United States

Environmental Protection

Agency

Air and Radiation EPA420-S-02-012

June 2002

The Effect of Cetane Number

Increases Due to Additives on

NOx Emissions from

Heavy-Duty Highway Engines

 Printed on Recycled Paper

Draft Technical Report
EPA420-S-02-012

June 2002

The Effect of Cetane Number Increases Due to

Additives on NOx Emissions from

Heavy-Duty Highway Engines

Draft Technical Report

Assessment and Standards Division

Office of Transportation and Air Quality

U.S. Environmental Protection Agency

NOTICE

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 which

may form the basis for a final EPA decision, position, or regulatory action.
Table of Contents

I. Introduction ............................................................1

A. Background ......................................................1

B. Cetane number as an emission control strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

II. Analytical approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

A. Database preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

B. Summary of analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

III. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

A. SAS modeling results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

B. Application to the in-use fleet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

C. Some predicted NOx impacts of additized cetane . . . . . . . . . . . . . . . . . . . . . . . . 16

Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
1

I. Introduction

A. Background

The control of diesel fuel properties as a means for reducing emissions of regulated

pollutants continues to be of interest to State air quality managers. Previous test programs have

shown various levels of benefits for changes to such fuel properties as cetane number, aromatics,

density, sulfur, and distillation properties. For areas that are out of attainment for ozone or

particulate matter, State air quality managers may consider changes to diesel fuel as one element

of their overall strategy for meeting the National Ambient Air Quality Standards.

One example of a State that has implemented a diesel fuel approach as part of its overall

strategy to reach attainment is Texas. When its Low Emission Diesel (LED) program was first

proposed for Houston and Dallas in the fall of 2000, EPA voiced concern about the NOx

emission reduction benefits claimed by Texas. Because of this concern, we initiated an effort to

evaluate the emission benefits of varying diesel fuel parameters. In July of 2001, we issued a

Staff Discussion Document1 with the preliminary results of this analysis.

Our process in conducting this evaluation involved reviewing existing engine emissions

data rather than conducting new emissions tests. Where data was available, we used a regression

model approach to analyze results and to develop a quantitative set of relationships between fuel

parameters and emissions changes (in the remainder of this technical report, this work will be

referred to as the Staff Discussion Document model). As part of our process, we met with

numerous stakeholders to review our preliminary conclusions, beginning in May of 2001, and in

response to requests from stakeholders, held a public workshop on August 28, 2001 to hear

comments on our Staff Discussion Document and our analysis.

After reviewing the comments made at the workshop, we estimated the NOx emission

factors for the Texas diesel fuel program based on this analysis. Our conclusions were

summarized in a memorandum to EPA's Region VI2

. In this memorandum, we limited the use of

the draft NOx model presented in the Staff Discussion Document to the evaluation of the benefits

of the Texas diesel fuel program. As a result, there currently exists no widely-applicable, EPAapproved model for estimating the emission impacts of more general changes in diesel fuel

properties. At this time, EPA has no plans to pursue such a model.

B. Cetane number as an emission control strategy

Of the various diesel fuel properties that could be controlled in order to produce emission

benefits, cetane number holds the greatest interest, particularly with regard to NOx. Even in the

absence of a more comprehensive model correlating all diesel fuel properties with emissions,

some States are still considering implementing cetane control programs. In such cases, the

emission benefits might be based on results from various individual test programs that attempted
2

to control cetane number. Since any NOx benefits claimed in a SIP as a result of cetane control

must eventually be approved by EPA, we have determined that it is now appropriate to

investigate the NOx benefits of cetane control in a comprehensive fashion.

The cetane number of diesel fuel can be increased in two different ways: naturally, and

via the use of additives. The "natural" approach involves the modification of various physical

properties of diesel fuel and/or modifying the concentration of various diesel fuel components.

The result is that multiple properties/components may change at the same time. This

"colinearity" is best illustrated for cetane, aromatics, and specific gravity, as shown in Figure I.B13

.

Figure I.B-1

Colinearities for natural cetane number

0.81 0.82 0.83 0.84 0.85 0.86 0.87 0.88

Specific gravity

35

40

45

50

55

60

Cetane number

0.81 0.82 0.83 0.84 0.85 0.86 0.87 0.88

Specific gravity

10

15

20

25

30

35

40

45

50

Total aromatics, vol% by FIA

10 15 20 25 30 35 40 45 50

Total aromatics, vol% by FIA

35

40

45

50

55

60

Cetane number

This colinearity can also be seen in variance inflation factors. Variance inflation factors

are based on the r2 value (coefficient of determination) resulting from a least-squares regression

in which one fuel property is made a function of all other fuel properties. A value close to 1

indicates that no correlation exists. A value higher than 5 would indicate a moderately strong

correlation, while values approaching 10 indicate very strong correlations. A listing of variance

inflation factors is shown in Table I.B-1 for in-use survey data.
3

Table I.B-1

Variance inflation factors for in-use survey data

Natural cetane

Additized cetane"

Sulfur

Aromatics

T10

T50

T90

Specific gravity

7.1

1.1

1.3

10.0

4.8

11.1

4.2

16.7 " "Additized cetane" is the increase in total

cetane number brought about through the

addition of cetane improver additives.

