li m Bi esea a 110 Received 8 June 2010 Received in revised form 15 November 2010 Accepted 15 May 2011 Available online 16 June 2011 ecosystem metabolism at the regional level due to its imbalanced development nature. The political and administrative systems in China are highly centralized but also have significant decentral- ization features. Understanding these features is necessary for exploration of possible initiatives to coordinate and enhance recommendations. 2. Methodology This study is both qualitative and quantitative. The data and information used to create this paper were derived from unpub- lished government reports and published papers and government documents (such as China statistics yearbooks and China energy statistics), as well as semi-structured interviews with key * Corresponding author. Tel.: þ86 24 83970372; fax: þ86 24 83970371. Contents lists availab Ener .e ls Energy 36 (2011) 4799e4808 E-mail address:
[email protected] (Y. Liu). 1. Introduction China’s rapid development has lasted for three decades. However, with China’s large size and population, as well as the absence of a comprehensive sustainable development scheme, such an increase has brought many challenges, such as resource depletion, water pollution, sandstorm, soil erosion, deforestation, desertification, and recently climate change [1]. In order to meet these challenges, a new sustainable development model which has the ability to overcome the current dilemma and achieve improvements in resource productivity and eco-efficiency should be created. This requires an in-depth analysis on societal and regional sustainable development. The national or central govern- ment is the highest level of government and has ultimate authority. At the next level, China is divided into 23 provinces, 5 autonomous regions (politically equal to one province), 4 municipalities (Beijing, Tianjin, Shanghai, and Chongqing) which are directly accountable to the central government (politically equal to one province) and two special administrative regions (Hong Kong and Macau). However, few studies have been conducted to compare different development perspectives at the regional level in China. Thus, the objective of this study is to investigate the imbalanced develop- ment nature of various Chinese regions, identify the key factors impeding regional sustainable development, and raising our Keywords: Multi-scale integrated analysis of societal metabolism (MSIASM) Chinese provinces Sustainable development 0360-5442/$ e see front matter � 2011 Elsevier Ltd. doi:10.1016/j.energy.2011.05.014 systematic picture. Multi-scale integrated analysis of societal metabolism (MSIASM) is such an approach as it integrates economic, social and ecological dimension. In this paper, we employ such an approach to evaluate regional societal and ecosystem metabolism in China. We set up a series of indicators to present different development perspectives and employ a complete decomposition model to further identify key factors for regional sustainable development. Our research outcomes indicate that both west and north China rely on natural resource for their development while east and south China have more balanced sector structure. We also found that urban areas, especially those large cities, have already reached the level of those developed countries. Thus, how to reduce the gap between urban and rural contexts will be the next challenge of the Chinese government. From temporal point of view, although in recent years China gained great achievement for economic development, there is a lack of attention on improving people’s life quality and social service. This requires a more balanced development strategy so that different regions can better utilize their resources and support each other and a more balanced sector structure so that economic development will not be always the main focus of regional government and more attention on improving social welfare will be paid. � 2011 Elsevier Ltd. All rights reserved. Article history: The complicated nature of regional development requires a more integrated approach to reflect its a r t i c l e i n f o a b s t r a c t Regional societal and ecosystem metabo integrated analysis of societal metabolis Yong Geng a, Ye Liu a,*, Dan Liu b, Hengxin Zhao a,c, aKey Laboratory of Pollution Ecology and Environmental Engineering & International R Chinese Academy of Sciences, P.O.Box417, No.72 Wenhua Road, Shenyang 110016, Chin b Economic Crime Investigation Department, China Criminal Police University, Shenyang cGraduate University of Chinese Academy of Sciences, Beijing 100039, China journal homepage: www All rights reserved. sm analysis in China: A multi-scale (MSIASM) approach ng Xue a rch Center for Circular Economy and Industrial Ecology, Institute of Applied Ecology, 854, China le at ScienceDirect gy evier .com/locate/energy informants in the country. Before the interviews, a brief session and several formal workshops were hosted by the authors so that the interviews could be probe respondents for greater clarity in answers and consistency in relation to the objectives of the ques- tions. The whole investigation process was administered with the endorsement and support of the Natural Science Foundation of China (NSFC). To appreciate the value of our investigation, one needs to understand the general difficulties of interviewing government officials