Increasing urbanization and changes in land use in Langat river basin lead to adverse impacts on the environment compartment. One of the major challenges is in identifying sources of organic contaminants. This study presented the application of selected chemometric techniques: cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) to classify the pollution sources in Langat river basin based on the analysis of water and sediment samples collected from 24 stations, monitored for 14 organic contaminants from polycyclic aromatic hydrocarbons (PAHs), sterols, and pesticides groups. The CA and DA enabled to group 24 monitoring sites into three groups of pollution source (industry and urban socioeconomic, agricultural activity, and urban/domestic sewage) with five major discriminating variables: naphthalene, pyrene, benzo[a]pyrene, coprostanol, and cholesterol. PCA analysis, applied to water data sets, resulted in four latent factors explaining 79.0% of the total variance while sediment samples gave five latent factors with 77.6% explained variance. The varifactors (VFs) obtained from PCA indicated that sterols (coprostanol, cholesterol, stigmasterol, β-sitosterol, and stigmastanol) are strongly correlated to domestic and urban sewage, PAHs (naphthalene, acenaphthene, pyrene, benzo[a]anthracene, and benzo[a]pyrene) from industrial and urban activities and chlorpyrifos correlated to samples nearby agricultural sites. The results demonstrated that chemometric techniques can be used for rapid assessment of water and sediment contaminations.
A novel sol-gel hybrid methyltrimethoxysilane-tetraethoxysilane (MTMOS-TEOS) was produced and applied as sorbent for solid phase extraction (SPE). Five selected organophosphorus pesticides (OPPs) were employed as model compounds to evaluate the extraction performance of the synthesized sol-gel organic-inorganic hybrid MTMOS-TEOS. Analysis was performed using gas chromatography-mass spectrometry. Several important SPE parameters were optimized. Under the optimum extraction conditions, the method using the sol-gel organic-inorganic hybrid MTMOS-TEOS as SPE sorbent showed good linearity in the range of 0.001-1 μg L(-1), good repeatability (RSD 2.1-3.1%, n=5), low limits of detection at S/N=3 (0.5-0.9 pg mL(-1)) and limit of quantification (1-3 pg mL(-1), S/N=10). The performance of the MTMOS-TEOS SPE was compared to commercial C18 Supelclean SPE since C18 SPE is widely used for OPPs. The MTMOS-TEOS SPE method LOD was 500-600 × lower than the LOD of commercial C18 SPE. The LOD achieved with the sol-gel organic-inorganic hybrid MTMOS-TEOS SPE sorbent allowed the detection of these OPPs in drinking water well below the level set by European Union (EU) at 0.1 μg L(-1) of each pesticides. The developed MTMOS-TEOS SPE method was successfully applied to real sample analysis of the selected OPPs from several water samples and its application extended to the analysis of several fruits samples. Excellent recoveries and RSDs of the OPPs were obtained from the various water samples (recoveries: 97-111%, RSDs 0.4-2.8%, n=3) and fruit samples (recoveries: 96-111%), RSDs 1-4%, n=5) using the sol-gel organic-inorganic hybrid MTMOS-TEOS SPE sorbent. Recoveries and RSDs of OPPs from river water samples and fruit samples using C18 Supelclean SPE sorbent were 91-97%, RSD 0.9-2.6, n=3 and 86-96%, RSD 3-8%, n=5, respectively). The novel sol-gel hybrid MTMOS-TEOS SPE sorbent demonstrate the potential as an alternative inexpensive extraction sorbent for OPPs with higher sensitivity for the OPPs.
This study investigated the level of bisphenol A (BPA) in surface water used as potable water, drinking water (tap and bottled mineral water) and human plasma in the Langat River basin, Malaysia. BPA was present in 93% of the surface water samples at levels ranging from below limit of quantification (LOQ; 1.3 ng/L) to 215 ng/L while six fold higher levels were detected in samples collected near industrial and municipal sewage treatment plant outlets. Low levels of BPA were detected in most of the drinking water samples. BPA in tap water ranged from 3.5 to 59.8 ng/L with the highest levels detected in samples collected from taps connected to PVC pipes and water filter devices. Bottled mineral water had lower levels of BPA (3.3±2.6 ng/L) although samples stored in poor storage condition had significantly higher levels (11.3±5.3 ng/L). Meanwhile, only 17% of the plasma samples had detectable levels of BPA ranging from 0.81 to 3.65 ng/mL. The study shows that BPA is a ubiquitous contaminant in surface, tap and bottled mineral water. However, exposure to BPA from drinking water is very low and is less than 0.01% of the tolerable daily intake (TDI).