From this table it is clear that natural cetane is highly correlated with other fuel properties. In

addition, the high variance inflation factors for aromatics and specific gravity indicate that these

three properties are highly correlated with one another (the distillation properties are primarily

correlated with each other). However, since fuels in test programs are sometimes the product of

more carefully designed blending that might decorrelate fuel properties from each another, the

values in Table I.B-1, based on a survey of in-use fuels, may be misleading. We therefore

repeated the calculation of variance inflation factors for the Staff Discussion Document model

database. The result was that the variance inflation factors were indeed lower than the values in

Table I.B-1, but not significantly.

Finally, a correlation matrix is another way to investigate colinearities between fuel

properties. Using our emissions database, we generated a correlation matrix by standardizing all

of the fuel property measurements (by subtracting the mean from every observation and dividing

by the standard deviation), multiplying the fuels matrix by its transpose, and normalizing the

results. The results for the primary fuel properties of interest are shown in Table I.B-2. The

matrix is necessarily identical on either side of the diagonal.
4

Table I.B-2

Correlation matrix for diesel emissions database

Natural

Cetane

Additized

cetane

Sulfur AromaticsT10 T50 T90 Specific

gravity

Natural

Cetane

1

Additized

cetane

-0.35 1

Sulfur -0.04 -0.17 1

Aromatics -0.57 0.20 0.30 1

T10 0.16 -0.08 0.01 0.13 1

T50 0.26 -0.07 0.11 0.30 0.69 1

T90 0.32 -0.10 0.10 0.23 0.30 0.70 1

Specific

gravity

-0.61 0.25 0.21 0.75 0.30 0.41 0.23 1

As the values in the correlation matrix approach 1 (or -1), the correlation between the two fuel

properties in question approaches a perfect linear correlation. Thus the Table I.B-2 values can be

viewed as correlation coefficients for one fuel property as a function of another fuel property.

The highest values are for T50 as a function of the adjacent distillation properties T10 and T90,

and the intercorrelation between natural cetane, aromatics and specific gravity. The correlation

matrix also highlights the fact that colinearity between diesel fuel properties is more pronounced

than for gasoline, likely due to the fact that gasoline is composed of 7-8 blending streams while

diesel fuel is composed of 2-3 streams. For instance, the average of the values in Table I.B-2

(ignoring the diagonal and using the absolute values) is 0.28. By way of comparison, the average

correlation coefficient for the fuels used in developing the Complex Model4 for the reformulated

gasoline program was 0.15. Although the selection of fuel properties of interest is somewhat

arbitrary in both cases, we can conclude that the degree of colinearity between fuel properties in

our diesel emissions database is significantly greater than that in our Complex Model database.

Given the strong colinearities between natural cetane and other fuel properties, it is not

surprising that many stakeholders questioned the draft emissions model described in Section I.A.

In particular, the NOx model contained no natural cetane term, despite the fact that many test

programs had shown a strong correlation between natural cetane and NOx emissions. On closer

examination, the absence of a natural cetane term appears to be a result of "aliasing". The NOx

model contained both an aromatics and a specific gravity term, and it is likely that these two

terms were sufficient to describe the combined effect of aromatics, specific gravity, and natural

cetane on NOx emissions. The natural cetane effect on NOx was, therefore, inherent in the
5

effects exhibited by aromatics and specific gravity. This concept is supported by the fact that our

estimate of NOx benefits for the Texas diesel fuel program was the same regardless of whether

we used the NOx model proposed in our Staff Discussion Document (the model which did not

contain a natural cetane term) or an alternative model that contained a total cetane term

representing the sum of natural and additized cetane.

The model proposed in our Staff Discussion Document could still be used to predict the

NOx impacts of changes in natural cetane so long as there existed a means for translating natural

cetane changes into the aromatics and specific gravity changes that would likely occur

collinearly. Although currently there is no commonly accepted way to do this, we were fortunate

in the case of the Texas LED program to have survey data for fuels sold in California. Since

Californian diesel fuel was deemed a reasonable representation of fuels that would be produced

under the Texas LED program, we could used them to estimate the benefits of the Texas

program. The result was that the colinearities between natural cetane and other fuel properties

were inherent in the California survey data, and we could place confidence in the resulting

predictions from the Staff Discussion Document model.

There exists an alternative way to estimate the impact of changes in cetane number on

NOx emissions, one that avoids the complication of colinearity between fuel properties. This

approach uses additized cetane instead of natural cetane. Additized cetane is largely uncorrelated

with other diesel fuel properties, as shown by the low variance inflation factor in Table I.B-1.

This result is expected since the additives used to increase cetane generally are used in

concentrations of 1 volume percent or less. These low additive concentrations mean that the

other components of diesel fuel are not diluted in any measurable way. Also, the properties of

the additives themselves are not so extreme that physical properties of diesel fuel such as

distillation properties or specific gravity are affected.

