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Evaluation of the potential use of e-fuels in the European aviation sector: a comprehensive economic and environmental assessment including externalities.

Diego Freire OrdóñezThorsteinn HalfdanarsonCaroline GanzerNilay ShahNiall Mac DowellGonzalo Guillén-Gosálbez
Published in: Sustainable energy & fuels (2022)
The decarbonisation of the transportation sector is key to meeting the climate goals. Whilst the electrification of road passenger transportation is proving to be a viable low-carbon solution in many contexts, a viable pathway towards a decarbonised aviation sector remains opaque. In this context, so-called e-fuels produced via the combination of H 2 O, CO 2 and renewable energy may have promise owing to their compatibility with existing infrastructure. Most studies on e-fuels focus only on the economic dimension, neglecting their environmental performance and associated costs. Here, we present a techno-economic evaluation and cradle-to-grave life cycle assessment of Fischer-Tropsch (FT) e-jet fuels produced at different locations in Europe from a range of CO 2 and green H 2 sources to comprehensively assess their potential in aviation, explicitly accounting for externalities. Our results show that e-jet fuel is at present much more expensive (at least 5.4-fold) than its fossil analogue, even when externalities are included ( i.e. , at least 2.3 fold the current cost of fossil jet fuel). Furthermore, e-jet fuels could exacerbate the damage to human health and ecosystems despite showing lower carbon footprint and resource scarcity impacts than their fossil counterparts. Overall, e-jet fuel could become more economically and environmentally attractive by reducing the cost and impact of CO 2 and green H 2 and, more specifically, the electricity used in their production processes. In this regard, the production plant's location emerges as a critical factor due to the costs associated with balancing the intermittency of site-specific renewables.
Keyphrases
  • human health
  • life cycle
  • climate change
  • high frequency
  • risk assessment
  • oxidative stress
  • machine learning
  • big data
  • public health
  • artificial intelligence
  • case control
  • plant growth
  • emergency medical