Soils Group, School of Agriculture, Food & Wine and Waite Research Institute, University of Adelaide, Waite Campus, Urrbrae, SA, 5064, Australia,
Environ Sci Pollut Res Int. 2014 Mar;21(6):4265-75. doi: 10.1007/s11356-013-2351-0. Epub 2013 Dec 4.
The paper-making process can produce large amounts of wastewater (WW) with high particulate and dissolved organic loads. Generally, in developed countries, stringent international regulations for environmental protection require pulp and paper mill WW to be treated to reduce the organic load prior to discharge into the receiving environment. This can be achieved by primary and secondary treatments involving both chemical and biological processes. These processes result in complex changes in the nature of the organic material, as some components are mineralised and others are transformed. In this study, changes in the nature of organics through different stages of secondary treatment of pulp and paper mill WW were followed using three advanced characterisation techniques: solid-state (13)C nuclear magnetic resonance (NMR) spectroscopy, pyrolysis-gas chromatography mass spectrometry (py-GCMS) and high-performance size-exclusion chromatography (HPSEC). Each technique provided a different perspective on the changes that occurred. To compare the different chemical perspectives in terms of the degree of similarity/difference between samples, we employed non-metric multidimensional scaling. Results indicate that NMR and HPSEC provided strongly correlated perspectives, with 86 % of the discrimination between the organic samples common to both techniques. Conversely, py-GCMS was found to provide a unique, and thus complementary, perspective.
造纸过程会产生大量废水(WW),其中含有大量的颗粒态和溶解态有机物质。一般来说,在发达国家,为了保护环境,国际上对制浆造纸厂 WW 的排放有严格的规定,要求在排放到受纳环境之前,必须进行处理以降低有机负荷。这可以通过初级和二级处理来实现,包括化学和生物过程。这些过程导致有机物质性质发生复杂变化,一些成分被矿化,而另一些则发生转化。在本研究中,使用三种先进的特性分析技术:固态(13)C 核磁共振(NMR)光谱、热裂解-气相色谱质谱联用(py-GCMS)和高效尺寸排阻色谱(HPSEC),跟踪了制浆造纸厂 WW 二级处理不同阶段有机物质性质的变化。每种技术都提供了对发生变化的不同看法。为了比较不同化学方法在样品之间相似/差异程度上的差异,我们采用了非度量多维尺度分析。结果表明,NMR 和 HPSEC 提供了高度相关的观点,两种技术共有 86%的有机样品之间具有区分度。相反,py-GCMS 则提供了独特的、因此是互补的观点。