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Updated: Jun 27, 2026

Online Size-exclusion and Ion-exchange Chromatography on a SAXS Beamline
Published on: January 5, 2017
Reconsidering the quantitative analysis of organic carbon concentrations in size exclusion chromatography
Ulrich Lankes1, Margit B Müller, Matthias Weber
1Engler-Bunte-Institut, Bereich Wasserchemie, Universität Karlsruhe (TH), 76128 Karlsruhe, Germany. ulrich.lankes@ebi-wasser.uka.de
Abstract:
The evaluation of the molecular size distribution of natural organic matter (NOM) in aquatic environments via size exclusion chromatography (SEC) is important for the understanding of environmental processes such as nutrient cycling and pollutant transport as well as of technical water treatment processes. The use of organic carbon (OC) detectors has become popular in recent studies due to improved availability and quantification possibilities, which supposedly are superior to those of ultraviolet (UV) detectors. A set of 12 NOM samples was used to demonstrate the limitations of online OC detection (OCD) when analyzing complex aquatic organic matter. A novel evaluation approach for SEC data is introduced by combining the information from UV absorbance (UVA) and OCD chromatograms as well as offline total OC (t-OC) and dissolved OC-specific UVA (SUVA) measurements. It could be shown that about 70% of certain OC components were not detected with the OCD system used in this study. For the investigated samples, these types of carbon accounted for up to 72% of the t-OC, i.e. for such NOM samples quantification by OCD is not possible or at least highly questionable. The addition of an oxidant improved the overall oxidation efficiency only slightly. Most likely NOM that predominantly consists of polysaccharides and features a nominal molecular weight of 150kg/mol or more was responsible for low OCD yields. For future applications, a further improvement of the OCD system would be worthwhile so that quantitative analytical data on the molecular size distribution of NOM and its structural characteristics such as the SUVA distribution can be obtained.
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