Title of article :
Chemometric data analysis of pollutants in wastewater—a case study Original Research Article
Author/Authors :
Kunwar P. Singh، نويسنده , , Amrita Malik، نويسنده , , Dinesh Mohan، نويسنده , , Sarita Sinha، نويسنده , , Vinod K. Singh، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2005
Pages :
11
From page :
15
To page :
25
Abstract :
In this study, chemometric techniques such as cluster analysis (CA), discriminant analysis (DA), principal component analysis (PCA) and partial least squares (PLS) were used to analyse the wastewater dataset to identify the factors which affect the composition of sewage of domestic origin, spatial and temporal variations, similarity/dissimilarity among the wastewater characteristics of cis- and trans-drains and discriminating variables. Samples collected from 24 wastewater drains in Lucknow city and from three sites on Gomti river in the month of January/February, May, August and November during the period of 5 years (1994–1999) were characterized for 32 parameters. The multivariate techniques successfully described the similarities/dissimilarities among the sewage drains on the basis of their wastewater characteristics and sources signifying the effect of routine domestic/commercial activities in respective drainage areas. Spatial and seasonal variations in wastewater composition were also determined successfully. CA generated six groups of drains on the basis of similar wastewater characteristic. PCA provided information on seasonal influence and compositional differences in sewage generated by domestic and industrial waste dominated drains and showed that drains influenced by mixed industrial effluents have high organic pollution load. DA rendered six variables (TDS, alkalinity, F, TKN, Cd and Cr) discriminating between cis- and trans-drains. PLS–DA showed dominance of Cd, Cr, NO3, PO4 and F in cis-drains wastewater. The results suggest that biological-process based STPs could treat wastewater both from the cis- as well as trans-drains, however, prior removal of toxic metals will be required from the cis-drains sewage. Further, seasonal variations in wastewater composition and pollution load could be the guiding factor for determining the STPs design parameters. The information generated would be useful in selection of process type and in designing of the proposed sewage treatment plants (STPs) for safe disposal of wastewater.
Keywords :
wastewater , Multivariate analysis , Sewage treatment , cluster analysis , Principal component , discriminant analysis , partial least squares
Journal title :
Analytica Chimica Acta
Serial Year :
2005
Journal title :
Analytica Chimica Acta
Record number :
1034564
Link To Document :
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