in China, given the regime’s apprehension that interview results may be used as a basis for criticizing the Chinese government. Also, it is impossible to conduct these interviews without the endorsement, support, and collaboration of the government units concerned. Consequently, such interviews represent a rare opportunity for examining the attitudes of related officials in China, as well as identifying the key barriers of regional sustainable development. In addition, interviewees were promised anonymity, and thus interviewee responses have been pooled and in some cases slightly reworded to obscure interviewee identities. We observed no evidence that the leadership in the investigated units made any effort to affect the outcomes of the interviews, and we explained clearly both in our briefing that all data and infor- mation were collected solely for academic purposes and would remain strictly confidential. Thus we can reasonably believe that the responses represent the true opinions of the respondents. Due to data unavailability, Tibet, Taiwan, Hong Kong and Macau are not included for this study. Thus, our study areas in this paper include the following regions in mainland China, namely, Beijing, Tianjin, Hebei, Shanxi, Inner Mongolia, Liaoning, Jilin, Heilongjiang, Shanghai, Jiangsu, Zhejiang, Anhui, Fujian, Jiangxi, Shandong, Henan, Hubei, Hunan, Guangdong, Guangxi, Hainan, Chongqing, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai, Ningxia, and Xinjiang. In terms of time span of this research, we chose year 2003 and 2007 as the study year due to data availability. Fig. 1 shows our study regions. The main method for our analysis is Multiple-Scale Integrated Assessment of Societal Metabolism (MSIASM), which was origi- nated by Giampietro, Mayumi and their colleagues [2e8]. This method has been used to study societal and ecosystemmetabolism for many counties and regions. For instance, with the application of this method, Falconi-Benitez and his colleagues found that the rapid capital aggregation in Ecuador in 1970’s only contributed to the utility of some limited resources and this development mode wasn’t benefit to the coordination of development in different economic sectors [9]. By employing this method, Iorgulescu and Polimeni investigated energy use in four countries (Romania, Hungary, Bulgaria and Poland) in east Europe, considering the complexity of the transition process [10]. Ramos-Martin found that the improvement of living standards in Spain was mainly due to Y. Geng et al. / Energy 36 (2011) 4799e48084800 Fig. 1. Location of th e study regions. y 36 economic development, but such an improvement was based upon sacrificing environmental benefits [11]. With regard to the appli- cation of this method in China, the social exosomatic metabolism of China at national level was studied [12], and the metabolism analyses both in Gansu province and Fujian province were con- ducted [13,14]. However, no comparison studies among different regions (provincial level) in China have been undertaken by using this method. Since such a region represents a human dominated self-organizing complex ecosystem and politically each region has their own authority to prepare their development strategies and management policies, it is necessary to investigate its material and energy metabolism process so that the complicated evolution nature of one region can be recognized and most appropriate development policies can be raised. The regional sustainability requires considering an economic dimension, a social dimension, a technical dimension, and an ecological dimension. Under such a circumstance, their relevant aspects cannot be captured when using a single perspective, thus, an integrated assessment method is needed, namely, MSIASM. Unlike the traditional societal and ecosystem metabolism method, such as material flow analysis (MFA), MSIASM method attempts to incorporate these qualitative differences in the inten- sity of flows into a simple scheme that can be used to analyze societal metabolism for sustainability issues [2]. In order to better understand the nature of MSIASM, it is useful to make a distinction between exosomatic energy metabolism (energy flows metabo- lized by a society outside human body,) and endosomatic energy metabolism (energy contained in food used to support human physiological processes). The exosomatic/endosomatic energy ratio indicates how much “human technology” and the availability of natural resources boost the ability of humans to control the production and consumption of goods and services. According to the principles of MSIASM, there are four types of parameters for analyzing societal and ecosystem metabolism. The following is a detailed explanation of these parameters. 