Evaluation of Alternatives to the Ontario Hydro Method as a Reference Method for CAMR
Bibliographic record
Abstract
In June 2005, the U.S. Environmental Protection Agency (EPA) finalized the Clean Air Mercury Rule (CAMR). As part of the rule, all coal-fired power plants will be required to do continuous mercury measurements. To complete the required relative accuracy test assessment (RATA), the only reference methods allowed are the wet-chemistry methods: the Ontario Hydro (OH) mercury speciation method (ASTM International D6784-02) and EPA Method 29. Either method will be a challenge and expensive. It would be much more desirable to use an instrumental reference method (IRM) or use sorbent traps as a reference method so that the results can be obtained quickly and cheaply. This report presents the results from testing at Reliant Energy, Inc.'s, Portland Station. The project was designed to compare mercury concentrations measured using sorbent traps to those obtained using the OH method. The tests were done using a RATA scenario and at three different conditions. In addition, as part of the project, limited IRM testing was also completed. The results from the testing show that the sorbent traps compared very well with the OH method and, therefore, must be considered as a potential reference method. Although the IRM testing using manual injection of elemental and oxidized mercury for dynamic spiking showed some promise, it was clear that additional testing was needed. However, this method of dynamic spiking may not be acceptable to EPA, as it does not consider vapor pressure curves for elemental mercury a National Institute of Standards Technology traceable standard.
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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 | 0.018 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".