COMPARISON OF TRANSPORT EFFECTS OF PERFLUORINATED AND
HYDROCARBON SURFACTANTS ON ENVIRONMENTAL CO-CONTAMINANTS
By
Rashad Najee Simmons

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Chemistry – Environmental Toxicology
2011

ABSTRACT
COMPARISON OF TRANSPORT EFFECTS OF PERFLUORINATED AND
HYDROCARBON SURFACTANTS ON ENVIRONMENTAL CO-CONTAMINANTS
By
Rashad Najee Simmons

The use of groundwater as drinking water justifies efforts for the prevention and
remediation of groundwater contamination by environmental pollutants. The inclusion of
hydrocarbon surfactants (HCSs), at high concentrations, in a groundwater system has
been used for groundwater remediation, and is known to increase the transport of
environmental pollutants. While much information is known about HCS, little to no
information is available for the perfluorinated surfactants (PFSs). The overall objective
of this research was to determine the transport effects of PFSs on known environmental
contaminants, in comparison to the transport effects of HCSs. Polycyclic aromatic
hydrocarbons, halogenated benzene compounds, and the BTEX series of compounds
(benzene, toluene, ethylbenzene, and p-xylene) were used as representatives of important
classes of hydrophobic neutral environmental pollutants. A series of aromatic amines
was used as representatives of cationic environmental pollutants. Reversed-phase liquid
chromatography (RPLC) was used to model the groundwater system.
Above their critical micelle concentration (CMC), surfactants form micelles that
can act as partitioning mediums for hydrophobic neutral pollutants, increasing their
transport. In the first study, the transport effects of HCSs and PFSs, above their CMC (>
20 mM), were compared in the RPLC system for representative neutral environmental
pollutants. Transport effects were elucidated from retention factors, k, and the

equilibrium constant per micelle of the model pollutants. The resulting data suggest that
the presence of HCSs and PFSs, above the CMC, increases the transport of cocontaminants in a groundwater system. However, PFSs (18 to 103 % increase) exhibit a
lesser transport effect than HCSs (32 to 247 % increase).
Previous literature suggests that surfactants below their CMC have a negligible
effect on the transport of hydrophobic neutral pollutants, while undergoing ion-pair
formation with ionic pollutants and decreasing their transport. In the second and third
studies, the transport effects of HCSs and PFSs, below their CMC (< 6 mM), were
compared in the RPLC system. Transport effects were elucidated from retention factors,
k, and selectivity factors, α, of the model pollutants. The resulting data suggest the
presence of HCSs statistically decreases transport of neutral pollutants (4 to 13 %), while
the presence of PFSs statistically increases their transport (5 to 16 %). Further results
show that transport of cationic aromatic amines decreases with increasing concentration
of both anionic HCSs and PFSs in RPLC system, with PFSs (99 to 100 % decrease)
exhibiting a greater transport effect than HCSs (96 to 100 % decrease).
Due to the differences in chemical and physical properties, PFSs exhibit different
transport effects in comparison to HCSs under the same conditions. The inclusion of
anionic PFSs in a groundwater system will increase the transport of neutral
environmental pollutants, while decreasing the transport of cationic pollutants. An
unintentional release of PFSs can lead to an increase in groundwater contamination by
neutral pollutants. However, the judicious use of PFSs can be used for remediation of
cationic pollutants in groundwater.

To my family, immediate and extended, near and far, living and departed,
for your support and love through this process.

iv

ACKNOWLEDGMENTS
“Intelligence plus character – that is the true goal of education. The complete
education gives one not only power of concentration, but worthy objectives upon which
to concentrate.”
– Dr. Martin Luther King Jr.

At this time, I would like to thank all those that helped and contributed my overall
education, and to the completion of this dissertation and the research contained within.
First and foremost, I would like to thank God the Creator for giving me divine courage to
pursue graduate school, strength to endure the tough road that it is, and wisdom to take
advantage of the opportunities it has afforded me. I would like to thank my wife, Sheena
Simmons, enduring this process with me, and strengthening me with her ever present
faith. I would like to thank my family and friends for their many prayers, words of
encouragement, and overall show of love towards me through this process.
To my advisor Dr. Victoria McGuffin, I would like to thank you for all of your
guidance throughout these many years. Thank you for your always honest discussions
with me, your patience, and your support. You have helped me to become a better
researcher, while also allowing me to develop into the educator that I am today. I will
take your words with me in life, wherever that may lead me.
To my esteemed committee members (Drs. Baker, Bruening, and Voice), I would
like to thank you for all of the input (both scientific and general) you have given me over
these many years. I have tried to soak up your knowledge, and follow your example of

v

how a good scientist should conduct oneself. In addition, thank you for all of your
encouragement to finish this dissertation process; it was greatly appreciated.
I would like to thank the following individuals for their contributions to this
research. Dr. Michael E. Mackay and Leslie Passeno, formerly of Michigan State
University (MSU), for the use of their equipment and help with the densitometry
measurements. Dr. James Jackson, MSU, for his discussions on the interactions of
cationic amines. Dr. Kathy Severin, MSU, for the use of a UV detector during the
duration of these studies. The East Asia and Pacific Summer Institutes and the National
Institute of Advanced Industrial Science and Technology in Tsukuba, Japan for the
opportunity to conduct research and gain experience in an international setting. The
King, Chavez, Parks Future Faculty Fellowship (KCP-FFF), the Graduate School at
MSU, and the Center for Water Science at MSU for funding to conduct the research.
Lastly, I would like to thank the Department of Chemistry and the Charles Drew
Science Scholars Program for giving me the opportunity to increase my intelligence and
character, through the education of MSU students.

vi

TABLE OF CONTENTS

LIST OF TABLES .............................................................................................................x
LIST OF FIGURES ........................................................................................................ xii
CHAPTER 1:
INTRODUCTION AND BACKGROUND .....................................................................1
1.1 Introduction ........................................................................................................1
1.2 Surfactants..........................................................................................................2
1.2.1 Hydrocarbon Surfactants ..........................................................................4
1.2.2 Fluorocarbon Surfactants ..........................................................................7
1.3 Environmental Pollutant Transport ..................................................................13
1.4 Environmental Pollutants .................................................................................16
1.4.1 Substituted Benzene Compounds ...........................................................18
1.4.2 Polycyclic Aromatic Hydrocarbons ........................................................19
1.5 Statement of Dissertation Objectives ...............................................................24
1.6 References ........................................................................................................27
CHAPTER 2:
EXPERIMENTAL METHODS .....................................................................................33
2.1 Introduction ......................................................................................................33
2.2 Chromatographic Measurements .....................................................................33
2.2.1 Stationary Phase ......................................................................................33
2.2.2 Instrumentation .......................................................................................34
2.2.3 Data Analysis ..........................................................................................34
2.2.4 Refractive Index ......................................................................................36
2.3 Conductivity Measurements ............................................................................37
2.3.1 Instrumentation .......................................................................................37
2.3.2 Data Analysis ..........................................................................................38
2.4 Densitometry Measurements ...........................................................................46
2.4.1 Instrumentation .......................................................................................46
2.4.2 Data Analysis ..........................................................................................46
2.5 Summary ..........................................................................................................47
2.6 References ........................................................................................................49
CHAPTER 3:
COMPARISON OF TRANSPORT EFFECTS ABOVE THE CRITICAL
MICELLE CONCENTRATION....................................................................................50
3.1 Introduction ......................................................................................................50
3.2 Experimental Methods .....................................................................................52
3.2.1 Mobile Phase and Analytes .....................................................................52
3.2.2 Experimental System ..............................................................................53
3.2.3 Data Analysis ..........................................................................................54
vii

3.3 Results and Discussion ....................................................................................56
3.3.1 Transport Effects of Sodium Dodecyl Sulfate ........................................57
3.3.2 Transport Effects of Lithium Perfluorooctane Sulfonate........................65
3.4 Summary ..........................................................................................................72
3.5 References ........................................................................................................75
CHAPTER 4:
COMPARISON OF TRANSPORT EFFECTS BELOW THE CRITICAL
MICELLE CONCENTRATION: NEUTRAL AROMATIC ANALYTES ..............78
4.1 Introduction ......................................................................................................78
4.2 Experimental Methods .....................................................................................79
4.2.1 Mobile Phase and Analytes .....................................................................79
4.2.2 Experimental System ..............................................................................80
4.2.3 Data Analysis ..........................................................................................81
4.2.3.1 Retention Factor Measurements .................................................81
4.2.3.2 Selectivity Factor Calculations ...................................................83
4.3 Results and Discussion ....................................................................................84
4.3.1 Transport Effects in Water ......................................................................85
4.3.2 Transport Effects of Sodium Dodecyl Sulfate ........................................87
4.3.3 Transport Effects of Lithium Perfluorooctane Sulfonate........................92
4.3.4 Effect of Ionic Surfactant on the Polarity of the System ........................99
4.3.5 Effect of Ionic Surfactant on the Solubility of the Analytes .................100
4.4 Summary ........................................................................................................102
4.5 References ......................................................................................................105
CHAPTER 5:
COMPARISON OF TRANSPORT EFFECTS BELOW THE CRITICAL
MICELLE CONCENTRATION: CATIONIC AROMATIC AMINES .................107
5.1 Introduction ....................................................................................................107
5.2 Experimental Methods ...................................................................................108
5.2.1 Mobile Phase and Analytes ...................................................................108
5.2.2 Experimental System ............................................................................109
5.2.3 Data Analysis ........................................................................................110
5.2.3.1 Retention Factor Measurements ...............................................110
5.2.3.2 Linear Solvent Strength Model .................................................112
5.2.3.3 Selectivity Factor Calculations .................................................113
5.3 Results and Discussion ..................................................................................114
5.3.1 Transport Effects in Water ....................................................................115
5.3.2 Transport Effects of Sodium Dodecyl Sulfate ......................................118
5.3.3 Transport Effects of Lithium Perfluorooctane Sulfonate......................129
5.4 Summary ........................................................................................................140
5.5 Appendix ........................................................................................................143
5.6 References ......................................................................................................145

viii

CHAPTER 6:
USE OF SYSTEM PEAKS FOR THE DETERMINATION OF THE RETENTION
OF FLUORINATED AND HYDROCARBON SURFACTANTS IN THE
EXPERIMENTAL SYSTEM .......................................................................................147
6.1 Introduction ....................................................................................................147
6.2 Experimental Methods ...................................................................................155
6.2.1 Mobile Phase and Analytes ...................................................................155
6.2.2 Experimental System ............................................................................155
6.2.3 Data Analysis and Calculations ............................................................156
6.2.3.1 Retention Factor Measurements ...............................................156
6.2.3.2 Linear Solvent Strength Model .................................................161
6.3 Results and Discussion ..................................................................................161
6.3.1 System Peaks ........................................................................................161
6.3.2 System Peaks in Sodium Dodecyl Sulfate Mobile Phases....................162
6.3.3 System Peaks in Lithium Perfluorooctane Sulfonate Mobile Phases ...179
6.4 Summary ........................................................................................................197
6.5 References ......................................................................................................199
CHAPTER 7:
DETERMINATION OF FLUORINATED SURFACTANTS IN WASTEWATER
SAMPLES BY HIGH-PERFORMANCE LIQUID CHROMATOGRAPHY WITH
TANDEM MASS SPECTROMETRY .........................................................................200
7.1 Introduction ....................................................................................................200
7.2 Experimental Methods ...................................................................................201
7.2.1 Fluorinated Surfactants .........................................................................201
7.2.2 Wastewater Samples .............................................................................203
7.2.3 Sample Extraction and Preparation .......................................................203
7.2.4 Experimental System ............................................................................205
7.2.5 Data Analysis ........................................................................................209
7.3 Results and Discussion ..................................................................................209
7.3.1 Detection of Perfluorooctane Sulfonate ................................................210
7.3.2 Detection of Perfluorooctanoic Acid ....................................................216
7.3.3 Detection of Perfluorobutyric Acid ......................................................221
7.4 Summary ........................................................................................................223
7.5 References ......................................................................................................225
CHAPTER 8:
CONCLUSIONS AND FUTURE DIRECTIONS .......................................................226
8.1 Experimental Methods ...................................................................................226
8.2 Transport Effects on Neutral Organic Pollutants ...........................................229
8.3 Transport Effects on Ionic Organic Pollutants...............................................230
8.4 Future Directions ...........................................................................................232
8.4.1 Transport Effects of Short Chain Perfluorinated Surfactants ...............232
8.4.2 Transport Effects of Mixed Surfactants Solutions ................................233
8.4.3 Transport Effects of a Perfluorinated Stationary Phase ........................235
8.5 References ......................................................................................................238
ix

LIST OF TABLES

Table 2.1:

Experimentally determined CMC values for SDS via conductivity
measurements .............................................................................................41

Table 3.1:

Physical data of representative hydrocarbon and perfluorinated surfactants
used in this study........................................................................................58

Table 3.2:

Summary of retention factors of analytes for several mobile phases ........60

Table 3.3:

Equilibrium constants of analytes from water to the SDS micelle ............64

Table 3.4:

Equilibrium constants of analytes from water to the LiPFOS micelle ......70

Table 4.1:

Retention factors of analytes in pure water................................................86

Table 4.2:

Retention and selectivity factors of analytes in pure water and SDS mobile
phases .........................................................................................................88

Table 4.3:

Retention and selectivity factors of analytes in pure water and LiPFOS
mobile phases .............................................................................................93

Table 4.4:

Retention and selectivity factors of analytes in pure water and LiNO3
mobile phases ...........................................................................................101

Table 5.1:

Retention and selectivity factors of cationic aromatic amines in pure water
mobile phase ............................................................................................116

Table 5.2:

Retention and selectivity factors of cationic aromatic amines in SDS
mobile phase ............................................................................................127

Table 5.3:

Retention and selectivity factors of cationic aromatic amines in LiPFOS
mobile phase ............................................................................................138

x

Table 7.1:

Summary of names, abbreviations, and structures for the perfluorinated
compounds (PFCs) ...................................................................................202

Table 7.2:

Summary of calibration curve slope and R values, characteristic MS/MS
transitions, limit of quantification (LOQ), and limit of detection
(LOD) .......................................................................................................211

2

xi

LIST OF FIGURES

Figure 1.1:

Graph of logarithmic concentration of surfactant in a mobile phase (Cm)
versus the logarithmic concentration of surfactant adsorbed on a stationary
phase (Cs). Region A: Very low surfactant concentration below the
CMC. Regions B and C: Surfactant concentration below the CMC.
Region D: Surfactant concentration above the CMC .................................6

Figure 1.2:

Graph of number of publications versus the year of publication based on a
literature search of the phrases: (■) perfluorinated compounds and (■)
perfluorinated surfactants...........................................................................10

Figure 1.3:

Structures of the substituted benzene compounds used as model analytes
for environmental pollutants (e.g. polyhalogenated biphenyls, dioxins, and
furans). The analytes are used in Chapters 3 – 4 ......................................20

Figure 1.4:

Structures of the amines used as analytes in Chapters 5 – 6 ......................21

Figure 1.5:

Structures of PAHs used as model analytes in Chapter 3 ..........................23

Figure 2.1:

Schematic diagram of the liquid chromatography system used for the
determination of transport effects of perfluorinated surfactants. System
components: single-piston reciprocating pump (P), injection valve (I),
analytical column with Poroshell stationary phase (A), UV-visible
absorbance detector (D), and computer data acquisition system (C).........35

Figure 2.2:

Graph of the current versus the concentration of sodium dodecyl sulfate
(SDS). Temperatures: (♦) ambient, (■) 10 °C, (▲) 15 °C, (x) 30 °C, (∗)
35 °C. Other experimental conditions as given in the text .......................39

Figures 2.3: Graphs of current versus the concentration of lithium perfluorooctane
sulfonate (LiPFOS). Temperatures: (A) 25 °C, (B) 23 °C. Other
experimental conditions as given in text ....................................................43

xii

Figure 3.1:

Plot of inverse retention factor versus the concentration of sodium dodecyl
sulfate (SDS) in the micelle. Analytes: (♦) benzene, (■) fluorobenzene,
(▲) hexafluorobenzene, (x) chlorobenzene, (*) bromobenzene, (•)
naphthalene, (○) biphenyl, (◊) phenanthrene, (□) anthracene, (∆) pyrene,
(+) hexachlorobenzene. Other experimental conditions as given
in the text....................................................................................................61

Figure 3.2:

Plot of inverse retention factor versus the concentration of lithium
perfluorooctane sulfonate (LiPFOS) in the micelle. Analytes: (♦)
benzene, (■) fluorobenzene, (▲) hexafluorobenzene, (x) chlorobenzene,
(*) bromobenzene, (•) naphthalene, (○) biphenyl, (◊) phenanthrene, (□)
anthracene, (∆) pyrene, (+) hexachlorobenzene. Other experimental
conditions as given in the text....................................................................67

Figure 3.3:

Plot of inverse retention factor versus the concentration of lithium
perfluorooctane sulfonate (LiPFOS) in the micelle. Analytes: (♦)
benzene, (■) fluorobenzene, (▲) hexafluorobenzene, (x) chlorobenzene,
(*) bromobenzene, (•) naphthalene, (○) biphenyl, (◊) phenanthrene, (□)
anthracene, (∆) pyrene, (+) hexachlorobenzene. Other experimental
conditions as given in the text....................................................................67

Figure 4.1:

Graph of the logarithmic retention factor versus the concentration of
sodium dodecyl sulfate (SDS) in the micelle. Analytes: (♦) benzene, (■)
fluorobenzene, (x) chlorobenzene, (*) bromobenzene, (▲) toluene, (○) pxylene, (•) ethylbenzene. Other experimental conditions as given
in the text....................................................................................................89

Figure 4.2:

Graph of logarithmic retention factor versus the concentration of lithium
perfluorooctane sulfonate (LiPFOS) in the micelle. Analytes: (♦)
benzene, (■) fluorobenzene, (x) chlorobenzene, (*) bromobenzene, (▲)
toluene, (○) p-xylene, (•) ethylbenzene. Other experimental conditions as
given in the text ..........................................................................................95

xiii

Figures 5.1: Graphs of the logarithmic retention factor versus methanol composition
(% B) in: (A) 1.0 mM aqueous sodium dodecyl sulfate (SDS), (B) 2.0 mM
SDS, (C) 3.0 mM SDS, (D) 4.0 mM SDS. Analytes: (♦) pyridine, (■) 4aminopyridine, (▲) aniline, (x) benzylamine, (*) o-toluidine, (•) mtoluidine, (○) p-toluidine, (◊) N-methylaniline, (□) N,N-dimethylaniline,
(∆) N-ethylaniline, (▬) N,N-diethylaniline, (+) 2,6-dimethylaniline.
Other experimental conditions as given in the text ..................................119
Figure 5.2:

Graph of the logarithmic extrapolated retention factor for each analyte
versus the concentration of SDS. Analytes: (♦) pyridine, (■) 4aminopyridine, (▲) aniline, (x) benzylamine, (*) o-toluidine, (•) mtoluidine, (○) p-toluidine, (◊) N-methylaniline, (□) N,N-dimethylaniline.
Other experimental conditions as given in the text ..................................124

Figures 5.3: Graphs of the logarithmic retention factor versus methanol composition
(% B) in: (A) 1.0 mM aqueous lithium perfluorooctane sulfonate
(LiPFOS), (B) 2.0 mM LiPFOS, (C) 3.0 mM LiPFOS, (D) 4.0 mM
LiPFOS. Analytes: (♦) pyridine, (■) 4-aminopyridine, (▲) aniline, (x)
benzylamine, (*) o-toluidine, (•) m-toluidine, (○) p-toluidine, (◊) Nmethylaniline, (□) N,N-dimethylaniline. Other experimental conditions as
given in the text ........................................................................................130

Figure 5.4:

Graph of the logarithmic extrapolated retention factor for each analyte
versus the concentration of LiPFOS. Analytes: (♦) pyridine, (■) 4aminopyridine, (▲) aniline, (x) benzylamine, (*) o-toluidine, (•) mtoluidine, (○) p-toluidine, (◊) N-methylaniline, (□) N,N-dimethylaniline.
Other experimental conditions as given in the text ..................................136

Figures 6.1: Representative chromatograms of amines in water mobile phase. Mobile
phase: 10.0 mM β-alanine aqueous mobile phase. Flowrate: 0.5 mL
−1
min . Analytes: (0) lithium nitrate, (1) 4-aminopyridine, (2) pyridine,
(3) aniline, (4) benzylamine, (5) p-toluidine, (6) N-methylaniline, (7) mtoluidine, (8) o-toluidine, (9) N,N-dimethylaniline, (10) N-ethylaniline,
(11) N,N-diethylaniline. Other experimental conditions as given in the
text............................................................................................................148

xiv

Figures 6.2: Representative chromatograms of amines in surfactant mobile phases. (A)
Mobile phase: 45:55 methanol/2.0 mM aqueous sodium dodecyl sulfate
−1
(SDS). Flowrate: 1.0 mL min . (B) Mobile phase: 45:55 methanol/2.0
mM aqueous lithium perfluorooctane sulfonate (LiPFOS). Flowrate: 0.3
−1
mL min . Analytes: (0) lithium nitrate, (4) benzylamine, (5) p-toluidine,
(6) N-methylaniline, (∗) unidentified system peak. Other experimental
conditions as given in the text..................................................................152

Figures 6.3: Representative chromatograms of pure methanol in surfactant mobile
phases. (A) Mobile phase: 45:55 methanol/2.0 mM aqueous SDS. (B)
Mobile phase: 45:55 methanol/2.0 mM aqueous LiPFOS. Flowrate: 1.0
−1
mL min . Analytes: (0) methanol, (∗) unidentified system peak, (∗S)
SDS system peak, (∗L) LiPFOS system peak. Other experimental
conditions as given in the text..................................................................158

Figures 6.4: Representative chromatograms of amines in SDS mobile phases. Mobile
−1
phase: 45:55 methanol/2.0 mM aqueous SDS. Flowrate: 1.0 mL min .
Analytes: (0) lithium nitrate, (1) 4-aminopyridine, (2) pyridine, (3)
aniline, (4) benzylamine, (5) p-toluidine, (6) N-methylaniline, (7) mtoluidine, (8) o-toluidine, (9) N,N-dimethylaniline, (∗) unidentified system
peak. Other experimental conditions as given in the text .......................163

Figures 6.5: Representative chromatograms of pure methanol in SDS mobile phases.
Mobile phase: 45:55 methanol/aqueous SDS. (A) 1.0 mM SDS, (B) 2.0
−1
mM SDS, (C) 3.0 mM SDS, (D) 4.0 mM SDS. Flowrate: 1.0 mL min .
Analytes: (0) methanol, (∗) unidentified system peak, (∗S) SDS system
peak. Other experimental conditions as given in the text .......................167

Figure 6.6:

Representative chromatogram of mobile phase in SDS mobile phases.
Mobile phase: 45:55 methanol/2.0 mM aqueous SDS. Flowrate: 1.0 mL
−1
min . Analytes: (∗) unidentified system peak. Other experimental
conditions as given in the text..................................................................172

Figure 6.7:

Graph of retention factor for SDS system peaks versus methanol
composition (%) in: (♦) 1.0 mM SDS, (■) 2.0 mM SDS, (▲) 3.0 mM
SDS, (x) 4.0 mM SDS. Other experimental conditions as given
in the text..................................................................................................175

xv

Figure 6.8:

Graph of extrapolated retention factor for SDS system peaks versus the
concentration of SDS. Other experimental conditions as given
in the text..................................................................................................177

Figures 6.9: Representative chromatograms of amine injections in LiPFOS mobile
phases. Mobile phase: 45:55 methanol/2.0 mM aqueous LiPFOS.
−1
Flowrate: 0.3 mL min . Analytes: (0) lithium nitrate, (1) 4aminopyridine, (2) pyridine, (3) aniline, (4) benzylamine, (5) p-toluidine,
(6) N-methylaniline, (7) m-toluidine, (8) o-toluidine, (9) N,Ndimethylaniline, (∗) unidentified system peak. Other experimental
conditions as given in the text..................................................................180

Figures 6.10: Representative chromatograms of pure methanol injections in LiPFOS
mobile phases. Mobile phase: 45:55 methanol/aqueous LiPFOS. (A) 1.0
mM LiPFOS, (B) 2.0 mM LiPFOS, (C) 3.0 mM LiPFOS, (D) 4.0 mM
−1
LiPFOS. Flowrate: 1.0 mL min . Analytes: (0) methanol, (∗)
unidentified system peak, (∗L) LiPFOS system peak. Other experimental
conditions as given in the text..................................................................184

Figure 6.11: Representative chromatogram of mobile phase injection in LiPFOS mobile
phases. Mobile phase: 45:55 methanol/2.0 mM aqueous LiPFOS.
−1
Flowrate: 0.3 mL min . Analytes: (∗) unidentified system peak. Other
experimental conditions as given in the text ............................................189

Figure 6.12: Graph of retention factor versus methanol composition (%) in: (♦) 1.0
mM LiPFOS, (■) 2.0 mM LiPFOS, (▲) 3.0 mM LiPFOS, (x) 4.0 mM
LiPFOS. Other experimental conditions as given in the text..................192

Figure 6.13: Graph of extrapolated retention factor for LiPFOS system peaks versus the
concentration of LiPFOS. Other experimental conditions as given in the
text............................................................................................................195

Figure 7.1:

Total ion chromatogram (TIC) for the five detection functions during a
PFC standard mixture injection. Detection functions: #1 (A), #2 (B), #3
(C), #4 (D), #5 (E). For interpretation of the references to color in this and
all other figures, the reader is referred to the electronic version of this
dissertation ...............................................................................................206

xvi

Figure 7.2:

Individual chromatograms of the characteristic MS/MS transitions
detected by function #3, during a PFC standard mixture injection.
Chromatograms: TIC of function #3 (A), PFHpA (B), PFHxS (C), PFOA
13
(D), C-PFOA (E), THPFOS (F), PFNA (G), PFOS (H) ......................208

Figure 7.3:

Individual chromatograms of PFOS from injections of PFC standard
mixture and water samples taken during the second day of PFOS
production. Chromatograms: 1.0 ppb PFC standard mixture (A), water
sample from adjacent stream site G (B), water sample from second
treatment tank B (C), water sample from first treatment tank A (D) .......212

Figure 7.4:

External calibration curve (bottom graph) and residue graph (top) for
PFOS ........................................................................................................213

Figure 7.5:

Concentration (ng L ) of PFOS in two waste water treatment tanks (sites
A0 – A3 and B0 – B3), as well as in an adjacent stream into which the
waste water was discharged (sites G1 – G2). Samples were collected one
day prior to production (J23■) and three subsequent days during
production of PFOS (J24■ – J25■ J26■) .................................................214

Figure 7.6:

External calibration curve (bottom graph) and residue graph (top) for
PFOA .......................................................................................................217

Figure 7.7:

Concentration (ng L ) of PFOA in two waste water treatment tanks (sites
A0 – A3 and B0 – B3), as well as in an adjacent stream into which the
waste water was discharged (sites G1 – G2). Samples were collected one
day prior to production (J23■) and three subsequent days during
production of PFOA (J24■ – J25■ – J26■) ............................................219

Figure 7.8:

External calibration curve (bottom graph) and residue graph (top) for
PFBA........................................................................................................222

−1

−1

xvii

CHAPTER 1: INTRODUCTION AND BACKGROUND
1.1 Introduction
One of the greatest resource of humanity is fresh drinking water. The human
race’s continuous survival is dependent on a recurrent source of clean and unpolluted
drinkable water. It is estimated that 25 % of all freshwater used in the U.S. is
groundwater, and that more than 40 % of the U.S. population utilizes groundwater as a
source of drinking water [1]. The protection of all freshwater sources, such as lakes,
rivers, groundwater aquifers, etc., from possible contamination is therefore of the utmost
importance. Contamination of drinking water can take place via direct point sources (e.g.
waste from industrial plants or treatment facilities) or nonpoint sources, such as rainwater
runoff or leaching of organic pollutants from underground gasoline tanks [2]. The
majority of research is focused on the detection, sources, and fates of persistent organic
pollutants in the environment. The persistent organic pollutants of interest consist of
aromatic hydrocarbons, halogenated compounds, and pesticides. However, little research
is reported on the transport effects of organic compounds on afore mentioned
environmental pollutants. Of the research that has been conducted, the main focus has
been dedicated to the transport effects of hydrocarbon surfactants on selected organic
pollutants, which has been reported in the literature [3-6]. For various reasons, the
transport effects of other organic compounds, such as perfluorinated surfactants, are not
readily researched, even though the use of perfluorinated surfactants grew from the 1950s
to about 2000. However, due to their resistance to degradation perfluorinated surfactants
were initially believed to be safe and non-toxic; thus little to no research was reported.
The use of groundwater as drinking water justifies efforts for the prevention and/or

1

remediation of groundwater contamination by environmental pollutants. Thus the effects
of perfluorinated surfactants on the transport of persistent organic pollutants, in a
groundwater system, needs to be investigated. Chapter 1 seeks to give background
information on surfactants, the transport of pollutants in the environment, and several
classes of co-pollutants of environmental importance.
1.2 Surfactants
Surfactants are organic compounds consisting of at least one lyophilic (solventloving) and lyophobic (solvent-fearing) group [7]. Since the most commonly used
solvent is water, the two groups are referred to as hydrophilic (i.e. the polar head group)
and hydrophobic (i.e. the nonpolar tail group), respectively. As such, all further
discussion of surfactants will be in terms of aqueous solutions. Surfactants are most
known for the ability to exhibit surface activity and to form self-assembled aggregates
(e.g. micelles, vesicles, bilayers, etc.) in liquids and aqueous solutions. The term surface
activity refers to the ability of a surfactant to reduce the surface or interfacial excess free
energy within a system [7]. The excess free energy per unit area (units of J m
−2

cm ), which is equivalent to force per unit length (units of mN m

−1

−2

or ergs
−1

or dyne cm ), is

referred to as the surface tension (γ) when the boundary is the air/liquid interface, and is
referred to as the interfacial tension when the boundary is the liquid/liquid or liquid/solid
interface. The addition of a surfactant can reduce the surface tension of water from 72
mN m

−1

down to around 30 mN m

−1

mN m

−1

for fluorocarbon surfactants at 25 °C [9].

for hydrocarbon surfactants [8] and as low as 15

There are four main classes of surfactants, which are distinguished via the
hydrophilic head group: anionic, cationic, nonionic, and zwitterionic (amphoteric).

2

Anionic surfactants contain a head group that has a negative charge when ionized in
−

aqueous solutions. Common anionic head groups include sulfates (−OSO3 ), sulfonates
−

−

−

(−SO3 ), carboxylates (−COO ), and phosphates (−OP(OR)2O ). Cationic surfactants
contain a head group that has a positive charge when ionized in aqueous solutions.
+

+

Common cationic head groups include primary (−N H3), secondary (−N (R)H2), tertiary
+

+

(−N (R)2H), and quaternary (−N (R)3) amines. Nonionic surfactants do not produce ions
in aqueous solutions, but rather contain polar functional groups such as alcohols, amides,
polyglucosides and glucamides, organosilicones, and ethoxylates. The most common
nonionic head groups include alkyl alcohol ethoxylates (−(OC2H4)XOH) or alkylphenol
ethoxylates (−C6H4(OC2H4)XOH). A zwitterionic surfactant has both a cationic portion
and an anionic portion at the same time. The most common zwitterionic head groups
+

−

usually include an amine and a carboxylate group (−N (R)2CH2COO ). Anionic
surfactants represent the most utilized and studied class of surfactants. As of 2000, in the
United States and Canada, the most utilized surfactants were anionic (59 %), followed by
nonionic (24 %), cationic (10 %), and zwitterionic (7 %) [10]. As such, all further
discussion of surfactants will be in terms of anionic surfactants.
To a lesser extent, a surfactant can be classified based on the hydrophobic tail
group. The hydrophobic tail group can either be a hydrocarbon chain, a fluorocarbon
chain, a hydrocarbon/fluorocarbon chain mix, or silicone chains [11]. The majority of
surfactants utilized in commercial and industrial applications have a hydrocarbon
hydrophobic tail group [12]. As such, hydrocarbon surfactants are also the most studied
form of surfactants. Over the years, there has been an emergence in the use of surfactants

3

with a fluorocarbon tail group in applications with conditions that preclude the use of
hydrocarbon surfactants. Both hydrocarbon and fluorocarbon surfactants are discussed in
further detail in the following sections.
1.2.1

Hydrocarbon Surfactants
Hydrocarbon surfactants (HCSs) are surfactants in which the hydrophobic tail

group consists of alkyl groups, typically of chain lengths between C4 – C18. The
hydrophobic tail groups of HCSs are also lipophilic, making them soluble in oils, organic,
non-aqueous, or hydrocarbon liquids/phases. Common hydrophobic tail groups include
alkylbenzene chains, saturated and unsaturated linear alkyl chains, and branched alkyl
chains. Both the length and linearity of the hydrophobic tail group affect several
properties of surfactants. As the length of the hydrophobic tail group increases, the
solubility of HCSs decreases in water, while increasing in organic solvents. In addition,
an increase in the hydrophobic tail chain length leads to an increase in the tendency of
HCSs to adsorb at an interface/surface or to form aggregates (e.g. micelles). Also, it
causes closer packing of HCSs at the surface and increases the sensitivity of ionic HCSs
to precipitate from water due to counterions [10]. Branching in the hydrophobic tail
group decreases toxicity and increases water solubility, while reducing both adsorption to
surfaces and biodegradability. HCSs have a greater affinity for hydrocarbon/water
interfaces in comparison to air/water interfaces [13]. This greater affinity is due to the
more highly favorable interactions of the hydrocarbon chain with the hydrocarbon phase.
In aqueous systems, surfactant monomers (free or unassociated surfactant
molecules) move towards surfaces and interfaces. Surfactants undergo various

4

interactions, within an aqueous system, with respect to changes in the total concentration
of the surfactant. These interactions are represented in Figure 1.1.
At extremely low concentrations of surfactants (Region A), surfactant monomers
will adsorb on a surface. There is little to no interaction between the adsorbed surfactant
monomers within this region. As the concentration of the surfactant increases (Regions B
and C), surfactant monomers begin to pack closer together at the surface and form a
monolayer or bilayer depending on the type of surface. Surfactant monomers will
continue to be adsorbed at the surface until surface saturation is reached. The change in
slope between Regions B and C is due to the decrease in adsorption sites on the surface.
As the concentration of surfactant increases (Region D), the excess surfactant monomers
(in solution) can self-assemble into aggregates called micelles [14].
The surfactant interactions of Regions B – D will be examined in greater detail.
In Regions B and C, the hydrophilic head group is oriented towards the polar phase (i.e.
water) and the hydrophobic tail group is oriented towards the nonpolar phase (e.g. air or a
surface). If the surface is a hydrophobic surface, then the surfactant monomer will adsorb
tail down and form a monolayer; or the monomer will partition into the surface. If the
surface is hydrophilic (i.e. charged as in soil) and has the same charge as the surfactant
head group, then the surfactant monomer will adsorb tail down and form a monolayer. If
the surface has the opposite charge as the surfactant head group, then the surfactant
monomer will adsorb head down and form a hemimicelle/admicelle layer. A
hemimicelle layer is a surfactant monolayer where the surfactant head group is adsorbed
onto the surface (via electrostatic interactions), with the tail group oriented upward.

