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.
The spatial distributions of Na, Mg, K, Ca, Cr, Fe, Ni, Cu, Zn, As, Se and Pb in Hemibagrus sp. from Selangor River and a reference site were determined with inductively coupled plasma-mass spectrometer, in comparison to the levels in their surrounding water body and sediments. The results demonstrated significant differences in elemental accumulation pattern in different fish tissues originated from both sites. The variations observed were mainly subjected to their metabolic activities, and also the influence of the surrounding medium. In general, the liver tends to accumulate higher concentration of metals followed by the gills, and muscle tissues. The data also indicate associations between the concentrations of metal contaminants measured in the fish and the levels observed at the sites. The concentrations of hazardous metals As, Se and Pb in all the studied tissues reflect the influence of anthropogenic inputs. This suggests the potential utility of widely available Hemibagrus sp. as a valuable bioindicator of metal pollution in environmental monitoring and assessment.
Rapid socioeconomic development in the Linggi River Basin has contributed to the significant increase of pollution discharge into the Linggi River and its adjacent coastal areas. The toxic element contents and distributions in the sediment samples collected along the Linggi River were determined using neutron activation analysis (NAA) and inductively coupled plasma-mass spectrometry (ICP-MS) techniques. The measured mean concentration of As, Cd, Pb, Sb, U, Th and Zn is relatively higher compared to the continental crust value of the respective element. Most of the elements (As, Cr, Fe, Pb, Sb and Zn) exceeded the freshwater sediment quality guideline-threshold effect concentration (FSQG-TEC) value. Downstream stations of the Linggi River showed that As concentrations in sediment exceeded the freshwater sediment quality guideline-probable effect concentration (FSQG-PEC) value. This indicates that the concentration of As will give an adverse effect to the growth of sediment-dwelling organisms. Generally, the Linggi River sediment can be categorised as unpolluted to strongly polluted and unpolluted to strongly to extremely polluted. The correlation matrix of metal-metal relationship, principle component analysis (PCA) and cluster analysis (CA) indicates that the pollution sources of Cu, Ni, Zn, Cd and Pb in sediments of the Linggi River originated from the industry of electronics and electroplating. Elements of As, Cr, Sb and Fe mainly originated from motor-vehicle workshops and metal work, whilst U and Th originated from natural processes such as terrestrial runoff and land erosion.
This study focused on the influence of ultramafic terrains on soil and surface water environmental chemistry in Peninsular Malaysia and in the State of Sabah also in Malaysia. The sampling included 27 soils from four isolated outcrops at Cheroh, Bentong, Bukit Rokan, and Petasih from Peninsular Malaysia and sites near Ranau in Sabah. Water samples were also collected from rivers and subsurface waters interacting with the ultramafic bodies in these study sites. Physico-chemical parameters (including pH, EC, CEC) as well as the concentration of major and trace elements were measured in these soils and waters. Geochemical indices (geoaccumulation index, enrichment factor, and concentration factor) were calculated. Al2O3 and Fe2O3 had relatively high concentrations in the samples. A depletion in MgO, CaO, and Na2O was observed as a result of leaching in tropical climate, and in relation to weathering and pedogenesis processes. Chromium, Ni, and Co were enriched and confirmed by the significant values obtained for Igeo, EF, and CF, which correspond to the extreme levels of contamination for Cr and high to moderate levels of contamination for Ni and Co. The concentrations of Cr, Ni, and Co in surface waters did not reflect the local geochemistry and were within the permissible ranges according to WHO and INWQS standards. Subsurface waters were strongly enriched by these elements and exceeded these standards. The association between Cr and Ni was confirmed by factor analysis. The unexpected enrichment of Cu in an isolated component can be explained by localized mineralization in Sabah.
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.
Burkholderia pseudomallei causes melioidosis, a life-threatening infection in both humans and animals. Water is an important reservoir of the bacteria and may serve as a source of environmental contamination leading to infection. B. pseudomallei has an unusual ability to survive in water for a long period. This paper investigates physicochemical properties of water associated with the presence of B. pseudomallei in water supply in small ruminant farms in Peninsular Malaysia. Physicochemical properties of water samples taken from small ruminant farms that included temperature, pH, dissolved oxygen (DO2), optical density (OD), and chemical oxygen demand (COD) were measured after which the samples were cultured for B. pseudomallei. Multivariable logistic regression model revealed that slightly acidic water pH and higher COD level were significantly associated with the likelihood of the B. pseudomallei presence in the water.
