Summary
Circularity metrics are useful for empirically assessing the effects of a circular economy in terms of profitability, job creation, and environmental impacts. At present, however, there is no ...standardized method for measuring the circularity of products. We start by reviewing existing product‐level metrics in terms of validity and reliability, taking note of theoretically justified principles for aggregating different types of material flows and cycles into a single value. We then argue that the economic value of product parts may constitute a useful basis for such aggregation; describe a set of principles for using economic value as a basis for measuring product circularity; and outline a metric that utilizes this approach. Our recommendation is to use the ratio of recirculated economic value to total product value as a circularity metric, using value chain costs as an estimator. In order to protect value chain actors’ sensitive financial data and facilitate neutrality regarding outsourcing or insourcing, we suggest a means to calculate product‐level circularity based on sequential approximations of adding one product part and activity at a time. We conclude by suggesting potential avenues for further research, including ways in which the proposed metric can be used in wider assessments of the circular economy, and ways in which it may be further refined.
This article evaluates the synergies between circularity assessment and Life Cycle Assessment (LCA) by investigating their alignments, misalignments, and challenges in addressing sustainability. The ...analysis emphasizes the significance of a multi-level approach, positioning these methods at various levels, including philosophy, strategy, assessment, and communication. The findings demonstrate that both LCA and circularity assessment can serve as sustainability assessment methods for circularity strategies, despite existing gaps. However, neither approach can provide a complete picture of a system's environmental performance on its own. Data availability, diverse assumptions, spotlights and shadows (highlighted and neglected elements), multiple life cycles, products, functions, strategies, and as well as temporal aspects are identified as the main challenges in addressing sustainability. This article provides recommendations based on the lessons learned from each approach, suggesting the integration of their strengths and addressing challenges to achieve a comprehensive understanding of environmental sustainability and make informed decisions for a circular and sustainable future. These recommendations include using function-based models and the principles of prospective and dynamic LCAs for the development of future circularity assessments. Additionally, circularity assessment can be used to establish LCA models, aiding in identifying hotspots during the goal and scope definition, and determining allocation and weighting factors in both Life Cycle Inventory (LCI) and Life Cycle Impact Assessment (LCIA).
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•The synergies between circularity assessment and LCA are reviewed•The gaps and challenges of both assessments are analyzed•How to handle multiplicity in circularity assessment and LCA is explained•The temporal aspects and its challenges in LCA are elaborated•Possibilities for diversifying circularity assessment and LCA are discussed
This open access book attempts to provide a perspective on the circularity assessment at different levels of the systemic hierarchy and advocates better resource management for a sustainable future. ...It demonstrates how relevant circularity indicators are used for quantifying the extent of circularity of each level. Illustrative case studies that discuss the process of quantitatively interpreting progress towards circularity are provided. This work caters to a broad readership inclusive of governance, basic research, engineering, and business stakeholders. The conclusion signifies the role of consumer community in achieving circularity.
Purpose
In a context where the transition to a circular economy is increasingly required, it is necessary to clarify the relationship between sustainability and circularity. In this commentary we ...summarise what are circularity indicators and what is LCA (Life Cycle Assessment), and we discuss their potential role in improving circular decision making.
Methods
Based on literature, a focus on how circularity indicators and LCA could be used in circular decision making is presented. Moreover, an analysis of recent studies has been carried out to identify the relationship between LCA and circularity indicators.
Results and discussion
We can state that no authors have concluded that circularity indicators can be used alone to choose the best option in circular economy projects. This is because the circularity indicators only provide a partial view on the environmental performance of a system. At the same time, it appears that the circularity indicators are easier to communicate, and a high degree of circularity could help to build good relationships with customers and increase reputation among stakeholders, as well as to have an easier access to funding.
Conclusions and recommendations
At the end, we propose a procedure to include both the LCA and the circularity measurement in the assessment of circular economy strategies. While still at an early stage of conceptualisation, it gives an idea on how to integrate environmental sustainability aspects into circular economy initiatives.
Circularity assessment and monitoring have become a core research topic in academic societies, as well as a basis for developing economic development measures. Despite the circular economy (CE) being ...a game-changer for the agro-food sector, little effort has been made to identify its level of circularity. In order to achieve the transition to a CE, stakeholders and industry professionals must be provided with appropriate indicators, tools and methods. Due to the complexity of CE measurement, it is necessary to devise indicators, methods and tools that are tailored to each industry. The objective of this review article is to identify the indicators and tools required for assessing the level of circularity in olive oil mills. This research collected data regarding available CE indicators at the company and product levels, as well as those applicable to the agro-food industry. As a result, a list of indicators appropriate to the needs of olive mills has been developed that could be used to measure the level of implementation of circular practices in this industry. The main conclusion reached is that once indicators are defined, they should be compared or combined with life cycle assessment methodologies to determine their applicability and effectiveness. There is no doubt that olive oil plays a significant economic, environmental and social role throughout the Mediterranean region. Hence, evaluating the CE is essential to demonstrate the effectiveness of current policies.
