Solubilization and mobilization of perchloroethylene by cosolvents in porous media

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Title:
Solubilization and mobilization of perchloroethylene by cosolvents in porous media
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xv, 156 leaves : ill. ; 29 cm.
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English
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Van Valkenburg, Michael Edward, 1963-
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Environmental Engineering Sciences thesis, Ph.D   ( lcsh )
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Thesis:
Thesis (Ph.D.)--University of Florida, 1999.
Bibliography:
Includes bibliographical references (leaves 147-155).
Statement of Responsibility:
by Michael E. Van Valkenburg.
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Typescript.
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Vita.

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University of Florida
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SOLUBILIZATION AND MOBILIZATION OF PERCHLOROETHYLENE BY
COSOLVENTS IN POROUS MEDIA














By

MICHAEL EDWARD VAN VALKENBURG


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA


1999





























This dissertation is dedicated to each person who gave his or her life so valiantly and
courageously for our country. I know this is but a little gesture, but nonetheless their
sacrifices have moved me so deeply, that any acknowledgement of them in remembrance is
the least that each of us can do. I hope in just reading this, you will remember them.













ACKNOWLEDGMENTS


I would certainly not be in the position to be even writing these acknowledgements

if it were not for the support of my family throughout the years. Through several times of

self-evaluation and self re-direction, they have always been supportive and helpful,

providing motivation when I had very little especially my Mom. I am thankful for my

Dad, for "buying me books and teaching me all he knew." I know he was far from

perfect, so am I, but he was, is, and always will be my Dad.

My wife, Kim, and our three children, Joseph, Lauryn, and Kelley have been so

understanding about times devoted away from them when they have wanted me the most,

and my attentiveness that could have always been better. There was always something

else on my mind to finish this! I wish I could have been there even more. I will always

try to be a better father and husband. There is more to come.

I extend my sincere appreciation to the U.S. Air Force (and the American

taxpayer) for sponsoring my education and completion of this dissertation. I thank the

Biomedical Sciences Corps for its flexibility and thank the U.S. Air Force Academy and

the Department of Chemistry for having the faith in me to complete this degree and

wanting me back to work in what has to be one of the nicest environments in the world!

Special thanks go to Col. Hans Mueh, Col. Clifford Utermoehlen, Lt. Col. Ron Furstenau,

and Maj. Rob Racicot.








Obvious thanks go to Dr. Mike Annable and my committee members for their

guidance in my completion of this project. Special thanks go to Dr. Joe Delfino for taking

the time to sit down for lunch with me in a deli in Denver, Colorado during an ACS

convention and encouraging me to become a Gator! Also, I valued his graduate program

guidance and wise advice that I took on numerous occasions. Thanks are given to Dr. Bill

Wise for his many hours of exchanging knowledge, in the lab and in the office, and to Dr.

Suresh Rao for his confidence building. Finally, special gratitude to Mike Annable for

being so understanding, supportive, and always open to my impromptu office visits

seeking guidance and tutelage.

Thanks also go to my fellow lab partners, Michael Brooks, Jaehyun Cho, Clayton

Clark, and Rick Young for their many instances of assistance and showing patience with

me, and to Randy Switt for all his computer help. To my fellow 2-D boxer and final lab

inmate Jim Jawitz I appreciate the use of "the box," his motivational assistance, the

hours of practical knowledge, and the many laughs. He will not be "forgotten" in this

document.

One final person, who I am sure does not get recognized enough and whose

expertise I am grateful for, is Lynn LaBauve, of the Marston Science Library Reference

Desk. Over the last three years she has sought me out numerous times to help in

searching the vast reference databases used in completing research. Those needing

reference help at the University of Florida should find her and they will reap the benefits.














TABLE OF CONTENTS
pEge

ACKNOWLEDGMENTS ............................................................................................iii

LIST OF TABLES ................................................................................................. viii

LIST OF FIGURES.................................................................................................. ix

ABSTRACT......................................................................................................................... xiii

CHAPTERS

1. INTRODUCTION................................................................................................ 1

Background............................................................................................................... 1
Selection of DNAPL................................................................................................ 5
Study Objectives.................................................................................................. 5
Dissertation Organization........................................................................................... 8

2. INVESTIGATIONS OF THE RELATIONSHIP OF COSOLVENT
FRACTION TO PERCHLOROETHYLENE (PCE) SOLUBILITY AND
EQUILIBRIUM INTERFACIAL TENSION...........................................................9 /

Introduction............................................................................................................... 9
Comparison of the Molecular Structures of Water and Low Molecular Weight
Alcohols....................................................................................................... 10
Solubility of Hydrocarbons into Water/alcohol Mixtures and its Relationship to
Amount of Cosolvent................................................................................. 13
Log-linear relationship................................................................................ 15
Cosolvency power........................................................................................ 17
Other methods for solubility estimation ........................................ ............ .. 17
Choice of solubility estimation method ..........................................................21
Interfacial Tension of Ternary Alcohol/water/PMOS Mixtures ............................... 21
Relation to amount of cosolvent......................................................................... 22
Different interfacial tension prediction methods .............................................. 23
Relation of IFT to Solubility of Organic Solute ....................................... .....27
Materials and Methods............................................................................................. 27
Results and Discussion.......................................... ..................................................29
Log Linear Solubility Estimation....................................... ........................... 29
Ethanol ............................................... ..................................................... 29








Isopropanol (IPA ) ......................................................................... ............ 30
UNIFAC Method........................... ......................... ................................... 31
Extended Hildebrand Method.......................................................................... 31
M inor cosolvent addition............................................... ............................... 35
Interfacial Tension Measurements and Predictions................................... ..... 36
Conclusions....................................................................................................................... 39

3. MOBILIZATION OF RESIDUAL PERCHLOROETHYLENE DURING
COSOLVENT FLOODING........................................................................... 42

Introduction................................................. .................... ........................................ 42
Solubilization vs. Mobilization .................................. ........................... 45
The Trapping Number Relationship...................................................................... 47
Study Objective ........................... .......................... ...................................... 49
M materials and M ethods................................................................................ .. ............... 50
GC Analysis ........................ ............................................................................. 50
Physical M easurements ................................................................ .................... 51
Sand Column Preparation........................................................................................... 51
PCE Saturation........................................................................................................ 52
Hydrodynamic Parameters ............. ............... .. ........ 52
Sand Column Mobilization Studies.......................................................... .......... 53
Results and Discussion.............................................................................. ..... 54
Equilibrated Gradient Column Studies...... .......... .. ................... 54
Blank Equilibrated Gradient Study .................................................................. 55
Non Equilibrated Column Studies ...................................... 55
Generation of Mobilization Curves................................................................... 58
Swelling Effects of Cosolvents.............................................................. ............ 62
Conclusions.................................................. .......................................................... 64

4. ENTRAPMENT VERSUS MOBILIZATION OF RESIDUAL
PERCHLOROETHYLENE DURING COSOLVENT FLOODING.................. ..... 66

Introduction....................................................... ...................................................... 66
Solubilization, Mobilization and the Trapping Number Relationship ......................... 68
Mobilization and Entrapment of Residual Non-Aqueous Phase Liquid...................... 68
Study O objective ....................................................................................................70
Materials and Methods.................................................................................... 70
Physical Measurements ........ ......................................................... .......... 71
Sand Column Preparation................................................................... 71
PCE Saturation and Generation of Trapping Curves.......................................... 72
Mobilization studies.............................................................................. 72
Entrapment studies....... ................................................................................74
Hydrologic Parameters........................................................................... 74
Results and Discussion................................................................. .... ........................ 76
Entrapment in Homogeneous Sand Column .................................. ..................77
Effect of Pore Size Heterogeneity on the Entrapment of PCE................................ 80








C conclusions ...................................................................................................................83

5. MOBILIZATION AND ENTRY OF DNAPL POOLS INTO FINER SAND
MEDIA: TWO-DIMENSIONAL BOX STUDIES................................................... 85

Introduction.... ....................................................................................................... .... ..85
Materials and Methods............................................................................................. 90
General Packing Procedure ................................................................................... 91
Dye Tracer Displacement .................................................................................... 93
DNAPL Introduction............................................................................................ 94
Hydraulic Controls During 2-D Box Experiments............................................. 94
Results and Discussion..................... ...................................................................... 95
No. 100-140 Fine Layer.................. ................................................................... 95
Step input of 100% alcohol ........................................................................... 95
One-dimensional horizontal sand column experiments.................... ............. 98
Step input of 80% alcohol............................................................................... 99
No. 60-70 Fine Layer...................................................................................... ... 101
Step input of 80% alcohol........................................................................... 101
Gradient Injection (10-90%) of Alcohol ...................................................... 101
No. 40-50 Fine Layer....................................................................................... 105
Background dye flush after DNAPL injection................................................. 105
Step input of 80% alcohol........................................................................... 106
No. 30-40 Fine Layer.......................................................................................... 107
Step input of 80% alcohol........................................................................... 107
Step input of 70% alcohol........................................................................... 109
Step input of 50% alcohol........................................................................... 110
Two-Dimensional Studies with t-Butyl Alcohol................................................ 110
Step input of 30% TBA: #30-40 finer layer ................................................... 111
Step input of 40% TBA: #100-140 finer layer ............................ ................ 11
Systematic Quantitative Evaluation and Prediction of Mobilization into Finer
Layers........................................................................................................ 116
Conclusions................................................................................................................. 120

6. SUMMARY AND CONCLUSIONS .......................................................... 122

APPENDICES

A MOISTURE RELEASE CURVES FOR SAND MEDIA........................................ 127

B TWO-DIMENSIONAL BOX SCHEMATICS....... ..... .................... .................. 134

REFERENCES.......................................... ............................................................147

BIOGRAPHICAL SKETCH ................................................................ ........... 156














LIST OF TABLES


Table page

2-1. Solubility parameters for study components (Barton 1975) ..................................32

3-1. Physical Measurements of PCE Saturated Cosolvent Solutions............................ 57

3-2. Physical properties of solutions used in swelling mobilization studies ....................64

4-1. Results of linear regression of entrapment studies ............................................. 79

5-1. Particle size ranges of sands used................................................. ........... ..... 92

5-2. Summary of Experimental Runs in 2-Dimensional Box Studies ............................96

5-3 Summary ofdesaturation profile curve fitting parameters. Beit Netofa Clay values
(a, n, and m) are from van Genuchten (1980). Pore radius for the clay is taken from
W ise (1992). .................................................................................................. 117

5-4 Results of globule force balance calculations. Mobilization of globule is predicted if
hd,,apt>hd""'h'. Permeability of 20-30 medium measured to be 6.35E-7 cm2. "Clay"
scenario based on Beit Netofa clay (van Genuchten 1980) is shown for comparison.
Fluid property values shown are approximate and for illustrative purposes ......... 119














LIST OF FIGURES


Figure page

2-1. Graph of data from Franks and Ives (1966), relating concentration of hydrogen bonds
to volume fraction of ethanol............................................................................. 12

2-2. Solubility of PCE as a function of cosolvent volume fractions (initial phase
volumetric phase ratio 1:1).......................................................... ........................ 30

2-3. Comparison of Measured Solubility Data and those predicted by the UNIFAC
M ethod ............................................................................................................ 32

2-4. PCE Solubility Prediction of the Hildebrand and Extended-Hildebrand Theories for
the IPA Cosolvent M ixtures............................................................................. ... 34

2-5. Solubility of PCE as a function of various cosolvent volume fractions (initial phase
volumetric phase ratio 1:1).................................................................................. 36

2-6. Relationship of equilibrated interfacial tension of PCE/alcohol/water ternary systems
as a function of initial cosolvent volume fraction ................................................. 37

2-7. Logarithmic plot of the IFT of ternary PCE/cosolvent/water mixtures versus initial
volume fraction of cosolvent. Additional data for addition of 10% isobutanol is
shown for reference.......................................................................................... 38

2-8. Interfacial tension of PCE/cosolvent/water mixtures related to solubility of PCE in
the aqueous phase. Numbers above selected data points indicate initial volume
fraction of cosolvent. ........................................................................................ 40

3-1. Gradient effluent profile for saturated PCE run (influent %'s shown are ethanol
volume fractions prior to saturation) ................. ............................................56

3-2. Gradient effluent profile using unsaturated ethanol mixtures percent of mobilization
show n. ............................................................................................................. 56

3-3. Gradient effluent profile using unsaturated ethanol cosolvent mixtures with PCE
saturation reduction shown. ........................................................................... 57








3-4. Mobilization curves showing effect ofa cosolvent (ethanol) flushing phase which is
pre-equilibrated with PCE (gradient 2 and 4) and a flushing phase with full
solubilization potential (non-equilibrated 1). All are gradient runs ........................ 59

3-5. PCE Desaturation Curves PCE saturated ethanol cosolvent runs compared with
data from Pennell et al. (1996). .......................................................................... ... 60

3-6 Ethanol mobilization curves with surfactant run superimposed................................. 61

3-7. Results from mobilization studies using pre-equilibrated IPA solutions, superimposed
on the ethanol study results. .................................................................................. 63

3-8. Results of mobilization of PCE during gradient TBA column flushing; TBA pre-
equilibrated with PCE........................................................................................ 63

4-1. Moisture release curve for No. 30-40 silica sand used for these studies, conducted
via Tempe cell. van Genuchten (1980) and Brooks & Corey (1964) fits are based on
minimizing the sum of squares of the difference between the actual data and the fitted
line................................................................................................................... 75

4-2. Relative permeability to the wetting phase at less than normal nonwetting phase
residual saturations: Morrow and Songkran (1982) data shown with regression R2 =
0.907) and fit of this study's Tempe cell data based on van Genuchten (1980)
parameters and the Mualem (1976) method......................................................... 76

4-3. PCE Desaturation curve experimental ethanol data only compared to those of
Pennell et al. (1996) ............................................................................................ 77

4-4. PCE desaturation curves for both mobilization and entrapment studies, with linear
regressions shown for the entrapment experiments ............................................ 79

4-5. Effective saturation of study 30-40 mesh sand as a function of capillary pressure,
resulting slope of regressed line is the Brooks and Corey lambda, X = 3.65............ 81

4-6. Results of entrapment experiments on the heterogeneous packing (#20-100 sand),
shown with homogeneous entrapment and mobilization results for reference. ......... 82

5-1. Schematic of DNAPL contamination of subsurface aquifer systems, showing free
phase and residual DNAPL....................................... .................................... 87

5-2. Typical 2-D box setup after injection of PCE, prior to any flushing...................... 93

5-3. Dyed PCE injected into Number 20-30 medium (approximately 2.7 ml) pooled over
a 1 cm layer of Number 100-140 medium...................................... ........... 97








5-4. Removal of residual dyed PCE by gradient ethanol injection (0-100% v/v) over one
pore volume. Darker band at interface is highly saturated PCE which is mobilizing
toward the lower left and pooling...................................................................... 99

5-5. Progression of DNAPL pool collapse Nos. 20-30 background medium, Nos. 100-
140 finer layer after 0.8 PV of 80% v/v ethanol/water step input. Downstream
direction is to the right in all pictures........................................ ........................ 100

5-6. Spreading of DNAPL pool downstream on top of finer Nos 100-140 layer. No
breakthrough occurred during this run 1.1 PV after 80% v/v ethanol/water step
input............................................................ ........................... ........ .. 100

5-7. Schematic of step input of 80% alcohol No. 60-70 finer layer........ ......... .. 103

5-8. Horizontal spreading of PCE pool upstream from injection zone Nos. 20-30
background media, 60-70 finer layer, 1.1 PV after gradient injection of 10 90% v/v
ethanol/water over 1PV. Blue band is location of 58% (leading edge) to 76%
ethanol........... .................................................. ............................... 104

5-9. Highly concentrated cosolvent phase in which dye has partitioned, entering finer
Nos. 60-70 layer. This is not free phase mobilization. Blue band above is from a
post gradient step input to 100% reagent alcohol ...................................... 104

5-10 Breakthrough of highly concentrated PCE containing cosolvent phase into finer
layer and subsequent reestablishment ofDNAPL below the finer layer due to lower
alcohol concentrations.......................................................... ....... ............ ....... 105

5-11. Water tracer study for 40-50 finer layer experiment. Note the significant holdup of
tracer in lower portions of PCE pool and noticeable progression of dye in finer layer
underneath ......................................... ....... ........... ........ .......... 106

5-12. Collapsing of PCE pool and spreading of DNAPL along 40-50 layer. No
breakthrough of DNAPL observed....................... .................... 107

5-13. Schematic for step input of 80% alcohol No. 30-40 finer layer..................... 109