The analysis of total organic carbon (TOC) by the American Public Health Association (APHA) closed-tube reflux colorimetric method requires potassium dichromate (K2Cr2O7), silver sulfate (AgSO4), and mercury (HgSO4) sulfate in addition to large volumes of both reagents and samples. The method relies on the release of oxygen from dichromate on heating which is consumed by carbon associated with organic compounds. The method risks environmental pollution by discharging large amounts of chromium (VI) and silver and mercury sulfates. The present method used potassium monochromate (K2CrO4) to generate the K2Cr2O7 on demand in the first phase. In addition, miniaturizing the procedure to semi microanalysis decreased the consumption of reagents and samples. In the second phase, mercury sulfate was eliminated as part of the digestion mixture through the introduction of sodium bismuthate (NaBiO3) for the removal of chlorides from the sample. The modified method, the potassium monochromate closed-tube colorimetry with sodium bismuthate chloride removal (KMCC-Bi), generates the potassium dichromate on demand and eliminates mercury sulfate. The semi microanalysis procedure leads to a 60% reduction in sample volume and ≈ 33.33 and 60% reduction in monochromate and silver sulfate consumption respectively. The LOD and LOQ were 10.17 and 33.90 mg L-1 for APHA, and 4.95 and 16.95 mg L-1 for KMCC-Bi. Recovery was between 83 to 98% APHA and 92 to 104% KMCC-Bi, while the RSD (%) ranged between 0.8 to 5.0% APHA and 0.00 to 0.62% KMCC-Bi. The method was applied for the UV-Vis spectrometry determination of COD in water and wastewater. Statistics was done by MINITAB 17 or MS Excel 2016. ᅟ Graphical abstract.
This study integrates the application of Dempster-Shafer-driven evidential belief function (DS-EBF) methodology with remote sensing and geographic information system techniques to analyze surface and subsurface data sets for the spatial prediction of groundwater potential in Perak Province, Malaysia. The study used additional data obtained from the records of the groundwater yield rate of approximately 28 bore well locations. The processed surface and subsurface data produced sets of groundwater potential conditioning factors (GPCFs) from which multiple surface hydrologic and subsurface hydrogeologic parameter thematic maps were generated. The bore well location inventories were partitioned randomly into a ratio of 70% (19 wells) for model training to 30% (9 wells) for model testing. Application results of the DS-EBF relationship model algorithms of the surface- and subsurface-based GPCF thematic maps and the bore well locations produced two groundwater potential prediction (GPP) maps based on surface hydrologic and subsurface hydrogeologic characteristics which established that more than 60% of the study area falling within the moderate-high groundwater potential zones and less than 35% falling within the low potential zones. The estimated uncertainty values within the range of 0 to 17% for the predicted potential zones were quantified using the uncertainty algorithm of the model. The validation results of the GPP maps using relative operating characteristic curve method yielded 80 and 68% success rates and 89 and 53% prediction rates for the subsurface hydrogeologic factor (SUHF)- and surface hydrologic factor (SHF)-based GPP maps, respectively. The study results revealed that the SUHF-based GPP map accurately delineated groundwater potential zones better than the SHF-based GPP map. However, significant information on the low degree of uncertainty of the predicted potential zones established the suitability of the two GPP maps for future development of groundwater resources in the area. The overall results proved the efficacy of the data mining model and the geospatial technology in groundwater potential mapping.
Water pollution is a global problem. During current study, ammonia, phosphate, phenol, and copper(II) were removed from aqueous solution by subsurface and surface flow constructed wetland. In current investigation, distilled water was polluted with four contaminants including ammonia, phosphate, copper (Cu), and phenol. Response surface methodology and central composite design were applied to optimize pollutant removal during treatment by subsurface flow constructed wetland (SSFCW). Contact time (12 to 80 h) and initial pollutant concentration (20 to 85 mg/L) were selected as independent factors; some upper and lower ranges were also monitored for accuracy. In SSFCW, water hyacinth transplanted in two substrate layers, namely zeolite and cockle shell. SSFCW removed 87.7, 81.4, 74.7, and 54.9% of ammonia, phosphate, Cu, and phenol, respectively, at optimum contact time (64.5 h) and initial pollutant concentration (69.2 mg/L). Aqueous solution was moved to a surface flow constructed wetland (SFCW) after treating via SSFCW at optimum conditions. In SFCW, Typha was transplanted to a fixed powdered substrate layer, including bentonite, zeolite, and cockle shell. SFCW could develop performance of this combined system and could improve elimination efficacy of the four contaminants to 99.99%. So this combined CW showed a good performance in removing pollutants. Graphical abstract Wetlands arrangement for treating aqueous solution in current study.
