Measurements of Octanol−Air Partition Coefficients (<i>K</i><sub>OA</sub>) for Polybrominated Diphenyl Ethers (PBDEs): Predicting Partitioning in the Environment
Bibliographic record
Abstract
Octanol−air partition coefficients ( K OA ) are reported for 13 polybrominated diphenyl ethers (PBDEs) over the temperature range (15−45) °C. K OA exhibited a log−linear relationship with inverse absolute temperature, and values at 25 °C range from 9.3 (PBDE-17) to 12.0 (PBDE-126). These are approximately 1 to 2 orders of magnitude greater than those measured for the counterpart polychlorinated biphenyls (PCBs). PBDEs also showed a strong temperature dependence. The enthalpy of phase change from octanol to air, Δ H OA, was (≈70 to ≈120) kJ mol -1 . This corresponds to a 20−100 times higher K OA value at 5 °C versus 35 °C. A method is presented for estimating K OA at any temperature for additional PBDEs using relative retention times. Log K OA values were compared against two sets of recently published subcooled liquid vapor pressures ( p o L ) that show significant discrepancies. Activity coefficients in octanol (γ O ) for PBDEs ranged from 1 to 10 when one set of vapor pressures was used. This was consistent with other classes of SOCs and indicated near ideal solution behavior. When the second set of values was used, calculated activity coefficients were in the range 10−100, suggesting that these vapor pressure values were inaccurate. Application of K OA for describing partitioning of PBDEs to aerosols and soils was also examined. The predicted percentages (at 25 °C) on aerosols ranged from 1.2% for PBDE-17 to 85% for PBDE-183 and agreed well with measured data, confirming that surface−air partitioning is an important process for the distribution and fate of PBDEs in the environment. Results of illustrative calculations for air−soil partitioning suggest that, because of their high K OA values, PBDEs will exhibit similar background soil concentrations as the PCBs despite having much lower air concentrations.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".