In search of an optimal moss transplant biomonitor for airborne microplastics: Moss cubes
Bibliographic record
Abstract
There is growing interest in the use of moss transplant samplers to assess atmospheric microplastics. Here we explored the influence of sampler design and exposure duration on the accumulation of microplastics. We evaluated three samplers, two bag samplers (5 cm × 8 cm) each containing 1 g of moss, but with different mesh sizes (1 mm versus 6 mm), and a 6 cm cube made from 6 mm mesh containing 3 g of moss. The cube samplers had the highest microplastic particle accumulation (2.92 mp/g), followed by 1 mm mesh bags (2.57 mp/g) and 6 mm mesh bags (1.97 mp/g). Further, cube samplers had the lowest variation between replicates, with all of them above the limit of detection. All sampler designs were dominated by fibres ranging from 80 % in cubes to 94 % in 6 mm mesh bags, suggesting that cubes captured a higher diversity of particle morphologies. The net loss in moss mass during sampler deployment was lowest for the cube samplers (3.9 %) and highest in 1 mm mesh bags (10.5 %). Transplant samplers exposed for six-weeks suggested higher particle accumulation than four-week exposures; however, mass concentration was lower in the six-week exposures, suggesting that heavier microplastics were lost. In general, the results suggest that effective moss transplant samplers should incorporate sufficient moss mass to ensure particle retention, larger mesh size (≥5 mm) to maximize exposure to atmospheric microplastics, and a three-dimensional shape to allow equal exposure from all sides. In this respect, we recommend the ‘moss cube’ sampler with a 6 mm mesh size containing at least 3 g of moss depending on cube dimensions. • Moss transplant sampler design strongly affected airborne microplastic accumulation. • Cube samplers (6 mm mesh, 3 g mos) had higher accumulation and lower variability. • Cube samplers captured the highest diversity of particle morphologies and sizes. • Six-week exposure increased accumulation but reduced mass suggesting particle loss. • 3-D samplers with large mesh size and high moss mass are optimal for microplastics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".