Modern society needs to address the major societal challenges related to human health, safety and the environment by developing new safe and environmentally friendly polymers and biopolymer-based ...materials and technologies. With this in mind, the present overview provides an integrated approach to understanding when and how polymers and biopolymers are subject to degradation phenomena throughout their life cycle, taking into account their specific conditions of synthesis, manufacture, use and end-of-life. It also discusses what kind of stabilization strategies could be applied to prevent the degradation of polymers and biopolymers.
The term “degradation” is therefore used in a broad sense to include all processes that lead to a change in the properties and overall performance of polymers and biopolymers, from synthesis to end-of-life. The main experimental techniques used to follow the degradation phenomena of polymers and biopolymers and to evaluate their structural and property changes are also briefly mentioned.
The work attempts to provide points for reflection on the importance of understanding degradation, which is directly related to the failure of polymers and biopolymers in-service conditions. It also briefly discusses the application of a controlled degradation strategy to solve the negative environmental impact of polymers and biopolymers and to implement an integrated circular approach for material recovery. Therefore, today with significant advances in polymer science and technology, understanding, tuning and controlling the degradation of polymers and biopolymers is of paramount importance, especially considering the environmental sustainability and biocompatibility of the degradation products.
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Critical literature review coupled with conceptual analysis provides a holistic framework for measuring a product's circularity performance based on its integrated contribution to the ...operationalization of various configurations of circular economy (CE) strategies. The following main results were obtained. First, we outline the “Сlosing–Slowing and Future–Past” (“CSFP”) quadrant model (“CSFP” quadrant model) of CE-related product attributes and the circular product categories derived as findings of our previous study in the form of modifications to develop a product-level circularity metric. Second, we propose fifteen product circularity profiles with singular and configurative CE strategy-related contributions building on the “СSFP” model and circular product categories. Third, we quantify the 6Rs (reuse, repair, refurbishment, remanufacturing, repurposing, recycling) for the strategy-related contributions derived from the “CSFP” quadrant model to propose a product circularity data profile coupled with a metrical scale for measuring product circularity performance and visualizing quantified circular contributions. To trial, showcase and validate the relevance of the developed model and associated visualization tool, we conduct two case studies comparing the circularity performances of smartphones and packaging bags, respectively. Companies can use the proposed framework as a maturity scale to enhance the circularity performance of a product. This work contributes to a more accurate measurement of product circularity performance and a sharper understanding of its integrated contribution to circular strategies.
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Spatially explicit capture–recapture (SECR) models have emerged as one solution to the problem of estimating the population density of mobile and cryptic animals. Spatial models embody assumptions ...regarding the spatial distribution of individuals and the spatial detection process. The detection process is modeled in SECR as a radial decline in detection probability with distance from the activity center of each individual. This would seem to require that home ranges are circular. The robustness of SECR when home ranges are not circular has been the subject of conflicting statements. Ivan et al. previously compared the SECR density estimator to a telemetry-scaled non-spatial estimator. I suggest that the apparent non-robustness of SECR in their study was a simulation artefact. New simulations of elliptical home ranges establish that the SECR density estimator is largely robust to non-circularity when detectors are spread in two dimensions, but may be very biased if the detector array is linear and home ranges align with the array. Transformation to isotropy reduces bias from designs of intermediate dimension, such as hollow square arrays. Possible alignment of home ranges should be considered when designing detector arrays.
The extension of sample entropy methodologies to multivariate signals has received considerable attention, with traditional univariate entropy methods, such as sample entropy (SampEn) and fuzzy ...entropy (FuzzyEn), introduced to measure the complexity of chaotic systems in terms of irregularity and randomness. The corresponding multivariate methods, multivariate multiscale sample entropy (MMSE) and multivariate multiscale fuzzy entropy (MMFE), were developed to explore the structural richness within signals at high scales. However, the requirement of high scale limits the selection of embedding dimension and thus, the performance is unavoidably restricted by the trade-off between the data size and the required high scale. More importantly, the scale of interest in different situations is varying, yet little is known about the optimal setting of the scale range in MMSE and MMFE. To this end, we extend the univariate cosine similarity entropy (CSE) method to the multivariate case, and show that the resulting multivariate multiscale cosine similarity entropy (MMCSE) is capable of quantifying structural complexity through the degree of self-correlation within signals. The proposed approach relaxes the prohibitive constraints between the embedding dimension and data length, and aims to quantify the structural complexity based on the degree of self-correlation at low scales. The proposed MMCSE is applied to the examination of the complex and quaternion circularity properties of signals with varying correlation behaviors, and simulations show the MMCSE outperforming the standard methods, MMSE and MMFE.