Multi-Ratio Equilibrium Passive Sampling Method to Estimate Accessible and Pore Water Concentrations of Polycyclic Aromatic Hydrocarbons and Polychlorinated Biphenyls in Sediment
Bibliographic record
Abstract
The freely dissolved concentration (C(w,0)) in the pore water and the accessible (releasable) concentration in the sediment (C(as,0)) are important parameters for risk assessment. These parameters were determined by equilibrating contaminated sediments and passive samplers using largely differing sampler–sediment ratios. This method is based on the principle that incubations at low sampler/sediment ratios yield the concentration in the pore water (minor depletion of the sediment phase) and incubations at high sampler/sediment ratios yield the accessible concentration in the sediment (maximum depletion of the sediment phase). It is shown that equilibration was faster in dense suspensions and at high sampler/sediment ratios when compared to low sampler/sediment ratios. An equilibrium distribution model was used to estimate C(w,0) and C(as,0) by nonlinear least-squares regression. The method was evaluated for three sediments (harbor, estuarine, marine). Accessible concentrations of 13 PAHs were 2 (low K(ow)) to 10 (high K(ow)) times lower than the total concentrations (three sediments). By contrast, the accessible concentrations of 15 PCBs were about 1.2 times lower than the total concentrations and displayed no trend with K(ow) (one sediment). Implications for risk assessment and considerations for application of multi-ratio equilibrium passive sampling with other sediments are discussed.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".