Urban Metabolic Efficiencies and Elasticities of Chinese Cities

SONG Tao; CAI Jianming; YANG Zhenshan; CHEN Mingxing; LIN Jing

doi:10.1007/s11769-016-0830-1

Urban Metabolic Efficiencies and Elasticities of Chinese Cities

doi: 10.1007/s11769-016-0830-1

1.
Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
2.
University of Chinese Academy of Sciences, Beijing 100049, China

基金项目: Under the auspices of National Natural Science Foundation of China (No. 41530634, 41530751), Key Consulting Project of the Chinese Academy of Science and Technology Strategic Consulting (No.Y02015001), Open Project Funding of Beijing Modern Industrial New Area Development Research Base in 2015 (No. JD2015002), Youth Innovation Promotion Association of Chinese Academy of Sciences (No. 2014042)

详细信息

通讯作者:
YANG Zhenshan.E-mail:yangzs@igsnrr.ac.cn

Urban Metabolic Efficiencies and Elasticities of Chinese Cities

1.
Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
2.
University of Chinese Academy of Sciences, Beijing 100049, China

Funds: Under the auspices of National Natural Science Foundation of China (No. 41530634, 41530751), Key Consulting Project of the Chinese Academy of Science and Technology Strategic Consulting (No.Y02015001), Open Project Funding of Beijing Modern Industrial New Area Development Research Base in 2015 (No. JD2015002), Youth Innovation Promotion Association of Chinese Academy of Sciences (No. 2014042)

More Information

Corresponding author: YANG Zhenshan.E-mail:yangzs@igsnrr.ac.cn

摘要: Urban metabolism is a complex system of materials, energy, population and environment, which usually can be measured by the Emergy Synthesis (ES) and the Slacks-Based Measure (SBM) approach. In this paper, by employing the two approaches of ES and SBM, as well as metabolic evolution index, urban metabolic stocks, efficiencies and elasticity of 31 Chinese cities are evaluated in a systematic way. The results imply that over the last decade (2000-2010), most of the cities, such as Chongqing, Nanjing, Shijiazhuang, Hangzhou, were experiencing drastic urban metabolic efficiency decline accompanied with a moderate decrease of industrial outputs. By contrast, metropolises and specialized cities have improved their urban metabolic performances, with higher output-input ratio and fewer undesirable outputs. However, their exported emergy experienced a substantial increase as well. It is concluded that local urban management might develop policies to diversify urban renewable supplies and address the undesirable output problems. The urban emergy of renewable resources should be specified as a prime focus for future research. In addition, mechanisms of different urban metabolic models will also be necessary for researchers.
- urban metabolism /
- emergy /
- Slacks-Based Measure (SBM) /
- metabolic elasticity
Abstract: Urban metabolism is a complex system of materials, energy, population and environment, which usually can be measured by the Emergy Synthesis (ES) and the Slacks-Based Measure (SBM) approach. In this paper, by employing the two approaches of ES and SBM, as well as metabolic evolution index, urban metabolic stocks, efficiencies and elasticity of 31 Chinese cities are evaluated in a systematic way. The results imply that over the last decade (2000-2010), most of the cities, such as Chongqing, Nanjing, Shijiazhuang, Hangzhou, were experiencing drastic urban metabolic efficiency decline accompanied with a moderate decrease of industrial outputs. By contrast, metropolises and specialized cities have improved their urban metabolic performances, with higher output-input ratio and fewer undesirable outputs. However, their exported emergy experienced a substantial increase as well. It is concluded that local urban management might develop policies to diversify urban renewable supplies and address the undesirable output problems. The urban emergy of renewable resources should be specified as a prime focus for future research. In addition, mechanisms of different urban metabolic models will also be necessary for researchers.
- urban metabolism /
- emergy /
- Slacks-Based Measure (SBM) /
- metabolic elasticity

