Abstract: In order to make full use of the existing environmental monitoring site data for refined population exposure assessment, and to solve the problem of choosing data when there are no monitoring sites around certain communities of the population to be measured, Baoding was taken as a research city with heavy air pollution. Based on the field monitoring in Baoding and the simulation by the Kriging method, the representativeness of a stationary monitoring site in the study of air pollutant exposure levels was determined. The results showed that for φ(SO₂), φ(NO₂), particulate matter and its main composition, the data representativeness of a stationary monitoring site was generally about 5-6 km, while for φ(CO), φ(O₃) and φ(VOCs), the spatial distribution in different areas was more uniform and the representativeness was larger. A comparation of six methods, including Radial Basis Functions, Local Polynomial Interpolation, Inverse Distance Weighting, Kriging, Kernel Smoothing and Diffusion Kernel, showed that the Kriging method had the highest predictive accuracy (the prediction error less than 10%). In conclusion, if there is a stationary monitoring site within 5 km, the monitoring concentrations can be used as the exposure levels to the air pollutants. The air pollutant levels beyond 5 km can be simulated using Kriging spatial interpolation based on the data at the nearest available station.