Articles written in Sadhana
Volume 47 All articles Published: 22 November 2022 Article ID 0251
Application of chemometric modeling for identification of pollution sources from drains of Ghaggar River, Punjab, India
HARNEET KAUR ANITA RAJOR AMRITPAL SINGH KALEKA
In the present research work, physicochemical analysis on the drainage system was conducted by including three drains of Ghaggar River (Punjab) India. The study was focused on the drains, namely Sirhind Choe (S1), Patiala River (S2), and Dhakanshu Drain (S3). These drains receive untreated sewage, agriculturalrunoff, and industrial effluents from several major cities, towns, and villages of Punjab. In this study, fifteen physicochemical parameters were determined from water samples collected from each drain in five seasons during 2017-2018. The analytical results of all three sites showed that total suspended solids (TSS), Chemical oxygen demand (COD), and Biochemical Oxygen Demand (BOD) were found above the permissible limit of the Center Pollution Control Board (CPCB), India. Further, ‘‘Chemometric Modeling’’ was used to interpret complex data. The statistical tools such as Correlation Analysis, Principal Component Analysis (PCA), Factor Analysis (FA), Cluster Analysis (CA), and Discriminant Analysis (DA) were performed on the data set. A strong interrelationship between the parameters of each site was depicted in the correlation analysis. The PCA/FAidentified the agricultural and domestic pollution from the study area. The temporal CA reduced the seasonal data into four significant clusters. The spatial DA predicted four parameters viz., total hardness, total dissolved solids, temperature, and sulfate as important discriminant variables with 100% correct assignment. In this study, chemometric modeling contributed to understanding the water quality patterns in wastewater drains scientifically and efficiently. The statistical tools identified major pollution contributors and temporal ways that provide sustainable water resource management guidelines.
Volume 48, 2023
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