[1]	Ascione M, Campanella L, Cherubinic F et al., 2009. Environmental driving forces of urban growth and development, an emergy-based assessment of the city of Rome, Italy. Landscape and Urban Planning, 93(3/4):238-249. doi: 10.1016/j.landurbplan.2009.07.011
[2]	Avkiran N K, Tone K, Tsutsui M, 2008. Bridging radial and non-radial measures of efficiency in DEA. Annals of Opera-tions Research, 164(1):127-138. doi: 10.1007/s10479-008-0356-8
[3]	Bristow D N, Kennedy C A, 2013. Urban metabolism and the energy stored in cities. Journal of Industrial Ecology, 17(5):656-667. doi: 10.1111/jiec.12038.
[4]	Boyd G A, Tolley G, Pang J, 2002. Plant level productivity, effi-ciency, and environmental performance of the container glass industry. Environmental and Resource Economics, 23(1):29-43. doi: 10.1023/A:1020236517937
[5]	Broto V, Allen A, Rapoport E, 2012. Interdisciplinary perspectives on urban metabolism. Journal of Industrial Ecology, 16(6):851-61. doi: 10.1111/j.1530-9290.2012.00556
[6]	Brown M T, Ulgiati S, 2002. Emergy evaluations and environ-mental loading of electricity production systems. Journal of Cleaner Production, 10(4):321-334. doi: 10.1016/S0959-6526(01)00043-9
[7]	Charnes A, Cooper W W, Rhodes E, 1978. Measuring the effi-ciency of decision making units. European Journal of Opera-tional Research, 2(6):429-444. doi: 10.1016/0377-2217(78)90138-8
[8]	Choi Y, Zhang N, Zhou P, 2012. Efficiency and abatement costs of energy-related CO₂ emissions in China:a slacks-based effi-ciency measure. Applied Energy, 98:198-208. doi: 10.1016/j.apenergy.2012.03.024
[9]	Cooper W W, Seiford L M, Tone K, 2000. Data Envelopment Analysis:A Comprehensive Text with Models, Applications, References and DEA-Solver Software. Boston:Kluwer Aca-demic Publishers.
[10]	Decker E H, Elliott S, Smith F A et al., 2000. Energy and material flow through the urban ecosystem. Annual Review of Energy and the Environment, 25:685-740. doi: 10.1146/annurev.energy.25.1.685
[11]	Fare R, Grosskopf S, Tyteca D, 1996. An activity analysis model of the environmental performance of firms-application to fos-sil-fuel-fired electric utilities. Ecological Economics, 18(2):161-175. doi: 10.1016/0921-8009(96)00019-5
[12]	Fare R, Grosskopf S, Noh D W et al., 2005. Characteristics of polluting technology:theory and practice. Journal of Econom-ics, 126(2):469-492. doi: 10.1016/j.jeconom.2004.05.010
[13]	Forkes J, 2007. Nitrogen balance for the urban food metabolism of Toronto. Canada Resources, Conservation and Recycling, 52(1):74-94. doi: 10.1016/j.resconrec.2007.02.003
[14]	Hanya T, Ambe Y, 1976. A Study on the Metabolism of Cities. Tokyo:HESC, Science Council of Japan.
[15]	Hendriks C D, Müller S, Kytzia P et al., 2000. Material flow analysis:a tool to support environmental policy decision mak-ing. Case studies on the city of Vienna and the Swiss lowlands. Local Environment, 5(3):311-328. doi: 10.1080/13549830050134257
[16]	Hu J L, Kao C H, 2007. Efficient energy-saving targets for APEC economies. Energy Policy, 35(1):373-382. doi: 10.1016/j.enpol.2005.11.032