2.1. Hour based human time Total Human Activity (THA) is the total hours for various human activities within a year. THA consists of four parts: total human time in the agricultural sector (HAAG), total human time in the industrial sector (HAIS), total human time in the service and government sector (HASG), and total human time in the household sector (HAHH). THA ¼ HAAG þ HAIS þ HASG þ HAHH (1) Here the total sum of HAAG, HAIS and HASG can be defined as the total human time for paid works (HAPW), while HAHH is the total time for unpaid works. With regard to China, according to China’s Gender Statistics [15], the value of HAAG is 2148 h, the value of HAIS is 2069 h, and the value of HAHH is 2054 h. SOHA (societal overhead of human activity) means that in order to have effective economic activities, certain time have to be allo- cated to support social welfares, such as supporting children growth, disables, seniors, as well as others for their unpaid activi- ties. SOHABP reflects the bio-physical significance of societal over- head of human activity, while SOHA$ reflects the economic significance of societal overhead of human activity. SOHA can be expressed by the following equation: SOHA$ ¼ HAHH=ðHAIS þ HASG þ HAAGÞ (2) SOHABP ¼ ðHAHH þ HASGÞ=ðHAIS þ HAAGÞ (3) The value of SOHA is determined by various factors, such as Y. Geng et al. / Energ life span, retirement age, level of education. Usually, developed economies have higher value of SOHA as they can allocate more time for improving their people’s well-being. 2.2. Joule based exosomatic energy throughput TET (Total exosomatic energy throughput) is the total amount of exosomatic energy consumed by the society within a year. TET consists of four parts: the exosomatic energy in the agricultural sector (ETAG), the exosomatic energy in the industrial sector (ETIS), the exosomatic energy in the service and government sector (ETSG), and the exosomatic energy in household sector (ETHH), namely TET ¼ ETAG þ ETIS þ ETSG þ ETHH (4) SOET (societal overhead of exosomatic energy throughput) means that in order to meet with the energy demand of consumption sectors, the manufacturing sectors have to consume certain energy. SOETBP reflects the bio-physical significance of societal overhead of exosomatic energy throughput, while SOET$ reflects the economic significance of societal overhead of exoso- matic energy throughput. SOET can be expressed by the following two equations: SOET$ ¼ ETHH=ðETIS þ ETSG þ ETAGÞ (5) SOETBP ¼ ðETHH þ ETSGÞ=ðETIS þ ETAGÞ (6) More developed economies usually have more advanced tech- nologies and can improve the overall eco-efficiency of the whole industrial ecosystem, thus, the related SOET value is also higher. 2.3. Exosomatic metabolism rate (EMR) EMR indicates the average hourly exosomatic energy consumption of the whole economic system and can be expressed by the following equation: EMR ¼ TET THA ¼ Xn i ETi THA ¼ Xn i ETi HAi � HAi THA ¼ Xn i EMRi � Si (7) Where ETi is the exosomatic energy in the sector i, HAi is the human time invested in the sector i, EMRi is the exosomatic metabolic rate in the sector i, Si is the rate of human time used in the sector i to the total human time. Si can be expressed by the Eq. (8). EMRi is the exosomatic metabolism rate from sector i and can be expressed by Eq. (9). Si ¼ X HAi=THAði ¼ AG; IS; SG;HHÞ (8) EMRi ¼ ETi HAi ði ¼ AG; IS; SG;HHÞ (9) With the social development, the value of EMR also increases. It reflects both the combination of various technologies utilized in different economic activities and the capitalization level of that economic system. From the above formula, the change of exoso- matic metabolic rate between the baseline year (t ¼ 0) and the ending year t can be further expressed as: DEMR ¼ EMRt � EMR0 (10) DEMRi ¼ EMRti � EMR0i (11) where DEMR and DEMRi are the changes of exosomatic metabolic rate in the whole economic system and sector i from baseline year (2011) 4799e4808 4801 to year t, respectively; EMRt is the exosomatic metabolic rate of the whole economic system in year t; EMR0 is the exosomaticmetabolic rate of the whole economic system in baseline year, EMRti is the exosomatic metabolic rate in the sector i in year t; EMR0i is the exosomatic metabolic rate in the sector i in baseline year. Further, complete decomposition model is employed to identify the key factors related with energy consumption and energy intensity [16e18]. According to this model, the value of EMR is influenced by two factors, namely, resource and technology aggregation, and sector structure [16]. Consequently, it can be separated as two parts, namely, EMRaggregate and EMRstructure, where EMRaggregate represents the contribution of resource and technology aggregation to the change of Exosomatic metabolism rate and EMRstructure, represents the contribution of sector structure to the change of Exosomatic metabolism rate. Thus, we hereby use two equations to reflect this relationship: This indicator indicates the total requests on production sector from consumption perspectives and can be used to reflect the economic development level. The higher value of this indicator means higher development level of the whole society and higher burden on the natural ecosystem. 