Resources Conservation and Recycling最新文献

英文中文

Efficient lithium recovery from industrial lithium iron phosphate (LFP) blackmass using formic acid-enabled hydrometallurgy 甲酸湿法冶金从工业磷酸铁锂（LFP）黑质中高效回收锂

IF 10.9 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Resources Conservation and Recycling

Pub Date : 2025-12-30 DOI: 10.1016/j.resconrec.2025.108766

Ayesha Tasawar , Daniel Dotto Munchen , Alexander Birich , Rungsima Yeetsorn , Walter Sebastian Scheld , Waritnan Wanchan , Benjamin Butz , Bernd Friedrich

As millions of LFP batteries reach their end of life, the challenge of selectively extracting lithium from industrial blackmass, loaded with impurities, has become a focal point for sustainable innovation in battery recycling. However, industrial-scale LFP recycling remains technically challenging due to the complex composition of real battery waste, including high graphite content, binders, and metallic inclusions that undermine conventional leaching processes. In this research study, a selective, green hydrometallurgical approach tailored for impurity-rich LFP blackmass is presented. Using only trace (“hint of acid”) amounts of formic acid with hydrogen peroxide and two-step leaching, achieving ∼94.5% lithium extraction in the two-step formic acid route, whereas the trace sulfuric acid + H₂O₂ condition delivers the highest selectivity, reaching >95% lithium recovery with negligible iron co-leaching, and producing lithium carbonate as an end product (confirmed by XRD and SEM) without the environmental burden of aggressive reagents or high-temperature treatment. Key to this process is careful control of solution pH and oxidation conditions, allowing a scalable, cost‑effective route to close the loop on LFP materials, and proving that the high‑yield lithium recovery and environmental responsibility can be achieved in the same process.

随着数以百万计的LFP电池寿命的结束，从工业黑质中选择性地提取锂的挑战已经成为电池回收可持续创新的焦点。然而，工业规模的LFP回收在技术上仍然具有挑战性，因为实际电池废物的成分复杂，包括高石墨含量、粘合剂和金属夹杂物，这些都会破坏传统的浸出工艺。在本研究中，提出了一种针对富含杂质的LFP黑质定制的选择性绿色湿法冶金方法。在过氧化氢和两步浸出中仅使用微量（“微量酸”）的甲酸，在两步甲酸路线中实现了~ 94.5%的锂提取，而微量硫酸+ h2o条件具有最高的选择性，在忽略铁共浸出的情况下，锂回收率达到>；95%，最终产品碳酸锂（通过XRD和SEM证实）没有腐蚀性试剂或高温处理的环境负担。该工艺的关键是仔细控制溶液pH值和氧化条件，允许可扩展的，成本有效的路线来闭合LFP材料的循环，并证明在同一过程中可以实现高产量的锂回收和环境责任。

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引用次数: 0

Identification of common types of plastics by vibrational spectroscopic techniques 用振动光谱技术鉴定普通塑料

IF 10.9 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Resources Conservation and Recycling

Pub Date : 2025-12-30 DOI: 10.1016/j.resconrec.2025.108767

Maria P.Garcia Tovar , Maria A.Villarreal Blanco , Oliva M. Primera-Pedrozo , Macy K. Christianson , Chih-Feng Wang , Pavel Valencia Acuña , John H. Miller , Luis de la Torre , Samuel P.Hernández Rivera

Polyethylene Terephthalate (PET), High-Density Polyethylene (HDPE), Polyvinyl Chloride (PVC), Low-Density Polyethylene (LDPE), Polypropylene (PP), and Polystyrene (PS) account for most plastic use worldwide, with production nearing 380 million tons annually. A considerable portion enters municipal solid waste and landfills, creating long-term environmental concerns. Scaling recycling operations requires automated sorting technologies, with spectroscopy and machine learning offering promising solutions. In this study, a six-class convolutional neural network (CNN) was developed for plastic identification using vibrational spectroscopies. Raman Scattering (RS) spectra collected from recycling samples enabled accurate chemical differentiation while assessing the influence of visible features such as color. A CNN trained on RS data achieved 100 % classification accuracy. To strengthen field applicability, Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy was incorporated, achieving 95% accuracy with a similar CNN model. These findings demonstrate the potential of integrating spectroscopy with deep learning for reliable plastic classification, advancing development of scalable, field-ready recycling technologies.

