EPA 600/R-05/032

February 2005

Predicted Ground Water, Soil and Soil Gas Impacts

from US Gasolines, 2004

First Analysis of the Autumnal Data

by

James W. Weaver

Ecosystems Research Division

National Exposure Research Laboratory

Athens, Georgia 30605 

Lewis Jordan and Daniel B. Hall

Department of Statistics

University of Georgia

Athens, Georgia 30602

National Exposure Research Laboratory

Office of Research and Development

U.S. Environmental Protection Agency

Research Triangle Park, NC 27711
ii

Notice

The U.S. Environmental Protection Agency through its Office of Research and Development

funded and managed the research described here. It has been subjected to the Agency’s peer and

administrative review and has been approved for publication as an EPA document. Mention of

trade names or commercial products does not constitute endorsement or recommendation for use. 

Abstract

Ninety Six gasoline samples were collected from around the U.S. in Autumn 2004. The

samples included regular and premium grade fuels, conventional and reformulated gasolines,

high and low elevation samples, and fuel subject to state regulations (especially bans of methyl

tert-butyl ether). A detailed hydrocarbon analysis was performed on each sample resulting in

data set of approximately 300 chemicals per sample. Comparisons were made between several

significant individual parameters. The results showed that benzene was, as required by the Clean

Air Act, below 1 percent in areas that require reformulated gasoline (RFG). Higher benzene

levels were found in some samples outside these areas. Methyl tert-butyl ether (MTBE) was

found in use in RFG areas where there were no state bans in place. Where MTBE was banned,

ethanol was found as the replacement oxygenate. Statistical analyses were performed on the

entire suite of reported chemicals. These analyses were used to determine which gasolines were

similar and if characteristics of the gasolines (conventional/reformulated, grade, elevation, and

MTBE ban status) could be used to segregate the fuels into a decision tree. The statistical

analyses showed that the gasolines were separable by these factors, but that differences due to

state regulations or variability in the fuels make certain gasolines dissimilar from gasolines of

similar characteristics. This feature was evident in the premium grade gasolines, presumably

because refiners use different approaches to boost the fuel’s octane number. Estimated

solubilities and vapor pressures of the majority of the chemicals were used to predict the

effective solubilities and gas phase concentrations of each chemical in a gasoline. Three types of

low elevation, regular grade gasolines were included: conventional, MTBE-RFG and ethanol

RFG. Pair-wise comparisons of these fuels showed predicted shifts in aqueous and gas phase

concentrations.
iii

Acknowledgments

The authors gratefully acknowledge the contributions of:

Hal White, US EPA, Office of Underground Storage Tanks; 

Dr. Patricia Ellis, Delaware Department of Natural Resources and Environmental

Conservation; 

Dr. Michel Boufadel, Temple University, Civil Engineering; 

Chris Englehart and Joe Haas, New York State Department of Environmental

Conservation; 

Dr. John T. Wilson, Eric Kleiner, and Fran Kremer, U.S. EPA, Office of Research and

Development; 

Jen Traub and Dr. Randall J. Charbeneau, The University of Texas at Austin, Department

of Civil and Environmental Engineering; 

Matt Jones, Levi Hein, Brad Thornhill, and Dr. Ken Rainwater, Texas Tech University,

Department of Civil and Environmental Engineering; 

Jeff Kuhn, Montana Department of Environmental Quality;

Chris Dufex and Mahesh Albuquerque, Colorado Division of Oil and Public Safety;

Andy Hess and Wally Moon, U.S. EPA Region 10, Seattle Washington; 

Mark Restaino U.S. EPA Region 5, Chicago, Illinois; 

Greg Lovato, Dr. Matthew Small, and Steve Linder, U.S. EPA Region 9, San Francisco, 

California; 

Randall S. Weaver, Statham, Georgia; 

Susan Swanson, The Cascade Group, Streetsboro, Ohio

Mike Birke and Robert Legg Southwest Research Institute, San Antonio, Texas

 Drs. Fred Tillman, and Jay Choi, National Research Council, Athens, Georgia;

Dr. Drew Ekman, Dr. Mike Cyterski, Carlyn Haley, Pam Gunter, Dr. Said Hillal, 

Dr. Susan Richardson, Tim Rowan, David Spidle, and Dr Paul Winget, U.S. EPA

Office of Research and Development, Athens, Georgia,

Sue Davis of U.S. EPA Office of Research and Development, Research Triangle Park,

North Carolina, and 

Rachel Claussen of U.S. EPA, Research Triangle Park, North Carolina. 

Special thanks to Brandy Manders of U.S. EPA, Office of Research and Development, Athens,

Georgia
iv

Foreword

The National Exposure Research Laboratory’s Ecosystems Research Division (ERD) in Athens,

Georgia, conducts research on organic and inorganic chemicals, greenhouse gas biogeochemical

cycles, and land use perturbations that create direct and indirect, chemical and non-chemical

stresses, exposures, and potential risks to humans and ecosystems. ERD develops, tests, applies

and provides technical support for exposure and ecosystem response models used for assessing

and managing risks to humans and ecosystems, within a watershed / regional context.

The Regulatory Support Branch (RSB) conducts problem-driven and applied research, develops

technology tools, and provides technical support to customer Program and Regional Offices,

States, Municipalities, and Tribes. Models are distributed and supported via the EPA Center for

Exposure Assessment Modeling (CEAM) and through access to Internet tools

(www.epa.gov/athens/onsite).

ERD undertook a nationwide study of gasoline composition to generate insight and input data for

risk assessment models, such as the Hydrocarbon Spill Screening Model (Weaver et al., 1994)

and the OnSite on-line calculators (Weaver, 2004). Further, from the nationwide scope of the

study, with its intent to include important geographic and regulatory zones, a set of relationships

defining typical gasolines has been developed. This report describes results from the first

analysis of data collected in the autumn of 2004. Future publications will present results from

later sampling and more comprehensive analyses.

Rosemarie C. Russo, Ph.D.

Director

Ecosystems Research Division

Athens, Georgia
v

Leaking Underground Storage Tank Assessment Report Series

A series of research reports is planned to present data and models for leaking underground

storage tank risk assessments. To date these include:

1. Gasoline Composition

Weaver, James W., Lewis Jordan and Daniel B. Hall, 2005, Predicted Ground Water, Soil and

Soil Gas Impacts from US Gasolines, 2004: First Analysis of the Autumnal Data, United

States Environmental Protection Agency, Washington, D.C., EPA/600/R-05/032.

2. Simulation Models

Weaver, James W., 2004, On-line Tools for Assessing Petroleum Releases, United States

Environmental Protection Agency, Washington, D.C., EPA 600/R-04/101.

As more reports are added to the series, they may be found on EPA’s web site at:

http://www.epa.gov/athens/publications.
1

Table of Contents

Notice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

Leaking Underground Storage Tank Assessment Report Series ..........................v

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Abbreviations and Acronyms ....................................................7

Introduction ..................................................................8

Literature and Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Approach and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Octane Number . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Benzene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Methyl Tert-Butyl Ether . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Tert-Butyl Alcohol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Tert-Amyl Methyl Ether . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Oxygen Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Ethanol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Brand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Similarities and Differences Among Gasolines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Cluster Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Principal Components Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Discriminant Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Representative Gasolines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Cluster Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
2

Predicted Environmental Impacts of the Study Fuels on Water and Air . . . . . . . . . . . . . . . . . . . 53

Predicted Aqueous Concentrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

Predicted Gas Phase Concentrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Discussion and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

Appendix: Theoretical Basis of the Principal Components Analysis . . . . . . . . . . . . . . . . . . . . . 79
3

List of Figures

Figure 1 Benzene data for RFG and conventional gasoline locales. . . . . . . . . . . . . . . . . . . . . . 19

Figure 2 MTBE and benzene contents for all fuels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Figure 3 MTBE content plotted against octane number. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Figure 4 Tert-Butyl Alcohol (TBA) content plotted against MTBE content, showing only small

amounts of TBA present in these fuels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Figure 5 Tert-Amyl Metyl Ether content plotted against octane number. . . . . . . . . . . . . . . . . . 23

Figure 6 Composite weight of oxygen from all oxygenates and benzene concentrations. . . . . 24

Figure 7 Fuel oxygen content plotted against octane number for all samples. . . . . . . . . . . . . . 26

Figure 8 Ethanol content plotted against octane number. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Figure 9 Ethanol content plotted against MTBE content showing the mutual exclusive nature of

the usage of these chemicals. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Figure 10 Distribution of benzene by brand. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Figure 11 Dendrogram showing the cluster analysis’ separation of 93 octane (left) from 87

(right) octane Georgia gasolines. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Figure 12 Dendrogram showing relationship between regular and premium gasolines from 

conventional gasoline areas in Georgia, Ohio and Oklahoma. . . . . . . . . . . . . . . . . . . . . 34

Figure 13 Dendrogram showing relationship between high elevation areas in Lubbock, Texas

and Helena, Billings and Great Falls, Montana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Figure 14 Dendrogram showing relationships between conventional gasolines from Georgia and

RFG gasolines from Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Figure 15 Analysis of three RFG areas without MTBE bans. . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Figure 16 Dendrogram of RFG gasolines from an MTBE-ban state (New York) and two states

without bans. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

Figure 17 Dendrogram of MTBE-ban states with State or Federal RFG requirements. . . . . . . 39

Figure 18 Dendrogram showing relationship between two MTBE ban, RFG gasoline areas. . 41

Figure 19 Plot of the cumulative proportion of variation explained by PC number. . . . . . . . . . 42

Figure 20 Scree graph of the variance estimate by PC number for the individual gasoline

component data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Figure 21 Principal Components plot of the 96 gasoline samples with respect to the first two

principal components labeled by state. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

Figure 22 Principal Components plot of the 96 gasoline samples with respect to the first two

principal components labeled by octane number. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

Figure 23 Plot of the 96 gasoline samples with respect to the first two principal components by

gasoline brand. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Figure 24 Decision tree for gasolines typical of the data collected in this study. The parenthesis

indicate where the cluster analysis indicated that samples from the various states are

similar enough to group together. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Figure 25 Cluster analysis performed on the representative gasolines. . . . . . . . . . . . . . . . . . . . 52

Figure 26 Effective solubility of hydrocarbon groups and oxygenates for the average

conventional, low-elevation, no-MTBE-ban, regular gasolines. . . . . . . . . . . . . . . . . . . . 55

Figure 27 Effective solubility of hydrocarbon groups and oxygenates for the average

reformulated, low-elevation, no-MTBE-ban regular gasolines. . . . . . . . . . . . . . . . . . . . 56
4

Figure 28 Effective Solubility for hydrocarbon groups and oxygenates for the Illinois regular

gasolines (low elevation, MTBE ban, RFG). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Figure 29 Gas phase concentration of hydrocarbon groups and oxygenates for the average

conventional, low-elevation, no-MTBE-ban regular gasolines. . . . . . . . . . . . . . . . . . . . 63

Figure 30 Gas phase concentration of hydrocarbon groups and oxygenates for the average

reformulated, low-elevation, no-MTBE-ban regular gasolines. . . . . . . . . . . . . . . . . . . . 64

Figure 31 Gas phase concentration for hydrocarbon groups and oxygenates for the Illinois

regular gasolines (low elevation, MTBE ban, RFG). . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Figure 32 Scatter plot of predicted gas phase concentration versus the effective solubility of the

average conventional, low-elevation, no-MTBE-ban, regular gasoline. . . . . . . . . . . . . . 72
5

List of Tables

Table 1 Geographic locations, characteristics, and numbers of samples included in the study. 

