摘要

Today's knowledge on total Natural Organic Matter (NOM) content proves not sufficient both at planning and operation of water treatment installations. Detailed characteristics of NOM present in raw and treated water enables better understanding of its changes during water treatment processes as well as substantially contributes towards operation optimization of subsequent stages of a technological set-up. UV absorbance, a common indicator used for NOM analysis in water, allows for both its qualitative and quantitative assessment. Specific UV absorbance (SUVA), being the UV absorbance of a water sample at 254 nm normalized for dissolved organic carbon (DOC), allows monitoring of water treatment processes, especially in terms of coagulant and oxidizing agent dosing. Other NOM characterization methods are a domain for research and are not widely employed in daily practice of water supply corporations. Among those techniques, fluorescence spectroscopy methods are worth noticing as they enable water quality monitoring in real time and are characterized by higher selectivity and sensitivity compared to UV absorbance. Fluorescence analysis that allows identification of biodegradable organic fractions, enables selection of adequate methods of their removal. Chromatography offers a number of analytical capabilities, especially when combined with a wide range of available detectors. It allows examination of NOM characteristics such as molecular weight, polarity, aromaticity or susceptibility to water disinfection by-product formation. Thus multiple possibilities of interpretation arise in regard to optimization of technological system operation in water treatment. In terms of NOM presence, fractionation methods employing membranes and selective resins are particularly helpful in water composition characterization. NOM particle separation according to its size, hydrophilicity, acidity and others enables monitoring its removal susceptibility in particular treatment processes and predicting the technological effects based on NOM characteristics.

  • 出版日期2016