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Promotion effect of Ce and Ta co-doping on the NH_(3)-SCR performance over V_(2)O_(5)/TiO_(2)catalyst

Journal of environmental Sciences 2025年第4期150卷 332-339页

作者： Long Liu Xin Shen Zhihua Lian Chunxi Lin Ying Zhu Wenpo Shan Hong He Collaborative Innovation Center of Chemistry for Energy Materials College of Chemistry and Chemical EngineeringXiamen UniversityXiamen 361005China Center for Excellence in Regional Atmospheric Environment and Key Laboratory of Urban Pollutant Conversion Institute of Urban EnvironmentChinese Academy of SciencesXiamen 361021China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China University of Chinese Academy of Sciences Beijing 100049China

NH_(3)-SCR(SCR:Selective catalytic reduction)is an effective technology for the de-NO_(x)process from both mobile and stationary pollution sources,and the most commonly used catalysts are the vanadia-based *** innovative V_(2)O_(5)-CeO_(2)/TaTiO_(x)catalyst for NO_(x)removal was prepared in this *** influences of Ce and Ta in the V_(2)O_(5)-CeO_(2)/TaTiO_(x)catalyst on the SCR performance and physicochemical properties were *** V_(2)O_(5)-CeO_(2)/TaTiO_(x)catalyst not only exhibited excellent SCR activity in a wide temperature window,but also presented strong resistance to H_(2)Oand SO_(2)at 275◦C.A series of characterizationmethods was used to study the catalysts,including H2-temperature programmed reduction,X-ray photoelectron spectroscopy,NH_(3)-temperature programmed desorption,*** was discovered that a synergistic effect existed between Ce and Ta *** introduction of Ce and Ta enlarged the specific surface area,increased the amount of acid sites and the ratio of Ce^(3+),(V^(3+)+V^(4+))and Oα,and strengthened the redox capability which were related to synergistic effect between Ce and Ta species,significantly improving the NH_(3)-SCR activity.

关键词： NH_(3)-SCR Vanadia-based catalysts Synergistic effect Co-doping Low temperature

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Insight into the effects of C_(3)H_(6)on fresh and hydrothermally aged Cu-SSZ-39 catalysts

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Chinese Chemical Letters 2025年第3期36卷 164-169页

作者： Jinpeng Du Junlin Chen Yulong Shan Tongliang Zhang Yu Sun Zhongqi Liu Xiaoyan Shi Wenpo Shan Yunbo Yu Hong He State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China University of Chinese Academy of Sciences Beijing 100049China Ganjiang Innovation Academy Chinese Academy of SciencesGanzhou 341119China Center for Excellence in Regional Atmospheric Environment Institute of Urban EnvironmentChinese Academy of SciencesXiamen 361021China

Hydrocarbons(HCs),as major poisoning substances,have a crucial influence on NH_(3)-SCR *** this work,the effects of C_(3)H_(6)on fresh and hydrothermally aged Cu-SSZ-39 catalysts with different copper contents were *** catalysts suffered a deactivation above 250℃,especially between 300-400℃,which was mainly related to the reaction between NH_(3)and C_(3)H_(6).However,the hydrothermally aged and the high-copper-loaded Cu-SSZ-39 catalysts could achieve a recovery of NH_(3)-SCR performance at high *** activity recovery was attributed to the oxidation of C_(3)H_(6)by CuxOy species,which therefore inhibited the reaction between NH_(3)and C_(3)H_(6).As a result,more NH_(3)could be available for the NH_(3)-SCR reaction and the Cu-SSZ-39 catalysts could maintain a good catalytic *** on these findings,we proposed that high loaded Cu-SSZ-39 catalysts with a little CuOx formed are preferred for application.

关键词： Diesel vehicle emission NO_(x)abatement NH3-SCR Cu-SSZ-39 zeolite C_(3)H_(6)poisoning

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Optimization of Regional Energy-Water Nexus System Under Multiple Uncertainties 15th

Optimization of Regional Energy-Water Nexus System Under Mul...

