Dear Chairwoman Nichols,

The Renewable Fuels Association (RFA) appreciates the opportunity to provide comment on the California Air Resources Board’s (CARB) Initial Statement of Reasons (ISOR) regarding re- adoption of the Low Carbon Fuel Standard (LCFS). While the proposal for re-adoption marks a slight improvement over the current regulation, we remain deeply concerned by several aspects of the proposal and believe it threatens the long-term durability of the LCFS program. Thus, RFA believes the ISOR needs significant revision before it can be presented to the Board for approval.

Grain-based ethanol has made a substantial contribution to LCFS compliance in the first four years of the program. Indeed, ethanol has accounted for 59% of total credits generated from 2011Q1 through 2014Q3, and 95% of the ethanol used for compliance has been grain-based ethanol, according to CARB reporting data. If not for the LCFS credits generated by grain-based ethanol, deficit generation would have certainly outpaced credits by now, and compliance with the program would be extremely difficult, if not impossible. Thus, it is not an exaggeration to state that the LCFS has endured so far only because of the contributions of grain ethanol. Yet, the ISOR proposes to continue punitive carbon intensity (CI) penalties for grain ethanol and other crop-based biofuels based on purported indirect land use change (ILUC) emissions. If finalized, the proposed re-adoption regulation will make the use of most grain ethanol infeasible for compliance as early as 2016. Why would CARB use flawed and prejudicial analysis to purposely diminish the compliance viability of the low-carbon fuel that has provided the largest volume of credits to date?

As the attached comments show, CARB’s ILUC analysis remains technically and methodologically flawed, and grossly overstates the land use impacts associated with biofuels expansion. A November publication by the Center for Agricultural and Rural Development (CARD) at Iowa State University makes a remarkably important contribution to the debate over ILUC modeling. The report marks the first time that actual land use changes over the past decade (i.e., the period in which commodity crop prices rose to record levels) have been quantified and discussed in the context of CARB’s ILUC modeling results. The CARD/ISU paper, which is discussed in detail in the attached comments, found that “[t]he pattern of recent land use changes suggests that existing estimates of greenhouse gas emissions caused by

land conversions due to biofuel production are too high because they are based on models that do not allow for increases in non-yield intensification of land use.” In essence, the authors found that the primary response of the world’s farmers to higher crop prices “…has been to use available land resources more efficiently rather than to expand the amount of land brought into production.”

The CARD/ISU research was submitted to CARB in early December. However, CARB’s ISOR fails to even mention or acknowledge the work in any way. For the first time, we have real-world data that provides important insight into actual market responses to increased biofuels demand and higher crop prices. As described in the attached comments, we believe CARB must take into account the new CARD/ISU research and use it to immediately re-calibrate the GTAP model.

We appreciate CARB’s consideration of our attached comments, which also address CA- GREET model revisions and assumptions used in CARB’s illustrative compliance scenarios. We welcome further dialog on this subject and look forward to responses to any of the comments offered in the attached document.


Geoff Cooper
Senior Vice President


The Renewable Fuels Association (RFA) offers the following comments in response to the California Air Resources Board’s (CARB) release of its Initial Statement of Reasons (ISOR) proposing re-adoption of the Low Carbon Fuel Standard (LCFS)

I. Indirect Land Use Change Analysis

CARB continues to rely on a fundamentally flawed approach to predicting indirect land use change (ILUC) that favors hypothetical modeling results over empirical data, real-world observations, and improved assessment methods.

Nearly six years have passed since CARB originally adopted the LCFS, which included carbon intensity (CI) penalties for certain biofuels for predicted ILUC. In the intervening years since the program was adopted, the scientific understanding of land use change has significantly progressed. Retrospective analyses of global agricultural land use have been conducted, actual market responses to increased demand and higher commodity prices have been observed and characterized, the reliability of predictive economic models has been improved, and new data has emerged to better guide certain modeling assumptions.

