Resources Conservation and Recycling最新文献_第10页

Vegetable yields and environmental impacts vary widely across types, production technologies, and global regions 蔬菜产量和环境影响因类型、生产技术和全球地区而异

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

Resources Conservation and Recycling

Pub Date : 2025-12-09 DOI: 10.1016/j.resconrec.2025.108735

Shiyu Cao , Lu Wang , Yi Yang

Vegetables are vital for sustainable and healthy diets, but their global environmental footprints remain unclear. This study quantitatively reviews the life-cycle environmental impacts of 13 major vegetables by synthesizing >100 studies. Vegetable yields and environmental impacts vary widely across types, production technologies, and global regions. Median yields and environmental impacts of the most productive vegetable types can exceed those of the least productive types by >40 times and >5 times, respectively (e.g., 356.0 vs. 8.4 t ha⁻¹; 0.86 vs. 0.17 kg CO₂e kg⁻¹). Compared with open-field systems, facility‑grown systems have generally much higher yields (e.g., +548 % for tomato) and lower blue water footprint (e.g., −75 % for lettuce) but higher carbon footprint (e.g., +273 % for tomato) due to energy-intensive operations. Reducing facility carbon footprint requires energy decarbonization and improved irrigation and nutrient management. On average, carbon footprint, blue water footprint, acidification, eutrophication, human toxicity, and land use per kg of vegetables produced are estimated at 0.52 kg CO₂e, 0.08 m³, 2.73 g SO₂e, 2.37 g PO₄³⁻e, 0.14 kg 1,4‑DCBe, and 0.17 m² a. These quantitative benchmarks can support region-specific mitigation prioritization and inform policy and industry decisions for lower-impact vegetable supply chains. Geograpically, the compiled data skew toward Europe, and in terms of environmental impacts, concentrate on carbon footprint, highlighting the need for more diverse regional coverage and inclusion of non-carbon footprints.

蔬菜对可持续和健康的饮食至关重要，但它们在全球的环境足迹尚不清楚。本研究通过综合100项研究，对13种主要蔬菜的生命周期环境影响进行了定量综述。蔬菜产量和环境影响因类型、生产技术和全球地区而异。产量最高的蔬菜品种的中位数产量和环境影响分别是产量最低的蔬菜品种的40倍和5倍（例如356.0 vs. 8.4 t ha - 1; 0.86 vs. 0.17 kg CO₂e kg - 1）。与露天种植系统相比，设施种植系统通常具有更高的产量（例如，番茄产量为+ 548%）和更低的蓝水足迹（例如，生菜产量为- 75%），但由于能源密集型操作，碳足迹更高（例如，番茄产量为+ 273%）。减少设施碳足迹需要能源脱碳和改善灌溉和养分管理。平均而言，每公斤蔬菜生产的碳足迹、蓝水足迹、酸化、富营养化、人体毒性和土地利用估计为0.52公斤CO₂e、0.08 m³、2.73 g SO₂e、2.37 g PO₄³−e、0.14公斤1,4 - DCBe和0.17 m²a。这些定量基准可以支持特定区域的缓解优先级，并为低影响蔬菜供应链的政策和行业决策提供信息。从地理上看，汇编的数据倾向于欧洲，就环境影响而言，主要关注碳足迹，强调需要更多样化的区域覆盖和非碳足迹的纳入。

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引用次数: 0

Material flow analysis of plastics in Australia: Towards a circular economy of polymers 澳大利亚塑料材料流分析：迈向聚合物的循环经济

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

Resources Conservation and Recycling

Pub Date : 2025-12-08 DOI: 10.1016/j.resconrec.2025.108718

Nargessadat Emami , Quoc Anh Nguyen , Alessio Miatto , Jacob Fry , Mohammad Sadegh Taskhiri , Mengyu Li , Manfred Lenzen , Deborah Lau , Heinz Schandl