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15th International Conference on environmental Science and Development, ICESD 2024

作者： Liu, Ruoyan Li, Yongping Huang, Guohe Zhou, Yanxiao Li, Yanfeng State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Beijing Normal University Beijing China Institute for Energy Environment and Sustainable Communities University of Regina Regina Sask Canada

ISBN: (纸本)9783031886829

In this paper, an interval chance-constrained programming (ICCP) method is proposed for collaborative energy-water nexus (EWN) system under multiple uncertainties. This method can solve the uncertainties expressed as probability distribution and interval. An ICCP-based energy-water nexus (ICCP-EWN) model is established, where 15 scenarios are designed for assessing the effect of water cycle coefficients and constraint violation risk. The results show that: (i) coal would remain the main energy sources for future energy supply, but the proportion of clean energy (e.g., natural gas, biomass) in the future power generation structure would significantly increase (about 15.6%);(ii) the water withdrawal of power generation in the energy system would be largest, where thermal power generation would have the largest proportion of water withdrawal, accounting for 85.0%;(iii) the decreasing α level and increasing p level will bring higher system benefits, and the reliability of the system would be reduced. These results can help determine the energy mix of a planned area, improve security of energy supply, and make trade-off between system benefits and the risk of violating constraints. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： chance-constrained programming energy-water nexus Kaikong river uncertainty

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Remarkable Enhancement of the Activity and Hydrothermal Stability of a CeO2-Based NH3-SCR Catalyst by Sn Modification

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Engineering 2025年第5期48卷 141-150页

作者： Zhu, Ying Liu, Jingjing He, Guangzhi Xie, Shaohua Shan, Wenpo Lian, Zhihua Liu, Fudong He, Hong Center for Excellence in Regional Atmospheric Environment & Key Laboratory of Urban Pollutant Conversion Institute of Urban Environment Chinese Academy of Sciences Xiamen361021 China Zhejiang Key Laboratory of Pollution Control for Port-Petrochemical Industry Ningbo Urban Environment Observation and Research Station Institute of Urban Environment Chinese Academy of Sciences Ningbo315800 China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing100085 China University of Chinese Academy of Sciences Beijing100049 China Department of Civil Environmental and Construction Engineering Catalysis Cluster for Renewable Energy and Chemical Transformations NanoScience Technology Center University of Central Florida OrlandoFL32816 United States

Catalytic activity and hydrothermal stability are both crucial for the application of the selective catalytic reduction of NOx with NH3 (NH3-SCR) catalyst in diesel vehicles. In this study, a tin (Sn)-modified Ce–Nb mixed-oxide catalyst was synthesized as an NH3-SCR catalyst for NOx emission control. After the introduction of Sn, both the NH3-SCR activity and the hydrothermal stability of the catalyst were remarkably promoted. Even after hydrothermal aging at 1000 °C, the developed Ce1Sn2Nb1Ox catalyst achieved more than 90% NOx conversion at 325–500 °C. Various methods, including N2-physisorption, X-ray diffraction, in-situ high-temperature X-ray diffraction, high-resolution transmission electron microscopy, X-ray photoelectron spectroscopy, X-ray absorption fine-structure spectroscopy, temperature-programmed reduction of hydrogen, temperature-programmed desorption of ammonia, and density functional theory calculations were used to investigate the promotional effects induced by the Sn species. The characterization results showed that the addition of Sn not only promoted the formation of the Ce–Nb active phase but also improved its thermal stability, contributing to the excellent NH3-SCR performance and hydrothermal stability. This study provides an excellent sintering-resistance catalyst for the application of diesel engine NOx emission control. © 2025 THE AUTHORS

关键词： Temperature programmed desorption

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Transport, transformation, and ecological impacts of brominated flame retardants in soils: A comprehensive review

Environmental Chemistry and Ecotoxicology

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environmental Chemistry and Ecotoxicology 2025年 7卷 1142-1157页

作者： Jia Zhang Dan Li Ying Yuan Kunlong Hui Wenbing Tan State Key Laboratory of Environmental Criteria and Risk Assessment State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution Chinese Research Academy of Environmental Sciences Beijing 100012 China

Brominated flame retardants (BFRs) have become significant contaminants of emerging concern (CECs), resulting in detrimental effects on soil health, human health, and ecosystem sustainability. Their environmental impacts have spurred extensive research into environmental chemistry and ecotoxicology. Despite the widespread detection of both BFRs and Novel Brominated Flame Retardants (NBFRs) in soils, there are few assessments of the environmental behavior and fate of the BFRs. Therefore, this review comprehensively identifies the sources, distribution, transport, transformation, ecotoxicological effects, and remediation strategies of BFRs in soils. Principal findings indicate that adsorption-desorption, mostly influenced by soil organic matter, controls the mobility and transformation of BFRs. Photolysis dominates surface soils, while aerobic and anaerobic biodegradation predominate in subsurface layers. The main factors influencing the bioavailability of BFRs are shed light on in this review. These factors such as the physicochemical properties of BFRs, soil characteristics, and combined pollution are specifically discussed. Moreover, the development, physiological, and biochemical responses of soil organisms to exposure to the BFRs are summarized. Single strategies for addressing BFRs have certain limitations. Urgent actions are needed to focus on environmental behavior and remediation strategies under the “One Health” framework to enrich research gap areas of BFRs, NBFRs, and transformation products.

