Integration of machine learning and meta-analysis reveals the behaviors and mechanisms of antibiotic adsorption on microplastics.

Microplastics (MPs) can adsorb antibiotics (ATs) to cause combined pollution in the environment. Research on this topic has been limited to specific types of MPs and ATs, resulting in inconsistent findings, particularly for the influencing factors and adsorption mechanisms. Therefore, this study combined meta-analysis and machine learning to analyze a dataset comprising 6805 records from 123 references.

Adsorption behavior and mechanism of heavy metals onto microplastics: A meta-analysis assisted by machine learning.

Microplastics (MPs) have the potential to adsorb heavy metals (HMs), resulting in a combined pollution threat in aquatic and terrestrial environments. However, due to the complexity of MP/HM properties and experimental conditions, research on the adsorption of HMs onto MPs often yields inconsistent findings. To address this issue, we conducted a comprehensive meta-analysis assisted with machine learning by analyzing a dataset comprising 3340 records from 134 references.