Creating a decarbonized economy: Decoupling effects and driving factors of CO2 emission of 28 industries in China

被引:2
作者
Luo, Gangfei [1 ]
Balezentis, Tomas [2 ]
Zeng, Shouzhen [1 ,3 ]
Pan, JiaShun [1 ,4 ]
机构
[1] Zhejiang Gongshang Univ, Coll Stat & Math, Hangzhou, Peoples R China
[2] Lithuanian Ctr Social Sci, Vilnius, Lithuania
[3] Ningbo Univ, Sch Business, Ningbo 315211, Peoples R China
[4] Hangzhou Engn Consulting Ctr Co Ltd, Hangzhou, Peoples R China
关键词
Carbon emission; LMDI; decoupling; driving factors; Chinese industry; MEAN DIVISIA INDEX; CARBON EMISSIONS; ENERGY-CONSUMPTION; DECOMPOSITION ANALYSIS; LMDI DECOMPOSITION; GROWTH; EFFICIENCY; COUNTRIES; SECTOR; IRON;
D O I
10.1177/0958305X221109603
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Identifying the carbon emission characteristics, driving factors, and decoupling status of the industrial subsectors is important for developing effective policy measures. This allows for implementing industrial emission reduction that, eventually, decouple carbon emission and economic growth. Such an analysis is especially important for the case of China on its way towards sustainable development and increasing global interrelationships. However, the literature still lacks comprehensive analysis, especially, at the industry level. This study uses the Logarithmic Mean Divisia Index and decoupling indicator to analyze how different factors contribute to CO2 emissions in 28 industries in China during 2002-2017. The results reveal that the growth of industrial CO2 emissions has been positive but decreasing. The highest CO2 emission change is observed for production and supply of electric and heat power, processing of petroleum, coking, and nuclear fuel, and smelting and pressing of metals. These sectors also show high carbon intensity levels. The economic output (scale) effect and population effect comprise the two major factors promoting the CO2 emission. The energy intensity effect is the key inhibiting factor of the industrial energy-related CO2 emission in China. The suppressive effects of energy and industrial structure have been continuously increasing. The economic growth and CO2 emission has been gradually decoupling in the case of the 28 sectors analyzed. Manufacture of cloths, leather, fur, feather, and related products as well as production and supply of gas exhibit a relatively stable strong decoupling. Based on the decoupling analysis, this study shows that energy intensity has induced the decoupling, whereas the opposite effect has occurred due to economic growth, and the other factors showed little effect on CO2 emission decoupling.
引用
收藏
页码:2413 / 2431
页数:19
相关论文
共 69 条
[1]   CO2 emissions of Turkish manufacturing industry: A decomposition analysis [J].
Akbostanci, Elif ;
Tunc, Gul Ipek ;
Turut-Asik, Serap .
APPLIED ENERGY, 2011, 88 (06) :2273-2278
[2]   Energy consumption, carbon emissions and economic growth nexus in Bangladesh: Cointegration and dynamic causality analysis [J].
Alam, Mohammad Jahangir ;
Begum, Ismat Ara ;
Buysse, Jeroen ;
Van Huylenbroeck, Guido .
ENERGY POLICY, 2012, 45 :217-225
[3]   Drivers in CO2 emissions variation: A decomposition analysis for 33 world countries [J].
Andreoni, Valeria ;
Galmarini, Stefano .
ENERGY, 2016, 103 :27-37
[4]   The LMDI approach to decomposition analysis: a practical guide [J].
Ang, BW .
ENERGY POLICY, 2005, 33 (07) :867-871
[5]  
Becken S., 2006, Journal of Sustainable Tourism, V14, P323, DOI 10.2167/jost547.0
[6]  
Birdsall N., 1992, Another look at population and global warming
[7]   An international comparison analysis of CO2 emissions in the construction industry [J].
Chen, Jindao ;
Wang, Yuhong ;
Shi, Qian ;
Peng, Xu ;
Zheng, Juhuan .
SUSTAINABLE DEVELOPMENT, 2021, 29 (04) :754-767
[8]   An empirical study on the CO2 emissions in the Chinese construction industry [J].
Chen, Jindao ;
Shen, Liyin ;
Song, Xiangnan ;
Shi, Qian ;
Li, Shengping .
JOURNAL OF CLEANER PRODUCTION, 2017, 168 :645-654
[9]   Logarithmic mean Divisia index (LMDI) decomposition of coal consumption in China based on the energy allocation diagram of coal flows [J].
Chong, ChinHao ;
Ma, Linwei ;
Li, Zheng ;
Ni, Weidou ;
Song, Shizhong .
ENERGY, 2015, 85 :366-378
[10]  
Chowdhury S., 2020, RES WORLD EC, V11, P196