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Trends and drivers of anthropogenic NOx emissions in China since 2020

Environmental Science and Ecotechnology 2024年第5期21卷 287-293页

作者： Hui Li Bo Zheng Yu Lei Didier Hauglustaine Cuihong Chen Xin Lin Yi Zhang Qiang Zhang Kebin He Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration Institute of Environment and EcologyTsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084China State Environmental Protection Key Laboratory of Environmental Planning and Policy Simulation and Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental PlanningBeijing 100041China Laboratoire des Sciences du Climat et de l’Environnement LSCE/IPSLCEA-CNRS-UVSQUniversite Paris-SaclayGif-sur-YvetteFrance Center for Satellite Application on Ecology and Environment Ministry of Ecology and Environment of ChinaBeijing 100094China Institute of Future Human Habitats Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China

Nitrogen oxides(NOx),significant contributors to air pollution and climate change,form aerosols and ozone in the ***,timely,and transparent information on NOx emissions is essential for decision-making to mitigate both haze and ozone ***,a comprehensive understanding of the trends and drivers behind anthropogenic NOx emissions from Chinadthe world's largest emitterdhas been lacking since 2020 due to delays in emissions *** we show a consistent decline in China's NOx emissions from 2020 to 2022,despite increased fossil fuel consumption,utilizing satellite observations as constraints for NOx emission estimates through atmospheric *** reduction is corroborated by data from two independent spaceborne instruments:the TROPOspheric Monitoring Instrument(TROPOMI)and the Ozone Monitoring Instrument(OMI).Notably,a reduction in transport emissions,largely due to the COVID-19 lockdowns,slightly decreased China's NOx emissions in *** subsequent years,2021 and 2022,reductions in NOx emissions were driven by the industry and transport sectors,influenced by stringent air pollution *** satellite-based inversion system developed in this study represents a significant advancement in the real-time monitoring of regional air pollution emissions from space.

关键词： China's NOx emissions Pollution control Socio-economic drivers Atmospheric inversion

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Stability Analysis of Event-Triggered Networked control systems with Time-Varying Delay and Packet Loss

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系统科学与复杂性学报（英文版） 2021年第1期34卷 265-280页

作者： WANG Zhao SUN Jian BAI Yongqiang The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of TechnologyBeijing 100081China The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of TechnologyBeijing 100081China The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of TechnologyBeijing 100081China

Networked control systems(NCSs)are facing a great challenge from the limitation of network communication ***-triggered control(ETC)is often used to reduce the amount of communication while still keeping a satisfactory performance of the system,by transmitting the measurements only when an event-triggered condition is ***,some network-induced problems would happen inevitably,such as communication delay and packet loss,which can degrade the control performance significantly and can even lead to *** this paper,a periodic event-triggered NCS considering both time-varying delay and packet loss is *** system is discretized into a piecewise linear system with *** the model is handled by a polytopic over-approximation method to be more suitable for stability ***,stability conditions are obtained and presented in terms of linear matrix inequalities(LMIs).The result is illustrated by a numerical example.

关键词： Delay event-triggered control networked control systems packet loss stability analysis

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Trajectory Prediction of High-Speed Train Group Tracking Based on LSTM-KF Hybrid Model 27

Trajectory Prediction of High-Speed Train Group Tracking Bas...

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27th IEEE International Conference on Intelligent Transportation systems, ITSC 2024

作者： Yang, Boyu Lv, Jidong Liu, Hongjie Chai, Ming Zhang, Qinglong Tang, Tao Lv, Jiahui National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China School of Civil and Resource Engineering University of Science and Technology Beijing China Beijing Jiaotong University The Associate Director of the Rail Traffic Control and Safety State Key Laboratory China

ISBN: (纸本)9798331505929

Operating multiple trains as a group under Train-to-Train communication is an efficient way in sparse railway networks. However, it is a barrier to accurate tracking for follower trains with the uncertain status of the preceding trains under communication delay. Therefore, we proposed a train trajectory prediction approach, aiming to obtain an accurate state of preceeding trains in a long time horizon. Firstly, we established a hybrid prediction model combined Long Short-Term Memory (LSTM) with the Kalman Filter (KF) and using the sliding window mechanism to enhance future prediction accuracy. Secondly, to fusion LSTM prediction data and the Kalman calculation model, we proposed the Hybrid Train Trajectory Prediction algorithm by adopting real-time calculation of the covariance matrix using real data and predicted data. Finally, we apply an experiment considering network characteristics in Western China. The result shows that the Mean Absolute Error (MAE) of series prediction in the longer time domain is 44% of the Recurrent Neural Network (RNN) model and 88% of the traditional LSTM model. © 2024 IEEE.

