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The characteristics of hourly wind field and its impacts on air quality in the Pearl River Delta region during 2013–2017

Xie, Jielan, Liao, Zhiheng, Fang, Xingqin, Xu, Xinqi, Wang, Yu, Zhang, Yu, Liu, Jian, Fan, Shaojia, Wang, Baomin
Atmospheric research 2019 v.227 pp. 112-124
air pollutants, air pollution, air quality, cities, nitrogen dioxide, ozone, particulates, prediction, river deltas, rivers, wind
The behavior of wind with respect to local features, especially over complex heterogeneous underlying surfaces, is of particular interest. Studies on objective wind field classification on the local scale are limited. To better understand wind behavior and its impact on air quality in the Pearl River Delta (PRD) region, an objective clustering technique is applied to five-year (2013–2017) 23-station observational hourly wind data, and the effect of modulation of the clustered local wind fields on regional air quality is explored using simultaneous 55-site pollutant (PM2.5, PM10, NO2, and O3) concentrations. The clustering results capture the features of five local wind field types (Type_N, Type_NE, Type_S, Type_SE, and Type_Calm) driven by synoptic/local circulation in the PRD region and their spatiotemporal evolution. Excellent synoptic interpretations of each wind field type are given. The results confirm the applicability of the clustering technique in objective classification of wind fields in the PRD region. The PM2.5, PM10, and NO2 concentrations show characteristics of wind-dependent spatial distributions in which pollutant transport within the PRD city cluster is significant. The quantified concentration difference (ΔC) between cities with higher and lower pollutant concentrations within the PRD region is also presented. The spatial distribution of the O3 concentration is quite different from those of PM2.5, PM10, and NO2, because central cities in the PRD region have obviously lower O3 concentrations than the surrounding cities except under Type_S wind fields. The emission source intensity is reflected in the spatial distribution of air pollutant concentrations under Type_Calm wind fields. This work enables further analysis of the formation process and mechanism of air pollution, and also provides important background information for air pollution prediction.