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Plastic input and dynamics in industrial composting 工业堆肥中的塑料输入和动态。
IF 7.1 2区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2025-02-01 DOI: 10.1016/j.wasman.2024.11.043
Stoyana Peneva , Quynh Nhu Phan Le , Davi R. Munhoz , Olivia Wrigley , Giovana P.F. Macan , Heidi Doose , Wulf Amelung , Melanie Braun
Green and biowaste, processed within large facilities into compost, is a key fertilizer for agricultural and horticultural soils. However, due to improper waste disposal of plastic, its residues often remain or even lead to the formation of microplastics (1  µm − 5 mm, MiPs) in the final compost product. To better understand the processes, we first quantified ‘macroplastics’ (> 20 mm, MaPs) input via biowaste collection into an industrial composting plant, and, then determined MiP concentrations at five stages during the composting process (before and after shredding and screening processes), and in the water used for irrigation. The total concentrations of MaPs in the biowaste collected from four different German districts ranged from 0.36 to 1.95 kg ton-1 biowaste, with polyethylene (PE) and polypropylene (PP) representing the most abundant types. The “non-foil” and “foil” plastics occurred in similar amounts (0.51 ± 0.1 kg ton-1 biowaste), with an average load of 0.08 ± 0.01 items kg−1 and 0.05 ± 0.01 items kg−1, respectively. Only 0.3 ± 0.1 kg MaP t−1 biowaste was biodegradable plastic. Compost treatment by shredding tripled the total number of MaPs and MiPs to 33 items kg−1, indicating an enrichment of particles during the process and potential fragmentation. Noticeably, a substantial amount of small MiPs (up to 22,714 ± 2,975 particles L-1) were found in the rainwater used for compost moistening, being thus an additional, generally overlooked plastic source for compost. Our results highlight that reducing plastic input via biowaste is key for minimizing MiP contamination of compost.
绿色和生物废物在大型设施内加工成堆肥,是农业和园艺土壤的关键肥料。然而,由于塑料垃圾处理不当,其残留物往往会在最终的堆肥产品中残留甚至形成微塑料(1µm - 5 mm, MiPs)。为了更好地了解这一过程,我们首先量化了通过生物废物收集进入工业堆肥厂的“宏观塑料”(bbb20毫米,MaPs),然后确定了堆肥过程中五个阶段(粉碎和筛选过程前后)以及用于灌溉的水中的MiP浓度。从德国四个不同地区收集的生物垃圾中,MaPs的总浓度从0.36到1.95 kg - t -1不等,其中聚乙烯(PE)和聚丙烯(PP)的含量最高。“非箔”塑料和“箔”塑料出现的数量相似(0.51±0.1 kg-1生物垃圾),平均负荷分别为0.08±0.01项kg-1和0.05±0.01项kg-1。只有0.3±0.1 kg MaP t-1生物垃圾是可生物降解的塑料。粉碎堆肥处理使map和MiPs的总数增加了两倍,达到33个kg-1,表明在处理过程中颗粒富集和潜在的破碎。值得注意的是,在用于堆肥润湿的雨水中发现了大量的小颗粒MiPs(高达22,714±2,975颗粒L-1),因此是一个额外的,通常被忽视的堆肥塑料来源。我们的研究结果强调,通过生物废物减少塑料的投入是最大限度地减少MiP污染的关键。
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引用次数: 0
A workflow to assess the recoverability of secondary raw materials via physical separation 通过物理分离评估二次原料可回收性的工作流程。
IF 7.1 2区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2025-02-01 DOI: 10.1016/j.wasman.2024.12.040
P. Boelens , L. Pereira , K. Tumakov , J.R. da Assuncao Godinho , C.G. da Silva Tochtrop , S. Gupta , B.M. Guy , R. Tolosana-Delgado , R. Möckel , T. Leißner , E. Löwer , D. Illing , A.D. Renno , L. Ott , F. Ellinger , M. Rudolph , J. Gutzmer
Printed circuit boards represent an extraordinarily challenging fraction for the recycling of waste electric and electronic equipment. Due to the closely interlinked structure of the composing materials, the selective recycling of copper and closely associated precious metals from this composite material is compromised by losses during mechanical pre-processing. This problem could partially be overcome by a better understanding of the influence of particle size and shape on the recovery of finely comminuted and well-liberated metal particles during mechanical separation. Here, we propose a workflow to quantify the role of the size and shape of such particles in various separation processes. As a case study, we compare an analytical heavy liquid separation to a new type of eddy current separator. Using X-ray computed tomography, we were able to distinguish metallic and non-metallic phases and determine the size and 3D microstructure of individual particles. For both separation processes, we trained a particle-based separation model that predicts the probability of individual particles to end up in the processing products. In particular, elongated particles were found to display a negative correlation between particle size and sphericity of metallic particles. In line with this correlation, the predicted metal recoveries are positively correlated with particle size but negatively correlated with sphericity in both separation processes. The suggested workflow is easily transferred to other recycling material systems. It allows to quantify the role of 3D geometrical particle properties in separation processes and provide robust predictions for the recoverability of different raw materials in complex recycling streams.
