A critical review of holistic 4E approaches for assessing sustainable aviation fuel pathways: implications for feedstock, technology, policy and scale-up

Abstract

The aviation sector urgently requires decarbonization, positioning Sustainable Aviation Fuels (SAF) as the most viable near-term option for reducing fossil jet fuel dependence. However, SAF scale-up remains constrained by coupled technological, thermodynamic, economic, environmental, and policy related trade offs. Although many studies assess individual dimensions of SAF production, the literature still lacks a critical synthesis explicitly connecting Energy, Exergy, Economic, and Environmental (4E) evidence across certified pathways. This review examines 4E related approaches applied to SAF by linking energy and exergy analyses with techno economic assessment, life cycle assessment (LCA), and their exergoeconomic and exergoenvironmental extensions where available. The systematic review reveals a fragmented evidence base, with only a limited subset of studies quantitatively addressing all four dimensions. Hydroprocessed Esters and Fatty Acids remains the most mature and economically competitive route, but its scalability is limited by sustainable lipid feedstock availability, hydrogen sourcing, and land use constraints. Gas-to-Jet, Alcohol-to-Jet, and Sugar-to-Jet offer greater feedstock flexibility or biochemical innovation, but face higher capital intensity, upgrading complexity, hydrogen demand, or blend limit restrictions. Across pathways, thermodynamic irreversibilities in heat exchange, separation, syngas conditioning, fermentation, and upgrading stages propagate into cost formation and environmental burdens. LCA evidence shows that Greenhouse gases reductions depend strongly on feedstock origin, hydrogen source, allocation choices, and system boundaries. By organizing these interdependencies through a pathway level 4E indicator linking matrix, this review provides an evidence based foundation for more transparent comparative assessments, process optimization, investment analysis, and policy design for SAF deployment