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ACS ES&T Air 2025年第2期2卷 249-263页

作者： Yicong He Kelsey R. Bilsback Manish Shrivastava Rahul A. Zaveri John E. Shilling John H. Seinfeld Bin Zhao Shuxiao Wang Christopher D. Cappa Jeffrey R. Pierce Shantanu H. Jathar Department of Mechanical Engineering Colorado State University Fort Collins Colorado 80523 United States；State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing 100084 China；State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084 China Department of Mechanical Engineering Colorado State University Fort Collins Colorado 80523 United States；PSE Healthy Energy Oakland California 94612 United States Pacific Northwest National Laboratory Richland Washington 99354 United States Divison of Chemistry and Chemical Engineering California Institute of Technology Pasadena California 91125 United States State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing 100084 China；State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084 China Department of Atmospheric Science Colorado State University Fort Collins Colorado 80521 United States Department of Civil and Environmental Engineering University of California Davis Davis California 95616 United States Department of Mechanical Engineering Colorado State University Fort Collins Colorado 80523 United States

Secondary organic aerosol (SOA) forms and evolves in the atmosphere through many pathways and processes, over diverse spatial and time scales. Hence, there is a need to represent these widely varying kinetic processes in large-scale atmospheric models to allow for accurate predictions of the abundance, properties, and impacts of SOA. In this work, we integrated a kinetic, process-level model (simpleSOM-MOSAIC) into a weather-chemistry model (WRF-Chem) to simulate the oxidation chemistry and microphysics of atmospheric SOA. simpleSOM-MOSAIC simulates multigenerational gas-phase chemistry, autoxidation reactions, aqueous chemistry, heterogeneous oxidation, oligomerization, and phase-state-influenced gas/particle partitioning of SOA. As a case study, the integrated WRF-Chem-simpleSOM-MOSAIC (WC-SSM) model was used to simulate the photochemical evolution downwind of a large city (Manaus, Brazil) in the Amazon and, in turn, study the anthropogenic and biogenic interactions in an otherwise pristine environment. Consistent with previous work, we found that OA was enhanced by up to a factor of 4 in the urban plume due to elevated hydroxyl radical (OH) concentrations, relative to the background, and that this OA was dominated by SOA from biogenic precursors (80%). In addition to accurately simulating the OA enhancement in the urban plume, the model reproduced the magnitude of the OA oxygen-to-carbon (O:C) ratio and broadly tracked the evolution of the aerosol number size distribution. Our work highlights the importance of including an integrated, kinetic representation of SOA processes in an atmospheric model.

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Technology pathway to decarbonisation in the building sector based on a policy review of major economies

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Advances in Climate Change Research 2025年第1期16卷 183-198页

作者： Jie XIONG Si-Yue GUO Xian ZHANG Run-Ming YAO Pan-Yu ZHU Xue-Ting PENG Nian YANG Ya-Ting ZHANG Mai SHI Xi LU School of Environment State Key Joint Laboratory of Environment Simulation and Pollution ControlTsinghua UniversityBeijing 100084China School of Architecture and Urban Planning Chongqing Jiaotong UniversityChongqing 400074China Institute for Energy Environmental&EconomyTsinghua UniversityBeijing 100084China The Administrative Centre for China’s Agenda 21(ACCA21) Ministry of Science and Technology(MOST)Beijing 100038China School of the Built Environment University of ReadingReading RG66DFUnited Kingdom Joint International Research Laboratory of Green Buildings and Built Environments(Ministry of Education) Chongqing UniversityChongqing 400045China Synavision GmbH Bielefeld 33602Germany Beijing Laboratory of Environmental Frontier Technologies Tsinghua UniversityBeijing 100084China Institute for Carbon Neutrality Tsinghua UniversityBeijing 100084China

Building decarbonisation is crucial to achieve the carbon neutrality *** many studies have been conducted,a gap remains in the research concerning technology development and policy *** study conducted a comprehensive review of the decarbonisation pathways proposed by the ten largest economies globally for the building sector at the national *** synthesising the relevant literature,a systemic framework of technologies applicable to the building sector is proposed,encompassing five major categories of technologies:energy efficiency,electrification and clean heating,on-site generation and flexible utilisation,green construction materials and processes,and sufficiency in operation and *** overview of each country’s emphasis on technological development,future expectations and prevailing trends in technology deployment is summarised and *** countries'policy documents address energy efficiency,electrification,and clean heating;however,the importance of flexibility and sufficiency warrants further *** balance among different technologies,the impacts of lock-in effects,and the considerations of equity and justice in renovation processes are critical concerns for the future deployment of *** study can provide a meaningful reference for the following research phase and the development of pathways to decarbonise buildings for countries worldwide.

