IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v223y2011i1p14-19.html
   My bibliography  Save this article

Analysis of an urban energy metabolic system: Comparison of simple and complex model results

Author

Listed:
  • Zhang, Yan
  • Li, Shengsheng
  • Fath, Brian D.
  • Yang, Zhifeng
  • Yang, Naijin

Abstract

A fundamental difference between simple and complex systems is how the research objects are subdivided to support different study purposes. Based on a comparison between two urban energy system models – one with 5 and the other with 17 sectors – we concluded that the two models were most similar in terms of their description of the overall system structure and most different in terms of their description of specific intra-system relationships. The smaller number of system components and relationships in the 5-sector model facilitated judgments of the system's overall situation, thereby revealing where the key problems were found. In contrast, the 17-sector model provided enough details about the system to assist in the formulation of concrete operational measures to solve specific problems. Our results indicate that the division of a model into sectors should depend on the explicit problem to be solved and the context for that problem; different goals will require different numbers of system components. The results also demonstrate how simple and complex models can be used in tandem to examine a system from different perspectives.

Suggested Citation

  • Zhang, Yan & Li, Shengsheng & Fath, Brian D. & Yang, Zhifeng & Yang, Naijin, 2011. "Analysis of an urban energy metabolic system: Comparison of simple and complex model results," Ecological Modelling, Elsevier, vol. 223(1), pages 14-19.
  • Handle: RePEc:eee:ecomod:v:223:y:2011:i:1:p:14-19
    DOI: 10.1016/j.ecolmodel.2011.08.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380011004224
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2011.08.005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fath, Brian D., 2007. "Network mutualism: Positive community-level relations in ecosystems," Ecological Modelling, Elsevier, vol. 208(1), pages 56-67.
    2. Zhang, Yan & Yang, Zhifeng & Fath, Brian D. & Li, Shengsheng, 2010. "Ecological network analysis of an urban energy metabolic system: Model development, and a case study of four Chinese cities," Ecological Modelling, Elsevier, vol. 221(16), pages 1865-1879.
    3. Ramos-Martin, Jesus & Giampietro, Mario & Mayumi, Kozo, 2007. "On China's exosomatic energy metabolism: An application of multi-scale integrated analysis of societal metabolism (MSIASM)," Ecological Economics, Elsevier, vol. 63(1), pages 174-191, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Yan & Liu, Hong & Fath, Brian D., 2014. "Synergism analysis of an urban metabolic system: Model development and a case study for Beijing, China," Ecological Modelling, Elsevier, vol. 272(C), pages 188-197.
    2. Hu, Guangwen & Mu, Xianzhong, 2018. "Dominants in evolution of urban energy metabolism: A case study of Beijing," Ecological Modelling, Elsevier, vol. 385(C), pages 26-34.
    3. Zhai, Mengyu & Huang, Guohe & Liu, Lirong & Zheng, Boyue & Guan, Yuru, 2020. "Inter-regional carbon flows embodied in electricity transmission: network simulation for energy-carbon nexus," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    4. Chen, Shaoqing & Chen, Bin, 2015. "Urban energy consumption: Different insights from energy flow analysis, input–output analysis and ecological network analysis," Applied Energy, Elsevier, vol. 138(C), pages 99-107.
    5. Zhang, Yan & Li, Yanxian & Zheng, Hongmei, 2017. "Ecological network analysis of energy metabolism in the Beijing-Tianjin-Hebei (Jing-Jin-Ji) urban agglomeration," Ecological Modelling, Elsevier, vol. 351(C), pages 51-62.
