Journal of Geographical Sciences ›› 2018, Vol. 28 ›› Issue (7): 1001-1019.doi: 10.1007/s11442-018-1518-5

• Special Issue: Geopolitical Environment Simulation on the Belt and Road Region • Previous Articles     Next Articles

Quantitative analysis of the impact factors of conventional energy carbon emissions in Kazakhstan based on LMDI decomposition and STIRPAT model

Jiaxiu LI1,2,3(), Yaning CHEN1,*(), Zhi LI1, Zhihui LIU2   

  1. 1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, CAS, Urumqi 830011, China
    2. College of Resource and Environment Science, Xinjiang University, Urumqi 830046, China
    3. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2017-09-26 Online:2018-07-20 Published:2018-07-20
  • Contact: Yaning CHEN E-mail:lijiaxiu15@163.com;chenyn@ms.xjb.ac.cn
  • About author:

    Author: Li Jiaxiu, PhD Candidate, specialized in climate change in central Asia. E-mail: lijiaxiu15@163.com

  • Supported by:
    CAS Strategic Priority Research Program, No.XDA19030204;CAS Western Light Program, No.2015-XBQN-B-17

Abstract:

Quantitative analysis of the impact factors in energy-related CO2 emissions serves as an important guide for reducing carbon emissions and building an environmentally-friendly society. This paper aims to use LMDI method and a modified STIRPAT model to research the conventional energy-related CO2 emissions in Kazakhstan after the collapse of the Soviet Union. The results show that the trajectory of CO2 emissions displayed U-shaped curve from 1992 to 2013. Based on the extended Kaya identity and additive LMDI method, we decomposed total CO2 emissions into four influencing factors. Of those, the economic active effect is the most influential factor driving CO2 emissions, which produced 110.86 Mt CO2 emissions, with a contribution rate of 43.92%. The second driving factor is the population effect, which led to 11.87 Mt CO2 emissions with a contribution rate of 4.7%. On the contrary, the energy intensity effect is the most inhibiting factor, which caused -110.90 Mt CO2 emissions with a contribution rate of -43.94%, followed by the energy carbon structure effect resulting in -18.76 Mt CO2 emissions with a contribution rate of -7.43%. In order to provide an in-depth examination of the change response between energy-related CO2 emissions and each impact factor, we construct a modified STIRPAT model based on ridge regression estimation. The results indicate that for every 1% increase in population size, economic activity, energy intensity and energy carbon structure, there is a subsequent increase in CO2 emissions of 3.13%, 0.41%, 0.30% and 0.63%, respectively.

Key words: quantitative analysis, energy-related CO2 emissions, STIRPAT model, Kazakhstan