关键词： Decarbonisation Building sector Carbon neutrality Pathway Framework of technologies

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Assessing the Significance of Regional Transport in Ozone Pollution through Machine Learning: A Case Study of Hainan Island

ACS ES&T Air

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ACS ES&T Air 2025年第3期2卷 416-425页

作者： Jun Liu Meiru Chen Biwu Chu Tianzeng Chen Qingxin Ma Yonghong Wang Peng Zhang Hao Li Bin Zhao Rongfu Xie Qing Huang Shuxiao Wang Hong He State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China；University of Chinese Academy of Sciences Beijing 100049 China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China；Center for Excellence in Regional Atmospheric Environment Institute of Urban Environment Chinese Academy of Sciences Xiamen 361021 China；University of Chinese Academy of Sciences Beijing 100049 China School of Environment Tsinghua University Beijing 100084 China College of Ecology and Environment Hainan University Haikou 570228 China；Hainan Research Academy of Environmental Sciences Haikou 571126 China School of Environmental Science and Engineering Hainan University Haikou 570228 China

Regional transport of air pollutants is a serious challenge to outdoor O3pollution control. Characterizing the transport of air pollutants by traditional air quality models heavily relies on accurate precursor emission inventories, chemical reaction mechanisms, and meteorological factors. In this study, the pollutant concentrations of upwind cities were incorporated as features into a random forest regression model (Traj-RF) to investigate the contribution of regional transport to local O3pollution. Hainan island was selected as the target area in this study, due to its air quality being affected significantly by regional transport. The Traj-RF model shows good predictive performance for O3with a coefficient of determination (R2) of 0.68 on the independent test set based on only observed air pollutants concentrations and meteorological data. The results of the Traj-RF model show that direct O3transport from upwind areas contributes approximately 27.5% to the O3concentration in Hainan, effectively highlighting the substantial role of regional transport in Hainan’s O3pollution. This refined machine learning method may have the potential to assess the impact of pollutant transport on regional air quality.

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A cooperative energy management strategy based on region-based traffic grade prediction

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Applied Energy 2025年 391卷

作者： Hou, Zhuoran Chu, Liang Hu, Jincheng Jiang, Jingjing Yang, Jun Zhang, Yuanjian State Key Laboratory of Automotive Simulation and Control Jilin University No. 5988 Renmin Street Nanguan District Changchun130022 China Department of Aeronautical and Automotive Engineering Loughborough University LeicestershireLE11 3TU United Kingdom

The progression of the Internet of Vehicles (IoVs) has cultivated a comprehensive information environment, laying the groundwork for vehicle-environment adaptive control. Region-based traffic condition prediction offers valuable insights into overall traffic trends, aiding urban applications and vehicle-environment cooperation. In this study, an adaptive energy management strategy based on region-based traffic grade prediction (TGP-EMS) is proposed for plug-in hybrid electric vehicles (PHEVs) based on IoVs, strengthening the adaptability via accurately obtaining future region-based traffic conditions. Firstly, traffic data collected from volunteering vehicles are processed to generate representative traffic graphs and the traffic conditions are separated into several grades with distinct traffic attributes. Secondly, a differentiable pooling is integrated into a hierarchical deep learning framework to establish a region-based traffic prediction model termed Graph Pool. Thirdly, an optimal explicit solving method based on an instantaneous optimization algorithm is proposed and successfully applied to energy management. Moreover, the robustness of the introduced explicit solving algorithm is optimized based on the beetle antennae search (BAS) algorithm. simulation results, accompanied by hardware-in-the-loop (HIL) tests, suggest that the introduced Graph Pool effectively captures spatial features across the entire traffic network, ensuring accuracy and consistency in predicting traffic conditions. Moreover, the TGP-EMS adeptly adjusts power distribution based on these predictions, showing an improvement of roughly 13.5 % compared to conventional rule-based energy management strategies. © 2025

关键词： Plug-in hybrid vehicles

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FDCA-DSTGCN: A Wind Farm Cluster Power Day-ahead Prediction Model Based on Frequency Domain Information Gain and Dynamic Trend Sensing

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IEEE Transactions on Sustainable Energy 2025年

作者： Yang, Mao Niu, Jiajun Wang, Bo Huang, Dawei Su, Xin Ma, Chenglian Ministry of Education Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin132012 China China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems Beijing100912 China

