English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper used the panel data of 30 provinces in China from year 2006 to 2018 to calculate the carbon emissions of each province. Moran’s I index is used to measure and analyze the spatial autocorrelation of carbon emissions among the provinces in China. The study considered three dimensions of urbanization such as population urbanization, land urbanization and economic urbanization to empirically analyze their effects on carbon emissions. In addition, spatial spillover effects were also explored. The main conclusions are as follows: (1) There is a positive spatial correlation between carbon emissions in China’s provinces, and Moran’s I index is greater than 0.5, indicating a significant correlation of carbon emissions; (2) in the context of three dimensions of urbanization, the direct effects are significant and positively influence regional carbon emission levels. Moreover, the indirect effects of population urbanization and land urbanization on regional carbon emissions are negative and coefficients are large. Whereas, the indirect effects of economic urbanization are small and insignificant. The total effect of population urbanization and economic urbanization are significantly positive and the total effects of land urbanization are found to be negative. (3) Environmental regulation and energy consumption structure as the control variables have a greater impact on carbon emissions, and the coefficient of the total effect is positive. Whereas, foreign direct investment and industrial structure have less impact and spatial spillover effects are not obvious.

The Impact of Multi-Dimensional Urbanization on China’s Carbon Emissions Based on the Spatial Spillover Effect