Displaying publications 101 - 120 of 215 in total

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  1. Fulltext Assessment of coastal river water quality in Bangladesh: Implications for drinking and irrigation purposes
    Uddin MR, Khandaker MU, Ahmed S, Abedin MJ, Hossain SMM, Al Mansur MA, et al.
    PLoS One, 2024;19(4):e0300878.
    PMID: 38635835 DOI: 10.1371/journal.pone.0300878
    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.
    Matched MeSH terms: Water Quality
  2. Microplastic concentrations in river water and bed sediments in a tropical river: implications for water quality monitoring
    Chen HL, Selvam SB, Ting KN, Gibbins CN
    Environ Monit Assess, 2023 Jan 18;195(2):307.
    PMID: 36652034 DOI: 10.1007/s10661-022-10856-5
    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.
    Matched MeSH terms: Water Quality
  3. Potential of bioretention plants in treating urban runoff polluted with greywater under tropical climate
    Jhonson P, Goh HW, Chan DJC, Juiani SF, Zakaria NA
    Environ Sci Pollut Res Int, 2023 Feb;30(9):24562-24574.
    PMID: 36336739 DOI: 10.1007/s11356-022-23605-5
    Bioretention systems are among the most popular stormwater best management practices (BMPs) for urban runoff treatment. Studies on plant performance using bioretention systems have been conducted, especially in developed countries with a temperate climate, such as the USA and Australia. However, these results might not be applicable in developing countries with tropical climates due to the different rainfall regimes and the strength of runoff pollutants. Thus, this study focuses on the performance of tropical plants in treating urban runoff polluted with greywater using a bioretention system. Ten different tropical plant species were triplicated and planted in 30 mesocosms with two control mesocosms without vegetation. One-way ANOVA was used to analyze the performance of plants, which were then ranked based on their performance in removing pollutants using the total score obtained for each water quality test. Results showed that vetiver topped the table with 86.4% of total nitrogen (TN) removal, 93.5% of total phosphorus (TP) removal, 89.8% of biological oxygen demand (BOD) removal, 90% of total suspended solids (TSS) removal, and 92.5% of chemical oxygen demand (COD) removal followed by blue porterweed, Hibiscus, golden trumpet, and tall sedge which can be recommended to be employed in future bioretention studies.
    Matched MeSH terms: Water Quality
  4. Water treatment and artificial intelligence techniques: a systematic literature review research
    Ismail W, Niknejad N, Bahari M, Hendradi R, Zaizi NJM, Zulkifli MZ
    Environ Sci Pollut Res Int, 2023 Jun;30(28):71794-71812.
    PMID: 34609681 DOI: 10.1007/s11356-021-16471-0
    As clean water can be considered among the essentials of human life, there is always a requirement to seek its foremost and high quality. Water primarily becomes polluted due to organic as well as inorganic pollutants, including nutrients, heavy metals, and constant contamination with organic materials. Predicting the quality of water accurately is essential for its better management along with controlling pollution. With stricter laws regarding water treatment to remove organic and biologic materials along with different pollutants, looking for novel technologic procedures will be necessary for improved control of the treatment processes by water utilities. Linear regression-based models with relative simplicity considering water prediction have been typically used as available statistical models. Nevertheless, in a majority of real problems, particularly those associated with modeling of water quality, non-linear patterns will be observed, requiring non-linear models to address them. Thus, artificial intelligence (AI) can be a good candidate in modeling and optimizing the elimination of pollutants from water in empirical settings with the ability to generate ideal operational variables, due to its recent considerable advancements. Management and operation of water treatment procedures are supported technically by these technologies, leading to higher efficiency compared to sole dependence on human operations. Thus, establishing predictive models for water quality and subsequently, more efficient management of water resources would be critically important, serving as a strong tool. A systematic review methodology has been employed in the present work to investigate the previous studies over the time interval of 2010-2020, while analyzing and synthesizing the literature, particularly regarding AI application in water treatment. A total number of 92 articles had addressed the topic under study using AI. Based on the conclusions, the application of AI can obviously facilitate operations, process automation, and management of water resources in significantly volatile contexts.
    Matched MeSH terms: Water Quality
  5. Isolation of Potential Bacteria as Inoculum for Biofloc Formation in Pacific Whiteleg Shrimp, Litopenaeus vannamei Culture Ponds
    Kasan NA, Ghazali NA, Ikhwanuddin M, Ibrahim Z
    Pak J Biol Sci, 2017;20(6):306-313.
