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Technical Memorandum From: Robert Anderson, Environmental Protection Agency To: Docket EPA - HQ - OAR - 2009 - 0211 Date: 10/XX/2010 Subject: Technical Summary of DOE Study on E15 Impacts On Tier 2 Vehicles and Southwest Research Teardown Report The purpose of this technical memo randum is to : (1) outline in more detail the research study design of the recently completed Department of Energy (DOE) E0 and E15 catal ys t durability test program (DOE V4 program hereafter) ; (2) explain in more detail anal ys es that w ere used as a basis for the partial waiver decision evaluating the data obtained from the DOE V4 program ; (3) summarize the results of the engine teardown report that the Southwest Research Institute (SwRI) completed for DOE on several vehicles tested in D OE V4 program; and , (4) explain how non - methane organic gas (NMOG) emissions were estimated for use in the anal ys es for the partial waiver decision. 1 – Study Design – DOE V4 Program The DOE V4 program was established to investigate the potential impact s of gasoline ethanol blended fuels containing greater than 10 volume percent (vol%) on the durability o f vehicle emissions control sy stems. The program began with a subcontracted effort at Southwest Research Institute (SwRI) in San Antonio, Texas and was later expanded and accelerated by placing additional subcontracts to perform portions of the needed work at Transportation Research Center (TRC) in East Liberty, Ohio, and Environmental Testing Corporation (ETC) in Aurora, Colorado. The SwRIand TRC subc ontracts and technical work was managed by O ak Ridge National Laboratory ( ORNL), while the ETC subcontract and technical work was managed by

the National Renewable Energy L aboratory

(NREL). The scope - of

- work for each subcontract differed in some details ( such as the number of fuels being evaluated) but were generall y the same in terms of the methodology of the program. Vehicle Selection and Matching There were a number of relevant criteria that determined the selection of vehicle models for the program. These included whether a vehicle model was Tier - 2 compliant, manufacturer, sales/registration volumes, and whether a vehicle model did or did not apply learned fuel trim (LFT or non - LFT, respectively) at wide - open throttle (WOT). Several studies provided information that impacted selection: EPA’s EPACT vehicle study at SwRI, Coordinating Research Council’s (CRC) E87 - 1 study , and DOE’s previous 16 vehicle screening study . Based on the vehicle set EPA used to represent the Tier 2 fleet in its EPAct program, DOE instructed the national laboratories to use similar criteria in selecting a vehicle set for long - term durability studies. 1 The make and model of 18 of the 19 vehicles tested were identical to the makes and

1 EPA selected vehicles for its EPAct study based on several criteria. The Agency selected vehicles based on MY engine family sales data since ther e are usually multiple models to choose from for each engine family. Additionally, EPA focused on high volume sellers since, by definition, high volume sellers are representative and eases recruitment.Draft

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models of the 19 - vehicle EPAct test vehicl e fleet. However, at the request of CRC, DOE substituted the Nissan Quest for a To yota Sienna. DOE also choose to have the model years (MY) of the test fleet vehicles range from MY2005 - MY2009 instead of just using MY2008 vehicles that EPAct utilized. Additionally , the sample size and vehicle selection methodology of this program conforms to EPA guidance necessary to conduct a long - term durability test program. 2 Matched sets of vehicles were needed to accomplish the desired testing program. The vehicle sets were matched to prevent confounding of the data by undesirable vehicle attribute changes. Specificall y, the engine family , engine displacement, evaporative emissions control family , model year, powertrain control unit calibration, axle ratios, wheel size, and tire size were constrained to be identical within a vehicle set. Phy sical inspections of the vehicles to eliminate obvious problematic vehicles (such as those with gross fluid leaks, obvious and excessive body damage, etc) were also a part of th e selection of vehicles for the matched sets. Odometer reading was also used to identify

candidate pre - owned vehicles with the goal of restricting the range of odometer readings within a vehicle set to a maximum of 10,000 miles. O ne vehicle from each set was aged and tested on E0 and E15. 3

2 See EPA Docket #EPA - HQ - OAR - 2009 - 0211 - 2559.2, API Te chnology Committee Meeting, Chicago, 6/4/08. 3 The number of vehicles in a matched set varied during the test program according to the number of fuels being targeted for test. In some cases four ethanol blend levels were tested (E0, E10, E15, and E20), while in other cases a subset of these f

uels were tested. Since the waiver request is for E15, this analysis focuses on those vehicles that were aged on E15 compared to those vehicles that were aged on E0.Draft

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Table 1 . Vehicle attribute summary.Draft

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The assignment of a particular vehicle to a particular fuel was random and was accomplished prior to any emissions tests being conducted on the vehicles. Table 1 provides information on the test vehicles in the program. Obtaining suitable matched sets of vehicles was challenging for several of the older model ye ar vehicles in the program. For this reason, there were a few instances where it was necessary to compromise the 10,000 mile odometer range target in order to obtain an otherwise suitably- matched set of vehicles. Fuels and Blending The fuels used at the several test sites were obtained commercially by the subcontractors. In all cases, for both emissions certification and aging fuels, the ethanol - containing fuels were splash - blended. Emissions and related tests were conducted using emissions certification gasoline (E0) or E15 blended from emissions certification gasoline and denatured fuel - grad e ethanol. These batches were subsequently anal yz ed to provide the information necessary to conduct the program. These anal ys es included : the actual ethanol content of the batch ; carbon ; hydrogen and ox ygen fractions ; and, density . Whenever possible, l arge enough batches to complete the several phases of the program were produced to reduce potential batch - to - batch effects on the results of the program. Aging fuels were produced by blending denatured fuel - grade ethanol with gasoline (E0) commerciall y av ailable at retail stations , rather than emissions certification gasoline, in order to control cost s . (Many thousands of gallons of aging fuel were used in the program.) Batches of E15 used for vehicle aging were anal yz ed for assurance that they contained the correct amount of ethanol. The se fuels were not, in general, subjected to the same level of analy sis that was required for the emissi ons test fuels at these sites. Emissions Test Protocol The vehicles were subjected to an initial emissions test (Fe deral Test Procedure ( FTP ) ) to assure that they

