Summertime ozone pollution in the Yangtze River Delta of eastern China during 2013-2017: Synoptic impacts and source apportionment

Severe ozone (O-3) pollution in China has magnified global concerns over the past years. Exploring the synoptic impacts and quantifying the source contributions are important for mitigating O-3 pollution. This study focuses on the summertime O-3 pollution over the Yangtze River Delta (YRD) in eastern China. We identify six predominant synoptic weather patterns (SWPs) over the YRD during 2013-2017 using the self-organising map (SOM) approach. We conduct O-3 source attribution based on ozone source apportionment technology (OSAT) in a regional transport model. Surface O-3 pollution is found to be sensitive to the predominant SWPs, including four O-3-polluted types (northeasterly, northerly and southwesterly and anticyclone) and two O-3-clean types (cyclone and the Meiyu front). The integrated influences of local chemistry and regional transport are important in O-3 pollution under different SWP5. Daily maximum 8-h average (MDA8) O-3 holds strong negative and positive correlations with relative humidity and sunshine duration, respectively. Among the six SWP5, the concentration and exceedance of MDA8 O-3 reach their maxima under the northerly type on a regional average. Higher O-3 levels, particularly under the northerly and northeasterly types, are primarily related to regional transport on various spatial scales. Local production accounts for the largest proportion of O-3 sources under the anticyclone type. Under the southwesterly type, favourable weather conditions superimposed on regional transport lead to severe O-3 pollution in coastal cities. The impact of super-regional transport is most pronounced along the eastern coast under the cyclone type. Source category analysis shows that transportation and industrial emissions play a prime role in surface O-3 formation. This study illustrates the imperative implementation of joint emission control over eastern China to reduce O-3 pollution. (C) 2019 Elsevier Ltd. All rights reserved.