    PMID: 29023055 DOI: 10.3923/pjbs.2017.306.313
    BACKGROUND AND OBJECTIVE: A new green technology to reduce environmental damages while optimizing production of Pacific Whiteleg shrimp, Litopenaeus vannamei was developed known as "Biofloc technology". Microbial communities in biofloc aggregates are responsible in eliminating water exchange and producing microbial proteins that can be used as supplemented feed for L. vannamei. This study aimed to isolate and identify potential bioflocculant-producing bacteria to be used as inoculum for rapid formation of biofloc.

    MATERIALS AND METHODS: For the purpose of this study, bacterial communities during 0, 30 and 70 days of culture (DOC) of L. vannamei grow-out ponds were isolated and identified through phenotypic and 16S rDNA sequences analysis. Phylogenetic relationships between isolated bacteria were then evaluated through phylogenetic tree analysis. One-way analysis of variance (ANOVA) was used to compare the differences of microbial communities at each DOC.

    RESULTS: Out of 125 bacterial isolates, nine species of bacteria from biofloc were identified successfully. Those bacteria species were identified as Halomonas venusta, H. aquamarina, Vibrio parahaemolyticus, Bacillus infantis, B. cereus, B. safensis, Providencia vermicola, Nitratireductor aquimarinus and Pseudoalteromonas sp., respectively. Through phylogenetic analysis, these isolates belong to Proteobacteria and Firmicutes families under the genera of Halomonas sp., Vibrio sp., Bacillus sp., Providencia sp., Nitratireductor sp. and Pseudoalteromonas sp.

    CONCLUSION: In this study, bioflocculant-producing bacteria were successfully identified which are perfect candidates in forming biofloc to reduce water pollution towards a sustainable aquaculture industry. Presence of Halomonas sp. and Bacillus sp. in all stages of biofloc formation reinforces the need for new development regarding the ability of these species to be used as inoculum in forming biofloc rapidly.

    Matched MeSH terms: Water Quality*
  6. Responses of phytoplankton community to eutrophication in Semerak Lagoon (Malaysia)
    Er HH, Lee LK, Lim ZF, Teng ST, Leaw CP, Lim PT
    Environ Sci Pollut Res Int, 2018 Aug;25(23):22944-22962.
    PMID: 29858995 DOI: 10.1007/s11356-018-2389-0
    Effects of aquaculture activities on the environmental parameters and phytoplankton community structure were investigated in a semi-enclosed lagoon located at Semerak River, Malaysia. Elevated concentrations of phosphate and ammonia were observed at the aquaculture area and the inner lagoon. Relatively low dissolved oxygen, high total chlorophyll a, and high phytoplankton abundances but low species richness were recorded. Chaetoceros, Pseudo-nitzschia brasiliana, Blixaea quinquecornis, and Skeletonema blooms were observed, and some were associated with anoxia condition. Eutrophication level assessed by UNTRIX suggests that the water quality in the lagoon is deteriorating. Dissolved inorganic phosphorus and nitrogen at the impacted area were 15 and 12 times higher than the reference sites, respectively. Such trophic status indices could provide a useful guideline for optimal aquaculture management plan to reduce the environmental impact caused by aquaculture.
    Matched MeSH terms: Water Quality*
  7. Performance of biotic indices in comparison to chemical-based Water Quality Index (WQI) in evaluating the water quality of urban river
    Wan Abdul Ghani WMH, Abas Kutty A, Mahazar MA, Al-Shami SA, Ab Hamid S
    Environ Monit Assess, 2018 Apr 19;190(5):297.
    PMID: 29675764 DOI: 10.1007/s10661-018-6675-6
    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.
    Matched MeSH terms: Water Quality/standards*
  8. Microbial water quality and the detection of multidrug resistant E. coli and antibiotic resistance genes in aquaculture sites of Singapore
    Ng C, Chen H, Goh SG, Haller L, Wu Z, Charles FR, et al.
    Mar Pollut Bull, 2018 Oct;135:475-480.
    PMID: 30301062 DOI: 10.1016/j.marpolbul.2018.07.055
    Poor microbial water quality jeopardizes the health and safety of food produced by aquaculture farms. Three fish farms and transect sites in Singapore were assessed for microbial water quality and antimicrobial resistance determinants. Of the 33 multidrug resistant E. coli isolated from surface waters of the Johor Straits, 81.8% were ESBL producers. The relative abundance of sul1, qnrA and intI1 genes were higher in sediments than surface waters. Among the surface water samples, higher concentrations (10-1-101) of beta-lactamases (blaSHV, blaOXA, blaCTX-M) were detected in the transect sites. This study highlights a potential antimicrobial resistance transmission chain from environmental waters, to animal carriers and humans.
    Matched MeSH terms: Water Quality*
  9. Assessment of groundwater nitrate contamination hazard in a semi-arid region by using integrated parametric IPNOA and data-driven logistic regression models
    Rizeei HM, Azeez OS, Pradhan B, Khamees HH
    Environ Monit Assess, 2018 Oct 04;190(11):633.
