检索结果-内蒙古大学图书馆

Nonradical degradation of phosphonates to orthophosphate via surface-activated peroxides on carbon nanotubes

Separation and Purification Technology 2025年 370卷

作者： Yang, Shuai Zhang, Lin Sun, Yibing Yang, Zhichao Li, Hongchao School of Environmental and Biological Engineering Nanjing University of Science and Technology Nanjing210094 China State Key Laboratory of Pollution Control and Resource Reuse School of Environment Nanjing University Nanjing210023 China Nanjing University Nanjing210023 China

The cleavage of the C-P bonds is essential for the removal and recovery of phosphorus from phosphonate-contaminated wastewaters. This study investigates the feasibility of utilizing carbon nanotubes (CNTs) to activate peroxides (e.g., peroxymonosulfate (PMS)) for degradation of phosphonates. With the exception of aminomethylphosphonic acid and 2-phosphonobutane-1,2,4-tricarboxylic acid, the investigated phosphonates are effectively degraded to orthophosphate (ortho-P), achieving conversion efficiencies ranging from 48.5% to 78.1% at a molar ratio of PMS to C-P bonds of 4:1. Taking aminotris(methylenephosphonic acid) (ATMP) as a model substrate, we deduce that the surface-activated PMS (CNTs-PMS*) serves as the primary reactive species, leading to C-P bonds cleavage predominantly through effective collision rather than the electron transfer process. Furthermore, the CNTs/PMS system maintains high performance over a wide pH range from 3.0 to 9.0 and in the presence of diverse inorganic ions, though its activity is reduced by natural organic matters. The practicality of the CNTs/PMS system in real water environments is also verified. The insights gained from this study are expected to significantly advance wastewater decontamination from phosphonates and enhance our cognition regarding the nonradical mechanism of peroxide activation by carbon-based materials. © 2025

关键词： Wastewater reclamation

来源：评论

学校读者我要写书评

暂无评论

Enhancing simultaneous nitrogen and phosphorus removal from municipal wastewater using micron zeolite powder carrier and hydrocyclone separator: Microbial distribution and correlation analysis

引用

Bioresource Technology 2025年 431卷 132598页

作者： Wang, Hong Liu, Shiyu Li, Yanzeng Li, Xinyu Li, Lei Yuan, Shijie Dai, Xiaohu State Key Laboratory of Pollution Control and Resource Reuse College of Environmental Science and Engineering Tongji University 1239 Siping Road Shanghai200092 China School of Civil and Environmental Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

This study developed a novel wastewater treatment process for efficient nitrogen and phosphorus removal using micron zeolite powder carriers and hydrocyclone separator. Under anaerobic/intermittent aeration, the total nitrogen and phosphorus removal efficiencies reached 85.2 ± 1.9 % and 78.9 ± 3.4 %, respectively, significantly outperforming conventional activated sludge system. High specific surface area and porosity of zeolite powder facilitated microbial aggregation and biofilm formation, resulting in an average sludge size of 125.3 ± 5.3 μm. The combination of powder carriers and hydrocyclone separators resulted in the differentiated distribution of functional microorganisms. Denitrifying bacteria, such as norank_Comamonadaceae (4.34 %), norank_AKYH767 (1.90 %), and Candidatus_Microthrix (2.61 %), were enriched in biofilm, while nitrifying bacteria and polyphosphate-accumulating organisms predominated in floc. Functional gene abundance related to denitrification and phosphorus removal was significantly upregulated. Correlation network analysis revealed enhanced microbial cooperation, improving the functionality and stability of community. This study offers the potential pathway for efficient nitrogen and phosphorus removal from municipal wastewater. © 2025 Elsevier Ltd

