多尺度建成环境对居民通勤出行碳排放的影响——来自广州的实证研究

通勤出行碳排放是城市交通碳排放的主要来源。然而,现有研究很少关注不同地理尺度建成环境对居民通勤出行碳排放的影响差异,且尚未得出一致的结论。本文基于居民出行调查数据和多层次混合效应模型对广州多尺度建成环境对居民通勤出行碳排放的影响进行了实证研究。研究发现：在控制居住自选择效应之后,居民通勤出行碳排放具有明显的空间差异,这些差异是由社区间的建成环境差异所导致的。在不同尺度建成环境中,社区尺度的建成环境对居民通勤出行碳排放的影响最显著。而且,居住地建成环境对通勤出行碳排放的影响比工作地建成环境的影响显著。对建成环境进行规划干预应更多着眼于居民所居住的社区以及与居民日常出行活动联系紧密的社区15分钟步行生活圈。虽然实证案例社区的选取可能存在局限性,但研究结论可为构建低碳城市空间结构、引导居民出行行为转变和制定具有针对性的低碳交通与土地利用政策提供一定的科学理论依据。

Examining the effects of the multi-scale built environment on residents′ CO2 emissions from commuting: An empirical study of Guangzhou

Commuting is the main source of CO₂ emissions from urban transport. However, existing studies have rarely paid attention to the differences in the effects of different geographical scales of built environments on residents' CO₂ emissions from commuting and had not yet reached a consensus conclusion. Based on the 2015 travel survey data and multilevel and mixed-effects models, this paper conducts an empirical study on the effects of multi-scale built environments on residents' CO₂ emissions from commuting in Guangzhou, China. The results show that after control for the residential self-selection effect, there are obvious spatial differences in the residents' CO₂ emissions from commuting among neighborhoods. It is shown that the residents in the central urban area generally emit less CO₂ emissions than their counterparts in the suburban area in commuting trips. These are caused by differences in built environments between neighborhoods. In terms of scale, the neighborhood's built environment has the most significant effect on residents' CO₂ emissions from commuting, followed by 1 km-buffer range of neighborhood boundary, and then subdistrict. Moreover, the effect of the built environment of the residence on CO₂ emissions from commuting is more significant than that of the workplace. These findings imply that planning interventions on the built environment should focus more on the neighborhoods in which residents live and the 15-minute walk life circle that is closely linked to the daily travel activities of residents. The distance between residence and workplace should be kept as short as possible, and the residential density of neighborhoods should be maintained at a reasonable level. Furthermore, optimizing the structure of road network and providing more community roads which are beneficial to non-motorized travel could help improve the environment for walking and bicycling and encourage people to use low-carbon, active and healthy travel modes. Although there may be some limitations in the selection of neighborhoods surveyed and random interception approach in the survey that may lead to non-possibility sampling, the conclusions can still provide a scientific basis for constructing a low-carbon urban spatial structure, guiding residents' travel behavior change and formulating targeted policies on low-carbon transportation and land use.