聚对苯二甲酸乙二醇酯（PET）、高密度聚乙烯（HDPE）、聚氯乙烯（PVC）、低密度聚乙烯（LDPE）、聚丙烯（PP）和聚苯乙烯（PS）占全球塑料使用量的大部分，年产量接近3.8亿吨。相当一部分进入城市固体废物和垃圾填埋场，造成长期的环境问题。扩展回收操作需要自动分拣技术，光谱和机器学习提供了有前途的解决方案。在这项研究中，开发了一个六类卷积神经网络（CNN）用于振动光谱的塑料识别。从回收样品中收集的拉曼散射（RS）光谱可以在评估颜色等可见特征的影响时进行精确的化学区分。在RS数据上训练的CNN达到了100%的分类准确率。为了增强现场适用性，采用了衰减全反射-傅里叶变换红外（ATR-FTIR）光谱，使用类似的CNN模型，准确率达到95%。这些发现表明，将光谱学与深度学习相结合，可以实现可靠的塑料分类，促进可扩展的现场回收技术的发展。

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引用次数: 0

Weaving the energy transition web: Structural dynamics and drivers of the global lithium-cobalt-nickel trade network 编织能源转型网络：全球锂钴镍贸易网络的结构动态和驱动因素

IF 10.9 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Resources Conservation and Recycling

Pub Date : 2025-12-30 DOI: 10.1016/j.resconrec.2025.108768

Chao Wang , Kangyu Tan , Ming K. Lim , Pezhman Ghadimi

The accelerating global energy transition has created unprecedented demand for critical minerals essential for batteries and clean energy technologies. While existing research has examined individual metal trade networks, the core scientific question of how these minerals jointly evolve as an integrated “energy transition web” remains unanswered. This study addresses this gap by constructing a multi-layer aggregated trade network for lithium-cobalt-nickel spanning 2010–2024. It uses complex network and quadratic assignment procedure (QAP) regression to identify mechanisms shaping network dynamics and their implications for supply-chain resilience. The results show that the network has transformed from sparse to a dense “small-world” structure, dominated by an intensifying Asian core. Traditional drivers such as economic scale have weakened, whereas environmental and strategic factors have emerged as primary drivers. These findings demonstrate that the global critical-mineral system is evolving into more interconnected yet more politically segmented energy-transition web, highlighting emerging vulnerabilities and informing future resource-security strategies.

全球能源转型加速，对电池和清洁能源技术所必需的关键矿物产生了前所未有的需求。虽然现有的研究已经检查了单个金属贸易网络，但这些矿物如何共同演变为一个综合的“能源过渡网络”的核心科学问题仍然没有答案。本研究通过构建一个跨越2010-2024年的锂钴镍多层聚合贸易网络来解决这一差距。它使用复杂网络和二次分配过程（QAP）回归来确定形成网络动力学的机制及其对供应链弹性的影响。结果表明，该网络已从稀疏结构转变为密集的“小世界”结构，并以不断强化的亚洲核心为主导。经济规模等传统驱动因素减弱，环境和战略因素成为主要驱动因素。这些发现表明，全球关键矿产系统正在演变成相互联系更加紧密但政治上更加分割的能源转型网络，突出了新出现的脆弱性，并为未来的资源安全战略提供信息。

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引用次数: 0

End-of-life portable lithium-ion batteries in Japan: Generation, collection system effectiveness, and unidentified flows 日本的报废便携式锂离子电池：产生、收集系统的有效性和未确定的流量

IF 10.9 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Resources Conservation and Recycling

Pub Date : 2025-12-26 DOI: 10.1016/j.resconrec.2025.108754

Masahiro Oguchi , Atsushi Terazono , Kazuo Hasunuma

End-of-life (EoL) management of lithium-ion batteries (LIBs) presents significant environmental and safety challenges. We estimated Japan’s EoL portable LIB generation and assessed the effectiveness of its collection systems. A survey of 33 electrical and electronic equipment categories found that 82 % of them contained LIBs, with many incorporating built-in batteries, leading to disposal in inappropriate waste streams. In 2020, approximately 8160 tonnes of EoL LIBs were generated, with six key categories—smartphones, laptops, tablets, cordless vacuum cleaners, power banks, and motor-assisted bicycles. Although Japan’s official collection schemes cover 77 % of EoL generation, only 14 % is actually collected. Possible paths for the rest 86 % include disposal in municipal solid waste, export with secondhand products, and untracked collections from businesses. Even considering these, however, the destination of nearly 40 % of EoL LIBs remains unknown, highlighting the need to identify remaining flows to enhance collection frameworks that ensure sustainable resource management and safe disposal.

