Laboratory Experiments to Evaluate the Effectiveness of Persulfate to Oxidize BTEX in Saline Environment and at Elevated Temperature Using Stable Isotopes
Bibliographic record
Abstract
In this study, batch experiments were carried out to investigate the effectiveness of persulfate (PS) as an oxidant agent to remediate benzene, toluene, ethylbenzene, and xylenes (BTEX) in saline environments and at high water temperatures (30 °C). This hydrological setting is quite common in contaminated groundwater aquifers in Middle Eastern countries. In general, increasing the system temperature from 10 to 30 °C greatly enhanced the effectiveness of PS, and resulted in a faster oxidation rate for the target contaminants. When PS was added to the reactor at 30 °C, the targeted contaminants were almost completely oxidized over a 98-day reaction period. During the chemical oxidation of the BTEX, carbon and hydrogen isotope fractionations were monitored and utilized as potential proof of contaminant degradation. The calculated carbon-enrichment values were −1.9‰ for benzene, −1.5‰ for ethylbenzene and toluene, −0.4‰ for ρ,m-xylene, and −1.4‰ for o-xylene, while the hydrogen enrichment values were −9.5‰, −6.8‰, −2.1‰, −6.9‰, and −9.1‰, respectively. In comparison with other processes, the hydrogen and carbon isotope fractionations during the chemical oxidation by PS were smaller than the isotope fractionations resulting from sulfate reduction and denitrification. This observation demonstrates the differences in the transformation pathways and isotope fractionations when compounds undergo chemical oxidation or biodegradation. The distinct trend observed on the dual isotope plot (Δδ13C vs. Δδ2H) suggests that compound-specific isotope analysis can be utilized to monitor the chemical oxidation of BTEX by PS, and to distinguish treatment zones where PS and biodegradation technologies are applied simultaneously.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".