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Development of New Binding Phases for
Speciation Measurements of Trace Metals
with the Diffusive Gradients in Thin Films
Technique
A thesis submitted in fulfilment of the requirements for the
Degree of Doctor of Philosophy
By
WEIJIA LI
School of Environmental and Applied Sciences
Faculty of Environmental Sciences
Griffith University
Australia
March 2004
CERTIFICATE OF ORIGINALITY
I hereby declare that this submission is my own work and to the best of my knowledge it
contains no materials previously published or written by another person, nor material
which to a substantial extent has been accepted for the award of any other degree or
diploma at Griffith University or any other educational institution, except where due
acknowledgement is made in the thesis. Any contribution made to the research by others,
with whom I have worked at Griffith University or elsewhere, is explicitly acknowledged
in the thesis.
I also declare that the intellectual content of this thesis is the product of my own work,
except to the extent that assistance from others in the project’s design and conception or in
style, presentation and linguistic expression is acknowledged.
(signed)……………………….
i
ACKNOWLEDGEMENTS
I wish to take this special opportunity to thank my supervisors, Dr. Huijun Zhao, Dr. Peter
Teasdale and Dr. Richard John, for their support, patience and assistance through out the
course of my period as a Ph.D. student. Thanks for invaluable ideas and guidance from
Dr. Huijun Zhao.
I wish to express my gratitude to School of Environmental and Applied Sciences, Griffith
University, Australia for providing me with scholarship to undertake this project.
Many thanks must also be given to head of the school, Clyde Wild, for his support; school
secretary, Carmel Wild, for her English corrections of my thesis, and many other staff
members in the School of Environmental and Applied Sciences for their help.
I also thank to my research group, especially, Dr. Shangqing Zhang, Mr. Dianlu Jiang, Mr.
Calvin Gladman, Miss Kylie Catterall, and Miss Kristy Morris, who have helped me in
various ways.
Thanks to staff members in the Chemistry Department, School of Molecular &
Microbiological Sciences, University of Queensland for their help and assistance.
I am deeply grateful my mother and father for their support and encouragement during the
course of this study.
Finally, I wish to thank my wife, Yali Qu, and my daughter, Mandy Li, for their great
understanding, patience and assistance at any time.
ii
LIST OF PUBLICATIONS [1-7]
[1] Li, W.; Teasdale, P. R.; Zhang, S.; John, R.; Zhao, H. Application of a Poly(4-
styrenesulfonate) Liquid Binding Layer for Measurement of Cu2+ and Cd2+ with
the Diffusive Gradients in Thin-Films Technique, Analytical Chemistry, 2003, 75,
2578-2583.
[2] Li, W.; Zhao, H.; Teasdale, P. R.; John, R.; Zhang, S. Synthesis and
characterisation of a polyacrylamide-polyacrylic acid copolymer hydrogel for
environmental analysis of Cu and Cd, Reactive and Functional Polymers, 2002,
52, 31-41.
[3] Li, W.; Zhao, H.; Teasdale, P. R.; John, R. Preparation and characterization of a
poly(acrylamidoglycolic acid-co-acrylamide) hydrogel for selective binding of
Cu2+ and application to diffusive gradients in thin films measurements, Polymer,
2002, 43, 4803-4809.
[4] Li, W.; Zhao, H.; Teasdale, P. R.; John, R.; Zhang, S. Application of a cellulose
phosphate ion exchange membrane as a binding phase in the diffusive gradients in
thin films technique for measurement of trace metals, Analytica Chimica Acta,
2002, 464, 331-339.
[5] Li, W.; Zhao, H.; Teasdale, P. R.; John, R. Application of new solid membrane
diffusive layer/liquid binding phase DGT technique for environmental speciation,
Environ. Sci. Technol., 2003, Submitted.
[6] Li, W.; Zhao, H.; Teasdale, P. R.; John, R. Development of a new generation DGT
technique using a solid membrane diffusive layer with a liquid binding phase,
Analytica Chimica Acta, 2003, Submitted.
iii
[7] Li, W.; Zhao, H.; Teasdale, P. R.; John, R. Evaluation of new binding phases
developed for use in diffusive gradients in thin films technique, Environ. Sci.
Technol., 2003, Submitted.
iv
Table of Contents
Certification………………………………………………………………………………...i
Acknowledgement………………………………………………………………………….ii
List of Publications………………………………………………………………………..iii
Table of Contents…………………………………………………………………………..v
Nomenclature……………………………………………...……………………………….x
Abstract…………………………………………………………………………………...xii
CHAPTER 1 General Introduction .............................................................................1
1.1. SIGNIFICANCE OF THIS RESEARCH...............................................................2
1.2. THE SPECIATION OF TRACE METALS IN NATURAL WATERS .................6
1.3. THE NEED FOR SPECIATION MEASUREMENTS OF TRACE METALS .....9
1.3.1. The Free-ion Activity Model ..........................................................................11
1.3.2. The Biotic Ligand Model................................................................................13
1.4. ISSUES TO CONSIDER WHEN SAMPLING AND MEASURING TRACE
METAL SPECIES ..........................................................................................................16
1.4.1. Sampling Factors ...........................................................................................16
1.4.2. Measurement Factors .....................................................................................18
1.5. TECHNIQUES USED FOR IN SITU MEASUREMENT AND SPECIATION OF
TRACE METALS ..........................................................................................................21
1.5.1. Diffusive Gradients in Thin Films (DGT) .....................................................23
1.6. OBJECTIVES OF THIS STUDY.........................................................................39
CHAPTER 2 Experimental and Methodology............................................................43
2.1. INTRODUCTION ..............................................................................................44
2.2. REAGENTS AND SOLUTIONS.......................................................................44
2.2.1. Chemicals and Materials.............................................................................44
2.2.2. Solutions .....................................................................................................45
2.3. PROCEDURES ..................................................................................................48
2.3.1. Preparation of Diffusive Gel.......................................................................48
2.3.2. Preparation of Chelex 100 Binding Gel......................................................49
2.3.3. Characterisation of the Structure and Composition of Binding Hydrogels 50
2.3.4. Assembling and Disassembling the Gel Based DGT Devices ...................50
2.3.5. Measurement of Diffusion Coefficient in Diffusive Layer ........................51
v
2.4. INSTRUMENTATION ......................................................................................53
2.4.1. Atomic Absorption Spectroscopy (AAS) ...................................................53
2.4.2. Measurement of Metal Concentrations in a Solution Containing PSS .......54
2.4.3. Solution pH Measurement ..........................................................................54
2.4.4. Solution Salinity Measurement...................................................................54
CHAPTER 3 Synthesis and Characterisation of a Poly(acrylamide-co-acrylic acid)
Copolymer Hydrogel Based Binding Phase for the Diffusive Gradients in Thin Films
(DGT) Technique
............................…………………………………………………………………………55
3.1 INTRODUCTION ..............................................................................................56
3.2 EXPERIMENTAL..............................................................................................59
3.2.1 Preparation of the Poly(acrylamide-co-acrylic acid) Copolymer Hydrogel
59
3.2.2 Characterisation of the Structure and Composition of the PAM-PAA
Hydrogels....................................................................................................................59
3.2.3 Swelling Properties of the PAM-PAA Hydrogel........................................60
3.2.4 Metal Binding Properties of the PAM-PAA Hydrogel...............................60
3.2.5 Elution and Analysis of the Metal Ions ......................................................61
3.2.6 Validation of the PAM-PAA Hydrogel for Use with DGT ........................62
3.3 RESULTS AND DISCUSSION .........................................................................62
3.3.1 Preparation of the Poly(acrylamide-co-acrylic acid) Copolymer Hydrogel ...
....................................................................................................................62
3.3.2 Composition of the PAM-PAA Copolymer Hydrogel ...............................63
3.3.3 PAM-PAA Hydrogel Swelling Properties ..................................................66
3.3.4 Metal Binding Properties of the PAM-PAA Hydrogel...............................69
3.3.5 Application of the PAM-PAA Hydrogel as a Binding Phase with DGT....74
3.4 CONCLUSIONS ................................................................................................76
CHAPTER 4 Preparation and Characterisation of a Poly(acrylamidoglycolic acid-
co-acrylamide) Hydrogel as a New DGT Binding Phase for Determination of Trace
Metals .................................................................................................................................78
4.1. INTRODUCTION ..............................................................................................79
4.2. EXPERIMENTAL..............................................................................................79
4.2.1. Preparation of Poly(acrylamidoglycolic acid-co-acrylamide) Hydrogel....79
4.2.2. Characterisation of the PAAG-PAM Hydrogel ..........................................80
4.2.3. Swelling Properties of the PAAG-PAM Hydrogel.....................................81
vi
4.2.4. Metal Binding Properties of the PAAG-PAM Hydrogel............................81
4.2.5. DGT Performance .......................................................................................82
4.2.6. Preparation of Polyacrylamide Hydrogel ...................................................83
4.3. RESULTS AND DISCUSSION .........................................................................83
4.3.1. Structure and Composition of the PAAG-PAM Hydrogel .........................83
4.3.2. Swelling Properties of the PAAG-PAM Gel ..............................................85
4.3.3. Metal Binding Properties of the PAAG-PAM Hydrogel............................87
4.3.4. Validation of Poly(AAGA-co AAm) as a Binding Phase for DGT Use ....91
4.4. CONCLUSIONS ................................................................................................93
CHAPTER 5 Application of a Cellulose Phosphate Ion Exchange Membrane as a
Binding Phase in the Diffusive Gradients in Thin Films Technique............................94
5.1. INTRODUCTION ..............................................................................................95
5.2. EXPERIMENTAL..............................................................................................96
5.2.1. Cellulose Phosphate Membrane Pre-treatment...........................................96
5.2.2. Preparation of the Polyacrylamide Hydrogel..............................................96
5.2.3. Binding of Metal Ions to Cellulose Phosphate Membrane .........................97
5.2.4. Elution and Analysis of Metal Ions ............................................................97
5.2.5. Assembly of DGT Devices .........................................................................98
5.2.6. DGT Validation Experiments .....................................................................98
5.2.7. Reuse of Binding Phase ..............................................................................99
5.3. RESULTS AND DISCUSSION .........................................................................99
5.3.1. Metal Ion Binding Properties......................................................................99
5.3.2. Elution and Regeneration..........................................................................105
5.3.3. Evaluation for Use as a Binding Phase with DGT....................................106
5.4. CONCLUSIONS ..............................................................................................111
CHAPTER 6 Development of a New Generation DGT Device Using a Solid
Membrane Diffusive Layer with a Liquid Binding Phase ..........................................112
6.1. INTRODUCTION ............................................................................................113
6.2. EXPERIMENTAL............................................................................................114
6.2.1. The DGT Device Using a Solution Binding Phase...................................114
6.2.2. Preparation of the Dialysis Membrane .....................................................115
6.2.3. Interaction of Cd2+ and Cu2+ with the Cellulose Dialysis Membrane ......115
6.2.4. Purification of Poly(4-styrenesulfonate)...................................................116
6.2.5. Determination of Metal-PSS Concentrations ...........................................116
6.2.6. Optimisation of PSS Solution Concentration ...........................................116
vii
6.2.7. Metal Binding Properties of the Poly(4-styrenesulfonate) Solution.........117
6.2.8. Determination of Stability Constant .........................................................117
6.2.9. Measurement of Metal Diffusion Coefficients in the Dialysis Membrane.....
..................................................................................................................118
6.2.10. Effect of Stirring Conditions on the DBL Layer ......................................118
6.2.11. Validation of the New DGT Device .........................................................119
6.3. RESULTS AND DISCUSSION .......................................................................119
6.3.1. Dialysis Membrane Diffusive Layer.........................................................119
6.3.2. Optimization of PSS Solution Concentration ...........................................121
6.3.3. Metal Ion Binding Properties of Poly(4-styrenesulfonate).......................123
6.3.4. Diffusion of Cd2+ and Cu2+ in the Cellulose Dialysis Membrane ............130
6.3.5. Effect of Stirring Conditions on the DBL Layer ......................................133
6.3.6. Validation of the PSS/dialysis DGT Device.............................................139
6.4. CONCLUSIONS ..............................................................................................142
CHAPTER 7 ........ Characterisation of the Dialysis Membrane/PSS DGT Device for
Trace Metal Speciation Measurements.........................................................................143
7.1. INTRODUCTION ............................................................................................144
7.2. EXPERIMENTAL............................................................................................147
7.2.1. Measurement of Diffusion Coefficients of EDTA-Metal Complexes......147
7.2.2. Measurement of DGT-labile Fractions .....................................................147
7.2.3. Theoretical Calculation of Free Cu and Cd Fractions ..............................148
7.2.4. Field Deployments of PSS DGT Devices.................................................149
7.2.5. Measurement of PSS DGT-labile and 0.45-filtered Cu and Cd
Concentrations ..……………………………………………………………………152
7.3. RESULTS AND DISCUSSION .......................................................................153
7.3.1. Diffusion of EDTA-Cu and EDTA-Cd in the Dialysis Membrane Diffusive
Layer …………………………………………………………………………..153
7.3.2. Measurement of Labile Metal Ions in the Presence of Ligands ...............155
7.3.3. Field Deployments ....................................................................................166
7.4. CONCLUSIONS ..............................................................................................170
CHAPTER 8 Evaluation of the New Binding Phases Developed for Use in the
Diffusive Gradients in Thin Films Technique ..............................................................171
8.1. INTRODUCTION ............................................................................................172
8.2. EXPERIMENTAL............................................................................................172
8.2.1. Diffusion Layer Preparation .....................................................................172
viii
8.2.2. Binding Phase Preparation........................................................................172
8.2.3. DGT Measurements in Laboratory ...........................................................173
8.2.4. DGT Field Deployment ............................................................................174
8.3. RESULTS AND DISCUSSION .......................................................................175
8.3.1. Measurement of DGT Labile Metal Ions in the Presence of Ligands ......175
8.3.2. Field Deployments ....................................................................................181
8.4. COMPARISON OF IMPORTANT PROPERTIES OF THE NEW BINDING
PHASES DEVELOPED IN THIS STUDY..................................................................190
8.4.1. Assembly of DGT Devices and the Interface between the Binding and
Diffusive Layers .......................................................................................................191
8.4.2. Swelling Effects ........................................................................................193
8.4.3. Biofouling Effects.....................................................................................194
8.4.4. Reusability ................................................................................................195
8.4.5. Elution.......................................................................................................196
8.4.6. Valid Deployment Conditions and Metal Binding Properties ..................196
8.5. CONCLUSIONS ..............................................................................................198
CHAPTER 9 General Conclusions ............................................................................200
REFERENCES…………………………………………………………………………..207
ix
NOMENCLATURE
A diffusive area
AAGA acrylamidoglycolic acid monohydrate
AAm acrylamide
AAS atomic absorption spectroscopy
ASV anodic stripping voltammetry
C the concentration in sample solution
C' solute concentrations at the interface of membrane and binding
solution
Cb solute concentrations in the bulk solution
Cm solute concentrations at the interface of membrane and the DBL
Ce concentrations of ions in the elution
CMF concentration of free metal
CM’ concentration of free metal dissociated from metal complexes
CML concentration of metal complex
D diffusion coefficient
Di diffusion coefficient of ion i
Dm diffusion coefficient in dialysis membrane
DMF diffusion coefficient of free metal
DML diffusion coefficient of metal complex
DBL diffusive boundary layer
DBS dodecylbenzenesulfonic acid, sodium salt
DET diffusive equilibration in thin films
DGT diffusive gradients in thin films
DOC dissolved organic carbon
EDTA ethylenediaminetetraacetic acid, disodium salt dihydrate
F flux
FTIR Fourier transform infrared spectroscopy
GL glucose
HA humic acid
ICP-MS inductively coupled plasma-mass spectrometry
IDA iminodiacetic acid
ISE ion selective electrode
K stability constant
x
m
m
k-1 metal complex dissociation reaction rate constant
M mass measured in binding phase
d the weights of the hydrogel disks in dried state
s the weights of the hydrogel disks in the swollen/hydrated state
PAAG-PAM poly(acrylamidoglycolic acid-co-acrylamide) hydrogel
PAM polyacrylamide gel
PAM-PAA poly(acrylamide-co-acrylic acid)
PIXE proton induced x-ray emissions
PSS poly(4-styrenesulfonate)
qw swelling ratio, defined as qw = ms / md
Sc schmidt number
t time of deployment
td time for transport of metal complex
TA tannic acid
TEMED tetramethylethylenediamine
Vb volume of PSS solution
Ve volume of HNO3 solution for elution
Vs volume of sample solution
P81 cellulose phosphate membrane
x the distance from the leading edge of the plate
Zi charge of ion i
∆g thickness of the diffusive gel
δ thickness of the boundary layer
σ fluid density
η dynamic viscosity
β ratio between free metal concentration and total metal concentration
τ time for dissociation of metal complex
xi
ABSTRACT
The recently developed technique of diffusive gradients in thin films (DGT) for speciation
measurement of analytes in the environment was further developed through the
development of series of new binding phases including poly(acrylamide-co-acrylic acid)
copolymer hydrogel (PAM-PAA), poly(acrylamidoglycolic acid-co-acrylamide)
(PAAGA-PAM) hydrogel, the Whatman P81 cellulose phosphate ion exchange membrane
(P81) and a liquid binding phase of poly(4-styrenesulfonate) (PSS). A new diffusion
layer, cellulose dialysis membrane, was also employed for the liquid binding phase DGT.
