WATER AND WASTEWATER
Year:2010 | Volume:21 | Issue:1 (73)|Papers Count:12

In this paper, a mathematical model is presented for studying the unsteady flow, aggradation, and degradation in alluvial channels. The one-dimensional, unsteady, gradually varied flow equations (saint-venant equations) and the sediment continuity equation are solved numerically using the second-order, explicit finite difference two-step scheme developed by Lax Wendroff- Richmayer. All the three governing equations are solved simultaneously during any step so that the water flow and sediment continuity equations are coupled. The computed results are compared with the experimental results obtained in a laboratory flume. Also the Aland River data in Badalan Station with different sediment discharge equations are used for simulating the unsteady flow model bed changes and hydraulic parameters for different sections and time steps. Results show that the model is capable of simulating unsteady open channel flow, bed load transport, aggradation and degradation satisfactorily.

Bends along open channels always pose difficulties for water transfer systems. One undesirable effect of bends in such channels, i.e. separation of water from inner banks, was studied. For the purposes of this study, the literature on the subject was first reviewed, and a strongly-curved open channel was designed and constructed on the laboratory scale. Several tests were performed to evaluate the accuracy of the lab model, data homogeneity, and systematic errors. The model was then calibrated and the influence of curvature on flow pattern past the curve was investigated. Also, for the first time, the influence of separation walls on flow pattern was investigated. Experimental results on three strongly-curved open channels with a curvature radius to channel width ratio of 1.5 and curvature angles of 30o, 60o, and 90o showed that, in all the cases studied, the effect of flow separation could be observed immediately after the curve. In addition, the greatest effect of flow separation was seen at a distance equal to channel width from the bend end. In the presence of middle walls and flow separation, the effect of water separation reduced at the bend, especially for a curvature of 90o.

MCM-41 includes a group of silica mesopore components with a high surface area whose adsorption capacities can be enhanced by modifying their surface with amine groups. In this study, the modified NH2-MCM-41 was used to investigate adsorption of Cd (II), Ni (II) and Pb (II) ions in a mixture of aqueous solutions. All the experiments were carried out in a batch system containing a solution of metal ions to study the effects of the initial metal concentration, adsorbent dosage, contact time, and solution pH. The results showed that optimum adsorption would be achieved at pH 5 and that adsorption capacity increased with increasing metal ion concentration but with decreasing adsorbent dosage. Experimental data were fitted with Langmauir and Freundlich models. Maximum adsorption capacities for Ni (II), Cd (II), and Pb (II) were 12.36, 18.25 and 57.74 mg/g, respectively. The results indicate that NH2-MCM-41 is an effective adsorbent for Ni (II), Cd (II) and Pb (II) ions with a high adsorption capacity.

In this research, a system was designed and constructed that included an efficient, economically feasible method for adjustable, in-situ generation of hydrogen and carbon dioxide coupled with a packed bed bioreactor. The system was subsequently tested for its ability to remove nitrate from drinking water. The major objective was to develop an economical technology with a high selectivity for nitrate ions but causing minimum changes in other drinking water quality parameters. Hydrogen (as the electron donor) and carbon dioxide (as the carbon source for autotrophic denitrifier bacteria) were generated in a cost-effective way by applying a very low DC voltage (5-10 volts) in an electrochemical reactor using methanol electrolysis. The gases were injected into a denitrification bioreactor inoculated with denitrifier bacteria which are naturally present in water. Finally, the system was put to a pilot operation to remove nitrate from a nitrate-contaminated well (a typical contamination range of 120 mg/L as NO3-) in Tehran aquifer for a period of 160 days. The results showed that the system was capable of achieving a nitrate removal efficiency of 95% with an HRT of 2-5 hr while its power consumption was minimal and only required the two harmless gases, hydrogen and carbon dioxide, to be injected without any chemical additions.

The present paper investigates the feasibility of treating the effluent from Southern Pars Gas Refinery by electrocoagulation using aluminum electrodes. Al3+ species and hydrogen ions have been shown to evolve at both Al-based cathode and anode. In this study, the effects of such operating parameters as pH, Na2SO4, poly aluminum chloride dosage, and current density on organic pollutant and COD removals have been studied. The optimum operating range for each operating variable was experimentally determined. Based on the results, organic pollutants and COD removal rates showed to increase by increasing current density, poly aluminum chloride, and Na2SO4.The highest removal efficiency was achieved at pH 7. Results also revealed that more than 95% of the COD was removed when the effluent was treated for 90 min at a current density of 40 mAcm-2. Power consumption for this removal level was measured to be 19/48 kwh per kg COD removal.

Propylene glycol is an organic compound which has wide applications in the pharmaceutical, cosmetics, chemical, and food processing industries. Propylene glycol is readily released into surface and ground waters and the neighboring soils via industrial wastewater effluents posing many health and environmental hazards. The main purpose of this study was to determine the efficiency of fixed bed activated sludge reactor for propylene glycol removal from synthetic wastewater. The lab scale reactor consisted of a cubic Plexiglas aeration tank with a total volume of 16 liters, 12 liters for aeration and 4 liters for settling. 25% of the aeration tank was filled with media as fixed bed for the biofilm to form. To evaluate the optimum efficiency of the reactor under variable organic loadings, the organic loading was increased in two consecutive stages: first by HRT depletion, and second by increasing COD concentration. The COD removal efficiencies obtained for hydraulic retention times of 8, 6, 4 and 2 hours and at an influent COD concentration of 500 mg/L were 95.86, 95.12, 93.96, and 79.08 %, respectively. In the fallowing stages and based on the results obtained from the first stage, a constant HRT of 6 hrs and COD concentrations of 1000, 1500, 2000 and 2500 mg/L were experimented. The removal efficiencies for the above concentrations were 95.95, 88.54, 75.95, and 35.69%, respectively. The results from this study indicate that the fixed bed activated sludge bioreactor satisfactorily capable of removing propylene glycol.

