Modeling Of Breakthrough Curves Research Articles

Removal of ciprofloxacin and heavy metals from water by bentonite/activated carbon composite: Kinetic, isotherm, thermodynamic and breakthrough curve modeling studies

This study explores the potential of a new, cost-effective adsorbent for removing ciprofloxacin (CIP) and heavy metals (HMs) from wastewater. This adsorbent is a mesoporous activated carbon (AC) crafted from sugarcane bagasse modified with bentonite (SCBB). The prepared composite was characterized using FTIR, XRD, SEM, and BET techniques. Optimal adsorption conditions were determined, with initial concentrations set at 15 and 300 mg/L, adsorbent doses at 100 and 50 mg, temperatures at 25 and 45 °C, and pH levels at 6 for CIP and HMs, respectively, in batch experiments. Kinetics data confirmed that adsorption follows pseudo-first-order model, with intraparticle diffusion identified as the rate-determining step. Three-parameter models were superior in describing experimental data compared to two-parameter models, with the Sips isotherm model indicating multilayer adsorption beyond monolayer saturation. Hydrophobicity likely plays a key role in CIP adsorption, potentially complemented by hydrogen bonding, while HMs are adsorbed through ion exchange, complexation, and pore diffusion processes. Furthermore, SCBB exhibited excellent adsorption performance (≥90 %) even after ten regeneration cycles. The impact of various operating parameters, including bed depth, feed concentration, and flow rate, were optimized in fixed bed column. Breakthrough data fitting the Dose Response, Thomas, and Yoon-Nelson models yielded high coefficients of determination (R2 ≥ 0.98). The techno-economic analysis identified SCBB preparation ($0.31/kg) as the main cost factor, but still predicts profitability with a payback period of 0.88 years and a break-even point of 58.6 %. Overall, the developed SCBB composite demonstrates significant potential as an efficient, cost-effective, and sustainable adsorbent, with applicability for the treatment of industrial wastewater contaminated with CIP and HMs.

Potential removal of arsenite from contaminated water using a fixed bed column packed with TiO2-impregnated pomegranate peel powder

A dynamic biosorption of arsenite in a fixed bed column packed with TiO2 impregnated pomegranate peel (PP@TiO2) has been investigated in this work, which is important to identify the effectiveness and affordability of an adsorbent in actual practice. To create an active adsorption site for As (III) ions, pomegranate peel powder (PP) was impregnated with TiO2. Under various operating parameters, the performance of a column packed with PP@TiO2 for adsorbing As (III) ions was evaluated. Breakthrough curve modelling showed that the bed depth service time (BDST) and Thomas models agreed well with the experimental data. The maximum column capacity of PP@TiO2 using the Thomas model was found to have resembled experimental value with high values of coefficient of determination. Therefore from these results, we may anticipate that PP@TiO2 can be a strong contender for the treatment of wastewater that has traces amount of the As (III) ion in a fixed bed system.

Successful removal of fluoride from aqueous environment using Al(OH)3@AC: column studies and breakthrough curve modeling.

In this study, we discuss the removal of fluoride from water through column adsorption methods using Al(OH)3@AC as a functional granular activated carbon. The height of the bed, fluoride concentration, and flow rate are the experimental factors used to obtain the breakthrough curves. As the flow rate increased, the breakthrough and saturation times decreased. The analysis of simplified column models, such as the Adams-Bohart, Thomas, and Yoon-Nelson models, revealed that the Clark model best described the adsorption process when fitting the experimental data. The obtained breakthrough curves agreed with the corresponding experimental data. The highest capacity for adsorption obtained during the column procedure was found to be 41.84 mg g-1 with a bed height of 3 cm, an initial fluoride concentration of 10 mg L-1 and a flow rate of 7.5 mL min-1.

