Simulate permeable reactive barrier by using a COMSOL model and comparison with the Thomas, Yoon-Nelson and Clark models for CR dye remediation by composite adsorbent (sewage and waterworks sludge)

Machine learning for the adsorptive removal of ciprofloxacin using sugarcane bagasse as a low-cost biosorbent: comparison of analytic, mechanistic, and neural network modeling

Contamination with traces of pharmaceutical compounds, such as ciprofloxacin, has prompted interest in their removal via low-cost, efficient biomass-based adsorption. In this study, classical models, a mechanistic model, and a neural network model were evaluated for predicting ciprofloxacin breakthrough curves in both laboratory- and pilot scales. For the laboratory-scale (d = 2.2 cm, Co = 5 mg/L, Q = 7 mL/min, T = 18 °C) and pilot-scale (D = 4.4 cm, Co = 5 mg/L, Q = 28 mL/min, T = 18 °C) setups, the experimental adsorption capacities were 2.19 and 2.53 mg/g, respectively. The mechanistic model reproduced the breakthrough data with high accuracy on both scales (R2 > 0.4 and X2 < 0.15), and its fit was higher than conventional analytical models, namely the Clark, Modified Dose-Response, and Bohart-Adams models. The neural network model showed the highest level of agreement between predicted and experimental data with values of R2 = 0.993, X2 = 0.0032 (pilot-scale) and R2 = 0.986, X2 = 0.0022 (laboratory-scale). This study demonstrates that machine learning algorithms exhibit great potential for predicting the liquid adsorption of emerging pollutants in fixed bed.

Transport dynamics of rare earth elements in weathering crust soils

In modern industries, rare earth elements (REEs) are considered as essential metals and invaluable natural resources. Ion-adsorption deposits (IADs) are repositories of REE in the weathering crust soils, in which REEs are adsorbed on clay minerals. In the last few decades, the mining of REEs from IADs has caused substantial environmental damage owing to the overuse of leaching agents for the desorption and transport of REEs in weathering crust soils. These environmental issues have sparked extensive research interest in modeling REE transport dynamics in weathering crust soils. Nevertheless, because current models treat REE adsorption and transport independently, they do not accurately describe REE transport dynamics. Therefore, in this study, a unified workflow that synergizes adsorption and transport dynamics is proposed to predict REE transport. The adsorption of REEs on IADs was found to follow the Freundlich isotherm with the coefficient of determination exceeding 0.9826. The adsorption capacities of La3+, Sm3+, Er3+, and Y3+ reach 1.3127, 1.4423, 1.5793, and 1.1061 mg g-1 at 300 ppm, respectively. For the breakthrough curve, an advection-dispersion-adsorption-equation (ADAE) model was developed and utilized to accurately and reliably predict REE transport dynamics in soil columns. It was found the saturation time of REEs in soils is 39.22, 44.15, 50.64, and 32.17 h, respectively at 2 mL min-1 and decreased with the increase of flow velocity. The upper and lower limits of REE transport are ADAE-Freundlich and ADAE-Toth. More importantly, the model was applied to simulate REEs transport in field-scale weathering crusts over 100 years and predict REE accumulation in the highly weathered layered, which is found in natural weathering crusts. The qualitative prediction of REE transport dynamics in weathering crusts may help fundamentally lower the usage of leaching agents and mitigate concomitant the environmental impacts of mining.

Exploring the Micropore Functional Mechanism of N2O Adsorption by the Eucalyptus Bark-based Porous Carbon

Nitrous oxide (N2O), recognized as a significant greenhouse gas, has received insufficient research attention in the past. In view of their low energy consumption and cost-effectiveness, the application of porous materials in adsorption is increasingly regarded as a potent strategy to reduce N2O pollution. In this study, a series of microporous porous carbons with a preeminent specific surface area (244.54-2018.08 m2 g-1), which are derived from the fast-growing eucalyptus bark, were synthesized by KOH activation at high temperatures. The obtained materials demonstrated a relatively fine N2O capture capability (0.19-0.68 mmol g-1) at normal temperature and pressure. More importantly, the optimal pore size affecting N2O adsorption (0.8 and 1.0 nm) has been detected, which is a meaningful view that has never been put forward in previous studies. The rationality of the N2O adsorption mechanism was also validated by combining the experimental analysis and Grand Canonical Monte Carlo (GCMC) simulation. The calculated results showed that 0.8 and 1.0 nm of the porous carbon were the preferred pore sizes for N2O adsorption, and the interaction force between N2O and the pore wall decreased with the increase of distance. This study provides a significant theoretical basis for the preparation of biomass porous carbon with excellent N2O adsorption performance and practical adsorption application.

