United States

Environmental Protection

Agency

Air and Radiation EPA420-R-03-002

February 2003

The Effect of Cetane Number

Increase Due to Additives on

NOx Emissions from

Heavy-Duty Highway Engines

 Printed on Recycled Paper

Final Technical Report
EPA420-R-03-002

February 2003

The Effect of Cetane Number Increase Due to

Additives on NOx Emissions from

Heavy-Duty Highway Engines

Final 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.
i

Abstract

This report presents a technical analysis of the NOx emissions impacts of increases in

cetane number brought about through the use of diesel fuel additives. The purpose of this

technical report is to provide information to parties who may be evaluating the value,

effectiveness, and appropriateness of the use of cetane improver additives. It was originally

provided to the public in draft form so that interested parties could comment on the methodology,

assumptions, and conclusions. Where deemed appropriate, modifications were made to the

report on the basis of those comments. This technical report is now being released in final form.

The analysis described in this report uses statistical regression analysis to correlate diesel

cetane number increases brought about through additives with NOx emissions from heavy-duty

highway engines. It relies upon pre-existing data from publicly available sources. The result is

that the effect of cetane improver additives on NOx emissions can be predicted for the in-use

fleet using a correlation which is a function of the natural cetane number of the unadditized base

fuel and the increase in cetane number brought about through additives. These NOx emission

effects are also a function of the calendar year in order to account for lower cetane sensitivity of

advanced technology engines. For instance, if cetane improvers are added to a national average

base fuel so that the total cetane number is increased by 5 numbers, the percent reduction in NOx

for calendar year 2003 is predicted to be 2.0 for highway engines. The correlations predict lower

NOx benefits for future calendar years. Nonroad engines may exhibit slightly higher NOx

benefits due to the slower introduction of cetane-insensitive technologies into the nonroad fleet.
Table of Contents

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i

I. Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

A. Nature and purpose of this technical report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

B. Public participation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

II. Introduction ............................................................3

A. Background on cetane analysis .......................................3

B. Cetane number as an emission control strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

III. Analytical approach ......................................................9

A. Database preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

1. Representativeness of fuels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2. Representativeness of engines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

B. Summary of analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

IV. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

A. SAS modeling results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

B. Confirmation of explanatory power . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

C. Application to the in-use fleet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

D. Some predicted NOx impacts of additized cetane . . . . . . . . . . . . . . . . . . . . . . . . 31

Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
1

I. Context

A. Nature and purpose of this technical report

This report presents a technical analysis of the NOx emissions impacts of increases in

cetane number brought about through the use of certain diesel fuel additives. It analyzes preexisting data from various emissions test programs to investigate these effects. The conclusions

drawn in this technical report represent the current understanding of this specific technical issue,

and are subject to re-evaluation at any time.

The purpose of this technical report is to provide information to interested parties who

may be evaluating the value, effectiveness, and appropriateness of the use of cetane improver

additives. This report informs any interested party as to the potential air emission impacts of

increases in cetane number brought about through use of these additives. It was originally

provided to the public in draft form so that interested parties would have an opportunity to

review the methodology, assumptions, and conclusions. The Agency also requested independent

peer reviews on the draft technical report from experts outside the Agency. 

This technical report is not a rulemaking, and does not establish any legal rights or

obligations for any party. It is not intended to act as a model rule for any State or other party. 

This report is by its nature limited to the technical analysis included, and is not designed to

address the wide variety of additional factors that could be considered by a State when initiating

a fuel control rulemaking. For example, this report does not consider isues such as air quality

need, cost, cost effectiveness, technical feasibility, fuel distribution and supply impacts, regional

fleet composition, and other potentially relevant factors.

State or local controls on motor vehicle fuels are limited under the Clean Air Act (CAA) -

certain state fuel controls are prohibited under the Clean Air Act, for example where the state

control applies to a fuel characteristic or component that EPA has regulated (see CAA Section

211(c)(4)). This prohibition is waived if EPA approves the State fuel control into the State

Implementation Plan (SIP). EPA has issued guidance describing the criteria for SIP approval of

an otherwise preempted fuel control. See “Guidance on the Use of Opt-in to RFG and Low RVP

Requirements in Ozone SIPs,” (August, 1997) at: http://www.epa.gov/otaq/volatility.htm.

