Water-based cooling towers and their water supply at two hospitals in Johor were surveyed for the presence Legionella pneumophila. L. pneumophila were grown from 19 (76%) out of 25 collected water samples. One hospital cooling tower was contaminated with L. pneumophila serogroup 1.
Due to the increasing importance of diesel and petroleum for industrial development during the last century, petrochemical effluents have significantly contributed to the pollution of aquatic and soil environments. The contamination generated by petroleum hydrocarbons can endanger not only humans but also the environment. Phytoremediation or plant-assisted remediation can be considered one of the best technologies to manage petroleum product-contaminated water and soil. The main advantages of this method are that it is environmentally-friendly, potentially cost-effective and does not require specialised equipment. The scope of this review includes a description of hydrocarbon pollutants from petrochemical industries, their toxicity impacts and methods of treatment and degradation. The major emphasis is on phytodegradation (phytotransformation) and rhizodegradation since these mechanisms are the most favourable alternatives for soil and water reclamation of hydrocarbons using tropical plants. In addressing these issues, this review also covers challenges to retrieve the environment (soil and water) from petroleum contaminations through phytoremediation, and its opportunities to remove or reduce the negative environmental impacts of petroleum contaminations and restore damaged ecosystems with sustainable ways to keep healthy life for the future.
Landfill leachate is one of the sources of surface water pollution in Selangor State (SS), Malaysia. Leachate volume prediction is essential for sustainable waste management and leachate treatment processes. The accurate estimation of leachate generation rates is often considered a challenge, especially in developing countries, due to the lack of reliable data and high measurement costs. Leachate generation is related to several variable factors, including meteorological data, waste generation rates, and landfill design conditions. Large variations in these factors lead to complicated leachate modeling processes. The aims of this study are to determine the key elements contributing to leachate production and then develop an adaptive neural fuzzy inference system (ANFIS) model to predict leachate generation rates. Accuracy of the final model performance was tested and evaluated using the root mean square error (RMSE), the mean absolute error (MAE), and the correlation coefficient (R). The study results defined dumped waste quantity, rainfall level, and emanated gases as the most significant contributing factors in leachate generation. The best model structure consisted of two triangular fuzzy membership functions and a hybrid training algorithm with eight fuzzy rules. The proposed ANFIS model showed a good performance with an overall correlation coefficient of 0.952.
Leachate is one of the main surface water pollution sources in Selangor State (SS), Malaysia. The prediction of leachate amounts is elementary in sustainable waste management and leachate treatment processes, before discharging to surrounding environment. In developing countries, the accurate evaluation of leachate generation rates has often considered a challenge due to the lack of reliable data and high measurement costs. Leachate generation is related to several factors, including meteorological data, waste generation rates, and landfill design conditions. The high variations in these factors lead to complicating leachate modeling processes. This study aims at identifying the key elements contributing to leachate production and developing various AI-based models to predict leachate generation rates. These models included Artificial Neural Network (ANN)-Multi-linear perceptron (MLP) with single and double hidden layers, and support vector machine (SVM) regression time series algorithms. Various performance measures were applied to evaluate the developed model's accuracy. In this study, input optimization process showed that three inputs were acceptable for modeling the leachate generation rates, namely dumped waste quantity, rainfall level, and emanated gases. The initial performance analysis showed that ANN-MLP2 model-which applies two hidden layers-achieved the best performance, then followed by ANN-MLP1 model-which applies one hidden layer and three inputs-while SVM model gave the lowest performance. Ranges and frequency of relative error (RE%) also demonstrate that ANN-MLP models outperformed SVM models. Furthermore, low and peak flow criterion (LFC and PFC) assessment of leachate inflow values in ANN-MLP model with two hidden layers made more accurate values than other models. Since minimizing data collection and processing efforts as well as minimizing modeling complexity are critical in the hydrological modeling process, the applied input optimization process and the developed models in this study were able to provide a good performance in the modeling of leachate generation efficiently.
