利用荧光激发发射矩阵 (FEEM) 和并行因子分析 (PARAFAC) 识别工艺水中的油类污染

Heena Madhav, Adam Gilmore
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引用次数: 0

摘要

南非发电公司 Eskom 广泛使用燃油。Eskom 的燃煤发电站在冷启动期间每小时使用多达 30,000 升燃油,其后果是导致大坝漏油。水处理厂中的油污染会造成不可逆转的膜污垢,需要进行昂贵的更换。这项研究工作的重点是开发一种快速方法,用于识别原油中低浓度的水溶性油成分馏分。在所开发的方法中,已知体积的原油水溶性成分被添加到各种工艺用水基质中。使用获得专利的 HORIBA Aqualog 光谱仪采集 FEEM,并使用 PARAFAC 对数据进行建模。结果用一个四组分模型进行了很好的描述,该模型包括一个油组分和三个天然有机物组分,分半验证匹配率为 90%。通过对 PARAFAC 成分得分进行线性回归验证了油类成分,R2 值为 0.98。根据这些分值,开发出了定性通过/未通过测试,这样就可以对加工用水进行分析,并根据该模型来指示是否存在超过破坏性阈值的油类污染。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of oil contamination in process water using fluorescence excitation emission matrix (FEEM) and parallel factor analysis (PARAFAC)
Fuel oil is widely used within Eskom, a power generation company in South Africa. Eskom's coal-fired power stations use up to 30,000 L of fuel oil per hour during a cold start-up, a consequence of which results in oil leaks to the dams. Oil contamination in water treatment plants causes irreversible membrane fouling, requiring costly replacement. This research work focused on the development of a rapid method for the identification of low concentrations of the water-soluble oil component fraction of crude fuel oil. For the developed method, known volumes of the water-soluble fraction of crude oil were spiked into various matrices of process water. FEEMs were collected using the patented HORIBA Aqualog spectrometer and data were modelled with PARAFAC. The results were well described with a four-component model, which included an oil component and three natural organic matter components, with a split-half validation match of 90%. The oil component was verified using linear regression of the PARAFAC component scores yielding an R2 value of 0.98. From the scores, a qualitative pass/fail test was developed such that process water can be analysed and subjected to the model to indicate the presence of oil contamination beyond a damaging threshold.
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