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The effect of hydrogen reduction of α-MnO_(2) on formaldehyde oxidation: The roles of oxygen vacancies

Chinese Chemical Letters 2023年第3期34卷 171-174页

作者： Liping Zhou Chunying Wang Yaobin Li Xiaofeng Liu Hua Deng Wenpo Shan Hong He College of Resources and Environmental Sciences Fujian Agriculture and Forestry UniversityFuzhou 350002China Center for Excellence in Regional Atmospheric Environment Key Laboratory of Urban Pollutant ConversionInstitute of Urban EnvironmentChinese Academy of SciencesXiamen 361021China Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control Ningbo Urban Environment Observation and Research StationInstitute of Urban EnvironmentChinese Academy of SciencesNingbo 315800China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China

A series of α-MnO_(2) catalysts with various Mn valence states were treated by hydrogen reduction for different periods of time. Their catalytic capacity for formaldehyde(HCHO) oxidation was evaluated. The results indicated that hydrogen reduction dramatically improves the catalytic performance of α-MnO_(2) in HCHO oxidation. The α-MnO_(2) sample reduced by hydrogen for 2 h possessed superior activity and could completely oxidize 150 ppm HCHO to CO_(2) and H_(2)O at 70℃. Multiple characterization results illustrated that hydrogen reduction contributed to the production of more oxygen vacancies. The oxygen vacancies on the catalyst surface enhanced the adsorption, activation and mobility of O_(2) molecules, and thereby enhanced HCHO catalytic oxidation. This study provides novel insight into the design of outstanding MnO_x catalysts for HCHO oxidation at low temperature.

关键词： Hydrogen reduction α-MnO_(2) Formaldehyde oxidation Oxygen vacancies

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Automatic segmentation of stem and leaf components and individual maize plants in field terrestrial LiDAR data using convolutional neural networks

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The Crop Journal 2022年第5期10卷 1239-1250页

作者： Zurui Ao Fangfang Wu Saihan Hu Ying Sun Yanjun Su Qinghua Guo Qinchuan Xin Guangdong Key Laboratory for Urbanization and Geo-simulation Sun Yat-sen UniversityGuangzhou 510275GuangdongChina State Key Laboratory of Vegetation and Environmental Change Institute of BotanyChinese Academy of SciencesBeijing 100093China Department of Ecology College of Urban and Environmental Scienceand Key Laboratory of Earth Surface Processes of the Ministry of EducationPeking UniversityBeijing 100871China

High-throughput maize phenotyping at both organ and plant levels plays a key role in molecular breeding for increasing crop yields. Although the rapid development of light detection and ranging(Li DAR) provides a new way to characterize three-dimensional(3 D) plant structure, there is a need to develop robust algorithms for extracting 3 D phenotypic traits from Li DAR data to assist in gene identification and selection. Accurate 3 D phenotyping in field environments remains challenging, owing to difficulties in segmentation of organs and individual plants in field terrestrial Li DAR data. We describe a two-stage method that combines both convolutional neural networks(CNNs) and morphological characteristics to segment stems and leaves of individual maize plants in field environments. It initially extracts stem points using the Point CNN model and obtains stem instances by fitting 3 D cylinders to the points. It then segments the field Li DAR point cloud into individual plants using local point densities and 3 D morphological structures of maize plants. The method was tested using 40 samples from field observations and showed high accuracy in the segmentation of both organs(F-score =0.8207) and plants(Fscore =0.9909). The effectiveness of terrestrial Li DAR for phenotyping at organ(including leaf area and stem position) and individual plant(including individual height and crown width) levels in field environments was evaluated. The accuracies of derived stem position(position error =0.0141 m), plant height(R^(2)>0.99), crown width(R^(2)>0.90), and leaf area(R^(2)>0.85) allow investigating plant structural and functional phenotypes in a high-throughput way. This CNN-based solution overcomes the major challenges in organ-level phenotypic trait extraction associated with the organ segmentation, and potentially contributes to studies of plant phenomics and precision agriculture.