关键词： Brominated flame retardants Soil Transport Transformation Bioavailability Toxicity

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Enhanced Ru–Ce interface electron transfer and reverse oxygen spillover promote chlorobenzene catalytic oxidation

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Applied Catalysis B: environmental 2025年 373卷

作者： Chen, Deli Si, Wenzhe Wang, Rong Yuan, Xing Zhou, Bin Chen, Zhen Peng, Yue Li, Junhua State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China

The catalytic oxidation of chlorinated volatile organic compounds (CVOCs) is still a big challenge due to chlorine poisoning and the polychlorinated byproducts. Ru-loaded CeO2 catalysts have attracted much attention in CVOCs oxidation. To optimize the surface electronic structure of Ru/CeO2, we reduced the CeO2 support to enhance the metal-support interaction of the Ru/CeO2 catalyst, resulting in higher Ru dispersion and stronger interface electron transfer. The Reduction treatment not only enhances the activation of O2 molecules by promoting the generation of interface electron-rich units but also stimulates stronger reverse oxygen spillover (ROS). The improved oxygen activation and migration ability accelerates the decomposition of intermediate products. Besides, the lower surface electrostatic potential also weakens the chlorine adsorption of the catalyst. After the modification, the oxidation rate of chlorobenzene increased by more than 1.5 times at 240–320 °C and the T90 decreased by about 50 °C. © 2025

关键词： Catalytic oxidation

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Machine learning for membrane bioreactor research:principles,methods,applications,and a tutorial

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Frontiers of environmental Science & Engineering 2025年第3期19卷 119-144页

作者： Yizhe Lai Kang Xiao Yifan He Xian Liu Jihua Tan Wenchao Xue Aiqian Zhang Xia Huang Beijing Yanshan Earth Critical Zone National Research Station College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijing 101408China Key Laboratory of Earth System Numerical Modeling and Application University of Chinese Academy of SciencesBeijing 101408China Environmental Chemistry Faculty College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijing 101408China State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China Department of Energy Environmentand Climate ChangeSchool of EnvironmentResourcesand DevelopmentAsian Institute of TechnologyP.O.Box 4Klong LuangPathumthani 12120Thailand State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China

Membrane fouling poses a significant challenge to the sustainable development of membrane bioreactor(MBR)technologies for wastewater *** accurate prediction of the membrane filtration process is of great importance for identifying and controlling *** learning methods address the limitations of traditional statistical approaches,such as low accuracy,poor generalization ability,and slow convergence,particularly in predicting complex filtration and fouling processes within the realm of big *** article provides an in-depth exposition of machine learning *** study then reviews advances in MBRs that utilize machine learning methods,including artificial neural networks(ANN),support vector machines(SVM),decision trees,and ensemble *** on current literature,this study summarizes and compares the model input and output characteristics(including foulant characteristics,solution environments,filtration conditions,operating conditions,and time factors),as well as the selection of models and optimization *** modeling procedures of SVM,random forest(RF),back propagation neural network(BPNN),long short-term memory(LSTM),and genetic algorithm-back propagation(GA-BP)methods are elucidated through a tutorial *** simulation results demonstrated that all five methods yielded accurate predictions with R2>***,the existing challenges in the implementation of machine learning models in MBRs were *** is notable that integration of deep learning,automated machine learning(AutoML)and explainable artificial intelligence(XAI)may facilitate the deployment of models in practical engineering *** insights presented here are expected to facilitate the establishment of an intelligent control framework for MBR processes in future endeavors.

关键词： Membrane bioreactor Machine learning Pollutant removal Membrane fouling Model prediction

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

ACS ES&T Air

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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.

