Effects of Ethanol on Vehicle Energy Efficiency and Implications on

Aug 4, 2014 - notion that ethanol decreases the fuel efficiency of vehicles.” “Fuel efficiency” ... current engines attain equivalent energy eff...
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Comment on “Effects of Ethanol on Vehicle Energy Efficiency and Implications on Ethanol Life-Cycle Greenhouse Gas Analysis”

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e commend Yan et al.1 for compiling and synthesizing a collection of literature that addresses the nuanced influence that blending ethanol into gasoline can have on the fuel economy of spark ignition (SI) engines, which affects the life-cycle GHG emissions of the blended fuel. As biofuel policies are often motivated by the goal of reducing petroleum demand, the proposed effective substitution ratio (ESR) is a simple metric for quantifying the petroleum fuel displacement value that alternative fuels currently do and potentially can offer. The authors collected, filtered, and analyzed a vast multidimensional array of data from dozens of different studies, with varying degrees of controls and transparent reporting of experimental conditions, for the purpose of drawing conclusions that may be generally applicable to the ESR of the U.S. fleet. However, we would like to draw attention to several major weaknesses within the paper by Yan et al., which relate to the authors’ assertion of novel energy-centric recommendations, decision to omit Brazilian engine studies, choice of statistical analyses, and interpretation of results. We conclude by providing an alternate interpretation of the results and expanding upon the authors’ recommendations for future work.

Additionally, it has been well-known since the 1930s that properly tuned SI engines can attain much greater thermal efficiency with ethanol-gasoline blends than with gasoline alone, despite ethanol’s lower volumetric and gravimetric energy density.4−7 Meanwhile, a novel contribution of their work, the ESR metric, is not mentioned in the abstract, rendering the abstract unrepresentative of their research.

2. OMISSION OF BRAZILIAN ENGINE RESEARCH The authors decided to compile “paired energy efficiency data from all known studies of existing SI-engine vehicles operating on ethanol/gasoline blends and pure gasoline,” which led the authors to eliminate all Brazilian studies on their list, instead of performing a separate but similar analysis with Brazilian data. This criterion is arbitrary, as the ESR metric could easily be adapted for Brazilian studies with E25 as the baseline (which is considered regular gasoline in Brazil). A modified Brazilian version of the ESR analysis could yield additional insights, and contextualize the authors’ gasoline-centric analysis, by determining the differentiable impact (if any) that higher blend levels have for flexible fuel vehicle (FFV) engines designed for E20−25. Even the authors state that, “the ESR values used for Brazilian vehicles are likely to be more realistic. . .”, but, because of this missed opportunity, we do not yet know. Some articles that could assist in estimating the ESR for ethanol-gasoline blends in Brazilian engines include Melo et al.,8,9 Amorim et al.,10 Costa and Sodré,11 and Szklo et al.12 Additionally, the authors’ suggestion that “for Brazil, dedicated ethanol vehicle could be feasible and beneficial. . .offering potentials to increase ESR compared with FFVs running on ethanol” may indicate a lack of knowledge of Brazil’s historical use of dedicated ethanol engines, which have existed since 1979 but were discontinued in 1998.13 FFVs were then introduced in 2003 in Brazil;13 while not operating optimally with pure ethanol, their engines have a higher compression ratio (CR) than most U.S. vehicles,10,14 and therefore should attain a higher ESR.

1. NOVELTY OF ENERGY-CENTRIC RECOMMENDATIONS In the abstract, the authors inaccurately refer to a “general notion that ethanol decreases the fuel efficiency of vehicles.” “Fuel efficiency” is not the proper term to describe this notion, as energy researchers use “efficiency” to describe useful output energy (e.g., work) provided per unit of input energy. We believe the authors should more appropriately mention the conventional wisdom that increasing ethanol blend levels decreases the “fuel economy” and “specific fuel consumption” of current vehicles. Furthermore, the authors state, “we argue that. . .vehicle efficiency should be evaluated based on energy rather than volume,” reflecting their suggestion in Section 4.4 that “[a] common metric for vehicle efficiency expressed in energy and distance such as km/MJ or MJ/km could therefore be highly beneficial for both policy makers and consumers.” Without belaboring their use of “efficiency”, this argument is not a novel conclusion from their work, as the functional unit used in many biofuel life-cycle studies and renewable fuel policies is fuel energy content and/or vehicle efficiency-adjusted travel distance.3 The more valuable purpose of this paper was to question a common assumption embedded in many LCA studiesthat current engines attain equivalent energy efficiency with various ethanol-gasoline blends, which is evident when fuels’ emission factors are expressed and compared per unit of energy (e.g., grams CO2-e/MJ-fuel). Indeed, this assumption is an oversimplification, as recent studies find that current vehicles (flexible fuel or not) tend to attain slightly greater thermal efficiency with higher ethanol blends,2,15 albeit without offering relationships that could be extrapolated to the entire fleet. © 2014 American Chemical Society