Elevations less than 2500 ft are judged “low.” Fuel requirements . . . . . . . . . . . . . . . . . 13

Table 2 ASTM D 6729-1 known pairs of co-eluting peaks. . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Table 3 Percent by weight of unidentified compounds in analytical results. . . . . . . . . . . . . . . . 16

Table 4 Specified chemicals included in the analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Table 5 Hydrocarbon groups and numbers of member compounds. . . . . . . . . . . . . . . . . . . . . 16

Table 6 Octane ratings of sampled gasolines. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Table 7 Oxygen content of each oxygenated additive, based upon the number of carbon,

hydrogen and oxygen atoms per mole of compound. . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Table 8 Cluster centroids in weight % for Georgia 87 octane and 93 octane gasolines defined

by all components present at 0.50 wt % or greater. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Table 9 Compounds that were present in greater abundance in Georgia premium than regular

grades by at least 0.50 wt %. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Table 10 Compounds that were present in lesser abundance in Georgia premium gasolines than

in regular grades by at least 0.50 wt %. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Table 11 Degree of similarity where all fuels of a given grade join in cluster analyses of

individual locales (states). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Table 12 Statistics of the first eight PC from the PCA of the individual gasoline components

including variance, proportion of the total variance estimate, and the cumulative

proportion of variation explained. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Table 13 Gasoline components with the largest loadings in the first eight principal components

including class, mean, standard deviation, and the rank of the standard deviation (from

largest (1) to smallest(8)). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Table 14 Discriminant analysis results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Table 15 Predicted higher aqueous constituent concentrations (>0.05 mg/L) of RFG (regular

grade, no-MTBE-ban, low-elevation) in comparison to conventional gasoline. . . . . . . . 57

Table 16 Predicted lower aqueous constituent concentrations (>0.05 mg/L) of RFG (regular

grade, no MTBE ban, low elevation) in comparison to conventional gasoline. . . . . . . . 59

Table 17 Predicted higher aqueous constituent concentrations (>0.05 mg/L) of MTBE-ban

RFG (regular grade, low elevation) in comparison to non-MTBE ban RFG gasoline. . . 60

Table 18 Predicted lower aqueous constituent concentrations (>0.05 mg/L) of MTBE-ban RFG

(regular grade, low elevation) in comparison to non-MTBE ban RFG gasoline. . . . . . . 61

Table 19 Predicted higher gas phase constituent concentrations (>0.05 mg/L) of RFG (regular

grade, low elevation) in comparison to conventional gasoline. . . . . . . . . . . . . . . . . . . . . 65

Table 20 (Continuation) Predicted higher gas phase constituent concentrations (>0.05 mg/L)

of RFG (regular grade, low elevation) in comparison to conventional gasoline. . . . . . . 67

Table 21 Predicted lower gas phase constituent concentrations (>0.05 mg/L) of RFG (regular

grade, low elevation) in comparison to conventional gasoline. . . . . . . . . . . . . . . . . . . . . 67

Table 22 Predicted higher gas phase constituent concentrations (>0.05 mg/L) of MTBE-ban

RFG (regular grade, low elevation) in comparison to non MTBE-ban RFG. . . . . . . . . . 69

Table 23 Predicted lower gas phase constituent concentrations (>0.05 mg/L) of MTBE-ban

RFG (regular grade, low elevation) in comparison to non MTBE-ban RFG. . . . . . . . . . 70
6

Table 24 (Continuation) Predicted lower gas phase constituent concentrations (>0.05 mg/L) of

MTBE-ban RFG (regular grade, low elevation) in comparison to non MTBE-ban RFG.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
7

Abbreviations and Acronyms

BTEX Benzene, Toluene, Ethylbenzene, Xylenes

CAAA Clean Air Act Amendments

CG Conventional gasoline

DHA Detailed hydrocarbon analysis

DIPE Di-Isopropyl Ether

DA Discriminant Analysis

ETBE Ethyl Tert-Butyl Ether

GC-MS Gas chromatography/mass spectroscopy

HCA Hierarchical Cluster Analysis

IUPAC International Union of Pure and Applied Chemistry

LUST Leaking underground storage tank

MTBE Methyl Tert-Butyl Ether

M/Z Mass to charge ratio

ON Octane number

PC Principal Component

PCA Principal Components Analysis

RFG Reformulated Gasoline

SPARC SPARC Performs Automated Reasoning in Chemistry

TAEE Tert Amyl-Ethyl Ether

TAME Tert Amyl-Methyl Ether

TAA Tert Amyl Alcohol

TBA Tert Butyl Alcohol

WO Winter oxygenate
1

Benzene, toluene, ethylbenzene and xylene, taken together, are known as BTEX.

8

Introduction

Gasoline consists of numerous petroleum-derived chemicals and additives. At a

fundamental level the composition determines the physical and operational properties of the fuel. 

Gasoline as a product, though, is defined in terms of these properties that include among others

the octane number and the vapor pressure. The concentration of certain individual components

remains important though as they may be regulated or mandated. The most notable of these are

benzene and oxygenated additives. As a potential source of environmental contamination,

however, the major consideration is the composition. Composition data are relatively scarce as

historically the greatest concerns for chemical contamination of ground water at leaking

underground storage tank (LUST) sites have been placed on benzene, methyl tert-butyl ether

(MTBE) and other aromatics (toluene, ethylbenzene and the xylenes1

). The logic of this

approach appears to follow from several factors: the status of benzene as a carcinogen, the low

taste and odor threshold of MTBE, the relatively high concentrations in fuel of BTEX and, in

some cases MTBE, and the solubilities and volatilities of these chemicals that allow them to

form ground water plumes and/or vapor clouds in the subsurface.

A more fully multicomponent approach may be called for in certain circumstances. The

non-MTBE oxygenates are becoming more prominent because of some states’ bans on MTBE

use, while the Federal oxygenate mandate remains in place. Ethyl Tert-Butyl Ether (ETBE),

Tert Amyl-Methyl Ether (TAME), Tert Amyl Ethyl Ether (TAEE) and Di-Isopropyl Ether

(DIPE) are possible ether oxygenates. Ethanol and Tert Butyl Alcohol (TBA) are possible

alcohol oxygenates. As shifts are made away from MTBE as the dominant oxygenate, other

changes in gasoline composition may occur. This might result in differing levels of various

other contaminants in soil gas or ground water. Knowledge of shifts in composition can provide

decision-makers with foreknowledge of potential impacts. A second reason for a

multicomponent approach is that biodegradation is generally agreed upon to be electron-acceptor

limited. Thus the pool of electron acceptors is available only for a finite mass of contaminants at

most sites. The loading of all species contributes to usage of electron acceptors and may need to

be considered. Multicomponent analysis may be useful for distinguishing among different

gasolines (Stout et al., 2003) as part of a environmental forensics investigation. A forth reason

for studying multicomponent gasoline composition is that detailed characterization of gasolines

may provide a means to predict the types of potential impacts that may occur. This need results

from the very nature of leaking underground storage tanks: leaks occur unseen and undetected

for years in many cases. It is clearly impossible to go back in time and measure the composition

of the leaked fuel. Knowledge of composition is needed to model or estimate the risks

associated with the release. 
9

Literature and Purpose

The Clean Air Act Amendments (CAAA) of 1990 required the US EPA to develop

oxygenated fuel regulations for cities that failed to meet carbon monoxide ambient air standards.

Beginning in 1992 gasolines sold in these areas were required to contain a minimum of 2.7%

oxygen by weight (Strikkers, 2002). Reformulated gasolines (RFG) which contain oxygenates

and meet other requirements were also mandated by the CAAA for certain ozone non-attainment

areas after January 1, 1995. EPA regulations require that the benzene content of reformulated

fuels be 1.0 % by volume or less when determined on a per gallon basis, or 0.95 % volume or

less on average with a 1.3 % volume maximum per gallon (40 CFR 80, Subpart 41). The oxygen

content must be 2.0 % by weight or more when determined on a per gallon basis, or 2.1 %

weight or more on average with a 1.5 % by weight minimum per gallon (40 CFR 80 Subpart 41). 

A so-called anti-dumping provision mandates compliance in areas using conventional gasoline

with baseline gasoline composition and properties based on 1990 gasoline production. State

requirements, including MTBE bans are given in state laws for California (California Air

Resources Board, 2003), Colorado (Colorado, 2002), and Washington (Washington State, 1996). 

Data on gasoline composition have been collected by several groups. The Canadian

Petroleum Products Institute (1994) performed a survey of Canadian gasolines during winter and

summer of 1993. Their analysis included 44 compounds, which represented a fairly high

fraction of most of the samples. Their study was divided by Canadian provinces, which gives

the study an East/West geographical separation, but they did not report specific octane number

nor elevation of the regular, mid and premium grade samples included in the 128 samples per

season. Only two of the samples contained a significant amount of MTBE.

Other, less intensive, sources of data include the generalized composition reported by

Gustafson et al. (1997), and Environment Canada (Jokuty et al., 1999), which contains six

examples of detailed chemical composition of gasoline among 450 petroleum products and crude

oils in total. Some states perform and publish surveys of gasoline composition which usually

focus on benzene, BTEX and oxygenates (e.g., Maine Department of Environmental Protection,

2005)

U.S. EPA collects certain data on reformulated gasoline including the amount of benzene

and oxygenates (US EPA, 2005). EPA collates data generated by industry collected in summer

and winter surveys. Summaries of the data are available on the EPA web site for the years 1995

to 2003. The surveys may contain as many as 10,000 gasoline retail samples that are collected

during one-week survey periods by the RFG Survey Association (U.S. EPA, 2005). Prior to

1998, the surveys reported only total oxygen and oxygenate content, benzene content, aromatics

content and Reid vapor pressure. In 1998 and subsequent years, the surveys also reported sulfur,

olefins and certain distillation properties. Separately EPA compiles compliance data from

producers and importers. Average values of parameters are available for summer and winter

composition for the years 1997-2002 for both conventional and reformulated gasolines as

national averages.
2

The oil industry uses the terms paraffins to refer to what are otherwise known as alkanes,

olefins for alkenes and alkynes, and naphthenes for cycloalkanes.

10

A voluntary industry consortium produces semiannual Petroleum Product Survey reports

and is based in Bartlesville, Oklahoma. This group collects data on benzene, oxygenates, the

boiling point distribution, vapor pressure, octane number and other properties in annual winter

and summer surveys of U.S. gasolines (e.g., Dickson 2004a, 2004b). These surveys have been

conducted since the 1930s and each may contain data from as many as 800 to 900 samples. 

Winter and summer sampling periods last from December through February for winter samples

and June through August for the summer samples.

The octane number (ON) of a fuel is an important measure of its quality (Strikkers,

2002). The typical octane number of gasolines produced in the 1920s was 40-60. It has

increased since in order to meet performance needs of modern engines, namely to allow higher

compression ratios without pre-ignition of fuel and the resultant engine knock. The octane

number is determined by measuring the combustion efficiency of a fuel in comparison to a

prescribed mixture of isooctane (2,2,4-trimethylpentane) and n-heptane. Of these, the first has

an ON of 100, and the second of 0, because of their ability or lack of ability, respectively, to

prevent fuel pre-ignition. Thus the relative combination of these represents chemicals either

suppressing or enhancing engine knock. The octane number posted at gasoline stations in the

U.S. is an average of the Research Octane Number and the Motor Octane Number, although

many other variations on Octane Number exist and are used for various purposes (Chevron

U.S.A., Inc, 2005). Higher ON is provided to fuel by increased amounts of aromatics, olefins

and iso-paraffins (Strikkers, 2002)2

. In general, branched hydrocarbons and aromatics are more

knock resistant than unbranched paraffins (ASTM, 1958, Meusinger and Moros, 2001). This

characteristic is illustrated in the archetypical octane enhancer 2,2,4-trimethylpentane or

isooctane.

The environmental impacts of fuels depend, in part, on their chemical properties. Data

on chemical properties are available from a variety of sources. There are no “complete” data

sets that include all hydrocarbons of interest. Further, the majority of property data are collected

at temperatures of 25 o

C and data for shallow subsurface temperatures (5 oC to 25 oC) are

unavailable. The International Union of Pure and Applied Chemistry (IUPAC) published two

series of hydrocarbon solubility data (Shaw, 1989a, 1989b) that include hydrocarbons from C5 to

C7 and C8 to C36 , respectively. For some well-studied compounds such as benzene, there were

multiple sets of solubilities reported over a range of temperatures. Depending upon the amount

and quality of the available data, IUPAC evaluated the data and provided recommended, best or

reported values.

Gustafson et al. (1997) developed parameter correlations for solubility, vapor pressure

and other properties based upon the equivalent carbon number of the compound. The

correlations were developed for aromatic and aliphatic constituents of fuels. Use of the

correlations requires estimation of the equivalent carbon number via the boiling point of the
3

SPARC is available at http://ibmlc2.chem.uga.edu/sparc.

11

chemical.

Because recommended values are not available for all desired properties of all chemicals

at all temperatures of interest, estimated properties were used instead. The SPARC Performs

Automated Reasoning in Chemistry (SPARC3

) property estimator (Karikhoff et al., 1991, Hillal

et al., 2003) uses artificial intelligence, molecular structure and large training datasets (8000 data

points) to generate property estimates.

Purpose

The purpose of this study was to generate data on gasoline composition that could be

used as inputs to risk assessment models for ground water or indoor air contamination. The

approach taken was to characterize the chemical composition of gasolines from various locations

around the U.S, using as detailed a method as practical. Unlike the established EPA/Industry

consortia, the purpose here was to collect a much data as possible on the individual chemicals

composing the fuels. This approach was chosen because environmental impacts from fuels

depend on the specifics of their composition and the desire was to evaluate the impacts from the

greatest number of hydrocarbons as possible.
4

Planned future sampling will provide true summer and winter samples and the data

reported here will be combined with the appropriate summer or winter data.

12

Approach and Methods

Gasolines were collected by sampling directly from retail pumps using the following

general protocol. A list of specified brands was used to choose two to four gas stations within a

1 mile to 2 mile radius of each other. Select brands were used because of the possible, but

unlikely, prospect that the petroleum-derived fractions of gasoline were brand specific. The

chosen stations were to be “clean” in appearance to minimize the potential for inclusion of offspec product in the study. Multiple stations were selected to provide close geographic

clustering and, where possible, stations across the street from each other were included. These

were included specifically to test for similarity among different brand names. To avoid mixing

of product in delivery lines, the stations were required to have three separate hoses for

dispensing gasoline. 