[17]	Huang S L, 1998. Urban ecosystems, energetic hierarchies and ecological economics of Taipei metropolis. Journal of Envi-ronmental Management, 52(1):39-51. doi: 10.1006/jema.1997.0157
[18]	Huang S L, Hsu W L, 2003. Materials flow analysis and emergy evaluation of Taipei's urban construction. Landscape and Ur-ban Planning, 63(2):61-75. doi: 10.1016/S0169-2046(02)00152-4
[19]	Huang S L, Chen C W, 2005. Theory of urban energetics and mechanisms of urban development. Ecological Modelling, 189 (1-2):49-71. doi: 10.1016/j.ecolmodel.2005.03.004
[20]	Ingwersen W W, 2011. Emergy as a life cycle impact assessment indicator-a gold mining case study. Journal of Industrial Ecol-ogy, 15(4):550-567. doi: 10.1111/j.1530-9290.2011.00333.x
[21]	Keller P A,1992. Perspectives on Interfacing Paper Mill Wastewaters and Wetlands. Gainesville:University of Florida.
[22]	Kennedy C, Cuddihy J, Yan J E, 2007. The changing metabolism of cities. Journal of Industrial Ecology, 11(2):43-59. doi: 10.1162/jie.2007.1107
[23]	Kennedy C, Pincetl S, Bunje P, 2011. The study of urban metabo-lism and its applications to urban planning and design. Envi-ronmental Pollution, 159(8-9):1965-1973. doi: 10.1016/j.envpol.2010.10.022.
[24]	Li L B, Hu J L, 2012. Ecological total-factor energy efficiency of regions in China. Energy Policy, 46:216-224. doi: 10.1016/j.enpol.2012.03.053
[25]	National Bureau of Statistics of China, 2001-2011. China Statis-tical Yearbook 2001-2011. Beijing:China Statistics Press. (in Chinese)
[26]	National Bureau of Statistics of China, 2001-2011. China Urban Statistical Yearbook 2001-2011. Beijing:China Statistics Press. (in Chinese)
[27]	National Bureau of Statistics of China, 2001-2011. China Envi-ronmental Statistical Yearbook 2001-2011. Beijing:China Statistics Press. (in Chinese)
[28]	Newcombe K, Kalina J D, Aston A R, 1978. The metabolism of a city:the case of Hong Kong. A Journal of the Human Envi-ronment, 7(1):3-5.
[29]	Newman P W G, Birrel R, Holmes D, 1996. Human Settlements in State of the Environment Australia. Melbourne:CSIRO Pub-lishing.
[30]	Odum H T, 1971. Environment, Power, and Society. New York:Wiley.
[31]	Odum H T, 1983. System Ecology:An Introduction. New York:Wiley.
[32]	Odum H T, 1996. Environmental Accounting:Emergy and Envi-ronmental Decision Making. New York:Wiley.
[33]	Odum H T, Brown M T, Brandt-Williams S, 2000. Introduction and Global Budget. In:Handbook of emergy evaluation. Center for Environmental Policy, Environmental Engineering Sciences, Gainesville:University of Florida.
[34]	Ramanathan R, 2002. Combining indicators of energy consump-tion and CO₂ emissions:a cross-country comparison. Interna-tional Journal of Global Energy, 17(3):214-227. doi: http://dx.doi.org/10.1504/IJGEI.2002.000941
[35]	Rogers P P, Jalal K F, Lohani B N et al., 1997. Measuring Envi-ronmental Quality in Asia. Philippines:Asian Development Bank.
[36]	Seiford L M, Zhu J, 2005. A response to comments on modeling undesirable factors in efficiency evaluation. European Journal of Operational Research, 161:579-581. doi: 10.1016/j.ejor.2003.09.018
[37]	Song Tao, Cai Jianming, Xu Hui et al., 2015. Urban metabolism based on emergy and slack based model:a case study of Bei-jing, China. Chinese Geographical Science, 25(1):113-123. doi: 10.1007/s11769-014-0680-7
