Skip to main content
Log in

Urban metabolic efficiencies and elasticities of Chinese cities

  • Published:
Chinese Geographical Science Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • 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

    Article  Google Scholar 

  • Avkiran N K, Tone K, Tsutsui M, 2008. Bridging radial and non-radial measures of efficiency in DEA. Annals of Operations Research, 164(1): 127–138. doi: 10.1007/s10479-008-0356-8

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • Boyd G A, Tolley G, Pang J, 2002. Plant level productivity, efficiency, and environmental performance of the container glass industry. Environmental and Resource Economics, 23(1): 29–43. doi: 10.1023/A:1020236517937

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Brown M T, Ulgiati S, 2002. Emergy evaluations and environmental loading of electricity production systems. Journal of Cleaner Production, 10(4): 321–334. doi: 10.1016/S0959-6526(01)00043-9

    Article  Google Scholar 

  • Charnes A, Cooper W W, Rhodes E, 1978. Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6): 429–444. doi: 10.1016/0377-2217(78)90138-8

    Article  Google Scholar 

  • Choi Y, Zhang N, Zhou P, 2012. Efficiency and abatement costs of energy-related CO2 emissions in China: a slacks-based efficiency measure. Applied Energy, 98: 198–208. doi: 10.1016/j.apenergy.2012.03.024

    Article  Google Scholar 

  • 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 Academic Publishers.

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Fare R, Grosskopf S, Tyteca D, 1996. An activity analysis model of the environmental performance of firms-application to fossil-fuel-fired electric utilities. Ecological Economics, 18(2): 161–175. doi: 10.1016/0921-8009(96)00019-5

    Article  Google Scholar 

  • Fare R, Grosskopf S, Noh D W et al., 2005. Characteristics of polluting technology: theory and practice. Journal of Economics, 126(2): 469–492. doi: 10.1016/j.jeconom.2004.05.010

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Hanya T, Ambe Y, 1976. A Study on the Metabolism of Cities. Tokyo: HESC, Science Council of Japan.

    Google Scholar 

  • Hendriks C D, Müller S, Kytzia P et al., 2000. Material flow analysis: a tool to support environmental policy decision making. Case studies on the city of Vienna and the Swiss lowlands. Local Environment, 5(3): 311–328. doi: 10.1080/135498300 50134257

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Huang S L, 1998. Urban ecosystems, energetic hierarchies and ecological economics of Taipei metropolis. Journal of Environmental Management, 52(1): 39–51. doi: 10.1006/jema.1997.0157

    Article  Google Scholar 

  • Huang S L, Hsu W L, 2003. Materials flow analysis and emergy evaluation of Taipei′s urban construction. Landscape and Urban Planning, 63(2): 61–75. doi: 10.1016/S0169-2046(02)00152-4

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Ingwersen W W, 2011. Emergy as a life cycle impact assessment indicator-a gold mining case study. Journal of Industrial Ecology, 15(4): 550–567. doi: 10.1111/j.1530-9290.2011.00333.x

    Article  Google Scholar 

  • Keller P A, 1992. Perspectives on Interfacing Paper Mill Wastewaters and Wetlands. Gainesville: University of Florida.

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Kennedy C, Pincetl S, Bunje P, 2011. The study of urban metabolism and its applications to urban planning and design. Environmental Pollution, 159(8–9): 1965–1973. doi: 10.1016/j.envpol.2010.10.022.

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • National Bureau of Statistics of China, 2001–2011. China Statistical Yearbook 2001–2011. Beijing: China Statistics Press. (in Chinese)

    Google Scholar 

  • National Bureau of Statistics of China, 2001–2011. China Urban Statistical Yearbook 2001–2011. Beijing: China Statistics Press. (in Chinese)

    Google Scholar 

  • National Bureau of Statistics of China, 2001–2011. China Environmental Statistical Yearbook 2001–2011. Beijing: China Statistics Press. (in Chinese)

    Google Scholar 

  • Newcombe K, Kalina J D, Aston A R, 1978. The metabolism of a city: the case of Hong Kong. A Journal of the Human Environment, 7(1): 3–5.

