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SSRN 2023年

作者： Fu, Lujun Lu, Ping Pan, Yufeng Zhong, Yi Sima, Chaotan Wu, Qiang Zhang, Jiangshan Cui, Lingzhi Liu, Deming National Engineering Research Center for Next Generation Internet Access System School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen518000 China Wuhan OV Optical Networking Technology Co. Ltd. Wuhan430073 China Faculty of Engineering and Environment Northumbria University Newcastle upon TyneNE1 8ST United Kingdom Department of Electronics and Information Engineering Huazhong University of Science and Technology Wuhan430074 China State Key Laboratory of NBC Protection for Civilian Beijing102205 China

An all-optical non-resonant photoacoustic spectroscopy system for multicomponent gas detection based on a silicon cantilever optical microphone (SCOM) and an aseismic photoacoustic cell is proposed and demonstrated. The SCOM has a high sensitivity of over 96.25 rad/Pa with sensitivity fluctuation less than ±1.56 dB between 5 Hz to 250 Hz. Besides, the minimal detectable pressure (MDP) of the sensor is 0.55 μPa·Hz-1/2 at 200 Hz, which indicates that the fabricated sensor has high sensitivity and low noise level. Six different gases of CO2, CO, CH4, C2H6, C2H4, C2H2 are detected at the frequency of 10 Hz, whose detection limits (1σ) are 20.89 ppb, 309.70 ppb, 498.32 ppb, 70.98 ppb, 384.45 ppb and 139.20 ppb, respectively. The system achieves high sensitivity and low detection limits for trace gas detection. In addition, the system exhibits seismic performance with suppressing vibration noise by 4.5 times, and achieves long-term stable operation. © 2023, The Authors. All rights reserved.

关键词： Photoacoustic spectroscopy

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Corrigendum to“Magnesium cationic cue enriched interfacial tissue microenvironment nurtures the osseointegration of gamma-irradiated allograft bone”[***.10C(April 2022)32-47]

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Bioactive Materials 2023年第2期20卷 165-165页

作者： Wenhao Wang Jie Shen Yuan Meng Miaoman Ye Shaozhang Lin Qi Zhao Le Wang Kenneth M.C.Cheung Shuilin Wu Yufeng Zheng Xuanyong Liu Paul K.Chu Kelvin W.K.Yeung Zhi-Yong Zhang Translational Research Centre of Regenerative Medicine and 3D Printing of Guangzhou Medical University Guangdong Province Engineering Research Center for Biomedical EngineeringState Key Laboratory of Respiratory DiseaseThe Third Affiliated Hospital of Guangzhou Medical UniversityGuangzhou510150PR China Department of Orthopaedics and Traumatology The University of Hong Kong999077Hong KongChina Shenzhen Key Laboratory for Innovative Technology in Orthopaedic Trauma The University of Hong Kong Shenzhen HospitalShenzhen518053PR China Department of Orthopaedic Surgery The Third Affiliated Hospital of Guangzhou Medical UniversityGuangzhou510150PR China Shenzhen Key Laboratory of Spine Surgery Department of Spine SurgeryPeking University Shenzhen HospitalShenzhen518036PR China Ministry of Education Key Laboratory for the Green Preparation and Application of Functional Materials Hubei Key Laboratory of Polymer MaterialsSchool of Materials&EngineeringHubei UniversityWuhan430062PR China Ministry of Education Key Laboratory for Advanced Ceramics and Machining Technology School of Materials Science&EngineeringTianjin UniversityTianjin300352PR China State Key Laboratory for Turbulence and Complex System Department of Materials Science and EngineeringCollage of EngineeringPeking UniversityBeijing100871PR China State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of CeramicsChinese Academy of SciencesShanghai200050PR China Department of Materials Science and Engineering City University of Hong Kong999077Hong KongChina

The authors regret a mistake of funding numbers in the Acknowledgment Section failed to be corrected during proof *** is the corrected funding statement in Acknowledgment SECTION This work was supported by the National Natural Science Foundation of China(NSFC)(Nos.81902189,81772354,82002303,31570980),Clinical Innovation Research Program of Guangzhou Regenerative Medicine and Health Guangdong laboratory(2018GZR0201002),National key Research and Development Plan(2018YFC1105103).

