Separation Technologies and Policy Challenges in Addressing Microplastic Pollution

Abstract

Microplastic accumulation in aquatic systems has emerged as a critical environmental and public health issue, with particles 
detected in human organs and across diverse ecosystems. Despite growing awareness, current treatment technologies remain insufficient to address the pervasive contamination. Existing separation methods—physical, chemical, and biological—show variable efficiencies ranging from 65% to 100%, yet challenges persist due to microplastics’ small size, heterogeneous composition, and continuous release into the environment. Recent advancements include adsorption, membrane filtration, photocatalysis, electrochemical processes, and biological or enzymatic degradation, complemented by artificial intelligence driven detection and hybrid systems integrating multiple mechanisms such as sieving, density, and magnetic separation. 
However, literature highlights key challenges: limited scalability, energy intensity, secondary pollution, and inconsistent removal across particle sizes. To overcome these limitations, computational modelling and machine learning offer promising 
pathways for optimising process parameters, predicting separation efficiency, and designing adaptive treatment systems. 
Future research should focus on integrating advanced separation technologies into existing water treatment infrastructure, 
developing sustainable materials for microplastic capture, and establishing standardised assessment frameworks. Addressing 
these gaps is crucial to mitigate ecological disruption, protect biodiversity, and ensure safe water resources.