    PMID: 30288624 DOI: 10.1007/s10661-018-7013-8
    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.
    Matched MeSH terms: Water Quality*
  10. Public awareness level and occurrence of pharmaceutical residues in drinking water with potential health risk: A study from Kajang (Malaysia)
    Mohd Nasir FA, Praveena SM, Aris AZ
    Ecotoxicol Environ Saf, 2019 Dec 15;185:109681.
    PMID: 31561079 DOI: 10.1016/j.ecoenv.2019.109681
    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.
    Matched MeSH terms: Water Quality*
  11. Microbial contamination and its associations with major ions in shallow groundwater along coastal Tamil Nadu
    Vasudevan U, Gantayat RR, Chidambaram S, Prasanna MV, Venkatramanan S, Devaraj N, et al.
    Environ Geochem Health, 2021 Feb;43(2):1069-1088.
    PMID: 32940833 DOI: 10.1007/s10653-020-00712-1
    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.
    Matched MeSH terms: Water Quality/standards
  12. Fulltext Land Use Land Cover Changes in Detection of Water Quality: A Study Based on Remote Sensing and Multivariate Statistics
    Hua AK
    J Environ Public Health, 2017;2017:7515130.
    PMID: 28377790 DOI: 10.1155/2017/7515130
    Malacca River water quality is affected due to rapid urbanization development. The present study applied LULC changes towards water quality detection in Malacca River. The method uses LULC, PCA, CCA, HCA, NHCA, and ANOVA. PCA confirmed DS, EC, salinity, turbidity, TSS, DO, BOD, COD, As, Hg, Zn, Fe, E. coli, and total coliform. CCA confirmed 14 variables into two variates; first variate involves residential and industrial activities; and second variate involves agriculture, sewage treatment plant, and animal husbandry. HCA and NHCA emphasize that cluster 1 occurs in urban area with Hg, Fe, total coliform, and DO pollution; cluster 3 occurs in suburban area with salinity, EC, and DS; and cluster 2 occurs in rural area with salinity and EC. ANOVA between LULC and water quality data indicates that built-up area significantly polluted the water quality through E. coli, total coliform, EC, BOD, COD, TSS, Hg, Zn, and Fe, while agriculture activities cause EC, TSS, salinity, E. coli, total coliform, arsenic, and iron pollution; and open space causes contamination of turbidity, salinity, EC, and TSS. Research finding provided useful information in identifying pollution sources and understanding LULC with river water quality as references to policy maker for proper management of Land Use area.
    Matched MeSH terms: Water Quality*
  13. The evaluation of water quality and metal concentrations of Titiwangsa Lake, Selangor, Peninsular Malaysia
    Said KS, Shuhaimi-Othman M, Ahmad AK
    Pak J Biol Sci, 2012 May 15;15(10):459-68.
    PMID: 24187900
    A study of water quality parameters (temperature, conductivity, total dissolved solid, dissolved oxygen, pH and water hardness) in Titiwangsa Lake was conducted in January, April, July and October 2010. The water quality parameters were tested and recorded at different sampling stations chosen randomly using hydrolab data sonde 4 and surveyor 4 a water quality multi probe (USA). Six metals i.e., cadmium, chromium, lead, nickel, zinc and copper were determined in five different compartments of the lake namely water, total suspended solids, plankton, sediment and fish. The metals concentration were determined by Inductively Coupled Plasma Mass Spectrometer (ICP-MS), perkin elmer elan, model 9000. The water quality parameters were compared with National Water Quality Standard (NWQS Malaysia) while metal concentrations were compared with Malaysian and international standards. The study shows that water quality parameters are of class 2. This condition is suitable for recreational activities where body contact is allowed and suitable for sensitive fishing activities. Furthermore, metal concentrations were found to be lower than the international standards, therefore toxic effects for these metals would be rarely observed and the adverse effects to aquatic organisms would not frequently occur.
    Matched MeSH terms: Water Quality*
  14. Artificial neural network modeling of the water quality index for Kinta River (Malaysia) using water quality variables as predictors
    Gazzaz NM, Yusoff MK, Aris AZ, Juahir H, Ramli MF
    Mar Pollut Bull, 2012 Nov;64(11):2409-20.
    PMID: 22925610 DOI: 10.1016/j.marpolbul.2012.08.005
    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.
    Matched MeSH terms: Water Quality/standards*
  15. Fulltext Waterborne parasites: a current status from the Philippines
    Onichandran S, Kumar T, Salibay CC, Dungca JZ, Tabo HA, Tabo N, et al.
    Parasit Vectors, 2014;7:244.