关键词： NSFC statement enriched

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Spatio-temporal Distribution of Drought in the Belt and Road Area During 1998–2015 Based on TRMM Precipitation Data

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Journal of Resources and Ecology 2017年第6期8卷 559-570页

作者： BAI Yongqing WANG Juanle WANG Yujie HAN Xuehua Bair Z. Tsydypov Altansukh Ochir Davaadorj Davaasuren State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China University of Chincse Academy of Sciences Beijing 100049 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023 China Shandong University of Technology Zibo Shandong 255012 China Baikal Institute of Nature Management Siberian Branch Russian Academy of Sciences U lan-Ude 670047 Russia School of Engineering and Applied Sciences National University of Mongolia Ulaanbaatar city 210646 Mongolia Department of the Geography School of the Art ＆ Sciences National University of Mongolia Ulaanbaatar city 210646 Mongolia

Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. Based on the Tropical Rainfall Measuring Mission Satellite（TRMM） 3 B43 precipitation data, we used the Precipitation Abnormity Percentage drought model to study the monthly spatio-temporal distribution of drought in south region of N50° of the Belt and Road area. It was observed that drought during winter was mainly distributed in Northeast Asia, Southeast Asia, and South Asia, while it was mainly distributed in Central Asia and West Asia during summer. The occurrence of historical droughts indicates an obvious seasonal cycle. The regional variations in drought were analyzed using the Breaks for Additive Season and Trend tool（BFAST） in six sub-regions according to the spatial distribution of six economic corridors in the Belt and Road area. The average drought conditions over the 18 years show a slight decreasing trend in Northeast Asia, West Asia, North Africa, South Asia, Central and Eastern Europe, and a slight increasing trend in Central Asia. However, it was a fluctuating pattern of first increasing and then decreasing in Southeast Asia. The results indicate that the total drought area in the Belt and Road region showed a general decreasing trend at a rate of 40,260 km^2 per year from 1998 to 2015.

关键词： drought distribution the Belt and Road TRMM Precipitation Abnormity Percentage BFAST

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Threshold Switching Selectors: A Threshold Switching Selector Based on Highly Ordered Ag Nanodots for X-Point Memory Applications (Adv. Sci. 10/2019)

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Advanced Science 2019年第10期6卷 1970058-1970058页

作者： Qilin Hua Huaqiang Wu Bin Gao Meiran Zhao Yujia Li Xinyi Li Xiang Hou Meng-Fan (Marvin) Chang Peng Zhou He Qian Institute of Microelectronics Tsinghua University Beijing 100084 China State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai 200433 China Department of Electrical Engineering National Tsing Hua University Hsinchu 30013 Taiwan

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Lithium Metal Anodes: A Triple-Gradient Host for Long Cycling Lithium Metal Anodes at Ultrahigh Current Density (Small 30/2020)

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Small 2020年第30期16卷

作者： TrungHieu Le Qinghua Liang Ming Chen Ciqing Yang Zhihao Yu Jie Cheng Feiyu Kang Ying Yang State Key Laboratory of Control and Simulation of Power System and Generation Equipments Tsinghua University Beijing 100084 China Department of Chemical Engineering The University of Melbourne Parkville VIC 3010 Australia Zhejiang Yuyuan Energy Storage Technology Co. Ltd. Huzhou 313100 China Laboratory of Advanced Materials Department of Materials Science and Engineering Tsinghua University Beijing 100084 China

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Meet the challenges in the “Carbon Age”

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Carbon Research 2022年第1期1卷 1-2页