The geographic locations that were chosen for the study were intended to include a

mixture of locales using conventional or reformulated gasoline (RFG), locales where ethanol

usage was likely, states with MTBE bans, low and high elevations, rural and urban areas, and a

balance of East and West coast samples (Table 1). The designation of RFG areas was based on

information from EPA that was updated as of February 23, 2004 (US EPA, 2005) and applies to

the specific town or city included (as Federal RFG requirements are not state-wide). A state

winter oxygenate requirement was in effect in Colorado (Colorado, 2002). Other requirements

for gasoline include limitations on Reid vapor pressure and sulfur content in some areas of the

country. Since these two were not included in the measured data, there is no further discussion. 

The varying requirements may, however, cause changes in other components of gasoline that are

included in this study. Information on MTBE bans was provided by the American Petroleum

Institute (API, 2004). 

Summer and winter samples were to be taken. The number of samples was limited by the

available project funding that meant roughly 120 samples in both winter and summer sampling

seasons would be analyzed. Because of several reasons, sampling was delayed and the data

presented in this report were collected between September and November 2004 and thus likely

contain both winter and summer samples.4

 This “autumnal” sample contains 96 samples, most

of which are likely to be winter samples.

Regular and Premium gasoline were dispensed into separate 1 gallon gasoline cans and

transferred to 20 ml scintillation vials. The vials were filled to the bottom of the threading: (1) to

prevent gasoline from flowing over the outside of the vial, (2) to prevent breakage of vials due to

thermal expansion, and (3) to comply with one of the requirements of the small quantity

exceptions to dangerous good shipping under 49 CFR 173.4. The vials were then overnight

shipped in chilled containers for storage in Athens, Georgia. In Athens, samples were then

selected for analysis and shipped to The Cascade Group (TCG) for analysis. All analyses were
13

completed by TCG within two weeks of receiving the samples.

The samples were analyzed by ASTM D 6729-1, a high resolution, gas chromatograph

method. The method uses a 100 meter capillary column and flame ionization detector. This

method was developed for the determination of individual hydrocarbon components of sparkignition engine fuels, including alcohol and ether oxygenated additives, all with boiling points

below 225 o

C. Since a typical gasoline is a mixture of over 400 components, it would be

impractical if not impossible to impose data quality indicators on each analyte of interest.

Therefore, one component from each of the functional groups was tracked to assess the overall

quality of the analytical performance. The laboratory routinely monitored the repeatability and

reproducibility of its analysis. The repeatability was monitored through the use of laboratory

replicates at the rate of one per 10 samples. Reproducibility was monitored through the use of a

quality control sample analyzed at the rate at least one per 15 samples. Potential matrix effects

were monitored by the use of a spiked sample. Every 20th sample was spiked with 1% each of the

following components: Ethlybenzene, MTBE and 2,2,4-Trimethylpentane. The quality control

samples were plotted on individual control charts and the upper and lower control limits were

determined in accordance with laboratory protocols.

Using this method to identify gasoline components relies on retention time. As a result,

there is a possibility of co-elution of some peaks. Although a majority of the hydrocarbons can

be clearly resolved, there is a possibility of co-elution of compounds with olefins above C7. 

Table 2 lists the potentially co-eluting compounds that are identified in ASTM D 6729-1. The

method notes that the list is not exhaustive. Although co-elution raises a potential problem in

interpreting the results, two factors mitigate this problem. First is that ASTM D 6729-1, Table 4,

indicates that one compound is predominant. Of the compounds listed in Table 4, most are not

of specific interest, with the exception of toluene. The second mitigating factor is that the coeluting compounds listed in Table A1.1 of ASTM D 6729-1, are usually present at no more than

1000 ppm (0.1% by mass). Thus reported concentrations of MTBE and ETBE that themselves

are above 0.1 represent likely masses of these chemicals and not the co-eluting chemicals. A

compound that co-eluted with ETBE, Methylcyclopentane, was found to interfere with the ETBE

results from ASTM D 6829-1. Despite any mitigating factors, the nature of the ETBE results, in

particular, requires that confirmation by other means be performed. Confirmation is planned for

future samples and thus the ETBE data were omitted from this report.
14

State Locale(s)

Elevation

Fuel Requirements

MTBE ban

No. of

Samples Regular Premium

California Los Angeles (Huntington Beach,

Irvine)

Low RFG Ye

s

5 3

Colorado Denver High WO Ye

s

3 3

Georgia Athens (Bogart, Watkinsville) Low CG No 4 5

Delaware Dover Low RFG No 3 3

Illinois Chicago (Batavia) Low RFG Ye

s

3 3

Montana Billings, Great Falls, Helena High CG No 6 6

New York Long Island (Centereach, Merrick,

Riverhead)

Low RFG Ye

s

6 6

Ohio Cincinnati Low CG No 3 3

Oklahoma Ada Low CG No 3 3

Pennsylvania/New

Jersey

Philadelphia (Bala Cynwyd, PA,

Pennsehawken, NJ)

Low RFG No 2 3

Texas High Plains (Lubbock, Wolfforth) High CG No 3 3

Virginia Arlington Low RFG Ye

s

4 4

Washington Seattle (Port Orchard) Low GG Ye

s

3 3

Total 48 48

Table 1 Geographic locations, characteristics, and numbers of samples included in the study. 

Elevations less than 2500 ft are judged “low.” Fuel requirements for reformulated gasoline (RFG),

winter oxygenates (WO), and conventional gasoline (CG) are provided on a location by location

basis.
15

Predominant compound Coeluting Compound(s)

Chemical Notes on Co-eluting compound

Co-eluting pairs listed in Table 4 of D 6729 

3,3-dimethylpentane 5-methyl-1-hexane

2-methylhexane C7-olefin

2,5-dimethylhexane C8-olefin

3,3-dimethylhexane C8-olefin

toluene 2,3,3-trimethylpentane if 2,3,3-trimethylpentane > 5 times the

toluene concentration

1,1,2-trimethylcyclopentane C7-triolefin

C8-diolefin C8-paraffin

4-methyloctane C9-olefin

1,2,3,4-tetramethylbenzene C11-aromatic

Co-eluting pairs listed only in notes to table A1.1 of D 6729 

n-propanol 3-methyl-1-pentene usually < 1000 ppm

MTBE 2,3-Dimethyl-1-butene usually < 1000 ppm

MSBE (Methyl sec-butyl ether) 1-hexene usually < 1000 ppm

ETBE 2,3-Dimethyl-1,3-

butadiene

usually < 1000 ppm

isobutanol 4,4-Dimethyl-1-pentene usually < 1000 ppm

Table 2 ASTM D 6729-1 known pairs of co-eluting peaks.

The results included identification of 312 chemicals in gasoline, of these 27 were

identified to only an isomer (i.e., C11-Aromatic, C10-Iso-Paraffin, etc.). Unknown chemicals

were grouped into five categories: unidentified, unidentified-aromatic, unidentified-Iso-Paraffin,

unidentified-naphthenes, and unidentified-olefins. Table 3 identifies the minimum, average and

maximum amounts of each of these categories of unknowns. Of the remaining chemicals in

gasoline, two sets of chemicals were specifically included in the analysis: the first group

included BTEX, trimethylbenzenes and oxygenates, the second included the 44 chemicals used
16

in the Canadian Petroleum Products Institute study of 1993 (Table 4). The remainder of

chemicals were selected from the analyte list of ASTM D 6729-1. In addition the chemicals

were classified by hydrocarbon group (Table 5).

Group Minimum Average Maximum

Unidentified 1.87 3.933 9.987

Unidentified-aromatics 0.004 0.049 0.094

Unidentified-ISO-Paraffins 0.088 0.333 0.584

Unidentified-naphthenes 0.08 0.267 0.801

Unidentified-olefins 0.021 0.082 0.202

Table 3 Percent by weight of unidentified compounds in analytical

results.

Aromatics and Oxygenates Additional CPPI (1994) Study Chemicals

Benzene

Toluene

Ethylbenzene

o-, m-, p-xylene

1,3,5-Trimethylbenzene

1,2,4-Trimethylbenzene

Methanol

Ethanol

t-Butanol

Methyl tert-butyl ether

Di-isopropyl ether

Ethyl-tert butyl ether

Tert-amyl alcohol

Tert-amyl methyl ether

Tert-amyl ethyl ether

1,3 Butadiene

iso-Butane

iso-Pentane

2,2-Dimethylbutane

2,3-Dimethylbutane

2-Methylpentane

3-Methylpentane

2,4-Dimethylpentane

2-Methylhexane

3-Methylhexane

2,2,4-Trimethylpentane

2,4-Dimethylhexane

2,3,4-Trimethylpentane

2,3,3-Trimethylpentane

2,3-Dimethylhexane

3-Methylheptane

2-Methylbutene-1

2-Methylbutene-2

1-Methyl-3-ethylbenzene

1-Methyl-4-ethylbenzene

1-Methyl-2-ethylbenzene

Cyclopentane

Methylcyclopentane

Cyclohexane

Methylcyclohexane

Naphthalene

2-Methylnaphthalene

1-Methylnaphthalene

trans-Butene-2

cis-Butene-2

trans-Pentene-2

cis-Pentene-2

n-Butane

n-Pentane

n-Hexane

n-Heptane

Table 4 Specified chemicals included in the analysis.
17

Group Member

s

Group Member

s

Di/Bicyclo

Naphthenes

1 Naphthenes 4

Di-Olefins 19 Napheheno/OlefinoBenzenes3

Indenes 1 Naphtheno-Olefins 4

Iso-Paraffins 76 n-Olefins 37

Iso-Olefins 53 Oxygenates 12

Mono-Aromatics 48 Paraffins 12

Table 5 Hydrocarbon groups and numbers of member compounds.

SPARC was used to generate estimates of the boiling points, and, for temperatures from

0o

C to 25oC in 5 oC increments, the vapor pressures, infinite dilution activity coefficients, and

solubilities of the chemicals reported in the gasoline samples. Of the 285 chemicals identified in

the analysis, SPARC was able to determine the properties for 281. These values were used in

the assessment of effective solubility and gas phase concentration that follows.
18

Results

The data were evaluated in two ways. The first method was through comparisons of

concentration of single components against the octane number or another component. In almost

all cases scatter plots were used to get a sense of the abundance of various components under

various circumstances. The second set of analyses were performed using the entire suite of

chemicals reported for each sample. Because of the large number of gasoline components,

statistical methods were used: hierarchical cluster analysis (HCA), discriminant analysis (DA),

and principal components analysis (PCA). The results from these analyses provided assessment

of the variation among the gasolines and formed the basis for the decision tree presented below.

Octane Number

Data collection was designed to obtain samples of regular and premium gasolines. The

octane ratings of these fuels vary, largely because of elevation. Lower octane fuels are sold at

higher elevations. Because of larger numbers of low elevation samples, the most common

regular and premium gasoline octane numbers were 87 and 93, respectively (Table 6).

Grade Octane

Number

Conventional Reformulate

d

Total

Regular 85.0 0 3 3

85.5 4 0 4

86 2 0 2

87 15 22 37

87.5 1 0 1

89 0 1 1

Premium 90 2 0 2

91 9 5 14

92 3 1 4

93 9 19 28

Totals 45 51 96

Table 6 Octane ratings of sampled gasolines.
5

The federal FRG mandate on benzene is given in volume percent, as opposed to the

weight percent used for these data.

19

Benzene

The benzene data showed variation at all octane levels (Figure 1). Because of mandates

of the Clean Air Act (CAA), benzene levels in RFG areas were approximately 1% or less5

. In

conventional gasolines benzene varied at levels that were generally between 0.5% and 3% by

weight. The higher levels (greater than 2%) were found over the whole octane range (85.5 to

93). The triangles indicating winter oxygenate and high benzene were from the Colorado

samples, where an wintertime oxygenate requirement is imposed (Colorado, 2002).

84 86 88 90 92 94

Octane Number

0

1

2

3

Benzene (wt %)

Conventional

Reformulated

Winter Oxygenate

Figure 1 Benzene data for RFG and conventional gasoline

locales.
20

Methyl Tert-Butyl Ether

The MTBE concentrations plotted against the benzene concentrations are shown in

Figure 2. The fuels with high MTBE concentrations all occur with benzene concentrations less

than 1%. This follows from requirements of the RFG program where benzene concentrations

must be less than one percent by volume. Five conventional gasoline samples had MTBE

concentrations of 2.8% to 4.2%. These concentrations could be the result of MTBE use as an

octane enhancer, mixing of fuel types, or other reasons. All of these samples, however, were

premium gasolines obtained in Georgia, suggesting the deliberate use of the oxygenate as an

octane enhancer. At benzene concentrations above 1%, all the MTBE concentrations are low

and most of the samples come from conventional gasoline areas.

0123

Benzene (wt %)

0

4

8

12

16

MTBE (wt %)

Conventional

Reformulated

Winter Oxygenate

Figure 2 MTBE and benzene contents for all fuels.

