<p>Fluorescence microscopy is increasingly seen as a fast, user-friendly, and high-throughput method for detecting microplastics (MPs) in soil; however, its effectiveness across diverse MP types and soil properties remains underexplored. This study tested a fluorescence microscopy–Nile red (NR) staining approach on eight MP types, covering both biodegradable and non-biodegradable plastics, in three size ranges (≤ 150 µm, 100–250 µm, 500–1000 µm) across loamy, clayey, and sandy soils. Each sample, processed in triplicate, underwent a relatively quick and straightforward extraction procedure involving density separation, organic digestion, and NR staining, followed by fluorescence and bright-field microscopy. A new digital image analysis pipeline using Image J was developed to expedite and (semi)automate MP quantification. Recoveries ranged from&#xa0;80%&#xa0;to&#xa0;90% for MPs with a Feret diameter of 500–1000 µm, regardless of soil type. In contrast, the recovery of smaller MPs (Feret dia. ≤ 250&#xa0;µm) varied depending on the soils and plastic types: recoveries for low-density polyethylene (LDPE) reached 85% in sandy soil and 90% in loamy soil, whereas those for biodegradable polybutylene adipate terephthalate/polylactic acid (PBAT/PLA) were only 60% and 10%, respectively. The lowest recovery rate was observed in clayey soil and for biodegradable plastics. The method was tested on non-agricultural soil samples, yielding a MP mean number concentration of 20.7 ± 9.0 MPs/g for MPs sized from dia. ≥ 25&#xa0;µm, comparable to Fourier transform infrared (FPA-µ-FTIR) results of 13.1 ± 7.3 MPs/g (<i>p</i> &gt; 0.05). We conclude that fluorescence microscopy with NR staining and automated particle quantification offers a time-efficient, reproducible, and accurate method for MP detection in light-textured soils, whereas limitations remain for reliable MP analysis in clay-dominated soils.</p> Graphical Abstract <p></p>

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Towards quality-assured measurements of microplastics in soil using fluorescence microscopy

  • Quynh Nhu Phan Le,
  • Crispin Halsall,
  • Stoyana Peneva,
  • Olivia Wrigley,
  • Melanie Braun,
  • Wulf Amelung,
  • Lorna Ashton,
  • Ben W. J. Surridge,
  • John Quinton

摘要

Fluorescence microscopy is increasingly seen as a fast, user-friendly, and high-throughput method for detecting microplastics (MPs) in soil; however, its effectiveness across diverse MP types and soil properties remains underexplored. This study tested a fluorescence microscopy–Nile red (NR) staining approach on eight MP types, covering both biodegradable and non-biodegradable plastics, in three size ranges (≤ 150 µm, 100–250 µm, 500–1000 µm) across loamy, clayey, and sandy soils. Each sample, processed in triplicate, underwent a relatively quick and straightforward extraction procedure involving density separation, organic digestion, and NR staining, followed by fluorescence and bright-field microscopy. A new digital image analysis pipeline using Image J was developed to expedite and (semi)automate MP quantification. Recoveries ranged from 80% to 90% for MPs with a Feret diameter of 500–1000 µm, regardless of soil type. In contrast, the recovery of smaller MPs (Feret dia. ≤ 250 µm) varied depending on the soils and plastic types: recoveries for low-density polyethylene (LDPE) reached 85% in sandy soil and 90% in loamy soil, whereas those for biodegradable polybutylene adipate terephthalate/polylactic acid (PBAT/PLA) were only 60% and 10%, respectively. The lowest recovery rate was observed in clayey soil and for biodegradable plastics. The method was tested on non-agricultural soil samples, yielding a MP mean number concentration of 20.7 ± 9.0 MPs/g for MPs sized from dia. ≥ 25 µm, comparable to Fourier transform infrared (FPA-µ-FTIR) results of 13.1 ± 7.3 MPs/g (p > 0.05). We conclude that fluorescence microscopy with NR staining and automated particle quantification offers a time-efficient, reproducible, and accurate method for MP detection in light-textured soils, whereas limitations remain for reliable MP analysis in clay-dominated soils.

Graphical Abstract