Matched MeSH terms: Water Pollution, Chemical/analysis; Water Pollution, Chemical/prevention & control
In recent times, surface water resource in the Western Region of Ghana has been found to be inadequate in supply and polluted by various anthropogenic activities. As a result of these problems, the demand for groundwater by the human populations in the peri-urban communities for domestic, municipal and irrigation purposes has increased without prior knowledge of its water quality. Water samples were collected from 14 public hand-dug wells during the rainy season in 2013 and investigated for total coliforms, Escherichia coli, mercury (Hg), arsenic (As), cadmium (Cd) and physicochemical parameters. Multivariate statistical analysis of the dataset and a linear stoichiometric plot of major ions were applied to group the water samples and to identify the main factors and sources of contamination. Hierarchal cluster analysis revealed four clusters from the hydrochemical variables (R-mode) and three clusters in the case of water samples (Q-mode) after z score standardization. Principal component analysis after a varimax rotation of the dataset indicated that the four factors extracted explained 93.3 % of the total variance, which highlighted salinity, toxic elements and hardness pollution as the dominant factors affecting groundwater quality. Cation exchange, mineral dissolution and silicate weathering influenced groundwater quality. The ranking order of major ions was Na(+) > Ca(2+) > K(+) > Mg(2+) and Cl(-) > SO4 (2-) > HCO3 (-). Based on piper plot and the hydrogeology of the study area, sodium chloride (86 %), sodium hydrogen carbonate and sodium carbonate (14 %) water types were identified. Although E. coli were absent in the water samples, 36 % of the wells contained total coliforms (Enterobacter species) which exceeded the WHO guidelines limit of zero colony-forming unit (CFU)/100 mL of drinking water. With the exception of Hg, the concentration of As and Cd in 79 and 43 % of the water samples exceeded the WHO guideline limits of 10 and 3 μg/L for drinking water, respectively. Reported values in some areas in Nigeria, Malaysia and USA indicated that the maximum concentration of Cd was low and As was high in this study. Health risk assessment of Cd, As and Hg based on average daily dose, hazard quotient and cancer risk was determined. In conclusion, multiple natural processes and anthropogenic activities from non-point sources contributed significantly to groundwater salinization, hardness, toxic element and microbiological contamination of the study area. The outcome of this study can be used as a baseline data to prioritize areas for future sustainable development of public wells.
Matched MeSH terms: Water Pollution/statistics & numerical data*
Landfills are sources of groundwater and soil pollution due to the production of leachate and its migration through refuse. This study was conducted in order to determine the extent of groundwater and soil pollution within and around the landfill of Seri Petaling located in the State of Selangor, Malaysia. The condition of nearby surface water was also determined. An electrical resistivity imaging survey was used to investigate the leachate production within the landfill. Groundwater geochemistry was carried out and chemical analysis of water samples was conducted upstream and downstream of the landfill. Surface water was also analyzed in order to determine its quality. Soil chemical analysis was performed on soil samples taken from different locations within and around the landfill in the vadose zone (unsaturated zone) and below the water table (in the soil saturated zone). The resistivity image along line L-L1 indicated the presence of large zones of decomposed waste bodies saturated with highly conducting leachate. Analysis of trace elements indicated their presence in very low concentrations and did not reflect any sign of heavy metal pollution of ground and surface water or of soil. Major ions represented by Na, K, and Cl were found in anomalous concentrations in the groundwater of the downstream bore hole, where they are 99.1%, 99.2%, and 99.4%, respectively, higher compared to the upstream bore hole. Electrical conductivity (EC) was also found in anomalous concentration downstream. Ca and Mg ions represent the water hardness (which is comparatively high downstream). There is a general trend of pollution towards the downstream area. Sulfates (SO4) and nitrates (NO3) are found in the area in low concentrations, even below the WHO standards for drinking water, but are significantly higher in the surface water compared to the groundwater. Phosphate (PO4) and nitrite (NO2), although present in low levels, are significantly higher at the downstream. There is no significant difference in the amount of fluoride (F) in the different locations. In the soil vadose zone, heavy metals were found to be in their typical normal ranges and within the background concentrations. Soil exchangeable bases were significantly higher in the soil saturated zone compared to the vadose zone, and no significant difference was obtained in the levels of inorganic pollutants. With the exception of Cd, the concentration ranges of all trace elements (Cu, Zn, Cr, Pb, and Ni) of Seri Petaling landfill soils were below the upper limits of baseline concentrations published from different sources.
Matched MeSH terms: Water Pollution, Chemical/analysis*
Boron has been classified as a drinking water pollutant in many countries. It is harmful to many plants, exceptionally sensible plants, and human health. Therefore, boron level needs to be decreased to 0.3 mg/L for drinking water and within 0.5 mg/L to 1 mg/L for irrigation water. In this study, various operational parameters namely pH, contact time and liquid/solid ratio were investigated to determine the potential of using date seed (or date pit or date stone) to remove boron from seawater. This study's main objective was to determine boron adsorption capacities of date seeds prepared by various methods (i.e., powdered, activated, acid-treated and defatted seed) by batch adsorption process using boron contaminated synthetic seawater. The process parameters of the selected biosorbent among the four date seed preparations methods were optimized. The surface characteristics were analyzed by using Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope (SEM). The results showed that acid-treated date seed was the best biosorbent in terms of removing 89.18% boron from aqueous solution at neutral pH, liquid to solid ratio of 5 within 2 hours of reaction time at room temperature (25°C±2°C).
