Abstract The increase of fluorescent natural organic matter (fNOM) fractions during drinking water treatment might lead to an increased coagulant dose and filter clogging, and can be a precursor for disinfection by-products. Consequently, efficient fNOM removal is essential, for which characterisation of fNOM fractions is crucial. This study aims to develop a robust monitoring tool for assessing fNOM fractions across water treatment processes. To achieve this, water samples were collected from six South African water treatment plants (WTPs) during winter and summer, and two plants in Belgium during spring. The removal of fNOM was monitored by assessing fluorescence excitation–emission matrices datasets using parallel factor analysis. The removal of fNOM during summer for South African WTPs was in the range 69–85%, and decreased to 42–64% in winter. In Belgian WTPs, fNOM removal was in the range 74–78%. Principal component analysis revealed a positive correlation between total fluorescence and total organic carbon (TOC). However, TOC had an insignificant contribution to the factors affecting fNOM removal. Overall, the study demonstrated the appearance of fNOM in the final chlorinated water, indicating that fNOM requires a customised monitoring technique.

中文翻译：

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PARAFAC 模型作为监测水处理厂天然有机物去除的创新工具

摘要饮用水处理过程中荧光天然有机物 (fNOM) 分数的增加可能会导致混凝剂剂量增加和过滤器堵塞，并且可能是消毒副产物的前兆。因此，有效去除 fNOM 至关重要，其中 fNOM 分数的表征至关重要。本研究旨在开发一种强大的监测工具，用于评估水处理过程中的 fNOM 分数。为了实现这一目标，我们在冬季和夏季从南非的六个水处理厂 (WTP) 以及春季从比利时的两个水处理厂采集了水样。通过使用平行因子分析评估荧光激发-发射矩阵数据集来监测 fNOM 的去除情况。南非 WTP 夏季 fNOM 去除率在 69-85% 范围内，冬季下降至 42-64%。在比利时 WTP 中，fNOM 去除率在 74-78% 范围内。主成分分析显示总荧光与总有机碳（TOC）之间呈正相关。然而，TOC 对影响 fNOM 去除的因素的贡献并不显着。总体而言，该研究证明了最终氯化水中出现了 fNOM，这表明 fNOM 需要定制的监测技术。