Environmental Science and Pollution Research

, Volume 26, Issue 16, pp 15920–15930 | Cite as

Extended STIRPAT model-based driving factor analysis of energy-related CO2 emissions in Kazakhstan

  • Chuanhe Xiong
  • Shuang ChenEmail author
  • Rui Huang
Research Article


Extended stochastic impact by regression on population, affluence, and technology model incorporating ridge regression was used to analyze the driving mechanism of energy-related CO2 emissions in Kazakhstan during 1992–2014. The research period was divided into two stages based on GDP of Kazakhstan in 1991 (85.70 × 109 dollars), the first stage (1992–2002), GDP < 85.70 × 109 dollars, the stage of economic recovery; the second stage (2003–2014), GDP > 85.70 × 109 dollars, the stable economic development stage. The results demonstrated that (1) population scale and the technological improvement were the dominant contributors to promote the growth of the CO2 emissions during 1992–2014 in Kazakhstan. (2) Economic growth and industrialization played more positive effect on the increase of the CO2 emissions in the stable economic development stage (2003–2014) than those in the stage of economic recovery (1992–2002). The proportion of the tertiary industry, the trade openness, and foreign direct investment were transformed from negative factors into positive factors in the stable economic development stage (2003–2014). (3) Due to the over-urbanization of Kazakhstan before the independence, the level of urbanization continued to decline, urbanization was the first factor to curb CO2 emissions during 1992–2014. Finally, some policy recommendations are put forward to reduce energy-related carbon emissions.


CO2 emissions Extended STIRPAT model Ridge regression Kazakhstan 


Funding information

This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA20010301), Jiangsu Natural Science Foundation (BK20181105), National Natural Sciences Foundation of China (41771140), Autonomous Deployment Project of Nanjing Institute of Geography and Limnology, CAS (NIGLAS2017QD12).


