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Assessing the impact of environmental activities on natural organic matter in South Africa and Belgium

机译:评估环境活动对南非和比利时天然有机物的影响

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The presence and persistence of natural organic matter (NOM) in drinking water treatment plants (WTPs) requires a robust and rapid monitoring method. Measurement and monitoring of NOM fractions using current technology is time-consuming and expensive. This study uses fluorescence measurements in combination with Parallel Factor (ParaFac) analysis to characterize NOM fractions. This was achieved through: (1) determining the origin and composition of NOM fractions using fluorescence index (FI), humification index, biological index, and freshness index, and (2) using multivariate analysis to reveal key parameters and hidden NOM fraction characteristics influenced by seasonal changes and environmental activities. The ParaFac model revealed that the NOM fractions for Belgium plants are mainly hydrophobic acids, aromatic proteins, biological activity, humic acid-like, and fulvic acid-like moieties. The NOM fractions in South African plants were mainly aromatic protein, humic acid-like, fulvic acid-like, tryptophan-like, and protein-like moieties. For Belgium plants in spring FI 1.7, indicating high microbial sources, whereas FI 1.3 for South African plants, signifying terrestrial sources of NOM. On the one hand, the first principal component (PC1) interpreted 33.02% of the total variance, and is a measure of fluorescent NOM relative concentration. On the other hand, the PC2 interpreted 21.47% and contains most of the information on humification, freshness, and biological indicators, while PC3 interpreted 17.74% and contains information on the origin and variation in environmental conditions. These results will assist in developing a method for online monitoring of NOM fractions in water sources based on environment activities and spectral measurements.[GRAPHICS].
机译:天然有机物(NOM)在饮用水处理植物(WTP)中的存在和持续存在需要一种稳健和快速的监测方法。使用当前技术的NOM部分的测量和监测是耗时和昂贵的。该研究使用荧光测量与平行因子(PARAFAC)分析组合结合表征NOM分数。这是通过的:(1)使用荧光指数(FI),湿度指数,生物指标和新鲜度指数确定NOM部分的起源和组成,以及使用多变量分析来揭示影响关键参数和隐藏的NOM分数特征通过季节性变化和环境活动。 PARAFAC模型揭示了比利时植物的NOM分数主要是疏水酸,芳香蛋白,生物活性,腐殖酸样和富含腐蚀性的部分。南非植物中的NOM部分主要是芳香蛋白,腐殖酸,富酸酸样,色氨酸样和蛋白质的部分。对于春季Fi> 1.7的比利时植物,表明南非植物的高微生物来源,而南非植物的Fi <1.3,则表示NOM的陆地来源。一方面,第一主成分(PC1)解释了总方差的33.02%,是荧光NOM相对浓度的衡量标准。另一方面,PC2解释了21.47%,含有关于腐殖质,新鲜度和生物指标的大部分信息,而PC3解释了17.74%,并包含有关环境条件的原产地和变异的信息。这些结果将有助于开发基于环境活动和光谱测量的水源在线监测的方法。[图形]。

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