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

doi:10.1007/s11442-022-1954-0

地理学报(英文版) ›› 2022, Vol. 32 ›› Issue (3): 401-420.doi: 10.1007/s11442-022-1954-0

收稿日期:2020-12-13 接受日期:2021-10-18 出版日期:2022-03-25 发布日期:2022-05-25

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

WANG Changjian¹^,²(), WANG Fei³^,^*(), ZHANG Xinlin⁴, WANG Yang¹, SU Yongxian¹, YE Yuyao¹, WU Qitao¹, ZHANG Hong’ou¹

1. Guangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China
2. Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 510070, China
3. School of Resources and Planning, Guangzhou Xinhua University, Guangzhou 510520, China
4. School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, Jiangsu, China

Received:2020-12-13 Accepted:2021-10-18 Online:2022-03-25 Published:2022-05-25
Contact: WANG Fei E-mail:wwwangcj@126.com;wangfei09@mails.ucas.ac.cn
About author:Wang Changjian (1986-), Associate Professor, specialized in economic geography and sustainability. E-mail: wwwangcj@126.com
Supported by:
National Key Research and Development Program(2019YFB2103101);Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)(GML2019ZD0301);GDAS Special Project of Science and Technology Development(2020GDASYL-20200102002);GDAS Special Project of Science and Technology Development(2020GDASYL-20200301003);National Natural Science Foundation of China(41501144)

摘要/Abstract

Abstract:

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 consumption. Coal dominates Guangdong’s energy consumption and remains the major source of CO₂. 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 Guangdong. Results 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 factor. Industrial 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 shifts. Increments 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.

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

. [J]. 地理学报(英文版), 2022, 32(3): 401-420.

WANG Changjian, WANG Fei, ZHANG Xinlin, WANG Yang, SU Yongxian, YE Yuyao, WU Qitao, ZHANG Hong’ou. Dynamic features and driving mechanism of coal consumption for Guangdong province in China[J]. Journal of Geographical Sciences, 2022, 32(3): 401-420.

图/表 9

References	Periods	Methodology	Area	Factors
(Michieka and Fletcher, 2012)	1971-2009	VAR	China	Urban population, per capita GDP
(Li and Leung, 2012)	1985-2008	Panel data	China	GDP
(Bloch et al., 2012)	1965-2008	VEC	China	GDP, labor, capital, income, coal price
(Lin et al., 2012)	1995-2008	Gaussian curves	China	Energy structure, carbon intensity, energy security
(Bhattacharya et al., 2015)	1978-2010	ADL	China	Coal technology
(Chong et al., 2015)	2001-2011	LMDI	China	Population, per capita GDP, energy intensity, energy structure
(Wu and Zhang, 2016)	1997-2012	IO	China	Domestic demand, foreign trade and industrial upgrading
(Zhang et al., 2018a)	2012	IO	China	Coal flow, coal industry
(Wu and Chen, 2018)	2012	MRIO	China	Exports and imports
(Zhang et al., 2018b)	1991-2013	LMDI	China	Population, per capita GDP, energy intensity, energy structure
(Wang et al., 2018)	1981-2015	PSO	China	Economic growth, energy structure, investment, and industrial structure
(Qiao et al., 2019)	2000-2016	EKC	China’s 30 provinces	Urbanization, per capita GDP, trade
(Liu et al., 2017)	2012	IO	China’s 3 regions	Coal flow, coal industry
(Tang et al., 2018)	1997-2014	LMDI, IO	China	Economic scale, industrial structure, energy intensity, energy mix, trade
(Chen et al., 2019)	1997-2012	IO	China	Fixed capital formation, household consumption, export
(Wang and Feng, 2018)	2000-2014	LMDI	China	Energy structure, energy intensity, industrial structure, industrial scale
(Chen et al., 2018)	2000-2015	LMDI	China	Per capita income, population, energy intensity, energy structure
(Chai et al., 2019)	1980-2016	LMDI	China	Per capita GDP, industrial structure, energy intensity, energy structure
(Ou et al., 2019)	2003-2016	LMDI	China’s 30 provinces	Population, per capita GDP, energy intensity, industrial structure, energy structure
(Liu et al., 2020)	2002-2017	IO	China	Fixed capital formation, coal intensity, production structure, commodity structure

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		Intermediate use	Final demands				Imports	Inter-provincial import	Total outputs
		1, 2, …, n	Consumption	Fixed capital formation	Exports	Inter-provincial export	Imports	Inter-provincial import	Total outputs
Intermediate inputs	1	X_ij	Y_i						X_i
	2
	…
	n
Value added		V_j
Total inputs		X_j
Coal consumption	1	C_kj	C_ky						C_k
	2
	…
	m

Code	Sector	Code	Sector
1	Agriculture	11	Metal products
2	Mining	12	General and specialized equipment
3	Foods and tobacco	13	Transportation equipment
4	Textiles	14	Electrical equipment
5	Wood products	15	Electronic equipment
6	Paper and printing	16	Other manufacturing industry
7	Petroleum processing and coking	17	Electricity, gas, water
8	Chemicals	18	Construction
9	Non-metallic mineral processing	19	Transportation
10	Metal smelting and rolling processing	20	Wholesale, retail, other service

	p	g	f₁	f₂	f₃	ΔC
2002-2005	2.2363	21.1358	-0.0712	5.6522	-0.0499	22.2857
2005-2007	2.1161	19.4111	-0.0731	0.1331	0.0119	17.0139
2007-2010	9.4406	20.0416	-0.0385	-1.1803	0.0145	17.3109
2010-2012	1.5986	17.7699	-0.0042	-3.8635	0.0238	12.9679
2012-2015	2.6988	23.7756	-0.0457	-6.6315	0.0436	-5.9335
2015-2017	3.2859	13.1229	-0.0303	-8.0687	0.0476	5.0595
	e₁	e₂	e₃	s₁	s₂	s₃
2002-2005	0.0158	-3.3961	0.0837	0.0162	-3.0999	-0.2372
2005-2007	-0.0854	-3.0555	-0.0792	-0.0511	-1.1306	-0.1835
2007-2010	0.1804	-8.7134	-0.0625	-0.2384	-2.0600	-0.0729
2010-2012	-0.3179	-10.5714	-0.0443	0.2571	8.2039	-0.0842
2012-2015	-0.0207	-20.0856	-0.1277	-0.0437	-5.5051	0.0086
2015-2017	0.0024	-5.0596	-0.0499	-0.0279	1.8896	-0.0524

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

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