Exhaust Emission Impacts of Replacing
Heavy Aromatic Hydrocarbons in
Gasoline with Alternate Octane Sources



£%	United States

Environmental Protect
Agency


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Exhaust Emission Impacts of Replacing

Heavy Aromatic Hydrocarbons in
Gasoline with Alternate Octane Sources

This technical report does not necessarily represent final EPA decisions
or positions. It is intended to present technical analysis of issues using
data that are currently available. The purpose in the release of such
reports is to facilitate the exchange of technical information and to
inform the public of technical developments.

Assessment and Standards Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency

NOTICE

4>EPA

United States
Environmental Protection
Agency

EPA-420-R-23-008
April 2023


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Exhaust Emission Impacts of Replacing Heavy Aromatic
Hydrocarbons in Gasoline with Alternate Octane Sources

Table of Contents

List of Figures	2

List of Tables	3

Executive Summary	5

1.	Introduction	6

1.1	Background	6

1.2	Correlating Fuel Properties with PM Emissions	6

1.3	U.S. Gasoline Market Fuel Composition	7

1.4	A New Vehicle Emissions Research Program	9

2.	Vehicle Emissions Study	10

2.1.	Test Fuels	10

2.1.1.	Primary Design Variables	10

2.1.2.	Test Fuel Matrix - Blending Approach	14

2.1.3.	Test Fuel Matrix-Final Confirmation	15

2.2.	Test Vehicles	17

2.3.	Emissions Testing: Procedures and Guidelines	17

2.3.1.	Test Cycles	18

2.3.2.	Dilution Tunnel Cleanliness	19

2.3.3.	Drivers	20

2.3.4.	Test Fuel Sequence	20

2.3.5.	Vehicle Fuel Change and Test Preparation	20

2.3.6.	Emissions Testing Procedures	21

2.3.7.	Particulate Matter (PM) Measurement	22

2.3.7.1.	Gravimetric	23

2.3.7.2.	OC/EC	23

2.3.7.3.	AVI. MicroSoot Sensor (MSS)	23

2.4.	Vehicle Emissions Results	23

2.4.1.	Particulate Emissions	23

2.4.2.	NOx Emissions	35

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2.4.3.	NMOG Emissions	45

2.4.4.	CO2 Emissions	54

2.4.5.	Influence of Drive Quality	62

3. Summary and Conclusions	64

Acknowledgement	65

References	65

Appendix A: Supplemental Emissions Analysis

Appendix B: Emissions Dataset

List of Figures

Figure 1.1. Incremental PMI value per unit volume of fuel, listed by carbon number	8

Figure 1.2. The content of aromatic species in the tail ends of US summer E10 regular-grade market gasoline.

[11]	9

Figure 2.1. Histogram of PMI of US 2018 gasoline per ASTMD6730	 11

Figure 2.2. Histogram of PMI of US 2019 gasoline per ASTM D6730	 11

Figure 2.3. Boxplot of aromatics volume percent from US market summer gasoline 2018 and 2019	12

Figure 2.4. U.S Federal Test Procedure (FTP)	18

Figure 2.5. Supplemental FTP orUS06	19

Figure 2.6. Summary of PM emissions reductions for the FTP cycle for each test fuel (relative to Fuel A),
shown by vehicle and for the test fleet average with 95% confidence interval	24

Figure 2.7. Summary of PM emissions reductions for the US06 cycle for each test fuel (relative to Fuel A),
shown by vehicle and for the test fleet average with 95% confidence interval	24

Figure 2.8. FTP PM dataset by vehicle, linear scale	25

Figure 2.9. FTP PM dataset by vehicle, log scale. Arrows indicate data removed from the analysis	26

Figure 2.10. FTP PM data as vehicle means by fuel, log scale	27

Figure 2.11. FTP PM data as vehicle means by PM Index, log scale	27

Figure 2.12. Analysis of conditional studentized residuals for FTP cycle PM data	28

Figure 2.13. Externally studentized residuals for PM FTP cycle data	29

Figure 2.14. US06 PM dataset by vehicle, linear scale. Arrows indicate data removed from the analysis	30

Figure 2.15. US06 PM dataset by vehicle, log scale. Arrows indicate data removed from the analysis	31

Figure 2.16. Comparison of MicroSoot Sensor and PM data for Veh C. Triangular point indicates a

measurement far away from the correlation trend	32

Figure 2.17. US06 PM data as vehicle means by fuel, log scale	32

Figure 2.18. US06 PM data as vehicle means by PM Index, log scale	33

Figure 2.19. Analysis of conditional studentized residuals for US06 cycle PM data	34

Figure 2.20. Externally studentized residuals for US06 cycle PM data	34

Figure 2.21. FTP NOx dataset by vehicle, linear scale	36

Figure 2.22. FTP NOx dataset by vehicle, log scale	36

Figure 2.23. FTP NOx data as vehicle means by fuel, log scale	37

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Figure 2.24. FTP NOx data as vehicle means by PM Index, log scale	37

Figure 2.25. Analysis of conditional studentized residuals for FTP cycle NOx data	38

Figure 2.26. Externally studentized residuals for FTP cycle NOx data	39

Figure 2.27. US06 NOx dataset by vehicle, linear scale	40

Figure 2.28. US06 NOx dataset by vehicle, log scale	41

Figure 2.29. US06 NOx data as vehicle means by fuel, log scale	42

Figure 2.30. US06 NOx data as vehicle means by PM Index, log scale	42

Figure 2.31. Analysis of conditional studentized residuals for US06 cycle NOx data	43

Figure 2.32. Externally studentized residuals for US06 cycle NOx data	44

Figure 2.33. FTP NMOG dataset by vehicle, linear scale	45

Figure 2.34. FTP NMOG dataset by vehicle, log scale	46

Figure 2.35. FTP NMOG data as vehicle means by fuel, log scale	46

Figure 2.36. FTP NMOG data as vehicle means by PM Index, log scale	47

Figure 2.37. Analysis of conditional studentized residuals for FTP cycle NMOG data	48

Figure 2.38. Externally studentized residuals for FTP cycle NMOG data	48

Figure 2.39. US06 NMOG dataset by vehicle, log scale. Red arrows indicate zero-value measurements	50

Figure 2.40. US06 NMOG dataset used in the analysis, linear scale	50

Figure 2.41. US06 NMOG dataset used in the analysis, log scale	51

Figure 2.42. US06 NMOG data as vehicle means by fuel, log scale	51

Figure 2.43. US06 NMOG data as vehicle means by PM Index, log scale	52

Figure 2.44. Analysis of conditional studentized residuals for US06 cycle NMOG data	53

Figure 2.45. Externally studentized residuals for US06 cycle NMOG data	53

Figure 2.46. FTP CO2 dataset by vehicle	55

Figure 2.47. FTP CO2 data as vehicle means by fuel	55

Figure 2.48. FTP CO2 data as vehicle means by PM Index	56

Figure 2.49. Analysis of conditional studentized residuals for FTP cycle CO2 data	57

Figure 2.50. Externally studentized residuals for FTP cycle CO2 data	57

Figure 2.51. US06 CO2 dataset by vehicle	59

Figure 2.52. US06 CO2 data as vehicle means by fuel	59

Figure 2.53. US06 CO2 data as vehicle means by PM Index	60

Figure 2.54. Analysis of conditional studentized residuals for US06 cycle CO2 data	61

Figure 2.55. Externally studentized residuals for US06 cycle CO2 data	61

List of Tables

Table 1.1 Objectives of the gasoline heavy aromatics program	9

Table 2.1. Test fuel matrix design targets	10

Table 2.2. Hydrocarbon content (vol%) for samples from 2018-2019 with the ten highest PMIs	12

Table 2.3. PMI and percentage contributions by hydrocarbon group for samples from 2018-2019 with the ten
highest PMIs	13

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Table 2.4. PMI and percentage contributions by aromatic carbon number for samples from 2018-2019 with the

ten highest PMIs	13

Table 2.5. Aromatic hydrocarbon content (vol%) for samples from 2018-2019 with PMI 2.3-2.8 and
corresponding PMI contribution	14

Table 2.6. Hand-blend fuel specifications	15

Table 2.7. Final fuel property results	16

Table 2.8. Vehicle test fleet	17

Table 2.9. Tunnel background PM sampling procedure, to be performed once a week	19

Table 2.10. Fuel testing sequence for each vehicle	20

Table 2.11. Fuel change and vehicle preparation procedure	21

Table 2.12. Vehicle test procedure	22

Table 2.13. Percent-PM-emissions per percent-PM-Index sensitivities by test cycle and vehicle	25

Table 2.14. Number of PM measurements collected and analyzed in the FTP cycle data analysis	28

Table 2.15. Fixed effect model parameters for FTP PM	29

Table 2.16. Differences in least squares means by fuel for FTP PM	30

Table 2.17. Number of PM measurements collected and analyzed in the US06 cycle model fitting	33

Table 2.18. Fixed effect model parameters for US06 PM	35

Table 2.19. Differences in least squares means by fuel for US06 PM	35

Table 2.20. Number of NOx measurements collected and analyzed in the FTP cycle model fitting	38

Table 2.21. PMI model parameters for FTP NOx	39

Table 2.22. Differences in least squares means by fuel for FTP NOx	40

Table 2.23. Number of NOx measurements collected and analyzed in the US06 cycle model fitting	43

Table 2.24. Fixed effect model parameters for US06 NOx	44

Table 2.25. Differences in least squares means by fuel for US06 NOx	45

Table 2.26. Number of NMOG measurements collected and analyzed in the FTP cycle model fitting	47

Table 2.27. PMI model parameters for FTP NMOG	49

Table 2.28. Differences in least squares means by fuel for FTP NMOG	49

Table 2.29. Number of NMOG measurements collected and analyzed in the US06 cycle model fitting	52

Table 2.30. Fixed effect model parameters for US06 NMOG	54

Table 2.31. Differences in least squares means by fuel for US06 NMOG	54

Table 2.32. Number of CO2 measurements collected and analyzed in the FTP cycle model fitting	56

Table 2.33. PMI model parameters for FTP CO2	58

Table 2.34. Differences in least squares means by fuel for FTP CO2	58

Table 2.35. Number of CO2 measurements collected and analyzed in the US06 cycle model fitting	60

Table 2.36. Fixed effect model parameters for US06 CO2	62

Table 2.37. Differences in least squares means by fuel for US06 CO2	62

Table 2.38. Differences in least squares means by fuel for FTP cycle IWR	63

Table 2.39. Differences in least squares means by fuel for US06 cycle IWR	63

Table 3.1. Percent-PM-emissions per percent-PM-Index sensitivities by test cycle and vehicle	64

Table 3.2. Summary of model results for a PM Index reduction from 2.5 to 1.5	64

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Executive Summary

High-boiling aromatics have been shown to be the primary contributor to particulate matter (PM) emissions
from gasoline engines. The U.S. Environmental Protection Agency (EPA), in collaboration with the
Environment and Climate Change Canada (ECCC) and seven global automotive vehicle manufacturers,
conducted a gasoline vehicle emissions test program to quantify the emissions impact of replacing a portion of
high-boiling aromatics with lower-boiling aromatics, ethanol, and high-octane aliphatic blending components.

The test program included ten high-sales U S & Canadian light-duty spark-ignited (SI) test vehicles, tested at
nine emission labs, using standardized vehicle emissions tests (US EPA FTP and US06), over a set of five
specialty-blended test gasolines.

The results indicate the potential for significant tailpipe PM reductions from light duty gasoline vehicles when
high-boiling aromatics are replaced with other high-octane blending components. As summarized in Figure
ES. 1 and Figure ES.2, switching to fuels in which high-boiling aromatics were reduced from 7.4 %v to 4.2-4.5
%v yielded an average PM emission reduction percentage of 35-45% on the FTP Composite cycle and 20-25%
on the US06 cycle in this study.

The program also measured regulated gaseous emissions, which are of interest when considering broader air
quality impacts of fuel formulation changes. No increase in emissions of NOx, NMOG, nor CO2 was observed
for the test fleet when replacing a portion of heavy aromatics with alternate octane sources.

120%

100%

80%

60%

40%

20%

0%

Fuel A

C10+aromatics: 7.4%

3

o

sP
0s





o







o









8r

a

o

o

i.



a

	o	

i"

I-

T





















Fuel B
4.5%

Fuel C
4.4%

Fuel D

4.2%

Base Fuel
4.5%

Vehicle

OVeh_A
OVeh_B
OVeh_C
OVeh_D
OVeh_E
OVeh_F
OVeh_G
OVeh_H
OVehJ
OVeh_J
m Average

Figure ES.l. Summary of PM emissions reductions for the FTP cycle for each test fuel (relative to Fuel
A), shown by vehicle and for the test fleet average with 95% confidence intervals.

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120%

100%

80%

60%

40%

20%

0%

Fuel A

C10+aromatics: 7.4%

<

"oi

3
LL
*4—

O

NO

(/)
(0

Q_

of

o

o

I-

Vehicle

OVeh_A
OVeh_B
OVeh_C
OVeh_D
OVeh_E
OVeh_F
OVeh_G
OVeh_H
C Veh_l
OVehJ
^Average

Fuel B

4.5%

Fuel C
4.4%

Fuel D
4.2%

Base Fuel
4.5%

Figure ES.2. Summary of PM emissions reductions for the US06 cycle for each test fuel (relative to Fuel
A), shown by vehicle and for the test fleet average with 95% confidence intervals.

1. Introduction
1.1 Background

Particulate matter (PM) pollution has been linked to a multitude of health problems [1,2]. Particles smaller than
2.5 micrometers in diameter, referred to as PM2.5, pose the greatest risk because they can penetrate deep into
the lungs and enter the bloodstream. Exposure to PM2.5 increases the risk of premature death and can impair
lung growth in children. For individuals with preexisting health challenges, PM2.5 can increase the risk of
cardiovascular and respiratory disease. The United States Environmental Protection Agency (US EPA)'s 2017
National Emissions Inventory estimates that gasoline-fueled vehicles and nonroad equipment contribute 31.9%
of the total mobile source primary PM2.5 emissions [1],

Multiple studies have shown that gasoline properties have a major influence on combustion-related PM
emissions [3, 4, 5, 6, 7], Heavy aromatic compounds in particular are major PM contributors. The heavy end of
gasoline consists almost exclusively of aromatics, and the heaviest several percent of those species have a
disproportionally large impact on the amount of PM emitted.

Advancements continue in engine, aftertreatment, and propulsion technology to mitigate PM emissions.
However, these improvements only affect new model year vehicles and engines. Over 250 million gasoline-
powered on-road vehicles and about 150 million nonroad vehicles and pieces of equipment exist in the United
States [8, 9], with many of them remaining in use for decades. Changes in fuel composition can affect this entire
population of equipment, resulting in immediate and substantial PM emission reductions.

1.2 Correlating Fuel Properties with PM Emissions

The PM Index is currently the parameter most frequently used to characterize the propensity of gasoline to
generate PM emissions. It was proposed in 2010 by Aikawa and colleagues [3] and has proven to be a robust
predictor. It is being widely used in the modeling of fuel impacts on PM emissions from spark-ignited (SI)
engine equipped vehicles and has been shown to be directly proportional to PM emissions [4, 6], The PM Index

6


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requires the use of a detailed hydrocarbon analysis (DHA) of the fuel and is calculated using the following
equation:

" (DBE; +1)

PM Index =

•xWt.

where DBE; is the double bond equivalent of compound i, VP(443K)i is the vapor pressure of compound i at
443 K, and Wti is the weight percent of compound i in the fuel.

DBE; is related to the degree of chemical-bond unsaturation of each hydrocarbon compound, and therefore to its
sooting tendency while the VP term is related to the volatility of each compound. In this way the chemical and
physical attributes, respectively, of each compound are considered. Heavy aromatic compounds, such as two
aromatic ring naphthalenes, are highly unsaturated and have low vapor pressures. Considering the equation
above, it is clear why such fuel components are main contributors to the PM Index (PMI) values of commercial
gasolines.

Given that the final PMI value represents the summation of individual fuel component contributions, a detailed
hydrocarbon analysis (DHA) is required. DHA is a laboratory method that uses gas chromatography (GC) to
separate and quantify each molecular component of a fuel. In practice, it is not possible to identify and quantify
100% of the species in a fuel sample; a typical market gasoline can consist of hundreds of components.
However, a recent DHA enhancement [10] has reduced the number of unidentified components to a fraction of
a percent, thereby improving the accuracy of the PM Index determination. To achieve this level of quality,
analysis times typically run up to three hours, after which the output data must be reviewed by a skilled operator
or chemist to confirm that species identifications and quantifications were performed correctly by the software.
Post-run corrections may be required in the high-boiling tail region of the chromatogram, a region that has great
leverage over the final PMI. The DHA - PMI methodology, while intensive, is a strong predictor of a gasoline's
propensity to create vehicle particulate emissions.

1.3 U.S. Gasoline Market Fuel Composition

The aforementioned leverage of heavy aromatic components on the final PMI value can be visualized using data
from a recent PMI fuel survey of U.S. market fuels. As detailed in the next section of this paper, this survey was
conducted in the summer of 2018 and 2019 by the Alliance for Automotive Innovation. The data shown in are
Figure 1.1 are derived from Tables 3.2 - 3.5 in Section 3. Although a single sample was used for this example,
the relationships shown are generally sample independent; the values will differ somewhat based upon the
concentrations of the specific species within the compound classes and carbon number groups.

Figure 1.1 demonstrates the disparity of PMI influence among aromatic species. Even a tiny volume of heavy
aromatics can swing the PMI to a high value. Also, the PMI contribution of all other compound classes is
minimal compared to that of the heavy aromatics.

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C6	C7	C8	C9 CIO Cll C12 C13 Other CCs

Aromatic Carbon Number

Figure 1.1. Incremental PMI value per unit volume of fuel, listed by carbon number.

To get a complete picture of this heavy aromatic leverage, an understanding of the volume of these species in
market gasoline is necessary. The volume information in Figure 1.2 was derived from DHA data from 708
summer regular-grade E10 gasoline samples [11], To characterize the distribution of aromatic species in U.S.
market gasoline, these data were grouped into three categories: total aromatics, monocyclic aromatics (e.g.,
benzene, toluene, xylenes), and bicyclic aromatics such as naphthalenes and indenes. Their percent content in
the tail end of the fuels is presented as a function of the cut-off temperature. (The term "cut-off temperature" is
used here to signify that each aromatic datapoint represents species boiling at or above this specific
temperature.) Also included in Figure 1.2 is a plot showing the volume fraction of all identified species in the
708 fuels and boiling at or above the cut-off temperature as determined by the ASTM D86 atmospheric
distillation test method. It should be noted that the U.S. market generally follows the ASTM D4814 gasoline
specification, in which the maximum FBP (final boiling point) is 437°F. Globally, most regions follow the
EN228 specification, in which the maximum FBP is 410°F.

It can be seen in this figure that aromatic species dominate the heavy end of U.S. market gasolines, exceeding
90%v at a cut-off temperature of 380°F. Bicyclic aromatics, which are most prone to the generation of PM
emissions, dominate its heaviest, least volatile fractions. This correlates with aromatic species >C10 in Figure
1.1. As an example, bicyclic aromatics constitute the majority of total aromatics starting just above 400°F, when
the fuel fraction above the cut-off falls below 2 v%.

Given that the heaviest few percent of gasoline aromatics are responsible for such a disproportionate effect on
PM emissions, it would seem natural to conclude that a distillation adjustment or product shift during the
refining process could address this issue. However, these heavy fractions can have high octane ratings;
removing even small fractions of these components could cause a drop in the anti-knock index. Also, the
volume of gasoline produced would be reduced in proportion to the volume of heavy fractions removed.

Naphthalene

(for example)

All other
compound

classes
combined

v

. i I

\7

8


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Figure 1.2. The content of aromatic species in the tail ends of US summer E10 regular-grade market

gasoline. [11]

1.4 A New Vehicle Emissions Research Program

The loss of octane and volume by removal of a few percent of the heaviest aromatic gasoline blending
components described in the previous section could be compensated for by using appropriate lighter, high-
octane refinery blending components and/or ethanol. In an effort to verify this concept experimentally, a
research program was conducted by seven auto manufacturers, the U.S. EPA, and Environment and Climate
Change Canada (ECCC). The program was designed to confirm the assumption listed in Table 1.1.

Table 1.1 Objectives of the gasoline heavy aromatics program.

Assumption

Program Activity to Confirm

• Vehicle PM emissions decrease when the
heavy tail of the fuel is replaced with
lower-PMI components, under conditions
in which octane and volume remain
generally constant.

•	Conduct a large test program:
o 10 vehicles

o 9 test facilities (1 —> 2 vehicles/lab)
o 5 fuels

o 2 standardized driving cycles

•	Fuels:

o Base (includes 10%v ethanol)
o Base + 3. l%v heavy aromatics
o Base + 3. l%v light aromatics
o Base + 3.1%v alkylate
o Base with 6%v ethanol

¦Fuel fraction		Total aromatics

• Monocyclic aromatics		Bicyclic aromatics

220 260 300 340 380 420
Cut-off temperature (°F)

80

60

40

20

0
460

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2. Vehicle Emissions Study
2.1. Test Fuels

In this study, the Test Fuel Matrix (Table 2.1) consisted of five carefully blended test fuel formulations,
developed to mimic a range of U.S. gasoline PMI values and processing changes a petroleum refiner could
potentially use to produce lower emission market fuels, while still meeting other market fuel quality limits.

Table 2.1. Test fuel matrix design targets.

Parameter

Base Fuel
Typical US Gasoline

Fuel A
Base Fuel +3.1 vol%
of CI 1+ Aromatics

Fuel B
Base Fuel +3.1 vol%
of C7-C9 Aromatics

Fuel C
Base Fuel + 3.1vol%
Alkylate

FuelD
Base Fuel + 6 vol%
Ethanol

PM Index Targets

1.6 ± 0.1

2.7 ± 0.1

Report

Report

Report

Ethanol Targets

9-10 vol%

9-10 vol%

9-10 vol%

9-10 vol%

14-15 vol%

Note: Resultant PMI values of Fuels B,C,D need to be determined by analysis. Aromatic hydrocarbons are listed by their carbon number.

Fuel A represents a high-PMI, high-distillation-endpoint gasoline in the current U.S. market. It's used as a
reference for emissions comparisons with Fuels B, C and D. Fuels B, C, and D represent three possible
scenarios for replacement of approximately half of the heavy (>C10 or CI 1+) aromatic fraction of Fuel A (3%v
replaced) with other high-octane hydrocarbons or ethanol, which restores the original octane rating. Fuel B
represents a replacement with 3%v of light (
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14,

Histogram of PMI ASTM D6730 US 2018

12

10

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CD
3
C"

tu

li 6

Vlean StDev N
Premium-] 554 0.4033 46

I	1 Regulan.648 0.4142 61

Count Mean Minimum Maximurr
k Total AROMATICSVol% 107 23.363 2.692 46.733
107 1.6076 0.5200 2.8100

PMI ASTM D6730

Figure 2.1. Histogram of PMI of US 2018 gasoline per ASTM D6730.

Histogram of PMI ASTM D6730 US 2019

Mean StDev	N

1.571 0.2046	7

I	1 Premium 44 0 3360	36

I	I Regular i 513 0.3712	80

Count Mean Minimum Maximum
Total AROMATICS Vol% 123 24.109 3.290 43.924
PMI ASTM D6730	123 1.4950 0.5500 2.3900

1.6	2.0

PMI ASTM D6730

Figure 2.2. Histogram of PMI of US 2019 gasoline per ASTM D6730.

11


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20

10

Market Gasoline 2018 and 2019 Summer

~	PM11-1.5
¦ PM11.5-2.3

~	PMI<1
HI PMl>2.3

*
*

-X-

ft

T

*

^ j *
? t+eT A

C7 AROMATICS VOL% C8 AROMATICS VOL% C9 AROMA TICS VOL% C10 AROMATICS VOL% C11+ AROMATICS VOL%

Figure 2.3. Boxplot of aromatics volume percent from US market summer gasoline 2018 and 2019.

The ten highest PMI fuels from these surveys were investigated further to characterize the PMI contributions by
hydrocarbon class and within the aromatic fraction. Table 2.2 shows the distribution of hydrocarbon groups in
each of the samples as well as averages by class and their corresponding PMI contributions. Table 2.3 shows
that the majority of PMI for these high PMI fuels is from aromatic hydrocarbons. Table 2.4 and Table 2.5 show
the distribution of aromatic hydrocarbons by carbon number in each of the samples as well as averages by
carbon number and their corresponding PMI contributions.

Table 2.2. Hydrocarbon content (vol%) for samples from 2018-2019 with the ten highest PMIs.

Vol9S

G18071iffi

G180704-10

G180725-07

G1S07KMS

G1M725-12

G180719-15

G1&07U-09

G180717-03

G190722-M.

G190711-07

P

8.51

11.83

12.31

15.14

11.20

14.62

1130

12.90

14.98

13.85

1

46.52

r 32.32

36.44

32.76

33.72

33.17

36.69

27.29

36.60

34.45

O

1.90

r 10.36

10.26

6.79

9.50

9.06

6.64

6.19

7.80

5.85

N

5.35

' 9.32

7.74

7.10

6.89

6.80

1126

3.14

7.11

882

A

37.70

r 26.13

23.21

28.13

28.49

25.64

24.01

40.58

23.20

26.96

Ethanol

0.00

r 9.94

9.90

9.98

10.00

9.91

9.97

9.77

9.50

9.57

X

0.00

r 0.01

0.00

0.00

0.00

0.00

0.00

0.10

0.00

0.04

U n known

0.03

0.12

0.15

0.10

0.21

0.82

0.13

0.04

0.80

0.47

Told

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

12


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Table 2.3. PMI and percentage contributions by hydrocarbon group for samples from 2018-2019 with the

ten highest PMIs.

PMI

G1M75J-03

01807W10

C1B3725-07

6180710-18

GIB'0725-12



G180714-09

Gl80717-03

G1SD722-S3

G199711-07

P

2.217

0.030

2.232

0.029

2.22s

0.024

u. J23

0.013

2.C33

0.021

1

2.122

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2.2-93

0.076

C.2-9S

0.087

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2-. 2-2 9

0.021

2,223

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2.225



2.222

0.018

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2.35

0.249

0.349

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2.248

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2.221

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2.251

A

1.352

2.133

2.3'52-

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2.3SE

2.2a

2.127

ID 57

2.CIS

2.134

Etbarc>l



3.212

D.C12

C.2-12

G.D12

D.C12

2.C12

2.212

0.212

2X12

X

: x:

Z-.XZ

I 111

r. -rr

2-.2-X

^ ^ CC'

2.X2

J ...

0.C2-2

2.20C-

~Dta!

