Products of petroleum crude are multifluorophoric in nature due to the presence of a mixture of a variety polycyclic aromatic hydrocarbons (PAHs). The use of excitation–emission matrix fluorescence (EEMF) spectroscopy for the analysis of such multifluorophoric samples is gaining progressive acceptance. In this work, EEMF spectroscopic data is processed using chemometric multivariate methods to develop a reliable calibration model for the quantitative determination of kerosene fraction present in petrol. The application of the N-way partial least squares regression (N-PLS) method was found to be very efficient for the estimation of kerosene fraction. A very good degree of accuracy of prediction, expressed in terms of root mean square error of prediction (RMSEP), was achieved at a kerosene fraction of 2.05%.

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