Yet, in spite of these advances in the science, CARB continues to rely on the narrow—and completely unsubstantiated—view that “[a] sufficiently large increase in biofuel demand in the U.S. would cause non-agricultural land to be converted to cropland both in the U.S. and in countries with agricultural trade relations with the U.S.”

CARB’s entire approach to ILUC is founded on the notion that farmers are limited to only two responses to increased demand for crops. While CARB recognizes four potential market responses to heightened demand for crops, its predictive modeling framework essentially allows only two of these responses to play out. The four potential market responses acknowledged by CARB are shown below.

  •   Response 1: “Grow more biofuel feedstock crops on existing crop land by reducing or eliminating crop rotations, fallow periods, and other practices which improve soil conditions”;
  •   Response 2: “Convert existing agricultural lands from food to fuel crop production”;
  •   Response 3: “Convert lands in non-agricultural uses to fuel crop production”; or
  •   Response 4: “Take steps to increase yields beyond that which would otherwise occur.”


CARB theorizes that there is essentially no crop yield response to increased demand (Response 4 above), and an artificially low elasticity value is used to reflect this belief in CARB’s economic model. Further, the CARB modeling framework does not allow double-cropping or reduction of fallow/idle cropland; thus, Response 1 above is also eliminated. As a result, CARB assumes increased demand for crops can only be met through displacement of animal feed and conversion of non-agricultural lands to crop production (Responses 2 and 3 above). Not coincidentally, Responses 2 and 3 have the most significant GHG impacts.

CARB has produced no evidence whatsoever that such land conversions have actually occurred on a meaningful scale in response to the LCFS or growth in U.S. biofuels demand. Indeed, empirical evidence suggests that demand growth has been primarily met through Responses 1 and 4 above, which are effectively excluded from CARB’s modeling framework.

Instead of tuning the modeling framework to reflect these observed market responses, CARB continues to rely on conjectural assumptions and model predictions to penalize biofuels for hypothetical market outcomes. In essence, CARB is using the exact same approach to estimating ILUC emissions that it used six years ago, making only minor adjustments to certain model parameters based on “judgment calls.”

RFA believes the principles of sound policymaking and regulation demand that CARB recognize and incorporate the best available science and data in the LCFS process, particularly when empirical data is available to fill important knowledge gaps.

a. A New Publication by Babcock & Iqbal Has Important Implications for CARB’s ILUC Analysis. CARB Should Give Serious Consideration to the Findings of the Paper, and Adjust its ILUC Estimation Methodology Accordingly

In mid-November, Babcock & Iqbal at the Center for Agricultural and Rural Development (CARD) published Staff Report 14-SR 109, “Using Recent Land Use Changes to Validate Land Use Change Models.”1 The paper (Attachment 1) makes a remarkably important contribution to the debate over ILUC modeling. The report marks the first time that actual global land use changes over the past decade (i.e., the period in which commodity crop prices rose to record levels) have been quantified and discussed in the context of CARB’s ILUC modeling results. The report was submitted to CARB staff in early December 2014, yet there is not a single mention of the paper (nor is there a response to its findings) in the ISOR.

Babcock & Iqbal examined historical global land use changes from 2004-2006 to 2010-2012 and determined that “…the primary land use change response of the world’s farmers from 2004

1 Babcock, B.A. and Z. Iqbal (2014), Using Recent Land Use Changes to Validate Land Use Change Models. Center for Agricultural and Rural Development Iowa State University Staff Report 14-SR 109. Available at:


to 2012 has been to use available land resources more efficiently rather than to expand the amount of land brought into production.”2 Among other important revelations, the paper shows that key regions where CARB’s GTAP analysis predicts biofuels-induced conversion of forest and grassland have actually experienced substantial losses of cropland.

