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SSRN 2025年

作者： Jiang, Saihua Song, Tao Kong, Qi Li, Shun Dai, Kang Attia, Nour F. Wang, Hetang Wang, Jianji School of Mechanical and Automotive Engineering Institute of Safety Science & Engineering South China University of Technology Guangzhou510641 China Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing South China University of Technology Guangzhou510641 China School of Mechanical Engineering Long Dong University Qingyang745000 China School of Safety Engineering China University of Mining and Technology Xuzhou221116 China School of Environmental Science and Engineering Guangdong University of Technology Guangzhou510006 China Gas Analysis and Fire Safety Laboratory Chemistry Division National Institute for Standards Giza12211 Egypt

Tactile sensing, one of the most fundamental human senses, facilitates extensive information exchange between humans and their environment. Similarly, tactile sensing provides robots multidimensional sensory information, enabling them to perceive and recognize objects. Triboelectric nanogenerator (TENG) sensors have shown great potential in addressing this need. Due to their high material selectivity, these sensors can utilize flexible materials to directly convert tactile information into electrical signals without external power, enabling self-powered flexible sensing. We developed a wearable flexible tactile TENG (FT-TENG) in this study. The device uses integrated PDMS-EGaIn ink as a conductive electrode, allowing direct ink-writing of patterned flexible conductive circuits on a PDMS substrate. Multiple flexible thin films were employed as friction layers, achieving comprehensive flexibility. Combined with the 1D-CNN algorithm, the device can accurately recognize various materials with over 99.53% accuracy. In surface roughness detection, the accuracy can exceed 85.26%. These results highlight FT-TENG’s potential as a tactile sensor for material perception in robotics. © 2025, The Authors. All rights reserved.

关键词： Conductive films

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Flood disaster chain deduction based on cascading failures in urban critical infrastructure

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reliability engineering and System Safety 2025年 261卷

作者： Wang, Yongming Ye, Zhoujing Jia, Xinran Liu, Huifang Zhou, Guoqing Wang, Linbing The Emergency Management Institute National Academy of Governance Beijing100089 China China Society of Emergency Management Beijing100089 China National Center for Materials Service Safety University of Science and Technology Beijing Beijing100083 China College of Geomatics and Geoinformation Guilin University of Technology Guilin541004 China Guangxi Key Laboratory of Spatial Information and Geomatics Guilin University of Technology Guilin541004 China School of Environmental Civil Agricultural and Mechanical Engineering University of Georgia United States

With the acceleration of global climate change and urbanization, cities are increasingly vulnerable to extreme rainfall and flooding disasters. Urban infrastructure, which is interconnected physically, geographically, and informationally, serves as a carrier for the propagation of disasters, amplifying their effects and exacerbating the overall system's vulnerability. This paper proposes a novel method for analyzing urban flood disaster chains, using cascading failures within critical urban infrastructure networks as a basis. The method first constructs extreme rainfall flood disaster scenarios for urban areas through numerical simulation, considering rainfall and hydrological conditions. Next, a network model is developed that encompasses key urban infrastructures, including electricity, transportation, and communication systems. The coupling mechanism of these three critical infrastructures is defined, considering their geographical and physical connections. By analyzing the failure modes and propagation pathways of these infrastructures under extreme rainfall scenarios, the method explains the nonlinear spatiotemporal evolution of flood disaster chains, from localized failures ("points") to broader network-wide disruptions ("lines"), and ultimately to extensive systemic failures ("planes"). Furthermore, the impact of protecting key nodes within the infrastructure on the spatiotemporal evolution of disaster chains is analyzed. This analysis demonstrates how safeguarding critical points can disrupt the disaster chain and mitigate the impacts of flooding, offering new perspectives and analytical tools for urban flood disaster management and emergency response strategies. The findings are significant for understanding the interdependencies within urban infrastructure and enhancing the disaster resilience of urban systems. © 2025

关键词： Urban transportation

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Coupling effect of phytic acid and chlorite on uranium removal by Shewanella putrefaciens under simulated natural environment

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Water Research 2025年 281卷 123582页

