Lee Cheng F, Hsiao Jen H, Cheng Shin J, Hsieh Huey H
Department of Environment and Resources Engineering, Diwan University, Madou, Tainan 721, Taiwan, ROC.
Int J Environ Res Public Health. 2007 Jun;4(2):106-10. doi: 10.3390/ijerph2007040004.
This study aims to classify regions with different air pollution characteristics into groups in Taiwan, and further to evaluate and compare the air quality of various groups. A selected multivariate analysis technique, cluster analysis, is applied to the pollution monitoring dataset which including PM10, SO2, NO2, CO and O3. The obtained results have proved that the regions with similar air pollution characteristic can be appropriately grouped by applying cluster analysis. All 22 regions are classified into six groups, and the pollution pattern for each group is characterized as: Group 1 (high SO2/NO2; low PM10), Group 2 (high PM10), Group 3 (high SO2/PM10), Group 4 (low SO2/NO2/CO; high O3), Group 5 (low CO/NO2; high O3) and Group 6 (low PM10/SO2/NO2/O3/CO). Results from air quality evaluation indicate that the regions in group 6 (Ilan, Hualien and Taitung) have the best air quality while the regions in group 3 (Kaohsiung and Kaohsiung City) have the worst air quality in Taiwan. The results from correlation analysis reveal that incidence of the respiratory system disease is significantly positively correlated with pollution of NO2 and CO at 99% confidence level.
本研究旨在将台湾地区具有不同空气污染特征的区域进行分组，并进一步评估和比较各群组的空气质量。一种选定的多元分析技术——聚类分析，被应用于包含PM10、SO2、NO2、CO和O3的污染监测数据集。所得结果证明，通过应用聚类分析可以对具有相似空气污染特征的区域进行合理分组。所有22个区域被分为六组，每组的污染模式特征如下：第1组（高SO2/NO2；低PM10），第2组（高PM10），第3组（高SO2/PM10），第4组（低SO2/NO2/CO；高O3），第5组（低CO/NO2；高O3）和第6组（低PM10/SO2/NO2/O3/CO）。空气质量评估结果表明，第6组（宜兰、花莲和台东）的区域空气质量最佳，而第3组（高雄和高雄市）的区域空气质量在台湾最差。相关性分析结果显示，呼吸系统疾病的发病率与NO2和CO的污染在99%置信水平上显著正相关。
