首页|成渝城市群物流业集聚对物流业碳排放的时空异质性影响研究

成渝城市群物流业集聚对物流业碳排放的时空异质性影响研究

扫码查看
我国物流业的快速发展导致物流业能源消耗快速增长,造成我国物流业面临巨大的节能减排压力.随着成渝双城经济圈的建设,成渝城市群的物流行业得到快速发展,并在发展中逐渐形成集聚的态势.在分析2011-2020年成渝城市群物流业集聚水平与物流业碳排放情况的基础上,运用莫兰指数和局部莫兰散点图,分析成渝城市群物流业碳排放的空间自相关情况,并运用时空地理加权回归(GTWR)模型,研究成渝城市群内的城市在不同时间下的物流业集聚对物流业碳排放的时空异质性影响.研究结果表明,成渝城市群物流业碳排放呈空间集聚态势,且相对稳定;成渝城市群内城市的物流业集聚对物流业碳排放的影响系数分布具有时空异质性,2020年影响系数分布呈现"南北高、东西低"的态势.
Spatial-Temporal Heterogeneity Impact of Logistics Industry Agglomeration on Carbon Emissions from Logistics Industry in Chengdu-Chongqing Urban Agglomeration
The rapid development of China's logistics industry has led to a significant increase in energy consumption in the logistics industry,imposing substantial pressure on energy conservation and emission reduction in China's logistics industry.With the advancement of the Chengdu-Chongqing Economic Circle,the logistics industry in the Chengdu-Chongqing urban agglomeration has experienced rapid growth and has progressively developed into an agglomeration.Based on an analysis of logistics industry agglomeration levels and carbon emissions from the logistics industry in the Chengdu-Chongqing urban agglomeration from 2011 to 2020,this paper used the Moran index and local Moran scatter plot to analyze the spatial autocorrelation of carbon emissions from the logistics industry in the Chengdu-Chongqing urban agglomeration.The paper also studied the spatial-temporal heterogeneity impact of logistics industry agglomeration on carbon emissions from the logistics industry in different cities within Chengdu-Chongqing urban agglomeration at different time by using the geographically and temporally weighted regression(GTWR)model.The results show that the carbon emissions from the logistics industry in the Chengdu-Chongqing urban agglomeration are spatially clustered and relatively stable;the distribution of the impact coefficients of logistics industry agglomeration on carbon emissions from the logistics industry in the Chengdu-Chongqing urban agglomeration is spatially and temporally heterogeneous,and the distribution of impact coefficients in 2020 shows the trend of"high in the north and south and low in the east and west".

Chengdu-Chongqing Urban AgglomerationLogistics Industry AgglomerationCarbon Emissions from Logistics IndustryMoran IndexGeographically and Temporally Weighted Regression(GTWR)Model

肖红、李鑫汝、许荟珍、龚恒娟

展开 >

重庆交通大学 经济与管理学院,重庆 400074

重庆交通大学 重庆口岸物流与航运发展研究中心,重庆 400074

成渝城市群 物流业集聚 物流业碳排放 莫兰指数 GTWR模型

2025

铁道运输与经济
中国铁道科学研究院

铁道运输与经济

北大核心
影响因子:0.924
ISSN:1003-1421
年,卷(期):2025.47(1)