The carbon footprint of alternative jet fuels produced in Brazil: exploring different approaches

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Abstract

Although the potential of Alternative Jet Fuels (AJF) to reduce greenhouse gases (GHG) emissions has been widely reported upon in the literature, there are still discrepancies among the results. These may be due to the different GHG accounting methods, including those used by different Low-Carbon Policies (LCPs). To have a clearer understanding of the life cycle performance of AJF, the carbon footprint of ten pathways was estimated, comprising promising feedstocks – such as soybean, palm, sugarcane, sugarcane residues, forestry residues, used cooking oil, beef tallow, and steel off-gases – and ASTM-approved technologies: Hydroprocessed Fatty Acids, Alcohol-to-Jet, and Fischer-Tropsch. Six methodological approaches were used: the attributional and the consequential life cycle assessment, as well as guidelines for the four LCPs: Renovabio (Brazil), CORSIA (aviation sector), RFS (United States), and RED II (Europe). Soybean-based pathway (24 to 98.7 gCO2e/MJ) had the low to no potential for reducing GHG when compared to their fossil counterparts, mainly due to land use change. Of all food-based pathways, AJF produced from sugarcane performed the best (-10.4 to 43.7 gCO2e/MJ), especially when power surplus was credited. AJF from palm oil could present significant GHG reduction for palm expansion in degraded pasturelands. By contrast, Fischer-Tropsch of lignocellulosic residues showed the highest potential for reducing GHG (-95% to -130%). Different from food-based pathways, the potential GHG reduction of residues-based pathways converged within a narrower range (-130% to -50%), except when residual feedstocks have to be redirected from their current economic use. It could lead to GHG emissions higher than fossil fuel.

Original languageEnglish
Article number105260
JournalResources, Conservation and Recycling
Volume166
DOIs
Publication statusPublished - 2021

Keywords

  • Alternative jet fuel
  • Attributional modeling
  • Carbon footprint
  • Consequential modeling
  • Life cycle assessment
  • Low-carbon policies

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