5-14. Schematic for step input of 70% alcohol No. 30-40 finer layer. ................... 109

5-15. Mobilization of DNAPL into finer 30-40 layer at two locations, upstream from
injection zone (small + mark in picture) 0.45 PV after step input of 80% v/v
ethanol/water mixture. Mobilization also occurred later at one other location
downstream of pool (see text)................. ........ .............109








5-16. Mobilization of the PCE pool by a 40% v/v TBA cosolvent mixture (0.6 PV)
resulting in the trapping of a volume of the cosolvent mixture on top of the finer
layer................. ............................................................................ .................. 113

5-17. PCE and TBA elution profiles from 2D Box after a step input of 40% v/v
TBA/H20. TBA profile data are shown as GC peak areas for reference .............. 114

5-18. DNAPL pool shape after the injection of one pore volume of 40% v/v TBA
cosolvent m ixture....... .............................................................................. ...... 115

A-1. Moisture release curve for Nos. 20-30 sand .......................... ................ 128

A-2. Pore size frequency distribution of Nos. 20-30 sand ....................................... 128

A-3. Moisture release curve for Nos. 30-40 sand .................................... ............ 129

A-4. Pore size frequency distribution of Nos. 30-40 sand .................................. 129

A-5. Moisture release curve for Nos. 40-50 sand ................................................... 130

A-6. Pore size frequency distribution of Nos. 40-50 sand .................................... 130

A-7. Moisture release curve for Nos. 60-70 sand .................. .................... 131

A-8. Pore size frequency distribution ofNos. 60-70 sand ....................................... 131

A-9. Moisture release curve for Nos. 100-140 sand............................................... 132

A-10. Pore size distribution of Nos. 100-140 sand ...................................... 132

A-6-11. Moisture release curve for wide distribution (#20-100) sand...................... 133

A-12. Pore size distribution of wide distribution (#20-100) sand ............ .............. 133














Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

SOLUBILIZATION AND MOBILIZATION OF PERCHLOROETHYLENE BY
COSOLVENTS IN POROUS MEDIA
By

Michael E. Van Valkenburg

May 1999


Chairman: Dr. Michael D. Annable
Major Department: Environmental Engineering Sciences

Batch equilibrium studies conducted for perchloroethylene (PCE)/cosolvent

systems determined that the log-linear solubility relationship is not a completely accurate

method to predict solubility of PCE in cosolvent mixtures over an entire range of volume

fractions. Batch studies resulted in cosolvency powers of 3.73 and 4.13 for ethanol and

isopropanol, respectively. However, log-linear predictions may be adequate for

estimations necessary for remediation efforts. The use of the Extended Hildebrand model

is recommended.

The interfacial tension (IFT) resulting from cosolvent mixtures when compared to

the initial volume fraction of cosolvent showed a relationship, similar to the log-linear

model. An "IFT reduction power" was determined for ethanol to be -3.60, and isopropyl

alcohol, -5.80, describing the ability ofcosolvents to reduce IFT with increasing volume








fraction. IFT values are accurately estimated by PCE solubility in regimes conducive to

cosolvent flushing.

Onset of residual PCE mobilization was found to begin at a trapping number (N,)

of 2 x 104. Solubilization of residual PCE is dominant at ethanol volume fractions less

than 85% and mobilization of PCE is avoided. Under severe conditions, mobilization via

cosolvents can occur. These include large step inputs of high cosolvent fractions (greater

than 85%), when DNAPL saturation is great enough for IFT reduction to cause

mobilization. Behavior of surfactant and cosolvent systems was similar on a mobilization

curve and is independent of alcohol type.

Entrapment and mobilization of residual NAPL are separate and distinct processes.

The entrapment process appeared to be log-linearly related to the trapping number for

homogeneous media. This is believed to be associated with the log-linear dependence of

saturation with capillary pressure. However, for heterogeneous media, increased

saturations with decreasing IFTs was observed.

Two-dimensional studies revealed that pooled DNAPL was found to collapse

under reducing IFT conditions and mobilized downward and up gradient along overriding

cosolvent fronts. This caused significant build-up of DNAPL on the lower confining layer.

The most significant production of DNAPL through any fine layer in these studies was

actually up stream from the source zone. Gradient injection to remove pooled DNAPLs

did not appear to provide significant benefit over step inputs. Entry pressure calculations

predicted breakthrough of PCE into the finer media in excellent fashion. Breakthrough of

PCE under typical ethanol flooding conditions (80% by volume) can generally be assumed

to occur in homogeneous sand media when the cosolvent/DNAPL entry pressure of the








finer media (h"-"') is less than0.35 cm. A swelling alcohol (t-butanol) used to remove

pooled DNAPL resulted in trapped cosolvent zones on top of finer layer due to density

effects. Partitioning of TBA into DNAPL allowed for more accumulation on finer layer

before entry was observed. Calculations for an example clay estimated that approximately

a half meter worth of equilibrated PCE-type DNAPL would have to accumulate before

entry into the clay pores under extreme cosolvent flooding conditions.













CHAPTER 1
INTRODUCTION


Background


Due to our industrial society's ever-increasing use of chemicals during the last 50

years, it has been increasingly necessary to manage the corresponding waste products

from these industrial operations. The management of these waste streams at various times

throughout this half-century has evolved from "drum it up and bury it in the back 40" type

methods to highly regulated disposal and stream reduction. Unfortunately, prior to the

1980's, industry did not realize the environmental and health impacts of our decisions,

which we thought were proper at the time. As a result, there are hundreds of thousands of

disposal sites in the United States alone, thousands of which are severe enough to be on

the Environmental Protection Agency's (EPA) National Priority List. A large number of

these sites are contaminated with a class of chemicals known as dense nonaqueous phase

liquids (DNAPLs), some of which are known carcinogens. These chemicals, immiscible

with water, include polychlorinated biphenyls (PCBs), creosotes, and halogenated

solvents. Prior to the early 1990s, this class of contaminants received minimal attention

from environmental engineers and hydrogeologists.

Until recently, remediation technologies for the removal of these DNAPLs from

subsurface environments focused on pumping of groundwater and subsequent treatment of

this stream. Risk reduction to possible receptors was the driving force behind these








actions. However, due to the solubility limitations of these types of treatment, remedial

action time-scales were long and expensive. The source of contamination is very slowly

removed due to solubilization into water. In the last few years, research efforts and

technology demonstrations have become more focused on source removal. These include

surfactant flooding and cosolvent flushing (Annable et al. 1996; Falta et al. 1997; Fortin et

al. 1997; Jawitz et al. 1998b; Lunn and Kueper 1997; Pennell and Abriola 1996; Pennell et

al. 1994; Pope and Wade 1995; Rao et al. 1997). Although these techniques tend to be

more aggressive and have high initial costs, the removal of a possible long-term source is

beneficial from risk reduction, economic, and legal perspectives.

The major concern with the use of surfactants and cosolvents is the possibility of

DNAPL movement during these remediation operations. The natural driving force behind

any movement of DNAPL in the subsurface is gravity. Downward DNAPL movement of

any kind is undesirable as this increases the likelihood of the contaminant leaving the more

accessible and shallower geologic zones and entering deeper drinking water aquifers.

Furthermore, once collected on top of a finer layer, entry, and subsequent breakthrough

presents severe risks to aquifers below. Remediation techniques using surfactant and/or

cosolvents increase solubility of the DNAPL into the aqueous phase, but concurrently

increase the possibility of DNAPL movement due to a decrease in interfacial forces

between the DNAPL and the aqueous phase. In fact, some remediation techniques using

surfactants have as their main objective the bulk movement of the DNAPL towards

recovery wells for extraction. This technology has been modified from the enhanced oil

recovery (EOR) field, where surfactants are used to move oil previously trapped in








reservoir rock. The movement of any non-aqueous phase liquid in the subsurface has been

labeled 'mobilization' and will be hereafter referred to as such.

The use of alcohols to enhance recovery of oils or NAPLs via miscible

displacement has long received attention (Morse 1952). Several other references to

alcohol use appear in early literature on the topic, including Gatlin (1959), Gatlin and

Slobod (1960), Kamath (1960), Paulsell (1953), Sievert (1958), and Slobod et al. (1958).

Due to the inherent risks of downward mobilization of DNAPLs, the use of

cosolvents to remove them via miscible displacement has increased in popularity. This is

due to the primary objective of'cosolvent flushing' being solubilization of the DNAPL,

rather than mobilization. However, this is not to say that mobilization does not occur if

cosolvents are used. Since the solubility of a contaminant increases generally

logarithmically with addition of a cosolvent to water, use of cosolvents (such as ethanol or

isopropyl alcohol) in their pure state, or at least at high volume fractions, would appear to

be a consistently wise choice. Nevertheless, mobilization of DNAPL at these high volume

fractions (>80% by volume) of cosolvents is very possible, especially if DNAPL

saturations are above residual levels.

DNAPLs in the subsurface can also be residually trapped in the vadose and

phreatic zones of the subsurface. Here the DNAPL exists as discrete globules in the pore

of the soil medium. Eventually, the draining DNAPL in the saturated zone can become

'pooled' on top of a layer of soil that is more restrictive to downward flow of any fluid. It

is less permeable than the surrounding layers. Here, it can spread laterally along the less-

permeable layer until equilibrium is achieved. Alternatively, continuing quantities of








DNAPL can accumulate and the height of the pool becomes great enough to where

gravity forces the DNAPL to enter the smaller pores of the less-permeable layer.

Mobilization of DNAPL can occur during the remediation of both these types of

sources, residual and pooled. Mobilization of a residual DNAPL, like PCE, can create

banks that can move ahead of the rich cosolvent flushing phase, or can move downward

along the cosolvent front, depending on the difference in gravity between the DNAPL and

the aqueous flushing phase. Pooled DNAPL can mobilize as described above, but the

presence of an underlying layer can prevent downward movement if the permeability is

low enough (high entry pressure), accumulation is small enough, and therefore entry

pressures into the finer media not exceeded. Under extreme conditions of low entry

pressure, low interfacial forces, and large pool thickness, entry of the DNAPL in to the

pores is possible. Eventual breakthrough into lower regions is then probable, depending

on the layer thickness and amount of DNAPL present.

Because of the complexities of DNAPL source removal briefly introduced above,

several questions arise: 1) is there an optimum amount of a cosolvent that can be used to

maximize solubilization, yet minimize the chance of mobilization; 2) can predictions be

made as to when mobilization of residual DNAPL will occur; 3) what DNAPL will be left

behind, or "entrapped," if the entire amount is not removed with the cosolvent used; 4)

can predictions be made as to whether pooled DNAPL will enter an underlying layer under

certain flushing conditions; and 5) are there better flushing methods to minimize the

chance of mobilization of either residual or pooled DNAPL? There are a variety of

chemical, physical, and hydrogeologic factors that can influence the outcome of these

questions. Several of these will be discussed in the chapters that follow.








Selection of DNAPL

A common solvent used throughout the last few decades is tetrachloroethylene,

also known as perchloroethylene, or "perc" (PCE, C2C4, Chemical Abstract Number

(CAS) 127-18-4). This solvent has been used as an industrial degreaser, but a more

common use even today is as a dry cleaning solvent. The former use has led to the better-

known industrial hazardous waste sites. Perchloroethylene has been found in at least 330

of the 1117 National Priorities List (NPL) hazardous waste sites. However, it is

increasingly evident that the thousands of dry cleaner establishments in the United States

had their share of mismanagement of PCE. There are over 600 contaminated dry cleaner

sites in Florida alone. Due to the sheer number of potential contaminated sites, the

toxicity of PCE (a drinking water equivalent level (DWEL) of 0.5 mg/L has been

established by the EPA), and often close proximity of these establishments to residential

areas, there is growing concern of the impact of long-term subsurface sources of PCE

contamination.

Study Objectives

Based on the background summarized above, the following paragraphs describe

the objectives of this research.

Determine solubility relationship of PCE to amount ofcosolvent. This objective is

to determine the solubility relationships (log-linear relationship or other) for a few

common alcohols used to remediate NAPLs, and justify the quantities used under different

remediation regimes. Due to the unique nature of water and the various intermolecular

interactions which occur when a solute is added (or when enough solute is added to

become a cosolvent), the scientific basis for the solubility relationship can become








complicated. Once a relationship has been established, an explanation for its features will

be proposed based on the chemical literature and this study's observations.

Measure the effects of the type of alcohol(s) and amounts) on interfacial tension

(IFT) and develop a relatively simple, yet useful relationship between the two. As the

mutual solubility between two phases increases, the interfacial tension between them

decreases. A critical feature of cosolvent flushing in the field is the rate of decrease in IFT

with increasing cosolvent volume fractions. This study will measure the relationship

between the amount of alcohol added and the IFT between the equilibrated phases.

Propose a relationship between the solubility of PCE into various cosolvent

mixtures and the resulting equilibrated IFT. It would be beneficial for field applications to

have an understanding of the expected solubility of PCE into the aqueous phase and the

corresponding IFT that results from this mixture. Mobilization of NAPL is a strong

function of IFT. To have an estimate of the aqueous phase concentration of PCE at

various IFT values would provide information helpful in determining if mobilization will

occur under a given flow regime. This study will attempt to establish this relationship to

possibly be used in further studies and field applications.

Development of a trapping number relationship using cosolvents. IFT is not the

only parameter governing mobilization. Relationships have been established (Pennell et al.

1996b) and applied to surfactant use in porous media. These relationships describe the

amount of NAPL removed from a given media via mobilization as a function of a

dimensionless "trapping number", which includes contributions from viscous, capillary,

and buoyancy forces. However, a similar relationship verified with cosolvents has not

been found in the literature. Sand column experiments were performed similar to Pennell








et al. (1996) using a cosolvent mixture(s) found from the previous bench top experiments

to develop and verify the dependence ofDNAPL (PCE) saturation on the trapping

number.

Determine the relative amounts of mobilization due to purely IFT reduction and to

possible swelling ofDNAPL. During cosolvent flooding both solubilization and

mobilization of the NAPL can occur. Mobilization occurs due to a variety of

hydrogeologic and physical parameters. A critical parameter during these remediation

operations is the IFT. To isolate the effects of reduction of IFT on mobilization of PCE,

soil column experiments were conducted with the influent cosolvent phase pre-equilibrated

with PCE.

Determine the relationship of entrapment of DNAPL to the trapping number and

the difference between entrapment and mobilization of residual PCE using cosolvents.

The entrapment of a NAPL in the pore structure after being exposed to reduced interfacial

tensions is important to evaluate, since a high removal efficiency is desired. The

entrapment process of PCE in a one-dimensional homogeneous sand column under

various trapping number environments will be evaluated and compared to the mobilization

experiments. Additionally, the effect of sand pore size heterogeneity on entrapment were

observed.

Qualitatively observe the effects of various cosolvent mixtures on the removal of

PCE pooled above various finer sand layers. Two-dimensional studies were conducted

varying the amount of cosolvent in the flushing phase and the mode of injection (step input

versus gradient input). General observations and conclusions were made to improve

removal of pooled systems using cosolvents.








Confirm the quantitative prediction of entry ofDNAPL into finer pores below

DNAPL pools, during cosolvent flushing processes. Entry ofDNAPLs into finer more

"impermeable" layers is undesirable during removal of DNAPL plumes. Prediction of

entry of these DNAPLs into finer layers is straightforward via basic force balance

calculations. However, under cosolvent flooding conditions, parameters used to calculate

entry pressures (density contrast and interfacial tension between the two fluids) are

changing during flooding processes, especially for strongly partitioning alcohols like t-

butyl alcohol. It is possible that the entry predictions can be made assuming equilibrium

density and interfacial tension values.

Dissertation Organization


Each of the following chapters (Chapters 2-5) is written to essentially be a stand-

alone document. Thus, a similar format of Introduction, Methods and Materials, Results

and Discussion, and Conclusions is used throughout. Chapter 2 includes the results of the

bench top solubility and interfacial tension studies (first through third objectives). Chapter

3 discusses the results of the mobilization studies of residual perchloroethylene (fourth and

fifth objectives). Chapter 4 further expands on the process of mobilization and its

comparison to the entrapment of DNAPL after exposure to reduced interfacial tension

conditions (sixth objective). Finally, Chapter 5 outlines the results of the two-dimensional

box studies to evaluate flooding processes on pooled DNAPL system and predict their

entry into a finer medium below (final two objectives). Chapter 6 summarizes the major

conclusions of the entire dissertation and identifies areas of future research.