2.Hi

2.334

1213

2.330

2.537

2.455

2.33-

2 IE 3

2 21£

2.384

PMI*

GtW7 »3-C3 GiWTW-SC Gf«5725-07 G190710-13 GW25-52 3!8®?1S-«5 G1I87U-0S GI90717-S3 G*9.?2J-€S GMfJ7tM»7

P

C.B19

1291

1347

1.249

113

3.984

2.99S

1605

1.-73

0861

1

4.S4S

3.680

-112

3.282

i ~ii

3.542

4 252

2.344

3.935

3.729

0

: i_-_

1033

12E5

0.236

2 £93

LOTS

1.262

0.435

1011

0.759

N

1.662

2.094

2148

1.823

1 £59

1.76B

2.XI

0.975

1.344

2.13a

A

92.33a

§1.375

90 592

92.224

9-.S91

§2.114

1 £-£

95 090

91.052

91033

Table 2.4. PMI and percentage contributions by aromatic carbon number for samples from 2018-2019

with the ten highest PMIs.

PMI

6fflC7I3-S GfSOm-fO Gt = "25-OT GIPU-'I G 38€725-f 2 G13071M5 GIBC7U-0S GI8S717-D3 G13C722-C3 G19C7II-C7

A6

2.x-

3.X3

3.223

3.233



2.235

3.3C4

3.333

2,614

1.167

A7

: 153

0 073

3.334

0 080

2.256

0.041

3.35S

::_e

2.912

6.006

A8

2.3^9

r

0.214

2.193

0.210

2.132

0 191

2.169

0.532

3.321

3 396

A9

2.431

0 308

2.3E3

0.354

2 32:

0.406

2,33-

2.391

7.232

7.470

A10

2.373

r

0.516

2.535

0.513

2.63-

§.573

j.5— u

2.3 = 3

5.C9S

5.305

All

2.1S8

r

0.518

2.39S

0.460

2,-26

0,531

2,479

2.192

1.623

1.981

A12

2.193

«M5§

2.369

2.37-

2.334

0.464

34£1

0.169

1.293

1.426

A13

C.134

' 0.042

3.152

2.13?

C.253

0.046

2.342

0.2.62

C.C63

0.042



2.253

' 0 000

3.316

G.C3-3-

O.K»

0.004

0000

5.011

ii.yvS

0.000

A15

C.X3

r 0 000

3.232

3.233

C.23C

0 000

0.000

2.333

::::

0 000

PMia

G180713-0} G180704-10

GIBfl7!5-97 SW71S-SS 0*80725-12 S18tT»15 G1BB714-03 GI8-J7I7-0J GI3C722-C8 G19071U07

A8

0225

ft 132

3.143

0.393.

C.272

0.2®

3.156

0.143

2.213

3.671

A7

8.342

3.410

1672

3.737

2.331

1830

2.763

5.599

13.497

18 891

A8

17.S61

12.236

S.£ 3 2

12.281

7.523

5,ill

S.327

25.S76

29.396

26. ICE

A9

22.39-

14.451

18.546

16.-59

2135-

17.9-3

15.862

19. CIS

25.234

23.-36

ilC

13.155

2- 179

24.654

2: 33"

26.56-

25

25.625

13.633

15.373

16.686

411

3.5-7

2- 23-

13.-35

21.-27

17.S37

23.-35

22.732

9.2-7

5.737

6,231

412

9.H7S

21 512

13.21B

17—1—

13.356

23.5-2

22,813

8.229

-.653

-.-35

A13

? 323

1969

7.321

5.-52

13.625

2.031

1 987

12.730

C.216

0,132

A14

2.991

ft OH

2.732

2.C22

2.2X

0.159

0000

0525

C.31B

0.000

A15

2.X3

ft®#

0.333

0 000

0 000

0.0®

0.000

0.000

C.C23

0.000

13


-------
Table 2.5. Aromatic hydrocarbon content (vol%) for samples from 2018-2019 with PMI 2.3-2.8 and

corresponding PMI contribution.





G1l070i-10

?

\ i.

G180725 12

„ I

'j , :



m" 1 ' V J. '

j -J i













: i <





-



:

: il

155

: ::

AH



153

11 5

* ?£

140

149

1.17

a so

127



121

- T"





in





086

136



a 26





3.92

O.ir





0.03





0.12

M .



0 12





0.D5







a oo

, u



ace





il 00

i



0.30

3 3D





a*o



1.18

02*





0.42





:

" lr

AJ



- •:(

. . „

5..71



2, 92



a;m







2 an

m







7.91



o?



19.45

>

,

S51

11?







'

6.71



7. 61



7, 7tt





~ I-

1®

•





i ;





r

2t8!



0 39





1.21

1£1





















145

173

156

1.64

1.87

188

IS8

In

1.S2

1.79

1.S7

: lr



2.11

2J3

22i

2.33

2J90

2.45

2.33

2,18

222

231

232

0.11



1.95

2.13

2.05

2.15

2.39

2 26

2.11

2M

2.02

2.19

2.13

3.3



92.3*

91.38

90.59

32.22

91®

9213

90.25

95.CB

9i.CS

92.G3

91®

133

2.1.2. Test Fuel Matrix - Blending Approach

The formulation of the Base Fuel was developed first. The intent was to replicate the composition and
properties of a typical US summer gasoline with special emphasis on the distribution of aromatic compounds
within the distillation range of this fuel. The first hand-blend of this fuel matched the aromatics distribution by
Carbon Number (C#) provided in Table 2.6.

Fuel A, the highest PMI fuel, was prepared by adding to the Base Fuel a blend consisting of ExxonMobil
Aromatic 150 and Aromatic 200 refinery stream products, which consist of specific boiling-range cuts of
reformate. The ratio of these two streams was adjusted to ensure the target PMI level of 2.7 ±0.1 and an
aromatics profile representative of high-PMI market fuels. The quantity of the blend added to the Base Fuel was
3. l%v, so that its content in Fuel A equals exactly 3.0 %v.

Fuels B, C and D were prepared by adding 3.1%v of C7-C9 aromatics, 3.1%v of refinery-sourced alkylate, and
6%v of fuel grade ethanol to the Base Fuel, respectively.

Hand-blends were evaluated using the following methods: ASTM D4052 density, D4815 ethanol, D86
distillation, D5191 DVPE (EPA equation), hydrocarbon composition and PM Index by Gage DHA, D6550
olefins, D5453 sulfur, D2699 & D2700 octane numbers and D5188 T(v/l=20). The following additional
requirements were included in the specifications:

•	Convert ethanol results to vol. % per Section 14.3 of D4815.

•	Use only OptiDist or equivalent stills to generate D86 distillation data. Stills should measure charge
volume in the receiving cylinder. In addition, report distillation data in l%v increments.

•	Calculate D5191 DVPE using the EPA equation per Code of Federal Regulations (CFR), Title 40, Part
80.46. Report total pressure measured during the test alongside the DVPE.

•	Sulfur adjustments should be made using benzothiophene, t-butyl disulfide, or a three-component sulfur
mixture containing 4.3 mass % dimethyl disulfide, 22.8 mass % thiophene, and 72.9 mass %
benzothiophene.

14


-------
Table 2.6. Hand-blend fuel specifications.

Parameter

Base Fuel
(Typical US
gasoline)

Fuel A (Base Fuel
w/3.1%v of CI 1+
aromatics)

Fuel B (Base Fuel
w/3.1%v of C7-C9
aromatics)

Fuel C (Base Fuel
w/3.1 %v alkylate)

Fuel D (Base Fuel
w/6%v EtOH)

Density, 60°F (D4052)

Report

Report

Report

Report

Report

PM Index (Gage DHA)

1.6 ± 0.1

2.7 ± 0.1

Report

Report

Report

Ethanol (D4815)

9.8 ± 0.2 %v

9.5 ± 0.2 %v

~ Fuel A

~ Fuel A

14.9 ± 0.2 %v

Total Content of Oxygenates
Other Than Ethanol (D4815)

0.1 %v max

Oxygen (D4815)

Report in %m

Report in %m

Report in %m

Report in %m

Report in %m

(R+M)/2 (D2699, D2700)

87.3 ±0.3

Report

Report

Report

Report

Sensitivity (D2699, D2700)

>7.5

DVPE (D5191, EPA

All fuels expected to remain in 8.95 ± 0.25 psi range

T10 (D86)

< 149 °F

T50 (D86)

185 ± 10 °F

Report

Report

Report

Report

T90 (D86)

320 ± 10 °F

Report

Report

Report

Report

Distillation End Point (D86)

< 437 °F

Distillation Residue (D86)

<1.3 %v

Total Aromatics (Gage DHA)

24.5 ±2 %v

Fuel A + 2.2 %v

Fuel A + 2.2 %v

Fuel A- 0.7 %v

Fuel A - 1.4 %v

Benzene (Gage DHA)

0.6 ± 0.2 %v

~ Base Fuel

~ Base Fuel

~ Base Fuel

~ Base Fuel

Toluene (Gage DHA))

6.1 ± 1.0 %v

Report

Report

Report

Report

C8 Aromatics (Gage DHA)

7.4 ±1.0 %v

Report

Report

Report

Report

C9 Aromatics (Gage DHA)

5.5 ±1.0 %v

Report

Report

Report

Report

CIO Aromatics (Gage DHA)

2.7 ±1.0 %v

Report

Report

Report

Report

Cll+Aro. (Gage DHA)

1.2 ± 0.5 %v

Report

Report

Report

Report

Olefin Content (D6550)

7 ± 3 %m

Report

Report

Report

Report

Sulfur Content (D5453)

7 ± 3 mg/kg

7 ± 3 mg/kg

Report

Report

Report

T(v/l=2o) (D5188)

>116°F

> 116 °F

>116°F

>116°F

> 116 °F

Drivability Index (D4814)

<1250

<1250

<1250

<1250

<1250

2.1.3. Test Fuel Matrix - Final Confirmation

Once the analytical results generated by the fuel blender indicated that hand-blends met requirements of the
specifications provided in Table 2.6, the blender submitted a sample of each hand blend to the General Motors
Pontiac chemistry laboratory and the U.S. EPA chemistry laboratory for additional confirmation of the
following analyses: ASTM D4052 density, D5599 ethanol, D86 distillation, D5191 DVPE (EPA equation),
D6550 olefins, D5453 sulfur, D2699/D2700 octane numbers and D5188 T(v/l=20). After confirming all tests
were within acceptable ranges, the project sponsors approved production of bulk blends for shipment to the test
labs. A detailed list of fuel properties measured from the bulk blends is given in Table 2.7.

15


-------
Tab

e 2.7. Final fuel proper!

y results.

Parameter

Unit

Method

Blending
Tolerance

Base Fuel (Typical
reaular-arade gasoline)

Fuel A (Base Fuel w/3.1
vol.% ofC10+Aromatics

Fuel B (Base Fuel w/3.1
vol.% of C7-C9

Fuel C (Base Fuel w/3.1
vol.% ofalkvlate)

Fuel D (Base Fuelw/6
vol.% of ethanol)

Specification

Average

Specification

Average

Specification

Average

Specification

Average

Specification

Average

Density @ 60°F

q/cm3

D4052





0.7428



0.7490



0.7477



0.7420



0.7457

Specific Gravity @ 60°F



D4052





0.7435



0.7497



0.7484



0.7428



0.7465

PMI Index byGaqe DHA



Gaqe DHA

±0.1

1.5

1.49

2.66

2.72

1.58

1.53

1.46

1.50

1.42

1.41

Ethanol

vol. %

D4815

±0.2

10

9.54

9.7

9.27

9.7

9.24

9.7

9.23

14.9

14.75

Other Oxyqenates

vol. %

maximum

0.1

0.0

0.1

0.0

0.1

0.0

0.1

0.0

0.1

0.0

Oxyqen

riass %





3.54



3.43



3.43



3.42



5.48

RON



D2699





91.1



91.4



91.7



91.2



93.8

MON



D2700





83.2



83.5



83.7



83.7



84.6

(R + M)/2



)2699/D270(

±0.3

87.2

87.2

87.4

87.5

87.5

87.6

87.2

87.4

89.2

89.2

Sensitivity







7.9



7.9



7.9



7.5



9.2

DVPE

psi

D5191 (EPA

±0.2

9.0

9.2

8.6

9.1

8.7

8.9

8.7

9.0

8.7

9.1

Distillation



























IBP

°F

D86





95.1



95.6



96.1



95.5



96.0

T5





117.0



118.7



118.9



118.3



119.4

T10

±5

127.6

125.0

128.6

126.5

128.9

127.2

128.1

126.2

129.3

127.2

T20





135.6



137.2



137.7



136.6



137.9

T30

±5

146.1

144.9

147.3

146.4

147.5

146.9

146.5

145.8

148.3

147.2

T40





152.6



154.7



155.6



153.5



155.0

T50

±5

196.7

192.9

207.2

205.1

206.3

204.8

202.1

199.8

161.7

161.5

T60





232.8



240.0



237.7



232.8



218.9

T70

±5

256.8

255.5

264.3

264.6

260.0

259.7

255.1

255.7

253.6

252.9

T80





280.7



292.8



283.2



279.9



278.6

T90

±5

313.9

312.0

331.5

331.9

313.3

315.6

314.1

312.0

311.6

311.3

T95





344.1



367.9



345.4



344.4



342.3

FBP

maximum

437

380.1

437

420.3

437

382.0

437

383.2

437

382.2

Residue, vol.%

%v

maximum

1.3

1.0

1.3

1.1

1.3

1.0

1.3

1.0

1.3

1.0

Recovery





97.4



97.9



97.8



98.1



98.1

Loss





1.5



1.5



1.6



1.5



1.5

Total Aromatics

%v

(Gage DHA)

±1

25.0

24.6

27.3

26.8

27.5

27.3

24.2

24.1

23.6

23.2

Benzene

±0.2

0.6

0.6

0.6

0.6

0.6

0.6

0.6

0.6

0.6

0.6

Toluene

± 1

6.3

6.2

6.1

6.0

7.1

7.3

6.1

6.0

7.9

5.9

C8 Aromatics

± 1

8.1

8.1

7.9

7.8

9.0

8.9

7.8

7.9

5.9

7.6

C9 Aromatics

± 1

5.5

5.3

5.4

5.2

6.3

6.0

5.4

5.2

5.2

5.0

C10 Aromatics

± 1

3.4

3.3

4.9

4.7

3.5

3.3

3.3

3.2

3.2

3.0

C11+ Aromatics

±0.3

1.1

1.2

2.4

2.5

1.1

1.2

1.1

1.2

1.0

1.2

PM Index byD6729



D6729





1.43



2.28



1 ;46



1.44



1.37

Total Aromatics

%v





25.1



27.7



27.3



24.8



24.1

Benzene





0.6



0.6



0.6



0.6



0.6

Toluene





6.7



6.5



7.8



6.3



6.4

C8 Aromatics





7.9



7.7



8.6



7.8



7.5

C9 Aromatics





5.4



5.4



6.0



5.4



5.2

C10 Aromatics





3.0



4.5



3.0



3.1



2.9

C11 + Aromatics





1.6



3.0



1.4



1.6



1.4

PM Index by D6730-1X



D6730-1X





1.48



0.00



1.53



1.45



1.41

Total Aromatics

%v





24.7



0.0



27.4



24.0



23.4

Benzene





0.6



0.0



0.6



0.6



0.6

Toluene





6.3



0.0



7.4



6.1



5.9

C8 Aromatics





7.9



0.0



8.8



7.7



7.6

C9 Aromatics





5.3



0.0



6.0



5.2



5.1

C10 Aromatics





3.0



0.0



3.0



2.9



2.8

C11 + Aromatics





1.5



0.0



1.5



1.5



1.5

Olefins

%m

D6550

±3

7

8.7

7

8.5

7

8.7

7

8.4

7

8.1

Sulfur

mq/kq

D5453

±3

7

6.3

7

6.0

7

6.0

7

6.1

7

5.8

Carbon (Part of D4809)

mass
%

D5291





82.62



82.98



82.99



82.82



80.86

Hydrogen (Part of
D4809)

mass
%

D5291





13.72



13.49



13.44



13.70



13.61

Carbon

mass
%

D3343M





82.70



82.98



82.96



82.71



80.99

Hydrogen

mass
%

D3343M





13.64



13.5



13.47



13.81



13.49

Water Content

mq/kq

E1064





1315



1259



1256



1314



1925

Lead

q/l

D3237



<0.013 q/l

<0.0027

<0.013 q/l

<0.0027

<0.013 q/l

<0.0027

<0.013 q/l

<0.0027

<0.013 q/l

<0.0027

Net Heat of
Combustion (D240)

MJ/kg

D240





41.58



41.63



41.56



41.78



40.74

Net Heat of Combustion •
D1319

MJ/kg

D3338





41.36



41.34



41.31



41.79



40.40

Oxidation Stability

minute

D525

minimum

240

>1,000

240

>1000

240

>1000

240

> 1000

240

> 1000

Copper Strip Corrosion,
3h at 122°F



D130

maximum

No. 1

1A

No. 1

1A

No. 1

1A

No. 1

1A

No. 1

1A

Solvent-Washed Gum
Content

mg/10
0 ml

D381

maximum

5

<0.5

5

<0.5

5

<0.5

5

<0.5

5

< 0.5

T(V/L20)

°F

D5188

minimum

116

128.7

116

129.7

116

130.3

116

129.8

116

129.3

Driveability Index



D4814

maximum

1250

1101

1250

1159

1250

1143

1250

1123

1250

1022

16


-------
2.2. Test Vehicles

The study included 10 vehicles selected in coordination with all 9 program participants. The principal guideline
adopted for vehicle selection was to develop a test fleet representative of propulsion system technologies
prevalent in the current on-road, light duty vehicle fleet. To this end, a concerted effort was made to select test
vehicles that covered a range of model years (2015-2022) and different emissions requirements (Tier 2 and Tier
3). Additional vehicle selection considerations included: popular U.S. sales models, variety of manufacturers,
vehicle mileage, body type (sedan/SUV/Truck), transmission (CVT/Automatic), and engine design features -
displacement, fuel injection (DI/PFI), aspiration (natural/forced), valvetrain, and EGR. All participants sourced
and inspected the vehicles they tested, with one participant testing two vehicles and the other eight participants
testing one vehicle each. A list of characteristics of the test vehicles is provided in Table 2.8.

Table 2.8. Vehicle test fleet.

Make

Honda

Toyota

Ford

GMC

Hyundai

Jeep

Toyota

Nissan

Honda

Dodge

Model

Civic

Camry

Expedition

Terrain

Tucson

Renegade

RAV4HV

Altima

Ridgeline

Ram 1500

MY

2016

2018

2015

2021

2022

2020

2019

2020

2020

2021

Odometer
[miles]

10,297

6,951

32,699

4,490

4,598

-3,000



4,500



2,990

Tier/Bin

IT3B125

T3B30

T2B5,
LDT4

T3B30

T3B70

T3B50

T3B30

T3B30

T3B125

T3B70

Engine
Displacement [11

1.5

2.5

3.5

1.5

2.5

1.3

2.5

2.5

3.5

5.7

Turbo

X

-

X

X

-

X

-

-

-

-

PFI

-

X

-



X

-

X

-

-

X

GDI

X

X

X

X

X

X

X

X

X

-

EGR

-

X

-

-

X

-

X

-

X

-

Atkinson/Miller

X

X

-

-

-

-

X

-

-

-

Transmission

CVT

Auto-8

Auto-6

Auto-9

Auto-8

Auto-9

CVT-6

CVT

Auto-9

Auto-8

Body type

Sedan

Sedan

SUV

SUV

SUV

SUV

SUV

Sedan

Truck

Truck

Fuel Tank
Capacity [gal]

12.4

16

28

15.6

14.3

15.3

14.5

16.2

19.5

21.6

City FE [mpg]

27

32

14

24

24

23

41

26

22

15

Recommended
Octane [AKI|

>87

>87

87

87

87

87

87

87

87

87

2.3. Emissions Testing: Procedures and Guidelines

Vehicle emissions testing was conducted at nine different test sites, one per each program participant. Some
labs used the same test cell and driver for all tests, while others used multiple cells and drivers. At least one lab
used a robotic vehicle operator.

As noted in Section 3.2, one participant tested two vehicles while the remaining eight participants tested one
vehicle each. Emissions testing at all nine test facilities was conducted in accordance with measurement
instruments, analytical gas specifications, chassis dynamometer specifications, vehicle preparation and test

17


-------
procedures in compliance with CFR Title 40 Part 1066^All participating test facilities are experienced in
conducting fuel economy and tailpipe emissions certification testing.

As described in Section 2, the primary focus of this test program was to evaluate the impact on tailpipe PM
emissions of replacing the heavy hydrocarbons contributing to the tail of the gasoline distillation curve with
lower PMI components. With this program objective in mind and the goal of reducing variability in the
measured emissions data, all program participants agreed to follow common guidelines and test procedures,
which are outlined in the following sub-sections.

2.3.1. Test Cycles

As per the Code of Federal Regulation (CFR) Title 40 Part 86 Section 86.1181-04 (Tier 2) and 86.1181-17 (Tier
3), exhaust emissions standards for Particulate Matter are defined based on the FTP (Figure 2.4) and the US06
(Figure 2.5) drive cycles. Consequently, the PM emissions data available in literature and EPA databases,
largely focus on the FTP and US06 drive cycles. Considering the CFR requirements and the availability of
historical PM emissions data for the FTP and US06 drive cycles, the current study also focused on collecting
emissions data for the two aforementioned test cycles.

100

•FTP

Q.

E

80

Bag 1

505s
Cold Start

Bag 2

864s

Hot Soat

(600s);

Bag 3

505s
Hot Start

600	1200

Time (sec)

1800

2400

Figure 2.4. U.S Federal Test Procedure (FTP).

18


-------
Figure 2.5. Supplemental FTP or US06.

2.3.2. Dilution Tunnel Cleanliness

Most of the participating test facilities were supporting other programs in parallel, whereby the background PM
level in the dilution and sampling system could be varying over the course collecting data for this study. To
address such concerns, the procedure outlined in Table 2.9 was recommended for tracking background levels.
This procedure was implemented by some participants, while others tracked background using procedures
already in place at their labs. Additionally, the participating labs were encouraged to schedule drive cycles with
higher loads, such as US06, in the test cell prior to test execution for the current study. The premise of this
recommendation was that high-temperature and/or flow operations would tend reduce the likelihood of tailpipe
PM measurements being contaminated by residual PM in the dilution tunnel.

Table 2.9. Tunnel background PM sampling procedure, to be performed once a week.

Step

Description

1

Load a preconditioned Teflon filter into the PM sampler and perform a leak
check.

2

Cap the inlet of vehicle exhaust into the CVS system and run Phase 1 of the
FTP-75 test cycle (the 505) while sampling PM.

3

Report background filter number, test number as well as the accumulated filter
weight in mg and mg/mile to the test engineer.

19


-------
2.3.3.	Drivers

While most test facilities used human drivers, a couple of the test facilities used robot drivers for executing the
vehicle test plan. In order to minimize test-to-test variability, all program participants were encouraged to avoid
switching drivers between tests. Where possible, the program participants attempted to retain the same driver
from their respective test facilities for all the tests. However, scheduling requirements at the respective test
facilities did not always permit the use of the same driver.

2.3.4.	Test Fuel Sequence

For each test vehicle, the fuel sequence started and ended with Fuel A to allow for a means to check for drift in
the measurements over the duration of the test program. However, to minimize the risk of the study's
conclusions being influenced by the order in which the fuels were tested, the sequence in between the first and
last fuel (Fuel A) was randomized for each vehicle, as illustrated in Table 2.10. Four vehicles were not tested on
Base fuel.

Table 2.10. Fuel testing sequence for each vehicle.

Make

Honda

Toyota

Ford

GMC

Hyundai

Jeep

Toyota

Nissan

Honda

Dodge

Model

Civic

Camry

Expedition

TERRAIN

Tucson

Renegade

RAV4 HV

Altima

Ridgeline

Ram 1500

MY

2016

2018

2015

2021

2022

2020

2019

2020

2020

2021

Fuel Test
Sequence

ACB(Base)DA

ABD(Base)CA

ADB(Base)CA

ACDB(Base)A

ACBDA

ABCDA

ADCBA

ABDCA

AD(Base)CBA

ABD(Base)CA

2.3.5. Vehicle Fuel Change and Test Preparation

In view of the current study's focus of measuring changes in tailpipe emissions from small changes in fuel
composition, special care was taken to avoid the contamination of measurements for one fuel with another. To
this end, all program participants adhered to the fuel change and vehicle preparation procedure outlined in Table
2.11.

20


-------
Table 2.11. Fuel change and vehicle preparation procedure.

Step

Description

1

With the ignition key in OFF position, drain vehicle fuel tank to empty.

2

Fill fuel tank to 20% with next test fuel in sequence.

3

With the ignition key in OFF position, drain vehicle fuel again to empty.

4

Fill the fuel tank to 55%.

5

Run a LA4 (UDDS) prep cycle followed by a HWFETx2 prep cycle and a US06x2
prep cycle. Following the US06 cycle, allow the vehicle to idle in neutral for two
minutes, then shut the engine off in preparation for the soak.

Note: Program participants are encouraged to log the following OBD2 parameters
during both parts of LA4 and US06 prep cycles for use in quality control of
emissions test results: Engine rpm, vehicle speed, engine load, short term fuel trim
- bank 1, long term fuel trim - bank 1, MIL status, absolute throttle position,
engine coolant temperature, fuel/air commanded equivalence ratio, manifold air
flow, spark timing, PID $42 control module voltage, purge duty cycle.

6

Move vehicle to soak area without starting the engine (or leave on dyno for soak).

7

Soak vehicle at nominal 75°F for a minimum of 12-28 hours. Record soak
temperature and duration.

Note: During the soak oeriod, maintain the nominal charge of the vehicle's batterv
using an appropriate charging device.

2.3.6. Emissions Testing Procedures

To minimize lab-to-lab variability in emissions measurements, a detailed step-by-step vehicle test procedure
was defined at the start of the study. All program participants strictly adhered to the procedure outlined in Table
2.12.

21


-------
Table 2.12. Vehicle test procedure.

Step

Description



Following a soak of 12-28 hours at nominal 75°F, perform the following:

1

1.	Check vehicle diagnostic trouble codes. Notify project engineer if any are
detected.

2.	Check tire pressure and adjust, if necessary.

Note: Record soak temperature and duration and include in test report.

2

Move vehicle to test area without starting engine.

3

Perform FTP-75 (3 phase) test followed by a US06x2 test. Collect separate PM
samples for each of the three phases of the FTP-75 test. Similarly, collect separate
PM samples for Highway and City portions of the US06 test. However, sampling
PM through the whole FTP-75 or US06 test (with appropriate adjustments in
flowrate) will be treated as equivalent in this study. Following the US06 cycle,
allow the vehicle to idle in neutral for two minutes, then shut the engine off in
preparation for the soak.

4

Move vehicle to soak area without starting the engine (or leave on dyno for soak).



Park vehicle in soak area for 12-28 hours at nominal 75°F.

