Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input–output analysis

Applied Energy xxx (2015) xxx–xxx

Contents lists available at ScienceDirect

Applied Energy journal homepage: www.elsevier.com/locate/apenergy

Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input–output analysis B. Zhang a,b, H. Qiao c,⇑, Z.M. Chen d, B. Chen e,f,⇑ a

School of Management, China University of Mining & Technology (Beijing), Beijing 100083, PR China State Key Laboratory of Coal Resources and Safe Mining, China University of Mining & Technology (Beijing), Beijing 100083, PR China c School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, PR China d School of Economics, Renmin University of China, Beijing 100872, PR China e State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, PR China f NAAM Group, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia b

h i g h l i g h t s
China had significant growth of embodied energy transfers via domestic trade.
Interregional trade of total embodied energy uses tripled between 2002 and 2007.
The temporal and spatial changes of regional energy use inventories were revealed.
Increasing complexities of China’s domestic supply chains were identified.

a r t i c l e

i n f o

Article history: Received 22 June 2015 Received in revised form 9 September 2015 Accepted 10 September 2015 Available online xxxx Keywords: Embodied energy transfer Domestic trade Multi-regional input–output analysis Regional China

a b s t r a c t This paper investigates the temporal and spatial changes of embodied energy transfers via China’s domestic trade over 2002–2007 based on the multi-regional input–output models. Interregional trade of total embodied energy uses approximately tripled between 2002 and 2007, and the total trade volumes in it were equivalent to 38.2% of the national total direct primary energy input in 2002 and 62.9% of that in 2007, respectively. Among all the eight regions, Northwest, Central, Northeast and Southwest were the interregional net exporters and deficit receivers of embodied energy in contrast to East Coast, South Coast, North Coast and Beijing–Tianjin as interregional net importers and surplus receivers. Significant growth of net embodied energy transfers can be identified from central and western inland regions to eastern coastal regions, and the Central region partly served as a ‘‘transmission channel”. By considering the interregional embodied energy transfers, regional energy use inventories changed largely, and the spatial and temporal differences between 2002 and 2007 were expanding. Industrial positions in domestic and global supply chains and inherent economic driving factors such as increasing regional consumption level, accelerated investment in fixed assets and rapidly expanding export were the major driving forces for the embodied energy transfers among regions. To form a set of useful tool for controlling energy consumption and achieving the goals for energy saving and emission reduction, China’s governors at all levels deserve to understand the relationships between energy producers and users from the view of demand-driven energy requirements. Ó 2015 Elsevier Ltd. All rights reserved.

1. Introduction As the world’s top primary energy consumer, China’s demands for energy resources continue to increase along with its rapid economic development. Although traditional energy policy ⇑ Corresponding authors at: School of Environment, Beijing Normal University, Beijing 100875, PR China. Tel./fax: +86 10 58807368 (B. Chen). E-mail addresses: [email protected] (H. Qiao), [email protected] (B. Chen).

schemes in China aimed at alleviating energy resource shortage focus on the development of domestic energy supply over the energy safety [1], the governments at various levels have a greater pressure to control vastly growing energy consumption and deal with negative environmental effects such as air pollution [2,3] and greenhouse gas emissions [3–5]. In 2011, the Chinese government assigned the energy intensity reduction goal of 16% in the 12th Five-Year Plan (2011–2015) to respond to the challenge of ensuring continuous growth of GDP at a high speed and

http://dx.doi.org/10.1016/j.apenergy.2015.09.076 0306-2619/Ó 2015 Elsevier Ltd. All rights reserved.

Please cite this article in press as: Zhang B et al. Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input– output analysis. Appl Energy (2015), http://dx.doi.org/10.1016/j.apenergy.2015.09.076

2

B. Zhang et al. / Applied Energy xxx (2015) xxx–xxx

achieving the reduction of energy consumption. Meanwhile, the reduction targets of CO2 emission intensity and major pollutant emissions such as SO2 were also assigned in this Plan. In 2013, the State Council announced that China will keep the total energy consumption below 4 billion tce in 2015. Recently, the State Council set forth a new target in the Energy Development Strategy Action Plan (2014–2020) that China will cap primary energy consumption at 4.8 billion tce by 2020 [6]. As a vast country, the national targets of China generally will be allocated down to 31 provincial authorities by requiring the regional targets correspondingly [7], considering the fact that substantial regional variations exist in physical geography, economic development, infrastructure, population scale and density, resident income level and lifestyle, and environmental resource condition across regions within China [8,9]. Since there are fewer barriers to trade between the regions than to trade between countries [10], the regions with high urbanization and industrialization level have tended to purchase much more final goods or services rather than produce them locally. In other words, China’s interregional goods trades are always associated with energy in domestic supply chains. Large interregional trade transfers of direct or indirect energy uses not only can help to distribute uneven endowments of energy resources among different regions, but also lead to great gaps between regions in terms of energy production and consumption. The implementation of regional end-reduction oriented energy policies may accelerate interregional direct or indirect energy transfers [11] and exacerbate related environmental problems such as carbon leakage [10,12,13], along with the rapid expansion of domestic trade in China. The concept of embodied energy originates from the theory of systems ecology [14,15]. Embodied energy use or demand-driven energy requirement is defined as the total primary energy input to satisfy final demand, i.e., the direct plus indirect energy resources input through the production processes to produce the goods used for final demand [16,17]. When direct primary energy input indicates the physical energy resource supply for production, embodied energy use reflects the direct and indirect energy requirements throughout the whole supply chain to satisfy different final demand categories [11,18]. Based on the input–output analysis methods [19], scholars have carried out a large number of input–output analyses regarding energy embodiments in the global, national and regional economic activities by considering the inter-industry linkages between energy producers and energy users [16–18,20–24]. Given the multi-regional input–output (MRIO) model can present the interactions among industrial sectors within an economy and the spatial linkage of industries between any two regions in the system, MRIO analysis has been widely used in analyzing the embodiments of resource uses and environmental emissions in certain economic activities [25–29]. Some studies have applied China’s MRIO models to reflect the impacts of international and interregional trade on regional ecological footprint [30,31], water footprint and virtual water uses [32–36], embodied energy uses [11,37], and consumption-based emissions of air pollutants [38– 40] and greenhouse gases [10,12,13,41–51]. For instance, Meng et al. [13] explained the relationship between China’s interregional spillover of energy-related CO2 emissions and domestic supply chains in 2002–2007. Zhang et al. [46] showed the trends and disparities of consumption-based CO2 emissions from China’s provincial regions over 2002–2007. Tian et al. [44] also used the MRIO analysis method to study China’s carbon footprint over 1997– 2007. Prior studies have contributed to support the provinciallevel policy-making processes such as the allocation of national emission reduction targets to the various provinces. Since the MRIO model can identify how much of a region’s primary energy inputs are created by its partner region’s final demands, Zhang

et al. [11] have conducted a MRIO study on the impact of domestic trade on China’s regional energy uses for the year 2007. However, systematic analyses of the temporal and spatial variations of the energy uses embodied in China’s domestic trade have not been conducted. The aim of this paper is to present a MRIO analysis of China’s interregional embodied energy transfers via domestic trade in 2002 and 2007 by using the recently available MRIO tables. The MRIO modeling can not only explain how primary energy inputs are created and distributed across regions, but also reveal the trends and disparities of regional energy use inventories considering interregional embodied energy transfers. Such analyses can identify regional energy use features and corresponding driving factors of embodied energy transfers to reflect the position and participation degree of different regions in domestic supply chains, and provide new insights for allocating regional responsibility for China’s energy demands in consideration of regional socioeconomic diversity and complexity. This paper is organized as follows. The next section introduces the methodology for MRIO analysis employed in the study and the data used. Section 3 presents the results of MRIO modeling for China’s interregional embodied energy transfers in 2002– 2007. Section 4 examines the relationships between China’s regional embodied energy uses and the increasing complexity of domestic supply chains in connection with the impacts of interregional trade, and discusses several key policy implications from our analysis. Main conclusions will be drawn in the ending section. 2. Material and methods 2.1. Introduction for the MRIO tables Following the methodological, data and institutional development, several MRIO tables for China have been published in recent years. China State Information Center of China [52] compiled a MRIO table for the year 1997 in China, which is classified into 8 regions and 30 industries. Ichimura and Wang [53] estimated a MRIO table with 7 regions and 9 sectors for the year 1987 in China. Shi and Zhang [54] compiled a MRIO table for the year 2002 in China, which is a competitive MRIO model with 30 provinces and 21 sectors covered. Liu and his fellows [55] finished a MRIO table for the year 2007 in China, which is classified into 30 province s and 30 industries. For the time-series research, Zhang and Qi [56] provided the 2002 and 2007 MRIO tables for China, which are the most recently available MRIO tables in China covering two different years. In this study, the two MRIO tables are adopted directly. It should be noted that, in these MRIO tables, the 30 provinces of Mainland China (Tibet is not included for lack of data) were integrated into 8 regions, i.e., Northeast, Beijing–Tianjin, North, Central, East Coast, South Coast, Northwest and Southwest (also see Fig. 1). The eight-region classification can relatively reflect the similarity of economic structure and spatial location of different provinces. Given the original MRIO tables have differentiated domestically produced goods from imported ones in the model to present the interregional trade dependency within China, the international imports item has been removed to focus on the domestic interregional connection. The format of revised MRIO table is shown in Table 1, with the economic sector classifications of 17 sectors. Detailed sectoral and regional information in the two MRIO tables are listed in Tables A1 and A2. 2.2. Mathematic forms of MRIO model and energy embodiment For the revised MRIO table (see Table 1), the basic row balance can be expressed as

