Petroleum Hydrocarbon Biodegradation under Seasonal Freeze−Thaw Soil Temperature Regimes in Contaminated Soils from a Sub-Arctic Site
Bibliographic record
Abstract
Several studies have shown that biostimulation in ex situ systems such as landfarms and biopiles can facilitate remediation of petroleum hydrocarbon contaminated soils at sub-Arctic sites during summers when temperatures are above freezing. In this study, we examine the biodegradation of semivolatile (F2: C10-C16) and nonvolatile (F3: C16-C34) petroleum hydrocarbons and microbial respiration and population dynamics at post- and presummer temperatures ranging from -5 to 14 °C. The studies were conducted in pilot-scale tanks with soils obtained from a historically contaminated sub-Arctic site in Resolution Island (RI), Canada. In aerobic, nutrient-amended, unsaturated soils, the F2 hydrocarbons decreased by 32% during the seasonal freeze-thaw phase where soils were cooled from 2 to -5 °C at a freezing rate of -0.12 °C d(-1) and then thawed from -5 to 4 °C at a thawing rate of +0.16 °C d(-1). In the unamended (control) tank, the F2 fraction only decreased by 14% during the same period. Biodegradation of individual hydrocarbon compounds in the nutrient-amended soils was also confirmed by comparing their abundance over time to that of the conserved diesel biomarker, bicyclic sesquiterpanes (BS). During this period, microbial respiration was observed, even at subzero temperatures when unfrozen liquid water was detected during the freeze-thaw period. An increase in culturable heterotrophs and 16S rDNA copy numbers was noted during the freezing phase, and the (14)C-hexadecane mineralization in soil samples obtained from the nutrient-amended tank steadily increased. Hydrocarbon degrading bacterial populations identified as Corynebacterineae- and Alkanindiges-related strains emerged during the freezing and thawing phases, respectively, indicating there were temperature-based microbial community shifts.
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 | 0.001 | 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) | 0.000 | 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 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".