Zeolite-Assisted Bioremediation of Petroleum Hydrocarbon-Contaminated Soils in Cold Climates: A Treatment Strategy and CO2 Respiration Modelling for Seasonal Freezing
Bibliographic record
Abstract
Unfrozen water availability in seasonally freezing and frozen soils is a prerequisite for microbial survival and adaptation in cold environments. The objectives of this study were to investigate the roles of zeolite in extending unfrozen water retention and microbial activity in petroleum hydrocarbon-contaminated cold-climate soils under seasonal freezing conditions, and to link the effect of unfrozen water to soil respiration modelling using soil-freezing characteristic curves (SFCC). Zeolite-amended soil microcosms subjected to soil drying, which is analogous to soil freezing, were prepared using petroleum hydrocarbon-contaminated soils inoculated with a hydrocarbon-degrading bacterium, Dietzia maris. Results showed the significant survival of Dietzia maris (1.3–3.3 x 106 CFU/g) under induced drying (water-stressed conditions without freezing temperatures) in the zeolite-amended contaminated soils compared to the unamended soils. Additionally, seasonal freezing-induced biostimulation experiments (4 to 10 °C at -1°C/day over 15 days) showed that the developed soil treatment strategy of introducing moderate doses of zeolite (2% w/w), N-based nutrients (200 mg N/kg) and porous carbon (1% w/w) increased unfrozen water retention, which shifted the SFCCs of the soils and extended soil respiration activity under seasonal freezing conditions. In contrast, the untreated soils and those treated with the higher doses of amendments (300 mg N/kg or 2–5% porous carbon) did not exhibit extended soil respiration activity. Soil CO2 respiration data for the treated soils showed that the effect of unfrozen water on soil respiration becomes significant below 0 °C (r = 0.82–0.90). The SFCC of the treated soils, a function of unfrozen water content (θ) and freezing temperature (T), was incorporated into the Arrhenius-based respiration model framework to address the coupled effects of θ and T on prolonging soil respiration activity at sub-zero temperatures (expressed as a CO2 production rate). The resulting SFCC-RESP model successfully predicted the observed CO2 soil respiration during freezing (R2 = 0.94–0.98). Integrating this soil respiration model with soil thermal modelling (SFCC-RESP and TEMP/W) produced spatial distributions of T, θ and CO2 production in the treated contaminated soils during seasonal freezing. This study suggests that zeolite used as a source of water-retaining microbial habitats can assist in the bioremediation of petroleum hydrocarbon-contaminated soils, and that the SFCC-RESP model can be an effective tool for developing bioremediation strategies specialized for seasonal freezing conditions.
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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) | 0.000 | 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".