Please cite this article in press as: Zhang B et al. Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input– output analysis. Appl Energy (2015), http://dx.doi.org/10.1016/j.apenergy.2015.09.076

3

B. Zhang et al. / Applied Energy xxx (2015) xxx–xxx

(a) EEIB in 2002 (Unit: Mtce)

Northeast

14

BeijingTianjin

10

23

Northwest

10

20 13

North Coast

18

12 27

48

East Coast

Central 39 12

Southwest

South Coast

(b) EEIB in 2007 (Unit: Mtce) 18

BeijingTianjin

Northeast

20

21

34

67

Northwest

12

North Coast

72

104

48

18

154

East Coast

Central

46

26

163

Southwest 20

33

40

South Coast

86

Fig. 1. Regional division of Mainland China and main net embodied energy flows in domestic trade. (Note: Only the embodied energy flows larger than 10 Mtce are presented.)

Please cite this article in press as: Zhang B et al. Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input– output analysis. Appl Energy (2015), http://dx.doi.org/10.1016/j.apenergy.2015.09.076

4

B. Zhang et al. / Applied Energy xxx (2015) xxx–xxx

Table 1 The format of revised MRIO table. Input

Output

Intermediate use

Final use

Northeast (R1) ...

Sector 1 Northeast (R1)

Sector 1 ... Sector 17 ... Sector 1 ... Sector 17

... Southwest (R8)

Direct primary energy input

xif ¼

...

Southwest (R8)

...

Sector 1

...

Sector 17

zfs ij

Northeast (R1) Consumption

...

Southwest (R8)

...

Consumption

Export

Others

eif

oif

Investment

fs

dit

8 X 17 8 X 2 X X f ;s zfi;j;s þ di;t þ eif þ oif

xif

Introduce the following denotations,

s¼1 t¼1

ð1Þ

8 X 17 X zfi;j;s þ pif s¼1 j¼1

where xif represents the total output of sector i in region f; zfi;j;s represents the intermediate use of sector j in region s supplied by secf ;s

tor i in region f. di;t represents the final use including consumption (rural household consumption, urban household consumption and government consumption) (t = 1) and investment (gross fixed capital formation and changes in inventories) (t = 2) of region s supplied by sector i in region f;

eif

pif is the total final use supplied by sector i in region f. Each sector in each regional economy links with the environment and the economy via exploiting direct primary energy inputs (extracting energy resources), importing embodied energy inputs (purchasing commodities), and exporting embodied energy inputs (selling commodities). By considering the energy uses embodied in both consumer goods and intermediate products [11,17,18], the total energy balance of sector i in region f with Eq. (1) can be formulated as 8 X 17 X

8 X 17 X

s¼1 j¼1

s¼1 j¼1

esj  zfj;i;s ¼

20

þe  f i

eif  zfi;j;s þ ¼

20

e  f i

zfi;j;s

þe  f i

z1;1 1;1

6B 6B . 6B . 6@ . 6 6 1;1 6 z1;17 6 6 Z ¼ 6 6 60 6 1;8 6 z1;1 6B 6B 6 B .. 6@ . 4 1;8 z1;17

eif  dfi;t;s þ eif  eif

8 X 17 X

13

20

13 c11 B C7 6B 7 6 B .. C 6@ . C A7 7 6 7 6 6 c117 7 7 6 7 6 .. 7; C ¼ 6 7 6 60 . 17 6 c8 7 7 6 6B 1 C7 6B . C7 6 B .. C 7 4@ A5

e817

8 X 2 X

c817 

z1;1 17;1

..

.. .

.

1

0

C C C  A

B B . B .. @

   z1;1 17;17 .. . 

z1;8 17;1

..

.. .

.

   z1;8 17;17

z8;1 1;1

8;1 z1;17

1

..

.

C C C  A

0

z8;8 1;1 B B . B .. @ 8;8 z1;17



z8;1 17;1

..

.. .

13

C7 C7 C7 . A7 7 7 8;1    z17;17 7 7 7 .. 7; 7 . 17 7    z8;8 7 17;1 C7 7 .. .. C 7 . . C A7 5    z8;8 17;17

and

s¼1 t¼1

oif

e11

C7 6B .. C 6B C7 7 6B 6@ . A7 7 6 1 6 e17 7 7 6 7 6 .. 7; E ¼ 6 7 6 60 . 17 6 e8 7 7 6 6B 1 C7 6B . C7 6 B .. C 7 4@ A5

represents the exports from sector i in

region f; oif is the other balance items of sector i in region f; and

cif þ

Investment

cif

s¼1 j¼1

¼

Sector 17

Total output

pif

s¼1 j¼1

ð2Þ where cif is the direct primary energy input (DEI) into sector i in region f; esj is the embodied energy use intensity of output from sector j in region s; zfj;i;s denotes the intermediate input from sector j in region s; and eif denotes the embodied energy use intensity of output from sector i in region f. For the whole system in terms of all regional economy with 136 entries, we have

8 P P P8 P17 1 1;s 1;s s 1 1 > c1 þ 8s¼1 17 > j¼1 ej  zj;1 ¼ s¼1 j¼1 e1  z1;j þ e1  p1 > 1 > P P P P > 8 17 8 17 1;s > 1 1 1 < c12 þ s¼1 j¼1 esj  z1;s s¼1 j¼1 e2  z2;j þ e2  p2 j;2 ¼ > > > > > > :

c817 þ

P8 P17 s¼1

.. .

e  z8;s j;17 ¼

s j¼1 j

P8 P17 s¼1

8 8 e  z8;s 17;j þ e17  p17

8 j¼1 17

ð3Þ

Then the above simultaneous equations can be expressed in a compressed matrix form of

C  þ Z   E ¼ X  E

ð4Þ

Please cite this article in press as: Zhang B et al. Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input– output analysis. Appl Energy (2015), http://dx.doi.org/10.1016/j.apenergy.2015.09.076

B. Zhang et al. / Applied Energy xxx (2015) xxx–xxx

Introduce C, Z, and E as the transposes of C  , Z  , and E , then Eq. (4) can be transformed into

E ¼ CðX  ZÞ1

ð5Þ cif ,

To get the value of E, the elements of C, i.e., can be extracted from the direct primary energy input of sector i in region f; the elements of Z, i.e., zfi;j;s , can be extracted from the whole economic intermediate input–output table; and the elements of X, i.e., P8 P17 f ;s f s¼1 j¼1 zi;j þ pi , can be calculated based on the data extracted from the economic intermediate and final demand input–output tables. Thereafter concrete analysis can be processed in terms of embodied energy flows in final demand and interregional trade, on basis of the data foundation of monetary transactions of goods and services across not only different sectors but also different regions. The embodied energy use (EEU) induced by total final demand or each category of it, such as consumption, can be calculated by multiplying the embodied energy use intensity matrix E by the corresponding final-use vector. The energy use embodied in interregional trade measures a region’s primary energy input caused by other regions’ final demands through interregional trade outflows in domestic supply chains or one region’s energy demand spillover to other regions in the process of domestic trade inflows. For the calculation of energy uses embodied in interregional trade, we resort to the method provided in Meng et al. [13] and Zhang et al. [37], in which the interregional trade in intermediate goods and services is treated as endogenous variables. For instance, the total primary energy use embodied in interregional trade outflows (EEIO) of Region 1 (Northeast) can be express as 1

1

EEIO ¼ C ðX  ZÞ

1

8 X 2 X s dt þ es þ os

!

s¼2 t¼1 8 X ¼ EEIT 1;s ;

ðs – 1Þ

ð6Þ

s¼2

C 1 ¼ ½ðc11 ; . . . ; c117 Þ; ð0; . . . ; 0Þ; . . . ; ð0; . . . ; 0Þ; 2

1;2

1;2

2;2

2;2

8;2

8;2

dt ¼ ½ðd1;t    d17;t Þ; ðd1;t    d17;t Þ; . . . ; ðd1;t    d17;t Þ;

ðs ¼ 2Þ;

e2 ¼ ½ð0; . . . ; 0Þ; ðe21 ; . . . ; e217 Þ; ð0; . . . ; 0Þ; . . . ; ð0; . . . ; 0Þ;

