Fe(III) Adsorption onto Microplastics in Aquatic Environments: Interaction Mechanism, Influencing Factors, and Adsorption Capacity Prediction

The adsorption of Fe(III) onto the surface of microplastics (MPs) enhances their toxicity and mobility in aquatic environments, posing a serious threat to human health and ecosystem balance. This study investigated the adsorption mechanism and influencing factors of Fe(III) on three types of MPs with varying particle sizes and aging degrees using batch experiments in freshwater and saltwater. Machine learning (ML) techniques were employed to predict the adsorption capacity and conduct attribution analysis. The results showed that Fe(III) adsorption in both freshwater and saltwater followed Pseudo-First-Order kinetics and Langmuir isotherms, indicating a monolayer homogeneous physical reaction driven by oxygen-containing functional groups, hydrogen bonds and aromatic rings on the MP surface. The adsorption capacity of MPs for Fe(III) was higher in freshwater than in saltwater, and was positively correlated with the aging degree and pH value, but negatively correlated with the particle size. Among the tested ML models, the Random Forest and Gaussian Process Regression models with Bayesian Optimization performed well in predicting adsorption capacity, with pH value and aging degree identified as key factors based on SHAP analysis. This study conducted a comprehensive investigation of the adsorption behavior between MPs and Fe(III) in water, providing valuable insights for the risk assessment and prevention of MP and Fe(III) pollution in aquatic environments.