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Urban energy consumption and CO2 emissions in Bei**g: current and future

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Abstract

This paper calculates the energy consumption and CO2 emissions of Bei**g over 2005–2011 in light of the Bei**g’s energy balance table and the carbon emission coefficients of IPCC. Furthermore, based on a series of energy conservation planning program issued in Bei**g, the Long-range Energy Alternatives Planning System (LEAP)-BJ model is developed to study the energy consumption and CO2 emissions of Bei**g’s six end-use sectors and the energy conversion sector over 2012–2030 under the BAU scenario and POL scenario. Some results are found in this research: (1) During 2005–2011, the energy consumption kept increasing, while the total CO2 emissions fluctuated obviously in 2008 and 2011. The energy structure and the industrial structure have been optimized to a certain extent. (2) If the policies are completely implemented, the POL scenario is projected to save 21.36 and 35.37 % of the total energy consumption and CO2 emissions than the BAU scenario during 2012 and 2030. (3) The POL scenario presents a more optimized energy structure compared with the BAU scenario, with the decrease of coal consumption and the increase of natural gas consumption. (4) The commerce and service sector and the energy conversion sector will become the largest contributor to energy consumption and CO2 emissions, respectively. The transport sector and the industrial sector are the two most potential sectors in energy savings and carbon reduction. In terms of subscenarios, the energy conservation in transport (TEC) is the most effective one. (5) The macroparameters, such as the GDP growth rate and the industrial structure, have great influence on the urban energy consumption and carbon emissions.

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Notes

  1. Only road transport is considered in the transport sector because its high influence on total energy consumption and the civil aviation and railway are not included in our study.

  2. The “even and odd-numbered license plates” limit means that for one certain motor vehicle, it is only permitted to run on the driveway in every 2 days depending on whether the license plate number is even or odd. For example, on Monday, Wednesday, and Friday, only motor vehicles with even license plate number can be used on the driveway and those with odd license plate number are permitted to be used on Tuesday and Thursday.

  3. The industrial structure adjustment also belongs to the uncertainty of the implementation of measures and policies.

References

  • Arnold, M., & Barth, V. (2012). Open innovation in urban energy systems. Energy Efficiency, 5(3), 351–364.

    Article  Google Scholar 

  • Bei**g Statistical Bureau (2006–2012). Bei**g Statistical Yearbook (2006–2012). Bei**g: China Statistics Press. (In Chinese).

  • Bi, J., Zhang, R., Wang, H., Liu, M., & Wu, Y. (2011). The benchmarks of carbon emissions and policy implications for China’ cities: case of Nan**g. Energy Policy, 39(2011), 4785–4794.

    Article  Google Scholar 

  • Bohringer, C., & Rutherford, T. F. (2009). Integrated assessment of energy policies: decomposing top-down and bottom-up. Journal of Economic Dynamics and Control, 33, 1648–1661.

    Article  MathSciNet  Google Scholar 

  • Cai, W. J., Wang, C., Chen, J. N., Wang, K., Zhang, Y., & Li, X. D. (2008). Comparison of CO2 emission scenarios and mitigation opportunities in China’s five sectors in 2020. Energy Policy, 36(2008), 1181–1194.

    Article  Google Scholar 

  • Cai, Z., Ou, X., Zhang, X., Zhang, X., He, J., & **ng, Y. (2013). Comparative study of energy consumption and CO2 emissions between Bei**g and London. Frontiers in Energy, 7(1), 1–5.

    Article  Google Scholar 

  • de la Rue de Can, S., & Price, L. (2008). Sectoral trends in global energy use and greenhouse gas emissions. Energy Policy, 36(2008), 1386–1403.

    Article  Google Scholar 

  • Dhakal, S. (2003). Implications of transportation policies on energy and environment in Kathmandu Valley, Nepal. Energy Policy, 31(2003), 1493–1507.

    Article  Google Scholar 

  • Dhakal, S. (2009). Urban energy use and carbon emissions from cities in China and policy implications. Energy Policy, 37(2009), 4208–4219.

    Article  Google Scholar 

  • Fan, J.-L., Liao, H., Liang, Q.-M., Tatano, H., Liu, C.-F., & Wei, Y.-M. (2013). Residential carbon emission evolutions in urban–rural divided China: an end-use and behavior analysis. Applied Energy, 101(2013), 323–332.

    Article  MATH  Google Scholar 

  • Feng, Y. Y., & Zhang, L. X. (2012). Scenario analysis of urban energy saving and carbon abatement policies: a case study of Bei**g city, China. Procedia Environmental Sciences, 13(2012), 632–644.