There is good reason to believe that additized cetane and natural cetane describe similar,

or at least overlapping, combustion mechanisms, since both additized and natural cetane are

measures of a fuel's propensity to auto-ignite. Any differences in NOx impacts between

additized and natural cetane may be related to the aromatics and specific gravity effects that are

collinear with natural cetane. That is, natural cetane increases accompanied by typical reductions

in aromatics and specific gravity might be expected to produce somewhat larger NOx benefits

than additized cetane alone. However, we have insufficient information at this time to quantify

any potential differences between natural and additized cetane effects on NOx.

As a result of our review of colinearities between diesel fuel properties and our current

understanding of the impacts of increased cetane number on combustion activity, we have

determined that correlating additized cetane number with NOx emissions is an appropriate means

for providing inventory impact information to States who are considering cetane control

programs. The remainder of this technical report describes the analyses we conducted to

investigate additized cetane effects on NOx emissions.
6

II. Analytical approach

A. Database preparation

The data that we used for our analysis was a subset of the database used to develop the

Staff Discussion Document models (discussed in Section I.A). That database was composed of

three portions covering engine characteristics, emission measurements, and fuel properties. The

fuel properties included values for CETANE_DIF which represented the increase in cetane

number resulting from the addition of a cetane improver additive to conventional diesel fuel. In

order to use this database for the analysis of additized cetane effects on NOx emissions, we

simply deleted (blanked out) any CETANE_DIF values in the fuel properties database for any

test fuels that either did not contain a cetane improver additive, or were not the base fuel to

which a cetane improver was added. In the course of curve-fitting using SAS, any fuels with a

missing value for CETANE_DIF were automatically dropped from the analysis. The result was a

collection of fuels whose additized cetane values were essentially uncorrelated with other fuel

properties. Although the correlation coefficients for additized cetane in Table I.B-2 were low,

the data subset used for our analysis produced correlation coefficients that were even lower, as

shown in Table II.A-1. A listing of the fuels that were retained for this analysis is given in the

Appendix.

Table II.A-1

Correlation coefficients for additized cetane

Full database

Subset of database used for

additized cetane analysis

Natural Cetane -0.35 -0.17

Additized cetane 1 1

Sulfur -0.17 -0.07

Aromatics 0.20 0.01

T10 -0.08 -0.10

T50 -0.07 -0.12

T90 -0.10 -0.10

Specific gravity 0.25 0.04

The final database used in our analysis provided a wide range of measurements for

additized cetane and natural cetane number. Figures II.A-1 through II.A-3 show the distribution

of cetane values in the database. Note that for Figure II.A-3, none of the base fuels (cetane

difference = 0) were included.
7

Figure II.A-1

Additized cetane versus natural cetane measurements

35 40 45 50 55 60

Natural cetane

0

5

10

15

Cetane difference via additives

Figure II.A-2 Figure II.A-3

Natural cetane distribution Additized cetane distribution

37 39 41 43 45 47 49 51 53 55 57 59

Natural cetane

0

10

20

30

40

Number of fuels

90% of data

39.3

50.9

0 2 4 6 8 10 12 14 16 18 20

Cetane difference

0

5

10

15

20

25

30

Number of fuels

90% of data

2.6

15.9

Although we eliminated all irrelevant fuels from the fuels dataset, doing so did not

guarantee that every engine in the database was tested on both an additized fuel and its

corresponding unadditized base fuel. Therefore, we took additional steps to ensure that every

engine used in the analysis was tested on both an unadditized fuel and an additized fuel. The

result was that all engines from the EPEFE study which received modifications to their injection
8

timings were excluded. Note that complete descriptions of the full database can be found in the

July 2001 Staff Discussion Document.

As in the development of the Staff Discussion Document model, we excluded all data

collected on the Japanese 13-mode cycle as being unrepresentative of the federal FTP. We also

included all repeat emission measurements (i.e. the same fuel tested on the same engine and

cycle multiple times) in the database without averaging those repeats or limiting their inclusion

in the database to some maximum number of observations.

B. Summary of analysis

In correlating additized cetane with NOx emissions, we generally followed the approach

described in our July 2001 Staff Discussion Document. This included using the procedure "proc

mix" in the statistical analysis package SAS to permit the simultaneous treatment of cetane

number as a continuous independent variable and engines as random effects. We chose to use

the natural logarithm of NOx emissions to mitigate the heteroscedastic nature of the NOx

measurements. We also standardized the independent variables by subtracting the mean and

dividing by the standard deviation. The means and standard deviations are shown in Table II.B1. Standardization removes the scale differences between fuel terms, and also reduces some of

the colinearity between first and second-order terms.

Table II.B-1

Means and standard deviations used for standardizing independent variables

Mean Standard deviation

Cetane difference 5.03963 4.94910

Natural cetane 45.13889 4.27954

In our earlier work, we found that technology groups B and L produced different

cetane/NOx relationships than other engine technology groups (see Table III.B.3-2 in the Staff

Discussion Document). Technology group B represents 2-stroke engines, while technology

group L represents engines equipped with exhaust gas recirculation (EGR). For our analysis of

additized cetane effects, we chose to exclude all technology group B data. Two-stroke engines

currently represent approximately 1 percent of the heavy-duty highway fleet5

, and are expected to

become an even smaller part of the fleet in the future. As a result we do not believe that

excluding the group B data from our analysis materially affected the applicability of the results to

the in-use fleet.

