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SSRN 2023年

作者： Chen, Yanan Li, Yan Qiu, Tianyi He, Haoran Liu, Ji Duan, Chengjiao Cui, Yongxing Fang, Linchuan The Research Center of Soil and Water Conservation and Ecological Environment Chinese Academy of Sciences Ministry of Education Shaanxi Yangling712100 China State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau Institute of Soil and Water Conservation CAS and MWR Yangling712100 China University of Chinese Academy of Sciences Beijing100049 China Institute of Environment Resource and Soil Fertilizer Zhejiang Academy of Agricultural Sciences Hangzhou310021 China College of Natural Resources and Environment Northwest A&F University Yangling712100 China Hubei Province Key Laboratory for Geographical Process Analysis and Simulation Central China Normal University Wuhan430079 China Department of Ecohydrology Leibniz Institute of Freshwater Ecology and Inland Fisheries Berlin12587 Germany Sino-French Institute for Earth System Science College of Urban and Environmental Sciences Peking University Beijing100871 China Wuhan University of Technology China

Nitrogen (N) fertilization drives the composition and function of soil microbial communities, which are crucial for regulating soil biogeochemical cycling and maintaining ecosystem stability. The influences of N fertilizer on soil microbial composition and diversity have been widely explored, while it is commonly overlooked that ecosystem processes are carried out via complex webs of co-occurrence networks among microbiome members. Here, we examined the effects of five N fertilization levels (0, 135, 180, 225, and 360 kg N ha-1) on microbial co-occurrence networks and key functional taxa such as ammonia-oxidizers in paddy soils. The results showed that N addition altered microbial community composition, which were positively related to soil total N and available phosphorus (P) contents. The abundance of ammonia-oxidizing archaea (AOA) significantly decreased after N addition, whereas ammonia-oxidizing bacteria (AOB) increased in N360 treatment. Compared with low-N group (N0 and N135), the high-N group (N225 and N360) shaped more complex microbial webs and thus improved the stability of the microbial community. Partial least squares path modelling further revealed that N fertilizer had a higher effect on microbial network complexity in the high-N group (0.83) than the low-N group (0.49). Although there were more positive links across all microbial networks, the proportion of negative links significantly increased in the high-N networks, suggesting that excess N addition aggravated the competition among microbial species. Disentangling these interactions between microbial communities and N fertilization advances our understanding of biogeochemical processes in paddy soils and their effects on nutrient supply to rice production. Our findings highlighted that highly N-enriched paddy soils have more stable microbial networks and can better sustain soil ecological functions to cope with the ongoing environmental changes. © 2023, The Authors. All rights reserved.

关键词： Nitrogen fertilizers

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INTRODUCTION

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Bulletin of the American Meteorological Society 2024年第8期105卷 S1-S11页

作者： Boyer, T. Blunden, J. Dunn, R.J.H. NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Met Office Hadley Centre Exeter United Kingdom European Centre for Medium-Range Weather Forecasts Reading United Kingdom University of Maryland College Park Maryland Scripps Institution of Oceanography University of California San Diego La Jolla California NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland Brandenburg University of Technology (BTU) Cottbus-Senftenberg Germany Servicio Meteorológico Nacional Buenos Aires Argentina NOAA/OAR Physical Sciences Laboratory Boulder Colorado European Centre for Medium-Range Weather Forecasts Bonn Germany Center for Geophysical Research and School of Physics University of Costa Rica San José Costa Rica Department of Meteorology and National Centre for Earth Observation University of Reading Reading United Kingdom Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Université Grenoble Alpes Institut des Géosciences de l’Environnement IRD CNRS Grenoble INP Grenoble France Hampton University Hampton Virginia Seychelles Meteorological Authority Mahe Seychelles Section for Glaciers Ice and Snow Norwegian Water Resources and Energy Directorate Oslo Norway National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Agriculture Osaka Metropolitan University Sakai Japan Science Faculty Universidad Nacional de Colombia Bogotá Colombia University of Bremen Bremen Germany NOAA Global Monitoring Laboratory Boulder Colorado Servicio Nacional de Meteorología e Hidrología del Perú Lima Perú Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CSIC-UV-GVA) Valencia Spain Hydro-Climate Extremes Lab (H-CEL) Ghent University Ghent Belgium Department o

In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. A

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Increasing importance of ammonia emission abatement in PM_(2.5)pollution control

