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.
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.
In a case study involving preliminary investigations for the feasibility of a beach resort complex in the west coast of Sarawak, Malaysia, since the acceptable quality of recreational water quality had not been specified, existing international standards and practices were reviewed to arrive at acceptable microbiological and physicochemical parametric levels. Water samples were collected on a weekly basis in the proposed beach complex at Tanjong Batu Coastal Reserve and also along the nearby Sungei Batang Kemena and its estuary. It was ascertained that the swimming water quality was acceptable in terms of faecal Coliforms, temperature, pH and dissolved oxygen. However E. Coli counts did indicate a potential risk of 1.68% for gastrointestinal illness and the ubiquitous presence of faecal Streptococci pointed to recent pollution of human or animal origin. Besides, grease and oil contents exceeded the WHO Guideline values. It was hence recommended that an appropriate sanitation or pollution survey should be carried out in the adjacent coastal catchment area and the beach. Also routine water sampling should be undertaken. Such action will help to pinpoint sources of pollution and lead to antipollution measures, thus helping to upgrade swimming water quality and establish swimming water quality standards.
A new commercial cationic polyelectrolyte chitosan (CM), obtained from the waste of mushroom production, was examined using models of water and wastewater namely kaolin and palm oil mill effluent (pome). As it is biocompatible, widely available, and economically feasible, chitosan mushroom has high potential to be a suitable replacement for alum. Also, it can be a promising alternative to chitosan obtained traditionally from Crustaceans due to its higher zeta potential and homogeneity based on the raw material required for its production. A wide range of coagulant dose (5-60 mg l(-1)) and wastewater pH (2-12) were taken into account to find the optimal conditions of coagulation. The optimal doses are 10 and 20 mg l(-1) at best pH (11 and 3) when treated with kaolin and palm oil mill effluent, respectively, while 1200 mg l(-1) of alum was not enough to reach the efficiency of chitosan mushroom. On the other hand, the optimum dose of chitosan mushroom (20 mg l(-1)) at pH 3 of pome produced (75, 73, and 98%) removal of chemical oxygen demand (COD), biological oxygen demand (BOD), and total suspended solids (TSS), respectively. The significant potential of chitosan mushroom was proved by zeta potential measurement. Indeed, it possesses the highest zeta potential (+70 mV) as compared to the traditional chitosan produced from crustaceans. In short, chitosan mushroom as a biocoagulant is eco-friendly and it enhances water quality that meets the requirements of environmental conservatives.
A computer-aided multivariate water quality index is developed based on partial least squares (PLS) regression. The index is termed as the partial least squares water quality index (PLS-WQI). Briefly, a training set was computationally generated based on the guideline of National Water Quality Standards for Malaysia (NWQS) to predict the water quality. The index is benchmarked with the well-established index developed by the Department of Environment, Malaysia (DOE-WQI). The PLS-WQI is a continuous variable with the value closer to I indicating good water quality and closer to V indicating poor water quality. Unlike other conventional indexing methods, the algorithm calculates the index in a multivariate manner. The algorithm allows rapid processing of a large dataset without tedious calculation; it can be an efficient tool for spatial and temporal routine monitoring of water quality. Although the algorithm is designed based on the guideline of NWQS, it can be easily adapted to accommodate other guidelines. The algorithm was evaluated and demonstrated on the simulated and real datasets. Results indicate that the algorithm is robust and reliable. Based on six parameters, the overall ratings derived are inversely correlated to DOE-WQI. When the number of parameter is increased, the overall ratings appear to provide better insights into the water quality.
The Malaysian Department of Environment-Water Quality Index (DOE-WQI) was determined for the Terengganu River basin which is located at the coastal water of the southern South China Sea between July and October 2008. Monthly samplings were carried out at ten sampling stations within the basin. Six parameters listed in DOE-WQI were measured based on standard methods: pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS) and ammonical nitrogen (AN). The results indicated the impact of various anthropogenic activities which contribute to high values of BOD, COD, TSS and AN at middle and downstream stations, as compared with the upstream of the basin. The reverses were true for the pH and DO values. The DOE-WQI ranged from 71.5-94.6% (mean 86.9%), which corresponded to a classification status range from slightly polluted to clean. With respect to the Malaysia National Water Quality Standards (NWQS), the level of most of the parameters measured remained at Class I which is suitable for the sustainable conservation of the natural environment, for water supply without treatment and as well as for very sensitive aquatic species. It is suggested that monitoring should be carried out continuously for proper management of this river basin.
