Analytical Pyrolysis and Microextraction Methods to Characterize Oil and Biochar from Thermal and Catalytic Cracking of Biomass

In this dissertation thermal and catalytic pyrolysis of protein-rich biomass was investigated. The study was focused on the liquid and solid products. This thesis was aimed to gather chemical information on the thermal behavior of proteinaceous substrates in the presence of zeolite and compare with lignocellulosic biomass. Furthermore, the thesis was focused on the development of reliable analytical methods by means of Py-GC-MS in order to predicting bio-oil composition and to investigating biochar structure and its correlation with thermal stability. In addition a sampling procedure for the direct analysis of pyrolysis vapours based on absorption onto a microfiber (SPME) was developed. Py-GC-MS was applied as screening method to study the effect of different catalysts (H-ZSM5, MCM-41) and biomass-catalyst weight ratio on aromatic hydrocarbons production. The obtained results demonstrated that Py-GC-MS enable the selection of pyrolysis conditions. H-ZSM5 confirmed to be the catalyst with the best performance in terms of hydrocarbon production. In addition, the chemical composition observed by Py-GC-MS significantly reflects that obtained on bench scale. However, some difference has been found. Indeed, formation of high molecular weight PAHs have been observed only on bench scale and nitrogen-containing compounds and oxygenated compounds exhibited some difference related to condensation step. Problems during condensation step led to using SPME as at-line monitoring technique during the process capable of hot gas phase analysis. Strong similarity between GC-MS analysis of hot vapours and bio-oil from condensation traps were found. Finally, Py-GC-MS was applied to the chemical characterization of biochars obtained under different pyrolysis conditions or from different feedstock. Py-GC-MS can provide molecular indices useful to gather information on biochar thermal stability and to predicting the biochar carbonization degree. Furthermore, the molecular pattern resulting from Py-GC-MS could be utilized to infer information on the nature of the initial substrate and differentiate biochars.