Unfortunately, CARB’s GTAP analysis does not take into account the methods of intensification (e.g., double-cropping, increases in the share of planted area that is harvested, return of fallowed land to production) that have been observed in the real world over the past decade. According to Babcock & Iqbal, GTAP and other models “…do not capture intensive margin land use changes so they will tend to overstate land use change at the extensive margin and resulting emissions.”3 This finding is corroborated by Langeveld et al (2013) (Attachment 2), who found GTAP and other models have “…limited ability to incorporate changes in land use, notably cropping intensity,” and “[t]he increases in multiple cropping have often been overlooked and should be considered more fully in calculations of (indirect) land-use change (iLUC).”4

Ultimately, the Babcock & Iqbal work calls into question the plausibility of CARB’s GTAP results and demonstrates that CARB’s ILUC results are directionally inconsistent with real-world data and observed market behaviors in many regions. The data and discussion presented in the paper challenge the very underpinnings of CARB’s analysis and are simply too important for the agency to ignore. Thus, as described more fully in the comments below, we believe CARB should move immediately to calibrate its GTAP model using the real-world land use data made available by Babcock & Iqbal.

b. Countries and regions where cropland has decreased and/or forestland and grassland have increased over the past decade should be presumed to not have converted pasture or forest to crops in response to biofuel- induced higher prices. CARB should calibrate its GTAP model to reflect the absence of extensive land use change in these countries and regions.

At the outset, it is important to note that the lack of a “counterfactual case” to compare to the real-world data (i.e., the ceteris paribus principle) is not sufficient reason to ignore the Babcock & Iqbal results. CARB has stated that comparing GTAP results to real-world data is “not productive,” because it is not possible to compare real-world data to a counterfactual case in which biofuel expansion did not occur. Appendix I to the ISOR further states:

GTAP-BIO is not predicting the overall aggregate market trend—only the incremental contribution of a single factor to that trend. If GTAP- BIO projects reduced exports, for example, this should be understood to mean that exports will be lower than what they would have been in

2 Id, Executive Summary.
3 Id, Executive Summary. (emphasis added)
4 Langeveld, J. W.A., Dixon, J., van Keulen, H. and Quist-Wessel, P.M. F. (2014), Analyzing the effect of biofuel expansion on land use in major producing countries: evidence of increased multiple cropping. Biofuels, Bioprod. Bioref., 8: 49–58. doi: 10.1002/bbb.1432. (emphasis added)


the absence of the effect being modeled (increased ethanol production, in this case). It is the difference between predicting an absolute change and a relative change.5

This statement by CARB seems to misunderstand the recommendation from stakeholders to consider and integrate empirical data and observed outcomes into CARB’s modeling work. RFA and other stakeholders fully understand that CARB’s GTAP modeling exercise is meant to isolate only the impacts of biofuels expansion on land use. However, empirical data can be useful for checking the directional consistency and general reasonableness of model predictions. According to the Babcock & Iqbal, “…the historical record of land use changes can be used to provide insight into the types of land that were converted…”6

Comparing empirical land use data to GTAP predictions is particularly useful in regions where cropland has contracted over the past decade. That is, if cropland in a certain region decreased according to historical data, then there is no justification for asserting—as GTAP does—that biofuel expansion caused extensive margin conversion of natural forest and grassland in that region. In other words, if there was no cropland expansion resulting from biofuels expansion and all other factors combined (i.e., in aggregate), then there certainly is no rationale for arguing that biofuels expansion in isolation of other factors led to cropland expansion.

That is not to say, however, that biofuels expansion did not have an impact on land use in the region. Indeed, cropland may have contracted even more in a “world without biofuels” (i.e., the counterfactual case). In other words, some additional cropland might have gone out of production in the absence of biofuels, and the function of biofuels demand may have been to keep that cropland engaged in production. Thus, the appropriate question for regions that have experienced cropland contraction over the past decade is whether there was foregone sequestration because of biofuels—not whether there was extensive conversion of forest and grassland and soil carbon loss because of biofuels. According to Babcock & Iqbal:

