EPA420-R-93-017

December 1993

	








Office of Mobile Sources

U.S. Environmental Protection Agency
2

TABLE OF CONTENTS

Page

I. Treatment of Ethanol .................................................... 4

A. Exclusion from Market ............................................ 4

B. Congressional Intent ............................................. 9

C. Waiver ....................................................... 11

D. Reactivity ..................................................... 18

E. Benefits of Ethanol to the Nation ................................... 25

F. Feasibility of Renewable Oxygenate Proposal ......................... 27

G. Emission Impacts of the Renewable Oxygenate Proposal ............... 29

H. Reg Neg ...................................................... 32

I. Appendices .................................................... 33

II. Simple Model ......................................................... 61

A. Simple Model Equations and Referenced Work ....................... 61

B. Technical Corrections ........................................... 69

C. Caps on Fuel Parameters ........................................ 70

D. Averaging and Trading ........................................... 71

III. Complex Model Baselines .............................................. 73

A. Baseline Fuels ................................................. 73

B. Baseline Emissions ............................................. 77

C. Appendices .................................................... 108

IV. Complex Model ....................................................... 113

A. Exhaust Emissions Model ........................................ 114

B. Complex Model for Non-Exhaust Emissions .......................... 162

C. Determining Emission Performances ................................ 179

D. Range and Extrapolation of the Model ............................... 187

E. Use of the Complex Model Under Non-Summer Conditions .............. 227

F. Behavior of Complete Complex Model ............................... 232

G. Vehicle Testing ................................................. 249

H. Appendices .................................................... 275

V. Environmental and Economic Impact of Phase I Reformulated Gasoline .......... 303

A. Introduction .................................................... 303

VI. Phase II Reformulated Gasoline Standards and NOx Standards for Reformulated

Gasoline ............................................................ 311

A. Introduction .................................................... 311

B. Scientific Justification for NOx Control ............................... 313

C. Derivation of Fuel Parameter Control Costs .......................... 326

D. Derivation of Fuel Parameter Interrelationships ........................ 348

E. Determination of Emissions Reductions ............................. 367

F. Cost-Effectiveness Determination .................................. 373

G. Comparison with Other RFG Cost-Effectiveness Analyses ............... 382

H. Factors to be Considered in Setting Phase II RFG Standards ............. 383

I. Standards ..................................................... 393

J. Appendix VI-A: Tables VI-A1 to VI-A6 ............................... 398

VII. Anti-Dumping Requirements for Conventional Gasoline--RIA ................... 412

A. Introduction .................................................... 412

B. Emission Requirements .......................................... 412
3

C. Individual Baseline Determination .................................. 416

D. Baseline Auditor ............................................... 458

E. Baseline Submission and Approval ................................. 464

VIII. Compliance with the Regulatory Flexibility Act ............................... 469

A. Determination and Justification of Small Entity Impacts ................. 469

B. Summary and Assessment of Issues and Comments ................... 471

IX. State Opt-in Provisions ................................................. 479

A. General Provisions .............................................. 479

B. Phase I Opt-in only .............................................. 479

C. Attainment Area Opt-in ........................................... 480

D. Opt-out ....................................................... 481

E. Opt-In Application ............................................... 481

F. Opt-In Lead Time ............................................... 481

G. Define Domestic Capacity ........................................ 482

H. Opt-in only after Stage II controls and enhanced I/M .................... 482
4

. Treatment of Ethanol

One of the most controversial issues in the reformulated gasoline

rulemaking has been the treatment of ethanol blends. In the April, 16, 1992

proposal, EPA treated all fuels equally by requiring them to meet the same

emission performance standards. The February 26, 1993 proposal, however,

proposed an incentive program for the use of renewable oxygenates such as

ethanol which would allow them to meet a less stringent performance standard. 

Numerous comments were received on a number of topics related to whether EPA

should or should not provide special treatment for ethanol blends. The

following discussion presents EPA's summary and analysis of those comments

received which EPA believed were relevant to the reformulated gasoline

rulemaking. Some other comments were received which did not have any

relevance to the rule (e.g., relating to ethanol's use as a neat or near-neat

alternative fuel in alternative fueled vehicles), and as a result did not

influence the decision making process. A large number of comments were also

received which made unsubstantiated statements regarding the reformulated

gasoline proposal. To the extent these statements had any bearing to the

final rule they are also addressed in the summary and analysis of comments

below.

A. Exclusion from Market

A number of comments were received from ethanol and grain producing

industries that the April 16, 1992 proposal effectively excluded ethanol

blends from participating in the reformulated gasoline market. Ethanol is

typically splash blended into finished gasoline obtained at the gasoline

terminal, increasing the volatility of the resulting blend. According to the

commenters the simple model's reliance on a straight RVP standard, with no

volatility waiver for ethanol blends, would require ethanol blenders to use

sub-RVP gasoline blendstocks to enable the resulting blend to meet the simple

model RVP standard. This would be a clear departure from past practice, where

ethanol could lawfully be splash blended into almost any finished gasoline (as

long as it did not already contain an oxygenate). Commenters claimed that

refiners would be unwilling to provide sub-RVP clear gasoline blendstocks for

blending with ethanol given the refiners competitive interest in minimizing

ethanol's market share. In addition, commenters claimed that limitations in

terminal storage capacity would also preclude the use of unique blendstocks

such as a sub-RVP clear gasoline. Commenters also noted that the proposal's

provisions on presumptive liability and contract requirements between refiners

and blenders would make provision of the sub-RVP blendstock too risky. 

Finally, even though volatility was only an issue during the high ozone

season, commenters claimed ethanol would as a practical matter be excluded

year round as refiners would likely establish long term contracts for

oxygenates that would make it unlikely for them to switch oxygenates during

the course of the year. In addition, it would be hard for marketers to switch

from an ethanol based ether (ETBE) for summer use and an alcohol (ethanol) for

winter use. Exclusion from the summer market would therefore lead to

exclusion year round and would jeopardize the ethanol industry's ability to

maintain a market even in the wintertime oxygenate program in CO nonattainment

areas. While the reformulated gasoline standards appeared to be fuel neutral

on their face, commenters believed that in practice they would lead to

exclusion of ethanol from the reformulated gasoline program.

As discussed below in subsection E. the commenters also claimed that

this exclusion of ethanol would reduce competition in the oxygenate market and

thereby cause higher prices for reformulated gasoline, reduce investment in

rural and farm communities, increase federal grain subsidies, reduce domestic

jobs, and otherwise have serious adverse effects on the ethanol and grain

producing industries.
 1

 Memorandum from Paul Argyropoulos, Acting Chief,

Regional/State/Local Coordination Section, to Paul Machiele,

"Estimates of Volume of Ethanol Use in Oxy Fuel Program Areas

During the 1992/1993 Control Season," August 24, 1993.

5

Other commenters disputed these various assertions. For example,

various refiners claimed that there was no foundation for the assertion that

ethanol would be excluded. Certain refiners noted that they have used ethanol

in the past and intended to continue to do so in the reformulated gasoline

program. Some commenters claimed ethanol use would in fact expand, based on

the need for oxygenates year round in the reformulated gasoline program and in

wintertime program in many CO nonattainment areas. The Department of Energy

commented that the reformulated gasoline and wintertime CO programs were

expected to cause a substantial increase in the demand for all oxygenates,

including ethanol.

In general the comments which argued ethanol would be excluded from the

market focussed on the possible reduction in ethanol market growth in the

future under the reformulated gasoline program, not a reduction in the current

size of the ethanol market. As shown in Appendix I.A., a minority of the

areas currently covered by the reformulated gasoline program (including areas

opted in as of November, 1993) had any gasohol market share in 1990. Of those

that did, only a few had gasohol market shares above the national average of

approximately 8%. As a result, only about 20% of the ethanol demand in 1990

was used in reformulated gasoline areas, and only about 10% was used in those

areas during the summer VOC control period. Even if ethanol achieves only a

small market share under the reformulated gasoline program, it is likely to be

greater than the 4.5% average market share of gasohol in those areas prior to

the reformulated gasoline requirements, and no economic hardship to the

industry should result. Furthermore, demand for ethanol has already risen

dramatically as a result of the wintertime oxygenated fuels program required

under section 211(m) of the CAA.1

 As a result, it is very difficult to

believe any case where ethanol demand would decrease below the level that

existed prior to the CAA amendments of 1990. That being said, EPA has always

maintained that ethanol blends would not be excluded from the RFG market by

the April 16, 1992 proposal and that demand for ethanol would grow

considerably as a result of the program.

The largest part of the cost associated with Phase I reformulated

gasoline is the oxygen content required to be added by the Act. The RVP

control cost is small in comparison to the oxygen cost. Since ethanol costs

less than MTBE per gallon and contains almost twice as much oxygen per gallon,

it has a considerable economic advantage (as shown in Appendix I.B),

particularly given various state subsidies, and thus should be able to expand

its market. This is particularly true during the 6.5 to 7.5 months of the

year when no VOC control is necessary. But even during the 4.5 to 5.5 summer

months the only significant economic issue is the incremental costs for

distribution and segregation of ethanol blends which are no different from

those in the winter. Even the additional RVP control costs for ethanol are

reduced by the oxygen averaging provisions of the reformulated gasoline

program which allow ethanol to be blended at 3.5 wt% oxygen instead of 2.0 wt%

and receive economic compensation for the additional oxygen. Thus, EPA

believes that the economic advantage of ethanol over other oxygenates will

translate into refiners supplying sub-RVP gasoline for blending with ethanol

out of economic necessity. If they choose not to, at least in the areas where

the incremental distribution costs are small or where state subsidies for

ethanol exist, they will place themselves at a considerable disadvantage

relative to their competitors. The economic advantage of ethanol relative to
 2 "Evaluation of the USDA Alternative Renewable

Oxygenate Proposal," Final Report, Jack Faucett Associates for

the National Corn Growers Association, October 30, 1993.

6

MTBE was supported by a recent analysis for the National Corn Growers

Association2 even with the higher cost of a sub-RVP blendstock.

The economic advantage of ethanol was very evident during the 1992-3

oxygenated fuels program where ethanol made large market gains, even in areas

which had traditionally used little or no ethanol, and ethanol producers

earned record profits. While some ethanol producers may find it necessary to

reduce their profit margin somewhat to remain competitive under the

reformulated gasoline program, this neither excludes ethanol from the

marketplace nor treats it unfairly relative to any of the other oxygenates.

Some commenters claimed that regardless of ethanol's economic advantage

refiners would somehow band together to cut ethanol out of the reformulated

gasoline market. EPA believes such an action by the refiners to be highly

unlikely. Not only have refiners not taken such an action in the past under

either the conventional gasoline market or under the oxygenated fuels program,

but comments have also been received from various refiners stating their

intent to blend ethanol into reformulated gasoline. Furthermore, the

competitive economic risk is simply too great if even one refiner decided to

break ranks and blend ethanol. If, however, refiners were to decide as a

group not to blend ethanol, nothing short of a legal mandate for the use of

ethanol in reformulated gasoline could prevent such action. EPA has no legal

authority under the CAA to provide such a mandate for the use of ethanol.

Regardless of whether refiners intended to exclude ethanol from the

reformulated gasoline market or not, some commenters believed this would occur

automatically due to the risk to the refiner and necessary contract

requirements which would result to ensure that the final gasoline blend met

the requirements for reformulated gasoline. While EPA believes that there may

be some additional risk to the refiners to rely on downstream blenders for the

final quality of their reformulated gasoline, EPA has provided mechanisms

whereby refiners can minimize or even eliminate such additional risk (refer to

§80.69 of the regulations). As such, EPA does not believe it to be a

significant enough risk such that they would avoid entering into contractual

agreements with downstream blenders. 

In addition to being economically competitive as a pure additive,

ethanol may also be economically competitive as an ether feedstock. Due to

their low blending vapor pressure, ETBE (ethyl tertiary butyl ether) and TAEE

(tertiary amyl ethyl ether), ethers made from ethanol, may become competitive

with other oxygenates during the summer months under the reformulated gasoline

program, especially in the future when the more stringent Phase II performance

standards take effect. In fact, some commenters stated that ETBE was already

cost competitive with MTBE. Contrary to comments received, the current lack

of ETBE or ETAE production is not solely a result of their relative cost. 

Such oxygenates and their production on a large scale are very recent

technological developments. As such there has been no reliable cost

information for them until recently. Furthermore, their cost effectiveness in

reformulated gasoline is expected to exceed that in conventional gasoline due

to their low blending vapor pressure, high octane value per unit oxygen, and

various other factors which are of value to refiners in meeting the

reformulated gasoline requirements, but are not of value otherwise. As shown

in Appendix I.B., when these factors are taken into account ETBE nears the

point of being cost competitive with MTBE even at today's ethanol costs. 
7

Some commenters claimed that if ethanol was unable to maintain a large

market share during the summer months, that it would become uneconomical to

use during the winter months as well. They believed refiners would be

unwilling to switch off between various oxygenates. This belief, however,

appears to be unfounded. First of all, it is based on the invalid assumption

that ethanol will have no market either in the RFG program or in conventional

fuel areas during the summer months. Secondly, contrary to the intent of

various refiners to blend ethanol as stated in their comments, it assumes no

refiners would enter into long term contracts to blend ethanol, and third, it

ignores the fact that refiners have been willing to switch off between

oxygenates in the past. During the 1992-3 oxygenated fuels program refiners

blended ethanol during the winter and then switched back to conventional

gasoline during the summer. Furthermore, many refiners switched between

oxygenates during the winter period as well based on the local economic

conditions. Ethanol and MTBE producers alike were able to produce and store

adequate oxygenate to meet the peak demand during the winter months. In

addition, contrary to the commenter's belief, it could be argued that it is

easier for ethanol blends to tolerate an interrupted market than MTBE blends. 

The nature of ethanol production is that it could be reduced during the summer

by optimizing on plant production of corn sweeteners which are in high demand

during the summer. As a result, while ethanol production may be reduced in

lieu of reducing its price to maintain market share, the ethanol production

plant may be able to maintain full operating capacity. Methanol used to

produce MTBE has no other compensating market during the winter and is forced

to either reduce its price to maintain market share, rely on storage, or shut

down production. Since the winter period when ethanol is at an economic

advantage is longer than the summer period when MTBE may be at an economic

advantage, ethanol should have less of a burden. In fact, some of the

statements made supporting the claim that ethanol would be excluded from the

RFG market: inadequate tankage for multi-grades of fuel, inability of

refiners to switch off between oxygenates, etc., are equally applicable if not

more so to MTBE. Furthermore, using ethanol to produce ETBE during the summer

when ETBE's other advantages have value could be a viable means of maintaining

ethanol production year-round.

None of the comments received provided any data, information, or

analyses to support the statements being made. As a result, EPA stands behind

its analysis and belief that ethanol is fully capable of competing in the

reformulated gasoline market either as gasohol or as an ether feedstock. This

is particularly the case during the initial years of the reformulated gasoline

program when ethanol will have to play a strong role due to the demand for

oxygenates under the program which cannot be met through the use of MTBE

alone. This belief was echoed by a variety of other commenters.

A. Congressional Intent

A number of comments were received stating that it was the intent of

Congress in the Clean Air Act (CAA) that ethanol be included in the

reformulated gasoline program and that the April 16, 1992 proposal by EPA

violated that intent by discriminating against ethanol.

Congressional intent in establishing the reformulated gasoline program

can best be learned from the text of the statute and the legislative history. 

A review of the terms of section 211(k) makes clear that the central,

overriding purpose of this provision was the achievement of significant

reductions in ozone forming VOCs and toxic air pollutants in the major

metropolitan areas confronted with the most severe air pollution problems. 

Section 211(k)(1) establishes this as the central focus of this program,

mandating that EPA require the greatest achievable reductions in these

pollutants, considering various factors such as cost, air quality and other

impacts. In addition to this broad expression of intent, Congress specified

certain minimum elements of the reformulated gasoline program. Section
 3

 See e.g., 136 Congressional Record S3510,11 (March 29,

1990) (Statement by Senator Daschle); 136 Congressional Record

H2852 (May 23, 1990) (Statement by Representative Richardson).

 4

 See e.g., 136 Congressional Record S3513 (March 29,

1990)(Statement by Senator Daschle); 136 Congressional Record

S16922 (October 27, 1990) (Statement by Senator Durenberger).

8

211(k)(1) established various restrictions on gasoline qualities such as

oxygen and benzene content, and a cap on NOx emission increases, and section

211(k)(3) established minimum standard levels of performance for VOC and

toxics emission reductions. Congress also addressed a variety of other

important elements of the reformulated gasoline program, from credit programs

to certification and opt-in by states.

All of the minimum requirements in section 211(k) are set in a fuel

neutral manner, using performance criteria that are independent of the type of

gasoline subject to the criteria. There is no indication from the text of the

statute that Congress intended that ethanol blends not be subject to the same

minimum standards applicable to all reformulated gasoline. This is in marked

contrast to section 211(h), where Congress quite clearly established one RVP

standard for gasolines in general, and a separate, less stringent RVP standard

for ethanol blends under specified circumstances.

The legislative history of this provision does contain many discussions

pertaining to ethanol and other oxygenates. Since many of the detailed

provisions of section 211(k) were first adopted in floor amendments to the

House and Senate Bills, much of that legislative history is found in the floor

debate in the House and Senate on their bills and on the conference committee

bill. A large part of the discussion there on ethanol shows the belief of

many congressmen that ethanol would play a major role in supplying the oxygen

content required for this program, and would help to clean up gasoline by

reducing toxic air pollution.3

 There were no indications, however, that

ethanol blends of reformulated gasoline were not subject to the minimum

requirements established for all reformulated gasolines. There are in fact

indications that Congress saw these as fuel neutral standards that all blends

would have to face.4

In sum, EPA believes Congressional intent was to achieve significant

reductions in important air pollutants in areas of the Country with some of

the worst air pollution problems, and intended to accomplish this in part by

establishing minimum standards of performance that were fuel neutral and that

all reformulated gasolines would have to meet. EPA believes its final rule

faithfully implements this intent by setting identical emission performance

standards for all reformulated gasolines, regardless of the oxygenate used.

It is also true that many congressmen expected that ethanol blends would

be able to meet these standards, and would thereby play a major role in the

program. EPA believes this was a well founded expectation, and as noted

above, believes that ethanol blends will in fact play an important role in

this program. However, there is no indication that Congress intended or

authorized EPA to dilute the minimum requirements of the section 211(k)

described above to ensure an important role for ethanol. Congress did

envision that ethanol would play a large role in the reformulated gasoline

program, but only if it could meet the minimum requirements applicable to all

reformulated gasoline.

As stated above, EPA believes that the demand for ethanol will grow as a

result of the reformulated gasoline program as it has under the oxygenated
 5

 Memorandum from Acting General Councel to the

Administrator, dated November 17, 1992, "Applicability of Onepsi Ethanol Waiver Under Section 211(k) of the Clean Air Act to

Reformulated Gasoline."

9

fuels program. While it is true that the demand for ethanol could increase

even more if special provisions or incentives are provided for its use such as

proposed in the February 1993 proposal, EPA does not now believe that such

provisions are consistent with the minimum requirements that Congress intended

for all reformulated gasoline. While EPA is not opposed to further expanding

demand for ethanol, the authority granted to EPA under Section 211(k) of the

CAA is limited in this respect. It would be much more appropriate to provide

such incentives for ethanol outside of the reformulated gasoline rulemaking as

is currently done with the federal tax incentives for ethanol. 

A. Waiver

A large number of commenters stated that EPA should grant a 1.0 psi RVP

waiver to ethanol blended reformulated gasolines. They argued that it was the

intent of Congress that the RVP waiver granted to ethanol blended with

conventional gasoline under Section 211(h) of the CAA also apply to ethanol

blended in reformulated gasolines under Section 211(k). They further argued

that the rationale used by Congress and EPA in granting the waiver under

Section 211(h) was equally applicable to reformulated gasoline and that the

ozone reactivity and other benefits were sufficient to offset any emission

increase which might result. Granting a waiver, it was stated, would allow

ethanol to effectively compete in the reformulated gasoline market. Finally,

some commenters explained that during the regulatory negotiations on this

rulemaking they had assumed that a one psi RVP waiver would be applied to

ethanol blends of reformulated gasoline.

There were also many comments disputing the above assertions. These

commenters claimed that a one psi waiver for ethanol blends was unlawful and

that granting such a waiver would violate the intent of Congress. They

claimed that a waiver would have serious adverse environmental impacts. They

argued that such a waiver would be discriminatory and unfair, and would be

counter to free market principles. Finally, they argued that such a waiver

was discussed during the regulatory negotiations, at least informally, and

that granting an RVP waiver for ethanol blends would violate the consensus

agreement reached during these negotiations.

1. Intent of Congress

EPA has closely considered the arguments that the 1.0 psi waiver for

ethanol blends provided under section 211(h) applies to the RFG program. For

the reasons set forth in a legal opinion issued by EPA's legal council,5

 EPA

believes that the 1.0 psi waiver under section 211(h) does not apply to

section 211(k).

2. Environmental Impact

EPA believes that granting a 1 psi RVP waiver for ethanol blends would

have significant adverse environmental impacts. As shown in a memorandum and
 6 Memorandum from Paul A. Machiele, Fuel Studies and

Standards Branch, to Richard D. Wilson, Director, Office of

Mobile Sources, "Update of the Relative Ozone Reactivity of

Reformulated Gasoline Blends," June 11, 1993.

 7 Letter from Chester J. France, Director, RDSD to Dr.

Gary Whitten, Chief Scientist, Systems Applications

International, September 24, 1993.

10

subsequent letter from EPA staff in the docket,6 7 an ethanol blend that meets

all of the requirements for reformulated gasoline except that it has an RVP

1.0 psi higher than that required of non-ethanol blends would cause roughly a

20% increase in VOC emissions relative to the baseline gasoline (including

estimates for the effect of commingling and distillation). This represents a

31% increase in VOC emissions compared to a fuel which meets the minimum

requirements for reformulated gasoline. Based on the relative costs of the

various oxygenates as shown in Appendix I.B., ethanol blends with a 1.0 psi

RVP waiver would have a significant competitive advantage over other

reformulated gasoline blends and could be expected to dominate the RFG market

in some areas, particularly mid-western RFG cities such as Chicago and

Milwaukee where ethanol distribution costs are relatively small. With a 1.0

psi waiver EPA expects there would be a significant shift to ethanol blends

and a resulting significant increase in VOC emissions over what would occur

without a waiver. Many areas would achieve significantly smaller reductions

in VOC emissions than the minimum 15% required under the Act, and in areas

with a large market share for ethanol blends, the reformulated gasoline

program would actually increase summertime VOC emissions and not decrease

them. For example, as shown in Table I.1., even at the pre-program ethanol

market share of approximately 8% an ethanol waiver would eliminate nearly 28%

of the VOC control otherwise achieved by the program. If the ethanol market

share increases to 24% as under 1992-3 the winter oxygenated fuels program (on

average), roughly 74% of the VOC control otherwise achieved by the program is

eliminated. At an ethanol market share above just 35%, as would be expected

in many areas where a waiver granted (particularly the Midwest as occurred

under the oxygenated fuels program), all of the VOC control of the program is

eliminated and VOC emission increases would actually occur relative to the

pre-program baseline.
11

Table I.1. Loss in In-Use VOC Emission Control as a Result of Ethanol Waiver

Under RFG*

Ethanol Market Share

0% 8% 24% 30% 35%

% VOC Reduction

Due to MTBE Share

11 10.1 8.4 7.7 7.2

% VOC Reduction

Due to Ethanol Share (with

distillation)

0 -1.0 -3.1 -3.9 -4.6

% VOC Reduction

Due to Commingling

0 -1.2** -2.4 -2.4 -2.4

Total % VOC Reduction 11 7.9 2.9 1.4 0.2

Percentage Change from 100%

MTBE Baseline

NA 28 74 87 98

* Emission percentage change input values for the table are based on those

calculated in the letter from Chester France to Dr. Gary Whitten

described in footnote 6. ** Commingling assumed half of that at higher market shares based on

analysis in Appendix I.D.

A 1.0 psi waiver would therefore have a large impact on the VOC emission

inventory. EPA believes this would have a significant adverse impact on ozone

levels in the areas of the country already facing the worst ozone problems. 

EPA does not agree with the arguments made by several commenters that for

reactivity and other reasons this increase in VOC emissions would not increase

ozone (see subsection D). This increase in VOC emissions would also place a

serious obstacle in the way of the states in their planning to meet the Act's

reasonable further progress requirements.

EPA would appear to have the flexibility, under certain circumstances,

to establish a different VOC or toxics emission reduction standard for ethanol

blends. Under section 211(k)(1), EPA is to consider "cost..., any nonairquality and other air-quality impacts" in establishing requirements that

obtain the greatest achievable emission reductions from gasoline

reformulation. This mandate, in conjunction with the minimum requirements of

section 211(k)(2) and (3), arguably would authorize EPA to establish a less

stringent RVP or VOC performance standard for ethanol blends if the

circumstances warranted and the ethanol blends still met all the minimum

requirements of section 211(k), including the minimum VOC and toxics

reductions required under section 211(k)(3). The Renewable Oxygenates Program

proposed by EPA in February 1993 was based in part on this approach. However,

for all of the reasons described above and elsewhere, EPA does not believe

that it could take this approach in the context of a 1.0 psi waiver for

ethanol blends. EPA believes that ethanol can and will play an important role

in reformulated gasoline without a 1.0 psi waiver, and that granting such a

waiver would therefore be unreasonable.

With a 1.0 psi waiver, the RVP standard for reformulated gasoline under

the first phase of the program would have to be roughly 7.1 psi in both

northern and southern areas if the ethanol blends were to still achieve the

minimum VOC and toxics reductions required under section 211(k). This would

not be a reasonable exercise of EPA's discretion given the cost, energy, and

other impacts described elsewhere. Even in the southern portions of the

country, where EPA does believe a 7.1 RVP standard is currently feasible, a
 8

 Phase I regulations applied to the 1989 through 1991

summertime control period (52 FR 31274, August 19, 1987), while

Phase II regulations applied thereafter (5 FR 23658, June 11,

1990). EPA recently revised the Phase II regulations to

conform with the requirements of § 211(h), added in the Clean

Air Act Amendments of 1990 (56 FR 64704 (December 12, 1991).

12

1.0 psi waiver for ethanol is not appropriate. In the context of a 1.0 psi

waiver, the RVP standard under Phase I in southern areas would have to be 6.2

psi if comparable emission reductions are to be achieved under the

reformulated gasoline program in the South as in the North; otherwise little

or no environmental benefit would be achieved in southern areas under the

reformulated gasoline program. Furthermore, since the majority of the

southern reformulated gasoline required under the Act is sold in California

which has its own strict requirements for reformulated gasoline, a waiver for

ethanol in southern areas would be of little or no benefit to the ethanol

blending industry. 

3. Gasoline Volatility Rulemaking Decision

Several commenters argued that EPA should allow a 1.0 psi waiver for

ethanol blends in the reformulated gasoline program for the same reasons EPA

allowed such a waiver in its national regulations of gasoline RVP. EPA

disagrees with these commenters for a number of reasons.

EPA established limits on the summertime volatility of gasoline in two

Phases, pursuant to its broad regulatory authority under section 211(c) of the

Act.8 These limits applied nationwide. For both Phase I and Phase II RVP

regulations EPA set a 1.0 psi waiver for ethanol blends that met certain

alcohol content requirements. The primary reason EPA adopted such a waiver

was to avoid the near catastrophic economic impact on that industry if no such

waiver was allowed. EPA was convinced of the reality of this jeopardy, and

the inability of the industry to survive it. At that time there was no

significant alternate market for ethanol such as widespread use of the ether

ETBE or a large-scale program to require the use of oxygenates in various

cities. In that context, EPA believed it would require strong evidence of

severe environmental consequences before it would impose a policy which might

eliminate that industry. There was no evidence of such severe environmental

consequences, and instead EPA's concerns over the negative air quality impact

of 1.0 psi RVP waiver had been moderated during the rulemaking process (See 55

FR 23665, 23666). At the same time, EPA announced that it would continue to

explore the economic and air quality issues involved with a 1 psi RVP waiver,

and reserved the right to propose changes in the RVP regulations if

appropriate (See 55 FR 23666).

EPA's concern over the environmental impact of a 1 psi RVP waiver

stemmed from the evidence showing that substantial VOC emission increases were

known to occur with ethanol blends relative to conventional gasoline. This

RVP and resulting VOC emission increase, however, existed with ethanol blends

prior to the volatility control rule. Thus, providing a waiver under the

volatility control rule required only the same RVP control from ethanol blends

as from non-ethanol containing gasoline. Since the rule was not expected to

increase the use of gasohol with its higher emission potential (the market

share of gasohol had been approximately 8% nationwide), EPA believed that

providing a waiver would not significantly compromise the environmental

benefits of the program nationwide. To illustrate this point, the volatility

control rulemaking reduced the volatility of all gasoline by approximately 2.7

psi RVP. The 1 psi RVP waiver for the 8% of the gasoline market represented
13

by ethanol blends, thus, represented a loss of only 0.08 psi across all in-use

gasoline, or less than 3% of the volatility control that would otherwise have

been achieved by the rulemaking. To the extent that ethanol blends achieved

lower exhaust VOC and CO emissions, these only served to offset what was

already considered to be a small loss in emission control relative to the

control achieved. As a result, providing the waiver did not result in any

environmental detriment, but just slightly diminished the potential

environmental benefits that could otherwise have been achieved by the

regulations. 

In balancing the severe economic impact of not allowing a RVP waiver

with the generally modest concerns about the VOC and ozone impacts of such a

waiver, EPA reasonably exercised its broad discretion under section 211(c)(1)

of the Act and provided a 1.0 psi RVP waiver in the national RVP regulations.

The situation confronted in this rulemaking is significantly different. 

First, the existence of a 1.0 psi waiver in the reformulated gasoline program

does not raise the same kind of life or death situation confronting the

ethanol industry in EPA's RVP rulemakings. The requirements for reformulated

gasoline do not apply nationwide, thereby maintaining markets for ethanol in

conventional gasoline during the summertime. In addition, refiners have no

choice on whether or not their reformulated gasoline will be oxygenated. 

Based on the year-round oxygen content requirement for reformulated gasoline,

and the wintertime oxygen requirement for gasoline marketed in numerous CO

nonattainment areas, EPA believes that the demand for ethanol will increase

significantly without an RVP waiver, either as an oxygenate or as a blendstock

to produce ETBE. This is in marked contrast to the situation confronting EPA

and the ethanol producing industry in the national RVP rulemaking.

Furthermore, the environmental impact of an RVP waiver under the

reformulated gasoline rulemaking would be significantly more severe than it

was under the volatility control rulemaking. As discussed above in subsection

C.2, a 1.0 RVP waiver coupled with the reformulated gasoline program's oxygen

requirement could result in a significant increase in the use of ethanol

during the summer months, leading to significant emission increases and the

elimination of a large percentage of the ozone-related benefits of the

program. This stands in stark contrast to the less than 3% loss of the

emission reductions from the gasoline volatility control program as a result

of the waiver.

Another significant difference between this rulemaking and the previous

national RVP rulemaking is the difference in statutory authority. The

nationwide RVP regulations were based on EPA's broad discretionary authority

under section 211(c) of the Act. An RVP or VOC performance waiver could be

established for ethanol blends in the reformulated gasoline program only if it

was authorized and justified under section 211(k). That provision, however,

places many more constraints on EPA's discretion than section 211(c),

including, for example, the minimum mandatory reductions in emissions of ozone

forming VOCs and toxics. This and the other statutory provisions in section

211(k) limit EPA's discretion to allow a 1.0 psi waiver for ethanol blends. 

For all the reasons described above and elsewhere, EPA does not believe that a

1.0 psi waiver for ethanol blends would be proper under section 211(k) of the

Act.

4. RVP Increase From Ethanol Blending

Some comments suggested that ethanol blends may not actually cause an

increase in the volatility of in-use gasoline. Other comments suggested that

the volatility increase disappears at ethanol concentrations of 20%. A great

deal of data and information collected by both EPA and outside parties on a

wide variety of gasolines demonstrates that ethanol does in fact increase the

vapor pressure of in-use gasolines when blended in at low concentrations. 
 9

 "Volatility Characteristics of Gasoline-Alcohol and

Gasoline-Ether Fuel Blends," Robert L. Furey, General Motors

Research Laboratories, SAE Paper No. 852116, October 1995.

14

Some of this data is discussed in section G. There is less data available as

to what the vapor pressure increase is at ethanol concentrations above 10

volume percent, but the available information suggests that blending as much

as roughly 50% ethanol into gasoline still increases the vapor pressure of the

blend.9 Since blends of 10 volume percent ethanol or less are all that could

lawfully be used in the reformulated gasoline program at the present time, the

fact that the volatility increase disappears with blends with greater than 50%

ethanol is not relevant to this rulemaking. Despite the available data, if

ethanol were to be determined not to cause an increase in the volatility of

the blend, then there would be no need for a waiver since ethanol could easily

comply with the RVP requirements.

Some comments were also received suggesting that the volatility increase

for ethanol blends was due to the butane in the gasoline, and not the ethanol

being added to the gasoline. While butane is a hydrocarbon found in gasoline

with a high vapor pressure, and as such represents the largest fraction of

evaporative emissions from today's gasolines, the RVP increase which occurs

when ethanol is added to gasoline is not due to butane. Ethanol, being an

alcohol, is a polar molecule that has a low vapor pressure when relatively

pure due to a strong tendency to self-associate through hydrogen bonding. 

When mixed with gasoline the hydrogen bonding is greatly reduced causing a

large increase in the vapor pressure of the mixture. The increased vapor

pressure increases the tendency of all of the hydrocarbons in the mixture to

evaporate, not just butane. The vapor pressure increase would occur even if

all butane were removed from the gasoline prior to blending with ethanol. In

fact, as the vapor pressure of the base gasoline decreases (and butane content

decreases) the RVP increase resulting from adding ethanol to the gasoline

increases rather than decreases. In any case, the source of the volatility

increase in ethanol blends is not important--no matter the source, blending

ethanol into gasoline at the levels expected in the reformulated gasoline

program leads to significant increases in volatility.

5. Mandate for Blendstock and Ethanol Market Share

In the context of the waiver discussion a number of commenters also

suggested that if a waiver were not granted that EPA should promulgate

provisions to mandate that refiners either produce a blendstock capable of

being blended with ethanol downstream and still meet the criteria for

reformulated gasoline certification, or use ethanol as the oxygenate in a

certain fraction of the RFG they produce. In the alternative, one commenter

suggested providing a 1.0 psi waiver for ethanol blends if refiners did not

provide an adequate supply of sub-RVP blendstock. While these approaches

would ensure the use of ethanol in the reformulated gasoline program during

the summer months, EPA does not believe that it has authority under either

§211(c) or 211(k) to impose the suggested provisions under the present

circumstances. Furthermore, as discussed in section G., these approaches

would not necessarily be environmentally neutral even though no increase in

RVP would result.
 10 In a similar fashion Congress, in the separate

provision addressing anti-dumping, established limits on the

average per gallon emissions of volatile organic compounds,

without reference to ozone forming potential, and again

specified that compliance with the anti-dumping requirements

was to be measured "on a mass basis." See §211(k)(8)(A) and

(C).

15

A. Reactivity

A number of comments were received which attempted to find methods by

which the evaporative VOC emission increases associated with splash blending

ethanol into gasoline could be offset. These comments stated that while the

RVP increase resulting from blending ethanol into gasoline may cause an

increase in evaporative VOC emissions, the additional exhaust VOC and CO

reductions resulting from the additional oxygen in a 10 volume percent ethanol

blend and the lower relative reactivity of emissions from ethanol blends

offset any increase in ozone that might occur. As a result, they stated that

this justified either the RVP waiver discussed above, or the inclusion of

relative ozone reactivity in the determination of the VOC performance

standards for reformulated gasoline. As discussed in the April 16, 1992

proposal, one method suggested for incorporating the ozone reactivity benefits

of ethanol blends was to include carbon monoxide (CO) in the definition of

what comprises a reactive VOC and adjust its mass to take into account its

relative ozone reactivity. This method was referred to as the "carbon mass

equivalent" method.

6. Statutory Authority for Reactivity Based Adjustment

The text of section 211(k) does provide EPA with certain discretion to

consider the relative reactivity of different volatile organic compounds;

however, it is clear from this section that EPA may not consider reactivity

for purposes of compliance with the minimum emissions reductions required by

section 211(k)(3). Section 211(k)(1) requires that EPA establish requirements

for reformulated gasoline that obtain the greatest achievable reductions in

emissions of "ozone forming volatile organic compounds... and toxic air

pollutants" and the provision for certification of reformulated gasoline again

refers to ozone forming volatile organic compounds (see section 211(k)(4)(B)). 

While the statute defines toxic air pollutants (see section 211(k)(10)(C)), it

defines neither ozone forming volatile organic compounds nor volatile organic

compounds. The use of the undefined phrase ozone forming volatile organic

compound would, therefore, appear to provide EPA with certain discretion to

consider ozone forming potential or reactivity of different VOCs.

At the same time, Congress clearly limited this discretion by explicitly

stating that the minimum reductions in emissions of ozone forming VOCs and

toxic air pollutants required under section 211(k)(3) "shall be on a mass

basis."10 Since both of these provisions must be given meaning, there would

appear to be only one reasonable interpretation. EPA would have discretion to

consider reactivity in deciding what volatile organic compounds should be

considered ozone forming, but compliance with section 211(k)(3)(B)'s minimum

percentage reduction in ozone forming VOCs would be based on mass reductions,

without further adjustment for ozone forming potential. In effect, EPA would

establish what VOCs are ozone forming VOCs and reformulated gasoline would

then have to meet at least a minimum percentage reduction, on a mass basis, of

these VOCs. Since the limitation to reductions on a mass basis refers to

requirements under section 211(k)(3)(B), if EPA required greater than these

minimum emissions reductions, then its authority under section 211(k)(1) would

appear to give EPA the discretion to consider reactivity in requiring these
 11Section 217, S. 1630 as passed by the Senate on January

23, 1990.

 12 See, e.g. 136 Cong. Rec. S16922 (daily ed. October 27,

1990) (statement of Senator Durenberger) ("The VOC reduction

requirement is 15 percent in the year 1995. The reduction is

measured in the mass of emissions comparing emissions from

[baseline vehicles burning baseline gasoline] and the same

vehicles burning any proposed reformulated gasoline...."); and

136 Cong. Rec. H12900 (daily ed. October 26, 1990) (statement

of Representative Hall) ("... the use of a mass basis test...

compares the percentage difference between emissions from

baseline gas and from the proposed reformulated gas"

(discussing the need to control the vehicle variable in

evaluating a reformulated gasoline performance)).

16

further reductions, as long as the minimum required reductions were obtained

on a mass basis.

The legislative history for this provision supports EPA's

interpretation. The bills passed by the House and Senate both contained

provisions for reformulation of gasoline, requiring reductions in "ozoneforming volatile organic compounds" and "ozone-forming potential of volatile

organic compounds,"11 respectively. Both provisions required 15% reductions

in these volatile organic compounds, but neither provision referred to mass

emissions. In fact, the House bill specifically required that the

Administrator consider "reactivity and relative toxicity" in establishing the

reformulated gasoline requirements. In conference, Congress removed the

reference to reactivity and relative toxicity found in the House bill, and

added the provision calling for measurement of emissions on a mass basis. The

House bill's anti-dumping provision was generally adopted by the conference

committee, but again a provision for determining compliance on a mass basis

was added. Although there is no indication in the conference committee report

on why these changes were made, the clear import of these changes is that

Congress intended to restrict the Administrator's ability to consider

reactivity, at least in the context of the minimum reductions required in

Phase I and II of the reformulated gasoline program. The statements of

various congressmen during debate of this provision support this view,

indicating the conscious choice of a mass basis standard.12

EPA's interpretation is also reasonable when considered in relation to

another important ozone control provision in the Act. Section 182 requires

that various ozone nonattainment areas submit SIP revisions providing for a

schedule of percentage VOC reductions from a 1990 baseline of actual VOC

emissions. Compliance with this requirement is based on reductions in the

mass of the VOCs, without adjustment for reactivity. Interpreting section

211(k) to allow for significant increases in VOC emissions would present a

major impediment for state compliance with the section 182 requirements. 

Commenters failed to provide a resolution to this problem other than suggest

that states be provided with a credit for the VOC increases caused by ethanol

blends. EPA does not have authority to grant such a credit.

Several commenters also suggested that EPA define CO as an ozone forming

VOC. While the technical and policy reasons for rejecting this approach are

discussed later, it is also important to note that EPA recently conducted a

rulemaking to define volatile organic compounds for a wide variety of CAA

purposes. In that final rule EPA followed its prior regulatory approach and

excluded CO from the definition, as well as several other chemical compounds
17

that include carbon. The agency clearly stated that CO and certain other

compounds were well understood by the scientific community not to be

considered as organic and, therefore, could not be considered as a VOC (see 57

FR 3944, February 3, 1992). Furthermore, as discussed below the relative

reactivity of CO is very low such that even if it were considered to be

organic, it would be excluded from the definition of VOC on this basis as well

under the established EPA regulations. The comments do not present material

to change this view, and it would be arbitrary for EPA to do so now, given the

significant, adverse impact this would have on EPA's and the states' overall

ozone control strategy.

7. Technical Validity

a. CO as an Ozone Forming VOC

As noted above, EPA has discretion to determine what VOCs are "ozone

forming" for purposes of section 211(k). The low relative reactivity of

methane and more recently ethane was the basis for their exclusion from the

Agency's definition of VOC in the rulemaking discussed in the previous

paragraph, and ozone forming VOC in the most recent proposal for this

rulemaking. According to the California Air Resources Board's (CARB) relative

reactivity scales, methane is more than one order of magnitude less reactive

than the next least reactive hydrocarbon, ethane, and more than two orders of

magnitude less reactive than the average hydrocarbons contained in gasoline

vehicle emissions. Since there are a number of compounds in the emissions

from gasoline vehicles that are just slightly more reactive than ethane, there

is no justification at this time for excluding any additional compounds from

the current definition. Ethanol's relative reactivity is more than five times

that of ethane, while methyl tertiary butyl ether's (MTBE) is 2-1/2 times that

of ethane and half that of ethanol. In fact, 50 of the 168 hydrocarbons in

CARB's scale have ozone reactivities less than that of ethanol. Furthermore,

since the emissions from ethanol blends are comprised of essentially the same

compounds as the emissions from MTBE and pure gasoline blends (with the

exception of the oxygenates themselves), just in different amounts, excluding

any of the compounds with the next lower relative ozone reactivity would

effect the performance of ethanol blends little relative to other fuels. 

Just as there is no justification for excluding any additional compounds

from the definition of what comprises reactive VOCs, there is also no

justification for including any additional compounds at the present time. A

number of comments were received suggesting EPA should include CO in the

definition of ozone forming VOC. CO, however has a relative ozone reactivity

of roughly one-fifth that of ethane and nearly one-fiftieth that of average

gasoline hydrocarbon emissions. Given its low reactivity relative to the

majority of hydrocarbons, it would be inappropriate to include it in the

definition of ozone forming VOC. This is particularly true given the relative

magnitude of CO emissions to hydrocarbon emissions in the exhaust of gasoline

vehicles. If the Agency included CO in the definition of VOC the relative

ease of reducing CO emissions to hydrocarbon emissions through fuel

modification would turn the reformulated gasoline program into a CO control

program and virtually eliminate all ozone benefits.

b. Reactivity Adjustment

Even if the Clean Air Act provisions allowed the minimum VOC performance

standard to be met on an ozone reactivity weighted basis, the science is far

from adequate to support a move away from mass based standards. All reactive

VOCs eventually react to form ozone. Their relative reactivity is merely a

measure of how quickly they react compared to other VOCs. Depending on the

ambient conditions, some VOCs may not react before being blown out of the nonattainment area by the prevailing winds. However, they will then react

downwind to form ozone. Thus, even the less reactive VOCs can represent a
 13 See Footnote 6

 14 Letter from Chester J. France, Director, RDSD to Dr.

Gary Whitten, Chief Scientist, Systems Applications

International, September 24, 1993.

 15 Letter from Paul A. Machiele, Fuel Studies and

Standards Branch, to Dr. Gary Whitten, Chief Scientist, Systems

Applications International, September 8, 1992.

 16 Letter from Paul A. Machiele, Fuel Studies and

Standards Branch, to Eric Vaughn, President, Renewable Fuels

Association, August 6, 1992.

 17 Letter from Charles L. Gray Jr., Director, Regulatory

Programs and Technology, to Timothy McNulty, Executive

Director, Council of Great Lakes Governors, June 4, 1993.

 18 Evaluation of the Ethanol Air Quality Study by the

Council of Great Lakes Governors," Memorandum from Paul A.

Machiele to Richard A. Rykowski, Chief, Fuel Studies and

Standards Branch, and Chester J. France, Director, Regulation

Development and Support Division, August 5, 1993.

18

significant concern, particularly in areas such as the northeast corridor,

where there are many ozone non-attainment areas at some distance downwind of

each other. Furthermore, the determination of the relative reactivity of the

various VOCs is a function of the ambient conditions. As a result, the

relative reactivity of various VOCs may be very different from day to day and

from city to city making it difficult to apply one set of relative reactivity

assumptions nationwide. A compound which demonstrates a low tendency to form

ozone in one city may demonstrate a higher tendency in another city, or even

the same city on a different day.

Even if we were to consider reactivity in the context of the

reformulated gasoline rulemaking despite the legal constraints and scientific

uncertainties, it would not be beneficial to ethanol. An analysis using the

CARB relative reactivities in a letter from Chester France to Dr. Gary

Whitten13 indicates that an ethanol blend with 1 psi higher RVP would, after

adjustments for ozone reactivity, increase VOC emissions from a typical 1990

model car by approximately 19% relative to other reformulated gasolines (if

the commingling effect of ethanol blends with other gasolines is incorporated

into the analysis).

Several commenters submitted modeling analyses prepared by Systems

Applications International (SAI) as justification for much larger ozone

reactivity benefits for ethanol blends than estimated by EPA. EPA has

carefully reviewed SAI's analyses and rejects their conclusions because the

analyses are fraught with invalid assumptions and inconsistencies which make

it impossible to use the studies to appropriately quantify the effect on ozone

resulting from the use of a reformulated gasoline containing ethanol with a

1.0 psi RVP waiver relative to a reformulated gasoline containing MTBE. EPA's

comments and criticisms of these studies are contained in various letters and

memorandums located in the Docket and in Appendix I.C.14 15 16 17 18 In the most

recent study for the Council of Great Lakes Governors, SAI attempted to

correct many of the problems which they recognized existed with the earlier
19

studies. However, a number of serious errors were made in the protocol

causing the study's results to be of little scientific value. One of the most

serious of these errors being the exhaust VOC and CO emission credit assigned

to the ethanol by comparing an ethanol blend with 3.5 weight percent (wt%)

oxygen to an MTBE blend with 2.0 wt% oxygen. This comparison, assumed in all

three of these SAI studies, is invalid for analyzing the air quality impacts

of fuels under the reformulated gasoline program due to the oxygen averaging

provisions of the Act. Furthermore, the magnitude of the credit given for the

additional oxygen is significantly larger than that now predicted by EPA's

Complex Model. Due to this and other erroneous assumptions, the study

drastically underpredicted the evaporative emission increases and

overpredicted the exhaust emission benefits with ethanol blends relative to

MTBE blends (not only in highway vehicles, but even more so in non-road

engines which are not even considered under section 211(k) of the Act) for a

reformulated gasoline scenario. Since the study assumed only a small

contribution of gasoline vehicles to the total VOC inventory, the result of

the combined set of assumptions was very little increase in VOC emissions for

the ethanol blend. The study also assumed large NOx emission increases for

both on-road and non-road engines with ethanol blends which, combined with the

very low VOC/NOx ratio assumptions caused the urban ozone decreases shown with

the ethanol blend despite a small increase in overall VOC. Such an assumption

with respect to NOx is in violation of the requirements for reformulated

gasoline under section 211(k), and is also inconsistent with the currently

available information on the effect of fuels on NOx. 

Even if the studies performed of Chicago and New York by SAI were valid

studies, it would be difficult for EPA to justify using their results to

reactivity weight VOC emissions in the reformulated gasoline rulemaking. 

Reformulated gasoline will be sold in many different areas of the country,

representing a wide variety of ambient conditions. Given our current

understanding of air chemistry, widely different results would be expected for

different cities, episodes, and timeframes. Thus, it would be difficult to

draw conclusions that are applicable nationwide from urban airshed modeling of

just one or two ozone episodes in one or two cities. This is especially the

case when the model is used to focus on the ozone effects of one specific

change, such as the use of ethanol, in motor vehicle fuel. The model

considers the entire emissions inventory (mobile, point, area and biogenic

sources) for the area, as well as a large number of other variables for which

input assumptions must be made. All of these factors can influence the

results and mask the impact of fuel changes on overall VOC mass emissions and

ozone. The influence of these factors is one of the primary reasons for the

widely different results of studies conducted by SAI for the Illinois Corn

Growers Association, National Corn Growers Association, and Council of Great

Lakes Governors and studies conducted by SAI for the Auto/Oil Air Quality

Improvement Research Program and in the past for EPA.

8. Carbon Mass Equivalent

In the April 16, 1992 proposal, EPA asked for comments on a concept

referred to as the carbon mass equivalent (CME) method, a modified approach

for treating CO as a VOC. Rather than merely counting the mass of CO

emissions as VOC as discussed above, this approach would exclude the mass of

oxygen from CO and apply certain other adjustments to its mass before counting

it as VOC. EPA received a number of comments supporting such an approach, as

well as a number of comments rejecting such an approach.

EPA does not believe the CME approach represents a valid approach in the

context of our reformulated gasoline rulemaking. Excluding only the oxygen

mass from carbon monoxide would still greatly overemphasize the ozone forming

potential of carbon monoxide relative to other gasoline vehicle emissions by

roughly a factor of 20. As discussed above, this would quickly turn the

reformulated gasoline program into a CO control program and virtually
20

eliminate all ozone benefits. The only rationale for making additional

adjustments to the mass of CO would be its relative ozone reactivity. This

would improperly incorporate ozone reactivity into the rulemaking, contrary to

EPA's authority under section 211(k). Furthermore, there is no justification

for giving credit for only the CO emission reductions resulting from one type

of oxygenate as was suggested by some of the comments, or even just oxygenates

as a group. The effects on CO of all fuel modifications would have to be

determined and appropriate credit given. If the proper adjustment were made

to the carbon mass to reflect the relative reactivity of CO and other

oxygenates and fuel parameters that affected CO emissions were also provided

this carbon mass equivalent, then ethanol blends would receive little

additional credit relative to other reformulated gasolines.

A. Benefits of Ethanol to the Nation

A number of comments were received supporting a strong role for ethanol

blends in reformulated gasoline through either an RVP waiver, former President

Bush's ethanol announcement or some other means on the basis of the benefits

of ethanol to our Nation relative to a situation where ethanol is excluded

from participation in the reformulated gasoline market. Such stated benefits

included: improved energy security, increased rural development, reduced

foreign trade deficit, reduced U.S. unemployment, reduced federal agricultural

subsidies, and many others.

EPA believes that the ethanol industry is important to the nation, and

provides many valuable benefits. As stated before, EPA does not believe that

ethanol will be locked out of the reformulated gasoline program, or that the

demand for ethanol will shrink. Instead, EPA believes that ethanol will play

a large role in providing oxygenate to meet the increased demand for oxygen

from the year-round reformulated gasoline program and from the wintertime CO

programs. In that context, the issue before the Agency is to identify and

quantify the benefits to the nation from any additional increase in demand

over and above that anticipated from these programs that might result from

either a one psi waiver under reformulated gasoline or from an incentive

program such as the program proposed by EPA in the February 26, 1993 proposal. 

EPA, of course, would also need to look at any adverse impacts from such an

increase in demand, as well as its authority to allow a one psi waiver or an

ethanol incentive plan like that proposed in February, 1993. Viewed in that

light, many of the comments submitted in support of the ethanol industry

position provide little help in resolving these issues. Few of the comments

contained any analysis supporting how the claimed benefits would be achieved,

and when analysis was provided, it focused on comparing the benefits of a

large increase in the demand for ethanol with a large decrease in demand. 

None of the comments showed why EPA's April 1992 proposal would fail to

achieve the claimed benefits. In addition, none of the comments provided a

direct link between such benefits and special provisions for ethanol. 

Finally, none of the comments provided an analysis showing that the claimed

increase in benefits was justified in light of the cost and environmental

impacts from such a program.

As discussed in Section A., EPA believes ethanol is not excluded from

the reformulated gasoline market. Rather, EPA believes that the reformulated

gasoline program will increase the market share of ethanol over and above the

increase already achieved under the wintertime oxygenated fuels program. As a

result, EPA believes that if the benefits to the nation discussed in the

comments will occur as a result of increased ethanol demand, then the

incremental increase in ethanol demand resulting from the reformulated

gasoline program will result in a corresponding incremental increase in such

benefits to the nation. As discussed in section C., however, further

encouraging the use of ethanol through an RVP waiver could easily eliminate

all of the VOC emission reductions of the reformulated gasoline program. As
 19 As discussed previously, neither the 1.0 psi waiver

under section 211(h), adjustments to reactivity, nor

adjustments based on CO emission reductions can be used to

offset the RVP and resulting VOC increase in ethanol blends. 

An energy analysis based on such assumptions would therefore

not be relevant.

21

such, there would not appear to be any rationale for attempting to increase

the ethanol market in this manner.

Similarly, the loss in environmental control discussed in Section G.

resulting from the renewable oxygenate provisions of the February 26, 1993

proposal strongly argue against its use to expand the market share of ethanol

despite the potential incremental benefits to the nation that might otherwise

accrue. Increasing the ethanol market to just 30% under the proposed program

is estimated to eliminate roughly 40-50% of the VOC emission reductions of the

reformulated gasoline program (as discussed below in Section G.). This is a

large environmental cost, particularly since it is possible that ethanol

market shares of 30% may occur without such provisions. Furthermore, comments

submitted by the Department of Energy indicate that there in fact would be no

energy or crude oil benefits under an ethanol incentive program as proposed by

EPA.19 The marginal net energy benefit of producing ethanol from corn using

the current processes is offset by the increased energy consumption at the

refinery to offset the RVP increase resulting from the use of ethanol. This

belief that there are no energy benefits was echoed by various other

commenters based on their own refinery modeling. Given the potential lack of

energy benefits, and the dramatic environmental impacts of either a waiver as

discussed above, or the special incentives in the February 26, 1993 proposal

as discussed below, EPA does not believe that the reformulated gasoline

rulemaking is the appropriate program by which benefits to the country such as

those described in the comments should be obtained. 

A. Feasibility of Renewable Oxygenate Proposal

In the February 26, 1993 proposal, EPA proposed an incentive program to

encourage the use of renewable oxygenates in reformulated gasoline. This

program, in keeping with the October 1, 1992 announcement by former President

Bush, essentially provided an RVP incentive of 0.3 psi RVP in a refiner's

performance standard for the use of 30% renewable oxygenates in his RFG. The

VOC emission increase resulting from the ethanol and other renewable oxygenate

blends would be offset by a reduction in the emissions from non-ethanol

blends. In order to provide additional incentive for a refiner to actually

use the renewable oxygenate, however, EPA proposed that refiners would forfeit

the ability to obtain the RVP incentive to their competitors if they did not

commit to use the renewable oxygenate. Without such an added incentive EPA

feared some refiners might decline to use the renewable oxygenate and instead

opt for the performance standard 0.3 psi more stringent. EPA also proposed

various tracking and recordkeeping provisions to ensure that the program

resulted in the required RVP control (and VOC control under the complex model)

in all areas covered by the reformulated gasoline program.

A large majority of comments from parties on both sides of the ethanol

issue claimed that EPA's proposal was unworkable and too intrusive to permit

efficient market operation. Ethanol producers and blenders and agriculture

interests argued that the program was so burdensome and complex and the

limitation on the ethanol market share which received the incentive so

restrictive that any incentive the program was designed to create was
22

effectively eliminated. Instead they argued for an outright waiver from the

RVP requirement as discussed above.

Similarly, the oil industry argued that the fuel tracking and

recordkeeping requirements on each batch of fuel were not feasible, especially

given the short lead time between now and the programs initiation in 1995 to

satisfy the proposals new tankage and distribution requirements. The

increased complexity in production, transportation, distribution, and

enforcement of the program would dramatically increase the cost of the

reformulated gasoline program to the consumer. Such a cost increase was not

justified given the small, or even negative energy benefits of the program (as

discussed above), and the negative environmental impact of the program (as

discussed below). Both the oil and non-ethanol oxygenate industries argued

that ethanol and its derivative ethers would already represent a considerable

portion of the RFG market and did not need any additional subsidies. 

Providing incentives for ethanol and its derivative ethers would place other

competing oxygenates at a considerable economic disadvantage with a resulting

economic impact on the industries which currently produce these oxygenates. 

They argued that any additional incentives or federal subsidies for ethanol

should be considered in forums other than the RFG rulemaking, as section

211(k) did not authorize EPA to provide such a incentive for ethanol use. 

EPA acknowledges the burden caused by the additional fuel tracking,

recordkeeping, and enforcement provisions of the February 26, 1993 proposal. 

While EPA believes that the program's design provides a large economic

incentive for the use of renewable oxygenates such as ethanol in reformulated

gasoline relative to other oxygenates (refer to Section VIII. of the Draft

Regulatory Impact Analysis), EPA also acknowledges the considerable increase

in cost for fuel production, transportation, distribution, and enforcement

which resulted from such an intrusion into the marketplace which may offset

much or all of this incentive. Given the significant increase in the cost and

burden to the regulated industry, the various questions raised in regard to

its workability and impact, the lack of any energy benefits (as discussed in

section E.), and the significant environmental loss (as discussed in section

G.), EPA does not believe it to be appropriate, in light of the provisions of

section 211(k), to adopt the renewable oxygenate program proposed in February,

1993. The lack of support from the ethanol industry for this proposal further

indicates that adoption of this proposal would not be appropriate.

In response to the criticisms of the proposal, EPA investigated a number

of options aimed at making the program more workable by reducing the fuel

tracking, recordkeeping, and enforcement burden associated with the proposal. 

While such options tended to make the program more workable from the

standpoint of the refining and fuel distribution processes, they also tended

to either reduce the assurance that the environmental benefits of the program

would be achieved in all areas covered by the RFG program, or to place

additional restrictions on the RVP and emission performance of the ethanol

blends (thereby reducing the certainty that ethanol would actually be used). 

Furthermore, they did little to address the environmental concerns discussed

in Section G. Given this and the other concerns with the proposal (cost, lack

of energy benefits, significant environmental loss, etc.), EPA did not believe

these options to be appropriate for promulgation either.

A number of comments were received concerning the justification and

rationale for various detailed provisions of the renewable oxygenate incentive

proposal (e.g., the percent of ethanol in the fuel needed to receive the RVP

incentive). Given the fact that we are not promulgating the proposal, EPA

does not believe there to be any reason to evaluate the relative merits of

these provisions.
 20 Refer to footnotes 5 and 6

 21 "Running Loss Emissions From Gasoline Fueled Motor

Vehicles," C.E. Lindhjem and D. Korotney, U.S. EPA, SAE Paper

No.

931991, October, 1993.

 22 "Fuel-Alcohol Permeation Rates of Flouroelastomers,

Fluoroplastics, and other Fuel Resistant Materials," W.M. Stahl

and R.D. Stevens, E.I. du Pont de Nemours and Co., Inc., SAE

Paper No. 920163, February, 1992.

23

A. Emission Impacts of the Renewable Oxygenate Proposal

As discussed above, granting ethanol a 1.0 psi waiver from the

reformulated gasoline requirements would result in a significant loss (if not

a total loss) in the environmental control of the reformulated gasoline

program. EPA also received a number of comments that there are significant

negative environmental impacts from providing incentives for ethanol use as

under the February 26, 1993 proposal. Despite EPA's best efforts to propose

an environmentally neutral incentive program for renewable oxygenates, VOC

emissions would be expected to rise under the program for four main reasons;

fuel commingling, distillation effects, unrestricted early use of the complex

model, and greater permeation of oxygenates through non-metal fuel lines and

hoses. Appendix I.D. contains EPA's analysis of the ethanol commingling

effect. References located in the docket20 discuss its impact on VOC

emissions. EPA's analysis of the distillation effects are discussed in detail

in a recent paper published in the technical literature21, and again, the

references cited above discuss its impact on VOC emissions. The emission

impact of unrestricted early use of the complex model is discussed below. EPA

has not had an opportunity to evaluate the effects of oxygenates on fuel line

and fuel tank permeation, but the reader is referred to SAE paper number

920163 suggesting dramatic increases in permeation emissions with oxygenates,

particularly alcohols.22

9. VOC Emission Increase Estimate

Assuming a 30% market share for ethanol in reformulated gasoline during

the summer months, the commingling effect is estimated to result in roughly a

2-2.5% increase in fleetwide (6-8% if applied to ethanol market share only)

gasoline vehicle VOC emissions (for an assumed 0.15-0.20 psi increase in inuse RVP), the distillation effect a 3% increase in gasoline vehicle emissions

(relative to CAA baseline gasoline), and unrestricted early use of the complex

model a 1-2% increase, for a total increase of 6-7.5% relative to a scenario

with no gasoline reformulated with ethanol. This represents a loss of 40-50%

of the VOC emission control required under section 211(k). EPA is in the

process of collecting additional data and information which will enable a

better analysis of the distillation effect, but does not expect the current

emission effect estimate to change appreciably once the new data is

incorporated due to the scientific theory which supports the effect. 

Inclusion of fuel tank and fuel line permeation, however, would be expected to

further increase the estimate.

Comments were received suggesting EPA take into consideration additional

effects on emissions when analyzing the in-use impact of ethanol blends such

as fuel weathering and enrichment of the air fuel ratio when vehicles

accelerate above and beyond that which occurs during EPA's certification test
 23 Refer to footnotes 5 and 6

24

procedure. Fuel weathering is already contained in the MOBILE model and as

such already reflected in EPA's evaporative emission estimates, including the

estimates of emission increases resulting from commingling. The emission

differences between EPA's certification test procedure and those which occur

during in-use driving, often referred to as off-cycle emissions, is currently

the focus of a great deal of study. However, there is not adequate data and

information available at the present time to approximate with any confidence

the magnitude of such emission effects.23 In addition, enrichment of exhaust

emissions during acceleration is only one of the off-cycle emission impacts

currently being evaluated. It is possible that off-cycle vehicle driving

patterns will have just as large of an effect on non-exhaust emissions as

exhaust emissions. Due to the lack of data, however, EPA is not able at this

time to determine whether such off-cycle emissions improve or exacerbate the

emission impacts of ethanol blends described above.

10. Unrestricted Early Use of CM

EPA proposed three different options for early use of the complex model,

that is, optional use of the complex model before its use became mandatory. 

The first option would require that the reformulated gasoline achieve VOC,

toxics, and NOx performance that was no worse than the complex model would

achieve for a simple model fuel using that refiner's 1990 baseline for sulfur,

T-90 (E300), and olefins. This was designed to ensure that early use of the

complex model would not upset the expected emissions benefits in the early

years of the reformulated gasoline program. For example, if a refiner could

optionally use the complex model and measure performance against the CAA

baseline, then those refiners with individual baselines that were more

stringent than the CAA baseline (for example, lower sulfur levels) could be

expected to use the complex model early and take credit for their lower sulfur

levels. However, those refiners who had baselines that were less than the CAA

baseline, for example with sulfur levels higher than the CAA baseline, would

be expected to use the simple model as use of the complex model would require

that they offset the emissions impact of higher sulfur levels. Unrestricted

early use of the complex model might in effect unbalance the emissions balance

imposed under the simple model which established refiner-specific caps on

sulfur, T-90, and olefins. EPA discussed the pros and cons of this option in

the April 1992 proposal.

EPA also proposed a second option in the April 1992 proposal, where

refiners could use the complex model early for fuel distributed to VOC control

region 1 (southern areas of the Country), and measure performance against the

CAA baseline and not their individual baselines. To limit interference with

the enforcement scenario proposed by EPA, a cap would be placed on maximum RVP

levels.

A third option for early use of complex model was proposed in February

1993 as part of the incentive program for ethanol blends. Under this option,

performance under the complex model would be measured using either the CAA

baseline or the refiners' 1990 baseline, at their option. This was described

as providing the maximum flexibility for refiners, and, therefore, the maximum

incentive for ethanol use. However, EPA was still concerned this would lead

to a reduction in the emissions benefits expected from the simple model.

Unfortunately, it is difficult to assess with any precision the

environmental impact that would result from unrestricted early use of the

complex model. EPA does not have any information at the present time to

estimate the number of refiners that would opt for early use of the complex

model, nor does EPA have any information on the number of refiners with 1990

baseline levels of sulfur, T90, and/or olefins below the CAA baseline levels,
25

or what the levels of these parameters are for these refiners. As shown in

Table I-2, if refiners had low levels of sulfur, T90 (high E300), and/or

olefins, they would achieve substantially lower emissions reductions than

required by the simple model. Assuming a normal distribution about the CAA

baseline 7/8 of all refiners would have a low baseline of one or more of

sulfur, T90, and olefins. Given these estimates, and the incentive for low

baseline refiners to opt for early use of the complex model relative to the

CAA baseline gasoline, it would not seem unreasonable to conclude that the

proposal to allow such an option would sacrifice 1-2 percentage points of the

VOC emission reductions expected under the simple model.

Table I-2 Emission Impacts of Unrestricted Complex Model Use

Fuel

Parameter

CAA

Baseline

Level

Refiner

A

Refiner

B

Refiner

C

Refiner

D

Sulfur (ppm) 339 150 339 339 150

E300 (%) 83 83 92 83 92

Olefins

(vol%)

9.2 9.2 9.2 3.0 3.0

VOC %Change

From

Baseline*

N/A -1.6 -1.4 -0.7 -2.3

NOx Change

From

Baseline*

N/A -5.4 +0.8 -0.5 -5.2

* Based on the Phase I Complex Model

A. Reg Neg

A number of comments were received suggesting that the renewable

oxygenate provisions of the February 26, 1993 proposal violated the agreement

reached through regulatory negotiation. As a result, these comments suggested

that if EPA were to promulgate the provisions, EPA would face numerous

lawsuits. While EPA shares the desire of the commenters to maintain the

provisions reached through negotiation, it must be made clear that the

negotiated agreement is not in and of itself legally binding. EPA's final

rule must be based on the authority provided by the Act. The regulatory

negotiation process is intended to develop a consensus among the affected

parties on how the Act should be interpreted and implemented. To EPA's

knowledge, there was no consensus reached during the negotiation on any

special provisions or waivers for ethanol blends. Only if a deviation from

the negotiated agreement, such as the renewable oxygenate provisions, also

resulted in a deviation from EPA's legal authority under the Act, however,

would EPA be at risk in any ensuing litigation.
26

A. Appendices

Appendix I.A. Ethanol Sales in 1990

The following table shows and analysis of the ethanol sales in 1990 in

those areas currently covered by the reformulated gasoline program. The

gasohol sales data on a state by state basis were obtained from the 1992

National Petroleum News Factbook. Sales data for each covered area was

obtained by ratioing the gasohol sales in the state by the proportion of the

state population represented by the covered area based upon 1990 census data. 

This same population weighting is what EPA used to obtain the percent of

national gasoline consumption in each covered area.
27

Insert ethanol sales table here
 24ETBE like MTBE can be added at the refinery. While it

shows promise for the future, ETBE has not been widely used in

the market to date. Ethanol blends cannot travel through

petroleum pipelines and thus ethanol is blended at the

distribution terminal.

28

Appendix I.B. Relative Economics of Oxygenates in RFG

Historically, oxygenates (primarily ethanol) have been used as fuel

extenders or more recently as octane enhancers. With the advent of the

oxygenated fuels program to control wintertime carbon monoxide emissions and

the reformulated gasoline program to control summer ozone, oxygenates now have

value for other purposes, as well.

First, the addition of an oxygenate to gasoline impacts the Reid vapor

pressure (RVP) of the blend. Since Phase I reformulated gasoline (RFG) has

restrictions on RVP, and Phase II RFG requires significant reductions in VOC

emissions that will likely require further reductions in RVP, the impact of

oxygenates on the RVP of the blend is an important factor to consider.

Second, oxygenates are high in octane, and thus enhance the octane of

the finished gasoline. Since other means of providing octane, such as the

addition of aromatics, are costly and often have negative consequences for

emissions, oxygenates are valuable for their role as octane enhancers.

Finally, in the context of an oxygen content requirement such as exists

in the RFG requirement for 2.1 wt% oxygen (on average), oxygenates are valued

for their oxygen content.

The relative costs of three major oxygenates, ethanol, MTBE, and ETBE,

have been compared based on their purchase prices and their values as fuel

extenders, RVP modifiers, octane enhancers, and oxygen sources. Since MTBE is

believed to be the oxygenate likely to be used in reformulated gasoline in the

largest volumes (given the current market conditions), the costs of ETBE and

ethanol have been compared relative to the cost of MTBE.24

 The purchase price of the oxygenates was determined from the spot market

prices or reasonable assumptions about their costs. The price of MTBE was

estimated to be $0.70 per gallon, based on the recent (1993) spot prices

reported in trade press publications such as Octane Week and Oxy-Fuel News. 

The price of ethanol was assumed to be $1.20 per gallon, the typical price

over much of 1993. (See below for further discussion of the price of

ethanol.) The purchase price of ETBE ($1.01/gallon) was estimated from the

price of MTBE, assuming ethanol is purchased at $1.20 per gallon and the

capital and operating costs for ETBE production are slightly higher (5% and

10%, respectively) than for MTBE since somewhat large equipment is necessary

to process the same volume of isobutylene into ETBE. The cost per gallon of

isobutylene was assumed to be equivalent for both ethers.

The value of the oxygenates as a fuel extender was based on the recent

spot market price of unleaded regular gasoline at the U.S. gulf coast (around

$0.50/gallon). Since the analysis was performed on the basis of the relative

cost per gallon of each oxygenate, the oxygenates have equivalent values as

fuel extenders and thus the magnitude of the value assumed for the gasoline

displaced is unimportant.

The values of the oxygenates as octane enhancers, oxygen additives, and

RVP modifiers were estimated based on market trends and on the results of the

refinery modelling used to develop costs for Phase II RFG. It was assumed
29

that the oxygenates were worth $0.006 per octane number added per gallon of

blend produced. All of the oxygenates have octane ratings higher than the

base gasoline, so all have a value as octane enhancers. The value of the

oxygen provided was assumed to be $0.003 per weight percent oxygen added per

gallon of blend produced. Since ethanol has the highest oxygen content per

gallon, it has the highest value as a source of oxygen. The cost of reducing

the RVP of the blendstock (to maintain a constant RVP in the final blend) was

estimated for this analysis to be $0.005 per psi per gallon of blend produced. 

(Recent refinery modeling, however, suggests that in some cases the cost of

RVP control could be considerably less expensive.) Ethanol has a higher RVP

than gasoline, so ethanol incurs a cost because the RVP of the blendstock must

be lowered. The ethers have lower RVPs than gasoline and thus are valuable

because the RVP of the blendstock does not have to be reduced to accommodate

these oxygenates.

Ethanol is eligible for a $0.54/gallon tax credit which adds to its

value. In this analysis, it was assumed that ethanol used in ETBE was

similarly eligible for this tax credit. Ethanol is also eligible for

additional tax credits and other forms of economic support as high as

$0.50/gallon of ethanol in a number of States. These credits have not been

factored into this analysis.

Table 1 presents the comparison of the oxygenates. As the table shows,

ethanol costs less and ETBE costs more than MTBE for use as a gasoline

oxygenate. When expressed on a cost per gallon of finished gasoline basis,

the ethanol has a small advantage over MTBE of around 0.4 cents per gallon

gasoline. ETBE, however, is slightly more costly than MTBE, adding an

additional 0.8 cents per gallon gasoline. Distribution costs have not been

included in this analysis. Since ethanol cannot be shipped through pipelines,

it tends to incur greater distribution costs if shipped over long distances. 

Distribution costs will vary significantly depending on the locations

involved, but for many of the RFG areas the incremental cost for distribution

of ethanol should be less than 5 cents/gallon of ethanol. ETBE, however, is

likely to be produced in the Gulf, while the ethanol is largely produced in

the Midwest. Therefore, ETBE will also incur an additional cost for the

distribution of the ethanol to the Gulf, which could reach about $0.01 per

gallon of ETBE produced.

Table 1: Costs of Oxygenates at 2.1 wt% Oxygen ($/gal oxygenate)

Ethanol Price: $1.20/gallon

Ethanol ETBE MTBE

Purchase Price 1.20 1.01 0.70

Fuel Extender Value -0.50 -0.50 -0.50

RVP Modifier Value 0.050 -0.020 0.001

Octane Enhancer Value -0.160 -0.148 -0.141

Oxygen Value -0.108 -0.049 -0.056

Blender's Tax Credit* -0.54 -0.23 0.00

Total Cost ($/gal oxygenate) -0.06 0.06 0.00

Total Cost ($/gal RFG) -0.004 0.008 0.000

* Federal credit only, individual state credits have not been included in

this analysis
30

Recently, the price of ethanol has decreased as the oxy-fuels season

started and refiners found that there was sufficient oxygenate supply. The

price reported for the October-November timeframe has been around $1.05 per

gallon. If this price is assumed for ethanol, the relative values ethanol and

ETBE as oxygenates compared to MTBE change somewhat, as shown in Table 2. At

the lower purchase price, combined with the tax credit, ethanol costs $0.01

less per gallon of gasoline than MTBE. ETBE costs the same as MTBE on this

basis.

Table 2: Costs of Oxygenates at 2.1 wt% Oxygen ($/gal oxygenate)

Ethanol Price: $1.05/gallon

Ethanol ETBE MTBE

Purchase Price 1.05 0.94 0.70

Fuel Extender Value -0.50 -0.50 -0.50

RVP Modifier Value 0.050 -0.020 0.001

Octane Enhancer Value -0.160 -0.148 -0.141

Oxygen Value -0.108 -0.049 -0.056

Blender's Tax Credit* -0.54 -0.23 0.00

Total Cost ($/gal oxygenate) -0.21 0.00 0.00

Total Cost ($/gal RFG) -0.013 0.000 0.000

* Federal credit only, individual state credits have not been included in

this analysis
31

Appendix I.C. Critique of the Draft Final Report: "Comparison of the Air

Quality Effects of Ethanol and MTBE in Reformulated Gasoline

in the New York Region in 1995," for National Corn Growers

Association, by Gary Z. Whitten, Systems Applications

International, August 18, 1992.

General Overview of Comments:

As discussed in the August 6, 1992 letter to Eric Vaughn shown in

Appendix I.C., EPA has serious reservations with respect to the ability of the

UAM to adequately evaluate the relative ozone impacts of oxygenated blends in

the New York airshed. Past experience with New York indicate that transport

of pollutants into the airshed dominates the result and makes establishment of

appropriate initial and boundary conditions extremely difficult. As a result,

we recommended that some other city be modeled instead where transport was not

such an overwhelming issue. Instead, SAI proposed a new approach of adjusting

the initial and boundary conditions based on the results from the first day. 

It was agreed, however, that external peer review of this method would be

obtained by a panel of recognized experts in the field. It was also agreed

that a number of sensitivity analyses would be performed to allow evaluation

of the study's results. These agreements were not fulfilled. The results

cited in the introduction and conclusion sections of the final draft report

contained in the docket to this rulemaking are not based upon any runs for

which the transport issue was addressed. Furthermore, while a sensitivity

analysis was performed using an approach for dealing with transport, peer

review of the method was not obtained, nor was enough information provided in

the draft final report by which EPA could evaluate the approach. As a result,

EPA has no choice other than to maintain our position expressed in the August

6, 1992 letter to Eric Vaughn that the results from the modeling of New York

are not valid.

Furthermore, our preliminary review of the report provided suggests that

even if the transport issue were adequately addressed, the inappropriate

assumptions made in the protocol would invalidate the results. Other than

using UAM-IV instead of UAM-V and including the specific air chemistry for

ethanol and MTBE, the protocol for New York is virtually identical to the

protocol used in the Chicago study. As a result, most of the comments and

criticisms of that study contained in Appendix I.B also apply to this study. 

Comments specific to the New York study are discussed below. As with the

previous Chicago study, however, the documentation which was provided for both

the protocol and the final results does not allow for a thorough evaluation of

the appropriateness of the study or usefulness of its results. 

The EKMA modeling which was performed for 14 cities also appears to be

of limited usefulness as discussed in the comments below.

Detailed Comments on the New York UAM:

1) Model Validation

 It is necessary to show that the model is adequately predicting

historical ambient ozone (and other pollutant) levels for the ozone

episode being modeled. There was no discussion of this. Presumably

since the same model and episode were used by AQIRP, it has been

validated, but it is not known if the same initial and background

assumptions were used.

 The modeling, with the exception of some sensitivity runs (which were

downplayed and ignored in the final conclusions) apparently did not

address the impact of transport on the initial and boundary conditions.
32

 In the sensitivity runs that were performed, the method of adjusting the

boundary conditions for transport was not adequately explained. While

it may be directionally better than making no adjustment, based on the

limited explanation in the final report, the method used appeared to be

of little merit. It used the effects of ethanol on the inventory 55 km

downwind from New York to adjust the boundary conditions since New York

is 55 km downwind from Philadelphia. As a result, it appears to ignore

the impacts of Newark, Jersey City, Baltimore, Washington D.C., Trenton,

etc. It is also unclear how well it represents the upwind effects of

Philadelphia since no explanation was given as to what the time period

was over which the emission effects of ethanol were evaluated in order

to adjust the initial and boundary conditions. The difference would be

dramatic between evening, early morning, or afternoon emission effects. 

Furthermore, as in the Chicago study, the primary compounds of interest

in this study (ethanol and MTBE) were substituted with similar CBM-IV

species in the air chemistry for the boundary conditions.

2) Episode Selected

 The maximum temperature, diurnal temperature swing, and any other

relevant episode information were not provided. Without such

information it is difficult to evaluate the results.

 There was no explanation provided for the assumptions made for the

initial and boundary conditions (other than the adjustments made for the

sensitivity runs).

3) Selection of 1995 as the Future Study Year

 The ozone impact of ethanol and MTBE blends in the year 1995 was

evaluated. The ozone impact of ethanol in particular, is the sum of a

number of impacts, some positive and some negative. One of the positive

impacts is the likelihood that ethanol provides additional exhaust VOC

and CO emissions beyond that provided by 11 volume percent MTBE. 

However, these benefits are greater for older vehicles than for recent

model year vehicles. Likewise, the evaporative emission detriments of

ethanol are greater for vehicles not designed to meet EPA's upcoming

enhanced evaporative and running loss emission control.

The choice of 1995 as the focus of the study (the earliest possible year

to evaluate reformulated gasoline) maximizes the exhaust emission

benefits of ethanol. However, assuming the same assumptions were made

for New York as for Chicago, unrealistic and insupportable assumptions

were made concerning the implementation of new vehicle evaporative

emission controls in 1995.

Since the decision to grant or not to grant ethanol a 1.0 psi waiver

will affect reformulated gasoline well into the next century, evaluating

the impact only in 1995 is unacceptable. At minimum, evaluations should

be performed in 2000 and 2005, as well.

4) Inventory

 The final report gives no detail of the control assumptions for area and

point sources assumed for 1995. If as in the Chicago study, no controls

were assumed for these sources despite the application of stringent

mobile source controls, and rapid growth was instead assumed, the

relative importance to ozone levels of the increases in mobile source

emissions resulting from the use of ethanol blends is underestimated.

 As confirmed in subsequent conversations and discussions since the time

of the previous Chicago study's release, the MOBILE model used in SAI's
33

work was not EPA's MOBILE4.1 model, but a version of MOBILE4.0 modified

by SAI and/or DOE. The impact of this on the results of the UAM,

however, may be small based on the analysis performed by SAI in a

September 10 memorandum from JGH to Dr. Whitten. The original MOBILE

model used by SAI with assumptions of enhanced I/M and a new evaporative

test procedure and Tier I controls gave similar results as using the

actual MOBILE4.1 model with corrected I/M assumptions, no new

evaporative test procedure assumptions, and Tier I controls. The

MOBILE4.1 results, however, do not appear to be consistent with the

actual inventories used. Apparently there are other assumptions made in

developing the inventories from the MOBILE model outputs that change the

relative contribution of the various pollutants and emission types. 

Until EPA is provided with such information we cannot ascertain the

validity of the mobile source inventory.

 Use of the same evaporative test procedure assumption as in the Chicago

study is just as inappropriate in the New York study (if in fact the

same assumption was made). Either 1998 or a later year should have been

modeled (decreasing the exhaust emission benefit of the ethanol blend),

or no evaporative emission reduction should have been claimed for 1995

due to the new test procedure.

 If the same assumption was made here as in the Chicago study, the

inspection and maintenance program assumptions are unrealistic. Not

only are these assumptions inconsistent with the proposed I/M rule, but

they also provide an effectiveness which can not be achieved in-use. 

Full effectiveness is not likely for a few years after the start of the

program which is currently scheduled for the beginning of 1995. Once

again, either 1998 or a later year should be modeled, or reduced

benefits claimed in 1995.

 Presumably, the same assumptions were used for the exhaust VOC emission

benefits for the oxygenated blends as in the Chicago study. As

discussed in the comments on the Chicago study, the assumption for

ethanol is too high relative to that for MTBE, especially considering

the I/M scenario assumed in the study. At a meeting in Ann Arbor on

9/11/92, apparently Dr. Whitten agreed with EPA's assessment of the

oxygenate effects as he raised no objection to EPA's assumptions. As a

result, SAI overstates the exhaust VOC benefit of ethanol blends in the

inventory. This is particularly important since much of the air quality

benefit given to ethanol to offset the evaporative and running loss

emission increases was in the form of exhaust VOC emissions.

 The fuel assumption of ethanol at 3.5 wt% oxygen and MTBE at 2.0 wt%

oxygen is not valid for a reformulated gasoline scenario. The oxygen

averaging provisions under the reformulated gasoline program will limit

the maximum average oxygen content in the fuel to 2.1 wt% oxygen. When

combined with the minimum oxygen content requirement for 1.5 wt% oxygen,

if ethanol is used at 3.5 wt% oxygen, it will only be used in 30% of the

fuel, with the remainder of the fuel containing ethanol or some other

oxygenate at 1.5 wt% oxygen. If the study is to have any relevance to

the reformulated gasoline rulemaking as it purports, then both the

ethanol and MTBE scenarios should have the same overall oxygen content. 

This will essentially eliminate the exhaust VOC and CO emission credits

applied to ethanol in the study, and greatly increase the ozone

estimates for the ethanol scenario relative to the MTBE scenario.

 Presumably the non-road inventory was based upon EPA's non-road study. 

However, there is no explanation of this. Furthermore, there is no

explanation made for the temporal, spacial, and growth assumptions made

for non-road emissions.
34

 Presumably the non-road inventory in Table 1 is only the gasoline

portion of the non-road inventory. However, it is not possible to know

this from the information provided. Neither the non-road or the diesel

related inventory is broken down into its constituent pieces allowing

for any clarification.

 One glaring error in the New York study which benefits ethanol

tremendously is that it was assumed that there were no evaporative or

running loss emissions from non-road vehicles. Since non-road vehicles

and engines do not have any evaporative emission control systems, the

non-road evaporative VOC inventory should be significant. As a result,

SAI provides a very large exhaust VOC credit to ethanol relative to MTBE

(roughly half that of the exhaust credit from on-road vehicles) and

ignores completely the evaporative emission increases with ethanol

relative to MTBE. EPA acknowledges that there is a general lack of

information on the evaporative VOC emissions from non-road sources, and

we will be working to improve our understanding of their magnitude. 

However, to ignore them completely while including the exhaust inventory

when the fuel effect being evaluated has dramatically different effects

on exhaust and evaporative emissions is unconscionable. Either non-road

emissions should have been assumed constant for both scenarios, or some

sensitivity runs performed with reasonable assumptions made as to their

magnitude.

 For the effect of oxygenates on non-road exhaust emissions, SAI used

data from Southwest Research Institute on one 4-stroke engine and one 2-

stroke engine. This test data may be of some use for demonstrating

certain trends, but is hardly adequate to quantify the effect of

oxygenates on exhaust emissions from non-road vehicles. The fuels used

in the testing are not representative of in-use fuels, and the two

engines are not representative of the wide variety of non-road emission

sources. As a result, there should be no distinction made between the

MTBE and ethanol fuels for the effect of oxygenates on non-road emission

sources in this study. The results of the study may be too sensitive to

any assumptions made for non-road, which cannot be substantiated.

 Why is there only a 9.8% increase in refueling emissions for LDVs with

ethanol, and why is it different for MDVs and HDVs? Based on the vapor

pressures of the fuels in question, there should be roughly a 12-13%

increase. 

 If the same assumption was made here as in the Chicago study, Stage II

refueling controls were assumed by SAI to reach full benefit by 1993,

but probably will not be in effect until 1995 and will not reach full

effectiveness for several years. Once again, either 1998 or a later

year should have been modeled, or reduced benefits claimed in 1995. 

 Based on the protocol, the same data, information, and assumptions were

supposedly made in the New York study as in the Chicago study regarding

the impact of ethanol and MTBE on VOC, CO, and NOx emissions. This held

true in the New York inventory for CO emissions. The percent changes in

CO emissions from MTBE to ethanol in the inventory were exactly the same

as in the Chicago study. However, the percent changes for VOC and NOx

were different. Exhaust VOC emissions decreased with ethanol by smaller

percentages, NOx emissions increased by smaller percentages (except for

HDVs which now showed a decrease in NOx instead of an increase), running

loss emissions increased by smaller percentages, and evaporative

emissions increased by slightly larger percentages. What is the

justification and rationale for these changes? Temperature conditions

were likely different prompting different evaporative and running loss

emission changes, but the changes should have been in the same

direction. Furthermore, given that the changes in CO were the same,
35

they should have been for exhaust VOC and NOx as well. There especially

does not appear to be any justification for why NOx was now assumed to

decrease with ethanol for heavy-duty vehicles.

 The study assumes 100% replacement of gasoline with gasohol under the

ethanol scenario. This is unrealistically high and results in the

commingling effects of ethanol on in-use RVP being ignored.

 Presumably SAI made the same faulty VMT and ambient temperature

adjustments to the running loss emissions that were made in the Chicago

study. The VMT adjustment shifts more emissions to the morning hours

than is appropriate based upon EPA information. The temperature

adjustment then zeros out most of these inflated morning running loss

emissions and forces the remaining running loss inventory to the end of

the day when there is not adequate time for it to react and contribute

to peak ozone. Emissions do not vary linearly with temperature so a

linear weighting of running loss emissions with ambient temperature does

not reflect the diurnal variability of running loss emissions. For

example, the methodology used assumes running loss emissions are zero at

the morning low temperature, eliminating virtually all running loss

emissions from the morning commute. While running loss emissions are

temperature dependent, all currently available data suggests that

significant running loss emissions occur even at morning low ambient

temperatures down to about 40

F. The effect of these VMT and

temperature assumptions together is to drastically reduce the impact of

running loss emissions on ozone formation. As a result, the largest

source of emission increases (running losses) in the inventory with

ethanol blends is virtually eliminated.

SAI could have very easily adjusted the running loss emission profile

for temperature in an appropriate manner by running the MOBILE model for

each hour of the ozone episode. In addition to being erroneous,

however, the adjustment made to running loss emissions based upon the

time of day is in and of itself biased in favor of ethanol. To make

adjustments only for running loss emissions without also making

adjustments for all other portions of the inventory is inappropriate.

 Another serious oversight in the study is that while fuel effects on

refueling emissions were taken into account, for some reason the fuel

effects on storage emissions which represent a three times larger

portion of the inventory were ignored. The effect of this is to ignore

some of the adverse effects of volatility increases with the ethanol

blend.

 The methodology used to develop the emission inventories (and speciation

profiles) for medium and heavy-duty vehicles was not explained in the

protocol. Based on follow up discussions, these inventories were based

on crude extrapolations of light-duty vehicle data which are not

supportable. The overall effect on the results of these assumptions is

unknown, but it does raise additional uncertainty as to the validity of

the study's results.

5) Speciation

 Refer to comments in Appendix I.B. on the Chicago study. Apparently the

same speciation profiles were assumed for both studies. As for that

study, EPA cannot agree with the profiles developed and recommends the

use of our own speciation profiles.

 Formaldehyde and acetaldehyde emission increases with ethanol are

ignored, while the formaldehyde and isobutylene increases with MTBE are

not. This is inappropriate.
36

 Using EPA default species for non-road is inappropriate since they are

based on light-duty vehicle data. The SwRI report from which the

oxygenate effects data was taken suggests that 2-stroke exhaust is

predominantly unburned fuel, and that 4-stroke exhaust resembles that of

conventional gasoline engines. If your assumption is true that 70% of

non-road exhaust is 2-stroke, then the speciation profiles should

approximate those of the raw fuel.

 The CO reactivity in a 1988 SAI study was assumed to be 71% greater than

that of ethane. The Carter reactivity for CO is 1/5th that of ethane. 

What was used in these studies? It could have a significant impact on

the results.

 

6) Results

 Results discussion ignores first day results. New York gets blown

through in a day. As a result first day results are just as valid as

second day. Much higher - why?

 The results are difficult to interpret since isoline results for the

ethanol blend scenario and no gasoline mobile source scenario were not

provided separately.

 The adjustment for transport in the sensitivity runs resulted in ozone

increases. These were ignored and downplayed in the discussion of the

results.

 As in the Chicago study, the results discussion still focussed only on

the peak ozone and not the larger and geographically dispersed ozone

increases.

 The sensitivity of ozone to VOC emission increases from ethanol were

more appropriate than in the Chicago study, but still lower than for

other studies - including the SAI/AQIRP study of New York. Since New

York was the least sensitive city in the AQIRP work, larger increases in

ozone would be expected in other cities.

Detailed Comments on the EKMA Modeling of 14 cities

 Mobile emission inventories for the cities were based on the New York

UAM inventory and were not specific to the different cities. Not

specific for temperatures or RVPs, etc. As a result, they were not

appropriate.

 As discussed above and in the comments on the Chicago UAM study, the New

York inventory has numerous inaccuracies and is based on many

unrealistic assumptions. As a result, the inventories used for the EKMA

modeling are also invalid.

 The baseline gasoline inventory was arbitrarily assumed to be MTBE

blended gasoline.

 Again, default chemistry is used for the many different VOC compounds,

and not the specific chemistry for the compounds being evaluated in the

study.

 No explanation is given why for Philadelphia and San Diego the EPA

inputs could not be used, and instead why the precursor ratios had to be

raised and the default chemistry replaced with an "updated version". 
37

Given the results for these two cities showed that removing all mobile

source emission increased ozone, something appears to have gone awry.

 No explanation given for the city selection and its representativeness

to the nation or the RFG program.

 It is not possible from the results to say that in 4 cities "ethanol

reduces ozone compared to the MTBE base." The results for three of

those cities should have been thrown out since eliminating all mobile

source emissions increased ozone.

 The results showed a -0.7 to 4.1% increase in the mobile source

contribution to ozone with the use of ethanol (average of 1.75%). While

much smaller than predicted by other studies, this is nevertheless a

very significant increase, representing a large fraction of the ozone

benefits achieved by RFG.

 How can the 23.2% motor vehicle contribution to the VOC inventory in

Chicago be reconciled with the 5.1% assumed in the Chicago UAM study?
38

Appendix I.D. Commingling Effect of Ethanol

I. INTRODUCTION

Ethanol has a Reid Vapor Pressure (RVP) of 2.4 psi, and most gasolines

will have an RVP of 6.5 to 9.0 during the summer months. When ethanol is

mixed with the gasoline a non-linear increase in the RVP is observed. For

example, if gasoline with an original RVP of 8.0 is mixed with ethanol (10% by

volume) the resultant RVP is approximately 9.1. This RVP increase can be

offset at the refinery by using a lower RVP gasoline so when the two

substances are mixed together the desired final RVP can be achieved. However,

due to the non-linear nature of ethanol's blending RVP, the mixing of ethanol

blends with other non-ethanol containing gasolines downstream of the refinery

in vehicle fuel tanks can result in an additional vapor pressure increase

across the in-use pool of gasoline. This RVP increase caused by fuel mixing

is what is known as the commingling effect. This study will only address the

commingling effect in vehicle fuel tanks. Other effects outside of the

vehicle fuel tanks are assumed to be small due to fuel segregation through the

fuel distribution system. 

The commingling effect is not a simple matter to model for any

geographical area. Many factors must be taken into account in order to

accurately describe the overall consumer refueling behavior which is so

critical in establishing a viable commingling model. Such factors are the

refueling patterns of the consumers using the various gasoline blends, their

loyalties to various brands, the base RVP of the fuels used, the market share

of gasolines using ethanol as an additive, and whether the geographical area

in question is utilizing reformulated gasoline or not (due to the cosolvent

effects of other oxygenates). Such complexities and variables are extremely

difficult to account for using simple hand or spreadsheet calculations, thus a

computer program was developed to attempt to include as many of these

variables as possible in order to develop a more accurate estimate of the

commingling effects that ethanol as a gasoline additive has on in-use RVP. 
 25U.S. Environmental Protection Agency, Arco Oxinol Waiver

Request, 1981.

39

II. THE COMMINGLING MODEL

A. General Overview

The commingling model developed here simulates real world conditions by

performing 100 refueling events for each of 1000 vehicle owners, for a total

of 100,000 refueling events. The model utilizes brand loyalty curves and

refueling pattern curves in order to determine the quantity and type of fuel

for each refueling event. 

The model is flexible enough to be used for a number of different in-use

assumptions (a listing of the computer program is contained in the appendix). 

One of these is whether it is a reformulated gasoline scenario where the

ethanol blend is assumed to be mixed with a MTBE blend, or a conventional

gasoline scenario where the ethanol blend is mixed with pure gasoline. The

model, however, is not flexible enough to model a scenario where the ethanol

blend is mixed with both MTBE blended gasoline and conventional gasoline. 

Another in-use assumption of the model is that the base RVP is the same for

all blends. This means that the RVP of the gasoline that is initially mixed

with the pure ethanol is lower such that all gasoline blends have the same

RVP. Thus, the results from this commingling analysis are incremental to any

RVP increase that might result from RVP waivers for ethanol blends. A third

in-use assumption is that of the ethanol market share in the particular region

being modeled. 

Two other important variables in the model are the brand loyalty and the

consumer refueling pattern. Due to a degree of uncertainty in the available

for brand loyalty and consumer refueling data, the model was designed to allow

for a number of different assumptions. This was done in order to bracket the

range of possible in-use conditions. 

B. Brand Loyalty

Figures #1 - #3 represent the various forms of owner brand loyalty

curves that were derived for use in this computer model. Figure #1 defines

the customer loyalty to a particular brand of fuel based on data collected by

Arco. This data, submitted to EPA in 1981 as part of ARCO's oxinol waiver

request, only has a few points and indicated a great propensity towards

extremely high owner loyalty25. Of particular importance with this data is

the seemingly large percentage of customers that have 100% brand loyalty. The

Arco data appeared to be unrealistic because of this fact. Much of the

reasoning behind the apparent skewing of this graph towards high loyalty may

be in the manner that the data was collected. The questionnaire only made an

inquiry as to how many customers purchase the same brand of gasoline 75% to

100% of the time. Thus it is the sensitivity of the data collection procedure

that produced this high loyalty skew. One would expect there to be actually

very few customers who are 100% loyal to one brand (never use a different

brand of gasoline, even on long trips), however, this data serves well as an

upper bound for consumer brand loyalty. Two other curves were developed in an

attempt to exhibit consumer brand loyalty in a less dramatic measure.

Figure #2 shows these two other curves. The curve labeled "Curve #2" is

an attempt to retain the general trend of the Arco data yet adjust for the

concept that there would be a decrease in the percentage of owners with high

loyalties (80% to 100%) to a particular brand. Curve #3 shows an assumed

normal distribution of loyalty that assumes that most people in major urban
 26Zero loyalty assumes that customers have no preference at

all to the brand of fuel they purchase. Thus in these cases

there is a completely random determination of the fuel brand

being used with each fill-up of fuel.

 27NPD Group Inc., "Special Gasoline Analysis, Annual 1992

Data Prepared for: U.S. Environmental Protection Agency". 1993.

40

areas purchase fuel from a number (e.g. 2-6) different brands. As such, the

maximum percentage of the time that they purchase the brand they use most

often tends to be rather low. A fourth brand loyalty not shown in Figure #2

but permitted in the model assumes that the consumers all have zero

loyalty26. This assumption is on the opposite end of the spectrum as the Arco

data and serves as the lower end of the loyalty bracket.

Figure #3 shows each of these brand loyalty assumptions as a cumulative

percentage of the total. The Arco data (at the far right in Figure #3) shows

the greatest trend toward high levels of consumer loyalty, while the other

three curves show lesser degrees of loyalty.

EPA has recently obtained some additional brand loyalty data through

contract with the NPD Group that serves to support the assumptions of curve

#227. These results are shown in Table #1
 28The 95% to 100% loyalty indicates that even though

consumers may report 100% loyalty only one purchase of a

different brand per year is enough to drop that loyalty to

about 97% to 99%. Therefore, consumer response to "always use

one brand" may not indicate their actual buying patterns. The

other loyalties, 45% to 50%, and 25% to 30% represent an

assumed distribution among multiple brand purchases. These

ranges were purposely made slightly higher than a strict

division of 100% by the number of brands involved to account

for the likely preferential use of one brand out of the total

number of brands purchased. Without any further information on

the loyalty to one particular brand, when more than one brand

is purchased, it is difficult to establish unequivocally what

the actual brand loyalty should be in the multiple brand

purchase scenarios. 

41

Table #1 Brand Loyalty Data, Total U.S. Industry - NPD Group

Brand Grouping Percent Loyalty

Always use One Brand 37.8%

Use 2 or 3 Brands 51.2%

Use Many Different Brands 11.0%

 By assuming that the heading "Always use one brand" indicates an actual

consumer loyalty of 90% - 100%, the "Use 2 or 3 brands" indicates a loyalty of

40% - 60%, and the "Use many different brands" corresponds to an actual

loyalty of 20% to 40%, then an average consumer loyalty of this data can be

compared to that for the other brand loyalty curves.28 Using these

assumptions consumer loyalty for the NPD data is calculated to range from 57%

to 73% (ave is 65%). The average brand loyalties for each of the curve of

Figure #3 are: 75% for the Arco data, 64.5% for the adjusted Arco data (Curve

2) and 50% for the even distribution (Curve 3). Thus Curve #2 appears to

closely match the interpretation of the NPD data, and may be the best

representation of consumer brand loyalty available for this model. 

There is, however, no one loyalty curve that will fit all geographical

areas. One may expect large cities to have a lower overall owner loyalty

because of the large number of different brands available in close proximity

to one another. Conversely, rural areas should have a higher degree of

consumer loyalty, particularly if there is only one or two gasoline stations

available and thus only one or two brands.

 There are two assumptions made in this model that are concerned with

consumer loyalty. The first assumption is that the loyalty curves the model

uses are applicable only to a fuel brand and nota particular oxygenate. 

There was no data available on oxygenate loyalty of which EPA was aware. 

Another assumption of the model is that it does not allow for individual

loyalties for various grades of gasoline. Ethanol tends to be used more in

mid and premium grades of gasoline than in the regular grade. At this time

EPA can not speculate on what effect, if any, these assumptions may have on

the model results. As more information becomes available that sheds light on

these two points EPA may consider their applicability to this model.

C. Refueling Patterns
 29U.S. Environmental Protection Agency, "Draft Regulatory

Impact Analysis, Control of Gasoline Volatility and Evaporative

Hydrocarbon Emissions from New Motor Vehicles", July, 1987.

 30 In this computer program reformulated gasoline is

assumed to be oxygenated with MTBE. All properties of the

reformulated gasoline and the non-reformulated gasoline were

assumed to be identical except for the difference in RVP boost

responses when mixed with another fuel containing ethanol.

42

 Two curves can be chosen in the model in order to describe the fuel fill

patterns of each customer for each individual fill-up as a percentage of the

total tank capacity. The data of Figure #4 indicates the fuel fill level

prior to a fill-up. The bars labeled "Case 1 (Actual Data)" are taken from a

General Motors refueling survey of over 1100 refueling events29. This data

shows a relatively uneven distribution in some areas. The bars labeled "Case

2 (Assumed Fit)" are a smoothing of the GM data. This is an attempt to

eliminate some of the unevenness in the data that may have been caused by

anomalies in the method of reporting the fuel tank fill levels, particularly

at the 0.2 gallons in/tank capacity level on the graph. It is also important

to note that whatever the fuel fill scenario that is used for any particular

run the model will always assume an existing "heel" in the tank of 10 percent

of capacity. Thus, any numbers derived from this graph are assuming that the

tank capacity does not include the "heel". 

Figure #5 describes the possible levels of the tank after fill-up. This

particular graph is for the case where the initial amount in the tank before

refill was equal to zero (except for the "heel"). There are other fill

scenarios based on each possible pre-fill level of the tank (i.e. 0.1, 0.2,

etc.). All scenarios are based on the same basic information. In Figure #5

the bars labeled "Case #1 (Actual Data)" are again from the GM refueling

survey, while the bars labeled "Case #2 (Assumed Fit)" are a smoothing of

portions of this GM data (particularly at the 0.8, 0.9, and 1.0 fill levels). 

The reasoning behind this smoothing is that the original GM data had an

inordinate amount of data points representing a complete fill-up. EPA

believes that the incidences of actual total fill-up are less than this due to

the manner in which the data was collected. The general inaccuracy of most

gasoline fill level gauges, many of which read full even though the tank is

much less than full causes an over estimation of "full" reportings. EPA hopes

to obtain more substantive information to either support the present data or

provide for a more accurate representation of typical consumer fill up

patterns in the future.

D. Vapor Pressure Curves

In order to assess the RVP boost that will be experienced with the

mixing of an ethanol fuel with either a non-reformulated or a reformulated30

gasoline a series of tests were performed to measure the resultant RVP boost

at various levels of ethanol/gasoline in the case of non-reformulated gasoline

and ethanol/MTBE/gasoline in the case of reformulated gasoline. Tables #2 and

#3 show the percentage of concentration of the various constituents in the

tests for non-reformulated and reformulated gasoline, respectively. The tests

in Table #3 adjusted the ethanol and MTBE concentrations to simulate the

mixing that would be experienced in an actual reformulated gasoline scenario. 

The results of these tests were used to produce the vapor pressure curves for

use in the commingling model. Smoothed graphs of the resultant curves are

shown in Figure #6. 
 31 These particular tests were done using a base RVP of

8.4. It has been found that as the base RVPs become greater

there is a decrease in the RVP boost for the same percentage of

added ethanol and conversely at increasingly lower RVPs there

is an increase in the RVP boost greater than that observed in

Figure #6.

 32General Motors Corp., Letter to U.S. Environmental

Protection Agency, May 21, 1993.

43

 The RVP boost represented in Figure #6 is only applicable at the base

RVP that these particular tests were performed31. In order to determine the

RVP boost at different base RVPs a RVP adjustment factor was determined. This

factor is applied to the RVP boost in order to arrive at the final adjusted

RVP boost of the mixture. 

 The RVP adjustment factor was determined based on experiments performed

at General Motors in which ethanol was added to gasolines of varying RVP32. 

It was determined upon examination of the trends in this data that the RVP

boost changed roughly 0.05 psi for every 1.0 RVP increase or decrease in the

base RVP. The resultant straight line curve that was used in the commingling

model is shown in Figure #7.

Although, in actuality this 0.05 psi RVP adjustment factor is at best an

estimate based on available information, its influence is actually quite small

for the ranges of RVP that are generally being considered (RVP 7.0 - 9.0). 

Table #4 provides some of the numerical data provided by GM upon which this

0.05 psi RVP adjustment was based. 

Table #2 - Non-reformulated Gasoline Testing Chart 

Run 

Number

Percent of 10%

Ethanol Blend in

Total Mixture 

Percent of Base

Gasoline in Total

Mixture

Total Percent of

Ethanol*

 in

Mixture

1A 0.0 100.0 0.0

2A 2.5 97.5 0.25

3A 5.0 95.0 0.5

4A 7.5 92.5 0.75

5A 10.0 90.0 1.0

6A 15.0 85.0 1.5

7A 20.0 80.0 2.0

8A 25.0 75.0 2.5

9A 30.0 70.0 3.0

10A 40.0 60.0 4.0

11A 50.0 50.0 5.0

12A 60.0 40.0 6.0

13A 80.0 20.0 8.0

14A 100.0 0.0 10.0

 * Denatured without methanol
44

Table #3 - Reformulated Gasoline Testing Chart 

Run 

Number

Percent of 10%

Ethanol Blend in

Total Mixture 

Percent of 11%

MTBE Blend in

Total Mixture

Total Percent of

Ethanol*

 in

Mixture

Total Percent of

MTBE in Mixture

1B 0.0 100.0 0.0 11.0

2B 2.5 97.5 0.25 10.725

3B 5.0 95.0 0.5 10.45

4B 7.5 92.5 0.75 10.175

5B 10.0 90.0 1.0 9.9

6B 15.0 85.0 1.5 9.35

7B 20.0 80.0 2.0 8.8

8B 25.0 75.0 2.5 8.25

9B 30.0 70.0 3.0 7.7

10B 40.0 60.0 4.0 6.6

11B 50.0 50.0 5.0 5.5

12B 60.0 40.0 6.0 4.4

13B 80.0 20.0 8.0 2.2

14B 100.0 0.0 10.0 0.0

 * Denatured without methanol

TABLE #4 GENERAL MOTORS RVP TEST DATA

BASE RVP RVP

STUDY 1 9.4 1.1

12.7 0.9

STUDY 2

7.0 1.1

9.0 1.0

14.0 0.7
 33 The term "actual" in this case does not imply that there

is one loyalty curve that is applicable. As was discussed

earlier the loyalty curve should vary from one geographical

area to the next depending on availability of gasoline stations

and other variables.

45

III. RESULTS AND CONCLUSIONS

 Figures #8 and #9 show the results of the commingling model for a base

RVP of 8 psi. Figure #8 shows the RVP boost due to the commingling effect

that can be expected across all the gasoline in the fleet based on ethanol

market shares of 10%, 30%, or 50%. For each market share a number of runs

were performed to incorporate results from the various loyalty and fill curves

that are available. Figure #9 provides what is called the "Effective

Commingling Boost", which is defined as the fleetwide RVP boost due to

commingling divided by the fraction of the fuel represented by the ethanol

blend. 

The results for an individual ethanol market share appear to be most

dependent upon the type of loyalty curve chosen. For each ethanol market

share the lowest commingling effect is calculated using the Arco brand loyalty

data which is considered to be the high end of the loyalty curves used. The

highest commingling effect is found when no brand loyalty is assumed. The

other two brand loyalty curves provide similar results that are in the middle

of these two extremes. It is believed that the these curves successful

bracket the "actual" loyalty curve and thus these results should bracket the

"actual" commingling effect33. 

The results appear to be fairly insensitive to the type of fill curve

used. In some instances there is little or no difference in the commingling

effect between the use of the actual General Motors fuel refill data or the

smoothed version of that data. Thus this variable appears to be not as

critical a factor as does the owner loyalty to a fuel brand. 

The results do show, however, that commingling can be a significant

effect. The effect appears to be greater as the ethanol market share becomes

large (Figure #8), however, the increase in the commingling effect appears to

level off at a maximum as the ethanol market share becomes 30% or greater. 

The effective commingling boost per gallon of ethanol blend, however, is the

greatest at low gasohol market shares. 

 One of the most dramatic points in these results is the fact that the

non-reformulated gasoline scenario results in a much greater commingling boost

than that of the reformulated gasoline case). This is due to the fact that

the presence of MTBE mitigates the RVP boost somewhat at low concentrations of

ethanol as is evident from Figure #6.
46

Insert page of graphs here
47

Insert page of graphs here
48

Insert page of graphs here
49

II. Simple Model

A. Simple Model Equations and Referenced Work

1. Baseline Determination

The Act requires EPA to promulgate standards for the

performance of reformulated gasoline that are relative to

emission levels from baseline vehicles using baseline fuel. In

order to determine whether fuels are meeting the performance

requirements of reformulated gasoline under the simple model, EPA

must, therefore, establish the baseline to which fuels are to be

compared. The following discussion describes how EPA derived the

emission baselines.

a. Control Periods

Before the emission baselines can be determined, the time

frame to which a fuel's performance will be compared must first

be identified. Section 211(k) of the Act requires control of VOC

emissions during the "high ozone season." For the purposes of

this rulemaking, the high ozone season is defined to be June 1

through September 15. This period covers the vast majority of

days during which the national ambient air quality standard for

ozone is exceeded nationwide and is consistent with the period

covered by EPA's gasoline volatility control requirements. Fuel

will be required to meet the VOC control requirements at the

retail outlet from June 1 through September 15 and at the

refinery from May 1 through September 15. Additional VOC

controlled fuel is likely to be produced by the refiner prior to

May 1 to ensure compliance on that date.

b. Baseline Gasoline

The Act specified the baseline fuel to be used in

determining compliance with the reformulated gasoline performance

requirements during the summer months (high ozone season). That

specification is shown below. The Act did not specify the

requirements for the winter baseline (non-high ozone season)

gasoline, but requires that EPA establish the winter baseline

specifications to reflect gasoline qualities in 1990. The July

9, 1991 (1) proposal contained a description of the data and

methodology EPA used in determining the winter baseline fuel. 

