Degradation of chlorinated butenes and butadienes by granular iron
Bibliographic record
Abstract
Sites where chlorobutyl rubber is produced have the potential to release a mixture of chlorinated butenes and butadienes, which are known to be toxic and persistent, into the groundwater environment.The potential contaminants include trans-1,4-dichlorobutene-2 (1,4-DCB-2), 3,4-dichlorobutene-1 (3,4-DCB-1), 2,3,4-trichlorobutene-1 (2,3,4-TCB-1), 2-chlorobutadiene-1,3 (chloroprene) and 2,3-dichlorobutadiene-1,3 (DCBD).Granular iron has been shown to reductively dechlorinate a number of compounds and has been used in permeable reactive barriers (PRBs) for in-situ groundwater remediation.To evaluate the possibility of using granular iron for the remediation of the above contaminants, a series of batch experiments were conducted.Results show that dechlorination reactions for chlorinated butenes closely followed pseudo-first-order kinetics with normalized half-lives ranging from 5.1 to 7.5 h.Chlorinated butadienes degraded much slower in batch tests with normalized half-lives ranging from 38.8 to 128 h.Chlorine mass balance calculations showed that 1,4-DCB-2, 3,4-DCB-1 and chloroprene were fully dechlorinated by granular iron.2,3,4-TCB-1 was transformed to chloroprene as an intermediate via a reductive β-elimination pathway.Neither the presence of CaCO 3 nor temperature affected degradation rates suggesting that mass transport to iron surfaces was limiting degradation in batch tests.A column experiment was conducted on 3,4-DCB-1 and a normalized half-life of 1.6 min was found.Faster degradation in the column was thought to be due to enhanced mixing effects.3,4-DCB-1 was converted to 1,3butadiene via reductive β-elimination, which was then converted to a mixture of 1-butene, cis-2-butene and trans-2-butene via catalytic hydrogenation.
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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".