PAM-PAA copolymer hydrogel was prepared by the controlled hydrolysis of
polyacrylamide (PAM) in an alkaline solution of 10% sodium hydroxide. The capacity of
the copolymer hydrogel to bind various metal ions was tested under a range of uptake
conditions. Ions such as Cu2+ and Cd2+ were bound more strongly to the copolymer
hydrogel than the competing ions such as Na+, K+, Ca2+ and Mg2+. Metals bound to the
copolymer hydrogel can be efficiently eluted in 2 M HNO3 solution (>94%). Application
of this new binding material to DGT technique was validated in a synthetic lake water
(Windermere, Lake District, UK) with a recovery of 99.0% for Cu2+.
PAAGA-PAM hydrogel was prepared by copolymerising 2-acrylamidoglycolic acid with
acrylamide. The metal ion binding properties of the hydrogel were characterised for Cu2+,
Cd2+ and competing ions under various experimental conditions. The hydrogel was shown
to bind Cu2+ and Cd2+ strongly under non-competitive binding conditions, with binding
capacities of 5.3 and 5.1 µmol cm-2, respectively. The binding capacity of each metal
decreased, under competitive binding conditions (with a range of metal ions present at
17.8 µN), to 1.3 and 0.17 µmol cm-2, respectively, indicating a strong selective binding
towards Cu2+. The metal ions were readily recovered (>94%) by eluting with 2 M HNO3.
xii
Finally, the copolymer hydrogel was tested as a binding phase with the DGT technique. A
linear mass vs. time relationship was observed for Cu2+ in Windermere water with a
recovery of close to 100%.
The use of a commercially available solid ion exchange membrane (P81) as the binding
phase in DGT analysis was demonstrated. P81 is a strong cation exchange membrane. Its
performance characteristics as a new binding phase in DGT measurement of Cu2+ and
Cd2+ were systematically investigated. Several advantages over the conventional ion
exchange resin-embedded hydrogel based binding phases used in DGT were observed.
These include: simple preparation, ease of handling, and reusability. The binding phase
preferentially binds to transition metal ions rather than competing ions. Within the
optimum pH range (pH 4.0 – 9.0), the maximum non-competitive binding capacities of the
membrane for Cu2+ and Cd2+ were 3.22 and 3.07 µmol cm-2, respectively. The suitability
of the new membrane–based binding phase for DGT applications was validated
experimentally. The results demonstrated excellent agreement with theoretically predicted
trends. The reusability of this binding phase was also investigated.
Application of a liquid binding phase and a dialysis membrane diffusive layer were
proposed for the first time. The binding phase was a 0.020 M solution of poly(4-
styrenesulfonate) (PSS) polyelectrolyte using a specially designed DGT device. The
binding properties of Cd2+, Cu2+, and a range of alkali and alkaline earth metal ions to the
PSS solution were characterised. The PSS behaved like a cation exchanger with
preferential binding to Cd2+ (6.0 µmole ml-1, log K = 9.0) and Cu2+ (2.5 µmole ml-1, log K
= 8.1) under competitive binding conditions. The DGT devices were successfully
validated for Cd2+ and Cu2+ in Windermere water.
The speciation performance of the solid and liquid binding phases developed in this study
was investigated in solutions containing ethylenediaminetetraacetic acid disodium salt
xiii
(EDTA), humic acid (HA), glucose (GL), dodecylbenzenesulfonic acid (DBS) and tannic
acid (TA) with Cu2+ and Cd2+. The ratios of labile metals over total metals were at good
agreement with calculated theoretical values using Stability Constants Database. The
results indicated that the DGT-labile concentration measured by DGT with these binding
phases is essentially free metal ion concentration in the sample.
All newly developed DGT binding phases were successfully applied for environmental
speciation. The field deployments were carried out in both freshwater and salt-water test
sites.
xiv
Chapter 1
Chapter 1 General Introduction
1
Chapter 1
1.1. SIGNIFICANCE OF THIS RESEARCH
This dissertation describes research and development of the diffusive gradients in thin
films (DGT) technique for the in situ measurement and speciation of trace metals,
particularly Cu and Cd. The speciation of trace metals is important for a number of areas
in environmental research and management, including toxicological studies and water
quality monitoring. The need to undertake in situ measurements of trace metal in natural
waters has also been increasingly recognized over the last decade 1-3. This recognition is
the result of a number of observations concerning the limitations of commonly used
approaches to trace metal measurement and speciation of natural waters. These
observations are described briefly below, and in more detail in the following review of
relevant literature. It will become apparent that the DGT technique has potential to meet
many of the needs highlighted below and therefore should be thoroughly investigated for
the purpose of in situ speciation of trace metals in waters.
(1) It is widely recognised that most waterways have compositions, including that of
the trace metal fraction, which vary over characteristic time scales 2. Marine waters
change only slowly due to their massive volume. Changes in trace metal concentrations
(usually gradual increases) have been measured in coastal waters and in enclosed seas, due
to increased anthropogenic inputs 4-7. Changes happen to trace metal concentrations much
more rapidly in estuaries and rivers than in marine waters. In estuaries and rivers trace
metal concentrations are influenced by a range of events, both anthropogenic and natural,
some of which can occur over a time scale of hours (e.g. tidal processes) 8-12. For these
more dynamic waterways, trace metal concentrations need to be measured at frequent and
regular intervals, especially when using conventional grab sampling approaches 2, 13, and
2
Chapter 1
particularly after events such as high rainfall or the release of effluent. An alternative
approach to monitoring such systems is to use devices, usually deployed in situ, that
continually accumulate trace metal analytes over a deployment period, such as the DGT
technique 14-16. A recent study has indicated that DGT measurements of trace metal
concentrations were significantly and highly correlated with measurements of composite
0.45 µm-filtered estuarine samples over the DGT deployment period 17. Although DGT
used in this way does not provide a continual measurement of the trace metal
concentration, it does give an average concentration for the entire deployment period. It
also requires much less effort and expense than an intensive collection of grab samples 17.
The DGT deployment time can be varied to investigate changes in the trace metal
concentration for a dynamic waterway over various time scales. While this aspect of DGT
measurements is not investigated specifically in this study the point is made to emphasise
the importance of developing techniques, such as DGT, which are capable of making
representative measurements of trace metals, even dynamic waterways.
(2) The difficulties of maintaining the integrity of water samples (in which trace metal
concentrations are to be measured) after collection and before analysis have also been
recognised widely. Improved sample preparation and handling approaches have now
minimised contamination and losses of trace metals before analysis 2, 18. The use of
quality control procedures have also improved the accuracy of the data obtained from the
trace measurements 1. However, while these procedures have improved total
measurements (on filtered and unfiltered water), there are still many difficulties in
carrying out speciation measurements in samples removed from a waterway. Indeed
maintaining the trace metal speciation of a water sample after collection has proven to be
very difficult 13, 19, 20. Virtually all approaches used to preserve trace metal samples will
lead to a change in the speciation. Therefore the best way to determine trace metal
3
Chapter 1
speciation is to use a number of in situ speciation techniques or to measure parameters that
can be used in speciation models. The DGT technique, while it is deployed in situ,
accumulates trace metal species that are able to pass through the diffusive layer and bind
to the binding phase. In this way DGT is able to selectively measure a range of trace
metal forms 21, 22. More importantly the trace metals are accumulated in a form that is
stable during transport and storage, and can be measured using sensitive laboratory
instrumentation after elution. This study seeks to develop a number of new DGT binding
phases that will be capable of measuring different trace metal fractions and of maintaining
the speciation between sampling and analysis.
(3) A better understanding has developed recently concerning the interpretation and
limitations of measurement techniques used to speciate trace metals. Most techniques
have attempted to fractionate or separate the various trace metals species. However, these
attempts at fractionation have been confounded by the fact that virtually all trace metals
exist in a variety of physico-chemical forms. These forms are often in dynamic
equilibrium with one another and they span continuums of both size and reactivity 1, 13.
Therefore most so-called speciation methods, rather than attempting to fractionate
perfectly between particular forms of trace metal species, should instead be reproducible
with respect to the species that they measure. There has consequently been a recent
preference for describing measurements in operational terms rather than in terms of
particular species. Through research these operational speciation measurements could be
compared with other measurements of important processes, such as biological uptake and
toxic effects. Such operational measurements will prove to be almost as useful as if they
were accurately and precisely able to determine trace metal speciation in natural waters.
4
Chapter 1
The DGT technique has been reported as being capable of speciation measurements 14, 23
25, but the potential for speciation measurements with DGT has not, as yet, been
investigated fully. The nature of the trace metal species that are measured by DGT (i.e.
are DGT-labile) have also not been investigated fully either. A complex is labile if the
thermodynamic equilibrium of dissociation of the complex is maintained at all distances
from the binding phase. These aspects of DGT are investigated in this dissertation
through the development of new binding phases that have various functional groups and,
therefore, various strengths of interaction with trace metal species (and may therefore have
different DGT-labile fractions). This study is the first to investigate, in depth, the
development of new binding phases for trace metal speciation of DGT.
The following literature review includes a more detailed description of the current
thinking and research on each of these and other topics. The review begins by describing
the range of trace metal species present in natural waters and describes important
processes that lead to changes in speciation. The importance of speciation measurements
is then discussed with respect to toxicological studies and models that describe the
interaction between trace metals species and organisms. Various methods used for
speciation measurements are described briefly, followed by a detailed description of DGT
and of studies that have contributed important information to the development of DGT.
Other important speciation methods are also described. Many of these methods have used
complexing functional groups and selective membranes. The field of membrane and
separation science, which frequently uses complexing functional groups, is also reviewed
with respect to their potential for use with a DGT binding phase. The purpose of this
research was to determine whether these approaches could be utilised in the preparation of
a range of new DGT binding phases that could be used for speciation measurements of
trace metal in natural waters.
5
Chapter 1
1.2. THE SPECIATION OF TRACE METALS IN NATURAL WATERS
It is well known 26 that trace metals in waters exist in various chemical forms due to the
formation of stable complexes with numerous inorganic and organic ligands, and the
adsorption of many species onto colloid and particle surfaces. The reactivity of metals in
biological or environmental processes is determined not by the total metal concentration in
a water sample, but by the concentration of the most reactive or labile species present.
The distribution of metal species influences the bioavailability, toxicity and mobility of
the metal 27-30. These distributions vary with aquatic conditions, regulated by salinity,
redox conditions, suspended sediments, organic matter and biota. Table 1.1 shows the
major forms of metal species in natural waters.
Organic matter content varies between 0.3 and 3 mg l-1 of carbon in open seas, and usually
between 1 to 10 mg l-1 in rivers, lakes and estuaries 31. In some waters, like wetlands,
organic matter content can go as high as 30 mg l-1 32. These organic compounds, released
by living organisms, or resulting from their decomposition, can be classified into two main
categories 28, 29: non-humic substances and humic substances. Non-humic substances
generally have well defined structures (e.g. proteins, polypeptides, carbohydrates, fats,
waxes, resin, pigments, amino acids and other low molecular weight compounds). Such
compounds are generally rapidly degraded and utilised by microorganisms 32. Humic
substances (HS) are formed by microbial activity on nonhumic substances, as well as
abiotic polymerisation. Phenol groups, quinines, phenol carboxylic acid groups and
related functional groups are common in humic substances. Humic substances are also
quite resistant to further microbial degradation and consequently tend to persist in
6
Chapter 1
waterways 32. In some freshwaters humic substances consist of between 60-80% of the
dissolved organic carbon 33-35. This percentage is usually lower in seawater (10-30%) 36.
Table 1.1 Physico-chemcal Forms of Metal Species in Natural Waters 37, 38
Physical states and Chemical forms Examplessize ranges (nm)
Soluble Oxidation state Cr 3+ (aq), CrO4
2 (aq)
(<5) Simple hydrated metal ion Zn(H2O)6 2+
(aq)
Simple inorganic complexes Zn(H2O)2Cl2(aq)
Stable ion pairs ZnCO3(aq), PbS(aq)
Complexed to low molecular weight HS
Cu2+-glycinate(aq)
Complexed to high molecular weight HS
Cu2+-fulvate(aq)
Organometallic complexes Hg(CH3)2(aq)
Colloidal Adsorbed on inorganic colloids Cu2+- Fe2O3(s), Cd2+- MnO2(s)
(10-500) Adsorbed on organic colloids Pb2+- humic acid
Adsorbed on mixed colloids, (inorganic/ organic)
Cu2+-Fe2O3(s)/humic acid
Particulate matter Precipitates, co-precipitates PbCO3(s), Cd-FeOx(s)
(>500) Mineral particles PbS(s)
Metals adsorbed on solids Cu2+-CuS, CuCO3 on clay minerals, MnIV oxides
Metals incorporated with organic material
Metals in plankton, detritus
7
Chapter 1
One of the most important speciation interactions is due to the complexation of trace
metals by organic matter. Natural waters contain both a vast range of organic matter of
biological origin and organic pollutants, which have a range of complexing properties.
Due to the high concentrations of natural organic matter (NOM) relative to trace metals
and the presence of complexing functional groups on the NOM, a large fraction of the
trace metals in many natural waters are complexed to NOM, usually the humic substances
(e.g. Pb-HS 39, Zn-HS 7 and Cu-HS 40). About 50% of dissolved lead 41, 42 15-35% of
dissolved cadmium 43 and > 90% of dissolved copper 44-46 and zinc in seawaters 47, 48 are
usually found to be complexed with natural organic ligands that appear to be produced by
organisms in the upper ocean 49.
Trace metals can also adsorb readily to particulate materials (mineral and organic).
Approximately 95% of trace metals transported from land to sea by surface waters are
adsorbed on mineral particles directly, or are bound to organic matter coating these
particles 50. During such transportation, sorbed species may be redistributed between the
aqueous and solid phases as a result of changes in the physicochemical conditions of the
water, leading to redistribution amongst various competitive equilibria, including the
formation of soluble complexes with inorganic ions (e.g. Cl-or OH-) and molecules (e.g.
H2O or NOM).
The flocculation of colloids into larger particles occurs in estuaries due to the increase in
ionic strength that partly neutralises the stabilising charge of the colloids and due to the
presence of humic matter that induces their aggregation 51, 52. These particles then settle
out of the water column and are incorporated into the bottom sediments. Over 50% of the
metal ions in rivers are removed by estuaries in this manner 53, 54.
8
Chapter 1
Some metals can occur in various oxidation states (e.g. Cr, Fe and Mn). While redox-
active metals usually exist in an oxidised form in waters, conversion to reduced ions can
occur in the sediment at depths below the redox boundary or when waters become anoxic.
Biological and photochemical-catalysed reactions can also influence the oxidation state of
a metal. The photochemically enhanced reduction of insoluble Fe (III) oxides provided a
possible source of Fe (II) 55, 56. A hydroxide ion donates an electron to a photoexcited Fe
(III) surface atom resulting in surface bound Fe (II) to solution 56. While iron is not a trace
metal, many trace metals that do not have various oxidation states have species that adsorb
strongly to iron (III) oxyhydroxide particles and colloids and therefore have speciation
indirectly dependent upon the oxidation-reduction conditions of a waterway.
Some trace metals can form organometallic species. Organometallic metals usually have a
harmful effect, due to their high solubility in fatty tissues and organs relative to their water
solubility. Through biological and chemical processes methyl-mercury is formed from
inorganic Hg in sediment 57, water 58, soil 59 and other sites, such as the roots of floating
aquatic macrophytes 60. Other organometallic species have been produced artificially,
such as tributyltin, which has been used as an antifouling agent within paints 61, 62.
1.3. THE NEED FOR SPECIATION MEASUREMENTS OF TRACE
METALS
Metal speciation studies are required to understand metal availability and thus potential
toxicity to organisms 27, 63-67. Changes in environmental conditions, whether natural or
anthropogenic, can strongly influence the behaviour of both essential and toxic elements
by altering the forms in which they occur. Some of the more important controlling
factors, as discussed above, include pH 68, 69, ionic strength 70, oxidation-reduction (redox)
potential 71 and the availability of “reactive species”, such as complexing ligands (both
9
73
Chapter 1
organic and inorganic) 72, particle surfaces for adsorption, and colloidal matter .
Examples of changes in the speciation of an element, that occurs in response to a change
in one or more of the above parameters, and which leads to an increase in toxicity or
bioavailability are:
(1) A decrease in the pH of soil groundwater, from acid rain or acid sulfate soils, can
increase the leachability of aluminium from aluminosilicate minerals in the soils 74,
75, resulting in detrimental effects, including, in extreme cases, fish-kills in
receiving waters.
(2) Arsenic, an extremely toxic element in its inorganic forms, is relatively innocuous
as arsenobetaine (a common form in fish) 76, 77.