The SIP approval process, a notice and comment rulemaking, would also consider a

variety of technical and other issues in determining whether to approve the State fuel control and

what emissions credits to allow. An EPA technical report like this one can be of value in such a

rulemaking, but the SIP rulemaking would need to consider a variety of factors specific to the

area, such as fleet make-up, refueling patterns, program enforcement and any other relevant

factors. Additional evidence on emissions effects that might be available could also be

considered. The determination of emissions credits would be made when the SIP rulemaking is

concluded, after considering all relevant information. While a technical report such as this may
2

be a factor in such a rulemaking, the technical report is not intended to be a determination of SIP

credits for a State fuel program.

B. Public participation

This technical report was made available to the general public in draft form on June 17,

2002. A comment period was established during which reviewers could submit written

comments on the analyses contained in the draft technical report. This comment period ended on

July 15, 2002. We received comments from the following companies/organizations:

• Alliance of Automobile Manufacturers

• American Petroleum Institute

• American Trucking Association

• California Truckers Association

• Cummins, Inc.

• Defense Energy Support Center

• Ethyl Corporation

• Flint Hills Resources, LP

• Kern Oil & Refining Company

• National Petrochemical & Refiners Association

We also requested and received comments from EPA's Office of Research and Development. 

We reviewed the comments received from stakeholders and updated this technical report

accordingly. We also submitted a draft of this technical report to two outside experts to obtain

independent peer review. Following the guidelines in EPA's Science Policy Council Handbook

on Peer Review, we generated responses to all the recommendations provided by the peer

reviewers and modified this technical report and the analyses contain herein where it was deemed

appropriate.

Parties interested in the draft technical report, background materials, and support

documents associated with this final technical report can find them at the following Web site:

http://www.epa.gov/otaq/models/analysis.htm

This Web site also contains copies of all comments received from our stakeholders, the reports

generated by the independent peer reviewers, and our responses to the peer reviewers'

recommendations.
3

II. Introduction

A. Background on cetane analysis

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

pollutants continues to be of interest to parties interested in or charged with reaching various air

quality goals. 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 determined that the NOx emission

reduction benefits claimed by Texas were based on a small amount of outdated data. As a result

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 comprehensive 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
4

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

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 to preclude the use of

less robust estimates that may misrepresent benefits.

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, via changes to 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 II.B-1. The data in

these graphs is drawn from a survey of in-use diesel fuels3

.

Figure II.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

These graphs provide strong evidence that changes in one fuel property will generally be

accompanied by concurrent changes in other fuel properties, confounding attempts to correlate

any one fuel property with emissions.

This colinearity can also be seen in variance inflation factors. Variance inflation factors
5

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. The formula for

variance inflation factors (VIF) is:

VIF = 1 / (1 - r2)

A value close to 1 indicates that no correlation exists. A value higher than 5 indicates a

moderately strong correlation, while values approaching 10 indicate very strong correlations. A

listing of variance inflation factors is shown in Table II.B-1 for the same in-use survey data

shown in Figure II.B-1.

Table II.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 many other fuel properties. 

In addition, the high VIFs 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 avoid some of these correlations between fuel properties, the values

in Table II.B-1, based on a survey of in-use fuels, may be misleading. We therefore repeated the

calculation of VIFs for the Staff Discussion Document model database. The result was that the

VIFs were indeed lower than the values in Table II.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 II.B-2. The

matrix is necessarily identical on either side of the diagonal.
6

Table II.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



 "Additized cetane" is the increase in total cetane number brought about through the addition of cetane

improver additives. 

