Circular Economy最新文献

To improve the effectiveness of recycling, echelon utilization, and recovery mechanism of waste power batteries (WPBs), 12 recycling modes were proposed based on extended producer-responsibility principle. By employing profit and sensitivity analyses, we found that resource-recovery companies (Rs) are the key for recycling, echelon utilization, and recovery mechanism. For R, the high resale price of waste LiNi_xMn_yCo_1−x−yO₂ batteries was not conducive to recovering waste batteries. However, the recycling behavior of R was beneficial for resisting the risk of high resale price of waste LiNi_xMn_yCo_1−x−yO₂ batteries. This condition increased the profits by saving on the buying cost and reselling of WPBs to echelon-utilization companies. Following the decrease in the number of recyclers in the recycling system, the profits of R also increased. However, when the proportion of recycled waste LiNi_xMn_yCo_1−x−yO₂ batteries was 100%, the profits of R faced risks due to the high resale price of waste LiNi_xMn_yCo_1−x−yO₂ batteries. For other recyclers, only the power-battery manufacturers (Ms) were willing to reduce the resale price of waste LiNi_xMn_yCo_1−x−yO₂ batteries to let R earn profit because R supplied regenerated materials to M at a lower price than the material companies. This condition created a cycle for WPB recovery and reduced the use of raw materials. Thus, Mode M–R was considered as the optimal recycling mode.

Under the goal of global sustainable development, the new energy vehicle industry is evolving rapidly, leading to a proliferation of spent lithium-ion batteries (LIBs). The recycling of LIBs is key to the sustainable development of the new energy industry, which is consistent with the concept of circular economy as well. And the green extraction of critical metals is the core part of the development. As an alternative to traditional pyrometallurgy and hydrometallurgy, emerging mechanochemical technology provides a new approach for high efficiency and green recycling of critical metals from spent LIBs, as it has the advantages of easy operation, flexibility, and short processing time. This article reviews the state of the art of mechanochemical technology in the recycling of critical metals from spent LIBs. Based on numerous practices, a framework including mechanochemical activation, organic reaction, inorganic reaction, redox reaction, gas-solid reaction, and solid-phase synthesis was constructed. These practices have proved that mechanochemical technology can provide a greener and more sustainable solution for recycling critical metals from spent LIBs. The metals can be transformed into high-value metal products at room temperature and under ordinary pressure, leading to efficient recycling of critical metals and significant reduction of wastes.

Electronic waste (e-waste) refers to obsolete electronic and electrical equipment and its materials. Due to the complex structure and composition of e-waste, improper disposal may generate substances harmful to humans and the environment and result in the loss of recyclable substances. To tackle the challenges in the end-of-life management of e-waste, there is a need for a systematic review of what the literature has investigated and found. Therefore, this paper aims to explore the extensive scientific literature related to e-waste management using a visualized approach. Overall, 8149 research articles were selected and exported from the Web of Science and then analyzed based on mapping knowledge domains. CiteSpace and Gephi, as effective tools, were utilized to identify hidden patterns and correlations from large and complex research outcomes from 1998 to 2019. This research discussed the evolution of global e-waste management, the knowledge-based network, research topics, frontiers and the cooperation relationships. Finally, this state-of-the-art review generated a few research directions that can be further investigated in this research field.

The benefits of consumer electronic products have transformed every societal sector worldwide. However, the adverse impacts of electronic waste (e-waste) disproportionately affect low-income communities and marginalized ecosystems in nations with economies in transition. The embodied carbon footprint of new electronic products, especially information and communications technology (ICT) devices, is an important source of greenhouse gas (GHG) emissions, accounting for 67% ± 15% of total lifetime emissions, instigated by mineral mining, manufacturing, and supply chain transportation. We estimate that between 2014 and 2020, embodied GHG emissions from selected e-waste generated from ICT devices increased by 53%, with 580 million metric tons (MMT) of CO₂e emitted in 2020. Without specific interventions, emissions from this source will increase to ∼852 MMT of CO₂e annually by 2030. Increasing the useful lifespan expectancy of electronic devices by 50%–100% can mitigate up to half of the total GHG emissions. Such outcomes will require coordination of eco-design and source reduction, repair, refurbishment, and reuse. These strategies can be a key to efforts towards climate neutrality for the electronics industry, which is currently among the top eight sectors accounting for more than 50% of the global carbon footprint.

Visual recognition technologies based on deep learning have been gradually playing an important role in various resource recovery fields. However, in the field of metal resource recycling, there is still a lack of intelligent and accurate recognition of metallic products, which seriously hinders the operation of the metal resource recycling industry chain. In this article, a convolutional neural network with dual attention mechanism and multi-branch residual blocks is proposed to realize the recognition of metallic products with a high accuracy. First, a channel-spatial dual attention mechanism is introduced to enhance the model sensitivity on key features. The model can focus on key features even when extracting features of metallic products with too much confusing information. Second, a deep convolutional network with multi-branch residual blocks as the backbone while embedding a dual-attention mechanism module is designed to satisfy deeper and more effective feature extraction for metallic products with complex characteristic features. To evaluate the proposed model, a waste electrical and electronic equipment (WEEE) dataset containing 9266 images in 18 categories and a waste household metal appliance (WHMA) dataset containing 11,757 images in 23 categories are built. The experimental results show that the accuracy reaches 94.31% and 95.88% in WEEE and WHMA, respectively, achieving high accuracy and high quality recycling.

Lithium (Li) is primarily found in mineral resources, brines, and seawater. Extraction of Li from mineral ore deposits is expensive and energy-intensive. Li-ion batteries (LIBs) are certainly one of the important alternatives to lessen the dependence on fossil fuel resources. The global demand for LIBs for portable electrical and electronic equipment (EEE) and EVs have increased significantly, and the amount of spent LIBs (S-LIBs) is rising logarithmically. S-LIBs contain both hazardous heavy metals and toxic organic chemicals that create a serious threat to human health and the ecosystem. The current position requires the recycling of S-LIBs indispensable for the protection of the environment and the recycling of scarce raw materials from economic aspects. In this manuscript, recent developments and state-of-the-art technologies for LIB recycling were focused on and reviewed comprehensively. Pretreatment methods (such as discharging, dismantling, cathode active material (CAM) removal, binder elimination methods, classification, and separation) for S-LIBs are introduced, and all available and novel technologies that are used in different physical and chemical recovery processes are summarized and compared. The pretreatment process in LIB recycling can both improve the recovery rate of the valuable components and significantly lessen the subsequent energy consumption. Notably, pretreatment, metal extraction, and product preparation stages play vital roles in all LIB recovery processes, based on pyrometallurgy, hydrometallurgy, biometallurgy, direct recycling, and mechanical treatment and water leaching. The main goal of this review is to address the novel S-LIB materials’ current recycling research status and innovations for integrated, eco-friendly, economic, low carbon, and clean energy technologies. In the end, different industrial recycling processes are compared, existing challenges are identified and suggestions and perspectives for future LIBs recycling applications are highlighted.