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Record W2106923425 · doi:10.1680/jees.2013.0043

Management of hydrocarbon-contaminated soil through bioremediation and landfill disposal at a remote location in Northern Canada

2013· article· en· W2106923425 on OpenAlexafffundvenueabout
David Sanscartier, Kenneth J. Reimer, Barbara A. Zeeb, Karen George

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsRoyal Military College of Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEnvironmental scienceBioremediationLeachateSoil contaminationMicrocosmWaste managementContaminationEnvironmental engineeringSoil PollutantsPetroleumBiodegradationBiostimulationTotal petroleum hydrocarbonBioaugmentationEnvironmental chemistrySoil waterSoil scienceGeologyChemistryEcology

Abstract

fetched live from OpenAlex

Northern communities often have limited resources to resolve petroleum hydrocarbon (PHC) contamination. This project investigated an innovative approach for the management of diesel-contaminated soil in a remote community in Labrador. The soil was first treated in a passively aerated biopile to reduce the concentrations of mobile PHCs. The treated soil was then disposed of in the local landfill. Maximum total petroleum hydrocarbon (TPH) concentrations in soil, concentrations of PHCs with less than 16 carbons in soil, and TPH in leachate decreased during the 1 year field treatment. Microcosms incubated at 7 and 22 °C in the laboratory showed the potential for biodegradation of the PHCs. However, volatilization was likely the predominant PHC removal mechanism in the field. Disposal of treated soil to landfills has the advantage of transforming waste (i.e., soil) into a valued product (i.e., cover for the refuse). The development of risk-based guidelines for the disposal of PHC-contaminated soil into landfills in Canada appears to be needed and is discussed in this paper. Guidelines should be protective of the environment while prevent over-treatment of the soil, which may result in unnecessary spending and environmental impacts. The cost of the system tested was compared to that of treating soil in an off-site facility.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.002
GPT teacher head0.151
Teacher spread0.149 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2013
Admission routes4
Has abstractyes

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