Dumping waste and dumping sites pose significant environmental issues with serious implications for human health, the environment, and wildlife. Dumping grounds can also cause difficulties such as leaching, which occurs when waste chemicals seep into the soil and damage groundwater resources. The vast quantity of dumped waste plastic is a major source of energy in the form of gas, fuel, and electricity. The selection of the most appropriate waste-to-energy (WtE) technology affects the dumped waste because it allows for reduced greenhouse gas emissions, diverts dumpsites, generates energy, supports the circular economy, and lowers post-recycling pollution. This complex selection problem requires careful consideration of uncertainties from multi-perspective analysis, vague information, and imprecision in decisions. The stratified fuzzy multi-criteria decision making approach is suitable for addressing different states of events, uncertain data, and sustainable choice selection. Hence, we improved the intuitionistic analytical hierarchical process with a stratified targeting concept for multi-level criteria importance and coupled it with weighted aggregated sum product assessment for ranking WtE techniques. The preferences of experts are characterized using intuitionistic fuzzy preference relations. An empirical study on dumped plastic waste and dumpsite management discovered that plasma technology becomes a more feasible option by satisfying stratification and is more effective in clearing landfills by recovering energy. The comparative analysis, sensitive analysis, and Spearman's rank correlation validate the proposed methodology, and this method seems to be a new dimension to handle ecological issues.& COPY; 2023 Elsevier B.V. All rights reserved.
An advanced stratified decision-making strategy to explore viable plastic waste-to-energy method: A step towards sustainable dumped wastes management / Kang, D.; Manirathinam, T.; Geetha, S.; Narayanamoorthy, S.; Ferrara, M.; Ahmadian, A.. - In: APPLIED SOFT COMPUTING. - ISSN 1568-4946. - 143:(2023), p. 110452. [10.1016/j.asoc.2023.110452]
An advanced stratified decision-making strategy to explore viable plastic waste-to-energy method: A step towards sustainable dumped wastes management
Ferrara M.Supervision
;
2023-01-01
Abstract
Dumping waste and dumping sites pose significant environmental issues with serious implications for human health, the environment, and wildlife. Dumping grounds can also cause difficulties such as leaching, which occurs when waste chemicals seep into the soil and damage groundwater resources. The vast quantity of dumped waste plastic is a major source of energy in the form of gas, fuel, and electricity. The selection of the most appropriate waste-to-energy (WtE) technology affects the dumped waste because it allows for reduced greenhouse gas emissions, diverts dumpsites, generates energy, supports the circular economy, and lowers post-recycling pollution. This complex selection problem requires careful consideration of uncertainties from multi-perspective analysis, vague information, and imprecision in decisions. The stratified fuzzy multi-criteria decision making approach is suitable for addressing different states of events, uncertain data, and sustainable choice selection. Hence, we improved the intuitionistic analytical hierarchical process with a stratified targeting concept for multi-level criteria importance and coupled it with weighted aggregated sum product assessment for ranking WtE techniques. The preferences of experts are characterized using intuitionistic fuzzy preference relations. An empirical study on dumped plastic waste and dumpsite management discovered that plasma technology becomes a more feasible option by satisfying stratification and is more effective in clearing landfills by recovering energy. The comparative analysis, sensitive analysis, and Spearman's rank correlation validate the proposed methodology, and this method seems to be a new dimension to handle ecological issues.& COPY; 2023 Elsevier B.V. All rights reserved.File | Dimensione | Formato | |
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