5

Figure 1.1

D

C

log Cs
s

B

or
or
or

or

A

or
or

log Cm
m
Figure 1.1: Graph of logarithmic concentration of surfactant in a mobile phase (Cm)
versus the logarithmic concentration of surfactant adsorbed on a stationary phase (Cs).
Region A: Very low surfactant concentration below the CMC. Regions B and C:
Surfactant concentration below the CMC. Region D: Surfactant concentration above the
CMC.

6

As the surfactant concentration increases, additional surfactant monomers adsorb (tail
down) to the hemimicelle layer forming an admicelle (e.g. bilayer). A hemimicelle layer
results in the surface becoming more hydrophobic, while an admicelle layer results in the
surface gaining an overall opposite charge. In Region D, the excess surfactant monomers
will typically aggregate into spherical shaped micelles in an aqueous system, with the
hydrophilic head group in contact with water and the hydrophobic tail group forming the
core of the micelle. The core of the micelle provides an environment for other
hydrophobic species in an aqueous system. The concentration (or narrow concentration
range) where the extensive aggregation of the surfactant monomers into micelles takes
place is called the critical micelle concentration (CMC). If the concentration of the
surfactant is significantly increased beyond this point, liquid crystal phases can begin to
form (e.g. hexagonal or lamellar phases).
1.2.2

Fluorocarbon Surfactants
Fluorocarbon surfactants are surfactants in which hydrogen atoms of the tail

group have been partially or completely replaced by fluorine atoms. The majority of
commercially available fluorocarbon surfactants are based on a linear tail group
(−(CF2)nF), where the value of n ranges from 4 – 13, but averages 8 [9]. Typical
fluorocarbon surfactants are perfluorinated or may contain a few methylene groups, e.g.
fluorotelomers or zonyl alcohol (C8F17CH2CH2OH). Perfluorinated surfactants (PFSs)
are surfactants in which all of the hydrogen atoms on the hydrocarbon tail group have
been substituted by fluorine atoms, e.g. perfluorooctanoic acid (C8F17COOH). PFSs are
commercially prepared via two main processes: electrochemical fluorination or
telomerization [9,15,16]. The electrochemical fluorination process was invented over 50

7

years ago by Joseph Simons and commercialized by the 3M Company [16]. The
electrochemical fluorination process produces both odd- and even-numbered
fluorocarbon chain surfactants, distributed in a 70:30 % ratio between linear and
branched surfactants, respectively [17,18]. The telomerization process was commercially
developed by the DuPont Company, and predominantly produces even-numbered, linear
fluorocarbon chain surfactants (greater than 90 %) [19,20].
Partially fluorinated surfactants have greater solubility in conventional
hydrocarbon solvents than perfluorinated surfactants, as well as lower toxicity by being
more biodegradable [21]. Research has been conducted that studied the properties of
PFSs [22-24], including electrical properties [25], phase structures [26], physicochemical
properties [27], and properties such as Krafft points, CMCs, and surface tension [28]. In
addition, the physiochemical properties of HCSs and PFSs have been compared [29]. In
this study, Blanco et al. concluded that PFSs with a chain length 1.5 times shorter than
the analogous HCSs would have similar CMCs and thermodynamic properties. In
aqueous solutions, fluorocarbon surfactants typically behave similarly to hydrocarbon
surfactants. PFSs form the same type of micelles and micellar phases as their
hydrocarbon analogues [30,31], with the micelles retaining a globular shape even at high
concentrations [32]. However, there are a few exceptions due to differences in physical
and chemical properties. These differences in properties are often advantageously used
in applications where conditions might be too harsh for HCSs, such as hydraulic fluids in
aircraft, aqueous fire fighting foams, and electroplating baths [9,33].
The substitution of fluorine atoms onto the tail group makes PFSs more
hydrophobic than HCSs in aqueous solutions [13]. In addition, the tail groups of PFSs

8

are also lipophobic (oil-fearing) [34], thus having a greater tendency to leave a water or
water-oil environment and form a separate microphase. The tail groups of fluorocarbon
surfactants are more rigid than HCSs [35]. As such, fluorocarbon surfactants tend to
gather more at the air/water interface than HCSs. The substitution of fluorine atoms
increases the surface activity, allowing fluorocarbon surfactants to greatly reduce the
surface tension of water in comparison to analogous HCSs. Due to the higher average
−1

−1

bond energy of the C-F bond (485 kJ mol ) compared to the C-H bond (413 kJ mol ),
fluorocarbon surfactants are considered to be more thermally and chemically stable in the
environment [36]. Fluorocarbon surfactants are stable to heat, acids and bases, and
reducing and oxidizing agents [18,37]. Fluorocarbon surfactants typically have a much
larger pH usage range than analogous HCSs, being tolerant to exposure to low pH (i.e. 1
– 2) [7]. There are several disadvantages of fluorinated surfactants. Fluorocarbon
surfactants are more resistant to degradation, have a greater potential for bioaccumulation
[38], and are more bioaccessible to humans and animals in the environment than HCSs.
In addition, fluorinated surfactants are 2 – 3 orders of magnitude more expensive than
HCSs for the same amount.
Since the year 2000, the numbers of peer-reviewed publications related to
perfluorinated substances have dramatically increased [17]. A literature search of the
phrases “perfluorinated surfactants” and “perfluorinated compounds” illustrates this
increase (Figure 1.2). The search of “perfluorinated compounds” is a more total search,
as the results include literature on PFSs as well.

9

Figure 1.2:

Graph of number of publications versus the year of publication based on a

literature search of the phrases: (■) perfluorinated compounds and (■) perfluorinated
surfactants.

10

19
57
19
65
19
70
19
74
19
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
20
06
20
08

Number of Publications

Figure 1.2

200

180

160

140

120

100

80

60

40

20

0

Publication Year

11

The main research areas in current literature consist of 1) detection of PFSs in
environmental matrices, 2) toxicological effects of PFSs in humans and animals, and 3)
sources and fates of PFSs in the environment.
PFSs have been detected using techniques such as nuclear magnetic resonance
[39], fast atom bombardment/mass spectrometry [40], liquid chromatography with mass
spectrometry or tandem mass spectrometry [37,41-45], quadrupole/time of flight mass
spectrometry [46], gas chromatography [47-50], gas chromatography with electron
impact mass spectrometry [51], and gas chromatography with chemical ionization mass
spectrometry [52,53]. PFSs have also been detected within a wide variety of
environmental matrices, with perfluorooctane sulfonate (PFOS) and perfluorooctanoic
acid (PFOA) as the main two detected PFSs. These environmental matrices include
−1

−1

house dust (PFOS 201 ng g , PFOA 148 ng g ) [51], surface and subsurface water in
−1

China [54], surface and drinking water (PFOA in drinking water 519 ng L , PFOA in
−1

−1

surface water 33900 ng L , PFOS in surface water 3160 ng L ) [55], groundwater
[49,56,57], biota [58,59], and effluent from wastewater treatment plants [60,61]. Studies
were conducted on the adsorption of PFOS onto sand and clay surfaces [62], as well as
adsorption on sediments [63]. In the area of toxicological effects on humans and animals,
studies have been conducted into the general toxicity of PFSs [64], toxicity of PFOS and
−1

PFOA in aquatic life (PFOS, LC50 = 45.2 µg L

for midges) [65], toxicity in rats [66],

and in a zooplanktonic community [67]. The third area of interest has been the study of
the sources and fates of PFSs in the environment. These include studies identifying the
transport of PFSs via their volatile precursors [68,69].

12

1.3 Environmental Pollutant Transport
There are a variety of ways that organic pollutants can be transported through the
environment depending on their chemical and physical properties. The transport of
organic pollutants can take place in or between the atmosphere, water, and soil.
Atmospheric transport of pollutants can consist of deposition of pollutant particulates and
gases, precipitation (i.e. in rain or snow) of pollutant gases and aerosols, and adsorption
of pollutants on particulate matter (i.e. dust, soot, etc.) with subsequent deposition.
Water transport of pollutants can consist of volatilization from the water, sorption on
sediment or suspended particulates, and uptake or release by biota. Soil transport of
pollutants can consist of volatilization from soil or vegetation, uptake or release by biota
or vegetation, adsorption of pollutants onto soil particulates and transport via runoff, and
leaching into groundwater [70]. Volatile organic pollutants most readily undergo
atmospheric transport, while transport via water or soil plays a larger role for semivolatile, persistent organic pollutants. Since PFSs are nonvolatile persistent organic
pollutants, an understanding of their transport in water and soil matrices is of utmost
importance; however atmospheric transport may not be neglected.
Atmospheric transport of volatile precursors of PFSs has been studied as a means
of environmental transport [68]. In the long range transport of PFSs to remote
environments (e.g. polar icecaps), it is theorized that the volatile fluorotelomers are
transported through the atmosphere and are later degraded into PFSs, such as PFOA or
PFOS. As stated in Section 1.2.2, studies have been conducted that detected PFSs in
various water matrices ranging from surface water to groundwater [49,54-57,60,61]. In
water at low concentrations, monomers of PFSs will congregate either at the air/water

13

interface with the perfluorinated tail group oriented towards air, or adsorb at a water/soil
surface with the perfluorinated tail group oriented towards soil. As the concentration of
PFSs increases, the monomers pack closer together at the air/water or water/soil
interfaces and form a monolayer. As surfactant concentration rises above the CMC,
micelle formation takes place and the micelle is transported through the water. In a
groundwater system, soil organic matter (SOM) is considered a key component in the
accumulation of persistent organic pollutants; thus it will also play an important role in
the transport process of PFSs. The transport of PFSs in groundwater can be retarded via
sorption on SOM. SOM acts like micelles [71], providing a more favorable environment
for hydrophobic organic pollutants than water in a groundwater system. The
predominant sorption process is the partitioning of hydrophobic organic pollutants into
SOM, however in soil with low carbon content, reactions with the underlying mineral
surface can become important. Researchers have utilized several techniques to study the
transport of organic pollutants, ranging from batch equilibration, leaching equilibration,
solubility enhancement, and reversed-phase separation studies [72].
One of the most widely utilized methods for studying pollutant transport is the
batch equilibration method [73-75]. In this method, a known mass of soil (or sediment)
is placed in a vial with a known volume of solution that contains a known concentration
of the solute (i.e. pollutant) in water. A known concentration of an electrolyte, such as
sodium chloride, can be added to the solution in order to simulate the ionic strength of
groundwater [76,77]. The vial is shaken over a timeframe long enough to reach
equilibrium, then the vial is centrifuged, with the resulting phases separated and analyzed
to determine the concentration of solute. The mass of solute sorbed per unit mass of soil

14

(or sediment) can be determined through the difference between the initial concentration
of the solute and the final concentration of the solute after equilibrium was reached. This
technique has been utilized to determine the sorption of selected organic compounds [7882]. While this method has advantages, there are several disadvantages. A disadvantage
is the loss of the pollutant through volatilization or degradation through reaction with the
soil, leading to incorrect concentration values. The phases can have incomplete
separation, leading to difficulties in concentration analysis. Most importantly, the length
of time for the batch study might be insufficient for the system to reach equilibrium.
Another technique is the leaching equilibration method, or column method. In
this method, a solution containing a known concentration of the solute (i.e. pollutant)
dissolved in water is pumped through a column containing a sorbent (e.g. soil) at a
known flow rate. The effluent is collected and analyzed for the concentration of the
solute. Collection stops when the concentrations at the column inlet and outlet are equal,
and equilibrium has been reached. This technique has been used to determine the
sorption of organic compounds [77,83]. Disadvantages of this method can include poor
packing of the sorbent in the column and length of time necessary to reach equilibrium.
The sorption coefficients determined via batch and column methods have been correlated
with octanol/water partition coefficients (KOW) [84,85] and water solubility (SW) [85,86].
In the study by Vowles and Mantoura, there was good correlation between the
logarithmic sediment or soil-water partition coefficient (KP) and the logarithmic KOW (R
2

= 0.961) and the logarithmic SW (R = 0.955) for 14 hydrocarbons. In addition, the
correlation increased upon examining a homologous series of hydrocarbons. The
2

2

correlation between log KP and log KOW was R = 0.998 and R = 0.996 for a

15

2

homologous series of polycyclic aromatic hydrocarbon and alkylbenzenes, respectively.
2

The correlation between log KP and log SW was R = 0.994 for a homologous series of
alkylbenzenes.
Reversed-phase separation via liquid chromatography has also been utilized to
study the sorption constants and transport of organic compounds. The theory of reversedphase liquid chromatography (RPLC) is analogous to the concept of partitioning in
sorption [84,87]. In RPLC, the mobile phase represents a polar phase, while the
stationary phase represents a non-polar phase. Typically, the polar mobile phase is either
a pure solvent (e.g. methanol or water) or a solution (i.e. methanol/water mixture). The
stationary phase typically consists of a totally porous octadecylsilica material. As nonpolar organic compounds (i.e. pollutants) travel through a RPLC column, they partition
between the mobile and stationary phases and are retained on the non-polar phase. The
retention times of the compounds are used to calculate retention factors. The retention
factors from RPLC studies for selected organic compounds have been correlated with
sorption coefficients and, by extension, with environmental transport of the compounds
[72,85,88,89]. In the study by Vowles and Mantoura, there is excellent correlation
between log KP and the logarithmic retention factors on octadecylsilane phase (log k’ODS)
2

for a homologous series of polycyclic aromatic hydrocarbons (R = 0.998) and a
2

homologous series of alkylbenzenes (R = 0.996).
1.4 Environmental Pollutants
Environmental pollutants can be separated into several major types, each
consisting of several subclasses of relevant chemicals and pollutants. Some of the major
types of environmental pollutants include air, water, and soil contaminants [90]. These

16

types of pollution can arise from point sources (e.g. industrial plants and waste treatment
facilities) and nonpoint sources (e.g. runoff and atmospheric deposition) [2]. The
chemical properties, amount (i.e. concentration), and environmental persistence of a
contaminant impact how it is classified as an environmental pollutant. Based on these
criteria, organic compounds are types of environmental pollutants whose study is of
utmost importance. The U.S. Environmental Protection Agency (EPA) currently
regulates a list of 126 priority pollutants [91], which contains such environmental organic
pollutants as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls
(PCBs), substituted benzene compounds, chlorinated organic compounds, and pesticides.
Some of these organic pollutants have been listed as either known to be human
carcinogens or reasonably anticipated to be a human carcinogen [92]. Persistent organic
pollutants consist of a diverse group of organic compounds that are toxic, persistent,
bioaccumulate, and prone to long-range transport [93]. Examples of persistent organic
pollutants of concern include PAHs, polyhalogenated biphenyls (i.e. PCBs and
polybrominated biphenyls), substituted benzene compounds (e.g. anilines or the BTEX
compounds of toluene, ethylbenzene, and xylene), polyhalogenated dibenzodioxins and
dibenzofurans (i.e. dioxins and furans, respectively), and organochlorine pesticides. New
and emerging persistent organic pollutants include perfluorinated octyl sulfonamides and
sulfonates. Some of these pollutants are produced as by-products during processes
involving related organic compounds. For example, polybrominated dibenzodioxins and
dibenzofurans can be produced during the pyrolysis [94] or recycling [95] of plastics
coated with brominated flame retardants (such as polybrominated biphenyls) [96]. Due
to the toxicity of some of the persistent organic pollutants, the use of model solutes is

17

preferred in this research described in Chapters 3 – 6. The backbone structure of a
majority of the organic pollutants is based on substituted benzene compounds and PAHs;
thus benzene, substituted benzene compounds, and PAHs make good model solutes. A
brief discussion of these solutes is given in the following sections (Sections 1.4.1 and
1.4.2).
1.4.1

Substituted Benzene Compounds
Substituted benzene compounds are organic compounds in which hydrogen atoms

on the benzene ring have been partially or completely replaced by a substituent atom or
group. Typically, the substituent atom is a halogen atom (e.g. fluorine, chlorine, or
bromine). Common organic pollutant substituent groups include hydroxyl (–OH), methyl
(–CH3), ethyl (–C2H5), amine (–NH2), or nitro (–NO2) groups. Replacing hydrogen
atoms on the benzene ring with substituents can change various chemical and physical
properties. In terms of halogen substituents, increasing the number of halogen atoms
increases toxicity, octanol-water partition coefficients, soil sorption coefficients, and
decreases water solubility [97]. In addition, the type of halogen substituent affects
toxicity, such that brominated compounds are less toxic than chlorinated compounds
[98]. In comparing halogen substituents to alkyl groups (i.e. methyl and ethyl), the
compounds with the alkyl groups are slightly less toxic than those with the halogen
substituents [99]. Increasing the number of alkyl substituents increases the hydrophobic
characteristics (i.e. increased octanol-water partition coefficients, decreased water
solubility, etc.). However, increasing the number of amine substituents increases the
hydrophilic characteristics (i.e. decreased octanol-water partition coefficients, increased
water solubility, etc.). The change in characteristics will lead to different interactions

18

within a groundwater system (both in the presence and absence of surfactants). Thus the
use of these types of compounds as model analytes is justified. The compounds used as
model analytes in Chapters 3 – 6 consisted of benzene, biphenyl, and various mono- and
perhalogenated benzene compounds. The structures are shown in Figures 1.3 and 1.4.
1.4.2

Polycyclic Aromatic Hydrocarbons
Polycyclic aromatic hydrocarbons (PAHs) are a subclass of organic compounds,

which contain two, or more, fused aromatic rings. PAHs can be distinguished from one
another by the number of atoms in their member rings, ring number, and annelation
structure. PAHs can consist of four-, five-, six-, or seven-member rings. PAHs
containing only six-member rings, which are classified as alternant PAHs, are the most
common and most studied PAHs in the environment. Ring number is used to identify the
number of fused rings contained within a PAH. As the ring number increases, PAHs
exhibit an increase in hydrophobic characteristics (e.g. decreased volatility, decreased
water solubility, etc.) [97]. The term annelation structure refers to the degree of fusion
between the rings within an individual PAH.

19

Cl

F

Benzene

Br
Chlorobenzene

Fluorobenzene
F

F

Cl

F

F

Cl

Cl
Cl
Hexachlorobenzene

Ethylbenzene

m-Xylene

Cl

Cl

F
F
Hexafluorobenzene

Toluene

Bromobenzene

o-Xylene

Biphenyl

p-Xylene

Figure 1.3: Structures of the substituted benzene compounds used as model analytes for
environmental pollutants (e.g. polyhalogenated biphenyls, dioxins, and furans). The
analytes are used in Chapters 3 – 4.

20

H2 N

H2N

H2N
Aniline

Benzylamine

2,6-Dimethylaniline

H2 N

H2N

NH2
m-Toluidine

o-Toluidine

p-Toluidine

HN

HN

N-Ethylaniline

N-Methylaniline

N

N

N,N-Diethylaniline

N,N-Dimethylaniline

Figure 1.4: Structures of the amines used as analytes in Chapters 5 – 6.

21

Annelation structure can be divided into the following three categories: linearly
fused, ortho-fused, and peri-fused. The ortho-fused (angularly-fused) PAHs are
compounds in which two rings have two, and only two, atoms in common [100]. The
peri-fused PAHs are compounds in which one ring contains two, and only two, atoms in
common with each of two or more rings of a continuous series of rings [100]. The
linearly fused PAHs are compounds in which all the rings are on a single axis in a
continuous series. As the ring number increases for the linearly-fused PAHs, the stability
decreases. This trend is not observed for the ortho-fused PAHs. The PAHs used as
model analytes in Chapter 3 are of the alternant class, range in ring number from 2 – 4,
and are of all three annelation categories. The structures of the PAHs are shown in
Figure 1.5.

22

Naphthalene

Anthracene

Phenanthrene

Pyrene

Figure 1.5: Structures of PAHs used as model analytes in Chapter 3.

23

1.5 Statement of Dissertation Objectives
It is believed that fluorocarbon surfactants behave like hydrocarbon surfactants in
aqueous solutions. Like HCSs, literature has shown that PFSs can enhance the
solubilization of PAHs [28,101,102]. However, fluorocarbon surfactants have been
shown to solubilize fluorinated compounds better than HCSs [103]. Nevertheless, little
to no research has been aimed at identifying what transport effects PFSs would have on
environmental co-contaminants. As such, the overall objective of the research within this
dissertation was to determine the transport effects of PFSs on known organic
contaminants, in comparison to the transport effects of HCSs, in an environmental
groundwater system. Several research objectives where established to be investigated;
and are as follows:
•

Develop a controllable analytical technique that can fundamentally resemble an
environmental groundwater system, in which to study transport effects.

•

Determine what transport effects the inclusion of a PFS, both above and below the
CMC, in a groundwater system will have on neutral organic pollutants, and
compare those effects to that of a HCS.

•

Determine what transport effects the inclusion of an anionic PFS, below the
CMC, in a groundwater system will have on cationic organic pollutants, and
compare those effects to that of a HCS.

•

Identify and quantify PFSs in environmentally relevant samples.
Chapter 2 of this dissertation addresses the first objective, and details the

experimental methods and instrumentation used during the course of this research to
model a groundwater system. Investigations to experimentally determine the CMC and

24

aggregation number of a PFS are detailed in Chapter 2, with the hopes of applying these
experiments to emerging PFS. In addition, Chapter 2 details the investigation to
determine the transport of surfactants within the experimental system using RPLC with
refractive index detection. Chapters 3 and 4 address the second objective, and detail the
research comparing the transport effects of PFSs and HCSs on neutral organic copollutants in a model groundwater system. Investigations are made both above (Chapter
3) and below (Chapter 4) the CMC, to compare the unknown transport effects of PFSs to
the transport effects of HCSs (above and below the CMC, respectively). Chapter 5
addresses the third objective, and details the research comparing the transport effects of
anionic PFSs and HCSs on cationic organic co-pollutants in a model groundwater system.
Chapter 6 details the investigation of system peaks as markers of surfactant retention
within the experimental system. Chapter 7 addresses the fourth objective, and details
research performed at the National Institute of Advanced Industrial Science and
Technology in Tsukuba, Japan, which uses a method to detect PFSs in environmental
samples. Chapter 8 gives a summary of future directions within the field of study into the
transport effects of PFSs.

25

REFERENCES

26

1.6 References
[1]

I. Toro-Suarez, Reduced Transport of Organic Pollutants in Soil Modified with
Hexadecyltrimethylammonium, Ph.D. Dissertation, Michigan State University,
East Lansing, MI, 1994.

[2]

U.S. Environmental Protection Agency, EPA's Polluted brochure, EPA-841-F-94005, 1994.

[3]

S.J. Grimberg, C.T. Miller, M.D. Aitken, Environ. Sci. Technol. 30 (1996) 29672974.

[4]

J.S. Leithner, M.P. Mastumotom, Hazardous Industrial Wastes 28 (1996) 211218.

[5]

R.T. Kureja, D. Hodko, O.J. Murphy, Contam. Soils 2 (1997) 151-165.

[6]

C. Madichie, G.M. Greenway, T. McCreedy, Anal. Chim. Acta 392 (1999) 39-46.

[7]

R.J. Farn, Chemistry and Technology of Surfactants, Blackwell Publishing,
Oxford, UK, 2006.

[8]

M. Pabon, J.M. Corpart, J. Fluorine Chem. 114 (2002) 149-156.

[9]

E. Kissa, Fluorinated Surfactants and Repellents, Marcel Dekker, New York, NY,
2001.

[10]

M.J. Rosen, Surfactants and Interfacial Phenomena, 3 ed., John Wiley and Sons,
Inc., 2004.

[11]

M.R. Porter, Handbook of Surfactants, 2
NY, 1994.

[12]

M.R. Porter, Handbook of Surfactants, Chapman and Hall, New York, NY, 1991.

[13]

P. Mukerjee, J. Am. Oil Chem. Soc. 59 (1982) 573-578.

[14]

M.J. Schwuger, Ber. Bunsenges. Phys. Chem. 83 (1979) 1193-1205.

[15]

H.C. Fielding, Organofluorine Chemicals and Their Industrial Applications, ed.
R.E. Banks, Ellis Horwood, New York, NY, 1979.

[16]

J.H. Simons, J. Electrochem. Soc. 95 (1949) 47-52.

rd

nd

27

ed., Chapman and Hall, New York,

[17]

J.W. Martin, K. Kannan, U. Berger, P. de Voogt, J. Field, J. Franklin, J.P. Giesy,
T. Harner, D.C.G. Muir, B. Scott, M. Kaiser, U. Järnberg, K.C. Jones, S.A.
Mabury, H. Schroeder, M. Simcik, C. Sottani, B. van Bavel, A. Kärrman, G.
Lindström, S. van Leeuwen, Environ. Sci. Technol. (2004) 248A-255A.

[18]

E. Kissa, Fluorinated Surfactants: Synthesis, Properties, and Applications, Marcel
Dekker, New York, NY, 1994.

[19]

J. C. D’eon, S.A. Mabury, Environ. Sci. Technol. 41 (2007) 4799-4805.

[20]

M.M. Schultz, D.F. Barofsky, J.A. Field, Environ. Eng. Sci. 20 (2003) 487-501.

[21]

E.G. Shafrin, W.A. Zisman, J. Phys. Chem. 66 (1962) 740-748.

[22]

E. Fisicaro, E. Pelizzetti, R. Bongiovanni, E. Borgarello, Colloid. Surface. 48
(1990) 259-275.

[23]

R. Bongiovanni, E. Borgarello, F.M. Carlini, E. Fisicaro, E. Pellizzetti, Colloid.
Surface. 48 (1990) 277-283.

[24]

R. Bongiovanni, E. Borgarello, C. Carniani, C. Genova, Colloid. Surface. 54
(1991) 75-82.

[25]

S. Erkoc, F. Erkoc, J. Mol. Struct. Theochem. 549 (2001) 289-293.

[26]

K. Fontell, B. Lindman, J. Phys. Chem. 87 (1983) 3289-3297.

[27]

K. Shinoda, M. Hato, T. Hayashi, J. Phys. Chem. 76 (1972) 909-914.

[28]

H. Kunieda, K. Shinoda, J. Phys. Chem. 80 (1976) 2468-70.

[29]

E. Blanco, A. González-Pérez, J.M. Ruso, R. Pedrido, G. Prieto, F. Sarmiento, J.
Colloid. Interf. Sci. 288 (2005) 247-260.

[30]

H. Hoffmann, J. Wurtz, J. Mol. Liq. 72 (1997) 191-230.

[31]

V. Tomasic, A. Chittofratia, N. Kallay, Colloid. Surface. A 104 (1995) 95-99.

[32]

R. Muzzalupo, G.A. Ranieri, C. La Mesa, Colloid. Surface. A 104 (1995) 327336.

[33]

G. Lewandowski, E. Meissner, E. Milchert, J. Hazard. Mater. 136 (2006) 385391.

[34]

P. Barthélémy, V. Tomao, J. Selb, Y. Chaudier, B. Pucci, Langmuir 18 (2002)
2557-2563.

28

[35]

K. Matsuoka, Y. Moroi, Curr. Opin. Colloid In. 8 (2003) 227-235.

[36]

E. Kissa, Fluorinated Surfactants, 2

[37]

M. Villagrasa, M.L. De Alda, D. Barcelo, Anal. Bioanal. Chem. 386 (2006) 953972.

[38]

R. Renner, Environ. Sci. Technol. 36 (2002) 54A-55A.

[39]

C.A. Moody, W.C. Kwan, J.W. Martin, D.C.G. Muir, S.A. Mabury, Anal. Chem.
73 (2001) 2200-2206.

[40]

M.M. Schultz, D.F. Barofsky, J.A. Field, Chimia 57 (2003) 556-560.

[41]

A-M. Weremiuk, S. Gerstmann, H. Frank, J. Sep. Sci. 29 (2006) 2251-2255.

[42]

N. Yamashita, K. Kannan, S. Taniyasu, Y. Horii, T. Okazawa, G. Petrick, T.
Gamo, Environ. Sci. Technol. 38 (2004) 5522-5528.

[43]

D. Skutlarek, M. Exner, H. Faerber, Environ. Sci. Pollut. R. Int. 13 (2006) 299307.

[44]

R. Loos, J. Wollgast, T. Huber, G. Hanke, Anal. Bioanal. Chem. 387 (2007)
1469-1478.

[45]

M. Murakami, K. Kuroda, N. Sato, T. Fukushi, S. Takizawa, H. Takada, Environ.
Sci. Technol. 43 (2009) 3480-3486.

[46]

L. Song, A.D. Wellman, H. Yao, J. Adcock, Rapid Commun. Mass Sp. 21 (2007)
1343-1351.

[47]

P. Voogt, M. Sàez, Trends Anal. Chem. 25 (2006) 326-342.

[48]

M. Joyce, M.J.A. Dinglasan, Y. Yun, E.A. Edwards, S.A. Mabury, Environ. Sci.
Technol. 38 (2004) 2857-2864.

[49]

C.A. Moody, J.A. Field, Environ. Sci. Technol. 33 (1999) 2800-2806.

[50]

C.A. Moody, J.A. Field, Environ. Sci. Technol. 34 (2000) 3864-3870.

[51]

M.J. Strynar, A.B. Lindstrom, Environ. Sci. Technol. 42 (2008) 3751-3756.

[52]

J.W. Martin, D.C.G. Muir, C.A. Moody, D.A. Ellis, W.C. Kwan, K.R. Solomo,
S.A. Mabury, Anal. Chem. 74 (2002) 584-590.

nd

ed., Marcel Dekker, New York, NY, 2002.

29

[53]

R. Alzaga, J.M. Bayona, J. Chromatogr. A 1042 (2004) 155-162.

[54]

X. Ju, Y. Jin, K. Sasaki, N. Saito, Environ. Sci. Technol. 42 (2008) 3538-3542.

[55]

D. Skutlarek, M. Exner, H. Faerber, Environ. Sci. Pollut. Res. Int. 13 (2006) 299307.

[56]

M.M. Schultz, D.F. Barofsky, J.A. Field, Environ. Sci. Technol. 38 (2004) 18281835.

[57]

C.A. Moody, G.N. Hebert, S.H. Strauss, J.A. Field, J. Environ. Monitor. 5 (2003)
341-345.

[58]

C.A. Moody, J.W. Martin, W.C. Kwan, D.C.G. Muir, S.A. Mabury, Environ. Sci.
Technol. 36 (2002) 545-551.

[59]

K.S. Guruge, P.M. Manage, N. Yamanaka, S. Miyazaki, S. Taniyasu, N.
Yamashita, Chemosphere 73 (2008) S210-S215.

[60]

M.H. Plumlee, J. Larabee, M. Reinhard, Chemosphere 72 (2008) 1541-1547.

[61]

B. Boulanger, J.D. Vargo, J.L. Schnoor, K.C. Hornbuckle, Environ. Sci. Technol.
39 (2005) 5524-5530.

[62]

R.L. Johnson, A.J. Anschutz, J.M. Smolen, M.F. Simcik, R.L. Penn, J. Chem.
Eng. Data 52 (2007) 1165-1170.

[63]

C.P. Higgins, R.G. Luthy, Environ. Sci. Technol. 40 (2006) 7251-7256.

[64]

C.M. Cooney, Environ. Sci. Technol. 42 (2008) 3486-3487.

