Evaluating NOx and CO emissions of bio-SPK fuel using a simplified engine combustion model: A preliminary study towards sustainable environment

Abstract

Awareness of environmental and economic issues associated with fossil fuel has led to the exploration of alternative fuels for aviation. Analysis and measurements of alternative fuel using real aircraft engines are complex and costly. Thus, evaluation only through computation is an option at present. This paper presents an analysis of aircraft engine emissions, particularly NOx and CO, from the blend of bio-synthetic paraffinic kerosene (bio-SPK) fuel with kerosene using a simplified gas emission model. Three different fuels, namely, a conventional aviation fuel Jet-A, Jatropha bio-SPK and Camelina bio-SPK were tested as pure and as blends with Jet-A. Chemical properties of the tested fuels were introduced into HEPHAESTUS, an in-house gas emission software developed in Cranfield University. HEPHAESTUS was developed based on the physics-based approach by incorporating a number of stirred reactors to predict NOx, CO, UHC and soot. Gaseous emissions generated from kerosene were observed to follow the trends provided by the ICAO databank. The capability of HEPHAESTUS in predicting the NOx and CO level from biofuel is yet to be explored. The level of NOx and CO predicted in this study followed the trends shown in the literature, although they quantitatively differed. Compared to Jet-A, NOx decreased and CO increased as the percentage of Jatropha bio-SPK and Camelina bio-SPK in the mixture increased. NOx reduction was consistent with the reduction in flame temperature because NOx generation considered in the model was dominantly based on thermal NOx. In contrast, increases in CO were due to low flame temperature that led to incomplete combustion. The consistency of the results obtained showed that the computational work performed in this study as an initial step toward the prediction of emission level of biofuels was successful. However, further studies on the experimental work or computational fluid dynamic simulation is essential.