This study's main goal is to evaluate how the research will look at the impact of geothermal energy production on the quality of the subterranean in the 27 European nations from 1990 to 2021. A considerable decline in the subterranean water supply can occur in EU14 emerging nations employing geothermal energy growth compared to EU13 emerging economies, according to research that uses the autoregressive distributed lag (ARDL). Fossil fuel use, population growth, and economic expansion are some factors that have a more detrimental effect on the subterranean water supply in EU14 emerging economies than in EU13 emerging nations. In contrast, the study's findings indicate that EU13 emerging nations may be better able to enhance their underground water supply than EU14 emerging economies because of more effective institutional qualities. The findings so indicate that increasing the amount of geothermal energy generation among the 27 European Union countries can accelerate subsurface water degradation at a high capacity and help achieve unionism's 2030 energy-related goals. When this is achieved, climate change will be put to check, as pollution of the environment. All calculations projected were seen to be of a good level of validity, and this is ascertained through three estimators considered in this study.
The distribution of benthic Foraminifera throughout the coastal waters of Taman Negara Pulau Pinang (Penang National Park), Malaysia was studied to assess the impact of various anthropogenic activities, such as fishing, ecotourism and floating cage culture. Samples were obtained at 200 m intervals within the subtidal zone, extending up to 1200 m offshore at Teluk Bahang, Teluk Aling, Teluk Ketapang and Pantai Acheh. The depth within coastal waters ranged between 1.5 m and 10.0 m, with predominantly muddy substrate at most stations. Water quality analysis showed little variation in micronutrient (nitrite, NO2; nitrate, NO3; ammonia, NH4 and orthophosphate, PO4) concentrations between sampling stations. Temperature (29.6±0.48°C), salinity (29.4±0.28 ppt), dissolved oxygen content (5.4±0.95 mg/l) and pH (8.5± 0.13) also showed little fluctuation between stations. A total of nine genera of foraminifera were identified in the study (i.e., Ammonia, Elphidium, Ammobaculites, Bigenerina, Quinqueloculina, Reopax, Globigerina, Textularia and Nonion). The distribution of benthic foraminifera was dominated by opportunistic groups that have a high tolerance to anthropogenic stressors. Ammonia had the highest frequency of occurrence (84.7%), followed by Bigenerina (50%), Ammobaculites (44.2%) and Elphidium (38.9%). The Ammonia-Elphidium Index (AEI) was used to describe the hypoxic condition of benthic communities at all sites. Teluk Bahang had the highest AEI value. The foraminiferal assemblages and distribution in Teluk Bahang, Teluk Aling, Teluk Ketapang and Pantai Acheh showed no correlation with physical or chemical environmental parameters.
Heavy metal accumulation and depuration may alter the effectiveness of Meretrix meretrix as a biomonitoring organism for water quality assessment. Therefore, this study was conducted to evaluate the effects of heavy metal accumulation and depuration on M. meretrix, by immersing it in Copper (Cu), Zinc (Zn), and Lead (Pb)
solutions under laboratory conditions. The results showed that M. meretrix is able to accumulate Cu, Zn, and Pb at the rate of 0.99, 21.80, and 0.57 μg/g per day, respectively, and depurates at the rate of 0.42, 23.55, and 1.01 μg/g per day, respectively. These results indicate that M. meretrix could be effectively used as a biomonitoring organism for Cu because the accumulation rate is significantly (p ≤ 0.05) higher than the depuration rate. However, this was not the case for Zn because the accumulation rate was almost similar to the depuration rate, while for Pb, accumulation or depuration did not occur in M. meretrix.
