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With the rapid increase in vehicle ownership, exhaust pollution has become one of the important sources of air pollution in China. In this study, a MAHA METDH 6.3 exhaust gas test experimental platform was developed, and an emission model suitable for coupling with real-time road conditions was established based on large-scale vehicle emission test data. Based on traffic big data such as traffic volume, average vehicle speed, and vehicle model distribution, ArcGIS was used to select the road network information in the study area and combined with the emission model to realize the spatial distribution of line sources of vehicle emissions. Finally, based on the road network simulation model built by VISSIM, the emission changes caused by the two measures of trunk line optimization and new energy vehicle development were simulated and analyzed. The results show that the spatial distribution characteristics of vehicle exhaust pollutants in Zhangdian District are closely related to road type. Taking trunk line optimization measures and developing new energy vehicles have a certain reduction effect on vehicle emissions in Zhangdian District. This study lays a foundation for proposing targeted measures to reduce motor vehicle emissions based on big traffic operation data.

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