[65]

M.M. MacDonald, A.L. Warne, N.L. Stock, S.A. Mabury, K.R. Solomon, P.K.
Sibley, Environ. Toxicol. Chem. 23 (2004) 2116-2123.

[66]

J.L. Butenhoff, G.L. Kennedy, S.R. Frame, J.C. O’Connor, R.G. York,
Toxicology 196 (2004) 95-116.

[67]

H. Sanderson, T.M. Boudreau, S.A. Mabury, K.R. Solomon, Ecotox. Environ.
Safe. 58 (2004) 68-76.

[68]

U. Schenker, M. Scheringer, M. Macleod, J.W. Martin, I.T. Cousins, K.
Hungerbühler, Environ. Sci. Technol. 42 (2008) 3710-3716.

[69]

J.C. D’eon, S.A. Mabury, Environ. Sci. Technol. 41 (2007) 4799-4805.

[70]

Y. Cohen, Environ. Sci. Technol. 20 (1986) 538-544.

30

[71]

E. Heyse, D. Augustijn, P.S.C. Rao, J.J. Delfino, Crit. Rev. Env. Sci. Tec. 32
(2002) 337-397.

[72]

A. D. Site, J. Phys. Chem. Ref. Data 30 (2001) 187-439.

[73]

T.B. Stauffer, W.G. MacIntyre, D.C. Wickman, Environ. Toxicol. Chem. 8 (1989)
845-852.

[74]

T.H. Dao, D. Bouchard, J. Mattice, T.L. Lavy, Soil Sci. 141 (1986) 26-30.

[75]

N. Carmosin, L.S. Lee, Environ. Sci. Technol. 42 (2008) 6559-6565.

[76]

G. Singh, W.F. Spencer, M.M. Cliath, M.T. van Genuchten, J. Environ. Qual. 19
(1990) 520-525.

[77]

J.A. Johnson, W.J. Farmer, Soil Sci. 155 (1993) 92-99.

[78]

C.T. Chiou, D.E. Kile, D.W. Rutherford, G. Sheng, S.A. Boyd, Environ. Sci.
Technol. 34 (2000) 1254-1258.

[79]

S. Sun, W.P. Inskeep, S.A. Boyd, Environ. Sci. Technol. 29 (1995) 903-913.

[80]

D.E. Kile, C.T. Chiou, H. Zhou, H. Li, O. Xu, Environ. Sci. Technol. 29 (1995)
1401-1406.

[81]

C.T. Chiou, S.E. McGroddy, D.E. Kile, Environ. Sci. Technol. 32 (1998) 264269.

[82]

G. Sheng, C.T. Johnston, B.J. Teppen, S.A. Boyd, J. Agr. Food Chem. 49 (2001)
2899-2907.

[83]

L.W. Lion, T.B. Stauffer, W.G MacIntyre, J. Contam. Hydrol. 5 (1990) 215-234.

[84]

C.T. Chiou, P.E. Porter, D.W. Schmedding, Environ. Sci. Technol. 17 (1983)
227-231.

[85]

P.D. Vowles, R.F.C. Mantora, Chemosphere 16 (1987) 109-116.

[86]

C.T. Chiou, L.J. Peters, V.H. Freed, Science 206 (1979) 831-832.

[87]

C. Horvath, W.J. Melander, J. Chromat. Sci. 15 (1977) 393-404.

[88]

K. Valkó, J. Chromatogr. A 1037 (2004) 299-310.

[89]

H. Hong, L. Wang, S. Han, Z. Zhang, G. Zou, Chemosphere 34 (1997) 827-834.

31

[90]

U.S. Environmental Protection Agency,
http://www.epa.gov/ebtpages/pollutants.html
http://www.epa.gov/ebtpages/pollutants.html#subtopics.

[91]

U.S. Environmental Protection Agency, EPA-40-CFR-423, Appendix A,
http://www.epa.gov/waterscience/methods/pollutants.htm.

[92]

Report on Carcinogens, 11 ed., U.S. Department of Health and Human Services,
Public Health Service, National Toxicology Program.

[93]

R. Lohmann, K. Breivik, J. Dachs, D. Muir, Environ. Pollut. 150 (2007) 150-165.

[94]

H. Thoma, G. Haushulz, E. Knorr, O. Hutzinger, Chemosphere 16 (1987) 277285.

[95]

J. Ebert, M. Bahadir, Environ. Int. 29 (2003) 711-716.

[96]

B. Jansson, L. Asplund, M. Olsson, Chemosphere 16 (1987) 2343-2349.

[97]

C.L. Yaws, Chemical Properties Handbook, McGraw-Hill Book Co., New York,
NY, 1999.

[98]

L.W.D. Weber, H. Greim, J. Toxicol. Env. Heal. A. 50 (1997) 195-216.

[99]

T.W. Schultz, G.W. Riggin, Toxicol. Lett. 25 (1985) 47-54.

th

[100] A.D. McNaught, A. Wilkinson, IUPAC Compendium of Chemical Terminology,
nd
2 ed., Blackwell Scientific Publications, Oxford, UK, 1997.
[101] Y.J. An, E.R. Carraway, M.A. Schlautman, Water Res. 36 (2002) 300-308.
[102] Y.-J. An, S.-W. Jeong, J. Colloid Interf. Sci. 242 (2001) 419-424.
[103] T. Asakawa, T. Kitaguchi, S. Miyagishi, J. Surfactants Deterg. 1 (1998) 195-199.

32

CHAPTER 2: EXPERIMENTAL METHODS
2.1 Introduction
In order to study the transport effects of hydrocarbon and perfluorinated
surfactants on co-contaminants in an environmental system, an analytical technique was
required that could fundamentally resemble such a system, but whose parameters were
controllable. For this purpose, reversed-phase liquid chromatography (RPLC) was used
as a model for a flow-through groundwater system. The stationary phase packing
material, as well as the instrumentation and treatment of the data for the various
experimental measurements are explained in the following sections.
2.2 Chromatographic Measurements
2.2.1

Stationary Phase
The commercially available stationary phase chosen consisted of pellicular

particles made of small, non-porous glass beads with a 5.0 µm diameter covered with
chemically bonded porous octadecylsilica (ODS) with a 300 Å pore size, 2.1 µmol m
2 −1

bonding density, 0.39 % carbon content, and 6.0 m g

−2

surface area. The pellicular

material (Poroshell 300SB-C18, Agilent) was selected because it is a well defined packing
material, whose properties of carbon content and surface area are substantially lower than
those of traditional, totally porous ODS materials routinely used in RPLC (12 – 18 %,
2 −1

200 – 400 m g

respectively). These properties of the pellicular material are within,

and more closely resemble, the typical ranges of carbon content (0.11 – 6.09 %) and
2 −1

surface area (1.07 – 54.0 m g ) for various soils, bed sediments, and suspended solids
[1]. Based on these properties, it is believed that the pellicular material is more
representative as a model for soil than traditional RPLC stationary phases.
33

2.2.2

Instrumentation
The liquid chromatography system, represented in Figure 2.1, was used to

determine the chromatographic retention of the model analytes in aqueous surfactant
mobile phases. The system consisted of a single-piston reciprocating pump (Beckman,
Model 110B) operating with a maximum pressure limit of 4500 psi. Samples were
introduced to the system via an injection valve (Valco, Model EC6W) with a 20 µL
injection loop. Upon injection, the samples are carried through a commercially available
analytical column (4.6 mm i.d. x 250 mm length) packed with the Poroshell material
previously described (Section 2.2.1), whose outlet is connected to a commercially
available ultraviolet-visible absorbance detector (Hitachi, Model L-4200). The UV
absorbance wavelength of 254 nm was specific for the detection of the analytes, and did
not incur any interference from the surfactants. The output signal from the UV-visible
absorbance detector was either recorded on a chart recorder (Linear Cole-Parmer
Instrument Company, Model 0555-0000) or converted to the digital domain (National
Instruments, Model PCI-MIO-16XE-50) and stored via a user-defined software program
(National Instruments, Labview v5.1) for further data analysis. All experiments were
carried out at ambient temperature.
2.2.3

Data Analysis
The void time, t0, was taken as the first positive deviation from the baseline

arising from either residue methanol or lithium nitrate (LiNO3) in each sample. The
retention time, tR, for each analyte was determined from the peak maximum, which was
appropriate for the symmetric Gaussian peaks observed in these studies.

34

A

D
I

C

P

Figure 2.1: Schematic diagram of the liquid chromatography system used for the
determination of transport effects of perfluorinated surfactants. System components:
single-piston reciprocating pump (P), injection valve (I), analytical column with
Poroshell stationary phase (A), UV-visible absorbance detector (D), and computer data
acquisition system (C).

35

The retention factor, k, was then calculated by

t
k= R

−

t0

(2.1)

t0

The k values (average of at least three trials) were used for the subsequent elucidation of
transport effects (Chapters 3 – 5), the determination of equilibrium constants (Chapter 3),
and selectivity factors (Chapters 4 – 5).
2.2.4

Refractive Index

RPLC with refractive index detection was investigated in an effort to
experimentally determine the retention of the representative hydrocarbon and
perfluorinated surfactants in the experimental system. Refractive index measurements
were performed in tandem with UV-visible absorbance detection, with the UV-visible
absorbance detector used as a secondary means to identify the carboxylic acids. The
liquid chromatography system previously described (Section 2.2.2) was used with slight
modification. The outlet of the analytical column was connected to a commercially
available refractive index detector (Beckman, Model 156), whose sample outlet was
connected, via a stainless steel connector, to the sample inlet of the UV-visible
absorbance detector. The UV absorbance wavelength of 203 nm was chosen for the
detection of carboxylic acids (with carbon chain lengths of C1 – C4, C6, and C8) and the
representative surfactants. The output signal from both the refractive index and UVvisible absorbance detector was recorded on a chart recorder for further data analysis.
Injections of the various carboxylic acids were first performed to validate the
sensitivity of refractive index detector. While peaks for the carboxylic acids were
observed with the UV-visible detector, corresponding peaks were not observed with the

36

refractive index detector. The refractive index detector proved to have an inadequate
sensitivity to accurately determine the retention of the carboxylic acids (at concentrations
−3

of 5.0 x 10

M). Thus, the retention of the surfactants within the chromatographic

system could not be determined via this method. Consequently, an alternative approach
based on the detection of system peaks via UV-visible absorbance was later employed
(Chapter 6).
2.3 Conductivity Measurements

Capillary electrophoresis (CE) techniques have previously been used to determine
the critical micelle concentration (CMC) of various surfactants [2-5]. Based on this
previously reported literature, conductivity measurements of aqueous sodium dodecyl
sulfate (SDS) and lithium perfluorooctane sulfonate (LiPFOS) solutions were performed
via CE to experimentally determine the CMC of the surfactants.
2.3.1

Instrumentation

Conductivity measurements were experimentally performed using a CE system
that had been constructed and utilized previously within the McGuffin research group [6].
The CE system was constructed of an incubation oven (Labline, Model 3500-DT), which
was able to hold a constant temperature within the range of 5.0 – 50.0 ± 0.2 °C. The
modified oven contained plexiglass inserts, which supported the various components of
the system (e.g. buffer and sample vials, capillary, etc.) while electrically insulating the
interior of the oven. The samples were carried through a fused-silica capillary (50.0 µm
i.d., 360 µm o.d., 60.0 cm length) upon injection using an auto-reversing high-voltage
power supply (Bertan High Voltage, Model 2341-A). The power supply was used in
fixed voltage mode (20.0 kV ± 0.1 %) while monitoring the current. A user-defined

37

software program (National Instruments, Labview v5.1) was used to store data from the
power supply that represented the current in fixed voltage mode.
2.3.2

Data Analysis

Prior to each set of SDS measurements, the CE system was rinsed with a 0.1 M
sodium hydroxide solution for 10 minutes, deionized water for 10 minutes, and 1.0 mM
SDS solution for at least two hours to equilibrate the capillary. Aqueous samples of SDS
at various concentrations (1, 2, 4, 6, 8, 10, 20, 30, and 40 mM) were each injected into the
system at five temperatures (ambient, 10 °C, 15 °C, 30 °C, and 35 °C), with the resulting
current measured. It was observed that increasing the SDS concentration resulted in the
current increasing. In addition, increasing the temperature of the system resulted in an
increase in the current, which was more prominent at higher concentrations of SDS.
A graph of the current versus surfactant concentration, at each temperature, for
SDS is shown in Figure 2.2. The graph displays an increasing linear trend with a break in
the slope of the line, resulting in two distinct linear regions for SDS. The break in the
slope represents the CMC of the surfactant solution at that temperature. Statistical
treatment of the data for the two regions via linear regression resulted in two equations
that were combined to determine the CMC of the surfactant at a specific temperature
(Table 2.1). For SDS, the slope trends and general shape of the lines were similar at all
temperatures. The experimentally determined CMC based on the data at ambient
temperature (22 °C) was 8.41 mM, and was within 4.0 % error of the reported literature
value of 8.1 mM (25 °C) [7].

38

Figure 2.2: Graph of the current versus the concentration of sodium dodecyl sulfate

(SDS). Temperatures: (♦) ambient, (■) 10 °C, (▲) 15 °C, (x) 30 °C, (∗) 35 °C. Other
experimental conditions as given in the text.

39

Figure 2.2
20
18
16

Current, I (µA)

14
12
10
8
6
4
2
0
0

5

10

15

20

25

Concentration of SDS (mM)

40

30

35

40

45

Table 2.1: Experimentally determined CMC values for SDS via conductivity
measurements

0.455 ± 0.012

Intercept ± std.
error
−0.09 ± 0.06

0.9979

high

0.176 ± 0.004

2.23 ± 0.11

0.9981

8.39

low
high

0.501 ± 0.013
0.208 ± 0.005

−0.05 ± 0.07
2.41 ± 0.12

0.9978
0.9984

22 °C

8.41

low
high

0.560 ± 0.014
0.251 ± 0.006

−0.04 ± 0.07
2.56 ± 0.15

0.9982
0.9983

30 °C

8.58

low
high

0.692 ± 0.016
0.311 ± 0.007

0.02 ± 0.08
3.29 ± 0.17

0.9984
0.9986

35 °C

8.64

low

0.779 ± 0.013

−0.14 ± 0.08

0.9994

high

0.360 ± 0.011

3.48 ± 0.25

0.9982

Experimental
Temperature

CMC
(mM)

10 °C

8.30

15 °C

Linear
Range
low

Slope ± std. error

41

R

2

Conductivity measurements of LiPFOS were performed after SDS measurements.
Prior to LiPFOS measurements, the CE system was rinsed with a 0.1 M lithium
hydroxide solution for 10 minutes, deionized water for 10 minutes, and a 6.5 mM
LiPFOS solution for at least two hours to equilibrate the capillary. Aqueous samples of
LiPFOS at various concentrations (1, 2, 4, 5, 6, 8, 10, 20, 30, and 40 mM) were each
injected into the system at ambient temperatures (25 °C and 23 °C), with the resulting
current measured.
A graph of the current versus surfactant concentration, at ambient temperature, for
LiPFOS is shown in Figure 2.3. The graph displayed an initial decreasing trend at very
low concentrations (1 – 4 mM), followed by an increasing trend (4 – 20 mM), and then a
decreasing trend (20 – 40 mM). Due to the “S-curve” shape of the graph, a definitive
break in the slope could not be identified, thus the CMC for LiPFOS could not be
experimentally determined from this method. A possible explanation for this
phenomenon could be the early formation of dimers or trimers of the fluorinated
surfactant at low concentrations prior to the formation of micelles at higher
concentrations. Due to the inability to determine the CMC of LiPFOS via this method,
the accepted literature values for the CMC of SDS and LiPFOS (8.1 mM and 6.5 mM
respectively) [7,8] were used in the calculations for the above CMC studies (Chapter 3).

42

Figures 2.3A-B: Graphs of current versus the concentration of lithium perfluorooctane

sulfonate (LiPFOS). Temperatures: (A) 25 °C, (B) 23 °C. Other experimental
conditions as given in text.

43

Figure 2.3A
40
35

Current, I (µA)

30
25
20
15
10
5
0
0

5

10

15

20

25

Concentration of LiPFOS (mM)

44

30

35

40

45

Figure 2.3B
40
35

Current, I (µA)

30
25
20
15
10
5
0
0

5

10

15

20

25

Concentration of LiPFOS (mM)

45

30

35

40

45

2.4 Densitometry Measurements

Several techniques, such as positron annihilation lifetime spectroscopy [9], small
angle neutron scattering [10], or light scattering techniques [11,12], have been used to
determine the aggregation number of surfactants. However, it can be difficult to obtain
reliable data by these methods for some surfactant solutions whose surfactant carbon
chain length approaches 1.0 nm. For this study, the aggregation number for the
representative hydrocarbon and perfluorinated surfactants were experimentally
determined via densitometry measurements.
2.4.1

Instrumentation

The density of aqueous SDS and LiPFOS solutions, within the concentration
range of 0.02 – 0.1 M, were measured by using a calculating digital density meter (Anton
PAAR, Model DMA 45 SI), which was held at a temperature of 25 °C by a PolyScience
temperature controller (VWR-Scientific Products, Model 1166).
2.4.2

Data Analysis

The density of a surfactant solution (ρ) can be expressed as
ρ = w1ρ1 + w 2ρ2

(2.2)

where ρ1 and ρ2 are the densities and w1 and w2 are the weight percents of the surfactant
and water, respectively. Since w2 = 1 – w1, equation 2.2 can be expressed as
ρ = ( ρ1 − ρ2 ) w1 + ρ2

(2.3)

A graph of the density of the surfactant solution versus the weight percent of the
surfactant yields a linear correlation, where the sum of the slope and the intercept

46

provides a quantitative estimate of the density of the surfactant. The density of the
surfactant is related to the volume of the surfactant monomer, v, by

ρ1 =

MW
( Na v )

(2.4)

where MW is the molecular weight of the surfactant, and Na is Avogadro’s number. The
volume of the surfactant is then related to the aggregation number, N, by
N=

4πR 3
3v

(2.5)

where R is the radius of the spherical micelle, which is equivalent to the length of the
linear surfactant monomer [13]. The length of LiPFOS (1.17 nm) and SDS (1.67 nm)
were calculated by using the PyMOL molecular modeling software (DeLano Scientific,
version 0.09).
The aggregation number of SDS determined from these experimental data (65 ±
8) was in good agreement with the literature value (62) [7,14]. Based on this good
agreement, the experimentally determined aggregation numbers for SDS and LiPFOS (11
± 3) were used in the calculations for the above CMC studies (Chapter 3).
2.5 Summary

The use of a well-defined experimental system, experimentally accurate physical
data, and robust data treatment is necessary in order to study the transport effects of
perfluorinated surfactants on co-contaminants. This chapter detailed the experimental
system and data analysis procedures that were used to collect and analyze the desired data
for the experiments performed in Chapters 3 – 5.

47

REFERENCES

48

2.6 References

[1]

D.E. Kile, C.T. Chiou, H. Zhou, H. Li, O. Xu, Environ. Sci. Technol. 29 (1995)
1401-1406.

[2]

A. Cifuentes, J.L. Bernal, J.C. Diez-Masa, Anal. Chem. 69 (1997) 4271-4274.

[3]

M. Schwing, Bulletin de l’Union des Physiciens 97 (2003) 323-328.

[4]

C.-E. Lin, J. Chromatogr. A 1037 (2004) 467-478.

[5]

H. Liu, Y. Gao, Z. Hu, J. Anal. Chem. 62 (2007) 176-178.

[6]

C.I.D. Newman, Capillary Electrophoresis for Thermodynamic and Kinetic
Studies, Ph.D. Dissertation, Michigan State University, East Lansing, MI, 2006.

[7]

D.W. Armstrong, Sep. Purif. Methods 14 (1985) 213-304.

[8]

K. Shinoda, M. Hato, T. Hayashi, J. Phys. Chem. 76 (1972) 909-914.

[9]

F. Bockstahl, G. Duplatre, Phys Chem Chem Phys 2 (2000) 2401-2405.

[10]

H. Hoffmann, J. Kalus, H. Thurn, Colloid Polymer Sci 261 (1983) 1043-1049.

[11]

Z.J. Yu, R.D. Neuman, Langmuir 8 (1992) 2074-2076.

[12]

C. Thevenot, B. Grassl, G. Bastiat, W. Binana, Colloid Surface Physicochem Eng
Aspects 252 (2005) 105-111.

[13]

J.N. Israelachvili, Intermolecular and Surface Forces: With Applications to
Colloidal and Biological Systems, Academic Press, San Diego, CA, 1989, p. 250.

[14]

M. Arunyanart, L.J. Cline Love, Anal. Chem. 56 (1984) 1557-1561.

49

CHAPTER 3: COMPARISON OF TRANSPORT EFFECTS ABOVE THE
CRITICAL MICELLE CONCENTRATION
3.1 Introduction

The ability of hydrocarbon surfactants to affect the transport, sorption, and
solubility of neutral hydrophobic organic compounds has been reported in the literature
[1-6]. Further studies have examined the effect of hydrocarbon surfactants on the
sorption of organic compounds in a soil-water system [7-9].
In addition to these environmental studies, hydrocarbon surfactants have been
used as mobile phase modifiers in many analytical separation techniques, such as ion-pair
chromatography, micellar liquid chromatography (MLC), and micellar electrokinetic
capillary chromatography [10,11]. The addition of a hydrocarbon surfactant at low
concentrations has been widely used for ion-pair chromatography in order to enhance the
separation of oppositely charged ions in solution. Although surfactant monomers have
also been shown to enhance the solubility of neutral hydrophobic organic compounds,
their general effectiveness is substantially less than that of surfactant aggregates formed
above the critical micelle concentration (CMC) [1,2,9]. In a micellar solution, neutral
compounds can partition into the micelle, thus increasing the solubility and transport in
the aqueous system [1-6,10,11].
Compared to hydrocarbon surfactants, perfluorinated surfactants have
characteristics that impart greater chemical and thermal stability, as well as the ability to
form micelles at lower concentrations [12-20]. These properties make the commercial
and industrial use of perfluorinated surfactants highly appealing. Throughout the last
three decades, the production and use of perfluorinated surfactants for commercial and
industrial applications increased. However, in response to growing concerns, the major

50

US manufacturer of perfluorinated surfactants, 3M, voluntarily ceased production of
surfactants based on perfluorooctane sulfonate (PFOS) chemistry in May 2000 [21]. In
March 2006, 3M, DuPont, and six other companies voluntarily agreed to reduce
emissions of perfluorooctanoic acid (PFOA) and related compounds [22,23]. Based on
numerous studies, perfluorinated surfactants are globally distributed and persistent in the
environment. These chemicals also bioaccumulate, thereby posing a significant health
risk in humans and animals [24-26]. Studies have been conducted to understand the
physicochemical properties [27] as well as the structural and electronic properties [28].
Additional studies have focused on the bioaccumulation and global distribution of
perfluorinated surfactants [29-33], as well as the ability of perfluorinated surfactants to
enhance the solubilization of polycyclic aromatic hydrocarbons [34]. Despite these
important studies, relatively little information is available regarding the effects of
perfluorinated surfactants on the transport of other environmental contaminants.
The main focus of this study is to compare the effects of perfluorinated and
hydrocarbon surfactants above their CMC on the transport of environmental
contaminants in a groundwater system. Reversed-phase micellar liquid chromatography
is used as a model for the groundwater system, with lithium perfluorooctane sulfonate
and sodium dodecyl sulfate as representatives of the two classes of surfactants. Various
halogenated benzenes and polycyclic aromatic hydrocarbons are used as models of the
environmental contaminants. The results of this study yield information concerning the
retention factor and equilibrium constant of the model contaminant between water and
the micelle. These values can be used in modeling programs to elucidate the transport of

51

pollutants that might leach from waste disposal or other contaminated sites into an
aquifer.
3.2 Experimental Methods
3.2.1

Mobile Phase and Analytes

The hydrocarbon surfactant, sodium dodecyl sulfate (SDS), was obtained from
Aldrich and was used as received. The perfluorinated surfactant, lithium perfluorooctane
sulfonate (LiPFOS), was prepared by dissolving the appropriate amounts of
heptadecafluorooctane sulfonic acid (TCI America) and lithium hydroxide monohydrate
(99.95 %, Aldrich) in deionized, distilled water. The micellar solutions were prepared by
dissolving the appropriate amount of surfactant in deionized, distilled water (Corning
Mega-Pure, Models D2 and MP-3A) and gently stirring the solution overnight to allow
equilibrium to be reached. The solutions were then filtered through a cellulose acetate
membrane (Alltech) with a 0.45 µm pore size. The analytes benzene, biphenyl,
naphthalene, anthracene, phenanthrene, pyrene, fluorobenzene, chlorobenzene, and
bromobenzene (Aldrich), as well as hexafluorobenzene, hexachlorobenzene, and
−3

hexabromobenzene (TCI America) were used as received. Stock solutions (1.0 x 10

M)

of the analytes were prepared in high-performance liquid chromatography-grade
methanol (Spectrum Chemical), except hexabromobenzene, which was prepared in
dichloromethane (Spectrum Chemical). Analytical samples were prepared by diluting the
proper amount of stock solution with the surfactant solution to acquire the working
−4

concentrations. The working concentrations were benzene (2.25 x 10
−6

M), naphthalene (3.80 x 10

−7

M), pyrene (3.80 x 10

(2.00 x 10

(4.99 x 10

−5

−5

−7

M), anthracene (4.99 x 10

−4

M), fluorobenzene (3.23 x 10

52

M), biphenyl

M), phenanthrene

M), chlorobenzene

−4

(2.98 x 10

−4

M), bromobenzene (3.45 x 10
−4

hexachlorobenzene (2.22 x 10
3.2.2

−3

M), hexafluorobenzene (1.31 x 10
−5

M), and hexabromobenzene (5.00 x 10

M),

M).

Experimental System

The experimental chromatographic methods, as detailed in Section 2.2, are briefly
recapped in this section. The commercial analytical column (4.6 mm i.d. x 250 mm
length) was packed with Poroshell 300SB-C18 pellicular particles (Agilent) of 5.0 µm
2

−1

diameter and 6.0 m g
µmol m

−2

surface area, with an octadecylsilica stationary phase of 2.1

bonding density and 0.39 % carbon content. The pellicular particles consist of

solid silica glass beads coated with a 300 Å layer of porous octadecylsilica. The MLC
system consisted of a single-piston reciprocating pump (Beckman, Model 110B), an
injector with a 20 µL injection loop (Valco, Model EC6W), an analog interface module,
and a UV-visible absorbance detector (Beckman, Models 406 and 166, respectively).
The UV absorbance wavelength of 254 nm was specific for the detection of the analytes,
and did not incur any interference from the surfactants. Chromatograms were recorded
on a chart recorder (Linear Cole-Parmer Instrument Company, Model 0555-0000). All
experiments were carried out at ambient temperature with a maximum pressure limit of
−1

4500 psi. The flow rate was 1.0 mL min
−1

min

during the SDS experiments and 0.5 mL

during the LiPFOS experiments. The lower flow rate was used for the LiPFOS

experiments due to higher back pressure in the RPLC system during measurements. The
void time was taken as the first positive deviation from the baseline arising from the
residual methanol in each sample.

53

3.2.3

Data Analysis

In order to elucidate meaningful information regarding the transport effects of
perfluorinated surfactants in a groundwater system, an analytical technique was used that
could fundamentally resemble such a system, but whose parameters were controllable.
Reversed-phase MLC was used to model a groundwater system, in which the
octadecylsilica stationary phase represents soil and the aqueous micellar mobile phase
represents groundwater that contains a surfactant above its CMC.
In the paper by Arunyanart and Cline Love [6], MLC is described by three
competing reversible equilibria, which are treated as binding phenomena instead of the
more traditional partitioning phenomena. Treating the equilibria in this manner
eliminates the need for prior information pertaining to the concentration of analytes in
solution, the volume of the stationary phase, or the partial specific volume of the micelle
aggregate. The first equilibrium is expressed as
K

1
→
A + S ← AS

(3.1)

which represents the analyte in the bulk mobile phase, A, binding to a stationary phase
site, S, to form a complex, AS. The second equilibrium is
K

2→

A + M ← AM


(3.2)

which represents the analyte in the bulk mobile phase, A, binding to a surfactant micelle
in the bulk mobile phase, M, to form a micellar complex, AM. The third equilibrium is
K

3→

AM + S ← AS + M


(3.3)

which represents the transfer of the analyte from the surfactant micelle in the bulk mobile
phase, AM, to a stationary phase site, S. Among these equilibria, only two are

54

independent and the other dependent. For example, the third equilibrium constant can be
expressed as the ratio of the first and second equilibrium constants. For this reason, we
may consider the retention mechanism to be controlled by the first and second equilibria
[11,35].
The retention factor, k, can be defined from the molar concentrations of the free
and bound analyte as
k=

φ[AS]
([A] + [AM])

(3.4)

where φ is the phase ratio, which is the ratio of the volumes of the stationary and mobile
phases. The value for k is experimentally determined by
t
k= R

−

t0

(3.5)

t0

where tR and t0 are the chromatographic retention time of the analyte and the void time of
the column, respectively. By combining Equations 3.1, 3.2, and 3.4, an expression can be
obtained that relates k to the binding constants of the two controlling equilibria, K1 and
K2, as well as the concentration of the surfactant micelle
k=

φ[S]K1

(3.6)

(1 + K 2[M])

By taking the reciprocal of Equation 3.6, the following expression is obtained
K2
1
1
=
[M] +
k
φ[S]K1
φ[S]K1

(3.7)

where [M] is the molar concentration of surfactant in the micellar form, which is equal to
the total concentration minus the CMC.

55

By graphing the inverse of k versus [M], a linear correlation is obtained. From
the ratio of the slope to the y-intercept, a quantitative value for K2 can be calculated.
This value of K2 represents the binding constant of the analyte between the bulk mobile
phase and the micelle, expressed per monomer of surfactant in Equation 3.2. Upon
multiplying K2 by the aggregation number of the surfactant, the equilibrium constant per
micelle, Keq, is obtained. The aggregation numbers used in this study for both SDS and
LiPFOS were experimentally determined during this study by means of densitometry
measurements, as previously described in Section 2.4.
3.3 Results and Discussion

The experimental conditions for this study were selected, insofar as possible, to
model a groundwater system. The Poroshell stationary phase was chosen because of its
2 −1

low carbon content (0.39 %) and surface area (6.0 m g ), which more closely resembles
the properties of soil than a traditional octadecylsilica stationary phase (12 – 18 %, 200 –
2 −1

400 m g ). In addition, this phase allows for the complete elution of all analytes even
at very low concentration of surfactants.
Sodium dodecyl sulfate (SDS) was chosen as the representative hydrocarbon
surfactant because it is commonly used in commercial products and has been detected in
the environment. Moreover, there is a large volume of information on SDS in the
literature [36,37]. Perfluorooctane sulfonate (PFOS) was chosen as the representative
perfluorinated surfactant because it is used commercially and has been detected in the
environment [29-33,38]. The lithium salt (LiPFOS) has a low Krafft point that allows it
to form micelles at room temperature [32] and has a CMC of the same magnitude as SDS

56

[11,21, Table 3.1]. In a study by Hu and Haddad [39], it was shown that surfactant
monomers could adsorb onto the surface of the stationary phase, thereby changing the
physical and chemical properties. To control this effect, it was desirable to maintain the
SDS and LiPFOS monomers at similar concentrations. In solutions where the total
surfactant concentration is above the CMC, the concentration of monomers is equal to the
CMC and, hence, is similar for SDS and LiPFOS.
Finally, the analytes chosen for this study represent important classes of
environmental contaminants. The polycyclic aromatic hydrocarbons (PAHs) are known
human carcinogens and environmental pollutants. Biphenyl and the halogenated benzene
compounds serve as models for polychlorinated biphenyls and polychlorinated and
polybrominated dibenzodioxins and dibenzofurans. Moreover, all of these analytes can
be used to examine how their differences in physical and chemical characteristics
influence the transport effects of hydrocarbon and perfluorinated surfactants.
3.3.1

Transport Effects of Sodium Dodecyl Sulfate

In preliminary studies, the experimental system and data analysis methods were
validated by using SDS mobile phases (0.02 – 0.1 M). Hexabromobenzene exhibited
limited solubility in the SDS mobile phase and, consequently, was excluded from further
studies. All other test analytes were soluble and eluted from the column at each
surfactant concentration, with the exception of hexachlorobenzene at the lowest
concentration. The elution order for the analytes in SDS was as follows: benzene <
fluorobenzene < hexafluorobenzene < chlorobenzene < bromobenzene < naphthalene <
biphenyl < phenanthrene < anthracene < pyrene < hexachlorobenzene.

57

Table 3.1: Physical data of representative hydrocarbon and perfluorinated surfactants
used in this study.