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.
Nowadays, water pollution has become a global issue affecting most countries in the world. Water quality should be monitored to alert authorities on water pollution, so that action can be taken quickly. The objective of the review is to study various conventional and modern methods of monitoring water quality to identify the strengths and weaknesses of the methods. The methods include the Internet of Things (IoT), virtual sensing, cyber-physical system (CPS), and optical techniques. In this review, water quality monitoring systems and process control in several countries, such as New Zealand, China, Serbia, Bangladesh, Malaysia, and India, are discussed. Conventional and modern methods are compared in terms of parameters, complexity, and reliability. Recent methods of water quality monitoring techniques are also reviewed to study any loopholes in modern methods. We found that CPS is suitable for monitoring water quality due to a good combination of physical and computational algorithms. Its embedded sensors, processors, and actuators can be designed to detect and interact with environments. We believe that conventional methods are costly and complex, whereas modern methods are also expensive but simpler with real-time detection. Traditional approaches are more time-consuming and expensive due to the high maintenance of laboratory facilities, involve chemical materials, and are inefficient for on-site monitoring applications. Apart from that, previous monitoring methods have issues in achieving a reliable measurement of water quality parameters in real time. There are still limitations in instruments for detecting pollutants and producing valuable information on water quality. Thus, the review is important in order to compare previous methods and to improve current water quality assessments in terms of reliability and cost-effectiveness.
As an inland dryland lake basin, the rivers and lakes within the Lake Bosten basin provide scarce but valuable water resources for a fragile environment and play a vital role in the development and sustainability of the local societies. Based on the Google Earth Engine (GEE) platform, combined with the geographic information system (GIS) and remote sensing (RS) technology, we used the index WI2019 to extract and analyze the water body area changes of the Bosten Lake basin from 2000 to 2021 when the threshold value is -0.25 and the slope mask is 8°. The driving factors of water body area changes were also analyzed using the partial least squares-structural equation model (PLS-SEM). The result shows that in the last 20 years, the area of water bodies in the Bosten Lake basin generally fluctuated during the dry, wet, and permanent seasons, with a decreasing trend from 2000 to 2015 and an increasing trend between 2015 and 2019 followed by a steadily decreasing trend afterward. The main driver of the change in wet season water bodies in the Bosten Lake basin is the climatic factors, with anthropogenic factors having a greater influence on the water body area of dry season and permanent season than that of wet season. Our study achieved an accurate and convenient extraction of water body area and drivers, providing up-to-date information to fully understand the spatial and temporal variation of surface water body area and its drivers in the basin, which can be used to effectively manage water resources.
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 Ephemeroptera, Plecoptera and Trichoptera (EPT) community structure and the specific sensitivity of certain EPT genera were found to be influenced by water parameters in the rivers of Gunung Jerai Forest Reserve (GJFR) in the north of peninsular Malaysia. The scores of EPT taxa richness of >10 in all rivers indicated all rivers' habitats were non-impacted, having good water quality coinciding with Class I and Class II of Malaysian water quality index (WQI) classification of potable water. The abundance of EPT was very high in Teroi River (9,661 individuals) but diversity was lower (22 genera) than Tupah River which was highly diverse (28 genera) but lower in abundance (4,263 individuals). The lowest abundance and moderate diversity was recorded from Batu Hampar River (25 genera). Baetis spp. and Thalerosphyrus spp., Neoperla spp. and Cheumatopsyche spp. were the most common genera found. Classification for all rivers using EPT taxa Richness Index and WQI gave different category of water quality, respectively. The WQI classified Tupah and Batu Hampar rivers into Class II and Teroi River (Class I) was two classes above the classification of the EPT taxa Richness Index.
