New Headspace-Mass Spectrometry Method for the Discrimination of Commercial Gasoline Samples with Different Research Octane Numbers

Abstract

A method for the discrimination of different gasoline samples according to their RON has been developed using an HS-MS system. The working conditions for the HS-MS analytical procedure were optimized by experimental design. The variables optimized were incubation temperature, incubation time, and sample volume. The optimal conditions were as follows: 145 °C incubation temperature, 10 min incubation time, and 80 μL sample volume. The optimized method was applied to a set of 30 gasoline samples with different RON values (95# and 98#). An hierarchical cluster analysis was applied in which the m/z (45−200 m/z) values were used as a variable to form groups. A perfect classification (100%) of the gasoline samples according to their RON was achieved. A linear discriminant analysis was carried out and the resulting linear discriminant function enabled a perfect classification of the gasoline samples according to the RON using only the m/z values of 88, 95, and 112. These results demonstrate the capacity of the new technique for the discrimination of gasoline samples according to their RON and the applicability of this method in this field. For the first time, HS-MS was used for this purpose. The main advantage of HS-MS vs previous methodologies is that no chromatographic separation and no sample manipulation are required. HS-MS is therefore faster than the current techniques used in these kinds of studies; it is also cheaper, ecofriendly, and easy to use for routine analysis.