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Journal of environmental sciences 2024年第5期139卷 364-376页

作者： Huan He Min Shi Xiaoxia Yang Juhong Zhan Yanting Lin Ziwei Guo Zhicheng Liao Chaochao Lai Xiaomin Ren Bin Huang Xuejun Pan Faculty of environmental science and Engineering Kunming University of Science and TechnologyKunming 650500China Yunnan Provincial Key lab of Soil Carbon Sequestration and Pollution Control Kunming 650500China Research Institute for environmental innovation(Suzhou)Tsinghua Suzhou 215163China

Dissolved organic matter(DOM)and iron minerals widely existing in the natural aquatic environment can mediate the migration and transformation of organic ***,the mechanism of interaction between DOM and iron minerals in the microbial degradation of pollutants deserves further *** this study,the mechanism of 17 alphaethinylestradiol(EE2)biodegradation mediated by humic acid(HA)and three kinds of iron minerals(goethite,magnetite,and pyrite)was *** results found that HA and iron minerals significantly accelerated the biodegradation process of EE2,and the highest degradation efficiency of EE2(48%)was observed in the HA-mediated microbial system with pyrite under aerobic ***,it had been demonstrated that hydroxyl radicals(HO·)was the main active substance responsible for the microbial degradation of ***·is primarily generated through the reaction between hydrogen peroxide secreted by microorganisms and Fe(II),with aerobic conditions being more *** presence of iron minerals and HA could change the microbial communities in the EE2 biodegradation *** findings provide new information for exploring the migration and transformation of pollutants by microorganisms in iron-rich environments.

关键词： Dissolved organic matter Iron mineral 17 alpha-ethinylestradiol Biodegradation

Satellite-enabled enviromics to enhance crop improvement

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Molecular Plant 2024年第6期17卷 848-866页

作者： Rafael T.Resende Lee Hickey Cibele H.Amaral Lucas L.Peixoto Gustavo E.Marcatti Yunbi Xu Universidade Federal de Goia´s(UFG) Agronomy DepartmentPlant Breeding SectorGoiania(GO)74690-900Brazil TheCROP a Precision-Breeding Startup:EnviromicsPhenomicsand GenomicsNo Zip-codeOperating VirtuallyGoiania(GO)and Sete Lagoas(MG)Brazil Queensland Alliance for Agriculture and Food innovation The University of QueenslandBrisbaneQLDAustralia Earth lab Cooperative Institute for Research in Environmental SciencesUniversity of Colorado BoulderBoulderCO 80303USA environmental data science innovation&inclusion lab Cooperative Institute for Research in Environmental SciencesUniversity of Colorado BoulderBoulderCO 80303USA Universidade Federal de Sa˜o Joa˜o del-Rei Forest Engineering DepartmentCampus Sete LagoasSete Lagoas(MG)35701-970Brazil Institute of Crop sciences Chinese Academy of Agricultural SciencesBeijing 100081China Peking University Institute of Advanced Agricultural sciences WeifangShandong 261325China BGI Bioverse Shenzhen 518083China

Enviromics refers to the characterization of micro-and macroenvironments based on large-scale environmental *** providing genotypic recommendations with predictive extrapolation at a site-specific level,enviromics could inform plant breeding decisions across varying conditions and anticipate productivity in a changing ***-based integration of statistics,envirotyping(i.e.,determining environmental factors),and remote sensing could help unravel the complex interplay of genetics,environment,and *** support this goal,exhaustive envirotyping to generate precise environmental profiles would significantly improve predictions of genotype performance and genetic gain in ***,informatics management platforms aggregate diverse environmental datasets obtained using optical,thermal,radar,and light detection and ranging(LiDAR)sensors that capture detailed information about vegetation,surface structure,and *** wealth of information,coupled with freely available climate data,fuels innovative enviromics *** enviromics holds immense potential for breeding,a few obstacles remain,such as the need for(1)integrative methodologies to systematically collect field data to scale and expand observations across the landscape with satellite data;(2)state-of-the-art AI models for data integration,simulation,and prediction;(3)cyberinfrastructure for processing big data across scales and providing seamless interfaces to deliver forecasts to stakeholders;and(4)collaboration and data sharing among farmers,breeders,physiologists,geoinformatics experts,and programmers across research *** these challenges is essential for leveraging the full potential of big data captured by satellites to transform 21st century agriculture and crop improvement through enviromics.

