Pyrolysis of municipal green waste a modelling, simulation and experimental analysis CQU.pdf (1.43 MB)
Pyrolysis of municipal green waste: A modelling, simulation and experimental analysis
journal contributionposted on 2022-10-25, 03:50 authored by Mohammed KabirMohammed Kabir, Ashfaque ChowdhuryAshfaque Chowdhury, Mohammad RasulMohammad Rasul
Pyrolysis is the thermo-chemical conversion of carbonaceous feedstock in the absence of oxygen to produce bio-fuel (bio-oil, bio-char and syn-gas). Bio-fuel production from municipal green waste (MGW) through the pyrolysis process has attracted considerable attention recently in the renewable energy sector because it can reduce greenhouse gas emissions and contribute to energy security. This study analyses properties of MGW feedstock available in Rockhampton city of Central Queensland, Australia, and presents an experimental investigation of producing bio-fuel from that MGW through the pyrolysis process using a short sealed rotary furnace. It was found from the experimentthat about 19.97% bio-oil, 40.83% bio-char and 29.77% syn-gas can be produced from the MGW. Then, a four-stage steady state simulation model is developed for pyrolysis process performance simulation using Aspen Plus software. In the first stage, the moisture content of the MGW feed is reduced. In the second stage, the MGW is decomposed according to its elemental constituents. In the third stage, condensate material is separated and, finally,the pyrolysis reactions are modelled using the Gibbs free energy minimisation approach.The MGW’s ultimate and proximate analysis data were used in the Aspen Plus simulation as input parameters. The model is validated with experimentally measured data. A good agreement between simulation and experimental results was found. More specifically,the variation of modelling and experimental elemental compositions of the MGW was found to be 7.3% for carbon, 15.82% for hydrogen, 7.04% for nitrogen and 5.56% for sulphur. The validated model is used to optimise the biofuel production from the MGW as a function of operating variables such as temperature, moisture content, particle size and process heat air–fuel ratio. The modelling and optimisation results are presented, analysed and discussed.
Number of Pages20
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External Author AffiliationsSchool of Engineering and Technology (2013- ); TBA Research Institute;