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Over the years, ion mobility spectrometry has evolved into a powerful technique for rapid identification of analytes in very complex sample matrixes such as human breath. Every analyte detected has a characteristic ion mobility value (and a retention time when additional preseparation techniques are employed) which is used to identify the peaks in a spectrum either by comparison with reference analytes or by simultaneous mass spectrometric measurements. In this study, the mass-mobility correlations between compounds in three different homologous series are used to predict the mobilities of the other substances in the same series in a medium of synthetic air. The results show a very high accuracy (>99.5%) of the prognosis. The linear trend equations of ion mobilities, as a function of the number of carbon atoms, obtained from the different series were then generalized into one linear equation for the reduced ion mobility for the polar aliphatic compounds and is validated by comparing it with the traditional Mason-Schamp equation. To compare the empirical equation obtained from the prognosis and the Mason-Schamp equation, the collision integral term in the latter was split into two terms to linearize it. The resulting novel ion mobility equation could be the starting step to completely describe the relationship between ion collision integral and the ion mobility for polar aliphatic compounds. The splitting of the collision integral into two terms will also give new inputs to describe the various ion models and the different forces that act on the ions and the neutral gas molecules upon which the collision integral is dependent on. This prognosis method could, furthermore, be extended to all other classes of organic compounds and could serve as a useful tool for identification of unknowns in ion mobility spectra, thereby considerably reducing the time-consuming and costly reference measurements and other coupling techniques that are currently employed.

For the first time, ion mobility spectrometers (IMS) with radioactive and UV ionization sources in combination with multicapillary columns (MCCs) have been used to determine methyl tert-butyl ether (MTBE), a gasoline additive, in water and nitrogen as well as the monoaromatic compounds benzene, toluene, and m-xylene (BTX). A membrane extraction unit was set up to extract the substances from water, which is simple, effective, and easy to automate for further applications. Thus, the detection of MTBE and BTX of gasoline vapors was accomplished after a preliminary silicone membrane extraction. Two-dimensional data analyses of IMS-chromatograms allow us to separate these substances clearly according to their different retention and drift times. Method detection limits for MTBE were 2 microg/L (UV) and 30 pg/L (63Ni) in nitrogen and 20 mg/L (UV) and 1 microg/L (63Ni) in water. Rather a good reproducibility was achieved with relative standard deviations of between 2.9 and 9%. The method presented in this article has been proven to be suitable for nearly real-time monitoring as the total analysis time is less than 90 s. As an example of application, the detection of MTBE and BTX in a mixture of volatile organic compounds of pure gasoline using the 2-D IMS-chromatogram is presented.