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AGEAIR: Investigation of the effects of performance deterioration and AGEing on gaseous and particulate emissions of in-service AIRcraft turbofan engines

At a glance

  • Project leader : Dr. Julien Anet
  • Deputy of project leader : Curdin Spirig
  • Project team : Dr. Lukas Durdina, Dr. Lukas Durdina, Jacinta Edebeli, Manuel Waltert
  • Project status : completed
  • Funding partner : Federal government (Bundesamt für Zivilluftfahrt BAZL)
  • Contact person : Julien Anet


The thresholds for various pollutants of turbofan engines with a thrust above 26.7 kN are defined in the Chicago convention, Annex 16, Volume 1-3. Since the emitted particulate matter has become increasingly finer in recent decades, the measurement standard had to be refined. From 2020 on, not only the so-called "smoke number", but also various other parameters will be used as threshold values for newly produced or in-use turbofan engines.
The influence of engine deterioration (or AGEing AIRcraft engines) on the composition of pollutants is still largely unknown. This knowledge is important for the following reasons: (i) The current pollutant certification – and the new one, coming into effect in 2020 - is a type certification for the considered turbofan engine. A change of the pollutant emission behaviour with increasing age is to be expected, in particular due to the wear of components (e.g. deposits on injectors, efficiency losses in compressors, etc.). (ii) The most common emission inventories derive their emission data from the type certification data (ICAO database), which is associated with unknown uncertainties. (iii) In contrast to road traffic, there are no known data sets on the influence of engine ageing on emissions in aviation.
To close this knowledge gap, measurements on CFM56-7B and PW4000 engines are planned. By doing so, two statistically relevant data sets can be created. These data sets are then correlated in a multivariate statistical model with various engine parameters such as EGT margin, run time or cycles. As such, the ageing effect can be quantified. The aim is to develop a simple parameterization which can be applied in emission inventories.