(3) Organotin compounds, of which perhaps the best known are the antifouling agents
of tributyltin 78 and triphenyltin 79, are generally more toxic than inorganic tin
species 80.
(4) Changes in the oxidation state of an element, in response to a change in the redox
status of the water, can also have a profound effect on bioavailability and toxicity.
For example, while chromium (III) is an essential element, chromium (IV) is
highly toxic; similarly arsenic (III) is generally much more toxic than arsenic (V)
54, 81.
The toxicity of a particular dissolved metal species towards an aquatic organism is closely
related to its ability to react with a biological membrane 5. The penetration of the
membrane by a metal ion, to react with the cell components, depends on the direct lipid-
solubility of the metal species (usually only uncharged organometallic species), or the
extent and rate of reaction of the metal ion with a membrane transport protein. Metal-
protein interactions, which lead to carrier-mediated transport of the metal across a
biomembrane, will, for bivalent ions, be thermodynamically favoured when the metal is in
the simplest chemical form, e.g. Cu(H2O)42+, CuCl+ or Cu(OH)+. For tervalent ions, such
10
Chapter 1
as Fe(III), however, the most bioavailable form may be an organic complex, as hydrolysis
and polymerisation can render the free ion inactive 82.
In some cases, kinetics rather than thermodynamics may dictate the biologically active
chemical species. The toxic form of aluminium appears to be Al(OH)2+, which reacts with
gill mucus to hinder the transport of oxygen, potassium and sodium 83. This species was
previously shown to be the kinetically-favored species in the reaction between aluminium
(III) and a hydroxyazo compound 84. The reaction of metal ions with biological
membranes is a particularly complex process, and cannot be explained by simple diffusion
models 85. Most studies of the toxicity of heavy metals for fish have shown that the free
(hydrated) metal ion is the most toxic form 54. In the case of copper, hydroxy complexes
are also believed to be toxic, although to a lesser extent 86. Strong complexes, and species
associated with colloidal particles, are usually assumed to be non-toxic, due to low
biological uptake where the exposure route is through contact with water.
Several models relating trace metal speciation with biological uptake through contact are
described below. However, contact with water containing trace metal species is not the
only mechanism of exposure. Some organisms, such as filter feeders and particle feeders,
are likely to take up trace metals through ingestion of particles and colloids with metals
adsorbed to the surface 87, 88. The bioavailable forms then depend upon the gut conditions
of the organism 89.
1.3.1. The Free-ion Activity Model
Prior to about 1975 researchers tended to emphasise the target organism and the influence
of biological variables (e.g. life stage, nutrition and age) rather than the exposure regime
(e.g. metal speciation, pH, hardness, alkalinity and ionic strength). In 1976, due to an
11
Chapter 1
improved understanding of metal speciation from environmental chemistry, aquatic
toxicologists shifted their focus from the target organism to the chemistry of the exposure
medium. Toxicological studies were performed in a defined media with synthetic ligands
(with known stability constants and hence 'known' metal speciation) 90. This approach
was highly successful in synthetic media, with ligands forming soluble hydrophilic
complexes. Eight years later, Morel 91 proposed that the bioavailability of a dissolved
metal is related to its free ion activity. He suggested that the decrease in metal toxicity,
observed in the presence of chelating agents, is simply the result of a decrease in the
bioavailability of metals due to chelation of the metals in the medium, and not to a
positive physiological effect of the chelating agents.
Significant correlations have been established between the toxicity of a metal and the
chemical reactivity of the metal, as measured by ionic size, ionization potential,
electronegativity, and its tendency to form bonds of a covalent nature 92. These
correlations presumably reflect the fact that metals must exert their toxicological activity
ultimately by reacting with surface functional groups on susceptible target molecules in
cellular compartments, and that these reactions are governed by physicochemical laws.
An insight into the potential toxicity of a metal and the candidate target molecules affected
may be gained by considering the relative ability of different metals to bind to organic
ligands. An understanding of metal-ligand binding is also fundamental to studying the
types of cellular macromolecules that may be involved in detoxifying metals by
sequestration 93, 94.
Experiments with a variety of aquatic organisms have developed a convincing body of
evidence to support the concept that the biological response elicited by a dissolved metal
is usually a function of the free-ion concentration, M(H2O)nz+. The free-ion concentration
12
Chapter 1
is determined not only by the total dissolved metal concentration, but also by the
concentration and nature of the ligands present in solution 91.
The interaction of a metal with an aquatic organism involves the following steps:
(1) advection or diffusion of the metal from the bulk solution to the biological
surface;
(2) diffusion of the metal through the outer 'protective layer', i.e. biomembrane;
(3) sorption/surface complexation of the metal at passive binding sites within the
protective layer, or at sites on the outer surface of the plasma membrane;
(4) uptake or 'internalisation' of the metal (transport across the plasma membrane)
95-97 .
The possibility of a metal entering a cell by passing across the cell membrane is clearly
dependent on the routes that are available and the forms in which the metal exists 98-100.
The following species may be involved in varying degrees for a metal to permeate the
membrane:
Metal ions (e.g. M2+); Hydrated ions (e.g. M(H2O)62+);
Charged metal complexes (e.g. MCl(H2O)5+);
Uncharged inorganic complexes (e.g. MCl20); and
Organometallic complexes (e.g. CH3M).
1.3.2. The Biotic Ligand Model
During recent years the biotic ligand model (BLM) has been proposed as a tool to evaluate
quantitatively the manner in which water chemistry affects the speciation and biological
availability of metals in aquatic systems 101-104. The BLM model incorporates features of
several detailed chemical equilibrium models, including the Gill Surface Interaction
13
Chapter 1
Model 105 and the Free Ion Activity Model 26, 91, into a unified framework that is used to
calculate the distribution of a metal among the free ion, inorganic complexes and organic
complexes 106, 107. In the context of the BLM framework, the tissue at the site of metal
accumulation is defined as the biotic ligand. The concentration of metal that is associated
with the biotic ligand is calculated in the same way as the concentration of metal that
exists in association with any other organic or inorganic complexing ligands in the water.
The biotic ligand competes with the other complexing ligands (e.g. natural organic matter
or organic ions) for binding of the available metal. The BLM framework provides a direct
basis for predicting the reduction in copper bioavailability due to increasing levels of
natural organic matter, carbonate alkalinity or pH.
The BLM also takes consideration of the interaction of the biotic ligand with other cations
in solution, such as calcium or sodium. The major ions compete with the trace metal ion
for binding at physiologically active sites at the biotic ligand. At sufficiently high levels,
this competitive binding of major ions to the biotic ligand will effectively inhibit the
accumulation of trace metals at the site of action. The explicit incorporation of this
competitive effect in the BLM, in conjunction with a relationship of toxicity to the level of
metal accumulation, provides a basis for predicting the reduction in metal toxicity
associated with the presence of elevated calcium concentrations. It is in this manner that
the BLM can be used to predict the well-recognized effect of decreasing toxicity of metals
with increasing hardness.
The excellent agreement between measured copper and silver LC50s (lethal concentration
associated with 50% mortality) (Figure 1.1) and BLM predicted LC50s demonstrates that
the BLM predictions represent a viable alternative to conducting bioassays to evaluate
14
Chapter 1
metal bioavailability 102, 103. The data requirements for application of the BLM include
chemical analysis of the receiving water or effluent and receiving water mixtures
Figure 1.1 BLM predicted LC50 vs observed LC50 for copper and silver (Cu data: Erickson et al. 108; Diamond et al. 109 and Ag data: Bury et al. 110; Bills et al. 111)
15
Chapter 1
associated with a discharge location. The required chemical analyses are generally of a
routine nature and would include pH, DOC, alkalinity, major cations (Ca2+, Mg2+, Na+,
K+) and major anions (Cl-, SO42-).
1.4. ISSUES TO CONSIDER WHEN SAMPLING AND MEASURING
TRACE METAL SPECIES
In order to comprehend the environmental chemistry of an element it would be necessary
to characterise, in full, the proportions and concentrations of all the various forms under
the diverse range of conditions possible in natural systems. Whilst this is clearly
impracticable, it is important to measure concentrations of some important species of trace
metals 112.
1.4.1. Sampling Factors
The determination of selected or consistent trace metal species is more challenging than
the determination of total metal concentrations. Trace metal species distributions are very
sensitive to physico-chemical changes, such as those that occur with sampling, storage and
handling. Some of the processes that may modify trace metal speciation include 18, 113, 114:
(1) Release or loss of elements or complexants (especially macromolecules and
colloids) by desorption/adsorption to any surface used during sample handling
(polymer/glassware, filtration apparatus, etc.) 115;
(2) Gaseous re-equilibration of the sample with the atmosphere due to pressure
change. Re-equilibration of gases with acid-base properties (e.g. CO2) may cause
significant variations in pH and thus modify compound speciation. When anoxic samples
are equilibrated with the atmosphere, oxidation of some of the inorganic species (Mn2+, 16
Chapter 1
Fe2+, S2-) may produce colloidal particles (MnO2, Fe(OH)3, S0) which may dramatically
change the species distribution of many trace metals, owing to their strong redox or
adsorption reactions with these colloids 116;
(3) Coagulation of colloidal matter, followed by sedimentation of the aggregates and
the associated trace compounds. Colloids are ubiquitous in natural waters and include a
large fraction of trace compounds 117;
(4) Microbial activity, such as the continued metabolism of microbes during sample
storage, may significantly alter the chemical composition of the sample. For example, the
pH may vary because of continued respiration (pH decrease) or photosynthesis (pH
increase). Dissolved concentrations of trace metals may also be changed as a result of
their continued uptake or release by living micro-organisms. Complexation or enzymatic
properties may also change owing to the release of biomolecules 118; and
(5) Virtually all methods used to preserve the trace metal concentration will dramatically
affect the speciation with the addition of acid or the freezing of the sample. Therefore
samples collected for speciation are often changed, which means that measurement should
be undertaken immediately.
Some of these problems (1-3) may be minimised by special (often tedious) precautions,
but problems (4) and (5) are natural processes which cannot be eliminated without
dramatically perturbing the sample. Indeed, in their natural environment, aquatic samples
are not at thermodynamic equilibrium; at best, they may be in steady state conditions due
to the continuous inputs (e.g. soil leaching, atmospheric inputs, cell growth) and outputs
(e.g. coagulation/sedimentation, cell death) of colloids and microbes 113, 119, 120. While the
17
Chapter 1
sampling process stops most of the inputs, coagulation and microbia turnover may
continue and any anti-coagulant or antibiotic may either induce drastic changes in the
chemical speciation of the test compounds or cause analytical problems 119.
1.4.2. Measurement Factors
Other difficulties with speciation occur at the measurement step, including:
(1) difficulties associated with isolating the metal species of interest from complex
matrices;
(2) most speciation measurement techniques available disturb (to some extent) the
equilibria existing between the various chemical species present in the system
under study;
(3) for species present at ultra-trace levels, few analytical procedures possess the
degree of sensitivity required; and
(4) suitable standard reference materials are often unavailable.
The nature of the challenge varies with matrix type; seawater is particularly challenging
due to the high concentrations of matrix ions.
Basically three general approaches have been used for measuring trace metal speciation in
waters. It will be useful to consider the general strategies of sampling with respect to
these various problems of speciation measurement. The conventional approach to water
quality sampling and analysis (where grab samples are collected, usually filtered, and
preserved by acidification before analysed in a laboratory) suffer from most of the above
limitations. Furthermore, the approach provides a measurement of the
concentration/speciation at only one time. In dynamic waters, such as rivers and estuaries,
this type of measurement is not likely to be representative of the average condition 121.
Therefore a comprehensive sampling program is required, with hourly sampling across
18
Chapter 1
tidal and diurnal cycles, for each major season, as well as event sampling 122. This
sampling approach is logistically complex, being time consuming and expensive, but does
provide good data, if the problems inherent to speciation measurements can be overcome.
The advantage of this approach is that the most sophisticated measurement instruments
can be used.
Another approach, on-site analysis, involves removal of a water sample followed by
immediate analysis on-site. The process is usually automated and often uses laboratory
procedures and instruments, which may have been adapted to suit the appropriate field
conditions. The on-site analyses approach comes close to the ideal of real time
measurements, minimising some artefacts that are associated with sample storage 123, 124.
While close to the ideal, the approach has not yet been widely utilised for environmental
monitoring. Problems that limit such use include it being expensive to implement for the
most sensitive instrumentation, which usually require controlled laboratory conditions.
The main exceptions to this are electrochemical methods. The automation required is also
likely to be challenging as the sample will usually have to be filtered on-line; this process
will need to be maintained to achieve accurate measurements. Another problem arises
with this approach having to be deployed close to land or boats, both of which can
influence the sample composition. If the sample has to be piped for long distances then
many of the surface related and microbiological processes listed above can become
problems.
Given these difficulties, alternate approaches to trace metal speciation have been sought;
they have usually involved some type of sensor that can be deployed in situ. There are
three ways in which in situ sensors can operate. They can continuously respond to a trace
metal species that interacts with the sensor (termed the labile fraction); they may make
19
Chapter 1
discrete measurements in situ; or the labile trace metal species are accumulated
continuously in situ and are stored in a stable form, while quantification takes place upon
returning to the laboratory 125. These various approaches minimise many of the
difficulties associated with trace metal speciation measurements concerning sampling,
preservation and storage. The main problems with many of the in situ techniques
currently reported include: lack of sensitivity; they are technologically complex and/or
expensive; or they cannot be used for very long time periods.
There has been a lot of recent interest and development with in situ measurement
approaches, for the reasons described above. The major advantages of in situ
measurements for natural water monitoring, compared with conventional sampling and
laboratory analysis, are:
(1) elimination of many of the artefacts due to sample handling, i.e. no or minimum
sample transformation;
(2) minimisation of the overall cost of data collection (in particular, due to a reduction
of analysis time);
(3) possibility of real-time analysis, allowing rapid detection of pollutant inputs (e.g.
monitoring of industrial wastes or water quality in water treatment plants);
(4) ability to accumulate detailed spatial and temporal data banks of complete
ecosystems (lakes, aquifers, etc.);
(5) possibility to perform measurements in locations which are difficult to access
(boreholes, deep lakes or oceans); and
(6) possibility of measuring concentration gradients and fluxes at environmental
interfaces (sediment-water; air-water), at high (sub-mm) spatial resolution 116.
These aspects are important both for studies of ecosystem functioning and for water
quality monitoring.
20
Chapter 1
A number of criteria have been recommended for the development of in situ probes:
(1) reliable, automatic measurements, in the field, (measurements are often required at
a depth in which no visual control is possible);
(2) simple, compact, low cost apparatus;
(3) no or minimum sample transformation (minimisation of artefacts);
4(4) high sensitivity for minor and trace compounds (10-7-10-15 mol l-1) ;
(5) multi-elemental analysis capability for trace metals;
(6) selective speciation measurement or other information on the distributions of
species;
(7) physically and chemically non-perturbing for the system tested; and
(8) preferably measurement time faster than the time scale of the process studied 18.
A number of speciation measurements used for in situ trace metal speciation
measurements are described in the following section. The diffusive gradients in thin films
(DGT) technique is then described and assessed in detail.
1.5. TECHNIQUES USED FOR IN SITU MEASUREMENT AND
SPECIATION OF TRACE METALS
Various approaches have been developed to measure trace metal species in situ over the
last decade including ion-selective electrodes (ISE), various voltammetric techniques,
ultra-filtration, dialysis, diffusive equilibrium in thin films (DET) and permeation liquid
membranes (PLM), as well as the DGT technique. ISEs involve the use of potentiometric
measurements. They directly relate the measured potential to the logarithm of the
concentration (or more specifically, the activity) of a specific hydrated ion 126, 127. The
applicability of ISEs may, however, be restricted by their sensitivity (detection limit 10-6 –
10-7) 128, 129 and selectivity. Unfortunately interfering ions in the waters can be an
21
Chapter 1
important source of errors, which can lead, in general, to the overestimation of the ion
concentration. ISEs have been developed for both Cd2+ (detection limit 10-7 mol l-1, Hg2+,
Ag+, Cu+ interfere) and Cu2+ (detection limit 10-8 mol l-1, Hg2+, Ag+, Cu+ interfere). To
date potentiometric measurements have been limited for use in natural waters due to the
low practical detection limits.
Voltammetric techniques, particularly those involving a stripping approach (anodic
stripping voltammetry, cathodic stripping voltammetry or chrono-potentiometric stripping
analysis) 130 provide the most direct method for the study of trace metal speciation at low
concentration levels (10-7 to 10-12 mol l-1). These techniques do not normally require the
pre-concentration of the water sample by physical methods 131, 132. However, many
factors, such as pH, temperature and ionic strength, may influence the electrode processes
and affect the signal 133, 134. Consequently calibration must be performed with great care,
and with due regard to the physicochemical processes involved. These voltammetric
techniques are highly operationally-defined and the trace metal fraction that is measured
has been defined already 134, 135. Their approaches have been used for on-site
measurements as well.
