Quantification of the contents in biojet fuel blends using near infrared spectroscopy and multivariate calibration

Abstract

In this work a methodology was developed for the quantification of the contents of petroleum-derived hydroprocessed esters and fatty acids (HEFAs) and farnesane jet fuels in binary and ternary mixtures using near infrared spectroscopy and multivariate calibration based on partial least squares (PLS) regression. The developed models are simpler, faster and cheaper when compared to the standard reference method ASTM D6866-12, with a further advantage of differentiation between biofuels. Petroleum-derived jet fuel and biofuels were determined in binary blends with a root mean square error of prediction (RMSEP) value of 0.48% (v/v) for both HEFA and petroleum-derived jet fuels, with a limit of detection of 0.56% (v/v). Ternary blends presented values of RMSEP of 0.69% (v/v), 0.35% (v/v) and 0.44% (v/v) for HEFA, farnesane and petroleum-derived jet fuels, respectively, with limits of detection in the range of 0.12 to 0.24% (v/v). The developed models, based on bias and permutation tests, did not present systematic errors and trends in residuals, turning them appropriately for analysis of biojet fuel blends.