WATER AND WASTEWATER
Year:2010 | Volume:21 | Issue:2 (74)|Papers Count:15

Horseradish peroxidase was successfully encapsulated in calcium alginate for phenol removal. The optimum gelation condition was found to be 0.75%w/v of sodium alginate solution and 4.5% w/v of calcium chloride hexahydrate. Upon immobilization, the pH profile of enzyme activity changed as it showed a higher relative value in basic and acidic solutions. It was also observed that enzyme activity retention of encapsulated HRP was independent of enzyme concentration. Besides, for each phenol concentration, there would be an enzyme concentration beyond which it had no significant effect on phenol removal. Investigation of phenol removal with time for both encapsulated and free enzymes showed that the encapsulated enzyme had a lower efficiency compared to the same concentration of the free enzyme; however, the capsules were reusable up to four cycles without any changes in their retention activity. The optimum ratio of hydrogen peroxide/phenol was found to depend on phenol concentration and that it varied from 0.94 to 1.15 for phenol concentrations between 2-10 mM.

The main objective of this study was to investigate the treatment of distillery vinasse through the integrated process of ozone oxidation and Granular Activated Carbon (GAC) in a continuous process. The continuous process was carried out both by each of the GAC and ozone processes alone and by the combination of the two in order to investigate the synergistic effects of the two modes on COD and color removal in the treatment of vinasse from laboratory ethanol production from cane molasses. The continuous processes were performed at an ozone generation rate of 240mg/h, GAC dose of 100g, and at room temperature (25°C). Color removal efficiency of O3 was higher than its COD removal from vinasse. The COD and color removal efficiencies of the O3 process were about 25% and 74%, respectively. Moreover, GAC/O3 process was found to negatively affect the synergy of COD and color removal efficiency from distillery vinasse. This negative effect decreased by increasing influent pH level. The results indicate that the initial Ph has a considerable effect on the three processes investigated.

In this study, the performance of an anaerobic baffled reactor (ABR Pilot 100 l and six compartments) for sulfate removal from the wastewater from Amirkabir Industrial Estate was investigated. The reactor was started with a hydraulic retention time (HRT) of 25 h at 35°C to be gradually reduced to 3.33 h. The best reactor performance was observed at a HRT of 4 h and a sulfate loading rate of 3.318 Kg SO4/m3.d at which the sulfate removal efficiency was 89.15%. In this condition, the highest sulfate removal was observed in the first compartment (69.08%) which had the lowest pH as acidogenesis and acetogenesis had taken place in earlier compartments. This result demonstrated that the sulfidogenesis occurred in the acidogenic phase. Maximum sulfate removal (66.11%) was obtained when temperature was reduced to 20°C (HRT of 4 h). Under the same conditions, the fourth compartment which had lowest pH level exhibited maximum sulfate removal percent (28.98%). This indicates that decreasing temperature leads to the acidogenic phase to shift toward the following reactor compartments. Also, these findings are a further indication of the ability of the acidogenic phase for sulfate removal.

Knowledge of petroleum leakage at oil refineries is vital for environmental study of water and soil pollution. Abadan Refinery is located between the Arvandrud and Bahmanshir rivers in the highly populated area of Abadan city. These rivers supply domestic, industrial, and agricultural water to Abadan city. During the war between Iran and Iraq, enormous volumes of oil and petroleum products leaked from storage tanks and pipelines at Abadan Refinery into the surrounding environment. The resulting pollution is a serious threat and a growing environmental concern for the region. In this work, twenty boreholes were dug to investigate petroleum leaks into the surrounding area both during and after the war. The thickness of petroleum floating on underground waters at the refinery was measured by sampling underground water over a period of one year along with measuring the piezometric heads of groundwater monitoring wells. Also, groundwater movement pattern at Abadan Refinery was determined by measuring the water table in each well over the same period. The results of sampling indicate that oil leaks were observed in just two wells; namely, wells No.3 and No.11. The results also show that the greatest portion of the oil spill in underground layers at Abadan Refinery was absorbed into clay soil.

