Abstract: Atmospheric pollution prediction is helpful to find effective ways to control air pollution and improve air quality.BP neural network which was trained using Bayesian Regularization method and early stopping method was used to forecast the hourly concentration of PM_2.5.The data of PM_2.5 hourly concentration were obtained from monitoring site of Marylebone Road in London,UK.The prediction relative error goes from 20% to 49%.The results show that compared with networks which were trained using other methods, Bayesian Regularization method and early stopping method can improve the generalization ability of BP neural network.