Integrated Waste-to-Energy Process Optimization for Municipal Solid Waste

Hossam A. Gabbar () and Muhammad Sajjad Ahmad
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Hossam A. Gabbar: Department of Energy and Nuclear Engineering, Faculty of Engineering and Applied Science, Ontario Tech University (UOIT), Oshawa, ON L1H 7K4, Canada
Muhammad Sajjad Ahmad: Department of Energy and Nuclear Engineering, Faculty of Engineering and Applied Science, Ontario Tech University (UOIT), Oshawa, ON L1H 7K4, Canada

Energies, 2024, vol. 17, issue 2, 1-20

Abstract: Within the past few decades, thousands of experiments have been performed to characterize urban waste and biomass to estimate their bioenergy potential and product identification. There is a need to develop an integrated process model based on the experimental literature, as well as simulations to obtain suitable products. In this study, municipal solid waste (MSW), including paper and plastic characterization and an integrated process model, were developed to optimize the final products in a reactor system. The process model has two modes, R&D and reactor control (RC), to obtain suitable products including bio-oil, char, and gases. A database was integrated based on thermokinetics, machine learning, and simulation models to optimize product efficiency. The experimental data include those obtained by thermogravimetric analysis and Fourier-transform infrared spectroscopy, which were linked to a pyrolysis experimental setup. Feedstock product mapping models were incorporated into the database along with the temperature, heating rates, elemental analysis, and final product concentration, which were utilized for the pyrolysis reactor setup. Product feasibility was conducted based on life cycle cost, affordability, and product efficiency. The present work will bridge the gap between experimental studies and decision-making based on obtained products under several experimental conditions around the world.

Keywords: process optimization; waste conversion; life cycle analysis; machine learning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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