    6. Zhang, Yan & Zheng, Hongmei & Fath, Brian D., 2014. "Analysis of the energy metabolism of urban socioeconomic sectors and the associated carbon footprints: Model development and a case study for Beijing," Energy Policy, Elsevier, vol. 73(C), pages 540-551.
    7. Duan, Cuncun & Chen, Bin, 2017. "Energy–water nexus of international energy trade of China," Applied Energy, Elsevier, vol. 194(C), pages 725-734.
    8. Li, Yanxian & Wang, Xinjing & Tian, Xin & Zhang, Yan, 2018. "Understanding the mechanism of urban material metabolism with ecological network analysis: An experimental study of Wuxi, China," Ecological Modelling, Elsevier, vol. 367(C), pages 58-67.
    9. Francisco Orlando Rosales & Brian D. Fath & Grace Yolanda Llerena, 2023. "Quantifying a virtual water metabolic network of the Metropolitan District of Quito, Ecuador using ecological network methods," Journal of Industrial Ecology, Yale University, vol. 27(5), pages 1304-1318, October.
    10. Zhang, Yan & Zheng, Hongmei & Yang, Zhifeng & Su, Meirong & Liu, Gengyuan & Li, Yanxian, 2015. "Multi-regional input–output model and ecological network analysis for regional embodied energy accounting in China," Energy Policy, Elsevier, vol. 86(C), pages 651-663.
    11. Panyam, Varuneswara & Huang, Hao & Davis, Katherine & Layton, Astrid, 2019. "Bio-inspired design for robust power grid networks," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    12. Adél Strydom & Josephine Kaviti Musango & Paul K. Currie, 2019. "Conceptualizing Household Energy Metabolism: A Methodological Contribution," Energies, MDPI, vol. 12(21), pages 1-19, October.
    13. Zhang, Yan & Lu, Hanjing & Fath, Brian D. & Zheng, Hongmei, 2016. "Modelling urban nitrogen metabolic processes based on ecological network analysis: A case of study in Beijing, China," Ecological Modelling, Elsevier, vol. 337(C), pages 29-38.
    14. Xuecheng Wang & Xu Tang & Baosheng Zhang & Benjamin C. McLellan & Yang Lv, 2018. "Provincial Carbon Emissions Reduction Allocation Plan in China Based on Consumption Perspective," Sustainability, MDPI, vol. 10(5), pages 1-23, April.
    15. Zhu, Xueting & Mu, Xianzhong & Hu, Guangwen, 2019. "Ecological network analysis of urban energy metabolic system—A case study of Beijing," Ecological Modelling, Elsevier, vol. 404(C), pages 36-45.
    16. Chen, Shaoqing & Chen, Bin, 2016. "Urban energy–water nexus: A network perspective," Applied Energy, Elsevier, vol. 184(C), pages 905-914.
    17. Meng, Fanxin & Liu, Gengyuan & Liang, Sai & Su, Meirong & Yang, Zhifeng, 2019. "Critical review of the energy-water-carbon nexus in cities," Energy, Elsevier, vol. 171(C), pages 1017-1032.
    18. Yang, Siyuan & Fath, Brian & Chen, Bin, 2016. "Ecological network analysis of embodied particulate matter 2.5 – A case study of Beijing," Applied Energy, Elsevier, vol. 184(C), pages 882-888.
    19. Chuang Tu & Xianzhong Mu & Yufeng Wu & Yifan Gu & Guangwen Hu, 2022. "Heterogenous impacts of components in urban energy metabolism: evidences from gravity model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(8), pages 10089-10117, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mingqi Zhang & Meirong Su & Weiwei Lu & Chunhua Su, 2015. "An Assessment of the Security of China’s Natural Gas Supply System Using Two Network Models," Energies, MDPI, vol. 8(12), pages 1-16, December.
    2. Borrett, Stuart R. & Sheble, Laura & Moody, James & Anway, Evan C., 2018. "Bibliometric review of ecological network analysis: 2010–2016," Ecological Modelling, Elsevier, vol. 382(C), pages 63-82.
    3. Zhang, Yan & Liu, Hong & Fath, Brian D., 2014. "Synergism analysis of an urban metabolic system: Model development and a case study for Beijing, China," Ecological Modelling, Elsevier, vol. 272(C), pages 188-197.
    4. Zhang, Yan & Zheng, Hongmei & Fath, Brian D., 2015. "Ecological network analysis of an industrial symbiosis system: A case study of the Shandong Lubei eco-industrial park," Ecological Modelling, Elsevier, vol. 306(C), pages 174-184.
