Detection and estimation of adulterated gasoline fuel in India using FTIR-ATR spectroscopy with chemometric methods

Abstract

In this work, Fourier Transform Infrared Attenuated Total Reflectance (FTIR-ATR) spectroscopy was combined with multivariate techniques, such as Principal Component Analysis (PCA), Soft Independent Modelling of Class Analogy (SIMCA), and Partial Least Squares Discriminant Analysis (PLS-DA), to classify and quantify the gasoline adulteration with kerosene. The Calibration models of Kerosene blended on gasoline fuel of 12 standard samples (2–24% v/v) were prepared. The chemometric tools were used to compare 142 samples from Mizoram and 12 samples from neighbouring states. The PCA and SIMCA approaches did not detect adulteration. The PLS-DA classification model found 7 samples were adulterated, with excellent specificity and sensitivity. The PLS regression model had the ability to predict adulterant concentrations with prediction errors less than 2% for all adulterants. The predicted concentration range of the PLS-R model is 0.3–13 % v/v, with high significant values of R-Square (0.996) and RMSE (0.405).