Environmental Skeptics and Critics, 2013, 2(4): 153-163
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Data mining using multivariate statistical analysis: The case of heavy metals in sediments of the Msimbazi Creek mangrove wetland

A. Mrutu1 , G. B. Luilo2
1Department of Chemistry, University of Missouri-Columbia, 601 S. College Avenue, Columbia, MO 65211, USA
2Department of Chemistry and Chemical Biology, University of New Mexico, USA

Received 14 August 2013;Accepted 18 September 2013;Published online 1 December 2013

Mangrove wetlands are important biological systems that usually filter out organic and inorganic contaminants from the wastewaters before entering the ocean. Our previous work showed that sediments of the Msimbazi Creek wetland are contaminated with heavy metals and the amounts decreased with increasing depth. However, the hidden relationships between the heavy metals and clay particles were not fully understood based on the numerical data. Therefore this work used the data from literature and the Statistical Package for Social Sciences (SPSS) software to study how significant the relationships are and predict the sources of heavy metals and clays. The results showed that Cd is the only metal that showed insignificant correlations with other heavy metals (with Pb and Zn) while the rest of heavy metals exhibited significant positive correlation (except Pb vs. Ni). Cluster analysis classified the heavy metals based on the concentration and the first 50 cm cores (0-50 cm) had higher heavy metals and % clay than the second 50 cm cores (51-100 cm). The results from the factor analysis suggests that Pb, Cd, Ni, and clay owe their source mostly from anthropogenic activities while Fe, Co, Cr, Zn and sand come from both anthropogenic and natural sources. These results support our previous suggestions that heavy metals and clays found in this wetland have mostly anthropogenic origin. However, we recommend isotopic tracing studies in order to accurately identify the origins of the heavy metals and clays in sediments of Msimbazi Creek mangrove wetland.

Keywords wetland;sediments;heavy metals;correlation;cluster analysis;factor analysis.

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