We also chose to exclude all group L data from our analysis. There are essentially no

EGR-equipped engines in the current fleet, but they are expected to become a significant portion

of the fleet over the next decade. The Heavy-Duty Engines Workgroup6 is our primary source for
9

data on the effects of additized cetane on an EGR-equipped engine, and that data suggests that

these engines exhibit no discernable NOx response to cetane. Therefore, the NOx impacts of

additized cetane that resulted from the analyses described below are expected to apply to the

entire fleet except EGR-equipped engines, as described more fully in Section III.B.

Engines were identified in proc_mix as categorical random variables in our modeling.

This is equivalent to specifying dummy variables for each engine in a fixed model, except that

tested engines are treated as a random sample of engines drawn from the full population of

engines in the fleet. We also recognized and accounted for two other types of random effects in

our modeling. The first is the cetane/NOx relationship that is specific to every test engine, and

the second is the effect of the unadditized base fuel on NOx emissions for each engine. By

controlling for these types of random effects, we believe that the overall estimated effect of

additized cetane on NOx can be confidently applied to the in-use fleet.

The primary independent variable included as a fixed effect in our model was cetane

difference, defined as the increase in cetane number brought about through the addition of a

cetane improver to conventional diesel fuel. We made no distinction between different types of

cetane improver additives since we were not concerned with the effectiveness of a given additive

in terms of cetane increase per unit concentration of additive. Instead we treated a given increase

in cetane number as having the same effect on NOx regardless of the specific additive used to

bring about that cetane number increase. This approach is consistent with conclusions reached in

several previous studies7,8,9. To account for potential nonlinear effects we also included a

squared cetane difference term.

Based on past studies of additized cetane effects on emissions, we had some evidence that

increases in cetane brought about through the use of additives produced diminishing NOx

impacts as the base (natural) cetane number of the diesel fuel increased. Thus, for instance, an

increase in cetane number from 45 to 50 might be expected to produced larger NOx impacts than

an increase in cetane number from 50 to 55. To account for this possibility, we introduced a term

into the model that represented the interaction of cetane difference and natural cetane number.

Figure II.A-1 shows that there is good separation between cetane difference values and natural

cetane values, i.e. no correlation exists between the two, which is an important prerequisite for

investigating interactive terms. Since the inclusion of an interactive term meant that the natural

cetane number was now represented in the model, we decided to also investigate the need for

linear and squared natural cetane number terms. The complete list of five terms investigated in

this analysis are given in Table II.B-2.
10

Table II.B-2

Independent variables investigated

in correlation between cetane number and NOx

Cetane difference

Cetane difference2

Natural cetane

Natural cetane2

Cetane difference × natural cetane

Only those terms that were statistically significant at the p = 0.05 level were retained

using a backwards stepwise approach. Once all the remaining terms were statistically significant,

we identified outliers as any whose residual exceeded four standard deviations from the predicted

effect, removed them, and regenerated the model.
11

III. Conclusions

A. SAS modeling results

The squared natural cetane number term was not statistically significant. After it was

dropped and the model regenerated, the remaining terms were all significant. Four outliers were

then identified out of 540 total observations. These outliers are listed in Table III.A-1 by the

labels used in the database.

Table III.A-1

Outliers excluded from final model

Study Engine Fuel NOx, g/bhp-hr

SAE902173 902173-1 A3 3.66

SAE902173 902173-1 A3 3.67

SAE902173 902173-1 B2 4.38

SAE902173 902173-1 D1 4.63

Once the outliers were excluded, the model was regenerated a final time. The coefficients for the

standardized variables and the associated P-values are given in Table III.A-2.

Table III.A-2

SAS proc mix output for final model

Variable Coefficient P-value

Intercept 1.5060 < 0.0001

Cetane difference -0.01677 < 0.0001

Cetane difference2 0.004139 < 0.0001

Natural cetane -0.02093 0.0057

Cetane difference × natural cetane 0.004720 < 0.0001

Using the mean and standard deviation for the standardized independent variables (Table II.B-1),

we converted the coefficients back into unstandardized form. The fixed effects portion of the

resulting model is shown below:
12

ln(NOx, g/bhp-hr) = 1.79883 (1)

- 0.015151 × (cetane difference)

+ 0.000169 × (cetane difference)2

- 0.006014 × (natural cetane)

+ 0.000223 × (cetane difference) × (natural cetane)

We can convert this equation into one that provides a percent change in NOx emissions as a

function of cetane difference and natural cetane. During this conversion, the natural cetane term

drops out since natural cetane is the same for the base fuel and the additized fuel. The constant

also drops out for the same reason. If the base fuel is assumed to contain no cetane improver

additives, the resulting equation is:

% change in NOx = {exp[ - 0.015151 × (cetane difference) (2)

+ 0.000169 × (cetane difference)2

+ 0.000223 × (cetane difference) × (natural cetane) ] - 1 } × 100%

The predicted NOx impacts are shown graphically in Figure III.A-1.
13

Figure III.A-1

Predicted effect of cetane difference on NOx for all heavy-duty highway engines

except 2-strokes and those equipped with EGR

0 5 10 15

Increase in cetane number due to additives

0%

1%

2%

3%

4%

5%

6%

Percent reduction in NOx

Natural cetane = 40

Natural cetane = 45

Natural cetane = 50

The predicted NOx impact of a given increase in cetane number brought about through

the use of additives diminishes as the natural cetane increases, consistent with expectations.