锂离子电池（lib）的寿命终止（EoL）管理提出了重大的环境和安全挑战。我们估计了日本的EoL便携式LIB生成，并评估了其收集系统的有效性。一项针对33种电气和电子设备类别的调查发现，82%的产品含有锂电池，其中许多产品内置电池，导致其被丢弃在不适当的废物流中。2020年，大约有8160吨的EoL lib被生产出来，主要有六个类别——智能手机、笔记本电脑、平板电脑、无线吸尘器、移动电源和电动辅助自行车。尽管日本官方的收集计划覆盖了77%的EoL发电量，但实际上只收集了14%。其余86%的可能途径包括城市固体废物处理，二手产品出口，以及企业无追踪收集。然而，即使考虑到这些，近40%的EoL lib的目的地仍然未知，这突出表明需要确定剩余的流量，以加强收集框架，确保可持续的资源管理和安全处置。

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引用次数: 0

Regional dynamics of Nd stocks, flows, and required industrial capacities: insights from EV and wind turbine material flows 钕储量、流量和所需工业能力的区域动态：来自电动汽车和风力涡轮机材料流的见解

IF 10.9 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Resources Conservation and Recycling

Pub Date : 2025-12-26 DOI: 10.1016/j.resconrec.2025.108761

Olivier Karl Anton Heldwein , Fridolin Krausmann , Johann Fellner

Neodymium is a critical raw material essential for electric vehicle (EV) motors and wind turbines in a decarbonized energy system. This study applies stock-driven, dynamic material flow analysis to investigate stock-flow development of Nd in light-duty EVs and wind turbines under the IEA’s Net-Zero-Emissions Scenario across five world regions and explores recycling potentials to meet regional demand. It shows that China keeps exporting as primary production exceeds domestic demand and could leverage refining capacity for recycling. In Europe, secondary supply temporarily surpasses demand as stocks decrease, while India’s circularity potential is hampered by continuous stock-growth. In the US, planned primary production and recycling could cover demand by the 2040s. Globally, secondary supply could meet >60 % of Nd-demand in light-duty EVs and wind in 2050, with mining decreasing from its 2035 peak to current levels. Fast mining expansion and the subsequent shift to secondary production require strategic planning and political support.

在脱碳能源系统中，钕是电动汽车（EV）电机和风力涡轮机必不可少的关键原材料。本研究采用库存驱动的动态物料流分析，在国际能源署（IEA）的净零排放情景下，在全球五个地区调查轻型电动汽车和风力涡轮机中钕的库存流动发展情况，并探索回收潜力，以满足区域需求。这表明，由于初级生产超过国内需求，中国继续出口，可以利用炼油能力进行回收。在欧洲，由于库存减少，二级市场供应暂时超过需求，而印度的循环潜力受到库存持续增长的阻碍。在美国，计划中的初级生产和回收可以在21世纪40年代之前满足需求。在全球范围内，到2050年，二次供应可以满足轻型电动汽车和风能60%的钕需求，采矿从2035年的峰值下降到目前的水平。矿业的快速扩张和随后向二次生产的转变需要战略规划和政治支持。

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引用次数: 0

Life-cycle carbon footprint and mitigation potentials of e-bikes in urban transport systems 城市交通系统中电动自行车的生命周期碳足迹及减排潜力

IF 10.9 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Resources Conservation and Recycling

Pub Date : 2025-12-24 DOI: 10.1016/j.resconrec.2025.108758

Yifei Liu , Qiuxia Zou , Yunchang Ding , Zeguo Yang , Ning Zhang , Ruichang Mao , Huabo Duan , Jiakuan Yang

Amid escalating climate risks, electric bicycles (e-bikes) are emerging as a prominent low-carbon micromobility option in densely populated cities across China and Southeast Asia. However, their overall decarbonization potential has yet to be systematically and comprehensively quantified. Using a spatially explicit life-cycle assessment, we quantifie the carbon emissions and reduction potential of e-bikes in Chinese cities during 2025–2050. Results show that e-bikes emit 45 g CO₂e per kilometer, with a life-cycle footprint of 576–890 kg CO₂e, which is 48–64 % higher than earlier estimates due to more complete inventories and incorporation of provincial grid-intensity factors. In 2024, China’s e-bike sector generated 32.4 ± 1.3 Mt CO₂e, while reducing 7.4 Mt CO₂e through modal substitution, alongside annual reductions of 36 kt NOₓ and 15 kt SO₂. Looking ahead, strategic integration of e-bikes into urban mobility systems could offset 2.9–5.1 % of China’s urban transport emissions by 2050, underscoring their critical role in decarbonizing urban mobility.

