**RMSE = 5.31**

The results show that the regressive model considers three classes of parameters (time, meteorology, and criteria pollutants) out of four to predict the value of PM2.5. Traffic information is filtered, certainly because of its redundancy with time. After attribute selection (M5 method), the final model is composed of 11 features out of 16. As hypothesized, a model based on a hybrid data source allows for a significant improvement of the prediction accuracy. The values of the correlation coefficient and the RMSE are better for the hybrid than the chemical model.