3. Results and discussion By employing the method of MSIASM, we undertook a detailed analysis on China’s national and regional societal and ecosystem metabolism. Fig. 2 shows our research outcomes for selected 30 Chinese regions for year 2003 and 2007, including all the details for the whole study regions, household sector, agricultural sector, industrial sector, and service and government sector. Generally, Y. Geng et al. / Energy 36 (2011) 4799e48084802 EMRaggregate ¼ X i S0i DEMRi þ 1 2 X i DSiDEMRi (12) EMRstructure ¼ X i EMR0i DSi þ 1 2 X i DSiDEMRi (13) whereDSi ¼ Sti � S0i ; Sti ; Sti is the rate of human time used in sector i to the total human time in year t; S0i is the rate of human time used in sector i to the total human time in the baseline year; ⊿Si is the rate change of human time used in sector i to the total human time from baseline year to year t. Here we set up two new indicators, namely raggregate and rstruc- ture, where raggregate represents the rate of contribution of resource and technology aggregation to the change of exosomatic metabo- lism rate and rstructure represents the rate of contribution of sector structure to the change of exosomatic metabolism rate. The sum of these two values should be equal to 1 and the values of these two indicators can be expressed by Eqs. (14) and (15): raggregate ¼ � EMRaggregate=DEMR �� 100% (14) rstructure ¼ ðEMRstructure=DEMRÞ � 100% (15) 2.4. Bio-economic pressure (BEP) BEP equals to the total required exosomatic energy metabolized by thewhole society (TETreq) divided byworking time in production sector (HAPS) and can be expressed by the following equation: BEP ¼ TETreq=HAPS (16) Fig. 2. Exosomatic energy throughput in different sectors in compared with year 2003, the total TET value for year 2007 increased from 51.5 EJ to 78.6 EJ, with an annual increasing rate of 11.1%, a little bit higher than the annual increasing rate of national GDP (10.9%) at the same period [19]. This means that China’s economic development between 2003 and 2007 couples with its energy consumption, while the expected decoupling development did not happen. In terms of exosomatic energy throughput value in different sectors for year 2007, Fig. 2 provides us with a clear picture, where industrial sector (77.4%) is the main contributor of energy consumption, followed by service and government sector (12.8%). Energy consumption from both household sector (7.9%) and agriculture sector (1.6%) are still very few, reflecting that China is the world’s manufacturing center, while its citizens still have a lower life quality. Such a reality indicates that China should seek a new development model. Especially, with the acceleration of global warming and resource scarcity, as well as increasing envi- ronmental issues, the traditional coupling development model cannot meet with these challenges. Circular economy is one inno- vative solution on responding these issues. It encourages economic activities to mimic natural ecosystem metaphor so as to realize a closed loop of material flow in the whole economic system [1]. It provides strategies to achieve greater efficiency through economies of systems integration, where partnerships between businesses meet common service, transportation and infrastructure needs and the concept adds value to businesses and communities by opti- mizing the use of energy, materials and community resources [20]. Thus, in order to realize decoupling development, circular economy should be further promoted. In order to compare different regions,we categorized 30 selected regions into four geographical groups, namely, north China (Beijing, Tianjin, Hebei, Shanxi, InnerMongolia, Liaoning, Jilin, Heilongjiang), the central-east (Shanghai, Jiangsu, Zhejiang, Anhui, Fujian, Jiangxi, Shangdong, Henan, Hubei, Hunan), the south (Guangdong, Guangxi, Hainan, Chongqing, Sichuan, Guizhou, Yunnan), the west (Shaanxi, the whole selected Chinese regions for 2003 and 2007. Gansu, Qinghai, Ningxia, Xinjiang). We also specially set up one group for four municipalities (Beijing, Tianjin, Shanghai, Chongqing), which are directly accountable to the central govern- ment, so that we can see the special development perspectives of urban development. Fig. 3 shows our research outcomes on percentage of ET value from various sectors in five geographical groups, reflecting the impact of sector framework on energy 0.80 MJ/h, while Inner Mongolia has the biggest increasing EMR value of 11.85MJ/h. Themain reason is that Hainan has been chosen by the central government as a national tourism center, thus fewer industries have been developed and both agriculture and service sectors are fully supported by the local government, while Inner Mongolia is a resource based region and during 2003-7 many coal cores, rare metal ores, and petroleum fields had been explored due 0% 20% 40% 60% 80% 100% National The north The center east The south The west Municipalities C on tr ib ut io n of se ct or s to po pu la tio n (% ) SG IS AG HH Fig. 3. Exosomatic energy throughput shares in different sectors in the selected Chinese regions for year 2007. nnua Y. Geng et al. / Energy 36 (2011) 4799e4808 4803 consumption. We can see that four municipalities have significant higher percentage of ETSG values in all energy consumption than other regions, indicating that service and government sector ismore developed in urban areas. The percentages of ETHH value in both north andwest China are higher than other regions because regions in north and west China have much colder winter, thus, energy consumption for heating is essential. In order to further identify the imbalanced nature of Chinese development, we conducted another detailed analysis for every studied region. Fig. 4 shows the detailed values of EMR in 30 selected regions. Figs. 5e8 show the detailed values of EMRAG, EMRIS, EMRSG, EMRHH in 30 regions respectively. Although the total values of EMR in 30 regions in 2007 are all increased, comparing with those in 2003, such values vary in different regions and can be used to evaluate different regional development models. With different geographical, cultural, environmental and resource perspectives, different regions have