When compared with the octane number (Figure 3), the MTBE concentration appeared to

depend on RFG requirements more than octane number. MTBE is high where RFG

requirements are in place and there is no MTBE ban. Otherwise the MTBE content is fairly low,

with the exception of the Georgia premium samples. 
21

84 86 88 90 92 94

Octane Number

0

4

8

12

16

MTBE (wt %)

Conventional

Reformulated

Winter Oxygenate

Figure 3 MTBE content plotted against octane number.
22

Tert-Butyl Alcohol

Figure 4 shows that the Tert-Butyl Alcohol (TBA) concentrations plotted against MTBE

content of the fuels. All TBA concentrations were about 0.1 % or less. The higher values

occurred with higher MTBE content, indicating some tendency for TBA to increase with MTBE.

0 4 8 12 16

MTBE (wt %)

0

0.2

0.4

0.6

0.8

1

TB

A (wt %)

Figure 4 Tert-Butyl Alcohol (TBA) content plotted

against MTBE content, showing only small amounts of

TBA present in these fuels.
23

Tert-Amyl Methyl Ether

Tert-Methyl Amyl Ether (TAME) was found at only low concentrations (< 1%) in the

fuel samples (Figure 5). 

84 86 88 90 92 94

Octane Number

0

0.2

0.4

0.6

0.8

1

TAME (wt %)

Conventional

Reformulated

Winter Oxygenate

Figure 5 Tert-Amyl Metyl Ether content plotted against

octane number.
24

Oxygen Content

The oxygen content of the fuels was supplied by several compounds including MTBE,

ethanol and ETBE. Small amounts of TAME and DIPE were found in some samples. The total

oxygen content of each sample was calculated by summing the contributions from each

oxygenate. Table 7 lists the fraction of oxygen supplied by each. Because the weight fraction of

oxygen in each additive varies, the amount of the compound needed to meet the RFG

requirements also varies. Because the ETBE data were in doubt, ETBE was omitted from the

results presented in Figure 6. The actual oxygen content of the fuels may be higher than

indicated because this omission.

Oxygenate Number of Atoms Weight

Fraction of

Carbon Oxygen

12 g/mole

Hydrogen

1 g/mole

Oxygen

16 g/mole

Methanol 1 4 1 0.50

Ethanol 2 6 1 0.35

Tert-Butyl Alcohol 4 10 1 0.22

Methyl Tert-Butyl Ether 5 12 1 0.18

Di-Isopropyl ether 6 14 1 0.16

Ethyl Tert-Butyl Ether 6 14 1 0.16

Tert-Amyl Alcohol 5 12 1 0.18

Tert-Amyl Methyl Ether 6 14 1 0.16

Tert-Amyl Ethyl Ether 7 16 1 0.14

Table 7 Oxygen content of each oxygenated additive, based upon the number of

carbon, hydrogen and oxygen atoms per mole of compound.

The oxygen content of these additive were summed and plotted against the benzene

concentration in Figure 6. RFG fuels show oxygen contents above 2 %. The majority of these

had benzene concentrations less than one. Five samples had total oxygen about 3% and had high

benzene concentration (above 1%). These were collected in Denver where state requirements

mandate the oxygen content at this level. Conventional gasoline samples showed oxygen

content below 1%, but not zero. 
25

0123

Benzene (wt %)

0

1

2

3

Oxygen Content (wt %)

Conventional

Reformulated

Winter Oxygenate

Figure 6 Composite weight of oxygen from all oxygenates

and benzene concentrations.
26

Figure 7 shows the oxygen content (wt %) plotted against the octane number for both

reformulated and conventional gasoline locations. This plot also shows that oxygen content is

high in RFG areas and that lesser amounts (< 1%) were found in conventional gasolines.

84 86 88 90 92 94

Octane Number

0

1

2

3

Oxygen Content (wt %)

Conventional

Reformulated

Winter Oxygenate

Figure 7 Fuel oxygen content plotted against octane

number for all samples.
27

Ethanol

Ethanol has replaced MTBE as the principal oxygenate in three states included in the

Study: New York, Illinois, and California. Figure 8 shows the ethanol content in the fuels. The

ethanol content was high only in RFG locales, indicating little incidental presence where an

oxgenate was not required. Figure 9 shows that MTBE and ethanol use were mutually exclusive,

as the presence of one was associated with the absence of the other.

84 86 88 90 92 94

Octane Number

0

2

4

6

8

10

Ethanol (wt %)

Conventional

Reformulated

Winter Oxygenate

Figure 8 Ethanol content plotted against octane number.
28

0 4 8 12 16

MTBE (wt %)

0

2

4

6

8

10

Ethanol (wt %)

Figure 9 Ethanol content plotted against MTBE content

showing the mutual exclusive nature of the usage of these

chemicals.
29

Brand

The gasolines sampled were sold under seventeen brand names. There is little evident

distinction among brands as indicated in Figure 10. This plot indicates that the benzene content

varies over roughly the same range regardless of brand. Other indicators of the lack of

significance of brand were generated by the cluster analysis and the principal components

analysis presented later.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Brand (1 to 17 )

0

1

2

3

Benzene (wt %)

Conventional

Reformulated

Winter Oxygenate

Figure 10 Distribution of benzene by brand.
30

Similarities and Differences Among Gasolines

Cluster Analysis

The chemical analysis determined the composition of the gasolines in terms of

approximately 300 compounds. Since all of these compounds vary from one gasoline to the

next, a cluster analysis using all the available concentration data used to determine which

gasolines were similar. Figure 11 shows the results of a cluster analysis that included only the

samples from Georgia. By including gasolines from only one geographic location, variation due

to elevation and differing regulations are eliminated. Differences may remain due to fuel source

or vendor, and octane number among others. 

The results presented in the figure are drawn as a dendrogram. On the horizontal axis the

sample identification is given. These samples are labeled GA for Georgia, 1,2,3, or 4 for the

station number, 87 or 93 for the octane number and 1,2,3, or 4 for the replicate number. Notice

especially that the samples are separated into two groups differing by octane number, where the

93 octane premium gasolines appear to the left of the center. The vertical axis represents the

degree of similarity between two samples. If two samples were identical then the similarity

would be 100% and they would be connected along the horizontal axis. For these data, no two

samples were exactly the same, so all of the connections occurred at lower levels of similarity. 

These lower levels are plotted inversely on the vertical axis, so that the further a connection is

away from the horizontal axis, the more dissimilar were the samples. Since the samples are all

gasolines, there is ultimately a connection made between all the samples, albeit at a low level of

similarity. 

The cluster analysis grouped the fuels into two clusters which differ by octane number. 

This result was generated by the clustering algorithm acting only on the compositional data and

not the octane data. Two samples (GA-1-93-2 and GA-F-1-93-1) differed only by the fill level

of the sample vials and are nearly identical. The analysis grouped these two samples closest

together of any of the nine at a similarity level of 97.5%. The other three 93 octane samples

were included in the grouping as the similarity level dropped to 77.7%. The 87 octane gasolines

grouped with only each other although generally at lower similarity levels (64.7%). 

Table 8 gives a definition of the clusters in terms of the most prevalent compounds

present at 0.50 wt % or more. In either case a different, but overlapping set, of compounds

defines the centroid of the cluster. The centroid is analogous to that of a physical object, but

here the number of dimensions (chemicals) is much greater than the three dimensions of space. 

Although defining the cluster, this analysis does not determine which compounds differentiate

the clusters. 

One noticeable difference between the regular and premium grades was the MTBE

content. In the regular grade fuel MTBE was present at an average mass percent of 0.52%, while

in the premium fuel MTBE was present at an average mass percent of 3.33%. This indicates that

the MTBE may be purposefully present in these Georgia gasolines as an octane enhancer. A
6

The region includes North Carolina, South Carolina, Georgia, Tennessee, Alabama,

Mississippi, Arkansas, and Louisiana.

31

similar result is found in industry data for their Southeast region6

, Florida and a few other

scattered samples (Dickson, 2004a, 2004b). 

The increased abundance of chemicals of at least 0.50% weight in Georgia premium

grade gasolines compared to regular grades is shown in Table 9. These data show that the

compounds that increase are predominantly iso-paraffins, oxygenates and aromatics. The pure

compound octane numbers from ASTM (1958) are given in the table. Since many of these

compounds are octane enhancers, their octane numbers are generally high (i.e., above that of the

regular grade fuel – 87). Similarly, Table 10 shows the compounds that decreased. These

include paraffins, oxygenates, aromatics and olefins, generally with lower octane numbers.

Figure 11 Dendrogram showing the cluster analysis’ separation of 93 octane (left) from 87

(right) octane Georgia gasolines.
32

87 Octane Cluster 93 Octane Cluster

Toluene 10.3725 Toluene 14.2292

i-Pentane 6.4405 2,2,4-Trimethylpentane 8.4866

m-Xylene 4.3295 i-Pentane 6.108

n-Pentane 4.075 1,2,4-Trimethylbenzene 4.2254

2,2,4-Trimethylpentane 3.477 2,3,4-Trimethylpentane 3.5538

2-Methylpentane 3.3808 Methyl-t-butylether 3.3262

Unidentified 3.2733 m-Xylene 3.246

1,2,4-Trimethylbenzene 2.814 1-Methyl-3-ethylbenzene 2.608

Ethyl-Tert-Butyl-Ethe and

Methylcyclopropane

2.534 Unidentified 2.5376

2-Methylhexane 2.493 n-Pentane 2.2486

o-Xylene 2.3658 2-Methylhexane 2.2142

n-Hexane 2.3655 2-Methylpentane 2.1668

Ethylbenzene 2.236 o-Xylene 1.8414

3-Methylpentane 2.2058 Ethylbenzene 1.53

1-Methyl-3-ethylbenzene 2.0488 p-Xylene 1.5

p-Xylene 1.8975 1,3,5-Trimethylbenzene 1.346

3-Methylhexane 1.7058 2,3-Dimethylbutane 1.287

2,3,4-Trimethylpentane 1.6695 1-Methyl-4-ethylbenzene 1.2142

Benzene 1.4538 3-Methylhexane 1.1952

n-Heptane 1.3763 3-Methylpentane 1.1754

n-Butane 1.2463 2,4-Dimethylhexane 1.0838

2-Methylbutene-2 1.1935 2,2,5-Trimethylhexane 1.0666

2,3-Dimethylbutane 1.0755 2,4-Dimethylpentane 1.0514

Methylcyclohexane 0.9983 2,5-Dimethylhexane 1.032

1,3,5-Trimethylbenzene 0.9268 2,2-Dimethylbutane 1.001

1-Methyl-4-ethylbenzene 0.9265 n-Butane 0.9968

t-Pentene-2 0.8038 2,3-Dimethylhexane 0.9952

1-Methyl-2-ethylbenzene 0.7798 1,2,3-Trimethylbenzene 0.9942

3-Methylheptane 0.7228 1-Methyl-2-ethylbenzene 0.9716

1,2,3-Trimethylbenzene 0.7148 n-Hexane 0.903

2,4-Dimethylpentane 0.7038 Ethyl-Tert-Butyl-Ether and

Methylcyclopropane

0.8538

n-Propylbenzene 0.701 n-Heptane 0.8476

1,2-Dimethyl-4-ethylbenzene 0.664 Benzene 0.822

n-Octane 0.6523 2-Methylbutene-2 0.8168

2-Methylheptane 0.6495 n-Propylbenzene 0.8078

Cyclohexane 0.6065 1,2-Dimethyl-4-ethylbenzene 0.678

2-Methylbutene-1 0.5715 1-Methyl-3-n-propylbenzene 0.6678

1-Methyl-3-n-propylbenzene 0.5595 t-Pentene-2 0.6048

2,4-Dimethylhexane 0.5475 1,3-Dimethyl-5-ethylbenzene 0.5464

2,3-Dihydroindene 0.5383 TAME 0.5064

2,3-Dimethylhexane 0.5208

Methyl-t-butylether 0.5188

Table 8 Cluster centroids in weight % for Georgia 87 octane and 93 octane gasolines

defined by all components present at 0.50 wt % or greater.
33

Chemical Pure Chemical

Octane Number

 ( R + M )/2 

Increase in wt %

Regular to

Premium

2,2,4-Trimethylpentane 100 5.0096

Toluene 118 3.8567

Methyl-t-butylether 147 2.8074

2,3,4-Trimethylpentane 99.5 1.8843

1,2,4-Trimethylbenzene 136 1.4114

2,2,5-Trimethylhexane 89.5 0.5923

2,2-Dimethylbutane 93 0.5725

1-Methyl-3-ethylbenzene 150 0.5592

2,4-Dimethylhexane 69 0.5363

2,5-Dimethylhexane -- 0.5175

Table 9 Compounds that were present in greater abundance in Georgia

premium than regular grades by at least 0.50 wt %. Octane Number data

were taken from ASTM (1958).

Chemical Pure Chemical

Octane Number 

( R + M )/2

Decrease in wt% 

Regular to

Premium

n-Pentane 64 -1.8264

Ethyl-Tert-Butyl-Ether and

Methylcyclopropane

-- -1.6802

n-Hexane 20.5 -1.4625

2-Methylpentane 80 -1.214

m-Xylene 134.5 -1.0835

3-Methylpentane 83 -1.0304

Unidentified -- -0.7357

Ethylbenzene 115.5 -0.706

Methylcyclohexane 94 -0.6909

Benzene 94 -0.6318

n-Heptane 0 -0.5287

o-Xylene 111 -0.5244

Table 10 Compounds that were present in lesser abundance in Georgia premium gasolines than

in regular grades by at least 0.50 wt %. Octane Number data were taken from ASTM (1958).