印刷电路板是回收废旧电器和电子设备的一个极具挑战性的部分。由于复合材料紧密相连的结构,从这种复合材料中选择性回收铜和密切相关的贵金属在机械预处理过程中受到损失。通过更好地了解粒度和形状对机械分离过程中细粉碎和充分释放的金属颗粒的回收的影响,可以部分地克服这一问题。在这里,我们提出了一个工作流来量化这些颗粒的大小和形状在各种分离过程中的作用。作为一个实例,我们比较了一种分析重液分离与一种新型涡流分离器。通过x射线计算机断层扫描,我们能够区分金属相和非金属相,并确定单个颗粒的尺寸和3D微观结构。对于这两个分离过程,我们训练了一个基于颗粒的分离模型,该模型预测了单个颗粒最终进入加工产品的概率。特别地,发现伸长的颗粒在颗粒大小和金属颗粒的球形度之间表现出负相关。根据这一相关性,两种分离过程中预测的金属回收率均与粒度呈正相关,而与球形度负相关。建议的工作流程很容易转移到其他回收材料系统。它可以量化3D几何颗粒特性在分离过程中的作用,并为复杂回收流中不同原材料的可回收性提供可靠的预测。
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引用次数: 0
Steam explosion pretreatment of separated dairy cattle manure: Mass balances and effect on biomethane potential 分离牛粪的蒸汽爆破预处理:质量平衡及其对生物甲烷势的影响。
IF 7.1 2区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2025-02-01 DOI: 10.1016/j.wasman.2024.11.037
Elisabeth Anne Cazier , Simone Brethauer, Patrice Claude Bühler, Michael Hans-Peter Studer
Manure is a renewable feedstock, whose theoretical potential for biogas production is scarcely deployed due to modest methane yields that prevent economic feasible operation of anaerobic digestion plants. Steam explosion pretreatment has the potential to improve the digestibility of manure, however it is energy intensive, and the optimal conditions depend on the feedstock. In this work, the solid and the liquid fraction of separated dairy cattle manure were pretreated between 130 and 210 °C for 5 to 40 min by steam explosion to individually determine the optimal conditions for each fraction. Additionally, mass balances for volatile solids (VS), cellulose, hemicellulose and proteins were performed to better understand the effects of the pretreatment. For the manure solids, a pretreatment at 130 °C for 20 min was most effective, the biomethane potential (BMP) improved by 40 %. In contrast, the BMP of the liquid fraction could not be improved at any pretreatment condition. The mass balances showed that at more severe conditions up to 18 % of the VS were lost by decomposition and/or evaporation, with the proteins being the most thermolabile fraction. Based on the observation, that a pretreatment of the liquid phase can be omitted, a heat integrated plant concept is suggested where the necessary heat input is only as large as in conventional anaerobic digestion. Taken together, this work underlined the benefits of steam explosion pretreatment of manure and identified the prevention of VS loss as a promising avenue for further improving the process.
