Fugacity approach to evaluate the sediment–water diffusion of polycyclic aromatic hydrocarbons
Bibliographic record
Abstract
Diffusion is an important process for sediment-water exchange and plays a vital role in controlling water quality. Fugacity fraction (ff) was used to estimate the sediment-water diffusion of polycyclic aromatic hydrocarbons (PAHs) between seawater and surficial sediment. A total of 33 surface sediment and sea water samples were collected concurrently from the northeast coastal area in China and 25 PAHs were analyzed including the alkylated and chlorated PAHs. Fugacity fraction was calculated based on the PAH concentrations in water and sediment, octanol-water partition coefficient of PAHs, organic matter content in sediment, and density of sediment. The calculated results showed that ff increased with decreasing molecular weight of PAHs. The low molecular weight PAHs (2-3 rings) transferred from sediment to water and the sediment acted as a secondary source to the water. The medium molecular weight PAHs (4-5 rings) were close to the sediment-water equilibrium and the transfer tendency shifted between sediment and water. The high molecular weight PAHs (5-6 rings) transferred from water into sediment and the sediment acted as a sink. Soot carbon and the difference of PAH concentrations between sediment and water were found to be important factors affecting the sediment-water diffusion. This study provided new insight into the process of sediment-water diffusion, which has a great influence on the quality of water, especially in severely-polluted sediment areas.
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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 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".