Analytical Perspective and Modeling of Breakthrough Curves for a Fixed-Bed Column of Modified Dolomite by Calcination and Ultrasound for Phosphate Immobilization: Experimental Design, Bayesian Statistics, and Data Prediction

Analytical Perspective and Modeling of Breakthrough Curves for a Fixed-Bed Column of Modified Dolomite by Calcination and Ultrasound for Phosphate Immobilization: Experimental Design, Bayesian Statistics, and Data Prediction

New trends in modelling of breakthrough curves to remove pollutants using adsorption on advanced monoliths geometries

This work proposes a rigorous mathematical model capable of reproducing the adsorption process in dynamic regime on advanced monoliths geometries. For this, four bed geometries with axisymmetric distribution of channels and similar solid mass were proposed. In each geometry a different distribution of channels was suggested, maintaining constant the bed dimensions of 15 cm high and 5 cm radius. The mathematical modeling includes mass and momentum transfer phenomena, and it was solved with the COMSOL Multiphysics software using mass transfer parameters published in the literature. The overall performance of the column was evaluated in terms of breakthrough (CA/CA0 = 0.1) and saturation times (CA/CA0 = 0.9). The mass and velocity distributions obtained from the proposed model show good physical consistency with what is expected in real systems. In addition, the model proved to be easy to solve given the short convergence times required (2–4 h). Modifications were made to the bed geometry to achieve a better use of the adsorbent material which reached up to 80%. The proposed bed geometries allow obtaining different mixing distributions, in such a way that inside the bed a thinning of the boundary layer is caused, thus reducing diffusive effects at the adsorbent solid-fluid interface, given dissipation rates of about 323 × 10−11 m2/s3. The bed geometry composed of intersecting rings deployed the best performance in terms of usage of the material adsorbent, and acceptable hydrodynamical behavior inside the channels (maximum fluid velocity = 35.4 × 10−5 m/s and drop pressure = 0.19 Pa). Based on these results, it was found that it is possible to reduce diffusional effects and delimit the mass transfer zone inside the monoliths, thus increasing the efficiency of adsorbent fixed beds.

Asymmetrical fixed-bed breakthrough curve modelling: Comparing simplistic, log-modified, fractal-like, and probability distribution function models

Column adsorption studies frequently adopt classical breakthrough curve models such as semi-mechanistic Bohart-Adams and Thomas models. They are logistic functions which simulate symmetrically sigmoidal curves centrosymmetric at 50% breakthrough; consequently, they fail and estimate erroneous results when dealing with asymmetric breakthrough curves. This work analyses and compares the trend of how log-modified, fractal-like modified, and probability distribution function models simulate asymmetric breakthrough curves with varied extents of tailing. We generated the asymmetric breakthrough curves by varying the bed depth: 6 mm, 9 mm, and 12 mm on a glass microcolumn of 100 mm length and 5.5 mm inner diameter at a fixed flow rate of 1 mL/min using 10 mg/L bisphenol-A as adsorbate and polyaniline as adsorbent. The asymmetrical curves were a consequence of polyaniline’s low specific surface area of 6.96 m²/g, heterogeneous particle size distribution, slow intraparticle and surface diffusion. The log-Bohart-Adams and fractal-like Bohart-Adams models perfectly fit the curves regardless of symmetry although log-Bohart-Adams performed subpar with increased tailing. The fractal-like Bohart-Adams model accurately estimated the breakthrough times of 13 min, 26 min, and 90 min for the 6 mm, 9 mm, and 12 mm bed depths with a critical bed depth of 5.65 mm. The normal and Gompertz probability distribution functions were unable to adapt to asymmetry of the curves owing to their fixed inflection points at c/cc = 0.5 and 0.37 respectively. Although the Weibull, log-normal, and log-Gompertz functions have floating inflection points, only log-Gompertz function had a satisfactory fit (Radj2>0.98) regardless of symmetry.