The countries in Figure 8 that either had negligible or negative extensive land use changes should be presumed to not have converted pasture or forest to crops in response to biofuel-induced higher prices. Rather, the presumption should be that any predicted change in land used in agriculture came from cropland that did not go out of production.7

Figure 8 from Babcock & Iqbal is embedded below. Note that many countries and regions for which CARB’s latest GTAP analysis predicts extensive change from forest and grassland to crops actually showed cropland losses or no change. This includes Canada, EU, Japan, China, India, Russia, the U.S., and Oceania. Further, the amount of corn ethanol-induced conversion of

5 ISOR, Appendix I at I-20.
6 Babcock, B.A. and Z. Iqbal (2014) at executive summary. 7 Id. at 26.


forest and grassland in the U.S. predicted by CARB’s GTAP model is two to four times larger than the actual extensive land use change in the U.S. driven by all factors in aggregate.

According to Babcock & Iqbal, the land use emissions implications in countries and regions where cropland decreased or stayed the same are that:

…the type of land converted to accommodate biofuels was not forest or pastureland but rather cropland that did not go out of production. Calculation of foregone carbon sequestration depends on what would have happened to the cropland if it did not remain in crops which, in turn, depends on where the cropland is located and the potential alternative uses. The magnitude of the change in estimated CO2 emissions from cropland that is prevented from going out of production relative to forest that is converted to cropland is potentially large.8

Unfortunately, CARB’s GTAP analysis suggests there was conversion of forest and grassland to crops in regions where real-world data show cropland actually contracted. The disagreement

8 Id.


between GTAP predictions and real-world data highlights the implausibility of GTAP results for certain regions. CARB can—and should—correct its analysis to better align with real-world land use patterns. The following section provides a method for calibrating CARB’s GTAP model to better reflect observed land use changes.

c. CARB should use data from Babcock & Iqbal (2014) to immediately calibrate its GTAP model to reflect real-world land use change patterns in key regions.

As stated in the Babcock & Iqbal paper, CARB should not presume that higher crop prices have caused conversion of forest and grassland to crops in countries and regions where cropland has actually decreased over the past 10 years. Thus, we believe CARB should calibrate its GTAP model to disallow forest and grassland conversion in AEZs and regions for which empirical data show forest or grassland expansion and/or cropland contraction. This can be easily accomplished by excluding GTAP predicted land conversions for the countries in Figure 8 of Babcock & Iqbal that show negative extensive change (i.e., loss of cropland). A more detailed method for accomplishing this calibration is available in comments submitted to CARB by Air Improvement Resource on Dec. 4, 2014.9

It could be argued that these countries should still be subject to emissions penalties for foregone sequestration, in that biofuels demand may have caused some cropland to remain in production that may otherwise have transitioned to some other use. But this should only be done if it can be demonstrated that the alternative use of the land would have resulted in carbon sequestration that is greater than the sequestration achieved if the land remained engaged in crop production.

For the countries in Figure 8 that do show extensive land use change over the past 10 years, CARB can continue to rely on GTAP predictions, but should also conduct more intensive research to better understand the precipitating causes of land conversions at the extensive margin in those countries. For example, while Sub-Saharan Africa (excluding South Africa) shows significant extensive change over the past decade, it is likely unrelated to biofuels expansion in the U.S. According to Babcock & Iqbal, “The extent to which extensive expansion in African countries was caused by high world prices is likely small for the simple reason that higher world prices were not transmitted to growers in many African countries.”10

In the longer term, CARB should migrate to the soon-to-be-released dynamic version of GTAP that contains updated baseline economic data. Further, CARB should closely monitor efforts to validate and back-cast the new version of GTAP and be prepared to consider new results from these exercises.

d. CARB’s GTAP Analysis Should Adopt CA-GREET2.0 Assumptions for Co- products Displacement Rates

9 Air Improvement Resources comments available at: 10Babcock, B.A. and Z. Iqbal (2014) at 16.


The recently released CA-GREET2.0 model correctly assumes that distillers grains from ethanol production displace both corn and soybean meal in livestock and poultry rations.11 The total mass of corn, soybean meal, and urea displaced by 1 pound of distiller grains is 1.111 pounds. While this assumption has modest impacts for the direct emissions associated with corn ethanol’s lifecycle, the impacts on land use are significant. We have detailed these impacts in many previous comments to CARB, dating back to 2008.

