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Record W1973370837 · doi:10.1021/es902409t

In Situ Optical Absorption Mercury Continuous Emission Monitor

2009· article· en· W1973370837 on OpenAlexafffund
Jérôme Thiebaud, Murray J. Thomson, Reza Mani, William Morrow, Eric A. Morris, Charles Q. Jia

Bibliographic record

VenueEnvironmental Science & Technology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Toronto
FundersOntario Centres of Excellence
KeywordsMercury (programming language)In situEnvironmental scienceEnvironmental chemistryAbsorption (acoustics)Remote sensingMaterials scienceChemistryOpticsComputer sciencePhysicsGeology

Abstract

fetched live from OpenAlex

This paper reports the development of an in situ continuous emission monitor (CEM) for measuring elemental mercury (Hg(0)) concentration in the exhaust stream of coal-fired power plants. The instrument is based on the ultraviolet atomic absorption of a mercury lamp emission line by elemental mercury and a light-emitting diode (LED) background correction system. This approach allows an in situ measurement since the absorption of other species such as SO(2) can be removed to monitor the Hg(0) contribution only. Proof of concept was established through a laboratory-based investigation, and a limit of detection, [Hg(0)](min), of 2 microg/m(3) was measured for a 1-min averaged sample and an absorption path length of 49 cm. [Hg(0)](min) is anticipated to be better than 0.2 microg/m(3) across a 7 m diameter stack. Finally, the apparatus was field-tested in a 230 MW coal-fired power plant. The operability of the measurement in real conditions was demonstrated, leading to the first Hg(0) concentration values recorded by the in situ CEM. Comparison with an accepted standard method is required for validation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.001
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 head0.007
GPT teacher head0.249
Teacher spread0.242 · 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 designBench or experimental
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

Citations8
Published2009
Admission routes2
Has abstractyes

Explore more

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