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Identifying Marine Sources of Beached Plastics Through a Bayesian Framework: Application to Southwest Netherlands

Geophysical research letters, 2022-02, Vol.49 (4), p.e2021GL097214-n/a [Peer Reviewed Journal]

2022 The Authors. ;2022. This article is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0094-8276 ;EISSN: 1944-8007 ;DOI: 10.1029/2021GL097214 ;PMID: 35860482

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Title:
Identifying Marine Sources of Beached Plastics Through a Bayesian Framework: Application to Southwest Netherlands
Author: Duinen, Bram ; Kaandorp, Mikael L. A. ; Sebille, Erik
Subjects: Abrupt/Rapid Climate Change ; Aerosols ; Aerosols and Particles ; Air/Sea Constituent Fluxes ; Air/Sea Interactions ; Atmospheric ; Atmospheric Composition and Structure ; Atmospheric Effects ; Atmospheric Processes ; Avalanches ; backtracking ; Bayes theorem ; Bayesian analysis ; Beaches ; Benefit‐cost Analysis ; Biogeosciences ; Climate and Interannual Variability ; Climate Change and Variability ; Climate Dynamics ; Climate Impact ; Climate Impacts ; Climate Variability ; Climatology ; Computational Geophysics ; Cryosphere ; Decadal Ocean Variability ; Disaster Risk Analysis and Assessment ; Earth System Modeling ; Earthquake Ground Motions and Engineering Seismology ; Effusive Volcanism ; Explosive Volcanism ; Fisheries ; Frameworks ; General Circulation ; Geodesy and Gravity ; Geological ; Global Change ; Global Change from Geodesy ; Gravity and Isostasy ; Hydrological Cycles and Budgets ; Hydrology ; Impacts of Global Change ; Informatics ; Lagrangian modeling ; Land/Atmosphere Interactions ; Marine Geology and Geophysics ; Marine Pollution ; Mass Balance ; Megacities and Urban Environment ; Modeling ; Mud Volcanism ; Natural Hazards ; Numerical Modeling ; Numerical Solutions ; Ocean influence of Earth rotation ; Ocean Monitoring with Geodetic Techniques ; Ocean/Atmosphere Interactions ; Ocean/Earth/atmosphere/hydrosphere/cryosphere interactions ; Oceanic ; Oceanography: Biological and Chemical ; Oceanography: General ; Oceanography: Physical ; Oceans ; Paleoceanography ; Physical Modeling ; plastic pollution ; Plastics ; Policy Sciences ; Pollution: Urban and Regional ; Pollution: Urban, Regional and Global ; Probability theory ; Radio Oceanography ; Radio Science ; Regional Climate Change ; Regional Modeling ; Research Letter ; Risk ; Rivers ; Sea Level Change ; Sea Level: Variations and Mean ; Seismology ; Simulation ; Solid Earth ; Surface Waves and Tides ; Theoretical Modeling ; Tsunamis and Storm Surges ; Urban Systems ; Volcanic Effects ; Volcanic Hazards and Risks ; Volcano Monitoring ; Volcano Seismology ; Volcano/Climate Interactions ; Volcanology ; Water Cycles
Is Part Of: Geophysical research letters, 2022-02, Vol.49 (4), p.e2021GL097214-n/a
Description: Beaches are thought to be a large reservoir for marine plastics. To protect vulnerable beaches, it is advantageous to have information on the sources of this plastic. Here, we develop a universally applicable Bayesian framework to map sources of plastic arriving on a specific beach. In this framework, we combine Lagrangian backtracking simulations of drifting particles with estimates of plastic input from coastlines, rivers and fisheries. The advantage over traditional Lagrangian simulations is that the Bayesian framework can consider information on known sources, and thus facilitates spatiotemporal source attribution for plastic arriving at the specified beach. We show that the main sources for our target beach in southwest Netherlands are the east coast of the UK, the Dutch coast, the English Channel (fisheries) and the Thames, Seine, Rhine and Trieux (rivers). We also show that floating time is a major uncertainty in source attribution using backtracking. Plain Language Summary A large part of plastic in the ocean is located at or near beaches. This plastic can break down into micro‐plastics or be ingested by animals. Therefore, it is important to clean up these beaches. The easiest way to do so is to prevent the plastic from entering the oceans initially by interfering at the source. In this study, we develop a framework to find these sources for a given beach. We first simulate the path that plastic has taken to reach this beach. We do this by releasing virtual plastic particles at the beach where they end up. Next, we calculate their paths back in time, computing their trajectories until they reach this beach. We then combine these simulations with data on the sources of plastic: where and when did plastic enter the ocean? We apply this framework to a beach in southwest Netherlands, near the town of Domburg. We quantify seasonal effects, where time‐varying currents cause the plastic to come from different sources. Lastly, we study how plastic sources vary with plastic age (the time between the plastic entering the ocean and beaching at its final location). Key Points Combined oceanic backtracking and Bayesian statistics supports source attribution of beached plastic Strong seasonal variability in likely sources is found, due to variability in plastic input and currents Floating time remains a major uncertainty in determining the origin of beached plastic via backtracking
Publisher: Washington: John Wiley & Sons, Inc
Language: English
Identifier: ISSN: 0094-8276
EISSN: 1944-8007
DOI: 10.1029/2021GL097214
PMID: 35860482
Source: Wiley Blackwell AGU Digital Library

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Identifying Marine Sources of Beached Plastics Through a Bayesian Framework: Application to Southwest Netherlands

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