That methodology was revised somewhat by the April 16, 1992 (2)

proposal. The final winter baseline fuel specification is shown

below, consistent with the non-high ozone period described above. 

Beyond the requirements of the Act, and in keeping with EPA's

July 9, 1991 and April 16, 1992 proposals for reformulated

gasoline, the summer baseline fuel is also assumed to be free of
 34 Memorandum from Dave Korotney to Air Docket A-92-12

entitled "1990 Baseline Vehicles", November 30, 1993.

50

oxygen and lead, and contain deposit control additives sufficient

to meet the requirements of Section 211(l) of the Act. 

Table II-1: Baseline Fuel Compositions

Summer Winter

Sulfur, ppm 339 338

Benzene, volume percent 1.53 1.64

RVP, psi 8.7 11.5

Octane, R+M/2 87.3 88.2

T10, degrees F 128 112

T50, degrees F 218 200

T90, degrees F 330 333

Aromatics, volume percent 32.0 26.4

Olefins, volume percent 9.2 11.9

Saturates, volume percent 58.8 61.7

c. Baseline Vehicles

Under Section 211(k) of the Act, reformulated gasoline must

result in reduced emissions relative to emissions from baseline

or representative model year 1990 vehicles when using baseline

gasoline. For the purposes of this rulemaking, EPA has based its

emission modeling on vehicles having technology representative of

that used in 1990. As a result, 1990 technology vehicles could

be as early as 1986 model year vehicles, or as late as current

model year vehicles. The data used to develop the simple model

relationships being promulgated today are based on this. For

more information regarding 1990 baseline vehicles, the reader is

referred to the Docket.34

2. In-Use Basis

a. MOBILE4.1 and Enhanced I/M

The goal of EPA in developing the procedures for certifying

fuel as meeting the reformulated gasoline requirements is to

assure that a certified fuel will achieve the required emission

reductions in-use. This goal necessitates the use of a fuel

effects model which predicts in-use emissions. For the simple

model, EPA proposed to use the MOBILE4.1 emissions model to

determine the baseline emission levels for 1990 technology

vehicles over their full useful life. Since the existence of an

enhanced inspection and maintenance (I/M) program will

significantly effect the in-use emission performance of 1990
 35 Memorandum II-A-2 from Jeffrey A. Herzog and Stephen

Mayotte to Public Docket No. A-91-02.

51

technology vehicles during the period when the reformulated

gasoline program is in place, EPA also proposed to assume an

enhanced I/M program was in place before determining baseline

emissions. As discussed at length in the February 26, 1993

proposal, a more recent MOBILE model now exists, and EPA has now

promulgated the requirements for enhanced I/M programs. The

latest MOBILE model and actual I/M program requirements differ

significantly from those assumed for the proposal. However,

given the impact of changes to these assumptions on the relative

benefits of exhaust and evaporative controls and the short lead

time available for refiners to respond to any such changes, the

simple model as promulgated here remains based upon the July 29,

1991 version of MOBILE4.1 and an enhanced I/M scenario consisting

of a gas cap check and a 2500 rpm idle test. EPA believes this

is appropriate for the same reasons relied on to delay mandatory

use of the complex model until January 1, 1998.

b. Temperature Conditions

MOBILE4.1 was developed to predict motor vehicle emissions

on an area-specific basis. In order to use MOBILE4.1, it is

necessary to specify a temperature range for the areas in which

motor vehicle emissions are being evaluated. For purposes of

reformulated gasoline, emissions are modelled during the summer

assuming temperatures ranging from 71.6 to 91.6 degrees

Fahrenheit in VOC control region 2 (northern areas) and ranging

from 69.4 to 94.0 degrees F in VOC control region 1 (southern

areas). These temperatures represent the population-weighted

average of minimum and maximum temperatures measured in each of

25 serious and worse ozone nonattainment areas during their ten

worst ozone days in each of the months of July and August for the

years 1986 to 1989 (in ten of the cities) and 1985 to 1987 (in

the other fifteen cities).35 (3)

Refueling emissions were derived assuming an ambient

temperature of 90°F for both VOC control regions 1 and 2. 

Distinguishing between the different areas did not appear

justified given the similarity of Class B and Class C area

temperatures, the relatively low magnitude of refueling

emissions, and the wide range of times and temperatures at which

refueling occurs during a day. 90°F was considered to represent

a severe case in order to account for average in-use refueling

emissions on high ozone days.

For determination of winter baseline emissions, an average

low temperature and an average high temperature of 39°F and 57°F,

respectively, are assumed. These temperatures were estimated
 36 Ibid.

52

from the historical 30-year average low and high temperatures for

the months of October through April for the 25 serious and worse

ozone nonattainment areas.36 (3)

c. Effects of Stage II Refueling Controls

The assumptions used in establishing the baseline emissions

should be representative of the conditions that will be

encountered during the time when the reformulated gasoline

provisions are in effect. For this reason, baseline emissions

are assumed to include the benefits of a Stage II refueling vapor

recovery program. By 1995, all serious, severe, and extreme

ozone nonattainment areas are required to have implemented Stage

II refueling control programs. The efficiency assumed for Stage

II controls in determining the emission baseline is 86 percent. 

EPA's regulatory impact analysis supporting refueling emission

regulations estimated the efficiency of Stage II equipment to be

86 percent in areas such as California where the program is very

strictly enforced. Because of the severity of ozone pollution in

areas that will be covered by the reformulated gasoline program

and because strong measures will be required to bring these areas

into attainment, it is assumed that Stage II programs in these

covered areas will be strictly enforced. For these same reasons

EPA is not revising its proposed efficiency assumption for Stage

II programs as suggested by some commenters.

3. Emission Effects

a. Definition of VOC

The Act requires reductions in emissions of ozone-forming

VOCs. This interpretation is consistent with the focus of

Section 211(k) on the areas with the most extreme ozone pollution

problem. EPA proposed in the April 16, 1992 SNPRM that methane

would be excluded from the definition of VOC on the basis of its

low reactivity in keeping with past EPA actions, but included all

other VOCs including ethane. EPA further proposed, however, that

should the Agency modify the definition of VOC, we might do so

for the reformulated gasoline rulemaking as well. As discussed

in the February 26, 1993 proposal, EPA has also excluded ethane

from the definition of VOC (57 FR 3941). As a result, the

performance of fuels meeting the VOC emission requirements under

the simple model, as expressed above, are determined on a nonmethane, non-ethane basis. This change resulted in slight

changes to the simple model equations previously proposed, but

the overall results of the simple model are essentially

unaffected. The ethane emissions were subtracted from the SNPRM

estimates of the VOC emissions. From the Auto\Oil Air Quality
53

Improvement Research Program (AQIRP), ethane emissions were

determined to be 3.5 percent of the nonmethane hydrocarbon

emissions. Ethane emissions were assumed to be unaffected by

fuel changes.

b. VOC Emission Effects

At the time of the proposed rule the impact on VOC and NOx

emissions of adding oxygenates to gasoline was calculated using

the EPA emission factor database. This database included both

normal and high emitting vehicles which are represented in the

in-use fleet. The understanding at the time was summarized in an

EPA memorandum. (4) The oxygenated fuels used in that analysis

were lower in aromatics level as is expected with the use of the

simple model.

The nonexhaust VOC emission effects were determined using an

early version of the MOBILE4.1. The only parameter that had an

effect on emissions was assumed to be the Reid Vapor Pressure

(RVP). The MOBILE4.1 model was run for several RVP levels and

regressed to produced the equation given in the regulations for

VOC emissions.

c. Exhaust Benzene Baseline Emissions and Effects

The exhaust benzene emissions can be affected in two ways. 

Reduction of exhaust VOC emissions through improved combustion or

catalyst efficiency should result in reduction of benzene

emissions. Also, the benzene fraction of VOC emissions may be

reduced either by reduction of fuel benzene or precursors

(primarily nonbenzene aromatics) of exhaust benzene. This method

is used for the aldehyde emissions as well.

The benzene fraction of exhaust VOC emissions was determined

from a correlation developed by Chevron using fuel benzene and

aromatics content as parameters. (5) The Chevron analysis used a

compilation of all of the studies available at the time of the

proposal. 

Since exhaust VOC emissions are reduced with added

oxygenate, benzene emissions are assumed to be reduced

proportionally. 

Low temperature testing indicated that the benzene and 1,3-

butadiene emissions fraction were found to be insensitive to

temperature. (6,7) Therefore, the winter baseline emissions

should be expected to increase as the exhaust VOC emissions

increase.

d. Nonexhaust Benzene Emissions
54

Benzene is the only toxic air pollutant that is emitted in

measurable quantities from refueling, evaporative, running loss

vapors. Reduction in fuel benzene can be expected to result in

proportional reductions in benzene emissions from all of these

nonexhaust emissions sources.

The nonexhaust benzene emissions were determined by applying

the GM headspace benzene fraction estimate to the mass emissions

estimated from the MOBILE model.(8) The MOBILE model was used to

predict the RVP effect on VOC emissions down to as low as 6.6

psi. Due to differences in the temperature conditions, slight

differences in nonexhaust VOC emissions occur between VOC control

region 1 and 2. The GM headspace model showed an effect of both

RVP and MTBE content on the fraction of VOC emissions that were

benzene. 

Evaporative benzene emissions include hot soak (evaporative

emissions immediately following the shutting off the engine) and

diurnal emissions (evaporative emissions from a sitting vehicle

as the daily ambient temperature rises). Hot soak emissions

occur at higher temperatures than diurnal emissions and the

relative volatility of benzene is slightly higher at those

temperatures. Running loss emissions occur at roughly the same

fuel temperatures as hot-soak emissions and have similar benzene

fractions.

Based on the emission factors contained in MOBILE4.1,

evaporative and running loss benzene emissions tend to be

dominated by emissions from vehicles with inoperative emission

control systems (those vehicles likely to "fail" EPA's purge and

pressure tests). The benzene fraction of evaporative and running

loss emissions from vehicles with properly operating systems

(those vehicles likely to "pass" EPA's purge and pressure tests)

and from "fail" vehicles, however, are comparable. Hence the

benzene weight fraction of evaporative and running loss VOC

emissions for a fuel is assumed in the simple model to be

described by the relationship originally derived for "fail"

vehicles.

One comment suggested that it was not appropriate to use

estimates not publicly available, like the GM model for

estimating emission impacts. While the GM model itself is not

available, the emission estimates from the model are available.

Furthermore, the underlying basis of the model has been published

by Reddy (9), and a separate program developed by EPA using

Reddy's paper as the basis confirmed the estimates from the GM

model. Another comment suggested that the headspace model

underestimated the benzene emissions with MTBE present. It was

explained that the higher average molecular weight of the

headspace vapor partially offsets the benzene fraction reduction. 

If the vapor has a higher molecular weight, it could be concluded
55

that the VOC emissions would be greater. However insufficient

data existed to quantify the effect of MTBE on evaporative

emissions at constant RVP. EPA believes it is not appropriate to

alter the benzene fraction estimate, since there is no

quantitative estimate for the mass emission increases claimed by

the commenter.

Under winter condition, EPA is assuming that nonexhaust

benzene (and all nonexhaust VOC) emissions will be negligible

relative to exhaust toxic emissions. A comment suggested that

the MOBILE model will predict emissions for wintertime conditions

at the higher RVP levels used, and therefore should be included

in the toxic model. While the RVP of the fuel is much greater

during the winter, the temperatures are much lower. EPA's MOBILE

model is based upon data collected above the temperatures

experienced in the winter and generally with RVP levels below

those of winter fuels. Projecting evaporative emissions in the

winter is outside of the capability of the MOBILE model. Biven

the lack of adequate data to model nonexhaust VOC and benzene

emissions in the winter, EPA is not changing from its proposed

baseline and toxics model in this regard.

e. Aldehyde Baseline Emissions and Effects

The baseline emissions for the aldehyde emissions,

formaldehyde and acetaldehyde, were determined from the AQIRP

results. The baseline emission estimates are slightly different

than the SNPRM values to account for the change in the definition

of VOC emissions from the SNPRM which excluded ethane. While a

comment expressed a concern that AQIRP results should not be used

exclusively, only aldehyde emissions effects were determined

using the AQIRP data and those exclusively because no other data

existed at the time. 

The results from AQIRP were used to determine the effects on

the formaldehyde and acetaldehyde fraction of exhaust VOC from

the addition of oxygenates. Explicit effects were calculated for

MTBE, ethanol, and ETBE.

The AQIRP data as released, however, were modified slightly

to exclude the acetaldehyde and formaldehyde results for ETBE and

ethanol from one of the vehicles (car #5A) due to emission

results which were confirmed as being in error. Furthermore, the

effect of ETBE on the weight percent of acetaldehyde was based on

the test results for ethanol due to the lack of adequate fuel

comparability for ETBE-containing fuels. However, for this case,

the ethanol results were adjusted based on a comparison of the

ETBE and ethanol results on similar fuels for which data was

available.

Responding to several comments, the EPA has included

aldehyde equations for the use of other oxygenates in the simple
56

model. Methyl tertiary-amyl ether (TAME) and any other methyl

ethers are assumed to have equivalent aldehyde emission

performance to MTBE. Ethyl tertiary-amyl ether (ETAE) and any

other ethyl ethers are assumed to have equivalent aldehyde

emission performance to ETBE. Alcohols (with the exception of

methanol) are assumed to have equivalent aldehyde emission

performance to ethanol. These assumptions were based on the

chemical similarity of the oxygenates. Aldehyde equations for

mixed oxygenates were also provided.

f. Butadiene Emissions and Effects

At the time of the proposal there was little information on

the effect of fuel reformulation on butadiene emissions. A

reduction in exhaust VOC emissions was assumed to result in a

proportional reduction in butadiene emissions. The baseline

emissions were determined from an analysis of the AQIRP.

For wintertime modeling, the baseline emissions were assumed

to be the same percentage of the VOC emissions as the summertime

emissions. See the benzene discussion above for the rationale.

g. POM Emissions and Effects

There was no data to determine the effect on POM emissions

from the use of reformulated gasolines. An assumption was made

that the reduction of POM emissions would be the same as the

reduction of VOC emissions. 

The baseline emissions of POM were determined from work of

Schuetzle (10). Table 8 in that paper shows that 18 mg/km of

particulate were produced from gasoline vehicles (half of the

vehicles were equipped with catalysts, the HC emissions were not

reported). Approximately 8.5 mg/km of the particulate was

extractable in three separate extracts, (1% ether in hexane

(nonpolar fraction), 1/1 ether/hexane (moderately polar), and

methanol (polar fraction). Selected standard PAH compounds were

recovered at greater than 80%.

The paper indicated the approximate percentage of PAH which

is interpreted as synonymous with POM in each fraction for diesel

exhaust. The extract from gasoline exhaust was found to be more

mutagenic on a gram basis than diesel extract therefore we may be

underestimating the POM emissions by applying the same percentage

of POM in diesel particulate extract to that for gasoline

particulates.

Gas phase POM were assumed zero because the mutagenicity was

low. The polar fraction was assumed zero because activity was

low and no data was presented. Both of these assumptions lead to

a lower estimate of the POM emissions than might have been.
57

The sum of the nonpolar and moderately polar extract

fraction multiplied by the POM fraction in each extract provides

an estimate of the fraction of POM in the particulate phase. 

This estimate multiplied by the amount of particulate extract for

gasoline engines provides the 1.4 mg/mi baseline emission

estimate of POM. 

One comment cited two references which estimated lower POM

emissions. Schuermann, et al. (1990) (11) reported that 0.2

mg/mi and 0.01 mg/mi of PAH were emitted from cars without and

with a catalyst respectively. Only 11 PAH compounds were

identified and quantified. Whether these compound were collected

from the gas phase or the particulate phase was not discussed in

the paper and a more extensive literature review is necessary. 

The HC emissions were not reported. Westerholm, et al. (1988)

(12) reported that gas phase PAH emissions from a car without a

catalyst were 0.4 mg/mi, and particulate associated PAH was 0.07

mg/mi. The HC emissions were 2.4 g/mi, and the particulate

collected was 7.3 mg/mi. The particulate was extracted with

dichloromethane (methylene chloride) and no recovery of selected

PAH compounds were reported. This raises questions regarding the

choice of solvent especially given the low value of recovered PAH

from the amount of particulate. 

B. Technical Corrections

Several errors were found in the proposed simple model. 

Baseline values were found to be in error for POM emissions and

Region 1 total VOC and toxic emissions. The baseline emissions

for the final simple model are given below. Any slight

difference between the final baseline levels and those in the

proposal are due to the round-off differences when ethane was

excluded from the VOC emissions. 
58

Table II-2: Simple Model Baseline Emissions

Summer Winter

Class B Class C

Exhaust VOCs (g/mi) 0.444 0.444 0.656

Hot Soak/Diurnal (g/mi) 0.390 0.339

Running Loss (g/mi) 0.431 0.390

Refueling (g/mi) 0.040 0.040

Total VOCs (g/mi) 1.304 1.213 0.656

Exhaust Benzene (mg/mi) 30.1 30.1 40.9

Evaporative Benzene 4.3 3.8 0.0

Running Loss Benzene 4.9 4.5 0.0

Refueling Benzene 0.4 0.4 0.0

1,3-Butadiene 2.5 2.5 3.6

Formaldehyde 5.6 5.6 5.6

Acetaldehyde 4.0 4.0 4.0

POMs 1.4 1.4 1.4

Total TAPs (mg/mi) 53.2 52.1 55.5

C. Caps on Fuel Parameters

The caps on three parameters (sulfur, T90, and olefins) were

chosen based on the information at the time indicating that

increasing these parameters increased either VOC or NOx

emissions. Subsequent comments felt that aromatics and T50

should be capped in addition to the three proposed. Other

comments felt that no properties be capped. In addition, some

comments felt that the driveability index (a combination of T10,

T50, and T90 with the most emphasis on T50 and T90) should be

included in the simple model or at least capped.

The basis for the caps was information from the AQIRP

technical bulletins (13, 14) which showed that T90 had a

significant impact on VOC emissions, olefins on NOx emissions,

and sulfur on both. Since allowing these parameters to increase

over the baseline value was certain to have a detrimental effect

emissions, it was necessary to cap them. Since that time

additional data and information has been developed for use in the

Complex Model. This data confirms that sulfur, T90 (E300) and

olefins should be capped either for the purposes of preventing

increases in VOC or NOx.

Aromatics and T50 (E200) have also been found to have a

significant effect on emissions. As a result, they may also be

deserving of caps. However, in the case of aromatics, a separate

cap is less important since its level is limited by the toxics

requirements in the model. In addition, for both aromatics and

T50, applying caps at this point in time would not be appropriate
59

due to the need to provide refiners with adequate leadtime. 

Similarly, regardless of the relative merits of using the

driveability index as a surrogate for or supplement to T10, T50,

and T90, it would not be appropriate in the context of leadtime

constraints to place a cap on the driveability index of the fuel.

D. Averaging and Trading

Since the air toxics standard is a year-round standard, as

long as unequal percent reductions are achieved in the summer and

the winter, the overall stringency of the standard is dependent

on the relative duration of the two periods. In the proposals,

the time period over which refiners could count fuel as being

controlled for air toxics relative to the summer baseline was

sometimes internally inconsistent, and inconsistent between

proposals for various reasons. As a result, EPA received a

number of comments on what the appropriate period should be. 

Based upon the comments, the averaging period for the toxic

emissions performance standard will be the same as for the VOCcontrolled season. This should avoid confusion and reduce

reporting time. 

Since the simple model does not include a NOx model, it

would not be possible to average NOx emissions as suggested by

one commentor.
60

References

(1) NPRM, 56 FR 31176, July 9, 1991.

(2) SNPRM, 57 FR 13416, April, 16, 1992.

(3) Memorandum II-A-2 from Jeffrey A. Herzog and Stephen Mayotte

to Public Docket No. A-91-02.

(4) Lindhjem, C.E., 'Effect of Oxygenates on Emissions', EPA 

Memorandum to Richard Rykowski, January, 7, 1992.

(5) Chevron Analysis

(6) Stump, F., Tejada, S., Ray W., Dropkin, D., Black, F., Snow,

R., Crews, W., Siudak, P., Davis, C.O., and Baker,

L., 'The Influence of Ambient Temperature on

Tailpipe Emissions from 1984 to 1987 Model Year

Light-Duty Gasoline Motor Vehicles-II',

Atmospheric Environment, v. 23, 1989, pp. 307-320.

(7) Stump, F., Tejada, S., Ray W., Dropkin, D., Black, F., Snow,

R., Crews, W., Siudak, P., Davis, C.O., and Carter, P.,

'The Influence of Ambient Temperature on Tailpipe

Emissions from 1985 to 1987 Model Year Light-Duty

Gasoline Motor Vehicles-II', Atmospheric Environment,

v. 24A, 1990, pp. 2105-2112.

(8) Reddy, S.R., Personal Communication to C.E. Lindhjem and P. 

Bush, April 16, 1991.

(9) Reddy, S.R., 'Evaporative Emissions from Gasolines and 

Alcohol-Containing Gasolines with Closely Matched

Volatilities', SAE-861556.

(10) Schuetzle, D., (1983), 'Sampling of Vehicle Emissions for 

Chemical Analysis Biological Testing', Environmental Health

Perspectives, v. 47, pp 65-80.

(11) Schuermann, D., et al., (1990), SAE-902116.

(12) Westerholm, R.N., et al., (1988), Environmental Science and 

Technology, 22, pp 925-930.

(13) Auto\Oil Air Quality Improvement Research Program, Technical 

Bulletin No. 1, 'Initial Mass Exhaust Emissions Results

from Reformulated Gasolines', December, 1990.

(14) Auto\Oil Air Quality Improvement Research Program, Technical

Bulletin No. 2, 'Effects of Fuel Sulfur Levels on Mass

Exhaust Emissions', February, 1991.
61

III. Complex Model Baselines 

 Section 211(k) of the Clean Air Act (CAA or the Act) requires

that gasoline sold in the worst ozone nonattainment areas of the

United States be reformulated to result in reduced emissions of VOC

and toxic compounds. The Act also states that the emissions from

gasoline in other areas of the United States cannot simultaneously

increase above 1990 levels. Refiners must certify their gasolines

for sale by showing, through testing and/or the Complex Model, that

their fuel meets the requirements of either the reformulated

gasoline or anti-dumping programs. In either case, the vehicle

emissions must be evaluated relative to the emissions from a

specified baseline gasoline (outlined in Section 211(k) of the Act)

in a specified baseline vehicle (defined by Section 211(k) as a

representative 1990 model year vehicle). Thus the Act implicitly

directs EPA to establish and promulgate the baseline emissions

against which all emission measurements will be evaluated.

The baselines discussed in this section do not apply to the

cost-effectiveness calculations presented in Sections V and VI.

Cost-effectiveness is based on in-use emission estimates, and

therefore the baseline fuels and baseline emissions cannot be

limited to 1990 baseline fuels and 1990 model year vehicles (i.e.

the conditions under which the Complex Model was developed).

Alternative baselines will be derived and presented in that

section.

Baseline emissions are produced from baseline fuels as

specified in the Act. Accordingly, this section is composed of two

subsections, one for baseline fuels and a second for baseline

emissions. This section is directed towards use of the Complex

Model. The baselines applied to the Simple Model are covered in

more detail in Section II, and baselines applied to the antidumping program are discussed in Section VII.

A. Baseline Fuels

The Clean Air Act directs the EPA to use a different baseline

fuel during different seasons. The Act provides the EPA with a

specific baseline fuel for the high ozone (i.e. summer) season,

which EPA has defined as the period from June 1 to September 15.

Although the Act refers to this baseline fuel as summer baseline

gasoline, its importance in the reformulated gasoline program has

resulted in its being commonly referred to as Clean Air Act

Baseline Gasoline, or CAAB. The Act does not specify a baseline

fuel for the non-high ozone (i.e. winter) season, but instead

directs the EPA to establish the parameters of such a baseline fuel

itself. Both of these baseline fuels will be discussed below.
62

1. Summer

Most of the summer baseline fuel parameters are specified

explicitly by the Act. The level of oxygen, however, was left to

the EPA to determine. As discussed in the July 1991 NPRM [56 FR

31176], the low volume of oxygenated fuels sold in ozone

nonattainment areas in 1990 led the Agency to conclude that the

oxygen content of the summer baseline fuel should be zero. The

final summer baseline fuel specifications are given in Table III-1.

Table III-1: Summer Baseline Fuel

Fuel parameter, units Value

Oxygen, wt%

Sulfur, ppm

RVP, psi

T50, o

F

T90, oF

Aromatics, vol%

Olefins, vol%

Benzene, vol%

0.0

339

8.7

218

330

32.0

9.2

1.53

In addition to the fuel parameters shown Table III-1, the Act also

specifies values for a number of other summer baseline fuel

parameters that are not included in the Simple or Complex Models:

API gravity 57.4

Octane, R+M/2 87.3

IBP, oF 91

T10, oF 128

End point, oF 415

Saturates, vol% 58.8

The distillation parameters shown in Table III-1 are given in

terms of T values, or the temperature at which a given percentage

of fuel has evaporated. Distillation characteristics of baseline

fuel (or any fuel) can alternatively be described with E values

which represent the volume percent of fuel that has evaporated at

a given temperature. Since the Complex Model uses E values instead

of T values as distillation parameters, the Agency developed a pair

of conversion equations. Described in more detail in Section

IV.A.2 below, these equations are derived from a simple regression

on data from the Complex Model database.

E200(%) = 147.91 - 0.49 x T50(oF)

E300(%) = 155.47 - 0.22 x T90(oF)

where E200 and E300 are the % evaporated at 200 and 300 o

F,

respectively, and T50 and T90 are the temperatures at which 50 and
63

90 percent of the fuel has been evaporated, respectively. Thus the

summer baseline fuel distillation parameters used by the Complex

Model are:

E200(%) = 147.91 - 0.49 x 218 = 41 %

E300(%) = 155.47 - 0.22 x 330 = 83 %

2. Winter

The winter baseline fuel was not defined explicitly by the

Act. Instead, the Agency was directed to establish specifications

for winter baseline fuel. As described in the July 1991 NPRM [56

FR 31176] and revised in the April 1992 SNPRM [57 FR 13416], the

Agency based its winter baseline fuel specifications on an analysis

of fuel surveys performed by the American Automobile Manufacturers

Association and by Southwest Research Institute. The collection of

winter season values for each fuel parameter was weighted according

to sales data, state fuel consumption data, and population data to

obtain the final, nationwide winter baseline fuel. Thus the

methodology and results of this analysis remain unchanged from the

proposals. The winter baseline fuel specifications are given in

Table III-2.

Table III-2: Winter Baseline Fuel

Fuel parameter, units Value

Oxygen, wt%

Sulfur, ppm

RVP, psi

T50, o

F

T90, oF

Aromatics, vol%

Olefins, vol%

Benzene, vol%

0.0

338

11.5

200

333

26.4

11.9

1.64

As for summer baseline gasoline, the distillation parameters

shown in Table III-2 are given in terms of T values instead of E

values. The conversion equations described above can be used to

estimate E values for winter baseline gasoline as well as for

summer baseline gasoline:

E200(%) = 147.91 - 0.49 x 200 = 50 %

E300(%) = 155.47 - 0.22 x 333 = 83 %

3. Response to Comments

A number of commenters took issue with the Agency's decision

to define baseline fuel values for E200 and E300 through equations
64

that provide these values from T50 and T90 measurements. These

conversion equations were based on single parameter regressions of

all the data in the Complex Model database. The commenters

suggested that the summer baseline fuel values for E200 and E300

should be based instead on the measured values for these fuel

parameters on summer baseline gasoline in the Complex Model

database. The average values as provided by the American Petroleum

Institute are 41.9% for E200 and 82.1% for E300. The Agency

recognizes the merit in this approach. However, the Agency has

determined that the use of the conversion equations for the

baseline fuel is preferable because this approach is consistent

with the use of the same conversion equations for other fuels.

"Other fuels" include the winter baseline gasoline (which is not

represented in the Complex Model database), fuels that are used in

the process of specifying performance standards, and fuels that are

candidates for certification with the Complex Model. In addition,

while the "summer baseline" gasolines in the Complex Model database

were blended so as to match the baseline fuel specifications laid

out in the Act, the inevitable variability introduced in the

blending and measurement processes (as discussed in Section IV.G)

caused the actual composition and properties of "summer baseline"

gasolines in the Complex Model database to vary from the Act's

specifications. 

Commenters also suggested that the conversion equations be

based not on all the data in the Complex Model database, but

instead on the hydrocarbon-only fuels. The Agency determined that:

1) It was not appropriate to have a different set of

conversion equations for hydrocarbon-only fuels and

oxygenated fuels; and

2) It was not appropriate to apply conversion equations

based on hydrocarbon-only fuels to reformulated

gasolines, all of which will be oxygenated.

Thus the Agency has concluded that its conversion equations, based

on all the data in the Complex Model database, provide the most

reliable means of estimating E200 and E300 values for the

hydrocarbon-only baseline gasolines, oxygenated reformulated

gasolines, and both oxygenated and hydrocarbon-only conventional

gasolines.

The Agency received many comments objecting to the use of a

7.8 psi RVP baseline fuel for summer Class B areas. The Agency

agrees with the commenters that the Act makes no provisions for a

summer baseline fuel with an RVP of 7.8 psi and that such a fuel is

not an appropriate baseline for determining performance standards.

Therefore, the Agency has calculated all performance standards

relative to CAA baseline fuel with an RVP of 8.7. However, the

Agency retains its position that a fuel identical to Clean Air Act

baseline gasoline but with an RVP of 7.8 psi provides the most
65

accurate measure of in-use emission reductions in Class B areas.

In such areas, EPA's volatility control requirements have capped

RVP levels at 7.8 psi. Thus a gasoline with an RVP of 7.8 psi that

is otherwise identical to CAA baseline gasoline has been used for

the Class B cost-effectiveness calculations presented in Sections

V.B and VI.F.

B. Baseline Emissions

While baseline fuels are categorized only by season, baseline

emissions are categorized by season, area class, and program phase.

They can be subdivided into exhaust and non-exhaust emissions and

by pollutant. Thus in the discussions that follow, baseline

emission derivations and presentations will be given within the

context of these category definitions.

Baseline emissions are based upon a number of derivation

approaches and sources. The derivation approaches are specific to

the subcategories described above. Of the sources, the MOBILE

emissions model is the most important, and therefore will be

discussed first in Section B.1. The following two sections outline

the scenarios under which the MOBILE model was run. The weighting

factors used to calculate toxic emissions will then be discussed

and presented in Section B.4. The last two subsections of Section

B will present the baseline emissions for summer and winter,

respectively.

1. MOBILE Emissions Model

The Agency's MOBILE emission factor model is an integrated set

of FORTRAN routines for use in the analysis of the air pollution

impact of gasoline and diesel fueled highway mobile sources.

MOBILE calculates emissions in terms of grams per mile for both

gasoline and diesel-fueled light-duty vehicles (LDVs), light-duty

trucks (LDTs), and heavy-duty vehicles (HDVs), and for gasolinefueled motorcycles. These emissions, or emission factors, can be

calculated in any one of five forms: total hydrocarbons (THC),

nonmethane hydrocarbons (NMHC), volatile organic compounds (VOC),

total organic gases (TOG), or nonmethane organic gases (NMOG).

These categories are defined in Table III-3. The effects of

various inspection and maintenance programs can also be modeled.
 37 EPA Memorandum from Jeffrey Herzog and Stephen Mayotte to Public

Docket No. A-91-02, "Summer and Winter Temperatures for the Top 25 Serious,

Severe, and Extreme Ozone Nonattainment Areas"

66

Table III-3: MOBILE Emission Factor Definitions

Emission

Factor

Option

Compounds included in the emission factor:

FID

Hydrocarbons Methane Ethane Aldehydes

THC

NMHC

VOC

TOG

NMOG

Yes

Yes

Yes

Yes

Yes

Yes

No

No

Yes

No

Yes

Yes

No

Yes

Yes

No

No

Yes

Yes

Yes

When quantifying emissions from a fleet of vehicles, it is

important to realize that emissions will vary over a vehicle's

lifetime, generally increasing with age due to factors including

normal mechanical aging and possible malmaintenance or tampering.

To ensure that the standards set for reformulated gasoline achieve

the intended environmental benefits, the Agency assesses emissions

on an "in-use" basis, such that emissions from 1990 model year

vehicles are the estimated average emissions from those vehicles

over their lifetimes.

MOBILE assumes that a 25-model-year "window" of vehicles

comprises the in-use fleet in any given calendar year. Any

vehicles over 25 years of age are grouped with and modeled as the

25-year-old vehicles. For example, if the calendar year of

evaluation were 1990, then MOBILE would assume that the in-use

fleet would consist of vehicles ranging in age from one (model year

1990) to 25 (model year 1966 and older).

EPA's MOBILE emissions model is designed to predict motor

vehicle emissions on an area-specific basis. In order to use the

MOBILE model, it is necessary to specify a temperature range for

that area in which motor vehicle emissions are being evaluated.

The area distinctions assumed by EPA are roughly consistent with

the ASTM area classifications A, B, C, D, and E. For this

analysis, a diurnal temperature range of 72 to 92 degrees

Fahrenheit was used for Class C areas, and a range of 69 to 94

degrees Fahrenheit was used for Class B areas. These temperatures

represent the average minimum and maximum summer temperatures for

high ozone days in these areas. For determination of winter

baseline emissions in the non-high ozone period, an average low

temperature and an average high temperature of 39°F and 57°F,

respectively, were assumed for both B and C areas.37
67

MOBILE calculates nonexhaust emissions in three separate

categories: running losses, refueling losses, and evaporative

losses. Running losses are losses that occur while the vehicle is

running, and are brought about by the heating of the fuel tank and

fuel lines. Refueling losses occur strictly during refueling of a

vehicle, and are due mainly to the displacement of vapors in the

fuel tank with fuel. Evaporative losses include both diurnal and

hot soak losses. Hot soak losses occur immediately after a vehicle

is turned off, and are due to the continued transfer of heat from

the engine to the fuel and the concurrent removal of cooling media

such as wind and engine coolant. Diurnal losses occur during daily

ambient temperature swings.

In the February 1993 NPRM [58 FR 17175], MOBILE5 was used to

determine baseline emissions of VOC and NOx for Phase II of the

reformulated gasoline program. Since then, MOBILE5a has been

released, and it provides slightly different baseline emission

estimates than MOBILE5. The changes to the baseline emission

estimates are minimal, however, prompting the Agency to replace

MOBILE5 with MOBILE5a without opportunity for public comment.

MOBILE5a was initially designed to augment MOBILE4.1 through

the addition of post-1990 vehicle based emission controls. Both

MOBILE 4.1 and MOBILE5a were intended to predict the same in-use

emission for calendar years prior to 1991. However, in the process

of adding the post-1990 vehicle controls, EPA also modified its

estimates of pre-1991 model year vehicle emissions, causing the two

models to produce differing projections for pre-1991 as well as

post-1990 calendar year emissions. The most significant changes in

MOBILE5a from MOBILE4.1 include:

• The effect of post-1990 vehicle and fuel emission

control programs mandated by the Clean Air Act have

been added;

• The California low-emitting vehicle program can be

modeled;

• A wider range of inspection and maintenance

programs can be modeled, most notably programs

meeting EPA's definition of "enhanced I/M."

• The basic emission rate equations for 1981 and

later light-duty gasoline vehicles have been

revised, based on results of the IM240 transient

test program at Hammond, IN.

• Speed correction factors for light-duty gasoline

vehicles have been revised.

Since the reformulated gasoline program uses 1990 vehicles for its

baseline, only those changes that affect 1990 model year vehicles

will affect the MOBILE5a output and therefore the Phase II baseline

emissions. Thus, only the last two points above contribute to the

difference in baseline values between MOBILE4.1 and MOBILE5a. The

significance of these changes in the MOBILE model on the derivation
 38 Based on total (exhaust + non-exhaust) non-methane, non-ethane VOC

emissions for light-duty cars (not including resting losses) in Class C areas

using an 8.7 RVP fuel. MOBILE model input files are shown in Appendices III-A

and III-B.

68

of the Complex Model for nonexhaust emissions is demonstrated by

the increase in total emissions from MOBILE5a over MOBILE4.1 of 13

percent,38 when a basic I&M scenario is assumed for MOBILE4.1 and

an enhanced I&M scenario is assumed for MOBILE5a. 

 For the simple model, the Agency derived baseline emissions

using a July 11, 1991 version of EPA's MOBILE4.1 emissions model.

As described below, EPA also used this version of MOBILE4.1 to

generate the baseline emissions for all of Phase I of the

reformulated gasoline program (i.e. through 1999). Thereafter, the

more recent MOBILE5a model will be used.

2. Inspection and Maintenance Programs

The baseline emissions used in the simple model were

determined from MOBILE4.1 under a scenario that included an early

definition of enhanced inspection and maintenance (I/M). This

early version of enhanced I/M consisted of a short idle test for

exhaust emissions and a visual check for tampering or malfunction

of the catalyst, the fuel inlet restrictor, and the gas cap. Since

publication of the simple model SNPRM, the Agency has promulgated

regulations for enhanced I/M programs that diverge in structure and

content from the original definition of enhanced I/M. The more

recent enhanced I/M program includes a dynamometer-based IM240

exhaust emissions test and fuel tank pressure and canister purge

checks for the vehicle's nonexhaust emission control systems.

Under the model enhanced I/M scenario, 98 percent of the vehicle

population will undergo inspections once a year, and waivers will

be granted for 1 percent of the inspected vehicles. The testing

procedures for the emission factor evaporative system pressure and

purge checks, as well as that for the IM240 transient test, are

provided in the final rulemaking on inspection and maintenance

program requirements [57 FR 52950]. The enhanced I/M program

assumed in the April 1992 SNPRM for the simple model [57 FR 13416]

would now be considered more representative of "basic" I/M.

The Clean Air Act requires ozone nonattainment areas to

achieve the primary standard (less than 0.121 ppm ozone) within a

specified time period depending on the area classification. The

Agency's final rule on inspection and maintenance programs directs

all states or areas within an ozone transport region that have a

1990 population of 100,000 or more to implement enhanced I/M

programs to achieve that standard, regardless of that area's

attainment classification. Serious or worse ozone nonattainment

areas having a 1980 population of 200,000 or more also are required

to implement enhanced I/M programs. Although all of these enhanced
 39 Communication with Lois Platte, EPA National Vehicle and Fuel

Emissions Laboratory, Sept. 21, 1992

69

I/M programs are required to begin by January 1, 1995, various

aspects of the program can be phased in over time. Thus, EPA does

not anticipate the full impact of enhanced I/M to be fully

effective until January 1, 1999, which is late in Phase I of the

reformulated gasoline program. Given that the complex model can be

used as early as 1995, the simple model's basic I/M program appears

to represent Phase I of the reformulated gasoline program best,

while the recently promulgated enhanced I/M is more representative

of I/M programs in Phase II.

Under the basic I/M program scenario, MOBILE4.1 predicts that

20 percent of the gasoline-fueled light-duty vehicles on the road

would be "failing" vehicles39 from a nonexhaust emissions

standpoint. A nonexhaust failing vehicle is defined as one whose

evaporative emission control systems do not work properly, as

determined by the pressure and purge checks associated with an

enhanced I/M program. This scenario is the one assumed for Phase

I. Under the auspices of an enhanced I/M program during Phase II,

MOBILE5a predicts that essentially every light-duty vehicle on the

road would be designated as "passing" in terms of evaporative

emissions because enhanced I/M programs are assumed to have 98

percent compliance and to grant waivers for only 1 percent of

failing vehicles.

3. Stage II Refueling Controls

By 1995, all serious and worse ozone nonattainment areas will

be required to implement Stage II refueling controls as a means of

limiting gasoline refueling emissions. These controls are designed

to capture displaced vapors from the vehicle fuel tank and return

them to the underground fuel storage tanks at the service station.

In the Draft Regulatory Impact Analysis for the simple model, Stage

II refueling controls were estimated to decrease uncontrolled

refueling emissions by 73 percent. This effectiveness has been

carried over to the complex models for both Phases I and II. 

On-board refueling controls will begin in 1996. Since the

Complex Model is concerned only with 1990-technology vehicles, onboard refueling controls have no bearing on baseline emissions or

on emission estimates using the Complex Model.

4. Weighting Factors

The statistical regressions that were used to develop the

Complex Model produced separate models (equations) for every

vehicle group for each of six exhaust pollutants. This

categorization of emission effects was done to most accurately

describe the unique combustion chemistry characteristics of
70

different types of vehicles. However, these separate equations

must be weighted according to the in-use contribution of each

vehicle type to the total mobile source emissions inventory in

order to determine the overall in-use performance of a given fuel.

The derivation of these weighting factors will be given in this

subsection. The normal emitter in-use contribution of each

technology type to the total mobile source VOC emissions inventory

is also used in deriving toxic emission baselines, as described in

Subsection III.B.5.

EPA subdivided normal emitting vehicles (those that emit less

than 0.82 g/mi of VOC) into nine broad vehicle technology types.

Each technology group was characterized by a particular combination

of emission control technologies. The technologies used to

separate normal emitters into technology groups were expected to

cause vehicles to respond differently to specific fuel

modifications or otherwise influence exhaust emissions. The

defining characteristics of each of these nine technology groups is

given in Table III-4.

Table III-4: Normal Emitter Technology Groups

Technology

group

Fuel

system

Catalyst

type

Fuel/Air

system EGR?

1 Multi 3-way CLL/No air Yes

2 Multi 3-way CLL/No air No

3 TBI 3-way CLL/No air Yes

4 Multi 3-way + Ox CLL/Air Yes

5 Multi 3-way CLL/Air Yes

6 TBI 3-way CLL/Air Yes

7 TBI 3-way + Ox CLL/Air Yes

8 TBI 3-way CLL/No air No

9 Carb 3-way + Ox CLL/Air Yes

For higher emitting vehicles, EPA has found technology type

distinctions to be superfluous for reasons outlined in Section

IV.A. Thus all light-duty vehicles fall into one of ten different

vehicle groups: either one of the nine normal emitter technology

groups, or the higher emitter group. The statistical regressions

that derived relationships between fuel parameters and exhaust

emissions made distinctions between these ten vehicle categories,

and so produced separate models (equations) for each. Since each

of these ten equations can give different emission results for

identical fuels, their results must be combined in such a way as to
 40 See EPA Memorandum from Joann Jackson-Stephens to Michael Sklar, "Reanalysis of 1990 Sales Fleet (CAFE)," March 1, 1993. Values from this memo

were normalized, since 1.41% of the 1990 vehicle sales did not fall into any of

the nine technology groups.

 41 See EPA Memorandum from Christian E. Lindhjem to Richard A. Rykowski,

"Effect of Oxygenates on Emissions," January 7, 1992.

71

reflect the contribution of each vehicle group to the overall inuse emissions of 1990 vehicles. 

The contribution of each of the nine technology groups given

in Table III-4 to the total mobile-source emissions inventory is

determined by two factors: the fraction of the 1990 sales fleet

accounted for by each type of vehicle (its sales weighting), and

the average emissions for each vehicle type. The sales weightings

were derived from reported 1990 light-duty vehicle and truck sales

reports submitted by vehicle manufacturers, and are equal to the

fraction of 1990 vehicles with the corresponding vehicle

technology40. Vehicle sales fractions were used to estimate the

fraction of total vehicle miles travelled by vehicles of a given

technology type. To compute the contribution of each technology

group to total emissions, the sales weightings were adjusted to

account for differences in the average level of total hydrocarbon

and NOx emissions from vehicles in each technology group, as

determined through the EPA Emission Factor program41. The sales and

technology group emissions weightings are given in Table III-5.

Table III-5: Sales Weightings and Emissions by Technology Group

Technology

group

Sales

weighting

Average

g/mi of

HC

Average

g/mi of

NOx

1 0.2631 0.278 0.519

2 0.2871 0.228 0.570

3 0.2181 0.230 0.479

4 0.1143 0.435 0.918

5 0.0431 0.179 0.389

6 0.0053 0.200 0.460

7 0.0525 0.389 0.613

8 0.0 -- --

9 0.0165 0.258 0.712
72

Note that technology group #8 has a sales weighting of 0.0%,

indicating that no vehicles with that particular technology type

were sold in 1990 in the U.S. For this reason, technology group #8

will be dropped from subsequent discussions, resulting in a set of

eight normal emitter technology groups numbered 1, 2, 3, 4, 5, 6,

7, and 9.

Within the normal emitter class, the relative weighting of the

emission results from each technology group is derived from the

combination of the sales weightings and the average emissions for

that technology group. The relative weighting for each technology

group, which applies only to normal emitting vehicles, was derived

from the following equation:

Technology group = Sales weighting * average emissions for the group 

 weighting (Sales weighting * technology group emission weighting)

This equation gives the values shown in Table III-6.

Table III-6: Technology Group Weightings for Normal Emitters

Technology group VOC weighting NOx weighting

1 0.26896 0.23842

2 0.24071 0.28573

3 0.18446 0.18241

4 0.18284 0.18321

5 0.02837 0.02927

6 0.00390 0.00426

7 0.07510 0.05619

9 0.01565 0.02051

Total 0.99999 1.00000

As stated before, a given vehicle can be categorized as a

normal emitter or a higher emitter. Since the weightings shown in

Table III-6 apply only to normal emitters, a weighting scheme that

applies to all vehicle groups' equations must combine the

weightings from Table III-6 with the in-use proportion of emissions

attributable to each emitter class. These proportions depend on

the inspection and maintenance (I&M) scenario assumed for each

Phase of the reformulated gasoline program. The fraction of

emissions attributable to normal and higher emitters for both

Phases are given in Table III-7.
73

Table III-7: Emitter Class Weightings By Pollutant and Phase

Phase I Phase II

VOC NOx VOC NOx

Normal emitters 0.52 0.82 0.444 0.738

Higher emitters 0.48 0.18 0.556 0.262

The final weightings that are applied to the performance estimates

for each of the nine separate vehicle group equations for each

exhaust pollutant are shown in Table III-8. The normal emitter

weightings are calculated from the product of the technology groupspecific weightings (Table III-6) and the normal emitter fraction

of total emissions (Table III-7). Since the five toxic species of

interest are also classified as VOCs, EPA has used the final VOC

weightings to weight the individual vehicle group equations for

each exhaust toxic pollutant as well.

Table III-8: Vehicle Group Weightings for the Complex Model

Vehicle group

Phase I Phase II

VOC NOx VOC NOx

Normals, technology

group #1

0.13986 0.19550 0.11942 0.17595

Normals, technology

group #2

0.12517 0.23430 0.10688 0.21087

Normals, technology

group #3

0.09592 0.14958 0.08190 0.13462

Normals, technology

group #4

0.09508 0.15023 0.08118 0.13521

Normals, technology

group #5

0.01475 0.02400 0.01260 0.02160

Normals, technology

group #6

0.00203 0.00349 0.00173 0.00314

Normals, technology

group #7

0.03905 0.04608 0.03334 0.04147

Normals, technology

group #9

0.00814 0.01682 0.00695 0.01514

Higher emitters 0.48000 0.18000 0.55600 0.26200
74

5. Summer Baseline Emissions

The MOBILE model was used as the basis for estimating fleetaverage gram/mile emissions from summer baseline fuel. However,

the MOBILE model is equipped only to provide emission estimates for

VOC and NOx. Therefore, baseline emissions for toxics were treated

separately. Accordingly, the first section below will present the

treatment of VOC and NOx baseline emissions, while the following

section will present the treatment of baseline emissions for

toxics. A table giving the summer baseline emissions for VOC, NOx,

and toxics is presented at the end of Section B.5.b.

a. VOC and NOx

To estimate gram/mile emissions of VOC and NOx from summer

baseline fuel, only the emissions from 1990 model year vehicles

could be considered. To implement this criterion while maintaining

a focus on in-use emissions from 1990 vehicles over their lifetime,

the MOBILE model was run in the year 2015 with all post-1990

vehicle programs turned off (Tier 1 standards are not included

because they do not apply to baseline 1990 vehicles). For the

summer season, the daily low and high temperatures modeled were 69

and 94°F, respectively, for Class B areas and 72 and 92°F,

respectively, for Class C areas (see Section B.1 above). The

conditions under which the baseline emission values were determined

for Phases I and II are shown below:

Phase I:  July 11, 1991 version of MOBILE4.1 

 Light-duty vehicles (i.e., passenger cars) only

 Basic I/M program consisting of a 2200 rpm idle

test and a gas cap inspection

Phase II:  MOBILE5a

 Emissions from light-duty vehicles and light-duty

trucks were combined by weighting per-mile

emissions by the percentage of vehicle miles

traveled

 Inspection and maintenance program met EPA's recent

guidelines for enhanced I/M, including purge and

pressure checks

The Agency designed the Phase I conditions to be identical to the

conditions used for the simple model for the reasons outlined in

Section 4 of the preamble. The MOBILE model input file for Phase

I baseline emission estimates is given in Appendix III-A, while the

input file for Phase II baseline emission estimates is given in

Appendix III-B.

Although the MOBILE model provides gram/mile estimates of VOC

for both exhaust and nonexhaust, the Agency determined baseline

emissions slightly differently for these two emission categories.
 42 See Section IV.B below for details on the derivation of the

nonexhaust model for VOC

75

The reason for this is that the nonexhaust equations in the Complex

Model are based on a simple regression using emission estimates

from the MOBILE model for various RVPs.42 The MOBILE model output

is given in only two decimal places. Thus when the nonexhaust

regression equations are evaluated for an RVP of 8.7 psi (the RVP

of summer baseline gasoline), the resulting emission estimate for

nonexhaust VOC is slightly larger than the estimate provided

directly by the MOBILE model (e.g. 0.492 g/mi vs. 0.483 g/mi for

Phase II, Class C). The Agency has determined that the regression

equations are more representative of the true relationship between

VOC emissions and RVP than the data derived directly from the

MOBILE model because of the error introduced in the MOBILE model

output through rounding. Therefore, the nonexhaust VOC baseline

values were derived from regressions based on the emissions from

the MOBILE model instead of from the MOBILE model output directly.

The exhaust VOC baseline values, on the other hand, were taken

directly from the MOBILE model output since MOBILE provided the

only source of baseline exhaust emission estimates.

As discussed in the February 1993 NPRM [58 FR 17175], the

definition of ozone-forming VOCs was changed to match EPA guidance

that all VOC emission estimates be in terms of nonmethane,

nonethane hydrocarbon emissions. The official version of MOBILE4.1

and MOBILE5a both provide VOC estimates in this form directly.

However, the July 11, 1991 version of MOBILE4.1 (the MOBILE model

used to develop the simple model and the Phase I baseline

emissions) gives VOC as nonmethane hydrocarbons only. When using

VOC values from the interim version of MOBILE4.1, then, it is

necessary to back out the fraction of ethane. Based on an analysis

of the Complex Model database, the Agency determined that the

average ethane content was approximately 2.95% of exhaust

nonmethane hydrocarbon emissions. This value would be expected to

change as changes are made to the Complex Model database, but not

to such a degree that the Phase I reformulated gasoline program

would be affected. Thus the VOC baseline emission values for Phase

I were reduced from 0.46 g/mi nonmethane VOC to 0.446 g/mi

nonmethane, nonethane VOC by subtracting 2.95% from the nonmethane

baseline emission estimate.

The baseline emissions for VOC and NOx as derived from the

MOBILE model are summarized in Table III-9.
76

Table III-9: Summer Baseline Emissions for VOC and NOx

Phase I Phase II

Class B Class C Class B Class C

Exhaust VOC, g/mi 0.446 0.446 0.907 0.907

Nonexhaust VOC, g/mi 0.860 0.769 0.559 0.492

NOx, g/mi 0.660 0.660 1.340 1.340

In addition to the fleet-average baseline emissions, emitter

class-specific baseline emissions are also needed to calculate the

overall emissions performance of reformulated and conventional

fuels. To derive emitter class-specific baseline emissions, the

fleet and emission inventories must first be apportioned by emitter

class. The database on which the MOBILE model is based provided

this information. No statistically significant differences in NOx

emissions between normal and higher emitters were found. The fleet

and emission inventories are shown in Tables 10 and 11 for Phase I

and Phase II, respectively.

Table III-10: Phase I Summer Fleet and Emissions Inventory

Normal

Emitters

High

Emitters

Overall

Fleet

Fraction of in-use fleet 0.82 0.18 1.00

Fraction of VOC inventory

Exhaust VOC emissions, g/mi/car

0.52

0.283

0.48

1.189

1.00

0.446

Fraction of NOx inventory

NOx emissions, g/mi/car

0.82

0.66

0.18

0.66

1.00

0.66

Table III-11: Phase II Summer Fleet and Emissions Inventory

Normal

Emitters

High

Emitters

Overall

Fleet

Fraction of in-use fleet 0.836 0.164 1.00

Fraction of VOC inventory

Exhaust VOC emissions, g/mi/car

0.444

0.482

0.556

3.075

1.00

0.907

Fraction of NOx inventory

NOx emissions, g/mi/car

0.82

1.34

0.18

1.34

1.00

1.34
77

VOC baseline emissions for each emitter class were determined

by using the following equation, as proposed in the draft

Regulatory Impact Analysis:

EFI x ABE = EFF x EBE

where,

ABE = Baseline emissions for the fleet (g/mile)

EBE = Baseline emissions for an individual emitter class (g/mile)

EFF = Emitter class fraction of vehicles in the fleet 

EFI = Emitter class fraction of the emissions inventory

ABE, EFF, and EFI are derived from the MOBILE model database, and

are given in Tables 10 and 11 above.

b. Toxics

As stated previously, the MOBILE model does not provide

emission estimates for toxic compounds. Thus the baseline

emissions for toxics must come from another source. In addition,

toxic compounds must be treated separately when estimating exhaust

and nonexhaust baseline emissions, since exhaust baseline toxic

values are derived mainly from the Complex Model database, while

nonexhaust baseline toxic values are computed directly from the

nonexhaust Complex Model in conjunction with General Motor's vapor

model. Baseline emissions of exhaust POM are also treated uniquely

due to the lack of POM emissions data. Baseline levels of these

three types of summer toxics emissions (exhaust other than POM,

nonexhaust, and POM) will be discussed separately in this section.

The Agency has determined that of the five toxic compounds

that must be regulated in the reformulated gasoline and antidumping programs, benzene is the only one that appears in

nonexhaust emissions since it is the only regulated toxic compound

naturally occurring in gasoline. As described in Section IV.B, the

nonexhaust benzene portion of the Complex Model is derived from the

General Motors (GM) vapor equilibrium model. This GM model

estimates the fraction of benzene in the vapors above a pool of

fuel (conditions simulating a vehicle's fuel tank). The Agency

executed a linear regression on the output from the GM model, and

combined the resulting regression equations with the nonexhaust VOC

equations. Thus the Agency converted benzene fraction estimates

into a model that provides benzene emission estimates in

grams/mile. For details on the development of the nonexhaust

model, see Section IV.B below.

Since the nonexhaust VOC model is based on emission estimates

produced from the MOBILE model, the nonexhaust benzene equations in

the Complex Model are the most appropriate source for determining

baseline emissions of benzene. Deriving the nonexhaust benzene
78

baseline emissions from the Complex Model is also consistent with

the method described above for determining baseline emissions for

nonexhaust VOC. Thus the summer baseline fuel was simply run

through the nonexhaust benzene portion of the Complex Model to

determine the baseline emissions of nonexhaust benzene. The

results are shown in Table III-12:

Table III-12: Summer Nonexhaust Benzene Baseline Emissions

Class B Class C

Phase I

Phase II

9.659

6.241

8.633

5.505

To determine baseline emissions for exhaust toxics, the most

complete source of information is the Complex Model database. The

Agency therefore performed an analysis of the toxic emissions data

in the Complex Model database to determine the average emissions of

each toxic pollutant. In this analysis, only the observations used

in the development of the Complex Model equations for toxic

compounds were considered. Normal emitter averages were estimated

separately from higher emitter averages. Also, the normal emitter

averages were derived separately for each technology group to mimic

the development of the Complex Model for normal emitters. For the

same reason, technology group distinctions were not made in the

analysis of the higher emitter averages. Average VOC emissions

were also calculated for the same observations. The results of

this analysis for normal emitters are shown in Tables 13 through

16, while the higher emitter results are shown in Table III-17.
79

Table III-13: Exhaust Benzene and VOC Emissions for Normal

Emitters

TECHNOLOGY

TYPE

NUMBER OF

OBSERVATIONS

EXHAUST

EMISSION

VARIABLE

MEAN

EMISSIONS

(mg/mile)

RATIO*

1 598 BENZENE 9.724 0.0504

VOC 193.0

2 431 BENZENE 11.11 0.0484

VOC 229.7

3 300 BENZENE 10.73 0.0538

VOC 199.5

4 138 BENZENE 8.086 0.0333

VOC 242.9

5 22 BENZENE 12.82 0.0398

VOC 322.4

6 70 BENZENE 27.58 0.0626

VOC 440.7

7 21 BENZENE 9.492 0.0402

VOC 235.8

9 8 BENZENE 6.449 0.0574

VOC 112.3

*

RATIO = MEAN EXHAUST BENZENE EMISSIONS/MEAN EXHAUST VOC EMISSIONS
80

Table III-14: Exhaust 1,3-Butadiene and VOC Emissions for Normal

Emitters

TECHNOLOGY

TYPE

NUMBER OF

OBSERVATIONS

EXHAUST

EMISSION

VARIABLE

MEAN

EMISSIONS

(mg/mile)

RATIO*

1 574 1,3-BD 1.225 0.00639

VOC 191.8

2 428 1,3-BD 1.599 0.00695

VOC 230.2

3 277 1,3-BD 1.056 0.00512

VOC 206.1

4 132 1,3-BD 0.868 0.00363

VOC 239.2

5 21 1,3-BD 1.951 0.00611

VOC 319.4

6 70 1,3-BD 2.154 0.00489

VOC 440.7

7 21 1,3-BD 0.791 0.00336

VOC 235.8

9 5 1,3-BD 0.824 0.00751

VOC 109.7

*

RATIO = MEAN EXHAUST 1,3-BUTADIENE EMISSIONS/MEAN EXHAUST VOC

EMISSIONS
81

Table III-15: Exhaust Acetaldehyde and VOC Emissions for Normal

Emitters

TECHNOLOGY

TYPE

NUMBER OF

OBSERVATIONS

EXHAUST

EMISSION

VARIABLE

MEAN

EMISSIONS

(mg/mile)

RATIO*

1 528 ACET 0.9725 0.00519

VOC 187.4 

2 427 ACET 1.225 0.00531

VOC 230.5

3 276 ACET 1.263 0.00633

VOC 199.4

4 134 ACET 1.638 0.00680

VOC 241.0

5 21 ACET 1.014 0.00315

VOC 322.2

6 66 ACET 2.883 0.00655

VOC 440.0

7 21 ACET 1.019 0.00432

VOC 235.8

9 8 ACET 0.9363 0.00834

VOC 112.3

*

RATIO = MEAN EXHAUST ACETALDEHYDE EMISSIONS/MEAN EXHAUST VOC

EMISSIONS
82

Table III-16: Exhaust Formaldehyde and VOC Emissions for Normal

Emitters

TECHNOLOGY

TYPE

NUMBER OF

OBSERVATIONS

EXHAUST

EMISSION

VARIABLE

MEAN

EMISSIONS

(mg/mile)

RATIO*

1 529 FORM 2.336 0.0125

VOC 187.4

2 425 FORM 2.727 0.0118

VOC 230.3

3 277 FORM 3.037 0.0152

VOC 199.8

4 135 FORM 5.715 0.0237

VOC 240.7

5 21 FORM 2.438 0.00757

VOC 322.2

6 70 FORM 6.431 0.0146

VOC 440.7

7 21 FORM 2.754 0.0117

VOC 235.8

9 8 FORM 3.091 0.0275

VOC 112.3

*

RATIO = MEAN EXHAUST FORMALDEHYDE EMISSIONS/MEAN EXHAUST VOC

EMISSIONS
83

Table III-17: Average Toxic and VOC Emissions from Higher Emitters

Number of

observations

Average

toxic

emissions,

mg/mi

Average

VOC

emissions,

mg/mi Ratio*

Benzene

1,3-Butadiene

Acetaldehyde

Formaldehyde

269

270

269

269

95.05

23.85

11.45

27.60

2082

2117

2117

2116

0.0457

0.0113

0.00541

0.0130

*RATIO = MEAN EXHAUST TOXIC EMISSIONS/MEAN EXHAUST VOC EMISSIONS

The toxics emission inventory is expected to be roughly

proportional to the VOC inventory because toxics are by definition

volatile organic compounds (though the effects of fuel

modifications on toxics emissions are expected to differ from the

effects of the same fuel modifications on exhaust VOC emissions).

Therefore, ratios of the average emissions of each toxic pollutant

with respect to the average emissions of VOCs for the same

observations were also calculated. These ratios were used to

compensate for the fact that the observations which contributed to

the average values in Tables 13-17 were not based only on summer

baseline fuel and were not based on vehicles with representative

in-use VOC emission levels. Summer baseline emission values for

exhaust toxics were calculated using the following procedure:

1. The normal emitter toxic emission ratios from Tables 13

through 16 were weighted by the normal emitter technology

group weighting factors. The normal emitter technology

group weighting factors were derived in Subsection

III.B.4 above, and are given in Table III-6. They

represent the fraction of the mobile source emissions

inventory for normal emitters that comes from each

technology group. 

2. The weighted ratios from step (1) were summed to obtain

a single, fleet-average ratio for each toxic emission for

normal emitters as shown in Table III-18. This step

yields overall toxic-to-VOC ratios for normal emitters

that are analogous to the values presented for higher

emitters in Table III-17.
84

Table III-18: Average Toxic and VOC Emissions from Normal

Emitters

Number of

observations Ratio*

Benzene

1,3-Butadiene

Acetaldehyde

Formaldehyde

1588

1528

1481

1486

0.0465

0.00556

0.00566

0.0149

*RATIO = MEAN EXHAUST TOXIC EMISSIONS/MEAN EXHAUST VOC EMISSIONS

3. The ratios in Tables 17 and 18 are based on all the

available data in the Complex Model database for which

both toxics and NMHC data were available. Since these

ratios are not based strictly on summer baseline

gasoline, they cannot provide the toxic baseline

emissions for summer baseline fuel. To convert the

ratios from Tables 17 and 18 into ratios that reflect the

effect of summer baseline fuel on toxic emissions when

used in representative in-use 1990 vehicles, a correction

was made. This correction was carried out in two steps.

The first step corrected for the fact that the toxic

emission averages are not based on summer baseline

gasoline. The second step corrected for the fact that

the VOC emission averages are not based on summer

baseline gasoline. These two corrections were performed

sequentially:

3.1) The average value of each fuel parameter was determined

for the same observations that were used to determine the

average toxics and VOC values in Table III-17 and 18.

This step was performed separately for the normal and

higher emitter observations, and for each toxic. Thus

there were a total of eight "average" fuel descriptions.

Discrepancies between these average fuels and summer

baseline fuel caused discrepancies between the ratios in

Tables 17 and 18 and the true ratios for summer baseline

gasoline. The average fuels for each toxic are given in

Tables 19 and 20.
85

Table III-19: Average Fuels for Normal Emitters

Benzene

1,3-

Butadiene

AcetaldehydeFormaldehyde

MTBE, wt% oxygen

ETBE, wt% oxygen

Ethanol, wt% oxygen

TAME, wt% oxygen

Sulfur, ppm

RVP, psi

E200, percent evap

E300, percent evap

Aromatics, vol%

Olefins, vol%

Benzene, vol%

1.236

0.021

0.198

0.015

218.6

8.264

47.55

84.94

28.58

7.943

0.953

1.254

0.022

0.199

0.014

220.4

8.268

47.49

84.90

28.41

7.969

0.921

1.311

0.023

0.206

0.013

218.3

8.248

48.43

85.28

28.15

8.028

0.966

1.313

0.021

0.209

0.013

217.9

8.249

48.43

85.31

28.14

8.005

0.964

Table III-20: Average Fuels for Higher Emitters

Fuel parameter Benzene

1,3-

Butadiene

AcetaldehydeFormaldehyde

MTBE, wt% oxygen

ETBE, wt% oxygen

Ethanol, wt% oxygen

TAME, wt% oxygen

Sulfur, ppm

RVP, psi

E200, percent evap

E300, percent evap

Aromatics, vol%

Olefins, vol%

Benzene, vol%

1.457

0.020

0.361

0.009

255.5

7.810

52.49

84.54

26.03

5.699

0.871

1.466

0.020

0.346

0.009

255.7

7.803

52.51

84.57

25.98

5.692

0.867

1.464

0.010

0.360

0.009

255.7

7.810

52.55

84.60

25.98

5.683

0.868

1.457

0.020

0.360

0.009

254.6

7.812

52.56

84.62

26.01

5.667

0.867

3.2) The Complex Model was used to determine a multiplicative

factor to convert emissions of each toxic for the average

fuel into emissions of each toxic for summer baseline

fuel. This step was accomplished by evaluating the

normal emitter toxic equations with the fuels from Table

III-19, evaluating the higher emitter toxic equations

with the fuels from Table III-20, and evaluating both

normal and higher emitter toxic equations with summer

baseline fuel. The multiplicative factor can then be

written as follows:

Toxic correction factor = exp(f(b))/exp(f(a))
86

where f is the normal or higher emitter polynomial

equation for the toxic of interest, b is summer baseline

gasoline, and a is the average fuel from either Table

III-19 or Table III-20. The toxic emission correction

factors are given in Table III-21.

Table III-21: Toxic Emission Correction Factors

Toxic pollutant

Normal emitter

correction factor

Higher emitter

correction factor

Benzene

1,3-Butadiene

Acetaldehyde

Formaldehyde

1.371

1.121

1.011

0.9373

1.500

1.402

0.9970

0.8151

3.3) The ratios from Tables 17 and 18 were multiplied by the

appropriate toxic correction factors from Table III-21.

This step converted the toxics portion of each ratio to

a value representing the toxic emissions from summer

baseline gasoline.

3.4) Beginning with the same average fuels, the Complex Model

was used to determine a multiplicative factor that will

convert VOC emissions for the average fuel to VOC

emissions for summer baseline fuel. This step was

accomplished by evaluating the normal emitter VOC

equation with the fuels from Table III-19, evaluating the

higher emitter VOC equation with the fuels from Table

III-20, and evaluating both normal and higher emitter VOC

equations with summer baseline fuel. The multiplicative

factor can then be written as follows:

VOC correction factor = exp(g(a))/exp(g(b))

where g is the normal emitter polynomial equation for

VOC, a is the average fuel from Tables 19 and 20, and b

is summer baseline gasoline. Note that the VOC

correction factor in this step has the reciprocal form of

the factor given in step (3.2) because this step is

correcting the denominator of each ratio instead of the

numerator. The VOC correction factors are given in Table

III-22.
87

Table III-22: VOC Emission Correction Factors

Toxic pollutant

Normal emitter

correction factor

Higher emitter

correction factor

Benzene

1,3-Butadiene

Acetaldehyde

Formaldehyde

0.8685

0.8694

0.8606

0.8603

0.9045

0.9039

0.9042

0.9044

3.6) The ratio from step (3.3) was multiplied by the

appropriate factors from Table III-22. This step

converts the VOC portion of each ratio to a value

representing the VOC emissions from summer baseline

gasoline. The ratios from Tables 17 and 18 were now

fully corrected to represent summer baseline gasoline,

and are shown in Table III-23.

Table III-23: Corrected Toxic:VOC Ratios

Toxic pollutant

Normal emitter

ratio

Higher

emitter

ratio

Benzene

1,3-Butadiene

Acetaldehyde

Formaldehyde

0.0554

0.00542

0.00492

0.0120

0.0620

0.0143

0.00488

0.00962

4. Each of the four normal emitter toxic emission ratios

from Table III-23 was multiplied by the Phase I VOC

baseline for normal emitters, which is 283 mg/mi (Table

III-10). For the higher emitter ratios, each value from

Table III-23 was multiplied by the Phase I VOC baseline

for higher emitters, which is 1189 mg/mi. This step

produced the Phase I normal and higher emitter toxics

baselines as shown in Table III-24.
88

Table III-24: Phase I Summer Toxic Baseline Emissions by Emitter

Class

Toxic pollutant Normal emitter

baseline, mg/mi

Higher emitter

baseline, mg/mi

Benzene

1,3-Butadiene

Acetaldeyhde

Formaldehyde

15.66

1.533

1.391

3.404

73.68

16.98

5.799

11.44

5. The normal and higher emitter toxic baselines were

weighted by the fraction of the in-use fleet attributable

to each emitter class, and the results were summed to

obtain the final Phase I toxic baseline emissions. The

fraction of the VOC inventory for Phase I is given in

Table III-10. The final Phase I exhaust toxic baseline

emissions for summer are shown in Table III-25.

Table III-25: Phase I Summer Toxic Baseline Emissions

Toxic pollutant Baseline, mg/mi

Benzene

1,3-Butadiene

Acetaldeyhde

Formaldehyde

26.10

4.313

2.185

4.850

6. To obtain Phase II summer baseline emissions for toxics,

steps 4 and 5 were repeated using Phase II VOC baselines

and fleet fractions (Table III-11). The ratios from

Table III-23 were multiplied by 482 and 3075 mg/mi for

normal and higher emitters, respectively, and the

resulting emitter class-specific baseline emission values

were combined via the Phase II in-use fleet fractions of

0.836 and 0.164 for normal and higher emitters,

respectively. The final Phase II exhaust toxic baseline

emissions for summer are shown in Table III-26.
89

Table III-26: Phase II Summer Toxic Baseline Emissions

Toxic pollutant Baseline, mg/mi

Benzene

1,3-Butadiene

Acetaldeyhde

Formaldehyde

53.54

9.382

4.440

9.697

Data on polycyclic organic material (POM) were extremely

limited since very few test programs had the capability of

measuring POM. The lack of data required EPA to pursue a different

approach to establish baseline emissions for POM. An analysis of

the limited data available to EPA showed that (1) POM emissions

were proportional to exhaust VOC emissions, and (2) the

proportionality constant is 0.003355. Thus the POM baseline can be

determined from the exhaust VOC baseline for both Phase I and II in

the following manner:

Phase I: POM baseline = 0.003355 x exhaust VOC baseline

POM baseline = 0.003355 x 0.446 g/mi x 1000 mg/g

POM baseline = 1.496 mg/mi

Phase II: POM baseline = 0.003355 x exhaust VOC baseline

POM baseline = 0.003355 x 0.907 g/mi x 1000 mg/g

POM baseline = 3.043 mg/mi

The final summer baseline emissions are shown in Table III-27.

Table III-27: Summer Baseline Emissions in mg/mile

Phase I Phase II

Class B Class C Class B Class C

Exhaust VOC

Nonexhaust VOC

NOx

Exhaust benzene

Nonexhaust benzene

Acetaldehyde

Formaldehyde

1,3-Butadiene

POM

446.00

860.48

660.00

26.10

9.66

2.19

4.85

4.31

1.50

446.00

769.10

660.00

26.10

8.64

2.19

4.85

4.31

1.50

907.00

559.31

1340.00

53.54

6.25

4.44

9.70

9.38

3.04

907.00

492.07

1340.00

53.54

5.51

4.44

9.70

9.38

3.04
90

6. Winter Baseline Emissions

The calculation of winter baseline emissions was approached in

a very different manner than used to estimate summer baseline

emissions. EPA chose to use a different approach since

insufficient testing has been done under winter conditions to

develop a separate Complex Model for the winter season. The Agency

determined that the MOBILE emissions model provided the most

appropriate sources of information on the fleet-average emissions

produced when using winter baseline fuel.

One simplifying factor in the determination of winter baseline

emissions is that, as discussed in Section IV.E below, the Agency

has determined that emissions of nonexhaust VOC and benzene under

winter conditions should be set to zero. Thus baseline nonexhaust

emissions under winter conditions do not need to be calculated.

Many aspects of the derivation of winter baseline emissions

parallel the derivation of summer baseline emissions. Thus this

section will treat VOC and NOx separately from toxics for the

reasons discussed in Section B.5 above.

a. VOC and NOx

The MOBILE model was run in a manner identical to that

discussed above for the derivation of summer baseline emissions of

exhaust VOC and NOx, but with two exceptions. First, minimum and

maximum wintertime temperatures of 39 o

F and 57 oF were used in

place of the summer temperature ranges. Second, the winter

baseline fuel was used in place of the summer baseline fuel. The

remaining details of running the MOBILE model to determine winter

baseline emissions of exhaust VOC and NOx are shown below:

Phase I:  July 11, 1991 version of MOBILE4.1 

 Light-duty vehicles (i.e., passenger cars) only

 Basic I/M program consisting of a 2200 rpm idle

test and a gas cap inspection

Phase II:  MOBILE5a

 Emissions from light-duty vehicles and light-duty

trucks were combined by weighting per-mile

emissions by the percentage of vehicle miles

traveled

 Inspection and maintenance program met EPA's recent

guidelines for enhanced I/M, including purge and

pressure checks

These conditions are identical to those used to develop the summer

baseline emission estimates. Winter VOC baseline emissions for

Phase I were corrected to reflect nonmethane, nonethane

hydrocarbons in a manner identical to that used to correct summer
91

VOC baseline emissions. The final winter baseline emissions for

exhaust VOC and NOx are shown in Table III-28.

Table III-28: Winter Baseline Emissions for VOC and NOx

Phase I Phase II

Class B Class C Class B Class C

Exhaust VOC, g/mi 0.660 0.660 1.341 1.341

Nonexhaust VOC, g/mi 0.000 0.000 0.000 0.000

NOx, g/mi 0.750 0.750 1.540 1.540

In addition to the fleet-average baseline emissions, emitter

class-specific baseline emissions were calculated using the same

method discussed in Section B.5 above for summer baseline

emissions. The emitter class fractions of the VOC inventory and

in-use fleet are the same in the summer and the winter, so

differences between summer and winter emitter class-specific

baseline emissions are derived solely from differences in fleetaverage baseline emissions. As with the summer baseline emissions,

no statistically significant differences in NOx emissions between

normal and higher emitters were found. The fleet and emission

inventories for winter are shown in Tables 29 and 30 for Phase I

and Phase II, respectively.

Table III-29: Phase I Winter Fleet and Emissions Inventory

Normal

Emitters

Higher

Emitters

Overall

Fleet

Fraction of in-use fleet 0.82 0.18 1.00

Fraction of VOC inventory

Exhaust VOC emissions, g/mi/car

0.52

0.419

0.48

1.760

1.00

0.660

Fraction of NOx inventory

NOx emissions, g/mi/car

0.82

0.75

0.18

0.75

1.00

0.75
92

Table III-30: Phase II Winter Fleet and Emissions Inventory

Normal

Emitters

Higher

Emitters

Overall

Fleet

Fraction of in-use fleet 0.836 0.164 1.00

Fraction of VOC inventory

Exhaust VOC emissions, g/mi/car

0.444

0.712

0.556

4.546

1.00

1.341

Fraction of NOx inventory

NOx emissions, g/mi/car

0.82

1.54

0.18

1.54

1.00

1.54

VOC baseline emissions for each emitter class were determined

using the same relationship described in Section B.5 above:

EFI x ABE = EFF x EBE

where,

ABE = Baseline emissions for the fleet (g/mile)

EBE = Baseline emissions for an individual emitter class (g/mile)

EFF = Emitter class fraction of vehicles in the fleet 

EFI = Emitter class fraction of the emissions inventory

ABE, EFF, and EFI are derived from the MOBILE model database, and

are given in Tables 29 and 30 above.

b. Toxics

As stated previously, the Agency has determined that

nonexhaust emissions are negligible in the winter. Therefore only

exhaust toxic baseline emissions need be determined. Winter

emissions of benzene, 1,3-butadiene, acetaldehyde, and formaldehyde

are discussed first, followed by a brief discussion of POM. A

table giving all the winter baseline emissions is presented at the

end of this subsection.

The steps in the derivation of winter baseline emissions for

exhaust toxics parallel those presented in Section B.5.b above for

summer baseline toxic emissions. Indeed, steps (1) and (2) are

identical in both cases. Deviations from the summer baseline

emission derivation procedure begin in step 3 and are detailed

below:

3. Since the ratios in Tables 17 and 18 represent average

fuels in the Complex Model database, they cannot provide

the toxic baseline emissions for winter baseline fuel.

The conversion of the ratios from Tables 17 and 18
93

required the same six steps that are described for the

summer scenario (i.e. steps 3.1 to 3.6), with the single

exception that winter baseline fuel replaced summer

baseline fuel in all calculations. The final, corrected

ratios representing winter baseline gasoline are given in

Table III-31.

Table III-31: Corrected Toxic:VOC Ratios for Winter

Toxic pollutant

Normal emitter

ratio

Higher

emitter

ratio

Benzene

1,3-Butadiene

Acetaldehyde

Formaldehyde

0.0509

0.00601

0.00544

0.0134

0.0635

0.0164

0.00538

0.00983

4. Each of the four normal emitter toxic emission ratios

from Table III-31 were multiplied by the Phase I winter

VOC baseline for normal emitters, which is 419 mg/mi

(Table III-29). For the higher emitter ratios, each

value from Table III-31 was multiplied by the Phase I

winter VOC baseline for higher emitters, which is 1760

mg/mi. This step produced Phase I normal and higher

emitter baselines as shown in Table III-32.

Table III-32: Phase I Winter Toxic Baseline Emissions by Emitter

Class

Toxic pollutant Normal emitter

baseline, mg/mi

Higher emitter

baseline, mg/mi

Benzene

1,3-Butadiene

Acetaldeyhde

Formaldehyde

21.29

2.515

2.277

5.625

111.7

28.95

9.463

17.31

5. The normal and higher emitter toxic baselines were

weighted by the fraction of the in-use fleet attributable

to each emitter class, and the results were summed to

obtain the final Phase I toxic baseline emissions. The

fraction of the VOC inventory for Phase I is given in

Table III-29. The final Phase I exhaust toxic baseline

emissions for summer are shown in Table III-33.
94

Table III-33: Phase I Winter Toxic Baseline Emissions

Toxic pollutant Baseline, mg/mi

Benzene

1,3-Butadiene

Acetaldeyhde

Formaldehyde

37.57

7.273

3.571

7.728

6. To obtain Phase II winter baseline emissions for toxics,

steps 4 and 5 were repeated using Phase II VOC baselines

and fleet fractions (Table III-30). Thus the ratios from

Table III-31 were multiplied by 712 and 4546 mg/mi for

normal and higher emitters, respectively, and the

resulting emitter class-specific baseline emission values

were weighted via the Phase II in-use fleet fractions of

0.836 for normal emitters and 0.164 for higher emitters.

The final Phase II exhaust toxic baseline emissions for

winter are shown in Table III-34.

Table III-34: Phase II Winter Toxic Baseline Emissions

Toxic pollutant Baseline, mg/mi

Benzene

1,3-Butadiene

Acetaldehyde

Formaldehyde

77.62

15.84

7.248

15.34

The winter POM baseline can be determined from the exhaust VOC

baseline for both Phase I and II with the following equations:

Phase I: POM baseline = 0.003355 x exhaust VOC baseline

POM baseline = 0.003355 x 0.660 g/mi x 1000 mg/g

POM baseline = 2.214 mg/mi

Phase II: POM baseline = 0.003355 x exhaust VOC baseline

POM baseline = 0.003355 x 1.341 g/mi x 1000 mg/g

POM baseline = 4.499 mg/mi

The final winter baseline emissions are shown in Table III-35.
95

Table III-35: Winter Baseline Emissions in mg/mile

Phase I Phase II

Exhaust VOC

Nonexhaust VOC

NOx

Exhaust benzene

Nonexhaust benzene

Acetaldehyde

Formaldehyde

1,3-Butadiene

POM

660.00

0.00

750.00

37.57

0.00

3.571

7.728

7.273

2.214

1341.00

0.00

1540.00

77.62

0.00

7.248

15.34

15.84

4.499

7. Response to Comments

A number of comments have been received concerning the use of

the MOBILE model for determining both the baseline emissions for

VOC and NOx and the nonexhaust VOC model. Some commenters

questioned the appropriateness of using MOBILE4.1 in place of the

more recent MOBILE5a. The Agency continues to believe that

retention of a MOBILE4.1-derived baseline maintains a consistent

baseline and exhaust:nonexhaust ratio throughout Phase I. This

consistency also allows refiners the lead time they require in

order to comply with baseline changes when they reach Phase II in

2000. These points are discussed in more detail in Section B above

and in Section III of the preamble.

Other commenters asserted that the MOBILE models have become

an integral part of the RFG rulemaking process, and should

therefore be subject to a notice and comment period. The MOBILE

models are publicly available, and the EPA has considered comments

on their results, as used in this rulemaking, to be valid.

However, EPA does not consider the MOBILE models themselves to be

subject to notice and comment provisions since they do not, by

themselves, constitute a rule. EPA has conducted public workshops

on the various iterations of the MOBILE model, including MOBILE5,

at which it solicited suggestions and input from the public. The

resulting models represent EPA's understanding of the impact of

various conditions and policy options on emissions from mobile

sources; since the Agency does not have access to a superior source

of such information, the Agency has chosen to utilize the MOBILE

models to help analyze the impact of its rules on mobile source

emissions.
96

C. Appendices

Appendix III-A: MOBILE4.1 Input File Used to Develop the

Simple Model and the Phase I Complex Model

(must be run with interim version of

MOBILE4.1)

Appendix III-B: MOBILE5a Input File Used To Develop the Phase

II Complex Model
97

Appendix III-A: MOBILE4.1 Input File Used to Develop the

Simple Model and the Phase I Complex Model

(must be run with interim version of

MOBILE4.1)

1 PROMPT - 

MOBILE4.1 v.7/11/91: Simple Model correlations 

1 TAMFLG - 

1 SPDFLG - 

1 VMFLAG - 

1 MYMRFG - 

1 NEWFLG - 

2 IMFLAG - enter I/M program 

1 ALHFLG - 

2 ATPFLG - enter ATP

2 RLFLAG - Stage II refueling controls

2 LOCFLG - enter LAP record once

1 TEMFLG - 

3 OUTFMT - print 112 column descriptive output format 

4 PRTFLG - print exhaust HC, CO and NOx results 

1 IDLFLG - 

3 NMHFLG - print VOC 

3 HCFLAG - print HC components 

83 20 68 20 00 00 100 1 1 2221 2 11 20 20 20

83 68 20 2221 11 100. 11111212

89 1 086 086

RegNeg C 71.6 91.6 11.5 08.7 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 08.5 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 08.3 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 08.1 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 07.9 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 07.7 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 07.5 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 07.2 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 07.0 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 08.7 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 08.5 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 07.8 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 07.6 89 1
98

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 07.4 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 07.2 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 07.0 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 06.8 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 06.6 89 1

1 15 19.6 75.0 20.6 27.3 20.6
99

Appendix III-B: MOBILE5a Input File Used To Develop the Phase

II Complex Model

1 PROMPT -

Phase II Complex model baseline runs for LDGVs & LDGTs

1 TAMFLG -

1 SPDFLG -

1 VMFLAG -

1 MYMRFG -

5 NEWFLG - no CAA mandates are modeled

2 IMFLAG - enter I/M program

1 ALHFLG -

8 ATPFLG - enter ATP; include pressure and purge checks

2 RLFLAG - enter Stage II

1 LOCFLG -

1 TEMFLG -

3 OUTFMT - print 112 column descriptive output format

1 PRTFLG - print exhaust & evap HC only

1 IDLFLG - 

3 NMHFLG - print VOC

2 HCFLAG - no HC components

83 20 68 20 03 03 096 1 1 2221 4211 0.80 20.0 2.00 Enhanced IM

83 84 20 2221 11 096. 12211111 ATP

83 83 20 2221 11 096. Pressure test

83 86 20 2221 11 096. Purge test

89 1 80. 60. Stage II

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 08.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 08.5 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 08.3 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 08.1 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 07.9 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 07.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 07.5 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 07.3 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 07.1 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 06.9 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 06.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 06.5 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1
100

................ B 69.4 94.0 09.5 08.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 08.5 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 08.3 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 08.1 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 07.9 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 07.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 07.5 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 07.3 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 07.1 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 06.9 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 06.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 06.5 90 1 1 1
101

IV. Complex Model

The Complex Model is designed to predict emissions as a

function of fuel properties. An empirical model is more

accurate, faster, cheaper and more practical to use than actual

vehicle testing in predicting the emission effects of fuel

modifications. Implicit in Section 211(k) the Clean Air Act, and

confirmed by actual test data, is the assumption that emissions

from vehicles can be linked to the properties of gasolines. The

vehicle itself has been found to be the single most significant

determinant of the level of emissions from any given vehicle; to

identify the effects of fuel property modifications on emissions,

EPA found it necessary to separate the emissions effect of each

vehicle from fuels' effects. The purpose of the Complex Models

developed in the following section is to be able to predict

emissions based on fuel properties which are readily measurable

and easily controllable. 

EPA has developed separate complex models for exhaust and

nonexhaust emissions which are based on entirely different data

sources. While the exhaust model is based on data from a number

of different test programs, the nonexhaust model is based on data

generated from EPA's ongoing nonexhaust emissions testing program

that has been used to develop EPA's MOBILE emission inventory

models. EPA believes this data to be sufficient to model the

relationship between fuel properties and nonexhaust VOC emissions

since nonexhaust emissions are better understood from a

theoretical standpoint and are influenced by fewer fuel

properties than are exhaust emissions.

The exhaust Complex Model described in the following 

sections has undergone some changes since it was proposed in the

February 1993 NPRM. These changes have been made in response to

the following factors:

 EPA's use of more appropriate data analysis methods

 EPA's improved understanding of the relationship

between fuel characteristics and emissions

 Comments received in response to the February NPRM,

public workshops, and EPA's docket submission that

described a number of alternative exhaust complex

models.

The Complex Model described below was developed through an open,

iterative process. EPA conducted six separate public workshops

to review various iterations of its models and formally submitted

five previous versions to the docket. As a result, the Complex

Model has been thoroughly peer reviewed, and EPA has considered

the suggestions and comments made by various parties seriously in

developing the model. While complete consensus between all

parties regarding the model and the process used to develop it
102

has not been achieved, the remaining differences are decidedly

minor.

A. Exhaust Emissions Model

When EPA began the model building process, several key

decisions had to be made regarding the selection of the

appropriate dependent and independent variables, the selection of

appropriate data, the selection of an appropriate modeling

method, and the choice of a simplification methodology. Each of

these decisions is reviewed in detail in Sections B.1 through B.5

below.

Fuels can be characterized in terms of a number of different

sets of fuel parameters. EPA used the results of individual fuel

studies, input from its public workshops, preliminary test

results, engineering intuition, available data, and ease of

measurement to select the set of fuel parameters used to model

exhaust emissions. The Complex Models include the effects of

fuel benzene (for benzene emissions only), aromatics, olefins,

RVP, E200, E300, sulfur, oxygen content and oxygenate type (for

acetaldehyde and formaldehyde emissions only) on emissions. 

Other parameters were considered by EPA but rejected after

considering the comments received at public workshops and the

available test data.

In the February 1993 proposal, EPA represented distillation

characteristics by parameters measuring the temperature at which

specified percentages of the fuel would have evaporated,

specifically T50 and T90 (representing the temperatures at which

50% and 90% of the fuel would have evaporated, respectively). At

the time of that proposal, EPA indicated that it might replace

these temperature-based parameters with parameters measuring the

percentage of fuel that had evaporated at a specified

temperature, specifically E200 and E300 (representing the

percentage of fuel that would evaporate at 200 degrees Fahrenheit

and 300 degrees Fahrenheit, respectively). Unlike the

temperature parameters, the percent evaporated parameters for a

mixture of two fuels can be estimated from a weighted average of

the percent evaporated values of its constituent blends, thereby

simplifying calculations for refiners and producers of gasoline. 

EPA has chosen to convert its models to a percent evaporated

basis since the NPRM was issued, removing the T50 and T90 terms

from its models in the process. The following correlations can be

used to convert any temperature basis values to percent

evaporated values:

E200 (%) = 147.91 - (0.49 x T50(in o

F))

E300 (%) = 155.49 - (0.22 x T90(in o

F))
103

These correlations were derived from the Complex Model fuels

database. A linear regression model was used to relate all

available E200 and E300 values to all corresponding T50 and T90

values in the database. Other non-linear relationships and

regressions were investigated, but they gave no more accurate

predictions and no greater explanatory power (in terms of the R2

of the correlations) than the simple linear relationships shown

above. Thus, EPA chose to use the linear relationships to

convert temperature-based distillation parameters to a percent

evaporated basis.

Separate models were developed for exhaust VOC, NOx, and

exhaust emissions of the five air toxics specified in Section

211(k), specifically benzene, 1,3-butadiene, formaldehyde,

acetaldehyde and polycyclic organic matter. Non-methane

hydrocarbon (NMHC) was used as the VOC model's dependent variable

for all runs; NMHC was converted to VOC by subtracting out the

approximately constant ethane fraction of NMHC (see Sections III

and IV.B.2). 

1. Data Sources

Since no single study of the effect of fuel modifications on

exhaust emissions was designed to look at effects of all fuel

parameters independently across their full range, EPA chose to

base its exhaust Complex Model on a number of studies. EPA used

all data submitted as long as the following conditions were met:

 The data were based on valid tests.

 Data were submitted to EPA in time for development of

the exhaust models.

 Data were based on tests of vehicles classified as

having "1990 technology" by the vehicles'

manufacturer.

 No evidence of inaccuracy, error, or

unrepresentativeness existed in the data.

Each of these points are discussed in more detail in Sections

A.1.a through A.1.c. Thus, the Complex Models described in this

section are based on data generated from a number of different

exhaust emission testing studies, rather than relying on the

results of a single test program. These models will be used to

estimate the exhaust emission performance of reformulated and

conventional gasolines based on their fuel properties.

a. Included Studies

The Complex Model database for exhaust emissions includes

data from the following studies:
104

- EPA's Emission Factors (EF) testing program, which is

designed to examine the effect of oxygenates on

emissions. Valid emissions data acquired through

approximately August 20, 1992 were used from the EF

testing program.

- The Auto/Oil Test Program: This program included a

number of distinct studies sponsored jointly by

companies in the automobile and oil industries. The

AMOT study (Auto/Oil-I) was parametrically designed to

examine the effects of aromatics, olefins, T90 and

oxygen (in the form of MTBE) on emissions. All

possible combinations of high and low values of each

parameter were tested. The Phase I and Phase II sulfur

studies (Auto/Oil-II and VIII) were designed to

determine the effects of different sulfur levels on

emissions. The RVP/Oxygenate study (Auto/Oil-VI) was

designed to isolate the effects of MTBE, ETBE, and

ethanol at different RVP levels on emissions. The TAME

study (Auto/Oil-IX) was designed to investigate the

effects on emissions when using TAME as the oxygenate. 

Matrix A, Matrix A2 and Matrix B heavy hydrocarbon

studies which were designed to investigate the effects

of E200 and E300 on exhaust emissions.

- The RVP/Oxygenate study sponsored by General Motors,

the California Air Resources Board, and the Western

States Petroleum Association (GM/CARB/WSPA), which

examined the effects of RVP, the driveability index

(defined as [T10 + (3 x T50) + (1.5 x T90)]), and

different oxygenates on emissions.

- The RVP/Oxygenate and Aromatics studies sponsored by

the American Petroleum Institute (API-RVP/OXY and APIAromatics). The API aromatics study was designed to

analyze the effects of different types of aromatics on

emissions; the API-RVP/OXY study was designed to

determine the effect of RVP, different oxygenates, and

temperature variations on emissions.

- Phase I and Phase II of EPA's reformulated gasoline

testing program, performed at Automotive Testing

Laboratories (ATL-I and ATL-II). ATL-I was designed to

examine the effects of sulfur, RVP, oxygen content, and

T90 on emissions. ATL-II was designed to study the

effects of oxygen content, oxygenate type, T50, T90,

distillation end point, olefins and heavy end aromatics

on emissions.

- ARCO's EC-X study, which was designed to examine the

effects of severe, multi-parameter reformulations
105

(involving changes in fuels' oxygen, sulfur,

distillation parameter, aromatics, and olefin levels)

on emissions.

- Chevron's distillation studies (Chevron studies A-F),

which examined the effects of T90, T50, T10,

driveability index, aromatics, and RVP on emissions.

- UNOCAL's reformulated gasoline study (#514C), which was

designed to study the effects of T10, T50, T90, fuel

octane, oxygen content, paraffins, olefins, RVP and

aromatics on emissions.

Additional information on the scope and intent of these

studies can be found in Air Docket A-92-12 [#II-G-1, December

1990; #II-G-2, January 1992; #II-G-3, January 1992; #II-G-4,

February 1992; #II-G-5, April 1992; #II-G-6, July 1991; #II-G-7,

July 1991; #II-G-8, #II-G-9, February 1992; #II-G-10, February

1991; and #II-G-11, February 1992].

b. Excluded Studies

Not all of the studies received by EPA were used to develop

the Complex Model. Studies were excluded from the database if

they did not meet the following conditions:

- The study must have based its emissions measurements on

appropriate Federal Test Procedure (FTP) driving

cycles, vehicle preparation cycles, and measurement

procedures. Emission measurements on different driving

cycles are not comparable to one another.

- The study must have tested at least one 1990 technology

vehicle [see EPA memorandum "1990 Baseline Vehicles,"

by Korotney and Machiele in Air Docket A-92-12,

November 30, 1993], since vehicles that did not have

1990-equivalent technology were excluded from the

database. As discussed in the preamble to this rule,

Congress specified that the emissions performance of

fuels were to be based on their performance in 1990

vehicles. EPA has interpreted this requirement to

extend to vehicles from other model years having

emission characteristics and emission control

technologies that were present in 1990 model year

vehicles, since such vehicles should respond similarly

to fuel modifications.

- The study results must have been submitted to EPA in

time for development of the Complex Model, i.e., by

June 1993.
106

- The study must have included vehicles from more than

one manufacturer in order to avoid bias that would not

be captured in EPA's technology group distinctions

(discussed in Sections IV.A.2.d and III.B.4). For

example, each manufacturer employs different catalyst

designs and computer controls that are not reflected in

EPA's technology group distinctions. A study which

included only one manufacturer's vehicles might detect

emission effects peculiar to that manufacturer's

vehicles.

- The study must have included sufficient quality control

measures to separate fuel effects from vehicle effects. 

Vehicle effects account for as much as 90% of the

observed variation in emissions and could, if not

properly controlled, overwhelm the effects of fuel

modifications.

Studies received by EPA that failed to meet one or more of these

criteria included: (1) The NIPER study, which contained no

vehicles with 1990-equivalent technology, (2) Toyota's

reformulated gasoline study, which included a small number of

Toyota vehicles and no vehicles from other manufacturers, and (3)

Auto/Oil's high emitter study, which did not maintain adequate

quality controls as discussed in Section A.1.c.

c. Excluded Tests

As discussed previously, all data were included in the

database unless strong evidence of inaccuracy, gross error, or

unrepresentative data existed. EPA recently revised its

definition of volatile organic compounds (VOCs) [see 57-FR-3941,

February 3, 1992 for details] to exclude methane, ethane and

various other substances, since these compounds have reactivities

that are considerably less than other hydrocarbon compounds. 

Since the Clean Air Act requirements for reformulated gasolines

call for reductions in "ozone forming volatile organic compounds"

(hereafter VOC's), EPA also excluded data in specific tests from

the database used to model VOC emissions if such tests did not

measure methane as well as total hydrocarbons. EPA has found

that the methane fraction of total hydrocarbon emissions tends to

be large and displays considerable variation across different

fuel reformulations. For tests that measured methane and total

hydrocarbons, the methane fraction averaged 14% but ranged from

6% to 22%. EPA has been unable to develop a model that

accurately predicts methane emissions or methane fraction of

total hydrocarbon emissions. Ethane, by contrast, comprises a

relatively small portion of hydrocarbon emissions, averaging

2.95% by mass of nonmethane hydrocarbons. In addition, EPA has

found the ethane fraction to be relatively stable (±0.9%) across

different fuel reformulations.
107

Because of this variation in methane fraction, EPA has

concluded that a model based on total hydrocarbons cannot be used

to estimate VOC (i.e., nonmethane, nonethane hydrocarbons). EPA

has concluded, however, that a model based on NMHC can be used to

estimate VOC since ethane is a small and relatively constant

fraction of NMHC. Some studies measured NMHC emissions directly;

other studies measured total hydrocarbon and methane emissions

separately, which allows calculation of NMHC via simple

subtraction. Approximately 20% of the data available to EPA in

studies that met the requirements outlined in Section A.1 above

contained neither separate methane and total hydrocarbon

measurements nor direct NMHC measurements. These data were

excluded from the database used to develop the complex exhaust

VOC model.

In certain situations, the equivalence ratio (EQR), a

calculated quantity which measures the ratio of the actual

air:fuel ratio to the ideal air:fuel ratio, has been found to

have a very strong influence on emissions [A-92-12 Docket

submittals #IV-E-3, December 1992; #II-E-6, December 1992; and

EPA memorandum by Rao and Sklar "Analysis of EQR for high

emitting vehicles," December 1993 ]. High variability in EQR is

correlated strongly with high variability in measured emissions. 

High variability in EQR occurs more often in higher emitting

vehicles than in normal emitting vehicles (the distinction

between normal and higher emitters is discussed in greater detail

in Sections IV.A.2.d and III.B.4). EPA's analysis showed that

higher emitting vehicles that are not stabilized [A-92-12 Docket

submittals #II-B-14, February 1993; and #II-B-12, February 1993]

prior to emissions testing exhibit large variations in both EQR

and exhaust emission levels. For this reason, data from higher

emitting vehicles which were not stabilized prior to being tested

were excluded from the database. This led to the exclusion of

the entire Auto/Oil high emitter study, as well as all data from

higher emitting vehicles tested in the EPA/EF emissions factor

testing program.

Finally, all data from tests on Fuel W in EPA's ATL-II

program were excluded from the database. Fuel W was created by

blending pure chemicals, instead of being composed of typical

refinery streams; over one-fourth of the fuel consisted of pure

cyclohexane. Since Fuel W's emissions effects differed

dramatically from the emissions effects from gasolines with

nearly identical sulfur, aromatics, olefin, E200, E300, oxygen,

and RVP levels, and since Fuel W's chemical composition differed

dramatically from such gasolines, EPA chose to exclude all Fuel W

data from the Complex Model database.

d. Excluded Vehicles and 1990 Model Year Technology Vehicles
108

Section 211(k)(10)(A) of the Clean Air Act requires that the

effectiveness of reformulated gasolines be determined in

reference to representative model year 1990 vehicles. As

discussed in the SNPRM [57 FR 13416 (April 16, 1992)], EPA

determined it was reasonable and necessary to look at '1990

technology type' vehicles. This decision was made because: (1)

vehicles with similar engine designs, fuel distribution systems,

and emission control systems would be expected to respond

similarly to fuel changes and (2) much more data is available on

emission effects of fuel changes from this expanded set of

vehicles than on 1990 model year vehicles alone [see EPA

memorandum in docket from Lindhjem to Rykowski, "Effect of

Oxygenates on Emissions," December, 1993].

Vehicles included in the studies discussed above were

classified as having '1990 technology' if they met both of the

following criteria:

(1) The vehicles must be of model year 1986 or later with

adaptive learning technology, since over 99% of 1990

vehicles utilized such technology.

(2) The manufacturer of the vehicle must have informed EPA

that one or more of its 1990 model year vehicles had

engine, fuel distribution, and emission control system

designs similar to those on the vehicle in question

[see EPA memorandum "1990 Baseline Vehicles," by

Korotney, November 30, 1993, in Air Docket A-92-12 for

more details]. 

A list of the included vehicles are given in the vehicles

database portion of the Complex Model database, which is

reproduced in Appendix IV-F.

2. General Model Specifications

a. Dependent Variables

Based on input from industry, other government agencies and

other interested parties, EPA decided to use the natural

logarithm (ln) of gross emissions as the dependent variable for

all pollutants. Modeling in log space (in which the dependent

variable is the natural logarithm of mass emissions per mile) has

several distinct advantages [see A-92-12 Docket submittals #II-E1, August 1992; II-E-2, August 1992; II-E-3, August 1992; II-E-4,

August 1992; and II-E-5, June 1992]. First, it increases the

explanatory power of the model by increasing the correlation

coefficient between emissions and fuel parameters. Second, EPA

found that models in log space have more normally distributed

residuals (the variation in the dependent variable that cannot be

explained by the model) than did models which were not

logarithmically transformed. A normal distribution of residuals
109

allows the use of a wide array of powerful statistical tools and

standard regression techniques, which enhances the quality and

usefulness of the model. Finally, heteroskedasticity (in which

the variance of the error differs for different values of the

independent variables) is reduced when emissions are transformed

using natural logarithms. NMHC and NOx were modeled on a

ln(grams/mile) basis while all air toxics were modeled on a

ln(milligrams/mile) basis. As discussed in Section A.1, all

tests for which methane measurements were not available had to be

excluded from the regressions when modeling NMHC emissions. NMHC

data were converted to VOC by subtracting the average fraction of

ethane.

b. Independent Vehicle Variables

Only vehicles with 1990-equivalent technology were used in

developing the regression models for all pollutants. The

definition of 1990 technology was specified by the each

manufacturer as detailed in Section A.1. Data from any vehicle

that did not meet the appropriate 1990 technology definition were

excluded from the regressions.

As discussed earlier, the vehicle itself is the dominant

influence on emissions from any vehicle-fuel combination. This

effect was modeled by including separate independent variables

for each vehicle. Dummy variables were used to account for these

effects, since they enable the isolation of the vehicles' effects

on emissions from fuel effects and are a standard regression

technique for handling categorical variables [see Hocking, R.R.

(1976), "The Analysis and Selection of Variables in Linear

Regression," Biometrics, 32, 1-50.], which take on discrete

values. Some vehicles were tested in more than one study. In

such cases, separate dummy variables were included for each

vehicle in the study in order to minimize "drift" in vehicle

emission levels over time and lab-to-lab measurement variation. 

For each study-vehicle combination, a dummy variable was defined

as "1" for observations providing data on the study-vehicle

combination and "0" for all other observations. In addition, EPA

chose to use a no-intercept model in order to isolate all

vehicle effects. EPA found that models with intercepts tended to

be biased and did not properly account for vehicle effects. 

Hence the number of dummy variables in the model for each

pollutant equals the number of vehicle-study combinations for

which emissions data on that pollutant were available.

c. Independent Fuel Variables

The independent fuel variables were chosen after careful

consideration of data availability, expected contribution to

emissions based on outside comments and engineering intuition,
110

and preliminary test results. As detailed in Section A.1.a, the

independent fuel variables for exhaust VOC, NOx, and 1,3-

butadiene emissions included oxygen, sulfur, aromatics, olefins,

E200, E300, and RVP. For exhaust benzene emissions, fuel benzene

content was added to the list of independent fuel variables. For

exhaust formaldehyde and acetaldehyde emissions, the independent

fuel variables included aromatics, olefins, E200, E300, sulfur

and RVP, as well as separate variables for oxygen content in the

form of tertiary amyl methyl ether (TAME), ethanol (ETOH), methyl

tertiary butyl ether (MTBE), and ethyl tertiary butyl ether

(ETBE).

The fuel components of exhaust emissions were separated into

two main categories for the VOC and NOx models. The first

category consisted of the effects of individual fuel parameters

on emissions. This effect could not always be modeled with a

simple linear term relating the fuel parameter to the natural

logarithm of mass emissions. In many cases, an additional

squared fuel term was required to adequately describe the

emissions effect of an individual fuel parameter. The second

category of fuel terms consisted of interactive effects between

two different fuel parameters. These terms were modeled as a

product of the two fuel parameters of interest. Due to the

paucity of toxics data, the poorer relative precision of toxics

emission measurements when compared to NMHC and NOx measurements,

and the limited understanding of fuel effects on toxic emissions,

toxics emission models included only linear fuel terms. 

Initially, EPA chose to pre-exclude all interactive terms from

the four toxics models but to allow all squared terms. However,

EPA analyses [see EPA memorandum "Alternative Exhaust Benzene

Complex Models," from Rao and Sklar to Air Docket A-92-12,

December 7, 1993] showed that adding the squared terms to the

toxics models did not improve their explanatory power while

introducing unexplainable behavior into the models. For these

reasons, the toxics models included only linear fuel terms. The

specifics of how particular terms were introduced into the model

is discussed in Sections A.3 and A.4 below.

The fuel variables were modeled in centered form during the

development of the Complex Model (see model development sections

below). A centered variable is one in which the variable is

expressed as a deviation from some intermediate value in the

regression equations rather than being expressed directly. EPA

used centered independent fuel variables in developing the

Complex Model to minimize collinearity problems. Once the

regression were completed, however, EPA chose to simplify the

resulting emission models by removing the centering values. This

"uncentering" procedure requires algebraic manipulation of the

centered regression equations to remove the centering values,

yielding equations that contain the uncentered variables. This

process is discussed in Section A.8.
111

d. Emitter Class and Technology Group Distinctions

Emission studies conducted by EPA and others have shown that

different vehicles have different emission characteristics. 

Differences in vehicles' emission control technologies and

differences in the state of operation of those technologies

account for some of these differences. For these reasons, EPA

hypothesized that fuel modifications would have different

emission effects on different types of vehicles. To account for

these differences, EPA's February 1993 proposal divided vehicles

into two "emitter classes" (normal and higher emitters) based on

their exhaust emission levels and modeled the response of each

emitter class to fuel modifications separately. For the final

Complex Model, EPA modeled higher emitters separately and then

incorporated the adjustment terms developed from the higher

emitter model into an overall in-use model, as discussed in

Section A.3 in greater detail [see A-92-12 Docket submittals #IVB-01, August 1992; IV-B-4, July 1993; IV-E-1, June 1992; and IVE-6, May 1993 for more details]. These changes were made in

response to EPA's evaluation of its proposed model and comments

received regarding the regression approach used to develop the

NPRM model. EPA continues to believe that the distinction

between normal and higher emitters to be both valid and necessary

since normal and higher emitters appear to respond differently to

many fuel modifications. 

In the NPRM, EPA further subdivided vehicles in each emitter

class into "technology groups" based on emission control

technology with which each vehicle was equipped. Categorization

of vehicles into technology groups was used to explicitly account

for the effects of differences in emission control technology,

which were the basis for the technology group definitions. These

control technologies included catalyst type, fuel distribution

system, EGR, air injection. The technology group distinctions

also implicitly accounted for other vehicle characteristics such

as engine design and engine control system, to the extent such

characteristics were correlated with specific technology groups.

However, as discussed in the February NPRM, EPA was

concerned that technology group distinctions among higher

emitters might not be appropriate, since such vehicles' higher

exhaust VOC emission levels suggest that their emission control

systems do not function properly. In addition, the limited

quantity of higher emitter data made it difficult to identify

statistically significant differences in emissions response

between different technology groups within the higher emitter

class of vehicles. The limited higher emitter data caused higher

emitter models developed for individual technology groups to have

low statistical power and poor fit. Many commenters expressed

identical concerns.
112

Efforts to subdivide higher emitters by characteristics such

as exhaust hydrocarbon to NOx ratio, as suggested by several

commenters, did not improve the quality of EPA's higher emitter

model [see EPA memorandum "Proposed Revisions to Technology Group

Definitions for Use in Exhaust Complex Model," from Sklar,

Lindhjem and Rao, December 2, 1993]. Thus, EPA's final exhaust

models do not divide higher emitters into technology groups. 

Technology group specific terms were retained when modeling

normal emitters, for the reasons discussed in the February 1993

Draft RIA and the April 1992 proposal. However, EPA's final

model limits the use of technology group specific effects to

represent statistically significant deviations from the average

effect across all vehicles, as discussed more fully in the model

development section (Section A.4). In response to other

comments, EPA attempted to reduce the number of normal emitter

technology groups. However EPA was unable to identify an

appropriate basis for consolidation and/or combination of the

various technology groups [see EPA memorandum "Proposed Revisions

to Technology Group Definitions for Use in Exhaust Complex

Model," from Sklar, Lindhjem and Rao, December 2, 1993]. EPA

considers its retention of emitter class and technology group

distinctions to be validated by the presence of emitter class and

technology group-specific fuel effects in its final Complex

Models presented below.

e. Technology Group and Emitter Class Definitions and

Weightings

EPA analyzed emissions data on different technology groups

separately since emissions control system designs were expected

to respond differently to changes in fuel parameters. These

differences have been shown to exist in previous EPA analyses

[see EPA memorandum "Effect of Oxygenates on Emissions," from

Lindhjem to Rykowski, December, 1993] as well as in the emissions

predictions from the February NPRM models. Technology groupings

were based on four criteria:

- Fuel delivery system (carburetted, throttle body

injection or port fuel injection)

- The presence or absence of exhaust gas recirculation

(EGR)

- The presence or absence of air injection

- Catalytic converter type (three-way, three-way plus

oxidation catalyst, etc.)

Of the possible combinations based on these four criteria, only

the nine most common technology groups were used to develop the

model. These nine technology groups encompassed over 99% of 1990

model year sales of cars and light-duty trucks (as discussed in

Section E and in the April 1992 SNPRM [92]). Table IV-1
113

summarizes the definitions of these nine technology groups and

the percentage of 1990 vehicle sales accounted for by each group.

