I-Cheng Chang1, Yu-Chun Chiang2, Tai-Yi Yu 3


Department of Environmental Engineering, National Ilan University, Yilan 26047, Taiwan
Department of Mechanical Engineering, Yuan Ze University, Taoyuan 32003, Taiwan
Department of Risk Management and Insurance, Ming Chuan University, Taipei 11103, Taiwan



Received: July 16, 2018
Revised: November 10, 2018
Accepted: December 5, 2018
Download Citation: ||https://doi.org/10.4209/aaqr.2018.07.0259  

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Cite this article:
Chang, I.C., Chiang, Y.C. and Yu, T.Y. (2019). Selection and Characterization of Fugitive River Dust Episodes over Zhuoshui River in Taiwan. Aerosol Air Qual. Res. 19: 995-1006. https://doi.org/10.4209/aaqr.2018.07.0259


HIGHLIGHTS

  • Principal component analysis was applied to screen river fugitive dust episodes.
  • Component scores of the PC1 for PM10 levels are utilized as the suitable indicators.
  • Statistical indicators related to PM10 and meteorological parameters are evaluated.

ABSTRACT


This study employs principal component analysis to identify fugitive river dust episodes over Zhuoshui River in Taiwan. The scores of the first unrorated principal component were applied as indicators for screening the dust episodes; this component explains 65% of the total variance of the daily PM10 concentrations at monitoring stations by Zhuoshui River. As the other principal components contributed less than 13% of the PM10 concentration, they were not suitable indicators of air pollution episodes. The number of days exceeding the National Ambient Air Quality Standard (NAAQS) for PM10 was used as indicators to evaluate the effectiveness of the component scores of the first principal component. Furthermore, air pollution episodes resulting from dust storms and transboundary pollution rather than river dust were excluded. The meteorological parameters, synoptic weather, PM10 concentrations, and principal components of the fugitive river dust episodes over Zhuoshui River were also analyzed as references for forecasting fugitive river dust episodes and implementing related air quality management.


Keywords: Principal component analysis; Synoptic weather; Fugitive river dust.

 



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