Exports-driven primary energy requirements and the structural paths of Chinese regions

doi:10.1007/s11707-020-0822-4

Front. Earth Sci.

2020, Vol. 14

Issue (4) : 803-815 https://doi.org/10.1007/s11707-020-0822-4

RESEARCH ARTICLE

Exports-driven primary energy requirements and the structural paths of Chinese regions

Ying LIU¹, Xudong WU², Xudong SUN¹, Chenghe GUAN^3,⁴, Bo ZHANG^1,⁴(

), Xiaofang WU⁵(

)

¹. School of Management, China University of Mining & Technology (Beijing), Beijing 100083, China
². School of Economics, Peking University, Beijing 100871, China
³. New York University Shanghai, Shanghai 200122, China
⁴. Harvard China Project, School of Engineering and Applied Sciences, Harvard University, MA 02138, USA
⁵. Economics School, Zhongnan University of Economics and Law, Wuhan 430073, China

Download: PDF(2355 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

As the major primary energy importer in the world, China has engaged in considerable efforts to ensure energy security. However, little attention has been paid to China’s embodied primary energy exports. Separating the international export from regional final demand, this paper focuses on quantifying provincial primary energy requirement arising from China’s exports, and tracing its concrete interprovincial supply chains using multi-regional input-output analysis and structural path analysis. Results show that China’s embodied primary energy uses in exports (EEE) reached 633.01 Mtce in 2012, compared to 565.15 Mtce in 2007. Four fifths of the EEE were supplied through interprovincial trade. Eastern coastal provinces accounted for nearly 70% of the national total EEE, while their primary energy supply mainly sourced from the central and western provinces. Most interprovincial supply chain paths of embodied primary energy exports were traced to the coal mining sectors of Shanxi, Inner Mongolia and Shaanxi. Critical receiving sectors in the final export provinces were Chemical industry, Metallurgy, Electronic equipment, Textile and other manufacturing sectors. Important transmission sectors were Electricity and hot water production and supply and Petroleum refining, coking, etc. In view of the specific role of exports in primary energy requirements, provincial energy uses are largely dependent on its domestic trade position and degrees of industrial participation in the global economy. Managing critical industrial sectors and supply chain paths associated with the international exports provide new insights to ensure China’s energy security and to formulate targeted energy policies.

Keywords embodied energy multi-regional input-output analysis structural path analysis interregional supply chains China’s exports

Corresponding Author(s): Bo ZHANG,Xiaofang WU

Online First Date: 11 September 2020 Issue Date: 08 January 2021

Cite this article:

Ying LIU,Xudong WU,Xudong SUN, et al. Exports-driven primary energy requirements and the structural paths of Chinese regions[J]. Front. Earth Sci., 2020, 14(4): 803-815.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-020-0822-4
https://academic.hep.com.cn/fesci/EN/Y2020/V14/I4/803

Fig.1 Regional distribution of the embodied primary energy uses in exports: (a) EEE composition by primary energy type; (b) EEE composition by aggregated sector.

Fig.2 Embodied primary energy uses in interprovincial outflows and inflows induced by exports in terms of (a) energy type and (b) aggregated sector.

Fig.3 Exports-driven interprovincial transfers of embodied primary energy. Note: The circle has four different radii to distinguish the four areas. The color of the connecting line is consistent with the interprovincial exporter of embodied primary energy; the width of the connecting line indicates the amount of trading flows.

Fig.4 Sectoral embodied primary energy flows through the first four layers of the supply chains caused by exports. Note: The left-hand side of the map shows the primary energy input. The intermediate consumption attributions of each aggregated sector at

P L 1

P L 2

, and

P L 3

are indicated by the dark gray ‘flow’ linking back to the final production attribution. An element

D s t

presents direct primary energy inputs from sector

s

P L t

. An element

E s t

P L t

represents embodied primary energy uses in the output of sector

s

P L t

. The flows from

P L t

P L t − 1

(

E i j t → t − 1

) measure embodied primary energy uses in the output of sector

i

P L t

purchased by sector

j

P L t − 1

. The colorful flows on the right-hand side indicate the embodied primary energy uses of industrial sectors attributed to final export. Detailed sectoral information are provided in Table S2, according to the classification of 30 industrial sectors.