This article describes design and application of feed-forward, fully-connected, three-layer perceptron neural network model for computing the water quality index (WQI)(1) for Kinta River (Malaysia). The modeling efforts showed that the optimal network architecture was 23-34-1 and that the best WQI predictions were associated with the quick propagation (QP) training algorithm; a learning rate of 0.06; and a QP coefficient of 1.75. The WQI predictions of this model had significant, positive, very high correlation (r=0.977, p<0.01) with the measured WQI values, implying that the model predictions explain around 95.4% of the variation in the measured WQI values. The approach presented in this article offers useful and powerful alternative to WQI computation and prediction, especially in the case of WQI calculation methods which involve lengthy computations and use of various sub-index formulae for each value, or range of values, of the constituent water quality variables.
Agarose film liquid phase microextraction (AF-LPME) procedure for the extraction and preconcentration of polycyclic aromatic hydrocarbons (PAHs) in water has been investigated. Agarose film was used for the first time as an interface between donor and acceptor phases in liquid phase microextraction which allowed for selective extraction of the analytes prior to gas chromatography-mass spectrometry. Using 1-octanol as acceptor phase, high enrichment factors in the range of 57-106 for the targeted analytes (fluorene, phenanthrene, fluoranthene and pyrene) were achieved. Under the optimum extraction conditions, the method showed good linearity in the range of 0.1-200 μgL(-1), good correlation coefficients in the range of 0.9963-0.9999, acceptable reproducibility (RSD 6.1-9.2%, n=3), low limits of detection (0.01-0.04 μgL(-1)) and satisfactory relative recoveries (92.9-104.7%). As the AF-LPME device was non-expensive, reuse or recycle of the film was not required, thus eliminating the possibility of analytes carry-over between runs. The AF-LPME technique is environment-friendly and compatible with the green chemistry concept as agarose is biodegradable polysaccharide extracted from seaweed and the procedure requires small volume of organic solvent and generates little waste. The validated method was successfully applied to the analysis of the four analytes in river water samples.
Influences of river hydrodynamic behaviours on hydrochemistry (salinity, pH, dissolved oxygen saturations and dissolved phosphorus) were evaluated through high spatial and temporal resolution study of a sandbar-regulated coastal river. River hydrodynamic during sandbar-closed event was characterized by minor dependency on tidal fluctuations, very gradual increase of water level and continual low flow velocity. These hydrodynamic behaviours established a hydrochemistry equilibrium, in which water properties generally were characterized by virtual absence of horizontal gradients while vertical stratifications were significant. In addition, the river was in high trophic status as algae blooms were visible. Conversely, river hydrodynamic in sandbar-opened event was tidal-controlled and showed higher flow velocity. Horizontal gradients of water properties became significant while vertically more homogenised and with lower trophic status. In essence, this study reveals that estuarine sandbar directly regulates river hydrodynamic behaviours which in turn influences river hydrochemistry.
Multivariate statistical techniques such as hierarchical Agglomerated cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), and factor analysis (FA) were applied to identify the spatial variation and pollution sources of Jakara River, Kano, Nigeria. Thirty surface water samples were collected: 23 along Getsi River and 7 along the main channel of River Jakara. Twenty-three water quality parameters, namely pH, temperature, turbidity, electrical conductivity (EC), dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD(5)), Faecal coliform, total solids (TS), nitrates (NO(3)(-)), phosphates (PO(4)(3-)), cobalt (Co), iron (Fe), nickel (Ni), manganese (Mn), copper (Cu), sodium (Na), potassium (K), mercury (Hg), chromium (Cr), cadmium (Cd), lead (Pb), magnesium (Mg), and calcium(Ca) were analysed. HACA grouped the sampling points into three clusters based on the similarities of river water quality characteristics: industrial, domestic, and agricultural water pollution sources. Forward and backward DA effectively discriminated 5 and 15 water quality variables, respectively, each assigned with 100% correctness from the original 23 variables. PCA and FA were used to investigate the origin of each water quality parameter due to various land use activities, 7 principal components were obtained with 77.5% total variance, and in addition PCA identified 3 latent pollution sources to support HACA. From this study, one can conclude that the application of multivariate techniques derives meaningful information from water quality data.
