Identification of gasoline adulteration using comprehensive two-dimensional gas chromatography combined to...

Area of Science:

• Analytical Chemistry
• Petroleum Science
• Environmental Monitoring

Background:

• Commercial gasoline in Brazil (Type C) contains 25% ethanol, making it susceptible to adulteration.
• Accurate detection of fuel adulterants is crucial for quality control and regulatory compliance.
• Existing methods may not be sufficient for complex fuel mixtures.

Purpose of the Study:

• To develop and validate a method for detecting adulteration in commercial Type C gasoline.
• To correlate chromatographic data with gasoline concentration using multivariate calibration.
• To establish GCxGC-FID and N-PLS as a viable alternative for routine fuel analysis.

Main Methods:

• Utilized comprehensive two-dimensional gas chromatography with flame ionization detection (GCxGC-FID) for detailed sample analysis.
• Employed multi-way partial least squares regression (N-PLS) for multivariate calibration and quantitative modeling.
• Calibrated models using blends of gasoline with white spirit, kerosene, and paint thinner; validated with spiked samples and real-world gasoline.

Main Results:

• Regression models successfully correlated chromatographic data with gasoline concentration.
• Root mean square error of prediction (RMSEP) for gasoline concentration ranged from 3.3% to 8.2% (v/v).
• Results from the developed method showed agreement with the official analysis method for real fuel samples.

Conclusions:

• GCxGC-FID combined with N-PLS provides an effective method for detecting and quantifying gasoline adulteration.
• This approach offers a reliable alternative for routine monitoring of fuel quality.
• The method is applicable to other analytical challenges involving the detection of specific components in complex mixtures.