5

Note: During the soak oeriod, maintain the nominal charge of the vehicle's battery
using an appropriate charging device.

6

Move vehicle to test area without starting the engine. Record soak temperature and
duration and include in test report.



Repeat Steps 3-7 a minimum of 4, but preferably 6 times.



Note: If 28 hour soak has been exceeded between tests, perform the following as
early as possible:

7

1.	Fill the fuel tank to 40% of tank volume with the same fuel.

2.	Run a LA4 (UDDS) prep cycle followed by a US06x2 prep cycle.

3.	Check vehicle diagnostic trouble codes. Notify project engineer if any are
detected.

4.	Park vehicle in soak area for 12-28 hours at nominal 75°F.

Note: During the soak period, maintain the nominal charge of the vehicle's
battery using an appropriate charging device

5.	Following the soak, check tire pressure and adjust, if necessary, and
proceed to Step 3.

2.3.7. Particulate Matter (PM) Measurement

The following subsections briefly describe the PM measurement techniques used by the program participants
during data collection for this study.

22


-------
2.3.7.1.	Gravimetric

Gravimetric PM mass emission measurements were made in all facilities (with one exception) by sampling the
tunnel-diluted exhaust using Teflon filters following Code of Federal Regulations Title 40, Part 1065. Labs
used either a single filter for all drive cycle phases (bags) or separate filters for each phase. Blank filters of the
tunnel dilution air were collected and analyzed, but no blank correction was applied to the results.

2.3.7.2.	OC/EC

In one facility, particulate mass was determined using an organic carbon/elemental carbon (OC/EC) method.
PM was captured from diluted exhaust on a prebaked quartz filter. Multiple cut-outs from the filter were
analyzed by thermal analysis using a Horiba MEXA 1370PM particulate analyzer. CO: measured after heating
to 980°C, first under nitrogen and then with oxygen present, is converted to masses of organic carbon and
elemental carbon, respectively, and their sum provides a measure of total PM [12], Blank filters (with and
without sampling the dilution air) were collected and analyzed, but no blank correction was applied to the
results.

2.3.7.3.	AVL MicroSoot Sensor (MSS)

In addition to Teflon filter based gravimetric measurements, all program participants were encouraged to collect
PM data using an MSS, with the objective of helping validate trends observed in filter PM data. However, not
all participating test facilities were adequately equipped for making MSS measurements. Consequently, MSS
data is not available for all vehicles and has been used in this study only for diagnostic purposes where
available.

2.4. Vehicle Emissions Results

The following subsections present detailed data review and statistical analysis for PM, NOx, NMOG, and CO2
emissions. All the analyses used FTP and US06 cycle composite values with phase weighting as described in 40
CFR Part 1065/1066. Observations of statistical significance for model parameters and comparisons are based
on the p < 0.05 criterion.

Two levels of results are presented for each cycle and emission. The first is a PM Index (PMI) model that draws
information from across all the test fuels. This result is of interest because PMI was a primary design parameter
for the fuel set and is a good predictor of PM emissions. However, this approach does not control for (attempt to
separate) potential impacts of other fuel parameters such as ethanol content or total aromatics. The second level
of results is a set of fuel-to-fuel comparisons that evaluate the overall impact of each formulation. This approach
fully quantifies the differences between each fuel but doesn't attempt to associate it with any particular
parameter. Results for additional emissions are provided in Appendix A.

2.4.1. Particulate Emissions

The particulate matter (PM) results presented in this report were not background corrected, meaning there was
no subtraction of filter weights collected from background air or blank tests. During the test program, each lab
followed its normal practices to monitor background PM levels and ensure good data quality in the reported PM
values.

The sections that follow provide a detailed statistical analysis of the PM emissions data both for the FTP cycle
and the US06 cycle. The results are also summarized at a high level in Figure 2.6 and Figure 2.7. These figures
show the percent reduction in PM emissions for each vehicle (and for the average of the test vehicle fleet) when
switching from fuel A (containing 7.4 %v C10+ aromatics) to fuels B, C, D, and the base fuel (each containing

23


-------
4.2-4.5 %v C10+ aromatics). For these fuels with reduced C10+ aromatic content, the average PM emission
reductions were 35-45% on the FTP Composite cycle and 20-25% on the US06 cycle for the 10 vehicles in this
study.1

120%

100%

80%

60%

40%

20%

0%

Fuel A

C10+aromatics: 7.4%

0)
3

o

0s-





o







o









8r

i-

o
&

o



a

r>

1"

V7

a

5T







w













Vehicle

OVeh_A
OVeh_B
OVeh_C
OVeh_D
OVeh_E
OVeh_F
OVeh_G
OVeh_H
OVehJ
OVehJ
h Average

Fuel B
4.5%

Fuel C
4.4%

Fuel D

4.2%

Base Fuel
4.5%

Figure 2.6. Summary of PM emissions reductions for the FTP cycle for each test fuel (relative to Fuel A),
shown by vehicle and for the test fleet average with 95% confidence interval.

120%

100%

"5 80%

3

o

"-•8

60%

40%

20%

0%

Fuel A

C10+aromatics: 7.4%





0

















@1

o



Or



T

I"

o
g



+



o
o

o

o



o







o













Fuel B
4.5%

Fuel C
4.4%

Fuel D
4.2%

Base Fuel
4.5%

Vehicle

OVeh_A
OVeh_B
OVeh_C
OVeh_D
OVeh_E
OVeh_F
OVeh_G
OVeh_H
OVehJ
OVehJ
^Average

Figure 2.7. Summary of PM emissions reductions for the US06 cycle for each test fuel (relative to Fuel A),
shown by vehicle and for the test fleet average with 95% confidence interval.

Table 2.13 presents percent-PM-emission per percent-PMI sensitivities (ratios) by test cycle and vehicle. The
vehicles are sorted from smallest to largest effect for the FTP and span a range of approximately 1.0 to 2.2. For
the US06 cycle, the range is approximately 0.5 to 2.3 if the value for Veh_G is excluded. (A review of data for

1 Fuel C results for VehD indicate an upward shift from Fuel A, in contrast to all other test vehicles. While these results are
unexpected, no anomalies were reported in the test procedures or vehicle operation for those measurements, thus they were retained in
the dataset.

24


-------
VehG finds it has a relatively low sensitivity to PMI over the US06, which allowed a few influential
measurements to tip the average value in the opposite direction of the other vehicles.)

Table 2.13. Percent-PM-emissions per percent-PM-Index sensitivities by test cycle and vehicle.



Veh H

Veh E

Veh A

VehC

Veh D

VehJ

Veh B

Veh F

VehJ

VehG

FTP

1.01

1.08

1.20

1.21

1.34

1.47

1.55

1.66

1.83

2.15

US06

0.51

0.44

1.67

0.80

1.15

1.42

0.64

1.22

2.27

-0.12

FTP Cycle Results

Figure 2.8 and Figure 2.9 provide a graphical overview of the measurements collected on the FTP cycle,
grouped by vehicle, on linear and log scales, respectively. The axis label "index" refers to the count of
individual observations. For the FTP cycle, the vehicle means range from under 0.5 mg/mi to about 7 mg/mi,
with individual vehicles spanning up to 5 mg/mi over their fuel and replicate sets.







Vehicle





o Veh.

_A

o Veh_B

o Veh_C

o Veh_D

o Veh_E

o Veh.

_F

o Veh_G

o Veh_H

o VehJ

o Veh_J

Figure 2.8. FTP PM dataset by vehicle, linear scale.

25


-------
Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o VehJ o Veh_J

Figure 2.9. FTP PM dataset by vehicle, log scale. Arrows indicate data removed from the analysis.

In Figure 2.9 five points are marked that were removed from the dataset before further analysis, on the basis
that they were sufficiently low or high as to indicate a procedural or instrumentation issue with those particular
tests. Figure 2.10 plots the remaining data as vehicle means by fuel (four of the vehicles did not test Base Fuel).
Figure 2.11 shows vehicle means by PM Index and indicates that all vehicles had an upward PM trend between
the low and high PM Index levels. It is notable that Veh B, Veh_C, and Veh_E showed an upward trend for
Fuel D, despite it having the lowest PMI. Table 2.14 summarizes the number of measurements collected and
analyzed for each vehicle.

26


-------
Fuel

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o Veh_l o Veh_J

Figure 2.10. FTP PM data as vehicle means by fuel, log scale.

Figure 2.11. FTP PM data as vehicle means by PM Index, log scale.

27


-------
Table 2.14. Number of PM measurements collected and analyzed in the FTP cycle data analysis.



VehA

VehB

VehC

VehD

VehE

VehF

VehG

VehH

Veh_I

VehJ

Total

Measurements
collected

20

21

26

26

30

24

29

32

22

26

256

Measurements
removed

0

0

1

0

1

0

0

0

0

3

5

Final dataset

20

21

25

26

29

24

29

32

22

23

251

Data analysis was performed using the SAS software package (current version). All emissions data were log-
transformed before model fitting began, with the exception of CO2. This is a common practice, as vehicle
emissions tend to follow approximately log-normal distributions. In addition, this transformation is a standard
approach to normalizing the distributions of residuals and stabilizing their variance across a range of emission
levels.2

The SAS Mixed procedure was used with the restricted maximum likelihood (REML) method in an initial
round of model fitting to examine the behavior of residuals and assess the effect of generating covariance
parameters specific to each vehicle. Adding these parameters produced a meaningful improvement in fit,
therefore this feature was retained in the final model fitting.

Figure 2.12 indicates conditional studentized residuals are approximately normally distributed with minimal
deviation across quantiles. Figure 2.13 shows the range of externally studentized residuals, where levels of ± 3.5
are commonly used as a screen for "outlier points". Results indicate all points fall within the acceptable range.

-1	0	1

Predicted



£3^

-1.8 -0.6 0.6 1.8
Residual

Quantile

Residual Statistics

Observations

251

Minimum

-2.941

Mean

-0.003

Maximum

2.4784

Std Dev

1.0022

Fit Statistics



Objective

-36.25

AIC

-14.25

AICC

-13.14

BIC

-10.93

Figure 2.12. Analysis of conditional studentized residuals for FTP cycle PM data.

2 Additional discussion is available in Section 5.1 of the EPAct study report, EPA-420-R-13-002, April 2013.

28


-------
0	50	100	150	200	250

Deleted Obs. Index

Figure 2.13. Externally studentized residuals for PM FTP cycle data.

Following this initial analysis, the model was refit using the maximum likelihood method to generate the
intercept and fixed effect coefficient for the PMI fuel term. The model parameters and related fit statistics are
presented in Table 2.15. These results indicate that PMI is a highly significant predictor of PM emissions, and
they can be used to compute a relative difference of 1.45 percent in vehicle PM emissions per percent PMI
change as the overall study result.

Table 2.15. Fixed effect model parameters for FTP PM.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

-0.5117

0.3084

10.2

-1.66

0.1274

PMI

0.3779

0.0176

113

21.48

<0001

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
2.16 presents least squares means for fuel pairs.

29


-------
Table 2.16. Differences in least squares means by fuel for FTP PM.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

Adjusted
P

A

B

0.3224

0.0257

85.6

12.54

<0001

A

C

0.5046

0.0258

84.9

19.59

<.0001

A

D

0.4975

0.0253

86.3

19.65

<0001

A

Base

0.4397

0.0370

81.3

11.88

<0001

B

C

0.1822

0.0295

84.3

6.17

<0001

B

D

0.1751

0.0291

85.4

6.01

<.0001

B

Base

0.1173

0.0398

93.3

2.95

0.0321

C

D

-0.0071

0.0292

84.9

-0.24

0.9992

C

Base

-0.0649

0.0399

93.3

-1.63

0.4833

D

Base

-0.0578

0.0394

88.7

-1.47

0.5870

Differences should be interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer
adjustment for multiple comparisons. These results indicate that Fuel A produced significantly higher PM than
the other fuels, and Fuel B produced significantly higher PM than Fuels C, D, and Base. Differences among
Fuels C, D, and Base were not significant.

11 SO 6 Cycle Results

The presentation of the US06 PM results follows the same outline as for the FTP cycle. Figure 2.14 and Figure
2.15 provide a graphical overview of the measurements collected on the US06 test cycle, grouped by vehicle, on
linear and log scales, respectively. The axis label "index" refers to the count of individual observations. For this
test cycle, the vehicle means range from under 0.5 mg/mi to about 4 mg/mi, with individual vehicles spanning
up to about 5 mg/mi over their fuel and replicate sets.

index







Vehicle



o Veh_A

o Veh.

.B

o Veh_C o Veh_D

o Veh_E

o Veh_F

o Veh]

G

o Veh_H o VehJ

o Veh_J

Figure 2.14. US06 PM dataset by vehicle, linear scale. Arrows indicate data removed from the analysis.

30


-------
1

o

o

-2

-3

T

~ T

o

o o

T

0

50

100

150

200

250

index

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o VehJ o Veh_J

Figure 2.15. US06 PM dataset by vehicle, log scale. Arrows indicate data removed from the analysis.

Across these two plots are marked five points that were considered candidates for removal from the dataset on
the basis that they were sufficiently low or high as to indicate a procedural or instrumentation issue with those
particular tests. On the log plot, the uppermost point for Veh C looks plausibly like the upper edge of its typical
operation, while on the linear plot it appears to be significantly higher than the other measurements. Review of
gaseous data including CO2 found nothing unusual for that test. However, a plot of MicroSoot Sensor (MSS)
results versus PM (Figure 2.16) shows this point (orange triangle) sitting far off the correlation trend observed
for this vehicle's other US06 tests. Thus, all five points were removed on the basis of procedural or analytical
problems.

31


-------






•











— «l

•



~





• •







•

•

y =

= 1.0158x + 0.873"

1



*

•



R2 = 0.

8039



















23456789

Filter PM (mg/mi)

Figure 2.16. Comparison of MicroSoot Sensor and PM data for Veh C. Triangular point indicates a

measurement far away from the correlation trend.

Figure 2.17 plots the remaining data as vehicle means by fuel (four of the vehicles did not test Base Fuel).
Figure 2.18 shows vehicle means by PM Index, where most vehicles indicate an upward PM trend between the
low and high PM Index levels. However, three vehicles (Veh B, Veh G, and VehJ) produced PM levels from
Fuel D that were equal to or greater than on Fuel A, despite Fuel D having the lowest PMI. Table 2.17
summarizes the number of measurements collected and analyzed for each vehicle.

Fuel

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o VehJ o VehJ

Figure 2.17. US06 PM data as vehicle means by fuel, log scale.

32


-------
-1.0

1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00

PMI
Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o VehJ o Veh_J

Figure 2.18. US06 PM data as vehicle means by PM Index, log scale.

Table 2.17. Number of PM measurements collected and analyzed in the US06 cycle model fitting.



VehA

VehB

VehC

VehD

VehE

VehF

VehG

VehH

Veh_I

VehJ

Total

Measurements
collected

20

23

26

25

30

25

31

33

23

22

258

Measurements
removed

0

1

1

0

0

0

0

1

0

2

5

Final dataset

20

22

25

25

30

25

31

32

23

20

253

Data analysis and model fitting proceeded in the same manner as for the FTP cycle as described above,
including log transformation of the data and generation of covariance parameter estimates on a per-vehicle
basis. Figure 2.19 indicates conditional studentized residuals are approximately normally distributed with
minimal deviation across quantiles. Figure 2.20 shows the range of externally studentized residuals, where
levels of ± 3.5 are commonly used as a screen for "outlier points". Results indicate all points fall within the
acceptable range.

33


-------
2
1

"to

5 0

cf)
d)

oc -1

-2
-3

o

o o

o ,

A § Si°

.

3

K

0 I

° o

S°o°

fl

yH ° o o
& as & 8

° 8 ^

o

o

o

13 » .

S

° o

o

o

3 0

a>
a:

-2

0

Predicted



o° °

£







o °



25 -

20

e 15
£

£ io-

5
0



-J

-0.9 0.3
Residual

-1 o
Quantile

Residual Statistics

Observations

253

Minimum

-2.839

Mean

-0.003

Maximum

2.6807

Std Dev

1.0022

Fit Statistics



Objective

198.3

AIC

220.3

AICC

221.4

BIG

223.63

Figure 2.19. Analysis of conditional studentized residuals for US06 cycle PM data.

4

"S

N

ft,
C

£
X

LU

2-



%

cPor>o

o o,

00

&



o	o

oo

o° oo* ° o°i

oo

~T$

°iSL0

tfp Oft ^

o

fb

o

,o

-2 -

o o

>Q&

o
, °o

/q
%



cP

oO
o

oo

O o

50

100

150

Deleted Obs. Index

200

250

Figure 2.20. Externally studentized residuals for US06 cycle PM data.

The intercept and fixed effect coefficient for the PMI fuel term are presented in Table 2.18. These results
indicate that PMI is a highly significant predictor of PM emissions, and can be used to compute a relative
difference of 1.0 percent in vehicle PM emissions per percent PMI change as the overall study result for the
US06 test cycle.

34


-------
Table 2.18. Fixed effect model parameters for US06 PM.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

-0.5799

0.2373

11.5

-2.44

0.0317

PMI

0.2208

0.0346

191

6.38

<0001

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
2.19 presents least squares means for fuel pairs.

Table 2.19. Differences in least squares means by fuel for US06 PM.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

Adjusted
P

A

B

0.2583

0.0584

189

4.42

0.0002

A

C

0.2177

0.0596

186

3.65

0.0031

A

D

0.3374

0.0569

169

5.92

<.0001

A

Base

0.2618

0.0731

126

3.58

0.0043

B

C

-0.0406

0.0680

189

-0.60

0.9753

B

D

0.0791

0.0656

176

1.21

0.7478

B

Base

0.0035

0.0801

142

0.04

1.0000

C

D

0.1197

0.0667

174

1.80

0.3794

C

Base

0.0442

0.0809

143

0.55

0.9823

D

Base

-0.0756

0.0790

134

-0.96

0.8742

Differences are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer adjustment for
multiple comparisons. These results indicate that Fuel A produced significantly higher PM than the other fuels,
but that differences between other fuels were not significant.

2.4.2. NOx Emissions
FTP Cycle Results

Figure 2.21 and Figure 2.22 provide a graphical overview of NOx measurements collected on the FTP cycle,
grouped by vehicle, on linear and log scales, respectively. The axis label "index" refers to the count of
individual observations. Vehicle means range from about 2 mg/mi to about 30 mg/mi, with individual vehicle
ranges smaller from a few mg/mi to over 30 mg/mi. Veh_C shows especially high variability over its replicates.

35


-------
X

O

0.05

0.04

~ 0.03

0.02

0.01

0.00

o o
o

0°0

cQo

oo

° <8

¦><£> °

Jo o

8>



k

8%°

50

100

150

200

250

index

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o Veh I o Veh_J

Figure 2.21. FTP NOx dataset by vehicle, linear scale.

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_N o Veh_l o Veh_J

Figure 2.22. FTP NOx dataset by vehicle, log scale.

Figure 2.23 plots the data as vehicle means by fuel (four of the vehicles did not test Base Fuel). Figure 2.24
shows vehicle means by PM Index, where some vehicles have increasing NOx trends with PM Index, and
others flat or decreasing. Table 2.20 summarizes the number of measurements collected and analyzed for each
vehicle.

36


-------
u>
o

-2.25

-2.50

I

B



l

Base
Fuel

i

C





Vehicle



o Veh A

o Veh B

o Veh C o Veh D

o Veh E

o Veh_F

o Veh_G

o Veh_H o VehJ

o Veh_J

Figure 2.23. FTP NOx data as vehicle means by fuel, log scale.

X

o

o>
o

-1.5

-2.0

-2.5

-3.0

1.00

1.25

1.50

1.75

2.00
PMI

2.25

2.50

o Veh_A o Veh_B
o Veh F o Veh G

Vehicle

o Veh_C o Veh_D o Veh_E
o Veh H o Veh I o Veh J

2.75

3.00

Figure 2.24. FTP NOx data as vehicle means by PM Index, log scale.

37


-------
Table 2.20. Number of NOx measurements collected and analyzed in the FTP cycle model fitting.

VehA

VehB

VehC

VehD

VehE

VehF

VehG

VehH

Veh_I

VehJ

Total

20

21

26

26

30

24

29

32

22

26

256

Data analysis was performed using the SAS software package (current version). All NOx emissions data were
log-transformed before model fitting began. This is a common practice, as vehicle emissions tend to follow
approximately log-normal distributions. In addition, this transformation is a standard approach to normalizing
the distributions of residuals and stabilizing their variance across a range of emission levels.3

The SAS Mixed procedure was used with the restricted maximum likelihood (REML) method in an initial
round of model fitting to examine the behavior of residuals and assess the effect of generating covariance
parameters specific to each vehicle. Figure 2.25 indicates conditional studentized residuals are approximately
normally distributed with some minor deviation toward the upper tail. Figure 2.26 shows the range of externally
studentized residuals, where levels of ± 3.5 are commonly used as a screen for "outlier points". Results indicate
all points fall within the acceptable range.

O

° o

o

° o9io
o o o

=8



S I1

§

o

-I ? 1

5 I

o ® ^

o

o

o

Predicted

Residual

4

-3-2-10123
Quantile

Residual Statistics

Observations

256

Minimum

-3.161

Mean

-0.002

Maximum

3.6415

Std Dev

1.0027

Fit Statistics



Objective

-95.93

AIC

-73.93

AICC

-72.84

BIC

-70.6

Figure 2.25. Analysis of conditional studentized residuals for FTP cycle NOx data.

3 Additional discussion is available in Section 5.1 of the EPAct study report, EPA-420-R-13-002, April 2013.

38


-------
03

a:

"S

OJ

x
LU

4

2-

&

<$&
CO

o

o S



"°o°o

oo °e,

-2 -

Jfe

o

°oV

qO OO
%°

^ °

rl^ R°°
CPop S o

® O^OO

-4

50

100	150

Deleted Obs. Index

200

250

Figure 2.26. Externally studentized residuals for FTP cycle NOx data.

Following this initial analysis, the model was refit using the maximum likelihood method to generate the
intercept and fixed effect coefficient for the PMI fuel term. The model parameters and related fit statistics are
presented in Table 2.21. These results indicate that PMI is not a significant predictor of NOx emissions in the
FTP.

Table 2.21. PMI model parameters for FTP NOx.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

-4.5537

0.2312

10.2

-19.69

<0001

PMI

-0.02484

0.01514

145

-1.64

0.103

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
2.22 presents differences of least squares means for fuel pairs.

39


-------
Table 2.22. Differences in least squares means by fuel for FTP NOx.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

Adjusted
P

A

B

-0.0287

0.0259

140

-1.11

0.8029

A

C

-0.0322

0.0258

139

-1.25

0.7233

A

D

-0.0378

0.0255

143

-1.48

0.5745

A

Base

-0.0076

0.0367

98.5

-0.21

0.9996

B

C

-0.0036

0.0298

138

-0.12

1.0000

B

D

-0.0091

0.0295

141

-0.31

0.9980

B

Base

0.0210

0.0397

109

0.53

0.9841

C

D

-0.0056

0.0295

140

-0.19

0.9997

C

Base

0.0246

0.0396

108

0.62

0.9714

D

Base

0.0302

0.0394

109

0.77

0.9397

Differences are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer adjustment for
multiple comparisons. These results show no significant differences between any fuel pairs.

11 SO 6 Cycle Data

The presentation of the US06 NOx results follows the same outline as for the FTP cycle. Figure 2.27 and Figure
2.28 provide a graphical overview of the measurements collected on the US06 test cycle, grouped by vehicle, on
linear and log scales, respectively. The axis label "index" refers to the count of individual observations. For this
test cycle, vehicle means range from about 3 mg/mi to about 32 mg/mi, with individual vehicle ranges smaller
spanning up to about 15 mg/mi.

0.04

0.03 -

~ 0.02
x

0.01 -

0.00

0	50	100	150	200	250

index



Vehicle



o Veh_A o Veh_B

o Veh_C o Veh_D

o Veh_E

o Veh_F o Veh_G

o Veh_H o VehJ

o VehJ





w ' 0

O

%

o
o

° * °

°	o	s>

O e°ORto0°0o ^%°°°

O	o 00 0 <£&

o o	° I	° ° ^<9

<5$	„ o

o

„ Q	O GCC1 Qii3D

o o	on 00

o° %'o	o°°T

Figure 2.27. US06 NOx dataset by vehicle, linear scale.

40


-------
o

O)

o

-1.50

-1.75

-2.00

-2.25

-2.50



















°

° o° °

o







o
o

a

o °
o

° °°0 o°

° °°°o o<^

o





°
-------
Fuel

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
|_o Vet^F o Veh_G o Veh_H o Veh_l o Veh_J

Figure 2.29. US06 NOx data as vehicle means by fuel, log scale.

o

o

-j	1	1	1	i		

1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00

PMI
Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o Veh_l o Veh_J

Figure 2.30. US06 NOx data as vehicle means by PM Index, log scale.

42


-------
Table 2.23. Number of NOx measurements collected and analyzed in the US06 cycle model fitting.

VehA

VehB

VehC

VehD

VehE

VehF

VehG

VehH

Veh_I

VehJ

Total

20

23

26

25

30

25

31

33

23

22

258

Data analysis and model fitting proceeded in the same manner as for the FTP cycle as described above,
including log transformation of the data and generation of covariance parameter estimates on a per-vehicle
basis. Figure 2.31 indicates conditional studentized residuals are normally distributed with minimal deviation
across quantiles. Figure 2.32 shows the range of externally studentized residuals, where levels of ± 3.5 are
commonly used as a screen for "outlier points". Results indicate all points are well within the acceptable range.

O

„ o

- o ® o °

0	o o o O Q

,-Sjs 0 o

° 25o °o

01	S g 8°o

o SP0 °Q |g

o

o

°g 8

i f

00 °oo 8 D
o
8 O

1 0° |i

jo lo 08

!° O i
~ O
O °

O

-5.5 -5.0 -4.5

Predicted

-4.0 -3.5

3 

01

-2 -

-1 0 1
Quantile

25

15

cl 10

M

-3.3

-2.1

-0.9 0.3
Residual

1.5

2.7

Residual Statistics



Observations

258

Minimum

-2.6&8

Mean

-0.002

Maximum

2.916

Std Dev

1.0027

Fit Statistics



Objective

-93.53

AIC

-71.53

AICC

-70.45

BIC

-68.2

Figure 2.31. Analysis of conditional studentized residuals for US06 cycle NOx data.

43


-------
03

a:

"S

OJ

x
LU

-4

100	150

Deleted Obs. Index

Figure 2.32. Externally studentized residuals for US06 cycle NOx data.

The solution for fixed effects for the PMI fuel parameter model is presented in Table 2.24. These results
indicate that PMI is a statistically significant predictor of NOx emissions. These results can be used to compute
a relative difference of 0.25 percent in vehicle NOx emissions per percent PMI change as the overall study
result for the US06 test cycle.