The pollution status of the downstream section of the Jakara River was investigated. Dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD(5)), chemical oxygen demand (COD), suspended solids (SS), pH, conductivity, salinity, temperature, nitrogen in the form of ammonia (NH(3)), turbidity, dissolved solids (DS), total solids (TS), nitrates (NO(3)), chloride (Cl) and phosphates (PO(3-)(4)) were evaluated, using both dry and wet season samples, as a measure of variation in surface water quality in the area. The results obtained from the analyses were correlated using Pearson's correlation matrix, principal component analysis (PCA) and paired sample t-tests. Positive correlations were observed for BOD(5), NH(3), COD, and SS, turbidity, conductivity, salinity, DS, TS for dry and wet seasons, respectively. PCA was used to investigate the origin of each water quality parameter, and yielded 5 varimax factors for each of dry and wet seasons, with 70.7 % and 83.1 % total variance, respectively. A paired sample t-test confirmed that the surface water quality varies significantly between dry and wet season samples (P < 0.01). The source of pollution in the area was concluded to be of anthropogenic origin in the dry season and natural origins in the wet season.
Bukit Merah Reservoir is the main potable and irrigation water source for Kerian District, Perak State, Malaysia. For the past two decades, the reservoir has experienced water stress. Land-use activities have been identified as the contributor of the sedimentation. The Soil and Water Assessment Tool (SWAT) was used to simulate and quantify the impacts of land-use change in the reservoir watershed. The SWAT was calibrated and two scenarios were constructed representing projected land use in the year 2015 and hypothetical land use to represent extensive land-use change in the catchment area. The simulation results based on 17 years of rainfall records indicate that average water quantity will not be significantly affected but the ground water storage will decrease and suspended sediment will increase. Ground water decrease and sediment yield increase will exacerbate the Bukit Merah Reservoir operation problem.
The Langat River in Malaysia has been experiencing anthropogenic input from urban, rural and industrial activities for many years. Sewage contamination, possibly originating from the greater than three million inhabitants of the Langat River Basin, were examined. Sediment samples from 22 stations (SL01-SL22) along the Langat River were collected, extracted and analysed by GC-MS. Six different sterols were identified and quantified. The highest sterol concentration was found at station SL02 (618.29 ng/g dry weight), which situated in the Balak River whereas the other sediment samples ranged between 11.60 and 446.52 ng/g dry weight. Sterol ratios were used to identify sources, occurrence and partitioning of faecal matter in sediments and majority of the ratios clearly demonstrated that sewage contamination was occurring at most stations in the Langat River. A multivariate statistical analysis was used in conjunction with a combination of biomarkers to better understand the data that clearly separated the compounds. Most sediments of the Langat River were found to contain low to mid-range sewage contamination with some containing 'significant' levels of contamination. This is the first report on sewage pollution in the Langat River based on a combination of biomarker and multivariate statistical approaches that will establish a new standard for sewage detection using faecal sterols.
Surface water is one of the essential resources for supporting sustainable development. The suitability of such water for a given use depends both on the available quantity and tolerable quality. Temporary status for a surface water quality has been identified extensively. Still the suitability of the water for different purposes needs to be verified. This study proposes a water quality evaluation system to assess the aptitude of the Selangor River water for aquatic biota, drinking water production, leisure and aquatic sport, irrigation use, livestock watering, and aquaculture use. Aptitude of the water has been classified in many parts of the river segment as unsuitable for aquatic biota, drinking water production, leisure and aquatic sport as well as aquaculture use. The water quality aptitude classes of the stream water for nine locations along the river are evaluated to contribute to decision support system. The suitability of the water for five different uses and its aquatic ecosystem are verified.