在气候风险不断升级的背景下，在中国和东南亚人口密集的城市，电动自行车（e-bikes）正成为一种突出的低碳微交通选择。然而，它们的整体脱碳潜力尚未得到系统和全面的量化。利用空间显式生命周期评估，我们量化了2025-2050年中国城市电动自行车的碳排放和减排潜力。结果表明，电动自行车每公里排放45克二氧化碳，生命周期足迹为576-890公斤二氧化碳，由于更完整的清单和纳入省级电网强度因素，这比之前的估计高出48 - 64%。2024年，中国电动自行车行业产生了32.4±130万吨二氧化碳排放量，同时通过模式替代减少了740万吨二氧化碳排放量，同时每年减少36万吨NOₓ和15万吨SO₂。展望未来，到2050年，电动自行车与城市交通系统的战略性整合可以抵消中国城市交通排放的2.9% - 5.1%，突显出它们在城市交通脱碳方面的关键作用。

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引用次数: 0

Assessing spatial variation in carbon stocks across China’s wetland ecosystems 中国湿地生态系统碳储量空间分异研究

IF 10.9 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Resources Conservation and Recycling

Pub Date : 2025-12-24 DOI: 10.1016/j.resconrec.2025.108763

Bo Peng , Zhiyong Zhou , Li Xu , Nianpeng He

China’s wetlands store substantial carbon in vegetation and soils,yet depth-resolved estimates remain inconsistent. Using 18,798 field records (2000–2023), we integrated vegetation and soil data at 20–cm intervals (0–100 cm) to map carbon stocks nationwide. Combining climate, soil, vegetation and topography, a Random Forest model produced spatial estimates of vegetation carbon (aboveground 385.4 Tg C; belowground 662.26 Tg C; total 1047.66 ± 437 Tg C) and soil carbon (0–100 cm: 8336.51 ± 1216 Tg C). Climate and topography dominated spatial variability, while performance was higher for the aboveground than for the deeper soil layers. These maps can be used to identify priority regions for conservation and hydrological restoration, providing actionable baselines for wetland carbon management and China’s mitigation targets.

中国的湿地在植被和土壤中储存了大量的碳，但深度分辨的估计仍然不一致。利用18798份野外记录（2000-2023年），以20厘米（0-100厘米）的间隔整合植被和土壤数据，绘制了全国范围内的碳储量图。结合气候、土壤、植被和地形，随机森林模型估算了植被碳（地上385.4 Tg C，地下662.26 Tg C，总1047.66±437 Tg C）和土壤碳（0-100 cm: 8336.51±1216 Tg C）的空间分布。气候和地形对空间变异起主导作用，而地上层的变异程度高于深层土壤。这些地图可用于确定保护和水文恢复的优先区域，为湿地碳管理和中国的减排目标提供可操作的基线。

引用次数: 0

Reframing law and behavior for circular economies 重新构建循环经济的法律和行为

IF 10.9 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Resources Conservation and Recycling

Pub Date : 2025-12-23 DOI: 10.1016/j.resconrec.2025.108729

Alessandro Creazza , Roland Geyer , Mitchell P. Jones , Tamar Makov , Nicola Saccani , Gerald Shurson , Katrien Steenmans , Andrea Urbinati

引用次数: 0

Advanced strategies for selective lithium extraction from spent lithium-ion battery cathodes 从废锂离子电池阴极中选择性提取锂的先进策略

IF 10.9 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Resources Conservation and Recycling

Pub Date : 2025-12-22 DOI: 10.1016/j.resconrec.2025.108756

Ying Zheng , Ziwen Dai , Fan Yang , Zhaoyang Li , Guang Hu , Sha Liang , Wenbo Yu , Shushan Yuan , Huabo Duan , Liang Huang , Jingping Hu , Huijie Hou , Jiakuan Yang

