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Energy embodied in the international trade of China: An energy input–output analysis
ARTICLE IN PRESS Energy Policy 38 (2010) 3957–3964
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Energy embodied in the international trade of China: An energy input–output analysis Hongtao Liu a,b,n, Youmin Xi a, Ju’e Guo a, Xia Li a,c a
Research Center of Chinese Management Issues, School of Management, Xi’an Jiaotong University, Xi’an 710049, China Department of Urban Studies and Planning, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Room 9-549, Cambridge, MA 02139, USA c School of Law, Xi’an Jiaotong University, Xi’an 710049, China b
a r t i c l e in fo
abstract
Article history: Received 20 July 2009 Accepted 5 March 2010 Available online 24 March 2010
Growing international trade has not only positively affected the People’s Republic of China’s (China’s) economic development, but also expanded the exportation of energy embodied in goods during their production. This energy flow out will pose risks to China’s rational utilization of natural resources as well as environmental protection. In this paper, we evaluate the energy embodied in goods produced in China during 1992–2005 and use input–output structural decomposition analysis to identify five key factors causing the changes of energy embodied in exports. (Direct primary energy efficiency, primary energy consumption structure, structure of intermediate inputs, structure of exports, and scale of exports.) For the three sub-periods of 1992–1997, 1997–2002, and 2002–2005, results show that China is a net exporter of energy, and the energy embodied in exports tends to increase over time. The expanding total volume of exports and increasing exports of energy-intensive goods tend to enlarge the energy embodied in exports within all three sub-periods, but these driving forces were offset by a considerable improvement of energy efficiency and changes in primary energy consumption structure from 1992 to 2002 and the effects of structure of intermediate input only in the sub-period from 1992 to 1997. From 2002 to 2005, the sharp augmentation of energy embodied in exports was driven by all the five factors. Our research has practical implications for the Chinese economy. Results of this study suggest that the energy embodied in trade should receive special attentions in energy policies design to limit the energy resource out-flow and pollution generation. & 2010 Elsevier Ltd. All rights reserved.
Keywords: Energy input–output analysis Embodied energy Structural decomposition analysis
1. Introduction With rapid economic development and international trade growth in the past decades, China has become the world’s top exporter, the second largest energy consumer, and the third largest economy (Asia Economic Institute, 2009; National Bureau of Statistics of China, 2008). All goods and services in an economy are directly and/or indirectly related to energy use and pollution (Lenzen, 1998; Machado et al., 2001; Peters and Hertwich, 2006). International trade might magnify natural resource depletion and environmental degradation (Shui and Harriss, 2006; Liang et al., 2007). China’s fast-growing economy and increased international trade have caused the overexploitation of resources and amplified dependency on oil imports (National Bureau of Statistics of China, 2008). Therefore, there is an urgent need for complete and
n Corresponding author at: Department of Urban Studies and Planning, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Room 9-549, Cambridge, MA 02139, USA. Tel.: + 1 617 999 8756. E-mail address: [email protected] (H. Liu).
0301-4215/$ - see front matter & 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.enpol.2010.03.019
balanced information on the energy use associated with international trade (Ma¨enpa¨a¨ and Siikavirta, 2007). Input–output analysis, a useful analytical framework developed by Wassily Leontief (1936), has been widely used in analyzing the energy embodied in goods and services (Hawdon and Pearson, 1995; Schaeffer and Leal de Sa´, 1996; Kondo and Moriguchi, 1998; Machado et al., 2001). For India, Murthy et al. (1997) analyzed carbon dioxide (CO2) emissions from energy consumption for different sectors in 1990, and Pachauri and Spreng (2002) analyzed direct and indirect energy requirements of households for the years 1983–1984, 1989–1990 and 1993–1994. For Australia, Lenzen (1998) described direct and indirect primary energy and greenhouse gas requirements. For Sydney, Lenzen et al. (2004) examined trends in energy consumption. For Brazil, Cohen et al. (2005) calculated the energy embodied in goods and services purchased by households. Input–output structural decomposition analysis (SDA), a major analytical tool that is traditionally used to study the observed changes in the level and mix of output (Rose and Casler, 1996), has also been used to identify the key factors of energy intensity and CO2 emission changes for multiple countries or regions
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(Casler and Rose, 1998; Chang et al., 2008; Limmeechokchai and Suksuntornsiri, 2007; Ang and Liu, 2001; Ang, 2004; Tuyet and Ishihara, 2006; Wood and Lenzen, 2009). For Japan, Nobuko (2004) examined the impact factors of CO2 emissions produced by Japanese industries between 1985 and 1995 by using input– output tables. For Spain, Llop (2007) made an in-depth analysis of the changes in Spanish emission multipliers during the period 1995–2000. For the United States, Weber (2009) analyzed aggregate energy use in 1997 and 2002 to discover the causes of changing energy usage and flows. For the OECD, Sun (1999) investigated the change of aggregate CO2 emissions from 1960 to 1995 based on a complete decomposition approach. For China, energy consumption and pollution generation have been investigated by a number of analyses (Vanden et al., 2004; Li et al., 2007; Liao et al., 2007; Peters et al., 2007). Polenske and McMichael (2002) identified the major differences in energy use and pollution generation among three generic coke-making technologies in China. Hu and Wang (2006) analyzed the energy efficiency of 29 administrative regions in China for the period of 1995–2002. Liu et al. (2007) analyzed the driving force behind China’s primary energy-related carbon intensity and measured the final energy-related carbon intensity in material production sectors. Ma and Stern (2008) analyzed changes in energy intensities in the period 1980–2003 and found that inter-fuel substitution contributed little to the changes in energy intensity. However, few analyses have focused on the energy embodied in China’s international trade and its driving factors. Within an input–output analytical framework, we explore energy flows into, out of, and within the Chinese economy over time, evaluate the impacts of international trade on energy use, and identify the underlying factors that contribute to modifying the energy embodied in exports from 1992 to 2005. This analysis will increase understanding of the relationship between international trade and energy requirements. Moreover, this paper aims to help policy makers design energy policies that enhance sustainable development for China.
2. Energy embodied in the international trade and decomposition
where for energy sector m (for column n), Xm is the total domestic ex im h is the exports; Ym is the imports; Ym is the total production; Ym domestic final demand; Xm,n is energy sector n’s direct requirement from energy sector m in monetary units; ESm is total energy consumption in physical units; EYm is energy use or energy consumption for final consumption in physical units; Em,n is energy sector n’s direct requirement from energy sector m in E physical units; c is the number of primary energy sectors; and Pm is the energy sector m’s weighted-average price for non-energy sectors. For example, the price of coal is used to quantify intermediate inputs of coal to produce non-energy goods, such as iron, steel, and chemical products. Thus, Em,j, the m energy (in physical units) used for the production of the jth non-energy sector (in physical units), can be computed as Em,j ¼
2.1. Energy input–output analysis In the last few decades, the conventional input–output analysis (IOA) developed by Wassily Leontief (1936) has been frequently used to analyze the energy embodied in goods and the factors underlying the changes in energy consumption (Casler and Hannon, 1989; Wu and Chen, 1990; Kagawa and Inamura, 2001; Pan et al., 2008). In the input–output model, the total output of an economy, X, can be expressed as the sum of intermediate consumption, AX, and final consumption, Y (Leontief, 1970), X ¼ AX þY ¼ ðIAÞ1 Y ¼ BY
input and output data for energy sectors and final consumption data provided in the energy balance table of China from the Chinese Energy Statistical Yearbooks. Then we compute intermediate energy inputs and outputs for other non-energy sectors using weighted-average energy prices, e.g., oil, coal products, hydroelectricity (including electricity generated by nuclear materials), and natural gas. In Eq. (2), we use m (row) and n (column) as subscripts to denote energy sectors. Xm,j represent how much of the m energy (in monetary units) is used for the production of non-energy sector j. With data extracted from the Chinese energy statistical yearbooks, we calculate the weighted-average price of energy m, which is required for the productions in non-energy sectors, as ratios of the summation of all intermediate inputs of energy sector m in monetary units to the total use of energy m for non-energy sectors in physical units, expressed in 103 Yuan1 /MJ2 (Eq. (2)). This methodology can partially avoid the price differential within the intermediate demand for energy products. For more details of this methodology, refer to Park and Heo (2008) P ex im h Xm Ym þ Ym Ym cn ¼ 1 Xm,n E P ¼ ð2Þ Pm ESm EYm cn ¼ 1 Em,n
ð1Þ
where X is the total output vector, Y is the final consumption vector, and A is the direct input coefficients matrix, describing the relationship between all sectors of the economy. AX denotes the intermediate input vector which can be obtained by multiplying the direct input coefficient matrix by the total output vector. B is the Leontief inverse matrix (I A) 1. For calculating energy intensities, energy sectors should be represented both in monetary and physical terms in energy input–output tables (Bullard and Herendeen, 1975; Bullard et al., 1978; Park and Heo, 2008). Therefore, monetary input–output tables published by National Bureau of Statistics of China should be transformed into physical input–output tables with the help of energy prices. To achieve this goal, we use intermediate energy
Xm,j E Pm
ð3Þ
Direct energy intensities are calculated as ratios of direct energy consumption (in physic terms) to total inputs (in monetary terms), expressed in MJ/103 Yuan Pc En,j ð4Þ ej ¼ n ¼ 1 Xj where ej is the direct energy intensity of sector j, and ej is the element of the direct energy intensity row vector, e. Total or cumulative energy intensities are computed by multiplying the direct energy intensity row vector with the Leontief inverse matrix of the corresponding input–output table as follows: L ¼ eB
ð5Þ
where L is the total energy intensity row vector, whose element Li, is the total energy intensity of sector i, which shows the physical energy consumption required for the production of one unit in sector i. Energy embodied in international trade, which is defined as indirect energy exportation (and imports), can be calculated by 1 The average conversion rate is 8.1917 Yuan/1 US dollar in 2005 (http:// finance.people.com.cn/GB/1037/4061677.html). 2 In this paper, we use SI units (International System of Units). 1 Megajoule (MJ)¼ 1 106 J ¼2.3901 102 kcal (thermo-chemical kilocalories) ¼0.03412 kgce (kilogram coal equivalent).
