Contamination and Pollution Assessment of Heavy Metal in Kuala Perlis Sediment Phase: A Statistical Analysis Approach

Authors

  • Arina Azmina Ahmad Zubir Water Research Group (WAREG), School of Environmental Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia.

Abstract

 

 A study on heavy metals pollution in sediment of Kuala Perlis was done which four types of heavy metals that are identified in the coastal area. The presence of Cr, Pb, Zn and Cu are resulted from the anthropogenic activities occurs in the land use of Kuala Perlis. Samples were collected with different depth phase (subsurface, 1ft, 2ft and 3ft) at five different points (A,B,C,D and E) based on the different land use activities. The distribution concentrations of Cr, Pb, Zn and Cu in each point were analyzed by using descriptive analysis. Based on the analysis Pb gives the highest in mean concentration compared to others in all points. The relation of metals concentration and the sediment characteristics were analyzed by Pearson correlation analysis. The correlation analysis shows the positive correlation among the metals with percentage of silt and clay and negative correlation among the metals with the sediment pH. The sediment pollution assessments were investigated by using contamination indices such as Enrichment Factor (EF), Geo-accumulation Index (Igeo), Contamination Factor (CF) and Pollution Load Index (PLI). Among the four metals tested Pb gives the highest value of EF, Igeo and CF in sediments collected from each sampling points meanwhile point A gives the highest PLI value. Based on the terminologies, since the PLI value <1 so, the sediment in Kuala Perlis coastal area are considered as unpolluted sediment.

Keywords:

Heavy Metals, Sediment, Descriptive Analysis, Pearson Correlation, Contamination Indices

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Published

2018-12-31

How to Cite

Arina Azmina Ahmad Zubir. (2018). Contamination and Pollution Assessment of Heavy Metal in Kuala Perlis Sediment Phase: A Statistical Analysis Approach. Applied Mathematics and Computational Intelligence (AMCI), 7(1), 1–12. Retrieved from https://ejournal.unimap.edu.my/index.php/amci/article/view/100