关键词： Biofilms

来源：评论

学校读者我要写书评

暂无评论

Microplastics in lakes: Distribution patterns and influencing factors

引用

Journal of Hazardous Materials 2025年 493卷

作者： Liang, Sijia Liu, Jianchao Bao, Meijun Fan, Yifan Kong, Ming Nanjing Institute of Environmental Sciences Ministry of Ecology and Environment Nanjing210042 China College of Environment Hohai University Jiangsu Nanjing210098 China State Key Laboratory of Pollution Control and Resource Reuse School of Environment Nanjing University Nanjing210023 China

As a kind of new pollutants, microplastics (MPs) have aroused public concern due to their widespread presence and potential ecological risks. Lakes, as crucial freshwater ecosystems and important water resources, are particularly vulnerable to MPs pollution. While MPs are known to be unevenly distributed within lakes, their distribution patterns and influencing factors have not been thoroughly understood. This review analyzes 84 field studies across 64 lakes worldwide to elucidate MPs distribution patterns and their driving mechanisms. Analysis reveals that MPs abundance is typically highest near areas of intense human activity and major water inflows, though hydrodynamics and wind conditions also influence spatial patterns. MPs characteristics (shape, size, color, polymer type) show distinct distribution patterns influenced by source types, transport mechanisms, and degradation processes. While surface water MPs concentrations vary seasonally due to precipitation, wind, and human activities, sediment cores indicate increasing MPs abundance in recent deposits. Integration of water and sediment sampling reveals that MPs characteristics affect their vertical distribution, with denser particles prone to sedimentation. This review identifies key knowledge gaps, including limited data on vertical distributions and temporal variations, and emphasizes the need for standardized methods and quantitative analysis of driving factors. These reviewed findings provide a foundation for understanding MPs fate in lake ecosystems and improving risk assessment capabilities, offering valuable insights for future surveys on MPs. © 2025 Elsevier B.V.

关键词： Lake pollution

来源：评论

学校读者我要写书评

暂无评论

How small is big enough? Big data-driven machine learning predictions for a full-scale wastewater treatment plant

引用

Water Research 2025年 274卷 123041页

作者： Ma, Yanyan Qiao, Yiheng Chen, Mengxue Rui, Dongni Zhang, Xuxiang Liu, Weijing Ye, Lin State Key Laboratory of Pollution Control and Resource Reuse School of Environment Nanjing University Nanjing210023 China Nanjing Gaoke Environmental Technology Co. Ltd. Nanjing210038 China Jiangsu Provincial Key Laboratory of Environment Engineering Jiangsu Provincial Academy of Environmental Science Nanjing210036 China

Wastewater treatment plants (WWTPs) generate vast amounts of water quality, operational, and biological data. The potential of these big data, particularly through machine learning (ML), to improve WWTP management is increasingly recognized. However, the costs associated with data collection and processing can rise sharply as datasets grow larger, and research on determining the optimal data volume for effective ML application remains limited. In this study, we comprehensively analyzed water quality, operational, and biological data collected from a full-scale WWTP over 970 days. Our results demonstrate that ML models can predict not only operational and water quality parameters (concentrations of dissolved oxygen and effluent chemical oxygen demand) but also the abundances of functional bacteria. Notably, we discovered that increasing data volume does not always improve model performance, and that data collection intervals do not need to be excessively small, as moderate intervals can still yield reliable predictions. These findings suggest that excessively large datasets may not be necessary for effective ML predictions in WWTPs. Overall, this study underscores the importance of optimizing dataset size to balance computation efficiency and prediction accuracy, providing valuable insights into data management strategies that can enhance the operational efficiency and sustainability of WWTPs. © 2024 Elsevier Ltd

关键词： Data accuracy

来源：评论

学校读者我要写书评

暂无评论

Identification of pollutant markers in rural mountainous areas of China by combining non-targeted analysis with zebrafish embryo toxicity tests

