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Record W50119261

Environmental impact assessment of offshore flares in "Sonda de Campeche", Mexico

2005· dissertation· en· W50119261 on OpenAlexaboutno aff
Francisco E Sanchez

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2005
Typedissertation
Languageen
FieldEnergy
TopicOil, Gas, and Environmental Issues
Canadian institutionsnot available
Fundersnot available
KeywordsSubmarine pipelineEnvironmental scienceEnvironmental impact assessmentPollutantPollutionAir pollutionEnvironmental engineeringNatural gasEnvironmental protectionWaste managementEngineeringLaw
DOInot available

Abstract

fetched live from OpenAlex

An Environmental Impact Assessment of offshore flares located in 'Sonda de Campeche', Mexico was performed to evaluate their effect on the regions adjoining offshore development. Air and water contamination besides solid wastes are considered to be the main pollutants. A comparative analysis of the laws pertaining to offshore industry in Mexico, Canada, and United States is addressed. As a result of this study, it was found that there was no significant impact from water pollutants or waste management residues during the installation or production phases of the flares, due to offshore development in the concerned areas. Moreover, for air pollution, four air contaminants (NO2, CO, CO2, and CH4) were found to comply with environmental laws (Mexican, and International). On the contrary, three other air pollutants (SO2, H2S, and PM10) do not comply with the standards. Therefore, three actions are recommended to be implemented in the following order. First, chemical absorption is suggested to remove NO X, SO2, and H2S. Following this, the height of flare is to be increased by 15 meters. Finally, a Floating Storage Re-gasification Unit is to be installed in a relatively isolated region. The last action ensures a drastic reduction of air pollution and provides a reservoir for natural gas. The natural gas can be purchased by a private company or can be utilized by the Mexican 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 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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.016
GPT teacher head0.296
Teacher spread0.280 · 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 designObservational
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
Published2005
Admission routes1
Has abstractyes

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