Contribution of Hydrolysis in the Abiotic Attenuation of RDX and HMX in Coastal Waters
Bibliographic record
Abstract
Sinking of military ships, dumping of munitions during the two World Wars, and military training have resulted in the undersea deposition of numerous unexploded ordnances (UXOs). Leaching of energetic compounds such as hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) and octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) from these UXOs may cause adverse ecological effects so that the long-term fate of these chemicals in the sea should be known. The present study assesses the contribution of alkaline hydrolysis into the natural attenuation of RDX and HMX in coastal waters. Alkaline hydrolysis rates were shown to be unaffected by the presence of sodium chloride, the most common component in marine waters. Kinetic parameters (E(a), ln A, k(2)) quantified for the alkaline hydrolysis of RDX and HMX in deionized water (30-50 degrees C, pH 10-12) agreed relatively well with abiotic degradation rates determined in sterilized natural coastal waters (50 and 60 degrees C, variable salinity) even if the latter were generally slightly faster than the former. Furthermore, similar products (HCHO, NO(2)(-), O(2)NNHCH(2)NHCHO) were obtained on alkaline hydrolysis in deionized water and abiotic degradation in coastal waters. These two findings suggested that degradation of nitramines in sterilized natural coastal waters, away from light, was mainly governed by alkaline hydrolysis. Kinetic calculations using the present parameters showed that alkaline hydrolysis of RDX and HMX in marine waters at 10 degrees C would respectively take 112 +/- 10 and 2408 +/- 217 yr to be completed (99.0%). We concluded that under natural conditions hydrolysis should not contribute significantly to the natural attenuation of HMX in coastal waters whereas it could play an active role in the natural attenuation of RDX.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".