作者： Li, Qingrong Zhang, Yang-Yang Zhang, Guo-Hao Qin, Yilin Cheng, Wencai Wang, Xinyu Fu, Liuyuan Wang, Nan Li, Xiaoan Dong, Faqin Li, Jun Nie, Xiaoqin National Collaborative Innovation Center for Nuclear Waste and Environmental Safety Southwest University of Science and Technology Mianyang621010 China CAEA Innovation Center of Nuclear Environmental Safety Technology Southwest University of Science and Technology Mianyang621000 China Fundamental Science Center of Rare Earths Ganjiang Innovation Academy Chinese Academy of Sciences Ganzhou341000 China Department of Chemistry Southern University of Science and Technology Shenzhen518055 China Mianyang Central Hospital NHC Key Laboratory of Nuclear Technology Medical Transformation Mianyang621000 China Department of Chemistry and Engineering Research Center of Advanced Rare‐Earth Materials of Ministry of Education Tsinghua University Beijing100084 China

Understanding the transport and transformation of uranium species in surface and underground water environments, including biological migration, is a critical issue in nuclear environmental research. While it is known that uranium is primarily immobilized through reduction and mineralization with clay minerals and microorganisms, the coupled processes involving these motifs and their molecular mechanisms under multiple environmental factors remain elusive. In this work, using phytic acid (denoted as IP6 hereinafter) as a typical organic ligand and chlorite (a layered hydrous aluminum silicate with Mg2+, Fe2+, etc.) as a typical inorganic clay mineral, we investigate the immobilization of UO22+ [abbreviated as U(VI) here in after] by S. putrefaciens under simulated natural aerobic conditions. The experimental results show that in aerobic environment, the reduction of uranium by S. putrefaciens is inhibited, and only mineralized products are observed. In the chlorite-U(VI) system, UO22+ enters the chlorite interlayer due to internal channel restriction effects and becomes more firmly fixed over time. When there are decomposed S. putrefaciens, UO22+ is fixed by its stronger binding sites and adsorbed on the surface of chlorite. After adding phytic acid, the process of uranium biomineralization by S. putrefaciens is blocked. In the simulated aerobic four component system, some Fe2+ and Mg2+ ions dissolve from the chlorite and replace the UO22+ adsorbed by IP6. The released UO22+ combines with the decomposing S. putrefaciens, and the complex deposits on the surface of the chlorite. At low pH values (pH6 dissolves the metal ions of the chlorite and reduces their coupling with uranium coordination. Quantum-chemical methods are utilized to understand the experimental results at the molecular level and to provide an analysis of the interlayer structure of uranium in clay minerals. This study delves into the migration and fixation mechanisms of uranium in complex aerobic wate

关键词： Binding sites

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Impact of climate change on arsenic concentrations in paddy rice and the associated dietary health risks in Asia: an experimental and modelling study

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The Lancet Planetary Health 2025年第5期9卷 e397-e409页

作者： Wang, Dongming Kim, Brent F Nachman, Keeve E Chiger, Andrea A Herbstman, Julie Loladze, Irakli Zhao, Fang-Jie Chen, Chuan Gao, Axiang Zhu, Yongguan Li, Fangbai Shen, Ren Fang Yan, Xiaoyuan Zhang, Jiabao Cai, Chuang Song, Lian Shen, Min Ma, Chuanqi Yang, Xiong Zhou, Wei Wang, Yujun Tang, Haoye Jiang, Yu Ding, Yanfeng Liu, Wuxing Sun, Jianqiang Zhou, Wei Navas-Acien, Ana Zhu, Chunwu Ziska, Lewis H State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of Sciences Nanjing China University of Chinese Academy of Sciences Beijing China Center for a Livable Future Johns Hopkins University Baltimore MD United States Department of Environmental Health & Engineering Johns Hopkins Bloomberg School of Public Health Baltimore MD United States Risk Sciences and Public Policy Institute Johns Hopkins Bloomberg School of Public Health Baltimore MD United States Department of Health Policy and Management Johns Hopkins Bloomberg School of Public Health Baltimore MD United States Columbia Center for Children's Environmental Health Columbia University New York NY United States Bryan College of Health Sciences Bryan Medical Center Lincoln NE United States State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization College of Resources and Environmental Sciences Nanjing Agricultural University Nanjing China Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing China National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China Guangdong Key Laboratory of Integrated Agroenvironmental Pollution Control and Management Institute of Eco-environmental and Soil Sciences Guangdong Academy of Sciences Guangzhou China University of Chinese Academy of Sciences Nanjing China Jiangsu Collaborative Innovation Center for Modern Crop Production Nanjing Agricultural University Nanjing China College of Environment Zhejiang University of Technology Hangzhou China Ministry of Agriculture Key Laboratory of Plant Nutrition and Fertilizer Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing China Environmental Health Sciences Mailman School of Public Health Columbia University New York NY United States

Background: Rising global atmospheric carbon dioxide (CO2) concentrations and surface temperatures could negatively affect rice yields and nutritional quality;however, their effects on arsenic accumulation in paddy ri...

