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Record W2887190833 · doi:10.11159/icepr18.116

Mycoremediation of Naphthenic Acids Sourced from Oil Sands Process Affected Water

2018· article· en· W2887190833 on OpenAlexaffvenueabout
Sarah M. Miles, Ania C. Ulrich

Bibliographic record

VenueProceedings of the World Congress on New Technologies · 2018
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOil sandsNaphthenic acidProcess (computing)Environmental sciencePetroleum engineeringMining engineeringGeologyMaterials scienceAsphaltComputer scienceMetallurgyGeographyArchaeology

Abstract

fetched live from OpenAlex

Extraction of bitumen from Alberta's oil sands requires large volumes of water, leading to an abundance of oil sands process-affected water (OSPW) that must be remediated prior to discharge or reuse [1].OSPW contains a variety of toxic organic compounds, including polyaromatic hydrocarbons (PAH), benzene, toluene, ethylbenzene, xylenes (BTEX), and naphthenic acids (NAs).NAs are known to be recalcitrant contaminants in OSPW, and a significant contributor to toxicity, which poses a major threat to the environment [2].With the ample presence of organic compounds, microbial communities are highly active in tailings ponds.Previous studies have shown that NAs can be removed from OSPW through microbial degradation under aerobic conditions, and thereby decreasing the toxicity of OSPW [3].NAs have become the primary target of remedial efforts in tailings treatment undertaken by industrial operators.Ongoing efforts into a cost and energy efficient remediation strategy of NAs have focused on bioremediation.However, limited research has been conducted on the use of mycoremediation in the treatment of NAs.The objective of my research is to characterize the capacity for NAs degradation of the fungal isolate Trichoderma harzianum, and to harness this process for surface OSPW mycoremediation.Through selective enrichment of OSPW, a microbial community enriched in NA-degraders was established, and several microbial isolates were identified including for the first time a fungal isolate T. harzianum.To effectively characterize the ability of the fungal isolate to degrade NAs, a microcosm study was conducted, containing OSPW-extracted NAs or commercially-produced NAs as the sole source of carbon.NA concentrations were monitored over time to determine degradation capacity and CO2 production was monitored as a proxy of fungal growth.Initial results indicate successful degradation with 23%-47% removal in 126 days of commercially-produced NAs as per GC-FID.Additional microcosms were prepared using model NAs, specifically cyclohexane carboxylic acid (CHCA), and 1-adamantane carboxylic acid (ACA).These model compounds were chosen to determine what possible effect NA cyclicity has on degradation potential.As CHCA is a single ring it potentially is the most easily degraded compound, and ACA with 3 rings is the most complex model NA available and the most difficult to degrade.Initial results indicate successful degradation of ACA with approximately 13% removal in 126 days as per HPLC-DAD.As ACA is often used as a negative control for biodegradation due to its inability to be biologically degraded.Finding T. harzianum possesses the capacity to degrade ACA is significant indicating perhaps the capacity for degradation of much larger complex ringed NAs.Alberta's oil sands industry has become heavily scrutinized, both within Canada and worldwide.An increased effort in limiting and rectifying the environmental impact from this industry will contribute to the reestablishment of Canada as a leading voice in environmental stewardship.The findings of this research will contribute to the framework needed to create energy efficient remediation efforts by industrial operators in the Alberta oil sands region, and will assist Canada to limit the environmental impact of the oil sands industry.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.009
GPT teacher head0.234
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2018
Admission routes3
Has abstractyes

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