Review on Energy Resilience

Energy Policy 49 (2012) 751–758

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Energy Policy

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Embodied energy use in China’s industrial sectors

Zhu Liu a,b, Yong Geng a,n, Soeren Lindner c, Hongyan Zhao a,b, Tsuyoshi Fujita d, Dabo Guan a,e

a Key Lab on Pollution Ecology and Environmental Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China b Graduate University of Chinese Academy of Sciences, Beijing 100049, China c Department of Land Economy, University of Cambridge, CB3 9EP, United Kingdom d National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Japan e School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, United Kingdom

H I G H L I G H T S

c A hybrid IO-LCA model was employed to analyze China’s energy use at sectoral level. c A case study on China’s sectoral energy consumption is done. c Construction and service sectors are actually energy intensive from the supply chain perspectives. c Upstream and downstream ectoral collaboration along the whole supply chain is necessary. c Energy conservation policies should be based upon a comprehensive analysis on sectoral energy use.

a r t i c l e i n f o

Article history:

Received 21 January 2012

Accepted 11 July 2012 Available online 3 August 2012

Keywords:

Energy consumption

EIO model

Production and consumption

15/$ - see front matter & 2012 Elsevier Ltd. A

x.doi.org/10.1016/j.enpol.2012.07.016

esponding author. Tel.: þ86 24 83970372; fa

ail address: [email protected] (Y. Geng).

a b s t r a c t

As the world’s top energy consumer, China is facing a great challenge to solve its energy supply issue. In

this paper energy use from all industrial sectors in China’s economy of 2007 was explored by

conducting an extended environmental input–output analysis. We compare the energy consumption

embodied in the final demand for goods and services from 29 sectors with the energy demand required

for the actual production process in each sector. Two different viewpoints for sectoral energy use have

been presented: energy use is directly allocated to the producer entity, and energy use is reallocated to

sector’s supply chain from consumption perspective. Our results show that considerable amount of

energy use is embodied in the supply chain, especially for ‘‘Construction’’ and ‘‘Other Service Activities’’

sectors, which is not detected if energy use is allocated on a production basis. When further dividing

embodied energy consumption into direct energy consumption and indirect energy consumption, total

indirect energy consumption is much higher than that of total direct energy consumption, accounting

for 80.6% of total embodied energy consumption in 2007. Our results provide a more holistic picture on

sectoral energy consumption and therefore can help decision-makers make more appropriate policies.

& 2012 Elsevier Ltd. All rights reserved.

1. Introduction

With rapid economic development and increasingly improved living standards, China is now the world’s top consumer of primary energy and CO2 emitter (Guan et al., 2009), accounting for 20% of the global energy consumption (British Petroleum (BP), 2011). Seventy percent of China’s primary energy consumption was from coal in 2009, with a total consumption of 3.02 Bt. Heavily depending on coal consumption as China’s primary energy source results in many negative environmental and health effects such as climate change, respiratory diseases, acidic rain, air

ll rights reserved.

x: þ86 24 83970371.

pollution, and solid wastes. Moreover, the Gross Domestic Pro- duct per unit energy consumption (energy efficiency) in China is just 60% of that in India, and 47% of that in Japan (international constant price) (World Bank, 2011). Since China will keep rapid economic growth in the next decades, total energy consumption will increase rapidly if energy efficiency cannot be improved simultaneously (Guan et al., 2008). Hence, it is important to control the vastly growing energy consumption by improving energy efficiency and by increasing the use of renewable energy.

To meet these challenges, the Chinese government has launched several programs to promote energy efficiency. The well-known ‘‘national energy intensity targets’’ were announced by the National Development and Reform Commission (NDRC) and were coupled with the national ‘‘Five-Year Social and Economic Development Plan’’ (Geng 2011). According to China’s

Z. Liu et al. / Energy Policy 49 (2012) 751–758752

11th Five-Year Plan (2006–2010), energy efficiency should have been improved by 20% during the period and was actually improved by 19.1% (National Development and Reform Commission (NDRC), 2011b). Similarly, the 12th Five-Year Plan (2011–2015) has set the energy efficiency target to 16% energy intensity reduction (National Development and Reform Commission (NDRC), 2011a). Each provincial government received its own reduction target based upon its GDP level and should pursue such a target by considering its own realities. For instance, to improve the overall energy efficiency, both national and local governments had closed a large number of inefficient power plants and industrial factories and replaced them with more efficient equipment during 2005–2010. Facilities with a total production capacity of 100 Mt of iron, 55 Mt of steel, 250 Mt of cement and 50 Mt of coal-burning power generation have been shut down or replaced (Xinhuanet, 2007).

