Close
About
FAQ
Home
Collections
Login
USC Login
Register
0
Selected
Invert selection
Deselect all
Deselect all
Click here to refresh results
Click here to refresh results
USC
/
Digital Library
/
University of Southern California Dissertations and Theses
/
Feasibility of in-situ removal of heavy metals by electroremediation of offshore muds
(USC Thesis Other)
Feasibility of in-situ removal of heavy metals by electroremediation of offshore muds
PDF
Download
Share
Open document
Flip pages
Contact Us
Contact Us
Copy asset link
Request this asset
Transcript (if available)
Content
FEASIBILITY OF IN-SITU REMOVAL OF HEAVY METALS BY
ELECTROREMEDIATION OF OFFSHORE MUDS
by
Muhammad Haroun
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(ENVIRONMENTAL ENGINEERING)
August 2009
Copyright 2009 Muhammad Haroun
ii
Dedication
For the late¸ Malak Kabara, may she rest in peace,
One of the first female lawyers in the Arab World.
A pioneer in her field and in the region.
My grandmother.
For, Sahar Al Halabi,
The UAE’s first practicing Architect.
A self-made woman, who is respected and looked up to by peers,
Whose dreams have been translated into tall and proud structures.
For my mother, for pushing me to build my own dream.
For the memory of the late H.H. Sheikh Zayed bin Sultan Al Nahyan, may he rest
in peace,
The founder and first president of the U.A.E. who has embraced education and
technology based on his tremendous vision, for all the citizens of the U.A.E.
Our Founder and Father.
You have been instrumental in my life, my drive and my ambition.
I have always looked up to you and always will.
I would also like to dedicate this to four distinguished U.A.E. statesmen, H.H.
Sheikh Khalifa bin Zayed Al Nahyan, the president of the U.A.E. and H.H.
Sheikh Mohamed bin Zayed Al Nahyan, the Crown Prince of Abu Dhabi and
Deputy Supreme Commander of the UAE Armed Forces, H.E. Ahmad Khalifa Al
Suwaidi and H.E. Youssef Omeir Al Youssef, all have supplied me with
uninterrupted support to reach the highest levels of education.
iii
Acknowledgements
My thanks for their help and support. This Doctoral Dissertation would not have been
possible without the support and guidance of three groups of individuals: my family; my
professors at USC and Lehigh, and my friends and supervisors in the U.A.E.
First and foremost, my family, without, whom this would not have been possible.
For her inspiration, my late grandmother, Malak Kabbara, one of the first female
practicing lawyers in the Arab world. She was the first person in my life that kept on
pushing me hardest and further into the biggest challenges while reminding me that one
has to make a positive change in this world.
For his motivation, my late grandfather, Dr. Mohammed Saeed Al Halabi, who was the
first U.A.E. practicing surgeon since the late sixties.
For her unwavering support, my mother, Sahar Al Halabi, who was the first practicing
Architect from the U.A.E., she always been a big source of inspiration and motivation.
The sacrifices of my mother, and prayers were the main driving force behind this effort,
For the rest of the women in my family, my sister Reem and aunt Maha. Not only has
their support and encouragement been instrumental in concluding this phase of my life,
but being given the opportunity to look up to so many strong women in my life, and so
iv
close to my path only reinforced in me the need to push and strive to better myself and set
my aims higher.
For my Uncle Hamdi, whose words of wisdom have helped guide me.
I would like to acknowledge the continuous support and guidance of my PhD committee
members, Dr. Meshkati, Dr. Chilingar, Dr. Ershaghi, and Dr. Pamukcu, for making this
Environmental Engineering PhD at USC a reality.
Dr. N. Meshkati has always guided me to organize my thoughts and helped me polish my
presentation style. He has advised me on how best to keep digging through my research
allowing me to stay on target.
Dr. G.V. Chilingar has always been there at all the oddest times of the day and night with
his door open offering me with his generous help, motivation and fuel to feed on my
curiosity in the field of Electrokinetics. This research would have never been possible
without Dr. Chilingar’s meticulous efforts in preparing me to be an independent thinker
while boosting my confidence.
Dr. I. Erhshaghi has provided me with the capability to address all the questions related
to electrokinetics and highlight the originality of this work. He has been there for me
from the very beginning with the generous guidance to ensure the highest quality of work.
He provided me with a clear vision of what is remains to be investigated.
v
Dr. S. Pamukcu has spent countless hours in enlightening me about electroremediation.
She has thoroughly trained me in her lab at Lehigh University, while closely monitoring
my lab performance. She provided me with all the necessary apparti developed through
her electrokinetic lab.
The help extended by Dr. J. P. Bardet, Chairman of The Sonny Astani Civil and
Environmental Engineering at USC, and Dr. T. F. Yen for their motivation and support.
I am also very appreciative for Dr. M. Sahimi, his Ph.D students and lab assistants, who
have been very curteous in giving me access to their ICP-MS at the Chemical
Engineering labs at USC.
I would like to also extend my thanks and appreciation to everyone at USC Viterbi
School of Engineering.
I would also like to extend my appreciation to everyone at The Petroleum Institute, Abu
Dhabi, U.A.E. Starting with Dr. M. Ohadi up to the entire Petroleum Engineering faculty,
research assistants and technicians, and all my friends at ADNOC including Mr. Rashed
Al Zahmi, for all their help and support.
I am also grateful for the full support of the government of the UAE in sponsoring this
research work and for establishing the Electrokinetic Research Center (ERC) at the
vi
Petroleum Institute in Abu Dhabi, U.A.E. This technology will result in further
breakthrough in the fields of enhanced petroleum recovery, ground stabilization, soil and
groundwater remediation, and other possible applications.
vii
Table of Contents
Dedication ii
Acknowledgements iii
List of Tables ix
List of Figures x
Abstract xxiv
Preface: Introduction to Study Area and Heavy Metals in the Environment xxvi
Commonly Encountered Toxic Heavy Metals
Maximum Limits Permissible in Drinking Water according to xlvii
Canadian, U.S. and WHO standards
Statement of the Problem l
Different Solutions for Decontamination li
Chapter One: Electrokinetics 1
Coehn’s rule 22
Electrokinetic Conductance Effects 33
Electrochemical Background 35
Economic Feasibility 55
Summary 60
Chapter Two: Electroremediation 61
Statement of the Problem 66
Concepts and Methods of Biodegradation of Hydrocarbons 68
Methods of Continuous Control and Management of Biodegradation 73
of Hydrocarbons In-Situ
Concepts and Models of Electrokinetic Transport of Contaminants and 76
Their Intermediate Substances
Mathematical Modeling of Contaminant Transport in the Porous 80
Medium
Multicomponent Cleanup Technologies and Examples of Their 89
Application in situ
Electroremediation of Soils 92
Chapter Three: Apparatus and Experimental Procedure 94
and preliminary results of electroremediation
viii
Chapter Four: Experimental results 108
Part I 109
Part II 175
Summary of removal efficiency (R.E.) at the anode region after 297
24 hours of electrokinetic treatment
Chapter Five: Summary and Conclusions 304
Chapter Six: Suggested Future Research Work 306
References 307
Appendix A: Nomenclature 314
ix
List of Tables
Table PreF-1: This table represents only a selection of contaminants that xlvii
are posted in the guidelines.
Table 1-1: Cruze’s (1905) measurements of Weidamann’s constant (V/i) 25
with increasing temperature.
Table 1-2: Variation of electrophoretic velocity with temperature 25
(Burton, 1934.)
Table 4-1: Ground water composition of Jefferson County water, Id 109
(USGS 1989)
Table 4-2-L: Removal efficiency for low concentration tests recorded 173
Table 4-2-H: Removal efficiency for high concentration tests recorded 174
at fractional ends of core.
Table 4-3a: Removal efficiencies vs Canadlian limit, U.S. limit, WHO limit 298
and Gulf limit of heavy metals at anode location after 24-hr EK test using
distilled water with 10 ppm salinity and no pH control.
Table 4-3b: Removal efficiencies vs Canadlian limit, U.S. limit, WHO limit 302
and Gulf limit of heavy metals at anode location after 24-hr EK test using
Abu Dhabi seawater with 26,000 ppm salinity and pH control.
x
List of Figures
Figure PreF-1 A & B: U.A.E. and Arab-Persian Gulf region xxix
Figure PreF-2: Map of Euphrates and Tigris river discharge into the xxx
Arab-Persian Gulf region.
Figure PreF-3: Map of U.A.E. across from Iran along the Strait of Hormuz, xxi
leading though the narrowest width of the Arab-Persian Gulf region.
Figure 1-1: Schematic diagram of Helmholtz double-layer in an electrokinetic 2
flow on application of direct current field. (Modified by Chilingar et al.,
1997.)
Figure 1-2: Electric double layer at the interface between a solid and liquid: 5
x
s
= surface of the solid, x
ζ
= shear plane, x
∞
= bulk liquid, x
ζ
– x
s
= stern layer,
x
∞
– x
ζ
= electrical diffuse (Gouy) layer. (Debye length, l/k). (After Donaldson
and Alam, 2008.)
Figure 1-3: Double layer potentials showing the Helmholtz planes and 7
their potentials. IHP = inner Helmholtz plane (xi). OHP = outer Helmholtz
plane (x = ). (After Donaldson and Alam, 2008.)
Figure 1-4: Two charged surfaces separated by distance d with a fluid 11
between. The film thickness on each surface is h = d/2. The number density
of the counter ions at the surface is ρs and the center is designated ρs which
is taken as zero at the reference point in the center. The electric field, which
is independent of distance is equal to the electric charge density, D, divided
by the electric permittivity, Es = D/εεo. (After Donaldson and Alam, 2008).
Figure 1-5 Curve 1: Repulsion of a surface caused by a double-layer 14
Coulombic charge in the absence of van der Waals attraction. This occurs in
high electrolyte concentrations. Curves 2 to 4: The increasing effect of van der
Waals forces as the thickness of the double layer decreases; this results form
decreasing electrolyte concentration. Curve 4: van der Waals attraction in the
absence of double-layer repulsion. (After Donaldson and Alam, 2008).
Figure 1-6: Schematic representation of zeta potential ((Modified after 16
Zetasizer Nano series technical note, Malvern Instruments,
www.nbtc.cornell.edu)
Figure 1-7: Typical plot of zeta potential (versus pH, showing the position 19
of the isoelectric point and the pH values where the dispersion is expected to
be stable (after Zetasizer Nano series technical note, Malvern Instruments,
www.nbtc.cornell.edu).
xi
Figure 1-8: Schematic diagram of a flow through a wide pore throat of a 40
water-wet reservoir rock showing distribution of anions and cations (double
layer), as envisioned by Wittle et al. (2008). The potential difference between
shear or slipping plane surface between the mobile and immobile double layers
and the free fluids is the zeta potential.
Figure 1-9: Schematic diagram of a double layer distribution in a narrow pore 41
throat of water-wet reservoir and flow as envisioned by Wittle et al. (2008).
Figure 1-10: Relationship between electrical potential gradient and 42
Normalized flow rate. (After Chilingar et al., 1970.)
Figure 1-11: Normalized flow rate (Q/Qi) versus electrical potential gradient 43
(E/L) showing a drop in the total flow rate due to plugging by deposited
copper compounds, (after Anbah et al., 1964, p.5).
Figure 1-12: Imposed electrical potential versus q/qi (actual rate of flow/initial 43
rate of flow) ratio. (After Anbah et al., 1964, p.5.)
Figure 1-13: Electrical current versus normalized flow rate, q/qi 44
(90% silica + 10% Wyo-gel synthetic core). (After Anbah et al., 1964, p.5.)
Figure 1-14: Electrical current versus flow rate, q/qi 45
(95% CaCo3 + 5% Wyo-gel synthetic core). (After Anbah et al., 1964, p.5.)
Figure 1-15: Electrode-arrangement for water flooding operation: (a) The 46
anode is laid down in the injection well to face the producing zone. (b) The
anode is driven into the wet ground near the injection well. (c) Four and five
spot flooding pattern (Anbah et al. 1965).
Figure 1-16: Electrode-arrangement for well stimulation. (a) Anodes are put 47
in specially drilled small-diameter holes around the treated well. (b) Anodes
are put either in shut-in wells or in directionally drilled small-diameter holes
from shut-in wells (Anbah et al. 1965).
Figure 1-17: Electrode-arrangement for selective ion-drive. Conducting pipes 48
driven into the wet ground are used as anodes or cathodes (Anbah et al. 1965).
Figure 1-18: Schematic diagram of locations of cathode and anode in EEOR 49
field operation. (Modified after Anbah et al., 1965; and Titus et al., 1985.)
xii
Figure 1-19: EEOR simulation results: reservoir temperatures after 100, 1000, 52
and 5400 hours of stimulation. Temperatures in oF (ordinate) and distances
are in feet (abscissa), from casing. (After Wittle et al., 2006.)
Figure 1-20: ECGO PAH destruction GCMS changes during treatment. 53
(After Wittle et al., 2008.)
Figure 1-21: Relative permeability curves for polar and non-polar oil. 54
Curves P and P’ are for polar oil, whereas N and N’ are for non-polar oil
(modified after G.A. Babalyan, in: Langnes et al., 1972, p. 229).
Figure 2-1: Contaminant distribution before purging. 85
(After Chilingar et al., 1997.)
Figure 2-2: Contaminant distribution after purging. 86
(After Chilingar et al., 1997.)
Fig 3-1: A schematic diagram showing the first apparatus and connections 94
used in Petroleum Engineering Laboratories at the University of Southern
California. (After Chilingar et al., 1962.)
Fig 3-2: Schematic diagram of second apparatus and connections used in 95
Petroleum Engineering Laboratories at the University of Southern California.
(After Chilingar et al., 1962.)
Fig 3-3: Schematic diagram of glass electrokinetic cell. 96
(After Pamukcu et al., 1993.)
Fig 3-4: Photograph of electrokinetic apparatus and multimeter for measuring 97
voltage, current and resistance. (See Fig. 1-8.)
Fig 3-5a: Electrokinetic apparatus, DC power source and graduated 98
glass burettes to measure both inflow and outflow at each of the two
electrode ends (anode and cathode). (See Fig. 3-3.)
Fig 3-5b: Electrokinetic apparatus, DC power source and graduated glass 98
burettes to measure both inflow and outflow at each of the two electrode
ends (anode and cathode). (See Fig. 1-8.)
Fig 3-6a: Photograph of electrokinetic apparatus for measuring large cores 99
(1 meter x 1 meter x 15 cm). (Designed by Dr. Sibel Pamukcu.)
Fig 3-6b: Photographs of electrokinetic apparatus for measuring large cores 100
(1 meter x 1 meter x 15 cm). (Designed by Dr. Sibel Pamukcu.)
xiii
Figure 3-7: Compaction apparatus used to prepare samples for E-K tests. 106
Figure 4-1-L-a: Results of EK test for electroremediation of arsenic using 111
distilled water (Pamukcu et al., 1993).
Figure 4-1-L-b: Results of EK test for electroremediation of arsenic using 112
distilled water (Pamukcu et al., 1993).
Figure 4-1-L-c: Results of EK test for electroremediation of arsenic 113
distilled water (Pamukcu et al., 1993).
Figure 4-2-L-a: Results of EK test for electroremediation of arsenic using 114
ground water (Pamukcu et al., 1993). (See Table 4-1 for composition)
Figure 4-2-L-b: Results of EK test for electroremediation of arsenic using 115
ground water (Pamukcu et al., 1993). (see Table 4-1 for composition)
Figure 4-2-L-c: Results of EK test for electroremediation of arsenic using 116
ground water (Pamukcu et al., 1993). (see Table 4-1 for composition)
Figure 4-3-L-a: Results of EK test for electroremediation of arsenic using 117
water with humic acid (900ppm) (Pamukcu et al., 1993).
Figure 4-3-L-b: Results of EK test for electroremediation of arsenic using 118
water with humic acid (900ppm) (Pamukcu et al., 1993).
Figure 4-3-L-c: Results of EK test for electroremediation of arsenic using 119
water with humic acid (900ppm) (Pamukcu et al., 1993).
Figure 4-4-L-a: Results of EK test for electroremediation of cadmium using 121
distilled water (Pamukcu et al., 1993).
Figure 4-4-L-b: Results of EK test for electroremediation of cadmium using 122
distilled water (Pamukcu et al., 1993).
Figure 4-4-L-c: Results of EK test for electroremediation of cadmium using 123
distilled water (Pamukcu et al., 1993).
Figure 4-5-L-a: Results of EK test for electroremediation of cadmium using 124
ground water (Pamukcu et al., 1993). (See Table 4-1 for composition)
Figure 4-5-L-b: Results of EK test for electroremediation of cadmium using 125
ground water (Pamukcu et al., 1993). (See Table 4-1 for composition)
xiv
Figure 4-6-L-a: Results of EK test for electroremediation of cadmium 126
using water with humic acid (900ppm) (Pamukcu et al., 1993).
Figure 4-6-L-b: Results of EK test for electroremediation of cadmium 127
using water with humic acid (900ppm) (Pamukcu et al., 1993).
Figure 4-6-L-c: Results of EK test for electroremediation of cadmium using 128
water with humic acid (900ppm) (Pamukcu et al., 1993).
Figure 4-7-L-a: Results of EK test for electroremediation of chromium using 130
distilled water (Pamukcu et al., 1993).
Figure 4-7-L-b: Results of EK test for electroremediation of chromium 131
using distilled water (Pamukcu et al., 1993).
Figure 4-7-L-c: Results of EK test for electroremediation of chromium 132
using distilled water (Pamukcu et al., 1993).
Figure 4-7-H-a: Results of EK test for electroremediation of chromium 133
using distilled water.
Figure 4-7-H-b: Results of EK test for electroremediation of chromium 134
using distilled water.
Figure 4-7-H-c: Results of EK test for electroremediation of chromium 135
using distilled water.
Figure 4-8-L-a: Results of EK test for electroremediation of chromium 136
using ground water (Pamukcu et al., 1993).
(See Table 4-1 for composition)
Figure 4-8-L-b: Results of EK test for electroremediation of chromium using 137
ground water (Pamukcu et al., 1993). (See Table 4-1 for composition)
Figure 4-8-L-c: Results of EK test for electroremediation of chromium using 138
ground water (Pamukcu et al., 1993). (See Table 4-1 for composition)
Figure 4-9-L: Results of EK test for electroremediation of chromium using 139
water with humic acid (900ppm) (Pamukcu et al., 1993).
Figure 4-9-H-a: Results of EK test for electroremediation of chromium 140
using water with humic substances (900ppm).
Figure 4-10-L-a: Results of EK test for electroremediation of lead using 142
distilled water (Pamukcu et al., 1993).
xv
Figure 4-10-L-b: Results of EK test for electroremediation of lead 143
using distilled water (Pamukcu et al., 1993).
Figure 4-10-L-c: Results of EK test for electroremediation of lead using 144
distilled water (Pamukcu et al., 1993).
Figure 4-10-H-a: Results of EK test for electroremediation of lead using 145
distilled water.
Figure 4-10-H-b: Results of EK test for electroremediation of lead using 146
distilled water.
Figure 4-10-H-c: Results of EK test for electroremediation of lead using 147
distilled water.
Figure 4-11-L-a: Results of EK test for electroremediation of lead using 148
ground water (Pamukcu et al., 1993). (See Table 4-1 for composition)
Figure 4-11-L-b: Results of EK test for electroremediation of lead using 149
ground water (Pamukcu et al., 1993). (See Table 4-1 for composition)
Figure 4-11-L-c: Results of EK test for electroremediation of lead using 150
ground water (Pamukcu et al., 1993). (See Table 4-1 for composition)
Figure 4-12-L-a: Results of EK test for electroremediation of lead using 151
water with humic acid (900ppm) (Pamukcu et al., 1993).
Figure 4-12-L-b: Results of EK test for electroremediation of lead using 152
water with humic acid (900ppm) (Pamukcu et al., 1993).
Figure 4-12-L-c: Results of EK test for electroremediation of lead using 153
water with humic acid (900ppm) (Pamukcu et al., 1993).
Figure 4-12-H-a: Results of EK test for electroremediation of lead using 154
water with humic acid (900ppm).
Figure 4-12-H-b: Results of EK test for electroremediation of lead using 155
water with humic acid (900ppm).
Figure 4-15-H-c: Results of EK test for electroremediation of lead using 156
water with humic acid (900ppm).
Figure 4-16-L: pH values before and after EK test for electroremediation 157
of arsenic using distilled water (Pamukcu et al., 1993).
xvi
Figure 4-17-L: pH values before and after EK test for electroremediation 158
of arsenic using ground water (Pamukcu et al., 1993). (See Table 4-1 for
composition).
Figure 4-18-L: pH values before and after EK test for electroremediation 159
of arsenic using water with humic acid (900ppm) (Pamukcu et al., 1993).
Figure 4-19-L: pH values before and after EK test for electroremediation 160
of cadmium using distilled water (Pamukcu et al., 1993).
Figure 4-20-L: Results of pH before and after EK test for electroremediation 161
of cadmium using ground water (Pamukcu et al., 1993).
(See Table 2-1 for composition).
Figure 4-21-L: pH values before and after EK test for electroremediation 162
of cadmium using water with humic acid (900ppm) (Pamukcu et al., 1993).
Figure 4-22-L: pH values before and after EK test for electroremediation 163
of chromium using distilled water (Pamukcu et al., 1993).
Figure 4-22-H: pH values before and after EK test for electroremediation of 164
chromium using distilled water.
Figure 4-23-L: pH values before and after EK test for electroremediation of 165
chromium using ground water (Pamukcu et al., 1993).
(See Table 2-1 for composition)
Figure 4-24-L: pH values before and after EK test for electroremediation 166
of chromium using water with humic acid (900ppm) (Pamukcu et al., 1993).
Figure 4-24-H: pH values before and after EK test for electroremediation 167
of chromium using water with humic acid (900ppm).
Figure 4-25-L: pH values before and after EK test for electroremediation of 168
lead using distilled water (Pamukcu et al., 1993).
Figure 4-25-H: pH values before and after EK test for electroremediation of 169
lead using distilled water.
Figure 4-26-L: pH values before and after EK test for electroremediation of 170
lead using ground water (Pamukcu et al., 1993).
(See Table 2-1 for composition).
xvii
Figure 4-27-L: pH values before and after EK test for electroremediation 171
of lead using water with humic acid (900ppm). (Pamukcu et al., 1993).
Figure 4-27-H: pH values before and after EK test for electroremediation 172
of lead using water with humic acid (900ppm).
Figure 4-28-a: Abu Dhabi Island – Study Area A 175
Figure 4-28-b: Al-Ruwais (Ruwais Industrial Complex) – Study Area B 176
Figure 4-28-c: Concentration profile of As after 24-hr EK test a long sample 182
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-29: Concentration profile of As after 24-hr EK test a long sample 183
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-30: Concentration profile of As after 24-hr EK test a long sample 184
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-31: Concentration profile of Ba after 24-hr EK test a long sample 186
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-32: Concentration profile of Ba after 24-hr EK test a long sample 187
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-33: Concentration profile of Ba after 24-hr EK test a long sample 188
length. (Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm
maleic acid)
Figure 4-34: Concentration profile of Be after 24-hr EK test a long sample 190
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-35: Concentration profile of Be after 24-hr EK test a long sample 191
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-36: Concentration profile of Be after 24-hr EK test a long sample 192
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-37: Concentration profile of Be after 24-hr EK test a long sample 193
length. (Abu Dhabi offshore mud, 26,000 ppm salinity &
450 ppm maleic acid)
Figure 4-38: Concentration profile of Bi after 24-hr EK test a long sample 196
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
xviii
Figure 4-39: Concentration profile of Bi after 24-hr EK test a long sample 197
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-40: Concentration profile of Bi after 24-hr EK test a long sample 198
length. (Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm
maleic acid)
Figure 4-41: Concentration profile of Cd after 24-hr EK test a long 200
sample length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-42: Concentration profile of Cd after 24-hr EK test a long sample 201
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-43: Concentration profile of Cd after 24-hr EK test a long sample 202
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-44: Concentration profile of Cd after 24-hr EK test a long sample 203
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-45: Concentration profile of Cs after 24-hr EK test a long sample 206
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-46: Concentration profile of Cs after 24-hr EK test a long sample 207
length. (Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic
acid)
Figure 4-47: Concentration profile of Cr after 24-hr EK test a long sample 209
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-48: Concentration profile of Cr after 24-hr EK test a long sample 210
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-49: Concentration profile of Cu after 24-hr EK test a long sample 213
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-50: Concentration profile of Cu after 24-hr EK test a long sample 214
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-51: Concentration profile of Cu after 24-hr EK test a long sample 215
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-52: Concentration profile of Cu after 24-hr EK test a long sample 216
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
xix
Figure 4-53: Concentration profile of Cu after 24-hr EK test a long sample 217
length. (Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm
maleic acid)
Figure 4-54: Concentration profile of Ga after 24-hr EK test a long sample 219
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-55: Concentration profile of Ga after 24-hr EK test a long sample 220
length. (Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm
maleic acid)
Figure 4-56: Concentration profile of In after 24-hr EK test a long sample 222
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-57: Concentration profile of In after 24-hr EK test a long sample 223
length. (Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm
maleic acid)
Figure 4-58: Concentration profile of Pb after 24-hr EK test a long sample 225
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-59: Concentration profile of Pb after 24-hr EK test a long sample 226
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-60: Concentration profile of Pb after 24-hr EK test a long sample 227
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-61: Concentration profile of Pb after 24-hr EK test a long sample 228
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-62: Concentration profile of Pb after 24-hr EK test a long sample 229
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-63: Concentration profile of Li after 24-hr EK test a long sample 232
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-64: Concentration profile of Li after 24-hr EK test a long sample 233
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-65: Concentration profile of Li after 24-hr EK test a long 234
sample length. (Abu Dhabi offshore mud, 26,000 ppm salinity & 450
ppm maleic acid)
Figure 4-66: Concentration profile of Rb after 24-hr EK test a long sample 236
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
xx
Figure 4-67: Concentration profile of Rb after 24-hr EK test a long sample 237
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-68: Concentration profile of Rb after 24-hr EK test a long sample 238
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-69: Concentration profile of Rb after 24-hr EK test a long sample 239
length. (Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm
maleic acid)
Figure 4-70: Concentration profile of Se after 24-hr EK test a long sample 242
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-71: Concentration profile of Se after 24-hr EK test a long sample 243
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-72: Concentration profile of Se after 24-hr EK test a long sample 244
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-73: Concentration profile of Se after 24-hr EK test a long sample 245
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-74: Concentration profile of Se after 24-hr EK test a long sample 246
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-75: Concentration profile of Se after 24-hr EK test a long sample 247
length. (Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm
maleic acid)
Figure 4-76: Concentration profile of Ag after 24-hr EK test a long 249
sample length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-77: Concentration profile of Ag after 24-hr EK test a long sample 250
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-78: Concentration profile of Ag after 24-hr EK test a long 251
sample length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-79: Concentration profile of Ag after 24-hr EK test a long sample 252
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-80: Concentration profile of Ag after 24-hr EK test a long sample 253
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
xxi
Figure 4-81: Concentration profile of Al after 24-hr EK test a long sample 255
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-82: Concentration profile of Al after 24-hr EK test a long sample 256
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-83: Concentration profile of Al after 24-hr EK test a long sample 257
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-84: Concentration profile of Co after 24-hr EK test a long sample 259
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-85: Concentration profile of Co after 24-hr EK test a long sample 260
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-86: Concentration profile of Sr after 24-hr EK test a long sample 263
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-87: Concentration profile of Sr after 24-hr EK test a long sample 264
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-88: Concentration profile of Sr after 24-hr EK test a long sample 265
length. (Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm
maleic acid)
Figure 4-89: Concentration profile of Ti after 24-hr EK test a long sample 267
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-90: Concentration profile of Ti after 24-hr EK test a long sample 268
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-91: Concentration profile of Ti after 24-hr EK test a long sample 269
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-92: Concentration profile of Ti after 24-hr EK test a long sample 270
length. (Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm
maleic acid)
Figure 4-93: Concentration profile of Ur after 24-hr EK test a long sample 273
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-94: Concentration profile of Ur after 24-hr EK test a long sample 274
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
xxii
Figure 4-95: Concentration profile of V after 24-hr EK test a long sample 277
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-96: Concentration profile of V after 24-hr EK test a long sample 278
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-97: Concentration profile of V after 24-hr EK test a long sample 279
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-98: Concentration profile of V after 24-hr EK test a long sample 280
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-99: Concentration profile of V after 24-hr EK test a long sample 281
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-100: Concentration profile of V after 24-hr EK test a long sample 282
length. (Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm
maleic acid)
Figure 4-101: Concentration profile of Zn after 24-hr EK test a long sample 285
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-102: Concentration profile of Zn after 24-hr EK test a long sample 286
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-103: Concentration profile of Zn after 24-hr EK test a long sample 287
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-104: Concentration profile of Zn after 24-hr EK test a long sample 288
length. (Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm
maleic acid).
Figure 4-105: Concentration profile of Mn after 24-hr EK test a long sample 290
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-106: Concentration profile of Mn after 24-hr EK test a long sample 291
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-107: Concentration profile of Ni after 24-hr EK test a long sample 293
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-108: Concentration profile of Ni after 24-hr EK test a long sample 294
length (Abu Dhabi offshore mud, distilled water 10 ppm salinity).
xxiii
Figure 4-109: 24 – Electrokinetic flow during the 24 hour test using different 296
salinity water on offshore mud samples of Abu Dhabi having varying
concentrations of heavy metals.
xxiv
Abstract
The present experimental work is directed towards investigation of the
electokinetically-enhanced transport of soil contaminants (specifically heavy metals) in
clay media and offshore muds.
The electrokinetic process is an emerging technology for in-situ soil
decontamination, in which chemical species, both ionic and nonionic, are transported to
electrode sites in soil. Electrokinetics refers to movement of water, ions and charged
particles relative to one another under the action of an applied direct current electric field.
In a porous compact matrix of surface-charged particles such as soil, the pore fluid
containing ions are made to flow to the collection sites under the applied electric field
(Pamukcu et al., 1993).
Remediation of anthropogenically contaminated clay-soil media were conducted
by Dr. Pamukcu at Lehigh University. Experiments of high concentrations of heavy
metals in clay-soil media were conducted at the University of Southern California by the
writer. Water containing acids were used for pH control.
The EK tests were performed for 24 hrs, and the initial and final concentrations
were analyzed using an ICP-MS equipment. The removal efficiency, initial and final pH
of slurry at 3 positions was recorded.
The effectiveness of the process demonstrated that up to 99% of initial
concentrations of metals can be removed from soil. In this process, the pH and
contaminant type was found to influence the removal rather than the electroosmotic flow.
xxv
In the absence of pH control mechanisms, the basic conditions developed at the cathode,
causing most of the metals to precipitate near the cathode as carbonates and hydroxides.
pH adjustment at the cathode appeared to minimize such precipitation and to enhance the
removal of some heavy metals.
Applicability of this electrokinetic technology in remediating offshore muds from
heavy metals was not evaluated to date. Tests were made using 22 different offshore mud
samples from different locations in Abu Dhabi, U.A.E., contaminated with 29 different
heavy metals. The experimental work was performed by the writer at the newly-
established Electrokinetic laboratories at the Petroleum Institute in Abu Dhabi, U.A.E. In
the process it was determined that D.C. current can be used to decontaminate the offshore
muds from heavy metals.
xxvi
Preface: Introduction to Study Area and Heavy Metals in the
Environment
Anthropogenic input of toxic contaminants into the environment has lead to
detrimental effects to the health of humans and animals. Contamination of soil and
ground water is also of great concern. The writer concentrated on inorganic contaminants.
The inorganic group, specifically heavy metals, exist in nature in very small
concentrations and are known as trace metals. Certain regions around the world are rich
in specific heavy metals present in water, e.g., Arsenic in South East Asia and Strontium
in the U.A.E. Certain industries, including oil and gas, petrochemical, mining, metallurgy,
landfills, and sewage systems contribute a significant increase in their concentration in
soils and offshore muds, in many cases augmenting the concentrations by several orders
of magnitude.
Certain heavy metals at low concentrations, however, may benefit life within our
ecosystems, e.g., chromium which accelerates the growth of plants. Once the pre-existing
trace concentrations are significantly increased, all forms of life are subjected to toxic
levels causing detrimental health problems, including cancer.
Among the leading emerging technologies for in-situ soil and ground
decontamination is Electrokinetics technology. As a result of application of DC current,
cations move towards the cathode, whereas anions move towards the anode.
Electrokinetics technology has been proven to be a viable method for
environmental restoration, i.e., the removal of soil contaminants in-situ (Chilingar et al.,
1952-2008; Pamukcu el al., 1991- 2008). The results obtained by the writer for heavy
metals confirm the above conclusion. The viability of using this technology to remediate
xxvii
the large volumes of offshore muds of Abu Dhabi, U.A.E., contaminated with heavy
metals, appears to be feasible.
In electrobioremediation, a term coined by Professor George V. Chilingar, the
function of D.C. current is mainly to drive bacteria and nutrients to considerable
distances inside the formation to be treated. Otherwise, bioremediation alone is not as
effective because one cannot inject bacteria and nutrients deep enough due to low
permeability of soils. Electrobioremediation would be considered in the future testing
phases together with the upscaling for pilot tests.
Offshore muds are composed of clays, which are predominantly negatively
charged and, therefore, act as storage “sponges” for positively charged heavy metals,
which can be absorbed and adsorbed in muds. Offshore muds are being deposited daily
across the coastlines worldwide, acting as toxic supply to the marine environment. This is
affecting the ecosystem due the suddenly significant concentrations of toxic and
carcinogenic compounds, leading to adverse health effects to all the coastline
communities. Whereas people whose diet is heavily focused on seafood are the most
affected, epidemiological studies conducted are showing evidence that water sources and
agriculture are affected by the sudden increase in the heavy metal concentration, leading
to detrimental health effects.
Most of the presence of heavy metals present in the offshore muds is due to
unregulated industrial discharges and lack of environmental proactive technology. For
example, in the Arabian-Persian Gulf area there is a very heavy oil/gas traffic, which
contributes heavily to both organic and inorganic contaminations. The increasing health
concerns are due to both the industrial toxic and carcinogenic heavy metals. Complex
xxviii
combinations of heavy metals, e.g., strontium plus chromium, leads to bone cancer
among other diseases.
The Euphrates and Tigris rivers discharge large volumes of sediments into the
Gulf waters that are deposited all across the Gulf on both the Arabian and Iranian
coastlines. Together with most refineries and aluminum, petrochemical and desalinization
plants, 40% (with projections of up to 70% of the world oil production by 2030) of the
daily world oil production is being shipped out continuously through the Gulf. Thus,
there exists a critical problem of frequent spills and contaminant discharge into the
relatively stagnant large water body. The United Arab Emirates is located at the outlet of
the Gulf waters leading to the Arabian Sea at the neck of the Gulf. Abu Dhabi, U.A.E.
stretches across the narrowest passage of the Gulf waters across from the straits of
Hormoz at the outlet of the Gulf water. Therefore, large quantities of offshore muds are
deposited along its coastline. (www.eia.doe.gov).
In addition, the hydrodynamic water current of the Arab-Persian Gulf follows a
counterclockwise direction that could be increasing further the contamination by heavy
metals of offshore muds. Therefore, Abu Dhabi, U.A.E. was selected as a prime
candidate for conducting the World’s first electrokinetic tests to attempt to decontaminate
the large quantities of offshore muds from toxic and carcinogenic heavy metals.
