Chiral PCB Signatures in Air and Soil: Implications for Atmospheric Source Apportionment
Bibliographic record
Abstract
Enantiomeric fractions (EFs) of chiral PCBs 95, 136, and 149 were measured in samples of topsoil and outdoor air at one urban and one rural location in the U.K. West Midlands between early 2001 and early 2002. While EFs in air were essentially racemic, those in topsoil indicated appreciable enantioenrichment of the second eluting enantiomer for PCB 95 and the (+) enantiomer for PCBs 136 and 149. This suggests (i) that essentially all atmospheric PCBs at both sites arise from racemic (i.e, primary) sources, rather than volatilization from soil and (ii) that appreciable enantioselective degradation of the monitored PCBs in topsoil occurs. This is one of only two reports of enantioselective degradation of PCBs in soil worldwide and is particularly noteworthy as it is occurring at PCB concentrations (e.g., 5.9 pg g(-1) for PCB 136) that are typical of the U.K. and other industrialized countries. The extent of enantioselective degradation in this study for PCBs 95 and 136 is consistent with those reported for soils in the Greater Toronto area (GTA). In contrast, enantioselective degradation of PCB 149 observed in this study is--while consistent with that reported for U.K. lacustrine sediments--in excess of that observed in either the GTA soil study or in U.S. lake sediments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".