通过三维荧光光谱技术和平行因子分析法相结合，提出了一种石油类污染物的识别和检测方法。以97#汽油、0#柴油和普通煤油的不同浓度CCl4溶液为测量样品，不考虑每种油的具体成分，仅将其视为一个整体作为一种组分来研究，通过汽油、柴油不同比例的混合以及存在煤油作为干扰物的情况下，利用FLS920全功能型荧光光谱仪测量得到样品的三维荧光光谱数据。经过激发与发射校正以及空白扣除，去除了仪器误差和散射的影响并得到了样品的真实光谱。实验采用基于平行因子的二阶校正算法分析测得的光谱数据，体现了算法的二阶优势，验证了在未知干扰存在的情况下依然能够对混合样品各成分进行准确的识别和浓度测量，并得到满意的回收率。

The identification and measuring method of petroleum pollutant is proposed by three-dimensional fluorescence spectroscopy combined with parallel factor analysis. Different concentration solutions of 97# gasoline, 0# diesel and kerosene in CCl4 are as measuring samples. Every petroleum product as one component is considered as a whole and the specific components are not taken into account. By mixing gasoline and diesel with different concentrations and taking kerosene as interfering substance, the three-dimensional fluorescence spectra of samples are measured with FLS920 fluorescence spectrometer. Instrumental error and effect of scattering are removed and the true spectra are obtained by using excitation and emission correction and blank subtraction. The experiments use the second-order calibration algorithms based on the parallel factor to analyze the spectral data and the second-order advantage is adequately exploited. It is proved that the identification and measurement of different components in mixed sample are achieved accurately in existence of interfering substance and good recovery is obtained.