Multi-level sustainability assessment of nature-based resource recovery systems

Abstract

The sustainable management of high-volume (HV) waste such as dredgings and mining waste remains a challenge due environmental, logistical, and economic challenges. Nature-based solutions are increasingly being explored as promising enablers of circular economy strategies for HV waste flows. Given the several spatial scales of planning and the plethora of stakeholders involved with HV waste management, this thesis focused on developing multi-level decision-making frameworks to quantify the sustainability benefits of nature-based secondary resource recovery at multiple levels under uncertainty ensuring robust and reliable decision-making.

The research reported in thesis is divided into three parts. The first focuses on the meso-level sustainability assessment through the integration of ecosystem services into life cycle assessment (ES-LCA) to improve the sustainability evaluation of nature-based solutions. The proposed framework addresses the absence of a comprehensive ES-LCA approach by incorporating ecosystem services into traditional LCA methodologies. An illustrative case study involving the London Olympic Park demonstrates the benefits of this approach, highlighting improvements in ecosystem service delivery and cost-effectiveness compared to conventional remediation methods. Sensitivity and qualitative uncertainty analyses validate the robustness of the framework, suggesting its potential for broader application in sustainability assessments.

The second part of the thesis presents a novel quantitative uncertainty assessment protocol for integrated ES-LCA of nature-based solutions. This protocol enhances decision-making by systematically evaluating the uncertainty inherent in environmental assessments. Using the London Olympic Park as a case study, the protocol demonstrates the identification of key parameters influencing ES-LCA outcomes and provides guidelines for implementing global sensitivity analysis. The results underscore the importance of considering uncertainty in sustainability assessments to ensure reliable and informed decision-making for nature-based solutions.

The third part of the thesis focuses on macro-level sustainability assessment through development of a robust multi-objective optimization framework for assessing the macro-level sustainability of nature-based secondary resource recovery from HV waste under climate change uncertainty. The framework integrates economic, social, and environmental objectives using mixed-integer linear programming to evaluate the resilience of proposed solutions. A national-scale case study of legacy mining waste illustrates the framework's application, revealing significant benefits in economic feasibility and climate resilience. The findings highlight the necessity of holistic approaches and adaptive strategies in long-term planning for sustainable waste management.