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Characterization of spatial patterns in river water quality using chemometric techniques
Norshidah Baharuddin1, Nor'ashikin Saim2, Sharifuddin M. Zain3, Hafizan Juahir4, Rozita Osman5, Aziah Aziz6.
Water pollution has become a growing threat to human society and natural ecosystem in recent decades, increasing the need to better understand the variabilities of pollutants within aquatic systems. This study presents the application of two chemometric techniques, namely, cluster analysis (CA) and principal component analysis (PCA). This is to classify and identify the water quality variables into groups of similarities or dissimilarities and to determine their significance. Six stations along Kinta River, Perak, were monitored for 30 physical and chemical parameters during the period of 1997-2006. Using CA, the 30 physical and chemical parameters were classified into 4 clusters; PCA was applied to the datasets and resulted in 10 varifactors with a total variance of 78.06%. The varifactors obtained indicated the significance of each of the variables to the pollution of Kinta River.
Affiliation:
- SIRIM Berhad, Malaysia
- Universiti Teknologi MARA, Malaysia
- University of Malaya, Malaysia
- Universiti Sultan Zainal Abidin, Malaysia
- Universiti Teknologi MARA, Malaysia
- SIRIM Berhad, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Web of Science (SCIE - Science Citation Index Expanded) |
Impact Factor
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JCR (1.009) |
Rank |
Q4 (Multidisciplinary Sciences) |
Additional Information |
JCI (0.15) |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q2 (Multidisciplinary) |
Additional Information |
SJR (0.251) |
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