Waste to Energy (WTE): Conventional and Plasma-assisted Gasification - Experimental and Modeling Studies
Lavaee, Mohammad Saleh
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Ever-increasing amounts of industrial and residential wastes and their environmental footprint dictates the need for effective Waste Management practices. Thermal waste processing technologies play an important role in energy recovery from the waste. Conventional and more importantly Plasma-assisted Gasification, an advanced thermal processing technology, have been introduced as promising and environmentally benign ways for energy utilization from biomass and municipal solid waste (MSW). This work aims to study the thermal technologies, which result in production of synthesis gas that is useful for heat and power generation; therefore, conventional and plasma-assisted gasification of biomass/MSW are reviewed. In addition, various economic, environmental and policy-related issues are examined in this study. From the experimental and modeling perspective, this study also reports on the work conducted to characterize the gasification process using a gasification reactor called Gasifier Experimenters Kit (GEK) level IV. Both the syngas quality and quantity have been investigated based on a variety of feedstock, such as wood charcoal, poplar and tamarack wood chips. Moreover, the composition of the gas has been analyzed using a Gas Chromatography (GC) unit and the exact concentrations of carbon monoxide, hydrogen, methane and nitrogen were measured. In this study, a thermochemical model based on the experimental setup (GEK IV) has also been developed in the AspenPlus® environment, an established simulation tool in chemical engineering and the energy industry. This model is capable of predicting the syngas composition, the energy required for the gasification reactions. A comparative analysis involving the experimental and simulation results is presented in this study.
Cite this work
Mohammad Saleh Lavaee (2013). Waste to Energy (WTE): Conventional and Plasma-assisted Gasification - Experimental and Modeling Studies. UWSpace. http://hdl.handle.net/10012/7461