ðs ¼ 2Þ;

o2 ¼ ½ð0; . . . ; 0Þ; ðo21 ; . . . ; o217 Þ; ð0; . . . ; 0Þ; . . . ; ð0; . . . ; 0Þ;

ðs ¼ 2Þ;

where EEIO1 is the total energy use embodied in interregional outflows of Region 1; ðc11 ; . . . c117 Þ in C 1 is the 1  17 row vector of s primary energy input by sector for Region 1; dt represents the 1;2

1;2

2

domestic final consumption of region s, and ðd1;1 ; . . . ; d17;1 Þ in dt 2 dt )

(the transposes of is the 1  17 row vector representing the consumption (t = 1) in Region 2’s final demand supplied by Region 1; ðe21 ; . . . ; e217 Þ in e2 is the 1  17 row vector representing the exports of Region 2; ðo21 ; . . . ; o217 Þ in o2 is the 1  17 row vector representing the other balance items of Region 2; and EEIT 1;s is the interregional transfer of embodied energy flows from Region 1 to Region s (s – 1) (in other words, the primary energy input in Region 1 caused by the final demand in terms of consumption, investment, exports and others in region s). Therefore, the primary energy input in Region 1 caused by the final demand in other regions can be identified. The total primary energy use embodied in interregional inflows (EEII) of Region 1 can be expressed as

EEII1 ¼

8 X EEIT s1 s¼2

ð7Þ

5

where EEII1 is the total energy use embodied in interregional inflows of Region 1; and EEIT s1 is the interregional transfer of embodied energy flows from Region s (s – 1) to Region 1. The EEIO and EEII indicators can avoid double counting in measuring bilateral trade balance and associated energy uses across regions, since the intermediate products may flow through a region’s borders multiple times to produce final products [13]. It is worthy of noting that the total EEII is equal to the total EEIO at the national level. The interregional net transfer of embodied energy in domestic trade balance (EEIB) can be determined according to the difference between EEIO and EEII, which represents the primary energy input in each region to produce interregional exported goods and services minus the energy input in other regions to produce interregional imported goods and services. The regions with positive EEIBs are deficit receivers of embodied energy from interregional trade, while those with negative EEIBs are identified as surplus receivers. The concerned regional EEIB can also be served as an indicator to measure the difference between regional DEI and EEU [11]. Similarly, the sectoral EEIO and EEII can be calculated according to interregional transfers of sectoral embodied energy flows in Eqs. (6) and (7) (excluding the intraregional embodied energy transfer of the regional economy).

2.3. Data sources and processing The major direct external energy inputs into regional economy to generate the supply of energy carriers include raw coal, crude oil, natural gas, hydropower, nuclear power and other renewable power (for the latter three categories, only the parts used for electricity generation are included due to data availability). The hydropower, nuclear power and other renewable energy inputs are estimated according to electricity generation data and corresponding electricity generation efficiencies. To keep the data consistency, the electricity generation efficiencies of hydropower, nuclear power, and other renewable energy provided in Zhang et al. [11] and Chen and Chen [17,18] are adopted directly, with the values of 90%, 33%, and 33%, respectively. The relevant primary energy data for all the 30 regions in 2007 are collected or derived from China Energy Statistical Yearbook 2008 [57] and China Electric Power Yearbook 2008 [58]. The energy data in 2002 are collected or derived from China Energy Statistical Yearbook 2003 [59] and China Electric Power Yearbook 2003 [60]. Since the raw coal data for 1996–2004 in China’s energy statistics have always been questioned [61,62], we resort to the updated data for regional coal output in 2002 provided in China Compendium of Statistics 1949–2008 [63]. We assume that the primary energy resources from natural ecosystems are directly inputted into two economic sectors in the MRIO table, i.e., raw coal, crude oil and natural gas for the Mining and dressing sector, and hydropower, nuclear power and other renewable energy for the Electric power, steam and hot water, water and gas production and supply sector. Detailed results of primary energy input into the regional economy in 2002–2007 are listed in Table 2.

3. Results 3.1. Overall variation and regional contributions Table 3 lists the interregional transfers of embodied energy flows (EEITs) via domestic trade in 2002–2007. The gross scale of interregional embodied energy transfer (total EEIO or EEII) in 2002 was only 480.87 Mtce, accounting for 38.2% of the national direct primary energy input (DEI). This value then increased to

Please cite this article in press as: Zhang B et al. Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input– output analysis. Appl Energy (2015), http://dx.doi.org/10.1016/j.apenergy.2015.09.076

6

B. Zhang et al. / Applied Energy xxx (2015) xxx–xxx

Table 2 Direct primary energy input into China’s regional economies over 2002–2007 (Mtce). Region

Sector 2

Sector 14

Raw coal

Crude oil

2002 Northeast Beijing–Tianjin North Coast East Coast South Coast Central Northwest Southwest

91.07 6.29 136.79 19.05 5.81 404.25 177.59 90.33

Total 2007 Northeast Beijing–Tianjin North Coast East Coast South Coast Central Northwest Southwest Total

Total

Natural gas

Primary electricity

97.97 17.37 45.35 3.00 18.13 9.23 48.00 0.25

4.78 1.18 1.78 0.61 4.20 2.97 14.23 13.65

1.14 0.07 0.07 4.06 13.43 9.21 3.96 13.85

194.95 24.91 183.99 26.73 41.56 425.66 243.79 118.09

931.18

239.31

43.40

45.79

1259.68

141.21 4.63 165.58 17.80 14.64 727.67 495.67 237.09

85.73 27.49 49.33 3.09 18.17 8.15 73.91 0.30

5.25 1.77 1.99 0.75 7.25 2.25 47.21 25.62

2.10 0.06 0.47 15.09 19.16 19.66 8.53 26.01

234.28 33.96 217.38 36.73 59.23 757.73 625.32 289.02

1804.30

266.17

92.09

91.09

2253.66

Table 3 The total EEITs over 2002–2007 (Mtce). Region

Northeast

Beijing–Tianjin

North Coast

East Coast

South Coast

Central

Northwest

Southwest

Total EEIO

2002 Northeast Beijing–Tianjin North Coast East Coast South Coast Central Northwest Southwest

0 1.29 3.37 0.24 1.05 11.44 15.07 5.37

11.60 0 14.12 0.64 1.28 20.54 14.69 4.85

15.08 4.46 0 1.54 2.60 56.55 27.82 8.14

4.54 0.95 7.20 0 4.06 40.90 27.35 8.10

4.46 0.35 2.83 0.87 0 17.11 10.43 8.54

6.25 0.90 8.37 2.14 4.67 0 26.29 8.40

5.67 0.45 4.35 0.56 1.70 12.98 0 10.02

4.04 0.26 1.70 0.41 1.94 9.37 11.02 0

51.63 8.67 41.94 6.40 17.29 168.88 132.66 53.41

Total EEII

37.83

67.72

116.18

93.09

44.58

57.01

35.73

28.73

480.87

2007 Northeast Beijing–Tianjin North Coast East Coast South Coast Central Northwest Southwest

0 2.48 5.99 0.38 1.33 14.80 26.62 7.66

10.26 0 12.10 0.40 0.79 16.92 21.20 4.06

26.97 5.62 0 1.36 2.35 98.38 74.17 14.85

48.52 7.96 18.87 0 5.73 166.98 155.17 33.86

35.17 3.85 10.13 2.07 0 45.46 88.17 25.53

41.23 5.00 25.90 4.01 5.80 0 126.87 35.24

8.53 0.91 7.05 0.91 2.26 23.33 0 13.36

15.66 1.46 6.56 1.00 5.65 31.73 59.44 0

186.35 27.28 86.61 10.14 23.92 397.58 551.65 134.56

Total EEII

59.27

65.73

223.70

437.11

210.38

244.05

56.35

121.50

1418.09

1418.09 Mtce in 2007, with a growth rate of 194.9%, which accounted for 62.9% of the gross DEI in this year. On a regional basis, there were remarkable disparities on the EEIO and EEII among the eight regions, and relatively large structure changes of regional EEIOs and EEIIs can be found over 2002–2007. As to the EEIO, Central and Northwest were the top two interregional exporters. In 2002, Central had the top EEIO of 168.88 Mtce, this data increased to be 397.58 Mtce in 2007; Northwest instead of Central became the largest interregional exporter in 2007 with the EEIO of 551.65 Mtce. Between 2002 and 2007, Northwest exhibited the fast growth rate (3.16-fold) of EEIO, followed by Northeast (2.61-fold), Beijing–Tianjin (2.15-fold), Central (1.35-fold) and North Coast (1.07-fold). By contrast, South Coast and East Coast had the lowest growth rates of EEIO with the values of 38.3% and 58.4%, respectively. In line with the increasing regional EEIO, regional differences in EEII between 2002 and 2007 were also expanding. North Coast had

the largest EEII of 116.18 Mtce in 2002 among all the eight regions, followed by East Coast, Beijing–Tianjin and Central. However, by 2007, East Coast became the largest interregional importer of embodied energy with an amount of 437.11 Mtce, at nearly double that of Central, followed by Central, North Coast and South Coast. Between 2002 and 2007, South Coast, East Coast, Central and Southwest had the top four fast growth rates of EEII, with the values of 3.72-fold, 3.67-fold, 3.28-fold and 3.23-fold, respectively. Fig. 2 shows the distribution of regional EEIBs over 2002–2007. Between 2002 and 2007, Northwest, Central and Northeast exhibited the fast growth of EEIB. By contrast, the EEIBs in East Coast, South Coast and North Coast experienced a dramatic decline. Obviously, in 2002, the Central region was the largest interregional net exporter with the EEIB of 111.87 Mtce, followed by Northwest of 96.93 Mtce, Southwest of 24.68 Mtce and Northeast of 13.80 Mtce. By 2007, Northwest became the largest interregional net exporter with the EEIB of 495.30 Mtce, followed by Central of