Background: Rising global atmospheric carbon dioxide (CO₂) concentrations and surface temperatures could negatively affect rice yields and nutritional quality;however, their effects on arsenic accumulation in paddy rice have not been assessed concurrently. We aimed to assess the impact of increases in CO₂ and temperature (individually and in combination) on arsenic concentrations in rice, characterise soil properties that might influence arsenic uptake, and model the associated risks of cancer and other health outcomes due to increased arsenic exposure. Methods: For this modelling study we performed in-situ multi-varietal trials using Free-Air CO₂ Enrichment platforms with and without supplemental temperature to examine the bioaccumulation of arsenic in paddy rice and the underlying biogeochemical mechanisms from 2014 to 2023. We modelled dietary inorganic arsenic exposure and the associated risks of cancer and non-cancer health outcomes via rice consumption for seven of the leading rice-consuming countries in east and southeast Asia. Findings: Concomitant increases in CO₂ and temperature resulted in a synergistic increase of inorganic arsenic in rice grain. The observed increase is likely to be related to changes in soil biogeochemistry that favoured reduced arsenic species. Modelled consumption of rice under these conditions resulted in projected increases in inorganic arsenic exposure and lifetime cancer and health risks for multiple Asian countries by 2050. Interpretation: Inorganic arsenic exposure and the associated health consequences might increase in rice grain grown in flooded systems with mid-century climate projections. The current assessment reinforces the urgent need for mitigation of arsenic exposure in rice relative to near-term climate change. Funding: national key Research and Development Program of China, national Natural science Foundation of China, key-Area Research and Development Program of Guangdong

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Occurrence and ecological risk of microplastics in different mariculture feeds

Water Cycle

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Water Cycle 2025年 6卷 306-318页

作者： Ge, Anqi Liu, Liuqingqing Xu, Jialu Sun, Cuizhu Yuan, Zixi Wang, Rongyuan Zheng, Hao Luo, Xianxiang Chen, Lingyun Li, Fengmin Institute of Coastal Environmental Pollution Control College of Environmental Science and Engineering Sanya Oceanographic Institution Ministry of Education Key Laboratory of Marine Environment and Ecology Ocean University of China Qingdao266100 China MSc in Management University of York YorkYO10 5DD United Kingdom Marine Ecology and Environmental Science Laboratory Qingdao Marine Science and Technology Center Qingdao266071 China North China Sea Environmental Monitoring Center State Oceanic Administration Qingdao266033 China Faculty of Agricultural Life and Environmental Science University of Alberta EdmontonABT6G 2P5 Canada National Joint Research Center for Ecological Conservation and High Quality Development of the Yellow River Basin Beijing100012 China

The pollution of microplastics (MPs) in mariculture animals and its risk to human health remain a growing concern. However, although much attention has been paid to the release of MPs in mariculture facilities, few reports can be found on the occurrence of MPs in mariculture feeds consumed by mariculture animals. Therefore, the present study investigated the occurrence patterns of MPs in 23 types of mariculture feeds for different species at different life history stages, and the related ecological risks of these MPs were also assessed. MPs were prevalent with an average abundance of 5491 ± 2712 particles kg−1 in all the mariculture feeds. Notably, the abundance of MPs in Stichopus japonicus (SJ) feeds was the highest, especially in adult stage feeds of SJ (19683 ± 6789 particles kg−1). The majority of MPs in mariculture feeds were 20–500 μm in size (81.4%), shaped as fragments (66.2%) and fibers (23.5%), mostly transparent (58.5%) and yellow (18.3%) in color, and the polymer types were dominated by polycaprolactone (PCL), polypropylene (PP), polyethylene (PE), and cellophane (CP), which together accounted for 61.6%. More importantly, the risk index (H) indicated that MPs in Sebastes schlegelii feeds had high risk (H: 100–1000), while Litopenaeus vannamei, Penaeus monodon, Stichopus japonicus, and Larimichthys crocea feeds had medium risk (H: 10–100). These findings offer valuable information about MP contamination in mariculture feeds and establish a theoretical foundation for the safe production and use of mariculture feeds, contributing to the development of a risk assessment framework for MPs in mariculture feeds. © 2025 The Authors