Table 2.24. Fixed effect model parameters for US06 NOx.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

-4.8007

0.2084

10.4

-23.03

<0001

PMI

0.0452

0.01353

112

3.34

0.0011

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
2.25 presents differences of least squares means for fuel pairs.

44


-------
Table 2.25. Differences in least squares means by fuel for US06 NOx.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

Adjusted
P

A

B

-0.0287

0.0259

140

-1.11

0.5519

A

C

-0.0322

0.0258

139

-1.25

0.0338

A

D

-0.0378

0.0255

143

-1.48

0.0225

A

Base

-0.0076

0.0367

98.5

-0.21

0.5576

B

C

-0.0036

0.0298

138

-0.12

0.6996

B

D

-0.0091

0.0295

141

-0.31

0.6527

B

Base

0.0210

0.0397

109

0.53

0.9873

C

D

-0.0056

0.0295

140

-0.19

1

C

Base

0.0246

0.0396

108

0.62

0.9938

D

Base

0.0302

0.0394

109

0.77

0.9922

Differences are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer adjustment for
multiple comparisons. These results show significant differences between fuel pairs A-C and A-D.

2.4.3. NMOG Emissions
FTP Cycle Data

Figure 2.33 and Figure 2.34 provide a graphical overview of NMOG measurements collected on the FTP cycle,
grouped by vehicle, on linear and log scales, respectively. The axis label "index" refers to the count of
individual observations. Vehicle means cover a wide range, from about 1 mg/mi to about 45 mg/mi, with
individual vehicle ranges around 1 mg/mi to over 20 mg/mi.

0.05

0.04

0.03

0.02

0.01











O O

P ° °
% °





O







<$> O

o o
° o

o





o o
o

°o°° %

o







od

&

°o°°



°£&oc

&

o





£



pm&°£0 f



o

o







50

100

150

200

250

index



Vehicle



o Veh_A o Veh_B

o Veh_C o Veh_D

o Veh_E

o Veh_F o Veh_G

o Veh_H o Veh_l

o Veh_J

Figure 2.33. FTP NMOG dataset by vehicle, linear scale.

45


-------
-1.25

-1.50

O -1.75
O

o -2.00

-2.25

-2.50

o

o 0o

8$° &

o

O O

%\°

"o?



°Q O

afro



$0 <£,

o o 9
%> ¦

vp-i? °°°

o

°o8c
o

p

o

5



° o cd2
oo



° g** o







I I



I I

50

100

150

200

250

index



Vehicle



o Veh_A o Veh_B

o Veh_C o Veh_D

o Veh_E

o Veh_F o Veh_G

o Veh_H o VehJ

o VehJ

Figure 2.34. FTP NMOG dataset by vehicle, log scale.

Figure 2.35 plots the data as vehicle means by fuel (four of the vehicles did not test Base Fuel). Figure 2.36
shows vehicle means by PM Index, where some vehicles have increasing NMOG trends with PM Index, and
others flat or decreasing. Table 2.26 summarizes the number of measurements collected and analyzed for each
vehicle.

Fuel

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o VehJ o Veh_J

Figure 2.35. FTP NMOG data as vehicle means by fuel, log scale.

46


-------
1

1 50

i

1 75

i

2.00
PMI

i i

2.25 2.50





Vehicle



o Veh A

o Veh B

o Veh C

o Veh D o Veh E

o Veh_F

o Veh_G

o Veh_H

o VehJ o Veh_J

Figure 2.36. FTP NMOG data as vehicle means by PM Index, log scale.

Table 2.26. Number of NMOG measurements collected and analyzed in the FTP cycle model fitting.

VehA

VehB

VehC

VehD

VehE

VehF

VehG

VehH

Veh_I

VehJ

Total

20

21

26

26

30

24

29

32

22

26

256

Data analysis was performed using the SAS software package (current version). All NMOG emissions data
were log-transformed before model fitting began. This is a common practice, as vehicle emissions tend to
follow approximately log-normal distributions. In addition, this transformation is a standard approach to
normalizing the distributions of residuals and stabilizing their variance across a range of emission levels.4

The SAS Mixed procedure was used with the restricted maximum likelihood (REML) method in an initial
round of model fitting to examine the behavior of residuals and assess the effect of generating covariance
parameters specific to each vehicle. Figure 2.37 indicates conditional studentized residuals are approximately
normally distributed with some minor deviation toward the tails. Figure 2.38 shows the range of externally
studentized residuals, where levels of ± 3.5 are commonly used as a screen for "outlier points". Results indicate
all points are well within the acceptable range.

4 Additional discussion is available in Section 5.1 of the EPAct study report, EPA-420-R-13-002, April 2013.

47


-------
-3-2-10 1 2 3
Quantile

Residual Statistics

Observations

256

Minimum

-3.401

Mean

0.0001

Maximum

4.1452

Std Dev

1.0026

Fit Statistics



Objective

-134.7

AIC

-112.7

AICC

-111.6

BIC

-109.3

Figure 2.37. Analysis of conditional studentized residuals for FTP cycle NMOG data.

"S

N

ft,
C

£
X

LU

4

2-



%

Ty
o
o o

Oo

05 O
o o

o OS

-2 -

50

100	150

Deleted Obs. Index

200

250

Figure 2.38. Externally studentized residuals for FTP cycle NMOG data.

Following this initial analysis, the model was refit using the maximum likelihood method to generate the
intercept and fixed effect coefficient for the PMI fuel term. The model parameters and related fit statistics are
presented in Table 2.27. These results indicate that PMI is a statistically significant predictor of NMOG
emissions, but with a relatively small effect at 0.22 percent NMOG emissions per percent PMI.

48


-------
Table 2.27. PMI model parameters for FTP NMOG.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

-4.3822

0.2332

10.3

-18.8

<0001

PMI

0.03994

0.01523

171

2.62

0.0095

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
2.28 presents differences of least squares means for fuel pairs.

Table 2.28. Differences in least squares means by fuel for FTP NMOG.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

Adjusted
P

A

B

0.038

0.02568

160

1.48

0.577

A

C

0.04129

0.0259

162

1.59

0.5034

A

D

0.08336

0.02552

165

3.27

0.0114

A

Base

0.02893

0.0341

102

0.85

0.9147

B

C

0.00329

0.02974

160

0.11

1

B

D

0.04535

0.02942

163

1.54

0.5371

B

Base

-0.0091

0.03725

116

-0.24

0.9992

C

D

0.04207

0.02962

164

1.42

0.6154

C

Base

-0.0124

0.03732

115

-0.33

0.9974

D

Base

-0.0544

0.03708

115

-1.47

0.5852

Differences in Table 2.28 are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer
adjustment for multiple comparisons. The results show significant differences between Fuel A and Fuel D.

11 SO 6 Cycle Data

Figure 2.39 provides an initial review of NMOG measurements collected on the US06 test cycle, grouped by
vehicle. The axis label "index" refers to the count of individual observations. The red arrows near the bottom of
the figure highlight several tests that produced zero-value NMOG results, indicating emissions were below the
quantitation limit of the measurement equipment. Given that the majority of measurements from VehH were
zeros, a decision was made to remove this vehicle's US06 NMOG emissions from subsequent analysis. In
addition, one highlighted point from Veh G was also removed. The remaining data is shown in Figure 2.40 and
Figure 2.41, where the vehicle means fall between 2-20 mg/mi, except for one vehicle that had a mean around
50 mg/mi and a relatively large span.

49


-------
index
Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o VehJ o Veh_J

Figure 2.39. US06 NMOG dataset by vehicle, log scale. Red arrows indicate zero-value measurements.

0.10

0.08

E 0.06

3

O

o

s 0.04

0.02

0.00

















o
o











o

o











o°%

-------
Vehicle



o Veh_A o Veh_B o Veh_C

o Veh_D o Veh_E

o Veh_F o Veh_G o VehJ

o Veh_J

Figure 2.41. US06 NMOG dataset used in the analysis, log scale.

Figure 2.42 plots the data as vehicle means by fuel (four of the vehicles did not test Base Fuel). Figure 2.43
presents vehicle means by PM Index. Similar to the FTP cycle, some vehicles have increasing NMOG trends
with increasing PM Index, while others are flat or slightly decreasing. Table 2.29 summarizes the number of
measurements collected and analyzed for each vehicle.

Fuel

Vehicle



o Veh_A o Veh_B o Veh_C

o Veh_D o Veh_E

o Veh_F o Veh_G o Veh_l

o Veh_J

Figure 2.42. US06 NMOG data as vehicle means by fuel, log scale.

51


-------
Figure 2.43. US06 NMOG data as vehicle means by PM Index, log scale.

Table 2.29. Number of NMOG measurements collected and analyzed in the US06 cycle model fitting.



VehA

VehB

VehC

VehD

VehE

VehF

VehG

VehH

Veh_I

VehJ

Total

Measurements
collected

20

23

26

25

30

25

31

33

23

22

258

Measurements
removed

0

0

0

0

0

0

1

33

0

0

34

Used in analysis

20

23

26

25

30

25

30

0

23

22

224

Data analysis and model fitting proceeded in the same manner as for the FTP cycle as described above,
including log transformation of the data and generation of covariance parameter estimates on a per-vehicle
basis. Figure 2.44 indicates conditional studentized residuals are normally distributed with minimal deviation
across quantiles. Figure 2.45 shows the range of externally studentized residuals, where levels of ± 3.5 are
commonly used as a screen for "outlier points". Results indicate all points fall within the acceptable range.

52


-------
5 0

V)
d>

a:

§8

go |<

mc

§6f

O O £

-5.0 -4.5 -4.0
Predicted

25
20
| 15
^ 10
5
0





h

-1.8 -0.6 0.6 1.8
Residual

2 o

crt

a>
cc

-1 0 1
Quantile

Residual Statistics

Observatbns

224

Minimum

-3.21

Mean

0.002

Maximum

3.1014

Std Dev

1.0029

Fit Statistics



Objective

21.002

AIC

41.002

AICC

42.045

BIG

42.975

Figure 2.44. Analysis of conditional studentized residuals for US06 cycle NMOG data.

Figure 2.45. Externally studentized residuals for US06 cycle NMOG data.

The solution for fixed effects for the PMI fuel parameter model is presented in Table 2.30. These results
indicate that PMI is a statistically significant predictor of NMOG emissions, with a slightly larger model
parameter than in the FTP cycle. These results can be used to compute a relative effect of 0.43 percent NMOG
emissions per percent PMI change over a PMI range of the test fuels.

53


-------
Table 2.30. Fixed effect model parameters for US06 NMOG.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

-4.7858

0.2388

9.38

-20.04

<0001

PMI

0.08112

0.02134

104

3.8

0.0002

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
2.31 presents differences of least squares means for fuel pairs.

Table 2.31. Differences in least squares means by fuel for US06 NMOG.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

Adjusted
P

A

B

0.07995

0.03593

98.5

2.22

0.1792

A

C

0.02927

0.03652

93

0.8

0.9296

A

D

0.1879

0.03551

102

5.29

<0001

A

Base

0.1014

0.05467

67.4

1.85

0.3515

B

C

-0.0507

0.04198

96

-1.21

0.7473

B

D

0.1079

0.04109

103

2.63

0.0729

B

Base

0.02147

0.05865

78.6

0.37

0.9961

C

D

0.1586

0.04164

98.1

3.81

0.0022

C

Base

0.07215

0.05899

78.4

1.22

0.738

D

Base

-0.0865

0.05819

78.4

-1.49

0.5748

Differences are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer adjustment for
multiple comparisons. These results show significant differences between fuel pairs A-D and C-D.

2.4.4. CO2 Emissions

Figure 2.46 provides a graphical overview of CO2 measurements collected on the FTP cycle, grouped by
vehicle. The axis label "index" refers to the count of individual observations. Vehicle means range from about
250 g/mi to about 480 g/mi, with individual vehicle ranges spanning up to 50 g/mi. Veh_C and Veh_H show the
largest variability in CO2 over their fuel and replicate sets.

54


-------
Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o VehJ o Veh_J

Figure 2.46. FTP CO2 dataset by vehicle.

Figure 2.47 plots the data as vehicle means by fuel (four of the vehi cles did not test Base Fuel). Figure 2.48
shows vehicle means by PM Index, where some vehicles have increasing CO2 trends with PM Index, and others
are flat or decreasing. Table 2.32 summarizes the number of measurements collected and analyzed for each
vehicle.



Vehicle



0 Veh_A 0 Veh_B

0 Veh_C

0 Veh_D 0 Veh_E

0 Veh_F 0 Veh_G

0 Veh_H

0 VehJ 0 Veh_J

Figure 2.47. FTP CO2 data as vehicle means by fuel.

55


-------
Figure 2.48. FTP CO2 data as vehicle means by PM Index.

Table 2.32. Number of CO2 measurements collected and analyzed in the FTP cycle model fitting.

VehA

VehB

VehC

VehD

VehE

VehF

VehG

VehH

Veh_I

VehJ

Total

20

21

26

26

30

24

29

32

22

26

256

Data analysis was performed using the SAS software package (current version). Unlike other emissions in this
study, no log-transformation was applied to the CO2 data as the distribution of points generally falls within a
narrow band defined by the vehicle efficiency and test cycle energy requirement.

The SAS Mixed procedure was used with the restricted maximum likelihood (REML) method to generate
covariance parameter estimates and to assess the behavior of residuals. In this case, covariance parameters were
generated for the dataset as a whole, rather than on a per-vehicle basis as for other emissions in this study, as the
latter did not produce a significant improvement in model fit. Figure 2.49 indicates conditional studentized
residuals show a relatively narrow distribution with some extension toward the tails. Figure 2.50 shows the
range of externally studentized residuals, where levels of ± 3.5 are commonly used as a screen for "outlier
points". Results indicate all points are well within the acceptable range.

56


-------
300	400

Predicted

40

0 -

-4.8 -3.6 -2.4

¦1.2 0 1.2
Residual

2.4 3.6 4.8

Quantile

Residual Statistics

Observations

256

Minimum

-4.749

Mean

-81E-6

Maximum

5.1272

Std Dev

1.0002

Fit Statistics



Objective

1688.5

AIC

1692.5

AICC

1692.6

BIC

1693.1

Figure 2.49. Analysis of conditional studentized residuals for FTP cycle CO2 data.

Figure 2.50. Externally studentized residuals for FTP cycle CO2 data.

Following this initial analysis, the model was refit using the maximum likelihood method to generate the
intercept and fixed effect coefficient for the PMI fuel term. The model parameters and related fit statistics are
presented in Table 2.33. These results indicate that PMI is a highly significant predictor of CO2 emissions over
the FTP cycle, but with a relatively small effect on the order of 1% per PMI unit.

57


-------
Table 2.33. PMI model parameters for FTP CO2.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

303.46

32.2644

10

9.41

<0001

PMI

2.9227

0.5914

246

4.94

<0001

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
2.34 presents differences of least squares means for fuel pairs.

Table 2.34. Differences in least squares means by fuel for FTP CO2.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

Adjusted
P

A

B

1.515

0.9688

246

1.56

0.5221

A

C

3.3537

0.9819

246

3.42

0.0066

A

D

6.561

0.9553

246

6.87

<0001

A

Base

1.0635

1.2101

246

0.88

0.9045

B

C

1.8387

1.1258

246

1.63

0.4776

B

D

5.046

1.1028

246

4.58

<0001

B

Base

-0.4515

1.3335

246

-0.34

0.9972

C

D

3.2073

1.1144

246

2.88

0.035

C

Base

-2.2902

1.3438

246

-1.7

0.4332

D

Base

-5.4975

1.3236

246

-4.15

0.0004

Differences are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer adjustment for
multiple comparisons. The results show significant differences between Fuel D and the other fuels.

11 SO 6 Cycle Data

Presentation of the US06 CO2 results will follow the same outline as for the FTP cycle. Figure 2.51 provides a
graphical overview of the measurements collected on the US06 test cycle, grouped by vehicle. The axis label
"index" refers to the count of individual observations. Vehicle means range from about 220 g/mi to about 520
g/mi, with individual vehicle ranges spanning up to 80 g/mi. Veh_C shows significantly larger variability over
its fuel and replicate sets than the other vehicles.

58


-------
Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o VehJ o Veh_J

Figure 2.51. US06 CO2 dataset by vehicle.

Figure 2.52 plots the data as vehicle means by fuel (four of the vehi cles did not test Base Fuel). Figure 2.53
presents vehicle means by PM Index. Similar to the FTP cycle, some vehicles have increasing CO2 trends with
increasing PM Index, while others are flat or slightly decreasing. Table 2.35 summarizes the number of
measurements collected and analyzed for each vehicle.

Fuel

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o VehJ o Veh_J

Figure 2.52. US06 CO2 data as vehicle means by fuel.

59


-------
500

I

3 400

CM

O

300

1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00

PMI
Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o VehJ o Veh_J

Figure 2.53. US06 CO2 data as vehicle means by PM Index.

Table 2.35. Number of CO2 measurements collected and analyzed in the US06 cycle model fitting.

VehA

VehB

VehC

VehD

VehE

VehF

VehG

VehH

Veh_I

VehJ

Total

20

23

26

25

30

25

31

33

23

22

258

Data analysis and model fitting proceeded in the same manner as for the FTP cycle as described above. Figure
2.54 indicates that conditional studentized residuals show a relatively narrow distribution with some extension
toward the tails. Figure 2.55 shows the range of externally studentized residuals, where levels of ± 3.5 are
commonly used as a screen for "outlier points". Results indicate all points are well within the acceptable range.









0



§-

l«	







	§

0

*¦

-51—







0

=1



F

%—







!

a —

I—Is	











60


-------
300	400

Predicted

40

30

10 -
0

-d

-4.5 -2.5 -0.5
Residual

-1 o 1
Quantile

Residual Statistics

Observations

258

Minimum

-6.397

Mean

-54E-6

Maximum

3.8542

Std Dev

1.0019

Fit Statistics



Objective

1862

AIC

1866

AICC

1866.1

BIC

1866.6

Figure 2.54. Analysis of conditional studentized residuals for US06 cycle CO2 data.

Figure 2.55. Externally studentized residuals for US06 cycle CO2 data.

The solution for fixed effects for the PMI fuel parameter model is presented in Table 2.36. Similar to the FTP
cycle, these results indicate that PMI is a highly significant predictor of CO2 emissions over the US06, but with
a relatively small effect, on the order of 1% per PMI unit.

61


-------
Table 2.36. Fixed effect model parameters for US06 CO2.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

337.58

31.1952

10.1

10.82

<0001

PMI

3.344

0.8242

248

4.06

<0001

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
2.37 presents differences of least squares means for fuel pairs.

Table 2.37. Differences in least squares means by fuel for US06 CO2.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

Adjusted
P

A

B

1.7458

1.3285

248

1.31

0.6827

A

C

1.5395

1.3382

248

1.15

0.7794

A

D

8.8066

1.3206

248

6.67

<0001

A

Base

2.4002

1.6489

248

1.46

0.5923

B

C

-0.2062

1.5251

248

-0.14

0.9999

B

D

7.0609

1.5093

248

4.68

<0001

B

Base

0.6544

1.8052

248

0.36

0.9963

C

D

7.2671

1.5192

248

4.78

<0001

C

Base

0.8607

1.8061

248

0.48

0.9894

D

Base

-6.4064

1.7983

248

-3.56

0.004

Differences are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer adjustment for
multiple comparisons. Similar to the FTP cycle, results show significant differences between Fuel D and the
other fuels.

2.4.5. Influence of Drive Quality

The data review and analysis presented so far examined the emissions measurements themselves, including
statistical confidence for the fuel effects and influence of any particular vehicle or observation. In addition, the
fitting of individual variance models for each vehicle before computing the overall effect of PMI or test fuel
further served to mitigate influence of the vehicle or the test lab.

Throughout the testing, the program participants recorded SAE Drive Quality Metrics (DQMs), which evaluate
conformity between the actual and target drive speeds for chassis dynamometer tests. [13] The DQMs combine
the speed variances with other information about the vehicle and test cycle to compute parameters such as the
Energy Economy Ratio (EER), Absolute Speed Change Rating (ASCR), and Inertial Work Rating (IWR). Each
metric represents a relative variance (i.e., percentage), with values close to zero indicating that a vehicle
followed the speed versus time trace more closely. Negative numbers indicate slightly lower speeds and
accelerations relative to the specified procedure while positive values indicate slightly higher speeds and
accelerations. Statistical analysis of DQMs can provide an indication of the influence of variation in vehicle

62


-------
operation on the study results. After an initial review of the DQM values across the dataset, IWR was chosen as
the parameter to use for this assessment.

Table 2.38 and Table 2.39 present differences of least squares means by fuel for IWR over the FTP and US06
cycles, respectively. Differences are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-
Kramer adjustment for multiple comparisons. The results show no significant differences in inertial work
among the test fuel comparisons except in one pair (Fuel D vs A in the FTP cycle). This suggests that the driver
or other conditions related to vehicle operation had no significant influence the fuel effects observed.

Table 2.38. Differences in least squares means by fuel for FTP cycle IWR.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

AdjP

A

B

0.1129

0.0426

47.9

2.65

0.0770

A

C

0.0512

0.0403

43.9

1.27

0.7099

A

D

0.1417

0.0384

41.8

3.69

0.0055

A

Base

0.0793

0.0485

43.7

1.63

0.4840

B

C

-0.0618

0.0489

48

-1.26

0.7154

B

D

0.0287

0.0474

46.6

0.61

0.9735

B

Base

-0.0337

0.0559

46.7

-0.6

0.9741

C

D

0.0905

0.0453

43.4

2

0.2852

C

Base

0.0281

0.0542

44.5

0.52

0.9850

D

Base

-0.0624

0.0528

43.4

-1.18

0.7610

Table 2.39. Differences in least squares means by fuel for US06 cycle IWR.

Fuell

Fuel2

Estimate

Standard
Error

DF

t Value

AdjP

A

B

0.0833

0.0804

51.6

1.04

0.8377

A

C

0.0270

0.0803

51.6

0.34

0.9972

A

D

0.0153

0.0768

48.5

0.2

0.9996

A

Base

-0.0982

0.0883

48.1

-1.11

0.7993

B

C

-0.0563

0.0937

52.7

-0.6

0.9743

B

D

-0.0680

0.0908

50.4

-0.75

0.9437

B

Base

-0.1815

0.1007

49.7

-1.8

0.3839

C

D

-0.0117

0.0907

50.4

-0.13

0.9999

C

Base

-0.1252

0.1006

49.7

-1.24

0.7259

D

Base

-0.1135

0.0978

47.8

-1.16

0.7737

63


-------
3. Summary and Conclusions

This study collected PM and gaseous emissions data from a test fleet of ten popular light-duty gasoline vehicles
spanning model years 2015-2022 using five test fuels blended to represent replacement of a portion of heavy
aromatics with alternate octane sources.

The emissions analysis provided two levels of results: an overall effect of PM Index (PMI) that incorporates
data from all test fuels, and a set of fuel-to-fuel comparisons to evaluate the impact of specific blending
changes. Comparisons between the fuels indicate that replacement of approximately 3 v% of Cio+ aromatics
with alternate octane sources provides significant PM reductions in all cases, with non-aromatic alternatives
producing the largest effect. The overall results indicate a significant sensitivity of PM emissions to PMI over
both the FTP and US06 test cycles, with a directionally consistent response from all vehicles over the FTP cycle
and all vehicles except one over the US06.

Table 3.1 presents percent-PM-emission per percent-PMI sensitivities (or ratios) by test cycle and vehicle. The
vehicles are sorted from smallest to largest effect for the FTP and span a range of approximately 1.0 to 2.2. For
the US06 cycle, the range is approximately 0.5 to 2.3 if the value for Veh_G is excluded. (A review of data for
VehG finds it has a relatively low sensitivity to PMI over the US06, which allows a few influential
measurements to tip the average value in the opposite direction of the other vehicles.)

Table 3.1. Percent-PM-emissions per percent-PM-Index sensitivities by test cycle and vehicle.



Veh H

Veh E

Veh A

VehC

Veh D

VehJ

Veh B

Veh F

VehJ

VehG

FTP

1.01

1.08

1.20

1.21

1.34

1.47

1.55

1.66

1.83

2.15

US06

0.51

0.44

1.67

0.80

1.15

1.42

0.64

1.22

2.27

-0.12

Data analysis also included gaseous emissions, which are of interest when considering broader air quality
impacts of fuel formulation changes. Table 3.2 presents a summary of overall test-fleet-average effects of PMI
on PM, NOx, NMOG, and CO2 emissions for the FTP and US06 test cycles.

Table 3.2. Summary of model results for a PM Index reduction from 2.5 to 1.5.



FTP Cycle

US06 Cycle



% emission change

% emission

% emission change

% emission



from 2.5 to 1.5 PMI

change per % PMI

from 2.5 to 1.5 PMI

change per % PMI

PM

-58%

1.45

-40%

1.00

NOx

NSSa

NSS°

-10%

0.25

CO2

-1%

0.02

-1%

0.02

NMOG

-9%

0.22

-17%

0.43

aNot statistically significant at the p < 0.05 level.

These results indicate that the largest impact of the fuel changes being investigated was the reduction of PM
emissions, and that no increase in emissions of NOx, NMOG, nor CO2 was observed for the test fleet overall
when replacing a portion of heavy aromatics with alternate octane sources.

64


-------
Acknowledgement

The U.S. EPA Office of Transportation and Air Quality acknowledges significant contributions by Environment

and Climate Change Canada (ECCC) and the seven participating global automotive vehicle manufacturers in

producing fuel chemistry and emissions data for this study.

References

1.	USEPA Technical Support Document, "2017 National Emissions Inventory: January 2021 Updated Release,
Technical Support Document," January 2021, accessed 29 October 2022, https://www.epa.gov/sites/default/
files/2021 -02/documents/nei2017_tsd_full j an2021 .pdf.

2.	American Lung Association, "Particle Pollution," accessed 29 October 2022, https://www.lung.org/clean-
air/outdoors/what-makes-air-unheal thy/particle-pollution.

3.	Aikawa, K., Sakurai, K., and Jetter, J. J., "Development of a Predictive Model for Gasoline Vehicle
Particulate Matter Emissions," SAE Technical Paper 2010-01-2115, 2010, https://doi.org/10.4271/2010-01-
2115.

4.	Aikawa, K., & Jetter, J. J., "Impact of Gasoline Composition on Particulate Matter Emissions from a Direct-
Injection Gasoline Engine: Applicability of the Particulate Matter Index," International Journal of Engine
Research, 15, 298 - 306, 2014, https://doi.org/10.1177/1468087413481216.

5.	Sobotowski, R.A., Butler, A.D., and Guerra, Z., "A Pilot Study of Fuel Impacts on PM Emissions from
Light-duty Gasoline Vehicles," SAE Int. J. Fuels Lubr. 8, no. 1 (2015): 214-233,
https://doi.org/10.4271/2015-01-9071.

