2 research outputs found

    Assessment of drinking water quality using principal component analysis and partial least square discriminant analysis: a case study at water treatment plants, Selangor

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    This study characterizes the drinking water quality on 28 water treatmentt plants in Selangor from 2009 to 2012 using multivariate techniques. The objectives of this study are to analyze the quality of collected drinking water and to detect the source of pollution for the most revealing  parameters.  The  Partial  Least  Square  Discriminant  Analysis (PLS-DA)  model showed a high correlation matrix of analysis for physicochemical quality of two types of water with  99.43% significant  value.  The classification  matrix  accuracy of the principal component  analysis  (PCA) highlighted  13  significant  physico-chemical water quality parameters and 14 significant heavy metal parameters. PCA was carried out to identify the origin and source of pollution of each water quality parameters. Therefore, this study proves that chemometric method is the principle way to characterize the drinking water quality.Keywords: partial least square, discriminant analysis; principal component analysis; drinking water qualit

    The assessment of the variation of physico-chemical sources for drinking water quality using chemometrics: A case study at water treatment plants in Klang Valley

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    This case study characterizes the drinking water quality by using the multivariate technique. The spatial variation of the physico-chemical and heavy metals parameters toxicity with the drinking water quality based on 28 water treatment plants in Selangor, Malaysia from 2009 to 2012 was evaluated. The objectives of this study are to analyze the physio-chemical activities and heavy metals activities in the collected drinking water samples from the treatment plants, and to detect the source of pollution for the most revealing parameters. The discriminant analysis (DA) and the principal component analysis (PCA) are the chemometric techniques used to investigate the spatial variation of the most significant physico-chemical and heavy metal parameters of the drinking water samples. The classification matrix accuracy for standard mode of DA, forward stepwise and backward stepwise for the physico-chemical and heavy metal parameters are excellent. PCA highlighted 13 significant parameters out of 18 physico-chemical water quality parameters and 14 significant parameters out of 16 heavy metal parameters. PCA was carried out to identify the origin and source of pollution of each water quality parameters. For that reason, this study proves that chemometric method is the principle way to explain the characteristic of the drinking water quality
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