MODELLING OF ATRAZINE TRANSPORT IN THE PRESENCE OF SURFACTANTS
Bibliographic record
Abstract
Laboratory experiments were conducted to examine the effect of detergents on transport of atrazine [2-chloro-4-(ethylamino)-6-(isopropylamino)-s-triazine] through loam and sandy loam soils under saturation conditions. The Convection Dispersion Equation (CDE) was used to model and quantify the effects of detergents on atrazine model parameters: the retardation factor (R), pore velocity (v) and dispersion coefficient (D). The transport parameters were estimated using moment technique and partition coefficient obtained from batch experiments and compared with best-fitted parameters, R and D, keeping pore velocity constant. Results indicated the CDE model was not successful in predicting atrazine transport in the presence of surfactants at high concentrations. In the case of anionic surfactant with Elora loam, the average predicted R and D from moment technique of 3.4 and 11.1 cm2/h, respectively were significantly different than fitted parameters (R = 39 and D = 227 cm2/h). The poor performance of CDE in the presence of surfactants results from physiochemical changes in herbicide solubility and retention to the soil matrix rather than changes in soil hydraulic properties since the predicted pore water velocities from moment technique were similar to those measured during leaching experiments. Nevertheless, BTC analysis with CDE showed that land application of anionic surfactant (sulphonic) significantly increased R and D and decrease v for both soils. Addition of sulphonic increased R of atrazine by 12 and 26 folds for loam and sandy loam soils, respectively. On the other hand non-ionic surfactants seemed to decrease R, especially in sandy loam soil, thus facilitating atrazine leaching through soil. Non-equilibrium conditions seemed to govern atrazine transport in the presence of surfactants; double peaks in breakthrough curves were observed, indicating a need for mathematical models to account for such phenomena. Atrazine dispersion and tailing seemed to be higher through Elora loam compared to Caledon sandy loam due to higher aggregation of the Elora soil.
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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 | 0.002 | 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".