In order to evaluate the water quality of one of the most polluted urban river in Malaysia, the Penchala River, performance of eight biotic indices, Biomonitoring Working Party (BMWP), BMWPThai, BMWPViet, Average Score Per Taxon (ASPT), ASPTThai, BMWPViet, Family Biotic Index (FBI), and Singapore Biotic Index (SingScore), was compared. The water quality categorization based on these biotic indices was then compared with the categorization of Malaysian Water Quality Index (WQI) derived from measurements of six water physicochemical parameters (pH, BOD, COD, NH3-N, DO, and TSS). The river was divided into four sections: upstream section (recreational area), middle stream 1 (residential area), middle stream 2 (commercial area), and downstream. Abundance and diversity of the macroinvertebrates were the highest in the upstream section (407 individual and H' = 1.56, respectively), followed by the middle stream 1 (356 individual and H' = 0.82). The least abundance was recorded in the downstream section (214 individual). Among all biotic indices, BMWP was the most reliable in evaluating the water quality of this urban river as their classifications were comparable to the WQI. BMWPs in this study have strong relationships with dissolved oxygen (DO) content. Our results demonstrated that the biotic indices were more sensitive towards organic pollution than the WQI. BMWP indices especially BMWPViet were the most reliable and could be adopted along with the WQI for assessment of water quality in urban rivers.
This study aimed to address the pressing issue of plastic pollution in aquatic ecosystems by assessing the prevalence and distribution of microplastics (MPs) in water and riverbank sediments of the Pekalongan River, a vital water source in Indonesia. From the present findings, MP concentrations in water ranged from 45.2 to 99.1 particles/L, while sediment concentrations ranged from 0.77 to 1.01 particles/g. This study revealed that fragment and film MPs constituted 30.1 % and 25.4 % of the total, respectively, with MPs measuring <1 mm and constituting 51.4 % of the total. Colored MPs, particularly blue and black MPs, accounted for 34 % of the total. The primary polymer components, as determined via Fourier transform infrared spectroscopy, were identified as polystyrene, polyester, and polyamide. In response to the escalating plastic waste crisis caused by single-use plastics, Pekalongan's local government implemented refuse segregation and recycling programs as part of its efforts to transition toward zero-waste practices.
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.
This study examined the concentration of heavy metals in 13 fish species. The results indicated that shellfish species (clams) have the highest metal concentrations, followed by demersal and pelagic fishes. The mean concentration of metals in clams are Zn 88.74 ± 11.98 µg/g, Cu 4.96 ± 1.06 µg/g, Pb 1.22 ± 0.19 µg/g, Cd 0.34 ± 0.04 µg/g dry wt. basis, whereas the same measure in fish tissues was 58.04 ± 18.51, 2.47 ± 1.21, 0.58 ± 0.27 and 0.17 ± 0.08 µg/g dry wt. basis. The concentrations of heavy metals in clams and fish tissues were still lower than the maximum allowable concentrations as suggested by the Malaysian Food Act (1983) and are considered safe for local human consumption.
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.
Polycyclic aromatic hydrocarbons (PAHs) and linear alkylbenzenes (LABs) were used as anthropogenic markers of organic chemical pollution of sediments in the Selangor River, Peninsular Malaysia. This study was conducted on sediment samples from the beginning of the estuary to the upstream river during dry and rainy seasons. The concentrations of ƩPAHs and ƩLABs ranged from 203 to 964 and from 23 to 113 ng g(-1) dry weight (dw), respectively. In particular, the Selangor River was found to have higher sedimentary levels of PAHs and LABs during the wet season than in the dry season, which was primarily associated with the intensity of domestic wastewater discharge and high amounts of urban runoff washing the pollutants from the surrounding area. The concentrations of the toxic contaminants were determined according to the Sediment Quality Guidelines (SQGs). The PAH levels in the Selangor River did not exceed the SQGs, for example, the effects range low (ERL) value, indicating that they cannot exert adverse biological effects.
