Co-Occurring Extremes of Fine Particulate Matter (PM_2.5) and Ground-Level Ozone in the Summer of Southern China

Concurrent pollution of fine particulate matter (PM2.5) and ozone has been increasingly reported in China recently. Here, we further confirm widespread co-occurring summertime PM2.5-ozone extremes in southern China. Annual-average frequency of co-occurrence is above 50% from 2015 to 2022, especially in Pearl River Delta region (72 +/- 12%). The spatial extent (city numbers) and temporal persistence (co-occurrence days) for cities with co-occurrence frequency >50% increase at a rate of two cities/year and 14 days/year, respectively. We further identify typical synoptic conditions (e.g., typhoon periphery circulation, West Pacific subtropical high) conducive to widespread co-occurrence. Through combining multi-source data, Random Forest model well predicts PM2.5-ozone co-occurrence and identifies common precursors (e.g., volatile organic compounds) as important variables. Finally, we postulate co-occurrence is linked to synoptic conditions and secondary generation of PM2.5-ozone from shared precursors. Our results suggest high potentials for co-occurring PM2.5-ozone extremes in southern China and control strategies on common precursors to mitigate concurrent pollution. Plain Language SummaryIn recent years, fine particulate matter (PM2.5) and ozone pollution have been increasingly reported to co-occur in many regions of China. In this study, we further report widespread co-occurrence of PM2.5-ozone extremes in the summer of southern China and explain the possible underlying reasons. The annual-average co-occurrence is observed with a frequency above 50% from 2015 to 2022, especially in the Pearl River Delta (PRD) region (72 +/- 12%). The spatial range and temporal duration for the cities with co-occurrence frequency above 50% increase annually in southern China. Based on a case study of consecutive co-occurrence episodes, we find typical weather conditions (e.g., typhoon periphery, West Pacific subtropical high) are along with the widespread co-occurrence. Then, we combine multi-source data in the PRD region and apply Random Forest model to predict the co-occurrence of PM2.5-ozone extremes and identify common precursors (e.g., volatile organic compounds) as important factors. Finally, we infer the co-occurring extremes are associated with typical weather conditions and shared precursors of PM2.5 and ozone. Our results not only imply high potentials for co-occurring PM2.5-ozone extremes in southern China but also suggest control strategies on shared precursors to tackle concurrent pollution.