Phase partitioning, transport and sources of Benzotriazole Ultraviolet Stabilizers during a runoff event
Bibliographic record
Abstract
Benzotriazole Ultraviolet Stabilizers (BT-UVs) are ubiquitous in the environment, given their wide use as additives in consumer products. Their bio-accumulative and toxic properties are increasingly being scrutinised, evinced by the recent proposition to add UV328 to the Stockholm Convention on Persistent Organic Pollutants. Here, we measured concentrations of six BT-UVs in the dissolved and particulate phases of stream water collected from an urban and rural stream during a runoff event. Under baseflow conditions, the less hydrophobic BT-UVs were present at low concentrations in the dissolved phase, while much higher loads of particulate BT-UVs occurred during stormflow, especially in the urban creek. Time-weighted average BT-UV concentrations were up to 4 times higher in the urban than in the rural creek. BT-UVs were found to be prevalent in water obtained from laundering textiles, which plausibly constitutes a major portion of domestic wastewater, and can serve as a BT-UV source to aquatic waterways. However, the observed dilution of a sewage tracer during the run-off event suggests that unregulated wastewater seepage is not responsible for the high BT-UV loads in storm water. High levels of UV328 and UV234 were detected in a select few plastic debris items collected from the urban watershed and in artificial turf grass, respectively. Whereas this may allow for the leaching of those BT-UVs into the creek, most plastic debris is more likely a sink than a source of BT-UVs. The observed input of particle-bound BT-UVs at the onset of the rain event indicates that most of the BT-UVs reach the creek with contaminated particles that had built up on surfaces during the antecedent dry period. UV328 was the dominant BT-UV in those particles. If such particle build-up occurs on road surfaces, it may suggest that the use of UV328 in automotive applications contributes to their presence in urban storm water.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".