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.
The study was to determine the concentration of aluminium (Al) and study the physicochemical parameters (pH, total dissolved solids (TDS), turbidity, and residual chlorine) in drinking water supply in selected palm oil estates in Kota Tinggi, Johor. Water samples were collected from the estates with the private and the public water supplies. The sampling points were at the water source (S), the treatment plant outlet (TPO), and at the nearest houses (H1) and the furthest houses (H2) from the TPO. All estates with private water supply failed to meet the NSDWQ for Al with mean concentration of 0.99 ± 1.52 mg/L. However, Al concentrations in all public water supply estates were well within the limit except for one estate. The pH for all samples complied with the NSDWQ except from the private estates for the drinking water supply with an acidic pH (5.50 ± 0.90). The private water supply showed violated turbidity value in the drinking water samples (14.2 ± 24.1 NTU). Insufficient amount of chlorination was observed in the private water supply estates (0.09 ± 0.30 mg/L). Private water supplies with inefficient water treatment served unsatisfactory drinking water quality to the community which may lead to major health problems.
Setiu Wetland is rapidly developing into an aquaculture and agriculture hub, causing concern about its water quality condition. To address this issue, it is imperative to acquire knowledge of the spatial and temporal distributions of pollutants. Consequently, this study applied combinations of hydrodynamic and particle tracking models to identify the transport behaviour of pollutants and calculate the residence time in Setiu Lagoon. The particle tracking results indicated that the residence time in Setiu Lagoon was highly influenced by the release location, where particles released closer to the river mouth exhibited shorter residence times than those released further upstream. Despite this fact, the pulse of river discharges successfully reduced the residence time in the order of two to twelve times shorter. Under different tidal phases, the residence time during the neap tide was longer regardless of heavy rainfalls, implying the domination of tidal flow in the water renewal within the lagoon.
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.
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.
Freshwaters provide valuable habitat and important ecosystem services but are threatened worldwide by habitat loss and degradation. In Southeast Asia, rainforest streams are particularly threatened by logging and conversion to oil palm, but we lack information on the impacts of this on freshwater environmental conditions, and the relative importance of catchment versus riparian-scale disturbance. We studied 16 streams in Sabah, Borneo, including old-growth forest, logged forest, and oil palm sites. We assessed forest quality in riparian zones and across the whole catchment and compared it with stream environmental conditions including water quality, structural complexity, and organic inputs. We found that streams with the highest riparian forest quality were nearly 4 °C cooler, over 20 cm deeper, had over 40% less sand, greater canopy cover, more stored leaf litter, and wider channels than oil palm streams with the lowest riparian forest quality. Other variables were significantly related to catchment-scale forest quality, with streams in the highest quality forest catchments having 40% more bedrock and 20 times more dead wood, along with higher phosphorus, and lower nitrate-N levels compared to streams with the lowest catchment-scale forest quality. Although riparian buffer strips went some way to protecting waterways, they did not maintain fully forest-like stream conditions. In addition, logged forest streams still showed signs of disturbance 10-15 years after selective logging. Our results suggest that maintenance and restoration of buffer strips can help to protect healthy freshwater ecosystems but logging practices and catchment-scale forest management also need to be considered.
This article contains water quality data collected in a shallow and narrow Setiu Lagoon during the southwest monsoon, wet period of northeast monsoon and dry period of northeast monsoon. The surface water quality parameters, which include the temperature, salinity, chlorophyll-a and nutrients (ammonia, nitrate, phosphate, and silicate) were sampled twice per day (high and low tides) at a total of eight stations. Hourly current speed and direction was obtained from mooring of two units of current meters. Compared to the Malaysia Marine Water Quality Criteria and Standard (MWQCS), nutrients in Setiu Lagoon were in Class 2. Although limited, this dataset can provide insights on the changes of water quality condition in Setiu Lagoon under the presence of anthropogenic pressures.