Table IV-1

Technology Group Definitions and Sales Weights*

TECHNOLOGY

GROUP

FUEL

SYSTEM

CATALYST AIR

INJECTION

EGR PERCENT

1990

SALES

1 Multi

(PFI)

3W No Air EGR 26.31

2 Multi

(PFI)

3W No Air No EGR 28.71

3 TBI 3W No Air EGR 21.81

4 Multi

(PFI)

3W + OX Air EGR 11.43

5 Multi

(PFI)

3W Air EGR 4.31

6 TBI 3W Air EGR 0.53

7 TBI 3W + OX Air EGR 5.25

8 TBI 3W No Air No EGR 0.00**

9 Carb. 3W +OX Air EGR 1.65 * Sales weights based on a non-California, 49 state analysis. See EPA

memorandum Number IV-B-2 in Docket A-92-12 for more details. ** Projected sales for technology group 8 were non-zero, but actual reported

1990 sales for this technology group were zero.

where

Multi = Multi-Port Fuel Injection

TBI = Throttle Body Injection

Carb. = Carburetted

3W = Three Way Catalyst

3W+OX = Three Way Catalyst plus an Oxidation Catalyst

Air = Supplementary air injection present

No Air = Supplementary air injection not present

EGR = Exhaust gas recirculation used

No EGR = Exhaust gas recirculation not used

EPA has also analyzed the effects of VOC emissions levels on

vehicle responses to fuel modifications. Higher vehicle

emissions indicate that certain control technologies may not be

functioning properly. Such vehicles have been shown in previous
114

EPA analyses [see EPA memorandum by Lindhjem "Effect of

Oxygenates on Emissions," December, 1993] and in the February

NPRM models to exhibit different emission responses to changes in

fuel properties than normal emitting vehicles equipped with

similar emission control technology. Depending upon the failure

mode causing a vehicle to be a higher emitter, higher emitters

may also exhibit different emission responses to changes in fuel

properties than other high emitting vehicles. Because reliable

data was not available as to the type of failure mode for

vehicles considered to be higher emitters, vehicles were 

classified as either 'normal' or 'higher' emitters based on their

total hydrocarbon emissions on a CAA-type base fuel on a standard

FTP test. Vehicles with total hydrocarbon emissions less than

twice the applicable standard (0.82 g/mi) were classified as

normal emitters. EPA modeled normal and higher emitting vehicles

separately to account for differences in the responses of such

vehicles to fuel modifications.

As discussed in the February 1993 proposal, the weight

assigned to each technology group or emitter class for modeling

purposes was set equal to its contribution to in-use emissions. 

The weighting factor assigned to normal emitters was then broken

down further by technology group, again according to their

projected contribution to in-use emissions. These estimates are

very similar to the numbers shown in the February 1993 proposal,

although small changes have been made to account for more

complete information about the fraction of 1990 sales accounted

for by each technology group. The final in-use eighting factors

for the eight normal emitter groups and the one higher emitter

group are shown below in Table IV-2. The rationale, derivation

and normalization of the weighting factors are discussed in more

detail in Section III.B.4.
115

Table IV-2

Vehicle Group Weightings for the Exhaust Complex Model

Vehicle

Group

Phase I Phase II

VOC/Toxics NOx VOC/Toxics NOx

Norm*-tg** 1 0.13986 0.19550 0.11942 0.17595

Norm-tg 2 0.12517 0.23430 0.10688 0.21087

Norm-tg 3 0.09592 0.14958 0.08190 0.13462

Norm-tg 4 0.09508 0.15023 0.08118 0.13521

Norm-tg 5 0.01475 0.02400 0.01260 0.02160

Norm-tg 6 0.00203 0.00349 0.00173 0.00314

Norm-tg 7 0.03905 0.04608 0.03334 0.04147

Norm-tg 9 0.00814 0.01682 0.00695 0.01514

Higher

emitters

0.48000 0.18000 0.55600 0.26200

*

"Norm" designates normal emitters **"tg" designates technology groups

3. Development Method Overview

The overall process used by EPA to arrive at the final

Complex Models for VOC, NOx and air toxics is summarized below. 

A more detailed discussion of the process can be found in the

following sections.

1. A "raw" model was developed which contained all regression

terms found to be significant in (1) a forward "stepwise"

fit, (2) a re-regression on surviving terms after data

outliers and influential points were excluded, (3) a reregression after deleting terms based on Mallows' Cp

criterion to balance overfitting and underfitting, and (4) a

final backwards fit to eliminate insignificant terms. Steps

2-4 were not taken during development of the February 1993

NPRM model. These steps are discussed in detail in Section

A.4.

2. The raw model was refined by deleting terms whose

contribution to the model's explanatory power was small. In

general, terms which contributed less than one percent of

the model's explanatory power were deleted to produce a

refined model which was simpler in form than the raw model

without sacrificing its ability to predict the emissions

impact of fuel modifications. Note that this step was not
116

taken during development of the February 1993 NPRM model. 

These steps are discussed in greater detail in Section A.5.

3. The refined model was simplified. Several commenters

expressed concern about the complexity and number of

equations in the final Complex Model. To address these

concerns, two steps were taken. First, the technology

group-specific models for normal emitters were consolidated

into a single model for all normal emitters. Second, the

fuel variables were uncentered. Both consolidation and

uncentering are discussed in Section A.8.

The resulting exhaust emission models contain two equations for

each pollutant (one for normal emitters and one for higher

emitters). By contrast, the model proposed in February 1993

contained as many as sixteen separate equations for each

pollutant. In addition, the final exhaust emission equations

have fewer fuel terms than did the February equations. However,

EPA does not believe that this less complicated complex model is

any less accurate than the complex models presented at public

workshops or in the February 1993 proposal. This belief is based

on the final models' comparable explanatory power and accuracy in

accounting for the emission effects seen in the vehicle testing

programs that comprise the Complex Model database, as discussed

in Section F.

4. Raw Model Development

As discussed previously, exhaust emissions are affected by

both vehicle characteristics and fuel characteristics. This

combined effect causes difficulty in trying to isolate the

effects of fuel characteristics on emissions. EPA's analysis

attempted to separate the vehicle and fuel components of exhaust

emissions by using dummy variables to isolate the effect of

vehicles on emissions. The vehicle was found to be the single

most significant determinant of the level of emissions from a

given vehicle on a given fuel, accounting for approximately 90%

of the variation in emissions. Fuel properties were found to be

a much smaller (5-6%) influence on variation in exhaust

emissions. The remaining 4-5% of the variation in emissions

remains unexplained.

EPA received a number of comments regarding the models

proposed in February 1993. After careful consideration, EPA

concluded that the following comments were valid and should be

incorporated into its final models:

 Some commenters noted that many emission effects were

likely to be consistent across technology groups or

emitter classes. They suggested that EPA include such

common effects in its models before resorting to

technology group-specific or emitter class-specific
117

terms to model vehicles' emissions response to fuel

modifications.

 Commenters noted that insufficient data were available

to model many potential terms, particularly interactive

terms, and that such terms should not be allowed to

enter the model. 

 Commenters argued that in the case of higher emitters,

EPA's models relied on a small fraction of the database

to model a large fraction of the in-use emissions. 

They argued that EPA should have used the more complete

data on normal emitters to model higher emittters'

response to fuel modifications.

While EPA does not believe that normal emitter data alone

should be used to build the higher emitter models, EPA agrees

that the normal emitter model, which is based on a more extensive

and complete data set than is available for higher emitters,

should form the basis of the higher emitter model. EPA used data

on higher emitters to develop adjustment terms that reflect the

difference between normal and higher emitter responses to fuel

modifications.

To incorporate the concerns raised in these comments, EPA

has utilized a modified version of the "unified" approach

advocated by a number of commenters to develop its final complex

models. The techniques used to address these comments are

summarized below and are discussed in greater detail in Sections

A.4.a and A.4.b:

1. Interactive terms were permitted to enter the model only

when sufficient data were available. The February 1993

models included all statistically significant interactive

terms, regardless of whether sufficient data were available

to estimate such an effect.

2. Models for higher emitters were constructed based solely on

data from such vehicles in order to determine which fuel

terms had statistically significant effects.

3. The entire database was analyzed using the "unified"

approach. The effects of each term on emissions was divided

into two parts: an average effect across all vehicles, and

a series of adjustment terms for each technology group and

for higher emitters. Higher emitter adjustment terms were

forced into this model for all terms found to be

statistically significant in the higher emitter model, in

order to assure that such effects were not obscured by the

disproportionately large share of the data on normal

emitters.
118

4. Overly influential data were dropped from the database and

the model was re-estimated based on the remaining data (see

Section A.4.a for further discussion of influential data).

5. Terms were deleted from the developed model to avoid

overfitting and collinearity problems. Mallows' Cp

criterion was used to assess the problem of overfitting.

6. The overall fuel terms and the corresponding fuel adjustment

terms (for the different technology groups) were computed in

the following manner:

a. An overall effect for the fuel term was estimated using

all available data in the database.

b. The difference between the overall effect and the

effect for each vehicle group was identified.

c. If the difference was significant for one or more

vehicle groups, the vehicle group adjustment term with

the difference that is the most significant was chosen.

d. Repeat steps b-c for the remaining vehicle groups until

there are no more significant vehicle group adjustment

terms.

These approaches were designed to take advantage of the

benefits of a regression on the entire database (a "fully

unified" approach) without losing sight of the unique behavior of

higher emitters. Since higher emitters were severely underrepresented in the complex model database compared to their

contribution to in-use emissions, EPA believed that a fully

unified approach would not have represented higher emitter

effects properly. However, the partially unified approach used

by EPA allowed the Agency to simplify its emission models without

losing explanatory power. By using technology group-specific

adjustment terms only if the technology group's response to fuel

modifications was sufficiently consistent in nature and different

in magnitude from the average normal emitter response, EPA was

able to rely on the same set of terms to explain fuel effects

across all eight normal emitter technology groups. In the NPRM

model, different terms were permitted in each technology groupspecific model. As a result, the model for one technology group

might include one fuel term instead of another fuel term that

might represent the data equally well, while the model for a

second technology group might include the second term but not the

first. The partially unified approach applied the same term to

both groups and only permitted additional terms to enter the

model if both the common term and the additional terms were

necessary to adequately model the data. A copy of the SAS

program used to develop the final complex models for all

pollutants can be found in Appendix IV-E.
119

a. Statistical Development of VOC and NOx Exhaust Models

The final VOC and NOx models are similar to the most

accurate of the three sets of models included in EPA's July 14,

1993 docket submittal [A-92-12 Docket submittal #IV-B-4, July

1993], while also including relevant comments regarding specific

aspects of the models [see Section B.10]. The following step-bystep procedure was used to develop the "raw" VOC and NOx exhaust

emission models.

1. The database was reviewed to ensure that specific studies

and observations were excluded according to the criteria

outlined in Section A.2. After excluding this data, the

database contained 5214 observations for NOx and 4287

observations for VOC (see step 3).

2. Each vehicle in the database was placed into a technology

group and an emitter class. Higher emitters were defined as

those vehicles which emit greater than 0.82 grams/mile of

total hydrocarbons on a base fuel [see A-92-12 Docket

submittal IV-B-3, June 1993]. The 0.82 grams/mile

represents a cutpoint of twice the VOC emissions standard

for cars. The small number of light duty trucks were

classified as higher emitters using the same criterion.

3. Total hydrocarbon (THC) emissions were converted to nonmethane hydrocarbons (NMHC) by subtracting measured methane

emissions from total hydrocarbon emissions. As discussed

above, this step can only be performed for those tests in

which exhaust methane was measured; other tests were

excluded from the database used to model exhaust VOC

emissions.

4. Fuel oxygenate levels (in volume percent) were converted to

fuel oxygen levels (in weight percent).

5. Mean values for each fuel parameter were calculated across

all observations in the database. These values are given

below:

Oxygen: 1.774834 weight percent

RVP: 8.611478 psi

E200: 46.72577 percent

E300: 85.89620 percent

Sulfur: 204.5779 ppmW

Olefins: 7.318716 volume percent

Aromatics: 28.26110 volume percent

These mean values were used as the centering values for each

fuel variable in the regression.
120

6. Separate dummy variables were included in the regression

models for for each vehicle-study occurrence (for the

reasons discussed in previous EPA submittals to the docket).

7. A model for higher emitting vehicles was constructed

according to the following procedure:

a. The vehicle-by-study dummy variable terms were included

in the model.

b. The following terms were pre-excluded from the higher

emitter VOC and NOx models (details of this step are

discussed in step 10 below):

OXY*E200 OXY*ARO OXY*OLE SUL*E200

ARO*SUL SUL*OLE SUL*RVP E200*E300

E200*ARO E200*OLE E200*RVP OLE*RVP

E300*RVP ARO*RVP

c. A stepwise regression on the higher emitter data was

performed, with the first step including all linear

fuel terms.

d. In subsequent steps, fuel terms which were

statistically significant at the 0.10 level were added

to the model. The first step included the vehiclestudy dummy variable terms (from step a) and the linear

fuel terms. Next, higher order terms (squared and twoparameter interactive terms) were added to the model

using a stepwise regression procedure if they were

significant at the 0.10 significance level, in keeping

with standard EPA practice. The February 1993 proposal

used a significance level of 0.15.

e. Once the stepwise model for higher emitters had been

constructed, Mallows' Cp criterion was used to

eliminate terms from the model. The Cp criterion was

proposed by Mallows [Mallows, C.L. (1973), "Some

Comments on Cp," Technometrics, 15, 661-675] for

selecting a model and is a measure of total squared

error. If Cp is plotted against the number of

independent parameters (p) in the model, Mallows

recommends the model where Cp first approaches p. When

such a model is chosen, the parameter estimates are

most unbiased and the risk of not including an

additional and possibly valid parameter is balanced by

the risk of adding an invalid parameter.

f. A backwards-elimination regression was run to remove 

linear fuel terms that were no longer significant at

the 0.10 level, unless such terms were necessary for

hierarchy considerations (as discussed below).
121

g. A separate higher emitter adjustment term was forced

into the "unified" models for VOC and NOx described

below for each fuel term remaining in the corresponding

higher emitter model resulting from step f. The

adjustment terms were the interactions of each

significant fuel term with a dummy variable designating

the higher emitter vehicle group.

8. A "fully unified" model was constructed as discussed below

in steps 9-14.

9. The vehicle-study terms and the overall linear fuel terms

were forced into the model. Adjustment terms for higher

emitters based on the results of step 7 were also forced

into the model.

10. Certain interactive fuel terms were not permitted to enter

the model, i.e., they were pre-excluded from the model. 

Sufficient data did not exist to incorporate all possible

fuel terms into the VOC and NOx models. In addition,

research into engine-out versus tailpipe emissions indicated

that some fuel properties affected catalyst performance

alone, while other fuel properties affected combustion

efficiency alone. Interactive effects between such

properties were considered improbable since different

vehicle components are involved. Statistical considerations

such as variance inflation also indicated that certain fuel

terms should not be permitted to play a role in the models. 

Variance inflation is an indication of the degree of multicollinearity between two or more fuel parameters. "Large"

values (in excess of ten) of variance inflation could lead

to serious distortions of regression coefficients. For

these reasons, which are discussed in greater detail in

EPA's July 14, 1993 docket submittal, the following terms

were pre-excluded from the normal emitter NMHC and NOx

models:

OLE*SUL RVP*SUL E200*SUL

ARO*E200 ARO*RVP OLE*RVP

RVP*E300 E200*OXY E200*E300

OLE*E200 E200*RVP

11. The stepwise regression procedure in SAS was used to add

terms to the models. Non-linear overall fuel terms (e.g.,

two-way interactions and squared terms) and normal-emitter

adjustment terms specific to individual vehicle groups were

added if they were statistically significant at the 0.10

level. The terms described in step 10 were not permitted to

enter the model, either as overall terms or adjustment

terms.
122

12. As with the higher emitter model developed in step 7, the

model resulting from step 11 was evaluated using Mallows' Cp

criterion to balance overfitting and underfitting. This

step also helped remove terms with significant variance

inflation values, which are indicative of collinearity

between terms in the model.

13. Outliers and influential points were removed from the data

set and the coefficients for the terms in the model

generated in step 12 were re-estimated. Emissions results

that are very different from model predictions can have a

large impact on the resulting model. These extreme results

can be caused by a number of factors that should not be

permitted to affect the Complex Models:

 Errors may have been made in measuring or

recording emission or fuel parameter levels

 Vehicles may have been placed in the wrong

technology group or emitter class, or it could

have had pre-1990 emission control technology

 The results may be due to the inherent variability

of vehicle emissions.

Such errors can occur during tests of fuels that are

significantly different from other fuels or of vehicle types

that are relatively uncommon. In such cases, the erroneous

results can distort the regression results significantly

since countervailing data from other fuels or vehicles would

not be available.

This problem was addressed by removing such observations

from the database and re-estimating the regression equations

with the remaining data. Outliers were defined as having an

Rstudent value greater than an absolute value of 4 (i.e., they

lie more than four standard deviations away from the mean

regression result). The probability of a deviation of this

size being due solely to the inherent variability of vehicle

emissions is less than 0.5 percent. Influential points were

defined as having a DFFITS value greater than 1.2. DFFITS

provides an estimate of the degree to which the observation,

by itself, alters the regression equation. Standard

statistical practice is to consider observations with DFFITS

values in excess of 1.0 to be overly influential. EPA

relaxed this criterion slightly in recognition of the

limited data available for many fuel parameter combinations

and vehicle types, thereby retaining some observations that

arguably could have been excluded. The number of data

excluded in this step was small relative to the total number

of data available, amounting to approximately 1.6% of the

normal emitter VOC data, 1.8% of the higher emitter VOC
123

data, 1.0% of the normal emitter NOx data, and 0.9% of the

higher emitter NOx data.

14. To ensure hierarchy (put simply, ensuring hierarchy requires

that if an interactive fuel term A*B is in the model, the

individual fuel parameters A and B also must be included in

the model) while also ensuring that the model was

parsimonious in its choice of terms, a series of backwardselimination runs were conducted to eliminate terms in the

model developed in step 13 that were no longer statistically

significant at the 0.10 level. Such terms include the

linear overall terms and the higher emitter adjustment

terms, which were forced into the model initially. In

addition, the variance inflation for the remaining terms was

examined to assure that the models were free of severe

multi-collinearity problems.

In the first backward elimination run, the nonsignificant

nonlinear fuel terms were removed from the model. Mallows'

Cp criterion was used to determine the useful terms. In the

second backward elimination run, the nonsignificant higher

emitter adjustment terms were removed from the model. 

Again, Mallows' Cp criterion was utilized. In the final

backward elimination run, the nonsignificant nonhierarchial

linear fuel terms (i.e., those not included in any

significant higher-order fuel terms) were removed from the

model. Mallows' Cp criterion was utilized to balance

overfitting and underfitting.

EPA also reviewed the resulting models for their statistical

soundness and overall reasonableness. The SAS code used to

arrive at these models can be found in Appendix IV-D-4. The

regression coefficients resulting from this methodology are shown

in Section A.5 below.

b. Statistical Development of the Toxic Exhaust Models

EPA modeled exhaust toxics emissions in a similar fashion to

the method used to develop the VOC and NOx models. All five of

the toxic air pollutants that the Clean Air Act specifies for

control through reformulated gasoline (benzene, acetaldehyde,

formaldehyde, 1,3-butadiene and polycyclic organic matter) are

also considered VOCs and are present in exhaust emissions. 

Benzene is a natural component of gasoline, so exhaust benzene

emissions include both unburned benzene and benzene formed in the

combustion process through the partial decomposition of more

complex aromatic compounds. The four other toxics are not

present in gasoline and hence are solely products of combustion.

The work discussed in the SNPRM [92] indicated that exhaust

toxics were best characterized in terms of the mass fraction of
124

total VOC emissions. This mass fraction could be multiplied by

total VOC emissions to determine mass emissions of toxic

compounds. During development of the Complex Model, however, EPA

and others found that exhaust toxics models based on milligrams

emitted per mile yielded better correlations than models based on

the fraction of total VOC emissions. For this reason, EPA chose

to construct models to estimate the natural logarithm of toxics

emissions (expressed in terms of mg/mile).

Only a few of the studies described in Section A.1 measured

exhaust toxic emissions. Hence less data were available for

toxics emissions from both normal and higher emitters than were

available for VOC or NOx emissions. As a general rule, less data

for exhaust toxics than for exhaust VOC or NOx meant that fewer

independent fuel variables could be included in the toxics

models. For its final toxics models, EPA elected to use only

linear fuel terms, eliminating the squared and the two-parameter

interactive terms found in the models with more data. EPA

concluded that the resulting increase in the accuracy of the

linear term coefficient estimates more than offset any reductions

in accuracy resulting from exclusion of nonlinear terms. This

conclusion is supported by EPA's efforts to develop a number of

nonlinear models, all of which had poorer explanatory accuracy

than EPA's linear toxics models [see EPA memorandum by Rao and

Sklar "Alternative Exhaust Benzene Complex Models," December 2,

1993].

As with the VOC and NOx models, a "partially unified" model

was built for each exhaust toxic pollutant. Normal emitter

technology group distinctions were retained while all higher

emitting vehicles were placed in a single group. The general

methodology used to develop the toxic models was essentially the

same as that used in developing the VOC and NOx models and is

outlined below.

1. Same as step 1 described in Section A.4.a.

2. Same as step 2 described in Section A.4.a.

3. Same as step 4 described in Section A.4.a.

4. The mean fuel parameter values used were identical to those

used in step 5 in Section A.4.a for the exhaust 1,3-

butadiene toxic model. The exhaust aldehyde models were

oxygenate specific and thus the following values were used

as the mean values for the different oxygenates (the other

fuel parameter centering values are identical to those given

in Section A.4.a step 5). The mean value of fuel benzene

content is given below for use in the exhaust benzene model:

MTBE: 0.947240 weight percent

ETBE: 0.023203 weight percent
125

TAME: 0.016443 weight percent

Ethanol: 0.314352 weight percent

Benzene: 1.066682 volume percent

5. Same as step 6 described in Section A.4.a.

6. A higher emitter model was constructed in a manner analogous

to that discussed in step 7 of Section A.4. The specific

steps followed are outlined below:

a. Dummy variables for each vehicle-study occurrence were

forced into the model.

b. The following terms were permitted to enter the model

via a stepwise regression if they were statistically

significant at the 0.10 level (note that in the

February 1993 NPRM, terms were included if they were

significant at the 0.15 level):

For BENZENE: Oxygen, Aromatics, Olefins, E200,

E300, RVP, Sulfur and Benzene

For BUTADIENE: Oxygen, Aromatics, Olefins, E200,

E300, RVP and Sulfur 

For ACETALDEHYDE: TAME, Ethanol, MTBE, ETBE,

Aromatics, Olefins, E200, E300, RVP

and Sulfur

For FORMALDEHYDE: TAME, Ethanol, MTBE, ETBE,

Aromatics, Olefins, E200, E300, RVP

and Sulfur

d. Terms were eliminated using Mallows' Cp criterion,

thereby balancing overfitting and underfitting risks.

e. Outliers and influential points, defined using the same

criteria described in Section A.4.a, were eliminated

and the model was re-estimated.

f. A backward-elimination regression was used to remove

non-significant fuel terms.

g. For each term identified and retained after step f

above, force a separate higher emitter adjustment term

into the "partially unified" model described below.

7. "Unified" models for each toxic pollutant were built, as

described in steps 9-14. The process was similar to that

used to build the VOC and NOx models, as described in

Section A.4.a. Outliers and influential points that were
126

removed in step 7 when building the high-emitter models

described in step 7 were re-included in the database. They

were removed in step 12 if they were still outliers.

8. The vehicle terms and the higher emitter adjustment terms

from step 7 were forced into the models.

9. Models for each toxic pollutant were built stepwise, in a

manner similar to the way the VOC and NOx models were built. 

The following terms were allowed to enter the model as

either overall terms or as adjustment terms for normal

emitter technology groups via the stepwise process if they

were statistically significant at the 0.10 level:

For BENZENE: Oxygen, Aromatics, Olefins, E200, E300,

RVP, Sulfur and Benzene

For BUTADIENE: Oxygen, Aromatics, Olefins, E200, E300,

RVP and Sulfur 

For ACETALDEHYDE: TAME, Ethanol, MTBE, ETBE, Aromatics,

Olefins, E200, E300, RVP and Sulfur

For FORMALDEHYDE: TAME, Ethanol, MTBE, ETBE, Aromatics,

Olefins, E200, E300, RVP and Sulfur

10. The Cp criterion was applied to the models resulting from

step 9. This step resulted in terms being eliminated from

the models when the models' risk of being overfitted

exceeded the risk of underfitting that would result from

elimination of the term.

11. The model generated in step 10 was used to determine which

observations were outliers or influential points, as defined

in step 13 in Section A.4.a. These outliers and influential

points were removed from the database.

12. A final stepwise backwards-elimination process was pursued

to remove fuel terms that were no longer statistically

significant at the 0.10 level until all remaining terms are

statistically significant. This model was free of variance

inflation problems. 

13. Same as step 13 described in Section A.4.a.

5. Raw Version of the Exhaust Emissions Complex Model

 Following the steps outlined in Section A.4 resulted in the

derivation of the raw regression model coefficients shown below:
127

Raw Regression Coefficients for Exhaust VOC Emissions

Table IV-3

Fuel

Term

Centered Raw Model Regression Coefficients for Exhaust VOC

TG*

 1 TG 2 TG 3 TG 4 TG 5 TG 6 TG 7 TG 9 HIGH**

Oxygen -.00293 -.00293 -.00293 -.00293 -.00293 -.00293 -.00293 -.00293 -.00293

Sulfur .000531 .00035 .000531 .000802 .00090 .000187 .000531 .000531 -.000014

RVP .03274 -.00006 .03274 .03274 .03274 .03274 .03274 .03274 .07378

E200 -.00782 -.00430 -.00430 -.00430 -.00430 -.00430 -.00430 -.00430 -.00430

E300 -.00757 -.00757 -.00757 -.00757 -.00757 -.00757 -.00757 -.00757 .00023

Aro .00316 .00316 .00316 -.0008 .00316 .00316 .00316 .00316 .00316

Olefins -.00251 -.00251 -.00251 -.00251 -.00251 -.00251 -.00251 -.00251 -.00251

Aro*E300 -.00029 -.00029 -.00061 -.00029 -.00029 -.00029 -.00029 -.00029 -.00029

E2002 .000086 .000086 .000086 .000086 .000086 .000086 .000086 .000086 .000086

RVP*Oxy -.00789 -.00789 -.00789 -.00789 -.00789 -.00789 -.00789 -.00789 -.00789

Sul*E300 .000016 .000016 .000016 .000016 .000016 .000016 .000016 .000016 .000016

Oxy*Sul 0 0 0 -9.3E-5 0 0 0 0 0

Sul2 0 -1.3E-6 0 0 0 0 0 0 0

Aro2 0 0 0 -.00031 0 0 0 0 0

E3002 .000525 .000525 .000525 .000525 .000525 .000525 .000525 .000525 .000525

* "TG" denotes EPA technology groups ** "HIGH" refers to higher emitter model coefficients
128

Raw Regression Coefficients for Exhaust NOx Emissions

Table IV-4

Fuel

Term

Centered Raw Model Regression Coefficients for Exhaust NOx

TG 1 TG 2 TG 3 TG 4 TG 5 TG 6 TG 7 TG 9 HIGH

Oxygen .00309 .00309 -.01890 .00309 .00309 .00309 .00309 .00309 -.00887

Sulfur .000706 .00046 .00046 -.00007 .00046 -1.5E-5 .00046 .00046 .00027

RVP .011857 .011857 .011857 .011857 .011857 .011857 .011857 .011857 -.01627

E200 .000915 .000915 .000915 .000915 .000915 .000915 .000915 .000915 .000915

E300 .002465 -.00014 .002465 -.00312 .002465 .002465 .002465 .002465 -.00421

Arom -.00113 .002143 .002143 .002143 .002143 .002143 .002143 .002143 .002143

Olefins .00234 .00234 .00234 .00234 .00234 .00234 .00234 .00234 .00234

Sulfur2 -1.7E-6 -1.0E-6 0 0 0 0 0 0 0

Arom2 -5.8E-5 -.00021 -5.8E-5 -5.8E-5 -5.8E-5 -5.8E-5 -5.8E-5 -5.8E-5 -5.8E-5

E3002 0 0 0 0 0 0 0 0 -.00057

Oxy*RVP 0 0 0 0 .024415 0 0 0 0

Oxy*Aro 0 -.00099 0 0 0 0 0 0 0

Oxy*Sul -9.4E-5 0 0 0 0 0 0 0 0

E300*Ole .000335 0 0 0 0 0 0 0 0

Oxy2 0 0 .003359 0 0 0 0 0 0

Olefins2 .000417 .000417 .000417 .000417 .000417 .000417 .000417 .000417 .000417

Raw Regression Coefficients for Exhaust Benzene Emissions

Table IV-5

Fuel

Term

Centered Raw Model Regression Coefficients for Exhaust Benzene

TG 1 TG 2 Tg 3 TG 4 TG 5 TG 6 TG 7 TG 9 HIGH

Oxygen 00000000 -.09605

Sulfur .001054 .000337 .001187 .000337 .000337 .000337 .000337 -.00195 .000337

RVP0 0 0 0 0 0 0 0 0

E200 -.00948 0 -.00578 000000

E300 00000000 .011251

Arom .02588 .02588 .02588 .02588 .04859 .02588 .02588 .02588 .01188

Olefins 000000000

Benzene .222318 .222318 .222318 .222318 .222318 .222318 .222318 .222318 .222318
129

Raw Regression Coefficients for Exhaust 1,3-Butadiene Emissions

Table IV-6

Fuel

Term

Centered Raw Model Coefficients for Exhaust 1,3-Butadiene

TG 1 TG 2 TG 3 TG 4 TG 5 TG 6 TG 7 TG 9 HIGH

Oxygen 00000000 -.06077

Sulfur .000506 0 .000544 -.00041 0 0 0 00

RVP 0 0 0 0 0 0 0 0 0

E200 -.00731 -.00731 -.00731 -.00731 -.00731 .00579 -.00731 -.00731 -.00731

E300 -.01678 -.01678 -.00625 -.01678 -.01678 -.01678 -.01678 -.01678 -.00806

Arom -.00401 -.00401 -.00401 -.00401 -.00401 -.00401 -.00401 -.00401 -.00401

Olefins .028238 .028238 .028238 .028238 .028238 .028238 .028238 .028238 .028238

Raw Regression Coefficients for Exhaust Formaldehyde Emissions

Table IV-7

Fuel

Term

Centered Raw Model Coefficients for Exhaust Formaldehyde

TG 1 TG 2 TG 3 TG 4 TG 5 TG 6 TG 7 TG 9 HIGH

Sulfur 0 0 0 0 0 0 0 00

RVP 0 0 0 0 0 0 0 0 0

E200 0 0 0 0 0 0 0 00

E300 -.01023 -.01023 -.01023 -.01023 -.01023 -.01023 -.01023 -.01023 -.01023

Arom -.00717 -.00717 -.00717 -.00717 -.00717 -.00717 -.00717 -.00717 -.00717

Olefins 00000000 -.03135

MTBE .046213 .046213 .046213 .046213 .046213 .046213 .046213 .046213 .046213

ETBE 0 0 0 0 0 0 0 00

ETOH 0 0 0 0 0 0 0 00

TAME 0 0 0 0 0 0 0 00
130

Raw Regression Coefficients for Exhaust Acetaldehyde Emissions

Table IV-8

Fuel

Term

Centered Raw Model Coefficients for Exhaust Acetaldehyde

TG 1 TG 2 TG 3 TG 4 TG 5 TG 6 TG 7 TG 9 HIGH

Sulfur .000263 .000263 .000263 .000263 .000263 .000263 .000263 .000263 .000263

RVP 0 0 0 0 0 0 0 0 0

E200 0 0 0 0 0 0 0 00

E300 -.01216 -.01216 -.01216 -.01216 -.01216 -.01216 -.01216 -.01216 -.01216

Arom -.00555 -.00555 -.00555 -.00555 -.00555 -.00555 -.00555 -.00555 -.00555

Olefins 0 0 0 0 0 0 0 00

MTBE -.03646 0000000 -.05598

ETBE .316467 .316467 .316467 .316467 .316467 .316467 .316467 .316467 .316467

ETOH .249326 .249326 .249326 .249326 .249326 .249326 .249326 .249326 .249326

TAME 0 0 0 0 0 0 0 00

Exhaust POM (polycyclic organic matter) performance is

calculated with the exhaust VOC regression coefficients since POM

was assumed to respond to fuel modifications in the same manner as

did VOC. EPA made this assumption since POM, while difficult to

measure accurately, is itself a VOC. Since data on unique POM

responses were not available, EPA considers the VOC model to

provide the most reasonable estimate of POM emissions. To

calculate mass emissions of POM for a target fuel, the ratio of

POM to exhaust VOC emissions for the baseline fuel must be

multiplied by the exhaust VOC emissions of the target fuel. The

ratio of baseline POM emissions to exhaust VOC emissions is shown

in Section III.B.5.

6. Raw Model Refinement

Once the Complex Model regression equations were determined,

the Agency took steps to refine the model by eliminating any terms

that did not significantly affect its behavior. In this complex

model development step, the Agency simplified the model's

structure while simultaneously preserving its behavior. EPA chose

to refine its model for several reasons. First, EPA recognized

that many of the terms in the raw models had relatively little

effect on emissions. Second, EPA had received numerous comments

asking that the Complex Model be simplified to facilitate its use. 

The refinement process used by EPA involved two steps:

1) Rank the terms in each pollutant-specific model

based on their contribution to the model's

explanatory power. This step was accomplished

through the random balance approach to model

simplification.
131

2) Execute a least-squares regression on the Complex

Model database to develop equations that contain

all the original terms except those terms that

cumulatively accounted for only a small (generally

less than 1%) portion of the model's explanatory

power.

This section presents the theory and methodology behind the random

balance algorithm, the results of applying the random balance

algorithm to the Complex Model, and the least-squares regression

approach.

a. The Random Balance Algorithm

Dr. H.T. McAdams of the Advanced Computing Center of Argenta

developed a method for simplifying models resulting from

statistical regressions. Dr. McAdams based this "random balance

algorithm" on the premise that a regression model may include some

terms that are statistically significant but contribute very

little to the model's explanatory or predictive power. Such terms

increase the model's complexity and can be eliminated while

retaining the essential behavioral characteristics of the model. 

This section provides an overview of the random balance algorithm;

a detailed description of the random balance algorithm and its use

in simplifying the Complex Model can be found in Appendix III-1.

The random balance algorithm, as used to refine the raw

Complex Model, can be summarized as follows: 

1) Generate 2000 random fuel blends whose fuel parameter values

are distributed evenly across the valid range of the raw

model. The valid range of the model is discussed in Section

D.2.

2) Use the raw Complex Model for exhaust emissions to estimate

the gram/mile emissions for each fuel blend. These estimates

are fleet-average estimates; they represent the weighted

estimates from the eight normal emitter and one higher

emitter regression equations using the Phase II weighting

factors.

3) Treat the emission estimates from step (2) as a data set, and

execute a simple, multi-parameter regression (least squares

polynomial fit) on the natural log of emissions. The

randomly generated fuels from step (1) operate as independent

variables in this step. The resulting single exponential

equation has the same behavioral characteristics as the nineequation raw model.

4) Calculate the contribution to the model's overall sum of

squares from individual fuel terms. The sum of squares is a

measure of the deviation of individual data points from the
132

regression curve. The sum of squares provides an indicator

of the model's overall explanatory power; the smaller the sum

of squares, the greater the model's overall explanatory

capability. This step is completed by squaring each of the

regression coefficients generated in step (3) and dividing by

an appropriate normalizing factor. The approximate

orthogonality of the moment matrix resulting from step (2)

allows this calculation to be made, as described in more

detail in Appendix IV-A. 

5) Rank the model terms on the basis of their contribution to

the model sum of squares.

The result of this process is a list of all the terms in the

exhaust Complex Models, ranked in order of importance. Those

terms which are least important contribute the least to the model

sum of squares. Decisions can then be made as to which terms can

be eliminated from the model without altering its behavior or

explanatory power.

b. Ranking of Raw Complex Model Terms

The raw Complex Model contained six exhaust pollutant

regression models that were candidates for refinement via with the

random balance algorithm. Of these six models, the raw models for

benzene, formaldehyde, acetaldehyde, and 1,3-butadiene were

strictly linear and contained relatively few fuel terms. The

Agency determined that the models for these four pollutants were

sufficiently simple to not require refinement. Therefore, only

the exhaust VOC and NOx models were refined via the random balance

algorithm.

The random balance algorithm yielded a list of terms for the

raw exhaust VOC and NOx models ranked in order of decreasing

contribution to each model's predictive power. These lists are

shown in Tables IV-9 and IV-10. In each table, the first column

of values gives the term name, the second column gives the

termwise contribution to the model's predictive capability, and

the third column gives the cumulative contribution to the model's

predictive capability.
133

Table IV-9 

Term Ranking for Raw Exhaust VOC Model

Term name Term Contribution

(percent)

Cumulative Contribution

(percent)

RVP

E200

E300

ARO

SUL

E300*E300

OLE

E300*ARO

E200*E200

OXY*RVP

SUL*E300

OXY

ARO*ARO

SUL*SUL

OXY*SUL

31.56

27.72

14.69

7.60

5.56

4.96

2.66

1.98

1.59

0.87

0.65

0.08

0.05

0.02

0.01

31.56

59.28

73.97

81.57

87.13

92.09

94.75

96.73

98.32

99.19

99.84

99.92

99.97

99.99

100.00

Table IV-10 

Term Ranking for Raw NOx Model

Term name Term Contribution

(percent)

Cumulative Contribution

(percent)

SUL

OLE

OLE*OLE

RVP

E200

ARO*ARO

SUL*SUL

E300

ARO

OXY

OXY*ARO

OXY*SUL

E300*OLE

OXY*OXY

OXY*RVP

E300*E300

50.98

28.74

8.60

3.47

2.77

1.76

1.69

0.68

0.56

0.24

0.16

0.15

0.14

0.03

0.02

0.01

50.98

79.72

88.32

91.79

94.56

96.32

98.01

98.69

99.25

99.49

99.65

99.80

99.94

99.97

99.99

100.00

Tables IV-9 and IV-10 show that some model terms contribute a

great deal to the explanatory power of the models, while others

contribute very little. These latter terms add complexity to the

Complex Model equations without a corresponding gain in

explanatory power. The Agency began the refinement process by
134

examining terms which contributed a combined 1 percent or less to

the corresponding models' sum of squares. The Agency also sought

to retain all linear terms in the refined VOC and NOx models

regardless of how much they contributed to the model sum of

squares in order to satisfy the provisions agreed to by the Agency

in the Agreement in Principle.

Applying the 1 percent cutoff to the VOC model would have

eliminated all terms below the OXY*RVP term in Table IV-9. These

terms contributed 0.81 percent of the raw model's sum of squares. 

Hierarchy considerations dictated retention of the linear oxygen

term despite its low explanatory contribution. A number of

commenters questioned whether the OXY*RVP term should be retained,

since fuel oxygen content and RVP were highly correlated in the

Complex Model database. In addition, the Agency's modeling

efforts indicated that models with the OXY*RVP term exhibited

unusual and unexplainable behavior. For these reasons, EPA chose

to add the OXY*RVP term to the list of terms to eliminate. 

Therefore, the following terms were marked for elimination from

the raw exhaust VOC model based on the results of the random

balance technique: OXY*RVP, SUL*E300, ARO*ARO, SUL*SUL, and

OXY*SUL.

Applying the 1 percent cutoff to the NOx model would have

eliminated all terms below the E300 term in Table IV-10. These

terms contributed 0.75 percent of the raw model's sum of squares. 

However, hierarchy considerations dictated retention of the firstorder aromatics and oxygen terms. Thus the following terms were

marked for elimination from the raw NOx model: OXY*ARO, OXY*SUL,

E300*OLE, OXY*OXY, OXY*RVP, and E300*E300.

c. Re-regression of the Raw Complex Model

Once the raw model was developed as described in the Sections

A.4 and A.5, it was evaluated using the random balance approach as

described in Section A.6 to determine the relative contribution of

individual model terms to the predictive power of the raw model. 

Terms retained after using an approximate cutpoint of 99 percent

were then pooled and a regression was run (using SAS) on those

terms to determine the coefficients shown in Section A.7 below for

each of the exhaust pollutants. Since the toxics models are

linear and only very few terms are present in each of the models,

the random balance technique was not used to refine the toxics

models. Thus, the regression coefficients for the exhaust toxics

models are identical to those shown in Section A.5.

7. Refined VOC and NOx Model Coefficients
135

Refined Exhaust VOC Model Coefficients

Table IV-11

Fuel

Term

Centered Refined Regression Model Coefficients for Exhaust VOC

TG 1 TG 2 TG 3 TG 4 TG 5 TG 6 TG 7 TG 9 HIGH

Oxygen -.00363 -.00363 -.00363 -.00363 -.00363 -.00363 -.00363 -.00363 -.00363

Sulfur .000515 .000274 .000515 .000836 .000876 .000209 .000515 .000515 -5.4E-5

RVP .03516 .01038 .03516 .03516 .03516 .03516 .03516 .03516 .04330

E200 -.00683 -.00360 -.00360 -.00360 -.00360 -.00360 -.00360 -.00360 -.00360

E300 -.00824 -.00824 -.00824 -.00824 -.00824 -.00824 -.00824 -.00824 -.00035

Aro .00355 .00355 .00355 -.00242 .00355 .00355 .00355 .00355 .00355

OLefins -.00286 -.00286 -.00286 -.00286 -.00286 -.00286 -.00286 -.00286 -.00286

E2002 .000106 .000106 .000106 .000106 .000106 .000106 .000106 .000106 .000106

E3002 .000408 .000408 .000408 .000408 .000408 .000408 .000408 .000408 .000408

Aro*E300 -.00029 -.00029 -.00062 -.00029 -.00029 -.00029 -.00029 -.00029 -.00029

Refined Exhaust NOx Model Coefficients

Table IV-12

Fuel

Term

Centered Refined Regression Model Coefficients for Exhaust NOx

TG 1 TG 2 TG 3 TG 4 TG 5 TG 6 TG 7 TG 9 HIGH

Oxygen .004409 .004409 -.00982 .004409 .004409 .004409 .004409 .004409 -.00913

Sulfur .000747 .000461 .000461 -7.1E-5 .000461 -1.5E-5 .000461 .000461 .000252

RVP .009077 .009077 .009077 .009077 .009077 .009077 .009077 .009077 -.01397

E200 .000931 .000931 .000931 .000931 .000931 .000931 .000931 .000931 .000931

E300 .002738 -7.7E-5 .002738 -.00302 .002738 .002738 .002738 .002738 -.00401

Aro -.00139 .002578 .002578 .002578 .002578 .002578 .002578 .002578 .002578

Olefins .002597 .002597 .002597 .002597 .002597 .002597 .002597 .002597 .002597

Sul2 -1.6E-6 -1.1E-6 0 0 0 0 0 0 0

Aro2 -8.0E-5 -.00022 -8.0E-5 -8.0E-5 -8.0E-5 -8.0E-5 -8.0E-5 -8.0E-5 -8.0E-5

Ole2 .000366 .000366 .000366 .000366 .000366 .000366 .000366 .000366 .000366

8. Simplification of the Refined Complex Model

After the raw exhaust Complex Model was refined (as discussed

in Section A.6) to eliminate terms that did not significantly

contribute to the model's predictive power, additional steps were

taken to simplify its structure. The first step was to reduce the

number of vehicle group equations in each pollutant-specific model

through an equation consolidation algorithm. The second step was
136

to convert the centered forms of the regression equations to an

uncentered form. Both of these simplification steps are described

below. EPA's reasons for simplifying the refined Complex Model

were similar to its reasons for refining the raw model.

a. Vehicle Group Consolidation

The statistical approach to the development of the exhaust

Complex Model resulted in separate equations for each vehicle

technology type and emitter class. Since there were eight normal

emitter technology type equations and a single higher emitter

equation, the raw Complex Model had a total of nine vehicle group

equations for each pollutant. The EPA determined that all nine

vehicle group equations would not be necessary if the behavior of

the model could be duplicated through simpler or fewer equations. 

Therefore, a vehicle group consolidation algorithm was applied to

the refined Complex Model.

The consolidation methodology proposed in the July 15, 1993

submittal to the docket made use of "pseudo-geometric averaging." 

In this methodology, the weighting factors wi (described in

Section III.B.4) were applied directly to the model term

coefficients within the exponentials. Although not strictly

mathematically correct, this method allowed the weighted

coefficients to be summed across normal emitter vehicle groups,

and resulted in a single equation that approximated the original

set of eight. Thus the final form of the proposed Complex

Model(s) in the July package contained two equations, one

representing normal emitters and a second representing higher

emitters. 

In applying pseudo-geometric averaging to the Complex Model,

two factors tended to reduce the accuracy of the consolidated

equations:

 Pseudo-geometric averaging resulted in an equation for normal

emitters whose emission performance estimates were offset

with respect to the refined and raw models' estimates. In

other words, the consolidated model had a consistent bias

with respect to the refined and raw models.

 The accuracy of pseudo-geometric averaging broke down for

large values of the independent variables (fuel parameters).

EPA considered correcting the consistent bias through the

application of a fixed correction factor to the consolidated

equations. However, EPA found no mechanism to correct the

increasing inaccuracy of the consolidated model as the value of

the fuel parameters increased. These two sources of inaccuracy

implied that pseudo-geometric averaging was not an appropriate

consolidation methodology, and EPA chose to discard pseudo-
137

geometric averaging for the final rulemaking in favor of a more

accurate and reliable consolidation approach.

EPA followed the same guidelines for these alternative

consolidation techniques that it applied to the pseudo-geometric

consolidation approach:

1) The unextrapolated forms of the regression equations

were used during the consolidation process instead of

the extrapolated forms.

2) EPA chose to consolidate the models into two equations,

one for normal emitters and a second for higher

emitters. Consolidation to a single equation would have

required that a separate Complex Model be promulgated

for each Phase of the reformulated gasoline program

since the vehicle group weighting factors are different

in each Phase. In addition, EPA expected any bias or

inaccuracy to be more apparent if normal and higher

emitters were consolidated into a single equation than

if normal emitters alone were consolidated (as had been

the case when using the pseudo-geometric consolidation

method).

3) The form and emission response characteristics of the

consolidated model were to remain similar to the form

and behavior of the unconsolidated refined model.

The random balance algorithm, introduced in Section A.6 as a

means of refining the raw models, can also be used to develop

consolidated regression equations. Consolidation is a by-product

of using random balance to rank model terms in order of

contribution to the model sum of squares. For the purposes of

regression equation consolidation, the random balance algorithm

can be summarized by the following three steps:

1) Generate 2000 random fuel blends distributed evenly across

the fuels space. The valid range limits discussed in Section

D.2 provided the maximum and minimum values for each fuel

parameter.

2) For each fuel blend, determine the emissions of VOC, NOx, and

toxics in grams/mile for the normal emitter exhaust Complex

Model. This step results in fleet average emission estimates

for normal emitters that represent the emission-weighted

results from the individual regression equations.

3) Treat the emission estimates from step (2) as a data set, and

execute a simple, multi-parameter regression (using a least

squares polynomial fit) on the natural log of these emission

estimates. The fuel parameters for the 2000 fuels from step

(1) operate as independent variables in this step.
138

Thus the random balance algorithm fits a single equation to the

results of a set of equations which duplicates their behavior in a

simpler form. Details of the random balance algorithm are

provided in Appendix IV-A.

The random balance algorithm yields a consolidated equation

that will necessarily be biased in its predictions as compared to

the unconsolidated model on which it is based. This bias arises

because the step (3) regressions are done in natural logarithm

space. The least squares fit to the natural logarithm of the

emission estimates calculated in step (2) results in normallydistributed emission estimates about the polynomial regression

equation. The exponential of the new regression equation is then

taken to convert the natural logarithm of emissions back to

emissions in grams/mile and place it in the same form as the

unconsolidated model. Exponentiation causes the distribution of

emission performances calculated in step (2) to become skewed in

one direction rather than remaining evenly distributed. As a

result, the consolidated model tends to estimate slightly larger

emission benefits than the unconsolidated model.

The bias introduced into the consolidated Complex Model

through the random balance algorithm is of the same magnitude and

direction as the bias introduced by pseudo-geometric averaging. 

However, EPA has determined that the merits of consolidation

outweigh the detriment posed by such bias since it is negligible,

as discussed below. In addition, EPA carried out an analysis of

the extent of the bias and concluded that no bias correction

through fixed correction factors or other means need be

implemented. The details of the analysis are given below.

The analysis of the consolidated Complex Model began with the

creation of 500 randomly generated fuel blends in an identical

manner to step (1) of the consolidation process. Then both the

consolidated and unconsolidated models were evaluated for each

fuel, and the difference between the two emission performances

were recorded. The product of the analysis was a set of

performance differences for each pollutant, one for each of the

500 random blends, equal to the performance of the consolidated

model for a given pollutant and target fuel minus the performance

of the unconsolidated model for the same pollutant and target

fuel. If no bias were present, the average performance delta

would be zero. Based on the form of the exhaust Complex Model

equations, EPA expected the bias to result in negative performance

differences. The average performance difference for summer, Class

C areas is given in Table IV-13.
139

Table IV-13

 Consolidation Performance Differences

Pollutant Phase I Phase II

Exhaust benzene

Non-exhaust benzene

1,3-Butadiene

Acetaldehyde

Formaldehyde

POM

Total toxics

-0.0762

 0.0

-0.0565

-0.3157

 0.0001

 0.0

-0.0620

-0.0651

0.0 

-0.0482

 -0.2696 

 0.0001

 0.0 

-0.0610

Exhaust VOC

Non-exhaust VOC

Total VOC

-0.02 

0.0 

-0.0073

-0.02 

0.0 

-0.0130

NOx 0.0043 0.0043

Before drawing conclusions from the values in Table IV-13, a

number of comments should be made. First, the models for

nonexhaust benzene, nonexhaust VOC, and exhaust POM did not

require consolidation, which is why their performance differences

were zero. They are included in Table IV-13 because it is the

bias for total toxics, total VOC, and NOx which determines the

accuracy of the consolidated Complex Model compared to that of the

unconsolidated Complex Model. Second, the expected negative value

for the performance differences was not exhibited for NOx and

formaldehyde. However, the positive performance differences are

all very small, and most likely result from two sources:

1) A consolidated equation that represents the behavior of

the unconsolidated model very well.

2) Random variation in the calculated emission estimates

for the random fuel blends.

The performance differences in Table IV-13 must be examined

in terms of their contribution to total toxics, total VOC, and NOx

because it is these three quantities that are regulated by the

reformulated gasoline program. Thus the average performance

differences were weighted according to the gram/mile emission

values for Clean Air Act (CAA) baseline fuel to obtain values for

total toxics and total VOC. After doing so, EPA has determined

that the average performance differences for total toxics, total

VOC, and NOx are negligible for the following reasons:

 The measurement uncertainty for the Complex Model

fuel parameters create emission estimate
140

uncertainty that is larger than the error

introduced by consolidating normal emitter

technology groups.

 The error introduced by consolidation for VOC and

toxics is small relative to the overall emission

reductions required by the program for these

pollutants.

 The error introduced by consolidation for NOx is

favorable, i.e., on average, the consolidated model

slightly overestimates the emissions from a given fuel,

though the error for any given fuel may be unfavorable. 

As a result, fuels that meet the NOx requirements of the

program under the consolidated model will, on average,

meet the NOx requirements under the unconsolidated model

by a slightly larger margin. 

For these reasons, EPA decided that the small average performance

differences did not require the application of fixed correction

factors or other measures in order to assure the integrity of the

reformulated gasoline and anti-dumping programs.

b. Uncentering

The statistical approach to the development of the Complex

Model included the use of centered independent variables. A

centered variable is one in which the variable is represented as a

deviation from some fixed value rather than just as its measured

value. This fixed value is called the "centering value." Thus

the centered form of the aromatics variable could be written as 

ARO - AROc

where ARO is the amount of aromatics in a given fuel in units of

volume percent, and AROc is the centering value of aromatics, also

in units of volume percent. Similar centered variables can be

constructed for all independent variables in the Complex Model:

OXY - OXYc SUL - SULc RVP - RVPc

E200 - E200c E300 - E300c OLE - OLEc

BEN - BENc MTB - MTBc ETB - ETBc

ETH - ETHc TAM - TAMc

Thus the linear, squared, and interactive terms in the Complex

Model take the following forms:

Linear: c1 * (RVP - RVPc)

Squared: c2 * (SUL - SULc)2

Interactive: c3 * (ARO - AROc) * (E300 - E300c)
141

where c1, c2, and c3 are coefficients determined through

statistical regression techniques. The centering value of each of

the 12 independent variables is approximately the mean value of

that variable measured across all observations in the Complex

Model database. The precise mean value was not used as the

centering value for three main reasons:

 The mean values are different for each pollutant, since not

all observations measured each pollutant.

 The centering values were calculated before all of the

studies included in the Complex Model database were made

available to EPA. Once these additional studies were

included in the database, the mean values and previouslycalculated centering values diverged.

 If the mean values were used as the centering values, then

the centering values would have changed as individual

observations were excluded based on the outlier and

influential point criteria discussed in Section A.4.

The centering values used in EPA's regressions are repeated below:

Table IV-14

Centering Values Used in Exhaust Complex Model

Fuel parameter Centering value

Oxygen

Sulfur

RVP

E200

E300

Aromatics

Olefins

Benzene

MTBE

ETBE

Ethanol

TAME

1.774834

204.5779

8.611479

46.72577

85.89620

28.26109

7.318716

1.066683

0.947240

0.023204

0.314352

0.016443

Centered independent variables were used in the development

of the Complex Model to minimize collinearity problems. Once the

regressions were completed, EPA chose to remove the centering

values in order to simplify the form of the Complex Model

equations. Algebraic manipulations of the regression equations

yielded equations that contained only the variables themselves,

rather than centered variables. This "uncentering" process

resulted in a simplified version of the Complex Model equations.
142

A hypothetical example can help illustrate the uncentering

algorithm. The Complex Model exhaust emission equations take the

following form: 

(A.1) Y(t) = [exp(f(t))/exp(f(b)) - 1] * 100

where "Y(t)" is the percent change in the exhaust emissions of any

exhaust pollutant Y, "t" refers to the set of target fuel

parameter values, and "b" refers to the set of baseline fuel

parameter values. The hypothetical second-order function f can be

written in its centered form as

(A.2) f(A,B) = 1(A - Ac) + 2(B - Bc) + 3(A - Ac)2

 +

4(B - Bc)2

 + 5(A - Ac)*(B - Bc)

where A and B represent hypothetical fuel parameters (independent

variables), and the coefficients i are constants that are

determined through statistical regressions.

The function f can be expanded to yield

(A.3) f(A,B) = 1A - 1Ac + 2B - 2Bc +

3A2

 - 23AAc + 3Ac

2

 + 4B2 - 24BBc + 4Bc

2

+

5AB - 5ABc - 5AcB + 5AcBc

Grouping similar terms yields

(A.4) f(A,B) = A * (1 - 23Ac - 5Bc) +

B * (2 - 24Bc - 5Ac) +

A2 * (3) +

B2 * (4) +

AB * (5) +

(-1Ac - 2Bc + 3Ac

2

 + 4Bc

2

 + 5AcBc)

At this point every variable in Equation (A.4) is expressed in its

uncentered form. The coefficients for the second-order terms

remain the same while the coefficients for the first-order terms

are now functions of the i and the centering values. In

addition, the function f now contains a constant. Equation (A.4)

can be rewritten more succinctly as follows:

(A.5) f(A,B) = 1A + 2B + 3A2

 + 4B2 + 5AB + 

where the i and  are defined as follows

1 = 1 - 23Ac - 5Bc

2 = 2 - 24Bc - 5Ac

3 = 3

4 = 4

5 = 5

 =-1Ac - 2Bc + 3Ac

2

 + 4Bc

2

 + 5AcBc
143

The i and are constants just as the i and centering values are

constants. Since the uncentered form of the function f in

Equation (A.5) is mathematically identical to the centered form in

Equation (A.2), the centered form of the function can be replaced

with the uncentered form without altering the model's behavior.

The Complex Model can be simplified still further by deleting

constants. Since the exhaust emission performance of a given fuel

is calculated using a ratio of two exponentials, constants found

in both exponentials will cancel one another when calculating

exhaust emission performance. The percent change in the exhaust

emissions of a pollutant Y can be calculated from Equation (A.1)

as follows (using the hypothetical exhaust emission function f

from Equation (A.5) to illustrate the point): 

(A.1) Y(t) = [exp(f(t))/exp(f(b)) - 1] * 100 

Incorporating Equation (A.5) into Equation (A.1) yields

 exp(1At + 2Bt + 3At

2

 + 4Bt

2

 + 5AtBt + ) 

(A.6) Y(t) = exp(1Ab + 2Bb + 3Ab

2

 + 4Bb

2

 + 5AbBb + ) - 1 

* 100

where At indicates the level of fuel parameter A in the target

fuel, while Ab indicates the level of fuel parameter A in the

baseline fuel. The exponential of a sum of two quantities is

defined as the product of the exponentials of each of those two

quantities. Thus Equation (A.6) can be written as follows:

exp(1At + 2Bt + 3At

2

 + 4Bt

2

 + 5AtBt)exp() 

(A.7) Y(t) = exp(1Ab + 2Bb + 3Ab

2

 + 4Bb

2

 + 5AbBb)exp() - 1 

* 100

The exp() terms cancel one another, and the equation for Y(t)

simplifies to

exp(1At + 2Bt + 3At

2

 + 4Bt

2

 + 5AtBt) 

(A.8) Y(t) = exp(1Ab + 2Bb + 3Ab

2

 + 4Bb

2

 + 5AbBb) - 1  * 100

Thus the constant , which was introduced into the function f

through the uncentering algorithm, can be dropped from the

function f altogether. The remaining function, devoid of the

constant , then contains only the uncentered variables and their

coefficients. Equation (A.8) is mathematically identical to the

centered form implied by Equations (A.1) and (A.2), so the

centered form of f can be replaced with the uncentered form

without altering the model's behavior in any way.

9. Final Complex Models
144

The simplification methodology described in Section A.8

produces two complex model equations (one for normal emitters and

one for higher emitters) for each pollutant. The coefficients

shown below represent the final, simplified coefficients for each

pollutant. The details of how to compute in-use performances and

in-use mass emissions for a target fuel from these coefficients

are discussed more fully in Section C.

Final Exhaust VOC Model

Table IV-15

Fuel

Term

Final Exhaust VOC Model Coefficients

Normal Emitters Higher Emitters

Oxygen -0.003641 -0.003626

Sulfur 0.0005219 -0.000054

RVP 0.0289749 0.0432950

E200 -0.014470 -0.013504

E300 -0.068624 -0.062327

Aromatics 0.0323712 0.0282042

Olefins -0.002858 -0.002858

E2002 0.0001072 0.0001060

E3002 0.0004087 0.0004080

Aromatics*E300 -0.0003481 -0.000287
145

Final Exhaust NOx Model

Table IV-16

Fuel

Term

Final NOx Model Coefficients

Normal Emitters Higher Emitters

Oxygen 0.0018571 -0.00913

Sulfur 0.0006921 0.000252

RVP 0.0090744 -0.01397

E200 0.0009310 0.000931

E300 0.0008460 -0.00401

Aromatics 0.0083632 0.007097

Olefins -0.002774 -0.00276

Sulfur2 -6.63 x 10-7 0

Aromatics2 -0.000119 -7.995 x 10-5

Olefins2 0.0003665 0.0003665

Final Exhaust Benzene Model

Table IV-17

Fuel

Term

Final Exhaust Benzene Model Coefficients

Normal Emitters Higher Emitters

Oxygen 0 -0.096047

Sulfur 0.0006197 0.000337

E200 -0.003376 0

E300 0 0.011251

Aromatics 0.026550 0.011882

Benzene 0.222390 0.222318
146

Final Exhaust 1,3-Butadiene Model

Table IV-18

Fuel

Term

Final 1,3-Butadiene Model Coefficients

Normal Emitters Higher Emitters

Oxygen 0 -0.060771

Sulfur 0.0001552 0

E200 -0.007253 -0.007311

E300 -0.014866 -0.008058

Aromatics -0.004005 -0.004005

Olefins 0.0282350 0.0436960

Final Exhaust Formaldehyde Model

Table IV-19

Fuel

Term

Final Formaldeyde Model Coefficients

Normal Emitters Higher Emitters

E300 -0.010226 -0.010226

Aromatics -0.007166 -0.007166

Olefins 0 -0.031352

MTBE 0.0462131 0.0462131
147

Final Exhaust Acetaldehyde Model

Table IV-20

Fuel

Term

Final Acetaldehyde Model Coefficients

Normal Emitters Higher Emitters

Sulfur 0.0002631 0.0002627

RVP 0.0397860 0

E300 -0.012172 -0.012157

Aromatics -0.005525 -0.005548

MTBE -0.009594 -0.055980

ETBE 0.3165800 0.3164665

Ethanol 0.2492500 0.2493259

The final coefficients for exhaust POM are identical to the final

coefficients shown for exhaust VOC in Table IV-15.

The aldehyde models are oxygenate specific. In Tables IV-19

and IV-20 the formaldehyde and acetaldehyde models contain MTBE

(methyl tertiary butyl ether), ETBE (ethyl tertiary butyl ether),

and ethanol terms. These terms represent the amount of oxygen (in

terms of weight percent) present in the fuel in the form of the

particular oxygenate in question. Data on the effects of MTBE,

ETBE, ethanol, and TAME (tertiary amyl methyl ether) on aldehyde

emissions were available in the Complex Model database. TAMEspecific terms were not found to be statistically significant in

the regression equations for either aldehyde and thus do not

appear in the final models.

The following procedure should be used to evaluate the

emission performance of fuels containing oxygenates other than

MTBE, ETBE, ethanol, or TAME. If the oxygenate is any type of

methyl ether other than TAME, use the MTBE terms to evaluate its

effects on aldehyde emissions. If the oxygenate is any type of

ethyl ether, use the ETBE terms to evaluate its effect on aldehyde

emissions. This distinction is made because the ethyl/methyl

group functionality (in the ether compound) is expected to play

the most important role in the combusion chemistry and kinetics

which produce the aledhydes. If the oxygenate is an alcohol other

than methanol, use the ethanol terms to evaluate its effect on

aldehyde emissions. If the oxygenate is neither an ethyl or

methyl ether (i.e, if it is any higher order ether), use the ETBE

terms to evaluate all toxic performances. This approach was taken

since, given the lack of data on the effects of higher order

ethers on aldehyde emissions, EPA considers the performance of
148

ETBE (which is the highest-order and heaviest ether for which

aldehyde effects data is available in the database) to be the best

available estimate of the aldehyde effects of higher-order and

heavier ethers. Fuels containing any other oxygenate (including

methanol) in greater than trace amounts cannot be certified using

the Complex Model unless the Model is augmented with the results

of an appropriately designed and conducted vehicle testing

program, as outlined in Section G.

10. Response to Comments

A number of comments have been made on issues related to the

development of the Complex Model. These comments are discussed

separately below for each subject area.

Although no commenters had objections to vehicle group 

consolidation, the proposed pseudo-geometric averaging approach to

consolidation was considered inappropriate by some. The two main

objections to this approach were:

1) It is mathematically incorrect; and

2) It results in a bias in the consolidated model that

might have required the use of performance margins to

offset this bias.

The Agency showed in the July 15, 1993 docket submission that

although pseudo-geometric averaging is not mathematically correct,

it does in fact result in a consolidated Complex Model that is

sufficiently accurate. Regardless, pseudo-geometric averaging has

been replaced by the more reliable and accurate random balance

approach to consolidation, eliminating this concern. In addition,

EPA's analysis of the final, consolidated Complex Model showed

that no margins or offsets need be applied to the regression

equations or the performance standards when the random balance

approach is used for consolidation. Those parties that commented

on the random balance consolidation approach put forth as an

alternative consolidation method in the July 15 docket submittal

had no objections to its use. Details of the random balance

approach and the analysis of any resulting bias are given in

Section A.8.

Commenters also expressed concern about the number of

equations in the final Complex Model. Several commenters asserted

that a single consolidated equation could represent the essential

behavior of the Complex Model as well as two or more equations. 

The Agency chose not to consolidate down to a single equation for

the following reasons (see Section A.8 for more details):
149

 Many potential users of the Complex Model expressed a

desire to see separate effects for normal and higher

emitting vehicles.

 The Agency recognized that further simplification would

yield diminishing returns as the models became simpler. 

Consolidating into a single equation would require the

promulgation of two unique Complex Models, since the

vehicle group weighting factors are different for each

Phase of the program. Thus the greater simplicity of a

single equation would be offset by the need to use

separate equations for each Phase.

 The analysis of the consolidated equations showed that

no offsets needed to be applied to the model to correct

for bias introduced through random balance consolidation

to two equations. However, the same would not have been

true if the raw model had been consolidated down to a

single equation. The differences between normal and

higher emitter equations are greater than the

differences among normal emitter technology groups, and

these greater differences would increase the size of the

bias introduced through consolidation. In other words,

the bias would be expected to increase and become

significant in the context of the reformulated gasoline

and anti-dumping programs if the model were consolidated

to a single equation for each pollutant.

 Consolidation from two equations to one equation does

not significantly increase the simplicity of the Complex

Model or decrease the calculation time. A single

equation also would not facilitate incorporation of the

Complex Model into linear programming models or

significantly simplify the derivation and application of

extrapolation equations compared to two-equation models.

Some commenters also stressed that "overestimation of

emission benefits" was an inappropriate descriptor of the bias

introduced through consolidation. These commenters particularly

disagreed with the use of this phrase in describing the proposal

to implement correction factors or offsets to the consolidated

Complex Model. As described above, this phrase is provided as a

description of the behavior of the consolidated Complex Model in

comparison to the unconsolidated Complex Model only. In other

words, consolidation results in Complex Model behavior that is

consistently skewed in one direction with respect to the raw

vehicle group equations. The Agency did not and does not wish to

imply that the consolidated Complex Model provides unwarranted

emission benefits when estimating real, in-use emissions. In

addition, the proposal to apply margins or offsets to correct for

this bias was presented simply as a mathematical correction

factor. As stated above, however, the bias is too small to
150

require any such correction factors when using the random balance

method to consolidate the normal emitter technology group

equations into a single equation.

Another set of comments focused on which of the three EPA

options proposed in July [see A-92-12 Docket submittals #IV-B-4,

July 1993 and #IV-B-5, July 1993] was most accurate while at the

same time fungible and simple to use. Most of the comments

focused on the following points:

 Any models that contain extrema points within the

allowable range of the model should not be consdiered

due to the possible blending problems that they may

cause

 Option 2 should be chosen for all pollutants since

maxima values in option 1 result in unexplainable

behavior

 Option 3 is oversimplifed

 Option 1 has "superior" aromatics and E300 responses and

is "most" technically correct and thus should be chosen

for all pollutants

 The effect of sulfur on VOC and NOx has been

underestimated by all the EPA options

 Olefins should be excluded from the model because

reducing olefins increases VOC emissions in all options

 Simplification of emissions equation structure while

retaining accuracy is very important

EPA has addressed most of these comments in arriving at the

final exhaust models shown in Section A.9. The final model chosen

for VOC was the option 1 model with the OXY*RVP term removed,

since this term caused the model to behave in ways not supported

by the available data and since few well-controlled observations

were available to estimate this term. The final model chosen for

NOx was the option 1 model. The toxics models are all linear. 

EPA believes that the ARO*E300 interactive term in the exhaust VOC

model is needed to represent the aromatics and E300 effects

accurately. The olefins effect in the final VOC model shows

emissions to increase as olefins are decreased which is what is

expected from data that exist in the Complex Model database. EPA

believes the squared terms (Sulfur2, aromatics2 and olefins2)

present in the NOx model are necessary to accurately predict fuel

effects on emissions. All extrema values (emission maxima or

minima) have been handled by appropriate extrapolation procedures

(see Section D.3). The predictability analysis in Section F.2

indicates that the final models chosen by EPA for VOC, NOx and
151

toxics accurately predict the exhaust emission effects from fuel

modifications. EPA believes that the final models being

promulgated are sufficiently simple without sacrificing accuracy.

B. Complex Model for Non-Exhaust Emissions

Vehicle emissions can be separated into two broad categories: 

exhaust emissions, resulting from combustion of the fuel, and

nonexhaust emissions, resulting from fuel evaporation, vapor

displacement, and permeation. The Agency has developed nonexhaust

models using a different process from that used to develop the

exhaust portion of the Complex Model. The nonexhaust model

predicts emissions of volatile organic compounds (VOC) and benzene

in warmer "Class B" and cooler "Class C" areas; in the

regulations, preamble, and other supporting documents for the

reformulated gasoline rule, Class B areas are referred to as VOC

Control Region 1 and Class C areas are referred to as VOC Control

Region 2. The nonexhaust VOC model was derived from EPA's Highway

Vehicle Emission Factor MOBILE models, while the nonexhaust

benzene model was derived from correlations originally developed

from General Motors' thermodynamic vapor equilibrium model. The

behavior of the non-exhaust benzene model has been confirmed by

EPA through independent emissions testing. The remainder of this

section describes the derivation and use of the Complex Model for

nonexhaust emissions.

EPA subdivides nonexhaust VOC emissions into evaporative,

running loss, and refueling VOC emissions. These emissions are

primarily a function of fuel volatility (RVP). Nonexhaust benzene

emissions are the only nonexhaust toxic emissions source regulated

by the reformulated gasoline program and are primarily a function

of RVP, benzene, and MTBE. MTBE is the only oxygenate currently

known to inhibit benzene vapor pressure at a given RVP level. The

simple model addressed these very same factors, so the Complex

Model for nonexhaust emissions follows the same development

pattern as that for the simple model: the Complex Model for

nonexhaust emissions includes only the effects of fuel benzene,

RVP, and MTBE levels on nonexhaust benzene emissions, and RVP on

nonexhaust VOC emissions. The July 11, 1991 MOBILE4.1 model with

basic I/M and the MOBILE5a model with enhanced I/M were used to

estimate nonexhaust VOC emissions for the Phase I and Phase II

timeframes, respectively. These two MOBILE models have been

described in Section III. The derivation of the Phase I Complex

Model for nonexhaust VOC emissions is described in Section B.1

below, while the analogous Complex Model for Phase II nonexhaust

VOC emissions is described in Section B.2. The Complex Model for

nonexhaust toxics emissions is covered in Section B.3.

1. Phase I Nonexhaust VOC Emissions Model
152

The Phase I relationship between nonexhaust VOC emissions and

RVP was developed by fitting a curve to nonexhaust VOC emission

predictions provided by MOBILE4.1. Since the same technique was

used to develop the nonexhaust portion of the simple model, the

nonexhaust VOC emissions equations in the Phase I Complex Model

are exactly the same as the the nonexhaust VOC equations in the

simple model. 

To assess the relationship between the Reid vapor pressure of

a given fuel and the nonexhaust VOC emissions that such a fuel

would be expected to produce, MOBILE4.1 was run for the year 2015

with summer temperatures and the basic I&M scenario described

previously. Fuel RVP levels ranged from 6.5 to 8.7 psi (the input

file is shown in Appendix IV). The year 2015 was chosen as the

target year to allow MOBILE4.1 to model a hypothetical in-use

fleet composed entirely of vehicles with 1990 technology. 

Separate results for Class C and Class B areas were produced,

since these areas' different average minimum and maximum summer

temperatures for high ozone days alter the relationship between

RVP and nonexhaust VOC emissions.

Each set of MOBILE4.1 results gave emission factors in terms

of total grams of VOCs per mile, categorized by vehicle type (LDV,

HDV, etc.) and emission type (refueling losses, evaporative

losses, and running losses). Both the simple model and Phase I

Complex Model are based on results for light-duty vehicles (i.e.,

cars). Table IV-21 shows the MOBILE4.1 results that were used to

develop the Phase I Complex Model for nonexhaust VOC emissions.
153

Table IV-21

Nonexhaust Emissions from MOBILE4.1 (July 11, 1991) 

Class RVP

VOC emissions for LDGVs in grams

per mile:

Refueling

Losses

Running

Losses

Evaporative

Losses

C 8.7 

8.5 

8.3 

8.1 

7.9 

7.7 

7.5 

7.2 

7.0 

0.04 

0.04 

0.04 

0.04 

0.04 

0.03 

0.03 

0.03 

0.03 

0.39

0.36

0.33

0.31

0.28

0.25

0.23

0.20

0.34

0.31

0.29

0.27

0.25

0.23

0.21

0.19

0.18

B 8.7 

8.5 

7.8 

7.6 

7.4 

7.2 

7.0 

6.8 

6.6 

0.04 

0.04 

0.03 

0.03 

0.03 

0.03 

0.03 

0.03 

0.03 

0.43

0.40

0.29

0.26

0.23

0.39

0.36

0.27

0.25

0.23

0.21

0.20

0.18

0.17

A numeric polynomial regression was carried out for each of

the three emission types (running, refueling, and evaporative

losses) to produce a relationship giving VOC emissions in grams

per mile as a function of the Reid vapor pressure in pounds per

square inch. This regression resulted in separate equations for

Class B and Class C areas, as shown in Table IV-22. 
154

Table IV-22

Phase I Nonexhaust Emission Regressions as a Function of RVP

Area

Class Vapor source Curve Fit R2

B Refueling 0.006668 * RVP - 0.018 0.685

B Running 0.002791 * RVP2 + 0.1096 * RVP -

0.734

1.000

B Evaporative 0.02293 * RVP2

 - 0.2461 * RVP +

0.7952

0.999

C Refueling 0.006668 * RVP - 0.018 0.685

C Running 0.016255 * RVP2

 - 0.1306 * RVP +

0.2963

0.998

C Evaporative 0.021239 * RVP2

 - 0.2393 * RVP +

0.813

0.999

Evaporative emissions within the MOBILE emissions model

include both hot-soak and diurnal emissions, but they are not

given in units of grams per mile. This conversion requires

calculation of a hot soak/diurnal ratio from the MOBILE4.1

database. The average weighting over all vehicle ages is 67.9

percent hot soak and 32.1 percent diurnal. Based on these

proportions, the evaporative emission equations can be split into

separate equations for hot soak and diurnal emissions, as shown in

Table IV-23.

Table IV-23

Evaporative Emissions Breakdowns into Hot Soak and Diurnal 

Area

Class Vapor source Curve Fit

B Hot Soak 0.01557 * RVP2 - 0.1671 * RVP + 0.5399

B Diurnal 0.00736 * RVP2

 - 0.0790 * RVP + 0.2553

C Hot Soak 0.014421 * RVP2 - 0.16248 * RVP +

0.5520

C Diurnal 0.006818 * RVP2

 - 0.07682 * RVP +

0.2610

2. Phase II Nonexhaust VOC Emissions Model

The Phase II Complex Model takes effect in the year 2000. 

The equations giving nonexhaust VOC emissions for the Phase II
155

Complex Model were derived in an analogous manner to that for the

Phase I model, with three main differences: MOBILE5a was used

instead of the July 11, 1991 version of MOBILE4.1, an enhanced I&M

program was assumed instead of a basic I&M program, and emissions

from light-duty trucks were considered in addition to emissions

from passenger cars. Thus nonexhaust VOC emissions were modeled

through curve fits to data produced by the MOBILE5a emissions

model (the input file to MOBILE5a is located in Appendix IV). 

Again, the year 2015 was chosen as the target year to force

MOBILE5a to consider only 1990 engine technology and evaporative

emission control systems. And as discussed in Section III, an

enhanced I&M scenario was assumed to apply to Phase II.

The Phase II Complex Model for nonexhaust emissions was based

on the MOBILE5a results for both light-duty cars and trucks

because sufficient data on light-duty truck exhaust emission

effects of fuel modifications now exist to allow the exhaust

emission portion of the Complex Model to cover both vehicle types. 

When the simple model was developed, very few light-duty trucks

had been tested. Emissions from heavy-duty gasoline trucks

(HDGTs) have been ignored for two reasons: HDGTs comprise only 3

percent of the vehicle miles travelled by the in-use fleet (as

estimated by MOBILE5a), and EPA does not have sufficient data to

describe the exhaust emissions performance of HDGTs as a function

of fuel parameters. To maintain a consistent basis for both the

exhaust and nonexhaust models, EPA chose to exclude heavy-duty

gasoline trucks from the baseline emissions inventories and

emission models for both exhaust and nonexhaust emissions.

To assess the relationship between the Reid vapor pressure of

a given fuel and nonexhaust VOC emissions, MOBILE5a was run for

the year 2015 under an enhanced I&M scenario with fuel RVPs

ranging from 6.5 to 9.9. Separate results for Class C and Class B

areas were produced. Each set of results gave emission factors in

terms of total grams of VOCs per mile, categorized by vehicle type

(LDV, HDV, etc.) and emission type (refueling, evaporative, and

running losses). Table IV-24 shows the MOBILE5a results that were

used to develop the Phase II Complex Model for nonexhaust VOC

emissions.
156

Table IV-24

Nonexhaust Emissions from MOBILE5a 

Class RVP

VOC emissions in grams per mile:

Refueling

Losses

Running

Losses

Evaporative

Losses

LDGV LDGT LDGV LDGT LDGV LDGT

C 9.9

9.7

9.5

9.3

9.1

8.9

8.7 

8.5 

8.3 

8.1 

7.9 

7.7 

7.5 

7.3 

7.1 

6.9 

6.7 

6.5 

0.05

0.05

0.05

0.05

0.05

0.05

0.05

0.05

0.05

0.05

0.04

0.04

0.04

0.04

0.04

0.04

0.04

0.04

0.07

0.07

0.07

0.07

0.07

0.07

0.06

0.06

0.06

0.06

0.06

0.06

0.06

0.06

0.06

0.05

0.05

0.05 

0.58

0.51

0.44

0.41

0.39

0.37

0.34

0.32

0.30

0.28

0.26

0.24

0.21

0.19

0.17

0.15

0.14

0.14

0.28

0.25

0.23

0.21

0.21

0.20

0.19

0.19

0.18

0.17

0.16

0.16

0.15

0.14

0.13

0.13

0.12

0.12

0.23

0.21

0.19

0.18

0.17

0.16

0.14

0.14

0.13

0.12

0.11

0.10

0.09

0.09

0.08

0.08

0.08

0.07

0.24

0.22

0.19

0.17

0.15

0.15

0.14

0.13

0.13

0.12

0.11

0.10

0.09

0.09

0.08

0.08

0.08

0.08

B 9.9

9.7

9.5

9.3

9.1

8.9

8.7 

8.5 

8.3 

8.1 

7.9 

7.7 

7.5 

7.3 

7.1 

6.9 

6.7 

6.5 

0.05

0.05

0.05

0.05

0.05

0.05

0.05

0.05

0.05

0.05

0.04

0.04

0.04

0.04

0.04

0.04

0.04

0.04

0.07

0.07

0.07

0.07

0.07

0.07

0.06

0.06

0.06

0.06

0.06

0.06

0.06

0.06

0.06

0.05

0.05

0.05 

0.66

0.58

0.49

0.47

0.44

0.42

0.39

0.36

0.34

0.31

0.29

0.26

0.24

0.21

0.18

0.16

0.15

0.15

0.29

0.26

0.23

0.23

0.22

0.21

0.21

0.20

0.20

0.19

0.18

0.18

0.17

0.16

0.16

0.15

0.15

0.15

0.29

0.26

0.24

0.22

0.20

0.19

0.18

0.16

0.15

0.14

0.13

0.12

0.11

0.10

0.10

0.09

0.08

0.08

0.31

0.27

0.24

0.23

0.21

0.19

0.18

0.16

0.15

0.14

0.13

0.12

0.12

0.11

0.10

0.09

0.09

0.08

The default values from MOBILE5a for the percent of vehicle

miles traveled (VMT) by each vehicle type was used to produce a

weighted average of the results for light-duty cars and trucks. 

In the MOBILE5a output, these values are listed as 58.2% for

light-duty gasoline vehicles (LDGVs) and 29.3% for light-duty
157

gasoline trucks (LDGTs), with the remainder consisting of diesel

vehicles, heavy-duty gasoline vehicles, and motorcycles. 

Normalizing these two values, the relative weighting of VMT

becomes 66.5 percent for light-duty gasoline cars and 33.5 percent

for light-duty gasoline trucks. These weightings were applied to

the values in Table IV-24 above. The resulting values are shown

in Table IV-25. 
158

Table IV-25

Nonexhaust Emissions from MOBILE5a 

Class RVP

VOC emissions in grams per mile:

Refueling

Losses

Running

Losses

Evaporative

Losses

C 9.9

9.7

9.5

9.3

9.1

8.9

8.7 

8.5 

8.3 

8.1 

7.9 

7.7 

7.5 

7.3 

7.1 

6.9 

6.7 

6.5 

0.0567

0.0567

0.0567

0.0567

0.0567

0.0567

0.0533

0.0533

0.0533

0.0533

0.0467

0.0467

0.0467

0.0467

0.0467

0.0433

0.0433

0.0433 

0.4795

0.4229

0.3697

0.3430

0.3297

0.3131

0.2898

0.2765

0.2598

0.2432

0.2265

0.2132

0.1899

0.1733

0.1566

0.1433

0.1333

0.1333

0.2333

0.2133

0.1900

0.1767

0.1633

0.1567

0.1400

0.1367

0.1300

0.1200

0.1100

0.1000

0.0900

0.0900

0.0800

0.0800

0.0800

0.0733

B 9.9

9.7

9.5

9.3

9.1

8.9

8.7 

8.5 

8.3 

8.1 

7.9 

7.7 

7.5 

7.3 

7.1 

6.9 

6.7 

6.5 

0.0567

0.0567

0.0567

0.0567

0.0567

0.0567

0.0533

0.0533

0.0533

0.0533

0.0467

0.0467

0.0467

0.0467

0.0467

0.0433

0.0433

0.0433

0.5361

0.4728

0.4029

0.3863

0.3663

0.3497

0.3297

0.3064

0.2931

0.2698

0.2532

0.2332

0.2166

0.1933

0.1733

0.1567

0.1500

0.1500

0.2967

0.2633

0.2400

0.2233

0.2033

0.1900

0.1800

0.1600

0.1500

0.1400

0.1300

0.1200

0.1133

0.1033

0.1000

0.0900

0.0833

0.0800

A numeric polynomial regression was carried out for each type

of emissions in Table IV-25 to produce a relationship giving VOC

emissions in grams per mile as a function of the Reid vapor

pressure in pounds per square inch. This resulted in separate

equations for Class B and Class C areas, as shown in Table IV-26.
159

Table IV-26

Nonexhaust Emissions Regressions as a Function of RVP - MOBILE5a

Area

Class Vapor source Curve Fit R2

B Refueling 0.004767 * RVP + 0.011859 0.908

B Running 0.017768 * RVP2 - 0.18746 * RVP +

0.61457

0.983

B Evaporative 0.014039 * RVP2

 - 0.17075 * RVP +

0.60037

0.996

C Refueling 0.004767 * RVP + 0.011859 0.908

C Running 0.016169 * RVP2

 - 0.17206 * RVP +

0.56724

0.985

C Evaporative 0.010853 * RVP2

 - 0.13346 * RVP +

0.48423

0.993

As stated above, evaporative emissions within the MOBILE

emissions model include both hot-soak and diurnal emissions. The

ratio of hot soak to diurnal emissions is specific to the area

class. For Class B areas, the average weighting of evaporative

emissions over all vehicle ages is 47.4 percent hot soak and 52.6

percent diurnal. For Class C areas, the average weighting of

evaporative emissions over all vehicle ages is 56.0 percent hot

soak and 44.0 percent diurnal. These values differ from the

MOBILE4.1 values because of 1) the changes to the diurnal

calculations in the MOBILE model that were made when version 5a

was being developed, and 2) the change in I/M assumption in Phase

II with respect to Phase I. Thus the equations for hot soak and

diurnal emissions can be derived from the equations for

evaporative losses shown in Table IV-26. The results are shown in

Table IV-27.
160

Table IV-27

Evaporative Emissions Breakdown for MOBILE5a

Area

Class Vapor source Curve Fit

B Hot Soak 0.006654 * RVP2

 - 0.08094 * RVP +

0.28458

B Diurnal 0.007385 * RVP2 - 0.08981 * RVP +

0.31580

C Hot Soak 0.006078 * RVP2

 - 0.07474 * RVP +

0.27117

C Diurnal 0.004775 * RVP2

 - 0.05872 * RVP +

0.21306

3. Derivation of Nonexhaust Toxics Equations

The MOBILE model was used to determine the relationship

between RVP and nonexhaust VOC emissions because MOBILE is based

on the most comprehensive collection of data on this subject. The

MOBILE model would therefore be the most natural source of

information on the relationship between fuel parameters and

nonexhaust emissions of toxic compounds. However, the MOBILE

model only provides emission estimates for VOC, NOx, and carbon

monoxide. Therefore, it was necessary for the EPA to develop the

nonexhaust toxics portion of the Complex Model in a manner

different from that used to develop the nonexhaust VOC model.

General Motors (GM) used their proprietary vapor equilibrium

model to predict the vapor composition above a pool of fuel

(conditions simulating a vehicle's fuel tank). The GM model

provided separate estimates for refueling, diurnal, and running

losses using a fuel matrix consisting of 12 fuels. These fuels

are shown in Table IV-28. Fuels 1, 2, and 3 are the base fuels

that were used to produce the subsequent blends. 
161

Table IV-28

GM Tank Vapor Model Fuels

Fuel # Oxygenate, vol% Type of blend RVP

1

2

3

4

5

6

7

8

9

10

11

12

none

none

none

MTBE, 11%

MTBE, 11%

MTBE, 11%

EtOH, 10%

EtOH, 10%

EtOH, 10%

EtOH, 10%

EtOH, 10%

EtOH, 10%

N/A

N/A

N/A

splash

splash

splash

splash

splash

splash

volatility-matched

volatility-matched

volatility-matched

7

8

8.7

7.46

8.36

9.03

8.20

9.13

9.82

7

8

8.7

The fuel benzene content was kept constant at 1 percent by

volume in all twelve test gasolines. Different benzene levels

were not tested since it is widely accepted that nonexhaust

benzene emissions will be proportional to fuel benzene content. 

Match-blending was carried out by adjusting the concentrations of

n-butane and toluene.

EPA believes that fuel tank vapor composition adequately

represents the composition of in-use emissions since nonexhaust

VOC emissions are dominated by emissions from vehicles which would

fail a pressure or purge test. On such "failing" vehicles, the

canister has little effect on the composition of emissions,

resulting in emissions with compositions essentially identical to

their tank composition. Emissions from passing vehicles might

have compositions which would differ from the composition of

failing vehicle fuel tank vapors. However, nonexhaust emissions

from passing vehicles comprise only a small fraction of the total

nonexhaust emission inventory. For this reason, EPA believes it

appropriate to base its model of the composition of nonexhaust

emissions on the composition of nonexhaust emissions from failing

vehicles.

The mass percent of benzene in the refueling, diurnal, and

running loss vapors as predicted by their tank vapor model was

provided directly by General Motors. These values are shown in

Table IV-29. The range of temperatures used to obtain these

results was 90 o

F for refueling emissions, 72-96 oF for diurnal

emissions, and 90-115 oF for running loss emissions. Since the

same temperature was used for both hot soak and running losses,

the results for these two categories of emissions were identical

and only the running loss results are shown below. 
162

Table IV-29

GM Tank Vapor Model Results

Fuel #

Mass percent benzene in vapors:

Refueling Diurnal Running Loss

1

2

3

4

5

6

7

8

9

10

11

12

0.828

0.742

0.690

0.722

0.660

0.620

0.720

0.654

0.612

0.829

0.736

0.683

0.815

0.731

0.679

0.711

0.650

0.611

0.714

0.648

0.607

0.823

0.730

0.676

0.884

0.800

0.748

0.769

0.709

0.670

0.757

0.695

0.656

0.859

0.772

0.721

The values in Table IV-29 indicate that the addition of MTBE

to gasoline lowers the mass percent of benzene in the vapor phase,

while the addition of ethanol has no effect on the mass percent of

benzene as compared to that for the base gasoline alone. To

quantify the change in mass percent benzene for MTBE blends,

linear curve-fitting was applied to the base fuel and the MTBE

blend. Table IV-30 shows the resulting equations giving the mass

percent benzene in the nonexhaust vapors for an unoxygenated

gasoline (fuels 1, 2, and 3 in Table I-20), and an 11% MTBE blend

(fuels 4, 5, and 6 in Table I-20).

Table IV-30

Linear Regressions of GM Model Results

Oxygenate Vapor source

Equation giving mass

percent benzene: R2

none Refueling 1.3972 - 0.081507 * RVP 0.998

none Diurnal 1.3758 - 0.080274 * RVP 0.999

none Running loss 1.4448 - 0.080274 * RVP 0.999

MTBE Refueling 1.2073 - 0.065186 * RVP 0.998

MTBE Diurnal 1.1868 - 0.063921 * RVP 0.998

MTBE Running loss 1.2400 - 0.063258 * RVP 0.999

In an effort to simplify the set of equations in Table IV-30,

the equations giving the mass percent benzene for MTBE blends were

combined with the equations giving the mass percent benzene for

unoxygenated gasoline. This was done by assuming that the slope
163

of the equation for a clear gasoline was approximately equal to

the slope of the equation for an MTBE blend for a given vapor

source. Thus the change in mass percent benzene due to the

addition of MTBE to a clear gasoline can be assumed constant over

the range of applicable RVPs. The equations from Table IV-30 were

evaluated at 8.0 RVP (the approximate center of the range of RVPs

for fuels 1-6 in Table IV-28), and the resulting mass percent

benzene values for MTBE blends were subtracted from the mass

percent benzene values for clear gasoline to obtain a "constant"

difference. These results are shown in Table IV-31.

Table IV-31

Differences in Regression Constants Between Blends

Vapor

Source

Mass % benzene in

vapors for clear

gasoline at 8.0 RVP

Mass % benzene in

vapors for 11 vol%

MTBE blend at 8.0 RVP

Change in mass %

benzene with the

addition of MTBE to

a clear gasoline

Refueling 0.7451 0.686 - 0.0591

Diurnal 0.7335 0.6756 - 0.0579

Running 0.8028 0.7338 - 0.0684

Hot soak 0.8024 0.7340 - 0.0684

An allowance can also be made for fuel MTBE contents of other

than 2.0% oxygen by weight (11% MTBE by volume) by multiplying the

last column of Table IV-31 by the ratio of MTBE content for the

target fuel and a fuel with 11% MTBE. The resulting equations,

giving the mass percent of benzene in the nonexhaust emissions for

any MTBE-oxygenated or unoxygenated blend, are shown in Table IV32. Note that in all equations below, "MTBE" is the weight

percent of oxygen in the form of MTBE in the fuel ("MTBE" would

necessarily be zero for any oxygenate other than MTBE).

Table IV-32

Revised GM Model Regressions 

Vapor source Equation giving mass percent benzene:

Refueling 1.3972 - [0.0591 * MTBE/2.0] - 0.081507 * RVP

Diurnal 1.3758 - [0.0579 * MTBE/2.0] - 0.080274 * RVP

Running loss 1.4448 - [0.0684 * MTBE/2.0] - 0.080274 * RVP

Hot soak 1.4448 - [0.0684 * MTBE/2.0] - 0.080274 * RVP

Two additional steps must be taken to convert the equations

in Table IV-32 to equations that provide the nonexhaust emissions

of benzene in grams/mile. First, changes in the benzene content

of a fuel are expected to result in a proportional change in the
164

benzene fraction of nonexhaust benzene emissions. To account for

fuel benzene contents other than the 1 vol% benzene that was used

to establish the results in Table IV-29, the equations giving the

mass percent benzene (Table IV-32) should be multiplied by the

volume percent benzene in the fuel. Second, to obtain benzene

emissions in grams/mile for each vapor source, the equations

giving the mass percent benzene must be 1) converted to mass

fraction benzene by dividing by 100, and 2) multiplied by the

total VOC emissions in grams/mile for that vapor source. The

final equations are shown in Table IV-33.

Table IV-33

Phase II Complex Model Nonexhaust Benzene Emissions

Vapor source Equation giving benzene emissions in grams/mile:

Refueling (BZV%/100) * RFVOC * (1.3972 - [0.0591 *

MTBE/2.0] - 0.081507 * RVP)

Diurnal (BZV%/100) * DVOC * (1.3758 - [0.0579 * MTBE/2.0]

- 0.080274 * RVP)

Running loss (BZV%/100) * RLVOC * (1.4448 - [0.0684 *

MTBE/2.0] - 0.080274 * RVP)

Hot soak (BZV%/100) * HSVOC * (1.4448 - [0.0684 *

MTBE/2.0] - 0.080274 * RVP)

BZV% = Volume percent of benzene in the fuel

RFVOC = Total grams per mile of VOC from refueling emissions

DVOC = Total grams per mile of VOC from diurnal emissions

RLVOC = Total grams per mile of VOC from running losses

HSVOC = Total grams per mile of VOC from hot soak emissions

The values for RFVOC, DVOC, RLVOC, and HSVOC for the Phase I and

II Complex Models were presented in Sections B.1 and B.2. 

4. Validation of Nonexhaust Toxic Emissions Model

Southwest Research Institute was contracted by EPA in July,

1992 to determine how fuel volatility, as measured by the vapor

pressure, is affected by the addition of various oxygenates in

gasoline blends. As part of this work, SwRI completed a gas

chromatograph speciation analysis of a subset of the fuels that

were tested and their associated vapors. From this speciation,

the mass percent benzene in the vapors and the volume percent

benzene in the fuel can be computed and compared to the nonexhaust

toxic emissions model described above. Thus, despite the fact

that the GM tank vapor model is proprietary, the results of the

study carried out by SwRI independently validate and substantiate

the nonexhaust benzene correlations described above.
165

Table IV-34 shows the properties for five fuels whose vapor

pressure was measured at both 100 and 130°F. The aromatics

content of fuels 3, 4, and 5 was increased through the addition of

toluene or 1,3,5-trimethylbenzene as indicated under the aromatics

content. Note that the presence of ethanol in fuels 2, 3, and 5

is assumed to have no effect on the mass percent benzene in the

vapors (see description of Table IV-29 above).

Table IV-34

SwRI Contract Fuels

Fuel

#

Aromatics

content RVP

Oxygenate,

vol%

BZV% at

100 Deg F

BZV% at

130 Deg F

1 20% 8.17 none 1.75 1.70

2 20% 9.10 EtOH, 10% 1.74 1.60

3 35% (toluene) 8.01 EtOH, 10% 1.36 1.37

4

35%

(trimethylben

zene)

6.93 none 1.40 1.40

5

35%

(trimethylben

zene)

8.05 EtOH, 10% 1.36 1.36

Using the volume percent benzene in the fuel and the RVP

levels for each of the five fuels shown in Table IV-28, the

nonexhaust toxic emissions model described above can be used to

predict the mass percent benzene in refueling, diurnal, running

loss, and hot soak emissions. These estimates can then be

compared to the mass percent benzene measured in the vapors by

SwRI. These measured values do not represent specific

measurements for either refueling, diurnal, hot soak, or running

losses. However, since the difference in emission levels for

these four sources results only from the differences in

temperatures under which the GM vapor model was run, the values

measured by SwRI can be appropriately compared to all four

sources. Tables IV-35 and IV-36 show these values for fuel

temperatures of 100o

F and 130°F, respectively.
166

Table IV-35

Comparison of Model to Measurements at 100°F

Fuel

Emissions Model benzene mass % prediction: SwRI

measured

benzene

mass % Refueling Diurnal Running Loss Hot Soak

1

2

3

4

5

1.28

1.14

1.02

1.17

1.01

1.26

1.12

1.00

1.15

0.99

1.38

1.24

1.09

1.24

1.08

1.38

1.24

1.09

1.24

1.08

1.28

1.23

1.00

1.34

1.03

Table IV-36

Comparison of Model to Measurements at 130°F

Fuel

Emissions Model benzene mass % prediction: SwRI

measured

benzene

mass % Refueling Diurnal Running Loss Hot Soak

1

2

3

4

5

1.24

1.05

1.02

1.17

1.01

1.23

1.04

1.01

1.15

0.99

1.34

1.15

1.10

1.25

1.08

1.34

1.15

1.10

1.25

1.08

1.39

1.11

1.16

1.33

0.92

Overall, the measured values for mass percent benzene given

by Southwest Research Institute differ from the values predicted

from the toxic emissions model by an average of +2.5 percent and a

maximum of 16.7 percent. The average value implies that the

nonexhaust model for benzene tends to underestimate the true

emissions. However, the repeatability of the RVP measurements in

the SwRI study was ±0.16 psi, equivalent to a percent change in

benzene emissions of ±3.8 percent (as calculated from the Phase

II, Class C nonexhaust equations). Thus the bias implied by the

average difference of +2.5 percent appears to be within the

measurement accuracy of the study. The data in Tables IV-35 and

IV-36 also imply that, for any given fuel, the model predictions

for mass percent benzene will differ from measured values by an

average of no more than -5.2 percent (95 percent confidence

limit). EPA has interpreted these results to suggest that the

correlations derived from the GM tank vapor model are sufficiently

accurate to form the basis for EPA's model for nonexhaust benzene

emissions.

5. Response to Comments

The Agency received a number of comments on the accuracy of

the nonexhaust benzene model in light of an analysis of more
167

recent data. This analysis suggested that the fraction of benzene

in nonexhaust vapors should be higher than that predicted by the

GM model results. Specifically, the analysis of hot soak and

diurnal heat build data showed that the weight fraction of benzene

in the vapor is a function of the total emissions. At extremely

low emission rates the fraction of benzene in the vapor is quite

high. As the emission rate increased, however, the benzene weight

fraction was found to asymptotically approach a lower limit. The

lower limit for hot soak emissions was significantly higher than

predicted by the GM model. The lower limit for the diurnal data

showed a close correlation to the GM model.

In response to these comments, the Agency has identified two

areas in which the requirements of the reformulated gasoline

program were compromised in the nonexhaust benzene study offered

to it. These two areas are described below:

 The Act requires that the impact of a fuel change on

emissions must be restricted to 1990 technology type vehicles

for the purposes of the reformulated gasoline and antidumping programs. The Agency has determined that carburetted

vehicles represent only a small proportion (<2%) of the 1990

fleet. However, a large fraction of the submitted heat build

data included carburetted vehicles. Thus the Agency has

determined that the conclusions reached as part of the

submitted study are not compatible with either the

reformulated gasoline or anti-dumping programs. 

The high proportion of carburetted vehicles in the submitted

test data is evident from the fact that carburetted vehicles

typically have higher hot soak emission rates than fuelinjected vehicles. The primary source of hot soak emissions

from carburetted vehicles is the carburetor bowl which is

extremely hot and may completely evaporate the fuel. The

primary source of hot soak emissions from fuel-injected

vehicles is vapors created in the fuel tank at a much lower

temperature. Therefore the high emission rate data is

probably dominated by carburetted vehicles which may consist

of whole fuel vapors. The submitted data and analysis for

hot soak emissions support this conclusion since the weight

fraction of benzene in the vapor approaches the fuel weight

fraction as the emission rate increases.

 The EPA has determined that the low emission rate data for

fuel-injected vehicles is not representative of in-use

emissions. A large fraction of these emission may be caused

by background emissions now characterized as resting loss

emissions. Resting losses were not included in the VOC

baseline and so should not be included in the toxic baseline. 

The source of these resting losses has not been determined,

but are thought to originate from permeation of fuel lines
168

and tanks. Permeation emissions may be characterized by a

high benzene weight fraction.

Based on its review of the submitted data and analyses on the

benzene fraction of nonexhaust vapors, the Agency has determined

that the General Motors vapor equilibrium model remains the most

appropriate and accurate source for developing the nonexhaust

benzene portion of the Complex Model.

A number of commenters took issue with the Agency's proposed

effect of individual oxygenates on nonexhaust benzene emissions. 

However, the conclusions reached by the different commenters were

contradictory. One commenter pointed to Auto/Oil data which

indicated that MTBE increases rather than decreases nonexhaust

emissions of benzene. Another commenter supported the suppression

of benzene emissions by MTBE, but indicated that recent

(unavailable) data supported a similar effect for the oxygenates

ETBE and TAME. Given the assailable nature and meager amount of

data on the effects of oxygenates on nonexhaust benzene emissions,

the Agency has determined that the Simple Model approach to the

development of a nonexhaust benzene model is the most appropriate

approach for the Complex Model.

C. Determining Emission Performances

1. Definition of Performance

Section 211(k) of the Clean Air Act requires that refiners

make gasoline that results in a decrease in emissions of 15

percent (in Phase I of the reformulated gasoline program) over the

emissions produced from baseline gasoline. Thus the CAA

identifies the measure of "cleanliness" of a given fuel by the

percentage difference between its emissions and emissions from the

baseline gasoline. For the purposes of this rulemaking, therefore,

the performance of a given fuel is defined as the percent change

in the vehicle emissions that would occur if baseline gasoline

were to be replaced with the given fuel in the fuel tank of a

typical 1990 vehicle. The definition of the baseline gasoline

depends on the season as described in Section III.A.

The Complex Model is designed to estimate the effects of

various fuel parameters on emissions of VOC, NOx, and toxic

compounds. If the Complex Model performance of a pollutant is

given by Y and the fleet average emissions for that same pollutant

in grams per mile terms is given by X, then performance of a

target fuel t as compared to a baseline fuel b is calculated from

(C.1) {[X(t) - X(b)]/X(b)} * 100 = Y(t)

The Complex Model can provide separate emissions performance

estimates for three main categories of pollutants: total VOC, NOx,
169

and total toxics. Each category includes emissions from one or

more sub-categories. Thus the X term in Equation (C.1) is the sum

of the contributions from various sources: 

Table IV-37

Contributing Sources to Each Pollutant Category

Pollutant

Category

Contributing Sources

VOC Exhaust VOC

Non-exhaust VOC

NOx Exhaust NOx

Toxics Exhaust benzene

Non-exhaust benzene

Exhaust 1,3-butadiene

Exhaust acetaldehyde

Exhaust formaldehyde

Exhaust POM

Note that the non-exhaust portion of the Complex Model contains

equations for only benzene and VOC, since other pollutants are

found only in exhaust emissions.

2. Exhaust Emissions Calculations

The Complex Model can provide both performance (i.e.,

percentage change) and mass (i.e., gram per mile) estimates of the

emissions from a target fuel as compared to a baseline fuel. The

calculations for each pollutant in the exhaust model are performed

initially in terms of percentage change from baseline levels,

while the non-exhaust model's calculations are performed initially

in terms of grams per mile. To obtain total performance estimates

as per Equation (C.1), both exhaust and non-exhaust estimates must

be expressed in terms of grams per mile. This section focuses

exclusively on the derivation of percentage change estimates for

exhaust emissions and their conversion to gram per mile estimates. 

Section C.3. provides details on how this method for determining

emissions performance, though different in form from that proposed

in the February 1993 NPRM [58 FR 17175], is mathematically

identical to the originally proposed method. Note that the

derivations shown in this and the following sections are based

upon the raw unconsolidated version of the final Complex Model,

but the conclusions are equally applicable to the model's

consolidated form.

The process used to develop the exhaust emission Complex

Model resulted in separate equations for each technology group and

emitter class for all six exhaust pollutants. Higher emitting
170

vehicles, however, were not categorized by technology group for

the reasons discussed in Section A.2. Hence there are nine

distinct equations for each pollutant, one for each of the eight

normal emitter technology groups and a ninth for higher emitters. 

Each of these nine equations relates fuel parameters to emissions

and has the following form:

(C.2) Ei = Ci * exp(fi(fuel parameters))

where E is emissions in grams per mile, C is a proportionality

constant of unknown magnitude, and the subscript i refers to a

specific vehicle group. As described in Section A, the function

fi is a polynomial which can contain linear, squared, and secondorder interactive terms.

The value of the proportionality constant Ci is unknown

because the statistical development process used to generate the

Complex Model did not include the use of intercept terms (see

Section IV.A.4 for details). Thus Equation (C.2) can only be used

to estimate the relative magnitude of emissions. For example,

Equation (C.2) can be evaluated for a specific target fuel and for

a baseline fuel, resulting in the following system of equations:

(C.3) Ei(b) = Ci * exp(fi(baseline fuel parameters))

= Ci * exp(fi(b))

(C.4) Ei(t) = Ci * exp(fi(target fuel parameters))

= Ci * exp(fi(t))

where b refers to the set of baseline fuel parameter values and t

refers to the set of target fuel parameter values. E(b)i and E(t)i

can be combined to obtain the percentage change in emissions that

would occur in a vehicle of vehicle group i if baseline gasoline

were replaced with the target gasoline. Mathematically this

percentage change is computed as follows:

(C.5) Percentage change in emissions from vehicles of

vehicle group i

= 100 * [Ei(t) - Ei(b)]/Ei(b)

= 100 * [Ciexp(fi(t)) - Ciexp(fi(b))]/[Ciexp(fi(b))]

= [exp(fi(t))/exp(fi(b)) - 1]*100

The final form of Equation (C.5) no longer contains the

proportionality constant Ci. As a result, the percentage change

in emissions can be calculated directly from Equation (C.5). 

To determine the fleet-average percentage change in

emissions, the equations for the individual vehicle groups must be

combined. Since each vehicle group contributes a different
171

fraction of the total fleet-wide emissions, the individual

percentage change estimates for each vehicle group must be

weighted to reflect the group's contribution to the overall

emissions inventory. The derivation of these weighting factors

was discussed in Section III.B.4 above. Thus the total

performance estimate for a given pollutant is given by

(C.6) Y =  {wi * [exp(fi(t))/exp(fi(b)) - 1] * 100}

where the wi are the weighting factors given in Table III-8 of

Section III.B.4.

Once the target fuel's fleet-average performance estimate has

been determined, it must be converted to a gram per mile basis

before being combined with the non-exhaust emission estimates. 

This conversion involves multiplying the fleet-average estimate of

the percentage change in emissions by the baseline emission

estimates X(b) derived in Section III.B. The conversion has the

following form, with X(t) representing the fleet-average emissions

from the target fuel in gram per mile terms and Y(t) representing

the fleet-average performance of the target fuel in terms of

percentage change from baseline:

(C.7) X(t) = X(b) + [X(b) * Y(t)/100]

Fleet-average exhaust and non-exhaust emissions, both expressed in

gram per mile terms, can be summed for each pollutant. The total

percentage change in emissions can then be calculated using

Equation (C.1).

The calculations described in this section do not take into

account any linear extrapolations. When linear extrapolation is

required, the calculation procedures described in this section

must be supplemented with other calculations. Both the conditions

under which extrapolation is required and the associated

calculation procedures are covered in Section IV.D.

3. Comparison of the Current Performance Calculation Method and

the Method Proposed in the February 1993 NPRM

The calculation of fleet-average performances for each

exhaust pollutant described above circumvents the need for vehicle

group-specific gram/mile estimates. This change was made to the

proposed method for calculating performances (as laid out in the

DRIA for the February 1993 NPRM, 58 FR 17175) to simplify both the

calculations themselves and the conceptual approach to the Complex

Model. It was also made in response to comments that expressed

confusion over the derivation of the proportionality constants

(the ki) used in the February 1993 proposed model. The method

described above is, in fact, mathematically equivalent to the

originally proposed method, except that the proportionality
172

constants and the calculation of vehicle group-specific gram per

mile emission estimates have been eliminated. This section

describes the mathematical conversion of the proposed method to

the final method described above.

As described previously, the exhaust equations for all

pollutants have the form of an exponential of a polynomial

function of the eight fuel parameters. Each such equation is

unique for every vehicle group and pollutant in the raw

(unconsolidated) form of the Complex Model. In the February 1993

Notice of Proposed Rulemaking [58 FR 17175], a procedure for

calculating gram/mile values for every vehicle group was outlined. 

This procedure provided total (fleet average) gram/mile values

from the gram/mile values for individual vehicle groups through

the following equation:

(C.8) X =  kiWiexp(fi)

X = Fleet average emissions of any pollutant in g/mi

ki = Adjustment factor for vehicle group i

fi = Polynomial function for vehicle group i, evaluated with

the fuel parameter values for the target fuel

Wi = Weighting factor for vehicle group i (note that these

weighting factors are not the same as the weighting

factors wi described in Section III.B.4 but instead are

the normalized sales weighting for vehicle group i,

unadjusted for differences in baseline emissions across

vehicle groups. Thus Wi retains the weighting factor

definition given in the February NPRM.)

In Equation (C.8), kiWiexp(fi) is the gram/mile contribution to the

total mobile source inventory from vehicle group i. Equation

(C.8) can be written more simply as

(C.9) X(t) =  Xi(t)

to show that the total, fleet average gram/mile estimate is made

up of the gram/mile estimates from the contributing vehicle

groups. Replacing X with X(t) shows that X is a function of the

target fuel.