3. STATISTICAL INTERPRETATION OF RESULTS The authors’ statistical interpretation of their results is weak. No p-value or statement of statistical significance is mentioned at any point in the entire paper, leading the reader to wonder if there is any. The main linear model’s results depicted in Figure 1b shows a large amount of variance within groups and far less between groups, further raising doubts about the model’s statistical significance. The extremely low R-squared (5%) may not preclude the statistical significance of ethanol blend percentage on ESR, but it tells the reader that blend percentage is not the main story and other issues are far more important. The researchers, upon seeing this, should have attempted to find this missing variance. Published: August 4, 2014 9950

dx.doi.org/10.1021/es502495u | Environ. Sci. Technol. 2014, 48, 9950−9952

Environmental Science & Technology

Correspondence/Rebuttal

efficient injections systems do not noticeably benefit. Like the authors, we hope that future engine researchers publish more comprehensive characterizations of experimental variables, for example, properties of gasoline blendstock (e.g., heating value, octane) and engine system parameters (e.g., CR, combustion controls). However, we believe that fuels and existing engines are understood well enough to estimate an engine system’s response to changes in fuel properties, if known. Valuable policy insights may be gained by building an approximated inventory of each engine in the current fleet, to determine when and where increasing the marginal supply of ethanol (e.g., from E10 to E12 for conventional vehicles or to E50 for FFVs) could in theory reap the greatest energy savings. Such a project could consist of characterizing each engine type by annual fuel consumption, engine settings, and typical drive cycle conditions, and developing a model with each of these parameters (using existing engine test data) to estimate the ESR for each engine type and region as a function of blend level. If such a project is administered globally, ethanol may be found to produce a significantly greater ESR when consumed in developing regions of the globe where vehicle fleets have a higher prevalence of carbureted engines and/or are not subjected to regular emissions testing to ensure optimal ignition settings. We also offer comments on the authors’ policy discussion of increasing the octane of the bulk gasoline fuel supply (section 4.4). While a coordinated increase in fuel octane and engine compression ratios could improve future U.S. fleet-wide energy efficiency,15 the authors neglect to mention the indirect lifecycle benefits that ethanol already offers by enabling refiners to produce lower octane blendstocks. Just as refiners of the 1950s could utilize octane in preblended gasoline to adjust their dosage of tetraethyl lead (so as not to exceed “octane giveway” targets),16 today’s refiners exploit ethanol’s high octane to displace demand for octane enhancers that may have high embodied energy and/or toxicity. In spite of the shortcomings that we identified in this article, we are encouraged that researchers are pursuing such technical, labor-intensive, policy-relevant work. While LCA researchers are increasingly incorporating the economic consequences of commodity demand perturbations into their models, and justifiably so, Yan et al.’s article is an inspiring example of the type of technical inquiry that should be more common among those researching the life-cycle impacts of alternative fuels (and other goods and services). To offer credence to the political and economic relevance of the ESR metric, if the U.S. fleet were found to have an average ESR of 1.01 or greater, we estimate that the 50 billion liters of ethanol consumed in 2013 displaced at least 33.2 billion liters of gasoline (vs. 32.9 billion liters, if substitution was strictly proportional to lower heating value)− i.e., for every 1% increase in the fleet-average ESR, an annual savings of 300 million liters of gasoline (worth nearly $300 million) could be found in the U.S. alone. Given the magnitude of potential benefits from exploiting ethanol’s advantageous properties as a gasoline additive, there are likely many costeffective opportunities for governments and private companies to optimize society’s use of ethanol in the existing fuelinfrastructure-vehicle system.