were emissions - compliant before acceptance into the program. Once in the program, vehicles were subjected to emissions and related tests at the beginning of mileage accumulation, at least one mid - mileage poi nt (two points for vehicles at ETC), and at the end of mileage accumulation. At SwRI and TRC, the acceptance tests also included tests at wide - open throttle to aid in classifying the vehicles as either LFT or non - LFT vehicles. At each emissions test interval, duplicate FTP tests were conducted on each vehicle using both E15 and E0. (i.e. the E15 vehicle received duplicate FTPs on both E 15 and E0.) Wide - open throttle tests were also conducted at each emissions test interval with the same fuels as the FTP tests. The vehicles also underwent compression and leak - down checks on each engine cylinder at each emissions interval. For the pre - owned vehicles, the vehicles’ initial mileage was dictated by market availability

and varied considerabl y, with more recent model years having a lower mileage at the beginning of the program. Emissions test and mileage accumulation intervals are based on the highest odometer reading in a given vehicle set. The new cars typicall y had a few hundred milesDraft

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of difference from the highest to lowest odometer reading in a vehicle set. However, the used cars had larger differences, ty picall y several thousand miles. As an example, a set of vehicles with mileages of 32,000, 35,000, and 38,000 would experience end - of - program emission s tests as the highest mileage car reached 120,000 miles. Thus, the two remaining vehicles in the set would experience end - of

- program emissions tests at lower mileages (114,000 and 117,000 miles respectivel y.) Mid - aging test intervals were determined in the same way . In this way , the overall mileage accumulation experienced b y the vehicles in a given set was the same regardless of the fuel being used. This method was used because it allowed any fuel effects that were identified to be characterized based on equivalent mileage accumulation. This same procedure was used with new cars as well, though the mileage differences within a vehicle set are slight for these vehicles compared with those ty pical of the used car sets. Tier 2 compliant vehicles were driven up to their statutory full - useful life (120,000 miles). The initial mileages of the Tier 2 vehicles were about 50,000 or lower, meaning that these vehicles were driven approximately 70,000 - 120,000 miles during the program. Emissions intervals were d etermined based in part on the initial mileage of the vehicles. New cars were first subjected to aging to an odometer reading of 4,000 miles on retail E0 to stabilize the engine and emissions control sy stems, followed by the emissions test for acceptance into the program and the initial emissions test sequence. Following these tests, these cars were subjected to mileage accumulation until approximately 60,000 miles on the odometer, at which point the first mid - aging emissions tests were conducted. This cycle was then repeated at approximately 90,000 miles for the vehicles under test at ETC for a second mid - aging emissions test series. At TRC and SwRI , the 90,000 mile emissions tests were not conducted. End - of - aging tests were conducted for all new vehi cles at odometer readings of 120,000 miles. Pre - owned vehicles were similarly subjected to initial acceptance tests, then initial emissions tests, followed by mileage accumulation. Vehicle sets with nominally less than 70,000 miles at the start of the program were subjected to mid - aging emissions tests at 95,000 miles, followed b y end - of

- aging tests at 120,000 miles. Vehicle sets with nominally more than 70,000 miles were driven 25,000 miles prior to the mid - aging emission test and an additional 25,000 miles to the end - of

- program emissions tests. An exception to this schedule was the Nissan Quest, for which the mid - aging emissions tests were dropped from the program at DOE’s direction to accelerate completion of the program for this vehicle model. Mileage Accumulation The standard road cycle (SRC) was used for all aging. The SRC is the official EPA driving cycle used for aging in the whole vehicle exhaust durability procedure. This is a recommended EPA procedure that the manufacturers regularl y use f or verifying full useful life emissions capability . It has an average speed of 46.3 miles per hour (mph) and a maximum of 75 mph. The Nissan Quest aging was changed part way through aging to a series of steady speed laps on the test track at TRC at the D OE’s direction to accelerate completion of this vehicle set. Vehicles under test at TRC were aged using a closed test track. At this site, drivers followed the SRC as they drove the vehicles around the track. (Signs were installed at variousDraft

