Estimation of Biodegradation and Liquid-Solid Partitioning Coefficients for Selected PAHs in Municipal Wastewater Treatment
Bibliographic record
Abstract
Abstract Batch testing was employed to estimate model parameters that are required for predicting the fate of polynuclear aromatic hydrocarbons (PAHs) in wastewater treatment. Linear partitioning was found to describe the partitioning of PAHs to solids and was best described when the soluble phase of the PAHs was determined by centrifugation alone. The liquid-solid partitioning coefficients obtained for primary and secondary sludges were statistically different, with the latter being higher than the former for most of the PAHs examined in this study. Temperature had a significant impact on the estimated biodegradation rate coefficients (Kb). The biodegradation rate coefficients for anthracene and phenanthrene (three-ring PAHs) were statistically different from benzo(a)anthracene and chrysene (four-ring PAHs). The presence of a nitro-adduct on acenaphthene resulted in a substantial increase in the Kb relative to the unsubstituted anthracene and phenanthrene. A sensitivity analysis revealed that the removal of PAHs in a full-scale wastewater treatment plant was most sensitive to the value of the liquid-solid partitioning coefficients. Approximately 60% of the PAHs were removed from the wastewater stream through partitioning to both primary and secondary solids, and subsequent discharge.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".