Development and application of novel high throughput metal waste chips and foam electrodes for electrocoagulation treatment of graywater.

In this study, novel high throughput metal waste chips and foam electrodes were developed for the electrocoagulation of graywater for the first time. The developed electrodes were then compared with traditional metal plate electrodes, which showed higher efficiency of developed electrodes. The effective parameters of pH, electrode distance, applied voltage, and reaction time on COD removal were optimized using RSM as a multivariate optimization technique, and the data were analyzed by ANOVA, normal plot, residual distribution, and 3D plots. The optimal conditions for electrocoagulation of graywater using metal (Al) plate electrode were determined as a pH of 6.86, electrode distance of 5 mm, and applied voltage of 5 V for a reaction time of 10 min, resulting in 89.1% COD removal and 74% turbidity removal. Finally, the performance of aluminum plate electrodes, foam electrodes, and electrodes made from metal waste chips was compared using COD removal efficiency as the index, revealing 84%, 93%, and 87% COD removal, respectively. These results demonstrated that the newly developed electrodes are suitable for graywater treatment with excellent COD removal efficiency, metal chip waste recycling, and cost-saving.

Water treatment by forward osmosis using novel D-Xylose coated magnetic nanoparticles as draw agent.

In this study, D-Xylose coated MNPs were synthesized and used as draw agent in forward osmosis (FO) process for water purification. Response surface methodology (RSM) was utilized for the design and optimization of synthesis parameters. In order to characterize the synthesized MNPs, FTIR, TEM, VSM, and UV characterization techniques were performed. The effect of independent parameters including D-Xylose mass, MNPs mass, and synthesis time on the osmotic pressure was investigated. Based on the optimization results, the osmotic pressure of a 2 wt./v% draw solution using 2.66 g D-Xylose, 0.13 g MNPs, and a 7.11 h synthesis time was 0.81 bar as the highest value. Using D-Xylose coated MNPs as draw agent and deionized water as the feed, the initial FO water flux was 2.98 LMH. Reusing the recovered MNP draw agent in two more consecutive tests resulted in the reduction of water flux to 2.68 and 2.30 LMH, respectively. Moreover, using 0.01 M NaCl solution as the feed, the initial water flux was reported as 1.3 LMH. To remove the draw agents from suspension, external magnetic field was applied to obtain a water turbidity of 0.08 NTU.

A hybrid statistical decision-making optimization approach for groundwater vulnerability considering uncertainty.

Recognizing the vulnerable areas for contamination is a feasible way to protect groundwater resources. The main contribution of the paper is developing a hybrid statistical decision-making model for evaluating the vulnerability of Shiraz aquifer, southern Iran, with modified DRASTIC (depth to the water table, net recharge, aquifer media, soil media, topography, impact of the vadose zone, and hydraulic conductivity) by using the genetic algorithm (GA), the analytical hierarchy process (AHP) method, and factorial analysis (FA). First, considering the variation of the uncertain parameters, 32 scenarios were defined to perform factorial analysis. Then using the AHP method and GA, DRASTIC parameters were rated and weighted in all scenarios. To achieve the optimal weights for parameters, the objective function in GA was maximizing the correlation coefficient between the vulnerability index and the nitrate concentration. The single and interactive effects of parameters on groundwater vulnerability were analyzed by factorial analysis. The results revealed that the net recharge had the highest single effect, and the resulted effect between net recharge and hydraulic conductivity was the most significant interactive effect on the objective function. Besides, the variation of aquifer media does not change the objective function. The application of the proposed method leads to a precise groundwater vulnerability map. This research provides valuable knowledge for assessing groundwater vulnerability and enables decision-makers to apply groundwater vulnerability information in future water resources management plans.

Application of molasses as draw solution in forward osmosis desalination for fertigation purposes.

Certain challenges exist in forward osmosis (FO) separation technique that has to be studied yet such as a selection of a proper draw solution (DS) to supply the required driving force for separation. In this work, the performance of molasses DS in terms of water flux (J w) was evaluated using a commercial FO membrane. Deionized water (DIW), an oilfield brackish wastewater (BWW) and seawater (SW) were used as three different feed solutions (FS). Effects of molasses concentration (C DS) and solutions cross-flow velocities on J w were investigated. The results indicated that the relationship between J w and C DS is non-linear that may be attributed to internal concentration polarization in the membrane support layer. J w was improved slightly by increasing the FS velocity and enhanced moderately by increasing the DS velocity from 6 to 11.5 cm/s. Fluxes of 16.7, 13.3 and 7.5 LMH were obtained during 30 min against the feeds of DIW, BWW and SW, respectively. After 12 h, the osmotic pressure of molasses is reduced from an initial value of 79.8 bar to 54.5, 62.8 and 66.3 bar for the FSs, respectively. Reverse solute flux is increased by decreasing J w and is more significant at values lower than 10.67 LMH for DIW feed. Based on the results, Molasses has a good performance ratio in comparison to other fertilizers and diluted molasses can potentially be used for fertigation purposes.

