Temporal and Spatial Trends of Atmospheric Polychlorinated Biphenyl Concentrations near the Great Lakes
Bibliographic record
Abstract
Polychlorinated biphenyl (PCB) concentrations were measured in the atmosphere at six regionally representative sites near the five Great Lakes from 1990 to 2003 as part of the Integrated Atmospheric Deposition Network (IADN). Concentration data for several individual PCB congeners and for total PCBs were analyzed for temporal and spatial trends after correcting for the temperature dependency of the partial pressures. Atmospheric PCB concentrations are decreasing relatively slowly for tetra- and pentachlorinated congeners, an observation that is in agreement with primary emissions modeling. Relatively rapid decreases in PCB concentrations at the sites near Lakes Michigan and Ontario may reflect successful reduction efforts in Chicago and Toronto, respectively. Atmospheric PCB concentrations near Lakes Superior and Huron are now so low that the air and water concentrations may be close to equilibrium. Atmospheric PCB concentrations at sites near Lakes Michigan, Erie, and Ontario are relatively higher than those measured at sites near Lakes Superior and Huron. The highest PCB level was observed at the site near Lake Erie, most likely due to nearby urban activity. However, this relatively higher concentration is still 6-10 times lower than that previously reported at the Chicago site. A correlation between average gas-phase PCB concentration with local population indicates a strong urban source of PCBs. The temperature dependence of gas-phase PCB concentrations is similar at most sites except at Burnt Island on Lake Huron, where very low concentrations, approaching virtual elimination, prevent reliable temperature correlation calculations.
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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 | 0.000 | 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".