Air−Soil Exchange of Organochlorine Pesticides in Agricultural Soils. 1. Field Measurements Using a Novel in Situ Sampling Device
Bibliographic record
Abstract
Initial results are presented for in situ measurements of soil−air partitioning for a range of organochlorine (OC) pesticides in two contaminated agricultural soils. A soil survey was conducted and used to identify high levels of several OC pesticides in two regions of southern Ontario that are known for their intensive agriculture, the Tobacco Belt and the Holland Marsh. Experiments were conducted at one field in each region by sampling air very close to the soil surface using a disc-shaped sampler. The equilibrium status of the sampled air was tested by comparing the chiral signature of the soil with the signature in air sampled by the device and ambient air. Although results showed that 104% of trans -chlordane (TC) and 96% of cis -chlordane (CC) in the air under the sampler originated from the soil, the propagated errors in these results (34% SD for TC and 26% SD for CC) are too large to provide conclusive evidence for equilibrium. Therefore, a soil−air quotient ( Q SA ) is reported here instead of the soil−air partition coefficient ( K SA ). This value is an approximation of the “true” K SA . Results show a linear relationship between log Q SA and log K OA and fit in with the relationship K SA = 0.411ρφ OC K OA where ρ is the soil density (kg L - 1 ). Using this relationship, fugacities were calculated in air and soil. Results of this calculation identify a strong disparity that favors soil-to-air transfer. This gradient is confirmed by measurements at different heights over one of the fields. Soil−air exchange is a key process in the overall fate of OC pesticides. The results from this study will improve our ability to model this process and account for differences between soils.
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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 | 0.000 | 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 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".