Liu Yilin

Ms. Liu Yilin


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 March 2020 in Atmosphere
Verified
Journal Article
Open access
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LYLiu Yilin
Liu Yilin
Jianjun HeJianjun He
Jianjun He
XLXIN LAI
XIN LAI
CZChenWei Zhang
ChenWei Zhang
Lei ZhangLei Zhang
Lei Zhang
HCHuizheng Che
Huizheng Che
At present, few studies have focused on the impact of circulation patterns on aerosol pollution in the Pearl River delta region (PRD) region based on the objective circulation classification method. Based on PM2.5 observation data, meteorological observation data, Aerosol Robotic Network (AERONET) aerosol observation data and European Center for Medium-Range Weather Forecasting (ECMWF) ERA (European Reanalysis)-Interim data in the PRD during 2013 to 2017, the air pollution level, meteorological conditions, and aerosol optical and radiation characteristics in different circulation patterns are studied in this paper. Using ECMWF ERA-Interim sea level pressure, nine circulation patterns were determined based on the T-mode principal component analysis (PCA) combined with the k-means clustering method. There were significant differences in PM2.5 values under different circulation patterns, indicating that the change of atmospheric circulation is an important factor driving the change of air quality. The prevailing wind in winter (northerly wind) facilitates the transport of pollutants from the north of the PRD and forms severe air pollution, while the prevailing wind in summer (southerly wind) brings clean air from the South China Sea; additionally, a high frequency of precipitation benefits the wet scavenging of pollutants, resulting in improved air quality in the PRD region. The impact of circulation patterns on the AOD (aerosol optical depth) is basically similar to that of the PM2.5 concentration. The study also found that the annual average total radiation was negatively correlated with the annual average PM2.5 concentration. In future, we plan to identify which methods and data are suitable for circulation classification in the PRD region.