Studies of adsorption of heavy metals onto spent coffee ground: equilibrium, regeneration, and dynamic performance in a fixed-bed column

"Equilibrium and dynamic adsorption of heavy metals onto spent coffee ground (SCG) were studied. The equilibrium adsorption of Cd2+, Cu2+, and Pb2+ in a batch system was modeled by an ion-exchange model (IEM) based on an ion-exchange of heavy metals with calcium and protons bonded to active sites on SCG surface. The maximum amount of adsorbed metal ions obtained using the IEM was 0.12, 0.21, and 0.32 mol/g of Cd2+, Cu2+, and Pb2+, respectively. Regeneration of SCG was evaluated using citric acid, calcium chloride, and nitric acid. The observed trend of desorption efficiency through four adsorption-desorption cycles was HNO3 > CaCl2 > C6H8O7. The effect of process variables such as flow rate and bed height during the dynamic adsorption was evaluated. Moreover, the applicability of a mass transfer model based on external mass transfer resistance, axial dispersion, and ion-exchange isotherm was evaluated, and the results were in good agreement with the experimental data for the adsorption in SCG packed column. The sensitivity analysis of the model parameters showed that axial dispersion coefficient is the most significant parameter in the dynamic simulation. The results obtained showed the potential of SCG as a low-cost material for wastewater metal removal in continuous systems.

Ciprofloxacin, ranitidine, and chlorphenamine removal from aqueous solution by adsorption. Mechanistic and regeneration analysis.

This work was supported by Consejo Nacional de Ciencia y Tecnología, for the schoolarship CVU49215Several studies have reported the presence of pharmaceuticals in freshwater bodies all around the world. For this investigation, the removal of the pharmaceuticals ciprofloxacin (CIP) ranitidine (RNT), and chlorphenamine (CPM) using lignocellulose-derived granular activated carbon (GAC) was analyzed, and the physicochemical mechanisms of removal were elucidated. Additionally, the textural and surface properties of the GAC were evaluated, the concentrations of the contaminants were monitored with UV–Vis Spectrophotometry. The results revealed that GAC is a mesoporous material with a surface area of 940 m2/g and an acidic character with a point of zero charge (pH PZC) around 2. The adsorption isotherms showed a consistent behavior with the Prausnitz–Radke model, reporting adsorption capacities of 668, 521, and 582μmol/g (221, 173 and 193 mg/g), at an equilibrium concentration of 50μmol/L, pH 7 and 25 °C for CIP, RNT and CPM, respectively. Moreover, studies at different pH levels, temperature, and reversibility suggested that adsorption obeys physical mechanisms, which led to the proposal of a chemical regeneration process with organic (ethanol and methanol) and inorganic (NaOH and HCl) diluents. Better results were obtained using the inorganic diluents, ranging between 44 and 73% thermodynamic desorption. Additionally, three reuse cycles were successfully performed at the best conditions, with a regeneration efficiency in the range of 68%–98% for each of the pharmaceuticals. The results demonstrate the viability of the use of GAC for the removal of drugs with different characteristics in scenarios that are very close to the real ones.Consejo Nacional de Ciencia y Tecnología CVU4921

Phenol adsorption onto coffee waste - granular activated carbon: kinetics and equilibrium studies in aqueous solutions

abstract In this research, the production of granular activated carbon from coffee waste (CW) by chemical activation with zinc chloride was studied by using a 23 factorial design with the three responses (surface area, yield, and hardness) and studying three factors (the activation temperature, activation time, and impregnation ratio). The findings expose that after the experimental design, the highest response values were achieved at an activation temperature of 600°C, an activation time of 40 min, and an impregnation ratio of 1.5 g ZnCl2 g–1 CW. At these conditions, the experimental tests produced a surface area of 1,279 m2 g–1. Batch studies of phenol adsorption onto coffee waste-activated carbon (CW-GAC) were performed at different solution pH, stirring speeds, and initial phenol concentrations. The maximum phenol adsorption capacity onto CW-GAC was 160.52 mg g−1 at pH 7. The adsorption kinetics was affected by stirring speed, the required time to achieve equilibrium decreased from 150 to 120 min when stirring speed varied from 200 to 400 min–1. Film and intraparticle diffusion mechanisms controlled the adsorption of phenol onto CW-GAC. Finally, the porous material developed in this research is capable of sequestering phenol from aqueous solutions to a higher extent than similar lignocellulosic-based activated carbons. Keywords: Adsorption; Coffee; Factorial experimental design; Granular activated carbon; Lignocellulosic wast