Figure PreF-1 A & B: U.A.E. and Arab-Persian Gulf region. (World Atlas)
EUPHRATES
Rising in the Caucasus Mountains of Armenia, it flows southwesterly across west-central
Turkey, then generally southeast through Syria and Iraq, ending in the waters of the
Persian Gulf.
xxix
It joins with the Tigris in southern Iraq, and from that junction continues on as the
Shatt al Arab. Overall it's (2,235 miles) (3,596 km) in length, and is certainly the longest
river in the Middle East. Historically important in ancient history, the once great city of
Babylon stood on its banks.
TIGRIS
Rising in the mountains of southern Turkey, the Tigris flows southeast through Iraq,
where in the southern part of that country it merges with the Euphrates to become the
Shatt al Arab, which then flows to the Persian Gulf. The river has numerous small
tributaries running from it's eastern bank, and is (1,180 miles) (1,899 km) in length.
Figure PreF-2: Map of Euphrates and Tigris river discharge into the Arab-
Persian Gulf region (World Atlas).
xxx
Figure PreF-3: Map of U.A.E. across from Iran along the Starit of Hormuz,
leading though the narrowest width of the Arab-Persian Gulf region
(GraphicMaps.com).
Persian Gulf, arm of the Arabian Sea, is in southwestern Asia, between the
Arabian Peninsula on the southwest and Iran on the northeast. The Gulf extends
Northwest 970 km (600 mi) from the Strait of Hormuz to the Shatt al Arab, a river
formed by the confluence of the Tigris and Euphrates rivers. The Gulf is connected to the
Arabian Sea by the Strait of Hormuz and the Gulf of Oman. The Persian Gulf varies in
width from 47 to 370 km (29 to 230 mi). The area is 230,000 sq. km (89,000 sq. mi) and
the greatest depth is 102 m (335 ft). The chief islands in the Gulf are Qeshm (belonging
xxxi
xxxii
to Iran) and the Island nation of Bahrain. The United Arab Emirates, Saudi Arabia, Qatar,
and Kuwait are on the south and Southwestern shores; Iraq is on the Northern tip; Iran is
on the Northeastern shore; and the Northern tip of Oman is to the West. (Encyclopedia).
The Iranian shore of the Persian Gulf is largely mountainous and fringed with
cliffs. Sandy beaches line the Arabian shore, which is broken by many small islands and
lagoons. Large banks of pearl-producing mollusks are found off the Arabian coast.
Spectacular cliffs rise from the shore around the Musandam Peninsula near the Strait of
Hormuz at the Southeastern end of the Gulf. The Tigris, Euphrates, and K ār ūn rivers
deposit large amounts of silt as they empty into the Gulf in the Northwest. The Persian
Gulf region is known for its high temperatures, uncomfortable humidity, and low rainfall.
(Encyclopedia).
The Persian Gulf and its surrounding countries contain about 66 percent of the
world’s proven reserves of oil and about 36 percent of total natural gas reserves (Year
2000 estimate). New reserves are still being discovered, both on land and offshore. Large
amounts of oil are refined in the area, and oil tankers carry oil from marine terminals to
all parts of the world. Major offshore oil fields include Safaniyah (belonging to Saudi
Arabia), the largest offshore oil field in the world; and Khafji and Hout, divided between
Saudi Arabia and Kuwait. Principal offshore gas fields include the North Field (Qatar),
the largest gas field in the world; Dorra (Saudi Arabia and Kuwait); and South Pars (Iran).
In 2000 the Persian Gulf region produced almost 29 percent of the world's oil. The
principal ports on the Persian Gulf include Kuwait, in Kuwait; Ad Damm ām and Al
Jubayl, in Saudi Arabia; B ūshehr, in Iran; and M īnā’ Salm ān, near Manama, in Bahrain.
Major oil spills in 1983, during the Iran-Iraq War, and in 1991, during the Persian Gulf
xxxiii
War, have adversely affected the Gulf environment, as has oil pollution from routine
tanker operations. (Encyclopedia).
Heavy metals in our environment:
There are 35 metals that are of concern because of occupational or residential exposure;
23 of these are the heavy elements or "heavy metals": antimony, arsenic, bismuth,
cadmium, cerium, chromium, cobalt, copper, gallium, gold, iron, lead, manganese,
mercury, nickel, platinum, silver, tellurium, thallium, tin, uranium, vanadium, and zinc
(Glanze, 1996). Interestingly, small amounts of these elements are common in our
environment and diet and are actually necessary for good health, but large amounts of
any of them may cause acute or chronic toxicity (poisoning). Heavy metal toxicity can
result in damaged or reduced mental and central nervous function, lower energy levels,
and result in damage to blood composition, lungs, kidneys, liver, and other vital organs.
Long-term exposure may result in slowly progressing physical, muscular, and
neurological degenerative processes that mimic Alzheimer's disease, Parkinson's disease,
muscular dystrophy, and multiple sclerosis. Allergies are not uncommon and repeated
long-term contact with some metals or their compounds may even cause cancer
(International Occupational Safety and Health Information Centre, 1999).
For some heavy metals, toxic levels can be just above the background
concentrations naturally found in nature. Therefore, it is important for to know about the
heavy metals and to take protective measures against excessive exposure. In most parts of
the United States, heavy metal toxicity is an uncommon medical condition; however, it is
a clinically significant condition when it does occur. If unrecognized or inappropriately
xxxiv
treated, toxicity can result in significant illness and reduced quality of life (Ferner, 2001).
For persons who suspect that they or someone in their household might have heavy metal
toxicity, testing is essential. Appropriate conventional and natural medical procedures
may need to be pursued (Dupler, 2001).
The association of symptoms indicative of acute toxicity is not difficult to
recognize because the symptoms are usually severe, rapid in onset, and associated with a
known exposure or ingestion (Ferner, 2001): cramping, nausea, and vomiting; pain;
sweating; headaches; difficulty breathing; impaired cognitive, motor, and language skills;
mania; and convulsions. The symptoms of toxicity resulting from chronic exposure
(impaired cognitive, motor, and language skills; learning difficulties; nervousness and
emotional instability; and insomnia, nausea, lethargy, and feeling ill) are also easily
recognized; however, they are much more difficult to associate with their cause.
Symptoms of chronic exposure are very similar to symptoms of other health conditions
and often develop slowly over months or even years. Sometimes the symptoms of chronic
exposure actually abate from time to time, leading the person to postpone seeking
treatment, thinking the symptoms are related to something else. (Life Extension on Heavy
Metal Toxicology).
DEFINITION OF A HEAVY METAL
"Heavy metals" are chemical elements with a specific gravity that is at least 5
times the specific gravity of water. The specific gravity of water is 1 at 4°C (39°F).
Simply stated, specific gravity is a measure of density of a given amount of a solid
substance when it is compared to an equal amount of water. Some well-known toxic
xxxv
metallic elements with a specific gravity that is 5 or more times that of water are arsenic,
5.7; cadmium, 8.65; iron, 7.9; lead, 11.34; and mercury, 13.546 (Lide, 1992).
BENEFICIAL HEAVY METALS
In small quantities, certain heavy metals are nutritionally essential for a healthy
life. Some of these are referred to as the trace elements (e.g., iron, copper, manganese,
and zinc). These elements, or some of their compounds, are commonly found naturally in
foodstuffs, in fruits and vegetables, and in commercially available multivitamin products
(International Occupational Safety and Health Information Centre, 1999). Diagnostic
medical applications include direct injection of gallium during radiological procedures,
dosing with chromium in parenteral nutrition mixtures, and the use of lead as a radiation
shield around x-ray equipment (Roberts, 1999). Heavy metals are also common in
industrial applications such as in the manufacture of pesticides, batteries, alloys,
electroplated metal parts, textile dyes, steel, and so forth. (International Occupational
Safety and Heath Information Centre, 1999). (Life Extension on Heavy Metal
Toxicology).
TOXIC HEAVY METALS
Heavy metals become toxic when they are not metabolized by the body and
accumulate in the soft tissues. Heavy metals may enter the human body through food,
water, air, or absorption through the skin when they come in contact with humans in
agriculture and in manufacturing, pharmaceutical, industrial, or residential settings.
Industrial exposure accounts for a common route of exposure for adults. Ingestion is the
xxxvi
most common route of exposure in children (Roberts, 1999). Children may develop toxic
levels from the normal hand-to-mouth activity of small children who come in contact
with contaminated soil or by actually eating objects that are not food (dirt or paint chips)
(Dupler, 2001). Less common routes of exposure are during a radiological procedure,
from inappropriate dosing or monitoring during intravenous (parenteral) nutrition, from a
broken thermometer (Smith et al., 1997), or from a suicide or homicide attempt (Lupton
et al., 1985).
As a rule, acute poisoning is more likely to result from inhalation or skin contact
of dust, fumes or vapors, or materials in the workplace. However, lesser levels of
contamination may occur in residential settings, particularly in older homes with lead
paint or old plumbing (International Occupational Safety and Health Information Centre
1999). The Agency for Toxic Substances and Disease Registry (ATSDR) in Atlanta,
Georgia, (a part of the U.S. Department of Health and Human Services) was established
by congressional mandate to perform specific functions concerning adverse human health
effects and diminished quality of life associated with exposure to hazardous substances.
The ATSDR is responsible for assessment of waste sites and providing health
information concerning hazardous substances, response to emergency release situations,
and education and training concerning hazardous substances (ATSDR Mission Statement,
November 7, 2001). In cooperation with the U.S. Environmental Protection Agency, the
ATSDR has compiled a Priority List for 2001 called the "Top 20 Hazardous Substances."
The heavy metals arsenic (1), lead (2), mercury (3), and cadmium (7) appear on this list.
(Life Extension on Heavy Metal Toxicology).
xxxvii
According to Life Extension, the commonly encountered Toxic Heavy Metals are as
follows:
Arsenic
Lead
Mercury
Cadmium
Iron
Aluminum
As noted earlier, there are 35 metals of concern, with 23 of them called the heavy
metals. Toxicity can result from any of these metals. This protocol will address the metals
that are most likely encountered in our daily environment. Briefly covered will be four
metals that are included in the ATSDR's "Top 20 Hazardous Substances" list. Iron and
aluminum will also be discussed even though they do not appear on the ATSDR's list.
ARSENIC
Arsenic is the most common cause of acute heavy metal poisoning in adults and is
number 1 on the ATSDR's "Top 20 List." Arsenic is released into the environment by the
smelting process of copper, zinc, and lead, as well as by the manufacturing of chemicals
and glasses. Arsine gas is a common byproduct produced by the manufacturing of
pesticides that contain arsenic. Arsenic may be also be found in water supplies worldwide,
leading to exposure of shellfish, cod, and haddock. Other sources are paints, rat poisoning,
xxxviii
fungicides, and wood preservatives. Target organs are the blood, kidneys, and central
nervous, digestive, and skin systems (Roberts 1999; ATSDR ToxFAQs for Arsenic).
LEAD
Lead is number 2 on the ATSDR's "Top 20 List." Lead accounts for most of the
cases of pediatric heavy metal poisoning (Roberts 1999). It is a very soft metal and was
used in pipes, drains, and soldering materials for many years. Millions of homes built
before 1940 still contain lead (e.g., in painted surfaces), leading to chronic exposure from
weathering, flaking, chalking, and dust. Every year, industry produces about 2.5 million
tons of lead throughout the world. Most of this lead is used for batteries. The remainder is
used for cable coverings, plumbing, ammunition, and fuel additives. Other uses are as
paint pigments and in PVC plastics, x-ray shielding, crystal glass production, and
pesticides. Target organs are the bones, brain, blood, kidneys, and thyroid gland
(International Occupational Safety and Health Information Centre 1999; ATSDR
ToxFAQs for Lead).
MERCURY
Number 3 on ATSDR's "Top 20 List" is mercury. Mercury is generated naturally
in the environment from the degassing of the earth's crust, from volcanic emissions. It
exists in three forms: elemental mercury and organic and inorganic mercury. Mining
operations, chloralkali plants, and paper industries are significant producers of mercury
(Goyer, 1996). Atmospheric mercury is dispersed across the globe by winds and returns
to the earth in rainfall, accumulating in aquatic food chains and fish in lakes (Clarkson,
xxxix
1990). Mercury compounds were added to paint as a fungicide until 1990. These
compounds are now banned; however, old paint supplies and surfaces painted with these
old supplies still exist. Mercury continues to be used in thermometers, thermostats, and
dental amalgam. (Many researchers suspect dental amalgam as being a possible source of
mercury toxicity [Omura et al., 1996; O'Brien, 2001]). Medicines, such as
mercurochrome and merthiolate, are still available. Algaecides and childhood vaccines
are also potential sources. Inhalation is the most frequent cause of exposure to mercury.
The organic form is readily absorbed in the gastrointestinal tract (90-100%); lesser but
still significant amounts of inorganic mercury are absorbed in the gastrointestinal tract (7-
15%). Target organs are the brain and kidneys (Roberts 1999; ATSDR ToxFAQs for
Mercury).
CADMIUM
Cadmium is a byproduct of the mining and smelting of lead and zinc and is
number 7 on ATSDR's "Top 20 list." It is used in nickel-cadmium batteries, PVC plastics,
and paint pigments. It can be found in soils because insecticides, fungicides, sludge, and
commercial fertilizers that use cadmium are used in agriculture. Cadmium may be found
in reservoirs containing shellfish. Cigarettes also contain cadmium. Lesser-known
sources of exposure are dental alloys, electroplating, motor oil, and exhaust. Inhalation
accounts for 15-50% of absorption through the respiratory system; 2-7% of ingested
cadmium is absorbed in the gastrointestinal system. Target organs are the liver, placenta,
kidneys, lungs, brain, and bones (Roberts 1999; ATSDR ToxFAQs for Cadmium).
xl
IRON
Discussion of iron toxicity in this protocol is limited to ingested or environmental
exposure. Iron overload disease (hemochromatosis), an inherited disorder, is discussed in
a separate protocol. Iron does not appear on the ATSDR's "Top 20 List," but it is a heavy
metal of concern, particularly because ingesting dietary iron supplements may acutely
poison young children (e.g., as few as five to nine 30-mg iron tablets for a 30-lb child).
Ingestion accounts for most of the toxic effects of iron because iron is absorbed
rapidly in the gastrointestinal tract. The corrosive nature of iron seems to further increase
the absorption. Most overdoses appear to be the result of children mistaking red-coated
ferrous sulfate tablets or adult multivitamin preparations for candy. (Fatalities from
overdoses have decreased significantly with the introduction of child-proof packaging. In
recent years, blister packaging and the requirement that containers with 250 mg or more
of iron have child-proof bottle caps have helped reduce accidental ingestion and overdose
of iron tablets by children.) Other sources of iron are drinking water, iron pipes, and
cookware. Target organs are the liver, cardiovascular system, and kidneys (Roberts 1999).
ALUMINUM
Although aluminum is not a heavy metal (specific gravity of 2.55-2.80), it makes
up about 8% of the surface of the earth and is the third most abundant element (ATSDR
ToxFAQs for Aluminum). It is readily available for human ingestion through the use of
food additives, antacids, buffered aspirin, astringents, nasal sprays, and antiperspirants;
from drinking water; from automobile exhaust and tobacco smoke; and from using
xli
aluminum foil, aluminum cookware, cans, ceramics, and fireworks (ATSDR ToxFAQs
for Aluminum).
Studies began to emerge about 20 years ago suggesting that aluminum might have
a possible connection with developing Alzheimer's disease when researchers found what
they considered to be significant amounts of aluminum in the brain tissue of Alzheimer's
patients. Although aluminum was also found in the brain tissue of people who did not
have Alzheimer's disease, recommendations to avoid sources of aluminum received
widespread public attention. As a result, many organizations and individuals reached a
level of concern that prompted them to dispose of all their aluminum cookware and
storage containers and to become wary of other possible sources of aluminum, such as
soda cans, personal care products, and even their drinking water (Anon., 1993).
However, the World Health Organization (WHO, 1998) concluded that, although
there were studies that demonstrate a positive relationship between aluminum in drinking
water and Alzheimer's disease, the WHO had reservations about a causal relationship
because the studies did not account for total aluminum intake from all possible sources.
Although there is no conclusive evidence for or against aluminum as a primary cause for
Alzheimer's disease, most researchers agree that it is an important factor in the dementia
component and most certainly deserves continuing research efforts. Therefore, at this
time, reducing exposure to aluminum is a personal decision. Workers in the automobile
manufacturing industry also have concerns about long-term exposure to aluminum
(contained in metal working fluids) in the workplace and the development of
degenerative muscular conditions and cancer (Brown, 1998; Bardin et al., 2000). The
ATSDR has compiled a ToxFAQs for Aluminum to answer the most frequently asked
xlii
health questions about aluminum. Target organs for aluminum are the central nervous
system, kidney, and digestive system.
Selenium and Zinc
Deficiency of selenium and zinc, important antioxidant micronutrients,
contributes to compromised immunity (Girodon et al., 1999) and lowered defense against
free radicals (Porter et al., 1999; Schumacher, 1999). Selenium and zinc act as cofactors
of antioxidant enzymes to protect against oxygen free radicals produced during oxidative
stress (Leung, 1998). Selenium is often found to be deficient in persons who have
experienced physical trauma. Porter et al. (1999) concluded that patients who
experienced severe trauma had fewer infections and less organ dysfunction when they
received selenium supplementation. Interestingly, studies on the protective benefits of
selenium have implications in the management of persons receiving chemotherapy,
enhancing mediation of oxygen free-radical damage to normal tissue, and decreasing side
effects such as nausea, emesis, vertigo, unsteady gait, and seizures caused by the
chemicals and drugs used in chemotherapy (Pakdaman, 1998). This is possibly a
characteristic of persons with brain tumors who frequently have low blood levels of
selenium (Pakdaman, 1998; Schumacher, 1999).
xliii
Strontium
Strontium is a soft, silver-yellow, alkaline-earth metal. It has three allotropic
crystalline forms and in its physical and chemical properties it is similar to calcium and
barium. Strontium reacts vigorously with water and quickly tarnishes in air, so it must be
stored out of contact with air and water. Due to its extreme reactivity to air, this element
always naturally occurs combined with other elements and compounds. Finely powdered
strontium metal will ignite spontaneously in air to produce both strontium oxide and
strontium nitride.
Applications
Strontium has uses similar to those of calcium and barium, but it is rarely
employed because of its higher cost. Principal uses of strontium compounds are in
pyrotechnics, for the brilliant reds in fireworks and warning flares and in greases. A little
is used as a getter in vacuum tubes to remove the last traces of air. Most strontium is used
as the carbonate in special glass for television screens and visual display units. Although
strontium-90 is a dangerously radioactive isotope, it is a useful by-product of nuclear
reactors from whose spent fuel is extracted. Its high-energy radiation can be used to
generate an electric current, and for this reason it can be used in space vehicles, remote
weather stations and navigation buoys.
Strontium in the environment
Strontium is commonly occurs in nature, formung about 0.034% of all igneous
rock and in the form of the sulfate mineral celestite (SrSO
4
) and the carbonate strontianite
xliv
(SrCO
3
). Celestite occurs frequently in sedimentary deposits of sufficient size, thus the
development of mining facilities attractive. The main mining areas are UK, Mexico,
Turkey and Spain. World production of strontium ores is about 140.000 tonnes per year
from an unassessed total of reserves.
Foods containing strontium range from very low e.g. in corn (0.4 ppm) and
orange (0.5 ppm) to high, e.g. in cabbage (45 ppm), onions (50 ppm) and lattuce (74
ppm).
Health effects of strontium
Strontium compounds that are water-insoluble can become water-soluble, as a
result of chemical reactions. The water-soluble compounds are a greater threat to human
health than the water-insoluble ones. Therefore, water-soluble forms of strontium have
the opportunity to pollute drinking water. Fortunately the concentrations in drinking
water are usually quite low
People can be exposed to small levels of (radioactive) strontium by breathing air
or dust, eating food, drinking water, or by contact with soil that contains strontium. We
are most likely to come in contact with strontium by eating or drinking.
Strontium concentrations in food contribute to the strontium concentrations in the human
body. Foodstuffs that contain significantly high concentrations of strontium are grains,
leafy vegetables and dairy products.
For most people, strontium uptake will be moderate. The only strontium
compound that is considered a danger to human health, even in small quantities, is
strontium chromate. The toxic chromium that it contains mainly causes this. Strontium
xlv
chromate is known to cause lung cancer, but the risks of exposure have been greatly
reduced by safety procedures in companies, so that it is no longer an important health risk.
The uptake of high strontium concentrations is generally not known to be a great danger
to human health. In one case someone experienced an allergic reaction to strontium, but
there have been no similar cases since. For children exceeded strontium uptake may be a
health risk, because it can cause problems with bone growth.
Strontium salts are not known to cause skin rashes or other skin problems of any kind.
When strontium uptake is extremely high, it can cause disruption of bone development.
But this effect can only occur when strontium uptake is in the thousands of ppm range.
Strontium levels in food and drinking water are not high enough to be able to cause these
effects.
Radioactive strontium is much more of a health risk than stable strontium. When
the uptake is very high, it may cause anaemia and oxygen shortages, and at extremely
high concentrations it is even known to cause cancer as a result of damage to the genetic
materials in cells.
Effects of strontium on the Environment
Strontium in its elemental form occurs naturally in many compartments of the
environment, including rocks, soil, water, and air. Strontium compounds can move
through the environment fairly easily, because many of the compounds are water-soluble.
Strontium is always present in air as dust, up to a certain level. Strontium concentrations
in air are increased by human activities, such as coal and oil combustion. Dust particles
that contain strontium will settle to surface water, soils or plant surfaces at some point.
xlvi
When the particles do not settle they will fall back onto earth when rain or snow falls. All
strontium will eventually end up in soils or bottoms of surface waters, where they mix
with strontium that is already present.
Strontium can end up in water through soils and through weathering of rocks.
Only a small part of the strontium in water comes from dust particles from the air. Most
of the strontium in water is dissolved, but some of it is suspended, causing muddy water
at some locations. Not much strontium ends up in drinking water.
When strontium concentrations in water exceed regular concentrations, this is
usually caused by human activities, mainly by dumping waste directly in the water.
Exceeded strontium concentrations can also be caused by settling of dust particles from
air that have reacted with strontium particles from industrial processes.
Strontium concentrations in soil may also be increased by human activities, such
as the disposal of coal ash and incinerator ash, and industrial wastes. Strontium in soil
dissolves in water, so that it is likely to move deeper into the ground and enter the
groundwater. A part of the strontium that is introduced by humans will not move into
groundwater and can stay within the soil for decades. Because of the nature of strontium,
some of it can end up in fish, vegetables, livestock and other animals.
One of the isotopes of strontium is radioactive. This isotope is not likely to occur
naturally in the environment. It ends up in the environment, though, as a result of human
activities, such as nuclear bomb testing and radioactive storage leaking. The only way to
decrease concentrations of this isotope is through radioactive decay to stable zirconium.
The concentrations of radioactive strontium in the environment are relatively low and the
particles will always end up in soils or water-bottoms eventually, where they mix with
xlvii
other strontium particles. It is not likely to end up in drinking water. Certain deep-sea
creatures incorporate strontium into their shells as strontium sulphate, and stony corals
require it, which is why it needs to be added in the water in aquaria.
(http://www.lenntech.com/Periodic-chart-elements/Sr-en.htm#ixzz0IATzpHUF&C).
Maximum Limits Permissible in Drinking Water according to
Canadian, U.S., WHO ad Gulf region standards
Table PreF-1: This table represents only a selection of contaminants that are posted
in the guidelines. A full list is available via the websites below.
The following table is a brief selection of some contaminants and physical conditions that
may be present in drinking water. A dash (-) indicates that there is no information
available regarding possible limits. Units are in milligrams per liter (mg/L) unless
otherwise noted. Milligrams per liter are equivalent to parts per million.
Canadian
Limit
US
limit WHO limit Gulf limit
Heavy
Metal (ppm) (ppm) (ppm) (ppm)
Silver 0.05 0.1
no
limit
0.05 0.1
no
limit
0.05 0.1
no
limit
0.05 0.1
no
limit
0.05 0.1
no
limit
Aluminum 0.1
0.05 -
0.2
no
limit
0.1
0.05 -
0.2
no
limit
0.1
0.05 -
0.2
no
limit
xlviii
Arsenic 0.01 0.01 0.01
Table 1,
Continued
0.01 0.01 0.01
0.01 0.01 0.01
Barium 1 2 0.7
1 2 0.7
Beryllium no limit 0.004
no
limit
no limit 0.004
no
limit
no limit 0.004
no
limit
Bismuth
Cadmium 0.005 0.005 0.003
0.005 0.005 0.003
0.005 0.005 0.003
0.005 0.005 0.003
Cesium
Chromiu
m 0.05 0.01 0.05
0.05 0.01 0.05
Cobalt no limit no limit no limit
no limit no limit no limit
Copper 1 1.3 2
1 1.3 2
1 1.3 2
1 1.3 2
Iron 0.3 0.3 no limit
0.3 0.3 no limit
0.3 0.3 no limit
Gallium
In
Lithium
Magnesium 50 - -
50 - -
Manganese 0.05 0.03 0.4
0.05 0.03 0.4
xlix
Sodium 200 no limit no limit
Table 1,
Continued
200 no limit no limit
200 no limit no limit
200 no limit no limit
200 no limit no limit
200 no limit no limit
Nickel no limit no limit 0.02
no limit no limit 0.02
Lead 0.01 0 0.001
0.01 0 0.001
0.01 0 0.001
0.01 0 0.001
0.01 0 0.001
Rubidium
Selenium
Strontium no limit no limit no limit
no limit no limit no limit
Titanium no limit no limit no limit
no limit no limit no limit
no limit no limit no limit
Uranium 0.02 no limit 0.009
0.02 no limit 0.009
Vanadium no limit no limit no limit
no limit no limit no limit
no limit no limit no limit
no limit no limit no limit
no limit no limit no limit
Zinc 5 5 no limit
5 5 no limit
5 5 no limit
l
* As per Canadian or BC Health Act Safe Drinking Water Regulation BC Reg
230/92, & Sch 120, 2001. Task force of the Canadian Council or Resource and
Environment Ministers Guidelines for Canadian Drinking Water Quality, 1996.
See their website for more information.
** As per the U.S. Environmental Protection Agency Drinking Water Standards.
See their website for more information.
*** As per the WHO (1998) Guidelines for drinking water quality, 2nd edition.
Geneva, World Health Organization. See their website for more information.
^ TCU = true colour unit
^^ Individual limits for some of the individual trihalomethanes & haloacetic
acids:
Trihalomethanes: bromodichloromethane (zero); bromoform (zero);
dibromochloromethane (0.06 mg/L). Chloroform is regulated with this group but
has no MCLG.
Haloacetic acids: dichloroacetic acid (zero); trichloroacetic acid (0.3
mg/L). Monochloroacetic acid, bromoacetic acid, and dibromoacetic acid are
regulated with this group but have no limits.
^^^ NTU = nephelometric turbidity unit. Based on conventional treatment/slow
sand or diatomaceous earth filtration/membrane filtration
Statement of the problem: To decontaminate large volumes of offshore
muds conatminated by toxic and carcinogenic heavy metals.
li
Different solutions for decontamination include:
1. Physical excavation: Time and labor intensive, requiring mining of
contaminated sediments. This renders the land unusable during the treatment
process.
2. Chemical treatment: Time and labor intensive, while having to deal with the
complex reactions occurring in-situ.
3. Biological treatment: Time and labor intensive, while having to deal with both
cultivating the required bacteria and the complex reactions occurring that will
leach out unknown products in-situ.
4. Electrokinetic treatment: If successful in offshore muds as in soils and sludges,
this technology will allow for a quick, cost effective remediation (in-situ).
1
Chapter 1: Electrokinetics
Electrokinetics is a term applied to a group of physicochemical phenomena involving the
transport of charges, action of charged particles, effects of applied electric potential and
fluid transport in various porous media to allow for a desired migration or flow to be
achieved. These phenomena include electroosmosis, ion migration, electrophoresis,
streaming potential and electroviscosity. These phenomena are closely related and all
contribute to the transport and migration of the desired ionic species and chemicals. The
physical and electrochemical properties of a porous medium and the pore fluid, and the
applied electrical potential all impact the direction and velocity of the fluid flow. Also, an
electrical potential is generated upon the forced passage of fluid carrying charged
particles through a capillary of porous medium.
These electrokinetic effects have been recognized for a considerable period of time, with
the effects of electroosmosis and electroviscosity being studied and evaluated by many
researchers.
Theory
Factors influencing electrokinetic phenomena
The theoretical development of electrokinetic phenomena and electrochemical transport
has been studied historically as far back as 1879 by Helmholtz that led to the introduction
of the first analytical equation. Helmholtz described the motion of the charged ionic
solution from the anode to the cathode and explained it by the presence of a double layer.
This double-layer theory is illustrated in Figure 1, where the negatively charged surface
of the clays attracts the positive ions of aqueous medium, forming the immobile double
layer. This immobile double layer is followed by a thick mobile layer with a
predominanance of positively-charged ions (cations), with a few diffused negatively-
charged ions (anions).
Figure 1-1: Schematic diagram of Helmholtz double-layer in an electrokinetic flow
on application of direct current field. (Modified by Chilingar et al., 1997.)
Later, the analytical solution was further modified by Smoluchowski in 1921 to arrive at
the Helmholtz-Smoluchowski’s equation (electrokinetic permeability):
2
3
K
= D / 4
where: D = dielectric constant
= zeta potential
= viscosity of the fluid
The proportionality constant, D, has been verified by several investigators for various
types of liquid--solid interfaces. However, extreme sensitivity and complexity of these
phenomena have lead to reports of discrepancies in the relative constancy of this term.
Probstein and Hicks (1993) have shown the effects concentration of ionic species within
the pore fluid, electric potential, and pH on the zeta potential ( . Thus, it doesn’t remain
constant throughout the electrically induced transport in soils that are governed by zeta
potential.
Zeta potential and the Electric Double Layer Interaction
There is a region at the surface of solids that has a difference in electrical potential across
just a few molecular diameters. When two dissimilar charged surfaces are contacted,
electrons at the surface of each one redistribute in such a manner that one of them
acquires a positive charge while the other becomes negatively charged. If a liquid and
solid are brought together, an electrical potential develops across a distance of a few
molecular diameters at the interface. The changes that are established are characteristic of
specific phases and are the underlying cause of many natural phenomena recognized as
4
electrophoresis, electroosmosis, colloid stability, fluid flow behavior, adsorption,
catalysis, corrosion, crystal growth, etc. (Donaldson and Alam, 2008).
The separation of charges is known as the interfacial electrical double layer. It is a
complex association of charges illustrated schematically in Fig. 1-2. There is a potential
charge (negative or positive) at one or two molecular distances from the surface. This
charge may originate from several sources such as: (1) inclusions of extraneous atoms in
the lattice structure, (2) dissolution of slightly soluble atoms at the surface of water, (3)
chemical reaction (chemisorption) of ions in water with surface atoms forming complex
polar molecules on the surface, or (4) exposure of metallic oxides at the surface which
react with water to form surface ions. These are some of the major causes of surface
charges; others are recognized in suspensions of particles and flocculants in water
(Hunter, 1981).
Counterions from the water solution balance the charges at the solid surface and form the
immobile Stern layer, Fig. 1-2. The thickness of the Stern layer is only one or two
molecular diameters consisting of ions that are adsorbed strongly enough to form an
immobile layer. The outer edge of the Stern layer where the ions are mobile is known as
the shear plane. There is a linear potential drop across the width of the Stern layer ( ψ
s
–
ψ
ζ
), followed by an exponential potential difference across the diffuse layer between the
shear plane and the bulk solution ( ψ – ψ
∞
); the bulk solution is designated as the
reference zero potential. This potential difference between the shear plane and the bulk
fluid is known as the zeta potential (Donaldson and Alam, 2008).
Figure 1-2 Electric double layer at the interface between a solid and liquid: x
s
=
surface of the solid, x
ζ
= shear plane, x
∞
= bulk liquid, x
ζ
– x
s
= stern layer, x
∞
– x
ζ
=
electrical diffuse (Gouy) layer. (Debye length, l/k). (After Donaldson and Alam,
2008.)
5
6
Cations, anions, and molecules with electrical dipoles can be adsorbed by nonelectrical
forces. Grahame has observed that anions are adsorbed by nonelectrical forces with the
centers of negative charges lying on an inner plane (within the Stern layer) from the
surface known as the Helmholtz inner plane (IHP at x
i
distance from the solid surface,
Fig. 1-3). The IHP is followed by the outer Helmholtz plane (OHP) drawn through the
charges of the hydrated counterions.
The thickness of the Helmholtz layers thus reflects the size of the adsorbed anions and
counterions within the Stern layer and is observed by the differences of the measured
linear potential differences within the Stern layer.
Figure 1-3 Double layer potentials showing the Helmholtz planes and their
potentials. IHP = inner Helmholtz plane (x
i
). OHP = outer Helmholtz plane (x = ).
(After Donaldson and Alam, 2008.)
7
8
The length of the exponential electrical field decay (from the shear plane to the bulk
fluid) is known as the Debye length (1/k). For example, if the plates of a capacitor
haveequal charge densities, the zeta potential is the potential difference from the center of
the separation to one of the plates (Donaldson and Alam, 2008):
1/k = x
o
– x
s
= εε
o
ψ
s
/
c
= ( εε
o
KT/ ρ
i
Z
2
ε
2
)^
1/2
* [c
2
/jm j/C m
2
/C = m] (1-2)
where ρ
i
is the number density of ions in the solution; Eq. 1-2 also shows that the charge
density of the surface (
c
) is proportional to the surface potential ( ψ
s
).
With respect to an ionic solution, the Debye length is the distance from the shear plane of
the Stern layer to the bulk fluid. The Debye length depends on the specific properties of
the ionic solution. For aqueous solutions (Donaldson and Alam, 2008):
1/k = B/ √(M) (1-3)
where B is a constant specific to the type of electrolyte. B is equal to 0.304 for
monovalent cations and anions (NaCl); 0.176 where either the cation or the anion has a
valency of two (CaCl
2
or Na
2
CO
3
); and 0.152 when both ions have a valency equal to
two (CaCO
3
). M is the molarity of the pore solution.
The composition of the Stern layer varies with respect to the nature of the surface charge
and ionic constituents of the electrolyte (Castellan, 1971):
1. The double layer may be entirely diffuse (no Stern layer) if ions are not adsorbed
on the solid surface, Fig. 1-4 In this case the Stern layer does not exist and the
9
potential difference declines exponentially from the solid surface to the bulk
solution.
2. If the concentration of ions in the electrolyte is sufficient to exactly balance the
surface charges of the solid, the potential will decrease linearly within the Stern
layer to zero at the shear plane. Thus the zeta potential is zero (equal to the
potential of the bulk fluid).
3. If the adsorption of ions does not completely balance the surface charge density,
the zeta potential has a finite value with respect to the bulk fluid.
4. If the surface charge is very strong, the Stern layer may contain an excess of ions
from the electrolyte.