Unfortunately, CARB’s GTAP analysis continues to assume 1 pound of distillers grains displaces only 1 pound of corn. This is problematic for at least two reasons: 1) CARB’s assumptions and boundary conditions for estimates of direct and indirect emissions should be consistent and uniform, 2) CARB’s current GTAP assumptions on distillers grains displacement are simply inconsistent with the reality of how distillers grains are fed.

We are fully aware that there is no simple method for setting displacement ratios in GTAP, as interactions amongst the various sectors in the model are characterized in terms of economic values (e.g., expenditures, receipts, etc.). However, the economic values representing ethanol co-products in CARB’s GTAP model are based on the 2004 database. Obviously, there have been significant changes in the distillers grains market since 2004; the ways in which these co- products are traded, priced, and fed have evolved dramatically. As we have discussed in previous comments to CARB, the agency can better reflect real-world feeding practices (i.e., some displacement of soybean meal) by adjusting the economic values associated with co- product trade in GTAP. RFA believes CARB must make this adjustment to ensure consistent boundaries and assumptions across its direct and indirect emissions analysis.

e. CARB Still Has Not Justified its Proposal to Use a Yield-Price Elasticity Value That is Lower than Recommended by Both Purdue and CARB’s Own Expert Work Group. CARB Should Use 0.25 as the Central Value, Not the Proposed Value of 0.185.

Despite new data and published scientific papers supporting the use of a range for YPE of 0.14- 0.53, CARB continues to propose using a range of 0.05-0.35. CARB staff has continued to ignore input from stakeholders, academia, and its own Expert Work Group on this parameter, instead relying on input from paid contractors at UC Davis and its own “expert judgment.”

In Appendix I, CARB states that “[a]n expert from UC Davis, contracted to conduct a review and statistical analysis of data from a few published studies also concluded that YPE values were small to zero.” Yet, it is quite clear from the brief (and somewhat unclear) report from the UC Davis contractor that the YPE response was examined only over the short term (i.e., 1-2 years).

This is inappropriate and scientifically indefensible, as demonstrated by previous stakeholder comments and remarks from Purdue University. For example, during the March 11 workshop on

11 The latest version of CA-GREET2.0 is available at: 7

ILUC, Purdue University Prof. Wally Tyner explained why it is inappropriate to include short-run estimates in the range used for CARB’s analysis, stating:

The yield-price elasticity is a medium-term elasticity…and we normally think of that as about 8 years. I personally think, and our group thinks, that any of those papers in the literature that represent one year are totally irrelevant to this. They may be fine for a one-year estimate, but a one-year estimate is totally irrelevant. Most of the short-term estimates are very low and most of the medium-term [estimates] were much higher—in the range of the 0.25 that we currently use.12

Tyner underscored this point again in a note to CARB following the March 11 workshop: “The yield to price elasticity does not measure changes over one crop year. In fact, any estimate done over one year would be totally inappropriate for GTAP and should be excluded from consideration in determining appropriate values for the parameter.”13

Babcock and other members of the Expert Work Group’s Elasticity Subgroup agreed that the use of a short-run elasticity is inappropriate for the purposes of CARB’s GTAP scenario runs:

…to the extent that existing studies provide reliable one-year estimates, they underestimate the long-run response of yields to price. There are sound theoretical reasons for believing that there are lags in the response to higher crop prices. Farmers have an incentive to adopt higher-yielding seed technologies and other management techniques with higher prices. Switching from one seed variety or technology such as seed-planting populations, may require more than a single season to accomplish. And there are likely five to 15 year lags involved in developing new seed varieties and new management techniques that may be only profitable under high prices.14