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science Bulletin 2022年第17期67卷 1745-1749页

作者： Wen Xu Yuanhong Zhao Zhang Wen Yunhua Chang Yuepeng Pan Yele Sun Xin Ma Zhipeng Sha Ziyue Li Jiahui Kang Lei Liu Aohan Tang Kai Wang Ying Zhang Yixin Guo Lin Zhang Lifang Sheng Xiuming Zhang Baojing Gu Yu Song Martin Van Damme Lieven Clarisse Pierre-François Coheur Jeffrey L.Collett Jr Keith Goulding Fusuo Zhang Kebin He Xuejun Liu College of Resources and Environmental Sciences National Academy of Agriculture Green DevelopmentKey Laboratory of Plant-Soil InteractionsMinistry of EducationNational Observation and Research tation of Agriculture Green Development(QuzhouHebei)China Agricultural UniversityBeijing 100193China College of Oceanic and Atmospheric Sciences Ocean University of ChinaQingdao 266100China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Desasters Nanjing University of Information Science&TechnologyNanjing 200433China State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Earth and Environmental Sciences Lanzhou UniversityLanzhou 730000China Laboratory for Climate and Ocean-Atmosphere Studies Department of Atmospheric and Oceanic SciencesSchool of PhysicsPeking UniversityBeijing 100871China School of Agriculture and Food the University of MelbourneVictoria 3010Australia College of Environmental and Resource Sciences Zhejiang UniversityHangzhou 310058China State Key Joint Laboratory of Environmental Simulation and Pollution Control Department of Environmental SciencePeking UniversityBeijing 100871China Universitélibre de Bruxelles SpectroscopyQuantum Chemistry and Atmospheric Remote SensingBrusselsBelgium Department of Atmospheric Science Colorado State UniversityFort Collins CO 80523USA Sustainable Agricultural Sciences Department Rothamsted ResearchHarpenden AL52JQUK School of Environment Tsinghua UniversityBeijing 100084China

在新冠肺炎疫情期间,中国采取的管制封锁措施大幅减少了交通和工业排放,但农业排放没有受到影响,甚至有所增加.通过全国大气氨浓度地面监测、实时连续观测和卫星观测等手段,我们发现,新冠肺炎疫情管制措施实施期间中国大气氨浓度大范围... 详细信息

在新冠肺炎疫情期间,中国采取的管制封锁措施大幅减少了交通和工业排放,但农业排放没有受到影响,甚至有所增加.通过全国大气氨浓度地面监测、实时连续观测和卫星观测等手段,我们发现,新冠肺炎疫情管制措施实施期间中国大气氨浓度大范围显著增加,上升幅度在农村地区最为明显(增加22%),在城市和偏远地区变化不明显;而且,管控期间大气氨浓度上升幅度与2015~2019年相同月份相比更大.基于大气化学模式模拟发现,中国北方大气氨浓度上升主要是由农业氨排放增加所致.随着未来我国二氧化硫和氮氧化物等酸性气体排放控制的强化,农业氨排放的协同减排对于进一步削减大气PM污染、提升空气质量尤为重要.进一步分析表明,疫情期间50%农业氨排放可有效抵消氨浓度上升造成的二次无机气溶胶的形成.

关键词：管制措施工业排放污染治理地面监测空气质量卫星观测 PM 偏远地区

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Flexible data handling in the flight control decision software for space science satellites 15th

Flexible data handling in the flight control decision softwa...

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15th International Conference on space Operations, spaceOps 2018

作者： Zhang, Y.Z. Peng, X.D. Gao, C. Laboratory of System Simulation and Concurrent Design Technology National Space Science Center Chinese Academy of Sciences Beijing100190 China Laboratory of System Simulation and Concurrent Design Technology University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781624105623

In order to support the in-orbit operation of the satellites in the Strategic Priority Program on space science, the Flight Control Decision Support Software (FCDSS) is developed. It belongs to the mission operation subsystem of the ground support system of the Strategic Priority Program on space science. The FCDSS is responsible for the comprehensive analysis of the operating status of the onboard equipment, the use of the satellite resources, the scientific detection results, and full life cycle visualization of the scientific mission in real time and afterwards, and mission situation analysis. The software contains two parts--"Flight Control Decision Analysis and Comprehensive Situation Visualization Unit" and "Full-lifecycle Data Processing Unit". The latter is the main focus in this paper. It is responsible for acquiring required data (such as telemetry data) from the database and do calculations for coverage analysis, observation plan analysis and etc. Due to the various types and massive amount of data need to be processed, it posed high requirements to data processing. In brief, in this paper, we will first describe the software architecture in detail. Then, give detailed information on the design and implementation of the data processing layer. At last, mission applications of the software will be shown with conclusions on the performance and lessons we have learned as the four mission carries on. © 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Visualization

