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Attribution of Plastic Sources Using Bayesian Inference: Application to River-Sourced Floating Plastic in the South Atlantic Ocean
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A Bayesian inference framework was developed to estimate the probability that a piece of marine plastic collected in the South Atlantic Ocean originated from a specific river source. The method combines river emission data with Lagrangian drift modeling to assign source probabilities. This approach could help target plastic pollution reduction efforts at the highest-contributing river sources.
Most marine plastic pollution originates on land. However, once plastic is at sea, it is difficult to determine its origin. Here we present a Bayesian inference framework to compute the probability that a piece of plastic found at sea came from a particular source. This framework combines information about plastic emitted by rivers with a Lagrangian simulation, and yields maps indicating the probability that a particle sampled somewhere in the ocean originates from a particular river source. We showcase the framework for floating river-sourced plastic released into the South Atlantic Ocean. We computed the probability as a function of the particle age at three locations, showing how probabilities vary according to the location and age. We computed the source probability of beached particles, showing that plastic found at a given latitude is most likely to come from the closest river source. This framework lays the basis for source attribution of marine plastic.
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