Characteristics and sources of O3 pollution under different pollution levels and durations in typical areas of North China Plain from 2019 to 2022
This study selects Juxian,Rizhao with complex terrain as the research area.Based on O3 monitoring data from provincial control stations in Juxian from 2019 to 2022,the O3 pollution days were classified according to different O3 pollution levels and durations.The pollution characteristics and sources of O3 were explored using backward trajectory model(HYSPLIT),potential source contribution function(PSCF),and concentration weighted trajectory(CWT)models.Results showed that the number of mild pollution days of O3 in Juxian decreased from 72 to 38 during the period of 2019 to 2021,while rebounded in 2022.The number of moderate pollution days of O3 have little change.Slight pollution days of O3 accounted for a high proportion of mild pollution days,with the contribution of 21.4%～39.5%,indicating a great potential for improvement for mild pollution days.Strengthening the control measures for slight pollution days will be beneficial for converting mild pollution days into excellent days and improving the local air quality excellence rate.The longer the duration of O3 pollution(e.g.,≥3d),the lower the frequency of pollution occurrence,while the O3 concentration increased with the extend of pollution duration.Simulation results of the HYSPLIT model revealed that the air mass trajectories of different O3 pollution levels and durations were mainly distributed in the southeast of Juxian and transmitted over medium and short-distances.Besides,trajectories from the southeast of Juxian contained the highest concentration of O3-8h-90%(250.0±65.9 µg/m3).The PSCF and CWT results showed that the potential source regions of O3 were mainly distributed in the southeast of Juxian,with the main potential source region appearing in the Yangtze River Delta region.The results are of great significance for guiding the joint prevention and control of air pollution in Juxian and surrounding areas.
O3pollution levelpollution durationbackward trajectorypotential source areas
NETL
NSTL
万方数据