However, there are certain conditions under which a "turnover" appears in the predicted effects.

For instance, when the natural cetane is 50, the slope of the cetane difference curve changes from

positive to negative at a cetane difference of approximately 11.8 . We do not believe that these

turnovers represent real impacts of additized cetane on NOx emissions, but rather are artifacts of

the squared cetane difference term that we used to represent nonlinear effects. We believe it

would be appropriate to insert a flat-line extrapolation at the point of any turnover, so that

additional increases in cetane number brought about through additives would cause no additional

changes in NOx emissions. To do this, we derived a formula that identifies the location of all

turnovers as a function of the natural cetane number. This formula is shown below:

Turnover in cetane difference = 44.83 - 0.6598 × (natural cetane) (3)

Thus for any values of the cetane difference that are larger than the value calculated from

equation (3), the predicted NOx impact should be the value calculated from equation (2) using
14

the cetane difference value calculated using equation (3). In practice, however, we do not believe

that this flat-line extrapolation will be necessary. Cetane improver additives are rarely used to

increase the cetane number of fuels that already have natural cetane numbers above 55, and even

in these cases the additive would have to add more than 8 cetane numbers (for a total cetane

number of more than 63) before the turnover would be reached and the extrapolation would be

necessary. Far more common is for cetane improver additives to be added to fuels having a

natural cetane number in the range of 40 - 50, and then only to raise the total cetane number 5 -

10 numbers. Within these ranges, no turnovers are encountered.

B. Application to the in-use fleet

As described in Section II.B, we excluded 2-stroke and EGR-equipped engines from our

analysis. As a result, equation (2) does not predict NOx effects for these types of engines. For 2-

stroke engines we do not believe that this result presents a hindrance to the application of

equation (2) to the in-use fleet. There were no heavy-duty 2-stroke diesel engines certified for

highway use for model years 1998 and 1999, and we expect that this trend will continue in the

future. As described in Section II.B, 2-stroke diesel engines currently account for approximately

1% of the heavy-duty highway fleet, so the application of equation (2) to the entire (non-EGR)

highway fleet for future years should introduce only negligible error.

Engines equipped with EGR, however, are expected to become an increasingly important

part of the highway fleet beginning this year. EGR-equipped engines are expected to exhibit no

discernable NOx response to cetane. Thus one possible approach to estimating fleet-wide NOx

effects of cetane improver additives is to use a weighted combination of equation (2),

representing engines without EGR, and the zero effect attributable to EGR-equipped engines.

Because the relative NOx inventories between EGR and non-EGR engines change over time,

these weighting factors would be dependent on calender year.

To estimate these weighting factors, one might use NOx inventories that represent the

specific areas where the cetane improver additives are intended to be used. For the purposes of

generating example weighting factors, we used the nationwide inventory modeling done in the

context of our rulemaking setting new standards for heavy-duty engines beginning in 2007 [66

FR 5002]. Using this modeling, we determined how the NOx inventory will be distributed

among the various model years in the nationwide fleet10. We assumed that all 2003 and later

heavy-duty diesel engines will have EGR despite the fact that this may be not true for all

manufacturers. Lacking a robust means for estimating the fraction of new engine sales that will

have EGR in the future, this assumption assures that we are not overestimating NOx benefits of

cetane control via additives for future years, since EGR-equipped engines have been shown to

exhibit no discernable NOx response to changes in cetane number. From this information we

were able to estimate the fraction of the NOx inventory that derived from non-EGR-equipped

engines for any calender year. These fractions are given in Table III.B-1.
15

Table III.B-1

Potential yearly weighting factors 'k' for additized cetane model

Fraction of diesel highway NOx inventory

which comes from non-EGR-equipped engines

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

0.93

0.84

0.77

0.70

0.65

0.61

0.57

0.55

0.54

0.53

0.51

0.50

0.48

0.46

0.44

0.41

0.39

0.36

Using the values in Table III.B-1, equation (2) could be modified to represent the entire in-use

fleet of heavy-duty diesel highway engines. The result is shown below:

% change in NOx = (4)

k × 100% × {exp[ - 0.015151 × (cetane difference)