However, most of these efforts focused on traditional energy- intensive sectors such as steel and cement; little attention has been paid to the hidden drivers for such heavy industrial production. Ignorance of the conveying effect through the whole supply chain can undermine the efforts for efficiency improve- ment in these energy-intensive sectors. Although significant energy efficiency improvement in these energy-intensive sectors has been made, the total industrial production and energy consumption from these sectors are still increasing due to the higher demand of their products. For instance, the growth rate of cement and steel production had been higher than the rate of GDP growth (10.52%) during 2005–2010, achieving 12.28% (Kong, 2012) for cement and 11.98% (Guo and Zhang, 2012) for steel, respectively. In addition, the lack of attention to the related effects from the supply chain may even cause inefficient energy consumption. For example, the Chinese government launched an ambitious target to reduce its energy intensity by 20% during 2005–2010 in 2004 (National Development and Reform Commission (NDRC), 2007). This reduction was adjusted for each province and was implemented as a ‘‘top-down’’ mandatory approach. Under such conditions, several regional officials had to take actions to ration the power supply in the second half of 2010 to reach their targets. Thus, factories within these regions had to buy diesel-burning power generators to maintain their normal operation, resulting in a national diesel shortage (Qiu, 2011).

With the above background, it is crucial to study how different industrial sectors use energy for their operations so that appro- priate national regulations and standards can be enacted to promote energy efficient production. Therefore, a comprehensive analysis of sectoral energy consumption is required, which should not only focus on the direct energy consumption activities but also consider the indirect activities potentially causing energy consumption throughout the whole supply chain, namely, the embodied energy consumption (direct plus indirect) perspective (Bullard and Herendeen, 1975; Peters, 2008; Skelton et al., 2011). One sector’s embodied energy consumption includes both energy consumption caused by final demand (direct energy consump- tion) and energy consumption caused by other sector’s activities throughout the supply chain (indirect energy consumption) (Brown and Herendeen, 1996).The embodied energy consumption provides a complete picture that does not only consider the direct energy consumption primarily due to final demand, but also identifies the drivers of the energy consumption and quantifies the amount of energy usage for which every sector is responsible (Leontief, 1970; Skelton et al., 2011). Such an analysis can facilitate policy-makers to understand how embodied energy consumption occurs along the entire supply chain so that an appropriate energy management policy for industrial sectors can be raised.

In this paper, the embodied energy consumption among China’s 29 industrial sectors was estimated by conducting an extended environmental input–output analysis. First, we selec- tively review the method of our input–output analysis. Then, we quantify and present the embodied energy consumption for 29 industrial sectors in China’s economic system. The main focus of this paper is to present our policy implications for sectoral energy conservation policy. Finally we draw our conclusions.

2. Methods and data

2.1. Selective review of environmental input–output analysis

A comprehensive analysis of energy consumption in industry supply chains requires an appropriate method that does not only focus on the energy consumption due to final demand of one single industrial sector but also consider the use of energy in intermediate production processes by other industrial sectors that are included in the supply chain. The standard Leontief input–output (I–O) model has been extended to the so-called environmental extend input–output model (EIO) to capture energy consumption flows in the economy (Leontief, 1936, 1970). EIO describes the energy consumption required to produce a unit of economic output (goods and services) driven by final demand. This tool allows the calculation of the direct energy consumption by a sector’s final demand as well as all indirect energy consumption from other sectors within the same supply chain (Duchin, 1998; Hubacek et al., 2009). This ‘‘top-down’’ approach for assessing environmental impacts of the whole economy has been widely applied for national energy analyses after the energy crisis in the early 1970s (Leontief, 1970; Lin and Polenske, 1995; Peters and Hertwich, 2008). Interactions between economic activities, the associated direct and indirect energy consumption and related environmental impacts can be explicitly determined by the input–output relationship described by Leon- tief and its extension to cover environmental impacts (e.g., Duchin, 2009; Feng et al., 2009, 2010; Guan and Hubacek, 2007, 2008; Hubacek et al., 2009; Weber et al., 2008). The input–output analysis has been extended to cover interregional and interna- tional trade in multi-regional input–output models (MRIO) (Leontief, 1970; Minx et al., 2009; Peters and Hertwich, 2008; Peters et al., 2011; Wiedmann et al., 2010); this type of model has been used to analyze international embodied energy consump- tion and related CO2 emissions inventories in the context of the Kyoto Protocol from the perspective of either consumers of goods and services or producers. For a single system boundary, energy consumption associated with the production process comprises the production entity (the production energy use) and the total energy consumption in its production activity (the embodied energy consumption). Several scholars have conducted their studies of embodied energy consumption in production activities in China. For example, Lin and Polenske (1995) explained energy consumption changes between 1981 and 1987 in China by analyzing effective changes in the production technologies as well as the final demand shift on the consumer side. Liu et al. (2009) conducted an energy input–output analysis in China to evaluate the indirect energy consumption of rural and urban households and studied how energy policies influenced final prices; they concluded that energy efficiency improvements did not only serve as a means to reach energy conservation goals but also have a positive impact on household income. Another example of studying the embodied energy in the supply chain of one single sector is the analysis on the environmental impacts of the coke-making process in China by using an input–output process model (Polenske and McMichael, 2002); they discovered

Z. Liu et al. / Energy Policy 49 (2012) 751–758 753

changes in the production technology of the supplying sectors and the subsequent impacts. Similar studies were also conducted by Liang et al. (2011).

