In situ remediation of 2,4-dicholrophenoxyacetic acid herbicide using amine-functionalized imidazole coordination complexes

Adsorption simulation of 2,4-D pesticide on novel zinc-based 2-amino-4-(1H-1,2,4-triazole-4-yl)benzoic acid coordination complexes using machine learning approach

The capacity of zinc-based 2-amino-4-(1H-1,2,4-triazole-4-yl)benzoic acid coordination complex (Zn(NH2-TBA)2) and modified Zn(NH-TBA)2COMe complex for removal of 2,4-dichlorophenoxyacetic acid (2,4-D) from aqueous solutions was investigated through adsorption modeling and artificial intelligence tools. Analyzing the adsorption characteristics of pesticides helps in studying the groundwater pollution by pesticides in agriculture area.In this study, Zn(NH2-TBA)2 was synthesized using Schiff base and its surface was modified using acetic anhydride group and their physical characteristics were identified using proton NMR, FTIR, and XRD. NMR results showed maximum modification yield obtained was 65% after 5 days. The porous structure and surface area monitored using nitrogen isotherm and BET surface area analysis presented relatively less surface area and porosity after modification. Adsorption modelling indicated that Toth model with a maximum adsorption capacity of 150.8 mg/g and 100.7 mg/g represents the homogenous adsorption systems which satisfy both low- and high-end boundary of adsorbate concentration in all settings according to the optimum point, while the kinetics and rate of 2,4-D adsorption follow the pseudo-first-order kinetic model in all situations. Artificial neural network (ANN), support vector regression, and particle swarm optimized least squares-support vector regression (PSO-LSSVR) were used for the optimization and modelling of adsorbent mass, adsorbate concentration, contact time, and temperature to develop predictive equations for the simulation of the adsorption efficiency of 2,4-D pesticide. The obtained results exhibited the better performance of ANN and PSO-LSSVR for prediction of adsorption results. The mean square error values of ANN (0.001, 0.012) and PSO-LSSVR (0.121, 0.105) were obtained for Zn(NH2-TBA)2 and Zn(NH-TBA)2COMe, respectively, while their respective coefficient of determination (R2) obtained were 0.999 and 0.988 for ANN and 0.980 and 0.825 for PSO-LSSVR. The study specified that machine learning predictive behavior performed better for Zn(NH2-TBA)2 compared to Zn(NH-TBA)2COMe that is also supported by theoretical kinetics and isotherm models. The research concludes that artificial intelligence models are the most efficient tools for studying the predictive behavior of adsorption data.

A novel magnetic adsorbent from activated carbon fiber and iron oxide nanoparticles for 2,4-D removal from aqueous medium

Carbonaceous materials have been widely applied as adsorbents, but there are some factors that affect their efficiency. In this context, advances in nanotechnology provide new and more efficient methodologies for water treatment. This study evaluated the efficiency of a novel carbon-based adsorbent developed from Brazilian polyacrylonitrile textile fiber and functionalized with iron oxide magnetic nanoparticles for the removal of 2,4-dichlorophenoxyacetic acid (2,4-D) from the aqueous medium. The synthesized adsorbent (ACF-Fe3O4) was characterized by FTIR, XRD, VSM, Zeta potential, SEM, EDX, and TEM. The characterization techniques showed that the adsorbent has peaks characteristic of its precursors and superparamagnetic characteristics, confirming the efficiency of the synthesis method. The adsorption tests evaluated the influence of adsorbent dosage, pH of the contaminant solution, contact time and temperature on the removal of 2,4-D. The experimental data were better adjusted by the pseudo-second order kinetic model and by the Langmuir isothermal model. The thermodynamic parameters revealed that the process is exothermic, spontaneous and thermodynamically favorable. Under the best experimental conditions, the maximum adsorption capacity obtained was 51.10 mg g-1 with an adsorbent concentration of 0.33 g L-1, natural pH of the solution, temperature of 288 K at the equilibrium time of six hours. Adsorbent reusage was studied in four desorption cycles. The adsorption mechanism can be explained through π-π bonds, hydrogen bonds and electrostatic interactions. The prepared material presented high-efficiency adsorption capacity of 2,4-D compared to other carbonaceous materials present in the literature, demonstrating its viability for the removal of this contaminant from the aqueous medium.

Adsorption of Phenoxyacetic Herbicides from Water on Carbonaceous and Non-Carbonaceous Adsorbents

The increasing consumption of phenoxyacetic acid-derived herbicides is becoming a major public health and environmental concern, posing a serious challenge to existing conventional water treatment systems. Among the various physicochemical and biological purification processes, adsorption is considered one of the most efficient and popular techniques due to its high removal efficiency, ease of operation, and cost effectiveness. This review article provides extensive literature information on the adsorption of phenoxyacetic herbicides by various adsorbents. The purpose of this article is to organize the scattered information on the currently used adsorbents for herbicide removal from the water, such as activated carbons, carbon and silica adsorbents, metal oxides, and numerous natural and industrial waste materials known as low-cost adsorbents. The adsorption capacity of these adsorbents was compared for the two most popular phenoxyacetic herbicides, 2,4-dichlorophenoxyacetic acid (2,4-D) and 2-methyl-4-chlorophenoxyacetic acid (MCPA). The application of various kinetic models and adsorption isotherms in describing the removal of these herbicides by the adsorbents was also presented and discussed. At the beginning of this review paper, the most important information on phenoxyacetic herbicides has been collected, including their classification, physicochemical properties, and occurrence in the environment.

Study on the migration mechanisms of water-soluble agents in high-pressure rotary jetting remediation

High-pressure rotary jetting (HPRJ) remediation is a recent-applied technology for in situ remediation of contaminated soils. The effectiveness of remediation depends upon the migration and distribution of the injected agents in the soil. However, the corresponding migration mechanisms have received little attention. In this study, laboratory HPRJ tests and numerical simulations were performed using chlorine (Cl^-) as a tracer to investigate the transport during HPRJ and the subsequent advection and diffusion. The test results showed that the HPRJ transported Cl^- into the mixing zone by eroding the sand, and the radius of the mixing zone could be reasonably predicted by the erosion model. The Cl^- concentration decreased linearly along the radial direction in the mixing zone. In addition, the Cl^- transport distance increased with the increase in nozzle diameter, jetting times, especially injection pressure, and decreased with an increasing rotation speed. The Cl^- concentration and radial uniformity were correlated positively with rotation speed, particularly nozzle diameter and jetting times. Numerical simulation showed that part of Cl^- migrated from the mixing zone to diffusion zone by advection-diffusion after rotary jetting, which contributed positively to the agent distribution distance and uniformity. The Cl^- migration was dominated by advection in the initial stage (30 days), while diffusion became more important thereafter.