The Effect of Temperature and Aeration Rate on Bioremediation of Diesel-contaminated Soil in Solid-phase Bench-scale Bioreactors
Bibliographic record
Abstract
Abstract Bioremediation of hydrocarbon (HC) contaminated soils is most effective in aerobic conditions. Despite the fact that mass transfer of oxygen is an important process parameter, the effect of this parameter on solid-phase bioremediation has received limited attention. In this study, the combined effect of temperature and aeration on the bioremediation of low organic content coarse-grained soils, freshly contaminated with diesel, was investigated in solid-phase bench-scale bioreactors. Total HC and carbon range soil concentrations, volatilization, and microbial activity were monitored throughout the six-month experiments at two temperatures (7 and 22°C) and at two aeration rates (13 and 45 mL·s−1). Total HC removal reached between 48 and 83%. Generally, removal increased proportionally with temperature and aeration rates, and decreased proportionally with HC compounds molecular weight. Both biodegradation and volatilization played important roles in removal in all treatments. The high aeration rate enhanced microbial activity in soil. Enhancement was believed to be due to increased mass transfer of oxygen from the soil gas to the soil solution, where microbial activity occurs. However, high aeration also enhanced volatilization, especially at 22°C where 51% of HCs were lost to volatilization. High aeration rate enhanced biodegradation of compounds > nC15 without promoting their excessive volatilization. Keywords: aeratedbiopilepetroleum hydrocarbonsvolatilizationbiodegradationcold climate Acknowledgments This work was financially supported by the Director General Environment of the Canadian Department of National Defense, and the Natural Sciences and Engineering Research Council of Canada. We thank the Analytical Services Group, Royal Military College (RMC), Kingston, ON, and the Analytical Services Unit, Queen's University, Kingston, ON, for help and guidance for data analysis; E. Creber and M. Serran for help in conducting laboratory work; Dr. R. Bathurst, Civil Engineering Department, RMC, for logistical support; and Dr. A. LeDuy, Département génie chimique, Université Laval, Québec, QC, for fruitful discussions.
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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 | 0.001 | 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 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".