Dialysis 136, 137 is also used in water studies to separate high molecular weight and
colloidal forms of trace metals from smaller species, which are often more labile 134, 138.
Dialysis can be accomplished over a range of nominal molecular weights from 210 to
300,000. The passage of species through a filter membrane depends on species geometry
as well as on molecular weight 139. A similar technique to dialysis 140, diffusive
equilibrium in thin films (DET), is based on the free exchange of ions between the water
in a hydrogel and the sample solution (e.g. natural waters), supposing that there are no
reactions between the hydrogel and analytes 141. DET also operates on a size-fractionation
22
Chapter 1
basis, although the actual sizes excluded have not been defined as yet. Dialysis and DET
are deployed in situ and are equilibrium techniques, where it is assumed that the
concentration collected is the same as that in the water sampled. All of these methods
require laboratory-based instrumental measurement of the trace metal metals accumulated.
Permeation liquid membranes (PLM) are an emerging technique that is similar to DGT in
some regards. PLMs use a water immiscible liquid membrane containing a complexing
agent selective for the analyte of interest 142, 143. This layer is called the carrier phase
because it is meant to selectively transport the trace metal analyte to an aqueous phase
containing an even stronger complexing agent (the stripping phase). The PLM device is
deployed in situ with the analytes accumulating within the stripping phase. As this phase
is a solution, some attempts have been made to incorporate an in situ sensor but sensitive
laboratory instrumentation can also be used 144, 145. The PLMs are selective for free and
lipophilic metal species. Determination of concentrations down to 10-13 mol l-1 is possible.
1.5.1. Diffusive Gradients in Thin Films (DGT)
The diffusive gradients in thin films (DGT) technique was developed from the DET
technique 14, 146. DGT added a binding phase to the diffusive hydrogel layer 14, 15. Analyte
species diffuse through the hydrogel layer to the binding phase, which for trace metals is a
hydrogel containing beads of Chelex 100 resin. These beads are situated along the
hydrogel surface in contact with the diffusive layer when the DGT device is assembled.
As a result, labile trace metal ions (and cations), diffuse through the diffusive layer to bind
to the binding phase. The solution concentration at the interface between the diffusive
layer and the binding phase should ideally be zero. If this occurs a constant concentration
gradient is maintained within the diffusive gel layer between this interface and the solution
23
Chapter 1
analyte concentration. A flux of labile trace metal ions occurs into the DGT device. This
flux is able to be quantified using an equation derived from Fick’s law of diffusion, and
can also be used to estimate the analyte solution in the sampled water. DGT thus has the
potential to be used to measure trace metal concentrations and speciation in natural waters
14, 16.
1.5.1.1. DGT Principle and Theory
Figure 1.2 shows a conceptional view of DGT. The diffusive gel is usually covered with a
membrane to protect the hydrogel surface from having particles adhering to it. The
membrane behaves like an extension of the diffusive layer 15, 147. The diffusive layer
thickness is ∆ g (diffusive hydrogel + membrane thickness).
Between the diffusive layer and the bulk solution a diffusive boundary layer (DBL) forms.
The DBL thickness, δ, is determined by the velocity of the water across the surface; it is
also a region where the transport of ions occurs solely by diffusion. Within a few minutes
of immersion into a water body with analyte concentration, C, a steady state linear
concentration gradient, is established between the solution and the resin gel, as described
above. By exploiting this simple steady state condition, the DGT technique can be used to
measure concentrations in situ. The flux, J, of an ion through the gel is given by Fick's
first law of diffusion (equation 1.1), where D is the diffusion coefficient for the ion at the
given temperature and dC/dx is the concentration gradient:
dCJ − = D × (1.1)dx
24
Chapter 1
If the concentration gradient of ions in the diffusive gel is kept constant, the flux is given
by equation 1.2, where C is the bulk solution concentration of an ion and C' is the analyte
concentration at the boundary between the binding gel and the diffusive gel:
'C − CJ − = D × (1.2)∆ g δ +
∆ g δ
C
0
r
Solu
tion
D
A
M
C’
Con
cent
ratio
n
Diffusive Laye
Bin
ding
Pha
se
Mem
bran
e
Relative Distance (cm)
Figure 1.2 Conceptual view of the steady state concentration gradient of a solute through a DGT device deployed in a well stirred solution with solution analyte concentration, C, diffusive layer thickness, ∆ g, including 0.45 µ m pore size cellulose nitrate membrane thickness, diffusion boundary layer, δ , analyte accumulated (M), diffusion coefficient (D), cross-sectional area (A).
If the analyte species are in rapid equilibra with the binding functional group and the
interaction between the two is strong enough (i.e. the stability constant is high), C' will
effectively be zero, providing the binding sites do not become saturated. In well stirred
25
Chapter 1
solutions, or natural waters with sufficient current, the boundary layer thickness, δ, is
negligibly small compared to the thickness of the diffusive layer, (usually ∆g of 0.4-1
mm). Various estimates suggest that a range of 0.1-0.01 mm DBL thickness 148 may be
typical of well-mixed waters. In a recent paper, Scally et al. 149 reported an average value
of 0.024 ± 0.002 cm for δ using the following equation 150:
1 ∆gC δ = +
M DCtA DCtA (1.3)
Given that C' equals zero and δ is negligible, equation 1.2 then simplifies to equation 1.4.
CJ = D ×∆g (1.4)
DGT devices are deployed for a certain time, t. On retrieval, the binding gel phase is
peeled off and the amount (mass or moles usually) of the accumulated trace metals are
measured. Mass can be measured directly in the binding gel by drying it and using a beam
technique, such as proton induced x-ray emissions (PIXE) 151, or in the case of
radionuclides, indirectly measuring radiation 152. More commonly, ions in the binding gel
are eluted with a known volume, Ve, of HNO3 solution (1 or 2 M) in the case of trace
metals bound to Chelex 100 resin 16, 21, 153. The concentrations of ions in the elution, Ce,
are then measured by an appropriate analytical technique after appropriate dilution. Using
these parameters, the accumulated mass (M) of analyte can be calculated, which in turn
can be used to calculate the flux through the known area of the exposed diffusive layer, A:
MJ = (1.5)At
26
Chapter 1
Combining equations 1.4 and 1.5, the rearrangement gives equation 1.6 (the DGT
equation), which relates the concentration, in the bulk solution, to the known values of ∆g,
D, and A, the measured deployment time, t, and the measured accumulated mass, M 14, 16.
∆C = g M (1.6)
DAt
This feature of DGT, whereby concentration is calculated from the measured mass and
deployment time makes it ideal for in situ applications. The relationship of external
concentration to measured mass is determined by the values of ∆g and A, which are fixed
geometric quantities, and by the diffusion coefficient of analyte species in the gel, which
can be measured under controlled conditions. These factors make DGT a kinetic
technique, which can be deployed for varying times (t).
The basic principles of DGT have been verified repeatedly in the laboratory 16. It has been
shown that the mass accumulated in the binding gel is proportional to deployment time (t)
and inversely proportional to diffusion layer thickness (∆g); these two parameters are the
ones most readily varied as part of a series of experiments. Experiments have confirmed
that there is no interaction between metal ions and the diffusion gel 154, 155, which is an
assumption of the DGT equation. DGT theory also required that the analyte concentration
on the interface between the diffusion layer and the binding phase be maintained at zero
through out the deployment. This experiment has since been used as a test to evaluate the
use of DGT with analytes other than trace metals 147, 150, 156.
Of course there is a difference between deploying DGT devices in controlled laboratory
experiments and in deploying them in the field. The main difference is that the trace metal
speciation will be much more complex, as most laboratory experiments will only use free
27
Chapter 1
metal ions or simple inorganic species. The other trace metal species present in natural
waters will have characteristic diffusion coefficients, which will be much lower than that
for the free metal ion species. With association and dissociation of metal complexes
continually occurring, membrane uptake and biological uptake of metals does not simply
depend on the free metal ion activity 26. The depletion of the free metal ion at the
membrane surface results in the dissociation of free metal ions from complexes 157, 158.
Anodic stripping voltammetry was used to obtain information on dynamic dissociation of
metal complexes in natural waters 159, 160.
In DGT, the measured analyte species are the ones which can diffuse through the diffusive
layer and be bound to the binding phase. Nevertheless, when metal ions are removed at
the surface of the resin phase, a dissociation of metal complexes may be induced within
the diffusive layer; the DGT measured mass will be the sum of contributions from both
free metal ions in solution, MF, and free metal ion, M’, dissociated from the complexes,
ML, 16, 149.
( CMF DMF + C ' M D )At (1.7)MLM = ∆g
where CMF is the concentration of free metal ion in the solution and DMF is the diffusion
coefficient of the free metal ion. CM’ is the concentration of metal dissociated from ML
and measured in the resin phase by DGT, and DML is the diffusion coefficient of the metal
complex, ML.
Assuming the dissociation of ML is a first order reaction with a rate constant, k-1, then,
C ' M = CML(1− exp( −k τ )) (1.8)−1
where τ is the time taken for the dissociation. 28
Chapter 1
This reaction can occur while ML is transported through the diffusion layer and the
concentration of MF is lowered in this zone. As MF is consumed at the resin phase, the
dissociation reaction shifts to produce more MF.
The characteristic time for transport of a complex through a diffusion layer of thickness
∆g, td, is given by equation 1.9 160,
2( ∆g )td = (1.9)2DML
As ML can only be measured if it dissociates during time td, it is a reasonable
approximation to set τ = td. Combining equation 1.7, 1.8 and 1.9 the total accumulated
mass of metal measured can be expressed
2CMLDML (1− exp( −k ( ∆g ) / 2DML )) + CMF DMF At (1.10)−1M = ∆g
When the dissociation of the ML is significant, k-1 >> DML/(∆g)2, then,
M = CMLDML + CMF DMF At (1.11)∆g
160When k-1 << DML/(∆g)2 then ML can be considered to be inert and the DGT
measurement is effectively only determined by the diffusion of MF,
M = CMF DMF At (1.12)
∆g
1.5.1.2. Diffusion Boundary Layer (DBL) and Biofouling Effect
Another important aspect of field deployment is the significance of the diffusion boundary
layer which varies in thickness with the velocity of the water across the surface of the 29
23
Chapter 1
DGT device. The flux of metal diffusing to the resin gel of a DGT assembly depends on
the thickness of the diffusion layer and the diffusion boundary layer (DBL) in solution. In
well-stirred solutions the DBL must be negligibly small because the measurements obeyed
the DGT equation. Free stream velocities of only a few cm s-1 are required for diffusive
boundary layer thickness to approach zero 148. If there is no stirring in the solution, or if
there is no or low flow (during in situ deployment, the DBL thickness can become
significant when compared with the diffusion layer thickness and a low mass
accumulation is obtained. This effect was observed to be important for still lake water 16,
. In other waters, such as estuaries, the rate of mixing will vary over a day, with the tidal
flows.
Webb and Keough 161 found, from a large number of comparisons, that estimates of metal
levels were higher for DGT devices with 0.8 mm diffusive layers than for those with 0.4
mm diffusive layers, where the 0.8 mm and 0.4 mm units were deployed simultaneously at
four sites: Westernport Marina, Hastings Jetty, St. Kilda Marina and St. Kilda Pier,
Melbourne, Australia, during 1999, from February 23 to March 25, and from August 25 to
September 24. It was explained that the biofouling of the membrane surface effectively
increased the diffusive boundary layer relative to the known diffusive layer thickness, ∆ g,
16, 161. When deploying DGT in still water or when major biofouling of the membrane is
likely, DGT devices with different ∆ g values are deployed at the same location for the
same time 150, 162 and equation 1.13 is used.
1 1 ∆ g −∆ g2− = 1
M1 M 2 DCtA (1.13)
With the two gel layer thicknesses, ∆g1 and ∆g1, C can be calculated from the measured
values of M1 and M2. Whether due to poor mixing or due to biofouling growth, the effect
of the DBL thickness, is effectively cancelled out through the use of this equation. Errors,
30
Chapter 1
however, may arise due to the variation in the extent of biofouling or the thickness of the
DBL between the DGT devices. The latter would be quite unusual if they were deployed
at the same site at the same time.
1.5.1.3. Speciation Ability
Several field studies using DGT have reported that DGT-labile concentrations differ from
0.45-µm filterable concentrations in a range of waterways. In seawaters, in the Gold
Coast Broadwater, Australia, the DGT-labile concentrations as a percent of the 0.45 µm
filterable fraction, were: 27 ± 12% for Ni, 29 ± 11% for Pb, 21 ± 2% for Cu and 28 ± 5%
for Zn 163 and 44 ± 14% for Ni, 41 ± 12% for Zn and 23 ± 13% for Cu in two different
seasons 164. Other fractions of DGT-labile concentrations of 0.45 or 0.2 µm-filterable
concentrations reported from field studies on marine or coastal waters include 14-38% Cu
in marine and estuarine waters around the USA 25 and 44-63% for Cu, and nearly 100%
for Co and Cd in north Australian coastal water 165. In fresh waters, similar ranges of
DGT-labile metal concentrations (as a percentage of a filtered fraction) have been
reported, and include: over 70% for both Cd and Cu 24 in both the Ring and Stitt Rivers,
Tasmania, Australia; 2.3% for Cd, 1.3% for Cu and 1.7% for Ni in Lake Tantare, Quebec,
Canada 22, and over 90% for Cd and Zn, 20-40% for Co, Ni and Pb, 5% for Cu in the
Water of Leith, an urban stream in Dunedin, New Zealand 166. Only one study has
systematically compared field DGT measurements with other speciation measurements,
which found that 10-35% of organically complexed Cu in seawater was DGT-labile 25.
The mechanism by which the DGT technique selectively measures trace metal species has
been investigated in a preliminary manner only. In principle, four factors provide
mechanisms that determine which species are measured by DGT. These mechanisms as
well as the results of studies that have experimentally investigated these are listed below: 31
Chapter 1
(1) Selectivity by a size exclusion mechanism, where trace metal species that are
larger than a particular size are not able to enter the DGT device. The DGT devices have
two size exclusion components, the 0.45 µm membrane at the interface with the water and
the diffusive gel itself. The membrane will effectively exclude all >0.45 µm material
which are usually defined as particulates. Less is known about the size exclusion
properties of the polyacrylamide hydrogel. One study used diffusive gels of different
porosity 154 to demonstrate that diffusion coefficients decreased as the gel pore sizes
decrease or the ion sizes increase.
(2) Differentiation of species on the basis of diffusional fluxes, where some species
will diffuse more quickly through the diffusive layer and therefore accumulate more
quickly in the binding phase. These species will have a larger influence on the DGT-
labile concentration estimated compared with species that diffuse more slowly. The
diffusional flux is dependent upon both the diffusion coefficient, which decreases with the
mass of the species 154, and the concentration of each species in the waterway (equation
1.4). The soluble inorganic trace metal species, including free ionic forms, ion pairs and
inorganic complexes will have higher diffusion coefficients compared with organic
complexes and colloidal species. As mentioned previously (section 1.2) in many natural
waters the dominant species are the organic complexes, but there is a great variety and
number of complexes present so the concentration of any given species might well be
comparable to those of the inorganic complexes. This is an area in which little
information is available, but it may well be the most important mechanism of selectivity
for DGT. For the most popularly used diffusive gel, agarose cross-linked polyacrylamide,
the diffusion coefficients of Cu2+, fulvic acid (AFA), humic acid extracted from peat
32
2
Chapter 1
(PHA) or stream water (AHA), and AHA-Cu complex were determined as 6.28 × 10-6 cm
2 2 2 2 -1 154 s-1, 1.15 × 10-6 cm s-1, 0.35 × 10-6 cm s-1, 0.60 × 10-6 cm s-1, and 0.57 × 10-6 cm s .
If the pore size of the gel is small enough to exclude more than 90% of the organic species
and still allow the inorganic species to diffuse through, then based on the DGT equation
(equation 1.6), the DGT device can estimate the concentration of inorganic species
directly 23. To measure inorganic and organic species separately, a series of DGT devices
with different pore size diffusive gels can be used. When the devices are deployed in the
same solution under the same conditions, the mass of metal accumulated on each DGT
device ((MDGT) is the sum of contributions from both labile inorganic and organic species.
According to equation 1.6, we have 23
C D in + C D M DGT = in or or At (1.14)∆g
where Din and Dor are diffusion coefficients of inorganic and organic species respectively,
and Cin and Cor are concentration of inorganic and organic species respectively.
Rearranging this equation,
M DGT ∆g Dor= Cin + Cor (1.15)Din At Din
then concentrations of inorganic and organic species can be determined through the plots
of (MDGT / Din) × ∆g / At versus Dor / Din. The intercept gives the concentration of labile
inorganic species and the slope the concentration of labile organic species 23, 167.
33
Chapter 1
(3) Selectivity for organic complexes based on the capability of the binding layer to
remove the trace metal ions. There are no published results investigating the importance
of this mechanism. However, studies have been undertaken comparing the uptake of trace
metals using the Chelex-100 binding phase with a synthetic ferrihydrite material 14, also
impregnated into a polyacrylamide hydrogel. The two binding phases gave significantly
different results for synthetic solutions without organic complexes being present 164. This
suggests that the strength of the binding phase will also be an important mechanism.