6.	Butler, A.D., Sobotowski, R.A., Hoffman, G.J., and Machiele, P., "Influence of Fuel PM Index and Ethanol
Content on Particulate Emissions from Light-Duty Gasoline Vehicles," SAE Technical Paper 2015-01-
1072, 2015, https://doi.org/10.4271/2015-01-1072.

7.	Coordinating Research Council, "Evaluation and Investigation of Fuel Effects on Gaseous and Particulate
Emissions on SIDI In-Use Vehicles," Report No. E-94-2, March 2017, CRC_2017-3-21_03-20955_E94-
2FinalReport-Rev 1 b .pdf (crcao. org).

8.	USEPA, "Population and Activity of Onroad Vehicles in MOVES3," Technical Report EPA-420-R-21-012,
April 2021, https://nepis.epa.gov/Exe/ZyPDF.cgi/P101 lTF8.PDF?Dockey=P1011TF8.PDF

9.	USEPA, "Nonroad Engine Population Growth Estimated in MOVES2014b," Technical Report EPA-420-R-
18-010, July 2018, https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100UXJK.pdf.

10.	Coordinating Research Council, "Enhanced Speciation of Gasoline," Report No. AVFL-29, June 2018,
http://crcsite.wpengine.eom/wp-content/uploads/2019/05/CRC-Project-AVFL-29-Final-Report_June-2018-
l.pdf.

11.	Sobotowski, R., Butler, A., Loftis, K., and Wyborny, L., "A Method of Assessing and Reducing the Impact
of Heavy Gasoline Fractions on Particulate Matter Emissions from Light-Duty Vehicles," SAE Int. J. Fuels
Lubr. 15(3):2022, https://doi.org/10.4271/04-15-03-0015.

12.	Akard, M., Oestergaard, K., Chase, R. E., Richert, J. F. O., Fukushima, H. and Adachi, M., "Comparison of
an Alternative Particulate Mass Measurement with Advanced Microbalance Analysis," SAE Technical
Paper 2004-01-0589, 2004, https://doi.org/10.4271/2004-01-0589.

13.	SAE J2951, "Drive Quality Evaluation for Chassis Dynamometer Testing"

65


-------
Appendix A:
Supplemental Emissions Analysis


-------
Al. Carbon Monoxide

FTP Cycle Data

Figure Al.l and Figure A1.2 provide a graphical overview of carbon monoxide (CO) measurements collected
on the FTP cycle, grouped by vehicle, on linear and log scales, respectively. The axis label "index" refers to the
count of individual observations. Vehicle means cover a wide range, from about 10 mg/mi to over 600 mg/mi,
with individual vehicle ranges spanning about 25 mg/mi to over 250 mg/mi.

o.o -

0	50	100	150	200	250

index







Vehicle





o Veh_

_A

o Veh_B

o Veh_C

o Veh_D

o Veh_E

o Veh_

_F

o Veh_G

o Veh_H

o VehJ

o Veh_J

Figure Al.l. FTP CO dataset by vehicle, linear scale.


-------






o\,%



 °



°o °° 1

o o

w°

o 8
O

o

° &

c
£

o [

° O 0°o O &

So° « ^ o
 % o

° n

o <&o°

°o®

£

C

o

%> $

P

q -  '¦jiy&J

o ° °



° o ~o 0 I 50 i i i i 100 150 200 250 index Vehicle o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E o Veh_F o Veh_G o Veh_H o Veh_l o Veh_J Figure A1.2. FTP CO dataset by vehicle, log scale. Figure A1.3 plots the data as vehicle means by fuel (four of the vehicles did not test Base Fuel). Figure A1.4 shows vehicle means by PM Index, where some vehicles have increasing CO trends with PM Index, and others flat or decreasing. Table Al.l summarizes the number of measurements collected and analyzed for each vehicle.


-------
Fuel

Vehicle

o Veh_A o Veh_B o Veh_C	o Veh_D o Veh_E

o Veh_F o Veh_G o Veh_H	o Veh J o Veh_J

Figure A1.3. FTP CO data as vehicle means by fuel, log scale.



Vehicle



o Veh_A o Veti_B

o Veh_C

o Veh_D o Veh_E

o Veh_F o Veh_G

o Veh_H

o Veh_l o Veh_J

Figure A1.4. FTP CO data as vehicle means by PM Index, log scale.

Table A1.1. Number of CO measurements collected and analyzed in the FTP cycle model fitting.

Veh A

Veh B

VehC

Veh D

Veh E

Veh F

Veh_G

Veh H

Veh_I

VehJ

Total

20

21

26

26

30

24

29

32

22

26

256


-------
Data analysis was performed using the SAS software package (current version). All CO emissions data were
log-transformed before model fitting began. This is a common practice, as vehicle emissions tend to follow
approximately log-normal distributions. In addition, this transformation is a standard approach to normalizing
the distributions of residuals and stabilizing their variance across a range of emission levels.1

The SAS Mixed procedure was used with the restricted maximum likelihood (REML) method in an initial
round of model fitting to examine the behavior of residuals and assess the effect of generating covariance
parameters specific to each vehicle. Figure A1.5 indicates conditional studentized residuals are normally
distributed with some minor deviation at the tails. Figure A1.6 shows the range of externally studentized
residuals, where levels of ± 3.5 are commonly used as a screen for "outlier points". Results indicate all points
fall within the acceptable range.

-2

cS 9 o

0 ° °

-2.5 -2.0 -1.5
Predicted

- 20

0







-3.2 -2.4 -1.6 -0.8 0 0.8 1.6 2.4 3.2 4
Residual

^ 0 -

-1 0 1
Quantile

Residual Statistics

Observations

256

Minimum

-3.45

Mean

-12E-5

Maximum

4.0019

Std Dev

1.0024

Fit Statistics



Objective

-132

AIC

-110

AICC

-108.9

BIC

-106.7

Figure A1.5. Analysis of conditional studentized residuals for FTP cycle CO data.

1 Additional discussion is available in Section 5.1 of the EPAct study report, EPA-420-R-13-002, April 2013.


-------
0	50	100	150	200	250

Deleted Obs. Index

Figure A1.6. Externally studentized residuals for FTP cycle CO data.

Following this initial analysis, the model was refit using the maximum likelihood method to generate the
intercept and fixed effect coefficient for the PMI fuel term. The model parameters and related fit statistics are
presented in Table A1.2. These results indicate that PMI is not a significant predictor of CO emissions in the
FTP cycle.

Table A1.2. PMI model parameters for FTP CO.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

-1.9293

0.2056

10.3

-9.38

<0001

PMI

-0.00317

0.01511

130

-0.21

0.8343

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
A1.3 presents differences of least squares means for fuel pairs.


-------
Table A1.3. Differences in least squares means by fuel for FTP CO.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

AdjP

A

B

-0.0319

0.0256

133

-1.25

0.7219

A

C

-0.0312

0.0250

118

-1.25

0.7220

A

D

0.0638

0.0242

111

2.63

0.0712

A

Base

-0.0612

0.0298

106

-2.05

0.2481

B

C

0.0007

0.0295

130

0.02

1.0000

B

D

0.0958

0.0289

126

3.31

0.0104

B

Base

-0.0293

0.0337

117

-0.87

0.9076

C

D

0.0950

0.0284

115

3.35

0.0095

C

Base

-0.0300

0.0333

111

-0.90

0.8958

D

Base

-0.1250

0.0327

107

-3.82

0.0021

Differences in Table A1.3 are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer
adjustment for multiple comparisons. These results indicate the largest differences occurred between Fuel D and
the other fuels.

US06 Cycle Data

Figure A1.7 provides an initial review of CO measurements collected on the US06 test cycle, grouped by
vehicle. The axis label "index" refers to the count of individual observations. The red arrows highlight
measurements for Veh_I, which are nearly identical in value for all tests. Given the implausibility of this
situation, a decision was made to remove this vehicle's US06 CO data from subsequent analysis. The remaining
data is shown in Figure A1.8 and Figure A1.9 (log and linear scales, respectively), where the vehicle means fall
between roughly 40 mg/mi and 6 g/mi, except for Veh J that had a mean around 8 g/mi and a large span.


-------
o
o

W

50

100

150

200

index

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh F o Veh G o Veh H o Veh I o Veh J

250

Figure A1.7. Initial review of US06 CO dataset by vehicle, log scale. Red arrows indicate suspect

measurements.

index

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o Veh_J

Figure A1.8. US06 CO dataset used in the analysis, linear scale.


-------












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9

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T

0	50	100	150	200	250

index

Vehicle

o Veh_A o Veh_B o Veh_C o Veti_D o Veh_E
o Veh_F o Veh_G o Veh_H o Veh_J

Figure A1.9. US06 CO dataset used in the analysis, log scale.

Figure ALIO plots the data as vehicle means by fuel (four of the vehicles did not test Base Fuel). Figure Al.ll
presents vehicle means by PM Index. Similar to the FTP cycle, some vehicles have increasing CO trends with
increasing PM Index, while others are flat or slightly decreasing. Table A1.4 summarizes the number of
measurements collected and analyzed for each vehicle.



Vehicle



o Veh_A o Veh_B

o Veh_C

o Veh_D o Veh_E

o Veh_F o Veh_G

o Veh_H

o Veh_J

-0.5

	1	

Base

Figure ALIO. US06 CO data as vehicle means by fuel, log scale.


-------




Vehicle



o Veh_A

o Veh B

o Veh_C

o Veh_D o VehE

o Veh_F

o Veh_G

o Veh_H

o Veh_J

Figure Al.ll. US06 CO data as vehicle means by PM Index, log scale.

Table A1.4. Number of CO measurements collected and analyzed in the US06 cycle model fitting.



Veh A

Veh B

VehC

Veh D

Veh E

Veh F

Veh_G

Veh H

Veh_I

VehJ

Total

Measurements

20

23

26

25

30

25

31

33

23

22

258

collected























Measurements

0

0

0

0

0

0

0

0

23

0

23

removed























Used in

20

23

26

25

30

25

31

33

0

22

235

analysis























Data analysis and model fitting proceeded in the same manner as for the FTP cycle as described above,
including log transformation of the data and generation of covariance parameter estimates on a per-vehicle
basis. Figure A1.12 indicates conditional studentized residuals are approximately normally distributed with
some deviation toward the left tail. Figure A1.13 shows the range of externally studentized residuals, where
levels of ± 3.5 are commonly used as a screen for "outlier points". Results indicate all points fall within the
acceptable range.


-------
3 o

-2

6is &

§ * ^
In

e

6

6>

b 8
| 8
e

» {
S 5 f

l| :

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0 °
<6

o

o

03

2 0

tn
0J

C£

-2

0

Predicted

-1 o
Quantile

25
20
e 15

I

S. 10

5 -



-3.3 -2.1

-0.9 0.3 1.5
Residual

2.7

Residual Statistics

Observations

235

Minimum

-3.354

Mean

-0.002

Maximum

2.5202

Std Dev

1.0023

Fit Statistics



Objective

368.36

AIC

388.36

AICC

389.35

BIC

390.33

Figure A 1.12. Analysis of conditional studentized residuals for US06 cycle CO data.

4

8.

"8

„N

C
CD

=3

CO

_>N

c:

o5

2 -





©

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ocr<
O

o °oo
o o0

GQ ^

0 6>°S° °



o







O



O

° o


-------
Table A1.5. Fixed effect model parameters for US06 CO.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

0.0065

0.4287

9.46

0.02

0.9883

PMI

0.0347

0.0363

74.9

0.95

0.3427

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
A1.6 presents differences of least squares means for fuel pairs.

Table A1.6. Differences in least squares means by fuel for US06 CO.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

AdjP

A

B

-0.0243

0.0538

55.3

-0.45

0.9911

A

C

-0.1216

0.0539

54.7

-2.26

0.1754

A

D

0.2351

0.0536

56.2

4.39

0.0005

A

Base

-0.1249

0.0871

68.7

-1.43

0.6077

B

C

-0.0973

0.0619

55.9

-1.57

0.5210

B

D

0.2594

0.0616

57.1

4.21

0.0008

B

Base

-0.1006

0.0919

76.9

-1.09

0.8090

C

D

0.3567

0.0617

56.6

5.78

<0001

C

Base

-0.0033

0.0920

76.9

-0.04

1.0000

D

Base

-0.3600

0.0917

77.0

-3.93

0.0017

Differences are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer adjustment for
multiple comparisons. These results, like for the FTP, show the largest differences between Fuel D and the other
fuels.


-------
A2. Fuel Economy

FTP Cycle Data

Figure A2.1 provides a graphical overview of carbon-balance fuel economy (CBFE) measurements collected on
the FTP cycle, grouped by vehicle. The term "carbon balance" describes the computation process, which sums
up all the carbon in the exhaust emissions and computes the equivalent gasoline volume using the carbon
content and density of the test fuel. This method does not apply any adjustments to represent a regulatory CAFE
result. The axis label "index" refers to the count of individual observations. Vehicle means cover a wide range,
from about 12 mpg to around 56 mpg.

10

0	50	100	150	200	250

index









Vehicle





o Veh.

.A

o Veh.

_B

o Veh_C

o Veh_D

o Veh_E

o Veh_

_F

o Veh_

G

o Veh H

o VehJ

o Veh_J

Figure A2.1. FTP CBFE dataset by vehicle.

Figure A2.2 plots the data as vehicle means by fuel (four of the vehicles did not test Base Fuel) and Figure A2.3
shows vehicle means by PM Index. Table A2.1 summarizes the number of measurements collected and
analyzed for each vehicle.


-------
/V 	





		

	0























W W w - w









	©



















o





















































I

A

I I

B Base
Fuel

I

C



I

D



Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D
o Veh_F o Veh_G o Veh_H o VehJ

o Veh_E
o VehJ





Figure A2.2. FTP CBFE data as vehicle means by fuel.

o>
Q.

E

60

50

40

CO

o 30

20

10

T	

.00

n—*

o o8

0

O <8

o »o

1.25

i

1.50

i

1.75

i

2.00
PMI

i i

2.25 2.50





Vehicle



o Veh A

o Veh B

o Veh C

o Veh D o Veh E

o Veh_F

o Veh_G

o Veh_H

o VehJ o VehJ

2.75

3.00

Figure A2.3. FTP CBFE data as vehicle means by PM Index.

Table A2.1. Number of CBFE measurements collected and analyzed in the FTP cycle model fitting.

Veh A

Veh B

VehC

Veh D

Veh E

Veh F

Veh_G

Veh H

Veh_I

VehJ

Total

20

21

26

26

30

24

29

32

22

26

256


-------
Data analysis was performed using the SAS software package (current version). Unlike other emissions in this
study, no log-transformation was applied to the CBFE data as the distribution of points generally falls within a
narrow band defined by the vehicle efficiency and test cycle energy requirement.

The SAS Mixed procedure was used with the restricted maximum likelihood (REML) method in an initial
round of model fitting to examine the behavior of residuals and assess the effect of generating covariance
parameters specific to each vehicle. In Figure A2.4, conditional studentized residuals have a somewhat narrow
distribution with notable extension of the upper tail. Figure A2.5 shows the range of externally studentized
residuals, where levels of ± 3.5 are commonly used as a screen for "outlier points". Results indicate all points
fall within the acceptable range.

7.5 -
5.0
2.5
0.0
-2.5

I I I I

30	40

Predicted

-3 -1.8 -0.6 0.6 1.8 3 4.2 5.4 6.6 7.£
Residual

-2-10 1
Quantile

Residual Statistics

Observations

256

Minimum

-3.361

Mean

261E-8

Maximum

8.0266

Std Dev

1.0047

Fit Statistics



Objective

730.21

AIC

734.21

AICC

734.25

BIC

734.81

Figure A2.4. Analysis of conditional studentized residuals for FTP cycle CBFE data.


-------
-2-

0	50	100	150	200	250

Deleted Obs. Index

Figure A2.5. Externally studentized residuals for FTP cycle CBFE data.

Following this initial analysis, the model was refit using the maximum likelihood method to generate the
intercept and fixed effect coefficient for the PMI fuel term. The model parameters and related fit statistics are
presented in Table A2.2. These results indicate that PMI is not a significant predictor of CBFE in the FTP cycle.

Table A2.2. PMI model parameters for FTP CBFE.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

31.1012

3.6644

10

8.49

<0001

PMI

0.0374

0.0906

246

0.41

0.6804

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
A2.3 presents differences of least squares means for fuel pairs.


-------
Table A2.3. Differences in least squares means by fuel for FTP CBFE.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

AdjP

A

B

0.0313

0.1547

246

0.2

0.9996

A

C

0.0425

0.1568

246

0.27

0.9988

A

D

-0.0492

0.1526

246

-0.32

0.9977

A

Base

0.2921

0.1933

246

1.51

0.5562

B

C

0.0112

0.1798

246

0.06

1.0000

B

D

-0.0805

0.1762

246

-0.46

0.9910

B

Base

0.2608

0.2130

246

1.22

0.7372

C

D

-0.0917

0.1780

246

-0.52

0.9858

C

Base

0.2496

0.2146

246

1.16

0.7726

D

Base

0.3412

0.2114

246

1.61

0.4898

Differences are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer adjustment for
multiple comparisons. These results show no statistically significant differences between any fuels.

US06 Cycle Data

Figure A2.6 provides a graphical overview of carbon-balance fuel economy (CBFE) measurements collected on
the US06 cycle, grouped by vehicle. The axis label "index" refers to the count of individual observations.
Vehicle means fall between roughly 14 and 36 MPG.









Vehicle





o Veh_

A

o Veh_

_B

o Veh_C

o Veh_D

o Veh_E

o Veh.

_F

o Veh.

_G

o Veh_H

o VehJ

o Veh_J

Figure A2.6. US06 CBFE dataset used in the analysis.


-------
Figure A2.7 plots the data as vehicle means by fuel (four of the vehicles did not test Base Fuel). Figure A2.8
presents vehicle means by PM Index. Table A2.4 summarizes the number of measurements collected and
analyzed for each vehicle.



—§	



Q	





	©

0









	©	























	0	



	©	





				

T

-9



	A	































—e—



n	











m

Uf y W

1

A

i

B



I

Base
Fuel



i

c

1

D



o Veh_A
o Veh_F

o Veh_B
o Veh_G

Vehicle
o Veh_C o
o Veh_H o

o o

~ _
1 1

Veh_E
Veh_J



Figure A2.7. US06 CBFE data as vehicle means by fuel.


-------




i  mr



|















9 i

k





,



H











I	





i

IB





o





La







fi



i





1



8-tc	



	•



1.00

1.25

1.50

1.75

2.00
PMI

2.25

2.50

2.75

3.00









Vehicle





o Veh

A

o Veh_

_B

o Veh_C

o Veh_D

o Veh_E

O' Veh.

_F

o Veh.

_G

o Veh_H

o VehJ

o Veh_J

Figure A2.8. US06 CBFE data as vehicle means by PM Index.

Table A2.4. Number of CBFE measurements collected and analyzed in the US06 cycle model fitting.

Veh A

Veh B

VehC

Veh D

Veh E

Veh F

Veh_G

Veh H

VehJ

VehJ

Total

20

23

26

25

30

25

31

33

23

22

258

Data analysis and model fitting proceeded in the same manner as for the FTP cycle as described above. Figure
A2.9 indicates conditional studentized residuals are approximately normally distributed with some deviation
toward the lower tail. Figure A2.10 shows the range of externally studentized residuals, where levels of ± 3.5
are commonly used as a screen for "outlier points". Results indicate all points fall well within the acceptable
range.


-------
CH .2

25

Predicted

30

S 20 -

o

-------
Table A2.5. Fixed effect model parameters for US06 CBFE.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

26.9158

2.2920

10

11.74

<0001

PMI

-0.1012

0.0555

248

-1.82

0.0696

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
A2.6 presents differences of least squares means for fuel pairs.

Table A2.6. Differences in least squares means by fuel for US06 CBFE.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

AdjP

A

B

-0.1213

0.0912

248

-1.33

0.6727

A

C

0.0804

0.0919

248

0.88

0.9058

A

D

-0.3513

0.0907

248

-3.87

0.0013

A

Base

0.0081

0.1132

248

0.07

1.0000

B

C

0.2018

0.1047

248

1.93

0.3060

B

D

-0.2300

0.1036

248

-2.22

0.1762

B

Base

0.1294

0.1240

248

1.04

0.8346

C

D

-0.4317

0.1043

248

-4.14

0.0005

C

Base

-0.0724

0.1240

248

-0.58

0.9774

D

Base

0.3594

0.1235

248

2.91

0.0319

Differences are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer adjustment for
multiple comparisons. These results indicate that the largest differences occurred between Fuel D and the other
fuels.


-------
A3. Inertial Work Rating

FTP Cycle Data

Figure A3.1 provides a graphical overview of inertial work rating (IWR) values generated over the FTP cycle,
grouped by vehicle. IWR is one of the SAE Drive Quality Metrics (DQMs) that are used evaluate conformity
between the actual and target drive speeds for chassis dynamometer tests. Statistical analysis of DQMs can
provide an indication of the influence of variation in vehicle operation on the study results. The axis label
"index" refers to the count of individual observations.

1

o°
o



o

o o° „ ° ^ °
u o

0 ° CP n ^
°°°° °° °00 °o
0 OO^V®®
% 0 _ °% &0° °oo °°$>
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o

<*>& ° °°
o

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o

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°o °

° ° o o °°o C

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_ <&°

%

°o°

O o°

° %

o00 ° °
°o°o


-------
Fuel

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F © Veh_G o Veh_H o VehJ o Veh_J

Figure A3.2. FTP IWR data as vehicle means by fuel.



o



0

















8

0

e





> oc

D o

1—d





c

¦	1

I







F?

—



	0

9





§ *







e

o





i	1	1	1	1	i	1

1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00

PMI

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o^Veh_F	o Veh_G ^ Veh_H o Veh_l _o Veh_J

Figure A3.3. FTP IWR data as vehicle means by PM Index.

Table A3.1. Number of IWR measurements collected and analyzed in the FTP cycle model fitting.

VehA

Veh B

VehC

Veh D

Veh E

Veh F

VehG

Veh H

Veh_I

VehJ

Total

20

21

26

26

30

24

29

32

22

26

256

Data analysis was performed using the SAS software package (current version). No log-transformation was
applied to the IWR data before analysis.


-------
The SAS Mixed procedure was used with the restricted maximum likelihood (REML) method in an initial
round of model fitting to examine the behavior of residuals and assess the effect of generating covariance
parameters specific to each vehicle. Figure A3.4 indicates conditional studentized residuals are approximately
normally distributed with minimal deviation at the tails. Figure A3.5 shows the range of externally studentized
residuals, where levels of ± 3.5 are commonly used as a screen for "outlier points". Results indicate all points
fall well within the acceptable range.

s o

-2

-3 -2

-1 0 1
Quantile

Residual Statistics

Observations

256

Minimum

-2.351

Wean

-0.003

Maximum

3.1192

Std Dev

1.0034

Fit Statistics



Objective

575.8

AIC

597.8

AICC

598.89

BIC

601.13

Figure A3.4. Analysis of conditional studentized residuals for FTP cycle IWR data.

D

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tn
a>
fH
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-------
Following this initial analysis, the model was refit using the maximum likelihood method to generate the
intercept and fixed effect coefficient for the PMI fuel term. The model parameters and related fit statistics are
presented in Table A3.2. These results indicate that PMI is a statistically significant predictor of IWR in the
FTP cycle.

Table A3.2. PMI model parameters for FTP IWR.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

0.4217

0.5132

10.2

0.82

0.43

PMI

0.0810

0.0235

47.2

3.45

0.0012

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
A3.3 presents differences of least squares means for fuel pairs.

Table A3.3. Differences in least squares means by fuel for FTP IWR.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

AdjP

A

B

0.1129

0.0426

47.9

2.65

0.0770

A

C

0.0512

0.0403

43.9

1.27

0.7099

A

D

0.1417

0.0384

41.8

3.69

0.0055

A

Base

0.0793

0.0485

43.7

1.63

0.4840

B

C

-0.0618

0.0489

48

-1.26

0.7154

B

D

0.0287

0.0474

46.6

0.61

0.9735

B

Base

-0.0337

0.0559

46.7

-0.6

0.9741

C

D

0.0905

0.0453

43.4

2

0.2852

C

Base

0.0281

0.0542

44.5

0.52

0.9850

D

Base

-0.0624

0.0528

43.4

-1.18

0.7610

Differences are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer adjustment for
multiple comparisons. Results show one significant difference for Fuel A vs D at the p < 0.05 level.

US06 Cycle Data

Figure A3.6 provides a graphical overview of IWR measurements collected on the US06 cycle, grouped by
vehicle. The axis label "index" refers to the count of individual observations.


-------
° ®D

0	°

	1	i	1	1	1	1—

0	50	100	150	200	250

index

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o Veh_l o Veh_J

Figure A3.6. US06 IWR dataset used in the analysis.

Figure A3.7 plots the data as vehicle means by fuel (four of the vehicles did not test Base Fuel). Figure A3.8
presents vehicle means by PM Index. Table A3.4 summarizes the number of measurements collected and
analyzed for each vehicle.

Fuel

Vehicle

o Veh_A o Veh_B o Veh_C o Veh_D o Veh_E
o Veh_F o Veh_G o Veh_H o VehJ o Veh_J

Figure A3.7. US06 IWR data as vehicle means by fuel.


-------
5

0

a.

I -5

-10

-15

1.50

1.75

2.00
PMI

2.25

2.50





Vehicle





o Veh A

o Veh B

o Veh C

o Veh D

o Veh E

o Veh_F

o Veh_G

o VehJH

o VehJ

o Veh_J

Figure A3.8. US06 IWR data as vehicle means by PM Index.

Table A3.4. Number of IWR measurements collected and analyzed in the US06 cycle model fitting.

Veh A

Veh B

VehC

Veh D

Veh E

Veh F

Veh_G

Veh H

VehJ

VehJ

Total

20

23

26

25

30

24

31

33

23

22

257

Data analysis and model fitting proceeded in the same manner as for the FTP cycle as described above. Figure
A3.9 indicates conditional studentized residuals are approximately normally distributed with some deviations
toward the tails. Figure A3.10 shows the range of externally studentized residuals, where levels of ± 3.5 are
commonly used as a screen for "outlier points". Results indicate all points fall within the acceptable range.


-------
-3 -2-10123
Quantile

Residual Statistics

Observations

257

Minimum

-2.619

Mean

-0.007

Maximum

3.795

Std Dev

1.0051

Fit Statistics



Objective

836.32

AIC

858.32

AICC

859.41

BIG

861.65

Figure A3.9. Analysis of conditional studentized residuals for US06 cycle IWR data.

3

75

3
T3

'(/>
0>

a:
~o

1

¦M

c
a>
T3
3

3 o









O

C

O

. (P

o

o







° ° ° 0o o
o (m

°*° * O VI







Oo °" o O O V

°°oV°°S ° o° £0 f ° %S>fp

o°\

°Q ° ° ° r, ®

8 ° ° ° 9>
0 o8



o°

°o
o

<9

0 O

0

o

o

o

o o

o

0 o

-------
Table A3.5. Fixed effect model parameters for US06 IWR.

