公路运输碳排放空间关联性及影响因素研究

Spatial Correlation and Influencing Factors of Road Transportation Carbon Emissions

基于2010年,2015年和2019年中国30个省域物流公路运输碳排放数据和空间关系网,采用社会网络分析法(social network analysis,SNA)、地理信息系统(geographic information system,GIS)和地理探测器,从整体碳排放空间分布、整体网络结构演变、网络密度、凝聚子群、网络节点以及影响因素等角度分析我国30个省份公路运输碳排放空间分布和特征。结果表明:(1)从空间分布看,2010—2019年公路运输碳排放空间分布中部和南部排放量较多,西部和北部较少;(2)整体网络分析中,网络结构具有明显的核心-边缘结构,核心省份网络密度高且具有较发达的公路网络体系;(3)在不同的省份中,以广东省为例的中部和东部省份处于网络连接的核心,而甘肃省等较为偏远的省份处于网络的边缘;(4)产业结构、货运量和载货汽车拥有量对碳排放影响最大,而且交叉因子的影响作用大于单一因素的影响作用。

Based on the carbon emission data and spatial relationship network of logistics road transportation in 2010,2015,and 2019 in 30 provinces of China,this paper used social network analysis(SNA),geographic information system(GIS)and geographic detectors to analyze,the spatial distribution and characteristics of the carbon emissions from the perspectives of overall emission spatial distribution,overall network structure evolution,network density,cohesive subgroups,network nodes and influencing factors.The results show that:(1)From the perspective of the spatial distribution,the highway carbon emission from 2010 to 2019 is higher in the central and southern prorinces,and lower in the western and northern ones.(2)In the overall network analysis,the network has obvious core edge structure,and the core provinces have high network density and more developed highway network system.(3)Different province plays a different role.Guangdong and other central and eastern provinces are at the core of the network connection,while Gansu and other remote provinces are at the edge of the network.(4)Industrial structure,freight volume and truck ownership have the greatest impact on the carbon emissions,and the impact of interleaving factors is greater than that of a single one.