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Record W2409907720

Design and optimization of surfactant based enhanced remediation of bunker C fuel oil contaminated soil

2015· dissertation· en· W2409907720 on OpenAlexfundaboutno aff

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2015
Typedissertation
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsnot available
FundersMitacs
KeywordsEnvironmental remediationEnvironmental scienceSoil contaminationWaste managementContaminationRemedial actionUnderground storage tankHazardous wastePetroleumPollutionFuel oilBrownfieldEnvironmental engineeringEngineeringSoil waterStorage tankCivil engineeringChemistry
DOInot available

Abstract

fetched live from OpenAlex

Soil pollution, particularly by petroleum compounds is a very important global issue. It is typically a result of improper storage and disposal, historic careless spills, accidental spills, and leaks from tanks. This environmental damage can result in wide spread groundwater and surface water contamination, and limit soil use for agricultural purposes. There are a large number of brownfield sites across Canada. These are sites that have been previously used for industrial and commercial activities and have been contaminated with hazardous wastes. Newfoundland and Labrador (NL) in particular, has numerous sites due to a legacy of fuel oil use for power generation at abandoned, old and emerging mining fields. Data from the federal contaminated site inventory indicate that on federal owned sites in NL, there are over 3000 m³ of oil-contaminated soil. It has therefore become necessary to develop remediation technologies that are economically and technically feasible, environmentally friendly, fast, and applicable in a wide range of physical settings. A wide range of technologies have been developed over the past few decades for the remediation of contaminated sites. Some of these processes have been found to be successful in removing only a specific group of contaminants from the soil. As a result, combinations of different approaches are usually adopted for more effective remediation thereby leading to more expensive remedial operations. Surfactant-enhanced remediation technology, otherwise known as soil washing has proven to be an effective method to remove a mixture of contaminants such as heavy metals, petroleum compounds, volatile organic compounds, pesticides and herbicides as well as other hazardous and non-degradable substances from contaminated soils. Surfactant remediation relies on the ability of surfactant formulations to remove both organic and inorganic contaminants from soil and sediments by desorbing them from the solid to liquid phase. The technology removes contaminants via two mechanisms; one occurs below the Critical micelle concentration (CMC) of the surfactants known as mobilization mechanism, and the other above the CMC known as solubilization mechanism. However, this technology has not been widely reported for the remediation of Bunker C fuel oil, a complex and recalcitrant petroleum compound that is persistent in the environment and extensively reported to be resistant to chemical and biological degradation, and therefore difficult to remediate. This research presents an assessment of the performance of soil washing technology for the remediation of Bunker C contaminated oil from weathered contaminated soil using patented surfactant formulations. Weathered soil are known to be more difficult to remediate than freshly contaminated soil hence, the study used weathered soil in order to be certain of the effects of soil washing on Bunker C removal. Specific research objectives include: (1) determining the micellar properties (Surface Tension and CMC) of the patented surfactants, (2) development of a reliable analytical method for the analysis of (heavy) petroleum hydrocarbons in soil, (3) evaluation of the parameters that govern the implementation of soil washing and an assessment of their effects on the washing of weathered Bunker C oil from contaminated soil at surfactants concentrations below the CMC (mobilization mechanism) using the multivariate experimental and statistical approach, (4) determination of the optimum conditions (optimization) for the removal of Bunker C oil with the tested surfactants. The research, in the course of analysing the Total Petroleum Hydrocarbon in the soil using the Canada-Wide Standard (CWS) for Petroleum Hydrocarbon in soil is used for the analysis of petroleum hydrocarbon compounds found considerable variability and inconsistencies in the results. This could be due, in part, to the different gas chromatography (GC) conditions, soil properties, as well as and other steps involved in the method. These differences impacts the determination of the effectiveness of remediation at hydrocarbon-contaminated sites. The thesis therefore, developed validated the analytical method for the quantitative analysis of TPH in (contaminated) soil. The newly developed method was successfully applied for a faster and more reliable analysis of TPH of Bunker C oil in contaminated soil. It is expected that this research will lay a road map for further studies on the application, optimization and development of a treatment system protocol for the use of soil washing for Bunker C remediation. It should be noted that although Bunker C is the contaminant, the hydrocarbon composition of Bunker C makes it a good surrogate for other heavy oils.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.021
GPT teacher head0.238
Teacher spread0.217 · 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.

Study designBench or experimental
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

Citations1
Published2015
Admission routes2
Has abstractyes

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