关键词： Terrestrial LiDAR Phenotype Organ segmentation Convolutional neural networks

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Investigation of suitable precursors for manganese oxide catalysts in ethyl acetate oxidation

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Journal of environmental Sciences 2021年第6期33卷 17-26页

作者： Yan Zhang Meng Wang Shunyu Kang Tingting Pan Hua Deng Wenpo Shan Hong He Center for Excellence in Regional Atmospheric Environment and Key Laboratory of Urban Pollutant Conversion Institute of Urban EnvironmentChinese Academy of SciencesXiamen 361021China Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control Ningbo Urban Environment Observation and Research StationChinese Academy of SciencesNingbo 315800China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China

The control of ethyl acetate emissions from fermentation and extraction processes in the pharmaceutical industry is of great importance to the *** have developed three Mn_(2)O_(3)catalysts by using different Mn precursors(MnCl_(2),Mn(CH_(3)COO)_(2),MnSO_(4)),named as Mn_(2)O_(3)-Cl,-Ac,-SO_(4).The tested catalytic activity results showed a sequence with Mn precursors as:Mn_(2)O_(3)-Cl>Mn_(2)O_(3)-Ac>Mn_(2)O_(3)-SO_(4).The Mn_(2)O_(3)-Cl catalyst reached a complete ethyl acetate conversion at 212℃(75℃lower than that of Mn_(2)O_(3)-SO_(4)),and this high activity 100%could be maintained high at 212℃for at least 100 *** characterization data about the physical properties of catalysts did not show an obvious correlation between the structure and morphology of Mn_(2)O_(3)catalysts and catalytic performance,neither was the surface area the determining factor for catalytic activity in the ethyl acetate *** we firstly found there is a close linear relationship between the catalytic activity and the amount of lattice oxygen species in the ethyl acetate oxidation,indicating that lattice oxygen species were essential for excellent catalytic *** H_(2)temperature-programmed reduction(H_(2)-TPR)results,we found that the lowest initial reduction temperature over the Mn_(2)O_(3)-Cl had stronger oxygen mobility,thus more oxygen species participated in the oxidation reaction,resulting in the highest catalytic *** convenient preparation,high efficiency,and stability,Mn_(2)O_(3)prepared with MnCl_(2)will be a promising catalyst for removing ethyl acetate in practical application.

关键词： Ethyl acetate Catalytic oxidation Manganese Precursor Lattice oxygen species

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A Method for Removing Outlier Noise from ArrayInSAR Point Clouds based on Hybrid Filtering

A Method for Removing Outlier Noise from ArrayInSAR Point Cl...

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2024 Symposium on Beyond the Canopy: Technologies and Applications of Remote Sensing

作者： Fangfang, Ji Jie, Yu Guoman, Huang Shucheng, Yang Lijun, Lu College of Resource Environment and Tourism Capital Normal University Beijing100048 China Chinese Academy of Surveying & Mapping Beijing100036 China State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation Capital Normal University Beijing100048 China Key Laboratory of 3-Dimensional Information Acquisition and Application Capital Normal University Beijing100048 China

Array Interferometric Synthetic Aperture Radar (ArrayInSAR) point cloud is a point cloud obtained by three-dimensional imaging of two-dimensional Synthetic Aperture Radar (SAR) images using array interferometric synthetic aperture radar technology, which can eliminate the phenomenon of layover in two-dimensional images and provide new data support for intelligent mapping. However, due to the influence of system thermal noise, baseline error and environment interference, there are noise points in the ArrayInSAR point cloud with uneven distribution and large elevation error, which bring a lot of gross errors to the 3D terrain results. To solve the problem that discrete points in ArrayInSAR point cloud data seriously affect the quality of three-dimensional data, this paper proposes an ArrayInSAR point cloud outlier noise removal method based on hybrid filtering. According to the distribution pattern of noise points, the outlier noise is divided into discrete outlier noise points and clusters of outlier noise. Firstly, the adaptive segmentation of point cloud dispersion coefficient within the k-neighborhood is used to remove discrete outlier noise points, and then the adaptive threshold segmentation algorithm based on the number of in-class points after K-means clustering is used to remove the cluster outlier noise of ArrayInSAR point cloud data. In order to verify the effectiveness, the proposed method is compared with other classical outlier noise removal methods. The experimental results show that the method proposed in this paper can effectively remove outlier noise in ArrayInSAR point cloud data and improve the quality of ArrayInSAR point clouds. © Author(s) 2024.

