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Impact of Synoptic Weather Types on Ground-Level Ozone Concentrations in Guangzhou, China

Journal article
Authors Wenhui Liao
Luolin Wu
Shengzhen Zhou
Xuemei Wang
Deliang Chen
Published in Asia-Pacific Journal of Atmospheric Sciences
ISSN 19767633
Publication year 2020
Published at Department of Earth Sciences
Language en
Links https://doi.org/10.1007/s13143-020-...
Keywords Guangzhou, Heavy pollution, Lamb-Jenkinson weather types (LWTs), O concentration 3
Subject categories Earth and Related Environmental Sciences

Abstract

© 2020, Korean Meteorological Society and Springer Nature B.V. Although precursor concentrations were reduced by emission control in Guangzhou, southern China from 2006 to 2016, ground-level O3 concentrations increased, forming potential risks to human health. This study explored the impacts of large-scale synoptic weather circulations on O3 concentration in Guangzhou, in a particular focus on high O3 pollution episodes. Twelve local weather types were clustered based on Lamb-Jenkinson weather types (LWTs). Analyses showed that LWTs strongly impacted daily O3 concentrations: A, AS, CN, and N+ weather types were likely associated with high ozone concentrations, while the ozone levels were relatively low under C, CE, CS, and S+ types. LWTs could explain 30–40% of the inter-annual variability of O3 concentration during the dry season. Numerical model simulations further demonstrated that continuous type A weather was the leading LWT correlated with high O3 concentrations, while type C weather was the predominant type correlated with low O3 concentrations. CMIP5 model results showed that occurrences of weather type A would increase by about 25% in the high emission scenario over the 2020–2069 period, which might worsen the O3 pollution in Guangzhou in the future. The increase in frequency weather type A would not be significant under the low emission scenario during the same period. Therefore, we should strictly implement the global emission reduction plan to prevent the change of weather circulation caused by climate change from aggravating ozone pollution in the future. The strong link between O3 concentrations and LWT frequencies makes the daily occurrence of LWTs a useful predictor for episodes of high O3 pollution and makes annual frequencies of LWTs good indicators of the inter-annual variability of the O3 concentration. These results are useful in efforts to predict O3 concentrations, providing a reliable weather forecast is available.

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