[38]	Stratton R W, Wong H M, Hileman J I, 2011. Quantifying varia-bility in life cycle greenhouse gas inventories for alternative middle distillate transportation fuels. Environmental Science & Technology, 45 (10):4637-4644. doi: 10.1021/es102597f
[39]	Sueyoshi T, Goto M, 2012. Environmental assessment by DEA radial measurement:U.S. coal-fired powerplants in ISO (In-dependent System Operator) and RTO (Regional Transmission Organization). Energy Economics, 34(3):663-676. doi: 10.y1016/j.eneco.2011.08.016
[40]	Tone K, 2001. A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130(3):498-509. doi: 10.1016/S0377-2217(99)00407-5
[41]	Tone K, 2004. Dealing with Undesirable Outputsin DEA:A Slacks-Based Measure (SBM) Approach. Presentation at NAPWIII, Toronto.
[42]	Tyteca D, 1996. On the measurement of the environmental per-formance of firms:a literature review and a productive effi-ciency perspective. Journal of Environmental Management, 46(3):281-308. doi: 10.1006/jema.1996.0022
[43]	Ulgiati S, Brown M T, 2009. Emergy and ecosystem complexity. Communications in Nonlinear Science and Numerical Simula-tion, 14(1):310-321. doi: 10.1016/j.cnsns.2007.05.028
[44]	Wolman A, 1965. The metabolism of the city. Scientific American, 213(3):179-190.
[45]	Wei C, Ni J, Du L, 2012. Regional allocation of carbon dioxide abatement in China. China Economic Review, 23(3):552-565. doi: 10.1016/j.chieco.2011.06.002
[46]	Zaim O, 2004. Measuring environmental performance of state manufacturing through changes in pollution intensities:a DEA framework. Ecological Economics, 48(1):37-47. doi: 10.1016/j.ecolecon.2003.08.003
[47]	Zhang Y, Yang Z F, Li W, 2006. Analyses of urban ecosystem based on information entropy. Ecological Modelling, 197 (1-2):1-12. doi: 10.1016/j.ecolmodel.2006.02.032
[48]	Zhang Y, Zhao Y W, Yang Z F et al., 2009a. Measurement and evaluation of the metabolic capacity of an urban ecosystem. Communications in Nonlinear Science and Numerical Simula-tion, 14(4):1758-1765. doi: 10.1016/j.cnsns.2008.03.017
[49]	ZhangY, Yang Z F, Yu X, 2009b. Evaluation of urban metabolism based on emergy synthesis:a case study for Beijing (China). Ecological Modelling, 220(13/14):1690-1696. doi: 10.1016/j.ecolmodel.2009.04.002
[50]	Zhang Y, Yang Z F, Fath B D, 2010a. Ecological network analysis of an urban water metabolic system:model development and a case study for Beijing. Science of the Total Environment, 408(20):4702-4711. doi: 10.1016/j.scitotenv.2010.06.019
[51]	Zhang Y, Yang Z, Fath B D et al., 2010b. Ecological network analysis of an urban energy metabolic system:model devel-opment, and a case study of four Chinese cities. Ecological Modelling, 221(25):1865-1879. doi: 10.1016/j.esd.2011.11.001
[52]	Zhou P, Ang B W, Poh K L, 2006. Slacks-based efficiency measures for modeling environmental performance. Ecological Economics, 60(1):111-118. doi: 10.1016/j.ecolecon.2005.12.001
[53]	Zhou P, Ang B W, Poh K L, 2008. A survey of data envelopment analysis in energy and environmental studies. European Jour-nal of Operational Research, 189(1):1-18. doi:10.1016/j.ejor. 2007.04.042

