MétaCan
Menu
Back to cohort
Record W2899780372 · doi:10.1080/10962247.2018.1535461

Distribution of mercury in the combustion products from coal-fired power plants in Guizhou, southwest China

2018· article· en· W2899780372 on OpenAlexaboutno aff
Songtao Liu, Jianmeng Chen, Yue Cao, Haikuan Yang, Chuanmin Chen, Wenbo Jia

Bibliographic record

VenueJournal of the Air & Waste Management Association · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
FundersFundamental Research Funds for the Central Universities
KeywordsMercury (programming language)Flue gasFly ashElectrostatic precipitatorCoal combustion productsCoalGypsumFlue-gas desulfurizationFlue-gas emissions from fossil-fuel combustionBottom ashEnvironmental chemistryWaste managementParticulatesEnvironmental scienceCombustionChemistryAir pollutionMetallurgyMaterials science

Abstract

fetched live from OpenAlex

Method 30B and the Ontario Hydro Method (OHM) were used to sample the mercury in the flue gas discharged from the seven power plants in Guizhou Province, southwest China. In order to investigate the mercury migration and transformation during coal combustion and pollution control process, the contents of mercury in coal samples, bottom ash, fly ash, and gypsum were measured. The mercury in the flue gas released into the atmosphere mainly existed in the form of Hg°. The precipitator shows a superior ability to remove Hgp (particulate mercury) from flue gas. The removal efficiency of Hg2+ by wet flue gas desulfurization (WFGD) was significantly higher than that for the other two forms of mercury. The synergistic removal efficiency of mercury by the air pollution control devices (APCDs) installed in the studied power plants is 66.69–97.56%. The Hg mass balance for the tested seven coal-fired power plants varied from 72.87% to 109.67% during the sampling time. After flue gas flowing through APCDs, most of the mercury in coal was enriched in fly ash and gypsum, with only a small portion released into the atmosphere with the flue gas. The maximum discharge source of Hg for power plants was fly ash and gypsum instead of Hg emitted with flue gas through the chimney into the atmosphere. With the continuous upgrading of APCDs, more and more mercury will be enriched in fly ash and gypsum. Extra attention should be paid to the re-release of mercury from the reutilization of by-products from APCDs.Implications: Method 30B and the Ontario Hydro Method (OHM) were used to test the mercury concentration in the flue gas discharged from seven power plants in Guizhou Province, China. The concentrations of mercury in coal samples, bottom ash, fly ash, and gypsum were also measured. By comparison of the mercury content of different products, we found that the maximum discharge source of Hg for power plants was fly ash and gypsum, instead of Hg emitted with flue gas through the chimney into the atmosphere. With the continuous upgrading of APCDs, more and more mercury will be enriched in fly ash and gypsum. Extra attention should be paid to the re-release of mercury from the reutilization of by-products from APCDs.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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 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

Citations15
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Air & Waste Management AssociationSame topicMercury impact and mitigation studiesFrench-language works237,207