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 evaluation of the importance of having accurate and representative stations in a network for river water quality monitoring is always a matter of concern. The minimal budget and time demands of water quality monitoring programme may appear very attractive, especially when dealing with large-scale river watersheds. This article proposes an improved methodology for optimising water quality monitoring network for present and forthcoming monitoring of water quality under a case study of the Selangor River watershed in Malaysia, where different monitoring networks are being used by water management authorities. Knowing that the lack of financial resources in developing countries like Malaysia is one of the reasons for inadequate monitoring network density, to identify an optimised network for cost-efficiency benefits in this study, a geo-statistical technique coupled Kendall's W was first applied to analyse the performance of each monitoring station in the existing networks under the monitored water quality parameters. Second, the present and future changes in non-point pollution sources were simulated using the integrated Cellular Automata and Markov chain model (CA-Markov). Third, Station Potential Pollution Score (SPPS) determined based on Analytic Hierarchy Process (AHP) was used to weight each station under the changes of non-point pollution sources for 2015, 2024, and 2033 prior to prioritisation. Finally, according to the Kendall's W test on kriging results, the weights of non-point sources from the AHP evaluation and fuzzy membership functions, six most efficient sampling stations were identified to build a robust network for the present and future monitoring of water quality status in the Selangor River watershed. This study proposes a useful approach to the pertinent agencies and management authority concerned to establish appropriate methods for developing an efficient water quality monitoring network for tropical rivers.
The study investigates the latent pollution sources and most significant parameters that cause spatial variation and develops the best input for water quality modelling using principal component analysis (PCA) and artificial neural network (ANN). The dataset, 22 water quality parameters were obtained from Department of Environment Malaysia (DOE). The PCA generated six significant principal component scores (PCs) which explained 65.40 % of the total variance. Parameters for water quality variation are mainlyrelated to mineral components, anthropogenic activities, and natural processes. However, in ANN three input combination models (ANN A, B, and C) were developed to identify the best model that can predict water quality index (WQI) with very high precision. ANN A model appears to have the best prediction capacity with a coefficient of determination (R2) = 0.9999 and root mean square error (RMSE) = 0.0537. These results proved that the PCA and ANN methods can be applied as tools for decision-making and problem-solving for better managing of river quality.
Availability of quality-certified water is pertinent to the production of food and pharmaceutical products. Adverse effects of manganese content of water on the corrosion of vessels and reactors necessitate that process water is scrutinized for allowable concentration levels before being applied in the production processes. In this research, optimization of the adsorption process conditions germane to the removal of manganese from biotreated palm oil mill effluent (BPOME) using zeolite 3A subsequent to a comparative adsorption with clinoptilolite was studied. A face-centered central composite design (FCCCD) of the response surface methodology (RSM) was adopted for the study. Analysis of variance (ANOVA) for response surface quadratic model revealed that the model was significant with dosage and agitation speed connoting the main significant process factors for the optimization. R(2) of 0.9478 yielded by the model was in agreement with predicted R(2). Langmuir and pseudo-second-order suggest the adsorption mechanism involved monolayer adsorption and cation exchanging.
Sg. Papar is one of the rivers in Kota Kinabalu which is mainly used for water supply especially in Papar district. For the past years, many pollution cases concerning Sg. Papar have been reported which originated from various sources including pig farm, agricultural run-off and deforestation. These resulted in a frequent shutdown of the water treatment plants in Papar district leading to water supply disturbance and water supply deficiency in the affected area. The data utilized in this study were obtained from water quality tests performed on river water samples taken from Limbahau water treatment plant recorded from September 2013 to September 2016. Principal Component Analysis (PCA) was used in this study to analyze and correlate the physicochemical parameters with the water treatment plant shutdown. The results revealed that eight parameters (pH, alum, nitrate, TDS, DO, conductivity, colour and chloride) analysed in this study correlate with each other and the parameter that mostly caused the drastic change in the river water and as pollution index is turbidity. This study is critical for understanding the relationship between the water quality paramters and environmental issues.
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.
In Sarawak, pig farm operators are required to treat the wastewater containing pig waste and spilt food in oxidation ponds before discharge. However, information on the impact of this industry on surface water quality is lacking. Therefore, the objective of this study is to determine the impact of pig farm effluent on the water quality of Serin River and its tributaries. Results of analysis show that the tributary that received pond effluent has significantly higher mean of total suspended solids (TSS), biochemical oxygen demand (BOD5) chemical oxygen demand (COD), ammonia-nitrogen (NH3 -N), reactive phosphorus (SRP) and Escherichia coli (E. coli) concentrations when compared to those of the tributary that did not receive pond effluent. Comparisons between the stations upstream and downstream of the discharge point indicated that BOD5 and COD were significantly higher at the downstream station that received pond effluent. Dissolved oxygen (DO) was the lowest at the tributary receiving effluent from pig farms with a mean of 2.40 mg/l. According to the Interim Water Quality Standard of the Department of Environment, water quality at the tributary that received pig farm effluent falls into Class III whereas that of the other stations falls into Class II. It is recommended that further studies be conducted on the management of waste to explore the possibility of turning the waste into a resource so that water quality of rivers can remain pristine for drinking and recreation.
