethanes (THMs), dihaloacetonitriles (DHANs), chloropropanones (CPs), chloral hydrate (CH) and trichloronitromethane (TCNM) was determined after chlorinating water sampled before and after each treatment step. Regression analysis was used to investigate the relationship between peak component fluorescence intensity (F), DBP concentration and speciation, and more commonly used aggregate parameters such as DOC, UV and SUVA. PARAFAC component 1 (C1) was in general a better predictor of DBP formation than other aggregate parameters, and was well correlated (R ≥ 0.80) with all detected DBPs except dibromochloromethane (DBCM) and dibromoacetonitrile (DBAN). These results indicate that the fluorescence-PARAFAC approach could provide a robust analytical tool for predicting DBP formation, and for evaluating the removal of NOM fractions relevant to DBP formation during water treatment.
平行因子（PARAFAC）分析荧光激发-发射矩阵（EEM）被用于研究未经处理、一级处理（强化混凝；EC）和二级处理的合成水的有机物和 DBPs 生成特性，这些合成水是使用苏万尼河天然有机物（SR-NOM）分离物制备的。有机物由四个不同的荧光组分表示；两个类腐殖酸（C1 和 C2）和两个类蛋白（C3 和 C4）。在 EC 处理之后，测试的二级处理方法是：粉末活性炭（PAC）、颗粒活性炭（GAC）、0.1%载银活性炭（SIAC）和 MIEX®树脂。与 EC 单独处理相比，二级处理更有效地去除天然有机物（NOM）和荧光 DBPs 前体组分。在对每种处理步骤前后采集的水样进行氯化后，确定了 17 种 DBPs 的形成，包括氯化、溴化和碘化三卤甲烷（THMs）、二卤乙腈（DHANs）、氯代丙酮（CPs）、水合氯醛（CH）和三氯硝基甲烷（TCNM）。回归分析用于研究峰组分荧光强度（F）、DBP 浓度和形态与常用的总有机碳（DOC）、紫外线吸收（UV）和比色指数（SUVA）等综合参数之间的关系。PARAFAC 成分 1（C1）通常是 DBPs 生成的更好预测因子，与除二溴一氯甲烷（DBCM）和二溴乙腈（DBAN）之外的所有检测到的 DBPs 都具有很好的相关性（R≥0.80）。这些结果表明，荧光-PARAFAC 方法可以为预测 DBPs 生成提供一种稳健的分析工具，并用于评估水处理过程中与 DBPs 生成相关的 NOM 分数的去除。
