4.6 Article

Impacts of Urbanization and Technology on Carbon Dioxide Emissions of Yangtze River Economic Belt at Two Stages: Based on an Extended STIRPAT Model

Journal

SUSTAINABILITY
Volume 13, Issue 13, Pages -

Publisher

MDPI
DOI: 10.3390/su13137022

Keywords

carbon dioxide emissions; STIRPAT; economic urbanization; energy intensity

Funding

  1. National Science Fund for Distinguished Young Scholars [71904059]
  2. Natural Science Research of Jiangsu Higher Education Institutions of China [19KJB580007]

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In the Yangtze River Economic Belt, the impact of urbanization and technology on CO2 emissions varies at different stages, with economic urbanization having the most significant effect on reducing CO2 emissions overall.
In the Yangtze River Economic Belt (YREB), one of the most important challenges at present is to promote green, low-carbon development. This study attempted to explore the impact of different dimensions of urbanization and technology on CO2 emissions at different stages in YREB by using an extended STIRPAT model on provincial panel data from 2000 to 2017. To examine the change differences based on the different effects of urbanization and technology on CO2 emissions, we divided the total study period into two stages according to the change trends of CO2 emissions and considered the YREB as a whole as well as the lower, middle, and upper reaches individually. The main findings are as follows. First, an inverted U relationship was found between economic urbanization and CO2 emissions for the entire study period along with the period of a rapid rise in CO2 emissions (Stage I) only in YREB and the upper reaches, while in the stable change period (Stage II), the inverted U relationship existed in the upper and lower reaches. An inverted U relationship between technology and CO2 emissions was only found in the middle reaches for Stage I and in the middle and lower reaches for Stage II. Second, during the entire study period, economic urbanization had the greatest inhibitory effect on carbon dioxide emissions, followed by energy intensity and population urbanization; during Stage I, the main reduction factors were economic urbanization and energy intensity, and population urbanization had a non-significant impact. Third, per capita gross domestic product (GDP) and population size had a positive impact on CO2 emission increases. Specifically, during Stage II, the fitting effect was not good (R-2 is 0.3948), and the whole formula was not significant. In lower reaches, the economic urbanization had a positive impact at Stage I, the energy intensity had a rebound effect and per capita GDP had a non-significant impact at Stage II.

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