VALIDATION OF MERCURY CEMS WHEN COFIRING BIOMASS AT MADISON ELECTRIC'S BLOUNT STATION
Bibliographic record
Abstract
The state of Wisconsin has been concerned about mercury deposition into its lakes and streams and has been evaluating strategies to reduce mercury emissions. As part of this effort, the Blount Station, owned and operated by Madison Gas and Electric Company (MGE), has undergone a project to evaluate the effects and potential mercury emissions reduction of cofiring preconsumer waste. MGE owns and operates the Blount Generating Station located in central Madison, Wisconsin. At present, Blount operates with nine boilers and six turbine generators. The two largest boilers at Blount produce 400,000 pounds of steam per hour at 950 F and 1250 psi. These larger boilers, MGE's Boiler Nos. 8 and 9, have the capability of cofiring both paper and plastic. MGE's Blount Generating Station was one of the first electric generating stations in the United States to retrofit its existing steam boilers to successfully burn refuse-derived fuel and other alternate fuels including waste paper and wood. It is the No. 9 boiler that was the focus of this project to determine the effect of cofiring PDF (plastic- and paper-derived fuel) on speciated mercury emissions. The project was laid out to compare four different fuel combinations: (1) coal feed only, (2) coal with plastic, (3) coal with paper, and (4) coal with paper and plastic. The design was to run the boiler for 2 days at each condition, thus allowing four samples to be taken at each condition. This plan was aimed at getting at least three representative samples at each condition and allowed for difficulties in sampling and boiler operation. The following objectives were accomplished as part of the project to determine the effects of cofiring PDF on mercury emissions and speciation at MGE Blount Station: Successfully completed all of the mercury sampling for each of the four boiler/PDF conditions using the Ontario Hydro (OH) mercury speciation method; Determined mercury concentrations at the stack location using mercury continuous emission monitors (CEMs) for each of the four boiler/PDF conditions; Calculated the overall mercury mass balance for each of the runs; Determined chlorine concentrations at the stack location using EPA Method 26A for each of the four boiler/PDF conditions; and Calculated speciated mercury flow to determine removal and/or transformations before its exiting the unit at the stack for each of the four boiler/PDF conditions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".