Three Year Field Test of a Plant Growth Promoting Rhizobacteria Enhanced Phytoremediation System at a Land Farm for Treatment of Hydrocarbon Waste
Bibliographic record
Abstract
Phytoremediation of total petroleum hydrocarbons (TPH) has the potential to be a sustainable waste management technology if it can be proven to be effective in the field. Over the past decade, our laboratory has developed a system which utilizes plant growth promoting rhizobacteria (PGPR) enhanced phytoremediation (PEP) that, following extensive greenhouse testing, was shown to be effective at remediating TPH from soils. This system consists of physical soil manipulation and plant growth following seed inoculation with PGPR. PGPR elicit biomass increases, particularly in roots, by minimizing plant stress in highly contaminated soils. Extensive development of the root system enhances degradation of contaminants by the plants and supports an active rhizosphere that effectively promotes TPH degradation by a broad microbial consortium. Following promising greenhouse trials, field tests of PEP were performed over a period of three years at a Southern Ontario site (approximately 130 g kg(-1) TPH) used for land farming of refinery hydrocarbon waste for many years. The low molecular weight fractions (the Canadian Council of Ministers of the Environment (CCME) fractions 1 and 2) were removed through land farming and bioremediation; the high molecular weight, recalcitrant fractions (CCME fractions 3 and 4) remained at high levels in the soil. Using PEP, we substantially remediated fractions 3 and 4, and lowered TPH from 130 g kg(-1) to approximately 50 g kg(-1) over a three year period. The amount of plant growth and extent of oil remediation were consistently enhanced by PGPR.
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 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 | 0.000 |
| 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".