El Niño and Southern Oscillation (ENSO) is a natural forcing that affects global climate patterns, thereon influencing freshwater quality and security. In the advent of a strong El Niño warming event in 2016 which induced an extreme dry weather in Malaysia, water quality variation was investigated in Kampar River which supplies potable water to a population of 92,850. Sampling points were stratified into four ecohydrological units and 144 water samples were examined from October 2015 to March 2017. The Malaysian Water Quality Index (WQI) and some supplementary parameters were analysed in the context of reduced precipitation. Data shows that prolonged dry weather, episodic and sporadic pollution incidents have caused some anomalies in dissolved oxygen (DO), total suspended solids (TSS), turbidity and ammoniacal nitrogen (AN) values recorded and the possible factors are discussed. The month of March and August 2016 recorded the lowest precipitation, but the overall resultant WQI remained acceptable. Since the occurrence of a strong El Niño event is infrequent and far between in decadal time scale, this paper gives some rare insights that may be central to monitoring and managing freshwater resource that has a crucial impact to the mass population in the region of Southeast Asia.
Temporal variation of Synechococcus, its production (μ) and grazing loss (g) rates were studied for 2 years at nearshore stations, i.e. Port Dickson and Port Klang along the Straits of Malacca. Synechococcus abundance at Port Dickson (0.3-2.3 × 10(5) cell ml(-1)) was always higher than at Port Klang (0.3-7.1 × 10(4) cell ml(-1)) (p 0.25), but nutrient and light availability were important factors for their distribution. The relationship was modelled as log Synechococcus = 0.37Secchi - 0.01DIN + 4.52 where light availability (as Secchi disc depth) was a more important determinant. From a two-factorial experiment, nutrients were not significant for Synechococcus growth as in situ nutrient concentrations exceeded the threshold for saturated growth. However, light availability was important and elevated Synechococcus growth rates especially at Port Dickson (F = 5.94, p 0.30). In nearshore tropical waters, an estimated 69 % of Synechococcus production could be grazed.
Steroid estrogens, such as estrone (E1), 17β-estradiol (E2), estriol (E3), and 17α-ethinylestradiol (EE2), are natural and synthetic hormones released into the environment through incomplete sewage discharge. This review focuses on the sources of steroid estrogens in wastewater treatment plants (WWTPs). The mechanisms and fate of steroid estrogens throughout the entire wastewater treatment system are also discussed, and relevant information on regulatory aspects is given. Municipal, pharmaceutical industry, and hospitals are the main sources of steroid estrogens that enter WWTPs. A typical WWTP comprises primary, secondary, and tertiary treatment units. Sorption and biodegradation are the main mechanisms for removal of steroid estrogens from WWTPs. The fate of steroid estrogens in WWTPs depends on the types of wastewater treatment systems. Steroid estrogens in the primary treatment unit are removed by sorption onto primary sludge, followed by sorption onto micro-flocs and biodegradation by microbes in the secondary treatment unit. Tertiary treatment employs nitrification, chlorination, or UV disinfection to improve the quality of the secondary effluent. Activated sludge treatment systems for steroid estrogens exhibit a removal efficiency of up to 100%, which is higher than that of the trickling filter treatment system (up to 75%). Moreover, the removal efficiency of advance treatment systems exceeds 90%. Regulatory aspects related to steroid estrogens are established, especially in the European Union. Japan is the only Asian country that implements a screening program and is actively involved in endocrine disruptor testing and assessment. This review improves our understanding of steroid estrogens in WWTPs, proposes main areas to be improved, and provides current knowledge on steroid estrogens in WWTPs for sustainable development.