Effect

Parameter
Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

-4.5329

0.8083

9.73

-5.61

0.0002

PMI

0.0090

0.0462

53.4

0.2

0.8455

In addition, a mixed-factor ANOVA analysis was conducted to provide comparisons among the test fuels. Table
A3.6 presents differences of least squares means for fuel pairs.

Table A3.6. Differences in least squares means by fuel for US06 IWR.

Fuell

Fuel2

Parameter
Estimate

Standard
Error

DF

t Value

AdjP

A

B

0.0833

0.0804

51.6

1.04

0.8377

A

C

0.0270

0.0803

51.6

0.34

0.9972

A

D

0.0153

0.0768

48.5

0.2

0.9996

A

Base

-0.0982

0.0883

48.1

-1.11

0.7993

B

C

-0.0563

0.0937

52.7

-0.6

0.9743

B

D

-0.0680

0.0908

50.4

-0.75

0.9437

B

Base

-0.1815

0.1007

49.7

-1.8

0.3839

C

D

-0.0117

0.0907

50.4

-0.13

0.9999

C

Base

-0.1252

0.1006

49.7

-1.24

0.7259

D

Base

-0.1135

0.0978

47.8

-1.16

0.7737

Differences are interpreted as Fuell relative to Fuel2. Adjusted P values use the Tukey-Kramer adjustment for
multiple comparisons. These results show no significant differences between any fuels.