The microbial composition in coastal water of the Port Dickson beach in Negeri Sembilan, Malaysia was analyzed using several microbial indicators for the purpose of selecting the best indicator for marine water pollution. The indicators studied were total coliform (TC), fecal coliform (FC), fecal streptococci (FS) and coliphage. Five locations were selected along the Port Dickson beaches and samplings were carried out in 1998 and 2001. The results showed an increase in the number of total coliform (TC), fecal coliform (FC) and fecal streptococci (FS) between these two sampling by 98.12%, 86.12% and 99%, respectively. The numbers of TC, FC and FS exceeded the recommended limit for recreational seawater based on U.S. EPA 1986 standard. There was a positive correlation between TC, FC and FS and negative to coliphages.
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.
Matched MeSH terms: Water Pollution, Chemical/statistics & numerical data*
Morphological deformities in parts of the head capsule of Chironomus spp. larvae inhabiting three polluted rivers (Permatang Rawa [PRR], Pasir [PR], and Kilang Ubi [KUR]) in the Juru River Basin, northeastern peninsular Malaysia, were studied. Samples of the fourth-instar larvae at one location in each river were collected monthly from November 2007 to March 2008 and examined for deformities of the mentum, antenna, mandible, and epipharyngis. At each sample location, in situ measurements of water depth, river width, water pH, dissolved oxygen, and water temperature were made. Samples of river water and benthic sediments were also collected monthly from each larval sample location in each river and taken to the laboratory for appropriate analysis. Total suspended solids (TSSs), ammonium-N, nitrate-N, phosphate-P, chloride, sulfate, and aluminum content in water were analyzed. Total organic matter and nonresidual metals in the sediment samples were also analyzed. Among the three rivers, the highest mean deformity (47.17%) was recorded in larvae collected from KUR that received industrial discharges from surrounding garment and rubber factories, followed by PRR (33.71%) receiving primarily residues of fertilizers and pesticides from adjacent rice fields, and PR (30.34%) contaminated primarily by anthropogenic wastes from the surrounding residential areas. Among the various head capsule structures, deformity of the mentum was strongly reflective of environmental stress and amounted to 27.9, 20.87, and 30.19% in the PRR, PR, and KUR, respectively. Calculated Lenat's toxic score index satisfactorily explained the influence of prevailing environmental variables on the severity of mentum deformities. Redundancy analysis and forward selection selected TSSs, sediment Zn, Mn, Cu, and Ni, and water pH, dissolved oxygen, water temperature, total organic matter, nitrate-N, chloride, phosphate-P, ammonium-N, sulfate, and aluminum as parameters that significantly affected some proportion of deformities. The total deformities correlated closely with deformities of mentum but only weakly with deformities in other parts of head. The total deformity incidence was strongly correlated with high contents of sediment Mn and Ni. The mentum and epipharyngis deformities incidence was highly correlated with an increase of TSSs, total aluminum, and ammonium-N and a decrease in pH and dissolved oxygen.
Matched MeSH terms: Water Pollution/adverse effects*
Abundance and diversity of benthic macroinvertebrates as well as physico-chemical parameters were investigated in five rivers of the Juru River Basin in northern Peninsula Malaysia: Ceruk Tok Kun River (CTKR), Pasir River (PR), Permatang Rawa River (PRR), Kilang Ubi River (KUR), and Juru River (JR). The physico-chemical parameters and calculated water quality index (WQI) were significantly different among the investigated rivers (ANOVA, P<0.05). The WQI classified CTKR, PR, and JR into class III (slightly polluted). However, PRR and KUR fell into class IV (polluted). High diversity and abundance of macroinvertebrates, especially the intolerant taxa, Ephemeroptera, Plecoptera, and Trichoptera, were observed in the least polluted river, CTKR. Decreasing abundance of macroinvertebrates followed the deterioration of river water quality with the least number of the most tolerant taxa collected from PR. On the basis of composition and sensitivity of macroinvertebrates to pollutants in each river, the highest Biological Monitoring Working Party (BMWP) index score of 93 was reported in CTKR (good water quality). BMWP scores in PRR and JR were 38.7 and 20.1, respectively, classifying both of them into "moderate water quality" category. Poor water quality was reported in PR and KUR. The outcome of the multivariate analysis (CCA) was highly satisfactory, explaining 43.32% of the variance for the assemblages of macroinvertebrates as influenced by 19 physical and chemical variables. According to the CCA model, we assert that there were three levels of stresses on macroinvertebrate communities in the investigated rivers: Level 1, characterized of undisturbed or slightly polluted as in the case of CTKR; Level 2, characterized by a lower habitat quality (the JR) compared to the CTKR; and Level 3 showed severe environmental stresses (PRR, PR, and KUR) primarily contributed by agricultural, industrial, and municipal discharges.
