EVALUATION OF MERCURY EMISSIONS FROM COAL-FIRED FACILITIES WITH SCR AND FGD SYSTEMS
Bibliographic record
Abstract
CONSOL Energy Inc., Research & Development (CONSOL), with support from the U.S. Department of Energy, National Energy Technology Laboratory (DOE) is evaluating the effects of selective catalytic reduction (SCR) on mercury (Hg) capture in coal-fired plants equipped with an electrostatic precipitator (ESP) - wet flue gas desulfurization (FGD) combination or a spray dyer absorber--fabric filter (SDA-FF) combination. In this program CONSOL is determining mercury speciation and removal at 10 coal-fired facilities. The objectives are (1) to evaluate the effect of SCR on mercury capture in the ESP-FGD and SDA-FF combinations at coal-fired power plants, (2) evaluate the effect of catalyst degradation on mercury capture; (3) evaluate the effect of low load operation on mercury capture in an SCR-FGD system, and (4) collect data that could provide the basis for fundamental scientific insights into the nature of mercury chemistry in flue gas, the catalytic effect of SCR systems on Hg speciation and the efficacy of different FGD technologies for Hg capture. This document, the second in a series of topical reports, describes the results and analysis of mercury sampling performed on a 330 MW unit burning a bituminous coal containing 1.0% sulfur. The unit is equipped with a SCR system for NOx control and a spray dryer absorber for SO{sub 2} control followed by a baghouse unit for particulate emissions control. Four sampling tests were performed in March 2003. Flue gas mercury speciation and concentrations were determined at the SCR inlet, air heater outlet (ESP inlet), and at the stack (FGD outlet) using the Ontario Hydro method. Process stream samples for a mercury balance were collected to coincide with the flue gas measurements. Due to mechanical problems with the boiler feed water pumps, the actual gross output was between 195 and 221 MW during the tests. The results showed that the SCR/air heater combination oxidized nearly 95% of the elemental mercury. Mercury removal, on a coal-to-stack basis, was 87%. The mercury material balance closures for the four tests conducted at the plant ranged from 89% to 114%, with an average of 100%. These results appear to show that the SCR had a positive effect on mercury removal. In earlier programs, CONSOL sampled mercury at six plants with wet FGDs for SO{sub 2} control without SCR catalysts. At those plants, an average of 61 {+-} 15% of the mercury was in the oxidized form at the air heater outlet. The principal purpose of this work is to develop a better understanding of the potential Hg removal ''co-benefits'' achieved by NOx, and SO{sub 2} control technologies. It is expected that this data will provide the basis for fundamental scientific insights into the nature of Hg chemistry in flue gas, the catalytic effect of SCR systems on Hg speciation and the efficacy of different FGD technologies for Hg capture. Ultimately, this insight could help to design and operate SCR and FGD systems to maximize Hg removal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".