Rivers in Malaysia are classified based on water quality index (WQI) that comprises of six parameters, namely, ammoniacal nitrogen (AN), biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), pH, and suspended solids (SS). Due to its tropical climate, the impact of seasonal monsoons on river quality is significant, with the increased occurrence of extreme precipitation events; however, there has been little discussion on the application of artificial intelligence models for monsoonal river classification. In light of these, this study had applied artificial neural network (ANN) and support vector machine (SVM) models for monsoonal (dry and wet seasons) river classification using three of the water quality parameters to minimise the cost of river monitoring and associated errors in WQI computation. A structured trial-and-error approach was applied on input parameter selection and hyperparameter optimisation for both models. Accuracy, sensitivity, and precision were selected as the performance criteria. For dry season, BOD-DO-pH was selected as the optimum input combination by both ANN and SVM models, with testing accuracy of 88.7% and 82.1%, respectively. As for wet season, the optimum input combinations of ANN and SVM models were BOD-pH-SS and BOD-DO-pH with testing accuracy of 89.5% and 88.0%, respectively. As a result, both optimised ANN and SVM models have proven their prediction capacities for river classification, which may be deployed as effective and reliable tools in tropical regions. Notably, better learning and higher capacity of the ANN model for dataset characteristics extraction generated better predictability and generalisability than SVM model under imbalanced dataset.
Biodiversity of aquatic insect and physicochemical water quality parameters in Mae Tao and Mae Ku watersheds were
assessed bi-monthly from February 2011 to February 2012. A total of 59 families representing 9 orders were recorded.
At order level, Trichoptera was found at the highest frequency in total abundance (45.75%) followed by Ephemeroptera
(18.06%), Hemiptera (13.45%), Odonata (9.62%), Diptera (8.17%), Coleoptera (4.6%), Megaloptera (0.17%),
Lepidoptera (0.11%) and Plecoptera (0.07%). The family Hydropsychidae was the most prominent and the most abundant
aquatic insect taxa followed by Chironomidae. Water temperature, dissolved oxygen and ammonia-nitrogen were similar
at all sampling stations. Significant variations in pH, electrical conductivity, total dissolved solids, sulfate, nitrate-nitrogen
and alkalinity were found at all sampling stations. Taxa richness and diversity index significantly correlated with dissolved
oxygen, sulfate, nitrate-nitrogen and ammonia-nitrogen (p<0.05, p<0.01). Physicochemical data and biological data
showed that mostly the surface water quality in Mae Tao and Mae Ku watersheds were within Type III of The Surface
Water Standard for Agriculture and Water Quality for Protection of Aquatic Resources in Thailand.
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.
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.
Saltwater intrusion in the coastal areas of Bangladesh is a prevalent phenomenon. However, it is not conducive to activities such as irrigation, navigation, fish spawning and shelter, and industrial usage. The present study analyzed 45 water samples collected from 15 locations in coastal areas during three seasons: monsoon, pre-monsoon, and post-monsoon. The aim was to comprehend the seasonal variation in physicochemical parameters, including water temperature, pH, electrical conductivity (EC), salinity, total dissolved solids (TDS), hardness, and concentrations of Na+, K+, Mg2+, Ca2+, Fe2+, HCO3-, PO43-, SO42-, and Cl-. Additionally, parameters essential for agriculture, such as soluble sodium percentage (SSP), sodium absorption ratio (SAR), magnesium absorption ratio (MAR), residual sodium carbonate (RSC), Kelly's ratio (KR), and permeability index (PI), were examined. Their respective values were found to be 63%, 16.83 mg/L, 34.92 mg/L, 145.44 mg/L, 1.28 mg/L, and 89.29%. The integrated water quality index was determined using entropy theory and principal component analysis (PCA). The resulting entropy water quality index (EWQI) and SAR of 49.56% and 63%, respectively, indicated that the samples are suitable for drinking but unsuitable for irrigation. These findings can assist policymakers in implementing the Bangladesh Deltaplan-2100, focusing on sustainable land management, fish cultivation, agricultural production, environmental preservation, water resource management, and environmental protection in the deltaic areas of Bangladesh. This research contributes to a deeper understanding of seasonal variations in the hydrochemistry and water quality of coastal rivers, aiding in the comprehension of salinity intrusion origins, mechanisms, and causes.
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.