Khuzestan Province accommodates the largest oil-fields with huge petroleum production in Iran. During the Persian Gulf war in 1991, more than 6-8 million gallons of oil was spilt in the Persian Gulf, the greatest amount of which was transported into Khuzestan soil. Thus, oil removal from contaminated soil by advanced technologies such as bioremediation seems to be of vital necessity. The aim of this study was to evaluate the effect of sewage-sludge application on bioremediation of oil-contaminated soil. Soil samples (5kg) were artificially contaminated with crude oil to a level of 1000 mg/kg. Sewage sludge treatments were applied at the 3 levels of 0, 100, and 200 gr/5kg soil in 3 replicates. The soils were kept in the normal moisture aerobic environment for 5 and 10 weeks. The soils were then analyzed for Hydrocarbon-degrading heterotrophic bacterial count. Oil extraction from the samples was accomplished using the oil Soxhlet extraction method and oil degradation was measured by GC chromatography. The results showed that the hydrocarbon-degrading and heterotrophic bacterial counts in all the treatments increased with time. Results indicate that heterotrophic bacterial population increased from 6×103 cfu/gr soil to 2×1010 cfu/gr soil. Also, C/N ratio decreased from 6 to 3. GC results indicated that all normal Alkanes and Isopernoids, i.e. Phytane and Pristane, decreased by 50-90 percent in all the treatments. It was also found that the application of sewage sludge at 100 gr/5kg soil to oilcontaminated soil leads to greater rates of biodegradation after 5 weeks. 

Sorption of 3 poisonous metal ions (Pb2+, Cd2+, Cr3+) in aqueous solutions by two phosphate sorbents under dynamic and static conditions was studied. Phosphate sorbents (MgNH4PO4. H2O, Mg3(PO4)2. 6H2O) were synthesized by known procedures. The resulting crystalline samples were analyzed for the contents of Mg2+, Pb2+, P, N using spectrophotometric and elemental analysis methods. Likewise, the amounts of Pb2+, Cd2+, Cr3+ in solutions were determined before and after the sorption process using the atomic absorption method. The relative standard deviations for Pb2+, Cd2+, Cr3+ were 4.7%, 2.17%, and 1.61% and the detection limits were 5mg/L, 0.05 mg/L, and 0.1 mg/L, respectively. The sorbents showed a high performance in the purification of contaminated solutions under static conditions. The sorption capacity levels of Mg3 (PO4)2. 6H2O and MgNH4 PO4. H2O were 9.8m.mol/gr and 8.9m.mol/gr for Pb2+; 10.5m.mol/gr and 9m.mol/gr for Cd2+; and 6.6m.mol/gr and 5.3m.mol/gr for Cr3+, respectively. Pb2+ , Cd2+, Cr3+. sorption by inorganic phosphate sorbents from solutions is associated with complicated chemical transformations of the sorbents. A proper account of these transformations allows for the sorption process to be optimized. The data on Pb2+, Cd2+, Cr3+ sorption under static conditions (24-h contact of Mg3 (PO4)2. 6H2O, MgNH4PO4. H2O, with solutions at 20°C) and under dynamic conditions were obtained and the sorption behaviors of the metal ions were investigated in response to the sorbents used. It was found that Mg3 (PO4)2. 6H2O was the best sorbent for Pb2+, Cd2+, Cr3+ under dynamic conditions.

In this study, we present an Artificial Neural Network (ANN) model for predicting COD and NH4+-N concentrations in landfill leachate from lab-scale landfill bioreactors. For this purpose, two different lab-scale systems were modeled. for neural network’s data obtained. In the first system, the leachate from a fresh-waste reactor was drained to a recirculation tank and recycled every two days. In the second, the leachate from a fresh waste landfill reactor was fed through a well-decomposed refuse landfill reactor, while the leachate from a welldecomposed refuse landfill reactor was simultaneously recycled to a fresh waste landfill reactor. The results indicate that leachate NH4+-N and COD concentrations accumulated to a high level in the first system, while. NH4+-N and COD removals were successfully carried out in the second. Also, average removal efficiencies in the second system reached 85% and 34% for COD and NH4+-N, respectively. Finally, the ANN’s results exhibited the success of the model as witnessed by the excellent agreement obtained between measured and predicted values.

