Driving characteristics of the spatial correlation pattern of carbon emissions from provincial transportation in China
Based on the provincial transportation carbon emission data from 2003 to 2020,the macro pattern,micro connectivity and driving characteristics of China's transportation carbon emission spatial correlation network were studied based on the modular structure analysis and the exponential random graph model.The spatial correlation network of China's transport carbon emissions presents periodic fluctuation characteristics,and the spatial distribution of hierarchical equilibrium development and core siphon has evolved into a new pattern with few core-mostly core-edge can be derived from results.Obvious spatial inertia,time inertia and regional concentration were shown in the carbon transfer path shows.In promoting the economic activities of trans-regional transportation collaborative emission reduction,brokerage attributes was instrumental.Reciprocity,connectivity and agglomeration of endogenous networks played an important driving role in the formation of transport carbon emission networks,and the driving relationship between emission,reception,inhibition and reciprocity among the attributes of actors was obvious.The influence of external networks had an obvious geographical proximity effect,showing a regular feature of geographical distance attenuation.Therefore,policy suggestions such as major projects in the short term,promoting the linkage of green transportation transformation,upgrading the level of coordination in the medium term,strengthening the coordination mechanism of cross-regional transportation carbon emission reduction,long-term top-level zero carbon design,and comprehensive coordination of industrialization-industrialization-marketization were proposed.
transportation carbon emissionmodal structure analysisexponential random graph modeldriving factor
万方数据
维普
