A heavy 16-day pollution episode occurred in Beijing from December 19, 2015 to January 3,2016. The mean daily AQI and PM_(2.5) were 240.44 and 203.6 μg/m~3. We analyzed the spatiotemporal characteristics of air pollutants, meteorology and road space speed during this period, then extended to reveal the combined effects of traffic restrictions and meteorology on urban air quality with observational data and a multivariate mutual information model. Results of spatiotemporal analysis showed that five pollution stages were identified with remarkable variation patterns based on evolution of PM_(2.5) concentration and weather conditions. Southern sites(DX, YDM and DS) experienced heavier pollution than northern ones(DL, CP and WL). Stage P2 exhibited combined functions of meteorology and traffic restrictions which were delayed peak-clipping effects on PM_(2.5).Mutual information values of Air quality–Traffic–Meteorology(ATM–MI) revealed that additive functions of traffic restrictions, suitable relative humidity and temperature were more effective on the removal of fine particles and CO than NO_2. A heavy 16-day pollution episode occurred in Beijing from December 19, 2015 to January 3, 2016. The mean daily AQI and PM_ (2.5) were 240.44 and 203.6 μg / m~3.We analyzed the spatiotemporal characteristics of air pollutants, meteorology and road space speed during this period, then extended to reveal the combined effects of traffic air and meteorology on urban air quality with observational data and a multivariate mutual information model. Results of spatiotemporal analysis showed that five pollution stages were identified with remarkable variation patterns based Southern China (DX, YDM and DS) experienced heavier pollution than northern ones (DL, CP and WL). Stage P2 showed combined functions of meteorology and traffic restrictions which were delayed peak- clipping effects on PM_ (2.5) .Mutual information values ​​of Air quality-Traffic-Meteorology (ATM-MI) revealed that additive functions of traffic restrictions, suitable relative humidity and temperature were more effective on the removal of fine particles and CO than NO_2.