It is more expensive to remove pollution from polluted groundwater than to prevent it; hence, tools are sought that help managers prevent groundwater pollution. One such tool is the aquifer vulnerability mapping which is used to specify the most vulnerable parts of an aquifer. In this research, the vulnerability map of the Hashtgerd aquifer was investigated. Irrigation return flow polluted by nitrate fertilizers, rural and urban wastewater, and industrial wastewater were found to be the main sources of pollution in the study area. The DRASTIC index was used and two methods of sensitivity analysis were performed on the results to ensure proper weights had been assigned to effective parameters. Then, Hashtgerd vulnerability map was compared with the relevant nitrate map to find a relatively acceptable tolerance. The results indicate that the highest vulnerability potential was of the medium class. The northern part of the study area has a high vulnerability potential while its southern stretches exhibit the lowest.

The proposed method by Shiono and Knight (SKM) is able to predict the lateral depth-averaged velocity and shear stress distribution in open channels. The SKM is needed to be calibrated. The calibration parameters are friction factor f, lateral eddy viscosity l, and secondary flow G. In practical problems, the assumption of l=0.07 from among these is considered as a standard value for the eddey viscosity. Thus, the accuracy of the depthavergad and the shear stress distributions using SKM will be subject to the determination of ¦ and G. In the present paper, we present the secondary flow cell pattern (G) and friction factor distribution (¦) in a straight prismatic triangular channel with a uniform roughness. The trial and error approach is used to define the best pattern of friction factor to produce the most appropriate results. The results of predicted depth-averaged velocity as well as shear stress distributions obtained from SKM as compared to measured values indicate that SKM can accurately predict the velocity and shear stress distributions if the two coefficients of ¦ and G are chosen based on accurate patterns.

This paper presents the solution of shallow water equations using the flux-difference splitting method. To handle more complex geometries, the governing equations are transferred from the physical to the computational domain by using boundary-fitted curvilinear coordinates. Roe's method has been employed to evaluate the numerical flux and the finite-volume approach has been used to discretize the equations. To ensure the balance of source term and flux gradient, the simple and powerful Surface Gradient Method (SGM) has been adopted, which not only enables the model to simulate flow over uneven bed topography but makes it shock-capturing as well. Some classical problems have been modeled to show that the results obtained from the proposed model are in good agreement with those of analytical solutions and other numerical methods.

This study was carried out in city of Marvedasht, Fars Province, in 2007 to estimate the water demand functions, to determine the factors affecting water consumption, and to estimate household water consumption sensitivity to water pricing during different seasons of the year. Regression analysis and the TSP software were used for estimating the functions and the t-test was used to determine the significance of the parameters studied. The required data were obtained from 50 households using the stratified random sampling method and questionnaires. The factors investigated included income level, water price, size of household, average age and literacy, residence construction type and garden, number of bathrooms, number of cooling systems installed, application of washing machine, number of automobiles, number of floors, and ownership. Based on the results obtained from the linear model, the independent variables used were capable of predicting 90.4, 84, 85.6, and 91.5% of the changes in water demand (the dependent variable) during the different seasons of spring, summer, autumn, and winter, respectively. Based on the estimated price elasticity, water demand falls by 11.6% for a 10% increase in water price. The independent variables used in the logarithmic method were capable of predicting 89, 85.5, 87.5 and 89.9% of the changes in water demand during spring, summer, autumn, and winter, respectively. Price elasticity rates for spring, summer, autumn, and winter were estimated at -0.9, -0.86, -0.87 and -0.92, respectively. The independent variable used in this study were able to account for 89.2% of the variations in water demand over the whole period and water price elasticity for the sampled households was estimated at - 0.88.

Ten irrigation wells were selected along Chaharbagh Street and the Zayandehrood River bank to investigate and classify the groundwaters used for irrigating Isfahan landscape for their quality. Monthly sampling was performed and the results of the quality tests were used as seasonal averages. Different measurements such as pH, EC, Na+, C1-, HCO3-, Fe+2 were made according to standard methods and the Surfer program was used and the results were represented as isolines. Also seasonal classification of wells was performed based on similarities found among the water quality of the wells using statistical programs. Results revealed the poor quality of water from some of the study wells due to the discharge of urban and industrial wastewaters, chemical manure, etc. Besides, investigation of changes in water quality indicated the declining irrigation water quality and the increasing availability of water for landscape irrigation.