Integrating mechanistic and machine learning understanding to reveal recovery-controlling factors in vegetable oil-mediated separation of microplastics from landfill matrices

Machine Learning Approaches for Predicting Microplastic Removal

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Researchers applied Bayesian optimization combined with machine learning models — including boosted regression trees, neural networks, and support vector regression — to predict microplastic removal during coagulation, finding the BOA-BRT hybrid outperformed conventional methods by up to 71%, with microplastic particle size identified as the most influential variable.

Advanced Characterization, Machine Learning and Optimization of Waste Polyethylene Terephthalate Microplastics for the Removal of Emerging Pollutants from Wastewater in Single and Multicomponent Systems

Advanced Characterization, Optimization and Machine Learning of Waste Polyethylene Terephthalate Microplastics for the Removal of Emerging Pollutants from Wastewater in Single and Multicomponent Systems

Microplastics in aquatic environments: Bridging occurrence and mitigation through machine learning detection and bioremediation strategies

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Tiny plastic particles called microplastics are showing up in shockingly high amounts in our water, sometimes millions of particles per liter, and they can end up affecting both aquatic life and, potentially, the food and water we consume. This review paper (summarizing existing research) highlights two promising solutions: certain fungi and algae that can remove over 90% of microplastics from water in lab settings, and AI tools that can quickly detect and track plastic pollution. The catch is that these cleanup methods work great in controlled settings but haven't yet been proven to work reliably in messy, real-world water systems.

The Efficiency of Different Digestion and Separation Methods for Extracting Microplastics in Typical Organic Solid Waste

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This study compared seven digestion protocols and three separation methods for extracting microplastics from organic solid waste such as compost and biogas residues, identifying 30% hydrogen peroxide digestion followed by two-stage density separation as optimal with over 86% recovery. Standardized extraction methods are critical for generating comparable data on microplastic contamination in agricultural inputs that ultimately transfer plastic particles into soils.