建成环境对城市居民日常出行碳排放的影响——以开封市248个居住区为例

居住区是居民日常生活最基本的空间单元,其建成环境对出行碳排放的影响是学术界关注的焦点。基于大样本调查数据核算居民各类出行碳排放,通过POI抓取、空间句法、网络分析等方法识别开封市主城区成规模的248个居住区的建成环境特征,借助核密度和GWR等方法剖析居住区尺度居民各类出行碳排放的空间分异规律。结果表明：① 城市内部居民出行碳排放空间差异显著,居住区公共服务供给的公平性问题突出,外圈层快速扩张区域应作为城市碳减排工作的关键区域;② 居住区尺度能较好地揭示建成环境对出行碳排放的影响,路网设计、建筑密度、土地利用混合度等因素对各类出行碳排放的作用机理差异较大,作用强度亦存在不同方向上的空间渐进规律;③ 根据出行碳排放结构及其对应的建成环境指标可识别出外层高密度欠通达低混合型居住区碳排放水平较高,内层低密度高通达高混合型居住区碳排放水平较低。研究结果可为居住区空间重构和城市碳排放的分区规划与治理提供科学依据。

Impact of built environment on carbon emissions from daily travel of urban residents: A case study of 248 residential areas in Kaifeng

Residential area is the most basic unit of residential daily life, and the impact of its built environment on daily travel carbon emissions is a major concern within academic field. We accounted all kinds of carbon emissions from residential daily travel based on a large number of sample questionnaire data, identified the built environment characteristics of 248 residential areas in the main urban area of Kaifeng city by POI capture, network analysis, spatial syntax and other methods, and analyzed the spatial distribution and the differentiation mechanism of carbon emissions of various types of residents in residential areas by means of nuclear density and GWR. The results show that: (1) There is a significant spatial difference in urban residents' travel carbon emissions, and there is a great difference in the fairness of public service supply in residential areas. (2) The study in residential area scale can better reveal the impact of built environment on travel carbon emissions. Location, accessibility, road network design, building density and land use mix degree, etc. have significant impacts on the residential daily travel carbon emissions. However, for different travel purposes, the impacts of these factors are quite different. What's more, there is a spatial asymptotic difference in the impact intensity in different directions. (3) According to the carbon emission grade combination of various purposes and corresponding built environment indexes, it can be identified that the carbon emission level of outer high-density under-accessible low-mixed residential areas is of high emissions, and that of inner low-density high-accessible high-mixed residential areas is of low emissions. The results can provide a scientific basis for the spatial reconstruction of residential areas and the zoning planning and governance of urban carbon emissions.