Enhancing oil-spill bioremediation in sub-Arctic soils through the rational use of nutrients and silica nanocarriers for biostimulation
Bibliographic record
Abstract
There are several thousand petroleum-contaminated sites in remote sub-Arctic Canada and effective site remediation strategies are required to ensure site cleanup with minimum environmental risks. Bioremediation, the bacterial degradation of petroleum hydrocarbons to less hazardous end products is a cost-effective technology that can be easily applied in situ or ex situ at remote sites. This thesis examines how parameters such as dose and mode of biostimulation (addition of inorganic N,P nutrients), microbiology and hydrocarbon degrading gene abundances, and soil aggregate structure influence biodegradation rates and extents in different sub-Arctic soils under representative field conditions in summer months. The first objective examines the rational basis for nutrient biostimulation. Results of a meta-analysis of 58 peer-reviewed studies and microcosm experiments with a sub-Arctic soil over a range of N, P doses showed similar findings: absence of universally favorable N, P doses and N doses > 1,000 mg/kg were unfavorable for enhancing biodegradation rates. Studying interrelationships between biostimulation impact, microbial community, and degradative gene abundance is critical to identify monitoring parameters to assess bioremediation potential. Thus, the second objective was to examine effects of Arctic diesel addition (~3500 mg/kg) and biostimulation (70 mg-N/kg, 78 mg-P/kg) on 7 unsaturated sub-Arctic soils at site summer temperatures. Surprisingly, the significant differences between nutrient amended and unamended soil microbiology did not reflect the relatively small difference in hydrocarbon reductions observed between both systems. One possibility is that nutrient–driven soil organic matter degradation or degradation of metabolites produced from parent hydrocarbon degradation influenced microbial community composition and activity. To develop strategies to provide nutrients at oil-water interface, an important location for degradation of oils containing poorly soluble (high molecular weight hydrocarbons), the third objective examined phosphate delivery specifically to the oil-water interface, an active habitat for hydrocarbon degraders. Core-shell nanoparticles were synthesized containing a hydroxyapatite (nHAP) core with a mesoporous silica shell, functionalized with oleic acid to enable interfacial attachment. nHAP dissolution in aqueous media from the composite nanoparticles was demonstrated. Batch reactors containing 1% hexadecane (model oil) showed 5–fold enhanced interfacial growth of Dietzia maris (a well-known hydrocarbon degrader) when dosed with the nanoparticles, compared to systems not dosed with the nanoparticles. Significantly larger cellular aggregate sizes at the oil-water interface were also observed. Finally, the fourth objective assessed the implications of porosities of soil aggregate interiors on biostimulation efficiency, considering the diffusion of nutrients, oxygen into soil aggregate pores necessary to achieve extensive biodegradation of hydrocarbons. X-Ray Micro Computed Tomography was used to image soil aggregates in a non-destructive manner at voxel sizes of 2.39–3.09 µm, and bioaccessible intra–aggregate porosities were quantified via image analysis. Soils with lower porosities yielded lower biodegradation rates and extents, implying lower porosities have reduced nutrient and oxygen availability in intra–aggregate regions, adversely impacting bioremediation behavior. The sustainability implications of this thesis, relevant to SDGs 8,11,13,14, involve a basis for reducing soil N, P addition, and improve remediation measures for diesel contaminated remote Northern regions, also home to Canada’s Traditional communities. Overall, this thesis examines biostimulation levels, soil microbiology, aggregate microstructure, and core-shell nutrient nanocarriers as parameters towards environment friendly, effective, and targeted bioremediation strategies for petroleum contaminated sub-Arctic soils
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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".