Please cite this article in press as: Zhang B et al. Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input– output analysis. Appl Energy (2015), http://dx.doi.org/10.1016/j.apenergy.2015.09.076

7

B. Zhang et al. / Applied Energy xxx (2015) xxx–xxx

600.00

2002 2007

400.00

Southwest

Northwest

Central

East Coast

South Coast

-400.00

North Coast

-200.00

Beijing-Tianjin

0.00 Northeast

EEIB (Mtce)

200.00

Region

-600.00

Fig. 2. Regional EEIBs over 2002–2007.

153.54 Mtce, Northeast of 127.09 Mtce and Southwest of 13.06 Mtce. Meanwhile, East Coast was the largest interregional net importer over 2002–2007 with the embodied energy surpluses of 86.69 Mtce in 2002 and 426.97 Mtce in 2007. By 2007, South Coast with the EEIB of 186.46 Mtce replaced North Coast (137.09 Mtce) as the second largest interregional net importer. In the whole, significant growth of interregional net embodied energy transfers between 2002 and 2007 can be found from western and central regions to eastern regions and from inland regions to coastal regions, as shown in Fig. 1. In 2007, the two largest flows of net embodied energy transfers started from Central to East Coast and from Northwest to East Coast, at a volume of 162.97 and 154.26 Mtce, respectively, and 73.7% of East Coast’s total EEII came from the two regions. These results indicate that increasing embodied energy transfers occurred interregionally in domestic supply chains, and China’s interregional economic ties grew closer. 3.2. Consumption-driven embodied energy transfers Final demands can be regarded as the driving force of either production or service provision in supply chains. The interregional input–output modeling can identify how much of a region’s primary energy inputs are induced by its partner regions’ each category of final demands. Table 4 lists the EEITs induced by

consumption (covering rural household consumption, urban household consumption and government consumption). Overall, the total consumption-driven EEITs grew from 176.03 Mtce in 2002 to 395.84 Mtce in 2007, revealing a dramatic change in magnitude. However, the proportion of consumption-induced EEITs in the national total decreased from 36.6% to 27.9% from 2002 to 2007. At the regional level, the data presented in Table 4 reveal that most of the consumption-driven EEITs between any two regions increased largely between 2002 and 2007. Central and Northwest had higher consumption-induced EEIOs comparing to other regions, accounting for 42.2% and 23.5% of the national total in 2007, respectively. The absolute level of the Northwest’s EEIO was 166.92 Mtce in 2007, 3.04 times of that in 2002. In 2002, there were little different for the consumption-driven EEIIs among the eight regions; however, by 2007, East Coast, North Coast, South Coast and Central became the main interregional importers. Consumption-driven EEIIs in the East Coast region contributed only 17.30% (30.39 Mtce) to the national total in 2002, but 24.6% (97.48 Mtce) in 2007. Furthermore, the Northwest’s deficit amounted to 154.00 Mtce in 2007 and rose by 269.2% over 2002–2007, while the East Coast’s surplus was 94.94 Mtce in 2007 and rose by 239.1%. MRIO analysis can not only identify the economic links between regions, but also reveal the relationship between different sectors [11,41]. Displayed in Fig. 3 is the sectoral EEITs induced by consumption. The Other Service Activities sector (S17) held the top values of EEITs, which increased from 63.39 Mtce (36.0% of the total consumption-driven EEIT) in 2002 to 137.03 Mtce (34.6%) in 2007. The five sectors of S1 (Agriculture), S3 (Food production and processing, tobacco processing), S7 (Petroleum processing, coking, nuclear fuel processing, chemical industry), S14 (Electric power, steam and hot water, water and gas production and supply) and S16 (Transport and storage services, wholesale and retail trade) also had significant EEITs, contributing respectively to 6.3%, 10.5%, 9.5%, 10.5% and 8.3% of the national total consumption-induced EEIT in 2007. The aforementioned six sectors contributed to 79.7% of the total consumption-driven EEITs in 2007. These sectors are all closely linked with people’s livelihood, such as consumption of food, electricity, heating, water, gas, transport service and other household services, and resulted in large variation of the consumption-driven EEITs over 2002–2007. In fact, China’s urban

Table 4 The EEITs caused by consumption over 2002–2007 (Mtce). Region

Northeast

Beijing–Tianjin

North Coast

East Coast

South Coast

Central

Northwest

Southwest

Total EEIO

2002 Northeast Beijing–Tianjin North Coast East Coast South Coast Central Northwest Southwest

0 0.85 1.87 0.12 0.57 6.30 9.65 3.01

3.50 0 3.84 0.18 0.40 6.48 4.41 1.67

4.57 1.40 0 0.43 0.74 15.44 8.46 2.20

1.31 0.32 2.05 0 1.17 13.45 9.33 2.75

1.31 0.11 0.69 0.21 0 5.27 3.63 2.91

2.57 0.47 3.39 1.02 2.31 0 13.88 3.93

2.29 0.21 1.48 0.22 0.65 4.48 0 3.93

2.06 0.16 0.80 0.22 1.00 4.71 5.63 0

17.61 3.52 14.12 2.39 6.84 56.14 54.98 20.41

Total EEII

22.37

20.47

33.24

30.39

14.14

27.57

13.27

14.58

176.03

2007 Northeast Beijing–Tianjin North Coast East Coast South Coast Central Northwest Southwest

0 1.22 1.57 0.09 0.38 4.63 9.38 2.05

2.45 0 2.36 0.07 0.17 3.40 4.62 0.75

8.13 1.96 0 0.32 0.53 22.36 20.25 3.65

12.59 2.09 3.38 0 0.98 33.80 37.63 6.99

9.83 1.21 3.55 0.68 0 14.13 27.16 7.53

16.18 1.99 8.20 0.91 1.94 0 45.76 13.17

2.79 0.39 1.76 0.17 0.57 4.78 0 2.46

5.93 0.63 2.40 0.28 1.73 9.74 22.11 0

57.91 9.50 23.23 2.54 6.30 92.85 166.92 36.61

Total EEII

19.31

13.83

57.21

97.48

64.10

88.16

12.92

42.84

395.84

Please cite this article in press as: Zhang B et al. Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input– output analysis. Appl Energy (2015), http://dx.doi.org/10.1016/j.apenergy.2015.09.076

8

B. Zhang et al. / Applied Energy xxx (2015) xxx–xxx

Consumption-driven EEITs (Mtce)

150.00

2002 2007 120.00

90.00

60.00

30.00

0.00 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17

Sector Fig. 3. Sectoral total EEITs induced by consumption over 2002–2007.