Surfactant Chemical Formula

−

+

SDS

C12H25OSO3 Na

LiPFOS

C8F17SO3 Li

−

+

Aggregation
Critical Micelle
c
Concentration (M)
Number

Krafft Point
b
(°C)

−3 a

65 ± 8

16

−3 b

11 ± 3

<0

8.1 x10

6.5 x10

a

Reference 11
Reference 32
c
This study, Section 2.4
a
The critical micelle concentration is the point (or narrow concentration range) where
extensive aggregation of the surfactant monomers takes place.
a
The aggregation number is the average number of monomer surfactant molecules per
micelle.
a
The Krafft point is the temperature (or narrow temperature range) above which the
solubility of a surfactant becomes equal to the critical micelle concentration.
b

58

This elution order was identical to that observed for the analytes in methanol/water
mobile phases on the same stationary phase.
The chromatographic retention times of the model analytes were used to calculate
the retention factors, k, according to Equation 3.5. The retention factors are summarized
in Table 3.2. It is noteworthy that the retention factors determined in this study were an
order of magnitude lower than those determined by Arunyanart and Cline Love [6] for
comparable analytes and concentrations of SDS. This discrepancy is believed to be due
to differences in the stationary phases, specifically carbon content, used in the two
studies. In comparing the retention factors in 0.1 M SDS to that in pure water (Table
3.2), the values decreased by 39 to 80 % for benzene and the monohalogenated benzenes.
Correspondingly, the linear velocities increased by 32 to 247 %. It is apparent that SDS
increases chromatographic transport of benzene and the substituted benzenes and, by
implication, increases environmental transport as well.
−1

Graphs of the inverse retention factor (k ) versus the concentration of SDS in the
micelle (M) are shown in Figure 3.1. Statistical treatment of these graphs via linear
−1

regression demonstrated that there was a linear relationship between k

and M, where

2

the R values were all greater than 0.97 (Table 3.3). For the more retained analytes, the
slope of the line became shallower and the intercept approached zero. From the graphs in
Figure 3.1, the overall effect was that the retention of the analytes decreased as the
concentration of SDS increased.

59

a

Table 3.2: Summary of retention factors of analytes for several mobile phases.
Analyte

Pure Water

0.1 M SDS

0.1 M LiPFOS

Benzene

1.57 ± 0.01

0.953 ± 0.004

1.17 ± 0.02

Fluorobenzene

1.95 ± 0.01

1.04 ± 0.03

1.31 ± 0.02

Chlorobenzene

5.70 ± 0.03

1.58 ± 0.03

2.83 ± 0.02

Bromobenzene

8.47 ± 0.03

1.73 ± 0.03

3.66 ± 0.02

Hexafluorobenzene

N/A

1.41 ± 0.01

1.90 ± 0.03

Hexachlorobenzene

N/A

4.96 ± 0.04

D/E

Naphthalene

N/A

2.03 ± 0.06

7.2 ± 0.2

Biphenyl

N/A

2.70 ± 0.02

14.9 ± 0.2

Phenanthrene

N/A

3.33 ± 0.02

47.5 ± 0.6

Anthracene

N/A

3.50 ± 0.07

36.3 ± 1.6

Pyrene

N/A

4.25 ± 0.11

66.9 ± 2.8

a

Retention factors are an average of at least three injections.
N/A… Analyte was not included in this mobile phase due to excessive retention.
D/E… Analyte exhibited excessive retention.

60

Figure 3.1:

Plot of inverse retention factor versus the concentration of sodium dodecyl

sulfate (SDS) in the micelle. Analytes: (♦) benzene, (■) fluorobenzene, (▲)
hexafluorobenzene, (x) chlorobenzene, (*) bromobenzene, (•) naphthalene, (○) biphenyl,
(◊) phenanthrene, (□) anthracene, (∆) pyrene, (+) hexachlorobenzene. Other
experimental conditions as given in the text.

61

Figure 3.1
1.2

1/Retention Factor

1.0

0.8

0.6

0.4

0.2

0.0
0.00

0.02

0.04

0.06

Concentration of SDS in Micelle (M)

62

0.08

0.10

The equilibrium constants, Keq, for the transfer of each analyte from water to the
SDS micelle are summarized in Table 3.3. For several of the comparable analytes, such
as benzene, the values were of the same magnitude as those reported by Arunyanart and
Cline Love [6]. In order to understand the accuracy of these values, it is useful to
examine the propagation of error. According to Equation 3.7, the uncertainty in Keq
values is determined by the uncertainty in the slope and intercept. For benzene, the
monohalogenated benzenes, and hexafluorobenzene, the uncertainty in the intercept was
low, resulting in small error in Keq. For the highly retained analytes, i.e.
hexachlorobenzene and the PAHs, there was large uncertainty in the intercept, even
resulting in negative values for several of the analytes. Due to this uncertainty, Keq
values for highly retained analytes were not reliably obtained via this method. This is
most notably evident from the negative Keq values acquired for three of the analytes,
anthracene, pyrene, and hexachlorobenzene. However, the retention factors (Table 3.2)
appear to be roughly correlated with the Keq values (Table 3.3), such that transport trends
of the analytes can be elucidated. For the series of monohalogenated benzenes, the Keq
values increased with the size and polarizability of the halogen substituent. Additionally,
the Keq values increased as the number of halogen substituents increased from one to six.
For the series of PAHs, the Keq values increased with the number of aromatic rings.
Moreover, the annelation structure of the PAHs appears to affect the Keq value. For
example, the fused-ring aromatic structure of naphthalene had a lower Keq value than the
non-fused-ring structure of biphenyl.

63

Table 3.3: Equilibrium constants of analytes from water to the SDS micelle.
SDS
Analyte

a

b

Method One

Method Two

Method Three

c

Keq
3
-1
(10 M )

R2

Keq
3
-1
(10 M )

R

0.981

1.28 ± 0.19

0.969

1.29 ± 0.23

0.970

1.43 ± 0.23

0.974

1.22 ± 0.25

0.946

1.24 ± 0.29

0.949

Chlorobenzene

3.99 ± 0.85

0.991

3.19 ± 0.43

0.988

3.32 ± 0.56

0.988

Bromobenzene

5.5 ± 1.4

0.993

4.31 ± 0.57

0.991

4.50 ± 0.75

0.992

Hexafluorobenzene

2.35 ± 0.37

0.988

1.95 ± 0.30

0.976

2.02 ± 0.38

0.977

Hexachlorobenzene

−17 ± 12

0.997

−9.87 ± 1.9

0.999

DNC

0.980

Naphthalene

29 ± 63

0.980

17 ± 4

0.997

18 ± 5

0.997

Biphenyl

110 ± 370

0.997

120 ± 72

0.999

130 ± 88

0.999

Phenanthrene

330 ± 3100

0.997

−250 ± 250

0.999

DNC

0.999

Keq
3
-1
(10 M )

R

Benzene

1.38 ± 0.18

Fluorobenzene

2

2

Anthracene

−510 ± 6700 0.998

120 ± 91

0.999

140 ± 120

0.999

Pyrene

−230 ± 1400 0.998

490 ± 1300

0.999

800 ± 3400

0.999

a

Data calculated via linear regression of Equation 3.7.
Data calculated via nonlinear regression of Equation 3.7.
c
Data calculated via nonlinear regression of Equation 3.6
DNC… Regression did not converge.

b

64

In addition, the angular ortho-condensed structure of phenanthrene had a lower Keq value
than the corresponding linear ortho-condensed structure of anthracene. These trends
provide important insight into the transport effects of SDS in environmental systems as
well.
3.3.2

Transport Effects of Lithium Perfluorooctane Sulfonate

Initial studies were performed in order to obtain information on retention factors
and the elution order of the model analytes in the perfluorinated surfactant solution, since
this information was not available. The experimental k values for each analyte in 0.1 M
LiPFOS are summarized in Table 3.2. The elution order for the analytes was similar to
that in 0.1 M SDS, with the notable exception that phenanthrene eluted after anthracene.
In comparing the retention factors in 0.1 M LiPFOS to that in pure water (Table
3.2), the values decreased by 25 to 57 % for benzene and the monohalogenated benzenes.
Correspondingly, the linear velocities increased by 18 to 103 %. It is apparent that
LiPFOS increases chromatographic transport of benzene and the substituted benzenes
and, by implication, increases environmental transport as well.
While the retention factors of the analytes decreased in both surfactant solutions,
LiPFOS exhibited a lesser effect than SDS. In comparing the experimental results in 0.1
M LiPFOS to that in 0.1 M SDS, the k values increased by 23 to 112 % for benzene, the
monohalogenated benzenes, and hexafluorobenzene, and by 255 to 1470 % for
hexachlorobenzene and the PAHs. Correspondingly, the linear velocities decreased by
10 to 41 % for the substituted benzenes and by 63 to 92 % for the PAHs. It is apparent
that LiPFOS induces less chromatographic and environmental transport than does SDS
for these analytes.

65

Based on the data obtained in this initial study, further studies with LiPFOS were
separated into two concentration ranges. For analytes with k values less than 10 in Table
3.2, the concentration range of 0.02 – 0.1 M LiPFOS was utilized. For analytes with k
values greater than 10, the concentration range of 0.1 – 0.3 M LiPFOS was utilized.
−1

Graphs of the inverse retention factor (k ) versus the concentration of LiPFOS in the
micelle (M) are shown in Figures 3.2 and 3.3. Statistical treatment of these graphs via
−1

linear regression demonstrated that there was a linear relationship between k

and M,

2

where the R values were all greater than 0.90 (Table 3.4). From the graphs in Figures
3.2 and 3.3, the overall effect was that the retention of the analytes decreased as the
concentration of LiPFOS increased. In comparing the results for hexafluorobenzene
(Figures 3.1 and 3.2), the slope of the line was shallower in LiPFOS than in SDS over the
same concentration range. The line for hexafluorobenzene crossed those for
chlorobenzene and bromobenzene in LiPFOS, but not in SDS.

66

Figures 3.2 & 3.3:

Plot of inverse retention factor versus the concentration of lithium

perfluorooctane sulfonate (LiPFOS) in the micelle. Analytes: (♦) benzene, (■)
fluorobenzene, (▲) hexafluorobenzene, (x) chlorobenzene, (*) bromobenzene, (•)
naphthalene, (○) biphenyl, (◊) phenanthrene, (□) anthracene, (∆) pyrene, (+)
hexachlorobenzene. Other experimental conditions as given in the text.

67

Figure 3.2

1/Retention Factor

0.8

0.6

0.4

0.2

0.0
0.00

0.02

0.04

0.06

Concentration of LiPFOS in Micelle (M)

68

0.08

0.10

Figure 3.3
2.5

1/Retention Factor

2

1.5

1

0.5

0
0.05

0.10

0.15

0.20

Concentration of LiPFOS in Micelle (M)

69

0.25

0.30

Table 3.4: Equilibrium constants of analytes from water to the LiPFOS micelle.
LiPFOS
a

b

Method One

Analyte

Method Two

Method Three

c

Keq
3
-1
(10 M )

R

0.989

0.100 ±
0.010

0.988

0.136 ±
0.006

0.996

0.136 ±
0.008

0.996

0.994

0.184 ±
0.011

0.993

0.184 ±
0.014

0.993

0.185 ±
0.014

0.992

0.194 ±
0.013

0.992

0.195 ±
0.017

0.992

1.1 ± 0.2

0.997

0.869 ±
0.049

0.999

0.876 ±
0.065

0.999

Keq
3
-1
(10 M )

R

0.993

0.096 ±
0.009

0.131 ±
0.005

0.997

Chlorobenzene

0.177 ±
0.011

Bromobenzene
Hexafluorobenzene

Keq
3
-1
(10 M )

R

Benzene

0.079 ±
0.004

Fluorobenzene

d

2

2

2

Hexachlorobenzene

−0.187 ±
0.000

1.000

N/A

N/A

N/A

N/A

Naphthalene

0.356 ±
0.025

0.997

0.358 ±
0.021

0.997

0.366 ±
0.027

0.997

Biphenyl

−0.36 ± 0.14 0.999

−0.417 ±
0.045

0.999

DNC

0.973

Phenanthrene

−0.15 ± 0.14 0.901

−0.823 ±
3.12

0.952

DNC

0.933

Anthracene

−0.486 ±
0.003

0.999

−0.488 ±
0.001

0.999

DNC

0.981

Pyrene

−0.673 ±
0.400

0.998

−0.499 ±
0.087

0.999

DNC

0.981

a

Data calculated via linear regression of Equation 3.7.
Data calculated via nonlinear regression of Equation 3.7.
c
Data calculated via nonlinear regression of Equation 3.6.
d
Values for hexachlorobenzene in LiPFOS were calculated from data at two
concentrations.
DNC… Regression did not converge.

b

70

These two observations suggest that hexafluorobenzene has a high affinity for the
perfluorinated surfactant, due to the similarity in their basic structure. This may imply
that any highly fluorinated analyte may be selectively transported by LiPFOS in
environment systems.
The equilibrium constants, Keq, for the transfer of each analyte from water to the
LiPFOS micelle are summarized in Table 3.4. From the Keq values, similar trends are
observed for LiPFOS and SDS. As the size, polarizability, and number of halogen
substituents increased, so too did the Keq values of the analyte. In addition, the Keq
values increased as the number of aromatic rings increased. However, upon more
detailed comparison, several differences are observable. The Keq value for
hexafluorobenzene was on the same order of magnitude in both LiPFOS and SDS
surfactants. The Keq value for monofluorobenzene was an order of magnitude lower in
LiPFOS than in SDS, whereas benzene and the other monohalogenated benzenes were
more than an order of magnitude lower. These observations suggest that the
perfluorinated surfactant maintains some degree of selectivity for analytes with one or
more fluorine substituents. The Keq value for naphthalene was two orders of magnitude
lower in LiPFOS than in SDS. The lower Keq values show that the analytes exhibit a
weaker binding to LiPFOS than to SDS, which results in decreased transport in the
perfluorinated surfactant compared to the hydrocarbon surfactant solutions.

71

The Keq values for the remaining PAHs and hexachlorobenzene could not be
reliably determined, due in large part to the uncertainty in the intercept. This uncertainty
resulted in negative intercepts and Keq values for these analytes. A possible explanation
for this phenomenon is that, for highly retained analytes, the binding constant of the
analyte between the bulk mobile phase and the stationary phase, K1, has a greater impact
on transport effects than the binding constant of the analyte between the bulk mobile
phase and the surfactant micelle, K2. According to Equation 3.7, the larger the values of
K1 compared to K2, the smaller the slope and the closer the intercept to zero. Under these
conditions, small imprecision in the retention data can lead to uncertainty in the slope and
even larger uncertainty in the intercept. An alternative explanation for this phenomenon
is that, for highly retained analytes, the binding constant of the analyte between the
surfactant micelle in the mobile phase and the stationary phase, K3, cannot be considered
negligible. This causes the treatment of the retention mechanism using Equations 3.1 and
3.2, substituted into Equation 3.4, to be unreliable. However, treatment using Equations
3.1 and 3.3 or Equations 3.2 and 3.3 yields similarly unreliable results. Hence, it appears
that equilibrium constants for highly retained analytes must be determined by other nonchromatographic methods.
3.4 Summary

The overall trend was that an increase in surfactant concentration above the CMC
resulted in an increase in transport, relative to that in the system devoid of any surfactant.
In general, the transport in the model groundwater system was less in the perfluorinated
surfactant solution than in the hydrocarbon surfactant solution. The transport trends of

72

the individual analytes were similar for the perfluorinated and hydrocarbon surfactants,
based on the size, polarizability, and number of halogen substituents on the aromatic
compound. Transport trends for large, highly retained analytes could not be reliably
elucidated from the equilibrium constants, due to large uncertainty. A more detailed
understanding of the retention mechanism of highly retained analytes in reversed-phase
micellar liquid chromatography is needed. In addition, studies are needed to further
characterize transport effects of perfluorinated surfactants on environmental pollutants,
based on different structures of the surfactant.

73

REFERENCES

74

3.5 References

[1]

D.E. Kile, C.T. Chiou, Environ. Sci. Technol. 23 (1989) 832-838.

[2]

D.A. Edwards, R.G. Luthy, Z. Liu, Environ. Sci. Technol. 25 (1991) 127-133.

[3]

Y. Moroi, K. Mitsunobu, T. Morisue, Y. Kadobayashi, M. Sakai, J. Phys. Chem.
99 (1995) 2372-2376.

[4]

D.J Luning Prak, P.H. Pritchard, Water Res. 36 (2002) 3463-3472.

[5]

C.L. Chun, J.-J. Lee, J.-W. Park, Environ. Pollut. 118 (2002) 307-313.

[6]

M. Arunyanart, L.J. Cline Love, Anal. Chem. 56 (1984) 1557-1561.

[7]

S. Sun, W.P. Inskeep, S.A. Boyd, Environ. Sci. Technol. 29 (1995) 903-913.

[8]

C.T. Jafvert, Environ. Sci. Technol. 25 (1991) 1039-1045.

[9]

S.-O. Ko, M.A. Schlautman, E.R. Carraway, Environ. Sci. Technol. 32 (1998)
2769-2775.

[10]

M.G. Khaledi, J. Chromatogr. A 780 (1997) 3-40.

[11]

D.W. Armstrong, Sep. Purif. Methods 14 (1985) 213-304.

[12]

B.D. Key, R.D. Howell, C.S. Criddle, Environ. Sci. Technol. 31 (1997) 24452454.

[13]

K.J. Hansen, L.A. Clemen, M.E. Ellefson, H.O. Johnson, Environ. Sci. Technol.
35 (2001) 766-770.

[14]

C. Damas, R. Naejus, R. Coudert, C. Frochot, A. Brembilla, M.-L. Viriot, J. Phys.
Chem. B 102 (1998) 10917-10924.

[15]

E. Kissa, Fluorinated Surfactants: Synthesis, Properties, and Applications, Marcel
Dekker, New York, NY, 1994.

[16]

R.E. Banks, B.E. Smart, J.C. Tatlow, Organofluorine Chemistry: Principles and
Commercial Applications, Plenum Press, New York, NY, 1994.

[17]

P. Varughese, M.E. Gangoda, R.K. Gilpin, J. Chromatogr. Sci. 26 (1988) 401405.

[18]

C.A. Moody, J.A. Field, Environ. Sci. Technol. 34 (2000) 3864-3870.

75

[19]

C.A. Moody, W.C. Kwan, J.W. Martin, D.C.G. Muir, S.A. Mabury, Anal. Chem.
73 (2001) 2200-2206.

[20]

C.A. Moody, J.W. Martin, W.C. Kwan, D.C.G. Muir, S.A. Mabury, Environ. Sci.
Technol. 36 (2002) 545-551.

[21]

A. Tullo, Chem. Eng. News 78(21) (2006) 9-10.

[22]

C. Hogue, Chem. Eng. News 84(5) (2006) 8.

[23]

C. Hogue, Chem. Eng. News 84(11) (2006) 10.

[24]

S.K. Ritter, Chem. Eng. News 82(24) (2004) 44-45.

[25]

C. Hogue, Chem. Eng. News 82(35) (2004) 17-19.

[26]

S.K. Ritter, Chem. Eng. News 84(5) (2006) 37-40.

[27]

K. Shinoda, M. Ható, T. Hayashi, J. Phys. Chem. 76 (1972) 909-914.

[28]

Ş. Erkoç, F. Erkoç, J. Molecular Structure (Theochem) 549 (2001) 289-293.

[29]

J.P. Giesy, K. Kannan, Environ. Sci. Technol. (2002) 148A-152A.

[30]

J.P. Giesy, K. Kannan, Environ. Sci. Technol. 35 (2001) 1339-1342.

[31]

K. Kannan, J. Koistinen, K. Beckmen, T. Evans, J.F. Gorzelany, K.J. Hansen,
P.D. Jones, E. Helle, M. Nyman, J.P. Giesy, Environ. Sci. Technol. 35 (2001)
1593-1598.

[32]

K. Kannan, J.C. Franson, W.W. Bowerman, K.J. Hansen, P.D. Jones, J.P. Giesy,
Environ. Sci. Technol. 35 (2001) 3065-3070.

[33]

S. Taniyasu, K. Kannan, Y. Horii, N. Yamashita, Organohalogen Compd. 59
(2002) 105-108.

[34]

Y.-J. An, E.R. Carraway, M.A. Schlautman, Water Res. 36 (2002) 300-308.

[35]

W.L. Hinze, S.G. Weber, Anal. Chem. 63 (1991) 1808-1811.

[36]

D. Myers, Surfactant Science and Technology, 3 Ed., John Wiley and Sons,
Hoboken, NJ, 2006, p. 35.

[37]

M.M. Singer, R.S. Tjeerdema, Rev. Environ. Contam. Toxicol. 133 (1993) 95149.

rd

76

[38]

United States Environmental Protection Agency, Prevention, Pesticides and Toxic
Substances (7505C), EPA-730-F-99-009, 1999.

[39]

W. Hu, P.R. Haddad, Anal. Commun. 35 (1998) 191-194.

77

CHAPTER 4: COMPARISON OF TRANSPORT EFFECTS OF
PERFLUORINATED AND HYDROCARBON SURFACTANTS BELOW THE
CRITICAL MICELLE CONCENTRATION: NEUTRAL ANALYTES
4.1 Introduction

The addition of certain reagents (e.g. amphiphilic ions, surfactants, etc.) to the
mobile phase in a reversed-phase liquid chromatography system can be used to adjust the
separation of oppositely charged metal ions and ionic compounds in solution [1]. This
technique has been given many different names throughout the years such as ion
interaction chromatography [2], soap chromatography [3], ion-exchange chromatography
[4], and ion-pair chromatography [5]. It has been postulated that the inclusion of an ion
interaction reagent could either increase (through partition) or decrease (through
competition for adsorption sites) the retention of a neutral compound [6,7]. However, the
change in retention of neutral compounds is so small that an apparent lack of retention
dependence on surfactant has been claimed [8]. This correlates with information in the
literature that states the effectiveness of the surfactant monomers to enhance the
solubility of neutral hydrophobic organic compounds is substantially less than that of
surfactant aggregates formed above the critical micelle concentration (CMC) [9-11].
Perfluorinated surfactants, which have different physical and chemical
characteristics than hydrocarbon surfactants, have been detected in the environment at
concentrations lower than their CMC [12-15]. Previous studies of perfluorinated
surfactants have focused on their bioaccumulation and global distribution [16-20], their
ability to enhance the solubilization of polycyclic aromatic hydrocarbons [21], and
transport effects above their CMC on neutral hydrophobic compounds [22]. Despite
these important studies, relatively little information is available regarding the effects of

78

low levels of perfluorinated surfactants on the transport of other environmental
contaminants.
The main focus of this study is to compare the effects of perfluorinated and
hydrocarbon surfactants below their CMC on the transport of neutral hydrophobic
environmental contaminants in a groundwater system. Reversed-phase liquid
chromatography (RPLC) is used as a model for the groundwater system, with lithium
perfluorooctane sulfonate and sodium dodecyl sulfate as representatives of the two
classes of surfactants. Benzene, toluene, ethylbenzene, and p-xylene are chosen as
representatives of the BTEX compounds. In addition, several monohalogenated benzenes
were chosen as models of halogenated environmental pollutants. The results of this study
yield information concerning the retention factors and several selectivity factors of the
model pollutants. These values can be used to elucidate the transport effects of
perfluorinated surfactants on pollutants that might leach from waste disposal,
underground gas tanks, or other contaminated sites into an aquifer.
4.2 Experimental Methods
4.2.1

Mobile Phase and Analytes

The hydrocarbon surfactant, sodium dodecyl sulfate (SDS), was obtained from
Aldrich and was used as received. The perfluorinated surfactant, lithium perfluorooctane
sulfonate (LiPFOS), was prepared by dissolving the appropriate amounts of
heptadecafluorooctane sulfonic acid (TCI America) and lithium hydroxide monohydrate
(99.95 %, Aldrich) in deionized, distilled water (Corning Mega-Pure, Models D2 and
MP-3A). The aqueous surfactant solutions were prepared by dissolving the appropriate
amount of surfactant in deionized, distilled water. The solutions were then filtered

79

through a cellulose acetate membrane (Alltech) with a 0.45 µm pore size. The surfactant
mobile phase solutions were adjusted to pH 4.00 ± 0.10 with hydrochloric acid. An
−1

aqueous stock solution of lithium nitrate (1.0 x 10

M, Spectrum Chemical) was

prepared in deionized, distilled water. The analytes fluorobenzene, chlorobenzene,
bromobenzene, benzene, toluene, ethylbenzene, and p-xylene (Aldrich) were used as
−1

received. Stock solutions of 9.0 x 10
−1

M for benzene, and 1.0 x 10

−2

M for the monohalogenated benzenes, 5.0 x 10

M for the remaining BTEX compounds were prepared in

high-performance liquid chromatography-grade methanol (Spectrum Chemical).
Analytical samples were prepared by diluting the proper amount of stock solution and
aqueous lithium nitrate (LiNO3) solution with the surfactant solution to acquire the
working concentrations in a 2 mL final volume. Where necessary, the stock solutions
were evaporated with nitrogen, such that the residual concentration of methanol was less
than 1 % (v/v) in the final analytical sample. The working concentrations in the
−2

analytical samples were LiNO3 (1.00 x 10
−4

chlorobenzene (5.37 x 10
−4

M), toluene (5.03 x 10

−4

M), fluorobenzene (5.82 x 10
−4

M), bromobenzene (5.18 x 10
−4

M), ethylbenzene (5.03 x 10

M),
−4

M), benzene (5.00 x 10

−4

M), and p-xylene (5.03 x 10

M).
4.2.2

Experimental System

The experimental chromatographic methods, as detailed in Section 2.2, are briefly
recapped in this section. The analytical column (4.6 mm i.d. x 250 mm length) was
packed with Poroshell 300SB-C18 pellicular particles (Agilent) of 5.0 µm diameter and
2 −1

6.0 m g

surface area, with an octadecylsilica stationary phase of 2.1 µmol m

80

−2

bonding

density and 0.39 % carbon content. The liquid chromatography system consisted of a
single-piston reciprocating pump (Beckman, Model 110B), an injector with a 20 µL
injection loop (Valco, Model EC6W), and a UV-visible absorbance detector (Hitachi,
Model L-4200). The UV absorbance wavelength of 254 nm was specific for the
detection of the analytes, and did not incur any interference from the surfactants.
Chromatograms were recorded on a chart recorder (Linear Cole-Parmer Instrument
Company, Model 0555-0000). All experiments were carried out at ambient temperature
with a maximum pressure limit of 4500 psi. The flow rate was 1.0 mL min
−1

SDS experiments and 0.5 mL min

−1

during the

during the LiPFOS and pure water experiments. The

void time, t0, was taken as the first positive deviation from the baseline arising from
LiNO3 in each sample. The retention time, tR, for each analyte was determined from the
peak maximum, which is appropriate for the symmetric Gaussian peaks observed in this
study. The retention factor, k, was then calculated by
−

t
k= R

t0

(4.1)

t0

The k values (average of at least three trials) were used for the subsequent elucidation of
transport effects and determination of selectivity factors as described in the following
section.
4.2.3

Data Analysis

4.2.3.1 Retention Factor Measurements

In order to elucidate meaningful information regarding the transport effects of
perfluorinated surfactants in an environmental system, an analytical technique was used
that could fundamentally resemble such a system, but whose parameters were

81

controllable. Reversed-phase liquid chromatography (RPLC) was used to model the
environmental system, in which the octadecylsilica stationary phase represents soil and
the aqueous mobile phase represents groundwater. When a surfactant is added to the
system below its CMC, the monomers distribute or partition between the mobile and
stationary phases. These surfactant monomers have the potential to alter the retention of
the analytes (pollutants).
In the RPLC system, the retention of a neutral analyte is mainly controlled by a
partitioning phenomenon, where the analyte is in equilibrium between the mobile and
stationary phases. The equilibrium constant, K, can be defined as
K=

aS
aM

=

γSCS

(4.2)

γ M CM

where aS and aM represent the activities, γS and γM represent the activity coefficients, and
CS and CM represent the analytical concentrations of the analyte in the stationary (S) and
mobile (M) phases, respectively. Assuming the activity coefficients are equal to unity,
Equation 4.2 indicates that the equilibrium constant is directly related to the ratio of the
analyte concentrations in the stationary and mobile phases. This equilibrium constant
represents all interactions between the analyte, stationary phase, mobile phase, and
surfactant monomers. However, the determination of this equilibrium constant is
difficult because of the inability to directly measure the concentrations of the analyte in
the mobile and stationary phases.
The retention factor, k, is defined as
(4.3)

k = Kφ

where φ is the phase ratio, defined as

82

φ=

VS

(4.4)

VM

where VM and VS are the volumes of the mobile and stationary phase, respectively.
Assuming that the phase ratio is constant, the value for k is proportional to K.
Consequently, the trends in retention factor are consistent with and can be used to predict
the trends in equilibrium constant. In particular, an increase in the retention factor
implies an increase in the concentration of the analyte in the stationary phase relative to
the mobile phase, according to Equation 4.2.
4.2.3.2 Selectivity Factor Calculations

In addition to the retention factors, several selectivity factors are also compared to
elucidate transport effects. Each selectivity factor provides different information
concerning the various interactions between the analytes and the surfactants.
The first selectivity factor, α1, is defined as the ratio of the retention factor of an
analyte to that of benzene, while all other experimental conditions remain constant.
α1 =

k analyte

(4.5)

k benzene

The value for α1 is related to the effect of the addition of a substituent group to the
benzene structure on the transport of the model analytes. As α1 increases, the additional
substituent group leads to increasing interaction of the neutral analyte with the stationary
phase.
The second selectivity factor, α2, is defined as the ratio of the retention factor of
an analyte in a surfactant mobile phase to that of the same analyte in pure water, while all
other experimental conditions remain constant.

83

α2 =

k surfactant

(4.6)

k water

The value for α2 is related to the effect of the surfactant monomers on the transport of the
model analytes. As α2 increases, the neutral analyte exhibits a preference of interaction
with the surfactant monomers in the stationary phase.
The third selectivity factor, α3, is defined as the ratio of the retention factor of an
analyte in LiPFOS mobile phase to that of the same analyte in SDS mobile phase, while
all other experimental conditions remain constant.
α3 =

k LiPFOS

(4.7)

kSDS

The value for α3 is related to the affinity of the model analyte for LiPFOS compared to
SDS. As α3 increases, the neutral analyte exhibits a greater preference for interaction
with LiPFOS than with SDS in the stationary phase.
4.3 Results and Discussion

The rationale behind the choice of stationary phase and surfactants has been
discussed in Section 2.2.1 and a previous report [22]. The Poroshell stationary phase was
2

−1

selected because its carbon content (0.39 %) and surface area (6.0 m g ) are within the
typical ranges for various soils, bed sediments, and suspended solids [23]. Sodium
dodecyl sulfate (SDS) and lithium perfluorooctane sulfonate (LiPFOS) were chosen as
representative surfactants because they are used commercially and have been detected in
the environment [15-20,24-27]. The analytes represent important classes of
environmental contaminants. The BTEX compounds are suspected human carcinogens,
which have entered the environment from spills and leakage of underground fuel tanks.

84

In addition, these analytes can be used to examine if their differences in physical and
chemical characteristics influence the transport effects of hydrocarbon and perfluorinated
surfactants.
4.3.1

Transport Effects in Water

In order to be able to compare the transport effects of the surfactant monomers,
the retention of the neutral analytes was determined in a water mobile phase devoid of
surfactants. Three water studies were performed, with the first study taking place before
any surfactant was introduced, the second after the SDS study, and the third after the
LiPFOS study. In all cases, the elution order for the analytes in the water mobile phase
was as follows: benzene < fluorobenzene < toluene <chlorobenzene < bromobenzene <
ethylbenzene < p-xylene. The retention order followed what is expected for a partition
mechanism. The retention factors for the analytes are shown in Table 4.1. A student’s ttest was performed at the 95 % confidence level (C.L.), which revealed that the retention
factors were statistically different between the first and second studies, but statistically
the same between the second and third studies. Based on these results, each surfactant
study will be compared with the preceding water study, as described in the following
sections.

85

a

Table 4.1: Retention factors of analytes in pure water.

Retention Factors (k)
Analyte

b

c

d

Study 1

Study 2

Benzene

1.94 ± 0.04

1.59 ± 0.04

1.56 ± 0.02

Fluorobenzene

2.43 ± 0.02

1.96 ± 0.03

1.95 ± 0.02

Chlorobenzene

6.82 ± 0.00

5.75 ± 0.09

5.70 ± 0.04

Bromobenzene

10.0 ± 0.0

8.54 ± 0.13

8.47 ± 0.04

Toluene

6.28 ± 0.02

5.38 ± 0.09

5.26 ± 0.00

Ethylbenzene

18.1 ± 0.0

16.2 ± 0.1

15.6 ± 0.1

p-Xylene

20.9 ± 0.1

18.0 ± 0.2



a

Study 3

e

Retention factors are an average of at least three injections. Experimental conditions as
given in the text.
b
Measurements in pure water were performed before the SDS mobile phase study.
c
Measurements in pure water were performed before the LiPFOS mobile phase study.
d
Measurements in pure water were performed after the LiPFOS mobile phase study.
e
Single injection of toluene.

