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The adsorptive removal of a pollutant from water is significantly affected by the presence of coexisting ions with various concentrations. Here, we have studied adsorption of arsenate [As(V)] by calcined Mg–Fe–(CO3)–LDH in the presence of different cations (Mg2+, Na+, K+, Ca2+, and Fe3+) and anions (CO32‒, Cl‒, PO43‒, SO42‒, and NO3‒) with their different concentrations to simulate the field condition. The experimental results indicated that Ca2+, Mg2+, and Fe3+ have a synergistic effect on removal efficiency of As(V), whereas PO43‒ and CO32‒ ions have a significant antagonistic impact. Overall, the order of inhibiting effect of coexisting anions on adsorption of As(V) was arrived as NO3–˂Cl–42–32–43–. Among them, competitive adsorption of phosphate with arsenic at different initial phosphate concentrations was found to be responsive to formulate a binary adsorption system. We have also developed a modified non-competitive Langmuir and Langmuir–Freundlich models; however, the modified competitive Langmuir model was arrived to be the most adequate model for this binary system. An Artificial Neural Network based multivariate prediction model was developed, delineating the impact of coexisting ions on the adsorption system. The proposed method may appropriately demonstrate the overall system and exhibited a significantly adequate prediction model with high R2, high F-value, and low error values. [ABSTRACT FROM AUTHOR]

The kinetic, isotherm and thermodynamic modeling of the adsorption of arsenite by layered double hydroxide have been performed to analyze the feasibility, efficacy and mechanism of the system. The fast uptake was observed during the initial phase of the process, which reached equilibrium at 240 min following Elovich model. The diffusion kinetic model exhibited that the rate-limiting step of adsorption was controlled by film diffusion as well as intraparticle diffusion. The isotherm modeling revealed the applicability of the Freundlich equation with the Kf values as 8.19–13.99 (mg g−1)(L mg−1)1/n at 283–323 K showing the increasing trend of adsorption capacity, which was further confirmed by the positive value of ΔH0 (9.49 kJ mol−1) demonstrating the endothermic nature of the adsorption process. The spontaneous nature of the adsorption reaction was established by the negative values of ΔG0. Application of the calcined Mg–Fe–LDH adsorbent for the removal of arsenic from real arsenic contaminated groundwater was also successfully performed. The effect of process parameters of the adsorption system was modeled by an artificial neural network (ANN) for adsorption capacity and removal efficiency. The optimized model exhibited high R2, F-value and low values of error functions, establishing the significant applicability of the ANN model. [ABSTRACT FROM AUTHOR]