The Schlenker work, which has served as the basis of CARB’s use of inappropriately low YPE values, was critiqued by the EWG’s Elasticities Subgroup. The subgroup raised several concerns with the Schlenker data, none of which (to our knowledge) have been adequately addressed by CARB staff. In short, the Elasticities Subgroup found that, “[t]he Roberts and Schlenker (2010) results provide no evidence that there is not a price-yield relationship,

12 Audio of Prof. Tyner comments are available at: preliminary/. (emphasis added)
13 See Appendix B of March 11, 2014 RFA comments, available at: (emphasis added)

14 ARB Expert Work Group. 2011. “Final Recommendations from the Elasticity Values Subgroup.” Available at:


they just find evidence that any short-run price yield relationship is overwhelmed by variations in yields caused by weather.”15

f. The GTAP model’s inability to explicitly consider double-cropping further justifies the use of a higher range of price-yield elasticity values.

As explained by CARB’s EWG, “…higher prices give farmers a greater incentive to double crop.”16 Indeed, Babcock & Iqbal adds to the body of empirical evidence that double-cropping has significantly increased during the recent period of higher commodity prices (see also Babcock & Carriquiry17). Unfortunately, GTAP simulations do not explicitly allow increased demand for agricultural commodities to be satisfied through increased double-cropping. While we believe the best way to account for the impact of double-cropping is to calibrate the GTAP model to the Babcock & Iqbal data (as described in previous sections), and alternative method would be to raise the yield-price elasticity in regions where double-cropping is known to occur.

The EWG Elasticities Subgroup recommended that the price-yield elasticity parameter could be used to partially account for double-cropping responses. In its final report, the subgroup explained that “the reality of double cropping” by itself justified the use of a positive (i.e., non- zero) value for the price-yield elasticity.18 The subgroup recommended that “…for countries that have the opportunity to double crop, such as the U.S., Brazil, Argentina, and some Asian rice producing countries such as Thailand…an additional increment should be given to the price- yield elasticity.”19 To date, CARB staff has failed to account for increased double-cropping in its GTAP modeling scenarios. At a minimum, 0.25 should be used as an average value, and an additional increment of 0.1 should be added (total = 0.35) for regions where double-cropping is known to occur.

II. The New CA-GREET2.0 Model Marks a Major Improvement Over CA- GREET1.8b. However, Certain Improvements to CA-GREE2.0 Are Still Needed to Better Reflect the Direct Carbon Intensity of Ethanol Pathways

In general, RFA supports CARB’s decision to revise and update its CA-GREET model based on the Argonne National Laboratory GREET1_2013 model. We believe Argonne’s GREET1_2013 model contains a number of important improvements and updated inputs that more accurately reflect the current CI performance of corn ethanol and many other fuel pathways. Much has changed since CARB released the original CA-GREET model more than six years ago; ethanol and feedstock producers have rapidly adopted new technologies and practices that have significantly reduced the fuel’s lifecycle CI impacts. Thus, it is encouraging to see the CA-

15 Id. (emphasis added)
16 Id.
17 Babcock, B. A. and M. Carriquiry, 2010. “An Exploration of Certain Aspects of CARB’s Approach to Modeling Indirect Land Use from Expanded Biodiesel Production.” Center for Agricultural and Rural Development Iowa State University Staff Report 10-SR 105.
18 ARB Expert Work Group. 2011. “Final Recommendations from the Elasticity Values Subgroup.” Available at:
19 Id.