关键词： envirotyping precision breeding genotype-environment interactions remote sensing predictive models enviromic information

Benefit of aerosol reduction to winter wheat during China's clean air action:A case study of Henan Province

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Journal of environmental sciences 2024年第7期141卷 90-101页

作者： Yang Bai Pengfei Zhao Xueyang Chen Lijun Wang Wenjuan Chang Jianzhong Guo Jiayao Wang College of Geography and environmental science Henan UniversityKaifeng 475004China Henan Industrial Technology Academy of Spatio-Temporal Big data Henan UniversityZhengzhou 475000China Henan Technology innovation Center of Spatio-Temporal Big data Henan UniversityZhengzhou 450046China Key laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions(Henan University) Ministry of EducationKaifeng 475000China

A strongly declining aerosol radiative effect has been observed in China since 2013 after implementing the clean air action,yet its impact on wheat(Triticum aestivum L.)production remains *** use satellite measures and a biophysical crop model to assess the impact of aerosol-induced radiative perturbations on winter wheat production in the agricultural belt of Henan province from 2013 to *** calibrating parameters with the extended Fourier Amplitude Sensitivity Test(EFAST)and the generalized likelihood uncertainty estimation(GLUE)method,the DSSAT CERES-Wheat model was able to simulate crop biomass and yield more *** found that the aerosol negatively impacted wheat biomass by 21.87%and yield by 22.48%from 2006 to 2018,and the biomass effects from planting to anthesis were more significant compared to anthesis to *** to the strict clean air action,under all-sky conditions,the surface solar shortwave radiation(SSR)in 2018 increased by about 7.08%over 2006-2013 during the wheat growing *** a result of the improvement of crop photosynthesis,winter wheat biomass and yield increased by an average of 5.46%and 2.9%,*** findings show that crop carbon uptake and yield will benefit from the clean air action in China,helping to ensure national food and health security.

关键词： Haze pollution Clean air action Aerosol-induced radiative perturbation Wheat production DSSAT model

Developing an atmospheric aging evaluation model of acrylic coatings:A semi-supervised machine learning algorithm

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International Journal of Minerals,Metallurgy and Materials 2024年第7期31卷 1617-1627页

作者： Yiran Li Zhongheng Fu Xiangyang Yu Zhihui Jin Haiyan Gong Lingwei Ma Xiaogang Li Dawei Zhang Beijing Advanced innovation Center for Materials Genome Engineering Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China National Materials Corrosion and Protection data Center University of Science and Technology BeijingBeijing 100083China BRI Southeast Asia Network for Corrosion and Protection(MOE) Shunde Innovation School of University of Science and Technology BeijingFoshan 528399China

To study the atmospheric aging of acrylic coatings,a two-year aging exposure experiment was conducted in 13 representative climatic environments in *** atmospheric aging evaluation model of acrylic coatings was developed based on aging data including11 environmental factors from 567 cities.A hybrid method of random forest and Spearman correlation analysis was used to reduce the redundancy and multicollinearity of the data set by dimensionality reduction.A semi-supervised collaborative trained regression model was developed with the environmental factors as input and the low-frequency impedance modulus values of the electrochemical impedance spectra of acrylic coatings in 3.5wt%NaCl solution as *** model improves accuracy compared to supervised learning algorithms model(support vector machines model).The model provides a new method for the rapid evaluation of the aging performance of acrylic coatings,and may also serve as a reference to evaluate the aging performance of other organic coatings.

关键词： acrylic coatings coatings aging atmospheric environment machine learning

Recent advances in core-shell organic framework-based photocatalysts for energy conversion and environmental remediation

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Journal of Energy Chemistry 2024年第8期95卷 168-199,I0004页

作者： Qibing Dong Ximing Li Yanyan Duan Qingyun Tian Xinxin Liang Yiyin Zhu Lin Tian Junjun Wang Atif Sial Yongqian Cui Ke Zhao Chuanyi Wang School of environmental science and Engineering Shaanxi University of Science and TechnologyXi’an 710021ShaanxiChina Guangdong Engineering Technology Research Center for environmental Purification and Functional Materials Guangzhou Institute of Industrial IntelligenceGuangzhou 511400GuangdongChina Jiangxi Key lab of Flexible Electronics Flexible Electronics Innovation InstituteJiangxi Science and Technology Normal UniversityNanchang 330013JiangxiChina Helmholtz-Zentrum Berlin für Materialien und Energie Kekuléstraße 512489 BerlinGermany

Direct conversion of solar energy into chemical energy in an environmentally friendly manner is one of the most promising strategies to deal with the environmental pollution and energy *** a variety of materials developed as photocatalysts,the core-shell metal/covalent-organic framework(MOF or COF)photocatalysts have garnered significant attention due to their highly porous structure and the adjustability in both structure and *** existing reviews on core-shell organic framework photocatalytic materials have mainly focused on core-shell MOF ***,there is still a lack of indepth reviews specifically addressing the photocatalytic performance of core-shell COFs and MOFs@***,there is an urgent need for a comprehensive review encompassing these three types of core-shell *** on this,this review aims to provide a comprehensive understanding and useful guidelines for the exploration of suitable core-shell organic framework photocatalysts towards appropriate photocatalytic energy conversion and environmental ***,the classification,synthesis,formation mechanisms,and reasonable regulation of core-shell organic framework were ***,the photocatalytic applications of these three kinds of core-shell structures in different areas,such as H_(2)evolution,CO_(2)reduction,and pollutants degradation are ***,the main challenges and development prospects of core-shell organic framework photocatalysts were *** review aims to provide insights into the development of a novel generation of efficient and stable core-shell organic framework materials for energy conversion and environmental remediation.