A study on the quality of water abstracted for potable use was conducted in the Selangor River basin from November 2008 to July 2009. Seven sampling sites representing the intake points of water treatment plants in the basin were selected to determine the occurrence and level of 15 organochlorine pesticides (OCPs), six phthalate esters (PAEs) and bisphenol A (BPA). Results indicated OCPs were still detected regularly in 66.1 % of the samples with the Σ(15)OCPs ranging from 0.6-25.2 ng/L. The first data on PAEs contamination in the basin revealed Σ(6)PAEs concentrations were between 39.0 and 1,096.6 ng/L with a median concentration of 186.0 ng/L while BPA concentration ranged from <1.2 to 120.0 ng/L. Although di-n-butyl phthalate was detected in all the samples, concentrations of di-ethyl(hexyl)phthalate were higher. Sampling sites located downstream recorded the highest concentrations, together with samples collected during the dry season. Comparison of the detected contaminants with the Department of Environment Water Quality Index (DOE-WQI) showed some agreement between the concentration and the current classification of stream water. While the results suggest that the sites were only slightly polluted and suitable to be used as drinking water source, its presence is cause for concern especially to the fragile firefly "Pteroptyx tener" ecosystem located further downstream.
Seven sulfonamides, trimethoprim, five macrolides, lincomycin and three tetracyclines were measured in 150 water samples of sewage, livestock and aquaculture wastewater, and river and coastal waters, in five tropical Asian countries. The sum of the concentrations of the target antibiotics in sewage and heavily sewage-impacted waters were at sub- to low-ppb levels. The most abundant antibiotic was sulfamethoxazole (SMX), followed by lincomycin and sulfathiazole. The average concentration of SMX in sewage or heavily sewage-impacted waters was 1720 ng/L in Vietnam (Hanoi, Ho Chi Minh, Can Tho; n=15), 802ng/L in the Philippines (Manila; n=4), 538 ng/L in India (Kolkata; n=4), 282 ng/L in Indonesia (Jakarta; n=10), and 76 ng/L in Malaysia (Kuala Lumpur; n=6). These concentrations were higher than those in Japan, China, Europe, the US and Canada. A predominance of sulfonamides, especially SMX, is notable in these tropical countries. The higher average concentrations, and the predominance of SMX, can be ascribed to the lower cost of the antibiotics. Both the concentration and composition of antibiotics in livestock and aquaculture wastewater varied widely. In many cases, sulfamethazine (SMT), oxytetracycline (OTC), lincomycin, and SMX were predominant in livestock and aquaculture wastewater. Both human and animal antibiotics were widely distributed in the respective receiving waters (i.e., the Mekong River and Manila Bay). SMT/SMX ratios indicate a significant contribution from livestock wastewater to the Mekong River and nearby canals, with an estimated ~10% of river water SMX derived from such wastewater. Mass flow calculations estimate that 12 tons of SMX is discharged annually from the Mekong River into the South China Sea. Riverine inputs of antibiotics may significantly increase the concentration of such antibiotics in the coastal waters.
A study was conducted to investigate the influence of Asian monsoon on chlorophyll-a (Chl-a) content in Sabah waters and to identify the related oceanographic conditions that caused phytoplankton blooms at the eastern and western coasts of Sabah, Malaysia. A series of remote sensing measurements including surface Chl-a, sea surface temperature, sea surface height anomaly, wind speed, wind stress curl, and Ekman pumping were analyzed to study the oceanographic conditions that lead to large-scale nutrients enrichment in the surface layer. The results showed that the Chl-a content increased at the northwest coast from December to April due to strong northeasterly wind and coastal upwelling in Kota Kinabalu water. The southwest coast (Labuan water) maintained high concentrations throughout the year due to the effect of Padas River discharge during the rainy season and the changing direction of Baram River plume during the northeast monsoon (NEM). However, with the continuous supply of nutrients from the upwelling area, the high Chl-a batches were maintained at the offshore water off Labuan for a longer time during NEM. On the other side, the northeast coast illustrated a high Chl-a in Sandakan water during NEM, whereas the northern tip off Kudat did not show a pronounced change throughout the year. The southeast coast (Tawau water) was highly influenced by the direction of the surface water transport between the Sulu and Sulawesi Seas and the prevailing surface currents. The study demonstrates the presence of seasonal phytoplankton blooms in Sabah waters which will aid in forecasting the possible biological response and could further assist in marine resource managements.
