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Record W2392150128

Effect of O_2/CO_2 and Air on Mercury Speciation in Coal Fired Flue Gases

2008· article· en· W2392150128 on OpenAlexaboutno aff
Kefa Cen

Bibliographic record

VenueProceedings of the CSEE · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMercury (programming language)Flue gasChemistryEnvironmental chemistryCoalCombustionSulfurCoal combustion productsElemental mercury
DOInot available

Abstract

fetched live from OpenAlex

To study the different effect of O2/CO2 and air atmospheres on mercury speciation,four coals were fired in a tube furnace in the above two atmospheres at 600,800 and 1000℃.Ontario Hydro method was used to identify mercury speciation in flue gases,and the characteristics of mercury speciation fired in air were compared with that in O2/CO2.The results show that more divalent mercury but less elemental mercury are produced when burned in air than in O2/CO2 atmosphere.The content of elemental mercury decreases and divalent mercury increases with temperature both in air and O2/CO2 atmosphere.When burned at same temperature and atmosphere,different coals have different effect on mercury speciation.For the coals with high sulfur content,more divalent mercury and less elemental mercury are produced in the flue gas than low sulfur content coals.If coals were fired completely,combustion temperature and coal type have no effect on mercury content resided in the ash for both air and O2/CO2 atmosphere.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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 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

Citations1
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the CSEESame topicMercury impact and mitigation studiesFrench-language works237,207