The similarity of three conventional, low elevation, gasolines were tested by performing

a cluster analysis of Georgia, Ohio and Oklahoma gasolines (Figure 12). These samples are

designated by state code, station number (1,2,3,4), octane number (87 or 93) and replicate

sample number (1,2,3,4). The 87 octanes are clustered with each other on the left most side of

Figure 12. The regular grade samples all cluster at 80.05% similarity, while the two main

subclusters (samples GA-1-87-2, GA-2-87-3 and GA-3-87-3 form the leftmost cluster) both join

at a similarity level of around 85%. The premium grade samples group into three clusters, the
34

first contains the Georgia samples only. The second and third, while containing one location

each, also show lower levels of similarity, 71% and 82%, respectively. This indicates that there

is more variability among the premiums than among the regulars, because the premiums fail to

cluster together. The poor clustering of the premium samples is partly due to the appreciable

MTBE contained in the Georgia premium samples which is absent in those from Ohio and

Oklahoma. The MTBE content is the most obvious difference between the fuels but others exist. 

The Ohio and Oklahoma samples themselves display variation because of their low level of

similarity where they cluster. The complete separation by grade in Figure 12, however, shows

that the 87 octane and 93 octane gasolines are more similar to each other than fuel of the

opposite grade from the same location. 

Figure 12 Dendrogram showing relationship between regular and premium gasolines from 

conventional gasoline areas in Georgia, Ohio and Oklahoma.

The degree of similarity of the premium grades in the entire data set versus that of the

regular grades was assessed through a cluster analysis of each location’s samples only (similar to

the analysis of Georgia gasolines presented in Figure 11). In the majority of locations the

regular gasolines were more similar to each other than were the premiums. Table 11 shows the

degree of similarity where all samples of a given grade join together. These values are the

minimum degree of similarity where all samples of a given grade have joined into a cluster. In
7

The regular grade and premium grade samples from one of the Montana gas stations

joined the cluster of the opposite grade. It is possible that these samples were mislabeled when

sampled or that wrong fuel had been delivered to the tanks at the station.

35

three locales (California, Colorado, and Texas High Plans), there was not good separation

between the regular and premium grades. In all other cases the two grades formed distinct

clusters.7

 On average the regular grade gasolines tended to cluster at higher degrees of similarity

than did the premiums, meaning that the regular grade fuels were more similar to each other than

were the premiums. This result suggests that refiners may be using a variety of approaches to

boosting the octane numbers of the premium fuels.

Locale Degree of Similarity

at Complete Joining

Premium Samples

Joined to Regular

Clusters

Regular

(%)

Premium

(%)

California 55.72 43.87 2 of 3

Colorado 47.98 43.59 2 of 3

Delaware 56.94 82.42 --

Georgia 64.70 77.76 --

Illinois 79.35 61.91 --

Montana 87.44 62.36 1 of 6

New York 60.51 67.72 --

Ohio 66.96 48.37 --

Oklahoma 84.69 80.58 --

Pennsylvania 84.10 21.94 --

Texas High Plains 32.60 32.38 2 of 3

Virginia 38.77 50.04 --

Washington 38.77 37.59 --

Average 64.44 54.66

Standard Deviation 17.86 19.18

Table 11 Degree of similarity where all fuels of a given grade join in cluster analyses of individual

locales (states).
36

High elevation samples from Montana and the Texas High Plains are shown in Figure 13. 

The two states’ samples do not join in common clusters. Further, four of the six Texas samples

cluster together despite differences in grade, while one premium sample (TX-1-90-2) remains

separate from all other samples until the lowest degree of similarity is attained.

Figure 13 Dendrogram showing relationship between high elevation areas in Lubbock, Texas

and Helena, Billings and Great Falls, Montana.

A comparison of reformulated and conventional gasolines is given in Figure 14 by

comparing the Georgia gasolines with RFG gasolines from Northern Virginia. Clustering of the

Georgia gasolines is the same as shown previously in Figure 11. Four distinct clusters were

found in the data. In addition to the two Georgia clusters, the Virginia gasolines formed two

grade-dependent clusters. Thus the two different clusters of Virginia gasoline are more similar

to each other than they are to the Georgia gasolines. The 93 octane Virginia cluster has a sample

(VA-4-93-4) that is unlike the others and only joins the cluster at a low level of similarity

(59.0%).
8

The Delaware 89 octane sample (DE-1-89-2) may represent fuel mislabeled by the

retailer. 

37

Figure 14 Dendrogram showing relationships between conventional gasolines from Georgia and

RFG gasolines from Virginia.

Figure 15 compares gasolines from low elevation, RFG, non-MTBE ban areas in

Arlington, Virginia, Dover, Delaware, and Philadelphia, Pennsylvania. These gasolines separate

along grade lines first8

. The regular gasolines form two distinct clusters: one composed of the

Virginia gasolines and the other composed of the Dover, Delaware and Philadelphia gasolines. 

Notably Dover and Philadelphia are close geographically and may consequentially receive

similar gasolines. The premium gasolines show similar behavior with a lessened tendency for

clustering. The samples VA-4-93-4 and PA-3-93-4 join together but were not sold under the

same brand name.
38

Figure 15 Analysis of three RFG areas without MTBE bans.

Three Federal RFG states in the study have banned MTBE: New York, Illinois and

California. To compare gasolines from MTBE-ban states with others, a cluster analysis was

performed on the data from Virginia, Pennsylvania and New York. Figure 16 shows that the

New York data is separate from the Pennsylvania and Virginia data. Beginning from the left of

Figure 16, the New York 87 octane gasolines cluster, followed by the New York 93 octane

gasolines. These two clusters join together at a similarity of 71.0%, before they join with the

clusters from Virginia and Pennsylvania. The data from these two states tend to cluster with

themselves before joining the other state. Even so they join each other at higher levels of

similarity, before joining with the corresponding gasoline grades from New York.
39

Figure 16 Dendrogram of RFG gasolines from an MTBE-ban state (New York) and two states

without bans. 

The MTBE-ban states and locales with RFG requirements (state or Federal) are

compared in Figure 17. The highest similarity between samples occurred for two California

gasolines (CA-3-87-2 and CA-4-87-2). Other California gasolines tended to cluster, but two

high octane gasolines were included with the 87 octane fuels. A high degree of similarity

occurred with the New York gasolines for both 87 octane and 93 octane gasolines. Some of the

Illinois and Colorado samples were grouped with the 87 octane New York gasolines. The

Illinois 93 octane samples were similar at a fairly low level (69.5%). Two of the Colorado high

octane samples (CO-2-91-1 and CO-3-91-1) grouped with the composited 87 and 93 octane

clusters formed largely by the New York samples. Since the Colorado samples were taken from

high altitude, and Colorado has specific state RFG requirements, the samples’ lack of similarity

with the other locales should not be unexpected.
40

Figure 17 Dendrogram of MTBE-ban states with State or Federal RFG requirements.

Figure 18 shows a cluster analysis of New York and Illinois samples. These both come

from states with MTBE bans, low elevation, and RFG requirements. The New York samples

form a cluster, that at lowered levels of similarity, are joined by the Illinois samples. The

premium gasolines from New York cluster with these regular gasolines at higher levels of

similarity than they do with the Illinois premiums. Again this result suggests a low level of

similarity among the premium grade samples.
41

Figure 18 Dendrogram showing relationship between two MTBE ban, RFG gasoline areas. 

Principal Components Analysis

The basic goal of principal component analysis (PCA) is to reduce the dimensionality of

a multivariate data set consisting of a large number of variables, while capturing as much of the

variation as possible in the data set. PCA is a mathematical technique that transforms a number

of potentially correlated variables into a small number of uncorrelated variables called principal

components (PC). The first PC accounts for as much of the variability in the data as possible,

and each succeeding PC accounts for as much of the remaining variability as possible (Kendall

1975, Jolliffe 2002). Further background information on PCA is given in an Appendix (page

79). The PCA performed on the gasoline data served two purposes. First it complimented the

results from the cluster analysis by indicating which groups of samples were similar to each

other. Second, it gave information on the components that had the biggest influence on the

groupings.

Results of the PCA on the individual gasoline components are presented in Table 12. 

Only 8 PC were required to account for 95 percent of the variation in the gasoline samples. The

total variance estimate of the gasoline components was found to be 87.53. The first two PC

accounted for almost 60 percent of the variation of the gasoline components. A plot of the

cumulative proportion of variation explained by PC number is given in Figure 19. The figure
42

shows that between 99 and 100 percent of the variation in the gasoline components can be

explained by 16 and 33 PC, respectively. A scree diagram is a plot of the variance of each PC

against the PC number, p (the rank importance of the PC, see page 79 for more information). 

Figure 20 contains the scree plot of the variance estimates by PC number which shows that the

variance estimates decrease rapidly until approximately the tenth PC. Beyond this point there

was little change in the variance estimates.

PC

Varianc

e

Proportio

n Cumulative

1 29.493 0.337 0.337

2 20.652 0.236 0.573

3 16.408 0.188 0.760

4 8.574 0.098 0.858

5 3.189 0.036 0.895

6 2.522 0.029 0.924

7 1.376 0.016 0.939

8 1.169 0.013 0.953

Table 12 Statistics of the first eight PC from the PCA of the individual

gasoline components including variance, proportion of the total variance

estimate, and the cumulative proportion of variation explained.
43

Figure 19 Plot of the cumulative proportion of variation explained by PC number.

Figure 20 Scree graph of the variance estimate by PC number for the individual gasoline

component data.
44

The largest loadings from the eight PC indicate which components contribute the most to

the variation (Table 13). Table 13 shows that the gasoline component corresponding to the

largest absolute loading in the first PC was 2,2,4-Trimethylpentane. This component also had

the largest standard deviation (rank =1) among all of the gasoline components analyzed. From

Table 13 we can also see that those gasoline components with the largest coefficients

consistently had the largest standard deviations. Thus, the eight gasoline components presented

in Table 13, represent those components which contributed the most to the variation among the

gasoline samples. As discussed below, the first two principal components were dominated by

2,2,4-Trimethylpentane (isooctane) and MTBE, representing the influence of octane number and

oxygenated additives, respectively.

PC Gasoline Component Class Mean Std. Dev.

Rank Std.

Dev.

1 2,2,4-Trimethylpentane Iso-Paraffins 5.62 4.60 1

2 Methyl-t-butylether Oxygenates 2.31 4.07 2

3 Toluene Mono-Aromatics 8.15 3.35 4

4 Ethanol Oxygenates 2.28 3.36 3

5 2-Methylhexane Iso-Paraffins 3.56 2.34 5

6 Unidentified1 3.93 1.60 7

7 n-Butane Paraffin 2.50 1.11 10

8 n-Pentane Paraffin 2.74 1.40 8

Table 13 Gasoline components with the largest loadings in the first eight principal components

including class, mean, standard deviation, and the rank of the standard deviation (from largest

(1) to smallest(8)).

A plot of the first two principal components labeled by state is given in Figure 21. From

the figure it can be seen that marked differences exist among the states, with the data falling into

roughly five clusters. Samples from Virginia, Pennsylvania/New Jersey, and Delaware were

concentrated at the bottom of the graph. These fuels are all low elevation RFGs relying on

MTBE for their oxygen content. Georgia premiums lay in the middle of the graph. As

previously noted, these conventional gasolines contained MTBE presumably as an octane

enhancer. At a level of the 2nd principal component of about 0 to 2, a large group of samples

form a thin band. These included the majority of the conventional gasolines. At a level of 3 to

5, a thin band was distinguished by the four locations with RFG requirements and MTBE bans. 

These gasolines shared the common characteristic of low MTBE concentration and ethanol use

to meet their oxygen requirement. The last separate cluster consisted of gasolines from

Colorado, that were under an oxygenate requirement. The 2nd principal component can be

identified with the the two dominant components that supply oxygen in the fuels: MTBE which

is at a maximum at the bottom and ethanol which is at its maximum at the top of Figure 21.
45

Marked differences appeared between the octane levels (Figure 22). With a few

exceptions, the octane numbers fell into two classes, 87.5 or lower and 90 or above. The regular

gasolines (87.5 or below) were grouped to the right of the value of about 3 on the horizontal axis,

while the premium gasolines (90 or above) levels fell to the left of this value. The first principal

component was most highly influenced along its negative axis (toward high octane fuels) by

2,2,4-Trimethylpentane (isooctane) and other iso-paraffins. In the positive direction (toward low

octane fuels) it was influenced most strongly by paraffins and a variety of compounds of the

other classes. Isooctane had the strongest influence of any chemical on this principal

component. The mean values 2.78 and 8.46 % were for the 87.5 or lower and 90 or above octane

groups, respectively. The dominance of isooctane explains the ability of this principal

component to separate the octane classes. Isooctane is neither the only chemical that influences

the octane number, nor the principal component. Thus there was not a direct relationship

between the principal component and the octane numbers.