GREET model finally catching up to the actual state of the industry. However, we believe the CA-GREET2.0 model could be further improved by adopting the recommendations below.

a. CARB Should Reduce Denaturant Content in Fuel Ethanol to 2.49% to Reflect Real-World Conditions

In order to comply with Federal requirements, ethanol producers limit the denaturant content of commercial fuel ethanol to 2.49% or less. GREET1_2013, upon which CA-GREET2.0 is based, appropriately assumes denaturant content is 2%. However, Appendix C to the ISOR specifies that CA-GREET2.0 assumes the non-ethanol content of denatured fuel ethanol is 5.4%, with 2.5% being denaturant, 1% being water, 0.5% being methanol, and 1.4% being “other.” While denatured fuel ethanol does contain trace amounts of water (1% or less), methanol and “other” components are generally absent from the fuel or present in amounts below those specified by CARB. Further, CARB assumes that all non-ethanol constituents of denatured fuel ethanol— including water and “other”—have the same carbon intensity as CARBOB. This is an unsubstantiated and unfair assumption. CARB should fix the denaturant content at 2.49% and treat any remaining non-ethanol constituents (which would be mostly water) as having the same CI as the ethanol.

b. CARB Should Include the GREET1_2013 Default Value for Enteric Fermentation Impacts in the Corn Ethanol Pathway

For the CA-GREET2.0 model, CARB is proposing to exclude the GREET1_2013 credit for methane emissions reduction resulting from feeding DDGS. We strongly disagree with this proposal and CARB’s rationale for the exclusion. We recommend that CARB adopt the GREET1_2013 methane emissions reduction credit for use in CA-GREET2.0.

CARB states that an “expanded system boundary” would be required for inclusion of methane emission reductions resulting from feeding DDGS to livestock. This implies that CARB views methane emissions reductions as a potential indirect or consequential effect. It could be argued that reduced methane emissions from livestock are a direct effect of corn ethanol expansion (via increased DDGS feeding). Nonetheless, even if we accept the argument that methane emission reductions are an indirect effect, CARB has no defensible reason for excluding these emission reductions. That is because CARB already has expanded the boundary conditions for its corn ethanol pathways to include consequential/indirect effects such as purported land use changes. CARB has also proposed to include indirect emissions associated with irrigation constraints, and at one point CARB was considering inclusion of hypothetical emissions that would indirectly result from “holding food consumption constant.” Thus, CARB is proposing to include a number of potential indirect/consequential emissions sources in the corn ethanol lifecycle, but plans to selectively exclude potential emissions reductions (i.e., credits). This reflects inconsistent and asymmetrical boundary conditions (and possible bias) in CARB’s analysis of corn ethanol emissions.


III. CARB’s Compliance Scenario Assumptions Regarding the Availability of Sugarcane Ethanol and Related Credit Generation Seem Highly Implausible

CARB’s new compliance scenarios continue to grossly over-estimate the amount of imported sugar-derived ethanol that is likely to be available to the U.S. and California marketplace in the future. As a result, CARB adopts an overly optimistic view of potential LCFS credit generation in the 2015-2020 timeframe.

In Appendix B, CARB states that its sugarcane ethanol estimate is derived from the Food and Agricultural Policy Research Institute’s (FAPRI) World Agricultural Outlook. It should be noted that due to budget constraints, FAPRI has not produced a comprehensive World Agricultural Outlook report since 2011. It is unfathomable that CARB would rely on the 2011 FAPRI publication for its projections of sugarcane ethanol availability when more current projections are available from multiple sources.

Indeed, FAPRI itself continues to publish annual “Projections for Agricultural and Biofuel Markets.”20 These projections are published in March of every year. Much has changed in the Brazilian and world sugar and ethanol sectors since 2011, and FAPRI has since significantly revised its outlook for U.S. imports of sugarcane ethanol.

