New Argonne lifecycle analysis of bioethanol pathways finds corn ethanol can reduce GHG emissions relative to gasoline by 19-48%; long-term, cellulosic offers the most benefits
|Well-to-wheels results for greenhouse gas emissions in CO2e for six pathways. Source: Wang et al. Click to enlarge.|
A new lifecycle analysis of five bioethanol production pathways by a team from Argonne National Laboratory led by Dr. Michael Wang found that, relative to petroleum gasoline, ethanol from corn; sugarcane; corn stover; switchgrass; and miscanthus can reduce lifecycle greenhouse gas (GHG) emissions [P10-P90 (P50)] by 19–48% (34%); 40–62% (51%); 90–103% (96%); 77–97% (88%); and 101–115% (108%), respectively when including land use change emissions. They researchers reported similar trends with regard to fossil energy benefits for the five bioethanol pathways. An open access paper on the study in published in the journal Environmental Research Letters.
While the results for cellulosic ethanol (stover, switchgrass and miscanthus) are in line with recent studies, and the findings for sugarcane ethanol are only slightly lower than other similar studies, the results for corn ethanol are in sharp contrast to other studies predicting that corn ethanol would have a greater life-cycle GHG impact than gasoline, the authors noted.
Bioethanol is the biofuel that is produced and consumed the most globally. The US is the dominant producer of corn-based ethanol, and Brazil is the dominant producer of sugarcane-based ethanol. Advances in technology and the resulting improved productivity in corn and sugarcane farming and ethanol conversion, together with biofuel policies, have contributed to the significantly expanded production of both types of ethanol in the past 20 years. These advances and improvements have helped bioethanol achieve increased energy and GHG emission benefits when compared with those of petroleum gasoline.—Wang et al.
In the study, the team used an updated, upgraded version of the GREET model (developed at Argonne by Dr. Wang and colleagues) to estimate life-cycle energy consumption and GHG emissions for the five bioethanol production pathways on a consistent basis. The GREET model covers bioethanol production pathways extensively; the team updated key parameters in the target pathways based on recent research.
Even when they included the highly debated land-use change (LUC) GHG emissions, when the feedstock was changed from corn to sugarcane and then to cellulosic biomass, bioethanol’s reductions in energy use and GHG emissions, when compared with those of gasoline, increased significantly. Thus, they concluded, in the long term, it is cellulosic ethanol production that will offer the greatest energy and GHG emission benefits.
|WTW GHG emission reductions for ethanol pathways relative to gasoline.|
Values are reductions for P10–P90 (P50), relative to P50 of gasoline GHG.
|Including LUC emissions||19-48%
|Excluding LUC emissions||29-57%
They separated GHG emissions into WTP (well-to-pump); PTW (pump-to-wheel); biogenic CO2 (i.e., carbon in bioethanol); and LUC GHG emissions. Combustion emissions are the most significant GHG emission source for all fuel pathways; however, they noted, in the five bioethanol cases, biogenic CO2 in ethanol offsets ethanol combustion GHG emissions almost entirely.
Because of the ongoing debate about the values and associated uncertainties of LUC GHG emissions, they produced two separate sets of results for ethanol: one with LUC emissions included, and the other with LUC emissions excluded. To show the importance of key parameters affecting WTW GHG emissions results for a given fuel pathway, they conducted a sensitivity analysis of GHG emissions with GREET for all six pathways with P10 and P90 values as the minimum and maximum value for each parameter. Findings of this exercise included:
Petroleum gasoline refining efficiency and recovery efficiency of the petroleum feedstock are the most sensitive parameters.
For corn ethanol, the N2O conversion rate in cornfields is the most sensitive factor, followed by the ethanol plant energy consumption. Enzyme and yeast used in the corn ethanol production process are not among the five most influential parameters in the corn ethanol life cycle.
For sugarcane ethanol, the most significant parameters, in order of importance, are ethanol yield per unit of sugarcane, the N2O conversion rate in sugarcane fields, nitrogen fertilizer usage intensity, sugarcane farming energy use and the mechanical harvest share. Sugarcane farming is evolving as mechanical harvesting becomes more widespread and mill by-products are applied as soil amendments.
The three cellulosic ethanol pathways have similar results. The electricity credit is the most significant parameter (except for switchgrass ethanol, for which the N2O conversion rate is the most significant).
Enzyme use is a more significant factor in cellulosic ethanol pathways than in the corn ethanol pathway because the greater recalcitrance of the feedstock currently requires higher enzyme dosages in the pretreatment stage.
The impact of fertilizer-related parameters on WTW GHG emissions results depends on the fertilizer intensity of feedstock farming.
Michael Wang et al. (2012) Well-to-wheels energy use and greenhouse gas emissions of ethanol from corn, sugarcane and cellulosic biomass for US use. Environ. Res. Lett. 7 045905 doi: 10.1088/1748-9326/7/4/045905