Probabilistic Risk Assessment of Polycyclic Aromatic Hydrocarbons (PAHs) in Produced Water
Bibliographic record
Abstract
The produced water extracted during oil and gas production includes formation water, injected water, small volumes of condensed water, and any chemical added during the oil/water separation process. Produced water contains both organic and inorganic constituents, and several studies have been conducted in the past to assess their risk. The toxicity and persistence of polycyclic aromatic hydrocarbons (PAHs) in produced water is of particular environmental concern, but there are very few studies on human health risk assessment from PAHs of produced water. This article summarizes the results of a conservative human health risk assessment approach for PAHs in produced water discharges to the marine environment. Due to the absence of available toxicity data for PAHs, the cancer slope factors were determined by using the relative potency factors (RPF) and Toxicity Equivalency Factors (TEF). Using the concentration distribution factors, the maximum cancer risks to humans were predicted in the range of 4.07 × 10−7 to 2.95 × 10−6. The 95th-percentile values show that the risks are well within the acceptable limits.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".