Detection of S-Metolachlor in Surface Water near Cornfields Using pH-Sensitive Green Molecularly Imprinted Polymers

In this study, <i>core-shell</i> molecularly imprinted polymers (CS-MIP) were utilized for the detection of the herbicide S-metolachlor in surface water samples, collected from a river and pond that are in the proximity of cornfields. The study revealed that no traces of herbicide were detected in the samples that were analyzed. The collected water samples were treated with membrane filtration-microfiltration and ultrafiltration. The adsorption isotherms were fitted using the Langmuir, Freundlich, Dubinin-Radushkevich, and Scatchard models. This indicated that the Scatchard model is the most appropriate for CS-MIP. The data obtained from the kinetic study were analyzed using the pseudo-first-order and pseudo-second-order models, as well as Fick's second law. For CS-MIP, the most suitable model was determined to be the particle diffusion model, while for <i>core-shell</i> non-imprinted polymers (CS-NIP), the film diffusion model was identified as the limiting step. A method for the desorption of S-metolachlor from the pH-sensitive sorbent bed has been developed, thereby enabling the material to be reused. The optimum eluent from the multicomponent solution was determined to be a 30% aqueous ethanol solution with a pH of approximately 9. This solution effectively removed the majority of contaminants, with the exception of S-metolachlor, which was retained within polymer pores.