Prediction of Gasoline Properties with near Infrared Spectroscopy

Abstract

The test measurements used for the analysis of gasoline quality are mostly complicated standard procedures which are time consuming and which require special equipment, large volume of samples and specialists. The standard test methods could be partly replaced with non-destructive near infrared (NIR) spectroscopic measurements which are fast and less expensive. The aim of this paper is to present a feasible procedure for the prediction of quality parameters of gasoline from its NIR spectrum in a large and very diverse sample set. 350 commercially available gasoline samples were collected from July 1996. The samples covered summer and winter grades of normal, super and superplus unleaded gasolines with minimum RON requirements of 91, 95 and 98, respectively. These fuels covered a wide range of samples from very different sources including Hungarian and foreign refineries and pumps. An InfraPrime Lab Analyser (Bran+Luebbe) with high quality optical fibres in combination with multivariate calibration (PLSR) was used to determine 12 different chemical and physical properties of gasolines including reseach octane number (RON), motor octane number (MON), benzene, methyl-tertier-buthyl-ether (MTBE), sulphur content, distillation characteristics, Reid vapour pressure (RVP) and density at 15°C. The developed NIR methods predicted four important gasoline properties (RON, MON, benzene and MTBE content) with reproducibilities equivalent to the standard test procedures. The standard errors of prediction were 0.34 for RON, 0.30 for MON, 0.13%(vv−1) for benzene and 0.21%(vv−1) for MTBE content. The correlation coefficients were better than 0.970 in these calibrations. Calibrations developed for other gasoline properties showed poor correlation coefficients and allowed each parameter to be predicted only with higher standard error than the reference values. The NIR methods described are suitable for routine selection measurements in large series of gasoline samples.