Scatter plot of production cost of cellulosic ethanol and percentage GHG savings relative to energy equivalent gasoline over simulation period. GHG savings are based on GHG intensities calculated by considering net carbon sequestered in soils, avoided GHG emissions due to supply of cogenerated electricity to the grid, aboveground GHG emissions, and GHG emissions with average ILUC effect. Production cost of ethanol is annualized over the simulation period. Average parameter values are used for determining production costs. Credit: ACS, Dwivedi et al. Click to enlarge.

The new analysis shows—unlike previous studies that provide a single estimate of GHG intensity of cellulosic biofuel from a particular feedstock—the heterogeneity in the GHG intensity of cellulosic biofuels depending on feedstock; location of feedstock production; and soil quality as well as the trade-offs involved between costs of biofuels and their potential to reduce GHG emissions relative to gasoline.

Simulated annual harvestable yields differed considerably across feedstocks and locations, with the harvestable yields of corn stover being more sensitive to changes in local weather conditions than the yields of switchgrass and miscanthus.

Miscanthus yield was on average at least 28% higher than that of switchgrass and at least 5 times higher than the corn stover yield. Yield of perennial grasses was slightly lower on low than high quality soils, with the difference ranging from 8% to 20% for miscanthus and 3% to 16% for switchgrass. This difference was not statistically significant at any of the three locations. Differences in crop yields led to differences in the average volume of ethanol across feedstocks.

The study also showed that the production cost of ethanol could range from a lower estimate of $0.88 L⁻¹ to a higher estimate of $1.66 L⁻¹. The team also found that ethanol conversion cost was a key determinant of any change in the overall production cost of ethanol derived from selected feedstocks.

The annual production costs of ethanol varied considerably mostly because of variations in feedstock yields and changes in input parameters for high, average, and low cost estimates, they said. Variations were highest in the case of corn stover followed by miscanthus.

We found that the minimum cost of abating GHG emissions with cellulosic biofuels was $48 Mg⁻¹ of GHG emissions and could be as high as $375 Mg⁻¹ of GHG emissions. These costs will be higher if the credits for soil carbon sequestration and cogenerated electricity are not realized. This suggests that at a minimum a carbon tax of $48 Mg⁻¹ of GHG emissions (CO₂ equivalent) would be needed to equalize the energy equivalent cost of consuming cellulosic ethanol and gasoline in 2010 prices.

… The potential heterogeneity in costs and GHG intensities across cellulosic biofuels from alternative feedstocks suggests a critical role for policy incentives that reward low GHG intensity feedstocks and do not treat all feedstocks in the same manner. The Renewable Fuel Standard provides uniform incentives for all cellulosic biofuels provided they meet a 60% threshold level of GHG savings relative to gasoline. Such policies, by themselves, are unlikely to create the incentives to use cellulosic feedstocks that could lead to less GHG intensive biofuels but may be more expensive to produce. Although a carbon tax would provide the differential incentives needed, it would need to be at least $48 Mg⁻¹ of GHG emissions (CO₂ equivalent) to equalize the post-tax cost of cellulosic biofuel and energy equivalent gasoline. In addition to varying with feedstock, yield, location, and climate variables, this estimate depends on the cost of conversion of cellulosic feedstocks to biofuel, the components of life-cycle GHG emissions included, and the price of gasoline.

—Dwivedi et al.

Resources

• Puneet Dwivedi, Weiwei Wang, Tara Hudiburg, Deepak Jaiswal, William Parton, Stephen Long, Evan DeLucia, and Madhu Khanna (2015) “Cost of Abating Greenhouse Gas Emissions with Cellulosic Ethanol” Environmental Science & Technology doi: 10.1021/es5052588