Given the focus on developing new binding phases in this dissertation, the significance of
this mechanism will be investigated. Chelex 100 has very strong binding groups, at high
effective concentrations, which may out-compete most other ligands for metal ions,
especially at the low concentrations of organic compounds present in most natural waters
168 .
(4) Selectivity for strong complexes that have rapid ligand exchange kinetics. Some
complexes will be strong enough that the DGT binding phase does not replace the binding
ligands of the complexes. However, these complexes may still be DGT-labile if the
complexes dissociate within the time it takes the species to diffuse across the diffusive
layer. In this case, equation 1.10 applies (section 1.5.1). The measured mass by DGT is
the mass contributed from free metal ions in sample solution and dissociated from weak
complexes 149.
1.5.1.4. Binding Phase
Polyacrylamide hydrogel, embedded with Chelex 100 chelating resin, has been used in
most previous studies of trace metal measurements with DGT. Clearly there are many
other materials that could be used as binding agents for DGT. Given the discussion in the
previous section on speciation, it is apparent that different fractions of trace metal species 34
Chapter 1
could be measured using binding materials with varying binding strengths. This section
describes concepts from other research fields in which the binding of trace metals is
required; such concepts are likely to provide ideas and materials appropriate for
applications with DGT.
Affinity membranes and hydrogels with chelating groups have been used for metal ion
separation and concentration 169, 170. They can be obtained by the copolymerisation of
different functional monomers, such as: diallyldimethylamonium chloride 171,
173 dimethylaminoethylmethacrylate 172, 2-acrylamido propanesulphonic acid , 3-
acrylamido-3-methylbutanoic acid 174; or by the modification of functional groups in the
polymer matrix, such as: Cibacron Blue F3GA-incorporated poly(2-hydroxyethyl
methacrylate) 175, Alkali Blue 6B-attached poly(2-hydroxyethyl methacrylate) 176 and
modification of poly(4-vinylpyridine) with dithizone 177. In addition, there are a number
of commercially available solid-state membranes containing functional groups appropriate
for binding trace metals.
Water soluble high molecular weight complexing agents have also been used for removal
of metal ions in ultrafiltration processes 178, 179. The use of a semipermeable membrane
allowed the retention of the polymeric materials, while maintaining diffusibility for the
species to be chelated or complexed. A wide variety of water soluble polymers may be
used, such as poly(ethylenimine) 180, poly(2-acrylamido-2-methyl-1-propanesulfonic acid)
181 and poly(methacrylic acid) 182. Water-soluble polymers are commercially available or
can be synthesized by different routes. One universal route for the synthesis of different
polymers is copolymerisation. With a good selection of both monomers it is possible to
improve properties such as water solubility, metal ion binding capacity and selectivity 183.
35
Chapter 1
N
CH2 Mn+
NCH CH2 CH CH2
CH2C O O C C O O CMn+
O O O O
i ii
CH CH2 CH2 CH CH CH2 CH CH2
Mn+
N N
OON Mn+
N S
CH CH2 CH CH2
S O O O O
iii iv
Figure 1.3 Schematic diagram representing the nature of metal ion binding: (i) carboxylic type complexes; (ii) maleylglycine type complexes; (iii) amine type complexes; and (iv) sulfonate type complexes.
Most suitable binding materials will make use of acidic functional groups, which are
Lewis bases (electron donors) or cation exchangers. As shown in Figure 1.3 183, polymers
interact with metal ions mainly through electrostatic forces 184, while selectivities arise
through the formation of coordination bonds 185. Functional groups, with carboxylic
groups, can act as mono and bidentate ligands 186, while polymers with sulfonate groups
favour the electrostatic polymer-metal ion interaction 184.
1.5.1.5. Overview of the DGT Technique
The DGT technique has many useful properties as an in situ measurement technique:
(1) the device is easy to use and effectively minimises contamination;
(2) it concentrates metals in situ and selects against many interfering matrix
constituents;
(3) many trace metals can be measured simultaneously;
36
Chapter 1
(4) it allows estimation of time-averaged concentrations over the length of the
deployment period, i.e. DGT never sleeps;
(5) it directly measures a flux;
(6) it is a kinetic technique, that is dependent on the deployment time and can thus be
used for varying times; and
(7) it is capable of speciation measurements, which is one of the main aspect being
explored in this study.
However, there are some aspects of DGT that could still be improved or developed
further.
Firstly, the Chelex 100 impregnated-polyacrylamide gel used, while proving to be
satisfactory for many studies, has a number of limitations for inexperienced users. The
Chelex 100 beads are aligned against the face of the gel, but it is sometimes difficult to tell
which face this is. If a binding gel is deployed upside down, then the diffusive path length
is increased to include some of the binding gel. if this happens the calculated solution
concentration will be underestimated 187. Furthermore this binding phase is not ideal
according to the assumptions implicit in the DGT equation. The Chelex 100 beads are not
continuous at the interface with the diffusive gel. Consequently not all binding will occur
right at the interface; some will occur at depth within the binding phase. This aspect will
produce a systematic error of about 5-10% underestimation of the solution concentration
and may also decrease the reproducibility of the results. Finally, the pattern of Chelex 100
(or other resins) within the binding gel is not fully reproducible. This leads to either
binding gel being thrown away or to a further increased variability of the results.
Each of these limitations could be overcome by development of new binding phases that
have a continuum of binding functional groups at each face; as required by the DGT
equation. This also removes the possibility of the binding phase being placed upside
37
Chapter 1
down. Some DGT studies have used colloidal sized micro-Chelex beads 151, which should
effectively overcome these limitations. However, this material is very expensive and has
not been used routinely with DGT deployments as yet. The current study will investigate
the development of materials for binding phases that more effectively meet the
conditions required by the DGT equation.
Another possible advancement of the DGT technique would involve the use of materials,
other than polyacrylamide gel for both the diffusive and binding phases. Acrylamide, the
monomer of polyacrylamide, is a suspected carcinogen and must be handled with care.
Polyacrylamide gel is also expensive to make, mainly due to the agarose-derived cross-
linker required. There is also some evidence that this cross-linker varies somewhat in
nature from batch to batch and there is currently only one supplier in the world. Because
of these reasons other materials will be investigated for use with DGT as part of this
study.
A final aspect of DGT that could be improved is to remove the need to use an estimated
correction factor to compensate for the fact that not all of the bound metal is released
during the elution step from the binding phase. To date only one study describes the
elution efficiencies for a range of metals 16. This step is also likely to decrease the
reproducibility of DGT given that 100% elution does not occur, and the correction factors
used are likely to be mean values. It would be more effective to use elution conditions
that were reproducible around 100%. Such an approach might also require the use of
binding phases from which metals are more easily removed, compared with the Chelex
100 binding phase. Another alternative is the use of a binding phase in which elution is
not necessary at all, i.e. a liquid binding phase. This approach is also considered in this
study.
38
Chapter 1
1.6. OBJECTIVES OF THIS STUDY
The aim of this work was to further develop the diffusive gradients in thin films (DGT)
technique capable of being used for the in situ measurements of trace elements in the
environment. The research had two main foci: the development of new DGT devices and
their evaluation. The following have been investigated in this thesis.
(1) Develop new DGT devices, particularly with new binding phases, to overcome the
limitations with the previous DGT as described above. These new binding phases need to
behave in a more ideal manner (i.e. with uniform binding occurring only at the interface
with the diffusive gel) and should be easier to handle and make. Ideally, it would be better
that the interface is between a solid and a liquid. This idea induces the use of a solution as
a binding phase along with the use of a membrane as a diffusive layer, which makes it
possible to eliminate the involvement of the polyacrylamide gel. To achieve these
objectives, a number of strategies, including syntheses of new hydrogels and applications
of new type of binding phases, were to be used in DGT sensor development and new
concept evaluation. Most importantly, these new DGT sensors with varying binding
properties of binding phases and diffusive properties of diffusive layer have differing
capacities of measuring trace metal species in waters.
(2) Investigate properties of the new binding phases and the new diffusive layer to
study the suitability of the phases for DGT use. These need to be done under varying
conditions.
(3) Deploy the newly developed DGT sensors in controlled laboratory conditions to
validate the agreement between the DGT response and theoretical prediction, and in a
39
Chapter 1
number of well selected natural water sites with compositions of varying metal ions and
binding ligands to test their ability for speciation measurements of trace metals in natural
waters.
Inevitably, this course of study was a multidisciplinary effort, with the various practical
requirements being documented in Chapter 2. These requirements included the design of
new DGT systems reflecting the DGT objectives; the design of new DGT devices suitable
for the new DGT systems; the syntheses and characterisation of new hydrogels with
properties for DGT use; the preparation of new binding phases and new diffusive layers;
the fabrication of DGT devices and application in waters; and the fabrication of cells for
diffusion coefficient measurements and dialysis purification. A synopsis of the research
carried out in each of the remaining chapters is described below.
Chapter 3 discusses the development of a new homogeneous binding hydrogel,
synthesised by converting the polyacrylamide (PAM) diffusive hydrogel used in DGT to a
binding hydrogel of poly(acrylamide-co-acrylic acid) copolymer hydrogel (PAM-PAA).
The specific objectives for this part of work were:
(1) to optimise synthesis conditions of the binding gel;
(2) to investigate the binding properties of the new binding phase under varying
conditions of pH, ionic strength, and time;
(3) to demonstrate the suitability and advantages of the new binding phase for DGT
use;
40
Chapter 1
This chapter aims to develop a new range of binding phases for DGT, i.e. binding phases
prepared by chemically immobilisation of binding functional groups on the hydrogel
backbone.
In order to develop a method for synthesising the homogeneous binding hydrogels, the
synthesis of the poly(acrylamidoglycolic acid-co-acrylamide) (PAAG-PAM) with
carboxylic binding functional groups is described as an example of a methodology
(Chapter 4).
Chapter 5 discusses the employment of a commercially available cellulose phosphate ion
exchange membrane (P81) as a new DGT binding phase. This development aims to
demonstrate a possibility of using non-gel based DGT binding phase.
Followed with the development of the new DGT solid binding phase, to further improve
the binding interface, the invention of application of a poly(4-styrenesulfonate) (PSS)
aqueous solution as a binding phase is discussed in Chapter 6. The aims of this chapter
are:
(1) to demonstrate the feasibility of use of a liquid (non-solid) binding phase for DGT;
(2) to study the application of cellulose dialysis membrane as a diffusive layer;
(3) to investigate the diffusion properties of the diffusion layer and binding properties
of the binding phase;
In Chapter 7, the performance of the liquid binding phase DGT is further discussed. To
study the capability of this new DGT device for speciation measurement of metals, a
computer program, stability constant database, were to be used to calculate free metal
fractions for comparison with the DGT results. The objectives of this chapter include,
41
Chapter 1
validation of this DGT device for the measurement of DGT labile metal in solutions
containing varying complexing ligands and its application in natural waters.
To evaluate and compare the new binding phases developed in previous chapters, Chapter
8 describes the use of the new binding phases and new diffusive layer in DGT application,
which include the deployment of the new DGT devices developed in previous chapters in
solutions containing varying complexing ligands at laboratory conditions and in natural
waters with varying compositions.
In summary, the overall objectives of this study are to develop new range of DGT binding
phases. These binding phases improve the binding interface which is important for
applying DGT equation. The use of the new binding phases and new diffusive layer in
DGT improve DGT technique as a tool for metal detection in waters to provide important
information on metal bioavailability.
42
Chapter 2
Chapter 2 Experimental and Methodology
43
Chapter 2
2.1. INTRODUCTION
This chapter gives a brief description of the general experimental methods used in the current
study. More detailed descriptions of experimental procedures, including those developed for
this study, will be given in the relevant chapters related to the research described in that
chapter.
2.2. REAGENTS AND SOLUTIONS
2.2.1. Chemicals and Materials
All reagents used in the study were of AR grade purity, unless otherwise stated. The 40%
acrylamide monomer aqueous solution, ammonium persulphate and N,N,N',N'-
tetramethylethylenediamine (TEMED) were supplied by Bio-Rad, Australia. The 2%
agarose-derived cross-linker solution was obtained from DGT Research Ltd., Lancaster
University, UK. The acrylamidoglycolic acid monohydrate and poly(4-styrenesulfonate) of
average molecular weight 70,000 were supplied by Aldrich, Australia. The cellulose nitrate
and cellulose phosphate (Whatman P81) membrane were supplied by Whatman International
Ltd., UK. The cellulose dialysis membrane with molecular weight cut-off (MWCO) 12,000
Daltons was purchased from Sigma, Australia. The piston designed gel based DGT holders
were obtained from DGT Research Ltd., Lancaster University, UK.
44
Chapter 2
Suprapur HNO3 (Merck) was used for the preparation of DGT elution and standard solution.
AR grade HNO3 was used to prepare 1:10 HNO3 acid baths for the cleaning of all plasticware
used.
2.2.2. Solutions
2.2.2.1. Solutions for Polyacrylamide Gel Preparation
All solutions were prepared with deionised water (18 MΩ cm), as follows:
(i) 10% ammonium persulphate solution was freshly made before being used for the
preparation of polyacrylamide gel.
(ii) The 2% agarose-derived cross-linker solution and 40% acrylamide solution were used
as purchased.
(iii) The polyacrylamide gel stock solution was made by thoroughly mixing 18.75 ml of
40% acrylamide monomer (Bio-Rad), 7.50 ml of 2% agarose-derived cross-linker
(DGT Research Ltd., Lancaster University, UK) and 23.75 ml of deionised water
(Milli-Q).
2.2.2.2. Standard Solutions for Calibration of Measurements
All 1000 ppm stock solutions of copper, cadmium, potassium, sodium, calcium, magnesium,
nickel, zinc and manganese were prepared by weighing the required amounts of the
appropriate salt (Aldrich) preserved by acidification to pH 2 with HNO3 (Suprapur) and
dissolving it in deionised water. The stock solutions were all stored in polyethylene bottles
45
Chapter 2
and kept in the dark. The standard solutions were prepared from the stock solutions by serial
dilutions.
2.2.2.3. Synthetic Lake Water for Laboratory Evaluation of DGT
Synthetic lake water (Windermere, Lake District, UK) 152 with composition of [Mg2+] = 40.5
-µM; [Ca2+] = 157 µM; [Na+] = 202 µM; [K+] = 17 µM; [Cl-] = 242 µM; [NO3 ] = 25 µM;
[SO42-] = 85.5 µM was prepared by weighing the required amounts of the appropriate salt and
dissolving in 25.0 l of deionised water according to the procedure of Chang 152. The
concentration of each salt in the final dilution and quantity required for the concentrated stock
solutions are shown in Table 2.1. Composite stock solutions I and III were prepared at 1000
times the final concentrations required in the synthetic lake water, while solution II was made
up at 10 times the final concentration required. Additionally 0.89 g of CaCO3 was added to
25.0 l of deionised water and bubbled with CO2 for 8 h to ensure dissolution. The appropriate
volumes of solutions I and III were then added to solution II, e.g. for 25.0 l of synthetic lake
water, 25.0 ml of stock solution I, 2.50 l of stock solution II and 25.0 ml of stock solution III
were mixed with 25.0 l of Deionised water. Air was bubbled through the mixed solution for
one day to equilibrate it with the atmosphere. The pH of the final solution was approximately
7. The calculated and analysed compositions of the synthetic lake water are shown in Table
2.2.
Solutions containing Cu2+ or Cd2+ were prepared by adding specific amounts of the salts in
the synthetic lake water solution (as made above).
46
Chapter 2
Table 2.1 Synthetic lake water stock solution compositions
Stock Chemicals Final dilution Concentration of salt Concentration
solution (µeq l-1) used to make stock factor
solutions (g l-1)
I MgCl2⋅6H2O 84 8.5 ×1000
CaCl2⋅6H2O 162 17.7
Ca(NO3)2⋅4H2O 34 4.1
II CaCO3 71 0.036 ×10
III Na2SO4 191 13.6 ×1000
KHCO3 20 2.0
NaHCO3 9 0.76
Although, the concentrations of metal ions in the solution can be calculated from the dilution
of the known mass of salts added to the solution, this calculation does not take into account
the proportions taken up by the DGT devices, nor any surface sorption or precipitation
reactions, either of which could reduce the metal concentrations. Any evaporation during the
course of the experiment can also increase the concentrations relative to the calculated values.
Because of these unknown factors, the metal concentrations in the solution were measured
independently using inductively coupled plasma - mass spectrometry (ICPMS). Aliquots of
5.0 ml of solution were withdrawn for analysis at the same time as the devices were extracted.
