Carcinogenic potential of soils contaminated with polycyclic aromatic hydrocarbons (PAHs) in Xiamen metropolis, China
Bibliographic record
Abstract
Xiamen is one of China's most rapidly developing metropolises. The objectives of the present study were: (1) to establish the levels and spatial distribution of polycyclic aromatic hydrocarbons (PAHs) in soil across the Xiamen metropolis, (2) to evaluate the extent to which PAH concentrations were elevated in the high urbanization area (HUA) of the island and how these compared with those in the low urbanization area (LUA) of the mainland, and (3) to evaluate the PAH hazard based upon their Carcinogenic Potential (CP), defined as toxicity equivalence of ∑PAHs. Twenty two alternative relative carcinogenic potency schemes were used and compared. Results demonstrated PAH concentrations to be greatly elevated across the entire metropolis. Significantly, the most enriched compounds represented the greatest concern with respect to carcinogenicity. The CP of more than 25% of the industrial samples from the island surpassed the Canadian guidance threshold value (600 μg kg⁻¹) for an excess lifetime cancer risk (ELCR) of 1 in 10⁻⁶. While soil samples from the remaining land uses on the island were all below this threshold, PAH levels in soil were nonetheless elevated (enrichment factors of between 4.1 ± 1.9 and 16.3 ± 12.4 in the HUA, and between 1.3 ± 0.7 and 10.8 ± 4.4 in the LUA). Results relating to agricultural locations on the island indicated 75% of the samples in HUA and 28% of the samples in LUA to be above the USEPA guidance value for BaP (15 μg kg⁻¹). Given the exceptionally high population density on the island there is a need for further research to evaluate multiple pathway PAH exposure risks.
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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".