86

4.3.2

Transport Effects of Sodium Dodecyl Sulfate

Injections of the analytes were performed in SDS mobile phases within the
concentration range of 1.0 – 5.0 mM. The elution order for the analytes in SDS was
identical to that observed in a water mobile phase on the same stationary phase. These
results imply that the addition of the surfactant monomers to the system does not change
the fundamental partitioning mechanism of the RPLC system, in relation to a pure water
system.
The experimental retention factors for the BTEX compounds and the
monohalogenated benzenes are summarized in Table 4.2. In comparing the k values in
1.0 mM SDS to those in pure water, the values increased by 2 to 15 %. A larger increase
of 8 to 34 % was observed upon comparing the k values in 5.0 mM SDS to those in pure
water. Statistical treatment of the data via a t-test at the 95 % C.L. shows that the overall
increase in k values with an increase in SDS concentration is statistically significant in all
cases. Consistently, fluorobenzene displayed a relatively small increase, whereas
chlorobenzene and bromobenzene displayed the largest increases.
A graph of the logarithmic retention factor versus the concentration of SDS is
shown in Figure 4.1. Statistical treatment of these graphs via linear regression
demonstrated that there was an increasing linear relationship between k and surfactant
2

concentration, where the R values were greater than 0.91 for chlorobenzene,
2

bromobenzene, and toluene. The R values were between 0.46 – 0.75 for fluorobenzene,
2

ethylbenzene, benzene, and p-xylene. Although several R values were less than 0.90,
the slope of each line was statistically greater than zero when tested at the 95 % C.L.

87

Table 4.2: Retention and selectivity factors of analytes in pure water and SDS mobile
a
phases.
Selectivity Factors (α)

Retention Factors (k)
Analyte

Pure Water

1.0 mM
SDS

5.0 mM
SDS

α1

Benzene

1.94 ± 0.04

2.02 ± 0.04

2.19 ± 0.04

1.00 ± 0.03

1.13 ± 0.03

Fluorobenzene

2.43 ± 0.02

2.51 ± 0.08

2.66 ± 0.08

1.21 ± 0.04

1.09 ± 0.04

Chlorobenzene

6.82 ± 0.00

7.75 ± 0.12

9.01 ± 0.07

4.11 ± 0.08

1.32 ± 0.01

Bromobenzene

10.0 ± 0.0

11.5 ± 0.2

13.4 ± 0.1

6.13 ± 0.12

1.34 ± 0.01

Toluene

6.28 ± 0.02

6.58 ± 0.03

7.09 ± 0.08

3.23 ± 0.07

1.13 ± 0.01

Ethylbenzene

18.1 ± 0.0

19.0 ± 0.2

20.1 ± 0.2

9.17 ± 0.19

1.11 ± 0.01

p-Xylene

20.9 ± 0.1

21.4 ± 0.0

22.5 ± 0.5

10.2 ± 0.3

1.07 ± 0.02

b

a

c

α2

d

Retention and selectivity factors are an average of at least three injections.
Experimental conditions as given in the text.
b
Measurements in pure water were performed before the SDS mobile phase study.
c
Selectivity factors calculated between analyte and benzene in 5.0 mM SDS (Equation
4.5).
d
Selectivity factors calculated for analyte between 5.0 mM SDS and pure water
(Equation 4.6).

88

Figure 4.1:

Graph of the logarithmic retention factor versus the concentration of

sodium dodecyl sulfate (SDS) in the micelle. Analytes: (♦) benzene, (■) fluorobenzene,
(x) chlorobenzene, (*) bromobenzene, (▲) toluene, (○) p-xylene, (•) ethylbenzene.
Other experimental conditions as given in the text.

89

Figure 4.1

Retention Factor (k)

100

10

1
0.0

1.0

2.0

3.0
Concentration of SDS (mM)

90

4.0

5.0

6.0

Based on these results, the overall effect was that the retention of the analytes increased
as the concentration of SDS increased. Consequently, SDS decreases chromatographic
transport of benzene and the substituted benzenes and, by implication, decreases
environmental transport as well.
The selectivity factor α1 was calculated from the average retention factors of the
analyte and benzene (Equation 4.5), with representative data summarized in Table 4.2.
All α1 values were greater than or equal to unity, which suggests that all substituents
increased the analyte interaction with the stationary phase. It was observed that α1 values
increased as the size of the substituent increased for the series of monohalogenated
benzenes and the BTEX compounds. For example, the α1 values increased from 1.2 to
6.1 as the size of the halogen substituent increased from fluorine to bromine (Table 4.2).
The α1 data were statistically treated via linear regression and a t-test at the 95 % C.L.
These results demonstrated that there is an increasing linear trend between α1 values and
increasing SDS concentration for chlorobenzene and bromobenzene. For the remaining
analytes, the α1 values were either statistically invariant (toluene, ethylbenzene, and
fluorobenzene) or statistically decreasing (p-xylene) with increasing SDS concentration.
This result suggests that the inclusion of chlorine and bromine substituents increases the
interaction of a pollutant with in the stationary phase as the SDS concentration increases.
In contrast, fluorine and short-chain alkyl substituents have little or no interaction.
The selectivity factor α2 was calculated from the average retention factors of the
analyte in surfactant and water mobile phases (Equation 4.6), with representative data
summarized in Table 4.2. All α2 values were greater than unity at each SDS mobile

91

phase concentration. It was observed that α2 values were consistently the highest for
chlorobenzene and bromobenzene, while relatively low for fluorobenzene. The α2 values
for the remaining analytes were grouped within a similar range. Statistical treatment
shows that there is an increasing linear trend between α2 values and increasing SDS
concentration for all analytes. These results suggest that chlorobenzene and
bromobenzene have increased interaction with SDS surfactant monomers in the
stationary phase, compared to a system devoid of surfactant. The interaction of the
remaining analytes with SDS monomers is of similar but smaller magnitude.
4.3.3

Transport Effects of Lithium Perfluorooctane Sulfonate

Injections of the analytes were performed in LiPFOS mobile phases over the same
concentration range as SDS (1.0 – 5.0 mM). The elution order for the analytes in
LiPFOS was identical to that observed in pure water and SDS mobile phases on the same
stationary phase. These results imply that the addition of the perfluorinated surfactant
does not change the fundamental partitioning mechanism of the RPLC system, in relation
to a system devoid of a surfactant or containing a hydrocarbon surfactant.
The experimental k values for each analyte in LiPFOS mobile phases are
summarized in Table 4.3. In comparing 1.0 mM LiPFOS to pure water, the k values
increased by 2 to 18 % for the BTEX and the monohalogenated benzenes, except for
bromobenzene which decreased by 3 %. In comparing 5.0 mM LiPFOS to pure water,
the majority of analytes displayed a decrease in k values (3 to 18 %), with the exceptions
of benzene, toluene, and fluorobenzene. Statistical treatment of the data via a t-test at the
95 % C.L. shows that the overall decrease in k values with an increase in LiPFOS
concentration is statistically significant in all cases.

92

Table 4.3: Retention and selectivity factors of analytes in pure water and LiPFOS mobile
a
phases.
Selectivity Factors (α)

Retention Factors (k)
Analyte

Pure
b
Water

1.0 mM
LiPFOS

5.0 mM
LiPFOS

α1

Benzene

1.59 ±
0.04

1.76 ±
0.04

1.62 ±
0.09

1.00 ±
0.08

1.02 ±
0.06

0.74 ±
0.04

Fluorobenzene

1.96 ±
0.03

2.31 ±
0.01

2.16 ±
0.12

1.31 ±
0.11

1.10 ±
0.07

0.81 ±
0.05

Chlorobenzene

5.75 ±
0.09

5.99 ±
0.02

5.19 ±
0.25

3.20 ±
0.24

0.90 ±
0.05

0.58 ±
0.03

Bromobenzene

8.54 ±
0.13

8.31 ±
0.06

7.01 ±
0.29

4.33 ±
0.31

0.82 ±
0.04

0.52 ±
0.02

Toluene

5.38 ±
0.09

5.96 ±
0.15

5.40 ±
0.10

3.33 ±
0.20

1.00 ±
0.03

0.76 ±
0.02

9.41 ±
0.54

0.94 ±
0.01

0.76 ±
0.01

0.97 ±
0.02

0.78 ±
0.02

Ethylbenzene
p-Xylene

16.2 ± 0.1 16.6 ± 0.1 15.3 ± 0.1

c

18.0 ± 0.2 19.7 ± 0.6 17.5 ± 0.1 10.8 ± 0.6

a

α2

d

α3

e

Retention factors are an average of at least three injections. Experimental conditions as
given in the text.
b
Measurements in pure water were performed before the LiPFOS mobile phase study.
c
Selectivity factors calculated between analyte and benzene in 5.0 mM LiPFOS
(Equation 4.5).
d
Selectivity factors calculated for analyte between 5.0 mM LiPFOS and pure water
(Equation 4.6).
e
Selectivity factors calculated for analyte between 5.0 mM LiPFOS and 5.0 mM SDS
(Equation 4.7).

93

Consistently, fluorobenzene displayed the smallest decrease, whereas chlorobenzene and
bromobenzene displayed the largest decrease.
Overall, the retention factors for each analyte were lower in LiPFOS than those in
SDS mobile phases of identical concentrations. With regard to 1.0 mM LiPFOS (Table
4.3) and 1.0 mM SDS (Table 4.2), the k values decreased by 8 to 13 % for the BTEX
analytes and by 8 to 28 % for the monohalogenated benzenes. The difference in k values
became more pronounced at concentrations of 5.0 mM for both surfactants, as the
decrease in k values almost doubles or triples in some cases. It is apparent that LiPFOS
induces less retention and, hence more transport, than does SDS for these analytes.
A graph of the logarithmic retention factor versus the concentration of LiPFOS is
shown in Figure 4.2. Statistical treatment of these graphs via linear regression
demonstrated that there was a decreasing linear relationship between k and surfactant
2

concentration, where the R values were between 0.85 – 0.96 for p-xylene,
2

chlorobenzene, bromobenzene, and ethylbenzene. The R values were between 0.31 –
2

0.54 for toluene, benzene, and fluorobenzene. Although several R values were less than
0.90, the slope of each line was statistically less than zero when tested at the 95 % C.L.
Based on these results, the overall effect was that the retention of the analytes decreased
as the concentration of LiPFOS increased. Consequently, LiPFOS increases
chromatographic transport of benzene and the substituted benzenes and, by implication,
increases environmental transport as well.

94

Figure 4.2:

Graph of logarithmic retention factor versus the concentration of lithium

perfluorooctane sulfonate (LiPFOS) in the micelle. Analytes: (♦) benzene, (■)
fluorobenzene, (x) chlorobenzene, (*) bromobenzene, (▲) toluene, (○) p-xylene, (•)
ethylbenzene. Other experimental conditions as given in the text.

95

Figure 4.2

Retention Factor (k)

100

10

1
0.0

1.0

2.0

3.0

4.0

Concentration of LiPFOS (mM)

96

5.0

6.0

The selectivity factor α1 was calculated from the average retention factors of the
analyte and benzene (Equation 4.5), with representative data summarized in Table 4.3.
All α1 values were greater than or equal to unity, as observed previously for SDS. The
α1 values were greater in LiPFOS (Table 4.3) than SDS (Table 4.2) for all analytes, with

the exception of chlorobenzene and bromobenzene. Identical in trend to SDS, the α1
values increased as the size of the substituent increased for the series of monohalogenated
benzenes and the BTEX compounds. The α1 data were statistically treated via linear
regression and a t-test at the 95 % C.L. These results demonstrated that there is a
decreasing linear trend between α1 values and increasing LiPFOS concentration for
chlorobenzene, bromobenzene, and p-xylene. For the remaining analytes, the α1 values
were statistically invariant (toluene, ethylbenzene, and fluorobenzene) with increasing
LiPFOS concentration. This suggests that the inclusion of the chlorine and bromine
substituents decreases the interaction of a pollutant with LiPFOS monomers in the
stationary phase.
The selectivity factor α2 was calculated from the average retention factors of the
analytes in surfactant and water mobile phases (Equation 4.6), with representative data
summarized in Table 4.3. The α2 values were slightly greater than or equal to unity at all
mobile phase concentrations for benzene, fluorobenzene, and toluene. The α2 values
were less than unity at all mobile phase concentrations for bromobenzene. The α2 values
for chlorobenzene and ethylbenzene were slightly greater than unity at low
concentrations (1.0 – 2.0 mM LiPFOS) and less than unity at higher concentrations (3.0 –
5.0 mM LiPFOS). It was observed that α2 values were the lowest for chlorobenzene,
97

bromobenzene, and ethylbenzene, while fluorobenzene had the highest α2 values at all
LiPFOS concentrations. Statistical treatment of the α2 data shows that there is a
decreasing linear trend between α2 values and increasing LiPFOS concentration for all
analytes. These results suggest that chlorobenzene and bromobenzene have decreased
interaction with the LiPFOS surfactant monomers adsorbed on the stationary phase.
However, fluorobenzene, which is more chemically similar to LiPFOS than the other
analytes, displayed an increased interaction with LiPFOS surfactant monomers adsorbed
on the stationary phase. These results are consistent with those for α1 summarized above.
The selectivity factor α3 was calculated from the average retention factors of the
analytes in LiPFOS and SDS mobile phases (Equation 4.7), with representative data
summarized in Table 4.3. All α3 values were less than unity, which suggests that all
analytes had a greater affinity for SDS surfactant in the stationary phase than for LiPFOS.
It was observed that α3 values were the lowest for chlorobenzene and bromobenzene and
highest for fluorobenzene at all surfactant concentrations. These results are consistent
with those for α2 summarized above, which indicate that chlorobenzene and
bromobenzene have the least interaction with LiPFOS, and fluorobenzene has the greatest
interaction. Statistical treatment of the α3 data shows that there is a decreasing linear
trend between α3 values and increasing surfactant concentration for all analytes. Hence,
the affinity of the analytes for SDS relative to LiPFOS becomes more pronounced with
increasing surfactant concentration. From these results, it is apparent that increasing SDS
concentration induces more retention and, hence less chromatographic and environmental
transport, than does increasing LiPFOS concentration.

98

4.3.4

Effect of Ionic Surfactant on the Polarity of the System

In a RPLC system, analyte retention can be described by a partition mechanism.
Partitioning occurs as the analyte distributes between a polar mobile phase and a nonpolar stationary phase. Neutral, non-polar analytes are more likely to partition into the
stationary phase and be retained. The addition of a surfactant monomer to the RPLC
system can lead to a change in polarity of the system, which can lead to a change in
retention compared to a pure water system.
The retention factor of an analyte in a RPLC system can be related to the
Hildebrand solubility parameter (δ) [28] by the following equation
ln k =

Vi 
2
2
δi − δM − δi − δS  − ln φ
RT 



(

)

(

)

(4.8)

where Vi is the molar volume of the analyte, R is the gas constant, T is the absolute
temperature, and δi, δM, and δS are the solubility parameters of the analyte, mobile phase,
and stationary phase, respectively [29,30]. In RPLC, the analytes are often intermediate
in polarity, such that δM > δi > δS. For a given analyte, the balance of interactions with
the mobile phase (δi – δM) and stationary phase (δi – δS) controls the retention factor.
Upon the addition of a surfactant to the RPLC system, the monomers can partition into
1/2

the octadecylsilica stationary phase. The SDS surfactant (δSDS = 29 MPa

[31]) will

cause the overall δS of the stationary phase to increase, leading to an increase in retention
factors according to Equation 4.8. However, the fluoroalkyl chain of LiPFOS (δC8F18 ≈
1/2

11.7 MPa

1/2

[31]) is much less polar than the alkyl chain of SDS (δC12H26 ≈ 16.1 MPa

[31]). Thus, the LiPFOS surfactant will cause the overall δS of the stationary phase to

99

decrease, leading to a decrease in retention factors according to Equation 4.8. The results
observed in this study are consistent with the general predictions of this model, thus
leading to the conclusion that the change in analyte retention arises from the change in
polarity of the system.
4.3.5

Effect of Ionic Surfactant on the Solubility of the Analytes

It has been reported in the literature that the addition of ionic species to pure
water can change the solubility of neutral non-polar analytes [32,33]. Therefore, it is
possible that this is the origin of the change in retention, rather than the change in polarity
of the stationary phase as described above. To examine this possibility, a study was
conducted to evaluate whether changes in the analyte retention were due to “salting out”
(hydrophobic effect) caused by the addition of the ionic surfactant. In order to simulate
the effects at the highest surfactant concentration used in this study, a 5.0 mM aqueous
lithium nitrate (LiNO3) mobile phase was used. The retention factors of the BTEX
compounds (excluding p-xylene) and the monohalogenated benzenes were calculated,
with representative data summarized in Table 4.4. Statistical treatment via a t-test at the
95 % C.L. demonstrated that the k values were statistically the same as those determined
in pure water mobile phase.

100

Table 4.4: Retention and selectivity factors of analytes in pure water and LiNO3 mobile
a
phases.

Analyte

Retention Factors (k)
b

Pure Water
Benzene
Fluorobenzene
Chlorobenzene
Bromobenzene
Toluene
Ethylbenzene

5.0 mM LiNO3

1.56 ± 0.02
1.95 ± 0.02
5.70 ± 0.04
8.47 ± 0.04
d
5.26 ± 0.00

1.55 ± 0.04
1.96 ± 0.06
5.72 ± 0.15
8.48 ± 0.22
5.27 ± 0.03

15.6 ± 0.1

15.5 ± 0.2

a

Selectivity
Factors (α)
c
α4
0.99 ± 0.03
1.00 ± 0.03
1.00 ± 0.03
1.00 ± 0.03
1.00 ± 0.01
0.99 ± 0.01

Retention factors are an average of at least three injections, except as noted below.
Experimental conditions as given in the text.
b
Measurements in pure water were performed before the LiNO3 mobile phase study.
c
Selectivity factors calculated for analyte between 5.0 mM LiPFOS and pure water
(equation 9).
d
Single injection of toluene.

101

The fourth selectivity factor, α4, is defined as the ratio of the retention factor of an
analyte in a 5.0 mM LiNO3 mobile phase to that of the same analyte in pure water, while
all other experimental conditions remain constant.
α4 =

k LiNO

3

(4.9)

k water

The value for α4 is related to the hydrophobic effect of the LiNO3 salt in the RPLC
system on the transport of the analytes. As the values of α4 are statistically equal to unity
(Table 4.4), there is no hydrophobic effect caused by the addition of the ionic salt at the
concentration of 5.0 mM. These results lend credibility to the claim that the addition of
the ionic surfactants (within the same experimental concentration range) does not induce
a hydrophobic effect on the analytes in the aqueous mobile phases used in this study.
4.4 Summary

During this study, the effects of a hydrocarbon and perfluorinated surfactant
below their CMC were determined on the transport of environmental contaminants in a
model groundwater system. The overall trend was that an increase in surfactant
concentration below the CMC resulted in a statistically significant change in the transport
relative to that in the system devoid of any surfactant. The addition of the hydrocarbon
surfactant below the CMC statistically decreased transport of the analytes in the model
groundwater system, while the addition of the perfluorinated surfactant statistically
increased transport. It is postulated that the adsorption of the hydrocarbon surfactant to
the stationary phase lead to increased analyte interaction, which caused the decrease in
analyte transport. The transport trends of the individual analytes were similar based on
size of the substituent in both surfactants. Transport trends of chlorobenzene and

102

bromobenzene were opposite that of fluorobenzene in both the hydrocarbon and
perfluorinated surfactant. The fluorinated analyte displayed a greater interaction with the
perfluorinated surfactant below the CMC. Further studies are needed to characterize
transport effects of perfluorinated surfactants on environmental pollutants, based on
different carbon chain lengths (C4 – C8) and head group (sulfonate, carboxylate, etc.) of
the surfactant.

103

REFERENCES

104

4.5 References

[1]

J. Ståhlberg, J. Chromatogr. A 855 (1999) 3-55.

[2]

B.A. Bidlingmeyer, S.N. Deming, W.P. Price Jr., B. Sachok, M. Petrusek, J.
Chromatogr. 186 (1979) 420-434.

[3]

J.H. Knox, G.R. Laird, J. Chromatogr. 122 (1976) 17-34.

[4]

J.C Kraak, K.M. Jonker, J.F.K. Huber, J. Chromatogr. 142 (1977) 671-688.

[5]

B. Fransson, K.G. Wahlund, I.M. Johansson, G. Schill, J. Chromatogr. 125 (1976)
327-344.

[6]

T. Cecchi, F. Pucciarelli, P. Passamonti, Chromatographia 53 (2001) 27-34.

[7]

J.R. Jezorek, K.A. Wagner, J. Chromatogr. A 776 (1997) 221-231.

[8]

C. Sarzanini, M.C. Bruzzoniti, G. Sacchero, E. Mentasti, Anal. Chem. 68 (1996)
4494-4500.

[9]

D.E. Kile, C.T. Chiou, Environ. Sci. Technol. 23 (1989) 832-838.

[10]

D.A. Edwards, R.G. Luthy, Z. Liu, Environ. Sci. Technol. 25 (1991) 127-133.

[11]

S.O. Ko, M.A. Schlautman, E.R. Carraway, Environ. Sci. Technol. 32 (1998)
2769-2775.

[12]

C.A. Moody, J.A. Field, Environ. Sci. Technol. 34 (2000) 3864-3870.

[13]

C.A. Moody, W.C. Kwan, J.W. Martin, D.C.G. Muir, S.A. Mabury, Anal. Chem.
73 (2001) 2200-2206.

[14]

C.A. Moody, J.W. Martin, W.C. Kwan, D.C.G. Muir, S.A. Mabury, Environ. Sci.
Technol. 36 (2002) 545-551.

[15]

United States Environmental Protection Agency, Prevention, Pesticides and Toxic
Substances (7505C), EPA-730-F-99-009, 1999.

[16]

J.P. Giesy, K. Kannan, Environ. Sci. Technol. (2002) 148A-152A.

[17]

J.P. Giesy, K. Kannan, Environ. Sci. Technol. 35 (2001) 1339-1342.

[18]

K. Kannan, J. Koistinen, K. Beckmen, T. Evans, J.F. Gorzelany, K.J. Hansen,
P.D. Jones, E. Helle, M. Nyman, J.P. Giesy, Environ. Sci. Technol. 35 (2001)
1593-1598.

105

[19]

K. Kannan, J.C. Franson, W.W. Bowerman, K.J. Hansen, P.D. Jones, J.P. Giesy,
Environ. Sci. Technol. 35 (2001) 3065-3070.

[20]

S. Taniyasu, K. Kannan, Y. Horii, N. Yamashita, Organohalogen Compd. 59
(2002) 105-108.

[21]

Y.J. An, E.R. Carraway, M.A. Schlautman, Water Res. 36 (2002) 300-308.

[22]

R.N. Simmons, V.L. McGuffin, Anal. Chimica Acta 603 (2007) 93-100.

[23]

D.E. Kile, C.T. Chiou, H. Zhou, H. Li, O. Xu, Environ. Sci. Technol. 29 (1995)
1401-1406.

[24]

K. Heinig, C. Vogt, Electrophoresis 290 (1999) 3311-3328.

[25]

J.A. Field, M. Schultz, D. Barofsky, Chimia 57 (2003) 556-560.

[26]

M.N. Khan, U. Zareen, J. Hazard. Mater. 133 (2006) 269-275.

[27]

S. Martinez-Barrachina, J. Alonso, L. Matia, R. Prats, M. del Valle, Anal. Chem.
71 (1999) 3684-3691.

[28]

A.F.M. Barton, Chem. Rev. 75 (1975) 731-754.

[29]

R. Tijssen, H.A.H. Billiet, P.J. Schoenmakers, J. Chromatogr. 122 (1976) 185203.

[30]

P.J. Schoenmakers, H.A.H. Billiet, L. de Galan, Chromatographia 15 (1982) 205214.

[31]

A.F.M. Barton, Handbook of Solubility Parameters and Other Cohesion
nd
Parameters, 2 Ed., CRC Press, Boca Raton, FL, 1991.

[32]

C.F. Poole, S.K. Poole, Chromatography Today, Elsevier Science Publishers,
Amsterdam, 1991, Chapter 4.

[33]

C. Tanford, The Hydrophobic Effect: Formation of Micelles and Biological
Membranes, John Wiley and Sons, New York, NY, 1980.

106

CHAPTER 5: COMPARISON OF TRANSPORT EFFECTS BELOW THE
CRITICAL MICELLE CONCENTRATION: CATIONIC AROMATIC AMINES
5.1 Introduction

Perfluorinated surfactants, such as perfluorooctane sulfonate, have different
physical and chemical characteristics than hydrocarbon surfactants [1-2]. They have
been detected in the environment at concentrations substantially lower than their critical
micelle concentration (CMC) [3-6]. Previous studies of perfluorinated surfactants have
focused on their bioaccumulation and global distribution [7-11], their ability to enhance
the solubilization of polycyclic aromatic hydrocarbons [12], and transport effects above
and below their CMC on neutral hydrophobic compounds [13-14]. However, relatively
little information is available regarding the effects of low levels of perfluorinated
surfactants on the transport of ionic environmental contaminants.
One way to elucidate this information is the use of reversed-phase liquid
chromatography (RPLC) with surfactants. The addition of surfactants to the mobile
phase in a RPLC system has been used to adjust the separation of oppositely charged
metal ions, ionic and neutral compounds in solution [15]. This technique has been given
different names throughout the years [16-17], and is currently referred to as ion-pair
chromatography [18] and ion interaction chromatography [19-20]. These terms are all
characterized by the use of a reversed-phase stationary phase and an interaction reagent
in the mobile phase, regardless of the presence of a pH buffer or an organic modifier [21].
In a RPLC system devoid of any surfactant, analyte retention is controlled either
via a partition or adsorption mechanism. However, the inclusion of an ionic surfactant in
the mobile phase also allows for the retention to be controlled either via the ion-pair or
ion interaction mechanism [21-22], as well as those previously mentioned. The addition

107

of a surfactant allows for the possibility of ion interactions such as ion-induced dipole,
ion-dipole, and/or ion-ion. Moreover, perfluorinated surfactants have greater
polarizability than hydrocarbon surfactants, which can potentially increase induced
dipole-induced dipole and dipole-induced dipole interactions. Any one or combination of
these interactions will have an effect on the transport of ionic environmental
contaminants.
The main focus of this study is to compare the effects of anionic perfluorinated
and hydrocarbon surfactants below their CMC on the transport of cationic environmental
contaminants in a model groundwater system. Lithium perfluorooctane sulfonate and
sodium dodecyl sulfate are used as representatives of the two classes of anionic
surfactants. Pyridine, 4-aminopyridine, aniline, and substituted anilines are used as
models of cationic environmental pollutants. The results of this study yield information
concerning the retention factors and several selectivity factors of the model pollutants.
These values can be used to elucidate the transport effects of perfluorinated surfactants
on pollutants that might leach into water systems or aquifers.
5.2 Experimental Methods
5.2.1

Mobile Phase and Analytes

The hydrocarbon surfactant, sodium dodecyl sulfate (SDS), was obtained from
Aldrich and was used as received. The perfluorinated surfactant, lithium perfluorooctane
sulfonate (LiPFOS), was prepared by dissolving the appropriate amounts of
heptadecafluorooctane sulfonic acid (TCI America) and lithium hydroxide monohydrate
(99.95 %, Aldrich) in deionized, distilled water (Corning Mega-Pure, Models D2 and
MP-3A). The surfactant solutions were prepared by dissolving the appropriate amount of

108

surfactant (1.0 – 4.0 mM) and β-alanine (10 mM, Aldrich) as buffer in various ratios of
methanol and deionized, distilled water (20 – 55 % v/v). The solutions were then filtered
through a cellulose acetate membrane (Alltech) with a 0.45 µm pore size. The resulting
buffered solutions were adjusted to pH 4.0 ± 0.1 with hydrochloric acid.
The aromatic amines pyridine, 4-aminopyridine, aniline, benzylamine, o-, m-, and
p-toluidine, N-methylaniline, N,N-dimethylaniline, N-ethylaniline, N,N-diethylaniline,
-3

and 2,6-dimethylaniline (Aldrich) were used as received. Stock solutions (1.0 x 10 M)
of the analytes were prepared in high-performance liquid chromatography-grade
methanol (Spectrum Chemical). Analytical samples were prepared via dilution of the
proper amount of stock solutions. First, the stock solutions were evaporated with
nitrogen, such that the residual concentration of methanol from the stock solutions would
be less than 1 % (v/v) in the final analytical sample. Next, the sample was diluted with
−1

the surfactant solution and 1.2 µL of aqueous lithium nitrate solution (2.00 x 10

M

LiNO3) to acquire the working concentrations in a 25.0 mL final volume. The working
−5

concentration in the analytical samples was 5.00 x 10
−6

10

5.2.2

M for the analytes and 9.60 x

M for LiNO3.
Experimental System

The experimental chromatographic methods, as detailed in Section 2.2, are briefly
recapped in this section. The commercial analytical column (4.6 mm i.d. x 250 mm
length) was packed with Poroshell 300SB-C18 pellicular particles (Agilent) of 5.0 µm
2

−1

diameter and 6.0 m g
µmol m

−2

surface area, with an octadecylsilica stationary phase of 2.1

bonding density and 0.39 % carbon content. The liquid chromatography

109

system consisted of a single-piston reciprocating pump (Beckman, Model 110B), an
injector with a 20 µL injection loop (Valco, Model EC6W), and a UV-visible absorbance
detector (Hitachi, Model L-4200). The UV absorbance wavelength of 205 nm was
specific for the detection of the aromatic amines, and did not incur any interference from
the surfactants. The signal from the UV-visible absorbance detector was converted to the
digital domain (Model PCI-MIO-16XE-50, National Instruments) and stored via a userdefined software program (Labview v5.1, National Instruments). All experiments were
carried out at ambient temperature with a maximum pressure limit of 4500 psi. The flow
-1

-1

rate was 1.0 mL min during the SDS experiments and 0.5 mL min during the LiPFOS
and pure water experiments. The void time, t0, was taken as the first positive deviation
from the baseline arising from LiNO3 in each sample. The retention time, tR, for each
analyte was determined from the peak maximum, which is appropriate for the symmetric
Gaussian peaks observed in this study. The retention factor, k, was then calculated by
−

t
k= R

t0

(5.1)

t0

The k values (average of at least three trials) were used for the subsequent elucidation of
transport effects and determination of selectivity factors as described in the following
section.
5.2.3

Data Analysis

5.2.3.1 Retention Factor Measurements

In order to elucidate meaningful information regarding the transport effects of
anionic perfluorinated surfactants on ionic analytes (e.g. cationic aromatic amines) in an
environmental system, an analytical technique was used that could fundamentally

110

resemble such a system, but whose parameters were controllable. Reversed-phase liquid
chromatography was used to model an environmental system, in which the
octadecylsilica stationary phase represents soil and the aqueous mobile phase represents
groundwater. When a surfactant is added to the RPLC system below its CMC, the
monomers distribute or partition between the mobile and stationary phases. These ionic
surfactant monomers have the potential to alter the retention of ionic analytes (pollutants)
through ion interactions, as described in Section 5.1.
The equilibrium constant, K, which includes ion interactions can be defined as
K=

aS
aM

=

γSCS

(5.2)

γ M CM

where aS and aM represent the activities, γS and γM represent the activity coefficients, and
CS and CM represent the analytical concentrations of the analyte in the stationary (S) and
mobile (M) phases, respectively. Assuming the activity coefficients are equal to unity,
Equation 5.2 indicates that the equilibrium constant is directly related to the ratio of the
analyte concentrations in the stationary and mobile phases. This equilibrium constant
represents all interactions between the analyte, stationary phase, mobile phase, and
surfactant monomers. The equilibrium constant is a vital piece of information needed to
model environmental systems. However, the determination of this equilibrium constant
is difficult because of the inability to directly measure the concentrations of the analyte in
the environmental mobile and stationary phases.
The retention factor, k, is defined as
(5.3)

k = Kφ

where φ is the phase ratio, defined as

111

φ=

VS

(5.4)

VM

where VM and VS are the volumes of the mobile and stationary phase, respectively.
Assuming that the phase ratio is constant, the value for k is proportional to K.
Consequently, the trends in retention factor are consistent with and can be used to predict
the trends in equilibrium constant. In particular, an increase in the retention factor
implies an increase in the concentration of the analyte in the stationary phase relative to
the mobile phase, according to Equation 5.2.
5.2.3.2 Linear Solvent Strength Model

When the determination of the analyte retention factor in solvent A (e.g. aqueous
surfactant solution) is impractical due to excessive retention, a stronger organic cosolvent B (e.g. methanol) can be added to the mobile phase to decrease the analyte
retention. The linear solvent strength (LSS) model relates the analyte retention as a
function of the percent composition of the organic solvent (% B) in the mixed mobile
phase [23], via the following equation
log k = − S(%B) + log k 0

(5.5)

where S is the slope and k0 is the analyte retention factor in pure solvent A (i.e. % B = 0).
Linear regression is performed on the logarithmic k values measured at various % B. The
k0 value of the analyte at a given surfactant concentration is determined from the
logarithmic y-intercept value.
The weighted mean [24] value for k0 is defined by

112

k

k=



∑  σ02,i 


 i 
 1 
∑  σ2 

i  i 

i

(5.6)

where k0,i is the extrapolated analyte retention factor at a given surfactant concentration
and σi is the standard deviation of that individual extrapolated retention factor. The
weighted standard deviation [24] of this mean value is defined by
σ=

1
 1 
∑  σ2 

i  i 


(5.7)

The value k ± σ represents the retention factor of the cationic analyte in an aqueous
surfactant mobile phase. The retention factor of the aromatic amine determined in this
manner is vital information needed for elucidation of transport effects.
5.2.3.3 Selectivity Factor Calculations

In addition to the weighted mean of the extrapolated retention factors determined
from Equation 5.6, several selectivity factors are also compared to elucidate transport
effects. Each selectivity factor provides different information concerning the various
interactions between the analytes and the surfactants.
The first selectivity factor, α1, is defined as the ratio of the retention factor of the
analyte to that of the base aromatic amine (aniline or pyridine), while all other
experimental conditions remain constant.

