Classification of PM10 distributions in Taiwan

被引:38
|
作者
Lu, HC
Chang, CL
Hsieh, JC
机构
[1] HungKuang Univ, Dept Environm Engn, Taichung 433, Taiwan
[2] Yuanpei Univ Sci & Technol, Dept Environm Engn & Hlth, Hsinchu, Taiwan
关键词
self-organizing maps; lognormal distribution; hierarchical clustering; K-means; air-quality basins;
D O I
10.1016/j.atmosenv.2005.10.051
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Daily average PM10 concentrations of 71 stations in Taiwan in wintertime (October to March) and summertime periods (April to September) were fitted individually by a lognormal distribution for a 2 yr period (2001 to 2002). The distribution parameters (geometric mean and geometric standard deviation) in wintertime were used to determine the air-quality basins for PM10 by utilizing three clustering techniques, viz. of hierarchical clustering (Ward's method), non-hierarchical clustering (K-means) and two-level approach (self-organizing maps neural network, then K-means clustering). All three techniques suggested that 71 air-monitoring stations in Taiwan can be divided into five air-quality basins which are located in northern, central, eastern, southwestern and southern Taiwan, respectively. The sequence of PM10 pollution levels in the five basins is southern Taiwan > southwestern Taiwan > central Taiwan > northern Taiwan > eastern Taiwan. Geometric means and geometric standard deviations in each of the five air-quality basins were significantly different from each other for the two-level approach method by the Waller-Duncan k-ratio t-test (k = 100, P = 0.05), suggesting that the two-level approach method is best among the three clustering methods. The clustering results of five air-quality basins in Taiwan are useful to decide the corresponding control strategy at different air-quality basins.(c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1452 / 1463
页数:12
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