关键词： Organic framework Core-shell structure Photocatalysis Energy conversion environmental remediation

Application of machine learning models in groundwater quality assessment and prediction:progress and challenges

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Frontiers of environmental science & Engineering 2024年第3期18卷 25-55页

作者： Yanpeng Huang Chao Wang Yuanhao Wang Guangfeng Lyu Sijie Lin Weijiang Liu Haobo Niu Qing Hu School of Environment Harbin Institute of TechnologyHarbin 150090China School of environmental science and Engineering Southern University of Science and TechnologyShenzhen 518055China Engineering innovation Center of SUSTech(Beijing) Southern University of Science and TechnologyBeijing 100083China Technical Center for Soil Agriculture and Rural Ecology and EnvironmentMinistry of Ecology and EnvironmentBeijing 100012China Chinese Academy of environmental Planning Beijing 100043China

Groundwater quality assessment and prediction(GQAP)is vital for protecting groundwater *** GQAP methods can not adequately capture the complex relationships among attributes and have the disadvantage of being computationally ***,the application of machine learning(ML)in GAQP(GQAPxML)has been widely studied due to ML’s reliability and *** many GQAPxML publications exist,a thorough review is *** review provides a comprehensive summary of the development of ML applications in the field of ***,the workflow of ML modeling is briefly introduced,as are data preparation,model development,model evaluation,and model ***,299 publications related to the topic are filtered,mainly through ML ***,many aspects of GQAPxML,such as publication trends,the spatial distribution of study areas,the size of data sets,and ML algorithms,are discussed from a bibliometric *** addition,we review in detail the well-established applications and recent findings for several subtopics,including groundwater quality assessment,groundwater quality modeling using groundwater quality parameters,groundwater quality spatial mapping,probability estimation of exceeding the groundwater quality threshold,groundwater quality temporal prediction,and the hybrid use of ML and physics-based ***,the development of GQAPxML is explored from three perspectives:data collection and preprocessing,model building and evaluation,and the broadening of model *** review provides a reference for environmental scientists to better understand GQAPxML and promotes the development of innovative methods and improvements in modeling quality.

关键词： Groundwater quality assessment Groundwater quality prediction Machine learning Groundwater modeling

Efficient ECG classification based on Chi-square distance for arrhythmia detection

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Journal of Electronic science and Technology 2024年第2期22卷 1-15页

作者： Dhiah Al-Shammary Mustafa Noaman Kadhim Ahmed M.Mahdi Ayman Ibaida Khandakar Ahmedb College of Computer science and Information Technology University of Al-QadisiyahAl Diwaniyah58001Iraq Intelligent Technology innovation lab Victoria UniversityMelbourne3011Australia

This study introduces a new classifier tailored to address the limitations inherent in conventional classifiers such as K-nearest neighbor(KNN),random forest(RF),decision tree(DT),and support vector machine(SVM)for arrhythmia *** proposed classifier leverages the Chi-square distance as a primary metric,providing a specialized and original approach for precise arrhythmia *** optimize feature selection and refine the classifier’s performance,particle swarm optimization(PSO)is integrated with the Chi-square distance as a fitness *** synergistic integration enhances the classifier’s capabilities,resulting in a substantial improvement in accuracy for arrhythmia *** results demonstrate the efficacy of the proposed method,achieving a noteworthy accuracy rate of 98% with PSO,higher than 89% achieved without any previous *** classifier outperforms machine learning(ML)and deep learning(DL)techniques,underscoring its reliability and superiority in the realm of arrhythmia *** promising results render it an effective method to support both academic and medical communities,offering an advanced and precise solution for arrhythmia detection in electrocardiogram(ECG)data.

关键词： Arrhythmia classification Chi-square distance Electrocardiogram(ECG)signal Particle swarm optimization(PSO)

Numerical study of the influence of the atmospheric pressure on the thermal environment in the passenger cabin

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Building Simulation 2024年第2期17卷 253-265页

作者： Xin Su Yu Guo Zhengwei Long Yi Cao Tianjin Key lab.of Indoor Air environmental Quality Control School of Environmental Science and EngineeringTianjin UniversityTianjin300072China Shanghai Aircraft Design and Research Institute Jinke RoadPudong DistrictShanghai201210China