The prolonged persistence of toxic arsenic (As) in environment is due to its non-biodegradable characteristic. Meanwhile, several studies have reported higher concentrations of As in Langat River. However, it is the first study in Langat River Basin, Malaysia, that As concentrations in drinking water supply chain were determined simultaneously to predict the health risks of As ingestion. Water samples collected in 2015 from the four stages of drinking water supply chain were analysed for As concentration by inductively coupled plasma mass spectrometry. Determined As concentrations along with the time series data (2004-2015) were significantly within the maximum limit 0.01 mg/L of drinking water quality standard set by World Health Organization. The predicted As concentration by auto-regression moving average was 3.45E-03 mg/L in 2020 at 95% level based on time series data including climatic control variables. Long-term As ingestion via household filtration water at Langat Basin showed no potential lifetime cancer risk (LCR) 9.7E-06 (t = 6.68; p = 3.37E-08) as well as non-carcinogenic hazard quotient (HQ) 4.8E-02 (t = 6.68; p = 3.37E-08) risk at 95% level. However, the changing landscape, ex-mining ponds and extensive use of pesticides for palm oil plantation at Langat Basin are considered as the major sources of increased As concentration in Langat River. Therefore, a two-layer water filtration system at Langat Basin should be introduced to accelerate the achievement of sustainable development goal of getting safe drinking water supply.
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.
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.
Beta-agonists and sulfonamides are widely used for treating both humans and livestock for bronchial and cardiac problems, infectious disease and even as growth promoters. There are concerns about their potential environmental impacts, such as producing drug resistance in bacteria. This study focused on their spatial distribution in surface water and the identification of pollution sources in the Langat River basin, which is one of the most urbanized watersheds in Malaysia. Fourteen beta-agonists and 12 sulfonamides were quantitatively analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). A geographic information system (GIS) was used to visualize catchment areas of the sampling points, and source profiling was conducted to identify the pollution sources based on a correlation between a daily pollutant load of the detected contaminant and an estimated density of human or livestock population in the catchment areas. As a result, 6 compounds (salbutamol, sulfadiazine, sulfapyridine, sulfamethazine, sulfadimethoxine and sulfamethoxazole) were widely detected in mid catchment areas towards estuary. The source profiling indicated that the pollution sources of salbutamol and sulfamethoxazole were from sewage, while sulfadiazine was from effluents of cattle, goat and sheep farms. Thus, this combination method of quantitative and spatial analysis clarified the spatial distribution of these drugs and assisted for identifying the pollution sources.
Polychlorinated biphenyls (PCBs) were monitored in surface water collected in the Selangor River basin, Malaysia, to identify the occurrence, distribution, and dechlorination process as well as to assess the potential adverse effects to the Malaysian population. Ten PCB homologs (i.e., mono-CBs to deca-CBs) were quantitated by using gas chromatography-mass spectrometry (GC/MS). The total concentration of PCBs in the 10 sampling sites ranged from limit of detection to 7.67 ng L(-1). The higher chlorinated biphenyls (tetra-CBs to deca-CBs) were almost not detected in most of the sampling sites, whereas lower chlorinated biphenyls (mono-CBs, di-CBs, and tri-CBs) dominated more than 90 % of the 10 homologs in all the sampling sites. Therefore, the PCB load was estimated to be negligible during the sampling period because PCBs have an extremely long half-life. The PCBs, particularly higher chlorinated biphenyls, could be thoroughly dechlorinated to mono-CBs to tri-CBs by microbial decomposition in sediment or could still be accumulated in the sediment. The lower chlorinated biphenyls, however, could be resuspended or desorbed from the sediment because they have faster desorption rates and higher solubility, compared to the higher chlorinated biphenyls. The health risk for the Malaysia population by PCB intake that was estimated from the local fish consumption (7.2 ng kg(-1) bw day(-1)) and tap water consumption (1.5 × 10(-3)-3.1 × 10(-3) ng kg(-1) bw day(-1)) based on the detected PCB levels in the surface water was considered to be minimal. The hazard quotient based on the tolerable daily intake (20 ng kg(-1) bw day(-1)) was estimated at 0.36.
