Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/103284
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dc.contributorDepartment of Building and Real Estate-
dc.creatorHong, Jen_US
dc.creatorGu, Jen_US
dc.creatorLiang, Xen_US
dc.creatorLiu, Gen_US
dc.creatorShen, GQen_US
dc.creatorTang, Men_US
dc.date.accessioned2023-12-11T00:32:54Z-
dc.date.available2023-12-11T00:32:54Z-
dc.identifier.issn0360-5442en_US
dc.identifier.urihttp://hdl.handle.net/10397/103284-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.rights© 2019 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Hong, J., Gu, J., Liang, X., Liu, G., Shen, G. Q., & Tang, M. (2019). Spatiotemporal investigation of energy network patterns of agglomeration economies in China: Province-level evidence. Energy, 187, 115998 is available at https://doi.org/10.1016/j.energy.2019.115998.en_US
dc.subjectAgglomeration economyen_US
dc.subjectChinaen_US
dc.subjectEmbodied energyen_US
dc.subjectSpatiotemporalen_US
dc.titleSpatiotemporal investigation of energy network patterns of agglomeration economies in China : province-level evidenceen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume187en_US
dc.identifier.doi10.1016/j.energy.2019.115998en_US
dcterms.abstractChina is currently in the fast track of urbanization and industrialization. This poses a series of challenges pertaining to environmental issues given the resultant boom in energy consumption and carbon emissions. To tackle these problems, this study explores the effects of economic agglomerations and geographic attributes on energy transmission patterns using multi-regional input-output model, complex network analysis, and exploratory spatial data analysis. The results show that Shandong, Jiangsu, and Zhejiang are the three leading regions with regard embodied energy consumption; they have distinct energy utilization models but can also provide instructive lessons for energy conservation at the provincial level. Energy interactions represent self-organizing agglomerative patterns, and the physical geographic clusters are highly consistent with the virtual administrative division of agglomeration economies. The in-depth investigation of major agglomerations has revealed that infrastructure construction remains a vital driver of local economies in developing areas, whereas more developed agglomeration economies have more balanced and service-oriented development. Bilateral connections in current major agglomeration economies have been enhanced, but multilateral connections are still rare. The findings of this study provide a bottom-up insight into the spatiotemporal effect on embodied energy system of China.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEnergy, 15 Nov. 2019, v. 187, 115998en_US
dcterms.isPartOfEnergyen_US
dcterms.issued2019-11-15-
dc.identifier.scopus2-s2.0-85071524332-
dc.identifier.eissn1873-6785en_US
dc.identifier.artn115998en_US
dc.description.validate202312 bcch-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberBRE-0473-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNatural Science Foundation of China; Chongqing Science and Technology Commission; Fundamental Research Funds for the Central Universitiesen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS24253398-
dc.description.oaCategoryGreen (AAM)en_US
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