Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 552867
Title Simplifying microplastic via continuous probability distributions for size, shape and density
Author(s) Kooi, M.; Koelmans, A.A.
Source Environmental Science & Technology Letters 6 (2019)9. - ISSN 2328-8930 - p. 551 - 557.
Department(s) Aquatic Ecology and Water Quality Management
Publication type Refereed Article in a scientific journal
Publication year 2019
Abstract Because of their diverse sizes, shapes and densities, environmental microplastics are often perceived as complex. Many studies struggle with this complexity, and either address only a part of this diversity, or present data using discrete classifications for sizes, shapes and densities. We argue that such classifications will never be fully satisfactory, as any definition using classes does not capture the essentially continuous nature of environmental microplastic. Therefore, we propose to simplify microplastics by fully defining them through a 3D probability distribution, with size, shape and density as dimensions. Besides introducing the concept, we parameterize these probability distributions, using empirical data. This parameterization results in an approximate yet realistic representation of ‘true’ environmental microplastic. This approach to simplify microplastic could be applicable to exposure measurements, effect studies and fate modelling. Furthermore, it allows for easy comparison between studies, irrespective of sampling or laboratory setup. We demonstrate how the 3D probability distribution of environmental versus ingested microplastic can be helpful in understanding bioavailability of and exposure to microplastic. We argue that the concept of simplified microplastic will also be helpful in probabilistic risk modelling, which would greatly enhance the understanding of the risk that microplastics pose to the environment.
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