First, since the study employs nested meta data (within and among studies), a dummy variable for each included study could have been included, which could account for much of the experimental variance and thereby enabling a much better Rsquared. The authors even note that “. . .five of the six ESR values higher than three. . .are derived from one study. . .” indicating a need to account for within-study correlation. The fact that the data is actually nested (or hierarchical) by study and was never mentioned as such, and the proper nested analysis never performed or shown to be statistically significant or not (for purposes of discounting the need for such a model), further brings the statistical value of the research into question. Second, a simple observation of this study’s results, as well as the results of several of the studies referenced in the paper, suggests there is a peak or optimal blend percentage located somewhere between the extremities. Yan et al. suggest in Figure 1b that E10 has a higher mean ESR than E5, E20, or E85− which, if had been shown to be statistically significant (which it was not), may suggest that U.S. vehicles currently make the most efficient use of ethanol when operating with the most commonly available blend level. This was an opportunity for a second order (quadratic) term to be introduced into the model, and by not doing so the authors did not fulfill a stated goal of this research to “explore whether there is an optimal blending level.” Again, the R-squared would have been improved using this standard technique. These statistical issues, along with the authors’ admission that they could not establish a utilitarian method to estimate the ESR, and could not definitively characterize the main contributions to ESR variance, renders the provided point estimates unusable. Third, the ESR and the relative change in vehicle energy efficiency results shown in Figure 1 are both outcomes calculated as ratios. This fact was not explained or discussed when interpreting the results. In section 4.1.2, the authors suggest that differences exist in the ability of various engine types (carbureted, indirect fuel injection, direct injection, FFVs) to take advantage of various ethanol blends, without offering a science-based explanation. The authors point out that carbureted engines showed the highest improvement when an ethanol blend was introduced over fuel injection and other engine technologies. However, as these results are ratios, this does not necessarily indicate that carburetors “better take advantage of” ethanol; rather, carburetors more likely waste less fuel energy with ethanol than without, as ethanol enables carburetor engines to run leaner (as the authors mention in Section 2). There was no discussion of the relative performance (between technologies) before ethanol addition or any indication in the language that the authors were aware that their interpretation perspective was not taking the ratio issue into account. Direct injection or flex fuel technologies showed negligible ESR improvement from ethanol addition (and possibly a reduction); this result is not unexpected, as these modern technologies are known to be relatively efficient already, largely due to better control of combustion stoichiometry than carbureted engines, but lacking the flexibility to fully exploit higher ethanol blends.

4. POLICY IMPLICATIONS AND FUTURE WORK Implications of this study might be better stated as inconclusive. Interpretation of the results point more to the notion that poorly performing SI engines (e.g., older vehicle engines that more frequently knock and/or run fuel-rich) could be improved greatly with ethanol addition, but that modern SI engines’

Bret Strogen*,† Simone Pereira Souza‡ Jeffrey R. Lidicker§

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dx.doi.org/10.1021/es502495u | Environ. Sci. Technol. 2014, 48, 9950−9952

Environmental Science & Technology

Correspondence/Rebuttal





number ethanol−gasoline blends: Quantifying the potential benefits in the United States. Fuel 2012, 97, 585−594. (16) Symonds, G. H. Linear programming solves gasoline refining and blending problems. Ind. Eng. Chem. 1956, 48, 394−401.

Energy Biosciences Institute; University of California, Berkeley, Berkeley, CA 94704, United States ‡ Mechanical Engineering School, University of Campinas, Brazilian Bioethanol Science and Technology Laboratory (CTBE), CNPEM/ABTLuS, Campinas, Brazil § Michigan Tech Transportation Institute, Michigan Technological University, Houghton, Michigan 49931, United States

AUTHOR INFORMATION

Corresponding Author

*Phone: 415-483-2738; e-mail: [email protected]. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS We thank the Energy Biosciences Institute at the University of California, Berkeley for partially funding this research. We also thank Dr. Márcio Turra de Á vila, Dr. Sam Saxena, and Henrique Pacini for their input on improving this manuscript.



REFERENCES

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dx.doi.org/10.1021/es502495u | Environ. Sci. Technol. 2014, 48, 9950−9952