    Article  Google Scholar 

  • Feng, Y. Y., Chen, S. Q., & Zhang, L. X. (2013). System dynamics modeling for urban energy consumption and CO2 emissions: a case study of Bei**g, China. Ecological Modelling, 252(2013), 44–52.

    Article  Google Scholar 

  • Gomi, K., Shimada, K., & Matsuoka, Y. (2010). A low-carbon scenario creation method for a local-scale economy and its application in Kyoto city. Energy Policy, 38(2010), 4783–4796.

    Article  Google Scholar 

  • Huang, C., Chen, C. H., Wang, B. Y., Dai, Y., Zhao, J., & Wang, H. K. (2005). Urban travel modal split and its impact on energy and environment. Journal of Highway and Transportation Research and Development, 22(11), 163–166 (In Chinese).

    Google Scholar 

  • IPCC. (2006). 2006 IPCC Guidelines for National Greenhouse Gas Inventories: volume II: energy. Japan: Institute for Global Environmental Strategies.

    Google Scholar 

  • IPCC. (2007). IPCC fourth assessment report (AR4). London: Cambridge University Press.

    Google Scholar 

  • Li, L., Chen, C., **e, S., Huang, C., Cheng, Z., Wang, H., et al. (2010). Energy demand and carbon emissions under different development scenarios for Shanghai, China. Energy Policy, 38(2010), 4797–4807.

    Article  Google Scholar 

  • Limmeechokchaia, B., & Chawana, S. (2007). Sustainable energy development strategies in the rural Thailand: the case of the improved cooking stove and the small biogas digester. Renewable Sustainable Energy Review, 11(5), 818–837.

    Article  Google Scholar 

  • Lin, J., Cao, B., Cui, S., Wang, W., & Bai, X. (2010). Evaluating the effectiveness of urban energy conservation and GHG mitigation measures: the case of **amen city, China. Energy Policy, 38(2010), 5123–5132.

    Article  Google Scholar 

  • Mi, Z.-F., Pan, S.-Y., Yu, H., & Wei, Y.-M. (2014). Potential impacts of industrial structure on energy consumption and CO2 emission: a case study of Bei**g. Journal of Cleaner Production in press.

  • National Bureau of Statistics P.R. China. (2012). China energy statistical yearbook (2012). Bei**g: China Statistics Press (In Chinese).

    Google Scholar 

  • Olivier, J.G.J., Janssens-Maenhout, G., Muntean, M., & Peters, J.A.H.W. (2013). (PBL) Trends in global CO2 emissions. PBL Netherlands Environmental Assessment Agency, Hague, Netherlands. ISBN: 978-94-91506-51-2.

  • Parshall, L., Gurney, K., Hammer, S. A., Mendoza, D., Zhou, Y., & Geethakumar, S. (2010). Modeling energy consumption and CO2 emissions at the urban scale: methodological challenges and insights from the United States. Energy Policy, 38(2010), 4765–4782.

    Article  Google Scholar 

  • Phdungsilp, A. (2010). Integrated energy and carbon modeling with a decision support system: policy scenarios for low-carbon city development in Bangkok. Energy Policy, 38(2010), 4808–4817.

    Article  Google Scholar 

  • Pradhan, S., Ale, B. B., & Amatya, V. B. (2006). Mitigation potential of greenhouse gas emission and implications on fuel consumption due to clean energy vehicles as public passenger transport in Kathmandu Valley of Nepal: a case study of trolley buses in Ring Road. Energy, 31(12), 1748–1760.

    Article  Google Scholar 

  • Roger, P. J., Wigley, T., & Green, C. (2008). Dangerous assumptions. Nature, 452, 531–532.

    Article  Google Scholar 

  • Rutter, P., & Keirstead, J. (2012). A brief history and the possible future of urban energy systems. Energy Policy, 50(2012), 72–80.

    Article  Google Scholar 

  • Shin, H.-C., Parka, J.-W., Kim, H.-S., & Shin, E.-S. (2005). Environmental and economic assessment of landfill gas electricity generation in Korea using LEAP model. Energy Policy, 33(2005), 1261–1270.

    Article  Google Scholar 

  • Solomon, S., Plattner, G.-K., Knutti, R., & Friedlingstein, P. (2009). Irreversible climate change due to carbon dioxide emissions. PNAS, 106, 1704–1709.

