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Record W1914298847 · doi:10.1029/2001wr000589

Modeling the impact of ethanol on the persistence of benzene in gasoline‐contaminated groundwater

2002· article· en· W1914298847 on OpenAlexaff
John Molson, James F. Barker, Emil O. Frind, Mario Schirmer

Bibliographic record

VenueWater Resources Research · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsGasolineBenzeneEnvironmental chemistryDissolutionPlumeEnvironmental scienceBiodegradationAquiferChemistryContaminationEthanolEnvironmental engineeringGroundwaterWaste managementOrganic chemistryGeologyEcologyGeotechnical engineering

Abstract

fetched live from OpenAlex

The effect of ethanol on the persistence of benzene in gasoline‐contaminated aquifers is simulated using a multicomponent reactive transport model. The conceptual model includes a residual gasoline source which is dissolving at the water table into an aquifer containing a limited amount of dissolved oxygen. The coupled processes include nonaqueous phase liquid (NAPL) source dissolution, transport of the dissolved components, and competitive aerobic biodegradation. Comparisons are made between dissolved benzene plumes from a gasoline spill and those from an otherwise equivalent spill containing 10% ethanol (gasohol). Simulations have shown that under some conditions a 10% ethanol component in gasoline can extend the travel distance of a benzene plume by up to 150% relative to that from an equivalent ethanol‐free gasoline spill. The increase occurs because ethanol preferentially consumes oxygen, which reduces the biodegradation rate of benzene. The impact is limited, however, because sufficient oxygen disperses behind the ethanol plume into the slightly retarded benzene plume. A sensitivity analysis for two common spill scenarios showed that background oxygen concentrations and benzene retardation have the most significant influence on ethanol‐induced benzene persistence. The results are highly relevant in light of the increasing use of ethanol‐enhanced fuels throughout the world and the forthcoming ban of methyl tertiary‐butyl‐ether (MTBE) in California and its probable replacement by ethanol by the end of 2002.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.100
GPT teacher head0.309
Teacher spread0.209 · 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 designSimulation or modeling
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

Citations71
Published2002
Admission routes1
Has abstractyes

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