Spatiotemporal distribution and risk assessment of polycyclic aromatic hydrocarbons in the Tigris River near Baghdad Medical City wastewater discharge
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) are persistent, carcinogenic contaminants.We tracked the 16 U.S. Environmental Protection Agency (EPA) priority PAHs in surface waters of the Tigris River at five stations spanning 100 m upstream to 1.5 km downstream of Baghdad Medical City's wastewater outfall during October 2024, January 2025, and April 2025.Samples underwent liquid-liquid extraction (LLE), copper desulfurization, and gas chromatography with flame-ionization detector (GC-FID) analysis.Total PAH concentrations (Σ16 PAHs) peaked at the sewer outlet in all seasons (up to 31 µg L⁻¹) and declined at 1.5 km downstream to levels close to the pre-sewage discharge point.Site explained 93.75% of the spatiotemporal variance (p < 0.001).The share of high-molecular-weight PAHs rose from 48% at the outfall to 67% after 1.5 km.Total risk quotient (ΣRQ) peaked at 2.5 × 10³ in January, exceeding the safety threshold, while benzo[a]pyrene-equivalent toxicity (BaP-TEQ) peaked at 1.9 µg BaP eq L⁻¹.Winter benzo[a]pyrene (0.262 µg L⁻¹) exceeded Dutch and Canadian aquatic criteria by 17-26-fold.Diagnostic ratios trace the origin of PAHs to medical waste and biomass combustion Keywords: benzo[a]pyrene, biomass combustion, diagnostic ratios, polycyclic aromatic hydrocarbons, risk quotient, Tigris River, wastewater.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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 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".