关键词： Invertebrates

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Kinetic Modeling of Secondary Organic Aerosol in a Weather-Chemistry Model: Parameterizations, Processes, and Predictions for GOAmazon

ACS ES&T Air

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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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Simultaneous analysis of multi-class antibiotics in bottled water using large-volume direct-injection LC-MS/MS

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RSC advances 2025年第21期15卷 16973-16982页

作者： Haijun Wang Qiao Zhang Xiaolin Li Huan Chen Xiaolan Zhu Liming Yang Hongling Yin Jing Sun Shuhong Fang Hui Zhang College of Resources and Environment Chengdu University of Information Technology Chengdu 610225 China zhanghui@***. Department of Environmental Engineering and Earth Science Clemson University South Carolina 29634 USA. Agilent Technologies (China) Co. Ltd 100102 China. Department of Chemical and Biomolecular Engineering National University of Singapore 117585 Singapore. Key Laboratory of Atmospheric Environment Simulation and Pollution Control at Chengdu University of Information Technology of Sichuan Province Chengdu 610225 China.

A large-volume direct-injection (LVDI) method was developed and validated for the simultaneous analysis of 69 antibiotics in bottled water using ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Target antibiotics included 23 sulfonamides, 19 quinolones, 12 macrolides, 11 β-lactams, and 4 tetracyclines. Optimization of ion source parameters led to enhanced signal intensities for 55 antibiotics. The 100 μL injection volume was both feasible and preferred, resulting in increased signal intensities while maintaining unchanged peak shapes for the antibiotics. Good absolute recoveries for the 69 antibiotics were obtained with the LVDI method, primarily ranging from 80% to 120%, whereas lower absolute recoveries of macrolides, quinolones, sulfonamides and β-lactams were observed with a solid-phase extraction (SPE) method. The limits of detection (LODs) for antibiotics were generally comparable between the LVDI and SPE methods, with values below 1 ng L for most antibiotics (0.00271-26.6 ng L). Analysis of 25 brands of bottled water using the LVDI method revealed the presence of 54 antibiotics from 5 classes, with detection frequencies (DFs) ranging from 4% to 100% and detected concentrations between 0.0453 and 37.4 ng L. Multiple antibiotics were detected simultaneously in bottled water, with more than 10 antibiotics identified in each of 9 different brands. Quinolones and sulfonamides were the predominant antibiotics, accounting for over 80% of the total concentration. Only sulfaclozine showed significantly different concentrations between purified drinking water and natural mineral water (22.2 17.2 ng L, < 0.05).

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Co-occurrence of multiple contaminants: Unentangling adsorption behaviour in agricultural soils

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environmental Pollution 2025年 373卷 126118页

作者： Tan, Gaowei Tang, Darrell W.S. Silva, Vera Mu, Hongyu Qin, Shijie Rima, Osman Geissen, Violette Yang, Xiaomei State Key Laboratory of Soil and Water Conservation and Desertification Control College of Soil and Water Conservation Science and Engineering Northwest A&F University Yangling 712100 China Soil Physics and Land Management Group Wageningen University & Research Wageningen6700 AA Netherlands Water Energy and Environmental Engineering University of Oulu Finland State Key Laboratory of Nutrient Use and Management College of Resources and Environmental Sciences National Academy of Agriculture Green Development National Observation and Research Station of Agriculture Green Development China Agricultural University Beijing100193 China College of Land Sciences and Technology China Agricultural University Beijing100193 China