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locations around the track to assist the drivers in following the SRC protocol.) At ETC and SwRI , the mileage accumulation was accomplished by using mileage accumulation dy namometers (MADs). When a MAD is used, a mechanical actuator is used to manipulate the accelerator pedal and allow the vehicle to accelerate and decelerate to match the desired driving profile. Some mileage accumulation at ETC was also conducted on emissions certification dy namometers when sufficient MAD capacity was not available. During mileag e accumulation, the subcontractor s followed manufacturer guidelines for scheduled maintenance on each vehicle. Oil changes were scheduled so that they did not occur less than 500 miles prior to any emissions tests. 2 – DOE V4 Waiver Analysis Battelle Memorial Institute ( Battelle ) acted as a data collection, dissemination, and anal ys is center for all three test sites under contract to ORNL . Battelle provided the data that were used in our analy ses. These data included the emissions test results broken d own b y bag and calculated composite values (computed according to 40 CFR 86. 144 - 94 ) . These data included CO, NOx, and NMOG results; however, the NMOG values used for these anal ys es are estimated NMOG results that were necessary due to limitations of measurement equipment at two of the three labs. Part 4 of this technical memo has an in - depth discussion about the background and method used for the estimated NMOG calculations. Table 1 shows average FTP composite emissions results for NOx, CO, and estimat ed NMOG for E0 and E15 vehicles tested on the fuel the vehicle would be aged on (i.e. the vehicle to be aged on E15’s test results on E15) at the beginning of testing. Table 2 shows the average FTP composite emissions results for the end of program testin g (i.e. full useful life mileage accumulation testing). Table 1. Start of Testing Average FTP Composite Emissions Test Results. 4 CO Nox Est. NMOG Vehicles E0 E15 E0 E15 E0 E15 Accord 0.22 0.12 0.017 0.014 0.031 0.018 Altima 0.46 0.38 0.030 0.023 0.0 66 0.050 Caliber 1.02 0.66 0.035 0.030 0.054 0.046 Camry 0.15 0.15 0.019 0.039 0.019 0.032 Caravan 1.61 1.16 0.052 0.024 0.044 0.041 Civic 0.52 0.23 0.007 0.024 0.026 0.019 Cobalt 0.62 0.49 0.035 0.027 0.039 0.041 Corolla 0.42 0.33 0.021 0.019 0.034 0.032 Explorer 1.06 1.00 0.010 0.009 0.051 0.051 F150 1.42 1.42 0.038 0.030 0.046 0.065 4 The average differences in these results are not statistically significant (directional paired t- test, 90% confidence level or Sign Test) for NOx and estimated NMOG. CO results were statistically significantly lower ( p= .018) for E15 when compared to E0 at the 90% confidence level for the paired t- test . It should be noted that these analyses do not take into account the differences that arise from vehicle - to - vehicle variation within a specific vehicle model. These analyses were not conducted for FUL test data since aging effects may impact the results.Draft

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– Internal Use Only Page 7 of 19 Focus 0.56 0.41 0.007 0.006 0.042 0.024 Impala 1.00 0.91 0.037 0.023 0.044 0.038 Liberty 0.86 0.78 0.011 0.007 0.049 0.053 Ody ssey 0.23 0.18 0.009 0.010 0.021 0.0 25 Outlook 0.25 0.27 0.011 0.010 0.026 0.030 Quest 0.70 0.023 0.074 Silverado 0.60 0.76 0.027 0.027 0.044 0.044 Taurus 0.55 0.30 0.003 0.002 0.026 0.016 Tundra 0.69 0.88 0.020 0.029 0.048 0.072 Average 0.68 0.59 0.021 0.020 0.040 0.041 *Note: The E0 Nissan Quest data are omitted since the E0 vehicle failed to complete the test program **Note: E0 and E15 results are on different vehicles, so emission differences are due to both fuel and vehicle differences. Table 2. End of testing Average FTP Composite Emissions Test Results CO Nox Est. NMOG Vehicle E0 E15 E0 E15 E0 E15 Accord 0.23 0.13 0.026 0.024 0.048 0.018 Altima 3.18 0.62 0.067 0.053 0.135 0.055 Caliber 2.60 3.61 0.078 0.059 0.083 0.077 Camry 0.29 0.25 0.053 0.052 0.032 0.035 Caravan 1.67 1.12 0.051 0.047 0.048 0.038 Civic 0.57 0.33 0.027 0.043 0.040 0.033 Cobalt 0.87 0.47 0.042 0.027 0.039 0.039 Corolla 0.55 0.57 0.061 0.047 0.048 0.053 Explorer 1.23 1.04 0.033 0.028 0.060 0.059 F150 3.25 2.23 0.078 0.060 0.077 0.090 Focus 1.1 0 0.67 0.113 0.062 0.032 0.028 Impala 1.13 1.44 0.038 0.039 0.040 0.047 Liberty 0.99 1.16 0.052 0.045 0.045 0.045 Ody ssey 0.60 0.20 0.074 0.039 0.051 0.028 Outlook 1.34 0.43 0.047 0.016 0.049 0.034 Quest 1.02 0.040 0.069 Silverado 0.54 0.76 0.0 32 0.035 0.048 0.056 Taurus 0.53 0.45 0.010 0.013 0.029 0.028 Tundra 0.80 0.94 0.042 0.035 0.052 0.055 Average 1.19 0.92 0.051 0.040 0.053 0.047 *Note: The E0 Nissan Quest data are omitted since the E0 vehicle failed to complete the test program **Note : E0 and E15 results are on different vehicles, so emission differences are due to both fuel and vehicle differences. The first question EPA attempts to answer when evaluating fuel waivers is whether the new fuel or fuel additive cause a vehicle to exceed full useful life emissions standards . With theDraft

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data collected from Battelle for all Tier 2 motor vehicles, the Agency compared the average composite emission levels for each vehicle tested on E0 and E15 to the applicable Tier 2 full useful life exhaust emissions standard. Based on historical anal ys es used to evaluate previous waivers, we treated these data as binomial data on whether a vehicle had passed or failed applicable Tier 2 full useful life standards. Vehicles that had emissions level greater th an the applicable Tier 2 full useful life exhaust emissions standard were treated as a failure. 5 We then conducted several anal ys es that are broken down into two distant ty pes: (1) anal ys es that compare the pass/fail performance of the E0 and E15 vehicle test groups and (2) anal ys es that compared the groups independentl y to an “ anticipated failure rate.” In the past, the Agency

