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This study employed three chemometric data mining techniques (factor analysis (FA), cluster analysis (CA), and discriminant analysis (DA)) to identify the latent structure of a water quality (WQ) dataset pertaining to Kinta River (Malaysia) and to classify eight WQ monitoring stations along the river into groups of similar WQ characteristics. FA identified the WQ parameters responsible for variations in Kinta River's WQ and accentuated the roles of weathering and surface runoff in determining the river's WQ. CA grouped the monitoring locations into a cluster of low levels of water pollution (the two uppermost monitoring stations) and another of relatively high levels of river pollution (the mid-, and down-stream stations). DA confirmed these clusters and produced a discriminant function which can predict the cluster membership of new and/or unknown samples. These chemometric techniques highlight the potential for reasonably reducing the number of WQVs and monitoring stations for long-term monitoring purposes. 相似文献
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Zahidi Hamzah Ahmad Zaharin Aris Mohammad Firuz Ramli Hafizan Juahir Tahoora Sheikhy Narany 《Arabian Journal of Geosciences》2017,10(2):49
Extensive agricultural, residential, and industrial activities have increased demand for water supplies, which can lead to groundwater quality degradation. The integration of geochemical methods, multivariate statistical analysis, and geostatistical approaches were carried out on 169 groundwater samples to elucidate the regional factors and processes that influencing the geochemical composition of groundwater in coastal shallow aquifer of Terengganu, Malaysia. Hydrochemical modelling revealed that the abundance of Ca and Mg was contributed by carbonate and silicate weathering while higher HCO3 and Cl were resulted from reverse ion exchange reaction. Therefore, the dominant hydrogeochemical facies of groundwater was Ca-Mg-HCO3-Cl type. The influence of salinization resulting from seawater mixing to the groundwater was corroborated by Cl/HCO3 ratio, which affected around 50.9% of the groundwater samples slightly or moderately. Spatial mapping using ordinary kriging found that the threat of sea water intrusion is more prominent in the major river confluence especially around Terengganu and Marang River in the northeast and Dungun and Kemaman River confluence in southeast of study area. Moreover, factor analyses concluded that salinization, anthropogenic activities, reverse ion exchange, weathering processes, agricultural impact, and seasonal variations were the factors that regulate 63% of the major ion chemistry in study area. Finally, these findings showed the importance of understanding the hydrochemical characteristics for effective utilization, aquifer protection, and prediction of changes to minimize the effects of salinization and reduce human pollution such as agriculture and urbanization. It is essential steps in order to safeguard the utilization of groundwater resources for future generations. 相似文献
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Nur Mun’im Mohd Han Mohd Talib Latif Murnira Othman Doreena Dominick Noorlin Mohamad Hafizan Juahir Norhayati Mohd Tahir 《Environmental Earth Sciences》2014,72(3):849-859
This study was carried out in order to determine the concentration of heavy metals, e.g., lead (Pb), cadmium (Cd), copper (Cu), zinc (Zn), iron (Fe), manganese (Mn), nickel (Ni) and chromium (Cr) in road dust in Kuala Lumpur’s city centre. Samples were collected from four sampling locations, each of which had four sampling points and three replications. Heavy metals from different fractions of particles separated by different diameter sizes: d < 63 μm (Fraction A), 63 < d < 125 μm (Fraction B) and 125 < d < 250 μm (Fraction C) were analyzed using inductively coupled plasma mass spectrometry. The results from this study showed that concentration of heavy metals was dominated by the smallest particle size: <63 μm and that Fe was the most abundant heavy metal overall, followed by Cu > Mn > Zn > Pb > Ni > Cr > Cd. The fact that Cd had the highest enrichment factor value (EF) for all particle sizes indicates that anthropogenic activities contributed to the presence of this metal. There was also a higher EF value for heavy metals in small particle (Fraction A), compared to Fraction B and C, which suggests that fine particles were being produced through anthropogenic activities. Cluster analysis and principal component analysis demonstrated the likelihood of the heavy metals detected in the road dust, originating from road traffic and industrial activities. 相似文献
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Adamu Mustapha Ahmad Zaharin Aris Hafizan Juahir Mohammad Firuz Ramli 《Arabian Journal of Geosciences》2013,6(12):4903-4915
The present study investigates the surface water quality of three important tributaries of Jakara Basin, northwestern Nigeria to provide an overview of the relationship and sources of physicochemical and biological parameters. A total of 405 water samples were collected from 27 sampling points and analyzed for 13 parameters: dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), suspended solids (SS), pH, ammonia-nitrogen (NH3NL), dissolved solids (DS), total solids (TS), nitrates (NO3), chloride (Cl), phosphates (PO4), Escherichia coli (E. coli) and fecal coliform bacteria (FCB). Pearson’s product–moment correlation matrix and principal component analysis (PCA) were used to distinguish the main pollution sources in the basin. Four varimax components were extracted from PCA, which explained 84.86, 83.60, and 78.69 % of the variation in the surface water quality for Jakara, Tsakama, and Gama-Kwari Rivers, respectively. Strong positive loading included BOD5, COD, NH3NL, E. coli, and FCB with negative loading on DO attribute to a domestic waste water pollution source. One-way ANOVA revealed that there was no significant difference in the mean of the three water bodies (p?>?0.05). It is therefore recommended that the government should be more effective in controlling the point source of pollution in the area. 相似文献
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