α1A =

k analyte
k analyte
or α1B =
k aniline
k pyridine

(5.8)

113

The value for α1 is related to the effect of the addition of a substituent group to the base
aromatic amine structure on the transport of the model analytes. As α1 increases, the
additional substituent group leads to increasing interaction of the ionic analyte with the
stationary phase or with the surfactant monomers in the stationary phase.
The second selectivity factor, α2, is defined as the ratio of the retention factor of
an analyte in a surfactant mobile phase to that of the same analyte in pure water, while all
other experimental conditions remain constant.
α2 =

k surfactant
k water

(5.9)

The value for α2 is related to the effect of the surfactant monomers on the transport of the
model analytes. As α2 increases, the ionic analyte exhibits a preference for interaction
with the surfactant monomers in the stationary phase.
The third selectivity factor, α3, is defined as the ratio of the retention factor of an
analyte in LiPFOS mobile phase to that of the same analyte in SDS mobile phase, while
all other experimental conditions remain constant.
α3 =

k LiPFOS
k SDS

(5.10)

The value for α3 is related to the affinity of the model analyte for LiPFOS compared to
SDS. As α3 increases, the ionic analyte exhibits a greater preference for interaction with
LiPFOS than with SDS in the stationary phase.
5.3 Results and Discussion

The rationale behind the choice of stationary phase and surfactants has been
discussed in Section 2.2.1 and a previous report [13], respectively. The Poroshell

114

stationary phase was selected because its carbon content (0.39 %) and surface area (6.0
2 −1

m g ) are within the typical ranges for various soils, bed sediments, and suspended
solids [25]. Sodium dodecyl sulfate (SDS) and lithium perfluorooctane sulfonate
(LiPFOS) were chosen as representative surfactants because they are used commercially
and have been detected in the environment [6-11,26-29]. The analytes represent
important classes of environmental contaminants that are suspected human carcinogens.
Aromatic amines, such as anilines and pyridines, are used in the manufacture of drugs,
dyes and pigments, urethanes, and pesticides (e.g. herbicides, fungicides, insecticides,
etc.) [30-31]. Commercial uses of the compounds can lead to direct or indirect exposure
in the environment. Moreover, all of these analytes can be used to examine how their
differences in physical and chemical characteristics influence the transport effects of
hydrocarbon and perfluorinated surfactants.
5.3.1

Transport Effects in Water

In order to be able to compare the transport effects caused by the different
surfactant monomers, the retention and elution order of the analytes were first determined
in a water mobile phase devoid of surfactants. The retention factors of the analytes are
shown in Table 5.1. It should be noted that the retention factors for most of the analytes
were less than unity (Table 5.1), signifying that the analytes were not strongly retained.
The retention factors for N,N-dimethylaniline, N-ethylaniline, N,N-diethylaniline, and
2,6-dimethylaniline were greater than unity but less than 10. The elution order for the
analytes in the water mobile phase was as follows: 4-aminopyridine < pyridine < aniline
< benzylamine < p-toluidine ≈ N-methylaniline < m-toluidine ≈ o-toluidine < N,Ndimethylaniline < N-ethylaniline < N,N-diethylaniline < 2,6-dimethylaniline.

115

Table 5.1: Retention and selectivity factors of cationic aromatic amines in pure water
mobile phase.
Selectivity Factor (α)

Aromatic Amines

pKa

Retention Factor
a
k

()

α1A

α1B

pyridine
4-aminopyridine
aniline
benzylamine
o-toluidine
m-toluidine
p-toluidine
N-methylaniline
N,N-dimethylaniline
N-ethylaniline
N,N-diethylaniline
2,6-dimethylaniline

5.23
9.17
4.60
9.35
4.45
4.69
5.08
4.85
5.07
5.12
6.57
3.89

0.20 ± 0.01
0.14 ± 0.01
0.27 ± 0.02
0.42 ± 0.01
0.93 ± 0.01
0.93 ± 0.02
0.78 ± 0.02
0.82 ± 0.03
1.41 ± 0.01
1.45 ± 0.01
3.25 ± 0.12
3.70 ± 0.04

0.72 ± 0.04
0.51 ± 0.04
1.00 ± 0.00
1.55 ± 0.09
3.43 ± 0.19
3.43 ± 0.20
2.88 ± 0.17
3.02 ± 0.19
5.19 ± 0.28
5.33 ± 0.29
11.95 ± 0.78
13.60 ± 0.76

1.00 ± 0.00
0.71 ± 0.04
1.39 ± 0.08










a

b

b

Retention factors are an average of three trials (Equation 5.1). Experimental conditions
as given in the text.
b
Selectivity factors calculated between (A) analyte and aniline or (B) analyte and
pyridine (Equation 5.8).

116

A student’s t-test was performed at the 95 % confidence level (C.L.), which revealed that
the retention factors of p-toluidine and N-methylaniline as well as of m-toluidine and otoluidine were statistically indistinguishable. The retention order of the amines in the
water mobile phase followed what is expected for a partition mechanism. The addition of
a methylene (−CH2−) or methyl (−CH3) substituent increased the non-polar characteristic
of the analyte, and lead to increased retention. The addition of a polar amine substituent
to the pyridine aromatic ring increased the polarity of the analyte, thus decreasing
retention. The inclusion of nitrogen in the aromatic ring, as opposed to an amine
substituent on the ring, decreased the retention of the analyte.
The selectivity factor α1 was calculated from the k values of substituted aromatic
amines and a base aromatic amine (Equation 5.8), with the data shown in Table 5.1. In
relation to aniline, most of the α1A values were greater than unity (Table 5.1), signifying
that the addition of the substituent increased analyte interaction with the stationary phase.
The α1A values of pyridine and 4-aminopyridine were less than unity, suggesting the
inclusion of nitrogen in the ring decreased analyte interaction with the stationary phase.
It is observed that addition of a methyl substituent, regardless of position on the ring,
contributed approximately the same amount to analyte interaction. The α1 values
increased with both the size (e.g. methyl versus ethyl) and number of substituents for the
series of anilines. In relation to pyridine, the α1B value was less than unity for 4aminopyridine (0.71 ± 0.04) and greater than unity for aniline (1.39 ± 0.08). This
suggests that the inclusion of a polar amine group decreased the interaction of pyridine
with the stationary phase, thus increasing environmental transport.

117

5.3.2

Transport Effects of Sodium Dodecyl Sulfate

In preliminary experiments, the aromatic amines were examined in an aqueous
SDS mobile phase (1.0 mM). The amines displayed excessive retention in this mobile
phase, and retention factors could not be accurately determined. The LSS method
(described in Section 5.2.3.2) was used for the remainder of this study. Retention factors,
k, of the amines were determined in varying mobile phase compositions of aqueous SDS
(1.0 – 4.0 mM) and methanol (20 – 50 % v/v). The retention of the analytes increased
with increasing SDS concentration, which is in accordance with ion-pair chromatography
and ion interaction theory [19].
Graphs of the logarithmic retention factor for each analyte versus the methanol
composition (% B) are shown in Figures 5.1A-D. Statistical treatment of these graphs via
linear regression demonstrated a linear relationship between log k and % B, where the
2

square of the correlation coefficient, R , values were all greater than 0.970. The linear
relationship observed is consistent with predictions of the LSS method. The aromatic
amines N-ethylaniline, N,N-diethylaniline, and 2,6-dimethylaniline displayed excessive
retention at low percentages of methanol in the 1.0 mM SDS mobile phase (Figure 5.1).
As a result, the aforementioned amines were excluded from further study. The retention
factors of the amines in aqueous surfactant mobile phases (k0) were extrapolated at each
SDS concentration using linear regression of Equation 5.5.
A graph of the logarithmic extrapolated retention factor for each analyte versus
the concentration of SDS is shown in Figure 5.2. There is a significant increase in
analyte retention from 0.0 to 1.0 mM SDS; however retention remains relatively constant
from 1.0 to 4.0 mM SDS.

118

Figures 5.1A-D:

Graphs of the logarithmic retention factor versus methanol

composition (% B) in: (A) 1.0 mM aqueous sodium dodecyl sulfate (SDS), (B) 2.0 mM
SDS, (C) 3.0 mM SDS, (D) 4.0 mM SDS. Analytes: (♦) pyridine, (■) 4-aminopyridine,
(▲) aniline, (x) benzylamine, (*) o-toluidine, (•) m-toluidine, (○) p-toluidine, (◊) Nmethylaniline, (□) N,N-dimethylaniline, (∆) N-ethylaniline, (▬) N,N-diethylaniline, (+)
2,6-dimethylaniline. Other experimental conditions as given in the text.

119

Figure 5.1A
100

Retention Factor

10

1

0.1
15

20

25

30

35

40

Methanol Composition (%)

120

45

50

55

Figure 5.1B

Retention Factor

100

10

1

0.1
20

25

30

35
Methanol Composition (%)

121

40

45

50

Figure 5.1C
100

Retention Factor

10

1

0.1
20

25

30

35
Methanol Composition (%)

122

40

45

50

Figure 5.1D
100

Retention Factor

10

1

0.1
25

30

35

40

Methanol Composition (%)

123

45

50

Figure 5.2:

Graph of the logarithmic extrapolated retention factor for each analyte

versus the concentration of SDS. Analytes: (♦) pyridine, (■) 4-aminopyridine, (▲)
aniline, (x) benzylamine, (*) o-toluidine, (•) m-toluidine, (○) p-toluidine, (◊) Nmethylaniline, (□) N,N-dimethylaniline. Other experimental conditions as given in the
text.

124

Figure 5.2
1.00E+04

Retention Factor

1.00E+03

1.00E+02

1.00E+01

1.00E+00

1.00E-01
0

0.5

1

1.5

2

2.5

Concentration of SDS (mM)

125

3

3.5

4

4.5

A t-test at the 95 % C.L. confirmed that the slope of this graph (within 1.0 – 4.0 mM SDS
range) was indistinguishable from zero. Based on this information, the weighted mean of
the extrapolated retention factors was used to elucidate transport effects.
The weighted mean retention factors ( k , calculated via Equation 5.6) and
standard deviations ( σ , calculated via Equation 5.7) for the analytes are shown in Table
5.2. The relative standard deviations (RSDs) were all less than 8.0 %, which indicates
the good precision of the individual extrapolated retention values. Most of the k values
were greater than 100, signifying that the analytes were highly retained. The overall
elution order was as follows: pyridine < 4-aminopyridine < aniline < benzylamine < mtoluidine < o-toluidine ≈ p-toluidine < N-methylaniline ≈ N,N-dimethylaniline.
Statistical treatment of the k values via a t-test at the 95 % C.L. revealed that the
retention factors of o-toluidine and p-toluidine as well as of N-methylaniline and N,Ndimethylaniline were statistically the same. Overall, the elution order follows the trend
of a partition mechanism. A note of interest is that the retention order of 4-aminopyridine
and pyridine reversed for all SDS mobile phases relative to pure water. It is believed that
the protonated amine substituent on 4-aminopyridine has a greater interaction with the
SDS in the stationary phase, thus leading to enhanced retention. In comparing the k
values in SDS (Table 5.2) to those in pure water (Table 5.1), a large increase of 2 to 4
orders-of-magnitude is observed. It is apparent that the presence of SDS decreases
chromatographic transport of the amines and, by implication, decreases environmental
transport as well.

126

Table 5.2: Retention and selectivity factors of cationic aromatic amines in SDS mobile
phase.
Aromatic Amines

Retention
a
Factor k

pyridine
4-aminopyridine
aniline
benzylamine
o-toluidine
m-toluidine
p-toluidine
N-methylaniline
N,N-dimethylaniline

39.32 ± 1.52
141.2 ± 6.0
422.6 ± 18.8
824.8 ± 40.9
1695 ± 117
937.7 ± 62.3
1700 ± 67
2303 ± 107
2468 ± 176

()

Selectivity Factor (α)
b
α1A

0.093 ± 0.004
0.33 ± 0.01
1.00 ± 0.00
1.95 ± 0.10
4.01 ± 0.28
2.22 ± 0.15
4.02 ± 0.16
5.45 ± 0.26
5.84 ± 0.42

a

b

α1B
1.00 ± 0.00
3.59 ± 0.19
10.75 ± 0.59







c

α2
201.6 ± 34.4
1016 ± 607
1554 ± 700
1954 ± 318
1815 ± 208
1004 ± 172
2169 ± 392
2799 ± 560
1748 ± 157

Retention factors calculated as the weighted mean of the extrapolated retention factors
within the experimental concentration range, 1.0 – 4.0 mM (Equation 5.6).
Experimental conditions as given in the text.
b
Selectivity factors calculated between (A) analyte and aniline or (B) analyte and
pyridine (Equation 5.8).
c
Selectivity factors calculated for analyte between SDS and pure water (Equation 5.9).

127

The selectivity factor α1 was calculated from the k values of substituted aromatic
amines and a base aromatic amine (Equation 5.8), with the results shown in Table 5.2.
Most of the α1 values are greater than unity, signifying that the addition of the substituent
increased analyte interaction with SDS in the stationary phase. The addition of a methyl
substituent at the meta- position increased the interaction of the amine with the SDS
monomers in the stationary phase by a factor of two. In contrast, the addition of the
methyl substituent at either the ortho- or para- position led to a four-fold increase. The
addition of a methyl group to the nitrogen of an amine substituent contributed to analyte
retention by a five-fold increase. The addition of a second methyl group to the nitrogen
resulted in the same increase. The addition of methyl or N-alkyl substituents increases
the basicity and inductive effect of aniline. These results suggest the addition of methyl
substituents to the analytes increased interaction with the SDS monomers in the
stationary phase. In relation to aniline, the α1A values of pyridine and 4-aminopyridine
were less than unity (Table 5.2). This result suggests that the inclusion of nitrogen in the
ring structure of an aromatic amine reduced interaction with the SDS monomers in the
stationary phase.
The selectivity factor α2 was calculated from the k values of the aromatic amines
in SDS and pure water mobile phases (Equation 5.9), with the results shown in Table 5.2.
Most of the α2 values are greater than 1000, implying that the ion-pairing mechanism
with SDS has a large contribution to the retention of the analytes when compared with
partition alone. Although the α2 value of pyridine (201.6 ± 34.4) is less than 1000, it still
suggests that SDS ion-pairing is the major contributor to retention.

128

These results suggest that all of the cationic aromatic amines have strong interactions
with SDS monomers in the stationary phase. This interaction causes the amines to
display a significant decrease in environmental transport when compared to a system
devoid of any surfactant. Based on these results, there is potential for SDS in
environmental remediation of cationic aromatic amines
5.3.3

Transport Effects of Lithium Perfluorooctane Sulfonate

Retention factors, k, of the amines were determined in varying mobile phase
compositions of aqueous LiPFOS (1.0 – 4.0 mM) and methanol (25 – 55 % v/v). Similar
to SDS, analyte retention increased with increasing LiPFOS concentration in accordance
with ion interaction theory [19].
Graphs of the logarithmic retention factor for each analyte versus the methanol
composition (% B) are shown in Figure 5.3A-D. Statistical treatment of these graphs via
linear regression demonstrated a linear relationship between log k and % B, where R

2

values were greater than 0.976. The linear relationship observed is consistent with
predictions of the LSS method. The retention factors of the amines in aqueous surfactant
mobile phases (k0) were extrapolated at each LiPFOS concentration using linear
regression of Equation 5.5.

129

Figures 5.3A-D:

Graphs of the logarithmic retention factor versus methanol

composition (% B) in: (A) 1.0 mM aqueous lithium perfluorooctane sulfonate (LiPFOS),
(B) 2.0 mM LiPFOS, (C) 3.0 mM LiPFOS, (D) 4.0 mM LiPFOS. Analytes: (♦) pyridine,
(■) 4-aminopyridine, (▲) aniline, (x) benzylamine, (*) o-toluidine, (•) m-toluidine, (○) ptoluidine, (◊) N-methylaniline, (□) N,N-dimethylaniline. Other experimental conditions
as given in the text.

130

Figure 5.3A
100

Retention Factor

10

1

0.1
20

25

30

35
40
Methanol Composition (%)

131

45

50

Figure 5.3B
100

Retention Factor

10

1

0
25

30

35

40

Methanol Composition (%)

132

45

50

Figure 5.3C

Retention Factor

100

10

1

0.1
30

35

40

45

Methanol Composition (%)

133

50

55

Figure 5.3D

Retention Factor

10

1

0.1
35

40

45

50

Methanol Composition (%)

134

55

60

A graph of the logarithmic extrapolated retention factor for each analyte versus
the concentration of LiPFOS is shown in Figure 5.4. Similar to SDS, there is a
significant increase in analyte retention from 0.0 to 1.0 mM LiPFOS; however retention
remains relatively constant from 1.0 to 4.0 mM LiPFOS. A t-test at the 95 % C.L
confirmed that the slope of this graph (within 1.0 – 4.0 mM LiPFOS) was
indistinguishable from zero. Based on this information, the weighted mean of the
extrapolated retention factors was used to elucidate transport effects.
The weighted mean retention factors ( k , calculated via Equation 5.6) and
standard deviations ( σ , calculated via Equation 5.7) for the analytes are shown in Table
5.3. The RSDs of the k values in LiPFOS were all less than 12.2 %, indicating that there
is good precision in the extrapolated retention values. The slightly higher RSDs denotes
a greater spread in the LiPFOS data than in SDS. All of the k values were greater than
100, signifying that the analytes were highly retained. The overall elution order was as
follows: pyridine < 4-aminopyridine < aniline < o-toluidine < p-toluidine ≈ benzylamine
< N,N-dimethylaniline < N-methylaniline < m-toluidine. Statistical treatment of the k
values via a t-test at the 95 % C.L. revealed that the retention factors of p-toluidine and
benzylamine were statistically the same. The elution order follows the general trend of a
partition mechanism. Similar to the SDS results, 4-aminopyridine and pyridine reversed
elution order for all LiPFOS mobile phases relative to pure water. While the trend in
elution order was similar between LiPFOS and SDS, it is noteworthy that m-toluidine
eluted after N,N-dimethylaniline in LiPFOS.

135

Figure 5.4:

Graph of the logarithmic extrapolated retention factor for each analyte

versus the concentration of LiPFOS. Analytes: (♦) pyridine, (■) 4-aminopyridine, (▲)
aniline, (x) benzylamine, (*) o-toluidine, (•) m-toluidine, (○) p-toluidine, (◊) Nmethylaniline, (□) N,N-dimethylaniline. Other experimental conditions as given in the
text.

136

Figure 5.4
1.00E+05

1.00E+04

Retention Factor

1.00E+03

1.00E+02

1.00E+01

1.00E+00

1.00E-01
0

0.5

1

1.5

2

2.5

3

Concentration of LiPFOS (mM)

137

3.5

4

4.5

Table 5.3: Retention and selectivity factors of cationic aromatic amines in LiPFOS
mobile phase.
Aromatic Amines

Retention
a
Factor k

Pyridine

217.1 ± 11.0

0.32 ± 0.02

4-aminopyridine

339.3 ± 19.7

0.50 ± 0.03

Aniline

683.9 ± 61.2

1.00 ± 0.00

Benzylamine

2553 ± 256

3.73 ± 0.38



6047 ± 1116

o-toluidine

2098 ± 212

3.07 ± 0.31



2246 ± 307

m-toluidine

7224 ± 530

10.56 ± 0.78



7739 ± 1347

p-toluidine

2394 ± 292

3.50 ± 0.43



3054 ± 656

N-methylaniline

6612 ± 347

9.68 ± 0.52



8036 ± 1621

N,N-dimethylaniline

6093 ± 220

8.91 ± 0.34



4316 ± 284

()

Selectivity Factor (α)
b
α1A

a

b

α1B
1.00 ±
0.00
1.56 ±
0.09
3.15 ±
0.29

α2

c

1113 ± 198
2442 ± 1462
2515 ± 1150

d

α3
5.52 ±
0.33
2.40 ±
0.15
1.62 ±
0.15
3.10 ±
0.31
1.24 ±
0.13
7.70 ±
0.57
1.41 ±
0.17
2.87 ±
0.15
2.47 ±
0.09

Retention factors calculated as the weighted mean of the extrapolated retention factors
within the experimental concentration range, 1.0 – 4.0 mM (Equation 5.6).
Experimental conditions as given in the text.
b
Selectivity factors calculated between (A) analyte and aniline or (B) analyte and
pyridine (Equation 5.8).
c
Selectivity factors calculated for analyte between LiPFOS and pure water (Equation
5.9).
d
Selectivity factors calculated for analyte between LiPFOS and SDS (Equation 5.10).

138

While the author does not have a definitive explanation for this phenomenon, it can be
postulated that steric hindrance of N-alkyl substituted anilines with the sulfonate head
group of LiPFOS contributes to this elution order. Other possible explanations for why
m-toluidine eluted after N,N-dimethylaniline are postulated by the author in the Appendix

5.6. In comparing the k values in LiPFOS (Table 5.3) to those in pure water (Table 5.1),
a large increase of 3 to 4 orders-of-magnitude in amine retention is observed. It is
observed that the k values in LiPFOS (Table 5.3) are greater than in SDS (Table 5.2),
with several of the values being an order of magnitude greater. It is apparent that the
presence of LiPFOS dramatically decreases chromatographic transport of the analytes
and, by implication, decreases environmental transport as well.
The selectivity factor α1 was calculated from the k values of substituted aromatic
amines and a base aromatic amine (Equation 5.8), with the results shown in Table 5.3.
Most of the α1 values are greater than unity, signifying that the addition of the substituent
increased analyte interaction with LiPFOS in the stationary phase. The addition of a
methyl substituent at the meta- position resulted in a ten-fold increase in the interaction of
the amine with the LiPFOS monomers in the stationary phase. In contrast, the addition of
the methyl substituent at either the ortho- or para- position led to a three-fold increase in
the interaction. In relation to aniline, the α1A values of pyridine and 4-aminopyridine
were less than unity (Table 5.3). These results suggest that, similar to the trends in SDS,
the inclusion of nitrogen in the ring structure of an aromatic amine reduced interaction
with the LiPFOS monomers in the stationary phase. Also, the addition of a methyl
substituent to the aromatic ring increased interaction with the LiPFOS monomers in the
stationary phase.

139

The selectivity factor α2 was calculated from the k values of the aromatic amines
in LiPFOS and pure water mobile phases (Equation 5.9), with the results shown in Table
5.3. All of the α2 values are greater than 1000, implying that the ion-pairing mechanism
with LiPFOS has a large contribution to the retention of the analytes compared with
partition alone. This result suggests that, similar to SDS, all of the cationic aromatic
amines have strong interactions with LiPFOS monomers in the stationary phase. This
interaction causes the amines to display a substantial decrease in environmental transport
when compared to a system devoid of any surfactant. In addition, all α2 values were
greater in LiPFOS than in SDS.
The selectivity factor α3 was calculated from the k values of the aromatic amines
in LiPFOS and SDS mobile phases (Equation 5.10), with the results shown in Table 5.3.
All α3 values are greater than unity, implying that the analytes have stronger interactions
with LiPFOS than SDS monomers in the stationary phase. Furthermore, the fact that α3
values ranged from 1.2 – 7.7 suggests that the ion-pairing mechanism with LiPFOS will
have selective interactions with certain cationic amines compared with SDS. Based on
these results, there is potential for the use of LiPFOS in environmental remediation of
cationic aromatic amines since the interactions are more pronounced in a LiPFOS than a
SDS mobile phase. Although perfluorinated surfactants are more expensive than their
hydrocarbon analogous, they are chemically and thermally more stable.
5.4 Summary

During this study, the effects of a hydrocarbon and perfluorinated surfactant on
the transport of environmental contaminants (e.g. cationic aromatic amines) in a model

140

groundwater system were determined. The overall trend was that the addition of either
an anionic hydrocarbon or anionic perfluorinated surfactant below the CMC substantially
decreased the transport of cationic aromatic amines, in relation to transport in the system
devoid of any surfactant. It is noteworthy that the amines displayed a decrease in
transport when the perfluorinated and hydrocarbon surfactants were compared.
Furthermore, an increase in surfactant concentration below the CMC resulted in a
statistically invariant change in transport, within the concentration range tested in this
study (1.0 – 4.0 mM). The individual amines displayed different transport trends
between surfactant and pure water mobile phases. In the pure water system, transport
was controlled via partitioning of the cationic aromatic amines between the polar mobile
phase and the non-polar stationary phase. However, both partitioning and ion interactions
impacted the transport of the amines in the presence of anionic surfactant monomers in
the stationary phase.
These results and conclusions have important implications for the environmental
transport or remediation of cationic aromatic amines. In particular, several of the cationic
aromatic amines exhibit selective interaction with the perfluorinated surfactant compared
to the hydrocarbon surfactant. Further studies are needed to characterize transport effects
of perfluorinated surfactants, particularly in relation to their head group (sulfonate,
carboxylate, etc.) and carbon chain length (C4 – C8), because of their importance to
commercial procedures or possible application in environmental remediation clean-up
techniques.

141

APPENDIX

142

5.5 Appendix

As stated in Section 5.3.3, while the elution order of the analytes was similar
between SDS and LiPFOS, an exception was that m-toluidine eluted after N,Ndimethylaniline in LiPFOS. Two ideas are postulated as to the cause of this deviation in
elution order.
First, through conversations with Dr. James Jackson of Michigan State
University, it was postulated that a different elution order might appear if m-toluidine was
protonated a site other than on the nitrogen. Dr. Jackson used a high level of ab initio
calculation to determine the gas-phase relative energies, ∆Hrel, of the toluidines at various
carbon protonation sites. The results showed that the C4-protonated isomer of m−1

toluidine has a lower relative energy (∆Hrel = −2.3 kcal mol ) than the N-protonated
structure, while other isomers, such as the C2- and C6-protonated isomers, are higher in
energy (∆Hrel = +3.4 kcal mol

−1

−1

and +1.7 kcal mol , respectively). If the C4-protonated

isomer played a significant role during the separation within the mobile phase, then it is
possible the isomer could behave substantially different than the N-protonated toluidines,
thus leading to the longer elution time of m-toluidine seen in this experiment.
Secondly, it has been reported in literature [32,33], that the pKa of substituted
anilines vary depending on the solvent. It is therefore postulated that the addition of the
co-solvent methanol altered the pKa of m-toluidine, affecting the protonation of mtoluidine in the mobile phase (pH 4.0). The variation in protonation could lead to
substantially different interactions within the experimental system, thus leading to the
different elution order and longer retention times for m-toluidine observed in this study.

143

REFERENCES

144

5.6 References

[1]

E. Kissa, Fluorinated Surfactants: Synthesis, Properties, and Applications, Marcel
Dekker, New York, NY, 1994.

[2]

R.E. Banks, B.E. Smart, J.C. Tatlow, Organofluorine Chemistry: Principles and
Commercial Applications, Plenum Press, New York, NY, 1994.

[3]

C.A. Moody, J.A. Field, Environ. Sci. Technol. 34 (2000) 3864-3870.

[4]

C.A. Moody, W.C. Kwan, J.W. Martin, D.C.G. Muir, S.A. Mabury, Anal. Chem.
73 (2001) 2200-2206.

[5]

C.A. Moody, J.W. Martin, W.C. Kwan, D.C.G. Muir, S.A. Mabury, Environ. Sci.
Technol. 36 (2002) 545-551.

[6]

United States Environmental Protection Agency, Prevention, Pesticides and Toxic
Substances (7505C), EPA-730-F-99-009, 1999.

[7]

J.P. Giesy, K. Kannan, Environ. Sci. Technol. (2002) 148A-152A.

[8]

J.P. Giesy, K. Kannan, Environ. Sci. Technol. 35 (2001) 1339-1342.

[9]

K. Kannan, J. Koistinen, K. Beckmen, T. Evans, J.F. Gorzelany, K.J. Hansen,
P.D. Jones, E. Helle, M. Nyman, J.P. Giesy, Environ. Sci. Technol. 35 (2001)
1593-1598.

[10]

K. Kannan, J.C. Franson, W.W. Bowerman, K.J. Hansen, P.D. Jones, J.P. Giesy,
Environ. Sci. Technol. 35 (2001) 3065-3070.

[11]

S. Taniyasu, K. Kannan, Y. Horii, N. Yamashita, Organohalogen Compd. 59
(2002) 105-108.

[12]

Y.J. An, E.R. Carraway, M.A. Schlautman, Water Res. 36 (2002) 300-308.

[13]

R.N. Simmons, V.L. McGuffin, Anal. Chimica Acta 603 (2007) 93-100.

[14]

R.N. Simmons, V.L. McGuffin, Anal. Chimica Acta, manuscript submitted.

[15]

J. Ståhlberg, J. Chromatogr. A 855 (1999) 3-55.

[16]

J.H. Knox, G.R. Laird, J. Chromatogr. 122 (1976) 17-34.

[17]

J.C Kraak, K.M. Jonker, J.F.K. Huber, J. Chromatogr. 142 (1977) 671-688.

145

[18]

B. Fransson, K.G. Wahlund, I.M. Johansson, G. Schill, J. Chromatogr. 125 (1976)
327-344.

[19]

B.A. Bidlingmeyer, S.N. Deming, W.P. Price Jr., B. Sachok, M. Petrusek, J.
Chromatogr. 186 (1979) 420-434.

[20]

B.A. Bidlingmeyer, J. Chromatogr. 18 (1980) 525-539.

[21]

M.C. Gennaro, Advances in Chromatography, Ed. By P.R. Brown and E.
Grushka, Marcel Dekker, New York, NY, 1995, p. 343-381.

[22]

S. Ahuja, Selectivity and Detectability Optimizations in HPLC, John Wiley and
Sons, New York, NY, 1989.

[23]

L.R. Snyder, J.W. Dolan, Advances in Chromatography, Ed. By P.R. Brown and
E. Grushka, Marcel Dekker, New York, NY, 1998, p. 115-187.

[24]

S.L. Meyer, Data Analysis for Scientists and Engineers, John Wiley and Sons,
New York, NY, 1975, p. 28.

[25]

D.E. Kile, C.T. Chiou, H. Zhou, H. Li, O. Xu, Environ. Sci. Technol. 29 (1995)
1401-1406.

[26]

K. Heinig, C. Vogt, Electrophoresis 290 (1999) 3311-3328.

[27]

J.A. Field, M. Schultz, D. Barofsky, Chimia 57 (2003) 556-560.

[28]

M.N. Khan, U. Zareen, J. Hazard. Mater. 133 (2006) 269-275.

[29]

S. Martinez-Barrachina, J. Alonso, L. Matia, R. Prats, M. del Valle, Anal. Chem.
71 (1999) 3684-3691.

[30]

United States Environmental Protection Agency, Pollution Prevention and Toxics
(7407), EPA-749-F-95-002a, 1994.

[31]

Allied Chemical Corporation, National Aniline Division, Aniline, Allied
Chemical Corporation, New York, NY, 1964.

[32]

T.V Kashik, B.V. Prokop’ev, G.V. Rassolova, S.M. Ponomareva, Russ. Chem.
B+ 20 (1971) 1847-1850.

[33]

H.C. Brown, D.H. McDaniel, O. Häfliger, Ed. By E.A. Braude, F.C. Nachod,
Determination of Organic Structures by Physical Methods, Academic Press, New
York, 1955.

146

CHAPTER 6: USE OF SYSTEM PEAKS FOR THE DETERMINATION OF THE
RETENTION OF FLUORINATED AND HYDROCARBON SURFACTANTS IN
THE EXPERIMENTAL SYSTEM
6.1 Introduction

As described in Chapter 5, amine mixtures were analyzed in a pure water mobile
phase (Figures 6.1A-C) and in methanol/aqueous surfactant mobile phases (of various
compositions). During the course of these experiments, several extra peaks were
observed in the chromatograms of the surfactant mobile phases (Figures 6.2A-B), which
were not associated with any of the amine analytes. These peaks, which are classified as
system peaks, are related to the components of the mobile phase and were not observed in
the pure water mobile phase chromatograms (Figures 6.1A-C). System peaks can occur
in a chromatographic system when 1) the mobile phase contains more than one
component [1], 2) the component is distributed between the mobile phase and the
stationary phase [2], and 3) the injection sample has a slightly different composition than
the mobile phase. System peaks can be observed providing the detector in use is
sensitive to those components. These peaks are often regarded as annoyances, and
chromatographers try to eliminate them from chromatograms. Several studies have been
conducted on various aspects of system peaks, such as their origin, formation, and
importance in chromatographic techniques [1,3-4], their relationship to adsorption
isotherms in the column [5], and their use for indirect detection [6] and quantitative
analysis [7]. System peaks are relaxation products after the column equilibrium has been
perturbed via an injection sample plug [1]. As such, system peaks are believed to provide
information about the interactions within the chromatographic system.

147

Figures 6.1A-C:

Representative chromatograms of amines in water mobile phase.
−1

Mobile phase: 10.0 mM β-alanine aqueous mobile phase. Flowrate: 0.5 mL min .
Analytes: (0) lithium nitrate, (1) 4-aminopyridine, (2) pyridine, (3) aniline, (4)
benzylamine, (5) p-toluidine, (6) N-methylaniline, (7) m-toluidine, (8) o-toluidine, (9)
N,N-dimethylaniline, (10) N-ethylaniline, (11) N,N-diethylaniline. Other experimental
conditions as given in the text.