Plastic is a critical material in Australia, widely used across industries for its versatility and cost-effectiveness. However, the growing volume of plastic waste, amounting to 3201 kt in 2020–21, poses significant environmental challenges. Only 13 % of plastic waste was recycled, while 81 % was sent to landfill, 1 % energy recovery and 5 % exported. This study examines the lifecycle of plastics in Australia, including production, consumption, waste generation, and recycling practices. Employing Material Flow Analysis (MFA) combined with Environmentally Extended Input-Output (EEIO) analysis, we trace the flows of major plastic types, identify systemic inefficiencies and reginal disparities in recycling. Results show that 77 % of the 1280 kt of virgin polymers consumed were imported, with polyethylene (HDPE and LDPE) being the most common type, followed by PVC and PP. The manufacturing and construction sectors together account for 84 % of total plastic consumption. Regional patterns vary considerably. New South Wales and Victoria report the highest plastic use, reflecting population size, while recycling rates differ widely. South Australia achieves a 20 % recycling rate, whereas the Australian Capital Territory recycles only 0.1 % locally due to the absence of recycling facilities. Of the total plastic waste recycled, 46 % was reprocessed domestically, and the remainder exported, highlighting gaps in local recycling infrastructure. These findings underscore the urgent need to improve Australia’s recycling capacity and practices. Strengthening domestic infrastructure is essential for mitigating environmental impacts and advancing towards a circular economy of plastics.

塑料在澳大利亚是一种重要的材料，因其多功能性和成本效益被广泛应用于各个行业。然而，不断增长的塑料废物量（2020-21年将达到3201万吨）构成了重大的环境挑战。只有13%的塑料垃圾被回收利用，81%被送往垃圾填埋场，1%被用于能源回收，5%被出口。本研究考察了澳大利亚塑料的生命周期，包括生产、消费、废物产生和回收实践。采用物料流分析（MFA）结合环境延伸投入产出（EEIO）分析，我们追踪了主要塑料类型的流动，确定了回收方面的系统性低效率和区域差异。结果表明，在消费的1280 kt原生聚合物中，77%是进口的，其中聚乙烯（HDPE和LDPE）是最常见的类型，其次是PVC和PP。制造业和建筑业合计占塑料总消费量的84%。区域模式差异很大。新南威尔士州和维多利亚州的塑料使用量最高，反映了人口规模，而回收率差异很大。南澳大利亚达到了20%的回收率，而澳大利亚首都地区由于缺乏回收设施，当地的回收率仅为0.1%。在回收的塑料废物总量中，46%在国内进行再加工，其余的用于出口，这凸显了当地回收基础设施的差距。这些发现强调了提高澳大利亚回收能力和做法的迫切需要。加强国内基础设施对于减轻环境影响和推进塑料循环经济至关重要。

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引用次数: 0

Real-time plastic waste segmentation for sustainable resource recovery in construction 实时塑料垃圾分割，实现建筑资源的可持续回收

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

Resources Conservation and Recycling

Pub Date : 2025-12-06 DOI: 10.1016/j.resconrec.2025.108719

Iman Ranjbar , Yiannis Ventikos , Mehrdad Arashpour

The construction and demolition (C&D) sector is a major contributor to Australia’s total waste, with reports indicating continuous annual growth. Among this waste, end-of-life plastic represents a valuable recyclable material with significant recovery potential. However, effective separation of plastic waste remains a challenge due to the highly cluttered and heterogeneous nature of C&D waste. This study focuses on the detection and segmentation of C&D plastic waste using advanced instance segmentation models to enable efficient waste sorting and recycling. A large, specialised dataset is curated, capturing the complex and very often deformed nature of C&D plastic waste across seven key categories: buckets, cables, drums, insulation, liquid containers, pipes, and PVC profiles. The dataset features a high density of objects per image, ensuring robust model training and generalisation in real-world scenarios. State-of-the-art instance segmentation models, including FastInst, RTMDet-Ins, YOLOv9, and YOLOv11, are trained and evaluated on this dataset. Among these, YOLOv11 demonstrated the highest performance, achieving a mean Average Precision (mAP) of 51.3 while maintaining a real-time inference speed of 89 frames per second (FPS). A systematic analysis of the models’ strengths and limitations is provided, highlighting challenges associated with segmenting highly cluttered and overlapping objects. Additionally, EigenCAM visualisations are used to interpret the model’s decision-making process. The findings demonstrate that the proposed models achieve accurate segmentation of C&D plastic waste, contributing to improved resource recovery and the advancement of a circular economy within the construction industry.

