MétaCan
Menu
Back to cohort
Record W2791681466 · doi:10.30955/gnj.001885

Modelling the dispersion of benzene emissions from a proposed ethanol producing facility in Farewell-Oshawa of Toronto, Canada

2017· article· en· W2791681466 on OpenAlexaboutno aff

Bibliographic record

VenueGlobal NEST Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceBenzeneDispersion (optics)BiofuelWind speedPollutantAtmospheric sciencesAtmospheric dispersion modelingAir pollutionMeteorologyWind directionAtmosphere (unit)Environmental engineeringWaste managementChemistryGeographyGeologyPhysicsEngineering

Abstract

fetched live from OpenAlex

The production and use of biofuels such as ethanol have been the target of intensive research. One source of ethanol is corn, which is abundant in many countries. In producing ethanol from corn, an assessment of the environmental impact of the process is needed. This study intends to provide insight into benzene emitted from a proposed biofuel plant, its dispersion behavior, and the effects it may have on the immediate environment. Three-season (January, April, and June) dispersion results of benzene emissions from the proposed ethanol-producing facility are evaluated by using the CALPUFF modelling system. Within the framework of the CALPro software, ambient benzene concentrations are modelled over a 24-hour period of exposure by considering the impact of pollutant transformation and removal, and meteorological factors such as wind direction and speed, and temperature. Simulations are performed for the plant area located in Farewell, Oshawa, Ontario, based on the emission and meteorological dataset for the year 2013. The modeling domain covers the area of 30 × 30 km2 with the grid spacing of 150 m. The number of grid lines is taken as 200 for each axis, and the dispersion of benzene emissions is simulated in nine vertical layers of the domain of study. Based on simulated one-hour and 24-hour average benzene concentrations, pollution dispersion results show that the maximum concentrations are recorded as 4.585 and 0.403 µg/m3 at 17h00 LST on hourly basis and on 24-hour basis, respectively, for the winter season. For the spring season, the highest concentrations are measured as 1.345 and 0.136 µg/m3 at 21h00 LST for one-hour and 24-hour periods, respectively. For the summer season, the peak benzene concentrations are found to be 1.085 and 0.277 µg/m3 at 01h00 LST. The results indicate that none of the months exceeds the half-hour limit of 7 µg/m3 set by Ontario Regulation 419/05, but they surpass the Ontario Regulation 419 Schedule 3 limit of 0.01 µg/m3 for a 24-hour dispersion period. This information may prove invaluable to further research on the impacts of the ethanol-production process on the environment.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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 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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueGlobal NEST JournalSame topicVehicle emissions and performanceFrench-language works237,207