Proefschrift KWR

Analytical methodologies for the characterisation of aquatic natural organic matter - Literature Thesis


“Natural organic matter (NOM) is a complex heterogeneous mixture of naturally occurring organic compounds which exist ubiquitously in natural waters worldwide. The presence of NOM in water has a negative impact on drinking water quality and treatment processes, due to colour, taste and odour, fouling of membranes, promoting biological growth. NOM can act as a precursor for the formation of disinfection by-products. In order to minimise these unwanted effects, it is of great importance to significantly reduce the concentration of NOM in treated water. Therefore proper characterisation of NOM in raw and drinking water is needed, for which many different analytical methodologies are currently used.
In this literature study, a review of methods used for NOM analysis and characterisation is provided, including methods for isolation/concentration (e.g. reverse osmosis, freeze-drying and passive sampling) and fractionation (e.g. resin fractionation, size exclusion chromatography and solid phase extraction), followed by general analysis methods (e.g. dissolved organic carbon, specific UV absorbance and fluorescence analysis) and in-depth characterisation methods (e.g. Fourier transform infrared spectroscopy, nuclear magnetic resonance and Fourier transform ion cyclotron resonance mass spectrometry). And finally applications of hyphenated analytical techniques are discussed (e.g. size exclusion chromatography – organic carbon detector, liquid chromatography – high resolution mass spectrometry and pyrolysis gas chromatography – mass spectrometry). In addition, recommendations are made for the most fitting analysis techniques for NOM characterisation to be used or implemented at KWR and an analytical approach is provided using LC-HR-MS for the comprehensive characterisation of NOM.”

(Citaat: Vughs, D. – Analytical methodologies for the characterisation of aquatic natural organic matter – Literature Thesis, June 2018)

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