Adequacy of Benzo(A)Pyrene and Benzene Soluble Materials as Indicators of Exposure to Polycyclic Aromatic Hydrocarbons in a Söderberg Aluminum Smelter
Bibliographic record
Abstract
Occupational and environmental exposure to polycyclic aromatic hydrocarbons (PAHs) occurs as a complex mixture that is evaluated using specific components, such as benzo(a)pyrene (BaP) and benzene soluble materials (BSM). Factors that influence the relationship between BaP, BSM, and other PAHs within an aluminum smelter were investigated. Personal samples collected from 1978 to 2001 were used: 576 samples were analyzed for both BaP and BSM; 479 samples were analyzed for BaP and nine other particulate PAHs. Differences in the log-transformed ratios (PAH/BaP, BaP/BSM) due to anode paste composition, pot group, season, and job were examined using linear regression. Pot groups represented differences in technology, process conditions, and building properties. The models' predicted PAH/BaP ratios were multiplied by BaP relative potency factors to estimate the relative toxicity of the mixture. The correlation between BaP and BSM depended on the anode paste source (range 0.1-0.8). In linear regression, 27% of the variability in the log-transformed BaP/BSM ratio was explained by coal tar pitch, work area, and job; no seasonal or pot group differences were observed. Within the potrooms, BaP was very strongly correlated with other PAHs (majority > 0.9). Depending on the PAH, between 23% and 89% of the variability in the log-transformed PAH/BSM was explained by season, coal tar pitch, pot group, and job. The BaP toxic equivalency factors of the mixture varied more across job (2.1-3.5) than across coal tar pitch source (1.8-2.8) or pot group (2.3-2.5). Seasonal and work area differences in the relationship between BaP and other PAHs have not been reported previously. Until these relationships are better understood, BaP seems to be a reasonable, albeit imperfect, indicator due to the strong correlation between BaP and other PAHs for a given set of conditions and due to the relative abundance of BaP exposure measurements.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".