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Reconsidering the quantitative analysis of organic carbon concentrations in size exclusion chromatography

机译:重新考虑尺寸排阻色谱法中有机碳浓度的定量分析

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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 chromato-grams 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 poly-saccharides and features a nominal molecular weight of 150 kg/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.
机译:通过尺寸排阻色谱法(SEC)评估水生环境中天然有机物(NOM)的分子大小分布对于理解环境过程(如养分循环和污染物运输以及水处理技术过程)非常重要。由于改进的可用性和定量可能性,有机碳(OC)检测器的使用在最近的研究中变得很流行,据认为这要优于紫外线(UV)检测器。一组12个NOM样品用于证明分析复杂的水生有机物时在线OC检测(OCD)的局限性。通过结合来自紫外线吸收率(UVA)和OCD色谱图以及离线总OC(t-OC)和溶解的OC特定UVA(SUVA)测量的信息,引入了一种新颖的SEC数据评估方法。可以证明,在这项研究中使用的OCD系统未检测到约70%的某些OC成分。对于所研究的样品,这些类型的碳最多占t-OC的72%,也就是说,对于此类NOM样品,无法通过OCD进行定量分析,或者至少是高度可疑的。氧化剂的添加仅略微改善了总氧化效率。主要由多糖组成且标称分子量为150 kg / mol或更高的NOM最可能是导致OCD产量低的原因。对于将来的应用,OCD系统的进一步改进将是值得的,以便可以获得有关NOM分子大小分布及其结构特征(例如SUVA分布)的定量分析数据。

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