Photodegradation of Metolachlor: Isolation, Identification, and Quantification of Monochloroacetic Acid
Bibliographic record
Abstract
The photolysis of metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl) acetamide] in a sunlight simulator under actinic radiation was investigated. The focus of the study was to determine the extent of monochloroacetic acid (MCA) production. MCA was concentrated and derivatized from photolysate as the n-propyl ester using propanol and sulfuric acid and then identified as the ester using GC/MS and GC/ECD. On the basis of regression analysis, it was shown that the direct photodegradation of approximately 10 microM metolachlor followed pseudo-first-order kinetics with respect to the metolachlor concentration, and the half-life of the herbicide ( approximately 74 h) was independent of the pH of the medium. Photolysis in synthetic field water (SFW) resulted in a significant reduction of photolysis time (t(1/2) approximately 9 h). Direct photolysis experiments indicate a 5.19 +/- 0.81% (n=3) conversion of metolachlor to MCA, while photolysis in synthetic field water and in a Don River water sample resulted in 29.8 +/- 4.6% (n = 3) and 12.6 +/- 4.1% (n = 3) conversion, respectively; MCA was shown to be hydrolytically stable over the time course of the photoreaction. The photodegradation of alachlor, butachlor and a model chloroacetanilide, 2-chloro-N-methylacetanilide, in SFW were also investigated.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".