Iranian Journal of

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Backgrounds and Objective: In arid and semi-arid regions of the world, urban runoff as a source of water restoration and is considered valuable. Wastewater treatment, while preserving the environment, it can be considered as water source. The aim of this study to evaluate the possibility of using powder grain Peregrina in wastewater treatment in comparing with Alum and PloyAluminum Chloride (PAC).
Materials and Methods: Flocculation and coagulation tests were done by Jar test. Wastewater quality parameters were measured according to standard method.
Results: Studies have been showed that in optimum Peregrina concentration, efficiency of turbidity reduction, total hardness, calcium hardness, magnesium hardness, total E. Coli are 95.11, 38, 55.5, 46.6, 97 and 97 percent respectively. It is noted that turbidity reducing directly related with coli form reduction. As, with increasing turbidity reduction, coliform reduction is increased. The most reduction of E. coli with combination of Alum, Ploy Aluminum Chloride and Peregrina was 100 percent. In optimum concentration of Alum, Ploy Aluminum Chloride and Peregrina, the quality of treated wastewater would be in the range of environmental standards. Therefore, treated wastewater can be entering to surface water and reuse as irrigation water.
Conclusion: The results derived from this study showed that the treated wastewater can be use in a variety of irrigation except sprinkler irrigation due to burn the leaves of plants. (high electrical conductivity).Also, the low cost of seed Peregrina and good performance in the refining operations, it is suggested that Peregrina as a replacement for poly aluminum chloride and an alum to be used for wastewater treatment.

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MicrosoftInternetExplorer4 Background and Objectives: Arsenic is one of the most toxically contaminants in groundwater and soils. Due to the ability of bio-accumulation of arsenic III in plants through irrigation with contaminated water and its entrance to the food chain, irreparable hazards would be caused. The aim of this research is the feasibility study of arsenic III removal from polluted water using calcium peroxide nanoparticles synthesized and also studying the effective parameters. Moreover, the adding effect of nanoparticles on the important parameters of irrigation would be assessed.
Materials and Methods: In this research, we first synthesized CaO₂ nanoparticles through chemical precipitation and then studied the arsenic removal efficiency from contaminated water samples. Nevertheless, the impact of the effective parameters including pH, initial arsenic III concentration, and CaO2 nanoparticles concentration were investigated. Finally, relevant results to nanoparticles effect on the important irrigation water quality parameters were presented.
Results: Our results showed that synthesized particles were in the range of 25-50 nanometers. In addition, the efficiency of the CaO₂ nanoparticles in arsenic III removal was 88 percent under following conditions:  irrigation pH range 6.5-8.5, nanoparticles dosage 40 mg/L, arsenic initial concentration 400 µg/L, and 30 minuts retention time. Moreover, the nanoparticles synthesized did not have any undesirable impact on significant parameters in irrigation water.
Conclusion: Generally, it can be concluded that CaO₂ nanoparticles based on the in situ chemical oxidation had significant effect on the reduction of arsenic III until lower than recommended standards for irrigation water. High rate of process and relatively short reaction time, and having no negative effects on the significant parameters of irrigation indicate that CaO₂ nanoparticles have significant potential in removal of arsenic III from contaminated water.

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Background and Objectives: Rivers are the most important resources supplying drinking, agricultural, and industrial water demand. Their quality fluctuates frequently due to crossing from different regions and beds as well as their direct relationship with their peripheral environments. Thus, it is essential to be considered the surveying and predicating changes in the water qualitative parameters in a river. In this study, in order to estimate some of the qualitative parameters (Total dissolved solids, electrical conductivity and sodium absorption rate) for Tehran Jajroud and Kermanshah Gharasu rivers, we used wavelet-artificial neural network (W-ANN) hybrid model during a statistical period of 24 years. Methods: We compared W-ANN model with ANN model in order to evaluate its capability in detecting signals and separating error signals for estimating water quality parameters of the abovementioned rivers. The evaluation of both models was performed by the statistical criteria including correlation coefficient, the Nash-Sutcliffe model efficiency coefficient (NS), the root mean square error (RMSE) and the mean absolute error (MAE). Results: The results showed that the optimized W-ANN with correlation coefficient of 0.9 has high capability to estimate SAR parameter in the stations studied. Moreover, we found that W-ANN had less error and higher accuracy in the case of EC and TDS parameters rather than ANN model. Conclusion: W-ANN proved high efficiency in forecasting of the water quality parameters of rivers, therefore, it can be used for decision making and assurance of monitoring results and optimizing the monitoring costs.