Accurate wind farm cluster power prediction (WFCPP) is of vital significance for new power systems with large-scale wind power integration. The current WFCPP modeling method ignores the important role of wind direction and frequency domain information, resulting in insufficient use of spatial information and difficult to improve the prediction accuracy. In order to solve the above problems, a day-ahead power prediction model for wind farm cluster power is proposed based on information gain in frequency domain and dynamic trend sensing. Firstly, a cluster division method based on graph theory and progressive fusion of multiple information is proposed, and a virtual information node is set up. Secondly, a method to identify prevailing wind direction under time window is proposed for subsets, and a dynamic weighted directed graph structure is designed based on prevailing wind direction and wind speed. Thirdly, a dynamic spatio-temporal graph convolutional network model with frequency domain gain channel attention mechanism (FDCA-DSTGCN) is proposed to integrate the above information and complete the prediction. Finally, the proposed method is applied to a wind farm cluster in Inner Mongolia of China. Compared with the existing and traditional prediction methods, the normalized root mean square error of the proposed method is reduced by 1.13% -2.15%, which verifies the effectiveness of the proposed method. © 2010-2012 IEEE.

关键词： Mean square error

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Impact of Mixed Benzene Site Exposure on Bioaccessibility in Simulated Lung Fluids and Health Risk Assessment

SSRN

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SSRN 2025年

作者： Ma, Xuemin Wang, Ying Chen, Shuhe Wu, Changyong Wang, Weipeng Wang, Yue Engineering Research Center of Environmental Pollution Control Chinese Research Academy of Environmental Sciences Beijing100012 China State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental Sciences Beijing100012 China 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 Beijing100012 China College of Urban and Rural Construction Agricultural University of Hebei Baoding071001 China

Benzene, toluene, ethylbenzene, and xylenes (BTEX) are major volatile organic compounds (VOCs) associated with petroleum production, posing significant health risks via inhalation. Conventional risk assessments primarily focus on single-compound or single-concentration exposures, overlooking the complex mixed-exposure scenarios prevalent at contaminated sites. This study refines health risk assessment frameworks by incorporating bioaccessibility-driven indices for inhalation exposure. Using a membrane oxygenator system, benzene and ethylbenzene were evaluated as representative pollutants under single and mixed exposures at low (5 mg/kg), medium (10 mg/kg), and high (20 mg/kg) concentrations. Results revealed significantly enhanced bioaccessibility of benzene and ethylbenzene in simulated lung fluid under mixed exposure compared to single exposure (P © 2025, The Authors. All rights reserved.

关键词： Lung cancer

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Aggregation Modeling of System Frequency Response Under Inertia control of Grid-following Direct-drive Wind Turbine

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Dianli Xitong Zidonghua/Automation of Electric Power Systems 2025年第10期49卷 39-48页

作者： Jiang, Chao Yang, Dongfeng Guo, Shujia Liu, Xiaojun Zhou, Shuyu Cao, Zhichong Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China School of Automation and Electrical Engineering Zhejiang University of Science and Technology Hangzhou310023 China State Grid Jilin Electric Power Research Institute Changchun130000 China

The inertia control of grid-following direct-drive wind turbines significantly influences the system frequency response pattern afrer disturbances. However, current research has not clearly identified the dominant response link of direct-drive wind turbines in frequency regulation, while the modeling is too complicated to be suitable for frequency characteristic analysis. Therefore, the linearized models under inertia control are derived for two typical types of direct-drive wind turbines according to the aerodynamic equations, generator models, power control link, and control circuit structure. The fast physical process of current control-boost circuit/stator voltage dynamic loop is clearly understood and reasonably ignored. It is revealed that the two types of direct-drive wind turbines have a common frequency response mechanism which can be described as the cascade effect of the speed regulator-wind rotor motion equation. Furthermore, combined with the frequency response model of synchronous unit, the aggregation model of system frequency response under the inertia control of grid-following direct-drive wind turbines is constructed, and the aggregation model is reduced to a second-order model by the balance truncation method for analytical calculation of frequency extremes. The accuracy and applicability of the aggregation model and its reduced-order model are verified by MATLAB/Simulink simulation, and the influence of control parameters and system states on frequency dynamic characteristics and stability margin is analyzed. © 2025 Automation of Electric Power Systems Press. All rights reserved.

关键词： Electric power system control

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Robust control for active suspension system under steering condition

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Science China(Technological Sciences) 2017年第2期60卷 199-208页

作者： WANG ChunYan DENG Ke ZHAO WanZhong ZHOU Guan LI XueSong Department of Automotive Engineering Nanjing University of Aeronautics and Astronautics State Key Laboratory of Automobile Simulation and Control Jilin University

To minimize the auto body's posture change caused by steering and uneven road, and improve the vehicle's riding comfort and handling stability, this paper presents an H∞ robust controller of the active suspension system, which considers the effects of different steering conditions on its dynamic performance. The vehicle's vibration in the yaw, roll, pitch and vertical direction and the suspension's dynamic deflection in the steering process are taken into account for the designed H∞ robust controller, and it introduces the frequency weight function to improve the riding comfort in the specific sensitive frequency bands to human body. The proposed robust controller is testified through simulation and steering wheel angle step test. The results show that the active suspension with the designed robust controller can enhance the anti-roll capability of the vehicle, inhibit the changes of the body, and improve the riding comfort of the vehicle under steering condition. The results of this study can provide certain theoretical basis for the research and application of active suspension system.