引用

Science of the Total Environment 2025年 965卷 178625页

作者： Li, Jiaqi Zhou, Min Chen, Zhongli Guo, Jinsong Fang, Fang Schäffer, Andreas Shao, Ying Key Laboratory of the Three Gorges Reservoir Region's Eco-Environment Ministry of Education Chongqing University Chongqing400045 China Institute for Environmental Research RWTH Aachen University Aachen52074 Germany State Key Laboratory of Pollution Control and Resource Reuse School of the Environment Nanjing University Nanjing210093 China

Emerging pollutants (EPs) are increasingly found around the world, yet their composition and the risks pose to soil environments remain unclear, making a challenge to EP management, particularly in mountainous rural areas. In this study, we collected soils from three types of mountainous villages, each representing different levels of economic development: an industrial village, an ecotourism village, and an agricultural village. We analyzed these samples using non-target analysis and Danio rerio embryotoxicity test (ZET). A total of 216 compounds (level 2) were identified by matching with mzCloud database, with 149, 107, and 157 found in YY (industrial village), DX (ecotourism village) and LH (agricultural village), respectively. Interestingly, 78 compounds were present in all three villages, while the number of unique substances ranged from 7 to 47 in each village, serving as potential pollution markers. The most prevalent substances identified were aliphatics, heterocyclics, and aromatics. The ZET results showed that all soil extracts had significant acute toxic effects. Further analysis revealed a correlation between the toxic substances and the economic types of the villages. Specifically, linear chain dicarboxylic acids, drugs, and oxygenated polycyclic aromatic hydrocarbons (OPAHs) were the primary toxicants in the industrial village, whereas phthalate esters dominated in the other two villages. These findings provide valuable insights for effective monitoring of EPs in mountainous rural areas. © 2025 Elsevier B.V.

关键词： Methyl ester

来源：评论

学校读者我要写书评

暂无评论

Enhanced fluoride removal from drinking water by activated carbon supported Ce-Al oxides: performance and mechanism

引用

RSC advances 2025年第18期15卷 14363-14374页

作者： Shaoying Guo Fuwang Zheng Junchao Xu Juan Jiang Zhou Cui Chunshan Wu Yilong Lin Qiyuan Sun Yuyi Zheng Baisheng Sa School of Pharmacy Fujian Health College Fuzhou 350101 China. College of Environmental and Resource Sciences Fujian Normal University Fujian Key Laboratory of Pollution Control & Resource Reuse Fujian College and University Engineering Research Center for Municipal Waste Resourceization and Management Fuzhou 350007 China zhengyy@***. Fujian Xiamen Environmental Monitoring Center Station Xiamen 361022 China. Multiscale Computational Materials Facility & Materials Genome Institute School of Materials Science and Engineering Fuzhou University Fuzhou 350108 China bssa@***. Fuzhou Research Academy of Environmental Science Fuzhou 350011 China.

Elevated fluoride levels in drinking water pose a significant challenge to human health, necessitating affordable and effective adsorbents for fluoride removal. This study presents the synthesis of a Ce-Al binary metal oxide composite adsorbent supported on activated carbon (Ce-Al-O/AC) for the defluoridation of drinking water. The adsorbent, employing the synergistic bimetallic effect, demonstrates robust fluoride removal performance across a wide pH range of 4-10. It is worth highlighting that the equilibrium adsorption capacity reaches 17.97 mg g at 298 K and pH 6 within 2 h, utilizing an adsorbent dose of 0.5 g L in an initial 10 mg L fluoride solution. The phosphate exerts the most significant influence on the defluoridation efficiency. The adsorption kinetics and isotherms align with the pseudo-second-order kinetics model and Langmuir isotherm model, respectively. Moreover, the defluoridation process is characterized as spontaneous and endothermic, with a maximum adsorption capacity of 31.65 mg g at 298 K. Further experimental and theoretical evidences reveal that fluoride adsorption is primarily driven by electrostatic interactions and ion exchange. The dynamic adsorption tests coupled with economic analyses highlight the promise of Ce-Al-O/AC as a cost-effective and efficient adsorbent for practical drinking water defluoridation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Treatment of high concentration phenol wastewater by low-frequency ultrasonic cavitation and long-term pilot scale study

