为解决微含量石油类污染物识别问题, 采用三维荧光光谱(EEMs)与平行因子(PARAFAC)相结合的技术, 研究了石油类样品荧光组分特征及平行因子组分识别方法。 依据水体中石油类含量的标准规定, 配制出与Ⅰ—Ⅴ类水体对应的CCL4含油样品, 用来模拟油类污染物成分。 首先对97#汽油、 0#柴油、 普通煤油及CCL4溶剂进行三维荧光光谱扫描, 得到纯组分样品的三维荧光光谱图, 其次对97#汽油、 0#柴油及普通煤油的标准样品进行三维荧光光谱图测定, 最后对97#汽油、 0#柴油、 普通煤油在CCL4溶剂中的混合样品进行三维荧光光谱图测定。 在掌握上述不同组分样品的三维荧光光谱特性的基础上, 重点分析微含量下97#汽油、 0#柴油及煤油混合液的三维荧光光谱, 应用平行因子方法解析出样品中三种组分的激发与发射特征光谱以及组分间的浓度比。 解决了混合样品荧光光谱出现叠加, 用化学分离或单纯荧光分析方法较难识别荧光组分的问题, 实现了对微含量含油混合样品的主要组分的识别, 并得到混合样品溶液中不同组分间浓度比。

In order to solve the identification problem of oil pollutants containing micro content, the fluorescence characteristics of oil samples were studied using fluorescence excitation emission matrix spectra (EEMs) combined with parallel factor (PARAFAC) analysis. According to the conventional standard of oil content in water, simulated the component of oil pollution in Ⅰ-Ⅴ water was simulated by preparing samples of CCL4 with oil content. Firstly, measured the EEMs of 97# gasoline, 0# diesel, kerosene and CCL4 were measured individually, then the EEMs of 97# gasoline, 0# diesel, and kerosene in CCL4 were measured, and finally, the EEMs of the composite sample with all three oil contents in CCL4 were measured. The EEMs of the composite sample were superimposed by the EEMs of all its different components. It is therefore difficult to analyze the fluorescence component by chemical separation or simple fluorescence analysis. Since the EEMs of each oil component are already measured, we used the PARAFAC analysis to decompose the EEMs of the composite sample, and then extract the concentration ratio of each component. In this work, we solved the problem of identifying and quantifying the main micro-content petroleum pollutant in composite oil samples using EEMs and PARAFAC analysis.