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Science Bulletin 2023年第18期68卷 1989-1992页

作者：陆克定周厚华 James Lee Beth Nelson 张远航 State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control State Key Joint Laboratory of Environmental Simulation and Pollution ControlCollege of Environmental Sciences and EngineeringPeking UniversityBeijing 100871China National Centre for Atmospheric Science Department of ChemistryUniversity of YorkYork YO105DDUK

Ambient ozone(O3)was first identified as a key harmful air pollutant in the study of photochemical smog during the 1950s in Los *** studies uncovered that surface O3 was not emitted directly,but formed from the reactions of nitrogen oxides(NO_(x))and volatile organic compounds(VOCs)in *** the relationship between O3 and its two main precursors,NOx and VOCs,is considered to be the cornerstone for enabling successful mitigation of *** the past,a central area for the study and practice of O3 pollution control was Los Angeles and the surrounding *** ambient O3 concentrations in the area were successfully and continuously reduced from 400 ppb(1 ppb=109 m^(3)/m^(3))to ca.120 ppb due to the joint mitigation of VOC and NOx emissions from 1960 to 2010[1].Nevertheless,O3 pollution still represents one of the most pervasive and stubborn environmental problems in megacities worldwide,with many populous centres regularly breaching WHO 8-hour Interim Targets-1 levels(160 lg/m^(3)),not to mention the updated air quality guideline value of 100 lg/m^(3).The difficulty of O3 pollution control is due to a number of factors,including its non-linear relationship with NOx[2],the difficulty of anthropogenic VOC control[3]and the contributions of biogenic VOCs.

关键词： pollution difficulty corners

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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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Improving Fugitive Dust Emission Inventory from Construction Sector Using UAV Images Recognition

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Aerosol and Air Quality Research 2024年第8期24卷 1-18页

作者： He, Yuyao Jang, Jicheng Zhu, Yun Chiang, Pen-Chi Xing, Jia Wang, Shuxiao Zhao, Bin Long, Shicheng Yuan, Yingzhi Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control College of Environment and Energy South China University of Technology Guangzhou Higher Education Mega Center Guangzhou510006 China Graduate Institute of Environmental Engineering Taiwan University Taipei10673 Taiwan Carbon Cycle Research Center National Taiwan University Taipei10672 Taiwan Department of Civil and Environmental Engineering University of Tennessee KnoxvilleTN37996 United States State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China

Over rapidly developing and urbanizing countries, frequent construction activities are the primary drivers behind the substantial emissions and contributors of fugitive dust. In this study, an innovative method was developed to compile a high-resolution spatiotemporal emission inventory from construction sector, utilizing unmanned aerial vehicle (UAV) images. This methodology offered detailed activity level information by distinguishing various types of construction lands and equipment. Focusing on the Shunde District of Guangdong in China, the new emission inventory derived from this method highlighted that travel, topsoil excavation, and loading collectively contributed up to 90% of particulate matter (PM) emissions during the earthwork phase. Moreover, this new inventory rectified the tendency of traditional methods to underestimate PM10 emissions and overestimate PM2.5 emissions, while revealing the non-linear relationship between PM emissions and construction area. This improved PM emission inventory appeared to precisely identify major emission hotspots and enhanced performance of the Community Multi-scale Air Quality (CMAQ) model, and the correlation coefficient (R-value) is 0.08 ± 0.02 higher than that of the traditional emission inventory. Post integration of monitoring data through the Software for the Modeled Attainment Test-Community Edition (SMAT-CE), the contributions of construction dust to local PM10 and PM2.5 concentrations were estimated at 3.27 ± 0.8 µg m–3 and 1.11 ± 0.27 µg m–3, respectively, with more pronounced impacts observed in the central, northwestern, and south-central zones of the study region. This study provides valuable insight for improving construction dust and PM emission inventories, which should be benefiting the development of air pollution prevention and control strategies over this study area as well as other rapidly growing urban areas. © The Author(s).