As described in Section C.1 above, the total percent change

in the emissions of any exhaust pollutant is given by

(C.1) {[X(t) - X(b)]/X(b)} * 100 = Y(t)

Substituting Equation (C.9) into Equation (C.1) yields

(C.10) [( Xi(t) -  Xi(b))/ Xi(b)] * 100 = Yi(t)

where the subscript i denotes individual vehicle groups. This

equation can be applied to the raw, refined, or consolidated
173

Complex Models; using the raw form of the Complex Model, for

example, the summations in the above equation can be written as

follows:

 Xi(t) = Xi(t) + Xi(t) +  + X10(t)

 Xi(b) = X1(b) + X2(b) +  + X10(b)

where vehicle groups #1 through #9 are the normal emitter

technology groups, while vehicle group #10 is the higher emitting

vehicles. Equation (C.10) then becomes Equation (C.11):

[(X1(t) ++ X10(t))-(X1(b) ++ X10(b))]*100

(X1(b) +  + X10(b)) = Y(t)

The terms in the numerator can be grouped according to vehicle

group to yield Equation (C.12):

[(X1(t)1 - X1(b)1) + (X2(t) - X2(b)) +  ]*100

(X1(b)1 +  + X10(b)) = Y(t)

Equation (C.12) can be separated into ten separate equations, each

representing a given vehicle group's contribution to the total

percent change in pollutant Y:

(C.13a) [(X1(t)-X1(b))/ Xi(b)] * 100 = Contribution to total

percent change in

pollutant Y from vehicle

group #1

(C.13b) [(X2(t)-X2(b))/ Xi(b)] * 100 = Contribution to total

percent change in

pollutant Y from vehicle

group #2

and so on for (C.13c), (C.13d), etc.

At this point, combining Equations (C.8) and (C.9) gives

(C.14) Xi(t) = kiWiexp(fi(t))

for the target fuel, and

(C.15) Xi(b) = kiWiexp(fi(b))

for the baseline fuel. The adjustment factors ki are defined as

follows:

ki = Ci/exp(fi(b))

Ci = Average emissions of pollutant Y from vehicle group i;

see EPA memorandum from Christian Lindhjem to Richard A.

Rykowski, "Effects of Oxygenates on Emissions," Jan. 7,
174

1992 and the DRIA for the February 1993 NPRM for further

details.

Substituting for ki in Equations (C.14) and (C.15) results in

(C.16) Xi(t) = kiWiexp(fi(t))

= CiWiexp(fi(t))/exp(fi(b))

(C.17) Xi(b) = kiWiexp(fi(b))

= CiWiexp(fi(b))/exp(fi(b))

= CiWi

Equation (C.17) implies that the baseline values Xi(b) are

constant. Equation (C.16) implies that the target fuel values are

equal to the corresponding baseline values multiplied by the ratio

of exp(fi(t)) to exp(fi(b)). Using vehicle group #1 as an example,

combine Equations (C.13a), (C.16), and (C.17) to obtain

(C.18) Contribution to total percent change in pollutant Y

from vehicle group #1

= 100*(X1(t) - X1(b))/ Xi(b)

= 100*[C1W1exp(f1(t))/exp(f1(b)) - C1W1]/ CiWi

= 100*(C1W1)*[exp(f1(t))/exp(f1(b)) - 1]/ CiWi

= 100*exp(f1(t))/exp(f1(b)) - 1]*(C1W1)/ CiWi

Equation (C.18) provides vehicle group #1's contribution to the

total percent change in pollutant Y. The term

100*[exp(f1(t))/exp(f1(b))-1] provides the percent change in

pollutant Y for vehicle group #1, equivalent to Equation (C.5). 

Thus if the form of Equation (C.18) were duplicated for the

remaining vehicle groups and all such equations were summed, the

result would be Equation (C.7). Since Equations (C.18) and (C.7)

are mathematically equivalent, the method proposed in the February

NPRM for calculating performances is mathematically equivalent to

the method that has been employed for the final Complex Model.

Since the Ci and Wi are constants, the term C1W1 is also a

constant, and (C1W1)/ CiWi is the normalized form of C1W1. Thus the

final weighting factor wi for vehicle group #1 (not to be confused

with the interim weighting factor W1) is defined as

(C1W1)/ CiWi = w1

The final weighting factors wi were derived in Section III.B.4

above.
175

Although the derivation of the vehicle group-specific percent

change equations outlined above uses the raw form of the final

Complex Model, the results are applicable to the refined,

consolidated, and uncentered forms of the Complex Model as well. 

As discussed above, the technology group weightings for normal

emitters (Table IV-2) were applied to the normal emitter vehicle

groups in the random balance approach to vehicle group

consolidation. Doing so resulted in a single equation for normal

emitters, and the emitter class emission weightings from Table 4

were then applied directly to the two remaining equations for each

pollutant. Thus the consolidated and uncentered models contain

two vehicle groups for each pollutant instead of the original

nine, one for normal emitters and one for higher emitters. The

derivations described in this subsection apply regardless of the

number of vehicle groups in a given model.

4. Response to Comments

A number of commenters noted the disparity between the

quantity of data on higher emitting vehicles in the Complex Model

database and the large weighting that higher emitters are given in

the Complex Model, particularly for VOC and toxics. Two options

were suggested for alternative treatments of higher emitters:

1) Assume that the emissions impact of fuel modifications

on higher emitters is generally similar to the emissions

impact of fuel modifications on normal emitters. This

assumption would imply that the statistical development

of the Complex Model should proceed with a "totally

unified approach," in which higher emitters would be

modeled in the same manner as normal emitter technology

groups.

2) Decrease the weighting assigned to higher emitter

effects in the final Complex Model.

The Agency's analysis of available data indicated that higher

emitters have fundamentally different responses to fuel

modifications than do normal emitters. The EPA therefore

continued to treat higher emitters as a distinct population of

vehicles requiring different analysis techniques than those used

to account for normal emitter technology group distinctions. For

this reason, EPA decided not to use the totally unified modeling

approach.

The Agency acknowledges the disparity between the proportion

of higher emitter data and the weighting given the higher emitter

equations in the Complex Model. However, the Agency does not

believe that the limited available data on higher emitters

justifies under-weighting emissions from such vehicles for the

following reasons:
176

 The Agency has no basis for arbitrarily lowering the

weighting for higher emitters to a level below the

contribution of such vehicles to in-use emissions. 

Doing so would result in models which are inconsistent

with EPA's knowledge of in-use emissions and with EPA's

MOBILE models.

 All interested parties were informed of the scarcity of

data on higher emitters and the large weight that higher

emitters were to receive in the final Complex Model

during the early stages of model development, beginning

with EPA's first public workshop on the Complex Model

held January 21-22, 1992. Despite the Agency's

solicitation for additional higher emitter data, the

only additional higher emitter data included in the

Complex Model database were obtained through EPAsponsored test programs. The Auto/Oil program did test

higher emitters but failed to stabilize their emissions

prior to testing. As discussed in Section A.1, EPA

considers inclusion of test results from unstable

vehicles to be inappropriate. 

 The fleet-average ratio of normal emitter emissions to

higher emitter emissions is based on an analysis of data

used to develop the MOBILE emissions model. Since this

data is regarded as the most complete set of available

data on the in-use mobile source emissions inventory,

EPA considers any other basis for these weightings to be

less reliable.

The Agency considers the weighting factors described and derived

above to provide the most appropriate allocation of the emissions

inventory to each emitter class and technology group.

D. Range and Extrapolation of the Model

Section C presented the procedure for calculating emission

performances with the Complex Model equations. The current

section describes some of the limitations of those regression

equations by addressing two specific issues:

 The fuel parameter ranges within which the Complex Model

equations can be applied.

 The methodology for extrapolating the Complex Model

equations to cover fuels whose properties are not

represented in the Complex Model database.

These limitations on the use of the regression equations arise

from the limitations of the Complex Model database. In regions of
 43 The "fuels space" refers to the multi-dimensional universe in which

each axis is represented by a single fuel parameter. A given point in the fuels

space specifies a set of fuel properties which represents a single, unique fuel.

177

the fuels space43 where emissions data is limited or absent, the

regression equations may not reliably reflect the response of inuse vehicles to fuel modifications. Limits on fuel parameter

ranges and extrapolation techniques are two methods that EPA has

chosen to compensate for the limitations of the Complex Model

database.

This section is divided into five parts. Section D.1 derives

and presents the limits of the data core, which is the subset of

the fuels space that contains the bulk of the data in the Complex

Model database. The data core delineates the range of fuel

parameters within which EPA considers the regression equations to

be most trustworthy since sufficient data from the Complex Model

database is available. Section D.2 presents EPA's approach to

designating the valid range, or the range of fuel parameters

within which fuels can be evaluated with the Complex Model. Since

the data core is smaller than the valid range, EPA has chosen to

employ a type of extrapolation to estimate emission performances

between these two ranges. Sections D.3, D.4, and D.5 present the

extrapolation methodology in three steps:

1) Section D.3 lays out the Agency's theoretical and

mathematical approach to linear extrapolation.

2) Section D.4 identifies the location of inappropriate

extrema (minimums and maximums) which can be

accommodated in the Complex Model through the

application of linear extrapolation.

3) Section D.5 applies the approaches outlined in Sections

D.3 and D.4 to the Complex Model regression equations

and presents the final extrapolation algorithm and

equations.

Both the fuel parameter ranges and extrapolation

methodologies are independent of the particular season, program

phase, and area class scenarios under which the Complex Model can

operate. The specific extrapolation approach to the Complex Model

applies to both the reformulated gasoline program and the antidumping program, but the limits on the fuel parameter ranges over

which the Complex Model is valid differ for the reformulated

gasoline and anti-dumping programs.

1. Derivation of Data Core
 44 Extrapolation generally begins at the limits of the data core. 

However, extrema also play a role in determining the locations at which

extrapolation should begin, as described in more detail in Section D.4.

 45 In the February 1993 NPRM, the data core was referred to as the valid

range of the Complex Model, and indeed was coincident with the valid range as

defined and specified in Section D.2 below.

178

As introduced above, the data core is the subset of the

multi-dimensional fuels space that contains the bulk of the data

in the Complex Model database. It can be pictured as a multidimensional box which is defined by upper and lower bounds on each

fuel parameter. The data core serves three main purposes:

1) It provides information on the limitations of the

Complex Model, which was derived from a database which

did not cover all possible fuel formulations.

2) It delineates the range for each fuel parameter within

which the regression equations are most reliable.

3) It provides the locations in the multi-dimensional fuels

space at which extrapolation should begin.44

Specification of the data core is the first step in translating

the limitations of the Complex Model database into the limitations

of the Complex Model.

For the February 1993 Notice of Proposed Rulemaking [58 FR

17175], the data core was determined from a visual examination of

the data in the Complex Model database.45 This visual examination

used frequency distributions of the values of individual fuel

parameters. The frequency distributions were simply graphical

displays in which the horizontal axis gave the level of a given

fuel parameter and the vertical axis gave the fractional frequency

of observations of those fuel parameter levels in the Complex

Model database. The Agency used the graphical displays to specify

the low and high values of each fuel parameter which enclosed the

bulk of the data (see the February 1993 Draft Regulatory Impact

Analysis for further details).

The Agency has since conducted a more rigorous analysis of

the data core based on four main factors:

 Distribution of the data.

 Covariation between fuel parameters.

 Behavior of the Complex Model.
179

 The fuel parameter ranges which encompass

various percentages of the data.

The distribution of the data is an extremely important factor

because regression equations tend to be most reliable in the

regions of the fuels space that contain the most data. Ideally,

the data in the database would be evenly distributed (i.e.,

homogeneous) over a given range for each fuel parameter. To the

extent that the database is not homogeneous, the regression

equations are that much less reliable.

Homogeneity is particularly important when examining the ends

of the data ranges. Since the ends of the data ranges typically

have fewer observations than more central portions of the data,

the reliability of the regression equations decreases as one

approaches those ends. This tendency implies that the limits of

the data core should not be coincident with the maximum and

minimum values observed in the database since it is near such

extreme values where the reliability of the regression equations

decreases rapidly.

Covariation between fuel parameters is an issue in

determining the limits of the data core because it can obscure

holes in the Complex Model database. Some portions of the multidimensional fuels space may appear to contain sufficient data when

in fact they do not. For example, the bulk of the data for E200

may lie between 35 and 70 percent for a given data set, while most

E300 values for the data set range from 70 to 95 percent. 

However, since fuels with high E200 values typically contain high

E300 values and vice-versa, not all combinations of E200 and E300

levels would be well represented in the data set. For example,

fuels with high E200 values (e.g., 65 percent) and low E300 values

(e.g., 75 percent) would not be well represented in the data set,

although the E200 and E300 values individually fall within their

respective ranges in the data set. Significant covariation

problems can be identified with graphical displays by plotting the

levels of one fuel parameter as a function of a second fuel

parameter. Covariation can also be identified analytically by

determining how well one can predict levels of a fuel paramter if

one knows the level of a second fuel parameter. For example, an

indication of the degree of covariation between two parameters can

be determined by calculating the R-squared value for a regression

with one fuel parameter as the dependent variable and a second

fuel parameter as the independent fuel variable. High covariation

would result in high R-square values.

If a significant correlation exists between two fuel

parameters, then the data core limits for one fuel parameter

depend on the level of a second fuel parameter. Covariation has

the effect of changing the shape of the data core from a multidimensional box to some other, more complex shape. EPA's

examination of covariation in the Complex Model database revealed
180

substantial covariation between the following fuel parameter

pairs:

Benzene and Sulfur Aromatics and E300

Benzene and Oxygen Olefins and Sulfur

Aromatics and E200 Olefins and Benzene

E200 and Oxygen E300 and Sulfur

E200 and E300

However, in no case did the covariation result in the complete

absence of emissions data from any portion of the multidimensional fuels space. Thus it was not necessary to specify the

data core with the upper and lower bounds on each fuel parameter

being a function of the values of another fuel parameter. 

Instead, the upper and lower bounds for each fuel parameter could

be determined independently.

The behavior of the Complex Model is also an important factor

in determining the extend of the data core. When discussing the

model's behavior, the exponential form of the model alters the

traditional implications of first- and second-order terms. Since

the statistical regressions employed to develop the exhaust

emission Complex Model used the natural logarithm of emissions as

the dependent variable (see Section A.2), emissions are

proportional to the exponential of the resulting polynomials, not

to the polynomials themselves. As a result, emissions are not

first- or second-order functions of the fuel parameters included

in the model in a strict mathematical sense. However, the

deviation between the behavior of an exponential of a polynomial

and the behavior of the polynomial itself is significant only for

large numerical values of the independent variables (the fuel

parameters, in the case of the complex model). In the Complex

Model, only sulfur measurements ever exhibit such high values, and

then only under the anti-dumping program (as discussed in Section

D.2). Therefore, the behavior of the polynomial functions which

are exponentiated in the Complex Model's exhaust emission

equations provides a good approximation to the behavior of the

actual exponential equations that comprise the exhaust emission

Complex Model. For this reason, the Complex Model exhaust

equations themselves will be referred to as being first- or

second-order in the discussions that follow based on the form of

the exponentiated polynomial with no loss of descriptive accuracy.

With the foregoing discussion in mind, the behavior of the

Complex Model can provide additional guidance in defining the

limits of the data core. As stated in the introduction to this

section, one purpose of the data core is to provide the locations

in the multi-dimensional fuels space at which extrapolation should

begin, since the regression equations become less reliable than

desired outside the data core. Models which exhibit questionable

or counter-intuitive behavior are less reliable than models which

do not exhibit such behavior. As a result, the range of fuel
181

parameters within which the regression equations are considered

reliable should be made more restrictive for those parameters for

which the complex model exhibits questionable or counter-intuitive

behavior. In other words, the size of the data core should be

reduced in such cases so as to restrict poorly-behaved equations

to smaller regions of the fuels space than well-behaved equations.

As described in Section D.3, all extrapolations beyond the

limits of the data core were linear extrapolations. Since a

linear extrapolation of a linear relationship results in the

original linear relationship, linear extrapolation of the Complex

Model regression equations only alters the second-order

relationships included in the Complex Model. Thus the behavior of

pollutant models should influence the extent of the data core only

for fuel parameters which are present in second-order terms. The

data core should be far less influenced by the Complex Model's

behavior for fuel parameters present only in linear terms. The

second-order terms which are present in the Complex Model are

shown in Table IV-38.

Table IV-38

 Second-order terms in the Complex Model

Pollutant Second-order terms in the regression equation

VOC E2002

, E3002, ARO*E300

NOx OLE2, SUL2, ARO2

Benzene none

Butadiene none

Acetaldehyde none

Formaldehyde none

As described in Section D.4, second-order terms may create

extrema which may not appropriately represent the effects of fuel

modifications for all possible fuel parameter values. In some

cases the existence and location of extrema are artifacts of the

distribution of the data in the Complex Model database. In such

cases, limiting the size of the data core helps exclude

inappropriate extrema from the model.

Finally, the range which encloses a fixed percentage of the

data for each fuel parameter also helps determine the extent of

the data core. Not only does such an analysis provide a less

qualitative approach to specifying the limits which enclose the

bulk of the data, it also provides information on the homogeneity

of data at the ends of the data ranges. Table IV-39 shows the

results of such an analysis. Table IV-39 includes five range
182

restriction limits. The 98% limits, for example, are determined

by allowing 1% of the data to fall below the "low" end of the

range and 1% of the data to fall above the "high" end of the

range. Similarly, the 95% limits are determined by allowing 2.5%

of the data to fall below the low end and 2.5% to fall above the

high end. Each limit is pollutant-specific for each parameter

since not all pollutants were measured for each fuel-vehicle

combination. For example, 96% percent of the acetaldehyde

observations were based on fuels with aromatics levels between

11.5 and 45.9 vol%, but 96% of the VOC observations were based on

fuels with aromatics levels between 17.9 and 45.9 vol%. 
183

Table IV-39 

Limits of the Bulk of the Data

 Parameter Pollutant

98% limits 97% limits 96% limits 95% limits 

Low High Low High Low High Low Hig

Aromatics Acetaldehyde

BenzeneButadieneFormaldehydeNOxVOC

11.3 11.3 11.3 11.3 

9.3 

11.5 

46.7 46.7 46.7 46.7 47.8 47.3 

11.3 11.3 11.3 11.3 

9.8 

17.9 

46.6 46.4 46.6 46.6 46.7 46.7 

11.5 11.5 11.5 11.3 11.3 17.9 

45.9 45.9 45.9 45.9 46.7 45.9 

11.5 11.5 11.5 11.5 11.5 18.1 

45.7 45.7 45.7 45.7 46.4 45.9 

Benzene Acetaldehyde

BenzeneButadieneFormaldehydeNOxVOC

0.39 0.39 0.39 0.39 0.39 0.38 

2.3 2.3 1.8 2.3 2.4 1.8 

0.39 

0.4 0.4 

0.39 0.39 0.39 

1.84 1.84 

1.8 

1.84 

2.3 1.8 

0.4 0.4 0.4 0.4 

0.39 0.39 

1.8 1.8 1.8 1.8 1.9 1.8 

0.4 0.4 0.4 0.4 0.4 

0.39 

1.8 1.8 1.8 1.8 

1.84 

1.7 

E200 Acetaldehyde

BenzeneButadieneFormaldehydeNOxVOC

30.96 26.68 26.68 30.96 27.42 30.02 

67.41 67.41 67.41 67.41 

67.8 

67.41 

31.72 30.96 30.96 31.72 30.02 30.96 

66.87 66.87 66.87 66.87 67.41 67.41 

31.72 30.96 30.96 31.72 30.96 31.72 

66.87 66.87 66.87 66.87 67.41 66.87 

31.88 31.34 30.96 31.88 31.34 31.88 

65.765.765.765.766.866.8

E300 Acetaldehyde

BenzeneButadieneFormaldehydeNOxVOC

71.65 71.19 71.19 71.65 71.65 71.65 

97.28 97.28 97.28 97.28 97.28 97.28 

71.99 71.65 71.65 71.99 71.99 71.99 

97.28 97.28 97.28 97.28 97.28 95.56 

72.02 71.99 71.99 72.02 72.02 71.99 

95.56 95.56 95.56 95.56 95.56 95.31 

72.68 72.02 72.02 72.68 72.02 72.02 

95.395.395.395.395.3

94.5 

Olefins Acetaldehyde

BenzeneButadieneFormaldehydeNOxVOC

0.6 

1 

0.6 0.6 

0 1 

21.8 21.8 21.8 21.8 21.9 21.8 

1 

1.1 

1 1 

0.2 

1 

20.3 20.3 20.3 20.3 21.8 21.8 

1.1 1.1 1.1 1.1 0.6 1.1 

19.3 19.3 19.3 19.3 20.3 20.3 

1.1 1.1 1.1 1.1 0.9 1.1 

18.5 18.3 18.5 18.5 20.3 20.3 
184

Oxygen Acetaldehyde

BenzeneButadieneFormaldehydeNOxVOC

0 0 0 0 0 0 

3.81 3.81 3.81 3.81 3.42 3.42 

0 0 0 0 0 0 

3.81 3.81 3.81 3.81 3.37 3.37 

0 0 0 0 0 0 

3.48 3.42 3.42 3.48 3.37 3.37 

0 0 0 0 0 0 

3.42 3.42 3.42 3.42 3.37 3.37 

RVP Acetaldehyde

BenzeneButadieneFormaldehydeNOxVOC

6.2 6.2 6.2 6.2 6.4 6.4 

9.7 

9.59 9.59 

9.7 

12 12 

6.2 6.2 6.2 6.2 6.4 6.4 

9.59 9.59 9.59 9.59 

12 12 

6.2 6.2 6.2 6.2 6.6 6.5 

9.55 9.55 9.55 9.55 11.5 11.7 

6.4 6.4 6.4 6.4 6.6 6.6 

9.4 

9.32 9.32 

9.4 

10.2 10.2 

Sulfur Acetaldehyde

BenzeneButadieneFormaldehydeNOxVOC

31 31 31 31 

7 

10 

371 371 371 371 466 466 

31 31 31 31 

7 

12 

371 371 371 371 466 466 

31 31 31 31 10 21 

371 371 371 371 466 466 

31 31 31 31 11 31 

371 371 371 371 452 466 
185

Table IV-39 is particularly useful when evaluating the

limits of the data core for fuel parameters which are included in

second-order terms as shown in Table IV-38. The second-order

effects decrease the reliability of the complex model's emission

estimates for fuels with levels of such fuel parameters that are

outside the bulk of the data. Thus the distribution of E200 data

in Table IV-39 for VOC observations should play a stronger role

in setting the limits of the data core than the distribution of

E200 data for NOx or benzene, since nonlinear E200 terms are

present only in the VOC model. The same considerations apply to

the other fuel parameters: the distribution of VOC observations

should play a strong role in determining data core limits for

E300 and aromatics, while the distribution of NOx data should

play a strong role in determining the data core limits for

olefins, sulfur, and aromatics.

RVP, oxygen, and fuel benzene content never appear in

second-order terms in the exhaust Complex Model. This fact

suggests that the effects of these parameters can be extended via

the regression curve approach to extrapolation (see Section D.3)

with relatively high confidence to parameter levels for which

emissions data is scarce or absent. Thus the location of the

data core limits for these three parameters has no bearing on

their extrapolation. To convert the ranges from Table IV-39 to a

more manageable form for these three fuel parameters, the range

limits for individual pollutants can be combined into a single

set of ranges for all pollutants. The number of observations for

each pollutant in the Complex Model database can be used to

develop a weighted average across all pollutants for RVP, oxygen,

and fuel benzene limits. The weightings are shown in Table IV40; useable observations are those observations were not deleted

as outliers or influential points during the model-building

process.

Table IV-40 

Number of Useable Observations by Pollutant

Pollutant Number of observations

in the database

Percent of total

observations

Acetaldehyde

Benzene

1,3-Butadiene

Formaldehyde

NOx

VOC

1785

1872

1821

1788

5246

4342

10.59

11.11

10.80

10.61

31.13

25.76

Total 16,854 100.00

This analysis allows conversion of the values in Table IV-39

into a form that is more conducive to determining an appropriate

data core, as shown in Table IV-41.
186

Table IV-41 

Restricted Limits of the Bulk of the Data

 Parameter Pollutant

98% limits 97% limits 96% limits 95% limits 

Low High Low High Low High Low Hi

Aromatics NOx

VOC

9.3 

11.5 

47.8 47.3 

9.8 

17.9 

46.7 46.7 

11.3 17.9 

46.7 45.9 

11.5 18.1 

4645

Benzene Overall 0.39 2.15 0.39 1.97 0.39 1.83 0.4 1.E200 VOC 30.02 67.41 30.96 67.41 31.72 66.87 31.88 66.

E300 VOC 71.65 97.28 71.99 95.56 71.99 95.31 72.02 94

Olefins NOx 0 21.9 0.2 21.8 0.6 20.3 0.9 20Oxygen Overall 0 3.59 0 3.56 0 3.40 0 3.RVP Overall 6.31 10.98 6.31 10.96 6.40 10.71 6.51 9.Sulfur NOx 7 466 7 466 10 466 11 45
187

Table IV-41 contains both pollutant-specific limits and

common limits. The pollutant-specific limits are taken directly

out of Table IV-39, and represent the data limits for pollutants

whose behavior includes second-order effects. The common limits

are determined by weighting all the pollutant-specific data

limits according to the values in Table IV-40. The common limits

therefore represent the data limits across all pollutants. The

final limits of the data core are discussed separately for each

parameter.

Aromatics: Since second-order aromatics terms occur in both

the NOx and VOC models, EPA chose to be cautious

in setting the aromatics limits of the data core. 

Table IV-39 shows that the VOC limits are always

more restrictive than the NOx limits. When moving

from the 98% VOC limit to the 97% VOC limit, the

low end of the aromatics range jumps from 11.5 to

17.9 vol%, indicating that very few observations

are present between those aromatics levels. The

low end remains stable at approximately 18 vol% as

the data limits become more restrictive. Thus the

low end of the data core has been set at 18 vol%

aromatics. Between the 96% and 94% limits, the

high end remains stable at approximately 46 vol%

aromatics. Between the 96% and 97% limits,

however, the high end jumps from 45.9 to 46.7

vol%, indicating that the data set begins to

become sparse beyond 46 vol%. This conclusion is

supported by the 98% high end limit. Thus the

high end of the data core has been set at 46 vol%.

Benzene: Since benzene is present in the benzene model only

in a linear term, EPA was less cautious in setting

benzene limits. The low end appears to be fixed

at approximately 0.4 vol% across all examined

limits, so EPA set the low end of the data core at

0.4 vol%. Between the 94% and 96% limits, the

high end is stable at approximately 1.8 vol%. The

high end jumps to 1.97 vol% at the 97% limit and

then to 2.15 vol% at the 98% limit, indicating

that data become scarce above the 96% limit but

are relatively common below it. Therefore the

high end of the data core for benzene has been set

at 1.8 vol%.

E200: E200 is present in the VOC model in a second-order

term, so EPA based its E200 data core limits on a

cautious interpretation of the distribution of VOC

data. The low end appears to change little

between the 95% and 96% VOC limits, indicating

that a clump of data exists for E200 values near

31.8 vol%. However, the low end increases to
188

32.65 vol% at the 94% limit and decreases to 30.96

vol% at the 97% limits; these jumps indicate that

data is not homogeneously distributed at the low

end of the E200 range. Thus the low end of the

data core has been set conservatively at 33 vol%. 

A similar inhomogeneity exists on the high end: 

more high end data exists between the 95% and 96%

limits than exists between the 94% and 95% limits. 

Thus the high end of the data core has been set

conservatively at 66 vol%. 

E300: E300 is present in two separate second-order terms

for VOC, so EPA based its E300 data core limits on

a cautious interpretation of the distribution of

VOC data. The low end is relatively constant at

72 vol%, which indicates that a significant amount

of data exists at the extreme low end of the

range. Thus the low end of the data core was set

at 72 vol%. However, the high-end E300 limits

vary significantly across the five data limits

examined. EPA therefore set the high end of the

data core conservatively at a level of 94 vol%.

Olefins: A second-order olefins term is present in the NOx

model, so EPA based its olefins data core limits

on a cautious interpretation of the distribution

of NOx data. The low end decreases rapidly

between the 95% and 98% limits, but is relatively

stable between the 94% and 95% limits. Since the

low end data begins thinning out dramatically

below 0.9 vol%, the low end of the data core was

set at 1.0 vol%. On the high end, a data gap

exists between the 96% and 97% limits, but

significant data appear available between the 95%

and 96% limits. Thus the high end was set

conservatively at 19 vol%.

Oxygen: The low end of the data distribution is fixed at

0.0 wt% for all five data limits. The high end is

constant at approximately 3.4 wt% between the 94%

and 96% limits. Above the 96% limit, the high end

data becomes thinner. Therefore, the low end of

the data core was set at 0.0 wt% and the high end

was set at 3.4 vol%.

RVP: RVP is not involved in any second-order terms in

the Complex Model, so EPA was less cautious in

setting RVP limits for the data core. Although a

clump of data exists between the 97% and 98%

limits for the low end, the data is much thinner

between the 94% and 97% limits. The low end of

the data core was therefore set at 7 psi. The
189

high end of the data distribution averages

approximately 10 psi across all pollutants and all

data limit levels, so the high end of the data

core was set at 10 psi.

Sulfur: Sulfur is present in second-order terms in the NOx

model, so EPA based the sulfur limits of the data

core on the distribution of NOx data. At the low

end of the range, the measurement tolerance for

sulfur is much larger than the difference between

the values for the various range limits. Thus the

low end of the data core was set at the average

level of 10 ppm sulfur. EPA retained the NPRM

high end limit of 450 ppm since there appears to

be a significant amount of data near 466 ppm

despite the thin amount of data between 443 and

466 ppm. In addition, the NOx model does not

exhibit unexpected or inappropriate behavior at

sulfur levels of 450 ppm.

Based on the foregoing discussion, the final data range

limits enclosing the bulk of the data are summarized in Table IV42.

Table IV-42

Data Core for the Complex Model

Pollutant Units

Limits of Data Core

Low end High end

Aromatics vol% 18 46

Benzene vol% 0.4 1.8

E200 vol% 33 66

E300 vol% 72 94

Olefins vol% 1 19

Oxygen wt% 0.0 3.4

RVP psi 7 10

Sulfur ppm 10 450
190

2. Valid Ranges

The valid range for the Complex Model is here defined as

that range of fuel parameters over which the Complex Model (and

any applicable extrapolations as described in Section D.5) can be

used to evaluate the emission performances of fuels. The Complex

Model can be used outside the valid range only if the model is

augmented through testing. The valid range is not meant to place

absolute fuel parameter restrictions on either the reformulated

gasoline (RFG) or anti-dumping programs, but rather on the use of

the Complex Model within those programs.

Specification of the valid range is a means of overcoming

some of the limitations of the Complex Model database. As

described in the previous section, the database from which the

Complex Model is derived does not cover all possible fuel blends

that might be encountered in the RFG and anti-dumping programs. 

The limits of the data core (as defined in Section D.1) reflect

the limitations of the database and therefore the limitations of

the empirically-based Complex Model regression equations. In an

effort to mitigate the disparity between the limitations of the

database and the needs of the RFG and anti-dumping programs, the

Agency has extrapolated the Complex Model regression equations to

cover as many fuel blends as possible. Even with extrapolation,

however, the Complex Model must be limited to some subset of the

fuels space to maintain the accuracy of its emissions performance

estimates. These limitations on the valid range of the Complex

Model are discussed in this section.

There are a number of factors which must be considered in

determining the valid range:

 The purpose of the valid range

Specification of the valid range is intended to make the

Complex Model as flexible and useful as possible without

sacrificing accuracy and reliability. Insofar as the

regression equations and their associated extrapolations are

trustworthy, they should be applied to as wide a range of

fuel parameters as possible.

 The needs of the program

The intent in developing the Complex Model was and is to

provide refiners flexibility in meeting the requirements of

the Clean Air Act. Any restrictions in the valid range

limit that flexibility.

The valid range for the Complex Model is specific to the

fuels program under which the Complex Model will be used,
191

resulting in two separate valid range sets: one for the RFG

program, and a second for the anti-dumping program. There

are two reasons for delineating two separate valid range

sets: 

1) EPA believes it appropriate to permit the Complex

Model to evaluate typical 1990 (non-reformulated)

gasolines in order to determine compliance with

anti-dumping regulations. However, EPA expects

reformulated gasolines to fall into more

restricted fuel parameter ranges than conventional

gasolines. Thus to fulfill the needs of each

program, the valid range for the anti-dumping

program should be less restrictive than the valid

range for the RFG program.

2) The accuracy of the Complex Model is less

important for the anti-dumping program than it is

for the reformulated gasoline program. EPA

believes that greater confidence is needed in

estimating emission reductions from the use of

reformulated gasolines because of the program's

primary mission of achieving emission reductions

in the worst ozone non-attainment areas. The

anti-dumping program for conventional gasolines

only requires that future gasolines produce

emissions which are no worse than those of

gasolines produced in 1990. Thus the

environmental impact of inaccuracies in the

model's emission estimates is more severe for the

RFG program than for the anti-dumping program. 

 The behavior of the Complex Model

When the Complex Model predicts emission effects for a given

fuel parameter which seem questionable, linearly

extrapolating beyond the data core is less reliable,

indicating that the valid range for that fuel parameter

should approach coincidence with the data core.

Even when the model's predictions seem reasonable, the

mathematical form by which the model incorporates emission

effects may only be appropriate within the data core. This

fact is of greatest concern when examining the location of

extrema (maximums and minimums). Extrema produce a

"turnover" effect that is an artifact of using second-order

polynomials during the regressions, when the underlying

phenomenon may obey a decaying exponential function or some

other function which does not produce "turnover" effects. 

Thus the model's emission performance estimates for fuels

with parameter levels that are outside the data core and are
192

far from an extrema point may be much higher or lower than

the true effect. Depending on the location of extrema,

placing the valid range limits too far from the data core

could result in emission performance estimates that differ

excessively excessively from the true values.

In some circumstances, it may be inappropriate to linearly

extrapolate first-order relationships beyond the limits of

the data core. A purely linear relationship may overstate

or understate the impact of fuel parameter modifications on

emissions, particularly for fuel parameter levels which are

well beyond the limits of the data core, since the linear

relationship is only an approximation of the underlying

phenonomenon being modeled. Thus some linear relationships

may be most appropriately restricted to the limits of the

dat core.

 The limits of the available data

The further one travels from the data core, the less

reliable are the emission performance estimates provided by

the model, regardless of extrapolation. Thus the size of

the data core will affect the size of the valid range.

 Specific valid range proposals from sources outside EPA

In response to the July 15, 1993 package submittal to the

docket, a number of commenters provided EPA with specific

proposals for the valid range for both the RFG and antidumping programs. These valid range proposals provided EPA

with a valuable benchmark, and are shown in Tables IV-43 and

IV-44. Note that "N/A" indicates that a specific proposal

was not made, while "none" indicates that the proposal was

for no valid range limit whatsoever.
193

Table IV-43

Proposals for Reformulated Gasoline Valid Ranges 

for the Complex Model

Low end of range

EPA API AAMA Penzoil ARCO P Exxon Mobil

Oxygen

Sulfur

RVP

E200

E300

Aromatics

Olefins

Benzene

0 

50 

6 

33 

76 

15 

2 

0.2 

0 

0 

6 

30 

70 

0 

0 

0 

0 

0 

6.7 

40 

80 

15 

0 

0 

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

0 

0 

N/A

30 

70 

0 

0 

0 

N/A

10 

6 

N/A

N/A

10 

2 

0 

0 

10 

6 

33 

76 

10 

0 

0 

High end of range

EPA API AAMA Penzoil ARCO P Exxon Mobil

Oxygen

Sulfur

RVP

E200

E300

Aromatics

Olefins

Benzene

3.7 

500 

10 

65 

94 

47 

20 

2 

3.7 

500 

15 

70 

100 

55 

25 

2 

3.7 

500 

10 

65 

95 

40 

20 

1 

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

3.7 

500 

N/A

70 

100 

55 

25 

2 

N/A

600 

15 

N/A

N/A

55 

30 

2 

3.7 

500 

15 

72 

94 

47 

20 

0 
194

Table IV-44

Proposals for Conventional Gasoline Valid Ranges 

for the Complex Model

Low end of range

EPA API AAMA Penzoil ARCO P Exxon Mobil

Oxygen

Sulfur

RVP

E200

E300

Aromatics

Olefins

Benzene

0 

0 

6 

30 

70 

10 

0 

0 

0 

0 

6 

30 

70 

0 

0 

0 

0 

0 

6.7 

35 

75 

10 

0 

0 

0 

0 

6 

30 

70 

10 

0 

0 

none

none

none

none

none

none

none

none

none

none

none

none

none

none

none

none

0 

0 

6 

25 

70 

10 

0 

0 

High end of range

EPA API AAMA Penzoil ARCO P Exxon Mobil

Oxygen

Sulfur

RVP

E200

E300

Aromatics

Olefins

Benzene

3.7 

1000 

10 

70 

95 

50 

25 

4.9 

3.7 

1000 

15 

70 

100 

60 

30 

4.9 

3.7 

1000 

10 

70 

95 

40 

25 

2 

3.7 

1000 

12 

70 

95 

55 

45 

5 

none

none

none

none

none

none

none

none

none

none

none

none

none

none

none

none

3.7 

1000 

15 

72 

95 

50 

25 

4.9 

The Agency used all of the above criteria in specifying the

valid range for the Complex Model. However, the Agency relied

most heavily on the behavior of the Complex Model, the limits of

the data core, and the valid range proposals from outside

parties, particularly when such proposals were supported by

available information. These three factors include elements from

all the other criteria, and have the most direct and definable

impact on the valid range. The needs of each program are

reflected in the valid range proposals in that commenters have a

unique perspective on the business ramifications of valid range

limitations. The valid range proposals reflect the purpose of

specifying the valid range to provide the greatest flexibility to

suit private interests. The Agency therefore seriously

considered each of the valid range proposals and weighed them

against the available data and observed behavior of the model

before specifying the final valid range. The final values are

shown in Table IV-45.

EPA defined the oxygen limits so as to encompass all

oxygenated gasolines which meet EPA's "substantially similar"

requirements, including a small blending tolerance. Similarly,

the E200, lower E300, and upper aromatics limits were set near to
195

those of the data core while making allowances for these

parameters' measurement and blending tolerances. The upper limit

for E300 was not constrained since high E300 values appear to

result in reduced emissions. However, EPA restricted its linear

extrapolation of E300 effects to 95 volume percent; fuels with

higher E300 values must be evaluated as if their E300 levels were

equal to 95 volume percent. In effect, this approach gives such

fuels no additional benefits for E300 increases beyond 95 volume

percent since EPA is not confident in its ability to quantify

these benefits. Nonetheless, EPA expects such increases to

result in lower emissions, so EPA chose not to restrict the upper

E300 limit of the model.

Aromatics reductions result in NOx reductions, with the

benefits increasing as aromatics levels decrease. As a result,

EPA's extrapolation of aromatics' effects likely underestimates

the benefits of aromatics reductions below 18 vol%. Since EPA

believes its model is unlikely to overestimate the benefits of

very low aromatics levels, EPA set a relatively unconstraining

lower aromatics limit of 10 volume percent when linearly

extrapolating its models. In addition, EPA decided to allow

fuels with aromatics levels below 10 volume percent to be

certified using the Complex Model, but such fuels' emission

performance must be evaluated as if their aromatics levels were

at 10 volume percent. This approach provides refiners with

greater flexibility without imposing significant risks on the

environment. Olefin limits were based on similar reasoning: EPA

considers the risk that its model underestimates the NOx

increases associated with olefin levels beyond 19 vol% to be

minimal.

EPA chose not to extend the upper limit of the valid range

for sulfur beyond 500 ppm for the reformulated gasoline program

because the NOx model had an emissions maximum at approximately

550 ppm sulfur. This maximum appears to be an artifact of the

form of the model (see Section D.4 for further discussion). The

available data indicates that as sulfur levels increase,

emissions increase but at a decreasing rate. Hence the straightline extrapolation used by EPA would be expected to deviate

significantly from the underlying "true" effect of sulfur as

sulfur levels increase to levels substantially above the upper

limit of the data core. This deviation is particularly important

for the RFG program, which requires fuels to meet absolute

emission performance standards. The anti-dumping program,

however, requires refiners to meet emission standards relative to

their 1990 baseline emissions; as a result, the accuracy of the

extrapolation is less critical. EPA has set a less restrictive

upper limit to the valid range for anti-dumping since it

considers the gain in flexibility to outweigh the possible losses

due to less precise extrapolation.
196

The upper RVP limit was set so as to not exclude any summer

gasolines which might be sold in 1995 or later. The lower limit

was set so as to encompass the RVP levels that EPA expects to

characterize Phase II reformulated gasolines, including the

associated measurement tolerance. EPA decided against setting a

less restrictive lower limit based on concerns expressed by some

commenters that such gasolines might produce driveability

problems. Poor driveability tends to result in increased

emissions, and EPA has no data which demonstrate emission

benefits of lowering RVP levels below 7 psi.

The only pollutant affected by fuel benzene levels is

benzene itself. The upper limit for RFG is largely irrelevant,

since benzene is limited to a maximum of 1.3 vol% under averaging

and 1 vol% under per-gallon compliance. Gasolines containing 5

vol% or more benzene must be labeled as hazardous materials under

existing OSHA requirements. EPA believes that this labeling

requirement has prevented marketing of such fuels in the past and

will continue to do so in the future. For this reason, EPA

believes that the 4.9 vol% limit on conventional gasolines

encompasses all such fuels that are likely to be produced.

Table IV-45

Final Valid Ranges for the Complex Model

Reformulated Gasoline Conventional Gasoline

Low end High end Low end High end

Oxygen

Sulfur

RVP

E200

E300

Aromatics

Olefins

Benzene

0

0

6.4

30

70

10

0

0

3.7

500

10

70

95

50

25

2

0

0

6.4

30

70

0

0

0

3.7

1000

11

70

100

55

30

4.9

3. Extrapolation Methodology

The regression equations that comprise the Complex Model are

empirical in nature. Thus the strictest possible application of

these equations would limit their use to the range of fuel

parameters specified by the data core. As discussed in Section

D.2, however, the valid range of the Complex Model has been

extended beyond these limits. To use of the Complex Model

outside the data core, EPA has extrapolated the regression

equations in such a manner as to maintain the integrity and

accuracy of the relationships between fuel properties and

emissions. This section provides the mathematical basis for
197

model extrapolation, while Section D.5 applies this methodology

to each of the pollutant models.

The choice of extrapolation methodology applied to a given

regression equation depends on one's confidence in the accuracy

of the underlying regression equation. The regression techniques

considered by EPA include:

 Regression curve approach

This approach uses the regression curve as-is for all areas

of the fuels space. It is easy to implement and requires no

changes to the derived regression equations. However, it

assumes that the regression equation accurately captures the

underlying relationship between fuel properties and

emissions. It also assumes that trends seen within the data

core continue at levels beyond the data core.

 Flat-line approach

This approach uses the regression curve only within the

limits of the data. It holds fuel parameters which fall

outside the data core at the nearest limit of the data core

when evaluating fuel performance by the Complex Model. In

graphical form, the slope of the emission performance versus

fuel parameter level curve discontinuously becomes zero

(i.e., flat) for fuel parameter levels equal to or beyond

the nearest limit of the data core.

This approach is attractive because it is straightforward to

implement. It is conservative from a statistical standpoint

since it assumes that nothing can be inferred from the

regression equations about areas of the fuels space not

covered by the data core. However, refiners would be given

no incentive at the margin to make high-emitting fuels

cleaner if they fall outside the data core. In addition,

this approach ignores the results of studies not included in

the Complex Model database which indicate that the emission

performance versus fuel parameter level curve has a non-zero

slope outside the data core.

 Straight-line approach

This approach uses the first derivative of the Complex Model

equations to extrapolate those equations. It assumes that

the relationship between emissions performance and fuel

parameter level at parameter levels beyond the data core can

be approximated accurately by the slope of the emissions

performance versus fuel parameter curve (in multidimensional space) at the limits of the data core.
198

This approach preserves the non-zero fuel parameter:emission

relationships observed within the data core. It avoids 

inferring second-order effects for fuels outside the data

core. However, this approach can be complex to implement

due to the need to take derivatives. In addition, the slope

observed at the limits of the data core may differ from the

actual slope outside the data core, though this problem is

mitigated to some degree since the difference is likely to

remain small for fuel parameter values that are relatively

close to the limits of the data core.

In addition to the choice of extrapolation approach, the

choice of the point from which to start the extrapolation also

must be determined before specific extrapolations can be applied

to the Complex Model. Ideally, this point would coincide with

the limits of the data core. However, the mathematical form of

the exhaust complex model is limited to first- and second-order

functions of fuel parameters. The actual relationship between

fuel properties and emission levels is unlikely to take this

form. A full mathematical model of the underlying phenomena or

the data included in the Complex Model database may require

decaying or growing exponentials, third-order polynomials, square

root relationships, or even more complex functions. The Complex

Model approximates the actual relationships between fuel

properties and emissions using first- and second-order

polynomials; such approximations can result in extrema (emission

maximums or minimums) which are artifacts of the form of the

exhaust Complex Model equations and which do not reflect the

underlying data used to develop the model. These inappropriate

extrema may occur within or outside of the data core. The

extrapolation approaches described above can be used to correct

such inappropriate extrema by selecting an appropriate starting

point for the extrapolation, such as the extrema point itself. 

The location of extrema in the Complex Model will be discussed in

Section D.4, while the ramifications of those extrema will be

addressed in Section D.5.

The regression curve and flat-line approaches to

extrapolation are mathematically straightforward to derive and

apply. The remainder of this section develops and presents the

mathematical basis for the straight-line approach to

extrapolation. This approach begins with the performance

calculation procedure described in Section C but includes the

following additional steps:

1) Determine which fuel parameters for the target

fuel fall within the extrapolation range but

outside the "allowable range," which is the range

within which the unmodified regression equations

can be used. The extrapolation range and

allowable range for all fuel parameters are

specified in Section D.5.
199

2) Determine the fuel parameter values for an "edge

target fuel" in which the fuel parameters that

would naturally fall within the extrapolation

range are held at the limits of the allowable

range. Target fuel parameters that are within the

allowable range should remain at their target fuel

levels when defining the edge target fuel.

3) Evaluate the performance of the edge target fuel. 

This step yields a performance estimate at the

edge of the allowable range, or an "edge

performance" symbolized by Y(et), where "et"

refers to "edge target fuel."

4) Determine the multi-dimensional slope of the

emissions versus fuel parameter curve at the point

in the multi-dimensional fuels space defined by

the edge target fuel's composition. This step is

accomplished by calculating the first derivative

of the exhaust regression equation(s).

5) Compute the additional performance benefit or

detriment due to the fuel parameter(s) that are

beyond the allowable range. This step yields an

"extrapolation performance factor" symbolized by

Y which is calculated by multiplying the

difference between the target fuel parameter level

and the nearest limit of the allowable range by

the slope calculated in step (4).

6) Add the edge performance to the extrapolation

performance factor to obtain the oveerall

oerformance of the original target fuel.

These six steps can be mathematically summarized as 

(D.1) Y(t) = Y(et) + Y

Determining the fuel parameter values for the edge target fuel

and calculating performance estimates for the edge target fuel

need no elaboration beyond that given in the steps above. 

Calculating Y, however, is considerably more complex because it

requires determining the first derivative of the exhaust model

for each pollutant.

As described in Section D.5, the entire non-exhaust model is

extrapolated by way of the regression curve approach, i.e., the

non-exhaust emissions for any fuel within the valid range can be

evaluated directly from the non-exhaust equations. Thus only the

exhaust model equations are candidates for straight-line

extrapolation. And since the calculations in the exhaust model
200

are first carried out in percentage change terms and must

subsequently be converted into gram/mile estimates, it is most

appropriate to use the percentage-change performance as the

dependent variable in determining the first derivative for the

exhaust models. As described in Section C above, the exhaust

pollutant performance of a target fuel is calculated from

Equation (C.7):

(D.2) Y(t) = 1

i

{wi * [exp(fi(t))/exp(fi(b)) - 1] * 100}

where Y is the fleet average percent change in any exhaust

pollutant, the wi are the vehicle group weighting factors, t

refers to the target fuel, and b refers to the baseline fuel. 

This is the equation from which the first derivative, and thus

the extrapolation performance factor Y, will be derived. 

In order to determine the extrapolation performance factor,

the first derivative of Equation (C.7) must be determined for the

edge target fuel as described in step (4). Since the derivative

of a sum is equivalent to the sum of the derivatives, the

derivative of each vehicle group term in Equation (D.2) can be

evaluated separately. Thus Equation (D.2) is first separated

into its vehicle group-specific terms:

(D.3) Y(et)i = wi * [exp(fi(et))/exp(fi(b)) - 1] * 100

Equation (D.3) is shown as being evaluated for the edge target

fuel, consistent with step 3) above. The total derivative of

Equation (D.3) is derived from the partial derivatives of

Equation (D.3) with respect to each of the fuel parameters. 

Mathematically, this total derivative can be written in its

general form as

(D.4) dYi = 1

j

(Yi/Pj)dPj

where the Pj are the possible fuel parameters in the Complex

Model equations for the pollutant of interest. As before, the

subscript i refers to the vehicle group, of which there are two

in the final Complex Model: one for normal emitting vehicles, and

a second for higher emitting vehicles. Note that linear

extrapolation of a first-order equation is identical to use of

the unmodified original equation and is therefore equivalent to

the the regression curve extrapolation approach. Thus the

straight line extrapolation approach need not be applied to fuel

parameters that are only found in first-order terms.

The total derivative of Equation (D.2) can be written

generally as

(D.5) dY = 1

i

(wi *dYi) = 1

i

 [wi * 1

j

(Yi/Pj)dPj]
201

The general Equation (D.4) can be applied specifically to

Equation (D.3) and the results weighted by the wi weighting

factors and then summed to obtain the Complex Model-specific

results of Equation (D.5). In other words, the solution to

Equation (D.4) is sufficient to solve Equation (D.5).

In order to best illustrate the evaluation of Equation (D.4), a

hypothetical second-order function f can be created. Eliminating

the vehicle group distinction indicated by the subscript i and

instead making the vehicle group distinction implicit, this

function can be written as

(D.6) f(A,B) = 1A+2B+3A2+4B2+5AB

In the above equation, A and B are hypothetical uncentered fuel

parameters, and the coefficients i are determined through

statistical regressions. Note that all possible combinations of

linear, squared, and interactive terms have been included in this

hypothetical function. Thus the vehicle group-specific equation

giving the performance of a target fuel as a function of the fuel

parameters A and B is

exp(1At+2Bt+3At

2

+4Bt

2

+5AtBt) 

(D.7) Y(t) = exp(1Ab+2Bb+3Ab

2

+4Bb

2

+5AbBb) 

- 1 * 100

where Y(t) is the performance of the target fuel for any

pollutant, At is the value of fuel parameter A for the target

fuel, Bb is the value of fuel parameter B for the baseline fuel,

and so on. To determine the total first derivative of Y, partial

derivatives of Y with respect to each of the fuel parameters must

be derived analytically and summed according to the following

equation:

(D.8) dY = (Y/A)dA + (Y/B)dB

dY is called the differential of Y. Since the total derivative

will be used to determine the slope of the curve at the edge

target fuel, each of the partial derivatives must be evaluated at

the edge target fuel:

(D.9) dY = (Y/A)

edge dA + (Y/B)edge dB

Since the Complex Model is at most a second-order model (in

logarithmic space), the first derivative must be first order. 

This fact implies that the total differentials for Y, A, and B in

Equation (D.9) can be written as finite deviations from the edge

target fuel:

dY = Y = Y(t) - Y(et)
202

dA = A = At - Aet if At < low end of allowable range or

 At > high end of allowable range

 = 0 if At low end of allowable range and

 At  high end of allowable range

dB = B = Bt - Bet if Bt < low end of allowable range or

 Bt > high end of allowable range

 = 0 if Bt low end of allowable range and

 Bt  high end of allowable range

The conditional statements associated with each fuel parameter

differential quantify the following conditional statement:

If the value of a fuel parameter for a given target

fuel lies within the allowable range, then do not use

the first derivative of the model to extrapolate the

function Y with respect to that fuel parameter;

otherwise, linearly extrapolate from the edge target

fuel to the fuel parameter value of the target fuel.

Thus a given fuel parameter differential will be zero if that

fuel parameter lies within the allowable range, but will be

nonzero if it lies outside the allowable range. Extrapolation

occurs only for fuel parameters which lie beyond the allowable

range.

The partial derivatives of pollutant Y with respect to each

of the two fuel parameters A and B are shown below. Note that

f(b) can be considered a constant since the baseline fuel does

not change.

Y/A = [exp(f(t))/exp(f(b))] * 100 * f(t)/A

= [exp(f(t))/exp(f(b))] * 100 * (1 + 2*3At + 5Bt)

Y/B = [exp(f(t))/exp(f(b))] * 100 * f(t)/B

= [exp(f(t))/exp(f(b))] * 100 * (2 + 2*4Bt + 5At)

The total derivative for Y can now be assembled for this

hypothetical regression equation, and the value of Y for a given

target fuel calculated as a function of the fuel parameters A and

B. When Equation (D.9) is evaluated with the differentials and

partial derivatives shown above, the specific form of Equation

(D.1) is produced:

Y(t) = Y(et) +

[exp(f(t))/exp(f(b))]*100*(1+2*3At+5Bt) * (At - Aet) +

[exp(f(t))/exp(f(b))]*100*(2+2*4Bt+5At) * (Bt - Bet)

(D.10)
203

And therefore, from Equation (D.1), 

Y = [exp(f(t))/exp(f(b))]*100*(1+2*3At+5Bt) * (At - Aet) +

[exp(f(t))/exp(f(b))]*100*(2+2*4Bt+5At) * (Bt - Bet)

(D.11)

Note that the conditional statements described above still apply

to the fuel parameter differentials (given as differences) in

Equation (D.10).

Equation (D.10) is a vehicle group-specific equation, and

therefore represents a solution to Equation (D.1) only for a

single vehicle group; Equations (D.10) and (D.11) actually give

the solutions for Yi(t) and Yi, respectively. To obtain the

fleet average solution to Equation (D.1), the vehicle groupspecific solutions must be weight-averaged with the vehicle group

weighting factors wi according to Equation (D.5). Thus dYi (or

Yi) has been determined only for a single vehicle group in this

example, and must be combined with the solutions for dYi for the

other vehicle group in order to determine the overall exhaust

emission performance of the target fuel.

4. Extrema

As discussed in the previous section, the second-order

polynomial form of the Complex Model can introduce inappropriate

extrema into the model. In fact, all second order equations

contain extrema points at which the direction of the emission

effect changes (from increasing to decreasing or vice-versa). 

The Agency has considered a number of approaches to mitigate the

effects of inappropriate extrema on predicted emissions using the

unmodified Complex Model. These approaches and the Agency's

concerns with each are reviewed below:

1. The Complex Model could be redeveloped from the

original database using growing or decaying exponential

functions instead of simple second-order polynomials.

This approach replaces one assumed functional form for

the underlying combustion and catalyst chemistry with a

different assumed functional form. Replacing only

those second-order relationships which would be better

represented with a decaying exponential would require a

far deeper understanding of combustion and catalyst

chemistry than is currently available. This approach

also raises the possibility that other non-polynomial

functions should be considered, would compromise the

consistency in model form between pollutant-specific

models, and could make the use of the random balance

method to consolidate the models for normal emitter

technology groups impossible.
204

2. Any second-order terms which result in questionable

behavior could be pre-excluded from the Complex Model,

which would then be re-estimated.

EPA rejected this approach after careful evaluation, as

indicated by the models included in the July 14, 1993

docket submittals. This approach relies on strictly

first-order effects, which can result in behaviors that

are just as questionable as the second-order effects. 

Also, linear extrapolation beyond the limits of the

data for the affected terms becomes unjustifiable since

the model's reliability and accuracy would decrease

rapidly as one moved beyond the data core. Further,

EPA's efforts to build such models resulted in poorer

predictability. Finally, EPA found that because of the

covariation between fuel parameters, pre-excluding one

second-order term resulted in the introduction of a

second-order term for a covarying parameter. For

example, when the ARO2

 term was pre-excluded, the

resulting model included an E3002 term that was just as

troublesome as the original ARO2 term.

3. One or more interactive terms could be forced into the

model in an effort to replace the squared term causing

the inappropriate behavior with better-behaved

interactive terms.

This approach assumes that the statistical derivation

of the Complex Model has assigned an effect to a

squared term which should instead be assigned to an

interactive term. All attempts by the Agency to

implement this approach resulted in a model which

retained the troublesome squared term or which suffered

from other behavioral shortcomings.

4. Flat-line extrapolations could be imposed from the

extrema points. This approach, which was supported by

a number of commenters, is illustrated in Figure IV-1,

which also shows a decaying exponential function. 

Statistical and chemical considerations suggest that

some of the second-order terms in the complex model

result from phenomena which exhibit such underlying

behavior.
205

Figure IV-1: Mitigating Extrema

0

5

10

15

Fue l param e te r

Em is s io n s

Sec ond-order poly nomial

Flat-line ex trapolation

Dec ay ing ex ponential

This approach required the fewest assumptions regarding

the form of the regression equation, and it resulted in

models which behaved in a manner consistent with the

available data. In addition, it most closely

approximated a decaying exponential effect without

compromising the form of the model.

The Agency determined that flat-line extrapolation was the most

appropriate method for mitigating questionable effects caused by

extrema.

Applying a flat-line extrapolation from an extremum point is

equivalent to linearly extrapolating the model from the same

point. At the extremum, the slope calculated by the linear

extrapolation method is zero (in fact, a zero first derivative is

a necessary condition for an extremum) and is thus identical to

the slope imposed by a flat-line extrapolation from that point.

The use of flat-line extrapolation implies that the

previously stated conditions under which linear extrapolation is

to be used must be supplemented. The points at which linear

extrapolations are to begin (i.e., the limits of the allowable

range) are defined by one of the following two considerations:

1) The limits of the data core.

2) The location of extrema.
206

The data core is the default criterion since it defines the range

of fuel parameters within which the regression equations are most

trustworthy. Insofar as the data core does not reach the limits

of the valid range, linear extrapolation must be used to extend

the regression equations without placing an unwarranted amount of

trust in their curvature. If, however, an extremum point is

located within the limits of the data core, the model may behave

inappropriately. In such cases, the extremum point replaces the

nearest data core limit as the limit of the allowable range, and

linear extrapolation begins at that point instead of at the end

of the data core.

Since the Complex Model regression equations are

multivariate, separate extrema can exist for each fuel parameter. 

Thus the partial derivative of the regression equation with

respect to a given fuel parameter must be calculated, set equal

to zero, and solved for the fuel parameter of interest to

determine the extremum location. When this is done for the

Complex Model, the extrema locations shown in Tables IV-46 and

IV-47 are identified. Note that "N/A" indicates that either a

strictly linear relationship exists between the fuel parameter

and pollutant in question, or there is no relationship

whatsoever.

Table IV-46

Phase I Extrema Locations for the Complex Model

VOC NOx Toxics*

Oxygen

Sulfur

RVP

E200

E300

Aromatics

Olefins

Benzene

MTBE

ETBE

Ethanol

TAME

N/A

N/A

N/A

65.8

80.3-101.8

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

554

N/A

N/A

N/A

36.2

3.77

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A
207

Table IV-47

Phase II Extrema Locations for the Complex Model

VOC NOx Toxics*

Oxygen

Sulfur

RVP

E200

E300

Aromatics

Olefins

Benzene

MTBE

ETBE

Ethanol

TAME

N/A

N/A

N/A

65.5

79.7-100.9

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

578

N/A

N/A

N/A

36.8

3.77

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A * All four toxics models are linear, and therefore contain no extrema

5. Extrapolation of the Final Complex Model

The linear extrapolation methodology for the Complex Model

equations as described above requires the pollutant-specific

forms of Equation (D.1) and the specific points at which

extrapolation is to begin. Calculation of the first derivative

and application of flat-line extrapolation from extrema are

required only for the exhaust VOC and exhaust NOx models. The

exhaust toxics models are strictly linear, and they and the nonexhaust VOC and benzene models can be extrapolated via the

regression curve approach (see Section D.3 for a description of

the various extrapolation methodology options). In this section,

the definition of the edge target fuel will be reiterated, the

points at which extrapolation is to begin (which define the

allowable ranges) will be presented, and then the pollutantspecific forms of Equation (D.1) will be derived and presented

for both exhaust VOC and NOx.

As described in Section D.3, linear extrapolation beyond the

allowable range requires the definition and evaluation of an edge

target fuel. It is at the position of the edge target fuel that

both the edge target fuel performance and the (multi-dimensional)

slope of the curve are calculated. The slope of the curve is

used to determine the extrapolation performance factor, and

Equation (D.1) is then used to determine the extrapolated

performance of the target fuel. The edge target fuel represents

the position in the multi-dimensional fuels space that is closest

to the position of the target fuel without going outside the

limits of the allowable range defined below. Since the allowable

range for a given fuel parameter is pollutant-specific, the edge

target fuel must also be defined separately for each pollutant. 

The edge target fuel can therefore be defined as follows:
208

All fuel parameters of the edge target fuel are

identical to those of the target fuel with the

following exception: if a given target fuel parameter

is outside of the allowable range, then hold the

equivalent edge target fuel parameter to the limit of

the allowable range which is closest in value to the

target fuel value.

Thus if the target fuel value of aromatics is 52 vol% and the

allowable range is defined as 18 to 46 vol%, then the edge target

fuel aromatics content should be 46 vol%, since 46 vol% is closer

to 52 vol% than is 18 vol%.

The data core and the location of extrema points were

specified above to delineate the allowable range, which is the

range of fuel parameters within which the Complex Model's exhaust

emission equations can be used without modification and outside

of which linear extrapolation must be employed. The general

guidelines used by EPA to establish the allowable ranges of fuel

parameters which are included in second-order (either squared or

interactive) terms can be stated as follows:

If an extremum point for a given fuel parameter is

located within the data core limits for that fuel

parameter, it indicates inappropriate model behavior. 

Therefore, linear extrapolation must begin at the

extreme point and proceed in the direction deemed most

appropriate. If an extreme point is not located within

the data core, linear extrapolation must begin at the

limits of the data core.

The appropriate direction of the linear extrapolation from an

extremum point depends primarily on the following two factors:

1) The position of the extremum point relative to the

limits of the data core.

2) The underlying combustion and catalyst chemistry, if

known.

2) The emission trends identified in specific studies or

in the Complex Model database.

Linear extrapolation of a given fuel parameter from the low end

of the data core proceeds downward to lower parameter values,

while linear extrapolation from the high end of the data core

proceeds upwards to higher parameter values. Any regression

equation containing fuel parameters that are strictly linear need

not be extrapolated using the straight-line, first derivative
 46 See discussion in Section D.1 regarding the effect of an exponential

function on the behavior of polynomials.

209

technique since such extrapolation is equivalent to using the

unmodified equation.46

Based on the foregoing discussion, EPA has defined the

allowable range for all second-order fuel parameters included in

the Complex Model as shown in Table IV-48. 

Table IV-48

Allowable Parameter Ranges for Use of the Complex 

Model Regression Equations

Fuel

parameter

Pollutant Phase I Phase II

Low

end

High

end

Low

end

High

end

Sulfur NOx 10 450 10 450

E200 VOC 33 65.83 33 65.52

E300 VOC 72 vary* 72 vary**

Aromatics VOC

NOx

18

18

46

36.2

18

18

46

36.8

Olefins NOx 3.77 19 3.77 19

 * The high end of the allowable range (in vol%) equals 79.75 +

0.3846*ARO, where ARO is the aromatics content of the target fuel,

or 94 vol%, whichever is lower.

 ** The high end of the allowable range (in vol%) equals 80.32 +

0.3903*ARO, where ARO is the aromatics content of the target fuel,

or 94 vol%, whichever is lower.

Only the allowable ranges for those fuel parameters present as

second-order terms are shown in Table IV-48; for all other fuel

parameters, the Complex Model equations can be used without

modification out to the limits of the valid range. Thus the

"allowable range" differs from the "valid range" only for those

fuel parameters with second-order effects on a given pollutant. 

The high and low values in Table IV-48 bracket the range of

values for a given fuel parameter within which the exhaust

regression equations can be used without modification, and

outside of which straight-line linear extrapolation must be

employed. The values in Table IV-48 also indicate the points at

which the multi-dimensional slope of the emissions versus fuel
210

parameter relationship must be evaluated when linear

extrapolation is required. For fuel parameters that contain an

extremum point somewhere within the data core, the location of

that extremum point defined one end of the allowable range. Note

that the allowable ranges given in Table IV-48 apply only to the

exhaust VOC and NOx portions of the Complex Model; the exhaust

toxics models and the nonexhaust VOC and benzene models can be

used without modification throughout all areas of the fuels

space, based on the regression curve approach to extrapolation

described in Section D.3.

The high end of the allowable range for the effect of E300

on VOC is variable due to the ARO*E300 term in the exhaust VOC

model. Since the upper and lower limits of the data core for

E300 are 72 vol% and 94 vol%, respectively, an extremum point

between these values must, by the conditions described above,

define one end of the allowable range. EPA derived a

relationship defining these extrema by taking the first

derivative of the exhaust VOC equations:

(D.12) Phase I E300 extremum =

80.32 vol% + 0.3903 x aromatics vol%

(D.13) Phase II E300 extremum =

79.75 vol% + 0.3846 x aromatics vol%

As per the discussion of extrema in Section D.4, Equations (D.12)

and (D.13) indicate that the E300 extremum point can be greater

than or less than 94 vol% depending on the target fuel aromatics

content. Thus the upper end of the allowable range for the

effect of E300 on exhaust VOC is conditional:

If the E300 extremum as calculated from Equation (D.12)

or (D.13) is less than 94 vol%, then the E300 extremum

becomes the upper limit of the allowable range for

E300. If the E300 extremum is greater than 94 vol%,

then the upper end of the allowable range for E300 is

94 vol%.

For exhaust VOC, linear extrapolation must be used if E200,

E300, or aromatics are outside of their allowable ranges. To

obtain the exhaust VOC-specific form of Equation (D.1), the first

partial derivatives of the exhaust VOC equation must be taken

with respect to each of these three fuel parameters. Since there

are two vehicle group exponential terms for all exhaust

regression equations, these partial derivatives must be derived

separately for each vehicle group. From Section A.9, the final

exhaust VOC regression equation for Phase I is

 (D.14) VOC(t) = 100% x 0.52 x [exp(a(t))/exp(a(b)) - 1] +

100% x 0.48 x [exp(b(t))/exp(b(b)) - 1]
211

where the functions a and b are defined as

a = (-0.003641 x Oxygen) + (0.0005219 x Sulfur) +

 (0.0289749 x RVP) + (-0.014470 x E200) +

 (-0.068624 x E300) + (0.0323712 x Aromatics) +

 (-0.002858 x Olefins) + (0.0001072 x E2002

) +

 (0.0004087 x E3002) + (-0.0003481 x Aromatics x E300)

b = (-0.003626 x Oxygen) + (-0.000054 x Sulfur) +

 (0.043295 x RVP) + (-0.013504 x E200) +

 (-0.062327 x E300) + (0.0282042 x Aromatics) +

 (-0.002858 x Olefins) + (0.000106 x E2002) +

 (0.000408 x E3002) + (-0.000287 x Aromatics x E300)

and a(t) refers to the evaluation of function a for the target

fuel, b(b) refers to the evaluation of function b for the

baseline fuel, and so on. The first partial derivatives with

respect to E200, E300, and aromatics can be derived separately

for normal emitting vehicles (the first term in Equation (D.14))

and higher emitting vehicles (the second term in Equation

(D.14)):

VOC1/E200 = 100% x 0.52 x [exp(a(t))/exp(a(b))] x

[0.000214416 x E200 - 0.0144703]

VOC1/E300 = 100% x 0.52 x [exp(a(t))/exp(a(b))] x

[0.000817412 x E300 - 0.0686242 - 0.00034806 x

ARO]

VOC1/ARO = 100% x 0.52 x [exp(a(t))/exp(a(b))] x

[-0.0003481 x E300 + 0.0323712]

VOC2/E200 = 100% x 0.48 x [exp(b(t))/exp(b(b))] x 

[0.000212 x E200 - 0.0135039]

VOC2/E300 = 100% x 0.48 x [exp(b(t))/exp(b(b))] x 

[0.000816 x E300 - 0.0623274 - 0.000287 x ARO]

VOC2/ARO = 100% x 0.48 x [exp(b(t))/exp(b(b))] x 

[-0.000287 x E300 + 0.0282042]

The subscript 1 indicates the normal emitter vehicle group, while

the subscript 2 indicates the higher emitter vehicle group. The

general extrapolation equation for VOC, per Equation (D.1), is

written as follows: 

(D.15) VOC(t) =

100% x 0.52 x [exp(a(et))/exp(a(b)) - 1] +

100% x 0.48 x [exp(b(et))/exp(b(b)) - 1] +

(VOC1/E200)

et x E200 +

(VOC1/E300)

et x E300 +

(VOC1/ARO)

et x ARO +
212

(VOC2/E200)

et x E200 +

(VOC2/E300)

et x E300 +

(VOC2/ARO)

et x ARO

Note that the first two terms are now evaluated for the edge

target fuel rather than the target fuel, as are the partial

derivatives. The final extrapolation equation for Phase I

exhaust VOC is therefore given by Equation (D.16):

Phase I VOC extrapolation equation:

(D.16) VOC(t) =

100% x 0.52 x [exp(a(et))/exp(a(b)) - 1] +

100% x 0.48 x [exp(b(et))/exp(b(b)) - 1] +

100% x 0.52 x [exp(a(et))/exp(a(b))] x

 {E200 x [0.000214416 x E200

et - 0.0144703] +

 E300 x [0.000817412 x E300

et - 0.0686242 -

 0.00034806 x ARO

et] + ARO x [-0.000348061 x E300

et + 0.0323712]} +

100% x 0.48 x [exp(b(et))/exp(b(b))] x

 {E200 x [0.000212 x E200

et - 0.0135039] + E300 x [0.000816 x E300

et - 0.0623274 -

 0.000287 x ARO

et] + ARO x [-0.000287 x E300

et + 0.0282042]}

a = (-0.003641 x Oxygen) + (0.0005219 x Sulfur) +

 (0.0289749 x RVP) + (-0.014470 x E200) +

 (-0.068624 x E300) + (0.0323712 x Aromatics) +

 (-0.002858 x Olefins) + (0.0001072 x E2002) +

 (0.0004087 x E3002) + (-0.0003481 x Aromatics x E300)

b = (-0.003626 x Oxygen) + (-0.000054 x Sulfur) +

 (0.043295 x RVP) + (-0.013504 x E200) +

 (-0.062327 x E300) + (0.0282042 x Aromatics) +

 (-0.002858 x Olefins) + (0.000106 x E2002) +

 (0.000408 x E3002) + (-0.000287 x Aromatics x E300)

The conditions under which the finite differences E200, E300,

and ARO are nonzero are identical to the conditions under which

these fuel parameters require extrapolation. Thus for each of

these three fuel parameters which is outside of the allowable

range as defined in Table IV-48, the associated finite difference

will be equal to the difference between the target fuel value and

the nearest limit of the allowable range. However, to simplify

the regulations, linear extrapolation from extrema points was

replaced with flat-line extrapolations, since for extrema points

these two extrapolation methodologies are equivalent. The

allowable range conditions can be translated into the following

mathematical conditions:

Phase I Conditions for extrapolating exhaust VOC:
 47 In fact, the conditions only guarantee that the terms in Equation

(D.16) which contain the partial derivatives (which should be zero at extrema

points) will be zero. However, mathematically the two approaches are equivalent. 

The regulations were written with the simplest, most straightforward approach to

facilitate implementation of extrapolation.

213

If E200

t < 33, then E200 = E200t - 33

Otherwise E200 = 0

If E300

t < 72, then E300 = E300t - 72

If E300

t > 94 and 80.32 + 0.39.3 x AROt > 94, then E300 =

 E300

t - 94

Otherwise E300 = 0

If ARO

t < 18, then ARO = AROt - 18

If ARO

t > 46, then ARO = AROt - 46

Otherwise ARO = 0

These conditions guarantee that the slope of the VOC regression

curve at the position of the extrema points will be zero47 as

required by the definition of extrema points.

The Phase II extrapolated performance equation for VOC is

identical to equation D.16, except that the vehicle group

weighting factors change:

Phase II VOC extrapolation equation:

(D.17) VOC(t) =

100% x 0.444 x [exp(a(et))/0.0620896 - 1] +

100% x 0.556 x [exp(b(et))/0.1037675 - 1] +

100% x 0.444 x [exp(a(et))/0.0620896] x

 {[0.000214416 x E200

et - 0.0144703] x E200 +

 [0.000817412 x E300

et - 0.0686242 -

 0.00034806 x ARO

et] x E300 + ARO x

 [-0.000348061 x E300

et + 0.0323712]} +

100% x 0.556 x [exp(b(et))/0.1037675] x 

 {[0.000212 x E200

et - 0.0135039] x E200 +

 [0.000816 x E300

et - 0.0623274 - 0.000287 x

 ARO

et] x E300 + ARO x

 [-0.000287 x E300

et + 0.0282042]}

a = (-0.003641 x Oxygen) + (0.0005219 x Sulfur) +

 (0.0289749 x RVP) + (-0.014470 x E200) +

 (-0.068624 x E300) + (0.0323712 x Aromatics) +

 (-0.002858 x Olefins) + (0.0001072 x E2002

) +

 (0.0004087 x E3002

) + (-0.0003481 x Aromatics x E300)
214

b = (-0.003626 x Oxygen) + (-0.000054 x Sulfur) +

 (0.043295 x RVP) + (-0.013504 x E200) +

 (-0.062327365 x E300) + (0.0282042 x Aromatics) +

 (-0.002858 x Olefins) + (0.000106 x E2002

) +

 (0.000408 x E3002) + (-0.000287 x Aromatics x E300)

Phase II Conditions for extrapolating exhaust VOC:

If E200

t < 33, then E200 = E200t - 33

Otherwise E200 = 0

If E300

t < 72, then E300 = E300t - 72

If E300

t > 94 and 79.75 + 0.3846 x AROt > 94, then

 E300 = E300

t - 94

Otherwise E300 = 0

If ARO

t < 18, then ARO = AROt - 18

If ARO

t > 46, then ARO = AROt - 46

Otherwise ARO = 0

The extrapolated performance equations and the associated

conditions for NOx are derived in an analogous manner to the

equations and conditions for VOC. The results for Phase I and

Phase II are shown below:

Phase I NOx extrapolation equation:

NOx(t) = 100% x 0.82 x [(exp(c(et))/1.6437758) - 1] +

100% x 0.18 x [(exp(d(et))/0.8353577) - 1] +

100% x 0.82 x [exp(c(et))/1.6437758] x 

{[-0.000001326 x SUL

et + 0.00069205] x SUL +

 [-0.0002381 x ARO

et + 0.0083632] x ARO +

 [0.00073304 x OLE

et - 0.0027735] x OLE} +

100% x 0.18 x [exp(d(et))/0.8353577] x 

{[-0.000159902 x ARO

et + 0.007097005] x ARO +

 [0.000732 x OLE

et - 0.0027603] x OLE}

c = (0.0018571 x Oxygen) + (0.0006921 x Sulfur) +

 (0.0090744 x RVP) + (0.0009310 x E200) +

 (0.000846 x E300) + (0.0083632 x Aromatics) +

 (-0.002774 x Olefins) + (-0.000000663 x Sulfur2) +

 (-0.000119 x Aromatics2) + (0.0003665 x Olefins2)

d = (-0.00913 x Oxygen) + (0.000252 x Sulfur) +

 (-0.01397 x RVP) + (0.000931 x E200) +

 (-0.00401 x E300) + (0.007097 x Aromatics) +

 (-0.00276 x Olefins) + (-0.00007995 x Aromatics2) +

 (0.0003665 x Olefins2)

Phase I Conditions for extrapolating exhaust NOx:

If SUL

t < 10, then SUL = SULt - 10
215

If SUL

t > 450, then SUL = SULt - 450

Otherwise SUL = 0

If ARO

t < 18, then ARO = AROt - 18

Otherwise ARO = 0

If OLE

t > 19, then OLE = OLEt - 19

Otherwise OLE = 0

Phase II NOx extrapolation equation:

NOx(t) = 100% x 0.738 x [(exp(c(et))/1.6437758) - 1] +

100% x 0.262 x [(exp(d(et))/0.8353577) - 1] +

100% x 0.738 x [exp(c(et))/1.6437758] x 

{[-0.000001326 x SUL

et + 0.00069205] x SUL +

 [-0.0002381 x ARO

et + 0.0083632] x ARO +

 [0.00073304 x OLE

et - 0.0027735] x OLE} +

100% x 0.262 x [exp(d(et))/0.8353577] x 

{[-0.000159902 x ARO

et + 0.007097005] x ARO +

 [0.000732 x OLE

et - 0.0027603] x OLE}

c = (0.0018571 x Oxygen) + (0.0006921 x Sulfur) +

 (0.0090744 x RVP) + (0.0009310 x E200) +

 (0.0008460 x E300) + (0.0083632 x Aromatics) +

 (-0.002774 x Olefins) + (-0.000000663 x Sulfur2) +

 (-0.000119 x Aromatics2) + (0.0003665 x Olefins2)

d = (-0.00913 x Oxygen) + (0.000252 x Sulfur) +

 (-0.01397 x RVP) + (0.000931 x E200) +

 (-0.00401 x E300) + (0.007097 x Aromatics) +

 (-0.00276 x Olefins) + (-0.00007995 x Aromatics2) +

 (0.0003665 x Olefins2)

Phase II Conditions for extrapolating exhaust NOx:

If SUL

t < 10, then SUL = SULt - 10

If SUL

t > 450, then SUL = SULt - 450

Otherwise SUL = 0

If ARO

t < 18, then ARO = AROt - 18

Otherwise ARO = 0

If OLE

t > 19, then OLE = OLEt - 19

Otherwise OLE = 0

6. Response to Comments

A number of comments were received concerning the fuel

parameter ranges that limit the use of the Complex Model which can

be summarized as follows:
216

 The limits on the use of the Complex Model must allow a

refiner as much flexibility as possible.

 The limits on the use of the Complex Model cannot

preclude legal 1990 fuels or California Phase II

reformulated gasolines.

Some commenters also suggested that all limits on the use of the

Complex Model should be removed. As described below, the Agency

determined that such limits were both necessary and expedient.

The Agency has recognized the need for flexibility in the

reformulated gasoline and anti-dumping programs. This need for

flexibility was one of the primary reasons for developing an

empirical model that estimates vehicle emissions given the

composition of a given fuel. Thus the Simple and Complex models

represent a strategy for liberating refiners from the burden of

testing every batch of fuel to determine if it complies with the

emission performance standards. In this capacity, empirical

models offer an increase in flexibility over testing.

However, implicit in the development of an empirical model

for vehicle emissions are limits to its applicability. These

limitations arise from the limitations of the database used to

develop the model. The most important ramification of the

limitations of the Complex Model database is that the model cannot

be applied reliably to all possible fuel compositions. Since the

models are based on test data gathered for a limited range of fuel

parameter levels, it would be inappropriate for the Agency to

assume that the Complex Model can be applied without restriction

to all possible fuels. Further discussion of the limitations of

the Complex Model and the criteria used to establish range limits

can be found in Section D.

The Agency has made every attempt to set fuel parameter range

limits that do not overly restrict the range of gasolines that can

be evaluated with the Complex Model. However, the wide variation

in the composition of 1990 gasolines makes it impossible to

designate range limits that simultaneously cover all possible 1990

gasolines and all possible reformulated gasolines while

simultaneously ensuring the reliability of the Complex Model's

emission performance predictions. Thus the Agency chose to

constrain the range of gasolines covered by the Complex Model in

order to ensure the reliability of the model within those limits. 

As discussed previously, EPA specified less restrictive limits on

the use of the model for anti-dumping purposes than for

reformulated gasoline purposes. The Agency believes that

extension of the valid range of the model beyond these limits

would be inappropriate given the limitations of the underlying

database. It should be noted that the limits imposed on the range

of gasolines which can be evaluated using the Complex Model do not

impose limits on the range of gasolines which may be produced and
217

sold under either the reformulated gasoline or anti-dumping

programs. The Complex Model may be augmented through vehicle

testing. In the case of the anti-dumping program, fuel suppliers

could continue to make a fuel identical to their 1990 baseline

fuel; alternatively, they could seek approval to produce and sell

fuels that are no worse (based on the emission performance trends

present in the Complex Model) for each parameter.

Commenters expressed general support for the extrapolation

methodology proposed by the Agency. However, the increased

complexity in the Complex Model equations introduced through

extrapolation led some commenters to suggest that the regression

curve approach should be used in all but the most extreme cases

(see Section D.3 above for details on the various extrapolation

approaches). The Agency has determined that the final

extrapolations presented in this section provide the most

appropriate approach to contending with the limitations of the

Complex Model database for the following reasons:

 Applying linear extrapolation to all second order terms

avoids arbitrary determination on the part of the Agency

as to which terms exhibit unacceptably "extreme"

behavior.

 The limitations of the database, as defined by the data

core, are used to determine the points at which

extrapolation should begin. Thus the definition of the

data core provides an appropriate basis for defining

points at which extrapolation should begin.

Some commenters also provided suggestions for the manner in which

to extrapolate specific model equations. For the most part, these

suggestions applied to the various Complex Model options which

were not adopted for the final Complex Model. The Agency has

taken the specific extrapolation suggestions that applied to the

final Complex Model equations into consideration.

E. Use of the Complex Model Under Non-Summer Conditions

While the VOC performance standard for reformulated gasolines

applies only in the summer, the toxics and NOx requirements apply

year-round. Similarly, the exhaust toxics and NOx requirements of

the anti-dumping program apply year-round. EPA therefore

recognizes that the complex model must be extended to cover

typical winter fuels in order to estimate the exhaust toxics and

NOx emission performance of gasolines during the winter months. 

Modeling winter emissions performance presents a number of unique

difficulties. These difficulties include:

 The data sources described in Section A.1 provide data

on emissions performances only under summer conditions.
218

 The wide range of temperatures encountered during the

winter season (September 16th to March 30th) in the

various geographical areas (north vs. south) within the

United States would make emissions testing and modeling

under winter conditions more difficult. The range of

temperatures during the summer season tend to be

considerably more uniform, particularly within each VOC

Control Region.

 The RVP levels of fuels included in the current complex

model database range from 7 to 10 psi, while winter

fuels tend to have RVP levels in the range of 11 to 13

psi.

For these reasons, the complex model described in Section A cannot

be used directly to evaluate fuels with typical winter RVP levels. 

The method chosen by EPA for extending the complex model for

determining performance during wintertime scenarios is described

below for both exhaust as well non-exhaust emissions. 

1. Non-Summer Exhaust Model

a. Winter Engine Operation

The effect of fuel modifications on exhaust VOC and NOx

emissions are thought to be minimally affected by the cooler

ambient wintertime temperatures. Auto/Oil data [A-92-12 Docket

submittal #II-G-1, December 1990] has shown that most fuel

parameters affect emissions in two ways as the fuel is burned in

the engine:

 Fuel properties affect the quantity of exhaust emissions

generated in the engine itself (i.e., an "engine-out"

effect).

 Fuel characteristics affect the efficiency of the

catalyst in reducing the level of emissions leaving the

vehicle (i.e., a "catalyst" effect).

Most fuel parameters affect both engine-out emissions and catalyst

efficiency. Fuel sulfur content is the one fuel parameter which

is believed to have only a catalyst effect. It is expected that

fuels will encounter almost identical conditions in the combustion

chamber (resulting in almost identical engine-out effects) and the

catalyst (resulting in almost identical catalyst effects) during

most of the driving cycle regardless of the ambient temperature. 

The only differences between summer and winter engine and catalyst

operating conditions are:

 Slightly cooler engine temperatures due to increased

heat transfer rates from the engine to the cooler winter

air.
219

 Slightly longer warm-up times for engine and catalyst

due to the thermal inertia of the colder engine block,

coolant, and catalyst as well as the increased heat

transfer rates to the ambient environment during warmup.

 Slightly longer open-loop engine operation resulting

from the longer warm-up time.

 Lower vapor generation rates and reduced canister

loading due to lower fuel temperatures and lower ambient

air temperatures.

Except for the last point, these differences are not expected to

heavily influence the emission effects of most fuel parameters in

winter when compared summer conditions. Hence EPA has concluded

that most fuel modifications should have similar exhaust emission

effects in both summer and winter, despite potentially large

differences in ambient temperatures during the two seasons.

This conclusion is supported by data available from the

Auto/Oil studies which has shown that the effect of most fuel

modifications on exhaust emissions is similar regardless of

temperature. Bag1 data taken on the FTP reflects measurements

taken during the cold phase of engine start-up while bag3 data

reflects measurements taken after the engine heats up to running

conditions. Thus, a comparison of the effects of fuel

modifications on exhaust emission data from bag1 and bag3 should

serve as an indicator of how temperature effects emissions. Data

from Auto/Oil [A-92-12 Docket submittal #II-G-1, December 1990]

has shown many fuel modifications to result in similar exhaust

emission effects in both bag1 and bag3. While the Auto/Oil data

confirms EPA's expectation that many fuel modifications would have

similar effects under summer and winter conditions, the amount of

data provided by the Auto/Oil study is too limited to form the

basis of a separate winter model.

EPA does not believe that this conclusion can be applied to

RVP, however. As indicated previously, vapor generation rates

under summer conditions are substantially higher than under winter

conditions for fuels with identical RVP levels. EPA believes that

RVP's effects on emissions are due in part to RVP's impact on

actual vapor generation in the engine. However, the Agency

believes that RVP's primary effect on emissions arise due to the

loading and subsequent purging to the engine of the evaporative

emissions control canister. Both phenomena are highly

temperature-sensitive; fuels with identical RVP levels generate

far more vapor and produce far greater canister loading under

summer conditions than under winter conditions. Vapor generation

and canister loading are a function of a fuel's true vapor

pressure, which increases as temperature increases in accordance

with basic principles of gas-phase chemistry. Hence EPA is not
220

confident that RVP effects estimated from test data gathered under

summer conditions can be used to estimate RVP effects under winter

conditions.

b. Winter Baselines and Fuels

The winter baseline emissions of VOC and NOx are derived

directly from the appropriate MOBILE models as outlined in Section

III.B. Winter baseline toxic emissions are derived from the

Complex Model database and the Complex Model itself. All winter

baseline emissions are determined using the following fuel

parameters, as discussed further in Section III.B:

Table IV-49 

Baseline Fuel Parameters Used in Determining

Winter Baseline Emissions

Fuel Parameter Winter Baseline Value

Oxygen

(weight percent)

0.00

Sulfur

(ppmW)

338.0

RVP

(psi)

11.5

E200

(percent)

50.0

E300

(percent)

83.0

Aromatics

(volume percent)

26.4

Olefins

(volume percent)

11.9

Benzene

(volume percent)

1.64

Winter fuel characteristics are comparable to summer fuel

characteristics except for Reid Vapor Pressure (RVP). The higher

winter RVP levels are needed to maintain similar actual vapor

generation rates under winter despite the generally lower fuel

temperatures under such conditions (particularly during engine

warm-up, when emissions are highest). As discussed previously,

the RVP levels of fuels included in the exhaust complex model

database ranged from 6.5 to 10 psi, while winter fuels tend to

have RVP levels in the 10-14 psi range. RVP's impact on canister

loading and purge rates are thought to be the primary causes of

its effect on exhaust emissions. Since data on the emission

effects of fuels with winter RVP levels under winter conditions
221

are extremely limited, EPA has not been able to model the effects

of winter RVP levels on exhaust emissions.

c. EPA Solution

Based on the points discussed in the previous section, EPA

proposed in the February 1993 NPRM that for purposes of evaluating

exhaust emission effects using the complex model, the RVP of

winter fuels be set at the summer statutory baseline RVP value. 

EPA did not receive comments opposing this approach, which the

Agency believes avoids the use of the model to make unfounded

predictions. EPA has incorporated this approach in the final

reformulated gasoline and anti-dumping requirements, which has the

effect of embedding into the Complex Model the assumption that the

RVP level of winter gasolines has no effect on NOx or exhaust

toxic emissions. Thus, to evaluate wintertime fuels using the

complex model, an RVP value equal to that of summer baseline

gasoline (8.7 psi) must be used instead of the fuel's actual RVP. 

This procedure effectively removes the contribution of RVP to

winter exhaust emissions. By removing any emissions-related

incentives to alter winter RVP levels from 1990 levels, this

approach also reduces the likelihood that in-use winter RVP

levels, or the associated emissions, will change from their 1990

levels. To the extent that such emissions do not change, the

approach outlined above becomes even more appropriate.

2. Non-Summer Non-Exhaust Model

a. NPRM Approach and Comments

In all its prior proposals, the Agency had proposed that

winter nonexhaust emissions, including winter nonexhaust benzene

emissions, be set equal to zero. EPA received a number of

comments requesting that both baseline emissions and the

nonexhaust toxics model include winter nonexhaust benzene

emissions.

These requests were based on the fact that the year-round

benzene limits would result in reduced nonexhaust benzene

emissions in the winter months, if such emissions existed. EPA

has evaluated this claim, taking into account winter temperature

ranges and the effects of different inspections and maintenance

programs on such emissions. EPA believes that this claim is

valid, since winter non exhaust emissions (including nonexhaust

benzene emissions) are unlikely to be zero under all winter

temperature ranges.

In the past, the absence of sufficient data on nonexhaust

emissions under winter temperature conditions has prevented EPA

from developing accurate models of winter nonexhaust emissions. 

The commenters provided a limited amount of data on winter
222

nonexhaust emissions to support their claim. However, the data

submitted was found to contain the following limitations:

 The data submitted in support of this claim were based

on measurements of nonexhaust emissions from vehicles

with very low nonexhaust emissions that are not

representative of actual in-use vehicles.

 The chemical composition of the measured nonexhaust

emissions were characteristic of resting losses rather

than diurnal, hot soak or running loss emissions. 

Resting losses are not included in EPA's baseline

emission estimates, so the Agency does not consider it

fair to include resting losses in its nonexhaust

emission models. Speciation of the nonexhaust emissions

also revealed the presence of compounds not found in

gasoline, suggesting that non-fuel sources of emissions

were present.

 No data were submitted on nonexhaust benzene emissions

from fail vehicles under winter conditions. Since

nonexhaust benzene emissions from such vehicles will

comprise a large portion of winter nonexhaust benzene

emissions, EPA is concerned that a model based only on

pass vehicles would not provide accurate estimates of

winter nonexhaust benzene emissions.

b. EPA Decision

For the reasons discussed in the previous section, the data

submitted by the commenters on winter nonexhaust emissions cannot

be used to evaluate wintertime baseline emissions. Thus, EPA is

promulgating models which assume that winter nonexhaust emissions,

including winter nonexhaust benzene emissions, be considered zero. 

However, given the merit of the claims made by the commenters, EPA

will consider including a model of winter benzene nonexhaust

emissions in the complex model in the future when sufficient

reliable data become available.

F. Behavior of Complete Complex Model

1. Fungibility

As the gasoline distribution system currently operates, all

gasoline is fungible. Fungibility means that a given batch of

gasoline is exchangeable and/or mixable with any other batch of

gasoline at any point between the refinery gate and a vehicle's
 48 Some segregation of conventional gasolines already occurs based on fuel

RVP, octane rating, and/or oxygenate type and content specifications.

223

fuel tank48. Fungibility simplifies gasoline distribution because

it permits gasoline to be stored, transported, and sold without

the constraints and costs associated with segregating every batch

of gasoline from every other batch. Thus gasoline is always

gasoline regardless of whether it derives from a mixture of other

gasolines.

Reformulated gasoline (RFG) will be distributed through the

same network of pipelines, trucks, and terminals that is currently

used for conventional gasoline. However, because RFG is produced

to very different specifications than conventional gasoline, the

production of RFG potentially will have significant impacts on the

fungibility of the gasoline distribution system. These impacts

fall into two categories:

1) The difference in production specifications for

conventional gasoline and RFG require that all

conventional gasoline must be segregated from all

RFG at all times.

2) The compliance of a given batch of RFG with the

emission standards is determined through the

Complex Model which, in general, is not linear. 

The result of this nonlinearity is that the

emissions performance of a mixture of two complying

RFGs cannot be easily inferred from the

performances of the individual fuels. It may be

possible, therefore, that the mixture of two

complying RFGs will yield a fuel that is not a

complying RFG, according to performance estimates

provided by the Complex Model.

The first impact on fungibility, that of segregation of all

RFG from all conventional gasoline, cannot be compromised. The

compliance of RFG is determined through evaluation of its fuel

parameters with the Complex Model. If a batch of RFG were to be

mixed with a batch of conventional gasoline, the value of its fuel

parameters could change dramatically. The "mixed" RFG would then

require re-evaluation with the Complex Model, and would be

unlikely to comply with the requirements of the reformulated

gasoline program. To assure that conventional and reformulated

gasoline is not mixed, conventional gasoline is required to

contain a chemical marker. This marker is not permitted to be

present in gasoline sold as reformulated gasoline.

The second impact on fungibility requires both elaboration

and analysis. The practical and financial requirement that RFG be
224

fungible throughout its distribution system requires that RFG

batches be allowed to mix with one another in any proportion and

at any point between the refinery gate and a vehicle's fuel tank

(in practice, the different standards and emission models

applicable in VOC Control Regions 1 and 2 require RFG for each

region to be segregated). Thus the requirement for a fungible

distribution system translates into a requirement that a mixture

of two complying RFGs must be a complying RFG. Since RFG

compliance is determined through the Complex Model which is not

linear, it cannot be assumed that mixtures of complying

reformulated gasolines are themselves complying reformulated

gasolines. To determine the degree to which certified

reformulated gasolines can be mixed and still remain in

compliance, an analysis of the behavior of the Complex Model was

conducted.

The nonlinearity in the Complex Model is due to the existence

of second-order terms and the exponential form of the regression

equations. This nonlinearity means that emissions from a mixture

of two fuels will differ from the weighted average of the two

fuels' individual emissions. However, this mixing may be either

beneficial or detrimental to an RFG mixture's compliance status. 

In other words, the Complex Model may predict any of the following

for a mixture of two complying RFGs:

1) The emissions performance of the mixture equals the

weighted average of the two original fuels'

emissions performances.

2) The emissions performance of the mixture is better

than the weighted average of the two original

fuels' emissions performances.

3) The emissions performance of the mixture is worse

than the weighted average of the two original

fuels' emissions performances, but the mixture

remains a complying RFG.

4) The emissions performance of the mixture is worse

than the weighted average of the two original

fuels' emissions performances, and the mixture

becomes a non-complying RFG.

Fungibility problems arise only for case (4).

The fungibility analysis involved evaluating the performance

of thousands of randomly generated fuels with the Complex Model. 

Emission estimates for total VOC, NOx, and total toxics were

calculated to determine the frequency of occasions in which the

mixture of two complying RFGs produced a non-complying RFG. The

analysis also provided information on the frequency of occasions

in which a mixture of two complying RFGs performed more poorly
 49 Performance is here defined as the percent change in emissions of a

target fuel as compared to a baseline fuel

225

than could be inferred from the two original fuels, but

nevertheless remained a certifiable RFG (case 3). The steps in

the analysis can be summarized as follows:

1. Create 24,000 fuels distributed randomly throughout the

fuels space defined by the valid range of the

extrapolated Complex Model.

2. Retain all "certifiable" and realistic fuels based on

VOC performances49 of -15.0 to -17.0 percent, NOx

performances of 0.0 to -2.0 percent, and toxics

performances of -15.0 to -30.0 percent. Fuels with

emission performance levels beyond these ranges are

either not permissible under a per-gallon compliance

scenario or are unrealistically low-emitting. Including

such fuels makes fungibility problems (in which the

mixture does not comply with the per-gallon

requirements) even less likely.

3. Generate 50:50 mixtures of pairs of fuels from among

those retained from step 2 by averaging the fuel

parameter values from the two contributing fuels.

4. Determine the Complex Model performance of the mixtures

generated in step 3 for VOC, NOx, and toxics.

5. Calculate the "Fungibility Effect" by subtracting the

average performance of the two constituent fuels from

the performance of the mixture (the average performance

of the two constituent fuels is equivalent to the

weighted average of the performances of the two fuels

mixed in a 50:50 ratio):

Fungibility Effect = M - [(0.5 x A) + (0.5 x B)]

M = Performance of the mixture (% change from baseline)

A = Performance of the first qualifying RFG (% change

from baseline)

B = Performance of the second qualifying RFG (% change

from baseline)

Fungibility effects were determined separately for each

pollutant. Note that negative fungibility effects are

beneficial, i.e. negative fungibility effects indicate

that emissions from the mixture are lower than would

have been expected based on the performance of the two

original fuels.
226

6. Examine the average fungibility effect to determine the

impact of fuel mixing on in-use compliance and the

potential application of ratchets to the applicable

emission standards.

7. Examine fuels for which the fungibility effect was

positive (i.e., detrimental) to identify situations that

might result in the issuance of a Notice of Violation.

8. Determine cases in which a detrimental fungibility

effect caused a mixture of two complying fuels to be

non-complying.

The scenario under which the analysis was performed was

designed to amplify any fungibility problems that might exist. 

For this reason, a per-gallon scenario with tight controls on the

initial performance estimates was assumed, along with a 50:50 fuel

mixing ratio. Averaging scenarios are less binding since NOVs can

be issued only for violations of the per-gallon minimum

performance requirements, and because the wide range of fuels

likely to exist under averaging are unlikely to consist only of

fuels with unfavorable fungibility effects. The 50:50 mixing

ratio tends to create the largest fungibility effects, since any

nonlinear effects are most noticeable at this ratio. Fungibility

effects and problems are independent of the program phase, area

class, and season assumed for the analysis, since the percentage

change estimates for the original fuels and mixtures are largely

independent of these conditions. Oxygenate type affects emissions

only in the case of the aldehydes and nonexhaust benzene, since

such effects are linear, the analysis is independent of oxygenate

type. The scenario analyzed below was based on Phase I summer

requirements in Class C areas and used MTBE as the oxygenate. The

results of the analysis are shown in Figures IV-2 through IV-7,

and are summarized in Table IV-50.
227

Figures IV-2 and IV-3: Results of VOC Fungibility Analysis
228

Figures IV-4 and IV-5: Results of NOx Fungibility Analysis
229

Figures IV-6 and IV-7: Results of Toxics Fungibility Analysis
230

Table IV-50 

Summary of Results of Fungibility Analysis

Total VOC NOx Total toxics

Performance of

contributing fuels

Minimum

Maximum

Average

-16.97

-15.00

-16.01

-1.98

 0.00

-0.93

-29.99

-15.49

-25.06

Performance of mixtures

Minimum

Maximum

Average

-17.77

-15.20

-16.42

-3.20

 0.43

-0.99

-29.70

-20.06

-25.40

Fungibility effects

Minimum

Maximum

Average

- 1.81

 1.01

- 0.42

-1.68

 0.86

-0.04

- 1.19

 0.02

- 0.35

A number of conclusions can be drawn from the values in Table

IV-50. First, the minimum and maximum performances of the

contributing fuels fall within the performance ranges given in

step 2, since only complying and realistic fuels were retained

from the 24,000 randomly generated fuels. Second, the average

performance of the mixtures is better than the average performance

of the contibuting fuels for total VOC, NOx, and total toxics,

which indicates that, on average, mixing fuels tends to result in

beneficial fungibility effects. Other conclusions are discussed

separately for VOC, NOx, and toxics:

Total VOC

The average VOC fungibility effect is beneficial, although a

small percentage of such effects are detrimental. However, in no

case does a fungibility effect result in a mixture of two fuels

having emission reductions of less than 15.0%. Thus this analysis

shows that although some mixtures of pairs of fuels will have

higher emissions than would be implied by the performances of the

two constituent fuels, these higher emissions will never result in

a mixture of two complying fuels being in non-compliance with the

standards for RFG. This conclusion also applies to compliance on

average. When complying on average, the performance of individual

fuel blends will cover a larger range than when complying on a

per-gallon basis. EPA has found that the distribution of VOC

fungibility effects becomes more beneficial as the range of

performances increases. In addition, EPA found that detrimental

fungibility effects are not large enough to result in violations
231

of the per-gallon minimum performance standards under averaging. 

Finally, the compliance margin imposed under averaging assures

that fuels complying on average will result in average VOC

performances that exceed the per-gallon standards applicable in

each Phase.

NOx

The average NOx fungibility effect is beneficial, although a

significant percentage of mixtures resulted in detrimental

fungibility effects. EPA found that the vast majority of mixtures

with detrimental effects comply with the program's NOx

requirements. Of the 124 fuel pairs that survived the screening

process of step 2, only two pairs resulted in detrimental

fungibility effects that also resulted in NOx noncompliance for

the mixture. These two fuel pairs, their mixtures, and the

Complex Model performances for each fuel are shown in Table IV-51.

Table IV-51 

Fuels Resulting in Non-complying Mixtures

Fuel

#1

Fuel

#2

#1 +

#2

Fuel

#3

Fuel

#4

#3 + #4

Oxygen

Sulfur

RVP

E200

E300

Aromatics

Olefins

Benzene

3.19

172

8.17

38.4

91.5

44.2

17.4

0.371

2.21

399

8.04

35.2

93.4

24.5

9.15

0.843

2.70

285

8.11

36.8

92.4

34.4

13.3

0.607

3.29

420

8.14

45.9

90.4

22.2

9.66

0.968

2.48

291

8.08

57.0

79.3

35.6

7.63

0.739

2.88

356

8.11

51.5

84.9

28.9

8.65

0.853

Performance:

Total VOC

NOx

Total Toxics

-15.26

- 0.22

-27.60

-15.49

- 0.99

-27.37

-15.37

 0.22

-27.79

-15.50

- 0.06

-29.55

-15.07

- 0.46

-26.85

-16.24

 0.44

-28.38

Such results show that the mixture of two complying RFGs can

result in a non-complying gasoline for NOx. However, the

following points indicate that such concerns are not warranted:

 The scenario under which the analysis was carried out was

designed to amplify fungibility effects and any associated

fungibility problems. Under actual in-use conditions, these

effects would be substantially smaller or nonexistent since

50:50 ratios of the two fuels are unlikely and since fuels

other than the fuels presented above are likely to be mixed. 

As more fuels are mixed, fungibility effects will tend to
232

reflect the average fungibility effects presented in Figures

IV-2 through IV-7.

 None of the four constituent fuels in Table IV-51 are

representative of in-use reformulated gasolines:

• Low sulfur does not typically accompany high olefins,

and vice-versa, as in Fuels #1 and #3.

• Low E200 does not typically accompany high E300 as in

Fuels #1, #2, and #3.

• Ultra-high octane fuels, such as Fuel #1, will most

likely not play a significant role in the reformulated

gasoline program. In addition, such fuels are unlikely

to be mixed with low-octane fuels such as fuel #2 due to

the price premium commanded by high-octane fuels and the

cost of the additional oxygenate.

 Very few, if any, refiners will produce RFGs whose

performances fall as close to the standards as those in Table

IV-51 do. To assure compliance with the per-gallon standards

given the uncertainties associated with measuring fuel

parameter levels, fuel suppliers are likely to maintain

compliance margins.

 The oxygenate contents are not at the levels commonly

associated with MTBE or ethanol fuels. In fact, fuels #1 and

#3 can be produced only with ethanol as the oxygenate.

Thus under in-use conditions, EPA does not anticipate any NOx

fungibility problems to arise under per-gallon compliance with the

"no NOx increase" provisions of the program. As discussed

previously, fungibility effects under averaging are likely to be

more beneficial than under per-gallon compliance since the range

of performances of fuels produced under averaging will be wider

than the range of performances of fuels produced under per-gallon

compliance. In addition, EPA found that detrimental fungibility

effects are not large enough to result in violations of the pergallon minimum performance standards under averaging. Finally,

the compliance margin imposed under averaging assures that fuels

complying on average will result in average NOx performances that

exceed the per-gallon standards applicable in each Phase.

Total Toxics

All exhaust toxics, except for POM, have strictly linear

relationships with all fuel parameters, and therefore would not be

expected to demonstrate either beneficial or detrimental
 50 Since the exhaust models are in the form of exponentials of

polynomials, there is in fact some curvature to "strictly linear" relationships

that can contribute to fungibility effects. However, the nature of an

exponential function is such that only beneficial effects would be exhibited, and

the relatively small order of magnitude of the independent variables (fuel

parameters) is such that the exhibited effects would be very small.

233

fungibility effects.50 The non-exhaust benzene models, however,

include a negatively squared relationship with RVP, and therefore

would be expected to exhibit beneficial fungibility effects at all

times. These facts are confirmed in the results for total toxics,

as the fungibility effects are almost always beneficial (though

POM could contribute a small detrimental fungibility effect). 

Thus it is apparent that all 50:50 mixtures of complying and

realistic fuel pairs also will comply and in fact will almost

always have lower emissions of toxics than the weighted average of

the contributing fuels' toxics emissions.

2. Predictability and Validation of Exhaust Complex Models

As discussed in the February 1993 NPRM and in previous EPA

submittals to the docket, there are two ways by which the accuracy

and/or precision of models can be investigated. One way is to

inspect the effect of changing one fuel parameter at a time on

exhaust emissions and compare the effect to directional effects

demonstrated by specific studies in the database. Another way is

to compare model predictions on vehicles and fuels from specific

test programs to measured emission effects of fuel modifications. 

Both of these methods will be discussed in this section.

a. Parametric Performance of Complex Models

Table IV-52 summarizes the effects of single parameter fuel

modifications on exhaust emissions as predicted by the final

(simplified) Phase I Complex Models (see Section A.9) for the 1990

in-use fleet. With the exception of the poorly-understood effects

of E200 fuel modifications on exhaust NOx and VOC emissions, the

emission effects predicted by the Complex Models for exhaust VOC

and NOx are directionally consistent with the effects predicted by

the Auto/Oil and ATL studies [See A-92-12 Docket submittals II-G-1

through II-G-5, December 1990; II-B-12, February 1993 and II-B-14,

February 1993]. Since emissions data from the Auto/Oil and ATL

studies comprise over 50% of the emissions database, the Complex

Models appear to demonstrate behavior that is directionally

consistent with the data in the Complex Model database. As

discussed in Sections III and IV.A, there are far fewer data on
234

toxic emissions than on VOC and NOx emissions. Hence the models'

predictions for toxic emissions behavior are expected to be less

accurate than the models' predictions of VOC and NOx emission

behavior. However, the effects of fuel modifications on exhaust

toxic emissions shown in Table IV-52 below are also, for the most

part, directionally consistent with the studies that measured and

quantified the effects of fuel parameter changes on toxic exhaust

emissions [See A-92-12 Docket submittals II-G-1 through II-G-5,

December 1990; II-B-12, February 1993 and II-B-14, February 1993].

Table IV-52

Phase I, Summer, In-Use Exhaust Complex Model Predictions

(all numbers are percent change in emissions from CAAB fuel)

Fuel

Parameter

Changed

VOC

&

POM

NOx Benzene Butadiene AcetaldehydeFormaldehyde

Oxygen

0->2 wt%

-0.72 -0.02 -8.39 -5.49 -6.07* +9.68*

Sulfur

339->139 ppm

-4.63 -6.81 -9.19 -1.59 -5.12 ---

RVP

8.7->7.7 psi

-3.52 -0.49 --- --- -2.03 ---

E200

41->51 %

-4.11 +0.94 -1.73 -7.02 --- ---

E300

83->87.3 %

-2.64 -0.01 +2.58 -4.85 -5.10 -4.30

Aromatics

32->27 vol%

-1.94 -0.76 -9.23 +2.02 +2.81 +3.65

Olefins

9.2->4.2 vol%

+1.44 -1.06 --- -16.3 --- +8.15

Benzene

1.53->0.95

vol%

--- --- -12.1 --- --- ---

*

 Calculated assuming oxygen in the form of MTBE

b. Validation of Complex Models

Because of the wide range of fuel parameters tested and the

large number of vehicles tested in both the normal and higher

emitter categories, EPA's ATL-I and ATL-II programs were chosen

for comparison to model predictions of VOC and NOx emissions. 

