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The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Predicting soil microplastic concentration using vis-NIR spectroscopy

Open access
Corradini, Fabio, Bartholomeus, Harm, Huerta Lwanga, Esperanza, Gertsen, Hennie, Geissen, Violette·2019·Science of The Total Environment

Abstract

Microplastic accumulation in soil may have a detrimental impact on soil biota. The lack of standardized methods to identify and quantify microplastics in soils is an obstacle to research. Existing techniques are time-consuming and field data are seldom collected. To tackle the problem, we explored the possibilities of using a portable spectroradiometer working in the near infrared range (350–2500 nm) to rapidly assess microplastic concentrations in soils without extraction. Four sets of artificially polluted soil samples were prepared. Three sets had only one polymer polluting the soil (low-density polyethylene (LDPE), polyethylene terephthalate (PET), or polyvinyl chloride (PVC)). The fourth set contained random amounts of the three polymers (Mix). The concentrations of microplastics were regressed on the reflectance observed for each of the 2150 wavelengths registered by the instrument, using a Bayesian approach. For a measurement range between 1 and 100 g kg−1, results showed a root-mean-squared-deviation (RMSD) of 8, 18, and 10 g kg−1 for LDPE, PET, and PVC. The Mix treatment presented an RMSD of 8, 10, and 5 g kg−1 for LDPE, PET, and PVC. The repeatability of the proposed method was 0.2–8.4, 0.1–5.1, and 0.1–9.0 g kg−1 for LDPE, PET, and PVC, respectively. Overall, our results suggest that vis-NIR techniques are suitable to identify and quantify LDPE, PET, and PVC microplastics in soil samples, with a 10 g kg−1 accuracy and a detection limit ≈ 15 g kg−1. The method proposed is different than other approaches since it is faster because it avoids extraction steps and can directly quantify the amount of plastic in a sample. Nevertheless, it seems to be useful only for pollution hotspots.

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Metadata

Authors
Corradini, F., Bartholomeus, H., Huerta Lwanga, E., Gertsen, H., & Geissen, V.
Venue
Science of The Total Environment
Publisher
Elsevier BV
Published
2019-02
Volume
650
Issue
Pt 1
Pages
922-932
ISSN
0048-9697 (ISSN-L)
OpenAlex
W2889579625
Cited by
244
References
5
FWCI
7.08
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Predicting soil microplastic concentration using vis-NIR spectroscopy. https://app.cochat.ai/papers/10.1016/j.scitotenv.2018.09.101
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Corradini, F., Bartholomeus, H., Huerta Lwanga, E., Gertsen, H., & Geissen, V. (2019). Predicting soil microplastic concentration using vis-NIR spectroscopy. Science of The Total Environment. https://doi.org/10.1016/j.scitotenv.2018.09.101

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