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Relationship between Urban Industrial Land Use Size and Sulfur Dioxide Emissions:Evidence from 294 Cities in China

Journal of Resources and Ecology 2024年第4期15卷 793-803页

作者： WANG Yang YANG Min WU Yingmei SUN Guiquan YUE Xiaoli zhang hong’ou Faculty of Geography Yunnan Normal UniversityKunming 650500China Guangzhou Institute of Geography Guangdong Academy of SciencesGuangzhou 510070China

Although the relationship between the size of urban industrial land use and pollutant emissions has been widely discussed from different perspectives(e.g.,the scale and crowding effects),the results of various studies have revealed positive,negative,and combined impact ***,how the expansion of urban industrial land use affects SO2 emissions remains *** need to clarify this relationship in order to facilitate the realization of China’s pollution reduction and emission reduction *** study used the panel data from 294 cities spanning from 2011 to 2019 to construct a spatial econometric *** objective was to explore the correlation between the scale of urban industrial land and sulfur dioxide emissions in *** results show that a large scale of urban industrial land use corresponds to lower sulfur dioxide emissions per unit of industrial added *** gaining a deeper understanding of the relationship between the scale of urban industrial land use and sulfur dioxide emissions,policymakers can further reduce pollutant emissions by rationalizing the planning of urban industrial land use and industrial *** addition to promoting industrial agglomeration and economies of scale in cities with extensive industrial land use,this strategy can support the development of efficient and environmentally friendly industries in areas with limited industrial land *** the technology and encouraging the development of green industries can help reduce environmental pollution and promote sustainable urban development.

关键词： urban industrial land sulfur dioxide emissions pollution reduction and emission reduction spatial panel model

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生态经济地理:一个有利于自然地理和人文地理融合的构想

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热带地理 2024年第8期44卷 1368-1375页

作者：叶玉瑶张虹鸥刘伟陈彩霞广东省科学院广州地理研究所广州510070

回应当前学界关于自然地理与人文地理能否走向融合的讨论,文章构建了一个有利于自然地理与人文地理融合的生态经济地理分析框架,提出关注“人”作为本身级联产业、技术、制度系统复杂关联的地域巨系统的能动性变化,及其与生态系统之间... 详细信息

回应当前学界关于自然地理与人文地理能否走向融合的讨论,文章构建了一个有利于自然地理与人文地理融合的生态经济地理分析框架,提出关注“人”作为本身级联产业、技术、制度系统复杂关联的地域巨系统的能动性变化,及其与生态系统之间的双向反馈关系,通过探讨环境变化和技术变革背景下人地系统耦合机制和调控途径,在综合权衡中寻找人类可持续发展的最佳答案。选用“桑-基鱼塘生态经济系统百年演变”“数据中心的‘数-能-水’系统级联”“生态修复规划的人文视角”3个案例来阐明生态经济地理的研究视角与思路。最后,围绕“格局―过程―关联―路径”的分析框架,提出了生态经济地理需重点关注的4个研究议题:生态系统与经济系统各要素耦合格局、不同系统间要素流动过程及影响、生态经济耦合系统的区域复杂关联、生态经济的可持续发展路径。以期以上述议题为牵引,加强自然与人文学者之间的相互协作,促进地理学科的融合发展,提升地理学解决综合性问题的能力。

关键词：自然地理学人文地理学学科融合生态经济地理人地关系

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地理学视角下的政策流动性研究进展与展望

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人文地理 2024年第1期39卷 1-7页

作者：郭杰杜志威张虹鸥汪坤广东省科学院广州地理研究所广州510070 广东省遥感与地理信息系统应用重点实验室广州510070 广东省地理空间信息技术与应用公共实验室广州510070

在全球化日益加剧背景下,政策流动性已成为国际人文地理学的一个重要且前沿的话题,引起了政治经济学、后殖民主义和后结构主义学者的广泛关注,并产生了丰富的理论与实证研究。在对政治学“规范—理性”研究视角的批判基础上,地理学者先... 详细信息

在全球化日益加剧背景下,政策流动性已成为国际人文地理学的一个重要且前沿的话题,引起了政治经济学、后殖民主义和后结构主义学者的广泛关注,并产生了丰富的理论与实证研究。在对政治学“规范—理性”研究视角的批判基础上,地理学者先后采用“关系—建构”和“拓扑—拼装”视角对政策流动与变异、政策流动下的不均衡地理、政策流通的(权力)拓扑网络等问题展开探讨。本文梳理了政策流动性的三次研究视角的转向,总结不同视角下的核心议题、研究方法与视角局限。在此基础上,本文尝试提出流动性研究对重新思考全球化与地方发展、城市关系网络与不均衡地理发展等问题带来的启示,以期为未来国内学者开展相关议题研究提供理论参考。