Selected fuels with a wide range of different fuel properties,

emissions effects, and oxygenate types) from the various Auto/Oil

programs were also chosen for comparison to the exhaust Complex

Models developed above. The fuels from the different programs and

their properties are summarized below in Tables IV-53, IV-54 and

IV-55.
235

Table IV-53

ATL-I Fuels Used for Validation of Complex Model

Fuel Oxygen

(wt %)

Sulfur

(ppmw)

RVP

(psi)

E200

(%)

E300

(%)

Arom

(v %)

Olef

(v %)

Benz

(v %)

C 2.0

(MTBE)

371 8.3 57.1 85.0 25.4 6.8 1.0

D 2.0

(MTBE)

364 7.6 54.1 83.8 25.8 6.4 1.0

E 2.0

(MTBE)

355 8.5 62.2 92.5 23.6 5.9 0.9

F 2.0

(MTBE)

112 8.3 54.8 83.9 24.2 6.4 0.9

G 2.0

(MTBE)

133 7.7 61.8 92.3 23.8 5.6 1.0

H 3.5

(ETOH)

353 8.0 57.8 84.7 27.3 7.0 1.0

Table IV-54

ATL-II Fuels Used for Validation of Complex Model

Fuel Oxygen

(wt %)

Sulfur

(ppmw)

RVP

(psi)

E200

(%)

E300

(%)

Arom

(v %)

Olef

(v %)

Benz

(v %)

K 2.0

(MTBE)

311 7.5 48.9 80.0 28.9 7.0 0.8

L 2.0

(MTBE)

307 7.7 52.3 81.8 26.4 7.0 0.8

M 2.0

(MTBE)

345 7.3 42.6 81.7 25.7 7.3 0.9

N 2.0

(MTBE)

337 7.7 52.4 76.2 23.1 7.8 0.6

P 2.0

(MTBE)

288 7.9 53.5 83.7 26.8 9.8 0.8

R 2.0

(MTBE)

320 7.9 53.6 81.1 25.0 7.4 0.6

S 2.0

(MTBE)

327 7.5 52.4 81.6 23.3 1.1 0.5

T 2.0

(MTBE)

59 7.6 52.9 81.4 22.8 1.3 0.5

U 2.0

(MTBE)

66 6.4 52.6 81.3 23.5 1.4 0.5

V 2.0

(MTBE)

31 6.2 50.5 90.8 21.7 2.8 0.8
236

Table IV-55

Auto/Oil Fuels Used for Validation of Complex Model

Fuel Oxygen

(wt %)

Sulfur

(ppmw)

RVP

(psi)

E200

(%)

E300

(%)

Arom

(v %)

Olef

(v %)

Benz

(v %)

H

(AMOT)

2.7

(MTBE)

313 8.5 65.3 92.0 20.2 20.2 1.52

O

(AMOT)

2.7

(MTBE)

288 8.6 47.9 91.9 46.7 19.3 1.38

R3A

(HC/A)

2.0

(MTBE)

90 8.48 46.2 87.1 28.2 14.5 0.62

MM

(RVP)

2.7

(MTBE)

345 8.0 67.4 91.3 22.2 5.4 1.41

N2

(RVP)

2.7

(MTBE)

313 8.8 65.7 91.3 22.5 4.7 1.31

NN

(RVP)

2.7

(ETBE)

313 8.0 50.7 92.6 21.2 3.8 1.50

T

(RVP)

3.5

(ETOH)

246 9.3 57.4 93.1 18.1 3.6 1.35

The exhaust emissions data (after converting total

hydrocarbons to non-methane hydrocarbons in order to facilitate

direct comparisons to percent change predictions from the Complex

Models) from these programs were placed in appropriate technology

groups and emitter classes and re-weighted according to the

revised weighting factors listed in Section III.B.4 for summer

Phase II VOC and NOx emissions. Shown in Table IV-56 is a direct

comparison of data to predicted exhaust emissions from the final

Complex Models for VOC and NOx. The percent change in emissions

shown in Table IV-56 for the data as well as predictions by the

model (which are in bold type) should be directly comparable since

all weightings and classifications used were identical.
237

Table IV-56

A Comparison of Data to Complex Model Predictions

Study/Fuel percent change in VOC

emissions from base fuel

percent change in NOx

emissions from base fuel

NORMAL

EMITTERS

HIGHER

EMITTERS

NORMAL

EMITTERS

HIGHER

EMITTERS

ATL-I/C -10.4/-8.44 -13.3/-9.4 -2.5/+1.5 -2.4/-1.4

ATL-I/D -13.4/-8.77 -10.8/-11.3 -2.9/+0.35 +1.5/-0.4

ATL-I/E -14.2/-11.6 -7.90/-8.7 -3.7/+1.8 -9.9/-5.2

ATL-I/F -14.5/-18.9 -14.7/-8.0 -4.8/-8.4 -11.5/-7.8

ATL-I/G -17.8/-22.8 -11.4/-10.5 -8.5/-6.8 -10.2/-9.3

ATL-I/H -9.4/-10.0 -20.3/-10.4 +5.7/+1.6 +3.5/-2.0

ATL-II/K -4.6/-3.5 -1.7/-7.6 -0.36/-0.28 +5.9/+0.2

ATL-II/L -10.2/-7.3 -5.3/-9.4 -1.3/-0.19 +2.6/-1.2

ATL-II/M -5.5/-2.9 -3.1/-8.5 -4.7/-0.54 +6.7/-0.7

ATL-II/N -1.2/-0.97 -3.4/-8.9 -4.1/-0.45 -1.6/+0.9

ATL-II/P -12.2/-10.3 -4.3/-9.8 -3.9/+0.72 +1.1/-1.6

ATL-II/R -10.4/-6.4 -2.6/-9.5 +1.2/+0.20 +0.9/-1.1

ATL-II/S -4.9/-6.3 +1.1/-10.1 -5.8/-0.95 -1.6/-1.7

ATL-II/T -12.4/-18.1 -3.1/-8.7 -10.6/-11.7 -2.8/-8.3

ATL-II/U -12.8/-20.2 -4.3/-13.0 -11.2/-12.1 +5.6/-6.3

ATL-II/V -22.5/-25.8 -2.7/-13.9 -10.2/-14.1 +4.8/-11.1

AO/H -17.8/-18.4 ---* +10.6/+7.8 ---*

AO/O -15.0/-15.6 --- +3.31/+8.2 ---

AO/R3A +1.39/-20.9 --- +3.89/-6.3 ---

AO/MM -10.1/-14.7 --- +9.02/+0.31 ---

AO/NN -8.10/-13.9 --- +13.3/+0.09 ---

AO/N2 -7.10/-13.1 --- +6.39/-2.3 ---

AO/T -7.30/-14.9 --- +12.0/-3.6 ---

*

 Higher emitter were not tested in the Auto/Oil Programs

For the most part, it is evident from Table IV-56 that the

discrepancies between actual test results and model predictions
238

are small and would be expected to fall within the 90% confidence

interval calculated in the ATL test programs [see A-92-12 Docket

submittals #II-B-12, February 1993 and #II-B-14, February 1993].

In some cases, the predictions are poor due to contradicting

emissions for similar fuels within the data in the Auto/Oil and

ATL studies.

3. Response to Comments

In response to previous EPA submittals to the docket, one

commenter expressed the need for the exhaust benzene model to be

developed in a different manner. The commenter suggested that the

effect of fuel benzene content and fuel aromatics content were

overestimated. However, the agency has analyzed many exhaust

benzene emission models [see EPA memorandum by Rao and Sklar

"Alternative Exhaust Benzene Models," December 2, 1993], including

the model suggested by this commenter, and concluded that the

exhaust benzene model presented in Section A is the simplest in

form and as accurate as any other model for exhaust benzene

emissions. EPA, in all of the models that it has developed for

predicting exhaust benzene emissions, has found that fuel benzene

content and aromatics content have a large effect on benzene

emissions, particularly when their effects on emissions from

vehicles with emission levels representative of in-use emission

levels.

Nearly all commenters expressed the need for a fungible fuel

distribution system. The Agency agreed with commenters that

fungibility is a critical element of the fuel distribution system. 

EPA evaluated fungibility throughout the development of the

Complex Model. The fungibility analysis methodology described in

Section F.1 was originally presented at the June 2, 1993 Complex

Model workshop in Romulus, Michigan in response to the need for a

fungible model. It has since been affirmed by the participants of

that workshop as an appropriate and accurate analysis tool.

In response to the July 15, 1993 docket submission of various

Complex Model options, commenters concluded that the Agency was

fulfilling its mission to develop a Complex Model that ensured

fungibility. The Agency has continued this mission in the

development of the final Complex Model, as the results of the

fungibility analysis in Section F.1 show. Thus the EPA's analysis

shows that, for real in-use fuels, the final Complex Model

presents no fungibility concerns.
239

G. Vehicle Testing

As discussed in Section V of the preamble, the purpose of

vehicle testing is to supplement the Complex Model, not to

supplant it. Vehicle testing is subject to a number of sources of

error and bias. The model is less vulnerable to bias and error

since it is based on the results from a number of independent

testing programs. Nonetheless, the results of new vehicle testing

programs can provide information beyond that available from the

test programs represented in the Complex Model database. New

vehicle testing programs are particularly valuable when they

examine the effects of fuel parameters at previously-untested

levels or the effects of fuel parameters that have not yet been

tested.

In order to provide useful information beyond that

incorporated in the Complex Model, vehicle testing programs need

to incorporate a number of measures to assure the relevance of

their results. These measures must, at minimum, address the

following concerns:

 The emission effects being measured must be the result

of the specific fuel modification for which benefits are

being claimed.

 The emissions effects being measured, including

nonlinear or interactive effects, must be quantifiable

across the entire set of vehicles of concern.

 The emission effects must meet the statistical

significance and explanatory power criteria used to

develop the Complex Model.

To address these concerns, the Agency has promulgated a set of

fuel specifications, fuel blending and measurement tolerances,

vehicle selection criteria, and data analysis processes to govern

vehicle testing programs undertaken to augment the Complex Model. 

The remainder of this section explains and justifies these

requirements. In addition, a summary and analysis of substantive

comments received by EPA regarding its prior vehicle testing

proposals is presented.

1. Specifications for Fuels Required for Vehicle Testing

Programs

a. Orthogonal fuel design

The properties of the fuels tested in a vehicle testing

program limit the emission effects that can be determined from the

test program's effects. Two fuels with different levels of the

fuel property of interest must be tested to determine whether a

first-order (i.e., linear) effect of the fuel property on
240

emissions exists and to estimate the size of this effect. Fuels

containing three different levels of the fuel property must be

tested to determine whether a second-order (i.e., squared) effect

exists and to estimate its size. Additional fuels must be tested

to determine the presence of interactive effects.

In the ideal case, test fuels would be orthogonal to one

another. A pair of fuels is said to be orthogonal with respect to

a fuel parameter when the two fuels are identical in all respects

except for that fuel parameter. As the number of properties being

investigated grows, the number of fuels required to construct an

orthogonal set of fuels increases exponentially. If two separate

levels of each fuel property are to be tested and there are N such

properties, then the number of fuels required equals two raised to

the Nth power: 2N. If three separate levels of each fuel property

are to be tested in order to determine the existence and size of

second-order effects, then the number of fuels required increases

to 3N

. In either case, the number of fuels increases rapidly as

the number of fuel properties increases. Since the exhaust

emission Complex Model incorporates seven fuel properties for VOC,

NOx, POM, and butadiene, eight properties for exhaust benzene, and

ten properties for acetaldehyde and formaldehyde, an ideal vehicle

test program would contain thousands of fuels. Such test programs

would be prohibitively costly to conduct.

Three factors reduce the number of fuels required for vehicle

testing to more manageable levels, however. First, the number of

fuels required for VOC and NOx testing can be reduced if testing

is conducted to identify second-order interactive effects only. 

In other words, by assuming that interactive effects will not take

the form (A2 x B) or (A x B x C) where A, B, and C are fuel

parameters, many fuels need not be tested. This assumption

appears reasonable, since the existence of such effects would

imply that simultaneous interactions between three separate

molecules significantly affect emissions. Such interactions are

far less likely to occur than pairwise interactions; in fact,

chemical reactions involving three separate molecules typically

are modeled as sequential pairwise reactions. By eliminating

three-way interactions, a comprehensive test program would require

fewer than 50 fuels.

Second, the Complex Model and Complex Model database already

include much of the information that a comprehensive program would

provide. Hence combining the test program results with the

Complex Model and Complex Model database permits the size of the

test program to be reduced still further.

Third, the Complex Model does not include all possible

effects, despite having analyzed a large body of test data. Since

the size of any one test program is likely to produce fewer data

than the existing Complex Model database contains, it is unlikely

that effects not found when analyzing the Complex Model database
241

would be found in an individual vehicle testing program. As a

result, some effects can be eliminated from consideration. In

other cases, notably for toxics emissions, measurement

uncertainties are sufficiently large to make the identification

and accurate estimation of interactive effects difficult. It

would be pointless to require testing to identify interactive

effects for exhaust toxics since such effects cannot be identified

with accuracy from test data.

Given the preceding discussion, EPA has identified fuels

that, if tested in a well-designed and well-conducted vehicle

testing program, can provide sufficient information to quantify

genuine emission effects with sufficient confidence to supplement

the Complex Model with the estimated emission effects. Two

separate sets of fuels have been identified. The first set of

fuels is designed to provide sufficient information to extend the

valid range of fuel parameters already included in the Complex

Model. In this case, the test program would be designed to

quantify the emissions effects of existing Complex Model fuel

parameters at levels that have not been adequate tested. The

second set of fuels is designed to provide sufficient information

to add a new fuel parameter to the Complex Model.

b. Fuels to be tested when extending the range of the Complex

Model

As discussed in Section V of the preamble, at least three

fuels must be tested when extending the range of the Complex

Model. These three "extension fuels" are specified in Tables IV57 and IV-58. Table IV-57 specifies the level of the parameter

being extended; Table IV-58 specifies all other parameters for the

three extension fuels.

Table IV-57: Level of Existing Complex Model Parameters Being

Extended

Fuel Property Extension Extension Extension

Being Extended Fuel #1 Fuel #2 Fuel #3

Sulfur, ppm Extension Level 80 450

Benzene, vol% Extension Level 0.5 1.5

RVP, psi Extension Level 6.7 8.0

E200, % Extension Level 38 61

E300, % Extension Level 78 92

Aromatics, vol% Extension Level 20 45

Olefins, vol% Extension Level 3.0 18

Oxygen, wt% Extension Level 1.7 2.7

Octane, R+M/2 87.5 87.5 87.5
242

Table IV-58: Levels for Fuel Parameters Other Than Those Being

Extended

Extension Extension Extension

Fuel Property Fuel #1 Fuel #2 Fuel #3

Sulfur, ppm 150 150 150

Benzene, vol% 1.0 1.0 1.0

RVP, psi 7.5 7.5 7.5

E200, % 50 50 50

E300, % 85 85 85

Aromatics, vol% 25 25 25

Olefins, vol% 9.0 9.0 9.0

Oxygen, wt% 2.0 2.0 2.0

Octane, R+M/2 87 87 87

These fuels are designed to test the effects of the fuel

parameter being extended at three separate levels in order to

estimate the linear and squared effects of the parameter in

question. Extension Fuel 1 will have levels of the parameter

being tested that are equal to the most extreme value for which

the augmentation will be valid. Extension Fuels 2 and 3 will have

levels of the parameter being tested within the range of the

Complex Model, which allows the test program to correlate its

results to those for the Complex Model. The properties of these

two fuels are near the limits of the valid range of the model for

reformulated fuels but are sufficiently far within those limits so

as to assure the reliability of the Complex Model correlations (as

discussed in Section D, the Complex Model correlations become less

reliable for fuels at or near the limits of the valid range of the

model).

The three fuels described above do not provide the

information needed to evaluate interactive effects. However, EPA

does not anticipate that test programs of the size required to

augment the model would be sufficient to identify interactive

effects that were not included in the Complex Model, which is

based on a much larger set of data than would be available from

augmentation test programs. Hence EPA does not require testing

for interactive effects unless such effects are already

incorporated in the Complex Model. For example, the VOC model

includes interactive effects for aromatics (with E300) but does

not include interactive effects for sulfur. As a result, a test

program to extend the range of sulfur levels covered by the model

would not be required to test for interactive effects, but a test

program to extend the aromatics range would be required to do so.

 To evaluate interactive effects, two additional fuels are

required. These two fuels must have the following

characteristics:
243

 The parameter being tested must be at the level

specified for Extension Fuel 1, i.e., it must be at the

most extreme value for which the augmentation will be

valid.

 Other parameters which interact with the parameter being

tested according to the Complex Model (for any

pollutant) must be at two different levels in the two

fuels. The first fuel (Extension Fuel #4) must contain

these other parameters at the level specified in Table

IV-57 for Extension Fuel #2, i.e., at relatively low

levels. The second fuel (Extension Fuel #5) must

contain these other parameters at the level specified in

Table IV-57 for Extension Fuel #3, i.e., at relatively

high levels.

 All other parameters must be present at the intermediate

levels specified in Table IV-58.

c. Fuels to be tested when adding a new parameter to the Complex

Model

More fuels must be tested when adding a new parameter to the

Complex Model for several reasons. First, the Complex Model

database cannot be used to supplement the results from the vehicle

testing program. Second, the Complex Model cannot be used to

reduce the testing needed to identify and quantify any interactive

effects. In order to quantify linear, squared, and interactive

effects for the new parameter, seven fuels must be tested

(referred to as "Addition Fuels"). The specifications for these

seven fuels are listed in Table IV-59.

Table IV-59: Properties of Fuels To Be Tested When Augmenting The

Model With A New Fuel Parameter

Fuel Property FUELS 

 1 2 3 4 5 6 7

Sulfur, ppm 150 150 150 35 35 500 500

Benzene, vol% 1.0 1.0 1.0 0.5 0.5 1.3 1.3

RVP, psi 7.5 7.5 7.5 6.5 6.5 8.1 8.1

E200, % 50 50 50 62 62 37 37

E300, % 85 85 85 92 92 79 79

Aromatics, vol% 27 27 27 20 20 45 45

Olefins, vol% 9.0 9.0 9.0 2.0 2.0 18 18

Oxygen, wt% 2.1 2.1 2.1 2.7 2.7 1.5 1.5

Octane, (R+M)/2 87 87 87 87 87 87 87

New Parameter* C C+B BC B CB

 2
244

*

 C = Candidate level, B = Baseline level

Addition Fuels 1, 2, and 3 are necessary to determine the

linear and squared effects for the parameter being tested. Since

emissions performance of reformulated fuels is calculated

relative to the emissions performance of Clean Air Act baseline

gasoline, Addition Fuel #3 must contain this parameter at a level

representative of that found in Clean Air Act baseline gasoline

in order to assign proper emissions credit for changes in this

fuel parameter. The parameter also must be tested at its

"candidate" level, the most extreme level at wich it is to be

tested (which can be higher or lower than its level in Clean Air

Act baseline fuel), as specified for Addition Fuel #1. The

parameter also must be tested at a level midway between these

first two levels, as in Addition Fuel #2, in order to estimate

the parameter's squared effects on emissions. Squared effects

are most easily determined if the parameter levels for the three

fuels are evenly spaced. For all three fuels, other fuel

parameters must be present at levels which satisfy two

requirements:

 They must be at levels typical of reformulated fuels

that are likely to be produced during 1995-1999.

 They must be at levels for which the Complex Model

correlations are highly reliable, i.e., they must be at

levels near the center of their range in the Complex

Model database.

Addition Fuels 4 through 7 are necessary to identify and

quantify any interactive effects associated with the parameter. 

Addition Fuels 4 and 5 represent "clean" fuels in that all

parameters other than the one being tested are set at levels that

generally result in emission reductions from baseline levels. 

Addition Fuels 6 and 7 represent "dirty" fuels since all

parameters other than the one being tested are set at levels that

generally result in emission increases from baseline levels. The

"clean" and "dirty" levels of these parameters are as widely

separated as possible while still remaining within the data core

and within the range expected to occur in reformulated gasolines

during 1995-1999. Oxygen levels were set so as to be compatible

with the use of any oxygenate under the "substantially similar"

requirements of existing law. The two "clean" fuels are required

to contain levels of the parameter being tested that are equal to

those specified for Addition Fuels 1 and 3, respectively; the

same is true for the two "dirty" fuels. The wide separation in

parameter levels among Addition Fuels 4 through 7 is designed to

improve the ability of the analysis method (discussed in Section

G.4) to isolate and quantify interactive effects associated with

the parameter being tested.
245

2. Blending and Measurement Tolerances

a. Blending precision

In the course of its own vehicle testing programs, EPA has

found that there are limits to the precision to which fuels can

be blended, particularly when fuels are blended from

representative refinery streams. These limitations appear to be

the result of limitations in the design and process control

capabilities of modern refineries. EPA's experience, combined

with comments received from refiners and fuel blenders, indicates

that fuel blenders cannot achieve precisions beyond those

specified in Table IV-60. In recognition of these limitations,

EPA has required that test fuels blended to the specifications

outlined in Section G.1 fall within these tolerances of the

specified values.

Table IV-60: Fuel Parameter Blending Tolerances

Fuel parameter Blending tolerance

Sulfur content ± 25 ppm

Benzene content ± 0.2 vol %

RVP ± 0.2 psi

E200 level ± 2 %

E300 level ± 4 %

Oxygenate content ± 1.0 vol %

Aromatics content ± 2.7 vol %

Olefins content ± 2.5 vol %

Saturates content ± 2.0 vol %

Octane ± 0.5

Detergent Control Additives ± 10% of the level required by

EPA's detergents rule

Candidate parameter To be determined as part of the

augmentation process

b. Impact of blending variation

Variation in test fuel properties from those specified in

Section G.1 will tend to reduce the statistical power of the test

program. Such variations would make estimates of emission

effects using simple averages of percent change in emissions per

unit change in each fuel parameter impossible. However, the

analysis method outlined in Section G.4 can compensate for small

deviations from the test fuel specifications by utilizing the

existing Complex Model database to help disentangle the effects

of fuel modifications from one another.

c. Measurement precision
246

Any measurement is subject to some degree of uncertainty. 

This uncertainty can be separated into two types. Uncertainty

can result from variations in separate measurements when using

the same measurement technique and instruments. Uncertainty can

also result from variations in measured values when using

different measurement techniques or instruments. The first type

of uncertainty can be reduced by taking multiple measurements; as

the number of measurements increases, the average measurement

becomes an increasingly precise estimate of the "true" value that

would be measured if the measurement technique and instruments

were applied without error. This type of uncertainty is

characterized by its repeatability level, which refers to the

probability that two successive measurements of the same sample

will fall within a certain range a specified percentage of the

time, typically 95 percent. The second type of uncertainty can

be reduced by calibrating the measurement technique and

instruments being used against a set of known values determined

through other, more reliable means. This type of uncertainty

often is characterized by its reproducibility level, which refers

to the probability that measurements of the same sample at two

different facilities will fall within a certain range a specified

percentage of the time.

Both sorts of measurement precision can affect the estimates

of emission effects from vehicle testing programs. Inaccuracies

in estimates of fuel parameter levels or emission levels can

cause the analysis method outlined in Section G.4 to provide

inaccurate estimates of emission effects. The procedures

outlined in the Code of Federal Regulations and §80.56-80.57 of

the reformulated gasoline regulations are designed to minimize

emission measurement errors, and the procedures outlined in

§80.46 are intended to minimize fuel property measurement errors. 

Nonetheless, some measurement uncertainty is inevitable.

EPA recognizes that for some fuel parameters, the size of

the measurement uncertainty can result in substantial uncertainty

in emission estimates. Reducing this uncertainty is particularly

important in vehicle testing programs since any inaccuracies in

fuel parameter measurements can affect the resulting augmentation

to the Complex Model. Inaccuracies in the augmentation, in turn,

can affect estimates of emission benefits for a large amount of

fuel and can influence capital investments by refiners and fuel

blenders. As a result, EPA has concluded that the modest costs

associated with repeat testing of test fuel properties are more

than offset by the gain in modeling accuracy. Hence EPA has

required test programs to measure the properties of their test

fuels to the accuracy specified in Table IV-61. Test programs

must conduct repeat measurements of the fuel properties such that

the 95% confidence limits of the measured values for each

parameter (based on a standard t-test) about the mean measured

values are no larger than the tolerances presented in Table IV61. Given the repeatability levels for relevant measurement
247

methods, EPA does not expect a large number of repeat

measurements to be required. The measurement tolerances,

repeatability levels for approved ASTM or EPA measurement

methods, and expected number of measurements required for each

parameter are presented in Table IV-61 (measurement methods refer

to ASTM designations unless specified otherwise). Test programs

are responsible for providing documentation regarding the

repeatability, reproducibility, and correlation of their

measurement techniques as part of their augmentation application. 

Table IV-61: Fuel Parameter Measurement Tolerances for Fuel

Certification by Vehicle Testing

Measurement Method & 95% No. of

Parameter Tolerance Repeatability Repeats

API Gravity, °API ± 0.2 D1288 (± 0.1) 1

Sulfur, ppm ± 10 D2622 (± 10) 1

Benzene, vol% ± 0.02 D3606 (± 0.03) 3

RVP, psi ± 0.05 D5191 (± 0.16) 11

Octane, (R+M)/2 ± 0.2 D4814 (± 0.1) 1

E200, vol% ± 2 D86 (± 3) 3

E300, vol% ± 2 D86 (± 1.3) 1

Oxygenate, vol% ± 0.2 GC/OFID See text

Aromatics, vol% ± 0.5 GC/MS See text

Olefins, vol% ± 0.3 GC/MS See text

Saturates, vol% ± 1.0 See text

Candidate parameter To be determined as part of the

augmentation process

In Table IV-61, no repeatability levels are provided for

oxygenate, aromatics, olefins, or saturates. EPA anticipates

that oxygenate will be added in measured amounts to a fuel sample

of known volume to produce the required test fuels; since the

volume of oxygenate to be added can be controlled to extremely

high levels of precision and accuracy, EPA does not anticipate

that meeting the required tolerances will present petitioners

with significant difficulties. The D86 measurement method does

not directly yield E200 and E300 values, but it can be modified

to do so by setting the sample temperature and measuring the

fraction of the sample that is recovered. Alternatively, the D86

method can be used to derive T50 and T90 values, which can then

be converted to E200 and E300 values using the correlations

presented in Section A. The repeatability levels presented in

Table IV-61 are based on this indirect method for determining

E200 and E300 values.

The fuel measurement methods promulgated in the reformulated

gasoline rule include the use of the GC/OFID measurement method

for oxygenates and a gas chromatograph/mass spectrometer

measurement method for olefins and aromatics; saturates can be
248

estimated by simple subtraction. These methods have been

promulgated since the standard ASTM measurement methods yield

unacceptably high repeatability and reproducibility errors. For

example, ASTM method D4815 for oxygenates yields 95%

repeatability levels of ± 0.83 volume percent for ethanol and ±

1.6 volume percent for MTBE. Such methods would require 18

repeat measurements of ethanol blends on average and 64 repeat

measurements of MTBE blends on average. The GC/OFID method has

95% repeatability levels of approximately ± 0.24 volume percent

ethanol and ± 0.37 volume percent MTBE. Hence test programs

employing the GC/OFID method would need to conduct between two

and four repeat measurements for oxygenate concentration. 

Aromatic and olefin measurements using ASTM method D1319 have 95%

repeatability levels of approximately 1.4 volume percent and 1.2

volume percent, respectively, and hence would require 8 and 16

repeat measurements, respectively. EPA believes that the

measurement methods promulgated in the final RFG rule for

aromatics and olefins are capable of significantlyg better

repeatability. Similarly, EPA's in-house experience with the RVP

measurement method (D5191) indicates that repeatability levels of

0.05 psi are achievable, which would reduce the number of repeat

tests required from eleven to one.

In addition to the requirements outlined in Table IV-61, EPA

requires that detergent control additive concentrations be

measured to within 2 percent of the level required by relevant

EPA regulations. Since detergent control additives are expected

to be added to gasolines in small quantities after blending, EPA

believes that test programs will be able to control the

concentration of such additives to high levels of precision

without incurring additional cost. 

The required measurement accuracy for test fuel properties

is considerably more stringent than the accuracy required for

routine testing of reformulated gasoline in the field. EPA

believes this greater stringency is warranted. The

specifications for test fuels are carefully designed to provide

the data needed to evaluate proposed augmentations. Variation in

the measured properties of the test fuels would affect the

results of an augmentation study. Since these results could

influence fuel production decisions for a number of refiners, EPA

considers it desirable to eliminate potential sources of error

wherever practicable.

The cost of greater fuel property measurement precision is

small compared with the total cost of vehicle testing programs. 

EPA estimates that a typical vehicle test program of the size

required to augment the Complex Model could cost on the order of

$300,000 to as much as $1 million, depending on the cost of

procuring the necessary vehicles; the necessary fuel parameter

measurements would cost less than $10,000 (based on typical

commercial laboratory fee schedules). Such costs are also small
249

when compared with the potential savings to refiners resulting

from augmentations to the model. In addition, EPA expects the

accuracy and precision of existing measurement methods to

improve, since the reformulated gasoline program introduces

strong financial incentives to do so in order to recoup

compliance margins and reduce the risk of noncompliance. For

these reasons, EPA has decided that the modest costs of greater

fuel property measurement accuracy are more than offset by the

resulting improvements in the accuracy of augmentations to the

model.

However, the Agency does not consider such increased

accuracy to be practicable or cost-effective for routine testing

of commercial reformulated gasolines. Repeat testing would be

required on each batch of gasoline, thereby increasing the cost

of reformulated fuels. This cost increase would be particularly

onerous for low-volume gasoline marketers, since the increased

costs of fuel property testing would be spread across a

relatively small volume of fuel. In addition, the uncertainty

associated with single measurements of fuel properties will tend

to average out across multiple fuel batches produced or sold

commercially; such averaging is neither possible nor desirable in

a vehicle testing program.

3. Vehicle Fleet Composition

a. Principles of Fleet Balancing

As discussed in Section A, EPA has found that vehicles with

different emission characteristics and different emission control

technology respond differently to fuel modifications. To capture

these effects adequately in a vehicle testing program, the

vehicles tested should reflect the emission characteristics and

technology distribution of the in-use fleet.

The purpose of the Complex Model is to predict the effect on

emissions of fuel modifications. To assure that sufficient

information will be available to estimate fuel effects on

emissions, EPA has defined two guiding principles for vehicle

selection:

1) The proportion of vehicles of each vehicle type

included in a test program should reflect the

contribution of that vehicle type to in-use emissions.

2) The vehicles included in a test program should include

as wide a variety of emission classes and technology

groups as possible without violating the first

principle.

EPA used these guiding principles to determine the desired

composition of vehicle testing fleets.
250

b. Distribution by Emitter Class

As discussed in Section III.B.4, normal emitters account for

52% of exhaust VOC and exhaust toxics emissions in Phase I and

44.4% of these emissions in Phase II. In keeping with Guiding

Principle (1), these proportions suggest that approximately half

of the vehicles tested should be normal emitters and half should

be higher emitters. By contrast, normal emitters account for 82%

of NOx emissions in Phase I and 73.8% of NOx emissions in Phase

II, which suggests that 75-80% of all vehicles tested should be

normal emitters.

However, the relative scarcity of higher emitter data

implies that the effects of fuel modifications on higher emitters

is known with less certainty than for normal emitters. To

compensate for this greater uncertainty, EPA considered requiring

a disproportionate share of the vehicles tested to be higher

emitters. At the same time, EPA was reluctant to deviate too far

from the emission ratios presented above. Hence the Agency

decided to require that half of all vehicles tested be higher

emitters. This distribution assures that sufficient data on

higher emitters will be available to estimate the effects of fuel

modifications with confidence. The Agency considers the increase

in the accuracy of emission estimates for higher emitters (for

VOC, NOx, and toxics) to more than compensate for the reduction

in the accuracy of normal emitter NOx emission estimates that

would result from requiring the proportion of normal emitters to

match the contribution of normal emitters to NOx emissions. A

more thorough discussion of this issue is contained in the April

1992 NPRM.

c. Technology groups

As discussed in Section A.3, EPA has modeled the response of

normal emitters by grouping vehicles with different emission

control technologies and allowing terms specific to each group to

enter the regression equations. This approach was required by

the imbalance between the contribution of each technology group

to in-use normal emitter emissions and the proportion of test

data available for each technology group. If the proportion of

test data were to match the proportion of emissions due to each

technology group, then the population of test vehicles would

reflect the origin of in-use emissions and separate models for

individual technology groups would be unnecessary.

EPA has chosen to reduce the burden of vehicle testing by

eliminating the need for technology group-specific regression

terms. Instead, EPA has chosen to require organizations involved

in vehicle testing to recruit a balanced set of normal emitting

vehicles according to Principles (1) and (2). As a result,
251

separate models for each technology group need not be constructed

when augmenting the model through vehicle testing.

To simplify the process of vehicle specification for the

normal emitter test fleet, EPA has developed a schedule to guide

vehicle acquisition. The schedule identifies the vehicle

characteristics required of the first, second, third, etc.

vehicle. An organization conducting vehicle testing is required

to include at least ten normal emitting vehicles to assure the

statistical validity and reliability of their results; such

organizations have the option of testing additional vehicles to

increase the statistical power of their test program. Additional

vehicles are to be added in the order specified so as to maintain

a balanced test fleet. The normal emitting vehicle acquisition

schedule is presented below in Table IV-62.
252

Table IV-62: Normal Emitting Vehicle Acquisition Schedule

 Veh. Fuel Air Tech. Manu-

 # System Catalyst Injection EGR Group facturer

 1 Multi 3W No Air EGR 1 GM

 2 Multi 3W No Air NoEGR 2 Ford

 3 TBI 3W No Air EGR 3 GM

 4 Multi 3W+OX Air EGR 4 Ford

 5 Multi 3W No Air EGR 1 Honda

 6 Multi 3W No Air NoEGR 2 GM

 7 TBI 3W No Air EGR 3 Chrysler

 8 ulti 3W+OX Air EGR 4 GM

 9 TBI 3W+OX Air EGR 7 Chrysler

 10 Multi 3W Air EGR 5 Toyota

 11 Multi 3W No Air EGR 1 Ford

 12 Multi 3W No Air NoEGR 2 Chrysler

 13 Carb 3W+OX Air EGR 9 Toyota

 14 TBI 3W No Air EGR 3 Ford

 15 Multi 3W+OX Air EGR 4 GM

 16 Multi 3W No Air EGR 1 Toyota

 17 Multi 3W No Air NoEGR 2 Mazda

 18 TBI 3W No Air EGR 3 GM

 19 Multi 3W+OX Air EGR 4 Ford

 20 Multi 3W No Air EGR 1 Nissan

Legend:

Fuel system:

Multi = Multi-point fuel injection

TBI = Throttle body fuel injection

Carb = Carburetted

Catalyst:

3W = 3-Way catalyst

3W+OX = 3-Way catalyst plus an oxidation catalyst

Air Injection:

Air = Air injection

No Air = No air injection

EGR:

EGR = Exhaust gas recirculation

No EGR = No exhaust gas recirculation
253

Table IV-63: Technology Group Definitions

Tech Fuel Air

Group System Catalyst Injection EGR

 1 Multi 3W No Air EGR

 2 Multi 3W No Air No EGR

 3 TBI 3W No Air EGR

 4 Multi 3W+OX Air EGR

 5 Multi 3W Air EGR

 6 TBI 3W Air EGR

 7 TBI 3W+OX Air EGR

 8 TBI 3W No Air No EGR

 9 Carb 3W+Ox Air EGR

EPA has not specified a similar schedule for higher emitters

since the Agency does not believe technology group distinctions

to affect the emissions response of such vehicles to fuel

modifications. This issue is discussed more fully in Section

A.2.

4. Analysis Process

The analysis process promulgated in the reformulated

gasoline rule is designed to extract the maximum amount of

information from the limited data available from each vehicle

testing program. It incorporates statistical analysis techniques

analogous to those used to develop the Complex Model, and it

utilizes the existing Complex Model database where possible to

supplement the data from individual test programs. The analysis

process is designed to achieve the following goals:

 Accurate estimation of the linear and nonlinear

emission effects due to the fuel property being tested.

 Accurate estimation of interactive effects between the

fuel property being tested and other fuel properties

known to affect emissions.

 Isolation of the effects of the fuel property being

tested on emissions from normal and higher emitting

vehicles.

 Isolation of the effects of the property being tested

from the effects of related or correlated fuel

properties already included in the model.

 Preservation of already-established Complex Model

effects within the data core.

The remainder of this section discusses the rationale for

the analysis method and statistical techniques promulgated in the
254

reformulated gasoline rule. It also discusses the basis for the

differences in analysis process when testing extension or

addition fuels.

a. Analysis method and statistical techniques

The analysis methods to be used to analyze test program data

are similar to those used to develop the Complex Model. The

basic process involves the following elements; many of these

techniques are discussed and justified in greater detail in

Section A.

1. Separate analyses are to be conducted for normal and

higher emitters, since past experience has shown that

emission responses to fuel modifications differ for

these two types of vehicles. In addition, petitioners

must demonstrate that their higher emitting vehicles

were stable over the course of the test program in

terms of their emissions on a given fuel. Past EPA

testing experience has shown that emissions from higher

emitters often demonstrate time trends or variations

that are unrelated to and considerably larger than the

effects of fuel modifications; control of such

variability is necessary if genuine fuel effects are to

be identified.

2. All models are to fit polynomials (first-order for

toxics, no higher than second-order for VOC and NOx) to

the natural logarithm of emissions, as was done for the

existing Complex Model. EPA and others have found that

transforming emissions using the natural logarithm

results in improved model accuracy and more normally

distributed residuals.

3. Petitioners must demonstrate that collinearity problems

are not exceedingly large. Variance inflation values

in excess of 10 will be interpreted to indicate that

the models constructed by the petitioner contains

severe collinearity problems, in keeping with standard

statistical practice.

4. Petitioners must demonstrate that the residuals from

their regressions are approximately normally

distributed. The statistical analysis process outlined

in the regulations requires such a distribution. 

Models without normally-distributed residuals cannot be

generated or evaluated using the more powerful

techniques associated with normally-distributed data.

5. Petitioners must demonstrate that their analysis has

adequately balanced potential overfitting and
255

underfitting of the data through the use of Mallows' Cp

criterion or other appropriate methods. Underfitted

models have too few terms to explain the observed

variation in the data; overfitted models have too many

terms, some of which are likely to be erroneous.

6. All regressions are to include separate terms for each

vehicle-study combination in the form of dummy

variables, as was done for the existing Complex Model.

7. To retain consistency with the existing Complex Model,

all regressions must retain terms with significance

levels of 0.90 or higher.

b. Special Analysis Requirements When Extending Existing Model

Parameter Ranges

Test programs designed to extend the valid range of the

model for existing Complex Model parameters can utilize the data

already available in the Complex Model database. This additional

data increases the statistical power of the analysis process and

allows the augmentation to be integrated with the existing

Complex Model smoothly. The analysis process involves the

following unique elements:

1. The test data on all extension fuels tested must be

combined with the Complex Model database used to

develop the Complex Model being promulgated today. All

analyses must be performed on this combined database.

2. The first step in analyzing this combined data set is

to fit a standard regression model to the combined

database. The model must contain separate terms for

each vehicle-study combination. It must also contain

all terms present in the existing Complex Model. The

coefficients for those terms which do not involve the

parameter being extended must be set equal to their

values in the existing centered, consolidated Complex

Model equations. The coefficients for terms which do

involve the parameter being extended (including any

linear, squared, and interactive terms) are to be

estimated by the regression. This approach assures

that the only changes in the existing Complex Model

will occur for those terms involving the parameter

being extended.

3. In some cases, the existing consolidated Complex Model

may not contain a squared term for the parameter being

extended. However, the additional data made available

through the test program may warrant inclusion of such

a term. To allow such terms to be included in the
256

model, a stepwise regression procedure should be used

to determine whether the squared term for the parameter

being extended would be statistically significant. The

linear term must be retained even if it is no longer

significant once the second-order term is added.

4. The fuel terms included in the models described above

must be expressed in centered form. The centering

value for these terms must be identical to the

centering value used to develop the Complex Model being

promulgated today. Centering values can be found in

Section A.8 and will be made available to petitioners

by EPA upon request. These centering values are

necessary during development of the augmented model;

the same centering values as were used during

development of the current Complex Model must be used

since the coefficients from that model will be used for

a number of terms in the models described previously. 

Once the augmented model has been developed, it should

be uncentered using the process described in Section

A.8.

5. The model resulting from the foregoing steps is the

augmented model. It can be used for levels of the fuel

parameter in question only when it is present in fuels

at levels between the extension level and the data

core. The performance of such fuels is to be

calculated as follows, with all performances being

expressed as percentage changes in emissions from

baseline levels:

a. Up to the limits of the data core, the

unaugmented Complex Model must be used to

determine the percentage change in emissions due

to the parameter in question. In other words,

the unaugmented model is to be used to estimate

the performance of a fuel identical to the

target fuel, but with levels of the augmentation

parameter set equal to the nearest limit of the

data core.

b. The performance of the fuel described in step

(5.a) must be determined using the augmented

model.

c. The performance of the actual target fuel must

be determined using the augmented model.

d. The performance of the actual target fuel, in

percentage terms, shall be set equal to the

following value:
257

100 - [(100 + a) * (100 + c)/(100 + b)]

These calculations maintain equivalency with the

Complex Model up to level at which the existing Complex Model

database becomes so sparse as to make the existing Complex Model

equations less reliable. This equivalency is necessary to avoid

fungibility problems from being introduced by model

augmentations. Without the adjustments described above, a model

augmentation might give greater credit for a fuel modification at

a given parameter level than the existing Complex Model. As a

result, mixing of fuels certified using an unadjusted augmented

model and the existing unaugmented model could produce a mixture

in which each original constituent met the emission reduction

requirements of the program but the mixture itself would not. 

This situation, and the compliance and certification problems it

presents, can be avoided by using the adjustments described

above.

c. Special Analysis Requirements When Adding New Model

Parameters

Test programs designed to augment the model with a new

parameter require a somewhat different analysis process involving

the following elements:

1. The first step is to adjust the measured emission

levels to account for deviations in fuel

characteristics other than the one being tested from

those specified. This process involves using the

Complex Model to determine the percentage change in

emissions between the desired and actual fuels, then

adjusting the measured emissions accordingly.

2. The second step is to develop a model based on this

adjusted emissions data from addition fuels 1, 2, and

3. This model must include separate dummy variable

terms for each vehicle, a linear term for the parameter

in question, and a squared term for the parameter in

question. If the squared term is not significant, it

must be dropped from the model, which must then be reestimated. If the linear term in the resulting model

is not significant, then it must be dropped from the

model. In such cases, EPA will not grant the

augmentation and the analysis process (and test

program) can end. However, the analysis results still

must be reported to EPA, since these results may be

helpful in revising the Complex Model or evaluating

other augmentation petitions.

3. The third step is to build a stepwise regression on a

data set which combines the test data from all seven
258

fuels and the data in the existing Complex Model

database. Using this data set, the vehicle terms for

the test fleet must be re-estimated. The initial model

must include separate terms for each vehicle-study

combination; it must also include all terms present in

the centered, consolidated Complex Model along with

their coefficients, and it must include the linear and

squared terms (if statistically significant) and their

coefficients as estimated previously based on addition

fuels 1, 2, and 3. Interactive terms between the

parameter in question and existing Complex Model fuel

parameters should be added in a stepwise fashion,

subject to the conditions discussed in Section G.4.a. 

Once the forward-fit model is complete, a backwards

elimination process can be used to satisfy Mallows' Cp

criterion. However, only the interactive terms added

in the stepwise regression process may be deleted in

the backwards elimination process. This step assures

the equivalency of the augmented and unaugmented

Complex Models within the range of the unaugmented

model, which is necessary to avoid fungibility problems

as discussed in Section G.4.b.

5. The fuel terms included in the models described above

must be expressed in centered form. The centering

value for these terms must be identical to the

centering value used to develop the Complex Model being

promulgated today. Centering values can be found in

Section A.8 and will be made available to petitioners

by EPA upon request. These centering values are

necessary during development of the augmented model;

the same centering values as were used during

development of the current Complex Model must be used

since the coefficients from that model will be used for

a number of terms in the models described previously. 

Once the augmented model has been developed, it should

be uncentered using the process described in Section

A.8.

6. The model resulting from the foregoing steps is the

augmented model. It must be used to calculate the

performance of all fuels which claim benefits from the

parameter in question.

5. Response to Comments

EPA has received a number of comments in response to the

April 1992 and February 1993 proposals. The Agency has

incorporated such comments into the final regulations governing

vehicle testing where such comments were appropriate or

adequately supported by data. However, these regulations do not

incorporate all the comments received by EPA. What follows is a
259

description of the major comments received by EPA, the Agency's

response to these comments, and the Agency's reasons for not

incorporating those comments which have not been addressed in the

final rule. EPA also received a number of comments which are not

relevant to this rulemaking; such comments are not discussed

below. Comments have been grouped by topic to simplify matters.

a. Direct Certification

Several commenters requested that vehicle testing be

permitted as a direct alternative for fuels certification instead

of requiring augmentation of the Complex Model. As discussed in

the preamble and in the introduction to this section, however,

EPA believes that direct fuel certification through vehicle

testing is neither practicable nor desirable. Certification of a

specific fuel would not extent to fuels with minor differences in

composition or other fuel properties, yet such differences

inevitably arise in the course of fuel production. As discussed

in Section G.2, fuel producers cannot precisely control the

properties of their fuel, which would make production of a

specific fuel formulation essentially impossible. Direct fuel

certification through testing is also not desirable since, as

discussed in the preamble and in Section A, the results of a

single test program are less reliable and more vulnerable to

accidental or deliberate manipulation than is a model based on

the results of multiple test programs.

b. Updates to the Model

EPA originally proposed to update the Complex Model every

five years to incorporate the most recently available data on

emission effects of fuel reformulations. Several commenters

objected to such frequent updates, noting that changes in the

model could invalidate investments in refinery technology

undertaken to meet standards using the previous version of the

model. Commenters called for updates no more often than once

every 10-15 years or asked that refiners be able to grandfather

fuel certification under an earlier version of the model for ten

years. EPA has reconsidered its plans to update the model every

five years, in part because it is difficult to predict when

sufficient additional data will be available to warrant such an

update. Instead, EPA plans to update the model through a formal

rulemaking process that will be undertaken when EPA determines

that sufficient new information is available to warrant such

action. As part of this rulemaking process, EPA will consider

the impact of changes in the model on refiners' capital

investments.

c. Test Fuels
260

EPA received numerous comments on its proposed test fuels. 

Many of the comments received in response to the April 1992

proposal have been incorporated in the final regulations

governing vehicle testing. For example, one commenter suggested

that the "candidate-baseline" fuel defined in the April 1992

proposal should not specify that the level of the "candidate

parameter" be zero, since the parameter may be present at nonzero levels in typical baseline fuels. EPA agrees with this

comment and has modified its fuel requirements accordingly. 

Another commenter objected to the test fuels required to augment

the simple model in the April proposal; EPA has since deleted the

simple model augmentation option from the rule. A commenter

noted that standard deviations cannot be averaged across

pollutants, as EPA had proposed in its April 1992 proposal; the

final requirements for vehicle testing do not include averaging

of standard deviation or variance across pollutants.

One commenter recommended that fuel parameter values for

interactive effects testing be no greater than the levels found

in industry average gasoline. EPA considers such an approach

inappropriate for several reasons. First, industry average

gasoline is not representative of expected reformulated fuels in

some respects, notably oxygen, RVP, aromatics, and (in Phase II)

sulfur levels. Second, interactive effects are more easily and

accurately estimated when testing for such effects extends over a

wide range of fuel parameters. Third, EPA recognizes that the

Complex Model will be used to assure compliance of conventional

fuels with the anti-dumping program, and such fuels can have fuel

properties that are quite different from those of industry

average gasoline. Hence testing only 1990 industry average

gasoline for interactive effects would make identification of

interactive effects more difficult and would not provide

sufficient data to estimate such effects for typical reformulated

or conventional gasolines.

A number of comments were received on detergent additive

requirements for test fuels. Commenters generally supported

requiring such additives in test fuels since they will be

required in reformulated gasolines. Some commenters recommended

specific additives or specific levels of additives; however, EPA

does not consider it appropriate to provide such specificity in

this rule. Instead, EPA has required test fuels to meet the

detergent additive requirements set forth in EPA's impending

detergent additives rule. In a related comment, the Agency was

asked to give credit for fuel modifications that result in

reduced emissions after extended use. EPA does not believe it

appropriate to do so beyond the extent shown in the required

vehicle test program. Such benefits are unlikely to be achieved

in-use unless two conditions are met: the fuel modifications are

used on all gasolines sold by the petitioner indefinitely, and

all of the petitioner's consumers exhibit perfect brand loyalty. 

Absent a showing that such conditions exist and can be assured,
261

EPA does not believe it appropriate to augment the model with

emission effects that occur only after extended use. EPA

believes that such modifications are more appropriately addressed

by other fuels-related programs required by Congress, such as

deposit control additives.

Comments were received recommending deletion of the API

gravity and end point specifications for test fuels. EPA has

deleted these specifications for fuel blending since these

characteristics are largely determined by characteristics with

specified blending tolerances. EPA has also eliminated the

requirement that end point be measured for all test fuels. End

point is closely correlated with E300, which is specified; in

addition, end point is difficult to measure accurately. However,

EPA has chosen to retain the API gravity measurement. This

parameter is relatively easy to measure and is specified in the

Act for Clean Air Act baseline fuel. The Agency believes that it

must be measured to assure comparability with Clean Air Act

baseline fuel and is not aware of any measurement difficulties

associated with it. Commenters also asked the Agency to

establish a minimum octane level instead of a blending tolerance. 

The Agency has decided to retain its blending tolerance

requirement while adding a minimum octane requirement, thereby

limiting octane values to the range of 86.5 to 87.5. Such tight

control is feasible, as discussed in Section G.2, and EPA

believes such control to be necessary to prevent distortion of

test results. Octane is known to affect engine performance, pergallon fuel efficiency, and spontaneous ignition (engine knock),

all of which can affect emissions.

One commenter suggested that test fuels be based on typical

at-the-pump fuels. However, as discussed in Section G.1, test

fuel characteristics must be controlled tightly in order to

extract useful information from test program results. At-thepump fuels do not allow such tight control. In addition, EPA

believes that the requirement that test fuels be blended from

typical or realistic refinery streams assures that test fuels

will have characteristics similar to those of typical commercial

gasolines, except for those deliberately altered as part of the

test program design.

d. Measurement methods and data requirements

EPA received several comments on its proposed measurement

methods and data requirements to support augmentation requests. 

Commenters suggested that EPA permit the use of equivalent

testing methods and notify petitioners of data requirements

before testing begins. EPA believes that these comments are

adequately addressed by the requirement that petitioners obtain

approval for their proposed test program before beginning

testing. This requirement provides petitioners with a means of
262

requesting and obtaining approval for the use of equivalent

testing methods. It also allows EPA to identify data

inadequacies in proposed test programs before testing begins.

Several commenters recommended that EPA base its fuel

property measurement methods on standard ASTM methods. EPA has

promulgated a set of approved measurement methods which match

standard ASTM practices in most cases. However, EPA found it

necessary to promulgate alternative methods in some cases in

order to assure sufficient accuracy and precision to meet the

needs of the program. EPA plans to submit these alternative

methods to ASTM for approval. Since such approval can take

several years, however, EPA believes it necessary to proceed with

the program without ASTM approval for these alternative methods. 

Interested parties are also permitted to use their own preferred

measurement methods if they can demonstrate, to the Agency's

satisfaction, that these methods provide comparable accuracy to

those promulgated by EPA. In the case of vehicle testing, the

Agency recognizes that the required measurement precision may be

beyond the capability of a single test using either standard ASTM

methods or the methods promulgated by EPA. Such precision and

accuracy can be achieved through multiple fuel property

measurements or the use of more precise ASTM methods than are

standard. As discussed in Section G.2, the modest cost of

replicate fuel measurements or more precise measurement methods

is more than justified by the gain in modeling accuracy.

Commenters also objected to the requirement that carbon

dioxide be measured during vehicle testing. EPA considers this

information necessary to assure the quality of the test program. 

In particular, carbon dioxide data is necessary to evaluate the

fuel economy performance of vehicles being tested; unexpectedly

low fuel economy provides an indication of vehicle malfunction or

improper test procedures.

e. Vehicle Selection

Several commenters suggested that EPA allow test programs to

select vehicles at random from the in-use fleet; other commenters

recommended basing the distribution of vehicles on 1990 market

share alone. However, as discussed in Section G.3, the test

fleet composition must reflect the contribution of each type of

vehicle to the total emissions inventory. Selecting vehicles at

random from the in-use fleet would not achieve such composition

except by chance, and selecting vehicles based only on market

share would ignore differences in emission levels among vehicles. 

Further, EPA is concerned that petitioners may restrict their

vehicle acquisition efforts to those vehicles expected to respond

strongly to the fuel modifications being tested. EPA's test

fleet requirements limit petitioners' ability to manipulate the

outcome of test programs in this manner. Finally, a test fleet
263

based only on market share or based on random selection from the

in-use fleet would be unlikely to result in a sufficient number

of higher emitters for two reasons. First, 1990 technology

vehicles currently on the road are less likely to be higher

emitters than would be the case if the entire fleet consisted of

such vehicles, as is necessary to estimate the in-use impact of

gasoline formulations on emissions. Second, EPA has found that

owners of higher emitting vehicles are less willing to allow

their vehicles to be tested than are owners of normal emitters. 

For these reasons, EPA has decided to retain its test fleet

composition requirements instead of permitting random selection

of test fleets from the in-use fleet or basing its test fleet

requirements only on market share. EPA believes these

requirements assure an appropriate mix of technology types,

models, emitter classes, and engine displacements.

A number of commenters objected to the test fleet

requirements regarding higher emitters proposed in the April 1992

NPRM. EPA believes its current proposal incorporates these

comments where valid. As discussed in Section G.3, higher

emitters must be tested in order to evaluate the actual in-use

emission effects of fuel parameters. Such vehicles account for a

large fraction of in-use emissions, and the Complex Model

indicates that such vehicles respond differently to fuel

modifications than do normal emitters. This conclusion is

strengthened by the fact that each interim version of the Complex

Model showed higher emitters to respond differently than normal

emitters to fuel modifications. In response to comments and its

own revised analysis of higher emitters, EPA has eliminated the

requirement that higher emitters match the vehicle technology

distribution set forth in Table IV-62. As suggested by several

commenters, EPA has attempted to classify higher emitters by

failure mode in order to assure that the higher emitter test

fleet is representative of in-use higher emitters. However,

available data is not sufficient to allow such classification and

commenters did not submit such data to EPA. EPA asked for and

received comment on a proposal to allow intentional disablement

of normal emitting vehicles' emission control systems to simulate

higher emitters and reduce the cost of procuring a representative

test fleet. Most commenters opposed this option, arguing that

intentionally disabled vehicles would not be representative of

in-use higher emitters. In addition, EPA was unable to determine

an appropriate basis for such disablements, asw discussed above. 

One commenter expressed concern that higher emitters would be

much more difficult to locate once enhanced I/M programs are in

place. However, EPA's analysis of its I/M Repair Database

suggests that approximately one-fourth of the in-use fleet would

consist of higher emitters when enhanced I/M is in place. 

Further, 1990 technology vehicles currently on the road would

tend to be higher-mileage, higher-emission vehicles by the time

enhanced I/M programs in place, which should make acquisition of

higher emitters less burdensome.
264

Another commenter asked that EPA provide a list of

equivalent 1990 vehicles. EPA has not been able to provide a

comprehensive list of such vehicles but has included in Appendix

IV-F a list of the vehicles in the Complex Model database deemed

to have 1990-equivalent technology. Petitioners are encouraged

to coordinate their vehicle selection process with EPA and with

the vehicle manufacturers to assure that all included vehicles

qualify as 1990-equivalent technology vehicles.

f. Analysis method

Commenters expressed concern over a number of requirements

in EPA's previous proposals, such as the repeatability

requirement and the use of stepwise regression techniques. The

final requirements for vehicle testing do not include

repeatability requirements except insofar as the vehicle's

emission characteristics must be shown to be stable when tested

on the same fuel. The need for this requirement is discussed in

Section G.4 and Section A. Stepwise regression techniques have

been found to be necessary during the development of the Complex

Model, as discussed in Section A.4; in fact, one of the

commenters who objected to stepwise regression techniques used

such techniques in developing their own complex model. No

suitable alternative techniques were identified by commenters,

and EPA believes the analysis method required for augmentation

petitions sufficiently restricts the use of stepwise regression

techniques to prevent their mis-application.

Another commenter asked that EPA drop the requirement that

emission changes be shown within the first 50 miles of operation

upon being acquired for vehicle testing. This requirement has

been dropped, in part because the required preconditioning,

stabilization, and testing procedures may require greater than 50

miles of vehicle operation.

g. Nonexhaust Testing

EPA's April 1992 and February 1993 proposals allowed

augmentation of the nonexhaust model. However, EPA no longer

believes that such augmentations should be permitted for reasons

discussed in the preamble to this rulemaking. As a result,

comments regarding nonexhaust emission testing procedures are no

longer relevant.
265

H. Appendices

Appendix IV-A: The Random Balance Algorithm

Appendix IV-B: Glossary and Nomenclature

Appendix IV-C: MOBILE4.1 Input File Used to Develop the Simple

Model and the Phase I Complex Model (must be run

with interim version of MOBILE4.1)

Appendix IV-D: MOBILE5a Input File Used To Develop the Phase II

Complex Model

Appendix IV-E: SAS code used to develop "raw" exhaust emission

models

Appendix IV-F: Included 1990 Technology Vehicles in the Complex

Model Database
266

Appendix IV-A: The Random Balance Algorithm

The random balance algorithm was developed by H. T. McAdams of

the Advanced Computing Center of Argenta, Illinois. This

appendix is a user's manual developed by Dr. McAdams for the

application of this algorithm to the development and

simplification of the Complex Model. The mathematical

manipulations program that Dr. McAdams uses in all his work is

Matlab, such that the algorithm described below is given in the

context of Matlab language and instructions.

The random balance algorithm is useful for two purposes:

1)To determine the ranking of terms in the Complex Model in order

of their contribution to reduction of the residual sum of squares 

2)To consolidate equations for separate tech groups into one or

more equations yielding essentially the same outputs as the

unconsolidated model

1. RANDOM NUMBER GENERATION

The procedure begins with the generation of a set of N "random

blends." In previous applications, N has been taken as 2000. 

However, other values of N can be used, up to the RAM capacity of

the PC being used. 

1.1 Linear Terms

The starting point in the random-balance process is generation of

a matrix of random numbers. The matrix has N = 2000 rows and as

many columns are there are fuel variables (linear terms only) in

the model. For VOC, there are seven: oxygen, sulfur, RVP, E200,

E3OO, aromatics and olefins.

NOTE: It is important that the random numbers be drawn from a

uniform, not a normal, distribution. In the ACCA procedure, the

random numbers are uniform on the interval[-0.5, 0.5], but other

conventions could be used provided subsequent computations are

programmed consistent with the choice of the interval.

Matlab generates random numbers on the interval [0,I] by the

simple instruction

 x = rand(2000,7) (1)

This produces a 2000 x 7 matrix of numbers randomly distributed

between 0 and 1. To transform to the interval [-0.5,0.5], it is

necessary only to subtract 0.5 from all values of the matrix. 

In Matlab, this is done by the simple instruction 
267

 x = x - 0.5 (2)

Or, (1) and (2) can be combined to the single instruction

 x = rand(2000,7) - 0.5 (3)

It is well to check the resulting array for zero mean and unit

correlation matrix. Such a check can be done quickly and simply

by the instructions 

 meanx = mean(x) (4)

 corrcoefx = corrcoef(x) (5)

Meanx is a row vector for which all elements should be

approximately zero. Corrcoefx is a 7 x 7 matrix in which all

elements on the main diagonal should be 1, and all off-diagonal

elements should be approximately 0. Several types of plots can

be easily and quickly made to verify this, notably

plot(corrcoefx(:)) or bar(corrcoefx(:)).

1.2 Quadratic and Interaction Terms

The Complex Model potentially contains linear, quadratic and

first-order interaction terms. To augment the above random 

matrix, one needs to annex a set of columns representing squares

of the variables (7 columns) and another set of columns 

representing products of all variables taken two at a time (21

columns).

The square terms can be generated simply by the instruction x.*x. 

The dot after the first x causes each column to be multiplied by

itself row by row, rather than as an inner product.

A simple .m-file to generate all the interactions is intergen.m

(see below). It can be easily programmed in another language by

simply reproducing the loops shown.

Table IV-A-1

INTERGEN.M 

function y=intergen(x)

[r,c]=size(x);

for i=1:c, 

for j=i+1:c,

q=x(:,i).*x(:,j);

y=[y q];

end

end
268

The linear, square and interaction parts of the moment matrix can

be combined simply by writing

 ucentall = [x x.*x intergen(x)] (6)

The name ucentall is simply a label (anything else would do), but

it identifies the result as "all terms of a centered uniform

distribution."

As before, one should check the means and correlations and

possibly visualize the results as a line or bar plot before

proceeding further.

NOTE: Equation (6) will be used in another connection later on.

2. TRANSFORMATION TO REAL FUEL-VARIABLE QUANTITIES

The 2000 x 7 matrix generated above ranges from -0.5 to 0.5. We

need to convert these random numbers to corresponding values of

the actual parameters. For this purpose, the range [-0.5, 0.5]

has to be mapped into the corresponding actual range of the fuel

variables.

In previous application of the random-balance methodology, the

ranges of the seven variables were as follows:

Table IV-A-2

Fuel variable Minimum Maximum

Oxygen

Sulfur

RVP

E200

E300

Aromatics

Olefins

0

50

7

32

76

20

2

3.7

350

10

64

93

45

20

Other values can be used if desired; however, note that it is

assumed that all values within the specified range are equally

likely.

NOTE: In the EPA July 14, 1993 submission to the docket, the

"Limits of Data in the Complex Model Database" are slightly

different, but the only notable departure is that the upper limit

for sulfur is given as 450 rather than 350.

Changing the range [-0.5, 0.5] to the tabled ranges of the fuel

variables is a simple matter of linear transformation:
269

 y = x * (Max - Min) + (Max + Min)/2 (7)

Thus, for oxygen, the transformation is

 y = x * (3.7 - 0.0) + (3.7 + 0.0)/2 = 3.7 x + 1.85

Similarly, for sulfur, the transformation is

 y = x * (350 - 50) + (350 + 50)/2 = 300 x + 200

and so on.

The Matlab .m-file to perform this transformation is invtran4.m

and is listed below.

Table IV-A-3

INVTRAN4.M

 function y=invtran4(x)

 %where x is the 7-column matrix of scaled fuel parameter

 % and y is the corresponding matrix of raw fuel-parameter 

 %values

 yl=3.7*x(:,1)+1.85;

 %yl is oxygen

 y2=300*x(:,2)+200;

 %y2 is sulfur

 y3=3*x(:,3)+8.5;

 %y3 is RVP

 y4=32*x(:,4)+48;

 %y4 is E200

 y5=17*x(:,5)+84.5;

 %y5 is E300

 y6=25*x(:,6)+32.5;

 %y6 is aromatics

 y7=18*x(:,7)+11;

 %y7 is olefins

 y=[yl y2 y3 y4 y5 y6 y7];

 %Note: Terms are: oxygen sulfur rvp E200 E300 aromatics 

 %olefins

 %The e200 transformation is based on a range from 32 to 64

 %as derived by regressing e200 on t50 and evaluating at 170 

 %and 235.

 %The e300 transformation is based on a range from 76 to 93

 %as derived by regressing e300 on t90 and evaluating at 280 

 %and 360.

 

If ranges are changed, the .m-file would have to be edited to

change the affected equations. As an alternative, a general form

of the .m-file could be easily written with the ranges specified
270

as a 7 x 2 input matrix. Note, however, the ranges would have to

be input each time the transformation were invoked.

2.1 Centered Fuel Variables

The transformation outlined above (invtran4.m) transforms the

random numbers in the interval [-0.5, 0.5] into uncentered or raw

forms of the fuel variables. Later, the transformed values will

be used as inputs to model equations. Generally, the equations

in these equations apply to centered variables. That being the

case, it is necessary to center the outputs from invtran4.m

before using those outputs as inputs to candidate model

equations. This, of course, can be easily accomplished simply by

subtracting the center value for a given fuel parameter from all

2000 random values in the column representing that variable.

In Matlab, of course, this is a subtraction of a matrix of center

values from a matrix of random numbers. The .m-file centerit.m

performs this task, and is listed below. The "ones" and "kron"

operation simply put the center values into a conformable matrix

having the same dimensions as the matrix of random "raw" values

of the fuel variables.

Table IV-A-4 

CENTERIT.M

function y=centerit(x,c)

% where x is a matrix of RAW (UNCENTERED) fuel parameters

% c is a column vector of centering values

% and y is the corresponding matrix of CENTERED fuel

% parameters

[q,junk]=size(x);

wons=ones(q,l);

z=kron(c',wons);

y=x-z;

%This .m-file centers raw variables by subtracting

%centering values.

2.2 Uncentered Fuel Variables

There is no reason that the model equations have to be in

centered form. If the model coefficients apply to uncentered

fuel variables, then the centering transformation (by means of

centerit.m) would not be used.

3. COMPUTING EMISSIONS FOR THE RANDOM BLENDS

It is assumed that separate model equations have been developed

for each of the tech groups/emission classes. These equations
271

consist of a set of coefficients for 35 algebraic terms

consisting of 7 linear terms, 7 quadratic terms and 21

first-order interaction terms. Inasmuch as many of these terms

may not even have been included in the model, the excluded terms

will have zero coefficients. This fact in no way invalidates

what is to follow because the zero coefficients will simply

eliminate any contribution from the excluded terms.

It is important to note that the invtran4.m and centerit.m

transformations produce only the linear-term values for the

random blends. It is necessary, therefore, to generate the

quadratic columns of the moment matrix by squaring all entries in

the linear-term columns and annexing these 7 columns to the 7

columns representing the linear terms. Likewise, it is necessary

to compute all cross-products of the linear columns and to annex

these 21 columns to the 14 columns accumulated at this point. 

Note that this procedure is exactly the same as for the

untransformed random numbers in the interval [-0.5, 0.5]. Note,

also, that if raw or uncentered variables are used, a similar

operation would apply to the raw form of the fuel variables.

What remains is to evaluate each of the group equations for the

2000 random blends by substituting the fuel-parameter values for

each blend into the model equation for that group. In Matlab,

this is conveniently performed as a matrix multiplication, as

shown in the .m-file simple4.m listed below. Note that this

routine requires as inputs only the matrix of blends to be

evaluated and the matrix of model coefficients. This coefficient

matrix consists of 35 rows (one for each term in the equation)

and as many columns as there are tech groups and emission

classes. The routine has, built-in, the annexation of the

required quadratic and interaction terms as well as an

exponentiation step required to transform the results from log

space to grams/mile space.

Table IV-A-5

SIMPLE4.M

function y=simp1e4(x,c)

%where x is a matrix of the blends to be evaluated

%with x in raw, centered or standardized form

%and c is the matrix of the model coefficients

%with c consistent with the form of x

%Note: order of variables must be consistent

%with arrangement of coefficients in c

%For the EPA iteration4 full model, order of terms is:

% oxygen sulfur RVP E200 E300 aromatics olefins

x=(x x.rx intergen(x));

y=x*c;

Y=exp(y);

%Note: This is for models having no intercept given.
272

 

As employed in the past, the outputs from the above operation

were weighted and combined into a single set of 2000 quantities

considered as representing the final model output for the

unconsolidated model. Revision has to be made, however, to

express the model outputs in terms of percent change from a

reference or baseline fuel. For this purpose, there should be

one more blend in the array input as x. That blend should be the

reference or baseline blend to which the outputs of the random

blend are to be compared. It should be expressed in centered or

uncentered form in agreement with the random blends and should be

affixed as the last blend in the list. The simple4.m algorithm

will perform all necessary computations for this blend, just as

it does for the 2000 or so random blends.

To compute the percent change from baseline, one needs to divide

the unscaled grams/mile for every number in a column by the last

number in that column. That gives the ratio of the emissions for

the target fuel to the emissions for the reference fuel. These

numbers then need to be subtracted from 1.0 and multiplied by 100

to yield a percent change from the reference fuel.

The operations described can be executed in Matlab as follows.

First, using the 2001 blends (random 2000 augmented by the

reference blend), execute the .m-file below.

Table IV-A-6

CHANGEI.M 

function y = change(x)

(r,c]=size(x);

q=kron(ones(r,l),x(r,:);

Y=(x./q ); 

This .m-file transforms all computed emissions into

corresponding ratios to the emission for the reference blend as

evaluated for each vehicle group. For the subsequent

computation of term contributions to the sum of squares, it is

not appropriate to express the output as percent change. Many of

the percent changes will be negative, and if one attempts to fit

a regression equation to such data, one will encounter logarithms

of negative numbers and the output will be in complex numbers. 

Rather, one must compute the percent changes from the final

reqression equation in the same way that they are computed for

the vehicle group equations in the unconsolidated model.

4. COMPUTING TERM CONTRIBUTIONS TO THE MODEL SUM OF SQUARES
273

Completion of the steps above yields emissions relative to the

baseline fuel for the 2000 random blends for each of the

technology groups or emission classes. The baseline fuel is also

included at this point, but should be deleted from the array for

what follows.

We need to fit the 2000 outputs for each of the vehicle groups to

a model consisting of the quasi-orthogonal fuel variables, as

represented in the matrix ucentall. This matrix consists of 35

columns and 2000 rows, the columns representing the union of the

linear, quadratic and interaction terms. For the purpose of

examining the relative contributions of terms, we need to square

each of the regression coefficients and divide by an appropriate

normalizing factor. This normalizing factor is the corresponding

diagonal term obtained from the matrix product ucentall*ucentall. 

Some further computations are required to express the term

contributions in percent of cumulative percent, and, of course,

some bookkeeping and display niceties have to be performed. 

The basic operation is that of multiple regression. Any

suitable regression program would suffice, but in the Matlab

environment it is convenient to use a .m-file called reggaer.m. 

(See Appendix IV-A.1)

However, as written, this .m-file would compute the regression

coefficients for only one column of input values. Consequently,

another .m-file was written to cycle the computation through all

columns (i.e., all vehicle groups). At the same time, the

program combines the group outputs into a composite output and

computes the regression equation for this composite also. This

.m-file is called sumvoc.m and is listed below.

Table IV-A-7

SUMVOC.M

function [A,C,LIST,SPART]=sumvoc(x,y,wdiag,list,wts) 

y=[y y*wts'];

 [qr,qc]=size(y); 

 LIST=list;

for i=1:qc,

 [a,c,list,spart]=doitall(x,log(y(:,i)),wdiag,list);

 A=[A;a];

 C=[C c];

 SPART=[SPART spart];

end 

The routine incorporates another .m-file called doitall.m, which,

in turn, incorporates the regression program reggaer.m. The file

called doitall.m is listed below.
274

Table IV-A-8

DOITALL.M

function [a,c,list,spart]=doitall(x,y,wdiag,list)

[tpart,apart,f,rr]=reggaer(x,y);

t=tpart(2:36,1);

wdiag=wdiag(2:36,:);

anov=t.*t.*wdiag;

anovper=1OO*anov/sum(anov); 

[h,k]=sort(anovper);

h=h(35:1:1);

k=k(35:-1:1);

cumh=cumsum(h);

a=[sum(anov) apart(2,1) rr];

c=[t anov anovper];

list=list(k,:);

spart=[k h cumsum(h)];

First, let us explain the outputs of some of the applicable

.m-files.

The .m-file reggaer.m can be thought of as an acronym for:

REGression Good And Easy with R-square

Its outputs are:

t-part A listing of the regression coefficients, their

standard errors and their t-values

a-part An analysis of variance showing model, residual and

total sums of squares, degrees of freedom and mean

squares

f The f-ratio for the model

rr The r-square for the model

The routine doitall.m augments reggaer.m by incorporating the

operation of squaring and normalizing regression coefficients, as

required to determine the relative contributions of terms. Note

that, for this purpose, it requires as input the diagonal

elements of ucentall*ucentall. Also required as input is an

alphanumeric listing of the terms. This is the input called

list.

The routine called sumvoc.m simply calls doitall.m repeatedly,

once for each vehicle group, includinq the composite group. How

does the composite get in there? As a result of the first line of

code: y = [y y*wts]. This instruction says "Annex to the
275

columns for the vehicle groups one more, which is just the

weighted combination of the ones you already have." To execute

this instruction, of course, it is necessary to input the

weights, as indicated in the .m-file calling sequence.

Note that all that is required is to invoke sumvoc.m. It is not

necessary to be concerned with the inner details of what has been

discussed above. It is important, however, to have all the

inputs:

x This is a matrix of 2000 rows and 35 columns. The rows

are the blends; the columns are the linear, quadratic

and interaction terms. For the present application, it

is simply the matrix ucentall as developed at the

outset of this manual

y This is the set of emissions or relative emissions for

the vehicle groups, as computed by simple4.m or as

modified by change.m.

wdiag This is a column vector consisting of the normalizing

factors obtained by multiplying ucentall*ucentall

list This is a string variable giving a list of the terms

represented by the 35 columns of the x-matrix.

wts This is a row vector of the weighting factors for the

vehicle groups.

The program sumvoc.m is, among other things, a summarizing

program. Its outputs, as specified in the code, are: A, C, LIST

and SPART. These are explained below:

A Consists of three columns and as many rows as there are

vehicle groups. The first column is the sum of the

cont n'butions of the term sums of squares for each of

groups. The second column is the total sum of squares

as computed by the ANOVA part of reggaer.m. The third

column is the correlation coefficient for the vehicle

group. It will be ideally 1 for all but the last row,

which represents the composite model and is an

approximation. Usually it will be well above 0.99.

C This matrix consists of 35 rows and three times as many

columns as there are vehicle groups. The first column

of each set of three consists of the regression

coefficients for the corresponding vehicle group. The

second column of each set of three consists of the

actual contributions to the sum of squares for the

various terms. The third column of each set of three

expresses these contributions as percent of the total

sum of squares.
276

LIST LIST is just that: a listing of the model terms in the

order in which they were entered in the model.

SPART This, like C, is a matrix of 35 rows and three times as

many columns as there are vehicle groups. This output

summarizes the results of sorting contributions to sums

of squares in decreasing magnitude and gives a

cumulative view. The first column is simply a listing

of the term numbers as ordered according to decreasing

contribution to the sum of squares. The second column

gives the percent contributions of the ordered terms,

and the third column gives the cumulative percent

totals.

At this point all the quantities of interest have been computed. 

However, the display and presentation of results leaves something

to be desired. Therefore, a so-called "script" .m-file was

written for this purpose; it is called compsum5.m (see Appendix

IV-A.2). Note that it requires no inputs; one simply types

compsum5 and presses Enter. The output is a formatted display of

results in a form which permits easy interpretation.

For compsum5.m to operate, however, the results of the previous

computation from sumvoc.m must be available. Also, those outputs

must be specifically labeled: a, b, c, d. Therefore, if

compsum5.m is going to be used, one must call for sumvoc.m as

follows: [a,b,c,d]= sumvoc( $,$$,$$$,$$$$,$$$$$), where $, $$,

$$$, $$$$, and $$$$$ are the names that have been given to x, y,

wdiag, list and wts, respectively. In other words, the input

quantities can be given any names appropriate to identify their

origin, but the output quantities must be labeled a, b, c and d

if compsum5.m is going to be used for display. 

5. COMPUTING THE FINAL MODEL EQUATION

After the term contributions have been reviewed and a decision

has been made as to what terms are to be retained, the original

data are refitted to an equation of the selected form and a set

of revised vehicle-group equations are returned.

The steps above are usually repeated, but the main objective is

the final, composite equation. However, this equation needs to

be put in terms of either centered or uncentered coefficients,

not coefficients for the quasi-orthogonal terms used to compute

term contributions.

Centered coefficients can be computed simply by fitting the

final, composite relative emissions to the desired terms. Any

suitable regression program can be used.
277

Using reggaer.m, one can compute the centered coefficients by the

following code:

Table IV-A-9

[tcent,acent,fcent,rcent]=

reggaer([xcent xcent.*xcent intergen(xcent)],

log(yvoc*wtsvtox'))

where yvoc is the final set of computed emissions for the

composite, unconsolidated model and wtsvtox is a row matrix of

weighting factors for the vehicle groups.

If one desires the uncentered coefficients, simply change the

above code to:

Table IV-A-10

[traw,,arawt,fraw,rraw]=

reggaer([xraw xraw.*xraw intergen(xraw)],

log(yvoc*wtsvtox'))

Percent change for a target blend can then be computed by

computing the yield for the target and for the baseline blend

using the equation:

 1OO*{[(Target yield)/(Baseline yield)] - 1}.

6. SOME CAVEATS

The procedures outlined above are tailored to a data set in which

there are seven fuel variables and a total of 35 terms to be

considered. If fewer terms are to be included in the model, the

extraneous terms can be assigned zero values. However, in the

case of toxics, no interaction terms are involved; consequently,

it may be cumbersome to carry along extra columns in the matrix. 

A simpler version of the appropriate .m-files can be used with

suitable modification. On the other hand, some of the toxics

have more than seven variables (such as separate terms for MTBE,

Ethanol, ETBE and TAME). In these cases, it will be necessary to

start with a larger matrix of random input values.

It is, of course, possible to put all of the above computations

into a very genera1 form which would accomodate all cases, but

that has not been done at this point. Such genera1ization would

have both advantages and disadvantages. It would make for a

unified approach, but it might necessitate carrying along a large

number of irrelevant quantities. Suggestions on this point are

solicited.
278

H. T. McAdams

Advanced Computing Center of Argenta

Argenta, Illinois

8-31-93
279

Appendix IV-A.1: GENERAL REGRESSION ROUTINE

%This .m-file computes the regression equation - i.e., intercept

%and slopes, and computes t for testing the significance of the

%slopes of the regression line against the null hypothesis

%that each slope = 0.

%It also provides an analysis of variance, an f-ratio and r

square.

%The ANOVA gives sum of squares, degrees of freedom

%and mean squares for the mean, regression and residuals.

function [tpart,apart,f,rr]=reggaer(x,y)

 [u,v]=size(x);

 x=[ones(u,1) x];

 tt=x'*x;

 q=inv(tt);

 b=q*x'*y;

%b is the vector of regression coefficients: intercept and slope

 z=y-x*b;

 [h,k]=size(b);

 t1=z'*z;

%tl is the residual sum of squares

 t2=u-h;

%t2 is the residual degrees of freedom

 t3=t1/t2;

%t3 is the residual mean squares

 z=z/(u-h);

%z is the error variance for the regression line

 varb=t3*q;

%varb is the variance of the regression coefficients.

stdb=sqrt(diag(varb));

t=abs(b./stdb);

s1=y'*y;

%sl is the totel sum of squares

[q,r]=size(y);

 s2=q;

%s2 is the total number of degrees of freedom

 s3=s1/s2;

%s3 is the total mean squares

 q1=sum(y)*sum(y)/q;

%ql is the sum of squares for the mean

 q2=r;

%q2 us the degrees of freedom for the mean

 q3=ql/q2;

%q3 is the mean squares for the mean

 w1=b'*x'*y-q1;

%wl is the regression sum of squares

 w2=h-q2;

%w2 is the regression degrees of freedom

 w3=w1/w2;

%w3 is the regression mean squares

 f=w3/t3;
280

sumsq=[q1 w1 t1 s1]';

df=[q2 w2 t2 s2]';

meansq=[q3 w3 t3 s3]';

b=b';

stdb=stdb';

t=t';

sumsq=sumsq';

df=df';

meansq=meansq';

tpart=[b' stdb' t'];

apart=[sumsq' df' meansq'];

f=f;

rr=w1/(w1+t1);
281

Appendix IV-A.2: SCRIPT FILE FOR DISPLAYING RANDOM BALANCE

OUTPUT

Note: This display is constructed for 10 vehicle groups. As

used, the 8th group is a dummy. 

COMPSUMS.M

sp= ";

al='The following compares the model sum of squares ';

a2='as computed as a weighted sum of coefficients squared';

a3='(first column) with the model sum of squares';

a4='computed from regular ANOVA (second column)';

aa='Third column is R-square';

disp(al)

disp(a2)

disp(a3)

disp(a4)

disp(aa)

disp(sp)

a(:,1:3)

aS='The following displays, for each of the groups';

a6='the regression coefficients (column 1)';

a7='the termwise contributions to model sum of squares (column

2)';

a8='the percent termwise cont. to model sum of squares (column

3)';

a9='Order of terms is as follows:';

disp(sp)

disp(a5)

disp(a6)

disp(a7)

disp(a8)

disp(a9)

disp(sp)

disp(c)

disp(sp)

gl='Group 1';

disp(g1)

b(:,1:3)

g2='Group 2';

disp(g2)

b(:,4:6)

g3='Group 3';

disp(g3)

b(:,7:9)

g4='Group 4';
282

disp(94)

b(:,10:12)

g5='Group 5';

disp(g5)

b(:,13:15)

g6='Group 6';

disp(g6)

b(:,16:18)

g7='Group 7';

disp(g7)

b(:,19:21)

g8='Group 8';

disp(g8)

b(:,22:24)

g9='Group 9';

disp(g9)

b(:,25:27)

g10='Group 10';

disp(g10)

b(:,28:30)

g11='Weighted Composite';

disp(g11)

b(:,31:33)

w3='The following gives, for each group, the term number';

w4='ranked in decreasing order of importance (column 1)';

w5='the percent contribution to model sum of squares (column 2)';

w6='and the cumulative percent contribution to 

model SS (column 3)';

w7='followed by an ordered listing of the term names';

disp(w3)

disp(w4)

disp(w5)

disp(w6)

disp(w7)

disp(sp)

a10=c;

hl='Group 1';

disp(hl)

d(:,1:3)

a10(d(:,1),:)

h2='Group 2';

disp(h2)
283

d(:,4:6)

a1O(d(:,4),:)

h3='Group 3';

disp(h3)

d(:,7:9)

a10(d(:,7),:)

h4='Group 4';

disp(h4)

d(:,10:12)

a1O(d(:,10),:)

h5='Group S';

disp(h5)

d(:,13:15)

alO(d(:,13),:)

h6='Group 6';

disp(h6)

d(:,16:18)

alO(d(:,16),:)

h7='Group 7';

disp(h7)

d(:,19:21)

alO(d(:,19),:)

h8='Group 8';

disp(h8)

d(:,22:24)

alO(d(:,22),:)

h9='Group 9';

disp(h9)

d(:,2S:27)

alO(d(:,2S),:)

hlO='Group 10';

disp(hlO)

d(:,28:30)

alO(d(:,28),:)

hll='Weighted Composite';

disp(hll)

d(:,31:33)

alO(d(:,31),:)
284

Appendix IV-B: Glossary and Nomenclature

BZV% Volume percent of benzene in the fuel

DVOC Total grams per mile of volatile organic compounds from

diurnal emissions

EtOH Ethanol

GM General Motors

HDGV Heavy-duty gasoline vehicle

HDV Heavy-duty vehicle

HSVOC Total grams per mile of volatile organic compounds from

hot soak emissions

I&M Inspection and maintenance; also IM, I/M

LDGT Light-duty gasoline truck

LDGV Light-duty gasoline vehicle; see LDV

LDT Light-duty truck

LDV Light-duty vehicle, equivalent to light-duty car

MTBE Methyl tertiary-butyl ether

POM Polycyclic organic matter

RFG Reformulated gasoline

RFVOC Total grams per mile of volatile organic compounds from

refueling emissions

RLVOC Total grams per mile of volatile organic compounds from

running loss emissions

OXY Total oxygen content of fuel in terms of weight percent

OLE Olefins content of fuel in terms of volume percent

SUL Sulfur content of fuel in terms of parts per million by

weight

ARO/AROM Aromatics content of fuel in terms of volume percent

E200 Percent fuel distilled at 200o

F

E300 Percent fuel distilled at 300oF

BEN Fuel benzene content in terms of volume percent

RVP Reid vapor pressure in terms of psi

VMT Vehicle miles travelled

VOC Volatile organic compounds, measured in grams per mile

on a nonmethane, nonethane basis

A,B = Generic fuel parameters

At,Bt = Generic fuel parameters for a target fuel

Ab,Bb = Generic fuel parameters for a baseline fuel

Aet = Value of generic fuel parameter A at the end of

the allowable range

Bet = Value of generic fuel parameter B at the end of

the allowable range

Ci = Average emissions of any pollutant from vehicle

group i

Ei = Unknown gram/mile emissions for vehicle group i,

resulting from statistical regressions that

disregard intercept terms

Ei(t) = Unknown gram/mile emissions for vehicle group i

for a specific target fuel
285

Ei(b) = Unknown gram/mile emissions for vehicle group i

for a specific baseline fuel

fi = Sum of fuel terms * coefficients for vehicle

group i for any fuel

fi(t) = Sum of fuel terms * coefficients for vehicle

group i where the fuel terms represent a

specific target fuel

fi(b) = Sum of fuel terms * coefficients for vehicle

group i where the fuel terms represent a

specific baseline fuel

f(t) = Second or first order function of fuel

parameters for a target fuel

f(b) = Second or first order function of fuel

parameters for a baseline fuel

ki = Proposed adjustment factor for vehicle group i

Pj = Any Complex Model fuel parameter

Wi = Proposed weighting factor for vehicle group i

wi = Final weighting factor for vehicle group i

X = Fleet average grams/mile of any pollutant for

any fuel

X(t) = Fleet average grams/mile of any pollutant for a

specific target fuel

Xi(t) = Grams/mile of any pollutant for a specific

target fuel for vehicle group i

X(b) = Fleet average grams/mile of any pollutant for a

specific baseline fuel

Xi(b) = Grams/mile of any pollutant for a specific

baseline fuel for vehicle group i

Y = Fleet average performance of any pollutant for

any fuel

Y(t) = Fleet average performance of any pollutant for a

specific target fuel

Yi(t) = Performance of any pollutant for a specific

target fuel for vehicle group i

Y(b) = Fleet average performance of any pollutant for a

specific baseline fuel

Yi(b) = Performance of any pollutant for a specific

baseline fuel for vehicle group i

Y = Emissions of any exhaust pollutant in percent

change from a baseline fuel

Y(t) = Emissions of a generic exhaust pollutant from a

target fuel

Y(b) = Emissions of a generic exhaust pollutant from a

baseline fuel

k = Coefficient determined through statistical

regressions

* = Denotes a multiplication symbol. For example,

A*B means the quantity A multiplied by the

quantity B
286

Appendix IV-C: MOBILE4.1 Input File Used to Develop the Simple

Model and the Phase I Complex Model (must be run

with interim version of MOBILE4.1)

1 PROMPT - 

MOBILE4.1 v.7/11/91: Simple Model correlations 

1 TAMFLG - 

1 SPDFLG - 

1 VMFLAG - 

1 MYMRFG - 

1 NEWFLG - 

2 IMFLAG - enter I/M program 

1 ALHFLG - 

2 ATPFLG - enter ATP

2 RLFLAG - Stage II refueling controls

2 LOCFLG - enter LAP record once

1 TEMFLG - 

3 OUTFMT - print 112 column descriptive output format 

4 PRTFLG - print exhaust HC, CO and NOx results 

1 IDLFLG - 

3 NMHFLG - print VOC 

3 HCFLAG - print HC components 

83 20 68 20 00 00 100 1 1 2221 2 11 20 20 20

83 68 20 2221 11 100. 11111212

89 1 086 086

RegNeg C 71.6 91.6 11.5 08.7 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 08.5 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 08.3 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 08.1 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 07.9 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 07.7 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 07.5 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 07.2 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg C 71.6 91.6 11.5 07.0 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 08.7 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 08.5 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 07.8 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 07.6 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 07.4 89 1
287

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 07.2 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 07.0 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 06.8 89 1

1 15 19.6 75.0 20.6 27.3 20.6

RegNeg B 69.4 94.0 11.5 06.6 89 1

1 15 19.6 75.0 20.6 27.3 20.6
288

Appendix IV-D: MOBILE5a Input File Used To Develop the Phase II

Complex Model

1 PROMPT -

Phase II Complex Model baseline runs for LDGVs & LDGTs

1 TAMFLG -

1 SPDFLG -

1 VMFLAG -

1 MYMRFG -

5 NEWFLG - no CAA mandates are modeled

2 IMFLAG - enter I&M program

1 ALHFLG -

8 ATPFLG - enter ATP; include pressure and purge checks

2 RLFLAG - enter Stage II

1 LOCFLG -

1 TEMFLG -

3 OUTFMT - print 112 column descriptive output format

1 PRTFLG - print exhaust & evap HC only

1 IDLFLG - 

3 NMHFLG - print VOC

2 HCFLAG - no HC components

83 20 68 20 03 03 096 1 1 2221 4211 0.80 20.0 2.00 Enhanced IM

83 84 20 2221 11 096. 12211111 ATP

83 83 20 2221 11 096. Pressure test

83 86 20 2221 11 096. Purge test

89 1 80. 60. Stage II

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 09.9 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 09.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 09.5 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 09.3 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 09.1 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 08.9 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 08.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 08.5 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 08.3 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 08.1 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 07.9 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 07.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 07.5 90 1 1 1
289

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 07.3 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 07.1 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 06.9 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 06.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ C 71.6 91.6 09.5 06.5 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 09.9 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 09.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 09.5 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 09.3 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 09.1 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 08.9 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 08.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 08.5 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 08.3 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 08.1 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 07.9 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 07.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 07.5 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 07.3 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 07.1 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 06.9 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 06.7 90 1 1 1

1 15 19.6 87.0 20.6 27.3 20.6 1

................ B 69.4 94.0 09.5 06.5 90 1 1 1
290

Appendix IV-E: SAS code used to Devlop Raw Exhaust Emission

Models
291

Appendix IV-F: Included 1990 Technology Vehicles in the Complex

Model Database

The list below shows the 1990 technology vehicles that are

currently in the complex model database used to develop the

exhaust models shown in Section A.
 51Bonner and Moore Management Science, "Study of the

Effects of Fuel Parameter Changes on the Cost of Producing

Reformulated Gasoline," Prepared for EPA under contract through

Southwest Research Institute and the National Institute for

Petroleum and Energy Research. This data was made available to

the public through the following document: "DOE and API Phase

II Cost Estimates," EPA Memorandum from Lester Wyborny, FSSB,

to the Air Docket, November 4, 1993. The Bonner and Moore work

performed for this analysis was based on a revised version of

the model used to generate costs for the draft RIA. This new

version includes provisions to prevent dumping of fuel

components into conventional gasoline.

292

V. Environmental and Economic Impact of Phase I Reformulated

Gasoline

The Phase I reformulated gasoline standards consist of two

fuel specifications (maximum benzene content and minimum oxygen

content) and three performance standards applying to VOC, toxics

and NOx emissions reductions required of reformulated fuels from

1995-1999. After 1999, the more stringent Phase II emission

performance standards, discussed in Section VI, take effect. 

EPA's April 1992 reformulated gasoline proposal extensively

discussed the development of the Phase I simple model standards. 

Phase I complex model standards and other Phase I issues were

discussed in the February 1993 proposal. Comments on and any

further developments of the Phase I standards, either under the

Simple or Complex Models, were discussed in Sections 2 and 4

above. This section presents both the costs and benefits of the

Phase I standards. 

A. Introduction

1. Phase I Fuel Control Costs 

The cost to produce Phase I RFG was determined for Regions

1, 2 and 3 through the recent refining cost analysis done by

Bonner and Moore (B & M).51 Unlike the Phase II data, individual

costs for each parameter change (added oxygenate, reduced benzene

and reduced RVP) were not determined in the B & M cost analysis. 

The cost of the phase I RFG program was calculated in one step

for all three parameter changes. Because the RFG specifications

differ between summer and winter, the B & M refinery model runs

separate summer and winter optimizations off the same base of

capital equipment. For accounting purposes, the model allocates

all the capital costs only to the winter. This produces

appropriate and accurate estimates of annual average costs, but

makes it difficult to develop separate winter and summer costs. 
293

Therefore, the winter and summer costs are shown averaged

together here and represent an annual average per gallon cost.

The costs developed below exclude the cost of oxygenates

already required to be used in winter oxyfuel areas. This was

done because the winter oxyfuel program began prior to the RFG

program and because this oxygenate produces substantial CO

emissions reductions which justify the cost of the oxygenate. 

The first column in Table V-1 below summarizes the

manufacturing costs estimated by the refinery model of producing

Phase I RFG. In the adjacent columns of that table, the capital

portion of these costs were then adjusted to reflect a 10 percent

rate of return on capital from a 15 percent basis. In Table V-2 

further below, the costs were further adjusted to account for the

change in fuel's heat content; the fuel economy effects were due

to the added oxygenates and reduced RVP. The effect of fuel

composition on vehicle fuel economy is addressed in the analysis

of the Phase II standards in Section VI.

Table V-1: Phase I RFG Costs Based on 10% ROI 

Region Unadjusted

Phase I

Costs (15%

ROI) (/gal)

Capital

Cost

(MM$)

Capital Cost 

at 10% and

15% ROI

 (/gal)

Adjusted

Phase I

Costs (10%

ROI)(/gal)

Region 1 3.34 475 15% 0.93

10% 0.71

 3.12

Region 2 1.96 586 15% 1.00

10% 0.75

 1.71

Region 3 3.12 1726 15% 1.31

10% 0.99

 2.80

Table V-2: Phase I RFG Costs Including Fuel Economy Effects 

Region Adjusted

Phase I

Refinery 

Costs

(/gal)

Fuel

Economy

Effect

 (%)

Fuel Economy

Effect Cost

 (/gal)

Total 

Phase I

Costs 

(/gal)

Region 1 3.12 1.20 1.02 4.14

Region 2 1.71 1.89 1.61 3.32

Region 3 2.80 1.84 1.56 4.64
294

Given the mandate for at least 2.0 volume percent oxygen,

the cost of producing Phase I RFG is partially determined by the

cost of adding oxygenates. The cost of oxygenate addition,

however, is largely driven by the purchase cost of the oxygenate,

or the raw materials used in producing the oxygenate. When the B

& M model was being set up to estimate the RFG program costs, the

oxygenate costs were programmed into the model based on the

expectations for the future market of oxygenate demand and supply

at that time. However, recent indications are that the oxygenate

costs may vary significantly from these earlier estimates and

that the cost of producing Phase I RFG should reflect these

varying oxygenate costs. Furthermore, much of the ethanol that

the model estimated would be blended into RFG was done so at an

unsubsidized cost (retail cost without the 54 c/gal subsidy). An

unsubsidized ethanol cost was used because, at that time, ethanol

blends under 10 percent ethanol were not permitted to take

advantage of the subsidy. Since then, the subsidy policy has

been modified and ethanol blends at less than 9 volume percent

are eligible for the excise tax credit. EPA is therefore

adjusting these costs to reflect the tax credit available to all

ethanol blends. 

All of the oxygenate cost projections were made by B & M in

a period of strong growth in oxygenate demand and when the

possibilities of supply just meeting demand were real. Thus, the

B & M projections tend to be quite high in today's terms. For

example, B & M projected a merchant MTBE price of $1.05/gal. 

Despite this being the beginning of the 1993-94 winter oxyfuel

season, MTBE has been selling for a few months on the spot market

for $0.66-0.75/gal. The summer runup in prices which occurred

during 1992 while refiners built up inventories for the winter

never materialized in 1993. The same could happen again with the

onset of the reformulated gasoline program. Oxygenate prices

could be relatively high in late 1994 and early 1995 and then

fall back to more reasonable levels. To account for this, a

range of MTBE and methanol prices is being used, as shown in the

table below. The low end of the ranges reflect today's low

energy prices and ample oxygenate supply. The high end of the

ranges are those projected by B & M. 

For ethanol, B&M projected the historical figure of

$1.20/gal, prior to consideration of the tax credit. This price

allows ethanol to be competitive as a gasoline extender and

doesn't reflect its octane or oxygenate value. During the summer

of 1992, ethanol prices reached $1.40/gal and higher. Recently,

with wholesale regular gasoline prices in the mid-40's per

gallon, ethanol has been selling for $1.00-1.05/gal. To be

consistent with the MTBE projections, the range of $1.20-1.60/gal

will be used here, or $0.66-1.06/gal after factoring in the

$0.54/gal excise tax credit. These are plant gate prices and

generally can be used as is throughout the Midwest. However, use

in reformulated gasoline, either directly or in producing ETBE,
295

outside the Midwest would involve a significant shipping cost. 

To account for this, distribution costs for shipping to the

Northeast and Gulf coast of 5/gal were added onto the price of

ethanol, respectively.

Regarding other oxygenates, TAME was not purchased in the

refinery modeling, but was produced within the refinery. Thus,

the range of methanol prices is adequate to describe its

potential cost to refiners. Also, neither ETBE production nor

purchase was considered given the technological and economic

uncertainties existing at the time of the study. In order to be

utilized in significant quantities, ETBE would have to be

competitive with MTBE and ethanol, and would thus yield roughly

equal or lower costs than those determined below. Table V-3 

below summarizes the oxygenate prices used in the model and the

oxygenate price range established by EPA. 

Table V-3: Oxygenate Costs used in the Phase I Analysis

Oxygenate Model Costs Cost Range

Ethanol $1.20 Before Subsidy $1.20 - $1.60

After Subsidy $0.66 - $1.06

MTBE $1.05 $0.80 - $1.05

Methanol $0.57 $0.40 - $0.57

The Phase I costs for Regions 1, 2 and 3 shown in Table V-2

were then adjusted to reflect the range of possible oxygenate

costs. The results are summarized in Table V-4. The regional

Phase I cost estimates were combined into a U.S. cost by

weighting each regional cost by the fraction of RFG produced by

that region (see Table VI-# in Section VI).

Table V-4: Final Phase I RFG Costs

Geographic Area Cost Range

 (c/gal) 

Region 1 2.6 - 4.1 

Region 2 2.3 - 6.5

Region 3 3.5 - 4.6

U. S. 3.0 - 4.9 (3.9 average)
296

Total annual cost to the nation would simply be the cost per

gallon from Table V-4 multiplied by the fuel consumption in the

reformulated gasoline areas plus any spillover into adjacent

areas. The Energy Information Agency projects total national

motor gasoline consumption to be 113.9 and 119.8 billion gallons

per year in 1995 and 2000, respectively. Interpolating, the

estimate for 1998 would be 117.5 billion gallons per year. In

the draft RIA for the February NPRM, reformulated gasoline was

estimated to represent 32.1 percent of national fuel consumption,

including a 10% spillover rate. (Of this total, 13.3% was in

Class B areas and 18.8% was in Class C areas.) Combining these

figures yields a total annual cost of $1.13-1.85 billion.

2. Emissions Reductions

In-use emission reductions for calendar year 1998 were

determined using both MOBILE5.0 and the complex model. Emission

reductions were estimated under both basic and enhanced I/M

scenarios because both of these I/M programs will be in place in

the 1995-1999 period. MOBILE5.0 was used to estimate baseline

VOC emissions and the effect of RVP on non-exhaust VOC emissions,

as was done in the Draft RIA. The complex model was used to

estimate the effect of fuel composition on exhaust VOC emissions. 

Derivation of the in-use baseline VOC emission projections is

described in more detail in Section III.B of the Draft RIA and

the baselines themselves are shown in Tables A1-A4 of that

section of the DRIA. 

Table V-5: 1998 In-Use Baseline VOC Emissions (g/mi)

Exhaust VOC Nonexhaust VOC Total VOC

Basic I/M Program

 Region 1 1.456 0.816 2.272

 Region 2 1.449 1.006 2.455

Enhanced I/M Program

 Region 1 0.991 0.570 1.561

 Region 2 0.991 0.681 1.672

Assuming fuels meeting the averaging requirements for Phase

I RFG under the Simple Model, and the effects of oxygen addition

and RVP and benzene reduction on other fuel parameters, as

developed in Section VI, the Phase I fuel compositions shown in

Table V-6 were developed.
297

Table V-6: Baseline and Phase I In-Use Fuel Compositions 

In-Use Baseline 

Fuel

Phase I In-Use Fuels

Fuel Parameter Region 1 Region 2

Oxygen 0.0 2.1 2.1

Sulfur 339 309 309

RVP (psi) 7.8/8.7(Region 1/2) 7.1 8.0

E200 (vol%) 41.0 46.7 46.7

E300 (vol%) 83.0 84.9 84.9

Aromatics (vol%) 32.0 25.5 25.5

Olefins (vol%) 9.2 13.1 13.1

Benzene (vol%) 1.53 0.95 0.95

The Phase I complex model was used to evaluate the effect of

these fuels on VOC emissions. The resulting percent reductions

were then applied to the baseline VOC emissions shown above. The

results are shown in Table V-7.

Table V-7: 1998 In-Use Phase I RFG VOC Emissions (g/mi)

Exhaust VOC Nonexhaust VOC Total VOC

Basic I/M Program

 Region 1 1.300 0.617 1.917

 Region 2 1.294 0.765 2.059

Enhanced I/M Program

 Region 1 0.886 0.443 1.330

 Region 2 0.886 0.535 1.421

The differences in the VOC emissions of Tables V-5 and V-6

represent the benefits of the Phase I RFG program. No

substantial NOx emission reduction is expected. To convert the

g/mile emission reductions to annual tons, a 1998 national fuel

consumption of 113.84 billion gallons was assumed, along with an

average gasoline vehicle fuel economy of 20.58, from the

MOBILE4.1 fuel consumption model. It was also assumed that RFG

would be sold in the 9 mandated areas plus those areas which had

opted in by mid-summer 1993. The result is that approximately
298

18.2 and 12.8 percent of national fuel consumption will be

reformulated gasoline in Class C and B areas, respectively. 

A significant issue is the calculation of the VOC emission

reduction. The VOC controls for reformulated gasoline only apply

in the summer, or high ozone season. Most other VOC control

programs apply yearround, due to the permanent nature of the

controls (e.g., modified painting facilities, motor vehicle

control, I/M programs, etc.). The effectiveness of these

programs is typically reported on an annual VOC control basis;

that is, the emission reductions estimated to occur include VOC

emissions reduced in the winter as well as the summer, even

though the winter VOC emission reductions have little ozone

related value. In order to be comparable with these programs,

the benefits of RFG must be put on an annual basis. This means

extending the real benefits occurring in the summer to the rest

of the year. This is appropriate since the RFG summer VOC

emission benefits provide the same in-use ozone reductions as a

yearround program which reduces summer emissions to the same

degree but also reduces emissions in the winter. To do this, the

gram per mile emission reductions were applied to yearround fuel

consumption.

Table V-8: VOC Emission Reductions of Phase I RFG

(annualized tons/yr)

Basic I/M Enhanced I/M

Class B 118,000 77,000

Class C 187,000 119,000

Total 305,000 196,000

Phase I RFG also reduces cancer incidence due to the

reduction in air toxics emissions required. Section VI outlines

a methodology for estimating baseline and controlled toxics

emissions from MOBILE5 and the complex model. It also outlines a

methodology for converting emissions of air toxics into cancer

incidence. That methodology was used here. The analysis of the

Phase II RFG standards in Section VI also presents a cancer

incidence reduction associated with the Phase I standards as a

starting point from which to conduct the Phase II analysis. 

Only three adjustments of the results of the Phase II

analysis need to be made to use the results directly here. The

first two refer to baseline emissions. First, the Phase I

analysis focuses on the year 1998, while the Phase II analysis

focuses on 2003. Second, this Phase I analysis considers the

fact that both basic and enhanced I/M programs will exist prior

to 2000, while only enhanced I/M is considered thereafter. The
299

result is that the toxics emissions benefits estimated in Section

VI, as well as the resulting cancer incidence reduction, need to

be increased to reflect the difference between the baseline VOC

emissions in Table V-5 above and those estimated in Section VI. 

The third difference is that the Phase II analysis assumes

that the fuel modifications will only occur in the summer. On

the other hand, the Phase I benefits are primarily due to the

addition of oxygenate (with its effect on aromatic content) and

the reduction of fuel benzene content and will occur yearround. 

(The toxics benefits of the summer RVP control are very slight

and can be ignored in this extrapolation from the Phase II

analysis.) Taking all this into account, the Phase I RFG

standards will reduce U.S. cancer incidences (assuming one year

exposure to both the baseline and controlled levels of emissions)

by 24 (assuming basic I/M in place) and 16 (assuming enhanced I/M

in place) incidences.
 52According to section 211(k)(10)(A) of the Act, "baseline

vehicle" means representative model year 1990 vehicles.

 53The formulation for summertime baseline gasoline is

defined in section 211(k)(10)(B) of the Act. See further

discussion of baseline emissions in section III.

300

VI. Phase II Reformulated Gasoline Standards and NOx Standards

for Reformulated Gasoline

A. Introduction

The development of the VOC and toxics emission reduction

standards for Phase II reformulated gasoline (RFG), as well as

the NOx emission reduction standards which EPA is also

promulgating, is presented here. The statutory requirements,

analytical methodologies, and results, as well as public comments

received on the proposal and EPA's responses, are discussed

below. The Phase II RFG standards and NOx standards can be found

at §80.41 and are summarized in section VI of the final

rulemaking preamble.

1. Statutory Requirements

Section 211(k) requires that reformulated gasoline achieve

the greatest reductions possible in volatile organic compounds

(VOCs) and toxics emissions, "taking into consideration the cost

of achieving such emission reductions, any nonair-quality and

other air-quality related health and environmental impacts and

energy requirements. Specifically, section 211(k)(3)(B) of the

Act requires that, in the year 2000 and beyond, "aggregate

emissions of ozone-forming volatile organic compounds from

baseline vehicles52 when using reformulated gasoline shall be 25

percent below the aggregate emissions of ozone forming volatile

organic compounds from such vehicles when using baseline

gasoline53." Similarly, a 25% reduction in emissions of toxic

air pollutants is required. The Act also specifies that the

Administrator may adjust the 25 percent reduction level to

provide for lesser or greater reductions based on technological

feasibility, giving consideration to the cost of achieving such

reductions. In no case can the required reduction be less than

20 percent. The Act further provides that emissions of oxides of

nitrogen (NOx) cannot increase as a result of the use of

reformulated gasoline. These VOC and toxics reductions and NOx

limit are known as the Phase II reformulated gasoline standards. 

Section 211(c) of the Act allows the Administrator to

regulate fuels or fuel additives if "any emission product of such
301

fuel or fuel additives causes, or contributes to, air pollution

which may reasonably be anticipated to endanger the public health

or welfare." Section 211(c)(2) further provides that EPA cannot

control these fuels and fuel additives "except after

consideration of all relevant medical and scientific evidence

available..., including consideration of other technologically or

economically feasible means of achieving emissions standards." 

In addition, EPA must find that the prohibition "will not cause

the use of any other fuel or fuel additive which will produce

emissions which will endanger the public health or welfare to the

same or greater degree than the use of the [regulated fuel/fuel

additive]." 

EPA had elected to use this authority to require

reformulated fuels to also achieve NOx reductions in order to

reduce ozone formation, based on scientific evidence regarding

the benefits of NOx control and on the cost-effectiveness of NOx

reductions. The determination of the need for and costeffectiveness of NOx control is evaluated in this study. A

discussion of the scientific justification for NOx reductions

under the reformulated gasoline program can be found in section B

below.

2. Factors to be Considered in Setting the Phase II RFG

Standards 

An analysis, per the requirements of section 211(k)(1), of

the costs, cost-effectiveness, health, environmental and energy

impacts of fuel component modifications used to reduce VOC, NOx,

and toxics emissions of baseline gasoline is presented below. 

Because the cost of achieving a Phase II reformulated gasoline

standard was specifically mentioned as a consideration in setting

the standard, this analysis focuses on the cost-effectiveness of

different fuel reformulations which achieve at least the minimum

reductions. Since it has been determined that the health and

environmental impacts of such fuel reformulations are beneficial

and increase as the percentage emission reduction increases, and

that the energy impacts are minimal, the Phase II reformulated

gasoline performance standards are determined based primarily on

cost-effectiveness. A discussion of these impacts is presented

in section H below.

EPA received a comment to the proposed standards which

stated that EPA must determine whether VOC or toxics are the

controlling factor in setting the Phase II RFG standards. As

will be shown by the following analysis, EPA has determined that

control of toxics below the minimum statutory level (20%) is not

cost effective. Hence, the standards will be set based on the

cost-effectiveness of VOC and NOx control, not on the basis of

toxics control.
302

B. Scientific Justification for NOx Control

Along with the proposed VOC and toxics standards for Phase

II reformulated gasoline, EPA proposed NOx standards, based on

the cost-effectiveness and environmental benefits of NOx control. 

Many comments were received regarding the NOx standards. These

comments are summarized below. Several of the comments

questioned the scientific evidence for the benefits of

controlling NOx to reduce ozone formation. Hence, a discussion

of the benefits of NOx reduction in terms of ozone impacts, as

well as other environmental and health benefits, is also

presented below. 

The following discussion summarizes EPA's consideration

under §211(c)(2)(A) of the relevant medical and scientific

evidence available to the agency, as well as its consideration of

other technologically or economically feasible means of achieving

NOx reductions through vehicle standards under §202. 

Furthermore, section H provides a comparison of the costeffectiveness of other means of NOx control from mobile or

stationary sources, and concludes that control of NOx emissions

from reformulated gasoline will not pose a greater burden on

industry or the public than these alternative technologies. 

Finally, since the complex model allows consideration of all of

the components of gasoline which affect NOx emissions, EPA

believes that the NOx standards (determined using the complex

model) will not lead to the use of any fuels or fuel additives

which will endanger the public health or welfare (through

increases in VOC, NOx, or toxics emissions) more than would occur

if NOx emissions from reformulated gasoline were not regulated.

EPA has previously established National Ambient Air Quality

Standards for ozone, NO2, and PM-10. In so doing, EPA provided

all of the medical and scientific information available to

support the fact that regulation of these pollutants is

beneficial to public health and welfare. Since NOx emissions

contribute significantly to the inventory of ozone and NO2, and

in some cases, PM-10, reductions in NOx emissions will lead to

reductions in the inventories of these pollutants.