粪肥是一种可再生原料,其理论上的沼气生产潜力几乎没有发挥出来,因为适度的甲烷产量阻碍了厌氧消化工厂经济可行的运行。蒸汽爆破预处理有可能提高粪便的消化率,但它是能源密集型的,最佳条件取决于原料。本研究对分离后的牛粪固体部分和液体部分进行蒸汽爆破预处理,在130 ~ 210℃范围内分别处理5 ~ 40 min,分别确定各部分的最佳处理条件。此外,还对挥发性固体(VS)、纤维素、半纤维素和蛋白质进行了质量平衡,以更好地了解预处理的效果。对于粪便固体,130℃预处理20 min最有效,生物甲烷势(BMP)提高40%。相比之下,在任何预处理条件下,液体组分的BMP都不能得到改善。质量平衡表明,在更恶劣的条件下,高达18%的VS因分解和/或蒸发而损失,其中蛋白质是最耐热的部分。根据观察,液相的预处理可以省略,建议热集成工厂的概念,其中所需的热量输入仅与传统厌氧消化一样大。综上所述,这项工作强调了蒸汽爆炸预处理粪肥的好处,并确定了防止VS损失是进一步改进该工艺的有希望的途径。
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引用次数: 0
Bacterial biofilm-based bioleaching: Sustainable mitigation and potential management of e-waste pollution 基于细菌生物膜的生物浸出:电子废物污染的可持续缓解和潜在管理。
IF 7.1 2区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2025-02-01 DOI: 10.1016/j.wasman.2024.12.010
Krishnamurthy Mathivanan , Ruiyong Zhang , Jayaraman Uthaya Chandirika , Thangavel Mathimani , Can Wang , Jizhou Duan
Significant advances in the electrical and electronic industries have increased the use of electrical and electronic equipment and its environmental emissions. The e-waste landfill disposal has deleterious consequences on human health and environmental sustainability, either directly or indirectly. E-waste containing ferrous and non-ferrous materials can harm the surrounding aquatic and terrestrial environments. Therefore, recycling e-waste and recovering metals from it before landfill disposal is an important part of environmental management. Although various chemical and physical processes are being used predominantly to recover metals from e-waste, the bioleaching process has gained popularity in recent years due to its eco-friendliness and cost-effectiveness. Direct contact between microbes and e-waste is crucial for continuous metal dissolution in the bio-leaching process. Biofilm formation is key for the continuous dissolution of metals from e-waste in contact bioleaching. Critical reviews on microbial activities and their interaction mechanisms on e-waste during metal bioleaching are scarce. Therefore, this review aims to explore the advantages and disadvantages of biofilm formation in contact bioleaching and the practical challenges in regulating them. In this review, sources of e-waste, available metallurgical methods, bioleaching process, and types of bioleaching microbes are summarized. In addition, the significance of biofilm formation in contact bioleaching and the role and correlation between EPS production, cyanide production, and quorum sensing in the biofilm are discussed for continuous metal dissolution. The review reveals that regulation of quorum sensing by exogenous and endogenous processes facilitates biofilm formation, leading to continuous metal dissolution in contact bioleaching.
电气和电子工业的重大进步增加了电气和电子设备的使用及其对环境的排放。电子垃圾填埋处理直接或间接地对人类健康和环境可持续性造成有害后果。含有铁和有色金属材料的电子垃圾会损害周围的水生和陆地环境。因此,在填埋前回收电子垃圾并从中回收金属是环境管理的重要组成部分。虽然各种化学和物理过程主要用于从电子废物中回收金属,但生物浸出过程近年来因其环保和成本效益而受到欢迎。在生物浸出过程中,微生物与电子垃圾的直接接触对金属的连续溶解至关重要。生物膜的形成是接触生物浸出中电子垃圾中金属连续溶解的关键。金属生物浸出过程中电子垃圾中微生物的活性及其相互作用机制的评述很少。因此,本文旨在探讨接触式生物浸出中生物膜形成的优缺点及其调控的实际挑战。本文综述了电子垃圾的来源、现有的冶金方法、生物浸出工艺以及生物浸出微生物的种类。探讨了接触浸出过程中生物膜形成的意义,以及生物膜中EPS生成、氰化物生成和群体感应在金属连续溶出过程中的作用和相互关系。研究表明,在接触浸出过程中,外源和内源过程对群体感应的调节促进了生物膜的形成,从而导致金属的持续溶解。
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引用次数: 0
ECCDN-Net: A deep learning-based technique for efficient organic and recyclable waste classification eccn - net:一种基于深度学习的高效有机和可回收废物分类技术。
IF 7.1 2区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2025-02-01 DOI: 10.1016/j.wasman.2024.12.023
Md. Sakib Bin Islam , Md. Shaheenur Islam Sumon , Molla E. Majid , Saad Bin Abul Kashem , Mohammad Nashbat , Azad Ashraf , Amith Khandakar , Ali K. Ansaruddin Kunju , Mazhar Hasan-Zia , Muhammad E.H. Chowdhury