Desalination of brackish water by gelatin-coated magnetite nanoparticles as a novel draw solute in forward osmosis process.

This paper presents the optimization of synthesis of gelatin-coated magnetite nanoparticles (MNPs) and their application as a draw solute in forward osmosis (FO) process. Persicaria bistorta root extract is used as the gelatin crosslinker, and its efficiency is compared with glutaraldehyde as a common crosslinker. Also, the impact of the concentration of gelatin and the draw solution on the osmotic pressure of the produced draw solution has been investigated using response surface methodology. Using Persicaria bistorta root extract as the crosslinker in the optimized conditions, the highest osmotic pressure (1.01 bar) was achieved in a concentration of 7.7%w/v and 14246 mg/l for gelatin and draw solution, respectively. Using glutaraldehyde under the same conditions resulted in osmotic pressure of 1.06 bar which is very close to the pressure found for Persicaria bistorta root extract (1.01 bar), confirming the benefit of the latter as a gelatin crosslinker. Further, using a solution with gelatin-coated MNPs as the draw solution, deionized water as the feed solution, and an osmotic pressure difference of 1.5 in the FO process generated an initial water flux of 1.54 LMH. By repeating the process in nine more cycles, the initial water flux was reduced to 0.365 LMH. These experiments confirm the as-prepared gelatin-MNPs as a promising draw solution in the FO process.

A novel method for optimization of slit Venturi dimensions through CFD simulation and RSM design.

This research presents a novel comprehensive method for optimizing the design of cavitating slit Venturi for a given cavitation intensity. This method is applicable to any cavitation number and can be used to provide the Venturi geometry that is suitable for a specific application. In this paper, cavitating Venturi design process is represented in seven steps. As an example, for the cavitation number of 0.2, geometrical and operational parameters of the Venturi were determined using the proposed seven steps. During the design process, the Venturi discharge coefficient was calculated using computational fluid dynamics (CFD) simulations. Furthermore, Venturi parameters such as inlet pressure, throat area, width, length, height and divergence angle, were optimized by the combination of CFD and Response Surface Methodology (RSM). In addition to calculating the mentioned optimum parameters, other hydraulic parameters of Venturi including discharge coefficient, flowrate, throat velocity, cavitation volume and length were also determined. Finally, the proposed design method in this study was verified by conducting sets of laboratory experiments.

Optimization of Ni(II) adsorption onto Cloisite Na+ clay using response surface methodology.

The aim of this study was to investigate the adsorption of Ni(II) from aqueous solutions onto Cloisite Na+ clay. The effects of the initial concentration of Ni(II), adsorbent dose, pH, and temperature on adsorption capacity were studied using response surface methodology. A second-order regression model was determined based on the experimental results. Analysis of variance used to evaluate the individual and combined effects of process variables showed that initial Ni(II) concentration and adsorbent dose were more significant than solution pH and temperature. Moreover, the interaction effects of the initial concentration of nickel and the adsorbent dose, as well as the solution pH and adsorbent dose were significant. High coefficient of determination (R2 = 0.93) and low probability values signify the validity of the model for predicting the adsorption capacity of Cloisite Na+ for Ni(II) ions. The optimal conditions for pH and adsorbent dose were found to be 6.9 and 0.21 g/L, respectively at a constant temperature of 25 °C and initial Ni(II) concentration of 50 mg/L. Under these conditions, the adsorption capacity of clay was found to be 31.43 mg/g. Moreover, the adsorption isotherms results indicated that these data could be best fitted to the Langmuir isotherm model (R2 = 0.99). The Langmuir maximum adsorption capacity was estimated to be 32.05 mg/g for an adsorbent dose of 0.2 g/L at pH 7 and 25 °C. In conclusion, the results showed that Cloisite Na+ clay can be utilized as an effective adsorbent for the removal of Ni(II) from aqueous solutions.

Green synthesis and optimization of nano-magnetite using Persicaria bistorta root extract and its application for rosewater distillation wastewater treatment.