The zeta potential of mineral surfaces in contact with aqueous solutions is a function
of pH. In general, acidic solutions promote positive charges at the surface with an
attendant positive zeta potential and basic solutions produce an excess of negative
charges at the surface from an increase of the hydroxide ion. The pH at which the zeta
potential is equal to zero is defined as the zero point charge (zpc). When the negative
and positive charges of ions in a solution are equally balanced, the solution is
electrically neutral and this condition is defined as the isoelectric point (iep).
Thomson and Pownall (1989) observed an approximate linear trend of the zeta
potential with respect to pH for calcite in dilute solutions of sodium chloride and a
mixed solution of sodium chloride and sodium bicarbonate, where ζ = -6.67*pH + 40.
The zero point charge occurred at pH > 6. Sharma et al. (1987) report inverted S-
10
shaped trends where ζ = -20*pH + 100 (zpc at pH ≈ 5) for Berea cores and dilute
sodium chloride solutions (Donaldson and Alam, 2008).
Zpc for most kaolinite ia at about pH = 2.
Figure 1-4 Two charged surfaces separated by distance d with a fluid between. The
film thickness on each surface is h = d/2. The number density of the counter ions at
the surface is ρ
s
and the center is designated ρ
s
which is taken as zero at the
reference point in the center. The electric field, which is independent of distance is
equal to the electric charge density, D, divided by the electric permittivity, E
s
= D/εε
o
.
(After Donaldson and Alam, 2008).
11
12
Considering that the total flow rate, q, in a porous medium is composed of the flow rate
where there is no electrical potential effect, q
n
, and an osmotic, countercurrent flow, q
os
:
q = q
n
– q
os
= k
n
dP/ndx – k’
os
(dψ/dx) 1-4
where k
n
is the permeability in the absence of electrical phenomena and k’
os
is the
transport coefficient resulting from the streaming potential, ψ.
The coefficient, k’
os
is obtained from the Helmholtz equation for the velocity of
electroosmotic flow in a tortuous capillary (Adamson, 1960; Scheidegger, 1974):
U
os
= eφζdψ/4 φμτ
2
dx 1-5
When an electrolyte is passes through a porous material (rock, glass, capillaries, etc.), a
potential difference develops across the ends of the core that is generally recognized as
the streaming potential.
Combining Eqs. 1-4 and 1-5 into Eq. 1-4 yields the fluid flow equation that includes the
effect of electroosmotic flow (Donaldson and Alam, 2008):
Q = (k
n
/n – e
2
φζ
2
R
n
/(4 π)
2
μt
2
)dP/dx = (k
n
/ μ – k
os
/ μ)dP/dx 1-6
13
DLVO (Derjaguin, Landau, Verwey, and Overbeek) Theory
The DLVO theory (Derjaquin and Landau, 1941; Verwey and Overbeek, 1948) is the
analysis of the competitive interactions of double layer forces and van der waals
attractive forces they affect the stability of colloidal suspensions of particles in
electrolytic solutions. Anions and cations maybe be adsorbed on surfaces by van der waal
attractive forces which are not affected by variations of pH or the concentration of
electrolytes. Curve 1, Fig. 1-5, describes the variation of the interactive potential energy
that occurs from complete repulsive energy (in the absence of van der waals attractive
forces); this occurs for a relatively thick double layer in a solution of high electrolyte
concentration. (Donaldson and Alam, 2008).
The van der waals forces become stronger (more negative) following an exponential
curve (U
(r)
= -r
n
) as the separation decreases and hence van der waals forces are
negligible at long distances. At short distances from the wall, however, the van der waals
forces exceed the repulsive double-layer forces and the result is strong attraction of the
surfaces (curve 4, Fig. 1-5). (Donaldson and Alam, 2008).
Figure 1-5 Curve 1: Repulsion of a surface caused by a double-layer Coulombic
charge in the absence of van der Waals attraction. This occurs in high electrolyte
concentrations. Curves 2 to 4: The increasing effect of van der Waals forces as the
thickness of the double layer decreases; this results form decreasing electrolyte
concentration. Curve 4: van der Waals attraction in the absence of double-layer
repulsion. (After Donaldson and Alam, 2008).
14
15
Between the two extremes, as particle surfaces approach, there is an initial attractive
minimum followed by a repulsive maximum that can be too great to allow actual contact
of the particle surfaces (curve 2, Fig. 1-5) and the particle will remain dispersed in the
electrolyte. If the surfaces have a low charge density and the repulsive maximum of the
potential energy is zero or negative (curve 3), the particles will coagulate because the
forces are entirely attractive. (Donaldson and Alam, 2008).
A value of 25 mV (positive or negative) can be taken as the arbitrary value that separates
low-charged surfaces from highly-charged surfaces.
The significance of zeta potential is that its value can be related to the stability of
colloidal dispersions. The zeta potential indicates the degree of repulsion between
adjacent, similarly charged particles in a dispersion. For molecules and particles that are
small enough, a high zeta potential will confer stability, i.e., the solution or dispersion
will resist aggregation because the surface charge because the surface charge disperency
of the particles are highly satisfied. When the potential is low, attraction exceeds
repulsion and the dispersion will break and flocculate. So, colloids with high zeta
potential (negative or positive) are electrically stabilized, whereas colloids with low zeta
potentials tend to coagulate or flocculate as outlined below:
Zeta potential is widely used for quantification of the magnitude of the electrical charge
at the double layer. However, zeta potential is not equal to the Stern potential or electric
surface potential in the double layer. Such assumptions of equality should be applied with
caution. Nevertheless, zeta potential is often the only available path for characterization
of double-layer properties.
Figure 1-6: Schematic representation of zeta potential ( (Modified after Zetasizer
Nano series technical note, Malvern Instruments, www.nbtc.cornell.edu)
16
17
There is a surface of shear (slipping plane) between the fixed and mobile sub-regions.
The zeta potential ( is the potential difference between this plane and the bulk liquid.
This zeta potential ( is smaller than the total or thermodynamic potential (after Butler et
al., 1951). The classical zeta potential ( equation is as follows (after Street et al., 1961):
4D (1-7)
where the double-layer thickness, , is equal to:
= f [1/(1/2*C
i
Z
i
2
)
1/2
] (1-8)
Anbah (1963) stated that the larger the ionic charge on the clay particle, the larger the
electric potential between the diffuse and inner fixed layer. Thus, fewer ions are able to
move in an external field. Overbeek and Liklema (1969) have shown that the higher the
ion concentration, the smaller the double layer thickness and, hence, the smaller the zeta
potential.
However with decreasing pH, the zeta potential ( decreases until a critical pH is
reached at which time a reversal in the sign of zeta potential occurs (Hunter and James,
1992). This is caused by the accumulation of H
+
ions in low--pH environments, resulting
in a compression of the Helmholtz double layer due to the cation build up. The reversal
of the sign of the zeta potential has been shown by Hunter and James (1992), as the
concentration of hydrolyzable metal ions increase the compression of the electric double
layers. This may lead to a reduction in electrokinetic flow in soils with high pore fluid
18
electrolyte concentrations, making electromigration the dominant mechanism of
electrochemical transport (Pamukcu et al., 2008). This reversal of sign of the zeta
potential ( has been found due to the accumulation of cations and the compression of
the electric double layer. The largest effect of zeta potential ( occurs during the
intermediate pH, slightly higher than the value needed for precipitation of the metal
hydroxide. It has been shown to be influenced by the type and concentration of
electrolytes added to the suspension (Kruyt, 1952; Smith and Narimatsu, 1993).
As mentioned earlier, the pH is one of the most important factors affecting the zeta
potential ( Thus, the zeta potential value alone is actually meaningless without defining
the solution conditions (After Zetasizer Nano series technical note, Malvern Instruments,
www.nbtc.cornell.edu).
1) On assuming a negative value zeta potential, if acid is added to this suspension, a
point will be reached where the charge will be neutralized. The further addition of
acid will cause a buildup of positive charge. Consequently, the zeta potential
( versus pH curve will be positive at low pH and lower or negative at high pH.
2) On the other hand, if more alkali is added to the system, then the accumulation
and buildup of negative charge on particle will prevail. The point where the plot
of the zeta potential versus pH passes through the zero zeta potential is called the
isoelectric point. Usually, the colloidal system is least stable at this point.
Figure 1-7: Typical plot of zeta potential ( versus pH, showing the position of the
isoelectric point and the pH values where the dispersion is expected to be stable
(after Zetasizer Nano series technical note, Malvern Instruments,
www.nbtc.cornell.edu).
In Figure 1-7, the isoelectric point of the sample is at pH ≈ 5.5. The sample is stable at
pH < 4 and pH > 7.5. In the unstable region, (Fig. 1-3), the zeta potential varies from
+30mV to -30mV.
Combined Flow Rate Equation
In some of the experiments performed by researchers at USC (Chilingar et al., 1970), an
electric potential was applied across a core where oil was already flowing
hydrodynamically. When the imposed electrical potential gradient and pressure drop are
in the same direction, the oil flow rate is increased by removing some brine.
They obtained, the total flow rate equation by adding the electroosmotic relation to the
Darcy equation: (Chilingar et al., 1968).
qt = Ak p/( L) + Ak
e
E/( L) (1-9)
This equation can then be presented in a dimensionless form by normalizing the flow
rates and, thus, eliminating the viscosity, area and length terms:
19
20
q
t
/q
i
= 1 + k
e
E/ k p (1-10)
and
(q
t
– q
i
)/q
i
= k
e
E/ k p (1-11)
Equation (1-10) shows that an increase in flow rate is dependent upon the zeta potential,
dielectric constant, brine concentration, Darcy permeability, and pressure drop. If the
dependence of k
e
on k is not considered, then Eq. (1-11) would suggest that as the
hydrodynamic permeability decreases, the percent increase in flow rate would become
more significant. However, it should be noted that viscosity changes with temperature,
and there is some heating as a result of application of an electrical potential. (see
Chilingar et al., 1970.)
Calculated k
e
/k, can be used as an index for predicting the probability of success
and applicability of Electrically Enhanced Oil Recovery (EEOR).
The larger the ratio, the better the chance of success in dewatering sand and increasing
the relative permeability to oil. In very tight formations, k
e
may exceed k causing an
increase in the degree of electric dewatering at the wellbore.
Two-phase Flow
When oil and brine flow simultaneously in a porous medium, and the flow is subjected to
an applied electrical potential, the flow rate of the oil as well as that of the brine is
affected by the electrical potential gradient. Although the electrical potential gradient
affects only the brine directly, the oil flow rate is affected indirectly because the
21
relationships that exist among the oil and water flow rates, fluid saturations,
permeabilities, and pressure gradients (Chilingar et al., 1970).
In the absence of an electrical potential gradient, the initial flow rate of brine, q
w1
, is
given by an adaptation of Darcy’s law to a linear flow system:
q
w1
= - k
w1
A p
w1
/(
w1
L) (1-12)
If an electric potential is applied across the core, the electric field will drive the cations in
the mobile part of the double layer towards the cathode.
These, in turn, will drag with them water molecules and, consequently increase the water
flow rate. If this increase in flow rate is to be prevented, a pressure difference ΔP
eo
must
be applied in the opposite direction. P
eo
is defined as the electroosmotic pressure
difference.
In an electroosmotic flow experiment, four variables can be controlled. These are
the oil and water flow rates and the pressure and electrical potential gradients. If one
elects to maintain a constant pressure gradient and a constant water flow rate and to vary
the applied electrical potential, the oil flow rate will vary with potential gradient as
indicated in the following derivation.
On applying an electric potential, the flow rate, q
w2
, will become:
q
w2
= - (k
w2
A/(
w2
))[ p
w2
/L+p
eo
/L] (1-13)
If the inlet and outlet pressures were held constant, with the outlet pressure being
atmospheric, then P
w1
= P
w2
=
P. If the water is introduced into the system through a
constant-rate pump, its flow rate would stabilize after the electric potential is applied for
a period of time. Upon stabilization of water flow rate, q
w1
=
q
w2
. Dividing,
22
q
w1
/q
w2
= 1 = (
w2
/
w1
)( k
w1
/ k
w2
)[ p/( p
+P
eo
)] (1-14)
Inasmuch as
w1
>
w2
owing to an increase in temperature, and p
+p
eo
> p
,
then
k
w1
> k
w2.
Because relative permeability is a function of saturation, a decrease in relative
permeability to water corresponds to a decrease in water saturation. This, in turn, would
result in an increase in oil saturation and thus an increase in relative permeability to oil.
At constant p, the oil flow rate will, therefore, increase with increasing oil permeability.
Thus, under the foregoing conditions, the application of an electrical potential gradient
results indirectly in an increase in oil flow rate (Chilingar et al., 1970).
Coehn’s rule
A general rule for the potential difference of the double layer was given by Coehn in
1909 as follows:
Substances of higher dielectric constants are positively charged in contact with
substances of lower dielectric constants. The corresponding potential difference is
proportional to the difference of the dielectric constants of the touching substances.
Later, researchers (Smoluchowski, 1921; Fairbrother et al., 1931; Verwey, 1941; and
Adamson et al., 1963) investigated this qualitative rule.
They have found that this rule does not apply to pure organic liquids with low
dielectric constants, such as benzene and carbon tetrachloride. However, Coehn’s rule is
still used to indicate the sign of the zeta potential and, hence, the direction of movement
of phases past each other.
23
Electrolytic concentration
The qualitative rule presented by Coehn, seems to represent a very special case where
ionic liquid content is very small even when compared to dilute aqueous solutions. The
electrochemical behavior of the solid--liquid interface greatly influences these
electrokinetic phenomena. In the case of relatively inert surfaces, such as quartz, the
electrical charge density depends primarily on the adsorbed electrolytes.
Many researchers, showed a linear logarithmic relationship between zeta potential and
concentration (c) (Adamson et al., 1963):
log c
The zeta potential, , goes through a maximum and then approaches zero, which is
explained by a combination of two processes: (1) adsorption process of ions on the
surface and (2) followed by a neutralization process of the charged surface with opposite
sign (Kruyt, 1952.)
Rutger et al. (1945) showed the effects of the H
+
and OH
-
ions on zeta potential at low
concentrations. A small addition of the OH
-
increased the negative zeta potential. In the
case of larger concentrations, all electrolytes decreased the zeta potential, especially
pronounced in the case of polyvalent ions, whereas the addition of H
+
ions decreased the
zeta potential.
Although electrolytes can strongly influence the zeta potential, they have no effect on the
total potential drop (Adamson et al., 1963.) The addition of multivalent ions may cause
the reversal of the sign of the zeta potential. This can be explained by the adsorbability
for these ions in a layer bearing a larger charge than is present on the wall. This will
24
cause a reversal of the charge and potential in the outer part of the double layer (Kruyt,
1952) in order to maintain the electro neutrality of the system.
The theory of the diffuse double layer leads to the conclusion that the
concentration of the electrolyte varies inversely with the effective thickness of the diffuse
part of the double layer, (and zeta potential.) The larger the ionic charges, the few the
ions needed for charge compensation, whereas the larger the ionic charges, the larger the
electric forces between the diffuse layer and the inner fixed layer. The fewer ions are
needed for charge compensation, the larger the valences of the adsorbed ions (Adamson
et al., 1963.)
Effect of temperature
The influence of temperature on electrokinetic phenomena has been studied by many
researchers [Smoluchowski, 1921; Abramson, 1934.] Cruze in 1905 [Smoluchowski,
1921] studied the effect of temperature and current through clay diaphragms. He found
that constant values of electro-osmosis were obtained only after the passage of current for
several hours. He also found marked dependence of the constant electro-osmotic flow on
the temperature and on the current strength. According to his measurements,
Wiedemann’s constant (V/i) increases with increasing temperature, reaches a maximum
and then decreases again. The quotient (V/i) is constant for a small current strength,
increases with increasing current density to a maximum and then decreases rapidly with
further increase of current. Some of Cruze’s results (Adamson et al., 1963.):
25
Table 1-1: Cruze’s (1905) measurements of Weidamann’s constant (V/i) with
increasing temperature.
T
o
C 9.45 24.16 30.97 36 40.21 49.86 65.81
V/i 6.24 9.26 9.97 10.27 9.54 6.17 4.45
Smoluchowski (1921) calculated analogous results by using Helmoholtz-Smoluchowski’s
equation, and assuming zeta potential to be constant, while allowing for the variation of
the viscosity and the specific resistance R.
He indicated that the apparent dependence of the electro-osmotic transport of
water on the current strength may be attributed to the heating effect of water in the
diaphragm at high current strength.
Perrin (1904), and Oettinger (1912), obtained results which agree on the
approximate constancy of the term, Dx, in the electrokinetic equations and its
independence of temperature. Burton (Abramson, 1934) determined the electrophoretic
velocity of particles of silver sol in water at different temperatures.
Some of his results are listed below:
Table 1-2: Variation of electrophoretic velocity with temperature (Burton, 1934.)
T
o
C 3.0 9.9 11.0 21.0 31.0 40.5
V X10
7
24.5 24.7 25.1 25.0 24.0 24.5
This shows that the electrophoretic velocity multiplied by the respective viscosity stays
approximately constant, or where V is approximately a constant, known as Burton’s
rule for electrophoresis velocity.
26
This relation is known as Burton’s rule for electrophoretic velocity.
Some interesting research work has been done on electrophoretic velocity of kaolinite
clay upon addition of NaOH (Chilingar, 1952.)
Further work, regarding the effect of temperature on electro-osmotic transmission
of liquid, was reported by Winterkorn (1947.) His investigation covered a variety of clay
minerals at different temperatures. It seems that he has corrected for the effect of
temperature on water viscosity, yet a marked increase in the electro-osmotic transport of
liquid at high temperature can be noticed. He attributed this increase to a thermal gradient
causing the fluid to flow in a manner similar to electro-osmosis, and the effect was called
thermo-osmosis.
Winterkorn (1947, 1955) confirmed the phenomenon of thermo-osmosis by an
experiment in which a thermal gradient was set up across a hydrophilic clay sample and
estimated the thermo-osmotic coefficient K
t
to be equal to 1 x 10
-7
cm/sec per degree
o
C
per cm. By means of a potentiometer connected to two platinum electrodes fixed at the
surface of the clay sample, he was able to measure a potential gradient across the sample.
As mentioned earlier, Helmholtz generated the first analytical equation by assuming:
1 - The hydrodynamic equations for viscous liquids are valid for the entire region of the
double layer.
2 - And laminar flow conditions prevail.
The electrokinetic velocity for a capillary tube is as follows (in Anbah et al., 1964):
u = i ( i – a)/4
where: i = current density
27
= specific resistance
= the liquid viscosity
= electrical potential at the solid wall
Later, modifications by Smoluchowski (1921) lead to the famous Helmholtz-
Smoluchowski’s equations:
v
e
= DE/4
V = A DE/4
where: A = cross-sectional area
D = dielectric constant
= zeta potential
E = potential difference
v
e
= electokinetic flow rate
For porous plugs, the cross-sectional area, A, was eliminated by the application of Ohm’s
law and by assuming no surface conductance:
AE = i/
v
e
= D i/4
where: = specific conductivity
i = current through capillaries
These equations were then proved to hold true for turbulent flow (Rutgers et al., 1957).
If surface conductance exists in the capillaries, then:
AE + SE = i
28
v
e
= D i/[4 + (S/A)
s
)]
where: S = circumference of capillary
s
= specific surface conductance
Upon measuring the conductivity or resistivity of the liquid (while present in the
capillaries) necessary corrections can be made:
v
e
= D i/4 ‘
where: ‘ is the corrected specific surface conductivity. Thus, it includes the bulk
conductivity, , and surface conductivity,
s
.
Through experimental work, ’ can be determined experimentally from the measured
resistance, R, across the core and its cell constant:
’ = C/R
According to Manegold and Solf (1931):
C = L/[(A(1-f)
where: L = length of core
A = cross sectional area
(1-f) = volume fraction available for ionic migration
= shape factor
Thus:
v
e
= AD Ri(1-f) /4L = (AD (1-f) /4 *(E/L)
According to Mazur and Overbeek (1951) and Lorenz (1952), a linear relation exists
between the gradient and flow of current in regions and the effects of simultaneous
29
electrical processes on the transport of liquid and electrical change in the capillary system
could be considered additive (see Anbah et al., 1964):
i = C
11
E + C
12
P
V = C
21
E + C
22
P
where: i = electrical current through capillaries,
taken as positive when passing from side 1 to side 2
V = volumetric flow rate from 1 to 2, measured similarly
E = electrical potential difference, taken as positive when side 1 is positive
P = pressure difference across system, positive when side 1 is higher
C
ij
= experimental coefficient
There are four variables and two equations only. In order to relate two variables with one
coefficient, a third independent equation is needed.
This can be done by holding one variable equal to zero. For example, at P equal to zero,
C
11
represents the conductance or reciprocal of resistance. At E =0, C
22
represents the
hydrodynamic permeability coefficient (Anbah et al., 1964):
Saxen’s law (1892) relates electro-osmosis and streaming potential,
[V/i = D / (4 = E/P]:
-(E/P)
i
= 0 = (V/i)
P
= 0
The minus sign indicates that the streaming potential and the pressure gradient act in
opposite directions. Referring to Eq. 1-27, if one variable is set equal to zero and the
other two variables are related, then:
(E/P)
i
= 0 = -C
12
/C
11
30
(V/i)
P
= 0 = C
21
/C
11
C
12
/C
11
= C
21
/C
11
C
12
= C
21
= C
e
This relationship Onsager’s relation (1931) can be obtained by reasoning based on the
thermodynamics of irreversible processes (Overbeek, 1953).
The coefficient C
e
represents the electrokinetic effect, and when interpreted in terms of
zeta potential for a capillary tube, C
e
is equal to AD /4, whereas for a porous plug,
C
e
= AD/e F.
where F = Formation factor
In the system where there is a coupling of two different transport processes, there are four
different electrokinetic experiments that can be performed, namely:
(1) Electroosmotic flow at zero pressure;
(2) Electroosmotic pressure at zero flow;
(3) Streaming potential at zero current;
(4) Streaming current at zero potential.
These phenomena can be expressed as functions of current, electrical potential, flow of
liquid, or pressure difference, thus leading to twelve coefficients. The coefficients for
electroosmotic flow rate at P = 0 are (Anbah et al., 1964):
At P=0:
(V/i)
p
= 0 = C
e
/C
11
(V/E)
p
= 0 = C
e
And for electroosmotic pressure at V = 0, can be expressed as:
31
At V = 0 :
(P/E)
v
= 0 = - C
e
/C
22
(P/i)
v
= 0 = - C
e
/(C
11
C
22
- C
e
2
)
Similarly, the coefficients for streaming potential at i = 0 are:
At i = 0:
(E/P)
i
= 0 = -C
e
/C
11
(E/V)
i
= 0 = -C
e
/(C
11
C
22
– C
e
)
Whereas for steaming current at E = 0, they are:
(i/P)
E
= 0 = C
e
(i/V)
E
= 0 = C
e
/C
22
The coefficients for permeability at E =0 and at i = 0, are, respectively:
(V/P)
E
= 0 = C
22
and
(V/P)
i
= 0 = C
22
- C
e
2
/C
11
Finally, the coefficients for electrical conductances at P = 0 and V = 0 are equal to:
(i/E)
P
= 0 = C
11
(i/E)
V
= 0 = C
11
- C
e
2
/C
22
Due to existence of Onsager’s relation, it appears that the absolute values of these
coefficients are pairwise equal:
(E/P)
i
= 0 = - (V/i)
P
= 0 and (i/P)
E
= 0 = (V/E)
P
= 0
Whichever experiment is performed or whichever combination is chosen, the system is
completely described by the three constants (C
11,
C
22
and C
e
). The choice of the
32
experiment to be performed is determined mainly by convenience and accuracy rather
than by principle. In a highly conductive electrolytic solution (C
11
is large), it is rather
difficult to measure the streaming potential, whereas the streaming current will give a
reasonable value and the estimated C
e
will probably be more nearly accurate (Anbah et al.,
1964).
It is a well-established fact (Elton, 1948; Mortada, 1952; Henniker, 1952; and
Street, 1961) that when permeability is measured in the conventional way, the streaming
potential has a retarding effect on the flow. This effect has been attributed to
electroosmotic back flow, to electroosmotic back pressure, or to an increase in the fluid
viscosity. It has been given various names, and has been referred to by such terms as
electrokinetic blocking or electroviscous drag.
From Eqs. 1-42 and 1-43, the difference between the permeabilities obtained at E = 0
and at i = 0 represents the electrokinetic retardation effect and is expressed by the term
C
e
2
/C
11
. This correction factor diminishes on increasing the concentration of electrolyte
in the flowing solution or by allowing the electric current to flow in an outside circuit
connected to the two ends of the core. It is of interest to note that, in the absence of any
electrokinetic effect, the permeability will be higher than C
22
. It could probably be
obtained by coating the surface of the capillary by a conducting material. Mortada (1952)
and Street (1959) related the true permeability K
t
to the apparent permeability K
a
for a
porous plug as follows (Anbah et al., 1964):
K/K
a
= 1 + (D
2
2
F)/(16
2
K)
33
Electrokinetic Conductance Effects
From Eq. 1-45, the electrical conductance measured at P = 0 is given by C
11
= (i/E)
p = 0
,
and from Eq. 1-46, the electrical conductance, measured at V = 0, is given by:
C
11
- Ce
2
/C
22
= (i/E)v = o
The electrical conductance, however, is ordinarily measured in the absence of any
electrokinetic effects and is equal to:
Co = i/E
Accordingly, it makes a difference whether the electrical conductance is measured at zero
flow, at zero pressure, or in the absence of all electrokinetic effects.
The difference is greatest when:
(a) The radius of the capillary is small, or in the case of porous media, the
permeability is low.
(b) When the specific conductivity of the electrolyte is low.
By subtracting Eq. 1-46 from 1-45, the difference Ce
2
/C
22
represents the electroosmotic
conductance effect, which is comparable to the electroviscous blocking. It is due to the
electroosmotic transport of excess charge of one sign by the motion of liquid, and the
transmission of current takes place mainly in the form of convection.
The difference (C
11
- C
0
) represents the total surface conductance. According to Lorenz
(1952), it arises from the increase of electrolyte concentration and altered ionic mobility
near the wall, and an electroosmotic term, which is due to transport of surplus charge by
the mobile part of the diffuse part of the double layer. The values of the different
34
electrical conductances, as defined in Eqs. 1-44, 1-45 and 1-48, are related to each other
in the following way:
(i/E)
p = 0
> (i/E)
v = 0
> (i/E)
The electroosmotic transmission of liquid through porous media can be given by:
Q
e
= (AD /4F)*(E/L)
= (AK
e
/ )*(E/L)
where: K
e
is electroosmotic permeability coefficient. The assumption that the
electroosmotic coefficient K
e
, is constant is justified if the system is under small potential
gradients, the fluctuation in temperature is negligible and the solid surface is considered
inert.
From Darcy’s equation, the hydrodynamic flow rate:
Q
h
= (AK/ )*(P/L)
If the two potential gradients, E/L and P/L are acting in the same direction, and the flow
of current coincides with flow of liquid, then from equations 1-27 and 1-28, the total flow
rate, Q
t
, is the resultant addition of two separate flow rates:
Q
t
= Q
e
+ Q
h
= (AK
e
/ )*(E/L) + (AK/ )*(P/L)
If the ratio Q
t
/Q
h
is defined as that of a normalized flow rate, then dividing equation 1-50
by 1-51, we arrive at:
Q
t
/Q
h
= 1 + Q
e
/Q
h
= 1 + (AD E/4FL)*( L/AKP)
= 1 + D E/4 FKP = 1 + (Ke/K)*(E/P)
On excluding any formation of tiny fissures as pointed out by Cassagrande (1947), and
by assuming the hydrodynamic flow rate, Q
h
, is to remain constant and equal to Q
i
, the
normalized flow rate may be expressed as:
Q
t
/Q
i
= 1 + (K
e
/K) * (E/P) = 1 + q
where q is fractional increase in flow rate and equal to (Q
t
– Q
i
)/ Q
i
On using similar reasoning, one can obtain an equation for the fractional increase or
percentage increase as follows:
(Q
t
– Q
i
)/Q
i
* 100 = 100q
Electrochemical Background
Five main mechanisms appear to be operative in EEOR, based on the available field and
laboratory data (Wittle et al., 2008):
Joule heating
Electromigration
Electrophoresis (movement of clay)
Electroosmosis
Electrochemically enhanced reactions.
All of these coupled reactions were described by the Lars Onsager (1931a, 1931b, 1969),
who received the Nobel Prize in Chemistry in 1969. Mitchell (1993) and Noubehecht and
Madden (1963) presented simpler representations. The matrix notation for the Onsager’s
relationships can be presented as follows:
6
Ji = ∑
j=1
L
ij
Φ
j
35
where: Ji = generalized flow, or flux vectors.
Φ
j
= generalized potential gradient (force) vectors.
L
ij
= generalized conductivity, or coupling coefficient (second rank) tensors.
Non-coupled fluxes are related to their potential gradients through the main diagonal
terms L
ii
, whereas the off diagonal L
ij
relate coupled fluxes. If the products J
i
* Φ
j
represent free energy dissipation, then according to Onsager’s principle:
L
ij
= L
ji
Upon examining Eqs. 1-58, one can observe that (after Wittle et al., 2008):
If J
1
is the electrical current density and Φ
1
is the electrical potential, then L
11
is
the electrical conductivity tensor, .
If J
2
is the heat flow and Φ
2
is the temperature, then L
22
is the thermal
conductivity tensor, K, and L
21
includes Joule heating.
If J
3
is the ionic flux and Φ
3
is the ionic concentration, then L
33
is the (ionic)
diffusion coefficient, D
i
and L
31
includes electromigration.
If J
4
is the charged-particle flux and Φ
4
is the charged-particle suspension density,
then L
44
is the (charged particle) diffusion coefficient, D
p
, and L
41
includes
electrophoresis.
If J
5
is the fluid flux and Φ
5
is the pressure, then L
55
is k/ , (k is the absolute
permeability tensor and is the fluid viscosity) and L
51
includes electroosmosis.
36
37
If J
6
is the chemical reaction product flux and Φ
6
is the chemical reactant
concentration, then L
66
is the chemical reaction rate constant, and L
61
includes
electrochemically enhanced reactions.
The primary electrokinetic mechanisms are described below:
Joule Heating
The passage of the electrical current through conducting fluids and solids within a
reservoir causes heating. Such Joule heating is responsible for raising the temperature and
reduces the viscosity of the fluids.
Electromigration
Under the influence of an applied electric field, the cations move to cathode and anions
migrate to anode. This is the basis of electroplating or electrorefining, as metallic cations
migrate from anode to cathode allowing the oxidation to occur at the anode.
Electrophoresis
Similar to electromigration, the charged colloidal particles that are suspended in solution
move to the electrode based on their surface charge sign. In the case of clays, being
generally negatively charged, exhibits flow towards the anode. This may result in many
scenarios from clearing blocked pore throats (increasing permeability), to clogging up
other pore throats. However, there is a potential destruction of the double layer, therefore
drastically reducing the electro-kinetics permeability. (Also see Tchilingarian, 1952).
38
Electroosmosis
As defined by Leo Casagrande (1952, 1959), Gray and Mitchell (1967), and
Tikhomolova (1993), the Helmholtz double layers are formed in connate waters adjacent
to clay minerals in narrow pore throats, allowing hydrated cations and water molecules to
pass through towards cathode, but blocking anions. This mechanism can dewater
expansive clays and increase permeability in petroleum reservoir rocks.
Electrochemically Enhanced Reactions
Electrochemically enhanced reactions appear to cause “cold-cracking” of heavy crudes
resulting in the breakdown into lighter components, with a significant increase in the flow
rate. Reactions between the pore fluids and matrix materials are enhanced by Eh/pH
changes caused by the passage of direct electrical current. (Wittle et al., 2008)
Helmholtz double layer
A schematic diagram illustrating the Helmholtz double layer within a pore throat is
presented in Figure 1-8.
The double layer is divided into two electrochemical regions:
A region of fixed water molecules and cations held by strong electrostatic forces
to negatively charged mineral surfaces. (stern layer)
39
A region of loosely bound cations and water molecules, which are partially
shielded from the negatively-charged surface charge minerals surfaces by the
water molecules and cations of the Stern layer. In the presence of an external
electrical field, this layer (Gouy layer) can move towards the cathode.
Distribution of negative and positive ions in formation water and distribution of
hydrocarbons during flow in wide and narrow pore throats is presented in Figs. 1-8 and 1-
9, as envisioned by Wittle et al. (2008).
It is important to note here that it is not really known how do oil and water flow (two-
phase flow) through reservoir rocks. For example, Dr. George V. Chilingar (personal
communication) believes that one phase is dispersed in another. In water-wet rocks, the
discontinuous phase (non-wetting, dispersed phase—oil) is dispersed in the continuous
phase (wetting, dispersion phase—water). This problem remains to be solved. The fact
remains, however, that on application of DC current, both oil and water move faster
towards the cathode in water-wet rocks. Whether this is true or not in the oil-wet rocks is
unknown.
Figure 1-8: Schematic diagram of a flow through a wide pore throat of a water-
wet reservoir rock showing distribution of anions and cations (double layer), as
envisioned by Wittle et al. (2008). The potential difference between shear or
slipping plane surface between the mobile and immobile double layers and the
free fluids is the zeta potential.
40
Figure 1-9: Schematic diagram of a double layer distribution in a narrow pore
throat of water-wet reservoir and flow as envisioned by Wittle et al. (2008).
41
Figure 1-10 shows relationship between the electrical potential and normalized flow rate
(qt/qi) in sand cores containing different clays (Kaolinite, illite, and montmorillonite).
Test on core devoid of clays, i.e., 20-mesh silica sand, also showed a lower increase in
flow rate upon application of D.C. current. Possibly, the double-layer also exists in the
case of pure silica. In addition, thermal effect plays a role.
Figure 1-10: Relationship between electrical potential gradient and normalized flow
rate. (After Chilingar et al., 1970.)
qi = initial flow rate before application of D.C. current.
Core no.1: 94% silica sand & 6% montmorillonite clay.
Core no.2: 94% silica sand & 6% illite clay.
Core no.3: 94% silica sand and 6% kaolinite clay.
Core no.4: 100% 20-mesh silica sand.
42
The following results are obtained by Anbah at al., 1964 at USC. The major variables
involved here are: 1) Electric potential gradient, 2) electrical current, 3) electrolytic
concentration, 4) applies pressure differential and 5) total flow rate. By holding some
variables constant and they captured the effects of the varying variable with varying flow
rate. The results are presented in the following figures:
Figure 1-11: Normalized flow rate (Q/Qi) versus electrical potential gradient (E/L)
showing a drop in the total flow rate due to plugging by deposited copper
compounds, (after Anbah et al., 1964, p.5).
Figure 1-12: Imposed electrical potential versus q/qi (actual rate of flow/initial rate
of flow) ratio. (After Anbah et al., 1964, p.5.)
43
Figure 1-13: Electrical current versus normalized flow rate, q/q
i
(90% silica + 10% Wyo-gel synthetic core). (After Anbah et al., 1964, p.5.)
44
Figure 1-14: Electrical current versus flow rate, q/q
i
(95% CaCo3 + 5% Wyo-gel synthetic core). (After Anbah et al., 1964, p.5.)
Figure 1-15 through 1-18, illustrate possible field implementation, where anode(s) are
placed at the ground surface and the cathode(s) are placed in or near the producing
well(s). These configurations have been suggested by Chilingar. (Personal
communication).