关键词： Kalman filters

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Channel Measurement and Analysis at Emergency Frequency Band in Primeval Forest

Channel Measurement and Analysis at Emergency Frequency Band...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2023

作者： Chen, Haoran Ai, Bo Fei, Dan Guan, Ke An, Hao Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing China Beijing Jiaotong University Frontiers Science Center for Smart High-speed Railway System Beijing China

ISBN: (纸本)9781665442282

In this paper, fixed-point channel measurements for emergency communication scene in the primeval forest were conducted at emergency communication frequency band. We estimate and model channel characteristics based on the measured data within 100 m by taking 5 m as the step fixed point in the primeval forest. The emergency frequency band is 380 MHz and the corresponding bandwidth is 20 MHz. Based on the measured data, we obtain the power delay profile (PDP) of different distance. Finally, multipath components (MPCs) and large-scale fading characteristics at different distances are analyzed which contributes to make primeval forest emergency communication more reliable. © 2023 IEEE.

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Health benefits from the rapid reduction in ambient exposure to air pollutants after China's clean air actions:progress in efficacy and geographic equality

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National Science Review 2024年第2期11卷 103-113页

作者： Tao Xue Ruohan Wang Meng Wang Yanying Wang Dan Tong Xia Meng Conghong Huang Siqi Ai Fangzhou Li Jingyuan Cao Mingkun Tong Xueqiu Ni Hengyi Liu Jianyu Deng Hong Lu Wei Wan Jicheng Gong Shiqiu Zhang Tong Zhu Institute of Reproductive and Child Health National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics Ministry of Education Key Laboratory of Epidemiology of Major Diseases(PKU) School of Public Health Peking University Health Science Centre State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management and Center for Environment and Health Peking University Advanced Institute of Information Technology Peking University Department of Epidemiology and Environmental Health School of Public Health and Health ProfessionsUniversity at Buffalo State Key Joint Laboratory of Environment Simulation and Pollution Control College of Environmental Sciences and EngineeringPeking University Department of Earth System Science Tsinghua University School of Public Health Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of HealthFudan University College of Land Management Nanjing Agricultural University National&Local Joint Engineering Research Center for Rural Land Resources Use and Consolidation Clean Air Asia

Clean air actions （CAAs） in China have been linked to considerable benefits in public ***,whether the beneficial effects of CAAs are equally distributed geographically is *** high-resolution maps of the distributions of major air pollutants (fine particulate matter[PM2.5]and ozone[O3]) and population,we aimed to track spatiotemporal changes in health impacts from,and geographic inequality embedded in,the reduced exposures to PM2.5and O3from 2013 to *** used a method established by the Global Burden of Diseases *** analyzing the changes in loss of life expectancy（LLE） attributable to PM2.5and O3,we calculated the gain of life expectancy （GLE） to quantify the health benefits of the air-quality ***,we assessed the geographic inequality embedded in the GLE using the Gini index （GI）.Based on risk assessments of PM2.5and O3,during the first stage of CAAs（2013 to 2017）,the mean GLE was 1.87 *** of the sum of the GLE was disproportionally distributed in about one quarter of the population exposed （GI 0.44）.During the second stage of CAAs（2017 to 2020）,the mean GLE increased to 3.94 months and geographic inequality decreased （GI 0.18）.According to our assessments,CAAs were enhanced,from the first to second stages,in terms of not only preventing premature mortality but also ameliorating health *** enhancements were related to increased sensitivity to the health effects of air pollution and synergic control of PM2.5and *** findings will contribute to optimizing future CAAs.

关键词： clean air action public health inequality fine particulate matter ozone

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Modeling and Trajectory Predicting for the Hypersonic Vehicle

Modeling and Trajectory Predicting for the Hypersonic Vehicl...

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第33届中国过程控制会议

作者： Ren Xiaoli Chai Yi Chen Xiaolong Huang Pengfei Xiefei Key Laboratory of complex system safety and control Ministry of Education College of AutomationChongqing University

In this paper,the cone-shaped hypersonic vehicle is taken as the research *** of all,ignoring the influence of secondary factors and sideslip angle during flight,and considering the coupling between aerodynamics and propulsion,the aircraft dynamics model,the aerodynamic model,and the standard atmospheric model were constructed ***,the curve of each state variable is obtained by jointly solving the three ***,according to the nonlinear time series of state variables,an aircraft trajectory prediction model based on random forest regression is *** simulation results show that the model has the characteristics of high speed,small error and high precision.

关键词： Hypersonic vehicle Dynamic model Aerodynamic model Random forest regression

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Trajectory-prediction-based Dynamic Tracking of a UGV to a Moving Target under Multi-disturbed Conditions

Trajectory-prediction-based Dynamic Tracking of a UGV to a M...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jinge Si Bin Li Yongkang Xu Liang Wang Chencheng Deng Shoukun Wang Junzheng Wang State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology School of Automation Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Tracking dynamic targets poses a significant challenge for Unmanned Ground Vehicles (UGVs). Existing methods often lack research on multi-disturbed conditions. To address this issue, we propose a trajectory-prediction-based dynamic tracking scheme, which includes target localization, trajectory prediction, and UGV control. Firstly, an estimation algorithm based on the Extended Kalman Filter (EKF) is employed to mitigate noise and estimate the absolute states of the target accurately. To enhance robustness, we present an Adaptive Trajectory Prediction (ATP) algorithm based on prediction anchors. In this method, a quantization standard for trajectory disturbance is designed for adaptive control. Subsequently, we iteratively solve prediction anchor points based on two motion models to robustly predict the target trajectory even in the presence of unknown disturbances. Finally, the Linear Time-Varying Model Predictive control (LTV-MPC) is utilized in the UGV controller for dynamic tracking. Experimental results demonstrate that the ATP exhibits superior prediction robustness and accuracy in perturbed environments compared to other prediction algorithms. In addition, the proposed scheme effectively achieves dynamic tracking of the Unmanned Aerial Vehicle (UAV) by the UGV under multi-disturbed conditions. Specifically, when the target moves at a speed of 1.0 m/s, the UGV can maintain a tracking error within 0.346 m.

