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Record W631224985 · doi:10.1520/stp104499

Sediment Contamination Due to Oil-Suspended Particulate Matter Aggregation during Oil Spills in Coastal Waters

2012· book-chapter· en· W631224985 on OpenAlexaff
Ali Khelifa

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsOil spillParticulatesEnvironmental scienceSedimentContaminationOceanographyEnvironmental chemistryEnvironmental engineeringGeologyChemistryEcologyGeomorphologyBiology

Abstract

fetched live from OpenAlex

Aggregation between suspended oil droplets and suspended particulate matter (SPM), which leads to the formation of oil-SPM aggregates (OSAs), is recognized as an important process affecting the fate of spilled oil in fresh and marine water systems. It affects oil sedimentation and; thus, contamination of bottom sediments during oil spill events. This paper presents laboratory results from a multi-year research project to gain quantitative understanding of the factors controlling the formation and fate of OSAs formed with naturally and chemically dispersed oils. The results relate to the measurements of OSA's content in total petroleum hydrocarbon (TPH), size distribution, density and settling velocity. Oil sedimentation caused by negatively buoyant OSAs varied from 0.3 % to 56 %. The highest percentage of oil sedimentation was obtained with chemically dispersed oil. The size of OSAs varied from 40 to 700 μm. The median size varied between 115 and 240 μm. The effective density and settling velocity varied between 10 and 200 g/L and 0.3 and 3 mm/s, respectively. The study showed that sediment grain size and concentration have strong influence on OSA formation. For a relatively low sediment concentration of 100 mg/L, OSA formation can lead to significant enhancement of oil transfer from the water surface to bottom sediments. Overall, the study showed that the formation and physical properties of OSAs are similar to those of sediment flocs.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.832
Threshold uncertainty score1.000

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)0.0200.010

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 head0.008
GPT teacher head0.198
Teacher spread0.190 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreOther

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

Citations1
Published2012
Admission routes1
Has abstractyes

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