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The monitoring of spatial variation and source of heavy metals pollution at the northern and southern regions of the Straits of Malacca, Malaysia, using chemometric analysis.

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The amount of suspended sediment yield and the size of sediment grains an indicator of hydrological cycle, especially in the river. The sediment transportation process is one of the measurements of water resources management. Equilibrium of the river depends on the flow rate of water and by several factors such as frequency of rainfall, climate changes and land use activities that changes then effected to the river flow. Sedimentation problems occur in reservoirs, rivers, lakes, flood plains and offshore. This study was carried out in the upstream area, Lata Berangin, Hulu Keruak, Besut, Terengganu. This study was implemented to prove the sedimentation problem, especially the formation of total suspended sediment (TSS) and the bed sediment grain size. There are three important parameters were quantified in this study such as the distribution of sediment grain size (phi), TSS (mg/L) and the river discharge values (Q) (m³/s). The technique of analysis of primary data obtained which determine the bed sediment grain size according with the procedure of Gerald and Kenneth and the phi (ϕ) value in this study using the scale Udden-Wentworth that included median, mean, standard deviation, skewness, kurtosis and the Gravimetric Method used to analyze the concentration TSS is the Gravimetric Method. From the result, the highest TSS up to 6.0 mg/L which is categorized under the class I, based on the National Water Quality Standard. Overall, the estimated daily-suspended sediment load values up to 1.1649 tonne/day at Station 2. Then, from the statistics for the median, mean, standard deviation, skewness and kurtosis showed that the size of sediment falls between phi-0.30φ to phi-1.00 φ which classified as very coarse and the majority of the sediment texture and a very leptokurtic, leptokurtic texture showed sedimentation production is not so high. Overall, the sedimentation problem in Lata Berangin, Hulu Keruak still in stable level. Most of this upstream area still not developed as land use activities around the river basin.

This study intends to show the effectiveness of hierarchical agglomerative cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), factor analysis (FA) and multiple linear regressions (MLR) for assessing the air quality data and air pollution sources pattern recognition. The data sets of air quality for 12 months (January-December) in 2007, consisting of 14 stations around Peninsular Malaysia with 14 parameters (168 datasets) were applied. Three significant clusters -low pollution source (LPS) region, moderate pollution source (MPS) region, and slightly high pollution source (SHPS) region were generated via HACA. Forward stepwise of DA managed to discriminate 8 variables, whereas backward stepwise of DA managed to discriminate 9 out of 14 variables. The method of PCA and FA has identified 8 pollutants in LPS and SHPS respectively, as well as 11 pollutants in MPS region, where most of the pollutants are expected derived from industrial activities, transportation and agriculture systems. Four MLR models show that PM 10 categorize as the primary pollutant in Malaysia. From the study, it can be stipulated that the application of chemometric techniques can disclose meaningful information on the spatial variability of a large and complex air quality data. A clearer review about the air quality and a novel design of air quality monitoring network for better management of air pollution can be achieved.