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multiplying total energy intensity of non-energy sectors by non-energy sectors’ exportation (and importation) Eex ¼ LYex ex
ð6Þ ex
where E is the energy embodied in exports; Y is non-energy sectors’ exports. Hence, the energy embodied in net exports (Enex) can be evaluated as Enex ¼ LYnex ¼ LðYex þYim Þ
2.2. Structural decomposition analysis In general, a country’s indirect energy exportation fluctuates for a variety of reasons—such as, growth in international trade, changes in international trade structure, changes in technology, and energy efficiency improvement (Hoekstra and van den Bergh, 2002; Liu and Ang, 2007). In this paper, we apply the input– output structural decomposition analysis (SDA) to identify the driving factors for changes in the energy embodied in exports over time (Wood and Lenzen, 2009). To begin with, changes in the energy embodied in exports (DEex) from sectors, between a base year (period t) and a comparative year (period t 1), can be expressed in terms of changes of total energy intensities and exports’ change as follows: ex ex ex DEex ¼ Eex t Et1 ¼ Lt Y t L t1 Y t1 ex ex ¼ ðLt Lt1 ÞYex t þ Lt1 ðYt Y t1 Þ ex ex ¼ ðLt Lt1 ÞYt þ Lt1 ðYt Yex t1 Þ ex ex ex ex ¼ DLYex t þL t1 DY ¼ ðL t L t1 ÞY t1 þ Lt ðY t Yt1 Þ ex ex ¼ DLYt1 þ Lt DY
ð8Þ
From Eq. (8), changes in the energy embodied in exports (DEex) comprise the change effect of total energy intensities (DL) and the change effect of exports (DYex). Note that this structure decomposition is additive and non-unique, and it does not include interaction terms. We use the simple average of only two decomposition forms, the so-called polar forms (Dietzenbacher and Los, 1998), to solve the non-uniqueness problem as follows: ex ex DEex ¼ 1=2ðDLÞðYex t þY t1 Þ þ 1=2ðLt1 þ L t Þ DY
ð9Þ
From Eqs. (1) and (5), the change effect of total energy intensities (DL) can be expressed as Eq. (10). Hence, we separate the changes in total energy intensities into the effects caused by changes in direct energy intensities and the effects caused by changes in the Leontief inverse
DL ¼ et Bt et1 Bt1 ¼ DeBt þet1 DB ¼ DeBt1 þ et DB ¼ 1=2ðDeÞðBt þ Bt1 Þ þ1=2ðet þ et1 ÞðDBÞ
exports (DYex) can be further decomposed into the effect of exports volume (DYSex , which represents changes in the total volume of exports) and exports structural factor (DFex, which represents changes in exports’ structure) ex ex ex ex ex ex ex ex ex DYex ¼ Yex t Y t1 ¼ YS,t Ft YS,t1 Ft1 ¼ DYS Ft þ YS,t1 DF ex ex ex ex ex ex ex 1 1 ex ¼ DY ex Fex t1 þ Yt DF ¼ 2 ðDYS ÞðFt þ Ft1 Þ þ 2ðYS,t þ YS,t1 Þ DF
ð13Þ
ð7Þ
where Ynex is net exports, and imports (Yim) is represented with negative values in input–output tables.
ð10Þ
The change in the Leontief inverse, DB, can be further expressed in terms of the change in the direct input-coefficients matrix A (i.e., the underlying technologies change)
DB ¼ Bt Bt1 ¼ ðIAt Þ1 ðIAt1 Þ1 ¼ Bt ½ðIAt1 ÞðIAt ÞBt1 ¼ Bt ðAt At1 ÞBt1 ¼ Bt ðDAt ÞBt1 ð11Þ where DA represents the change effects of structure of intermediate inputs. Exports can be expressed as follows: .X X X ex Yiex ¼ Yiex Yex Yiex Fex ¼ YSex Fex Y ¼ ð12Þ P P ex where Fex ¼ Yex = Yiex and YSex ¼ Yi . Fex (column vector) represent the structure of exports with ratios of each sector’s export to the total volume of exports. Therefore, changes in
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Similar to the decomposition of the change in exports, changes in direct energy intensities (De) can be further decomposed into the change effect of energy consumption level and the energy consumption structural factor. Here, we define g ¼ ½gn,j as the direct energy intensity matrix showing the direct energy consumption of primary energy n required for the production of one unit in sector j. Because the total of primary energy consumption required for sector j can be obtained as X gn,j ð14Þ eS,j ¼ n
Hence, the direct energy intensity matrix can be further written as 1 g ¼ diagðeS ÞU diagðeS Þ Ug ¼ diagðeS ÞUG ð15Þ where diagðeS Þ is the diagonal matrix whose diagonal elements 1 are direct energy intensities and fdiagðeS Þg is the inverse of the diagonal intensity matrix. G is the energy intensity share matrix showing the ratio of primary energy n to the total of energy consumption required for the production of one unit of sector j
De ¼ et et1 ¼ eS,t Gt eS,t-1 Gt1 ¼ DeS Gt þeS,t1 DG ¼ DeS Gt1 þeS,t DG ¼ 12 ðDeS ÞðGt þGt1 Þ þ 12ðeS,t þ eS,t1 Þ DG
ð16Þ
Combining all the separate parts, we obtain the following expression for the decomposition of the energy embodied in exports: ex DEex ¼ 18ðDeS ÞðGt þ Gt1 ÞðBt þ Bt1 ÞðYex t þ Yt1 Þ ex þ 18ðeS,t þeS,t1 ÞðDGÞðBt þ Bt1 ÞðYt þYex t1 Þ nex þ 14ðet þ et1 ÞBt ðDAt ÞBt1 ðYnex þ Y Þ t t1 ex þ 14ðLt þLt1 ÞðDYSex ÞðFex t þFt1 Þ ex ex þ 14ðLt þLt1 ÞðYS,t þYS,t1 Þ DFex
ð17Þ
The changes in the energy embodied in exports are decomposed into the effects caused by changes in primary energy efficiency in the first term on the right-hand side of Eq. (17), the effects caused by the changes in primary energy consumption structure in the second term, the effects caused by the changes of structure of intermediate inputs in the third term, the effects due to changes in the total volume of exports in the fourth term, and the effects due to changes in exports’ structural is the last term. In this decomposition, all the terms are multiplied by a Leontief inverse matrix, so that the measurements capture both direct and indirect impacts of each causal expression on the energy embodied in exports and take account of the linkage through the induced intermediate demand. 2.3. Data sources Input–output tables used in this paper were originally developed by the National Bureau of Statistics of China, which include 62 sectors for 1992, 1997, 2002, and 2005, held at 2000 constant prices. Hence, energy intensities obtained by using them are comparable for different years and the requirement of decomposition studies (economic data in constant prices) can be
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3. Results 3.1. Economic development and international direct energy trade of China In the last decades, China’s economy has developed quickly, which is partly driven by the rapidly increasing international trade (Fig. 1). During the period from 1991 to 2007, China’s GDP increased from 2178 billion Yuan to 24,953 billion Yuan at current prices (Fig. 2). The rapidly increasing economy leads to accelerated requirements of energy, which makes China the second largest energy consumer in the world now. From the perspective of international direct-energy trade (Fig. 2), China became a net direct energy importing country in 1997. Since 2001, China’s direct-energy imports have increased quickly while its direct energy exports took a slightly downward trend. This opposite relationship
1400 1200 1000
Total Exports Total Imports
800 600 400 200
19
9 19 1 9 19 2 9 19 3 9 19 4 9 19 5 9 19 6 9 19 7 9 19 8 9 20 9 0 20 0 0 20 1 0 20 2 0 20 3 0 20 4 0 20 5 0 20 6 07
0
Fig. 1. China’s total value of imports and exports at current prices (billion US$).
