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Record W1529968943 · doi:10.2172/822884

LARGE-SCALE MECURY CONTROL TECHNOLOGY TESTING FOR LIGNITE-FIRED UTILITIES-OXIDATION SYSTEMS FOR WET FGD

2004· report· en· W1529968943 on OpenAlexaboutno aff
Michael J. Holmes, Steven A. Benson, Jeffrey S. Thompson

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
FundersNational Energy Technology LaboratoryNorth Dakota Industrial CommissionU.S. Department of Energy
KeywordsFlue gasEngineeringMercury (programming language)Waste managementCoalEnvironmental scienceComputer science

Abstract

fetched live from OpenAlex

The Energy & Environmental Research Center (EERC) is conducting a consortium-based effort directed toward resolving the mercury (Hg) control issues facing the lignite industry. Specifically, the EERC team--the EERC, EPRI, URS, ADA-ES, Babcock & Wilcox, the North Dakota Industrial Commission, SaskPower, and the Mercury Task Force, which includes Basin Electric Power Cooperative, Otter Tail Power Company, Great River Energy, Texas Utilities (TXU), Montana-Dakota Utilities Co., Minnkota Power Cooperative, BNI Coal Ltd., Dakota Westmoreland Corporation, and the North American Coal Company--has undertaken a project to significantly and cost-effectively oxidize elemental mercury in lignite combustion gases, followed by capture in a wet scrubber. This approach will be applicable to virtually every lignite utility in the United States and Canada and potentially impact subbituminous utilities. The oxidation process is proven at the pilot-scale and in short-term full-scale tests. Additional optimization is continuing on oxidation technologies, and this project focuses on longer-term full-scale testing. The lignite industry has been proactive in advancing the understanding of and identifying control options for Hg in lignite combustion flue gases. Approximately 1 year ago, the EERC and EPRI began a series of Hg-related discussions with the Mercury Task Force as well as utilities firing Texas and Saskatchewan lignites. This project is one of three being undertaken by the consortium to perform large-scale Hg control technology testing to address the specific needs and challenges to be met in controlling Hg from lignite-fired power plants. This project involves Hg oxidation upstream of a system equipped with an electrostatic precipitator (ESP) followed by wet flue gas desulfurization (FGD). The team involved in conducting the technical aspects of the project includes the EERC, Babcock & Wilcox, URS, and ADA-ES. The host sites include Minnkota Power Cooperative Milton R. Young Unit 2 and TXU Monticello Unit 3. The work involves establishing Hg oxidation levels upstream of air pollution control devices (APCDs) and removal rates across existing ESP and FGD units, determining costs associated with those removal rates, investigating the possibility of the APCD acting as a multipollutant control device, quantifying the balance of plant impacts of the control technologies, and facilitating technology commercialization.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.305
Teacher spread0.256 · 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

Citations8
Published2004
Admission routes1
Has abstractyes

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