148

Figure 6.1A

0

4

5
6

0

9

5

10
Time (min)

149

15

20

Figure 6.1B
0

1

3

0

8

5

10
Time (min)

150

15

20

Figure 6.1C
0

7
10
2
11

0

5

10
Time (min)

151

15

20

Figures 6.2A-B:

Representative chromatograms of amines in surfactant mobile

phases. (A) Mobile phase: 45:55 methanol/2.0 mM aqueous sodium dodecyl sulfate
−1

(SDS). Flowrate: 1.0 mL min . (B) Mobile phase: 45:55 methanol/2.0 mM aqueous
−1

lithium perfluorooctane sulfonate (LiPFOS). Flowrate: 0.3 mL min . Analytes: (0)
lithium nitrate, (4) benzylamine, (5) p-toluidine, (6) N-methylaniline, (∗) unidentified
system peak. Other experimental conditions as given in the text.

152

Figure 6.2A
4
5

0

6
*
*

*

0

2

4

6
Time (min)

153

8

10

12

Figure 6.2B
4
5

0
6
*

*

0

5

10

15
Time (min)

154

20

25

As described in Chapter 2 (Section 2.2.4), refractive index measurements were
unsuccessful in determining the retention of the surfactants in the experimental system. It
was therefore surmised that if the system peaks were related to the surfactants, then they
could be used to determine surfactant retention within the chromatographic system.
Thus, the main goal of this experiment was to determine the retention of the surfactants
within the experimental chromatographic system based on the retention and identification
of the system peaks. These retention values can be used to elucidate information about
the environmental transport of the surfactants themselves through a groundwater system,
which can have an impact on the transport of co-contaminants.
6.2 Experimental Methods
6.2.1

Mobile Phase and Analytes

The mobile phases and amine mixtures were the same as used in Chapter 5, and
the preparation of which was previously described in Section 5.2.1.
6.2.2

Experimental System

The analytical column, liquid chromatography system, and detection system were
the same as used in Chapter 5. All details are the same as described in Section 5.2.2,
including the UV absorbance wavelength of detection (205 nm). All experiments were
carried out at ambient temperature with a maximum pressure limit of 4500 psi. The flow
−1

during the sodium dodecyl sulfate (SDS) experiments and varied

−1

and 0.3 mL min

rate was 1.0 mL min

between 1.0 mL min

−1

during the lithium perfluorooctane sulfonate

(LiPFOS) experiments.

155

6.2.3

Data Analysis and Calculations

6.2.3.1 Retention Factor Measurements

As stated in previous chapters, reversed-phase liquid chromatography (RPLC) is
used to model an environmental system in which the octadecylsilica stationary phase
represents soil and the aqueous mobile phase represents groundwater. When a surfactant
is added to the RPLC system below its critical micelle concentration (CMC), the
surfactant monomers distribute or partition between the mobile and stationary phases.
When the surfactant mobile phase in the column is allowed to reach equilibrium, this
equilibrium is maintained as long as the chromatographic system is not disturbed, either
by 1) changing the mobile phase or 2) injection of a sample plug.
The equilibrium constant, K, is directly related to the ratio of the surfactant
monomer concentrations in the stationary and mobile phases. This equilibrium constant
represents all interactions between the surfactant monomers, stationary phase, and mobile
phase. The equilibrium constant is a vital piece of information needed to model
environmental systems. However, the determination of this equilibrium constant is
difficult because of the inability to directly measure the concentrations of the surfactant
monomers in the environmental mobile and stationary phases.
The retention factor, k, is defined as
(6.1)

k = Kφ

where φ is the phase ratio. Assuming that the phase ratio is constant, the value for k is
proportional to K. Consequently, the retention factor of the system peak can be used to
elucidate information about the interactions of the surfactants in the experimental
chromatographic system.

156

When a pure solvent is injected, the sample at the column head is relatively
devoid of the other mobile phase components. This causes a perturbation of the column
equilibrium, which the system tries to reestablish. Consequently, any mobile phase
component adsorbed on the stationary phase surface is extracted into the injected volume
[5]. The reestablishment of the column equilibrium results in the appearance of system
peaks corresponding to each component. In order to identify which system peak is
attributed to the surfactants in the experiment system, injections of pure methanol and the
mobile phase were performed. Representative chromatograms of injections of pure
methanol are located in Figures 6.3A and B for SDS and LiPFOS, respectively. For the
methanol injections, the retention factor, k, was calculated by
t
k= R

−

t0

(6.2)

t0

where the void time, t0, was taken as the first positive deviation from the baseline arising
from methanol, and the retention time, tR, for the system peaks was determined from the
negative peak minimum, which is appropriate for the peaks observed in this study. The k
values were used for the subsequent elucidation of surfactant retention.

157

Figures 6.3A-B:

Representative chromatograms of pure methanol in surfactant

mobile phases. (A) Mobile phase: 45:55 methanol/2.0 mM aqueous SDS. (B) Mobile
−1

phase: 45:55 methanol/2.0 mM aqueous LiPFOS. Flowrate: 1.0 mL min . Analytes:
(0) methanol, (∗) unidentified system peak, (∗S) SDS system peak, (∗L) LiPFOS system
peak. Other experimental conditions as given in the text.

158

Figure 6.3A

0

*
*

*

*S

0

2

4
Time (min)

159

6

8

Figure 6.3B
0

*

*
*

*L

0

2

4
Time (min)

160

6

8

6.2.3.2 Linear Solvent Strength Model

Because the determination of surfactant retention factors in solvent A (e.g.
aqueous surfactant solution) is impractical due to excessive retention, a stronger organic
co-solvent B (e.g. methanol) was added to the mobile phase to decrease retention. The
linear solvent strength (LSS) model relates the surfactant retention as a function of the
percent composition of the organic solvent (% B) in the mixed mobile phase [8], via the
following equation
log k = − S(%B) + log k 0

(6.3)

where S is the slope and k0 is the surfactant retention factor in pure solvent A (i.e. % B =
0). Linear regression is performed on the logarithmic k values measured at various % B.
The k0 value of the analyte at a given surfactant concentration is determined from the
logarithmic y-intercept value.
6.3 Results and Discussion

The rationale behind the choice of stationary phase, surfactants, and analytes has
been discussed in Chapters 2 and 5. In order to identify the system peaks, injections of
surfactant mobile phases and pure methanol were performed, and the chromatograms
collected concurrently with the amine analyte mixtures from Chapter 5.
6.3.1

System Peaks

System peaks can be characterized by having constant k values (irrespective of
the sample injected), positive or negative peaks (relative to the detector base line), and
peak areas that depend on the nature of the injected solutes [1]. In order to utilize this
information, several injections and observations were made in both the SDS and LiPFOS
mobile phases.

161

6.3.2

System Peaks in Sodium Dodecyl Sulfate Mobile Phases

As described in Section 6.1, several peaks were observed in the chromatograms
that were not associated with any amine analytes. Representative chromatograms of
amines in SDS mobile phases are shown in Figures 6.4A-C. It was observed that the
retention times of several of the unidentified peaks did not change, regardless of the
analyte mixture injected. This phenomenon is a characteristic of system peaks.
Injections of pure solvents (methanol and mobile phase) were performed in an effort to
correctly identify the system peak due to SDS.
Representative chromatograms of pure methanol in SDS mobile phases are shown
in Figures 6.5A-D, and of the mobile phase in SDS mobile phases are shown in Figure
6.6. In comparing the chromatograms of Figures 6.4, 6.5, and 6.6, the large negative
system peak, which is present in the chromatograms arising from the injections of amines
and pure methanol, is absent in the chromatograms arising from the injections of the SDS
mobile phase itself. In addition, as the concentration of SDS in the mobile phase
increases, the peak area of the negative peak changes. Based on these observations, the
negative system peak is attributed to the SDS component of the mobile phase.

162

Figures 6.4A-C:

Representative chromatograms of amines in SDS mobile phases.
−1

Mobile phase: 45:55 methanol/2.0 mM aqueous SDS. Flowrate: 1.0 mL min .
Analytes: (0) lithium nitrate, (1) 4-aminopyridine, (2) pyridine, (3) aniline, (4)
benzylamine, (5) p-toluidine, (6) N-methylaniline, (7) m-toluidine, (8) o-toluidine, (9)
N,N-dimethylaniline, (∗) unidentified system peak. Other experimental conditions as
given in the text.

163

Figure 6.4A
4
5

0

6
*
*

*

0

2

4

6
Time (min)

164

8

10

12

Figure 6.4B
1

8

3

0

*

*
*

0

2

4

6
Time (min)

165

8

10

12

Figure 6.4C

9

7

0

2
*
*
*

0

2

4

6
Time (min)

166

8

10

12

Figures 6.5A-D:

Representative chromatograms of pure methanol in SDS mobile

phases. Mobile phase: 45:55 methanol/aqueous SDS. (A) 1.0 mM SDS, (B) 2.0 mM
−1

SDS, (C) 3.0 mM SDS, (D) 4.0 mM SDS. Flowrate: 1.0 mL min . Analytes: (0)
methanol, (∗) unidentified system peak, (∗S) SDS system peak. Other experimental
conditions as given in the text.

167

Figure 6.5A
0

*
*

*S

0

2

4
Time (min)

168

6

8

Figure 6.5B

0

*
*

*

*S

0

2

4
Time (min)

169

6

8

Figure 6.5C
0

*

*

*

*S

0

2

4
Time (min)

170

6

8

Figure 6.5D
0

*
*
*
*S

0

2

4
Time (min)

171

6

8

Figure 6.6:

Representative chromatogram of mobile phase in SDS mobile phases.
−1

Mobile phase: 45:55 methanol/2.0 mM aqueous SDS. Flowrate: 1.0 mL min .
Analytes: (∗) unidentified system peak. Other experimental conditions as given in the
text.

172

Figure 6.6

* *

0

2

4

6
Time (min)

173

8

10

Retention factors, k, of the SDS system peaks were determined in varying mobile phase
compositions of aqueous SDS (1.0 – 4.0 mM) and methanol (20 – 50 % v/v), during
injections of pure methanol. A graph of the retention factor for the SDS system peak
versus the methanol composition (% B) of the mobile phase is shown in Figure 6.7.
Statistical treatment of these data via linear regression demonstrated a linear relationship
2

between log k and % B, where the square of the correlation coefficient, R , values were
all greater than 0.892, except for the 4.0 mM SDS concentration (0.655). It was observed
that the logarithmic retention factor of the SDS system peak decreased with increasing
methanol composition, which is consistent with predictions of the LSS method. In
addition, the retention factor of the SDS system peak decreased with increasing surfactant
concentration in the mobile phase, at each methanol composition.
The retention factor of the SDS system peak in an aqueous surfactant mobile
phase (k0) was determined by extrapolation at each SDS concentration using linear
regression of Equation 6.3. A graph of the extrapolated retention factor for the SDS
system peak versus the concentration of SDS is shown in Figure 6.8, where the error bars
represent the standard deviation (±) of the individual extrapolated retention factors.
There is a significant decrease in the SDS system peak retention from 1.0 to 2.0 mM
SDS; however retention remains relatively constant from 2.0 to 4.0 mM SDS. The higher
extrapolated retention factor at 1.0 mM SDS (32) than for 2.0 – 4.0 mM SDS (all below
10), suggests that the SDS surfactant monomers have saturated the stationary phase at a
surfactant concentration of 2.0 mM and above. It has been shown in literature that
parameters, such as retention factor and loading factor, are concentration dependent and
will decrease with increasing concentration [9].

174

Figure 6.7:

Graph of retention factor for SDS system peaks versus methanol

composition (%) in: (♦) 1.0 mM SDS, (■) 2.0 mM SDS, (▲) 3.0 mM SDS, (x) 4.0 mM
SDS. Other experimental conditions as given in the text.

175

Figure 6.7

Retention Factor

10

1

0.1
0

10

20

30
Methanol Composition (%)

176

40

50

60

Figure 6.8:

Graph of extrapolated retention factor for SDS system peaks versus the

concentration of SDS. Other experimental conditions as given in the text.

177

Figure 6.8
45
40
35

Retention Factor

30
25
20
15
10
5
0
0

0.5

1

1.5

2

2.5

Concentration of SDS (mM)

178

3

3.5

4

4.5

The phenomenon seen in this experiment suggests a simple Langmuir isotherm for the
chromatographic system with SDS, as the retention of SDS in the system decreases with
an increase in the concentration of SDS (in the mobile phase) from 1.0 to 2.0 mM, and
remains constant thereafter.
6.3.3

System Peaks in Lithium Perfluorooctane Sulfonate Mobile Phases

Representative chromatograms of the amines in LiPFOS mobile phases are shown
in Figures 6.9A-C. Similar to SDS, it was observed that the retention times of several of
the unidentified peaks did not change, regardless of the analyte mixture injected.
However, not all of the same peaks were observed in the LiPFOS mobile phases that
were seen in the SDS mobile phases, or observed at the same relative position. Injections
of pure solvents (methanol and mobile phase) were performed in an effort to correctly
identify the system peak due to LiPFOS.
Representative chromatograms of the pure methanol in LiPFOS mobile phases are
shown in Figures 6.10A-D, and of the mobile phase in LiPFOS mobile phases are shown
in Figure 6.11. In comparing the chromatograms of Figures 6.9, 6.10, and 6.11, the large
negative system peak, which is present in the chromatograms arising from the injections
of pure methanol, is absent in the chromatograms arising from the injections of the
LiPFOS mobile phase itself. Similar to SDS, as the concentration of LiPFOS in the
mobile phase increases, the peak area of the negative peak changes. In comparing the
shape of the negative system peak in LiPFOS to SDS, it is seen that the peak has less of a
triangular shape, thus leading to a less pronounced peak minimum.

179

Figures 6.9A-C:

Representative chromatograms of amine injections in LiPFOS

mobile phases. Mobile phase: 45:55 methanol/2.0 mM aqueous LiPFOS. Flowrate: 0.3
−1

mL min . Analytes: (0) lithium nitrate, (1) 4-aminopyridine, (2) pyridine, (3) aniline,
(4) benzylamine, (5) p-toluidine, (6) N-methylaniline, (7) m-toluidine, (8) o-toluidine, (9)
N,N-dimethylaniline, (∗) unidentified system peak. Other experimental conditions as
given in the text.

180

Figure 6.9A
4
5

0
6
*

*

0

5

10

15
Time (min)

181

20

25

Figure 6.9B
8

1

3
0

*

*

*

0

5

10

15
Time (min)

182

20

25

Figure 6.9C
9

7

0
2
*

*

*

*

*

0

5

10

15
Time (min)

183

20

25

Figures 6.10A-D:

Representative chromatograms of pure methanol injections in

LiPFOS mobile phases. Mobile phase: 45:55 methanol/aqueous LiPFOS. (A) 1.0 mM
LiPFOS, (B) 2.0 mM LiPFOS, (C) 3.0 mM LiPFOS, (D) 4.0 mM LiPFOS. Flowrate:
−1

1.0 mL min . Analytes: (0) methanol, (∗) unidentified system peak, (∗L) LiPFOS
system peak. Other experimental conditions as given in the text.

184

Figure 6.10A
0

*
*

*
*L

0

2

4
Time (min)

185

6

8

Figure 6.10B
0

*

*
*

*L

0

2

4
Time (min)

186

6

8

Figure 6.10C

0

*

*
*

*L

0

2

4
Time (min)

187

6

8

Figure 6.10D

0

*

*
*

*L

0

2

4
Time (min)

188

6

8

Figure 6.11: Representative chromatogram of mobile phase injection in LiPFOS mobile

phases. Mobile phase: 45:55 methanol/2.0 mM aqueous LiPFOS. Flowrate: 0.3 mL
−1

min . Analytes: (∗) unidentified system peak. Other experimental conditions as given
in the text.

189

Figure 6.11

**

0

5

10

15
Time (min)

190

20

25

The triangular peak shape for SDS is typical for a simple Langmuir isotherm, while the
strange peak shape for LiPFOS suggests that a simple isotherm is not taking place, but
the possible formation of dimers and trimers. The lack of a simple isotherm is consistent
with conductivity measurements (Section 2.3). Based on these observations, the negative
system peak is attributed to the LiPFOS component of the mobile phase.
Retention factors, k, of the LiPFOS system peaks were determined in varying
mobile phase compositions of aqueous LiPFOS (1.0 – 4.0 mM) and methanol (25 – 55 %
v/v), during injections of pure methanol. A graph of the retention factor for the LiPFOS
system peak versus the methanol composition (% B) of the mobile phase is shown in
Figure 6.12. Statistical treatment of these data via linear regression demonstrated a linear
2

relationship between log k and % B, where the square of the correlation coefficient, R ,
values were all greater than 0.918. It was observed that the logarithmic retention factor
of the LiPFOS system peak decreased with increasing methanol composition, which is
consistent with predictions of the LSS method. In addition, the retention factor of the
LiPFOS system peak decreased with increasing surfactant concentration in the mobile
phase, at each methanol composition. It is noteworthy to mention that at the higher
compositions of methanol the LiPFOS system peak retention factors begin to converge to
values <1.0 for all surfactant concentrations in the mobile phase.

191

Figure 6.12: Graph of retention factor versus methanol composition (%) in: (♦) 1.0

mM LiPFOS, (■) 2.0 mM LiPFOS, (▲) 3.0 mM LiPFOS, (x) 4.0 mM LiPFOS. Other
experimental conditions as given in the text.

192

Figure 6.12

Retention Factor

10

1

0.1
0

10

20

30
Methanol Composition (%)

193

40

50

60

The retention factor of the LiPFOS system peak in an aqueous surfactant mobile
phase (k0) was determined by extrapolation at each LiPFOS concentration using linear
regression of Equation 6.3. A graph of the extrapolated retention factor for the LiPFOS
system peak versus the concentration of LiPFOS is shown in Figure 6.13, where the error
bars represent the standard deviation (±) of the individual extrapolated retention factor.
There appears to be a decrease in the LiPFOS system peak retention from 1.0 to 4.0 mM
LiPFOS. However, upon taking the standard deviations into consideration, the retention
remains relatively constant from 1.0 to 3.0 mM LiPFOS. This variability in the data
suggests that the LiPFOS surfactant is experiencing slightly different interactions in the
experimental chromatographic system, such as the possible formation of dimers and
trimers. In comparing the extrapolated retention factors of LiPFOS (Figure 6.13) to SDS
(Figure 6.8), it is observed that the retention factors are the same at 1.0 mM surfactant
concentration but lower in SDS than in LiPFOS at the higher surfactant concentrations
(2.0 – 4.0 mM).

194

Figure 6.13: Graph of extrapolated retention factor for LiPFOS system peaks versus the

concentration of LiPFOS. Other experimental conditions as given in the text.

195

Figure 6.13
60

50

Retention Factor

40

30

20

10

0
0

0.5

1

1.5

2

2.5

Concentration of LiPFOS (mM)

196

3

3.5

4

4.5

6.4 Summary

During this study, the retention of anionic hydrocarbon and perfluorinated
surfactants (SDS and LiPFOS) within the experimental chromatographic system was
determined based on the identification and retention factors of system peaks. From
injections of pure methanol and the mobile phase, the system peak attributed to each
surfactant could be identified. The overall trend was that the retention factors of both
surfactant system peaks decreased as the concentration of the surfactant in the mobile
phase increased, below the CMC. It is noteworthy that the perfluorinated surfactant is
less retained in the experimental chromatographic system than the hydrocarbon
surfactant. Furthermore, an increase in surfactant concentration below the CMC resulted
in a decrease in the retention of the surfactants (extrapolated to pure water), within the
concentration range tested in this study. However, there was more variability in the
perfluorinated surfactant data than the hydrocarbon surfactant data, a similar occurrence
that was seen in the results of Chapter 5.
These results and conclusions have important implications for the study of the
transport effects of perfluorinated surfactants on co-contaminants. In particular, the
perfluorinated surfactant exhibited decreased interaction within the experimental
chromatographic system, as compared to the hydrocarbon surfactant. In addition, a
difference in isotherms between the perfluorinated and hydrocarbon surfactant systems
was observed. Further studies are needed to characterize the retention of the surfactants
within the experimental system. The use of current analytical detection techniques, such
as mass spectrometry, coupled with liquid chromatography might lead to a better
understanding of the interactions of the surfactants within the experimental system.

197

REFERENCES

198

6.5 References

[1]

S. Levin, E. Grushka, Anal. Chem. 58 (1986) 1602-1607.

[2]

S. Levin, E. Grushka, Anal. Chem. 61 (1989) 2428-2433.

[3]

J. Srbek, P. Coufal, Z. Bosakova, E. Tesarova, J. Separation Sci. 28 (2005) 12631270.

[4]

K. Kalikova, V. Hruska, J. Svobodova, R. Chudoba, B. Gas, E. Tesarova, J.
Separation Sci. 32 (2009) 2864-2870.

[5]

S. Levin, E. Grushka, Anal. Chem. 59 (1987) 1157-1164.

[6]

J.Stahlberg, M. Almgren, Anal. Chem. 61 (1989) 1109-1112.

[7]

N.Mizrotsky, L. Kristol, E. Grushka, J. Chromatogr. A. 691 (1995) 21-27.

[8]

L.R. Snyder, J.W. Dolan, Advances in Chromatography, Ed. By P.R. Brown and
E. Grushka, Marcel Dekker, New York, NY, 1998, p. 115-187.

[9]

S. Golshan-Shirazi, G. Guiochon, J. Chromatogr. 603 (1992) 1-11.

199

CHAPTER 7: DETERMINATION OF FLUORINATED SURFACTANTS IN
WASTEWATER SAMPLES BY HIGH-PERFORMANCE LIQUID
CHROMATOGRAPHY WITH TANDEM MASS SPECTROMETRY
7.1 Introduction

Fluorinated organic compounds (FOCs) have been used as aerosol propellants,
refrigerants, adhesives, surfactants, fire retardants, plastics, herbicides, pesticides, plant
growth regulators, anesthetics, medicines, and even as blood substitutes [1-2]. A major
class of FOCs is the perfluorinated compounds (PFCs), with more and more reports of
the concentrations of the primary PFCs appearing in literature [3]. Due to the ubiquitous
nature of some PFCs, it becomes necessary to have a reliable methodology for their
detection and quantation in environmental samples. The acquisition of reliable
concentration data can prove useful in understanding the transport and fate of PFCs.
During the term of the 2006 East Asia and Pacific Summer Institutes (EAPSI)
program, the author received training on a specially modified high-performance liquid
chromatography with tandem mass spectrometry (LC-MS/MS) system at the National
Institute of Advanced Industrial Science and Technology (AIST) in Tsukuba, Japan. The
LC-MS/MS system permits detection and quantitation of fluorinated surfactants down to
the part-per-quadrillion level. Water samples, which were previously collected from the
treatment tanks at an industrial manufacturing site and from the effluent in a nearby
stream, were analyzed. The levels of 28 anionic fluorinated surfactants were quantitated
in samples that had been collected, before and during a production cycle, over a period of
four days.

200

7.2 Experimental Methods
7.2.1

Fluorinated Surfactants

Some of the most commercially utilized PFCs are the classes of fluorinated
surfactant, in particular the anionic perfluorinated surfactants [4-5]. In addition, some
perfluorinated surfactants are byproducts in fluorinated telomer alcohols and carboxylic
acids (fluorotelomers) production [6], with some fluorotelomers believed to
environmentally degrade into perfluorinated surfactants [7-9]. For these reasons, pure
analytical standards of these classes of compounds are necessary for any detection
method.
Mixtures of 28 anionic fluorinated surfactant standards, which were supplied by
the Yamashita research group at AIST, were used as external standards (for construction
of calibration curves) and internal standards (for spiking of recovery samples). A
summary of the names, abbreviations, and structures for each fluorinated surfactant is
located in Table 7.1.

201

Table 7.1: Summary of names, abbreviations, and structures for the perfluorinated
compounds (PFCs).
Name
Abbreviation
Structure
Perfluoroalkyl sulfonates (PFAS):
Perfluoroethane sulfonic acid
PFEtS
F(CF2)2SO3¯
Perfluoropropane sulfonic acid
PFPrS
F(CF2)3SO3¯
Perfluorobutane sulfonic acid
PFBS
F(CF2)4SO3¯
Perfluorohexane sulfonic acid
PFHxS
F(CF2)6SO3¯
Perfluorooctane sulfonic acid
PFOS
F(CF2)8SO3¯
1H,1H,2H,2H-perfluorooctane
THPFOS
F(CF2)6(CH2)2SO3¯
sulfonic acid
Perfluoroalkyl carboxylic acids (PFCA):

Perfluorobutyric acid

PFBA

Perfluoropentanoic acid

PFPeA

F(CF2)3COO¯
F(CF2)4COO¯

Perfluorohexanoic acid

PFHxA

F(CF2)5COO¯

Perfluoroheptanoic acid

PFHpA

F(CF2)6COO¯

Perfluorooctanoic acid

PFOA

F(CF2)7COO¯

Perfluorononanoic acid

PFNA

F(CF2)8COO¯

Perfluorodecanoic acid

PFDA

F(CF2)9COO¯

Perfluoroundecanoic acid

PFUnDA

F(CF2)10COO¯

Perfluorododecanoic acid

PFDoDA

F(CF2)11COO¯

Perfluorotetradecanoic acid

PFTeDA

F(CF2)13COO¯

F(CF2)15COO¯
Perfluorohexadecanoic acid
PFHxDA
Perfluorooctadecanoic acid
PFODA
F(CF2)17COO¯
13
13
13
13
C labeled Perfluorooctanoic acid
C-PFOA
F(CF2)8 CF2 COO¯
Fluorinated telomer alcohols and carboxylic acids (FTOH and FTCA):
1H,1H,2H,2H-perfluoro-1-decanol
8:2 FTOH
F(CF2)8(CH2)2O¯
1H,1H,2H,2H-perfluoro-1-dodecanol
10:2 FTOH
F(CF2)10(CH2)2O¯
1H,1H-perfluoro-1-octanol
7:1 FTOH
F(CF2)7CH2O¯
1H,1H-perfluoro-1-undecanol
10:1 FTOH
F(CF2)10CH2O¯
8:2 fluorotelomer acid
8:2 FTCA
F(CF2)8CH2COO¯
8:2 fluorotelomer unsaturated acid
8:2 FTUCA
F(CF2)7CF=CHCOO¯
Fluorooctane sulfonamides (FOSA):
Perfluorooctane sulfonamide
PFOSA
F(CF2)8SO2NH¯
N-ethylperfluorooctane
N-EtFOSAA F(CF2)8SO2N(C2H5)CH2COO¯
sulfonamidoacetate
N-ethylperfluorooctane sulfonamide
N-EtFOSA
F(CF2)8SO2N(C2H5)¯

202

7.2.2

Wastewater Samples

The Yamashita research group at AIST provided representative waste water
samples for this study. The waste water samples had been previously collected from a
perfluorooctane sulfonate (PFOS) manufacturing plant in Japan, prior to the arrival of the
author. Multiple samples were taken from inside two waste water treatment tanks (sites
A0 – A3 and B0 – B3), as well as one location from a stream adjacent to the facility (sites
G1 – G2) into which the waste water was discharged. Due to the hydrophobic and
hydrophilic nature of surfactants, a higher concentration of surfactants is expected at the
water/air interface [10]. Based on this information, waste water samples were taken at
depths between 0.0 – 50.0 cm from the surface. Samples were collected one day prior to
production (J23) and three subsequent days (J24 – J26) during production of PFOS. The
waste water samples were stored in 1.0 L polypropylene containers with screw tops, and
were kept in a refrigerator at a temperature of 4 ± 2 °C before extraction.
7.2.3

Sample Extraction and Preparation

For the purpose of this study, the waste water samples were separated into smaller
aliquots for extraction. The stored 1.0 L samples were allowed to equilibrate to room
temperature and mixed by inversion, to insure accurate sampling. After inversion, two
100 mL aliquots of stored waste water samples (for sites B0 – B3 and G1 – G2) were
placed into two clean polypropylene containers with screw tops. After inversion, two 1.0
mL aliquots of A0 – A3 samples were placed into two clean polypropylene containers
with screw tops, and diluted to 50 mL with methanol. The water samples were kept
refrigerated over the course of the study.

203

All water samples were extracted utilizing the standard methods of the Yamashita
group [11]. Prior to extraction, the water samples were allowed to equilibrate to room
temperature and mixed within the bottles by inversion. Next, the samples were treated by
®

solid-phase extraction using weak anion-exchange cartridges (Waters Oasis WAX) in
order to isolate any extractable anionic fluorinated surfactants. Prior to loading a water
sample, the cartridge was preconditioned by washing with 4.0 mL of 0.1 % NH4OH in
−1

methanol, 4.0 mL methanol, and 4.0 mL of Milli-Q water at a rate of 2 drops s . The
waste water sample (50 – 100 mL) was then loaded onto the cartridge at a rate of 1 drop
−1

s . The cartridge was prevented from drying out during the preconditioning and water
loading phases. After the water loading, the cartridge was subsequently washed with 4.0
mL of 25 mM acetate buffer (pH 4.0) and then dried via a vacuum pump. To elute the
target fraction, the cartridge was eluted first with 4.0 mL methanol and then with 4.0 mL
−1

of 0.1 % NH4OH in methanol at a rate of 1 drop s , and the target fraction was collected
in a 10.0 mL graduated polypropylene vial. The column was eluted a second time with
4.0 mL of 0.1 % NH4OH in methanol and the eluant was collected in a separate
polypropylene vial; to ensured the elution of all target compounds. Diluted extract
samples were prepared by taking 0.1 mL of the extracted fractions and diluting to 10.0
mL with methanol in a graduated polypropylene vial. The extracted fractions and diluted
extract samples were kept refrigerated at 4 ± 2 °C until they could be analyzed. Prior to
analysis, 100 µL aliquots of the extracted samples were transferred to polypropylene LC
autosampler vials.

204

7.2.4

Experimental System

The water samples were analyzed using high-performance liquid chromatography
with tandem mass spectrometry (LC-MS/MS). The LC-MS/MS system used in this study
was specially modified to replace all components that could potentially introduce
interferences (e.g. fluorinated polymers, Teflon tubing, etc.), thereby permitting reliable
detection of PFCs down to the picogram (pg) level [12]. Samples (10 µL) were injected,
via an autosampler, into the liquid chromatography system (Agilent, Model HP1100) and
onto a Keystone Betasil C18 reversed-phase octadecylsilica column (2.1 mm i.d. x 50 mm
length, 5.0 µm particle size). The mobile phase consisted of a 2.0 mM aqueous
−1

ammonium acetate buffer with a 10 – 100% methanol gradient at 300 µL min . The LC
effluent was directed via an electrospray interface to a Micromass Quattro II tandem
mass spectrometer (Waters). The MS/MS system was operated in the negative ion mode
with fixed MS/MS transitions to detect the individual PFCs.
Five functions were used for the detection of the characteristic MS/MS transitions
for the individual PFCs, which had been previously utilized by the Yamashita research
group at AIST. The total ion chromatogram (TIC) for each function, during a PFC
standard mixture injection, is shown in Figure 7.1. The TIC for each function is
comprised of chromatograms for multiple MS/MS transitions. For brevity, only the
individual chromatograms for the PFCs detected within function #3 are shown in Figure
7.2.

205

Figure 7.1: Total ion chromatogram (TIC) for the five detection functions during a PFC

standard mixture injection. Detection functions: #1 (A), #2 (B), #3 (C), #4 (D), #5 (E).
For interpretation of the references to color in this and all other figures, the reader is
referred to the electronic version of this dissertation.

206

Figure 7.1
E

D

PFOA

C

PFOS

B
PFBA
A
2.00

4.00

6.00

8.00

10.00

12.00

Time (min)

207

14.00

16.00

18.00

20.00

Figure 7.2
H
G
F
E
D
C
B
A
8.00

9.00 10.00 11.00 12.00 13.00 14.00
Time (min)

Figure 7.2: Individual chromatograms of the characteristic MS/MS transitions detected
by function #3, during a PFC standard mixture injection. Chromatograms: TIC of
13
function #3 (A), PFHpA (B), PFHxS (C), PFOA (D), C-PFOA (E), THPFOS (F),
PFNA (G), PFOS (H).