Matched MeSH terms: Water Pollution, Chemical/statistics & numerical data
This study was conducted to evaluate the effect of an eminent decay fungus, Phanerocheate chrysosporium of organic residues on wastewater sludge for its improvement through decomposition and separation of waste particles by Liquid State Bioconversion (LSB). The effect of fungal treatment was compared to uninoculated (Control) at three different harvests 7, 14 and 21 days after inoculation (DAI). The observed results showed that the weight loss and solid content of wastewater sludge were significantly influenced by Phanerocheate chrysosporium. Both parameters were highly influenced at 7 DAI. The COD and pH of wastewater sludge were also highly influenced by fungal treatment.
Matched MeSH terms: Water Pollution/prevention & control
Emerging booster biocides contamination raises particular attention in the marine ecosystem health. This study provides the baseline data on the occurrence of Irgarol-1051 (2-methylthio-4-tert-butylamino-6-cyclopropylamiono-s-triazine) in the selected coastal water around Malaysia. The maximum detected concentration of Irgarol was 2021 ng/L at Klang West, commercial and cargo port. Coral reef Islands (Redang and Bidong) were relatively less contaminated compared to other coastal areas. The temporal variation revealed that only 1% of 28 stations sampled on November, 2011 was above the environmental risk limit of 24 ng/L as suggested by Dutch Authorities, while in January and April, 2012; 46% and 92% of the stations were above the limit respectively. The present findings demonstrate the wide detection of novel antifouling materials Irgarol-1051 which advocates the need for proper monitoring and conservation strategies for the coastal resources.
Matched MeSH terms: Water Pollution, Chemical/statistics & numerical data
This study assesses the 'radio-ecological' impacts of Fukushima nuclear accident on non-human biota using the ERICA Tool, which adopts an internationally verified methodology. The paper estimates the impacts of the accident on terrestrial and marine biota based on the environmental data reported in literature for Japan, China, South Korea and the USA. Discernible impacts have been detected in the marine biota around Fukushima Daiichi nuclear power plant. This study confirms that the Fukushima accident had caused heavier damage to marine bionts compared with terrestrial flora and fauna, in Japan.
Matched MeSH terms: Water Pollution, Radioactive/statistics & numerical data*
Multivariate statistical techniques such as multivariate analysis of variance (MANOVA) and discriminant analysis (DA) were applied for analyzing the data obtained from two rivers in the Penang State of Malaysia for the concentration of heavy metal ions (As, Cr, Cd, Zn, Cu, Pb, and Hg) using a flame atomic absorption spectrometry (F-AAS) for Cr, Cd, Zn, Cu, Pb, As and cold vapor atomic absorption spectrometry (CV-AAS) for Hg. The two locations of interest with 20 sampling points of each location were Kuala Juru (Juru River) and Bukit Tambun (Jejawi River). MANOVA showed a strong significant difference between the two rivers in terms of heavy metal concentrations in water samples. DA gave the best result to identify the relative contribution for all parameters in discriminating (distinguishing) the two rivers. It provided an important data reduction as it used four parameters (Zn, Pb, Cd and Cr) affording 100% correct assignations. Results indicated that the two rivers were different in terms of heavy metals concentrations in water, and the major difference was due to the contribution of Zn. A negative correlation was found between discriminate functions (DF) and Cr and As, whereas positive correlation was exhibited with other heavy metals. Therefore, DA allowed a reduction in the dimensionality of the data set, delineating a few indicator parameters responsible for large variations in heavy metal concentrations. Correlation matrix between the parameters exhibited a strong evidence of mutual dependence of these metals.
