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Using Dynamic Release Modeling to Predict Historic and Current Macro- and Microplastic Releases
Summary
Researchers developed a Dynamic Probabilistic Material Flow Analysis model coupled with a release model to quantify historic and current macro- and microplastic emissions in Switzerland, providing a dataset tracking plastic releases across product lifecycles.
Dataset connected to the following publication: Zipeng Liu, Bernd Nowack,Using dynamic release modeling to predict historic and current macro- and microplastic releases,Resources, Conservation and Recycling,Volume 214,2025,108011,ISSN 0921-3449,https://doi.org/10.1016/j.resconrec.2024.108011.(https://www.sciencedirect.com/science/article/pii/S0921344924006025)Abstract: Confronting the pervasive challenge of plastic pollution, our study pioneers a dynamic release model to quantify the historic and current plastic emissions. Utilizing Dynamic Probabilistic Material Flow Analysis (DPMFA) coupled to a release model, we comprehensively tracked emissions of macro- and microplastics in Switzerland from 1950 to 2022, covering 35 product categories and 183 release pathways for seven polymers (LDPE, HDPE, PP, PS, EPS, PVC, PET). The plastic usage exhibited a “Peak Plastic” around the year 2010 with a subsequent decrease in per capita use of plastics from 120±5 to 107±5 kg/cap in 2022. Over the considered timeframe, 27±1 kg/cap of macroplastics and 4 ± 1 kg/cap of microplastics were released to the environment, with the most substantial contributions coming from LDPE and PET. The overall emission factor was 0.66±0.07 % for macroplastics and 0.010±0.01 % for microplastics. The model can provide a crucial framework for crafting targeted interventions toward sustainable plastic lifecycle management.Keywords: Plastic; MFA; Release; Dynamic; Microplastics
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