According to a new study, that compared the greenhouse gas emission reductions of corn ethanol and those of crude oil production and fracking, corn ethanol’s carbon intensity is declining while the carbon intensity of petroleum is increasing. The study was conducted by Life Cycle Associates and found that the carbon impacts associated with crude oil production continue to worsen as more marginal sources of fuel are introduced into the fuel supply.

According to the report, “As the average carbon intensity of petroleum is gradually increasing, the carbon intensity of corn ethanol is declining. Corn ethanol producers are motivated by economics to reduce the energy inputs and improve product yields.”

The study, commissioned by the Renewable Fuels Association (RFA), found that average corn ethanol reduced greenhouse gas (GHG) emissions by 32 percent compared to average petroleum in 2012. This estimate includes prospective emissions from indirect land use change (ILUC) for corn ethanol. When compared to marginal petroleum sources like tight oil from fracking and oil sands, average corn ethanol reduces GHG emissions by 37-40 percent.
As more unconventional crude oil sources enter the U.S. oil supply, and as corn ethanol production processes become even more efficient, the carbon impacts of ethanol and crude oil will continue to diverge. The study predicts that by 2022, average corn ethanol reduces GHG emissions by 43-60 percent compared to petroleum.

“The majority of unconventional fuel sources emit significantly more GHG emissions than both biofuels and conventional fossil fuel sources,” according to the study. “The biggest future impacts on the U.S. oil slate are expected to come from oil sands and fracking production.” In the absence of biofuels, “…significant quantities of marginal oil would be fed into U.S. refineries, generating corresponding emissions penalties that would be further aggravated in the absence of renewable fuel alternatives.”

The study also reveals several fundamental flaws with the GHG analysis conducted by the Environmental Protection Agency (EPA) for the expanded Renewable Fuel Standard (RFS2) regulations. Just one example: corn ethanol was already determined to reduce GHG emissions by 21 percent compared to gasoline in 2005, according to the analysis. Yet, the EPA’s analysis for the RFS2 assumes corn ethanol GHG reductions won’t reach 21 percent until 2022.

The EPA’s analysis also assumes the carbon intensity of crude oil will be the same in 2022 as it was in 2005, a presumption that has already been disproven by the real-world increase in the carbon intensity of crude oil. “As unconventional sources of crude oil have grown in recent years, the carbon intensity of petroleum fuels has increased above the baseline levels initially identified in the Renewable Fuel Standard…” according to the authors, who call on EPA to address several shortcomings with its analysis.
RFA President and CEO Bob Dinneen made the following comments on the results of the new study. “When it comes to ethanol’s carbon footprint, biofuel critics and some regulatory agencies are unfortunately stuck in the past. We don’t need to wait until 2022 for corn ethanol to deliver on its promise to reduce GHG emissions. This study uses the latest data and modeling tools to show that corn ethanol has significantly reduced GHG emissions from the transportation sector since enactment of the original RFS in 2005.”

“Further,” said Dinneen, “the report highlights that ethanol’s GHG performance will continue to improve and diverge with crude oil sources that will only get dirtier as time goes on. When ethanol is appropriately compared to the unconventional petroleum sources it is replacing at the margin, the GHG benefits are even more obvious. We urge EPA officials to closely examine this new information and make good on their commitment to ensure the RFS regulations are based on the latest data and best available science.”

Other key findings and recommendations from the study can be found here.

Posted on January 16, 2014 by Joanna Schroeder