1. Comments on Proposed Standards

EPA received a variety of comments on the proposed NOx

standards. Some commenters claimed that a NOx reduction standard

was counter to the regulatory negotiation agreement. The focus

of Reg-Neg was on how the provisions of section 211(k) were to be

interpreted and implemented; it did not address EPA's authority

under section 211(c) to regulate emissions of NOx. The

scientific evidence summarized below has convinced EPA of the

need to control mobile source emissions of NOx during the summer

months in ozone nonattainment areas, and EPA is doing so under

the authority granted by section 211(c). EPA has determined that
303

NOx standards for gasoline sold in ozone nonattainment areas

should be coordinated with the Phase II performance standards for

VOC and toxics since the environmental benefits of the combined

programs generally will be as great as the benefits of the

programs implemented separately, while costs will be considerably

less. The special distribution and enforcement requirements will

already be in place for the Phase II standards and thus neither

industry nor government will incur additional costs (beyond

manufacturing costs) as a result of implementing an additional

NOx standard. Furthermore, EPA has decided to promulgate the NOx

standards with the Phase II RFG standards to reduce the burden on

the industry of complying with two separate regulations within a

short timeframe (which could negatively impact decisions

regarding capital investment if they were not well coordinated). 

Other comments questioned the ability to control NOx

emissions with any parameter other than oxygen. Since EPA

requires oxygen in reformulated gasoline (as directed by the

Clean Air Act), one comment suggested that the only way to

control NOx would be to eliminate the requirement of a minimum

oxygen content. The complex model clearly shows that some

parameters, most notably sulfur, can have a significant impact on

NOx emissions. Furthermore, the model indicates that the

addition of oxygen leads to a small (essentially negligible)

decrease in NOx emissions. While the impact of various

oxygenates on NOx emissions can vary due to other changes in the

fuel which accompany oxygen addition, the oxygen alone does not

appear to increase NOx in 1990 model year vehicles. In addition,

all fuel modifications considered below to reduce NOx emissions

were evaluated with fuels already containing 2.1 weight percent

oxygen. Hence, it is clear that significant reductions in NOx

can be achieved without lessening the oxygen requirement. In any

case, section 211(k)(2) allows EPA to waive the oxygen content

requirement for reformulated gasoline only if the Administrator

determines that compliance with the oxygen content requirement

would prevent or interfere with attainment of an applicable

NAAQS. EPA therefore could not waive this requirement for the

reasons presented by the commenter.

Many comments addressed the cost-effectiveness of NOx

control. Some raised questions about the accuracy of the costs

used, which impacts the cost-effectiveness determination. The

cost-effectiveness analysis presented later in this section uses

improved costs and is believed to be representative of the impact

of NOx control on the average refinery. Some of the comments

supported NOx control on the basis of the cost-effectiveness

analysis presented with the proposal, citing the benefits that

specific locations would realize by reducing the mobile source

contribution to the NOx inventory. As discussed below, although

the benefits of NOx reduction vary from city to city, in general

most ozone nonattainment areas will benefit from a reduction in

NOx in addition to the mandated reductions in VOC emissions.
 54Although by the year 2000 a portion of the vehicles will

have lower NOx emissions because they will meet the "Tier 1"

emission standards, these emissions benefits are expected to be

offset by increases in annual vehicle miles travelled.

 55National Research Council, Rethinking the Ozone Problem

in Urban and Regional Air Pollution, National Academy Press,

Washington, D.C., 1991.

 56U.S. EPA, "Summary of Public Comments and EPA Responses

on the Draft Report 'The Role of Ozone Precursors in

Tropospheric Ozone Formation and Control'," EPA-454/R-93-025,

July 1993.

 57For example, due to the transport of ozone over the

region, control strategies that might not benefit one area

within the nonattainment region may help an area downwind.

304

Some comments questioned the validity of the information

which claims ozone benefits from NOx reductions, while others

supported the benefits of reducing NOx emissions in ozone

nonattainment areas. Most comments centered around the question

of how much a given nonattainment area would benefit from NOx

reductions in addition to VOC reductions. The following section

presents EPA's response to these comments.

2. Benefits of NOx Reductions

EPA proposed NOx standards based on the reduction in ozone

formation that is expected to result from a combination of

reductions in both VOC and NOx emissions. Gasoline vehicles

contributed 20-35% of total urban NOx emissions in 1990, and are

expected to continue to represent a large fraction of the NOx

inventory in the year 2000.54 Hence, control of mobile source

NOx emissions can be an important step in meeting the air quality

requirements of various urban areas. 

A recent report by the National Research Council (NRC)

concluded that "the optimal set of controls relying on VOCs, NOx,

or, most likely, reductions of both, will vary from one place to

the next."55 In response to the NRC report, EPA acknowledged

that NOx control in addition to or instead of VOC control is

likely to reduce ozone in many areas.56 Similarly, EPA

acknowledges that the magnitude of the ozone benefits for VOC

controls is dependent on the particular area.57 

Many stationary source emission control measures can be

applied on a selective basis to individual areas based on their

air quality needs. For ozone control strategies based on fuel

controls, however, it is extremely difficult if not impossible to
305

tailor the relative reductions in VOC and NOx emissions to the

specific needs of individual areas. The fungible nature of the

gasoline distribution system in this country would simply not

allow for detailed specific VOC and NOx standards for each and

every individual area. Such a requirement would greatly hamper

the efficient distribution of the fuel, thereby resulting in

extremely large increases in fuel distribution costs, rendering

such emission controls through fuel reformulation cost

ineffective. The reformulated gasoline standards avoid the vast

majority of these concerns by applying one consistent set of fuel

standards to a range of areas. By so doing, the program achieves

significant ozone reductions on average in a cost effective

manner, while at the same time recognizing that the controls

would be more effective at reducing ozone in some areas than in

others.

With this in mind, EPA proposed in February 1993, that a NOx

reduction standard be applied to all RFG areas. While either NOx

or VOC reductions by themselves may provide little ozone benefit

in a minority of the covered areas, the combination of NOx

control with VOC control will ensure that significant ozone

reductions are achieved in all of the covered areas. Applying

fuel NOx controls nationwide (as is done out of necessity with

tighter vehicle emission control standards) would be

inappropriate, however, since most of the additional NOx

reductions would be achieved in areas for which little or no

ozone benefit would result. Therefore, EPA believes it

appropriate to apply a NOx reduction standard to the same areas

for which the reformulated gasoline standards apply. 

The following presents a summary of the scientific evidence

which favors NOx reductions for most, if not all, ozone

nonattainment areas. The benefits include the primary benefit of

reducing ozone precursors as well as secondary benefits which

will benefit human health and the environment.

a. Effect of NOx on Ozone

Although both NOx and VOC emissions are regulated for

certain types of sources, including motor vehicles, the primary

focus of past ozone abatement strategies has been on VOC. This

is largely due to the belief that the most cost effective way to

reduce ozone formation was to limit the amount of VOC in the

ambient air. However, many areas where VOC reduction has been

applied as the primary ozone control strategy have not reached

attainment. In recent years, improved knowledge of emission

sources and atmospheric chemistry has shown that both VOC and NOx

emissions can enhance ozone formation. The benefits of either

VOC or NOx emission reductions can depend on the ratio of VOC to
 58Finlayson-Pitts, B.J. and J.N. Pitts, Jr., "Atmospheric

Chemistry of Tropospheric Ozone Formation: Scientific and

Regulatory Implications," Air & Waste, Vol.43, August,

pp.1091-1100, 1993.

 59U.S. EPA, EPA-454/R-93-025.

 60National Research Council, Rethinking the Ozone Problem

in Urban and Regional Air Pollution, National Academy Press,

Washington, D.C., U.S.A., 1991.

 61Ibid.

 62Milford, J.B., Russell, A.G., and McRae, G.J., "A New

Approach to Photochemical Pollution Control: Implications of

Spatial Patterns in Pollutant Responses to Reductions in

306

NOx in the airshed.58 This ratio varies spatially and temporally

within a given air basin and can differ between severe ozone

episodes or more typical ozone exceedances. However, although

simple smog chamber experiments typically show that combined VOC

and NOx reductions are less effective at controlling ozone than

reducing either one alone, the complexity of variations in

meteorology, emissions sources, and control feasibility often

make combined VOC and NOx control the option of choice in real

world situations.59 

Prior to the development of more sophisticated models,

information about the response of ozone levels to VOC and NOx

emissions was often based on EKMA modelling. This modelling

produces graphical representations (isopleths) of the

relationship between VOC and NOx concentrations in the formation

of ozone. Regions where ozone formation is either VOC or NOx

limited are easily determined from these plots. At low VOC to

NOx ratios, less than about 8 on a molar basis, ozone formation

is VOC limited, so VOC control is more effective. A low ratio is

typical of highly urbanized areas. For VOC to NOx ratios greater

than 8, ozone formation is NOx limited, and NOx control is more

effective. For instance, the Houston area has been identified by

the EKMA analyses as an area in which ozone formation is NOx

limited and thus VOC control alone would do little to reduce

ozone levels in this area.60 Many areas downwind of urban

centers also have large VOC to NOx ratios and so would be NOxlimited.

Ozone grid-based modelling studies using more sophisticated

analytical techniques have shown that NOx control is generally a

more effective ozone reduction strategy than VOC control. The

recent National Research Council study61 utilized work in the

California South Coast basin62 to suggest that NOx control is
Nitrogen

Oxides and Reactive Organic Gas Emissions," Environ. Sci.

Technol., v 23, pp. 1290-1301, 1989.

 63Sillman, S., Samson, P.J., and Masters, J.M., "Ozone

Production in Urban Plumes Transported over Water:

Photochemical Model and Case Studies in the Northeastern and

Midwestern United States," J. Geo. Res., v. 98, n. D7, pp.

12,687-12,699, 1993.

 64Sillman, S. and Samson, P., "Simulated Ozone over Lake

Michigan and the Northeast Corridor: Identifying the

Differences between Hydrocarbon-limited and NOx-limited

Regions," Presentation at the 86th Annual Meeting and

Exhibition, Denver, CO, June 13-18, 1993, 93-WP-68B.05.

 65U.S. EPA, Regional Ozone Modeling for Northeast Transport

(ROMNET), EPA Report 450/4-91-002a, June 1991. 

 66Sillman and Samson, 86th Annual Meeting of Air & Waste

Management Association, June 13-18, 1993.

307

essential to meeting the ambient air quality standards and that

even marginal NOx reductions result in improved air quality in

most areas. Subsequent studies63,64,65 have shown that NOx control

is an effective ozone reduction strategy for the northeast United

States, including the Baltimore, Philadelphia, New YorkConnecticut, and Boston-Maine regions. The EPA ROMNET report on

ozone modelling for the northeastern states indicated that NOx

control reduced ozone for nearly all of the northeastern

modelling domain, except New York City and nearby areas. In New

York City, ozone levels increased when only NOx emissions were

reduced, indicative of VOC-limited ozone formation. When both

VOC and NOx emissions were reduced, however, ozone was reduced

throughout the modelling domain. Of course, with Phase II

reformulated gasoline, NOx emission control will only occur along

with significant VOC emission reductions (several times greater

than the NOx reductions). Therefore, ozone reductions are

expected over the entire region modelled by the EPA study, which

includes four of the mandated nine reformulated gasoline regions. 

These include areas that are VOC-limited as well as NOx-limited

for ozone formation as well as most of the opt-in areas. The

ROMNET study also suggested that the benefits of NOx controls may

extend beyond rural regions since net ozone transport into cities

is reduced.

Similar modelling has been performed for the Lake Michigan

region (including Chicago, IL; Muskegon, MI; and Milwaukee,

WI).66 The results of this study indicated that NOx control

without VOC control could be detrimental for the Lake Michigan
 67U.S. EPA, EPA-454/R-93-025, July 1993.

 68Statement by Bill Oliver, Radian Corp., Presentation at

the 1992 Conference on Lake Michigan Ozone and the Clean Air

Act, Chicago, IL, September 1992.

 69Finlayson-Pitts and Pitts, Air & Waste, Vol.43, August,

pp.1091-1100, 1993.

 70Fujita, E.M., Croes, B.E., Bennett, C.L., Lawson, D.R.,

Lurmann, F.W., and Main, H.H., "Comparison of Emissions

Inventory and Ambient Concentration Ratios of CO, NMOG, and NOX

in California's South Coast Basin," JAPCA, v 42, pp.264-276,

1992.

308

region. As long as VOC reductions are greater than NOx

reductions, however, the combination of the two will result in

ozone benefits. The sensitivity of the modelling results to the

VOC emissions inventory was also tested, and showed that if the

VOC emissions inventory was underestimated (as discussed in the

next paragraph), NOx emission reductions become universally

effective in the Lake Michigan region.

The NRC and EPA67 have indicated that emissions inventories

of VOC and carbon monoxide may have been underestimated in the

past. The estimated relative benefits of VOC or NOx control as

ozone reduction strategies depends upon the assumption of the

emission inventories. As the VOC emission inventory estimate

increases, NOx control becomes a more effective strategy for

reducing ozone levels. Several changes have led to higher

estimates in the VOC emission inventory since the grid models

cited in the previous paragraphs were performed. EPA's MOBILE5

emission model estimates significantly higher VOC emissions than

the MOBILE4 model which was used in the ozone modelling studies

cited above. In addition, indications are that the effectiveness

of stationary source controls is not as great as assumed in the

ozone modelling studies.68 This also increases the VOC emissions

inventory estimate. Therefore, even though NOx control has been

shown to be very effective in reducing ozone, the efficacy of NOx

reduction may have been underestimated in past modelling.

Ambient measurements have also indicated that the VOC

inventory may be underestimated. Measurements of VOC/NOx ratios

have been typically a factor of approximately two higher than

predicted from the emission inventories in major cities

throughout the U.S.69,70 The measurement of ambient VOC may be

actually too low because measurement methods tend to
 71 Chameides, W.L., Fehsenfeld, M.O., Rodgers, M.O.,

Cardelino, C., Martinez, J., Parrish, D., Lonneman, W., Lawson,

D.R., Rasmussen, Zimmerman, P., Greenberg, J., Middleton, P.,

and Wang, T., "Ozone Precursor Relationships in the Ambient

Atmosphere," J. Geo. Res., v. 97, n. D5, pp. 6037-6055, 1992. 

 72 O'Shea, W.J. and Scheff, P.A., "A Chemical Mass Balance

for Volatile Organics in Chicago," JAPCA, v. 38, pp. 1020-1026,

1988.

 73 Aronian, P.F., Scheff, P.A., Wadden, R.A., "Wintertime

Source-Reconciliation of Ambient Organics," Atmospheric

Environmental, v. 23, n. 5, pp. 911-920, 1989.

 74 Harley R.A., Hannigan, M.P., and Cass G.R.,

"Respeciation of Organic Gas Emissions and the Detection of

Excess Unburned Gasoline in the Atmosphere," Environ. Sci.

Technol., v. 26, pp. 2395-2408, 1992.

 75Chameides, W.L., Fehsenfeld, M.O., Rodgers, M.O.,

Cardelino, C., Martinez, J., Parrish, D., Lonneman, W., Lawson,

D.R., Rasmussen, Zimmerman, P., Greenberg, J., Middleton, P.,

and Wang, T., "Ozone Precursor Relationships in the Ambient

Atmosphere," J. Geo. Res., v. 97, n. D5, pp. 6037-6055, 1992. 

 76At this time Atlanta is not participating in the

reformulated gasoline program. However, the Atlanta area is a

serious ozone nonattainment area.

309

underestimate the total.71 The VOC/NOx ratio of most urban areas

was thought to be much lower than ambient measurements would

indicate. Several other studies72,73,74 have concluded through a

technique called source/receptor modelling that the VOC emission

inventory is underestimated. If the VOC emission inventory is

severely underestimated, then regions where NOx control are

estimated to increase ozone levels may not exist.

Another concern is that biogenic emissions or their

importance may have been underestimated in the past.75 In the

Atlanta area, biogenic emissions of VOC may be high enough that,

in the absence of NOx control, even 100% control of anthropogenic

VOC would not enable the region to meet the National Ambient Air

Quality Standard (NAAQS) ozone standard.76 In addition, the VOC

emissions from biogenic sources tend to be more reactive than

those from stationary or mobile sources. Results of EPA's ROMNET

study suggest that the impact of biogenics on ozone formation

extend beyond the southeastern U.S. to include much of the

northeast, as well. To the extent that biogenic VOC emissions

compound the air quality problems of a given region, NOx control

becomes more effective.
310

Areas downwind of urban plumes tend to have high VOC/NOx

ratios indicative of NOx-limited ozone formation. This may be

due to increases in local biogenic emissions or transformation

and subsequent deposition of nitrated compounds created upwind. 

Reducing the upwind NOx emissions may be the only means for

meeting the ozone standard downwind, even if those emission

reductions do not improve air quality in the upwind areas. Many

nonattainment areas are downwind of other nonattainment areas,

particularly in the Northeast corridor and the Lake Michigan

region. Hence, NOx emissions can impact more than just emission

source areas.

Since reformulated gasoline can assist control of both VOC

and NOx emissions from motor vehicles, its use should provide

ozone reductions in areas that are either VOC or NOx limited. In

the VOC limited areas where NOx emission reductions may cause

ozone increases, the magnitude of VOC reductions provided by

reformulated gasoline should prevent any ozone increases (as

demonstrated by the Lake Michigan and other studies). In the

great majority of areas, reformulated gasoline with NOx control

will provide reductions in ozone. As such, the RFG program

represents an ideal opportunity to reduce ozone in all areas

through both VOC and NOx control.

b. Secondary Benefits

The secondary benefits of NOx emission reductions are also

important. As discussed below, these include reductions in acid

rain, deposition of nitrates in lakes and estuaries, ambient

levels of nitrogen dioxide, secondarily formed particulates, and

highly toxic nitrated polycyclic organic matter, as well as

potential global warming benefits. 

NOx emissions from gasoline vehicles are a significant

fraction of the overall NOx emission inventory. While the

primary cause of acid rain may be sulfur dioxide emissions, the

benefit of reducing NOx emissions should not be ignored. NOx

emissions can be precursors to acid aerosols in the form of

nitrates or by contributing to the formation of sulfates by

reaction with sulfur dioxide gas. Hence, any reduction in NOx

emissions from gasoline vehicles should help reduce acid rain

precursors. (Furthermore, the acid rain benefits of NOx

reductions through gasoline reformulation will be enhanced by the

fact that the majority of the NOx emission reductions are

expected to be achieved through the removal of sulfur from the

gasoline.) 

Several studies indicate that atmospheric deposition

accounts for a significant portion of nitrogen deposited into

certain sensitive estuaries (e.g., 25% of the nitrogen in
 77"Progress Report of the Nutrient Reduction Reevaluation,"

Chesapeake Bay Program, February 1992.

 78Farber, R.J., Baas, J.R., Pilinis, C., and Countess,

R.J., "Modelling the Secondary Component of PM10," PM10 Standards

and Nontraditional Particulate Source Controls, Chow, J.C. and

Ono, D.M. editors, Air and Waste Management Association,

Pittsburgh, PA, November, 1992.

 79California Air Resources Board, "The Effects of Oxides of

Nitrogen on California Air Quality," Report No. TSD-85-01,

March 1986.

 80U.S. EPA, Motor Vehicle-Related Air Toxics Study, EPA

Report 420-R-93-005, April 1993.

311

Chesapeake Bay is due to atmospheric deposition).77 The

atmospheric deposition of nitrates can also contribute to the

depletion of oxygen in lakes and estuaries as a result of an

increase in the algae and other plant matter growth in these

waterways. The benefit of reducing these nitrates through

control of gasoline vehicle emissions has not previously been

evaluated, but could be significant.

Nitrated particulate matter related to NOx emissions (e.g.,

ammonium nitrate) has also been shown to be a significant

fraction of some area's PM-10 problem.78 Some particulate

nitrates may be toxic, mutagenic, or carcinogenic.79 These small

particles are carried deep into the lung and are known to cause

potentially serious respiratory effects. They also contribute to

impaired visibility, raising the public's awareness of this air

pollution. Any NOx reduction should reduce these particles. 

Since mobile source NOx emissions are ground-based and

distributed over wide areas, reducing these could have more

impact on human health than reductions from stationary sources. 

EPA has also cited polycyclic organic matter (POM) as an 

air toxic.80 The toxicity of these compounds increases greatly

when nitrated. A reduction in NOx emissions should reduce the

transformation of POM to the more toxic nitrated form.

A change in NOx emissions is also known to affect

concentrations of the hydroxyl radical in the troposphere (the

lower layer of the atmosphere). The concentration of the

hydroxyl radical in turn impacts the concentration of

tropospheric ozone, a greenhouse gas. NOx reductions thus could

have positive benefits in reducing global warming. However, the

impacts of a reduction in U.S. mobile source emissions of NOx on
 81Hangebrauck, Robert P. and John W. Spence, U.S. EPA,

"Ozone and Global Warming," August, 1992.

312

global tropospheric ozone concentrations and the corresponding

relationship to global warming are unclear at this time.81

In sum, while the benefits of reducing ozone levels as a

result of NOx reductions are the primary basis for the controls

being promulgated, the other direct and indirect benefits of

reducing atmospheric NOx levels also appear to be substantial.

3. Consideration of §202 Motor Vehicle Controls

Before controlling or prohibiting a fuel or fuel additive

under §211(c)(1)(A), the Administrator must consider "other

technologically or economically feasible means of achieving

emission standards under section [202]." This has been

interpreted as requiring consideration of regulation through

motor vehicle standards under §202 prior to regulation of fuels

or fuel additives under §211(c)(1)(A) [Ethyl Corp. v.

Environmental Prot. Agcy., 541 F.2d 1, 32 (D.C. Cir. 1976)]. 

This does not establish a mandatory preference for vehicle

controls over fuel controls, but instead calls for the good faith

consideration of motor vehicle standards before imposition of

fuel controls [541 F.2d at 32 n.66]. This reflects Congress'

recognition that fuel controls under §211(c)(1)(A) might

logically involve controls on fuel composition itself, while

vehicle standards under §202 are generally performance standards,

regulating vehicle emissions and not the design or structure of

the vehicle. Fuel controls might therefore lead to greater

government involvement in the regulation of the manufacturing

process than would be expected from vehicle controls [541 F.2d at

11 n.13]. 

Congress addressed this concern by requiring agency

"consideration" of vehicle standards under §202 before imposition

of fuel controls under §211(c)(1)(A). It is important to note

that the Administrator must in good faith consider such vehicle

controls, but retains full discretion in deciding whether to

adopt either fuel or vehicle controls, or both [541 F.2d at 32

n.66].

In evaluating motor vehicle controls under §202 in this

context, the first major point to consider is that EPA has

already imposed more stringent NOx control standards on motor

vehicles. The Tier 1 standards for light-duty motor vehicles and

trucks require reductions in light-duty motor vehicle NOx

emissions starting with model year 1994, with a percentage phasein of the more stringent Tier 1 standards until they apply to all
 8256 FR 25724, June 5, 1991. Also, note that the Tier 1

standards apply to light-duty trucks with a loaded vehicle

weight rating of 3,750 lbs. or less.

 83Fleet turnover is included in EPA's MOBILE5a model [58 FR

29409, May 29, 1993]. As of 1990, the median vehicle age was 7

years (i.e., one-half of the vehicles were younger than this

and one-half were older).

 84Ibid.

313

new model year 1996 and later light-duty vehicles and trucks.82

In-use compliance with these standards is also phased-in, such

that model year 1998 and later new light-duty vehicles must

comply with the Tier 1 NOx standard in-use. The same applies for

light-duty trucks, with model year 1999 instead of 1998 [56 FR

25787] For heavy-duty vehicles, EPA recently reduced the NOx

standard to 4 g/bhp-hr, starting with model year 1998 [58 FR

15781, March 24, 1993]

While these motor vehicle and motor vehicle engine controls

are expected to reduce mobile source emissions of NOx, this

result is limited by certain basic facts. First, the standards

only apply to new motor vehicles and engines. It will therefore

take several years after the first model year of the standards

before vehicles and engines certified to these standards will

make up a significant portion of the motor vehicle fleet.83 In

addition, it is expected that emissions reductions based on the

reduction in the NOx standard will be offset to a significant

extent by an increase, over time, in total vehicle miles

travelled.84

In addition to motor vehicle controls under §202, EPA has

recently adopted or proposed other controls aimed at in-use NOx

emissions from mobile sources. The enhanced inspection and

maintenance (I/M) rules call for use of these more stringent I/M

procedures starting with 1996 [57 FR 52950, November 5, 1992]. 

EPA has also proposed standards that would limit NOx emissions

from new large horsepower diesel non-road engines, pursuant to

§213 of the Act [58 FR 28809, May 17, 1993]. While enhanced I/M

programs will directly affect the whole motor vehicle fleet, the

non-road engine regulations are similar to the motor vehicle

regulations under §202 in that they would apply to new non-road

engines only, and therefore involve a certain time before a

significant portion of this category of non-road engines is

replaced by new engines certified to meet the NOx standards. 

Finally, the centrally fueled fleets program and the California

Pilot program [§§246 and 249] will result in tighter NOx

standards for a small segment of the motor vehicle fleet.
314

Additional mobile source controls, whether under §202 or

under other authority such as described above, may well be cost

effective and reasonable options that EPA might decide to adopt. 

However, there are certain limitations imposed by Congress on the

adoption of more stringent standards. For example, Congress

spelled out when and under what conditions EPA may promulgate

more stringent NOx standards for light-duty vehicles and trucks. 

Congress required that EPA conduct a study on whether more

stringent standards for light-duty vehicles and trucks should be

adopted, and report back to Congress no later than June 1, 1997

[§202(i)(1),(2)]. Based on the study EPA must conduct a

rulemaking to determine whether there is a need for such further

reductions, whether the technology will be available for such

reductions, and whether further reductions in emissions from such

vehicles will be cost effective. If these determinations are

made in the affirmative, then EPA would proceed to promulgate

emissions standards that are more stringent than the Tier 1

standards [§202(i)(3)(C)]. If EPA does promulgate more stringent

standards, they may not take effect any earlier than model year

2004, and no later than model year 2006.

It is clear from this that EPA has not, at this time,

completed the lengthy process for determining whether or not more

stringent standards should be established for light-duty vehicles

and trucks under §202(i). Congress established a detailed

provision spelling out the procedures to follow and the

substantive determinations that must be made before such controls

could be adopted. There is no indication, and EPA does not

believe, that these mandated procedures and criteria preclude the

exercise of discretion under §211(c)(1)(A) prior to completion of

the rulemaking under §202(i). Congress required that EPA

consider motor vehicle controls, but did not establish a

mandatory preference for such controls and did not preclude the

adoption of fuel control prior to a decision on Tier 2 motor

vehicle standards.

In any case, it is clear that a decision to impose more

stringent NOx standards for light-duty vehicles and trucks under

§202(i) could not take effect prior to model year 2004. It would

then take several years before a significant portion of the inuse fleet would include vehicles or trucks certified to a NOx

standard more stringent than the Tier 1 standard. A similar

situation would apply to a more stringent NOx standard for heavyduty engines. The mandatory leadtime and stability provision of

§202(a)(3)(C) would preclude imposition of more stringent NOx

standards for heavy-duty engines until model year 2001 at the

earliest. It would again take several years before a significant

portion of the in-use heavy-duty fleet contained engines

certified to a more stringent NOx standard. For non-road engines

and vehicles, EPA expects to continue to explore NOx controls for

this category of mobile sources. But as with motor vehicles, any

new or more stringent NOx standards will only apply to new non-
315

road engines, after providing a reasonable period for leadtime. 

The effect on in-use emissions is delayed based on the time

needed before new non-road engines replace earlier models.

Given these circumstances, there are several important

reasons why promulgation of a NOx reduction standard for

reformulated gasoline is important, whether or not additional

vehicle or engine controls are later adopted by the Agency. 

First, emissions reductions from the NOx performance standard

would start as soon as the standard is applicable, with no delay

based on fleet turnover time. Significant NOx emission

reductions would be achieved right away, in the spring of 2000,

while more stringent light-duty or heavy-duty standards would not

be expected to significantly affect in-use emissions until much

later in that decade. Second, a NOx reduction standard for

reformulated gasoline would act to reduce emissions from all

mobile sources that use gasoline, whether highway or non-road,

while §202 or §213 standards only act to limit emissions from new

engines or vehicles in that specific category of mobile sources. 

Third, this fuel control is specifically aimed at areas of the

country that are in nonattainment for ozone, and is limited in

time to that part of the year when ozone is of most concern. 

Vehicle or engine controls, in contrast, apply to all new engines

or vehicles, wherever they are used, throughout the year. This

fuel control thus allows a more narrow regulatory solution aimed

at the specific geographical areas and time periods when control

is needed. Fourth, the expected increase in vehicle miles

travelled over time leads EPA to believe that this fuel control

is needed to continue to achieve the in-use NOx emission

reductions necessary for many areas of the country to reach

attainment for ozone. Fifth, the NOx controls required in this

rule will reduce NOx emissions at a reasonable cost, about $5,000

per ton. This compares favorably with the cost-effectiveness of

other mobile and stationary source control strategies, as

supported in section H below. Finally, the NOx fuel standard

adopted here minimizes any concern there might be that a fuel

control would tend to interfere in the production process by

directing refiners on how to make their product. The NOx

standard is not a fuel recipe, but instead establishes a

performance standard, leaving refiners free to produce their

gasoline in any way that achieves the desired reductions.

EPA is not at this time determining whether additional

vehicle or engine NOx controls should be adopted under §202 or

any other provision of the Act. Instead, based on all of the

above, EPA believes that a NOx reduction standard for

reformulated gasoline under §211(c)(1)(A) is an appropriate

exercise of discretion, whether or not the agency imposes

additional vehicle or engine NOx controls in the future.
316

C. Derivation of Fuel Parameter Control Costs

This section describes the methodology used to determine the

costs of controlling individual fuel parameters and highlights

important factors which influence the estimation of fuel

parameter control costs. Also addressed are the fuel economy

impacts of different fuel formulations and how they were included

in the analysis. A table summarizing the costs derived from this

analysis can be found in subsection 5 below.

1. Refinery Modelling and Assumptions

Refinery modelling is the best method currently available

for estimating the cost of particular refinery changes, such as

those which are required to produce fuel formulations which meet

various emission performance standards. Mathematical refinery

models are created to estimate the changes in manufacturing costs

associated with the control of one or more fuel components. 

Optimal solutions are found by the model such that all product

specifications, for gasoline as well as other refinery products,

are met at the lowest cost. The change in manufacturing costs,

or the incremental cost of control, is the difference between the

cost of producing fuel under a defined base case and the new cost

which occurs when a fuel specification is changed. 

EPA received many comments on the costs used to develop the

cost-effectiveness analysis which supported the proposed Phase II

RFG standards. EPA used refinery modeling studies as the basis

for the proposed Phase II costs. One comment suggested that the

costs used in the analysis did not accurately reflect all of the

costs incurred, since they were only based on manufacturing

costs. In particular, if the fungibility (the ability of a

mixture of two complying fuels to still comply with the

standards) of Phase II fuel became an issue, then the costs would

be significantly higher than those used here due to the increased

complexity of the distribution system. Since EPA has

demonstrated (see section III) that fungibility will not be a

problem for either Phase I or Phase II reformulated gasoline,

such costs do not need to be included in this analysis. An

exception to this are fuels containing ethanol, since such fuels

must be segregated from non-ethanol containing fuels. However,

this segregation has been clearly required throughout all EPA's

proposed rules regarding reformulated gasoline. Also, the

refinery studies used below either use MTBE-based gasolines not

requiring segregation, or use MTBE and ethanol-based fuels with

ethanol prices sufficiently high to cover the costs of

segregation. Thus, no additional modifications to the analysis

are necessary.

Another comment suggested that it is inappropriate to use

independent refinery models to generate costs for controlling

individual parameters, and that aggregate nationwide models
317

should not be used. Rather, costs should be generated from

refinery models for regions with high levels of RFG production,

such as PADD 1. EPA disagrees. The actual cost of producing

reformulated gasoline at various NOx emission performance levels

will include the costs for regions having high reformulated

gasoline concentrations and those with low concentrations. Both

need to be considered if the costs developed here are to be

comparable to those of other NOx control programs. The costs

imposed on individual regions is important when competitive and

regional economic impacts are evaluated. However, national

average costs should be used when comparing the costeffectiveness of the reformulated gasoline program to that of

another program. 

A third comment suggested that the costs estimated in this

analysis should include the costs of complying with the program,

not just the manufacturing costs. This is true. However,

changing the emission performance standards for Phase II should

have little or any effect on the non-manufacturing costs of the

program, except for fuel economy effects, which are addressed

below. The costs of recordkeeping and other compliance related

costs should be the same for Phase II as they were for Phase I

and not depend on the level of the Phase II standards. Thus,

they do not change in this incremental analysis and need not be

included.

Two basic methodologies can be used to estimate the cost of

various RFG standards. In one, a version of EPA's complex model

for reformulated gasoline is expressed as a series of linear

equations and integrated into a refinery model. The refinery

model is then used to determine the lowest cost of reducing

emissions of the particular pollutants of concern (VOC, NOx and

toxics). This method is preferable when the emission effects of

fuel changes are known and when sufficient time is available to

integrate this emission information with the cost analysis. The

weakness of this approach is that the results become suspect

whenever the emissions model is changed. Since the refinery

model was trading off up to eight fuel parameters at a time based

on the coefficients of the emissions model, changes to these

coefficients can lead to markedly different results.

The other method more loosely couples the emissions model

and the refinery model. The refinery model is used to develop

costs for varying individual fuel parameters. The effect of

these fuel changes on emissions and their cost are then compared

and the most cost-effective fuel modifications identified. The

refinery model is then rerun, if necessary, to first modify the

most cost-effective fuel parameter, then the second, and so on. 

This method always results in a less optimum refinery

configuration (i.e., higher costs) than the first method, because

the refinery model is only evaluating a small number of possible

ways to achieve the specified emission reduction. Of course,
 85Bonner and Moore Management Science, "Study of the

Effects of Fuel Parameter Changes on the Cost of Producing

Reformulated Gasoline," Prepared for EPA under contract through

Southwest Research Institute and the National Institute for

Petroleum and Energy Research. This data was made available to

the public through the following document: "DOE and API Phase

II Cost Estimates," EPA Memorandum from Lester Wyborny, FSSB,

to the Air Docket, November 4, 1993. The Bonner and Moore work

performed for this analysis was based on a revised version of

the model used to generate costs for the draft RIA. This new

version includes provisions to prevent dumping of fuel

components into conventional gasoline.

 86Lester Wyborny, U.S. EPA, "Aromatics and E200

Reformulation Costs," Memorandum to the Air Docket, December

10, 1993.

318

care must be taken to ensure that emissions of the other

pollutants of interest are being maintained or reduced while

control of the primary pollutant is being evaluated. 

EPA, for its own work (and the work contracted by the

Agency), chose to follow the second method for both time and

resource related reasons. The complex model was being developed

concurrently with the cost analysis. Repeatedly modifying the

refinery model to incorporate each new version of the complex

model would have been costly and time consuming, and would have

delayed the promulgation of the standards. As described below,

as fuel modification costs using the first method have become

available from other sources (only very recently), the parameter

by parameter costs were compared to complex model based costs to

ensure basic consistency in the two estimates of how refineries

would act to reduce fuel-based emissions.

The majority of the refinery modelling on which EPA

estimated its cost estimates was performed by Bonner and Moore (B

& M) through an EPA contract with the Southwest Research

Institute and a Department of Energy (DOE) contract with the

National Institute for Petroleum and Energy Research (NIPER).85 

Bonner and Moore, for EPA, created a specialized version of their

refinery model to estimate the cost of the RFG program. In

addition to the work done by B & M, EPA staff ran the B & M model

to determine costs for two of the parameters, as discussed

further below.86 Other refinery modelling and fuel modification

costs used or considered were generated by the Department of
 87Lester Wyborny, U.S. EPA/FSSB, "DOE and API Phase II Cost

Estimates," Memorandum to the Air Docket, November 4, 1993.

 88Ibid.

 89Turner, Mason & Company, "WSPA Study of the Cost Impacts

of Potential CARB Phase 2 Gasoline Regulations," Prepared for

the Western States Petroleum Association, November 18, 1993.

 90Turner, Mason & Co., "Costs of Alternate Gasoline

Reformulations, Results of U.S. Refining Study," Prepared for

the Economics Committee of the Auto-Oil Air Quality Improvement

Research Program, April 1992.

 91National Petroleum Council, "U.S. Petroleum Refining: 

Meeting Requirements for Cleaner Fuels and Refineries," August

1993.

319

Energy through the Oak Ridge National Laboratory,87 and for API,88

WSPA,89, Auto-Oil90 and the National Petroleum Council91 by the

Turner, Mason and Company (Turner/Mason). A more complete

comparison of EPA's analysis with the other refinery analyses may

be found in section G below.

EPA used B & M-estimated Phase II RFG sulfur and olefin

costs in the February 26, 1993 proposed rule. That B & M data,

like the data used here for the final rule, is most attractive to

EPA because unlike other modelling work on the Federal RFG

program, it attempts to model the effect of the RFG program on

the entire refining industry. However, commenters pointed out

that the B & M modelling work for the proposed rule permitted

parameter values to increase in conventional gasoline (a

violation of the antidumping restrictions), which would lead to

low estimated investments and decreased RFG program costs. EPA

corrected that situation in the final rule by directing B & M to

cap parameter levels in conventional gasoline at 1990

conventional gasoline levels. This approach, while it prevents

any shifting of regulated gasoline components to conventional

fuel, is overly restrictive in that most refiners will use the

complex model to evaluate their conventional gasoline composition

after 1994 to compare it to their 1990 gasoline. The complex

model would give refiners more flexibility in meeting their

antidumping restrictions resulting in some cost savings. Thus,

the B & M modelling work for the final rule would tend to be

slightly overstated.

2. Factors Influencing Cost 

A number of economic reporting factors influence the

estimated cost of producing gasoline in addition to the operating
 92U.S. EPA, "Analysis of the Economic and Environmental

Effects of Methanol as an Automotive Fuel," Special Report,

Office of Mobile Sources, September 1989.

 93Turner, Mason & Co., April 1992.

 94U.S. EPA, "Control of Sulfur and Aromatics Contents of

On-Highway Diesel Fuel," Draft Regulatory Impact Analysis, July

1989. 

320

costs of a specific refinery. Those factors which impacted EPA's

cost analysis are discussed below.

a. Rate of Return on Investment 

The internal rate of return is an economic factor used by

businesses such as the refining industry in evaluating the

economic breakeven point for their investments. Although the

refining industry and their consultants often evaluate potential

investments at a 15 percent real rate of return, EPA has

determined that the historical rate of return for the oil

industry is much closer to 10 percent.92 This appears to reflect

the fact that most pre-investment analyses are inherently

optimistic and do not quite yield their predicted profits. To

reflect both the pre-investment actions of refiners and real

results, EPA believes it most appropriate to operate the refinery

model with a 15 percent real rate of return hurdle on capital

investment to most accurately reflect the tradeoff between

operating costs and capital. Once the refinery model has

determined an optimum processing approach, capital costs are then

reannualized using a 10 percent real rate of return to reflect

the actual and historically acceptable performance of capital. 

This is very similar to the approach taken by the Auto-Oil group

in their refinery modeling,93 where they used a 15 percent real

rate of return internal to the refinery model and then present

the costs using both 9 and 13 percent real rates of return. 

In adjusting annualized capital costs for the parameter

changes described below, a 0.171 annual cost recovery factor

(i.e., the fraction of total capital investment that must be

recovered each year to achieve the specified real rate of return

on capital) was used in lieu of the 0.226 cost recovery factor

contained in the Bonner and Moore model.94 In addition, where

refinery modeling data were extracted from other studies for

direct use or for comparison purposes, the cost recovery factors

were adjusted using the same methodology. 

b. Cost Amortization
321

Phase II VOC and NOx emission controls are necessary only

during the high ozone period. Hence, any capital costs

associated with fuel component controls implemented solely to

achieve such emissions reductions were amortized only over that

period. In the NPRM, EPA used a 4.5 month amortization period. 

Members of the refining industry and others commented that a 4.5

month period is too short because the high ozone period is 4.5

months long at terminals and refiners will have to begin making

RFG in advance to ensure that the fuel distribution system up to

and including terminals will have turned over before the starting

date. Previous analyses performed in support of EPA's RVP

control program showed that fuel had to be produced between 0 and

60 days prior to arrival at a terminal. Thus, EPA has extended

the RFG production period to 5.5 months, or 168 days. 

The amortization of capital costs estimated by B & M over

the high ozone season was accomplished by the following steps. B

& M evaluated the cost of reformulating gasoline by running both

winter and summer refinery models, which operated off the same

set of capital equipment. Thus, the seasonal differences in fuel

quality and production volumes were analyzed by the model and any

capital equipment built to meet one season's requirements (in

this case the summer's) was available during the other season as

well. B & M's total annualized capital cost (in $ per year) for

each incremental fuel scenario was first multiplied by the ratio

of the capital recovery factors described above and then divided

by the volume of gasoline production for the ozone period. 

Incremental annual operating costs (again in $ per year) were

taken from both the winter and summer periods and divided by

summer RFG production, though practically speaking, those

occurring in the winter were quite small and generally

negligible. Thus, the operating cost per gallon RFG was

essentially that determined in the summer portion of the model.

Since the studies by Turner, Mason, and Co. for the Auto-Oil

program and WSPA were completed solely on an annual basis, it was

necessary to adjust the costs reported in those studies by

amortizing the capital related costs over the high ozone season. 

This was accomplished by separating the total manufacturing cost

into an operating cost and an annualized capital cost,

multiplying the capital cost component by the ratio of 12 months

to 5.5 months and by the ratio of the capital cost recovery

factors described above, and then adding the adjusted capital

cost to the operating costs to obtain the adjusted manufacturing

cost. This adjustment made their costs consistent with the

methodology used for the B & M data.

c. Consideration of Regional Costs

The refinery models used to estimate the costs of

reformulating gasoline were designed to model refinery operation

changes on a regional basis. Consistent with this approach, EPA
 95California is imposing its own Phase II reformulated

gasoline requirements on gasoline sold in California beginning

in 1996. The California Phase II requirements are likely to

require more severe reformulation than that of the Federal

Phase II reformulated gasoline and to exceed the federal

performance standards. Thus, it is likely that the Federal

Phase II standards will not affect fuel composition in the

State of California.

322

directed B & M to divide the nation's refining capacity into

three regions: Region 1 corresponds to PADD 1 (Petroleum

Administration for Defense District 1), Region 3 to PADD 3, and

Region 2, which covers the remainder of the U.S., excluding

California.95 The modelling and the subsequent cost analyses

were based on reformulated gasoline production from these three

areas. 

EPA had B & M evaluate the refining costs for two separate

RFG demand scenarios which bracketed the possible opt-in

scenarios envisioned for the RFG program. In one, named scenario

"A," the covered areas included the mandated nine extreme and

severe areas (minus those of California), and those areas which

had opted-in to the RFG program as of the summer of 1992. The

second, named scenario "B," included the nine mandated areas

(minus those in California), all ozone nonattainment areas which

have currently opted into the RFG program (prior to Kentucky's

recent decision), the Northeast states which are members of the

Ozone Transport Commission (OTC), and all other serious and

moderate nonattainment areas (California areas excepted). In the

case of the OTC states, the attainment areas were included as

well as the nonattainment areas. This would mean that all the

gasoline sold in the OTC areas would be RFG. 

In anticipation of many more nonattainment areas opting-in

to the RFG program, scenario "B" was chosen and analyzed for the

cost of the RFG program. At the end of the study, however,

additional areas and the OTC had still not opted into the RFG

program as anticipated by using the "B" scenario. In fact, very

few areas have opted into the program since the proposal was

made; the nonattainment areas of Kentucky are the only new

additions. Analyzing the level of opt-in at this time, only 31

percent of the nation's gasoline (excluding California) would be

RFG, which is 22 percent less than that used in the study. If

the level of opt-in remains at the current level, it is likely

that the costs of the program will have been overstated. 

However, if many more areas opt-in to the program and the level

of RFG approaches that which was modelled, then the costs will

more closely represent that of the case modelled.
323

The amount of RFG required was calculated by applying the

fraction of the total state population living in the covered

areas to the total state gasoline demand of the year 1990. These

fractions were then expressed as a fraction of national gasoline

demand and listed in the draft Regulatory Impact Analysis. The

calculated nationwide percentage of RFG was next adjusted upward

by 10 percent to account for "spillover." Spillover is the

amount of RFG which is expected to be sold either outside a

covered area, or before or after the required period of the

program. 

EPA determined this spillover rate based on information

available on the oxygenated fuels program, on its own analysis,

and on input from B & M. The oxy-fuels program has been

estimated to have a 5 percent spillover rate. This program,

however, involves minimal reformulation and, in some cases, the

fuels can even be blended at the terminals rather than at the

refinery. The greater reformulation required to make RFG

requires that refiners begin producing it sooner to ensure that

RFG formulation will meet the emission reduction standards at the

furthest point from the refinery by the program start date each

year. However, RFG costs are expected to be greater than those

for the oxy-fuel program. Thus, there will be a greater

incentive to minimize unnecessary costs, such as spillover. 

Based on the difference between the two programs, EPA recognized

that the spillover rate for the RFG program would be larger than

that of the oxygenate program. B & M, based on their expertise

in fuel distribution, recommended a 10 percent rate, which seemed

reasonable considering the differences between the two programs. 

Hence, EPA decided to use 10 percent as the spillover rate. 

The national RFG production estimate based on the scenario

described above, was then subdivided among the three gasoline

producing regions, facilitating the modelling on a regional

basis. To do this, B & M first placed each RFG area into one of

the three regions to determine regional demand for RFG. B & M

then used the historical movement of finished gasoline to

estimate which regions would supply each region's fuel

consumption. Based on this approach, the projected amount of RFG

produced by each region is listed in Table VI-1. The last column

of Table VI-1 lists the fraction of gasoline produced within that

region which is projected to be RFG.
324

Table VI-1: 

Reformulated Gasoline Production Among Various Regions

Bonner & Moore Region

(PADDs Included)

Fraction of

Total RFG

Produced in

U.S.

Fraction of

Gasoline in

Region that is

RFG

Region 1 (PADD 1) 0.21 0.96

Region 2 (PADDs 2, 4,

and 5; excl. CA)

0.24 0.36

Region 3 (PADD 3) 0.55 0.55

These figures are useful in understanding the cost data in

several ways. The regional RFG production fractions listed above

were used to weight the costs for each region and develop a

national cost estimate. The larger the contribution by any one

region to the quantity of RFG produced nationally, the larger the

effect of that region's costs on the overall RFG program cost. 

Hence, the fact that most RFG will be produced in Region 3 is

useful in understanding the various trends in costs. Also, the

fraction of gasoline produced as RFG in any one region is useful

in understanding why costs may be high in one region and low in

another. The higher the percent RFG, the higher the relative

cost, since more severe reformulation of a refinery's gasoline

pool is likely required. Since the assumptions regarding the use

of reformulated gasoline by the OTC are significantly higher than

what is now expected, the costs estimated for Region 1 are higher

than those likely to occur. The Region 1 costs would be

considerably lower if a larger non-RFG market had been assumed,

since refiners would have had more flexibility in producing their

entire product slates. 

For similar reasons, marginal costs to produce RFG may be

higher for small refiners than those estimated by the regional

refinery models, unless a sizeable market exists for conventional

fuel. Given the apparent unlikelihood that the Northeast OTC

will use Title I of the Clean Air Act to require RFG in

attainment areas as well as non-attainment areas, it appears that

all regions of the U.S., even Region 1, will have sizeable

conventional gasoline demands. This demand will provide a

profitable conventional fuel outlet for the fuel from the small,

high RFG cost refiners.

In contrast to the Bonner and Moore studies, the abovereferenced Turner, Mason, and Co. studies performed for both WSPA

and Auto-Oil (and some of the studies performed for API) assumed

all the gasoline produced in a specific PADD was reformulated. 
 96Turner, Mason & Co., April 1992.

325

Because of the lack of refining flexibility expected from 100%

production of RFG, the costs derived from these studies are

likely higher than what would be experienced by the average

refiner under the expected level of participation in the program. 

Hence, for the fuel parameter changes for which the Turner/Mason

costs had to be used, the overall cost and cost-effectiveness are

expected to be overstated and therefore somewhat conservative. 

There are a few cases when multi-regional costs were not

available for developing national costs. This occurred in two

cases when the B & M refinery model data was supplanted by other

data determined to be more appropriate. However, to be

consistent with the multi-regional approach, it was necessary to

develop adjustment factors that would approximate a broader

source of costs. These factors would adjust a single regional

cost to a (non-California) national cost. 

For these cases, the regional to national cost adjustment

was made by the same methodology used in the draft RIA. In that

case, Turner/Mason, working for Auto-Oil,96 determined the

refining costs to reduce olefins, T-90 and aromatics, and to add

oxygen, in each PADD. The cost from each PADD was integrated

with the projected production of RFG to develop regional

adjustment factors. The following table summarizes the

adjustment factors used to adjust costs from certain regions of

interest to a non-California national cost, representing the RFG

costs in all three regions. 

Table VI-2: 

Factors for Adjusting Regional Costs to National Costs

Adjustment Made Adjustment Factor

PADD 5 to National Cost 1.38

PADD 3 to National Cost 1.14

PADD 1 to National Cost 0.89

One comment on the methodology used in the proposal

presented results of an informal survey of several members of the

refining industry, and used these results to argue that EPA's

analysis understated the costs of Phase II RFG. Although the

commenter acknowledged that the results were based on only a

fraction of the refiners who will be affected by this rulemaking,

the commenter summarized the results as follows. First, a number
326

of large refineries will not make RFG (i.e., they will only

produce conventional gasoline). Second, for the refiners that do

make RFG, RFG will constitute a large fraction of the products

from that refinery. Finally, costs will likely vary between

refiners, and most refiners will be limited by one or two

parameters in making RFG. These results led to the conclusion

that RFG costs will be higher than those proposed by EPA. 

While the commenter's interpretation that the survey results

indicates that costs will be higher than those estimated by EPA,

the survey can also be interpreted to indicate that costs will be

lower than those represented by the oil industry and thus support

EPA's approach to estimating costs. First, the fact that not all

major refiners plan to produce reform argues for reduced costs,

not increased costs. All the refinery models employed to

estimate RFG costs model all the refineries in a given region or

PADD. These refineries include those whose process configuration

is advantageous for producing RFG and those whose processes are

not. It is most likely that the refiners who will choose not to

make RFG are the ones who cannot do so in a cost-effective

manner. If the production costs for such refineries were removed

from the calculation of regional costs, the regional costs would

be lower than the averages calculated by the existing models. 

Second, how the connection between fewer refineries planning

to produce RFG and higher RFG fractions for those refiners should

affect the use of EPA's RFG cost estimates is not clear. The oil

industry's refinery modelling assumed high RFG fractions for all

refineries and that is clearly more onerous than the actual

situation is likely to be. EPA, through its refinery modelling

by Bonner and Moore, assumed more realistic RFG fractions and

allowed the refinery model to determine how to produce RFG. One

industry comment on EPA's approach has been that it allows the

model to build too few, but very large, units to satisfy the RFG

demand for an entire region or PADD. This approach is actually

confirmed by the oil industry survey. While EPA's approach could

potentially underestimate costs by allowing the refinery model

too much flexibility in shifting low and high emission components

around within this massive regional refinery, EPA finds no

evidence that this actually occurred. When the model

occasionally produced very low costs for Region 2, which had the

lowest RFG fraction, EPA decided not to use these results, but

instead based its RFG costs on those estimated by Bonner & Moore

for Regions 1 and 3.

Third, the survey indication that most refiners' production

of RFG will be limited by one or two fuel parameters is

consistent with EPA's modelling approach of focusing on

improvements in a single fuel parameter while holding all others

constant or allowing them to improve (i.e., lower emissions). 

While the sophistication of imbedding the complex model into a

refinery model is still technically preferred, the survey results
 97Lester Wyborny, U.S. EPA/FSSB, "DOE and API Phase II Cost

Estimates," Memorandum to the Air Docket, November 4, 1993.

327

indicate that the added sophistication may not significantly

affect the results. 

3. Fuel Component Control Costs

The costs of modifying the various fuel parameters have been

significantly updated relative to those in the draft RIA. In the

draft RIA, it was generally necessary to extrapolate costs

representing only a single region or PADD to the entire nation. 

Most often the region for which costs were available (i.e.,

California) would not even be producing Federal Phase II RFG

since the California Phase II RFG standards are more stringent. 

Although an attempt was made to develop national average costs

from that data, such costs are almost inherently less accurate

then those developed by actually modelling the refineries of each

covered region. 

Since the time the draft RIA was developed, a number of

studies (performed by both B & M and Turner/Mason) have evaluated

RFG costs in more than one region and generally provide much

improved estimates of fuel reformulation costs. In addition, EPA

funded its own study. The greater access to cost data allows EPA

more capabilities in determining and comparing RFG program costs. 

The following sections describe the costs estimated for

controlling each fuel parameter, including any adjustments made

which have not already been described. After all fuel parameter

costs have been described and combined with the complex model to

estimate the cost-effectiveness of emission control, the results

will also be compared to those of refinery studies which imbedded

the complex model into the refinery model to generate costeffectiveness estimates directly. The final costs used in this

analysis are summarized in subsection 5 below. The derivation

of the final costs are shown in Tables VI-A1, VI-A2, VI-A3 and

VI-A4 in the Appendix.

a. RVP Control Costs

The B & M refinery model were used to project the cost of

RVP control.97 The cost of RVP control was modelled from 8.0 psi

down to 7.3 psi for the first increment, down to 7.1 psi for the

second increment, and down to 6.5 psi for the third increment. 

Although the ranges over which the parameter values changed for

each region did not agree exactly, the costs for the most similar

ranges were grouped together. The fuel economy adjusted costs

for a RVP reduction from 8.0 to 6.5 psi were about 0.7¢/gal. As

shown below in section F, reducing RVP to control VOC emissions
328

is very cost effective all the way down to 6.5 RVP. Although a

further reduction below 6.5 psi would likely be cost effective,

such reductions were not considered because, as discussed in

later sections, it is not known whether driveability problems

would result at lower RVPs. Also, no exhaust emission data exist

below 6.5 RVP, so possible increases in exhaust emissions could

not be ruled out. 

The low costs for RVP control estimated by the B & M model

cost data are corroborated by other studies which also have

evaluated the cost of RVP reductions. The NPC study showed that

when the fuel economy effect is taken into account, initial RVP

reductions down to 7.2 psi were virtually at no cost, while

further RVP reductions down to 6.5 psi were made at a 1.2¢/gal

cost. Although cost figures were not available from the DOE

study, DOE concluded that RVP costs for VOC control were much

cheaper and cost-effective relative to other any parameter

changes which would also reduce VOC emissions. 

b. Sulfur Control Costs

The B & M regional refinery models were also used to

estimate the costs of sulfur control. Sulfur control was

modelled down to 250 ppm for the first increment, to 160 ppm for

the second increment, to 100 ppm for the third increment, and to

50 ppm for the last increment. The sulfur costs for the value of

138 ppm sulfur used in setting the NOx standard was interpolated

from the other data using a curve fitting program available in

Cricket Graph. As shown in Table VI-A2 located in the appendix,

the B & M Region 2 costs are quite low compared to those for

Regions 1 and 3. This is likely due to the low fraction of RFG

being produced in Region 2, as described above. These very low

costs could be realistic, representing the ability of refineries

to shift blendstocks between conventional fuel and RFG to reduce

sulfur very inexpensively. However, they could also represent an

unrealistic flexibility to do this, given that the entire

region's refinery capability was combined into a single refinery. 

Insufficient time prevented further analysis to resolve this

issue. In order to avoid the possibility of underestimating the

cost of sulfur control, the Region 2 costs were excluded from the

analysis and the nationwide cost was generated by weighting the

Region 1 and 3 costs using renormalized weightings from Table VI1 above. 

The B & M Region 3 sulfur control costs were compared to

Region 3 (PADD 3) cost data generated by Auto-Oil and API, both

studies performed by Turner, Mason, and Co. These other studies

were adjusted to a 10% rate of return on investment and the

capital costs were amortized over the high ozone season to make

the studies consistent. As shown in Figure VI-A1 (see the

Appendix), the Auto-Oil costs turned out to be very similar to

the B & M sulfur costs over the range from 340 ppm down to 100
 98"Documents Concerning Refinery Modeling for the

Reformulated Gasoline Program," EPA Memorandum From Lester

Wyborny, RDSD to the Docket, . 

 99Turner, Mason & Company, November 18, 1993.

329

ppm; about 1.5-1.6¢/gal. The API costs (based on refinery

modelling cases VAT and VH), however, are about twice that of the

Auto-Oil and B & M costs over a smaller range. The API parameter

data for those refinery model runs indicated that there were also

some increases in E200 and E300 along with the sulfur reductions. 

It is feasible that the refinery model used by API, with the

complex model integrated in the model, would have made these

changes to realize the necessary reductions in VOC. However, it

is doubtful that the model would have actively reduced these

parameters considering their higher cost per pollutant reduced as

determined in this study. Instead, it is likely that they

increased as a result of refinery changes associated with

reductions in sulfur or other parameters. If one assumes that

E200 and E300 were purposefully reduced by the API version of the

model, thereby incurring a reformulation cost, the cost for that

refinery model run can be adjusted to account for the full E200

and E300 reduction. The E200 and E300 costs derived in this

analysis were used for that purpose. The adjusted API costs are

indicated on Figure VI-A1 as a dashed line. Even after this

adjustment, the API costs are still substantially higher than

that those from B & M and Auto-Oil. 

Because of the importance that sulfur reductions play in

controlling NOx emissions, EPA held a number of discussions with

DOE and API in an attempt to determine the differences between

the API costs and those generated by B & M and other studies,

like the Auto-Oil study compared here. The discussions centered

around several documents which summarized the approaches or

critiqued approaches of these models. These documents include a

list of the underlying assumptions used in the API refinery

modeling runs by Turner/Mason, a critique of the B & M refinery

runs by Turner/Mason, and a reply by B & M to the Turner/Mason

critique.98 The numbers used in this final analysis represent

EPA's best estimate of the costs of sulfur control, taking all of

these other issues into account.

c. Olefins Control Costs

EPA based its cost of olefin reductions on those estimated

by Turner/Mason for WSPA99 instead of those generated by B & M. 

The B & M estimates were not used because much of the olefin

content was used to make oxygenate (in the form of TAME or MTBE)

prior to the olefin reduction refinery modelling runs. Since the
330

olefin level was already partially reduced, the cost of reducing

olefins in a subsequent step may not reflect the true cost of

olefin control at lower oxygen levels. Based on the results of

the cost-effectiveness analyses described below, EPA does not

expect the overall RFG pool oxygen content to increase much above

2.1 weight percent prior to the reduction of olefins for NOx

control, which should reduce the olefin demand from the levels

predicted by the refinery modelling. 

Turner/Mason estimates of olefin control costs for both WSPA

and Auto-Oil were considered for use here. The WSPA estimates

were determined to be more desirable for cost-effectiveness

purposes because they were expressed as a series of reductions

instead of one single large reduction. To compensate for the

fact that the WSPA study was based solely on California

refineries, the WSPA olefin costs were increased by the 38

percent adjustment factor described above. The WSPA analysis

contained cost data for olefin reduction in increments of 11 down

to 8 percent, and then down to 5 percent. The cost to decrease

olefins from 11 to 8 percent was estimated to cost about

0.4¢/gal, while further reductions to 5 percent were projected to

cost 2¢/gal. 

d. Oxygen Control Costs

For the February 26, 1993 proposed rule, EPA based its

oxygenate costs on the Auto-Oil (A/O) study of the RFG program,

which relied upon MTBE as the oxygenate. The purchased price of

MTBE was estimated by A/O to be about 60¢/gal. In comments

received on the proposed standards, it was suggested that the

analysis in the draft RIA underestimated the cost of oxygenate

because it used current contract prices for MTBE rather than

projections of future prices. As will become evident below, the

final rule is based on much higher oxygenate market prices, and

even includes a price range of oxygenate costs to account for

potential future price fluctuations. Furthermore, the choices of

oxygenates was expanded beyond MTBE to include TAME and ethanol. 

For the final rule, the per-gallon costs for an oxygen

increase from 2.1 percent (the control level under Phase I

averaging) to 2.7 percent were initially taken from the B & M

refinery model cost data. The model could choose among the

production or purchase of TAME and MTBE, or the purchase of

ethanol. TAME and MTBE were generally produced at the refinery

although MTBE was sometimes purchased from the outside, while the

ethanol was always purchased from the outside. Based on this

approach and the built-in economic criteria, the model generally

preferred ethanol as the most cost effective choice for the

addition of oxygen for Phase II RFG.

Table VI-3 below summarizes the oxygenate prices used by the

model. To account for the historical fluctuations in oxygenate
331

prices, the cost analysis was expanded to consider a range of

oxygenate prices. Table VI-3 also contains the ranges in

oxygenate prices which were used in this expanded analysis. The

Phase I cost analysis located in section V contains a description

of the reasoning behind the values used in the oxygenate price

range. In general, the range represents the range in oxygenate

prices observed over the last several years. 

Table VI-3: Oxygenate Costs

Oxygenate

B & M Model

Costs Cost Range Used by EPA

Ethanol $1.20 Before Subsidy $1.20 - $1.60

After Subsidy $0.66 - $1.06

MTBE $1.05 $0.80 - $1.05

Methanol $0.57 $0.40 - $0.57

The Phase II RFG oxygen addition costs for Regions 1, 2 and

3 determined by the B & M refinery model were then adjusted to

reflect this revised range of possible oxygenate prices. In

Table VI-4 below, the cost of oxygenate addition determined by

the B & M refinery model is listed first followed by the adjusted

costs. The regional oxygenate costs were combined into a U.S.

cost by weighting each regional cost by the fraction of RFG

produced by that region (see Table VI-1). The national average

cost was used to determine the cost-effectiveness of adding

oxygen to Phase II RFG (above the level of 2.1 wt% oxygen).

Table VI-4: Phase II RFG Oxygen Addition Costs

Geographic Area

 Estimated RFG Costs

 B & M Refinery Model 

 (¢/gal RFG)

 

 RFG Cost Range

 (¢/gal RFG) 

Region 1 1.37 0.62 - 1.23 

Region 2 1.12 (0.25) - 0.76

Region 3 1.16 0.32 - 1.00

U. S. 1.20 0.24 - 0.99 

 (0.61 average)
 100E300 was calculated from T-90 using the formula: E300 =

155.033 - (T90 x 0.22)

332

e. E200 Control Costs

E200 control costs were developed using EPA's in-house

version of the B & M model. No other studies evaluated the costs

of controlling E200 alone. (E200 was monitored and varied in a

number of the refinery studies which imbedded the complex model

in a refinery model and which are evaluated in section G below.) 

While these costs were not reviewed by B & M personnel, in

general, the E200 costs seemed reasonable for the changes in

gasoline characteristics that occurred. However, because the

refinery model was not specifically designed to evaluate all of

the E200 control technologies currently available, the costs may

be somewhat high. The B & M model estimated the costs of

controlling E200 in 3 percent increments. 

f. E300 Control Costs

E300 control costs were taken from the Auto-Oil study. 

Attempts were made to derive the E300 costs in-house using the B

& M model. Results of these modelling runs were insufficient,

however, because the costs quickly escalated for even small

increases in E300. A review of the refinery processes used by

the model to increase E300 revealed that the model was not

programmed with sufficient analytical tools to make accurate

estimates. Thus, the Auto-Oil E300 costs were used instead. 

Although WSPA costs were also available, those costs were from

refinery runs of Padd 5 refiners, which are not even covered by

the Federal RFG program. The Auto-Oil costs from Padd 3 are

therefore considered more relevant to this study. Furthermore,

because both studies were done by Turner/Mason, the costs should

have been be derived using nearly identical approaches. 

The E300 costs based on Auto-Oil were calculated from T90

control using a formula derived by EPA to convert to E300, the

derivation of which is described in section III.100 The costs

were adjusted upward by 14 percent to project PADD 3 costs to

nationwide costs. For the E300 study for Auto-Oil, Turner/Mason

used increments from 84 to 88% evaporated, 88 to 91% evaporated,

and 91 to 96% evaporated. The adjusted cost to increase E300 to

88 percent cost 1.1¢/gal, to increase to 91 percent cost

1.9¢/gal, and to increase to 96 percent cost about 4¢/gal.

g. Aromatics Control Costs

Aromatics control costs were derived from the B & M refinery

model by EPA. The aromatics concentration was reduced to 28
333

volume percent for the first increment, down to 24 percent for

the second increment, and down to 20 percent for the third

increment. When the Region 2 costs were compared to Regions 1

and 3, it was decided that their costs should not be not used

because of their much lower values. As stated above, because

there was insufficient time to verify that the less expensive

parameter reductions generated by the Region 2 refinery model for

some parameters were made in a realistic fashion, EPA elected to

err on the conservative side and drop the costs from the cost

analysis. The aromatics costs were therefore based only on

Regions 1 and 3. 

The B & M aromatics costs were compared to those generated

by WSPA and Auto-Oil (which, as PADD 5 models, were adjusted to a

nationwide basis by the 1.38 factor developed previously). The

WSPA costs were determined to be 2.9 cents per gallon over a 3

percent aromatics change between 25 and 22 percent. The Auto-Oil

costs proved to be 12 cents per gallon over an aromatics

reduction from 45 vol% to 20 vol%. To provide for a comparison

among the data, the Auto-Oil cost was ratioed down to represent a

3 percent aromatics change and the cost was determined to be 1.7

cents per gallon. Both the WSPA and the adjusted Auto-Oil costs

are higher than that generated from the B & M models which, for a

reduction from 25 to 22 percent, was projected to cost 1.3 cents

per gallon. The methodology used by the B & M model is different

from that observed in the Auto-Oil study and results in less

aromatics reduction upon the addition of oxygen. Considering

that aromatics was not a cost-effective means for reducing any of

the controlled pollutants even at the lower B & M control cost,

and due to time and resource restraints, EPA did not evaluate

further the reason for the cost differences among the different

models. 

The first incremental aromatics reduction from the B & M

cost data was not needed in the cost-effectiveness analysis

because the aromatics concentration in the Phase I RFG parameter

data, which formed a starting point for the Phase II analysis,

had already decreased to a level below the lower value of that

range. As described more fully below in the parameter

interrelationships section, it was necessary to adjust the Phase

I parameter values to ensure that the final Phase I RFG parameter

values would reflect a sufficient aromatics reduction to meet the

toxics requirements. 

4. Fuel Economy Effects 

Reformulating gasoline to reduce emissions can affect the

vehicular fuel economy. In the draft RIA, EPA found that the

change in a fuel's heat content is currently the best indicator

of the change in fuel economy between fuels of different

compositions. In this section, the methodology for estimating

the costs attributed to the changes in the heat content of RFG
334

will be described. The changes in fuel economy are associated

with specific RFG parameter changes, including increased oxygen

content, reduced RVP, reduced aromatics content, and increased

E300. As found in the draft RIA, most other fuel components are

expected to have relatively minor effects on fuel economy and

thus the impacts of these effects were not included in the

analysis. 

a. Changes in Fuel Economy

In the draft RIA, EPA listed the estimated fuel economy

impacts of various fuel parameter changes as determined by AutoOil and ATL (under contract with EPA) testing. However, the test

data for some of the parameter changes varied significantly in

magnitude. This variance is largely attributed to measure

uncertainty in both the fuel and emissions, as well as the effect

of changes in other fuel parameters that were not controlled by

the test programs and variability in vehicle operation between

tests. In the draft RIA, EPA found that fuel economy generally

changed in proportion to fuel heat content. No comments that

were accompanied by any data or engineering analysis not already

considered in the draft RIA were received challenging this

finding.

In order to estimate the effect of various fuel

reformulations on heat content and, therefore, fuel economy, EPA

had B & M calculate the heat content of reformulated gasoline as

they ran their refinery models for economic purposes. This was

done for oxygenate addition and RVP reduction. These calculated

effects were used in lieu of the test data, since the test fuels

did not necessarily reflect the other changes in gasoline

properties likely to accompany either oxygen addition or RVP

control. One drawback of B & M calculating the fuel economy

effect for RVP is that the evaporative effects were not

considered; the RVP adjusted costs for fuel economy effects are

expected to be somewhat overstated for this reason. B & M did

not evaluate the fuel economy impacts of adjusting E300 or

aromatics, and thus the available test data was used. Since the

test data also showed a very minor fuel economy impact for olefin

reductions, B & M was not asked to evaluate olefins for their

fuel economy effect and any effects were considered negligible. 

Sulfur has not been found to cause a fuel economy impact and also

was not studied. The fuel economy impact estimates made from the

test data and B & M study are listed below in Table VI-5.
335

Table VI-5: Fuel Economy Impacts of Fuel Parameter Control

Parameter

Studied Study

Energy Impact per Unit

Parameter Change

Oxygen - MTBE Auto-Oil I -0.9/wt% increase

Auto-Oil VI -0.70/wt% increase

EPA ATL (Phase I) -0.5/wt% increase

Bonner and Moore -1.05/wt% increase

Oxygen - EtOH Auto-Oil VI -0.61/wt% increase

Bonner and Moore -0.95/wt% increase

Oxygen - ETBE Auto-Oil VI -0.64/wt% increase

RVP Auto-Oil VI 2.6/psi decrease

EPA ATL 0.7/psi decrease

Bonner and Moore 0.3/psi decrease

T90(E300)* Auto-Oil I -0.02/deg F increase

(-0.0732/%E300

decrease)

EPA ATL 0.003/deg F increase

(0.013/%E300 decrease)

Average:

T90/E300

-0.009/deg F increase

(-.03/%E300 decrease)

Aromatics Auto-Oil I -0.12/vol %

* E300 was calculated from T-90 using the formula: E300 = 155.033 - (T90 x

0.22)

For adding oxygenate, B & M first calculated that

conventional gasoline contains about 4.75 million BTU per barrel,

and MTBE and ethanol, the oxygenates blended in the largest

quantities in their analysis, contain 3.92 and 3.19 million BTU

per barrel, respectively. They then calculated the decrease in

energy that occurred by supplanting some of the conventional

gasoline with oxygenate to yield a fuel containing 2.1 weight

percent oxygen (an 11.5 volume percent addition of MTBE or 6.0

volume percent addition of ethanol). The calculation showed that

the heating value of the resulting gasoline-MTBE blend would be

2.1 percent less energy dense than conventional gasoline, or that

the gasoline/ethanol blend would be 1.9 percent less energy dense

than conventional gasoline. As an approximation, EPA assumed
336

that either oxygenate would reduce the energy content of gasoline

by about 2 percent.

B & M made a similar calculation for reducing RVP. In their

analysis, butane was the only component removed to control RVP;

an eight percent decrease in butane content resulted in a 1.2

percent increase in heating value. EPA then calculated that

based on an RVP blending value for butane of 60 psi, each two

percent reduction in gasoline butane content would result in

about one psi change in RVP. The application of these two

figures determined that each psi decrease in RVP would result in

about a 0.3 percent increase in fuel economy. 

b. Fuel Consumption Costs

The percentage changes in fuel economy identified above can

be converted to a monetary cost by multiplying them by the retail

(less taxes) price of gasoline, here estimated to be 85 cents per

gallon. This price is 5 cents per gallon higher than that used

in the draft RIA to accommodate the cost of producing Phase I RFG

(the high end of the range presented in Section V). This fuel

economy cost is then added to the refining cost. The effects of

this calculation are demonstrated in the following summary table.

5. Summary of Fuel Parameter Control Costs

The refinery costs determined by the methodologies explained

above are listed below in Table VI-6. The costs are expressed in

cents per gallon per unit change in the given parameter (i.e.,

for RVP, the unit quantity is one psi) as indicated by the last

column. In all cases, the cost is applicable to the range

incremental to the previous range. For example, the cost for

sulfur reduction down to 160 ppm covers the cost for reducing

sulfur from 250 ppm to 160 ppm, and does not include the cost of

reducing sulfur to 250 ppm. To determine the cost for reducing a

parameter over part or all of a range, the change in fuel

parameter value (final value minus the starting value) would be

multiplied by the fuel economy adjusted cost.

The first three columns of the summary table show the cost

in each region, as determined by each individual regional

refinery model. Where a space for a regional cost is left blank,

that cost was either not determined by the B & M refinery model,

or the cost was not used for the reasons described above. The

regional costs were factored into a national cost using the

expected fraction of RFG produced by each region, as described

above. The national cost is then adjusted by the fuel economy

effect calculated for that parameter, one exists.
337

Table VI-6: Incremental Costs for Individual Parameter Changes

Fuel

Parameter &

Control

Level

National

Average

Cost

Fuel

Economy

Effect

(c/gal/x)

Fuel

Econ.

Adjusted

Cost

 Units

(for columns

2 and 5)

(c/gal/x)

RVP to 7.3 0.412 0.220 0.192 x = psi

RVP 

7.1 to 7.3

 0.416 0.220 0.196

RVP 

7.3 to 6.5

 0.427 0.220 0.207

Sulfur to

250

 0.00203 - 0.00203 x = ppm

Sulfur 

250 to 160

 0.00625 - 0.00625

Sulfur 

160 to 100

 0.0125 - 0.0125

Olefins to

8.0

 0.179 - 0.179 x = %

Olefins 

8.0 to 5.0

 0.922 - 0.922

Oxygen 

2.1 to 2.7

 1.14 0.85 1.99 x = %

Aromatics to

28

 0.0664 0.085 0.152 x = %

Aromatics 

28 to 24

 0.305 0.085 0.391

Aromatics 

24 to 20

 0.367 0.085 0.452

E300 (+4)

84 to 88 

 0.285 0.026 0.311 x = %

E300 (+3)

88 to 91 

 0.645 0.026 0.671

E300 (+5)

91 to 96

 0.634 0.026 0.660

E200 (+2,+3)

to 58 

 0.125 - 0.125 x = % 

E200 (+3)

58 to 61 

 0.439 - 0.439

E200 (+3)

61 to 64 

 0.989 - 0.989
338

D. Derivation of Fuel Parameter Interrelationships

Controlling one parameter of a fuel (a fuel property or

component) can affect the levels of other fuel parameters, since

the refiner will compensate for the change by adjusting the fuel

composition to meet minimum gasoline specifications in the manner

which is most cost effective for its refinery. This effect of

one fuel parameter on another is hereafter referred to as an

interrelationship. To be able to determine the emissions that

would result from a change in a single fuel parameter, it is

necessary to estimate the final fuel composition based on these

interrelationships. 

1. Methodology

For the draft RIA, factors representing fuel parameter

interrelationships (or fuel component interactions, as they were

called in that document) were developed from the available

refinery modelling data. In response to this information, EPA

received several comments. One stated that the change in fuel

properties was underestimated for some parameters and

overestimated for others. Specifically, the commmenter claimed

that EPA appeared to recognize the dilution effects of adding

oxygen, but that it was not clear that this was always included

in the analysis. Since specific references to the areas where

EPA overlooked the impact of adding oxygen, or other cases where

EPA over- or underestimated the impacts of various fuel

parameters, it is difficult to respond directly to this comment. 

As explained below, the analysis of parameter interrelationships

has been revised based on new information and is believed to be

reasonable. When an interrelationship between two parameters was

identified, this was used consistently throughout the analysis.

A second comment raised a concern with the fact that EPA

used data from a single PADD when developing these parameter

relationships, assuming that the effects seen in this one PADD

would be experienced in other PADDs (which is not necessarily the

case). The refinery modelling data presented in the draft RIA

and used to develop parameter interrelationships was limited in

its applicability to the RFG program for several reasons. The

data was based largely on a single PADD (usually PADD 5, in some

cases PADD 3) model, not on multiple PADD data (which could be

averaged to develop a national factor). The refinery costs and

operating parameters for one PADD are unlikely to be

representative of what a typical refinery elsewhere in the

country would experience. Furthermore, refineries in PADD 5,

which supply California's fuel, are somewhat different than

refineries elsewhere because of the greater percentage of

hydrocracker capacity in the PADD, and because of the heavier

crude feedstocks used there. California is developing its own

RFG program and Federal Phase II RFG will not likely be produced

in PADD 5. Hence, for most fuel parameter changes analyzed in
339

this study, parameter interrelationships were developed from new

refinery modelling data for multiple regions, generated by the

Bonner and Moore (B & M) refinery model; exceptions to this are

discussed below.

Data was generated for each of the three regions defined by

B & M (discussed in subsection 2.c above). The methodology for

determining parameter interrelationships was similar to that used

to estimate costs. Each parameter interrelationship was

determined for the entire range over which the primary parameter

was changed. The interrelationship was expressed as a ratio of

the percent change in the secondary (uncontrolled) parameter to

the overall change in the primary (controlled) parameter. For

example, if reducing the sulfur level from 250 ppm to 160 ppm

resulted in a change in olefin content from 5.5 vol% to 5.3 vol%,

then it was assumed that for every change of -90 ppm sulfur

(within the approximate range of 250 to 160 ppm), the olefins

content would change -3.8% [=(5.5-5.3)/5.5 x 100]. The

interrelationship factor would thus be 0.042% olefins/ppm sulfur

[=-3.8%/-90ppm].

Interrelationship factors were developed for each of the

three refining regions. A single interrelationship factor

representing the average national impact was then developed by

weighting the factor for each region by the fraction of total

(national) RFG produced by that region (see Table VI-1 above).

These factors were included in the RFG cost-effectiveness

analysis only if it was determined that the factors represented a

significant and consistent relationship between the two

parameters. These engineering judgements were made on the basis

of the magnitude of the factor, the consistency of the trend

between the three regions, and the confidence in the refinery

modelling outputs (i.e., did the results agree with what would

likely happen in a refinery).

The following table presents the results of this analysis of

parameter interrelationships. The factors listed in the last

column are national parameter interrelationship figures derived

from the various refining regions and were used in the RFG costeffectiveness analysis to represent the interrelationship of

various fuel parameter changes. Details of the derivation of

these factors are provided below.
340

Table VI-7: Fuel Parameter Interrelationship Factors

Controlled

Parameter Range of Control

Uncontrolled

Parameter

(% Change in Uncontrolled)/

(Real Change in Controlled)

Phase I:

Oxygen

Benzene

RVP

Up to 2.1 wt%

Down to 0.95

vol%

Down to 8.0 psi

Sulfur 91% of Baseline Value1/

E200 114% of Baseline Value2/

E300 102% of Baseline Value

Aromatics 80% of Baseline Value

Sulfur Down to 250 ppm Olefins 0.033

250 to 160 ppm 0.011

160 to 50 ppm 0.046

Down to 250 ppm Aromatics 0.008

250 to 160 ppm 0.013

160 to 50 ppm 0.042

Olefins Down to 6.9 vol% E200 1.791

6.9 to 5.0 vol% 1.699

RVP Down to 7.3 psi E200 4.146

7.3 to 6.9 psi 2.643

6.9 to 6.5 psi 5.663

Oxygen 2 to 2.7 vol% Aromatics -7.297

2 to 2.7 vol% E200 1.064

Aromatics Down to 28 vol% E300 -0.583

28 to 24 vol% -0.336

24 to 20 vol% -0.392

E200 Up to 54 %evap E300 0.221

54 to 57 %evap 0.338

57 to 60 %evap 0.340

E300 Up to 88 %evap E200 1.282

88 to 91 %evap 0.600

91 to 96 %evap 0.707 1/The fuel parameter interrelationships of Phase I RFG were combined and

represented as a straight percent change from the baseline value (see text).

2/ For VOC control region 1, the increase in E200 was only 111% from baseline for Phase

I RFG, reflecting the fact that more light compounds are removed to reduce the RVP to

the lower level of 7.8 psi in this area.

2. Individual Fuel Parameter Interrelationships

a. Phase I RFG Parameters

Although the Phase II RFG analysis is separate from that

for Phase I, it is important to understand the parameter
 101Bonner and Moore Management Science, "Study of the

Effects of Fuel Parameter Changes on the Cost of Producing

Reformulated Gasoline," Prepared for EPA under contract through

Southwest Research Institute, (see "DOE and API Phase II Cost

Estimates," EPA Memorandum from Lester Wyborny, FSSB, to the

Air Docket, November 4, 1993.)

341

interrelationships of the Phase I requirements (2.1 wt% oxygen,

0.95 vol% benzene, and RVP at 8.0 psi) since they determine the

starting fuel composition of the Phase II fuel. The standards

for Phase II RFG are based on the percent reduction in

emissions from the Clean Air Act baseline fuel emissions. 

However, the cost-effectiveness of Phase II RFG is based solely

on the costs incremental to those incurred by refiners in

meeting the Phase I standards. 

The Bonner and Moore refinery modelling data obtained since

the draft RIA included a revised analysis of the production of

Phase I RFG. This data was reviewed to determine the Phase I

parameter interrelationships.101 The methodology outlined above

for determining the B & M parameter interrelationships for each

parameter change could not be followed for the Phase I data

because the Phase I refinery model run included changes in all

three parameters. To represent the fuel parameter changes

resulting from implementation of the Phase I RFG requirements,

the overall percent change from baseline for each uncontrolled

parameter affected by these changes (aromatics, olefins,

sulfur, E200, and E300) was calculated from the B & M data. 

The results of this calculation are presented in Table VI-8

below.

Table VI-8: Phase I RFG Interrelationships (Bonner & Moore)

Controlled

Parameter

Range of Control Uncontrolled

Parameter

% of Original

(Baseline) Value

Oxygen

Benzene

RVP

Up to 2.1 wt%

Down to 0.95

vol%

Down to 8.0 psi

Sulfur 94

E200 105

E300 104

Aromatics 89

 

The Phase I parameter interrelationships determined from

the B & M data were different than those presented by other

studies. Specifically, the addition of oxygen appeared to have

little impact on the aromatics content beyond simple dilution,

even though other studies, such as that performed by Auto-Oil,
342

show that aromatics would be reduced beyond the level achieved

by dilution since the oxygenates can replace octane usually

provided by aromatics. The small change in aromatics by the B

& M refinery model is probably caused by the refinery model's

large use of olefins to produce oxygenates. Since some of the

increase in octane from the addition of oxygenate was offset by

the loss in high octane olefins, aromatics could not decrease

as much as expected, resulting in higher aromatic values. 

Because this approach is not expected to be taken by refiners

who also must meet the toxics requirement, a more average

approach than that by B & M was adopted. 

The data presented in the draft RIA, based on Auto-Oil

studies, showed a slightly different relationship between the

various fuel parameters as a result of the Phase I RFG changes. 

Although the Auto-Oil data was based on modelling of refineries

in a single PADD, most of these relationships were similar to

those seen in the new Bonner & Moore data. However, the change

in aromatics as a result of the addition of oxygen was more

reasonable in the Auto-Oil data. The relationships between

parameters calculated from the Auto-Oil data are shown in Table

VI-9. 

Table VI-9: Phase I RFG Interrelationships (Auto-Oil)

Controlled

Parameter

Range of Control Uncontrolled

Parameter

% of Original

(Baseline) Value

Oxygen

Benzene

RVP

Up to 2.1 wt%

Down to 0.95

vol%

Down to 8.0 psi

Sulfur 86

E200 120

E300 104

Aromatics 71

 

The parameter interrelationships for the Phase I RFG used

as the starting point for the Phase II RFG cost-effectiveness

analysis were determined from a combination of Bonner and Moore

and Auto-Oil data, since neither study presented the best

relationships between parameters for Phase I RFG. For each

uncontrolled parameter, the percent change from baseline

calculated from these two studies was averaged for each region

for which data was available. The national weighted average

percent change was then calculated and used in the costeffectiveness analysis. These combined values are listed in

Table VI-7.
343

b. Impact of Reducing Sulfur Content on Other Fuel Parameters

There are essentially three options available to reduce the

sulfur content of gasoline. The majority of sulfur in finished

gasoline results from the gasoline components coming from the

FCC unit. One option to reduce the sulfur level is to

desulfurize the feed to the FCC unit; this would not impact

other finished gasoline parameters. The other options are to

desulfurize the output of the FCC unit or to use less FCC

gasoline in the finished product. These options would result

in a reduction in the level of olefins in the final product,

since these streams are also high in olefin content. This

reduction in olefins decreases the octane of the gasoline,

which must be made up by increasing the level of oxygen,

aromatics, or alkylates in the finished gasoline.

The refinery modelling data used in this analysis indicated

that reducing the sulfur content of reformulated gasoline may

have some impact (depending on the refining region and the

level of sulfur control) on olefins, aromatics, E200, and/or

E300. This data is presented in Table VI-10. In addition, the

table shows the percent change in the uncontrolled parameter

resulting from each change in sulfur content.
344

Table VI-10:

Data Used to Develop Sulfur Interrelationship Factors

Controlled

Parameter Region From To

Uncontrolle

d Parameter From To % Change

Sulfur 1 337 ppm 250 ppm Olefins 6.9 vol% 5.5 vol% -20.3

250 160 5.5 5.3 -3.6

160 50 5.0 4.1 -18.0

21/ 454 250 6.9 6.9 0.0

250 160 6.9 6.9 0.0

160 50 5.0 5.0 0.0

3 441 250 6.9 6.9 0.0

250 160 6.9 6.9 0.0

160 50 5.0 5.0 0.0

Sulfur 1 337 250 Aromatics 29.7 vol% 29.7 vol% 0.0

250 160 29.7 29.0 -2.4

160 50 27.2 26.3 -3.3

21/ 454 250 31.2 28.3 -9.3

250 160 29.7 26.3 -11.4

160 50 26.5 24.4 -7.9

3 441 250 31.1 30.5 -1.9

250 160 30.5 30.3 -0.7

160 50 28.9 27.4 -5.2

Sulfur 1 337 250 E200 51.5 %evap 51.1

%evap

-0.7

250 160 51.4 50.3 -2.1

160 50 51.1 52.1 2.0

21/ 454 250 53.7 55.9 4.1

250 160 53.3 53.0 -0.7

160 50 52.3 51.8 -1.0

3 441 250 56.5 57.4 1.6

250 160 54.5 54.9 0.8

160 50 53.5 56.8 6.2

Sulfur 1 337 250 E300 85.8 %evap 85.8

%evap

-0.1

250 160 85.5 85.9 0.5

160 50 85.9 86.6 0.8

21/ 454 250 85.1 86.8 2.0

250 160 86.4 87.2 0.9

160 50 86.5 87.3 1.0

3 441 250 85.6 86.6 1.1

250 160 87.7 86.6 -1.3

160 50 86.7 88.2 1.7
345

1/Data from Region 2 was questionable (as discussed in the text) and was excluded

from the analysis.

The data in Table VI-10 shows that only in Region 1 does

reducing the sulfur content of the fuel have an impact on

olefins; in the other two Regions no impact is indicated. This

could be a result of the fact that refiners in Region 1 had

little flexibility when reducing sulfur content, since 96% of

the gasoline produced in that region was reformulated (under

the scenario analyzed here), and thus, refiners were forced to

control sulfur in a manner which also affected olefins. For

this region, it is likely that the sulfur was removed from the

output of the FCC, causing the removal of olefins at the same

time. The Region 2 interrelationship numbers may be

questionable, because (as discussed previously) the data also

indicated that there was less cost than expected associated

with controlling sulfur levels in finished RFG. It appears

that the B & M model overestimated the existence of

hydrotreating capacity in this region, or overoptimized the

gasoline production options in this region since less than onehalf of the fuel is reformulated. In contrast, although there

also appears to be no impact on olefins of reducing sulfur for

the Region 3 data, there was a reasonable cost associated with

sulfur control in this region. The lack of an

interrelationship between sulfur and olefins may be explained

by the fact that the Region 3 refineries may elect to

desulfurize the feed to the FCC unit without affecting the

olefin level. 

Other studies, most notably the work performed for Auto-Oil

and referenced in the draft RIA, also indicated an

interrelationship between sulfur control and olefin content. 

The magnitude of this interrelationship, as developed in the

draft RIA, was somewhat greater than that developed from the B

& M data. However, that data was only for one PADD (PADD 3)

and therefore is less applicable to the national average than

the value developed here. The fact that the A/O study showed a

sulfur-olefin interrelationship for PADD 3 refineries while the

B & M model did not show an interrelationship in Region 3

demonstrates the variation between the assumptions contained in

different models. Either relationship is possible, depending

on how the refineries decide to reduce sulfur levels. It would

not be appropriate to "mix and match" data from two different

models to develop a national average because of such

differences. Hence, since the cost data from the B & M model

appeared to be reasonable, the results from B & M for Region 3

were used.

A national average factor was derived based on the impacts

shown in Regions 1 and 3. Because of the uncertainties in the

costs for Region 2, the parameter data were not included when

deriving a national average impact of reducing sulfur on
346

olefins. Factors representing the overall impact of reducing

the level of sulfur on the olefin content were developed from

the data in Table VI-10 for each of the three ranges of sulfur

reduction analyzed (down to 250 ppm, 250 ppm to 160 ppm, and

160 ppm to 50 ppm), using the method outlined previously. The

factors are listed in Table VI-7.

Table VI-10 also shows that reducing the sulfur content of

gasoline typically leads to a reduction in aromatics. This

impact is strongest in Region 2; for the reasons outlined

above, however, the data regarding the impacts of sulfur

control from Region 2 was excluded from the analysis. In

Region 1, where olefins are reduced as a result of sulfur

removal, one might expect the level of aromatics to increase to

provide additional octane; the opposite effect was observed. 

In Region 3, where sulfur removal does not appear to impact

olefins, one may expect there to be no change in aromatics,

since the volume of sulfur removed is too small to have much

impact on the concentration of aromatics (or any other

parameters) remaining. However, the impact indicated by the

data is small and is not unreasonable. The data presented in

the draft RIA indicated no impact of reducing sulfur content on

aromatics. However, since the old data was based only on

estimates for PADD 3, and since the change in aromatics

resulting from a change in sulfur is seen in both regions in

the B & M data, it was determined that this interrelationship

should be included in the cost-effectiveness analysis. 

The overall impact of reducing the sulfur level on

aromatics over each of the three ranges analyzed was estimated

by weighting the percent change in aromatics and the real

change in sulfur in the manner described in subsection D.1. 

The results of this calculation are presented in Table VI-7.

The impact on E200 and E300 of a reduction in sulfur, as

shown in Table VI-10, tends to be small and is somewhat

inconsistent between different regions. Since there is no

easily identified change in refinery operations that would

likely result in a change in these parameters as a result of a

reduction in gasoline sulfur content, it was determined that no

interrelationship exists between sulfur and either of these

parameters. This is supported by the Auto-Oil RFG study in

which reductions in sulfur had no consistent effect on E200 or

E300. 

c. Impact of Reducing Olefin Content on Other Fuel Parameters

Olefin removal can be achieved through hydrogenation,

alkylation or oxygenate production. Hydrogenation will also

reduce the level of sulfur, and valuable octane will also be

lost due to the reduction in olefins. In the case of
347

alkylation and oxygenate production, the loss of octane-rich

olefins would be offset by the addition of oxygenates or

alkylates, reducing the need to increase the severity of the

reformer to produce more aromatics. 

An analysis of the olefin interrelationships determined

from the B & M refinery modelling listed in Table VI-11

indicates a definite impact on E200, a minimal impact on

sulfur, aromatics, and E300, and no impact on other fuel

parameters.

Table VI-11: 

Data Used to Develop Olefins Interrelationship Factors

Controlled

Parameter Region From To

Uncontrolled

Parameter From To % Change

Olefins 1 7.2 vol% 6.9 vol% Sulfur 334 ppm 337 ppm +2.0

5.3 5.0 160 160 0.0

2

8.9 6.9 454 454 0.0

6.9 5.0 160 160 0.0

3 8.9 6.9 441 441 0.0

6.9 5.0 160 160 0.0

Olefins 1 7.2 6.9 Aromatics 29.7 vol% 29.7 vol% 0.0

5.3 5.0 28.1 27.2 -3.2

2 8.9 6.9 29.7 31.2 5.1

6.9 5.0 25.0 26.5 6.0

3 8.9 6.9 31.0 31.1 0.3

6.9 5.0 28.9 28.9 0.0

Olefins 1 7.2 6.9 E200 51.7 %evap 51.5 %evap -0.4

5.3 5.0 53.3 52.3 -1.9

2 8.9 6.9 57.4 53.7 -6.5

6.9 5.0 53.3 52.3 -1.9

3 8.9 6.9 57.9 56.5 -2.4

6.9 5.0 55.3 53.5 -3.2

Olefins 1 7.2 6.9 E300 86.0 %evap 85.8 %evap -0.2

5.3 5.0 87.3 86.5 -0.9

2 8.9 6.9 85.8 85.1 -0.8

6.9 5.0 87.3 86.5 -0.9

3 8.9 6.9 85.2 85.6 0.4

6.9 5.0 86.6 87.3 0.8
348

The data in Table VI-11 indicates no clear relationship

between a reduction in olefins and the sulfur level of the

fuel. The only change in sulfur level was shown for Region 1

in reducing olefins down to 6.9%, and in this case sulfur

actually increased slightly. Since this is not the expected

outcome of reducing olefins, and since the change in sulfur

level was very small, a relationship was not defined. The data

used in the draft RIA indicated some impact on sulfur due to

olefins control, but the data was only for PADD 5 and the

magnitude of that impact was difficult to measure. No

interrelationship between these parameters was assumed in this

cost-effectiveness analysis.

The data in Table VI-11 also indicate that reducing the

olefins in the fuel has some impact on the aromatics content,

although the impact varies with the region and the level of

olefin reduction considered. For example, in Region 1, where

there was a decrease in sulfur when olefins were decreased

(down to 6.9%), one would deduce that the olefins were removed

via hydrogenation and that aromatics content would, if

anything, increase to make up for the lost octane. However

some isomerization of straight chain hydrocarbon gasoline

components to higher octane components that occurred may have

eliminated the potential aromatics effect. In Regions 2 and 3,

where sulfur was not impacted by the reduction in olefins, one

would surmise that the olefins were reduced using alkylation

and that perhaps the aromatics content would be reduced, too. 

But the data shows that the aromatics content of the fuels

produced in Regions 2 and 3 actually increase when the olefins

content is reduced. Since each PADD was assigned a different

methodology for the reduction of olefins, it was not possible

to determine an interrelationship between olefins and aromatics

for this study. Past studies indicated some change in

aromatics as a result of olefins control, but, again, this data

was based solely on PADD 5 refinery modelling.

The data in Table VI-11 do show a relationship between

olefins and both E200 and E300, although the magnitude of these

relationships differs significantly. Since the impact on E300

is small and since the impact varied directionally in

different regions, this relationship was determined to be

insignificant. However, the relationship between olefins and

E200 appeared to be more significant and was consistent across

the different regions. In addition, it is reasonable to

surmise that E200 would decrease as the C4 and C5 olefins were

alkylated to heavier components. Hence, this interrelationship

was included in the cost-effectiveness analysis. The factor

representing the overall impact of reducing olefins on E200,

derived by weighting the results from each of the three

regions, is listed in Table VI-7.
349

d. Impact of Reducing RVP on Other Fuel Parameters 

The Reid vapor pressure (RVP) of gasoline is reduced by

adjusting the level of butane and other hydrocarbons (primarily

pentane) in the fuel. Most reductions in RVP will be achieved

by removing butane, however, deep cuts in RVP may require

removal of pentanes as well. Both of these hydrocarbons are

high in octane and their removal would require that the lost

octane be replaced in the finished gasoline. Octane may be

added by increasing aromatics or oxygen, or by producing

additional alkylates (and using the displaced C4 and C5

hydrocarbons in the process).

As shown in Table VI-12, a reduction in RVP appears to have

some impact on aromatics, E200, and E300, but the size of the

impact and the agreement between different regions varies. 

From the standpoint of refinery operations, there is no clear

connection between a reduction in RVP and the aromatics content

of the finished gasoline. The impact shown here is small, and

can be considered insignificant given the small level of RVP

reduction considered. Other studies show no impact on

aromatics from RVP control. Similarly, the impact on E300 of

reducing RVP is small, and the results are inconsistent between

the three regions, so no interrelationship was assumed. 

However, the trend of E200 increasing with a reduction in RVP

is sizeable, and can be explained by the fact that removing C4

(and perhaps C5) paraffins would decrease E200. Hence, an

interrelationship between RVP reduction and E200 was assumed in

the cost-effectiveness analysis.
350

Table VI-12: Data Used to Develop RVP Interrelationship Factors

Controlled

Parameter Region From To

Uncontrolled

Parameter From To % Change

RVP 1 7.6 psi 7.3 psi Aromatics 29.7 vol% 29.8 vol% 0.3

7.3 6.9 29.8 29.7 -0.3

6.9 6.5 29.7 29.7 0.0

2 7.6 7.3 28.4 28.5 0.4

7.3 6.9 28.5 28.5 0.0

6.9 6.5 28.5 27.9 -2.1

3 7.6 7.3 30.5 30.6 0.3

7.3 6.9 30.6 30.7 0.3

6.9 6.5 30.7 30.5 -0.8

RVP 1 7.6 7.3 E200 51.1 %evap 50.7 %evap -0.8

7.3 6.9 50.7 50.5 -0.3

6.9 6.5 50.5 49.5 -2.1

2 7.6 7.3 55.9 55.2 -1.2

7.3 6.9 55.2 55.0 -0.4

6.9 6.5 55.0 53.3 -3.1

3 7.6 7.3 57.4 56.3 -1.9

7.3 6.9 56.3 55.6 -1.3

6.9 6.5 55.6 54.5 -2.0

RVP 1 7.6 7.3 E300 85.8 %evap 85.7 %evap -0.1

7.3 6.9 85.7 85.6 0.0

6.9 6.5 85.6 85.5 -0.2

2 7.6 7.3 86.8 86.7 -0.1

7.3 6.9 86.7 86.7 0.0

6.9 6.5 86.7 86.4 -0.3

3 7.6 7.3 86.6 86.3 -0.3

7.3 6.9 86.3 86.5 0.3

6.9 6.5 86.5 87.7 1.4

e. Impact of Increasing Oxygen on Other Fuel Parameters 

Adding oxygen to gasoline increases the octane of the fuel;

other octane-rich components can then be reduced to produce

fuel with the desired level of octane. (Some of this reduction

occurs simply via dilution of the other components.) Since

many high-octane components of gasoline require severe

processing conditions to produce, a reduction in the amount of
351

these compounds required is beneficial to the refinery. It is

most likely that the addition of oxygen to the fuel would be

offset by reducing the aromatics content through a less severe

reforming configuration. It is also possible that other fuel

parameters could be affected if the refiner elects to reduce

the volume of crude throughput to produce a constant volume of

products. This would likely lead to a reduction in sulfur and

olefins in the finished gasoline due to changes in the

operation of the refinery (primarily the catalytic cracking and

reforming operations) in response to the lower volume of crude

processed.

The Bonner and Moore refinery modelling data used to

estimate the impact of adding oxygen on other fuel parameters

is presented in Table VI-13, and indicates that in all three

regions both aromatics and E200 are affected by the addition of

oxygen. The aromatics content of the fuel is reduced, which is

the expected response to the increase in octane provided by the

oxygenate. However, this reduction is less than expected and,

as stated earlier, is probably caused by the large decrease in

olefins observed. The change in fuel composition is expected

to result in a minor change in E200, as the data indicates. 

However, the impact on E300 is small and is inconsistent

between regions.

Table VI-13: 

Data Used to Develop Oxygen Interrelationship Factors/1

Controlled

Parameter Region From To

Uncontrolled

Parameter From To % Change

Oxygen 1 2.0 wt% 2.7 wt% Aromatics 29.0 vol% 28.1 vol% 3.1

2 2.0 2.7 26.3 25.0 4.9

3 2.0 2.7 30.3 28.9 4.6

Oxygen 1 2.0 2.7 E200 50.3 %evap 50.6 %evap 0.5

2 2.0 2.7 53.0 53.3 0.7

3 2.0 2.7 54.9 55.3 0.6

Oxygen 1 2.0 2.7 E300 85.9 %evap 85.8 %evap -0.2

2 2.0 2.7 87.2 86.5 -0.9

3 2.0 2.7 86.6 87.3 0.8

/

 Based on data from Bonner & Moore for EPA.

A review of the Auto-Oil data (presented in Table VI-14

below), which was developed by a different model, indicates

that an increase in oxygen results in a large decrease in

aromatics. This response of the refinery is more expected than

the one predicted by the B & M model. However, the Auto-Oil
352

data was developed only for a single PADD, and thus is not

directly applicable to a national average estimate. 

Since it is reasonable to expect that many refiners will

want to have a significant reduction in aromatics upon addition

of oxygen, the results from the two data sets were averaged,

and the average factors used in this analysis. Since both

studies also indicated some interrelationship between oxygen

and E200, the average of this impact from the two data sets

also was used in the cost-effectiveness analysis presented

here. However, although the Auto-Oil data shown in Table VI-14

indicates a relationship between oxygen and E300, such a

relationship was not included in this analysis because the

Auto-Oil data was only based on PADD 5 and the Bonner and Moore

data for the rest of the country did not strongly corroborate

such a relationship. 

Table VI-14: Auto-Oil Data Used to Develop Oxygen

Interrelationship Factors - Based on PADD V Data/1

Controlled

Parameter

From To Uncontrolled

Parameter

From To

Oxygen 0.4 wt% 2.7 wt% Aromatics 34.4 vol% 23.6 vol%

E200 43.5 %evap 52.4 %evap

E300 79.4 %evap 83.1 %evap /1Taken from the scenario xMxx vs. base. The E200 and E300 values have been calculated

from the Auto-Oil values for T50 and T90 using the conversion equations developed by EPA

(see section III).

f. Impact of Lowering Aromatics on Other Fuel Parameters

Reducing aromatics significantly below the level achieved

through addition of oxygenates will require refining changes to

make up for the octane loss. The octane could be increased

through increased alkylation of C4 and C5 olefins. The reduction

in aromatics combined with a conversion of olefins could have an

impact on E200 and E300 depending on the changes in distillation

resulting from the new composition; these changes would be

refinery specific.

The following table presents the data obtained from the B &

M refinery modelling to explain the relationship between

aromatics and other fuel parameters. Although a change in

olefins would be expected, the results from the three regions

modelled are very inconsistent, and a trend cannot be determined. 

The impact of aromatics reduction on E200 similarly is

inconsistent and makes it impossible to determine an

interrelationship between the parameters based on this data. 

However, the results for E300, albeit small, are consistent and

make sense directionally, as it is reasonable to assume that E300
353

may increase if the heavier aromatics are removed or reduced. 

Hence, an interrelationship between aromatics and E300 was

included in the cost-effectiveness analysis.

Table VI-15: 

Data Used to Develop Aromatics Interrelationship Factors

Controlled

Parameter Region From To

Uncontrolled

Parameter From To % Change

Aromatics 1 30 vol% 28 vol% Olefins 5.70 vol% 6.64 vol% 16.5

28 24 6.64 6.56 -1.2

24 20 6.56 6.57 0.2

2 28.3 28 6.9 6.9 0.0

28 24 6.9 6.9 0.0

24 20 6.9 6.9 0.0

3 30 28 6.9 6.9 0.0

28 24 6.9 6.9 0.0

24 20 6.9 6.9 0.0

Aromatics 1 30 28 E200 51.3 %evap 53.2 %evap 3.7

28 24 53.2 55.3 3.9

24 20 55.3 57.7 4.3

2 28.3 28 55.8 55.4 -0.7

28 24 55.4 54.7 -1.3

24 20 54.7 57.2 4.6

3 30 28 62.8 58.7 -6.5

28 24 58.7 59.1 0.7

24 20 59.1 61.2 3.6

Aromatics 1 30 28 E300 85.9 %evap 86.7 %evap 0.9

28 24 86.7 88.2 1.7

24 20 88.2 89.1 1.0

2 28.3 28 86.8 86.8 0.0

28 24 86.8 88.3 1.7

24 20 88.3 89.4 1.2

3 30 28 86.3 87.6 1.5

28 24 87.6 88.5 1.0

24 20 88.5 90.2 1.9

 

g. Impact of Increasing E200 or E300 on Other Fuel Parameters 
 102Lester Wyborny, November 4, 1993.

354

Increasing the percent of fuel evaporated at either 200 or

300 degrees Fahrenheit requires a change in the fractionation

scheme at the refinery. E300 control will require elimination

of many of the heaviest components of gasoline, while E200

control could result in removal or conversion of mid-range

components such as olefins. These changes could have an impact

on the overall octane value of the fuel, and could thus have

implications for other fuel parameters.

The data used to develop the interrelationship between E200

and other fuel parameters is listed in Table VI-16; this data

was generated in-house using the B & M refinery model.102 The

results from modelling Region 3 were somewhat questionable

since E200 started at a higher level than expected. However,

because no other data was available to evaluate E200, the data

from all three Regions was used to develop the

interrelationships between E200 and other parameters.
355

Table VI-16: Data Used to Develop E200 Interrelationship

Factors

Controlled

Parameter Region From To

Uncontrolled

Parameter From To % Change

E200 1 50

%evap

54

%evap

Olefins 5.14 vol% 5.45 vol% 6.0

54 57 5.45 5.14 -5.7

57 60 5.14 7.07 37.5

2 53 54 6.41 7.23 12.8

54 57 7.23 8.26 14.2

57 60 8.26 8.46 2.4

3 55 58 8.44 8.90 5.5

58 61 8.90 8.90 0.0

61 64 8.90 8.90 0.0

E200 1 50 54 Aromatics 29.2 %vol 26.8 %vol -8.0

54 57 26.9 23.3 -13.2

57 60 23.3 21.7 -6.8

2 53 54 24.9 25.3 1.7

54 57 25.3 23.6 -6.7

57 60 23.6 22.2 -6.0

3 55 58 31.0 33.6 8.1

58 61 33.6 32.7 -2.7

61 64 32.7 29.7 -9.2

E200 1 50 54 E300 88.1 %evap 89.1

%evap

1.2

54 57 89.1 90.1 1.1

57 60 90.1 91.8 1.8

2 53 54 89.3 89.4 0.2

54 57 89.4 90.2 0.8

57 60 90.2 90.8 0.7

3 55 58 87.7 88.1 0.5

58 61 88.1 89.1 1.0

61 64 89.0 89.8 0.9

The data in Table VI-16 shows some interrelationships

between E200 and the parameters aromatics and E300. The data

for the relationship between E200 and olefins is inconsistent

across the three regions examined, and thus no

interrelationship between these parameters was determined. In

contrast, the data shows a more significant relationship
356

between E200 and aromatics, although this is a somewhat

unexpected reaction of the refineries to increasing E200. 

Similarly, the data shows a definite and not altogether

unexpected relationship between E200 and E300.

The B & M refinery model did not yield satisfactory results

for the control of E300. Hence, it was necessary to use the

data generated by Turner and Mason for Auto-Oil that was used

in the development of parameter relations for the draft RIA. 

The Turner and Mason data looked at controlling T-90, the

temperature at which 90% of the fuel has evaporated. Since the

Complex Model now includes E300, the T-90 data was transposed

to represent E300 based on the relationship between these two

parameters cited previously. This data is presented in Table

VI-17. One weakness in this data is that it only represents

one region of refineries (PADD 3) rather than modelling several

regions covering the entire country. However, it does

represent 55 percent of the RFG likely to be produced and

provides one measure of how a refinery may react to a need to

increase E300.

Table VI-17: Data Used to Develop E300 Interrelationship

Factors

Controlled

Parameter Region1 From To

Uncontrolled

Parameter From To % Change

E300 PADD 3 84 %evap 88 %evap Olefins 12.2 %vol 12.6 %vol 3.3

88 91 12.6 12.4 -1.6

91 96 12.4 11.5 -7.3

E300 PADD 3 84 88 Aromatics 20 %vol 20 %vol 0.0

88 91 20 19.5 -2.5

91 96 19.5 17.3 -11.3

E300 PADD 3 84 88 E200 52.9 %evap 55.6 %evap 5.1

88 91 55.6 56.7 1.8

91 96 56.6 58.6 3.5

1

This data is based on the Turner and Mason work for Auto-Oil. For that study, refineries were

modelled in PADD-specific groups. PADD 3 would correspond to the Bonner and Moore Region 3.

The data presented above indicates no clear relationship

between E300 and either olefins or aromatics, and a measurable

relationship between E300 and E200. The data is questionable

for the impact on olefins, because for the first increase in

E300 olefins increased, while for the second two increases,

olefins decreased. The aromatics data is questionable because

in the Turner and Mason work aromatics was limited to a level

of 20 vol%, and appears to have reached this ceiling. Hence,
357

the data may not accurately reflect any interactions between

E300 and aromatics. The E200 data shows the expected

correlation with E300, and therefore this interrelationship was

included in the cost-effectiveness analysis.

E. Determination of Emissions Reductions

The cost-effectiveness of a particular fuel component

change is determined based on reductions in in-use emissions

(i.e., the impact the fuel will have on emissions from vehicles

in-use at the time the fuel is sold). In contrast, the actual

Phase II reformulated gasoline emission performance standards

and NOx standards for RFG are based on the reformulated fuel's

effect on 1990 model year vehicle emissions relative to those

with Clean Air Act baseline fuel. The following discussion

explains how baseline emissions and emission reductions from

baseline were determined.

