A novel assessment framework for circular urban areas with its application to a Swedish municipality

As local authorities worldwide increasingly embrace the circular economy (CE) concept, it is crucial to equip decision-makers with the necessary tools to design and monitor effective urban-level circular strategies. With this study, we introduce a novel framework for assessing the urban metabolism and circularity of urban areas to support decision-making within the CE context. The framework integrates a structured dashboard of 27 CE indicators with the urban metabolic life cycle assessment approach (UM-LCA), which couples Material and Energy Flow Analysis (MEFA) with Life Cycle Assessment. We developed this framework building on insights from two prior studies, where we explored the utility of MEFA and UM-LCA as decision-support tools within the CE context, and by identifying CE indicators in the literature based on the RACER (Relevant, Acceptable, Credible, Easy, Robust) criteria. To demonstrate the applicability and utility of the framework and examine its strengths and weaknesses, we applied the framework to the Umeå urban area in Sweden. The application of the framework provided a detailed quantitative analysis of material and energy flows and environmental impacts per sector within the urban area, indicating key sectors in terms of resource use, waste generation and environmental performance. It also provided a comprehensive evaluation of Umeå's current level of CE development, highlighting areas of strength and improvement, and offered a prospective assessment of the environmental implications of potential future circular strategies. Overall, the framework proved to be a valuable tool for generating detailed insights into material and energy flows, environmental impacts and circularity, which can be particularly useful for the design, monitoring and evaluation of urban-level circular strategies. However, the application also revealed some weaknesses of the framework, including its significant data demands, complexity and limited capacity to capture social and economic aspects, suggesting areas for further research to fully unlock its potential as a decision-support tool.