The Chemometric Approach as a Useful Tool in the Identification of Metal Pollution Sources of Riverine-Mangrove Sediment of Kota Marudu, Sabah, Malaysia
The chemometric statistical approach was applied to evaluate the level of metals accumulation in sediment and to identify the probable pollution sources in the riverine-mangrove ecosystem of Kota Marudu, East Malaysia. Parameters, such as pH, electrical conductivity, salinity, organic matter, lead (Pb), cadmium (Cd), copper (Cu), chromium (Cr), zinc (Zn), aluminum (Al), nickel (Ni) and iron (Fe) were determined from sediment samples collected from 17 sampling points located throughout the district of Kota Marudu, Sabah. The results from cluster analysis indicate the presence of two prominent c... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2014 |
Reihe/Periodikum: | EnvironmentAsia, Vol 7, Iss 2, Pp 70-78 (2014) |
Verlag/Hrsg.: |
Thai Society of Higher Eduction Institutes on Environment
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Schlagwörter: | chemometric / metals / sediment / HACA / PCA / Geography. Anthropology. Recreation / G / Environmental sciences / GE1-350 |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-27640035 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://doaj.org/article/69ebef5d0d9c4ce3822fbba13eed73ee |
The chemometric statistical approach was applied to evaluate the level of metals accumulation in sediment and to identify the probable pollution sources in the riverine-mangrove ecosystem of Kota Marudu, East Malaysia. Parameters, such as pH, electrical conductivity, salinity, organic matter, lead (Pb), cadmium (Cd), copper (Cu), chromium (Cr), zinc (Zn), aluminum (Al), nickel (Ni) and iron (Fe) were determined from sediment samples collected from 17 sampling points located throughout the district of Kota Marudu, Sabah. The results from cluster analysis indicate the presence of two prominent clusters that represent sources of pollution that might be induced from natural sources and human activities. Meanwhile, principal analysis from this study has proven that pH, electrical conductivity, salinity, Cd and Cr are responsible for the large spatial variations explaining 31.73% of the total variance, whilst organic matter, Fe and Al explain 24.75% of the total variance. The third factor is followed by Cu and Zn with 15.35% whereas Pb and Ni account for a total variance of 14.44%. The present study reveals the usefulness of the chemometric statistical approach as a remarkable and useful tool to reveal meaningful information concerning the spatial variability of large and complex riverine-mangrove data.