has generally

performed analy ses for fuel or fuel additive waiver requests evaluating two questions. The second question EPA l ooks at to evaluate a fuel waiver is whether the new fuel or fuel additive cause an adverse effect on the emissions of regulated pollutants that might contribute to vehicles exceeding their standards over their full useful life? For this we assessed the r ate of emission deterioration of these vehicles operating on E15 in comparison to those operating on E10 to determine any statistically significant differences. Further elaboration of statistical methods and results are discussed below. Pass/Fail Analys es Comparing E0 and E15 W e conducted two kinds of statistical anal ys es that either compared the pass/fail performance of the E15 vehicle test group to E0 vehicle test group or that compared the E15 and E0 test group separatel y to an anticipated failure r ate. 6 Table 2 shows how the Tier 2 vehicles that were aged on E0 performed when tested after FUL mileage accumulation relative to the applicable Tier 2 exhaust emissions standard while Table 3 shows how the Tier 2 vehicles performed on E15. Table 2. E0 FUL Results Compared to Tier 2 Standards Year Model LFT@WOT Nox NMOG CO 2007 Accord N Pass Pass Pass 2006 Silverado Y Pass Pass Pass 2008 Altima N Pass Fail Pass 2008 Taurus Y Pass Pass Pass 2007 Caravan N Pass Pass Pass 2006 Cobalt N Pass Pass Pas s 2007 Caliber N Fail Pass Pass 2009 Civic N Pass Pass Pass 5 These values assumed the applicable rounding procedures for certification as outlined in 40 CFR 86 . 1838 - 01 . 6 In previous waivers, the Agency has conducted analyses that compared the failure rates of test vehicle fleets to an expected failure rate.Draft

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2009 Explorer Y Pass Pass Pass 2009 Corolla Y Pass Pass Pass 2009 Liberty N Pass Pass Pass 2005 Tundra Y Pass Pass Pass 2006 Impala Y Pass Pass Pass 2005 F150 Y Pass Pass Pass 2006 Quest N N/A N/A N/A 2009 Outlook Y Pass Pass Pass 2009 Camry Y Pass Pass Pass 2009 Focus Y Fail Pass Pass 2009 Ody ssey N Pass* Pass Pass *Denotes that average of emissions tests were below applicable FUL standard, but had at least one test value above the a pplicable FUL standard. Table 3. E15 FUL Results Compared to Tier 2 Standards Year Model LFT@WOT Nox NMOG CO 2007 Accord N Pass Pass Pass 2006 Silverado Y Pass Pass Pass 2008 Altima N Pass Pass Pass 2008 Taurus Y Pass Pass Pass 2007 Caravan N Pass P ass Pass 2006 Cobalt N Pass Pass Pass 2007 Caliber N Pass Pass Pass 2009 Civic N Pass Pass Pass 2009 Explorer Y Pass Pass Pass 2009 Corolla Y Pass Pass Pass 2009 Liberty N Pass Pass Pass 2005 Tundra Y Pass Pass Pass 2006 Impala Y Pass Pass Pass 20 05 F150 Y Pass Pass Pass 2006 Quest N Pass Pass Pass 2009 Outlook Y Pass Pass Pass 2009 Camry Y Pass Pass Pass 2009 Focus Y Fail Pass PassDraft

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2009 Ody ssey N Pass Pass Pass First, the Agency

compared the two groups using Fisher’s Exact Test. Fisher's exact test is a statistical test used to determine if there are nonrandom associations between two categorical variables like the pass/fail binomial data across two test groups that we are looking at in this program. 7 Table 4 is a 2 X 2 contingency table tabulating the results of this analy sis test program for NOx. Since the E15 vehicle test group performed similarl y to the E0 test group, we cannot reject the hypothesis that the two vehicle test groups had different results. Since E15 performed better f

or CO and estimated NMOG, the results for those pollutants are similar for NOx. It should also be noted that since the test subjects in this test are assumed to be independent, the Nissan Quest that completed testing on E15 was included in the anal ys is. However, its inclusion does not impact the results. 8 Ultimately , concerning direct comparisons of the pass/fail performance of the E0 and E15 vehicle groups, it is unlikely that any statistical anal ys is comparing the proportion of vehicles that failed in each group would show that E15 performed worse than E0. This is due to the fact that either fewer vehicles failed for a particular pollutant (e.g. NMOG and NOx) on E15 compared to E0 or that the two groups performed identically

(e.g. CO). Table 4. Fisher 's Exact Probability Test for NOx Pass Fail Total E0 16 2 18 E15 18 1 19 Total 35 2 37 p = 0.374 The Agency

also decided to compare the failure rate of the E15 group independently to an assumed “anticipated failure rate.” Vehicle testing experience has shown that various factors, such as testing variability and differences in vehicle performance across models lead to a small number of anticipated emissions failures across the national fleet. For purposes of assessment in this waiver, we det ermined our anticipated failure rate experienced in the In - use Verification Program (IUVP). We use this anticipated failure rate to conduct a binomial test to evaluate the hy pothesis of whether E15 had a higher failure rate than the anticipated failure rate of 5% for each pollutant with a 90% confidence level. The binomial test is an exact test of the statistical significance of deviations from a theoreticall y expected distribution of observations into two categories (in this case pass/fail). 9 If E15 had no effect on the proportion of vehicles expected to fail, the number of vehicles should be approximately 5%. In this case, the low number of 7 F or a more formal discussion of Fischer’s Exact Test see S. Siegel, Nonparametric Statistics, New York: McGraw Hill, 1956: 96. 8 With sufficient sample sizes, analyses using more continuous distributions may be used. However, given the low sample size in this case, it is reasonable to use Fisher’s exact test in lieu of those methods. Additionally, given the similar performance of the E0 and E15 vehicle test groups, it is unlikely that any such methods would demonstrate the E15 group performed worse than th e E0 group for Tier 2 vehicles when looking strictly at whether vehicles passed or failed FUL certification standards. 9 For a more formal discussion of the binomial test see M. Hollander and D. Wolfe, Nonparametric Statistical Methods , 2 nd , New