45
Figure 1-15: Electrode-arrangement for water flooding operation: (a) The anode is
laid down in the injection well to face the producing zone. (b) The anode is driven
into the wet ground near the injection well. (c) Four and five spot flooding pattern
(Anbah et al. 1965).
46
Figure 1-16: Electrode-arrangement for well stimulation. (a) Anodes are put in
specially drilled small-diameter holes around the treated well. (b) Anodes are put
either in shut-in wells or in directionally drilled small-diameter holes from shut-in
wells (Anbah et al. 1965).
47
Figure 1-17: Electrode-arrangement for selective ion-drive. Conducting pipes driven
into the wet ground are used as anodes or cathodes (Anbah et al. 1965).
48
Figure 1-18: Schematic diagram of locations of cathode and anode in EEOR field
operation. (Modified after Anbah et al., 1965; and Titus et al., 1985.)
49
Three-Dimensional Current Flow Ramifications
For one-dimensional linear circuit theory, Ohm’s law is:
I = ΔV/R (1-60)
or ΔV = IR (1-61)
Joule heat loss across a given circuit element, with resistance R, as follows:
P = I ΔV = I
2
R (1-62)
where: P = power loss, over the individual circuit element of resistance, R.
ΔV = voltage drop across the individual circuit element.
R = individual circuit element resistance.
I = current through the entire circuit, controlled by the total voltage drop
across the entire circuit and the sum of all of the resistances in the circuit.
In three-dimensions, Ohm’s law (Equation 1-60) becomes:
J = E = Φ = ρ
-1
Φ (1-63)
or
Φ = ρ J (1-64)
In three-dimensions, the local Joule heating power loss is given by:
p
x,y,z
= J*E = J * Φ
= │J │
2
ρ (1-65)
where: p
x,y,z
= local power loss at the point of interest
E = local electric field vector
Φ = local electrical potential field gradient
= local electrical conductivity tensor
ρ = the local electrical resistivity tensor (inverse of )
50
51
J = local current density vector
I is constant in equations 1-60 to 1-62, and is dependent only on the total voltage drop
across the entire circuit element in the circuit, and the sum of the circuit element
resistances in the circuit. All of the parameters in Eqs. 1-63 to 1-64 are functions of
position for a heterogeneous earth model.
Electric current densities follow the paths of least resistance, so that the total Joule power
loss:
P
T
= ∫∫∫P
xyz
dxdydz (1-66)
For the entire (earth system is minimized, this means that regions of high resistivity,
│J │is much lower than in regions of low resistivity.
Figure 1-19 illustrate the Joule heating simulation results in the vicinity of the
downhole electrode within a heavy oil reservoir (according to Wittle et al., 2008). Here it
shows that even after 19.5 months of EEOR with DC application, the temperature beyond
14 ft of the electrode surface is essentially unchanged.
Figure 1-19: EEOR simulation results: reservoir temperatures after 100, 1000, and
5400 hours of stimulation. Temperatures in
o
F (ordinate) and distances are in feet
(abscissa), from casing. (After Wittle et al., 2006.)
Figure 1-20 show a series of Gas Chromatography Mass Spectrograph (GCMS) spectras
from polyaromatic Hydrocarbon (PAH) contaminated soils undergoing Electro-chemical
Geo-Oxidation (ECGO) remediation. It demonstrates the spectra peak shift from complex
hydrocarbons to simpler ones with time, as in in-situ cold-cracking.
52
Figure 1-20: ECGO PAH destruction GCMS changes during treatment. (After
Wittle et al., 2008.)
53
Wittle et al. (2008) did not explain why the water cut decreases on application of D.C.
current. The writer believes that this is due to changing polarity of the oil upon
application of D.C. current. As pointed out by Chilingar et al. (2005), with increasing
polarity of oil, the relative permeability to oil increases, whereas the relative permeability
to water decreases (Fig. 1-21).
Figure 1-21: Relative permeability curves for polar and non-polar oil. Curves P and
P’ are for polar oil, whereas N and N’ are for non-polar oil (modified after G.A.
Babalyan, in: Langnes et al., 1972, p. 229).
54
55
Economic Feasibility
A very approximate estimation can be made for the economic feasibility of applying
electrical current to enhance the flow of reservoir fluids during oil production.
Many assumptions should be made in order to make such rough calculation. The
variables which will affect the economic considerations include: (1) thickness, depth, and
resistivity of the pay zone, (2) arrangement of the electrodes, (3) duration of the electrical
treatment, (4) labor cost, and (5) price of electricity at the site of application (Anbah et al.,
1965).
In general, the rock resistivity is a function of the amount of interstitial water
present. This, in turn, is determined by the rock porosity and the amount of pore space
that is filled by interstitial water. The flow of electrical current in such a case in not a
simple linear flow but follows an irregular path around the individual sand grains. This
flow pattern will increase the length of the current flow lines and the resistivity of the
rock. Inasmuch as the current is mainly transmitted through the rock in the form of
electrolytic conduction, the resistivity of the interstitial formation water seems to be the
deciding factor in the formation resistivity as a whole. The presence of clay, however,
greatly affects the electrical resistivity of the formation, especially in the case of fresh
formation water (Anbah et al., 1965).
Although the electroosmotic flow depends mainly on the imposed electrical
potential gradient, the associated electrical current is conditioned by the type of formation
under consideration and its electrolytic content. There is no simple relation between the
amount of liquid transported by electroosmosis and the quantity of electricity consumed.
56
The presence of expandable colloidal matter in a microporous media further complicates
the picture (Anbah et al., 1965).
In field application, the energy consumption will depend on the dimensions of the
electrodes, the applied electrical potential, and the underground condition. If these factors
are known, the amount of transmitted electrical current can be estimated. Upon switching
the current on, it will drop gradually because the over-all resistance will increase after the
oil starts flowing and the anode surface area will decrease as a result of corrosion and
material selection (Anbah et al., 1965).
The total amount of current transmitted (I) for various electrode arrangement can be
estimated (Rudenberg, 1945; Cassagrande, 1949) by using equations such as those
presented below:
(a) For two cylindrical electrodes of equal length and crossectional area,
I = 2 πLE/( ρlnd/r) (1-67)
where ρ is the formation resistivity in ohm-meters; L and r are the length and radius of
the electrode in meters, E is the imposed electrical potential in volts; and d is the distance
between the anode and the cathode in meters.
(b) For two cylindrical electrodes with different radii,
I = ( πLE/ ρ)(1/lnd/r
1
+ 1/lnd/r
2
) (1-68)
(c) For a row of alternate anodes and cathodes the amount of electrical current can be
given approximately by
I = (N πLE/ ρ)(1/lnd/r
1
+ 1/lnd/r
2
) (1-69)
where N is the number of electrodes in each group.
57
(d) For spherical flow of current from a sphere with radius a to a distance x in the
ground,
I = (2 πLE/ ρ)(1/a + 1x) (1-70)
and when x approaches infinity, 1/x goes to zero and
I = 2 πLE/ ρa
Before one can proceed with estimating the consumption of power, some assumptions
have to be made. The following estimation of the current application, because it is very
difficult to estimate the decrease in the current flow as a result of the increase in the
overall resistance. On assuming that (1) the electrical current is available at the electrode;
(2) the formation resistivity is constant and is equal to 10 ohm-meters; (3) the electrode-
length and radius are equal to three and 0.1 meters, respectively; (4) the applied potential
is equal to three and 0.1 meters, respectively; (4) the applied potential is equal to 100
volts, and (5) the distance between electrodes is equal to 40 meters (Anbah et al., 1965)
and substituting the above values in Eq. 1-67:
I = 2*3.14*3*100/(10*ln40/0.01) = 31.4 amps
Thus, the power consumption is then equal to
31.4 *100/1000 = 3.14 Kw
The approximate cost of electricity (at $0.059/Kw.-hr.) = 3.14 x 24 x 0.059 = $ 4.45 per
day per well. If the labor cost is assumed to be $50 per day per well, then the total cost
becomes $230.76 per well per day. (See Handbook of Construction Cost, Halbert Powers
Gillette, 2006.)
58
It is assumed that the equipment needed (electronic power supply, electrodes,
power cables, etc.) will cost approximately $55,000 per well. If the estimated life of the
equipment is five years and its salvage value is 11,000, then by using straight-line
depreciation at 6 per cent average interest, the annual depreciation plus interest is equal to
$10,494 per well. (Modified after Anbah et al. 1965)
According to laboratory experimental results and the application of
electroosmosis in related engineering field, an average increase in the elctroosmotic flow
rate of water (corresponding to 3.14 KW.-hr.) can be estimated as 0.75 cc./sec. or 41.7
B/D. If it is further assumed that a piston like displacement of water to oil (banking) takes
places, an average increase in the oil produced is estimated to be 13.9 B/D per well. The
annual gross dollar return (at $70/Bbl) is equal to $355,145.00, and after CMR tax (at
$6/Bbl) is equal to $324,704.00. This value minus the annual labor and electricity cost
will give the net annual profit of: $324,704.00 - $84,227.40 = $240,476.60. The net profit
is approximately equal to 240,476.60/10,494.00 ≈ $22.92 dollar returned per dollar
invested (modified after Anbah et al., 1965).
These sample calculations are presented here in order to indicate the possibility of
such application in the field. It should be kept in mind, however, that for field application
the current is best applied in an interruptive manner which will cause a considerable
saving in power consumption. For the purpose of well stimulation, the application of
current may not exceed a period of one to two weeks. It is believed that such short
electrical treatment may lead to 50 or even 100 per cent increase in the average flow rate
of oil and water. It is also believed that the electrochemical well stimulation method will
59
prove in the future to be economically feasible, especially in specific cases where clay
swelling is extremely active.
The economic feasibility of using this technique in oil production will be more
apparent in a large-scale field application. In order to ensure optimum results, it is
strongly recommended that such large-scale application should be preceded by a flood
pot test followed by a pilot test (Anbah et al., 1965).
60
Summary
One can summarize the major features and advantages of electrokinetic technology as
follows:
The flow rate of oil and water can be increased by the application of direct current.
Chemical additives may be used in conjunction with electrical treatment to
augment the flow rate of transportable fluids in question.
Electrochemical treatment may be used for well stimulation.
Electrokinetics can be used as a selective ion-drive process.
Electrokinetic flow rate increases with increasing potential gradient (or electrical
current, I), first reaching a maximum, then decreasing with further increase in
electrical current.
Facilitates beneficial chemical changes in produced fluids.
It is cost competitive with steam EOR, with no depth constraint.
Thief zone problems (e.g., in the case of steam injection in EOR) do not exist.
There is no water or working fluid requirement.
Reduces water consumption and water cut when compared to steam EOR.
No hazardous emissions or liquid problems.
Facility installation can be incremental, allowing the spreading of capital over the
lifetime of the desired projects.
Brandon et al. (1993) showed the effectiveness of application of D.C. current in
releasing the stuck drillpipe in aqueous drilling fluids. They quoted the earlier
work of Chilingar et al. (1968).
61
Chapter 2: Electroremediation
Restoration of soils contaminated with hydrocarbons and metals is one of the most
important problems of environmental protection. During the last 40 years, considerable
progress has been made in the development of effective remediation technologies.
Modem purging technologies are based on the chemical and biological degradation of
contaminants and their conversion to safe forms or to intermediate substances convenient
for transport in soils. To accelerate transport of contaminants or their intermediate
substances in soils, electrical fields (direct current) are applied to zones being remediated.
This allows the volumetric rate of transport to increase ≈ 50-60 times, and the substances
to collect at convenient removal sites.
When a direct current electric field is applied to a wet porous medium polluted by
hydrocarbons or by ionic species, the aqueous phase is displaced by electroosmosis in the
pores and the ions migrate towards the electrodes. As a result, the value of the local pH at
the interfaces between water, oil and solid is changed, as well as the electric conductivity
of the medium: the ionic strength is increased towards each electrode and decreased
between them.
These mechanisms result in release of the oil droplets which block the capillary
tubes of the medium, either by mechanical action (movement of the water), or by
chemical action (change of the surface tension at the interfaces). Additionally, the
electromigration of ions through the medium can decrease the contamination level of
aquifers by changed chemical species (Lancelot et al., 1987).
62
These mechanisms were identified on polluted chalk cores, sandstone blocks, and
sand packs. The role of the various parameters was analyzed: the direction of the current
is unsensitive, the adding of surfactants increases the flow and a sequence of currents
plus water-drives with small gradient increases the oil recovery (Lancelot et al., 1987).
The use of electric current for improving the remediation of aquifers polluted by
hydrocarbons can be considered together with other commonly used techniques (e.g.,
gravitational pumping).
The electrokinetic method can also be used for remediation of aquifers polluted
by ionic species (Lancelot et al., 1987). Electrokinetically-enhanced transport of
contaminants is perhaps one of the most promising in-situ decontamination processes
capable of removing heavy metals and organic contaminants from soils, sludges and
lagoons.
The significance of this technology appears to be in its projected low operation
cost and its potential applicability to a wide range of contamination situations. It is also
viewed by researchers and industry as a potential “problem solver” when other remedial
technologies appear non-workable or fail to remediate a site. Present day urgency to
develop innovative technologies appears non-workable or fail to remediate a site. Present
day urgency to develop innovative technologies to cleanup contaminated soils and
ground water makes it necessary to look at the fundamental mechanisms associated with
the electrokinetic technology and to develop it into a well-engineered and predictable
process for field applications.
63
Fundamental experiments were performed by a group of researchers at the
University of Southern California in the early sixties. The experiments involved
application of direct electrical current for acceleration of the flow of solutions in
soils (Chilingar et al., 1997).
This, together with the latest advances in biodegradation of the eighties and
nineties, led to the development of sophisticated multicomponent remediation
technologies.
Success of these technologies depends on the selection of appropriate
combinations of microbiotic and chemicals degradation, and oriented electrokinetic
transportation of contaminants to the collection site.
A proper combination of remediation techniques is determined by the biological,
physical, chemical, and ecological conditions of the remediated zone.
The primary goal here is to:
(i) Review recent advances in electroremediation technologies and remediation science.
(ii) Evaluate the present state of the problem and the current trends in its development.
Another goal is to attract attention of the researchers to the key problems and bottlenecks
of the theoretical foundations and mathematical modeling of remediation processes.
Many technological operations, such as oil and gas exploration, production,
transportation, and usage of their derivatives lead to soil contamination by hydrocarbons.
If leaks and spills occur at the sites of manufacturing plants, then the soils are usually
contaminated with a mixture of hydrocarbons and metals. Contaminated areas cannot be
reused for other purposes without careful cleanup of soils to guarantee compliance with
64
the established environmental standards. Until recently, the only possible way to meet the
strict Environmental Protection Agency (EPA) standards was excavation of contaminated
soil, transportation, and burial at suitable places with all necessary precautions usually
taken for waste disposal. This, however, is a very expensive procedure.
The first recorded use of electrokinetics applied to dewatering soils and sludges in
the field was by Cassagrande (1949). Work and subsequent research in the electrokinetic
decontamination of soils has accelerated in recent years following the detection of high
concentrations of metals and organics in electroosmotically drained water of a dredged
sludge by Segall et al. (1980). Other field work including that of Lageman et al. (1989)
and Banarjee et al. (1988) has been conducted with reasonable success for heavy metal
transport.
Many laboratory and field tests were very successful. The process, using both
bacteria and D.C. current, was termed “electrobioremediation.” Huge volumes of
offshore muds are contaminated with heavy metals. I believe that these muds can be
cleaned by applying D.C. current to drive the heavy metals towards the cathode (well),
where they can be disposed of.
Recently developed complex cleaning technologies combine several efficient
methods of contaminant degradation with drastic acceleration of their transport in soils.
There are many examples of their successful application in situ, so that in most cases of
contamination with hydrocarbons and metals, it is possible to clean the sites to the
established environmental standards in an acceptable length of time at reasonable cost
without excavation of huge masses of soil.
65
Experiments on the application of direct electrical current for acceleration of the
flow of solutions in soils and sandstones were performed by a group of researchers at the
University of Southern California in the sixties under the direction of Professor George V.
Chilingar (e.g., Chilingar, 1952; Adamson et al., 1963a, 1963b, 1966; Chilingar et al.,
1964, 1965, 1966, 1968a, 1968b, 1968c, 1970; Amba et al., 1964, 1965).
These experiments, together with recent advances in biodegradation (Atlas, 1977, 1981;
Wilson, 1985; Nelson et al., 1987; Roberts et al., 1989; Morgan & Watkinson, 1989;
Leahy & Colwell, 1990; Sims, 1990; Hinchee et al., 1991; Huesemann, 1994), led to
development of a set of sophisticated multicomponent technologies (e.g., Bumett & Loo,
1994; Loo, 1991, 1993, 1994; Loo et al., 1994).
These technologies use combinations of microbiotic and chemical degradation,
appropriate for a particular site, and specific physical, chemical, geological, and
biological conditions, together with an electrokinetic-accelerated controlled transport.
In spite of the fact that the spectrum of cleaning technologies is broad enough to meet any
specific environmental and geological conditions, remediation technologies have not
been widely applied in soil cleanup practice. One of the main reasons is a complicated
science-intensive process of decision making on the choice of cleaning strategy for a site
of interest.
Blacker and Goodman (1994) indicated that considerable improvement in this
field could be achieved if policy judgments are separated from technical issues, and
cleanup goals are translated into measurable performance criteria. After that, it is possible
to apply well-developed optimization techniques to choose the "best" decision, which
66
will include an optimal combination of remediation technologies, appropriate methods
for waste ransport and removal, and methods for transformation of toxic waste into
harmless substances.
The unfavorable factor is that in choosing the remediation process, multicriteria
optimization may be the most appropriate because the state of the contaminated site and
cleaning technologies is usually assessed with multiple criteria (concentrations of
contaminants at many points of the site, for example).
At the final stage of optimization, inclusion of informal experts' opinions and
informal schemes of compromise may be necessary that considerably complicate the
decision—making process (Chilingar et al., 1997).
Electrokinetics essentially involves installing wells/drains, inserting electrodes,
and applying a low electric potential across the electrodes. Nutrients may be added to the
solution at the anode and/or cathode electrode, and, as a result of electromigration and/or
electro-osmosis, the nutrients are transported from the electrodes into the soil.
Basically, electromigration refers to the transport of charged species toward the
electrodes, whereas electro-osmosis refers to the bulk movement of liquid toward the
electrodes (generally from the anode to the cathode; Eykholt, 1992; Acar and
Alshawabkeh, 1993).
Statement of the Problem
A direct-current electric field applied to the electrolytic solution considerably accelerates
the rate of its flow in porous media (Chilingar et al. 1968a, 1968b, 1968c; Shapiro &
67
Probstein, 1993). It permits control of the direction of purging underground currents and
of the contaminants collection site. In combination with suitable amendments (nutrients,
etc.), a direct-current electric field creates favorable conditions for chemical and
biological degradation of hydrocarbon compounds (Cozzarelli et al., 1995; Morgan &
Watkinson, 1989). Multiple laboratory experiments and mathematical modeling have
proven the advantages of this technology. However, the application of bioremediation for
in situ cleaning sometimes yields unexpected results. In situ, one can observe a situation
when, after several days of successful cleaning, the species biodegradation and transport
can be retarded or even interrupted. Among the possible causes of retardation, one can
identify, for example, the soil cementation around the cathode or clogging of the purging
system with the produced biomass (Chilingar et al., 1997).
Specially designed laboratory experiments and mathematical modeling can reveal
the causes of these complications and suggest possible methods for their elimination. One
needs to control the pH along the area between electrodes (Hicks & Tondorf, 1994).
Also, it is necessary to calculate carefully the amount of amendments for biostimulation
(Pollard et al., 1994).
Thus, as pointed by Chilingar et al. (1997), the understanding of the main features
and control mechanisms of electrobioremediation is critical for successful application of
this technology in-situ.To determine the necessary amount of amendments and to
establish other control variables, one needs to solve some inverse mathematical problems
for finding influences that cause desirable effects. For that purpose, one needs to use
suitable mathematical models that reflect the main properties of underlying processes are
68
needed. The example of such a model for the process of electrokinetic transport is given
by Shapiro and Probstein (1993).
The reviewed publications show that good cleaning results in situ can be obtained
by application of a suitable combination of several purging technologies. For the
selection of an appropriate combination and its adjustment to the site's conditions, one
needs a high level of understanding of the mechanisms of all underlying physical,
chemical, and biological processes.
A review of the main technological aspects of the remediation procedure is
presented here, including: methods of electrobioremediation of hydrocarbons and metals
in soil, and transport and removal of the products of degradation using specially designed
electrical fields.
Concepts and Methods of Biodegradation of Hydrocarbons
As stated by Pollard et al. (1994), the objective of bioremediation in situ is to stimulate
the activity of the hydrocarbon-degrading microbiotic processes in the subsurface layer
and zones saturated with water. This goal can-be achieved by adding oxygen and
nutrients in a closed-loop control system (Hopper, 1989).
Amendments and solvents used to stimulate the biological activity of
microorganisms are introduced to the contaminated zone using some natural or artificial
channels such as a system of pores and fractures, wells, and infiltration galleries.
The process of biotreatment leads to the formation of soluble materials that are
transported with controlled flow of underground fluids to the place of collection or
69
the recovery system. If a recovery unit is used in the closed-loop remediation system,
these solutions are treated at the surface and then reinjected to recharge the contaminated
zone. Recharging of the purged zone prevents the possible ground subsidence caused by
the soil dewatering. Careful control of the amount of oxygen, nutrients, and solvents used
is necessary in order to accelerate the treatment process and prevent off-site migration of
contaminants and potentially harmful metabolites. Specific problem associated with oil
degradation in soil were considered by Raymond et al. (1976).
As Pollard et al. (1994) concluded, in most cases the main limiting factor for the
rate of in situ remediation is the amount of amendments supplied to the subsurface
microbial population (see also Lee et al., 1988). The sites with low horizontal hydraulic
permeability are not considered amenable to biodegradation because of the retardation of
transport flows that are necessary for the effective delivery of necessary amendments and
removal of the products of biodegradation. Success of the treatment depends on the
degree of hydraulic control that can be achieved in the "delivery-recovery system."
Without continuous delivery of nutrients and removal of metabolites, the remediation
system may become biologically inactive or clogged with biomass because of excessive
microbial activity.
Both of these extreme situations mean failure of the process of bioremediation. A
carefully dosed and controlled supply of amendments, therefore, is to be delivered to the
contaminated soil to ensure optimal conditions for the growth of bacterial colonies. This
condition leads to the formulation of the problem of optimal control of the delivery rate
of various amendments.
70
In this process, only soluble by-products can be recovered from the contaminated
site. Poorly soluble species, some of which may be harmful, may readsorb on the solid
matrix. In such cases, Mahaffey et al. (1991) recommended intensive soil washing using
surfactants. In turn, this demands precise identification of the components of
contamination to select an appropriate surface detergent.
Under unfavorable environmental conditions, which can considerably restrain
in-situ remediation, so-called enhanced land treatment procedures are being used.
Enhanced land treatment technologies have been successfully used for the treatment
of a wide variety of petroleum-contaminated soils (see references in Pollard et al., 1994).
In these technologies the contaminated soil is excavated, mixed with necessary
amendments, treated in special covered units to improve its characteristics, and then
returned to the site. Actually, this is the process of production of a new soil with given
desirable properties. Covered treatment facilities allow for organization of a highly
effective process for controlling volatiles, temperature, and the water and air regime
within the cleaning unit.
One should realize, however, that careful monitoring of remediation process
performance must be conducted using a mass balance approach, physical and chemical
measurements, and bioassay response data. This is the kind of complex, expensive, and
scope-restricted technology that cannot be recommended for broad applications
(Chilingar et al., 1997).
When time is critical for the process of restoration, slurry bioreactors are
recommended. In this technology, soil is treated as a water slurry in a closed reactor
71
(Visscher et al., 1990). A well-characterized and carefully seeded microbial population is
used for rapid biotransformation of even the most refractory contaminants.
Optimal process control allows for considerable reduction of the treatment time in
comparison with in situ or enhanced land remediation. Reactors can operate under either
aerobic or anaerobic conditions.
The anaerobic microbial population, however, is generally less flexible in
adapting to changes in the substrate availability and is less tolerant of inhibitory toxic
metals. The method can be recommended for the fast treatment of limited volumes of
clayey soils (Pollard et al., 1994).
For the sandy soils, a combined technology can be used, consisting of soil
washing, biological water-phase treatment, and slurry-phase bioreactor. One successful
example of the application of this combined technology is described by Stinson et al.,
(1992). They reported that more than 87% removal efficiency was achieved for
polynuclear aromatic hydrocarbons in this process. Bhandari et al., (1994) conducted a
series of experiments on petroleum-contaminated soil washing and discovered that it was
highly effective in combination with biotreatment.
European experience (Pheiffer, 1990; Nunno et al., 1988) has shown that soil
washing can be conducted on a large scale and at low costs if the clayey fraction is low.
Multiple studies in the United States, however. have demonstrated that each kind of soil
requires a careful preliminary evaluation of its mineralogy, porosity, permeability. and
contamination conditions because these factors considerably effect the final result of soil
restoration (e.g., Nash & Traver, 1988).
72
For effective biodegradation, it is necessary to develop conditions for electron
removal from the hydrocarbon compounds. The electron acceptance leads to faster
degradation of complex-compound hydrocarbons. Ionization caused by electron
acceptors allows for faster transport and removal of contaminants and their by-products
from the remediation site under electromagnetic field.
Conditions favorable for electron acceptor development can be effectively
reached under either aerobic or anaerobic conditions (Pollard et al., 1994).
Under aerobic conditions, oxygen serves as the terminal electron acceptor for the
oxidation of organic compounds by microorganisms. Under anaerobic conditions, some
other ions or compounds can serve as the terminal electron acceptors. Most of the
biotreatability studies and applications are concentrated on aerobic conditions because
these conditions provide the simplest and fastest means for oxidation and degradation of
contaminants such as hydrocarbons. Various species of hydrocarbons undergo their own
chain of transformations in soil and groundwater. Many researchers focused their
investigations on the group of aromatic hydrocarbons because of their toxicity and high
solubility in groundwater.
As Cozzarelli et al. (1995 and references therein) pointed out, these molecular-
weight alkylbenzenes are frequently reported to be present in the groundwater. The
hydrocarbons of this group are naturally degraded in the environment by aerobic and
anaerobic microbial processes. Their degradation can be stimulated by adding certain
substances, such as nitrates, as the electron acceptors to accelerate oxidation under
anaerobic conditions (Chilingar et al., 1997).
73
In applying any bioremediation technology to the petroleum-contaminated site,
it is necessary to be aware of considerable complications affecting the biodegradation
process.
Pollard et al. (1994) and McCarty (1991) pointed out some of the typical factors
that may lead to this type of complication:
(1) Multimedium nature of contamination process (soil, soil vapor, several soil layers,
groundwater, distinct hydrocarbon phases);
(2) Existence of a complex and problematic matrix of organic and inorganic contaminants
with a wide spectrum of environmental and toxicological properties;
(3) Heterogeneous subsurface conditions, which are difficult to characterize;
(4) Lack of optimal environmental conditions for the in situ
treatment.
Methods of Continuous Control and Management of Biodegradation of
Hydrocarbons In-Situ
Huesemann (1995) pointed out that the extent of hydrocarbon biodegradation
in contaminated soils is critically dependent on four factors: "the presence of
hydrocarbon degrading bacteria, the creation of optimal environmental conditions
to stimulate biodegradative activity, the predominant petroleum hydrocarbon
types in the contaminated matrix, and, finally, the bioavailability of the contaminants
to degradative bacteria."
74
Biotreatment of contaminated soils in situ is difficult primarily because it involves many
poorly defined situations and processes. Initially, it is necessary to conduct a pilot study
to understand the geologic scenario of the site and to evaluate the types of hydrocarbons
and degree of contamination. Sometimes this study can be time and budget consuming. It
may even be difficult to define how to characterize the final goal of treatment: it can be
characterized, for example, by the total petroleum hydrocarbon (TPH) feasible content in
soil, or by the concentrations of separate hydrocarbon species. One also needs to evaluate
an initial state of the site in quantitative terms to observe and monitor the remediation
process. Then it is necessary to formulate a set of mathematical relations linking the site
state variables with the modifiable control variables and parameters of the medium.
These relations are often called the "governing equations" (in spite of the fact that they
can include sets and inequalities as well) because they allow for defining quantitatively
the studied process, and for choosing and controlling the direction and scope of desirable
changes. (Chilingar et al., 1997.)
Finally, to realize the treatment process, one needs to choose some admissible
values of the control variables and to apply them in situ. It is a typical control problem;
however, it is a very difficult one. There are no readily applicable methods for its solution.
In addition, all underlying processes occur underground, and the measurement tools are
far from perfect. Solution and analysis of a remediation optimization problem must
include uncertainty accepting approaches such as stochastic control, fuzzy sets, and
sensitivity analysis.
75
The latter is especially important because it requires minimal additional
information in comparison with deterministic models. An advanced version of the
sensitivity analysis directly applicable to the considered problem was developed by Katz
et al. (1996).
A pilot study is usually aimed at evaluation of the contaminated site. One of
the main objectives of this study is to determine predominant petroleum hydrocarbon
types in the contaminated matrix. To formulate the purpose of bioremediation
cleanup correctly, one needs to estimate the possible extent of the degradation of
the predominant petroleum hydrocarbon type in contaminated soils.
For that purpose, Huesemann (1995) developed a predictive model based on the
correlation between the molecular structure of saturates and the extent of biodegradation.
This model allows for estimation of the final gravimetric TPH concentration if the
concentrations of the 86 compound classes in the initial gravimetric TPH are
known.
There is considerable need for mathematical models describing the dynamics
of hydrocarbon degradation and growth of bacterial colonies in the presence of
various nutrients. This model can be formulated, for example, in terms of a system
of differential equations describing general processes of growth. The current state
of the hydrocarbon degradation study is favorable for the estimation of coefficients
of such a model. Using this model, it will be much easier to choose the proper
amounts of amendments that are necessary for optimal development of the process
of biodegradation (Chilingar et al., 1997).
76
Concepts and Models of Electrokinetic Transport of Contaminants and
Their Intermediate Substances
Methods of electrokinetic transport of solutions in soil attracted significant
attention from many researchers in connection with in situ remediation (see, for
example, a fundamental work of Shapiro and Probstein (1993) or Amba et al.,
(1964)). Biological ionization of contaminant solutions in soil allows electrokinetic
methods to be applied for purging hazardous chemicals from a contaminated site.
The most advanced variant of electrokinetic techniques for removing hazardous materials
from soil is developed and described by Probstein et al. (1991).
Electrokinetic is described as the flow of an ionic liquid under interaction of an
electric field with a charged surface formed in the pores and capillaries. One of the most
important advantages of electrokinetic flow is that it is relatively insensitive to pore
size. "That is, unlike pressure-driven flows in which channeling of the fluid through
the largest pores is inevitable, electrokinetics permits a more uniform flow distribution
and a high degree of control of the direction of flow" (Shapiro & Probstein,
1993; Chilingar et al., 1970).
On the basis of extensive research, the present authors believe that double—layer
theory best explains the electrokinetic transport through porous media on application
of direct current (Fig. 1-1). As the predominantly positively-charged mobile layer moves
toward the cathode, the free solution in the center of the capillaries is dragged along
owing to friction forces. Simple purging equipment for field reclamation includes a direct
current power supply with a set of anode and cathode electrodes placed into wells drilled
77
on the site. The direct current field causes an electrokinetic effect in which
saturating liquid is driven by interaction of the electric field with the charged
double layer.
The flow direction is from the anode to the cathode. After it accumulates in the
cathode wells, highly contaminated effluent can be pumped, property treated, and
disposed of. Or, possibly, the polarity can be changed temporarily to convert the cathode
to the anode, where oxidation takes place.
Theory best explains the electrokinetic transport through porous media on
application of direct current (Figure 1-1). Laboratory experiments and the results of
application of electrokinetic reclamation in situ show that electrokinetic flow can
successfully compete with hydraulic Darcy's flow in the soils with low hydraulic
permeability.
Lageman et al.(1989) reported that the highest degree of removal of heavy metals
(over 90% of the initial contaminants) had been achieved for clayey, low-permeability
soils, whereas for porous, high-permeability soils, such as peat and river slush, the degree
of removal was only 65%. Laboratory results of Renaud and Probstein (1987),
Shapiro et al. (1989), and Acar et al. (1990) on electrokinetic purging of acetate
and phenol from saturated kaolinite clay had demonstrated more than 94% removal
of the initial contaminants.
The process of transport of contaminants and their derivatives involves two
major phenomena:
78
(1) the flow of contaminant solutions through a solid matrix due to Darcy's law and
electrokinetics.
(2) spatial redistribution of dissolved substances with respect to moving liquid due to
diffusion and migration of charged particles.
The total movement of the matter of the contaminant solution in the
direct current electric field (DC field) can be expressed as the sum of four
components: hydrodynamic flow of fluids driven by the pressure gradient, electrokinetic
flow of fluids due to interaction of the double layer with the DC field,
diffusion of components dissolved in the flowing solution, and migration of ions
inside moving fluids due to attraction of charged particles to electrodes.
The obvious merits of electrorestoration are the high degree of contaminant
removal, multifold acceleration of biochemical degradation, and directed rapid
transport of contaminant solution to designated wells for removal. In spite of these
merits, electrorestoration has not been widely applied as a purging technology in
situ. Frequently, its application in the field yields unexpected results. The commercia1
application of this technology requires a careful pilot study for the contaminated
site with the adjustment of the technology to the particular conditions of the site.
In turn, the technology itself must be carefully studied to understand effective
control influences for such an adjustment.
According to Hicks and Tondorf (1994), one might expect, for example, that
removal of heavy metals in the DC field is effective because electromigration of
79
ions is rapid and does not depend on the zeta potential. Laboratory experiments
with single metals mostly demonstrate high removal efficiency.
The limited field trials, however, produced inconsistent results. (These results, by
the way, can be reproduced in the laboratory.) Hicks and Tondorf arrived at the
conclusion that poor performance in situ can be attributed to the interaction of metals
with naturally occurring electrolytes, humic substances, and co-disposed wastes.
"Immobilization of contaminants in the narrow band in the soil, analogous to isoelectric
focusing, was reproduced experimentally and simulated with a mathematical
model. It was shown that the focusing effect can be eliminated by controlling the
pH at the cathode using a water rinse. Immobilization resulting from precipitation
of carbonates and co-disposed wastes may additionally require chelating agents and
control of the redox potential to achieve removal" (Hicks & Tondorf 1994).
As Shapiro and Probstein (1993) showed, the effect of electrode reactions on
the process of electrokinetics can be significant. Their influence on pore fluid and
surface charges of soil particles propagates at least several centimeters from
electrodes. For the low-pH front that moves from the anode to the cathode, these
reactions influence the whole area of medium involved in electrokinetic transport.
At the cathode the area with high pH is generally localized at a radius of a few
centimeters to around 20 cm. (Sometimes cathodes are converted into extremely
hard, well-cemented pillars, owing to precipitation of carbonates and hydroxides.)
This means that for understanding the electrokinetic transport in the field, one
needs to conduct experiments covering the whole area between the two electrodes.