Removal of antibiotics through fixed bed adsorption: Comparison of different breakthrough curve models

Fixed bed adsorption serves as an effective method for eliminating organic micropollutants, including antibiotics, from water. To evaluate the performance of fixed bed adsorbers, researchers typically rely on the use of breakthrough curve models. Of particular significance is the accuracy of these models in predicting the time at which a specific breakthrough concentration occurs. In this study, we conducted a comparative analysis of four distinct breakthrough curve models. Within this set of models, the Thomas and Yan models are well-established, while the log-Gompertz and Chu–Hashim models are more recent additions to the field. The log-Gompertz model is essentially empirical, whereas the Chu–Hashim model represents a modified version of the Thomas model. The Chu–Hashim model incorporates the concept of steric hindrance, accounting for the decline in the rate of adsorption as the adsorber approaches saturation. Our modeling study revolved around the adsorptive removal of antibiotics, specifically flumequine and tetracycline. The findings revealed that both the Thomas and Yan models provided poor correlations to the antibiotic breakthrough data. Furthermore, they consistently underestimated the time at which a specific breakthrough concentration was reached. The Thomas model performed the worst in this respect. In contrast, both the log-Gompertz and Chu–Hashim models correlated well with the experimental breakthrough data, with the Chu–Hashim model consistently delivering superior correlations. Additionally, the breakthrough times predicted by these recently introduced models closely aligned with the experimental times, showcasing their practical utility and superiority over the widely used Thomas and Yan models.

Breakthrough curve modeling for lysozyme by ion-exchange nanofiber membrane: Linear and nonlinear analysis

BackgroundNanofibers prepared by electrospinning technology are widely used as an adsorber in protein purification processes. However, the evaluation of dynamic adsorption performance has not been reported yet. MethodsLysozyme was subjected to assess dynamic adsorption of weak ion exchange nanofiber membranes by applying a continuous flow system. Different operating conditions were selected to study the lysozyme adsorption breakthrough curve, which included four factors: pH, feedstock lysozyme concentration, feed flow rate, and stacked membrane layers. The breakthrough curve was applied to analyze the performance for dynamic binding with lysozyme as a model protein. In addition, the adsorption models (Bohart-Adams, Thomas, Yoon-Nelson, and BDST) were fitted to the breakthrough curves using linear and nonlinear regression analysis. Significant findingsIt was found that the four operating parameters had considerable influences on the dynamic adsorption performance. Among these models, the breakthrough curve was well-fitted by using linear regression analysis of the Yoon-Nelson model. The breakthrough curve characteristics could be used to describe the dynamic binding performance of interested membranes to lysozyme molecules.

Experimental Design and Breakthrough Curve Modeling of Fixed-Bed Columns Utilizing a Novel 3D Coconut-Based Polyurethane-Activated Carbon Composite Adsorbent for Lead Sequestration

This study presents a novel polyurethane-activated carbon composite (PACC) as an effective and sustainable adsorbent for treating lead-ion-contaminated waters. The PACC was characterized using Scanning Electron Microscopy with Energy Dispersive X-ray (SEM-EDX), Fourier Transform Infrared Spectroscopy (FTIR), Brunauer, Emmett, and Teller (BET) surface area analyzer, X-ray Diffraction (XRD), and Thermogravimetric Analyzer (TGA) to evaluate its physicochemical and thermal properties. Furthermore, the PACC was employed in an experimental column adsorption setup to investigate its adsorption performance and to develop a dynamic method suitable for industrial implementation. Parameters such as bed height (50, 100, 150 mm), flow rate (4, 6, 8 mL min−1), pH (2, 4, 6), and initial metal-ion concentrations (10, 50, 100 mg L−1) were examined. The experimental data exhibited strong agreement with the Thomas and Yoon–Nelson models (R2 ≥ 0.96), indicating efficient adsorption mechanisms. Remarkably, the used adsorbent has the potential for facile regeneration without substantial loss in capacity. The PACC demonstrated excellent adsorption performance for lead ions in aqueous solutions in a fixed-bed column system. Thus, the novel PACC material holds the potential for scalable application in industrial settings to address water pollution challenges, especially in regions with uncontrolled effluent discharge.

Breakthrough Curve Modeling and Analysis for Lysozyme Adsorption by Tris(hydroxymethyl)aminomethane Affinity Nanofiber Membrane.

