A decision support framework for safe and sustainable by-design practices promoting circularity in waste-to-energy supply chains

Advancing a safe and sustainable waste-to-energy supply chain is predominant for achieving a circular business model. However, establishing such a supply chain requires addressing its inherent complexities and developing mitigation strategies for implementing safe and sustainable by-design practices. While earlier research has mainly focused on sustainable chemicals and materials for promoting sustainable by-design practices, the sustainable waste-to-energy supply chain has been largely overlooked. This study systematically evaluates challenges considering associated uncertain future events and examines mitigation strategies for the practical implementation of safe and sustainable by-design practices. To achieve this, a novel decision support framework is developed, integrating a trapezoidal fuzzy-based stratified best-worst method, quality function deployment, and a mixed-integer linear programming model. Data is collected from domain experts to the framework's applicability. The findings reveal that the ‘environmental’ dimension poses the most critical sustainability challenge, with the ‘complexity of pollution prevention in WtE life cycle’ identified as the most significant sub-challenge. The results also indicate ‘Optimize waste-to-energy production to minimize emissions’ as the most impactful mitigation strategy. Furthermore, the model demonstrates that within budgetary and time constraints, nine out of fifteen mitigation strategies can be simultaneously implemented to mitigate the examined challenges effectively. These findings offer valuable insights for policymakers for real-time implementation of sustainable by-design practices. Moreover, these findings may have global implications for other supply chains, such as food processing, chemicals, pharmaceuticals, and garments, in their efforts to successfully adopt sustainable by-design practices.