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Volume 8, No. 2, June 2008, Pages 112-129 PDF(354 KB)  
doi: 10.4209/aaqr.2007.09.0039   

Characteristics and Receptor Modeling of Atmospheric PM2.5 at Urban and Rural Sites in Pingtung, Taiwan

W. C. Wang1, K. S. Chen1, S. J. Chen2, C. C. Lin3, J. H. Tsai2, C. H. Lai4, S. K. Wang1

1 Institute of Environmental Engineering, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan, ROC
2 Department of Environmental Science and Engineering, National Pingtung University of Science and Technology, Pingtung 91201, Taiwan, ROC
3 Sustainable Environment Research Center, National Cheng Kung University, 70101, Taiwan, ROC
4 Department of Nursing, Central Taiwan University of Science and Technology, Taichung 40601, Taiwan, ROC

 

Abstract

 

Suspended particles of PM2.5 in air were sampled concurrently at an urban site and a rural site in Pingtung County in southern Taiwan, in the spring, the summer and the fall of 2005. All samples were analyzed to identify eight water-soluble ions, carbonaceous contents, and 19 metal elements. Measurements reveal that the overall means of PM10 (and PM2.5) are 59.2 (47.4) μg/m3 at Pingtung (urban) site, and 63.6 (45.7) μg/m3 at Chao-Chou (rural) site. Although both sites exhibited strong correlations (R = 0.98 at Pingtung, and R = 0.78 at Chao-Chou) between PM10 and PM2.5 masses, the mean PM2.5/PM10 ratio was 0.81 at Pingtung, higher than 0.68 at Chao-Chou, suggesting that relatively large bare lands and outdoor burning on farms may have caused more coarse particles to be present in PM2.5 at a rural site (Chao-Chou) than at an urban site (Pingtung). Results of CMB (chemical mass balance) modeling show that the main contributors to PM2.5 mass at Pingtung are vehicle exhaust (49.3–62.4%) and secondary aerosols (SO42–, NO3 and NH4+) (31.2–37.8%), while those at Chao-Chou are the outdoor burning (25.3–50.4%) of agricultural waste, secondary aerosols (27.2–34.3%) and vehicle exhaust (12.0–26.9%), depending on the seasons.

 

 

Keywords: PM2.5; Water-soluble ions; Carbonaceous species; Receptor modeling; CMB analysis.

 

 

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