  1. Al-Mulali U, Ozturk I (2015) The effect of energy consumption, urbanization, trade openness, industrial output, and the political stability on the environmental degradation in the MENA (Middle East and North African) region. Energy 84:382–389CrossRefGoogle Scholar
  2. Al-mulali U, Sab CNBC (2012) The impact of energy consumption and CO2 emission on the economic and financial development in 19 selected countries. Renew Sust Energ Rev 16:4365–4369CrossRefGoogle Scholar
  3. Al-mulali U, Fereidouni HG, Lee JY, Sab CNBC (2013) Exploring the relationship between urbanization, energy consumption, and CO2 emission in MENA countries. Renew Sust Energ Rev 23:107–112CrossRefGoogle Scholar
  4. Ang BW (2004) Decomposition analysis for policy making in energy: which is the preferred method? Energy Policy 32:1131–1139CrossRefGoogle Scholar
  5. Ang BW, Liu FL (2001) A new energy decomposition method: perfect in decomposition and consistent in aggregation. Energy 26:537–548CrossRefGoogle Scholar
  6. Arunrat N, Wang C, Pumijumnong N (2016) Alternative cropping systems for greenhouse gases mitigation in rice field: a case study in Phichit province of Thailand. J Clean Prod 133:657–671CrossRefGoogle Scholar
  7. Bilgen S (2014) Structure and environmental impact of global energy consumption. Renew Sust Energ Rev 38:890–902CrossRefGoogle Scholar
  8. Bulletin of Chinese Academy of Sciences (2017) Synergy third pole region environment and “The Belt and Road” development. Bull Chin Acad Sci 32(Z2):23–25 (In Chinese)Google Scholar
  9. Cansino JM, Román R, Ordóñez M (2016) Main drivers of changes in CO2 emissions in the Spanish economy: a structural decomposition analysis. Energy Policy 89:150–159CrossRefGoogle Scholar
  10. Carlson KM, Gerber JS, Mueller ND et al (2017) Greenhouse gas emissions intensity of global croplands. Nat Clim Chang 7:63–68CrossRefGoogle Scholar
  11. Collins N, Bekenova K (2017) Fuelling the New Great Game: Kazakhstan, energy policy and the EU. Asia Europe Journal 15:1–20CrossRefGoogle Scholar
  12. Dace E, Muizniece I, Blumberga A, Kaczala A (2015) Searching for solutions to mitigate greenhouse gas emissions by agricultural policy decisions—application of system dynamics modeling for the case of Latvia. Sci Total Environ 527–528:80–90CrossRefGoogle Scholar
  13. Dahl C, Kuralbayeva K (2001) Energy and the environment in Kazakhstan. Energy Policy 29:429–440CrossRefGoogle Scholar
  14. EIA (2017) International Energy Statistics. Accessed 27 Nov 2017
  15. Gómez A, Dopazo C, Fueyo N (2014) The causes of the high energy intensity of the Kazakh economy: a characterization of its energy system. Energy 71:556–568CrossRefGoogle Scholar
  16. Government of Kazakhstan (2016) National Inventory Report. GoK, Kazakhstan, Astana, 300.Google Scholar
  17. Guan DB, Hubacek K, Weber CL, Peters GP, Reiner DM (2008) The drivers of Chinese CO2 emissions from 1980 to 2030. Glob Environ Chang 18:626–634CrossRefGoogle Scholar
  18. Guan D, Liu Z, Geng Y, Lindner S, Hubacek K (2012) The gigatonne gap in China’s carbon dioxide inventories. Nat Clim Chang 2:672–675CrossRefGoogle Scholar
  19. Hassiba RJ, Linke P (2017) On the simultaneous integration of heat and carbon dioxide in industrial parks. Appl Therm Eng 127:81–94CrossRefGoogle Scholar
  20. Hoekstra R, van den Bergh JCJM (2003) Comparing structural and index decomposition analysis. Energy Econ 25(1):39–64CrossRefGoogle Scholar
  21. Hoerl AE, Kennard RW (1970) Ridge regression: biased estimation for nonorthogonal problems. Technometrics 12:55–67CrossRefGoogle Scholar
  22. International Energy Agency (IEA) (2017) World Energy Statistics. Accessed 27 Nov 2017
  23. IPCC (2014) In: Core Writing Team, Pachauri RK, Meyer LA (eds) Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, Geneva 151 ppGoogle Scholar
  24. Jeong K, Kim S (2013) LMDI decomposition analysis of greenhouse gas emissions in the Korean manufacturing sector. Energy Policy 62:1245–1253CrossRefGoogle Scholar
  25. Jin W (2012) Can technological innovation help China take on its climate responsibility? An intertemporal general equilibrium analysis. Energy Policy 49:629–641CrossRefGoogle Scholar
  26. Jotzo F, Burke PJ, Wood PJ, Macintosh A, Stern DI (2012) Decomposing the 2010 global carbon dioxide emissions rebound. Nat Clim Chang 2:213–214CrossRefGoogle Scholar