This study used the most recently available input–output tables (2007) and constructed the EIO model to reveal China’s sectoral embodied energy consumption; our study focuses on China’s sectoral direct and indirect energy consumption and presents the related policy implications for energy conservation and efficiency in the national Five-Year plan.

2.2. EIO model development

The EIO model captures the energy consumption of each economic sector from supply chain perspectives. The total output of one economy is expressed:

X ¼Zþy¼ AXþy ð1Þ

X represents total economic output, which can be expressed as a vector; Z represents the intermediate demand matrix; y repre- sents the final demand vector, including the components of ‘‘rural and urban households consumption’’, ‘‘government consump- tion’’, ‘‘gross capital formation’’, ‘‘export’’ and ‘‘others’’; and A represents the economy’s direct demand matrix. Matrix A describes the relationship between all sectors of the economy. Assuming that (I�A) is nonsingular, then the total economic output vector X can be expressed by Eq. (2):

X ¼ I�Að Þ �1

y ð2Þ

I represents the identity matrix, (I�A)�1 is the Leontief inverse. Eq. (2) illustrates the gross output needed to satisfy both the final consumption ‘‘y’’ and the corresponding intermediate consump- tion ‘‘(I�A)�1’’ from each economic sector.

Table 1 Sectors classification for Chinese ecomony.

Group code Group Sectoral code Sector name

A Agriculture 1 Farming, fores

B Mining 2 Coal mining an

3 Petroleum and

4 Ferrous metals

5 Other metals m

C Manufacturing 6 Food processin

7 Textile

8 Garments and

9 Timber proces

10 Paper printing

11 Petroleum pro

12 Raw chemical

medical and p

13 Nonmetal min

14 Smelting and p

15 Metal product

16 Ordinary and s

17 Transportation

18 Electric equipm

19 Electronic and

20 Instruments, m

21 Handicraft ma

22 Waste collecti

D Power and heating supply 23 Electricity pow

24 Gaseous fuels

25 Water treatme

E Construction 26 Construction

F Tertiary industry (Service) 27 Transport, logi

28 Wholesale, ret

29 Other service a

The EIO method combines the economic IO model with sectoral environmental impacts by multiplying the total economic output by each sector’s energy intensity (energy consumption per unit economic output from each sector i). The total (both direct and indirect) energy consumption can be expressed by Eq. (3):

E¼FX ¼FyþFAyþFA 2 yþFA

3 yþFA

4 y � � � ¼F I�Að Þ

�1 y ð3Þ

E represents the matrix of the total embodied energy consump- tion; F represents the factor vector of the energy intensity for each sector. Fy is the direct energy consumption due to final demand, FAy is the first round of indirect energy consumption due to intermediate industrial activities. FA2y, FA3y, FA4y� � � (Infinite recursive reduction series of FAjy) are the second, third, fourth, y round indirect energy consumption of intermediate activates. F can be calculated by Eq. (4):

Fi ¼Di=Xi ð4Þ

Fi represents the intensity factor of sector i; Di represents the production energy consumption for sector i; Xi represents the total economic output from sector i.

2.3. Data sources

In this study, we adopted the most recently available input– output table, namely, the one for the year of 2007 (National Bureau of Statistics of China (NBSC), 1996–2010), covering 42 economic sectors in total. Production energy consumption data from each sector were extracted from the Chinese Energy Statis- tics Year Book (CESYB) (National Bureau of Statistics of China (NBSC), 1995–2010). The input–output table is available at 42 industrial sectors in details, while the energy consumption data cover 29 sectors. We aggregate the 42 economic sectors into 29 sectors to keep the two datasets consistent. Table 1 presents the

try, animal husbandry, fishery and water conservancy

d dressing

natural gas extraction

mining and dressing

ining and dressing

g, food production, beverage production, tobacco processing

other fiber production, leather, furs, feather and related production

sing, bamboo, cane, palm and straw production, furniture manufacturing

, educational and sports goods production

cessing and coking, gas production and supply

materials and chemical production,

harmaceutical production, chemical fiber, rubber production, plastic production

eral production

ressing of ferrous and nonferrous metals

s

pecial equipment

equipment

ent and machinery

telecommunications equipment

eters, cultural and office machinery

nufacturing and other manufacturing products

on, separation, processing & treatment

er/heating supply

production and supply

nt and supply

stics, postal and telecommunication services

ail trade, hotels, catering service

ctivities

Table 2 Sectoral energy mix in China.

