A Decision Support System for Circular Economy Transition in Historical Small Towns

Guest Editors

About this Special Issue

This Special Issue is part of the PRIN 2022 Project "H-SMA-CE: A Decision Support System for Circular Economy Transition" (CUP: J53D23009390006 — CI: 2022JZLL7J).

It aims at gathering scientific contributions in order to define a framework for promoting the exploration of the theme of circular economies in historical small towns, with a view to optimizing waste and energy flow management and enhancing local features and particularities. Currently, whilst different CE models have been proposed, they are difficult to apply in real-life contexts. Among the main issues are problems linked to the lack of integration (e.g., including context, models, indicators, solutions, strategy) and dynamism in the used approaches. Here, the static view includes an inventory (collection of qualitative and quantitative data on input and output flows), and the design and assessment of methods and tools (e.g., life cycle-based ones), operating according to a "reference flow" of a supply chain (Kennedy et al., 2007). Other studies deal with the construction of indicators, though with serious gaps at both the micro- and meso-level.

This Special Issue seeks papers providing an in-depth analysis of the literature concerning circular economies (CEs), urban metabolism (UM), urban symbiosis (US) methods/tools, best practices, and circularity metrics. Furthermore, it seeks contributions on territorial context considering the flows, chains, and actors involved in a representative HST. Contributions should feature relevant, state-of-the-art evidence.

Case studies carrying out circular economy interventions, focused on waste flows and their potential use for energy generation, as well as their average costs and benefits, will be considered (performed on the reference HST). Papers should highlight proposals for optimal interventions and the definition of a set of CE indexes which allow for the identification of circularity gaps.

Finally, papers presenting innovative models and simulations, specifically those given through a spreadsheet-based DSS model, and other systems are also welcome.

Keywords

Published Papers (3)