    Article  Google Scholar 

  • Steemers, K. (2003). Energy and the city: density, buildings and transport. Energy and Buildings, 35(2003), 3–14.

    Article  Google Scholar 

  • Stockholm Environment Institute (SEI). (2011). User guide, LEAP: long range energy alternative planning system. Boston: Stockholm Environment Institute.

    Google Scholar 

  • Wang, Q. Y. (2006). The energy conservation handbook 2006. Energy conservation and environmental protection. Bei**g: Magazine (In Chinese).

    Google Scholar 

  • Wang, K., Wang, C., Lv, X., & Chen, J. (2006). Abatement potential of CO2 emissions from China’s iron and steel industry based on LEAP. Journal of Tsinghua University (Science and Technology), 46(12), 1982–1986 (In Chinese).

    Google Scholar 

  • Wang, Z., Yin, F., Zhang, Y., & Zhang, X. (2012). An empirical research on the influencing factors of regional CO2 emissions: evidence from Bei**g city, China. Applied Energy, 100(2012), 277–284.

    Article  Google Scholar 

  • World Bank (2010). Cities and climate change: an urgent agenda. Washington DC.

  • **, F., Geng, Y., Chen, X., Zhang, Y., Wang, X., Xue, B., et al. (2011). Contributing to local policy making on GHG emission reduction through inventorying and attribution: a case study of Shenyang, China. Energy Policy, 39(2011), 5999–6010.

    Article  Google Scholar 

  • Ye, Y.-L., & Han, Y.-D. (2010). Effect of industrial development on energy intensity in Bei**g. Journal of North China Electric Power University (Social Sciences), 3, 16–20 (In Chinese).

    Google Scholar 

  • Yu, H., Yang, R., Zhang, Y., & Wang, S. (2013). Study on the energy demand and environmental emissions of urban transport—acase study of Bei**g. Journal of Bei**g Institute of Technology (Social Sciences edition), 15(5), 10–15 (In Chinese).

    Google Scholar 

  • Zhang, X. P. (2005). Temporal-spatial characteristics of energy consumption in China and its determinants since the 1990s. China Population, Resources and Environment, 15, 38–41 (In Chinese).

    Google Scholar 

  • Zhang, Q. Y., Tian, W. L., Wei, Y. M., & Chen, Y. X. (2007). External costs from electricity generation of China up to 2030 in energy and abatement scenarios. Energy Policy, 35(2007), 4295–4304.

    Article  Google Scholar 

  • Zhang, J., Zhang, Y., Yang, Z., Fath, B. D., & Li, S. (2013). Estimation of energy-related carbon emissions in Bei**g and factor decomposition analysis. Ecological Modelling, 252(2013), 258–265.

    Article  Google Scholar 

  • Zhou, D.,Levine, M., Dai, Y., Yu, C., Guo, Y., Sinton, J.E., et al. (2004). China’s sustainable energy future: scenarios of energy and carbon emissions (summary). Lawrence Berkeley National Laboratory. Paper LBNL-54067. <http://repositories.cdlib.org/lbnl/LBNL-54067>.

  • Zhou, J., Cui, S. H., Lin, J. Y., & Li, F. (2011). LEAP based analysis of transport energy consumption and air pollutants emission in **amen city. Environmental Science and Technology, 34(11), 164–170 (In Chinese).

    Google Scholar 

Download references

Acknowledgments

The authors gratefully acknowledge the financial support from National Natural Science Foundation of China (71020107026), the “Strategic Priority Research Program” of the Chinese Academy of Sciences (XDA05150600), National Basic Research Program of China under the Grant No. 2012CB955704.

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Authors and Affiliations

  1. Center for Energy and Environmental Policy Research, Bei**g Institute of Technology, 5 South Zhongguancun Street, Haidian District, Bei**g, 100081, China

    Hao Yu, Su-Yan Pan, Bao-Jun Tang, Zhi-Fu Mi, Yan Zhang & Yi-Ming Wei

  2. School of Management and Economics, Bei**g Institute of Technology, Bei**g, 100081, China

    Hao Yu, Su-Yan Pan, Bao-Jun Tang, Zhi-Fu Mi, Yan Zhang & Yi-Ming Wei

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  1. Hao Yu
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  2. Su-Yan Pan
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  5. Yan Zhang
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Correspondence to Yi-Ming Wei.

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Yu, H., Pan, SY., Tang, BJ. et al. Urban energy consumption and CO2 emissions in Bei**g: current and future. Energy Efficiency 8, 527–543 (2015). https://doi.org/10.1007/s12053-014-9305-3

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