Remoción del colorante AV7 presente en solución acuosa mediante carbón activado

Se investigó la remoción del colorante ácido violeta 7 mediante carbón activado en un sistema de adsorción en lote. Se estudiaron los efectos de parámetros experimentales en la capacidad de adsorción, tales como la masa del adsorbente y el pH. Las mejores condiciones experimentales para la adsorción de ácido violeta 7 fueron a pH natural del colorante (pH 6) y 100 mg de adsorbente al obtener una capacidad de adsorción de 102 mg/g. La cinética de adsorción fue descrita por el modelo de Pseudo-Segundo orden que está basado en un mecanismo de quimisorción

Artificial neural network modeling of phenol adsorption onto barley husks activated carbon in an airlift reactor.

Purpose and method of the study: The production of activated carbon from barley husks (BH) by chemical activation with zinc chloride was optimized by using a 23 factorial design with replicates at the central point, followed by a central composite design with two responses (the yield and iodine number) and three factors (the activation temperature, activation time, and impregnation ratio). Both responses were simultaneously optimized by using the desirability functions approach to determine the optimal conditions of this process. The experimental data from the batch phenol adsorption onto barley husks activated carbon (BHAC) was represented by adsorption isotherms (Langmuir and Freundlich) and kinetic models (pseudo-first and pseudosecond order, and intraparticle diffusion models), besides the regeneration of phenolloaded BHAC with different solvents was evaluated. Experimental data confirmed that the breakthrough curves were dependent on BHAC dosage, phenol initial concentration, air flow rate, and influent flow rate. Adaline and feed-forward backpropagation Artificial Neural Networks (ANNs) were developed to predict the breakthrough curves for the adsorption of phenol onto barley husks activated carbon (BHAC) in an airlift reactor. Feed-forward back-propagation networks were tested with different quantity of neurons at the hidden layer to determine the optimal number of neurons in the ANN architecture to represent the breakthrough curves performed at different operational conditions for the airlift reactor. Contributions and conclusions: After the simultaneous dual optimization of BHAC production, the maximal response values were obtained at an activation temperature of 436 °C, an activation time of 20 min, and an impregnation ratio of 1.1 g ZnCl2 g BH-1 , although the results after the single optimization of each response were quite different. At these conditions, the predicted values for the iodine number and yield were 829.58 ± 78.30 mg g-1 and 46.82 ± 2.64%, respectively, whereas experimental tests produced values of 901.86 mg g-1 and 48.48%, respectively. Moreover, activated carbons from BH obtained at the optimal conditions mainly developed a porous vstructure (mesopores > 71% and micropores > 28%), achieving a high surface area (811.44 m2 g-1 ) that is similar to commercial activated carbons and lignocellulosic-based activated carbons. These results imply that the pore width and surface area are large enough to allow the diffusion and adsorption of pollutants inside the adsorbent particles. Freundlich isotherm model satisfactorily predicted the equilibrium data at 25 and 35 °C, whereas the Langmuir isotherm model well represented the equilibrium data at 45 °C. The maximum phenol adsorption capacity onto BHAC was 98.83 mg g-1 at 25 °C and pH 7, similar to phenol adsorption onto commercial activated carbons. The kinetic data were adequately predicted by both the pseudo-first order and intraparticle diffusion models. The external mass transfer was minimized at stirring speeds greater than 400 min-1 , and the adsorption kinetics are affected by both initial phenol concentration and temperature. Adsorption equilibrium was reached within 40 and 200 min at initial phenol concentration of 1000 mg L-1 at 35 °C and 30 °C, respectively. Ethanol/water solutions at 10% V/V were the most effective regenerating agent, with desorption capacity of 47.79 mg g-1 after five adsorption-desorption cycles. The breakthrough curves of phenol adsorption onto BHAC in an airlift reactor in continuous operation were adequately predicted with feed-forward back-propagation ANN architecture with 2 neurons in the hidden layer for the single-input single-output problem. Correlation coefficients higher than 0.95 were observed between the breakthrough curves predicted by the developed Adaline network and those obtained experimentally for the multiple-input single-output problem. Further improvements and generalization of the developed predictive Adaline network are discussed