Water pollution has become a growing threat to human society and natural ecosystem in recent decades, increasing the need to better understand the variabilities of pollutants within aquatic systems. This study presents the application of two chemometric techniques, namely, cluster analysis (CA) and principal component analysis (PCA). This is to classify and identify the water quality variables into groups of similarities or dissimilarities and to determine their significance. Six stations along Kinta River, Perak, were monitored for 30 physical and chemical parameters during the period of 1997-2006. Using CA, the 30 physical and chemical parameters were classified into 4 clusters; PCA was applied to the datasets and resulted in 10 varifactors with a total variance of 78.06%. The varifactors obtained indicated the significance of each of the variables to the pollution of Kinta River.
In recent decades, various conventional techniques have been formulated around the world to evaluate the overall water quality (WQ) at particular locations. In the present study, back propagation neural network (BPNN) and adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), and one multilinear regression (MLR) are considered for the prediction of water quality index (WQI) at three stations, namely Nizamuddin, Palla, and Udi (Chambal), across the Yamuna River, India. The nonlinear ensemble technique was proposed using the neural network ensemble (NNE) approach to improve the performance accuracy of the single models. The observed WQ parameters were provided by the Central Pollution Control Board (CPCB) including dissolved oxygen (DO), pH, biological oxygen demand (BOD), ammonia (NH3), temperature (T), and WQI. The performance of the models was evaluated by various statistical indices. The obtained results indicated the feasibility of the developed data intelligence models for predicting the WQI at the three stations with the superior modelling results of the NNE. The results also showed that the minimum values for root mean square (RMS) varied between 0.1213 and 0.4107, 0.003 and 0.0367, and 0.002 and 0.0272 for Nizamuddin, Palla, and Udi (Chambal), respectively. ANFIS-M3, BPNN-M4, and BPNN-M3 improved the performance with regard to an absolute error by 41%, 4%, and 3%, over other models for Nizamuddin, Palla, and Udi (Chambal) stations, respectively. The predictive comparison demonstrated that NNE proved to be effective and can therefore serve as a reliable prediction approach. The inferences of this paper would be of interest to policymakers in terms of WQ for establishing sustainable management strategies of water resources.
The mass mortality of cobia (Rachycentron canadum) within 2-3 days was reported by 3 private farms in Bukit Tambun, Pulau Pinang, in February and March 2007. Only cobia with body weights of 3-4 kg were affected. Most diseased cobia swam on the surface and displayed flashing behaviour. All samples were positive for viral nervous necrosis (VNN) with low to medium levels of infection. Infestations by leeches (Zeylanicobdella arugamensis), body monogeneans (Benedenia sp.) and copepods (Caligus sp.) were also found, but no pathogenic bacteria were isolated. All water quality parameters monitored were within optimal ranges for culturing cobia. The main causes of high mortality in cobia remain unclear during the study. However, we believe that the mass mortality of cobia could be probably due to VNN infection and that the rate of mortality will increase further when cobia are subjected to aquaculture-related stresses (e.g., limited space). Traditional cages with a size of 2 (length) × 2 (width) × 1 m (depth) should only be used for rearing cobia below 1 kg in weight given the species' natural behaviours. In addition, cobia fingerlings should be screened for VNN prior to stocking them in cages.
In this study, vegetative cell suspensions of two Bacillus subtilis strains, L10 and G1 in equal proportions, was administered at two different doses 10(5) (BM5) and 10(8) (BM8) CFU ml(-1) in the rearing water of shrimp (Litopenaeus vannamei) for eight weeks. Both probiotic groups showed a significant reduction of ammonia, nitrite and nitrate ions under in vitro and in vivo conditions. In comparison to untreated control group, final weight, weight gain, specific growth rate (SGR), food conversion ratio (FCR) and digestive enzymatic activity were significantly greater in the BM5 and BM8 groups. Significant differences for survival were recorded in the BM8 group as compared to the control. Eight weeks after the start of experiment, shrimp were challenged with Vibrio harveyi. Statistical analysis revealed significant differences in shrimp survival between probiotic and control groups. Cumulative mortality of the control group was 80%, whereas cumulative mortality of the shrimp that had been given probiotics was 36.7% with MB8 and 50% with MB5. Subsequently, real-time RT-PCR was employed to determine the mRNA levels of prophenoloxidase (proPO), peroxinectin (PE), lipopolysaccharide- and β-1,3-glucan- binding protein (LGBP) and serine protein (SP). The expression of all immune-related genes studied was only significantly up-regulated in the BM5 group compared to the BM8 and control groups. These results suggest that administration of B. subtilis strains in the rearing water confers beneficial effects for shrimp aquaculture, considering water quality, growth performance, digestive enzymatic activity, immune response and disease resistance.
