Energy Consumption and CO2 Emissions of Beijing Heating System: Based on a System Dynamics Model

  • Hefeng Tong
  • Weishuang Qu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7041)


Beijing is a typical North China city, and it uses about 15–18% of its total energy consumption for heating. The building construction industry is also a key source of CO2 emissions. This article, based on a system dynamics model, aims to simulate and forecast Beijing’s energy consumption and CO2 emissions under different scenarios. Under the baseline scenario, the energy consumption of Beijing’s heating system in 2030 will be 15.44 MTce and the corresponding CO2 emissions will be 9.71 MT. Gas is the major energy source for heating systems, accounting for more than 60% of the energy used. In the less building scenario, the energy used for heating in 2030 is projected to be 13.91 MTce, 9.88% less than baseline scenario. The cumulative saving in energy used for heating will be 19.39 MTce, with CO2 reductions of 12.38 MT. In the energy efficiency scenario, the energy consumed for heating in 2030 is projected to be 13.16 MTce, 14.73% less than baseline scenario. The cumulative saving in energy used for heating is projected to be 21.02 MTce, with a CO2 reduction of 12.13 MT. Thus, to achieve greater energy savings, a combination of policy measures, from both the demand side (smaller residential properties) and the technology side is needed.


Heating System Energy Consumption CO2 Emissions System Dynamics 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    IPCC (Intergovernmental Panel on Climate Change): Climate Change 2007: Mitigation of Climate Change. United Kingdom: Cambridge University Press (2007)Google Scholar
  2. 2.
    THUBERC: Development of China Building Energy Efficiency Annual Report 2008. China Building Industry Press, Beijing (2009)Google Scholar
  3. 3.
    Zhao, J., Zhu, N., Wu, Y.: Technology line and case analysis of heat metering and energy efficiency retrofit of existing residential buildings in northern heating areas of China. Energy Policy 37(6), 2106–2112 (2009)CrossRefGoogle Scholar
  4. 4.
    Forrester, J.W.: Industrial Dynamics. MIT Press, Cambridge (1961)Google Scholar
  5. 5.
    Naill, R.F.: A System Dynamics Model for National Energy Policy Planning. System Dynamics Review 8(1), 1–19 (1992)CrossRefGoogle Scholar
  6. 6.
    Ahmad, S., Simonovic, S.P.: Dynamic modeling of flood management policies. In: Proceedings of the 18th International Conference of the System Dynamics Society: Sustainability in the Third Millennium, Bergen, Norway, pp. 6–10 (2000)Google Scholar
  7. 7.
    Rodriguez-Ulloa, R., Paucar-Caceres, A.: Soft system dynamics methodology (SSDM): combining soft system methodology (SSM) and system dynamics (SD). Systemic Practice and Action Research 18(3), 303–334 (2005)CrossRefGoogle Scholar
  8. 8.
    Duran, Encalada, J., Paucar-Caceres, A.: System Dynamics Urban Sustainability Model for Puerto Aura in Puebla, Mexico. System Practice and Action Research 22(2), 77–99 (2009)CrossRefGoogle Scholar
  9. 9.
    Fong, W.K., Matsumoto, H., Lun, Y.F.: Application of System Dynamics model as decision making tool in urban planning process toward stabilizing carbon dioxide emissions from cities. Building and Environment 44(7), 1528–1537 (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Hefeng Tong
    • 1
  • Weishuang Qu
  1. 1.Institute of Scientific & Technical Information of ChinaBeijingChina

Personalised recommendations