Efficient waste management is essential to minimizing environmental harm as well as encouraging sustainable progress. The escalating volume and sophistication of waste present significant challenges, prompting innovative methods for effective waste categorization and management. Deep learning models have become highly intriguing tools for automating trash categorization activities, providing effective ways to optimize processes for handling waste. Our work presents a novel deep learning method for trash classification, with the goal to improve the accuracy, also efficiency of garbage image categorization. We examined the effectiveness of several pre-trained models, such as InceptionV2, Densenet201, MobileNet v2, and Resnet18, using objective evaluation and cross-validation. We proposed an Eco Cycle Classifier Deep Neural Network (ECCDN-Net) model that is particularly built for the categorization of waste images. ECCDN-Net utilizes the advantageous qualities of Densenet201 and Resnet18 by merging their capacities to extract features, enhanced with auxiliary outputs to optimize the classification procedure. The set of images used in this study comprises 24,705 images that are divided into two distinct classes: Organic and Recyclable. The set allows extensive evaluation and training of deep learning models for waste classification of images tasks. Our research demonstrates that the ECCDN-Net model classifies waste images with 96.10% accuracy, outperforming other pre-trained models. Resnet18 had 92.68% accuracy, MobileNet v2 93.27%, Inception v3 94.77%, and Densenet201, a significant improvement, 95.98%. ECCDN-Net outperformed these models in waste image categorization with 96.10% accuracy. We ensure the reliability and generalizability of our methods throughout the dataset by integrating and cross-validating deep learning models. The current work introduces an innovative deep learning-based approach that has promising potential for waste categorization and management strategies.
有效的废物管理对于尽量减少对环境的危害和鼓励可持续发展至关重要。废物的数量和复杂性不断增加,提出了重大挑战,促使采用创新方法进行有效的废物分类和管理。深度学习模型已经成为自动化垃圾分类活动的非常有趣的工具,为优化垃圾处理过程提供了有效的方法。本文提出了一种新的深度学习垃圾分类方法,旨在提高垃圾图像分类的准确率和效率。通过客观评估和交叉验证,我们检验了几种预训练模型的有效性,如InceptionV2、Densenet201、MobileNet v2和Resnet18。我们提出了一个生态循环分类器深度神经网络(ECCDN-Net)模型,该模型是专门为垃圾图像分类而建立的。ECCDN-Net利用了Densenet201和Resnet18的优势,通过合并它们提取特征的能力,并辅以辅助输出来优化分类过程。本研究中使用的图像集包括24,705张图像,分为两个不同的类别:有机和可回收。该集允许广泛的评估和训练深度学习模型,用于图像任务的废物分类。我们的研究表明,ECCDN-Net模型对垃圾图像的分类准确率为96.10%,优于其他预训练模型。Resnet18的准确率为92.68%,MobileNet v2的准确率为93.27%,Inception v3的准确率为94.77%,Densenet201的准确率为95.98%。ECCDN-Net在垃圾图像分类方面优于这些模型,准确率为96.10%。我们通过整合和交叉验证深度学习模型来确保我们的方法在整个数据集中的可靠性和泛化性。目前的工作介绍了一种创新的基于深度学习的方法,该方法在废物分类和管理策略方面具有很大的潜力。
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引用次数: 0
Unveiling the resource potential of space debris: A forecast of valuable metals to 2050 揭示空间碎片的资源潜力:对2050年贵重金属的预测。
IF 7.1 2区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2025-02-01 DOI: 10.1016/j.wasman.2024.12.019
Fumihiro Hayashi , Arata Kioka , Takuma Ishii , Takumu Nakamura
The proliferation of space debris poses a significant challenge in modern space exploration, with potential repercussions for the future space environment and activities. Various research and technological developments have addressed these concerns, including estimating the number of space debris orbiting the Earth and its efficient removal. This paper proposes a novel resource-oriented perspective on space debris and focuses on the composition and resource potential of space debris. This study forecasts for the first time the annual mass changes in resource materials (Al, Al2O3, Ti, Fe, Cu, and Ag) by the year 2050 by employing a debris environment model simulation. Our simulation reveals that the masses of all the studied resource elements in an Earth orbital altitude of 400 km will increase by 2050. For example, Al and Ti at the 400 km altitude band will increase from 3.0 × 106 kg and 3.2 × 105 kg (in 2016) to 3.8 × 107 kg and 4.2 × 106 kg (in 2050), respectively, climbing at least ten times from 2016 to 2050, on the conservative estimates with a high post-mission disposal success rate. These comparative influxes of Al and Ti in 2050 due to space debris are at least 100 times higher than the natural influxes into the Earth’s atmosphere due to meteoroids, further highlighting the significance of space debris. Our simulation results suggest that space debris may hold significant space resource potential in the next 25 years but can be a considerable environmental contaminant impeding space sustainability.
