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From bottle to microplastics: Can we estimate how our plastic products are breaking down?
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A review of plastic fragmentation modeling found that while models predicting microplastic generation from mechanical stress, chemical degradation, and biological breakdown are developing, there remains a critical lack of empirical data on fragmentation rates needed to parameterize these models.
Microplastics (MPs) have become an emerging new pollutant of rising concern due to the exponential growth of plastics in consumer products. Most MP and nanoplastic pollution comes from the fragmentation of plastics through mechanical stress, chemical reactions and biological degradation that occurs during use and after disposal. Models predicting the generation and behavior of MP in the environment are developing, however there is lack of data to predict the rates of MP generation as a function of the abrasive forces. A method to deliver scalable, quantitative release rates of MPs during mechanical stress throughout a plastic's life cycle (e.g., sanding, chewing, river and ocean disposal) is described. A custom abrasion machine was built with features to provide data to calculate power input. The generation rate of MPs through abrasion was tested for the following 3D printed polymers: polylactic acid (PLA), polycarbonate (PC), thermoplastic polyurethane 85A (TPU), polyethylene glycol terephthalate (PETG), high-impact polystyrene (HIPS), and nylon. Each material underwent tensile strength material tests to identify which mechanical properties drive their abrasion rate. Abrasion rate was not observed to correlate to macroscopic mechanic properties. Results indicate that the order of abrasion from most to least were HIPS, nylon, PC, PLA, PETG, and then TPU. This study will help comprehend and provide data to understand generation rates of MPs from consumer plastic products and macro-plastic debris. This will be instrumental in helping to better understand the release of MPs and nanoplastics into the environment and to provide data for fate and transport models, especially in order to predict the amount of plastic entering water systems. MP generation rates and power inputs can be correlated with each plastic's use to inform which release the most MPs and how to better change these products in order to reduce pollution in water sources.
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