Code Coala Cokea Crude oila Gasolinea Kerosenea Diesela Fuel oila Natural gasb Electricityc

1 2338 82 0 247 1 1875 1 0 979 2 16518 75 0 20 3 57 6 5 610 3 343 0 1204 34 0 170 35 91 316 4 213 126 0 10 2 43 1 0 516 5 587 16 0 5 1 57 1 0 173 6 2938 16 1 36 1 86 45 3 634 7 2393 4 0 22 2 39 47 1 1142 8 299 2 0 17 1 41 22 0 201 9 386 3 0 10 1 19 3 0 181

10 3432 11 1 22 2 40 37 1 564 11 25656 98 30309 27 2 46 396 27 416 12 14281 2287 2328 90 6 187 470 227 3930 13 17105 258 15 35 3 233 606 31 1884 14 25139 26258 0 37 4 132 263 20 6153 15 265 95 0 26 2 48 17 1 688 16 812 648 0 60 6 76 15 7 687 17 742 116 0 45 8 62 12 7 424 18 139 19 0 25 1 44 15 2 347 19 126 1 0 15 1 46 32 7 487 20 20 3 0 5 1 8 0 0 62 21 451 4 0 6 1 11 3 0 294 22 6 3 0 0 0 1 1 0 11 23 131923 7 8 21 0 267 604 71 4642 24 1471 32 0 3 0 9 6 9 46 25 31 0 0 4 0 2 0 0 224 26 565 18 0 199 0 434 16 2 309 27 685 1 164 2763 1130 6794 1390 17 532 28 868 71 0 352 5 604 25 17 930 29 811 7 0 950 43 858 12 16 1709

a Unit: 104 t. b Unit: 108 m3. c Unit: 108 kW h (kilo-watts-hours).

Fig. 1. Production energy use (extracted from the CESYB) vs. embodied energy consumption(calculated by the EIO model) for 6 sector groups. (Units: Mt SCE).

Z. Liu et al. / Energy Policy 49 (2012) 751–758754

29 sectors classification and more aggregated 6 sector groups. This classification principle has been widely used in IO-based energy and carbon footprint research in China (Chang et al., 2010; Chen and Zhang, 2010; Zhang, 2010). Based on equation 5, A is a matrix with 29�29 elements, Y^ is a diagonal matrix with the values of final energy demand along its diagonal, F is a column vector with energy intensity data of 29 sectors.

The mix of energy consumption from each sector was listed in Table 2. There are 9 types of energy sources: raw coal, coke, crude oil, gasoline, kerosene, diesel, fuel oil, natural gas and electricity. It should be noted that the final electricity consumption was counted as the energy consumption from electricity sector, instead of the primary energy consumption for power generation. The total amount of energy consumption from each sector can be converted into the Standard Coal Equivalent (SCE), based on the calorific value of various energy types.

3. Results

3.1. Pattern of embodied energy consumption

Fig. 1 depicts the comparison results between production energy use and embodied energy consumption for 6 industrial groups, and Fig. 2 depicts the comparison results for 29 economic sectors.

In this study, a system boundary was set up according to China’s territorial boundary, and energy embodied in imports was not included (excluded in the final demand Y), thus the sum of all sector’s production energy use and the sum of their embodied energy consumption are equal. The embodied energy consumption for each sector was the energy consumption reallocated through this sector’s supply chain, thus significant differences exist between production energy use and embodied energy consumption for 6 groups and 29

sectors. From Fig. 1, it is very clear that ‘‘Manufacturing’’ (Group C) industry was the main contributor to total production energy use, while ‘‘Manufacturing’’ (Group C), ‘‘Construction’’ (Group E) and ‘‘Service Industry’’ (Group F) were the three main contributors to total embodied energy consumption. Particularly, ‘‘Manufacturing’’ (Group C) industry dominated both production energy use and embodied energy consumption, accounting for 65.8% of the total amount of production energy use and 50.4% of total amount of embodied energy consumption.

