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An empirical research on the influencing factors of regional CO2 emissions: Evidence from Beijing city, China

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Listed:
  • Wang, Zhaohua
  • Yin, Fangchao
  • Zhang, Yixiang
  • Zhang, Xian

Abstract

In order to further study the realization of carbon intensity target, find the key influencing factors of CO2 emissions, and explore the path of developing low-carbon economy, this paper empirically studied the influences of urbanization level, economic level, industry proportion, tertiary industry proportion, energy intensity and R&D output on CO2 emissions in Beijing using improved STIRPAT (stochastic impacts by regression on population, affluence and technology) model. The model is examined using partial least square regression. Results show that urbanization level, economic level and industry proportion positively influence the CO2 emissions, while tertiary industry proportion, energy intensity and R&D output negatively do. Urbanization level is the main driving factor of CO2 emissions, and tertiary industry proportion is the main inhibiting factor. In addition, along with the growth of per capita GDP, the increase of CO2 emissions does not follow the Environmental Kuznets Curve model. Based on these empirical findings and the specific circumstances of Beijing, we provide some policy recommendations on how to reduce carbon intensity. Beijing should pay more attention to tertiary industry and residential energy consumption for carbon emission reduction. It is necessary to establish a comprehensive evaluation index of social development. Investing more capital on carbon emission reduction science and technology, and promoting R&D output is also an efficient way to reduce CO2 emissions.

Suggested Citation

  • Wang, Zhaohua & Yin, Fangchao & Zhang, Yixiang & Zhang, Xian, 2012. "An empirical research on the influencing factors of regional CO2 emissions: Evidence from Beijing city, China," Applied Energy, Elsevier, vol. 100(C), pages 277-284.
  • Handle: RePEc:eee:appene:v:100:y:2012:i:c:p:277-284
    DOI: 10.1016/j.apenergy.2012.05.038
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    References listed on IDEAS

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    1. Jia, Junsong & Deng, Hongbing & Duan, Jing & Zhao, Jingzhu, 2009. "Analysis of the major drivers of the ecological footprint using the STIRPAT model and the PLS method--A case study in Henan Province, China," Ecological Economics, Elsevier, vol. 68(11), pages 2818-2824, September.
    2. Margolis, Robert M. & Kammen, Daniel M., 1999. "Evidence of under-investment in energy R&D in the United States and the impact of Federal policy," Energy Policy, Elsevier, vol. 27(10), pages 575-584, October.
    3. Wang, Can & Chen, Jining & Zou, Ji, 2005. "Decomposition of energy-related CO2 emission in China: 1957–2000," Energy, Elsevier, vol. 30(1), pages 73-83.
    4. Ke Wang & Shiwei Yu & Wei Zhang, 2011. "China's regional energy and environmental efficiency: A DEA window analysis based dynamic evaluation," CEEP-BIT Working Papers 17, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    5. Shafik, Nemat & Bandyopadhyay, Sushenjit, 1992. "Economic growth and environmental quality : time series and cross-country evidence," Policy Research Working Paper Series 904, The World Bank.
    6. Shi, Anqing, 2003. "The impact of population pressure on global carbon dioxide emissions, 1975-1996: evidence from pooled cross-country data," Ecological Economics, Elsevier, vol. 44(1), pages 29-42, February.
    7. York, Richard & Rosa, Eugene A. & Dietz, Thomas, 2003. "STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts," Ecological Economics, Elsevier, vol. 46(3), pages 351-365, October.
    8. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    9. Zhang, ZhongXiang, 2003. "Why did the energy intensity fall in China's industrial sector in the 1990s? The relative importance of structural change and intensity change," Energy Economics, Elsevier, vol. 25(6), pages 625-638, November.
    10. Paul, Shyamal & Bhattacharya, Rabindra Nath, 2004. "CO2 emission from energy use in India: a decomposition analysis," Energy Policy, Elsevier, vol. 32(5), pages 585-593, March.
    11. Knapp, Tom & Mookerjee, Rajen, 1996. "Population growth and global CO2 emissions : A secular perspective," Energy Policy, Elsevier, vol. 24(1), pages 31-37, January.
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    More about this item

    Keywords

    Carbon dioxide emission; STIRPAT model; Partial least square regression; Beijing city;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

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