MétaCan
Menu
Back to cohort
Record W2076581897 · doi:10.1002/cjce.5450830608

Dissolution Rate of BTEX Contaminants in Water

2005· article· en· W2076581897 on OpenAlexvenueno aff
Derrick O. Njobuenwu, Stephen A. Amadi, Peter C. Ukpaka

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsnot available
Fundersnot available
KeywordsBTEXDissolutionEthylbenzeneBenzeneEnvironmental chemistryTolueneSolubilityContaminationChemistryXyleneMass transfer coefficientMass transferEnvironmental engineeringEnvironmental scienceChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The BTEX group of contaminants consists of benzene, ethylbenzene, toluene, and three isomers of xylene. The dissolution rate, solubility, slick area and mass transfer coefficient were examined for the BTEX. The release of BTEXs into the environment is influenced by their fate and transport mechanisms. Thus, the fate and transport mechanisms are affected by the contaminant characteristics, which vary with the different BTEX compounds. A comprehensive model has been developed to simulate the molecular dissolution rate of BTEX contaminants in a natural water stream. The developed model modifies the work of Cohen et al. (1980) by considering the physicochemical properties of the BTEX compounds and physical processes relevant to the spreading of contaminants in the sea. The model shows that Benzene with greater solubility in water and dissolution coefficient has the largest dissolution rate while o‐xylene with the biggest density has the lowest dissolution rate because of its low fraction. The benzene dissolution rate is about 2.6, 20.6 times that of Toluene, ethylbenzene, respectively, but with a varying proportion with the xylenes. The model has been validated against the theories of mass transfer rate at the surface at appropriate surface area. The developed model can be found useful in prediction and monitoring the dissolution rate of contaminants in soil and water systems.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.424

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 head0.005
GPT teacher head0.165
Teacher spread0.161 · 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 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

Citations30
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicWater Treatment and DisinfectionFrench-language works237,207