Fig.5 Net embodied primary energy transfers in interprovincial trade balance of 30 provincial regions in 2007 and 2012. Note: The size of the sphere represents the volume of provincial EEE in 2012. Tibet is excluded in this figure.

Fig.6 Typical patterns of embodied primary energy export in nine eastern coastal provincial regions in (a) 2007 and (b) 2012. Note: The 42 industrial sectors in the 2012 MRIO table are merged into 30 sectors (see Table S2), in order to keep consistency with the 2007 MRIO table (Tibet is not included in this table). Energy resources are extracted in the source sectors of the source provinces. The embodied primary energy uses are finally exported by the export provinces through their export sectors.

1	CEPY Editorial Board (2013). China Electric Power Yearbook 2013. Beijing: China Statistics Press (in Chinese)
2	B Chen, J S Li, X F Wu, M Y Han, L Zeng, Z Li, G Q Chen (2018). Global energy flows embodied in international trade: a combination of environmentally extended input–output analysis and complex network analysis. Appl Energy, 210: 98–107 https://doi.org/10.1016/j.apenergy.2017.10.113
3	G Q Chen, X D Wu, J Guo, J Meng, C Li (2019). Global overview for energy use of the world economy: household-consumption-based accounting based on the world input-output database (WIOD). Energy Econ, 81: 835–847 https://doi.org/10.1016/j.eneco.2019.05.019
4	G Q Chen, X F Wu (2017). Energy overview for globalized world economy: source, supply chain and sink. Renew Sustain Energy Rev, 69: 735–749 https://doi.org/10.1016/j.rser.2016.11.151
5	W Chen, S Wu, Y Lei, S Li (2017). Interprovincial transfer of embodied energy between the Jing-Jin-Ji area and other provinces in China: a quantification using interprovincial input-output model. Sci Total Environ, 584-585: 990–1003 https://doi.org/10.1016/j.scitotenv.2017.01.152 pmid: 28169031
6	Z M Chen, G Q Chen (2011). An overview of energy consumption of the globalized world economy. Energy Policy, 39(10): 5920–5928 https://doi.org/10.1016/j.enpol.2011.06.046
7	C Feng, X Tang, Y Jin, Y Guo, X Zhang (2019). Regional energy-water nexus based on structural path betweenness: a case study of Shanxi Province, China. Energy Policy, 127: 102–112 https://doi.org/10.1016/j.enpol.2018.12.002
8	C Gao, B Su, M Sun, X Zhang, Z Zhang (2018). Interprovincial transfer of embodied primary energy in China: a complex network approach. Appl Energy, 215: 792–807 https://doi.org/10.1016/j.apenergy.2018.02.075
9	J Guo, Z Zhang, L Meng (2012). China’s provincial CO2 emissions embodied in international and interprovincial trade. Energy Policy, 42: 486–497 https://doi.org/10.1016/j.enpol.2011.12.015
10	J Hawkins, C Ma, S Schilizzi, F Zhang (2015). Promises and pitfalls in environmentally extended input–output analysis for China: a survey of the literature. Energy Econ, 48: 81–88 https://doi.org/10.1016/j.eneco.2014.12.002
11	R Herendeen (1973). An Energy Input-output Matrix for the United States, 1963: User’s Guide. CAC document No. 69, University of Illinois
12	J Hong, Q Shen, F Xue (2016). A multi-regional structural path analysis of the energy supply chain in China’s construction industry. Energy Policy, 92: 56–68 https://doi.org/10.1016/j.enpol.2016.01.017