Malaysia is facing an increasing trend in industrial solid waste generation due to industrial development. Thus, there is a paramount need in taking practical actions and measurements to move toward sustainable industrial waste management. The main aim of this study is to assess practicing solid waste minimization by manufacturing firms. Analysis showed that majority of firms (92%) dispose of their wastes rather than utilize other sustainable waste management options. Also, waste minimization methods such as segregation of wastes, on-site recycle and reuse, improved housekeeping, and equipment modification were found to have significant contribution to waste reduction (p
Groundwater hazard assessments involve many activities dealing with the impacts of pollution on groundwater, such as human health studies and environment modelling. Nitrate contamination is considered a hazard to human health, environment and ecosystem. In groundwater management, the hazard should be assessed before any action can be taken, particularly for groundwater pollution and water quality. Thus, pollution due to the presence of nitrate poses considerable hazard to drinking water, and excessive nutrient loads deteriorate the ecosystem. The parametric IPNOA model is one of the well-known methods used for evaluating nitrate content. However, it cannot predict the effect of soil and land use/land cover (LULC) types on calculations relying on parametric well samples. Therefore, in this study, the parametric model was trained and integrated with the multivariate data-driven model with different levels of information to assess groundwater nitrate contamination in Saladin, Iraq. The IPNOA model was developed with 185 different well samples and contributing parameters. Then, the IPNOA model was integrated with the logistic regression (LR) model to predict the nitrate contamination levels. Geographic information system techniques were also used to assess the spatial prediction of nitrate contamination. High-resolution SPOT-5 satellite images with 5 m spatial resolution were processed by object-based image analysis and support vector machine algorithm to extract LULC. Mapping of potential areas of nitrate contamination was examined using receiver operating characteristic assessment. Results indicated that the optimised LR-IPNOA model was more accurate in determining and analysing the nitrate hazard concentration than the standalone IPNOA model. This method can be easily replicated in other areas that have similar climatic condition. Therefore, stakeholders in planning and environmental decision makers could benefit immensely from the proposed method of this research, which can be potentially used for a sustainable management of urban, industrialised and agricultural sectors.
Landfill leachate is one of the sources of surface water pollution in Selangor State (SS), Malaysia. Leachate volume prediction is essential for sustainable waste management and leachate treatment processes. The accurate estimation of leachate generation rates is often considered a challenge, especially in developing countries, due to the lack of reliable data and high measurement costs. Leachate generation is related to several variable factors, including meteorological data, waste generation rates, and landfill design conditions. Large variations in these factors lead to complicated leachate modeling processes. The aims of this study are to determine the key elements contributing to leachate production and then develop an adaptive neural fuzzy inference system (ANFIS) model to predict leachate generation rates. Accuracy of the final model performance was tested and evaluated using the root mean square error (RMSE), the mean absolute error (MAE), and the correlation coefficient (R). The study results defined dumped waste quantity, rainfall level, and emanated gases as the most significant contributing factors in leachate generation. The best model structure consisted of two triangular fuzzy membership functions and a hybrid training algorithm with eight fuzzy rules. The proposed ANFIS model showed a good performance with an overall correlation coefficient of 0.952.
This study investigates adsorption-desorption and the leaching potential of glyphosate and aminomethylphosphonic acid (AMPA) in control and amended-addition of cow dung or rice husk ash-acidic Malaysian soil with high oxide mineral content. The addition of cow dung or rice husk ash increased the adsorptive removal of AMPA. The isotherm data of glyphosate and AMPA best fitted the Freundlich model. The constant Kf for glyphosate was high in the control soil (544.873 mg g-1) followed by soil with cow dung (482.451 mg g-1) then soil with rice husk ash (418.539 mg g-1). However, for AMPA, soil with cow dung was high (166.636 mg g-1) followed by soil with rice husk ash (137.570 mg g-1) then the control soil (48.446 mg g-1). The 1/n values for both glyphosate and AMPA adsorptions were
The objective of this study was to identify the spatial and temporal variabilities of selected nutrients in the Setiu Wetlands Lagoon (SWL), Malaysia. Water samples were collected quarterly at ten monitoring sites. This study presents results from a 10-year field investigation (2003 to 2010 and 2014 to 2015) of water quality in the SWL. For the spatial pattern, four clusters were identified with hierarchical cluster analysis. Analysis of the temporal trend shows that the high total suspended solid loading in 2010 was due to large-scale land clearing upstream of the SWL. The enrichment of ammonium after 2010 could plausibly be due to land-based aquaculture diffuse discharges. In 2005-2007, expansion of oil palm plantations within the Setiu catchment had doubled the phosphorus concentration in the SWL. The natural and anthropogenic alterations of the lagoon inlets profoundly influenced the spatial distribution patterns of nutrients in the SWL. These results suggest that intense anthropogenic disturbances close to the SWL accounted for the water quality deterioration.
