Journal
ENVIRONMENTAL RESEARCH LETTERS
Volume 12, Issue 11, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/1748-9326/aa9500
Keywords
plastic debris; microplastic; ocean modeling; fragmentation
Funding
- European Research Council (ERC) under European Union's Horizon research and innovation programme [715386]
- National Science Foundation [OCE-1260403]
- Division Of Ocean Sciences
- Directorate For Geosciences [1260403] Funding Source: National Science Foundation
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Understanding the global mass inventory is one of the main challenges in present research on plastic marine debris. Especially the fragmentation and vertical transport processes of oceanic plastic are poorly understood. However, whereas fragmentation rates are unknown, information on plastic emissions, concentrations of plastics in the ocean surface layer (OSL) and fragmentation mechanisms is available. Here, we apply a systems engineering analytical approach and propose a tentative 'whole ocean' mass balance model that combines emission data, surface area-normalized plastic fragmentation rates, estimated concentrations in the OSL, and removal from the OSL by sinking. We simulate known plastic abundances in the OSL and calculate an average whole ocean apparent surface area-normalized plastic fragmentation rate constant, given representative radii for macroplastic and microplastic. Simulations show that 99.8% of the plastic that had entered the ocean since 1950 had settled below the OSL by 2016, with an additional 9.4 million tons settling per year. In 2016, the model predicts that of the 0.309 million tons in the OSL, an estimated 83.7% was macroplastic, 13.8% microplastic, and 2.5% was < 0.335mm 'nanoplastic'. A zero future emission simulation shows that almost all plastic in the OSL would be removed within three years, implying a fast response time of surface plastic abundance to changes in inputs. The model complements current spatially explicit models, points to future experiments that would inform critical model parameters, and allows for further validation when more experimental and field data become available.
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