建筑和拆除（C&；D）部门是澳大利亚总垃圾的主要贡献者，报告显示每年持续增长。在这些废物中，报废塑料是一种有价值的可回收材料，具有显著的回收潜力。然而，由于塑料废物的高度杂乱和异质性，有效分离塑料废物仍然是一个挑战。本研究的重点是使用先进的实例分割模型对C&；D塑料垃圾进行检测和分割，以实现高效的垃圾分类和回收。一个大型的、专门的数据集，收集了七个关键类别的C&；D塑料废物的复杂和经常变形的性质：桶、电缆、桶、绝缘、液体容器、管道和PVC型材。该数据集的特点是每张图像的物体密度很高，确保了现实世界场景中鲁棒的模型训练和泛化。最先进的实例分割模型，包括FastInst， RTMDet-Ins， YOLOv9和YOLOv11，在此数据集上进行训练和评估。其中，YOLOv11表现出了最高的性能，实现了51.3的平均精度（mAP），同时保持了89帧每秒（FPS）的实时推理速度。对模型的优势和局限性进行了系统的分析，强调了与分割高度混乱和重叠对象相关的挑战。此外，EigenCAM可视化用于解释模型的决策过程。研究结果表明，所提出的模型实现了对塑料垃圾的准确分割，有助于提高资源回收率，促进建筑行业循环经济的发展。

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引用次数: 0

Upcycling anaerobic digestion methane to single-cell protein as a low-carbon strategy 将厌氧消化甲烷升级为单细胞蛋白质作为低碳策略

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

Resources Conservation and Recycling

Pub Date : 2025-12-04 DOI: 10.1016/j.resconrec.2025.108731

Pan-Long Lv , Qing-Rui Hu , Yu-Yang Hu , Wenjing Gong , Qian Li , Rong Chen

Anaerobic digestion of organic waste generates substantial amounts of dissolved methane (CH₄) and nitrogen source, presenting both environmental challenges and opportunities for resource recovery. This study produces single-cell protein (SCP) by utilizing CH₄ as carbon sources in a CH₄-based membrane biofilm reactor (MBfR). Over 270 days of continuous operation, the reactor achieved highly efficient nitrogen removal and SCP production. Results demonstrated that nitrate was a more effective nitrogen source than ammonia for SCP synthesis, achieving SCP yields of 3.3 g/g N and 1.2 g/g CH₄ with protein content exceeding 50%. The addition of acetate alleviated ammonia inhibition, and increased SCP yield to 5.7 g/g N. Metagenomic analysis identified Methylocystis played key roles in methane oxidation and SCP biosynthesis. Life cycle assessment revealed a carbon footprint of 1.25 kg CO₂-eq/kg for CH₄-based SCP. Using CH₄ from waste anaerobic digestate avoided 10.2 kg CO₂-eq/kg emissions.

有机废物的厌氧消化产生大量的溶解甲烷（CH4）和氮源，对环境提出了挑战，同时也为资源回收带来了机遇。本研究利用CH4作为碳源，在基于CH4的膜生物膜反应器（MBfR）中生产单细胞蛋白（SCP）。经过270天的连续运行，该反应器实现了高效的脱氮和SCP生产。结果表明，在SCP合成中，硝态氮是比氨更有效的氮源，SCP的产率为3.3 g/g N和1.2 g/g CH4，蛋白质含量超过50%。添加乙酸减轻了氨抑制作用，使SCP产量提高到5.7 g/g n。宏基因组分析发现，甲基藻在甲烷氧化和SCP生物合成中起关键作用。生命周期评估显示，基于ch4的SCP的碳足迹为1.25 kg co2当量/kg。利用厌氧废液中的CH4可避免10.2 kg co2当量/kg的排放。

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引用次数: 0

Material circularity in the UK’s foundation industries 英国基础工业的材料循环

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

Resources Conservation and Recycling

Pub Date : 2025-12-03 DOI: 10.1016/j.resconrec.2025.108728

Natanael Bolson , Masoud Ahmadinia , Rossi Setchi , Sam Evans , Jonathan Cullen

As the UK advances toward its 2050 net-zero target, moving beyond energy efficiency to comprehensive resource management is essential. This study evaluates how circular economy principles can reshape the use of aluminium, lead, steel, glass, and paper in the UK’s foundation industries. Using a circularity index, we assess current performance and identify improvement pathways, quantifying the potential of enhanced recycling and material reuse. Results show that circularity strategies alone could reduce emissions by 42% and energy use by 17%, with reductions rising to 69% and 56% respectively, when combined with best-practice energy intensities. While aluminium and steel offer the largest gains, barriers remain for lead, glass, and paper due to technical and quality constraints. These findings highlight the opportunities and the complexities of industrial circularity, providing evidence to guide policymakers and industry leaders in accelerating the transition to a more sustainable and resource-efficient economy.