作者： Wu, Fengchang Li, Fangbai Zhao, Xiaoli Bolan, Nanthi S. Fu, Pingqing Lam, Su Shiung Mašek, Ondřej Ong, Hwai Chyuan Pan, Bo Qiu, Xueqing Rinklebe, Jörg Tsang, Daniel C. W. Van Zwieten, Lukas Vithanage, Meththika Wang, Shaobin Xing, Baoshan Zhang, Gan Wang, Hailong State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental Sciences Beijing China Institute of Eco-environmental and Soil Sciences Guangdong Academy of Sciences Guangzhou China School of Agriculture and Environment The University of Western Australia Perth Australia Institute of Surface-Earth System Science School of Earth System Science Tianjin University Tianjin China Higher Institution Centre of Excellence (HICoE) Institute of Tropical Aquaculture and Fisheries (AKUATROP) Universiti Malaysia Terengganu Kuala Nerus Malaysia School of GeoSciences University of Edinburgh Edinburgh UK School of Information Systems and Modelling University of Technology Sydney Sydney Australia Faculty of Environmental Science & Engineering Kunming University of Science & Technology Kunming China School of Chemical Engineering and Light Industry Guangdong University of Technology Guangzhou China School of Architecture and Civil Engineering University of Wuppertal Wuppertal Germany Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Kowloon Hong Kong China New South Wales Department of Primary Industries Wollongbar Australia Ecosphere Resilience Research Center University of Sri Jayewardenepura Nugegoda Sri Lanka School of Chemical Engineering and Advanced Materials University of Adelaide Adelaide Australia Stockbridge School of Agriculture University of Massachusetts Amherst USA Guangzhou Institute of Geochemistry Chinese Academy of Sciences Guangzhou China School of Environmental and Chemical Engineering Foshan University Foshan China

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Measurement of rainfall-erosion impacted soil infiltration capability of slope land with run-on-ponding water

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Rengong Jingti Xuebao/Journal of Synthetic Crystals 2006年第4期35卷 7-11页

作者： Lei, Tingwu Pan, Yinghua Liu, Han Zhao, Xiaofen Zhan, Weihua Yuan, Jianping Key Laboratory of Modern Precision Agriculture System Integration Research College of Hydraulic and Civil Engineering Beijing 100083 China State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau Institute of Soil and Water Conservation Yangling 712100 China Geographic and Resources Management College Yantai Normal University Yantai 264025 China Machinery and Electric Engineering School Huangshi Institute of Technology Huangshi 435003 China Bureau of Comprehensive Development Ministry of Water Resources Beijing 100053 China

Soil infiltration capability(IC) of slope lands is closely related to the rainfall redistributed on the surface. A new method for IC estimated from runoff-ponding water was advanced in this paper. Mathematic models were derived to compute the IC with data for the advance process of runoff and that of ponding depth on soil surface. laboratory experiments of two cases (rainfall intensity of 60 mm/h, slope gradient of 5 degrees and runoff surface length of 1 m;and rainfall intensity of 30 mm/h, slope gradient of 20 degrees and runoff surface length of 1. 5 m) were conducted to collect required data for the demonstration of the experimental and computational procedures to determine the IC curves. The rationale of the measurement and the related algorithms were justified. And comparisons of the cumulated infiltrated waster with rainfall amounts were made to determine the measurement errors to demonstrate the measurement accuracy of the method. The newly suggested method overcomes the shortcomings of the conventional rain simulator and double ring methods. This method has the capability of measuring the full IC curve of slope surface as influenced by rainfall splash, runoff, and soil erosion. This method may supply the researchers in related fields with a useful tool.