CHAPTER 2
INVESTIGATIONS OF THE RELATIONSHIP OF COSOLVENT FRACTION TO
PERCHLOROETHYLENE (PCE) SOLUBILITY AND EQUILIBRIUM
INTERFACIAL TENSION




Introduction


Optimization of remediation technologies is a prime concern to engineers,

scientists and environmental regulators. This optimization involves engineering, scientific,

economic, environmental impact and health risk considerations. One recent technology

for Non-Aqueous Phase Liquid (NAPL) or Dense Non-Aqueous Phase Liquid (DNAPL)

removal from subsurface environments is the use ofcosolvents to increase the

solubilization of contaminants and to flush the mixtures (and NAPL if mobilization occurs)

into recovery wells. Cosolvents are commonly binary alcohol-water mixtures and less

commonly ternary alcohol A-alcohol B-water mixtures. The exact "recipes" for these

mixtures are rather loosely chosen. Relationships between the solubilities of the

contaminants of interest and the resulting interfacial tensions (IFTs) for different amounts

ofcosolvent would be beneficial to optimization of these technologies. Hereafter, the

term IFT, and IFT measurements presented in the results section, are defined (or

measured) at the interface between the cosolvent mixture and the DNAPL phase. One

common DNAPL is perchloroethylene (PCE), a historically common industrial degreaser

and dry cleaning solvent. An objective of this investigation was to determine the effects of








various cosolvents and cosolvent mixtures on the solubility of PCE and the resulting

equilibrium interfacial tension between the two phases (organic and aqueous). From these

results, it is desired to develop a simple predictive relationship between these factors. An

accurate understanding of the IFTs of these mixtures also allows better prediction of the

mobilization of a separate PCE phase. This situation is a concern due to the density of

PCE (approximately 1.62 g/ml) and its possible downward movement (mobilization), out

of the control of the remediation scheme.

Comparison of the Molecular Structures of Water and Low Molecular Weight Alcohols

Cosolvents typically used for cosolvent flooding operations are monohydric

(contain only one alcohol group, e.g., ethanol or isopropyl alcohol). When these

monohydric alcohols are present in binary alcohol/water mixtures, deviations from ideal

solution behavior are seen, especially at lower volume fractions (Franks and Ives 1966).

These deviations can be attributed in a general way to the bifunctional nature of these

types of solute molecules. It is a push-and-pull effect where the small hydrophobic

portion of the molecule resists the pull exerted by the hydrophilic hydroxyl group. This

hydroxyl group, either as a proton donor or acceptor, can hydrogen bond with the solvent

(water) molecules. Although hydrogen bonding plays a role in the behavior of these

systems, it cannot account for all observed phenomena. Other structural differences need

consideration. Deviations from ideal behavior is noticeably lessened if a second hydroxyl

group is added to the molecule (e.g., glycols) which shifts the balance of forces in favor of

a more "aqueous behavior" (Franks and Ives 1966).

The structure of water is tetrahedral in shape, with the polar O-H bonds being

approximately sp3 hybridized. Thus, each oxygen atom can form approximately four








tetrahedrally-disposed hydrogen bonds (Frank and Wen 1957). Formation of these

hydrogen bonds is energetically favorable, until it suffers collective destruction by high

energy fluctuation. Thus, a three-dimensional cluster of water molecules is formed, which

lifetime is on the order of 10' seconds (Franks and Ives 1966). Although this lifetime is

short, it is still two or three orders of magnitude greater than the period of molecular

vibration. Liquid water is considered to be a mixture of these clusters (which can be

open) and a dense fluid composed of non-hydrogen bonded water molecules (Franks and

Ives 1966). This order-disorder balance in water is sensitive and is highly significant to its

properties. This is particularly the case in the reaction of water with hydrophobic parts of

bifunctional molecules, like alcohols.

For aliphatic alcohols, like ethanol, the C-H bonds are sp3 hybridized, with the 0-

H again being close to the same hybridization. Similar to water, it can form hydrogen

bonds between alcohol molecules, but generally no more than two hydrogen bonds can

form (each oxygen acting as a proton donor and as an electron acceptor). Linear

polymers of 5-7 molecules (or less for sterically hindered alcohols) are formed, with

lifetimes on the order of 100" to 10-9 seconds (Magat 1959). It is clear that hydrogen

bonding has a significant effect on the properties of alcohols, but not in the same way as

water, in which increasing hydrogen bonding leads to more cavity formation, or an

"openness" of structure. Franks and Ives (1966) consider an 80% mole fraction

ethanol/water mixture (similar to the concentrations used in cosolvent flooding processes)

and note that the number of "moles" of hydroxyl group per mole of liquid phase for pure

water, the mixture, and pure ethanol (EtOH) are 2, 1.2, and 1, respectively. Even more








significant are the concentrations of protons available for hydrogen bonding in these

liquids 111, 24, and 17 moles/1 (Franks and Ives 1966), as shown in Figure 2-1.


0.2 0.3 0.4 0.5 0.6
Mole Fraction Ethanol


0.7 0.8 0.9 1


Figure 2-1. Graph of data from Franks and Ives (1966), relating concentration of
hydrogen bonds to volume fraction of ethanol.



It is therefore much more difficult for a hydrophobic solute like PCE to enter into

this network at lower mole fractions of EtOH. This may account for negative deviations

in log-linear behavior of the solubility of PCE at lower EtOH fractions (Morris et al.

1988). Thus, it takes higher concentrations of EtOH molecules to form their own

network of hydrogen bonded polymers, that consist of a larger area of hydrophobic

properties, to which PCE can intermolecularly bond.

PCE (C2C14) is a symmetric molecule, therefore non-polar. However, the four C-

Cl bonds are locally very polar, and can thus lead to dipole-dipole intermolecular bonding

with other molecules. This can explain why PCE has a solubility in water (150 mg/l; (Lide


0 0.1








1996)) higher than a non-polar molecule with lower localized polarity, like hexane (11

mg/l; (Lide 1996)). However, water, having all polar characteristics within the molecule,

is not a similar environment for a non-polar solute to enter. The hydrogen-bonding

network decreases this possibility further. Hence, the relatively low solubility. PCE is

completely miscible with EtOH, due to decreased hydrogen bonding (as compared to

water) and the presence of a hydrophobic portion of the EtOH molecule, which leads to

strong dispersion forces between the two. Additionally, dipole-dipole forces are present

between these two compounds.

Solubility of Hydrocarbons into Water/alcohol Mixtures and its Relationship to Amount of
Cosolvent

An ideal solution can be defined as one that does not deviate from Raoult's Law

(Atkins 1994):


Pa =aPa, (2-1)

where pa [ML-'T2] is the vapor pressure of a in the liquid (binary for our purposes), x, is

the mole fraction of a in the liquid, and pa is the vapor pressure of the pure liquid a.

Using Raoult's Law, for an ideal solution:

a = l +RTInx,a, (2-2)

where a [ML2T2moles-'] is the chemical potential of a in the liquid, /a* is the chemical

potential of the pure liquid a at standard state, R [ML2T 2moles'degrees"'] is the universal

gas constant, and T [K]is the absolute temperature. The chemical potential of substance a

expresses how the free energy of the system changes as a is added (Atkins 1994). As can

be seen from Equation ( 2-2), how this potential changes depends on the composition of








the system (xa). The chemical potential, hence the free energy of the system, is held to this

relationship for an ideal solution. Physical properties like solubilization and IFT that

depend upon the free energy of the system are therefore strongly linked to this

relationship, often exhibiting log-linear behavior with composition, especially in more

dilute solutions (Chen and Delfino 1997; Morris et al. 1988). Adding alcohols to water to

enhance the solubility of contaminants during remediation processes is one example of

where this miscibility relationship is beneficial. However, volume fractions ofcosolvents

used are generally high (70-90%) (Annable et al. 1996) and deviations from ideal solution

behavior are often observed.

Solubility estimation methods most commonly used ("mixed solvent solubility

estimation methods") assume that the solvent molecules are randomly mixed. Therefore,

deviations from these models (in a positive sense) indicate that in organic/solvent water

systems the solvent molecules are not randomly mixed. Increased deviations from random

mixing with water occur as cosolvent molecular size increases and hydrogen bonding

capability decreases (Dickhut et al. 1991). This is due to cosolvent self-interaction

increasing, providing a more desirable environment for hydrophobic solutes in aqueous

solution, and decreased hydrogen bond "networking" allowing the solute to move more

freely and find more desirable zones.

Non-ideal binary monohydric alcohol and water mixtures have been studied for

quite some time. Use of alcohols as industrial solvents has also prompted more detailed

studies. Solubility relationships of various hydrocarbons in these mixtures to the amount of

alcohol present have been determined (Dickhut et al. 1989; Groves 1988; Pinal et al.

1990). The most prevalent relationship used is log-linear.








It has been shown that a 70% ethanol/18% water/12% n-pentanol mixture can be

used to solubilize various hydrocarbons from contaminated media (Annable et al. 1996;

Rao et al. 1997). Binary methanol, ethanol and isopropyl alcohol/water mixtures have

also been used (Augustijn et al. 1994; Brandes 1992; Imhoffet al. 1995). Typically, high

volume fractions (>80% v/v) of alcohol are used. Specific studies on the superiority of

these mixtures in cosolvent flushing applications could not be found. However, as the

fraction of cosolvent increases, the aqueous solubility of NAPL constituents increases

(Brandes and Farley 1993). However, monohydric alcohols, like ethanol, and water

binary mixtures have been shown to behave non-ideally. Simple relationships like the log-

linear model (Li et al. 1996; Yalkowsky et al. 1976) may not be applicable over the large

volume fraction range possible for the use of cosolvents.

Log-linear relationship

The log-linear model is used quite frequently when describing cosolvent systems.

Yalkowsky (Banerjee and Yalkowsky 1988) and others have shown that in solutions of

appreciable (>10% v/v) cosolvent, the molar solubility of a non-polar solute can be

approximated by:


log Sm =fclog Sc + (l-fc)log Sw, (2-3 )

where Sm, Sc, and Sw are the solubilities of the non-polar solute in the mixture, pure

cosolvent, and pure water, respectively, andfc is the cosolvent volume fraction. This

equation neglects solute-solvent interactions and is based upon the accepted linear

relationship between the free energy of solution and the solute surface area (Valvani et al.

1976). The model is exactly obeyed only as the solvent components become identical (Li








and Andren 1995). The log-linear model assumes the water and cosolvent behave as two

distinct entities and neglects the interaction between them. This model fails when

interactions between solvent components are strong and differ from interactions among

molecules of individual pure components and when the solute strongly prefers one solvent

component over the other (Li and Andren 1995). Over the total volume fraction

spectrum, deviations obviously occur mostly at both extremes, where one of the solvents

is present at very low concentrations and cannot avoid interaction with the other solvent.

At very low cosolvent volume fractions, the solute solubilized will only be influenced by

one cosolvent molecule at a time. Any solubility enhancement will therefore be

proportional to the number of cosolvent molecules present. This cosolvent will be

hydrated in solution, and consequently, it will disrupt the water network structure

(Grunwald 1986). In these situations, one would expect the log-linear relationship that

applies at higher cosolvent fractions to become linear, due to a change in the mechanism

of solubilization (Banerjee and Yalkowsky 1988). This change usually occurs in the range

of 0.1
arrangement of molecules with no tendency to segregate (i.e., an ideal mixture) (Dickhut

et al. 1991). At these low volume fractions, cosolvents are more like cosolutes in

behavior and do not influence the solution in an appreciable way.

For a remediation process, cosolvent volume fractions are typically on the order of

80%; so the minor cosolvent is water. Any operation therefore in the 80 to 100% range

could possibly be in the linear portion of the solubility relationship discussed above. The

primary advantage of the log linear method is its simplicity, which makes it a convenient








tool for estimating solubilities ofhydrophobic chemicals in a variety of aqueous mixtures

(Li and Andren 1995).

Cosolvency power

The relative solubilization enhancement is usually presented as the "cosolvent

power", a (Banerjee and Yalkowsky 1988; Yalkowsky et al. 1976). This cosolvency

power is defined as the logarithm of the ratio of the solute solubilities in pure cosolvent to

pure water, or

a= log Sc log Sw. (2-4)

In some instances the solute may be completely miscible in the pure cosolvent (i.e., PCE in

ethanol) where the use of the "end-to-half- slope" (o0.5) is necessary (Li et al. 1996). This

is defined as

a05 = (log So, log S,)/0.5, (2-5)

where So, is the solubility atf, = 0.5. In combination with Equation ( 2-3), this results in

the expression,

log S = o-0.5 + logS,. ( 2-6)


Other methods for solubility estimation

To account for deviations from ideal or regular solution theory, other methods

have been developed in previous research. These include the Extended Hildebrand (EH)

method, the Excess Free Energy (EFE) method, and the Universal Functional Group

Activity Coefficient (UNIFAC) method.








Extended Hildebrand (EH) method. Hildebrand and Scott (1950) and Scatchard

(1931) introduced regular solution theory to describe solutions that maintain ideal entropy

of mixing, but involve heat change during mixing. This can occur only if the random

distribution of molecules is maintained even in the presence of specific solute-solvent

interactions (Barton 1975). However, solutions of organic compounds in polar solvents

are not regular since significant solvation can occur (Li and Andren 1995). To attempt to

account for deviations from ideal behavior, Martin et al. (1979; 1982) assumed the binary

cosolvent and water mixture is itself ideal, but the ternary (or higher) solution behavior

may deviate from the ideal due to solute(s)-solvent interactions. This method is

represented by the following expression for the mole fraction solubility:

In x, = (T-T.) (qz +,2-2W), (2-7)
RT RT

where

(S. = 8 + z2, +... ), (2-8)


and xj is the mole fraction solubility of solute s in solvents (/=1,2,3..); Asf [ML2T2 moles

'degrees K-'] is the molar entropy of fusion; R is the ideal gas constant; Tand Tm are the

absolute system and melting temperature; qs [L3moles'] is the molar volume of the solute;

zj is the solute free volume fractions of the solvents in the mixture; 8s, and j are the

Hildebrand solubility parameters for the solute and each solvent, respectively; and W [ML"

'T2] is the interaction energy in those systems with strong solute-solvent interactions.

This estimation technique requires the determination of the solute specific interaction








energy, W. The EH method is most useful in situations in which solubility determinations

for a specific solute are desired, as in this study (Dickhut et al. 1991).

Excess free energy (EFE) method. The EFE method (Williams and Amidon

1984b) accounts for some deviations from the log-linear prediction. Non-ideal solution

behavior is attributed to excess free energy from n-body interactions in the given system.

By ignoring four-body and higher order interactions, the model is reduced to a three-suffix

equation for the mole fraction solubility of a solute in a mixed solvent. For a ternary

system (solvent, cosolvent and solute) this model is given as:

Inxix = Inx,, +z2 Inx, -A,-21z2(2z 1)(q, /q) +A-,12z2(q2 /q2)+Csz 2, (2-9)

where A,, and A2, are the binary solvent-cosolvent interaction constants; qi is the molar

volume of the species i; and C, is the ternary interaction constant. This method requires

vapor/liquid equilibrium data (at the system temperature) to derive the solvent-cosolvent

interaction constants. However, A,, and A2, can also be calculated using UNIFAC data.

The ternary interaction constant, C,, requires, in practice, solute solubility measurements

over a range of cosolvent fractions to determine this parameter (Williams and Amidon

1984a). This method is less acceptable because it relies on the experimental solubility data

to determine the parameters needed for mixed solvent solubility estimations (Dickhut et al.

1991). Furthermore, specifically for the systems studied herein, the solute (PCE) is

completely miscible in one of the solutes (ethanol or isopropyl alcohol). Therefore, the

mole fraction solubility of PCE in ethanol is undefined. This eliminates this model as a

tool to predict PCE solubility in these systems.








UNIFAC method. The UNIFAC method uses the sizes and shapes of molecules in

the solvent mixture and the interactions between the functional groups they contain to

account for the non-ideal solution behavior (Fredenslund et al. 1977). Its fundamental

assumption is that the chemical behavior of a fluid is due to the sum of contributions made

by the molecules' functional groups. This method calculates the activity coefficients (yi)

based on the functional groups of a molecule of species i and their interactions with other

groups in the system. It is given as:



In x = ](T T,) In ysmr, (2-10)
RT

where

In y = Iny C + ln yR (2-11)

and y,,m, is the UNIFAC activity coefficient of the solute in the solvent mixture, f is the

combinatorial fraction and f is the residual fraction. The combinatorial fraction reflects

the size and shape of the molecules, and the residual fraction depends on the functional

group interactions. Parameters for each functional group, such as volume and area

parameters (normalized van der Waals volume and surface areas) and parameters of

interaction with other functional groups (obtained from phase equilibrium experimental

data) are put into a series of equations to calculate f and f. The UNIFAC method is

limited by the experimental data used to determine its parameters in Equation ( 2-11),

some of which have been updated since the inception of this method (Hansen et al. 1991).