The aim of this research is to synthesize magnetite nanoparticles, using Persicaria bistorta root extract as the reducing agent, and to test its adsorption properties in the treatment of rosewater distillation wastewater. Taking advantage of Taguchi method, effect of synthesis parameters, including molar concentration of FeCl2, concentration of plant extract, temperature, and pH on crystallite size and magnetization strength is studied. Based on the successful synthesis of magnetite nanoparticles and characterization experiments, Persicaria bistorta root extract can be considered as a proper alternative as the reducing agent. Data analysis shows that crystallite size and magnetization are positively correlated with concentration of FeCl2 and pH, while inversely related to temperature and independent of plant extract concentration. The optimum values achieved for concentration of FeCl2, temperature, and pH are 0.15 M, 70 °C, and 11, respectively, with the production of nanoparticles with magnetite size of 45.5 nm and magnetization value of 62.5 emu/g. In addition, the application of as-synthesized magnetite nanoparticles as an adsorbent for treatment of rosewater distillation wastewater proved its high adsorption capacity for chemical oxygen demand (COD) up to 149 mg/g. Adsorption data also shows a good fitness with Langmuir and Freundlich isotherm models.

Comparison of photo-Fenton, O3/H2O2/UV and photocatalytic processes for the treatment of gray water.

This research was carried out to compare and optimize the gray water treatment performance by the photo-Fenton, photocatalysis and ozone/H2O2/UV processes. Experimental design and optimization were carried out using Central Composite Design of Response Surface Methodology. The results of experiments showed that the most effective and influencing factors in photo-Fenton process were H2O2/Fe2+ ratio, in ozone/H2O2/UV experiment were O3 concentration, H2O2 concentration, reaction time and pH and in photocatalytic process were TiO2 concentration, pH and reaction time. The highest COD removal in photo-Fenton, ozone/H2O2/UV and photocatalytic process were 90%, 92% and 55%, respectively. The results were analyzed by design expert software and for all three processes second-order models were proposed to simulate the COD removal efficiency. In conclusion the ozone/H2O2/UV process is recommended for the treatment of gray water, since it was able to remove both COD and turbidity by 92% and 93%, respectively.

Optimization of toluene removal over W-doped TiO2 nano-photocatalyst under visible light irradiation.

This study outlines the optimization of photocatalytic degradation of toluene by W-doped TiO2 nanoparticles under visible light irradiation. Experiments were carried out based on the central composite design (CCD) methodology. W-TiO2 nanoparticles were synthesized with various tungsten contents at different calcination temperatures by the sol-gel method. The nanoparticles' characteristics were determined using appropriate techniques such as field emission scanning electron microscopy, particle size analysis, X-ray diffraction and energy-dispersive spectroscopy. The effect of different operational conditions of coating mass, initial toluene concentration, and exposure time on the toluene removal efficiency was investigated. Result showed that tungsten has a fundamental role in improving the photocatalytic activity of TiO2 under visible light, as well as improving its photoactivity under UV irradiation by decreasing the rate of electron/hole charge recombination. Analysis of the obtained data on toluene removal with a CCD approach illustrated that the quadratic model can effectively predict the toluene removal with coefficient of determination of R2 = 0.862. Tungsten content and exposure time affect the toluene removal efficiency more than other factors. Results showed that maximum toluene removal efficiency slightly depends on the initial concentration of toluene. At the initial toluene concentration of 4000 ppm, the optimum values of the calcination temperature, tungsten content, coating mass, and exposure time were 500°C, 0.52 wt%, 11.7 g/m2, and 8 h, respectively, with 59% removal of toluene.

Verifying the performance of artificial neural network and multiple linear regression in predicting the mean seasonal municipal solid waste generation rate: A case study of Fars province, Iran.

Predicting the mass of solid waste generation plays an important role in integrated solid waste management plans. In this study, the performance of two predictive models, Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) was verified to predict mean Seasonal Municipal Solid Waste Generation (SMSWG) rate. The accuracy of the proposed models is illustrated through a case study of 20 cities located in Fars Province, Iran. Four performance measures, MAE, MAPE, RMSE and R were used to evaluate the performance of these models. The MLR, as a conventional model, showed poor prediction performance. On the other hand, the results indicated that the ANN model, as a non-linear model, has a higher predictive accuracy when it comes to prediction of the mean SMSWG rate. As a result, in order to develop a more cost-effective strategy for waste management in the future, the ANN model could be used to predict the mean SMSWG rate.