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Modelling size and shape distributions of micro- and macroplastics emitted to the natural environment

Zenodo (CERN European Organization for Nuclear Research) 2024 Score: 45 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Yvette Mellink, Yvette Mellink, Koelmans Albert A., Yvette Mellink, Merel Kooi Koelmans Albert A., Yvette Mellink, Yvette Mellink, Merel Kooi Yvette Mellink, Merel Kooi Merel Kooi, Merel Kooi, Merel Kooi, Merel Kooi, Merel Kooi, Merel Kooi, Merel Kooi Merel Kooi Yvette Mellink, Merel Kooi Merel Kooi Merel Kooi Yvette Mellink, Joris Quik, Koelmans Albert A., Yvette Mellink, Yvette Mellink, Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Yvette Mellink, Merel Kooi Joris Quik, Merel Kooi Merel Kooi Merel Kooi Joris Quik, Merel Kooi Merel Kooi, Merel Kooi, Merel Kooi, Merel Kooi, Joris Quik, Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Merel Kooi Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Merel Kooi Koelmans Albert A., Koelmans Albert A., Merel Kooi, Merel Kooi, Merel Kooi Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Yvette Mellink, Yvette Mellink, Yvette Mellink, Koelmans Albert A., Koelmans Albert A., Merel Kooi

Summary

This study developed a model incorporating the physical size, shape, and density distributions of plastic particles to predict environmental risk more accurately than approaches based on mass alone. For the first time, physical property distributions were integrated into a risk assessment framework for plastics in water, soil, and air, improving exposure and hazard estimates.

Polymers

The risk of plastic particles to organisms and humans is largely determined by their physical properties, such as size, shape, and density, making it essential to assess these properties of plastics found in water, soil, and air for a proper risk assessment. This study, for the first time, incorporates the physical characteristics of plastics in a dynamic probabilistic material flow analysis (DPMFA) model. The DPMFA model simulates the flow of plastics from nine sources of plastic through the anthroposphere and to the natural environment. The sources include: clothing, household textiles, technical textiles, agriculture, tyre wear, paint, packaging, intentionally produced microplastics, and pellets. Model compartments represent different product subcategories (e.g., 'agricultural films' and 'wall paint'), processes (e.g., 'tumble drying clothes' and 'road cleaning') or locations (e.g., 'waste water treatment plant' and 'soil'). The time dimension of the model allows for incorporating both in-use plastic emissions and delayed generations of waste when products reach the end of their lifetime. We apply continuous probability density functions (PDFs) to describe the sizes and shapes of the plastic particles that flow between the model compartments. By assigning a size and shape PDF to each plastic particle flow, we can capture the differences in sizes and shapes between in-use and end-of-life plastic emissions. Here, we present our model predictions of the sizes, shapes, and densities of plastic particle mixtures in various environmental compartments (water, soil, and air), and identify the contributions of the initial nine plastic source categories to relevant environmental compartments. The plastic emission estimates, together with the physical properties, form the basis for modelling subsequent transport and fate processes of microplastics in the environment. The initial size and shape distributions of macroplastic litter are particularly valuable for fragmentation modelling. Also see: https://micro2024.sciencesconf.org/559028/document

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