Wang, D., Tang, Y.-T. orcid.org/0000-0001-5271-648X, He, J. et al. (2 more authors) (2024) A mini-review for identifying future directions in modelling heating values for sustainable waste management. Waste Management & Research: The Journal for a Sustainable Circular Economy. ISSN 0734-242X
Abstract
Global estimations suggest energy content within municipal solid waste (MSW) is underutilized, compromising efforts to reduce fossil CO2 emissions and missing the opportunities for pursuing circular economy in energy consumption. The energy content of the MSW, represented by heating values (HVs), is a major determinant for the suitability of incinerating the waste for energy and managing waste flows. Literature reveals limitations in traditional statistical HV modelling approaches, which assume a linear and additive relationship between physiochemical properties of MSW samples and their HVs, as well as overlook the impact of non-combustible substances in MSW mixtures on energy harvest. Artificial intelligence (AI)-based models show promise but pose challenges in interpretation based on established combustion theories. From the variable selection perspectives, using MSW physical composition categories as explanatory variables neglects intra-category variations in energy contents while applying environmental or socio-economic factors emerges to address waste composition changes as society develops. The article contributes by showing to professionals and modellers that leveraging AI technology and incorporating societal and environmental factors are meaningful directions for advancing HV prediction in waste management. These approaches promise more precise evaluations of incinerating waste for energy and enhancing sustainable waste management practices.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in Waste Management & Research: The Journal for a Sustainable Circular Economy is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | AI-based modelling; Heating value; circular economy; energy content; municipal solid waste; physiochemical analyses |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > School of Architecture and Landscape |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 24 Sep 2024 10:00 |
Last Modified: | 24 Sep 2024 11:17 |
Status: | Published online |
Publisher: | SAGE Publications |
Refereed: | Yes |
Identification Number: | 10.1177/0734242x241271042 |
Related URLs: | |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:217550 |