WATER AND WASTEWATER
Year:2016 | Volume:27 | Issue:3 (103)|Papers Count:9

Removal of copper from aqueous solutions was investigated using manganese dioxide nanoparticles as a new and suitable adsorbent. For this purpose, manganese dioxide nanoparticles were synthesized using the cathode electrochemical deposition method and the effects of pH, contact time, MnO2 concentration, and copper concentration on copper removal efficiency were investigated in a batch system. Scanning electron microscope (SEM), XRD, and FTIR were used to characterize the synthesized manganese dioxide nanoparticles. Results showed that nanoparticle diameters ranged from 30 to 50 nm and that a copper adsorption efficiency of bove 96% percent would be achieved at an optimum pH of 7. It was found that increasing the copper concentration and reducing adsorbent dosage led to enhancements in adsorption capacity but slight reductions in adsorption efficiency. Experimental data also indicated that copper adsorption fitted the Freundlich model with an adsorption capacity of above 169 mg.g‒1 and that it obeyed a pseudo-second order kinetic equation. It was concluded that manganese dioxide nanoparticles may be used as a suitable adsorbent with a high potential for the removal of copper from aqueous solutions.

In this study, the electro spinning method was used to manufacture polyacrylonitrile (PAN) nanofibers. The procedure involved spinning a solution of 10%wt PAN in dimethyl formamide (DMF) in an electric field of 21 kV and with a tip to collector distance of 16 cm. The nanofibers thus obtained had an average diameter of 100 nm. Then, scanning electron microscopy (SEM) images were used to investigate the morphology of the nanofibers. In the next step, the nanofiner surface was modified with diethylenetriamine and FTIR was employed to ensure the presence of amines on the nanofiber surface. The functionalized nanofibers were then used for the first time to adsorb ions of cadmium (a heavy metal with industrial applications) and its adsorption capacity was evaluated. The chemical charactristics of the nanofibers and the effects of such parameters as pH, temprature, and contact time on adsorption efficiency were investigated. The results showed that maximum adsorption efficiency was achieved within the first 10 minutes of the process at a pH in the range of 5‒7 when about 80% of the cadmium ions were adsorbed. Moreover, only slight changes were observed with longer contact times or with increasing temperature. Finally, the adsorption data fitted well with the Langmuir isotherm.

Removing pathogens from water to prevent the spread of water-borne diseases is of great importance. The present study was designed and implemented to investigate the effects of electric current on Staphylococcus aureus bacteria, Escherichia coli, and the Candida albicans yeast. For this purpose, nutrient Agar and Sabouraud Dextrose Agar were used as the media to activate the bacteria and yeasts, respectively. Part of the colony from each medium was taken into an experimental tube to prepare suspensions. The number of microorganisms in 1 cc of each suspension was calculated at time zero and the suspension was poured into the electrolysis container. Samples of the microbial suspensions were taken in triplicates after 5, 10, 15, 20, 25, and 30 minutes and transferred into the culture medium. Measurements were recorded upon completion of the incubation period. It was found that the bacteria and the yeast could be killed using a voltage of 16.5 v and a current of mA such that the number of E. coli decreased significantly after 25 and 30 minutes. The results indicate that each microorganism species exhibits its own charateristic sensitivity to electrical current so that increased voltage and/or prolonged exposure to the current will have a higher inhibitory effect on the growth of most species of microorganism.

Wastewater is nowadays a major concern in human societies that has encouraged many scientists to direct their efforts at developing new and efficient methods for its treatment. Most of the methods so far proposed or developed are time-consuming and/or cost intensive. Microbial Fuel Cell (MFC) is a new technique that is capable of direct conversion of the chemical energy due to wastewater treatment into electrical energy. Most treatment processes commonly release sulfide ions that are highly toxic and deterimental. In the method proposed in this study, the sulfide ions generated during wastewater treatment were used as electron donors in the anaerobic compartment of a dual chamber microbial fuel cell and the removal of different concentrations of sulfide ions and the power generated were studied. For this purpose, the effects of three different concentrations of sulfide (0.1, 0.8, and 1.5 g.l‒1) on MFC performance were explored to find that a sulfide removal efficiency of 98% could be achieved after 21h, 6 days, and 10 days, respectively. Also, cyclic voltammetry was used for the detection of electrochemical activity by microorganisms and sulfide oxidation in the anode chamber.

Dye-bearing wastes pose serious risks to and leave harmful effects on the environment. Increasing wastewater color intensity leads to reduced light reaching the aquatic environment, which adversely affects the life and growth of aquatic plants and invertebrates. Among the many methods available for dye removal from wastewater, membrane separation, oxidation, coagulation, and anaerobic treatment are more common but they are all costly and involve complex processes. Bio sorption, in contrast, enjoys both ease of application and simple design so that it is widely used for removing dyes, heavy metals, and phenolic compounds from both water and wastewater. In this paper, the ability of citrulluscolosynthis ash as a bioadsorbent for the removal of reactive red dye is investigated for the first time. Sodium hydroxide is also used to modify the plant ash surface which expectedly enhances its dye removal efficiency. Measurements and removal levels are determined using a UV-vis spectrophotometer. Finally, the effects of pH, adsorbent dosage, dye concentration, and reaction time on dye removal efficiency are also explored. Results show that the optimum conditions to achieve maximum dye removal are as follows: A pH level of 2, an adsorbant dosage of 1.75 g l-1, an initial concentration equal to 90 mg L-1, and A reaction time of 70 min. Adsorption isotherm is found to obey the Ferundlich isotherm. Also, an adsorption capacity of 36 mg g‒1 is achieved under the best conditions. It may thus be concluded that modified citrulluscolosynthis ash can be used as an effective adsorbent to treat colored wastewaters.