Mangrove located near urban area is exposed to various industrial discharge including heavy metals. Mangrove soil is capable of accumulating and storing these heavy metals. Heavy metals are toxic and non-biodegradable, so their accumulations affect water quality, while bioaccumulation and bio-assimilation of heavy metals in mangrove organisms negatively impact the food chain. Bacteria-derived biosurfactants are compounds capable of removing heavy metals from soil and sediment. Furthermore, environmentally friendly properties, such as biodegradability and low toxicity, exhibited by biosurfactants make them a suitable replacement for chemical surfactants for remediation efforts. This study was conducted to investigate the lead- (Pb) and zinc- (Zn) removing capability of rhamnolipid (RL), a type of biosurfactant produced by marine bacterium, Pseudomonas aeruginosa UMTKB-5. Rhamnolipid solutions of three different concentrations (25 mg/L, 50 mg/L and 75 mg/L) were added to mangrove soil and incubated for 7 days. The removal of Pb from soils was up to 18.3% using 25 mg/L RL solution, while 50 mg/L RL solution removed 48.3%, and 75 mg/L RL solution removed 75.9% Pb over time. Meanwhile, zinc removal of 25 mg/L RL solution was up to 24.9%, while 50 mg/L removed 16.5%, and 75 mg/L RL removed 30.5% of Zn. The results showed that RL from P. aeruginosa UMTKB-5 could be a potential biomaterial to be used to remediate heavy metals in sediment.
The deltaic estuarine system of the Matang Mangrove Forest Reserve of Malaysia is a site where several human settlements and brackish water aquaculture have been established. Here, we evaluated the level of fecal indicator bacteria (FIB) and the presence of potentially pathogenic bacteria in the surface water and sediments. Higher levels of FIB were detected at downstream sampling sites from the fishing village, indicating it as a possible source of anthropogenic pollution to the estuary. Enterococci levels in the estuarine sediments were higher than in the surface water, while total coliforms and E. coli in the estuarine sediments were not detected in all samples. Also, various types of potentially pathogenic bacteria, including Klebsiella pneumoniae, Serratia marcescens and Enterobacter cloacae were isolated. The results indicate that the Matang estuarine system is contaminated with various types of potential human bacterial pathogens which might pose a health risk to the public.
Poor water quality is a serious problem in the world which threatens human health, ecosystems, and plant/animal life. Prediction of surface water quality is a main concern in water resource and environmental systems. In this research, the support vector machine and two methods of artificial neural networks (ANNs), namely feed forward back propagation (FFBP) and radial basis function (RBF), were used to predict the water quality index (WQI) in a free constructed wetland. Seventeen points of the wetland were monitored twice a month over a period of 14 months, and an extensive dataset was collected for 11 water quality variables. A detailed comparison of the overall performance showed that prediction of the support vector machine (SVM) model with coefficient of correlation (R(2)) = 0.9984 and mean absolute error (MAE) = 0.0052 was either better or comparable with neural networks. This research highlights that the SVM and FFBP can be successfully employed for the prediction of water quality in a free surface constructed wetland environment. These methods simplify the calculation of the WQI and reduce substantial efforts and time by optimizing the computations.
In this paper, stormwater runoff from a residential catchment located in Miri, Sarawak, was characterized to determine the pollutant concentrations and loading. The observed average event mean concentrations were 116 mg/L for TSS, 115 mg/L for COD, 1.5 mg/L for NH3-N, and 0.23 mg/L for Pb. Based on Interim National Water Quality Standards (INWQS) for Malaysia, the average event mean concentration, EMC value for TSS exceeded class II (50 mg/L), exceeded class V (>100 mg/L) for COD, and exceeded class III (0.9 mg/L) for NH3-N. All four water quality parameters exhibited first flush characteristic but to varying magnitude which was influenced by the storm characteristics.