A plot of the first two principal components labeled by gasoline brand is given in Figure

23. No obvious patterns can be detected among the 17 brands under which the gasolines were

sold.
46

Figure 21 Principal Components plot of the 96 gasoline samples with respect to the first two principal compone
47

Figure 22 Principal Components plot of the 96 gasoline samples with respect to the first two principal componenumber. 
48

Figure 23 Plot of the 96 gasoline samples with respect to the first two principal components by gasoline brand.
49

Discriminant Analysis

A step-wise discriminant analysis was used to determine which chemical components

were most powerful in distinguishing among the samples (see Rencher, 1995). The analysis tests

the statistical level of significance of each variable and determines if it contributes to

discriminating among the samples. The results of this analysis are shown in Table 14. The

significance level was high for RFG/Conventional gasoline, MTBE ban, grade, elevation and

altitude. It was low for all factors taken together and brand. Thus gasolines having the same

values for the characteristics and a high significance level are expected to separate well based on

composition. Two clear compositional indications emerged: for distinguishing an MTBE ban

gasoline, the most important chemical was ethanol. This follows from the substitution of ethanol

for MTBE in CA, CO, IL and NY. Ethanol and MTBE were most important for distinguishing

RFG from conventional gasolines, clearly because of their usage as oxygenates.

Group Tested Significance 

Level

Number of

Components

Required

Five Most Significant

Components

All 0.59 18 Methyl-t-butylether

Ethanol

n-Hexane

3t-Ethylmethylcyclopentane

n-Pentadecane

RFG/Conventional

gasoline

0.99 19 Ethanol

Methyl-t-butylether

1c,2t,4-Trimethylcyclopentane

C9-Olefin4

o-Xylene

MTBE Ban (y/n) 0.96 20 Ethanol

n-Pentadecane

3t-Ethylmethylcyclopentane

C10-Isoparaffin2

3,4-Dimethylpentene-1

Brand (17) 0.40 22 3,5,5-Trimethylhexene-1

1-Methyl-3-n-propylbenzene

1t-M-2-(4-MP)cyclopentane

n-Pentadecane

2,3,3-Trimethylbutene-1

Grade (<89, >90) 0.95 23 Ethyl-Tert-Butyl-Ether and

Methylcyclopropane

4-Methylnonane

n-Hexane

2-Methylindan

1t,3-Pentadiene

Altitude (H/L) 0.94 23 C11-Isoparaffin2

i-Propylbenzene

2,2-Dimethylpropane

Benzene

2-Methylbutene-1

Table 14 Discriminant analysis results.
50

Representative Gasolines

Figure 24 shows a decision tree that represents four characteristics of the fuels: grade,

sale elevation, MTBE ban status, and legal requirements. The latter include the federal

reformulated gasoline mandate, state requirements (as the California RFG requirement, or

Colorado winter oxygenate requirement) and, alternatively, conventional gasoline. These

provide a potential means for dividing or grouping samples. For a given grade of gasoline there

are 12 branches which may represent 12 or more types of gasoline because of the number of state

requirements. Seven of the branches were represented in this study. In all cases more data

would be desirable to increase the number of samples in each category.

Division of the data by the characteristics is supported to some degree by the statistical

analyses. These provide a scientific basis for what appear to be logical groupings. The

discriminant analysis supported division by grade, elevation, MTBE ban and RFG requirement

as these were found to be factors that provided a high degree of reliability of discriminating

between samples. The principal components analysis supported division by grade and combined

MTBE ban status and RFG requirements. The cluster analysis generally supports division by

grade, RFG requirement, and MTBE ban status, though not elevation. Because it was performed

on subsets of the data, the cluster analysis showed that the premium gasolines were more

variable than the regular gasolines. 

Figure 24 indicates where the data are likely to be best grouped together. At the ends of

the decision tree, parenthesis around state names indicate that the cluster analysis indicated

similarity. All of these are not clear cut, and other judgements could be made to separate or join

data together. One argument in favor of grouping data together at the end of each branch of the

decision tree is that the variability will be maximized by this procedure. Risk assessments

relying on typical data, such as these, should include the maximum range of variability that

might occur. 
51

Grade Elevation MTBE Ban

Status

Legal Requirements

Premium > 3000 ft ban Federal RFG

State Requirement CO

Conventional

no ban Federal RFG

State Requirement

Conventional (TX), (MT)

< 3000 ft ban Federal RFG (NY), (IL)

State Requirement CA

Conventional WA

no ban Federal RFG (VA), (DE, PA)

State Requirement

Conventional (GA), (OH), (OK)

Regular > 3000 ft ban Federal RFG

State Requirement CO

Conventional

no ban Federal RFG

State Requirement

Conventional (TX), (MT)

 < 3000 ft ban Federal RFG (NY, IL)

State Requirement CA

Conventional WA

no ban Federal RFG (VA, DE, PA)

State Requirement

Conventional (GA, OH, OK)

Figure 24 Decision tree for gasolines typical of the data collected in this study. The parenthesis

indicate where the cluster analysis indicated that samples from the various states are similar

enough to group together.
52

Cluster Analysis

The degree-of-similarity of the representative gasolines was tested by performing a

cluster analysis. Figure 25 shows the results from averaging all samples at each branch of the

decision tree. For the maximum differentiation between the representative gasolines, ideally the

clustering would be at low levels of similarity. The identification of these data are: RFG –

N/Y/Y-State, MTBE ban – Y/N, grade R/P, elevation H/L. A few clear indications emerged

from this figure. Beginning on the right hand side, the low elevation, RFG, grades join at a low

level of similarity (Y-N-R-L and Y-N-P-L). Some RFG gasolines do not cluster well with

others: YS-Y-P-H and Y-Y-P-L. The remaining categories showed a fairly low level of

similarity for the most part, with the exception of the N-N-R-H and N-Y-R-L samples which join

at a level of similarity (85%) that was judged to be favorable for individual samples. 

Figure 25 Cluster analysis performed on the representative gasolines.
9

In addition to the specific chemicals, 5 groups of unknowns and 30 groups of

generalized composition were reported. 

53

Predicted Environmental Impacts of the Study Fuels on Water and Air

From an environmental contamination perspective, fuel composition is most relevant for

soil contamination where the fuel itself is contained within the sample. Ground water and soil

gas contamination are equally important, but the relevance of each compound depends on its

abundance in the fuel and its properties.

Raoult’s Law partitioning relationships were used to determine the equilibrium

concentration of each chemical in air and water at 15 o

C (Schwarzenbach et al., 2003). 

(1)

where Sei is the effective solubility of chemical i resulting from the gasoline mixture [mg/L], xi

 is

the mole fraction of chemical i in the mixture [moles/moles], and Si

 is the solubility of chemical i

[mg/L]. Similarly the effective vapor pressure due to the presence of the chemical in the mixture

are given by Raoult’s Law

(2)

where Pei is the partial pressure of chemical i resulting from the gasoline mixture [atm], xi

 is the

mole fraction of chemical i in the mixture [moles/moles], and VPi

 is the vapor pressure of

chemical i [atm].

Because solubility and vapor pressure data are not available for all hydrocarbons at all

temperatures of interest and because there exists considerable variability in literature values, the

SPARC Performs Automated Reasoning in Chemistry (SPARC) calculator was used to estimate

all properties used in the analysis. SPARC estimates are generally viewed to be within one-third

to one-half log unit of true values. Thus the SPARC estimates may differ from commonly used

estimates of some parameters. SPARC recognized 292 of the 296 chemicals with CAS numbers

in the data set.9

 The disadvantages of SPARC were outweighed by the advantage of having a

consistent set of parameters for all chemicals at all temperatures of interest (0 o

C to 25 oC). The

mole fractions, xi, were calculated from the mass fractions, mi, by

(3)
54

and using the gram-molecular weights, gmwi

 [g/mole]. Equation 3 was used by assuming a

sample size of 1g of gasoline. From this mass the number of moles of each identifiable chemical

was determined, summed and used to calculate the mole fractions. Chemicals that were

unidentified were omitted from the calculation, so the results gave an approximation of the true

mole fractions. 

Gas phase concentrations, Ca, that would be associated directly with the fuel were

calculated from equations 2 and 3, and the ideal gas law:

(4)

where R is the gas constant, 8.205 x 10-5 atm - m3/mole oK, and T is the temperature in Kelvin.

Predicted Aqueous Concentrations

Figure 26 shows a plot of the effective solubility of each chemical, labeled by group

(oxygenate, BTEX, parafins, etc), and plotted against the weight % in the sample. The data were

the average conventional gasoline, no MTBE ban, low elevation, regular grade samples. Only

solubilities above 0.001 mg/L were plotted as any lower values would be below typical detection

limits. The plotting position on this graph indicates the partitioning behavior of the compound. 

For example, compounds plotting at the lower right (high weight % and low effective solubility)

are present in large quantities in the fuel but have little impact on water quality. Conversely, the

plotting in the upper right are compounds with high effective solubility and abundance in the

fuel. These are the major components of fuel that do potentially impact water quality. 

The highest effective solubilities (10 mg/L to 100 mg/L) occurred for oxygenates and

BTEX (Figure 26). In the next lower group (1 mg/L to 10 mg/L) were representatives of all the

remaining groups. Many hydrocarbons plot lower in effective solubility (less than 1 mg/L) and

also occur at low weight percent.

Similar results for the average no-MTBE-ban, low-elevation, regular-grade, reformulated

gasoline are shown in Figure 27. Here MTBE had the highest effective solubility, again

followed by BTEX and oxygenates in the 10 mg/L to 100 mg/L range. Table 15 shows predicted

concentration increases greater than 0.05 mg/L between conventional gasoline and RFG. The

compounds with the highest increases are all oxygenates, followed by naphthenes and olefins. 

Table 16 shows the corresponding decreases in concentration. The compounds with the largest

decreases are BTEX, and mono-aromatics, followed by a few paraffins, an iso-paraffin and diolefins.

If an MTBE ban were introduced, gasoline composition might be similar to the data

obtained from the Illinois samples. The average effective solubility of chemicals in the average
55

Illinois sample are plotted in Figure 28. The highest effective solubility was found for ethanol,

followed by a similar pattern for the other fuels. For this potential change in fuel, there are a

smaller number of chemicals with increased effective solubility (Table 17), including the

alcohols and benzene along with two paraffins and an iso-paraffin. Compounds with decreased

effective solubility (Table 18) are the ether oxygenates, BTEX other than benzene, and a suite of

other compounds including n-olefins, iso-olefins and other compounds.

0 4 8 12

Mass Percent in Fuel

0.001

0.01

0.1

1

10

100

1000

10000

100000

Effective Solubility (mg/L)

Oxygenates

BTEX

Other Aromatics

Naphthenes (all)

Paraffins 

Iso-Paraffins

n Olefins

Iso Olefins

Di-Olefins

Conventional, No MTBE Ban, Low Elevation, Regular Grade

Figure 26 Effective solubility of hydrocarbon groups and oxygenates for the average

conventional, low-elevation, no-MTBE-ban, regular gasolines.
56

0 4 8 12

Mass Percent in Fuel

0.001

0.01

0.1

1

10

100

1000

10000

100000

Effective Solubility (mg/L)

Oxygenates

BTEX

Other Aromatics

Naphthenes (all)

Paraffins

Iso-Paraffins

n-Olefins

Iso-Olefins

Di-Olefins

RFG, No MTBE Ban, Low Elevation, Regular Grade

Figure 27 Effective solubility of hydrocarbon groups and oxygenates for the average

reformulated, low-elevation, no-MTBE-ban regular gasolines.
57

Class Chemical Change in Concentration (mg/L)

Oxygenates Methyl-t-butylether 1580

Oxygenates t-Butanol 42.2

Oxygenates TAME 4.89

Oxygenates 2-Butanol 4.70

Oxygenates n-Butanol 3.80

Oxygenates i-Propanol 3.78

Oxygenates n-Propanol 2.92

Oxygenates i-Butanol 1.59

Naphtheno-Olefins 1-Methylcyclopentene 0.50

Naphtheno-Olefins Cyclopentene 0.48

n-Olefins t-Butene-2 0.33

Iso-Olefins 2-Methylbutene-2 0.27

n-Olefins t-Pentene-2 0.26

n-Olefins c-Butene-2 0.25

Mono-Naphthenes Cyclopentane 0.15

n-Olefins c-Pentene-2 0.11

n-Olefins Butene-1 0.09

Naphtheno-Olefins Cyclohexene 0.07

n-Olefins t-Hexene-2 0.06

Iso-Olefins 2-Methylpentene-2 0.06

Table 15 Predicted higher aqueous constituent concentrations (>0.05 mg/L)

of RFG (regular grade, no-MTBE-ban, low-elevation) in comparison to

conventional gasoline.
58

Class Chemical Change in Concentration (mg/L) 