1. Non-Fuel Factors Affecting Baseline Emissions Determination

The determination of both statutory baseline emissions and

in-use baseline emissions is affected by many factors, such as

specific characteristics of the fleet (age of vehicles, types

of vehicles, etc.) or the other regulatory programs in place at

the time (e.g., enhanced inspection and maintenance, fuel

volatility control). The primary factors affecting the base

emissions used in this analysis are briefly discussed below.

a. Enhanced Inspection and Maintenance 

Enhanced inspection and maintenance (I/M) programs are

expected to be fully implemented and phased in by the year

2000. The program is mandated for all serious and worse ozone

nonattainment areas. Under enhanced I/M, emissions are lower

relative to a basic I/M program because vehicles are kept in

better condition. Vehicles with poorly maintained exhaust and

evaporative emission control systems are identified and must be

repaired. The impact of enhanced I/M programs on the emission

reductions achieved is that the same percentage reduction in

emissions applied to a lower baseline emissions value yields

lower absolute reductions. Enhanced I/M is assumed in this

analysis. 

b. MOBILE Model

The MOBILE5a emissions model (with enhanced I/M) is

utilized in this analysis to determine the in-use baseline

emissions. Different base emissions would result if earlier

versions of the MOBILE model were used. Baseline emissions

determination is also affected by the average vehicle speed

used in the MOBILE model. In this analysis, EPA utilized its
358

standard Federal Test Procedure (FTP) speed of 19.6 miles per

hour. EPA is currently investigating other speeds or

distributions of speeds to more accurately estimate baseline

emissions. Revised speed estimates would likely be higher,

decreasing VOC and increasing NOx emissions estimates. 

However, since the investigation is not yet complete, the FTP

value was assumed here.

One comment received on the proposal raised concern with

using the MOBILE5 model instead of the MOBILE4.1 model. The

exhaust emissions calculated by MOBILE5 are significantly

higher than those calculated by MOBILE4.1. The commenter

suggested that the cost-effectiveness analysis presented by EPA

was optimistic because it was based on a percent reduction in

emissions applied to this larger emission inventory, in effect

improving the cost-effectiveness of each incremental change in

fuel composition because the number of tons over which the

costs were spread was large. MOBILE5 (and the subsequent

MOBIlE5a model) went through a thorough review process,

including a number of public workshops. In particular, EPA

believes that the increase in in-use VOC exhaust emissions

relative to MOBILE4.1 are real. Non-exhaust VOC emissions did

not increase much in MOBILE5 relative to MOBILE4.1, because

time and resources did not allow a number of possible

modifications in the nonexhaust emission methodology to be

implemented. Future modifications to the MOBILE model could

produce even higher nonexhaust VOC emissions. In any event,

the VOC emissions reductions on which the analysis is based are

reasonable. The MOBILE5 model contains the latest information

on vehicle emissions and fuel economy. It is the most

realistic model available to estimate the fleet emissions in

the future that is available.

c. Other Factors Influencing Emissions

Other factors can also influence base emissions and thus

the reductions determined from those base emissions. For

instance, Stage II evaporative controls (controls at the fuel

pump to reduce evaporative emissions when refueling vehicles)

are included in the MOBILE5a analysis. Onboard (on the

vehicle) refueling emissions controls are not considered,

however, since the rules governing them have not been

promulgated and such controls were not installed on 1990 model

year vehicles. The incremental control of onboard vapor

recovery to Stage II is small compared to the total vehicle VOC

emissions where both are in place. Given the current court

order under which EPA is working (see 58 FR 30731), it is

likely that vehicles sold in the year 2000 and/or later will

have onboard refueling control systems. For the purposes of

this analysis, however, this would not greatly affect the
 103In the draft RIA, southern areas were called "Class B"

and northern areas were called "Class C."

359

baseline in-use emissions because fewer than 50% of the

vehicles would likely have such controls at that time.

2. Baseline Fuel Assumptions

Changes in fuel composition and emissions relative to the

Clean Air Act baseline fuel are used to determine the VOC, NOx,

and toxics emissions performance standards. The base fuel

composition from which the cumulative emissions reductions were

estimated (and thus from which the proposed performance

standards were determined) was the statutory summertime

baseline gasoline presented in section 211(k)(10) of the Act. 

The baseline emissions are estimated using the Phase II complex

model as discussed in section III. 

In the draft RIA, northern area (VOC control region 2)

emission reductions were determined relative to the statutory

baseline.103 Southern area (VOC control region 1) emission

reductions were shown relative to both the statutory baseline

and to a baseline with all of the statutory values except for

RVP, which was set at 7.8 psi (the 1992 Phase II gasoline

volatility requirement for southern ozone nonattainment areas). 

The proposed standards for southern areas were determined

relative to the latter baseline. Several comments were

received expressing a concern about setting standards for the

two regions relative to different baselines. In this revised

analysis, the standards for both VOC control regions are

determined relative to the statutory baseline RVP of 8.7 psi. 

Based on comments received and on its own analysis, EPA

realized that the actual 1990 summertime olefin value was

approximately 13 volume percent (vol%) while the value

specified in the Act was 9.2 vol%. This difference between the

actual 1990 value and the statutory value significantly impacts

estimations of emissions, total reductions in emissions, costs,

and cost-effectiveness. Additionally, the actual impact on

refiners of utilizing an unrepresentative baseline in setting a

performance standard could result in anti-competitive impacts. 

Therefore, in determining cost-effectiveness, EPA used a

nationwide summertime baseline olefins value of 13.1 volume

percent. This value was determined from the Bonner & Moore

modelling work, and includes 1990 olefin levels in California. 

The value is in agreement with EPA's own estimate based on

gasoline surveys in select cities across the country. The

baseline emissions when the olefin content is 13.1 volume

percent (vol%) and when the olefin content is 9.2 vol% are

shown in Table VI-18 below for comparison. Once the percent
 104The Phase I complex model indicates that refiners will be

able to meet the Phase I requirements (15% reduction in VOC, no

NOx increase) even with an olefins level of 13.1%.

360

reduction standards are determined based on the costeffectiveness of the fuel changes relative to the in-use

emissions assuming the 13.1 vol% olefin level, refiners must

still certify their fuel relative to the statutory baseline

fuel containing 9.2 vol% olefins.104

Table VI-18: 

Phase II RFG Emissions at Different Olefin Levels (mg/mi)/1

VOC Control

Region

Region 1 (Southern) Region 2 (Northern)

Olefin Level 9.2 13.1 9.2 13.1

VOC 1466 1456 1399 1389

NOx 1340 1369 1340 1369

Benzene 52 52 52 52

Acetaldehyde 4 4 4 4

Formaldehyde 8 7 8 7

1,3-Butadiene 7 8 7 8

POM 3 3 3 3

/1Determined using Phase II complex model with all other fuel parameters at

Clean Air Act summer baseline values.

To determine the cost-effectiveness of Phase II RFG

incremental to Phase I, the costs and emissions reductions

associated with the Phase I fuel had to be evaluated. Hence,

while the Phase II standards are expressed relative to the Clean

Air Act baseline, the cost-effectiveness of fuel reformulations

in excess of the Phase I requirements were determined relative to

a fuel meeting the Phase I definition (2 wt% oxygen, 1 vol%

benzene, and 8.0 psi RVP).

Because the Phase II VOC and the NOx emission reduction

requirements are only required during the high ozone season,

there are no Phase II or NOx control requirements outside of the

high ozone season. Phase II toxics control applies year-round. 

However, toxics control has been shown to be cost-ineffective

(see subsection F.3 below as well as the draft RIA), and thus was
361

evaluated using the same costs and emissions baselines that were

developed for VOC and NOx control. Hence, there is no need for a

"wintertime" baseline fuel for Phase II RFG (although the

wintertime baseline fuel still applies for the antidumping

provisions; see section III). 

3. In-Use Basis

The performance standards developed in this document are set

as percentage reductions in emissions from the statutory baseline

fuel, as described above. However, in-use emissions better

estimate the emissions of vehicles that will be on the road

during and after the year 2000. Use of the statutory baseline to

estimate cost-effectiveness would only represent the emissions

reductions that would be achieved from 1990 technology vehicles. 

Thus it is more appropriate to base the cost-effectiveness, i.e.,

the cost per actual benefit, on the emissions reduction from the

in-use emissions baseline. 

Baseline exhaust and nonexhaust emissions of vehicles in-use

in the year 2003 (a representative year after 1999) were obtained

from MOBILE5a, assuming enhanced inspection and maintenance

programs in all severe or worse ozone nonattainment areas. This

emissions estimate includes light-duty gasoline vehicles and

trucks. To determine the in-use emissions resulting from each

fuel parameter change, the in-use baseline emissions were

adjusted by the percent change in the Phase II complex model

emissions projections calculated from that fuel parameter change.

4. Emission Reductions

Incremental reductions in emissions are determined relative

to emissions from a previous fuel formulation, while total

reductions are determined relative to the emissions resulting

from Phase I RFG and also to the emissions from the statutory

baseline fuel. This allows calculation of the cost-effectiveness

based on the incremental reduction in in-use emissions. It also

permits determination of an emission reduction standard based on

the total reduction from the statutory baseline emissions. 

To determine each incremental reduction in emissions, the

emissions reduction (calculated in grams/mile) must be expressed

in terms of the net tons emitted. (The grams/mile numbers can be

used directly to calculate reductions in the number of cancer

incidences as a result of toxics control, as discussed in section

F below). Estimates of the level of fuel consumption and the

average fuel economy of the fleet are required to complete this

calculation.

Summer fuel consumption estimates in the year 2000 for ozone

nonattainment areas in VOC control regions 1 and 2 were estimated

based on the 1990 fuel consumption and population data from the
 105reference (chris b.)?

 106Energy Information Administration, Annual Energy Outlook: 

1993, DOE/EIA-0383(93).

362

1990 census for the mandated RFG areas, the currently opted-in

areas, and for the remainder of the Ozone Transport Region. The

National Petroleum News (June 1992) showed 1990 fuel consumption

to be approximately 115 billion gallons.105 A DOE fuel

consumption projection for the year 2000 is also about 115

billion gallons.106 Since there was little difference between the

actual 1990 and projected 2000 fuel consumptions, EPA used 115

billion gallons per year as its base number. The ratio of the

population of an RFG area to its state population was then

multiplied by the state summer fuel consumption (from MaySeptember 15--again, estimated from 1990 actual fuel consumption

data). Summing these estimates for individual states yielded the

total summer fuel consumption for all the RFG areas.

A fleet fuel economy of 20.58 miles per gallon was estimated

from the MOBILE4.1 fuel consumption model for the year 2000 and

was used in this conversion calculation. This fuel economy

includes both light-duty vehicles and light-duty trucks. The

MOBILE4.1 model was used because a fuel consumption model based

on MOBILE5a has not been developed. 

Finally, in order to provide an equitable comparison of the

proposed reformulated gasoline VOC and NOx controls with other

VOC and NOx control programs, the incremental VOC and NOx

emission reductions, in tons, were annualized, i.e., converted

from summer tons to annual tons. One commenter recommended that

cost-effectiveness be determined on the basis of actual summer

tons. While it is true that the RFG program is a summer program,

and although ozone formation primarily occurs during summer

months, historically EPA has measured the cost-effectiveness of

VOC control programs in terms of annual tons reduced. This

precedent has been set by stationary source controls, which

operate year-round but only achieve ozone benefits in the summer

months, as well as mobile source controls, such as the recent

gasoline volatility regulations. In annualizing the emission

reduction benefits, EPA assumed a summer season of 5.5 months (to

account for the lead time needed to produce and deliver RFG).

This summer season is longer than the one used in the draft RIA

(4.5 months). It was adjusted in response to a comment received

which stated that the total time over which refiners must produce

reformulated gasoline was understated in the draft RIA (as

discussed previously).

A similar analysis methodology was followed for estimating

toxics emissions reductions. Baseline values of each toxic were
363

obtained from the Phase II complex model. New emissions were

determined from the complex model for each fuel component change. 

The emission reductions were determined from the sum of the

toxics emissions and was determined relative to the previous fuel

composition. Thus, tons of toxics reduced are determined from

the sum of all of the toxics emissions. 

F. Cost-Effectiveness Determination

In this analysis, cost-effectiveness is defined as the cost

of an emission control strategy per ton of VOC or NOx emissions

reduced or per cancer incidence (CI) avoided (for air toxics). 

Cost-effectiveness can be used to compare different control

strategies or different options within one control strategy

(e.g., incremental changes in fuel composition). A low cost per

ton reduced (or per cancer incidence averted) is desirable.

In general, for this analysis EPA estimated the incremental

emissions reductions associated with a given fuel component

change, and determined the incremental cost-effectiveness for

that fuel change relative to the previous fuel composition. A

copy of the results of this analysis is attached as Tables VI-A5 

and VI-A6 in the Appendix. The tables report incremental costeffectiveness for reductions in VOC, NOx, VOC + NOx (and several

related VOC + NOx cost-effectiveness expressions) and toxics for

each of the two VOC control regions.

1. Comments on Analysis in Draft Regulatory Impact Analysis

In the draft RIA, EPA presented an analysis of the costeffectiveness of VOC, NOx, and toxics control based on the

refinery costs and emissions reductions estimated in that study. 

The costs were evaluated in terms of the reductions achieved, and

were also expressed on a per-gallon-gasoline-produced basis to

more directly reflect the costs to consumers. EPA received

comments on many parts of the analysis. One commenter suggested

that EPA analyze the cost which would be incurred by each

household to bring an area into compliance with the NAAQS, and

use this as the basis for the cost-effectiveness analysis. While

such an analysis may be interesting from an economic standpoint,

it was not required for EPA to perform this type of analysis to

determine the cost-effectiveness of the reformulated gasoline

program. The methodology used in the draft RIA and here is

consistent with the methodology used to analyze and support all

other stationary and mobile source emission control programs.

Several commenters presented evaluations of the cost of

Phase II RFG over Phase I, based on the proposed standards. 

These evaluations suggested costs which ranged from 5.5-15¢/gal,

depending on the level of VOC control (25-35% reduction). It was

estimated by another commenter that the cost for small refiners
364

may be 5¢/gal greater than for large refiners. As will be

explained below, EPA has estimated that the cost of VOC control

will be significantly less than the range projected by the

commenters, depending on the level of control required and the

parameters controlled to achieve that standard. However, EPA

agrees that some refiners will realize costs higher than the

average estimates presented here. A more detailed discussion of

the impacts of this rulemaking on small entities is presented in

section VIII of this document.

Another comment emphasized the need to use a "valid" complex

model when determining the cost-effectiveness for use in setting

the Phase II standards. As discussed above, EPA used the final

complex model to determine the emissions reductions achievable

through incremental changes in fuel parameters. These emissions

reductions will be the basis of the cost-effectiveness analysis

presented below.

2. Factors Affecting Cost-Effectiveness Determination

a. Phase I Fuel Requirements

In this analysis, the combined effect of the Phase I RFG

requirements was evaluated prior to evaluating the effects of

additional fuel parameter changes because the costs of these

requirements will be incurred by refiners prior to the year 2000. 

After accounting for the production of Phase I RFG, the most

incrementally cost effective fuel changes were made. The

analysis proceeded through each potential fuel change until the

most costly (highest cost per reduction achieved) parameter

change was identified.

b. Complex Model Fuel Parameter Range Limits

The range over which fuel components were allowed to change

was governed by the data from which the fuel component control

costs were derived, with the additional check that the limits

defined by the complex model for each fuel component were not

exceeded. If cost data was available for several levels of

control of a single fuel component, each level of control was

incorporated as a discrete control level, as described

previously. The fuel components and the specific levels of

control to which each fuel component was held are discussed in

section IV.

c. VOC Control Region

Separate cost-effectiveness analyses must be done for each

VOC control region because of differences in the nonexhaust

emissions experienced in the two regions (resulting primarily

from the different average ambient temperatures) which affect the

total percent and gram per mile reductions for VOC, NOx, and
 107U.S. EPA, "Motor Vehicle-Related Air Toxics Study,"

Office of Mobile Sources, Report No. EPA 420-R-93-005, April

1993.

365

toxics. Total percent reductions are determined from the CAA

statutory summer baseline gasoline composition.

3. Analysis Methodology

For the purpose of this analysis, cost-effectiveness is

defined as the ratio of the incremental cost of a control measure

to the incremental benefit, e.g., the cost in dollars per ton of

VOC or NOx emissions reduced or the number of cancer incidences

avoided. The use of cost-effectiveness allows for the relative

ranking of various control strategies so that a specified

environmental goal can be achieved at minimum cost. 

In this analysis, cost-effectiveness was evaluated using

incremental fuel parameter controls and costs. In other words,

only a single fuel parameter was modified at a time, e.g., RVP

was reduced to 7.3 psi from 7.8 psi, or sulfur was reduced from

250 ppm to 160 ppm. The incremental fuel component control cost

(in cents per gallon) determined as described in section C above

was converted to total incremental cost (in millions of dollars)

using the same average fuel consumption data that was used to

calculate total emissions. The incremental cost-effectiveness

was determined by dividing the total incremental cost by the

actual incremental reduction in emissions (in tons or in cancer

incidences). Cumulative actual reductions, total cost, and total

cost-effectiveness are determined in an analogous manner. 

Cumulative numbers are identified as "total."

Determining the cost-effectiveness of toxics reduction

requires a slightly different approach. Reductions in cancer

incidence must be determined separately for each toxic, and then

the resulting cancer incidences added together to determine the

overall reduction in cancer incidence for each year that the

program is in place. Thus, for each toxic air pollutant,

emissions reductions (in mg/mile) were converted to cancer

incidence per year (CI/yr) using a "unit risk factor" for each

toxic and the population of the participating nonattainment area. 

Each unit risk factor (cancer incidences-per-year per gram-permile per person) was assumed to be constant. In the draft RIA,

unit risk factors were derived from an EPA paper of 1989. For

this analysis, updated unit risk factors were derived from data

presented in EPA's recent Air Toxics Study107. The factor for

converting gram per mile emissions to micrograms per cubic meter

used in the Air Toxics Study was adjusted to reflect the carbon

monoxide emissions predicted by MOBILE5a instead of using the

factor derived from MOBILE4.1 described on page 4-7 of that
366

report. The emissions were adjusted from 1988 to the year 2000

with the factor 1.218 to reflect anticipated changes in vehicle

miles travelled. The adjustments for ambient conditions and

potency of each toxic were used as described in the Air Toxics

Study. Table VI-19 presents the unit risk factors derived for

this analysis. 

Table VI-19: Unit Risk Factors for Air Toxics

Toxic Pollutant (CI/yr)/(g/mi)/

(person)

Benzene 3.696 x 10-6

Formaldehyde 4.910 x 10-6

Acetaldehyde 2.048 x 10-6

1,3-Butadiene 9.103 x 10-5

POM 5.344 x 10-5

The Phase II reformulated gasoline standards can be

determined from this cost-effectiveness analysis, by determining

the maximum level of control that can be achieved for a

reasonable incremental cost-effectiveness. Other factors, such

as the economic impact on the industry and the technological

feasibility of that level of control, can also be considered when

choosing the standard.

EPA received many comments on the methodology used in the

draft RIA (which is essentially the same methodology used in this

analysis), as well as suggestions for alternative methods of

determining cost-effectiveness. One recommended method involved

using a refinery model consisting solely of Petroleum Allocation

for Defense District (PADD) 1 refineries to develop a

relationship between cost and a single pollutant (e.g., VOC), and

using this relationship to select an average standard based on a

cost-effectiveness limit. According to this commenter, the costeffectiveness limit should be based on the "knee" in the cost

curve (the point at which costs escalate dramatically for an

incremental reduction in emissions), i.e., the maximum acceptable

cost-effectiveness should be determined individually rather than

being based on a preselected value. The standards for other

pollutants should then be set based on the fuel composition used

to reach the VOC standard. 

The methodology used by EPA does not differ significantly

from the recommended one. As explained above, the standards were

developed using the complex model to determine emissions

reductions. Rather than basing the costs on a single region, EPA
367

averaged the costs for several regions, excluding California,

based on the relative volumes of RFG produced in each region. In

addition to use of the cost-effectiveness limit, EPA also

attempted to insure that the standards provided adequate

flexibility for individual refiners, prevented typical refiners

from incurring unreasonable costs, and did not force the industry

to make a fuel with a specified formula.

4. Results of Cost-Effectiveness Analysis

Tables VI-20 and VI-21 present the results of the costeffectiveness analysis performed by EPA. The per-gallon costs

and (average) cost-effectiveness for VOC and NOx reductions are

listed, based on the cost estimates for VOC control region 2

(northern areas). The cost-effectiveness of VOC reductions for

VOC control region 1 will be slightly less than those shown in

Table VI-20. The incremental cost for each parameter change will

be slightly less in region 1 because less RFG will be consumed

there, and thus the overall cost will be less. In addition,

fewer tons of VOC will reduced in the region due to differences

in the emissions predicted by the complex model for the two

regions, but the reduced cost overrides the $/ton analysis. In

contrast, the cost-effectiveness of VOC control for control

region 1 compared to Phase I RFG will be greater than those for

control region 2. This is largely due to the fact that the

actual emissions reductions achieved in region 1 will be lower

than in region 2 since these areas start with a lower RVP fuel

(as a result of EPA's fuel RVP regulations). The incremental

cost-effectiveness of NOx control is very close between the two

regions, largely because the incremental reductions in emissions

(mg/mi) estimated by complex model are close. Similarly, the

cost-effectiveness for NOx control incremental to Phase-I RFG is

quite close between the regions. This is because the baselines

are closer than they were for VOC (since RVP has a negligible

impact on NOx).
368

Table VI-20: Fuel Parameter Control Costs and VOC Reductions/1

Fuel Parameter

Control

Incremental

Cost

(¢/gal)

Cumulative

reduction

(%)

Incremental

Cost-Eff. 

($/ton)

Incremental

to Phase I

($/ton)

Phase I

 RVP: 8.0 psi

 Oxygen: 2.1wt%

 Benzene: 0.95%

RVP to 7.1 psi 0.18 22.9 400 400

RVP to 6.7 psi 0.08 25.5 600 400

Sulfur to 250 ppm 0.12 26.1/2 3,700 600

Sulfur to 160 ppm 0.56 27.1 11,000 1,300

Sulfur to 138 ppm 0.24 27.4 19,000 1,600

Sulfur to 100 ppm 0.52 27.8 24,000 2,300

Olefins to 8.0 vol% 0.78 26.2 (-) 3,700

Aromatics to 20vol% 2.01 27.8 24,000 6,000

Oxygen to 2.7 vol% 0.61 28.2 28,000 6,600

Olefins to 5.0 vol% 2.77 27.4 (-) 11,000

E300 to 88% 0.35 27.4 48,000 11,000

E300 to 91% 2.01 27.5 198,000 14,000

E200 to 44% 0.38 27.7 37,000 14,000

E200 to 47% 1.32 28.4 36,000 15,000

E200 to 50% 2.97 29.0 96,000 18,000

/1 Based on costs and emissions reductions for VOC control region 2 (northern

areas). Assumes all costs allocated to VOC control.

/2 RVP control down to 6.5 psi, the limit considered reasonable at this point

in time for driveability purposes, would increase this value to 27.2%
369

Table VI-21: Fuel Parameter Control Costs and NOx Reductions/1

Fuel Parameter

Control

Incremental

Cost

(¢/gal)

Cumulative

Reduction 

(%)

Incremental

Cost-Eff. 

($/ton)

Incremental

to Phase I

($/ton)

Phase I

 RVP: 8.0 psi

 Oxygen: 2.1wt%

 Benzene: 0.95%

RVP to 6.7 psi - 0.4 - -

Sulfur to 250 ppm 0.12 2.4 1,300 3,200

Sulfur to 160 ppm 0.56 5.8 3,700 3,500

Sulfur to 138 ppm 0.24 6.8 5,200 3,700

Sulfur to 100 ppm 0.52 8.7 6,200 4,200

Olefins to 8.0 vol% 0.78 10.8 8,000 5,000

Aromatics to 20vol% 2.01 11.9 40,000 8,200

Oxygen to 2.7 vol% 0.61 12.5 25,000 8,900

Olefins to 5.0 vol% 2.77 14.1 37,000 12,000

E300 to 88% 0.35 14.1 (-) 13,000

E300 to 91% 2.01 14.2 820,000 16,000

E200 to 44% 0.38 13.9 (-) 17,000

E200 to 47% 1.32 13.7 (-) 19,000

E200 to 50% 2.97 13.5 (-) 24,000

/1 Based on costs and emissions reductions for VOC control region 2 (northern

areas). Assumes all costs allocated to NOx control.

As Table VI-20 shows, the largest reduction in VOC emissions

can be achieved through reductions in the RVP of the fuel. These

reductions can be achieved at a cost-effectiveness well below the

$5,000-$10,000/ton levels proposed in the February NPRM. Control

of sulfur and other parameters can result in incremental

reductions in VOC, but the costs increase dramatically, thereby

reducing the cost-effectiveness. Similarly, Table VI-21 shows

that the largest reduction in NOx emissions occurs as a result of

reducing the level of sulfur in the fuel. Attempts to reduce NOx

emissions by controlling other parameters are in most cases cost

ineffective and in some cases detrimental. 

Overall, controlling RVP to 6.7 psi and sulfur to 250 ppm

could yield an overall reduction from baseline VOC emissions of

about 26% at an incremental cost-effectiveness of about $3,700

per ton of VOC reduced. However, the total cost-effectiveness of
 108If the cost-effectiveness of this level of NOx reduction

is credited based on the additional level of VOC control

achieved, at a value of $500/ton VOC reduced, the costeffectiveness of this last increment of NOx reduction is about

$5,000/ton NOx.

370

this level of VOC reduction relative to Phase I RFG is only about

$600/ton. This latter value is important when comparing the

cost-effectiveness of potential VOC standards with alternative

methods of VOC control (see section H), since these other

programs are usually evaluated based on the cost-effectiveness

relative to the baseline rather than the cost-effectiveness of

the last increment of control.

Reducing the sulfur level of the fuel further, to 138 ppm,

would yield an overall reduction in NOx emissions of 6.8% (plus a

total VOC reduction of 27.4%) at an incremental costeffectiveness of about $5,200 per ton of NOx (assuming that all

of the costs are allocated to the NOx control).108 Again, if one

notices the cost-effectiveness incremental to Phase I RFG, this

level of NOx control is even more cost-effective at about

$3,700/ton. The overall cost-effectiveness of this level of VOC

and NOx control relative to Phase I RFG, if each unit of NOx is

valued equally to each unit of VOC, is $4,100/combined ton (see

Table VI-A6 in the Appendix). If NOx reductions are deemed to be

more valuable than reductions in VOC (as some researchers have

suggested), the cost-effectiveness of this strategy improves. 

NOx reductions exceeding 10% could be achieved with more

stringent sulfur control (down to 100 ppm) as well as control of

olefins, at incremental cost-effectiveness less than $10,000 per

ton of NOx. However, it should be noted that the olefins control

is more costly than readily apparent due to an increase in VOC

emissions (as predicted by the complex model). Under such a

scenario, total VOC reductions would be 27.8%. 

Table VI-22 presents the results of EPA's analysis of the

cost-effectiveness of toxics reductions. This information is for

reductions in total toxics (the five toxics of concern for

reformulated gasoline). The cost per cancer incidence is a

function of the reduction in each individual toxic, since each

toxic has a different risk factor for cancer, as discussed

previously. As the table shows, toxics control in Phase II RFG

is not cost-effective when expressed either on a $thousand/ton

basis or a $million/cancer incidence basis. Toxics control of

25% reduction would cost over $220,000 per ton of overall toxics

reduced for the last increment of reduction (from 24.6% to

25.0%), or close to $40 million per cancer incidence avoided. 

Less than one cancer incidence would be avoided nationwide per

year at a toxics reduction of about 25%. The cost-effectiveness
371

of toxics control in VOC control region 1 would be even higher

(see Table VI-A5 in the Appendix).

Table VI-22: Fuel Parameter Control Costs and Toxics Reductions/1

Fuel Parameter

Control

Incremental

Cost

(¢/gal)

Cumulative

Reduction 

(%)

Incremental

Cost-Eff. 

($M/ton)

Incremental

Cost-Eff.

($MM/CI)

Phase I

 RVP: 8.0 psi

 Oxygen: 2.1wt%

 Benzene: 0.95%

RVP to 7.1 psi 0.18 24.5 100 1,300

RVP to 6.7 psi 0.08 24.6 225 (-)

Sulfur to 250 ppm 0.12 26.1 30 40

Sulfur to 160 ppm 0.56 28.3 90 90

Sulfur to 138 ppm 0.24 29.0 130 200

Sulfur to 100 ppm 0.46 30.0 170 250

Olefins to 8.0 vol% 0.78 30.0 (-) 50

Aromatics to 20vol% 2.01 33.5 200 370

Oxygen to 2.7 vol% 0.61 35.7 95 170

Olefins to 5.0 vol% 2.77 35.9 4,700 300

E300 to 88% 0.35 36.0 1,200 190

E300 to 91% 2.01 36.1 4,800 510

E200 to 44% 0.38 36.5 400 120

E200 to 47% 1.32 36.8 1,400 390

E200 to 50% 2.97 37.1 3,500 860

/1 Expressed in terms of total toxics reductions. Based on costs and

emissions reductions for VOC control region 2 (northern areas). Assumes all

costs allocated to toxics control.

Tables VI-A5 and VI-A6 also present information on the

reductions in each of the five individual toxics of concern. 

These tables show that emissions of all toxics except

formaldehyde are reduced as a result of the controls listed in

Table VI-22. Only the control of E200 and E300 have a positive

impact on formaldehyde emissions. RVP control negatively impacts

1,3-butadiene emissions. Olefin control tends to increase

emissions of benzene and POM, although this impact varies

depending on the levels of the other fuel parameters. The cost-
 109Wyborny, Lester, U.S. EPA, "Documents Concerning Refinery

Modeling for the Reformulated Gasoline Program," Memorandum to

the Docket. 

 110Ibid.

372

effectiveness of controlling any one of the toxics, if all of the

costs were allocated to that control, range from several hundred

thousand to several million dollars per ton of pollutant reduced.

G. Comparison with Other RFG Cost-Effectiveness Analyses

Contrary to VOC and toxics cost-effectiveness, which are

either very economical or too costly, respectively, NOx costeffectiveness will figure substantially into the decision-making

process for establishing a NOx standard. For this reason, NOx

cost-effectiveness values were compared between various refinery

models to better understand the cost of reducing NOx. The sulfur

reduction cases (sulfur has the largest impact on NOx reductions)

from the B & M cost data were compared to the cost data from

other models which optimized around NOx reduction (i.e., refinery

models into which the complex model was incorporated directly). 

Even though multiple parameters changed in these other NOx

studies, sulfur was still the major factor which the refinery

models chose to modify. This observation at least verifies that

the models are similar. 

An important reason for making the NOx comparison in

addition to the sulfur comparisons made above in section C is to

allow the comparison with additional studies which could not be

used specifically for the sulfur analysis. The costeffectiveness analysis by DOE,109 and the Turner/Mason costeffectiveness analyses for the National Petroleum Council and API

could then be compared. Several discussions were held with DOE

and with API late in 1993 concerning some of the assumptions made

by API in the running of their computer model.110 These

assumptions are important since they determine, to a large

degree, the difference in sulfur costs noted above. The DOE

staff integrated some of these assumptions into their refinery

model. In addition, these later runs allowed the DOE model to

incorporate the final version of the complex model (although

negligible differences would be expected between the final

version and other late versions on which the API model were

based). To compare the NPC data, the parameter values for

several of the computer runs (case code numbers Q40L and Q6N

Base) were entered into the complex model and the resulting NOx

changes were noted. The cost-effectiveness calculated from the

various refinery models were normalized to the EPA data on the

basis of the fuel economy of the vehicle fleet in 2003, the 2003
373

vehicle fleet NOx emission factors, and the same methodology for

calculating cost-effectiveness (annualized tons, 10% rate of

return on investment, etc.). 

NOx cost-effectiveness was compared separately for PADD 1

and PADD 3 refinery model runs. The plot of PADD 1 costeffectiveness is shown in Figure VI-A2 located in the appendix. 

The DOE cost-effectiveness curve is steeper initially than the B

& M curve, showing a lower cost-effectiveness value (more costeffective) at the same percent NOx reduction. The DOE curve

changes to a higher cost-effectiveness value after it crosses the

B & M line. The DOE data corroborates the B & M data at one

point just above the 7 percent NOx reduction line, indicating

that greater levels of NOx reduction become less cost effective. 

The API data parallels the B & M plot but indicates higher costeffectiveness values (i.e., less cost effective control) at each

percent reduction in NOx value. 

The plot of cost-effectiveness versus NOx reduction for PADD

3 is shown in Figure VI-A3. This plot shows that the DOE, AutoOil and NPC data all corroborate the B & M data by showing

similar levels of cost-effectiveness in the range of 6-9%

reduction in NOx. In contrast, the API data is significantly

higher in cost, as it was for PADD 1. 

H. Factors to be Considered in Setting Phase II RFG Standards

Various economic, technological, and environmental factors

should be considered in addition to the estimated costeffectiveness when setting performance standards for Phase II

reformulated gasoline. The following sections present EPA's

consideration of many of these issues.

1. Comparison to Cost-Effectiveness of Other Control Strategies

The cost-effectiveness of VOC and NOx control under the

Phase II reformulated gasoline program is most easily evaluated

when compared to other stationary and mobile source VOC and NOx

control strategies. Several comments received on the proposed

standards recommended that EPA evaluate the cost-effectiveness of

the Phase II standards compared to other control measures. One

commenter suggested that such a comparison should include the

option to adopt programs such as RVP control instead of

reformulated gasoline. The draft RIA did contain some

comparisons with other mobile and stationary source control

programs. That comparison has been expanded here to include a

more detailed discussion of the cost-effectiveness of alternative

means to control VOC and NOx emissions from stationary and mobile

sources.

It is important to note that not all of the other studies

compared here used the same methodology used by EPA to determine
 111The Clean Air Act section 183(d) Guidance on CostEffectiveness; OAQPS, U.S. Environmental Protection Agency;

November 1991. 

 112U.S. EPA, "Issues Relating to VOC Regulation Cutpoints,

Deficiencies, and Deviations. Clarification to Appendix D of

November 24, 1987 FEDERAL REGISTER," Office of Air Quality

374

the cost-effectiveness of Phase II RFG. This analysis is based

on the incremental cost-effectiveness of a particular change in

fuel composition relative to a previous, less costly change. 

Most other analyses determine overall cost-effectiveness relative

to a baseline value. If multiple options are considered by these

studies, the cost-effectiveness of each option is evaluated

relative to this baseline rather than relative to the preceding

option. Hence, in many cases it is more appropriate to compare

the incremental cost-effectiveness of Phase II RFG relative to

Phase I RFG with the cost-effectiveness of other studies.

Another factor which will affect the comparison of the costeffectiveness of Phase II RFG with other control programs is the

fact that the Phase II standards are being set now (as agreed in

Reg-Neg) even though they will not take effect until the year

2000. The cost-effectiveness of VOC and NOx programs being

evaluated seven years from now are expected to be much higher

than those estimated here, since many of the less costly controls

will already be implemented. Although EPA cannot project what

controls may be under consideration by the year 2000, it is

reasonable to assume that the Phase II RFG program will be

competitive by comparison.

a. Stationary Source Emission Control Cost-Effectiveness

In response to the cost-effectiveness analysis presented in

the proposal, one commenter stated that since EPA used average

costs which may be low compared to the costs realized in PADD 1

(since PADD 1 will have a high fraction of RFG produced), the

cost-effectiveness of Phase II RFG in PADD 1 would greatly exceed

the cost-effectiveness of stationary source controls in PADD 1. 

EPA disagrees, based on the cost-effectiveness estimates

presented below. Furthermore, comments received from the state

regulators in PADD 1 indicated that the cost-effectiveness of

Phase II RFG presented in the draft RIA was competitive with the

cost of various control strategies currently in use or planned.

The cost-effectiveness of stationary source VOC emissions

was determined from recommended control strategies for severe

nonattainment areas.111 A review of the estimated costeffectiveness of controlling VOC emissions from stationary

sources yielded a wide range of values.112 Many existing VOC
Planning and Standards, May 25, 1988 (Revised 1/11/90).

 113"Evaluation and Costing of NOx Controls for Existing

Utility Boilers in the NESCAUM Region"; Draft Report prepared

by Acurex Corp., prepared for Bill Neuffer, OAQPS, U.S. EPA,

October, 1992.

375

control strategies have small costs or even result in savings. 

However, many other VOC control options have significant costs

associated with them. For example, the estimated costeffectiveness of reducing emissions from automobile and light

truck coating operations in assembly plants is $1,000-4,000/ton

VOC. Reducing emissions from the production of pneumatic rubber

tires is estimated to cost between $150 and $18,800 per ton of

VOC reduced. The cost-effectiveness depends on the operation to

which control is applied. Control of emissions from floating

roof tanks used for storage of petroleum liquids can cost up to

$3,700/ton VOC reduced. Reducing emissions from the production

of high density polyethylene, polypropylene, and polystyrene

resins can cost between $1,000 and $3,000/ton VOC reduced

depending on the level of control required at these facilities.

The comparative cost-effectiveness of stationary source NOx

emission controls was based on those suggested for utility

boilers.113 In ozone nonattainment areas, standards are being

considered that will require controls more stringent than

suggested by reasonable achievable control technology (RACT)

standards. The RACT standards will likely be met through the use

of low NOx burner technology. This technology has a relatively

low cost-effectiveness at up to $1,000/ton, but the achievable

emissions reduction is limited. In order to meet the ozone air

quality standard in many areas, additional control will likely be

required particularly by the year 2000. One of the likely

strategies utilized will be selective catalytic reduction (SCR)

which is estimated to cost $3,000-$10,000/ton NOx. 

b. Mobile Source Emission Control Cost-Effectiveness

Although there is some merit to comparison with stationary

source control options, it is more appropriate to compare the

cost-effectiveness of Phase II RFG with other mobile source

control programs. Emissions from mobile sources occur at groundlevel and are more widely dispersed than emissions from a large

point source. Control of these emissions is therefore more

important in trying to reduce the formation of ozone, because

mobile source emission control (through fuel or vehicle measures)

will help all areas to reduce ozone, while controlling point

source emissions will only help a narrow area affected by the

emission plume from that source. Hence, estimates of the cost-
 114"Inspection/Maintenance Program Requirements," Final

Rule, November 5, 1992, 57 FR 52984.

 11540 CFR Part 51 (52950) Inspection/Maintenance Program

Requirements; Final Rule; Environmental Protection Agency,

November 5, 1992.

376

effectiveness of various mobile source control strategies has

also been examined.

(1). Mobile Source VOC Control

The cost-effectiveness of several VOC control strategies has

been identified for comparison with the Phase II RFG VOC

standard. Enhanced inspection and maintenance (I/M) programs

will cost between $900-1,700/ton VOC reduced, while basic I/M was

estimated to cost $5,400/ton VOC.114 The Tier 1 standards for

light duty vehicles (already implemented for the 1994 model year)

were estimated to cost about $6,000/ton VOC. On-board

diagnostics are estimated to cost about $2,000 per ton of VOC

reduced as a result of this computerized engine monitoring

system. 

(2). Mobile Source NOx Control

 The enhanced I/M program is primarily a VOC and CO control

strategy, although NOx reductions are achieved. The cost of NOx

emissions reduction is difficult to separate from the costs of

VOC and CO emissions reductions. The cost-effectiveness of NOx

control through enhanced I/M programs is estimated to be $3,000-

6,000/ton115. An enhanced I/M program which employs a more

stringent NOx cutpoint than typically assumed is estimated to

have a cost-effectiveness of $4,000-8,000/ton.

The Tier 1 emissions standards for light duty vehicles will

incur an estimated incremental cost of $2,000-6,000/ton NOx if

credit is only given for those emission reductions achieved in

ozone nonattainment areas during the ozone season (to allow

direct comparison with reformulated gasoline). Achieving the

Tier 2 mobile source NOx standards (should EPA determine that

such standards are necessary to meet air quality requirements) is

likely to cost more than $10,000/ton of NOx reduced. 

Certain NOx controls for heavy duty vehicles (both highway

and nonroad) are likely to be very cost effective in comparison

to other programs. Since heavy duty vehicles contribute a large

fraction of the NOx inventory, control of emissions from these

vehicles has the potential to result in large reductions. EPA is

developing and studying such controls. However, heavy duty NOx

controls alone are unlikely to achieve the in-use reductions in
377

NOx necessary to achieve the ozone NAAQS in most areas. All NOx

control strategies that are not implemented or are not already

under consideration are likely to be very costly; NOx control

combined with the reformulated gasoline program is very

reasonable by contrast. 

2. Cost-Effectiveness Cutoff Limits

In the NPRM, EPA proposed determining the Phase II RFG

standards based on a predetermined maximum limit for the costeffectiveness of that level of control. Two cost-effectiveness

limits were presented, $5,000 and $10,000 per ton, and comments

were requested regarding the appropriate limit to select. 

Several comments were received which addressed this subject. One

commenter stated that the $5,000/ton VOC limit is appropriate. 

Another stated that the $5,000-10,000/ton range proposed is the

upper end of costs incurred by many areas to achieve VOC control,

in effect establishing more costly criteria than required for

other programs. The recommendation that EPA choose a low costeffectiveness target because of weaknesses in the analysis (as

presented in the draft RIA) was also received. However, EPA also

received the comment that the upper end of the proposed range was

reasonable considering the costs currently incurred by many

states for existing control programs. (No support was given for

this last statement.)

As discussed in the previous section, EPA has examined the

cost-effectiveness of a variety of stationary and mobile source

VOC and NOx control options. Depending on the type of programs

and level of reduction achieved, these programs have a costeffectiveness ranging from essentially zero (or even a cost

savings) to well over $10,000/ton reduced. After considering

this information, EPA believes that a cost-effectiveness

benchmark of $10,000/ton is too high at this time and that a

benchmark around $5,000/ton is more appropriate for the Phase II

VOC standard and accompanying NOx standard. However, as

explained elsewhere in this document and in the preamble for this

rulemaking, other factors were taken into consideration when

setting the standards, and hence, the cost-effectiveness limit

was not the only deciding factor.

3. Other Economic Considerations

The economic impact on the refining industry of the Phase II

reformulated gasoline standards and NOx standards for

reformulated gasoline will depend on the severity of the

standard. It will also depend on the fuel parameter changes

which are necessary to achieve those standards. The costs and

cost-effectiveness analyzed here are for the average refinery,

and thus, across the industry there will be a variety of costs

and economic impacts of this regulation. The cost experienced by

the consumer, whether inside or outside of an ozone nonattainment
378

area, will depend not only on manufacturing costs but also on

market conditions. 

While it is true that the cost-effectiveness for an

individual refinery may be different than that used here to set

the standards, EPA believes that the standards have been set with

enough flexibility to prevent refiners from incurring extreme

costs. It is not currently possible to set the standards taking

into account the individual cost-effectiveness of each refinery

or the emissions reductions achieved in every distinct area using

RFG. Such an analysis would require knowledge of the operating

costs and configuration of each refinery, as well as the volume

of reformulated gasoline produced. However, because EPA

considered the ability of refiners to achieve the emissions

reductions and thus did not specify a single fuel formulation to

meet the Phase II standards, each refiner will be able to choose

the refinery configuration that will produce RFG in the most

cost-effective manner for that refinery. For example, if the

refiner produces a gasoline that is high in olefins, it is likely

that he can still meet the NOx standard without incurring costs

greater than $10,000/ton NOx (as the costs in Table VI-21 show. 

Similarly, if a refiner produces a fuel that is high in

aromatics, he can meet the VOC standard without incurring

significantly higher costs. 

4. Energy Factors

Production of Phase II reformulated gasoline subject to

performance standards for VOC, NOx, and toxics will require an

increase in the amount of energy used at the refinery. An

estimate of the energy used depends on many factors, including

how the energy balance is evaluated, the type and source of

oxygenate, the refinery configuration, and the reformulation

approach. Determining an exact energy increase associated with

reformulated gasoline production (on the basis of a constant

level of gasoline energy produced) is difficult.

Cost-effective control of VOC and NOx will likely be

achieved largely through reductions in the sulfur content and

Reid vapor pressure (RVP) of the fuel. Removing sulfur from

gasoline is an energy intensive process; the amount of energy

required varies depending on the sulfur level of the crude used

by the refinery. Reducing the RVP of the fuel requires removal

of the lighter compounds in the fuel, also an energy consuming

process. Overall, it is expected that the energy consumption by

refineries in producing Phase II reformulated gasoline will

increase slightly over the level of energy used to make Phase I

RFG, but the magnitude of this increase is difficult to measure

due to the many variables involved.

As discussed in subsection C.4, changes in some parameters

impact the energy density of the resulting gasoline (and hence,
379

the fuel economy achieved by the vehicle). Although there may be

some increase in energy consumed in the form of gasoline as a

result of this (it could take more energy to go one mile),

especially as a result of the addition of oxygen, the impact for

Phase II fuels is likely to be small. This is because few of the

fuel changes which would negatively impact fuel economy, such as

increasing the oxygen content to 2.7 wt%, are likely to be costeffective for refiners to use in meeting the standards.

There may also be energy benefits resulting from reduced

consumption of gasoline in areas using reformulated gasoline. 

Historically, when the retail price of gasoline has risen,

consumption has declined. Phase II reformulated gasoline is

expected to cost 1.2¢/gallon more than Phase I RFG. It is

possible that consumers may reduce gasoline consumption in

response to this price increase. As a result, less petroleum

will be needed to produce gasoline, potentially leading to a

reduction in oil imports. However, the reduction gasoline

consumption resulting from the increased price of Phase II RFG is

likely to be small compared to the likely impact of Phase I RFG.

5. Environmental and Health Factors

In response to the proposed Phase II RFG standards, EPA

received the comment that EPA should detail the value of the

health, welfare, and environmental improvements achieved through

the standards. Specifically, it was suggested that these

benefits be demonstrated in terms of the VOC and NOx reductions

achieved. Section F presented EPA's analysis of the costeffectiveness of various levels of VOC and NOx control, expressed

in terms of the cost per ton of pollutant reduced. The following

paragraphs discuss the health and welfare benefits of achieving

these reductions.

The purpose of the reformulated gasoline program is to

reduce ozone formation and cancer incidences due to motor vehicle

emissions of VOC and toxics in those areas most in need of such

reductions. The most widespread problems among the major air

pollutants for which an NAAQS standard has been established is

ozone. Ozone is formed through atmospheric reactions of NOx and

hydrocarbons in the presence of sunlight. Emissions from both

mobile and stationary sources contribute to ozone formation.

Reducing ozone levels (through reductions in emissions of

VOC and/or NOx) in highly populated urban areas would help to

reduce short-term health effects caused by exposure periods as

short as one hour, such as impaired lung function, cough, nausea,

chest pain, throat irritation, increased susceptibility to

respiratory infection, and increased sensitivity of asthmatics to

allergens (e.g., pollen) and other bronchoconstrictors. Exposure

to elevated ozone levels can even affect respiratory performance

in healthy individuals during exercise outdoors. Long-term
 116U.S. EPA, "Review of the National Air Quality Standards

for Ozone - Assessment of Scientific and Technical

Information," OAQPS, EPA-450/2-92-001, June 1989, p.X-25.

 117Ibid., p.X-26,27.

380

health effects of exposure to ozone include accelerated aging of

the lungs, reduces elasticity of the lungs, scarring of lung

tissue, and permanent reductions in baseline lung function. 

Reducing ozone levels in rural areas where fewer people are

exposed would enhance agricultural crop yield production,

currently estimated to be reduced by as much as 2 to 3 billion

dollars per year by existing ozone concentrations.116 In

addition, lower ozone levels would help reduce damage to forest

ecosystems which experience lower tree growth rate, foliar

damage, and increased susceptibility to stress (e.g., insects,

disease, drought) caused by current tropospheric ozone levels. 

Ozone can also damage watershed areas and marine life.117 It

persists for several days in the lower atmosphere and can travel

hundreds of miles.

The environmental benefits to the areas receiving

reformulated gasoline are measured in terms of tons of VOC

emissions reduced and number of cancer incidences avoided. The

benefits of the NOx reduction program similarly are measured in

terms of the tons of NOx reduced. In addition to these

measurable benefits in terms of ozone precursor reduction and

human health, there are many other health and environmental

benefits of reducing VOC, NOx, and toxics emissions. Additional

information on the benefits of NOx reductions can be found in

section B above.

Reductions in mobile source emissions of air toxics

(benzene, 1,3-butadiene, formaldehyde, acetaldehyde, and POM) may

result in fewer cancer incidences. The number of cancer

incidences likely to be reduced as a result of the Phase II

standards has been estimated to be quite small, as summarized in

subsection F.3. 

A number of adverse non-cancer health effects have also been

associated with exposure to air toxics, particularly with higher

level exposures experienced in particular microenvironments such

as parking garages. Benzene is known to cause disorders of the

blood. It can also be immunotoxic, and may be a developmental

and reproductive toxicant. High level exposure to 1,3-butadiene

can cause eye, nose, and throat irritation, while very high

exposure can cause effects on the brain leading to respiratory

paralysis and even death. Epidemiologic studies of 1,3-butadiene

have also indicated a possible association with heart disease,
 118Cotruvo, Joseph A. et al, "Formaldehyde Risk Assessment

Update (1991)," Toxic Air Pollutants from Mobile Sources: 

Emissions and Health Effects, Proceedings of an International

Specialty Conference, Air and Waste Management Association,

VIP-23, 1992.

 119EPA document 420-R-93-005, April 1993.

381

blood disease, and lung disease at relatively high exposures. 

Exposure to low airborne concentrations of formaldehyde can lead

to irritation of the mucus membranes of the eyes and respiratory

tract and potentially to cellular changes in the nasal cavity.118

A more thorough discussion of the variety of possible non-cancer

effects of concern from exposure to air toxics is contained in

EPA's Motor Vehicle-Related Air Toxics Study.119

In addition to the ozone reductions and decrease in cancer

incidences which will be experienced as a result of the

reformulated gasoline program, other benefits are likely to

occur. For example, the 2.0 volume percent oxygen requirement

for RFG will reduce emissions of carbon monoxide (CO) by 10-15

percent, an added benefit to areas which exceed the NAAQS

standard for that pollutant. This will occur primarily in Phase

I of the RFG program, when the oxygenate mandate takes effect. 

Additional reductions in CO emissions are likely to occur with

Phase II RFG, as well. However, these Phase II benefits cannot

currently be quantified as a complex model for CO emissions has

not yet been developed. 

In areas not receiving reformulated gasoline, no detrimental

effects are expected since the gasoline sold in those areas must

comply with the anti-dumping provisions. Additionally, it is

likely that spillover of reformulated gasoline into these areas

will provide even cleaner fuel to those areas. 

6. Technological Feasibility

The technological feasibility of producing fuels to meet the

Phase II standards was also considered. EPA believes that the

refinery modelling results (from which the fuel parameter control

costs were estimated) provide adequate support for the

feasibility of making the fuel parameter changes used to achieve

the standards. The refinery models utilize only well-developed,

demonstrated, commercially available technologies, and hence will

only produce fuels within the limits of these technologies. 

Furthermore, one comment received on the proposal supported the

technical feasibility of Phase II RFG controls by noting that the

California Air Resources Board has set specifications for

California Phase II RFG which demonstrate the feasibility of

going beyond 25% VOC emissions reductions. Given the incentives
382

created by this rulemaking, in all likelihood new technologies

will be developed between now and the year 2000 which will reduce

the costs for certain types of fuel parameter changes. Thus, EPA

believes that the determination of fuel parameter control costs

using the results of the existing refinery models is conservative

and that the feasibility of producing such emission-reducing

fuels is justifiable. This position was supported by many of the

comments received.

7. Fuel Safety Factors and Driveability Concerns

Comments concerning the safety of low RVP fuels in vehicle

fuel tanks were received which suggested that a minimum RVP level

be established and required for RFG. One comment suggested that

producers will make RFG with an RVP in the "high 5 psi range" if

faced with a standard for an RVP of 6.5 psi. Since no safety

studies are available for fuels with such low volatilities, the

commenter recommended setting 7.0 psi as the minimum for RFG. 

Another comment questioned whether the study presented by EPA in

the Draft RIA did not adequately address the transitional months

(May and September) or the low temperatures and low RVPs that

could be experienced in areas on the fringe of nonattainment

areas.

In EPA's evaluation of the safety of vehicle fuel tanks with

low RVP fuels, a thorough analysis of the safety of low RVP fuel

for the summer months (May through September) was performed. 

This analysis showed that gasoline with an RVP above 5.0 should

not yield a combustible mixture in the fuel tank under any likely

summertime temperatures. This analysis was based on the 0th and

10th percentile lowest temperatures experienced during these

months in the nonattainment areas. The analysis further showed

that a fuel tank filled with gasoline at an RVP of 6.0 psi or

greater would not contain a flammable mixture. Extending these

results to other fuel storage vessels, it is unlikely that

gasoline with a minimum RVP of 6.0 psi would lead to flammability

problems in pipelines or storage tanks.

Some concerns were raised about driveability problems

arising from the use of low RVP fuels. No testing was performed

by the Agency or other organizations to evaluate driveability at

low ambient summer temperatures. However, EPA expects that

driveability of a 6.5 psi fuel in the summer should be similar to

current winter fuels, based on the actual vapor pressure of fuels

currently in production. EPA discussed this finding with

representatives of both the oil and the automotive industries,

who did not indicate a concern with fuel RVPs as low as 6.5 psi. 

However, they did express an uneasiness with lower RVPs. Until

such time as data can be gathered to fully evaluate the

driveability impacts of low RVP fuels, it is not possible to

determine the true driveability impacts of fuels with RVPs lower

than 6.5 psi. However, given that most refiners will likely
383

produce gasoline with an RVP around 6.7 psi to meet the Phase II

standards, EPA believes it to be appropriate to treat 6.5 psi as

a practical lower limit for RVP.

I. Standards

In the draft RIA, EPA presented cost-effectiveness analyses

for the use of Phase II reformulated gasoline in each of the two

VOC control regions. Based on these analyses, the Agency

proposed a range of possible standards for each VOC control

region. The standards were proposed as a range instead of a

single number because EPA was requesting comment on what level of

cost-effectiveness ($5,000 or $10,000/ton) was reasonable to

require, and because EPA was considering a variety of minimum

levels for the Reid vapor pressure of Phase II RFG. The

following sections summarize comments which were received on the

proposed standards and present the final standards derived based

on the cost-effectiveness analysis presented in this document.

1. Comments on Proposed Standards

Several comments were received on the proposed standards. 

One comment suggested that since refiners are likely to reduce

parameters to levels lower than the mandated limits to ensure

compliance with the standards, the cost analysis should be based

on a marginal increase in the standard to determine the true

cost-effectiveness of the program. Another comment stressed that

EPA distinguish carefully between the RFG standards and the

characteristics of the gasoline that will be produced to meet the

standards within the compliance margins. The concern expressed

by both commenters was that EPA would set standards without

considering the fact that refiners may be operating near the

"knee" of the cost-effectiveness curve (the point beyond which

the costs increase dramatically for a relatively small reduction

in emissions) at the levels of some parameters required to meet

those standards. Because refiners would likely produce fuels

with even lower levels of the gasoline parameters to ensure

compliance, they may be pushed past the knee in the curve for

some of the parameters.

The cost-effectiveness analysis presented here, on which the

standards for Phase II RFG will be based, is inherently an

average cost analysis, since it is based on regional refinery

modelling data. Hence, the standards derived from this analysis

will be averaging standards. There is no need for refiners to

have a compliance margin in meeting the averaging standard. The

difference between the stringency of the averaging standard and

the per gallon standard is intended to be roughly equivalent to

the compliance margin, as the provisions of section VII of the

preamble demonstrate. As determined in Reg-Neg, this difference

is 1.5% VOC. As long as the per gallon minimum does not
384

constrain the ability to meet the averaging standard, variations

between gallons and measurement error can be accommodated. 

Refiners will be able to meet the averaging standard exactly, and

thus there is no need to artificially adjust the costeffectiveness analysis to allow for compliance with the averaging

standard. Furthermore, since refiners can choose which standard

each gallon will meet after it has been produced, any measurement

error is in their favor, since they can apply any gallon to the

averaging standard. Hence, EPA's standards are actually

conservative. 

Another recommendation suggested that the incremental costeffectiveness analysis begin at the statutory minimum (20%

reduction in VOC, no net increase in NOx), and that the standards

be set at a point on the cost curve to avoid excessive

incremental cost-effectiveness. Since the standards are based on

an incremental cost-effectiveness analysis the starting point for

the analysis is irrelevant. If the standards were set based on

the total cost-effectiveness incremental to the Phase I

standards, the concern raised by this comment would have been

appropriate.

It was also suggested that EPA define the VOC and toxics

performance requirements (standards) based on the emissions

reductions achieved by a fuel meeting pre-specified design value

property limits. The design values suggested by the commenter

were based on the parameter values used in the draft RIA to

determine the proposed standards. In effect, this would set a

fuel specification to ensure that a certain level of VOC control

would be achieved, using the complex model to determine that

level of control. EPA believes that it is inappropriate to set

the standards based on design values. This would severely limit

the flexibility of individual refiners in meeting the standards. 

In effect, this approach would set a fuel specification; the

Phase II standards are meant to be a performance standards that

can be met with any fuel formulation that is cost-effective to an

individual refiner. Furthermore, EPA has revised its costeffectiveness analysis using the final complex model and updated

cost information, so the parameter values used to obtain the

proposed standards no longer necessarily are necessary or

required to meet the new standards. 

Another comment suggested that EPA set the Phase II

standards somewhat less stringent than California Phase II

reformulated gasoline, and that the federal standards include a

cap on olefins, aromatics, and oxygen. EPA has set the standards

based on the need for emissions control, the cost-effectiveness

of that control, and on the burden to refiners of meeting the

requirements. Since the purpose of the complex model is to allow

refiners greater flexibility in meeting the performance standards

under both Phase I and Phase II, it would be inappropriate to set

caps on any fuel parameter for Phase II RFG. The caps on some
385

parameters which EPA has instituted only apply to fuels certified

with the simple model. These caps were only intended to provide

a safeguard on the emission performance of RFG fuels until such

time as those parameters could be modelled.

Two comments concerned the joint requirements of VOC and NOx

standards. The first said that the desire to control both VOC

and NOx was in conflict because the fuel parameter changes that

reduce NOx tend to increase VOC (and vice versa). EPA's revised

analysis, using the final version of the complex model, does not

support this claim. According to EPA's analysis, it is possible

to reduce both VOC and NOx. Reductions in RVP, the main source

of VOC control, yields small (minimal) reduction in NOx. 

Similarly, sulfur reductions to reduce NOx also yield minimal

reductions in VOC. The second comment supported the requirement

of a NOx standard if it was consistent with the goals of

maximizing VOC and toxics reductions. Toxics reductions have

already been shown to be cost-ineffective. As the costeffectiveness analysis in section F demonstrates, NOx control can

be achieved with maximum VOC control in a manner which is most

cost effective for both pollutants.

2. Final VOC Standards and NOx Standards

Based on the cost-effectiveness analysis and other

considerations presented above, EPA is setting VOC reduction

standards for Phase II reformulated gasoline and concurrent NOx

reduction standards for gasoline sold in areas participating in

the RFG program beginning in the year 2000. These standards are

shown in Table VI-23 below. The combination of fuel parameters

on which the standards are based is just one of many fuel

formulations which could be used to achieve the standards. It

must be stressed that these standards are performance standards

which may be met by the refiner's choice of fuel parameter

controls; they are not specifications for fuel composition.
386

Table VI-23: VOC Standards for Phase II Reformulated Gasoline and

NOx Reduction Standards (Percent Reduction in Emissions)

Controlled Emission VOC Control

Region 1

VOC Control

Region 2

VOC - per gallon

 - averaging

 - minimum

27.51 25.9

29.0 27.4

25.0 23.4

NOx - per gallon

 - averaging

 - minimum

5.5 5.5

6.8 6.8

3.0 3.0 1

Reductions relative to a base fuel with RVP at 7.8 psi on a

per gallon basis would be VOC: 17.2%; NOx: 5.3%

The 5.5% per gallon NOx reduction standard has been

determined to be the level of reduction that can be cost

effectively achieved. This is based on control of sulfur down to

138 ppm. The VOC standard was determined based on the level of

VOC control that can be cost effectively achieved through RVP

reduction (i.e., down to 6.7 psi) as well as the VOC reductions

achieved by reducing sulfur to meet the NOx standard. If EPA had

elected to set only a VOC standard and had pushed RVP down to the

practical limit (6.5 psi, as discussed previously), essentially

the same level of VOC reduction would have been achieved. 

However, setting both the VOC and NOx standards based on an RVP

of 6.5 psi and sulfur at 138 ppm would severely restrict the

flexibility of refiners. Furthermore, such strict standards

could pose an undue burden on some refiners with baseline levels

of certain parameters (e.g., olefins) above the average. Hence,

EPA set the VOC and NOx standards based on the emissions

reductions that could be achieved with a fuel containing 138 ppm

sulfur and an RVP of 6.7 psi. As this analysis shows, EPA is

setting a NOx standard that refiners can meet in a cost effective

manner without jeopardizing their ability to meet the VOC

standard for Phase II reformulated gasoline. The costeffectiveness of this level of NOx reduction, if credit is given

for the additional VOC reductions achieved at this level of NOx

control (on the order of $500/ton VOC reduced), is about

$5,000/ton NOx reduced.

As a result of these standards, VOC emissions will be

reduced by about 10,000 tons in VOC control region 1 (southern)

areas each summer and 32,000 tons in VOC control region 2

(northern) areas. In addition, southern areas will experience a

reduction of about 8,600 tons NOx and northern areas will
 120The toxics standard is a requirement for an average

percent reduction over the entire year, not solely in the

summer (high ozone) season.

387

experience a reduction of 13,800 tons NOx. The emissions

reductions experienced in southern areas are smaller than

experienced in northern areas due to the fact that southern areas

are already required to use fuels with lower Reid vapor

pressures, and thus the emissions reduction benefits of RFG use

in these areas is smaller.

3. Toxics Standard

The statute sets the minimum Phase II standard for toxics

reduction at 25%, although EPA has the authority to reduce this

down to 20% "based on technological feasibility, considering

cost."120 There was general support in the comments on the NPRM

for the fact that the cost-effectiveness of toxics control beyond

a 20% reduction is questionable. No substantive comments were

received opposing the option of setting the standard at the

minimum 20% reduction. The cost-effectiveness analysis presented

here indicates that the technology implemented by refiners to

comply with the required VOC and NOx reductions will result in a

26% reduction in toxics annually on average. Hence, most

refiners will clearly be able to meet a 25% toxics standard. For

certain non-average refiners with high baseline levels of various

parameters, however, compliance with the VOC and NOx standards

may not automatically lead to compliance with a 25% toxics

standard. For these refiners, additional reductions in toxics to

meet the standard would require expensive controls, putting them

at a competitive disadvantage relative to those refiners who

comply with the toxics standard "for free" based on their

compliance with the VOC and NOx standards. 

If marginal reductions in air toxics were cost effective,

EPA would be justified in requiring their control. However, this

is not the case. The additional toxics control required by the

subset of refiners described above results in very high cost per

cancer incidence avoided, in excess of $100 million/CI, well

beyond the $1-10 million/CI which the Agency believes to be

achievable through other programs. In addition, benzene

reduction (which, along with aromatics reduction, is one of the

two likely means of reducing toxics) would impact only emissions

of benzene, not 1,3-butadiene, which has been shown to be of

greater cancer-causing risk to the public. (The statutory

requirements of section 211(k) requires a focus on reductions in

mass emissions of air toxics, not on a reduction in cancer risk,

and therefore does not permit EPA to set the standard based on

relative cancer risk.) Even though a 25% toxics standard is

technologically feasible, the circumstances discussed above raise
388

questions about the increased cost to this subset of refiners of

implementing additional toxics reduction technology.

Based on these concerns, EPA is setting the per gallon

toxics standard at the statutory minimum 20% (and the averaging

standard at 21.5%). Despite the fact that the toxics standard is

reduced to 20%, EPA nevertheless anticipates that the average inuse toxics performance will still be above 25%, as discussed

above. Total toxics emissions will be reduced by about 370 tons

in VOC control region 1 annually, and 630 tons in VOC control

region 2. Approximately 3-4 cancer incidences will be avoided

annually nationwide as a result of this level of toxics

reduction.
389

J. Appendix VI-A: Tables VI-A1 to VI-A6
390

Table VI-A1 Phase II RFG Refining Costs for Individual Parameter Changes

Parameterand Range ofParameterChange

Region Cost

(¢/gal)

CapitalCharge  (MM$)

CapitalCost 15%and 10%ROI(¢/gal)

AdjustedCost @10% ROI(¢/gal)

Cost perUnitParameterChange 

Unitsfor Cost

RVP:7.79 to 7.33 1 0.309 79.6

15%: 0.33910%: 0.257 .226 0.492 c/gal/psi

7.85 to 7.37 2 0.255 28.4

 0.106 0.080 0.229 0.477 c/gal/psi

7.64 to 7.30 3 0.175 137.6

 0.226 0.171 0.120 0.352 c/gal/psi

RVP:7.33 to 7.09 1 0.170 57.6

 0.245 0.185 0.110 0.461 c/gal/psi

7.37 to 7.16 2 0.121 10.2

 0.038 0.029 0.112 0.533 c/gal/psi

7.30 to 6.94 3 0.215 225.5

 0.371 0.281 0.125 0.347 c/gal/psi

RVP:7.09 to 6.5 1 0.568 69.8

 0.297 0.224 0.495 0.839 c/gal/psi

7.16 to 6.5 2 0.482 146.5

 0.545 0.412 0.349 0.530 c/gal/psi

6.94 to 6.5 3 0.219 302.5

 0.498 0.377 0.098 0.223 c/gal/psi

Oxygen:2.1 to 2.7 1 0.800 (62.6)

 (0.267) (0.202) 0.865 1.44 c/gal/%

2.1 to 2.7 2 0.566 (52.0)

 (0.194) (0.147) 0.613 1.02 c/gal/%

2.1 to 2.7 3 0.521 (322.7)

 (0.531) (0.402) 0.650 1.08 c/gal/%
391

Table VI-A2 Phase II RFG Refining Costs for Individual Parameter Changes

Parameterand Range ofParameterChange

Region Cost Capital

Charge  (MM$)

CapitalCost 10%and 15%ROI(c/gal)

AdjustedCost @10% ROI(c/gal)

Cost perUnitParameterChange 

Unitsfor Cost

Sulfur:337 to 250 1 0.156 61.7

15%:0.26310%:0.199

0.0925 0.00106 c/gal/ppm

453 to 250 2 0.098 75.2 0.280

0.212

0.0298 0.00014 c/gal/ppm 

441 to 250 3 0.514 137.1 0.226

0.171

0.459 0.00240 c/gal/ppm

Sulfur:250 to 160 1 0.721 56.1

0.2390.181

0.662 0.00736 c/gal/ppm

250 to 160 2 0.101 11.32 0.0421

0.032

0.091 0.0010 c/gal/ppm 

250 to 160 3 0.756 579.3 0.953 0.524 0.00582 c/gal/ppmSulfur:160 to 100 1 0.789 (18.0)

(0.077)(0.058)

0.807 0.0135 c/gal/ppm

160 to 100 2 - - - c/gal/ppm 160 to 100 3 0.756 66.0 0.109

0.082

0.730 0.0122 c/gal/ppm

Sulfur:100 to 50 1 1.30 91.9

0.3920.297

1.21 0.0241 c/gal/ppm

100 to 50 2 - - - - c/gal/ppm 

100 to 50 3 0.733 (86.9) (0.143)

(0.108)

0.768 0.0154 c/gal/ppm
392

Table VI-A3 Phase II RFG Refining Costs for Individual Parameter Changes

Parameterand Range ofParameterChange

Region Cost Capital

Charge  (MM$)

CapitalCost 15%and 10%ROI(c/gal)

AdjustedCost @10% ROI(c/gal)

Cost perUnitParameterChange 

Unitsfor Cost

Aromatics:29.65 to 28 1 0.313 33.0

0.1400.106

0.278 0.169 c/gal/%

28.34 to 28 2 0.014 18.8 0.070

0.053

(0.003) (0.009) c/gal/% 

30.54 to 28 3 0.285 541 0.890

0.673

0.068 0.0269 c/gal/%

Aromatics:28 to 24 1 1.011 (275.0)

(1.17)(0.885)

1.297 0.324 c/gal/%

28 to 24 2 0.237 147.8 0.550

0.416

0.104 0.0259 c/gal/% 

28 to 24 3 1.23 104 0.171

0.129

1.19 0.298 c/gal/%

Aromatics:24 to 20 1 1.44 (38.0)

(0.162)(0.123)

1.481 0.370 c/gal/%

24 to 20 2 0.809 93.5 0.348

0.263

0.724 0.181 c/gal/% 

24 to 20 3 1.43 (83.0) (0.137)

(0.103)

1.46 0.365 c/gal/%

Olefins:11 to 8 5 0.3

 0.138 0.104

0.390 0.130 c/gal/% 

8 to 5 5 3.0 0.620

 0.469

2.00 0.668 c/gal/% 
393

Table VI-A4 Phase II RFG Refining Costs for Individual Parameter Changes

Parameterand Range ofParameterChange

Region Cost Capital

Charge  (MM$)

CapitalCost 15%and 10%ROI(c/gal)

AdjustedCost @10% ROI(c/gal)

Cost perUnitParameterChange 

Unitsfor Cost

E200 +2,+3:50.37 to 54 1 1.27 (111)

(0.473)(0.358)

1.39 0.384 c/gal/%

52.97 to 54 2 0.104 0 0 0.105 0.102 c/gal/% 

54.9 to 58 3 0.181 298 0.490

0.371

0.06 0.020 c/gal/%

E200 +3:54 to 57 1 2.91 299

1.270.961

2.60 0.867 c/gal/%

54 to 57 2 0.827 414 1.54

1.17

0.452 1.151 c/gal/% 

58 to 61 3 0.955 24 0.039

0.030

0.946 0.315 c/gal/%

E200 +3:57 to 60 1 8.56 1037

4.423.34

7.49 2.50 c/gal/%

57 to 60 2 1.22 30 0.112

0.085

1.20 0.400 c/gal/% 

61 to 64 3 1.39 (34) (0.056)

(0.423)

1.40 0.466 c/gal/%

E300:84 to 88

 3

 0.83 410

0.1460.110

1.00 0.251 c/gal/% 

88 to 91 3 1.32 910 0.325

0.246

1.70 0.568 c/gal/% 

91 to 96 3 1.65 2705 0.965

0.730

2.79 0.558 c/gal/% 
394

Table VI-A5 Lester's spreadsheet for class B
395

Table VI-A5, cont'd
396

Table VI-A5, cont'd
397

Table VI-A6 Lester's spreadsheet for class C
398

Table VI-A6, cont'd
399

Table VI-A6, cont'd
400

Figure VI-A1
401

Figure VI-A2
402

Figure VI-A3
 121 For ease in discussion, the term "refiner", as used in

this discussion of the anti-dumping program, will hereafter

include refiners, blenders and importers. Where appropriate,

blenders and importers will be mentioned specifically.

403

VII. Anti-Dumping Requirements for Conventional Gasoline--RIA

A. Introduction

Section 211(k)(8) of the Act requires that the Administrator

promulgate regulations ensuring that the gasoline sold in areas

not participating in the reformulated gasoline program not be

more polluting than it was in 1990. Such gasoline is known as

conventional gasoline. To implement this requirement, EPA is

promulgating requirements known as the anti-dumping provisions

for conventional gasoline producers and importers. The purpose

of the anti-dumping provisions is to ensure that fuel components

that cause harmful emissions and that are removed from or limited

in reformulated gasoline not be "dumped" into conventional

gasoline, and to likewise ensure that environmentally beneficial

fuel components not be used to make reformulated gasoline to the

detriment of conventional gasoline. 

 Specifically, the Act requires that average per gallon

emissions of specified pollutants from conventional gasoline use

must not deteriorate relative to emissions from 1990 gasoline, on

a refiner, blender or importer basis. Compliance is measured by

comparing emissions of a refiner's121 post-1994 conventional

gasoline against its baseline gasoline. An individual baseline

is developed for each refiner based on the quality of its 1990

gasoline, although under certain circumstances the individual

baseline is set at the statutory baseline. These requirements

apply to all conventional gasoline producers whether or not

reformulated gasoline is also produced. 

B. Emission Requirements

The Act specifies that EPA regulations ensure that emissions

of VOC, CO, NOx and toxics due to conventional gasoline use not

increase over 1990 levels, on a refiner basis. Additionally,

each of the four pollutants is to be considered separately,

except that increases in NOx emissions due to oxygenate use may

be offset by equivalent or greater reductions in the other

pollutants. 

In the July 9, 1991 proposal, EPA discussed how it may be

possible to determine, on a seasonal or yearround basis, that

emissions of one or more pollutants from conventional gasoline

use may or may not increase. Even though emissions reductions
 122 It is possible that no dumping of benzene and aromatics

would occur. Refiners could choose to modify refinery

operations to reduce production of benzene and aromatics rather

than divert these two fuel components to conventional gasoline.

404

which may be expected to occur on average may not occur for every

refiner, blender and importer, any environmental detriment is

likely to be minimal. Thus, it is appropriate not to require

monitoring of those emissions that are not expected, on average,

to increase. Reduced monitoring and compliance requirements will

also result in cost savings. 

For several reasons, VOC and CO emission increases are not

expected in conventional gasoline areas, and thus EPA is not

regulating these two pollutants under the anti-dumping

provisions. As discussed in the July 9, 1991 proposal, Phase II

volatility requirements and spillover of oxygenated and

reformulated gasoline are expected to contribute to VOC

reductions in conventional gasoline areas. Since outside of the

high ozone season there are no VOC controls imposed on

reformulated gasoline, there is no need to impose VOC control on

conventional gasoline to counteract potential dumping. EPA also

does not expect CO emissions to increase, in or out of the high

ozone season, primarily due to the oxygenated fuels program.

Toxics and NOx emissions, however, could increase in

conventional gasoline areas as a result of reformulated gasoline

dumping. The reformulated gasoline benzene cap of 1.0 volume

percent, as well as the reduction in aromatics due to the volume

and octane contributions of oxygenate, could result in increased

toxics emissions in conventional gasoline due to dumping of

aromatics and benzene122. Because the oxygenate and benzene

requirements are yearround, toxics emissions due to conventional

gasoline use could also increase yearround. Likewise, the net

effect of conventional gasoline fuel component changes (due to

the production of reformulated gasoline) could result in

increased conventional gasoline NOx emissions. Because of the

potential for toxics and NOx emissions to increase, EPA is

regulating emissions of these two pollutants under the antidumping provisions. 

1. Emission Requirements Prior to January 1, 1998

Prior to mandatory use of the complex model on January 1,

1998, the requirements of section 211(k)(8) of the Act will be

met by requiring that the annual average exhaust benzene

emissions of a refiner's conventional gasoline not exceed its

baseline exhaust benzene emissions. 
405

The exhaust benzene emissions due to conventional gasoline

may be determined using the simple model. Only the effects of

fuel benzene and fuel aromatic content on exhaust benzene are

included in this model. Monitoring of only the benzene and

aromatic content of conventional gasoline is sufficient during

this period because, by the simple model, these are the only fuel

components which will be removed from reformulated gasoline which

affect toxic emissions. 

Per the negotiated agreement, anti-dumping compliance using

the simple model also requires that the annual average sulfur,

olefin and T90 values of a party's conventional gasoline not

exceed its baseline values of those parameters by more than 25

percent. These limits will provide additional assurance that

conventional gasoline emissions will not rise prior to use of the

complex model. EPA does not expect the levels of these

parameters in conventional gasoline to naturally increase due to

the reformulated gasoline program, since the simple model for

reformulated gasoline caps these three fuel parameters at

baseline levels and thus does not require their reduction. 

However, the relaxed caps for conventional gasoline sulfur,

olefin and T90 will provide some processing flexibility for

refiners while not harming the environment.

The exhaust benzene emissions due to conventional gasoline

may also be determined using the complex model. Because all of

the parameters affecting exhaust benzene emissions are part of

the model (benzene, aromatics, RVP, sulfur, olefins, E300, E200,

and oxygen) there is no need for separate "caps" on fuel

parameters as associated with the simple model. 

While a refiner may choose to use either the simple model or

the complex model prior to January 1, 1998, it must use the same

model for determining reformulated and conventional gasoline

compliance, if both fuels are produced. Commenters suggested

that use of the complex model (for reformulated gasoline

compliance) by one refinery should not require it at others, nor

require it to be used to determine anti-dumping compliance. 

However, the anti-dumping program is inherently tied to the

reformulated gasoline program in that the specific model used to

certify reformulated gasoline will affect which fuel components

are likely to be dumped. Requiring use of the same model for

reformulated gasoline and anti-dumping will ensure that the

effect of these components on conventional gasoline emissions

will be the same as on reformulated gasoline emissions. Without

use of the same model, incentives would exist to shift dirty

components to conventional fuel areas using whichever model

predicts the lowest emissions increase due to those components. 

If no reformulated gasoline is produced, the refiner may use

either model to comply with the anti-dumping requirements.
 123 No credit can be taken nor penalties received under the

anti-dumping program for nonexhaust benzene reductions, or

increases. Nonexhaust benzene emissions will decrease,

relative to 1990, due to RVP reductions, which are a VOC

reduction strategy already considered under the anti-dumping

program as the reason for not explicitly controlling VOC

emissions.

406

A refiner's baseline exhaust benzene emissions are

determined by evaluating the refiner's baseline fuel parameter

values in the model chosen by the refiner. At the end of a

compliance period, the average fuel parameter values of a

refiner's conventional gasoline over that period are evaluated in

the same model used to determine the refiner's baseline

emissions. The resulting emission values are then compared to

the baseline emission values to determine if the party is in or

out of compliance with the anti-dumping requirements. 

2. Emission Requirements Beginning on January 1, 1998 

When complex model use becomes mandatory on January 1, 1998,

the requirements of section 211(k)(8) of the Act shall be met by

requiring that the exhaust toxic emissions and the NOx emissions

of a party's conventional gasoline, as determined using the

complex model, not exceed that party's baseline exhaust toxic and

NOx emissions. 

The exhaust toxics emissions requirement under mandatory use

of the complex model includes all five pollutants defined in

section 211(k)(10)(C) as toxics. These are exhaust benzene,

formaldehyde, acetaldehyde, 1,3-butadiene and POM. Benzene

emissions occur in both exhaust and nonexhaust emissions, and

accordingly, §211(k)(10)(c) does not limit the toxic air

pollutant benzene to exhaust benzene. However, as stated, EPA is

only promulgating anti-dumping regulations applicable to exhaust

benzene. Nonexhaust benzene emissions will be effectively

controlled by the summertime volatility controls applicable to

conventional gasoline.123 The sum of the baseline exhaust

emissions of each of these toxics is the value that must not be

exceeded by the sum of the exhaust emissions of each toxic

pollutant due to a refiner's or importer's post-1994 annual

average conventional gasoline. 

In addition to the exhaust toxics requirement discussed

above, conventional gasoline NOx emissions are also controlled

when use of the complex model becomes mandatory. However, the

Act states that any NOx emissions increase in conventional

gasoline due to oxygenate use can be offset by VOC, CO and toxic

emission reductions. The VOC and CO emissions reductions which

occur with oxygenate use are much greater than any potential NOx
407

increase, as discussed in the July 9, 1991 proposal. To allow

for the determination of NOx emissions without the effect of

oxygenate use, EPA is allowing NOx baseline emissions

determination and subsequent compliance to be determined on a

nonoxygenate or oxygenate basis, as will be discussed in

paragraph C.4.e.

C. Individual Baseline Determination

1. Requirements for Refiners, Blenders and Importers

a. Requirements for Producers of Gasoline and Gasoline

Blendstocks

Each U.S. refinery which converts crude oil and its

derivatives into gasoline and gasoline blendstocks, and which was

in operation for at least 6 months in 1990, must determine an

individual baseline using Method 1 and/or Method 2 and/or Method

3-type data (these three data types are discussed in paragraph

C.2). Such a refinery is not allowed to have the statutory

baseline (further discussed in paragraph C.2.e) as its individual

baseline. EPA is requiring at least 6 months of operation in

order to ensure that the data is sufficiently representative of

the refinery's 1990 gasoline. A refinery in operation for less

than 6 months in 1990 gets the anti-dumping statutory baseline as

its individual baseline.

The requirement that such a refinery determine an individual

baseline rather than use the statutory baseline is to minimize

negative competitive and environmental impacts. It is possible

that, in 1990, half of the refineries produced gasoline which

results in higher emissions than the statutory baseline and half

produced gasoline which results in lower emissions. If the

statutory baseline were required, those with higher emissions

would be penalized because they would have to comply with more

stringent requirements relative to complying with their own

baseline. Those with lower emissions would be able to produce

dirtier gasoline than they did in 1990, and actually could

utilize components which were "dumped" (to produce reformulated

gasoline). If the statutory baseline was allowed, but not

required, again those with lower emissions would benefit, and

would be the only ones to use the statutory baseline because they

could produce dirtier gasoline. Those with higher baseline

emissions would not be penalized, but their post-1994 gasoline

would not be able to be any dirtier than their 1990 gasoline. In

both cases, the competitive and environmental impacts are

adverse. To minimize these results, EPA is requiring that each

refiner develop sufficient data, by estimating the quality of

their 1990 gasoline based on actual 1990 and post-1990 refinery

data, thereby avoiding default to the statutory baseline.
408

While baseline parameters may be estimated from data on

gasoline shipment or production information, baseline volume is

that volume of gasoline which actually left the refinery in 1990. 

While this may be more than was produced in 1990 due to shipments

made from inventory, fuel parameters are not likely to differ

much from 1990 production. Additionally, the volume of gasoline

which was shipped is what actually contributed to emissions. 

Likewise, gasoline exported in 1990 is not included in the

baseline determination since that gasoline did not contribute to

motor vehicle emissions in this country. The baseline of an

entity which produced only gasoline blendstocks in 1990 (and did

not produce gasoline) will be the anti-dumping statutory baseline

if in the future such an entity produces gasoline. 

b. Requirements for Purchasers of Gasoline and/or Gasoline

Blendstocks

Per the April 16, 1992 proposal, EPA is requiring that the

individual baseline of a refiner who exclusively purchases

blendstocks and/or gasoline and mixes these purchased components

to form another gasoline be determined using Method 1-type data. 

Refiners engaged in this type of refinery operation are commonly

called "blenders" or "terminal operators". If a blender does not

have data on every batch of 1990 gasoline for each of the

required parameters, its baseline will be the anti-dumping

statutory baseline. 

EPA also proposed this requirement in the July 9, 1991

proposal, at which time it discussed its reasoning behind

allowing blenders to only use Method 1-type data. Method 2 or 3-

type data, i.e., data based on 1990 or post-1990 blendstocks,

would not be appropriate for determining the quality of gasoline

produced at a blending facility in 1990, since blendstocks can

vary from week to week in both proportion, type and composition.

Thus, it is not feasible to determine the quality of a blender's

1990 gasoline by analyzing post-1990 changes in refinery

operations. To allow such data would create an incentive for

blenders to discover or develop 1990 and post-1990 data on

selected blendstocks that would yield relatively high baseline

emissions. Confirming the accuracy of this data would be very

difficult. Therefore, use of any data other than that on 1990 

gasoline composition would not yield a confident estimate of the

quality and emissions of the blender's 1990 production. 

Some commenters suggested that blenders be allowed the same

opportunities as refiners to use 1990 and post-1990 gasoline and

blendstock data. Otherwise, they claimed, a blender may have to

"reformulate" its conventional gasoline, and would thus be

penalized for not measuring a fuel parameter that was not

required to be measured in 1990. As stated, EPA does not believe

that use of blendstock data or post-1990 gasoline or blendstock
409

data would allow an accurate portrayal of a blender's 1990

production.

One commenter suggested that blenders with insufficient 1990

data, or those not in business in 1990, should have a more

stringent baseline than the statutory baseline because they would

have an advantage over half of the U.S. refiners (i.e., those

cleaner than the statutory baseline). The Act requires EPA to

set the statutory baseline as the individual baseline for those

with insufficient data from which to develop an individual

baseline. The Act does not require any entity to default to a

more stringent baseline than either their individual baseline or

the statutory baseline, depending on data sufficiency, as

determined by EPA. Since there is neither a clear advantage nor

disadvantage for use of the statutory baseline by blenders (and

no additional supporting data was provided by the commenter to

support its claim) it is not appropriate to impose additional

requirements or a more stringent baseline on blenders.

EPA is not requiring a blender who blended only gasoline and

oxygenates in 1990 and who will continue to only blend gasolines

and oxygenates in the future (post-1994) to establish a baseline,

although it may. No environmental harm is expected because the

gasoline will already have been accounted for in the refiner's

baseline and compliance calculations. Additionally, the CO and

VOC reductions from oxygenate use should more than offset any NOx

increases due to oxygenate. 

Finally, because of the blendstock accounting requirements

specified in §80.101, refiners as described in this paragraph are

required to determine a baseline API gravity (which can be

converted to specific gravity), if using Method 1-type data to

determine an individual baseline. Because API gravity is

routinely determined for gasoline, and thus should exist if other

Method 1-type data exists, this requirement, although not

proposed, does not impose significant additional burden on such

refiners. 

c. Requirements for Importers of Gasoline and Gasoline

Blendstocks

In the July 9, 1991 proposal, EPA proposed to allow persons

importing refinery-finished gasoline to establish a baseline

using Method 1, 2 or 3-type data. As proposed, the foreign

refineries in which the gasoline was produced would have to

establish a baseline in the same way as domestic refineries. EPA

also proposed that the importer could only use Method 1-type data

if the gasoline was not refinery-finished, i.e., if it was

blended outside of a foreign refinery. If lacking sufficient

Method 1-type data, the importer would use the statutory baseline

as its individual baseline. 
410

In the April 16, 1992 proposal, EPA proposed to allow

importers to develop a baseline using only Method 1-type data, or

lacking sufficient Method 1-type data, utilize the statutory

baseline. EPA also proposed to allow importers which were also

foreign refiners, and which imported at least 75 percent of the

1990 gasoline production of its foreign refinery into the U.S. in

1990, to develop a baseline for the refinery in the same way as

domestic refiners. 

Although this differed from the earlier 1991 proposal, EPA

stated that it believed that artificially high baseline emissions

could result if importers were generally allowed to use Methods 2

and 3-type data given the inability to track the 1990 gasoline

imports of most importers. EPA also stated that to allow

importers to develop high baseline emissions without the data

required by Method 1 would encourage gaming, e.g., high-emissions

producing gasoline could leave the U.S. (from a refiner with a

relatively low baseline) and come back in via an importer with a

high baseline. This clearly would be dumping, and would be

environmentally and competitively detrimental. 

EPA also stated that it did not believe that, in general,

importers, particularly those who are not refiners, would have

adequate 1990 data on their imported gasoline from which to

establish an individual baseline. If importers were allowed to

establish individual baselines based on 1991/2 data, these

baselines could be relatively high since there would be no way to

1) prevent the importer from choosing high emission gasoline to

import in 1991/2 simply to get an advantageous baseline, and 2)

insure the 1991/2 gasoline was the same as 1990 gasoline

imported. Additionally, EPA stated that use of a baseline

auditor to verify an importer's baseline would likely be

ineffective unless the importer was also a refiner which met the

75 percent criteria. 

Most commenters agreed with EPA's proposal. Some felt,

however, that the "75 percent" criteria was self-selecting--only

those importer/refiners with higher baseline emissions relative

to the statutory baseline would choose to develop an individual

baseline using Methods 1, 2 and/or 3. Those importer/refiners

with relatively low baseline emissions would use the statutory

baseline. Use of the statutory baseline could lead to dumping

since they would be complying with a baseline which was less

stringent than one based on their own 1990 gasoline quality. EPA

agrees that "dumping" could occur, but expects it to be minimal

since few foreign refineries are likely to meet the "75 percent"

criterion. However, requiring those that meet the "75 percent"

criterion to develop a baseline using Method 1-, 2- and 3-type

data is consistent with the requirements for domestic refiners,

which clearly meet the criterion (i.e., in most, if not all

cases, more than 75 percent of domestic refineries' 1990 gasoline

was utilized in the U.S. in 1990). 
411

One commenter claimed that location, not percent of

production imported, dictates enforceability. Enforcement of a

non-domestic refinery is governed less by location and more by

the willingness of the company and/or country to open its

refinery for compliance visitations. Again, not many refineries

are expected to meet the 75 percent criteria, and ones that

choose to use it to establish a baseline are likely to be

receptive to required visitations. Another commenter

specifically stated that Canadian refineries should be treated

the same as domestic refineries for the purpose of establishing

baselines. As stated, EPA believes that it will be relatively

easy to accurately determine the quality of the gasoline produced

in 1990 for sale in the U.S. at a refinery outside of the U.S. if

a significant amount of the production of the refinery came to

the U.S. Independent of where the refinery is located, if less

than this amount was imported, it will be more difficult to

combine information on refinery operations and blendstock and

gasoline data (i.e., Methods 2 and 3-type data) and allocate such

information so as to establish the quality of the refinery's 1990

gasoline which was sent to the U.S. In any case, 1990 blendstock

data or post-1990 blendstock or gasoline data will not provide a

reasonable basis for estimating the qualities of gasoline

imported into the U.S. in 1990.

Others felt that an importer should be allowed to use all

available data to establish a baseline and have its baseline

verified by an auditor. However, as stated, EPA believes that

significant dumping could occur if all available data is allowed. 

One commenter suggested that importers with insufficient 1990

data, or those not in business in 1990, should have a more

stringent baseline than the statutory baseline because they would

have an advantage over half of the U.S. refiners (those cleaner

than the statutory baseline). As discussed previously for

blenders, however, the Act does not require those with

insufficient data to default to a more stringent baseline. 

Another commenter stated that the statutory baseline composition

did not represent the quality of imported gasoline, and suggested

that importers should get a statutory baseline that better

represented the quality of such gasoline. Again, Congress has

already established the statutory baseline that is applicable

when an importer has insufficient data on the gasoline it

imported into the U.S. in 1990. While EPA has discretion in

determining the terms of the wintertime gasoline for purposes of

the statutory baseline, EPA is directed to establish the

specifications of "1990 industry average gasoline", and not some

subset of the industry average. 

EPA is retaining the requirements for importers essentially

as proposed on April 16, 1992. Thus an importer who imported

gasoline into the U.S. in 1990 shall have its individual baseline

determined using Method 1-type data. If the importer does not

have data for every batch of 1990 gasoline imported, for each of
412

the required fuel parameters, it shall have the anti-dumping

statutory baseline as its individual baseline. Additionally, An

importer who did not import gasoline (e.g., an importer which

imported gasoline blendstocks or which did not import anything)

into the U.S. in 1990 but who does so after 1994, shall have the

anti-dumping statutory baseline as its individual baseline. 

Finally, an importer which is also a refiner that imported more

than 75 percent of the 1990 gasoline production of a refinery

into the U.S. in 1990, must determine a baseline for that

refinery in the same manner as domestic refiners, i.e., using 

Method 1-, 2- and or 3-type data. 

2. Types of Data

Compliance under section 211(k)(8) of the Act is measured

against the individual baseline of each refiner. As specified in

today's rulemaking, the baseline consists of the estimated 1990 

emissions and/or appropriate fuel parameters and volumes of each

refiner. Additionally, the Act states that if no adequate or

reliable data exist regarding the gasoline sold by a refiner in

1990, the refiner must use the statutory baseline gasoline fuel

parameters as its baseline fuel parameters. 

After consulting with refiners, EPA believes that there

likely will be insufficient directly measured 1990 fuel parameter

data available, even in the case of some of the largest refiners,

from which to determine individual baseline values for each of

the required fuel parameters. At the same time, EPA is concerned

about the use of the statutory baseline parameters by those

without individual baseline data, as discussed earlier in

paragraph 1.a. For these reasons, refiners are required to

estimate the quality of their 1990 gasoline based on actual 1990

and post-1990 refinery data.

In the proposals, three methods (Methods 1, 2 and 3) were

described for refiners to use to determine their baseline

parameter values. The methods differed in the type of data used

in each. In the proposals, a parameter value was to be

determined solely by a single method. For example, if not enough

Method 1 data existed to determine a baseline aromatics value,

the baseline aromatics value would be determined using Method 2,

if enough Method 2 data existed. However, requiring each

parameter to be determined only using one method could result in

some of the available data not being utilized. In the above

example, the Method 1 data that did exist would not be used in

the baseline aromatics determination. However, since Method 1-

type data is based on 1990 gasoline, it is the best, most

accurate data for determining a baseline value, and should be

used to the fullest extent possible. Thus in order to improve

the use of available data so as to develop an accurate and

representative 1990 baseline, EPA is allowing baseline parameter

values to be determined using a combination of the methods, or
413

data types, if necessary. The three data types (corresponding to

the three proposed methods) are described below. 

EPA considers the data required for any of the methods to be

adequate and reliable for the purposes of determining baselines, 

The available data must be used in a hierarchical manner,

however, in that available Method 1-type data must be used first,

followed by available Method 2-type data, etc. In other words,

if insufficient Method 1-type data exists from which to determine

a given parameter, Method 2 type data should be used to

supplement any available Method 1-type data. If insufficient

Method 2-type data exists, Method 3-type data should be used to

supplement any available Method 1 or 2-type data. In this way,

the best available data is utilized. The data used in each

method should support the data and results in the other methods. 

For instance, the sum of the gasoline blendstock volumes

determined or used in Methods 2 and 3 should closely approximate

the total gasoline production as determined in Method 1. 

a. Method 1

Method 1-type data consists of a refiner's records of 1990

batches, or shipments if not batch-blended, of gasoline. 

Specifically, the measured fuel parameter value and volume of

batches or shipments of gasoline produced or shipped but not

exported are included in the baseline determination, as long as

no data is double-counted. The distinction between a refinery's

1990 production of gasoline and its 1990 shipments of gasoline

was not discussed in the proposals. However, because it is

likely that there were differences between 1990 production and

1990 shipments (e.g., due to shipping from inventory) available

data on gasoline produced or shipped in 1990 must be used in the

baseline determination (although, as stated, double-counting of

data must be avoided). The phrase "batches, or shipments if not

batch blended" is a slight modification of the proposal language

which included only the word "shipments". Commenters stated that

many shipments can be made from a single batch, and that sampling

the batch and shipments from that batch would result in doublecounting the contribution of that batch in the determination of a

fuel parameter value. In order to avoid such double-counting,

EPA modified the language as shown.

Method 1-type data is the most reliable data available for

determining baseline parameter values, as it is actual 1990

gasoline data. However, only those parameters which are subject

to pipeline specifications and which are relevant to the

reformulated gasoline program, e.g., RVP and distillation

properties, are likely to be determinable using Method 1-type

data. Even if parameters were subject to pipeline

specifications, in some cases the specification was only a

threshold value. For instance, one pipeline specification

requires gasoline to have no more than 5 volume percent benzene. 
414

Refiners did not likely test for the actual benzene content,

other than to determine or estimate that it was less than 5

volume percent. Meeting such a threshold specification would not

provide enough data from which to determine a baseline parameter

value. Most refiners did not measure the other fuel parameters

of interest (to the reformulated gasoline program) which are not

pipeline specifications, because there were no such requirements.

Although not specified in the proposals, EPA is requiring

that gasoline blendstocks which become gasoline solely upon the

addition of a specific type and amount of oxygenate be included

in the baseline determination. Additionally, unless evidence is

provided which indicates that such blendstocks were blended with

less than 10 percent ethanol or nonethanol oxygenates, or were

not further modified downstream, the refiner shall assume that

said blendstocks were blended with ten (10.0) volume percent

ethanol. This requirement provides some assurance that baseline

emissions are not artificially low due to selective inclusion or

exclusion of such blendstock. Requiring that the blendstock be

assumed to have been blended with ethanol (unless otherwise

shown) will result in a more stringent baseline than if it were

assumed blended with a (lower volume of a) different oxygenate,

or even not further modified. Hence, the burden of proof of

actual disposition of such product is on the refiner.

Additionally, gasoline entering a refinery by purchase or

transfer, including intracompany transfers, and which leaves the

refinery unchanged from its arrival state, shall not be included

in the receiving refinery's baseline, since it will have already

been accounted for in the baseline of the original producer.

b. Method 2

Method 2-type data consists of a refiner's 1990 gasoline

blendstock composition data and 1990 production records. Because

it consists of 1990 data, Method 2-type data is also expected to

be very reliable and useful in accurately estimating 1990

baseline parameter values. Only data on those blendstocks used

in the production of gasoline within the refinery are used in the

baseline determination. Most of the blendstocks used in a

refiner's gasoline are produced in the refinery, however, some

are purchased or otherwise transferred from outside of the

refinery. All data on any blendstock used in the refinery's

gasoline, whether produced inside or purchased outside of the

refinery, is to be used in the baseline determination. 

The average fuel parameter value of each gasoline blendstock

is determined from the measured fuel parameter values and

associated volumes of each type of blendstock. The associated

volume is the volume of a batch of blendstock, or, for a

continuous process, it is the volume proportional to the amount

of the blendstock blended into gasoline in that month. 
415

Some commenters suggested that accounting for blendstocks

which do not contribute to toxics emissions makes no sense. 

However, the quality of all blendstocks used in 1990 gasoline

contributes to a refiner's baseline toxic emissions

determination, and some blendstocks tend to increase toxics while

other blendstocks decrease toxics. Another commenter suggested

that blendstocks sold for off-site blending be included in the

baseline. Such blendstocks are not included in a baseline

determination--only those blendstocks which contributed to a

refiner's 1990 gasoline production are included. Some commenters

suggested that only streams that constituted a minimum fraction

of the gasoline, say 2 or 5 percent, be required to be included. 

However, the quality of even small volume streams could

significantly affect baseline parameter and associated emissions,

and thus must be included.

c. Method 3

Method 3-type data consists of a refiner's post-1990

blendstock composition data and 1990 production records. As will

be discussed, in some cases post-1990 gasoline data may also be

used in the determination of baseline fuel parameter values. As

for Method 2-type data, when blendstock data is used, only

blendstocks used in the production of gasoline within the

refinery are evaluated for baseline purposes, whether the

blendstocks were produced in the refinery or purchased or

transferred from an outside source. The average fuel parameter

value of each gasoline blendstock is determined from the measured

post-1990 fuel parameter values and associated volumes of that 

blendstock. The average post-1990 fuel parameter value and the

total 1990 volume of each type of blendstock are then used in the

estimation of the baseline value of the parameter. 

In order to ensure that the fuel parameter values obtained

with Method 3-type data adequately represent the 1990 values of

those parameters, the refiner must provide a detailed

documentation and comparison of its 1990 and post-1990 refinery

operations, especially in areas which affect the fuel

parameter(s) being determined from Method 3-type data. 

Circumstances which would cause its post-1990 gasoline to differ

from its 1990 gasoline must be accounted for in determining a

fuel parameter using Method 3-type data. For instance, if post1991 data is used, appropriate adjustments must be made for the

refinery operational changes that occurred due to the 1992

volatility rules and the oxygenated fuels program, two situations

which could cause post-1990 operations to differ from 1990

operations. The refiner must adjust its post-1990 data to

account for such situations, perhaps using refinery modeling. In

effect, the refiner is "backing out" its 1990 parameter values

from its post-1990 data. The required documentation will assist

the baseline auditor in its verification and EPA in its review of

the refiner's baseline submission. 
416

In the case where a blendstock was used in a refiner's 1990

gasoline but is no longer used, the adjustments made to account

for 1990 and post-1990 operational differences will allow

determination of that blendstock's composition. In the case

where a blendstock was not used in a refiner's 1990 gasoline, but

is used now, no data on that blendstock is included in the

baseline determination.

EPA received many comments stating that the use of post-1990

gasoline data was more accurate than using post-1990 blendstock

data for a Method 3-based determination. In this regard, some

commenters suggested letting the baseline auditor verify that

differences between 1990 and post-1990 operations were accounted

for and that post-1990 gasoline represented 1990 gasoline. In

April 1992, EPA proposed that post-1990 gasoline data could be

used if each blendstock in post-1990 gasoline was within 10

percent of the volumetric fraction of that blendstock in 1990

gasoline. One commenter said the blendstock fractional

requirements were arbitrary, and that there should be no such

requirements--the auditor would verify the similarity between

1990 and post-1990 gasoline composition. Another commenter

suggested that 10 percent was still too narrow, and that the

criterion should be 50 percent, or 10 percent if blendstock

fractions were determined relative to the volume of the total

blend, not of only the blendstock. Additionally, some commenters

cited the lower cost of collecting and analyzing gasoline rather

than blendstock data as a reason for allowing post-1990 gasoline

data to be used in the baseline determination.

EPA is allowing post-1990 gasoline data to be used to

estimate 1990 baseline parameters, subject to certain

requirements. In addition to requiring the same detailed

documentation of 1990 and post-1990 operations as required when

using post-1990 blendstock data, the volumetric fraction of each

blendstock in post-1990 gasoline must be within plus or minus ten

(10.0) percent of the volumetric fraction of the same blendstock

in 1990 gasoline or be within plus or minus two (2.0) percent on

an absolute basis relative to the 1990 value. 

Under the first criterion, for example, if a refiner's 1990 

gasoline contained 30 volume percent reformate, post-1990

gasoline data may be used (provided all other parameter values

also conformed to these requirements) as long as it contained

27.0-33.0 volume percent reformate, i.e., +/- 10 percent. Under

the second criterion, for example, if a refiner's 1990 gasoline

contained 3.0 volume percent dimate, post-1990 gasoline may be

used (provided all other parameter values also conformed to these

requirements) as long as it contained 1.0-5.0 volume percent

dimate, i.e., +/- 2.0 percent on an absolute basis. 

These two criteria are expected to cover typical year-toyear blendstock volumetric fraction fluctuations. Larger
417

differences would indicate more significant refinery operational

changes. Post-1990 gasoline data for which a single 1990

blendstock does not meet either of the blendstock fraction

requirements cannot be used in the baseline determination. 

However, EPA also received comment that many refiners would not

be able to use post-1990 gasoline data, even with the expanded

criteria, simply due to butane utilization changes from 1990. 

Because butane, and thus RVP, were reduced after 1990 due to

volatility controls, and because RVP reductions reduce emissions,

EPA is exempting butane from the blendstock requirements for

using post-1990 gasoline.

If post-1990 gasoline data does not meet the blendstock

fraction requirements described above, it will be difficult for a

refiner to show similarity or account for differences between

1990 and post-1990 operations without looking into post-1990

operations at the blendstock level, thus making any gasoline data

moot. Although the criteria specified for being allowed to use

post-1990 gasoline data may disadvantage some refiners which have

collected post-1990 gasoline data but not blendstock data (and

thus require them to collect additional data after the final

rule), EPA has indicated throughout its proposals that Method 3 

was primarily based on blendstock data, with gasoline data

allowed as the exception.

Finally, as for Method 1-type data (i.e., gasoline data),

EPA is requiring that post-1990 gasoline blendstocks which could

become gasoline solely upon the addition of a specific type and

amount of oxygenate be included in the baseline determination, to

provide some assurance that baseline emissions are not

artificially low due to selective inclusion or exclusion of such

blendstocks. 

While the data for Method 1 is obviously more reliable than

that required for Method 3, the Agency considers reliance on the

data for Method 3 appropriate because it 1) provides a fair

approximation of 1990 gasoline, and 2) provides an additional

means for determining baseline parameters, thus not requiring the

statutory baseline for refiners with insufficient 1990 data for

Method 1. As discussed, use of the statutory baseline for

refiners should be avoided because of potential and likely

negative environmental and competitive effects. 

d. E200 and E300

Although not previously included among the fuel parameters

for which baseline values are required to be determined, EPA is

now requiring that baseline values be determined for the fuel

parameters E200 and E300, the percent evaporated at 200°F and

300°F, respectively. Although these two fuel parameters replace

T50 and T90, respectively, in the complex model, baseline values
 124 As discussed in Section IV, when the complex model is

used to determine emissions, winter RVP is held at 8.7 psi

because there are no RVP effects on winter emissions.

418

of T90 are still required to be determined if producing

reformulated gasoline or using the simple model. 

EPA expects E200 and E300 values to be determined directly

from gasoline or blendstock data, even if distillation

information has to be regraphed. If such a determination is not

possible, and can be proven, E200 and E300 values may be

estimated from otherwise acceptable T50 and T90 data using the

following equations: 

E200 = 147.91 - (0.49 x T50)

E300 = 155.47 - (0.22 x T90)

e. Anti-Dumping Statutory Baseline and Emissions 

As mentioned earlier, in some cases a blender or importer

may not be able, or be allowed, to develop an individual baseline

from its own data. In that case, the blender or importer would

have the statutory baseline as its individual baseline. Although

the compliance period for conventional gasoline is annual (as

discussed in the proposals and in §80.101 of this rulemaking),

emissions determined using the complex models are determined on a

summer and winter basis. Thus, separate anti-dumping summer and

winter baseline fuel parameter values are required. For those

without unique individual baselines, these values are the

statutory summer baseline specified in the Act, and the winter

baseline determined by EPA as required by the Act (and as

specified in Section II of this document)124. 

Because of the blendstock accounting requirements specified

in §80.101, a baseline statutory value API gravity (which can be

converted to specific gravity) is also required. As indicated in

section 211(k)(10) of the Act, the summer value is 57.4 °API. 

The corresponding winter value determined by EPA is 60.2 °API.

Because separate summer and winter baseline fuel parameter

values are required, the single set of fuel parameters specified

in the proposals as the anti-dumping statutory baseline is

basically moot with regard to the final rule, except for annual

average values of sulfur, olefins and T90. However, for

clarification and completeness, it is discussed here. Few

substantive comments were received concerning the proposed annual

average statutory baseline (which is a weighted average of the

summer and winter statutory values), and none led to a change in

the proposed fuel parameter values. However, the baseline listed
 125 The RVP that results from combining the CAA statutory

baseline RVP of 8.7 psi and the wintertime statutory baseline

RVP (determined by EPA) of 11.5 psi is 10.4 psi. However, as

discussed above, an RVP of 8.7 is used in the winter complex

models. Hence, the annual average RVP shown here is 8.7 psi.

419

in the February 1993 proposal reflected a nonhigh ozone season of

September 16-March 31 (and thus a high ozone season of April 1-

September 15). The current high ozone season (upstream from

retail outlets) is May 1-September 15. The proposed anti-dumping

statutory baseline has been modified to reflect the change in

fuel parameter values and fuel consumption due to the change in

the length of the high ozone season, and is shown below. 

Benzene, volume percent 1.60

Aromatics, volume percent 28.6

Olefins, volume percent 10.8

RVP, psi 8.7125

T50, degrees F 207

T90, degrees F 332

E200, percent 46.5

E300, percent 82.4

Sulfur, ppm 338

API Gravity 59.1

Finally, the annual average anti-dumping baseline emissions

are shown below. These emissions were determined by evaluating

the summer and winter statutory baseline fuel parameters in the

appropriate summer or winter model or equation, and then

determining annual average emissions by weighting the summer and

winter emissions by the fuel consumption fractions in the high

ozone and nonhigh ozone seasons, 39.6% and 60.4%, respectively. 

As stated, annual average sulfur, olefins and T90 are shown

above.

Phase I

Phase II

Exhaust Benzene--Simple Model 6.45

------

Exhaust Benzene--Complex Model(mg/mile) 33.03 

------ 

Exhaust Toxics (mg/mile) 50.67

 104.5

NOx (mg/mile) 714.4

 1461.

3. Data Collection and Testing Requirements

a. Sampling Requirements
420

In the April 16, 1992 proposal, EPA briefly discussed

sampling requirements for obtaining data from which to

determine baselines. In the February 26, 1993 proposal, EPA

discussed additional requirements and changes to the

requirements previously discussed. The primary reasons for

specifying sampling requirements is to ensure that enough

gasoline or blendstock samples were taken from which to develop

a representative baseline, and to minimize the picking and

choosing of data.

In the April 16, 1992 proposal, EPA stated that sufficient

sampling must be done, implying that the responsibility for

sampling was left to the refiner, but would have to be verified

by the auditor, and of course, ultimately accepted by EPA. In

the February 26, 1993 proposal, EPA specified specific minimums

in order to ensure acquisition of adequate and representative

data. Many commenters commented that they had sampled based on

the earlier proposal requirements for sufficient sampling, and

that EPA's later proposal could void data collected, and the

time and money spent. EPA still believes it is the better

course to specify minimum sampling requirements, and thus is

specifying that for Method 1 and Method 3 gasoline data, at

least half of the batches (by number of batches, not volume),

or shipments if not batch blended, in a calendar month shall

have been tested for a particular parameter. For Method 2 and

Method 3 blendstock data, at least weekly sampling of

continuous blendstock streams and, if blendstocks are produced

on a batch basis, sampling of at least half of the batches of

each blendstock produced in a month is required.

However, EPA believes that at least some of the sampling

performed in response to the April 1992 proposal may well be

adequate. To void such sampling would be an unnecessary waste

of resources if in fact it is adequate and representative of

the gasoline or blendstock produced or imported over a certain

period of time. To avoid this result, EPA will also accept

less than the minimum data if the refiner can explain why the

data is less than the minimum requirements and why it is

sufficient in quantity and quality to use in the baseline

determination. Although less than the minimum data required

may be used, all available samples must be analyzed and the

results used in baseline determination if more than the minimum

number of samples are available. In addition, the auditor must

verify all of the above information and conclude that the

sampling is sufficient in quantity and quality to use in

baseline determination. 

