The unusual suspects: Screening for persistent, mobile, and toxic plastic additives in plastic leachates
Bibliographic record
Abstract
Plastic additives are a diverse group of chemical compounds added to plastic products to give them their unique physical-chemical properties. Persistent, mobile, and toxic (PMT) plastic additives are a highly polar, environmentally stable sub-group of plastic additives with a variety of uses in plastic products. Due to their mobility into water, they can pose a significant long-term risk to the aquatic environment. Despite the potential threat, PMT plastic additives remain largely unregulated and under-studied. Notably, there is a need for dedicated analytical methodology and leaching studies to determine their potential emission from plastic products. Here we present an optimized leaching protocol and novel instrumental analysis method for the screening of 124 PMT plastic additives registered for use in Canada using high performance liquid chromatography with quantitative time-of-flight mass spectrometry (HPLC-QToF-MS). The analytical method covered a log Kow/Dow range between 0.21 and 6.02, which covered 72% of the PMT plastic additives used in Canada. A total of 52 PMT plastic additive suspects were leached in the optimization experiments, 44 of which were unique based on accurate mass and retention time. The conditions that resulted in the greatest numbers of PMT plastic additives leached were lake water, UV light exposure, and a timeframe of approximately 30 days. The analytical and leaching methods presented here offer new tools to study PMT plastic additives and assess their leaching in an environmentally relevant matrix, which can inform monitoring, threat assessment, and regulatory efforts moving forward.
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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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".