Venugopal T, Giridharan L, Jayaprakash M
Department of Geology and Mining, Guindy, Chennai, 600032, India.
Arch Environ Contam Toxicol. 2008 Aug;55(2):180-90. doi: 10.1007/s00244-007-9117-y. Epub 2008 Jan 9.
A multivariate statistical technique has been used to assess the factors responsible for the chemical composition of the groundwater near the highly polluted Adyar River. Basic chemical parameters of the groundwater have been pooled together for evaluating and interpreting a few empirical factors controlling the chemical nature of the water. Twenty-three groundwater samples were collected in the vicinity of the Adyar River. Box-whisker plots were drawn to evaluate the chemical variation and the seasonal effect on the variables. R-mode factor analysis and cluster analysis were applied to the geochemical parameters of the water to identify the factors affecting the chemical composition of the groundwater. Dendograms of both the seasons gives two major clusters reflecting the groups of polluted and unpolluted stations. The other two minor clusters and the movement of stations from one cluster to another clearly bring out the seasonal variation in the chemical composition of the groundwater. The results of the R-mode factor analysis reveal that the groundwater chemistry of the study area reflects the influence of anthropogenic activities, rock-water interactions, saline water intrusion into the river water, and subsequent percolation into the groundwater. The complex geochemical data of the groundwater were interpreted by reducing them to seven major factors, and the seasonal variation in the chemistry of water was clearly brought out by these factors. The higher concentration of heavy metals such as Fe and Cr is attributed to the rock-water interaction and effluents from industries such as tanning, chrome-plating, and dyeing. In the urban area, the Pb concentration is high due to industrial as well as urban runoff of the atmospheric deposition from automobile pollution. Factor score analysis was used successfully to delineate the stations under study with the contributing factors, and the seasonal effect on the sample stations was identified and evaluated.
一种多元统计技术已被用于评估造成高度污染的阿迪亚尔河附近地下水化学成分的因素。已将地下水的基本化学参数汇总在一起，以评估和解释控制水化学性质的一些经验因素。在阿迪亚尔河附近采集了23个地下水样本。绘制了箱线图以评估化学变化以及变量的季节效应。对水的地球化学参数应用了R型因子分析和聚类分析，以识别影响地下水化学成分的因素。两个季节的树状图给出了两个主要聚类，反映了污染站和未污染站的分组。另外两个较小的聚类以及站点从一个聚类到另一个聚类的移动清楚地显示了地下水化学成分的季节变化。R型因子分析的结果表明，研究区域的地下水化学反映了人为活动、岩石与水的相互作用、咸水侵入河水以及随后渗入地下水的影响。通过将复杂的地下水地球化学数据简化为七个主要因素来解释这些数据，这些因素清楚地显示了水化学的季节变化。铁和铬等重金属的较高浓度归因于岩石与水的相互作用以及制革、镀铬和染色等行业的废水排放。在城市地区，由于工业以及汽车污染导致的大气沉降的城市径流，铅浓度很高。因子得分分析成功地用于用影响因素描绘所研究的站点，并识别和评估了对采样站点的季节效应。
