Robinia pseudoacacia L. (Black Locust) Leaflets as Biomonitors of Airborne Microplastics
Bibliographic record
Abstract
Here we investigate the suitability of Robinia pseudoacacia L. (black locust) leaflets as a novel biomonitor of airborne microplastics (MPs) including tyre wear particles (TWPs). Leaflets were collected from rural roadside locations (ROs, n = 5) and urban parks (UPs, n = 5) in Siena, Italy. MPs were removed by washing, identified by stereomicroscope, and analysed for polymer type by Fourier transform infrared spectroscopy. Daily MP deposition was estimated from leaf area. The mass magnetic susceptibility and the bioaccumulation of traffic-related potentially toxic elements (PTEs) were also analysed. The total number of MPs at ROs was significantly higher at 2962, dominated by TWPs, compared with 193 in UPs, where TWPs were not found. In contrast, total microfibres were significantly higher in UPs compared with ROs (185 vs. 86). Daily MP deposition was estimated to range from 4.2 to 5.1 MPs/m2/d across UPs and 29.9–457.6 MPs/m2/d across ROs. The polymer types at ROs were dominated by rubber (80%) from TWPs, followed by 15% polyamide (PA) and 5% polysulfone (PES), while in UPs the proportion of PES (44%) was higher than PA (22%) and polyacrylonitrile (11%). The mean mass magnetic susceptibility, a proxy of the bioaccumulation of traffic-related metallic particles, was higher at ROs (0.62 ± 0.01 10–8 m3/kg) than at UPs (–0.50 ± 0.03 10–8 m3/kg). The content of PTEs was similar across sites, except for significantly higher concentrations of Sb, a tracer of vehicle brake wear, at ROs (0.308 ± 0.008 µg/g) compared with UPs (0.054 ± 0.006 µg/g). Our results suggest that the waxy leaflets and easy determination of surface area make Robinia an effective biomonitor for airborne MPs including TWPs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.009 |
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; both teacher heads agree on what is shown here.
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".