Atenolol adsorption onto multi-walled carbon nanotubes modified by NaOCl and ultrasonic treatment; kinetic, isotherm, thermodynamic, and artificial neural network modeling

SU-101 for the removal of pharmaceutical active compounds by the combination of adsorption/photocatalytic processes

Pharmaceutical active compounds (PhACs) are some of the most recalcitrant water pollutants causing undesired environmental and human effects. In absence of adapted decontamination technologies, there is an urgent need to develop efficient and sustainable alternatives for water remediation. Metal-organic frameworks (MOFs) have recently emerged as promising candidates for adsorbing contaminants as well as providing photoactive sites, as they possess exceptional porosity and chemical versatility. To date, the reported studies using MOFs in water remediation have been mainly focused on the removal of a single type of PhACs and rarely on the combined elimination of PhACs mixtures. Herein, the eco-friendly bismuth-based MOF, SU-101, has been originally proposed as an efficient adsorbent-photocatalyst for the elimination of a mixture of three challenging persistent PhACs, frequently detected in wastewater and surface water in ng L-1 to mg·L-1 concentrations: the antibiotic sulfamethazine (SMT), the anti-inflammatory diclofenac (DCF), and the antihypertensive atenolol (At). Adsorption experiments of the mixture revealed that SU-101 exhibited a great adsorption capacity towards At, resulting in an almost complete removal (94.1 ± 0.8% for combined adsorption) in only 5 h. Also, SU-101 demonstrated a remarkable photocatalytic activity under visible light to simultaneously degrade DCF and SMT (99.6 ± 0.4% and 89.2 ± 1.4%, respectively). In addition, MOF-contaminant interactions, the photocatalytic mechanism and degradation pathways were investigated, also assessing the toxicity of the resulting degradation products. Even further, recycling and regeneration studies were performed, demonstrating its efficient reuse for 4 consecutive cycles without further treatment, and its subsequent successful regeneration by simply washing the material with a NaCl solution.

Modeling Free Nitrous Acid Inhibition on the Removal of Nitrogen and Atenolol during Sidestream Partial Nitritation Processes

Sidestream serves as an important reservoir collecting pharmaceuticals from sludge. However, the knowledge on sidestream pharmaceutical removal is still insufficient. In this work, atenolol biodegradation during sidestream partial nitritation (PN) processes characterized by high free nitrous acid (FNA) accumulation was modeled. To describe the FNA inhibition on ammonia oxidation and atenolol removal, Vadivelu-type and Hellinga-type inhibition kinetics were introduced into the model framework. Four inhibitory parameters along with four biodegradation kinetic parameters were calibrated and validated separately with eight sets of batch experimental data and 60 days' PN reactor operational data. The developed model could accurately reproduce the dynamics of nitrogen and atenolol. The model prediction further revealed that atenolol biodegradation efficiencies by ammonia-oxidizing bacteria (AOB)-induced cometabolism, AOB-induced metabolism, and heterotrophic bacteria-induced biodegradation were 0, ∼ 60, and ∼35% in the absence of ammonium and FNA; ∼ 14, ∼ 29, and ∼28% at 0.03 mg-N L-1 FNA; and 7, 15, and 5% at 0.19 mg-N L-1 FNA. Model simulation showed that the nitritation efficiency of ∼99% and atenolol removal efficiency of 57.5% in the PN process could be achieved simultaneously by controlling pH at 8.5, while 89.2% total nitrogen and 57.1% atenolol were removed to the maximum at pH of 7.0 in PN coupling with the anammox process. The pH-based operational strategy to regulate FNA levels was mathematically demonstrated to be effective for achieving the simultaneous removal of nitrogen and atenolol in PN-based sidestream processes.

