Abstract
As one of the “three major strategies” for China’s regional development, the Yangtze River Economic Belt (YREB) is under severe pressure to reduce carbon dioxide emissions, this paper analyzes the spatiotemporal disparities, and driving factors of carbon emissions based on energy consumption and related economic development data in the YREB over the 2005–2016 11-year period. Using the Stochastic Impacts Regression on Population, Affluence and Technology (STIRPAT) model, we empirically test the factors affecting YREB carbon emissions and key drivers in various provinces and municipalities. The main findings are as follows. First, per capita GDP, both industrial structure and energy intensity have positive effects on increasing carbon emissions. Second, per capita GDP and energy intensity have the largest impact on the increase of carbon emissions, and the urbanization rate has the largest inhibitory effect on carbon emissions.
Highlights
Globally, climate change has brought severe challenges to human survival and development, China, as the country with the highest carbon dioxide (CO2) emissions, is especially pressured
To establish an effective emission reduction mechanism, the following questions must be clarified: Historically, what levels of carbon emissions have been experienced in the Yangtze River Economic Belt (YREB), which factors drive those carbon emissions and how are they related within the provinces and municipalities? To clarify, the main regions needed to achieve carbon emission reductions in the YREB and the key points of carbon emission reduction in different regions, this paper mainly analyzes these issues
We employed the Stochastic Impacts Regression on Population, Affluence and Technology (STIRPAT) model to analyze the impacts of the population size, wealth level, the urbanization rate, the industrial structure and energy intensity on regional carbon emissions, aiming to establish an effective emission reduction mechanism and aid local sustainable development decision-making
Summary
Climate change has brought severe challenges to human survival and development, China, as the country with the highest carbon dioxide (CO2) emissions, is especially pressured. To establish an effective emission reduction mechanism, the following questions must be clarified: Historically, what levels of carbon emissions have been experienced in the YREB, which factors drive those carbon emissions and how are they related within the provinces and municipalities? In this paper, taking the 11 provinces and municipalities in YREB as the study area, we studied the spatiotemporal change of carbon emissions. We employed the Stochastic Impacts Regression on Population, Affluence and Technology (STIRPAT) model to analyze the impacts of the population size, wealth level, the urbanization rate, the industrial structure and energy intensity on regional carbon emissions, aiming to establish an effective emission reduction mechanism and aid local sustainable development decision-making
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