Empirical and modeling evidence of regional atmospheric transport of current-use pesticides
Bibliographic record
Abstract
Water samples from 30 lakes in Canada and the northeastern United States were analyzed for the occurrence of 27 current-use pesticides (CUPs). Eleven CUPs were frequently detected in lakes receiving agricultural inputs as well as in remote lakes hundreds of kilometers from known application areas. These included the triazine herbicide atrazine and its desethylated degradation product; the herbicides alachlor, metolachlor, and dacthal; the organophosphate insecticides chlorpyrifos, diazinon, and disulfoton; the organochlorine insecticides alpha-endosulfan and lindane; and the fungicides chlorothalonil and flutriafol. For six of the pesticides, empirical half-distances on the order of 560 to 1,820 km were estimated from the water-concentration gradient with latitude. For most of the pesticides, a suite of assessment models failed to predict such atmospheric long-range transport behavior, unless the effect of periods of lower hydroxyl radical concentrations and dry weather were taken into account. Observations and model results suggest that under the conditions prevailing in south-central Canada (relatively high latitude, low precipitation rates), many CUPs will be able to undergo regional-scale atmospheric transport and reach lakes outside areas of agricultural application. When assessing the potential of fairly reactive and water-soluble substances to undergo long-range transport, it is imperative to account for periods of no precipitation, to assure that degradation rate constants are correct, and to apply oxidant concentrations that are valid for the region and time period of interest.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".