In this study, a polyacrylonitrile nanofiber membrane was first hydrolyzed and then functionalized with tris(hydroxymethyl)aminomethane (P-Tris), then used as an affinity nanofiber membrane for lysozyme adsorption in membrane chromatography. The dynamic adsorption behavior of lysozyme was investigated in a flow system under various operating parameters, including adsorption pHs, initial feed lysozyme concentration, loading flow rate, and the number of stacked membrane layers. Four different kinetic models, pseudo-first-order, pseudo-second-order, Elovich, and intraparticle diffusion kinetic models, were applied to experimental data from breakthrough curves of lysozyme. The results showed that the dynamic adsorption results were fitted well with the pseudo-second-order kinetic model. The breakthrough curve experimental results show significant differences in the breakthrough time, the dynamic binding capacity, the length of the mass transfer zone, and the utilization rate of the membrane bed under different operating parameters. Four dynamic adsorption models (i.e., Bohart-Adams, Thomas, Yoon-Nelson, and BDST models) were used to analyze the breakthrough curve characteristics of the dynamic adsorption experiments. Among them, the Yoon-Nelson model was the best model to fit the breakthrough curve. However, some of the theoretical results based on the Thomas and Bohart-Adams model analyses of the breakthrough curve fit well with the experimental data, with an error percentage of <5%. The Bohart-Adams model has the largest difference from the experimental results; hence it is not suitable for breakthrough curve analysis. These results significantly impact dynamic kinetics studies and breakthrough curve characteristic analysis in membrane bed chromatography.

Modeling of breakthrough curves in removal of Cr(VI) and methylene blue using immobilized activated carbon from natural rubber waste

The activated carbon fines, derived from rubber sludge, were effectively immobilized inside calcium alginate beads to remove Cr(VI) ions and methylene blue (MB) in a fixed bed reactor after characterization of beads (FTIR, FESEM-EDS, BET, and thermogravimetric analysis) and batch study. The Langmuir batch uptake capacity was 136.45 and 324.87 mg g−1 for Cr(VI) and MB, respectively, at 30 °C. Contrary to the usual interpretation, it was shown that fitting of PFO model to experimental batch kinetic data may result from diffusive mechanism. Conventional practice of comparison of Bohart-Adams, Thomas, and Yoon-Nelson model being erroneous, these models were replaced by a generic function to explain breakthrough (BTC) curves. The equilibrium dispersive model (axial dispersion coefficient: 0.35 × 10−4 - 2.90 × 10−4 m2 min−1) predicted BTC for intermediate flow rates (5–15 mL min−1) and inlet concentrations (5–15 mg L−1) better than the one based on adsorption kinetics.

Column studies on the removal of chromium, lead, and Arsenic (Cr6+, Pb+2, and As3+) ions using graphene coated iron oxide (GCIO) as efficient nanoadsorbents

The efficient graphene coated iron oxide (GCIO) nanoadsorbent was prepared for removal of various ions, viz., Cr(VI), Pb(II), and As(III), by coating graphene onto the iron oxide surfaces taken as a base material. The as-prepared nanoadsorbent was further characterized by several analytical techniques such as Fourier transform infrared (FTIR) spectroscopy, energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscopy (TEM), Raman spectroscopy, Differential scanning calorimetry (DSC), and Zeta-potential measurements, respectively. These techniques provided valuable information about the nanoadsorbent and confirmed the interactions between Cr6+, Pb2+, and As3+ ions and the nanoadsorbent. The effect of concentration of adsorbate solution, contact time between adsorbate–adsorbent, and flow rate of adsorbate were studied using a sensitive, simple, and selective spectrophotometric method that enabled quantification of Cr6+, Pb+2, and As3+ ions, respectively. Various modeling of breakthrough curves was applied for monitoring progress of the adsorption process and the results showed that the three metal ions followed second order kinetic model thus confirming that GCIO is an excellent, effective, and economic adsorbent.

