| description abstract | Urban transportation significantly contributes to greenhouse gas emissions, with CO2 emissions from urban travelers varying across different regions. Identifying the determinants of residents’ travel-related CO2 emissions (TCE) from a spatial perspective is significant for formulating effective carbon reduction strategies. However, limited research explores the spatial heterogeneous relationship between TCE and its determinants. In this study, we focus on Guiyang, China, as a representative city and adopt Traffic Analysis Zones (TAZ) as geospatial units of analysis to capture regional differences in CO2 emissions. By analyzing data from the 2021 Guiyang resident travel survey, we measure per capita CO2 emissions and reveal that in Guiyang, each person emits 599.42 g of CO2 during their travels. Furthermore, we apply a semiparametric geographically weighted regression model to investigate the spatial nonstationarity of the variables’ impact on TCE. Our findings reveal that local variables have heterogeneous effects on TCE across different TAZs. For example, while the Huaxi district in southern Guiyang shows a negative correlation between TCE and the proportion of low-income individuals, most regions in Guiyang exhibit the opposite trend with a positive correlation. In the northern regions of Guiyang, such as Kaiyang and Xifeng, the proportion of car ownership negatively impacts TCE, contrasting with conclusions drawn from other regions. Moreover, the results of geographical variation tests indicate that sociodemographic attributes exhibit greater spatial heterogeneity in their influence on TCE, in contrast to built environment attributes. These results provide valuable theoretical support for policymakers in designing location-specific, low-carbon transportation policies, with significant implications for advancing sustainable transportation development. | |