关键词： Image enhancement

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Emerging Organic Contaminants in Chinese Surface Water:Identification of Priority Pollutants

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Engineering 2022年第4期8卷 111-125页

作者： Mengmeng Zhong Tielong Wang Wenxing Zhao Jun Huang Bin Wang Lee Blaney Qingwei Bu Gang Yu Beijing Key Laboratory for Emerging Organic Contaminants Control State Key Joint Laboratory of Environment Simulation and Pollution Control(SKLESPC)School of EnvironmentTsinghua UniversityBeijing 100084China Department of Chemical Biochemicaland Environmental EngineeringUniversity of Maryland Baltimore CountyBaltimoreMD 21250USA School of Chemical and Environmental Engineering China University of Mining and Technology-BeijingBeijing 100083China

The occurrence and impacts of emerging organic contaminants(EOCs)in the aquatic environment have gained widespread attention over the past two *** to large number of potential contaminants,monitoring campaigns,treatment plants,and proposed regulations should preferentially focus on specific pollutants with the highest potential for ecological and human health *** the present study,a multi-criteria screening approach based on hazard and exposure potentials was developed for prioritization of 405 unregulated EOCs already present in Chinese surface *** potential,exposure potential,and risk quotients for ecological and human health effects were quantitatively analyzed and used to screen *** hazard potential was defined by contaminant persistence,bioaccumulation,ecotoxicity,and human health effects;similarly,the exposure potential was a function of contaminant concentration and detection *** total,123 compounds passed the preselection process,which involved a priority index equal to the normalized hazard potential multiplied by the normalized exposure *** on the prioritization scheme,11 compounds were identified as top-priority,and 37 chemicals were defined as *** results obtained by the priority index were compared with four other prioritization schemes based on exposure potential,hazard potential,or risk quotients for ecological effects or human *** priority index effectively captured and integrated the results from the more simplistic prioritization *** on identified data gaps,four uncertainty categories were classified to recommend:①regular monitoring,derivation of environmental quality standards,and development of control strategies;②increased monitoring;③fortified hazard assessment;and④increased efforts to collect occurrence and toxicity ***,20 pollutants were recommended as priority *** prioritized list of contaminants provides the necessary information for autho

关键词： Prioritization Emerging organic contaminants Hazard potential Ecotoxicity Risk assessment

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Transformation of dissolved organic matter during groundwater arsenite removal using air cathode iron electrocoagulation

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Chemosphere 2024年 358卷 142083页

作者： Yuan, Ying Chen, Jiabao Zhang, Hao Wu, Yue Xiao, Yu Huang, Wan Wang, Yang Tang, Jun Zhang, Fang State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution Chinese Research Academy of Environmental Sciences Beijing100012 China School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua University Beijing100084 China College of Environmental Science and Engineering Guilin University of Technology Guilin541004 China

Dissolve organic matters (DOM) usually showed negative effect on the removal of inorganic arsenic (As) in groundwater by electrochemical approaches, yet which parts of sub-component within DOM played the role was lack of evidence. Herein, we investigated the effects of land-source humic-like acid (HA) on groundwater As(III) removal using air cathode iron electrocoagulation, based on the parallel factor analysis of three-dimensional excitation–emission matrix and statistical methods. Our results showed that the land-source HA contained five kinds of components and all components presented significantly negative correlations with the removal of both As(III) and As(V). However, the high aromatic fulvic-like acid and low aromatic humic-like acid components of land-source HA presented the opposite correlations with the concentration of As(III) during the reaction. The high aromaticity fulvic-like components of land-source HA (Sigma-Aldrich HA, SAHA) produced during the reaction facilitated the oxidation of As(III) due to its high electron transfer capacities and good solubility in wide pH range, but the low aromaticity humic-like ones worked against the oxidation of As(III). Our findings offered the novel insights for the flexible activities of DOM in electron Fenton system. © 2024 Elsevier Ltd

