Utilization of metal industry solid waste as an adsorbent for adsorption of anionic and cationic dyes from aqueous solution through the batch and continuous study

Efficient extraction of metals (Fe, Zn, Pb) from hazardous jarosite using ionic liquid and waste-derived solvents

The present study evaluated a solvo-metallurgical technique for metal extraction from industrial solid waste (jarosite) using ionic liquids (ILs) and waste-derived solvents. The jarosite contains a considerable amount of metal ions, namely iron, zinc, and lead. The jarosite was characterized by XRF, XRD, SEM, and FTIR techniques. The parameters affecting metal extraction, such as stirring time, acid molarity, and temperature, have been examined. Aliquat 336 was used to extract metals from fresh and roasted jarosite after equilibration with HCl. The response surface methodology (RSM) was used to optimize the parameters for the maximum metal extraction using [A336] [Cl]. Maximum extraction of iron (86.75%), zinc (51.96%), and lead (94.38%) from roasted jarosite was achieved at optimum conditions (125-min stirring time, 5 M acid molarity, and 20 ml/g liquid-to-solid ratio). Furthermore, the metal extraction was investigated using waste-derived solvents. The results show that waste-derived solvents, such as biomass and plastic pyrolysis oil, can effectively extract metals from fresh and roasted jarosite. Biomass pyrolysis oil achieved the highest extraction at 50 °C for 90 min, while plastic pyrolysis oil achieved the highest extraction at 50 °C for 60 min from roasted jarosite. These solvents are also cost-effective because they are made from waste plastic and biomass.

Comparing different versions of the Yoon-Nelson model in describing organic micropollutant adsorption within fixed bed adsorbers

The Yoon-Nelson model serves as a widely used tool for describing the breakthrough behavior of organic micropollutants within fixed bed adsorbers. This study aims to augment its modeling efficacy through two proposed refinements found in the literature: a logarithmic transformation and the incorporation of steric hindrance effects. We systematically evaluated the original Yoon-Nelson model alongside the modified versions, using breakthrough data associated with micropollutant adsorption on solid materials. Three distinct cases were scrutinized: (1) caffeine adsorption on activated carbon; (2) tetracycline adsorption on hierarchical porous carbon; and (3) diclofenac adsorption on organoclay. While all three models demonstrated comparable performance with highly symmetric breakthrough data in case 1, their efficacy diverged significantly when confronted with strongly asymmetric breakthrough data in cases 2 and 3. The original Yoon-Nelson model and the logarithmically modified version fell short in accurately representing these intricate breakthrough curves. In contrast, the version incorporating steric hindrance effects showcased substantial accuracy, outperforming other models in capturing the complexities of asymmetric breakthrough data. This advancement markedly enhances the modeling accuracy and versatility of the Yoon-Nelson model, particularly in assessing the dynamic behavior of organic micropollutants within fixed bed adsorbers.

Malachite green (cationic dye) removal with modified Pinus brutia biochar

Dyes are frequently used in industries such as textile, leather, paper and printing, to water sources causes harmful effects on the environment and human health. Therefore, it is crucial to effectively remove colored contaminants from water in order to protect the environment and public health, maintain biodiversity and preserve the esthetic aspects of water resources. In this study, wood chips obtained from Pinus brutia (PB) tree grown in many parts of the world were turned into biochar and then modified and used for the removal of malachite green, a cationic dye. For this purpose, biochar (PBB) was made by collecting PB wood and turning it into chips (PB). Later, PBB was modified to gain nano-magnetic properties. The structure of the obtained PBB and nM-PBB adsorbents was characterized by FT-IR. pH (2-9), temperature (25 °C-55 °C), time change (15 min-240 min), adsorbent amount change (0.05 g-0.45g) and MG concentration (25 mg/L-250 mg/L) were investigated in MG removal of PBB and nM-PBB. The process was found to be pseudo-second-order and spontaneous endothermic reaction. PBB and nM-PBB were found to be suitable for Langmuir isotherm in MG removal (qmax=13.004 mg/g for PBB, qmax=18.215 mg/g for nM-PBB).

Computational and experimental assessment of efficient dye adsorption method from aqueous effluents by halloysite and palygorskite clay minerals

The removal of dyes from effluents of textile industries represents a technological challenge, due to their significant environmental impact. The application of halloysite (Hal) and palygorskite (Pal) clay minerals as adsorbents for the removal of Congo red (CR) and methylene blue (MB) was evaluated in this work. The materials were applied both in natural and acid-treated forms, and characterized by XRD, XPS, SEM-EDS, FTIR, and N2 adsorption-desorption isotherm techniques to identify their properties and main active sites. The adsorbents showed potential to remove CR (> 98%) and MB (> 85%) within 180 min, using 0.3 g adsorbent and initial dye concentration of 250 mg L-1. Semi-empirical quantum mechanical calculations (SQM) confirmed the interaction mechanism between dyes and the adsorbents via chemisorption (- 69.0 kcal mol-1 < Eads <  - 28.8 kcal mol-1), which was further observed experimentally due to the high fit of adsorption data to pseudo-second order kinetic model (R2 > 0.99) and Langmuir isotherm (R2 > 0.98). The use of Pal and Hal to remove dyes was proven to be economically and environmentally viable for industrial application.