30000 25000 20000 15000 10000 5000 0
9 19 1 9 19 2 9 19 3 9 19 4 9 19 5 9 19 6 9 19 7 9 19 8 9 20 9 0 20 0 0 20 1 0 20 2 0 20 3 0 20 4 0 20 5 0 20 6 07
satisfied. The input–output tables’ sectors were reclassified into 52 sectors, which are 44 non-energy sectors, 4 primary energy sectors (crude oil, coal products, hydro-electricity including electricity generated by nuclear materials, and natural gas) and 4 secondary energy sectors: coke, petroleum products (gasoline, kerosene, diesel oil, fuel oil, PLG, and others), coal-burning electricity, and heat. We obtain energy use data from the energy balance table of China (standard quantity) provided by the Chinese Energy Statistical Yearbook. We exclude new and renewable sources of energy from this study, due to the difficulty in allocating their consumption to individual sectors. For energy sectors in the energy input–output tables, we use intermediate energy input and final consumption data (in physical units) taken from the energy balance table of the Chinese Energy Statistical Yearbooks. Then using Eq. (2), we compute intermediate energy inputs (in physical units) for other non-energy sectors using nominal energy prices. In this paper, we use International System of Units (SI units). Therefore, we convert kilogram coal equivalent (kgce) into Megajoule (MJ) (1 MJ¼ 0.03412 kgce). Double-counting occurs in the use of transformed secondary energy sources such as petroleum products. For instance, the energy in petroleum products consumed in a sector is the same energy as the primary energy in the oil used by the producer of petroleum products. We use the term ‘‘direct energy intensity’’ to include all primary energy sources and externally transformed secondary energy sources (purchased petroleum products, purchased electricity, etc.), used directly by a sector to produce its output (Weber, 2009).
19
3960
Fig. 2. Development of GDP in China at current price (billion Yuan).
indicates China’s rising dependency on foreign energy, which crude oil and petroleum products play the main part. In 2006, China’s dependency on oil imports stood at 47% (National Bureau of Statistics of China, 2008).
3.2. Input–output results The direct and total energy intensities by industry for China in 1992, 1997, 2002, and 2005, which are expressed in MJ/103 Yuan in 2000 constant prices, are presented in Tables 1 and 2. Both of the tables also provide the average direct primary energy intensity and the average total primary energy intensity of all 52 industries. As shown in Table 1, the average direct primary energy intensity of 52 sectors decreased incessantly from 1992 to 1997, and from 1997 to 2002, but increased from 2002 to 2005. Just like direct primary energy intensities, the average total primary energy intensities of 52 sectors decreased from 1992 to 1997 and from 1997 to 2002, but increased from 2002 to 2005. By importing goods from other countries, China can avoid energy use. Therefore, in the calculation of embodied energy in imports, we assume that imported goods and domestic products have the same energy intensities in this study (Kagawa and Inamura, 2001; Li and Hewitt, 2008; Weber, 2009), and energy embodied in imports of non-energy goods is expressed as negative energy use. With this assumption, we evaluate the indirect energy use resulting from domestic consumption (rural and urban households), exports, and imports (Table 3). In Table 3, it is clear that the majority of energy embodied in goods is consumed by households. Besides households’ indirect energy consumption (the energy embodied in non-energy goods consumed by households), the energy embodied in exports is the other major source. After joining the World Trade Organization (WTO), China’s foreign trade maintained rapid growth, and the total international trade grew at an average annual rate of 24.3% during 2001–2007, which led to a high total volume of international trade, as much as 2.174 trillion US dollars in 2007 (National Bureau of Statistics of China, 2008). China has become the world’s largest exporter. With the rapid growth of international trade, the energy embodied in imports increased from 579.8 to 2554.55 EJ (shown as negative in Table 3 to indicate avoided energy use by importation) from 1992 to 2005, while the energy embodied in China’s exports increased from 588.69 to 2806.85 EJ, for a net increase in the energy embodied in exports from 8.9 to 252.3 EJ. Not only is China a net exporter of the energy embodied in international trade during the period from 1992 to 2005, but its exports are also, on average, substantially more intensive in energy than its imports. Considering that imported goods and domestic products are assumed to have the same energy intensities in this study, the numbers shown in Table 3 for imports are not a true representation of energy embodied in
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Table 1 Direct primary energy intensities of non-energy products. Sectors (MJ/103 Yuan)
1992
1997
2002
2005
Agriculture Mining and processing of ferrous metal ores Mining and processing of non-ferrous metal ores Mining and processing of non-metal ores and mining of other ores Processing and manufacture of food Manufacture of beverages and alcohol Manufacture of tobacco Manufacture of textile Manufacture of textile wearing apparel, footwear and caps Processing of timber & manufacture of furniture Manufacture of paper and paper products Printing, reproduction of recording media Manufacture of articles for culture, education and sport activities Manufacture of chemical manure products Manufacture of pesticides Manufacture of medicines Manufacture of chemical fibers Manufacture of rubber Manufacture of plastics Manufacture of raw chemical materials and chemical products Manufacture of glass and glass products Manufacture of ceramic products Manufacture of non-metallic mineral products Smelting and pressing of metals Manufacture of metal products Manufacture of machinery Manufacture of transport equipment Manufacture of electrical machinery and equipment Manufacture of computers Manufacture of audio–visual equipment Manufacture of communication and other electronic equipment Manufacture of measuring instruments and machinery Manufacture of office machinery Manufacture of artwork and other manufacturing Recycling and disposal of waste Production and supply of water Construction Transportation and storage Postal and telecommunication services Wholesale and retail trades Hotels and catering Financial and insurance services Real estate Other services Average direct energy intensity (52 sectors)
14.57 340.97 206.30 282.44 59.32 159.20 65.12 409.23 44.94 155.06 248.45 53.73 32.64 861.07 193.83 256.03 129.02 234.44 105.74 61.50 407.94 1066.85 1102.67 784.08 212.45 83.99 50.84 40.11 47.16 9.23 48.78 76.15 77.30 75.03 0.00 157.58 10.10 170.59 35.12 34.93 77.62 33.21 83.95 69.38 250.90
16.95 110.10 95.73 97.01 60.15 121.32 31.79 285.78 12.90 79.02 135.52 27.13 27.41 1185.96 209.69 398.51 40.52 96.43 96.96 34.26 396.70 259.02 666.60 377.75 146.78 65.14 38.47 81.56 4.00 8.73 19.88 22.49 16.47 130.86 0.00 113.03 12.01 46.07 8.97 15.00 48.59 8.92 58.33 58.08 201.18
29.12 90.05 79.66 54.54 27.78 71.97 9.25 288.42 9.21 62.21 76.81 11.85 15.12 599.55 152.24 211.30 22.71 304.73 60.09 25.87 205.62 160.51 357.44 219.66 94.33 45.76 27.01 36.39 3.70 1.94 9.83 10.55 4.47 75.83 0.00 99.61 11.91 34.97 24.94 16.37 38.97 6.84 33.27 46.96 143.90
29.79 98.49 88.23 64.54 25.81 80.77 13.02 272.57 8.95 64.01 81.48 13.80 14.86 698.49 183.93 211.70 31.18 269.17 77.64 31.02 212.29 176.84 287.14 253.33 101.02 50.18 30.25 39.30 3.76 1.39 10.14 9.50 3.97 103.35 0.00 84.01 11.03 30.68 21.08 10.27 46.92 6.90 29.34 50.43 173.64
imports. The energy embodied in imports would be smaller if the trading partners were actually less energy intensive than China, and vice versa for a more energy-intensive trading partner (Wiedmann et al., 2007; Weber, 2009).