  27. Kang JD, Zhao T, Liu N, Zhang X, Xu XS, Liu T (2014) A multi-sectoral decomposition analysis of city-level greenhouse gas emissions: case study of Tianjin, China. Energy 68:562–571CrossRefGoogle Scholar
  28. Karatayev M, Hall S, Kalyuzhnova Y, Clarke ML (2016) Renewable energy technology uptake in Kazakhstan: policy drivers and barriers in a transitional economy. Renew Sust Energ Rev 66:120–136CrossRefGoogle Scholar
  29. NRGI Kazakhstan report (2014) Natural Resource Governance Institute. Available at ( Accessed 27 Nov 2017
  30. Kofi AP, Bekoe W, Amuakwa-Mensah F, Mensah JT, Botchway E (2012) Carbon dioxide emissions, economic growth, industrial structure, and technical efficiency: empirical evidence from Ghana, Senegal, and Morocco on the causal dynamics. Energy 47:314–325CrossRefGoogle Scholar
  31. Li K, Lin B (2015) The improvement gap in energy intensity: analysis of China’s thirty provincial regions using the improved DEA (data envelopment analysis) model. Energy 84:589–599CrossRefGoogle Scholar
  32. Li F, Dong SC, Li X, Liang XX, Yang WZ (2011) Energy consumption-economic growth relationship and carbon dioxide emissions in China. Energy Policy 39:568–574CrossRefGoogle Scholar
  33. Li B, Gasser T, Ciais P et al (2016) The contribution of China’s emissions to global climate forcing. Nature 531:357–361CrossRefGoogle Scholar
  34. Li W, Sun W, Li GM, Cui PF, Wu W, Jin BH (2017) Temporal and spatial heterogeneity of carbon intensity in China’s construction industry. Resour Conserv Recycl 126:162–173CrossRefGoogle Scholar
  35. Li J, Chen Y, Li Z, Liu Z (2018) Quantitative analysis of the impact factors of conventional energy carbon emissions in Kazakhstan based on LMDI decomposition and STIRPAT model. J Geogr Sci 28(7):1001–1019CrossRefGoogle Scholar
  36. Liu Y, Yan B, Zhou Y (2015) Urbanization, economic growth, and carbon dioxide emissions in China: a panel cointegration and causality analysis. J Geogr Sci 26:131–152CrossRefGoogle Scholar
  37. Luo Y, Long X, Wu C, Zhang J (2017) Decoupling CO2 emissions from economic growth in agricultural sector across 30 Chinese provinces from 1997 to 2014. J Clean Prod 159:220–228CrossRefGoogle Scholar
  38. MacGregor J (2017) Determining an optimal strategy for energy investment in Kazakhstan. Energy Policy 107:210–224CrossRefGoogle Scholar
  39. Mensah JT (2014) Carbon emissions, energy consumption and output: a threshold analysis on the causal dynamics in emerging African economies. Energy Policy 70:172–182CrossRefGoogle Scholar
  40. Ministry of National Economy of the Republic of Kazakhstan (2012) Statistical yearbook of Kazakhstan. Accessed 15 Aug 2014
  41. Monacrovich E, Pilifosova O, Danchuk D et al (1996) Estimating the potential of greenhouse gas mitigation in Kazakhstan. Environ Manag 20(1):S57–S64CrossRefGoogle Scholar
  42. Mousavi B, Lopez NSA, Biona JBM, Chiu ASF, Blesl M (2017) Driving forces of Iran’s CO2 emissions from energy consumption: an LMDI decomposition approach. Appl Energy 206:804–814CrossRefGoogle Scholar
  43. Patarasuk R, Gurney KR, Keeffe DO et al (2016) Urban high-resolution fossil fuel CO2 emissions quantification and exploration of emission drivers for potential policy applications. Urban Ecosyst 19:1013–1039CrossRefGoogle Scholar
  44. Riti JS, Song DY, Shu Y, Kamah M (2017) Decoupling CO2 emission and economic growth in China: is there consistency in estimation results in analyzing environmental Kuznets curve? J Clean Prod 166:1448–1461CrossRefGoogle Scholar
  45. Saljnikov E, Saljnikov A, Rahimgalieva S et al (2014) Impact of energy saving cultivations on soil parameters in northern Kazakhstan. Energy 77:35–41CrossRefGoogle Scholar
  46. Sarbassov Y, Kerimray A, Tokmurzin D et al (2013) Electricity and heating system in Kazakhstan: exploring energy efficiency improvement paths. Energy Policy 60:431–444CrossRefGoogle Scholar
  47. Schweitzer GE (2008) Science policy in Kazakhstan. Science 322(5907):1474–1475CrossRefGoogle Scholar
  48. Shahbaz M, Loganathan N, Sbia R, Afza T (2015) The effect of urbanization, affluence and trade openness on energy consumption: a time series analysis in Malaysia. Renew Sust Energ Rev 47:683–693CrossRefGoogle Scholar
  49. Shahbaz M, Loganathan N, Muzaffar TA, Ahmed K, Jabran MA (2016) How urbanization affects CO2 emissions in Malaysia? The application of STIRPAT model. Renew Sust Energ Rev 57:83–93CrossRefGoogle Scholar