The presence of endocrine disruptors in source water is of great concern because of their suspected adverse effects on humans, even when present at very low levels. As the main source of potable water supply, rivers in Malaysia are highly susceptible to contamination by various endocrine disruptors originating from anthropogenic activities. In this study, the contamination levels of 1,1,1-trichloro-2,2-bis (4-chlorophenyl) ethane (DDT) and its metabolites and di-(2-ethylhexyl) phthalate (DEHP) in rivers of Selangor were examined using gas chromatography-mass spectrometry. Samples were collected from sites representing source water for 18 drinking water treatment plants in Selangor between July 2008 and July 2009. DDT and its metabolites were detected in only 14% of the 192 samples analysed at levels ranging from 0.6 to 14.6 ng/L. Meanwhile DEHP was detected in 96.8% of the samples at levels ranging from below quantitation level (18 ng/L) to 970 ng/L. The detected levels of DDTs and DEHP were lower than the WHO and Malaysian Guidelines for Drinking Water Quality. Data obtained from this study should also serve as a reference point for future surveillance on these endocrine disruptors.
Concentrations of the heavy metals copper (Cu), cadmium (Cd), zinc (Zn), lead (Pb) and nickel (Ni) were determined in the liver, gills and muscles of tilapia fish from the Langat River and Engineering Lake, Bangi, Selangor, Malaysia. There were differences in the concentrations of the studied heavy metals between different organs and between sites. In the liver samples, Cu>Zn>Ni>Pb>Cd, and in the gills and muscle, Zn>Ni>Cu>Pb>Cd. Levels of Cu, Cd, Zn and Pb in the liver samples from Engineering Lake were higher than in those from the Langat River, whereas the Ni levels in the liver samples from the Langat River were greater than in those from Engineering Lake. Cd levels in the fish muscle from Engineering Lake were lower than in that from the Langat River. Meanwhile, the Cd, Zn and Pb levels in the fish muscle from the Langat River were lower than in that from Engineering Lake, and the Ni levels were almost the same in the fish muscle samples from the two sites. The health risks associated with Cu, Cd, Zn, Pb and Ni were assessed based on the target hazard quotients. In the Langat River, the risk from Cu is minimal compared to the other studied elements, and the concentrations of Pb and Ni were determined to pose the greatest risk. The maximum allowable fish consumption rates (kg/d) based on Cu in Engineering Lake and the Langat River were 2.27 and 1.51 in December and 2.53 and 1.75 in February, respectively. The Cu concentrations resulted in the highest maximum allowable fish consumption rates compared with the other studied heavy metals, whereas those based on Pb were the lowest. A health risk analysis of the heavy metals measured in the fish muscle samples indicated that the fish can be classified at one of the safest levels for the general population and that there are no possible risks pertaining to tilapia fish consumption.
Field and laboratory studies were conducted to estimate concentration of potential contaminants from landfill in the underlying groundwater, leachate, and surface water. Samples collected in the vicinity of the landfill were analyzed for physiochemical parameters, organic contaminants, and toxic heavy metals. Water quality results obtained were compared from published data and reports. The results indicate serious groundwater and surface water contamination in and around the waste disposal site. Analysis of the organic samples revealed that the site contains polychlorinated biphenyls and other organo-chlorine chemicals, principally chloro-benzenes. Although the amount of PCB concentration discovered was not extreme, their presence indicates a potentially serious environmental threat. Elevated concentrations of lead, copper, nickel, manganese, cadmium, and cobalt at the downgradient indicate that the contamination plume migrated further from the site, and the distribution of metals and metals containing wastes in the site is nonhomogeneous. These results clearly indicate that materials are poorly contained and are at risk of entering the environment. Therefore, full characterization of the dump contents and the integrity of the site are necessary to evaluate the scope of the problem and to identify suitable remediation options.