空间碎片的扩散对现代空间探索构成重大挑战,并可能对未来的空间环境和活动产生影响。各种研究和技术发展已经解决了这些问题,包括估计绕地球轨道运行的空间碎片的数量及其有效清除。本文提出了一种新的空间碎片资源导向视角,重点研究了空间碎片的组成和资源潜力。本文首次采用岩屑环境模型模拟,预测了到2050年资源材料(Al、Al2O3、Ti、Fe、Cu和Ag)的年质量变化。我们的模拟表明,到2050年,在地球轨道高度400公里处,所有研究资源元素的质量都将增加。例如,400 km高度波段的Al和Ti将分别从3.0 × 106 kg和3.2 × 105 kg(2016年)增加到3.8 × 107 kg和4.2 × 106 kg(2050年),保守估计从2016年到2050年至少增加10倍,任务后处置成功率很高。2050年空间碎片造成的Al和Ti的相对流入至少是流星体自然流入地球大气层的100倍,进一步凸显了空间碎片的重要性。我们的模拟结果表明,空间碎片在未来25年内可能具有巨大的空间资源潜力,但也可能成为阻碍空间可持续性的重大环境污染物。
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引用次数: 0
Hydrothermal pretreatment for enhanced thermochemical or biochemical conversion of pharmaceutical biowastes into fuels, fertilizers, and carbon materials 通过水热预处理,加强制药生物废料向燃料、肥料和碳材料的热化学或生物化学转化。
IF 7.1 2区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2025-02-01 DOI: 10.1016/j.wasman.2024.12.007
Yilin Wei , Xiang Meng , Weiyuan Meng , Lijian Leng , Zhiyong Zeng , Xinming Wang , Shengqiang Liu , Hao Zhan
Pharmaceutical biowastes, rich in organic matter and high in moisture, are typical light industry byproducts with waste and renewable attributes. Thermochemical and biochemical conversion technologies transform these residues into value-added bioproducts, including biofuels, biofertilizers, and bio-carbon materials. Hydrothermal pretreatment effectively removes toxic substances and enhances feedstock for these processes. This review comprehensively examines its role in improving the formation of bioproducts from pharmaceutical biowastes, focusing on (i) upgrading and denitrogenating solid biofuels with better combustion performance; (ii) enhancing biodegradability and gaseous biofuel production via organic matter decomposition; (iii) enriching soluble carbon and nitrogen for liquid biofertilizer; (iv) eliminating antibiotic residues and reducing antibiotic resistance in solid biofertilizers; and (v) stabilizing carbon and nitrogen structures and optimizing pore characteristics for functionalized carbon materials. The review recommends a potential staged thermochemical approach to co-produce nitrogen-enriched liquid biofertilizers and porous carbon materials from pharmaceutical biowastes. Hydrothermal pretreatment emerges as a key technique for facilitating the migration and conversion of essential elements like carbon and nitrogen. This study reveals the potential of hydrothermal pretreatment to address the limitations of pharmaceutical biowastes and offers insights into their valorization.