13	X Jiang, Q Zhang, H Zhao, G Geng, L Peng, D Guan, H Kan, H Huo, J Lin, M Brauer, R V Martin, K He (2015). Revealing the hidden health costs embodied in Chinese exports. Environ Sci Technol, 49(7): 4381–4388 https://doi.org/10.1021/es506121s pmid: 25751364
14	K Kanemoto, M Lenzen, G P Peters, D D Moran, A Geschke (2012). Frameworks for comparing emissions associated with production, consumption, and international trade. Environ Sci Technol, 46(1): 172–179 https://doi.org/10.1021/es202239t pmid: 22077096
15	M Lenzen (2016). Structural analyses of energy use and carbon emissions–an overview. Econ Syst Res, 28(2): 119–132 https://doi.org/10.1080/09535314.2016.1170991
16	B Liu, D Wang, Y Xu, C Liu, M Luther (2018a). Embodied energy consumption of the construction industry and its international trade using multi-regional input–output analysis. Energy Build, 173: 489–501 https://doi.org/10.1016/j.enbuild.2018.05.040
17	W D Liu, Z P Tang, M Y ( Han 2018b). The 2012 China Multi-Regional Input-Output Table of 31 Provincial Units. Beijing: China Statistics Press (in Chinese)
18	M Llop, X Ponce-Alifonso (2015). Identifying the role of final consumption in structural path analysis: an application to water uses. Ecol Econ, 109: 203–210 https://doi.org/10.1016/j.ecolecon.2014.11.011
19	B Meng, J Xue, K Feng, D Guan, X Fu (2013). China’s inter-regional spillover of carbon emissions and domestic supply chains. Energy Policy, 61: 1305–1321 https://doi.org/10.1016/j.enpol.2013.05.108
20	J Meng, J F Liu, Y Xu, S Tao (2015). Tracing primary PM2.5 emissions via Chinese supply chains. Environ Res Lett, 10(5): 054005 https://doi.org/10.1088/1748-9326/10/5/054005
21	A Nawab, G Liu, F Meng, Y Hao, Y Zhang, Y Hu, M Casazza (2019). Exploring urban energy-water nexus embodied in domestic and international trade: a case of Shanghai. J Clean Prod, 223: 522–535 https://doi.org/10.1016/j.jclepro.2019.03.119
22	National Bureau of Statistics of China (2015). China Energy Statistical Yearbook 2014. Beijing: China Statistics Press (in Chinese)
23	National Bureau of Statistics of China (2019). China Energy Statistical Yearbook 2018. Beijing: China Statistics Press (in Chinese)
24	W Nordhaus (2009). The economics of an integrated world oil market. In: Address Prepared for Annual Conference of Energy Information Agency, 2009, and the 2009 Meeting of International Energy Workshop
25	Y Oshita (2012). Identifying critical supply chain paths that drive changes in CO2 emissions. Energy Econ, 34(4): 1041–1050 https://doi.org/10.1016/j.eneco.2011.08.013
26	G P Peters (2008). From production-based to consumption-based national emission inventories. Ecol Econ, 65(1): 13–23 https://doi.org/10.1016/j.ecolecon.2007.10.014
27	G P Peters, J C Minx, C L Weber, O Edenhofer (2011). Growth in emission transfers via international trade from 1990 to 2008. Proc Natl Acad Sci USA, 108(21): 8903–8908 https://doi.org/10.1073/pnas.1006388108 pmid: 21518879
28	L Shao, Y Li, K Feng, J Meng, Y Shan, D Guan (2018). Carbon emission imbalances and the structural paths of Chinese regions. Appl Energy, 215: 396–404 https://doi.org/10.1016/j.apenergy.2018.01.090
29	A Skelton, D Guan, G P Peters, D Crawford-Brown (2011). Mapping flows of embodied emissions in the global production system. Environ Sci Technol, 45(24): 10516–10523 https://doi.org/10.1021/es202313e pmid: 22050071
