Faculty of Applied Sciences, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia.
Environ Monit Assess. 2012 Jan;184(2):1001-14. doi: 10.1007/s10661-011-2016-8. Epub 2011 Apr 15.
Increasing urbanization and changes in land use in Langat river basin lead to adverse impacts on the environment compartment. One of the major challenges is in identifying sources of organic contaminants. This study presented the application of selected chemometric techniques: cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) to classify the pollution sources in Langat river basin based on the analysis of water and sediment samples collected from 24 stations, monitored for 14 organic contaminants from polycyclic aromatic hydrocarbons (PAHs), sterols, and pesticides groups. The CA and DA enabled to group 24 monitoring sites into three groups of pollution source (industry and urban socioeconomic, agricultural activity, and urban/domestic sewage) with five major discriminating variables: naphthalene, pyrene, benzo[a]pyrene, coprostanol, and cholesterol. PCA analysis, applied to water data sets, resulted in four latent factors explaining 79.0% of the total variance while sediment samples gave five latent factors with 77.6% explained variance. The varifactors (VFs) obtained from PCA indicated that sterols (coprostanol, cholesterol, stigmasterol, β-sitosterol, and stigmastanol) are strongly correlated to domestic and urban sewage, PAHs (naphthalene, acenaphthene, pyrene, benzo[a]anthracene, and benzo[a]pyrene) from industrial and urban activities and chlorpyrifos correlated to samples nearby agricultural sites. The results demonstrated that chemometric techniques can be used for rapid assessment of water and sediment contaminations.
城市化的不断增加和土地利用的变化导致冷架河流域的环境受到负面影响。其中一个主要挑战是确定有机污染物的来源。本研究应用了选择的化学计量技术：聚类分析（CA）、判别分析（DA）和主成分分析（PCA），根据对冷架河流域 24 个监测站采集的水和沉积物样本的分析，对污染来源进行分类，这些监测站监测了多环芳烃（PAHs）、甾醇和农药组的 14 种有机污染物。CA 和 DA 能够将 24 个监测站分为三组污染源（工业和城市社会经济、农业活动和城市/家庭污水），有五个主要的鉴别变量：萘、苊、苯并[a]芘、粪甾醇和胆固醇。PCA 分析应用于水数据集，得出四个潜在因素，解释了总方差的 79.0%，而沉积物样本给出了五个潜在因素，解释了 77.6%的方差。PCA 得到的变因子（VF）表明，甾醇（粪甾醇、胆固醇、豆甾醇、β-谷甾醇和豆甾烷醇）与家庭和城市污水密切相关，多环芳烃（萘、苊、苊、苯并[a]蒽和苯并[a]芘）来自工业和城市活动，而毒死蜱与附近农业地区的样本有关。结果表明，化学计量技术可用于快速评估水和沉积物的污染。
