Thermal decomposition kinetics of some aegean lignites and biomasses and desulphurization of gediz lignite

Today, most of the energy resources are obtained from fossil fuels. However, the decreasing reserves of fossil fuels and their environmental damages have become an important problem. Conventional energy production from coal causes environmental problems such as acid rain, emission of harmful gases such as sulphur and nitrogen. This situation has increased the focus on clean coal technologies and finding sustainable energy sources such as biomass. Within the scope of this doctoral thesis, firstly, the thermal degradation behaviour, oxidation characteristics and solid state reaction kinetics parameters of lignites from Soma and Gediz regions and palm and olive seed wastes, which are commonly found in our country, were determined. The effects of biomass and coal components on the pyrolysis process were investigated at four different heating rates by thermogravimetric analysis (TGA) at a maximum temperature of 1000 oC. Volatiles, functional groups and mineralogical changes formed and lost during the reaction were characterised by FT-IR and XRD analyses. Kissinger-Akashiro-Sunose (KAS) and Ozawa-Flynn-Wall (OFW) model independent approaches were used for kinetic calculations based on TGA data. Gediz region coal, which will be used in desulphurization studies, is a lignite with high quality coal deposits with very high thermal value. However, it has limitations in industrial use due to its high sulphur content (7.24%). It is aimed to obtain clean coal and increase the usability of coal by removing impurities and sulphur from Gediz coal considering environmental concerns and these limitations. For this purpose, leaching method with H2O2/H2SO4 solution was applied to remove sulphur from the coal structure. After calculating the sulphur removal efficiencies with the determined reaction parameters, the optimum operating conditions were determined by experimental design with Taguchi and Response Surface Method. Best operating conditions for sulphur removal were determined by statistical analysis of variance and the results were tested by ANOVA.