Life cycle environmental impacts of selected U.S. ethanol production and use pathways in 2022.
Projected life cycle greenhouse gas (GHG) emissions and net energy value (NEV) of high-ethanol blend fuel (E85) used to propel a passenger car in the United States are evaluated using attributional life cycle assessment. Input data represent national-average conditions projected to 2022 for ethanol produced from corn grain, corn stover, wheat straw, switchgrass, and forest residues. Three conversion technologies are assessed: advanced dry mill (corn grain), biochemical (switchgrass, corn stover, wheat straw), and thermochemical (forest residues). A reference case is compared against results from Monte Carlo uncertainty analysis. For this case, one kilometer traveled on E85 from the feedstock-to-ethanol pathways evaluated has 43%-57% lower GHG emissions than a car operated on conventional U.S. gasoline (base year 2005). Differences in NEV cluster by conversion technology rather than by feedstock. The reference case estimates of GHG and NEV skew to the tails of the estimated frequency distributions. Though not as optimistic as the reference case, the projected median GHG and NEV for all feedstock-to-E85 pathways evaluated offer significant improvement over conventional U.S. gasoline. Sensitivity analysis suggests that inputs to the feedstock production phase are the most influential parameters for GHG and NEV. Results from this study can be used to help focus research and development efforts.
Hsu
David D
DD
National Renewable Energy Laboratory, Golden, Colorado 80401-3393, USA. david.hsu@nrel.gov
Inman
Daniel
D
Heath
Garvin A
GA
Wolfrum
Edward J
EJ
Mann
Margaret K
MK
Aden
Andy
A
D000383:Agriculture / Q000191:economics; D000393:Air Pollutants / Q000009:adverse effects / Q000191:economics; D004736:Energy-Generating Resources / Q000191:economics*; D000431:Ethanol / Q000737:chemistry*; D005544:Forecasting; D005742:Gasoline / Q000009:adverse effects / Q000191:economics*; D017752:Greenhouse Effect; D016018:Least-Squares Analysis; D008962:Models, Theoretical; D009010:Monte Carlo Method; D014481:United States; D001335:Vehicle Emissions
D000393:Air Pollutants; D005742:Gasoline; D001335:Vehicle Emissions; D000431:Ethanol