Since 1990 data is the best data from which to calculate

baseline fuel parameter values, it makes sense that data

collected closer to 1990 is more easily adjusted to estimate

1990 values than data collected later. Thus to prevent using
 126 Certain data may be excluded from the baseline

determination, if it can be shown that the sample was

mislabeled or incorrectly analyzed or if the results are

significantly different than would be expected based on

operating conditions, etc. Such data must be reported, and the

auditor must verify the reasoning in support of such an

exclusion.

421

more data than is necessary in the baseline calculation

(because excessive data may skew the results or allow gaming),

only data collected through the end of the calendar year in

which the minimum data requirements are met are allowed to be

used in the calculation of a given baseline parameter. 

However, data collection may also cease when the minimum

requirements are met. In any case, all data collected through

the time data ceased to be collected for baseline development

purposes must be included in the baseline determination. 

Picking and choosing of data should thus be minimized even if

less than the minimum data is utilized because all data

collected must be included in the baseline determination126.

At least three months of summer and three months of winter

data must be available for the determination of a parameter

value. Summer months include any month in which any volume of

gasoline was produced to meet the federal summer volatility

requirements. Winter is any month which could not be

considered a summer month. Thus transition months may be used

to satisfy the three months of summer data requirement. This

requirement will insure that the average parameter values

calculated by the above methods will adequately represent a

refiner's 1990 gasoline quality and composition, including

representative summer and winter data. One commenter suggested

that if annual data were available, fuel parameters should be

allowed to be calculated on an annual basis instead of

requiring separate summer/winter determinations. EPA will

accept annual data, however, because annual average baseline

emissions are determined on a seasonal basis first, separate

summer and winter average baseline fuel parameter values must

be determined from the annual data. Some commenters suggested

that EPA accept less than three months of summer and winter

data if it could be shown that the composition of a blendstock

stream did not change seasonally. Although in certain cases

this may be true, it is more efficient to require all refiners

to meet the minimum requirements than to ascertain whether the

quality of a few streams of a few refiners did not change

seasonally. In certain instances where a refiner markets its

product only in an area or areas which experience no seasonal

changes relative to gasoline requirements, e.g., Hawaii, only

three months of data are required.
422

b. Post-Final Rule Data Collection

Many refiners began collecting data to be used in the

baseline determination soon after the proposals were published. 

They were of course taking a risk that significant changes

could occur between the proposals and the final rule. 

Nonetheless, many have estimated their baseline parameter and

emissions values, and are working with potential auditors to

verify those determinations. However, some refiners began

collecting data late, were waiting for the final rule or just

recently realized that they need additional data. These

refiners are being allowed extra time to complete and submit

their baselines, however proof must be given that additional

data was needed and indeed was collected after today. The

requirement to collect at least three months of data on a

refiner's winter gasoline and at least three months of data on

a refiner's summer gasoline must still be met.

c. Negligible Parameter Values

In February 1993, EPA proposed that if a refiner can show,

and the auditor verify, that a refinery stream contains

negligible amounts of one or more of certain fuel properties

for which a baseline value must be determined, testing of that

stream for the fuel property(ies) is not necessary. The fuel

properties discussed were aromatics, benzene, olefins,

saturates and sulfur. Saturates are now excluded since a

baseline saturates value is not required to be determined. 

Oxygen was not included in the proposal. It is, however,

reasonable to include it because it is a required baseline

parameter, and is likely to exist in negligible amounts in many

blendstock streams. Although each fuel component uniquely

affects emissions, the effect of assuming a zero value,

relative to "negligible" threshold values, is not expected to

significantly affect emissions.

The proposed minimum values for a fuel component to be

negligible in a stream were 1.0 volume percent for benzene,

aromatics, olefins and saturates, and 10 ppm for sulfur. The

final minimum values are shown below. 

Aromatics 1.0 volume percent

Benzene 0.15 volume percent

Olefins 1.0 volume percent

Oxygen 0.2 weight percent

Sulfur 30.0 ppm

Although not explicitly stated in the proposals, this

provision applies to blendstock streams on an average basis. 

Thus fuel parameters deemed negligible for a given blendstock

stream are expected, on average, not to exist in the stream at
423

greater than the appropriate minimum. These final values

differ from those proposed based on commenter suggestions that

more appropriate negligible values should be approximately 10

percent of the expected value of the fuel parameter. EPA

agreed with this for all of the parameters except for

aromatics, and modified the "negligible" threshold values for

these parameters. The "10 percent" level for aromatics would

be about 2.8 volume percent. Since some large streams have

aromatic contents of approximately this magnitude, it would not

be appropriate to credit a large stream with a zero value, even

though this would result in a more stringent baseline. Thus

the negligible aromatics threshold is unchanged from the

proposal. 

As stated, a negligible oxygen threshold was not originally

proposed, and in fact, there is no statutory baseline oxygen

value from which to estimate a 10 percent value. Most nonoxygenate refinery streams contain little or no oxygen. 

Although accounting for small quantities of oxygen would reduce

baseline emissions, resulting in a more stringent baseline, the

minor environmental effects of having a slightly less stringent

baseline must be balanced against the costs of testing for such

small quantities. Thus a de minimis level of 0.2 weight

percent was set as the negligible oxygen threshold. 

Any properties shown to exist in a refinery stream in

negligible amounts shall be assigned a value of 0.0. One

commenter suggested accepting benzene, sulfur, olefins and

aromatics estimates of zero (for certain identified streams)

since any error would result in lower baseline emissions. 

However, the fuel component values of a given stream do not

necessarily uniformly meet the negligible threshold values

described above. Hence EPA is requiring each refiner to

determine individually for which streams certain fuel

components exist, on average, in negligible amounts. 

d. Sample Compositing

There have been no major changes in this provision from the

proposals. Thus, samples that have been retained but not yet

analyzed may be mixed together in volumes proportional to the

volume of the batch, or shipment if not batch-blended, from

which the sample was taken and the mixture analyzed for the

required fuel parameters. Blendstock samples obtained from

continuous processes over a calendar month may be mixed

together in equal volumes to form one blendstock sample (e.g.,

all samples of reformate taken in a calendar month may be

mixed) and the sample analyzed for the required fuel

parameters. Based on comments received, some of the details of

the compositing procedure have changed. Specifically,

comparison, and adjustment, if necessary, of sample RVP is
424

required, so as to avoid misrepresentation of a sample which

may have lost volatile components. Additionally, certain

compositing requirements were changed to better reflect

refinery conditions. 

e. Test Methods

Many commenters were concerned that the test methods they

had used to analyze samples would be invalid because they were

not the same as the required test methods being promulgated

today for reformulated gasoline. EPA had proposed, on April

16, 1992, that sampling and measurement techniques used to

determine baseline parameters must yield results which are

equivalent to the results obtained per the techniques and

methodologies specified for the reformulated gasoline program. 

However, because of constantly evolving test methods, in

addition to the fact that the final regulations concerning

reformulated gasoline test methods will only be known today, it

would be inappropriate to disallow data not determined using

the test methodologies required in the reformulated gasoline

program.

Nonetheless, EPA is concerned that the test methods used be

adequate. In a modification of the proposal, EPA will accept

data determined using methods other than those required under

the reformulated gasoline program, upon petition and approval,

as long as the methodology or technique was a standard

industry-accepted measurement technique at the time the

measurement was taken. The baseline auditor will verify that

the techniques used to determine the baseline data meet either

of the requirements discussed above. 

It is possible that the industry-accepted methods in place

at the time will yield results which are less accurate than

more recent test methods or test methods required beginning in

1995. EPA recognizes this fact, however, it would not be

appropriate to waste the resources expended by not accepting

data determined under earlier, industry-standard methods. 

Also, no significant environmental deterioration, if any, is

expected by accepting such data because development of new test

methods inherently involves consideration of previous test

methods, hence any differences should be minimal. No

allowances will be made, however, for different analytical

methods utilized in the baseline and compliance calculations. 

It is reasonable not to adjust baseline or compliance values

due to different measurement techniques because all refiners

should be affected in the same manner if industry standard test

methods were used to determine baseline parameter values. 

However, if data were determined under two test methods, EPA

may accept the data determined under the more accurate test

method, upon petition and approval.
425

Although not previously discussed, oxygen content may be

estimated using oxygenate purchase, sale and/or blending

records or analytically. However, the other fuel parameter

values of the oxygenate (e.g., the sulfur content of the

oxygenate) must be determined analytically, or be deemed

negligible, if allowed. All oxygen associated with allowable

gasoline oxygenates shall be included in the baseline oxygen

content if oxygen content is determined analytically. Oxygen

content shall be assumed to be contributed solely by the

oxygenate indicated on the blending records, etc., if oxygen

content is determined from such records.

4. Baseline Fuel Parameter Determination 

The methodology for calculating baseline fuel parameters,

and changes in the methodology from the proposals, is discussed

below. The equations and other details can be found at §80.91

in the regulations. 

a. Closely Integrated Gasoline Producing Facilities

Many refiners also operate gasoline blending facilities

and/or import gasoline and thus would be considered to have

multiple modes of operation, i.e., gasoline producing, blending

and importing are each considered to be a mode of operation. 

In the July 9, 1991 proposal, EPA proposed two options for

dealing with multiple modes of operation. Under the first

option, each mode would have its own baseline (be it a unique

baseline or the statutory baseline) and would comply with that

baseline. EPA stated that, under this option, post-1994

shifting of gasoline and blendstocks between the modes could

occur. Dumping could thus result if each mode were required to

comply with a separate baseline. Under the second option, the

baselines of each mode would be combined to form a single

baseline for compliance purposes. This option could reduce

dumping since all of a refiner's gasoline would contribute to

its baseline. However it could also provide a refiner

significant flexibility and possibly a competitive advantage

over those with more limited operations. 

In the April 16, 1992 proposal, EPA proposed having

individual baselines for each mode to minimize anti-competitive

effects. Integrated companies which have more than one mode of

operation would have more flexibility than smaller refineries

if allowed to have a single baseline for their entire

operation. Further review of this issue suggested that

separate baselines for each mode might instead reduce dumping

by not allowing significant quantities of "dirtier" than

average gasoline to be produced or imported, a change from the
426

view expressed in the July 9, 1991 proposal. Accounting and

compliance determinations would also be less complicated if

each mode of operation were subject to its own baseline.

In the February 26, 1993 proposal, EPA requested comment on

allowing closely integrated blending operations to be included

in the baseline determination of a refinery. For example, a

blending facility which receives most of its gasoline and

blendstocks from an associated refinery, and very little from

outside of the company, would be considered closely integrated. 

In such a situation, the concern about anticompetitive effects

is greatly reduced. EPA also stated that it does not expect

"closely integrated" to apply broadly to refiners who happen

also to have blending operations. In this proposal, EPA did

not propose a similar inclusion of operations for refiners with

import operations.

Many commenters supported allowing a single baseline for

multiple modes of operation. Some commenters suggested that

refiners with import operations also be allowed to develop a

single baseline covering their refining and importing

operations. One commenter suggested basing individual

baselines on whether marketing or producing gasoline occurred

at a facility. Requiring 60-75 percent of a blending

facility's blendstocks to have come from a single refinery was

suggested for defining a closely integrated refinery-terminal

relationship. If closely integrated, one commenter suggested

that the blending facility baseline be determined using Method

1-type data. 

For the reasons described above, EPA is not, in general,

allowing a single baseline for multiple modes of operation. 

However, EPA is allowing refiners with blending facilities

which are closely integrated to include a blending facility's

production (properties and volumes) in a single baseline. The

criteria for being "closely integrated" is that at least 75

percent of the blendstock received at the blending facility in

1990 came from the associated refinery. EPA believes that the

"closely integrated" criteria of 75 percent is reasonable

because oxygenates and butane, among others, are blended into

gasoline after the refinery. Based on the usual amounts (in

volume percent) of oxygenates and butanes frequently added

outside of the refinery, EPA estimated the "75 percent"

criteria. For instance, ethanol blended into gasoline in 1990

was likely blended at the 10 volume percent level. Thus only

90 percent of the gasoline was refinery-produced blendstock

(refinery meaning the associated refinery). While EPA could

have required 90 percent of a blending facility's blendstock to

have come from the associated refinery, in the case of ETBE, up

to 17 percent ETBE by volume could be added to gasoline. Thus

only 83 percent of the blending facility's gasoline would have
427

been (or will be) refinery-produced blendstock. If butane is

added in the winter, even less of the blending facility's

gasoline would have been refinery-produced. Using the rule of

thumb of 2 volume percent butane per psi increase,

approximately 6 volume percent butane would be required to

increase the RVP of summer gasoline from 9.0 psi to 12.0 psi, a

not uncommon winter fuel RVP. Thus, as little as 77 percent of

a blending facility's blendstock could be refinery produced. 

The 75 percent criterion insures that a significant portion of

a blending facility's blendstock comes from the associated

refinery, but allows it some leeway in obtaining blendstocks

from other sources. 

One or more blending facilities may be included in an

aggregate baseline (to be discussed in paragraph 5.c) if each

blending facility received at least 75 percent of its

blendstock from one or more of the refineries in the aggregated

baseline with which it is associated. For instance, the 75

percent criteria is satisfied if the terminal received 25

percent of its 1990 blendstock from refinery A and 50 percent

from refinery B. Alternatively, it may also have received the

entire 75 percent from either refinery A or B, refinery A and B

being part of an aggregate baseline. EPA believes it is

reasonable to allow this since the blending facility is still

dependent on receiving a significant portion of its blendstock

from within the company. 

Although not previously proposed, some comments were

received regarding other types of closely integrated facility

relationships. EPA is thus allowing a single individual

baseline to be determined for two or more refineries (or sets

of gasoline blendstock-producing units) which are

geographically near each other but are not within a single

refinery gate, and whose 1990 operations were significantly

interconnected. The burden is placed on the refiner to show

that its two facilities are "significantly interconnected". In

this case, the two facilities will have a single set of

baseline parameter values and associated emissions. 

Some commenters suggested that U.S. refiners with import

operations also be allowed to develop a single baseline

covering their refining and importing operations. EPA rejected

this suggestion because it would be difficult for EPA to track

a fuel's production location before the fuel is or was

imported, particularly when considering 1990 production. Also,

allowing such a situation would amount to trading between

foreign and domestic refineries, which was not mandated nor

intended by Congress. 

b. Seasonal Weighting
428

In the February 26, 1993 proposal, EPA proposed that a

refinery's own production volumes of 1990 summer and winter

gasoline (based on whether the fuel RVP met EPA 1990 summertime

volatility specifications) be used in the weighting of data on

a summer and winter basis. This change from the previous

proposal, in which EPA specified a summer/winter split,

received a lot of support. 

As discussed in paragraph 5.a, the 1990 annual baseline

volume is the larger of the gasoline volume produced in or

shipped from the refinery in 1990. Thus, a refinery's own

baseline volumes of summer and winter gasoline (either on a

produced or shipped basis) shall be used for weighting the

summer and winter anti-dumping emissions and sulfur, olefins

and T90 values. Summer volume consists of the volume of

gasoline produced to meet the 1990 Federal volatility

requirements. All other gasoline volume, including transition

volumes, is considered winter volume (i.e., fuel produced or

shipped during transitions from winter to summer is considered

winter data because it does meet the summer volatility

requirements). Because fuel production can lead fuel

consumption by up to 2 months, use of refinery-specific volumes

and time periods in the baseline determination will result in

more representative baselines. 

c. Grade Weighting

To minimize data-skewing due to inconsistent or special

sampling situations (for instance, a trial gasoline which was

heavily sampled compared to normal sampling), and to thus get a

more representative baseline, average fuel parameter values

shall be determined first for each grade of gasoline produced,

and the resulting values weighted by the fraction of each grade

sold in the period over which the value is determined. "Grade"

shall mean each traditional grade of gasoline produced in the

refinery in 1990, e.g., regular, midgrade, premium, not each

different integer octane number as proposed in February 1993. 

EPA changed this definition based on comments received stating

that requiring each octane number was onerous and impractical. 

d. Equations

The equations have been modified slightly from the February

1993 proposal to require that specific gravity be included in

the determination of baseline sulfur and oxygen contents. 

Because both of these fuel parameters are determined on a

weight basis, and because gasoline and blendstocks vary,

sometimes significantly, in weight-to-volume ratio, correct

accounting of such terms must include a weight-to-volume

conversion. 
 127 Certain conventional gasoline areas which are CO

nonattainment areas are required to contain oxygen during their

oxygenated fuel season. 

429

The equations have also been modified to reflect the

separate determination of summer and winter baseline fuel

parameter values.

e. Oxygen in the baseline

Congress mandated that reformulated gasoline contain

oxygen, but did not mandate a post-1994 conventional gasoline

oxygen content.127 In 1990, some refiners produced or utilized

significant amounts of oxygenated gasoline while others used

almost no oxygen in their gasoline. The Act requires that,

relative to 1990, increases in NOx emissions due to oxygenate

use be offset by reductions (on a mass basis) in VOC, CO and

toxics emissions.

The issue of how to treat oxygen content in the baseline

and for compliance purposes was not addressed in the negotiated

agreement nor in the July 9, 1991 proposal. However, the issue

was discussed in the April 16, 1992 proposal, and two viable

options for dealing with a refiner's baseline oxygen were

identified. Under the first option, only a positive difference

between the post-1994 annual average oxygen level and the

baseline oxygen level would be included in the compliance

calculation. If less oxygen were used in post-1994 gasoline

than in 1990, the individual baseline value would be used in

the compliance calculation, and there would be no penalty for

using less oxygen in post-1994 conventional gasoline than in

1990. If more oxygen were used in post-1994 conventional

gasoline than in 1990, credit would be given for the effect of

the excess oxygen on emissions. The second option excluded

oxygen in both the baseline and compliance determinations. 

Thus there would be no penalty for using less oxygen than in

1990 and no credit for using more oxygen (in conventional

gasoline) than in 1990. If no credit is given for oxygen usage

above base levels, there may be less processing flexibility

relative to conventional gasoline production. In that

proposal, EPA noted that Congress purposely did not include

oxygen content in the statutory definition of summertime

baseline fuel. EPA likewise did not include oxygen content in

its determination of the proposed statutory wintertime baseline

gasoline. 

Several commenters suggested that the baseline be

determined on a non-oxygenate basis so as not to penalize those

who "reformulated", i.e., produced cleaner gasoline, early. 

Others supported including only the positive difference between
430

1990 and post-1994 oxygenate use. Others suggested variations-

-excluding it in the baseline but including it in compliance;

excluding it from the baseline and normalizing the values of

the other parameters to account for the dilution effect of

oxygenate; and including it, as is, in both the baseline and

compliance calculations. Relative to other calculations, some

commenters suggested that oxygenate volume be excluded from

conventional gasoline volumes. Others argued that including

oxygenate used in conventional gasoline designated for areas

for CO reduction purposes would give credit in one program for

another mandated program, and that aromatics markets

distortions and increased toxics emissions and dumping could

result. 

The anti-dumping provisions of §211(k)(8) require a

comparison of 1990 and post-1994 emissions, based on 1990

gasoline quality and post-1994 gasoline quality, respectively. 

The quality of any gasoline includes its oxygen content, thus

including oxygen content in the baseline and compliance

calculations would be the most appropriate consideration of

oxygen content. EPA is therefore requiring baseline parameter

values to be determined on an oxygenated basis. However,

§211(k)(8)(C) of the Act also requires that increases in NOx

emissions, due to conventional gasoline oxygenate use, be

offset by reductions in the other three pollutants. As stated

earlier, significant VOC and CO reductions will occur even

without the reformulated gasoline rulemaking. To ensure that

an increase in NOx emissions is not associated with the use of

oxygen, EPA is allowing refiners to choose to use either an

oxygenated or nonoxygenated baseline when determining NOx

emissions. Compliance would be measured on the same basis. 

Under this provision, a refiner could choose to switch from a

nonoxygenated to an oxygenated baseline, beginning with the

next averaging period. While EPA is allowing refiners to

choose whether to use a nonoxygenated or an oxygenated baseline

when determining NOx emissions, the initial decision to use an

oxygenated baseline, or the switch from a nonoxygenated to an

oxygenated baseline is permanent. EPA is allowing only the

onetime change to minimize unnecessary administrative

complications due to every refiner potentially changing its

baseline NOx value annually. EPA expects a refiner to operate

its refinery to its advantage, and thus it is not likely to

make such decisions (of whether to use a nonoxygenated or an

oxygenated baseline for NOx purposes) lightly. Additionally,

Congress intended that the anti-dumping program compare a

refiner's 1990 emissions with its post-1994 emissions, based on

its fuels' actual average composition, i.e, its actual

oxygenated quality, and a change to this baseline for NOx

purposes should thus be permanent.
431

In determining the nonoxygenated parameter values from the

oxygenated values, only the physical dilution and distillation

effects of the oxygenate shall be considered. For instance, if

a refiner's actual (oxygenated) baseline aromatics were 30

volume percent and actual oxygenate use was 5 volume percent,

the nonoxygenated baseline aromatics value would be 31.6 volume

percent, or 30/(100%-5%). Adjustments to refinery operations

that would have been different had oxygenates not been used

(i.e., octane) shall not be included because many potential

adjustments are possible. In the above example, while it is

likely that reformer severity may have been higher had

oxygenates not been used (thus resulting in perhaps even a

higher aromatics baseline value) such operational effects due

to oxygenate use shall not be considered because they cannot be

known with certainty. 

A few commenters suggested that oxygenate volume be

excluded from conventional gasoline baseline volumes. EPA

disagrees--Congress specified that certain NOx emissions

increases be offset, but did not specify how to deal with

baseline volumes, leaving it to EPA's discretion. 

Additionally, the reason for allowing NOx emissions to be

evaluated on a nonoxygenate basis in the first place is so as

not to penalize refiners whose emissions increase due to

oxygenate use. It is possible that restricting baseline

volumes by excluding oxygenate volumes could penalize some

refiners. Thus, it would be inappropriate for EPA to restrict

the applicability of the individual baseline to the

nonoxygenated gasoline volume. The total gasoline volume

(including the volume of actual 1990 oxygenate use and the

volume of those oxygenates assumed or shown to have been

blended as discussed in paragraph 2.a) will thus be used to

determine the 1990 baseline volume, as well as for the volumes

to determine applicability of the individual baseline. 

f. Work-in-Progress

Work-in-progress (WIP) refers to one or more major capital

changes or commitment(s) made by a refiner prior to or in

1990, the baseline year for anti-dumping purposes. In those

cases, the gasoline produced in 1990 might significantly differ

from gasoline produced after the WIP was finished. However,

since the anti-dumping baseline is based on 1990 gasoline, a

refiner's compliance for post-1994 conventional gasoline would

be measured by comparing emissions of conventional gasoline

produced after the WIP with the emissions of 1990 gasoline

produced prior to the WIP. For some of these refiners,

compliance with the anti-dumping requirements (to not exceed

1990 emissions levels) could only be accomplished by not

operating, or not fully operating, the new or upgraded unit. 

The inability to make use of the new or upgraded unit could in
432

turn threaten the financial viability of some companies. EPA

is allowing WIP baseline adjustments, under certain

circumstances, as discussed below. A WIP adjustment allows a

refiner to modify its baseline volumes and fuel parameter

values such that they reflect the quality of its gasoline after

completion of the WIP. In order to obtain a WIP modification,

a refiner must petition EPA and EPA must approve the petition. 

(1) Background

In the July 9, 1991 proposal, EPA asked for comments as to

whether baseline adjustments should be allowed for major

construction, or associated financial commitment, which

occurred in 1990 and which would change a refinery's future

gasoline quality. At the same time, EPA expressed concern

about the legal basis for providing the option of having an

"adjusted" baseline when the Act clearly states that a

refiner's 1990 baseline is the basis for compliance with the

anti-dumping requirements. 

WIP was also addressed in the regulatory negotiations, and

the negotiated agreement provided general guidelines on which

to base the decision for allowing a WIP baseline adjustment. 

The guidelines were meant to restrict petitions for WIP

adjustments to those extreme situations where it would be

appropriate to make an adjustment. The guidelines in the

agreement were stated as follows: 

"A refiner's baseline will be modified for refinery

work-in-progress at year-end 1990 if it can be

demonstrated that

1. such a modification was significant, i.e., if at

least a five percent difference between baseline

emissions calculated with and without the work-inprogress resulted, and 

2. such work was associated with other regulatory

requirements, and

3. failure to grant credit would result in an

extraordinary regulatory burden, i.e., a substantial

portion of the refinery's capital would be at risk if

the adjustment were not granted, and

4. such credit would not result in significant

environmental harm (e.g., the credit will not cause

the refiner to be five percent above the Clean Air Act

antidumping baseline, etc.)."
433

EPA's April 16, 1992 proposal further discussed baseline

adjustments for WIP. The guidelines presented in the

negotiated agreement were included in this proposal as

requirements, all of which had to be met in order to obtain an

adjustment. In this proposal, adjustments were proposed to be

allowed only for significant differences in exhaust benzene

emissions. EPA also stated that authority for a WIP baseline

adjustment could be found in Alabama Power Company v. Costle, 636 F.2d 323.357 (D.C. Cir 1979) which explained that agencies

possess "equitable discretion...to afford case-by-case

treatment--taking into account circumstances peculiar to

individual parties in the application of a general rule to

particular cases, or even in appropriate cases to grant

dispensation from the rule's operation." Thus, in allowing WIP

adjustments, EPA would be exercising its "equitable" discretion

to afford limited relief to refiners which had work-in-progress

and which would be extraordinarily burdened by the anti-dumping

requirement that they not exceed their 1990 emissions. EPA

proposed that the "substantial" capital-at-risk requirement

would be met if the capital involved with the WIP was greater

than or equal to 10 percent of the refinery's depreciated plant

and equipment value. 

In the February 26, 1993 proposal, EPA expanded upon and

clarified certain aspects of the WIP criteria. First, EPA

proposed that the WIP adjustment also apply to the fuel

components which are capped when the simple model is used, and

to exhaust toxics and NOx emissions in the years when the

complex model is required. The latter emissions requirement is

consistent with the negotiated agreement since the first

guideline in the agreement states "...at least a five percent

difference between baseline emissions...". While allowing a

WIP adjustment to apply to the fuel parameters controlled under

the simple model (sulfur, olefin and T90) was not specified in

the agreement, it is appropriate to allow such adjustments

because those fuel parameters are standards with which a

refiner must comply. Specifically, EPA proposed that if one or

more of the following situations occurred, and all other

criteria were also met, a WIP adjustment would be allowed: 
434

1) at least a 25.0 percent difference exists between

sulfur, olefin and/or T90 values calculated with and

without the WIP adjustment; 

2) at least a 5.0 percent difference exists between

the refiner's baseline exhaust benzene emissions

calculated with and without the WIP adjustment; 

3) at least a 5.0 percent difference exists between

the refiner's baseline exhaust toxics emissions

calculated with and without the WIP adjustment; 

4) at least a 5.0 percent difference exists between

the refiner's baseline NOx emissions calculated with

and without the WIP adjustment. 

Also in the February 26, 1993 proposal, EPA proposed and

requested comments on allowing either the "10 percent" criteria

from the April 16, 1992 proposal or a $10 million minimum cost

of the WIP to satisfy the capital-at-risk criteria. Comments

were received which stated that the 10 percent requirement

could be biased against recently built or recently upgraded

refineries because the depreciated value would be higher for

these facilities than for older refineries of the same size. 

The commenter also claimed that newer facilities tend to

benefit the environment more than similar, older facilities,

and thus could be unfairly penalized, compared to older

facilities, by the proposal. 

EPA also proposed that WIP include projects actually under

construction in 1990 and projects for which contracts were

signed in 1990 such that construction would be completed in

time to comply with the regulatory requirement motivating the

WIP (per the proposed requirement that stated the WIP must be

associated with other regulatory requirements).

In the February 26, 1993 proposed regulations, EPA expanded

on the last of the criteria outlined in the agreement, that a

WIP adjustment not result in significant environmental harm. 

The agreement suggested that the adjustment not cause the

refiner's baseline to be more than five percent above the
 128 From §80.91(c)(4)(iv) of the March 31, 1992 proposed

regulations. The April 16, 1992 proposal published in the

Federal Register contained only the preamble language, it did

not include the associated regulations. However, both the

preamble and regulations were completed on March 31, 1992; the

April 16, 1992 published preamble differed from the March 31,

1992 preamble only in minor ways to allow it to be printed in

the Federal Register. Thus the regulations associated with the

April 16, 1992 published proposal are actually dated March 31,

1992. 

 129 From §80.91(d)(4)(iv).

435

"Clean Air Act anti-dumping baseline". In the April 16, 1992128

proposal regulations, EPA addressed this criteria as follows:

"...Such a credit would not cause a refiner's baseline

exhaust benzene emissions...to exceed the exhaust

benzene emissions due to the baseline gasoline...by

more than five (5.00) percent.

...A work-in-progress-adjusted baseline exhaust

benzene emission value which is greater than 105

percent of the exhaust benzene emissions due to the a

baseline gasoline...shall be allowed if the pre-workin-progress baseline exhaust benzene emissions value

was greater than the work-in-progress-adjusted value." 

As stated, EPA's 1993 proposal would expand this criteria

by creating parallel requirements to cover the exhaust toxics

and NOx emissions and simple model fuel parameters. The

language included in the February 26, 1993 also proposed

regulations (shown below129 in paragraph (A)) to cap exhaust

emissions and sulfur, olefin and T90 values. Additionally, the

language shown in paragraph (A) capped the WIP adjustment of

refiners whose unadjusted baseline (parameters or emissions, as

applicable) was less than the statutory baseline at 105 percent

of the statutory baseline. The language shown in paragraph (B)

and (C) allowed refiners whose unadjusted baseline was greater

than the statutory baseline to maintain their unadjusted

baseline value (and not have to reduce it to 105 percent of the

statutory baseline).

"...(A) Such a credit would not cause a refiner's

baseline exhaust benzene emissions, exhaust toxics

emissions or NOx emissions,...to exceed the respective

emissions due to the baseline gasoline...by more than

five (5.00) percent nor allow its sulfur, olefin or

T90 values to exceed the corresponding values...by

more than five (5.00) percent. 
 130 From §80.91(d)(5).

436

(B) Work-in-progress-adjusted baseline exhaust

benzene, exhaust toxics, or NOx emission

values,...which are greater than 105 percent of the

respective emissions due to the baseline

gasoline...shall be allowed if the pre-work-inprogress baseline values were greater than the workin-progress-adjusted values.

(C) Work-in-progress-adjusted baseline sulfur, olefin

or T90 values which are greater than 105 percent of

the respective baseline values...shall be allowed if

the pre-work-in-progress baseline values were greater

than the work-in-progress-adjusted values."

(2) Comments

Most commenters supported allowing WIP adjustments (if all

other criteria were met) for significant differences between

unadjusted and WIP adjusted values of exhaust toxics emissions,

NOx emissions, sulfur, olefin or T90. A few commenters

suggested that different complex and simple model emissions

requirements have different comparison criteria. Additional

comments suggested reducing the threshold values between WIPunadjusted and adjusted values, i.e., the difference in

emission or parameter values which would be the impetus for

desiring a WIP-adjustment. Commenters stated that lower

differences between these two values (unadjusted and adjusted)

were also significant, and the proposed levels were rather high

and perhaps impractical. Comments also included the

recommendation that if simple model requirements are the

impetus for the WIP, that a refiner revert back to an

unadjusted baseline when the complex model is used.

Few comments were received regarding the requirement that

the WIP be associated with other regulatory requirements.

However, additional clarification of the language was requested

concerning "..completed in time...to comply...", per the

February 26, 1993 definition of WIP as 

"...projects under construction in 1990 and projects

which were contracted for and which will be completed

in time for the refiner to comply with the regulatory

requirement..."130

This language was included in the February proposal to

ensure that the WIP would be completed in a timely manner,

since the WIP was ostensibly being done to comply with a
437

regulatory requirement. Less than timely completion would

indicate that the regulatory requirement was not a driving

factor in initiating the WIP. Clarification was also requested

as to what types of contracts would be considered to have

committed the refiner to the WIP. Other suggestions included

allowing WIP adjustments for work not necessarily associated

with a regulatory requirement, including WIP which would have a

beneficial effect on a refinery's overall environmental

performance. 

Several comments reiterated a concern expressed in the

regulatory negotiation discussions, namely, that a WIP

adjustment should be an exception, i.e., few refiners should

qualify. 

As stated above, in the February 26, 1993 proposal, EPA

proposed to allow "substantial regulatory burden" to be

fulfilled if the WIP value was at least 10 percent of the

refinery's depreciated plant and equipment value, or at least

$10 million. Some commenters suggested that the WIP

requirements be more stringent, ranging from opposition to any

modification of capital at risk (presumably from the 10 percent

criteria) to increasing the threshold value to $50 million. 

Other comments suggested reducing the threshold value to $5

million (possibly a more appropriate value for small refiners)

or to 5 percent (instead of 10 percent) or eliminating any

"dollar" amount because no one should be penalized because its

investment fails to meet arbitrary time or cost criteria. 

Other alternatives suggested include considering 5 percent of

the refinery replacement cost or 10 percent of the depreciated

book value.

EPA received many comments and suggested language with

regard to the simultaneous capping of emissions and parameter

values in the February 26, 1993 proposal. Commenters also

suggested that the five percent statutory baseline cap was too

stringent and that the requirement for showing a difference

between unadjusted and unadjusted values was inconsistent with

the comparison to the statutory baseline. Other commenters

stated that because most new refinery projects are subject to

very stringent environmental regulations their overall

environmental performance will likely improve. 

(3) Final Rule

EPA is requiring that a refiner meet each of three criteria

in order to qualify for a WIP baseline adjustment. A fourth

criteria is also required to minimize environmental harm due to

WIP adjustments. 
438

The first criteria, the showing of significant difference

between unadjusted and adjusted values (i.e., calculated with

and without the WIP adjustment) has been changed from the

February 26, 1993 proposal, considering comments received on

this issue. As stated, the February proposal required at least

a 25 percent difference in sulfur or olefins or T90 or at least

a 5 percent difference in exhaust benzene emissions or exhaust

toxics emissions or NOx emissions. Upon further analysis of

fuel changes and corresponding emissions, reducing the

threshold values seemed reasonable, and neither environmentally

nor competitively detrimental. Additionally, reducing the

thresholds did not appear to reduce the stringency of the WIP

criteria, because the proposed values may have been too

stringent, and perhaps unrealistic relative to actual refinery

situations. In this final rule, at least the following minimum

differences must be shown between WIP unadjusted and adjusted

values:

Minimum Differences between Unadjusted and WIP-Adjusted

Values

Exhaust benzene emissions (simple model): 2.5%

Exhaust benzene emissions (complex model): 2.5%

Sulfur:

10.0%

Olefins:

10.0%

T90:

10.0%

Exhaust toxic emissions:

2.5%

NOx emissions:

2.5%

Although not previously specified, the differences shown

above shall be calculated as follows:

|Unadjusted Value - Adjusted Value|

----------------------------------- x 100 = ____%

Unadjusted Value

EPA realizes that if many refiners qualified for a WIP

adjustment, negative competitive effects could result. 

Additionally, allowing many adjustments could indicate that EPA

has exceeded its equitable authority under Alabama Power, supra

(there is, however, no specified limit on the number of

refineries which may qualify). EPA has set the above WIP

criteria so that adjustments are received only by those

exceptionally burdened by the combination of the reformulated
439

gasoline/anti-dumping rules and other legislative or regulatory

requirements. 

The second criteria requires a showing that the WIP was

associated with another regulatory requirement. Obviously, the

wording of the agreement, "...associated with other regulatory

requirements..." leaves a lot of room for interpretation. EPA

is requiring that the WIP be associated with a legislative or

regulatory environmental requirement enacted or promulgated

prior to January 1, 1991. Such requirements are not limited to

gasoline or Federal requirements. For instance, stationary

source or other fuel quality regulations are acceptable

regulatory requirements. However, the WIP only applies to

projects involving gasoline blendstock or distillate-producing

units under construction in 1990 or for which contracts were

signed prior to or in 1990 such that the refiner was

financially committed to permanently changing refinery

operations. EPA believes that the contracts should have

committed the refiner to purchasing materials and construction

of the WIP. As such, a process engineering design contract

does not commit the refiner to actually implementing the WIP

and would not be considered a WIP contract under this

provision. 

The third criteria requires a showing that the WIP cost was

equal to or greater than 10 percent of the refinery's

depreciated book value as of the WIP start-up date or had a

cost of at least $10 million. Based on comments, "book" value

was substituted for the proposed "plant (including capitalized

engineering costs) and equipment" value. Commenters suggested

that "book" value was a more universally used and understood

term in the refining industry. EPA believes that both the $10

million or 10 percent criteria are fairly stringent

requirements, and that more stringent requirements could

threaten the viability of some refiners. Less stringent

criteria could indicate that the value of the WIP was not

actually sufficient to cause hardship should no WIP-adjustment

be allowed. Thus, this provision is being promulgated

essentially as proposed.

EPA is requiring that determination and verification of the

WIP-adjusted baseline fuel parameter values be achieved using

data obtained subsequent attainment of reliable operation of

the WIP. 

Finally, in order to minimize environmental harm due to WIP

adjustments, EPA is limiting WIP increases in baseline exhaust

benzene, exhaust toxics and NOx emissions and sulfur, olefins

and T90 values to the larger of 1) the unadjusted individual

baseline value of each emission or fuel parameter or 2) 105

percent of the corresponding anti-dumping statutory baseline
440

value. The "105 percent" values are explicitly stated in

§80.91. Note that sulfur, olefins and T90 are only constrained

when compliance is determined using the simple model. When

compliance is determined using the complex model, the WIPadjusted values of these three fuel parameters are not subject

to the caps. Because a WIP adjustment allows a refinery's

entire baseline (fuel parameters, emissions, and volume) to be

adjusted, thus affecting all of the emissions and fuel

parameters controlled under the anti-dumping requirements, the

requirement described above should adequately minimize

environmental harm by not allowing extreme changes in emissions

or controlled fuel parameters relative to statutory baseline

gasoline. 

Finally, while it may be true, as commenters suggested,

that overall refinery emissions may decrease due to new

refinery projects, section 211(k)(8) does not provide EPA

authority to consider emissions other than those vehicle

emissions specified. Hence, minimization of potential negative

environmental effects due to WIP must be relative to the

allowed WIP adjustments.

g. Baseline Adjustment for Extraordinary Circumstances

In the February 26, 1993 proposal, EPA asked for comment on

whether it should allow baseline adjustments for certain

extenuating circumstances. If adjustments were not allowed,

ostensibly a refinery's baseline would be unrepresentative of

the gasoline it would have produced in 1990 had the

circumstance not occurred. EPA requested comment on what

criteria would have to be met, or proof given, to demonstrate

that 1990 refinery operations were indeed different than if the

circumstance had not occurred. EPA also asked for comment as

to the degree of financial hardship that might be required to

be shown and on additional criteria which might have to be met

in order to restrict any such petition to situations falling

within the Agency's authority under Alabama Power, as discussed

in the April 16, 1992 proposal. 

EPA also requested comment as to whether two examples of

potential extenuating circumstances should indeed be considered

extenuating. The first example was the occurrence of downtime

which occurs every 4-5 years and which happened to occur in

1990 (nonannual turnaround). The second example involved

disasters which shut down a gasoline blendstock producing unit

for 30 days or more. EPA also inquired as to whether requiring

30 days downtime was appropriate. 

EPA also requested comment on whether a baseline adjustment

should be allowed for the Defense Department's phaseout of JP-4

jet fuel. JP-4 is a naphtha/kerosene blend. Its replacement,
441

JP-8, is a heavier fuel, and is produced from different

feedstocks. The most likely alternate use of the JP-4

feedstock is in gasoline. However, that feedstock cannot be

used in gasoline without first going through a reformer to

increase its octane to suitable gasoline levels. Thus, the

average aromatic content of a refiner's gasoline will likely

increase relative to its 1990 values if the refiner had

produced JP-4. Additionally, total gasoline volume produced

will likely also increase relative to 1990, and this increase

in gasoline production would be subject to the statutory

baseline, instead of the refiner's individual baseline. In

certain instances, JP-4 was such a large portion of the

refiner's total 1990 production that the refiner may have

extreme difficulty in meeting the anti-dumping requirements and

could be forced to cease operating.

Many commenters felt that baseline adjustments should be

allowed for the above situations as well as for others,

including: almost meeting work-in-progress requirements;

changes in process units and crude quality; the Persian Gulf

War; strikes; neighboring unit owned by another company started

up or shutdown subsequent to 1990; loss of a significant market

(not limited to JP-4). Others stated that because every site

is unique, baseline adjustments should be evaluated on a caseby-case basis. Still others suggested that EPA allow

adjustments only for small refiners, or for a certain level of

JP-4 production. Regarding the JP-4 situation, commenters felt

that relief should be given in the anti-dumping program because

of the involvement of two governmental units in creating an

apparent conflict for certain refiners.

Several commenters, however, felt that no extenuating

circumstance baseline adjustment should be allowed. Among the

reasons cited for not allowing adjustments were: competitive

inequities; Congressional intent to account for 1990 only;

difficulty in defining extenuating circumstances; could be used

to void work-in-progress requirements.

The 30 day downtime requirement received some support, and

not much in the way of criticism.

After reviewing this issue, EPA has decided to allow

baseline parameter and volume adjustments, upon petition and

approval, due to the occurrence of unforeseen, unplanned

downtime of 30 days or more of one or more gasoline blendstock

or distillate producing units due to equipment failure or

natural cause beyond the control of the refiner as well as for

nonannual turnaround of a gasoline blendstock or distillate

producing unit which occurred in 1990 and which resulted in the

minimum amount of downtime. Fuel parameter and volume

adjustments shall be made by assuming that the downtime did not
 131 Alabama Power Company v. Costle, 636 F.2d 323.357 (D.C.

Cir 1979).

 132 As discussed in paragraph 5.c, a refiner with more than

one refinery may determine an aggregate baseline, i.e., a

conventional gasoline compliance baseline, which consists of

the volume-weighted emissions or fuel parameters, as

442

occur in 1990. Baseline parameter and emissions values

calculated with and without the adjustment are to be included

in the baseline submission, and any adjustment must be verified

by the baseline auditor. EPA believes that it is appropriate

to allow adjustments in these cases because the circumstances

described above would truly cause a refiner's 1990 baseline to

be different than it otherwise would have been. 

EPA is also permitting baseline adjustments for certain

refiners which produced JP-4 jet fuel in 1990. Specifically, a

refiner which owns a single refinery which does not produce

reformulated gasoline, and whose ratio of 1990 JP-4 production

to 1990 gasoline production equals or exceeds 0.5, may, upon

petition and approval, be allowed to adjust its baseline fuel

parameter values and volume to reflect its refinery operation

had it not produced JP-4 in 1990. EPA believes that it has

authority to allow such adjustments due to the discretion

afforded EPA by Congress. Specifically, Congress did not

prohibit EPA from providing relief in certain instances. 

Additionally, Alabama Power v. Costle131 gives EPA "case-by-case

discretion" to grant variances or even dispensation from a rule

where imposition of the requirement would result in minimal

environmental benefit but would extremely burden a regulated

party. 

As stated, JP-4 baseline adjustments will be allowed only

for those refiners which will not produce reformulated

gasoline. While the anti-dumping requirements, in general,

apply to all conventional gasoline whether or not reformulated

gasoline is also produced, in these specific cases no dumping

will occur due to reformulated gasoline production. The intent

of Congress with regard to the anti-dumping program will be met

while not unduly burdening those that meet the specified

criteria. Since both the unadjusted and adjusted baselines

must be determined, if a refiner granted such an adjustment

subsequently produces reformulated gasoline, its conventional

gasoline compliance would immediately be subject to its

original unadjusted baseline.

JP-4 baseline adjustments are generally limited to singlerefinery refiners. These refiners have no way to aggregate

baselines132 so as to reduce the combined burden of JP-4 phaseout
applicable, of two or more refineries. 

443

and the anti-dumping requirements on their operations. As

stated, in some cases, if no relief were granted in this area,

the viability of a refinery could be at stake. 

Finally, JP-4 must have constituted a significant portion

of a refiner's 1990 production in order for a significant

burden to exist. As such, EPA is requiring that the ratio of

the refinery's 1990 JP-4 production to its 1990 gasoline

production must equal or exceed 0.5. EPA believes this ratio

indicates that a significant amount of the refinery feedstock

used for JP-4 production would have to be converted in order to

produce gasoline. In its February 1993 proposal, EPA requested

comment on what minimum portion of a refinery's 1990 production

JP-4 should have constituted for the circumstance to be

extenuating. Several different ratio options were suggested by

commenters, as follows: JP-4 production to total refinery

production, 20%; JP-4 production to gasoline production, 5%;

JP-4 production to gasoline production, 75%; and, JP-4

production to gasoline plus JP-4 production, 10%. EPA's 0.5

JP-4 to gasoline ratio is in line with some of the commenters

suggestions. 

A baseline adjustment may also be obtained for a refiner

which has more than one refinery if all of its refineries

produced JP-4 in 1990 and meet the threshold criteria and none

of its refineries produce reformulated gasoline in a given

calendar year. While such a refiner may aggregate its

refineries for conventional gasoline compliance purposes, since

there will be no dumping (if no reformulated gasoline is

produced), EPA believes that minimal environmental harm will

result if a baseline adjustment is allowed under these

circumstances as well. If one of the refineries produces

reformulated gasoline in a given year, the unadjusted baselines

of each of the refiner's refineries will be its compliance

baseline, or will be part any aggregate baseline in which it is

included.

While the adjusted emissions baselines of those approved

for JP-4 adjustments are likely to be higher than their actual

1990 baselines (primarily due to increased benzene and

aromatics) EPA expects minimal negative environmental affects. 

Because the number of refineries meeting the criteria is

expected to be small and the total production of all such

refineries is also small, less gasoline is affected by any

baseline adjustments than if the criteria were less stringent. 

Also, there will be no dumping by these refiners due to

reformulated gasoline production. In this situation, EPA

believes that any negative environmental effects resulting from
444

the allowed adjustments are justifiably balanced by the reduced

burden on qualifying refiners.

Although EPA is allowing baseline adjustments for the

specific circumstances described above, it in no way means this

to be a precedent to allow adjustments for actual or so-called

extenuating circumstances now or in the future. The language

of the Act does not allow EPA to broadly permit baseline

adjustments, although under certain, limited circumstances,

particularly those which caused a baseline to be different than

it otherwise might have been in 1990, EPA is not prohibited

from allowing adjustments. In any case, Congress' intended

representative baselines be utilized in the anti-dumping

program. However, a baseline is neither unrepresentative of

1990, nor incalculable, because of post-1990 changes in crude

availability, fuel specifications, fuel markets, etc. Congress

certainly knew that these types of changes could affect

baseline determinations, yet in creating the anti-dumping

requirements it did not require EPA to consider such factors in

determining baselines. In fact, no direction was given to

account for two mandated fuel changes, Phase II volatility

control and lead phaseout. Also, unlike work-in-progress (a

specific extenuating circumstance occurring in 1990),

provisions for dealing with such situations, while mentioned

during the regulatory negotiation discussions, were not part of

the negotiated agreement. 

It is likely that circumstances for which baseline 

adjustments are not allowed may cause a refiner's 1990 and

other pre-1995 conventional gasoline to be unrepresentative of

post-1995 conventional gasoline production and that such

circumstances may negatively affect some refiners. However,

every refiner will be subject to future changes in markets,

fuel quality requirements, etc., all of which will affect the

refiner's gasoline quality and ability to comply with its antidumping baseline. Thus, except in extreme cases, baseline

adjustments due to post-1990 changes which affect refiners

would not be practical (due to the myriad circumstances which

may exist) nor necessarily fair, and are definitely not

supported by the language of the Act nor the intent of

Congress. EPA is appropriately not providing for such

adjustments.

h. Inability to Meet the Requirements

EPA realizes that every refinery is different with respect

to configuration, geography, crude availability, etc. EPA also

realizes that many unique situations occurred in 1990 that are

probably not covered by the anti-dumping and baseline

development provisions being promulgated today. While EPA's

goal with regard to baseline development is to develop
445

individual baselines which adequately represent a refiner's or

importer's 1990 fuel, it does not want to penalize a refiner's

or importer's baseline development for trivial reasons. Thus,

if a refiner or importer is unable to comply with one or more

of the specified requirements in its baseline development, it

may, upon petition and approval, accommodate the lack of

compliance in a reasonable, logical, technically sound manner,

considering the appropriateness of the alternative. This

provision was not included in the proposals, but is included in

the final rule because sufficient comment was received

indicative of the innumerable details and specific

circumstances that exist in the baseline development. 

5. Baseline Volume and Emissions Determination

a. Individual Baseline Volumes for Refiners, Blenders and

Importers

The individual baseline volume of a refiner which utilizes

Methods 1, 2 and or 3-type data to determine its baseline fuel

parameters shall be the larger of the total volume of gasoline

produced in or shipped from the refinery in 1990, excluding

volumes exported. This provision is added because the volumes

of 1990 shipments and production could differ, due to shipping

from inventory or to not shipping some production at the end of

the year. Thus for each refiner, either produced or shipped

volumes could be larger. While 1990 gasoline shipments

actually contributed to emissions, data is available (by

Methods 1, 2 or 3) on 1990 gasoline production. The difference

between the shipped and produced gasoline is expected to be

negligible with respect to baseline determination. Volumes of

oxygenates blended into gasoline at the refinery and oxygenate

assumed or shown to have been blended into gasoline downstream

of the refinery, shall be included. The baseline volume shall

be determined after all adjustments, such as for work-inprogress or extenuating circumstances, have been performed.

For the same reasons discussed above, the individual

baseline volume of a blender utilizing only Method 1-type data

or having the anti-dumping statutory baseline as its individual

baseline shall be also the larger of the volume of 1990

gasoline produced in or shipped from the refinery (blending

facility). The individual baseline volume of an importer

utilizing only Method 1 or having the anti-dumping statutory

baseline as its individual baseline shall be the total volume

of gasoline imported into the U.S. in 1990. 

b. Baseline Emissions Calculation

Every refiner must develop a set of individual baseline

data which include fuel parameter values, volume, emissions and
446

blendstock-to-gasoline ratios. As discussed in Section IV,

there are separate complex models from which to determine

summer and winter emissions. As such, average baseline fuel

parameters must be determined separately for summer and winter. 

Conventional gasoline baseline emissions (and sulfur, olefins

and T90 values) will first be determined separately, on a

summer and winter basis, using summer and winter fuel parameter

values. As discussed in Section IV, when using the winter

complex model, RVP is held at 8.7 psi; thus, the actual average

winter RVP (for baseline or compliance purposes) is not a

factor in determining winter emissions. The summer and winter

emissions (and sulfur, olefins and T90 values) will then be

weighted by the respective summer and winter baseline volumes

to determine annual average baseline emissions (and sulfur,

olefins and T90 values). Compliance is determined in a similar

manner.

As also discussed in Section IV, there are two complex

models--one for use prior to 2000 and one for use in 2000 and

beyond. As such, every refinery will have two sets of baseline

total exhaust toxics and NOx emissions--one set applicable

prior to 2000, and one in 2000 and beyond. Note that baseline

fuel parameter values and baseline volume do not change, only

the emissions determined from the baseline fuel parameters. In

the case of NOx, it is likely that every refinery will actually

have four potential baseline NOx emissions values, depending on

whether the nonoxygenated or oxygenated set of baseline fuel

parameters is used to evaluate NOx emissions (see discussion in

paragraph 4.e).

Regarding baseline emissions, many commenters were

concerned about the effect of future revisions to the complex

model on 1990 baseline emissions and future compliance,

particularly should additional fuel parameters be added to the

model. Many thought that the current (final) complex model

should be grandfathered for anti-dumping purposes, i.e., that

the baseline set per the final rule should always be the basis

for anti-dumping compliance, regardless of future complex model

revisions. Grandfathering the complex model, as suggested

could prevent reformulation of conventional gasoline. Others

suggested EPA specify a time frame for establishing baseline

values of new parameters added to the model. In the event of

revisions to the complex model, EPA will promulgate additional

regulations which will consider the impact on conventional

gasoline, including consideration of lead time, cost and other

factors. 

c. Conventional Gasoline Compliance Baselines
 133 California Phase II gasoline must be sold yearround in

California beginning January 1, 1996.

447

The Clean Air Act refers to gasoline sold by a refiner,

blender or importer, but does not specify an averaging unit for

baseline determination. EPA considered three possible options

for baseline determination--refinery basis, refiner basis, or

some combination of the two. During the regulatory

negotiation, it was agreed that EPA would propose allowing a

refiner to elect to establish an individual refinery baseline. 

In the April 1992 proposal, EPA proposed that a refiner could

choose to have an individual baseline for each of its

refineries or to have a single refiner baseline (and no

individual refinery compliance baselines), but not a

combination of the two.

Based on earlier comments, EPA realized that a refiner may

desire to have an individual baseline for each of its

refineries, if for example, one refinery has low baseline

emissions and the other has high baseline emissions, and the

low emission refinery will soon be producing primarily

reformulated gasoline. If the operations of the high emission

refinery do not change, the refiner would be out of compliance

with the anti-dumping requirements because the contribution of

the low emission refinery fuel in the anti-dumping calculation

would be less. Thus, the refiner would be penalized for

producing reformulated gasoline while maintaining conventional

gasoline operations that are very similar to its 1990

operations. A similar situation could exist for refiners with

both California and non-California refineries. If a refiner's

California refinery was a low emission refinery which did not

produce conventional gasoline in the future (because it was

producing California Phase II gasoline133), the rest of the

refiner's gasoline would be subject to a baseline which

included the California refinery's low baseline if all

refineries had to be aggregated. 

EPA also realized, however, that allowing refiners to

simply pick a combination of averaged and individual refinery

baselines could give multi-refinery refiners an opportunity to

game the system and potentially grant them a significant

advantage over single-refinery refiners. Thus in the proposal,

EPA stated that a refiner could not have multiple refiner

baselines, i.e., either all of its refineries were included in

its refiner baseline, or they all had their own baseline. 

Most of the comments received on this issue claimed that

EPA had not interpreted the Agreement-in-Principle's provision

correctly. The agreement, according to the commenters, allowed
 134 When two or more refineries are grouped for the purpose

of having a single conventional gasoline compliance baseline,

the refineries shall be considered "aggregated", and the

resulting

baseline shall be an "aggregate" baseline.

448

refiners to decide how to aggregate134 their refineries'

baselines. Some suggested that if aggregations are only

allowed as proposed, compliance with the simple model, complex

model and/or anti-dumping requirements would be difficult. It

was also suggested that refiners should be able to re-aggregate

their refineries' baselines annually, or at least once.

A few commenters agreed with EPA's proposal, although some

went further and suggested that all refineries should be

required to comply with their individual baselines, so as to

minimize advantages for multi-refinery companies over single

refinery companies. One commenter stated that refineryspecific baselines could actually increase dumping of high

emission feedstreams.

Upon further consideration of this issue, EPA is allowing

refiners to choose to have one or more individual refinery

conventional gasoline compliance baselines and one or more

"refiner" baselines (i.e., more than one grouping of two or

more refineries to form a compliance baseline). All baseline

determination and compliance requirements applicable to

refiners also apply to refineries with individual baselines and

to aggregate baselines. NOx compliance of all refineries in

the aggregate must be on the same basis, oxygenated or

nonoxygenated. Moreover, the decision to group or not group

refineries is a onetime decision, i.e., refineries cannot be

re-aggregated annually. Because of this, and because a

refiner's total emissions will be conserved, the possibility of

gaming will be reduced. Thus EPA believes that allowing more

than one individual or aggregate baseline is equitable as well

environmentally sound. 

Because baseline aggregation, as well as determination of

the 1990 equivalent conventional gasoline volume (per §80.101),

depends on a refiner's 1990 baseline volume, refiners which get

the statutory baseline as their individual baseline (i.e., were

in operation for less than 6 months in 1990) do not have

baseline volumes. Hence, the baselines of such refineries

cannot be aggregated with other refiners for conventional

gasoline compliance purposes. 

An individual baseline (including both parameter and

emission values) must still be calculated for each refinery. 

Individual baselines are required for several reasons. First,
 135 EPA's authority to establish such individual baselines

is based on section 211(c) of the Act which allows the

Administrator to regulate fuels or fuel additives to protect

the public health or welfare. 

449

aggregate baselines are determined by volume-weighting the

individual baseline emission values (and sulfur, T90 and olefin

values under the simple model) of the included refineries. 

Second, reformulated gasoline compliance under either the

simple model (for sulfur, olefin and T90) or early use of the

complex model is on a refinery basis. Finally, individual

baselines must be known in the event that ownership of a

refinery changes. 

As proposed, EPA is also requiring that a refiner establish

individual refinery baselines under certain circumstances. 

Specifically, as discussed in the July 9, 1991 and April 16,

1992 proposals, "localized dumping" could occur in certain

geographical areas. If significant increases in toxic

emissions are occurring in a conventional gasoline area

surrounding a reformulated gasoline opt-in area, and if the

area is served by an isolated distribution system, EPA will

require refineries in the affected area to have individual

baselines for compliance purposes135. If the refinery was part

of an aggregate baseline, the other refineries constituting the

aggregate remain in the aggregate, although the aggregate

baseline must be recalculated to reflect the loss of the

baseline of the refinery which left the aggregate as required. 

Most commenters supported this proposal. One commenter

requested that refineries which will produce no reformulated

gasoline and which supply an isolated area be exempt from the

anti-dumping requirements. The Act requires all domestic

refiners, blenders and importers to comply with the antidumping requirements, regardless of the location of gasoline

production. One commenter requested that this proposal not be

limited to a conventional gasoline area surrounding an opt-in

area but that it apply to all conventional gasolines areas

which may experience localized toxics emissions increases. 

This suggestion was rejected, in part, because the Act directs

EPA to focus on refiners, and not on areas. Additionally, it

would be extremely difficult to determine such areas, unless

those areas are somewhat isolated. Also, this proposal was

discussed at length in the regulatory negotiations, and the

associated language was meant to limit its scope. EPA believes

this is reasonable as refiners are required to maintain

conventional gasoline emissions at their own baseline levels,

and because several refiners supply most areas. Except for the

isolated areas which are provided for by this provision, few

areas are likely to see unidirectional changes in toxics
450

emissions over an averaging period. This provision attempts to

address a narrow problem, and EPA has appropriately limited it

to achieve this goal.

d. Baseline Recalculation

Pursuant to this rulemaking, each refinery will have a 1990

individual baseline, whether that baseline is a unique

baseline, determined per the regulations, or whether it is the

anti-dumping statutory baseline. Its individual baseline is

retained forever, whether new units are added to the refinery,

or other units are shutdown (the situation of the entire

refinery shutting down is discussed below). 

In the April 16, 1992 proposal, EPA proposed that baselines

would be required to be recalculated under certain

circumstances. EPA did not receive significant comment on this

issue. The circumstances which would require baselines to be

recalculated are discussed below. Only aggregate baselines are

required to be recalculated, although a refinery which was part

of an aggregate baseline may end up having to comply with its

individual baseline under certain circumstances.

If a refinery was in operation for at least six months in

1990 and is later sold, and if the refinery was part of and/or

becomes part of an aggregate baseline, any aggregate baseline

affected by the sale shall be recalculated to reflect the

inclusion or exclusion, as appropriate, of the baseline fuel

parameter values, emissions and associated volumes of the

refinery being exchanged. 

In a change from the proposals, EPA is requiring that if

all gasoline producing units in a refinery are shut down for

any length of time, and if the refinery is part of an aggregate

baseline, the aggregate baseline shall be recalculated due to

the shutdown. Excluding the baselines of shutdown refineries

is more consistent with the other baseline recalculation

situations. However, if a refinery is only partially shutdown,

it must still comply with the requirements of the anti-dumping

program for any conventional gasoline (and blendstocks, if

necessary, per the requirements of §80.102) it produces. 

Note that if a shutdown refinery is later sold to another

refiner, its old aggregate baseline (if it was one of more than

two refineries comprising the aggregate baseline) and its new

aggregate baseline, if applicable, would be recalculated. If

the shutdown and later sold refinery was one of two refineries

comprising an aggregate baseline, the remaining refinery would

then have an individual baseline--it could not be reaggregated, either by combining with another refinery with an
 136 EPA recognizes that the term "auditor" usually refers to

a person who evaluates financial data. However, in the context

of the baseline development discussed in this rulemaking,

"auditor" or "baseline auditor" refers to a person or an

organization retained to technically evaluate the baseline

determination of a refiner for correctness. 

451

individual baseline or by inclusion in another aggregate

baseline.

Any baseline changes due to the circumstances described

above, or to similar circumstances, must be verified by a

certified baseline auditor, and submitted (with appropriate

documentation) to EPA within 30 days of the event causing the 

baseline fuel parameter values to require recalculation.

D. Baseline Auditor 

In the regulatory negotiations, although not specified in

the negotiated agreement, the concept of having individual

baseline determinations verified by an independent source prior

to submission to EPA was discussed. The independent source is

also known as the baseline auditor136. In the July 9, 1991

proposal, EPA briefly discussed its expectations of the

auditor, namely that the auditor will verify individual

baselines using good engineering judgement. Also briefly

discussed were possible auditor certification options. In the

April 16, 1992 EPA briefly discussed that it would develop, in

consultation with petroleum refining experts, auditor

certification criteria as well as technical guidelines for the

auditor to follow in its verification. On December 15, 1992,

EPA held a workshop to discuss the roles and qualifications of

baseline auditors and certain aspects of the baseline approval

process. Based on comments received at and following the

workshop, as well as comments to previous proposals, in the

February 26, 1993 proposal, EPA proposed specific requirements

that a potential auditor would have to meet to be able to

verify baselines, and also presented its specific expectations

of the auditor's verification.

As discussed below, EPA is requiring that the auditor, and

any individuals and organizations which participate in

substantive aspects of a baseline verification process, meet

certain independence and technical criteria, and that the

auditor assume responsibility for its verification of an

individual baseline. However, ultimate responsibility for the

accuracy of its baseline rests with the refiner. Nonetheless,

if a refiner uses an auditor which does not meet the specified

requirements, its baseline submission will not be accepted

until it is verified by an auditor meeting the requirements. 
452

Note that those refiners, blenders and importers which can and

do utilize the statutory baseline are not required to have a

baseline auditor.

1. Auditor Qualifications

a. Personnel

The baseline auditor can be an individual or an

organization. However, if it is an organization which is

retained for baseline verification, the primary analyst(s) must

be identified. The primary analyst is the individual who must

sign the statement that is included with the baseline

submission indicating that it has reviewed the baseline

determination and that the baseline was correctly determined. 

An auditor may utilize contractors and subcontractors, which

may be individuals or organizations. There was a request for

EPA to define "auditor", "contractor" and "subcontractor" as

well as delineate the qualifications and restrictions

associated with each. The auditor is a person or organization

retained by a refiner to meet the audit requirements of these

regulations. EPA believes the terms "contractor" and

"subcontractor" are generally understood, and EPA intends these

terms to have these meanings. The primary analyst of the

auditor is responsible for the verification, even if parts of

the verification were performed by individuals or organizations

it, or its organization, hired to perform those parts. EPA is

requiring that all individuals or organizations involved in

substantive aspects of a baseline verification meet the

applicable criteria as specified in §80.92 of the regulations.

EPA is also allowing a baseline auditor to be the same

individual or organization which determined a refiner's

baseline. Not allowing the dual roles adds considerably to the

time required for baseline determination, since the auditor

performing the verification (potentially the second outside

organization involved in a refiner's baseline determination)

must learn about the refinery from ground zero, whereas the

person or organization which determined the baseline will have

already established a knowledge base. The cost savings could

be considerable for smaller refiners who do not have the inhouse capability to prepare the baseline. Several commenters

who addressed this issue agreed that the auditor should be

allowed to also be the baseline preparer, mostly from a cost

savings point-of-view. One commenter was concerned that the

independence of the review would be lost. While some

independence of review may be lost, this concern is minimized

by the independence requirements discussed below, and EPA

believes that the cost and time savings are relevant

considerations. 
453

b. Independence

One of the primary criteria required of the auditor is that

it be independent of the organization whose baseline it is

verifying. This requirement is intended to mitigate conflictsof-interest. Any person involved in substantive aspects of a

baseline verification, including organizations and individuals

associated with the auditor, its contractors and

subcontractors, must meet the independence criteria. 

"Substantive aspects" would include any function that involves

analysis, review, calculations, etc. relative to the

verification. Thus, for instance, clerical personnel would

likely be exempt from these requirements. Also, individuals

within the same organization may meet the independence criteria

for some refiners but not for others. Independence must only

be shown for the refiner on whose baseline verification the

person is working. Persons who do not meet the independence

criteria may work on developing the baseline, but not on the

verification.

The independence requirement is designed to avoid conflict

of interest, and thereby minimize the chance that the results

of an audit are influenced either intentionally or

unintentionally by factors other than the accuracy of the

baseline determination, such as a desire to avoid injuring an

ongoing financial or other relationship. Another concern in

such a situation is that if the auditor also develops the

baseline, then as an auditor of themselves they may be

influenced to avoid pointing out mistakes made in developing

the baseline. EPA believes, however, that this risk is limited

in nature, and the benefits in time and cost from allowing the

auditor to also develop the baseline outweigh the risks.

Few comments were received relative to the criteria which

were proposed in the February 26, 1993 proposal. Thus, EPA is

promulgating the following independence requirements. First,

no person subject to the independence criteria shall have

worked in the past three years as an employee of the refiner or

importer whose baseline is being verified. This does not

include having been a contractor or subcontractor to the

refiner or importer. This is a slight modification of the

proposal, where the criterion was five years, and is based on

comments received that industry turnover is sufficiently high

that three years was also appropriate. EPA agrees that three

years is probably sufficient to establish independence. 

The second independence requirement requires that personnel

subject to the independence criteria be financially independent

of the refiner or importer. Thus, no person subject to the

independence criteria shall 1) have received more than one

quarter of its revenue (a change from income) from the refiner
454

or importer during the previous year (prior to its hire by the

refiner or importer) and 2) have a total of more than 10

percent of its net worth (a change from total investment

holdings) with the refiner or importer. As indicated, some of

these requirements are slight modifications of those proposed,

based on comments suggesting more appropriate wording. Income

received from the refiner or importer to develop the baseline

being audited (verified) is excepted. EPA agreed with the

suggestion of one commenter, and is thus including as a

requirement, that compensation for baseline auditing services

be independent of the outcome of the audit. 

c. Technical Ability

Because verification of a refiner's or importer's baseline

is likely to be technically challenging, the auditor must be

technically able to evaluate a baseline determination. Its

technical knowledge must include, but is not limited to, an

understanding of: petroleum refining processes; gasoline

blending; the effects of process and feedstock changes on the

quality of gasoline blendstock streams; associated

computational procedures and methods of product analysis. It

must have data gathering and analysis skills, and financial

knowledge relative to refinery operations and capital

equipment. 

Few comments were received concerning the proposed specific

technical requirements of auditors. In order to increase the

likelihood that an auditor will possess the necessary technical

knowledge and ability, EPA is requiring that the primary

analyst(s) have a minimum amount of refinery-associated

experience. Specifically, a primary analyst must have 1)

worked at least 5 years in either refinery operations or as a

consultant for the refining and gasoline-producing industry,

and 2) at least 3 years experience working with refinery

computer models, such as those used to evaluate unit operations

or for refinery planning and economic analyses, if such models

are used in support of the baseline determination and/or

verification (the primary analyst must have this experience

with the specific model(s) used in the baseline verification). 

EPA expects the primary analyst to know the relevant details

and assumptions of the baseline determination it verified. EPA

may allow, upon petition, a primary analyst to have less than

the minimum experience if its technical ability can be

otherwise satisfactorily demonstrated.

2. Auditor Certification

EPA is requiring that the qualifications of an auditor be

shown in a statement which is submitted to EPA. The statement

should show how the auditor, its contractors and subcontractors
455

meet the independence and technical criteria. It can also

include additional information which may assist EPA in its

review of the auditor's qualifications. If the auditor's

qualification statement does not adequately address the

independence and technical ability criteria, the auditor will

not be certified for baseline auditing, and baseline

submissions verified by that auditor will not be accepted until

such criteria are fully addressed and the auditor is shown to

meet all the requirements.

In the February 26, 1993 proposal, EPA proposed that an

auditor's qualification statements can be submitted with a

refiner's or importer's baseline submission, without the

auditor having first been approved by EPA. In this case, the

refiner or importer is assuming that the auditor will meet the

requirements. However, if the auditor does not meet the

criteria, the baseline submission will not be accepted until

the baseline has been verified by a qualified auditor. EPA

also proposed that qualification statements can also be

submitted to EPA prior to a baseline submission by a refiner or

importer or at any time by the auditor. If no response was

received from EPA within 30 days of application or the date the

final rulemaking is published in the Federal Register

(whichever is later), the auditor would be deemed EPAcertified. 

Most commenters agreed with allowing either refiner,

importer, or auditor submission of qualifications, as discussed

above. One commenter thought that EPA should notify auditors

of approval rather than letting them be certified by default,

and that they should be pre-certified. EPA believes however,

that refiners could evaluate the requirements described in the

February 26, 1993 proposal (which are not much different from

those listed in this final rulemaking) and evaluate the

credentials of the auditor they want to use to verify their

baseline determination. Since its baseline will not be

approved unless the auditor meets the qualifications, the

refiner or importer is likely to carefully choose its auditor. 

Thus EPA does not believe that precertification is necessary. 

In a modification of the proposal, EPA is changing the timing

of being certified by default from 30 to 45 days. This allows

some additional time for the qualification statement to reach

EPA, considering mailing and delivery delays, etc.

As stated, the refiner or importer is responsible for

choosing an auditor which meets the requirements. In the

February 26, 1993 proposal, EPA had proposed that within thirty

(30) days of hiring a baseline auditor, or the date the final

rulemaking is published in the Federal Register (whichever is

later), each refiner and importer must inform EPA of the name,

organization address and telephone number of each auditor
456

hired. However, upon further review, EPA believes that this

information only need be provided to EPA once, and that

notification in the baseline submission will suffice. The

baseline submission must include all auditors hired, whether or

not they were retained through completion of the verification

or not. 

3. Auditor Responsibilities

The auditor is to verify the baseline determination, not

necessarily perform a second determination. Based on comments

received, it did not appear necessary to require a redevelopment of the baseline--verification would suffice. 

During the workshop, EPA had discussed the possibility of

requiring auditors to submit a plan of their verification

process to EPA prior to beginning the verification. EPA

believes that such a requirement would increase the time

required to prepare a baseline submission, and impose

additional costs, and is unnecessary if the auditor

(particularly the primary analyst) is required to meet certain

criteria. Since EPA is specifying such criteria, and

considering the time and cost aspects, auditors are not

required to submit a verification plan.

The auditor's primary responsibility is to insure that all

baseline determination and submission requirements are

fulfilled. This includes, but is not limited to: insuring

that all data is correctly accounted for; that, depending on

the circumstance, all the appropriate criteria are met; that

calculations are done correctly; that proper adjustments have

been made when necessary, such as when using Method 3-type

data, or when adjusting for work-in-progress or extenuating

circumstances, as allowed. 

EPA is also requiring the refiner to include in its

baseline submission a statement, prepared and signed by the

primary analyst, stating that to the best of its knowledge, it

has thoroughly reviewed the sampling methodology and baseline

calculations, and that they meet the requirements and

intentions of the rulemaking, and that it agrees with the final

baseline values (fuel parameters, emissions, volumes, and

blendstock-to-gasoline ratios) listed in the baseline

submission. As stated, the refiner or importer is ultimately

responsible for the adequacy and accuracy of its baseline

determination. However, because EPA plans to rely heavily on

the auditor's verification, if EPA discovers that an auditor

has displayed gross incompetency or intentionally committed a

significant error in the verification process, EPA may pursue

debarment of the auditor under 18 USC 1001. 
457

In accordance with the refiner being ultimately responsible

for the accuracy of their baseline, the refiner will be the

first point of contact for questions concerning the baseline

determination. In certain situations, a re-verification of all

or part of the baseline submission may be required, and the

refiner may want to involve the auditor at the start of such

discussions. 

E. Baseline Submission and Approval

1. Baseline Submission

a. Timing

EPA is requiring refiners and importers to submit two

copies of their baseline determination to EPA within 6 months

of the date the final rule is published in the Federal

Register. Two copies will allow multiple simultaneous review

of baseline submissions. The six month timeframe was proposed

in the February 26, 1993 proposal and received some support via

comments (and minimal negative comments). EPA believes this

timeframe is reasonable whether baseline auditors are

precertified by EPA or whether the refiner or importer has

assumed responsibility for choosing a qualified auditor without

pre-certification. It is also reasonable considering the fact

that many refiners have already gathered sufficient data, began

estimating their baselines, and are working with potential

auditors in anticipation of the final requirements. If a

refiner must collect data after today, it must submit its

baseline to EPA by September 1, 1994. Although this date is

very close to the first day of the reformulated gasoline

program, refiners will have been able to complete collection of

the required minimum data at least 30 days prior to this date

(most likely earlier). It will also give EPA time to review

and approve the submissions. 

EPA will consider petitions for extensions of the

deadlines, however, refiners are encouraged to submit baseline

submission packages as soon as possible after today.

b. Petitions

In many situations in the baseline determination, a refiner

or importer is required to petition EPA in order to be allowed

to account for a variance from a requirement. In other

situations, the refiner or importer is required to "show" that

it meets certain criteria. In either of these situations,

approval will be given by the Director of the EPA's Office of

Mobile Sources, or designee. As will be discussed below, all

petitions must be included in the baseline submission--in fact,

in most cases, baseline calculations have to be determined both
458

with and without the requested variance, since the outcome of

the request would be unknown. Although not previously

proposed, EPA is allowing petitions and "showings" to be

submitted prior to the baseline submission deadline although an

early decision on the request is not guaranteed. Nonetheless,

the baseline submission must be submitted by the applicable

deadline, whether or not EPA has decided to approve or

disapprove the request.

c. Submission Requirements

Baseline submissions are required from all refiners,

including blenders, and importers. Although minimum

requirements concerning the information contained in the

baseline submissions is specified in §80.93, no set format for

the baseline submissions is specified. EPA expects to issue a

sample "baseline submission" memorandum soon which refiners and

importers may follow in setting up their baseline submissions. 

The baseline submission must include a letter signed by the

chief executive officer of the company, or designee, which

states that the data submitted is the extent of the data

available for the determination of all the required baseline

fuel parameter values, that sampling methodology and baseline

calculations meet the requirements and intentions of the

rulemaking, and that the final baseline parameter and emission

values listed represent its 1990 gasoline, to the best of its

knowledge. If an entity is permitted to utilize the antidumping statutory baseline parameters as its individual

baseline parameters, and does so, it must also include a letter

signed by the chief executive officer of the company, or

designee, indicating that insufficient data exists for a

baseline determination by the methods allowed for that entity. 

Where an auditor is required to verify a baseline, the

auditor's statement of verification, and the auditor's

qualifications if not previously certified by EPA, must be also

be included in the submission.

The baseline submission must contain information relevant

to the development of the baseline value for each of the

following fuel parameters: benzene; aromatics; olefins;

sulfur; T50; T90; E200; E300; oxygen, including oxygenate type;

and RVP. It must also contain the baseline emissions values

and baseline volumes. Additionally, the blendstock-to-gasoline

ratio discussed in Section IX of the Preamble and defined in

§80.102 must be determined for each calendar year 1990-1993. 

Although this requirement was not included in the proposals, it

makes sense to include it in the baseline submission, and have

the auditor verify it as for any other baseline data, because

future compliance will be based on this ratio. 
459

Based on comments to its proposals, EPA has determined that

a number of its proposed baseline submission requirements, such

as parameter measurement dates and extensive crude oil

information, were not pertinent to the baseline determination. 

EPA thus revised its requirements; the minimum information

which must be included in the baseline submission is described

in §80.93. Certain information on crudes and refinery unit

operations is still required because EPA may wish to evaluate

baseline submissions using a refinery flow simulation system. 

EPA may require additional data to aid its review of the

baseline submission. A refiner or importer may also include

additional information which may be useful to EPA in its

evaluation of the baseline submission. In addition to the

numerical data requirements, EPA is requiring that a narrative

of the development of each baseline parameter value be included

in the baseline submission. The narrative should discuss and

explain the sampling and calculation methodologies, as well as

discuss technical judgement and reasoning. Such a narrative

will assist EPA in its review of the baseline submission. 

2. Baseline Approval

EPA had proposed that it would publish baseline parameter

values, by refinery, for public comment while it reviewed

baseline submissions. Based on comments and further review of

this issue, EPA believes that no substantive comments could

result from publishing such information because of the

complexity of the baseline determination. Additionally, EPA

realizes that certain aspects of the baseline determination

must necessarily remain confidential in order to prevent

serious, negative competitive effects. 

Several issues were raised in the comments concerning

confidential treatment of information submitted by refiners. 

Issues of confidential treatment for any information submitted

is regulated by EPA's Confidential Business Information (CBI)

regulations, 40 CFR Part 2 Subpart B. Under the Freedom of

Information Act (FOIA), a person has a right to release of

documents unless the documents are covered by an exemption such

as the CBI exemption. A lot of the information submitted by

refiners for baseline approvals might well be CBI, and would be

protected under CFR 40 Part 2. 

The CBI claim should be made with the baseline submission,

or it can be released without further contact with the

submitting party (40 CFR 2.203 (a)(c)). In accordance with 40

CFR Part 2, Subpart 2, any person or organization providing

information to EPA in connection with the determination of a

baseline, including establishing a baseline or investigating

baseline determination discrepancies, may assert that some or

all of the information submitted, except the baseline emissions
460

or parameter values which are the standard for a refiner,

refinery or importer, is entitled to confidential treatment. 

Such confidential information must be clearly distinguished

from other information to the greatest extent possible, and

clearly labeled "Confidential Business Information." 

Information covered by a claim of confidentiality will be

released by EPA only to the extent allowed by procedures set

forth in 40 CFR Part 2, Subpart B.

Because an entity's baseline will become its standard for

compliance with the anti-dumping, and possibly reformulated

gasoline, requirements, upon Agency approval of a baseline, the

baseline exhaust benzene, exhaust toxics and NOx emissions

values and 125 percent of the baseline sulfur, olefins and T90

values will be published in the Federal Register for each

applicable gasoline producing or importing facility of a

refiner, blender or importer. The standards themselves are not

entitled to confidential treatment under 40 CFR 2.301 (e)

(special CBI rules applicable to Clean Air Act cases). Since

EPA must release them upon request, and because commenters did

not provide any clear or compelling reason for not publishing

them, and because there are benefits from publishing them

(citizen suit enforcement, more information to the general

public about EPA's standards, better deterrence to

noncompliance), EPA should publish them.

Several commenters suggested publishing a refiner's or

importer's anti-dumping index (ADI), a ratio of the individual

baseline emissions to the emissions due to the statutory

baseline. However, there is little difference between this

value and the actual value if the statutory baseline emissions

are known. Another suggestion included providing such

information only upon request. Again, there is little

difference between "on request" and publishing such information

at one time. One commenter stated that no where in the statute

was publication of baseline data required. As discussed above,

no compelling reasons for not publishing a refiner's standards

were presented by commenters. Another commenter added EPA

could use the "rule of three" which has been used by DOE; in

this method, three numbers are averaged and the average

reported, however, none of the individual numbers are publicly

available. Although in many instances this method may be

useful, such as in reporting fuel production by grade, in this

case, EPA does not believe its obligation to the public would

be fulfilled using the "rule of three" since each refiner has a

unique standard with which it must comply, and which will be

publicly available.

EPA cannot specify a timeframe for approval of baseline

submissions because it cannot regulate itself. EPA realizes, 

however, the importance of having an approved baseline as far
461

in advance of the first day of the reformulated gasoline

program (January 1, 1995) as possible. As such, it will

endeavor to review and approve all baselines submitted within

the appropriate timeframe in a timely manner. The baseline

determination is not a "one-try" effort; EPA will work with the

refiner or importer until it is satisfied that the baseline is

an accurate reflection of the 1990 gasoline of the refiner or

importer. 

If a baseline has not been approved by EPA prior to January

1, 1995, then a refiner or importer may still introduce

reformulated or conventional gasoline into commerce, with

certain limitations. First, the refiner or importer would not

be able to use the complex model early, under §80.41, as early

use of the complex model requires knowledge of the individual

baseline to determine the appropriate performance standard. 

Once an individual baseline was approved, however, then early

use of the complex model would be allowed. Second, both the

reformulated gasoline and anti-dumping programs have standards

based on the annual averages of either emissions or certain

fuel parameters. For example, simple model standards for

reformulated gasoline require that the annual average for

sulfur, olefins and T90 not exceed the baseline values for

these parameters. The anti-dumping standards require that the

annual average for these parameters not exceed 125% of the

baseline parameter values, and in addition, the average annual

emissions for exhaust benzene, exhaust toxics and NOx may not

exceed the baseline values for these emissions. A refiner or

importer may introduce conventional gasoline into commerce in

conventional gasoline areas prior to approval of baseline of

the individual baseline, however, the qualities of this

gasoline will be used to determine compliance with these

various annual averages. Failure to have a baseline approved

prior to January 1, 1995 could therefore make it harder to plan

for and comply with these annual anti-dumping standards. 

Finally, failure to have an approved baseline may in certain

circumstances make it impossible to certify reformulated

gasoline under §80.41. In such a case, the gasoline would be

considered conventional gasoline and could not be introduced

into commerce in any area covered by the reformulated gasoline

program. Refiners and importers are urged to submit accurate,

clearly described baseline determinations as soon as possible.
 137U.S. Environmental Protection Agency, Memorandum to

Assistant Administrators, "Compliance with the Regulatory

Flexibility Act," EPA Office of Policy, Planning, and

Evaluation, 1984. In addition, U.S. Environmental Protection

Agency, Memorandum to Assistant Administrators, "Agency's

Revised Guidelines for Implementing the Regulatory Flexibility

Act," Office of Policy, Planning, and Evaluation, 1992.

462

VIII. Compliance with the Regulatory Flexibility Act

The Regulatory Flexibility Act (RFA) of 1980 requires

federal agencies to examine the effects of the reformulated

gasoline regulation and to identify significant adverse impacts

of federal regulations on a substantial number of small entities. 

Because the RFA does not provide concrete definitions of "small

entity," "significant impact," or "substantial number," EPA has

established guidelines setting the standards to be used in

evaluating impacts on small businesses137. For purposes of the

reformulated gasoline regulations, a small entity is any business

which is independently owned and operated and not dominant in its

field as defined by SBA regulations under section 3 of the Small

Business Act.

A. Determination and Justification of Small Entity Impacts

The Agency has found that the reformulated gasoline and

anti-dumping regulations may possibly have some economic impact

on a substantial number of small refiners. However, these

regulations may not significantly affect gasoline blenders,

terminal operators, service stations and ethanol blenders under

the same EPA criteria. Small business entities are not required

by the Clean Air Act to manufacture reformulated gasoline. 

Since most small refiners are located in the mountain states or

in California, which has its own (more stringent) reformulated

gasoline program, the vast majority of small refiners are

unaffected by the federal reformulated gasoline requirements. 

All businesses (both large and small) maintain the option to

produce conventional gasoline to be sold in areas not obligated

by the Act to receive reformulated gasoline or those areas which

have not chosen to opt into the program. 

All refiners will be affected by the anti-dumping

requirements, which are less stringent than those for the

reformulated gasoline portion of the program. The anti-dumping

regulations affecting conventional gasoline are not expected to

disproportionately impact small refiners of conventional

gasoline. 
463

In addition, all refiners have the option to use either the

simple or complex model during the first years of the

reformulated gasoline program. The complex model provides 

refiners with the ability to adjust the levels of various fuel

parameters such as RVP, oxygen, aromatics, olefins, benzene,

sulfur, and fuel distillation parameters in meeting the emission

performance requirements of reformulated gasoline. As a result,

refiners have greater flexibility under the complex model than

under the simple model (which focuses primarily on volatility

control) in choosing the least-cost method of compliance. 

Because refineries differ in process unit configuration, raw

material requirements, and product mix, the additional

flexibility afforded by the complex model should reduce the cost

of producing reformulated gasoline. Such a situation is expected

to provide a more equitable situation for small refiners,

especially those with conversion equipment. 

The component of the reformulated gasoline program most

likely to unfavorably impact small entities is the fundamental

necessity that reformulated gasoline meet more stringent emission

standards and thus processing requirements. The Agency is

unaware of any alternative options which might relieve the

regulatory burden on small entities while simultaneously

maintaining the program benefits required by the statute. 

Exempting small refiners from the reformulated gasoline

regulations would result in the failure of meeting CAA

performance standards, which is illegal. All reformulated

gasoline is required to meet the same performance and

compositional standards. Additionally, enforcement of a

reformulated gasoline program (with exemptions or less stringent

standards), in-use, would be impossible to enforce due to the

inherent nature of the fungible gasoline distribution system in

existence. 

The Agency interpretation of the Regulatory Flexibility Act

requires the consideration and promulgation of alternatives or,

in lieu of regulatory options, the justification for declining to

promulgate alternatives. Nonetheless, any flexibility, in

regards to the performance standards, granted to small business

entities would unfairly provide a competitive advantage over the

business entities not classified as "small". One available

option is reducing, but not eliminating, regulatory requirements

on small entities. Requirements could be scaled to just offset

any competitive disadvantage. However if EPA were to promulgate

such guidelines, the small entities that would be eligible to

meet these "less stringent" standards 1) would be hindering

enforcement, as a result of the fungible gasoline distribution

system mentioned above, and 2) would not be meeting statutory

provisions, such as the fifteen percent reduction in VOCs and

toxics. 
464

It is worthy of note that although EPA has received several

comments which claim that the reformulated gasoline regulations

will result in closing the small business entities affected by

this rule, convincing evidence supporting this claim has not been

submitted. Despite the lack of persuasive documentation and the

inability to exempt small businesses from the requirements of the

reformulated gasoline program, EPA has made accommodations where

possible and appropriate. One example of the versatility

embedded in the reformulated gasoline regulations, by EPA, is the

flexibility available to all refiners, both small and large, to

choose to have one or more individual refinery conventional

gasoline compliance baselines and one or more "refiner" baselines

(i.e. more than one grouping o f two or more refineries to form a

compliance baseline). Another example of the flexibility of the

regulations is the ability to produce reformulated gasoline on a

per gallon or averaging basis. Also, certain refiners who

produced JP-4 jet fuel in 1990 may be able to adjust their

baselines so as to reduce the compliance burden. 

 

In accordance with Section 604 of the RFA, EPA has prepared

the following regulatory flexibility analysis which includes a

summary and assessment of the issues raised by public comments on

the Initial Regulatory Flexibility Analyses contained in the

previous proposals.

B. Summary and Assessment of Issues and Comments

1. Background

As part of the Administrator's effort to ensure that the

regulations do not unfavorably affect small business entities,

most small business entities which will be affected by this

rulemaking were represented in the negotiated rulemaking

processes which contributed, in part, to the development of this

final rule. The following organizations which represent in whole

or in part the interests of affected small businesses were formal

participants in the negotiated rulemaking process and signatories

to the agreement in principle: National Corn Growers

Association, Renewable Fuels Association, Oxygenated-fuels

Association, Rocky Mountain Refiners Association, National

Council of Farmer Cooperatives, Society of Independent Gasoline

Marketers of America, Petroleum Marketers of America Association,

Independent Liquid Terminals Association, American Independent

Refiners Association, and National Petroleum Refiners

Association.

EPA believes that the participation of these parties has

helped assure adequate consideration of the special position of

smaller entities in the marketplace. During the negotiated

rulemaking sessions, the public hearings on the previous

proposals, and the public comment period, the small businesses
465

which are potentially affected by the rule made their interests

known. A summary of the comments are presented below. 

Interested readers are referred to both dockets (A-91-02 and A92-12) of this rulemaking for transcripts of the hearings and

copies of all written comments.

2. Oxygenate Treatment

Many of the affected small businesses were concerned about

the treatment of oxygenates. Some produce oxygenates and were

thus concerned that EPA not favor certain oxygenates in the way

that it ensured that there would be no NOx increase. The

evidence about the effect of oxygenates on NOx emissions was not

complete at the time of the April 1992 supplemental proposal. 

Some testing had been done which showed that while oxygen in fuel

lowers CO and VOC emissions, at some concentrations and in some

forms it may raise NOx emissions. When additional data became

available, however, there did not appear to be any significant

difference between the NOx emission effects of oxygen from

different oxygenates. Furthermore, it appeared that reducing the

concentration of a number of additional fuel parameters

(aromatics, olefins, sulfur, etc.) could reduce NOx emissions. 

Consequently, under the regulations being promulgated today, all

oxygenates are treated equally. Refer to Section II of the

preamble for a detailed discussion.

Though all oxygenates are treated equally in the

regulations, VOC and toxics emission performance will be

different for different oxygenates. Refiners, blenders, and

importers must take emission performance into account when

reformulating gasoline with various oxygenates. The market for

ethanol is still expected to grow as a result of the reformulated

gasoline program. Consequently, ethanol market growth will not

pose an economic hardship on small or large ethanol producers

(refer to Section I of the RIA). It is likely that terminal

operators not affiliated with major oil companies would be more

likely to do ethanol blending than terminals associated with

large refiners. However, EPA has addressed the needs of blenders

in its reformulated gasoline enforcement schemes by enabling them

to blend oxygenates with reformulated gasoline blendstocks

formulated for downstream oxygenate blending. As a result there

is no need for blenders to separately certify that they produce

reformulated gasoline and/or make baseline comparisons as

appropriate. Ethanol blenders will need to change the way they

currently do business (unless they choose not to produce

reformulated gasoline), but all blenders must do this if

reformulated gasoline performance standards are to be met. 

3. Definition of Domestic Capacity
466

Small businesses expressed concerned, through comments, with

the definition of domestic capacity to produce reformulated

gasoline. Some suggested definitions that would require all

constituents of reformulated gasoline to be domestically produced

or available at domestic ports. While some of the commenters

were concerned with creating a strong domestic market for their

oxygenates, many more were concerned that the definition be as

broad as possible. If domestic capacity were broadly construed,

insufficient supply would not permit EPA to extend the start of

the program to opt-in areas. As commenters explained it, an

unexpected extension might make a small refiner's investments in

improvements less valuable. Small refiners have less of an

ability to absorb risk or to obtain financing for investments

than do their larger competitors. Thus, small refiners want a

broad definition. EPA agrees that it is in the interest of

domestic oxygenate producers to have a limited definition in

order that demand for their supplies be high. Oxygenate

producers, as indeed all gasoline and gasoline component

suppliers, will be able to operate most efficiently if

uncertainty about opt-ins is minimized. 

EPA has not at this time provided a specific definition of

domestic capacity. Furthermore, there is no fixed definition of

that term in the regulatory negotiation agreement or the Clean

Air Act. According to §211(k)(6)(B), EPA must consult with the

Secretary of Energy before determining whether an area has

insufficient domestic capacity. If the Administrator finds that

there is insufficient domestic capacity to produce reformulated

gasoline, the start of the program may be delayed in opt-in areas

for up to three years. Parties wanting EPA to perform an

evaluation of domestic capacity for a specific area should make a

formal request to the EPA. 

4. Attainment Area Blending of Ethanol

Prior to publication to the 1992 SNPRM, EPA was concerned as

to whether there could be an impact on terminal operators and

gasoline distributors who currently blend unfinished gasoline

components with ethanol for attainment area use. If these

blenders were not producing their own ethanol, the Agency

surmised that the cost of ethanol to attainment area distributors

would rise due to use of ethanol in reformulated gasoline. There

will be no associated rise in the price they will receive for

their gasoline since they sell into unaffected areas. At the

time of the April 1992 supplemental proposal, EPA invited comment

as to the extent to which these blenders do not produce ethanol. 

Since EPA has not received any comments to date on this issue,

the reformulated gasoline program was developed and finalized

with the assumption that such terminal operators and gasoline

blenders were not detrimentally impacted by the regulation.

5. Refiner/Refinery Averaging
 138 "Costs of Alternate Gasoline Reformulations, Results of

U.S. Refining Study for Economics Committee of the Auto/Oil Air

Quality Improvement Research Program," Turner, Mason & Company,

April 1992.

 139 "Estimated Costs of Modifying Gasoline Properties,

Economics Bulletin No. 2," Auto/Oil Air Quality Improvement

Research Program, January 1992.

467

Several small business commenters are refiners with only one

refinery. These commenters were concerned with the ability of

multi-refinery refiners to average their baseline fuels across

many refineries for the anti-dumping provisions. They believe

that such an averaging provision gives a competitive advantage to

large refiners. As discussed in Section __, refiners are allowed

to determine the baseline for their refineries on a refinery by

refinery basis, a refiner basis, or some other basis. If one

refinery's baseline is determined based on its own data, then the

calculation of the baseline for the other refineries of that

refiner must not include that refinery. 

The smaller refiners were also concerned that there be some

variance procedure in cases where they serve a future

reformulated gasoline area and could not produce reformulated

gasoline through no fault of their own. Since these refiners

generally have only one refinery and can often supply only one

market, they are more likely to be unable to supply reformulated

gasoline than a multi-refinery refiner with refineries proximate

to the pipeline. Fortunately, the regulations provide a

mechanism for sale of conventional gasoline in covered areas

under certain very specific conditions. The smaller refiners

acknowledged during the regulatory process that strict adherence

to these conditions (i.e., no fault, return of economic

advantage, continuing efforts, etc.) were necessary to avoid

abuse of the provision.

6. Phase II Standards Impact on Small Refiners

Small refiners were worried that compliance with the Phase

II reformulated gasoline requirements would be more costly than

compliance with the Phase I requirements because of the greater

VOC reduction required. Small refineries which choose to produce

reformulated gasoline are likely to experience higher costs per

quantity of product produced than large refineries. For

instance, refining costs in PADD IV, which tends to have much

smaller refineries than the other PADDs, are 6-7 cents per gallon

higher than for PADD III and V refineries and 3-4 cents higher

than for PADD I and II refineries138. As stated in the A/O

Economics Bulletin139, because of their size, PADD IV refineries

get less benefit from economies of scale for capital investments. 
 140 "Evaluation of the Use of Ethanol and MTBE in

Reformulated Gasoline," Prepared by Sobotka & Co., Inc. for

U.S. EPA under Contract No. 68-W9-0077, September 30, 1992.

468

However, this implies that the small refineries are not

technologically limited by the more stringent requirements. 

Also, there are very few ozone non-attainment areas in PADD IV

and none have yet opted into the reformulated gasoline program. 

Thus, PADD IV refineries are not expected to be impacted by the

Phase II standards. In addition, significant relief exists for

all refiners, in that the Phase II requirements do not go into

effect until the year 2000. Thus, approximately six years of

planning and lead time are available for determining the

necessary refinery changes. 

It is possible that using additional oxygenate in

reformulated gasoline may be a cost-effective method of meeting

the proposed standards. Some small refiners expressed concern

that reformulated gasoline requirements would place them at a

disadvantage in producing reformulated gasoline if it limited

their ability to use ethanol. However, a Sobotka analysis140 of

this situation concluded that small refineries are not

disadvantaged by the federal reformulated gasoline requirements

(at current opt-in levels) because they either: (1) do not

manufacture gasoline, or (2) do not ship a significant portion of

their gasoline output to the affected markets, or (3) could

readily serve conventional gasoline markets. 

7. Phase II Standards Impacts on Oxygenate Producers

In the 1993 NPRM, EPA was concerned that Phase II Standards

would decrease the demand for oxygenates in reformulated

gasoline. It is possible that using additional oxygenate in

reformulated gasoline may be a cost-effective method of meeting

the proposed standards. In that case, oxygenate demand should

increase and oxygenate producers should not be adversely affected

by the Phase II standards. It is possible that the relative use

of various oxygenates could shift from their Phase I usages,

because, as stated above, the Phase II proposed standards will be

more stringent and will have a slightly different baseline

emissions level. However, the use of all oxygenates is still

expected to be greater after 2000 than prior to 1995. 

8. Regulation Development Representation Deficiency

The Agency also received comments from trade associations,

with small entities as members, that were not represented on the

regulatory negotiation committee for reformulated gasoline, such

as the American Waterways Operators (AWO) and the National Tank
469

Truck Carriers (NTTC). As representatives of non-signatory

parties to the Agreement-In-Principle, these organizations

postulate that EPA did not consider the impact of the proposed

regulations on their industries. Although EPA recognizes that

NTTC and AWO were not part of the regulatory negotiation, there

has been ample opportunity to testify at public hearings and

submit comments on the previous proposals to the Agency. In

addition, many of their interests were raised through other

organizations who require their services. Their issues are

similar in some respects to the pipeline and barge industries. 

Demand for these industries' services may increase, if the need

to transport reformulated gasoline to opt-in areas is present. 

EPA has analyzed comments submitted during the rulemaking

process. 

EPA also received comments stating that small independent

developers and marketers of oxygenated fuels were not represented

in the regulation development process, and should have been

included. EPA believes that small independent developers and

marketers of oxygenated fuels were represented in the regulation

development process. Specifically, the American Methanol

Institute (AMI), the Renewable Fuels Association (RFA), the

National Corn Growers, the National Council of Farmer

Cooperatives (NCFC is made up of small blenders, producers and

marketers), and the National Petroleum Refinery Association

(small refiners make up a portion of NPRA's membership) were all

participants in the Reg-Neg process. EPA believes these

associations adequately represented small developers and

marketers of oxygenated fuels. In addition, the small

independent fuel oxygenate developers and marketers who commented

did not raise any issues related to the success or failure of

their businesses which have not already been addressed. 

9. Enforcement Alternatives

NTTC states that the cost of the reformulated gasoline

program to the tank truck industry was not considered when the

rules were being developed for reformulated gasoline. NTTC

further claims that the February 1993 NPRM favors large oil

companies private carriers and jobbers at the expense of common

carriers. They believe this because the common carriers will not

receive any economic benefit from the ultimate sale of the

reformulated gasoline product. Private carriers and jobbers

would benefit if the product not meeting the reformulated

gasoline specifications is sold, whether the uncertified sale was

intentional or not. They are particularly concerned that the

presumptive liability provisions alone will unduly burden tank

truck carriers because they will be forced to pay penalties for

reformulated gasoline specification violations over which they

have no control. As a result, EPA's final rule makes carriers

liable only where the carrier has caused a violation or where a

violation is found at the carrier's facility. The scope of the

recordkeeping requirements for each type of party (e.g., refiners

vis-a-vis retailers of gasoline), and therefore the cost to the
 141EPA estimates the cost to collect and store a sample will

be about $230, and the lab analysis costs will be about $42

(based on an analysis cost of $415 and analysis of 10% of the

samples collected at a refinery), for a total of $272.

470

party, reflects only that party's opportunity to create or alter

the characteristics and quality of reformulated gasoline. Thus,

the smaller facilities, such as truck carriers and retailers,

have a minimal burden under the regulations whereas refiners and

importers have significant requirements.

Some commentors stated that the costs of independent

sampling and testing will be disproportionately high for small

refiners, because their batch sizes are small in comparison to

batch sizes for larger refiners, and because independent labs may

not be conveniently located relative to small refineries,

requiring long distance sample shipping. It is true that the

per-gallon costs of independent sampling and testing will be

larger for a refinery producing reformulated gasoline in small

batches in comparison to the per-gallon costs for a refiner

producing larger batches. Nevertheless, EPA believes this cost

difference is insignificant. For a 20,000 barrel batch, a smallsized batch, the per-gallon cost of independent sampling and

testing would be $0.0003; for a 50,000 barrel batch, the pergallon cost would be $0.0001141. EPA anticipates that samples

collected at refineries located distant from any reliable

independent laboratory will be shipped to the laboratory, but

does not believe such sample shipping is costly. These

conclusions are based on EPA's experience in conducting gasoline

quality inspections throughout the country over at least the past

dozen years, when its inspectors have shipped several thousand

samples per year to EPA's laboratory for analysis.

10. Disproportionate Regulatory Burden

The American Independent Refiners Association (AIRA), a

national trade association comprised of small and independent

refiners, accounts for twenty to thirty percent of domestic

gasoline production. It claims that Congress and several federal

agencies, EPA included, have previously recognized the importance

of small and independent refiners to a competitive marketplace

for petroleum products. AIRA contends that the small,

independent sector of the refining industry is particularly

vulnerable to the burdens of the previous proposals because they

have limited processing flexibility, economies of scale, and

limited availability of capitol. As a result, small, independent

refiners will experience disproportionate negative disadvantages

vis-a-vis major refiners because they have less throughput over

which to spread the costs precipitated by the requirements of the

proposed rule. In regards to producing reformulated gasoline, if

capitol, production, and compliance costs to small refiners are

extremely high and burdensome, they need not produce reformulated

gasoline. 
471

11. Renewable Oxygenate Provisions

Finally, AIRA criticized EPA's assessment of the Renewable

Oxygenate Program (ROP) in regards to small refiners. They

perceived that neither of the Initial Regulatory Flexibility

Analyses included in the prior proposals nor the 1993 Draft

Regulatory Impact Analysis adequately considered small and

independent refiners. AIRA specifically commented that the

requirements to produce sub-RVP gasoline would disproportionately

disadvantage small and independent refiners. EPA is not

promulgating the renewable oxygenate provisions published in the

February 26, 1993 proposal, and instead is basing the final rule

on the provisions as proposed in the April 16, 1992 proposal, as

discussed in Section I of this document or Section II of the

preamble for reformulated gasoline program.
472

IX. State Opt-in Provisions

The 1990 Clean Air Act Amendments (the Act) require that by

January 1, 1995, Phase I reformulated gasoline be made available

in the nine ozone nonattainment areas having a 1980 population in

excess of 250,000 and having the highest ozone design values. In

the year 2000 Phase II of the reformulated gasoline program

begins, requiring even lower emitting gasoline. In an attempt to

expand the benefits of the reformulated gasoline program,

§211(k)(6) of the Act allows areas, other than those mandated, to

choose to participate in the reformulated gasoline program. 

Areas which so choose are considered to have "opted into" the

reformulated gasoline program. Several key issues regarding the

opt-in provisions are discussed below. 

A. General Provisions

Section 211(k)(6) of the Act specifies that upon application

of the Governor of a State, the Administrator shall allow any

area in the State classified as a Marginal, Moderate, Serious, or

Severe Area for ozone nonattainment to opt into the reformulated

gasoline program. The Act also states that opt-in shall become

effective on January 1, 1995 or one year after such application

is received, whichever is later, and that EPA shall publish each

application in the Federal Register upon receipt. 

Section 211(k)(6) grants EPA the authority to delay

reformulated gasoline in opt-in areas for up to three one-year

periods based on insufficient supply. Such a delay could be

based on a petition from an outside party, or at EPA's own

initiative. At the present time, EPA has yet to receive any such

petitions and believes that there will be more than sufficient

supply of reformulated gasoline for a January 1, 1995

implementation date, given the current level of opt-in. If a

delay is necessary, EPA must delay implementation for areas with

a lower ozone classification before issuing any such delay for

areas with a higher classification.

B. Phase I Opt-in only

In its February 26, 1993 proposal, EPA requested comments on

an option that would permit states to opt into only Phase I of

the reformulated gasoline program and maintain the Phase I

requirements beyond the year 2000 when Phase II of the

reformulated gasoline program begins. EPA received a number of

comments and upon review has decided that opting into Phase I of

the reformulated gasoline program alone shall not be permitted.

The Act does not compel the EPA to permit Phase I-only optin. Section 211(k)(10) defines reformulated gasoline as any

gasoline which is certified by the Administrator as complying

with subsection 211(k). Per §211(k)(3)(B), the definition of

reformulated gasoline is set to change in the year 2000 from its
473

Phase I definition to the more stringent Phase II requirements.

Thus, in the year 2000, Phase I gasoline will no longer be

considered reformulated gasoline under §211(k) requirements.

EPA received many arguments for and against allowing Phase

I-only opt-ins. Those in favor argued that more areas would

likely opt into the program because the Phase I gasoline is

better defined, and the economic burden on the consumer would be

more predictable and not as onerous as with Phase II.

Nonetheless, a number of areas have already opted into the

reformulated gasoline program. Supporters also contend that

§211(k) of the Act does not preclude Phase I-only opt-in, so it

should be allowed. However, as discussed above, the definition

of reformulated gasoline in fact changes in the year 2000, thus

presenting a regulatory hurdle. Some comments pointed out that

under the authority given in §211(c)(4)(C), States could require

Phase I gasoline standards separately after the year 2000 as part

of a State Implementation Plan (SIP). That section also states

that the Administrator may approve such SIP provisions only if

EPA determines that such State control or prohibition is

necessary to achieve the national primary or secondary ambient

air quality standard.

Those opposed to Phase I-only opt-in were primarily

concerned with fuel proliferation, or the possibility that both

Phase I and Phase II gasoline would be required in the market in

2000. Such a situation presents logistical concerns regarding

the manufacture, supply, and distribution of an additional type

of gasoline (and potentially additional grades), and enforcement

of the entire reformulated gasoline program. EPA believes that

the petroleum supply and distribution system will already be

strained given the existing reformulated gasoline program. The

strain could be exacerbated by allowing Phase I gasoline to

endure when Phase II gasoline becomes a requirement for covered

areas in the year 2000. The argument was also made that

emissions from the increase in tankage and other equipment

necessary for handling additional types and/or grades of gasoline

would reduce the regulation's environmental benefit, although the

extent to which this may occur is unknown.

Given the potential for supply and distribution problems,

enforcement problems, and the weak statutory authority in the

Act, EPA has decided not to allow Phase I-only opt-ins.

C. Attainment Area Opt-in
474

A few comments addressed the issue of whether areas in ozone

attainment could opt into the reformulated gasoline program. 

EPA's position is that attainment areas may not opt into the

program, with a possible exception given to areas in an ozone

transport region.

The opt-in language of §211(k)(6)(A) of the Act clearly

limits opt-in to areas in a State classified as Marginal,

Moderate, Serious, or Severe for ozone nonattainment. One

exception is included in §184(c) of the Act which provides that

upon petition of any State within a transport region established

for ozone, and based on the recommendation of the area's

Interstate Transport Commission, the commission may develop

recommendations for additional control measures to be applied

within all or a part of such transport region if the commission

determines such measures are necessary to bring any area in such

region into attainment. This provision gives the commission the

opportunity to recommend that an area opt into the reformulated

gasoline program, even those areas in the ozone transport region

which are already in attainment. Once a commission has made its

recommendation, the usual opt-in application procedures and lead

times apply.

D. Opt-out

Once an area has opted into the reformulated gasoline

program, the issue arises whether it may, at a later date, decide

to opt out of the program. This notion was brought up in several

comments, even as a possible alternative to the Phase I-only optin provision discussed above. While EPA is currently considering

opt-out provisions, section 211(k) does not give EPA the

authority to develop an opt-out procedure. Thus, EPA is not

including any opt-out provisions in this rulemaking, but may

pursue separate actions in the future.

E. Opt-In Application

One commenter asked that EPA develop an opt-in application

procedure. EPA feels that this procedure is adequately outlined

in §211(k)(6)(A) of the Act, which specifies that the Governor of

the State must apply to the EPA. EPA has already received a

number of applications in the form of a letter simply requesting

that an area be opted into the reformulated gasoline program. 

EPA feels that this process has been an adequate one. Written

requests for opt-in may be sent to the Administrator of the

Environmental Protection Agency, West Tower Waterside Mall, 401 M

Street, S.W., Washington D.C., 20460.
475

F. Opt-In Lead Time

A few comments requested that extra lead time be given

before allowing areas to opt into the reformulated gasoline

program. EPA feels that given the existing safeguards in the

Act, such a delay is not warranted. §211(k)(6)(B) allows EPA to

delay reformulated gasoline in opt-in areas for up to three years

based on insufficient supply. This is in addition to the

§211(k)(6)(A) provision that reformulated gasoline not be

required in opt-in areas until January 1, 1995 or one year after

the application is received, whichever is later. A delay could

be based on a petition from an outside party, or at EPA's own

initiative. At the present time, EPA has yet to receive any such

petitions and believes that there will be more than sufficient

supply of reformulated gasoline for a January 1, 1995

implementation date, given the current level of opt-in.

G. Define Domestic Capacity

One party's comments contained a request that EPA include

specific definitions for domestic capacity. EPA is unable to

provide a specific definition of domestic capacity for all areas

at this time. According to §211(k)(6)(B), EPA must consult with

the Secretary of Energy before determining whether insufficient

domestic capacity to produce reformulated gasoline exists. EPA

will define domestic capacity as part of any petition to delay

opt-in.

H. Opt-in only after Stage II controls and enhanced I/M

One commenter suggested that opt-in should be allowed only

after an area has implemented Stage II vapor control and an

enhanced inspection and maintenance (enhanced I/M) program. 

Given the wide variety of air pollution concerns, EPA believes

that it is of utmost importance to give States the freedom to

implement, through their State Implementation Plans, whatever

programs they feel will best allow them to achieve attainment. 

EPA believes that most opt-in areas will have considered the

benefits of Stage II and enhanced I/M, and some will implement

these programs, but the decision should rest with the States

based on their own needs. EPA is not comfortable in this

rulemaking preempting State efforts by requiring that Stage II

and enhanced I/M be implemented before allowing opt-in to the

reformulated gasoline program, and hence is not promulgating any

such requirements.