On-road vehicle emissions have become the main source of urban air pollution and attracted broad attentions. Vehicle emission factor is a basic parameter to reflect the status of vehicle emissions, but the measured emission factor is difficult to obtain, and the simulated emission factor is not localized in China. Based on the synchronized increments of traffic flow and concentration of air pollutants in the morning rush hour period, while meteorological condition and background air pollution concentration retain relatively stable, the relationship between the increase of traffic and the increase of air pollution concentration close to a road is established. Infinite line source Gaussian dispersion model was transformed for the inversion of average vehicle emission factors. A case study was conducted on a main road in Beijing. Traffic flow, meteorological data and carbon monoxide (CO) concentration were collected to estimate average vehicle emission factors of CO. The results were compared with simulated emission factors of COPERT4 model. Results showed that the average emission factors estimated by the proposed approach and COPERT4 in August were 2.0 g x km(-1) and 1.2 g x km(-1), respectively, and in December were 5.5 g x km(-1) and 5.2 g x km(-1), respectively. The emission factors from the proposed approach and COPERT4 showed close values and similar seasonal trends. The proposed method for average emission factor estimation eliminates the disturbance of background concentrations and potentially provides real-time access to vehicle fleet emission factors.