Carbon emissions monitoring of road operating vehicles is usually based on the statistical calculation methods at large spatiotemporal scales, and a set of multi-level spatiotemporal monitoring method that combines macro and micro dimensions has not been explored. Moreover, the dynamic monitoring technology means of traffic carbon emission are lacking and the monitoring accuracy is low, which cannot meet the needs of daily monitoring management and carbon emission trading of operating enterprises and traffic management departments. Therefore, taking carbon emissions of road operating vehicles as the target, the influencing factors and characteristics of carbon emissions of road operating vehicles were analyzed based on the multi-source data of road operating vehicles collected from Portable Emission Measurement System (PEMS) and bench testing. A carbon emission factor data set was constructed based on typical operating vehicle types and working conditions, then a multi-level spatiotemporal monitoring model for carbon emissions of operating vehicles was established at different spatiotemporal scales. Finally, we select typical light SUV vehicles and heavy truck cement vehicles, which can achieve precise measurement of carbon emissions and holographic monitoring of carbon emissions for single vehicle and regional vehicles as well. The research is conduced to assist in the monitoring and managing carbon emissions of road operating vehicles.