关键词： K-means clustering

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近二十年能源结构调整使我国土壤多环芳烃浓度下降

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Engineering 2023年第2期21卷 115-123,M0005页

作者：夏星辉刘亚男张真瑞席楠楠保嘉傲杨志峰 Key Laboratory of Water and Sediment Sciences of Ministry of Education&State Key Laboratory of Water Environment Simulation School of EnvironmentBeijing Normal UniversityBeijing 100875China Laboratory for Earth Surface Processes College of Urban and Environmental SciencesPeking UniversityBeijing 100871China Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education Institute of Environmental and Ecological EngineeringGuangdong University of TechnologyGuangzhou 510006China

近几十年来,我国在快速发展和工业化的同时,在环境污染防治方面也做出了巨大努力。然而,这些全国性措施(如能源结构调整)对土壤中污染物浓度的影响尚未得到很好的量化。多环芳烃(PAHs)污染在全球范围内引发重要关注,且PAHs排放与能源结... 详细信息

近几十年来,我国在快速发展和工业化的同时,在环境污染防治方面也做出了巨大努力。然而,这些全国性措施(如能源结构调整)对土壤中污染物浓度的影响尚未得到很好的量化。多环芳烃(PAHs)污染在全球范围内引发重要关注,且PAHs排放与能源结构有关。因此,我们推测我国能源结构的调整可能会降低土壤中PAHs的含量。为了验证这一假设,我们于2008年和2019年在北京54个点位重复采集了土壤样品,分析了美国环境保护署(US EPA)提出的16种优控PAHs化合物(Σ_(16)PAHs)的浓度,并收集了过去20年全国1704个土壤采样点的数据。结果表明,我国Σ_(16)PAHs浓度沿城市-郊区-农村-背景点梯度下降,且Σ_(16)PAHs浓度与区域总产值(GRP)有关,在GRP较低时Σ_(16)PAHs浓度随GRP的增加而增加,随后在GRP达到一定水平时趋于平稳。过去20年,我国土壤Σ_(16)PAH的平均浓度呈下降趋势,其中北京土壤Σ_(16)PAHs的平均浓度从2008年的22.7μg·g^(-1)总有机碳(TOC)显著下降到2019年的10.0μg·g^(-1)TOC。源识别分析推断,土壤PAHs浓度的下降趋势是由于我国煤炭、焦炭、部分油类消费量下降以及电力、天然气等清洁能源消费量上升所致。本研究例证了调整能源结构在降低土壤多环芳烃浓度和改善土壤环境质量中的重要作用。

关键词：能源结构调整环境污染防治土壤采样梯度下降全球范围近二十年 GRP

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Future climate change decreases multi-pathway but increases respiratory human health risks of PAHs across China

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National Science Open 2024年第2期3卷 128-147页

作者： Jiaao Bao Xinghui Xia Ying Zhu Bingxiang Zhao Erxue Gu Yanan Liu Xiao Yun Zhenrui Zhang Nannan Xi Yong Geng Ying Xu Zhifeng Yang Derek C.G.Muir Key Laboratory of Water and Sediment Sciences of Ministry of Education State Key Laboratory of Water Environment SimulationSchool of EnvironmentBeijing Normal UniversityBeijing 100875China State Environmental Protection Key Laboratory of Environmental Health Impact Assessment of Emerging Contaminants School of Environmental Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240China College of Urban and Environmental Sciences Laboratory for Earth Surface ProcessesSino-French Institute for Earth System SciencePeking UniversityBeijing 100871China National Climate Center China Meteorological AdministrationBeijing 100081China Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education Institute of Environmental and Ecological EngineeringGuangdong University of TechnologyGuangzhou 510006China Aquatic Contaminants Research Division Environment and Climate Change CanadaBurlington L7S 1A1Canada

Future climate change will affect the environmental fate of hydrophobic organic contaminants(HOCs)and associated human health risks,yet the extent of these effects remains ***,we couple a high-resolution environmental multimedia model with a bioaccumulation model to study the multimedia distribution of 16 priority polycyclic aromatic hydrocarbons(PAHs),a group of HOCs,and assess future PAH-related human health risks under varying climate change scenarios over China at a continental *** removing the effects of PAH emission changes,we find that the total PAH concentrations would decrease in the air,freshwater,sediment,soil,and organisms,while the high-molecular-weight PAH would increase in the air with climate warming from 1.5°C to 4°***,the multi-pathway exposure human health risks predominately influenced by dietary ingestion are expected to decrease by 1.7%–20.5%,while the respiratory risks are projected to rise by 0.2%–5.8%in the ***,the persistently high multi-pathway human health risks underscore the need for reducing future PAH emissions by 69%compared with 2009 levels in *** study demonstrates the urgency of limiting PAH emissions under future climate change for public health and highlights the importance of including the contribution of dietary ingestion in human health risk assessment.