    PMID: 24885105 DOI: 10.1186/1756-3305-7-244
    Despite the amount of awareness created, waterborne disease still poses threat, especially in developing countries. Due to the scarcity of reported data on waterborne parasites, the consumption of unsafe water prolongs. Thus, the occurrences of waterborne parasites from various samples were investigated from one of the Southeast Asian country, the Philippines.
    Matched MeSH terms: Water Quality*
  16. Trend analysis of a tropical urban river water quality in Malaysia
    Othman F, M E AE, Mohamed I
    J Environ Monit, 2012 Dec;14(12):3164-73.
    PMID: 23128415 DOI: 10.1039/c2em30676j
    Rivers play a significant role in providing water resources for human and ecosystem survival and health. Hence, river water quality is an important parameter that must be preserved and monitored. As the state of Selangor and the city of Kuala Lumpur, Malaysia, are undergoing tremendous development, the river is subjected to pollution from point and non-point sources. The water quality of the Klang River basin, one of the most densely populated areas within the region, is significantly degraded due to human activities as well as urbanization. Evaluation of the overall river water quality status is normally represented by a water quality index (WQI), which consists of six parameters, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen and pH. The objectives of this study are to assess the water quality status for this tropical, urban river and to establish the WQI trend. Using monthly WQI data from 1997 to 2007, time series were plotted and trend analysis was performed by employing the first-order autocorrelated trend model on the moving average values for every station. The initial and final values of either the moving average or the trend model were used as the estimates of the initial and final WQI at the stations. It was found that Klang River water quality has shown some improvement between 1997 and 2007. Water quality remains good in the upper stream area, which provides vital water sources for water treatment plants in the Klang valley. Meanwhile, the water quality has also improved in other stations. Results of the current study suggest that the present policy on managing river quality in the Klang River has produced encouraging results; the policy should, however, be further improved alongside more vigorous monitoring of pollution discharge from various point sources such as industrial wastewater, municipal sewers, wet markets, sand mining and landfills, as well as non-point sources such as agricultural or urban runoff and commercial activity.
    Matched MeSH terms: Water Quality/standards*
  17. Fulltext Determination of aluminium and physicochemical parameters in the palm oil estates water supply at Johor, Malaysia
    Siti Farizwana MR, Mazrura S, Zurahanim Fasha A, Ahmad Rohi G
    J Environ Public Health, 2010;2010:615176.
    PMID: 21461348 DOI: 10.1155/2010/615176
    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.
    Matched MeSH terms: Water Quality*
  18. Assessment of water quality parameters using multivariate analysis for Klang River basin, Malaysia
    Mohamed I, Othman F, Ibrahim AI, Alaa-Eldin ME, Yunus RM
    Environ Monit Assess, 2015 Jan;187(1):4182.
    PMID: 25433545 DOI: 10.1007/s10661-014-4182-y
    This case study uses several univariate and multivariate statistical techniques to evaluate and interpret a water quality data set obtained from the Klang River basin located within the state of Selangor and the Federal Territory of Kuala Lumpur, Malaysia. The river drains an area of 1,288 km(2), from the steep mountain rainforests of the main Central Range along Peninsular Malaysia to the river mouth in Port Klang, into the Straits of Malacca. Water quality was monitored at 20 stations, nine of which are situated along the main river and 11 along six tributaries. Data was collected from 1997 to 2007 for seven parameters used to evaluate the status of the water quality, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen, pH, and temperature. The data were first investigated using descriptive statistical tools, followed by two practical multivariate analyses that reduced the data dimensions for better interpretation. The analyses employed were factor analysis and principal component analysis, which explain 60 and 81.6% of the total variation in the data, respectively. We found that the resulting latent variables from the factor analysis are interpretable and beneficial for describing the water quality in the Klang River. This study presents the usefulness of several statistical methods in evaluating and interpreting water quality data for the purpose of monitoring the effectiveness of water resource management. The results should provide more straightforward data interpretation as well as valuable insight for managers to conceive optimum action plans for controlling pollution in river water.
    Matched MeSH terms: Water Quality/standards*
  19. A novel computer-aided multivariate water quality index
    Sim SF, Ling TY, Lau S, Jaafar MZ
    Environ Monit Assess, 2015 Apr;187(4):181.
    PMID: 25773897 DOI: 10.1007/s10661-015-4416-7
    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.
    Matched MeSH terms: Water Quality/standards
  20. Artificial neural network modeling of the water quality index using land use areas as predictors
    Gazzaz NM, Yusoff MK, Ramli MF, Juahir H, Aris AZ
    Water Environ Res, 2015 Feb;87(2):99-112.
    PMID: 25790513
    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.
    Matched MeSH terms: Water Quality/standards*
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