Determination of Ethanol Fuel Adulteration by Methanol Using Partial Least-Squares Models Based on Fourier Transform Techniques

Abstract

The use of ethanol fuel is becoming worldwide and Brazil is the largest consumer of ethanol fuel as hydrated ethyl alcohol fuel (AEHC). Due to the similarities of the physical−chemical properties of ethanol and methanol, ethanol fuel is being adulterated with methanol. In the present work, we propose the use of partial least-squares regression (PLS) calibration models based on Fourier transform mid-infrared (FTMIR) and Fourier transform near-infrared (FTNIR) measurements as a fast, precise, and accurate method to evaluate the quality of AEHC as well as to detect its adulteration with methanol. Eighty mixtures of methanol/ethanol/water standards were prepared. Sixty were used for calibration, and twenty, for validation. The validation samples were also analyzed by gas chromatography flame ionization detection (GC-FID) to determine the ethanol and methanol content. The results have shown that among the two investigated spectroscopic techniques, PLS/FTNIR presented the best performance for the detection of methanol with a root-mean-square error of prediction (RMSEP % w/w) of 0.15 as compared to the value of 0.54 obtained by the FTMIR model, while the GC-FID results presented a prediction error of 0.52 (% w/w). The minimum detected net concentration of MeOH with the FTNIR model was ca. 0.51 (% w/w)