-------
Appendix B:
Emissions Dataset


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_A

FTP

A

2.72

-3.6542

0.0039

0.1047

0.0057

241.1

0.0030

0.0032

0.0010

36.43

2.373

Veh_A

FTP

A

2.72

0.9641

0.0042

0.1473

0.0050

254.2

0.0033

0.0036

0.0011

34.54

2.568

Veh_A

FTP

A

2.72

0.9643

0.0041

0.1323

0.0059

246.8

0.0030

0.0032

0.0013

35.59

2.366

Veh_A

FTP

A

2.72

-1.1709

0.0048

0.1448

0.0075

246.6

0.0034

0.0037

0.0016

35.61

2.408

Veh_A

FTP

A

2.72

0.7854

0.0042

0.1393

0.0091

253.7

0.0031

0.0034

0.0014

34.62

2.317

Veh_A

FTP

A

2.72

-1.7965

0.0044

0.1319

0.0068

244.9

0.0032

0.0036

0.0013

35.86

2.084

Veh_A

FTP

A

2.72

-1.9190

0.0045

0.1351

0.0070

244.6

0.0031

0.0033

0.0016

35.91

2.268

Veh_A

FTP

A

2.72

-1.9350

0.0049

0.1398

0.0068

249.1

0.0030

0.0033

0.0020

35.25

2.250

Veh_A

FTP

B

1.53

-3.7279

0.0046

0.1343

0.0067

244.1

0.0030

0.0033

0.0018

35.83

1.733

Veh_A

FTP

B

1.53

-0.1576

0.0040

0.1045

0.0065

254.7

0.0030

0.0033

0.0012

34.35

1.775

Veh_A

FTP

B

1.53

-1.2564

0.0041

0.1028

0.0062

245.4

0.0030

0.0033

0.0013

35.66

1.881

Veh_A

FTP

B

1.53

-1.7929

0.0047

0.1310

0.0069

247.8

0.0034

0.0037

0.0015

35.31

2.005

Veh_A

FTP

C

1.50

-2.8549

0.0049

0.1383

0.0058

240.7

0.0032

0.0035

0.0019

35.89

1.545

Veh_A

FTP

C

1.50

0.8187

0.0043

0.1532

0.0060

248.7

0.0091

0.0100

0.0015

34.74

1.583

Veh_A

FTP

C

1.50

-3.5230

0.0046

0.1113

0.0070

243.0

0.0034

0.0037

0.0014

35.56

1.189

Veh_A

FTP

C

1.50

-2.2321

0.0043

0.1029

0.0073

252.4

0.0034

0.0037

0.0013

34.24

1.313

Veh_A

FTP

D

1.41

-2.3551

0.0041

0.1155

0.0057

243.0

0.0032

0.0036

0.0012

35.56

1.435

Veh_A

FTP

D

1.41

-3.1940

0.0037

0.0941

0.0066

244.5

0.0028

0.0032

0.0011

35.35

1.423

Veh_A

FTP

D

1.41

0.2581

0.0045

0.1394

0.0059

253.2

0.0034

0.0039

0.0013

34.12

1.258

Veh_A

FTP

D

1.41

-2.9681

0.0045

0.1156

0.0065

244.4

0.0033

0.0038

0.0013

35.36

1.477

Veh_A

US06

A

2.72

-14.2270

0.0064

0.0805

0.0040

252.0

0.0107

0.0110

0.0000

34.87

1.079

Veh_A

US06

A

2.72

-0.5396

0.0056

0.4365

0.0042

267.5

0.0058

0.0059

0.0001

32.78

1.344

Veh_A

US06

A

2.72

-12.3117

0.0054

0.1699

0.0045

252.9

0.0101

0.0104

0.0000

34.72

1.002

Veh_A

US06

A

2.72

-10.6040

0.0047

0.4933

0.0033

255.8

0.0048

0.0050

0.0001

34.26

1.270

Veh_A

US06

A

2.72

-0.1346

0.0069

0.7817

0.0043

272.6

0.0067

0.0069

0.0002

32.10

0.658

Veh_A

US06

A

2.72

-11.5300

0.0068

0.1123

0.0039

256.7

0.0066

0.0068

0.0002

34.22

0.546

Veh_A

US06

A

2.72

-10.8184

0.0052

0.2566

0.0042

259.1

0.0051

0.0053

0.0001

33.87

0.719

Veh_A

US06

A

2.72

-7.0620

0.0038

0.0968

0.0035

264.2

0.0037

0.0039

0.0001

33.25

0.684

Veh_A

US06

B

1.53

-13.8354

0.0042

0.0887

0.0035

251.9

0.0044

0.0046

0.0000

34.74

0.522

Veh_A

US06

B

1.53

-0.6968

0.0051

0.4876

0.0035

265.8

0.0053

0.0055

0.0000

32.84

0.801

Veh_A

US06

B

1.53

-7.4522

0.0041

0.1931

0.0035

260.1

0.0044

0.0046

0.0000

33.62

0.437

Veh_A

US06

B

1.53

-9.3296

0.0035

0.2129

0.0040

257.4

0.0038

0.0039

0.0000

33.97

0.692

Veh_A

US06

C

1.50

-12.7264

0.0050

0.1322

0.0031

250.9

0.0051

0.0053

0.0001

34.44

0.419

lof 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_A

US06

C

1.50

-1.2663

0.0053

0.6598

0.0045

253.8

0.0054

0.0055

0.0000

33.92

0.899

Veh_A

US06

C

1.50

-12.6864

0.0058

0.1398

0.0035

252.4

0.0059

0.0061

0.0001

34.42

0.351

Veh_A

US06

c

1.50

-12.7376

0.0043

0.1698

0.0035

261.1

0.0045

0.0046

0.0043

33.26

0.388

Veh_A

US06

D

1.41

-10.1492

0.0040

0.1642

0.0033

254.7

0.0042

0.0043

0.0001

33.92

0.654

Veh_A

US06

D

1.41

-1.6125

0.0057

0.4718

0.0046

262.8

0.0058

0.0060

0.0001

32.81

0.806

Veh_A

US06

D

1.41

-12.8400

0.0059

0.0669

0.0042

248.7

0.0063

0.0064

0.0000

34.76

0.403

Veh_A

US06

D

1.41

-10.7722

0.0035

0.1655

0.0037

250.4

0.0035

0.0036

0.0001

34.50

0.339

Veh_B

FTP

D

1.41

-0.6701

0.0113

0.0341

0.0044

162.6

0.0090

0.0103

0.0023

55.77

0.196

Veh_B

FTP

A

2.72

-0.6655

0.0122

0.0385

0.0013

160.5

0.0101

0.0110

0.0021

57.61

0.252

Veh_B

FTP

D

1.41

-0.6501

0.0109

0.0278

0.0019

165.7

0.0087

0.0099

0.0022

54.13

0.202

Veh_B

FTP

D

1.41

-0.5110

0.0109

0.0363

0.0027

155.1

0.0086

0.0098

0.0023

61.88

0.232

Veh_B

FTP

B

1.53

-0.4632

0.0128

0.0423

0.0021

162.9

0.0104

0.0114

0.0024

56.81

0.094

Veh_B

FTP

A

2.72

-0.3227

0.0133

0.0448

0.0015

165.1

0.0110

0.0121

0.0023

55.57

0.272

Veh_B

FTP

B

1.53

-0.2416

0.0115

0.0428

0.0019

161.0

0.0096

0.0105

0.0019

57.14

0.147

Veh_B

FTP

B

1.53

-0.1959

0.0125

0.0443

0.0023

165.9

0.0103

0.0113

0.0022

54.69

0.101

Veh_B

FTP

C

1.50

-0.1911

0.0115

0.0306

0.0026

168.9

0.0094

0.0103

0.0021

53.55

0.194

Veh_B

FTP

A

2.72

-0.1490

0.0148

0.0584

0.0018

166.2

0.0123

0.0134

0.0025

55.47

0.286

Veh_B

FTP

C

1.50

-0.1363

0.0113

0.0344

0.0019

159.4

0.0093

0.0102

0.0020

58.56

0.111

Veh_B

FTP

A

2.72

-0.1319

0.0140

0.0473

0.0085

162.8

0.0117

0.0128

0.0024

56.84

0.206

Veh_B

FTP

D

1.41

-0.1305

0.0117

0.0280

0.0029

162.3

0.0092

0.0105

0.0024

55.84

0.234

Veh_B

FTP

B

1.53

-0.1222

0.0128

0.0419

0.0025

167.0

0.0106

0.0116

0.0022

53.69

0.140

Veh_B

FTP

B

1.53

-0.0050

0.0156

0.0592

0.0023

166.4

0.0133

0.0146

0.0023

54.80

0.134

Veh_B

FTP

A

2.72

0.0081

0.0141

0.0563

0.0035

169.7

0.0118

0.0129

0.0023

53.89

0.339

Veh_B

FTP

A

2.72

0.0442

0.0136

0.0453

0.0021

156.2

0.0117

0.0128

0.0020

63.11

0.392

Veh_B

FTP

A

2.72

0.1750

0.0109

0.0296

0.0025

166.7

0.0088

0.0097

0.0020

54.57

0.287

Veh_B

FTP

C

1.50

0.2358

0.0115

0.0542

0.0023

163.1

0.0095

0.0104

0.0020

56.47

0.238

Veh_B

FTP

A

2.72

0.2661

0.0120

0.0433

0.0014

164.3

0.0097

0.0106

0.0023

56.13

0.318

Veh_B

FTP

C

1.50

0.5591

0.0131

0.0526

0.0025

161.9

0.0107

0.0117

0.0024

57.58

0.138

Veh_B

US06

A

2.72

-2.0674

0.0148

0.1168

0.0069

251.5

0.0127

0.0131

0.0021

34.70

0.377

Veh_B

US06

A

2.72

-2.8128

0.0108

0.1338

0.0062

247.7

0.0092

0.0095

0.0016

35.26

0.364

Veh_B

US06

A

2.72

-2.7915

0.0106

0.1236

0.0064

247.8

0.0089

0.0091

0.0018

35.26

0.280

Veh_B

US06

A

2.72

-3.4037

0.0108

0.0772

0.0061

247.3

0.0088

0.0091

0.0020

35.41

0.320

Veh_B

US06

A

2.72

-4.1688

0.0089

0.0966

0.0060

250.6

0.0075

0.0077

0.0015

34.84

0.211

2 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_B

US06

A

2.72

-3.1561

0.0086

0.0601

0.0047

245.8

0.0072

0.0074

0.0015

35.56

0.221

Veh_B

US06

A

2.72

-3.5419

0.0081

0.0853

0.0054

247.6

0.0066

0.0068

0.0015

35.27

0.188

Veh_B

US06

A

2.72

-1.9445

0.0160

0.2352

0.0054

245.2

0.0139

0.0143

0.0021

35.66

0.227

Veh_B

US06

A

2.72

-3.4042

0.0186

0.1449

0.0051

245.7

0.0165

0.0170

0.0021

35.54

0.178

Veh_B

US06

B

1.53

-4.3472

0.0083

0.0561

0.0054

246.6

0.0068

0.0070

0.0015

35.30

0.206

Veh_B

US06

B

1.53

-3.1039

0.0080

0.0612

0.0048

246.7

0.0063

0.0065

0.0017

35.30

0.345

Veh_B

US06

B

1.53

-2.7072

0.0063

0.0374

0.0045

247.2

0.0050

0.0052

0.0013

35.31

0.242

Veh_B

US06

B

1.53

-3.6977

0.0088

0.0718

0.0039

246.2

0.0072

0.0074

0.0016

35.44

0.184

Veh_B

US06

B

1.53

-3.8261

0.0066

0.0313

0.0062

246.3

0.0052

0.0053

0.0014

35.45

0.065

Veh_B

US06

C

1.50

-1.7980

0.0093

0.0867

0.0028

249.1

0.0075

0.0077

0.0018

34.83

0.171

Veh_B

US06

C

1.50

-2.6628

0.0089

0.0905

0.0044

243.8

0.0074

0.0076

0.0016

35.54



Veh_B

US06

C

1.50

-1.5753

0.0111

0.2018

0.0050

247.5

0.0092

0.0094

0.0020

35.08

0.169

Veh_B

US06

C

1.50

-2.4368

0.0120

0.0950

0.0066

246.4

0.0100

0.0104

0.0019

35.25

0.156

Veh_B

US06

C

1.50

-3.2767

0.0178

0.1929

0.0055

264.0

0.0153

0.0157

0.0025

32.83

0.263

Veh_B

US06

D

1.41

-4.0494

0.0081

0.0530

0.0039

242.2

0.0066

0.0068

0.0015

35.65

0.309

Veh_B

US06

D

1.41

-2.9170

0.0104

0.1005

0.0073

245.1

0.0087

0.0089

0.0018

35.20

0.551

Veh_B

US06

D

1.41

-2.6491

0.0067

0.0359

0.0030

243.8

0.0053

0.0054

0.0014

35.36

0.179

Veh_B

US06

D

1.41

-0.6324

0.0050

0.0406

0.0057

247.4

0.0037

0.0038

0.0013

34.93

0.245

Veh_C

FTP

A

2.72

6.1734

0.0369

0.1367

0.0306

487.8

0.0258

0.0283

0.0120

17.86

8.100

Veh_C

FTP

A

2.72

0.2027

0.0401

0.2675

0.0191

478.7

0.0271

0.0297

0.0141

18.20

8.200

Veh_C

FTP

A

2.72

5.8207

0.0522

0.3557

0.0142

486.2

0.0388

0.0425

0.0153

17.91

10.130

Veh_C

FTP

A

2.72

3.3338

0.0433

0.3588

0.0222

486.0

0.0301

0.0330

0.0142

17.92

9.200

Veh_C

FTP

A

2.72

2.2118

0.0508

0.2433

0.0194

494.9

0.0354

0.0388

0.0167

17.60

8.546

Veh_C

FTP

A

2.72

2.5501

0.0398

0.2146

0.0143

494.1

0.0255

0.0279

0.0155

17.63

8.301

Veh_C

FTP

A

2.72

4.1579

0.0424

0.2828

0.0121

490.0

0.0282

0.0309

0.0153

17.77

8.972

Veh_C

FTP

A

2.72

-0.2650

0.0391

0.2262

0.0189

491.7

0.0258

0.0283

0.0143

17.72

8.103

Veh_C

FTP

B

1.53

2.1983

0.0377

0.2589

0.0231

498.0

0.0255

0.0279

0.0131

17.50

5.469

Veh_C

FTP

B

1.53

1.0656

0.0391

0.1898

0.0210

494.9

0.0268

0.0294

0.0132

17.61

6.077

Veh_C

FTP

B

1.53

3.8029

0.0417

0.2531

0.0444

490.0

0.0287

0.0315

0.0141

17.78

5.767

Veh_C

FTP

B

1.53

3.2705

0.0349

0.2185

0.0344

492.9

0.0222

0.0243

0.0138

17.68

6.728

Veh_C

FTP

Base

1.49

1.9563

0.0332

0.2033

0.0479

481.2

0.0220

0.0242

0.0121

17.98

5.446

Veh_C

FTP

Base

1.49

3.5542

0.0393

0.2252

0.0245

474.5

0.0268

0.0294

0.0136

18.23

6.121

Veh_C

FTP

Base

1.49

1.0859

0.0342

0.2298

0.0290

480.9

0.0042

0.0046

0.0101

17.99

5.216

3 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_C

FTP

Base

1.49

-0.6617

0.0443

0.2466

0.0286

486.0

0.0297

0.0326

0.0158

17.80

5.560

Veh_C

FTP

C

1.50

0.8746

0.0343

0.2855

0.0236

487.7

0.0225

0.0247

0.0128

17.72

5.664

Veh_C

FTP

C

1.50

0.8156

0.0483

0.3074

0.0143

485.4

0.0341

0.0374

0.0154

17.80

5.511

Veh_C

FTP

C

1.50

3.0836

0.0351

0.2583

0.0120

486.9

0.0227

0.0249

0.0134

17.75

5.444

Veh_C

FTP

C

1.50

1.2354

0.0352

0.2425

0.0377

486.2

0.0229

0.0251

0.0135

17.77

5.265

Veh_C

FTP

D

1.41

2.0575

0.0377

0.2435

0.0441

474.3

0.0256

0.0291

0.0132

18.09



Veh_C

FTP

D

1.41

0.3299

0.0398

0.2141

0.0418

470.0

0.0261

0.0296

0.0146

18.26

5.200

Veh_C

FTP

D

1.41

1.7103

0.0404

0.2555

0.0282

468.1

0.0281

0.0319

0.0134

18.33

5.900

Veh_C

FTP

D

1.41

3.1898

0.0481

0.2720

0.0320

467.6

0.0343

0.0389

0.0150

18.35

6.700

Veh_C

FTP

D

1.41

6.2909

0.0388

0.2284

0.0310

480.6

0.0276

0.0313

0.0122

17.86

5.100

Veh_C

FTP

D

1.41

1.6209

0.0107

0.0957

0.0087

456.1

0.0037

0.0042

0.0076

18.29

6.000

Veh_C

US06

A

2.72

6.1100

0.0343

1.2312

0.0099

528.0

0.0223

0.0230

0.0130

16.45

5.200

Veh_C

US06

A

2.72

-2.6100

0.0257

1.9297

0.0132

549.5

0.0271

0.0279

0.0141

15.78

5.700

Veh_C

US06

A

2.72

-5.3800

0.0303

0.3557

0.0142

486.2

0.0196

0.0202

0.0116

16.53

4.500

Veh_C

US06

A

2.72

-2.6800

0.0283

1.7641

0.0107

534.8

0.0171

0.0176

0.0121

16.22

5.700

Veh_C

US06

A

2.72

-4.9700

0.0218

2.2273

0.0095

539.9

0.0127

0.0131

0.0099

16.04

5.310

Veh_C

US06

A

2.72

3.5500

0.0283

1.7209

0.0096

564.0

0.0179

0.0184

0.0155

15.38

4.598

Veh_C

US06

A

2.72

-1.0400

0.0219

1.4875

0.0104

542.5

0.0133

0.0137

0.0093

16.00

5.181

Veh_C

US06

A

2.72

-6.4700

0.0242

1.5707

0.0069

535.5

0.0144

0.0148

0.0106

16.21

4.460

Veh_C

US06

B

1.53

0.6200

0.0294

1.9781

0.0073

538.8

0.0173

0.0178

0.0131

16.09

3.132

Veh_C

US06

B

1.53

-2.6800

0.0254

1.5207

0.0076

543.6

0.0155

0.0160

0.0107

15.97

3.683

Veh_C

US06

B

1.53

2.5500

0.0306

3.8743

0.0195

550.3

0.0171

0.0176

0.0146

15.68

5.779

Veh_C

US06

B

1.53

-4.9400

0.0263

3.6763

0.0091

534.2

0.0146

0.0150

0.0127

16.15

2.916

Veh_C

US06

Base

1.49

-4.0200

0.0218

1.4534

0.0082

525.8

0.0125

0.0129

0.0100

16.39

8.307

Veh_C

US06

Base

1.49

-1.8900

0.0232

1.7900

0.0084

525.0

0.0140

0.0144

0.0103

16.40

4.065

Veh_C

US06

Base

1.49

0.2400

0.0262

1.9493

0.0093

527.0

0.0152

0.0157

0.0119

16.33

3.733

Veh_C

US06

Base

1.49

3.9100

0.0222

1.4583

0.0096

557.4

0.0124

0.0128

0.0106

15.47

4.146

Veh_C

US06

C

1.50

0.0700

0.0255

1.5123

0.0089

546.0

0.0155

0.0160

0.0109

15.77

4.310

Veh_C

US06

C

1.50

-0.6900

0.0254

2.0351

0.0101

554.9

0.0147

0.0151

0.0116

15.50

4.860

Veh_C

US06

C

1.50

-1.2000

0.0237

1.5861

0.0096

543.0

0.0138

0.0142

0.0107

15.86

4.980

Veh_C

US06

C

1.50

-6.3800

0.0231

1.3501

0.0084

528.0

0.0130

0.0134

0.0114

16.32

4.130

Veh_C

US06

D

1.41

0.3100

0.0312

1.2021

0.0126

518.1

0.0192

0.0198

0.0130

16.52

3.500

Veh_C

US06

D

1.41

2.9200

0.0306

1.4352

0.0110

517.4

0.0304

0.0313

0.0002

16.53

6.300

4 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_C

US06

D

1.41

-0.8700

0.0277

1.1399

0.0096

511.6

0.0166

0.0171

0.0120

16.73

3.400

Veh_C

US06

D

1.41

-2.1700

0.0271

1.1966

0.0161

506.4

0.0161

0.0166

0.0118

16.90

2.900

Veh_C

US06

D

1.41

-3.0900

0.0220

0.8232

0.0100

521.0

0.0130

0.0134

0.0098

16.45

2.900

Veh_C

US06

D

1.41

-3.6300

0.0257

1.0320

0.0102

500.3

0.0165

0.0170

0.0100

17.11

3.000

Veh_D

FTP

A

2.72

-0.5004

0.0054

0.0998

0.0132

293.3

0.0040

0.0044

0.0019

29.71

0.650

Veh_D

FTP

A

2.72

0.6442

0.0076

0.0948

0.0113

298.8

0.0061

0.0066

0.0018

29.16

0.620

Veh_D

FTP

A

2.72

0.5377

0.0059

0.1401

0.0149

291.9

0.0041

0.0045

0.0021

29.84

0.670

Veh_D

FTP

A

2.72

2.9721

0.0070

0.0964

0.0113

297.6

0.0054

0.0059

0.0018

29.28

1.160

Veh_D

FTP

A

2.72

2.6254

0.0065

0.3771

0.0124

299.6

0.0046

0.0051

0.0021

29.04

0.990

Veh_D

FTP

A

2.72

0.8295

0.0057

0.1375

0.0095

296.6

0.0043

0.0047

0.0016

29.38

0.560

Veh_D

FTP

A

2.72

2.2527

0.0067

0.1220

0.0085

300.7

0.0053

0.0058

0.0017

28.97

0.600

Veh_D

FTP

A

2.72

1.9594

0.0063

0.1541

0.0086

299.2

0.0047

0.0051

0.0019

29.12

0.840

Veh_D

FTP

A

2.72

1.3344

0.0061

0.1105

0.0095

291.3

0.0047

0.0052

0.0017

29.91

0.770

Veh_D

FTP

B

1.53

1.0525

0.0056

0.0746

0.0119

290.2

0.0041

0.0045

0.0020

30.04

0.490

Veh_D

FTP

B

1.53

-0.4700

0.0063

0.0912

0.0154

286.3

0.0045

0.0049

0.0021

30.45

0.570

Veh_D

FTP

B

1.53

0.5788

0.0060

0.0962

0.0139

297.0

0.0045

0.0049

0.0021

29.36

0.340

Veh_D

FTP

B

1.53

-0.9005

0.0063

0.0770

0.0124

292.6

0.0049

0.0054

0.0018

29.80

0.360

Veh_D

FTP

B

1.53

-0.0299

0.0056

0.1171

0.0098

283.7

0.0041

0.0045

0.0021

30.73

0.340

Veh_D

FTP

B

1.53

1.3016

0.0056

0.1285

0.0130

284.1

0.0040

0.0043

0.0022

30.68

0.370

Veh_D

FTP

C

1.50

1.5968

0.0082

0.1333

0.0122

284.3

0.0059

0.0065

0.0026

30.40

0.740

Veh_D

FTP

C

1.50

4.1644

0.0067

0.1230

0.0130

292.7

0.0048

0.0052

0.0022

29.53

0.810

Veh_D

FTP

C

1.50

2.4927

0.0061

0.1167

0.0127

289.2

0.0045

0.0049

0.0020

29.90

0.740

Veh_D

FTP

C

1.50

-0.5243

0.0072

0.0974

0.0102

289.2

0.0052

0.0057

0.0024

29.90

1.040

Veh_D

FTP

C

1.50

3.6817

0.0064

0.0964

0.0135

294.4

0.0048

0.0053

0.0019

29.36

0.720

Veh_D

FTP

D

1.41

2.5747

0.0072

0.0911

0.0108

295.5

0.0057

0.0065

0.0020

29.06

0.350

Veh_D

FTP

D

1.41

2.1399

0.0070

0.1006

0.0139

293.4

0.0054

0.0061

0.0020

29.26

0.320

Veh_D

FTP

D

1.41

1.3832

0.0059

0.0990

0.0101

289.3

0.0042

0.0048

0.0019

29.68

0.240

Veh_D

FTP

D

1.41

1.6562

0.0070

0.1067

0.0126

287.6

0.0053

0.0060

0.0022

29.86

0.330

Veh_D

FTP

D

1.41

2.2479

0.0081

0.1128

0.0122

287.7

0.0062

0.0071

0.0022

29.84

0.380

Veh_D

FTP

D

1.41

1.7661

0.0053

0.0786

0.0132

287.9

0.0037

0.0042

0.0019

29.83

0.210

Veh_D

US06

A

2.72

-1.9962

0.0079

2.5961

0.0326

384.4

0.0048

0.0050

0.0036

22.45

1.030

Veh_D

US06

A

2.72

-4.3293

0.0067

2.6572

0.0337

368.8

0.0043

0.0044

0.0028

23.38

0.820

Veh_D

US06

A

2.72

-2.9614

0.0082

4.2441

0.0330

369.8

0.0050

0.0052

0.0037

23.16

0.660

5 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_D

US06

A

2.72

-2.7801

0.0074

3.7692

0.0338

371.0

0.0044

0.0046

0.0035

23.13

1.080

Veh_D

US06

A

2.72

0.3842

0.0071

2.8776

0.0336

373.0

0.0045

0.0046

0.0030

23.09

0.610

Veh_D

US06

A

2.72

-6.0461

0.0049

0.7768

0.0356

357.5

0.0031

0.0032

0.0022

24.31

0.710

Veh_D

US06

A

2.72

0.2266

0.0044

0.7391

0.0345

362.5

0.0027

0.0028

0.0020

23.97

0.540

Veh_D

US06

A

2.72

1.7833

0.0053

1.5032

0.0393

361.9

0.0032

0.0033

0.0023

23.94

0.580

Veh_D

US06

A

2.72

5.5112

0.0057

0.8381

0.0357

350.1

0.0038

0.0039

0.0022

24.81

1.060

Veh_D

US06

B

1.53

-4.4002

0.0047

1.2500

0.0296

350.8

0.0026

0.0027

0.0021

24.73

0.360

Veh_D

US06

B

1.53

-6.5399

0.0059

1.7707

0.0361

366.3

0.0035

0.0036

0.0028

23.63

0.600

Veh_D

US06

B

1.53

-6.4326

0.0061

1.6687

0.0359

358.3

0.0037

0.0038

0.0028

24.17

0.820

Veh_D

US06

B

1.53

-6.1596

0.0047

0.7692

0.0354

354.5

0.0029

0.0029

0.0021

24.52

0.350

Veh_D

US06

B

1.53

-6.4103

0.0043

0.6579

0.0308

352.6

0.0027

0.0028

0.0018

24.67

0.470

Veh_D

US06

B

1.53

-4.8155

0.0051

1.2135

0.0316

361.5

0.0032

0.0033

0.0022

24.00

0.790

Veh_D

US06

C

1.50

-1.2267

0.0052

1.1945

0.0317

362.1

0.0033

0.0034

0.0023

23.77

0.580

Veh_D

US06

C

1.50

-0.3142

0.0058

1.9061

0.0296

365.1

0.0035

0.0036

0.0027

23.50

0.600

Veh_D

US06

C

1.50

-1.9513

0.0060

2.2899

0.0341

366.5

0.0033

0.0034

0.0031

23.37

1.030

Veh_D

US06

C

1.50

-2.2782

0.0066

2.5177

0.0313

367.7

0.0037

0.0038

0.0033

23.28

0.590

Veh_D

US06

D

1.41

-1.8544

0.0049

1.0140

0.0335

360.9

0.0029

0.0030

0.0022

23.70

0.680

Veh_D

US06

D

1.41

-3.8956

0.0037

0.4646

0.0342

359.0

0.0022

0.0022

0.0017

23.88

0.660

Veh_D

US06

D

1.41

-5.7204

0.0033

0.4077

0.0292

349.5

0.0020

0.0020

0.0015

24.53

0.400

Veh_D

US06

D

1.41

-3.9463

0.0037

0.5240

0.0324

354.5

0.0022

0.0023

0.0017

24.18

0.450

Veh_D

US06

D

1.41

-5.4905

0.0032

0.3494

0.0294

348.8

0.0019

0.0020

0.0015

24.59

0.380

Veh_D

US06

D

1.41

-2.5480

0.0039

0.4725

0.0313

353.1

0.0025

0.0026

0.0016

24.28

0.360

Veh_E

FTP

A

2.72

1.5206

0.0184

0.2208

0.0138

304.9

0.0134

0.0147

0.0052

28.56

4.035

Veh_E

FTP

A

2.72

1.0320

0.0174

0.2422

0.0154

307.0

0.0123

0.0135

0.0053

28.37

4.043

Veh_E

FTP

A

2.72

1.5588

0.0196

0.2260

0.0137

307.7

0.0147

0.0161

0.0053

28.28

4.237

Veh_E

FTP

A

2.72

1.4708

0.0196

0.2518

0.0145

307.8

0.0144

0.0158

0.0054

28.28

4.100

Veh_E

FTP

A

2.72

1.3675

0.0205

0.2548

0.0144

306.2

0.0155

0.0169

0.0053

28.46

0.000

Veh_E

FTP

A

2.72

0.5605

0.0198

0.3093

0.0155

303.4

0.0146

0.0159

0.0054

28.74

4.173

Veh_E

FTP

A

2.72

0.7643

0.0172

0.2047

0.0149

304.0

0.0127

0.0139

0.0047

28.66

4.498

Veh_E

FTP

A

2.72

-0.0245

0.0219

0.1939

0.0106

305.7

0.0173

0.0189

0.0048

28.47

4.065

Veh_E

FTP

A

2.72

2.2474

0.0191

0.1698

0.0124

305.0

0.0147

0.0161

0.0046

28.57

3.683

Veh_E

FTP

A

2.72

1.5258

0.0169

0.1647

0.0128

305.2

0.0126

0.0138

0.0045

28.57

4.060

Veh_E

FTP

A

2.72

1.5251

0.0182

0.1924

0.0132

307.0

0.0135

0.0147

0.0050

28.38

4.473

6 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_E

FTP

A

2.72

0.7817

0.0183

0.1710

0.0139

303.2

0.0136

0.0149

0.0049

28.76

3.645

Veh_E

FTP

B

1.53

1.8409

0.0173

0.2703

0.0135

305.7

0.0124

0.0136

0.0052

28.46

3.228

Veh_E

FTP

B

1.53

2.3344

0.0159

0.2281

0.0163

307.2

0.0113

0.0124

0.0048

28.37

3.069

Veh_E

FTP

B

1.53

0.3928

0.0167

0.2501

0.0150

307.0

0.0121

0.0132

0.0049

28.37

3.248

Veh_E

FTP

B

1.53

1.6721

0.0171

0.2079

0.0151

308.7

0.0128

0.0141

0.0045

28.19

3.084

Veh_E

FTP

B

1.53

1.6584

0.0179

0.2502

0.0138

310.3

0.0133

0.0145

0.0049

28.10

3.457

Veh_E

FTP

B

1.53

0.4384

0.0162

0.2646

0.0135

307.6

0.0115

0.0125

0.0050

28.28

3.380

Veh_E

FTP

C

1.50

0.9735

0.0159

0.2615

0.0137

304.1

0.0114

0.0124

0.0048

28.41

2.436

Veh_E

FTP

C

1.50

0.9784

0.0177

0.2316

0.0149

304.7

0.0130

0.0142

0.0049

28.32

2.455

Veh_E

FTP

C

1.50

2.2849

0.0200

0.2791

0.0151

306.6

0.0148

0.0162

0.0054

28.13

2.925

Veh_E

FTP

C

1.50

3.4843

0.0184

0.2271

0.0136

306.3

0.0137

0.0150

0.0049

28.23

2.520

Veh_E

FTP

C

1.50

1.0772

0.0188

0.2269

0.0153

305.1

0.0142

0.0155

0.0048

28.32

2.504

Veh_E

FTP

C

1.50

1.5210

0.0145

0.2252

0.0145

305.8

0.0099

0.0108

0.0048

28.23

2.514

Veh_E

FTP

D

1.41

1.9389

0.0158

0.1881

0.0145

304.8

0.0115

0.0131

0.0045

28.18

2.373

Veh_E

FTP

D

1.41

1.5326

0.0144

0.1865

0.0167

304.0

0.0100

0.0113

0.0046

28.27

2.737

Veh_E

FTP

D

1.41

0.8609

0.0147

0.1770

0.0132

303.3

0.0105

0.0119

0.0044

28.37

2.609

Veh_E

FTP

D

1.41

1.0184

0.0149

0.1915

0.0146

303.2

0.0104

0.0118

0.0048

28.36

2.914

Veh_E

FTP

D

1.41

0.8633

0.0163

0.1693

0.0126

305.3

0.0120

0.0136

0.0045

28.18

2.909

Veh_E

FTP

D

1.41

0.8156

0.0149

0.2221

0.0145

304.1

0.0103

0.0117

0.0048

28.27

2.964

Veh_E

US06

A

2.72

-0.4200

0.0149

2.6555

0.0132

347.9

0.0063

0.0065

0.0090

24.77

1.115

Veh_E

US06

A

2.72

-2.1560

0.0144

1.8607

0.0146

343.3

0.0064

0.0066

0.0083

25.21

2.357

Veh_E

US06

A

2.72

-1.3170

0.0156

1.9370

0.0151

343.4

0.0070

0.0072

0.0089

25.20

1.113

Veh_E

US06

A

2.72

-2.0470

0.0160

2.1129

0.0188

347.2

0.0071

0.0073

0.0093

24.90

1.480

Veh_E

US06

A

2.72

-1.7300

0.0174

2.1921

0.0199

338.1

0.0081

0.0083

0.0097

25.54

1.308

Veh_E

US06

A

2.72

-1.9740

0.0148

1.8620

0.0203

337.6

0.0064

0.0066

0.0087

25.58

0.960

Veh_E

US06

A

2.72

-0.2550

0.0165

2.1570

0.0224

343.6

0.0077

0.0080

0.0092

25.11

1.056

Veh_E

US06

A

2.72

-2.3000

0.0145

1.8799

0.0158

343.3

0.0067

0.0069

0.0082

25.21

0.929

Veh_E

US06

A

2.72

-3.1800

0.0156

2.1784

0.0174

337.8

0.0073

0.0075

0.0087

25.54

1.236

Veh_E

US06

A

2.72

-2.6640

0.0172

2.2945

0.0220

343.2

0.0082

0.0085

0.0094

25.16

1.418

Veh_E

US06

A

2.72

-2.5840

0.0175

2.2521

0.0257

344.9

0.0084

0.0086

0.0095

25.02

1.336

Veh_E

US06

A

2.72

-1.4000

0.0157

1.8586

0.0217

338.9

0.0071

0.0073

0.0090

25.51

1.119

Veh_E

US06

B

1.53

-2.3800

0.0161

2.1766

0.0190

343.5

0.0072

0.0074

0.0093

25.17

0.962

Veh_E

US06

B

1.53

-0.9080

0.0159

2.2745

0.0177

343.4

0.0074

0.0076

0.0089

25.16

1.311

7 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_E

US06

B

1.53

-2.3380

0.0157

2.0830

0.0204

342.2

0.0074

0.0076

0.0087

25.26

1.163

Veh_E

US06

B

1.53

-1.7040

0.0145

2.4309

0.0172

348.3

0.0062

0.0064

0.0087

24.79

1.231

Veh_E

US06

B

1.53

-1.2810

0.0155

2.5716

0.0208

350.4

0.0070

0.0072

0.0089

24.63

1.426

Veh_E

US06

B

1.53

-1.5280

0.0143

1.9097

0.0194

344.6

0.0066

0.0068

0.0081

25.06

0.855

Veh_E

US06

C

1.50

-2.1060

0.0166

2.4967

0.0169

342.8

0.0075

0.0077

0.0095

24.93

0.890

Veh_E

US06

C

1.50

-1.7730

0.0189

3.0796

0.0198

345.4

0.0089

0.0091

0.0104

24.72

1.770

Veh_E

US06

C

1.50

-2.6530

0.0169

2.3460

0.0214

341.3

0.0076

0.0078

0.0097

25.09

0.949

Veh_E

US06

C

1.50

-0.8850

0.0179

3.1456

0.0192

352.7

0.0086

0.0088

0.0097

24.16

1.644

Veh_E

US06

C

1.50

-0.1680

0.0138

2.2622

0.0189

348.3

0.0063

0.0065

0.0078

24.60

0.727

Veh_E

US06

C

1.50

-1.9850

0.0153

2.2006

0.0166

348.2

0.0069

0.0071

0.0088

24.61

1.230

Veh_E

US06

D

1.41

-0.8640

0.0155

2.1338

0.0197

339.6

0.0070

0.0072

0.0089

25.06

0.946

Veh_E

US06

D

1.41

-0.8640

0.0155

2.1338

0.0197

339.6

0.0070

0.0072

0.0089

25.06

1.494

Veh_E

US06

D

1.41

-1.0580

0.0144

1.8457

0.0197

341.6

0.0066

0.0068

0.0082

24.95

0.931

Veh_E

US06

D

1.41

-2.5510

0.0130

1.9595

0.0177

340.4

0.0055

0.0057

0.0079

25.08

1.016

Veh_E

US06

D

1.41

-2.1640

0.0138

1.5418

0.0163

333.0

0.0062

0.0064

0.0079

25.65

0.976

Veh_E

US06

D

1.41

-4.0690

0.0158

2.0421

0.0206

335.2

0.0068

0.0070

0.0094

25.44

1.139

Veh_F

FTP

A

2.72

4.3485

0.0269

0.0665

0.0046

243.4

0.0227

0.0249

0.0040

35.82

0.796

Veh_F

FTP

A

2.72

4.1936

0.0372

0.0970

0.0078

241.8

0.0330

0.0362

0.0041

36.03

0.830

Veh_F

FTP

A

2.72

3.6327

0.0307

0.0832

0.0058

240.7

0.0267

0.0293

0.0038

36.20

0.791

Veh_F

FTP

A

2.72

3.7492

0.0288

0.0729

0.0048

240.6

0.0242

0.0265

0.0044

36.23

0.874

Veh_F

FTP

A

2.72

3.7733

0.0261

0.0642

0.0047

240.8

0.0218

0.0239

0.0042

36.20

0.774

Veh_F

FTP

A

2.72

3.7804

0.0271

0.0672

0.0045

240.4

0.0227

0.0248

0.0044

36.26

0.778

Veh_F

FTP

A

2.72

3.9452

0.0273

0.0629

0.0061

240.2

0.0232

0.0254

0.0040

36.28

0.730

Veh_F

FTP

A

2.72

3.7737

0.0292

0.0644

0.0054

240.7

0.0250

0.0274

0.0041

36.22

0.736

Veh_F

FTP

B

1.53

3.8287

0.0301

0.0847

0.0053

241.6

0.0261

0.0286

0.0040

36.07

0.537

Veh_F

FTP

B

1.53

3.9421

0.0274

0.0753

0.0054

240.7

0.0234

0.0257

0.0039

36.21

0.442

Veh_F

FTP

B

1.53

3.6580

0.0250

0.0704

0.0052

239.3

0.0218

0.0239

0.0032

36.42

0.421

Veh_F

FTP

B

1.53

3.5104