随着英国向2050年净零排放目标迈进，从提高能源效率转向全面资源管理至关重要。这项研究评估了循环经济原则如何重塑英国基础工业中铝、铅、钢、玻璃和纸张的使用。使用循环指数，我们评估当前的性能和确定改进途径，量化加强回收和材料再利用的潜力。结果表明，如果与最佳实践的能源强度相结合，仅循环策略就可以减少42%的排放和17%的能源使用，分别减少69%和56%。虽然铝和钢铁的涨幅最大，但由于技术和质量的限制，铅、玻璃和纸张仍然存在障碍。这些发现突出了工业循环的机遇和复杂性，为指导政策制定者和行业领导者加速向更可持续和资源节约型经济转型提供了证据。

引用次数: 0

Addressing the ‘last mile’ deficiency: A bi-objective model for e-waste reverse logistics network design 解决“最后一英里”缺陷：电子垃圾逆向物流网络设计的双目标模型

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

Resources Conservation and Recycling

Pub Date : 2025-12-03 DOI: 10.1016/j.resconrec.2025.108713

Zhiqin Ni , Hing Kai Chan , Zhen Tan

Although China’s official e-waste recycling rate has been higher than the global average over the past decade, the certified reverse logistics network, primarily composed of licensed disassemblers, faces fierce competition from uncertified channels due to limited community access to the certified network. This paper develops a robust bi-objective mixed-integer linear programming model to help certified network decision-makers establish community collection and treatment centers that address the ‘last mile’ deficiency, aiming to provide accessible services to communities competing with uncertified channels while maintaining economic viability. The robust bi-objective mixed-integer linear programming model considers maximizing the collection rate and the profit of the three-echelon reverse logistics network. A piecewise function is proposed to simulate competition between community collection and treatment centers and uncertified channels based on prior literature. Two realistic uncertainty parameters—the lower boundary of the entire collection and the reuse rate—are incorporated into the model, which deliberately addresses the dynamics of collection and processing complexity. A real-world case is presented to validate the model's effectiveness in supporting location decision-making for community collection and treatment centers. The Gurobi optimizer is used to solve the robust model, and the resulting optimal solutions are presented on the Pareto front. ArcGIS software illustrates the eight selected community collection and treatment centers, which achieved a 61.6 % collection rate and a profit of 0.15 million RMB, as shown on the map. This study presents a reliable and effective model for location decisions for community collection and treatment centers under realistic uncertainties, facilitating licensed disassemblers’ decision-making that balances regulatory and economic objectives.

尽管中国官方的电子垃圾回收率在过去十年中一直高于全球平均水平，但由于社区对认证网络的访问有限，主要由持牌拆解商组成的认证逆向物流网络面临着来自未认证渠道的激烈竞争。本文开发了一个鲁棒的双目标混合整数线性规划模型，以帮助认证网络决策者建立社区收集和治疗中心，解决“最后一英里”缺陷，旨在为与未认证渠道竞争的社区提供无障碍服务，同时保持经济可行性。鲁棒双目标混合整数线性规划模型考虑了三梯队逆向物流网络的回收率和利润最大化。在前人文献的基础上，提出了一个分段函数来模拟社区收集和治疗中心与未经认证的渠道之间的竞争。模型中引入了两个现实的不确定性参数——整个集合的下边界和重用率，有意地解决了集合和处理复杂性的动态问题。通过一个实际案例验证了该模型在支持社区收集和治疗中心选址决策方面的有效性。利用Gurobi优化器对鲁棒模型进行求解，并在Pareto前沿给出了得到的最优解。ArcGIS软件对选定的8个社区收集和治疗中心进行了绘图，如图所示，这些中心的回收率为61.6%，利润为15万元人民币。本研究为现实不确定性下的社区回收处理中心选址决策提供了一个可靠、有效的模型，帮助持牌拆解商平衡监管目标和经济目标。

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引用次数: 0

AI-enhanced sorting enabling direct high-purity tantalum urban mining: a novel pathway from e-waste to critical materials 人工智能增强分选，实现直接高纯度钽的城市开采：从电子废物到关键材料的新途径

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

Resources Conservation and Recycling

Pub Date : 2025-12-03 DOI: 10.1016/j.resconrec.2025.108717

Dong Xia , Kok Yuen Koh , Raunaq Nayar , Colin Locoge , Nicolas M. Charpentier , Mya Mya Khin , Tien Hoa Nguyen , Guillaume Zante , Hicham Khodja , Jean-Christophe P. Gabriel

