Research on Spatial Characteristics and Influencing Factors of Provincial Carbon Emissions in China

Kernel density distribution and Moran's Index methods were utilized to indicate the dynamic evolution trend and spatial cluster characteristics of carbon emissions among 30 provinces in China during 2000-2015. Spatial Durbin Model was constructed to explore the key influencing factors. The results are as follows:(1)Carbon emission density keeps a decreasing trend in this period and the low transformation trend has been accelerated since the New Normal Stage;(2)Spatial cluster characteristics of carbon emissions density in 30 provinces are mainly divided into "High-High" and "Low-Low" types. Moreover, this spatial spillover effects show a growing trend;(3)The economic scale and industrial structure of a province have a significant positive effect upon its carbon emission density while patent output scale has a significant negative effect. FDI scale and energy consumption structure of its neighborhood exert spatial spillover effects on its emission density significantly. On the one hand, to accelerate the pace of industrial structure adjustment, to optimize industrial spatial layouts and to develop green technology are the main ways in the future to stimulate regional low carbon transformation in China. Meanwhile, ecological town construction and continuously improving FDI quality are the potential factors to drive carbon emissions down. Spatial spillover effects among provinces in carbon emission reductions shouldn't be neglected.