关键词： Groundwater

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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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An AuNPs/Mesoporous NiO/Nickel Foam Nanocomposite as a Miniaturized Electrode for Heavy Metal Detection in Groundwater

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Engineering 2023年第8期27卷 199-208页

作者： Boyuan Xue Qian Yang Kaidong Xia Zhihong Li George Y.Chen Dayi Zhang Xiaohong Zhou State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China National Key Laboratory of Science and Technology on Micro/Nano Fabrication Institute of MicroelectronicsPeking UniversityBeijing 100871China Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things Guangdong and Hong Kong Joint Research Centre for Optical Fiber SensorsShenzhen UniversityShenzhen 518060China College of New Energy and Environment Jilin UniversityChangchun 130021China The Research Institute of Environmental Innovation(Suzhou) Tsinghua UniversitySuzhou 215000China

Heavy metals,notably Pb2+and Cu^(2+),are some of the most persistent contaminants found in *** monitoring of these metals,which relies on efficient,sensitive,cost-effective,and reliable methods,is a *** present a nanocomposite-based miniaturized electrode for the concurrent measurement of Pb2+and Cu^(2+)by exploiting the electroanalytical technique of square wave *** also propose a facile in situ hydrothermal calcination method to directly grow binder-free mesoporous Ni O on a three-dimensional nickel foam,which is then electrochemically seeded with gold nanoparticles(Au NPs).The meticulous design of a low-barrier Ohmic contact between mesoporous Ni O and Au NPs facilitates target-mediated nanochannel-confined electron transfer within mesoporous Ni *** a result,the heavy metals Pb2+(0.020 mg.L^(-1)detection limit;2.0–16.0 mg.L^(-1)detection range)and Cu^(2+)(0.013 mg.L^(-1)detection limit;0.4–12.8 mg.L^(-1)detection range)can be detected simultaneously with high ***,other heavy metal ions and common interfering ions found in groundwater showed negligible impacts on the electrode’s performance,and the recovery rate of groundwater samples varied between 96.3%±2.1%and 109.4%±0.6%.The compactness,flexible shape,low power consumption,and ability to remotely operate our electrode pave the way for onsite detection of heavy metals in groundwater,thereby demonstrating the potential to revolutionize the field of environmental monitoring.

关键词： AuNPs Mesoporous NiO Miniaturized electrode Heavy metal ions Groundwater Square wave voltammetry

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Identification of resistant pharmaceuticals in ozonation using QSAR modeling and their fate in electro-peroxone process

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Frontiers of environmental Science & Engineering 2021年第5期15卷 325-338页

作者： Majid Mustafa Huijiao Wang Richard H.Lindberg Jerker Fick Yujue Wang Mats Tysklind Department of Chemistry UmeåUniversityUmeåS-90187Sweden School of Environment Beijing Key Laboratory for Emerging Organic Contaminants ControlState Key Joint Laboratory of Environmental Simulation and Pollution Control(Ministry of Education)Tsinghua UniversityBeijing100084China

The abatements of 89 pharmaceuticals in secondary effluent by ozonation and the electro-peroxone(E-peroxone)process were *** on the results,a quantitative structure-activity relationship(QSAR)model was developed to explore relationship between chemical structure of pharmaceuticals and their oxidation rates by *** orthogonal projection to latent structure(OPLS)method was used to identify relevant chemical descriptors of the pharmaceuticals,from large number of descriptors,for model *** resulting QSAR model,based on 44 molecular descriptors related to the ozone reactivity of the pharmaceuticals,showed high goodness of fit(R^(2)=0.963)and predictive power(Q^(2)=0.84).After validation,the model was used to predict second-order rate constants of 491 pharmaceuticals of special concern(k_(O_(3)))including the 89 studied *** predicted k_(O_(3))values and experimentally determined pseudo-first order rate constants of the pharmaceuticals’abatement during ozonation(k_(OZ))and the E-peroxone process(k_(EP))were then used to assess effects of switching from ozonation to the E-peroxone process on removal of these *** results indicate that the E-peroxone process could accelerate the abatement of pharmaceuticals with relatively low ozone reactivity(k_(O_(3))<∼10^(2)M^(−1)⋅s^(−1))than ozonation(3–10 min versus 5–20 min).The validated QSAR model predicted 66 pharmaceuticals to be highly O_(3)-*** developed QSAR model may be used to estimate the ozone reactivity of pharmaceuticals of diverse chemistry and thus predict their fate in ozone-based processes.

