Compositional and kinetic analysis of oil shale pyrolysis using TGA–MS

Abstract

There are vast resources of oil shale in the western United States. Development of technically and economically effective technologies for the conversion of oil shale to liquid fuels will help provide a long-term and secure source of transportation fuels. Developing good understanding of the decomposition kinetics of oil shale to oil and other products, along with the oil compositional information are important regardless of the process used. Themogravimetric analysis combined with online mass spectrometry (TGA–MS) affords the opportunity to obtain compositional information while the decomposition is being measured quantitatively. In this work we provide data on the TGA–MS analyses of Green River oil shale from Utah. Compounds of about 300 atomic mass units were targeted in the mass spectrometric analyses.The weight loss results from the TGA part of the analysis and the subsequent kinetic parameters derived from the data were consistent with our prior work. The activation energies of decomposition were in the 90–230kJ/mol range with respect to conversion with uncertainty numbers of about 10%. Lighter hydrocarbons evolved slightly earlier and their amounts were higher in comparison to heavier hydrocarbons. Alkanes such as hexane and decane were detected at slightly lower temperatures than their equivalent carbon number aromatic compounds, but the differences were not significant. Higher heating rates generated more alkenes compared to respective alkanes and as the carbon number increased, this ratio decreased.Kinetics of the formation of naphtha group of compounds (C5–C12) were derived using the advanced isoconversion method. The activation energies in the range of 41–206kJ/mol were lower than for the entire decomposition process. However, because the compound evolution signals as detected by mass spectrometry are noisier than the overall weight loss data, the uncertainties in these measurements were much greater in certain conversion ranges. Similar principles can be used to derive single component evolution kinetics.