This study investigated relationships of a water quality index (WQI) with multiple water quality variables (WQVs), explored variability in water quality over time and space, and established linear and non-linear models predictive of WQI from raw WQVs. Data were processed using Spearman's rank correlation analysis, multiple linear regression, and artificial neural network modeling. Correlation analysis indicated that from a temporal perspective, the WQI, temperature, and zinc, arsenic, chemical oxygen demand, sodium, and dissolved oxygen concentrations increased, whereas turbidity and suspended solids, total solids, nitrate nitrogen (NO3-N), and biochemical oxygen demand concentrations decreased with year. From a spatial perspective, an increase with distance of the sampling station from the headwater was exhibited by 10 WQVs: magnesium, calcium, dissolved solids, electrical conductivity, temperature, NO3-N, arsenic, chloride, potassium, and sodium. At the same time, the WQI; Escherichia coli bacteria counts; and suspended solids, total solids, and dissolved oxygen concentrations decreased with distance from the headwater. Lastly, regression and artificial neural network models with high prediction powers (81.2% and 91.4%, respectively) were developed and are discussed.
Jakara River Basin has been extensively studied to assess the overall water quality and to identify the major variables responsible for water quality variations in the basin. A total of 27 sampling points were selected in the riverine network of the Upper Jakara River Basin. Water samples were collected in triplicate and analyzed for physicochemical variables. Pearson product-moment correlation analysis was conducted to evaluate the relationship of water quality parameters and revealed a significant relationship between salinity, conductivity with dissolved solids (DS) and 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), and nitrogen in form of ammonia (NH4). Partial correlation analysis (r p) results showed that there is a strong relationship between salinity and turbidity (r p=0.930, p=0.001) and BOD5 and COD (r p=0.839, p=0.001) controlling for the linear effects of conductivity and NH4, respectively. Principal component analysis and or factor analysis was used to investigate the origin of each water quality parameter in the Jakara Basin and identified three major factors explaining 68.11 % of the total variance in water quality. The major variations are related to anthropogenic activities (irrigation agricultural, construction activities, clearing of land, and domestic waste disposal) and natural processes (erosion of river bank and runoff). Discriminant analysis (DA) was applied on the dataset to maximize the similarities between group relative to within-group variance of the parameters. DA provided better results with great discriminatory ability using eight variables (DO, BOD5, COD, SS, NH4, conductivity, salinity, and DS) as the most statistically significantly responsible for surface water quality variation in the area. The present study, however, makes several noteworthy contributions to the existing knowledge on the spatial variations of surface water quality and is believed to serve as a baseline data for further studies. Future research should therefore concentrate on the investigation of temporal variations of water quality in the basin.
This study investigates the applicability of multivariate statistical techniques including cluster analysis (CA), discriminant analysis (DA), and factor analysis (FA) for the assessment of seasonal variations in the surface water quality of tropical pastures. The study was carried out in the TPU catchment, Kuala Lumpur, Malaysia. The dataset consisted of 1-year monitoring of 14 parameters at six sampling sites. The CA yielded two groups of similarity between the sampling sites, i.e., less polluted (LP) and moderately polluted (MP) at temporal scale. Fecal coliform (FC), NO3, DO, and pH were significantly related to the stream grouping in the dry season, whereas NH3, BOD, Escherichia coli, and FC were significantly related to the stream grouping in the rainy season. The best predictors for distinguishing clusters in temporal scale were FC, NH3, and E. coli, respectively. FC, E. coli, and BOD with strong positive loadings were introduced as the first varifactors in the dry season which indicates the biological source of variability. EC with a strong positive loading and DO with a strong negative loading were introduced as the first varifactors in the rainy season, which represents the physiochemical source of variability. Multivariate statistical techniques were effective analytical techniques for classification and processing of large datasets of water quality and the identification of major sources of water pollution in tropical pastures.