80
In addition, for successful application of electrokinetics in situ, one needs to
provide continuous control of pH level in the vicinity of electrodes. One possible
way to achieve this is the periodic rinsing of the cathode with fresh water.
These examples can explain some of the causes of failure of electrokinetic
technology in situ. It is a complex technology that requires, for its successful
application, understanding of the multiple features of interaction of an electric
field with flowing charged fluid and a porous medium.
For widespread application in situ, one needs to carefully investigate the various
possible conditions of contamination and soil and rock types. The results of such an
investigation may indicate the cleaning policies to be recommended for in situ application.
Mathematical Modeling of Contaminant Transport in the Porous Medium
If the direction of the hydraulic pressure gradient coincides with the direction of
the DC electric field current, i.e., Darcy's flow and the electrokinetic transport
occur in the same direction, a one-dimensional mathematical model can be used to
show the main mechanisms of species transport. In this case, redistribution of the
species concentration in space can be described as a result of combined influence
of three mechanisms: Darcy flow, electrokinetics, diffusion.
The first two relate to the contaminant solution flow with respect to the solid soil
matrix, whereas the last redistributes the species inside the flowing fluids. (Chilingar et
al., 1997.)
For the purpose of simplified analysis, it is reasonable to consider a one-
dimensional fluid flow in the direction from anode to cathode. Denoting the
distance from the anode by x and the distance between anode and cathode by I ,
one can consider 0 < x < 1.
The total fluid flow rate q
t
(x) at point x can be expressed for this case in the
following form:
q
t
(x) = q
h
(x) + q
(x) (2-1)
where q
h
is the hydraulic component of the flow and q
is the electrokinetic
component of the total flow q
t.
To define q
h
(x), one can use Darcy's law (e.g., Bear, 1973):
q
h
(x) = Ak
h
μ
-1
dp/dx = Ak
h
μ
-1
p
(2-2)
where A is the cross-sectional area perpendicular to the direction of fluid flow, k
h
, is
Darcy's permeability of a porous medium in the direction of flow, is the
viscosity of fluid, and dp/dx = p is the pressure derivative in the direction of flow
at point x.
For the electrokinetic flow rate q
(x), one may use the Helmholtz—
Smoluchowski
equation version of the following form (Smoluchowski, 1921):
q
(x) = Ak
μ
-1
d
/dx = Ak
μ
-1
(2-3)
for which electrokinetic permeability k
, is defined by
k
=
(4 πF)
-1
D (2-4)
where F is the formation factor, D is the dielectric constant, is the zeta
81
potential, Φ is the electric field potential, and dΦ/dx = Φ is the potential
derivative in the direction of flow at point x.
Chilingar et al. (1970) conducted a simple analysis of conditions that are
responsible for the relationship between hydrodynamic and electrokinetic components
of flow. Based on Eqs. (2-2) and (2-3), they presented the ratio:
(q
t
- q
h
) / q
h
= k
Φ/ k
h
p (2-5)
This ratio shows that an increase in the electrokinetic flow rate is proportional to
the zeta potential, dielectric constant, and potential gradient.
The direct conclusion from Eq. (2-5) is that the electrokinetic technique is
especially effective in cases when hydraulic permeability K, is very small, which is
valid, for example, for clays or clayey sands (Chilingar et al., 1997).
Electrokinetic flow rate increases with increasing clay content in sands. For sands,
it is possible to raise the hydrodynamic component of the total flow by injection of
special purging solutions (Shapiro & Probstein, 1993).
Electrical field application in situ, as a rule, leads to an increase in temperature.
In turn, the temperature increase reduces the viscosity of hydrocarbon-containing
fluids that, according to Eqs. (2-2) and (2-3), would result in an increase of the
total flow rate (Chilingar et al., 1970).
Analyzing the results of "in situ" trials and verifying corresponding mathematical
models, one should keep in mind this additional positive side effect to avoid possible
misinterpretations of electrokinetic efficiency. This effect is insignificant for the
dissolved gaseous hydrocarbons (e.g., butane and methane) (Chilingar et al., 1997).
82
83
For crude oils (e.g., California crude oils), however, the viscosity can be reduced more
than 20 times upon heating from 50
o
C to 100
o
C (Ungerer et al., 1990), which (at least in
theory) would increase the total fluid flow 20 times.
Discussing an electrical field application for the acceleration of fluid transport in
situ, one needs to consider electrical properties of soils (electrical resistivity, for example)
and ionization rate of the flowing fluids that can considerably affect the total flow rate.
In addition, Chilingar et al. (1970) discovered that application of the DC field to some
soils leads to an increase of their hydraulic permeability, which in turn, can considerably
accelerate fluid transport. Some clays are destroyed (become amorphous) upon
application of a direct electric current, possibly as a result of driving the interlayer water
out (Harton et al., 1967).
Discussing the transport of contaminants in soil, one should remember that the
final goal of this process is to collect wastes at some location of the site convenient
for their final removal.
In terms of harmful species distribution, it means that initial uniform distribution
of the contaminants must be changed in the process of transport to the "peak" form, with
the sharp peak located at the place of removal.
The species concentrations at all other points of the site must be lowered
considerably (below acceptable levels) in the process of cleaning. Desirable species
distribution before and after purging is illustrated in Figures 2-1 and 2-2 (Chilingar et al.,
1997).
84
Actually, in this situation one faces a control problem that can be formulated
as follows. Starting from the distribution shown in Figure 2-1, one needs to achieve
the distribution shown in Figure 2-2, for example. To achieve this, it is necessary to
identify the control variables that affect the form of species distribution. For this
purpose, it is necessary to use an appropriate mathematical model of the transport
process.
Figure 2-1: Contaminant distribution before purging. (After Chilingar et al., 1997.)
85
Figure 2-2: Contaminant distribution after purging. (After Chilingar et al., 1997.)
86
According to Shapiro and Probstein (1993), one can ascribe the redistribution
of species in the flowing fluid to diffusion and electromigration. The process of
redistribution can be described by equations for species concentration and electrical
current density as follows:
δc
i
/ δt = -
j
i
+R
i
(2-6)
I = - Φ - F ∑
i€M
(z
i
D
i
c
i
) + Fu ∑
i€M
(z
i
c
i
) (2-7)
where for each species i, i € M, M = (1,2,. . . , m); c
i
is the concentration in moles
per unit volume of solution; δc
i
,/ δt is the partial derivative of c
i
, with respect to
time t; R
i
is the molar rate of production of the ith species due to chemical
reactions; j
i
is the molar flux; I is the electric current density, Φ is the electric
potential; D, is the diffusion coefficient; F is the Faraday constant; u is the mass
average velocity of flow; z
i
is the charge number; and is the scalar electrical
conductivity of the solution:
= F
2
∑(z
i
2
υ
i
c
i
) (2-8)
Mobility υ
i
, is related to the diffusion coefficient by the Nernst—Einstein equation:
υ
i =
D
i
/RT (2-9)
The molar flux ji is given by the Nernst-Plank equation:
j
i
= - υ
i
z
i
Fc
i
Φ - D
i
c
i
+ c
i
u (2-10)
Shapiro and Probstein (1993) applied these equations to a tortuous capillary model
of a porous medium.
87
88
As a result, one can obtain a partial differential equation for the distribution of
concentrations of species in the porous medium of the following form:
δC
i
/ δt = D
i
/ τ
2
δ
2
C/ δx
2
- δ/ δx[C
i
(u
,i
+ u
c
+ u
h
)]+ R
i
(2-11)
with the parameter τ describing the tortuosity of the porous medium.
In Eq. (2-11), C
i
is the average (through the cross section perpendicular to the
direction of flow) concentration of the ith component; u
,i
, u
c
, and u
h
, are the
average electromigration, electrokinetic, and hydraulic components of the flow
velocity, respectively.
These components are changeable within some limits and can be considered as control
variables.
Shapiro and Probstein (1993), computed several variants of the numerical
solutions of Eq. (2-11) with realistic boundary conditions. The modeled distributions
of concentrations for acetic acid in the saturated clay soil are in good agreement
with the results of specially designed experiments. Their experiments showed that a
very high degree of removal of contaminants can be achieved on application of a
DC current when used under appropriate conditions. Thus for example, the phenol
contaminant fraction removed from clay samples reached 95% of the initial phenol
concentration after 1.5 pore volumes of effluent were collected and removed.
These experimental results are in good agreement with the theoretical results
predicted by the model. Applying Eq. (2-11) for the modeling of contaminant
concentration distribution, one needs to be aware that a high degree of spatial and
89
temporal resolution is required to integrate the differential equations used in the
model (Chilingar et al., 1997).
Multicomponent Cleanup Technologies and Examples of Their Application
in-situ
Examples of successful application of cleanup technologies in situ show that the
best final results are achieved when one uses some combination of several
methods. There is a wide variety of mechanical, physical, chemical, and bioremediation
cleaning methods that are applied in contemporary practices for the restoration
of a contaminated site. It is even difficult to name and characterize all of
them. (This can be the goal of a separate article. Good classification of the
bioremediation methods with general recommendations of their applications was
presented by Pollard et al. (1994).)
For any particular contaminated site, one should select the most appropriate
cleanup technology (or the most appropriate combination of different technologies).
The choice of a concrete technology (or technologies) depends on many factors, e.g., the
site size, type of predominant contamination, the site's future use, and available resources
(time and money). Examples of such an approach to the selection of cleanup strategy
were presented by Blacker and Goodman (1994) and Fairless (1990).
They developed some reasonable selection methodology of cleaning technologies, based
on the principles of system analysis: from the final goal, through the quantitative
characterization of the problem to the choice of preferable alternatives.
90
Many good examples of successful application of the combined technologies
were presented by W. Loo and associates. Loo (1994) used a combined system,
including primarily passive co metabolic biotreatment and electrokinetic transport
of amendments and contaminants in solution for degradation of gasoline and diesel
in the soil and groundwater. In one case, leakage of g- gasoline and diesel from an
underground storage tank caused soil and groundwater contamination in the clayey
Bay Mud of Hayward, California. The soil contamination extended to a depth of
about 10 ft (3 m) with a TPH concentration of 100-3900 ppm (Chilingar et al., 1997).
The gasoline and diesel in the soil were degraded to less than 100 ppm of TPH and to less
than 10 ppm in groundwater. The remediation process was completed in 4 weeks.
A combination of biodegradation and electrokinetic transport with a hot air
venting system and ultraviolet light biocontrol system was used by Loo et al. (1994)
for degradation of gasoline in the clayey soil. The gasoline soil plume covered an
area of about 2400 ft2 (223 m
2
), to a depth of about 30 ft (9 m). The upper 15 ft
(4.6 m) of sediments were composed of highly conductive marine clay, whereas the
lower 15 ft consisted of well-cemented conglomeratic sandstone.
The gasoline concentration ranged from 100 td 2200 ppm. The process of
remediation was completed after about 90 days of treatment. The concentration of
gasoline in the soil after treatment was far below the proposed cleanup level of 100 ppm.
The cost of treatment was about $50 per ton of soil for this advanced soil treatment
process, which provided a cost-effective remediation with minimum disruption to
business operations at the site (Chilingar et al., 1997).
91
A closed recovery system for soil and groundwater for a site contaminated with
gasoline in Greenville, North Carolina, was developed by Burnett and Loo (1994).
The dissolved contaminant plume covered an area of 18,000 ft2 (1672 m
2
) and
penetrated to a depth of about 15 ft. The total volume of spill was estimated at
300,000 gal (1,135,500 L). The initial concentration of gasoline in the plume
averaged about 40 mg/L of total content of benzene + toluene + ethylene + xylene
(BTEX).
A special enhanced bioremediation system was designed to clean this site. The
system consisted of two groundwater recovery wells, a treatment unit, and an
infiltration gallery.
The treatment unit consisted of transfer pumps, pressure filters, granulated
activated carbon filters, air spargers, holding tanks, chemical feed system, water heater,
and monitoring means. The bioenhancement process included heating, addition of
nutrient amendments (monoammonium phosphate and trisodium phosphate), and oxygen
addition (dilute hydrogen peroxide). In 6 months of operations, BTEX in the plume had
been reduced to the level less than 6.5 mg/L with the passage of 11 pore volumes of
displacement (Chilingar et al., 1997).
In the considered examples, the treatment was successful owing to specially
developed and designed combined systems of remediation. These systems were
developed on the basis of information about the scale of contamination, concentrations
of contaminants, soil type, and final goal of remediation. For the widespread
92
application of cleanup technologies in situ, one needs to achieve a high degree of
formalization and unification in the development of cleanup projects.
Electroremediation of Soils
The methodology can be imagined as a set of decision-making matrices (tables),
which lists the characteristics of contaminants, soils, and groundwater, the scope of
contamination, and the corresponding combinations of cleanup technologies.
Performance of all technological units must be carefully controlled to avoid
possible complications in situ. To understand and control the remediation processes,
one needs mathematical models that can be easily tuned for specific site
conditions. As an example, one can consider the model of electrokinetic transport
discussed by Shapiro and Probstein (1993). Such models can be used to formulate
control problems for various performance criteria and a variety of realistic constraints
for in situ cleanup.
It was shown in recent publications (Hicks & Tondorf, 1994; Shapiro & Probstein,
1993) that for successful electrorestoration of hydrocarbon- and metal contaminated soils,
it is necessary to control redox potential and pH along the path of electrokinetic transport
to prevent cementation and stabilization.
These parameters can considerably affect the results of restoration.
Understanding- their influences on electrokinetics for various combinations of
93
contaminants, purging fluids, soils. and characteristics of the applied electrical field
allows for the design of effective techniques to achieve a high degree of decontamination.
Chapter 3: Apparatus and Experimental Procedure
Laboratory Equipment
In figures 3-1 and 3-2, an illustration diagram shows the first apparatus and connections
used in D.C. technology at the laboratory at the University of Southern California by
Professor George V. Chilingar. (After Adamson et al., 1962-1963.)
Fig 3-1: A schematic diagram showing the first apparatus and connections used in
Petroleum Engineering Laboratories at the University of Southern California.
(After Chilingar et al., 1962.)
94
Fig 3-2: Schematic diagram of second apparatus and connections used in Petroleum
Engineering Laboratories at the University of Southern California. (After Chilingar
et al., 1962.)
95
In figures 3-3, 3-4, 3-5 and 3-6, an illustration diagram shows the glass core
electrokinetic apparatus and connections used at the Fritz Engineering laboratory of the
Lehigh University by Professor Sibel Pamukcu. (After Pamukcu et al., 1993.)
Fig 3-3: Schematic diagram of glass elektrokinetic cell (After Pamukcu et al., 1993)
96
Fig 3-4: Photograph of electrokinetic apparatus and multimeter for measuring
voltage, current and resistance. (See Fig. 1-8.)
97
Fig 3-5a: Electrokinetic apparatus, DC power source and graduated glass burettes
to measure both inflow and outflow at each of the two electrode ends (anode and
cathode). (See Fig. 3-3.)
Fig 3-5b: Electrokinetic apparatus, DC power source and graduated glass burettes
to measure both inflow and outflow at each of the two electrode ends (anode and
cathode). (See Fig. 1-8.)
98
Fig 3-6a: Photograph of electrokinetic apparatus for measuring large cores
(1 meter x 1 meter x 15 cm). (Designed by Dr. Sibel Pamukcu.)
99
Fig 3-6b: Photographs of electrokinetic apparatus for measuring large cores
(1 meter x 1 meter x 15 cm). (Designed by Dr. Sibel Pamukcu.)
100
101
Experimental procedure and preliminary results of electroremediation by the writer
The following heavy metals were tested in the laboratory for part (I) of this study using
kaolinite clay in:
(1) Distilled water.
(2) Ground water.
(3) Water with humic substances of 900 ppm.
Arsenic
Cadmium
Chromium
Lead
Slurry samples of kaolinite clay were prepared each containing one of the heavy metals.
The slurry was compacted into an EK sample tube and tested for 24 hours. The initial
concentration of the contaminant was recorded at three positions along the sample tube:
anode, center and cathode. After the 24-hour test, samples were extracted using the
3050B EPA method for acid digestion. The AAS and ICP-MS methods were used for
chemical analysis of lead. All other heavy metal concentrations were determined using
the ICP-MS equipment.
The initial and final sample water content and pH were determined for each test.
Facilities and Equipment
The apparatus consisted of two parts: an electrokinetic (E-K) cell and a flow control
panel. A schematic diagram of the electrokinetic apparatus assembly is given in Figures
102
3-3 – 3-5. The electrokinetic test apparatus used in this project was developed based in
the following considerations (Pamukcu et al., 1993):
i) electrode reactions will take place and hence electrodes should be
isolated from the soil;
ii) electrode reactions will produce gas at the electrode surfaces due to
electrolysis, and a convenient method for gas ventilation has to be
provided to accurately measure the water transport;
iii) electrode surface has to be larger than the soil cross sectional area so
the a low current density at the electrodes will produce a relatively
large current density in the soil;
iv) ports for extracting inflow and outflow fluid samples have to provided
for the analysis and monitoring process.
Based on these considerations, the electrode surface area was selected to be six times
larger than the sample cross-sectional area. Clear acrylic plastic was used for all cell parts
to provide visibility and also defect gas generation at the electrode sites, the soil-water
interface and possibly in the soil. The electrodes are made of high grade graphite rods to
minimize electrode deterioration.
The electrokinetic cell has the following components (Pamukcu et al., 1993):
Sample tube: The sample tube has an ID of 3.55 cm and a length of 7.62 cm and is made
of clear acrylic tube. The tube accommodates three auxiliary graphite electrodes (1 mm
103
diameter), separated at equal distance along one side, through which voltage can be
measured during experiments. The tube is assembled to the electrode chambers with O-
rings placed inside the housings cut on the inner walls (facing the sample tube) of the
chambers.
Porous stones: Carborandum porous stones are placed at each end of the sample tube to
hold the soil sample in place during the experiment. The porous stones have a
permeability of 10
-3
cm/sec, which is highly porous compared to the clay soils tested
which have hydraulic permeabilities ranging from 10
-6
to 10
-8
cm/sec. Therefore, they do
not influence the rate of flow through soil. The stones are washed with dilute nitric acid
to ensure removal of metal impurities and particles which might clog the stone or
influence the results of the chemical analyses. They are then boiled in distilled water
before each usage.
Electrode chambers: These chambers are approximately 130 cm
3
in volume. They
house the electrodes at each end of the soil sample tube. The end plates are removable for
filling and emptying these chambers of fluid. This feature also facilitates cleaning of the
chambers and electrodes after each test run. Teflon membrane gaskets situated at these
ends provide a water tight seal.
Electrodes: Electrode assemblies with a surface area of 22.6 cm
2
facing the soil
specimen were constructed of graphite rods with a 0.635 cm diameter held together with
graphite conductive adhesive. The assembly’s connecting rod is flush with the outer
surface of the back wall. An electrode socket is placed through the center of the exposed
104
rod and fixed in place with carbon conductive epoxy glue. These connections are wired to
a variable DC power source.
Fluid connections: Teflon or stainless steel quick-connections are provided on the
bottom of the back wall of the electrode chambers. These outlet or inlets are then
connected to volume measuring tubes and pumped via Teflon tubing. The advantage of
the quick connections is that they close the connection upon detachment, which allows
the electrokinetic (E-K) cell to be detached from the control panel while the electrode
chambers are still charged with fluid.
Gas expulsion or sample extraction/injection ports: These ports are pressure valves
provided on the cover plate over each electrode chamber. These valves have metal
surfaces which are coated to control any deterioration by electrochemical reactions or
metal ion deposition on them. Sample extractions or fluid injections are accomplished
using a volumetric syringe which allows for accurate control of quantities of fluids.
Burettes: Glass burettes with a capacity of 25 cc are used to measure inflow, normally at
the anode (positive electrode) chamber, and outflow, normally at the cathode (negative
electrode) chamber to an accuracy of 0.1 cc.
Vent-pressure valves: Vented pressure valves exist at the top of each burette to provide
gas expulsion.
Power supply: Dedicated electrical units for each E-K cell consist of variable direct
current (DC) power supply capable of applying either constant voltage (0 to 30.6 volt), or
constant current (0 to 2500 mA). These units also contain analog meters for measuring
voltage and current.
105
Compaction Apparatus: A schematic diagram of the compaction apparatus used is
shown in Figure 2-3. The apparatus consist of a PVC sample cell (guide tube) measuring
45.72 cm length by 2.67 cm diameter, in which the slurry sample is injected. The weight
base with compacting column causes a piston like displacement based on choice of
several weights that allow for a varied pressure range of 5 psi to 30 psi. This is then
placed on top of the injected slurry that’s contained within the PVC sample cell with the
porous stone placed at the bottom end. The weights are placed in the tray at the top of the
compacting column in progressive increments, throughout a period of 24 hours
amounting to a final pressure of 30 psi to be exerted for final compaction to reach a
compacted sample having uniform density, porosity and contaminant concentration
distribution. During compaction, fluid is drained at the top and bottom of the sample via
porous stones resting on both ends of the core.
Soil slurries are prepared by mixing an aqueous solution of the desired
contaminant with the soil, and the type of water chosen with a prepared water content of
55%. After the 24 hour period of compaction, all the samples had a water content of 40%
recorded as the initial water content before the E-K test.
Figure 3-7: Compaction apparatus used to prepare samples for E-K tests.
Electrokinetic Testing
In all experiments, a constant 20-volts DC potential was applied across the core samples.
During the E-K test: Volumetric electroosmotic inflow and outflow readings are take n
from the graduated burettes. The system is checked to insure the delivery of the 20 V
applied, recording the current density as well. This is done using a multi-meter to read
voltage across the E-K apparatus via power connections to each of the primary electrodes
and on the secondary electrodes along the sample tube. Readings were taken at 0, 15 and
30 minutes and one and two hours after the start of the test (Pamukcu et al., 1993).
After the E-K test: During cell disassembly, the pH of the anode and cathode fluid is
recorded and a sample is taken for analysis. Since the cathode fluid is generally basic
(high pH), it may contain some precipitates of certain metals, it is acidifed with HCl to
ensure a more accurate chemical analysis of the chemical content. The colors of both
106
107
water and soils are noted. Finally the soil is extruded from the sample tube and measured
at the center of the soil cross-section at 5 evenly spaced points along its length for pH,
water content and redox-potential in millivolts (Pamukcu et al., 1993).
108
Chapter 4: Experimental Results
Here, we will demonstrate the feasibility of using electrokinetics to decontaminate heavy
metals from clay formations. In the first part of this chapter, experimental testing
confirmed the efficiency of using electroremediation to treat moderately and highly
artificially contaminated clays in labs at both Lehigh University as well as at the
University of Southern California. In the final part, the world’s first conducted test on
field collected data of contaminated offshore muds was performed at the Petroleum
Institute in Abu Dhabi, U.A.E. to prove the efficacy of using electrokinetics in such a
high salinity environment as a suitable option for in-situ treatment
The results will be split into two sections:
1. a) Artificially polluted clay specimens of low concentration heavy metals
performed at Lehigh University by Dr. Sibel Pamukcu.
b) Artificially polluted clay specimens of high concentration heavy metals
performed at USC by the writer.
2. Field collected data from the coastline of two geographic locations in Abu
Dhabi, U.A.E. by the writer.
109
Part I
Laboratory Simulation
pH 7.90 ppm
Ca 47.06
Mg 14
Bicarbonate 90.51
Chloride 83.43
Sodium 32.04
Potassium 3.51
Sulfate 55.34
Fluoride --
Silica --
Nitrogen, Nitrite --
Nitrogen, NO
2
+ NO
3
--
Arsenic 2.01 ppb
Barium 54.95
Beryllium --
Cadmium 0.098
Strontium 171.61
Zinc 173.66
Table 4-1: Ground water composition of Jefferson County water, Id (USGS 1989)
110
The following results were obtained after 24-hour EK tests:
The following results of part I, are split into two categories, low concentration (L) and
high concentration (H) samples. The low concentration tests were performed by Dr.
Pamukcu at Lehigh University, while the high concentration tests were performed by the
writer at the University of Southern California.
(i) Arsenic: Arsenic was in anionic (HAsO
4
2-
) form in the initial mixing state into the
slurry. Fig. 2-4 through 2-6, show the fraction of arsenic found at three different locations
in the core: the anode, the center, and the cathode end. Arsenic content was reduced
(from its initial concentration) at both the cathode and anode regions of cores. Highest
concentration of arsenic was present at the center of the cores by the end of treatment.
Arsenic speciation and solubility is greatly affected by the pH and redox potential of the
soil. The availability of arsenic, in the form of aresnite (As(III)) increase at low redox
potential and alkaline conditions. The average pH of the center section was 2.9 ranging
from 1.8 to 3.0. Subsequent analysis of redox potential variation of kaolinite clay during
electrokinetics showed that, in general, the anode end of the soil remains in oxidizing
state, while the cathode end is in reducing state. At high redox levels (oxidizing state) the
majority of As is found in arsenate form (As(IV)) which is not as soluble as As(III), and
tend to be retained on the oxide surfaces of the clay minerals (Masscheleyn et al., 1991).
Accumulation of arsenic at the center of the soil specimens can be explained by the low
pH and the oxidizing state of the soil at that location. Accumulation was evident at the
center of the soil samples for most of the specimens except for the low concentration case
in which the metal appeared not to migrate substantially (Pamukcu et al., 1993).
Distilled water:
Concentration profile of low concentration As in kaolinite clay using distilled water
- 24 hr EK test
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from Anode to Cathode
C oncentration (p p m )
Final Concentration KSASLM1
Initial Concentration KSASLM1
Figure 4-1-L-a: Results of EK test for electroremediation of arsenic using distilled
water (Pamukcu et al., 1993).
111
Concentration profile of low concentration As in kaolinite clay using distilled water
- 24 hr EK test
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C on centration (p p m )
Final Concentration KSASLM2
Initial Concentration KSASLM2
Figure 4-1-L-b: Results of EK test for electroremediation of arsenic using distilled
water (Pamukcu et al., 1993).
112
Concentration profile of low concentration As in kaolinite clay using distilled water
- 24 hr EK test
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
0 0.1 0.20.30.40.5 0.60.70.8 0.9
Fractional distance from anode to cathode
C o n cen tratio n
1
(p p m )
Final Concentration KSASLM3
Initial Concentration KSASLM3
Figure 4-1-L-c: Results of EK test for electroremediation of arsenic using distilled
water (Pamukcu et al., 1993).
113
Ground water:
Concentration profile of low concentration As in kaolinite clay using ground water
- 24 hr EK test
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C oncentration (p p m )
Final Concentration KGASLM1
Initial Concentration KGASLM1
Figure 4-2-L-a: Results of EK test for electroremediation of arsenic using ground
water (Pamukcu et al., 1993). (See Table 4-1 for composition)
114
Concentration profile of low concentration As in kaolinite clay using ground water
- 24 hr EK test
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C on c e ntra tion (p p m )
Final Concentration KGASLM2
Initial Concentration KGASLM2
Figure 4-2-L-b: Results of EK test for electroremediation of arsenic using ground
water (Pamukcu et al., 1993). (see Table 4-1 for composition)
115
Concentration profile of low concentration As in kaolinite clay using ground water
- 24 hr EK test
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KGASLM3
Initial Concentration KSASLM3
Figure 4-2-L-c: Results of EK test for electroremediation of arsenic using ground
water (Pamukcu et al., 1993). (see Table 4-1 for composition)
116
Water with humic substances (900ppm):
Concentration profile of low concentration As in kaolinite clay using distilled water with 900
ppm humic substances
- 24 hr EK test
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C oncentration (p p m )
Final Concentration KHASLM1
Initial Concentration KHASLM1
Figure 4-3-L-a: Results of EK test for electroremediation of arsenic using water
with humic substances (900ppm) (Pamukcu et al., 1993).
117
Concentration profile of low concentration As in kaolinite clay using distilled water with 900 ppm
humic substances
- 24 hr EK test
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
Co ncentration (p p m )
Final Concentration KHASLM2
Initial Concentration KHASLM2
Figure 4-3-L-b: Results of EK test for electroremediation of arsenic using water
with humic substances (900ppm) (Pamukcu et al., 1993).
118
Concentration profile of low concentration As in kaolinite clay using distilled water with
900 ppm humic substances
- 24 hr EK test
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KHASLM3
Initial Concentration KHASLM3
Figure 4-3-L-c: Results of EK test for electroremediation of arsenic using water with
humic substances (900ppm) (Pamukcu et al., 1993).
119
120
(ii) Cadmium: Figs. 4-4 – 4-6, show the fraction of cadmium found at three different
locations in the soil after the 24 hours of electrokinetic treatment of soil specimens
containing high cadmium concentration. Cadmium is a divalent cation which showed a
migration path toward the cathode. Cadmium exhibited a maximum concentration at the
cathode end of the soil sample. This is attributed to the increase in the hydrolysis with an
increase in pH at the cathode end. The average pHs measured at the cathode ends were
5.3, 8.1 and 9.0 for distilled water, groundwater and humic solution specimens of
kaolinite clay, respectively. Until around pH 8, Cd remains in its divalent cationic form.
Beyond this value it starts forming complex species which are either charged positively
or negatively or neutral. The tendency and the abundance of these products control the
removal rate until the acid front reaches the cathode region in the soil. However, with
high pH prevailing at the soil—water interface of the cathode end of the soil, a thin layer
of precipitate would form at the interface making it difficult for cadmium to be removed
into the cathode electrode water chamber (Pamukcu et al., 1993). There is also an
increase in soil adsorption capacity with increasing pH which would contribute to the
accumulation of the metal at this region (Sposito, 1984; Basta and Tabatabai, 1992).
Distilled water:
Concentration profile of low concentration Cd in kaolinite clay using distilled water
- 24 hr EK test
0
5
10
15
20
25
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C oncentration (p p m )
Final Concentration KSCDLM1
Initial Concentration KSCDLM1
Figure 4-4-L-a: Results of EK test for electroremediation of cadmium using distilled
water (Pamukcu et al., 1993).
121
Concentration profile of low concentration Cd in kaolinite clay using distilled water
- 24 hr EK test
0
5
10
15
20
25
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KSCDLM2
Initial Concentration KSCDLM2
Figure 4-4-L-b: Results of EK test for electroremediation of cadmium using distilled
water (Pamukcu et al., 1993).
122
Concentration profile of low concentration Cd in kaolinite clay using distilled water
- 24 hr EK test
0
5
10
15
20
25
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KSCDLM3
Initial Concentration KSCDLM3
Figure 4-4-L-c: Results of EK test for electroremediation of cadmium using distilled
water (Pamukcu et al., 1993).
123
Ground water:
Concentration profile of low concentration Cd in kaolinite clay using ground water
- 24 hr EK test
0
20
40
60
80
100
120
140
160
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KGCDLM2
Initial Concentration KGCDLM2
Figure 4-5-L-a: Results of EK test for electroremediation of cadmium using ground
water (Pamukcu et al., 1993). (See Table 4-1 for composition)
124
Concentration profile of low concentration Cd in kaolinite clay using ground water
- 24 hr EK test
0
10
20
30
40
50
60
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C oncen tration (p p m )
Final Concentration KGCDLM3
Initial Concentration KGCDLM3
Figure 4-5-L-b: Results of EK test for electroremediation of cadmium using ground
water (Pamukcu et al., 1993). (See Table 4-1 for composition)
125
Water with humic substances (900ppm):
Concentration profile of low concentration Cd in kaolinite clay using distilled water
with humic substances (900ppm) - 24 hr EK test
0
50
100
150
200
0 0.10.20.30.40.5 0.60.70.80.9
Fractional distance from anode to cathode
C oncentration
1
(p p m )
Final Concentration KHCDLM1
Initial Concentration KHCDLM1
Figure 4-6-L-a: Results of EK test for electroremediation of cadmium using water
with humic substances (900ppm) (Pamukcu et al., 1993).
126
Concentration profile of low concentration Cd in kaolinite clay using distilled water
with humic substances (900ppm) - 24 hr EK test
0
50
100
150
200
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KGCDLM2
Initial Concentration KHCDLM2
Figure 4-6-L-b: Results of EK test for electroremediation of cadmium using water
with humic substances (900ppm) (Pamukcu et al., 1993).
127
Concentration profile of low concentration Cd in kaolinite clay using distilled water
with humic substances (900ppm) - 24 hr EK test
0
20
40
60
80
100
120
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KHCDLM3
Initial Concentration KHCDLM3
Figure 4-6-L-c: Results of EK test for electroremediation of cadmium using water
with humic substances (900ppm) (Pamukcu et al., 1993).
128
129
(iii) Chromium: Chromium was introduced to the soil in anionic form—(Cr
2
O
7
2-
).
Chromate (chromium in the hexavalent oxidation state) is an anion which carries two
negative charges. Approximately, 30% of the Cr was extracted at the anode chamber by
the end of the 24 to 48 hours of treatments (see Fig. 4-7 – 4-9). In this case, the
electromigration of the ion took place in the opposite direction of the electrokinetic water
flow. There was accumulation of metal at the discharge end (anode end of the soil)
(Pamukcu et al., 1993).
Distilled water:
Concentration profile of low concentration Cr in kaolinite clay using distilled
water - 24 hr EK test
0
20
40
60
80
100
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KSCRLM1
Initial Concentration KSCRLM1
Figure 4-7-L-a: Results of EK test for electroremediation of chromium using
distilled water (Pamukcu et al., 1993).
130
Concentration profile of low concentration Cr in kaolinite clay using
distilled water - 24 hr EK test
0
20
40
60
80
100
00.2 0.4 0.6 0.81
Fractional distance from anode to cathode
C oncentration (p p m )
Final Concentration KSCRHM2
Initial Concentration KSCRHM2
Figure 4-7-L-b: Results of EK test for electroremediation of chromium using
distilled water (Pamukcu et al., 1993).
131
Concentration profile of low concentration Cr in kaolinite clay using
distilled water - 24 hr EK test
0
20
40
60
80
100
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KSCRHM3
Initial Concentration KSCRHM3
Figure 4-7-L-c: Results of EK test for electroremediation of chromium using
distilled water (Pamukcu et al., 1993).
132
Concentration profile of high concentration Cr in kaolinite clay using
distilled water - 24 hr EK test
0
1000
2000
3000
4000
5000
0 0.2 0.4 0.6 0.8 1
Fractional distance from anode to cathode
Co n cen tratio n (p p m )
Final Concentration
KSCRHM1
Initial Concentration
KSCRHM1
Figure 4-7-H-a: Results of EK test for electroremediation of chromium using
distilled water.
133
Concentration profile of high concentration Cr in kaolinite clay using
distilled water - 24 hr EK test
0
1000
2000
3000
4000
5000
6000
0 0.2 0.4 0.6 0.8 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KSCRHM2
Initial Concentration KSCRHM2
Figure 4-7-H-b: Results of EK test for electroremediation of chromium using
distilled water.
134
Concentration profile of high concentration Cr in kaolinite clay using
distilled water - 24 hr EK test
0
1000
2000
3000
4000
5000
6000
7000
0 0.2 0.4 0.6 0.8 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KSCRHM3
Initial Concentration KSCRHM3
Figure 4-7-H-c: Results of EK test for electroremediation of chromium using
distilled water.
