Assessment of Polycyclic Aromatic Hydrocarbons (PAHs) Contamination in Surface Soil along Tehran-Semnan Road, Iran
Bibliographic record
Abstract
ABSTRACT: The objective of the current research is carrying out the evaluation of the distribution,source, and environmental health risk of polycyclic aromatic hydrocarbons (PAHs) compounds in soil samples taken from the vicinity of Tehran-Semnan road, Iran. This road is a densely populated one in central northern part of Iran with a heavy load of vehicular traffics and several industrial complexes. Four different sampling sites (S1 to S4) were selected in the studied area and then a concentration of 16 PAHs compounds in taken soil samples were measured by High-Performance Liquid Chromatography (HPLC). Total PAHs concentrations varied significantly from 148.4 ng g-1 to 721 ng g-1. The Siman-e Tehran (S1) site has the highest average total PAHs concentrations (654.55 ng g-1) and Dehenamak (S4) has the lowest average total PAHs concentrations (168.7 ng g-1) among the studied sites. The obtained total PAH concentrations in the studied soil samples are relatively lower than those reported in the literature for similar areas. The diagnostic ratios of fluoranthene to pyrene (Flu/Pyr) and phenanthrene to anthracene (Phe/Ant) were used to determine the petrogenic and pyrogenic sources of PAHs, respectively. The derived results indicated that PAHs contamination in the majority of studied soil samples was caused by both petrogenic and pyrogenic process.
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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 | 0.001 | 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".