The Potential of AHP-TOPSIS and Fuzzy-TOPSIS Hybrid MCDM Techniques for Evaluation of Mature Landfill Leachate Treatment Technologies

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This study employed integrated AHP-TOPSIS and Fuzzy-TOPSIS multi-criteria decision-making methods to evaluate landfill leachate treatment technologies, finding hybrid approaches superior to conventional methods.

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This withdrawn Research Square preprint describes the evaluation of mature landfill leachate treatment technologies using hybrid multi-criteria decision-making approaches, specifically AHP-TOPSIS and fuzzy-TOPSIS. The paper’s available text does not include study details or results, because the full manuscript was withdrawn by the authors for corrections, and the authors explicitly request that it not be cited as a reference. No competing interests were reported, but this withdrawal substantially limits access to the methods, outcomes, and any stated caveats. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Leachate is a noxious liquid with a high concentration of organic and inorganic substances produced by interactions of several environmental factors in a landfill. It is quite toxic to groundwater, surface water, and the environment; thus, it must be treated thoroughly before disposal. There are a few traditional and advanced technologies that exist for the treatment of landfill leachate, which are broadly categorized as biological, physicochemical, and hybrid technologies. According to the literature, every technology has pros and cons, and no single treatment method is sufficient to provide the required efficiency. Thus, selecting the optimal methodology for landfill leachate treatment requires a multi-criteria decision-making (MCDM) approach that incorporates several criteria and alternatives. In the research, integrated AHP-TOPSIS and integrated Fuzzy-TOPSIS approaches were employed to evaluate their potential to rank the available treatment options and to determine the optimal treatment strategy for optimal treatment of leachate. In this decision-making process, ten criteria (the removal efficiency of chemical oxygen demand (COD), biochemical oxygen demand (BOD), ammonia nitrogen, and heavy metals, operation and maintenance cost, installation time, treatment time, environmental effect, simplicity of operation and maintenance, and treatment plant flexibility with dependability) were considered. The weights of the considered criteria were determined using the AHP and Fuzzy techniques. A combination of two biological techniques, a combination of physical and biological methods, and an integration of the physicochemical method with biological methods were included among the considered alternatives (treatment approaches). The alternatives were prioritised with the help of integrated decision-making processes from a total of fifteen different treatment options. The findings indicate that membrane biological reactor (MBR) (A8), advanced oxidation process (AOPs) + MBR (A10), and coagulation-flocculation (A13) and up-flow anaerobic sludge blanket reactor (UASB) + Membrane filtration (MF) (A1) (A8>A10>A13>A1) are the first four treatment approaches as determined by only AHP, integrated AHP-TOPSIS, and Fuzzy-TOPSIS methodology. The calculated results indicate that the hybrid methods are better suited than conventional treatment approaches for toxic landfill leachate treatment.
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WITHDRAWN: The Potential of AHP-TOPSIS and Fuzzy-TOPSIS Hybrid MCDM Techniques for Evaluation of Mature Landfill Leachate Treatment Technologies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article WITHDRAWN: The Potential of AHP-TOPSIS and Fuzzy-TOPSIS Hybrid MCDM Techniques for Evaluation of Mature Landfill Leachate Treatment Technologies Aishi Nath, Animesh Debnath This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3890699/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Editorial Note The full text of this preprint has been withdrawn by the authors while they make corrections to the work. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author. Editorial notes are used to provide important context regarding the topic of a preprint or to alert readers to potential issues concerning that preprint or a downstream publication associated with it. For more information on editorial notes, see our Editorial Policies . Abstract The full text of this preprint has been withdrawn by the authors while they make corrections to the work. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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