Pilot‐scale <i>in situ</i> bioremediation of gasoline‐contaminated groundwater: Impact of process parameters
Bibliographic record
Abstract
Abstract This study evaluated the impact of groundwater velocity and dissolved oxygen (DO), added as hydrogen peroxide to overcome oxygen solubility limitations, and contaminant concentrations, on the efficiency of an engineered in situ bioremediation (ISB) strategy to treat groundwater contaminated with benzene, toluene, and xylene (BTX). BTX served as model compounds of gasoline contamination. Groundwater velocities of 1, 2, and 4 m/d were studied. At each velocity, two concentrations of BTX were employed—10 and 50 mg/l of each of the contaminants to reflect “hot spot” conditions following a spill or major leak. Similarly DO:BTX mass ratios of 1.5:1 and 3.2:1 were employed. The results of the study indicated that BTX removal efficiencies of 96.7 to 99.7% were achievable at a groundwater velocity of 1 m/d with final concentrations reaching as low as 30 μg/l. BTX removal efficiencies decreased to 70 to 85 percent at a velocity of 2 m/d, and to 37 to 53% at a velocity of 4 m/d. At any given groundwater velocity, BTX removal efficiencies generally increased with increasing DO and BTX concentrations. Mathematical equations for the first‐order biodegradation rate coefficients as a function of the three parameters were derived. Statistical analysis of the data revealed that groundwater velocity was the most significant parameter impacting biodegradation efficiency, accounting for approximately 80% of the variability. Hydraulic conductivity of the aquifer decreased by approximately 80% over the course of the seven‐month study, with 90% of the decline occurring within the first six weeks. Plate counts also impacted hydraulic conductivity. However, it was not possible to model hydraulic conductivity by plate counts only.
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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 | 0.000 | 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 | 0.001 |
| 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".