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Shapes of Hyperspectral Imaged Microplastics
[Image: see text] Shape matters for microplastics, but its definition, particularly for hyperspectral imaged microplastics, remains ambiguous and inexplicit, leading to incomparability across data. Hyperspectral imaging is a common approach for quantification, yet no unambiguous microplastic shape c...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10448723/ https://www.ncbi.nlm.nih.gov/pubmed/37561646 http://dx.doi.org/10.1021/acs.est.3c03517 |
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author | Liu, Fan Rasmussen, Lasse A. Klemmensen, Nanna D. R. Zhao, Guohan Nielsen, Rasmus Vianello, Alvise Rist, Sinja Vollertsen, Jes |
author_facet | Liu, Fan Rasmussen, Lasse A. Klemmensen, Nanna D. R. Zhao, Guohan Nielsen, Rasmus Vianello, Alvise Rist, Sinja Vollertsen, Jes |
author_sort | Liu, Fan |
collection | PubMed |
description | [Image: see text] Shape matters for microplastics, but its definition, particularly for hyperspectral imaged microplastics, remains ambiguous and inexplicit, leading to incomparability across data. Hyperspectral imaging is a common approach for quantification, yet no unambiguous microplastic shape classification exists. We conducted an expert-based survey and proposed a set of clear and concise shapes (fiber, rod, ellipse, oval, sphere, quadrilateral, triangle, free-form, and unidentifiable). The categories were validated on images of 11,042 microplastics from four environmental compartments (seven matrices: indoor air; wastewater influent, effluent, and sludge; marine water; stormwater; and stormwater pond sediments), by inviting five experts to score each shape. We found that the proposed shapes were well defined, representative, and distinguishable to the human eye, especially for fiber and sphere. Ellipse, oval, and rod were though less distinguishable but dominated in all water and solid matrices. Indoor air held more unidentifiable, an abstract shape that appeared mostly for particles below 30 μm. This study highlights the need for assessing the recognizability of chosen shape categories prior to reporting data. Shapes with a clear and stringent definition would increase comparability and reproducibility across data and promote harmonization in microplastic research. |
format | Online Article Text |
id | pubmed-10448723 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-104487232023-08-25 Shapes of Hyperspectral Imaged Microplastics Liu, Fan Rasmussen, Lasse A. Klemmensen, Nanna D. R. Zhao, Guohan Nielsen, Rasmus Vianello, Alvise Rist, Sinja Vollertsen, Jes Environ Sci Technol [Image: see text] Shape matters for microplastics, but its definition, particularly for hyperspectral imaged microplastics, remains ambiguous and inexplicit, leading to incomparability across data. Hyperspectral imaging is a common approach for quantification, yet no unambiguous microplastic shape classification exists. We conducted an expert-based survey and proposed a set of clear and concise shapes (fiber, rod, ellipse, oval, sphere, quadrilateral, triangle, free-form, and unidentifiable). The categories were validated on images of 11,042 microplastics from four environmental compartments (seven matrices: indoor air; wastewater influent, effluent, and sludge; marine water; stormwater; and stormwater pond sediments), by inviting five experts to score each shape. We found that the proposed shapes were well defined, representative, and distinguishable to the human eye, especially for fiber and sphere. Ellipse, oval, and rod were though less distinguishable but dominated in all water and solid matrices. Indoor air held more unidentifiable, an abstract shape that appeared mostly for particles below 30 μm. This study highlights the need for assessing the recognizability of chosen shape categories prior to reporting data. Shapes with a clear and stringent definition would increase comparability and reproducibility across data and promote harmonization in microplastic research. American Chemical Society 2023-08-10 /pmc/articles/PMC10448723/ /pubmed/37561646 http://dx.doi.org/10.1021/acs.est.3c03517 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Liu, Fan Rasmussen, Lasse A. Klemmensen, Nanna D. R. Zhao, Guohan Nielsen, Rasmus Vianello, Alvise Rist, Sinja Vollertsen, Jes Shapes of Hyperspectral Imaged Microplastics |
title | Shapes of Hyperspectral
Imaged Microplastics |
title_full | Shapes of Hyperspectral
Imaged Microplastics |
title_fullStr | Shapes of Hyperspectral
Imaged Microplastics |
title_full_unstemmed | Shapes of Hyperspectral
Imaged Microplastics |
title_short | Shapes of Hyperspectral
Imaged Microplastics |
title_sort | shapes of hyperspectral
imaged microplastics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10448723/ https://www.ncbi.nlm.nih.gov/pubmed/37561646 http://dx.doi.org/10.1021/acs.est.3c03517 |
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