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
1
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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
2
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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
3
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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.
5
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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.
7
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_ 2.0
oj
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QJ _ _
0.0
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
9
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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
><
u
c
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
r 0.086
2.2-93
0.076
C.2-9S
0.087
:.:?3
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0088
0
0.X7
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2-. 2-2 9
0.021
2,223
0.0®
2.225
2.222
0.018
N
2.35
0.249
0.349
2 jii
2.248
: ;-i
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2.221
:
2.251
A
1.352
2.133
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2 14 £
2.3SE
2.2a
2.127
ID 57
2.CIS
2.134
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3.212
D.C12
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G.D12
D.C12
2.C12
2.212
0.212
2X12
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: x:
Z-.XZ
I 111
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2-.2-X
^ ^ CC'
2.X2
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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
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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
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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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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 &
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6
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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.
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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
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o
o
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o
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° ° 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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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
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°°oV°°S ° o° £0 f ° %S>fp
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°Q ° ° ° r, ®
8 ° ° ° 9>
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-------
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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