Fourteen beta-agonists were quantitatively analyzed in cattle, chicken and swine liver specimens purchased at 14 wet markets in Selangor State, Malaysia, by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The health risks of ractopamine and clenbuterol residues in the Malaysian population were assessed based on quantitative data and meat consumption statistics in Malaysia. Wastewater samples collected at swine farms (n = 2) and cattle/cow farms (n = 2) in the Kuala Langat district were analyzed for the presence for the 14 compounds. Wastewater in chicken farms was not collected because there was negligible discharge during the breeding period. The environmental impacts caused by beta-agonists discharged from livestock farms were spatially assessed in the Langat River basin using a geographic information system (GIS). As a result, 10 compounds were detected in the liver specimens. Ractopamine, which is a permitted compound for swine in Malaysia, was frequently detected in swine livers; also, 9 other compounds that are prohibited compounds could be illegally abused among livestock farms. The health risks of ractopamine and clenbuterol were assessed to be minimal as their hazard quotients were no more than 7.82 × 10(-4) and 2.71 × 10(-3), respectively. Five beta-agonists were detected in the wastewater samples, and ractopamine in the swine farm resulted in the highest contamination (30.1 μg/L). The environmental impacts of the beta-agonists in the Langat River basin were generally concluded to be minimal, but the ractopamine contamination released from swine farms was localized in coastal areas near the estuary of the Langat River basin because most swine farms were located in that region.
Arsenic and 5 heavy metals (nickel, copper, zinc, cadmium and lead) were quantitated in surface water (n = 18) and soil/ore samples (n = 45) collected from 5 land uses (oil palm converted from forest, oil palm in peat swamp, bare land, quarry and forest) in the Selangor River basin by inductively coupled plasma mass spectrometry (ICP-MS). Geographic information system (GIS) was used as a spatial analytical tool to classify 4 land uses (forest, agriculture/peat, urban and bare land) from a satellite image taken by Landsat 8. Source profiling of the 6 elements was conducted to identify their occurrence, their distribution and the pollution source associated with the land use. The concentrations of arsenic, cadmium and lead were also analyzed in maternal blood (n = 99) and cord blood (n = 87) specimens from 136 pregnant women collected at the University of Malaya Medical Center for elucidating maternal exposure as well as maternal-to-fetal transfer. The source profiling identified that nickel and zinc were discharged from sewage and/or industrial effluents, and that lead was discharged from mining sites. Arsenic showed a site-specific pollution in tin-tungsten deposit areas, and the pollution source could be associated with arsenopyrite. The maternal blood levels of arsenic (0.82 ± 0.61 μg/dL), cadmium (0.15 ± 0.2 μg/dL) and lead (2.6 ± 2.1 μg/dL) were not significantly high compared to their acute toxicity levels, but could have attributable risks of chronic toxicity. Those in cord blood were significantly decreased in cadmium (0.06 ± 0.07 μg/dL) and lead (0.99 ± 1.2 μg/dL) but were equivalent in arsenic (0.82 ± 1.1 μg/dL) because of the different kinetics of maternal-to-fetal transfer.
A study was carried out to determine the level of rare earth elements (REEs) in water and sediment samples from ex-mining lakes and River in Kinta Valley, Perak, Malaysia. Surface water and sediments from an ex-mining lake and Kinta River water samples were analyzed for REEs by inductively coupled plasma mass spectrometry. The total concentration of REEs in the ex-mining lake water samples and sediments were found to be 3685 mg/l and 14159 mg/kg, respectively, while the total concentration of REEs in Kinta River water sample was found to be 1224 mg/l. REEs in mining lake water were found to be within 2.42 mg/l (Tb) to 46.50 mg/l (Ce), while for the Kinta River, it was 1.33 mg/l (Ho) to 29.95 mg/l (Ce). Sediment samples were also found with REEs from 9.81 mg/kg (Ho) to 765.84 mg/kg (Ce). Ce showed the highest average concentrations for mining lake (3.88 to 49.08 mg/l) and Kinta River (4.44 to 33.15 mg/l) water samples, while the concentration of La was the highest (11.59 to 771.61 mg/kg) in the mining lake sediment. Lu was shown to have the highest enrichment of REEs in ex-mining lake sediments (107.3). Multivariate statistical analyses such as factor analysis and principal component analysis indicated that REEs were associated and controlled by mixed origin, with similar contributions from anthropogenic and geogenic sources. The speciation study of REEs in ex-tin mining sediments using a modified five-stage sequential extraction procedure indicated that yttrium (Y), gadolinium (Gd), and lanthanum (La) were obtained at higher percentages from the adsorbed/exchanged/carbonate fraction. The average potential mobility of the REEs was arranged in a descending order: Yb > Gd > Y = Dy > Pr > Er > Tm > Eu > Nd > Tb > Sc > Lu > Ce > La, implying that under favorable conditions, these REEs could be released and subsequently pollute the environment.