3.3. Structural decomposition analysis results The proposed SDA models are applied (Eq. (17)) to explore all factors’ effects and their contributions to the changes in the energy embodied in exports during the three sub-periods between 1992 and 2005. Decomposition results are shown in Tables 4 and 5. The amount of the energy embodied in exports during the period from 1992 to 1997 increased by 175.46 EJ (Table 4). Changes in the direct primary energy efficiency, the primary energy consumption structure and the structure of intermediate inputs all decreased the energy embodied in exports, which accounts for 86.4%, 5.3% and 18.0% of the accumulated change of energy embodied in exports, respectively. But changes in export structure and total volume of exports both contributed to the increase of the energy embodied in exports, which
accounted for 3.9% and 205.8%, respectively. These results indicate that although energy efficiency increased, the decreasing proportion of coal in total primary energy consumption (Table 6) and the improvement of technology did have positive effects on reducing the energy embodied in exports, but the growth of international trade and the change of export structure had bigger impacts on increasing of energy embodied in exports. The increase of energy embodied in exports was 229.45 EJ during the period from 1997 to 2002. During this period, the primary energy efficiency increased and the proportion of coal in the total primary energy consumption decreased. These two factors produced negative effects on the increase of the energy embodied in exports. While changes in the structure of intermediate inputs, the growth of exports, and changes in export structure all led to positive effects on the increase of energy embodied in exports, and their accumulated effects were much bigger than that of changes both in direct primary energy efficiency and primary energy consumption structure. During the period from 2002 to 2005, the increase of the energy embodied in exports had reached 1813.25 EJ. All of the five factors had positive effects on the increase of the energy embodied in exports. Therefore, within these 3 years, the growth
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Table 2 Total primary energy intensities of non-energy products. Sectors (MJ/103Yuan)
1992
1997
2002
2005
Agriculture Mining and processing of ferrous metal ores Mining and processing of non-ferrous metal ores Mining and processing of non-metal ores and mining of other ores Processing and manufacture of food Manufacture of beverages and alcohol Manufacture of tobacco Manufacture of textile Manufacture of textile wearing apparel, footwear and caps Processing of timber & manufacture of furniture Manufacture of paper and paper products Printing, reproduction of recording media Manufacture of articles for culture, education and sport activities Manufacture of chemical manure products Manufacture of pesticides Manufacture of medicines Manufacture of chemical fibers Manufacture of rubber Manufacture of plastics Manufacture of raw chemical materials and chemical products Manufacture of glass and glass products Manufacture of ceramic products Manufacture of non-metallic mineral products Smelting and pressing of metals Manufacture of metal products Manufacture of machinery Manufacture of transport equipment Manufacture of electrical machinery and equipment Manufacture of computers Manufacture of audio–visual equipment Manufacture of communication and other electronic equipment Manufacture of measuring instruments and machinery Manufacture of office machinery Manufacture of artwork and other manufacturing Recycling and disposal of waste Production and supply of water Construction Transportation and storage Postal and telecommunication services Wholesale and retail trades Hotels and catering Financial and insurance services Real estate Other services Average total energy intensity (52 sectors)
134.63 596.92 437.24 600.13 411.71 296.43 105.94 1865.85 250.44 403.89 807.78 270.25 82.59 1057.72 258.85 3077.79 208.89 445.64 495.28 114.36 691.81 1098.85 2168.44 1276.19 880.50 2127.30 655.38 149.19 68.61 25.07 257.73 284.99 199.73 544.27 32.78 288.02 146.04 1870.64 47.77 718.27 670.51 972.97 866.71 930.21 756.69
206.73 285.29 303.71 316.27 379.93 217.74 77.76 1170.35 201.92 250.78 567.11 160.77 62.22 1418.03 282.81 2292.49 95.78 286.63 262.34 92.05 565.65 284.20 1013.56 596.98 691.78 1961.78 732.47 192.16 69.10 61.10 374.65 226.73 60.07 358.86 159.61 241.82 112.60 885.52 22.47 411.72 448.51 680.97 627.08 1144.14 573.96
246.15 196.62 172.34 185.30 252.97 113.62 27.70 611.15 119.22 190.72 322.76 131.25 33.50 699.30 182.68 1485.72 57.39 460.07 163.23 83.06 275.08 170.55 549.91 343.93 398.06 939.60 513.45 98.25 69.31 28.83 275.39 163.72 19.66 167.34 83.14 159.94 100.20 533.30 42.95 496.62 292.56 604.58 433.62 1004.88 406.81
309.51 179.45 256.27 203.15 271.69 165.26 44.66 688.87 190.47 270.49 473.51 184.00 40.88 854.79 232.38 2202.41 70.08 513.45 187.42 92.10 372.03 195.85 561.26 364.24 431.12 1423.13 838.74 152.29 165.36 23.37 537.37 414.05 24.39 261.33 156.13 169.47 126.08 472.99 46.10 403.73 349.09 791.29 326.92 1075.04 488.91
Table 3 Energy embodied in non-energy goods (EJ). 1992 Energy embodied in goods consumed by households Energy embodied in goods consumed by rural households Energy embodied in goods consumed by urban households Net embodied energy in international trade Energy embodied in exports Energy embodied in imports
1997
2002
2005
1147.34 491.54 655.80
1464.75 546.67 918.08
1556.19 437.20 1118.99
2621.52 633.73 1987.80
8.90 588.69 579.80
31.67 764.15 732.48
49.00 993.60 944.60
252.30 2806.85 2554.55
Unit: Exajoule (EJ) ¼ 1 1018 J ¼2.3901 1014 kcal (thermo-chemical kilocalories)¼ 34.12 million tons of coal equivalent.
of energy embodied in exports was about 10 times that from 1992 to 1997 and eight times that from 1997 to 2002, which indicates that there might have been deteriorations of energy efficiency and technology, rapid growth of exports, and increasing exportation of energy-intensive goods from 2002 to 2005. China’s energy intensity (energy consumption per unit GDP) declined steadily from 1980 to 2002 with an average decline of 5% per year. But China’s energy intensity increased from 2002 to 2005 with an average increase of 2% per year. China’s Tenth Five-Year period (from 2000 to 2005) was marked as a period of fast extensive
economic growth, as a result of China’s economic policies at that time which aimed at encouraging production and increasing fiscal revenue. Therefore, a large number of small-size companies in energy intensive industries which used outdated equipment with heavy energy consumption and pollution, were established, and the exports’ structure worsened notably. Tables 4 and 5 show that the energy embodied in exports increased within the 13 years in each sub-period, especially displaying a big change in the period from 2002 to 2005. Our decomposition analysis shows that almost all the increase of the
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Table 4 SDA results of changes in the energy embodied in exports. 1992–1997 1997–2002 2002–2005 Direct primary energy efficiency 151.52 Primary energy consumption structure 9.21 Structure of intermediate inputs 31.65 Structure of exports 6.8 Scale of exports 361.04 Total increment 175.46
139.1 10.86 3.57 7.18 368.66 229.45
85.03 5.05 233.66 31.68 1457.83 1813.25
Unit: EJ.
Table 5 SDA results of changes in the energy embodied in exports (percent). 1992–1997 1997–2002 2002–2005 Direct primary energy efficiency 86.4 Primary energy consumption structure 5.3 Structure of intermediate inputs 18.1 Structure of exports 3.9 Scale of exports 205.8 Total increment 100
60.6 4.7 1. 6 3.1 160.7 100
4.7 0.3 12.9 1.8 80.4 100
Table 6 The structure of primary energy consumption in China.
Total primary energy consumption (PJ) Proportion of coal (%) Proportion of oil (%) Proportion of natural gas (%) Proportion of hydro-electricity (%)
1992
1997
2002
2005
319.95 75.7 17.5 1.9 4.9
339.95 71.7 20.4 1.7 6.2
359.71 66.3 23.4 2.6 7.7
384.44 68.9 21 2.9 7.2
Unit: 1 Petajoule (PJ)¼ 1 1015 J¼ 2.3901 1011 kcal (thermo-chemical kilocalories) ¼ 34.12 Million tons of coal equivalent.
energy embodied in China’s exports came from the growth in export volumes during each sub-period, which caused China’s energy embodied in exports to increase by 2118.16 EJ from 1992 to 2005. The changes in the structure of China’s exports led to an additional 45.66 EJ increase. Although China increased the importation of energy from the global market and the changes in the structure of imports decreased China’s energy demand, the energy embodied in China’s net international trade still increased during the period from 1992 to 2005 (Table 3) because of China’s increased trade account surplus and the growth of energyintensive products’ exportation. China’s rapid growth of international trade succeeded in generating extensive growth in the national economy. But this economic growth was made at the expense of increasing energy consumption and deteriorating environment. China’s government must raise the priority of energy and the environment, and pay more attention to reducing exportation of energy-intensive products, promoting rational utilization of energy resources and improving energy utilization efficiency.
4. Conclusions and discussions Since the economic reform in the late 1970s, China has experienced dramatic growth in its economy, energy consumption, and international trade. Therefore, there is an increasing dependence on oil importation and an urgent need for energy saving for China. Although international trade has had a significant positive impact on China’s economic development, a
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lot of energy is also exported in the form of energy embodied in goods. Based on energy input–output tables, this paper calculates and analyzes direct primary energy intensities, total primary energy intensities, the energy embodied in goods consumed by domestic rural and urban households, the energy embodied in exports, and the energy embodied in imports (based on the assumption that imported and domestic goods have the same energy intensities). This paper also focuses on the decomposition of the change in the energy embodied in exports and ascertains its major driving forces, which are the effects of direct primary energy efficiency, primary energy consumption structure, structure of intermediate inputs, and the level and structure of exports. Results from this study show that international trade plays an important role both in China’s economic growth and in its energy consumption. A large amount of energy is embodied in exports, which is more than the energy embodied in imports. Findings indicate that China is a net exporter of energy. Moreover, China’s energy embodied in exports increased from 1992 to 2005, especially within the sub-period from 2002 to 2005. The augmentation of energy embodied in exports was mainly driven by the total volume of exports. The increasing export of energy intensive goods also produced positive effects on the increase of energy embodied in exports. In addition, we found that changes in the structure of intermediate inputs only created positive effects on the decrease of the energy embodied in exports over the period from 1992 to 1997, and the deteriorated energy efficiency and higher proportion of coal in total primary energy consumption were reasons driving the increase of energy embodied in exports during 2002–2005. Some policy implications could be deduced from these results. Although it has been partially counterbalanced by net energy importation, China’s increased trade account surplus has been accompanied by growth of energy embodied in exports. Unless trade and environmental policies are further integrated, the net amounts of carbon dioxide emissions and pollution embodied in China’s international trade will also increase, impacting the country’s total carbon dioxide emissions and pollution generation significantly. In any case, findings suggest that China’s international trade policies and energy policies should incorporate environmental concerns in order to harmonize the country’s economic development targets with its environmental priorities, including those related to rational utilization of natural resources.
Acknowledgements The authors are grateful to the Chinese Academy of Sciences for their data, and for financial support from the National Natural Science Foundation of China, under the Grant nos. 70773091 and 50539130.We also thank professors Karen R. Polenske and Xikang Chen for their comments on an earlier draft.