0.0274

0.0712

0.0057

241.4

0.0236

0.0259

0.0037

36.10

0.479

Veh_F

FTP

Base

1.49

4.0119

0.0265

0.0809

0.0050

238.8

0.0223

0.0245

0.0041

36.22

0.398

Veh_F

FTP

Base

1.49

4.4680

0.0266

0.0846

0.0054

238.5

0.0226

0.0248

0.0039

36.27

0.430

Veh_F

FTP

Base

1.49

4.1589

0.0293

0.0839

0.0058

237.5

0.0257

0.0282

0.0035

36.42

0.399

Veh_F

FTP

Base

1.49

4.5260

0.0281

0.0846

0.0053

236.8

0.0238

0.0261

0.0042

36.53

0.527

Veh_F

FTP

C

1.50

4.0776

0.0257

0.0758

0.0058

236.5

0.0218

0.0239

0.0038

36.55

0.362

8 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_F

FTP

C

1.50

3.9239

0.0275

0.0891

0.0051

237.6

0.0229

0.0251

0.0045

36.37

0.436

Veh_F

FTP

C

1.50

4.0739

0.0265

0.0810

0.0051

237.2

0.0222

0.0243

0.0042

36.43

0.396

Veh_F

FTP

c

1.50

4.4208

0.0254

0.0703

0.0048

238.0

0.0211

0.0231

0.0042

36.32

0.453

Veh_F

FTP

D

1.41

3.5123

0.0254

0.0739

0.0052

236.8

0.0210

0.0239

0.0042

36.28

0.363

Veh_F

FTP

D

1.41

3.8794

0.0250

0.0766

0.0055

237.2

0.0206

0.0234

0.0043

36.23

0.282

Veh_F

FTP

D

1.41

4.2262

0.0253

0.0795

0.0056

238.3

0.0210

0.0239

0.0042

36.05

0.397

Veh_F

FTP

D

1.41

4.0540

0.0257

0.0774

0.0054

238.6

0.0213

0.0241

0.0043

36.01

0.407

Veh_F

US06

A

2.72

-2.1154

0.0210

1.3062

0.0232

268.8

0.0167

0.0172

0.0042

32.20

1.175

Veh_F

US06

A

2.72

-2.8137

0.0208

1.6310

0.0070

271.1

0.0177

0.0182

0.0030

31.87

0.785

Veh_F

US06

A

2.72

-3.3760

0.0167

1.3348

0.0252

265.7

0.0141

0.0146

0.0025

32.57

1.052

Veh_F

US06

A

2.72

-2.9746

0.0173

1.1416

0.0054

262.3

0.0135

0.0139

0.0037

33.02

0.526

Veh_F

US06

A

2.72

-3.1937

0.0143

0.8279

0.0059

261.6

0.0111

0.0114

0.0031

33.18

0.593

Veh_F

US06

A

2.72

-3.7014

0.0162

1.3085

0.0143

262.3

0.0125

0.0129

0.0037

32.99

0.964

Veh_F

US06

A

2.72

-3.3724

0.0174

1.0332

0.0064

263.4

0.0140

0.0144

0.0034

32.90

0.646

Veh_F

US06

A

2.72

-3.0788

0.0177

1.0800

0.0072

263.1

0.0140

0.0144

0.0036

32.94

0.553

Veh_F

US06

A

2.72

-2.7978

0.0169

1.2656

0.0065

263.2

0.0132

0.0136

0.0037

32.89

0.764

Veh_F

US06

B

1.53

-3.1159

0.0186

1.3568

0.0062

265.3

0.0151

0.0156

0.0034

32.61

0.558

Veh_F

US06

B

1.53

-2.5712

0.0179

1.3157

0.0066

264.8

0.0145

0.0149

0.0034

32.68

0.719

Veh_F

US06

B

1.53

-2.9081

0.0165

1.3549

0.0058

264.0

0.0136

0.0140

0.0028

32.77

0.788

Veh_F

US06

B

1.53

-3.4271

0.0169

1.3159

0.0216

263.5

0.0135

0.0139

0.0033

32.84

0.674

Veh_F

US06

Base

1.49

-2.5266

0.0166

1.3110

0.0207

262.7

0.0130

0.0133

0.0035

32.71

0.594

Veh_F

US06

Base

1.49

-2.4936

0.0162

1.3302

0.0200

260.5

0.0123

0.0126

0.0038

32.97

0.436

Veh_F

US06

Base

1.49

-2.7684

0.0182

1.3306

0.0067

260.4

0.0140

0.0144

0.0041

32.99

0.498

Veh_F

US06

Base

1.49

-3.0603

0.0149

1.0054

0.0056

260.1

0.0117

0.0120

0.0032

33.08

0.733

Veh_F

US06

C

1.50

Status

0.0180

1.3457

0.0058

262.5

0.0139

0.0144

0.0040

32.68

0.741

Veh_F

US06

C

1.50

-3.3117

0.0147

0.7226

0.0134

259.7

0.0115

0.0119

0.0031

33.16

0.651

Veh_F

US06

C

1.50

-2.7071

0.0157

0.6826

0.0060

261.2

0.0127

0.0131

0.0029

32.98

0.279

Veh_F

US06

C

1.50

-3.4144

0.0143

0.7350

0.0059

260.3

0.0111

0.0115

0.0031

33.08

0.435

Veh_F

US06

D

1.41

-3.6917

0.0169

0.9392

0.0067

258.3

0.0134

0.0138

0.0034

33.09

0.441

Veh_F

US06

D

1.41

-3.0828

0.0179

1.1532

0.0242

259.1

0.0136

0.0140

0.0042

32.94

0.371

Veh_F

US06

D

1.41

-3.8413

0.0178

0.9391

0.0062

258.4

0.0145

0.0150

0.0032

33.08

0.441

Veh_F

US06

D

1.41

-3.5863

0.0158

0.7907

0.0141

258.4

0.0125

0.0129

0.0032

33.11

0.595

Veh_G

FTP

A

2.72

-0.0711

0.0185

0.1092

0.0157

387.7

0.0137

0.0150

0.0051

22.48

1.639

9 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_G

FTP

A

2.72

-0.0773

0.0164

0.1009

0.0145

390.0

0.0130

0.0143

0.0044

22.35

1.634

Veh_G

FTP

A

2.72

-0.1661

0.0156

0.1202

0.0124

387.7

0.0110

0.0120

0.0051

22.48

1.665

Veh_G

FTP

A

2.72

-0.1129

0.0132

0.1165

0.0119

390.2

0.0089

0.0098

0.0048

22.33

1.511

Veh_G

FTP

A

2.72

0.0180

0.0166

0.1051

0.0147

389.7

0.0114

0.0125

0.0056

22.36

2.318

Veh_G

FTP

A

2.72

-0.0885

0.0147

0.1083

0.0149

390.2

0.0098

0.0107

0.0053

22.33

2.036

Veh_G

FTP

A

2.72

-0.2056

0.0147

0.0993

0.0112

387.8

0.0101

0.0111

0.0049

22.57

1.964

Veh_G

FTP

A

2.72

-0.2139

0.0140

0.0994

0.0096

390.8

0.0094

0.0103

0.0050

22.39

2.416

Veh_G

FTP

A

2.72

-0.2697

0.0125

0.0907

0.0132

389.2

0.0087

0.0096

0.0042

22.48

2.738

Veh_G

FTP

A

2.72

-0.1074

0.0155

0.1048

0.0122

387.5

0.0103

0.0113

0.0056

22.58

1.829

Veh_G

FTP

A

2.72

-0.0160

0.0162

0.1093

0.0106

386.2

0.0114

0.0125

0.0054

22.66

1.903

Veh_G

FTP

B

1.53

-0.1953

0.0130

0.1170

0.0151

385.7

0.0095

0.0104

0.0049

22.71

0.749

Veh_G

FTP

B

1.53

-0.2148

0.0143

0.1135

0.0136

383.5

0.0100

0.0110

0.0049

22.84

0.931

Veh_G

FTP

B

1.53

-0.2100

0.0145

0.1102

0.0148

385.4

0.0111

0.0122

0.0049

22.73

0.884

Veh_G

FTP

B

1.53

-0.1874

0.0127

0.1168

0.0120

387.9

0.0090

0.0098

0.0047

22.59

0.724

Veh_G

FTP

Base

1.49

-0.1389

0.0157

0.1004

0.0149

381.9

0.0115

0.0126

0.0045

22.80

0.810

Veh_G

FTP

Base

1.49

-0.2799

0.0144

0.1170

0.0134

384.6

0.0098

0.0108

0.0050

22.64

0.885

Veh_G

FTP

Base

1.49

-0.2799

0.0156

0.1044

0.0131

386.6

0.0109

0.0119

0.0051

22.52

1.095

Veh_G

FTP

C

1.50

-0.2222

0.0139

0.1165

0.0148

383.0

0.0097

0.0106

0.0050

22.87

0.628

Veh_G

FTP

C

1.50

-0.2997

0.0153

0.1039

0.0108

386.3

0.0111

0.0122

0.0048

22.50

0.635

Veh_G

FTP

C

1.50

-0.1549

0.0129

0.1192

0.0147

385.5

0.0083

0.0091

0.0049

22.55

0.750

Veh_G

FTP

C

1.50

-0.1349

0.0158

0.0997

0.0126

382.8

0.0117

0.0128

0.0043

22.70

0.671

Veh_G

FTP

C

1.50

-0.1806

0.0143

0.1087

0.0136

383.3

0.0103

0.0113

0.0049

22.67

0.754

Veh_G

FTP

D

1.41

-0.2246

0.0138

0.0960

0.0153

382.7

0.0102

0.0116

0.0043

22.65

0.550

Veh_G

FTP

D

1.41

-0.1444

0.0144

0.1009

0.0160

379.5

0.0097

0.0110

0.0052

22.84

0.556

Veh_G

FTP

D

1.41

-0.3152

0.0144

0.1043

0.0145

385.9

0.0098

0.0111

0.0050

22.47

0.530

Veh_G

FTP

D

1.41

-0.4318

0.0139

0.0909

0.0132

382.2

0.0098

0.0111

0.0043

22.69

0.647

Veh_G

FTP

D

1.41

-0.4268

0.0144

0.1008

0.0133

382.0

0.0107

0.0122

0.0048

22.69

0.716

Veh_G

FTP

D

1.41

-0.1957

0.0120

0.1090

0.0131

385.2

0.0078

0.0088

0.0050

22.51

0.829

Veh_G

US06

A

2.72

-4.8984

0.0207

3.7817

0.0162

355.0

0.0120

0.0124

0.0092

24.15

0.515

Veh_G

US06

A

2.72

-4.9236

0.0158

4.1389

0.0161

359.9

0.0070

0.0072

0.0093

23.79

0.684

Veh_G

US06

A

2.72

-4.8919

0.0243

5.1518

0.0141

360.0

0.0143

0.0148

0.0105

23.68

1.156

Veh_G

US06

A

2.72

-4.7989

0.0224

5.1221

0.0162

360.3

0.0128

0.0132

0.0102

23.67

1.328

Veh_G

US06

A

2.72

-5.1071

0.0189

2.4139

0.0129

367.3

0.0113

0.0116

0.0081

23.49

1.969

10 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_G

US06

A

2.72

-4.9432

0.0168

1.0254

0.0149

368.1

0.0103

0.0106

0.0068

23.58

1.329

Veh_G

US06

A

2.72

-4.8650

0.0140

1.2709

0.0172

358.1

0.0080

0.0083

0.0064

24.31

1.150

Veh_G

US06

A

2.72

-5.0837

0.0171

2.4253

0.0188

359.6

0.0098

0.0101

0.0077

24.09

1.699

Veh_G

US06

A

2.72

-4.7809

0.0198

3.7526

0.0167

358.7

0.0115

0.0118

0.0088

24.01

1.564

Veh_G

US06

A

2.72

-4.5705

0.0216

4.1953

0.0192

362.1

0.0124

0.0127

0.0098

23.75

0.975

Veh_G

US06

A

2.72

-5.0805

0.0189

2.9250

0.0211

359.8

0.0109

0.0113

0.0084

24.03

1.689

Veh_G

US06

B

1.53

-4.9471

0.0211

3.4555

0.0162

362.7

0.0127

0.0131

0.0089

23.69

1.702

Veh_G

US06

B

1.53

-4.9882

0.0213

4.0895

0.0154

365.0

0.0125

0.0129

0.0093

23.48

0.824

Veh_G

US06

B

1.53

-4.9539

0.0175

3.5708

0.0149

357.1

0.0097

0.0100

0.0083

24.16

1.047

Veh_G

US06

B

1.53

-5.1285

0.0169

2.4787

0.0157

356.9

0.0098

0.0101

0.0074

24.29

1.233

Veh_G

US06

B

1.53

-4.9359

0.0164

2.8579

0.0168

357.3

0.0091

0.0093

0.0077

24.22

1.140

Veh_G

US06

Base

1.49

-4.9778

0.0179

3.5458

0.0137

354.9

0.0098

0.0101

0.0085

24.16

1.225

Veh_G

US06

Base

1.49

-4.8662

0.0191

2.9878

0.0160

357.8

0.0111

0.0114

0.0085

24.03

0.729

Veh_G

US06

Base

1.49

-4.6541

0.0181

3.1864

0.0180

356.1

0.0101

0.0104

0.0085

24.12

1.461

Veh_G

US06

Base

1.49

-4.9486

0.0148

1.6395

0.0158

356.7

0.0082

0.0085

0.0069

24.25

0.765

Veh_G

US06

C

1.50

-5.0638

0.0224

4.7061

0.0160

355.1

0.0131

0.0135

0.0098

23.98

1.228

Veh_G

US06

C

1.50

-4.9671

0.0042

4.0943

0.0166

356.1

0.0000

0.0000

0.0093

23.98

0.931

Veh_G

US06

C

1.50

-5.0850

0.0204

4.2254

0.0140

355.5

0.0116

0.0119

0.0093

24.01

0.805

Veh_G

US06

C

1.50

-5.0089

0.0210

4.6245

0.0141

355.3

0.0117

0.0121

0.0098

23.98

1.468

Veh_G

US06

C

1.50

-4.9607

0.0176

3.3848

0.0151

355.7

0.0094

0.0097

0.0086

24.08

2.485

Veh_G

US06

D

1.41

-5.0395

0.0123

0.5310

0.0133

352.1

0.0070

0.0072

0.0056

24.58

1.215

Veh_G

US06

D

1.41

-4.8136

0.0146

1.2355

0.0163

352.0

0.0085

0.0088

0.0064

24.51

2.013

Veh_G

US06

D

1.41

-4.2929

0.0117

0.5682

0.0149

354.8

0.0067

0.0069

0.0053

24.38

1.102

Veh_G

US06

D

1.41

-5.0716

0.0118

0.5775

0.0127

354.7

0.0066

0.0068

0.0055

24.39

1.511

Veh_G

US06

D

1.41

-5.0776

0.0109

0.3779

0.0131

353.0

0.0061

0.0063

0.0051

24.53

1.699

Veh_G

US06

D

1.41

-4.9898

0.0133

0.3986

0.0173

352.2

0.0078

0.0080

0.0058

24.58

2.027

Veh_H

FTP

A

2.72

1.1966

0.0108

0.1991

0.0086

283.7

0.0068

0.0074

0.0046

31.08

2.117

Veh_H

FTP

A

2.72

-3.0904

0.0124

0.2154

0.0061

281.6

0.0065

0.0072

0.0063

31.31

1.989

Veh_H

FTP

A

2.72

1.1246

0.0099

0.1987

0.0090

288.7

0.0055

0.0060

0.0049

30.54

2.169

Veh_H

FTP

A

2.72

-0.7497

0.0156

0.2104

0.0045

280.2

0.0119

0.0130

0.0040

31.46

2.868

Veh_H

FTP

A

2.72

-2.9534

0.0144

0.2273

0.0064

273.2

0.0104

0.0114

0.0043

32.27

1.799

Veh_H

FTP

A

2.72

1.0880

0.0106

0.1849

0.0046

283.1

0.0069

0.0076

0.0040

31.14

1.764

Veh_H

FTP

A

2.72

0.9571

0.0100

0.1542

0.0071

276.5

0.0054

0.0059

0.0049

31.89

2.227

11 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_H

FTP

A

2.72

1.2741

0.0130

0.2480

0.0070

274.5

0.0080

0.0088

0.0050

32.11

2.777

Veh_H

FTP

A

2.72

0.8508

0.0130

0.2140

0.0060

275.5

0.0090

0.0099

0.0040

32.00

2.441

Veh_H

FTP

B

1.53

-1.9547

0.0160

0.2590

0.0080

279.5

0.0110

0.0121

0.0050

31.57

1.704

Veh_H

FTP

B

1.53

-3.0383

0.0110

0.1656

0.0036

277.5

0.0079

0.0087

0.0036



1.855

Veh_H

FTP

B

1.53

-1.5879

0.0138

0.1951

0.0034

278.2

0.0107

0.0117

0.0032

31.73

1.762

Veh_H

FTP

B

1.53

-2.1753

0.0132

0.2029

0.0055

281.8

0.0083

0.0091

0.0054

31.32

1.580

Veh_H

FTP

B

1.53

-2.8807

0.0120

0.2561

0.0041

271.5

0.0079

0.0087

0.0043

32.50

1.962

Veh_H

FTP

Base

1.49

-1.5584

0.0173

0.3143

0.0057

300.2

0.0125

0.0137

0.0052

29.19

1.900

Veh_H

FTP

Base

1.49

-3.6243

0.1132

0.2267

0.0049

296.4

0.0070

0.0077

0.0047

29.58

1.311

Veh_H

FTP

Base

1.49

-2.0667

0.0127

0.2659

0.0045

286.7

0.0091

0.0100

0.0041

30.57

1.643

Veh_H

FTP

Base

1.49

-2.5854

0.0130

0.2670

0.0050

273.3

0.0070

0.0077

0.0060

32.06

1.446

Veh_H

FTP

Base

1.49

1.2141

0.0120

0.2660

0.0080

281.6

0.0080

0.0088

0.0050

31.12

1.346

Veh_H

FTP

Base

1.49

-2.4904

0.0135

0.2568

0.0043

301.2

0.0082

0.0090

0.0059

29.10

1.666

Veh_H

FTP

Base

1.49

0.3637

0.0122

0.2484

0.0062

278.0

0.0079

0.0087

0.0046

31.53

1.736

Veh_H

FTP

Base

1.49

-2.2141

0.0120

0.1910

0.0070

263.3

0.0080

0.0088

0.0050

33.31

2.245

Veh_H

FTP

Base

1.49

-0.1410

0.0120

0.2050

0.0160

275.8

0.0070

0.0077

0.0060

31.79

1.297

Veh_H

FTP

Base

1.49

-1.7558

0.0131

0.4092

0.0047

307.6

0.0093

0.0103

0.0042

28.48

2.316

Veh_H

FTP

C

1.50

-2.9281

0.0154

0.2838

0.0043

278.5

0.0109

0.0119

0.0047

31.45

2.379

Veh_H

FTP

C

1.50

-2.5473

0.0132

0.2299

0.0048

275.9

0.0075

0.0082

0.0060

31.75

1.513

Veh_H

FTP

C

1.50

1.0443

0.0120

0.2010

0.0070

284.5

0.0080

0.0088

0.0040

30.80

1.145

Veh_H

FTP

C

1.50

-2.4439

0.0170

0.2380

0.0060

271.6

0.0120

0.0132

0.0050

32.25

1.339

Veh_H

FTP

D

1.41

-2.8565

0.0130

0.2070

0.0040

268.5

0.0070

0.0079

0.0060

32.56

1.180

Veh_H

FTP

D

1.41

2.0585

0.0170

0.3490

0.0090

280.5

0.0110

0.0125

0.0070

31.14

1.581

Veh_H

FTP

D

1.41

-1.2940

0.0160

0.2150

0.0070

272.6

0.0110

0.0125

0.0050

32.07

1.222

Veh_H

FTP

D

1.41

1.1680

0.0160

0.1950

0.0040

270.0

0.0120

0.0136

0.0050

32.38

1.549

Veh_H

US06

A

2.72

-3.8910

0.0015

3.9894

0.0087

342.8

0.0000

0.0000

0.0026

25.29

1.539

Veh_H

US06

A

2.72

-9.4400

0.0009

0.7826

0.0062

334.4

0.0003

0.0004

0.0008

26.31

0.723

Veh_H

US06

A

2.72

-5.8940

0.0015

3.1535

0.0051

338.2

0.0000

0.0000

0.0024

25.72

1.669

Veh_H

US06

A

2.72

-4.6890

0.0019

3.1946

0.0025

343.4

0.0000

0.0000

0.0025

25.34

1.443

Veh_H

US06

A

2.72

-11.0790

0.0009

0.6820

0.0151

322.3

0.0000

0.0000

0.0011

27.30

1.022

Veh_H

US06

A

2.72

-9.8610

0.0005

0.8343

0.0162

327.0

0.0000

0.0000

0.0011

26.89

0.943

Veh_H

US06

A

2.72

-9.3320

0.0010

0.3010

0.0040

333.3

0.0000

0.0000

0.0010

26.45

1.021

Veh_H

US06

A

2.72

-5.4730

0.0030

5.5780

0.0090

335.4

0.0000

0.0000

0.0030

25.65

1.587

12 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_H

US06

A

2.72

-3.5720

0.0010

2.1840

0.0040

333.0

0.0000

0.0000

0.0010

26.24

1.216

Veh_H

US06

B

1.53

-11.5600

0.0008

0.8770

0.0041

319.7

0.0000

0.0000

0.0013

27.52

0.831

Veh_H

US06

B

1.53

-9.8130

0.0005

0.0623

0.0052

331.4

0.0000

0.0000

0.0009

26.66

1.093

Veh_H

US06

B

1.53

-6.9750

0.0009

0.0981

0.0040

333.5

0.0002

0.0002

0.0009

26.49

1.089

Veh_H

US06

B

1.53

-9.0430

0.0008

0.6267

0.0069

335.4

0.0001

0.0001

0.0010

26.27

0.805

Veh_H

US06

B

1.53

-3.3370

0.0010

1.8690

0.0040

343.8

0.0010

0.0010

0.0000

25.49

1.554

Veh_H

US06

Base

1.49

-4.8870

0.0009

1.2663

0.0052

342.9

0.0001

0.0001

0.0009

25.45

1.251

Veh_H

US06

Base

1.49

-8.6260

0.0022

2.0180

0.0024

340.6

0.0001

0.0001

0.0022

25.54

0.663

Veh_H

US06

Base

1.49

-2.7810

0.0016

3.4919

0.0069

339.6

0.0000

0.0000

0.0022

25.44

1.188

Veh_H

US06

Base

1.49

-7.0030

0.0012

0.9281

0.0085

327.3

0.0001

0.0001

0.0011

26.70

1.019

Veh_H

US06

Base

1.49

-9.9290

0.0009

0.6942

0.0092

333.3

0.0001

0.0001

0.0009

26.25

0.724

Veh_H

US06

Base

1.49

-7.9650

0.0009

0.8058

0.0083

340.7

0.0001

0.0001

0.0008

25.67

0.773

Veh_H

US06

Base

1.49

-9.3990

0.0010

1.0830

0.0040

326.0

0.0000

0.0000

0.0020

26.79

0.914

Veh_H

US06

Base

1.49

-4.7630

0.0020

4.1730

0.0030

331.3

0.0000

0.0000

0.0030

25.98

1.209

Veh_H

US06

Base

1.49

-1.9710

0.0020

3.6660

0.0040

346.5

0.0000

0.0000

0.0020

24.93

1.366

Veh_H

US06

Base

1.49

-5.6700

0.0010

4.8720

0.0040

332.1

0.0000

0.0000

0.0020

25.84

1.076

Veh_H

US06

C

1.50

-8.0960

0.0020

2.9100

0.0040

326.5

0.0000

0.0000

0.0030

26.50

7.262

Veh_H

US06

C

1.50

-8.4660

0.0020

2.0900

0.0050

332.8

0.0000

0.0000

0.0020

26.10

1.078

Veh_H

US06

C

1.50

-4.5880

0.0030

4.2890

0.0040

343.6

0.0000

0.0000

0.0030

25.04

1.682

Veh_H

US06

C

1.50

-10.3600

0.0010

1.6300

0.0030

322.3

0.0000

0.0000

0.0020

27.00

0.643

Veh_H

US06

C

1.50

-2.7020

0.0020

4.2650

0.0050

338.9

0.0000

0.0000

0.0030

25.39

1.141

Veh_H

US06

D

1.41

-10.7400

0.0008

0.4487

0.0120

323.6

0.0000

0.0000

0.0010

26.99

0.844

Veh_H

US06

D

1.41

-3.5840

0.0010

1.6510

0.0100

346.7

0.0000

0.0000

0.0020

25.06

1.334

Veh_H

US06

D

1.41

-8.7480

0.0020

0.8300

0.0060

320.8

0.0000

0.0000

0.0020

27.17

0.657

Veh_H

US06

D

1.41

-5.6260

0.0010

1.6810

0.0050

325.5

0.0000

0.0000

0.0020

26.68

0.441

Veh_l

FTP

A

2.72

-0.3238

0.0423

0.1478

0.0268

222.1

0.0383

0.0420

0.0090

39.20

4.106

Veh_l

FTP

A

2.72

-0.2971

0.0558

0.1684

0.0316

222.8

0.0465

0.0509

0.0091

39.08

4.100

Veh_l

FTP

A

2.72

-0.4281

0.0565

0.1455

0.0323

218.1

0.0472

0.0518

0.0090

39.93

4.040

Veh_l

FTP

A

2.72

-0.3193

0.0552

0.1457

0.0298

222.2

0.0457

0.0501

0.0092

39.18

4.467

Veh_l

FTP

A

2.72

-0.7699

0.0549

0.1359

0.0320

214.6

0.0442

0.0484

0.0104

40.57

3.598

Veh_l

FTP

A

2.72

-0.6044

0.0460

0.1637

0.0306

213.7

0.0362

0.0397

0.0095

40.74

3.487

VehJ

FTP

A

2.72

-0.4664

0.0537

0.1577

0.0302

209.8

0.0427

0.0468

0.0107

41.49

3.233

Veh_l

FTP

B

1.53

-0.6194

0.0520

0.1512

0.0293

216.4

0.0433

0.0474

0.0085

40.22

2.137

13 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

VehJ

FTP

B

1.53

-0.5352

0.0617

0.1687

0.0372

215.2

0.0519

0.0569

0.0096

40.45

2.142

VehJ

FTP

B

1.53

-0.7236

0.0487

0.1314

0.0273

217.4

0.0398

0.0436

0.0087

40.05

2.413

VehJ

FTP

B

1.53

-0.5473

0.0580

0.1733

0.0295

216.1

0.0482

0.0528

0.0096

40.28

1.823

VehJ

FTP

Base

1.49

-0.6092

0.0497

0.1536

0.0291

216.7

0.0400

0.0439

0.0095

39.89

1.566

VehJ

FTP

Base

1.49

-0.6131

0.0455

0.1575

0.0293

216.5

0.0355

0.0390

0.0097

39.92

2.102

VehJ

FTP

Base

1.49

-0.3521

0.0552

0.1655

0.0352

216.3

0.0462

0.0507

0.0088

39.96

1.847

VehJ

FTP

C

1.50

-0.2608

0.0513

0.1474

0.0304

216.1

0.0435

0.0476

0.0076

39.95

1.697

VehJ

FTP

C

1.50

-0.5272

0.0544

0.1683

0.0354

217.6

0.0443

0.0486

0.0099

39.68

2.023

VehJ

FTP

C

1.50

-0.8080

0.0517

0.1528

0.0358

215.6

0.0417

0.0457

0.0098

40.05

1.937

VehJ

FTP

C

1.50

-0.5645

0.0548

0.1480

0.0340

216.7

0.0444

0.0487

0.0102

39.85

1.782

VehJ

FTP

D

1.41

-0.4997

0.0471

0.1253

0.0290

214.9

0.0366

0.0415

0.0102

39.95

1.322

VehJ

FTP

D

1.41

-0.4470

0.0561

0.1434

0.0328

214.1

0.0461

0.0523

0.0098

40.09

1.530

VehJ

FTP

D

1.41

-0.3437

0.0490

0.1657

0.0336

215.8

0.0388

0.0440

0.0099

39.77

1.512

VehJ

FTP

D

1.41

-0.3336

0.0604

0.1791

0.0360

216.9

0.0501

0.0568

0.0100

39.56

2.196

VehJ

US06

A

2.72

-4.1284

0.1064

3.0459

0.0060

246.8

0.0772

0.0795

0.0285

34.63

1.971

VehJ

US06

A

2.72

-3.8958

0.1124

3.0428

0.0059

246.0

0.0806

0.0830

0.0311

34.73

1.848

VehJ

US06

A

2.72

-4.0354

0.0973

3.0322

0.0057

247.8

0.0714

0.0735

0.0252

34.50

2.254

VehJ

US06

A

2.72

-4.1313

0.1293

3.0431

0.0053

245.1

0.0940

0.0968

0.0344

34.85

3.174

VehJ

US06

A

2.72

-4.4741

0.0712

3.0316

0.0053

240.6

0.0412

0.0425

0.0292

35.52

2.057

VehJ

US06

A

2.72

-4.7854

0.0833

3.0435

0.0047

230.6

0.0527

0.0542

0.0299

37.02

0.991

VehJ

US06

A

2.72

-4.7451

0.0717

3.0331

0.0048

238.3

0.0426

0.0439

0.0283

35.85

1.263

VehJ

US06

B

1.53

-3.4919

0.0897

3.0447

0.0052

239.4

0.0607

0.0625

0.0283

35.68

1.019

VehJ

US06

B

1.53

-4.6258

0.0554

3.0410

0.0051

240.2

0.0344

0.0354

0.0205

35.58

0.904

VehJ

US06

B

1.53

-4.0180

0.0823

3.0615

0.0057

235.1

0.0550

0.0566

0.0267

36.31

0.628

VehJ

US06

B

1.53

-4.7359

0.0615

3.0502

0.0057

240.8

0.0393

0.0404

0.0216

35.48

0.907

VehJ

US06

Base

1.49

-3.9782

0.0712

3.0541

0.0055

234.2

0.0469

0.0483

0.0237

36.19

0.988

VehJ

US06

Base

1.49

-4.1763

0.0736

3.0567

0.0049

233.5

0.0475

0.0489

0.0255

36.30

0.876

VehJ

US06

Base

1.49

-3.9243

0.0753

3.0568

0.0051

242.1

0.0475

0.0489

0.0271

35.03

0.946

VehJ

US06

C

1.50

-4.0027

0.0700

3.0427

0.0053

235.4

0.0489

0.0504

0.0206

35.99

0.862

VehJ

US06

C

1.50

-3.5276

0.0832

3.0410

0.0054

238.8

0.0552

0.0569

0.0273

35.48

0.990

VehJ

US06

C

1.50

-4.0221

0.0790

3.0504

0.0054

240.7

0.0534

0.0550

0.0250

35.20

0.785

VehJ

US06

C

1.50

-3.6385

0.0737

3.0557

0.0053

232.8

0.0497

0.0512

0.0234

36.37

0.875

VehJ

US06

C

1.50

-4.2774

0.0765

3.0465

0.0050

234.5

0.0483

0.0498

0.0275

36.12

1.099

14 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

VehJ

US06

D

1.41

-4.2099

0.0288

3.0445

0.0052

230.1

0.0156

0.0160

0.0129

36.58

0.680

VehJ

US06

D

1.41

-4.1549

0.0352

3.0453

0.0046

235.5

0.0178

0.0184

0.0170

35.77

0.566

VehJ

US06

D

1.41

-4.0723

0.0398

3.0619

0.0051

231.0

0.0225

0.0232

0.0169

36.45

1.005

VehJ

US06

D

1.41

-4.0526

0.0281

3.0593

0.0055

237.7

0.0164

0.0169

0.0114

35.44

0.671

VehJ

FTP

A

2.72

4.7130

0.0222

0.4530

0.0194

487.7

0.0185

0.0203

0.0036

13.44

1.401

VehJ

FTP

A

2.72

-0.8618

0.0205

0.4456

0.0148

476.8

0.0168

0.0184

0.0039

13.14

0.901

VehJ

FTP

A

2.72

-0.7266

0.0242

0.5247

0.0165

477.7

0.0199

0.0218

0.0041

13.17

0.924

VehJ

FTP

A

2.72

0.1830

0.0250

0.5460

0.0150

479.8

0.0203

0.0223

0.0052

13.23

1.702

VehJ

FTP

A

2.72

1.5716

0.0210

0.3873

0.0169

478.8

0.0172

0.0188

0.0035

13.20

0.945

VehJ

FTP

A

2.72

0.8918

0.0252

0.5539

0.0126

484.4

0.0200

0.0219

0.0053

13.36

1.604

VehJ

FTP

A

2.72

0.4716

0.0206

0.4601

0.0149

480.1

0.0171

0.0188

0.0038

13.23



VehJ

FTP

A

2.72

3.7144

0.0235

0.6104

0.0128

487.6

0.0171

0.0188

0.0047

13.45

1.629

VehJ

FTP

A

2.72

5.5957

0.0152

0.3729

0.0177

487.8

0.0129

0.0141

0.0029

13.44

1.638

VehJ

FTP

A

2.72

3.8664

0.0219

0.5728

0.0155

489.0

0.0178

0.0195

0.0049

13.48

6.141

VehJ

FTP

B

1.53

-1.1049

0.0162

0.3242

0.0135

476.5

0.0137

0.0150

0.0026

12.87

1.479

VehJ

FTP

B

1.53

-1.9137

0.0238

0.5783

0.0102

475.8

0.0192

0.0211

0.0049

13.12



VehJ

FTP

B

1.53

0.0278

0.0240

0.5528

0.0136

476.6

0.0197

0.0216

0.0046

13.14

0.893

VehJ

FTP

B

1.53

-0.9470

0.0240

0.4697

0.0127

475.5

0.0197

0.0216

0.0043

13.11

0.689

VehJ

FTP

Base

1.49

-0.3797

0.0255

0.5554

0.0105

477.0

0.0214

0.0235

0.0038

12.96

0.813

VehJ

FTP

Base

1.49

-2.5556

0.0209

0.5041

0.0101

472.2

0.0188

0.0206

0.0046

13.08

1.277

VehJ

FTP

Base

1.49

-2.6390

0.0333

0.5424

0.0103

475.8

0.0284

0.0312

0.0051

13.18

0.881

VehJ

FTP

Base

1.49

-1.2825

0.0172

0.4823

0.0104

470.1

0.0138

0.0152

0.0038

13.02

0.575

VehJ

FTP

C

1.50

0.1105

0.0230

0.4263

0.0104

473.1

0.0188

0.0206

0.0043

13.07

0.640

VehJ

FTP

C

1.50

-1.5018

0.0228

0.4816

0.0114

469.1

0.0189

0.0207

0.0046

12.96

0.818

VehJ

FTP

C

1.50

-1.3139

0.0214

0.4330

0.0119

471.6

0.0177

0.0194

0.0042

13.03

0.425

VehJ

FTP

C

1.50

-1.9733

0.0236

0.4293

0.0126

474.9

0.0195

0.0214

0.0043

12.88

1.028

VehJ

FTP

D

1.41

-2.1218

0.0172

0.4220

0.0113

466.3

0.0143

0.0163

0.0028

13.19

0.820

VehJ

FTP

D

1.41

-0.5335

0.0189

0.3512

0.0142

465.8

0.0165

0.0188

0.0030

12.78

0.347

VehJ

FTP

D

1.41

-2.5160

0.0188

0.3998

0.0108

470.5

0.0165

0.0188

0.0029

13.31

0.485

VehJ

FTP

D

1.41

2.0850

0.0212

0.3545

0.0121

471.4

0.0174

0.0198

0.0032

13.33

0.813

VehJ

US06

A

2.72

-0.0666

0.0149

8.0578

0.0089

518.9

0.0080

0.0083

0.0079

14.63



VehJ

US06

A

2.72

-0.0581

0.0121

7.9107

0.0051

518.8

0.0063

0.0065

0.0066

14.62

1.138

VehJ

US06

A

2.72

-0.0745

0.0070

5.3027

0.0060

513.2

0.0043

0.0044

0.0032

14.35

0.708

15 of 16


-------
Vehicle

Cycle

Fuel

Fuel_PMI

IWR

THC
g/mi

CO
g/mi

NOX
g/mi

C02
g/mi

NMHC
g/mi

NMOG
g/mi

CH4
g/mi

CBFE
mi/gal

PM

mg/mi

Veh_J

US06

A

2.72

-0.0841

0.0144

9.7906

0.0051

510.3

0.0077

0.0079

0.0077

14.47

0.648

Veh_J

US06

A

2.72

-0.0734

0.0118

8.1209

0.0069

506.6

0.0062

0.0064

0.0064

14.29

0.587

Veh_J

US06

A

2.72

-0.0821

0.0137

11.9353

0.0093

512.9

0.0078

0.0081

0.0068

14.63

0.700

Veh_J

US06

B

1.53

-0.0760

0.0159

9.9582

0.0054

505.2

0.0089

0.0091

0.0081

14.06

0.648

Veh_J

US06

B

1.53

-0.0973

0.0063

7.4578

0.0071

503.2

0.0025

0.0026

0.0043

14.17

0.193

Veh_J

US06

B

1.53

-0.0976

0.0102

8.4625

0.0066

503.5

0.0056

0.0058

0.0052

14.22

0.366

Veh_J

US06

B

1.53

-0.0946

0.0119

6.3799

0.0071

501.7

0.0070

0.0072

0.0057

14.08

0.575

Veh_J

US06

Base

1.49

-0.0809

0.0198

10.0105

0.0062

506.6

0.0114

0.0118

0.0096

14.44

0.301

Veh_J

US06

Base

1.49

-0.0927

0.0160

8.5324

0.0095

503.0

0.0101

0.0104

0.0068

14.01

0.517

Veh_J

US06

Base

1.49

-0.1135

0.0144

9.0413

0.0059

500.0

0.0077

0.0079

0.0077

14.22



Veh_J

US06

Base

1.49

-0.0892

0.0117

7.8029

0.0063

503.9

0.0066

0.0068

0.0058

14.27

0.762

Veh_J

US06

C

1.50

-0.0890

0.0162

10.5013

0.0057

508.4

0.0074

0.0076

0.0101

14.48

0.957

Veh_J

US06

C

1.50

-0.1078

0.0148

7.0049

0.0057

499.7

0.0068

0.0071

0.0092

14.09

0.300

Veh_J

US06

C

1.50

-0.1061

0.0140

8.2653

0.0062

507.5

0.0068

0.0071

0.0067

14.35

0.354

Veh_J

US06

C

1.50

-0.1044

0.0166

11.1954

0.0068

500.8

0.0079

0.0081

0.0099

14.04

0.501

Veh_J

US06

D

1.41

-0.0989

0.0163

6.1858

0.0058

500.2

0.0095

0.0098

0.0077

14.40

1.365

Veh_J

US06

D

1.41

-0.0820

0.0112

3.9795

0.0066

500.5

0.0066

0.0068

0.0053

13.88

1.031

Veh_J

US06

D

1.41

-0.0999

0.0126

6.9882

0.0059

507.9

0.0069

0.0071

0.0066

14.66

0.398

Veh_J

US06

D

1.41

-0.1011

0.0096

5.3893

0.0055

506.6

0.0061

0.0063

0.0039

14.55

0.248

16 of 16


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