Managers of water quality and water monitoring programs are often faced with constraints in terms of budget, time, and laboratory capacity for sample analysis. In such situation, the ideal solution is to reduce the number of sampling sites and/or monitored variables. In this case, selecting appropriate monitoring sites is a challenge. To overcome this problem, this study was conducted to statistically assess and identify the appropriate sampling stations of monitoring network under the monitored parameters. To achieve this goal, two sets of water quality data acquired from two different monitoring networks were used. The hierarchical agglomerative cluster analysis (HACA) were used to group stations with similar characteristics in the networks, the time series analysis was then performed to observe the temporal variation of water quality within the station clusters, and the geo-statistical analysis associated Kendall's coefficient of concordance were finally applied to identify the most appropriate and least appropriate sampling stations. Based on the overall result, five stations were identified in the networks that contribute the most to the knowledge of water quality status of the entire river. In addition, five stations deemed less important were identified and could therefore be considered as redundant in the network. This result demonstrated that geo-statistical technique coupled with Kendall's coefficient of concordance can be a reliable method for water resource managers to identify appropriate sampling sites in a river monitoring network.
This study proposes a neural network (NN) model to predict and simulate the propagation of vehicular traffic noise in a dense residential area at the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia. The proposed model comprises of two main simulation steps: that is, the prediction of vehicular traffic noise using NN and the simulation of the propagation of traffic noise emission using a mathematical model. First, the NN model was developed with the following selected noise predictors: the number of motorbikes, the sum of vehicles, car ratio, heavy vehicle ratio (e.g. truck, lorry and bus), highway density and a light detection and ranging (LiDAR)-derived digital surface model (DSM). Subsequently, NN and its hyperparameters were optimised by a systematic optimisation procedure based on a grid search approach. The noise propagation model was then developed in a geographic information system (GIS) using five variables, namely road geometry, barriers, distance, interaction of air particles and weather parameters. The noise measurement was conducted continuously at 15-min intervals and the data were analysed by taking the minimum, maximum and average values recorded during the day. The measurement was performed four times a day (i.e. morning, afternoon, evening, and midnight) over two days of the week (i.e. Sunday and Monday). An optimal radial basis function NN was used with 17 hidden layers. The learning rate and momentum values were 0.05 and 0.9, respectively. Finally, the accuracy of the proposed method achieved 78.4% with less than 4.02 dB (A) error in noise prediction. Overall, the proposed models were found to be promising tools for traffic noise assessment in dense urban areas.
This study was conducted to determine the effects of rice husk ash (RHA) and Fe-coated rice husk ash (Fe-RHA) on the bioavailability and mobility of As, Cd, and Mn in mine tailings. The amendments were added to the tailings at 0, 5, 10, or 20% (w/w) and the mixtures were incubated for 0, 7, 15, 30, 45, and 60 days. The CaCl2 extractable As, Cd, and Mn in the amended tailings were determined at each interval of incubation period. In addition, the tailings mixture was leached with simulated rain water (SRW) every week from 0 day (D 0) until day 60 (D 60). The results showed that both RHA and Fe-RHA application significantly decreased the CaCl2-extractable Cd and Mn but increased that of As in the tailings throughout the incubation period. Consequently, addition of both RHA and Fe-RHA leached out higher amount of As from the tailings but decreased Cd and Mn concentration compared to the controls. The amount of As leached from the Fe-RHA-amended tailings was less than that from RHA-amended tailings. Application of both RHA and Fe-RHA could be an effective way in decreasing the availability of cationic heavy metals (Cd and Mn) in the tailings but these amendments could result in increasing the availability of anionic metalloid (As). Therefore, selection of organic amendments to remediate metal-contaminated tailings must be done with great care because the outcomes might be different among the elements.