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Record W2020774664 · doi:10.1115/ipc2014-33016

Measurements of NOx Emissions From DLE and Non-DLE Gas Turbine Engines Employed in Natural Gas Compressor Stations and Comparison With PEM Models

2014· article· en· W2020774664 on OpenAlexaffabout
K. K. Botros, L. Siarkowski, S. Barss, R. Manabat

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsTransCanada (Canada)Nova Chemicals (Canada)
Fundersnot available
KeywordsNOxPollutantEnvironmental scienceNatural gasVolume (thermodynamics)Criteria air contaminantsCompressor stationGas compressorGas turbinesEnvironmental engineeringAir pollutionEngineeringAir pollutantsWaste managementCombustionChemistryMechanical engineering

Abstract

fetched live from OpenAlex

The Environmental Protection Agency (EPA) publishes emissions factors for gas turbines in its Compilation of Air Pollutant Emission Factors, “Volume I Stationary Point and Area Sources, Publication No. AP-42”. This document uses an emissions factor (EF) which is a representative value that attempts to relate the quantity of a pollutant released to the atmosphere with an activity associated with the release of that pollutant. For natural gas-fired gas turbines, EPA NOx (nitrogen oxides) emissions factors are usually expressed as the weight of pollutant per unit fuel volume burned or its equivalent heating value (e.g. kg/m3 or kg/GJ). In most cases, these factors are simply averages of available data, and are generally assumed to be representative of long-term averages for all facilities in the source category. Additionally, AP-42 specifies two EFs depending on the engine load being above or below 80% of rated power. In this paper, NOx emissions tests were conducted on four gas turbines. The first two were non dry low emissions (non-DLE) General Electric engines (LM1600), one in Alberta and the other in Ontario, with significant elevation difference. The other two were Rolls-Royce (R-R) engines; one DLE (RB211-24G) while the other is a non-DLE (RB211-24C), both in Alberta at the same elevation. These tests were conducted at different ambient temperatures varying from −7°C to +28°C using Continuous Emissions Monitoring (CEM) emissions samples based on EPA Method 7E standard. Predictive Emission Monitoring (PEM) systems were also developed based on these and previous testing, and predictions are compared to measured data. The difference between NOx emissions from these four engines at different loads (minimum to maximum) and different ambient conditions are presented and compared. A comparison with AP-42 emissions factors is presented and discussed. It was found that the elevation difference between the two LM1600 engines makes a significant difference in NOx emissions. Additionally, the emissions from the DLE engine when it is operating out of the DLE mode (at low loads) emits higher NOx than a non-DLE engine at the same load and ambient conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.239
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2014
Admission routes2
Has abstractyes

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