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Record W1997756647 · doi:10.1021/es0515607

Mercury Speciation in Coal-fired Power Plant Plumes Observed at Three Surface Sites in the Southeastern U.S.

2006· article· en· W1997756647 on OpenAlexfundno aff
Eric S. Edgerton, Benjamin E. Hartsell, John J. Jansen

Bibliographic record

VenueEnvironmental Science & Technology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
FundersCanadian Pulmonary Fibrosis FoundationSouthern Company
KeywordsMercury (programming language)PlumeEnvironmental chemistryCoalEmission inventoryEnvironmental scienceParticulatesAtmospheric sciencesChemistryMeteorologyMineralogyAir pollutionGeologyGeography

Abstract

fetched live from OpenAlex

Elemental Hg (Hg0), reactive gaseous Hg (RGM) and fine particulate Hg (Hgp) were measured intermittently at three sites in the southeastern U.S. from June 2001 through November 2004. Simultaneous measurements of SO2 and NOy were used to identify plumes from coal fired power plants (CFPPs). Emission signatures and back trajectories were used to identity specific CFPPs, and to compare observed (i.e., at the site) versus expected (i.e., at the stack) Hg speciation. Results for 41 precipitation-free plume events show that observed RGM:SO2 is substantially lower (by a factor of 2-4) than expected RGM:SO2. Hgp represented 2%, or less, of total-Hg in CFPP plumes, in general agreement with emission estimates. Results for 21 events, where both RGM and Hg0 could be estimated, show that total-Hg (i.e., RGM + Hg0) was essentially conserved from the point of emission to the site, and that Hg0 was the dominant form (average 84%). Emission estimates, based on coal analyses and the EPRI-ICR Hg speciation model, indicate that Hg0 should represent about 42% of Hg in the observed plumes. Possible explanations for these differences include, but are not limited to, in-plume reduction of RGM to Hg0, measurement error, errors in emission estimates, and depositional losses. Further work is needed to confirm these results and to determine if they apply to CFPPs in general, or the limited set of observed CFPPs.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.215
Teacher spread0.199 · 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

Citations92
Published2006
Admission routes1
Has abstractyes

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