Classification of Torbanite and Cannel Coal II. Insights from Pyrolysis-GC / MS and Multivariate Statistical Analysis
Petrographic and megascopic criteria have traditionally been used as the basis for the classification of torbanite and cannel coal. For this study, it was hypothesized that modern analytical organic geochemical and multivariate statistical techniques could provide an alternative approach. Towards this end, the demineralized residues of 14 torbanite (rich in Botryococcus-related alginite) and cannel (essentially, rich in organic groundmass and / or sporinite) coal samples were analyzed by pyrolysis-gas chromatography / mass spectrometry (Py-GC / MS). Cluster analysis performed on the Py-GC / MS data clearly distinguished the torbanite from the cannel coal demonstrating a consistency between the chemical properties and the petrographic composition. All the torbanite samples group into one cluster, their pyrolyzates having an overwhelming predominance of straight chain hydrocarbons, a characteristic typical of Botryococcus. The presence of the C9-C26 n-α, ω-alkadiene series is the key feature distinguishing the torbanites from the other samples. The cannel coals exhibit more chemical diversity, reflecting their greater variability in petrographic composition. The Breckinridge cannel, dominated by a highly aliphatic lamalginitic groundmass, chemically fits the torbanite category. The bituminitic groundmass-dominated cannel coals fall into a cannel sub-cluster, their pyrolyzates having a characteristic predominance of n-alk-1-enes and n-alkanes (particularly the long-chain homologues), with no detectable alkadienes. The vitrinitic groundmass-dominated Ohio Linton cannel and the sporinite-rich Canadian Melville Island cannel are readily distinguishable from the other cannels by the relatively abundant aromatic and phenolic compounds in their pyrolyzates. The internal distribution patterns of alkylaromatic and alkylphenolic isomers are shown to be less significant in the classification of this sample set. Multivariate statistical analysis of the pyrolysis data not only successfully discriminated torbanites from cannel coals, but recognized subtler differences between the examples of these two coal types, in substantial agreement with the petrographic characterization. As such, these methods can substitute for or supplement the traditional microscope-based approach.