York: Wile y - Interscience, 1999: 20.Draft

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vehicles aged on E15 that failed to meet the emissions standards at the end of the test program indicates that w e cannot reject the hypothesis that the rate of failure experienced in the test program was greater than 5% for NOx, CO, and estimated NMOG ( p= 0.245 for NOx, p =0.623 for estimated NMOG, and p= 0.623 for CO). Therefore, we cannot conclude that E15 caused a significant number of vehicles to fail meet their emissions standards when compared to the failure rate experienced as part of the IUVP test program. 10 Emission Deterioration with E0 and E15 blends We performed a statistical anal ys is of the data from th e DOE catal ys t durability test program in order to assess whether the emission deterioration rates were any different between the matched pairs of vehicle aged to full useful life mileage on E0 and E15 respectivel y. Since 1) not all vehicles started the t est program with the same mileage, and 2) deterioration over time, particularl y at low mileage, is extremel y nonlinear, it was necessary to normalize the data by excluding mileage points less than nominally 10,000 miles. Since the E0 Nissan Quest was not able to complete the program, the E15 Nissan Quest could not be included in this deterioration anal ys is. We chose a statistical model in the SPSSTM suite of statistical software for this analy sis which had the following characteristics: 1) Utilized the natural logarithm of emissions, 2) Was linear in nature, 3) Allowed each individual vehicle to have its own base emission level, 4) Allowed each matched set of vehicles (i.e., the two F150’s) to have a unique rate of emissions deterioration aside from an effect of ethanol blend percentage, and 5) Allowed a single offset to the emission deterioration rate of all the vehicles to represent the impact of E15, in order to determine the average impact of E15 on emission deterioration. The decision to anal yz e the natural logarithm of emissions, as opposed to emissions, was due to the range of base emissions observed across the test vehicles. NOx emissions at the lowest mileages tested varied by a factor of twelve, while NMOG emissions varied by a factor of four. An analy sis o f deterioration of absolute emissions in terms of g/mi would have placed great weight on those vehicles with the highest base emissions and essentially ignored those with the lowest emission levels. In contrast, an anal ys is of the natural logarithm of emi ssions essentially

measures deterioration in terms of the percent of base emissions. Thus, each vehicle is provided roughly

equal weight in this ty

pe of analy sis. This approach is also consistent with those used in EPA’s analy ses of emission data in its development of both the Complex Model and the EPA Predictive Models. The decision to utilize a linear model was necessary due to the fact that we only had emission data at two mileage points for a number of the test vehicles. Also, extensive experienc e with emission deterioration has demonstrated that such deterioration tends to be linear in nature once the catal ys t is past its “green” stage and in the absence of some type of component failure. 10 Using the binomial test for 19 vehicles compared to an expected probability of 0.05, two vehicles would have had to have failed for E15 to fail this test.Draft

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As will be seen below, it is difficult to discern a stati stically significant difference between a simple, linear deterioration rate. Discerning statistically significant difference between non linear rates would be even more difficult. Vehicles of different model ty pes obviousl y have different emission level s, as described above. However, even within a matched pair of vehicles of the same model ty pe, base emissions vary for two reasons. One, no two vehicles’ components are exactly the same and manufacturing variability

exists, as well. Also, the pre - owned vehicles which were part of the test program were driven differentl y prior to their purchase for the program. Thus, the degree of emission deterioration upon entrance into the test program were likel y different. For example, eight of the E0 - aged vehicles had lower base NMOG emissions than it s matching E15 - aged vehicle, while eight had higher base NMOG emissions. Two, the other reason that the emissions of matched vehicles differ is the immediate impact of ethanol blend percentage on emissions, any effect on emission deterioration aside. These two effects (vehicle to vehicle and fuel) cannot be separated in this ty pe of test program, since different vehicles had to be used for aging on the different ethanol blends. Thus, deterioration in emissions must b e determined primarily using each individual vehicle’s data (i.e., relative to each vehicle’s baseline emission level). 11 We took a slightly

different approach towards emission deterioration rate. In our statistical model, we allowed each group of identical vehicle models, but not each individual vehicle, to have its own rate of emissions deterioration. Like base emissions, individual vehicle’s emission deterioration rates can differ. They will differ more across vehicle ty pe and model than they

will between ostensibl y identical vehicles (i.e., those of the same make and model). (In this data set, average deterioration rates can vary by an order of magnitude between different model types.) Still, the emissions from even identical vehicles will tend to deteriorate at different rates. However, we could not allow each vehicle in the modeling to have its own deterioration rate, as we would then have no comparison left upon which to base the effect of ethanol blend content on deterioration. Therefore, w e essentiall y assumed that any differences in the underlying emission deterioration rate between vehicles within a model ty pe would average out across the test program. The fact that all vehicles were aged using the same durability driving cycles during the program supports this assumption. The net result was a statistical model with the following variables: A coefficient for each vehicle (treating the two vehicles of the same model ty pe as individual vehicles with independent coefficients) A coefficient for each model ty pe b y the number of miles it had been aged on either E0 or E15 (this mileage was almost alway s identical for the two blends) A coefficient for the number of miles any vehicle had been aged on E15 This last coefficient was not vehicle sp ecific and therefore represents the overall impact of E15 on emission deterioration relative to E0. Tables 2, 3, and 4 present the specific 11 The instantaneous exhaust emissions impact of E15 compared to E0 is dis cussed in great detail in section IV.? of the waiver document.Draft