关键词： Ozone Electro-peroxone Wastewater Quantitative structure activity relationship Advanced oxidation processes

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Cerium-tungsten oxides supported on activated red mud for the selective catalytic reduction of NO_(x)

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Green Energy & Environment 2023年第1期8卷 173-182页

作者： Qiuzhun Chen Dong Wang Chuan Gao Bin Wang Shengli Niu Gaiju Zhao Yue Peng Junhua Li Chunmei Lu John Crittenden National Engineering Laboratory for Coal-Burning Pollutants Emission Reduction School of Energy and Power EngineeringShandong UniversityJinan250061China State Key Joint Laboratory of Environment Simulation and Pollution Control National Engineering Laboratory for Multi Flue Gas Pollution Control Technology and EquipmentSchool of EnvironmentTsinghua UniversityBeijing100084China Brook Byers Institute for Sustainable Systems and School of Civil and Environmental Engineering Georgia Institute of Technology828 West Peachtree StreetAtlantaGA30332United States Energy Institute Qilu University of Technology(Shandong Academy of Sciences)Jinan250013ShandongChina

Activated red mud(RM)has been proved to be a promising base material for the selective catalysis reduction(SCR)of *** inherent low reducibility and acidity limited its low-temperature *** this work,molybdenum oxide,tungsten oxide,and cerium oxide were used to reconfigure the redox sites and acid sites of red mud based *** activated red mud was reconfigured by cerium-tungsten oxide(Ce-W@RM),the NOx conversion kept above 90%at 219-480℃.The existence of Ce^(3+)/Ce^(4+) redox electron pairs provided more surface adsorbed oxygen(O_(α)) and served as a redox *** interactions between Ce,W species and Fe oxide in red mud occurred,which led to the formation of unsaturated chemical bond and promoted the activation of adsorbed NH_(3) ***_(3) and Ce_(2)(WO_(4))_(3)(formed by solid-state reaction between Ce and W species)could provide more Brønsted acid sites(W-O modes of WO_(3),W=O or W-O-W modes of Ce_(2)(WO_(4))_(3)).CeO_(2) species could provide more Lewis acid *** Langmuir-Hinshelwood(L-H)routes and Eley-Rideal(E-R)routes occurred in the low-temperature SCR reaction on the Ce-W@RM ***_(4)^(+) species on Brønsted acid sites,NH_(3) species on Lewis acid sites,bidentate nitrate and bridging nitrate species were key active intermediates species.

关键词： Air pollution control NOx Selective catalytic reduction Cerium Tungsten

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Perspectives on the impacts of climate change and their adaptation

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National Science Open 2024年第1期3卷 4-5页

作者： Guohe Huang Jiapei Chen State Key Joint Laboratory of Environmental Simulation and Pollution Control China-Canada Center for EnergyEnvironment and Ecology ResearchUR-BNUSchool of EnvironmentBeijing Normal UniversityBeijing 100875China Environmental Systems Engineering Program University of ReginaReginaSaskatchewan S4S 0A2Canada

The pressing impacts of climate change and the imperative for adaptation strategies emphasize the immediate necessity for proactive global *** challenges encompass the enhancement of climate modeling,the development of sector-tailored strategies,and the implementation of adaptation *** these issues necessitates worldwide collaborations,sustainable practices,technological innovations.

关键词： climate adaptation collaboration

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