    Google Scholar 

  • Newman P W G, Birrel R, Holmes D, 1996. Human Settlements in State of the Environment Australia. Melbourne: CSIRO Publishing.

    Google Scholar 

  • Odum H T, 1971. Environment, Power, and Society. New York: Wiley.

    Google Scholar 

  • Odum H T, 1983. System Ecology: An Introduction. New York: Wiley.

    Google Scholar 

  • Odum H T, 1996. Environmental Accounting: Emergy and Environmental Decision Making. New York: Wiley.

    Google Scholar 

  • 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.

    Google Scholar 

  • Ramanathan R, 2002. Combining indicators of energy consumption and CO2 emissions: a cross-country comparison. International Journal of Global Energy, 17(3): 214–227. doi: http://dx.doi.org/10.1504/IJGEI.2002.000941

    Article  Google Scholar 

  • Rogers P P, Jalal K F, Lohani B N et al., 1997. Measuring Environmental Quality in Asia. Philippines: Asian Development Bank.

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Song Tao, Cai Jianming, Xu Hui et al., 2015. Urban metabolism based on emergy and slack based model: a case study of Beijing, China. Chinese Geographical Science, 25(1): 113–123. doi: 10.1007/s11769-014-0680-7

    Article  Google Scholar 

  • Stratton R W, Wong H M, Hileman J I, 2011. Quantifying variability in life cycle greenhouse gas inventories for alternative middle distillate transportation fuels. Environmental Science & Technology, 45 (10): 4637–4644. doi: 10.1021/es102597f

    Article  Google Scholar 

  • Sueyoshi T, Goto M, 2012. Environmental assessment by DEA radial measurement: U.S. coal-fired powerplants in ISO (Independent System Operator) and RTO (Regional Transmission Organization). Energy Economics, 34(3): 663–676. doi: 10.y1016/j.eneco.2011.08.016

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Tone K, 2004. Dealing with Undesirable Outputsin DEA: A Slacks-Based Measure (SBM) Approach. Presentation at NAPWIII, Toronto.

    Google Scholar 

  • Tyteca D, 1996. On the measurement of the environmental performance of firms: a literature review and a productive efficiency perspective. Journal of Environmental Management, 46(3): 281–308. doi: 10.1006/jema.1996.0022

    Article  Google Scholar 

  • Ulgiati S, Brown M T, 2009. Emergy and ecosystem complexity. Communications in Nonlinear Science and Numerical Simulation, 14(1): 310–321. doi: 10.1016/j.cnsns.2007.05.028

    Article  Google Scholar 

  • Wolman A, 1965. The metabolism of the city. Scientific American, 213(3): 179–190.

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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 Simulation, 14(4): 1758–1765. doi: 10.1016/j.cnsns.2008.03.017

    Article  Google Scholar 

  • Zhang Y, 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Zhang Y, Yang Z, Fath B D et al., 2010b. Ecological network analysis of an urban energy metabolic system: model development, and a case study of four Chinese cities. Ecological Modelling, 221(25): 1865–1879. doi: 10.1016/j.esd.2011.11. 001

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Zhou P, Ang B W, Poh K L, 2008. A survey of data envelopment analysis in energy and environmental studies. European Journal of Operational Research, 189(1): 1–18. doi: 10.1016/j.ejor.2007.04.042

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhenshan Yang.

Additional information

Foundation item: 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)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, T., Cai, J., Yang, Z. et al. Urban metabolic efficiencies and elasticities of Chinese cities. Chin. Geogr. Sci. 26, 715–730 (2016). https://doi.org/10.1007/s11769-016-0830-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11769-016-0830-1

Keywords

Navigation