47
Chapter 2
Table 2.2 The composition of Windermere Lake Water 188
Measured Concentrations Concentrations Expected Concentrations in Natural in Synthetic Lake Water from Preparing Synthetic Lake Water (µmol l-1)Ions Lake Water (µmol l-1(µmol l-1)
Mg2+ 41
Ca2+ 135
Na+ 202
K+ 21
Cl+ 246
-NO3 35
SO42- 88
)
42 40.5
133.5 157
200 202
20 17
246 242
34 25
95.5 85.5
2.3. PROCEDURES
2.3.1. Preparation of Diffusive Gel
The diffusive gel – polyacrylamide (PAM) – was prepared with acrylamide, agarose derived
cross-linker (DGT Research Ltd., UK), ammonium persulphate and N,N,N',N'-
tetramethylethylenediamine (TEMED). A stock solution comprising 18.75 ml of 40%
acrylamide monomer (Bio-Rad), 7.50 ml of 2% agarose-derived cross-linker (DGT Research
Ltd., Lancaster University, UK) and 23.75 ml of deionised water (Milli-Q) was mixed
thoroughly.
48
14
Chapter 2
Polymerisation was induced by adding 70 µl of freshly prepared 10% (w/w) ammonium
persulphate (Bio-Rad) solution and 25 µl of 99% N,N,N',N'-tetramethylethylenediamine
(TEMED) (Bio-Rad) to the 10.0 ml of monomer stock solution. The solution was gently
mixed and immediately pipetted into a mould comprising two slightly offset, clean glass
plates (12 cm × 12 cm) separated by an inert U-shaped plastic spacer of known thickness
(0.25 mm) and held firmly together with clips. The mould was then incubated at 40 ± 2oC for
1 h to allow the polymerisation to occur and the resulting PAM hydrogel to set. The hydrogel
was then hydrated in deionised water for at least 24 h with the water being changed at least
three times to remove any unreacted reagents. The PAM sheets were then stored in 0.1 M
NaNO3 prior to use.
2.3.2. Preparation of Chelex 100 Binding Gel
The Chelex 100 resin embedded polyacrylamide hydrogel was prepared according to Davison
. Firstly, the resin was soaked in Milli Q water, then the excessive water was removed with
a clean tissue. Then 10 ml of the gel solution (acrylamide solution containing the cross-
linker) used for preparing the diffusive gel was mixed thoroughly with 2 g (wet weight) of
Chelex-100 (100-200 mesh) to create a stable suspension. Sufficient resin (about 0.2 g wet
weight per millilitre) should be used to ensure that the resin density on the gel surface is
maximal without affecting the casting or the setting of the gel. Polymerisation and gelation
were induced by the addition of 60 µl of ammonium persulphate solution and 20 µl of
TEMED. The casting and rehydration procedures described above (for the preparation of the
diffusive gel) were then carried out. The typical resin-gel thickness was 0.4 mm after
hydration. The binding gel was stored in pure water (milli-Q).
49
Chapter 2
2.3.3. Characterisation of the Structure and Composition of Binding Hydrogels
The FTIR spectra of hydrogels were obtained using a Perkin Elmer FTIR Series 1000FTIR
spectrophotometer to determine the change in the functional groups present. Disks of the gels
were stretched out to make very thin films (a few µm), dried in the air and placed directly in
the instrument. Each spectrum was collected by accumulating five scans at a resolution of
eight wave numbers in the wavelength range of 4000 – 400 cm-1.
The elemental compositions of the hydrogels were determined by elemental analysis on a
Carlo Erba 1106 Elemental Analyser. The samples (~ 5 mg) were air dried before analysis.
2.3.4. Assembling and Disassembling the Gel Based DGT Devices
The gel based DGT devices were designed based a simple piston design commercially
available from DGT Research, Ltd, Lancaster University, UK (Figure 2.1) 16. It consisted of
a backing cylinder and a front cap with a 2.0 cm diameter window. The gel sheets described
above were cut into discs of 4.9 cm2 and assembled by placing the appropriate binding gel,
the diffusion gel and a 100 µm thick 0.45 µm pore size cellulose nitrate membrane filter (0.45
µm, Whatman), in order, on the top of the backing cylinder before firmly pressing down the
front cap to form a tight seal. The membrane filter effectively extends the diffusive layer and
protects the gel from particles and biological films in natural waters 15. It is essential that
there are no trapped air bubbles to impede the diffusion. The diffusive gels were conditioned
in an electrolyte solution, such as NaNO3 (0.01-0.1 M) prior to deployment to prevent the
possibility of a junction potential across the gel which would affect diffusion 154.
50
Chapter 2
After deployment, the diffusive gel was peeled off and the binding gel was soaked in 5 ml of
2 M HNO3 shaking well, overnight. The acid solution was then analysed for metal ion
content by FAAS after the appropriate dilution.
r
Outer Sleeve with 2.0 cm Diameter WindowPiston
Diffusive GelBinding Layer
Membrane Filte
Figure 2.1 Schematic representation of plastic DGT holder based on a simple piston design.
2.3.5. Measurement of Diffusion Coefficient in Diffusive Layer
Two types of diffusive membranes were used, a commercial and well-characterized dialysis
membrane and a carefully produced gel-membrane. In both cases, the diffusion of metal ions
across the membranes was experimentally calibrated to correct any factors that may affect the
diffusion. The diffusion coefficients, D, of Cd2+ and Cu2+ ions in the diffusive layer
(hydrogel or dialysis membrane) were determined using a specially designed diffusion cell
147, as shown in Figure 2.2.
The diffusion medium, a polyacrylamide hydrogel of known thickness (∆g) was sealed in
between the two compartments of the diffusion cell. A 1.4 cm diameter area of the gel was
exposed to the solution through the circular opening between the two compartments. One
51
Chapter 2
compartment (compartment A) initially contained a solution of 50.0 ml of 10 ppm Cd2+ or
Cu2+ prepared in synthetic lake water. The other compartment (compartment B) initially
contained a 50.0 ml solution of the same matrix ions as compartment A. Each compartment
was mixed well with an overhead stirrer. 4.50 ml aliquots of solution were taken from
compartment B and 0.200 ml from compartment A, (accompanying the addition of the same
volumes of the two initial solutions to both compartments) at 10 min. intervals for 70 or 80
min. Concentrations of Cd2+ and Cu2+ in the samples were measured using FAAS. The
replacement of the withdrawn samples with the original matrix solution diluted the solution in
both compartments. The effect of the sampling on the concentration of compartments A and
B was corrected for, based on the sample analysis for the gel case.
Stirring motors
Spacers
Stirrers
A B
Clamps
Diff
usiv
e la
yer
Openings for sampling
Figure 2.2 Cross section through a diaphragm diffusion cell.
52
Chapter 2
The diffusion coefficients were calculated from the slope of a linear plot of the measured
mass passing through the membrane, M, versus the product of time, t, and ∆C, the corrected
concentration difference of Cd2+ or Cu2+ between the two compartments during the diffusing
time period using the following equation:
DAM = ( )∆Ct (2.1)∆g
DAslope = , where A and ∆g are known. ∆g
2.4. INSTRUMENTATION
2.4.1. Atomic Absorption Spectroscopy (AAS)
The flame atomic absorption spectrometer (FAAS) (SpectrAA-200, Varian) was used for the
measurement of the total metals in the samples 189. Analytical standards and blanks were
prepared in the same matrix as the samples and run before each batch of the sample runs. A
standard was run every 6 samples to ensure that there was no change in sensitivity of AAS
and that no evaporation of the sample occurred. 5.0 ml samples were used in the
measurement.
The analytical errors were determined by replication of the blanks 190 and the data were
interpreted by the statistical methods given by Wilson 191. The detection limit, defined as
4.653σw, where σw is the standard deviation of the blanks (n = 15), was found to be 6.3×10-6
mol l-1 for Cu, 1.8×10-6 mol l-1 for Cd, 7.5×10-6 mol l-1 for Na, 5.8×10-7 mol l-1 for K, 3.7×10-7
mol l-1 for Mg and 6.6×10-6 mol l-1 for Ca with an air/acetylene flame. 53
Chapter 2
2.4.2. Measurement of Metal Concentrations in a Solution Containing PSS
The concentrations of metal-PSS complexes were determined by a flame atomic absorption
spectrometer (FAAS) (SpectrAA-200, Varian), according to the standard guidelines of the
manufacturers. The calibration curves were obtained by plotting the apparent concentrations
of the standard solutions containing PSS of the same amount as in the diluted samples 192.
The instrument sensitivities were 5.5×10-7 mole l-1 for Cu and 1.7×10-7 mole l-1 for Cd with
air/acetylene flame.
2.4.3. Solution pH Measurement
The pH of solutions was measured using a pH meter from Ionode PTY LTD, Australia. It
was calibrated with standard buffer solutions (Australian Chemical Reagents, Australia)
before use.
2.4.4. Solution Salinity Measurement
The salinity of the natural waters was measured using MC-84 Conductivity-Salinity-Temp.
Meter (TPS Pty Ltd, Australia), calibrated by manufacturers specified standard solutions (TPS
Pty Ltd, Australia).
54
Chapter 3
Chapter 3 Synthesis and Characterisation of a
Poly(acrylamide-co-acrylic acid) Copolymer
Hydrogel Based Binding Phase for the Diffusive
Gradients in Thin Films (DGT) Technique
55
Chapter 3
3.1. INTRODUCTION
The advantages and limitations of the DGT technique have been described and discussed
in Chapter 1. Most of the limitations arise from the use of the Chelex-100 impregnated
polyacrylamide gel binding phase. While most of these are overcome with user
experience, some of the limitations are inherent to the binding phase. The interface
between the binding phase containing Chelex 100 and the polyacrylamide diffusive layer
is not an ideal one. As the diagrams below indicate, the Chelex 100 binding gel does not
have a continuous interface with the diffusive gel. This discontinuance occurs, even if
each of the beads are packed as close together as possible, which may not actually be the
case (Figure 3.1).
Effective interface
Figure 3.1 Schematic diagram of Chlex 100 binding gel and its interface with diffusive gel.
56
Chapter 3
The influence of the discontinuous interface is to move the effective interface into the
binding phase. Even if the beads are perfectly aligned, the average interface will move
about 25 µm into the binding phase on average. This move will introduce a slight
systematic error in the DGT measurements of about 3%, which then underestimates the
concentration calculated. The interface will also not be truly two-dimensional, possibly
increasing the variation of results obtained. Consequently, there is a need to develop new
binding phases for use with the DGT technique. These new binding phases should
overcome the limitations, described here and in the Chapter 1, whilest maintaining all of
the advantages inherent to DGT. This chapter, and the next three, will describe studies
into different strategies to develop new binding phases. These strategies include
introducing functional groups to the surface of the polyacrylamide gel, which are then able
to bind the trace metals. Such a binding phase is likely to be an ideal phase, according to
the assumptions implicit in the use of the DGT equation. Two main approaches can be
used to introduce these functional groups: derivatization of the polyacrylamide hydrogel;
or use of a copolymer derived from acrylamide and another monomer that has a suitable
functional group and which will form a copolymer with acrylamide. Both approaches are
described in this and the following chapter, respectively.
Another strategy (Chapter 5) for introducing new binding phases is to use a non-gel based
membrane as the binding phase. Today, there are many commercially available chelating
or ion exchange membranes that can bind trace metals (Introduction to Chapter 5). These
introduce new advantages to DGT, such as re-use of the binding phase.
A final strategy for introducing new binding phases is to remove the need to use
polyacrylamide at all, either as a binding phase or diffusive layer. A range of other
57
Chapter 3
membranes is investigated as diffusive layers, along with soluble polymers with functional
groups able to bind trace metals.
Each of these strategies to develop new binding phases is expected to lead to different
functional groups with differing binding strengths. These binding phases can measure
quite different trace metal species, and thus this aspect is investigated for each of the
binding phases developed here.
This chapter focuses on the development of a polyacrylamide hydrogel with a
homogeneous and dense distribution of the functional groups able to bind trace metals.
Through chemical reactions it is possible for the functional groups that are capable of
binding metal ions, such as amine 193, amidoxime 194, dithizone 177, carboxylic acid 195, and
phosphorus 196, to be covalently immobilised on a hydrogel network backbone. There are
some well known polymer hydrogels, such as polyacrylamide, poly(ethylene glycol),
poly(vinyl alcohol) and poly(2-hydroxyethyl methacrylate), which can be chosen as
polymerisation reaction skeletons.
Also described in this chapter is the preparation for, and the characterisation of a
poly(acrylamide-co-acrylic acid) copolymer hydrogel (PAM-PAA) by the conversion of a
fraction of the amide groups on the polyacrylamide (PAM) gel backbone to acrylic acid.
Additionally, the ability of this copolymer hydrogel to bind various metal ions under a
range of conditions is examined, while the swelling properties of the new hydrogel are
also characterised. Finally the feasibility of using the new homogeneous copolymer
hydrogel for environmental analysis with DGT is investigated.
58
Chapter 3
3.2. EXPERIMENTAL
3.2.1. Preparation of the Poly(acrylamide-co-acrylic acid) Copolymer Hydrogel
The poly(acrylamide-co-acrylic acid) (PAM-PAA) copolymer hydrogel was prepared
directly from the PAM hydrogel with a partial hydrolysis reaction similar to that described
previously 197. However, in this work, the hydrolysis process was controlled by
equilibration reaction conditions and was undertaken on a different form of
polyacrylamide.
PAM hydrogel sheets were placed in 40 ml of 10% (w/v) NaOH solution 198, within a
sealed flask at 75 - 80oC for 5 h, during which the amide groups underwent a controlled
hydrolysis reaction. The ammonium gas given off could not leave the flask, however,
which meant that the reaction proceeded to equilibrium and did not need to be regulated
by time in order to obtain a reproducible degree of hydrolysis. The PAM-PAA hydrogel
was then thoroughly washed with deionised water and rehydrated for 24 h. The sheets
were then soaked in 0.10 M HNO3 for another 24 h, followed by a thorough washing with
deionised water and storage in 0.1 M NaNO3 at 4oC.
3.2.2. Characterisation of the Structure and Composition of the PAM-PAA
Hydrogels
The FTIR spectra of the PAM and PAM-PAA hydrogels were obtained using a FTIR
spectrophotometer (Perkin Elmer FTIR Series 1000) to determine the changes in the
functional groups present (Chapter 2).
Further, the elemental composition of the PAM and PAM-PAA hydrogels were
determined by elemental analysis on a Carlo Erba 1106 Elemental Analyser (Chapter 2).
59
Chapter 3
3.2.3. Swelling Properties of the PAM-PAA Hydrogel
The weight of each dried PAM-PAA hydrogel disk was measured before the swelling test
experiment. These disks were then soaked in solutions with pH ranging from 1.8 to 9.0
and a constant ionic strength (equivalent to 0.010 M NaCl) at room temperature (23ºC) for
24 h. The solution pH was adjusted by adding hydrochloric acid or sodium hydroxide,
while the constant ionic strength was maintained by the addition of an appropriate amount
of NaCl. The weights of each of the hydrated (swelled) samples were measured after the
hydrogels had equilibrated in the test solution. Each measurement was performed in
triplicate. The equilibrium swelling ratios were calculated, based on equation 3.1 199:
qw = ms / md, (3.1)
where qw, is the equilibrium swelling ratio, and ms and md are the weights of the hydrogel
disks in the swollen (hydrated) and the dry state, respectively. The effect of the ionic
strength on the hydrogel swelling behaviour was tested in the same manner by varying the
NaNO3 concentrations from 1.0 × 10-5 M to 1.0 M at pH 7.0.
3.2.4. Metal Binding Properties of the PAM-PAA Hydrogel
The binding properties of the PAM-PAA hydrogel to metals were investigated using
individual (non-competitive binding) and mixed (competitive binding) metal ion solutions.
The binding capacities of a range of individual metal ions, including Cd2+, Cu2+, K+, Na+,
Ca2+ and Mg2+ were examined. The experiments were carried out by immersing a PAM
PAA hydrogel in a solution containing 7.5 µM of a metal ion at pH 7.0 for 24 h, with
constant stirring. The metal solutions were sampled and preserved before and after the
60
Chapter 3
hydrogels were deployed. Each measurement was undertaken in triplicate, as were those
described below.
The influence of the ionic strength on the binding capacity of the copolymer hydrogel was
tested by varying the NaNO3 electrolytes from 1.0 × 10-5 M to 0.10 M for metal ion
concentrations of 7.5 µM at pH 7.0 for 24 h. To evaluate the influence of pH on the
hydrogel binding capacity, the pH of the uptake solution was varied from 1 to 12, as
described above.
The competitive binding of metal ions was also investigated by immersing a PAM-PAA
hydrogel disk in a solution containing 7.5 µM of each metal ion at pH 7.0 for 24 h.
The binding capacity is defined as the maximum metal ion uptake measured at the
saturated part of the binding curve and is determined by measuring the disappearance of
metal ion in the uptake solution.
3.2.5. Elution and Analysis of the Metal Ions
The elution efficiency for the PAM-PAA hydrogel was measured for all metals of interest.
The solutions, with the same concentrations as in the uptake experiments, were used. The
initial and final concentrations were measured for the uptake solutions to determine the
amount of metal ion removed. The elution efficiency was calculated by comparing this
value with the amount of metal ion eluted and measured. The elution of the metals from
the copolymer hydrogel was carried out in 5.0 ml of 2.0 M HNO3 for 24 h. The elution
solution was then diluted to an appropriate concentration with deionised water. The metal
ion concentrations were determined using a flame atomic absorption spectrometer
61
Chapter 3
(FAAS). The metal concentrations of the various test solutions were also measured by
FAAS after preservation with HNO3 to pH < 2.