引用

Chemosphere 2025年 370卷 143937页

作者： Sun, Haohao Li, Jie Zhang, Yunian Zhuang, Lu Zhou, Zhou Ren, Yanfang Xu, Xia He, Junyu Xue, Yingang School of Environmental Science and Engineering Changzhou University Jiangsu Changzhou213164 China State Key Laboratory of Pollution Control and Resource Reuse School of the Environment Nanjing University Jiangsu Nanjing China College of Urban Construction Changzhou University Jiangsu Changzhou213164 China

Acoustic cavitation is an advanced, eco-friendly oxidation technology effective in removing organic pollutants from water. However, research on its use for degrading phenol, a common and challenging phenolic pollutant, is limited. This study explores the optimal conditions for phenol degradation using acoustic cavitation and assesses its practical application through extensive pilot tests. Results from batch tests show that low-frequency (15 kHz) ultrasonic cavitation effectively treats high concentrations of phenol (1000 mg L−1). Aeration and acidic pH enhance removal efficiency, while alkaline conditions inhibit degradation. Analysis of total organic carbon (TOC), degradation products, and volatile organic compounds (VOCs) reveals that the primary intermediates are substituted benzenes and alkanes. Long-term pilot tests demonstrated the device's effectiveness in phenol removal and its operational stability over 180 days. The study also establishes a relationship between removal efficiency, hydraulic retention time (HRT), and operating costs, highlighting the feasibility of low-frequency ultrasonic cavitation for treating high-concentration phenolic wastewater and its potential role in the pretreatment stage of biochemical processes. © 2024

关键词： Wastewater treatment

来源：评论

学校读者我要写书评

暂无评论

Cost-Effective Mapping of Hyperlocal Air pollution Using Large-Scale Mobile Monitoring and Land-Use Machine Learning

ACS ES&T Air

引用

ACS ES&T Air 2025年第2期2卷 151-161页

作者： Tie Zheng Yifan Wen Sheng Xiang Pan Yang Xuan Zheng Yan You Shaojun Zhang Ye Wu School of Environment State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua University Beijing 100084 China State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Beijing Normal University Beijing 100875 China State Key Laboratory of Pollution Control and Resource Reuse Tongji University Shanghai 200092 China；College of Environmental Science and Engineering Tongji University Shanghai 200092 China College of Chemistry and Environmental Engineering Shenzhen University Shenzhen 518060 China Macao Environmental Research Institute Macau University of Science and Technology Macau 999078 China；National Observation and Research Station of Coastal Ecological Environments in Macao Macao Environmental Research Institute Macau University of Science and Technology Macao 999078 China School of Environment State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua University Beijing 100084 China；State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084 China；Beijing Laboratory of Environmental Frontier Technologies Beijing 100084 China

The advent of large-scale mobile monitoring using fast-response instruments has enabled hyperlocal mapping (≤100 m) of traffic-related air pollution (TRAP), with important implications for air quality management. However, most related studies have been confined within small areas due to the high cost and labor intensity. This study pioneers a cost-effective TRAP mapping method by incorporating large-scale mobile monitoring and land-use machine learning (LUML). Here, over 4.6 million 1 Hz high-frequency measurements (∼1300 h) were collected on a part of major roadways in the Chinese megacity of Shenzhen. Unmeasured locations were estimated by LUML models to reduce measurement costs and labor intensity. Various ML algorithms and varying spatial aggregation segment lengths were incorporated to optimize the model performance. Hyperlocal maps of NO, NO2, and PM2.5were predicted across the entire road network covering over 1700 km2. Based on our results, LU-RF (random forest) for mapping NO and NO2and LU-GBM (Gradient Boosting Machine) for mapping PM2.5, demonstrated superior performance. Deep learning models, in contrast, did not yield comparable results. Finer partitioning of road segments (≤100 m) improved NO prediction performance, but worsened that for NO2and PM2.5. By deployment of optimal ML algorithms and segment lengths, the TRAP mapping accuracy increased by 20–80% compared to conventional land-use regression models. This study provides a promising and cost-effective approach to hyperlocal air pollution mapping and management in cities worldwide.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhanced catalytic ozonation of fiberboard wastewater using Ni-Cu co-doped Fe-ceramsite derived from sludge digestion residues