30	B Su, B W Ang, Y Li (2019). Structural path and decomposition analysis of aggregate embodied energy and emission intensities. Energy Econ, 83: 345–360 https://doi.org/10.1016/j.eneco.2019.07.020
31	X Sun, J Li, H Qiao, B Zhang (2017). Energy implications of China’s regional development: new insights from multi-regional input-output analysis. Appl Energy, 196: 118–131 https://doi.org/10.1016/j.apenergy.2016.12.088
32	X Su, X Zhang (2016). A detailed analysis of the embodied energy and carbon emissions of steel-construction residential buildings in China. Energy Build, 119: 323–330 https://doi.org/10.1016/j.enbuild.2016.03.070
33	M Tang, J Hong, G Liu, G Q Shen (2019). Exploring energy flows embodied in China’s economy from the regional and sectoral perspectives via combination of multi-regional input-output analysis and a complex network approach. Energy, 170: 1191–1201 https://doi.org/10.1016/j.energy.2018.12.164
34	Z Tang, W Liu, P Gong (2015). The measurement of the spatial effects of Chinese regional carbon emissions caused by exports. J Geogr Sci, 25(11): 1328–1342 https://doi.org/10.1007/s11442-015-1237-0
35	X Tian, B Chen, Y Geng, S Zhong, C Gao, J Wilson, X Cui, Y Dou (2019). Energy footprint pathways of China. Energy, 180: 330–340 https://doi.org/10.1016/j.energy.2019.05.103
36	X Tang, B C Mclellan, B Zhang, S Snowden, M Höök (2016). Trade-off analysis between embodied energy exports and employment creation in China. J Clean Prod, 134: 310–319 https://doi.org/10.1016/j.jclepro.2015.08.122
37	Z Wang, L Wei, B Niu, Y Liu, G Bin (2017). Controlling embedded carbon emissions of sectors along the supply chains: a perspective of the power-of-pull approach. Appl Energy, 206: 1544–1551 https://doi.org/10.1016/j.apenergy.2017.09.108
38	C L Weber, G P Peters, D Guan, K Hubacek (2008). The contribution of Chinese exports to climate change. Energy Policy, 36(9): 3572–3577 https://doi.org/10.1016/j.enpol.2008.06.009
39	T Wiedmann (2009). A review of recent multi-region input–output models used for consumption-based emission and resource accounting. Ecol Econ, 69(2): 211–222 https://doi.org/10.1016/j.ecolecon.2009.08.026
40	X D Wu, J L Guo, M Y Han, G Q Chen (2018). An overview of arable land use for the world economy: from source to sink via the global supply chain. Land Use Policy, 76: 201–214 https://doi.org/10.1016/j.landusepol.2018.05.005
41	X D Wu, J L Guo, X Ji, G Q Chen (2019a). Energy use in world economy from household-consumption-based perspective. Energy Policy, 127: 287–298 https://doi.org/10.1016/j.enpol.2018.12.005
42	X D Wu, J L Guo, J Meng, G Q Chen (2019b). Energy use by globalized economy: total-consumption-based perspective via multi-region input-output accounting. Sci Total Environ, 662: 65–76 https://doi.org/10.1016/j.scitotenv.2019.01.108 pmid: 30690380
43	X F Wu, G Q Chen (2017). Energy use by Chinese economy: a systems cross-scale input-output analysis. Energy Policy, 108: 81–90 https://doi.org/10.1016/j.enpol.2017.05.048
44	X F Wu, G Q Chen (2018). Coal use embodied in globalized world economy: from source to sink through supply chain. Renew Sustain Energy Rev, 81(Part 1): 978–993 https://doi.org/10.1016/j.rser.2017.08.018
