Uncovering Variations, Determinants, and Disparities of Multisector-Level Final Energy Use of Industries Across Cities
With continuous industrialization and urbanization, cities have become the dominator of energy consumption, to which industry is making leading contribution among all sectors. Given the insufficiency in comparative study on the drivers of energy use across cities at multisector level, this study sel...
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doaj-1035345aac814c2fbb76b83862b0a5cf2020-11-24T21:21:52ZengMDPI AGSustainability2071-10502019-03-01116180610.3390/su11061806su11061806Uncovering Variations, Determinants, and Disparities of Multisector-Level Final Energy Use of Industries Across CitiesXianrui Liao0Wei Yang1Yichen Wang2Junnian Song3College of New Energy and Environment, Jilin University, Changchun 130012, ChinaCollege of New Energy and Environment, Jilin University, Changchun 130012, ChinaCollege of New Energy and Environment, Jilin University, Changchun 130012, ChinaCollege of New Energy and Environment, Jilin University, Changchun 130012, ChinaWith continuous industrialization and urbanization, cities have become the dominator of energy consumption, to which industry is making leading contribution among all sectors. Given the insufficiency in comparative study on the drivers of energy use across cities at multisector level, this study selected seven representative cities in China to quantify and analyze the contributions of factors to changes in final energy use (FEU) in industrial aggregate and sectoral levels by using Logarithmic Mean Divisia Index method. Disparities in the drivers of industrial FEU across cities were explicitly revealed within two stages (2005–2010 and 2010–2015). Some key findings are presented as follows. Alongside the increase in industrial output of seven cities within two stages, the variation trends in industrial FEU are different. Industrial output effect (contribution rate 16.7% ~ 184.0%) and energy intensity effect (contribution rate −8.6% ~ −76.5%) contributed to the increase in aggregate FEU positively and negatively, respectively. Beijing had the largest contribution share of industrial structure effect (−24.4% and −12.8%), followed by Shenyang and Xi’an. Contributions of energy intensity effect and industrial output effect for <i>Chemicals</i>, <i>Nonmetals</i>, <i>Metals</i>, and <i>Manufacture of equipment</i> were much larger than those of other sectors. The results revealed that production technological innovations, phase-out of outdated capacities of energy intensive industries, and industrial restructuring are crucial for reduction in industrial FEU of cities. This study also provided reference to reasonable industrial layout among cities and exertion of technological advantages from a national perspective.https://www.mdpi.com/2071-1050/11/6/1806Final energy useIndustrial sectorsLogarithmic Mean Divisia IndexDecomposition analysisCities |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xianrui Liao Wei Yang Yichen Wang Junnian Song |
spellingShingle |
Xianrui Liao Wei Yang Yichen Wang Junnian Song Uncovering Variations, Determinants, and Disparities of Multisector-Level Final Energy Use of Industries Across Cities Sustainability Final energy use Industrial sectors Logarithmic Mean Divisia Index Decomposition analysis Cities |
author_facet |
Xianrui Liao Wei Yang Yichen Wang Junnian Song |
author_sort |
Xianrui Liao |
title |
Uncovering Variations, Determinants, and Disparities of Multisector-Level Final Energy Use of Industries Across Cities |
title_short |
Uncovering Variations, Determinants, and Disparities of Multisector-Level Final Energy Use of Industries Across Cities |
title_full |
Uncovering Variations, Determinants, and Disparities of Multisector-Level Final Energy Use of Industries Across Cities |
title_fullStr |
Uncovering Variations, Determinants, and Disparities of Multisector-Level Final Energy Use of Industries Across Cities |
title_full_unstemmed |
Uncovering Variations, Determinants, and Disparities of Multisector-Level Final Energy Use of Industries Across Cities |
title_sort |
uncovering variations, determinants, and disparities of multisector-level final energy use of industries across cities |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2019-03-01 |
description |
With continuous industrialization and urbanization, cities have become the dominator of energy consumption, to which industry is making leading contribution among all sectors. Given the insufficiency in comparative study on the drivers of energy use across cities at multisector level, this study selected seven representative cities in China to quantify and analyze the contributions of factors to changes in final energy use (FEU) in industrial aggregate and sectoral levels by using Logarithmic Mean Divisia Index method. Disparities in the drivers of industrial FEU across cities were explicitly revealed within two stages (2005–2010 and 2010–2015). Some key findings are presented as follows. Alongside the increase in industrial output of seven cities within two stages, the variation trends in industrial FEU are different. Industrial output effect (contribution rate 16.7% ~ 184.0%) and energy intensity effect (contribution rate −8.6% ~ −76.5%) contributed to the increase in aggregate FEU positively and negatively, respectively. Beijing had the largest contribution share of industrial structure effect (−24.4% and −12.8%), followed by Shenyang and Xi’an. Contributions of energy intensity effect and industrial output effect for <i>Chemicals</i>, <i>Nonmetals</i>, <i>Metals</i>, and <i>Manufacture of equipment</i> were much larger than those of other sectors. The results revealed that production technological innovations, phase-out of outdated capacities of energy intensive industries, and industrial restructuring are crucial for reduction in industrial FEU of cities. This study also provided reference to reasonable industrial layout among cities and exertion of technological advantages from a national perspective. |
topic |
Final energy use Industrial sectors Logarithmic Mean Divisia Index Decomposition analysis Cities |
url |
https://www.mdpi.com/2071-1050/11/6/1806 |
work_keys_str_mv |
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