医药生物废弃物是典型的轻工业副产物,具有废弃物和可再生特性,有机质含量高,水分含量高。热化学和生物化学转化技术将这些残留物转化为增值生物产品,包括生物燃料、生物肥料和生物碳材料。水热预处理有效地去除了有毒物质,提高了这些工艺的进料质量。本文综述了其在改善制药生物废弃物形成生物产品方面的作用,重点介绍了(1)具有更好燃烧性能的固体生物燃料的升级和脱氮;(ii)通过有机物分解提高生物可降解性和气体生物燃料的生产;(三)为液体生物肥料富集可溶性碳和氮;(iv)消除固体生物肥料中的抗生素残留并降低抗生素耐药性;(5)稳定功能化碳材料的碳氮结构和优化孔隙特性。该综述推荐了一种潜在的分阶段热化学方法,可以从制药生物废弃物中共同生产富氮液体生物肥料和多孔碳材料。水热预处理是促进碳、氮等必需元素迁移转化的关键技术。本研究揭示了水热预处理解决制药生物废物局限性的潜力,并为其增值提供了见解。
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引用次数: 0
Perceptions of value in retired smartphones: The role of monetary incentives in influencing end-of-hibernation decisions 对退休智能手机价值的看法:货币激励在影响报废决定中的作用。
IF 7.1 2区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2025-02-01 DOI: 10.1016/j.wasman.2024.12.015
Mostafa Sabbaghi
Each year, a significant number of smartphones are retired, yet retained by consumers. These hibernating smartphones have the reuse potential for another lifecycle. Nonetheless, they often stay in storage for a long time and may ultimately face inadequate recovery. This study explores consumers’ perceptions regarding the value of hibernating smartphones over time. It examines the influence of factors such as the duration of smartphone storage and monetary incentives on users’ decision-making regarding the End-of-Hibernation (EoH). The findings demonstrate that, on average, participants perceive the value of a newly retired smartphone to be 28% higher than its market value. This perceived value increases to 83% after three years since the smartphone’s retirement. Participants’ tendency to keep a hibernating smartphone increases as the gap between the monetary incentive and their perceived value of the device increases. Conversely, the longer the smartphone stays in hibernation, the less inclined users are to keep it.
每年都有大量智能手机退役,但仍被消费者保留。这些 "冬眠 "的智能手机具有在另一个生命周期重复使用的潜力。然而,它们往往会被长期存放,最终可能面临回收不足的问题。本研究探讨了消费者对冬眠智能手机价值的看法。研究探讨了智能手机的存储时间和货币激励等因素对用户做出 "结束休眠"(EoH)决策的影响。研究结果表明,平均而言,参与者认为新退役智能手机的价值比其市场价值高 28%。智能手机退役三年后,这种感知价值增加到 83%。随着金钱奖励与参与者对智能手机感知价值之间差距的扩大,参与者保留冬眠智能手机的倾向也随之增加。相反,智能手机冬眠的时间越长,用户就越不愿意保留它。
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引用次数: 0
Differentiating low-carbon waste management strategies for bio-based and biodegradable plastics under various energy decarbonization scenarios 不同能源脱碳情景下生物基塑料和可生物降解塑料的低碳废物管理策略的区别。
IF 7.1 2区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2025-02-01 DOI: 10.1016/j.wasman.2024.12.001
Yuxin Huang , Mengqi Han , Zhujie Bi , Nannan Gu , Dungang Gu , Tingting Hu , Guanghui Li , Jiaqi Lu
Bio-based and biodegradable (bio-)plastics are heralded as a key solution to mitigate plastic pollution and reduce CO2 emissions. Yet, their end-of-life treatments embodies complex energy and material interactions, potentially leading to emissions through incineration or recycling. This study investigates the cradle-to-grave, emphasizing the waste management stage, carbon footprint for several types of bio-plastics, leveraging both GWP100a and CO2 uptake methods to explore the carbon reduction benefits of recycling over disposal. Our findings indicate that in scenarios characterized by carbon-intensive electricity, using polylactic acid (PLA) as an example, incineration with energy recovery (−1.6316 kg CO2-eq/kg, PLA) yields a more favorable carbon footprint compared to chemical recycling (−1.5317 kg CO2-eq/kg, PLA). In contrast, in environments with a high proportion of renewable energy, chemical recycling is a superior method, and compared to incineration (−1.4087 kg CO2-eq/kg, PLA), the carbon footprint of chemical recycling (−2.0406 kg CO2-eq/kg, PLA) are significantly reduced. While mechanical recycling presents considerable environmental benefits, its applicability is constrained by the waste quality, especially in the case of biodegradable plastics like PLA. In addition, the degradation of biodegradable plastics such as PLA was modeled during compost and anaerobic digestion processes. This enables us to quantify the specific biogenic carbon emissions released during these processing steps, revealing the direct emissions with dynamic degradation. This study highlights the importance of tailoring bio-plastic waste management strategies to support global energy decarbonization while understanding their life-cycle carbon metabolism to effectively tackle plastic pollution and climate change.
