Pesticides in the Atmosphere Across Canadian Agricultural Regions
Bibliographic record
Abstract
The Canadian Atmospheric Network for Currently Used Pesticides (CANCUP) was the first comprehensive, nationwide air surveillance study of pesticides in Canada. This paper presentsthe atmospheric occurrence and distribution of pesticides including organochlorine pesticides (OCPs), organophosphate pesticides (OPPs), acid herbicides (AHs), and neutral herbicides (NHs) during the spring to summer of 2004 and 2005 across agricultural regions in Canada. Atmospheric concentrations of pesticides varied within years and time periods, and regional characteristics were observed including the following: (i) highest air concentrations of several herbicides (e.g., mecoprop, triallate, and ethalfluralin) were found at Bratt's Lake, SK, a site in the Canadian Prairies; (ii) the west-coast site at Abbotsford, BC, had the maximum concentrations of diazinon; (iii) the fruit and vegetable growing region in Vineland, ON, showed highest levels for several insecticides including chlorpyrifos, endosulfan, and azinphos-methyl; (iv) high concentrations of atrazine and metolachlor were measured at St. Anicet, QC, a corn-growing region; (v) the Kensington site in PEI, Canada's largest potato-producing province, exhibited highest level of dimethoate. Analysis of particle- and gas-phase fractions of air samples revealed that most pesticides including OCPs, OPPs, and NHs exist mainly in the gas phase, while AHs exhibit more diversity in particle-gas partitioning behavior. This study also demonstrated that stirred up soil dust does not account for pesticides that are detected in the particle phase. The estimated dry and wet deposition fluxes indicate considerable atmospheric inputs for some current-use pesticides (CUPs). This data set represents the first measurements for many pesticides in the atmosphere, precipitation, and soil for given agricultural regions across Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".