Circular economy and sustainability最新文献

The influence of environmental policy has been known to move beyond the country or regional contexts in which they have been implemented. Examples in literature include the "California effect" and the "Brussels effect", showing how the policies adopted in the EU and California influence other jurisdictions. In this paper we study the following: To what extent are companies operating in the United States influenced by circular economy policies outside their direct context? By interviewing companies operating in the United States, we find that firms are influenced by and actively work to influence circular economy policy, both as it originates from outside the United States (the Brussels effect, referring to policies in Europe) and from within the United States (such as the California effect). Key barriers to circular innovation include the lack of a comprehensive policy framework in the U.S., opposition from competitors, and making the business model work in the U.S. legal context. Strategies to overcome these include: getting legal support for circular business models, developing U.S. regulations, level the playing field for all U.S.-based companies, lobbying for supporting regulation, and collaboration. We find that EV battery recycling is a positive exception where U.S. policy provides clarity for circular innovation. Finally, we find that the characteristics of the 'typical' U.S. consumer may call for specific circular business models. We suggest future research to enhance our understanding on how policy might positively drive circular economy innovations in international companies.

This research presents a comprehensive analysis of Circular Economy (CE) practices across the United Kingdom, using advanced Natural Language Processing (NLP) techniques, specifically Named Entity Recognition (NER), chosen for its reproducible, large-scale extraction of locations, sectors and 9R actions from 1.2 million words of policy text. The study examines 36 key documents, comprising roadmaps, policy statements, and sectoral reports, to categorise CE activities such as recycling, reduction, reuse, and recovery. The dataset includes 22,589 distinct entries, covering 52 locations, 34 industrial sectors, and 109 stakeholder categories. Notably, recycling emerges as the most dominant activity, representing 42.8% of all practices, which suggests an over-reliance on waste management solutions rather than upstream interventions like reduction and remanufacturing. Analysis shows that Construction & Demolition (19.8%) and Food & Beverage (13.7%) account for most initiatives, while the Digital, Electronics and Aviation sectors together contribute barely 1%. Local authorities lead 18% of actions, yet trade organisations add less than 1%. Regional priorities also differ: Wales directs 46% of activity to waste management, whereas Scotland and Northern Ireland devote 44% and 53% respectively to decarbonisation and resource-efficiency measures. These disparities reveal structural asymmetries in investment and skills and therefore justify a devolved-yet-co-ordinated policy mechanism, similar to the UK Industrial Strategy Council, that can harmonise regional targets while preserving local strengths. This research offers critical insights into sectoral and geographic patterns, allowing policymakers to prioritise gaps in existing CE initiatives. Although recycling diverts material from landfill, our results indicate that this downstream concentration yields lower value-retention and slower decarbonisation than upstream actions (e.g. design-for-reuse or remanufacturing), signalling an urgent need to rebalance UK policy towards the upper tiers of the 9R hierarchy. Notably, our findings reveal a fragmented approach to CE in the UK- with regions pursuing different priorities and a heavy reliance on recycling- underscoring the need for a unified national CE roadmap. We therefore recommend the development of an integrated UK-wide CE strategy that incentivises upstream practices (e.g. reduction and reuse) and harmonises regional efforts to achieve broader circular economy goals.

The petrochemical industry is composed of several interconnected processes that use fossil-based feedstock for producing chemicals. These processes are typically geographically clustered and often belong to different parties. Reducing the environmental impacts of the petrochemical industry is not straightforward due to, on the one hand, their reliance on fossil fuels for energy and as a feedstock and, on the other hand, the significant level of interconnected energy and material flows among processes. Current methods for analyzing changes to existing processes cannot capture the multitude and level of interactions. The goal of this paper is to create a model of a petrochemical cluster and analyze its physical characteristics and performance. This paper addresses this goal by developing an assessment method that combines process simulations, multiplex graph analysis, and key performance indicators. The method is applied to a case study based on the petrochemical cluster in the Port of Rotterdam, resulting in a uniquely highly detailed model of a petrochemical cluster. The network analysis results show that only some of the processes are very interconnected. From the performance analysis, it can be observed that the olefins process is the most carbon-intense and has high CO₂ emissions. Additionally, the results showed the importance of considering existing interconnections when assessing the current performance of existing petrochemical clusters or the performance due to future changes to chemical processes. For instance, some changes would occur to an industrial cluster by introducing alternative carbon sources, such as biomass or CO₂.

Supplementary information: The online version contains supplementary material available at 10.1007/s43615-024-00410-5.

The dependence on finite reserves of raw materials and the generation of waste are two unsolved problems of the traditional linear economy. Healthcare, as a major sector of any nation, is currently facing them. In addition, the reprocessing of healthcare waste poses humans at risk of contamination. Another open issue is that circular economy, which is a paradigm that is being proposed to address material supply uncertainties and waste generation, still lacks physics-based modeling approaches that enable the design and analysis of circular flows of materials. Hence, in this paper, first we report on the on-going development of a flexible robotic cell enabled by deep-learning vision for automating three main tasks in a circular healthcare, namely, resources mapping and quantification, disassembly, and waste sorting of small medical devices. Second, we combine compartmental dynamical thermodynamics with the mechanics of robots to integrate robotics into a system-level perspective. Our thermodynamic framework is a step forward in defining the theoretical foundations of circular material flow designs because it enhances material flow analysis (MFA) by adding dynamical energy balances to the usual mass balances and by leveraging dynamical systems theory. Third, we propose two circularity indicators by leveraging our thermodynamic framework and graph theory. While our initial set-up of the robotic cell is for reprocessing glucose meters and inhalers, other medical devices can be considered after making the proper adaptations; in addition, it can switch from sorting to disassembly to resources mapping and quantification, or run them in parallel. Our thermodynamic systemic modeling framework involves more physics and system dynamics than MFA, and hence, can yield the needed improvements in model accuracy and reproducibility at the cost of extra complexity. Finally, the proposed circularity indicators can help healthcare chain managers in assessing whether the robotic cell can process the input stream of materials within the desired time and with the desired level of separation at the output material flow. Software and a demo video are publicly available.