Atmospheric deposition of current use pesticides in the Arctic: Snow core records from the Devon Island Ice Cap, Nunavut, Canada
Bibliographic record
Abstract
Current use pesticides (CUPs) have been detected in the Arctic, even though there are no direct sources and their long range atmospheric transport potential is generally lower than that of legacy pesticides. Data on the deposition of CUPs in the Arctic are required to assess the impact of their global usage and emission. In this study, selected CUPs were measured in the layers of a snow pit sampled on the Devon Ice Cap, Nunavut, Canada. The oldest sampled layers correspond to deposition from the early 1990s. Dacthal and endosulfan sulfate were most frequently detected, with peak deposition fluxes of 1.0 and 0.4 pg cm(-2) per year. While endosulfan sulfate was more abundant than its parent compounds in most years, endosulfan (sum of α and β isomers) was predominant in 2003 and 2006, which together with air mass backward trajectories suggests a possible origin from ongoing use in Eurasia. The interannual variation in CUP deposition fluxes could not be explained with annual variations in the extent of air mass origin over agricultural lands, suggesting that other factors, such as the interannual variation in pesticide use, play a role in affecting the long range transport of CUPs to the Arctic. The very high variability in the concentrations of CUPs in the horizontal layers of Arctic ice caps is most plausibly explained by the highly episodic nature of long range atmospheric transport and deposition. While this strong influence of rare events limits the suitability of ice caps as reliable records of historical trends in Arctic contaminant deposition with annual resolution, the presence of concentration peaks in the ice record is proof of the possibility of such transport and deposition.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".