+ 0.000169 × (cetane difference)2

+ 0.000223 × (cetane difference) × (natural cetane) ] - 1 }

There were no nonroad engines in the database we used to evaluate the effects of

additized cetane on NOx emissions. However, most nonroad engines use technologies similar to

those found in highway engines, although in a given year the highway vehicle technology is

generally more advanced. Since our previous modeling showed few technology-specific effects

of cetane on NOx, and even those distinctions have been accounted for in our current analysis by

excluding technology groups B and L, any differences between highway and nonroad technology

may not be important for additized cetane effects on NOx. As a result, it might be appropriate to

apply equation (2) to heavy-duty nonroad engines. However, we caution that there exists no

robust set of data to validate the use of equation (2) for nonroad, and the concerns we raised in

Section VII.B.6 of our Staff Discussion Document regarding this type of extrapolation have not

yet been fully addressed.
16

Finally, we discussed in Section I.B how natural and additized cetane are related, and the

fact that additized cetane is more easily analyzed since it can be disassociated from changes in

other fuel properties. Based on our current understanding of diesel ignition properties, natural

and additized cetane likely represent overlapping effects on combustion and thus on NOx.

Although we do not at this time have sufficient information to quantify the differences in NOx

effects between natural and additized cetane, preliminary analyses suggest that changes in natural

cetane, if accompanied by the collinear changes in aromatics and specific gravity shown in

Figure I.B-1, would produce larger NOx benefits than equivalent changes in additized cetane. If

so, then equation (4) would provide environmentally conservative predictions of changes in

natural cetane. Equation (4) can be modified for application to changes in natural cetane to

produce the following:

% change in NOx = (5)

k × 100% × {exp[ - 0.015151 × (NATCETf - NATCETi)

+ 0.000169 × (NATCETf - NATCETi

)

2

+ 0.000223 × (NATCETf - NATCETi) × (NATCETi)]-1}

where

k = Factor from Table III.B-1 representing engines without EGR

NATCETi = Initial value of natural cetane number

NATCETf = Final value of natural cetane number

C. Some predicted NOx impacts of additized cetane

The predicted NOx impact of a given change in cetane number is a function of both the

calender year (Table III.B-1) and the natural (or initial) cetane number of the base fuel. We can

choose some representative years and base fuel cetane values to predict specific NOx impacts

using equations (2) and (4). For instance, one of the primary years in which many current nonattainment areas must show attainment with the ozone standard is 2007. Thus we have made

NOx predictions both for the next full calender year 2003 and for 2007. In this example we also

used the current national average cetane number to represent the base fuel for areas that have not

implemented a clean diesel fuel program. According to survey data collected by the Alliance of

Automobile Manufacturers, the current average cetane number is approximately 45. If we

wanted to raise the cetane number of such base fuels to 50, equations (2) and (4) would predict

the NOx impacts shown in Table III.C-1.
17

Table III.C-1

Examples of predicted NOx effects (% reduction in NOx)

Cetane number increased 5 numbers to 50

National average base fuel assumed

2003 2007

Highway engines 2.0 1.4

Nonroad engines 2.1 2.1

States always have separate NOx inventory estimates for highway and nonroad. We have

therefore made no attempt to combine the estimates for highway and nonroad in Table III.C-1

into a single estimate representing total diesel contributions to the NOx inventory.
18

Appendix

Database used in additized cetane analysis

All studies are listed by their database STUDY_ID label. See Appendix A of Staff Discussion

Document for full citations for studies that comprise the full database.

