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Synoptic and meteorological drivers of regional ozone pollution events in China

Wenyu Wei, Yuanyuan Fang, Yuntao Zhou

2021Environmental Research Communications11 citationsDOIOpen Access PDF

Abstract

Abstract Surface ozone (O 3 ) pollution events are becoming more frequent and have recently emerged as a severe air pollution problem in China. However, the spatial–temporal distribution of surface O 3 , as well as its primary synoptic and meteorological drivers, remains poorly understood. The purpose of this study was to identify the key synoptic and meteorological drivers of O 3 pollution in different regions of China. To achieve this goal, this study established meteorology overlaps of regional O 3 pollution events in space and time and applied a comprehensive statistical model selection method for optimal synoptic and meteorological models, based on a newly released O 3 dataset for 2015–2018. It was observed that extreme regional O 3 pollution events (duration >7 d) occurred more frequently and exhibited a high co-occurrence frequency (>50%) with air stagnation (AS). Moreover, the beginning and end of 69% of the regional O 3 pollution events coincided with regional daily maximum temperature changes. The intensity of AS is the dominant driver of O 3 pollution event intensity across most of the six selected megacity regions. Although other meteorological drivers, such as the intensity of hot days (HD) and meridional wind of 10 m were also important, their impacts varied according to the region. Overall, increase in extreme AS and HD led to the worsening of regional O 3 pollution events. These findings imply that mitigating regional O 3 pollution should consider changing synoptic and meteorological conditions.

Topics & Concepts

PollutionEnvironmental scienceAir pollutionMegacityClimatologySynoptic scale meteorologyChinaMeteorologyAir quality indexGeographyGeologyChemistryArchaeologyOrganic chemistryEconomicsBiologyEcologyEconomyAtmospheric chemistry and aerosolsAir Quality and Health ImpactsAir Quality Monitoring and Forecasting
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