population expanded from 39% to 45% of the national population and the per capita consumption expenditure of urban households increased from 8400.5 Yuan (2007 constant price) to 11855.0 Yuan over 2002–2007 [64]. 3.3. Investment-driven embodied energy transfers China’s economic growth has long been labeled investmentdriven, and the infrastructure construction and energy-intensive industrial activities always result in huge embodied energy requirements [65–67]. Table 5 reveals the EEITs driven by investment in terms of gross fixed capital formation and changes in inventories over 2002–2007. The total investment-driven EEITs showed a rapid growth from 205.40 Mtce (42.7% of the national total EEIT) in 2002 to 592.29 Mtce (41.8% of the total) in 2007, with a growth rate of 188.4%. Comparison of investment-driven EEIO and EEII shows that the differences between EEIO and EEII were significant in most regions. The investments of three coastal regions (i.e., South Coast, East Coast and North Coast) had the largest embodied energy spillover effect on northern and western inland regions’ EEIO in both 2002 and 2007. In 2002, Central and Northwest accounted for 36.0%

and 24.7% of the national total investment-induced EEIO. By 2007, Northwest replaced Central as the largest interregional exporter, and the investment-driven EEIOs in Northwest and Central respectively increased by 327.9% (166.59 Mtce) and 142.4% (105.17 Mtce) over this period. The four largest interregional outflows of embodied energy all came from the Central and Northwest regions. Meanwhile, the investment-induced EEIIs in East Coast, Central and North Coast experienced a dramatic increase, and clear rank changes occurred between 2002 and 2007. East Coast had the largest increment of EEII (125.19 Mtce, 32.4% of the national total increment), followed by Central (90.50 Mtce, 23.4%) and North Coast (62.47 Mtce, 16.1%) from 2002 to 2007. Consequently, different regions had diverse characteristics concerning the embodied energy trade balance. The large embodied energy transfers from inland regions to coast regions had put the former into a great domestic trade energy deficit. For example, the interregional net embodied energy outflows of Northwest showed a significant increase from 30.9 Mtce in 2002 to 183.38 Mtce in 2007, while the net inflows of embodied energy in East Coast experienced a rapid increase from 32.54 Mtce in 2002 to 155.48 Mtce in 2007. The large variation of EEITs revealed the rapid expansion of capital investments in eastern coastal provinces. Displayed in Fig. 4 is the distribution of sectoral investmentdriven EEITs in 2002 and 2007. Sector 15 (Construction) is an energy-intensive sector from a life-cycle perspective, which needs a great deal of direct and indirect industrial inputs such as cement, electricity and metal products. Certainly, this sector had the largest investment-driven EEITs among all the 17 sectors, which increased from 133.49 Mtce (with a share of 65.0% in the national total) in 2002 to 357.18 Mtce (60.3%) in 2007. The following four largest sectors in 2007 were S10 (Ordinary machinery, equipment for special purposes), S12 (Electric equipment and machinery, electronic and telecommunications equipment), S11 (Transportation equipment) and S9 (Smelting and pressing of ferrous and nonferrous metals, metal products), accounting for 11.9%, 8.8%, 5.1% and 4.6% of the national total, respectively. These sectors provided metal products, heavy machinery as well as electric products to meet demand for gross capital formation, though their EEITs were much less than those of the Construction sector over this period. The aforementioned 5 sectors mentioned above, out of all the 17 sectors, contributed to 90.8% of the total investment-driven EEITs in 2007. Therefore, investment-driven final demands, primarily in the Construction

Table 5 The EEITs caused by investment over 2002–2007 (Mtce). Region

Northeast

Beijing–Tianjin

North Coast

East Coast

South Coast

Central

Northwest

Southwest

Total EEIO

2002 Northeast Beijing–Tianjin North Coast East Coast South Coast Central Northwest Southwest

0 0.40 1.30 0.11 0.43 4.44 4.85 2.09

5.48 0 6.67 0.35 0.57 9.06 6.29 2.12

7.20 1.83 0 0.82 1.27 26.46 12.35 4.17

1.97 0.30 2.72 0 1.49 17.05 9.00 3.11

1.41 0.08 0.91 0.30 0 4.82 2.43 2.23

3.40 0.38 4.45 1.04 2.09 0 10.94 4.05

3.02 0.20 2.45 0.32 0.91 7.64 0 5.36

1.80 0.10 0.83 0.18 0.85 4.39 4.92 0

24.28 3.29 19.32 3.10 7.61 73.87 50.80 23.13

Total EEII

13.61

30.53

54.10

35.64

12.19

26.36

19.90

13.07

205.40

2007 Northeast Beijing–Tianjin North Coast East Coast South Coast Central Northwest Southwest

0 0.99 3.54 0.25 0.82 8.85 14.33 5.00

4.66 0 5.95 0.22 0.38 8.46 10.23 2.34

12.72 2.24 0 0.76 1.36 53.01 38.23 8.25

15.74 2.42 8.01 0 2.59 65.78 53.07 13.21

4.39 0.47 1.85 0.47 0 10.62 12.69 4.95

17.20 1.99 13.86 2.50 3.16 0 59.93 18.21

4.43 0.40 3.90 0.56 1.37 13.96 0 9.39

7.43 0.62 3.42 0.60 3.22 18.36 28.92 0

66.59 9.14 40.53 5.35 12.91 179.04 217.39 61.34

Total EEII

33.77

32.25

116.57

160.83

35.44

116.86

34.01

62.56

592.29

Please cite this article in press as: Zhang B et al. Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input– output analysis. Appl Energy (2015), http://dx.doi.org/10.1016/j.apenergy.2015.09.076

9

B. Zhang et al. / Applied Energy xxx (2015) xxx–xxx

Investment-driven EEITs (Mtce)

400.00 2002 2007

300.00

200.00

100.00

0.00 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17

Sector Fig. 4. Sectoral total EEITs induced by investment over 2002–2007.

sector, can be considered as the important cause of growth in embodied energy transfers via domestic trade from 2002 to 2007.

Central (30.1% of the total), Northeast (14.3%) and Southwest (8.4%). Meanwhile, the exports-driven EEIIs in East Coast and South Coast had a dramatic increase between 2002 and 2007. The gross quantity of exports-driven EEII in East Coast increased from 33.64 Mtce in 2002 to 203.64 Mtce in 2007, which represented an overall increase of 504.8%. East Coast also contributed the largest fraction of 48.6% to the total exports-driven EEII in 2007, followed by South Coast of 26.9%, North Coast of 9.7% and Beijing– Tianjin of 15.4%. Exports demands in eastern coast regions were mainly supported by embodied energy from central and western inland regions. In the case of the East Coast region in 2007, exports caused embodied energy outflows from Northwest (75.87 Mtce) and Central (72.99 Mtce), which were equal to 73.2% of East Coast’s total exports-driven EEII. Certainly, East Coast and South Coast held the top two interregional net import of exports-driven embodied energy, while Northwest and Central contributed the largest interregional net export over 2002–2007. Thereafter, the international exports-induced EEITs were decided by the large volumes of foreign trade demands in China’s eastern coastal regions, owing to their location advantages and great economic openness. Fig. 5 presents the sectoral EEITs induced by international exports. For most manufacturing sectors such as S4–S13, which

3.4. Exports-driven embodied energy transfers

120.00 2002 2007

Exports-driven EEITs (Mtce)

In addition to the increases in regional consumption level and accelerated investment in fixed assets, rapidly expanding exports is the other major driving force for embodied energy transfers among regions. Table 6 presents the EEITs induced by international exports. The total exports-driven EEITs increased from 86.19 Mtce in 2002 and 418.63 Mtce in 2007 with a growth rate of 385.8%, and the shares in the national total rose from 17.9% in 2002 to 29.5% in 2007. On close examination of each pair flux of exports-driven embodied energy between any two regions, most of them increased largely between 2002 and 2007. Prominently, the fluxes of exports-driven embodied energy from Northwest to East Coast, from Central to East Coast, and from Northwest to South Coast had the increases of 59.94, 64.48 and 44.51 Mtce, respectively. At the absolute level, in 2007, the Northwest region had the largest exports-driven EEIO, which increased by 515.6% since 2002 (135.80 Mtce), accounting for 38.7% of the total, followed by

100.00

80.00

60.00

40.00

20.00

0.00 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17

Sector Fig. 5. Sectoral total EEITs induced by international exports over 2002–2007.

Table 6 The EEITs caused by international exports over 2002–2007 (Mtce). Region

Northeast

Beijing–Tianjin

North Coast

East Coast

South Coast

Central

Northwest

Southwest

Total EEIO

2002 Northeast Beijing–Tianjin North Coast East Coast South Coast Central Northwest Southwest

0 0.27 0.5 0.02 0.16 1.18 2.65 0.57

1.74 0 2.29 0.08 0.21 3.11 2.38 0.65

1.38 0.54 0 0.12 0.25 5.83 2.99 0.71

1.46 0.4 2.94 0 1.67 13.05 11.39 2.73

1.7 0.15 1.14 0.34 0 6.87 4.29 3.31

0.24 0.06 0.53 0.1 0.39 0 2.00 0.48

0.22 0.02 0.25 0.02 0.08 0.57 0 0.45

0.18 0.01 0.12 0.01 0.13 0.61 0.65 0

6.93 1.46 7.76 0.69 2.89 31.22 26.34 8.9

Total EEII

5.35

10.47

11.82

33.64

17.79

3.79

1.61

1.72

86.19

2007 Northeast Beijing–Tianjin North Coast East Coast South Coast Central Northwest Southwest

0 0.86 1.07 0.05 0.13 2.34 5.64 0.84

3.64 0 3.66 0.11 0.24 4.94 6.6 0.99

4.91 1.17 0 0.21 0.31 19.21 12.57 2.17

24.85 4.52 8.19 0 2.31 72.99 75.87 14.73

20.9 2.13 4.77 0.9 0 21.54 48.8 13.63

3.35 0.43 1.5 0.25 0.24 0 8.78 1.48

1.36 0.14 1.03 0.12 0.23 3.51 0 1.22

1 0.08 0.28 0.05 0.24 1.65 3.87 0

60.01 9.33 20.51 1.69 3.71 126.19 162.14 35.06

Total EEII

10.93

20.18

40.56

203.46

112.67

16.03

7.61

7.17

418.63

Please cite this article in press as: Zhang B et al. Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input– output analysis. Appl Energy (2015), http://dx.doi.org/10.1016/j.apenergy.2015.09.076