Background: The public health issue of consuming groundwater is a major concern because people often extract groundwater directly from the aquifers either through wells or boreholes without treating it with any form of filtration system or chlorine disinfection. Based on the Malaysian National Drinking Water guidelines the current study was designed to provide a better understanding on the variable factors that are influencing the quality of well-water in an urbanised village in Malaysia. Well water quality assessment of heavy metals, chemicals, microbial and physical parameters were carried out for Sungai Buloh Village in the Klang Valley to ensure it was safe for human consumption.
Materials and Methods: Water samples were collected from wells at four sites (Sites A,B,C,D), a river and a tap inside a house in Sungai Buloh village. Soil was sampled from the riverbed and area surrounding the wells. Samples were collected every two months over a one year duration from all sites. The water samples were processed and examined for viruses, coliforms and protozoa as well as for heavy metal contaminants.
Results: The turbidity and colour ranged in the average of 0.57-0.13 Nephelometric Turbidity (NTU) and 4.16-5.00 Total Conjunctive Use (TCU) respectively for all sites except Site C. At Site C the turbidity level was 2.56 ± 1.38 NTU. The well-water was polluted with coliforms (1.2 to 2.4 x 103 CFU/100 ml) in all sites, E. coli (0.12 - 4 x 102 CFU/100 ml CFU/ 100 ml) and Cryptosporidium oocysts (0.4 cysts/100 ml). All the heavy metals and chemical parameters were within the Malaysian Guidelines’ limits except manganese. The average pH ranged from 5.44 - 6.62 and the temperature was 28 ºC.
Conclusion: In summary, the well water at Sungai Buloh is considered unsafe for consumption due to pollution. Therefore the major thrust will be to provide better quality of drinking water to the residents of the village.
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.
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.
Global concerns have been observed due to the outbreak and lockdown causal-based COVID-19, and hence, a global pandemic was announced by the World Health Organization (WHO) in January 2020. The Movement Control Order (MCO) in Malaysia acts to moderate the spread of COVID-19 through the enacted measures. Furthermore, massive industrial, agricultural activities and human encroachment were significantly reduced following the MCO guidelines. In this study, first, a reconnaissance survey was carried out on the effects of MCO on the health conditions of two urban rivers (i.e., Rivers of Klang and Penang) in Malaysia. Secondly, the effect of MCO lockdown on the water quality index (WQI) of a lake (Putrajaya Lake) in Malaysia is considered in this study. Finally, four machine learning algorithms have been investigated to predict WQI and the class in Putrajaya Lake. The main observations based on the analysis showed that noticeable enhancements of varying degrees in the WQI had occurred in the two investigated rivers. With regard to Putrajaya Lake, there is a significant increase in the WQI Class I, from 24% in February 2020 to 94% during the MCO month of March 2020. For WQI prediction, Multi-layer Perceptron (MLP) outperformed other models in predicting the changes in the index with a high level of accuracy. For sensitivity analysis results, it is shown that NH3-N and COD play vital rule and contributing significantly to predicting the class of WQI, followed by BOD, while the remaining three parameters (i.e. pH, DO, and TSS) exhibit a low level of importance.
We discuss the accuracy and performance of the adaptive neuro-fuzzy inference system (ANFIS) in training and prediction of dissolved oxygen (DO) concentrations. The model was used to analyze historical data generated through continuous monitoring of water quality parameters at several stations on the Johor River to predict DO concentrations. Four water quality parameters were selected for ANFIS modeling, including temperature, pH, nitrate (NO3) concentration, and ammoniacal nitrogen concentration (NH3-NL). Sensitivity analysis was performed to evaluate the effects of the input parameters. The inputs with the greatest effect were those related to oxygen content (NO3) or oxygen demand (NH3-NL). Temperature was the parameter with the least effect, whereas pH provided the lowest contribution to the proposed model. To evaluate the performance of the model, three statistical indices were used: the coefficient of determination (R (2)), the mean absolute prediction error, and the correlation coefficient. The performance of the ANFIS model was compared with an artificial neural network model. The ANFIS model was capable of providing greater accuracy, particularly in the case of extreme events.