Tantalum’s supply chain instability demands efficient urban mining from e-waste. Here, we present an AI-enhanced process that combines intelligent sorting with sustainable hydrometallurgy for high-yield/high-purity Ta recovery. A hybrid sorting system, cascading an interpretable convolutional neural network (CNN) with automated multi-energy X-ray transmission (MEXRT) spectroscopy, achieved 99.6 % precision and 96.9 % recall at 3000 components/hour, resolving the Ta/Nb ambiguity. Spatial activation mapping illustrated the visual sorting mechanism, facilitating feature-driven upgrading. Meanwhile, Canny edge detection and K-edge detection enabled real-time and pixel-wise spectral analysis under multithreaded processing. Downstream, streamlined physical separation and thermodynamically guided reverse leaching selectively recovered Ta with 98.2 % efficiency under mild conditions. Advanced characterization using transmission electron microscopy and ion beam analysis revealed a quantifiable core-shell Ta/Ta₂O₅ structure in leached products, guiding calcination into >99.8 % pure Ta₂O₅. This work establishes a closed-loop urban mining framework, demonstrating how AI and tailored refining enable a circular economy for critical metals.

钽供应链的不稳定性要求从电子垃圾中高效地进行城市开采。在这里，我们提出了一种人工智能增强的工艺，将智能分选与可持续湿法冶金相结合，用于高产量/高纯度的Ta回收。混合分选系统将可解释卷积神经网络（CNN）与自动多能x射线传输（MEXRT）光谱级联，在3000个组分/小时的情况下，达到99.6%的精度和96.9%的召回率，解决了Ta/Nb的模糊性。空间激活映射说明了视觉排序机制，便于功能驱动升级。同时，Canny边缘检测和k边缘检测实现了多线程处理下的实时逐像素光谱分析。下游，在温和条件下，流线型物理分离和热力学引导反浸选择性地回收Ta，效率为98.2%。利用透射电子显微镜和离子束分析的高级表征揭示了浸出产物中可量化的核壳Ta/Ta2O5结构，指导煅烧得到纯度为99.8%的Ta2O5。这项工作建立了一个闭环城市采矿框架，展示了人工智能和量身定制的精炼如何实现关键金属的循环经济。

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引用次数: 0

Cradle-to-grave life cycle assessment of electrodialysis for ammonium recovery 电渗析铵回收的摇篮到坟墓生命周期评价

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

Resources Conservation and Recycling

Pub Date : 2025-12-03 DOI: 10.1016/j.resconrec.2025.108716

Zhengwen Zhang , Mohammed Tahmid , Hyuck Joo Choi , Marta C. Hatzell , Roger H. French , Chris Yuan

Electrodialysis technology is a promising technology for recovering ammonium ions from anaerobic digestion digestate. In this study, a cradle-to-grave life cycle assessment model was developed to evaluate the environmental performance of electrodialysis for ammonium recovery, with system boundary encompassing upstream production, use, and end-of-life phases. The environmental impacts of the electrodialysis technology were assessed using the ReCiPe 2016 midpoint method and benchmarked against those of the baseline air stripping (AS) technology. The cradle-to-grave energy consumption of electrodialysis is 28.74 MJ per kilogram of ammonium recovered, representing a 32.3 % reduction compared to that of AS technology. Additionally, electrodialysis exhibits lower impact values across all 13 evaluated environmental categories, with reductions ranging from 13.1 % to 90.4 %. With continued technological advancement, electrodialysis offers significant potential as an environmental-friendly technology for industrial-scale ammonium recovery.

电渗析技术是一种很有前途的从厌氧消化消化液中回收铵离子的技术。在这项研究中，建立了一个从摇篮到坟墓的生命周期评估模型，以评估电渗析回收铵的环境性能，系统边界包括上游生产、使用和生命周期结束阶段。使用ReCiPe 2016中点方法评估电渗析技术的环境影响，并与基线空气剥离（AS）技术进行基准测试。电渗析从摇篮到坟墓的能耗为28.74 MJ / kg铵回收，与AS技术相比降低了32.3%。此外，电渗析在所有13个评估的环境类别中都显示出较低的影响值，减少幅度从13.1%到90.4%不等。随着技术的不断进步，电渗析作为一种环境友好型的工业铵回收技术具有巨大的潜力。

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引用次数: 0

Creating circular pathways for nutrients in aquaculture using biochar 利用生物炭为水产养殖中的营养物质创造循环途径

