CHARACTERIZATION AND MODELING OF THE FORMS OF MERCURY FROM COAL-FIRED POWER PLANTS
Bibliographic record
Abstract
The 1990 Clean Air Act Amendments (CAAAs) required the U.S. Environmental Protection Agency (EPA) to determine whether the presence of mercury in the stack emissions from fossil fuel-fired electric utility power plants poses an unacceptable public health risk. EPA's conclusions and recommendations were presented in the Mercury Study Report to Congress (1) and the Utility Air Toxics Report to Congress (1). The first report addressed both the human health and environmental effects of anthropogenic mercury emissions, while the second addressed the risk to public health posed by the emission of mercury and other hazardous air pollutants from steam-electric generating units. Given the current state of the art, these reports did not state that mercury controls on coal-fired electric power stations would be required. However, they did indicate that EPA views mercury as a potential threat to human health. In fact, in December 2000, the EPA issued an intent to regulate for mercury from coal-fired boilers. However, it is clear that additional research needs to be done in order to develop economical and effective mercury control strategies. To accomplish this objective, it is necessary to understand mercury behavior in coal-fired power plants. The markedly different chemical and physical properties of the different mercury forms generated during coal combustion appear to impact the effectiveness of various mercury control strategies. The original Characterization and Modeling of the Forms of Mercury from Coal-Fired Power Plants project had two tasks. The first was to collect enough data such that mercury speciation could be predicted based on relatively simple inputs such as coal analyses and plant configuration. The second was to field-validate the Ontario Hydro mercury speciation method (at the time, it had only been validated at the pilot-scale level). However, after sampling at two power plants (the Ontario Hydro method was validated at one of them), the EPA issued an information collection request (ICR). The ICR required all coal-fired utilities to submit the mercury concentrations in their coal for one year quarterly, and 80 coal-fired power plants were selected to do mercury flue gas analysis. It was decided by EPRI and the U.S. Department of Energy (DOE) that this project would be suspended until the results of the ICR were known. This report presents the results that were obtained at the two power plants referred to as Sites 111 and E-29. The EERC teamed with Radian International (now URS Corp.) to do the sampling and analysis at these two power plants.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".