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.
Studies on the occurrence of pharmaceutical residues in drinking water were conducted especially in developed countries. However, limited studies reported the occurrence of pharmaceutical residues in developing countries. Thus, this study is conducted to fill the knowledge gap of pharmaceutical residue occurrences in developing countries, particularly in Malaysia, along with public awareness level and its potential human health risk. This study investigates public awareness level of drinking water quality and pharmaceutical handling, the occurrence of nine pharmaceutical residues (amoxicillin, caffeine, chloramphenicol, ciprofloxacin, dexamethasone, diclofenac, nitrofurazone, sulfamethoxazole, and triclosan) and potential human health risks in drinking water from Kajang (Malaysia) using commercially competitive enzyme-linked immunosorbent assay kits. In general, the public awareness level of Kajang population showed poor knowledge (82.02%), and less positive attitude (98.88%) with a good practice score (57.3%). Ciprofloxacin was detected at the highest concentration (0.667 ng/L) while amoxicillin was at the lowest concentration (0.001 ng/L) in drinking water from Kajang (Malaysia). Nevertheless, all the reported occurrences were lower than previous studies conducted elsewhere. There was no appreciable potential human health risk for all the pharmaceutical residues as the risk quotient (RQ) values were less than 1 (RQ water risk management and regulation in Malaysia.
Bera Lake is the largest natural fresh water reservoir in Malaysia. It has vital environmental and ecological importance for human and wild life. Nevertheless, water quality of this lake has been degraded during the last few decades due to land development projects at catchment area. Therefore, a comprehensive water quality assessment of Bera Lake was implemented in order to compare current water quality with the implementation of land development projects. In situ water quality surveying was implemented using calibrated full option Hydrolab DS 5. Eleven parameters viz., temperature, depth of sampling, salinity, Turbidity, total dried solid, pH, NH4(+), N03(-), Cl(-), saturation percentage of dissolved oxygen, specific conductivity were recorded in fifty one stations at 0.2h, 0.5h, and 0.8h depth. National Water Quality Standards for Malaysia (NWQS) and Water Quality were used to evaluate Bera Lake quality based on previous and resultant data. Vertical water quality analysis revealed a clear stratification in Bera Lake water profile in terms of temperature, dissolved oxygen, chloride (Cl(-)), nitrate (NO(3)), pH and specific conductivity (EC) parameters. Results clearly demonstrate the important role of land use changes since 1972 in the physico-chemical condition of water quality at Bera Lake. Classifications of water quality before and after land development project were calculated as class II and class V, respectively. A long-term and comprehensive monitoring of water quality assessment is recommended in order to reach plan of sustainable water resources use with conservation approach.
This paper aims to assess the influence of land use and land cover (LULC) indicators and population density on water quality parameters during dry and rainy seasons in a tourism area in Indonesia. This study applies least squares regression (OLS) and Pearson correlation analysis to see the relationship among factors, and all LULC and population density were significantly correlated with most of water quality parameter with P values of 0.01 and 0.05. For example, DO shows high correlation with population density, farm, and built-up in dry season; however, each observation point has different percentages of LULC and population density. The concentration value should be different over space since watershed characteristics and pollutions sources are not the same in the diverse locations. The geographically weighted regression (GWR) analyze the spatially varying relationships among population density, LULC categories (i.e., built-up areas, rice fields, farms, and forests), and 11 water quality indicators across three selected rivers (Ayung, Badung, and Mati) with different levels of tourism urbanization in Bali Province, Indonesia. The results explore that compared with OLS estimates, GWR performed well in terms of their R2 values and the Akaike information criterion (AIC) in all the parameters and seasons. Further, the findings exhibit population density as a critical indicator having a highly significant association with BOD and E. Coli parameters. Moreover, the built-up area has correlated positively to the water quality parameters (Ni, Pb, KMnO4 and TSS). The parameter DO is associated negatively with the built-up area, which indicates increasing built-up area tends to deteriorate the water quality. Hence, our findings can be used as input to provide a reference to the local governments and stakeholders for issuing policy on water and LULC for achieving a sustainable water environment in this region.