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coefficients of the linear models developed for the natural logarithm of NOx, NMOG and CO emissions, respectivel y. Table 2. Model of NOx Emission Deterioration Base Emission Level (ln(emissions(g/mi)) Model Ty pe Deterioration Rate (change in ln(emissions(g/mi)) per 1000 miles Vehicle Model EO E15 2007 Honda Accord - 3.978 - 4.108 0.003273 2008 Nissan Altima - 3.4 09 - 3.69 0.006937 2007 Dodge Caliber - 3.314 - 3.674 0.009208 2009 Toyota Camry - 3.769 - 3.882 0.007135 2007 Dodge Caravan - 3.228 - 3.631 0.004621 2009 Honda Civic - 3.915 - 3.707 0.003623 2006 Chevrolet Cobalt - 3.248 - 3.827 0.004818 2009 Toyota Corolla - 3 .068 - 3.402 0.001796 2009 Ford Explorer - 3.540 - 3.948 0.001839 2005 Ford F150 - 3.452 - 3.66 0.01195 2009 Ford Focus - 3.320 - 3.836 0.008952 2006 Chevrolet Impala - 3.061 - 3.399 - 0.00308 2009 Jeep Liberty - 3.943 - 4.241 0.008561 2009 Honda Odys sey - 3.306 - 4.049 0.006325 2009 Saturn Outlook - 3.749 - 4.732 0.005077 2006 Chevrolet Silverado - 3.566 - 3.631 0.003667 2008 Ford Taurus - 5.994 - 5.776 0.01569 2005 Toyota Tundra - 3.685 - 3.704 0.006862 Change in Deterioration Rate due to E15 aging 0.00125

Table 3. Model of NMOG Emission Deterioration Base Emission Level (ln(emissions(g/mi)) Model Ty pe Deterioration Rate (change in ln(emissions(g/mi)) per 1000 miles Vehicle Model EO E15 2007 Honda Accord - 3.348 - 3.861 0.002422 2008 Nissan Altima - 2.6 60 - 3.019 0.003436 2007 Dodge Caliber - 2.946 - 2.992 0.007783 2009 Toyota Camry - 3.508 - 3.398 0.000817 2007 Dodge Caravan - 3.110 - 3.233 0.001839 2009 Honda Civic - 3.451 - 3.604 0.001919Draft

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2006 Chevrolet Cobalt - 3.340 - 3.166 0.000669 2009 Toyota Corolla - 2.837 - 2.548 - 0.00172 2009 Ford Explorer - 3.106 - 2.979 0.002885 2005 Ford F150 - 3.004 - 2.799 0.007143 2009 Ford Focus - 3.510 - 3.305 - 0.00129 2006 Chevrolet Impala - 3.229 - 3.194 0.000973 2009 Jeep Liberty - 2.851 - 2.533 - 0.00299 2009 Honda Odys sey - 3.4 78 - 3.85 0.0034 2009 Saturn Outlook - 3.115 - 3.332 0.000658 2006 Chevrolet Silverado 0.082 - 3.058 0.003436 2008 Ford Taurus - 3.825 - 3.996 0.002629 2005 Toyota Tundra - 3.095 - 2.898 0.002404 Change in Deterioration Rate due to E15 aging - 0.00114 Table 4. Model of CO Emission Deterioration Base Emission Level (ln(emissions(g/mi)) Model Ty pe Deterioration Rate (change in ln(emissions(g/mi)) per 1000 miles Vehicle Model EO E15 2007 Honda Accord - 3.377 - 3.99 0.002451 2008 Nissan Altima - 2.68 9 - 3.163 0.003453 2007 Dodge Caliber - 2.979 - 3.133 0.007827 2009 Toyota Camry - 3.531 - 3.539 0.00077 2007 Dodge Caravan - 3.140 - 3.373 0.001829 2009 Honda Civic - 3.471 - 3.741 0.001832 2006 Chevrolet Cobalt - 3.367 - 3.303 0.000645 2009 Toyota Corolla - 2. 868 - 2.69 - 0.00175 2009 Ford Explorer - 3.126 - 3.114 0.002829 2005 Ford F150 - 3.032 - 2.937 0.007082 2009 Ford Focus - 3.545 - 3.456 - 0.00117 2006 Chevrolet Impala - 3.256 - 3.337 0.000987 2009 Jeep Liberty - 2.879 - 2.667 - 0.00306 2009 Honda Odys sey - 3.511 - 4.001 0.003464 2009 Saturn Outlook - 3.147 - 3.481 0.000698 2006 Chevrolet Silverado 0.081 - 3.197 0.00343 2008 Ford Taurus - 3.856 - 4.12 0.002521 2005 Toyota Tundra - 3.123 - 3.036 0.002376 Change in Deterioration Rate due to E15 aging - 0.00109Draft