The cabin air pressure remains lower than the horizontal atmospheric pressure when the airplane is in *** pressure is one of the parameters that must be taken into consideration while studying the thermal environment of an airplane *** are still no reference values for aircraft cabins despite the fact that numerous studies on low pressure heat transfer have demonstrated the connection between convective heat transfer coefficient(CHTC)and air *** this paper,a correction method for CHTC under low pressure conditions was established by using the dummy heat dissipation in the low-pressure cabin *** this basis,a thermal environment simulation model was developed,then was applied to the simulation of a seven-row aircraft cabin containing 42 passengers,and the CHTC and heat loss of dummy surface in the cabin were ***,the results of PMV calculated by using heat dissipation and air parameters at sampling points were *** results show that the modified CHTC can accurately reflect the cabin thermal environment under low pressure conditions,and the correction of CHTC can be realized by adjusting the turbulent Prandtl number,which is nonlinear correlated with the *** simulation results of the thermal environment in the seven-row cabin show that the CHTC changes by about 42%before and after *** air pressure decreases during take-off,which reduces the average CHTC of the crew surface from 5.09 W/(m^(2)·K)to 4.56 W/(m^(2)·K),but the air temperature rises by about 0.2°C as a *** deviation of PMV results calculated by using simulated heat loss data and using air parameters of measuring points in space is up to 0.5,but the latter is representative for calculating the thermal comfort level of the whole cabin.

关键词： low pressure aircraft cabin simulation heat dissipation convective heat transfer coefficient

Electrochemical converting ethanol to hydrogen and acetic acid for large scale green hydrogen production

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Nano Research 2024年第3期17卷 1542-1551页

作者： Yufeng Zhang Wei Zhu Jinjie Fang Zhiyuan Xu Yanrong Xue Jiajing Pei Rui Sui Xingdong Wang Xuejiang Zhang Zhongbin Zhuang State Key lab of Organic-Inorganic Composites and Beijing Advanced innovation Center for Soft Matter science and Engineering Beijing University of Chemical TechnologyBeijing 100029China laboratory of Advanced Functional Materials of Nanjing Nanjing Xiaozhuang UniversityNanjing 211171China Beijing Key laboratory of Energy environmental Catalysis Beijing University of Chemical TechnologyBeijing 100029China

Electrochemical coupling hydrogen evolution with biomass reforming reaction(named electrochemical hydrogen and chemical cogeneration(EHCC)),which realizes green hydrogen production and chemical upgrading simultaneously,is a promising method to build a carbon-neutral ***,we analyze the EHCC process by considering the market *** ethanol to acetic acid and hydrogen approach is the most feasible for large-scale hydrogen *** develop AuCu nanocatalysts,which can selectively oxidize ethanol to acetic acid(>97%)with high long-term *** isotopic and in-situ infrared experiments reveal that the promoted water dissociation step by alloying contributes to the enhanced activity of the partial oxidation reaction path.A flow-cell electrolyzer equipped with the AuCu anodic catalyst achieves the steady production of hydrogen and acetic acid simultaneously in both high selectivity(>90%),demonstrating the potential scalable application for green hydrogen production with low energy consumption and high profitability.

关键词： selective ethanol electrooxidation gold alloy catalyst electrochemical-coupled hydrogen production market assessment interfacial water activation

Machine learning and neural network supported state of health simulation and forecasting model for lithium-ion battery

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Frontiers in Energy 2024年第2期18卷 223-240页

作者： Nan QI Kang YAN Yajuan YU Rui LI Rong HUANG Lai CHEN Yuefeng SU Beijing Institute of Technology Chongqing innovation Center Chongqing 401120China Department of Energy and environmental Materials School of Materials Science and EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing Electric Vehicle Co. Ltd.Beijing 100176China

As the intersection of disciplines deepens,the field of battery modeling is increasingly employing various artificial intelligence(AI)approaches to improve the efficiency of battery management and enhance the stability and reliability of battery *** paper reviews the value of AI methods in lithium-ion battery health management and in particular analyses the application of machine learning(ML),one of the many branches of AI,to lithium-ion battery state of health(SOH),focusing on the advantages and strengths of neural network(NN)methods in ML for lithium-ion battery SOH simulation and *** is one of the important branches of ML,in which the application of NNs such as backpropagation NN,convolutional NN,and long short-term memory NN in SOH estimation of lithium-ion batteries has received wide *** so far have shown that the utilization of NN to model the SOH of lithium-ion batteries has the advantages of high efficiency,low energy consumption,high robustness,and scalable *** the future,NN can make a greater contribution to lithium-ion battery management by,first,utilizing more field data to play a more practical role in health feature screening and model building,and second,by enhancing the intelligent screening and combination of battery parameters to characterize the actual lithium-ion battery SOH to a greater *** in-depth application of NN in lithium-ion battery SOH will certainly further enhance the science,reliability,stability,and robustness of lithium-ion battery management.

关键词： machine learning lithium-ion battery state of health neural network artificial intelligence