Bioremediation of Petroleum Hydrocarbons in the Subsurface
Bibliographic record
Abstract
Abstract Due to human activity and, to a lesser extent, natural processes, petroleum hydrocarbons continue to pollute the environment. These contaminants of concern can be found globally and their remediation is key to restoring affected sites to safe and functional status. Conventional treatment of sites contaminated with petroleum hydrocarbons relies heavily on remediation approaches that are often financially prohibitive or may be technically impractical and that sometimes produce undesirable by-products. Using microbes that occur in nature (if not always at the site), can be a viable treatment with distinct advantages. Understanding the environment, contaminants, and natural biological processes occurring are key aspects for effective application of remediation techniques that rely on biological processes. Whether by stimulating the native microbial community, or, secondarily, by augmenting the native community with known degrader populations to degrade the target compounds, bioremediation is a practical, effective, and sustainable natural solution to a wide array of contamination around the globe. This chapter explores approaches to bioremediation of both soil and groundwater contaminated by petroleum hydrocarbons, describing how the approaches work and the benefits and challenges associated with them. It focuses on the use of aerobic and anaerobic microbial bioremediation, phytoremediation, and mycoremediation to address petroleum hydrocarbons.
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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) | 0.001 | 0.001 |
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".