关键词： polycyclic aromatic hydrocarbons future climate change human health risks emission reduction

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Refining the Factors Affecting N_(2)O Emissions from Upland Soils with and without Nitrogen Fertilizer Application at a Global Scale

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Advances in Atmospheric Sciences 2024年第9期41卷 1804-1820页

作者： Wenqian JIANG Siqi LI Yong LI Meihui WANG Bo WANG Ji LIU Jianlin SHEN Xunhua ZHENG State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Key Laboratory for Agro-ecological Processes in Subtropical Regions Institute of Subtropical AgricultureChinese Academy of SciencesChangsha 410125China Changsha Research Station for Agricultural&Environmental Monitoring Chinese Academy of SciencesChangsha 410125China University of Chinese Academy of Sciences Beijing 100049China State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex Shanghai Academy of Environment SciencesShanghai 200233China Institute of Carbon Neutrality Qilu ZhongkeJinan 251699China Hubei Province Key Laboratory for Geographical Process Analysis and Simulation Central China Normal UniversityWuhan 430079China Department of Ecohydrology Leibniz Institute of Freshwater Ecology and Inland FisheriesBerlin 12587Germany Key laboratory of Environment Change and Resources Use in Beibu Gulf Ministry of EducationNanning Normal UniversityNanning 530001China Golden Mantis school of Architecture Soochow UniversitySuzhou 215123China

Nitrous oxide(N_(2)O)is a long-lived greenhouse gas that mainly originates from agricultural *** and more studies have explored the sources,influencing factors and effective mitigation measures of N_(2)O in recent ***,the hierarchy of factors influencing N_(2)O emissions from agricultural soils at the global scale remains *** this study,we carry out correlation and structural equation modeling analysis on a global N_(2)O emission dataset to explore the hierarchy of influencing factors affecting N_(2)O emissions from the nitrogen(N)and non-N fertilized upland farming systems,in terms of climatic factors,soil properties,and agricultural *** results show that the average N_(2)O emission intensity in the N fertilized soils(17.83 g N ha^(-1)d^(-1))was significantly greater than that in the non-N fertilized soils(5.34 g N ha^(−1) d^(−1))(p<0.001).Climate factors and agricultural practices are the most important influencing factors on N_(2)O emission in non-N and N fertilized upland soils,*** different climatic zones,without fertilizer,the primary influence factors on soil N_(2)O emissions are soil physical properties in subtropical monsoon zone,whereas climatic factors are key in the temperate *** fertilizer,the primary influence factors for subtropical monsoon and temperate continental zones are soil physical properties,while agricultural measures are the main factors in the temperate monsoon *** enhanced agricultural practices,such as reduced N fertilizer rate combined with the addition of nitrification and urease inhibitors can potentially mitigate N_(2)O emissions by more than 60%in upland farming systems.

关键词： N_(2)O emissions influencing factors nitrogen cycling upland farming systems

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Evaluating Hazards of Land Subsidence to the Highway Using PS-InSAR Technique

Evaluating Hazards of Land Subsidence to the Highway Using P...

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2021 SAR in Big Data Era, BIGSARDATA 2021

作者： Fan, Yan Yu, Jie College of Resource Environment and Tourism Capital Normal University State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation Beijing China

ISBN: (纸本)9781665401234

Inhomogeneous land subsidence will result in road surface dislocation and threaten the normal operation of expressway. Persistent scatterer interferometric synthetic aperture radar (PS-InSAR) technique is effective in monitoring large area surface deformation. By analyzing the TerraSAR-X images, we revealed the land subsidence characteristics by the PS-InSAR technique along the expressway, which was used for evaluating the hazard degrees of land subsidence. Firstly, taking the airport 2nd highway as the research object, we obtained deformation information by PS-InSAR technique from TerraSAR-X images during 20112015. Secondly, the InSAR results were validated using 8 leveling benchmarks. Thirdly, plotting deformation rate profile, we analyzed the temporal and spatial deformation characteristics. Finally, according to grading standards, the hazard induced by land subsidence degrees were assessed along the expressway. The results showed that: (1) the airport 2nd highway presented uneven settlement during 20112015. The annual average deformation rate range was -15 mm/year -83 mm/year. The accumulated settlement range was -6.1 cm -33.7 cm. (2) The land subsidence presented obvious seasonal patterns along the airport 2nd highway. (3) The hazard degree of land subsidence along the airport 2nd highway was x-weak, weak and medium. © 2021 IEEE.