关键词： vehicle active suspension system steering condition H∞ robust control sensitive frequency bands

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Quantitative relationship between hippocampal injury and mechanical load and body weight in closed head injury of male rats using quadratic orthogonal regression

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Scientific Reports 2025年第1期15卷 1-13页

作者： Wang, Peng Song, Xuewei Wang, Qiushi Qiu, Jinlong Zhu, Xiyan Yu, Tianming Xiang, Hongyi Zhao, Hui State Key Laboratory of Automotive Simulation and Control College of Automotive Engineering Jilin University Jilin Changchun China Institute for Traffic Medicine Daping Hospital Army Medical University Chongqing China

Memory dysfunction, a common symptom following closed head impact injuries, suggests deficits in hippocampal function. This defect is thought to be related to impact strength and individual animal weight. In this study, head impact experiments were performed on male Sprague Dawley rats to establish a quantitative relationship between impact strength, body weight and hippocampal injury. A two-factor, three-level experimental design was established using the L₉(3⁴) orthogonal table, with impact strength and body weight as the variables. According to the protocol, rats were injured using a BIM-IV animal impact machine, and the effects of impact strength and body weight factors on hippocampal injury were evaluated by the results of Morris water maze and hematoxylin–eosin staining of the hippocampus at 24 h post-injury. Using the percentage of cell loss in the hippocampus as an indicator, quadratic regression models were established to describe the effects of impact strength and body weight on cell loss in the CA1, CA3, and DG regions of the hippocampus. The results revealed a quadratic, non-linear relationship between impact strength, body weight and the percentage of cell loss in these regions. Specifically, increasing impact strength resulted in a higher proportion of cell loss, whereas increasing body weight was associated with a reduction in cell loss. Consistent with these pathological findings, higher impact strength prolonged the time required for rats to locate the hidden platform in the Morris water maze, while higher body weight shortened the platform-finding time under the same impact strength. The quadratic orthogonal regression equations for hippocampal injury as a function of mechanical load and body weight provide valuable insights for predicting hippocampal damage and understanding its underlying mechanisms. © The Author(s) 2025.

关键词： Closed head injury Hippocampal injury Quadratic orthogonal regression

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Hydrothermal aging alleviates hydrocarbon poisoning effects on high-silica Cu-SSZ-16 catalysts for NH 3 -SCR

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Journal of Environmental Sciences 2025年 158卷 13-23页

作者： Huan Zhou Jianqi Liu Yan Zhang Shichao Han Jinpeng Du Wenpo Shan Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention Institute of Urban Environment Chinese Academy of Sciences Xiamen 361021 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 Ningbo 315800 China Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai 201210 China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China

Hydrocarbons (HCs) exert toxic effects on the activity of Cu-based zeolite catalysts for NH 3 -SCR on diesel vehicles. This study investigated the hydrocarbon resistance of both fresh and hydrothermally aged high-silica Cu-SSZ-16 catalysts. It was found that low-temperature activity of Cu-SSZ-16 catalyst decreased after C 3 H 6 poisoning, which was mainly due to the blockage of pore channels and the coverage of Cu active sites as well as acid sites by the formation of carbon deposits. Additionally, [Cu(OH)] + -Z was proposed to be more easily affected by C 3 H 6 poisoning than Cu 2+ -2Z. Hydrothermally aged Cu-SSZ-16 presented better C 3 H 6 resistance than the fresh catalyst since less carbon deposits were accumulated and [Cu(OH)] + -Z species were partially transformed to more-stable Cu 2+ -2Z in the aged sample. This was probably because of the reduction of acid sites and the formation of CuO x , which enhanced the oxidation of C 3 H 6 , thereby inhibiting the formation of carbon deposits. In addition, the coverage of the active Cu species also influenced the adsorption and oxidation of NO, causing a decrease in low-temperature activity. Thus, the low-temperature activity could be fully recovered by hydrothermal treatment at 500 °C due to the removal of carbon deposits and recovery of Cu active sites as well as acid sites. In summary, high-silica Cu-SSZ-16, with high resistance to HCs and excellent hydrothermal stability, is a competitive candidate as a catalyst for the NH 3 -SCR reaction in practical application.

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