• Spectroscopy and Spectral Analysis
  • Vol. 34, Issue 9, 2561 (2014)
CHEN Zhi-kun1、2, WANG Yang3, WANG Fu-bin2, WANG Yu-tian1, and ZHOU Yan2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: 10.3964/j.issn.1000-0593(2014)09-2561-07 Cite this Article
    CHEN Zhi-kun, WANG Yang, WANG Fu-bin, WANG Yu-tian, ZHOU Yan. Excitation-Emission Matrix Spectroscopy and Parallel Factor Analysis for Micro-Content Petroleum Pollutant[J]. Spectroscopy and Spectral Analysis, 2014, 34(9): 2561 Copy Citation Text show less

    Abstract

    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.
    CHEN Zhi-kun, WANG Yang, WANG Fu-bin, WANG Yu-tian, ZHOU Yan. Excitation-Emission Matrix Spectroscopy and Parallel Factor Analysis for Micro-Content Petroleum Pollutant[J]. Spectroscopy and Spectral Analysis, 2014, 34(9): 2561
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