Studies that contained no additized fuels are were therefore eliminated from

the additized cetane analysis

ACEA SAE 852078 SAE 942053

CARB-LOCO SAE 881173 SAE 961973

CARB-TOXIC SAE 922214 SAE 961974

SAE 1999-01-1117 SAE 932685 SAE 971635

SAE 1999-01-3606 SAE 932731 SAE 972898

SAE 2000-01-2890 SAE 932734 VE-1_PHASE I

SAE 790490 SAE 932800

Studies/fuels included in the additized cetane analysis

FBATCH_ID STUDY_ID CETANE_NUM CETANE_DIF BASE FUEL

EPD1 EPEFE 51

EPD10 EPEFE 58

EPD11 EPEFE 57.1 7.6 EPD7

EPD2 EPEFE 50.2

EPD3 EPEFE 50

EPD4 EPEFE 50.3 0 BASE

EPD5 EPEFE 50.6

EPD6 EPEFE 50.2

EPD7 EPEFE 49.5 0 BASE

EPD8 EPEFE 54.8 4.5 EPD4

EPD9 EPEFE 59.1 8.8 EPD4

HDE-10N HDEWG II 42.3 0 BASE

HDE-11 HDEWG II 48.1 5.8 HDE-10N

HDE-12 HDEWG II 52.7 10.4 HDE-10N

HDE-14N HDEWG II 42.1 0 BASE

HDE-15 HDEWG II 47.9 5.8 HDE-14N

HDE-16 HDEWG II 52.2 10.1 HDE-14N

HDE-16N HDEWG II 53.4

HDE-18 HDEWG II 47.9

HDE-1N HDEWG II 42.8 0 BASE

HDE-2 HDEWG II 48 5.2 HDE-1N

HDE-3 HDEWG II 53.2 10.4 HDE-1N

HDE-4N HDEWG II 42.2 0 BASE

HDE-5 HDEWG II 47.7 5.3 HDE-4N

HDE-6 HDEWG II 53 10.6 HDE-4N

HDE-7N HDEWG II 42.8 0 BASE
19

HDE-8 HDEWG II 48.1 5.3 HDE-7N

HDE-8N HDEWG II 48

HDE-9 HDEWG II 52.6 9.8 HDE-7N

HDE-R HDEWG II 46.9

FUEL1 SAE1999-01-1478 39.7 0 BASE

FUEL1A SAE1999-01-1478 42.1 2.4 FUEL1

FUEL1B SAE1999-01-1478 43.2 3.5 FUEL1

FUEL1C SAE1999-01-1478 45.8 6.1 FUEL1

FUEL1D SAE1999-01-1478 47.9 8.2 FUEL1

FUEL1E SAE1999-01-1478 51.1 11.4 FUEL1

FUEL1F SAE1999-01-1478 41.6 1.9 FUEL1

FUEL1G SAE1999-01-1478 42.5 2.8 FUEL1

FUEL1H SAE1999-01-1478 45.7 6 FUEL1

FUEL1I SAE1999-01-1478 47.9 8.2 FUEL1

FUEL1J SAE1999-01-1478 51.1 11.4 FUEL1

FUEL2 SAE1999-01-1478 46.3 0 BASE

FUEL2A SAE1999-01-1478 48.9 2.6 FUEL2

FUEL2B SAE1999-01-1478 51.6 5.3 FUEL2

FUEL2C SAE1999-01-1478 54.6 8.3 FUEL2

FUEL2D SAE1999-01-1478 59.1 12.8 FUEL2

FUEL2E SAE1999-01-1478 60.5 14.2 FUEL2

FUEL2F SAE1999-01-1478 48.3 2 FUEL2

FUEL2G SAE1999-01-1478 51.1 4.8 FUEL2

FUEL2H SAE1999-01-1478 54.9 8.6 FUEL2

FUEL2I SAE1999-01-1478 58.4 12.1 FUEL2

FUEL2J SAE1999-01-1478 61.2 14.9 FUEL2

0 SAE902172 42.5

1 SAE902172 39.9

2 SAE902172 39.6 0 BASE

2A SAE902172 47.1 7.5 2

2B SAE902172 55.5 15.9 2

2S SAE902172 39.6

4 SAE902172 46.4 0 BASE

4B SAE902172 61.9 15.5 4

5 SAE902172 48.6 0 BASE

5B SAE902172 67 18.4 5

6 SAE902172 51.8

A1 SAE902173 45.3 0 BASE

A2 SAE902173 49.8 4.5 A1

A3 SAE902173 51 5.7 A1

A4 SAE902173 55.9 10.6 A1

B1 SAE902173 39.6 0 BASE

B2 SAE902173 46 6.4 B1

B3 SAE902173 48 8.4 B1

B4 SAE902173 48.2 8.6 B1

B5 SAE902173 50.3 10.7 B1

B6 SAE902173 56.7 17.1 B1
20

C1 SAE902173 47.7 0 BASE

C2 SAE902173 50.5 2.8 C1

C3 SAE902173 55.1 7.4 C1

C4 SAE902173 55.4 7.7 C1

D1 SAE902173 49.8 0 BASE

D2 SAE902173 55.1 5.3 D1

D3 SAE902173 55.3 5.5 D1

D4 SAE902173 59.7 9.9 D1

C1 SAE910735 42

C2 SAE910735 44.8 0 BASE

C2I SAE910735 52.6 7.8 C2

C2S SAE910735 43.8

CR SAE910735 50.8

DD10 SAE912425 62.7

DD11 SAE912425 53.1

DD12 SAE912425 47

DD4 SAE912425 50.7 0 BASE

DD5 SAE912425 60.7 10 DD4

DD8 SAE912425 50.2

DD9 SAE912425 50.7

A SAE922267 51.6 0 BASE

B SAE922267 55.1 3.5 A

C SAE922267 54.6

D SAE922267 42.3 0 BASE

E SAE922267 47.9 5.6 D

F SAE922267 49 6.7 D

G SAE922267 38.4 0 BASE

H SAE922267 47.6 9.2 G

I SAE922267 47.3

J SAE922267 52

K SAE922267 39.6

L SAE922267 50.4

LS SAE932767 43 0 BASE

LS-N SAE932767 52 9 LS

LS-P SAE932767 53 10 LS

A SAE942019 46 0 BASE

A-DTBP SAE942019 57 11 A

A-EHN SAE942019 56 10 A

B SAE942019 41 0 BASE

B-DTBP SAE942019 58 17 B

B-EHN SAE942019 57 16 B

C SAE942019 38 0 BASE

C-DTBP SAE942019 49 11 C

