Iron(III)-poly(hydroxamic acid) resin complex has been studied for its sorption abilities with respect to arsenate and arsenite anions from an aqueous solution. The complex was found effective in removing the arsenate anion in the pH range of 2.0 to 5.5. The maximum sorption capacity was found to be 1.15 mmol/g. The sorption selectivity showed that arsenate sorption was not affected by chloride, nitrate and sulphate. The resin was tested and found effective for removal of arsenic ions from industrial wastewater samples.
Matched MeSH terms: Water Pollution, Chemical/prevention & control*
Population in urban centers in Kenya is increasing rapidly due to rural urban migration in search of better paying jobs. This migration has resulted in unauthorized settlements in the various urban centers. The income per capital of these people is less than a dollar a day. The amount of money is inadequate for survival and this has resulted into cultivating on open grounds for food crops. Unfortunately, these slums have come up along rivers, which carry, wastewater from household and industries. This wastewater is rich in heavy metals and the inhabitants of these areas use this contaminated water for irrigating their crops. The food crops from such areas have very high levels of heavy metals. The present study has screened Zea mays, Commelina bengalensis and Amaranthus hybridus for their ability to bioaccumulate these metals from contaminated soils using atomic absorption spectrophotometer (AAS). The results obtained showed that the C. bengalensis has high potential for removal of Cu, Pb and Cd metals as compared to the Zea mays and Amaranthus hybridus even though, results showed that C. bengalensis has a low potential for the removal of Zn as compared to Zea mays and Amaranthus hybridus.
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.
This study is the first report on the occurrence of Giardia and Cryptosporidium (oo)cysts in recreational rivers water from Malaysia. It was carried out in water samples at two rivers, 'Sungai Congkak' and 'Sungai Batu', located in Selangor State. The occurrence of both Giardia lamblia and Cryptosporidium parvum (oo)cysts was higher in Sungai Congkak (50% or 15/30 and 10% or 3/30 respectively) than Sungai Batu (16% or 5/30 and 3.3% or 1/30 respectively). The mean density of cysts/L was 0.72 in Sungai Congkak and 0.023 in Sungai Batu, and that of oocysts/L was 0.023 in Sungai Congkak and 0.0033 in Sungai Batu, showing that the occurrence of Giardia was higher and more frequent than Cryptosporidium in both rivers. Sungai Congkak also showed higher faecal coliforms count (ranging from 0.48x10³ to 73x10³ CFU/100 mL) than Sungai Batu (0.41x10³ to 16x10³ CFU/100 mL). On the other hand, the Giardia and Cryptosporidium (oo)cysts and faecal coliforms were more concentrated at the downstream station, followed by midstream and upstream stations which might be due to human factors where settlements and recreation areas were located around and between midstream and downstream stations. The (oo)cysts and faecal coliforms also increased during public holidays due to the significantly higher number of visitors (bathers) compared with the week days. All the parameters (physical, faecal coliforms and rainfall) did not show consistent significant correlation (based on r values of Pearson correlation analysis) with both protozoa, therefore these parameters are not suitable as indicator for the presence of Giardia and Cryptosporidium (oo)cysts in both rivers.
Water from La Pampa, Argentina, was used for washing and cooking rice to examine the in-situ impact of using naturally-contaminated water for food preparation on the elemental dietary intake. Whilst washing with the control tap water (28 μg/L As) reduced the concentration of As in rice by 23%, the use of different well waters (281-1144 μg/L) increased As levels significantly (48-227%) in comparison with the original concentration in the rice (0.056 µg/g). Cooking the rice at a low water-to-rice ratio (2:1) using modern methods increased the levels of As in the cooked samples by 2-3 orders of magnitude for both pre-washed and un-washed rice. Similar trends were observed for vanadium. Although the levels of manganese, iron, copper, zinc and molybdenum in rice were reduced during washing and cooking for most water samples, the molybdenum concentration in the cooked rice doubled (2.2-2.9 µg/g) when using water containing >1 mg/L Mo.
Water pollution is a critical management issue, with many rivers and streams draining urban areas being polluted by the disposal of untreated solid waste and wastewater discharge, storm water and agricultural runoff. This has implications for biodiversity, and many rivers in the developing world are now considered compromised. We investigated benthic macroinvertebrate community structure and composition in relation to physico-chemical conditions of the water column and sediments. The study was conducted in an Austral catchment subject to both urban and agricultural pollutants in two different seasons. We assessed whether sediment characteristics were more important drivers of macroinvertebrate community composition than water column characteristics. We expected clear differences in macroinvertebrate community composition and in the associated community metrics due to distinct flow conditions between the two seasons. A combination of multivariate analyses (canonical correspondence analysis (CCA)) and biological indicator analysis were used to examine these patterns. Chironomidae was the most abundant family (>60%) in the upper mainstem river and stream sites. Stream sites were positively associated with CCA axis 2, being characterised by high turbidity and lower pH, salinity, phosphate concentration, channel width and canopy cover. Canopy cover, channel width, substrate embeddedness, phosphate concentration, pH, salinity and turbidity all had a significant effect on macroinvertebrate community composition. Using CCA variation partitioning, water quality was, however, a better predictor of benthic macroinvertebrate composition than sediment chemical conditions. Furthermore, our results suggest that seasonality had little effect on structuring benthic macroinvertebrate communities in this south-eastern zone of South Africa, despite clear changes in sediment chemistry. This likely reflects the relative lack of major variability in water chemistry compared to sediment chemistry between seasons and the relatively muted variability in precipitation between seasons than the more classic Austral temperate climates.