关键词： Deformation

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Integrating NLP and Ontology Matching into a Unified System for Automated Information Extraction from Geological Hazard Reports

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Journal of Earth Science 2023年第5期34卷 1433-1446页

作者： Qinjun Qiu Zhen Huang Dexin Xu Kai Ma Liufeng Tao Run Wang Jianguo Chen Zhong Xie Yongsheng Pan Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518034China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of GeosciencesWuhan 430074China Beijing Key Laboratory of Urban Spatial Information Engineering Beijing 100045China School of Geography and Information Engineering China University of GeosciencesWuhan 430074China Wuhan Geomatics Institute Wuhan 430074China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China Geological Environmental Center of Hubei Province Wuhan 430034China Faculty of Earth Resources China University of GeosciencesWuhan 430074China State Key Laboratory of Geological Processes and Mineral Resources China University of GeosciencesWuhan 430078China Wuhan Zondy Cyber Science&Technology Co. Ltd.Wuhan 430074China

Many detailed data on past geological hazard events are buried in geological hazard reports and have not been fully utilized. The growing developments in geographic information retrieval and temporal information retrieval offer opportunities to analyse this wealth of data to mine the spatiotemporal evolution of geological disaster occurrence and enhance risk decision making. This study presents a combined NLP and ontology matching information extraction framework for automatically recognizing semantic and spatiotemporal information from geological hazard reports. This framework mainly extracts unstructured information from geological disaster reports through named entity recognition, ontology matching and gazetteer matching to identify and annotate elements, thus enabling users to quickly obtain key information and understand the general content of disaster reports. In addition, we present the final results obtained from the experiments through a reasonable visualization and analyse the visual results. The extraction and retrieval of semantic information related to the dynamics of geohazard events are performed from both natural and human perspectives to provide information on the progress of events.

关键词： geological hazard report spatiotemporal information geological hazard ontology natural language processing gazetteers onlology machine learning

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Towards rational design of Cu-SSZ-13 catalysts with less N2O formation in NH3-SCR reaction: The effect of Brønsted acid sites

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Journal of environmental Sciences (China) 2025年 157卷 546-557页

作者： Liu, Jianqi Du, Jinpeng Wang, Jingyi Han, Shichao Shan, Yulong Zhang, Yan Wu, Xuanhao Gao, Shan Yu, Yunbo Wu, Zhongbiao Shan, Wenpo He, Hong Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention Institute of Urban Environment Chinese Academy of Sciences Xiamen361021 China University of Chinese Academy of Sciences Beijing100049 China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing100085 China Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control Ningbo Urban Environment Observation and Research Station Institute of Urban Environment Chinese Academy of Sciences Ningbo315800 China Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai201210 China Department of Environmental Engineering Zhejiang University Hangzhou310058 China Zhejiang Tianlan Environmental Protection Technology Co. Ltd. Hangzhou311202 China

Ammonia Selective Catalytic Reduction (NHs-SCR) technology has been employed to eliminate NOx from diesel engine exhaust, with Cu-SSZ-13 serving as the commercial catalyst. The greenhouse gas N2O is produced as a byproduct when using Cu-SSZ-13 as the NH3-SCR catalyst. To achieve synergistic control of pollutants and greenhouse gases in diesel engine exhaust, rational design of Cu-SSZ-13 catalysts is required. In this study, the effect of Brønsted acid sites in Cu-SSZ-13 catalysts on the formation of N2O was investigated. Mild thermal treatment was innovatively employed to prepare Cu-SSZ-13 catalysts with different amounts of Brønsted acid sites. EPR, H2-TPR, NH3-TPD, NMR were utilized to determine that the Brønsted acid sites were modified while the Cu species remained unchanged. Thereby an accurate assessment of the influence of Brønsted acid sites on N2O formation could be achieved. Our results showed that Cu-SSZ-13 with more Brønsted acid sites produced less N2O during the NH3-SCR reaction. In the low-temperature region, the presence of framework acid sites facilitates the decomposition of the NH4NO3 assisted by NO to form N2 and H2O, reducing the formation of N2O. In the high-temperature region, the Brønsted acid sites promote the decomposition of NH2NO into N2 and H2O. Meanwhile, the N2O-SCR reaction can also be promoted by Brønsted acid sites, thereby decreasing N2O emissions. This study suggests that in the future design and synthesis of Cu-SSZ-13 zeolites, attention should be paid to creating more Brønsted acid sites in Cu-SSZ-13 to reduce N2O emissions. © 2024

关键词： Emission control

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