(428b) Ecological Network Analysis and Information Theory to Evaluate the Performance of Circular Economy Designs

Circular Economy (CE) is an alternative business model to the conventional take-make-waste Linear Economy (LE) model, where products are reused, redistributed, refurbished, remanufactured, and recycled at their End of Life (EoL). Despite the huge efforts across the globe for moving from LE to CE designs, there is a lack of proper metrics that capture and evaluate the circularity, resilience, and robustness of different CE designs. In the present work, we develop a set of metrics based on Ecological Network Analysis (ENA) and Information Theory (IT) and apply these metrics on CE designs. We use eight metrics based on ENA and IT for trophic chains which have high potential to be used for a meaningful evaluation of the performance of CE systems, i.e., (1) Total System Throughput (TST), (2) Mean Trophic Level (MTL), (3) Detritivory : Herbivory ratio (D : H) (4) Ascendency (A), (5) Reserve (φ), (6) Development Capacity (DC), (7) Relative Ascendency (α), and (8) Robustness (R). In addition, we propose guidelines and/or modifications to develop metrics with meaningful insights for evaluating CE performance. We demonstrate the usefulness of these metrics in two “toy problem” examples. In the first toy problem, we develop one LE and four CE scenarios indicating different recovery strategies in CE systems, i.e., Reuse, Redistribute, Refurbish (or Remanufacture) and Recycle. Qualitatively speaking, in the case of equal recovery efficiency, CE strategies with inner (tighter) loops (e.g., Reuse) are more favorable than outer loops (e.g., recycle). Thus, in this toy problem, we study whether ENA-based metrics can be used to quantitatively capture the differences between circular strategies through implementing loops with different tightness in the system. We assume consumer’s demand in all scenarios are the same, and we set a fixed 50% recovery efficiency for all CE scenarios (50% of the waste is recovered after use phase and is circulated). Moreover, we study whether metrics based on IT can demonstrate the difference between CE systems over LE systems with respect to the resilience and robustness of the system. Results indicate that all CE designs have higher resilience and robustness compared to the LE scenario, which indicates that by applying circular strategies, we can develop a more robust economy that is resilient to unprecedented perturbations. In addition, in CE scenarios, MTL and D:H ratio is the highest for the Reuse scenario, and it decreases as we implement outer cycles for recovery. This indicates that the Reuse scenario is less dependent on the primary resources and lower trophic levels compared to other CE scenarios, which shows advantage of the Reuse scenario over other CE scenarios in terms of resource consumption. Conversely, TST decreases as outer cycles are implemented in the CE design with the Reuse scenario having the lowest TST. This indicates that less system activity is needed in the reuse scenario in order to meet consumer’s demand. This could indirectly indicate less resource consumption and environmental impacts since the scale of the industrial activity is lower. In the second toy problem, we study the importance of diversity in available upstream and EoL options for feedstock provision and waste handling and recovery of a product. More specifically, we study the possible tradeoffs between circularity efficiency and resilience in CE systems. In one scenario, we assume that there is only one upstream process and one EoL option that are highly efficient (we define efficiency as the amount of resource needed to produce one unit of flow of final product). In the second scenario, we introduce an alternative upstream and EoL options in addition to those that are available in the first scenario, which are less efficient compared to the already available options for upstream and EoL processes. In other words, in this scenario, there are two upstream processes for feedstock provision and two EoL processes for waste handling and treatment, and the total efficiency of this system is lower compared to the first scenario. However, despite the lower efficiency of the second scenario, this scenario demonstrates a higher resilience (φ) and robustness (R) due to the implementation of a diverse set of EoL and upstream processes. This indicates that efforts toward designing CE systems should not be only focused on implementing and developing emerging technologies with highest efficiency. Instead, implementation of a diverse set of emerging technologies at different life cycle stages of a CE can help build robust and resilient supply chain solutions. Finally, we apply the metrics on polyethylene terephthalate (PET) supply chains in order to first, demonstrate the applicability of the metrics for a real-world system, and secondly, to evaluate the circularity and resilience of PET supply chains and guide its development toward a sustainable and resilient circular economy.