    5. Zhu, Xueting & Mu, Xianzhong & Hu, Guangwen, 2019. "Ecological network analysis of urban energy metabolic system—A case study of Beijing," Ecological Modelling, Elsevier, vol. 404(C), pages 36-45.
    6. Yuting Wang & Lei Wang & Zhemin Li, 2020. "Dynamic Analysis of China’s Imported Raw Milk Powder Consumption," Sustainability, MDPI, vol. 12(4), pages 1-15, February.
    7. Lu, Weiwei & Su, Meirong & Fath, Brian D. & Zhang, Mingqi & Hao, Yan, 2016. "A systematic method of evaluation of the Chinese natural gas supply security," Applied Energy, Elsevier, vol. 165(C), pages 858-867.
    8. Patten, Bernard C. & Straškraba, Milan & Jørgensen, Sven E., 2011. "Ecosystems emerging. 5: Constraints," Ecological Modelling, Elsevier, vol. 222(16), pages 2945-2972.
    9. Mayumi, Kozo & Tanikawa, Hiroki, 2012. "Going beyond energy accounting for sustainability: Energy, fund elements and the economic process," Energy, Elsevier, vol. 37(1), pages 18-26.
    10. Kozo Mayumi & Mario Giampietro & Jesus Ramos-Martin, 2011. "Reconsideration of Dimensions and Curve Fitting Practice in Economics Elaborating on Georgescu-Roegen’s Economic Methodology," UHE Working papers 2011_05, Universitat Autònoma de Barcelona, Departament d'Economia i Història Econòmica, Unitat d'Història Econòmica.
    11. Xinhui Feng & Yan Li & Lu Zhang & Chuyu Xia & Er Yu & Jiayu Yang, 2022. "Carbon Metabolism in Urban “Production–Living–Ecological” Space Based on Ecological Network Analysis," Land, MDPI, vol. 11(9), pages 1-22, August.
    12. Xiaoyue Wang & Shuyao Wu & Shuangcheng Li, 2017. "Urban Metabolism of Three Cities in Jing-Jin-Ji Urban Agglomeration, China: Using the MuSIASEM Approach," Sustainability, MDPI, vol. 9(8), pages 1-21, August.
    13. Aliyu, Murtala Bello & Mohd, Mohd Hafiz, 2021. "The interplay between mutualism, competition and dispersal promotes species coexistence in a multiple interactions type system," Ecological Modelling, Elsevier, vol. 452(C).
    14. Andreoni, Valeria, 2020. "The energy metabolism of countries: Energy efficiency and use in the period that followed the global financial crisis," Energy Policy, Elsevier, vol. 139(C).
    15. Recalde, Marina & Ramos-Martin, Jesús, 2012. "Going beyond energy intensity to understand the energy metabolism of nations: The case of Argentina," Energy, Elsevier, vol. 37(1), pages 122-132.
    16. Pere Ariza-Montobbio & Susana Herrero Olarte, 2021. "Socio-metabolic profiles of electricity consumption along the rural–urban continuum of Ecuador: Whose energy sovereignty?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(5), pages 7961-7995, May.
    17. Zhai, Mengyu & Huang, Guohe & Liu, Lirong & Zheng, Boyue & Guan, Yuru, 2020. "Inter-regional carbon flows embodied in electricity transmission: network simulation for energy-carbon nexus," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    18. Zhang, Yan & Yang, Zhifeng & Fath, Brian D. & Li, Shengsheng, 2010. "Ecological network analysis of an urban energy metabolic system: Model development, and a case study of four Chinese cities," Ecological Modelling, Elsevier, vol. 221(16), pages 1865-1879.
    19. María Jesús Ávila-Gutiérrez & Alejandro Martín-Gómez & Francisco Aguayo-González & Juan Ramón Lama-Ruiz, 2020. "Eco-Holonic 4.0 Circular Business Model to Conceptualize Sustainable Value Chain towards Digital Transition," Sustainability, MDPI, vol. 12(5), pages 1-32, March.
    20. Fath, Brian D. & Scharler, Ursula M. & Baird, Dan, 2013. "Dependence of network metrics on model aggregation and throughflow calculations: Demonstration using the Sylt–Rømø Bight Ecosystem," Ecological Modelling, Elsevier, vol. 252(C), pages 214-219.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:223:y:2011:i:1:p:14-19. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.