Monetizing and selection of sustainable tannery sludge-to-energy technology using a simulation-based novel integrated MCDM model along with life cycle Techno-Economic-ESG analysis

• Published in: Chemical engineering journal (Lausanne, Switzerland : 1996) Switzerland : 1996), 2024-11, Vol.499, p.155428, Article 155428
• Main Authors: Moktadir, Md. Abdul, Ren, Jingzheng, Ayub, Yousaf, Shi, Tao
• Format: Article
• Language: English
• Subjects: Energy technology selection; SDGs; Sustainability; Tannery sludge valorization; Techno-Economic ESG framework; Waste-to-energy
• ISSN: 1385-8947
• DOI: 10.1016/j.cej.2024.155428

[Display omitted] •Monetization and selection of sustainable tannery sludge-to-energy technology.•Proposed a novel simulation-based life cycle Techno-Economic-ESG framework.•‘Revenue per day with subsidy’ is identified as the most important criterion.•‘TS to power generation with carbon capture’ is recognized as sustainable TS-to-energy technology. Tannery sludge (TS) is a harmful, hazardous byproduct of the leather processing industry. This industrial solid waste generally undergoes uncontrolled landfilling and pollutes the surrounding environment, including water, air, and soil. Thus, to protect the environment and promote sustainable development goals (SDGs), an innovative TS valorization process design is urgently necessary. Nonetheless, the previous literature mainly focused on the physicochemical characteristics of TS and entirely ignored developing innovative processes for energy recovery. Further, there is a lack of study on developing life cycle techno-economic, environmental, social, and governance (T-E-ESG) frameworks for the TS-to-energy recovery scheme selection in an uncertain environment. To address these gaps, this study, for the first time, develops a simulation-based data-driven life cycle T-E-ESG framework for assessing TS-to-energy recovery schemes. A comprehensive fuzzy Delphi and hybrid weighting method (fuzzy-based best-worst method and level-based weight assessment) integrated with the fuzzy Bonferroni combined compromise solution (CoCoSo) model are proposed for evaluating TS-to-energy recovery schemes based on the T-E-ESG framework. The extended literature review identified thirty T-E-ESG factors, further verified using the fuzzy Delphi technique. The findings of the hybrid weighting method confirmed that the two most important factors are ‘Revenue per day with subsidy’ and ‘Energy efficiency’. The fuzzy Bonferroni CoCoSo analysis indicated ‘TS to power generation with carbon capture’ as the optimal solution for TS valorization as it received the highest relative significance score value of 2.2655, which ensured its’ suitability for real-time implication. The study findings may be used as a benchmark for the policymakers to establish optimal TS-to-energy recovery plant in developing countries.