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.
In this study, the microcrystalline cellulose/metal-organic framework 199 hybrid (MCC/MOF-199) was applied as sorbent for the dispersive micro-solid phase-extraction (D-μSPE) of chlorophenols. The D-μSPE method combined with high-performance liquid chromatography- ultraviolet detection (HPLC-UV) was employed to determine of four chlorophenols including 2-chlorophenol (2-CP), 4-chlorophenol (4-CP), 2,3-dichlorophenol (2,3-DCP), and 2,5-dichlorophenol (2,5-DCP) in aqueous. The main parameters of the D-μSPE process that influence the extraction (i.e. the amount of sorbent, elution condition, extraction time, and pH) were investigated and optimized. Based on the outputs, the presence of MCC on the surface of MOF-199 leads to improve the properties of MOF-199 and the MCC/MOF-199 has the highest sorption capacity, durability, and porosity in comparison with MCC and MOF-199. According to the validation study at the optimized conditions, the linearity for the analytes was achieved in the range from 0.1 to 200 ng mL-1 for 2-CP and 4-CP and 0.15 to 200 ng mL-1 for 2,3-DCP and 2,5-DCP with correlation coefficients between 0.9928 and 0.9965. The limits of detection calculated at S/N=3 were in the range of 0.03-0.05 ng mL-1. Besides, the relative standard deviations (RSDs) for three spiking levels (0.2, 10,100 ng mL-1) do not exceed 6.8% and extraction recoveries are between 81.0% and 88.3%. Finally, the D-μSPE-HPLC-UV method was successfully applied to the analysis of CPs in real water samples (mineral, river and wastewater samples) with good recoveries (95.8 to 99.5%) and satisfactory precisions (RSD < 6.8%).
Long-term (21-30 years) erosional responses of rainforest terrain in the Upper Segama catchment, Sabah, to selective logging are assessed at slope, small and large catchment scales. In the 0.44 km(2) Baru catchment, slope erosion measurements over 1990-2010 and sediment fingerprinting indicate that sediment sources 21 years after logging in 1989 are mainly road-linked, including fresh landslips and gullying of scars and toe deposits of 1994-1996 landslides. Analysis and modelling of 5-15 min stream-suspended sediment and discharge data demonstrate a reduction in storm-sediment response between 1996 and 2009, but not yet to pre-logging levels. An unmixing model using bed-sediment geochemical data indicates that 49 per cent of the 216 t km(-2) a(-1) 2009 sediment yield comes from 10 per cent of its area affected by road-linked landslides. Fallout (210)Pb and (137)Cs values from a lateral bench core indicate that sedimentation rates in the 721 km(2) Upper Segama catchment less than doubled with initially highly selective, low-slope logging in the 1980s, but rose 7-13 times when steep terrain was logged in 1992-1993 and 1999-2000. The need to keep steeplands under forest is emphasized if landsliding associated with current and predicted rises in extreme rainstorm magnitude-frequency is to be reduced in scale.
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.
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.
This paper describes the design of an artificial neural network (ANN) model to predict the water quality index (WQI) using land use areas as predictors. Ten-year records of land use statistics and water quality data for Kinta River (Malaysia) were employed in the modeling process. The most accurate WQI predictions were obtained with the network architecture 7-23-1; the back propagation training algorithm; and a learning rate of 0.02. The WQI forecasts of this model had significant (p < 0.01), positive, very high correlation (ρs = 0.882) with the measured WQI values. Sensitivity analysis revealed that the relative importance of the land use classes to WQI predictions followed the order: mining > rubber > forest > logging > urban areas > agriculture > oil palm. These findings show that the ANNs are highly reliable means of relating water quality to land use, thus integrating land use development with river water quality management.