Modelling accumulation of marine plastics in the coastal zone; what are the dominant physical processes?
Critchell, K.; Lambrechts, J. (2016). Modelling accumulation of marine plastics in the coastal zone; what are the dominant physical processes? Est., Coast. and Shelf Sci. 171: 111-122. https://dx.doi.org/10.1016/j.ecss.2016.01.036
In: Estuarine, Coastal and Shelf Science. Academic Press: London; New York. ISSN 0272-7714; e-ISSN 1096-0015, more
Anthropogenic marine debris, mainly of plastic origin, is accumulating in estuarine and coastal environments around the world causing damage to fauna, flora and habitats. Plastics also have the potential to accumulate in the food web, as well as causing economic losses to tourism and sea-going industries. If we are to manage this increasing threat, we must first understand where debris is accumulating and why these locations are different to others that do not accumulate large amounts of marine debris. This paper demonstrates an advection-diffusion model that includes beaching, settling, resuspension/re-floating, degradation and topographic effects on the wind in nearshore waters to quantify the relative importance of these physical processes governing plastic debris accumulation. The aim of this paper is to prioritise research that will improve modelling outputs in the future. We have found that the physical characteristic of the source location has by far the largest effect on the fate of the debris. The diffusivity, used to parameterise the sub-grid scale movements, and the relationship between debris resuspension/re-floating from beaches and the wind shadow created by high islands also has a dramatic impact on the modelling results. The rate of degradation of macroplastics into microplastics also have a large influence in the result of the modelling. The other processes presented (settling, wind drift velocity) also help determine the fate of debris, but to a lesser degree. These findings may help prioritise research on physical processes that affect plastic accumulation, leading to more accurate modelling, and subsequently management in the future.
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