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Pyrolysis Two-Dimensional GC-MS of Miscanthus Biomass: Quantitative Measurement Using an Internal Standard Method

Groenewold Gary S., Johnson Kristyn M., Fox S. Carter, Rae Cathy, Zarzana Christopher A., Kersten Bethany R., Rowe Salene M., Westover Tyler L., Gresham Garold L., Emerson Rachel M., Hoover Amber N.
Energy & Fuels 2017 v.31 no.2 pp. 1620-1630
Miscanthus, acetic acid, biomass, gas chromatography-mass spectrometry, guaiacol, heat treatment, nuclear magnetic resonance spectroscopy, phenol, pyrolysis, quantitative analysis, temperature profiles
Accurate measurement of biomass pyrolysis products can provide valuable guidance for thermal processing. However, pyrolysis generates large numbers of compounds in varying concentrations, factors that can make compound identification and quantitation difficult. In this study, Miscanthus biomass samples were analyzed using pyrolysis/two-dimensional gas chromatography/mass spectrometry (Py-GCxGC-MS), which provided a more comprehensive chromatographic separation and mass spectral compound identification. Quantitative measurement was performed for 34 calibrated pyrolysis compounds using an internal standard method. Pyrolysis efficiency was measured as a function of sample mass, pyrolysis temperature, and pyrolysis temperature ramp rate. For most of the calibrated pyrolysis products, production efficiency decreased with sample mass, increased with pyrolysis temperature, and decreased with pyrolysis temperature ramp rate. Significantly, the temperature profiles of the different pyrolysis products were variable, notably acetic acid and the vinyl and formyl derivatives of phenol and guaiacol, which were produced at lower temperatures compared to other compounds such as the syringyl derivatives and levoglucosan. Lignol ratios were compared with those generated using ¹H/¹³C heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance spectroscopy (NMR). Lower fractions of syringyl- and guaiacyl-lignols and higher fractions of the phenol-lignols were generated by Py-GCxGC-MS compared to HSQC-NMR.