Spatio-temporal Characteristics of Ozone Suppression and Its Response to Atmospheric Circulation Under High-Temperature Conditions in the North China Plain

To reveal the patterns and causes of ozone (O₃) suppression under extreme high temperatures in the North China Plain (NCP), this study utilized O₃ observation data, surface meteorological observation data, and ERA5 reanalysis data from 2014 to 2023. The Z-test method was employed to define the critical temperature (T_x) for ozone suppression, and the spatio-temporal characteristics of this phenomenon as well as the influencing mechanisms of atmospheric circulation were analyzed. The results indicate that ozone suppression in the NCP is concentrated in five cities, including Beijing, located along the Yanshan Mountains and Northern Taihang Mountains. The critical temperature T_x ranges from 33 to 35°C. May, June, and July are the months when ozone suppression is most likely to occur in major cities of the region; T_x values are relatively higher in June and July (34-37°C) and lower in May and September. In terms of interannual variation, the maximum T_x value of 37.6°C was recorded in 2023, which is positively correlated with the frequency of extreme high temperatures in summer. Atmospheric circulation analysis shows that the geopotential height negative anomaly occurs over Northeast Asia during the occurrence of ozone suppression, the NCP region is affected by northwest winds which facilitates pollutant diffusion. Meanwhile, the region is controlled by a high-pressure warm ridge, promoting subsidence and warming. These two factors result in a negative correlation between high temperatures and O₃ concentrations. A case study in July 2023 verified that the subsidence motion dominated by upper-tropospheric northwest winds not only drives temperature rise but also improves diffusion conditions, serving as the key meteorological cause of ozone suppression. This study provides scientific support for the precise prevention and control of ozone pollution and the optimization of climate models in the NCP.