This study investigates the spatial water quality pattern of seven stations located along the main Langat River. Environmetric methods, namely, the hierarchical agglomerative cluster analysis (HACA), the discriminant analysis (DA), the principal component analysis (PCA), and the factor analysis (FA), were used to study the spatial variations of the most significant water quality variables and to determine the origin of pollution sources. Twenty-three water quality parameters were initially selected and analyzed. Three spatial clusters were formed based on HACA. These clusters are designated as downstream of Langat river, middle stream of Langat river, and upstream of Langat River regions. Forward and backward stepwise DA managed to discriminate six and seven water quality variables, respectively, from the original 23 variables. PCA and FA (varimax functionality) were used to investigate the origin of each water quality variable due to land use activities based on the three clustered regions. Seven principal components (PCs) were obtained with 81% total variation for the high-pollution source (HPS) region, while six PCs with 71% and 79% total variances were obtained for the moderatepollution source (MPS) and low-pollution source (LPS) regions, respectively. The pollution sources for the HPS and MPS are of anthropogenic sources (industrial, municipal waste, and agricultural runoff). For the LPS region, the domestic and agricultural runoffs are the main sources of pollution. From this study, we can conclude that the application of environmetric methods can reveal meaningful information on the spatial variability of a large and complex river water quality data.

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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.

Air pollution is becoming a major environmental issue in Malaysia. This study focused on the identification of potential sources of variations in air quality around the study area based on the data obtained from the Malaysian Department of Environment (DOE).  Eight air quality parameters in ten monitoring stations for seven years (2006 – 2012) were gathered.  The Principal Component Analysis (PCA) method from chemometric technique was applied to identify the source identification of pollution around the study area. The PCA method has identified methane (CH4), non-methane hydrocarbon (NmHC), total hydrocarbon (THC), ozone (O3) and particulate matter under 10 microns (PM10) are the most significant parameters around the study area.  From the study, it can be concluded that the application of the PCA method in chemometric techniques can be applied for the source apportionment purpose. Hence, this study indicated that for the future and effective management of the Malaysian air quality, an effort should be placed as a priority in controlling point and non-point pollution sources.

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