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

Resources Conservation and Recycling

Pub Date : 2025-12-02 DOI: 10.1016/j.resconrec.2025.108707

Efstathios Reppas-Chrysovitsinos , Marta Behjat , Niklas Wennberg , Gregory Peters , Magdalena Svanström

Global food production drives planetary-boundary transgressions, including nitrogen and phosphorus cycle disruption, land use change, and climate change. Increasing nutrient circularity can improve sustainability. This study explores an integrated approach that combines a recirculating aquaculture system (RAS) with biochar from forestry-residue pyrolysis to improve process-level nutrient retention while producing carbon-rich biochar with potential for soil-carbon storage upon land application. In RAS, biochar acts as a filter, capturing nutrients and transforming waste into nutrient-enriched biochar for agriculture. Substance Flow Analysis shows that integration increases nitrogen retention from 30.6 % to 44.6 % and phosphorus retention from 25.5 % to 99.6 % versus separate RAS and pyrolysis. This demonstrates the potential of linking aquaculture, forestry, and agriculture with biochar to support more circular and sustainable food production. This early-stage study examines how and to what extent the approach influences nutrient flows under different assumptions and evaluates a simple recovery-efficiency indicator for assessing circularity in integrated systems.

全球粮食生产推动了地球边界越界，包括氮和磷循环中断、土地利用变化和气候变化。增加养分循环可以提高可持续性。本研究探索了一种综合方法，将循环水产养殖系统（RAS）与林业残渣热解产生的生物炭相结合，以提高工艺水平的养分保留，同时生产富含碳的生物炭，并在土地应用时具有土壤碳储存的潜力。在RAS中，生物炭充当过滤器，捕获营养物质并将废物转化为农业所需的营养丰富的生物炭。物质流分析表明，与单独的RAS和热解相比，整合使氮保留率从30.6%提高到44.6%，磷保留率从25.5%提高到99.6%。这表明了将水产养殖、林业和农业与生物炭联系起来，以支持更加循环和可持续的粮食生产的潜力。这项早期研究考察了在不同假设下该方法如何以及在多大程度上影响养分流动，并评估了用于评估综合系统循环的简单回收率效率指标。

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引用次数: 0

Beyond connectivity: How smart 5G technologies affect carbon emissions across industries 超越连接：智能5G技术如何影响各行业的碳排放

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

Resources Conservation and Recycling

Pub Date : 2025-12-02 DOI: 10.1016/j.resconrec.2025.108700

Kaixuan Wang , Shuo Sun , Youbang Guan , Chong Huang , Pei Xiao , Ming Xu , Lirong Liu

As the rollout of 5G accelerates, its soaring energy demand poses a growing climate challenge. According to a World Bank Group report, the Information and Communication Technology (ICT) sector is responsible at least 1.7 % of global greenhouse gas (GHG) emissions. This study examines an intelligent suite of energy-saving methods—particularly deep reinforcement learning sleep modes, adaptive RIS, and cluster-zooming cell-free MIMO at the network edge, alongside dynamic power adjustments on user devices—and quantifies their environmental impact using an ICT-focused environmentally extended input-output (EEIO) model. Anchored in the UK’s 2019 economic and emissions data, the model captures both production and consumption effects across 33 sectors. Results spotlight two standout strategies—AI-powered base station sleep control and refined user device signaling—as catalysts for deep, economy-wide CO₂ reductions. Notably, the financial, IT services, and programming sectors benefit most from these ripple effects. Our findings outline practical paths towards greener 5G deployments and underscore policy opportunities to amplify their socioeconomic value.

随着5G的加速推出，其飙升的能源需求构成了日益严峻的气候挑战。根据世界银行集团的一份报告，信息和通信技术（ICT）部门至少占全球温室气体（GHG）排放量的1.7%。本研究考察了一套智能节能方法——特别是深度强化学习睡眠模式、自适应RIS和网络边缘的集群缩放无小区MIMO，以及用户设备上的动态功率调整——并使用以ict为重点的环境扩展输入输出（EEIO）模型量化了它们对环境的影响。该模型以英国2019年的经济和排放数据为基础，捕捉了33个行业的生产和消费影响。研究结果强调了两种突出的策略——人工智能驱动的基站睡眠控制和改进的用户设备信号——作为深度、经济范围内的二氧化碳减排的催化剂。值得注意的是，金融、IT服务和编程部门从这些连锁反应中获益最多。我们的研究结果概述了实现更绿色5G部署的实际途径，并强调了扩大其社会经济价值的政策机会。

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引用次数: 0