Choice of solubility estimation method

Whatever the method finally chosen to best represent PCE/cosolvent/water

behavior, some general conclusions have been made in the literature. As the cosolvent

molecular size decreases, the hydrogen bonding capability increases. This leads to

significant non-ideal behavior. This indicates that in these types of systems (especially

ethanol and isopropyl alcohol) the solvent molecules are not randomly mixed. Self-

interaction among organic solvent molecules increases and is hydrophobic. This creates a

more desirable environment for hydrophobic solutes, increasing solubility higher than

expected in ideal solvent mixtures (Dickhut et al. 1991). It is generally accepted that no

single model is able to accurately predict hydrophobic species solubility in any system,

especially over a wide range of environments, such as increasing cosolvent fractions. Until

one such model is developed, use of the best resulting fit to the experimental data

produced will have to be sufficient.

If solubilization relationships are characterized, it may be possible to use a lower

fraction of alcohol and have similar NAPL solubilities, by selecting a better cosolvent

mixture. Given economic, hydraulic, and environmental factors, even a cosolvent that

results in NAPL solubility slightly less than a possible competitor could potentially be a

viable candidate in the field. This is especially important if mobilization of NAPL is

strongly undesirable. Interfacial tension is the key parameter that can determine whether

mobilization will occur or not, and is discussed below.

Interfacial Tension of Ternary Alcohol/water/PMOS Mixtures

Solubilities of hydrophobic organic compounds (or Partially Miscible Organic

Substances, PMOS) are strongly dependent upon the nature of the interfaces between the








two phases in organic/aqueous phase systems. The cohesional and adhesional forces of

the molecules of a liquid-liquid system are the factors that determine the extent to which a

given solute is soluble in a given solvent. It is these factors which also determine the

magnitude of the interfacial tension (IFT) (Donahue and Bartell 1958). IFT is a critical

parameter necessary to characterize this interface and to characterize non-homogeneous

liquid systems (Glinski et al. 1994). It is often necessary to know the IFT to predict the

fate of organic liquids. IFT is defined as the change in Gibbs free energy per unit change

in interfacial area.


T,P (2-12)


Accurate estimation of this parameter is critical to predict behavior of liquid phases

during field remediation operations. To predict IFT, semi-empirical formulae are used.

These include Antonov's Rule (Antonov 1907), and the methods of Girifalco and Good

(1957), Donahue and Bartell (1958), and Fu (1986).

Relation to amount ofcosolvent

Consider only two dissimilar liquids. The IFT between the two liquids results from

an imbalance of forces acting on molecules at the interface. The IFT value is a function of

the interaction between not only the molecules of the two different liquids, but also the

molecules of the individual liquids themselves. The magnitude of the IFT reflects the

relative difference between intermolecular forces within the bulk liquid and the

intermolecular forces between the liquids (Demond and Lindner 1993). This can be

extended to more than binary systems, with increasing intermolecular interactions to

consider.








As a cosolvent is added in increasing proportion to an aqueous mixture the

interfacial tension between it and a separate organic phase decreases. This decrease is due

to the increasing similarity between the two phases. The cohesional forces within the two

phases are high when the phases are dissimilar, resulting in excess free surface energy, or

interfacial tension. As cosolvent is added to the aqueous phase, these cohesional forces

decrease, decreasing the IFT. At the same time, the increasing similarity between the two

phases increases the mutual solubility of the solutes within each phase. The historical

literature has recognized this relationship between solubility, IFT, and the amount of

cosolvent added. The major estimation techniques are described below.

Different interfacial tension prediction methods

Method ofFu et al. The only method at the present time to estimate IFT for

ternary (or quaternary) systems is the one developed by Fu et al. (1986). It is derived

from the thermodynamic equation developed by Shain and Prausnitz (1964)


RT yvxf
'ow= R-ln( (2-13)
A,s T',x,

where R is the universal gas constant, T is the absolute temperature, y" and y, are the

activity coefficients of component i in the interfacial and bulk phases, respectively, x: and

x, are the mole fractions of component i in the interfacial and bulk phases, respectively,

and A is the partial molal cross-sectional area of component i in the interfacial phase

[L2mole'1]. This can be applied to any mixture containing any number of components, as

long as values for the thermodynamic parameters are known (or estimated). This method








makes a couple of simplifying assumptions that lead to the final expression for calculating

the interfacial tension of a ternary mixture.


KRTX
Yow = Aw exp(X)(xq, +x2q2 +x3,q3) (2-14)

where K is an empirical constant (relating the number of molecules in the interfacial phase

to the ratio of the molecular cross-sectional area to its surface area);
9
X= -In(x,+x2+x3r); A, is the van der Waals surface area of a standard segment (2.5 x 10

cm2/mol, (Abrams and Prausnitz 1975)); xi is the mole fraction of the ith component in the

phase where that component is a solute, x3, is the mole fraction for the third component in

the phase where it is richer; and qi = Aw/Awo, where Awi is the van der Waals surface area

for component i (qi is the pure component area parameter defined by the UNIQUAC

model) (Abrams and Prausnitz 1975).

The value ofK is suggested by Fu et al. (1986) to be 0.9414, based on a linear

regression of 54 binary systems. The average relative deviation from the measured IFT

was 23%. However, if only data with IFT greater than 10 dyne/cm are considered, this

deviation decreases to 6.3% (Fu et al. 1986). With the value of K taken to be 0.9414, Fu

et al. tested 23 ternary systems and the average relative deviations were 17.9% for

mixtures with IFT > 5 dyne/cm, and 11.5% if only those data points with and IFT > 10

dyne/cm are considered. However, this may be a significant, especially if trying to predict

a value during cosolvent flooding operations when IFTs can decrease well below 10

dyne/cm. Additionally, for some systems either x,3 or x,, (mole fraction of the third








component in the richer or poorer phase) can be chosen to obtain a better correlation.

The exact cause of this phenomenon is not clear.

Donahue and Bartell. Donahue and Bartell (1958) relied on the fact that

miscibility and IFT reflect the same intermolecular forces. They discovered there was a

linear relationship between the IFT of liquid pairs and the log of the sum of mutual

solubilities in binary systems.

Yow = a b n(So, + Sw(o) (2-15)


where a and b are empirical constants (regressed intercept and slope, respectively), SoM is

the mole fraction solubility of the organic in water, and Sw,) is the mole fraction solubility

of the water in the organic. For higher order systems it is obvious that this method cannot

be applied directly. However, an additional relationship of the IFT being a function of the

mutual solubility of the cosolvent alcohol and the NAPL is still possible.

Others. The oldest method still in use to estimate interfacial tension is Antonov's

rule (Antonov 1907). It is stated by the relationship



Yow = YW(O) YO(w>, (2-16)

where Yow is the estimated IFT between the organic liquid and water, YW(O) is the surface

tension of water saturated with the organic, and o(w>) is the surface tension of the organic

saturated with water. As this is for a binary system only, its applicability to cosolvent

systems is unfounded. Furthermore, use of this method for PCE systems has been shown

to be inaccurate (Donahue and Bartell 1958).








Girifalco and Good's method is derived on the basis of the work necessary to

separate the liquids at their interface. They assumed that the potential energy function for

the interaction across the interface was described by the geometric mean of the IFTs

(Demond and Lindner 1993). This method states that the IFT of a binary system is:


Yow = Yo + Yw= (24(orw)'2, (2-17)

where Q is the interaction parameter describing the similarity ofintermolecular force

between the two liquids, and Yo and ,w are the interfacial tensions between the oil phase

and air, and water and air, respectively. The value of O ranges from 0.5 to 1.15 for

organic liquid water systems, with lower values associated with dissimilar liquids and

higher values associated with similar systems (Demond and Lindner 1993). Again, this is

a method applicable to only binary systems.

Choice of IFT estimation method

Antonov's rule and Girifalco and Good's method are either too simplistic (lack a

theoretical basis) or do not perform well, respectively (Demond and Lindner 1993).

Girifalco and Good's method has a theoretical base, but is applicable only to binary

systems. The most accurate methods appear to be those ofFu et al. (1986) and Donahue

and Bartell (1958) (Demond and Lindner 1993). Donahue and Bartell's method performs

better if measured mutual solubility data are available. Fu's method is preferred in cases

where the mutual solubility data must be estimated. However, both of these methods have

lower accuracy for systems where the IFT is less than 10 dyne/cm (Demond and Lindner

1993). This region of IFTs is where cosolvent flushing schemes will transition from

maximizing solubility or mobilization of the contaminant. Furthermore, Fu's method is the


I








only one to directly apply to ternary systems. This method or a more direct empirical

correlation is favored in this study.

Relation of IFT to Solubility of Organic Solute

As mentioned previously, there are various methods that can estimate the

relationship between the solubility of a PMOS into a cosolvent/water phase and the

amount ofcosolvent added. Correspondingly, a relationship exists (Fu's method) between

the IFT and the mole fraction solubility of a third solute (cosolvent). Therefore, with

proper connection between the two relationships, one should be able to determine the

dependence of the solubility of a PMOS with the equilibrated interfacial tension of the

system. In a subsurface system, this type of direct relationship between these important

parameters will allow quick comparison of enhanced solubility with the predicted IFT. If

the remediation technique is designed to solubilize and not mobilize a DNAPL plume,

there could be situations where driving to increase the solubilization of the DNAPL would

result in significant lowering of IFT, and hydraulically move the system into mobilization

regimes. If mobilization is a concern, a lowering of the cosolvent fraction a given amount

may safely increase the IFT and only impact solubility by a small factor. This could lead to

only a few additional pore volumes of the flushing fluid, or fractions thereof, used to

obtain similar mass recovery of the DNAPL, while ensuring less risk of mobilization.

Materials and Methods


All chemicals were obtained from Fischer Scientific and were chromatography

grade, with the exception of ethanol (EtOH). 99.9% EtOH was obtained from Ultra-

Chem Corporation. Various mixtures of cosolvent and water were made in 40 ml EPA








vials with Teflon-lined screw caps. The resulting mixtures were defined by the volume

fraction of cosolvent (fC) in the aqueous phase, which were calculated from the amounts of

water and alcohols that were measured separately and then combined in preparing the

solvent mixtures (Li and Andren 1994). Ten milliliters (ml) of PCE and 10 ml of the

cosolvent mixture was added to each vial, so that the initial ratio of aqueous to NAPL

phases was 1:1. The vial was then placed in a mechanical rotator and rotated at room

temperature (250.5 oC) for 48 hours, removed and allowed to settle for 24 hours. A 1 to

2 ml sample of the aqueous phase was then taken and placed in GC autosampler vials and

crimp sealed with Teflon lined caps. The remaining fluid in each vial was then carefully

poured into a straight-walled glass crystallization dish (50 mm diam. x 35 mm depth),

which had been previously cleaned for IFT measurements using the procedure of Wilson

et al. (Wilson et al. 1990). After a few minutes of settling, the IFT was measured with a

Du Nuoy ring tensiometer, Fisher Scientific Model 21 Tensiomat. The solubility ofPCE

was determined by injection of 1 jl of the equilibrated aqueous phase into a Perkin-Elmer

Autosystems GC. The GC column used for this study was a 30 meter x 0.530 mm, 3 Pm

fixed phase, DB-624 column, manufactured by J&W Scientific. Column conditions were

set at 350C for 2.5 minutes, then ramped up 6 degrees per minute to 950C. The carrier

head pressure was set at 4 psig. A flame-ionization detector (FID) was used in the

analysis for PCE. Although the detection for PCE is much improved using an electron

capture detector (ECD), the concentration range of interest was from 150 ppm to 20,000

ppm. With these higher concentrations and the wide range of possible results, the linearly

responding FID was chosen over the ECD. Additionally, simultaneous analysis for other

components (non-halogenated) was also possible.








Results and Discussion


Initial data collection has been conducted for various cosolvent/water/PCE

mixtures. Results of solubility measurements support the non-ideality of alcohol/water

mixtures. The results show a sigmoidal type relationship of solubility to the original

volume fraction ofcosolvent (Figure 2-2).

Log-linear Solubility Estimation

Ethanol

Using the relationships described in Yalkowsky et al. (1976), a cosolvency power

for EtOH was determined to be o .5 = 3.73. This "end-to-half-slope" cosolvency power is

applicable when the solute (PCE) is completely miscible with the cosolvent (ethanol), and

is calculated by Equation ( 2-5). The cosolvency power is then used as the linear slope in

Equation ( 2-6). The resulting log-linear prediction is shown in Figure 2-2 for reference.

Solubility of PCE in low volume fraction EtOH mixtures (f < 0.35) is below the log-linear

predictions. This is possibly due to an insufficient quantity of EtOH to fully influence the

mixture as a cosolvent and the strong hydrogen bonding network of water still present, as

discussed above. Furthermore, at these low EtOH fractions, the PCE solute molecule may

only be influenced by one cosolvent molecule at a time (Li and Andren 1995).

Correspondingly, at higher volume fractions (f > 0.5) PCE solubilities are slightly above

those predicted for the log-linear relationship. Ethanol present at high fractions

overwhelms the water molecules and the cavity network structure so that hydrogen

bonding is no longer a large factor (Franks and Ives 1966). Increases at higher, could be

due to the self-alignment of the ethyl groups of ethanol molecules, presenting a more









favorable organic "zone" for PCE partitioning, and breaking the three-dimensional

hydrogen bond network of water completely. PCE favors solubilization in alcohols much

more than water, and this strong preference leads to failure of the log-linear method (Li

and Andren 1995).


1000000




100000


1

I1W
0
u,
U


1000


0 10 20 30 40 50 60 70
Volume % of Cosolvent

ethanol ethanol (2) *- isopropanol


80 90 100


Figure 2-2. Solubility of PCE as a function ofcosolvent volume fractions (initial phase
volumetric phase ratio 1:1).



Isopropanol (IPA)


IPA shows increased solubility of PCE as compared to EtOH. The decreased

polarity of the IPA molecule (relative to EtOH), increase in hydrophobicity, and the

decrease in hydrogen bonding due to steric hindrances allows for increased amounts of

PCE to solubilize into the cosolvent mixture. The resulting cosolvency power is








approximately 4.13, an average based on the solubilities of PCE atf, = 0.4 andf = 0.6.

The solubility ofPCE atfEtoH = 0.8 is approximately the same as that at an IPA fraction fc

= 0.7. This example of reduction in cosolvent use can be economically and politically

beneficial in some field scenarios. Typical costs for these solvents are $0.40/lb and

$0.35/lb for ethanol and isopropyl alcohol, respectively (Chemical Marketing Reporter,

1995). Therefore, cost savings can be obvious.

UNIFAC Method

Results of the solubility estimations are plotted with those predicted by the

UNIFAC method and are presented in

Figure 2-3. The UNIFAC method appears to be adequate for describing cosolvent

effect on the solubility of PCE. Large deviations (under predictions) occur at lower

volume fractions for isopropanol, most likely due to the inability of UNIFAC to properly

account for solute-cosolvent/solvent interactions at these lower cosolvent fractions.

UNIFAC estimations improve quickly atfc = 0.2 and differences between actual and

predicted values remain the same as the volume fraction approaches those most likely used

in remediation scenarios. Thus, the method may be adequate for quick approximations in

these systems.

Extended Hildebrand Method

The solubility parameters for the various components are given below in Table 2-1.

It has been reported (Martin et al. 1982) that when the range of solubility parameters of

the solvent pair approaches the solubility parameter of the solute, the curve may bow

sufficiently that a log-linear expression of solubility on volume fraction of cosolvent no










1.E+00



I.E-01 O



1.E-02 -



1.E-03


4*J A--


0.1 0.2 0.3 0.4 0.5 0.6
Initial volume fraction of cosolvent


0.7 0.8 0.9


* Ethanol Data e IPA Data O UNIFAC Ethanol o UNIFAC IPA


Figure 2-3. Comparison of Measured Solubility Data and those predicted by the UNIFAC
Method.


Table 2-1. Solubility parameters for study components (Barton 1975)

Component Solubility Parameter (cal/cm3)

Water 23.4
PCE 9.3
ethanol 12.7
isopropyl alcohol 11.5


longer fits the data satisfactorily. A quadratic or higher polynomial must therefore be used


as required by methods such as the extended Hildebrand method. Thus, the log- linear


approach, even though it is often useful, should be used with caution over a wide range of


0 9


1.E-05 -



1.E-06


i I I I I I I








cosolvent volume fractions (Martin et al. 1982). To apply the extended Hildebrand

approach takes a little more effort, but it usually reproduces the solubility in mixed solvent

systems better over an entire range of solvent compositions.