FAPRI’s 2014 projections include yearly estimates of U.S. ethanol imports through 2023. FAPRI projects that U.S. ethanol imports will average 182 mg per year in the 2015-2023 timeframe, with exports never exceeding 197 mg in any single year. Importantly, these projections include the effects of the California Low Carbon Fuel Standard. According to FAPRI:

  •   “Sugarcane ethanol imports from Brazil continue to decline in 2014 before leveling out.”
  •   “Lower RFS requirements for advanced biofuel could imply reduced ethanol imports.”
  •   “However, low-carbon fuel requirements in California provide some incentive forcontinued ethanol imports.”Thus, CARB’s current 2020 projections (Appendix B reference, high and low cases) of sugarcane- and molasses-based ethanol are roughly 6-13 times higher than FAPRI’s current outlook, which do take into the account the likely “pull” from the LCFS. Further, total ethanol imports to the entire United States (most of which were sugar-derived) were just 84 million gallons in 2014, compared to CARB’s compliance scenario assumption of 410-912 million gallons. In fact, CARB’s projection that California would receive 120 million gallons of sugar- related ethanol in 2014 is 42% larger than actual imports to the entire U.S. Of the 84 million gallons imported by the U.S., only 7.96 million gallons—or 9.5% of the U.S. total—entered through California ports. Thus, actual California imports in 2014 were equivalent to just 6.6% of the volume anticipated by CARB.

    20 2014 FAPRI Baseline available here:


Similarly, CARB’s projection that California will receive 510 million gallons of sugar-derived ethanol in 2020 compares to FAPRI’s projection that the entire U.S. will receive only 172 million gallons of sugar ethanol that year.

CARB has suggested that higher LCFS credit values could lure larger volumes of sugar ethanol to California than projected by FAPRI. However, empirical data from the past four years show no discernible relationship between credit values and sugarcane ethanol imports to California.21 It is also worth noting that Brazil is soon increasing its ethanol blend rate, which will further reduce the amount of sugarcane ethanol that is available to export.

CARB Projections of Sugar Ethanol Availability vs. FAPRI Projections and Actual

2,500 2,000 1,500 1,000


2014 2015 2016 2017 2018 2019 2020

CARB ISOR, U.S. Sugar Ethanol Imports, High Case

CARB ISOR, U.S. Sugar Ethanol Imports, Reference Case

CARB ISOR, U.S. Sugar Ethanol Imports, Low Case

CARB ISOR, California Share of U.S. Sugar Ethanol Imports

FAPRI (2014), U.S. Sugar Ethanol Imports

2014 Actual U.S. Ethanol Imports

We strongly recommend that CARB refine its estimates of sugar-related ethanol and use FAPRI’s latest projections of sugarcane ethanol availability when conducting its analysis of potential fuel availability.


Thank you for considering RFA’s comments on the ISOR for the re-adoption of the LCFS. We would be pleased to address any questions you may have regarding the contents of these comments or any other issues related to ethanol’s role in the LCFS.

21 See analysis of sugarcane ethanol import response to LCFS credit prices at:


Million Gallons


Babcock, B.A. and Z. Iqbal (2014), Using Recent Land Use Changes to Validate Land Use Change Models. Center for Agricultural and Rural Development Iowa State University Staff Report 14-SR 109.

Using Recent Land Use Changes to Validate Land Use Change Models

Bruce A. Babcock and Zabid Iqbal

Staff Report 14-SR 109

Center for Agricultural and Rural Development Iowa State University
Ames, Iowa 50011-1070

Bruce A. Babcock is Cargill Chair of Energy Economics, Department of Economics, Iowa State University, 468H Heady Hall, Ames, IA 50011. E-mail:

Zabid Iqbal is a graduate research assistant, Department of Economics, Iowa State University, 571 Heady Hall, Ames, IA 50011. E-mail:

This publication is available online on the CARD website: Permission is granted to reproduce this information with appropriate attribution to the author and the Center for Agricultural and Rural Development, Iowa State University, Ames, Iowa 50011-1070.

The authors gratefully acknowledge research support provided to Iowa State University by the Renewable Fuels Foundation and the Bioindustry Industry Center.

For questions or comments about the contents of this paper, please contact Bruce A. Babcock,

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August 5, 2015
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Oregon Clean Fuels Program
Air Quality Planner
Oregon Department of Environmental Quality
RE: Comments on July 27 CFP Advisory Committee Meeting