Divalent cation contributions to the co-transport and deposition of functionalized multi-walled carbon nanotubes in porous media in the presence of bentonite or goethite nanoparticles: Experiment and simulation

This work investigates the influence of cation type (Ca2+ as compared to K+) on the co-transport and deposition of functionalized multi-walled carbon nanotubes (MWCNTs) with negatively (bentonite nanoparticles, BNPs) or positively (goethite nanoparticles, GNPs) charged natural nanoparticles under the same ionic strength (IS = 1 mM) conditions. In packed column tests with quartz sand (QS), the co-transport of MWCNTs was slightly increased by BNPs and inhibited by GNPs in both CaCl2 and KCl solutions, whereas the co-transport of BNPs or GNPs was facilitated by MWCNTs in both solutions. However, the co-transport of MWCNTs in the presence of BNPs or GNPs exhibited a different dependency on the cation type in quartz crystal microbalance with dissipation (QCM-D) tests. No deposition of MWCNTs and BNPs was observed in QCM-D studies in the presence of KCl, while enhanced deposition of MWCNTs and GNPs occurred in this same solution. In contrast, the deposition of both MWCNTs and BNPs or MWCNTs and GNPs increased in QCM-D in the presence of CaCl2. In both column and QCM-D studies, Ca2+ exhibited a more significant impact on co-transport than K+, especially for MWCNTs with GNPs than BNPs. Results from molecular dynamic simulations, aggregation studies, and interaction energy calculations indicate that non-DLVO interactions (e.g., H-bonding and cation-π interaction) between two nanoparticles (MWCNTs with BNPs or GNPs) played a non-negligible role in interpreting the deposition and co-transport in the presence of the divalent cation Ca2+. Mathematical modeling of breakthrough curves and retention profiles and aggregation results suggest that both straining and competitive blocking were enhanced and played dominant roles in the co-transport of MWCNTs in the presence of BNPs or GNPs in QS, especially in the presence of Ca2+. This work sheds novel insights on the contribution of divalent cations to interactions between two colloids and their co-transport in porous media. This information is needed to assess the environmental fate and risks of engineered nanoparticles (ENPs) and natural nanoparticles in aquatic and soil environments with abundant divalent cations.

Dynamic adsorption of CO2 by CHA zeolites – Size matters

The performance of K-CHA nanozeolite composed of discrete nanoparticles prepared by an organic template-free direct synthesis is compared to that of conventional micron-sized K-CHA with an order of magnitude difference in particle size and identical chemical composition (Si/Al ratio and cations) for the separation of dilute CO2 from N2. Breakthrough curve analysis of the zeolites meshed to identical sizes demonstrates the superior performance of nanozeolites for gas separation due to the significantly faster diffusion of CO2 molecules through the bed composed of meshed nanozeolite particles evidenced by the enhanced mass transfer, more rapid establishment of equilibrium, and faster desorption of CO2. Modelling of the CO2 breakthrough curves indicates enhanced mass transfer properties of the CHA nanozeolite due to the higher linear driving force parameter values. Variation of the modelling parameters and back-calculation of the diffusion coefficients indicates that axial diffusion contributes significantly to the mass transfer behaviour, yet also reveals significantly lower micropore diffusion resistance for the nano-sized K-CHA. These results demonstrate for rapid kinetically controlled sorption-based separations, that by reducing the size of the discrete crystallites of the meshed adsorbent particle by an order of magnitude, significant improvements in the utilization of the bed can be achieved due to the shortening of the mass-transfer zone, improving the separation performance.

Mathematical modeling of breakthrough curves for 8-hydroxyquinoline removal from fundamental equilibrium and adsorption rate studies

The mathematical modeling of the dynamic adsorption of 8-Hydroxyquinoline on activated carbon (AC) in batch and fixed-bed adsorbers is outlined in this study. The model is centered on the mass transport phenomena occurring in the solution and inside the adsorbent and considers the axial dispersion, convective transport, intraparticle diffusion mechanisms, and adsorption on the active site. Moreover, this work proposes a methodology to solve the model based on basic studies of adsorption equilibrium and rate; therefore, the prediction of the breakthrough curves by fitting the mass transport parameters is not considered, which is a significant advance in the design of fixed-bed columns. The equilibrium results demonstrated that 8-HQ adsorbs on AC by dispersive π-π and hydrophobic interactions with a mass 8-HQ adsorbed of 454 mg g−1. The kinetic study revealed that the time to achieve equilibrium diminished by up to 200 min upon establishing a turbulent stirring regime. In addition, it was found that intraparticle transport is governed by surface diffusion. Finally, using the information obtained in the batch regime, it was possible to interpret and predict the packed bed behavior in a broad range of operational conditions with an error of 10.6 % in the prediction of the breakthrough point.

