Self-contamination from clothing in microplastics research
Self-contamination should not be underestimated when quantifying microplastics (MPs) in environmental matrices. Standardised and validated methodologies for MP sampling, extraction, and analysis are lacking. The various applications of plastics in our society have made them ubiquitous, even in cloth...
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Published in | Ecotoxicology and environmental safety Vol. 189; p. 110036 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Netherlands
Elsevier Inc
01.02.2020
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Subjects | |
Online Access | Get full text |
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Summary: | Self-contamination should not be underestimated when quantifying microplastics (MPs) in environmental matrices. Standardised and validated methodologies for MP sampling, extraction, and analysis are lacking. The various applications of plastics in our society have made them ubiquitous, even in clothing, rendering MP self-contamination inevitable. In the present study, we sampled lake sediment, snow, and ice, purposefully wearing red overalls composed of cotton; fibres from which we could quantify using Fourier-Transform Infrared Spectroscopy (FTIR), serving as an indication of possible self-contamination from clothes. The suitability of cotton as a representation of MP contamination was also evaluated. For all detected fibres, 25 ± 1%, 20 ± 7%, and 8 ± 6% for snow, ice, and sediment, respectively, originated from sampling attire. These findings demonstrate that self-contamination can play a significant role when quantifying MP pollution, highlighting that sampling conducted to date might have overestimated the presence of MP or even contaminated MP-free samples.
•MP self-contamination during sampling was tested in lake sediment, snow, and ice.•Cotton was used as a self-contamination representative for MP.•Up to 15% of MP fibres can originate from sampling attire.•Self-contamination from clothing in MP research should not be underestimated. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0147-6513 1090-2414 1090-2414 |
DOI: | 10.1016/j.ecoenv.2019.110036 |