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Title: Well-to-wake analysis of ethanol-to-jet and sugar-to-jet pathways

To reduce the environmental impacts of the aviation sector as air traffic grows steadily, the aviation industry has paid increasing attention to bio-based alternative jet fuels (AJFs), which may provide lower life-cycle petroleum consumption and greenhouse gas (GHG) emissions than petroleum jet fuel. Here, this study presents well-to-wake (WTWa) results for four emerging AJFs: ethanol-to-jet (ETJ) from corn and corn stover, and sugar-to-jet (STJ) from corn stover via both biological and catalytic conversion. For the ETJ pathways, two plant designs were examined: integrated (processing corn or corn stover as feedstock) and distributed (processing ethanol as feedstock). Also, three H 2 options for STJ via catalytic conversion are investigated: external H 2 from natural gas (NG) steam methane reforming (SMR), in situ H 2, and H 2 from biomass gasification. Results demonstrate that the feedstock is a key factor in the WTWa GHG emissions of ETJ: corn- and corn stover-based ETJ are estimated to produce WTWa GHG emissions that are 16 and 73%, respectively, less than those of petroleum jet. As for the STJ pathways, this study shows that STJ via biological conversion could generate WTWa GHG emissions 59% below those of petroleum jet. STJ via catalytic conversion could reduce themore » WTWa GHG emissions by 28% with H 2 from NG SMR or 71% with H 2 from biomass gasification than those of petroleum jet. This study also examines the impacts of co-product handling methods, and shows that the WTWa GHG emissions of corn stover-based ETJ, when estimated with a displacement method, are lower by 11 g CO 2e/MJ than those estimated with an energy allocation method. Corn- and corn stover-based ETJ as well as corn stover-based STJ show potentials to reduce WTWa GHG emissions compared to petroleum jet. Particularly, WTWa GHG emissions of STJ via catalytic conversion depend highly on the hydrogen source. On the other hand, ETJ offers unique opportunities to exploit extensive existing corn ethanol plants and infrastructure, and to provide a boost to staggering ethanol demand, which is largely being used as gasoline blendstock.« less
Authors:
ORCiD logo [1] ;  [2] ;  [1]
  1. Argonne National Lab. (ANL), Argonne, IL (United States)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Report Number(s):
NREL/JA-5100-67911
Journal ID: ISSN 1754-6834
Grant/Contract Number:
AC36-08GO28308; AC02-06CH11357
Type:
Accepted Manuscript
Journal Name:
Biotechnology for Biofuels
Additional Journal Information:
Journal Volume: 10; Journal Issue: 1; Journal ID: ISSN 1754-6834
Publisher:
BioMed Central
Research Org:
National Renewable Energy Lab. (NREL), Golden, CO (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; life-cycle analysis; well-to-wake analysis; ethanol-to-jet; sugar-to-jet; greenhouse gas emissions; fossil fuel use; water consumption
OSTI Identifier:
1343401
Alternate Identifier(s):
OSTI ID: 1373566

Han, Jeongwoo, Tao, Ling, and Wang, Michael. Well-to-wake analysis of ethanol-to-jet and sugar-to-jet pathways. United States: N. p., Web. doi:10.1186/s13068-017-0698-z.
Han, Jeongwoo, Tao, Ling, & Wang, Michael. Well-to-wake analysis of ethanol-to-jet and sugar-to-jet pathways. United States. doi:10.1186/s13068-017-0698-z.
Han, Jeongwoo, Tao, Ling, and Wang, Michael. 2017. "Well-to-wake analysis of ethanol-to-jet and sugar-to-jet pathways". United States. doi:10.1186/s13068-017-0698-z. https://www.osti.gov/servlets/purl/1343401.
@article{osti_1343401,
title = {Well-to-wake analysis of ethanol-to-jet and sugar-to-jet pathways},
author = {Han, Jeongwoo and Tao, Ling and Wang, Michael},
abstractNote = {To reduce the environmental impacts of the aviation sector as air traffic grows steadily, the aviation industry has paid increasing attention to bio-based alternative jet fuels (AJFs), which may provide lower life-cycle petroleum consumption and greenhouse gas (GHG) emissions than petroleum jet fuel. Here, this study presents well-to-wake (WTWa) results for four emerging AJFs: ethanol-to-jet (ETJ) from corn and corn stover, and sugar-to-jet (STJ) from corn stover via both biological and catalytic conversion. For the ETJ pathways, two plant designs were examined: integrated (processing corn or corn stover as feedstock) and distributed (processing ethanol as feedstock). Also, three H2 options for STJ via catalytic conversion are investigated: external H2 from natural gas (NG) steam methane reforming (SMR), in situ H2, and H2 from biomass gasification. Results demonstrate that the feedstock is a key factor in the WTWa GHG emissions of ETJ: corn- and corn stover-based ETJ are estimated to produce WTWa GHG emissions that are 16 and 73%, respectively, less than those of petroleum jet. As for the STJ pathways, this study shows that STJ via biological conversion could generate WTWa GHG emissions 59% below those of petroleum jet. STJ via catalytic conversion could reduce the WTWa GHG emissions by 28% with H2 from NG SMR or 71% with H2 from biomass gasification than those of petroleum jet. This study also examines the impacts of co-product handling methods, and shows that the WTWa GHG emissions of corn stover-based ETJ, when estimated with a displacement method, are lower by 11 g CO2e/MJ than those estimated with an energy allocation method. Corn- and corn stover-based ETJ as well as corn stover-based STJ show potentials to reduce WTWa GHG emissions compared to petroleum jet. Particularly, WTWa GHG emissions of STJ via catalytic conversion depend highly on the hydrogen source. On the other hand, ETJ offers unique opportunities to exploit extensive existing corn ethanol plants and infrastructure, and to provide a boost to staggering ethanol demand, which is largely being used as gasoline blendstock.},
doi = {10.1186/s13068-017-0698-z},
journal = {Biotechnology for Biofuels},
number = 1,
volume = 10,
place = {United States},
year = {2017},
month = {1}
}