Alteration of Tecoma chip wood waste into microwave-irradiated activated carbon for amoxicillin removal: Optimization and batch studies

Amoxicillin (AMOX) in wastewater can promote antibiotic resistance in bacteria and affecting aquatic ecosystems, due to inadequate removal by conventional wastewater treatment plants. This study aimed to (i) optimizing Tecoma chip wood based activated carbon (TCAC) to adsorb amoxicillin (AMOX) using response surface methodology (RSM) and (ii) evaluating AMOX adsorption through batch and continuous modes. The RSM revealed the optimum conditions to be 657 W, 20 min and 0.99 g/g for radiation power, radiation time and impregnation ratio (IR), respectively. These optimum conditions resulted in AMOX removal efficiency of 88.07 mg/g and 27.68 % of TCAC’s yield. The BET surface area and total pore volume of TCAC were 924.85 m2/g and 0.3485 cm3/g respectively. The surface of TCAC was occupied with several functional groups namely primary amine, hydroxy, alkyl carbonate and terminal alkyne. These functional groups enhanced the adsorption process by forming hydrogen bond with AMOX molecules. The isotherm study revealed that AMOX-TCAC adsorption system obeyed the Langmuir model and the maximum monolayer adsorption capacity, Qm is 357.14 mg/g. Pseudo-second order (PSO) model fitted the best for the adsorption of AMOX by TCAC in the kinetic studies. Boyd plot divulged that the rate limiting step in the adsorption process was the film diffusion. Thermodynamic study confirmed the adsorption process to be endothermic, spontaneous and controlled by physisorption. In bed column studies, the percentage removal of adsorbates was found to increase when the adsorbates flowrate decreased, adsorbates initial concentration decreased, and bed height increased. For the breakthrough curve model, the adsorption is best fitted to Yoon Nelson model. TCAC demonstrated its efficacy in the removal of AMOX, proving successful in both batch mode and continuous mode operations. These findings suggest the potential for scaling up TCAC production for industrial purposes, indicating its suitability for larger-scale applications.

Sequestration of Contaminants from Wastewater: A Review of Adsorption Processes

AbstractAdsorption has widespread applications in separation processes, particularly aiming at environmental decontamination owing to its economic and highly efficient outcomes. This literature studies various isotherm models concerning adsorption which is accompanied by information related to the mechanism of the adsorption process, which is a crucial aspect of the system design. Many modification techniques bring about a significant enhancement in the working capacity. The build‐up of industrial activities causes a spike in the dispersion of toxic compounds along with non‐biodegradable contaminants from industrial wastewater. The separation techniques have emerged with greater efficiency in eliminating specific pollutants in terms of discharge legislation. Such methods have been reviewed hereby in this document based on literature published lately. Concerning the process of adsorption, this review elucidates the adsorption isotherms, kinetic models, breakthrough curve modelling, thermodynamic concepts, and the regeneration of the support required in batch or continuous reactors.