In this study, dried waste activated sludge from a municipal wastewater treatment plant was used for Cd (II) ion adsorption with and without pretreatment. Waste activated sludge was treated with 1% Hydrogen peroxide. Cd (II) adsorption was investigated at an initial Cd (II) concentration of 50 mgL−1 with an adsorbent particle size of 50-70 mesh in erlenmeyer flasks used as batch reactors. The pseudo-first and pseudo-second order kinetic models were used to determine the correlation among the experimental data. The results showed that pretreatment of waste sludge with H2O2 increased equilibrium adsorption capacity. The equilibrium adsorption capacity values obtained for waste activated sludge with and without pretreatment were 39.84 and 20.2 mgg−1, respectively, which increased with increasing solution pH. The correlation coefficients obtained for pseudo-first (R2>0.87) and pseudo -second (R2>0.96) order kinetic models showed that the latter model better described the experimental data on both types of treated and untreated activated sludge than the latter.

Removal of toxic heavy metals from wastewater is an important environmental challenge. In this work, the Sheep Gut Waste (SGW) is used as a low-cost adsorbent for the removal of Pb2+, Fe3+, and Cu2+ from aqueous solutions and industrial wastewaters. Bath experiments were used to determine the best adsorption conditions. The effects of contact time, pH, initial metal concentration, and amount of adsorbent on the adsorption process were studied. The time required for the removal of metal ions was about two hour. Effective removal of metal ions was demonstrated at pH values of 4-8. The maximum adsorption capacities of Cu–SGW, Fe-SGW and Pb-SGW were 9.76 mmol g-1, 11.19 mmol g-1, and 3.01 mmol g-1, respectively. Metal adsorption onto SGW was evaluated by Langmuir and Freundlich isotherms. Results indicate that the Langmuir isotherm model is the most suitable one for the adsorption process using sheep gut waste.

A vast variety of pesticides are used for agricultural pests in Iran. The release of these persistent organic pollutants. into water supplies leaves adverse effects on both the environment and public health. Advanced oxidation processes have been used recently for pesticide removal. In this research, the combined UV/O3 process has been investigated for the removal of organophosphorus pesticides (Diazinon, Chlorpyrifos), Carbamate pesticides (carbaryl). In this survey, samples have been prepared by adding given concentration (1, 5, 10, 15, 20 mg/L) of the pesticides to deionized water. The samples at separation periods were exposed to the combined UV/O3 (UV=50-200 Wm-2 and O3=1g hr-1) in a bath reactor at different pH levels (6, 7, 9) and for different contact times (0.5, 1, 1.5, 2 hr) and the removal efficiencies were determined. Residual concentrations were determined using GC/MS/MS and HPLC. Based on the results, increasing pH reduced pesticide concentration and increased contact time had a direct effect on enhancing removal efficiency. The combined UV/O3 process was found to have a high efficiency (>80%) in degrading both halogenated Organophosphorus(Chlorpyrifos) and non- halogenated Organophosphorus (Diazinon) pesticides. Its removal efficiency for degrading carbamate pesticide (Carbari) was found to be >90%. Based on our results, this method may be suggested for the removal of pesticides from aqueous solutions.

It is essential to use new technologies in water treatment plants to reach high quality potable water. The three-layer filter is one such new technology. In this paper, we will present the results of a laboratory investigation on the pilot scale to evaluate the performance of mineral garnet in multi-layer filters and to compare it with the two-layer blank filter in the removal of turbidity and biological organisms. All experiments were performed using standard methods and the results were evaluated by statistical tests. In the good padding situation and when using water and air backwash system, the removal efficiencies obtained by the multi-layered filter for turbidity, diatome, algae, and nematode were 92.4, 97.8, 97.6, 94.4, and 96.5%, respectively. The removal efficiencies achieved by the two-layer blank filter were 88.8, 85.2, 86.7, 80.5, and 72.1%, respectively. Water and wastewater companies, consultants and manufacturers are recommended to consider the multi-media filters as a preferrable alternative for designing new water treatment plants or for renewing existing plants.

Water demand forecasting is one of the most important concerns for managers of water supply systems as the results can affect many decisions. Daily demand forecasting cannot be usually accomplished by mathematical functions because it is a complicated function of many variables. In this paper, neural networks are used to predict Tehran daily water demand. At first, weather data from three Tehran weather stations are weighted via the Thissen method and the effective input data parameters are selected using the regression of the weighted effective weather and consumption data. The effective parameters include daily average temperature, relative humidity, and last day to last week (7 days) as well as last year water consumptions. Three different ANN models are built in this stage: a three-layer model with one hidden layer including seven neurons, a four-layer model with two hidden layers including seven neurons in the first and four neurons in the second hidden layer, and a RBF three-layer model with twenty neurons in the middle layer. Comparison of the results of ANN with neuro-fuzzy and time series models shows that ANN models have a higher capability for predicting Tehran daily water consumption. Among these models, the ANN perceptron 3-layer model with a nonlinear output produced more accurate results.