Removal of Reactive Red 120 dye from wastewater using electrocoagulation: optimization using multivariate approach, economic analysis, and sludge characterization

Response surface methodology for process optimization in livestock wastewater treatment: A review

With increasing demand for meat and dairy products, the volume of wastewater generated from the livestock industry has become a significant environmental concern. The treatment of livestock wastewater (LWW) is a challenging process that involves removing nutrients, organic matter, pathogens, and other pollutants from livestock manure and urine. In response to this challenge, researchers have developed and investigated different biological, physical, and chemical treatment technologies that perform better upon optimization. Optimization of LWW handling processes can help improve the efficacy and sustainability of treatment systems as well as minimize environmental impacts and associated costs. Response surface methodology (RSM) as an optimization approach can effectively optimize operational parameters that affect process performance. This review article summarizes the main steps of RSM, recent applications of RSM in LWW treatment, highlights the advantages and limitations of this technique, and provides recommendations for future research and practice, including its cost-effectiveness, accuracy, and ability to improve treatment efficiency.

A comparative study for the removal of reactive red 49 (RR49) and reactive yellow 15 (RY15) using a novel electrode by electrocoagulation technique

The present work deals with the investigation of the efficiency of the electrocoagulation (EC) technique in the removal of two different reactive dyes as a simple, durable, and cost-effective technique for wastewater treatment. The difference in structure between Reactive Red 49 (RR49) and Reactive Yellow 15 (RY15) is explored during the treatment process through the use of a novel design of electrodes. The optimum conditions obtained were 80 and 60 mg/L of initial dye concentrations, pH of 5.9 and 4 for RR49 and RY15, respectively, 0.5 g of NaCl electrolyte, and 900 and 500 rpm of stirring rate for RR49 and RY17 dyes respectively, which led to the highest percent removal (98.5%) for both dyes. The suitable temperatures were 20 and 30 °C for RR49 and RY15, respectively. The thermodynamic parameters were designated, and it was a spontaneous process for both dyes. The removal process was designated to pseudo- second-order for the RR49 dye and pseudo- first-order for the RY15 dye and fitted to the Langmuir model. Analysis of Variance (ANOVA) was presented to assess the variation of the outcomes attained from each factor.

Degradation of Azo Dyes with Different Functional Groups in Simulated Wastewater by Electrocoagulation

Increasing attention has been paid to the widespread contamination of azo dyes in water bodies globally. These chemicals can present high toxicity, possibly causing severe irritation of the respiratory tract and even carcinogenic effects. The present study focuses on the periodically reverse electrocoagulation (PREC) treatment of two typical azo dyes with different functional groups, involving methyl orange (MO) and alizarin yellow (AY), using Fe-Fe electrodes. Based upon the comparative analysis of three main parameters, including current intensity, pH, and electrolyte, the optimal color removal rates for MO and AY could be achieved at a rate of up to 98.7% and 98.6%, respectively, when the current intensity is set to 0.6 A, the pH is set at 6.0, and the electrolyte is selected as NaCl. An accurate predicted method of response surface methodology (RSM) was established to optimize the PREC process involving the three parameters above. The reaction time was the main influence for both azo dyes, while the condition of PREC treatment for AY simulated wastewater was time-saving and energy conserving. According to the further UV–Vis spectrophotometry analysis throughout the procedure of the PREC process, the removal efficiency for AY was better than that of MO, potentially because hydroxyl groups might donate electrons to iron flocs or electrolyze out hydroxyl free radicals. The present study revealed that the functional groups might pose a vital influence on the removal efficiencies of the PREC treatment for those two azo dyes.

Optimization of the Sunset Yellow dye removal by electrocoagulation using a response surface method

In recent years, among the various treatment methods, the electrocoagulation process has been used for the treatment of effluents containing various dye pollutants. Sunset Yellow (S.Y.) azo dye is one of the common food colors widely used in various food industries. This study investigated the removal of the dye S.Y. from aqueous media by the electrocoagulation method in an electrochemical reactor using concentric iron electrodes. The experiments were designed using the response surface method (RSM) with the help of Minitab software in such a way that the effect of various process-influencing parameters, such as current density, electrolysis time, electrolyte concentration, pH of the solution, and the effluent flow rate, on the desired pollutant removal efficiency was investigated. According to the results of the process optimization by RSM, the optimal conditions for the process were obtained as follows: pH of 10, current density of 2.65 mA/cm², electrolysis time of 42.32 min, initial dye concentration of 20 mg/L, and effluent flow rate of 2.5 L/min. Under the above optimal conditions, the efficiency of dye removal was more than 99%.

Decolorization of Reactive Black B from wastewater by electro-coagulation: optimization using multivariate RSM and ANN

The present study is aimed to model and optimize the electrocoagulation (EC) process with five important parameters for the decolorization of Reactive Black B (RBB) from simulated wastewater. A multivariate approach, response surface methodology (RSM) together with central composite design (CCD) is used to optimize process parameters such as pH (5–9), electrode gap (0.5–2.5 cm), current density (2.08–10.41 mA/cm2), process time (10–30 min), and initial dye concentration (100–500 mg/l). The predicted percentage decolorization of dye is obtained as 97.21% at optimized conditions: pH (6.8), gapping (1.3 cm), current density (8.32 mA/cm2), time (23 min), and initial dye concentration (200 mg/L), which is very close to experimental percent decolorization (98.41%). The statistical analysis of variance (ANOVA) is performed to evaluate the quadratic model (RSM), and shows good fit of experimental data with coefficient of determination R2 >0.93. An Artificial Neural Network (ANN) is also used to predict the percentage decolorization and gives overall 94.96% which shows performance accuracy between the predicted and actual value of decolorization. The additional considerations of operating cost and current efficiency are also taken care to show the efficacy of EC process with mathematical tool. The sludge characteristics are determined by FE-SEM/EDX.