Influence of Eutrophication on Air−Water Exchange, Vertical Fluxes, and Phytoplankton Concentrations of Persistent Organic Pollutants
Bibliographic record
Abstract
The influence of eutrophication on the biogeochemical cycles of persistent organic pollutants (POPs) such as polychlorinated biphenyls (PCBs) is largely unknown. In this paper, the application of a dynamic air−water−phytoplankton exchange model to Lake Ontario is used as a framework to study the influence of eutrophication on air−water exchange, vertical fluxes, and phytoplankton concentrations of POPs. The results of these simulations demonstrate that air−water exchange controls phytoplankton concentrations in remote aquatic environments with little influence from land-based sources of pollutants and supports levels in even historically contaminated systems. Furthermore, eutrophication or high biomass leads to a disequilibrium between the gas and dissolved phase, enhanced air−water exchange, and vertical sinking fluxes of PCBs. Increasing biomass also depletes the water concentrations leading to lower than equilibrium PCB concentrations in phytoplankton. Implications to future trends in PCB pollution in Lake Ontario are also discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".