Water constitutes a major environmental and public health concerns worldwide. A large proportion of global water consumption is sourced from surface water. The dependency level on surface water is higher in developing countries, especially in rural-to-semi-urban areas, where subsurface water is not accessible. Presented in this paper is a spatiotemporal and hydrochemical quality assessment of the spring-originated Landzun Stream in Bida, Nigeria; which is usually consumed in its untreated state. Water samples were systematically collected in eighteen locations along the stream channel in both rainy and dry seasons at an equidistance interval of 500m. On-site and laboratory measurement of important physical and hydrochemical parameters were carried out using standard procedures. Water temperature in the rainy season (34-37 °C) slightly exceeds measured values in the dry season (29-33 °C). 72.22% (rainy) and 83.33% (dry) of collected samples did not meet the odourless requirement for drinking water. Similarly, estimated percentages of 66.67 and 94.44 of collected samples in rainy and dry seasons respectively have a taste. Contrary to data in the rainy season, 89%, 11%, 67% and 56% of the dry season's samples were enriched in magnesium (Mg), lead (Pb), potassium (K) and iron (Fe) respectively above the 2018 World Health Organisation guidelines for drinking water. This study further established that seasonal variation plays a major role in altering the aesthetic surface water quality. The intake of untreated surface water is a vehicle for potential water-borne diseases and allergies, hence alternative sources of drinking water for the populace dependent on the Landzun Stream is recommended to reduce risks and possible dangers of consuming the stream water.
Longitudinal water quality trends were assessed in the Tengi River system, Selangor, Malaysia, as the water moved from a peat swamp forest, through different agricultural land uses and finally through a town and then to the Straits of Malacca. Water draining from the peat swamp forest was dark in color due to its organic content and low in dissolved oxygen, pH, E. coli, calcium, nitrate and ammonia. The normal diurnal pattern for water temperature was observed for the peat swamp forest drainage, but there was no clear diurnal pattern evident in the dissolved oxygen data. The E. coli levels increased monotonically from the peat swamp forest waters (0 colonies/100 mL) through the agricultural areas (100-2000 colonies/100 mL) and town (7100 colonies/100 mL) and similarly pH increased along the same continuum. Dissolved oxygen increased from the peat swamp forest through the agricultural areas, but was lower in the town-impacted reach of the Tengi River.
Water from the dental unit waterlines (DUWLs) is known to contaminate with microbial from the biofilm that formed in the tubing system. The water quality from DUWLs is important to patients and dental health care professionals as they could be infected either directly from the contaminated water or aerosol that is generated during dental procedures. Suppliers claimed that dental units supplied to the hospital can only use a specific disinfectant which is uneconomic compared with the others. The aims of this study were to evaluate and compare the efficacy of different disinfectant on the water quality of DUWLs. Four disinfectants (Calbenium, A-dec ICX tablet, Dentel 5, Metassys) and distil water were evaluated. 350 mL water sample was collected separately, from the outlet of high-speed handpiece, scaler, 3-ways syringe and cup filler into a sterile thiosulfate bag on the 1st, 2nd, 4th, 8th, 12th and 24th weeks of the study. The samples were tested on the following day for total viable count (TVC). There is significant difference in the efficacies of the different disinfectants. Only one disinfectant consistently produces water quality within the recommended level of American Dental Association (ADA). Within the limitation of this study, it was found that there is alternative disinfectant that can reduce the TVC to the level recommended by ADA. However, the water qualities produced with these disinfectants were not consistent although they did not cause any technical problem to the dental units during the period of study.
By convention, dissolved trace elements in the river water are considered to be the fraction that passes through a 0.45 μm filter. However, several researchers have considered filtration cut-off other than 0.45 μm for the separation of dissolved trace elements from particulate fraction. Recent research indicated that trace elements could exist in particulate form as colloids and natural nanoparticles. Moreover, the trace elements in the continental dust (aerosols) constitute a significant component in their geochemical cycling. Due to their high mobility, the trace elements in the micron and sub-micron scale have biogeochemical significance in the coastal zone. In this context, this study focuses on the highly mobile fraction of trace elements in particulates (<11 μm) and dissolved form in the Lower Baram River. A factor model utilizing trace elements in the dissolved and mobile phase in the particulates (<11 μm) along with water column characteristics and the partition coefficient (Kd) of the trace elements indicated a more significant role for manganese oxyhydroxides in trace element transport. Perhaps, iron oxyhydroxides play a secondary role. The factor model further illustrated the dissolution of aluminium and authigenic clay formation. Except for Fe and Al, the contamination risk of mobile trace elements in particulates (<11 μm) together with dissolved form are within the permissible limits of the Malaysian water quality standards during monsoon (MON) and postmonsoon (POM) seasons.
