An Output-Based Approach to Emissions Standards for Gas Turbine Facilities
Bibliographic record
Abstract
The trend towards more gas turbine power and thermal efficiency, derived through high firing temperatures and air compression ratios, has been translated into increased uncontrolled emissions of NOx. Most of these can be readily reduced by 70–90% with reliable Dry Low Emissions combustion. However, legal and regulatory pressures are requiring NOx emission reductions in the order of 98% in some regions. A key point in these traditional methods is that engine system efficiency and CO2 emissions, as well as other impacts, are not directly considered. More efficient units with higher pressure ratios have difficulty meeting ultra-low ppm concentration based standards, especially under transient conditions. This paper examines the permitting approach on overall plant emissions prevention versus controls, and engine operating parameters for several types of units. This can establish a relationship between the mass quantity of NOx emissions, the engine airflows, and the system operational power output. The intent is to explore whether a different approach to emissions standards would enhance engine system reliability and emission prevention effectiveness for already clean energy facilities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 teacher head, 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".