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Extracting microplastic decay rates from field data
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Researchers developed a mathematical model to analyze how microplastic particles break down over time in the environment, concluding that current snapshot data of plastic size distributions is insufficient for predicting decay rates, and that future studies must track the same locations over time while measuring both size and mass of particles.
Being able to estimate and predict future microplastic distributions in the environment is one of the major challenges of the rapidly developing field of microplastic research. However, this task can only be achieved if our understanding of the decay of individual microplastic particles is significantly enhanced. Here, we show by using a rate equation model that currently available data of size distributions measured at single times cannot provide useful insights into this process. To analyze what data contains more information we generated more complex artificial data mimicking subsequent measurements using a stochastic simulation algorithm. Applying our model to this data revealed the following minimal requirements for future experimental data: (1) data should be collected as time series at identical spots and (2) size measurements should be combined with mass measurements. In contrast to currently available data, flux rates and decay parameters of individual particles can be extracted from such data.
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When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.