关键词：政策流动性变异社会建构拼装理论地理非均衡发展

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中国城市新型基础设施建设影响人工智能产业链发展的时空分异研究

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地理与地理信息科学 2024年第2期40卷 59-66页

作者：许吉黎黄冠叶玉瑶张虹鸥刘郑倩广东省科学院广州地理研究所/广东省遥感与地理信息系统应用重点实验室广东广州510070 香港大学城市规划与设计系中国香港999077

近年来,新型基础设施建设(“新基建”)在国家战略层面密集部署,成为培育新兴产业和构筑新兴产业链的重要支撑。鉴于现有研究对城市空间尺度“新基建”影响新兴产业链不同环节发展效应的时空分异关注有限,该文分析2011—2022年中国主要... 详细信息

近年来,新型基础设施建设(“新基建”)在国家战略层面密集部署,成为培育新兴产业和构筑新兴产业链的重要支撑。鉴于现有研究对城市空间尺度“新基建”影响新兴产业链不同环节发展效应的时空分异关注有限,该文分析2011—2022年中国主要城市“新基建”和人工智能产业链发展的时空特征,揭示城市“新基建”影响人工智能产业链上中下游不同环节发展效应的时空分异特征。研究发现:①2011年以来中国主要城市新型基础设施和人工智能产业链取得快速发展,在国家中心城市和城市群核心城市形成空间集聚;②城市“新基建”综合发展水平有效推动了人工智能产业链的发展,影响程度由高到低依次是下游应用层、中游技术层和上游基础层,推动效应随时间推移而强化;③城市“新基建”影响人工智能产业链发展的效应在空间上主要凸显于东部沿海地区和核心城市群,影响程度在城市群发展梯队之间的空间异质性超过东中西部三大地带之间的空间异质性,第一梯队城市群正成为城市“新基建”赋能人工智能产业链发展的重要空间载体。

关键词：新型基础设施新兴产业人工智能产业产业链城市群时空分异

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Identifying Spatial Heterogeneity in the Effects of High-Tech Firm Density on Housing Prices:Evidence from Guangdong-hong Kong-Macao Greater Bay Area,China

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Chinese Geographical Science 2023年第2期33卷 233-249页

作者： WANG Yang WU Kangmin zhang hong’ou LIU Yi YUE Xiaoli Faculty of Geography Yunnan Normal UniversityKunming 650500China Guangzhou Institute of Geography Guangdong Academy of SciencesGuangzhou 510070China Institute of Strategy Research for Guangdong Hong Kong and Macao Greater Bay AreaGuangzhou 510070China Key Laboratory of Regional Sustainable Development Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China School of Architecture and Urban Planning Guangdong University of TechnologyGuangzhou 510090China

Innovation capitalization is a new concept in innovation geography *** research on a city scale has proven that innovation is an important factor affecting housing prices and verified that innovation has a capitalization ***,few studies investigate the spatial heterogeneity of innovation ***,case verification at the urban agglomeration scale is ***,this study proposes a theoretical framework for the spatial heterogeneity of innovation capitalization at the urban agglomeration *** the Guangdong-hong Kong-Macao Greater Bay Area(GHMGBA),China as a case study,the study investigated the spatial heterogeneity of the influence of high-tech firms,representing innovation,on housing *** work verified the spatial heterogeneity of innovation *** study constructed a data set influencing housing prices,comprising 11 factors in 5 categories(high-tech firms,convenience of living facilities,built environment,the natural environment,and the fundamentals of the districts)for 419 subdistricts in the *** the global scale,the study finds that high-tech firms have a significant and positive influence on housing prices,with the housing price increasing by 0.0156%when high-tech firm density increases by 1%.Furthermore,a semi-geographically weighted regression(SGWR)analysis shows that the influence of high-tech firms on housing prices has spatial *** areas where high-tech firms have a significant and positive influence on housing prices are mainly in the GuangzhouFoshan metropolitan area,western Shenzhen-Dongguan,north-central Zhongshan-Nansha district,and Guangzhou—all areas with densely distributed high-tech *** results confirm the spatial heterogeneity of innovation capitalization and the need for further discussion of its scale and spatial *** study offers implications for relevant GHMGBA administrative authorities for spatially differentiated development strateg

关键词： innovation capitalization high-tech firms housing prices spatial heterogeneity semi-geographically weighted regression(SGWR) Guangdong-hong Kong-Macao Greater Bay Area(GHMGBA)