45	T Xu, G Yong, J Sarkis, S Zhong (2018). Trends and features of embodied flows associated with international trade based on bibliometric analysis. Resour Conserv Recycling, 131: 148–157 https://doi.org/10.1016/j.resconrec.2018.01.002
46	X Yang, W Zhang, J Fan, J Li, J Meng (2018). The temporal variation of SO2 emissions embodied in Chinese supply chains, 2002–2012. Environ Pollut, 241: 172–181 https://doi.org/10.1016/j.envpol.2018.05.052 pmid: 29804050
47	O Yuko (2012). Identifying critical supply chain paths that drive changes in CO2 emissions. Energy Econ, 34(4): 1041–1050 https://doi.org/10.1016/j.eneco.2011.08.013
48	B Zhang, Z M Chen, X H Xia, X Y Xu, Y B Chen (2013). The impact of domestic trade on China’s regional energy uses: a multi-regional input–output modeling. Energy Policy, 63: 1169–1181 https://doi.org/10.1016/j.enpol.2013.08.062
49	B Zhang, S Guan, X Wu, X Zhao (2018a). Tracing natural resource uses via China’s supply chains. J Clean Prod, 196: 880–888 https://doi.org/10.1016/j.jclepro.2018.06.109
50	B Zhang, H Qiao, B Chen (2015). Embodied energy uses by China’s four municipalities: a study based on multi-regional input–output model. Ecol Modell, 318: 138–149 https://doi.org/10.1016/j.ecolmodel.2014.10.007
51	B Zhang, H Qiao, Z M Chen, B Chen (2016). Growth in embodied energy transfers via China’s domestic trade: evidence from multi-regional input–output analysis. Appl Energy, 184: 1093–1105 https://doi.org/10.1016/j.apenergy.2015.09.076
52	B Zhang, X Qu, J Meng, X Sun (2017). Identifying primary energy requirements in structural path analysis: a case study of China 2012. Appl Energy, 191: 425–435 https://doi.org/10.1016/j.apenergy.2017.01.066
53	Q Zhang, J Nakatani, Y Shan, Y Moriguchi (2019). Inter-regional spillover of China’s sulfur dioxide (SO2) pollution across the supply chains. J Clean Prod, 207: 418–431 https://doi.org/10.1016/j.jclepro.2018.09.259
54	W Zhang, F Wang, K Hubacek, Y Liu, J Wang, K Feng, L Jiang, H Jiang, B Zhang, J Bi (2018b). Unequal exchange of air pollution and economic benefits embodied in China’s exports. Environ Sci Technol, 52(7): 3888–3898 https://doi.org/10.1021/acs.est.7b05651 pmid: 29498268
55	H Zhao, Q Zhang, H Huo, J Lin, Z Liu, H Wang, D Guan, K He (2016). Environment-economy tradeoff for Beijing–Tianjin–Hebei’s exports. Appl Energy, 184: 926–935 https://doi.org/10.1016/j.apenergy.2016.04.038
56	G Zhao, C Gao, R Xie, M Lai, L Yang (2019). Provincial water footprint in China and its critical path. Ecol Indic, 105: 634–644 https://doi.org/10.1016/j.ecolind.2018.06.058
57	N Zhao, L Xu, A Malik, X Song, Y Wang (2018). Inter-provincial trade driving energy consumption in China. Resour Conserv Recycling, 134: 329–335 https://doi.org/10.1016/j.resconrec.2017.09.009

[1]

Download

[1]	Jing MING, Xiawei LIAO, Xu ZHAO. Grey water footprint for global energy demands[J]. Front. Earth Sci., 2020, 14(1): 201-208.
[2]	Bo ZHANG,Z. M. CHEN,L. ZENG,H. QIAO,B. CHEN. Demand-driven water withdrawals by Chinese industry: a multi-regional input-output analysis[J]. Front. Earth Sci., 2016, 10(1): 13-28.
[3]	Xi JI, Zhanming CHEN, Jinkai LI. Embodied energy consumption and carbon emissions evaluation for urban industrial structure optimization[J]. Front Earth Sci, 2014, 8(1): 32-43.

Viewed

Full text

Abstract

Cited

Shared

Discussed