Aircraft-engine particulate matter emissions from conventional and sustainable aviation fuel combustion: comparison of measurement techniques for mass, number, and size
Bibliographic record
Abstract
Abstract. Sustainable aviation fuels (SAFs) have different compositions compared to conventional petroleum jet fuels, particularly in terms of fuel sulphur and hydrocarbon content. These differences may change the amount and physicochemical properties of volatile and non-volatile particulate matter (nvPM) emitted by aircraft engines. In this study, we evaluate whether comparable nvPM measurement techniques respond similarly to nvPM produced by three blends of SAFs compared to three conventional fuels. Multiple SAF blends and conventional (Jet A-1) jet fuels were combusted in a V2527-A5 engine, while an additional conventional fuel (JP-8) was combusted in a CFM56-2C1 engine. We evaluated nvPM mass concentration measured by three real-time sampling techniques: photoacoustic spectroscopy, laser-induced incandescence, and the extinction-minus-scattering technique. Various commercial instruments were tested including three LII 300s, one PAX, one MSS+, and two CAPS PMSSA. Mass-based emission indices (EIm) reported by these techniques were similar, falling within 30 % of their geometric mean for EIm above 100 mg/kgfuel (approximately 10 μg PM m−3 at the instrument), this geometric mean was therefore used as a reference value. Additionally, two integrative measurement techniques were evaluated: filter photometry and particle size distribution (PSD) integration. The commercial instruments used were one TAP, one PSAP, and two SMPSs. These techniques are used in specific applications, such as on-board research aircraft to determine PM emissions at cruise. EIm reported by the alternative techniques fell within approximately 50 % of the mean aerosol-phase EIm. In addition, we measured PM-number-based emissions indices using PSDs and condensation particle counters. The commercial instruments used included TSI SMPSs, a Cambustion DMS500, and an AVL APC, and the data also fell within approximately 50 % of their geometric mean. The number-based emission indices were highly sensitive to the accuracy of the sampling-line penetration functions applied as corrections. In contrast, the EIm data were less sensitive to those corrections since a smaller volume fraction fell within the size range where corrections were substantial. A separate, dedicated experiment also showed that the operating laser fluence used in the LII 300 laser-induced incandescence instrument for aircraft engine nvPM measurement is adequate for a range of SAF blends investigated in this study. Overall, we conclude that all tested instruments are suitable for the measurement of nvPM emissions from the combustion of SAF blends in aircraft engines.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".