Trilinear chemometric analysis of two-dimensional comprehensive gas chromatography–time-of-flight mass spectrometry data

Two-dimensional comprehensive gas chromatography (GC×GC) is a powerful instrumental tool in its own right that can be used to analyze complex mixtures, generating selective data that is applicable to multivariate quantitative analysis and pattern recognition. It has been recently demonstrated that by coupling GC×GC to time-of-flight mass spectrometry (TOFMS), a highly selective technique is produced. One separation on a GC×GC/TOFMS provides retention times on two chromatographic columns and a complete mass spectrum for each component within the mixture. In this manuscript, we demonstrate how the selectivity of GC×GC/TOFMS combined with trilinear chemometric techniques such as trilinear decomposition (TLD) and parallel factor analysis (PARAFAC) results in a powerful analytical methodology. Using TLD and PARAFAC, partially resolved components in complex mixtures can be deconvoluted and identified using only one data set without requiring either signal shape assumptions or fully selective mass signals. Specifically, a region of overlapped peaks in a complex environmental sample was mathematically resolved with TLD and PARAFAC to demonstrate the utility of these techniques as applied to GC×GC/TOFMS data of a complex mixture. For this data, it was determined that PARAFAC initiated by TLD performed a better deconvolution than TLD alone. After deconvolution, mass spectral profiles were then matched to library spectra for identification. A standard addition analysis was performed on one of the deconvoluted analytes to demonstrate the utility of TLD-initiated PARAFAC for quantification without the need for accurate retention time alignment between sample and standard data sets.