机动车导致的PM2.5、PM1污染受到高度关注，而城市高架桥附近污染更为严重，且暴露人群多，时间长，是重要的城市空气污染热点和高暴露风险区。因此，高架桥附近污染时空演变机理是城市空气污染控制的重要基础，对改善人居环境具有重要意义。受时变交通流、颗粒物理化特性、高架桥物理结构、两侧建筑群和气象因素等动态变化的边界条件耦合影响，高架桥颗粒物污染扩散是复杂的三维非稳态过程，污染时空演变特征与机理尤为复杂，研究难度大。 .主要针对几种典型高架桥道路场景，开展PM1、PM2.5颗粒物污染实地综合观测实验研究和车载排放测试实验，分别针对高架桥上部、底部颗粒物排放、扩散沉积过程进行分析和建模，建立一种精度高、运算稳定的计算模型。并在超算平台上将排放模型、计算模型与微观交通仿真模型进行耦合，以实现对高架桥附近污染的动态模拟，从而构建污染知识图谱，并揭示颗粒物污染三维时空演变特征与机理，以提供控制污染依据。

Traffic-induced Particulate Matter(PM) pollution in atmospheric environment has been highly concerned in recent years. it is more serious around urban viaducts where lots of people is directly exposed with longer time, causing adverse impacts on health. Therefore, spatial-temporal evolving mechanism of PM pollution is necessary and important for improving air quality. But due to the combined effects of three dimensional viaduct physical structure and irregular shape buildings on both sides of viaducts, non-steady state turbulent vortices in the upper, bottom and both sides of the viaduct are more likely to form. And time-varying traffic flows, PM physical-chemical properties and meteorological parameters also make the three dimensional spatial-temporal distribution of PM pollution more uneven, and so it will be a challenging research to reveal the mechanism..a comprehensive observational experiment on PM1 and PM2.5 particulate matter pollution in mainly for several typical viaduct road scenes are made, and vehicle PM(PM1,PM2.5) emissions is measured by Portable Emission Measure System. And then the analysis on process of diffusion -transformation on the upper, bottom, and sides of the Viaduct will made, to develop a computational model with higher-precision and less amount of calculation. Next, the emissions model will be connected in real time with traffic simulation model and diffusion-transformation model of CFD, by some algorithm and computer program. So the dynamic simulation of PM pollution will be implemented on the Supercomputer Tianhe-2. Finally, the pollution knowledge map is built and spatial-temporal evolving mechanism of PM pollution is revealed. Therefore these results will be very helpful for assessing air pollution and making polices to better air quality.