With respect to the 29 economic sectors (Fig. 2), sectors of ‘‘Petroleum Processing and Coking, Gas Production and Supply’’ (No. 11), ‘‘Raw Chemical Materials and Chemical Production, Medical and Pharmaceutical Production, Chemical Fiber, Rubber Production, Plas- tic Production’’ (No. 12),‘‘Nonmetal Mineral Production’’ (No. 13), ‘‘Smelting and Pressing of Ferrous and Nonferrous Metals’’ (No. 14), ‘‘Electricity Power/Heating Supply’’ (No. 23) and ‘‘Transport, Logistics,

Z. Liu et al. / Energy Policy 49 (2012) 751–758 755

Postal and Telecommunications Services’’ (No. 27) are the greatest contributors to the total production energy use, accounting for 70% of the total production energy use. Each of these sectors accounts for 5.8%, 15.3%, 7.55, 25.0%, 7.9% and 8.0% of total production energy use, respectively. Meanwhile, sector of ‘‘Construction’’ (No. 26) is the largest contributor of the total embodied energy consumption (26.1%), followed by ‘‘Other Service Activities’’ (No. 29) (12.4%), ‘‘Ordinary and Special Equipment’’ (No. 16) (7.5%), ‘‘Electronic and Telecommunications Equipment’’ (No. 19) (6.4%), ‘‘Transportation Equipment’’ (No. 17) (6.0%) and ‘‘Electric Equipment and Machinery’’ (No. 18) (5.4%).

3.2. Direct energy consumption versus indirect energy consumption

By using Eq. (3), embodied energy consumption from 29 sectors was further decomposed into direct energy consumption and indirect energy consumption (Fig. 3).

The results indicated that indirect energy consumption accounts for 80% of the total embodied energy consumption. Particularly, ‘‘Construction’’ sector has the largest amount of embodied energy consumption, with approximately 95% of its embodied energy con- sumption allocated into indirect energy consumption.

To further explore the energy consumption features of typical economic sectors, three sectors were chosen for a more detailed analysis of their embodied energy consumption. Based on Eq. (3), embodied energy consumptions of ‘‘Construction’’ sector (No. 26), ‘‘Other Service Activities’’ sector (No.29) and ‘‘Ordinary and Special Equipment’’ sector (No.16) have been presented in Figs. 4–6, respectively.

The results showed that indirect energy consumptions from these three sectors were mainly caused by energy consumptions from their upstream/downstream sectors, especially from sectors of ‘‘Raw Chemical Materials and Chemical Production, Medical and

Fig. 2. Production energy use vs. embodied energy con

Fig. 3. Direct and indirect energy consum

Pharmaceutical Production, Chemical Fiber, Rubber Production, Plastic Production’’ (No. 12), ‘‘Nonmetal Mineral Production’’ (No. 13), ‘‘Smelting and Pressing of Ferrous and Nonferrous Metals’’ (No. 14), ‘‘Electricity Power/Heating Supply’’ (No. 23) and ‘‘Trans- port, Logistics, Postal and Telecommunications Services’’ (No. 27). Because sectors of No. 12, No. 13 and No. 14 are typical heavy industrial and energy-intensive sectors, the higher proportion of embodied energy consumption in ‘‘Construction’’ and ‘‘Other Service Activities’’ can be explained by the intermediate activities’ energy consumption from those energy-intensive sectors.

4. Discussion

By employing the EIO method, our study results provided an innovate perspective for explaining the rapid growth of ‘‘energy- intensive’’ sectors in China. While heavy industries, such as smelting and pressing of metals, are typical energy-intensive sectors and have higher level of production energy use, sectors, such as ‘‘Construction’’ (No. 26), have relatively higher embodied energy consumptions and should be considered energy-intensive sectors from a supply chain perspective.

By uncovering the supply chain energy consumption for a single sector (Figs. 4–6), our results illustrated that those heavy industrial sectors and the relevant energy supply sectors along upstream/downstream supply chains are the main contributors of the high embodied energy consumption for sectors such as ‘‘Construction’’. Consequently, the supply chain energy consump- tions contribute to higher values of the embodied energy con- sumption of certain sectors.

Given the above information, it is necessary to find appropriate explanations for such phenomena. First, China’s soaring economy has been primarily driven by infrastructure construction and

sumption for 29 economic sectors (Units: Mt SCE).

ption for 29 sectors (Units: Mt SCE).

Fig. 4. Embodied energy consumption for ‘‘Construction’’ sector (Units: Mt SCE).

Fig. 5. Embodied energy consumption for ‘‘Other Service Activities’’ sector (Units: Mt SCE).

Fig. 6. Embodied energy consumption for ‘‘Ordinary and Special Equipment’’ sector (Units: Mt SCE).

