Abstract: Daily travelling is one of the main sources of public air pollution exposure risk. The ambient air quality of 75.1% of cities exceeds the national standard in China. In such situation, avoiding air pollution exposure strength during daily travelling is a new requirement to prevent and control the public health damage. This research integrates the common Kriging interpolation method, model of exposure dose evaluation and Dijkstra path search algorithm to design and develop a public health path planning APP service for Android smartphone device. It has implemented the public health path planning in the situation of dynamic changes of pollution concentration with exposure dose as the indicator. The results of outdoor PM2.5 exposure test show that the healthy path under the Application（APP） service is effective to avoid the risk of air pollution exposure, reducing exposure dose by 5.0% and 7.3% of the traveling individuals compared with the shortest path and the fastest path respectively.

Key words: routing planning, air pollution, Android, PM2.5, health traveling

摘要： 日常出行吸入空气污染物是公众空气污染暴露风险发生的主要途径之一。在我国当前仍有75.1%的城市环境空气质量超标背景下，如何有效降低室外日常出行空气污染暴露强度成为了公众防控大气污染健康损害的一种新需求。集成普通克里格空间插值方法、暴露剂量评估模型、Dijkstra路径搜索算法，设计与开发了面向Android智能手机终端的公众健康路径规划应用程序（APP），实现了空气污染浓度动态变化情景下以暴露剂量为指标的健康路径出行规划功能。以室外PM2.5暴露为例的测试结果表明，APP服务规划下的健康路径相比最短路径和最快路径可分别降低出行个体5.0%和7.3%的暴露剂量，是一种公众规避空气污染暴露风险的有效路径规划服务。

关键词: 路径规划, 大气污染, Android, PM2.5, 健康出行