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Energy embodied in the international trade of China: An energy input–output analysis Hongtao Liu a,b,n, Youmin Xi a, Ju’e Guo a, Xia Li a,c a
Research Center of Chinese Management Issues, School of Management, Xi’an Jiaotong University, Xi’an 710049, China Department of Urban Studies and Planning, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Room 9-549, Cambridge, MA 02139, USA c School of Law, Xi’an Jiaotong University, Xi’an 710049, China b
a r t i c l e in fo
abstract
Article history: Received 20 July 2009 Accepted 5 March 2010 Available online 24 March 2010
Growing international trade has not only positively affected the People’s Republic of China’s (China’s) economic development, but also expanded the exportation of energy embodied in goods during their production. This energy flow out will pose risks to China’s rational utilization of natural resources as well as environmental protection. In this paper, we evaluate the energy embodied in goods produced in China during 1992–2005 and use input–output structural decomposition analysis to identify five key factors causing the changes of energy embodied in exports. (Direct primary energy efficiency, primary energy consumption structure, structure of intermediate inputs, structure of exports, and scale of exports.) For the three sub-periods of 1992–1997, 1997–2002, and 2002–2005, results show that China is a net exporter of energy, and the energy embodied in exports tends to increase over time. The expanding total volume of exports and increasing exports of energy-intensive goods tend to enlarge the energy embodied in exports within all three sub-periods, but these driving forces were offset by a considerable improvement of energy efficiency and changes in primary energy consumption structure from 1992 to 2002 and the effects of structure of intermediate input only in the sub-period from 1992 to 1997. From 2002 to 2005, the sharp augmentation of energy embodied in exports was driven by all the five factors. Our research has practical implications for the Chinese economy. Results of this study suggest that the energy embodied in trade should receive special attentions in energy policies design to limit the energy resource out-flow and pollution generation. & 2010 Elsevier Ltd. All rights reserved.
Keywords: Energy input–output analysis Embodied energy Structural decomposition analysis
1. Introduction With rapid economic development and international trade growth in the past decades, China has become the world’s top exporter, the second largest energy consumer, and the third largest economy (Asia Economic Institute, 2009; National Bureau of Statistics of China, 2008). All goods and services in an economy are directly and/or indirectly related to energy use and pollution (Lenzen, 1998; Machado et al., 2001; Peters and Hertwich, 2006). International trade might magnify natural resource depletion and environmental degradation (Shui and Harriss, 2006; Liang et al., 2007). China’s fast-growing economy and increased international trade have caused the overexploitation of resources and amplified dependency on oil imports (National Bureau of Statistics of China, 2008). Therefore, there is an urgent need for complete and
n Corresponding author at: Department of Urban Studies and Planning, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Room 9-549, Cambridge, MA 02139, USA. Tel.: + 1 617 999 8756. E-mail address: [email protected] (H. Liu).
0301-4215/$ - see front matter & 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.enpol.2010.03.019
balanced information on the energy use associated with international trade (Ma¨enpa¨a¨ and Siikavirta, 2007). Input–output analysis, a useful analytical framework developed by Wassily Leontief (1936), has been widely used in analyzing the energy embodied in goods and services (Hawdon and Pearson, 1995; Schaeffer and Leal de Sa´, 1996; Kondo and Moriguchi, 1998; Machado et al., 2001). For India, Murthy et al. (1997) analyzed carbon dioxide (CO2) emissions from energy consumption for different sectors in 1990, and Pachauri and Spreng (2002) analyzed direct and indirect energy requirements of households for the years 1983–1984, 1989–1990 and 1993–1994. For Australia, Lenzen (1998) described direct and indirect primary energy and greenhouse gas requirements. For Sydney, Lenzen et al. (2004) examined trends in energy consumption. For Brazil, Cohen et al. (2005) calculated the energy embodied in goods and services purchased by households. Input–output structural decomposition analysis (SDA), a major analytical tool that is traditionally used to study the observed changes in the level and mix of output (Rose and Casler, 1996), has also been used to identify the key factors of energy intensity and CO2 emission changes for multiple countries or regions
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(Casler and Rose, 1998; Chang et al., 2008; Limmeechokchai and Suksuntornsiri, 2007; Ang and Liu, 2001; Ang, 2004; Tuyet and Ishihara, 2006; Wood and Lenzen, 2009). For Japan, Nobuko (2004) examined the impact factors of CO2 emissions produced by Japanese industries between 1985 and 1995 by using input– output tables. For Spain, Llop (2007) made an in-depth analysis of the changes in Spanish emission multipliers during the period 1995–2000. For the United States, Weber (2009) analyzed aggregate energy use in 1997 and 2002 to discover the causes of changing energy usage and flows. For the OECD, Sun (1999) investigated the change of aggregate CO2 emissions from 1960 to 1995 based on a complete decomposition approach. For China, energy consumption and pollution generation have been investigated by a number of analyses (Vanden et al., 2004; Li et al., 2007; Liao et al., 2007; Peters et al., 2007). Polenske and McMichael (2002) identified the major differences in energy use and pollution generation among three generic coke-making technologies in China. Hu and Wang (2006) analyzed the energy efficiency of 29 administrative regions in China for the period of 1995–2002. Liu et al. (2007) analyzed the driving force behind China’s primary energy-related carbon intensity and measured the final energy-related carbon intensity in material production sectors. Ma and Stern (2008) analyzed changes in energy intensities in the period 1980–2003 and found that inter-fuel substitution contributed little to the changes in energy intensity. However, few analyses have focused on the energy embodied in China’s international trade and its driving factors. Within an input–output analytical framework, we explore energy flows into, out of, and within the Chinese economy over time, evaluate the impacts of international trade on energy use, and identify the underlying factors that contribute to modifying the energy embodied in exports from 1992 to 2005. This analysis will increase understanding of the relationship between international trade and energy requirements. Moreover, this paper aims to help policy makers design energy policies that enhance sustainable development for China.
2. Energy embodied in the international trade and decomposition
where for energy sector m (for column n), Xm is the total domestic ex im h is the exports; Ym is the imports; Ym is the total production; Ym domestic final demand; Xm,n is energy sector n’s direct requirement from energy sector m in monetary units; ESm is total energy consumption in physical units; EYm is energy use or energy consumption for final consumption in physical units; Em,n is energy sector n’s direct requirement from energy sector m in E physical units; c is the number of primary energy sectors; and Pm is the energy sector m’s weighted-average price for non-energy sectors. For example, the price of coal is used to quantify intermediate inputs of coal to produce non-energy goods, such as iron, steel, and chemical products. Thus, Em,j, the m energy (in physical units) used for the production of the jth non-energy sector (in physical units), can be computed as Em,j ¼
2.1. Energy input–output analysis In the last few decades, the conventional input–output analysis (IOA) developed by Wassily Leontief (1936) has been frequently used to analyze the energy embodied in goods and the factors underlying the changes in energy consumption (Casler and Hannon, 1989; Wu and Chen, 1990; Kagawa and Inamura, 2001; Pan et al., 2008). In the input–output model, the total output of an economy, X, can be expressed as the sum of intermediate consumption, AX, and final consumption, Y (Leontief, 1970), X ¼ AX þY ¼ ðIAÞ1 Y ¼ BY
input and output data for energy sectors and final consumption data provided in the energy balance table of China from the Chinese Energy Statistical Yearbooks. Then we compute intermediate energy inputs and outputs for other non-energy sectors using weighted-average energy prices, e.g., oil, coal products, hydroelectricity (including electricity generated by nuclear materials), and natural gas. In Eq. (2), we use m (row) and n (column) as subscripts to denote energy sectors. Xm,j represent how much of the m energy (in monetary units) is used for the production of non-energy sector j. With data extracted from the Chinese energy statistical yearbooks, we calculate the weighted-average price of energy m, which is required for the productions in non-energy sectors, as ratios of the summation of all intermediate inputs of energy sector m in monetary units to the total use of energy m for non-energy sectors in physical units, expressed in 103 Yuan1 /MJ2 (Eq. (2)). This methodology can partially avoid the price differential within the intermediate demand for energy products. For more details of this methodology, refer to Park and Heo (2008) P ex im h Xm Ym þ Ym Ym cn ¼ 1 Xm,n E P ¼ ð2Þ Pm ESm EYm cn ¼ 1 Em,n
ð1Þ
where X is the total output vector, Y is the final consumption vector, and A is the direct input coefficients matrix, describing the relationship between all sectors of the economy. AX denotes the intermediate input vector which can be obtained by multiplying the direct input coefficient matrix by the total output vector. B is the Leontief inverse matrix (I A) 1. For calculating energy intensities, energy sectors should be represented both in monetary and physical terms in energy input–output tables (Bullard and Herendeen, 1975; Bullard et al., 1978; Park and Heo, 2008). Therefore, monetary input–output tables published by National Bureau of Statistics of China should be transformed into physical input–output tables with the help of energy prices. To achieve this goal, we use intermediate energy
Xm,j E Pm
ð3Þ
Direct energy intensities are calculated as ratios of direct energy consumption (in physic terms) to total inputs (in monetary terms), expressed in MJ/103 Yuan Pc En,j ð4Þ ej ¼ n ¼ 1 Xj where ej is the direct energy intensity of sector j, and ej is the element of the direct energy intensity row vector, e. Total or cumulative energy intensities are computed by multiplying the direct energy intensity row vector with the Leontief inverse matrix of the corresponding input–output table as follows: L ¼ eB
ð5Þ
where L is the total energy intensity row vector, whose element Li, is the total energy intensity of sector i, which shows the physical energy consumption required for the production of one unit in sector i. Energy embodied in international trade, which is defined as indirect energy exportation (and imports), can be calculated by 1 The average conversion rate is 8.1917 Yuan/1 US dollar in 2005 (http:// finance.people.com.cn/GB/1037/4061677.html). 2 In this paper, we use SI units (International System of Units). 1 Megajoule (MJ)¼ 1 106 J ¼2.3901 102 kcal (thermo-chemical kilocalories) ¼0.03412 kgce (kilogram coal equivalent).
