Precise facility-specific speed correction factors (SCFs) are important parameters for direct and quick evaluation of the effect of traffic flow variations on vehicle emissions. However, the traditional method in developing SCFs is time consuming and costly, which impedes the development of SCFs and their applications. Based on massive instantaneous vehicle activity data, this paper proposes a novel method for deriving SCFs for light-duty vehicles on restricted access roadways in Beijing. First, a large sample of 60-s speed-specific trajectories is divided from the vehicle activity data, and grouped into speed-specific trajectory pools. Then, a database and two models of speed-specific and vehicle-specific power (VSP) distributions are established for different speed ranges. Further, by combining emission rates and VSP distributions, the SCFs for nitrogen oxides (NOx), hydrocarbons (HC), and carbon monoxide (CO) pollutants are derived for different emission standards. The derived SCFs from different sources of VSP distributions are compared with each other and validated by using another independent data source. The analysis result shows that, by using the VSP distribution database, the proposed method is applicable and effective in generating reliable SCFs in high resolution. The VSP distribution models can predict well SCFs within each speed range, while discontinuous predictions occur at their range boundary. Finally, several recommendations are made for future studies on developing comprehensive SCFs, which may help in practice to monitor dynamic traffic emissions when the real-time speed data are available.