New zeolite made from Tunisian raw clay: study and modeling for C3H6 breakthrough dynamic adsorption onto zeolite material

In this study, Tunisian raw clay (RC) was utilized as a cheap source of silicium and aluminum for the preparation of faujasite zeolite (FAUsyn) using the alkaline fusion technique. The zeolite's structural analysis was carried out using the XRD, nitrogen adsorption-desorption, and SEM-EDX techniques. The data collected demonstrate that the produced zeolite only included one homogeneous faujasite phase. Textural analysis shows that the FAUsyn prepared from RC has a hierarchical porosity (micro-, meso-, and macropores). The total porosity was found to be 0.33 cm3/g as well as the BET area was equal to 360 m2/g. Adsorption experiments for propene capture were performed using the FAUsyn as adsorbent material. The performance of the column was examined in relation to various parameter impacts, including flow rate (50, 100, and 150 mL/min), input concentration (4, 8, and 12 mg/L), and bed depth (10, 14, and 18 cm). Finally, experimental and theoretical studies were investigated to predict adsorption capacities and kinetics parameters. To clarify and estimate column inputs, a model that incorporates axial dispersion, Langmuir equation, and migration within the adsorbent's pore was improved. COMSOL Multiphysics software was used to execute the model and resolve it computationally. The results of the experiments and the expected breakthrough curves were very well agreed. Modeling obtained results can be extrapolated to industrial level.

A two-dimensional analytical model for heavy metal contaminants transport in permeable reactive barrier

Permeable reactive barrier (PRB) remediation technology has been widely used in the remediation of groundwater contamination. In numerical simulations, neglecting the non-uniform distribution of heavy metal contamination along the depth may lead to deviations between simulation results and reality. The distribution of heavy metals in the soil layer around a non-ferrous mining area in Hezhou, Guangxi, southern China was investigated, and it was found that the standard Gaussian function could well describe the non-uniform distribution of heavy metals in the soil layer. A two-dimensional analytical model solved by the finite element method was used to simulate the migration process of heavy metal contamination in the aquifer and PRB. The results show that the uniform distribution of contaminants along the depth ignores the dilution effect, which may underestimate the service life of the PRB and lead to an overly conservative design of the PRB. The breakthrough time of the PRB decreases with the increase of the maximum initial concentration (C_in,max) and the high concentration range (σ), and increases almost linearly with the barrier thickness (L_w). An optimal design method for PRB location and thickness is proposed, which can provide a reference for the engineering application of PRB.

A review of the main methods for composite adsorbents characterization

Adsorption is a promising technology for removing several contaminants from aqueous matrices. In the last years, researchers worldwide have been working on developing composite adsorbents to overcome some limitations and drawbacks of conventional adsorbent materials, which depend on various factors, including the characteristics of the adsorbents. Therefore, it is essential to characterize the composite adsorbents to describe their properties and structure and elucidate the mechanisms, behavior, and phenomenons during the adsorption process. In this sense, this work aimed to review the main methods used for composite adsorbent characterization, providing valuable information on the importance of these techniques in developing new adsorbents. In this paper, we reviewed the following methods: X-Ray diffraction (XRD); spectroscopy; scanning electron microscopy (SEM); N2 adsorption/desorption isotherms (BET and BJH methods); thermogravimetry (TGA); point of zero charge (pHPZC); elemental analysis; proximate analysis; swelling and water retention capacities; desorption and reuse.

Immobilization of microorganisms in activated zeolite beads and alkaline pretreated straws for ammonium-nitrogen removal from urban river water

The non-treated wastewater from residential areas contains high concentrations of ammonium-nitrogen (NH₄⁺-N). When discharged into the drainage water system, it deteriorates the water quality in urban rivers. This study used two types of materials to form eco-bags, using activated zeolite bead (AZB) and alkaline pretreated straw (APS), in geotextile bags for easy recovery and reuse. The AZB and APS provided the breeding habitat for the microorganisms that promoted biofilm formation on their surface. The immobilization of engineered denitrification microorganisms facilitated the removal of NH₄⁺-N from the urban river water. The NH₄⁺-N removal in the AZB and APS bags were in the range of 64-73%, and 56-61%, respectively, while the chemical oxygen demand (COD) removal in the AZB and APS bags ranged from 33-36%, and 30-31%, respectively. In addition, as evident from DNA and microbial community analysis, the microorganisms demonstrated a greater proclivity to grow and proliferate on the surface of AZB and APS and improved the water quality of urban rivers.