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multiplying total energy intensity of non-energy sectors by non-energy sectors’ exportation (and importation) Eex ¼ LYex ex
ð6Þ ex
where E is the energy embodied in exports; Y is non-energy sectors’ exports. Hence, the energy embodied in net exports (Enex) can be evaluated as Enex ¼ LYnex ¼ LðYex þYim Þ
2.2. Structural decomposition analysis In general, a country’s indirect energy exportation fluctuates for a variety of reasons—such as, growth in international trade, changes in international trade structure, changes in technology, and energy efficiency improvement (Hoekstra and van den Bergh, 2002; Liu and Ang, 2007). In this paper, we apply the input– output structural decomposition analysis (SDA) to identify the driving factors for changes in the energy embodied in exports over time (Wood and Lenzen, 2009). To begin with, changes in the energy embodied in exports (DEex) from sectors, between a base year (period t) and a comparative year (period t 1), can be expressed in terms of changes of total energy intensities and exports’ change as follows: ex ex ex DEex ¼ Eex t Et1 ¼ Lt Y t L t1 Y t1 ex ex ¼ ðLt Lt1 ÞYex t þ Lt1 ðYt Y t1 Þ ex ex ¼ ðLt Lt1 ÞYt þ Lt1 ðYt Yex t1 Þ ex ex ex ex ¼ DLYex t þL t1 DY ¼ ðL t L t1 ÞY t1 þ Lt ðY t Yt1 Þ ex ex ¼ DLYt1 þ Lt DY
ð8Þ
From Eq. (8), changes in the energy embodied in exports (DEex) comprise the change effect of total energy intensities (DL) and the change effect of exports (DYex). Note that this structure decomposition is additive and non-unique, and it does not include interaction terms. We use the simple average of only two decomposition forms, the so-called polar forms (Dietzenbacher and Los, 1998), to solve the non-uniqueness problem as follows: ex ex DEex ¼ 1=2ðDLÞðYex t þY t1 Þ þ 1=2ðLt1 þ L t Þ DY
ð9Þ
From Eqs. (1) and (5), the change effect of total energy intensities (DL) can be expressed as Eq. (10). Hence, we separate the changes in total energy intensities into the effects caused by changes in direct energy intensities and the effects caused by changes in the Leontief inverse
DL ¼ et Bt et1 Bt1 ¼ DeBt þet1 DB ¼ DeBt1 þ et DB ¼ 1=2ðDeÞðBt þ Bt1 Þ þ1=2ðet þ et1 ÞðDBÞ
exports (DYex) can be further decomposed into the effect of exports volume (DYSex , which represents changes in the total volume of exports) and exports structural factor (DFex, which represents changes in exports’ structure) ex ex ex ex ex ex ex ex ex DYex ¼ Yex t Y t1 ¼ YS,t Ft YS,t1 Ft1 ¼ DYS Ft þ YS,t1 DF ex ex ex ex ex ex ex 1 1 ex ¼ DY ex Fex t1 þ Yt DF ¼ 2 ðDYS ÞðFt þ Ft1 Þ þ 2ðYS,t þ YS,t1 Þ DF
ð13Þ
ð7Þ
where Ynex is net exports, and imports (Yim) is represented with negative values in input–output tables.
ð10Þ
The change in the Leontief inverse, DB, can be further expressed in terms of the change in the direct input-coefficients matrix A (i.e., the underlying technologies change)
DB ¼ Bt Bt1 ¼ ðIAt Þ1 ðIAt1 Þ1 ¼ Bt ½ðIAt1 ÞðIAt ÞBt1 ¼ Bt ðAt At1 ÞBt1 ¼ Bt ðDAt ÞBt1 ð11Þ where DA represents the change effects of structure of intermediate inputs. Exports can be expressed as follows: .X X X ex Yiex ¼ Yiex Yex Yiex Fex ¼ YSex Fex Y ¼ ð12Þ P P ex where Fex ¼ Yex = Yiex and YSex ¼ Yi . Fex (column vector) represent the structure of exports with ratios of each sector’s export to the total volume of exports. Therefore, changes in
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Similar to the decomposition of the change in exports, changes in direct energy intensities (De) can be further decomposed into the change effect of energy consumption level and the energy consumption structural factor. Here, we define g ¼ ½gn,j as the direct energy intensity matrix showing the direct energy consumption of primary energy n required for the production of one unit in sector j. Because the total of primary energy consumption required for sector j can be obtained as X gn,j ð14Þ eS,j ¼ n
Hence, the direct energy intensity matrix can be further written as 1 g ¼ diagðeS ÞU diagðeS Þ Ug ¼ diagðeS ÞUG ð15Þ where diagðeS Þ is the diagonal matrix whose diagonal elements 1 are direct energy intensities and fdiagðeS Þg is the inverse of the diagonal intensity matrix. G is the energy intensity share matrix showing the ratio of primary energy n to the total of energy consumption required for the production of one unit of sector j
De ¼ et et1 ¼ eS,t Gt eS,t-1 Gt1 ¼ DeS Gt þeS,t1 DG ¼ DeS Gt1 þeS,t DG ¼ 12 ðDeS ÞðGt þGt1 Þ þ 12ðeS,t þ eS,t1 Þ DG
ð16Þ
Combining all the separate parts, we obtain the following expression for the decomposition of the energy embodied in exports: ex DEex ¼ 18ðDeS ÞðGt þ Gt1 ÞðBt þ Bt1 ÞðYex t þ Yt1 Þ ex þ 18ðeS,t þeS,t1 ÞðDGÞðBt þ Bt1 ÞðYt þYex t1 Þ nex þ 14ðet þ et1 ÞBt ðDAt ÞBt1 ðYnex þ Y Þ t t1 ex þ 14ðLt þLt1 ÞðDYSex ÞðFex t þFt1 Þ ex ex þ 14ðLt þLt1 ÞðYS,t þYS,t1 Þ DFex
ð17Þ
The changes in the energy embodied in exports are decomposed into the effects caused by changes in primary energy efficiency in the first term on the right-hand side of Eq. (17), the effects caused by the changes in primary energy consumption structure in the second term, the effects caused by the changes of structure of intermediate inputs in the third term, the effects due to changes in the total volume of exports in the fourth term, and the effects due to changes in exports’ structural is the last term. In this decomposition, all the terms are multiplied by a Leontief inverse matrix, so that the measurements capture both direct and indirect impacts of each causal expression on the energy embodied in exports and take account of the linkage through the induced intermediate demand. 2.3. Data sources Input–output tables used in this paper were originally developed by the National Bureau of Statistics of China, which include 62 sectors for 1992, 1997, 2002, and 2005, held at 2000 constant prices. Hence, energy intensities obtained by using them are comparable for different years and the requirement of decomposition studies (economic data in constant prices) can be
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3. Results 3.1. Economic development and international direct energy trade of China In the last decades, China’s economy has developed quickly, which is partly driven by the rapidly increasing international trade (Fig. 1). During the period from 1991 to 2007, China’s GDP increased from 2178 billion Yuan to 24,953 billion Yuan at current prices (Fig. 2). The rapidly increasing economy leads to accelerated requirements of energy, which makes China the second largest energy consumer in the world now. From the perspective of international direct-energy trade (Fig. 2), China became a net direct energy importing country in 1997. Since 2001, China’s direct-energy imports have increased quickly while its direct energy exports took a slightly downward trend. This opposite relationship
1400 1200 1000
Total Exports Total Imports
800 600 400 200
19
9 19 1 9 19 2 9 19 3 9 19 4 9 19 5 9 19 6 9 19 7 9 19 8 9 20 9 0 20 0 0 20 1 0 20 2 0 20 3 0 20 4 0 20 5 0 20 6 07
0
Fig. 1. China’s total value of imports and exports at current prices (billion US$).
