Study of municipal solid waste treatment using plasma gasification by application of Aspen Plus
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Rishika Anilkumar
Abstract
Plasma gasification is a viable and efficient technique for handling solid waste, including hazardous waste, while also holding the potential for energy recovery. The objective of this study is to analyze the treatment of municipal solid waste (MSW) using plasma gasification by application of Aspen Plus software. An earlier proposed model was used to analyze the effect of employing different types of gasifying agents as plasma gas, on the composition of syngas produced. The lower heating value, cold gasification efficiency and carbon conversion efficiency were calculated and compared in each case. A sensitivity analysis study was also carried out to observe the effect of variation in plasma gas flow rate and feed flow rate on the composition of syngas generated. The capital, operational and maintenance costs of the process were determined using existing correlations. For a feed rate of 20,000 kg per hour of MSW, the highest yield of syngas (CO (33.48 %), and H2 (34.30 %) with the highest LHV (7.9 MJ/N-m3)) were produced when air was employed as plasma gas. The cold gas efficiency and the carbon conversion efficiency were at their peak when air was used as the gasifying agent. The sensitivity analysis revealed that as the flow rate of plasma gas increases syngas production decreases while the increase in MSW flow rate results in an increase in syngas production. Additionally, the cost analysis revealed that for a plasma gasification plant that can handle 500 tons of MSW per day, the estimated capital and annual operational and maintenance costs are $125,496,721 and $9,833,892 respectively.
Acknowledgments
We acknowledge Vellore Institute of Technology, Vellore for providing us with the research facility including Aspen software access.
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Research ethics: This is original work carried out by the authors. IRB Approval not required.
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Informed consent: Not applicable.
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Author contributions: Rishika Anilkumar and Anil Kumar Vinayak – Aspen simulation; Bandaru Kiran – data collection; Anand V P Gurumoorthy – conceptualization, editing and overall supervision.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interests: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: All data generated or analyzed during this study are included in this published article [and its supplementary information files].
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/cppm-2024-0053).
© 2024 Walter de Gruyter GmbH, Berlin/Boston
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Articles in the same Issue
- Frontmatter
- Research Articles
- Comparative study of deterministic and stochastic optimization algorithms applied to the absorption of CO2 by alkanolamine solution
- Modeling the kinetics, energy consumption and shrinkage of avocado pear pulp during drying in a microwave assisted dryer
- Study of municipal solid waste treatment using plasma gasification by application of Aspen Plus
- Numerical analysis of segregation of microcrystalline cellulose powders from a flat bottom silo with various orifice positions
- Prediction of syngas production in the gasification process of biomass employing adaptive neuro-fuzzy inference system along with meta-heuristic algorithms
- Industrial high saline water desalination by activated carbon in a packed column- an experimental and CFD study
- Dual-loop PID control strategy for ramp tracking and ramp disturbance handling for unstable CSTRs
- A control perspective on hybrid membrane/distillation propane/propylene separation process
- Prediction of surface heating effect on non-equilibrium homogeneous condensation in supersonic nozzle using CFD method
- Modeling the emitted carbon dioxide and monoxide gases in the gasification process using optimized hybrid machine learning models