The log-linear method would seem to apply to such a system as ethanol/water/

PCE, since the solubility parameter of the solute is 3 to 4 units below that of the organic

solvent (ethanol) (Martin et al. 1982). However, as seen in Figure 2-4 below, the

Extended Hildebrand theory predicts the solubility of IPA better than either UNIFAC or

the log-linear method. This is due to the inclusion of solute-solvent interaction, which is

important when the solute (PCE) is more miscible in one of the solvents isopropanoll)

than the other (water). The Hildebrand method is incorrect throughout the entire

cosolvent regime, but improves as the solvent-solvent interaction assumption becomes

more valid as isopropanol becomes the primary solvent, similar to most cosolvent

remediation scenarios.

The main advantage of the extended Hildebrand approach is that it handles solutes

in polar and non-polar systems, whether the solute's solubility parameter is greater than,

less than, or lies between the solubility parameters for the solvent pair (Martin et al. 1982).

Although the extended Hildebrand is widely applicable, some corrections are needed in

various situations. These include a correction factor for the entropy of mixing to account

for the differences in molecular size (Flory-Huggins correction term) and a term for the

additional entropy effects associated with hydrogen bonding substances (Amidon et al.

1974). For water/alcohol solvent systems, this is especially true. Transfers of small

hydrocarbons from nonpolar liquids to water are accompanied by large negative entropies










1.E+00


1.E-01 A


1.E-04 A


1.E -03 ---------------------------------




1.E-05


I.E-OB
1.E-06


1.E-07
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Inital volume fraction of cosolvent

I A IPA Data Hildebrand A Ext. Hildebrand



Figure 2-4. PCE Solubility Prediction of the Hildebrand and Extended-Hildebrand
Theories for the IPA Cosolvent Mixtures.



and small heat effects (Amidon et al. 1974). Alcohols are known to be associated through

hydrogen bonding in the liquid state, with this association decreasing in order of primary,

secondary, and tertiary due to steric limitations (Franks and Ives 1966). Other methods to

improve the solubility prediction of alcohol systems, such as the Molecular Surface Area

approach and the Microscopic Surface Tension (Amidon et al. 1974) have shown only

"good" results.

Williams and Amidon (1984b) described the non-ideality of an ethanol-barbital-

system at low-volume fractions of ethanol as due to greater solute-solvent interactions

than solvent-solvent. This results in solubilities below ideal predictions. Conversely, at








high volume fractions solvent-solvent interactions dominate to result in above ideal

solubility predictions (Williams and Amidon 1984b). This is exactly what occurs in

ethanol and isopropanol cosolvent systems.

Minor cosolvent addition

Results from addition of other less-polar solvents (in small fractions) to try to

increase the solubility of PCE, while decreasing the total amount of solvents in the

mixture, is presented in Figure 2-5. The benefits of this are little to none at all. For

example, the solubility of PCE in a 60% EtOH/30% H20/10% isobutyl alcohol mixture is

just under 100,000 mg/1. This is a total alcohol content of 70%. A cosolvent mixture of

only 70% EtOH/30% H20 results in a PCE solubility of approximately 90,000 mg/l.

Furthermore, the addition of a less-polar solvent may not aid in solubility due to its

partitioning into the DNAPL phase. Here, it does little to improve the aqueous solubility,

but it can cause density changes if significant amounts of solvent partition into the NAPL

phase. This partitioning can also cause swelling of the NAPL, possibly mobilizing

DNAPL due to lower IFTs. These lower IFTs are due to the interface of these systems

becoming surrounded by like molecules in both phases, reducing the tension between

them. Even if there is a slight improvement in the solubility of PCE, the increased

environmental risk of the addition of two solvents to the subsurface and the added

complexity of phase behavior and mobilization possibilities due to reduced IFT are not

sufficiently outweighed.



















A

B


0
o A
A
+ o-


100
0 10 20


40 50
% of Major Coeolvent


60 70 80


EtOH only X EtOH only (2) a IPA only 0 EtOH vd5% IPA + EtOH w/10% IPA
EtOH v5% IBA O EtOH d10% IBA A EtOH w5% POH E EtOH W5%POH (2)



Figure 2-5. Solubility of PCE as a function of various cosolvent volume fractions (initial
phase volumetric phase ratio 1:1)




Interfacial Tension Measurements and Predictions


Interfacial tension measurements agree well with literature values (Imhoffet al.

1995; Pennell et al. 1996b). IFT exponentially decreases as a function of cosolvent

volume fraction (Figure 2-6). IPA IFT measurements indicate that these mixtures have a

stronger response to increases in volume fraction of cosolvent, as compared to the EtOH

mixtures. In addition, over the ranges of economical remediation application (>70% for

EtOH), IFT is fairly insensitive to additional volume fractions of cosolvent. If

mobilization is a concern, then a drastic reduction in IPA fraction may be necessary, with

resulting decreases in solubility being the tradeoff for hydraulic stability. Assuming the


1000000


1000=0


1000









40

35

30

I 25

_20-
0-





5

10
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9


I*EtOH ,IPA


Figure 2-6. Relationship of equilibrated interfacial tension of PCE/alcohol/water ternary
systems as a function of initial cosolvent volume fraction.



appropriate regime is considered, a possible benefit of using IPA over EtOH may be that

similar levels of solubilization may be achieved for smaller volume fractions of cosolvent

(IPA vs. EtOH).

A relationship between the logarithm ofIFT and f was determined and plotted as

Figure 2-7. Data are strongly correlated, with coefficient of determination (R2) values of

0.9978 and 0.9975 for EtOH and IPA, respectively. It is interesting to note that this

correlation involves the volume fraction of cosolvent prior to mixing. This volume

fraction is obviously not the same value after equilibrium has been achieved, especially for

alcohols that can significantly partition into the NAPL phase, such as IPA. Although this





38


100





S10- y = 37.193e-3o63x
R2 = 0.9978






y = 36.17e5.79'
R2 = 0.9975

0.1
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

I* EtOH IPA EtOH+1O%IBAI



Figure 2-7. Logarithmic plot of the IFT of ternary PCE/cosolvent/water mixtures versus
initial volume fraction ofcosolvent. Additional data for addition of 10% isobutanol is
shown for reference.



relationship may have a weak scientific basis when using the pre-equilibrated volume

fractions, the dependence is adequate to use as a predictive tool for field applications. This

relationship is similar to the log-linear solubility relationship as represented by:


In IFT = Qf + In IFTo ( 2-18 )


where 0 is now the "IFT reduction power" of the given cosolvent in aqueous mixtures

and IFTo is the interfacial tension between pure water and NAPL (PCE). By regression of

the data, QEtoH = -3.60 and QIPA = -5.80. This similarity to the log-linear relationship








should not be surprising because IFT is strongly dependent on the mutual solubilities of

the two phases' solutes.

Upon correlation of solubility and IFT (a combination of Figure 2-2 and Figure

2-7), the results indicate a possible method for estimation of in-situ IFTs based upon

solubility of PCE in the cosolvent mixture. This assumes local equilibrium is achieved.

Figure 2-8, showing the logarithm of IFT as a function of the logarithm of the solubility of

PCE, is the result. The largest deviations from a linear relationship occur at very low

solubilities, where remediation technologies are not economically realistic. At higher

solubilities, the prediction is quite close to experimental values and IFT predictions are

within a few percent. The benefit of using such a plot is the direct estimation of in-situ

IFT at the flushing front using the aqueous phase concentration of the given contaminant

determined from extraction wells. Knowledge of this in-situ IFT is critical to determine

the amount of mobilization that is likely occurring. This can be determined by using

relationships developed by Pennell et al. (1996).

Conclusions


Use of log-linear solubility relationships is not a completely accurate method to

predict solubility of PCE in cosolvent mixtures over the entire range of possible volume

fractions. Improved predictions are possible at higher volume fractions of cosolvent.

These predictions may be adequate for estimations necessary for field studies or

remediation efforts. Deviations from the log-linear model are similar to those found in the

literature (Dickhut et al. 1991; Li and Andren 1995) and can be explained by fundamental

theories described in the literature (Franks and Ives 1966). For improved estimation of





40





100








R2R2 = 0.9703


68






0.1
100 1000 10000 100000 1000000
PCE Aqueous Phase Solubility (mgil)
I EtOH IPA




Figure 2-8. Interfacial tension of PCE/cosolvent/water mixtures related to solubility of
PCE in the aqueous phase. Numbers above selected data points indicate initial volume
fraction of cosolvent.



PCE solubilities, the use of the Extended Hildebrand or the UNIFAC model is

recommended. Their added complexity is beneficial to accurate solubility predictions over

the entire range ofcosolvent fractions.

The interfacial tension resulting from various cosolvent mixtures based on the

initial volume fraction of cosolvent leads to an interesting relationship, which is similar to

the log-linear model. An "IFT reduction power" can be determined for each cosolvent,

which quantitatively describes the ability of the cosolvent to reduce the IFT as it is added








in increasing volume fractions. IFT can also be accurately estimated by PCE aqueous

phase solubility, especially in regimes conducive to cosolvent flushing. Due to the

dependency of PCE aqueous phase solubility upon the aqueous and DNAPL phase ratio, it

should be clarified that this approach is limited. Incorporating this predictive information

into a trapping number relationship (Pennell et al. 1996b) will allow better prediction of

regimes with solubilization, yet without mobilization of the NAPL/DNAPL phase. This is

the topic of the next few chapters.

A historical conclusion remains appropriate:

"The best advice which comes from years of study of liquid mixtures is to
use any model in so far as it helps, but not to believe that any moderately
simple model corresponds very closely to any real mixture" (Scatchard
1949)













CHAPTER 3
MOBILIZATION OF RESIDUAL PERCHLOROETHYLENE DURING COSOLVENT
FLOODING


Introduction


Until recently, remediation technologies for the removal of organic contaminants

from subsurface environments focused on the pumping of groundwater and subsequent

treatment of these streams. Risk reduction to possible receptors was the driving force

behind these actions. However, due to solubility limitations, remedial action time-scales

are long and expensive for such treatment. Sources of contamination are very slowly

removed due to natural solubilization. In the last few years, research efforts and

technology demonstrations have become more focused on source removal. These include

surfactant flooding and cosolvent flushing (Annable et al. 1996; Falta et al. 1997; Fortin et

al. 1997; Jawitz et al. 1998b; Lunn and Kueper 1997; Pennell and Abriola 1996; Pennell et

al. 1994; Pope and Wade 1995; Rao et al. 1997). Although these techniques tend to be

more aggressive and have higher initial costs, the removal of a long-term source is

beneficial from risk reduction, economic, and legal perspectives.

Of these recent technologies, methods that increase the solubility of the

contaminant into a mobile flushing phase have shown promising results (Annable et al.

1996; Fountain et al. 1991). Two general types of chemicals are used to enhance

contaminant solubility: surfactants and cosolvents. Both increase the aqueous phase

solubility of the contaminant by up to five orders of magnitude, thereby accelerating








remediation efforts. The resulting faster cleanup times are desired to decrease health risks

to potential receptors and to reduce project operations and maintenance costs (Sillan

1999).

These processes also reduce the interfacial tension between the aqueous and

organic phases. This reduction can drastically change the force balance keeping the

organic phase trapped in the soil pores rather than being forced out due to the advective

flow of the flushing phase. This possible movement of the organic phase has been labeled

'mobilization'. Correspondingly, the residual NAPL left behind after any flushing action

designed to reduce the NAPL saturation is labeled as being 'entrapped'. The process itself

is termed 'entrapment'. Literature related to these processes is large, yet incomplete in

many aspects, since the mechanisms are complicated by interrelated properties, including

complex formation pore structure, fluid properties, and applied conditions. In addition,

the variability of the media and fluids is so great that most generalized conclusions have

limited applicability (Stegemeier 1977).

Mobilization of oil for the purpose of Enhanced Oil Recovery (EOR) has been

studied for a number of years, by several research communities (Lam et al. 1983; Moore

and Slobod 1956; Morrow 1987; Morrow et al. 1988; Morrow and Songkran 1981; Patel

and Greaves 1987; Ramamohan and Slattery 1984; Taber 1969). This research focused

primarily on the use of surfactants to decrease the interfacial tension and mobilize the

entrapped oil phase, with efficiency increased by use of a polymer flood behind this bank.

In fact, the first patent issued to cover the use of surface-active materials as an aid to the

water flooding of petroleum reservoirs was awarded in 1927 (Atkinson 1927). This

concept and the conclusions resulting from the associated research has been more recently








applied to the field ofsurfactant and cosolvent flushing (Annable et al. 1996; Augustijn et

al. 1997; Pennell et al. 1996b). Taber (1981) recognized the tendencies of the research

and oil recovery communities to use high quantities of alcohols as "cosurfactants" in

flushing formulations. He noted that although alcohols are expensive, "the potential

advantages for oil [or NAPL] recovery are so great that future research may continue to

examine the possibility of using alcohols as the main slug material for some processes."

Earlier research applied to EOR focused on the relationships between viscous forces of the

flushing fluid and the capillary pressures associated with holding residual oil in the pore

structure (Stegemeier 1977; Taber 1969; Taber 1981). Later research amended these

relationships to include not only viscous and capillary forces, but forces associated with

buoyancy effects (Morrow et al. 1988; Morrow and Songkran 1981; Ng et al. 1978). In

most historical research on this topic, buoyancy forces were neglected, or the phases

chosen so that their phase densities were nearly identical (Pennell et al. 1996b). These

buoyancy effects can become significant as density differences between phases become

large, especially when applied to chlorinated hydrocarbon contaminant systems. These

mobilization and entrapment relationships developed will be defined below.

Attempts to change the balance of forces and permit an aqueous flushing phase to

release or displace a NAPL effectively may be classed into three broad and often

overlapping categories. These are attempts to (1) change wettability, (2) change oil-water

interfacial tension, or (3) remove the interface completely via miscible flooding (Taber

1981). The interplay of each of these processes is so great during cosolvent flooding that

this operation cannot be put solely into one or the other category. However, any

cosolvent remediation scheme employed today can be classified via the main NAPL








displacement process desired. These are either complete solubilization or mobilization of

the contaminant. This is not to say that the secondary process is avoided at all times.

Again, the forces that are in action during these operations do not allow such segregation.

For the sake of discussion purposes, these two categories are used below.

Solubilization vs. Mobilization

Increased solubilization of contaminants occurs when the aqueous phase becomes

more similar in polarity to the organic phase. When two phases are dissimilar in polarity, a

tension develops at the interface causing the two phases to remain separate. As modifiers

(such as cosolvents) are added to the system, the two phases become more similar,

solubilization is increased, and the interfacial tension (IFT) is reduced. If enough modifier

is added, the IFT can be decreased to very low values, and ultimately to zero, at which

point the two phases are miscible. It is very low IFT regimes where mobilization of the

organic phase can result (Pennell et al. 1996b). This is because the rate of solubilization

may not keep pace with the lowering of IFT, resulting in high, mobile DNAPL saturations.

The excess free phase organic can now move as a separate phase under the reduced IFT.

If the organic contaminant is denser than water (DNAPL), such as perchloroethylene

(PCE), mobilization can lead to movement of contaminants to deeper aquifers. Hydraulic

controls during remediation may reduce the chance of downward mobilization.

In some instances, mobilization of the NAPL is favored, especially for an LNAPL.

However, a question developing in the field ofin-situ flushing ofDNAPLs, is the whether

to flush under cosolvent (or surfactant) conditions which encourage mobilization of the

DNAPL plume or simply to enhance solubilization of the DNAPL contaminant into the

flushing mixture. In some situations, one may be more favored over the other. Predictive








capabilities allowing engineers to better understand the regime in which they desire to

remediate would be beneficial. An improved understanding of what occurs at the

transition between solubilization and mobilization regimes is desired.

Remediation of residual NAPL by contact with a flushing alcohol-rich solution is a

complex process. During cosolvent flooding both solubilization and mobilization of the

NAPL can occur. Mobilization occurs due to a variety of hydrologic and physical

parameters. A NAPL globule is displaced when the IFT is reduced to an extent that the

forces created by the presence and motion of the continuous aqueous phase and buoyancy

is sufficient to overcome capillary forces holding the NAPL globule in place (Lam et al.