关键词： Target tracking Accuracy Heuristic algorithms Noise Prediction algorithms Autonomous aerial vehicles Robustness

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Experimental research on GM-APD LIDAR point cloud classification algorithm based on deep learning

Experimental research on GM-APD LIDAR point cloud classifica...

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2022 Applied Optics and Photonics China: Advanced Laser Technology and Applications, AOPC 2022

作者： Jiang, Yanze Sun, Jianfeng Ding, Yuanxue Jiang, Peng Zhang, Hailong Li, Sining Zhou, Shuaijun National Key Laboratory of Science and Technology on Tunable Laser Institute of OptoElectronic Harbin Institute of Technology Heilongjiang Harbin150001 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Aerospace Automatic Control Institute Beijing100854 China

ISBN: (纸本)9781510662223

Geiger mode Avalanche Photo Diode (Gm-APD) array lidar is a lidar that can perform single-photon detection. It offers a wide range of applications due to its low power consumption, small size, and extended detecting distance. There haven't been many research on this detector's target classification because of its late development and small detector array. The classification technique based on the Gm-APD array lidar point cloud is the focus of this paper's research: Firstly, the Gm-APD array lidar is utilized to perform imaging tests on four targets from various angles in order to create a target classification *** that, several data preprocessing methods were chosen and implemented based on the characteristics of the obtained data, such as filling in missing values, performing range image and intensity image interpolation, using the principle of keyhole imaging to convert the range image to point cloud data, realizing the information fusion of distance image and intensity image, and using multiple point cloud data enhancement methods. Finally, the point cloud classification networks PointNet and PointNet++ are trained on point cloud data with varying levels of preprocessing, the results are compared and analyzed, and the impact of different preprocessing methods on the classification accuracy of the two networks is determined. Inferences were made and experiments were carried out to verify the inferences. The data set preprocessing method with the highest classification accuracy of the two networks is discovered, laying the groundwork for future Gm-APD lidar target classification and detection research. © 2023 SPIE.

关键词： Optical radar

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A Gray-Level Co-occurrence Matrix-Based Image Smoke Feature Recognition Method

A Gray-Level Co-occurrence Matrix-Based Image Smoke Feature ...

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Information Science and Education (ICISE-IE), International Conference on

作者： Xuanqi Huang Hai Zhang Longyun Chi Aiping Wang Beihang University Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (数字)9798331506766

ISBN: (纸本)9798331506773

Smoke recognition plays a crucial role in fire monitoring and environmental awareness. Existing methods often suffer from issues such as confusion between smoke and background, as well as dynamic changes, leading to low recognition accuracy. Traditional methods struggle to effectively extract smoke features and have high computational costs. To address these shortcomings, this paper proposes a smoke region recognition algorithm based on clustering and the Gray-Level Co-occurrence Matrix (GLCM), referred to as KM-GLCM By applying clustering and GLCM techniques, the texture features of smoke are progressively extracted. A determination criterion based on information entropy is designed to achieve accurate recognition and labeling of smoke images, even in the presence of smoke-background confusion and dynamic changes.

关键词： Information science Image recognition Accuracy Heuristic algorithms Clustering algorithms Feature extraction Robustness Computational efficiency Labeling Information entropy

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The Current Research Status of Unmanned Aerial Vehicle Maneuver Penetration Decision-Making

The Current Research Status of Unmanned Aerial Vehicle Maneu...

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Artificial Intelligence and Computer Engineering (ICAICE), International Conference on

作者： Yutao Zhuang National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing P. R. China

ISBN: (数字)9798331528911

ISBN: (纸本)9798331528928

In modern warfare, maneuver penetration is an essential aspect of unmanned aerial vehicle (UAV) combat operations. As the capabilities of both offensive and defensive sides continue to improve, the operational patterns of maneuver penetration scenarios are constantly evolving. This paper first introduces the maneuver capabilities and detection characteristics of both offensive and defensive systems in contemporary warfare, providing a macro definition of the maneuver penetration problem. Then, it conducts a survey and analysis of the applications of traditional and new artificial intelligence algorithms in maneuver penetration decision-making. Finally, it discusses the future research directions and challenges of artificial intelligence algorithms in this field and envisions the development of maneuver penetration decision-making.

关键词： Surveys Heuristic algorithms Decision making Line-of-sight propagation Autonomous aerial vehicles Deep reinforcement learning safety Trajectory Artificial intelligence Vehicle dynamics

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