Bayesian Computational Technique for Modeling Caffeine Adsorption in a Fixed-Bed Column: Use of the Maximum Adsorption Capacity Deterministically and Experimental Design

This work applied a Bayesian computational technique for parameter estimation of adsorption breakthrough curve models with experimental data of caffeine (CAF) adsorption onto granular activated carbon (GAC). Different operational conditions were evaluated (volumetric flow: Q, adsorbent mass: W, and initial CAF concentration: C0) by a two-level factorial experimental design (23) to determine the best operational conditions. The models (Thomas, Yoon–Nelson, Yan, Clark, Gompertz, and Log-Gompertz) were fitted to the experimental data, estimating and not estimating the maximum adsorption capacity (qS). For model selection, five statistical metrics were calculated. The results showed that the proposed Bayesian technique, not estimating qS, was effective and all analyzed operational conditions obtained 95% of CAF removal. In the best condition, when qS reached 7.317 mgCAF/gGAC, the model that best adjusted the experimental data was Log-Gompertz, being suitable for practical approaches, and for its mechanisms, the Clark model best predicted the evaluated fixed-bed column.

Green approach for fabrication of sand-bimetallic (Fe/Pb) nanocomposite as reactive material for remediation of contaminated groundwater using permeable reactive barrier

In this study, the quartz sand (QS) was supported by the nanoparticles (Fe/Pb) that were made using an in-situ green synthesis technique using pomegranate peel extract to produce a QS-Fe/Pb nanocomposite, it was utilized as a reactive material in permeable reactive barrier (PRB) for remediating the contaminated groundwater with ciprofloxacin(CIP) & copper(Cu(II)) in batch and continuous modes. The characterization of the nanocomposite was determined using many tests, including XRD, FTIR, SEM, EDX, TEM, and surface area. Several parameters influencing the removal process in batch and continuous modes were studied to obtain the best conditions that achieve the highest removal percent (99%) and to evaluate the activity of the nanocomposite as a reactive bed. Two isotherm models (Freundlich and Langmuir), three kinetic models (intraparticle diffusion, second-order, and pseudo-first), and five breakthrough curve models (Thomas-BDST, Bohart–Adams, Belter-Cussler-Hu Model, Yan, and Clark) were utilized. The results indicated that Freundlich and the pseudo-second-order models show a better fit for the batch experimental data with adsorption capacity of 15 and 9.8 mg/g for CIP & Cu(II), respectively, while Clark model was the most representative of the continuous experimental data. This study proved that the prepared nanocomposite could be a successful reactive material in PRB.

Fixed bed column experiments using cotton gin waste and walnut shells-derived biochar as low-cost solutions to removing pharmaceuticals from aqueous solutions

Acetaminophen (ACT), sulfapyridine (SPY), ibuprofen (IBP) and docusate (DCT) are pharmaceuticals with widespread usage that experience incomplete removal in wastewater treatment systems. While further removal of these pharmaceuticals from wastewater effluent is desired prior to beneficial reuse, additional treatment technologies are often expensive and energy intensive. This study evaluated the ability of biochar produced from cotton gin waste (CG700) and walnut shells (WS800) to remove four pharmaceuticals (ACT, SPY, IBP, and DCT) from aqueous solution. Physico-chemical properties of the biochars were characterized by Brunauer-Emmett-Teller (BET) analysis, scanning electron microscopy (SEM), Fourier Transform Infrared Spectroscopy (FT-IR), and zeta potential. The increased pyrolysis temperature during the production of WS800 led to an increase in the specific surface area and increased dehydration of the biochar represented by the loss of the OH-group. Fixed-bed column experiments were performed to determine the difference in removal efficiency between the biochars and elucidate the effects of biochar properties on the adsorption capacity for the pharmaceuticals of interest. Results showed that CG700 had a greater affinity for removing DCT (99%) and IBP (50%), while WS800 removed 72% of SPY and 68% of ACT after 24 h. Adsorption was influenced by the solution pH, surface area, net charge, and functional groups of the biochars. The mechanisms for removal included pore filling and diffusion, hydrophobic interactions, hydrogen bonding, and π-π electron donor acceptor interactions. To conduct predictive modeling of the column breakthrough curves, the Thomas, Adams-Bohart, and Yoon-Nelson models were applied to the experimental data. Results demonstrated that these models generally provided a poor fit for the description of asymmetrical breakthrough curves. Overall, the results demonstrate that biochars from cotton gin waste and walnut shells could be used as cost-effective, environmentally friendly alternatives to activated carbon for the removal of pharmaceuticals from aqueous solutions.