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New performance correlations of municipal solid waste gasification for sustainable syngas fuel production

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Abstract

Municipal solid waste (MSW) is one of the most important carbonaceous solid waste collected by the municipality that includes residential, industrial, institutional, commercial and construction waste. In this work, modelling and simulation analyses using ASPEN plus simulation software integrated with response surface methodology (RSM)-based optimization method are used to investigate the performance of MSW gasification process. The principal objective is to develop new correlations for the key performance indicators of MSW gasification (hydrogen H2 and carbon monoxide CO contents in the syngas, cold gasification efficiency CGE, and carbon conversion CC) versus three main input factors (gasification temperature 600–1000 \(^\circ{\rm C}\), equivalence ratio 0.1–0.5, and oxygen content in air 21–100%). The MSW gasification model was developed using Aspen Plus and the results were validated with experimental data. The comparison showed a good agreement between the simulation and experimental results. RSM based on central composite design (CCD) and analysis of variance (ANOVA) were used to optimize the MSW gasification process. New correlations for the output variable (H2, CO, CGE, and CC) of the gasification process were presented by second-order polynomial equations. The results showed that the coefficients of determination \({R}^{2}\) for the predicted model for H2, CO, CGE, and CC were respectively 0.9913, 0.9630, 0.9618 and 0.9730 (high accuracy of the new proposed correlations or the regression models). The optimized gasifier operating parameters to maximize the H2, CO, CGE, and CC are T = 1000 \(^\circ{\rm C}\), ER = 0.132 and oxygen = 100%. The optimum values for the H2, CO, CGE, and CC are 44.86%, 53.8%, 95.04%, and 79.96%, respectively. The results showed that the most significant factors affecting the H2, CO, CGE, and CC in order of importance are respectively gasification temperature, oxygen percentage and equivalence ratio.

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Abbreviations

\(\mathrm{Adj}-{\mathrm{R}}^{2}\) :

Adjusted regression coefficient

\({\left(\frac{\mathrm{Air}}{\mathrm{Fuel}}\right)}_{\mathrm{Actual}}\) :

Actual air to fuel mass ratio, kg/kg

\({\left(\frac{\mathrm{Air}}{\mathrm{Fuel}}\right)}_{\mathrm{Stoic}}\) :

Stoichiometric air to fuel mass ratio, kg/kg

f:

Response surface

\(\mathrm{HHV}\) :

Higher heating value, MJ/kg

LHV:

Lower heating value, MJ/kg

\({\mathrm{C}}_{\mathrm{Syngas}}\) :

Carbon in the syngas

\({\mathrm{C}}_{\mathrm{feed}}\) :

Carbon in the feed

\({\dot{\mathrm{m}}}_{\mathrm{MSW}},{\dot{\mathrm{m}}}_{\mathrm{feed}}\) :

Mass flow of MSW, kg/h

\({\dot{\mathrm{m}}}_{\mathrm{syngas}}\) :

Mass flow of syngas, kg/h

\(N\) :

Number of runs

\(n\) :

Number of independent variables

\({n}_{c}\) :

Number of central points with replicates or repeated runs at the centre

\({\mathrm{P}}_{\mathrm{in}}\) :

Power input to the gasifier, kW

\({\mathrm{P}}_{\mathrm{out}}\) :

Power output from the gasifier, kW

\({\mathrm{R}}^{2}\) :

Regression coefficient

SD:

Standard deviation

\({\mathrm{x}}_{\mathrm{n}}\) :

Set of independent variables (factors)

\({\mathrm{X}}_{\mathrm{i }},{\mathrm{X}}_{\mathrm{j}}\) :

Coded values of the input variables

\({y}_{i}\) :

Mass fraction of species i in the product gas

\({y}_{C}\) :

Mass percentage of carbon in ultimate analysis of original feed, %

Y:

Response variable of the system

\(\alpha\) :

Axial distance

\({\upbeta }_{\mathrm{o}}\),\({\upbeta }_{\mathrm{i}}\) \({\upbeta }_{\mathrm{ii}}\) :

Constant, linear and quadratic coefficients

\({\upbeta }_{\mathrm{ij}}\) :

Interaction between the coefficients

\(\upeta\) :

Overall efficiency, %

\(\upvarepsilon\) :

Random error

ER:

Equivalence ratio

CC:

Carbon conversion efficiency, %

CCD:

Central composite rotatable design

CGE:

Cold gas efficiency, %

MSW:

Municipal solid waste

RSM:

Response surface methodology

ER:

Equivalence ratio

CC:

Carbon conversion efficiency, %

CCD:

Central composite rotatable design

CGE:

Cold gas efficiency, %

MSW:

Municipal solid waste

RSM:

Response surface methodology

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Funding

The authors gratefully acknowledge the financial support by the University of Sharjah and the Research Institute for Sciences and Engineering (RISE) – Targeted Research Project (Plasma Gasification Project Ref Number 1702040686).

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Authors and Affiliations

  1. Sustainable Energy Development Research Group, Research Institute for Science and Engineering, University of Sharjah, Sharjah, United Arab Emirates

    Amira Nemmour & Chaouki Ghenai

  2. Sustainable and Renewable Energy Engineering Department, College of Engineering, University of Sharjah, Sharjah, United Arab Emirates

    Abrar Inayat & Chaouki Ghenai

  3. Mechanical Engineering Department, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates

    Isam Janajreh

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  1. Amira Nemmour
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Contributions

Amira Nemmour: software, formal analysis, methodology, validation, writing – review & editing.

Abrar Inayat: methodology, validation, writing – review & editing.

Isam Janajreh: investigation, validation, writing – review & editing.

Chaouki Ghenai: conceptualization, formal analysis, investigation, methodology, supervision, project administration, validation, writing – review & editing, and securing funding.

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Correspondence to Chaouki Ghenai.

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Nemmour, A., Inayat, A., Janajreh, I. et al. New performance correlations of municipal solid waste gasification for sustainable syngas fuel production. Biomass Conv. Bioref. 12, 4271–4289 (2022). https://doi.org/10.1007/s13399-021-02237-8

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