The co-occurrence of pesticides, pharmaceuticals, and MPs has resulted in combined toxicity and high risks to ecosystems and human health. However, understanding on the interactions among co-occurring pollutants in soils remains limited. This study focused on adsorption behaviour of a pesticide mixture (chlorpyrifos (CPF), pendimethalin (PDM) and pyraclostrobin (PCS)) in three soils (sandy soil (S1), loamy soil (S2), and silt soil (S3)) to examine the absorption behaviour of pesticides in the presence of the pharmaceutical compound albendazole (ALB) and starch-based microplastics (MPs). The results showed that ALB significantly decreased (p d of pesticides showed positive correlations (p d of pesticides and soil properties was observed in soil-MPs matrices. This study indicates that co-occurring pollutants could alter the adsorption behaviour of pesticides in soil and thereby affect their bioavailability and mobility in the soil ecosystem. Further study is urgently needed to assess the ecotoxicity of co-occurring multi-contaminants, as well as their potential transport to other environmental compartments. © 2025 The Authors

关键词： Soil pollution

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Potential Challenges and Food Security Responses to Climate Change in China and Mongolia in the Post-COP28 Era

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Journal of Resources and Ecology 2025年第1期16卷 22-35页

作者： CHEN Jiannan Faith Ka Shun CHAN WANG Jiayu FENG Meili WANG Zilin Ochir ALTANSUKH SHAO Yating LI Pengfei WANG School of Human Settlements and Civil Engineering Xi’an Eurasia UniversityXi’an 710054China College of Geomatics Xi’an University of Science and TechnologyXi’an 710054China School of Geographical Sciences University of Nottingham Ningbo ChinaNingboZhejiang 315100China Water@Leeds Research Institute and School of Geography University of LeedsLeeds LS29JTUK Research Centre for Intelligent Management&Innovation Development/Research Base for Shenzhen Municipal Policy&Development Southern University of Science and TechnologyShenzhenGuangdong 518000China Key Laboratory of Urban Environment and Health Institute of Urban EnvironmentChinese Academy of SciencesXiamenFujian 361021China Department of Environment and Forest Engineering School of Engineering and Technology and Environmental Engineering LaboratoryNational University of MongoliaUlaanbaatar 14201Mongolia State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China

After the COP28 Conference,many countries are increasingly concerned about their future practices regarding food *** North Asia,the Northeast China is the major food production base for the *** the border,the economy of Mongolia is heavily reliant on agricultural production and animal *** recent years,climatic extremes such as droughts and floods,combined with human-induced overgrazing,have posed alarming threats to food *** review illustrates the challenges and constraints these two countries are facing due to climate changes and summarizes the existing measures and established programs in both ***,we develop the“climate resilient agriculture”(CRA)framework for improving agricultural *** framework emphasizes the importance of international institutions,such as the World Bank,and developed countries to provide more financial and technological support to bolster climate resilience in Northern ***,we conclude by encouraging cross-border co-production and collaborations among governments to implement the CRA framework to tackle future climatic challenges.

关键词： agricultural sensitivity climatic extremes climate resilient agriculture(CRA) food security China and Mongolia

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A model-free deep learning-based health prognosis methodology with epistemic and aleatoric uncertainties

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Expert Systems with Applications 2025年 284卷

作者： Sun, Bo Pan, Junlin Wu, Zeyu Feng, Qiang Lu, Chen Wang, Zili School of Reliability and Systems Engineering Beihang University Beijing100191 China State Key Laboratory of Reliability and Environmental Engineering Technology Beijing100191 China Intelligent Science & Technology Academy of CASIC Beijing100043 China

Aleatoric uncertainty inherent in degradation data and epistemic uncertainty introduced by a research method directly affect the trustworthiness of health prognosis, specifically in terms of the state of health (SOH) and remaining useful life (RUL). In this paper, a deep learning methodology integrating Bayesian deep learning (BDL) and model-free approaches is proposed to eliminate the influence of uncertainties and improve the accuracy of the prediction results. First, an advanced dropout approach is introduced to quantify the epistemic uncertainty due to the neural network model parameters in a model-free manner. Then, a data augmentation approach and an arbitrary polynomial chaos expansion method are used in a model-free manner to quantify the aleatoric uncertainty inherent in the data distribution. Next, a model-free BDL model is constructed for health probability prognosis that incorporates two types of uncertainty. In addition, an incremental learning approach based on an asynchronous calibration strategy is presented to adaptively update the prediction model. To verify the effectiveness of the proposed method, lithium-ion battery SOH prognosis and turbofan engine RUL prediction experiments are conducted using degradation datasets. The results show that the proposed method can provide more accurate point estimations and more trustworthy interval estimations. © 2025 Elsevier Ltd

关键词： Size distribution

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