10

B. Zhang et al. / Applied Energy xxx (2015) xxx–xxx

provided China’s major export products, the exports-driven sectoral EEITs were especially higher than those of other sectors, and the absolute amount in these sectors increased greatly between 2002 and 2007. Particularly, the four sectors of S12, S7, S9 and S4 (Textile, garments and other fiber products, leather, furs, down and related Products) had higher exports-driven EEITs than other sectors, which contributed to 22.6%, 21.8%, 14.9% and 10.1% of the national total in 2007. These results can be explained by the growth of industrial products in China destined for international exports, which were mainly manufacturing goods, such as textile products, industrial raw materials, and primary machinery and equipment products [68]. 4. Discussions Interregional embodied energy transfers provided direct evidence on how domestic trade can affect regional energy use inventories inside China. Given the total trade volumes in embodied energy were equivalent to 38.2% of the total DEI in 2002 and 62.9% of that in 2007, respectively, the energy use inventories in terms of EEU for China’s 8 regions were quite different from those in terms of DEI, as listed in Table 7. Significant changes can be observed in the comparison of the orders by regional DEIs and EEUs over 2002–2007. By 2007, Central, Northwest, Southwest, Northeast and North Coast had the top five DEIs, while Central, East Coast, North Coast, Southwest and South Coast had the largest EEUs. The fast growth of interregional net embodied energy transfers (the EEIB deficit or surplus) can explain the temporal and spatial changes of regional energy use inventories over this period. East Coast was the area with the fastest growing EEU, and the largest increases of EEIB occurred in this region during the period. South Coast and North Coast showed similarly large increases of the EEU and EEIB. Northwest, Central, Southwest and Northeast had a higher degree of energy self-sufficiency with their EEUs responsible for less than 100% of their DEIs due to the net outflows of embodied energy. Considering the EEITs, significant changes for regional per capita energy uses and energy uses per GDP also had occurred, as demonstrated in Table 7. For instance, Beijing–Tianjin became the largest per capita embodied energy user in 2002; by 2007, the East Coast region replaced Beijing–Tianjin as the largest per capita embodied energy user, followed by Beijing–Tianjin and North Coast. Compared with the differences of regional DEI per GDP, the differences of EEU per GDP among all the eight regions turned to relatively small. The pattern of regional trade structure depends on a regional demand for final products and reflects a region’s position and participation degree in domestic supply chains [10,13]. A certain

region’s DEIs induced by other region’s final demands through domestic trade reflect that the region acts as a producer of intermediate products in domestic supply chains, which explains how a region’s DEIs are embodied in domestic final consumption and in trade (interregional trade and exports) to satisfy other regions’ final demand. During 2002–2007, significant growth of net embodied energy transfers can be identified from western and central regions to eastern regions and from inland regions to coastal regions. The results can be explained by the closer regional industrial linkages and deeper interdependence of China’s regional economies. Most central and western inland regions had a large surplus in the balance of embodied energy trade, which reflects that these regions were located at the upstream of interregional supply chains by providing highly energy-intensive intermediate products to other regions. In fact, the central and western provinces such as Shanxi, Inner Mongolia, Xinjiang and Shaanxi were the main primary energy suppliers in China [69], and these provinces exported a greater quantity of embodied energy by joining the domestic supply chains of the leading coastal regions. China’s eastern coastal regions located in the down-stream of domestic supply chains are the most important manufacturing center locally and worldwide. Its final demands influenced the spatial distribution of production activities across China and further drove a large amount of embodied energy transfers via interregional economic linkage. It is worthy of noting that the Central region, linking the western provinces and the eastern provinces, also played a role as a kind of ‘‘transmission channel” of embodied energy transfers from western inland regions to eastern coastal regions due to its central position and function in domestic supply chains, well-developed transportation infrastructure and comparative advantage in energy resources in China. Meng et al. [13] also had a similar conclusion that the Central region served as a ‘‘transmission channel” of CO2 emissions from inland regions to coastal regions. In addition to the industrial positions in domestic and global supply chains, inherent economic driving factors such as consumption, investment and international exports play an important role in determining the EEITs. China’s household consumption, especially in the developed provinces, has increasingly reflected a more energy-intensive lifestyle afforded by higher incomes. For most regions, the growth of consumption-induced EEITs resulted mainly from sectors closely linked with people’s livelihood, such as consumption of food, electricity, heating, water, gas, transport service and other household services. Energy demands in China are dominated by investment-driven industrial production [67,70]. In contrast to other developed countries, China’s regional investment policies mainly focus on the development of infrastructure construction, commercial buildings and high energy-consuming

Table 7 Regional energy use inventories over 2002–2007. Region

Northeast

Beijing–Tianjin

North Coast

East Coast

2002 DEI (Mtce) EEU (Mtce) Per capita DEI (tce) Per capita EEU (tce) DEI per GDP (gce/Yuan) EEU per GDP (gce/Yuan)

194.95 181.15 1.82 1.69 150.64 139.97

24.91 83.97 1.03 3.46 32.44 109.34

183.99 258.24 1.16 1.63 89.20 125.19

26.73 113.42 0.20 0.83 9.08 38.52

2007 DEI (Mtce) EEU (Mtce) Per capita DEI (tce) Per capita EEU (tce) DEI per GDP (gce/Yuan) EEU per GDP (gce/Yuan)

234.28 107.20 2.16 0.99 100.23 45.86

33.96 72.41 1.24 2.64 23.58 50.27

217.38 354.48 1.33 2.17 54.79 89.35

36.73 463.70 0.25 3.19 6.48 81.77

South Coast

Central

Northwest

Southwest

41.56 68.86 0.34 0.57 19.33 32.03

425.66 313.79 1.18 0.87 149.08 109.90

243.79 146.86 2.09 1.26 244.18 147.10

118.09 93.41 0.48 0.38 75.10 59.40

59.23 245.69 0.43 1.77 14.25 59.12

757.73 604.20 2.15 1.71 145.60 116.10

625.32 130.02 5.20 1.08 321.41 66.83

289.02 275.96 1.20 1.15 102.98 98.32

Note: The data of GDP in 2002 were calculated at 2007 constant price [64].

Please cite this article in press as: Zhang B et al. Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input– output analysis. Appl Energy (2015), http://dx.doi.org/10.1016/j.apenergy.2015.09.076

B. Zhang et al. / Applied Energy xxx (2015) xxx–xxx

industries [22,38], which used a lot of energy-intensive materials such as steel and cement, and caused the rapid increase of investment-induced EEITs. The export demands of industrial raw industrials, primary machinery and equipment products, and transport and storage services also contributed to the expanding EEITs. The increasing participation of China’s eastern coastal provinces in global supply chains, with a large share of manufacturing for exports in their total products [40], has rapidly increased the embodied energy transfers in their trade partners’ interregional exports. Understanding China’s regional diversity and complexity on energy uses from the view of demand-driven energy requirements is essential to assessing the optimum energy-conversation and emission-reduction targets at the national and regional level. A region’s energy-saving potentials depend on not only its intraregional production technologies, energy use efficiencies, but also its position and participation degrees in domestic and global supply chains [13,37]. Embodied energy-surplus coastal regions generally have upgraded industrial and consumption structures, higher energy-use technologies, and higher export dependency [22]. Conversely, embodied energy-deficit inland regions with high primary energy inputs have weaker economies and contain simple industrial structures dominated by energy and raw material production, low-level manufacturing industries, and low energy-use technologies, resulting in a low level of economic development [41,44]. Considering the embodied energy transfers is important for policy makers to recognize visible and hidden energy use along the entire supply chains and address cross-boundary potentials for energy saving at the regional, national and global supply chains [37]. It’s urgent to narrow the regional gaps of available capitals and technologies, consumption levels and environmental capacities among the well-developed eastern areas and the less-developed central and western areas [46], by considering the benefit or loss to a particular region’s energy from bilateral trade with other regions. Policies should pay more attention to improve the resource taxes and price mechanisms of primary energy resources, promote manufacturing energy utilization technologies, reduce the overcapacities in many industrial sectors, alter conventional capital investment practices, make optimum use of new and existing buildings and infrastructures, optimize the industrial and trade structures based on consumption-based accounting method, and then promote regional socio-economic development quality. In addition, the transfer of energy-intensive industries from developed provinces to undeveloped provinces may always result in more energy consumption and more CO2 emissions. To attain the overall energy-conversation and emission-reduction goals, the interregional transfer of energy-intensive and emission-intensive industries with backward or outdated production capacities should be largely avoided and given special attention in energy policy design.