1983). In studying the process of mobilization, complexities arise because the trapped

NAPL phase and the cosolvent containing aqueous phase are not in chemical equilibrium

and mass transfer occurs from one phase to the other. Hirasaki (1980) has discussed some

of the many non-equilibrium phenomena that can contribute to the mobilization process

(Lam et al. 1983). To isolate the effects of reduction of IFT on mobilization of PCE, soil

column experiments were conducted with the influent cosolvent phase equilibrated and not

equilibrated with PCE. Furthermore, solubilization of a partitioning cosolvent such as t-

butyl alcohol (TBA) into the NAPL can cause density reduction; hence, a volumetric

swelling of the NAPL. Severe swelling in itself may cause mobilization (Lam et al. 1983).

This will specifically be addressed in a later chapter.

While interfacial tension (IFT) is critical, it is not the only parameter governing

mobilization. Relationships have been established and applied to surfactant use in porous

media (Pennell et al. 1996b). These relationships describe the amount of NAPL removed

(or remaining NAPL saturation) from a given media via mobilization as a function of a








dimensionless "trapping number", which includes contributions from viscous, capillary,

and buoyancy forces, as described below.

The Trapping Number Relationship

To illustrate the interplay of viscous and buoyancy forces on the displacement of

an organic liquid in two-dimensional domains, the relationship of the trapping number

developed by Pennell et al. (1996b) can be used. Other authors have arrived at similar

relationships, which linearly combine a "capillary number" and a "bond number" (Dawson

and Roberts 1997). The Pennell study investigated the influences of forces on the

mobilization of residual PCE during surfactant flushing. The balance of forces was in

terms of two dimensionless numbers the capillary and Bond numbers.

The capillary number is defined in terms of aqueous flow within a pore, and relates

the viscous to the capillary forces:


N =qW
N = cos. (3-1)
Y, cos9 o

where q, [LT'] is the Darcy velocity of the aqueous phase, pw [MLI'T'] is the dynamic

viscosity of the aqueous phase, ,ow [MT2] is the IFT between the organic liquid and

water, and 0 is the contact angle between the NAPL globule and the pore wall (usually

assumed to be zero for low IFTs situations).

The bond number represents the ratio of buoyancy to capillary forces. It is

represented by









NB = Apgkko (3-2)
NB cos .

where Ap is the density difference between the two liquids [M L3], g is the gravitational

constant [LT2], k is the intrinsic permeability of the porous medium [L2], and kw is the

relative permeability for the aqueous phase.

A total trapping number (NT) was developed that relates viscous and buoyancy

forces to the capillary forces acting to retain organic liquids within a porous medium

(Pennell et al. 1996b). For vertical flow, N, is the sum of the two dimensionless numbers,

the capillary number (Nc8) and the bond number (NB):


NT = INca + NB. (3-3)

In the case of horizontal flow the trapping number is:


NT= 4N + (3-4)

When the trapping number is exceeded, the combination of viscous and buoyancy

forces exceeds the capillary forces holding the NAPL globule within a given pore. This

excess force will cause the globule to physically move through that pore. In Pennell's

(1996b) laboratory studies, there is not a sharp point when mobilization begins, but rather

a sloping curve when PCE saturation is plotted against the logarithm of the trapping

number. This is due to small anisotropies within the "homogenous" sand columns used

(Pennell et al. 1996b). Researchers have observed that small-scale heterogeneities might

lead to locally high residual DNAPL saturations that are more easily mobilized than

DNAPL residuals in homogenous media (Imhoffet al. 1995; Padgett and Hayden 1999).








As demonstrated by Pennell et al. (1996b), these relationships can be used to

predict the soil, hydraulic and IFT conditions required for the onset of PCE mobilization.

Their study using surfactants indicated that ultra-low IFTs (<0.001 dyne/cm) are not

required to induce mobilization of PCE in unconsolidated porous media. Therefore,

predictive capabilities in low IFT ranges (0.1 to 10 dyne/cm) would be beneficial, when

considering cosolvents. Their results indicate that the value of NT should be less than 2 x

10- to minimize the potential for NAPL mobilization. They also concluded that NAPL

mobilization is a more efficient recovery process than micellar solubilization. Finally,

comparison of data from Pennell et al. (1996b) and historical data showed that the

trapping number is applicable to systems with or without significant buoyancy effects. As

mentioned previously, the Pennell study was conducted using surfactant solutions. To

date, no reference has been found in the literature that has generated complete

mobilization curves using cosolvents in simulated porous media. Padgett and Hayden

(1999) used the same mobilization relationship. However, their focus was the onset of

mobilization ofPCE via ethanol flushing in varying heterogeneous media. It is critical to

use the total trapping number analysis when selecting surfactant formulations to minimize

NAPL mobilization (Pennell et al. 1996b), but it is proposed this can be extended to

cosolvents as well.


Study Objective

The objective of this study was to conduct soil column experiments similar to

Pennell et al. (1996b) using cosolvent mixtures typically used in the remediation field and

predict mobilization characteristics of PCE using the trapping number relationship.








Comparison of mobilization curves to historical data is desired, as well as possible

differences in surfactant versus alcohol systems, and finally, differences in cosolvents used.

Materials and Methods


HPLC grade PCE (CAS 127-18-4) and isopropyl alcohol (CAS 67-63-0) was

obtained from Fisher Scientific, Fair Lawn NJ. The absolute ethanol (>99.5 %; CAS 64-

17-5) used in these studies was purchased through Spectrum Quality Products, Inc.,

Gardena CA. The water used for the cosolvent solutions and for soil column flushing was

purified through a NanopureTM filtration process, and brought to an ionic strength of 102

M (350 ppm) with calcium chloride. This is published as an average groundwater ionic

strength value (Stumm and Morgan 1981). Stock solutions of cosolvent/water mixtures

were made with varying volume fractions of cosolvent. These solutions were made in 1-

liter quantities using standard volumetric glassware.

GC Analysis

Component solution concentrations were determined via gas chromatography

(GC) analysis. GC analysis was performed on a 30 m x 0.530 mm, 3 pm fixed phase, DB-

624 column, manufactured by J&W Scientific, using a flame ionization detector (FID).

Although the detection limit for PCE is much lower for an electron capture detector

(ECD), ultra-low (ppb) detection was not required for this study as the lowest expected

value was the solubility of PCE in pure water (150 ppm). Additionally, the strongly linear

response of the FID over several orders of response magnitudes made it the desired

choice.








Physical Measurements

Density measurements were performed gravimetrically. Two milliliters of solution

were measured in a gas-tight volumetric syringe and weighed on a precision Mettler

Balance ( 0.0001g). A sample's density measurements were repeated at three times to

ensure accuracy and precision of this technique. Viscosities of solutions were determined

by a Cannon-Fenske Routine Viscometer (Cannon Instrument Company, State College,

PA). A du Nuoy ring tensiometer (Fisher Tensiomat Model 11) was used to determine the

equilibrium interfacial tension of all samples. The lower limit of this instrument is

approximately 0.1 dyne/cm, although IFTs below 1.0 dynes/cm are subject to visual and

experimental error. These values were used in all trapping number calculations, assuming

equilibrium is quickly achieved within the soil column. For strongly partitioning alcohols,

this assumption becomes less valid. This method will tend to underestimate the IFT and

therefore overestimate both the capillary and trapping numbers, since the nonequilibrium

IFT is greater than the equilibrium value (Lam et al. 1983).

Sand Column Preparation

A small-scale glass column (4.8 cm x 15 cm, chromatography column from Kontes

Corporation) was used for this study. All end materials shipped with the column were

removed except for the 30-40 mesh nylon screen. The soil column was incrementally

packed with well-sorted Number 30-40 sand. This sand size was chosen so that the pore

size would be approximately equal to the screen mesh size to avoid entrapment of NAPL,

yet the sand still contained within the column. Vibration of the soil increments was also

performed to improve packing characteristics. Once the column was packed it was

weighed with all necessary column parts attached. The soil mass was weighed by








difference and the internal volume of the column used to calculate the bulk density. Using

the density of silica sand (2.65 g/cm3) and the mass of sand added to the column, the

volume of sand (Vs) can be calculated. The porosity of the soil column is then easily

calculated form the total volume of the column as: 1r = (1-Vs)/Vt. Approximately 15

pore volumes of de-aired water (via vacuum) were then pumped through the column and

the pore volume determined.

PCE Saturation

"Pure" PCE (dyed with 5 X 10-5 M oil-red-o dye, Fisher Scientific, CAS 1320-06-

5) was introduced to the column to establish residual saturations. This dye concentration

has been shown not to significantly affect solubilization and IFT properties (Pennell et al.

1996b; Young 1999). The PCE was introduced in an up flow mode to achieve stable

displacement of water. When PCE appeared at the top of the column, the flow rate was

increased 5 fold to increase PCE saturation (Dawson and Roberts 1997). The flow was

then reversed and 3 pore volumes of water pumped through in a down flow mode to

displace free product PCE, at a flow rate of 5.0 ml/min. The flow was again reversed and

a few milliliters of water pumped into the column to remove PCE held at the influent

screen due to end effects. The resulting PCE saturation (0/oS, was determined

gravimetrically.

Hydrodynamic Parameters

The intrinsic permeability (k) of the porous media was determined by measuring

inlet and outlet pressures during aqueous phase flow. Resistance due to column end

effects and tubing were measured independently using an empty soil column of the same








construction and identical tubing and fitting (Morrow et al. 1988). This resistance was

subtracted from pressure drop measurement over the filled column to determine pressure

drop across the media only. A differential pressure transducer (Cole-Palmer Instrument

Company, Niles IL, 0-5 inches H20 differential transducer) was used to monitor this

pressure difference at various times during an experimental run.

Relative permeability (k,) values were determined again by differential pressure

measurements at various DNAPL saturations. However, these measurements during

initial runs were inconsistent. Subsequently, all relative permeability values were

estimated using van Genuchten parameters (van Genuchten 1980) for the sand medium,

found from Tempe cell testing.

Sand Column Mobilization Studies

Experiments were conducted, similar to Pennell's (1996b), to develop a

mobilization curve for PCE and cosolvent mixtures. The column was sequentially flushed

with increasing volume fractions of cosolvent, continuously. Gradually increasing inlet

cosolvent fractions avoided front instabilities due to the density differences. At the front,

due to dilution, PCE may come out of the flushing phase, creating a macroemulsion. This

emulsion may resolubilize as it is exposed to the higher cosolvent fractions, or elute from

the column as a macroemulsion. This is not desired, as this quantity of PCE is more

difficult to quantify. Gradient elution was performed, also in part, to help minimize

macroemulsion formation.

To determine the amount of PCE solubilized compared to the amount mobilized,

one of the phenomena must be eliminated to quantify both. The trapping number curve

was first constructed using aqueous streams (water plus cosolvent) equilibrated with PCE.








This eliminated solubilization and allowed visual volumetric determination of mobilization

(from purely IFT reduction) based on the PCE phase generated from the column. Similar

experiments were then conducted on the same sand column using non-equilibrated ethanol

mixtures (without any PCE added). PCE saturations and trapping numbers were

determined and results between the two methods compared. Equilibrated cosolvent runs

were then repeated using IPA and t-butyl alcohol as cosolvents and compared to those of

ethanol to investigate swelling impacts.

For each cosolvent fraction, the run was continued for at least one pore volume,

generally two, to ensure the resident fluid was characteristic of the injected fluid, yet

minimize any possibility of local solubilization. Gradient elution improves the efficiency of

this process. The remaining NAPL saturation percentage (%/SpCE) was then determined

both gravimetrically and volumetrically (based on visual measurement in a graduated

cylinder). This was done for various cosolvent volume fractions ranging from 20% to

90% v/v cosolvent/water mixtures.

Results and Discussion


Equilibrated Gradient Column Studies

For each run, a series of trapping numbers (Pennell et al. 1996b) was determined,

using the predicted IFTs from the batch equilibrium experiments. A plot of %SPCE versus

trapping number, NT, was then generated. Results from gradient soil column

displacement experiments are shown in Figure 3-1 through Figure 3-3. Figure 3-1 is the

effluent PCE concentration as a function of pore volumes (PV; I PV is approximately 100

ml) of saturated EtOH/H20/PCE cosolvent mixtures flushed through the column. Note








that the volume percentages of ethanol shown are pre-equilibrated volume fractions, which

differ from equilibrium volume fractions, especially at higher percentages of ethanol. It

can be seen that effluent PCE concentrations, after 1 PV of each fluid has passed,

approach equilibrium conditions. Significant mobilization begins to occur when the 85%

EtOH solution is resident within the column. Reduction in DNAPL saturation at earlier

pore volumes (0-4 PVs) is thought to be artificial, caused by small amounts of PCE being

removed from the effluent end of the column apparatus due to possibly lower capillary

forces, under moderate IFT reductions.

Blank Equilibrated Gradient Study

A gradient experiment was conducted virtually identical in procedure to the one

described above, except no PCE was loaded into the column. Each flushing phase was

pre-equilibrated with PCE. This was done to determine if any of the free-phase PCE

generated from the column during any experiments could arise from simply the dilution of

solubilized PCE at each of the gradient fronts. After completion of the entire gradient,

less than 0.2 ml of PCE was collected. This volume was decided to be insignificant to our

studies. The possibility of frontal dilution contributing to the mobilized DNAPL volume

was discarded.

Non Equilibrated Column Studies

Results from a non-equilibrated gradient elution are presented in Figure 3-2.

Effluent concentrations show that these mixtures at study flow regimes quickly reach

equilibrium conditions. Mobilization does occur as shown, but it represents a very small

percentage (< 0.7%) of the total DNAPL saturation. Under this gradient regime,

essentially all DNAPL was removed via solubilization prior to introduction of the 90%













1000000






100000


10000


1000 0
20% *




100 :
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0
Pore Volumes



Figure 3-1. Gradient effluent profile for saturated PCE run (influent %'s shown are

ethanol volume fractions prior to saturation).


3.0 4.0
Pore Volumes


1



1



1







I


0.8


0.7


0.6


05


04 s


0.3


0.2


0.1


Figure 3-2. Gradient effluent profile using unsaturated ethanol mixtures percent of

mobilization shown.


6.0



14.0



2.0



10.0



8.0
-J
0.
Q



g.0



4.0



2.0










1000000


AAAAAAAAAAA&AAA&MA&&AAAAAj&AAAAA 80% 18

100000 AA- 1
60% a
'Solubility Potential' of Influen 14


E. 10000 ------------ ---- --------- ------------------- *1



1 0 I 0
E 10000 12- 1

10


S 20%
6

100A 4

2

10 0
0.0 1.0 2.0 30 4.0 5.0 6.0 7.0
Pore Volumes



Figure 3-3. Gradient effluent profile using unsaturated ethanol cosolvent mixtures with
PCE saturation reduction shown.




EtOH cosolvent. Significant reductions in PCE saturations occur during the injection of


the 80% EtOH mixture. This can be seen in Figure 3-3. Calculations to determine the

trapping number were conducted using physical measurements shown in Table 3-1.



Table 3-1. Physical Measurements of PCE Saturated Cosolvent Solutions

Kinematic Dynamic
EtOH IFT pc Viscosity viscosity

v/v % dyne/cm g/cm3 cSt cP
0 37 1.002 0.92 0.922
20 15.85 0.9752 1.586 1.547
40 7.74 0.9444 2.42 2.285
60 4.25 0.9107 2.542 2.315
80 1.91 0.9303 1.945 1.809
85 1.14 0.9689 1.661 1.609
90 0.55 1.0765 1.285 1.383








Generation of Mobilization Curves

Relative permeabilities (k,) calculated from pressure measurements made during a

run were inconsistent due to probable variability in column conditions, including strong

buoyancy effects. Therefore, permeabilities during the run were estimated using van

Genuchten parameters (van Genuchten 1980) for the sand medium, found from Tempe

cell testing. Although these values are calculated, they are reasonably close to actual

values. Furthermore, small differences in k, will not introduce significant error into the

trapping number. The contact angle (0) for the relationship was assumed to be zero.

Although this is probably not valid at higher IFT values, it becomes more appropriate as

IFT decreases, and subsequently in areas where mobilization occurs. Data points to

construct these curves were based on properties of the displacing fluid and relative

permeability of the media being flooded. As can be seen in Figure 3-4, mobilization for

PCE begins at a trapping number of approximately 2 x 104. This is different by an order

of magnitude from that of Pennell (1996b). For surfactants, it was predicted that

mobilization of PCE would begin at a trapping number of approximately 2 x 10-5 to 5 x

10-5.