This study evaluates the impact of anthropogenic activities on the Shahrood River using water physico-chemical variables and macroinvertebrates data sets obtained over a period of 12 months between February 2012 and February 2013 at 8 sampling sites. Biotic indices i.e. FBI and BMWP based on macroinvertebrates and physico-chemical indices (MPI, HPI and NSF-WQI) were employed to evaluate the water quality status in connection with natural- and human-induced pressures. Based on physico-chemical indices, water quality was categorized as low polluted level and it is suitable for drinking purposes. The water quality based on biotic indices was related to the anthropic activities; a clear deterioration of the water quality was observed from upstream to downstream sites. The water quality along the river changed from very good (class I; reference sites) to good (class II; midstream sites) and turned into moderate (class III) and poor (class IV) quality (downstream sites). These findings indicate that biotic indices are more powerful indicators in assessing water quality than physico-chemical indices. Allocapnia, Glossosoma and Hesperoperla were exclusively related to least disturbed sites, and Naididae, Orthocladiinae and Ecdyonurus were found in sites showing notable degradation. Our results recommended that the use of macroinvertebrates could be employed as a cost-effective tool for biomonitoring and controlling of polluted riverine ecosystems in the Middle East. Finally, the results from this study may be useful not only for developing countries, but also for any organization struggling to use macroinvertebrate based indices with restricted financial resources and knowledge.
Matched MeSH terms: Water Pollution, Chemical/statistics & numerical data
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.
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 Pollution, Chemical/statistics & numerical data*
The bioremediation of polluted groundwater, wastewater aeration pond and biopond sites was investigated using bacteria isolated from these sites located at the oil refinery Terengganu Malaysia. Out of 62 isolates, only 16 isolates from groundwater (8) and wastewater aeration pond (3) and biopond (5) were chosen based on growth medium containing 1% (v/v) Tapis crude oil. Only four isolates; Acinetobacter faecalis, Staphylococcus sp., Pseudomonas putida and Neisseria elongata showed percentage biodegradation of crude oil more than 50% after 5 days using Mineral Salts Medium (MSM). The effect of physical parameters (temperature, pH and agitation) on growth by all four strains showed a maximum growth in MSM medium with 1% Tapis crude oil at 37 degrees C with pH 7 and agitation of 130 rpm.
Matched MeSH terms: Water Pollution, Chemical/analysis*
In this study, the ranges of pollutants found in the soft tissues of Perna viridis collected from Kg. Masai and Kg. Sg. Melayu, both located in the Straits of Johore, were 0.85-1.58 μg/g dry weight (dw) for Cd, 5.52-12.2 μg/g dw for Cu, 5.66-8.93 μg/g dw for Ni and 63.4-72.3 μg/g dw for Zn, and 36.4-244 ng/g dry weight for ∑PAHs. Significantly (p < 0.05) higher concentrations of Cd, Cu, Ni, Zn and ∑PAHs in the mussels were found in the water of a seaport site at Kg. Masai than a non-seaport site at Kg. Sg. Melayu population. The ratios of low molecular weight/high molecular weight hydrocarbons (2.94-3.42) and fluoranthene/pyrene (0.43-0.45) in mussels from both sites indicated the origin of the PAHs to be mainly petrogenic. This study has demonstrated the utility of using the soft tissues of P. viridis as a biomonitor of PAH contamination and bioavailability in the coastal waters of Peninsular Malaysia.
Matched MeSH terms: Water Pollution, Chemical/statistics & numerical data
Bioretention systems have been implemented as stormwater best management practices (BMPs) worldwide to treat non-point sources pollution. Due to insufficient research, the design guidelines for bioretention systems in tropical countries are modeled after those of temperate countries. However, climatic factors and stormwater runoff characteristics are the two key factors affecting the capacity of bioretention system. This paper reviews and compares the stormwater runoff characteristics, bioretention components, pollutant removal requirements, and applications of bioretention systems in temperate and tropical countries. Suggestions are given for bioretention components in the tropics, including elimination of mulch layer and submerged zone. More research is required to identify suitable additives for filter media, study tropical shrubs application while avoiding using grass and sedges, explore function of soil faunas, and adopt final discharged pollutants concentration (mg/L) on top of percentage removal (%) in bioretention design guidelines.
Matched MeSH terms: Water Pollution/prevention & control*
With the development of Chinese economy, more and more attention has been paid to environmental protection, the implementation of water price policy affects economic and environmental changes in China. This paper analyzes the impact of water price policy on agricultural land use and the scale of water pollution discharge in 240 cities in China between 2001 and 2017, by including data from China Urban Statistical Yearbook and China Land & Resources Almanac. The theoretical analysis of this study indicates that the optimal scale of pollution depends on the local initial endowment, economic investment capital and the marginal cost of environmental pollution caused by government's economic activities. Furtherly, the economic activities have a worsening impact on environmental pollution, but when the government implements environmental protection and water price policy measures in response to environmental pollution caused by economic activities, it has a significant impact on the decline in the scale of pollution. The government has promoted the pollution suppression model in the formulation of water prices, which has internalized the external cost of pollution in economic activities and can effectively reduce the scale of agricultural water pollution discharge.