3.2.6. Validation of the PAM-PAA Hydrogel for Use with DGT
The applicability of the new binding phase for DGT analysis was validated according to
the DGT equation (equation 1.6) 14, 21, 24.
The PAM-PAA hydrogel binding phase and the PAM hydrogel diffusive layer were
placed, in a layered manner, into the traditional DGT device and covered with a 0.45 µm
pore size nitrocellulose membrane 24. The DGT assemblies were deployed in duplicate for
different periods ranging from 25 to 150 h, in a well-stirred solution of 0.75 µM Cd2+ in
synthetic lake water (Windermere, Lake District, UK) 152. These experiments were set up
so that the Cd2+ concentration was maintained at the initial value throughout the
deployment period. The mass of Cd2+ in the binding gel and the concentration of Cd2+ in
the solution before and after exposure to the DGT devices were measured according to the
procedure described above.
3.3. RESULTS AND DISCUSSION
3.3.1. Preparation of the Poly(acrylamide-co-acrylic acid) Copolymer Hydrogel
The poly(acrylamide-co-acrylic acid) copolymer hydrogel (PAM-PAA) was prepared
from the polyacrylamide (PAM) hydrogel via a hydrolysis reaction. The reaction was
carried out in a strong alkaline solution to convert the amide groups on the PAM gel
backbone into carboxylic groups. As the hydrolysis reaction proceeded, the PAM units
were converted into polyacrylic acid (PAA) units and ammonia was produced. Under the
62
Chapter 3
experimental conditions used, the hydrolysis of the amide groups could not proceed to
completion because the released ammonia remained within the sealed flask, but rather
proceeded to equilibrium instead. Thus, the end product of the reaction was the PAM
PAA copolymer:
H2NC O + n OH-m
CH CH2 CH
C
CH2
OHO
CH
C OH2N
CH2 xrq
As the hydrolysis reaction proceeded, the gel was observed to swell and become fragile.
Further swelling of the PAM-PAA occurred when the hydrogel was hydrated in deionised
water. As the swollen hydrogel had poor mechanical strength, placing the PAM-PAA
hydrogels in a 0.1 M solution of HNO3 for 24 h reduced the swelling and improved the
mechanical strength. Treating the hydrogel with the HNO3 solution also removed all the
un-reacted alkali and products, such as ammonia. The hydrogels produced in this manner
were found to be quite sticky, which made handling and deployment difficult. This
stickiness was removed by storing the hydrogel in 0.1 M NaNO3 prior to use. After this
pre-treatment the hydrogel was easy to handle at pH values appropriate for deployment in
natural waters. These observations suggested that the cross-linker was not significantly
degraded during the hydrolysis reaction.
3.3.2. Composition of the PAM-PAA Copolymer Hydrogel
The FTIR and elemental microanalysis were carried out to ensure that the reaction had
proceeded as expected and to elucidate the composition of the new copolymer hydrogel.
The FTIR spectrum of the PAM hydrogel had absorption peaks at 3365.73, 1654.55,
1451.21, 1325.44 and 634.31 cm-1 (Figure 3.2), which was consistent with the standard
infrared spectrum of polyacrylamide 200. The spectrum of the PAM-PAA copolymer
63
Chapter 3
showed peaks at 3401.41, 2756.22, 1702.51, 1247.41 and 634.50 cm-1. The absorption
peak at 1247.41 cm-1 (Figure 3.3) suggested a syndiotactic-rich structure of PAM-PAA 201
203, while peaks indicative of atactic-rich 201 and isotactic forms 203 of polyacrylic acid
were not observed. The band at 1702.51 cm-1 for PAM-PAA gel was due to the carbonyl
component of the carboxylic acid group. The band for commercial polyacrylic acid
occured at 1715 cm-1 201. The carbonyl absorption bands of the remaining amide groups
overlapped with the carboxylic absorption bands. The broad absorption bands from
3401.41 cm-1 to 2956.22 cm-1 were assigned to the –OH from the carboxylic group 200.
Based on the above information, the general composition of the PAM-PAA copolymer
was proposed to be:
CH
C
CH2
OHO
CH
C OH2N
CH2 xrq
T%
98.7
80
60
40
20
3 3 6 5 . 73 1 6 5 4 . 55
1 3 2 5 . 44
6 3 4 . 31 1 4 5 1 . 21
4000 3000 2000 1500 1000 400 -1cm
Figure 3.2 FTIR Spectrum of PAM hydrogel recorded as a film. 64
Chapter 3
107.6
1 0 0
9 0
8 0
T%
7 0 2956.22
6 0 3401.41 1247.41
1702.51 5 0
4 0 0 0 3 0 0 0 2 0 0 0 1 5 0 0 1 0 0 0 6 0 0 -1cm
Figure 3.3 FTIR Spectrum of PAM-PAA hydrogel recorded as a film.
Table 3.1 shows the results of the elemental microanalysis. The molar ratio of nitrogen to
carbon in the PAM gel (1:3.04) was close to that of the acrylamide monomer (H2C =
CHCONH2, 1:3). The nitrogen to carbon ratio decreased to 1:8.38, after the hydrolysis
reaction, to form the PAM-PAA copolymer. This meant that the molar ratio of acrylamide
to acrylic acid in the copolymer repeat units was 1:1.8, suggesting that most of the
polymer is made of repeat units of acrylic acid units in a ratio of approximately 2:1 with
the acrylamide units, i.e. q ≈ 2r.
Table 3.1 Elemental microanalysis of the PAM and PAM-PAA hydrogels
% N % C % H
PAM-PAA 3.99±0.05 28.65±0.09 5.17±0.08
PAM 16.1±0.03 42.0±0.05 7.22±0.09
65
Chapter 3
3.3.3. PAM-PAA Hydrogel Swelling Properties
The swelling properties of hydrogels are of interest in many applications 204, 205. The
characteristic hydrogel swelling behaviour depends on the functional groups present. For
a given hydrogel, the degree of swelling usually depends on the pH and ionic strength of
the solution 199, 206-210. In using the PAM-PAA hydrogel as a binding phase for DGT
applications, the swelling properties of the gel have to be characterised because the pore
size of the gel network, and the volume of the hydrogel, depend upon its swelling
properties. These properties, in turn, affect the ease of handling of the hydrogel and other
practical considerations for its use with the DGT technique.
The effect of pH on the swelling properties of the PAM-PAA hydrogel is shown in Figure
3.4. The swelling mostly occurred from pH 3 to 6. At pH > 6 the change in the
equilibrium swelling ratio with pH was slight. A fully hydrated gel disk was 120 times
heavier than a dried gel disk for pH > 6. At pH < 3 the degree of swelling was very low.
When the hydration was carried out in a solution of pH < 3, the carboxylic acid groups on
the copolymer backbone were converted to the protonated acid form. A low qw (Figure
3.4) indicated that the water content for the acid form of the hydrogel was low. When the
solution pH was above 6, the carboxylic groups on the copolymer backbone were
converted to the salt (basic) form and the maximum degree of swelling was achieved.
Within the pH range 3 to 6, an almost linear relationship between the swelling ratio and
pH was observed. Within this pH range, the acid and salt forms of the carboxylic groups
on the copolymer backbone were both present. The exact ratio of the acid and salt forms
of the carboxylic groups was determined by the equilibrium pH under constant ionic
66
Chapter 3
strength. The presence of both acid and salt forms of the carboxylic groups on the
copolymer backbone constituted a “hydrogel buffer” system. Under such conditions the
Henderson-Hasselbalch equation 3.2 applies:
pH = pK + log ]ylic group of carbox [base form (3.2)a ]ylic group of carbox [acid form
Since the ratio of the acid and base forms of the carboxylic acid groups were determined
by pH, and directly proportional to the swelling ratio, the concentration of the acid and the
base forms of the carboxylic acid groups were equal, at the point where the swelling ratio
equals half of the maximum value. Figure 3.4 shows that, at this point, pH ≈ 4.5.
According to equation 3.2, the pKa for the PAM-PAA copolymer was, therefore, 4.5. This
number agreed with a previously reported pKa value for a polyacrylamide-polyacrylic acid
copolymer 210.
Figure 3.5 shows the dependence of the swelling of the PAM-PAA copolymer on the ionic
strength at a given pH. When the pH of the solution was fixed at 7.0, an increase in the
ionic strength resulted in a decrease in the swelling ratio. The most significant effect on
the swelling ratio of the gel was observed when the NaNO3 concentration ranged between
10-3 M and 10-1 M. The ionic strength affected the swelling ratio by changing the charge
distribution on the surface of the gel network. At high ionic strength, such as with the
NaNO3 concentrations above 0.1 M, the solution produced a strong “charge screening
effect” on the hydrogel network, in which the electrostatic repulsion between adjacent
strands of polymer were minimised, causing the strands to move closer together and the
polymer to have less capacity to absorb water 211. As a result, the degree of hydration and
swelling was reduced 199, 211.
67
Chapter 3
Swel
ling
Rat
io (q
w )
120
80
40
0 0 2 4 6 8 10
pH
Figure 3.4 Effect of pH on the equilibrium swelling ratio (qw) of the PAM-PAA gel (n = 3). The experiments were carried out at room temperature (23oC) and with a constant ionic concentration equivalent to 0.010 M NaCl.
For application as a binding gel with DGT, the swelling properties of PAM-PAA need to
be minimised. The DGT devices with PAM-PAA would ideally be deployed in
environments with a pH greater than 6 and with a fairly stable ionic strength. Fortunately,
these conditions are met by most natural waters. The PAM-PAA hydrogels would also
need to be pretreated by storing them in a solution with similar ionic strength to the
environment in which it was to be deployed, taking care not to introduce contamination.
This procedure is recommended for the diffusion gels currently used with DGT 14.
68
Chapter 3
300
Swel
ling
Rat
io (q
w ) 200
100
0 -7 -5 -3 -1 1
Log [NaNO3]
Figure 3.5 Effect of ionic strength on equilibrium swelling ratio (qw) of the PAMPAA gel (n = 3). The experiments were carried out at room temperature (23oC) and at pH 7.0.
3.3.4. Metal Binding Properties of the PAM-PAA Hydrogel
The solution forms of poly(acrylic acid-co-polyacryamide) copolymers have been
investigated previously for their metal retention properties 212. The binding properties of
the PAM-PAA copolymer hydrogel for metal ions were investigated, initially, in a non
competitive manner. Metal uptake curves for Cu2+ and Cd2+ are given in Figure 3.6. In
both cases, a linear relationship between the metal ion uptake and the uptake time were
observed initially, before saturation at about 1.59 µmoles cm-2 for Cu2+ and at about 1.56
µmoles cm-2 for Cd2+. The linear rate of uptake was greater for Cu2+ (0.088 µmoles cm-2
h-1) than for Cd2+ (0.057 µmoles cm-2 h-1).
69
Chapter 3
2
1.5
Upt
ake
(µm
ole
cm-2
)
1
0.5
0 0 10 20 30 40 50
Cd Cu
Time (h)
Figure 3.6 Effect of immersion time on Cu2+ and Cd2+ ion uptake (n = 3). The experiments were carried out at room temperature (23oC) using gel disks with 4.9 cm2 surface area and 0.040 cm thickness.
Table 3.2 Non-competitive metal Ion binding capacity of PAM-PAA gel (n = 3)
Cu2+ Cd2+ K+ Na+ Ca2+ Mg2+
Binding Capacity (µmole cm -2)
1.59 1.56 0.550 0.670 0.490 0.530
Elution 1.51 1.50 0.530 0.730 0.470 0.530 (µmole cm -2)
Elution Efficiency 95.0 96.2 98.0 109 95.9 100 (%)
Ca
The individual metal ion binding capacity in these sample solutions were calculated from
the maximum metal ion uptake (saturation) and the results are summarised in Table 3.2.
The binding capacities observed were in the order of Cu2+ > Cd2+ >> Na+ > K+ > Mg2+ >
2+. This order indicates that the affinity of the PAM-PAA hydrogel toward the binding
70
214
Chapter 3
of the transition metal ions, such as Cu2+ and Cd2+, was stronger than that towards alkali or
alkaline earth metal ions.
From a mechanistic viewpoint, the order of increasing binding capacities does not exhibit
classical ion exchange behaviour, where the affinity is proportional to the ionic charge
only. The copolymer does, however, exhibit an order of affinity in accord with the
increasing acidity and polarizability of the divalent metal ions measured, similar to that
described by the Irving-Williams theory 213. The monovalent alkali metal ions have a
higher capacity than the divalent alkaline earth metal ions due to the influence of the ion
exchange behaviour and the greater concentrations required to balance the charge with the
copolymer hydrogel. It is likely that the Cd2+ and Cu2+ also have increased affinity, due to
the coordination (formation of inner sphere complexes) with the carboxylic acid groups
. Previous studies 154 have shown that the amide group in polyacrylamide does not
interact significantly with the metal ions. The amide groups may, however, play a
secondary role in the complexation of the transition metals alongside the carboxylic acid
groups.
The most common binding phase previously used with the DGT technique was Chelex
100 resin encapsulated in polyacrylamide. The reported Cd2+ binding capacity for such a
binding phase was 1.1 µmole cm-2 16, while the maximum binding capacity of the PAM
PAA hydrogel obtained was 1.59 µmole cm-2 (Table 3.2). This capacity suggests that the
PAM-PAA hydrogel has a density of binding sites comparable with the Chelex-100
binding gel.
In general, the pH affects the binding capacity by shifting the equilibrium of the
coordination reaction and/or ion exchange ability in two ways: changing the concentration
71
Chapter 3
of the active ligands and/or the concentration of the soluble metal ions. The effect of the
solution pH on the binding capacity is shown in Figure 3.7. A very low binding capacity
was observed when the solution pH was below 5. This decrease of capacity was because
the protonated forms of the carboxylic acid groups are much less capable of forming B
indi
ng C
apac
ity (µ
mol
e cm
-2)
complexes than the salt form 215. When the solution pH was greater than 5, the salt form
of the carboxylic groups dominated and the maximum binding capacity was achieved.
The binding capacity decrease, at very high pH, was due to a significant change in the
speciation of the metal ions from the free metal ion to the metal hydroxide, which is much
less soluble 216. The optimum solution pH range for the PAM-PAA binding gels was
greater than 5 on this basis, but greater than 6 based on the swelling dependence on pH.
This ideal pH range for metal ion uptake by PAM-PAA made it suitable for DGT
applications in natural waters.
2
1.6
1.2
0.8
0.4
0 0 5 10
pH
Cd Cu
Figure 3.7 Effect of pH on the binding capacity of the PAM-PAA gel for Cu2+ and Cd2+ (n = 3). The experiments were carried out at room temperature (23oC) using gel disks with 4.9 cm2 surface area and 0.04 cm thickness and an immersion time of 24 h.
72
Chapter 3
An important requirement for a binding phase with the DGT technique was the efficient
elution of bound metal ions from the binding phase. The weak binding of the protonated
hydrogel implies that the bound metal ions can be readily eluted from the gel in acidic
media. The high efficiency of the acid elution is demonstrated by the recovery data for a
range of metals in Table 3.2.
The effect of the ionic strength on the binding capacities of Cd2+ and Cu2+ is shown in
Figure 3.8. It was found that the binding capacities decreased almost linearly with a
logarithmic increase in the NaNO3 concentration. This decrease of binding strength with
increasing ionic strength demonstrates that the complexes formed between the transition
metal ions and the PAM-PAA copolymer were weak. Therefore, acid-base interactions
would be the dominant interaction type with ion exchange behaviour also important for
the non-transition metal ions. The binding capacities, even at these high ionic strengths,
were sufficient for the gel to be used to bind Cu2+ and Cd2+ from natural waters.
The binding capacities of the PAM-PAA copolymer hydrogel for metals under conditions
of direct competitive uptake were also investigated (Table 3.3). The binding capacities for
Cu2+ and Cd2+ dropped from 1.59 µmole cm-2 and 1.56 µmole cm-2 for non-competitive
binding to 0.923 µmole cm-2 and 0.574 µmole cm-2, respectively, with competitive
binding. When the solution contains more than one type of metal ion, the binding capacity
for each metal ion depends on its ability to compete with others for the available binding
sites. This is a greater decrease than expected for an ionic strength effect (Figure 3.8),
indicating a direct competition between the two transition metals (and, to a lesser extent,
the alkali and alkali earth metal ions). The results in Table 3.3 suggests that the PAM
PAA hydrogel binds with Cu2+ more selectively than with Cd2+.
73
Chapter 3
0
2
Cd CuB
indi
ng C
apac
ity (µ
mol
e cm
-2 )
0.4
0.8
1.2
1.6
-6 -4 -2 0
Log [NaNO3]
Figure 3.8 Effect of ionic strength on the binding capacity of the PAM-PAA gel for Cd2+ and Cu2+ (n = 3). The experiments were carried out at room temperature (23oC) using gel disks with 4.9 cm2 surface area and 0.04 cm thickness and an immersion time of 24 h.