Lithium-ion batteries (LIBs) have revolutionized portable electronics, electric vehicles, and grid-scale energy storage. However, the resulting surge in spent LIBs poses severe challenges to environmental sustainability and resource security. Conventional pyrometallurgical and hydrometallurgical recycling technologies are hindered by fundamental limitations, including high energy consumption, the generation of secondary pollution, complex processes, and inefficient lithium recovery. These challenges have driven the development of short-route, efficient, and green recycling technologies. Among these, selective lithium recovery strategies targeting lithium extraction while preserving valuable transition metal cathode structure, show exceptional promise. This review critically assesses recent advancements in selective lithium recovery technologies, including selective leaching, roasting–leaching hybrid processes, mechanochemical methods, and electrochemical approaches. By analyzing their underlying mechanisms, comparing the techno-economic and environmental trade-offs across pathways, and identifying key research challenges, we provide a forward-looking perspective on future research directions for designing next-generation sustainable LIBs recycling processes.

锂离子电池（lib）已经彻底改变了便携式电子产品、电动汽车和电网规模的能源存储。然而，由此产生的废lib激增对环境可持续性和资源安全构成了严峻挑战。传统的火法冶金和湿法冶金回收技术受到高能耗、产生二次污染、工艺复杂和锂回收效率低等基本限制。这些挑战推动了短程、高效和绿色回收技术的发展。其中，选择性锂回收策略以锂提取为目标，同时保留有价值的过渡金属阴极结构，显示出非凡的前景。本文综述了选择性锂回收技术的最新进展，包括选择性浸出、焙烧浸出混合工艺、机械化学方法和电化学方法。通过分析其潜在机制，比较不同途径的技术经济和环境权衡，并确定关键的研究挑战，我们为设计下一代可持续的锂离子电池回收工艺提供了前瞻性的研究方向。

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引用次数: 0

Mapping daily 1-km resolution XCO2 in China using deep learning and multi-source data 利用深度学习和多源数据绘制中国每日1公里分辨率XCO2图

IF 10.9 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Resources Conservation and Recycling

Pub Date : 2025-12-22 DOI: 10.1016/j.resconrec.2025.108755

Wei Shao , Tianxiang Yue , Lili Zhang , Wenjie Tian , Hao Wang , Haowei Zhou , Chenchen Wu , Liqiang Zhang

High-resolution spatiotemporal column-averaged CO₂ (XCO₂) data is essential for understanding anthropogenic carbon emissions, but current satellite limitations hinder detailed analysis. To address this, we develop the Spatial-Temporal Attention XCO₂ Network (STAXN) to improve prediction accuracy by capturing spatial-temporal variability and multiscale influences of auxiliary variables. Monte Carlo validation demonstrates robust performance, with an RMSE of 0.90 ppm and an R² of 0.97. Using this model, we generate a 1-km resolution daily XCO₂ dataset for China (2015–2020) and analyze XCO₂ anomaly patterns. Seasonal XCO₂ anomalies peak in summer and winter, with nighttime light exhibiting strong positive effects (β = 0.134, 0.107), and GPP exerting the most substantial adverse influence in winter (β = −0.200). The centroid trajectories of XCO₂ anomalies exhibit consistent seasonal shifts, shaped by regional disparities in carbon efficiency, industrial structure, and emission intensity. These findings offer valuable insights into China’s carbon emission dynamics, informing policy and management strategies.

高分辨率时空柱平均CO2 （XCO2）数据对于了解人为碳排放至关重要，但目前卫星的限制阻碍了详细分析。为了解决这一问题，我们开发了时空关注XCO2网络（STAXN），通过捕获辅助变量的时空变异性和多尺度影响来提高预测精度。蒙特卡罗验证显示了稳健的性能，RMSE为0.90 ppm， R²为0.97。利用该模型，我们生成了中国（2015-2020）1 km分辨率的XCO2日数据集，并分析了XCO2异常模式。季节XCO2异常在夏季和冬季达到峰值，其中夜间光照表现出较强的正向影响（β = 0.134, 0.107），而GPP在冬季的不利影响最大（β = - 0.200）。碳效率、产业结构和排放强度的区域差异决定了XCO2异常质心轨迹呈现出一致的季节变化。这些发现为了解中国的碳排放动态提供了有价值的见解，为政策和管理策略提供了信息。

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引用次数: 0

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