Analysis of the influencing factors on CO2 emissions at different urbanization levels: regional difference in China based on panel estimation

  • Yanan Wang
  • Wei ChenEmail author
  • Minjuan Zhao
  • Bowen Wang
Original Paper


A large amount of carbon dioxide emissions have drawn more and more attention recently. Existing regional research is mainly based on the classification of geographical location, without considering the differences in urbanization. Using panel data of 30 provinces in China during the period of 1997–2014, this paper investigates the impact of population, per capita GDP, energy intensity, urbanization, industry proportion and tertiary industry proportion on CO2 emissions. Taking into account regional differences, 30 provinces in China are divided into four regions according to the features of “urbanization–CO2 emissions.” The results show that the impacts of population and per capita GDP on CO2 emissions in the LU–LC region are higher than the other three regions. The energy intensity has positive effect on CO2 emissions in the four regions. The impact of energy intensity on CO2 emissions in HU–HC and HU–LC regions is greater than the other two regions. Meanwhile, the impact of urbanization on CO2 emissions differs across regions. The urbanization has a significant negative effect on CO2 emissions in the HU–LC region, indicating the urbanization increases CO2 emissions. However, the urbanization has a positive effect on CO2 emissions in the LU–HC region, indicating the urbanization increases CO2 emissions in the region. The impact of industry proportion is not statistically significant in all the regions, while the impact of tertiary industry proportion on CO2 emissions is negatively significant in the HU–LC and LU–HC regions, which indicates that the adjustment and upgrading of industrial structure play important roles in the decrease in carbon emissions.


Regional difference Urbanization CO2 emissions STIRPAT model 



This study was funded by the Project of Humanities and Social Sciences of the Ministry of Education of China (18XJC790014), Major projects of the National Social Science Foundation of China (15ZDA052); the National Natural Science Foundation of China (71503200, 41602336); the Research Start-up Funds of Northwest A&F University (2452016161, Z109021611); the Fundamental Research Funds for the Central Universities (2452015231, 2017RYWB01, 2017RWYB06); the Shaanxi soft science project (2016KRM054); and the Science and technology planning project of Yangling demonstration zone (2015RKX-03).


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Yanan Wang
    • 1
  • Wei Chen
    • 1
    Email author
  • Minjuan Zhao
    • 1
  • Bowen Wang
    • 1
  1. 1.College of Economics and ManagementNorthwest A&F UniversityYanglingChina

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