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Table 5 summarizes the average emission deterioration rates on the E0 and E15 blends. The average emission deterioration rate for the E0 blend is the average of the vehicle specific deterioration rates shown in Tables 2, 3, and 4 above, respectivel y, for NOx, NMOG and CO emissions. The average emission deterioration rate for the E15 blend is the average deterioration rate for the E0 blend plus the change in deterioration rate to due to E15 aging shown in these same tables. Table 2. Emission Deteriorati on on E0 and E15 Blends (ln(emissions per 1000 miles) NOx NMOG CO E0 deterioration rate 0.0060 0.0020 0.0020 E15 deterioration rate 0.0072 0.0009 0.0009 The results of the statistical anal ys is shown in Table 5 indicate that the rate of deterioration in NMOG and CO emissions decreased slightly on average, while that for NOx emissions increased slightly . However, none of the three impacts were statistically significant deterioration at the 90% confidence level. 12 Thus, due to the variability in the ef fect across the various test vehicles, we cannot confidentl y reject the hypothesis that the emission deterioration rates on both blends are the same. In other words, there is a significant chance that the average impacts observed are the result of the ran domness in the data. This conclusion is supported by the fact that the average changes in NMOG/CO and NOx emission deterioration rates went in opposite directions. If the catal ys ts had in fact been deteriorating faster with E15, then all emissions should have deteriorated consistently. Therefore, the catal ys t durability test program results also support the conclusion that E15 will not contribute to Tier 2 vehicles exceeding their emission standards over their full useful life. 3 – Analysis of SwRI Pow ertrain Component Inspection Data Background Southwest Research Institute released a report , (SwRI ® ) Project 08 - 58845 Status Report, "Powertrain Component Inspection from Mid - Level Blends Vehicle Aging Study”, that details the results of their Teardo wn measurements of the engines from the vehicles that they aged as part of the DOE Catal ys t Durability Program. Summary Six pairs of engines and fuel sy stem components were disassembled and analyzed for signs of wear and material compatibility problems after E0 and E15 mileage accumulation. Vehicles were matched pairs of used vehicles from MY2006 to MY2008 with mileage ranging from 10k

12 The Agency has typically used a confidence level of 90% in CAA section 211(f)(4) waiver requests instead of the mo re conventional 95% confidence level. We feel that the 90% confidence level increases the likelihood that increases in deterioration would be statistically significant and therefore would be more conservative in this case. However, these differences are also not statistically significant at the 95% confidence level.Draft

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to 50k miles prior to the program. Miles of test program aging ranged from 68K to 102K miles depending on the initial mileage. The following powertrain components were anal yzed:  evaporative s ys tem for leaks  evaporative canister working storage capacity  intake valve deposits  valves and camshafts for wear  fuel pump flow performance  Fuel injector flow rate analy sis  Engin e oil chemical analy sis for wear particles  Intake valve seals were visually inspected. Making any conclusive statements about the inspection data is limited by the lack of baseline, “before”, measurements prior to the aging program’s start, and the aging process itself. So it is not the most rigorous for engine components and materials. Furthermore, the engines were run near continuousl y with few starts or soaks. Nevertheless, It would only be noteworthy

if significant component degradation did occur. Nonetheless, looking at the following observations, the measurement results show no sy stemic trends pointing to greater wear or degradation caused by fuel - related differences. The one very consistent trend was a greater buildup of valve deposits with E 15 use

– possibly due to detergent dilution when displacing 15% of the gasoline with Ethanol. Types of analysis performed Evaporative Emissions System Integrity Check

—Evaporative s ys tem leak checked using a pressure test and smoke. All vehicles passe d the tests. Evaporative Canister Butane Working Capacity

– Measure each canister’s working storage capacity (maximum amount of fuel vapor that can be absorbed). With no measurements taken before aging, we can only make relative comparisons between the canisters from E0 aged vehicles to canisters from matching E15 aged vehicles. When comparing the 6 Canisters aged on E15 to the matching 6 aged on E0, there was no trend indicating any difference between them. The variations in results was uniforml y distributed. No statistically significant change in evaporative canister working capacity is suggested with this small data set. Intake Valve Deposits - Quantified in milligrams by weighing the valves before and after cleaning them. All of the E15 engines have a consistent and often very significant increase in intake valve deposits. 41 of the 44 (95%) intake valves from E15 aged engines had more deposits than the valves from the E0 aged engines. 77% of the E15 valves had more than twice the deposit s as their corresponding E0 valves. This could be the result of having 15% less detergent in the fuel as the Ethanol displaced the detergent - enriched gasoline. Valvetrain / Camshaft Measurements -- The following measurements (cam lobe, valve seat and valve stem height) are intended to check if there is any noticeable increase in wear on theDraft

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camshafts and valve seats due to the E15 fuel usage. Only limited observations are possible from the data since there were no baseline “before” measurements prior to the aging program’s start. Nonetheless, looking at the observations following below, the measurement results show no sy stemic trends pointing to greater wear caused by the E15 exposure. Cam Lobe Wear - The overall cam lobe height was measured for any indications of increased wear with E15 fuel compared to the E0 aging. As stated in the SWRIreport, “Because the cams were not measured at the beginning of the program, and due to normal part- to - part variation, the measurements are potentially inconclusive with respect to any fuel- related differences in cam wear”. With no “before” measurements, there are no actual wear numbers to compare. Nonetheless, b y comparing the final lobe dimensions of the 12 pairs of camshafts (intake plus exhaust) there are two observations.  There is no trend showing smaller E15 lobes. Looking at each matched pair, only 2 of the 12 E15 aged camshafts have smaller dimensions than the corresponding E0 cam.  The ty

pical differences were less than 0.02mm (0.0008”). This is very minimal and may be due more to the variation of the initial cam grinding process than wear. Valve Seat Width and Valve Surface Contour

– 3 different dimensions were measured on the valve seat surface for indications of valve seat recession. Without initial measurements, results aren’t conclusive since we don’t know how much wear was due to the aging program versus prior aging on unknown fuels. With that limitation in mind and focusing the peak wear depth on the valve seat contact point (the report labeled this the “Z” term):  Comparing the matched sets of valves, all E15 engines showed similar or less wear than their corresponding E0 valves, except for the Silverado.  Intake valve seat wear for both E0 and E15 aged engines was 1 to 8 microns or, more importantly , less than 0.0001”.  Exhaust valve seat wear was ty pically 8 to 25 microns with the Silverado approaching 30 microns (0.0012”). Itis normal for Exhaust valves to wear more than intake valves.  Such low wear values indicate none of the valves experienced significant wear on this the particular aging cycle. Field vehicles with high mileage can have more than ten times this amount of wear. Valve Stem Height - valve stem height increase can be an indicator of valve seat recession. Un fortunatel y, it is variable with casting and machining variances. As stated in the SWRIreport : “Because valve stem heights at the beginning of the program are not known, and because of variations in actual cylinder head geometry and valve length, it is difficult to draw any conclusions about valve seat wear.”