Z. Liu et al. / Energy Policy 49 (2012) 751–758756

capital investment (Minx et al., 2011; Peters et al., 2010). Such a strategy has been effective in maintaining China’s rapid GDP growth even during the global economic recession (Guan and Barker, 2012). Based on the Chinese official statistics (National Bureau of Statistics, 2010), capital investment had contributed to

45% of the annual GDP growth during 2000–2007, whereas household consumption and exports had contributed to 30% and 25%, respectively. Capital investment creates market demand for the large-scale production expansion of cement, steel and other highly energy-intensive materials, as well as demand for the

Z. Liu et al. / Energy Policy 49 (2012) 751–758 757

associated electricity generation to support such production (Chen et al., 2011; Minx et al., 2011; Peters et al., 2007). For example, the average annual growth rate of cement output was 10.7% from 1985 to 2010. In 2010, China’s cement output was 1.87 Bmt, accounting for 56% of the world’s total cement produc- tion (International Cement Review, 2011). Similarly, China’s steel production had increased from 152 Mt in 2001 to 695.5 Mt in 2011, accounting for 45.5% of the world’s total steel production (Guo and Zhang, 2012). Most of the cement and steel were consumed by ‘‘Construction’’ sector, resulting in this sector being the most intensive sector for embodied energy consumption. Thus, the supply chain demand of such sectors caused very large amounts of production activity in heavy industries; in other words, these sectors are also ‘‘energy-intensive’’, but energy consumption is concentrated in supply activity rather than their direct production for final demand.

Second, a sector’s classification limited the analysis of the energy consumption in the supply chain. Because of the mismatch between sectoral classifications in China’s IO tables and the classifications in sectoral energy consumption, we merged similar sectors in this study for consistency between the sectors in IO and the sectors in the energy consumption data; the aggregated sectoral classification contains 29 sectors. Thus, several subsec- tors may be merged together and some sectors may contain too many sectoral activities, especially ‘‘Other Service Activities’’, for which activities that do not belong to other sectors are all contained within it. Such classifications of energy consumption sectors have been already widely used for IO-related research in China. For example, a classification of 24 sectors was proposed by Chang and his colleagues (Chang et al., 2010), 26 sectors were proposed by Chen and Zhang (2010) and 29 sectors were proposed by Zhang (2010); the sectoral aggregation and disag- gregation was also discussed by Kahrl and Roland-Holst (2008) as well as by Chen and Zhang (2010). Given the scale and proportion of the embodied energy consumption from these sectors, the uncertainty brought by such simplification cannot negate the result that China’s construction and service sectors are actually energy-intensive when considering their embodied energy con- sumption. However, such uncertainty cannot be ignored, espe- cially when the EIO model is coupled with life-cycle analysis (Hendrickson et al., 2006). Because the CESYB is the only official and open published data source which contains China’s sectoral detailed energy consumption, it is impossible to directly improve the data quality based on current statistics system; thus, we encourage any efforts of further disaggregation of sectoral energy consumption and improvement in the data quality of China’s energy statistics from different sources in the future.

5. Policy implications

Generally, current Chinese energy conservation policies focus on production energy use, thus, heavy industries received a lot of attention for their energy saving efforts. For example, during the 11th Five-Year Plan (2006–2010), energy-saving targets for Chi- na’s 1000 highest energy consuming enterprises were arranged by the NDRC, aiming to save approximately 2.9 EJ of energy consumption during 2006–2010 (Price et al., 2010). In 2010, factories with production capacities of 10 MkW h of power gen- eration, 6 million tons of steel and 25 Mt of iron were closed (National Development and Reform Commission (NDRC), 2011b; Xinhuanet, 2007). Additionally, more ambitious plans have been prepared to improve energy efficiency of 17 heavy industrial sectors (such as cement, iron and steel) during the 12th Five-Year Plan (2011–2015). However, current policy overlooks the supply chain of those heavy industries. The continuous expansion of

those industries would result in multiple increase of energy demand by their upstream suppliers. This would further lead to higher energy consumption for the whole economy (Lenzen et al., 2008). Thus, energy saving measures and efficiency improvement policies should not only consider the traditional heavy industries but also pay attention to the relevant sectors along their supply chains. An integrated policy approach should be employed instead of only addressing energy efficiency issues in several individual sectors. Such integrity requires that policy makers integrate energy supply management, energy demand manage- ment, energy efficiency management, and energy-related emis- sion management throughout the whole supply chain. Moreover, policy makers should seek new economic growth strategies, rather than only relying on infrastructure construction and capital investment. For instance, increasing investment in education service and technological innovation aspects could be helpful for long-term economic growth and the adjustment of the whole economic structure.

With respect to the ‘‘bottom-up’’ implementation of such energy saving and efficiency improvement policies, different strategies should be adopted based on a certain sector’s energy consumption features. For those heavy industries, such as thermal power generation and smelting metal, efforts should focus on the improvement of their efficiency through cleaner production, energy audits, technology updates, compulsory phase-out/shut- down of inefficient and backward manufacturing facilities, capa- city-building programs on energy saving awareness, etc. For those sectors with higher embodied energy consumptions, such as construction sector, efforts should focus on addressing their supply chain energy consumption, such as greening their supply chain and controlling the irrational final demand. Market-based instruments, such as sectoral financial subsidies, preferable tax rates and low interest bank loans, should be employed so that the energy consumption along the supply chain can be adjusted according to their final demand and consumption.

