Abstract: A method, apparatus and storage medium for forecasting air pollutant concentration, including: constructing a training set, a validation set and a test set based on a data set; the data set is obtained by collecting pollutant concentration data and meteorological data in a predetermined length of time in a target area; constructing an adjacent matrix A of a graph structure based on the spatial distribution of monitoring stations in the target area; establishing a neural network model F(x;?|A), where x is the input data of it, including pollutant concentration data and meteorological data within predetermined time period, training the neural network model using the data of the training set, adjusting the parameters ? of the neural network model using the data of the validation set and the data of the test set, and obtaining the modified neural network model; using the modified neural network model for air pollutant concentration forecasting.