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 II.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 II.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 II.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
7

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, included in the

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 use 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 as the independent variable instead of natural cetane. Additized

cetane is here defined as increases in the total cetane number brought about through the use of

small quantities (~1 vol% or less) of compounds designed to specifically and solely bring about

this result. Examples of such cetane improver additives include 2-ethylhexylnitrate and ditertiary butyl peroxide. Other bulk blending components that could increase the natural cetane

number of conventional diesel fuel but which would generally be added at significantly larger

concentrations, such as biodiesel or Fischer-Tropsch diesel, would not be considered to be cetane

improver additives nor as sources of "additized cetane" for the purposes of this analysis, since

they always affect other fuel properties in addition to cetane number.

Additized cetane is largely uncorrelated with other diesel fuel properties, as shown by the

low variance inflation factor in Table II.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 non-cetane properties of the additives themselves are not so extreme

that physical properties of diesel fuel such as distillation properties or specific gravity are

affected. Table II.B-2 indicates that the correlation coefficient between natural and additized

cetane is -0.35, a value that may appear to be non-negligible. However, this degree of colinearity

is due to human intervention and the need to enhance fuels with poor natural cetane by using

additives to meet minimum cetane requirements. It does not reflect properties inherent in the

fuel makeup as is the case for other fuel property pairs. As described in more detail in Section

III.A below, the colinearity between natural and additized cetane is reduced substantially when
8

the database is limited to those observations for which both an additized fuel and its associated

unadditized base fuel were tested.

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

or at least similar, 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 inherent 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, excluding the inherent effects

of aromatics and specific gravity.

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 with NOx emissions is an appropriate means for

providing inventory impact information to anyone considering the use of higher cetane diesel

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

additized cetane effects on NOx emissions.
9

III. 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 II.A). That database was composed of

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

database included values for a fuel property titled "CETANE_DIF" which represented the

increase in cetane number resulting from the addition of a cetane improver additive to

conventional diesel fuel. CETANE_DIF is thus the same as "additized cetane" referred to in

Section II. 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. Base fuels with CETANE_DIF values of zero

were left intact. 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 II.B-2 were low, the data

subset used for our analysis produced correlation coefficients that were even lower, as shown in

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

Table III.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. Figure III.A-1 shows the distribution of cetane

values in the database and the lack of correlation between natural and additized cetane. 
10

Figure III.A-1

Additized cetane versus natural cetane measurements

35 40 45 50 55 60

Natural cetane

0

5

10

15

Additized cetane

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

timings were excluded. No other engines were excluded for this reason. 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, since the

overall loads in this steady-state cycle are too low in comparison to the 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.

1. Representativeness of fuels

The goal of our analysis was to determine the impact on NOx emissions of increases in

cetane number brought about through additives. Generally the amounts of the additive required

is small, one percent or less, so that the impacts on fuel properties other than cetane number is

negligible. Since only one fuel property changes when cetane improver additives are used, we
11

have assumed that the other fuel properties play no role in the effect that increased cetane number

has on emissions. The one exception to this assumption is the base (natural) cetane number,

which was taken into account explicitly in our analysis as described in Section III.B.

However, to ensure that fuel properties other than cetane would not bias the emission

effects we estimated, we reviewed the composition and properties of the base fuels in the

database to determine the degree to which they could be said to represent in-use fuels. In this

comparison we made use of survey data collected by the Alliance of Automobile Manufacturers

in 2000. We created distributions for each fuel property and placed the results from the base

fuels in our database side-by-side with distributions created from the in-use survey data. The

results are shown in Figures III.A.1-1 through III.A.1-6.