5. Conclusions China’s sharply increasing energy production and utilization with related environmental impacts has become an increasingly pronounced global concern. It is critical to explore the energy uses embodied in domestic final consumption and in trade (interregional trade and exports) associated with the hidden socio-economic driving factors, so that more appropriate policy designs for energy saving and emission reduction can be achieved by considering China’s regional diversity and complexity. The national total embodied primary energy requirement in 2007

11

amounted to 2253.66 Mtce, 78.9% larger than 1259.68 Mtce in 2002. Meanwhile, the total interregional embodied energy transfers (EEITs) grew from 480.87 Mtce in 2002 to 1418.09 Mtce in 2007 with the growth rate of 194.9%, and then the total trade volumes in embodied energy were equivalent to 38.2% and 62.9% of the national total direct primary energy input in 2002 and in 2007, respectively. The increased embodied energy transfers via domestic trade revealed that the economic relationship among sub-national regions in China tightened between 2002 and 2007. Overall, increasing net embodied energy fluxes explicitly moved from central and western regions to eastern regions and from inland regions to coast regions through closer interregional trade in domestic supply chains. The regions of East Coast, South Coast, North Coast and Beijing–Tianjin were the interregional net importers and surplus receivers of embodied energy, while Northwest, Central, Northeast and Southwest were the interregional net exporters and deficit receivers. By allocating the overall EEIT variation into different final demand categories, investment and international exports caused considerable EEITs across regions. The total investment-driven EEITs showed a rapid growth from 205.40 Mtce (42.7% of the national total EEIT) in 2002 to 592.29 Mtce (41.8%) in 2007, and the total exports-driven EEITs from 86.19 Mtce (17.9%) to 418.63 Mtce (29.5%). Meanwhile, although consumption-induced EEITs grew from 176.03 Mtce in 2002 to 395.84 Mtce in 2007, the shares decreased from 36.6% to 27.9% over this period. In 2014, China’s total primary energy production and consumption amounted to 3.60 and 4.26 billion tce [71], respectively, 1.53 and 1.60 times of those in 2007, owing to its rapidly increasing urbanization, industrialization, internationalization and modernization processes, which means that the embodied energy transfers via interregional economic linkages have largely increased in recent years. Given China has ambitious plans to cap its total primary energy consumption and further decrease the adverse environmental impact of energy production and utilization such as the emission level of major air pollutants and greenhouse gases in the near future, its sound energy and environmental policies for achieving the sustainability of energy resource uses must be considered from multiple and comprehensive perspectives, which may also contribute to global energy saving and emission mitigation. Examining demand-driven energy requirements and embodied energy transfers in domestic and global supply chains will be useful for understanding and illustrating the influence of industrial positions, final consumption demands and trades (interregional trade and exports) on national and regional energy uses and related energy-saving and emission-reduction potentials. Acknowledgements This study has been supported by the National Natural Science Foundation of China (Grant nos. 71403270, 51421065, 71373262, 71573021), Foundation of State Key Laboratory of Coal Resources and Safe Mining, China University of Mining & Technology (SKLCRSM14KFA03), China Sustainable Energy Program of Energy Foundation (G-1407-21749), Doctoral Program of Higher Education of China (No. 20130003110027) and National Key Technology R&D Program (No. 2012BAK30B03). Appendix A See Tables A1 and A2.

Please cite this article in press as: Zhang B et al. Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input– output analysis. Appl Energy (2015), http://dx.doi.org/10.1016/j.apenergy.2015.09.076

12

B. Zhang et al. / Applied Energy xxx (2015) xxx–xxx Table A1 Sector information for MRIO analysis. Code

Sector category

S1 S2 S3 S4 S5 S6

Agriculture Mining and dressing Food production and processing, tobacco processing Textile, garments and other fiber products, leather, furs, down and related Products Timber processing, bamboo, cane, palm & straw products, furniture manufacturing Papermaking and paper products, printing and record medium reproduction, cultural, educational and sports articles Petroleum processing, coking, nuclear fuel processing, chemical industry Nonmetal mineral products Smelting and pressing of ferrous and nonferrous metals, metal products Ordinary machinery, equipment for special purposes Transportation equipment Electric equipment and machinery, electronic and telecommunications equipment Other industrial activities Electric power, steam and hot water, water and gas production and supply Construction Transport and storage services, wholesale and retail trade Other service activities

S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17

Table A2 Regional information in 2007. Regions

Provinces covered

Population (million)

GDP (billion Yuan)

Per capita GDP (USD)

Northeast Beijing–Tianjin North Coast East Coast South Coast Central Northwest Southwest

Heilongjiang, Jilin, Liaoning Beijing, Tianjin Shandong, Hebei Jiangsu, Shanghai, Zhejiang Fujian, Guangdong, Hainan Henan, Shanxi, Hubei, Hunan, Anhui, Jiangxi Shaanxi, Inner Mongolia, Ningxia, Gansu, Qinghai, Xinjiang Sichuan, Chongqing, Guangxi, Yunnan, Guizhou

108.52 27.48 163.1 145.43 138.75 352.93 120.27 239.87

2337.32 1440.37 3967.54 5671.04 4155.68 5204.09 1945.53 2806.67

2948.57 7175.64 3330.20 5338.41 4100.27 2018.64 2214.54 1601.84

Data sources: CSY [64].

References [1] Leung GCK, Cherp A, Jewell J, Wei YM. Securitization of energy supply chains in China. Appl Energy 2014;123:316–26. [2] Qiu J. Fight against smog ramps up. Nature 2014;506:273–4. [3] Dong H, Dai H, Dong L, Fujita T, Geng Y, Klimont Z, et al. Pursuing air pollutant co-benefits of CO2 mitigation in China: a provincial leveled analysis. Appl Energy 2015;144:165–74. [4] Liu Z, Guan D, Crawford-Brown D, Zhang Q, He K, Liu J. A low-carbon road map for China. Nature 2013;500(7461):143–5. [5] Dai H, Mischke P, Xie X, Xie Y, Masuia T. Closing the gap? Top-down versus bottom-up projections of China’s regional energy use and CO2 emissions. Appl Energy 2015. http://dx.doi.org/10.1016/j.apenergy.2015.06.069. [6] Xinhuanet. China unveils energy strategy, targets for 2020; 2014. . [7] Zhang B, Chen GQ. China’s CH4 and CO2 emissions: bottom-up estimation and comparative analysis. Ecol Ind 2014;47:112–22. [8] Wang S, Fang C, Guan X, Pang B, Ma H. Urbanisation, energy consumption, and carbon dioxide emissions in China: a panel data analysis of China’s provinces. Appl Energy 2014;136:738–49. [9] Liu Y, Zhou Y, Wu W. Assessing the impact of population, income and technology on energy consumption and industrial pollutant emissions in China. Appl Energy 2015;155:904–17. [10] Liu HG, Liu WD, Fan XM, Liu ZG. Carbon emissions embodied in value added chains in China. J Clean Prod 2015;103:362–70. [11] Zhang B, Chen ZM, Xia XH, Xu XY, Chen YB. The impact of domestic trade on China’s regional energy uses: a multi-regional input–output modeling. Energy Policy 2013;63:1169–81. [12] Feng K, Davis SJ, Sun L, Li X, Guan D, Liu W, et al. Outsourcing CO2 within China. Proc Natl Acad Sci 2013;110(28):11654–9. [13] Meng B, Xue J, Feng K, Guan D, Fu X. China’s inter-regional spillover of carbon emissions and domestic supply chains. Energy Policy 2013;61: 1305–21. [14] Costanza R. Embodied energy and economic valuation. Science 1980;210: 1219–24. [15] Odum HT. Systems ecology. New York: John Wiley & Sons Inc; 1983. [16] Chen GQ, Chen ZM. Carbon emissions and resources use by Chinese economy 2007: a 135-sector inventory and input–output embodiment. Commun Nonlinear Sci Numer Simul 2010;15(11):2647–732.

