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Title: Life-Cycle Analysis of Alternative Aviation Fuels in GREET

Abstract

The Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model, developed at Argonne National Laboratory, has been expanded to include well-to-wake (WTWa) analysis of aviation fuels and aircraft. This report documents the key WTWa stages and assumptions for fuels that represent alternatives to petroleum jet fuel. The aviation module in GREET consists of three spreadsheets that present detailed characterizations of well-to-pump and pump-to-wake parameters and WTWa results. By using the expanded GREET version (GREET1_2011), we estimate WTWa results for energy use (total, fossil, and petroleum energy) and greenhouse gas (GHG) emissions (carbon dioxide, methane, and nitrous oxide) for (1) each unit of energy (lower heating value) consumed by the aircraft or(2) each unit of distance traveled/ payload carried by the aircraft. The fuel pathways considered in this analysis include petroleum-based jet fuel from conventional and unconventional sources (i.e., oil sands); Fisher-Tropsch (FT) jet fuel from natural gas, coal, and biomass; bio-jet fuel from fast pyrolysis of cellulosic biomass; and bio-jet fuel from vegetable and algal oils, which falls under the American Society for Testing and Materials category of hydroprocessed esters and fatty acids. For aircraft operation, we considered six passenger aircraft classes and four freight aircraft classes inmore » this analysis. Our analysis revealed that, depending on the feedstock source, the fuel conversion technology, and the allocation or displacement credit methodology applied to co-products, alternative bio-jet fuel pathways have the potential to reduce life-cycle GHG emissions by 55–85 percent compared with conventional (petroleum-based) jet fuel. Although producing FT jet fuel from fossil feedstock sources — such as natural gas and coal — could greatly reduce dependence on crude oil, production from such sources (especially coal) produces greater WTWa GHG emissions compared with petroleum jet fuel production unless carbon management practices, such as carbon capture and storage, are used.« less

Authors:
 [1];  [1];  [1];  [2];  [2];  [2];  [3];  [3]
  1. Argonne National Lab. (ANL), Argonne, IL (United States)
  2. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
  3. Volpe National Transportation Systems Center, Cambridge, MA (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Bioenergy Technologies Office (EE-3B); U.S. Department of Transportation, Federal Aviation Administration; Air Force Research Laboratory; Department of Defense
OSTI Identifier:
1255237
Report Number(s):
ANL/ESD/12-8
127787
DOE Contract Number:  
AC02-06CH11357
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Elgowainy, A., Han, J., Wang, M., Carter, N., Stratton, R., Hileman, J., Malwitz, A., and Balasubramanian, S. Life-Cycle Analysis of Alternative Aviation Fuels in GREET. United States: N. p., 2012. Web. doi:10.2172/1255237.
Elgowainy, A., Han, J., Wang, M., Carter, N., Stratton, R., Hileman, J., Malwitz, A., & Balasubramanian, S. Life-Cycle Analysis of Alternative Aviation Fuels in GREET. United States. doi:10.2172/1255237.
Elgowainy, A., Han, J., Wang, M., Carter, N., Stratton, R., Hileman, J., Malwitz, A., and Balasubramanian, S. Fri . "Life-Cycle Analysis of Alternative Aviation Fuels in GREET". United States. doi:10.2172/1255237. https://www.osti.gov/servlets/purl/1255237.
@article{osti_1255237,
title = {Life-Cycle Analysis of Alternative Aviation Fuels in GREET},
author = {Elgowainy, A. and Han, J. and Wang, M. and Carter, N. and Stratton, R. and Hileman, J. and Malwitz, A. and Balasubramanian, S.},
abstractNote = {The Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model, developed at Argonne National Laboratory, has been expanded to include well-to-wake (WTWa) analysis of aviation fuels and aircraft. This report documents the key WTWa stages and assumptions for fuels that represent alternatives to petroleum jet fuel. The aviation module in GREET consists of three spreadsheets that present detailed characterizations of well-to-pump and pump-to-wake parameters and WTWa results. By using the expanded GREET version (GREET1_2011), we estimate WTWa results for energy use (total, fossil, and petroleum energy) and greenhouse gas (GHG) emissions (carbon dioxide, methane, and nitrous oxide) for (1) each unit of energy (lower heating value) consumed by the aircraft or(2) each unit of distance traveled/ payload carried by the aircraft. The fuel pathways considered in this analysis include petroleum-based jet fuel from conventional and unconventional sources (i.e., oil sands); Fisher-Tropsch (FT) jet fuel from natural gas, coal, and biomass; bio-jet fuel from fast pyrolysis of cellulosic biomass; and bio-jet fuel from vegetable and algal oils, which falls under the American Society for Testing and Materials category of hydroprocessed esters and fatty acids. For aircraft operation, we considered six passenger aircraft classes and four freight aircraft classes in this analysis. Our analysis revealed that, depending on the feedstock source, the fuel conversion technology, and the allocation or displacement credit methodology applied to co-products, alternative bio-jet fuel pathways have the potential to reduce life-cycle GHG emissions by 55–85 percent compared with conventional (petroleum-based) jet fuel. Although producing FT jet fuel from fossil feedstock sources — such as natural gas and coal — could greatly reduce dependence on crude oil, production from such sources (especially coal) produces greater WTWa GHG emissions compared with petroleum jet fuel production unless carbon management practices, such as carbon capture and storage, are used.},
doi = {10.2172/1255237},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2012},
month = {6}
}

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