Bioremediation of Petroleum-Contaminated Soil Using Composting
Bibliographic record
Abstract
A site in Saskatchewan consisted of an earthen pit excavated in the ground and filled with petroleum waste (used oil, gasoline, diesel fuel, paint thinners). This pit was in use for approximately 20–25years. As part of the decommissioning of the site, the site owner has to remediate the waste oil disposal pit. It was determined, based on investigation and study, that bioremediation was a suitable alternative for remediation of the contaminated soil in and around the pit. It was decided to conduct a bench scale treatability study to assess the potential for successful bioremediation of the site using composting. Two reactors were set up, each with a nutrient amendment (ammonium phosphate fertilizer). A mixture of grass clippings and sheep manure was added to one reactor to determine if the composting process could be accelerated by the addition of these abundantly available waste materials. Based on the results of the treatability study, the half-life of the petroleum hydrocarbons at the subject site was estimated to be 36.3 and 121.6days with and without the addition of grass clippings and sheep manure (Reactors 1 and 2), respectively. It was estimated that it would take approximately 192 and 643days to remediate the soil (reduce the total petroleum hydrocarbons to 1,000ppm) using the amendments of Reactors 1 and 2, respectively. The results of the study showed that the site could be remediated using composting.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".