Microbes in groundwater play a key role in determining the drinking water quality of the water. The study aims to interpret the sources of microbes in groundwater and its relationship to geochemistry. The study was carried out by collecting groundwater samples and analyzed to obtain various cations and anions, where HCO3-, Cl- and NO3- found to be higher than permissible limits in few samples. Microbial analysis, like total coliform (TC), total viable counts (TVC), fecal coliforms (FC), Vibrio cholera (V. cholerae) and total Streptococci (T. streptococci) were analyzed, and the observations reveal that most of the samples were found to be above the permissible limits adopted by EU, BIS, WHO and USEPA standards. Correlation analysis shows good correlation between Mg2+-HCO3-, K+-NO3-, TVC- V. cholerae and T. streptococci-FC. Major ions like Mg+, K+, NO3, Ca2+ and PO4 along with TS and FC were identified to control the geochemical and microbial activities in the region. The magnesium hardness in the groundwater is inferred to influence the TVC and V. cholerae. The mixing of effluents from different sources reflected the association of Cl with TC. Population of microbes T. streptococci and FC was mainly associated with Ca and Cl content in groundwater, depicting the role of electron acceptors and donors. The sources of the microbial population were observed with respect to the land use pattern and the spatial distribution of hydrogeochemical factors in the region. The study inferred that highest microbial activity in the observed in the residential areas, cultivated regions and around the landfill sites due to the leaching of sewage water and fertilizers runoff into groundwater. The concentrations of ions and microbes were found to be above the permissible limits of drinking water quality standards. This may lead to the deterioration in the health of particular coastal region.
Deterioration of water quality mainly due to high total ammonia nitrogen (TAN) and nitrite will affect the productivity of shrimp culture. In this study, three indigenous strains assigned as VCM5, VCM8 and VCM12 were evaluated for their ability to degrade TAN and nitrite. These strains were inoculated into shrimp aquaculture wastewater to enhance the degradation of TAN and nitrite. All the strains reduced TAN and nitrite level from the shrimp aquaculture wastewater significantly (p<0.05). Strain VCM5 (GenBank accession number KJ700465) and VCM8 (GenBank accession number KJ700464) showed 99.71% sequence similarity with the 16S rRNA gene type species Bacillus vietnamensis 15-1T (ABO99708) and strain VCM12 (GenBank accession number KJ700463) showed 99.05% sequence similarity with 16S rRNA gene sequence type species Gordonia bronchialis DSM43247T (CP001802).
Recent increase in awareness of the extent of microplastic contamination in marine and freshwater systems has heightened concerns over the ecological and human health risks of this ubiquitous material. Assessing risks posed by microplastic in freshwater systems requires sampling to establish contamination levels, but standard sampling protocols have yet to be established. An important question is whether sampling and assessment should focus on microplastic concentrations in the water or the amount deposited on the bed. On three dates, five replicated water and bed sediment samples were collected from each of the eight sites along the upper reach of the Semenyih River, Malaysia. Microplastics were found in all 160 samples, with mean concentrations of 3.12 ± 2.49 particles/L in river water and 6027.39 ± 16,585.87 particles/m2 deposited on the surface of riverbed sediments. Fibres were the dominant type of microplastic in all samples, but fragments made up a greater proportion of the material on the bed than in the water. Within-site variability in microplastic abundance was high for both water and bed sediments, and very often greater than between-site variability. Patterns suggest that microplastic accumulation on the bed is spatially variable, and single samples are therefore inadequate for assessing bed contamination levels at a site. Sites with the highest mean concentrations in samples of water were not those with the highest concentrations on the bed, indicating that monitoring based only on water samples may not provide a good picture of either relative or absolute bed contamination levels, nor the risks posed to benthic organisms.