to choose their own develop- ment strategy by considering both national demand and their own realities. For instance, Hainan has the least increasing EMR value of 20 25 30 /h) 2003 2007 A 0 5 10 15 N at io na l Th e n o rt h Th e ce nt er e as t Th e so u th Th e w es t M un ic ip al iti es B ei jin g Ti an jin H eb ei Sh an x i In ne r M on go lia Li ao n in g Jil in H ei lo ng jia ng Sh an gh ai Jia n gs u Zh eji an g A nh ui Fu jia n EM R _ SA (M J Fig. 4. EMR in the selected Chines to increasing demand on natural resources, resulting in that this region is the most rapid one for both economic development and energy consumption. Now it is one of the most important energy resource areas in China and has established a heavy industry network. With an increasing exploitation of various ores and oil fields, it is expected that their total EMR value will continue to rise up. For other regions, we can find a general trend that many regions in northern China (Heilongjiang, Jilin, Liaoning, Hebei, Shandong, Shanxi, Shaanxi, Ningxia, Xinjiang, Qinghai, Beijing, Tianjin) have higher EMR values than other regions, indicating that northern China consumed more energy for their development (Here we use northern China to present those regions geographically locating in the northern part of China, which is different from north China we defined earlier in this paper). Through a structural analysis on different components (EMRAG, EMRIS, EMRSG, EMRHH) of EMR, we can find that regions in eastern China (Heilongjiang, Jilin, Liaoning, Hebei, Henan, Jiangsu, Zhejiang, Beijing, Guangdong, Fujian) have higher EMRAG values than those in western China, except Sichuan, indicating that east China is the main place for agricultural 10% 30% A nn l increasing rate National average -50% -30% -10% Jia ng xi Sh an do n g H en an H ub ei H un an G ua ng do n g G ua n gx i H ai na n Ch on gq in g Si ch ua n G ui zh ou Y un n an Sh aa nx i G an su Qi ng ha i N in gx ia X in jia n g ual a v erag e(% ) e regions for 2003 and 2007. -200% -150% -100% -50% 0% 50% 100% 0 5 10 15 20 25 30 National The north The center east The south The west Municipalities Beijing Tianjin Hebei Shanxi Inner Mongolia Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Shaanxi Gansu Qinghai Ningxia Xinjiang Annual average(%) EMR_AG(MJ/h) 2003 2007 A n n u al increasing rate N ational average Fig.5. EM R A G in the selected Chinese regions for 2003 and 2007. -50.00% -30.00% -10.00% 10 .00% 30 .00% -100 100 300 500 700 900 1100 1300 1500 National The north The center east The south The west Municipalities Beijing Tianjin Hebei Shanxi Inner Mongolia Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Shaanxi Gansu Qinghai Ningxia Xinjiang Annual average(%) EMR_IS(MJ/h) 2003 2007 A n n u al increasing rate N ation al av erage Fig.6. EM R IS in the selected Chinese regions for 2003 and 2007. -150% -100% -50% 0% 0 10 20 30 40 50 60 70 80 90 100 National The north The center east The south The west Municipalities Beijing Tianjin Hebei Shanxi Inner Mongolia Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Shaanxi Gansu Qinghai Ningxia Xinjiang Annual average(%) EMR_SG(MJ/h) 2003 2007 A nnual increasing rate N atio n al average Fig.7. EM R SG in the selected Chinese regions for 2003 and 2007. Y.G eng et al./ Energy 36 (2011) 4799 e 4808 4804 Fu jia n nua hine y 36 development due to its abundant water resources, fertile soil and advantageous geographical situations (Here we use eastern China to present those regions geographically locating in the eastern part of China, which is different from central-east China we defined earlier in this paper). Sichuan province is special because it is a traditional agricultural region with suitable climate, soil and water reserves. Thus, east China and Sichuan should further support their agricultural development since to raise the large population of China is vital to the country’s security. In terms of industrial sector, regions in northeast China (Heilongjiang, Jilin and Liaoning), northwest China (Xinjiang, Qinghai, Ningxia, Gansu and Shaanxi), and central north China (Inner Mongolia, Hebei, Beijing and Tianjin), as well as Shanghai and Guizhou, have higher EMRIS values because most heavy industries and manufacturing indus- tries locate in these regions. Consequently, circular economy poli- cies (cleaner production, eco-industrial parks and regional eco- industrial network) should be mainly promoted in such regions so as to increase their overall eco-efficiency. With regard to service and governmental sector, regions including Shandong, Hebei, Hunan, Henan, Yunnan, Fujian, Jilin, Liaoning and Sichuan had 0.00 0.50 1.00 1.50 2.00 2.50 3.00 N at io na l Th e no rth Th e ce nt er e as t Th e so u th Th e w es t M un ic ip al iti es B ei jin g Ti an jin H eb ei Sh an x i In ne r M on go lia Li ao n in g Jil in H ei lo ng jia ng Sh an gh ai Jia n gs u Zh eji an g A nh ui EM R _ H H (M J/h ) 2003 2007 An Fig. 8. EMRHH in the selected C Y. Geng et al. / Energ increased their EMRSG values between 2003 and 2007. This indi- cates the rapid development of service industries in those regions and dynamic changes of their economic structure. During such a progress, more job opportunities have been created and more public services have been provided, resulting in more harmonious social development. But such values in Jiangsu and Gansu decreased in the same