Abstract One-dimensional gas chromatography coupled with time-of-flight mass spectrometry (1D GC-TOF/MS) and comprehensive two-dimensional gas chromatography coupled with TOF/MS (GC×GC-TOF/MS) were evaluated as complementary platforms for diesel-fuel compositional profiling. Across all samples, 1D GC-TOF/MS reported 1,850 library-annotated features (similarity score ≥ 700), whereas GC×GC-TOF/MS reported 27,146 deconvoluted features, comprising 8,108 annotated features and 19,038 unnamed Peak-ID features. Only 595 annotated features were common to both workflows, yet workflow-specific statistical evaluation and PCA of GC×GC feature-occurrence profiles consistently highlighted the same atypical samples. Broad chemical grouping of annotated and predicted GC×GC features showed that paraffinic and olefinic/naphthenic hydrocarbon families dominated most fuels. In contrast, sample 51 × 57, and to a lesser extent K8LZ1 depending on feature inclusion, exhibited redistributed class patterns and a higher proportion of oxygenated or FAME-associated features. Integrating chromatographic profiling with routine physicochemical descriptors indicated that meaningful compositional divergence may occur even within a narrow specification window. Overall, 1D GC-TOF/MS remains effective for robust comparative screening, while GC×GC-TOF/MS provides additional selectivity and peak capacity to interrogate compositionally congested diesel matrices and to support future chemometric modelling.
Zieliński et al. (Fri,) studied this question.
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