Shrimp waste-derived porous carbon adsorbent: Performance, mechanism, and application of machine learning

Aquaculture generates significant amount of processing wastes (more than 500 million pounds annually in the United States), the bulk of which ends up in the environment or is used in animal feed. Proper utilization of shrimp waste can increase their economic value and divert them from landfills. In this study, shrimp waste was converted to a porous carbon (named SPC) via direct pyrolysis and activation. SPC was characterized, and its performance for adsorbing ciprofloxacin from simulated water, natural waters, and wastewater was benchmarked against a commercial powdered activated carbon (PAC). The surface area of SPC (2262 m²/g) exceeded that of PAC (984 m²/g) due to abundance of micropores and mesopores. The adsorption of ciprofloxacin by SPC was thermodynamically spontaneous (ΔG = -19 kJ/mol) and fast (k₁ = 1.05/min) at 25 °C. The capacity of SPC for ciprofloxacin (442 mg/g) was higher than that of PAC (181 mg/g). SPC also efficiently and simultaneously removed low concentrations (200 µg/L) of ciprofloxacin, long-chain per- and polyfluoroalkyl substances (PFAS), and Cu ions from water. An artificial neural network function was derived to predict ciprofloxacin adsorption and identify the relative contribution of each input parameter. This study demonstrates a sustainable and commercially viable pathway to reuse shrimp processing wastes.

Sensitivity Analysis with the Monte Carlo Method and Prediction of Atenolol Removal Using Modified Multiwalled Carbon Nanotubes Based on the Response Surface Method: Isotherm and Kinetics Studies

Atenolol (ATN) is a β-blocker drug extensively used to treat arrhythmias and high blood pressure. Because the human body cannot metabolize it completely, this drug has been commonly found in many environmental matrices. In the present study, the response surface method (RSM) was used for adsorption prediction of ATN on modified multiwalled carbon nanotubes (M-MWCNTs) by NaOCl and ultrasonic. The sensitivity analysis was done by the Monte Carlo method. Sensitivity analysis was performed to determine the effective parameter by the Monte Carlo simulator. Statistical analysis of variance (ANOVA) was performed by using the nonlinear second-order model of RSM. The influential parameters including contact time (min), adsorbent dosage (g/L), pH, and the initial concentration (mg/L) of ATN were investigated, and optimal conditions were determined. Kinetic of ATN adsorption on M-MWCNTs was evaluated using pseudo-first, pseudo-second-order, and intraparticle diffusion models. Equilibrium isotherms for this system were analyzed by the ISOFIT software. As per our result, optimum conditions in the adsorption experiments were pH 7, 60 min of contact time, 0.5 mg/L ATN initial concentration, and 150 mg/L adsorbent dose. In terms of ATN removal efficiency, coefficients of R2 and adjusted R2 were 0.999 and 0.998, respectively. Sensitivity analysis also showed that contact time has the greatest effect on increasing the removal of ATN. Pseudo-first-order (R2 value of 0.99) was the best kinetic model for the adsorption of ATN, and for isotherm, BET (AICC value of 3.27) was the best model that fit the experimental data. According to the obtained results from sensitive analysis, time was the most important parameter, and after that, the adsorbent dose and pH affect positively on ATN removal efficiency. It can be concluded that the modified multiwalled carbon nanotubes can be applied as one of the best adsorbents to remove ATN from the aqueous solution.

Investigating the biological degradation of the drug β-blocker atenolol from wastewater using the SBR

Drug compounds are one of the main contributors to the entry of micro-pollutants into the environment, known as a constant threat to environmental stability. Atenolol is a type of beta-blocker extensively used to cure cardiovascular disorders. The residues of this compound have been continuously detected in aquatic environments because it is a polar and poorly biodegradable compound. Thus, removing atenolol from wastewater is essential before discharging into the environment. Biological processes are considered the most important removal process for polar drugs in wastewater treatment plants. Accordingly, for the first time in this study, the SBR performance was investigated in the biodegradation and mineralization of atenolol under different concentrations (50-600 mg/L) and hydraulic retention times (48-32 h). Based on the results, the time required for the acclimation of biomass to atenolol (C: 50 mg/L and the HRT: 48 h) was 80 days. The SBR efficiencies under optimum conditions (C: 400 mg/L and HRT: 40 h) in removing the atenolol and COD were 91% and 87%, respectively. For the first time in this study, one of the main pathways of the atenolol biodegradation was identified. Based on the review and comparison of the results of this study with existing literature showing that the SBR used in this study was able to remove higher concentrations with better efficiencies than other processes. Therefore, it can be concluded that the SBR used in this study could be considered an efficient and promising technique for treating wastewaters containing atenolol and other beta-blocker group drugs.