Figure III.A.1-1

Comparison of base fuels from database to in-use fuels for sulfur content

0

25

50

75

100

125

150

175

200

225

250

275

300

325

350

375

400

425

450

475

500

525

550

575

600

Sulfur, ppm

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

Percent of observations

Database

AAM survey

90% of database

90% of in-use surveys
12

Figure III.A.1-2

Comparison of base fuels from database to in-use fuels for natural cetane

36 38 40 42 44 46 48 50 52 54 56 58 60

Natural cetane

0.0%

10.0%

20.0%

30.0%

40.0%

Percent of observations

Database

AAM survey

90% of database

90% of in-use surveys

Figure III.A.1-3

Comparison of base fuels from database to in-use fuels for aromatics content

12

14

16

18

20

22

24

26

28

30

32

34

36

38

40

42

44

46

48

50

52

Aromatics, vol%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

Percent of observations

Database

AAM survey

90% of database

90% of in-use surveys
13

Figure III.A.1-4

Comparison of base fuels from database to in-use fuels for specific gravity

0.8

0.805

0.81

0.815

0.82

0.825

0.83

0.835

0.84

0.845

0.85

0.855

0.86

0.865

0.87

0.875

0.88

0.885

Specific gravity

0.0%

10.0%

20.0%

30.0%

40.0%

Percent of observations

Database

AAM survey

90% of database

90% of in-use surveys

Figure III.A.1-5

Comparison of base fuels from database to in-use fuels for T50

410

420

430

440

450

460

470

480

490

500

510

520

530

540

550

560

570

580

590

T50, oF

0.0%

10.0%

20.0%

30.0%

40.0%

Percent of observations

Database

AAM survey

90% of database

90% of in-use surveys
14

Figure III.A.1-6

Comparison of base fuels from database to in-use fuels for T90

550

555

560

565

570

575

580

585

590

595

600

605

610

615

620

625

630

635

640

645

650

T90, oF

0.0%

5.0%

10.0%

15.0%

20.0%

Percent of observations

Database

AAM survey

90% of database

90% of in-use surveys

With the possible exception of aromatics, the range of property values for base fuels in the

database encompases the range of values for in-use fuels. This result ensures that NOx emission

effects that we estimate for additized cetane will not be unduly influenced by other fuel

properties, and thus can be used to represent the NOx emission effects that would be expected in

the field. For aromatics, the database range substantially overlaps the in-use survey range, and

extends to lower aromatics levels which may be more representative of clean diesel fuel such as

that required in California. Thus we believe that our database is fully representative of in-use

fuels.

2. Representativeness of engines

The degree to which we can apply the results of our analysis to the in-use fleet of heavyduty engines also depends on the degree to which engines in our database are representative of

in-use engines. To evaluate this issue, we focused on the distribution of model years among

engines in our database. Since we excluded all 2-stroke and EGR-equipped engines as described

in Section III.B below, all engines used in our analysis were built in the 1990's. Figure III.A.2-1

shows the distribution of model years for these engines.
15

Figure III.A.2-1

Distribution of engine model years in the database

1984198519861987198819891990

1991

199219931994199519961997199819992000

2001

20022003

Model year

0%

5%

10%

15%

20%

25%

30%

35%

Percent of engines

Database

2003 fleet

5

4

7

5

1

(numbers above bars represent the actual number of engines in the database)

The distribution of model years is more broad for the in-use 2003 fleet than for the

database. However, the current in-use fleet is comprised primarily of engines built in the 1990's,

consistent with the database. Also, the average model year for the database is 1994, compared to

an average of 1996 for the in-use 2003 fleet. We do not consider this difference to be significant

in the context of estimating the impact of cetane on NOx emissions. Finally, engines built after

1999 will not constitute a majority of the highway engine NOx inventory for several more years. 

Thus we have determined that the distribution of model years in our database is sufficient to

represent the current fleet for the purposes of our analysis.

As time goes on and the fleet turns over, however, it is possible that the emission effects

estimated in our analysis will become less representative of effects exhibited by the in-use fleet. 

One step we have taken to account for this possibility is to assume that all engines built after

2002 will be equipped with EGR and will, as a result, exhibit no benefits from higher cetane (see

Section IV.C for details). This is a conservative assumption, since there are indications that

some manufacturers will not use EGR in their 2002+ engines. For those manufacturers that do

use EGR, early indications are that EGR will continue to be used on engines built to meet the

2007 standards.

