Removal of blue cat 41 dye from aqueous solutions with ZnO nanoparticles in combination with US and US-H[2]O[2] advanced oxidation processes

Background: The purpose of the present study was to assess the efficiency of ultrasound/hydrogen peroxide processes and ultrasound/hydrogen peroxide/ZnO nanoparticles in the removal of blue cat 41 dye from aqueous solutions

Methods: ZnO nanoparticles were prepared using the hydrothermal method. Variables including pH, concentration of ZnO nanoparticles, initial dye concentration, concentration of hydrogen peroxide, and contact time were investigated

Results: H[2]O[2] alone is not effective in dye removal. In conditions of H[2]O[2] = 20 mg/L and US = 30 kHz, removal efficiency rates of 6.5%, 23.5%, 30%, 51.8%, and 55%, respectively, were obtained. The maximum removal efficiency rate was obtained at the nanoparticle concentration of 3 g/l. Also, removal efficiency was reduced when the initial dye concentration was increased

Conclusion: The combination of nanoparticles and US and H[2]O[2] is very effective in removing blue cat 41 dye. As a result, photo catalytic processes can be considered to effectively remove environmental pollutants

Prediction and modeling of fluoride concentrations in groundwater resources using an artificial neural network: a case study in Khaf

Background: one issue of concern in water supply is the quality of water. Measuring the qualitative parameters of water is time-consuming and costly. Predicting these parameters using various models leads to a reduction in related expenses and the presentation of overall and comprehensive statistics for water resource management

Methods: the present study used an artificial neural network [ANN] to simulate fluoride concentrations in groundwater resources in Khaf and surrounding villages based on the physical and chemical properties of the water. ANN modeling was applied with regard to diverse inputs

Results: the MLP[1] model with eight inputs of parameters such as root mean square error [RMSE] and correlation coefficient of actual and predicted outputs exhibited the best results. The lowest fluoride concentration [0.15 mg L[-1]] was found in Sad village, and the highest concentration [3.59 mg L[-1]] was found in Mahabad village. Based on World Health Organization [WHO] standards, 56.6% of the villages are in the desirable range, 33.3% of them had fluoride concentrations below standard levels, and 10% had higher than standard concentrations of fluoride

Conclusion: the simulation results from the testing stage for MLP[1] as well as the high conformity between experimental and predicted data indicated that this model with its high confidence coefficient can be used to predict fluoride concentrations in groundwater resources