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强厄尔尼诺期间大气环流对华北地区灰霾的影响

强厄尔尼诺期间大气环流对华北地区灰霾的影响

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第24届中国大气环境科学与技术大会暨中国环境科学学会大气环境分会2018年学术年会

作者： Ge Zhang Yang Gao Wenju Cai L.Ruby Leung Shuxiao Wang Bin Zhao Minghuai Wang Huayao Shan Xiaohong Yao Huiwang Gao Key Laboratory of Marine Environmental Science and Ecology Ministry of EducationOcean University of Key Laboratory of Marine Environmental Science and Ecology Ministry of EducationOcean University of Physical Oceanography Laboratory/CIMST Ocean University of China and Qingdao National Laboratory for Atmospheric Sciences and Global Change Division Pacific Northwest National LaboratoryRichlandWashi State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsi Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and School of Atmospheric Sciences Nanjing UniversityNanjing210023China

利用全国PM2.5监测网数据分析发现，华北地区在 2015 年 12 月和 2016 年 1 月出现 PM2.5 浓度异常高、低的跷跷板现象，此现象可能与强厄尔尼诺和北极涛动(AO)共同导致的局地气象变化有关.

关键词：灰霾强厄尔尼诺北极涛动东亚冬季风 WRF-CMAQ

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Persistent eutrophication and hypoxia in the coastal ocean

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Cambridge Prisms: Coastal Futures 2023年 1卷 e19-e19页

作者： Dai, Minhan Zhao, Yangyang Chai, Fei Chen, Mingru Chen, Nengwang Chen, Yimin Cheng, Danyang Gan, Jianping Guan, Dabo Hong, Yuanyuan Huang, Jialu Lee, Yanting Leung, Kenneth Mei Yee Lim, Phaik Eem Lin, Senjie Lin, Xin Liu, Xin Liu, Zhiqiang Luo, Ya-Wei Meng, Feifei Sangmanee, Chalermrat Shen, Yuan Uthaipan, Khanittha Wan Talaat, Wan Izatul Asma Wan, Xianhui Sean Wang, Cong Wang, Dazhi Wang, Guizhi Wang, Shanlin Wang, Yanmin Wang, Yuntao Wang, Zhe Wang, Zhixuan Xu, Yanping Yang, Jin-Yu Terence Yang, Yan Yasuhara, Moriaki Yu, Dan Yu, Jianmin Yu, Liuqian Zhang, Zengkai Zhang, Zhouling State Key Laboratory of Marine Environmental Science Xiamen University Xiamen China College of Ocean and Earth Sciences Xiamen University Xiamen China Fujian Institute for Sustainable Oceans Xiamen University Xiamen China China-ASEAN College of Marine Sciences Xiamen University Malaysia Sepang Malaysia College of the Environment and Ecology Xiamen University Xiamen China Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies Xiamen University Xiamen China Department of Earth System Science Ministry of Education Key Laboratory for Earth System Modeling Institute for Global Change Studies Tsinghua University Beijing China Thrust of Earth Ocean and Atmospheric Sciences Department of Ocean Science Department of Mathematics The Hong Kong University of Science and Technology Kowloon Hong Kong Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Zhuhai China School of Biological Sciences Area of Ecology and Biodiversity Swire Institute of Marine Science Institute for Climate and Carbon Neutrality Musketeers Foundation Institute of Data Science State Key Laboratory of Marine Pollution The University of Hong Kong Hong Kong Hong Kong State Key Laboratory of Marine Pollution and Department of Chemistry City University of Hong Kong Hong Kong Hong Kong Institute of Ocean and Earth Sciences University of Malaya Kuala Lumpur Malaysia Department of Marine Sciences University of Connecticut Groton CT United States Department of Ocean Science and Engineering Southern University of Science and Technology Shenzhen China Marine and Coastal Resources Research and Development Institute Department of Marine and Coastal Resources Bangkok Thailand Institute of Oceanography and Environment Universiti Malaysia Terengganu Kuala Terengganu Malaysia Department of Geosciences Princeton University Princeton NJ United States State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of Oceanography Ministry of Natural Resour