208

7.2.5

Data Analysis

In order to validate this method, procedural blanks (400 mL of Milli-Q water) and
procedural recovery samples (400 mL of Milli-Q water, spiked with 160 µL of a 50 ppb
PFC standard mixture) were extracted and analyzed concurrently with the waste water
samples. The data analysis for all blank, recovery, and waste water samples was
performed using the MassLynx software. Calibration curves for the PFCs where
assembled based on detector response (peak area) versus concentrations of external
standards. The external standards where injected at six different concentrations (2, 10,
−1

50, 200, 1000, 20000 ng L ). The concentrations of the target PFCs in all the water
samples were quantified via comparison to these external calibration curves.
7.3 Results and Discussion

Over the course of this study, 28 individual PFCs were identified and quantitated
in procedural blank, recovery, and waste water samples. Recoveries for these known
PFCs ranged from 81 – 117 % for perfluoroalkyl sulfonates, 75 – 133 % for
perfluoroalkyl carboxylic acids, and 64 – 112 % for fluorooctane sulfonamides and
alcohols. Concentrations of these known PFCs in the blank samples were below the limit
of quantification (LOQ), with the exception for perfluorobutyric acid (PFBA). The LOQ
was determined from the lowest standard concentration within ± 20 % relative standard
deviation from the calibration curve. Upon analysis of the waste water extracts, PFOS,
perfluorooctanoic acid (PFOA), and PFBA were the only PFCs detected at concentrations
above their LOQ on a consistent basis in the diluted samples. As such, only these three
PFCs are discussed in further detail in the following sections. A summary of

209

characteristic MS/MS transitions, LOQ, limit of detection (LOD), and slopes and R

2

values of the calibration curves for all the PFCs is located in Table 7.2.
7.3.1

Detection of Perfluorooctane Sulfonate

As stated in Section 7.2.5, the concentrations of the target PFCs in the water
samples were quantified based on comparison of peak areas to calibration curves
constructed from external standards. For brevity, the individual chromatograms of PFOS
from injections of water samples and a 1.0 ppb PFC standard mixture are shown in Figure
7.3. In comparing the chromatograms of water samples and PFC standard mixtures,
shifts in peak retention times of the target PFCs were observed. However, the general
peak shape was maintained. Base on these observations, the peak area for each target
PFC was determined based on peak shape and peak retention time. The calibration curve
and the residue graph (used to determine the LOQ) for PFOS are shown in Figure 7.4.
From Figure 7.4, a linear relationship between the peak area and concentration of PFOS
2

−1

is observed, where the R value is 0.9999 (Table 7.2). PFOS had a LOQ of 10 ng L

and % recovery of 103 ± 12 (where % recovery is an average of six recovery samples).
The PFOS concentration results, corrected for dilution factor, are summarized in Figure
−1

7.5. On the day prior to production (J23), concentrations ranged from 4.0 – 13 µg L
−1

the first treatment tank (A0 – A3), 65 – 265 ng L
−1

B3), and 205 – 250 ng L

in

in the second treatment tank (B0 –

in the adjacent stream (G1 – G2). On the first day of PFOS

production (J24), concentrations in the first treatment tank increased dramatically, as high
−1

as 520 µg L , but decreased on the second (J25) and third (J26) production days to 5.5 –
−1

41 µg L .

210

2

Table 7.2: Summary of calibration curve slope and R values, characteristic MS/MS
transitions, limit of quantification (LOQ), and limit of detection (LOD).
LOQ
LOD
Slope
2
PFCs
F#
Transition (m/z)
R
-1
-1
(intercept)
(ng L ) (ng L )
Perfluoroalkyl sulfonates (PFAS):

PFEtS
PFPrS
PFBS
PFHxS
PFOS
THPFOS

1
1
2
3
3
3

5.21 (33)
0.9997 198.80 → 79.80
8.41 (35)
0.9996 248.90 → 79.60
6.94 (0.0)
0.9979 298.70 → 79.70
6.94 (4.5)
0.9985 398.70 → 79.70
6.11 (0.0)
0.9999 498.60 → 79.70
8.35 (0.0)
0.9999 426.70 → 406.70
Perfluoroalkyl carboxylic acids (PFCA):

50
10
50
50
10
200

PFBA
1
20.2 (804)
0.9994 212.80 → 168.80
50
PFPeA
2
23.2 (-61)
0.9992 262.80 → 218.70
50
50
PFHxA
2
20.6 (0.0)
0.9975 312.80 → 268.80
PFHpA
3
25.7 (46)
0.9990 362.80 → 318.80
10
PFOA
3
30.0 (0.0)
0.9927 413.00 → 368.70
50
50
PFNA
3
17.3 (22)
0.9994 462.70 → 418.80
200
PFDA
4
15.0 (28)
0.9933 512.80 → 468.80
PFUnDA
4
19.8 (0.0)
0.9955 563.00 → 519.00
50
50
PFDoDA
4
17.7 (0.0)
0.9976 612.70 → 568.80
10
PFTeDA
5
16.1 (0.0)
0.9976 712.90 → 669.00
PFHxDA
5
9.17 (0.0)
0.9973 812.90 → 769.30
50
PFODA
5
9.01 (41)
0.9999 912.90 → 869.00
10
13
3
28.2 (0.0)
0.9990 414.90 → 369.90
10
C-PFOA
Fluorinated telomer alcohols and carboxylic acids (FTOH and FTCA):
8:2 FTOH
10:2 FTOH
7:1 FTOH
10:1 FTOH
8:2 FTCA
8:2 FTUCA

5
5
5
5
4
4

8
1
1
1
1
0.5
7
1
0.5
1
2
0.8
0.4
0.7
0.7
1
1
7
2

0.15 (11)
0.9936 463.00 → 354.80
0.09 (0.0)
0.9841 563.50 → 455.10
0.16 (19)
0.9569 398.90 → 218.90
1.64 (0.0)
0.9966 549.00 → 369.00
1.66 (0.0)
0.9762 477.00 → 393.00
41.9 (0.0)
0.9991 457.00 → 393.00
Fluorooctane sulfonamides (FOSA):

200
200
200
200
50
50

100
100
40
10
2
0.4

497.70 → 77.70
583.90 → 418.70
525.90 → 168.90

10
200
2

0.5
10
0.3

PFOSA
5
30.0 (0.0)
N-EtFOSAA
4
4.80 (0.0)
N-EtFOSA
5
30.9 (0.0)
F#... Detection function number.

0.9996
0.9993
0.9994

211

Figure 7.3

100
A

%
0
9.00

10.00

11.00

12.00

9.00

10.00

11.00

12.00

9.00

10.00

11.00

12.00

9.00

10.00

11.00

12.00

100
B

%
0
100

C

%
0
100

D

%
0

Time (min)

Figure 7.3: Individual chromatograms of PFOS from injections of PFC standard mixture
and water samples taken during the second day of PFOS production. Chromatograms:
1.0 ppb PFC standard mixture (A), water sample from adjacent stream site G (B), water
sample from second treatment tank B (C), water sample from first treatment tank A (D).

212

Figure 7.4
120
120

Residual

Residual

100
100
80
80
60
60
40
40
20
20

00

Conc

100000
100000
80000
80000

Response

Response (peak area)

120000
120000

60000
60000
40000
40000
20000
20000

00

Conc
0

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

2000 4000 6000 8000 10000 12000 14000 16000 18000
Concentration (ng L−1)

Figure 7.4: External calibration curve (bottom graph) and residue graph (top) for PFOS.

213

−1

Figure 7.5: Concentration (ng L ) of PFOS in two waste water treatment tanks (sites

A0 – A3 and B0 – B3), as well as in an adjacent stream into which the waste water was
discharged (sites G1 – G2). Samples were collected one day prior to production (J23■)
and three subsequent days during production of PFOS (J24■ – J25■ J26■).

214

Figure 7.5
1.00E+06

-1

Concentration (ng L )

1.00E+05

1.00E+04

Adjusted
LOQ
1000
−
ng L 1

1.00E+03

1.00E+02

1.00E+01

LOQ
10
−
ng L 1

1.00E+00
G1

G2

BO

B1

B2

B3

Sample Site

215

A0

A1

A2

A3

Concentrations in the second treatment tank also increased during production (in
comparison to J23), but remained relatively constant over all three production days (J24 –
−1

J26) at 6.7 – 42 µg L . The PFOS concentrations in the first treatment tank (A0 – A3),
on the second and third production days, were similar to that in the second treatment tank
(B0 – B3) over all three production days. Finally, in the adjacent stream into which the
effluent was discharged (G1 – G2), PFOS concentration levels generally increased from
−1

2.2 – 3.2 µg L

−1

on the first production day to 4.5 – 9.9 µg L

on the third production

day. The PFOS concentration levels in the stream were 10- to 50-fold higher during
−1

production (J24 – J26) than prior to production (J23, 205 – 250 ng L ). All
concentration levels, once corrected for dilution, were significantly larger than the LOQ,
−1

which was 10 ng L . An adjusted LOQ for PFOS was determined by multiplying the
LOQ by a factor of 100. Only the sites G1 –G2 and B0 – B3 on the day prior to PFOS
production, and the B0 site on the first day of production, had PFOS concentration levels
below this adjusted LOQ.
7.3.2

Detection of Perfluorooctanoic Acid

The calibration curve and the residue graph (used to determine the LOQ) for
PFOS are shown in Figure 7.6. From Figure 7.6, a linear relationship between the peak
2

area and concentration of PFOA is observed, where the R value is 0.9927 (Table 7.2).
−1

PFOA had a LOQ of 50 ng L

and % recovery of 108 ± 7 (where % recovery is an

average of six recovery samples).

216

Figure 7.6
100
100

Residual

Residual

80
80
60
60
40
40
20
20

00
Conc

500000
400000
400000
Response

Response (peak area)

-20
−20

300000
300000
200000
200000
100000
100000

00

Conc
0

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

2000 4000 6000 8000 10000 12000 14000 16000 18000
Concentration (ng L−1)

Figure 7.6: External calibration curve (bottom graph) and residue graph (top) for PFOA.

217

The PFOA concentration results, corrected for dilution factor, are summarized in
Figure 7.7. On the day prior to production (J23), concentrations ranged from 25 – 48 µg
−1

L

−1

in the first treatment tank (A0 – A3), 180 – 520 ng L
−1

(B0 – B3), and 345 – 600 ng L

in the second treatment tank

in the adjacent stream (G1 – G2). On the first day of

PFOS production (J24), the concentrations of PFOA in the first treatment tank increased
−1

dramatically, as high as 532 µg L , but decreased on the second (J25) and third (J26)
−1

production days to 27 – 57 µg L . Concentrations in the second treatment tank also
increased during production (in comparison to J23), but remained relatively constant over
−1

all three production days at 1.4 – 5.0 µg L . The PFOA concentrations in the first
treatment tank (A0 – A3) were consistently an order of magnitude higher than in the
second treatment tank (B0 – B3) over all three production days. Finally, in the adjacent
stream into which the effluent was discharged (G1 – G2), PFOA concentration levels
−1

remained relatively constant at 1.6 – 2.8 µg L

over all three production days. The

PFOA concentration levels in the stream were 2- to 5-fold higher during production (J24
−1

– J26) than prior to production (J23, 345 – 600 ng L ) in of PFOS. All concentration
levels, once corrected for dilution, were significantly larger than the LOQ, which was 50
−1

ng L . An adjusted LOQ for PFOA was determined by multiplying the LOQ by a factor
of 100. All sites had PFOA concentration levels below this adjusted LOQ, with the
exception of sites A0 – A3.

218

−1

Figure 7.7: Concentration (ng L ) of PFOA in two waste water treatment tanks (sites

A0 – A3 and B0 – B3), as well as in an adjacent stream into which the waste water was
discharged (sites G1 – G2). Samples were collected one day prior to production (J23■)
and three subsequent days during production of PFOA (J24■ – J25■ – J26■).

219

Figure 7.7
1.00E+06

-1

Concentration (ng L )

1.00E+05

1.00E+04

Adjusted
LOQ
5000
ng L−1

1.00E+03

1.00E+02
LOQ
50
ng L−1

1.00E+01

1.00E+00
G1

G2

BO

B1

B2

B3

Sample Site

220

A0

A1

A2

A3

7.3.3

Detection of Perfluorobutyric Acid

The calibration curve and the residue graph (used to determine the LOQ) for
PFBA are shown in Figure 7.8. From Figure 7.8, a linear relationship between the peak
2

area and concentration of PFOS is observed, where the R value is 0.9994 (Table 7.2).
−1

PFBA had a LOQ of 50 ng L

and % recovery of 122 ± 4 (where % recovery is an

average of six recovery samples).
The results for PFBA are not shown here. Generally, the PFBA concentrations in
−1

the waste water extracts were similar to those found in the blanks (5.3 – 13.4 µg L ). It
was therefore concluded that PFBA is a contaminant in the current procedure. Further
studies will be necessary to identify and eliminate the source of this contamination or, if
not possible, to provide statistically reliable quantitation of PFBA in the blank.

221

Figure 7.8
20.0
20

Residual

Residual

0.0
0

−-20.0
20
−-40.0
40
−-60.0
60
Conc

300000
300000
Response

Response (peak area)

400000

200000
200000

100000
100000

00

Conc
0

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

2000 4000 6000 8000 10000 12000 14000 16000 18000
Concentration (ng L−1)

Figure 7.8: External calibration curve (bottom graph) and residue graph (top) for PFBA.

222

7.4 Summary

During this study, a specially modified LC-MS/MS system was used to detect and
quantify the concentrations of known PFCs in water samples, which were sampled from
two treatment tanks of a perfluorinated surfactant manufacturer and an adjacent stream
into which the waste water was discharged into. Concentrations for most of the known
PFCs were consistently below the LOQ in the diluted extraction samples, with the
exception of PFOS, PFOA, and PFBA. Concentrations of PFOS and PFOA were
generally higher during the days of perfluorinated surfactant production than the day
prior to production. In the adjacent stream, PFOS and PFOA concentrations were also
higher during the days of perfluorinated surfactant production than the day prior to
production. However, the PFOS and PFOA concentrations in the stream were either less
than or equal to the concentrations in the second treatment tank.
Concentrations of PFBA in the water samples were detected at the same levels as
in the blank samples. This suggests that PFBA is currently a contaminant. As the use of
PFBA in industry increases, further work in identifying and eliminating PFBA
contamination in blank samples needs to be pursued, so that PBFA concentrations can be
reliably quantified in water samples. This technique is robust, reliable, and fast (with a
sample run time of 20 minutes). As more PFC standards are made available, this
technique will allow for the reliable quantation of PFCs in water samples, which can have
great impact on issues in regulating perfluorinated surfactants.

223

REFERENCES

224

7.5 References

[1]

B.D. Key, R.D. Howell, C.S. Criddle; Environ. Sci. Technol. 31 (1997) 24452454.

[2]

R.E. Banks, B.E. Smart, J.C. Tatlow; Organofluorine Chemistry: Principles and
Commercial Applications; Plenum Press: New York, NY, 1994.

[3]

J.P. Giesy, K. Kannan; Environ. Sci. Technol. 36 (2002) 146A-152A.

[4]

E. Kissa, Fluorinated Surfactants: Synthesis, Properties, and Applications, Marcel
Dekker, New York, NY, 1994.

[5]

R.E. Banks, B.E. Smart, J.C. Tatlow, Organofluorine Chemistry: Principles and
Commercial Applications, Plenum Press, New York, NY, 1994.

[6]

R. Renner, Environ. Sci. Technol. 42 (2008) 648-650.

[7]

J.R. Parsons, M. Saez, J. Dolfing, P. deVoogt, Environ Contamination Toxicology
196 (2008) 53-71.

[8]

R. Renner, Environ. Sci. Technol. 40 (2006) 4.

[9]

M.H. Russell, W.R. Berti, B. Szostek, R.C. Buck, Environ. Sci. Technol. 42
(2008) 800-807.

[10]

E. Pramauro, E. Pelizzetti, Comprehensive Analytical Chemistry: Surfactants in
Analytical Chemistry – Applications of Organized Amphiphilic Media, vol. 31,
ed. by S.G. Weber, Elsevier Science B.V., Amsterdam, The Netherlands, 1996.

[11]

M.K. So, N. Yamashita, S. Taniyasu, Q. Jiang, J.P. Giesy, K. Chen, T.K.S. Lam,
Environ. Sci. Technol. 40, (2006) 2924-2929.

[12]

N. Yamashita, K. Kannan, S. Taniyasu, Y. Horii, T. Okazawa, G. Petrick, T.
Gamo, Environ. Sci. Technol. 38 (2004) 5522-5528.

225

CHAPTER 8: CONCLUSIONS AND FUTURE DIRECTIONS

Although perfluorinated surfactants (PFSs) have been utilized since the 1950s, it
is only over the past decade that the number of peer-reviewed publications related to
them has dramatically increased. However, the majority of this literature remains
focused on either detection in the environment, toxicological effects in biota, or the
sources/fates in the environment. While several studies have investigated the
solubilization of organic pollutants by PFSs, virtually no investigations have been made
into the transport effects of PFSs on co-contaminants in the environment. Through
understanding of these transport effects, information can be gained about how the PFSs
interact with various organic pollutants in the environment. This information can be
utilized in models of risk assessment (e.g. contamination at spill sites) or as a basis for
remediation techniques.
The research performed in this dissertation has sought to provide information to
fill in this gap in knowledge. Based upon the experimental methods utilized, information
pertaining to the transport effects of PFSs on organic pollutants in a model groundwater
system was obtained through the use of reversed-phase liquid chromatography.
8.1 Experimental Methods

Chapter 2 details the experimental methods used to study the transport effects of
PFSs on organic pollutants in a flow-through groundwater system, as well as identify
various properties of the surfactants (i.e. critical micelle concentration and aggregation
number). Reversed-phase liquid chromatography (RPLC) is utilized as a model for a
flow-through groundwater system, with the resultant retention factors used to elucidate
transport effects.

226

The main limitation of using RPLC to model a groundwater system is that several
properties of traditional RPLC stationary phases do not resemble those of various soils.
These differences in properties (i.e. carbon content and surface area) can lead to retention
values (e.g. retention factors and equilibrium constants) and transport effects
unrepresentative of a groundwater system. To overcome this limitation, a stationary
phase with properties that more closely resembled those of soil was chosen. The
pellicular stationary phase used in this research had a lower carbon content and surface
2

−1

area (0.39 %, 6.0 m g , respectively), than traditional octadecylsilica stationary phases
2 −1

used in RPLC (12 – 18 %, 200 – 400 m g , respectively), which fell within the typical
2 −1

range (0.11 – 6.09 %, 1.07 – 54.0 m g , respectively) for various matrices (e.g. soils,
sediments, and suspended solids). The lower carbon content of the pellicular stationary
phase allows for the elution of hydrophobic solutes (i.e. polycyclic aromatic
hydrocarbons) in aqueous mobile phases, which are traditionally highly retained in RPLC
systems, thus providing a more complete elucidation of transport effects. The lower
carbon content also results in shorter retention times, allowing for a faster overall RPLC
experimental procedure.
Another contributing factor to the transport effects of PFSs on organic pollutants
is the critical micelle concentration (CMC) of each surfactant. As new PFSs are
developed, an understanding of their CMC is necessary. As demonstrated in Chapter 2, a
conductivity method based on the use of capillary electrophoresis (CE) identified an
experimental CMC for sodium dodecyl sulfate (SDS) within 4.0 % error of the reported
literature value. Alternatively, when this method was applied to the perfluorinated
surfactant, lithium perfluorooctane sulfonate (LiPFOS), a CMC could not be determined.

227

However, the results did suggest the possible formation of dimers or trimers prior to the
formation of micelles, at concentrations below the CMC. The possible formation of
dimers or trimers is also supported by the system peak results in Chapter 6. The use of
system peaks is an indirect method that uses retention factors of system peaks to elucidate
surfactant interaction within the system. In addition, differences in surfactant isotherms
are observed indirectly through differences in the chromatographic profile of the
surfactants. The interaction of dimers or trimers with the stationary phase (or soil) can
change the surface chemistry, thus changing the transport of organic pollutants within a
groundwater system.
Experiments in Chapters 2 and 6 sought to provide information on the transport of
the surfactants in the experimental system (i.e. a model groundwater system). A series of
experiments beyond those presented within Chapters 2 and 6 is needed to further describe
the interactions of PFSs within a model groundwater system. One experiment should
evaluate the direct adsorption of different PFSs to various stationary phases over a range
of surfactant concentrations. For this experiment, the batch equilibration method could
be utilized to determine the mass of surfactant adsorbed per unit mass of stationary phase.
The main limitations using this method would be the need for large quantities of
stationary phase packing material and the long equilibration times.
A second experiment should evaluate the direct transport of PFSs in the model
groundwater system, using RPLC with mass spectrometry detection. The retention
factors determined from the injection of aqueous PFS solutions in a pure water mobile
phase would give information on the direct transport of PFSs within the experimental
system. Limitations of this type of study might be long retention times of the surfactants

228

(leading to long experimental analysis) and the need for stationary phases that closely
resemble soil.
8.2 Transport Effects on Neutral Organic Pollutants

Chapters 3 and 4 detail the transport effects of model surfactants (e.g. SDS and
LiPFOS) on a series of neutral substituted benzene compounds and polycyclic aromatic
hydrocarbons (PAHs), using aqueous surfactant mobile phases both above and below
their CMC. In both Chapters 3 and 4, the elution order exhibited by the model pollutants
implies that their transport is dominated by the partition mechanism; with the addition of
a surfactant acting to either enhance or deter overall transport.
As shown in Chapter 3, increasing the concentration of PFSs above the CMC
increased the overall transport of a neutral organic pollutant in a groundwater system.
However, pollutant transport decreased as the number, size, and polarizability of halogen
substituents increased. In terms of PAHs, transport decreased as the ring number
increased. Non-polar organic pollutants displayed greater interaction with hydrocarbon
surfactants (HCSs) than PFSs, resulting in diminished transport effects for PFSs when
compared to HCSs. The inclusion of fluorine as a substituent caused the model pollutant
to have a greater affinity for PFSs than HCSs.
As shown in Chapter 4, the addition of a surfactant, below its CMC, will have a
differing and noteworthy contribution to the transport effects of organic pollutants.
Increasing the concentration of PFSs below the CMC increased the overall transport of
neutral organic pollutants in a groundwater system. However, pollutant transport
decreased with increasing concentrations of HCSs below the CMC. As surfactants are
added to a system devoid of surfactants, the surfactant monomers adsorb to the stationary

229

phase (or soil). The adsorption of HCS monomers caused the stationary phase to become
more hydrophobic. This hydrophobic environment leads to decreased transport of nonpolar neutral organic pollutants, due to interaction between the pollutant and the HCS
monomers adsorbed onto the stationary phase. However, the adsorption of PFS
monomers caused the stationary phase to become both more hydrophobic and lipophobic.
This environment leads to increased transport of non-polar neutral organic pollutants, due
to less interaction between the pollutant and PFS monomers adsorbed onto the stationary
phase. However, fluorinated pollutants experience decreased transport due to greater
interactions with adsorbed PFS monomers on the stationary phase.
A series of experiments in addition to those presented in Chapters 3 – 4 is needed
to completely identify the transport effects of PFSs on neutral organic pollutants. These
experiments should evaluate the transport effects caused by varying different aspects (e.g.
head group) of the perfluorinated surfactant utilized in RPLC. By systematically varying
the perfluorinated surfactant utilized, and observing the retention values, a more complete
understanding of the transport effects of PFSs on neutral organic pollutants in a
groundwater system can be obtained, both above and below the CMC.
8.3 Transport Effects on Ionic Organic Pollutants

Chapter 5 details the transport effects of model anionic surfactants (i.e. SDS and
LiPFOS), below their CMC, on a series of cationic aromatic amines. The overall elution
order exhibited by the amines implies that their transport can be explained via a partition
mechanism. However, the addition of the surfactants introduces transport effects due to
ion-pairing and ion interaction mechanisms. In accordance with ion-pairing
chromatography, the transport of the cationic pollutants greatly decreased as the

230

concentration of the anionic surfactant increased. As the concentration of surfactant in
the mobile phase increased, there was a corresponding increase in the amount of
surfactant monomers adsorbed on the stationary phase. The cationic amines interacted
with the adsorbed surfactant monomers, were highly retained on the stationary phase, and
exhibited decreased transport.
A series of experiments beyond those presented in Chapter 5 is needed to expand
upon the transport effects of perfluorinated surfactants on cationic pollutants in a
groundwater system. The first experiment should evaluate the transport effects caused by
−

varying the head group of the perfluorinated surfactants. Sulfonates (−SO3 ) and
−

carboxylates (−COO ) are the head groups of the most commonly utilized PFSs. The
−

head groups of lesser utilized PFSs include sulfates (−OSO3 ), phosphates
−

−

(−OP(OR)2O ), and sulfonamides (−SO2NR ). While fluorinated telomer alcohols
(−OH) are precursors to PFSs, their inclusion in an RPLC study would be impractical due
to their high volatility. The PFS utilized in this research contained a sulfonate head
group. For a more complete understanding of transport effects, a RPLC study using a
PFS with a carboxylate head group should be conducted and compared to the results
presented here.
A second experiment should evaluate what changes in mobile phase composition
will have on the transport effects of anionic perfluorinated surfactants on cationic
pollutants. As stated in Section 5.3.2, since the cationic aromatic amines were highly
retained in aqueous surfactant mobile phases, an organic co-solvent (i.e. methanol) was
added to the mobile phases in order to facilitate elution of the amines. It has been
reported in literature [1,2], that the pKa of substituted anilines vary depending on the

231

solvent. A study that determines the pKa of the substituted anilines in various
methanol/water solutions would provide information regarding the protonation state of
the amines, and would contribute greatly to an understanding of the interactions between
the cationic amines and adsorbed surfactant monomers utilized in this research.
8.4 Future Directions

Based on the research presented in this dissertation, there still remain several
noteworthy areas of investigation. The following sections (Sections 8.4.1 – 8.4.3) give a
brief overview of those areas of study.
8.4.1

Transport Effects of Short-Chain Perfluorinated Surfactants

Due to their thermal and chemical stability, long-chain PFSs tend to be more
resistant to environmental degradation, and thus tend to bioaccumulate. As such, the
development [3] and use of short-chain PFSs (i.e. carbon chain lengths less than 6) have
been on the rise, as they are believed to undergo environmental degradation more readily.
A series of experiments could be performed to evaluate the transport effects on
organic pollutants caused by varying the chain length of the surfactant utilized in RPLC.
As stated previously, the model perfluorinated surfactant used in this research was a longchain surfactant, consisting of eight carbons. A series of aqueous PFSs mobile phases,
both above and below the CMC, could be used to elucidate what effect varying the chain
length between C4 – C6 would have on pollutant transport in a groundwater system. As
the chain length decreases, the solubility in water will increase, thus having a direct
impact on transport of organic pollutants. As the chain length decreases, the CMC of the
surfactant increases, thus the transport effects below the CMC become more important.
In addition, a shorter chain surfactant monomer will have less interaction with the

232

stationary phase (e.g. soil). This decreased interaction will lead to less adsorbed
surfactants, and increased transport effects on cationic pollutants (in comparison to a
longer chain surfactant).
8.4.2

Transport Effects of Mixed Surfactant Solutions

In some applications the use of a single surfactant is unsuitable, and there is a
need for a binary mixture of surfactants. The binary mixture can accomplish applications
that neither surfactant can perform alone. The binary mixture can enter the environment
in a similar fashion as the individual surfactants, and thus contribute to the overall
transport of environmental co-contaminants. A secondary means of developing a binary
mixture is through the mixing of separate surfactants, released into the environment as
waste. It therefore stands to reason that binary mixtures of surfactants already exist
within the environment to varying degrees. Thus the effects of a binary mixture of
surfactants on the environmental transport of persistent organic pollutants need to be
investigated.
In a review by Noriaki Funasaki, the topic of whether hydrocarbon and
fluorocarbon surfactants mix either completely or partially is discussed [4]. Due to the
differences in chemical and physical properties of hydrocarbon and fluorocarbon
surfactants, the mixing of HCSs with PFSs is believed to be nonideal. In a study
conducted by Barthélémy et al.,

19

F-NMR and UV-visible absorbance spectroscopy were

utilized to determine the miscibility of surfactant mixtures as a function of total surfactant
concentration over a range of hydrocarbon-fluorocarbon ratios [5]. Both the

19

F-NMR

and UV-visible absorbance results identified three distinct regions. The first region takes
place below the CMC of both surfactants. It consists of the surfactants existing as

233

monomers. The latter two regions are defined by the differences in the CMC values of
the surfactants. The second region takes place above the CMC of one surfactant (i.e.
PFS) but below that of the other (i.e. HCS). It consists of micelles enriched by the lower
CMC surfactant and monomers of both surfactants. The third region takes place above
the CMC of both surfactants. It consists of two types of micelles (one enriched by PFS
and the other by HCS) and monomers of both surfactants. Since the micelle is a dynamic
system, and monomers move between it and the bulk solution, a micelle can contain
monomers of both surfactants. It has also been suggested that a single mixed micelle can
form when the CMCs of the pure surfactants are within a factor of 3 of each other [6].
However, if the surfactants are completely immiscible (i.e. no mixing of the surfactant
monomers in the micelle), then the micelle will only contain monomers of an individual
surfactant. The formation of these various regions may have little or no effect on
transport or may lead to synergistic transport effects on co-pollutants [6]. The synergistic
effect on the solubilization of PAHs by mixed micellar surfactant solutions (i.e. anionic
hydrocarbon/nonionic hydrocarbon) has been reported in the literature [7].
A series of experiments could be performed to evaluate the transport effects of a
mixed surfactant solution on organic pollutants. The transport effects could be elucidated
based on changes in pollutant retention factors, as a function of total surfactant
concentration over a range of perfluorinated/hydrocarbon surfactant ratios. The use of
RPLC, in conjunction with data from either

19

F-NMR or UV-visible absorbance studies,

would provide this information. Several aqueous mobile phases, consisting of a common
type of binary surfactant mixture (i.e. anionic perfluorinated/anionic hydrocarbon or
anionic perfluorinated/nonionic hydrocarbon), should be tested. By identifying the extent

234

to which binary mixtures effect the transport of organic pollutants, parameters can be
developed to increase the ability of environmental modeling systems to better model sites
where mixed surfactant contamination is a high possibility. Alternatively, the
information could be used in groundwater remediation techniques, in order to tailor a
pumping solution to effectively remove particular organic pollutants.
8.4.3

Transport Effects of a Perfluorinated Stationary Phase

In the environment, hydrocarbon surfactants can adsorb onto the surface of soil,
presenting a new surface to organic pollutants that has different chemical and physical
properties compared to the native soil. This phenomenon would also apply to
fluorocarbon surfactants (i.e. PFSs) as well. In RPLC, fluorocarbon surfactant monomers
will adsorb onto the stationary phase, thus forming a new stationary phase.
In order to gain a greater understanding of transport effects that adsorbed
fluorocarbon surfactants have on organic pollutants, a series of experiments need to be
performed. The first experiment should evaluate the retention of model neutral organic
pollutants in a RPLC system utilizing various commercially available fluorinated
stationary phases, with pure water as the mobile phase. Commercially available
fluorinated stationary phases have been previously used in literature [8-11], as well as in
various liquid chromatography applications [12]. The most common types of fluorinated
stationary phases either consist of a partially fluorinated alkyl chain, a chain ending with
a perfluorophenyl group, or a perfluorinated linear alkyl chain. The perfluorinated linear
alkyl phase could be used as the stationary phase in a RPLC system, and the retention
values can be compared to the results presented in Chapters 3 – 5. The perfluorinated
linear alkyl stationary phase has a C6 chain length with the particles being 5.0 µm in

235

2 −1

diameter, having a 300 Å pore size, 5.0 % carbon content, and 100 m g

surface area.

This would more closely resemble soil with a complete surface coverage of
perfluorinated surfactant monomers. In addition, the properties of this stationary phase
are comparable to the stationary phase used to perform the research in this dissertation
(Section 8.1), thus allowing for a direct comparison of transport effects.
A second experiment could evaluate the retention of model organic pollutants in a
RPLC system with a perfluorinated stationary phase, while utilizing aqueous surfactant
solutions as the mobile phase. Aqueous HCS and PFS solutions similar to those utilized
in Chapters 3 – 5 could be used for this type of study. This study would provide
information into the interactions of the pollutants between the surfactant mobile phase
and the perfluorinated stationary phase. This type of experiment would most likely
provide the closes approximation of the transport effects experienced by organic
pollutants in a groundwater system containing perfluorinated surfactants or a mixture of
perfluorinated and hydrocarbon surfactants.

236

REFERENCES

237

8.5 References

[1]

T.V Kashik, B.V. Prokop’ev, G.V. Rassolova, S.M. Ponomareva, Russ. Chem.
B+ 20 (1971) 1847-1850.

[2]

H.C. Brown, D.H. McDaniel, O. Häfliger, Ed. By E.A. Braude, F.C. Nachod,
Determination of Organic Structures by Physical Methods, Academic Press, New
York, 1955.

[3]

M. Terrazas, R. Dams, Speciality Chemicals Magazine 24 (2004) 19-21.

[4]

N. Funasaki, Surf. Sci. Series 46 (1992) 145-188.

[5]

P. Barthélémy, V. Tomao, J. Selb, Y. Chaudier, B. Pucci, Langmuir 18 (2002)
2557-2563.

[6]

T.J. Connolly, V.C. Reinsborough, X. Xiang, Aust. J. Chem. 45 (1992) 769-775.

[7]

L. Zhu, S. Feng, Chemosphere 53 (2003) 459-467.

[8]

P. Varughese, M.E. Gangoda, R.K. Gilpin, J. Chromat. Sci. 26 (1988) 401-405.

[9]

H.Y. Aboul-Enein, V. Serignese, Anal. Chim. Acta 319 (1996) 187-190.

[10]

I. De Miguel, A. Roueche, D. Betbeder, J. Chromatogr. A 840 (1999) 31-38.

[11]

K. Jinno, H. Nakamura, Chromatographia 39 (1994) 285-293.

[12]

W. Zhang, J. Fluorine Chem. 129 (2008) 910-919.

238