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In this study, the efficiency of photo-oxidation (P) and electro-oxidation (E) processes were examined, combined and separately, in amoxicillin (AMX) removal in a modified reactor in which a granular activated carbon bed was used as an electrode in the E process. Moreover, the effects of time, electrolyte concentration, and current density on AMX removal efficiency were investigated using Design-Expert software and Box–Behnken design to determine optimum conditions for removing the contaminant. Then, the effect of concentration and pH variables on the removal efficiency was investigated. After determining the optimal conditions for all variables, chemical oxygen demand (COD) removal efficiency and finally the toxicity of the effluent from the combined photoelectron oxidation reactor (PE) were also investigated. The results showed that in order to achieve the efficiency of about 98%, the optimum conditions for electrolyte concentration, time, and current density variables were 950 mg/L, 10 min, and 40 mA/cm2, respectively. Furthermore, the removal efficiency of AMX increased by decreasing pH and contaminant concentration. The analysis of the effluent from the reactor in terms of toxicity showed that the toxicity reduced. Using granular activated carbon as a porous electrode increases the efficiency of the PE process, which, by removal of 98% AMX and 64% COD, provides good performance in reducing the toxicity properties of effluent.

In this study, response surface methodology (RSM) was employed for investigating the removal of As(V) from aqueous solution using multiwalled carbon nanotube (MWCNT)/alumina nanocomposite. The synthesized nanocomposite was characterized by scanning electron microscopy and X-ray diffraction. For conducting the experiments, four independent variables of initial As(V) concentration ranging from 0.1 to 0.9 mg L–1, pH 3–11, contact time ranging from 15 to 1,450 min and adsorbent dose 0.5–1.5 g L–1were selected and consecutively coded as X1, X2, X3, and X4at three levels (-1, 0, and 1). A second-order polynomial regression model was then applied to predict responses. Regression analysis showed good fit of the experimental data to the second-order polynomial model with R2value of 0.9409 indicates the high correlation between observed and predicted values. At the optimum conditions that were initial As(V) concentration 0.5 mg L–1, pH 7, contact time 80 min, and adsorbent dose 1 g L–1, the As(V) removal efficiency was about 99.4%. This study proved that Box–Behnken design under RSM could efficiently be applied for modeling of As(V) removal by MWCNT/alumina nanocomposite.

This study investigated the performance of continuous-flow electrocoagulation (CFR-EC) reactor for aged landfill leachate treatment with a novel configuration of iron and aluminum electrodes to enhance the applicability of the process. The effects of the applied current density (ACD), initial pH, and hydraulic retention time (HRT) on the percentage removal of COD, TOC, BOD5, color, turbidity, and heavy metals (HMs) were modeled with Box-Behnken design (BBD). The results demonstrated that the models are significant (R20.97—p-value < 0.0029 and R20.92—p-value < 0.0001 for Fe and Al electrodes). COD, TOC, BOD5, and NH3-N removal were maximized at HRT 50 min (40.0 mL min−1) and pH 11 reaching 59, 64, 55, and 27%, respectively, by applying the ACD of 1.1 mA cm−2in the CFR-ECFereactor. The CFR-ECFereactor presented a higher color (59%) and turbidity reduction (86%) than the CFR-ECAlreactor. At optimum condition, the removal percentages of HMs: Cr6+, Pb2+, As3+, Mg2+, B3+, Mn3+, Ni2+, and Ba2+were 50, 70, 80, 99, 81, 99, 20, and 65%, respectively. The total process cost for landfill leachate treatment was 0.21 $/m3. The CFR-ECFewas an effective and affordable reactor for pollutant removal from landfill leachate.

Iran's most important iron ore mine is located in the central region, and because of the water shortage in this area, the need to reuse the effluent from this mine is essential. On the other hand, there are no suitable conditions for treating large effluent volumes in iron mine in central Iran. For this reason, produced effluent should be reduced and returned to the consumption cycle by using appropriate technology. This study aimed to investigate the ozonation/lime effect on polymer consumption reduction and evaluate the treatment and economic efficiency compared to the currently used treatment method (coagulation-flocculation without ozonation/lime).

AbstractIn this study, dye removal from synthetic colored wastewater using electrocoagulation process was studied. Acid Red 73 was used as model dye compound. The effects of operational parameters, such as current density, reaction time, initial dye concentration, electrolyte concentration, initial pH, and polyaluminum chloride (as a coagulant), on dye removal were investigated. The cost of wastewater treatment at optimal condition was investigated. The results showed that electrocoagulation process was able to remove 99% dye and 88% chemical oxygen demand. Using polyaluminum chloride as a coagulant had significant impact on improving process efficiency, time, and cost reduction. It can be concluded that electrocoagulation was a very effective and fast method to remove acid dye from colored wastewater.

In this study, dye removal from synthetic colored wastewater using electrocoagulation process was studied. Acid Red 73 was used as model dye compound. The effects of operational parameters, such as current density, reaction time, initial dye concentration, electrolyte concentration, initial pH, and polyaluminum chloride (as a coagulant), on dye removal were investigated. The cost of wastewater treatment at optimal condition was investigated. The results showed that electrocoagulation process was able to remove 99% dye and 88% chemical oxygen demand. Using polyaluminum chloride as a coagulant had significant impact on improving process efficiency, time, and cost reduction. It can be concluded that electrocoagulation was a very effective and fast method to remove acid dye from colored wastewater.