6. Conclusions

The aim of this study is to uncover the whole picture of China’s sectoral embodied energy consumption. Through the use of an economic input–output assessment (EIO) model, patterns of embodied energy consumption were analyzed for 29 sectors. Our results indicate that some sectors that are not traditionally regarded as ‘‘energy-intensive’’ are actually the sectors with higher embodied energy consumption, such as construction sector. Therefore, energy conservation policies should be revised based upon such realities so that the rational consideration can be given to these key sectors. Policy implications from this paper can be used for those decision-makers to reconsider their energy management targets and regulations by considering sectoral realities.

Acknowledgements

This study was supported by Natural Science Foundation of China (71033004, 31100346, 41101126), Chinese Academy of Sciences (2008-318), the Shenyang Scientific Research Foundation (F10-238-6-00), and Ministry of Science and Technology (2011BAJ06B01).

References

British Petroleum (BP), 2011. BP Statistical Review of World Energy, 2011. Brown, M., Herendeen, R., 1996. Embodied energy analysis and EMERGY analysis:

a comparative view. Ecological Economics 19, 219–235.

Z. Liu et al. / Energy Policy 49 (2012) 751–758758

Bullard, C.W., Herendeen, R.A., 1975. The energy cost of goods and services. Energy Policy 3, 268–278.

Chang, Y., Ries, R.J., Wang, Y., 2010. The embodied energy and environmental emissions of construction projects in China: an economic input–output LCA model. Energy Policy 38, 6597–6603.

Chen, G., Zhang, B., 2010. Greenhouse gas emissions in China 2007: inventory and input–output analysis. Energy Policy 38, 6180–6193.

Chen, Q., Kang, C., Xia, Q., Guan, D., 2011. Primary exploration on low-carbon technology roadmap of China’s power sector. Energy 36, 1500–1512.

Duchin, F., 1998. Structural Economics: Measuring Change in Technology, Life- styles, and the Environment. Island Press, Washington, D.C., Covelo, CA.

Duchin, F., 2009. Input–output economics and material flows. Handbook of Input– Output Economics in Industrial Ecology, 23–41.

Feng, K., Hubacek, K., Guan, D., 2009. Lifestyles, technology and CO2 emissions in China: a regional comparative analysis. Ecological Economics 69, 145–154.

Feng, K., Hubacek, K., Guan, D., Contestabile, M., Minx, J., Barrett, J., 2010. Distributional effects of climate change taxation: the case of the UK. Environ- mental Science & Technology 44, 3670–3676.

Geng, Y., 2011. Eco-indicators: Improve China’s sustainability targets. Nature 477, 162.

Guan, D., Barker, T.S., 2012. Low Carbon Development in the least developed region: a case study of Guangyuan, Sichuan province, southwest China. Natural Hazards 62, 243–254.

Guan, D., Hubacek, K., 2007. Assessment of regional trade and virtual water flows in China. Ecological Economics 61, 159–170.

Guan, D., Hubacek, K., 2008. A new and integrated hydro-economic accounting and analytical framework for water resources: a case study for North China. Journal of Environmental Management 88, 1300–1313.

Guan, D., Hubacek, K., Weber, C.L., Peters, G.P., Reiner, D., 2008. The drivers of Chinese CO2 emissions from 1980 to 2030. Global Environmental Change: Human and Policy Dimensions 18, 626–634.

Guan, D., Peters, G.P., Weber, C.L., Hubacek, K., 2009. Journey to world top emitter—an analysis of the driving forces of China’s recent emissions surge. Geophysical Research Letters, 36.

Guo, H., Zhang, T.Z., 2012. Prediction of demand for China steel and iron ore resources. Metallurgy Mineral 427, 6–9.

Hendrickson, C.T., Lave, L.B., Matthews, H.S., 2006. Environmental life cycle assessment of goods and services: an input–output approach. Resources for the Future.

Hubacek, K., Guan, D., Barrett, J., Wiedmann, T., 2009. Environmental implications of urbanization and lifestyle change in China: ecological and water footprints. Journal of Cleaner Production 17, 1241–1248.

International Cement Review, 2011. The Global Cement Report, ninth ed. Trade- ship Publications Ltd, Dorking, UK.

Kahrl, F., Roland-Holst, D., 2008. Energy and exports in China. China Economic Review 19, 649–658.

Kong, X.Z., 2012. Transformation pathway for China’s cement industry. China Cement, 15–18.