Coastal eutrophication and hypoxia remain a persistent environmental crisis despite the great efforts to reduce nutrient loading and mitigate associated environmental damages. Symptoms of this crisis have appeared to spread rapidly, reaching developing countries in Asia with emergences in Southern America and Africa. The pace of changes and the underlying drivers remain not so clear. To address the gap, we review the up-To-date status and mechanisms of eutrophication and hypoxia in global coastal oceans, upon which we examine the trajectories of changes over the 40 years or longer in six model coastal systems with varying socio-economic development statuses and different levels and histories of eutrophication. Although these coastal systems share common features of eutrophication, site-specific characteristics are also substantial, depending on the regional environmental setting and level of social-economic development along with policy implementation and management. Nevertheless, ecosystem recovery generally needs greater reduction in pressures compared to that initiated degradation and becomes less feasible to achieve past norms with a longer time anthropogenic pressures on the ecosystems. While the qualitative causality between drivers and consequences is well established, quantitative attribution of these drivers to eutrophication and hypoxia remains difficult especially when we consider the social economic drivers because the changes in coastal ecosystems are subject to multiple influences and the cause-effect relationship is often non-linear. Such relationships are further complicated by climate changes that have been accelerating over the past few decades. The knowledge gaps that limit our quantitative and mechanistic understanding of the human-coastal ocean nexus are identified, which is essential for science-based policy making. Recognizing lessons from past management practices, we advocate for a better, more efficient indexing system of coastal eutrophica

关键词： eutrophication harmful algal bloom hypoxia regime shift socioeconomic-ecological system

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Understanding the Differences in Various Satellite Remotely Sensed Soil Moisture Downscaling Methods

SSRN

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SSRN 2024年

作者： Hao, Longfei Wei, Zushuai Zhao, Tianjie Zhong, Yanmei Peng, Jian School of Surveying and Land Information Engineering Henan Polytechnic University Jiaozuo454150 China School of Artifical Intelligence Jianghan University Wuhan430056 China State Key Laboratory of Remote Sensing Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing100101 China School of Resource and Environmental Science Wuhan University Wuhan430079 China Department of Remote Sensing Helmholtz Centre for Environmental Research—UFZ Leipzig04318 Germany Remote Sensing Centre for Earth System Research—RSC4Earth Leipzig University Leipzig04103 Germany

Passive microwave remote sensing soil moisture products encounter limitations in regional-scale applications due to their coarse spatial resolution. To address this issue, various soil moisture downscaling methods have been proposed. Visible-thermal infrared remote sensing data, with its rich observations and high resolution, has emerged as an ideal data source to support downscaling methods. However, the suitability of these downscaling methods varies significantly across diverse study areas and input data types. Additional research and discussion are needed regarding the computation and combination of land surface parameters, the selection of regression models, and the scope of applicability of different methods. Therefore, this study constructed 40 downscaling methods using 5 global or local regression models combined with 8 downscaling factor combinations. The Disaggregation based on Physical And Theoretical scale Change (DISPATCH) algorithm was selected for comparison due to its semi-empirical characteristics. The accuracy differences of these downscaling algorithms were comprehensively evaluated using in situ and airborne data from three field campaigns (SMAPEx-5, SMAPVEX16, SMELR). The research findings suggest that across the semi-arid regions of Yanco and Shandian River, the majority of combinations demonstrate high accuracy. Conversely, in Iowa, characterized by a semi-humid climate, the accuracy of most combinations experiences a modest reduction. The introduction of brightness temperature can significantly improve the R and ubRMSE of the downscaling results, but it simultaneously smoothes the spatial details of various downscaling methods. Among these methods, the DISPATCH downscaled results exhibit consistent spatial patterns and rich spatial details. When compared to global linear regression, local linear regression proves to be more accurate but is susceptible to the influence of missing values. Machine learning methods yield more stable downscaling r

关键词： Soil moisture

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