I haven’t seen any discussion around here about the new meta-model report on ethanol EROEI put out at Berkley by the name of “ERG Biofuel Analysis Meta-Model.” You can read about the model here http://rael.berkeley.edu/EBAMM/. NPR even did a segment with the author’s of the study so I figure we should take a look at it.
This study takes on Pimentel, Patzek, Shapouri, Graboski, de Oliveira, and Wang. For the low EROEI studies, they added a result from Graboski named “coproduct credits” measured in (MJ/L). Though these coproducts actually come as outputs of the ethanol process they argue that since they displace other energy sources that we should model them as inputs into the systems for the purposes of calculating EROEI. Using this displacement model does seem reasonable, though the values range anywhere from 1.86 as reported by Pimentel to Shapouri’s fantastic 7.97. As a default, if a model didn’t include coproducts then they used the Graboski’s 4.13 value, probably because of its proximity to the mean of the aforementioned range.
Since a lot of people give credit to the Patzek and Pimentel numbers on this site, I’ll report how those fared in this report. Patzek gets blasted pretty hard at UNDERSTATING the amount of energy inputs needed! However, because he doesn’t consider the coproducts, they feel he overstates the energy loss of corn ethanol. His reported NEV (MJ/L) of -5 becomes -1.6 when the “coproducts” gets added back in.
Pimentel gets accused of overstating the amount of energy needed to manufacture Nitrogen and of not adding his 1.86 “coproducts” factor back into the NEV calculations. Reducing the Nitrogen costs and adding back in the coproduct amount turns the -6.1 NEV into a -3.7 one.
So if you feel that Patzek and Pimentel have done the best job in their research on this subject, then nothing has changed for you. Both studies, even after correction, still show a negative Net Energy.
Now how did the “high” NEV studies fare? Shapouri’s NEV of 8.9 gets dropped to 8.0. Graboski’s 3.9 NEV gets dropped to a 3.1. Wang’s 6.9 gets dropped to 6.1. The only exception to this rule comes from de Oliviera’s study which didn’t consider coproducts as they felt that no good data for coproducts existed at the time of their study. EBAMM faithfully adds the Graboski 4.1 MJ/L factor back in to make the de Olivera number go from 1.6 to 4.8.
To put it simply, they raised the 3 lowest NEV studies and lowered the 3 highest studies. The 3 highest studies made errors in the amount of energy inputs needed. The 3 lowest didn’t include the coproducts as energy outputs of the system. We, the poor readers, don’t end up with any clearer idea of if the coproducts should be 1.9, 4.1, or 7.3 MJ/L. If we use the 7.3 value in all of the studies, then every one of the studies shows a positive Net Energy Value. If we use the 1.9 MJ/L factor found in Pimentel, we get no NEV greater than 4 for any of the studies and half of them at or less than 0.
Also, the studies range from 19 to 27 MJ/L of energy inputs for each L of output even after their corrections. Patzek and Pimentel have much higher agricultural energy costs 27,000 MJ/ha and 32,000 MJ/ha respectively. This contrasts greatly with Shapouri’s number of 18,000 MJ/ha. Patzek and Pimentel include labor transportation and Farm Machinery energy costs while Shapouri ignores them. One of these guys has it right, and one has it way wrong.
So wrapping it up, Net Energy Value ends up being in the eye of the beholder. None of the studies agree and all of them overstated their cases. The meta-study makes no real conclusions other than when asked “How much energy do we get from making Corn ethanol?” we can reply “Not much. Maybe none.”





