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Record W2105614276 · doi:10.1002/cjce.20331

Mercury speciation and emission from the coal‐fired power plant filled with flue gas desulfurization equipment

2010· article· en· W2105614276 on OpenAlexvenueno aff
Yunjun Wang, Yufeng Duan, Liguo Yang, Zhijun Huang, Changsui Zhao

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsFlue-gas desulfurizationMercury (programming language)Flue gasElectrostatic precipitatorEnvironmental chemistryCoalWaste managementGypsumChemistryPower stationFlue-gas emissions from fossil-fuel combustionElemental mercuryFlueSulfur dioxideEnvironmental scienceMetallurgyMaterials scienceInorganic chemistryEngineering

Abstract

fetched live from OpenAlex

Abstract Mercury speciation and emission from two Chinese coal‐fired power stations equipped with flue gas desulfurization device were investigated. Research results reveal that Hg 0 is the main form in the flue gas in Plant 1; Hg 2+ is the main form in the flue gas in Plant 2. Most of mercury was emitted to the atmosphere, which was about 77–98%, and the elemental mercury released to atmosphere ranged 73–94% approximately. A pot of mercury is adsorbed by bottom ash, electrostatic precipitator (ESP) ash, and gypsum in Plant 1. However, most mercury, the scale of which is 75–83.2%, is collected by ESP ash, and only 7.0–12.2% mercury is emitted to the atmosphere in Plant 2. The mercury removal by NID semi‐desulfurization system is higher than wet flue gas desulfurization (WFGD) desulfurization system.

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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
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 head0.006
GPT teacher head0.178
Teacher spread0.172 · 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

Citations18
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical Engineering→Same topicMercury impact and mitigation studies→French-language works237,207→