[1]	Shan MAN, Yongchun YANG, Tonggang ZENG, Meimei WANG. Cross-border Urban Networks Based on Manufacturing Global Value Chain: A Study of Listed Companies in Western China . Chinese Geographical Science, 2023, 33(6): 1033-1052. doi: 10.1007/s11769-023-1389-2
[2]	Yan CHEN, Miaomiao XIE, Bin CHEN, Huihui WANG, Yali TENG. Surface Regional Heat (Cool) Island Effect and Its Diurnal Differences in Arid and Semiarid Resource-based Urban Agglomerations . Chinese Geographical Science, 2023, 33(1): 131-143. doi: 10.1007/s11769-022-1324-y
[3]	Yanlin SU, Chunyan LU, Yue SU, Zili WANG, Yufei HUANG, Nuocheng YANG. Spatio-temporal Evolution of Urban Expansion Based on a Novel Adjusted Index and GEE: A Case Study of Central Plains Urban Agglomeration, China . Chinese Geographical Science, 2023, 33(4): 736-750. doi: 10.1007/s11769-023-1369-6
[4]	Chunjiang LI, Wanqu XIA, Yanwei CHAI. Delineation of an Urban Community Life Circle Based on a Machine-Learning Estimation of Spatiotemporal Behavioral Demand . Chinese Geographical Science, 2021, 31(1): 27-40. doi: 10.1007/s11769-021-1174-z
[5]	Fang LIU, Zengxiang ZHANG, Xiaoli ZHAO, Bin LIU, Xiao WANG, Ling YI, Lijun ZUO, Jinyong XU, Shunguang HU, Feifei SUN, Yafei WANG. Urban Expansion of China from the 1970s to 2020 Based on Remote Sensing Technology . Chinese Geographical Science, 2021, 31(5): 765-781. doi: 10.1007/s11769-021-1225-5
[6]	ZHENG Wensheng, KUANG Aiping, WANG Xiaofang, CHEN Jing. Measuring Network Configuration of the Yangtze River Middle Reaches Urban Agglomeration: Based on Modified Radiation Model . Chinese Geographical Science, 2020, 30(4): 677-694. doi: 10.1007/s11769-020-1131-2
[7]	CAO Yingqiu, XU Li, ZHANG Zhen, CHEN Zhi, HE Nianpeng. Soil Microbial Metabolic Quotient in Inner Mongolian Grasslands: Patterns and Influence Factors . Chinese Geographical Science, 2019, 29(6): 1001-1010. doi: 10.1007/s11769-019-1084-5
[8]	ZHANG Zengxiang, LIU Fang, ZHAO Xiaoli, WANG Xiao, SHI Lifeng, XU Jinyong, YU Sisi, WEN Qingke, ZUO Lijun, YI Ling, HU Shunguang, LIU Bin. Urban Expansion in China Based on Remote Sensing Technology: A Review . Chinese Geographical Science, 2018, 28(5): 727-743. doi: 10.1007/s11769-018-0988-9
[9]	QIAO Weifeng, GAO Junbo, LIU Yansui, QIN Yueheng, LU Cheng, JI Qingqing. Evaluation of Intensive Urban Land Use Based on an Artificial Neural Network Model:A Case Study of Nanjing City, China . Chinese Geographical Science, 2017, 27(5): 735-746. doi: 10.1007/s11769-017-0905-7
[10]	ZHU Jianhua, CHEN Xi, CHEN Tian. Spheres of Urban Influence and Factors in Beijing-Tianjin-Hebei Metropolitan Region Based on Viewpoint of Administrative Division Adjustment . Chinese Geographical Science, 2017, 27(5): 709-721. doi: 10.1007/s11769-017-0881-y
[11]	ZHENG Wensheng, RUN Jiying, ZHUO Rongrong, JIANG Yupei, WANG Xiaofang. Evolution Process of Urban Spatial Pattern in Hubei Province Based on DMSP/OLS Nighttime Light Data . Chinese Geographical Science, 2016, 26(3): 366-376. doi: 10.1007/s11769-016-0814-1
[12]	ZHANG Zuo, TAN Shukui, TANG Wenwu. A GIS-based Spatial Analysis of Housing Price and Road Density in Proximity to Urban Lakes in Wuhan City, China . Chinese Geographical Science, 2015, 25(6): 775-790. doi: 10.1007/s11769-015-0788-4
[13]	LU Yi, CAO Min, ZHANG Lei. A Vector-based Cellular Automata Model for Simulating Urban Land Use Change . Chinese Geographical Science, 2015, 25(1): 74-84. doi: 10.1007/s11769-014-0719-9
[14]	SONG Tao, CAI Jianming, XU Hui, DENG Yu, NIU Fangqu, YANG Zhenshan, DU Shanshan. Urban Metabolism Based on Emergy and Slack Based Model: A Case Study of Beijing, China . Chinese Geographical Science, 2015, 25(1): 113-123. doi: 10.1007/s11769-014-0680-7
[15]	YIN Kai, ZHAO Qianjun, LI Xuanqi, CUI Shenghui, HUA Lizhong, LIN Tao. A New Carbon and Oxygen Balance Model Based on Ecological Service of Urban Vegetation . Chinese Geographical Science, 2010, 20(2): 144-151. doi: 10.1007/s11769-010-0144-7
[16]	FANG Chuanglin, SONG Jitao, SONG Dunjiang. Stability of Spatial Structure of Urban Agglomeration in China Based on Central Place Theory . Chinese Geographical Science, 2007, 17(3): 193-202. doi: 10.1007/s11769-007-0193-8
[17]	ZHANG Xiu-ying, FENG Xue-zhi, DENG Hui. LAND-COVER DENSITY-BASED APPROACH TO URBAN LAND USE MAPPING USING HIGH-RESOLUTION IMAGERY . Chinese Geographical Science, 2005, 15(2): 162-167.
[18]	LIU Xin-wei, CHEN Bai-ming, ZHANG Ding-xiang. EMERGY ANALYSIS OF GRAIN PRODUCTION SYSTEM IN JIANGSU AND SHAANXI PROVINCES . Chinese Geographical Science, 2004, 14(3): 209-214.
[19]	ZHANG Xin-chang, PAN Qiong, ZHAO Ling-ling, YE Shen-tao. GIS-BASED ANALYSIS OF URBAN LAND-USE CHANGES—A Case Study of Haizhu District of Guangzhou City,China . Chinese Geographical Science, 2002, 12(4): 339-345.
[20]	LI Jiang, WANG Xiao-yan, GUO Qing-sheng. RESEARCH ON FRACTAL CHARACTERISTICS OF URBAN TRAFFIC NETWORK STRUCTURE BASED ON GIS . Chinese Geographical Science, 2002, 12(4): 346-349.