 There is no consistent difference between the E0 and E15 engines when comparing valve heights between corresponding pairs of engines.  The exception is the Accord exhaust valves which are uniforml y taller on the E0 engine. This is likely

a manufacturing difference.  Several E15 engines had 1 valve noticeabl y taller than the rest. There is no way to determine if this is manufacturing variability or valve recession.Draft

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ASTM D5185 Analyses of Engine Oil Drain Samples – The difference in metal levels between the E0 and E15 related oil samples do not show any trends indicating that E15 increases internal engine wear relative to E0 fuel. As stated in the SWRIr eport: “ There do not appear to be any unusua lly high wear metal levels in any of the engine oil drains.” Fuel Pu mp Evaluations - Fuel pump flow rate was measured at pressures above and below the mean expected pressure specified by the manufacturerSome pumps exhibited different flow rates but without measurements before the start of aging, w e can not distinguish between part - to - part variation and deterioration. None of the flow rate curves looked significantly different between the two aging fuels in the matched pairs. As stated in the SWRIreport: “ While pump characteristics prior to the vehicle aging program are unknown, there do not appear to be any serious differences between the RE0 fuel pumps and the RE15 fuel pumps.” Fuel Injector flow rate analysis - SwRIflow tested the injectors at 3 duty cycle settings. They concluded all injectors fall within 3% of the mean for each engine application. It appears these were static flow tests which are less sensitive to pintle characteristics. Dy namic testing would be more appropriate for detecting any pintle mechanical degradation. While the test results indicate no adverse effects related to e thanol exposure, a more appropriate measurement would allow a definitive conclusion. 4 – Estimated NMOG Calculation The term “non - methane organic ga ses” (NMOG) describes the sum of hydrocarbon emissions other than methane that may or may not contain oxygen, a set that is inclusive of many compounds that are both directly harmful to health as well as contribute to smog and ozone pollution. Ox ygen - cont aining species (referred to as oxygenated hydrocarbons, or OHCs) are ty picall y a very small fraction of NMOG emissions for non - oxygenated fuels, but can become a significant portion for a gasoline - ethanol blended fuel. As such, NMOG is the basis for Tier 2 emissions standards, and also for evaluating emissions related to the waiver decision. Generation of NMOG results from an emission test is complicated by the fact that the ty pe of hydrocarbon analyzer ty picall y used in emission test cells produces an in complete account of OHCs. Thus, the OHCs must be measured b y other methods and combined with the non - methane hydrocarbon (NMHC or NONMHC) to properl y account for all NMOG emissions. During the planning phase of the program, EPA and DOE staff agreed that NMOG emissions would be computed as NONMHC plus at least methanol, ethanol, formaldehyde, and acetaldehyde. Other alcohol and/or carbonylspecies may be included, but ty

pically don’t change the result significantly

since they

are emitted in much smaller amounts than these.Draft

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As described in Section 1 above, DOE used three commercial emission testing companies to produce emission results for this waiver: Southwest Research Institute (SwRI), Transportation Research Corporation (TRC), and Environmental Testing Corporation (ETC). Between the three labs, there were differences in both how OHCs were measured and how NMOG was calculated, complicating the task of aggregating all results into a consistent form necessary for evaluation of the data. Of the three la

bs, SwRImeasured the required OHCs for all tests, in a way consistent with ty pical best practices, and computed NMOG accordingl y. ETC did not produce useable OHC results for all compounds for all tests, and thus were not able to compute NMOG as defined f or all tests due to the level of uncertainty in the emission measurement. TRC utilized an approach similar to ETC at the start of testing, but then switched part - way through the test program to measure OHC emissions similar to SwRI . Due to the inconsistencies in data, DOE (in agreement with EPA) performed calculations on the contractor- reported values to produce NMOG estimates for all tests on a consistent basis. The first step was to produce NONMHC from test - cell - reported values (that contained incomple te accounting for ox ygenated species) for all 3 laboratories that were all measured on a consistent basis. Attached to this memo is a document entitled “Derivation of Mass - Correction Method for NMOG Determination, August 20, 2010” that describes this calculation in detail. The second step was to adjust the NONMHC results to reflect the presence of OHCs in NMOG emissions. Examining data from SwRI , the NMOG to NONMHC ratio was found to have a linear correlation with fuel ethanol content. A linear fit equation was generated for this ratio as a function of fuel ethanol content for composite (FTP weighted) emission results. This equation is given here, solved for NMOG, where ETOH is defined as the fuel ethanol content in volume percent: 

##   ETOH 0079 . 0 0293 . 1 NONMHC NMOG estimated     To avoid inconsistent treatment of vehicles and fuels between the three labs, this equation was used to generate estimated NMOG results for all tests in the program. This approach is sufficiently

accurate to address the question of whether a vehicle’ s emissions deterioration is worse with E15, since this question involves looking at rates of change, and tests at all mileage points are consistently

treated by

the ratio. We believe it is also sufficiently accurate to estimate actual NMOG measurements, as the difference between estimated and actual NMOG measurements, where data was available, is very small.