We also investigated the degree to which engines built in the later 1990's were less

responsive to higher cetane than engines built in the early 1990's. There has been some limited
16

information suggesting that the more frequent use of injection rate-shaping and diffusion burning

could mute the impact that cetane has on NOx emissions by reducing the amount of pre-mix

burning and thus raising the adiabatic flame temperature. To do this analysis, we calculated

engine-specific NOx effects for every unique pair of base fuel and its additized counterpart. For

each engine in the database, the average % change in NOx was calculated from all repeat

emission measurements on a given base fuel and its associated additized counterpart. The

average % change in NOx was then divided by the change in cetane brought about through

additives to produce an estimate of the % reduction in NOx for a unit increase in cetane number. 

We then plotted these effects by model year. To determine if engines were becoming less

responsive to higher cetane over the course of the last decade, we conducted a least-squares

regression on these values, with model year as the independent variable. We also conducted a

least-squares regression that included dummy variables for the engines. The results are shown in

Figure III.A.2-2.

Figure III.A.2-2

Effects of increased cetane on NOx by model year

1990 1992 1994 1996 1998 2000

Model year

-1.00%

-0.50%

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

% reduction in NOx / change in cetane

Average

The graph shows that the least-squares regressions result in lines that are very similar to the flat

average. Although the slope was negative for both regression lines, suggesting that more recent

engines may indeed exhibit less NOx sensitivity to cetane than older engines, in both cases the

curve was not statistically significant at the p = 0.10 level. The regression coefficients and pvalues are shown in Table III.A.2-1
17

Table III.A.2-1

Correlations between model year and % reduction in NOx/change in cetane

Coefficient p-value

Overall regression -0.000209 0.11

Regression including dummy

variables for engines -0.000062 0.35

Based on this investigation, it is reasonable to assume that the effects of cetane on NOx are the

same for all engines built in the 1990's. In addition, since we do not have conclusive data to the

contrary, it appears reasonable to assume that these effects are also representative of model years

1999 - 2002.

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 included all

repeat emission measurements in the database without averaging those repeats or limiting their

inclusion in the database to some maximum number of observations. The SAS curve-fitting

procedure "proc mix" treats these repeat observations in a manner that precludes them from

overweighting the results.

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 III.B-1. Standardization removes the scale differences between fuel terms, and also

reduces some of the colinearity between first and second-order terms. 

Table III.B-1

Means and standard deviations used for standardizing independent variables

Mean Standard deviation

Additized cetane 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
18

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

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. The July 2001 Staff Discussion

Document did conclude that a group L model adjustment term was statistically significant, but its

magnitude was very similar to the overall term and of opposite sign. The result was that the

predicted effect of cetane on NOx for group L engines was nearly zero (the correlation predicted

a very small increase in NOx for EGR-equipped engines). However, the adjustment term was

significant only because EGR-equipped engines could not be assigned the same NOx effect as

non-EGR engines. When we attempted to generate an independent model for EGR-equipped

engines, the effect on NOx was not significant, consistent with the findings of the Heavy-Duty

Engines Workgroup. 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 IV.C.

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 additized

cetane, 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 additized cetane 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
19

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 produce 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 additized cetane and natural cetane number. 

Figure III.A-1 shows that there is good separation between additized cetane 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 III.B-2.

Table III.B-2

Independent variables investigated 

in correlation between cetane number and NOx

Additized cetane

Additized cetane2

Natural cetane

Natural cetane2

Additized cetane × 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 data points whose residual exceeded four standard deviations from

the predicted effect, removed them, and regenerated the model.
20

IV. Conclusions

A. SAS modeling results

The initial modeling run indicated that 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 IV.A-1 by the labels used in the database.

Table IV.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 IV.A-2.