Also shown in Figure 3-4 is the PCE desaturation curve for the non-equilibrated

run. This clearly shows the non-equilibrated experiment never reaches the critical trapping

number required for mobilization. On a column average basis, the saturation decreases

due to solubilization before the mobilization trapping number is reached. Therefore,

significant mobilization in the column effluent is not observed. Additionally, the gradient

profile could have been stopped, and the injected concentration fixed at any one of the

alcohol fractions (60, 80 or 85%) and saturations reduced to zero without










18 -


x X x
14
U
gradient2 X12equilibrated gradient

e 10-
8

I 6'


4 x

2t

0
1.0E-06 1.0E-05 1.0E-04 1 .OE-03
Trapping Number
a gradient2 Xgradient4 non-equilibrated gradient

Figure 3-4. Mobilization curves showing effect of a cosolvent (ethanol) flushing phase
which is pre-equilibrated with PCE (gradient 2 and 4) and a flushing phase with full
solubilization potential (non-equilibrated). All are gradient runs.



mobilization. This can be seen if one extrapolates the portions of the desaturation curve

where significant reduction in saturation occurs. Thus, if flooding regimes are controlled,

the removal process of NAPL may never cross the mobilization envelope.

Resulting mobilization curves for the ethanol system are shown in Figure 3-5 with

Pennell et al. (1996b) data shown for reference. The data indicate that mobilization of

PCE begins at a trapping number of approximately 2 x 10-4. Three gradient runs are

shown in addition to three runs that were conducted independently, without any gradient.

These were conducted to verify that the desaturation curve for PCE residual was not

dependent on mode of flushing or previous exposure to lower cosolvent volume fractions.

As can be seen, the trapping relationship is independent of the mode of flushing.






60



180

16-

U X
14
m$.



I X
C 12

S10
a-


6 I
A
4-

2-


1.0E-06 1.E-05 1.0E-04 1.0-03 1.0E02
Trapping Number
A Pennell (1996) a gradient2 x gradient4 gradient5 Single Runs


Figure 3-5. PCE Desaturation Curves PCE saturated ethanol cosolvent runs compared
with data from Pennell et al. (1996).




From initial results, it appears that there is a difference between this study's data

and those from the surfactant work of Pennell et al. (1996b). Taber (1969) noticed a

difference between displacements of residual oil with surfactants and water/alcohol

systems. Although the Taber's initial critical value of the capillary number only was

approximately the same in each case, the surfactant tended to desaturate more oil for the

same capillary numbers, i.e., more oil was recovered at a lower capillary number. Taber

explained this difference by the adsorption of surfactant on the media surfaces, causing

earlier mobilization due to lower interfacial forces. Pennell et al. (1993) noted, that

critical trapping number values derived from the capillary and Bond numbers is system






61



specific and can vary over an order of magnitude depending on the properties of the


organic phase, matrix, and experimental design. To determine the possible reasoning for


this difference, surfactant solutions similar to Pennell et al. (1996b) were made and their


methods repeated. The results are shown in Figure 3-6. Physical data of each surfactant


solution were assumed to be those published in Pennell et al. (1996b). Spot checks of


solution properties matched those in their work reasonably well, but values ofIFT were


getting too low (<1 dyne/cm) to be reproducible with the du Nuoy ring tensiometer used


for this work. The data from the surfactant series falls essentially on top of the cosolvent


grouping. This suggests that the difference between the data sets is not due to differences


between surfactant and cosolvents, but rather those related to media or experimental


specifics.


1I

16

14

O 12 *

| 0
A

10



sil 6 1

4
X
A
2
A
a ----------------------- ---- 0 ---
1i.OE-06 1.0E-05 1.0E-04 1.0E-03 1IOE-02
Trapping Number
A Pennel (1996) gradient2 x gradient4 gradient5 Single Runs o Surfactant 1]



Figure 3-6 Ethanol mobilization curves with surfactant run superimposed.








To further understand possible differences between NAPL removal due to

solubilization and mobilization, runs were conducted with all phases in equilibrium with

each other. The only column loading and flushing method possible to achieve this was to

first load the column with the desired cosolvent that had been pre-equilibrated with PCE.

The corresponding equilibrated PCE phase was then loaded into the column (up flow) at 5

ml/min until PCE was eluting from the top of the column, then flow was increased to 25

ml/min until a total of one pore volume of DNAPL had been introduced. Equilibrated

cosolvent then was flushed downward through the column (down flow) at 5 ml/min to

bring the DNAPL phase to a new residual. This method and the results are described in

the next chapter.

Swelling Effects of Cosolvents

Results from similar experiments conducted for ethanol are shown in Figure 3-7

and Figure 3-8 below for isopropyl alcohol (IPA) and t-butyl alcohol (TBA), respectively.

Physical properties of these solutions are in Table 3-2. Swelling of the DNAPL due to

IPA partitioning is slight. The impact of this swelling is not significant on the outcome of

the onset of mobilization, as shown on the trapping number curve. Note that the volume

of DNAPL remaining behind after each gradient increase in cosolvent volume fraction had

to be corrected back to a pre-flushing volume for comparison purposes. Swelling of the

PCE due to TBA was great, making mass balance calculations subject to probable error.

Swelling correction factors were based on batch studies using a 1:1 aqueous to PCE initial

phase ratio.

















X+ x Xx
a o o o *


A A


1.0E-05


1.0E-04
Trapping Number


I Pennell (1996) o gradient2 x gradient4 o gradient5 o Single Runs IPA Gradient + IPA Single Runs I


Figure 3-7. Results from mobilization studies using pre-equilibrated IPA solutions,

superimposed on the ethanol study results.


x


1.0E-04
Trapping Number


I Pennell (1996) 0 gradient2 x gradient4 o gradient5 o Single Runs a TBA Gradient


Figure 3-8. Results of mobilization of PCE during gradient TBA column flushing; TBA

pre-equilibrated with PCE.


C 12


110


% 8


6


4


1.0E-06


1,0E-03


1.0E-02


18


16-


14-





10-


j8

5 6
U


j X
U


U8


4


2


0-
1.0E-06


1.0E-05


1.0E-03


1.E0-02


~


"" '""" "" ' "''


18 -


1








Table 3-2. Physical properties of solutions used in swelling mobilization studies.
Kinematic Dynamic
Cosolvent fc IFT p4 Viscosity Viscosity
v/v % dyne/cm g/cm3 cSt cP
100 %H20 37.00 1.002 0.929 0.930
IPA 40 3.01 0.947 3.08 2.91
IPA 60 1.17 0.931 3.57 3.32
IPA 75 0.42 0.975 2.89 2.82
IPA 85 0.08 1.087 1.99 2.16
TBA 19.2 5.69 0.978 2.09 2.05
TBA 32.1 1.28 0.969 2.69 2.60
TBA 49.6 0.36 0.960 3.21 3.08




Conclusions

The trapping number is an effective parameter to help predict mobilization of non-

aqueous phase liquids in subsurface environments. Trapping number results and onset of

PCE mobilization were found similar, although slightly greater, to those of

Pennell et al. (1996b) for both surfactant and cosolvents. Ethanol used as a cosolvent (at

volume fractions less than 85%) enhanced solubilization of PCE to the point where this

process is dominant and mobilization of PCE can be avoided for the media studied.

However, under severe conditions, mobilization using cosolvents can occur. This includes

large step inputs to high cosolvent fractions, where DNAPL saturation is still great enough

for immediate IFT reduction to cause mobilization, at least in a local sense. This of course

could be important if, within that locality, DNAPL moves out of the zone of hydraulic

control. These issues are further addressed in two-dimensional box studies.

As should be expected, differences between surfactant and cosolvent systems are

not apparent on a mobilization curve. Mobilization curves appear to be independent of





65

alcohol type. Swelling effects, when DNAPL volumes are adjusted to pre-equilibrated

values did not appear to affect onset of mobilization. However, as partitioning of the

alcohol into the NAPL increased, the volume ofNAPL increases and becomes difficult to

quantify. Further research into this area is needed.













CHAPTER 4
ENTRAPMENT VERSUS MOBILIZATION OF RESIDUAL
PERCHLOROETHYLENE DURING COSOLVENT FLOODING


Introduction


Enhanced Oil Recovery (EOR) has been practiced for quite some time and

approaches have been "refined" to improve the collection efficiency of oil. In the oil

recovery industry, quick and efficient removal of oil from subsurface environments is

obviously desired. EOR is achieved under immiscible conditions either by reducing the

amount of oil entrapped or by mobilization of some of the trapped oil. Under strongly

water wetting conditions, which is assumed throughout this research, trapped NAPL is

held as discrete blobs. The processes of entrapment and mobilization are associated with

displacement of continuous and discontinuous oil, respectively (Morrow et al. 1988).

Therefore, maximizing mobilization of free-phase NAPL and minimizing the amount

entrapped behind the flooding front is desired. For the remediation of contaminant plume

sources, minimization of contaminant left behind is an obvious goal from a risk

management standpoint, but if mobilization of banks of NAPL is the desired scheme,

maintaining this bank by minimizing entrapment is also desired for process efficiency.

Many studies have been conducted focusing on these processes relating to EOR (Moore

and Slobod 1956; Morrow 1987; Morrow et al. 1988; Stegemeier 1977; Taber 1969).

With the recent increase in application of this technology to remediation of contaminants,

additional information relating to these processes








specifically focused on NAPL contaminants is needed. Until recently, remediation

technologies for the removal of organic contaminants from subsurface environments

focused on pumping of groundwater and subsequent treatment of this stream. Risk

reduction to possible receptors was the driving force behind these actions. However, due

to the solubility limitations of these types of treatment, remedial action time-scales are

long and expensive. The source of contamination is very slowly removed due to natural

solubilization. In the last few years, research efforts and technology demonstrations have

become more focused on source removal. These include surfactant flooding and

cosolvent flushing (Chaudhry 1994; Fortin et al. 1997; Pennell and Abriola 1996).

Although these techniques tend to be more aggressive and have high initial costs, the

removal of a possible long-term source is beneficial from risk reduction, economic, and

legal perspectives.

Of these recent technologies, methods that increase the solubility of the

contaminant into a mobile flushing phase have shown promising results (Annable et al.

1996; Falta et al. 1997; Fountain et al. 1991; Jawitz et al. 1998b; Rao et al. 1997; Sillan

1999). Two general types of chemicals are used to enhance contaminant solubility:

surfactants and cosolvents. Both increase the aqueous phase solubility of the contaminant

accelerating remediation efforts by two to five orders of magnitude. The resulting faster

cleanup times are desired to decrease health risks to potential receptors and to reduce

project operations and maintenance costs.

These processes also reduce the interfacial tension between the aqueous and

organic phases. This reduction can drastically change the force balance keeping the

organic phase trapped in the soil pores or being force out due to the advective flow of the








flushing phase or density contrasts. This possible movement of the organic phase has been

labeled 'mobilization'.

Solubilization, Mobilization and the Trapping Number Relationship

Prior discussion and literature review of solubilization and mobilization of NAPLs

via cosolvent and surfactant flushing can be found in chapters 2 and 3 and is not repeated

here for brevity. The reader is encouraged to review those sections, if necessary.

Mobilization and Entrapment of Residual Non-Aqueous Phase Liquid

Differences between the processes of entrapment and mobilization have been

documented previously in EOR research (Morrow et al. 1988; Morrow and Songkran

1981). During their entrapment experiments, saturations appeared uniform throughout the

column and relative permeabilities at reduced residuals were not functions of time and

flow rate. Morrow and Songkran (1981) estimated that mobilization of trapped NAPL

blobs is about five times more difficult to achieve than prevention of trapping. In their

efforts to mobilize a trapped gas, severe solution effects (due to pressure gradients and

gas solubilities) were encountered in an attempt to mobilize by increasing the capillary

number. These were in distinct contrast to trapping behavior, where solution effects

proved to be insignificant (Morrow and Songkran 1981). During the entrapment process,

local changes in interfacial shapes within individual pores are small and not likely to

account for the large changes in residual saturation that were measured under different

capillary numbers. The mechanism of entrapment, they believed, is due to change in

imbibition mechanism caused by small hydrostatic pressure differences across a NAPL

blob. This is due to either a change in Bond number from density contrast changes. When

capillary forces dominate, NAPL blobs become isolated from the main body of continuous








fluid once an imbibition event occurs. Each NAPL blob will have a few to several pore

openings across which an imbibition capillary pressure is maintained. With an increase in

the trapping number, specifically the Bond number, the tendency for imbibition to occur

into the upper (for a DNAPL) region of a vertical pore increases since the hydrostatic

pressure between the region increases. If this additional hydrostatic pressure is sufficient

to allow imbibition into the upper region first, the blob is mobilized. A similar mechanism

can apply to reduction of DNAPL saturation by increasing viscous forces except that the

required supplemental pressure at the leading edge of the blob is provided by the viscous

pressure gradient.

Movement of a trapped NAPL globule involves drainage at its leading edge and

imbibition at the rear. Assuming a completely water wetted random sphere pack, the

pressure drop required for mobilization (APm, [ML'T2]) is given by the difference between

drainage and imbibition displacement pressures. At 70% water saturation, this difference

is 2.8/rp (a, is the interfacial tension [MT2] and rp, particle radius [L]) (Morrow and

Songkran 1981). The value of the supplementary hydrostatic pressure component due to

buoyancy effects is:

APs = 0.5460/rp (4-1)


Therefore the ratio of AP/APm is 0.2, and thus it is approximately five times more difficult

to mobilize entrapped fluid than to prevent entrapment (Morrow and Songkran 1981).

Another main conclusion of Morrow and Songkran (1981) is that the space

occupied by residual oil saturations after trapping will generally be a subset of the space

occupied by the residual saturation prior to any flooding and possible mobilization. This is








under conditions where capillary forces are dominant. This seems to indicate that

whatever information on pore size distribution that can be produced from pores filled with

residual oil, would be indicative of the distribution for the entire media.

It was also noted that permeabilities (for a given saturation), obtained when

residuals are reduced by change in entrapment mechanism, do not necessarily correspond

to those resulting when residual saturations are decreased by mobilization of trapped fluid

(Morrow et al. 1988). Although this difference could be present during this study, it

would not be large enough to effect the entire trapping number significantly.

Study Objective

The objective of this study was to conduct two types of soil column experiments. The

first was to generate mobilization curves similar to Pennell et al. (1996b) using a cosolvent

mixture typically used in remediation. The second was to generate "entrapment curves"

for the same media, using similar fluids. Finally, a comparison was then made between the

desaturation curves for the mobilization and entrapment studies.

Materials and Methods


HPLC grade PCE (CAS 127-18-4) was obtained from Fisher Scientific, Fair Lawn

NJ. The absolute ethanol (>99.5 %; CAS 64-17-5) used in these studies was purchased

through Spectrum Quality Products, Inc., Gardena CA. Due to large difference in cost

and small difference in physical properties, reagent alcohol (Fisher Scientific; 90.4 vol. %

ethanol, 4.6% methanol, 5.0% isopropanol) was also used when absolute ethanol was not

necessary. This included column final washings. The water used for the cosolvent

solutions and for soil column flushing was purified through a Nanopure filtration process,








and brought to an ionic strength of 102 M (350 ppm) with calcium chloride, as done in the

previous chapter (Stumm and Morgan, 1981).

Stock solutions of ethanol/water mixtures were made in I liter quantities using

standard volumetric glassware. Volume percentages were based on volumes of water and

ethanol prior to mixing. Although the final total volume is less upon mixing (thus the

volume percentages are no longer exact), the difference is minimal (1-2%). Furthermore,

labeling of these solutions by using these pre-mixed volume fractions is for convenience

only and exact physical parameters used in calculations are determined later.

Physical Measurements

Density measurements were performed gravimetrically. Two milliliters of solution

were measured in a gas-tight volumetric syringe and weighed on a precision Mettler

Balance ( 0.0001g). A sample's density measurements were repeated no less than three

times to ensure accuracy and precision of this technique. Viscosities of solutions were

determined by a Cannon-Fenske Routine Viscometer (Cannon Instrument Company, State

College PA). A du Nuoy ring tensiometer (Fisher Tensiomat Model 11) was used to

determine the interfacial tension of all samples. The lower limit of this instrument is

approximately 0.1 dyne/cm. Laboratory temperature was well controlled and was 23

0.50C.