[17] Chen ZM, Chen GQ. An overview of energy consumption of the globalized world economy. Energy Policy 2011;39(10):5920–8. [18] Chen ZM, Chen GQ. Demand-driven energy requirement of world economy 2007: a multi-region input–output network simulation. Commun Nonlinear Sci Numer Simul 2013;18(7):1757–74. [19] Miller RE, Blair PD. Input–output analysis: foundations and extensions. 2nd revised ed. Cambridge: Cambridge University Press; 2009. [20] Liu Z, Geng Y, Lindner S, Zhao H, Fujita T, Guan D. Embodied energy use in China’s industrial sectors. Energy Policy 2012;49:751–8. [21] Lindner S, Guan DB. A hybrid-unit energy input–output model to evaluate embodied energy and life cycle emissions for China’s economy. J Ind Ecol 2014;18(2):201–11. [22] Li Z, Pan L, Fu F, Liu P, Ma L, Angelo A. China’s regional disparities in energy consumption: an input–output analysis. Energy 2014;78:426–38. [23] Xie SC. The driving forces of China’s energy use from 1992 to 2010: an empirical study of input–output and structural decomposition analysis. Energy Policy 2014;73:401–15. [24] Cui LB, Peng P, Zhu L. Embodied energy, export policy adjustment and China’s sustainable development: a multi-regional input–output analysis. Energy 2015;82:457–67. [25] Wiedmann T. A review of recent multi-region input–output models used for consumption-based emission and resource accounting. Ecol Econ 2009;69 (2):211–22. [26] Chen GQ, Chen ZM. Greenhouse gas emissions and natural resources use by the world economy: ecological input–output modeling. Ecol Model 2011;222 (14):2362–76. [27] Peters GP, Minx JC, Weber CL, Edenhofer O. Growth in emission transfers via international trade from 1990 to 2008. Proc Natl Acad Sci 2011;108: 8903–8. [28] Wiedmann T, Wilting HC, Lenzen M, Lutter S, Palm V. Quo Vadis MRIO? Methodological, data and institutional requirements for multi-region input– output analysis. Ecol Econ 2012;70(11):1937–45. [29] Hawkins J, Ma C, Schilizzi S, Zhang F. Promises and pitfalls in environmentally extended input–output analysis for China: a survey of the literature. Energy Econ 2015;48:81–8. [30] Zhou X, Imura H. How does consumer behavior influence regional ecological footprints? An empirical analysis for Chinese regions based on the multiregion input–output model. Ecol Econ 2011;71:171–9. [31] Guo S, Shen GQ. Multiregional input–output model for China’s farm land and water use. Environ Sci Technol 2015;49(1):403–14.

Please cite this article in press as: Zhang B et al. Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input– output analysis. Appl Energy (2015), http://dx.doi.org/10.1016/j.apenergy.2015.09.076

B. Zhang et al. / Applied Energy xxx (2015) xxx–xxx [32] Dong H, Geng Y, Fujita T, Fujii M, Hao D, Yu X. Uncovering regional disparity of China’s water footprint and inter-provincial virtual water flows. Sci Total Environ 2014;500–501:120–30. [33] Feng K, Hubacek K, Pfister S, Yu Y, Sun L. Virtual scarce water in China. Environ Sci Technol 2014;48(14):7704–13. [34] Zhang C, Anadon LD. A multi-regional input–output analysis of domestic virtual water trade and provincial water footprint in China. Ecol Econ 2014; 100:159–72. [35] Jiang Y, Cai W, Du P, Pan W, Wang C. Virtual water in interprovincial trade with implications for China’s water policy. J Clean Prod 2015;87: 655–65. [36] Zhao X, Liu J, Liu Q, Tillotson M, Guan D, Hubacek K. Physical and virtual water transfers for regional water stress alleviation in China. Proc Natl Acad Sci 2015;112(4):1031–5. [37] Zhang B, Qiao H, Chen B. Embodied energy uses by China’s four municipalities: a study based on multi-regional input–output model. Ecol Model 2014. http:// dx.doi.org/10.1016/j.ecolmodel.2014.10.007. [38] Liang S, Zhang C, Wang YF, Xu M, Liu WD. Virtual atmospheric mercury emission network in China. Environ Sci Technol 2014;48(5):2807–15. [39] Zhao HY, Zhang Q, Davis SJ, Guan D, Liu Z, Huo H, et al. Assessment of China’s virtual air pollution transport embodied in trade by a consumption-based emission inventory. Atmos Chem Phys 2014;14:25617–50. [40] Liu Q, Wang Q. Reexamine SO2 emissions embodied in China’s exports using multiregional input–output analysis. Ecol Econ 2015;113:39–50. [41] Guo J, Zhang Z, Meng L. China’s provincial CO2 emissions embodied in international and interprovincial trade. Energy Policy 2012;42:486–97. [42] Feng K, Klaus H, Sun L, Liu Z. Consumption-based CO2 accounting of China’s mega-cities: the case of Beijing, Tianjin, Shanghai and Chongqing. Ecol Ind 2014;47:26–31. [43] Su B, Ang BW. Input–output analysis of CO2 emissions embodied in trade: a multi-region model for China. Appl Energy 2014;114:377–84. [44] Tian X, Chang M, Lin C, Tanikawa H. China’s carbon footprint: a regional perspective on the effect of transitions in consumption and production patterns. Appl Energy 2014;123:19–28. [45] Zhang B, Li JS, Peng BH. Multi-regional input–output analysis for China’s regional CH4 emissions. Front Earth Sci 2014;8(1):163–80. [46] Zhang Y, Wang H, Liang S, Xu M, Liu W, Li S, et al. Temporal and spatial variations in consumption-based carbon dioxide emissions in China. Renew Sustain Energy Rev 2014;40:60–8. [47] Zhang Z, Guo J, Hewings GJD. The effects of direct trade within China on regional and national CO2 emissions. Energy Econ 2014;46:161–75. [48] Chen ZM, Liu Y, Qin P, Zhang B, Lester Leo, Chen G, et al. Environmental externality of coal use in China: welfare effect and tax regulation. Appl Energy 2015;156:16–31. [49] Zhang Y. Provincial responsibility for carbon emissions in China under different principles. Energy Policy 2015;86(2015):142–53. [50] Jiang Y, Cai W, Wan L, Wang C. An index decomposition analysis of China’s interregional embodied carbon flows. J Clean Prod 2015;88:289–96.

13

[51] Liu LC, Liang QM, Wang Q. Accounting for China’s regional carbon emissions in 2002 and 2007: production-based versus consumption-based principles. J Clean Prod 2015;103:384–92. [52] China State Information Center. Multi-regional input–output model for China. Beijing: Social Sciences Academic Press; 2005. [53] Ichimura S, Wang HJ. Interregional input–output analysis of the Chinese economy. Beijing: Chemical Industry Press; 2007. [54] Shi M, Zhang Z. Interprovincial input–output model and economy relationship in China. Beijing: Science Press; 2012. [55] Liu WD, Chen J, Tang ZP, Liu HG, Han D, Li FY. Compliment theory and practice of China’s interregional input–output table for 30 regions in 2007. Beijing: China Statistics Press; 2012 [in Chinese]. [56] Zhang YX, Qi SC. 2002 and 2007 China multi-regional input–output models. Beijing: China Statistics Press; 2012. [57] CESY. China Energy Statistical Yearbook 2008. Beijing: China Statistics Press; 2008. [58] CEPY. China Electric Power Yearbook 2008. Beijing: China Electric Power Press; 2008. [59] CESY. China Energy Statistical Yearbook 2003. Beijing: China Statistics Press; 2003. [60] CEPY. China Electric Power Yearbook 2003. Beijing: China Electric Power Press; 2003. [61] Akimoto H, Ohara T, Kurokawa J, Horii N. Verification of energy consumption in China during 1996–2003 by using satellite observational data. Atmos Environ 2006;40(40):7663–7. [62] Zhang B, Chen GQ, Li JS, Tao L. Methane emissions of energy activities in China 1980–2007. Renew Sustain Energy Rev 2014;29:11–21. [63] CCS. China Compendium of Statistics (1949–2008). Beijing: China Statistics Press; 2010. [64] CSY. China Statistical Yearbook 2008; 2008. . [65] Chen GQ, Zhang B. Greenhouse gas emissions in China 2007: inventories and input–output analysis. Energy Policy 2010;38(10):6180–93. [66] Fu F, Liu H, Polenske KR, Li Z. Measuring the energy consumption of China’s domestic investment from 1992 to 2007. Appl Energy 2013;102:1267–74. [67] Fu F, Ma LW, Li Z, Polenske KR. The implications of China’s investment-driven economy on its energy consumption and carbon emissions. Energy Convers Manage 2014;85:573–80. [68] Xia Y, Fan Y, Yang C. Assessing the impact of foreign content in China’s exports on the carbon outsourcing hypothesis. Appl Energy 2015;150:296–307. [69] Mischke P, Xiong W. Mapping and benchmarking regional disparities in China’s energy supply, transformation, and end-use in 2010. Appl Energy 2015;143:359–69. [70] Ma L, Allwood JM, Cullen JM, Li Z. The use of energy in China: tracing the flow of energy from primary source to demand drivers. Energy 2012;40:174–88. [71] National Bureau of Statistics of China. Statistical Communiqué of the People’s Republic of China on the 2014 National Economic and Social Development; 2015. .

Please cite this article in press as: Zhang B et al. Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input– output analysis. Appl Energy (2015), http://dx.doi.org/10.1016/j.apenergy.2015.09.076