Table IV.A-2

SAS proc mix output for final model

Variable Coefficient P-value

Intercept 1.5060 < 0.0001

Additized cetane -0.01677 < 0.0001

Additized cetane 2 0.004139 < 0.0001

Natural cetane -0.02093 0.0057

Additized cetane × natural cetane 0.004720 < 0.0001

Using the mean and standard deviation for the standardized independent variables (Table III.B1), we converted the coefficients back into unstandardized form. The fixed effects portion of the

resulting model is shown below:
21

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

- 0.015151 × (additized cetane)

+ 0.000169 × (additized cetane)2

- 0.006014 × (natural cetane)

+ 0.000223 × (additized cetane) × (natural cetane)

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

function of additized cetane 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 × (additized cetane) (2)

+ 0.000169 × (additized cetane)2

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

The predicted NOx impacts are shown graphically in Figure IV.A-1.
22

Figure IV.A-1

Predicted effect of additized cetane 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. If

the average natural cetane number in a particular area happens to be close to 40, the use of cetane

improver additives will have a substantially larger benefit than would be produced in areas with

an average natural cetane number close to 50. Thus regional differences in base fuel properties

can and should be taken into account when using equation (2). There is also a possibility that

natural cetane numbers nationwide will increase with the introduction of ultra-low sulfur

highway diesel fuel in 2006, since the hydrogenation typically used to remove sulfur tends also to

increase natural cetane. Although we do not have the means at present to quantify this effect,

early indications are that any increase in natural cetane number will be quite small.

We note that there are certain conditions under which a "turnover" appears in the

predicted effects in Figure IV.A-1. For instance, when the natural cetane is 50, the slope of the

additized cetane curve changes from positive to negative at a value 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 additized cetane term that we used to represent nonlinear
23

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 additized cetane = 44.83 - 0.6598 × (natural cetane) (3)

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

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

additized cetane 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. Confirmation of explanatory power

Although we did not have an independent set of emissions data with which to validate the

model due to the fact that we used all the available data to construct the model, we were able to

confirm the explanatory power of the correlations described in Section IV.A using two

alternative approaches. First, we compared equation (2) with regression equations generated by

other researchers. A review of the literature produced seven different regression models from

four different studies, each of which included either an additized cetane term or a total cetane

(natural + additized) term. For natural cetane and other fuel properties present as independent

variables in some of the models, we used the nationwide average values given in Table III.D-1 of

the July 2001 Staff Discussion Document. Figure IV.B-1 presents this comparison.
24

Figure IV.B-1

Comparison of EPA correlation to those from other researchers

0 5 10 15

Increase in cetane number due to additives

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

Percent reduction in NOx

SAE 950251

SAE 950250, 5g

SAE 950250, 4g

VE-10, 5g DDC 60

VE-10, 4g DDC 60

SAE 922267, 1994

SAE 922267, 1991

EPA analysis

Our correlation falls in the middle of the range of effects estimated via regression analysis from

other researchers. In addition, our correlation predicts that cetane improver additives pro0duce

less NOx benefit as the cetane number increases. Most other models are strictly linear,

suggesting that our correlation provides a more conservative prediction at higher values of

additized cetane.

We also compared predictions from our model to the individual observations in our

database. To do this, we first had to convert the emission measurements in the database into %

change values. Since repeat emission measurements sometimes made it difficult to match

specific base fuel measurements with specific additized fuel measurements, we first averaged any

repeat emission measurements of a given fuel on a given engine. We then calculated a % change

in NOx value for every unique pair of base fuel and its additized counterpart. Equation (2) was

then used to predict a % change value for each fuel pair. Finally, the predicted and observed

values were plotted against one another. The results are shown in Figure IV.B-2.
1

 We assumed a NOx measurement standard deviation of 0.037 g/bhp-hr based on repeat measurements

presented in the July 2001 Staff Discussion Document, and a mean NOx emission level of 3.7 g/bhp-hr, representing a

1997 engine. Under these conditions, a large sample of emission measurements on additized and unadditized fuels would

result in approximately 91% of paired observations exhibiting a reduction in NOx and 9% of observations exhibiting an

increase in NOx.