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The pattern,evolution,and mechanism of venture capital flows in the Guangdong-hong Kong-Macao Greater Bay Area,China

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Journal of Geographical Sciences 2022年第10期32卷 2085-2104页

作者： WU Kangmin WANG Yang zhang hong’ou LIU Yi YE Yuyao YUE Xiaoli Guangdong provincial Key Laboratory of Remote Sensing and Geographical Information System Guangzhou Institute of GeographyGuangdong Academy of SciencesGuangzhou 510070China Faculty of Geography Yunnan Normal UniversityKunming 650500China Institute of Strategy Research for Guangdong Hong Kong and Macao Greater Bay AreaGuangzhou 510070China Key Laboratory of Regional Sustainable Development Modeling Institute of Geographic Sciences and Natural Resources ResearchCASBeijing 100101China

As an important innovation flow,venture capital has been examined in urban network ***,the segmentation of capital categories and the cross-scale connection of capital remain scarcely *** study focuses on the structure and industry differentiation of venture capital flows in the Guangdong-hong Kong-Macao Greater Bay Area(GBA)and its cross-scale network *** on a venture capital database covering capital amount,investment subject address information,and industry information(2000-2018),this article examines the spatial distribution and network structure of venture capital in the GBA by means of a distance-based test of spatial concentration approach and social network *** findings show that:(1)Venture capital institutions and startups in the GBA present a high-concentration distribution *** the past 20 years,venture capital activities in the GBA have substantially increased,forming a complex urban network structure with Guangzhou,Shenzhen,and hong Kong as the core of this network.(2)Different types of venture capital show significantly different urban network structures,with manufacturing,the Internet industry,the financial sector,the cultural media industry,and the medical and health industry as the five industry types with the largest capital flow in the GBA.(3)Cross-scale research on the venture capital network reveals the position of the GBA as a capital hub in China,which forms a dense venture capital connection network with major cities on a national scale.(4)The network structure of venture capital in the GBA is influenced by multi-dimensional proximity,institutional factors,urban economy,and path *** with these three key mechanisms,the GBA has grown into a national-scale and even global-scale venture capital center.

关键词： venture capital Guangdong-hong Kong-Macao Greater Bay Area collaboration scale

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Dynamic features and driving mechanism of coal consumption for Guangdong province in China

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Journal of Geographical Sciences 2022年第3期32卷 401-420页

作者： WANG Changjian WANG Fei zhang Xinlin WANG Yang SU Yongxian YE Yuyao WU Qitao zhang hong’ou Guangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and ApplicationGuangzhou Institute of GeographyGuangdong Academy of SciencesGuangzhou 510070China Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou) Guangzhou 510070China School of Resources and Planning Guangzhou Xinhua UniversityGuangzhou 510520China School of Geography Geomatics and PlanningJiangsu Normal UniversityXuzhou 221116JiangsuChina

Guangdong Province,as one of China’s fast-developing regions,an important manufacturing base,and one of the national first round low-carbon pilots,still faces many challenges in controlling its total energy *** dominates Guangdong’s energy consumption and remains the major source of CO_(2).Previous research on factors influencing energy consumption has lacked a systematic analysis both from supply side(factors related to scale,structure,and technologies)and demand side(investment,consumption,and trade).This paper develops the logarithmic mean Divisia index(LMDI)method that focuses on the supply side and the structural decomposition analysis(SDA)method that focuses on the demand side to systematically identify the key factors driving coal consumption in *** are as follows:(1)Supply side analysis indicates that economic growth has always been the most important factor driving coal consumption growth,while energy intensity is the most important constraining *** structure and energy structure have different impacts on coal consumption control during different development phases.(2)Demand side analysis indicates that coal is consumed mainly for international exports,inter-provincial exports,fixed capital formation,and urban household.(3)Industries with the fastest coal consumption growth driven by final demand have experienced significant *** in industrial sectors were mainly driven by inter-provincial exports and urban household consumption in recent years.(4)Research on energy consumption in subnational regions under China’s new development pattern of“dual circulation”should not only focus on exports in the context of economic globalization but also pay more attention to inter-provincial exports on the background of strengthened interregional connections.

