Nonlinear Mechanism and Heterogeneous Path of Urban Carbon Peaking:Empirical Analysis Based on Panel Data of Prefecture-level Cities in Shandong Province
The issue of carbon dioxide emissions brought about by rapid economic development has become a globally recognized envi-ronmental problem,in response to this,China has proposed the"dual carbon"goal in 2020.As a major carbon-emitting province,the mechanism of carbon dioxide emissions and the trajectory towards carbon peak in Shandong Province are worthy of attention.Based on the Environmental Kuznets Curve(EKC),this paper employs the Panel Smooth Transition Regression model(PSTR)to empirically analyze the carbon peaking pathways at the prefecture-level cities in Shandong Province.Results indicate that the emissions of carbon dioxide in prefecture-level cities of Shandong Province are influenced by factors such as regional economic development level,industrial structure,population agglomeration,and level of technology.The relationship between economic development and carbon emissions conforms to the inverted"U-shaped"characteristic of the EKC curve.Heterogeneity analysis reveals that there is a significant regional heterogeneity in the carbon emission mechanisms and pathways among the prefecture-level cities in Shandong Province.Cities like Qingdao,Jinan,and Weihai have a higher per capita GDP level at the carbon peak point compared to other cities,which are likely ex-pected to be the first to achieve the carbon peak target in Shandong Province.In addition,light industry-dominated cities such as Binzhou,Dezhou,and Jining exhibit average carbon reduction levels within the province and need to particularly focus on optimizing industrial structures and controlling population sizes during the carbon reduction process.Heavy industry-dominated cities like Zaozhuang,Heze,and Zibo,which reach their carbon peak at relatively lower economic development levels,have higher proportions of heavy industry,for these cities,improving economic development levels and reasonably controlling population sizes are crucial for effec-tive carbon reduction.
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