Desorption of Herbicides from Atmospheric Particulates During High-Volume Air Sampling
Bibliographic record
Abstract
Pesticides can be present in the atmosphere either as vapours and/or in association with suspended particles. High-volume air sampling, in which air is aspirated first through a glass fibre filter to capture pesticides associated with atmospheric particulates and then polyurethane foam (PUF), often in combination with an adsorbent resin such as XAD-2, to capture pesticides present as vapours, is generally employed during atmospheric monitoring for pesticides. However, the particulate fraction may be underestimated because some pesticides may be stripped or desorbed from captured particulates due to the pressure drop created by the high flow of air through the filter. This possibility was investigated with ten herbicide active ingredients commonly used on the Canadian prairies (dimethylamine salts of 2,4-D, MCPA and dicamba, 2,4-D 2-ethylhexyl ester, bromoxynil octanoate, diclofop methyl ester, fenoxaprop ethyl ester, trifluralin, triallate and ethalfluralin) and seven hydrolysis products (2,4-D, MCPA, dicamba, bromoxynil, diclofop, clopyralid and mecoprop). Finely ground heavy clay soil fortified with active ingredients/hydrolysis products was evenly distributed on the glass fibre filters of high-volume air samplers and air aspirated through the samplers at a flow rate of 12.5 m3/h for a 7-day period. The proportion desorbed as vapour from the fortified soil was determined by analysis of the PUF/XAD-2 resin composite cartridges. The extent of desorption from the fortified soil applied to the filters varied from 0% for each of the dimethylamine salts of 2,4-D, MCPA and dicamba to approximately 50% for trifluralin, triallate and ethalfluralin.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".