Incorporating oral, inhalation and dermal bioaccessibility into human health risk characterization following exposure to Chromated Copper Arsenate (CCA)-contaminated soils
Bibliographic record
Abstract
Exposure to potentially toxic metal(loid)s (PTMs) in soil may happen via ingestion, inhalation, and dermal pathway. A more accurate risk characterization should consider PTM bioavailability. Using ten soil samples collected in the Montreal area (Canada) near CCA-treated utility poles, this study aims to characterize non-carcinogenic and carcinogenic human health risks associated with As, Cr, Cu, Pb, and Zn through a multi-pathway exposure approach. This innovative study incorporates, for the first time, the bioaccessible fraction of the metal(loid)s for three exposure routes and two different scenarios. For the residential and industrial scenarios, the oral and dermal pathways yielded a hazard index (HI) much higher than 1 with and without bioaccessibility considerations (range 1.7 – 349 without bioaccessibility and 0.8–134 with bioaccessibility), whereas the inhalation pathway caused a lower hazard (HI < 1). For the dermal pathway, the hazard quotient was higher when bioaccessibility of field-collected samples was considered due to inherent assumptions from the US EPA soil approach to calculate the dermal dose. For carcinogenic risk, As and Pb were the most significant contributors to risk for the oral pathway, followed by the same elements for the dermal pathway. The overall carcinogenic risk was higher than the acceptable risk ( > 10−4) with and without bioaccessibility considerations (range 1.9E-4 – 9.6E-3 without bioaccessibility and 6.8E-5 – 3.8E-3 with bioaccessibility). Bioaccessibility tests provide a more accurate assessment of exposure to PTMs compared to total concentrations in soils.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".