Ciprofloxacin, a pharmaceutically active compound, is present as a micropollutant in wastewater, which cannot be removed by conventional techniques due to its recalcitrant nature. Therefore, in the present study, the photocatalytic degradation of this bio-toxic compound was demonstrated using a three-dimensional sulfur-doped graphitic-carbon nitride/zinc oxide hybrid, with enriched oxygen vacancies. The influence of various water matrices and experimental conditions on the ciprofloxacin degradation was optimized. The hybrid material showed 98.8% and 75.8% degradation efficiency under optimum experimental conditions (i.e., catalyst dose: 1 g/L; pH: 5; initial ciprofloxacin concentration: 20 mg/L; temperature: 27 °C) under ultraviolet (UV) and visible light, respectively. A neural-network-based multivariate approach was used to predict a significant model considering the experimental conditions that showed adequate statistical significance (R 2 : 0.992 and F-value: 8707.1). The relative significance of the experimental conditions was assessed, suggesting that the initial ciprofloxacin concentration has a more significant effect on the degradation efficiency than the other factors. The rate kinetics and reaction mechanisms for ciprofloxacin degradation were demonstrated, and the driving radicals involved were identified. A higher rate of reaction was found under UV irradiation (0.01702 min -1 ) than under visible light (0.00802 min -1 ). Superoxide radicals were identified as the main driving radicals, which caused substantial photocatalytic reactions among the hybrid and ciprofloxacin molecules. Microscopic and macroscopic analyses of the used hybrid were conducted, which confirmed the presence of higher defect concentrations, crystallinity, and interlinked stacked structure in the hybrid. Hence, the 3D hybrid can be efficiently used and reused for ciprofloxacin degradation. This advanced photocatalytic system can be widely used to remediate emerging contaminants in wastewater treatment., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The adsorptive removal of a pollutant from water is significantly affected by the presence of coexisting ions with various concentrations. Here, we have studied adsorption of arsenate [As(V)] by calcined Mg-Fe-(CO 3 )-LDH in the presence of different cations (Mg 2+ , Na + , K + , Ca 2+ , and Fe 3+ ) and anions (CO 3 2‒ , Cl ‒ , PO 4 3‒ , SO 4 2‒ , and NO 3 ‒ ) with their different concentrations to simulate the field condition. The experimental results indicated that Ca 2+ , Mg 2+ , and Fe 3+ have a synergistic effect on removal efficiency of As(V), whereas PO 4 3‒ and CO 3 2‒ ions have a significant antagonistic impact. Overall, the order of inhibiting effect of coexisting anions on adsorption of As(V) was arrived as NO 3 - ˂Cl - 4 2- 3 2 - 4 3 - . Among them, competitive adsorption of phosphate with arsenic at different initial phosphate concentrations was found to be responsive to formulate a binary adsorption system. We have also developed a modified non-competitive Langmuir and Langmuir-Freundlich models; however, the modified competitive Langmuir model was arrived to be the most adequate model for this binary system. An Artificial Neural Network based multivariate prediction model was developed, delineating the impact of coexisting ions on the adsorption system. The proposed method may appropriately demonstrate the overall system and exhibited a significantly adequate prediction model with high R 2 , high F-value, and low error values.

Ciprofloxacin is a pharmaceutically active compound which belongs to a class of micropollutants that cannot be removed using conventional water treatment systems. In this study, photocatalytic degradation using materials with high surface area and active sites was proposed to remove such contaminants. We demonstrated an easily scalable and simple synthesis route to prepare a 3D porous sulfur-doped g-C 3 N 4 /ZnO hybrid material, and the preparation process parameters were optimized using response surface methodology targeting Ciprofloxacin degradation. The hybrid material removed up to 98% of the bio-toxic Ciprofloxacin from synthetic water. The porous, defect engineered, thermally stable, and chemically interconnected hybrid material presented an 18 and 38% improved degradation efficiency compared to ZnO and sulfur-doped g-C 3 N 4 (or S-C 3 N 4 ), respectively. Based on our experimental results, an empirical relation correlating synthesis process parameters and degradation efficiency was developed using face-centered central composite design (FCCD) and response surface methodology (RSM). The current model can be used to design catalytic materials for removing bio-toxic and other micropollutants from water., Competing Interests: Declaration of competing interest None., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The kinetic, isotherm and thermodynamic modeling of the adsorption of arsenite by layered double hydroxide have been performed to analyze the feasibility, efficacy and mechanism of the system. The fast uptake was observed during the initial phase of the process, which reached equilibrium at 240 min following Elovich model. The diffusion kinetic model exhibited that the rate-limiting step of adsorption was controlled by film diffusion as well as intraparticle diffusion. The isotherm modeling revealed the applicability of the Freundlich equation with the K f values as 8.19-13.99 (mg g -1 )(L mg -1 ) 1/ n at 283-323 K showing the increasing trend of adsorption capacity, which was further confirmed by the positive value of Δ H 0 (9.49 kJ mol -1 ) demonstrating the endothermic nature of the adsorption process. The spontaneous nature of the adsorption reaction was established by the negative values of Δ G 0 . Application of the calcined Mg-Fe-LDH adsorbent for the removal of arsenic from real arsenic contaminated groundwater was also successfully performed. The effect of process parameters of the adsorption system was modeled by an artificial neural network (ANN) for adsorption capacity and removal efficiency. The optimized model exhibited high R 2 , F -value and low values of error functions, establishing the significant applicability of the ANN model.