关键词： coal consumption Logarithmic mean Divisia index(LMDI) input-output analysis(IOA) structural decomposition analysis(SDA) supply-side and demand-side analysis

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Development of a convolutional neural network based geomechanical upscaling technique for heterogeneous geological reservoir

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第6期16卷 2111-2125页

作者： Zhiwei Ma Xiaoyan ou Bo zhang Earth and Environmental Sciences Division Los Alamos National LaboratoryLos AlamosUSA Civil and Environmental Engineering University of AlbertaEdmontonCanada

Geomechanical assessment using coupled reservoir-geomechanical simulation is becoming increasingly important for analyzing the potential geomechanical risks in subsurface geological ***,a robust and efficient geomechanical upscaling technique for heterogeneous geological reservoirs is lacking to advance the applications of three-dimensional(3D)reservoir-scale geomechanical simulation considering detailed geological ***,we develop convolutional neural network(CNN)proxies that reproduce the anisotropic nonlinear geomechanical response caused by lithological heterogeneity,and compute upscaled geomechanical properties from CNN *** CNN proxies are trained using a large dataset of randomly generated spatially correlated sand-shale realizations as inputs and simulation results of their macroscopic geomechanical response as *** trained CNN models can provide the upscaled shear strength(R^(2)>0.949),stress-strain behavior(R^(2)>0.925),and volumetric strain changes(R^(2)>0.958)that highly agree with the numerical simulation results while saving over two orders of magnitude of computational *** is a major advantage in computing the upscaled geomechanical properties directly from geological realizations without the need to perform local numerical simulations to obtain the geomechanical *** proposed CNN proxybased upscaling technique has the ability to(1)bridge the gap between the fine-scale geocellular models considering geological uncertainties and computationally efficient geomechanical models used to assess the geomechanical risks of large-scale subsurface development,and(2)improve the efficiency of numerical upscaling techniques that rely on local numerical simulations,leading to significantly increased computational time for uncertainty quantification using numerous geological realizations.

关键词： Upscaling Lithological heterogeneity Convolutional neural network(CNN) Anisotropic shear strength Nonlinear stressestrain behavior

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Entangled photons enabled ultrafast stimulated Raman spectroscopy for molecular dynamics

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Light(Science & Applications) 2024年第8期13卷 1615-1622页

作者： Jiahao Joel Fan Zhe-Yu ou Zhedong zhang Department of Physics City University of Hong KongKowloonHong Kong SARChina City University of hong Kong Shenzhen Research InstituteShenzhenGuangdongChina

Quantum entanglement has emerged as a great resource for studying the interactions between molecules and *** propose a new scheme of stimulated Raman scattering with entangled photons.A quantum ultrafast Raman spectroscopy is developed for condensed-phase molecules,to monitor the exciton populations and *** results are obtained,showing an entanglement-enabled time-frequency scale not attainable by classical *** Raman signal presents an unprecedented selectivity of molecular correlation functions,as a result of the hong-ou-Mandel *** work suggests a new paradigm of using an unconventional interferometer as part of spectroscopy,with the potential to unveil advanced information about complex materials.

关键词： materials. spectroscopy selectivity

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Alleviating the anisotropic microstructural change and boosting the lithium ions diffusion by grain orientation regulation for Ni-rich cathode materials

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Journal of Energy Chemistry 2024年第1期88卷 213-222,I0005页

作者： Xinyou He Shilin Su Bao zhang Zhiming Xiao Zibo zhang Xing ou Engineering Research Center of the Ministry of Education for Advanced Battery Materials School of Metallurgy and EnvironmentCentral South UniversityChangsha 410083HunanChina Zhejiang Power New Energy Co.Ltd Zhuji 311899ZhejiangChina

Generally,layered Ni-rich cathode materials exhibit the morphology of polycrystalline secondary sphere composed of numerous primary *** the arrangement of primary particles plays a very important role in the properties of Ni-rich *** disordered particle arrangement is harmful to the cyclic performance and structural stability,yet the fundamental understanding of disordered structure on the structural degradation behavior is ***,we have designed three kinds of LiNi_(0.83)Co_(0.06)Mn_(0.11)O_(2) cathode materials with different primary particle orientations by regulating the precursor coprecipitation *** finite element simulation and in-situ characterization,the Li^(+)transport and structure evolution behaviors of different materials are ***,the smooth Li^(+)diffusion minimizes the reaction heterogeneity,homogenizes the phase transition within grains,and mitigates the anisotropic microstructural change,thereby modulating the crack evolution ***,the optimized structure evolution ensures radial tight junctions of the primary particles,enabling enhanced Li^(+)diffusion during dynamic ***-loop bidirectional enhancement mechanism becomes critical for grain orientation regulation to stabilize the cyclic *** precursor engineering with particle orientation regulation provides the useful guidance for the structural design and feature enhancement of Ni-rich layered cathodes.

关键词： Ni-rich cathode Grain orientation regulation Anisotropic microstructural change Precursor engineering Li~+-ions diffusion

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