135
Ground water:
Concentration profile of low concentration Cr in kaolinite clay using
ground water - 24 hr EK test
0
20
40
60
80
100
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KGCRLM1
Initial Concentration KGCRLM1
Figure 4-8-L-a: Results of EK test for electroremediation of chromium using ground
water (Pamukcu et al., 1993). (See Table 4-1 for composition)
136
Concentration profile of low concentration Cr in kaolinite clay using
ground water - 24 hr EK test
0
20
40
60
80
100
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C oncentration (p p m )
Final Concentration KGCRHM2
Initial Concentration KGCRHM2
Figure 4-8-L-b: Results of EK test for electroremediation of chromium using
ground water (Pamukcu et al., 1993). (See Table 4-1 for composition)
137
Concentration profile of low concentration Cr in kaolinite clay using
ground water - 24 hr EK test
0
20
40
60
80
100
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KGCRHM3
Initial Concentration KGCRHM3
Figure 4-8-L-c: Results of EK test for electroremediation of chromium using ground
water (Pamukcu et al., 1993). (See Table 4-1 for composition)
138
Water with humic substances (900ppm):
Concentration profile of low concentration Cr in kaolinite clay using water with 900 ppm
humic substances - 24 hr EK test
0
20
40
60
80
100
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KHCRLM3
Initial Concentration KHCRLM3
Figure 4-9-L: Results of EK test for electroremediation of chromium using water
with humic substances (900ppm) (Pamukcu et al., 1993).
139
0
1000
2000
3000
4000
5000
6000
7000
0 0.2 0.4 0.6 0.8 1
Fractional distance from anode to cathode
C oncentration (p p m )
Final Concentration KHCRHM3
Initial Concentration KHCRHM3
Concentration profile of high concentration Cr in kaolinite clay using water with 900 ppm
humic substances - 24 hr EK test
Figure 4-9-H-a: Results of EK test for electroremediation of chromium using water
with humic substances (900ppm).
140
141
(iv) Lead: Results are shown in Figure 4-10 – 4-12. Lead is one of the preferentially
adsorbed metals by clay minerals (Basta and Tabatabal, 1992). It is mostly in the form of
a divalent cation below pH of 9. Above pH 9, the Pbo is the stable species (Dragun,
1988). At sufficiently high pH (>11) it forms an anionic species of hydrolysis product,
Pb(OH)
6
-2
, which is expected to migrate in the opposite direction of electrokinetic flow.
Other hydrolysis products of lead which occur at pH levels greater than 6 are: Pb
2
(OH)
4
+3
,
Pb
4
(OH)
4
+4
, Pb
6
(OH)
8
+4
. These species would exhibit increased ionic velocities due to
their higher valances. The effect of high pH on the clay adsorption of metal becomes
more significant at high concentrations of the metal, as shown in Fig. 4-10. This
accumulation is attributed to: (i) precipitation and anion species formation, (ii) increased
concentration of lead at the discharge end (cathode region of soil), (iii) increased
adsorption and retention of lead on clay due to high pH and increased concentration at the
cathode region of the soil (Pamukcu et al., 1993).
Distilled water:
Concentration profile of low concentration Pb in kaolinite clay using distilled
water - 24 hr EK test
50
150
250
350
450
550
650
750
850
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C oncentration (p p m )
Final Concentration KSPbLM1
Initial Concentration KSPbLM1
Figure 4-10-L-a: Results of EK test for electroremediation of lead using distilled
water (Pamukcu et al., 1993).
142
Concentration profile of low concentration Pb in kaolinite clay using
distilled water - 24 hr EK test
50
150
250
350
450
550
650
750
850
0 0.2 0.4 0.6 0.8 1
Fractional distance from anode to cathode
Concentration (p p m )
Final Concentration KSPbLM2
Initial Concentration KSPbLM2
Figure 4-10-L-b: Results of EK test for electroremediation of lead using distilled
water (Pamukcu et al., 1993).
143
Concentration profile of low concentration Pb in kaolinite clay using
distilled water - 24 hr EK test
50
150
250
350
450
550
650
750
850
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C oncentration (p p m )
Final Concentration KSPbLM3
Initial Concentration KSPbLM3
Figure 4-10-L-c: Results of EK test for electroremediation of lead using distilled
water (Pamukcu et al., 1993).
144
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
0 0.2 0.4 0.6 0.8 1
Fractional distance from anode to cathode
C oncentration (p p m )
Final Concentration KSPbHM1
Initial Concentration KSPbHM1
Concentration profile of high concentration Pb in kaolinite clay using
distilled water - 24 hr EK test
Figure 4-10-H-a: Results of EK test for electroremediation of lead using distilled
water.
145
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
0 0.2 0.4 0.6 0.8 1
Fractional distance from anode to cathode
C oncentra tio n (p p m )
Final Concentration KSPbHM2
Initial Concentration KSPbHM2
Concentration profile of high concentration Pb in kaolinite clay using
distilled water - 24 hr EK test
Figure 4-10-H-b: Results of EK test for electroremediation of lead using distilled
water.
146
Concentration profile of high concentration Pb in kaolinite clay using
distilled water - 24 hr EK test
50
2050
4050
6050
8050
10050
12050
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C oncentratio n (p p m )
Final Concentration KSPbHM3
Initial Concentration KSPbHM3
Figure 4-10-H-c: Results of EK test for electroremediation of lead using distilled
water.
147
Ground water:
Concentration profile of low concentration Pb in kaolinite clay using ground
water - 24 hr EK test
0
50
100
150
200
250
300
350
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C on centration (p p m )
Final Concentration KGPbLM1
Initial Concentration KGPbLM1
Figure 4-11-L-a: Results of EK test for electroremediation of lead using ground
water (Pamukcu et al., 1993). (See Table 4-1 for composition)
148
Concentration profile of low concentration Pb in kaolinite clay using
ground water - 24 hr EK test
0
50
100
150
200
250
300
350
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n c en tratio n (p p m )
Final Concentration KGPbLM2
Initial Concentration KGPbLM2
Figure 4-11-L-b: Results of EK test for electroremediation of lead using ground
water (Pamukcu et al., 1993). (See Table 4-1 for composition)
149
Concentration profile of low concentration Pb in kaolinite clay using
ground water - 24 hr EK test
0
50
100
150
200
250
300
350
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n c en tratio n (p p m )
Final Concentration KGPbLM3
Initial Concentration KGPbLM3
Figure 4-11-L-c: Results of EK test for electroremediation of lead using ground
water (Pamukcu et al., 1993). (See Table 4-1 for composition)
150
Water with humic substances (900ppm):
Concentration profile of low concentration Pb in kaolinite clay using water with humic
substances (900 ppm) - 24 hr EK test
50
150
250
350
450
550
650
750
850
950
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tratio n (p p m )
Final Concentration KHPbLM1
Initial Concentration KHPbLM1
Figure 4-12-L-a: Results of EK test for electroremediation of lead using water with
humic substances (900ppm) (Pamukcu et al., 1993).
151
Concentration profile of low concentration Pb in kaolinite clay using water with humic
substances (900 ppm) - 24 hr EK test
50
150
250
350
450
550
650
750
850
950
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C onc e ntra tion (p p m )
Final Concentration KHPbLM2
Initial Concentration KHPbLM2
Figure 4-12-L-b: Results of EK test for electroremediation of lead using water with
humic substances (900ppm) (Pamukcu et al., 1993).
152
Concentration profile of low concentration Pb in kaolinite clay using water with humic
substances (900 ppm) - 24 hr EK test
50
150
250
350
450
550
650
750
850
950
0 0.2 0.4 0.6 0.8 1
Fractional distance from anode to cathode
C o nc e n tra tion (p p m )
Final Concentration KHPbLM3
Initial Concentration KHPbLM3
Figure 4-12-L-c: Results of EK test for electroremediation of lead using water with
humic substances (900ppm) (Pamukcu et al., 1993).
153
0
1000
2000
3000
4000
5000
6000
7000
8000
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C on centratio n (p p m )
Final Concentration KHPbHM1
Initial Concentration KHPbHM1
Concentration profile of high concentration Pb in kaolinite clay using water with
humic substances (900 ppm) - 24 hr EK test
Figure 4-12-H-a: Results of EK test for electroremediation of lead using water with
humic substances (900ppm).
154
Concentration profile of high concentration Pb in kaolinite clay using water with
humic substances (900 ppm) - 24 hr EK test
0
1000
2000
3000
4000
5000
6000
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C onc e ntra tio n (p p m )
Final Concentration KHPbHM2
Initial Concentration KHPbHM2
Figure 4-12-H-b: Results of EK test for electroremediation of lead using water with
humic substances (900ppm).
155
Concentration profile of high concentration Pb in kaolinite clay using water with
humic substances (900 ppm) - 24 hr EK test
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
C o n cen tra tio n (p p m )
Final Concentration KHPbHM3
Initial Concentration KHPbHM3
Figure 4-15-H-c: Results of EK test for electroremediation of lead using water with
humic substances (900ppm).
156
pH Values before and after the E-K 24 hour test:
pH throughout core length from anode to cathode at KSASLM
1
2
3
4
5
6
7
8
9
10
11
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
p H
KSASLM1
KSASLM2
KSASLM3
pH of slurry
Figure 4-16-L: pH values before and after EK test for electroremediation of arsenic
using distilled water (Pamukcu et al., 1993).
157
pH throughout core length from anode to cathode at KGASLM
1
2
3
4
5
6
7
8
9
10
11
0 0.1 0.20.30.40.5 0.60.7 0.8 0.9
Fractional distance from anode to cathode
1
p H
KGASLM1
KGASLM2
KGASLM3
pH of slurry
Figure 4-17-L: pH values before and after EK test for electroremediation of arsenic
using ground water (Pamukcu et al., 1993). (See Table 4-1 for composition).
158
pH throughout core length from anode to cathode at KHASLM
1
3
5
7
9
11
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
p H
KHASLM1
KHASLM2
KHASLM3
pH of slurry
Figure 4-18-L: pH values before and after EK test for electroremediation of arsenic
using water with humic substances (900ppm) (Pamukcu et al., 1993).
159
pH throughout core length from anode to cathode at KSCDLM
0
1
2
3
4
5
6
7
8
9
10
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
pH
KSCDLM1
KSCDLM2
KSCDLM3
pH of slurry
Figure 4-19-L: pH values before and after EK test for electroremediation of
cadmium using distilled water (Pamukcu et al., 1993).
160
pH throughout core length from anode to cathode for KGCDLM
0
1
2
3
4
5
6
7
8
9
10
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
p H
KGCDLM2
KGCDLM3
pH of slurry
Figure 4-20-L: Results of pH before and after EK test for electroremediation of
cadmium using ground water (Pamukcu et al., 1993). (See Table 2-1 for
composition).
161
pH throughout core length from anode to cathode at KHCDLM
0
2
4
6
8
10
12
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
p H
KHCDLM1
KHCDLM2
KHCDLM3
pH of slurry
Figure 4-21-L: pH values before and after EK test for electroremediation of
cadmium using water with humic substances (900ppm) (Pamukcu et al., 1993).
162
pH throughout core length from anode to cathode at KSCRLM
0
1
2
3
4
5
6
7
0 0.10.2 0.30.40.5 0.60.7 0.80.9
Fractional distance from anode to cathode
1
p H
KSCRLM1
KSCRLM2
KSCRLM3
pH of slurry
Figure 4-22-L: pH values before and after EK test for electroremediation of
chromium using distilled water (Pamukcu et al., 1993).
163
pH throughout core length from anode to cathode at KSCRHM
0
1
2
3
4
5
6
7
8
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
pH
KSCRHM1
KSCRHM2
KSCRHM3
pH of slurry
Figure 4-22-H: pH values before and after EK test for electroremediation of
chromium using distilled water.
164
pH throughout core length from anode to cathode at KGCRLM
0
2
4
6
8
10
12
14
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
p H
KGCRLM1
KGCRLM2
KGCRLM3
pH of slurry
Figure 4-23-L: pH values before and after EK test for electroremediation of
chromium using ground water (Pamukcu et al., 1993). (See Table 2-1 for
composition)
165
pH throughout core length from anode to cathode at KHCRLM
0
1
2
3
4
5
6
7
8
9
10
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
p H
KHCRLM3
pH of slurry
Figure 4-24-L: pH values before and after EK test for electroremediation of
chromium using water with humic substances (900ppm) (Pamukcu et al., 1993).
166
pH throughout core length from anode to cathode at KHCRHM
0
1
2
3
4
5
6
7
8
9
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
pH
KHCRHM1
pH of slurry
KHCRHM2
KHCRHM3
Figure 4-24-H: pH values before and after EK test for electroremediation of
chromium using water with humic substances (900ppm).
167
pH throughout core length from anode to cathode at KSPbLM
1
2
3
4
5
6
7
8
9
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
p H
KSPbLM1
pH of slurry
KSPbLM2
KSPbLM3
Figure 4-25-L: pH values before and after EK test for electroremediation of lead
using distilled water (Pamukcu et al., 1993).
168
pH throughout core length from anode to cathode at KSPBHM
0
1
2
3
4
5
6
7
8
9
10
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
pH
KSPBHM1
pH of slurry
KSPBHM2
KSPBHM3
Figure 4-25-H: pH values before and after EK test for electroremediation of lead
using distilled water.
169
pH throughout core length from anode to cathode at KGPbLM
1
2
3
4
5
6
7
8
9
10
0 0.10.20.3 0.40.50.60.7 0.80.9 1
Fractional distance from anode to cathode
p H
KGPbLM1
pH of slurry
KGPbLM2
KGPbLM3
Figure 4-26-L: pH values before and after EK test for electroremediation of lead
using ground water (Pamukcu et al., 1993). (See Table 2-1 for composition).
170
pH throughout core length from anode to cathode at KHPbLM
1
2
3
4
5
6
7
8
9
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
p H
KHPbLM1
pH of slurry
KHPbLM2
KHPbLM3
Figure 4-27-L: pH values before and after EK test for electroremediation of lead
using water with humic substances (900ppm). (Pamukcu et al., 1993).
171
pH throughout core length from anode to cathode at KHPBHM
0
1
2
3
4
5
6
7
8
9
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
pH
KHPBHM1
pH of slurry
KHPBHM2
KHPBHM3
Figure 4-27-H: pH values before and after EK test for electroremediation of lead
using water with humic substances (900ppm).
172
173
Table 4-2-L: Removal efficiency for low concentration tests recorded
at fractional ends of core (Pamukcu et al., 1993).
Removal Efficiency (%) at:
Heavy Metal Sample Anode Center Cathode
Arsenic KSASHM1 53.78 22.69 26.89
KSASHM2 27.79 15.51 57.44
KSASHM3 38.82 8.35 51.84
KGASHM1 44.87 -27.88 53.53
KGASHM2 55.26 22.01 66.27
KGASHM3 -48.00 9.67 50.67
KHASHM1 -12.42 -3.36 0.00
KHASHM2 11.19 -32.46 47.39
KHASHM3 6.56 -27.54 34.10
Cadmium KSCDHM1 95.91 86.10 -216.08
KSCDHM2 96.25 71.38 -256.22
KSCDHM3 91.73 63.37 -272.23
KGCDHM2 97.44 95.59 -409.09
KGCDHM3 98.58 97.17 -51.33
KHCDHM1 95.72 81.28 -258.58
KHCDHM2 94.85 53.40 -576.70
KHCDHM3 96.73 87.61 -241.18
Chromium KSCRHM1 38.83 88.78 93.59
KSCRHM2 58.70 12.54 92.35
KSCRHM3 64.25 56.83 93.50
KGCRHM1 13.11 58.29 92.42
KGCRHM2 52.92 35.42 96.47
KGCRHM3 57.23 46.54 95.59
KHCRHM3 N/A 58.58 93.37
Lead KSPBHM1 74.24 1.94 -77.36
KSPBHM2 64.25 18.09 53.94
KSPBHM3 68.52 29.17 -133.17
KGPBHM1 62.63 -15.88 -39.17
KGPBHM2 78.77 -11.90 2.93
KGPBHM3 82.05 -19.23 -30.77
KHPBHM1 78.89 -29.65 -152.53
KHPBHM2 64.44 20.83 -126.85
KHPBHM3 57.38 -4.46 14.36
Heavy Metal Sample Anode Center Cathode
Chromium KSCRHM1 52.00 89.61 95.08
KSCRHM2 58.70 89.97 97.85
KSCRHM3 64.25 56.83 98.81
KHCRHM1 51.78 91.12 98.06
KHCRHM2 55.18 85.13 99.14
KHCRHM3 59.45 82.24 98.93
Lead KSPBHM1 89.29 59.90 87.18
KSPBHM2 89.26 56.97 87.18
KSPBHM3 87.04 -92.63 87.18
KHPBHM1 96.36 68.68 87.18
KHPBHM2 95.72 72.74 87.471
KHPBHM3 95.93 75.53 87.18
Table 4-2-H: Removal efficiency for high concentration tests recorded
at fractional ends of core.
174
Part II
Study Area A in Abu Dhabi city, U. A. E.
Figure 4-28-a: Abu Dhabi Island – Study Area A
175
Figure 4-28-b: Al-Ruwais (Ruwais Industrial Complex) – Study Area B
176
177
Geological and Sedimentlogical Setting
The Holocene sediment province of the Arabian Gulf coast is dominated with
shallow water carbonate/evaporite facies of the Permian subsurface and consists of
seaward reefs, islands and tidal deltas protecting sheltered saline lagoons and supertidal
evaporate/carbonate flats. Holocene sediments of the United Arab Emirates (UAE) coast
accumulate on rocks of Miocene and Pleistocene age. The Miocene substrate consists of a
sequence of marls, sandstone limestone and evaporates which slope gently southward
(Al-Sharhan, A.S. and A.A.El-Sammak, 2004).
The barrier island-lagoon subsystem runs along a wide stretch of the UAE coast
from Jebel Dhana to Ras Ghanada. The physiography of the eastern part of this
subsystem is strongly affected by the presence of the Great Pearl Bank and associated
islands. The western section of this subsystem is composed of a complex of islands and
lagoons. Eastward, in the protected lagoons, carbonate muds and pellets are accumulating,
whereas to the west of Al Dhabaiya Island, only carbonate muds accumulate in a narrow
belt south of the offshore bank. Grapestones and skeletal debris are the dominant
components of the deposits (El Gawad, E. A., et al., 2008).
Occasional mangrove colonization of small areas of sand and mud flats occur.
Seaward of the algal flats and hardground is an undulating surface of carbonate sands and
muds. Locally, in the lower lying areas tidal creeks dissect this surface and incise it into
carbonate muds. Also, along tidal channels mud-cracks are common (Alsharhan, A.S.,
Kendall, C.G.St.C., 2002).
178
Abu-Dhabi Island
This area is dominated by intertidal flats, lagoons, tidal deltas, barrier islands and
coastal terraces except where local hills of Tertiary and Quaternary rocks jut out as
peninsulas. In places, the sabkha surface lies flush with eroded Quaternary rocks. The
seaward margins of the “T” shaped islands parallel the coast while their stems lie at right
angles to the dominant wind direction and separate the protected lagoons to the south
associated with narrow tidal channel and deltas.
The sediments of the sabkha area around Abu Dhabi consist of a mixture of sand
sized carbonate-evaporite minerals. Algal mats and mangroves (Avicennia marina)
dominate the intertidal zone. Flanking these salt flats are remnants of the intertidal zone
characterized by the presence of algal mats, mangroves or both of them (El Gawad, E. A.,
et al., 2008).
Study area A is dominated by carbonate mud that accumulates around mangroves,
this muddy facies is commonly densely burrowed by crabs. In addition, tidal channels
and mud-cracks are common around mangrove areas. In the lower lying areas tidal
creeks dissect this surface and incise them into narrow strips of carbonate muds parallel
to the shore at the top of the intertidal flats (Kendall, C. G., Alsharhan, A.S. and Whittle,
G.L., 1995).
179
Al-Ruwais Area:
The Ruwais area is situated on the Gulf coast 250 km west of the capital Abu
Dhabi. The port’s cargo consists primarily of fuel, crude oils and petrochemical products.
Study area B is dominated by beach rock and old shoreline. Intertidal and shallow
subtidal areas (0-2m) with exposed surfaces are dominated by micro and macro algal
species. Significant seasonal variation occurs with macroalgal die-off and loss off
biomass during the summer period with re-growth occurring during the cooler winter
season. This biological assemblage traps the wave action suspended fine sediments
present in the water column and results in an accumulation of deposited fine sediment
within this area (Kendall, C. G., Alsharhan, A.S. and Whittle, G.L., 1995).
Here, sandy shoals and coral banks are cut by tidal channels. The lagoon south of
the barrier is a continuous open body of water connected to the Arabian Gulf with
circulation that is less restricted than the lagoons to the northeast and the west (El Gawad,
E. A., et al., 2008).
180
Results
Twenty two different samples of offshore muds were collected along the coastline
from both study areas A and B. Out of the 35 heavy metals, 29 were present with varying
concentrations depending on the proximity to refineries, aluminum plants, petrochemical
plants, desalinization plants, and other industries. The salinity of those samples was in the
order of 20,000 ppm allowing a significantly high current to pass through with just 20 V
applied by a DC power supply. The voltage may be optimized in the future to improve
the removal efficiencies, while reducing both the operating cost as well as the electrode
reactions that produces the O
2
gas at anode and H
2
gas at cathode. In-as-much as basic
conditions are established at the cathode, there is precipitation of hydroxides and
carbonates, which causes cementation at the cathode region. The reactions at the
electrodes are as follows:
Anode: 2H
2
0 – 4e
-
=> O
2
+ 4H
+
Cathode: 1/2O
2
+ H
2
0 + 2e
-
=> 2OH
-
(neutral & alkaline solution)
2e
-
+ 2H
+
=> H
2
(acidic solution)
Thus, there is a need to control the acidity, during the application of DC current.
In our tested samples, the current ranged from 10 mA to 85 mA depending on the salinity
of water in each specimen. The first 75 runs were performed using distilled water with 10
ppm salinity without pH control. The final 30 runs were performed using the actual Gulf
sea water (26,000 ppm) salinity containing 450 ppm of maleic acid for pH control.
181
Heavy Metals:
Arsenic: Figures 4-28-c through 4-30 show the fraction of the arsenic found at three
locations: anode side, center and cathode end of tested core after 24 hours of
electrokinetic treatment. The initial concentrations were predetermined at the anode end
of the contaminated offshore mud sample. The removal efficiency was calculated at the
anode using equation 4-1 for all results obtained. After 24 hours, substantial reduction of
arsenic from its initial concentration at the anode region at the anode region using
distilled water with 10 ppm salinity, was found to be 34.25, 17.67, and 10.07% as shown
in Figures 4-28-c through 4-30 respectively. Electrokinetics was the main driving force
of the As ion in the direction of the water flow. There was accumulation of metal at the
discharge end (cathode end of the mud sample as can be seen in Figure 4-28-c through 4-
30, where Figure 4-30 displayed a significant level of accumulation at the cathode region.
The shape of the curve in Figure 4-30 can be explained by the lack of pH control.
(Pamukcu et al., 1993).
Arsenic: ADOMAS4, ADOMAS5, RICOMASR3 samples in Figure 4-28-c through
4-30 using Distilled water with 10 ppm salinity
Figure 4-28-c: Concentration profile of As after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
182
Figure 4-29: Concentration profile of As after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
183
184
Figure 4-30: Concentration profile of As after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
185
Barium: Figures 4-31, 4-32 and 4-33 show the fraction of the barium found at three
locations: anode side, center and cathode end of tested core after 24 hours of
electrokinetic treatment. The initial concentrations were predetermined at the anode end
of the contaminated offshore mud sample. The removal efficiency was calculated at the
anode using equation 4-1 for all results obtained. After 24 hours, substantial reduction of
barium from its initial concentration at the anode region using distilled water with 10
ppm salinity, was found to be 11.04 and 13.81% as shown in Figures 4-31 and 4-32
respectively. The migration pattern after the 24-hour period accumulated at the cathode
region. Electrokinetics was the main driving force of the Ba ion in the direction of the
water flow. There was accumulation of metal at the discharge end (cathode end of the
mud sample) as can be seen in Figure 4-35 and 4-36. The shape of the curve in Figure 4-
34 can be explained by the lack of pH control.
Figure 4-33 shows the results conducted with Abu Dhabi seawater having 26,000
ppm salinity, as well as 450 ppm of maleic acid added for pH control. The migration
pattern was similar to that of Figure 4-31, through 4-32, however, the maximum removal
efficiency of barium after 24 hours at the anode region here 36.68% as opposed to the
13.81%. This finding was interesting as it confirmed that the presense of both high
salinity and pH control mechanism influenced all the samples tested here to consistently
show higher removal efiiciencies at all the three locations analyzed. As you can see the
bell shaped curve of figure 4-32, was eliminated here due to the pH control. The high
salinity caused a higher conductivity in the bulk solution, where both the current and
electrokinetic flow increased several fold. One explanation for this is that the
electromigration force is now a dominat force allowing the ionic mobility to travel at 2-3
times faster than in the case of dominant electroosmosis, while another theory is the
abundance of large volumes of cations in this high salinity carrying their waters of
hydration further promoting ionic species velocity. This needs to be investigated further.
Barium: ADOMBA2, ADOMBA4 samples in Figure 4-31 through 4-32 using
Distilled water with 10 ppm salinity
Figure 4-31: Concentration profile of Ba after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
186
Figure 4-32: Concentration profile of Ba after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
187
Barium: Sample RICOMSWPHBA3 in Figure 4-33 using Abu Dhabi seawater with
26,000 ppm salinity and 450 ppm maleic acid
Figure 4-33: Concentration profile of Ba after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
Beryllium.
188
189
Figures 4-34 through 4-37 show the fraction of the beryllium found at three
locations: anode side, center and cathode end of tested core after 24 hours of
electrokinetic treatment. The initial concentrations were predetermined at the anode end
of the contaminated offshore mud sample. The removal efficiency was calculated at the
anode using equation 4-1 for all results obtained. After 24 hours, substantial reduction of
beryllium from its initial concentration at the anode region using distilled water with 10
ppm salinity, was found to be 8.66, 22.16 and 23.77% as shown in Figures 4-34 through
4-36 respectively. Beryllium is a cation which carries three positive charges.
Electrokinetics was the main driving force of the Be ion in the direction of the
water flow. There was accumulation of metal at the discharge end (cathode end of the
mud sample) as can be seen in Figure 4-35 and 4-36. The shape of the curve in Figure 4-
34 can be explained by the lack of pH control.
Figure 4-37 shows the results conducted with Abu Dhabi seawater having 26,000
ppm salinity, as well as 450 ppm of maleic acid added for pH control. The migration
pattern was similar to that of Figure 4-34, through 4-36, however, the maximum removal
efficiency of beryllium after 24 hours at the anode region here 27.82% as opposed to the
23.77%. This finding was interesting as it confirmed that the presense of both high
salinity and pH control mechanism influenced all the samples tested here to consistently
show higher removal efiiciencies at all the three locations analyzed. As you can see the
bell shaped curve of figure 4-34, was eliminated here due to the pH control. The high
salinity caused a higher conductivity in the bulk solution, where both the current and
electrokinetic flow increased several fold. One explanation for this is that the
electromigration force is now a dominat force allowing the ionic mobility to travel at 2-3
times faster than in the case of dominant electroosmosis, while another theory is the
abundance of large volumes of cations in this high salinity carrying their waters of
hydration further promoting ionic species velocity. This needs to be investigated further.
Beryllium: 4, 5, R3 samples in Figure 4-34 through 4-36 using Distilled water with
10 ppm salinity
Figure 4-34: Concentration profile of Be after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
190
Figure 4-35: Concentration profile of Be after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
191
Figure 4-36: Concentration profile of Be after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
192
Berellium: Sample RICOMSWPHBE2 in Figure 4-37 using Abu Dhabi seawater
with 26,000 ppm salinity and 450 ppm maleic acid
Figure 4-37: Concentration profile of Be after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
193
194
Bismuth: Figures 4-38 through 4-40 show the fraction of the bismuth found at three
locations: anode side, center and cathode end of tested core after 24 hours of
electrokinetic treatment. The initial concentrations were predetermined at the anode end
of the contaminated offshore mud sample. The removal efficiency was calculated at the
anode using equation 4-1 for all results obtained. After 24 hours, substantial reduction of
bismuth from its initial concentration at the anode region using distilled water with 10
ppm salinity, was found to be 12.75 and 40.06% as shown in Figures 4-38 through 4-39
respectively. after 24 hours. Electrokinetics was the main driving force of the Bi ion in
the direction of the water flow. There was accumulation of metal at the discharge end as
shown in both figure 4-35 and 4-36 (cathode end of the mud sample) as can be seen in
Figure 4-38 and 4-39.
Figure 4-40 shows the results conducted with Abu Dhabi seawater having 26,000
ppm salinity, as well as 450 ppm of maleic acid added for pH control. The migration
pattern was similar to that of Figure 4-38, through 4-39, however, the maximum removal
efficiency of bismuth after 24 hours at the anode region here 28.94% as opposed to the
40.06%, however consistency was achieved using the seawater and pH control, where the
lowest removal efficiency recored at the anode here was 21.93 as opposed to 12.75% as
shown in Figure 4-39. This finding was interesting as it confirmed that the presense of
both high salinity and pH control mechanism influenced all the samples tested here to
consistently show higher removal efiiciencies at all the three locations analyzed. The high
salinity caused a higher conductivity in the bulk solution, where both the current and
electrokinetic flow increased several fold. One explanation for this is that the
195
electromigration force is now a dominat force allowing the ionic mobility to travel at 2-3
times faster than in the case of dominant electroosmosis, while another theory is the
abundance of large volumes of cations in this high salinity carrying their waters of
hydration further promoting ionic species velocity. This needs to be investigated further.
Bismuth: 3, R3 samples in Figure 4-38 through 4-40 using Distilled water with 10
ppm salinity
196
Figure 4-38: Concentration profile of Bi after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-39: Concentration profile of Bi after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
197
Bismuth: Samples RICOMSWPHBI1 in Figure 4-40 using Abu Dhabi seawater with
26,000 ppm salinity and 450 ppm maleic acid
Figure 4-40: Concentration profile of Bi after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
198
199
Cadmium: Figures 4-41 through 4-44 show the fraction of cadmium found at three
locations in the tested offshore mud specimens after the 24 hours of electrokinetic
treatment. Being a divalent cationic species, cadmium exhibited a migration path toward
the cathode. The maximum cadmium accumulation was recorded at the cathode region.
This is attributed to the increase in the hydrolysis with an increased pH at the cathode end
due to the electrode reactions triggered. Until around Ph 8, Cd remains in its divalent
cationic form. Beyond this value it starts forming complex species which are either
positively, negatively charged or neutral. The tendency and the abundance of these
products control the removal rate until the acid front reaches the cathode region in the
mud. However, the with the high pH prevailing at the clay-water interface of the cathode
end of the mud, a thin layer of precipitate would form at the interface making it difficult
for cadmium to be removed out of the cathode end of the mud. There is also an increase
in mud adsorption capacity with increasing pH which would contribute to the
accumulation of the metal in this region (Sposito, 1984; Basta and Tabatai, 1992;
Pamukcu 1993). The initial concentrations were predetermined at the anode end of the
contaminated offshore mud sample. The removal efficiency was calculated at the anode
using equation 4-1 for all results obtained. After 24 hours, substantial reduction of Cd
from its initial concentration at the anode region using distilled water with 10 ppm
salinity, was found to be 31.7, 24.91, 8.74 and 12.40% as shown in Figures 4-41 through
4-44 respectively. Electrokinetics was the main driving force of the Cd ion in the
direction of the water flow. There was accumulation of metal at the discharge end
(cathode end of the mud sample) as can be seen in Figure 4-42 through 4-44. The shape
of the curve in Figures 4-42 through 4-44 can be explained by the lack of pH control.
Cadmium: 2, 3, 5, R3 samples in Figure 4-41 through 4-44 using Distilled water with
10 ppm salinity
Figure 4-41: Concentration profile of Cd after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
200
Figure 4-42: Concentration profile of Cd after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
201
Figure 4-43: Concentration profile of Cd after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
202
Figure 4-44: Concentration profile of Cd after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
203
204
Cesium: Cesium is a monovalent cation which strongly exchanges with most clays.
During the short term test, more than 16.17% was transported out of the anode region
towards the cathode chamber of the offshore mud cores after 24 hours of electrokinetic
treatment. This is illustrated in figures 4-45 similar results observed with cesium as with
strontium. The initial concentrations were predetermined at the anode end of the
contaminated offshore mud sample. The removal efficiency was calculated at the anode
using equation 4-1 for all results obtained. In the Cs case, the migration rate of the metal
appeared to be slower, perhaps due to the larger ionic atmosphere of Cs which would
promote lower electromigration velocity. Also, the affinity of the clay to Cs may have
contributed to the delayed response. Electrokinetics was the main driving force of the Cs
ion in the direction of the water flow. There was accumulation of metal at the discharge
end as shown in both figure 4-45 (cathode end of the mud sample).
A significant fraction of the cesium was removed to the cathode water chamber in
the offshore mud sample by use of the electroosmotically permeated water that included
the 26,000 ppm salinity seawater with pH control mechanism consisting of 450 ppm of
maleic acid through the anode chamber. Here a maximum removal efficiency of 31.45%
as opposed to 16.18% was achieved. This result demonstrates the high affinity of the acid
solution to cesium and its potential as an effective chelating agent to mobilize the cesium
from the offshore muds. Electrokinetics was the main driving force of the Cs ion in the
direction of the water flow. There was accumulation of metal at the discharge end
205
(cathode end of the mud sample). The shape of the curve can be explained by the lack of
pH control. (Pamukcu et al., 1993).
This finding was interesting as it confirmed that the presense of both high salinity
and pH control mechanism influenced all the samples tested here to consistently show
higher removal efiiciencies at all the three locations analyzed. The high salinity caused a
higher conductivity in the bulk solution, where both the current and electrokinetic flow
increased several fold. One explanation for this is that the electromigration force is now a
dominat force allowing the ionic mobility to travel at 2-3 times faster than in the case of
dominant electroosmosis, while another theory is the abundance of large volumes of
cations in this high salinity carrying their waters of hydration further promoting ionic
species velocity. This needs to be investigated further.
Cesium: R3 samples in Figure 4-45 using Distilled water with 10 ppm salinity
206
Figure 4-45: Concentration profile of Cs after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Cesium: Samples RICOMSWPHCS1 in Figure 4-46 using Abu Dhabi seawater with
26,000 ppm salinity and 450 ppm maleic acid
Figure 4-46: Concentration profile of Cs after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
207
208
Chromium: Figures 4-47 through 4-48 show the fraction of the Chromium found at three
locations: anode side, center and cathode end of tested core after 24 hours of
electrokinetic treatment. The initial concentrations were predetermined at the anode end
of the contaminated offshore mud sample. The removal efficiency was calculated at the
anode using equation 4-1 for all results obtained. After 24 hours, substantial reduction of
chromium from its initial concentration at the anode region at the anode region using
distilled water with 10 ppm salinity, was found to be 15.71 and 22.98% as shown in
Figures 4-47 through 4-48 respectively. Electrokinetics was the main driving force of the
Cr ion in the direction of the water flow. There was accumulation of metal at the
discharge end (cathode end of the mud sample as can be seen in Figure 4-47 through 4-
48). The shape of the curve in Figure 4-47 can be explained by the lack of pH control.
(Pamukcu et al., 1993).
