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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Energyarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Energy
Article . 2020 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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A spatiotemporal investigation of energy-driven factors in China: A region-based structural decomposition analysis

Authors: Rongxiao He; Danfei Ni; Jingke Hong; He Huang; Xianzhu Wang;

A spatiotemporal investigation of energy-driven factors in China: A region-based structural decomposition analysis

Abstract

Abstract To achieve China′s mandatory energy conservation and emission reduction targets, it is necessary to examine the driving factors in the energy increase with the due consideration of regional disparities. This study develops a region-based structural decomposition analysis method to capture the spatial heterogeneity of driving factors between eastern, central, and western China from a temporal perspective. The results show that there is a clear declining trend both in the amount and growth rate of energy increase linked to the continuous decrease in the rate of national GDP growth. Historically, final demand was the largest driver of increased energy use during the whole period under investigation whilst the change in energy intensity and structural change are identified as the biggest contributors to reductions from 2007 to 2010 and from 2010 to 2012, respectively. From a spatial perspective, energy demands in eastern regions have grown most, followed by the western and central regions. The impacts of all driving factors were more local-dominant. The changes in production structure and final demand volumes generated the most significant spillover effects. The findings of this study enhance the understanding of dynamic evolution in energy-driven factors at the regional level, which is beneficial to making well-directed energy conservation policies by considering regional specificity.

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