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• W4289202885 startingPage "1895" @default.
• W4289202885 abstract "Abstract Despite the persistent research interest in marine microplastic (MP) particles, the pollutant is still largely misunderstood. Significant data gaps hinder experts’ understanding of the sources, pathways, and fate of marine MPs, making it difficult to assess its environmental implications. Interdisciplinary work is required to fully understand the complexity of marine MPs (MMP) and to address the potential stress that this form of pollution may put on marine ecosystems. This study introduces an approach called information flow analysis (IFA), which intends to connect different fields of study through data flows, demonstrating the importance of these fields in the development of life cycle impact assessment (LCIA) of MMPs. The IFA approach was used to clarify where microplastic data is expected to come from with the goal of providing insight into how to obtain the data required for risk assessment (RA) and life cycle assessment (LCA). In order to observe and demonstrate these links, the next step was to develop a site‐specific coarse material flow analysis (MFA) based on previously estimated MP emissions from Norway and data from MP sampling in the inner Oslofjord. The coarse MFA demonstrated that MP sources in Norway were estimated to contribute between 85% and 96% rubbery MP particles and between 4% and 15% semisynthetic MP particles in 2018, while blue mussels sampled by the Norwegian Institute for Water Research (NIVA) contained 93% rubbery MP particles and 7% semisynthetic MP particles. This seems to demonstrate a connection between Norwegian MP sources (emissions) and MP levels observed in the environment." @default.
• W4289202885 created "2022-08-01" @default.
• W4289202885 creator A5018521995 @default.
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• W4289202885 date "2022-08-01" @default.
• W4289202885 modified "2023-09-30" @default.
• W4289202885 title "Using information flow analysis to establish key data gaps in the assessment of marine microplastic pollution" @default.
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• W4289202885 doi "https://doi.org/10.1111/jiec.13312" @default.
• W4289202885 hasPublicationYear "2022" @default.
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