Understanding the factors affecting adsorption of pharmaceuticals on different adsorbents - A critical literature update

Remediation of emerging pharmaceutically active compounds (PhACs) as micropollutants in wastewater is of foremost importance as they can cause extremely detrimental effects on life upon bioaccumulation and generation of drug-resistance microorganisms. Presently used physicochemical treatments, such as electrochemical oxidation, nanofiltration and reverse osmosis, are not feasible owing to high operating costs, incomplete removal of contaminants along with toxic by-products formation. Adsorption with the utilization of facile and efficient nanoparticulate adsorbents having distinctive properties of high surface area, excellent adsorption capacity, ability to undergo surface engineering and good regeneration displays great potential in this aspect along with the incorporation of nanotechnology for effective treatment. The application of such nanosorbents provides optimal performance under a wide range of physicochemical conditions, decreased secondary pollution with reduced mechanical stress along with excellent organic compound sequestration capacity, which in turn improves the quality of potable water in a sustainable way compared to current treatments. The present review intends to consolidate the range of factors that affect the process of adsorption of different PhACs on to various nanosorbents and also highlights the adsorption mechanism aiding in the retrieval.

Sonophotocatalytic treatment of AB113 dye and real textile wastewater using ZnO/persulfate: Modeling by response surface methodology and artificial neural network

The present study investigates the synergistic performance of the sonophotolytic-activated ZnO/persulfate (US/UV/ZnO/PS) process in the decolorization of acid blue 113 (AB113) dye from aqueous solution and its feasibility for the treatment of real textile wastewater. Decolorization of AB113 solution was modeled by central composite design-response surface methodology (CCD-RSM) and artificial neural network (ANN) approaches and optimized by CCD-RSM and genetic algorithm (GA) approaches. Statistical metrics indicated that both CCD-RSM and ANN approaches seemed satisfactory. However, the results of statistical fit measures indicated a relative superiority of CCD-RSM as compared to the ANN approach. The results of optimization of the process parameters by CCD-RSM and GA approaches appeared to be similar as follows: pH = 6.1, reaction time = 25 min, US power density = 300 W/L, ZnO = 0.88 g/L and PS = 2.43 mmol/L. The synergistic effect of the hybrid US/UV/ZnO/PS process in comparison with its individual processes (US, UV, ZnO, and PS) was found to be 54.3%. Quenching experiments discovered that and HO are the main oxidizing radicals in a mildly acidic condition of the reaction solution. The removal efficiency of AB113 in the presence of some anions decreased in the order of bicarbonate > sulfate > phosphate > nitrate > chloride. Further, the reusability feasibility of ZnO showed that the ZnO material retained its photocatalytic property after five successive cycles of reusability test, while Zn²⁺ ion concentration in the reaction solution was measured to be 2.81 mg/L. The findings also indicated that the integrated process application suppresses extremely chemical and electrical costs. The study of the feasibility of the US/UV/ZnO/PS process in the treatment of real textile wastewater was done by determining COD, TOC and BOD₅/COD ratio. Results demonstrated that the 96.6 and 97.1% reduction of COD and TOC was achieved after 5 and 7 h reaction time, respectively. The obtained BOD₅/COD ratio changed from about 0.15 (for non-treated wastewater) to about 0.61 with increasing reaction time from zero to 90 min. In conclusion, the hybrid US/UV/ZnO/PS system can be proposed as a novel and promising approach to be utilized as a pretreatment technique before a biological treatment process to facilitate the biological treatment of recalcitrant textile wastewater.

Fixed bed adsorption column studies and models for removal of ibuprofen from aqueous solution by strong adsorbent Nano-clay composite

In this study, ibuprofen was removed using a strong nano-clay-composite based on cloisite 15A, PVP and β-cyclodextrin (CD@clay-PVP) adsorbent through a fixed-bed column system. Chemically modified nano-clay was characterized by using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and XRD. Different input situations were evaluated and included adsorbent bed height, initial concentrations, and the impact of the flow rate on the adsorbent. The various mathematical models employed to predict the breakthrough curve and model parameters include Thomas, bed-depth service time (BDST), Yoon-Nelson, and Clark. The characteristics of parameters related to the models were obtained by linear and nonlinear regression to design the process for the columns. Based on error analysis and adsorption conditions, all of the models are identical in describing the adsorption fixed-bed columns.