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Prediction of Direct Normal Irradiation Based on CNN-LSTM Model

Prediction of Direct Normal Irradiation Based on CNN-LSTM Mo...

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2020年第五届多媒体系统和信号处理国际会议

作者： Chengying Zhang Zhen Yan Chao Ma Xiaoli Xu Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing Key Laboratory of Measurement and Control of Mechanical and Electrical System Beijing Information Science and Technology University

Due to the intermittency and instability of power output of solar power stations(SPS), the safety and stationarity of the electric grid are facing considerable challenges. So, it is essential to predict the power output of SPS accurately. To date, as the most important meteorological factor determining the power output of SPS, the prediction of direct normal irradiation(DNI) has always been a hotspot, however at the same time a challenging problem. In recent years, with the improvement of hardware performance, deep learning methods have witnessed rapid development in the field of forecasting of renewable energies. In this paper, a hybrid method combining convolutional neural network(CNN) and longshort term memory(LSTM) neural network is proposed, the former can be effectively used for extraction of spatial feature, while the latter is used for extraction of temporal feature. As a case study, the proposed method is used for prediction of DNI of four typical days, i.e. spring equinox, summer solstice, autumn equinox, and winter solstice, based on the meteorological conditions of Zhangbei. The results show that deep learning methods can be effectively used for prediction of DNI, however, the proposed method in this paper achieves higher prediction accuracy than that of the compared methods.

关键词： Solar power station Direct normal irradiation prediction Deep learning Convolutional neural network Long-short term memory Convolutional-LSTM network

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Wireless sensor network localization approach based on bayesian MDS 5th

Wireless sensor network localization approach based on bayes...

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5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017

作者： Pei, Zhongmin Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101416 China

ISBN: (纸本)9789811308956

The aim of wireless sensor networks (WSNs) are to perceive, collect and process the information of sensor nodes within the coverage of the network. As a bridge between the physical world and the digital one, WSNs have widely been applied in many fields. One of the key issues for most applications is to know the location of sensor nodes. Though localization algorithms based on multidimensional scaling (MDS), which only need several anchor nodes, have been proven to be robust with respect to range-based implementations, these methods are sensitive inaccuracy range measure. This article proposes a novel localization algorithm based on Bayesian MDS, named as MDS-MAP(P, B), where P and B denote the use of patching of local maps and Bayesian MDS, respectively. Experimental results in real-world systems show that our method is more robust and efficient. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Sensor nodes

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Denoising of hyperspectral images based on principal component analysis and adaptive sparse coding 10

Denoising of hyperspectral images based on principal compone...

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10th IAPR Workshop on Pattern Recognition in Remote Sensing, PRRS 2018

作者： Xiaorui, Song Lingda, Wu Space Engineering University Science and Technology on Complex Electronic System Simulation Laboratory Beijing101416 China

ISBN: (纸本)9781538684795

In view of the special properties of hyperspectral images(HSI) in the transform domain, in this paper, a new denoising method of HSI based on principal component analysis(PCA) and adaptive sparse coding is proposed. Firstly, the principal component image of each channel is obtained by performing PCA transform on the noisy HSI. Then, the first PCA output channels which contain a majority of the total energy of an HSI data cube are retained, and the rest PCA output channels which contain a small amount of energy, termed noise component images, are subjected to noise reduction through an adaptive sparse coding method. The encoding dictionaries are learned from each channel of noise component images by an approach of online dictionary learning. Finally, the denoised HSI is obtained by the inverse PCA transform. The proposed method takes the advantages of PCA and adaptive sparse representation that has better adaptability to the HSI. It not only performs better in denoising, but also preserves the details and alleviates the blocking artifacts well. The effectiveness of the proposed approach to hyperspectral denoising, termed PCASpC, is illustrated in a series of experiments with synthetic and realworld data where it outperforms the state-of-the-art. © 2018 IEEE.