period, reflecting that these two provinces made less effort on providing both public and private service. Therefore, they should pay more attention on supporting service and government sector. Finally, with regard to household sector, EMRHH values in Hebei, Jiangxi, Guizhou, Qinghai, Xinjiang decreased in the range of �0.41w�0.02 MJ/h, especially Xinjiang had the largest decreasing value, while other regions increased by 0.0004w4.21 MJ/h, especially Inner Mongolia had the largest increasing value. This indicates that within the same period, people’s life quality in the five regions (Hebei, Jiangxi, Guizhou, Qinghai, Xinjiang) decreased while their economy increased. Therefore, their governments should consider making appropriate policies to improve their people’s life quality, rather than only focusing on economy, so that a more balanced development can be realized. The value of SOHA (both SOHA$ and SOHABP) can be used to reflect social development level. As such, the value of SOET (both SOET$ and SOETBP) can also be used to reflect social development level since more developed regions have more advanced technol- ogies and higher resource efficiency. Figs. 9 and 10 show our research outcomes on SOHA$ and SOHABP in 30 selected regions for year 2003 and 2007 respectively, while Figs. 11 and 12 show our research outcomes on SOET$ and SOETBP in 30 selected regions for year 2003 and 2007 respectively. From these four figures, we can see that four municipalities have higher values on both SOHA and SOET, indicating that urban regions generally have higher social development level due to their abundant financial and technology foundation, advanced education and management, higher resource utilization efficiency andmore intelligent human resource. Then for other regions, we can see that most north and west regions have relatively higher values of both SOHA and SOET, indicating that such regions paymore attention on social development, whilemany east and south regions pay more attention on industrial development. Moreover, many south and each regions do have resource shortage pressure and mainly rely on natural resources provided by north and west region. For temporal point of view, except Beijing and Shanghai, most regions have a decreasing trend on SOHA and SOET, -100.00% -50.00% 0.00% 50.00% Jia n gx i Sh an do ng H en an H ub ei H un an G ua n gd o n g G ua ng xi H ai n an Ch on gq in g Si ch u an G ui zh ou Y un na n Sh aa n x i G an su Qi n gh ai N in gx ia X in jia ng A nnual averag e(% ) l increasing rate National average se regions for 2003 and 2007. (2011) 4799e4808 4805 indicating that for the next couple of decades, the regional governments of China should focus on improving local social well- being, such as supporting education, health care and elders’ life. Our research outcomes also support the views of RamosdMartin and his colleagues on China’s development [12], namely, the increasing elder population and resource shortage pressures will become the main barriers for China’s sustainable development. Consequently, the Chinese government both at national and regional levels should seriously consider how to develop appro- priate strategies and policies for balancing different sectors. We also calculated the values of BEP in all selected regions in 2007, which was shown in Fig. 13. The value of BEP can reflect environmental pressures brought by local economic development and people’s life quality based on current productivity levels. Such a value is relevant with nutrition and health level of local citizens, social infrastructure and GDP per capita, etc [6,7]. By comparing with the values of BEP for developed countries [5], we found that the BEP value in Shanghai for 2007 (312 MJ/H) is similar to Greece (268.5 MJ/H) and Australia (344.3 MJ/H), meaning that Shanghai has reached the level of those middle leveled developed countries. But except Beijing, Tianjin and Inner Mongolia, such values in most of other regions are still low, indicating that they are still in the early stage of social and economic development. -60.00% -40.00% -20.00% 0.00% 20 .00% 0 4 8 12 16 20 National The north The center east The south The west Municipalities Beijing Tianjin Hebei Shanxi Inner Mongolia Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Shaanxi Gansu Qinghai Ningxia Xinjiang Annual average (%) SOHA_$ 2003 2007 A nnual increasing rate N ation al av erag e Fig.9. V alues of SO H A $ in selected regions. -50.00% -30.00% -10.00% 10 .00% 0.00 5.00 10 .00 15 .00 20 .00 25 .00 30 .00 35 .00 40 .00 National The north The center east The south The west Municipalities Beijing Tianjin Hebei Shanxi Inner Mongolia Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Shaanxi Gansu Qinghai Ningxia Xinjiang Annual average(%) SOHA_BP 2003 2007 A n n u al increasing rate N ational average Fig.10. V alues of SO H A B P in selected regions. -100.00% -70.00% -40.00% -10.00% 20 .00% 0 0.1 0.2 0.3 0.4 National The north The center east The south The west Municipalities Beijing Tianjin Hebei Shanxi Inner Mongolia Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Shaanxi Gansu Qinghai Ningxia Xinjiang Annual average(%) SOET_$ 2003 2007 A nnual increasing rate N ational averag e Fig.11. V alues of SO ET $ in selected regions. Y.G eng et al./ Energy 36 (2011) 4799 e 4808 4806 -120.00% -80.00% -40.00% 0.00% 40.00% 0 0.5 1 1.5 N at io na l Th e no rth Th e c en te r