Udayakumar P, Abhilash P P, Ouseph P P
Chemical Sciences Division, Centre for Earth Science Studies, Thiruvananthapuram-31, India.
J Environ Sci Eng. 2009 Jul;51(3):179-86.
Miscellanies of statistical approaches were employed to illustrate the real picture of quality environmental variables observed in a nationalized monitoring programme. The interpretation and evaluation of the quality data, that was observed, were made very easier by utilizing the wide scope of spectacular statistical software, SPSS 11.0 through the Principal Component Analysis (PCA). The whole data for the study period, which was classified in to three distinct seasons, has been factorized using the PCA. The main and ultimate aim of this study is to reveal and categorize the key parameters of the Mangalore coast for the pollution sources to the ecosystem and their inputs can be perceived if there any point sources of pollution exist. Box plots were derived from the PCA data and were graphically represented. The variance was observed to be above 75% from the original data for all seasons. The major parameter affecting the ecological health of the coastal water was nitrate-nitrogen brought by the rivers in this region, which finally ends up in the estuary. Water quality data observed in the Mangalore coast during the three seasons, viz. pre-monsoon, monsoon and post-monsoon (February to October 2006), has been used and endeavors were made to determine and quantify the factors that caused fluctuations in the hydrology of this region.
采用多种统计方法来说明在一项国家监测计划中观察到的优质环境变量的真实情况。通过主成分分析（PCA）利用功能强大的统计软件SPSS 11.0的广泛功能，对所观察到的质量数据进行解释和评估变得非常容易。研究期间的全部数据分为三个不同季节，已使用PCA进行因子分解。本研究的主要和最终目的是揭示并分类芒格洛尔海岸对生态系统污染源的关键参数，并且如果存在任何污染点源，能够了解其输入情况。箱线图由PCA数据得出并以图形方式呈现。所有季节的方差相对于原始数据均观察到高于75%。影响该沿海地区生态健康的主要参数是该地区河流带来的硝酸盐氮，其最终流入河口。已使用芒格洛尔海岸在三个季节（即季风前、季风期和季风后，2006年2月至10月）观测到的水质数据，并努力确定和量化导致该地区水文波动的因素。