引用

Journal of Cleaner Production 2025年 503卷

作者： Zheng, Qiang Li, Lei Jin, Ruofei Ji, Qiuyan Duan, Xiumei Zhou, Jiti Tian, Tian School of Environmental Science and Technology Dalian University of Technology Dalian116024 China State Key Laboratory of Pollution Control & Resource Reuse School of Environment Nanjing University Nanjing210023 China College of Chemistry and Environmental Engineering Yingkou Institute of Technology Yingkou115014 China

Passivation of metal catalysts hinders heterogeneous catalytic ozonation in degrading refractory organic pollutants (ROP). With strong electron interactions, polymetallic catalysts can enhance interfacial electromigration and regenerate active sites, improving ROP degradation. In this study, a Ni-Cu@Fe-Ceramsite catalyst was developed by co-doping nickel and copper onto Fe-ceramsite derived from sludge digestion residue, targeting ozonation of fiberboard wastewater. Morphological analysis showed nickel and copper uniformly distributed on the catalyst surface, increasing active sites while preserving porosity. Ni-Cu@Fe-Ceramsite achieved a 76.1 % removal of ROP at an initial CODcr concentration of 260 mg/L, representing a 14.6 % increase in ROP degradation efficiency and a 12 % improvement in ozone utilization compared to unmodified Fe-ceramsite. Additionally, it outperformed ozone alone by 33.6 % in degradation efficiency and 23 % in ozone utilization. The enhanced performance is attributed to the synergistic effects of nickel, copper, and iron, which boost metal reduction and the catalyst's electron-supplying ability, initiating reactions that decompose ozone molecules into reactive oxygen species such as ·OH, ·O2−, 1O2. This study underscores the potential of Ni-Cu@Fe-Ceramsite as an effective catalyst for wastewater treatment. © 2025 Elsevier Ltd

关键词： Ozonization

来源：评论

学校读者我要写书评

暂无评论

Climate Downscaling Using Neural Operator: Spatiotemporal Multimodal Fusion Operator with State-Query Coupled Kernel

Climate Downscaling Using Neural Operator: Spatiotemporal Mu...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Haodi Zhang Yichi Wang Yifan Jian Jiahui Jiang Zhaohai Bai Lin Ma College of Computer Science and Software Engineering Shenzhen University Center for Agricultural Resources Research Institute of Genetic and Developmental Biology Chinese Academy of Sciences State Key Laboratory of Pollution Control and Resource Reuse School of the Environment Nanjing University

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Climate downscaling is crucial for detailed small- scale analysis and for acquiring climate data in regions without weather stations. Operator learning has proven potential for this task. However, several challenges remain in operator learning, such as multimodal fusion, spatiotemporal fusion and input state and query adaptation. To address these challenges, we propose a Spatiotemporal Multimodal Fusion Operator with a State- Query Coupled Kernel (SMCK). This framework includes a latent space fusion encoder that encodes climate variables using position-wise multihead attention for multimodal fusion and integrates historical information to generate robust and precise representation. Additionally, we introduce a state-query coupled kernel that combines radial basis functions and discrete fourier encoding to enhance query location representation, while also adapting to the state to obtain the coupled kernel. Extensive experiments demonstrate that our method achieves state-of-the-art performance and provides strong support for climate downscaling and the planning of climate-related strategies.

关键词： Couplings Signal processing Encoding Robustness Spatiotemporal phenomena Planning Kernel Speech processing Forecasting Meteorology

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：