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Finding Microplastics in Soils: A Review of Analytical Methods
Open accessAbstract
Research on microplastics in soils is still uncommon, and the existing publications are often incomparable due to the use of different sampling, processing, and analytical methods. Given the complex nature of soils, a suitable and efficient method for standardized microplastic analysis in the soil matrix has yet to be found. This paper proposes a critical review on the different published methods for sampling, extraction, purification, and identification/quantification of microplastics in complex environmental matrices, with the main focus on their applicability for soil samples. While large microplastic particles can be manually sorted out and verified with chemical analysis, sample preparation for smaller microplastic analysis is usually more difficult. Of the analytical approaches proposed in the literature, some are established, whereas others are a proof of principle and have not yet been applied to environmental samples. For the sake of development, all approaches are discussed and assessed for their potential applicability for soil samples. So far, none of the published methods seems ideally suitable for the analysis of smaller microplastics in soil samples, but slight modifications and combinations of methods may prove promising and need to be explored.
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Metadata
- Authors
- Möller, J. N., Löder, M. G. J., & Laforsch, C.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2020-01-30
- Volume
- 54
- Issue
- 4
- Pages
- 2078-2090
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W3003825264
- Cited by
- 559
- References
- 117
- FWCI
- 15.25
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.