  50. Shuai C, Shen L, Jiao L, Wu Y, Tan Y (2017) Identifying key impact factors on carbon emission: evidences from panel and time-series data of 125 countries from 1990 to 2011. Appl Energy 187:310–325CrossRefGoogle Scholar
  51. Sugar L, Kennedy C, Leman E (2014) Greenhouse gas emissions from Chinese cities. J Ind Ecol 16(4):552–563CrossRefGoogle Scholar
  52. Sun D, Zhang Y, Xue R, Zhang Y (2017) Modeling carbon emissions from urban traffic system using mobile monitoring. Sci Total Environ 599:944–951CrossRefGoogle Scholar
  53. Tan H, Sun A, Lau H (2013) CO2 embodiment in China–Australia trade: the drivers and implications. Energy Policy 61:1212–1220CrossRefGoogle Scholar
  54. Tokbolat S, Al-Zubaidy S, Badr A (2016) Low-energy design for future housing developments in Kazakhstan: a case study. Energy Effic 9:211–222CrossRefGoogle Scholar
  55. Tsai MS, Chang SL (2013) Taiwan’s GHG mitigation potentials and costs: an evaluation with the MARKAL model. Renew Sust Energ Rev 20:294–305CrossRefGoogle Scholar
  56. Vetter SH, Sapkota TB, Hillier J et al (2017) Greenhouse gas emissions from agricultural food production to supply Indian diets: implications for climate change mitigation. Agric Ecosyst Environ 237:234–241CrossRefGoogle Scholar
  57. Wang C, Cai W, Lu X, Chen J (2007) CO2 mitigation scenarios in China’s road transport sector. Energy Convers Manag 48:2110–2118CrossRefGoogle Scholar
  58. Wang C, Zhang X, Du H, Wang F et al (2013a) Variations and influence factors of carbon emission of primary energy consumption in Kazakhstan. Arid Land Geogr 36(4):757–763 (In Chinese).Google Scholar
  59. Wang P, Wu W, Zhu B, Wei Y (2013b) Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China. Appl Energy 106:65–71CrossRefGoogle Scholar
  60. Wang C, Wang F, Zhang X et al (2017) Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang. Renew Sust Energ Rev 67:51–61CrossRefGoogle Scholar
  61. Wong SL, Chang Y, Chia WM (2013) Energy consumption, energy R&D and real GDP in OECD countries with and without oil reserves. Energy Econ 40:51–60CrossRefGoogle Scholar
  62. World Bank (2017a) World Development Indicators. Accessed 27 Nov 2017
  63. World Bank (2017b) World Development Indicators. Accessed 27 Nov 2017
  64. Xiong C, Yang D, Huo J, Zhao Y (2015) The relationship between energy consumption and economic growth and the development strategy of a low-carbon economy in Kazakhstan. J Arid Land 7(5):706–715CrossRefGoogle Scholar
  65. Xiong C, Yang D, Huo J (2016a) Spatial-temporal characteristics and LMDI-based impact factor decomposition of agricultural carbon emissions in Hotan Prefecture, China. Sustainability 8(3):262CrossRefGoogle Scholar
  66. Xiong C, Yang D, Xia F, Huo J (2016b) Changes in agricultural carbon emissions and factors that influence agricultural carbon emissions based on different stages in Xinjiang, China. Sci Rep 6:36912CrossRefGoogle Scholar
  67. Xu B, Lin B (2015) How industrialization and urbanization process impacts on CO2 emissions in China: evidence from nonparametric additive regression models. Energy Econ 48:188–202CrossRefGoogle Scholar
  68. Xu SC, He ZX, Long RY, Chen H (2016) Factors that influence carbon emissions due to energy consumption based on different stages and sectors in China. J Clean Prod 115:139–148CrossRefGoogle Scholar
  69. Ye B, Jiang J, Li C, Miao L, Tang J (2017) Quantification and driving force analysis of provincial-level carbon emissions in China. Appl Energy 198:223–238CrossRefGoogle Scholar
  70. York R, Rosa EA, Dietz T (2003) STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts. Ecol Econ 46:351–365CrossRefGoogle Scholar
  71. Zhang B, Chen GQ (2014) Methane emissions in China 2007. Renew Sust Energ Rev 30:886–902CrossRefGoogle Scholar
  72. Zhang W, Li K, Zhou D, Zhang W, Gao H (2016) Decomposition of intensity of energy-related CO2 emission in Chinese provinces using the LMDI method. Energy Policy 92:369–381CrossRefGoogle Scholar
  73. Zhang N, Liu Z, Zheng X, Xue J (2017) Carbon footprint of China’s belt and road. Science 357:1107CrossRefGoogle Scholar
  74. Zheng Y, Luo D (2013) Industrial structure and oil consumption growth path of China: empirical evidence. Energy 57:336–343CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and LimnologyChinese Academy of SciencesNanjingChina
  2. 2.Key Laboratory of Virtual Geographic Environment for the Ministry of EducationNanjing Normal UniversityNanjingChina

Personalised recommendations