关键词： Principal component analysis

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Visualization of pairwise data: An overview 3

Visualization of pairwise data: An overview

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3rd IEEE International Conference on Data science in Cyberspace, DSC 2018

作者： Pei, Zhong-Min Xiong, Ming-Hui Xiong, Wei Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101416 China

ISBN: (纸本)9781538642108

It is difficult for some applications to extract feature functions in the process of data visualization. Focus on the problem of large-scale pairwise data visualization, the paper first introduces and analysis the problem. Then the current mainstream methods for pairwise data visualization are analyzed. On the basis of active learning and configuration suture, the paper proposes a fast visualization method. The overall research framework, the key technologies are presented to provide some research ideas and recommendations for pairwise data visualization. © 2018 IEEE.

关键词： Data visualization

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Flow Visualization of Centrifugal Pump by the Combination of LIF and PIV

Flow Visualization of Centrifugal Pump by the Combination of...

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Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), International Conference on

作者： Qi Zhang Hanyang Gu Shuai Liu Junlong Li Sichao Tan Jianke Su School of nuclear science and engineering Shanghai Jiao Tong University China Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University Harbin China Support Center of Nuclear Technology CAEA Beijing China

ISBN: (数字)9781728192772

ISBN: (纸本)9781728192789

The visual experimental system for the centrifugal pump was established. The mock centrifugal pump with six curving semi-open impellers was manufactured by polymethyl methacrylate. The flow characteristics inside the mock centrifugal pump was studied by the combination of laser induced fluorescence (LIF) and particle image velocimetry (PIV). The polyamide resin particles were dissolved into the fluid of the circulation for PIV analysis, and fluorescent dye rhodamine B was head-on injected to the impellers for LIF analysis. The front plane of the impellers was covered by Nd: YAG laser sheet, one CCD camera collected the reflected laser light from the particles. Synchronously, another camera collected the fluorescence of rhodamine B. The velocity distribution characteristic was presented, and the time evolution of injected dye in the channel between impeller and septum was obtained. The inlet fluid moved circumferentially along the impeller under centrifugal force, the central region had smaller velocity. The injected dye gathered into blocks near the central area, and was evenly distributed near the edge of the pump impellers. The combination of LIF and PIV was proved to be credible method in the research of centrifugal pump.

关键词： Fluorescence Impellers Pumps Fluids Pump lasers Cameras Charge coupled devices

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Joint Spatial and Temporal Enhancement Technique for Weak Signal Detection in Coherent LiDAR systems

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Laser and Optoelectronics Progress 2025年第9期62卷

作者： Jia, Honghui Lu, Zhiyong Sun, Jianfeng Li, Chaoyang Xu, Lingling Jiang, Yuxin Yuan, Haoming Su, Wanling Wangzhijiang Innovation Center for Laser Aerospace Laser Technology and System Department Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai201800 China Key Laboratory of Space Laser Communication and Detection Technology Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai201800 China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing100049 China Shanghai Satellite Network Research Institute Company Limited Shanghai200120 China Shanghai Key Laboratory of Satellite Network Shanghai200120 China

Coherent LiDAR systems face challenges in long-distance target detection due to weak echo signal energy and interference from external factors such as atmospheric turbulence, resulting in low signal-to-noise ratios (SNRs) and reduced detection performance. To address these issues, we propose a joint temporal and spatial enhancement technique based on a coherent radar system with multiaperture reception to optimize the extraction of weak signals. The proposed technique improves the SNR and detection performance by extending the accumulation period in the temporal dimension and increasing the number of receiving apertures in the spatial dimension. The theoretical simulations and experimental results demonstrate the effectiveness of the proposed method. Specifically, temporal and spatial accumulation methods yield SNR gains that are consistent with the theoretical predictions. For varying accumulation times of single-aperture echo signals and equivalent accumulation times of multiaperture echo signals, the expected improvements are achieved. By combining spatial and temporal accumulation, weak echo signals with power as low as 0. 56 fW are detected under conditions involving 36-aperture spatial accumulation and 20-ms temporal accumulation, achieving an SNR of 24. 3 dB. The proposed technique significantly enhances the capability of coherent LiDAR systems to detect weak signals and thus holds important practical application value. © 2025 Universitat zu Koln. All rights reserved.

关键词： Image enhancement

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