The invention brings forward a constructing method of a combined air quality forecasting model, wherein the method is based on a BP neural network and multi-element stepwise regression. The method comprises the following steps: (1), establishing a BP neural network forecasting module based on a training sample set; (2), carrying out severe-pollution scene determination based on the BP neural network forecasting result; to be specific, (21), defining a severe-pollution scene; (22), establishing a determination equation; (23), carrying out determination by using a neural network forecasting value; and (24), carrying out determination on the determination equation based on the neural network forecasting value determination result; (3), establishing a severe-pollution multi-element stepwise regression forecasting model according to the severe-pollution scene determination result; and (4), with combination of the forecasting determination process, outputting a forecasting result. According to the invention, the forecasting precision of the urban air quality, especially the early-warning forecasting of the severe-pollution scene, is improved comprehensively; and thus stable air quality precision forecasting under different pollution degrees can be realized.