Effects of tropical cyclones with different tracks on ozone pollution over the Pearl River Delta region

ATMOSPHERIC RESEARCH(2023)

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摘要
Tropical cyclone's activities can affect the ozone pollution characteristics to a certain extent over the Pearl River Delta (PRD) region based on different track types of tropical cyclones. In this study, we utilize the Finite Mixture Model algorithm to classify tropical cyclones which land on the South China coastal area between 2009 and 2018 into 6 track's types, and those types are land on the PRD region directly (A1 type), the east of the PRD region (B1 and B2 types) and the west of the PRD region (C1, C2 and C3 types) respectively. Combined with observation data, the results indicate that the A1 type, B1 type and B2 type tropical cyclones can increase the ozone con-centration about 44.9% similar to 65.3% in the PRD region before landfall accompanied with stagnant meteorological conditions usually, such as high temperature (>27 degrees C), low humidity (<80%) or weak wind (<3 m/s). And it should be emphasized that, due to the northward or northeastward deflection of the tracks, the ozone concen-tration in the PRD region does not decrease obviously (<10%) on the landing-day under B1 and B2 types, and ozone pollution maybe persistent longer than other types. By simulating typical cases of each track's type within WRF-Chem model coupled with process analysis method, and the results indicate that tropical cyclone's pe-ripheral subsidence airflow is more obvious over the PRD region under A1, B1 and B2 cases before landfall, and it maybe an external condition which can limit the development of boundary layer and vertical diffusion of ozone, rather than transporting ozone downward from the upper atmosphere to the near surface level. In addition, based on process analysis result, the chemical reaction with strong radiation condition maybe the essential cause of ozone production and pollution, and the physical process can cause the ozone consumption.
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关键词
Surface ozone, Tropical cyclones, WRF-Chem model, Track cluster, Process analysis
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