Accelerated biodegradation of petroleum hydrocarbon waste
Bibliographic record
Abstract
Conventional landfarming approaches to bioremediation of refinery and other petroleum sludges are not acceptable environmentally and are banned in most North American jurisdictions. While initial bioreactor-based systems for treatment of these sludges required batch-cycle process-times of 1-3 months, an accelerated process has now been developed which can be completed in 10-12 days. In this process, up to 99% of total petroleum hydrocarbons are degraded and the sludges are converted from hazardous to non-hazardous according to the United States EPA's toxicity characteristic leachate procedure criteria. Understanding and exploiting mechanisms to improve hydrocarbon accession to the degrading microorganisms was a key development component of the process. Contrasting physiological mechanisms were observed for different component organisms of the mixed culture with respect to their associations with the hydrocarbon substrate; and the beneficial effects of using surfactants were demonstrated. The mixed culture used in the process exhibited a capacity for high-rate degradation of volatile organic carbons and the potential use of the culture as a liquid biofilter was demonstrated. The culture was also effective as an inoculant for the bioaugmentation of total petroleum hydrocarbon-contaminated soil and as a de-emulsifier of oilfield emulsions and could transform some other environmental contaminants which are not predominant components of crude oil.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".