Mono-Aromatics Toluene -17.80

Mono-Aromatics Benzene -17.80

Mono-Aromatics m-Xylene -2.16

Mono-Aromatics o-Xylene -1.58

Mono-Aromatics Ethylbenzene -1.00

Mono-Aromatics p-Xylene -0.90

Paraffin n-Butane -0.83

Iso-Paraffin i-Pentane -0.74

Mono-Aromatics 1,2,4-Trimethylbenzene -0.52

Mono-Aromatics 1-Methyl-3-ethylbenzene -0.25

Paraffin n-Pentane -0.19

Mono-Aromatics 1,2,3-Trimethylbenzene -0.16

Mono-Aromatics 1-Methyl-2-ethylbenzene -0.16

Di-Olefins 2-Methyl-1,3-Butadiene -0.13

Mono-Aromatics 1,3,5-Trimethylbenzene -0.12

Mono-Aromatics 1-Methyl-4-ethylbenzene -0.11

Mono-Aromatics n-Propylbenzene -0.09

Di-Olefins 1c/t,4-Hexadiene -0.07

Di-Olefins 1t,3-Pentadiene -0.06

Table 16 Predicted lower aqueous constituent concentrations (>0.05 mg/L)

of RFG (regular grade, no MTBE ban, low elevation) in comparison to

conventional gasoline.
59

0 4 8 12

Mass Percent in Fuel

0.001

0.01

0.1

1

10

100

1000

10000

100000

Effective Solubility (mg/L)

Oxygenates

BTEX

Other Aromatics

Naphthenes

Paraffins

Iso-Paraffins

Olefins

Iso-Olefins

Di-Olefins

RFG, MTBE Ban, Low Elevation, Regular Grade

Figure 28 Effective Solubility for hydrocarbon groups and oxygenates for the Illinois

regular gasolines (low elevation, MTBE ban, RFG).
60

Class Chemical Change in Concentration (mg/L)

Oxygenates Ethanol 61080

Oxygenates i-Butanol 2.69

Mono-Aromatics Benzene 2.57

Paraffin n-Butane 1.47

Iso-Paraffins i-Pentane 0.60

Paraffin n-Pentane 0.39

Table 17 Predicted higher aqueous constituent concentrations (>0.05

mg/L) of MTBE-ban RFG (regular grade, low elevation) in comparison

to non-MTBE ban RFG gasoline.
61

Class Chemical Change in

Concentration (mg/L)

Oxygenates Methyl-t-butylether -1606

Oxygenates t-Butanol -44.28

Mono-Aromatics Toluene -10.26

Oxygenates TAME -5.36

Oxygenates 2-Butanol -4.70

Oxygenates n-Butanol -3.94

Oxygenates i-Propanol -3.78

Oxygenates n-Propanol -2.92

Mono-Aromatics m-Xylene -1.73

Mono-Aromatics o-Xylene -1.16

Mono-Aromatics Ethylbenzene -1.05

Mono-Aromatics p-Xylene -0.73

Naphtheno-Olefins Cyclopentene -0.45

n-Olefins c-Butene-2 -0.44

n-Olefins t-Butene-2 -0.41

n-Olefins t-Pentene-2 -0.33

Iso-Olefins 2-Methylbutene-2 -0.32

Naphtheno-Olefins 1-Methylcyclopentene -0.28

Mono-Aromatics 1,2,4-Trimethylbenzene -0.26

Mono-Aromatics 1-Methyl-3-ethylbenzene -0.20

n-Olefins c-Pentene-2 -0.17

Mono-Naphthenes Cyclopentane -0.16

n-Olefins Pentene-1 -0.15

Iso-Olefins 2-Methylbutene-1 -0.14

Mono-Aromatics 1-Methyl-2-ethylbenzene -0.11

Indenes 2,3-Dihydroindene -0.10

Mono-Aromatics 1,2,3-Trimethylbenzene -0.09

Mono-Aromatics 1-Methyl-4-ethylbenzene -0.07

Di-Olefins 2-Methyl-1,3-Butadiene -0.07

Mono-Aromatics 1,3,5-Trimethylbenzene -0.07

Iso-Paraffins 3-Methylpentane -0.07

Iso-Paraffins 2-Methylpentane -0.06

Iso-Olefins 2-Methylpentene-2 -0.06

n-Olefins t-Hexene-2 -0.06

Di-Olefins 1t,3-Pentadiene -0.06

Table 18 Predicted lower aqueous constituent concentrations (>0.05 mg/L) of

MTBE-ban RFG (regular grade, low elevation) in comparison to non-MTBE ban

RFG gasoline.
62

Predicted Gas Phase Concentrations

The predicted gas phase concentrations resulting from direct contact between the fuel and

air for the average conventional, no-MTBE-ban, low-elevation, regular-grade gasoline are shown

in Figure 29. The highest concentrations (greater than 100 mg/L) were found from paraffins and

iso-paraffins. In the next lower category (10 mg/L to 100 mg/L) are more paraffins, n-olefins,

and iso-olefins. BTEX and other classes of compounds appear between 1 mg/L and 10 mg/L.

Figure 30 shows the average gas phase concentrations from the similar RFG, no-MTBEban samples. The main, obvious difference in the plots is the presence of MTBE at high weight

% and high concentration. Tables 19, 20 , and 21 show the increased and decreased gas phase

concentrations for a shift from conventional to RFG fuel. MTBE, and a variety of iso-olefins

have increased concentration, while various aromatics and others decrease.

Concentrations for Illinois samples (MTBE ban) are shown in Figure 31. The general

pattern shown is similar to the other fuels. Ethanol has a lowered concentration compared to

MTBE. Concentrations that increase (Table 22) are ethanol and several iso-paraffins, indicating

a need to increase the octane number, among others. Decreasing (Tables 23 and 24)

concentrations were noted for MTBE and a variety of other compounds.
63

0 4 8 12

Mass Percent in Fuel

0.001

0.01

0.1

1

10

100

1000

Gas Phase Concentration (mg/L)

Oxgenates

BTEX

Other Aromatics

Naphthenes (all)

Paraffins

Iso-Parafins

n Olefins

Iso-Olefins

Di-Olefins

Conventional, No MTBE Ban, Low Elevation, Regular Grade

Figure 29 Gas phase concentration of hydrocarbon groups and oxygenates for the

average conventional, low-elevation, no-MTBE-ban regular gasolines.
64

0 4 8 12

Mass Percent in Fuel

0.001

0.01

0.1

1

10

100

1000

Gas Phase Concentration (mg/L)

Oxygenates

BTEX

Other Aromatics

Naphthenes (all)

Paraffins

Iso-Paraffins

n Olefins

Iso Olefins

Di-Olefins

RFG, No MTBE Ban, Low Elevation, Regular Grade

Figure 30 Gas phase concentration of hydrocarbon groups and oxygenates for the

average reformulated, low-elevation, no-MTBE-ban regular gasolines.
65

Class Chemical Change in Concentration

(mg/L)

Oxygenates Methyl-t-butylether 152.5

Iso-Paraffins i-Butane 4.97

n-Olefins t-Butene-2 3.72

Paraffin n-Hexane 3.18

n-Olefins c-Butene-2 2.82

n-Olefins t-Pentene-2 2.50

n-Olefins Butene-1 1.72

Iso-Olefins 2-Methylbutene-2 1.37

n-Olefins c-Pentene-2 1.06

Iso-Paraffins 3-Methylpentane 1.03

n-Olefins t-Hexene-2 0.82

Naphtheno-Olefins 1-Methylcyclopentene 0.78

Mono-Naphthenes Cyclopentane 0.68

Oxygenates TAME 0.67

Iso-Olefins 2-Methylpentene-1 0.60

n-Olefins Pentene-1 0.58

Naphtheno-Olefins Cyclopentene 0.55

Iso-Olefins 2-Methylpentene-2 0.50

n-Olefins t-Hexene-3 0.50

Iso-Olefins 3,3-Dimethylpentene-1 0.48

Iso-Olefins 3-Methyl-c-pentene-2 0.41

n-Olefins c-Hexene-2 0.34

Mono-Naphthenes Methylcyclohexane 0.28

Iso-Olefins 4-Methyl-t-pentene-2 0.26

Iso-Olefins 2-Methyl-2-hexene 0.24

Iso-Olefins 3-Methyl-t-hexene-3 0.23

Iso-Paraffins 3-Methylhexane 0.22

Iso-Olefins 3-Methylbutene-1 0.21

n-Olefins Hexene-1 0.21

Mono-Naphthenes 1c,3-Dimethylcyclopentane 0.15

Iso-Olefins 5-Methyl-c-hexene-2 0.13

n-Olefins c-Heptene-2 0.13

Iso-Olefins 4-Methyl-t/c-hexene-2 0.13

Iso-Olefins 4-Methylpentene-1 0.12

n-Olefins t-Heptene-3 0.12

n-Olefins c-Heptene-3 0.12

Iso-Paraffins 2,2,5-Trimethylhexane 0.12

n-Olefins t-Heptene-2 0.11

Mono-Naphthenes Ethylcyclopentane 0.11

Iso-Paraffins 2-Methylhexane 0.11

Iso-Olefins 3-Methyl-t-hexene-2 0.11

Iso-Olefins 2-Methyl-t-hexene-3 0.10

Iso-Olefins 3-Methyl-c-hexene-2 0.10

Iso-Olefins 1,5-DM-Cyclopentene 0.09

Table 19 Predicted higher gas phase constituent concentrations (>0.05 mg/L) of

RFG (regular grade, low elevation) in comparison to conventional gasoline.
66

Class Chemical Change in Concentration

(mg/L)

Naphtheno-Olefins Cyclohexene 0.09

Iso-Olefins 4-Methyl-c-pentene-2 0.09

Mono-Naphthenes 1t,3-Dimethylcyclopentane 0.08

Iso-Olefins 2-Ethyl-3-methylbutene-1 0.08

Mono-Naphthenes 1t,2-Dimethylcyclopentane 0.07

Mono-Naphthenes 1,1,2-Trimethylcyclopentane 0.06

Oxygenates t-Butanol 0.05

Iso-Olefins 3-Methyl-c-hexene-3 0.05

Iso-Olefins 3-Ethylpentene-2 0.05

Table 20 (Continuation) Predicted higher gas phase constituent concentrations

(>0.05 mg/L) of RFG (regular grade, low elevation) in comparison to conventional

gasoline.
67

Class Chemical Change in Concentration

(mg/L)

Paraffin n-Butane -62.91

Iso-Paraffins i-Pentane -45.31

Paraffin n-Pentane -9.36

Mono-Aromatics Toluene -3.46

Mono-Aromatics Benzene -2.98

Iso-Paraffins 2,2-Dimethylbutane -2.22

Iso-Paraffins 2,2,4-Trimethylpentane -1.43

Iso-Paraffins 2,3-Dimethylbutane -1.05

Iso-Paraffins 2,2-Dimethylpropane -0.47

Iso-Olefins 2-Methylbutene-1 -0.43

Mono-Aromatics m-Xylene -0.41

Iso-Paraffins 2,3,4-Trimethylpentane -0.27

Mono-Aromatics Ethylbenzene -0.25

Mono-Aromatics o-Xylene -0.22

Mono-Aromatics p-Xylene -0.17

Di-Olefins 1c/t,4-Hexadiene -0.16

Iso-paraffins 2,4-Dimethylpentane -0.14

Di-Olefins 2-Methyl-1,3-Butadiene -0.12

Iso-paraffins 2,4-Dimethylhexane -0.11

Mono-Aromatics 1,2,4-Trimethylbenzene -0.07

Iso-paraffins 2,3-Dimethylhexane -0.07

Di-Olefins 1t,3-Pentadiene -0.07

Mono-Aromatics 1-Methyl-3-ethylbenzene -0.06

Iso-paraffins 3-Methylheptane -0.06

Iso-paraffins 2-Methylpentane -0.06

Paraffin n-Octane -0.05

Table 21 Predicted lower gas phase constituent concentrations (>0.05 mg/L) of RFG

(regular grade, low elevation) in comparison to conventional gasoline.
68

0 4 8 12

Mass Percent in Fuel

0.001

0.01

0.1

1

10

100

1000

Gas Phase Concentration (mg/L)

Oxygenates

BTEX

Other Aromatics

Naphthenes

Paraffins

Iso-Paraffins

Olefins

Iso-Olefins

Di-Olefins

RFG, MTBE Ban, Low Elevation, Regular Grade

Figure 31 Gas phase concentration for hydrocarbon groups and oxygenates for the

Illinois regular gasolines (low elevation, MTBE ban, RFG).
69

Class Chemical Change in Concentration

(mg/L)

