Toxicological effects caused by the interaction of microplastics with marine species may be exacerbated by the potential of the former to act also as vectors of other contaminants (Syberg et al., 2015; Alimba & Faggio, 2019), such as the chemical additives used in the production of plastics other than conventional pollutants that concentrate on the organic surface of marine litter (Rochman, 2015; Tourinho et al., 2019). In our work, we provide a simple yet comprehensive modelling framework to account for both the distribution of microplastics at sea and their chemical interactions with the marine environment, focusing here on the Mediterranean Sea. Surface microplastics dispersal patterns are obtained with Lagrangian particle tracking simulations (as in Eriksen et al., 2014, and many others), where plastic particles are released from the most impacting sources of pollution, i.e. mismanaged plastic waste originated by coastal areas, in the watersheds of major rivers and due to maritime activities (Guerrini et al., 2019). During their transport by surface currents, as provided by oceanographic reanalysis products (Copernicus Marine Environment Monitoring Services, Simoncelli et al., 2014), simulated plastic particles interact with the surrounding environment in response to chemical gradients. Such particle-based simulations are coupled with the advection-diffusion of contaminants using a Eulerian model, so as to attempt a full description of the dynamics of primary pollutants in the sea. Our model permits thus to integrate the spatiotemporal evolution of pollutants in the water with the chemical exchanges occurring through microplastic particles. While providing further understanding in the distribution of microplastics at a Mediterranean-wide scale, our modelling approach contributes to assess their role as a vector of other pollutants of concern in the marine environment.

A modelling approach to map microplastics and associated contaminants in the Mediterranean Sea

Federica Guerrini;Lorenzo Mari;Renato Casagrandi
2020-01-01

Abstract

Toxicological effects caused by the interaction of microplastics with marine species may be exacerbated by the potential of the former to act also as vectors of other contaminants (Syberg et al., 2015; Alimba & Faggio, 2019), such as the chemical additives used in the production of plastics other than conventional pollutants that concentrate on the organic surface of marine litter (Rochman, 2015; Tourinho et al., 2019). In our work, we provide a simple yet comprehensive modelling framework to account for both the distribution of microplastics at sea and their chemical interactions with the marine environment, focusing here on the Mediterranean Sea. Surface microplastics dispersal patterns are obtained with Lagrangian particle tracking simulations (as in Eriksen et al., 2014, and many others), where plastic particles are released from the most impacting sources of pollution, i.e. mismanaged plastic waste originated by coastal areas, in the watersheds of major rivers and due to maritime activities (Guerrini et al., 2019). During their transport by surface currents, as provided by oceanographic reanalysis products (Copernicus Marine Environment Monitoring Services, Simoncelli et al., 2014), simulated plastic particles interact with the surrounding environment in response to chemical gradients. Such particle-based simulations are coupled with the advection-diffusion of contaminants using a Eulerian model, so as to attempt a full description of the dynamics of primary pollutants in the sea. Our model permits thus to integrate the spatiotemporal evolution of pollutants in the water with the chemical exchanges occurring through microplastic particles. While providing further understanding in the distribution of microplastics at a Mediterranean-wide scale, our modelling approach contributes to assess their role as a vector of other pollutants of concern in the marine environment.
2020
978-84-120734-6-1
microplastics, marine pollution, Lagrangian modelling, Eulerian modelling, Advection-diffusion
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1147120
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