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Multimedia contamination characteristics, risk assessment, and source quantification of phthalates in the Shaying River Basin, China

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environmental Geochemistry and Health 2025年第6期47卷 1-19页

作者： Hao, Minghui Zuo, Qiting Zhao, Xinna Shi, Shujuan Wu, Junfeng Gao, Hongbin Lu, Yizhen School of Municipal and Environmental Engineering Henan University of Urban Construction Pingdingshan467036 China Henan Key Laboratory of Water Pollution Control and Rehabilitation Technology School of Municipal and Environmental Engineering Henan University of Urban Construction Pingdingshan467036 China School of Water Conservancy and Transportation Zhengzhou University Zhengzhou450001 China Henan International Joint Laboratory of Water Cycle Simulation and Environmental Protection Zhengzhou450001 China Henan Ecological Environmental Monitoring Center Zhengzhou450003 China

Phthalates (PAEs), a class of typical endocrine-disrupting chemicals, have been widely detected in the environment due to their prevalent use as plasticizers in plastic products. This study investigates the multimedia contamination characteristics and potential ecological risks of PAEs in water, soil, and sediments of the Shaying River (SYR) Basin. A Geodetector model (GDM) was employed to identify the key drivers influencing the spatial distribution of PAEs, while factor analysis and the Positive Matrix Factorization (PMF) model were utilized to quantitatively apportion the potential sources of PAEs. Results revealed that the concentrations and spatial variation of PAEs were significantly higher in soil and sediments than in water, with distinct compositional profiles. Water samples exhibited a higher proportion of low-molecular-weight PAEs compared to soil and sediment, where high-molecular-weight PAEs prevailed to a lesser extent. Notably, among the 6 target PAEs, di-n-butyl phthalate (DBP) and di-(2-ethylhexyl) phthalate (DEHP) were uniformly the primary PAEs in water, soil, and sediment of the SYR Basin, posing higher ecological risks to algae, crustaceans, amphibians, and fish compared to the other 4 PAEs. The spatial distribution of PAEs in the SYR Basin was comprehensively influenced by land use, precipitation, human activities, and soil types. key factors vary across media, but the interaction between popdensity and other variables significantly enhanced the interpretation degree, jointly shaping the PAEs distribution patterns. Primary sources of PAEs in the basin were sewage and wastewater discharges (37.0%), nonpoint industrial sources (36.4%), and domestic sources (25.6%). © The Author(s), under exclusive licence to Springer Nature B.V. 2025.

关键词： Risk assessment

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Daytime Ozone Production Determined by Ratios of Total Volatile Organic Compound Consumption to Nitrogen Oxide Concentrations

ACS ES&T Air

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ACS ES&T Air 2025年第3期2卷 331-342页

作者： Xudong Zheng Qinwen Tan Jie Ren Bin Luo Danlin Song Miao Feng Hefan Liu Yue Qin Yufang Hao Liming Zeng Xin Li Sihua Lu Huabin Dong Shaodong Xie College of Environmental Sciences and Engineering State Key Joint Laboratory of Environmental Simulation and Pollution Control Peking University Beijing 100871 China Chengdu Academy of Environmental Sciences Chengdu Sichuan 610072 China Sichuan Academy of Environmental Policy and Planning Chengdu Sichuan 610041 China College of Environmental Sciences and Engineering State Key Joint Laboratory of Environmental Simulation and Pollution Control Peking University Beijing 100871 China；Laboratory of Atmospheric Chemistry Energy and Environment Research Division Paul Scherrer Institute Villigen 5232 Switzerland

To reduce the uncertainty in analyzing ozone (O3) sensitivities based on observed concentrations of volatile organic compounds (VOCs) and nitrogen dioxide, this study proposed the application of consumed VOC concentrations to establish their nonlinear relationship in the actual atmosphere. These parameters were calculated based on the reaction rates and online observations of VOCs, nitrogen dioxide, and O3concentrations at Deyang, Chengdu, and Meishan in the Chengdu Plain, China, during summer 2019. The nighttime isoprene consumption was maximum at 2.03 ppbv at Meishan. The daytime acetaldehyde consumption was a maximum at 2.68 ppbv at Deyang, possibly due to its higher primary emissions and secondary production and its consumption by both OH radicals and photolysis. When the ratios of the total consumed VOC concentrations to the observed or initial NOx(NOx= NO + NO2) concentrations were 3.51 ppbv ppbv–1or 2.22 ppbv ppbv–1, daytime O3variations reached a maximum of 8.45 ppbv or 7.52 ppbv, respectively. The ratios delineated the VOC-sensitive and NOx-sensitive areas. Over 98% of hourly data were in VOC-sensitive areas at both Chengdu and Meishan, respectively, while over 14% of hourly data belonged to NOx-sensitive areas at Deyang. This provided a more accurate method for assessing real-time O3sensitivity and thus implementing dynamic hierarchical control strategies.

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