Paraffin n-Butane 111.13

Iso-paraffins i-Pentane 36.77

Paraffin n-Pentane 19.22

Oxygenates Ethanol 13.04

Iso-paraffins 2,2,4-Trimethylpentane 3.45

Iso-paraffins 2,2-Dimethylpropane 1.68

Iso-paraffins 2,4-Dimethylpentane 1.33

Iso-Olefins 3-Methylbutene-1 0.90

Iso-paraffins 2-Methylhexane 0.62

Iso-paraffins 2,3,4-Trimethylpentane 0.57

Iso-paraffins 2-Methyl-3-ethylpentane 0.48

Mono-Aromatics Benzene 0.43

Iso-paraffins 2,3-Dimethylbutane 0.34

Iso-paraffins 2,4-Dimethylhexane 0.15

Mono-Naphthenes 1c,2c,3-Trimethylcyclopentane 0.13

Mono-Naphthenes 1t,2-Dimethylcyclopentane 0.12

Mono-Naphthenes Cyclohexane 0.11

Mono-Naphthenes 1t,4-Dimethylcyclohexane 0.10

Iso-paraffins 2,5-Dimethylhexane 0.09

Mono-Naphthenes 3c-Ethylmethylcyclopentane 0.06

Iso-Olefins 2-Methyl-c-hexene-3 0.06

Table 22 Predicted higher gas phase constituent concentrations (>0.05 mg/L) of

MTBE-ban RFG (regular grade, low elevation) in comparison to non MTBE-ban

RFG.
70

Class Chemical Change in Concentration

(mg/L)

Oxygenates Methyl-t-butylether -155.16

Iso-paraffins i-Butane -7.11

Iso-paraffins 2-Methylpentane -5.17

n-Olefins c-Butene-2 -5.00

n-Olefins t-Butene-2 -4.66

Iso-paraffins 3-Methylpentane -4.20

n-Olefins t-Pentene-2 -3.15

Paraffin n-Hexane -3.14

Iso-paraffins 2,2-Dimethylbutane -2.99

Mono-Aromatics Toluene -1.99

n-Olefins Pentene-1 -1.92

n-Olefins c-Pentene-2 -1.65

Iso-Olefins 2-Methylbutene-2 -1.62

Iso-Olefins 2-Methylbutene-1 -1.36

Iso-paraffins 3-Methylhexane -1.08

n-Olefins t-Hexene-2 -0.82

Mono-Naphthenes Cyclopentane -0.75

Oxygenates TAME -0.74

n-Olefins Butene-1 -0.72

n-Olefins t-Hexene-3 -0.56

Iso-Olefins 2-Methylpentene-2 -0.54

Naphtheno-Olefins Cyclopentene -0.52

Iso-Olefins 3,3-Dimethylpentene-1 -0.48

Naphtheno-Olefins 1-Methylcyclopentene -0.45

Iso-Olefins 3-Methyl-c-pentene-2 -0.45

Iso-Olefins 2-Methylpentene-1 -0.44

n-Olefins c-Hexene-2 -0.33

Mono-Aromatics m-Xylene -0.33

n-Olefins Hexene-1 -0.33

Iso-Olefins 4-Methyl-t-pentene-2 -0.31

Mono-Aromatics Ethylbenzene -0.26

Iso-paraffins 3,3-Dimethylpentane -0.24

Iso-Olefins 2-Methyl-2-hexene -0.22

Iso-Olefins 4-Methylpentene-1 -0.20

Mono-Aromatics o-Xylene -0.16

Iso-Olefins 5-Methyl-c-hexene-2 -0.16

Paraffin n-Heptane -0.15

Mono-Aromatics p-Xylene -0.14

n-Olefins c-Heptene-3 -0.13

Iso-Olefins 3-Methyl-t-hexene-2 -0.13

n-Olefins c-Heptene-2 -0.13

Iso-Olefins 4-Methyl-t/c-hexene-2 -0.13

n-Olefins t-Heptene-2 -0.12

Iso-Olefins 3-Methyl-c-hexene-2 -0.11

Iso-Olefins 4-Methyl-c-pentene-2 -0.11

Table 23 Predicted lower gas phase constituent concentrations (>0.05 mg/L) of

MTBE-ban RFG (regular grade, low elevation) in comparison to non MTBE-ban

RFG.
71

Class Chemical Change in Concentration

(mg/L)

n-Olefins t-Heptene-3 -0.10

Iso-Olefins 2-Methyl-t-hexene-3 -0.09

Iso-Olefins 1,5-DM-Cyclopentene -0.09

Iso-Olefins 3-Methyl-t-hexene-3 -0.08

Iso-Olefins 2-Methyl-c-hexene-3 -0.08

Iso-Olefins 2-Ethyl-3-methylbutene-1 -0.07

Mono-Naphthenes 1,1,2-Trimethylcyclopentane -0.07

Di-Olefins 2-Methyl-1,3-Butadiene -0.06

Di-Olefins 1t,3-Pentadiene -0.06

Naphtheno-Olefins Cyclohexene -0.06

Iso-Olefins 3-Methyl-c-hexene-3 -0.06

Oxygenates t-Butanol -0.06

Mono-Naphthenes Ethylcyclopentane -0.06

Iso-Olefins 3-Ethylpentene-2 -0.05

Mono-Aromatics 1-Methyl-3-ethylbenzene -0.05

Table 24 (Continuation) Predicted lower gas phase constituent

concentrations (>0.05 mg/L) of MTBE-ban RFG (regular grade, low

elevation) in comparison to non MTBE-ban RFG.

Figure 32 shows one final example where the predicted gas phase concentration of the

average conventional, no MTBE ban, low elevation, regular grade gasoline components were

plotted against their effective solubilities. For reference a line of equal gas phase concentration

and effective solubility was plotted. The gas phase results are based upon vapor pressure (i.e.,

direct volatilization from the fuel) and the oxygenates plotted below the equal-concentration line,

as did many naphthenes and aromatics. The BTEX compounds, paraffins, Iso-Paraffins and all

three types of olefins plotted above the line, indicating that their presence is greater in the gas

phase than in the water phase. Notably, in the preceding figures of gas phase concentration

(Figures 29, 30, and 31) there was a shift upward of paraffins and Iso-Paraffins relative to the

plots for the effective solubility (Figures 26, 27 and 28).
72

1E-007 1E-006 1E-005 0.0001 0.001 0.01 0.1 1 10 100 1000

Effective Solubility (mg/L)

1E-007

1E-006

1E-005

0.0001

0.001

0.01

0.1

1

10

100

1000

Gas Phase Concentration (mg/L)

Oxygenates

BTEX

Other Aromatics

Naphthenes

Paraffins

Iso-paraffins

Olefins

Iso-Olefins

Di-Olefins

Conventional gasoline, No MTBE, Low Elevation, Regular Grade

Figure 32 Scatter plot of predicted gas phase concentration versus the effective solubility

of the average conventional, low-elevation, no-MTBE-ban, regular gasoline.
73

Discussion and Conclusions

Data were collected on 312 components of gasoline based on 96 samples collected from

across the United States. The sample locations were selected to include RFG and conventional

gasoline, high and low elevation, regular and premium grades, likely ethanol-using locations and

MTBE-ban states. Evaluation of single compound concentrations lead to several findings:

1) The benzene concentration of Federal RFG fuels were consistently below 1% by weight. This

result follows from federal requirements and agrees with data collected by EPA for compliance

(US EPA, 2005). In conventional fuels, higher benzene concentrations of roughly 0.5% to 3%

were found. These values generally agree with data generated by industry (Dickson, 2004a,

2004b). Data on conventional fuels available from EPA show the average benzene concentration

to range from 1.11 % to 1.17% by volume for summer and 1.08% to 1.15% by volume for winter

for the years from 1997 to 2002. These data are not necessarily in conflict with the current study

data as the averages are based on many more samples and include more locations across the

country. The EPA data show that benzene ranged from 0.01 % to about 5.0% by volume for

summer and winter samples in 2002 and 2003 (John Weihrauch, U.S. EPA, Office of

Transportation and Air Quality, 2005, personal communication).

A) In Colorado the state oxygenate requirement did not limit the amount of benzene in

the fuel while it required an oxygen content of 3.1 %, which is higher than the federal

requirement.

2) Where MTBE bans are in place, ethanol has replaced MTBE as the main oxygenate in use. 

Ethanol was not found in other samples suggesting it was used only where needed to meet an

oxygenate requirement.

3) Only low concentrations of TBA were found in the fuels and were associated with MTBE.

The gasoline data generated for this study represent seven combinations of elevation, RFG

requirements, and MTBE ban status. The regular gasolines showed more similarity given a

particular combination of these factors, than did the premiums. This result suggests that refiners

use more approaches to raise the octane rating of the fuels. Statistical analysis of the data support

the division of the samples by grade, elevation, MTBE ban status and RFG requirements for some

combinations of the factors. Differences due to state RFG requirements, regional use of

oxygenates for octane enhancement and lack of commonality among high elevation fuels, require

specific local data to achieve the goal of prediction of release composition. The need to predict

release composition follows from the lack of detailed characterization of most fuels and lag time

between release and field sampling. Both of these are expected to continue in the future.

The environmental impact of these fuels depends on the exposure pathway. When contact

with contaminated soils is a significant pathway, the components of the fuel are themselves

directly important. If exposure occurs through ground water or soil gas, then the concentrations

in these media indicate the importance of the various components of the fuel. Effective
74

solubilities and gas phase concentrations were approximated from estimates of solubility vapor

pressure and the individual gasoline component concentration data. In several examples, these

showed that a smaller number of components result in high (say greater than 1 mg/L)

concentrations in these media. For ground water the highest concentrations were found for the

oxygenates and BTEX. For the gas phase concentration, the highest were found for paraffins and

oxygenates, with the BTEX occurring at lower concentration. These only provide a rough guide,

because the toxicity of the compound and the exposure ultimately determines the significance of

these chemicals.
75

References

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Regulations of Fuels and Fuel Additives

American Petroleum Institute, 2004, State MTBE Activity Laws, 6/14/04, Unpublished

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American Society for Testing and Materials, 1958, Knocking Characteristics of Pure

Hydrocarbons, ASTM Special Publication No. 225, Philadelphia, 96 pp.

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Dickson, C. L., 2004, Motor Gasolines, Winter 2003-04, Northrup Grumman Mission Systems,

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Appendix: Theoretical Basis of the Principal Components Analysis 

Following the theory presented by Jolliffe (2002), let X be a vector of p random variables,

such that the variances of the p random variables and the structure of the covariances or

correlations between the p variables are of interest. Unless p is small, it is often unbeneficial to

look at the p variances and all of the 0.5p(p-1) correlations or covariances. An alternative

approach is to find a few (less than p) variables that preserve most of the information given by

these variances and correlations or covariances. The initial step is to find a linear function "1

T

 X

of the elements of X having maximum variance, where "1 is a vector of p constants "11, "12,..., "1p,

and T

 denotes the transpose, such that 

(5)

Next, find a linear function "s

T

 X which is uncorrelated with "1

T

 X having maximum variance,

and continuing repeating this sequence so that at the kth stage a linear function "k

T

 X is found that

has maximum variance subject to being uncorrelated with "1

T

 X, "s

T

 X, ... ,"k

T

 X. Up to p PC

could be found, however it is hoped that the majority of the variation in X will be accounted for

by m PC, where m is less than p.

The first step in PCA is deciding whether to use the correlation matrix or covariance

matrix. Use of the correlation matrix forces all of the variables to have equal variance and this in

turn may defeat the purpose of identifying those variables that contribute more significantly to the

total variability (Khattree and Naik, 2000). The PC of a PCA based on covariance matrices are

also insensitive to units of measurement on the same scale. Since all of the gasoline variables are

measured on a percent weight basis, ensures the PC will be interpretable and unbiased by those

variables having large variance. PCA in this work was done utilizing the covariance matrix of the

variables.

There are two commonly used methods for determining the number of PC to select. The

first, and most commonly used, is based on the cumulative proportion of total variance. An

appropriate minimum percentage of total variation desired to be explained by the PCA is

prespecified, and the smallest number of principal components that satisfies this criterion is

selected. The prespecified percentage is usually taken to be 95 percent variation explained. The

second method is graphical and uses what is called a scree diagram. A scree diagram is a plot of

the variances against the p PC. From the plot, the number of m PC to be selected is determined in

such a way that the slope of the graph is steep to the left of m, but at the same time not steep to

the right. The idea being that the number of PC to be selected is such that the differences between

consecutive variances are becoming increasingly smaller. Both of the techniques described above

will be used in determining an appropriate number of PC.

When the number of variables p is large, it is often the case that a subset of m variables,

where m < p contains virtually all the information available in all p variables. It is useful then to

select an appropriate value of m, and then determine which subset of m variables are best. It has
79

been cited that if X can successfully be described by m PC, then X can be replaced by a subset of

m variables (Jolliffe 1970, 1972, 1973). The variable corresponding to the maximum of the

absolute values of the coefficients in the first PC is selected first. The second variable selected is

that variable (if not already selected) whose coefficient in the second PC has the maximum

absolute value. If the variable corresponding to the maximum coefficient was already selected

then we choose the variable corresponding to the next maximum. Proceeding this way, we select

a subset of required size from the list of original variables.

Given the data have p variables the observations can be plotted as points in p-dimensional

space. Two-dimensional plots are of use in detecting patterns in the data. If the data lie close to a

two dimensional subspace, plots of the m < p PC will provide an adequate representation for

detecting patterns or clusters of data since the majority of the variation is accounted for by the m

PC. Graphical analysis will be conducted to determine if unique trends among the samples are

observed. For these data, we looked for patterns among location, octane number, MTBE ban

(Yes or No), RFG or conventional gasoline, brand, and altitude.