基于呼吸暴露的体力型出行活动模式、影响机制与规划应对研究——以上海为例

Active travel moedes including walking and cycling are of significance in promoting green transport and public health; however, air pollution causes health risks to the travellers. Our research team discovered that active travel is influenced by respiratory exposure evidently, its underlying behavioral mechanism has not been ascertained yet. We select several typical areas in Shanghai for case study and utilize portable devices to measure the concentration of some key pollutants in active travel micro-environment, then to simulate temporal and spatial distribution of polltant concentration through building up a CFD pollution diffusion model. With overlay analysis of real-time trajectory data of active travels, we quantitatively estimate the individual's exposure dose, and then compare the differences on exposure characteristics of each study area due to district design attributes. Further, we track the changes of active travel activities under different exposure concentration circumstances by panel analysis method to understand the effects of respiratory exposure on travel frequency, time, duration and mode shift, etc. We also adopt RP and SP sampling survey method to acquire individual’s travel activity data under the perceived and informed exposure scenarios. In that, we build a PSL route choice model to reveal individuals’ preferences for different exposure levels of route, considering the trade-off of exposure dose and travel distance factors. Finally, from the perspective of planning application, a healthy-oriented planning model for activel travel as well as a technical method integrating design intervention and traffic organization with respiratory exposure estimation is proposed. The study will have essential implications on improving “walkable and bikable” green transport as well as healthy city planning theories and practices.

步行、自行车等体力型出行有利于促进绿色交通与公共健康，而空气污染却给出行者带来健康风险。课题组初步发现体力型出行行为受到呼吸暴露的影响，但其内在机制未被探明。本研究选取上海若干典型地区，采用移动设备测定步行和骑行微环境的代表污染物浓度，构建CFD污染扩散模型动态模拟街道环境浓度时空间分布；结合出行轨迹数据量化评估个体暴露剂量，比较地区暴露模式差异及其街区设计特征要素的影响。采用面板分析方法，考察不同呼吸暴露水平下体力型出行活动频次、时辰、时长、方式等变化；通过RP和SP结合的抽样调查方法，获取个体基于感知与告知暴露情形的出行活动数据，构建暴露与距离相权衡的PSL路径选择模型，揭示个体对不同暴露水平的路径选择偏好。最后从规划应对角度，提出“设计干预-交通组织-暴露评估”相整合的技术方法和体力型出行呼吸健康导向的街区规划模式，对完善“宜步行、宜骑行”的绿色交通和健康城市规划理论有重要意义。

步行、自行车等体力型出行有利于促进绿色交通与公共健康，而空气污染却给出行者带来健康风险。本研究选取上海若干典型地区，采用移动设备测定步行和骑行微环境的空气污染物浓度，绘制不同污染物的呼吸暴露浓度地图；构建了CFD污染扩散模型，模拟不同道路的街谷形态对其PM2.5污染扩散的影响，解释了交通量大而街谷开敞的四平路PM2.5暴露浓度并不高于街坊内部支路的现象，表明窄密支路网会因通风不佳而不利于体力出行者的呼吸健康。接着结合骑行轨迹大数据，量化评估骑行个体的呼吸暴露剂量，并对街区总体呼吸暴露模式进行分析，发现车流量低而开敞的校园路径暴露风险最低，但其他道路的NO2和PM2.5暴露分布存在较大差异。进一步通过RP和SP结合的抽样调查方法，了解骑行者在基于感知暴露与告知暴露两种情形下的出行路径选择变化，发现骑行者在被告知暴露水平后，对路径骑行时间的要求有所降低，在路径选择时更愿意考虑减少呼吸暴露风险，表现为选择短路径的比例降低，而选择低暴露路径的比例提高；进而通过构建暴露与距离相权衡的路径选择模型，考察了呼吸暴露要素与安全、便捷、舒适等其他要素对于体力出行者路径选择的不同影响，探明了骑行路径选择行为受呼吸暴露影响的机制，有利于全面认识骑行者对出行路径选择的偏好特征。最后，从健康风险干预的角度，提出了“街区设计-网络优化-交通管治-暴露评估”相整合的规划技术框架，以指导面向体力出行呼吸健康的街区规划设计。本项目成果从呼吸健康的维度拓展了“宜步行”、“宜骑行”城市的理论内涵，对完善健康交通和健康城市规划理论有重要意义，也有利于推动促进体力出行活动的规划实践。