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The smallprint of the RFS2 renewable fuel standard
As by volume the most relevant renewable fuel standard world wide, a closer look at the details of this regulation is worthwhile - to understand the issues behind decarbonization policies in transport. The RFS2 details that
“EPA is making threshold determinations based on a methodology that includes an analysis of the full lifecycle of various fuels, including emissions from international land-use changes resulting from increased biofuel demand. EPA has used the best available models for this purpose, and has incorporated many modifications to its proposed approach based on comments from the public, a formal peer review, and developing science. EPA has also quantified the uncertainty associated with significant components of its analyses, including important factors affecting GHG emissions associated with international land use change.”
Specific lifecycle GHG emission thresholds for each of four types of renewable fuels were established, requiring a percentage improvement compared to lifecycle GHG emissions for gasoline or diesel. One of these fuels, ethanol produced from corn starch produced at a new natural gas facility using advanced efficient technologies will meet the 20% reduction threshold compared to the 2005 gasoline baseline (says EPA). Other fuels meet the 50% or 60% benchmark.
While the life cycle methodology of the EPA if fairly comprehensive, a few important caveats were noted in a review of the RFS2 by Richard Plevin:
- EPA performs its analysis in a projected 2022 world, assuming a variety of technology changes. This is similar to accounting for today’s emissions from coal power plants as if they had implemented anticipated CCS technology. In 2012 all and in 2017 most corn ethanol pathways analyzed by the EPA do not meet the 20% GHG reduction requirement, or even produce greater GHG emissions than the gasoline baseline.
- In the EPA model corn ethanol achieves productivity gains without additional use of fertilizer. The peak of corn ethanol production is achieved in 2016 - inducing most ILUC - while productivity assumptions refer to 2022 with additional 9.4% crop yield. Hence, ILUC are systematically underestimated.
- EPA attributes large soil carbon sequestration to biodiesel, most likely for increased used of no-till. However, no-till may increase N2O emissions (Six et. al). There is uncertainty on this issue, but EPA treats net soil carbon sequestration as a fact.
- Cellulosic ethanol obtains a low GHG rating by co-product credits generated by electricity from biochemical cellulosic refineries that displaces the average US grid electricity. Taking the average US grid as benchmark is a courageous assumption. More detailed analysis could significantly change the life cycle emissions.
- An additional supply of biofuels reduces the world market price of petroleum, by this increasing its demand. In one study, the global petroleum effect is estimated to be around 27% implying that each MJ of biofuel replaces 0.73 MJ of petroleum (Stoft, 2009). Hence, biofuels that are less then 27% below gasoline baseline could have a net positive global warming effect. This effect is acknowledged but not modeled by EPA.
Interested readers should consult the detailed analysis of Richard Plevin (here). Most importantly perhaps is the treatment of uncertainty. EPA performs a basic uncertainty analysis. A number of uncertainties are completely ignored, most importantly the uncertainty about the fraction of land displaced by biofuels that must be replaced elsewhere and the assumed production period (Plevin et al., forthcoming). As a result, numbers are presented with relative certainty where epistemic uncertainty dominates. There are two additional important issues that go beyond pure carbon accounting. First, there is considerabe interaction between biofuel and food production. The EPA’s comprehensive analysis treats reduction in food consumption, e.g. in India and Africa, as a GHG benefit. Without these shift from food to fuel production, biodiesel from soybean would not meet the threshold. Second, the economic feasability of large scale cellulosic ethanol production is unclear. For example, target values for biodiesel have already been scaled down by more than 90% for 2010.
In summary, EPAs carbon accounting should be taken with some care. In particular, today’s corn ethanol may have higher than baseline gasoline GHG emissions (e.g., Hertel et al., 2010). By focussing on potential 2022 technologies, this emission disbenefit is insufficiently reflected. Some policy maker pressure the EPA with respect to corn ethanol, arguing that corn ethanol production decreases energy independence and produces jobs. However, from this perspective, pro-corn ethanol policies should be designed from the perspective of jobs and energy independence, rather than using the RSF2 as camouflage.
References
Hertel, T. W., A. Golub, et al. (2010). “Global Land Use and Greenhouse Gas Emissions Impacts of U.S. Maize Ethanol: Estimating Market-Mediated Responses.” BioScience 60(3): 223-231.
Plevin, R. J., M. O’Hare, et al. (forthcoming). The greenhouse gas emissions from market-mediated land use change are uncertain, but potentially much greater than previously estimated, UC Berkeley.
Six, J., S. M. Ogle, et al. (2004). “The potential to mitigate global warming with no-tillage management is only realized when practised in the long term.” Global Change Biology 10(2): 155-160.
Stoft, S. (2009). “The Global Rebound Effect Versus California’s Low-Carbon Fuel Standard”
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