Influential factors on the levels of cation exchange capacity in sediment at Langat river.

An exploratory study was carried out at 22 sampling stations along the Langat River, Selangor in order to investigate on the vitality of cation exchange capacity (CEC) in sediment (0–5 cm). Parameters such as pH, Eh, salinity, and electrical conductivity (EC) were determined. The CEC in sediment has been calculated by the determination of Ca2+, Na+, Mg2+, and K+ using the flame atomic absorption spectrophotometer, while the organic matter content in sediment was ascertained using the loss on ignition method. The characteristic of the sediment shows that pH (3.09–7.46), salinity (0.02–10.71 ppt), EC (3.39–517 μS/cm) and Eh (−16.20–253.10 mV) were substantially high in variation. This study also revealed that exchangeable Ca2+ and Mg2+ were controlled by organic matter contents, while exchangeable Na+ and K+ were influenced by salinity. Salinity was observed to play a major part in controlling all the exchangeable cations, as it gives strong significant correlations with Na+, K+, Mg2+, CEC, and organic matter at p < 0.01. The presence of seawater, clay mineralogy, and organic matter proves that it does play an important role in determining the CEC and soon relates to the pollution magnitude in the sediment

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 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

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 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