Abstract:

Numerous studies have examined the influencing factors of CO₂ emissions from transportation at the national, city and community levels. However, fewer studies have considered the effect of residential self-selection. Ignoring this effect is likely to result in underestimating the role of the built environment, thus affecting relevant planning and policy development. Is the effect of residential self-selection in Chinese cities the same as in Western cities? How and to what extent does the built environment affect CO₂ emissions from travel after controlling for the effect of residential self-selection? To address these questions, this paper first measures the CO₂ emissions from travel on the basis of the Travel Intelligent Query System (TIQS) developed by us on the Baidu map LBS (Location Based Service) open platform, and 1239 questionnaires conducted in 15 communities in Guangzhou in 2015. It develops a structural equation model (SEM) to examine the effects of the influencing factors on CO₂ emissions of trips with different purposes. The results show that the effect of residential self-selection also exists in Chinese cities. Changing residents' preference of travel mode will help reduce travel-related CO₂ emissions. After controlling the effect of residential self-selection, the built environment still has significant effects on CO₂ emissions from travel. Although some of them are direct effects, others are indirect effects that work through mediating variables, such as car ownership and travel distance. For different trip purposes, the mechanisms of CO₂ emissions are not the same. Specifically, the distance to city public centers has a significant positive total effect on CO₂ emissions from commuting trips, which is an indirect effect. Residential density significantly affects CO₂ emissions from social, recreational and daily shopping trips, but it has no significant effect on CO₂ emissions from commuting trips. Bus stop density is positively associated with CO₂ emissions from commuting trips, and negatively associated with CO₂ emissions from social and daily shopping trips. In addition, land-use mix has a negative effect on CO₂ emissions from commuting, social and daily shopping trips, and metro station density and road network density have significant negative effects on CO₂ emissions from all types of trip. These results suggest that it is necessary to comprehensively consider the effects of the built environment on CO₂ emissions from different types of trip, and carry out targeted intervention on the built environment in related planning and policy development so as to guide the public to change their travel behavior and to promote low-carbon travel.

Key words: residential self-selection, built environment, travel-related CO₂ emissions, influence mechanism, Guangzhou