30000 25000 20000 15000 10000 5000 0
9 19 1 9 19 2 9 19 3 9 19 4 9 19 5 9 19 6 9 19 7 9 19 8 9 20 9 0 20 0 0 20 1 0 20 2 0 20 3 0 20 4 0 20 5 0 20 6 07
satisfied. The input–output tables’ sectors were reclassified into 52 sectors, which are 44 non-energy sectors, 4 primary energy sectors (crude oil, coal products, hydro-electricity including electricity generated by nuclear materials, and natural gas) and 4 secondary energy sectors: coke, petroleum products (gasoline, kerosene, diesel oil, fuel oil, PLG, and others), coal-burning electricity, and heat. We obtain energy use data from the energy balance table of China (standard quantity) provided by the Chinese Energy Statistical Yearbook. We exclude new and renewable sources of energy from this study, due to the difficulty in allocating their consumption to individual sectors. For energy sectors in the energy input–output tables, we use intermediate energy input and final consumption data (in physical units) taken from the energy balance table of the Chinese Energy Statistical Yearbooks. Then using Eq. (2), we compute intermediate energy inputs (in physical units) for other non-energy sectors using nominal energy prices. In this paper, we use International System of Units (SI units). Therefore, we convert kilogram coal equivalent (kgce) into Megajoule (MJ) (1 MJ¼ 0.03412 kgce). Double-counting occurs in the use of transformed secondary energy sources such as petroleum products. For instance, the energy in petroleum products consumed in a sector is the same energy as the primary energy in the oil used by the producer of petroleum products. We use the term ‘‘direct energy intensity’’ to include all primary energy sources and externally transformed secondary energy sources (purchased petroleum products, purchased electricity, etc.), used directly by a sector to produce its output (Weber, 2009).
19
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Fig. 2. Development of GDP in China at current price (billion Yuan).
indicates China’s rising dependency on foreign energy, which crude oil and petroleum products play the main part. In 2006, China’s dependency on oil imports stood at 47% (National Bureau of Statistics of China, 2008).
3.2. Input–output results The direct and total energy intensities by industry for China in 1992, 1997, 2002, and 2005, which are expressed in MJ/103 Yuan in 2000 constant prices, are presented in Tables 1 and 2. Both of the tables also provide the average direct primary energy intensity and the average total primary energy intensity of all 52 industries. As shown in Table 1, the average direct primary energy intensity of 52 sectors decreased incessantly from 1992 to 1997, and from 1997 to 2002, but increased from 2002 to 2005. Just like direct primary energy intensities, the average total primary energy intensities of 52 sectors decreased from 1992 to 1997 and from 1997 to 2002, but increased from 2002 to 2005. By importing goods from other countries, China can avoid energy use. Therefore, in the calculation of embodied energy in imports, we assume that imported goods and domestic products have the same energy intensities in this study (Kagawa and Inamura, 2001; Li and Hewitt, 2008; Weber, 2009), and energy embodied in imports of non-energy goods is expressed as negative energy use. With this assumption, we evaluate the indirect energy use resulting from domestic consumption (rural and urban households), exports, and imports (Table 3). In Table 3, it is clear that the majority of energy embodied in goods is consumed by households. Besides households’ indirect energy consumption (the energy embodied in non-energy goods consumed by households), the energy embodied in exports is the other major source. After joining the World Trade Organization (WTO), China’s foreign trade maintained rapid growth, and the total international trade grew at an average annual rate of 24.3% during 2001–2007, which led to a high total volume of international trade, as much as 2.174 trillion US dollars in 2007 (National Bureau of Statistics of China, 2008). China has become the world’s largest exporter. With the rapid growth of international trade, the energy embodied in imports increased from 579.8 to 2554.55 EJ (shown as negative in Table 3 to indicate avoided energy use by importation) from 1992 to 2005, while the energy embodied in China’s exports increased from 588.69 to 2806.85 EJ, for a net increase in the energy embodied in exports from 8.9 to 252.3 EJ. Not only is China a net exporter of the energy embodied in international trade during the period from 1992 to 2005, but its exports are also, on average, substantially more intensive in energy than its imports. Considering that imported goods and domestic products are assumed to have the same energy intensities in this study, the numbers shown in Table 3 for imports are not a true representation of energy embodied in
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Table 1 Direct primary energy intensities of non-energy products. Sectors (MJ/103 Yuan)
1992
1997
2002
2005
Agriculture Mining and processing of ferrous metal ores Mining and processing of non-ferrous metal ores Mining and processing of non-metal ores and mining of other ores Processing and manufacture of food Manufacture of beverages and alcohol Manufacture of tobacco Manufacture of textile Manufacture of textile wearing apparel, footwear and caps Processing of timber & manufacture of furniture Manufacture of paper and paper products Printing, reproduction of recording media Manufacture of articles for culture, education and sport activities Manufacture of chemical manure products Manufacture of pesticides Manufacture of medicines Manufacture of chemical fibers Manufacture of rubber Manufacture of plastics Manufacture of raw chemical materials and chemical products Manufacture of glass and glass products Manufacture of ceramic products Manufacture of non-metallic mineral products Smelting and pressing of metals Manufacture of metal products Manufacture of machinery Manufacture of transport equipment Manufacture of electrical machinery and equipment Manufacture of computers Manufacture of audio–visual equipment Manufacture of communication and other electronic equipment Manufacture of measuring instruments and machinery Manufacture of office machinery Manufacture of artwork and other manufacturing Recycling and disposal of waste Production and supply of water Construction Transportation and storage Postal and telecommunication services Wholesale and retail trades Hotels and catering Financial and insurance services Real estate Other services Average direct energy intensity (52 sectors)
14.57 340.97 206.30 282.44 59.32 159.20 65.12 409.23 44.94 155.06 248.45 53.73 32.64 861.07 193.83 256.03 129.02 234.44 105.74 61.50 407.94 1066.85 1102.67 784.08 212.45 83.99 50.84 40.11 47.16 9.23 48.78 76.15 77.30 75.03 0.00 157.58 10.10 170.59 35.12 34.93 77.62 33.21 83.95 69.38 250.90
16.95 110.10 95.73 97.01 60.15 121.32 31.79 285.78 12.90 79.02 135.52 27.13 27.41 1185.96 209.69 398.51 40.52 96.43 96.96 34.26 396.70 259.02 666.60 377.75 146.78 65.14 38.47 81.56 4.00 8.73 19.88 22.49 16.47 130.86 0.00 113.03 12.01 46.07 8.97 15.00 48.59 8.92 58.33 58.08 201.18
29.12 90.05 79.66 54.54 27.78 71.97 9.25 288.42 9.21 62.21 76.81 11.85 15.12 599.55 152.24 211.30 22.71 304.73 60.09 25.87 205.62 160.51 357.44 219.66 94.33 45.76 27.01 36.39 3.70 1.94 9.83 10.55 4.47 75.83 0.00 99.61 11.91 34.97 24.94 16.37 38.97 6.84 33.27 46.96 143.90
29.79 98.49 88.23 64.54 25.81 80.77 13.02 272.57 8.95 64.01 81.48 13.80 14.86 698.49 183.93 211.70 31.18 269.17 77.64 31.02 212.29 176.84 287.14 253.33 101.02 50.18 30.25 39.30 3.76 1.39 10.14 9.50 3.97 103.35 0.00 84.01 11.03 30.68 21.08 10.27 46.92 6.90 29.34 50.43 173.64
imports. The energy embodied in imports would be smaller if the trading partners were actually less energy intensive than China, and vice versa for a more energy-intensive trading partner (Wiedmann et al., 2007; Weber, 2009).