ea st Th e so u th Th e w es t M un ic ip al iti es B ei jin g Ti an jin H eb ei Sh an x i In ne r M on go lia Li ao n in g Jil in H ei lo ng jia ng Sh an gh ai Jia ng su Zh eji an g A nh ui Fu jia n Jia n gx i Sh an do n g H en an H ub ei H un an G ua ng do n g G ua n gx i H ai n an Ch on gq in g Si ch u an G ui zh ou Y un na n Sh aa n x i G an su Qi n gh ai N in gx ia X in jia ng A nnual av erage(% )SO ET _B P 2003 2007 annual increasing rate National average ETBP Y. Geng et al. / Energy 36 (2011) 4799e4808 4807 Fig. 12. Values of SO 300 400 J/h ) Finally, in order to identify the key factors for driving or impeding societal metabolism of various regions, we undertook a further analysis by using complete decomposition model. Fig. 14 shows the impact of contribution of resource and technology aggregation and sector structure to thechangeof exosomaticmetabolismrate.Wecan see that regions in north China and west China rely on resource and technology aggregation for their economic development, while 0 100 200 N at io na l Th e no rth Th e ce nt er e as t Th e so u th Th e w es t M un ic ip al iti es B ei jin g Ti an jin H eb ei Sh an x i In ne r M on go lia Li ao n in g Jil in H ei lo ng jia ng Sh an gh ai Jia ng su BE P( M Fig. 13. BEP values in the selecte 0% 20% 40% 60% 80% 100% N at io na l Th e no rth Th e c en te r ea st Th e so u th Th e w es t M un ic ip al iti es B ei jin g Ti an jin H eb ei Sh an x i In ne r M on go lia Li ao n in g Jil in H ei lo ng jia ng Sh an gh ai Jia ng su C on tr ib ut io n ra te (% ) EMR_aggregation Fig. 14. Contribution of resources and technology in selected regions. National average regions in south China and central east China rely on sector structure for their economic development. This exactly reflects the fact that both west and north China are resource-rich regions and develop their economy by exploring natural resources, while both east and south China mainly focus on manufacturing and service industries. However, natural resource will sooner or later be depleted. Thus, these regions have to reconsider their long term development Zh eji an g A nh ui Fu jia n Jia n gx i Sh an do ng H en an H ub ei H un an G ua n gd on g G ua ng xi H ai n an Ch on gq in g Si ch u an G ui zh ou Y un na n Sh aa n x i G an su Qi n gh ai N in gx ia X in jia ng d Chinese regions for 2007. Zh eji an g A nh ui Fu jia n Jia n gx i Sh an do n g H en an H ub ei H un an G ua n gd on g G ua n gx i H ai n an Ch on gq in g Si ch u an G ui zh ou Y un n an Sh aa n x i G an su Qi n gh ai N in gx ia X in jia ng EMR_structure , and sector structure to the change of EMR. approach, moving from resource based industry to more service and high-tech based industry. The central government also recognized such a dilemma and therefore initiated both west development and Generally, MSIASM method provides a feasible way for governments at different levels to recognize main barriers and challenges of their development. By providing a systematic picture Y. Geng et al. / Energy 36 (2011) 4799e48084808 northeast old industrial base revitalization projects in early 2000’s. Themain missions include activities of changing industrial structure in such regions, facilitating service industry, improving local infra- structure and capacity building. We believe that such actions can help balance regional development so that the whole country can move towards a harmonious society, a target set up by the central government. 4. Conclusions Science for sustainability policy requires the handling of multi- dimensional and multi-scale analyses. Integrated assessment is about generating information relevant for decision-making. In this regard, MSIASM is an appropriate approach to evaluate the overall eco-efficiency of regional development. Such an approach can help both national and regional governments identify key barriers of their development, thus, stipulating appropriate policies to balance various sectors and various regions. Especially, by providing a systematic picture on exosomatic energy consumption in different sectors and regions, decision-makers can recognize both strength and weakness of their development, as well as challenges and opportunities. As the largest developing country, China has made significant progress on economic development. However, without a compre- hensive consideration on various sectors and regions, such a rapid development also brought many challenges to the whole country, such as resource depletion and environmental pollution. By employing the method of MSIASM, we identified the imbalanced nature of Chinese development. Both west and north China regions are resource-rich and rely on heavy industry for their development, but lack of support for service industry, while east and south China have better sector structure, but lack of attention on improving people’s social well-being. Such a reality requires that west and north China regions should support efforts to minimize the dependence on natural resources and heavy industries and more developed south and east China regions should offer more public services to improve the life quality of their citizens, rather than only focusing on developing economy. Large cities, such as Beijing and Shanghai, have already reached the level of many developed countries in terms of social and economic development. But there is a great gap between urban and rural areas and such a