Chromium: 5, R3 samples in Figure 4-47 through 4-48 using Distilled water with 10
ppm salinity
209
Figure 4-47: Concentration profile of Cr after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-48: Concentration profile of Cr after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
210
211
Copper: Copper can be present as both a monovalent and a divalent cation in its
oxidation states under normal pH conditions. Figures 4-49 through 4-52 show the fraction
of the copper found at three locations: anode side, center and cathode end of tested core
after 24 hours of electrokinetic treatment. The initial concentrations were predetermined
at the anode end of the contaminated offshore mud sample. The removal efficiency was
calculated at the anode using equation 4-1 for all results obtained. After 24 hours,
substantial reduction of beryllium from its initial concentration at the anode region using
distilled water with 10 ppm salinity was found to be 52, 15.90, 9.57 and 37.58% as
shown in Figures 4-49 through 4-52 respectively. Copper is a cation which carries two
positive charges. Electrokinetics was the main driving force of the Cu ion in the direction
of the water flow. There was accumulation of metal at the discharge end (cathode end of
the mud sample) as can be seen in Figure 4-50 and 4-51. The shape of the curve in Figure
4-51 and 4-52 can be explained by the lack of pH control.
Figure 4-53 shows the results conducted with Abu Dhabi seawater having 26,000
ppm salinity, as well as 450 ppm of maleic acid added for pH control. The migration
pattern was similar to that of Figure 4-50, however, the maximum removal efficiency of
copper after 24 hours at the anode region here 26.032% as opposed to the 15.90%. This
finding was interesting as it confirmed that the presense of both high salinity and pH
control mechanism influenced all the samples tested here to consistently show higher
removal efiiciencies at all the three locations analyzed. As you can see the bell shaped
curve of figure 4-51 and 4-52, was eliminated here due to the pH control. The high
salinity caused a higher conductivity in the bulk solution, where both the current and
212
electrokinetic flow increased several fold. One explanation for this is that the
electromigration force is now a dominat force allowing the ionic mobility to travel at 2-3
times faster than in the case of dominant electroosmosis, while another theory is the
abundance of large volumes of cations in this high salinity carrying their waters of
hydration further promoting ionic species velocity. The different valencies of this species
having different electrokinetic velocity (Higher the charge, higher the EK velocity). This
needs to be investigated further.
.
Copper: 1, 3, 5, R3 samples in Figure 4-49 through 4-52 using Distilled water with
10 ppm salinity
Figure 4-49: Concentration profile of Cu after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
213
Figure 4-50: Concentration profile of Cu after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
214
Figure 4-51: Concentration profile of Cu after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
215
Figure 4-52: Concentration profile of Cu after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
216
Copper: Sample RICOMSWPHCU2 in Figure 4-53 using Abu Dhabi seawater with
26,000 ppm salinity and 450 ppm maleic acid
Figure 4-53: Concentration profile of Cu after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
217
218
Gallium: Gallium is a cation which carries three positive charges. Figure 4-54 show the
fraction of the gallium found at three locations: anode side, center and cathode end of
tested core after 24 hours of electrokinetic treatment. The initial concentrations were
predetermined at the anode end of the contaminated offshore mud sample. The removal
efficiency was calculated at the anode using equation 4-1 for all results obtained.
Substantial reduction of bismuth from its initial concentration at the anode region was
found to be 2.83 %. after 24 hours. Although the removal efficiency was quite low, long-
term electroremediation tests would certainly increase the removal efficiency.
Electrokinetics was the main driving force of the Ga ion in the same direction of the
water flow. There was accumulation of metal at the discharge end as shown in both
Figure 4-54 (cathode end of the mud sample).The shape of the curve can be explained by
the lack of pH control.
Figure 4-55 shows the results conducted with Abu Dhabi seawater having 26,000
ppm salinity, as well as 450 ppm of maleic acid added for pH control. The maximum
removal efficiency of Ga at the anode region here 29.36% as opposed to the 2.83%. This
finding was interesting as it confirmed that the presense of both high salinity and pH
control mechanism influenced all the samples tested here to consistently show higher
removal efiiciencies at all the three locations analyzed. The high salinity caused a higher
conductivity in the bulk solution, where both the current and electrokinetic flow
increased several fold. One explanation for this is that the electromigration force is now a
dominat force allowing the ionic mobility to travel at 2-3 times faster than in the case of
dominant electroosmosis, while another theory is the abundance of large volumes of
cations in this high salinity carrying their waters of hydration further promoting ionic
species velocity. This needs to be investigated further.
Gallium: Sample ADOMGA5 in Figure 4-54 using Distilled water with 10 ppm
salinity
Figure 4-54: Concentration profile of Ga after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
219
Gallium: Sample RICOMSWPHGA2 in Figure 4-55 using Abu Dhabi seawater with
26,000 ppm salinity and 450 ppm maleic acid
Figure 4-55: Concentration profile of Ga after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
220
221
Indium: Indium is a cation which carries three positive charges. Figure 4-56 show the
fraction of the indium found at three locations: anode side, center and cathode end of
tested core after 24 hours of electrokinetic treatment. The initial concentrations were
predetermined at the anode end of the contaminated offshore mud sample. The removal
efficiency was calculated at the anode using equation 4-1 for all results obtained.
Substantial reduction of indium from its initial concentration at the anode region was
found to be 18.0% after 24 hours. Electrokinetics was the main driving force of the
indium ion in the same direction of the water flow. There was accumulation of metal at
the discharge end as shown in both Figure 4-56 (cathode end of the mud sample).The
shape of the curve can be explained by the lack of pH control.
Figure 4-57 shows the results conducted with Abu Dhabi seawater having 26,000
ppm salinity, as well as 450 ppm of maleic acid added for pH control. The maximum
removal efficiency of indium at the anode region here 38.41% as opposed to the 18%.
This finding was interesting as it confirmed that the presense of both high salinity and pH
control mechanism influenced all the samples tested here to consistently show higher
removal efiiciencies at all the three locations analyzed. The high salinity caused a higher
conductivity in the bulk solution, where both the current and electrokinetic flow
increased several fold. One explanation for this is that the electromigration force is now a
dominat force allowing the ionic mobility to travel at 2-3 times faster than in the case of
dominant electroosmosis, while another theory is the abundance of large volumes of
cations in this high salinity carrying their waters of hydration further promoting ionic
species velocity. This needs to be investigated further.
Indium: Sample RICOMINR3 in Figure 4-56 using Distilled water with 10 ppm
salinity
Figure 4-56: Concentration profile of In after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
222
Indium: Sample RICOMSWPHIN1 in Figure 4-57 using Abu Dhabi seawater with
26,000 ppm salinity and 450 ppm maleic acid
Figure 4-57: Concentration profile of In after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
223
224
Lead: Results are shown in Figure 4-58 through 4-62. Lead is one of the preferentially
adsorbed metals by clay minerals (Basta and Tabatabal, 1992). It is mostly in the form of
a divalent cation below pH of 9. Above pH 9, the PbO is the stable species (Dragun,
1988). At sufficiently high pH (>11) it forms an anionic species of hydrolysis product,
Pb(OH)
6
-2
, which is expected to migrate in the opposite direction of electrokinetic flow.
Other hydrolysis products of lead which occur at pH levels greater than 6 are: Pb
2
(OH)
4
+3
,
Pb
4
(OH)
4
+4
, Pb
6
(OH)
8
+4
. These species would exhibit increased ionic velocities due to
their higher valances. The effect of high pH on the clay adsorption of metal becomes
more significant at high concentrations of the metal, as shown in Fig. 4-62. This
accumulation is attributed to: (i) precipitation and anion species formation, (ii) increased
concentration of lead at the discharge end (cathode region of soil), (iii) increased
adsorption and retention of lead on clay due to high pH and increased concentration at the
cathode region of the soil (Pamukcu et al., 1993).
The removal efficiency was calculated at the anode using equation 4-1 for all
results obtained. Figure 4-59, demonstrated 100% removal of Pb at the anode after just 24
hours of treatment, while figure 4-58 showed only 13% removal at the same location
after 24 hours of electrotreatment. The shape of the curve on figure 4-58 and 4-62, can be
explained by the lack of pH control.
Lead: 2, 3, 4, R3, R4 samples in Figure 4-58 through 4-62 using Distilled water with
10 ppm salinity
Figure 4-58: Concentration profile of Pb after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
225
Figure 4-59: Concentration profile of Pb after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
226
Figure 4-60: Concentration profile of Pb after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
227
Figure 4-61: Concentration profile of Pb after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
228
Figure 4-62: Concentration profile of Pb after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
229
230
Lithium: Lithium exits as a monovalent ion throughout the pH range of 2 to 10. Lithium
is a cation which carries three positive charges. Figure 4-63 through 4-65 show the
fraction of the lithium found at three locations: anode side, center and cathode end of
tested core after 24 hours of electrokinetic treatment. The initial concentrations were
predetermined at the anode end of the contaminated offshore mud sample. The removal
efficiency was calculated at the anode using equation 4-1 for all results obtained.
Substantial reduction of lithium from its initial concentration at the anode region was
found to be 6.80 and 23.51% after 24 hours using the distilled water with 10 ppm salinity
as shown in Figures 4-63 and 4-64 respectively. Electrokinetics was the main driving
force of the lithium ion in the same direction of the water flow. There was accumulation
of metal at the discharge end as shown in both Figures 4-63 and 4-64 (cathode end of the
mud sample). The shape of the curve can be explained by the lack of pH control.
Figure 4-65 shows the results conducted with Abu Dhabi seawater having 26,000 ppm
salinity, as well as 450 ppm of maleic acid added for pH control. The maximum removal
efficiency of lithium at the anode region here 19.097% as opposed to the 23.51%,
however consistency was achieved using the seawater and pH control, where the lowest
removal efficiency recored at the anode here was 14.102 as opposed to 6.80% as shown
in Figure 4-65. This finding was interesting as it confirmed that the presense of both high
salinity and pH control mechanism influenced all the samples tested here to consistently
show higher removal efiiciencies at all the three locations analyzed. The high salinity
caused a higher conductivity in the bulk solution, where both the current and
231
electrokinetic flow increased several fold. One explanation for this is that the
electromigration force is now a dominat force allowing the ionic mobility to travel at 2-3
times faster than in the case of dominant electroosmosis, while another theory is the
abundance of large volumes of cations in this high salinity carrying their waters of
hydration further promoting ionic species velocity. This needs to be investigated further.
Lithium: ADOMLI5, RICOMLIR3 samples in Figure 4-63 through 4-64 using
Distilled water with 10 ppm salinity
Figure 4-63: Concentration profile of Li after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
232
Figure 4-64: Concentration profile of Li after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
233
Lithium: Sample RICOMSWPHLI2 in Figure 4-65 using Abu Dhabi seawater with
26,000 ppm salinity and 450 ppm maleic acid
Figure 4-65: Concentration profile of Li after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
234
235
Rubidium: Rubidium exits as a monovalent cationic species throughout the pH range of
2 to 10. Rubidium is a cation which carries three positive charges. Figure 4-66 through 4-
69 show the fraction of the indium found at three locations: anode side, center and
cathode end of tested core after 24 hours of electrokinetic treatment. The initial
concentrations were predetermined at the anode end of the contaminated offshore mud
sample. The removal efficiency was calculated at the anode using equation 4-1 for all
results obtained. Substantial reduction of rubidium from its initial concentration at the
anode region was found to be 10.69, 24.31 and 20.47% after 24 hours using the distilled
water with 10 ppm salinity as shown in Figures 4-66, 4-67 and 4-68 respectively.
Electrokinetics was the main driving force of the rubidium ion in the same direction of
the water flow. There was accumulation of metal at the discharge end as shown in both
Figures 4-66 and 4-68 (cathode end of the mud sample). The shape of the curve can be
explained by the lack of pH control.
Figure 4-65 shows the results conducted with Abu Dhabi seawater having 26,000
ppm salinity, as well as 450 ppm of maleic acid added for pH control. The maximum
removal efficiency of rubidium at the anode region here 29.97% as opposed to the
24.31%, as shown in Figure 4-69. This finding was interesting as it confirmed that the
presense of both high salinity and pH control mechanism influenced all the samples
tested here to consistently show higher removal efiiciencies at all the three locations
analyzed. The high salinity caused a higher conductivity in the bulk solution, where both
the current and electrokinetic flow increased several fold. One explanation for this is that
the electromigration force is now a dominat force allowing the ionic mobility to travel at
2-3 times faster than in the case of dominant electroosmosis, while another theory is the
abundance of large volumes of cations in this high salinity carrying their waters of
hydration further promoting ionic species velocity. This needs to be investigated further.
Rubidium: 2, 5, R3 samples in Figure 4-66 through 4-68 using Distilled water with
10 ppm salinity
Figure 4-66: Concentration profile of Rb after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
236
Figure 4-67: Concentration profile of Rb after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
237
Figure 4-68: Concentration profile of Rb after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
238
Rubidium: Sample RICOMSWPHRB2 in Figure 4-69 using Abu Dhabi seawater
with 26,000 ppm salinity and 450 ppm maleic acid
Figure 4-69: Concentration profile of Rb after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
239
240
Selenium: Selenium can be found in several cation forms, carrying two, four and six
positive charges. Selenium exits as a monovalent ion throughout the pH range of 2 to 10.
Selenium is a cation which carries three positive charges. Figure 4-70 through 4-75 show
the fraction of the selenium found at three locations: anode side, center and cathode end
of tested core after 24 hours of electrokinetic treatment. The initial concentrations were
predetermined at the anode end of the contaminated offshore mud sample. The removal
efficiency was calculated at the anode using equation 4-1 for all results obtained.
Substantial reduction of selenium from its initial concentration at the anode region was
found to be 41.35, 47.47, 24.24, 20.20, and 9.96% after 24 hours using the distilled water
with 10 ppm salinity as shown in Figures 4-70 through 4-74 respectively. Electrokinetics
was the main driving force of the selenium ion in the same direction of the water flow.
There was accumulation of metal at the discharge end as shown in both Figures 4-70
through 4-74 (cathode end of the mud sample). The shape of the curve in Figures 4-71, 4-
72 and 4-73 can be explained by the lack of pH control.
Figure 4-75 shows the results conducted with Abu Dhabi seawater having 26,000
ppm salinity, as well as 450 ppm of maleic acid added for pH control. The maximum
removal efficiency of selenium at the anode region here 42.85% as opposed to the
47.47%, however consistency was achieved using the seawater and pH control, where the
lowest removal efficiency recored at the anode here was 34.12% as opposed to 9.96% as
shown in Figure 4-74. This finding was interesting as it confirmed that the presense of
both high salinity and pH control mechanism influenced all the samples tested here to
241
consistently show higher removal efiiciencies at all the three locations analyzed. The high
salinity caused a higher conductivity in the bulk solution, where both the current and
electrokinetic flow increased several fold. One explanation for this is that the
electromigration force is now a dominat force allowing the ionic mobility to travel at 2-3
times faster than in the case of dominant electroosmosis, while another theory is the
abundance of large volumes of cations in this high salinity carrying their waters of
hydration further promoting ionic species velocity. This needs to be investigated further.
Selenium: ADOMSE1, ADOMSE4, RICOMSER1, RICOMSER3, RICOMSER4
samples in Figure 4-70 through 4-74 using Distilled water with 10 ppm salinity
242
Figure 4-70: Concentration profile of Se after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-71: Concentration profile of Se after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
243
Figure 4-72: Concentration profile of Se after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
244
Figure 4-73: Concentration profile of Se after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
245
246
Figure 4-74: Concentration profile of Se after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Selenium: Sample RICOMSWPHSE3 in Figure 4-75 using Abu Dhabi seawater
with 26,000 ppm salinity and 450 ppm maleic acid
Concentration profile of Se after 24‐hr EK test along sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
0.84
0.48
0.63
1.03
0.0
0.2
0.4
0.6
0.8
1.0
1.2
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fractional distance from anode to cathode
Concentration (pp m )
Final Concentration RICOMSWPHSE3
Initial Concentration RICOMSWPHSE3
Figure 4-75: Concentration profile of Se after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
247
248
Silver: Silver can be found as a monovalent cationic metal. Silver exits as a monovalent
ion throughout the pH range of 2 to 10. Silver is a cation which carries three positive
charges. Figure 4-76 through 4-80 show the fraction of the silver found at three locations:
anode side, center and cathode end of tested core after 24 hours of electrokinetic
treatment. The initial concentrations were predetermined at the anode end of the
contaminated offshore mud sample. The removal efficiency was calculated at the anode
using equation 4-1 for all results obtained. Substantial reduction of silver from its initial
concentration at the anode region was found to be 48.84, 20.77, 47.75, 40.85, and 11.88%
after 24 hours using the distilled water with 10 ppm salinity as shown in Figures 4-76
through 4-80 respectively. Electrokinetics was the main driving force of the silver ion in
the same direction of the water flow. There was accumulation of metal at the discharge
end as shown in both Figures 4-76 through 4-80 (cathode end of the mud sample). The
shape of the curve in Figures 4-77, 4-78 and 4-79 can be explained by the lack of pH
control.
Ag: 2, 3, 4, 5, R3 samples in Figure 4-76 through 4-80 using Distilled water with 10
ppm salinity
Figure 4-76: Concentration profile of Ag after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
249
Figure 4-77: Concentration profile of Ag after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
250
Figure 4-78: Concentration profile of Ag after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
251
Figure 4-79: Concentration profile of Ag after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
252
Figure 4-80: Concentration profile of Ag after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
253
254
Aluminum: Aluminum can be found as a monovalent cationic metal. Aluminum exits as
a monovalent ion throughout the pH range of 2 to 10. Aluminum is a cation which carries
three positive charges. Figure 4-81 through 4-83 show the fraction of the aluminum found
at three locations: anode side, center and cathode end of tested core after 24 hours of
electrokinetic treatment. The initial concentrations were predetermined at the anode end
of the contaminated offshore mud sample. The removal efficiency was calculated at the
anode using equation 4-1 for all results obtained. Substantial reduction of aluminum from
its initial concentration at the anode region was found to be 20.72, 32.84, and 21.72%
after 24 hours using the distilled water with 10 ppm salinity as shown in Figures 4-81
through 4-83 respectively. Electrokinetics was the main driving force of the aluminum
ion in the same direction of the water flow. There was accumulation of metal at the
discharge end as shown in both Figures 4-81 through 4-83 (cathode end of the mud
sample). The shape of the curve in Figures 4-81 and 4-82 can be explained by the lack of
pH control.
Aluminum: 4, 5, R3 samples in Figure 4-81 through 4-83 using Distilled water with
10 ppm salinity
Figure 4-81: Concentration profile of Al after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
255
Figure 4-82: Concentration profile of Al after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
256
Figure 4-83: Concentration profile of Al after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
257
258
Cobalt: Cobalt is a divalent cation which is in only oxidation state under normal pH
conditions. Below pH of 9 it does not precipitate. The neutral species of Co(OH)
2
dominates above pH 9, and anionic species (Co(OH)
3
-
, Co(OH)
4
2-
) appear at pH>11
(Pamukcu et al., 1993).
Figure 4-84 through 4-85 show the fraction of the cobalt found at three locations:
anode side, center and cathode end of tested core after 24 hours of electrokinetic
treatment. The initial concentrations were predetermined at the anode end of the
contaminated offshore mud sample. The removal efficiency was calculated at the anode
using equation 4-1 for all results obtained. Substantial reduction of cobalt from its initial
concentration at the anode region was found to be 15.90 and 34.10% after 24 hours using
the distilled water with 10 ppm salinity as shown in Figures 4-84 through 4-85
respectively. Electrokinetics was the main driving force of the cobalt ion in the same
direction of the water flow. There was accumulation of metal at the discharge end as
shown in both Figures 4-81 through 4-83 (cathode end of the mud sample). The shape of
the curve in Figures 4-81 and 4-82 can be explained by the lack of pH control.
Cobalt: 5, R3 samples in Figure 4-84 through 4-85 using Distilled water with 10 ppm
salinity
259
Figure 4-84: Concentration profile of Co after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-85: Concentration profile of Co after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
260
261
Strontium: Strontium remains as a divalent ion for a large range of pH values and is
stable to precipitation throughout the pH range of 2 to 10. The accumulation of the metal
at the cathode region is due to retardation effects of electrophoresis and relaxation as the
concentration of the cation increases at the cathode region (Kortum and Bockris, 1951).
The mechanism which triggers the accumulation is probably the increased cation
retention capacity of the clay at high pH levels (Pamukcu et al., 1993).
Figure 4-86 through 4-88 show the fraction of the strontium found at three locations:
anode side, center and cathode end of tested core after 24 hours of electrokinetic
treatment. The initial concentrations were predetermined at the anode end of the
contaminated offshore mud sample. The removal efficiency was calculated at the anode
using equation 4-1 for all results obtained. Substantial reduction of strontium from its
initial concentration at the anode region was found to be 8.44 and 2.960% after 24 hours
using the distilled water with 10 ppm salinity as shown in Figures 4-86 through 4-87
respectively. Electrokinetics was the main driving force of the strontium ion in the same
direction of the water flow. There was accumulation of metal at the discharge end as
shown in both Figure 4-86 through 4-87 (cathode end of the mud sample). The shape of
the curve in Figures 4-86 and 4-87 can be explained by the lack of pH control.
Figure 4-88 shows the results conducted with Abu Dhabi seawater having 26,000 ppm
salinity, as well as 450 ppm of maleic acid added for pH control. The maximum removal
efficiency of strontium at the anode region here 9.746% as opposed to the 8.44%, as
shown in Figure 4-88. This finding was interesting as it confirmed that the presense of
both high salinity and pH control mechanism influenced all the samples tested here to
262
consistently show higher removal efiiciencies at all the three locations analyzed. The high
salinity caused a higher conductivity in the bulk solution, where both the current and
electrokinetic flow increased several fold. One explanation for this is that the
electromigration force is now a dominat force allowing the ionic mobility to travel at 2-3
times faster than in the case of dominant electroosmosis, while another theory is the
abundance of large volumes of cations in this high salinity carrying their waters of
hydration further promoting ionic species velocity. This needs to be investigated further.
Another important factor to consider is that the sea water and formation water in the
U.A.E. are very rich in strontium. Thus, more complex strategies must be deployed to
isolate each treatment section along the coastline. In addition, maybe a long-term
electroremediation strategy will be required.
Strontium: ADOMSR3, ADOMSR4 samples in Figure 4-86 through 4-87 using
Distilled water with 10 ppm salinity
Figure 4-86: Concentration profile of Sr after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
263
Figure 4-87: Concentration profile of Sr after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
264
Strontium: Sample RICOMSWPHSR2 in Figure 4-88 using Abu Dhabi seawater
with 26,000 ppm salinity and 450 ppm maleic acid
265
729.51
876.02
808.28
700.00
800.00
900.00
1000.00
1100.00
1200.00
Concentration (ppm)
Concentration profile of Sr after 24‐hr EK test along sampl
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm m
Final Concentr
InitialConcent
Figure 4-88: Concentration profile of Sr after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
266
Titanium: Titanium exits as divalent ionic species throughout the pH range of 2 to 10.
Figure 4-89 through 4-92 show the fraction of the titanium found at three locations:
anode side, center and cathode end of tested core after 24 hours of electrokinetic
treatment. The initial concentrations were predetermined at the anode end of the
contaminated offshore mud sample. The removal efficiency was calculated at the anode
using equation 4-1 for all results obtained. Substantial reduction of titanium from its
initial concentration at the anode region was found to be 21.61, 12.22 and 19.49% after
24 hours using the distilled water with 10 ppm salinity as shown in Figures 4-89 through
4-91 respectively. Electrokinetics was the main driving force of the titanium ion in the
same direction of the water flow. There was accumulation of metal at the discharge end
as shown in both Figures 4-89 through 4-91 (cathode end of the mud sample). The shape
of the curve in Figures 4-89 and 4-90 can be explained by the lack of pH control.
Figure 4-92 shows the results conducted with Abu Dhabi seawater having 26,000 ppm
salinity, as well as 450 ppm of maleic acid added for pH control. The maximum removal
efficiency of titanium at the anode region here 25.04% as opposed to the 19.49%, as
shown in Figure 4-92. This finding was interesting as it confirmed that the presense of
both high salinity and pH control mechanism influenced all the samples tested here to
consistently show higher removal efiiciencies at all the three locations analyzed. The high
salinity caused a higher conductivity in the bulk solution, where both the current and
electrokinetic flow increased several fold. One explanation for this is that the
electromigration force is now a dominat force allowing the ionic mobility to travel at 2-3
times faster than in the case of dominant electroosmosis, while another theory is the
abundance of large volumes of cations in this high salinity carrying their waters of
hydration further promoting ionic species velocity. This needs to be investigated further.
Titanium: ADOMTI2, ADOMTI3, RICOMTIR3 samples in Figure 4-89 through
4-91 using Distilled water with 10 ppm salinity
Figure 4-89: Concentration profile of Ti after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
267
Figure 4-90: Concentration profile of Ti after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
268
Figure 4-91: Concentration profile of Ti after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
269
Titanium: Sample RICOMSWPHTI2 in Figure 4-92 using Abu Dhabi seawater with
26,000 ppm salinity and 450 ppm maleic acid
0.0384
0.0419
0.0446
0.0513
0.0000
0.0100
0.0200
0.0300
0.0400
0.0500
0.0600
0 0.10.20.30.40.5 0.60.70.80.9 1
Concentration (ppm)
Fractional distance from anode to cathode
Concentration profile of Ti after 24‐hr EK test along sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
Final Concentration RICOMSWPHTI2
Initial Concentration RICOMSWPHTI2
Figure 4-92: Concentration profile of Ti after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
270
271
Uranium: Uranium is a complex ionic species. Below pH of 6, Ur exits as a cation
species in nature. At approximately pH of 6, the UO
2
(OH)
2
.H
2
O precipitates (Brovec,
1981). At higher pHs, the anion hydroxide species such as UO
2
(OH)
3
-
and UO
2
(OH)
4
2-
occurs, which would migrate in the opposite direction of flow. This is due to
electromigration, which occurs 2 to 3 times faster than electrokinetics. These species may
never be able to travel back to the anode chamber since they encounter low pH
environment on the way and tend to change back to cationic form and, therefore, change
direction back towards the cathode again. Diffusion of the metal would then allow this
metal to precipitate at both ends of the mud sample. (Pamukcu et al., 1993).
Figure 4-93 through 4-94 show the fraction of the Ur found at three locations: anode side,
center and cathode end of tested core after 24 hours of electrokinetic treatment. The
initial concentrations were predetermined at the anode end of the contaminated offshore
mud sample. The removal efficiency was calculated at the anode using equation 4-1 for
all results obtained. Substantial reduction of uranium from its initial concentration at the
anode region was found to be 6.67 and 10.01% after 24 hours using the distilled water
with 10 ppm salinity as shown in Figures 4-93 through 4-94 respectively. Electrokinetics
was the main driving force of the uranium ion in the same direction of the water flow.
There was accumulation of metal at the discharge end as shown in both Figures 4-93
through 4-94 (cathode end of the mud sample). The wide range of removal efficiency and
the shape of the curve in Figures 4-93 through 4-94 can be attributed to:
272
(i) The different valencies of this species having different electrokinetic velocity.
(Higher the charge, higher the EK velocity).
(ii) Lack of pH control.
Uranium: ADOMUR3, RICOMURR3 samples in Figure 4-93 through 4-94 using
Distilled water with 10 ppm salinity
Figure 4-93: Concentration profile of Ur after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
273
274
Figure 4-94: Concentration profile of Ur after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
275
Vanadium: Vanadium exits as divalent, trivalent, quadravalent and pentavalent ionic
species throughout the pH range of 2 to 10. The mechanism which triggers the
accumulation has probably increased the cation retention capacity of the clay at high pH
levels.
Figure 4-95 through 4-100 show the fraction of the vanadium found at three
locations: anode side, center and cathode end of tested core after 24 hours of
electrokinetic treatment. The initial concentrations were predetermined at the anode end
of the contaminated offshore mud sample. The removal efficiency was calculated at the
anode using equation 4-1 for all results obtained. Substantial reduction of vanadium from
its initial concentration at the anode region was found to be 13.73, 14.48, 5.59, 23.86 and
19.18% after 24 hours using the distilled water with 10 ppm salinity as shown in Figures
4-95 through 4-99 respectively. Electrokinetics was the main driving force of the
vanadium ion in the same direction of the water flow. There was accumulation of metal at
the discharge end as shown in both Figures 4-95 through 4-100 (cathode end of the mud
sample). The shape of the curve in Figures 4-96 and 4-98 can be explained by the lack of
pH control.
Figure 4-100 shows the results conducted with Abu Dhabi seawater having
26,000 ppm salinity, as well as 450 ppm of maleic acid added for pH control. The
maximum removal efficiency of vanadium at the anode region here 18.40% as opposed to
the 23.86%, however consistency was achieved using the seawater and pH control, where
the lowest removal efficiency recored at the anode here was 12.37% as opposed to 5.59%
as shown in Figure 4-97. This finding was interesting as it confirmed that the presense of
276
both high salinity and pH control mechanism influenced all the samples tested here to
consistently show higher removal efiiciencies at all the three locations analyzed. The high
salinity caused a higher conductivity in the bulk solution, where both the current and
electrokinetic flow increased several fold. One explanation for this is that the
electromigration force is now a dominat force allowing the ionic mobility to travel at 2-3
times faster than in the case of dominant electroosmosis, while another theory is the
abundance of large volumes of cations in this high salinity carrying their waters of
hydration further promoting ionic species velocity. This needs to be investigated further.
Vanadium: 2, 3, 4, 5, R3 samples in Figure 4-95 through 4-99 using Distilled water
with 10 ppm salinity
Figure 4-95: Concentration profile of V after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
277
Figure 4-96: Concentration profile of V after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
278
279
Figure 4-97: Concentration profile of V after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
Figure 4-98: Concentration profile of V after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
280
Figure 4-99: Concentration profile of V after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
281
Vanadium: Sample RICOMSWPHV2 in Figure 4-100 using Abu Dhabi seawater
with 26,000 ppm salinity and 450 ppm maleic acid
7.36
8.33
9.01
9.03
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Concentration (ppm)
Fractional distance from anode to cathode
Concentration profile of V after 24‐hr EK test along sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
Final Concentration RICOMSWPHV2
Initial Concentration RICOMSWPHV2
Figure 4-100: Concentration profile of V after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid)
282
283
Zinc: Zinc is amphoteric for which the divalent cation is stable below the pH of 7.7. The
neutral species (Zn(OH)
2
) predominates above pH 9.1. The anionic species, (Zn(OH)
3
-
and Zn(OH)
4
2-
) become significant after pH 11. Due to the amphoteric nature of zinc and
its tendency to form polynuclear hydrolysis species, similar removal fractions were
obtained at the anode and cathode. (Pamukcu et al., 1993).
Figure 4-101 through 4-104 show the fraction of the zinc found at three locations:
anode side, center and cathode end of tested core after 24 hours of electrokinetic
treatment. The initial concentrations were predetermined at the anode end of the
contaminated offshore mud sample. The removal efficiency was calculated at the anode
using equation 4-1 for all results obtained. Substantial reduction of zinc from its initial
concentration at the anode region was found to be 13.44, 7.40 and 44.17% after 24 hours
using the distilled water with 10 ppm salinity as shown in Figures 4-101 through 4-103
respectively. Electrokinetics was the main driving force of the zinc ion in the same
direction of the water flow. There was accumulation of metal at the discharge end as
shown in both Figures 4-101 through 4-104 (cathode end of the mud sample). The shape
of the curve in Figures 4-101 and 4-102 can be explained by the lack of pH control.
Figure 4-100 shows the results conducted with Abu Dhabi seawater having
26,000 ppm salinity, as well as 450 ppm of maleic acid added for pH control. The
maximum removal efficiency of zinc at the anode region here 53.045% as opposed to the
44.17%, however consistency was achieved using the seawater and pH control, where the
lowest removal efficiency recored at the anode here was 11.67% as opposed to 7.40% as
shown in Figure 4-102. This finding was interesting as it confirmed that the presense of
284
both high salinity and pH control mechanism influenced all the samples tested here to
consistently show higher removal efiiciencies at all the three locations analyzed. The high
salinity caused a higher conductivity in the bulk solution, where both the current and
electrokinetic flow increased several fold. One explanation for this is that the
electromigration force is now a dominat force allowing the ionic mobility to travel at 2-3
times faster than in the case of dominant electroosmosis, while another theory is the
abundance of large volumes of cations in this high salinity carrying their waters of
hydration further promoting ionic species velocity. This needs to be investigated further.
Zinc: 2, 5, R3 samples in Figure 4-101 through 4-103 using Distilled water with 10
ppm salinity
Figure 4-101: Concentration profile of Zn after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
285
Figure 4-102: Concentration profile of Zn after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
286
Figure 4-103: Concentration profile of Zn after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
287
Zinc: Sample RICOMSWPHZN3 in Figure 4-104 using Abu Dhabi seawater with
26,000 ppm salinity and 450 ppm maleic acid
288
9.63
9.81
20.50
10.00
15.00
20.00
25.00
Concentration (ppm)
Concentration profile of Zn after 24‐hr EK tes
(Abu Dhabi offshore mud, 26,000 ppm salinity
Figure 4-104: Concentration profile of Zn after 24-hr EK test a long sample length.
(Abu Dhabi offshore mud, 26,000 ppm salinity & 450 ppm maleic acid).
289
Manganese: Manganese exits as divalent and trivalent ionic species throughout the pH
range of 2 to 10.
The mechanism which triggers the accumulation is probably the increased cation
retention capacity of the clay at high pH levels. Figure 4-105 through 4-106 show the
fraction of the manganese found at three locations: anode side, center and cathode end of
tested core after 24 hours of electrokinetic treatment. The initial concentrations were
predetermined at the anode end of the contaminated offshore mud sample. The removal
efficiency was calculated at the anode using equation 4-1 for all results obtained.
Substantial reduction of manganese from its initial concentration at the anode region was
found to be 15.38 and 18.75% after 24 hours using the distilled water with 10 ppm
salinity as shown in Figures 4-105 through 4-106 respectively. Electrokinetics was the
main driving force of the manganese ion in the same direction of the water flow. There
was accumulation of metal at the discharge end as shown in both Figures 4-105 through
4-106 (cathode end of the mud sample). The shape of the curve in Figures 4-105 can be
explained by the lack of pH control.
Manganese: 5, R3 samples in Figure 4-105 through 4-106 using Distilled water with
10 ppm salinity
Figure 4-105: Concentration profile of Mn after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
290
Figure 4-106: Concentration profile of Mn after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
291
292
Nickel: Nickel exits as divalent ionic species throughout the pH range of 2 to 8, whereas,
at pH>8 both Ni(OH)
+
and Ni
2+.
are present. At pH levels higher than 9, anionic (Ni(OH)
3
-
and Ni(OH)
4
2-
) and aqueous neutral (Ni(OH)
2
) species of Ni(II) appear. At high
concentrations of Ni(II), Ni(OH)
2
precipitates. The removal trend of nickel was similar to
that of cobalt. (Pamukcu et al., 1993).
