Impacts of Lindane Usage in the Canadian Prairies on the Great Lakes Ecosystem. 1. Coupled Atmospheric Transport Model and Modeled Concentrations in Air and Soil
Bibliographic record
Abstract
A coupled atmospheric transport, soil-air, water-air exchange model was developed to investigate the impacts of gamma-hexachlorocyclohexane (gamma-HCH or lindane) usage in the Canadian prairies over the Great Lakes region. The fate of gamma-HCH in air and soil is governed by atmospheric dynamics and physical and chemical processes that are described by the coupled model. These processes include transport and turbulent diffusion in the atmosphere, dry and wet deposition, exchange at the interfacial boundaries of air-water and soil-air, and removal processes from the soil such as diffusion, leaching, and degradation. Numerical experiments were conducted for the period of May 1, 1998-April 30, 1999, starting with application of lindane in the spring. The coupled model was executed with two lindane emission (usage) inventories in the model domain. The first scenario contained all known fresh emission sources in Canada-98% was usage in the prairies; the second excluded emission sources from Ontario and Quebec. The model showed that, in the absence of the reemission from past application of lindane, usage of lindane in Ontario and Quebec has a negligible impact on air concentrations in these regions and that the lindane budget in the Great Lakes ecosystem is mostly attributed to applications of lindane in the canola fields in Canadian prairie provinces. Model-predicted air concentrations and seasonal trends agreed well with measured data over the same time period for several background sites operated under the Integrated Atmospheric Deposition Network. Air temperature was shown to play a key role on surface-air exchange dynamics of gamma-HCH. A future paper will assess loadings to the Great Lakes based on these validated model results.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".