C-EHN SAE942019 49 11 C

D SAE942019 43 0 BASE

D-EHN SAE942019 53 10 D

D-EHN/DTBP SAE942019 53 10 D
21

A-1 SAE970758 56

A-10 SAE970758 53 10 A-9

A-2 SAE970758 65

A-3 SAE970758 43

A-4 SAE970758 60

A-5 SAE970758 58

A-6 SAE970758 56

A-7 SAE970758 51 0 BASE

A-8 SAE970758 58 7 A-7

A-9 SAE970758 43 0 BASE

MAN18 SAE972894 58.7

MAN2 SAE972894 50.9 0 BASE

MAN2* SAE972894 56 5.1 MAN2

MAN7 SAE972894 56.5 0 BASE

MAN7* SAE972894 60.9 4.4 MAN7

A SAE972904 44.8 0 BASE

B SAE972904 50.5 0 BASE

C SAE972904 54.7

D SAE972904 55.4 10.6 A

E SAE972904 55.6 10.8 A

F SAE972904 55.1 4.6 B

VE 10 A VE 10 44.3 0 BASE

VE 10 AA VE 10 41.1 0 BASE

VE 10 B VE 10 52 7.7 VE 10 A

VE 10 BB VE 10 47 5.9 VE 10 AA

VE 10 C VE 10 58.8 14.5 VE 10 A

VE 10 CC VE 10 50.5 9.4 VE 10 AA

VE 10 D VE 10 50.8

VE 10 DD VE 10 51.9 10.8 VE 10 AA

VE 10 E VE 10 51.5

VE 10 EE VE 10 55.2 14.1 VE 10 AA

VE 10 F VE 10 51.4

VE 10 FF VE 10 44.7 0 BASE

VE 10 G VE 10 50.5

VE 10 GG VE 10 52.7 8 VE 10 FF

VE 10 H VE 10 54.2

VE 10 HH VE 10 53.6 8.9 VE 10 FF

VE 10 I VE 10 59.4

VE 10 II VE 10 57.5 12.8 VE 10 FF

VE 10 J VE 10 46.3

VE 10 JJ VE 10 58.9 14.2 VE 10 FF

VE 10 K VE 10 54.3

VE 10 KK VE 10 51.7

VE 10 L VE 10 54.3

VE-1A VE-1_PHASE II 42.6 0 BASE

VE-1B VE-1_PHASE II 51.4 8.8 VE-1A

VE-1C VE-1_PHASE II 55.1
22

VE-1D VE-1_PHASE II 39.3 0 BASE

VE-1E VE-1_PHASE II 40.4 1.1 VE-1D

VE-1F VE-1_PHASE II 50.7 11.4 VE-1D

VE-1G VE-1_PHASE II 49 0 BASE

VE-1H VE-1_PHASE II 53.4 4.4 VE-1G

VE-1K VE-1_PHASE II 44.1 0 BASE

VE-1L VE-1_PHASE II 53.9 9.8 VE-1K

VE-1M VE-1_PHASE II 48.6

VE-1N VE-1_PHASE II 38.5

VE-1O VE-1_PHASE II 49.2
23

1. "Strategies and Issues in Correlating Diesel Fuel Properties with Emissions," Staff Discussion

Document, EPA report number EPA420-P-01-001, July 2001.

2. EPA Memorandum, "Texas Low Emission Diesel (LED) Fuel Benefits," from Robert Larson,

Transportation and Regional Programs Division, OAR, to Karl Edlund, Region VI. September

27, 2001.

3. Alliance of Automobile Manufacturers International Diesel Fuel Survey, 1999. Summer and

winter #2 regular and premium diesel fuel blends for the United States only.

4. Defined at 40 CFR 80.45, and presented in the Federal Register at 59 FR 7725 (Feb. 16, 1994)

5. Personal communication with John Duerr of Detroit Diesel Corporation, June 5, 2001. Total

sales of heavy-duty two-stroke highway engines between 1981 and 1997 was approximately

178,000. DDC sales of 2-stroke engines ended in 1997. For the 2002 fleet, approximately

59,000 are still in use, representing approximately 1% of the 2002 fleet.

6. Matheaus, Andrew C., T.W. Ryan III, R. Mason, G. Neely, R. Sobotowski, "Gaseous

Emissions from a Caterpillar 3176 (with EGR) Using a Matrix of Diesel Fuel (Phase 2)," Final

Report under EPA contract 68-C-98-169, September 1999.

7. Nandi, M., D.C. Jacobs, F.J. Liotta, H.S. Kesling, "The performance of a peroxide-based

cetane improvement additive in different diesel fuels," SAE paper no. 942019

8. Starr, M.E., "Influence on transient emissions at various injection timings, using cetane

improvers, bio-diesel, and low aromatic fuels," SAE paper no. 972904

9. Schwab, S.D., G.H. Guinther, T.J. Henly, K.T. Miller, "The effects of 2-ethylhexyl nitrate and

di-tertiary-butyl peroxide on the exhaust emissions from a heavy-duty diesel engine," SAE paper

no. 1999-01-1478

10. Based on inventory descriptions given in Chapter II, Section B, "Regulatory Impact

Analysis: Heavy-Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur Control

Requirements," December 2000, EPA420-R-00-026

References