Influencing Factors and Their Spatial–Temporal Heterogeneity of Urban Transport Carbon Emissions in China

Abstract

Based on the panel data of China’s 284 prefecture-level cities from 2006 to 2020, this study employs spatial econometric and geographically weighted regression models to systematically analyze the influencing factors and their spatial–temporal heterogeneity of urban transport carbon emissions. The findings reveal the following: (1) GDP per capita, population, urban road area, and private car per capita are important factors causing the increase in urban transport carbon emissions, while the improvement of urban density, public transportation effectiveness, and government environmental protection can mitigate emissions and promote low-carbon development in urban transportation. (2) The worsening impact of GDP per capita on urban transport carbon emissions shows a decreasing trend over time, forming a spatial gradient pattern of gradually increasing from southwest to northeast. However, a similar effect of population increase during the research period, which currently displays an increasing spatial differentiation from north to south in sequence. (3) As another key deteriorating urban transport carbon emission, the influencing degree of private car per capita has gradually decreased from 2006 to 2020 and represented certain spatial gradient patterns. (4) Although the urban road area is favorable to urban transport carbon reduction in the early stage, it gradually begins to change in an unfavorable direction. The urban density is the contrary, i.e., the increase in that begins to play a positive role in promoting the development of low-carbon transportation among more cities. In addition, the influence coefficient of the former also presents an increasing distribution characteristic from south to north. (5) The reduction effect of public transportation effectiveness and government environmental protection on transport carbon emissions are both gradually prominent, where the former also shows space inertia of “increasing gradient from north to south and from north to northeast”.