The bioaccumulation of organochlorines (OCs) in the muscle tissue of sea-run (anadromous) and freshwater-resident (fluvial) white-spotted charr (Salvelinus leucomaenis) was determined to assess the ecological risk related to intraspecies variations in diadromous fish life history as they migrate between sea and freshwater. Generally, there were significant correlations between the accumulation of OCs such as DDTs, HCB, HCHs and CHLs. In addition, various biological characteristics, such as total length (TL), body weight (BW) and age, and number of downstream migration (NDM) were correlated. A positive correlation occurred between the lipid content and the OC concentrations. Close linear relationships were found between TL, BW and NDM and the lipid content. Although they are both the same species, the OCs concentrations in the anadromous fish were significantly higher than those in the fluvial individuals. These results suggest that anadromous S. leucomaenis have a higher ecological risk for OCs exposure than the fluvial fish.
Matched MeSH terms: Water Pollution, Chemical/statistics & numerical data
Industrial, and municipal wastes are part of the main sources of environmental hazards as well as groundwater and surface water pollutions. If not well composed, treated, and safely disposed, it could permeate through the subsurface lithologies by reaching down to the underground water aquifers, particularly in zones of unprotected aquifer units. Pollutants, most especially the landfills leachates that encompassed organic contaminants, ammonia, nitrates, total nitrogen, suspended solids, heavy metals and soluble inorganic salts, i.e., soluble nitrogen, sulphur compound, sulphate and chlorides, could posed undesirable environmental impacts due to inappropriate disposals that may give rise to gaseous fumes and leachate formations. An electrical resistivity geophysical technique utilizing the RES2D no-invasive, cost-effective and rapid method of data collection was integrated with the 3D Oasis Montaj software to approximate the volume of the generated rectangular prism model of the contaminants delineated from mixtures of the industrial, and municipal wastes plumes to be 312,000 m 3.
Field and laboratory studies were conducted to estimate concentration of potential contaminants from landfill in the underlying groundwater, leachate, and surface water. Samples collected in the vicinity of the landfill were analyzed for physiochemical parameters, organic contaminants, and toxic heavy metals. Water quality results obtained were compared from published data and reports. The results indicate serious groundwater and surface water contamination in and around the waste disposal site. Analysis of the organic samples revealed that the site contains polychlorinated biphenyls and other organo-chlorine chemicals, principally chloro-benzenes. Although the amount of PCB concentration discovered was not extreme, their presence indicates a potentially serious environmental threat. Elevated concentrations of lead, copper, nickel, manganese, cadmium, and cobalt at the downgradient indicate that the contamination plume migrated further from the site, and the distribution of metals and metals containing wastes in the site is nonhomogeneous. These results clearly indicate that materials are poorly contained and are at risk of entering the environment. Therefore, full characterization of the dump contents and the integrity of the site are necessary to evaluate the scope of the problem and to identify suitable remediation options.
Rhodovulum sulfidophilum was grown in settled undiluted and nonsterilized sardine processing wastewater (SPW). The aims were to evaluate the effects of inoculum size and media on the biomass production with simultaneous reduction of chemical oxygen demand (COD).
AIMS: Rhodovulum sulfidophilum was grown in sardine processing wastewater to assess growth characteristics for the production of bacterial biomass with simultaneous reduction of chemical oxygen demand.
METHODS AND RESULTS: Growth characteristics were compared in diluted and undiluted, settled and non-settled wastewater growing in anaerobic light and aerobic dark conditions; and also at different agitation speeds. The highest biomass (8.75 g l(-1)) and a reduction in chemical oxygen demand of 71% were obtained in unsettled, undiluted wastewater after 120 h culture with 15% inoculum. In settled wastewater, highest biomass (7.64 g l(-1)) and a COD reduction of 77% was also obtained after 120 h. Total biomass was higher (4.34 g l(-1)) after 120 h culture in anaerobic light compared to (3.23 g l(-1)) in aerobic dark growth.
CONCLUSIONS, SIGNIFICANCE AND IMPACT OF THE STUDY: Better performance, mean of total biomass (6.97 g l(-1) after 96 h), total carotenoids (4.24 mg g(-1) dry cell from 24 h) and soluble protein (431 microg ml(-1) after 96 h) were obtained from aerobic dark culture at 300 rev min(-1). The COD reduction, however, was lower (69%) after 96 h culture. Thus, the benefits in the production of bacterial biomass in non-sterilized sardine processing wastewater with the reduction of chemical oxygen demand could be achieved.