Pollution Sources Identification of Water Quality Using Chemometrics: a Case Study in Klang River Basin, Malaysia

  • Authors

    • Mohd Saiful Samsudin
    • Azman Azid
    • Saiful Iskandar Khalit
    • Shazlyn Milleana Shaharudin
    • Fathurrahman Lananan
    • Hafizan Hafizan Juahir
    2018-12-29
    https://doi.org/10.14419/ijet.v7i4.43.25824
  • Chemometric, Water Quality, Principal Component Analysis, Absolute Principle Component Scores- Multiple Linear Regressions, Hierarchical Agglomerative Cluster Analysis.
  • Abstract

    The objectives of this paper are to review the status of Klang River Basin and to investigate the most significant pollutant using chemometric techniques. The extraction of secondary physico-chemical water quality data by Department of Environment, Malaysia from 2003 to 2007 were taken. Principal Component Analysis (PCA) used to identify the significant water quality parameters and Absolute Principal Component Scores-Multiple Linear Regression (APCS-MLR) was applied to evaluate which pollution source contributed the most significant from the other factors. Then, Hierarchical Agglomerative Cluster Analysis (HACA) was used to find which monitoring station of Klang River provided the most significant pollutant. The result shows 9 PCs (75% of the total variance) which extracted from PCA. APCS-MLR model revealed anthropogenic activities which NH3-N as the main parameter is the most significant in Klang River. Based on HACA specified 1K16 has the highest amount of NH3-N concentration in Klang River.  Therefore, the utilization of envirometric techniques achieved the research objectives which will beneficial for present and future river water quality management.

     

     

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  • How to Cite

    Saiful Samsudin, M., Azid, A., Iskandar Khalit, S., Milleana Shaharudin, S., Lananan, F., & Hafizan Juahir, H. (2018). Pollution Sources Identification of Water Quality Using Chemometrics: a Case Study in Klang River Basin, Malaysia. International Journal of Engineering & Technology, 7(4.43), 83-89. https://doi.org/10.14419/ijet.v7i4.43.25824

    Received date: 2019-01-13

    Accepted date: 2019-01-13

    Published date: 2018-12-29