Sand Column Preparation

A small-scale glass column (4.8 cm X 15 cm, chromatography column from

Kontes Corporation) was used for this study. All end materials shipped with the column

were removed except for the 40 mesh nylon screen. The soil column was incrementally

packed with well-sorted Number 30-40 sand. This sand size was chosen so that the pore








size would be approximately equal to the screen mesh size to avoid entrapment of NAPL,

yet still contain the sand within the column. Vibration of the soil increments was also

performed to improve packing characteristics. Once the column was packed it was

weighed with all necessary column parts attached. The soil mass was weighed by

difference and the internal volume of the column used to calculate the bulk density. Using

the particle density of silica sand (2.65 g/cm3) and the mass of sand added to the column,

the volume of sand (Vs) can be calculated. The porosity of the soil column is then easily

calculated form the total volume of the column as: iT = (1-Vs)/Vt. Approximately 15 pore

volumes of de-aired water (via vacuum) were then pumped through the column and the

pore volume determined.

PCE Saturation and Generation of Trapping Curves

Mobilization studies

Experiments were conducted, similar to Pennell's (1996b), to develop a trapping

number curve for PCE and the ethanol cosolvent mixtures. "Pure" PCE (dyed with <5 x

10-5 M oil-red-o dye, Fisher Scientific, CAS 1320-06-5) was introduced to the column to

establish residual saturations. This dye concentration range has been shown not to

significantly affect solubilization and IFT properties (Pennell et al. 1996b; Young 1999).

The PCE was introduced in a up flow mode to achieve stable displacement of water.

When PCE appeared at the top of the column, the flow rate was increased 5 fold to

increase PCE saturation (Dawson and Roberts 1997). The flow was then reversed and 3

pore volumes of water pumped through in a down flow mode to displace free product








PCE, at a flow rate of 5.0 ml/min. The resulting PCE saturation (%/SpCE) was determined

gravimetrically, based on density difference between water and PCE.

The column was then sequentially flushed with increasing volume fractions of

cosolvent, without stoppage. Gradually increasing inlet cosolvent fractions avoided front

instabilities due to the density differences. At the front, due to dilution, PCE may come of

solution, creating a macroemulsion. This emulsion may eventually resolubilize as it moves

through the column, exposed to the higher cosolvent fraction, or elute from the column as

a macroemulsion. This is not desired, as this quantity of PCE is more difficult to quantify.

Gradient elution was performed to help avoid macroemulsion formation.

To determine the amount of PCE solubilized compared to the amount mobilized,

one of the phenomena must be eliminated to quantify both. The trapping number curve

was first constructed using aqueous streams (water plus cosolvent) pre-equilibrated with

PCE. This eliminated solubilization and allowed visual determination of mobilization

(from purely IFT reduction) based on the PCE phase generated from the column. Similar

experiments were then conducted on the same sand column using unsaturated ethanol

mixtures (without any PCE added). PCE saturations and trapping numbers were

determined and results between the two methods compared.

For each cosolvent fraction, the run was continued for at least one pore volume to

ensure the resident fluid was characteristic of the injected fluid. The remaining %SPCE

was then determined by visual volumetric measurement of mobilized DNAPL. This was

done for cosolvent volume fractions 20%, 40%, 60%, 80%, 85%, and 90% EtOH/water

mixtures. For each run, a series of trapping numbers (Pennell et al. 1996b) was








determined, using the predicted IFTs from the batch equilibrium experiments. A plot of

%SPCE versus trapping number, NT was then generated.

Entrapment studies

To maintain equilibrium between all fluids for the entrapment experiments,

independent runs using cosolvent and DNAPL phases which had been previously

contacted and brought to equilibrium was necessary. Three PV's of a reagent alcohol

mixture were flushed through the column at a flow rate of 25 ml/min. The cosolvent

phase (with solubilized PCE) from the desired batch solution was then flushed through the

column in the upflow mode. Only one PV of this fluid was necessary, as the front of this

displacement was very efficient and stable, i.e., no fingering occurred. Subsequently, the

corresponding equilibrated DNAPL phase (mostly dyed PCE) was introduced into the

column at 5 ml/min in the upflow direction until production of DNAPL appeared in the

effluent tubing. Then the flowrate was increased to 25 ml/min until a total of one PV was

used. Finally, the DNAPL was brought to residual saturation with the same pre-

equilibrated cosolvent phase. All fluids were introduced into the column at a flow rate of

5 ml/min, unless specifically noted otherwise.

Porous Medium Parameters

The intrinsic permeability (k) of the porous media and hence, the effective

permeability (ke = kkrw), was determined following PCE addition by use of inlet and

outlet pressure difference measurements. Resistance due to the column was measured in

the absence of packing to allow correction for the resistance due to inlets and outlet

screens, connections and tubing (Morrow et al. 1988). This resistance was subtracted

from pressure drop measurements over the filled column to determine pressure drops









across the media only. A differential pressure transducer (Cole-Palmer Instrument

Company, Niles, Illinois, 0-5 inches H20 differential transducer) was used to monitor this

pressure difference.

Relative permeabilities were estimated based on van Genuchten parameters (van

Genuchten 1980) determined by Tempe cell (Soil Moisture Equipment Co., Santa

Barbara, CA) measurements (Figure 4-1). These were compared to the data from

Morrow and Songkran (1981) and found to match closely with actual data measured in

porous media (glass beads). This data is reproduced in Figure 4-2.

Thus, the relative permeabilities determined via the van Genuchten parameters

based upon the Mualem (1976) method were determined to be adequate for the soil

column. Measurement of the relative permeability with the pressure transducers was

initially attempted, but fluctuations associated with column resistance effects and


40

30-


25- -


1 5

0
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35
Moisture Content

Data -- Fitted van Genuchten - - Brooks&Corey


Figure 4-1. Moisture release curve for No. 30-40 silica sand used for these studies,
conducted via Tempe cell. van Genuchten (1980) and Brooks & Corey (1964) fits are
based on minimizing the sum of squares of the difference between the actual data and the
fitted line.

















j




I


0 i
I 4


08
o.e9-------


0FR2= 0.9071
0.75

07.5

%- #
0651________________


0.6
00' \ s


0.55--

0.5 --
0


2 4 6


8
%S ,P


10


12 14


I Morrow Data - Mualem Fit Regression Line (Morrow and Songkran data)

Figure 4-2. Relative permeability to the wetting phase at less than normal nonwetting
phase residual saturation: Morrow and Songkran (1982) data shown with regression (R2
= 0.907) and fit of this study's Tempe cell data based on van Genuchten (1980)
parameters and the Mualem (1976) method.




buoyancy effects, due to sometimes large density differences, made these measurements


erratic. Although this parameter is not directly measured for this study, this should not


provide significant error, as differences in relative permeability estimates are minor.




Results and Discussion



Entrapment in Homogeneous Sand Column


Curves for the soil column mobilization experiments relating PCE (DNAPL)


saturation to the total trapping number are shown in Figure 4-3, with Pennell et al. (1996)


data shown for reference. The data indicate that mobilization of PCE begins at a trapping






77



18

16-
X X Xx
14

S124 e

10 A A

a
08 A



4-












ofPennell et al. (1996).
x
A
2
A

i.OE-06 1.0E-05 1.OE-04 1.0E-03 1.E-02
Trapping Number

A Pennell (1996) a gradient2 Xgradient4 gradient5 Single Runs


Figure 4-3. PCE Desaturation curve experimental ethanol data only compared to those
of Pennell et al. (1996).




number of approximately 2 x 104 Three gradient runs are shown in addition to three runs

that were conducted independently, without any gradient. These were conducted to verify

that the desaturation curve for PCE residual was not dependent on mode of flushing or

previous exposure to lower cosolvent volume fraction flushing fluids. As can be seen, the

trapping relationship is independent of the mode of flushing.

The DNAPL saturation percentages that resulted from the entrapment experiments

were plotted against the run's corresponding trapping number and are shown

in Figure 4-4. The data from the mobilization experiments and Pennell et al. (1996) data

are shown again for reference. There were two different series of entrapment experiments








conducted. The first involved all pre-equilibrated fluids, conducted as described

previously in Materials and Methods. However, in an effort to determine the possible

causes of the difference shown in the figure between mobilization and entrapment

processes, another series of "entrapment studies" was conducted. These were

accomplished identically to the previous entrapment method, except that the DNAPL

phase loaded into the column was HPLC grade PCE instead of PCE equilibrated with an

ethanol cosolvent mixture. This change does not account for much of the difference

between the two processes, indicating that mobilization is not heavily dependent on mass

transfer limitations of a slightly partitioning cosolvent, like ethanol. As long as the

aqueous phase/NAPL interface is amply supplied with components required to keep the

interfacial tension to it equilibrium value, proper mobilization or entrapment will occur.

This is obviously more critical during mobilization, as fresh NAPL interfaces are

constantly being met with the flushing cosolvent phase.

The slight shift between the two entrapment runs (all phases equilibrated versus

only the cosolvent phase equilibrated) can be possibly attributed to slight differences in

actual interfacial tensions. The use of equilibrated IFT in the trapping number calculation

is presumably close to the actual IFT in the sand medium. The use of equilibrated IFTs

for the cosolvent-equilibrated run may underestimate the actual IFT, and therefore

overestimate the trapping number. This difference is likely small and lead to the small shift

of the two trapping relationships shown in Figure 4-4. One of the remarkable features of

these studies is the extreme linearity of the relationship between the DNAPL saturation

and the trapping number. Table 4-1 shows the results of a linear regression performed

through both sets of data.

















x



y = -4.1967Ln(x) 29.214
R2= 0.9992
A A


x xx

U.


X
Sx
0


y = -4.1904Ln(x) 30.042
R2 = 0.9958


1.E-05


1.0E-04
Trapping Number


n ' '


1.0E-3


1.01-02


A Pennell (1996) gradient2 Xgradient4 gradient5 0 independent runs cosolvent equilibrated +all equilibrated fluids

Figure 4-4. PCE desaturation curves for both mobilization and entrapment studies, with
linear regressions shown for the entrapment experiments


Table 4-1. Results of linear regression of entrapment studies

Data Series Slope y-intercept R
Entrapment -4.1904 -30.042 0.9958
(all pre-equilibrated)
Entrapment -4.1967 -29.214 0.9992
(PCE not pre-equilibrated)



It is worth repeating that each data point is done independently from the others.


The slopes of the regression of both data sets are nearly identical. Therefore, the slope


appears to be independent of phase equilibrium. As the x-axis is representative of the


capillary pressure through the capillary number, it appears the slope represents a factor


16-

14

12

10

18


1 6

4

2


1.0E-06


4Q __________________------------------------------"-------------*-








relating to the pore size distribution of the media. Taber (1969) stated the similarity

between curves of capillary number and percent saturation and standard capillary pressure

curves was "obvious". He further stated this similarity should be expected since both

processes represent the displacement of a fluid from capillaries of various sizes by a

different and immiscible fluid. Thus, the pore size distribution of the porous medium

should affect both processes in a similar way (Taber 1969). Of all the factors included in

the Trapping Number, the effect of alcohol addition on trapping and mobilization

phenomena in these type of studies is due to change in IFT, and not changes in other fluid

properties (Ryan and Dhir 1996). If this is the case, trapping number curves should

provide us with similar information as capillary pressure curves, which are heavily

dependent on IFT. Separate air-water desaturation studies conducted on the same sand

using a Tempe cell resulted in a Brooks-Corey lambda of approximately 3.65 (see Figure

4-5). Previous researchers have stated the space occupied by residual oil saturations will

generally be a sub-set of the space occupied by the normal residual saturation (Morrow

and Songkran 1981). This method of obtaining pore-size information has not been found

to date in previous literature.

Effect of Pore Size Heterogeneity on the Entrapment of PCE

Similar to the totally equilibrated entrapment studies discussed above, another

series of experiments was conducted on the one-dimensional sand column filled with a

widely graded sand mixture. This sand medium consisted of equal weight fractions of

#20-30, #30-40, #40-50, #50-60, #70-80, and #80-100 sands. The drainage curve and the

pore size distribution of this mixture are shown in Appendix A.


















f y = 8215.7x J'321
S\ R2 = 0.9989










0.01
10 100
Capillary Pressure, cm HIO

Figure 4-5. Effective saturation of study 30-40 mesh sand as a function of capillary
pressure, resulting slope of regressed line is the Brooks and Corey lambda, X = 3.65.



Two methods of packing the column were attempted wet and dry, both with

subsequent vibration. The wet packing was accomplished in 3 cm layer with only about 1-

2 cm of water above to keep it fully saturated. This was done to minimize the distance of

travel for the different particle sizes with varying settling velocities. However, after

completion, significant heterogeneity (layering) was observable. This packing was still

used for study and results are shown below.

To minimize the layering, a quick fill of the sand mixture under dry conditions was

also done. Subsequent vibration necessitated the addition of a small layer of new sand at

the top of the column. The column was then saturated with water from below via vacuum

aspiration.









The results of the wide distribution packing are added to the desaturation curves

presented above and this is shown in Figure 4-6 below. As shown in Figure 4-6, the wide

distribution and the homogeneous entrapment studies do not behave similarly. It was

expected that the slope of the entrapment curve for the wider pore distribution would be

less, resulting in a more gradual desaturation curve. However, it appears that the behavior

is exactly the opposite. The data reveal that the saturation generally increases with higher

trapping numbers (lower interfacial tensions). This may be due to PCE being able to enter

smaller and smaller pores as the interfacial tension between it and the equilibrated

cosolvent decreases. Additionally, small layered zones of finer media in the column may

allow fluids with lower IFT to enter and never be able to come out. As previously


18

16-
X X XX
14- 0 X

S12




6-
10-





+ X
\ x



2

0 a-
1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02
Trapping Number
I gradient2 X gradient4 gradient5 0 Single Runs Entrap PCE + all preset *20-100

Figure 4-6. Results of entrapment experiments on the heterogeneous packing (#20-100
sand), shown with homogeneous entrapment and mobilization results for reference.








mentioned, Morrow and Songkran (1981) concluded that it is approximately five times

more difficult to mobilize than to prevent the entrapment of a NAPL. Therefore, it is

possible for the DNAPL to enter more pores at lower IFTs and subsequently not be able

to as easily be mobilized back out. This behavior was not observed in the homogeneous

packing since relatively all pore sizes are similar in size.



Conclusions


Entrapment and mobilization of residual NAPL are separate and distinct processes.

This difference can be seen if both processes are plotted on a trapping number curve. The

entrapment process, represented by the percent of remaining DNAPL saturation (%

SNAPL), appears to be log-linearly related to the trapping number. The exact interpretation

of this relationship is not clear now, but it is believed to be associated with the log-linear

dependence of saturation with capillary pressure. This is similar to the Brooks-Corey

relationship shown in Figure 4-5.

Dependence of the entrapment process on media heterogeneity is not clearly

shown. It was expected that the slope of the entrapment curve for the heterogeneous

media would be less than that of the homogeneous sand, indicating a more gradual release

of NAPL throughout the wider range of pore sizes. Difficulty in truly reproducing

isotropic heterogeneous packing may have contributed to the scatter of data for the wide

pore size distribution packing. However, it is plausible that due to lower permeability

zones in the packing, the reducing IFT allows additional PCE/DNAPL to remain in these

smaller pores, increasing saturation. This may be a negative factor in choosing to use





84


gradient elution of DNAPLs, as reduced IFTs ahead of any mobilized DNAPL could

entrap contaminant in smaller pores, leading to longer removal times and possible lower

removal efficiencies.













CHAPTER 5
MOBILIZATION AND ENTRY OF DNAPL POOLS INTO FINER SAND MEDIA:
TWO-DIMENSIONAL BOX STUDIES


Introduction


In-situ flushing remediation is quickly becoming a popular method to remove

source-zone contamination. Whether using surfactants, alcohols, or oxidants as injection

fluids to accelerate the displacement, dissolution, or chemical transformation of

contaminants, control of contaminant movement is critical. Control is critical not only

during the flushing process to improve recovery and to minimize environmental impact,

but consideration of contaminant control is vital during the planning and proposal stages

as well. Proposals to property owners, local, state and federal government agencies are

more likely to gain approval after sound recommendations and strategies for contaminant

control have been outlined. The basis for these a priori strategies often include theoretical

chemical and hydrologic calculations or modeling, but the most valuable input arises from

field experience. Test cells constructed to study flushing technologies, including one at

Hill Air Force Base (AFB), Utah (Annable et al. 1996) and one currently being used at

Dover AFB, Delaware provide excellent opportunities from which to draw conclusions

and apply them to the "open-field" real remediation situation. However, an important

experimental method that lies between these two study options in scale, is the use of a 2-

Dimensional (2-D) box or chamber to study the movement and remediation processes of

these flushing chemicals. A good review of 2-D laboratory experiments can be found in