生物基和可生物降解(生物)塑料被誉为减轻塑料污染和减少二氧化碳排放的关键解决方案。然而,它们的报废处理体现了复杂的能量和材料相互作用,可能导致通过焚烧或回收排放。本研究考察了从摇篮到坟墓的过程,强调了废物管理阶段,几种生物塑料的碳足迹,利用GWP100a和二氧化碳吸收方法来探索回收比处置的碳减排效益。我们的研究结果表明,在以碳密集型电力为特征的情况下,以聚乳酸(PLA)为例,与化学回收(-1.5317 kg CO2-eq/kg, PLA)相比,焚烧与能量回收(-1.6316 kg CO2-eq/kg, PLA)产生更有利的碳足迹。相比之下,在可再生能源比例较高的环境中,化学回收是一种优越的方法,与焚烧(-1.4087 kg CO2-eq/kg, PLA)相比,化学回收的碳足迹(-2.0406 kg CO2-eq/kg, PLA)显著降低。虽然机械回收具有可观的环境效益,但其适用性受到废物质量的限制,特别是在PLA等可生物降解塑料的情况下。此外,在堆肥和厌氧消化过程中模拟了PLA等可生物降解塑料的降解。这使我们能够量化在这些加工步骤中释放的特定生物源碳排放,揭示动态降解的直接排放。本研究强调了定制生物塑料废物管理策略的重要性,以支持全球能源脱碳,同时了解其生命周期的碳代谢,以有效应对塑料污染和气候变化。
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引用次数: 0
An explainable machine learning system for efficient use of waste glasses in durable concrete to maximise carbon credits towards net zero emissions 一个可解释的机器学习系统,用于有效利用耐用混凝土中的废玻璃,以最大限度地提高碳信用额,实现净零排放。
IF 7.1 2区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2025-02-01 DOI: 10.1016/j.wasman.2024.12.034
Xu Huang, Junhui Huang, Sakdirat Kaewunruen
Recycling waste glass (WG) can be time-consuming, costly, and impractical. However, its incorporation into concrete significantly reduces environmental impact and carbon emissions. This paper introduces machine learning (ML) to civil engineering to optimise WG utilisation in concrete, supporting sustainability objectives. By employing a dataset of 471 experimental samples of waste glass concrete (WGC), various ML algorithms are applied, including Gradient Boosting Regressor (GBR), Random Forest (RF), Support Vector Regression (SVR), Adaptive Boosting (AdaBoost), Deep Neural Network (DNN), and k-Nearest Neighbours (kNN), to predict properties containing compressive strength (CS), alkali-silica reaction (ASR), and saved carbon credits (SCC). The proposed models achieve outstanding prediction performance with Coefficient of determination (R2) values of 0.95 for CS, 0.97 for ASR, and 0.99 for SCC using GBR and SVR, demonstrating high prediction accuracy with Root mean square error (RMSE) values of 3.31 MPa for CS, 0.03 % for ASR, and 0.11 for SCC. The SHapley Additive exPlanations (SHAP) analysis is utilised to interpret the model results, ensuring transparency and interpretability of the proposed ML models. The results reveal that the incorporation level of WG is a more significant influencing factor for these properties than the mean size of WG (MSWG).
回收废玻璃(WG)既耗时又昂贵,而且不切实际。然而,将其掺入混凝土中可以显著减少对环境的影响和碳排放。本文将机器学习(ML)引入土木工程,以优化混凝土中的WG利用率,支持可持续发展目标。通过使用471个废玻璃混凝土(WGC)实验样本的数据集,应用各种ML算法,包括梯度增强回归器(GBR)、随机森林(RF)、支持向量回归(SVR)、自适应增强(AdaBoost)、深度神经网络(DNN)和k-近邻(kNN),来预测包含抗压强度(CS)、碱-硅反应(ASR)和节省碳信用额度(SCC)的性能。基于GBR和SVR的模型预测CS、ASR和SCC的决定系数(R2)分别为0.95、0.97和0.99,具有较高的预测精度,CS、ASR和SCC的均方根误差(RMSE)分别为3.31 MPa、0.03%和0.11。SHapley加性解释(SHAP)分析用于解释模型结果,确保提议的ML模型的透明度和可解释性。结果表明,与平均粒径(MSWG)相比,水泥浆掺入量对这些性能的影响更为显著。
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Waste management
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