Figure 4-107 through 4-108 show the fraction of the nickel found at three
locations: anode side, center and cathode end of tested core after 24 hours of
electrokinetic treatment. The initial concentrations were predetermined at the anode end
of the contaminated offshore mud sample. The removal efficiency was calculated at the
anode using equation 4-1 for all results obtained. Substantial reduction of nickel from its
initial concentration at the anode region was found to be 18.66 and 26.56% after 24 hours
using the distilled water with 10 ppm salinity as shown in Figures 4-107 through 4-108
respectively. Electrokinetics was the main driving force of the manganese ion in the same
direction of the water flow. There was accumulation of metal at the discharge end as
shown in both Figures 4-107 through 4-108 (cathode end of the mud sample). The wide
range of removal efficiency and the shape of the curve in Figures 4-107 through 4-108
can be attributed to:
(iii) The different valencies of this species having different electrokinetic velocity.
(Higher the charge, higher the EK velocity).
(iv) Lack of pH control.
(v) The formation of the complex anionic species migrating to the anode.
Nickel: 5, R3 samples in Figure 4-107 through 4-108 using Distilled water with 10
ppm salinity
Figure 4-107: Concentration profile of Ni after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
293
Figure 4-108: Concentration profile of Ni after 24-hr EK test a long sample length
(Abu Dhabi offshore mud, distilled water 10 ppm salinity).
294
295
Figure 4-109 shows the electrokinetic flow potential, where cumulative volumetric flow
is plotted against total electron transfer as columbs. Here we see that in both distilled
water containing 10 ppm salinity and Abu Dhabi seawater (26,000 ppm salinity), the
electrokinetic flow follows a similar pattern, with the slope of the seawater curve having
1.5 times larger response. This allows one to possibly conclude that the electrokinetic
flow efficiency is in the same order of magnitude as far as short term electrokinetic test.
y = 2E‐05x
y = 3E‐05x
0
50
100
150
200
250
0 1000000 2000000 3000000 4000000 5000000 6000000 7000000 8000000
Q(cc)
C (mA*Sec)
Electrokinetic flow during 24 test using different salinity water (Q Vs.
C)
Distilled Water w/ 10 ppm salinity
Abu Dhabi seawater 26,000 ppm salinity
Linear (Distilled Water w/ 10 ppm
salinity)
Linear (Abu Dhabi seawater 26,000 ppm
salinity)
Figure 4-109: 24 – Electrokinetic flow during the 24 hour test using different salinity
water on offshore mud samples of Abu Dhabi having varying concentrations of
heavy metals.
296
297
Summary of removal efficiency (R.E.) at the anode region after
24 hours of electrokinetic treatment using distilled water
having 10 ppm salinity and no pH control
R.E. = 100 – 100 (Final C/Initial C) %
The following table is a brief selection of some contaminants and physical conditions that
may be present in drinking water. A dash (-) indicates that there is no information
available regarding possible limits.
Units are in milligrams per liter (mg/L) unless otherwise noted. Milligrams per liter are
equivalent to parts per million.
298
Table 4-3a: Removal efficiencies vs Canadlian limit, U.S. limit, WHO limit and Gulf
limit of heavy metals at anode location after 24-hr EK test using distilled water with
10 ppm salinity and no pH control.
Removal
Efficiency (%)
Canadian
Limit
US
limit
WHO
limit
Gulf
limit
Heavy Metal Sample Ci(ppm) Cf(ppm) at Anode (ppm) (ppm) (ppm) (ppm)
Silver 2 0.0075 0.00382 48.84 0.05 0.1
no
limit
3 0.0104 0.00826 20.77 0.05 0.1
no
limit
4 0.0145 0.00758 47.75 0.05 0.1
no
limit
5 0.0068 0.00404 40.85 0.05 0.1
no
limit
R3 0.0061 0.00534 11.88 0.05 0.1
no
limit
Aluminum 4 459.63 364.404 20.72 0.1
0.05 ‐
0.2
no
limit
5 265.35 178.206 32.84 0.1
0.05 ‐
0.2
no
limit
R3 645.01 504.922 21.72 0.1
0.05 ‐
0.2
no
limit
Arsenic 4 1.2847 0.84463 34.25 0.01 0.01 0.01
5 0.5097 0.41963 17.67 0.01 0.01 0.01
R3 0.4509 0.4055 10.07 0.01 0.01 0.01
Barium 2 6.3671 5.66415 11.04 1 2 0.7
4 3.0842 2.65835 13.81 1 2 0.7
Beryllium 4 0.019 0.01732 8.66 no limit 0.004
no
limit
5 0.0121 0.00941 22.16 no limit 0.004
no
limit
R3 0.0488 0.03723 23.77 no limit 0.004
no
limit
Bismuth 3 0.01 0.00601 40.06
R3 0.0064 0.00554 12.75
Cadmium 2 0.015 0.01023 31.70 0.005 0.005 0.003
3 0.0187 0.01407 24.91 0.005 0.005 0.003
5 0.0076 0.00695 8.74 0.005 0.005 0.003
R3 0.0139 0.01221 12.40 0.005 0.005 0.003
Cesium R3 0.0489 0.04096 16.18
299
Chromium 5 4.9931 3.9699 15.71 0.05 0.01 0.05
Table
4-3a
Contin
ued
R3 7.6479 6.52419 22.98 0.05 0.01 0.05
Cobalt 5 0.5237 0.44139 15.90 no limit
no
limit
no
limit
R3 3.05 2.01 34.10 no limit
no
limit
no
limit
Copper 1 7.6266 3.66092 52.00 1 1.3 2
3 2.3136 1.94573 15.90 1 1.3 2
5 0.7479 0.67636 9.57 1 1.3 2
R3 1.8923 1.1811 37.58 1 1.3 2
Iron 5 2.83 0.3 0.3
no
limit
R3 18.00 0.3 0.3
no
limit
2 95.20 0.3 0.3
no
limit
Gallium 4 0.0775 0.07535 2.83
In 5 0.0019 0.00154 18.00
Potassium R4 53.25
5 6.80
R3 23.51
4 7.84
Lithium 5 0.8654 0.80655 6.80
R3 3.6855 2.81902 23.51
Magnesium R3 18.75 50 ‐ ‐
1 35.00 50 ‐ ‐
Manganese 5 11.332 9.58931 15.38 0.05 0.03 0.4
R3 44.254 35.9567 18.75 0.05 0.03 0.4
Sodium 4 54.51 200
no
limit
no
limit
5 32.04 200
no
limit
no
limit
R4 85.90 200
no
limit
no
limit
5 18.66 200
no
limit
no
limit
R3 26.56 200
no
limit
no
limit
2 13.04 200 no no
300
limit limit
Nickel 5 10.003 8.13667 18.66 no limit
no
limit 0.02
R3 6.6189 4.86083 26.56 no limit
no
limit 0.02
Table
4-3a
Contin
ued
Lead 2 2.7922 2.42803 13.04 0.01 0 0.001
3 1.4094 0 100.00 0.01 0 0.001
4 4.0084 1.44746 63.89 0.01 0 0.001
R3 0.6698 0.46944 29.92 0.01 0 0.001
R4 0.5763 0.43352 24.78 0.01 0 0.001
Rubidium 2 0.4561 0.40741 10.69
5 0.2666 0.20181 24.31
R3 1.4572 1.15883 20.47
Selenium 1 0.175 0.10261 41.35
4 0.6285 0.33015 47.47
R1 0.4489 0.34008 24.24
R3 0.5153 0.41121 20.20
R4 0.3092 0.27843 9.96
Strontium 3 176.46 161.557 8.44 no limit
no
limit
no
limit
4 245.42 238.307 2.90 no limit
no
limit
no
limit
Titanium 2 0.0092 0.00718 21.61 no limit
no
limit
no
limit
3 0.0473 0.04154 12.22 no limit
no
limit
no
limit
R3 0.0087 0.00699 19.49 no limit
no
limit
no
limit
Uranium 3 2.5009 2.33407 6.67 0.02
no
limit 0.009
R3 0.6207 0.55859 10.01 0.02
no
limit 0.009
Vanadium 2 2.0293 1.75075 13.73 no limit
no
limit
no
limit
3 2.3883 2.04257 14.48 no limit
no
limit
no
limit
4 2.6039 2.45831 5.59 no limit
no
limit
no
limit
5 1.9565 1.48962 23.86 no limit
no
limit
no
limit
R3 5.745 4.64314 19.18 no limit
no
limit
no
limit
Zinc 2 4.3982 3.80719 13.44 5 5
no
limit
301
5 1.3308 1.23235 7.40 5 5
no
limit
R3 4.9792 2.77967 44.17 5 5
no
limit
* As per Canadian or BC Health Act Safe Drinking Water Regulation BC Reg 230/92, & Sch 120,
2001. Task force of the Canadian Council or Resource and Environment Ministers Guidelines for
Canadian Drinking Water Quality, 1996. See their website for more information.
** As per the U.S. Environmental Protection Agency Drinking Water Standards. See their website
for more information.
*** As per the WHO (1998) Guidelines for drinking water quality, 2nd edition. Geneva, World
Health Organization. See their website for more information.
^ TCU = true colour unit
^^ Individual limits for some of the individual trihalomethanes & haloacetic acids:
Trihalomethanes: bromodichloromethane (zero); bromoform (zero); dibromochloromethane (0.06
mg/L). Chloroform is regulated with this group but has no MCLG.
Haloacetic acids: dichloroacetic acid (zero); trichloroacetic acid (0.3 mg/L). Monochloroacetic
acid, bromoacetic acid, and dibromoacetic acid are regulated with this group but have no limits.
^^^ NTU = nephelometric turbidity unit. Based on conventional treatment/slow sand or diatomaceous earth
filtration/membrane filtration
302
Summary of removal efficiency (R.E.) at the anode region after
24 hours of electrokinetic treatment using Abu Dhabi
seawater having 26,000 ppm salinity and maleic acid for pH
control
Table 4-3b: Removal efficiencies vs Canadlian limit, U.S. limit, WHO limit and Gulf
limit of heavy metals at anode location after 24-hr EK test using Abu Dhabi
seawater with 26,000 ppm salinity and pH control.
using seawater with 26,000 ppm
salinity
Removal
Efficiency
(%) at:
Heavy
Metal Sample
Ci
(ppm)
Anode
Cf (ppm)
Anode Anode Center Cathode
Silver 2 0.02 0.0153 0.3123290.205088 0.159333
Aluminum 1 1569.91 1105.390505 0.29589 -0.0101 -0.05891
2 1176.02 806.006221 0.31463 0.153545 0.063857
3 1247.50 1064.159659 0.146969 -0.2437 -0.01595
Barium 1 17.48 14.834 0.151143-0.21087 -0.02056
2 8.42 6.112244 0.274047 -0.3641 0.005672
3 7.05 4.462181437 0.366799 -0.12155 0.151556
Berelium 1 0.10 0.077603 0.24669 0.012066 0.057855
2 0.06 0.042306 0.278252 0.178552 -0.09143
3 0.06 0.048850547 0.244501 -0.1597 0.06558
Bismuth 1 0.03 0.018518 0.2893550.230793 0.291772
2 0.01 0.009562 0.219301 0.225669 -2.97069
Cadmium 2 0.06 0.054842 0.1527970.018368 0.002642
3 0.07 0.058072843 0.168452 -0.13767 -0.00937
Cesium 1 0.15 0.101687 0.314514-0.00818 -0.03243
2 0.12 0.0853 0.26532 0.10792 0.049731
3 0.13 0.112243229 0.12933 -0.12939 0.021436
303
Chromium 1 15.45 12.524895 0.189572 -0.04652
Table 4-3b
Continued
--0.04095
2 11.54 9.292712 0.194436 0.078758 -0.01524
3 11.56 9.411847286 0.186115 -0.05472 0.108137
Cobalt 1 2.08 1.74735 0.161542-0.06359 -0.01128
2 2.06 1.626463 0.209952 0.123827 0.06263
Copper 2 4.92 4.065371 0.1743750.143097 0.081368
3 3.65 2.696437466 0.26032 0.178504 0.17169
Gallium 1 1.37 1.021954 0.255372 -0.13709 -0.03392
2 0.73 0.516297 0.293597 -0.13508 0.006406
3 0.74 0.555350912 0.248343 -0.16689 0.071563
Indium 1 0.005 0.003068 0.384183 0.228623 0.215978
2 0.002 0.00175 0.164678 0.155609 0.100716
3 0.002 0.001930208 0.130145 -0.04665 -0.0047
Lithium 1 3.46 2.969554 0.141021-0.06007 -0.07562
3 4.027 3.257982106 0.190971 -0.10244 0.030916
Manganese 2 88.46 80.356900060.091651 -0.08695 0.020217
3 0.13 0.118433902 0.103738 -0.07249 0.033254
Nickel 1 14.67 13.149394 0.103493-0.12766 -0.13935
2 25.59 20.77246 0.188357 0.149285 0.088135
Lead 3 1.17 0.6357161 0.4562280.125249 0.340742
Rubidium 1 2.33 1.62825 0.299708 -0.01811 -0.02973
2 1.15 0.828862 0.279211 0.117078 0.041122
3 1.24 0.897687775 0.27877 0.000135 0.168975
Selenium 2 1.04 0.685253 0.3412350.356514 0.382645
3 0.63 0.360745034 0.428473 0.252165 -0.21977
Strontium 2 808.28 729.508784 0.09746 -0.0838 -0.418
Titanium 2 0.05 0.038449 0.250434 0.183332 0.130598
3 0.05 0.03966132 0.128284 -0.0004 -0.00373
Uranium 2 2.71 2.50308 0.0770160.041859 -0.01674
Vanadium 2 9.03 7.361849 0.1843140.076917 0.00191
3 9.67 8.472572847 0.123703 0.031452 -0.12645
Zinc 1 12.77 11.280571 0.116668-0.01532 0.016889
2 9.66 8.512559 0.119164 0.046321 -0.03907
3 9.81 4.608141018 0.530452 0.521252 0.471604
304
Chapter 5: Summary and Conclusions
Recent publications demonstrate the effectiveness of electroremediation of soils
and sludges. Although electrokinetic purging was not successful in all cases, the character,
number, scope, and results of conducted research demonstrate that it can be
recommended as a convenient and cost-effective cleaning technology in offshore muds.
The results of modeling and laboratory experiments have identified the causes of
incomplete removal of contaminants to allow for the development of procedures for
achieving a high degree of decontamination. Assessing the possible extent of
electrotreatment, one needs to consider carefully the wide range of related constraints that
can considerably reduce the expected effect of this remediation.
Necessary information regarding these constraints must be obtained during the
pilot study. Analysis of the published literature shows that considerable knowledge
regarding particular aspects of electroremediation have been collected for the past couple
of decades. This information allows one to identify, analyze, and eliminate (or mitigate)
the causes of insufficient performance of electrorestoration in-situ.
It is necessary to emphasize that the best remediation results are achieved in situ
using a combination of various cleaning technologies. Only a few publications attempt to
integrate the results of various disciplines (geology, geochemistry, chemistry, physics,
etc.) into integrated study on industrial application of electrokinetics for decontamination
of metals and hydrocarbons (Chilingar et al., 1997).
305
The main role in such a study must be given to the procedures of gathering and
classifying the necessary data and procedures of decision making aimed at
identification and selection of the best combination of remediation technologies
(Chilingar et al., 1997).
The writer achieved up to 99% removal efficiencies in decontaminating
artificially contaminated kaolinite clay samples from heavy metals. Depending on the
heavy metals and ability to control pH, 2.83 to 100 % removal efficiencies were achieved
for the field-collected offshore mud samples with 20 V DC application after only 24
hours.
The experiments conducted by the writer on field-collected offshore mud samples
demonstrate that electroremediation is an efficient and promising solution. pH control
was very critical and was acheived using a solution containing organic humic substances
or maleic acids.
306
Chapter 6: Suggested Future Research Work
1 The main thrust of future research work should be concentrated on determining
the feasibility of using DC technology (EEOR) in various carbonate formations:
a) Porous and permeable limestones containing clays and those
devoid of clays.
b) Dolomized limestone (dolomitization gives rise to porosity,
of ≈ 13.1%). (Asmari Formation)
2 Modifying the experimental apparatus to include:
Adding 3 probes for measuring pH, pressure and voltage/current along the core
samples on a real time basis. Modifying the electrode chamber to increase the
surface area to avoid the accumulation of gas generated due to the reactions at the
electrodes — O
2
at the anode and H
2
at the cathode. This would allow for higher
voltage applications for testing in the laboratory while reducing the volume of gas
bubbles that cause insulation and, thus, reduce the electokinetics performance.
3 Upscaling and optimizing voltage, current and electrode configuration, including
investigating the optimum critical distance between electrodes for field
applications.
4 Solving the PDE for contaminant mass transport to include 2-D and 3-D flow for
all heavy metal species with control of pH and salinity.
307
References
Acar, Y. B., R. W. Gale, J. Hamed, and G. Putman. 1990. Transportation Research
Record,1288, pp. 23-24. Transportation Research Board, National Research Council,
Washington,D.C.
Adamson, L. G., S. A. Amba,. G. V. Chilingar, and C. M. Beeson. 1963a. Possible use of
electric current for increasing volumetric rate of flow of oil and water during primary or
secondary recovery. Chimika Chronika 28(1):1-4.
Adamson, L. G., G. V. Chilingar, and C. M. Beeson. 1963b. Some data on electrokinetic
phenomena and their possible application on petroleum production. Chimika Chronika
28(10):121-127.
Adamson, L. G., G. V. Chilingar, C. M. Beeson, and R. A. Armstrong. 1966.
Electrokinetic dcwatering, consolidation and stabilization of soils. Engineering Geology
1:291-304.
Al-Sharhan, A.S. and A.A.El-Sammak, 2004, Grain size analysis and characterization of
sedimentary environments of the United Arab Emirates coastal area, Journal of coastal
research, 20 (2), pp: 464-477.
Alsharhan, A.S., Kendall, C.G.St.C., 2002. Holocene carbonate/ evaporites of Abu Dhabi,
and their Jurassic ancient analogs. In: Barth, H.J., Boer, B.B. (Eds.), Sabkha Ecosystems.
Kluwer Academic Publishers, pp. 187–202.
Amba, S. A., G. V. Chilingar, and C. M. Beeson. 1964. Use of direct electrical current for
increasing the flow rate of reservoir fluids during petroleum recovery. Journal of
Canadian Petroleum Technology 3(1):8-14.
Amba, S. A,, G. V. Chilingar, and C. M. Beeson. 1965. Application of electrical current
for increasing the flow rate of oil and water in a porous medium. Journal of Canadian
Petroleum Technology 4(2): 81-85.
Amba, S. A,, G. V. Chilingar, and C. M. Beeson. 1965. Application of electrokinetic
phenomena in civil and petroleum engineering. Annals NewYork Academy of Sci.
118(14):585-602
Petroleum Technology 4(2):81-85.
Atlas, R. M. 1977. Stimulated petroleum biodegradation. Critical Reviews in
Microbiology
5:371-386.
308
Atlas, R. M. 1981. Microbial degradation of petroleum hydrocarbons. Microbiological
Reviews 45:180-209.
Bcar, J. 1973. Dynamics of Fluids in Porous Media, 764 pp. Elsevier, Amsterdam.
Bhandari, A., C. D. Dennis, and J. Novak. 1994. Soil washing and biotreatment of
petroleum-contaminated soils. Journal of Environmental Engineering 120(5):1151-1169.
Blacker, S., and D. Goodman. 1994. Risk-based decision making ease study: Application
at a Superfund cleanup. Environmental Science and Technology 28(11):471-477.
Briant, J. 1961. Theses: Les phenomenes electrocinetiques en milieu hydrocarbure et
l’epaissuer de la double couche. La revue de l’institut Francais du petrole et annals des
combustibles liquids. Vol. XVI, no. 6, p. 1 – 48, no. 7-8, p. 49 – 75.
Burnett, W. E., and W. W. Loo. 1994. In-situ bioremediation of gasoline in soil and
groundwater: A case history. Paper presented at the Superfund XV Conference,
Washington, D. C.
Chilingar, G. V. 1952. Possible utilization of electrophoretic phenomenon for separation
of fine sediments into grades. Journal of Sedimentary Petrology 22(1): 29-32.
Chilingar, G. V., L. G. Adamson, R. A. Armstrong, and C. M. Beeson. 1964. Soils
stabilized through electroosmosis. Southwest Builder and Contractor 145(24): 100-102.
Chilingar, G. V., L. G. Adamson, and H. H. Rieke 111. 1966. Notes on application of
electrokinetic phenomena in soil stabilization. In Proceedings of the International Clay
Conference, Jerusalem, Vol. 1, pp. 81 -89.
Chilingar, G. V., L. G. Adamson, H. H. Rieke, and R. R. Gray. 1968b. Electrochemical
treatment of shrinking soils. Engineering Geology 2(3): 197-203.
Chilingar, G. V., S. A. Amba, and C. M. Beeson. 1965. Application of electrokinetic
phenomena in civil engineering and petroleum engineering. Annals of the New York
Academy of Science 118(14): 585-602.
Chilingar, G. V., C. M. Beeson, and S. A. Amba. 1968a. Uso de corriente electrica
directa para aumentar la proportion del fluxo de fluidos en 10s yacimientos: Effecto del
tipo de arcilla sobre la produccion de flujo. Ingenieria Petrolera 5(3): 22-32.
Chilingar, G. V., K. S. Chang, J. E. Davis, H. J. Farhanghi, L. G. Adamson, and S.
Sawabini.1968c. Possible use of direct electrical current for augmenting reservoir energy
during petroleum production. Compass of Sigma Gamma Epsilon 45(4): 272-285.
309
Chilingar, G. V., A. El-Nassir, and R. G. Stevens. 1970. Effect of direct electrical current
on permeability of sandstone cores. Journal of Petroleum Technology 22(7): 830-836.
Chilingar, G. V., W.W. Loo, L.F. Khilyuk, and S. A. Katz. 1997. Electrobioremediation
of soils contaminated with hydrocarbons and metals: progress report. Energy sources,
19:129-146.
Chilingar, G. V., Buryakovsky, L.A., Eremenko, N.A., and Gorfunkel, M.V., 2005.
Geology and Geochemistry of Oil and Gas, Elsevier, 370 pp.
Cozzarelli, I. M., J. S. Herman, and M. J. Baedecker. 1995. Fate of microbial metabolites
of hydrocarbons in a coastal plain aquifer: The role of electron acceptors. Environmental
Science and Technology 29: 458-469.
El Gawad, E. A., Lotfy, M.M., Sadooni, F.N., 2008, Sedimentology and hydrocarbon
potentiality of arid Sabkha, UAE., Journal of Applied Sciences Research, 4 (9), pp:1124-
1130.
Fairless, B. 1990. Applying total quality principles to Superfund planning, Part 11:
DQOS in Superfund-A dioxin case study. In Proc. American Society of Quality Control
17
th
Annual Meeting, Enew Division Session L, Tucson, Arizona, pp. 17-21.
Halbert, P. F. 2006. Handbook of Construction Cost.
Harton, J. H., S. Hamid, E. Abi-Chedid, and G. V. Chilingar. 1967. Effect of
electrochemical treatment on selected physical properties of clayey silt. Engineering
Geology 2(3): 191-196.
Hicks, R. E., and S. Tondorf. 1994. Electrorestoration of metal contaminated soils.
Environmental Science and Technology 28(12): 2203-2210.
Hinchee, R. E., D. C. Downey, R. R. Dupont, P. K. Aggarwal, and R. Miller. 1991.
Enhancing biodegradation of petroleum hydrocarbons through soil venting. Journal of
Hazardous Materials 27: 315-325.
Hopper, D. R. 1989. Cleaning up contaminated sites. Chemical Engineering (August):
94-110.
Huesemann, M. H. 1994. Guidelines for landtreating petroleum hydrocarbon
contaminated soils. Journal Soil Contamination 3:299-318.
310
Huesemann, M. H. 1995. Predictive model for estimation of extent of petroleum
hydrocarbon biodegradation in contaminated soils. Environmental Science and
Technology 29(1): 7-18.
Katz, S. A., L. F. Khilyuk, and G. V. Chilingar. 1996. Sensitivity analysis and
multivariant modeling for formation pressure and temperature fields in inhomogeneous
media. Journal of Petroleum Science and Engineering 1695-108.
Kendall, C. G., Alsharhan, A.S. and Whittle, G.L., 1995, Holocene carbonate/evaporites
of Abu Dhabi, United Arab Emirates-Field trip guidebook, International conference on
“Quaternary deserts and climatic change,”published by the united Arab Emirates
University.
Lageman, R., W. Pool, and G. Seffings. 1989. Chem. Ind. 18575.
Lancelot, F., H. Londiche, and G. De Marsily. 1987. Experimental results on the
influence of electric fields on the migration of oil, ionic species and water in porous
media. Journal of Petroleum Science and Engineering, 4(1990): 67-74.
Langnes, G.I., Robertson, J.O., and Chilingar, G.V., 1972. Secondary Recovery and
Carbonate Reservoirs, Elsevier, 304 pp.
Leahy, J. G., and R. R. Colwell. 1990. Microbial degradation of hydrocarbons in the
environment. Microbiology Review (54): 305-315.
Lee, M. D., J. M. Thomas, R. S. Borden, P. B. Bedient, C. H. Ward, and T. J. Wilson.
1988. Biorestoration of aquifers contaminated with organic compounds. CRC Critical
Reuiews in Environmental Control 18: 29-89.
Loo, W. W. 1991. Heat enhanced bioremediation of chlorinated solvents and toluene in
soil.
Pmc. of HMCRI R & D Conf., Anaheim, Calif., pp. 133-136.
Loo, W.W. 1993. Biotreatment of chlorinated solvents in soil and groundwater utilizing
glucose as the co-substrate. Paper presented at the Hazmacon Conf., San Jose,
Calif.
Loo, W. W. 1994. Electrokinetic enhanced passive in situ bioremediation of soil and
groundwater containing gasoline, diesel and kerosene. Paper presented at the Hazmacon
Conf., San Jose, Calif.
311
Loo, W. W., I. S. Wang, and K. T. Fan. 1994. Electrokinetic enhanced bioventing of
gasoline in clayey soil: A case history. Paper presented at the Superfund XV Conference,
Washington, D. C.
Mahaffey, W. R., G. Compeau, M. Nelson, and J. Kinsella. 1991. Developing strategies
for PAH and TCE bioremediation. Wafer and Environmental Technology 3233-86.
McCarty, P. L. 1991. Engineering concepts for in situ bioremediation. Journal of
Hazardous Materials 28: l-10.
Morgan, P., and R. J. Watkinson. 1989. Hydrocarbon degradation in soils and methods
for biotreatment. Critical Reuiews in Biotechnology 8:305-333.
Nash, J. H., and R. P. Traver. 1988. Field application of pilot soil-washing system. EPA
Document EPA/68-03-3450. Office of Research and Development, US. Environmental
Protection Agency, Cincinnati, Ohio.
Nelson, M. J. K., et al. 1987. Biodegradation of TCE and involvement of an aromatic
biodegradative pathway. Applied Environmental Microbiology 5:949-954.
Nunno, T. J., J. A. Hyman, and T. H. Pheiffer. 1988. Assessment of international
technologies for Superfund applications. EPA Document EPA/540/2-88/003, 37 pp.
Office of Solid Waste and Emergency Response. U.S. Environmental Protection Agency,
Washington, D.C.
Pamukcu, S., Wittle, J.K. 1993. Electronically enhanced in-situ soil decontamination.
Pamukcu, S., Wittle, J.K. 1993. Electrokinetic treatment of contaminated soils, sludges
and lagoons. DOE Contract No. 02112406.
Pamukcu, S., Wittle, J.K. 1994. Electrokinetic removal of coal tar constituents from
contaminated soils. EPRI TR-103320, Project 2879-21.
Pamukcu, S., Weeks, A., Wittle, J.K. 1997. Electrochemical extraction and stabilization
of selected inorganic species in porous media. Journal of hazardous materials, 55, 305 –
318.
Pamukcu, S., Weeks, A., Wittle, J.K. 2004. Enhanced reduction of Cr(VI) by direct
electrical current in a contaminated clay. Environmental Science Technology, 38, 1236 –
1241.
Pamukcu, S. Personal communication 2008.
312
Pheiffer, T. H. 1990. EPA's assessment of European contaminated soil treatment
techniques.Environmental Progress 49582-587.
Pollard, S. J. T., S. E. Hmdey, and P. M. Fedorak. 1994. Bioremediation of petroleum
and creosote-contaminated soils: A review of constraints. Waste Management and
Research 12:173-194.
Pheiffer, T. H. 1990. EPA's assessment of European contaminated soil treatment
techniques.Environmental Progress 49582-587.
Probstein, R. F., P. S. Renaud, and A. P. Shapiro. 1991. Electroosmosis techniques for
removing hazardous materials from soil. US. Patent 5074986.
Raymond, R. L., J. 0 Hudson, and V. W. Jamison. 1976. Oil degradation in soil. Applied
Environmental Microbiology 31: 522-535.
Renaud, P. S., and R. F. Probstein. 1987. Electroosmotic control of hazardous waste.
PhysicoChemical Hydrodynamics 9(1/2): 345.
Shapiro, A. P., and R. F. Probstein. 1993. Removal of contaminants from saturated clay
by electroosmosis. Environmental Science Technology 27(2): 283-291.
Shapiro, A. P., P. S. Renaud, and R. F. Probstein. 1989. Preliminary studies on the
removal of chemical species from saturated porous media by electroosmosis.
PhysicoChemical Hydrodynamics 11(5/6):785.
Sims, R. S. 1990. Soil remediation techniques at uncontrolled hazardous waste sites: A
critical review. Journal of the Air Waste Management Association 40: 704-732.
Smoluchowski, von M. 1921. Handbuch der Electrizitat und des Magnetismus, 11.
Translated
by P. E. Bocque. In Engineering Research Bulletin 33:47-158.
Stinson, M. K., H. S. Skovronek, and W. D. Ellis. 1992. EPA Site demonstration of the
BioTrol soil washing process. Journal of the Air and Waste Management Association
42:96-103.
Ungcrcr, P., J. Burrus, B. Doligez, P. Y. Chenet, and F. Bessis. 1990. Basin evaluation by
integrated two-dimensional modeling of heat transfer, fluid flow, hydrocarbon generation,
and migration. Petroleum Geology Bulletin 74(3):309-335.
313
Visschcr, K., J. Brinkman, and E. R. Soczo. 1990. Biotechnology in hazardous waste
management in the Netherlands. In Biotechnology and Biodegradation: Advances in
Applied Biotechnology, Vol. 4, pp. 389-403. Gulf Publ. Co., Tx.
Wittle, J.K.; D.G. Hill, and G.V. Chilingar. SPE 114012, 2008, Direct current electrical
enhanced oil recovery in heavy-oil reservoirs to improve recovery, reduce water cut, and
reduce H
2
S production while increasing API gravity.
Wilson, J. T., 1985. Biotransformation of TCE in soil. Applied Environmental
Microbiology,
1:242-243.
314
Appendix A: Nomenclature
Nomenclature used for specimen ID:
KS: Kaolinite in distilled water
KG: Kaolinite in ground water
KH: Kaolinite in water containing 900 ppm of humic substances in solution.
As: Arsenic
Cd: Cadmium
Cr: Chromium
Pb: Lead
H: High concentration
L: Low concentration
Nomencalture for Abu Dhabi offshore mud sample IDs electroremediated for 24 hour
period:
ADOM:Abu Dhabi Offshore Mud
RICOM: Ruwais Industrial Complex Offshore Mud
L: Low Concentration
H: High Concentration
SW: Abu Dhabi seawater with 26,000ppm
PH: 450 ppm of Maleic acid for pH control
AG: Silver
AL: Aluminum
AS: Arsenic
BA: Barium
BE: Berellium
BI: Bismuth
CD: Cadmium
CR: Chromium
CO: Cobalt
CU: Copper
CS: Cesium
315
GA: Gallium
IN: Indium
LI: Lithium
MN:Manganese
NI: Nickel
PB: Lead
RB: Rubidium
SE: Selenium
SR: Strontium
TI: Titanium
UR: Uranium
V: Vanadium
ZN:Zinc
Abstract (if available)
Abstract
The present experimental work is directed towards investigation of the electokinetically-enhanced transport of soil contaminants (specifically heavy metals) in clay media and offshore muds.
Linked assets
University of Southern California Dissertations and Theses
Conceptually similar
PDF
Electroremediation of offshore muds contaminated with heavy metals
PDF
Control of displacement fronts in porous media by flow rate partitioning
PDF
An environmentally sustainable development of ultrasound-assisted chemical process: the use of Fenton's reagent and ultrasonic transducers to remove methyl tertiary butyl ether from drinking wate...
PDF
Wear of metal-on-metal artificial discs for the lumbar spine
PDF
The feasibility studies on sonochemical processes for treating used oil: toxin reduction for eliminating recycle interference
PDF
Regeneration of used petroleum-based lubricants and biolubricants by a novel green and sustainable technology
PDF
Investigating statistical modeling approaches for reservoir characterization in waterfloods from rates fluctuations
PDF
Locating and quantifying sources of air pollution by nonparametric trajectory analysis
PDF
The effects of gravity and thermal gradient on the drying processes in porous media
PDF
Accurate and efficient uncertainty quantification of subsurface fluid flow via the probabilistic collocation method
PDF
Molecular modeling of silicon carbide nanoporous membranes and transport and adsorption of gaseous mixtures therein
PDF
Superoxide radical and UV irradiation in ultrasound assisted oxidative desulfurization (UAOD): a potential alternative for green fuels
PDF
Identifying and quantifying the impact of air pollution source areas by nonparametric trajectory analysis
PDF
Toxicological characteristics of particulate matter in an urban environment and their linkage to the source-specific constituents
PDF
A study of the application of membrane-based reactive separation to the carbon dioxide methanation
PDF
Analysis of the existence of long range internal stresses in deformed metals
PDF
Complex pattern search in sequential data
PDF
Preparation of polyetherimide nanoparticles by electrospray drying, and their use in the preparation of mixed-matrix carbon molecular-sieve (CMS) membranes
PDF
Vibration of nearby structures induced by high-speed rail transit
PDF
Continuum and pore netwok modeling of preparation of silicon-carbide membranes by chemical-vapor deposition and chemical-vapor infiltration
Asset Metadata
Creator
Haroun, Muhammad
(author)
Core Title
Feasibility of in-situ removal of heavy metals by electroremediation of offshore muds
School
Viterbi School of Engineering
Degree
Doctor of Philosophy
Degree Program
Environmental Engineering
Publication Date
08/09/2009
Defense Date
06/22/2009
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
Abu Dhabi,decontamination,electrokientics,electroremediation,heavy metals,in-situ,in-situ decontamination,in-situ electroremediation,OAI-PMH Harvest,offshore,offshore muds
Place Name
Abu Dhabi
(city or populated place)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Chilingar, George (
committee chair
), Meshkati, Najmedin (
committee chair
), Ershaghi, Iraj (
committee member
), Pamukcu, Sibel (
committee member
)
Creator Email
haroun.muhammad@gmail.com,haroun@usc.edu
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-m2558
Unique identifier
UC1449834
Identifier
etd-Haroun-3123 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-265684 (legacy record id),usctheses-m2558 (legacy record id)
Legacy Identifier
etd-Haroun-3123.pdf
Dmrecord
265684
Document Type
Dissertation
Rights
Haroun, Muhammad
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Repository Name
Libraries, University of Southern California
Repository Location
Los Angeles, California
Repository Email
cisadmin@lib.usc.edu
Tags
decontamination
electrokientics
electroremediation
heavy metals
in-situ
in-situ decontamination
in-situ electroremediation
offshore
offshore muds