Development of an analytical method combining chemometrics and synchronous fluorescence: analysis of diesel-kerosene mixtures

Synchronous fluorescence spectroscopy (SFS) is a widely accepted technique for the analysis of multi fluorophoric samples. Petroleum products are multi fluorophoric since they contain a mixture of variety polycyclic aromatic compounds (PACs). In this work, chemometric multivariate methods have been combined with SFS data to develop a reliable calibration for the estimation of kerosene fraction present in diesel. Efficient and robust models are created using multivariate techniques such as principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLSR). The models developed by these methods are able to perceive very low level of kerosene contamination with low prediction error.