25

Figure IV.B-2

Comparison of predicted and observed impacts of additized cetane

-5.00% 0.00% 5.00% 10.00% 15.00%

Predicted % reduction in NOx

-5.00%

0.00%

5.00%

10.00%

15.00%

Observed % reduction in NOx

If the model perfectly predicted all the data, all the observations would fall exactly on the

diagonal. The fact that the observations are distributed around the diagonal can be explained by

measurement variability. For instance, 9% of the observations in the database indicated that

NOx emissions actually increased when a cetane improver additive was added to a base fuel (the

observations below the horizontal line in Figure IV.B-2). But this same result could be predicted

from a knowledge of NOx measurement variability and an expected cetane improver NOx

benefit of 2%1. These NOx increases do not change the fact that the fleet-wide effect of cetane

improver additives is to lower NOx in a statistically significant way. 

In addition, a least-squares regression on the data in Figure IV.B-2 does produce a slope

that is close to 1.0 (actual value was 0.86, with an associated p-value of <0.0001). This

regression line, along with the 90% confidence interval around the regression line, is shown in

Figure IV.B-3. Note that the 1:1 diagonal falls entirely within the confidence interval, providing

another indication that equation (2) provides a good explanation of the observed values.
26

Figure IV.B-3

Least-squares regression of predicted versus observed impacts 

of additized cetane, including 90% confidence limits

-5.00% 0.00% 5.00% 10.00% 15.00%

Predicted % reduction in NOx

-5.00%

0.00%

5.00%

10.00%

15.00%

Observed % reduction in NOx

1:1 ideal relationship

Regression

For multi-parameter regression equations of the sort generated by our maximum

likelihood curve-fitting approach, there is no straightforward mechanism for combining termspecific standard error estimates into confidence limits around equation (2). The SAS procedure

"proc mix" employed in our analysis does have the capability of generating confidence intervals

around every observation in the database, but this falls short of confidence limits around the

regression equation itself. In order to generate a quantitative measure of uncertainty for equation

(2), we used the predicted and observed % reduction values to calculate the standard error

associated with the residuals, where the residuals were simply the difference between predicted

and observed values for every observation. These values were calculated for several different

ranges of values for natural cetane and additized cetane. Although this approach provides only

an estimate of uncertainty in the regression equation at several discrete points on the curve, it is

useful to illustrate the potential uncertainty in the predicted effects. The results are shown in

Table IV.B-1.
27

Table IV.B-1

Standard errors and number of observations for % change residuals

Natural cetane range

Additized cetane range

2.5 to 7.5 7.5 to 12.5 12.5 to 17.5

Median = 5 Median = 10 Median = 15

37.5 to 42.5 Median = 40 0.357 (35) 0.271 (43) 0.468 (14)

42.5 to 47.5 Median = 45 0.553 (21) 0.310 (72) 0.267 (24)

47.5 to 52.5 Median = 50 0.269 (44) 0.285 (54) 1.722 (2)

 Values in parentheses are the number of observations

The standard errors for the residuals were then converted into confidence intervals by multiplying

the standard errors by the appropriate value of t (from Student's t-distribution):

Confidence interval = mean predicted effect ± t × standard error

Table IV.B-2 presents the t × standard error values assuming a 90% confidence band, while

Figure IV.B-4 shows how the confidence intervals would appear for the case of a base fuel with

natural cetane of 45.

Table IV.B-2

90% t × standard error values about predicted % reduction values

Natural cetane range

Additized cetane range

2.5 to 7.5 7.5 to 12.5 12.5 to 17.5

Median = 5 Median = 10 Median = 15

37.5 to 42.5 Median = 40 0.60 0.46 0.83

42.5 to 47.5 Median = 45 0.95 0.52 0.46

47.5 to 52.5 Median = 50 0.45 0.48 10.87
28

Figure IV.B-4

Predicted effect of additized cetane on NOx with 90% confidence intervals 

for base fuel with natural cetane of 45

0 5 10 15

Increase in cetane number due to additives

0%

1%

2%

3%

4%

5%

6%

Percent reduction in NOx

C. Application to the in-use fleet

As described in Section III.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 III.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, based on testing done by the Heavy-Duty Engines

