Evaluation of the UTOPIA Model for Simulating the Size Distribution of Microplastics in the Environment
Year: 2025
Type: dissertation
Abstract: Microplastics are widespread contaminants with complex environmental behavior, making their fate and transport challenging to predict. This study evaluates the UTOPIA model's ability to simulate observed microplastic size distributions across freshwater, marine, and sediment environments. The model was configured using over 50,000 simulation runs to explore a wide range of emission scenarios and parameter combinations, particularly focusing on fragmentation style, fragmentation timescale, and discorporation half-life. Model performance was assessed using RMSE, R², and visual overlay comparisons against observed environmental data from 11 published studies. Results show that UTOPIA can replicate observed size distributions when input parameters are environmentally plausible. Among the three parameters tested, fragmentation style emerged as the most influential factor affecting model fit, followed by fragmentation timescale. Discorporation half-life was the least important of the three, but sometimes played a secondary role, especially in model scenarios with emissions to terrestrial compartments. Analysis of the top-performing runs revealed clear patterns linking plastic density with specific fragmentation behaviors. Specifically, UTOPIA’s modeled size distribution of microplastics agreed best with measurements from the real environment for low-density plastics with faster, erosive fragmentation, and for high-density plastics with slower, more sequential fragmentation. These findings not only validate the UTOPIA model's structure but also offer recommendations for selecting default input parameters in data-scarce situations. This work contributes to reducing uncertainty in fate modeling and supports the use of size distribution data to constrain model assumptions about microplastic degradation processes.
Author: Krishnappan, Rakesh
Institution: Stockholm University
Language: English
Subfield: Pollution
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6893158366
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