W. C. Wang, K. S. Chen

  • Institute of Environmental Engineering, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan, ROC

Received: August 31, 2008
Revised: August 31, 2008
Accepted: December 29, 2016
Download Citation: ||https://doi.org/10.4209/aaqr.2008.06.0020  

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Cite this article:
Wang, W.C. and Chen, K.S. (2008). Modeling and Analysis of Source Contribution of PM10 during Severe Pollution Events in Southern Taiwan. Aerosol Air Qual. Res. 8: 319-338. https://doi.org/10.4209/aaqr.2008.06.0020



This work simulates the hourly variations of PM10 (suspended particles with diameter < 10 μm) during severe pollution events in southern Taiwan (Kaohsiung City and Pingtung County) in spring, autumn and winter of 2005 by using the Air Pollution Model (TAPM). Comparisons between simulations and measurements at three sites (industrial, urban and rural) were satisfactory. The synoptic weather chart indicated that prevailing winds were northwest (spring), north (autumn), and northeasterly (winter). Meteorological conditions suggest that PM10 typically accumulated and triggered a pollution episode on days with high surface pressure and low winds. Estimations using the TAPM model suggest that point-source emissions were the predominant contributors (about 49.1%) to PM10 concentrations at Hsiung-Kong site industrial site in Kaohsiung City, followed by area sources (approximately 35.0%) and transport from neighboring areas (7.8%). Because Pingtung City (urban) and Chao-Chou town (rural) are located downwind of Kaohsiung City when north or northeasterly winds prevail, the two sites also experience severe pollution events despite the lack of industrial sources; transport from neighboring areas contributed roughly 39.1% to PM10 concentrations at Pingtung site and 48.7% at Chao-Chou site. Since traffic emissions contributed little (around 8%) to PM10 concentrations at the three sites, reducing PM10 emissions from industrial sources in Kaohsiung City should be an effective way of improving air quality for Kaohsiung City and downwind areas such as Pingtung County.

Keywords: Particulate matter; PM10; Source contribution; Meteorological condition; TAPM; Air pollution modeling

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