Constructing an environmental, social, and governance (ESG) metrics framework for assessing medical waste...

As global crises escalate, the spotlight on sustainable development and Environmental, Social, and Governance (ESG) concerns intensifies. The amount of medical waste has reached an unprecedented level, and achieving a net-zero emissions target underlines the need for efficient waste management strategies. Despite various proposed valorization processes, there remains a critical need for an integrated assessment framework capable of evaluating their performance, efficiency, sustainability, and efficacy. This study proposed an innovative ESG metrics framework considering sixteen attributes for evaluating medical waste valorization alternatives, which aims to comprehensively address the multi-criteria nature of medical waste management, incorporating factors such as greenhouse gas emissions, energy efficiency, and more. In order to accommodate the varying perspectives of decision-makers ranging from optimistic to pessimistic, decomposed fuzzy sets (DFS) are utilized to address the inherent uncertainties in the assessment process. Integrating the Weighted Influence Nonlinear Gauge System (WINGS) and Combinative Distance-based Assessment (CODAS) under a DFS environment can determine criteria prominence, cause-effect relationships, and alternative rankings. More specifically, five alternatives for medical waste valorization: rotary kiln incineration, pyrolysis incineration, steam gasification, and plasma gasification with different sub-systems are considered in this study. The results indicate that eight criteria were reflected as causal criteria that directly influence process performance, and improving them may directly influence the remaining eight effectual criteria. Among five valorization alternatives, 'rotary kiln incineration with heat recovery and flue gas purification' is identified as the optimal solution under the ESG metrics. The proposed model's robustness and viability are validated through sensitivity analysis, comparative assessment, and correlation investigation with other DFS-based models. Finally, theoretical and policy implications are drawn to provide valuable insights for policymakers and other stakeholders in medical waste valorization.