gap is becoming bigger. With a fact that over 50% population is rural population, how to stipulate appropriate policies so as to reduce such a gap will be the next focal point of Chinese government. Further, with the continuous implementation of “one child policy”, the increasing elder population will bring more challenges to the whole society, thus, requiring Chinese government to take necessary actions, such as providing suitable infrastructure and improving public health care and education service. From sector point of view, industrialization is the common driving force for the Chinese government to develop their economy. But such industri- alization has also brought negative environmental impacts to the country, thus, sound industrialization policies are of paramount importance. It calls for smart management of resources and the adoption of an environmentally responsible development strategy. It also calls for great development of service industries and more attention on household sector. of their social development, those decision-makers can raise more appropriate policies so that they can seek sustainable development through optimizing the overall eco-efficiency of the whole economic systems. Acknowledgments This project is supported by the Natural Science Foundation of China (71033004), Chinese Academy of Science’s “one hundred talent program” (2008-318), Ministry of Science and technology (2011BAJ06B01), the Shenyang Scientific Research Foundation (1091147-9-00, F10-238-6-00), the Liaoning Science Foundation (20092078). References [1] Geng Y, Doberstein B. Developing the circular economy in China: challenges and opportunities for achieving leapfrog development. International Journal of Sustainable Development and World Ecology 2008;15(3):231e9. [2] Mayumi K. Temporary emancipation from land: from the industrial revolution to the present time. Ecological Economics 1991;4:35e56. [3] Giampietro M, Mayumi K. A dynamic model of socioecononmic systems based on hierarchy thoery and its application to sustainability. Structural Change and Economic Dynamics 1997;8(4):453e69. [4] Giampietro M, Mayumi K. Multiple-scale integrated assessment of societal metabolism: introducing the approach. Population and Environment 2000; l22:109e53. [5] Pastore G, Giampietro M, Mayumi. Societal metabolism and multiple-scale integrated assessment: empirical validation and examples of application. Population and Environment 2000;22(2):211e54. [6] Giampietro M, Mayumi K, Ramos-Martin J. Multi-scale integrated analysis of societal and ecosystem metabolism (MuSIASEM): theoretical concepts and basic rationale. Energy 2009;34:313e22. [7] Giampietro M. Socioeconomic pressure, demographic pressure. environ- mental loading and technological changes in agriculture. Agriculture, Ecosystems and Environment 1997;65:201e29. [8] Giampietro M, Mayumi K, RamosdMartin J. Can biofuels replace fossil energy fuels?A multi-scale integrated analysis based on the concept of societal and ecosystem metabolism：Part 1. International. Journal of Transdisciplinary Research 2006;1(1):51e87. [9] FalconidBenitez F. Integrated assessment of the recent economic history of Ecuador. Population and Environment 2001;22(3):257e80. [10] Iorgulescu R, Polimeni J. A multi-scale integrated analysis of the energy use in Romania, Bulgaria, Poland and Hungary. Energy 2009;34:341e7. [11] RamosdMartin J. Historical analysis of energy intensity of Spain: from a “conventional view” to an “integrated assessment”. Population and Envi- ronment 2001;22(3):281e313. [12] Ramos-Martin J, Giampietro M, Mayumi K. On China’s exosomatic energy metabolism: an application of multi-scale integrated analysis of societal metabolism(MSIASM). Ecological Economics 2007;63:174e91. [13] Wang TS, Sun CQ, Zhang ZQ. The analysis of Gansu’s social econmic devel- opment in terms of “Human activity”: the application of multiple-scale inte- grated assessment of societal metabolism (MSIASM). Gansu Social Sciences 2008;3:213e24 [in Chinese]. [14] Wang TS. The rational of multiple-scale integrated assessment of societal metabolism. Advances in Earth Science 2008;23:63e9 [in Chinese]. [15] Women’s Studies Institute of China & Department of Social Science of National Bureau of Statistics of China. Gender statistics of China (1990-1995). Beijing: China Statistics Press; 1998. [16] Sun JW. Changes in energy consumption and energy intensity: a complete decomposition model. Energy Economics 1998;20(1):85e100. [17] Streets DG, Jiang KJ, Hu XL, Sinton JE, Zhang XQ, Xu DY, et al. Recent reduc- tions in China’s greenhouse gas emission. Science 2001;294:1835e7. [18] Wang C, Chen JN, Zou J. Decomposition of energy-related CO2 emission in China: 1957-2000. Energy 2005;30:73e83. [19] State Statistics Bureau. China energy Statistical yearbook for 2003-2008. Beijing: China Statistics Press; 2003-2008. [20] Geng Y, Zhu QH, Doberstein B, Fujita T. Implementing China’s circular economy concept at the regional level: a review of progress in Dalia, China. Waste Management 2009;29:996e1002. Regional societal and ecosystem metabolism analysis in China: A multi-scale integrated analysis of societal metabolism(MSIA ... 1 Introduction 2 Methodology 2.1 Hour based human time 2.2 Joule based exosomatic energy throughput 2.3 Exosomatic metabolism rate (EMR) 2.4 Bio-economic pressure (BEP) 3 Results and discussion 4 Conclusions Acknowledgments References