Application of Principal Component Analysis and Correlation for Assessing Groundwater Contamination in and around Municipal Solid Waste Landfill of Ghazipur, Delhi

Abstract

The present study has been executed to assess the groundwater quality and to investigate the possible sources of contamination in the adjoining areas of Ghazipur landfill site, Delhi. The groundwater samples were collected during pre and post monsoon seasons and various physico-chemical and heavy metals concentration were also analyzed. The results show that the samples which were taken adjacent to landfill site had a higher concentration of total dissolved solids (2383 mg/l), chloride (991mg/1), total hardness (659 mg/l), ammonical nitrogen (2.3mg/l), sodium (350 mg/l), calcium (534 mg/l) and sulphate (631 mg/l). Most of the heavy metals concentration in groundwater samples was found within the prescribed limit except Cu and Pb. The principal component analysis (PCA) extracted 3 factors which collectively explained 80.1% of the variation in data during post-monsoon whereas 75.4% of the variation in pre-monsoon season. The obtained results clearly show that K+, Mg2+, Na+, SO42-, and NO3- ions significantly contribute towards the high temporal pollution load to groundwater quality. Factor analysis also suggested that the continuous percolation of these contaminants from the nearby landfill could be the possible sources of contamination into groundwater aquifer system. The concentration of heavy metals in leachate have followed the order as- Fe>Zn>Cu>Pb>Ni>Cr>Cd. The overall result indicates that the landfill leachate is significantly affecting the nearby groundwater quality through continuous leaching over a long period of time. As the groundwater is used by some local residents for domestic purposes, immediate action and alternative effort should be made to supply clean water.

Differences in the Composition of Leachate from Active and Non-Operational Municipal Waste Landfills in Poland

“…The factor loadings correspond to the correlation coefficients between the individual components and the variables under investigation [38]. This method has been used in numerous studies, e.g., to assess groundwater pollution by landfill leachate, to analyze the test results of the leachate itself or to choose the location of landfills [39][40][41][42].…”

A Study on Hydrochemical Characteristics and Evolution Processes of Groundwater in the Coastal Area of the Dagujia River Basin, China

“…The PCs were extracted using the varimax method [11], as shown in Table 2. The Kaiser-Meyer-Olkin values of the QA and BA were 0.593 and 0.544, respectively, indicating that the hydrochemical parameters of the samples were suitable for the PCA analysis [42]. In this study, the first three PCs were selected for both QA and BA.…”

Analysis of the Bacterial Biocenosis of Activated Sludge Treated with Leachate from Municipal Landfills

“…Basic non-parametric statistics (minimum, maximum) were used to characterise selected physicochemical properties and toxicity of leachates, used among others at small sample size [46]. Principal component analysis (PCA) was used to indicate the factors affecting the values of the studied variables to the greatest extent and to indicate the cases (taxonomic level units) most related to the principal components [31,47].…”