Petroleum compounds are pollutants that most commonly occur in soils around oil refineries and that often find their ways into groundwater resources. Phytoremediation is a cost-effective alternative to physicochemical methods for oil-contaminated soil remediation, where feasible. In this study, a greenhouse experiment was conducted to evaluate the phytoremediation of oil-contaminated soils around Isfahan Oil Refinery. Four different plants (namely, sorghum, barley, agropyron, and festuca) were initially evaluated in terms of their germ inability in both contaminated and control (non-contaminated) soils. Sorghum and barley (recording the highest germ inability values) were chosen as the species for use in the phytoremediation experiments. Shoot and root dry weights, total and oil-degrading bacteria counts, microbial activity, and total concentrations of petroleum hydrocarbons (TPHs) were determined at harvest 120 days after planting. A significant difference was observed in the bacterial counts (total and oil-degrading bacteria) between the planted soils and the control. In contaminated soils, a higher microbial activity was observed in the rhizosphere of the sorghum soil than in that of barley. TPHs concentration decreased by 52%‒64% after 120 days in contaminated soil in which sorghum and barley had been cultivated. This represented an improvement of 30% compared to the contaminated soil without plants. Based on the results obtained, sorghum and barley may be recommended for the removal of petro-contaminants in areas close to Isfahan Oil Refinery. Nevertheless, caution must be taken as such cultivated lands may need to be protected against grazing animals.

Wastewater systems form an important urban infrastructure that are used for the collection and treatment of wastewater for return into the environment or water reuse. The sewers network in this system forms its most important component, any failure in which may lead to adverse consequences and disruption in urban life. Proper functioning of a sewers network depends on its operation and maintenance (O & M) program that requires timely inspections to identify the high risk sewers with any likelihood of failure in order to gurantee the sustained and sound performance of the whole network. In this study, the Bayesian network is used to develop a model for calculating failure event probability in wastewater collection systems. Given the capabilities of the Bayesian network and the characteristic features of the sewers network, the proposed model is capable of predicting likely failure events. The procedure used for model implementation consists of the following four main steps: preparation of model inputs, training the Bayesian network, validation of the trained network, and receiving output results. To illustrate the application of this method, part of Tehran wastewater collection system is selected as a case study and failure probabilities are calculated. Based on the model results, Tehran sewers can be divided into five categories priotized according to inspection and maintenance requirements. The results indicate that the probability of failure for most of the existing sewers is very low and low (37%) or moderate (60%) due to the newly annexed sewers in the collection system.

Groundwater is a major source of water supply for domestic, agricultural, and industrial uses; hence, its quality modeling is an important task in hydro-environmental studies. While many data-based models have been developed for this purpose, the performance of such data-based models can be drastically enhanced if they are based on temporal and spatial pre-processing. In this study, geostatistics tools (e.g., Co-Kriging), as spatial estimators, and self-organizing map (SOM), as a clustering technique, were employed in conjunction with Adaptive Neuro-Fuzzy Inference System (ANFIS) for the temporal forecasting of such quality parameters as electrical conductivity (EC) and total dissolved solids (TDS) of the groundwater in Ardabil Plain. Using the results thus obtained, the impact of spatial data clustering was also investigated on the same parameters. The results showed that, if propoer input data are selected, the proposed spatial clustering technique is capable of imporving groundwater quality forecasts made by ANFIS.

Land use change is a gradual process that entails dire consequences for groundwater quality and quantity. Quantitative changes in groundwater can be usually monitored by controlling the annual groundwater balance. Monitoring qualitative changes in groundwater, however, is both time-consuming and expensive. DRASTIC and SINTACS models exploit aquifer properties to predict its vulnerability. In this study, aquifer vulnerability assessment was performed by the DRASTIC & SINTACS models for future land use management in Khovayes, southwest Iran. The DRASTIC Model is based on hydrological and hydrogeological parameters involved in contaminant transport. SINTACS parameters are the same as those of the DRASTIC model, except that weighting and ranking the parameters are more flexible. Once vulnerability maps of the study region had been prepared, they were verified against the nitrate map. A correlation coefficient of 0.4 was obtained between the DRASTIC map and the nitrate one while the correlation between the SINTACS and the nitrate maps was found to be 0.8. Map removal and single-parameter sensitivity analyses were carried out, which showed the southwestern stretches of the study area as the region with the highest risk of vulnerability.