|Net Energy Value of different ethanol production pathways calculated using the MIT Monte Carlo method, and compared to earlier results. All the calculations have the same system boundary and use fuel’s LHV. Click to enlarge.|
Switchgrass-derived ethanol offers a slightly better net energy value than corn stover cellulosic ethanol, but the switchgrass-based fuel produces significantly lower emissions of greenhouse gases than does its corn-stover based counterpart, according to a new ethanol life cycle analysis by MIT.
The four different cellulosic ethanol pathways assessed in the study all performed much better than the five conventional corn ethanol pathways in the study, some of which showed little to no GHG abatement benefit when compared to gasoline.
Prior high-profile life cycle analyses (LCA) for corn and cellulosic ethanol have relied on single-value system inputs in their calculations. Much depends of the assumptions underlying the selection or calculation of the input value.
However, there is a wide range of variability in the inputs, and, accordingly, LCA results have also varied widely. For corn ethanol, for example, different LCAs have calculated net energy values ranging from -3.2 MJ/L to +9.0 MJ/L.
The study by Tiffany Groode and John Heywood at MIT’s Laboratory for Energy and the Environment tackles the ethanol LCA problem by incorporating a Monte Carlo simulation of the numerous normally distributed inputs accounting for the wide range of agricultural and technological variability into the analysis.
This produces a probability density function (PDF) that represents a range of outcomes for the ethanol production systems fossil energy consumption and GHG emission values. This range of outcomes, rather than the single-value results provides new insights to the ongoing debate around ethanol’s energy security and GHG reduction potential as an alternative fuel.
|Greenhouse Gas emissions for different pathways. Click to enlarge.|
Using the Monte Carlo methodology, Groode and Heywood calculated the net energy value (NEV) and greenhouse gas (GHG) emissions for different corn- and cellulosic-ethanol production scenarios.
For the current best practice corn ethanol case, the duo calculated a net energy benefit for corn ethanol of 3.8 MJ/L plus or minus a standard deviation of 2.3 MJ/L and the emissions of 90±13 gCO2-equivalent/MJ.
Additionally, while mean values for Iowa Corn (Kernel) Ethanol production show moderate energy benefits, there is little to no GHG benefit when compared to gasoline consumption. However, on an energy basis, Iowa Corn (Kernel) Ethanol does decreases petroleum consumption by 68%, since natural gas is the main fossil fuel input.
Results reported by Shapouri, Wang, and Farrell are within one standard deviation of the Monte Carlo models results, indicating that they are all roughly equivalent given the range of variation in key inputs. However, Pimentel’s reported value [-3.2 MJ/L] is more than three standard deviations below the mean Monte Carlo NEV value, making it less than 1% probable. This is primarily a result of Pimentel’s use of older information.
The MIT researchers also assessed other alternative corn ethanol bioethanol production scenarios, including the use of gasifying DDGS to produce process combined heat and power. This scenario brought the NEV and GHG values closer to those of the cellulosic (stover and switchgrass) pathways.
However, a scenario for corn-ethanol produced in Georgia, traditionally non-corn producing state, resulted in the worst performance of any of the scenarios, with an NEV that decreased from a positive 3.75 MJ/L to a negative 7.6 MJ/L and a 47% increase in GHG emissions. The poor results stem from the increased fertilizer inputs, irrigation, and lower corn yields.
The researchers extended the model out to 2025 to project the performance of both best-practice corn ethanol and switchgrass ethanol. Although corn ethanol in 2025 shows some improvement, it still significantly trails cellulosic ethanol.
The research was supported by BP.
LFEE 2007-02 RP; Groode, T. A. and J. B. Heywood; “Ethanol: A Look Ahead”; June, 2007