Polycyclic aromatic hydrocarbons (PAHs) in surface soil from the Guan River Estuary in China: Contamination, source apportionment and health-risk assessment
Bibliographic record
Abstract
To analyse the distribution characteristics, potential sources and health risks of PAHs in the surface soil of the Guan River Estuary Industrial Area, 30 samples along the Guan River were collected. Sixteen types of PAHs were detected by gas chromatography-mass spectrometry (GC-MS). The results showed that the total content of the 16 PAHs (16PAHs) ranged from 1212.8-12264.5 ng/g, and the arithmetic mean and median were 3504.8 ng/g and 2396.5 ng/g, respectively. The concentrations of 7 carcinogenic PAHs (7carPAHs) ranged from 546.1-5742.3 ng/g, accounting for 34-54% of the 16PAHs. The pollution of the PAHs was intermediate compared with that of other industrial areas in China. Fluoranthene, pyrene and benzo[a] pyrene (BaP) are the main monomer PAHs. There was a weak positive correlation between the total organic carbon and the PAHs, and a negative correlation between the PAHs and the pH was found. The characteristic ratio and principal component analysis (PCA) show that the PAHs mainly come from combustion sources, especially the combustion process of coal and coke from industrial areas. The TEQBaP (toxic equivalency quantity relative to BaP) concentrations of 7 types of carcinogenic PAHs accounted for 99% of the 16TEQBaP. According to the Canadian soil environmental quality standard, 87% of the sampling site's PAH pollution values exceeded the safety value, suggesting that there is a potential ecological risk in the Guan River Estuary industrial area.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".