3.3. Structural decomposition analysis results The proposed SDA models are applied (Eq. (17)) to explore all factors’ effects and their contributions to the changes in the energy embodied in exports during the three sub-periods between 1992 and 2005. Decomposition results are shown in Tables 4 and 5. The amount of the energy embodied in exports during the period from 1992 to 1997 increased by 175.46 EJ (Table 4). Changes in the direct primary energy efficiency, the primary energy consumption structure and the structure of intermediate inputs all decreased the energy embodied in exports, which accounts for 86.4%, 5.3% and 18.0% of the accumulated change of energy embodied in exports, respectively. But changes in export structure and total volume of exports both contributed to the increase of the energy embodied in exports, which
accounted for 3.9% and 205.8%, respectively. These results indicate that although energy efficiency increased, the decreasing proportion of coal in total primary energy consumption (Table 6) and the improvement of technology did have positive effects on reducing the energy embodied in exports, but the growth of international trade and the change of export structure had bigger impacts on increasing of energy embodied in exports. The increase of energy embodied in exports was 229.45 EJ during the period from 1997 to 2002. During this period, the primary energy efficiency increased and the proportion of coal in the total primary energy consumption decreased. These two factors produced negative effects on the increase of the energy embodied in exports. While changes in the structure of intermediate inputs, the growth of exports, and changes in export structure all led to positive effects on the increase of energy embodied in exports, and their accumulated effects were much bigger than that of changes both in direct primary energy efficiency and primary energy consumption structure. During the period from 2002 to 2005, the increase of the energy embodied in exports had reached 1813.25 EJ. All of the five factors had positive effects on the increase of the energy embodied in exports. Therefore, within these 3 years, the growth
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Table 2 Total primary energy intensities of non-energy products. Sectors (MJ/103Yuan)
1992
1997
2002
2005
Agriculture Mining and processing of ferrous metal ores Mining and processing of non-ferrous metal ores Mining and processing of non-metal ores and mining of other ores Processing and manufacture of food Manufacture of beverages and alcohol Manufacture of tobacco Manufacture of textile Manufacture of textile wearing apparel, footwear and caps Processing of timber & manufacture of furniture Manufacture of paper and paper products Printing, reproduction of recording media Manufacture of articles for culture, education and sport activities Manufacture of chemical manure products Manufacture of pesticides Manufacture of medicines Manufacture of chemical fibers Manufacture of rubber Manufacture of plastics Manufacture of raw chemical materials and chemical products Manufacture of glass and glass products Manufacture of ceramic products Manufacture of non-metallic mineral products Smelting and pressing of metals Manufacture of metal products Manufacture of machinery Manufacture of transport equipment Manufacture of electrical machinery and equipment Manufacture of computers Manufacture of audio–visual equipment Manufacture of communication and other electronic equipment Manufacture of measuring instruments and machinery Manufacture of office machinery Manufacture of artwork and other manufacturing Recycling and disposal of waste Production and supply of water Construction Transportation and storage Postal and telecommunication services Wholesale and retail trades Hotels and catering Financial and insurance services Real estate Other services Average total energy intensity (52 sectors)
134.63 596.92 437.24 600.13 411.71 296.43 105.94 1865.85 250.44 403.89 807.78 270.25 82.59 1057.72 258.85 3077.79 208.89 445.64 495.28 114.36 691.81 1098.85 2168.44 1276.19 880.50 2127.30 655.38 149.19 68.61 25.07 257.73 284.99 199.73 544.27 32.78 288.02 146.04 1870.64 47.77 718.27 670.51 972.97 866.71 930.21 756.69
206.73 285.29 303.71 316.27 379.93 217.74 77.76 1170.35 201.92 250.78 567.11 160.77 62.22 1418.03 282.81 2292.49 95.78 286.63 262.34 92.05 565.65 284.20 1013.56 596.98 691.78 1961.78 732.47 192.16 69.10 61.10 374.65 226.73 60.07 358.86 159.61 241.82 112.60 885.52 22.47 411.72 448.51 680.97 627.08 1144.14 573.96
246.15 196.62 172.34 185.30 252.97 113.62 27.70 611.15 119.22 190.72 322.76 131.25 33.50 699.30 182.68 1485.72 57.39 460.07 163.23 83.06 275.08 170.55 549.91 343.93 398.06 939.60 513.45 98.25 69.31 28.83 275.39 163.72 19.66 167.34 83.14 159.94 100.20 533.30 42.95 496.62 292.56 604.58 433.62 1004.88 406.81
309.51 179.45 256.27 203.15 271.69 165.26 44.66 688.87 190.47 270.49 473.51 184.00 40.88 854.79 232.38 2202.41 70.08 513.45 187.42 92.10 372.03 195.85 561.26 364.24 431.12 1423.13 838.74 152.29 165.36 23.37 537.37 414.05 24.39 261.33 156.13 169.47 126.08 472.99 46.10 403.73 349.09 791.29 326.92 1075.04 488.91
Table 3 Energy embodied in non-energy goods (EJ). 1992 Energy embodied in goods consumed by households Energy embodied in goods consumed by rural households Energy embodied in goods consumed by urban households Net embodied energy in international trade Energy embodied in exports Energy embodied in imports
1997
2002
2005
1147.34 491.54 655.80
1464.75 546.67 918.08
1556.19 437.20 1118.99
2621.52 633.73 1987.80
8.90 588.69 579.80
31.67 764.15 732.48
49.00 993.60 944.60
252.30 2806.85 2554.55
Unit: Exajoule (EJ) ¼ 1 1018 J ¼2.3901 1014 kcal (thermo-chemical kilocalories)¼ 34.12 million tons of coal equivalent.
of energy embodied in exports was about 10 times that from 1992 to 1997 and eight times that from 1997 to 2002, which indicates that there might have been deteriorations of energy efficiency and technology, rapid growth of exports, and increasing exportation of energy-intensive goods from 2002 to 2005. China’s energy intensity (energy consumption per unit GDP) declined steadily from 1980 to 2002 with an average decline of 5% per year. But China’s energy intensity increased from 2002 to 2005 with an average increase of 2% per year. China’s Tenth Five-Year period (from 2000 to 2005) was marked as a period of fast extensive
economic growth, as a result of China’s economic policies at that time which aimed at encouraging production and increasing fiscal revenue. Therefore, a large number of small-size companies in energy intensive industries which used outdated equipment with heavy energy consumption and pollution, were established, and the exports’ structure worsened notably. Tables 4 and 5 show that the energy embodied in exports increased within the 13 years in each sub-period, especially displaying a big change in the period from 2002 to 2005. Our decomposition analysis shows that almost all the increase of the
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Table 4 SDA results of changes in the energy embodied in exports. 1992–1997 1997–2002 2002–2005 Direct primary energy efficiency 151.52 Primary energy consumption structure 9.21 Structure of intermediate inputs 31.65 Structure of exports 6.8 Scale of exports 361.04 Total increment 175.46
139.1 10.86 3.57 7.18 368.66 229.45
85.03 5.05 233.66 31.68 1457.83 1813.25
Unit: EJ.
Table 5 SDA results of changes in the energy embodied in exports (percent). 1992–1997 1997–2002 2002–2005 Direct primary energy efficiency 86.4 Primary energy consumption structure 5.3 Structure of intermediate inputs 18.1 Structure of exports 3.9 Scale of exports 205.8 Total increment 100
60.6 4.7 1. 6 3.1 160.7 100
4.7 0.3 12.9 1.8 80.4 100
Table 6 The structure of primary energy consumption in China.
Total primary energy consumption (PJ) Proportion of coal (%) Proportion of oil (%) Proportion of natural gas (%) Proportion of hydro-electricity (%)
1992
1997
2002
2005
319.95 75.7 17.5 1.9 4.9
339.95 71.7 20.4 1.7 6.2
359.71 66.3 23.4 2.6 7.7
384.44 68.9 21 2.9 7.2
Unit: 1 Petajoule (PJ)¼ 1 1015 J¼ 2.3901 1011 kcal (thermo-chemical kilocalories) ¼ 34.12 Million tons of coal equivalent.
energy embodied in China’s exports came from the growth in export volumes during each sub-period, which caused China’s energy embodied in exports to increase by 2118.16 EJ from 1992 to 2005. The changes in the structure of China’s exports led to an additional 45.66 EJ increase. Although China increased the importation of energy from the global market and the changes in the structure of imports decreased China’s energy demand, the energy embodied in China’s net international trade still increased during the period from 1992 to 2005 (Table 3) because of China’s increased trade account surplus and the growth of energyintensive products’ exportation. China’s rapid growth of international trade succeeded in generating extensive growth in the national economy. But this economic growth was made at the expense of increasing energy consumption and deteriorating environment. China’s government must raise the priority of energy and the environment, and pay more attention to reducing exportation of energy-intensive products, promoting rational utilization of energy resources and improving energy utilization efficiency.
4. Conclusions and discussions Since the economic reform in the late 1970s, China has experienced dramatic growth in its economy, energy consumption, and international trade. Therefore, there is an increasing dependence on oil importation and an urgent need for energy saving for China. Although international trade has had a significant positive impact on China’s economic development, a
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lot of energy is also exported in the form of energy embodied in goods. Based on energy input–output tables, this paper calculates and analyzes direct primary energy intensities, total primary energy intensities, the energy embodied in goods consumed by domestic rural and urban households, the energy embodied in exports, and the energy embodied in imports (based on the assumption that imported and domestic goods have the same energy intensities). This paper also focuses on the decomposition of the change in the energy embodied in exports and ascertains its major driving forces, which are the effects of direct primary energy efficiency, primary energy consumption structure, structure of intermediate inputs, and the level and structure of exports. Results from this study show that international trade plays an important role both in China’s economic growth and in its energy consumption. A large amount of energy is embodied in exports, which is more than the energy embodied in imports. Findings indicate that China is a net exporter of energy. Moreover, China’s energy embodied in exports increased from 1992 to 2005, especially within the sub-period from 2002 to 2005. The augmentation of energy embodied in exports was mainly driven by the total volume of exports. The increasing export of energy intensive goods also produced positive effects on the increase of energy embodied in exports. In addition, we found that changes in the structure of intermediate inputs only created positive effects on the decrease of the energy embodied in exports over the period from 1992 to 1997, and the deteriorated energy efficiency and higher proportion of coal in total primary energy consumption were reasons driving the increase of energy embodied in exports during 2002–2005. Some policy implications could be deduced from these results. Although it has been partially counterbalanced by net energy importation, China’s increased trade account surplus has been accompanied by growth of energy embodied in exports. Unless trade and environmental policies are further integrated, the net amounts of carbon dioxide emissions and pollution embodied in China’s international trade will also increase, impacting the country’s total carbon dioxide emissions and pollution generation significantly. In any case, findings suggest that China’s international trade policies and energy policies should incorporate environmental concerns in order to harmonize the country’s economic development targets with its environmental priorities, including those related to rational utilization of natural resources.
Acknowledgements The authors are grateful to the Chinese Academy of Sciences for their data, and for financial support from the National Natural Science Foundation of China, under the Grant nos. 70773091 and 50539130.We also thank professors Karen R. Polenske and Xikang Chen for their comments on an earlier draft.
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