Date of Award
Doctor of Philosophy
Nicole Labbe, Stuart Daw, Paul Ayers
The focus of this dissertation was to understand and model how inorganic contaminants (mainly H2S, COS, NH3, and HCN) are formed during biomass gasification to provide information for effective contaminant abatement and producer gas remediation. This dissertation was partitioned into five research studies with specify objectives. In the first study, a simple thermo-gravimetric approach coupled with CHN analyzer and inductively coupled plasma optical emission spectrometry (ICP-OES) was used to track the conversion profile of C, H, N, S, and O during the pyrolysis stage of biomass gasification. The activation energy for the sulfur and nitrogen conversion was drastically lower at 800 °C compared to 600 and 700 °C. Additionally, the elemental concentrations of sulfur and nitrogen were higher for pyrolyzed biomass compared to fresh biomass. In the second study, a non-stoichiometric equilibrium model of biomass gasification was implemented. We demonstrated that the yields of CO, CO2, and H2 during gasification were equilibrium-controlled. However, the yields of CH4 and contaminant species were kinetically-limited. Furthermore, we establish that NH3 + CO ↔ HCN + H2O and H2S + CO2 ↔ COS + H2O reactions were important to nitrogen and sulfur species distribution, respectively. In the third, an inert fluidized bed system was simulated using computational fluid dynamics and discrete element method (CFD-DEM). Also, experimental validation of the developed model was performed on three important hydrodynamic variables of fluidized bed systems (pressure drop, minimum fluidization velocity, and bed height). The CFD-DEM model produced a realistic representation of the particle motion and reasonably predicted the hydrodynamics properties of the experimental system. The fourth and fifth studies were designed to simulate the formation of nitrogen (NH3 and HCN) and sulfur (H2S, COS, SO2) contaminants, respectively, by coupling the developed CFD-DEM model in the third study with appropriate chemical reactions, heat transfer, and particle shrinkage models. We found that the proposed CFD-DEM model gave reasonably prediction for the selected contaminants species. Hence, the proposed model is a valuable tool for gaining insight into the formation and extent of producer gas contaminants.
Oyedeji, Oluwafemi Ademola, "Understanding and modeling the formation of syngas contaminants during biomass gasification. " PhD diss., University of Tennessee, 2019.