Lenzen, M., Wood, R., Foran, B., 2008. Direct versus Embodied Energy-the Need for Urban Lifestyle Transitions’. Droege, P. (Ed.), pp. 91–120.

Leontief, W., 1970. Environmental repercussions and the economic structure: an input–output approach. The Review of Economics and Statistics 52, 262–271.

Leontief, W.W., 1936. Quantitative input and output relations in the economic systems of the United States. The Review of Economics and Statistics 18, 105–125.

Liang, S., Jia, X.P., Zhang, T.Z., 2011. Three-dimensional hybrid enterprise input– output model for material metabolism analysis: a case study of coal mines in China. Clean Technologies and Environmental Policy 13, 71–85.

Lin, X., Polenske, K.R., 1995. Input–output anatomy of China’s energy use changes in the 1980s. Economic Systems Research 7, 67–84.

Liu, H.T., Guo, J.E., Qian, D., Xi, Y.M., 2009. Comprehensive evaluation of household indirect energy consumption and impacts of alternative energy policies in China by input–output analysis. Energy Policy 37, 3194–3204.

Minx, J.C., Baiocchi, G., Peters, G.P., Weber, C.L., Guan, D., Hubacek, K., 2011. A Carbonizing Dragon: China’s fast growing CO2 emissions revisited. Environ- mental Science & Technology 45, 9144–9153.

Minx, J.C., Wiedmann, T., Wood, R., Peters, G.P., Lenzen, M., Owen, A., Scott, K., Barrett, J., Hubacek, K., Baiocchi, G., Paul, A., Dawkins, E., Briggs, J., Guan, D., Suh, S., Ackerman, F., 2009. Input–output analysis and carbon footprinting: an overview of applications. Economic Systems Research 21, 187–216.

National Bureau of Statistics, 2010. China Statistical Yearbook. China Statistics Press, Beijing 2009.

National Bureau of Statistics of China (NBSC), 1995–2010. Chinese Energy Statistics Yearbook. China Statistics, Beijing.

National Bureau of Statistics of China (NBSC), 1996–2010. Chinese Statistics Year Book. China Statistics, Beijing.

National Development and Reform Commission (NDRC), 2007. China’s National Climate Change Programme, Beijing.

National Development and Reform Commission (NDRC), 2011a. The 12th Five- Year Plan Outline of National Economy and Social Development of People’s Republic of China.

National Development and Reform Commission (NDRC), 2011b. Achievement for Energy Conservation Target in 11th Five Year Plan. National Development and Reform Commission (NDRC), Beijing.

Peters, G., Guan, D., Hubacek, K., Minx, J., Webber, C., 2010. Effects of China’s economic growth. Science 328, 825–826.

Peters, G., Webber, C., Guan, D., Hubacek, K., 2007. China’s growing CO2 emissions—a race between lifestyle changes and efficiency gains’’. Environ- mental Science & Technology 41, 5939–5944.

Peters, G.P., 2008. From production-based to consumption-based national emis- sion inventories. Ecological Economics 65, 13–23.

Peters, G.P., Hertwich, E.G., 2008. CO2 embodied in international trade with implications for global climate policy. Environmental Science & Technology 42, 1401–1407.

Peters, G.P., Minx, J.C., Weber, C.L., Edenhofer, O., 2011. Growth in emission transfers via international trade from 1990 to 2008. Proceedings of the National Academy of Sciences 108, 8903.

Polenske, K.R., McMichael, F.C., 2002. A Chinese cokemaking process-flow model for energy and environmental analyses. Energy Policy 30, 865–883.

Price, L., Wang, X., Yun, J., 2010. The challenge of reducing energy consumption of the Top-1000 largest industrial enterprises in China. Energy Policy 38, 6485–6498.

Qiu, J., 2011. China announces energy-saving plans. Nature. Skelton, A., Guan, D., Peters, G.P., Crawford-Brown, D., 2011. Mapping flows of

embodied emissions in the global production system. Environmental Science & Technology 45, 10516–10523.

Weber, C.L., Peters, Glen P., Guan, D., Hubacek, K., 2008. The contribution of Chinese exports to climate change. Energy Policy 36, 3572–3577.

Wiedmann, T., Wood, R., Minx, J., Lenzen, M., Guan, D., Harris, R., 2010. A climate footprint time series of the UK—results from a ulti-region input–output model. Economic System Research 22, 19–42.

World Bank, 2011. World Development Indicators. World Bank. Xinhuanet, 2007. The binding index convoy conflict for the energy-saving and

emission reduction targets. Xinhuanet, http://news.xinhuanet.com/newscen ter/2007-11/27/content_7155551.htm.

Zhang, Y., 2010. Supply-side structural effect on carbon emissions in China. Energy Economics 32, 186–193.