点击查看大图

计量

文章访问数: 523
HTML全文浏览量: 20
PDF下载量: 1005
被引次数: 0

姓名
邮箱
手机号码
标题
留言内容
验证码

留言板

Urban Metabolic Efficiencies and Elasticities of Chinese Cities

doi: 10.1007/s11769-016-0830-1

通讯作者:
YANG Zhenshan.E-mail:yangzs@igsnrr.ac.cn

Urban Metabolic Efficiencies and Elasticities of Chinese Cities

Corresponding author: YANG Zhenshan.E-mail:yangzs@igsnrr.ac.cn

计量

Urban Metabolic Efficiencies and Elasticities of Chinese Cities

doi: 10.1007/s11769-016-0830-1

1. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

2. University of Chinese Academy of Sciences, Beijing 100049, China

通讯作者: YANG Zhenshan.E-mail:yangzs@igsnrr.ac.cn

English Abstract

Urban Metabolic Efficiencies and Elasticities of Chinese Cities

1. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

2. University of Chinese Academy of Sciences, Beijing 100049, China

Corresponding author: YANG Zhenshan.E-mail:yangzs@igsnrr.ac.cn

全文HTML

目录

留言板

Urban Metabolic Efficiencies and Elasticities of Chinese Cities

doi: 10.1007/s11769-016-0830-1

通讯作者: YANG Zhenshan.E-mail:yangzs@igsnrr.ac.cn

Urban Metabolic Efficiencies and Elasticities of Chinese Cities

Corresponding author: YANG Zhenshan.E-mail:yangzs@igsnrr.ac.cn

计量

出版历程

Urban Metabolic Efficiencies and Elasticities of Chinese Cities

doi: 10.1007/s11769-016-0830-1

1. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; 2. University of Chinese Academy of Sciences, Beijing 100049, China

通讯作者: YANG Zhenshan.E-mail:yangzs@igsnrr.ac.cn

English Abstract

Urban Metabolic Efficiencies and Elasticities of Chinese Cities

1. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; 2. University of Chinese Academy of Sciences, Beijing 100049, China

Corresponding author: YANG Zhenshan.E-mail:yangzs@igsnrr.ac.cn

全文HTML

目录

通讯作者:
YANG Zhenshan.E-mail:yangzs@igsnrr.ac.cn

1. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

2. University of Chinese Academy of Sciences, Beijing 100049, China

1. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

2. University of Chinese Academy of Sciences, Beijing 100049, China