Workgroup under the auspices of the Mobile Source Technical Review Subcommittee. This test

program did not include an evaluation of the impacts of injection rate-shaping or other

combustion management techniques that some contend are the primary, or possibly additional,

reasons for the cetane-insensitivity of future engines. However, for our purposes it is not

necessary to identify the specific reasons for cetane-insensitivity of future engines if we make the

simplifying assumption that all future engines will employ cetane-insensitive technologies. 
29

Thus our approach to estimating fleet-wide NOx effects of cetane improver additives was to use

a weighted combination of equation (2), representing engines without cetane insensitive

technologies, and the zero effect attributable to cetane-insensitive engines. Because the relative

NOx inventories between these two categories of engines change over time, these weighting

factors would be dependent on calendar 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 employ EGR or some other cetane-insensitive technology 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 employ cetane-insensitive technologies in the future, this

assumption assures that we are not overestimating NOx benefits of cetane control via additives

for future years. From this information we were able to estimate the fraction of the NOx

inventory that derived from cetane-sensitive engines for any calendar year. These fractions are

given in Table IV.C-1.
30

Table IV.C-1

Potential yearly weighting factors 'k' for additized cetane model

Fraction of diesel highway NOx inventory

which comes from cetane-sensitive 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 IV.C-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 × (additized cetane)

+ 0.000169 × (additized cetane)2

+ 0.000223 × (additized cetane) × (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 (excluding locomotive

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 many of 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,

excluding locomotives. This approach is consistent with the conclusion drawn by the American

Petroleum Institute in a letter to the Ozone Transport Commission11, in which API concluded that

nonroad engines would exhibit NOx responses to cetane that were "similar" to highway engine
31

effects. 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. Thus the

decision to apply equation (2) to nonroad in any particular context may be dependent on the

availability of supporting data or other relevant factors.

Finally, we discussed in Section II.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 II.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 NOx

due to 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 IV.C-1 representing engines without EGR

NATCETi = Initial value of natural cetane number

NATCETf = Final value of natural cetane number

Equation (5) would be relevant for changes in natural cetane brought about through conventional

means, namely lowering aromatics content or other refinery-based changes to the composition of

the fuel. It would not be appropriate to use equation (5) to represent changes in natural cetane

brought about through the additional of high cetane bulk blending components, such as biodiesel

or Fischer-Tropsch fuels, to conventional diesel fuel.

The only alternatives to equation (5) that we considered for correlating natural cetane

with NOx emissions were those in the Staff Discussion Document. Since that analysis showed

that the effects of natural cetane on NOx could actually be better represented by aromatics and

density alone, equation (5) permits one to directly predict the NOx impact of changes in natural

cetane instead of inferring the impacts through changes in aromatics and density.

D. Some predicted NOx impacts of additized cetane
32

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

calendar year (Table IV.C-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 calendar 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 IV.D-1.

Table IV.D-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

The modest NOx reductions predicted by equation (4) suggest that cetane improver

additives are, by themselves, an unlikely candidate for producing NOx emission reductions that

are equivalent to those produced for clean diesel fuel in California or other areas with Californialike fuel. For instance, the July 2001 Staff Discussion Document concluded that California

diesel fuel produces NOx reductions of approximately 6.2 percent (see Table III.F-2 in the Staff

Discussion Document). Assuming a natural cetane number of 45 as the base, Figure IV.A-1

shows that the NOx benefits of cetane improver additives could not exceed 4 percent even for

large concentrations of additive. In fact, cetane improver additives are already used in California

by many refiners under the equivalent formulation provision of that state's clean fuel regulations. 

On average, cetane improver additives are responsible for approximately one-third of the NOx

reductions generated by California diesel fuel, with the remaining NOx reductions being

generated by higher natural cetane, lower aromatics, and lower density.
33

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
34

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
35

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
36

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
37

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
38

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

11. Letter from Edward H. Murphy, American Petroleum Institute, to Leah Weiss, Ozone

Transport Commission, "Re: API Comments on OTC Diesel Cetane Model Rule," September 26,

2000

References