Table 3.3 Competitive metal Ion binding capacity of PAM-PAA gel (n = 3)
Cu2+ Cd2+ K+ Na+ Ca2+ Mg2+
Binding Capacity 0.923 0.574 0.019 0.018 0.024 0.024(µmole cm-2)
3.3.5. Application of the PAM-PAA Hydrogel as a Binding Phase with DGT
The use of the PAM-PAA hydrogel as a binding phase for DGT, was validated using the
linear relationship between M and t, derived from the DGT equation 15, as shown in Figure
3.9. The mass of Cd2+ accumulated on the hydrogel increased linearly with time over a
74
Chapter 3
deployment period of up to 150 h with r2 = 0.994. The theoretical line is also shown in
Figure 3.9 and was calculated using the known parameters associated with the DGT
equation. The line of best fit for the correlation indicated a recovery of 99.0% when
compared with the theoretical line. A similar r2 value and recovery percentage was M
ass
(µg)
obtained with Cu2+ indicating that the PAM-PAA copolymer is suitable for use as a
binding phase with DGT. For the AAS instrument, used to measure the concentration in
the eluents in this experiment with detection limits of 1.8×10-6 mol l-1 for Cd, the detection
limits for DGT after 100 h of deployments, were 1.5×10-7 mol l-1 for Cd when 5 ml
solutions were used for the AAS analysis.
5
4
3
2
1
0 0 50 100 150
Time (h)
R2 = 0.9938
CdFigure 3.9 Mass vs. time validation of the PAM-PAA hydrogel for use with DGT for
2+. The experiments were carried out in a well-stirred solution made of the synthetic lake water matrix containing 0.75 µM Cd2+, with ∆g = 0.040 cm and A = 3.1 cm2. The dash line is the theoretical line calculated using standard DGT equation.
75
Chapter 3
6
5
4
Mas
s (µ
g)
3
2
1
0 0 50 100 150 200
R2 = 0.9798
Time (h)
CuFigure 3.10 Mass vs. time validation of the PAM-PAA hydrogel for use with DGT for
2+. The experiments were carried out in a well-stirred solution made of the synthetic lake water matrix containing 0.80 µM Cu2+, with ∆g = 0.040 cm and A = 3.1 cm2. The dash line is the theoretical line calculated using standard DGT equation.
3.4. CONCLUSIONS
A novel poly(acrylamide-co-acrylic acid) copolymer hydrogel (PAM-PAA) was found to
be selective for the transition metals Cu2+ and Cd2+, over alkali and alkaline earth metals,
and also suitable for use with the diffusive gradients in thin-films technique (DGT) used
for the environmental analysis of most natural waters. The PAM-PAA hydrogel is a
single-phase homogeneous binding gel which, therefore, overcomes many of the
limitations associated with the conventional Chelex 100 resin based gel. The PAM-PAA
hydrogel was prepared by the controlled hydrolysis of polyacrylamide hydrogel in alkali
solution at mild conditions. The gel can potentially be mass produced due to the facile
synthesis process. The FTIR and elemental analysis indicated that the composition of the
76
Chapter 3
copolymer was approximately 2 units of acrylic acid for every unit of acrylamide in a
syndiotactic-rich structure (evenly distribution of functional groups). The equilibrium
degree of swelling (qw) of the PAM-PAA hydrogel increased to 120 times that of the dried
state at pH > 6, and was relatively stable at higher pHs. This swelling property limited its
application in DGT. A dramatic increase or decrease of the gel volume may cause the
breakage of upper layer in DGT devices or the incomplete coverage of the diffusive layer.
The pKa was found to be about 4.5. At a pH > 5, most carboxylic acid groups were in the
salt form and had a greater capacity to bind the transition metals Cu2+ (1.59 µmoles cm-2)
and Cd2+ (1.56 µmoles cm-2). The degree of swelling and the binding capacity were also
influenced by the ionic strength. With these swelling properties the gels needed to be
stored in appropriate conditions (NaNO3 solution) before use with DGT to avoid swelling
and stickiness during deployment. The optimum deployment conditions were at pH > 6
under conditions of relatively stable ionic strength.
77
Chapter 4
Chapter 4 Preparation and Characterisation of a
Poly(acrylamidoglycolic acid-co-acrylamide)
Hydrogel as a New DGT Binding Phase for
Determination of Trace Metals
78
Chapter 4
4.1. INTRODUCTION
The previous chapter describes the preparation of a new binding phase for the
measurement of trace metals with DGT, where the polyacrylamide hydrogel was
converted to a poly(acrylamide-co-acrylic acid) copolymer. Another strategy to produce
copolymers with suitable functional groups is to use different starting monomers. Such
copolymers can be synthesised by photo-induced polymerisation 217, electrolytic
polymerisation 218, catalyst induced polymerisation 219, interpolymer complex 220 and the
modification of natural products 221. Theoretically, any monomers with binding functional
groups, such as amine 193, amidoxime 194, dithizone 177, carboxylic acid 195 and phosphorus
196, can be combined to form a copolymer suitable for use as a binding gel for DGT.
In this chapter the synthesis and characterisation of a poly(acrylamidoglycolic acid-co-
acrylamide) (PAAG-PAM) copolymer hydrogel is described. This copolymer also
contains carboxylic acid functional groups. The copolymer is characterised to determine
its structure, metal binding properties under various conditions, and whether it is suitable
for use as a binding phase for accumulating trace metals with DGT.
4.2. EXPERIMENTAL
4.2.1. Preparation of Poly(acrylamidoglycolic acid-co-acrylamide) Hydrogel
Poly(acrylamidoglycolic acid-co-acrylamide) (PAAG-PAM) hydrogel was prepared from
a monomer solution containing 2.23 g of acrylamidoglycolic acid monohydrate (AAGA)
(Aldrich), added to 10.0 ml of deionised water (Milli-Q), followed the addition of 1.5 ml
of 30% NaOH with constant stirring to bring the pH close to 7. The solution was then 79
Chapter 4
titrated with 1 M NaOH to pH = 7.0. The volume of the solution was made up to 15.0 ml
with deionised water (Milli-Q) and thoroughly mixed. The PAAG-PAM hydrogel was
prepared by adding 780 µl of 40% acrylamide (AAm), 800 µl of 2% agarose-derived
cross-linker (DGT Research Ltd, Lancaster, UK), 70 µl of freshly made 10% (w/w)
ammonium persulphate (Bio-Rad) solution and 30 µl of 99% N,N,N',N'-
tetramethylethylenediamine (TEMED) (Bio-Rad) to the AAGA solution. This formula
gave a molar ratio of 3:1 for AAGA and AAm, which was subsequently found to be the
optimum ratio for handling purposes and for the metal binding capacity. The well-mixed
solution was immediately pipetted into a suitable mould comprising two slightly offset,
clean glass plates, separated by an inert plastic spacer of known thickness (0.040 cm) and
held firmly together with clips. The mould was then incubated at 60 ± 2oC for 3 h. The
set gel sheets were then hydrated in deionised water (Milli-Q) for 24 h, with the water
being replenished several times. They were then soaked in 10% HNO3 for another 24 h
(to remove any metal contamination within the gel) prior to being washed again with the
water. The gel sheets were cut into disks of 4.9 cm2 and stored in 0.1 M NaNO3, which
facilitated subsequent handling. This storage solution contained several grams of Chelex
20 resin to reduce trace metal impurities.
4.2.2. Characterisation of the PAAG-PAM Hydrogel
The FTIR spectra of the PAAG-PAM hydrogel were obtained using a Perkin Elmer Series
1000 FTIR spectrophotometer (see Chapter 2 for conditions used).
The elemental composition of the PAAG-PAM gel was determined by elemental
microanalysis on a Carlo Erba 1106 Elemental Analyser (see Chapter 2 for conditions
used).
80
Chapter 4
4.2.3. Swelling Properties of the PAAG-PAM Hydrogel
The hydrogel disks were soaked in solutions of differing pH at room temperature (23oC)
for 24 h. The pH value of each solution was obtained by adding either hydrochloric acid
or sodium hydroxide. After the hydrogel disks had been equilibrated in each solution, the
degree of swelling was measured by accurately weighing each disk. For the measurement
of the equilibrium swelling ratio, qw, the disks were weighed both in their hydrated and
dried states. The dried gel disks were obtained by drying them in an oven at 40 °C to a
constant weight over 48 hours. The equilibrium swelling ratio 199 was calculated from
equation 3.1,
qw = ms / md
where ms and md are the weights of the hydrogel disks in the swollen/hydrated state and
dried state, respectively. The experiments on the swelling properties of the hydrogel were
also carried out as a function of the electrolyte concentration, with NaNO3 ranging from
10 µM to 0.10 M.
4.2.4. Metal Binding Properties of the PAAG-PAM Hydrogel
The binding properties of the PAAG-PAM hydrogel for metal ions Cu2+, Cd2+, K+, Na+,
Ca2+ and Mg2+, were tested under non-competitive conditions by immersing a gel disk in a
solution containing a metal ion concentration of 1.0 mM at pH 6 – 7, for several time
periods up to 24 h. This experiment enabled the measurement of the binding capacity and
also the rate of binding for each metal, provided that the saturation occurred within the 24
h period. The amount of metal ion bound in the gel was eluted by soaking the gel in 5.0
ml of 2 M HNO3 for 24 h before being diluted to an appropriate concentration with
81
Chapter 4
deionised water and measured with a flame atomic absorption spectrometer (FAAS). The
metal concentrations of the tested solutions were also measured by FAAS before and after
gel immersion.
To study the competitive binding of the gel, a disk was immersed in a stirred solution
containing Cu2+, Cd2+, K+, Na+, Ca2+ and Mg2+, each at 17.8 µN concentration. Elution
was performed as described above. The effects of various conditions on the gel binding
for Cu2+ and Cd2+ were studied by changing the time of exposure (1 - 24 h), pH (from 0.2
to 12) and NaNO3 concentration (10 µM - 1 M).
4.2.5. DGT Performance
A validation test for the new DGT binding phase was undertaken according to procedures
described previously 16, 147. The PAAG-PAM hydrogel binding phase, the PAM hydrogel
diffusive layer (see Chapter 2 for preparation) and a wet 100 µm pore size cellulose nitrate
membrane filter, as a protective layer, were placed, in that order, into a DGT assembly 16.
Eight DGT assemblies were exposed to a well-stirred solution of 0.79 µM of Cu2+ over
various periods of time, up to 145 h, in synthetic lake water (Windermere, Lake District,
UK). A sufficient volume of solution was provided to ensure that the depletion of Cu2+ by
the DGT assemblies was negligible. The mass of Cu2+ accumulated in the PAAG-PAM
gel was measured by FAAS. The elution was carried out as described above.
The performance of the DGT measurement was evaluated in two ways. Firstly, from
equation 3.1, a linear relationship was expected between measured M and deployment
time, t, up to the capacity of the binding gel, if the DGT device was acting according to
theory. Secondly, a line of best fit for M vs. t was compared with a theoretical line
82
3
Chapter 4
derived from the actual solution concentration, C and equation 3.1. A comparison of the
gradients of these lines provided an estimation of the recovery of the measurement.
Recoveries of > 90% are desirable with DGT.
4.2.6. Preparation of Polyacrylamide Hydrogel
Polyacrylamide (PAM) hydrogels were prepared according to previously described
procedures (Chapter 2) 153, 156.
4.3. RESULTS AND DISCUSSION
4.3.1. Structure and Composition of the PAAG-PAM Hydrogel
The PAAG-PAM hydrogel was prepared by copolymerising AAGA with AAm at a 3:1
molar ratio in the presence of the initiators ammonium persulphate and N,N,N',N'-
tetramethylethylenediamine (TEMED) according to the following reaction:
OH
CH
C O
a CH
CO 2
CH2CH2 nbCH
C O
OH
CH2 CH
CO 2
CH2
+ (NH4)2S2O8
60oC
NHHOOCCHNH HOOCCHNH NHTEMED
The FTIR and elemental analysis were undertaken to determine the composition and
structure (i.e. a and b values) of the copolymer gel. The FTIR spectrum of PAAG-PAM
with the characteristic peaks is shown in Figure 4.1. The Peaks appear at 1651.67 cm-1
(C=O in the carboxylic and amide groups), 3443.37 cm-1 (NH and OH in carboxylic
groups and amide groups), and 1096.28 cm-1 (the secondary alcohol groups), 2922.29 cm-1
(carboxylic groups) and 1384.07 cm-1 (aminoacid) 222. These data confirmed that the
PAAG-PAM copolymer hydrogel was formed with functional groups from both
acrylamide and AAGA.
83
Chapter 4
T %
3443.37
2922.29
2352.64
1651.67 1384.07
1096.28
650.96
50
54
58
62
65
4000.0 3000 2000 15000 1000 400 -1cm
Figure 4.1 FTIR spectrum of PAAG-PAM hydrogel in KBr pellet with the main diagnostic peaks highlighted.
Table 4.1 Microelemental analysis results of PAAG-PAM
C% H% N%
Experimental values 36.96±0.57 5.96±0.09 10.88±0.16
Theoretical* values 40.91 4.92 10.61
* Based on the monomer ratio of AAGA to AAm of 3:1.
The elemental analysis of PAAG-PAM gel was performed to determine the values of a
and b. The elemental analysis indicated a C:N:H ratio of 4:1:0.5 (Table 4.1). The molar
ratio of AAGA and AAm in the PAAG-PAM gel, calculated from the carbon and nitrogen
stoichiometry, based on the data shown in Table 4.1, was approximately 3.53:1, or
approximately 7:2. This result indicated that the copolymerisation reaction was not
exactly complete, as some AAm monomers did not form part of the polymer and would
84
Chapter 4
have been removed during rinsing. The PAAG-PAM gel structure can therefore be
written as follows:
OH
HOOCCHNH C O O C NH2 Sw
ellin
g R
atio
( qw
) CH2 CH 7 CH2 CH
2 n
4.3.2. Swelling Properties of the PAAG-PAM Gel
Since the PAAG-PAM gel had carboxylic acid groups on the network chain, the degree of
swelling was expected to vary with the pH. Figure 4.2 shows the observed variation of the
gel swelling ratio, qw, with the pH at 23oC. The qw was strongly dependent on the pH, due
to the dissociation of the carboxylic group on the gel network. The highest degree of
swelling was reached at around pH 5.4. A similar swelling phenomenon has been
observed in other hydrogel work 207.
600
500
400
300
200
100
0 0 4 8 12
pH
Figure 4.2 Effect of pH on the equilibrium swelling ratio, qw, of the PAAG-PAM hydrogel; temperature 23oC.
85
Chapter 4
As shown in Figure 4.3, the swelling ratio of the PAAG-PAM gel decreased as the NaNO3
concentration increased. The increase of NaNO3 concentration tends to screen the Sw
ellin
g R
atio
( qw
) attraction between the polar water molecule and the polyelectrolyte gel, therefore,
decreasing the water content of the hydrogel 211.
600
400
200
0 -6 -5 -4 -3 -2 -1 0
Log [NaNO3]
Figure 4.3 Effect of ionic strength on the equilibrium swelling ratio, qw, of the PAAGPAM hydrogel; temperature 23oC, pH 7.0.
This dependence of the swelling of the hydrogel on the pH and ionic strength has
implications for its use as a binding phase for DGT. The gel will thus need to be stored in
a solution of similar pH and ionic strength to that in which the DGT assembly is to be
deployed to ensure that the swelling does not interfere with the measurement. This
swelling problem is also the case present with PAM/Chelex 100 resin-based binding gels.
86
Chapter 4
4.3.3. Metal Binding Properties of the PAAG-PAM Hydrogel
4.3.3.1. Non-competitive Binding Capacities
The binding properties of the PAAG-PAM hydrogel for metal ions were investigated
initially in a non-competitive manner. The non-competitive binding capacity for each
metal ion was calculated from the maximum metal ion uptake (saturation) within 24 h.
The results are summarised in Table 4.2. The binding capacities observed were in the
order of Cu2+ ≈ Cd2+ >> Na+ ≈ Mg2+ ≈ K+ ≈ Ca2+. This order indicated that the affinity of
the PAAG-PAM hydrogel towards the binding of the transition metal ions, such as Cu2+
(5.3 µmole cm-2) and Cd2+ (5.1 µmole cm-2), was stronger than that towards the alkali or
alkaline earth metal ions. This difference was due to the coordination bonds that formed
between these transition metals and the various ligands on the gel network 214.
Table 4.2 Non-competitive and competitive binding capacities (µmole cm-2) of various metals by PAAG-PAM hydrogel
Cu2+ Cd2+ K+ Na+ Ca2+ Mg2+
Non-competitive binding capacity 5.3 5.1 0.78 0.85 0.68 0.82
Competitive binding capacity 1.3 0.17 0.027 0.024 0.024 0.027
4.3.3.2. Competitive Binding Capacities
As there are many ions present in natural waters, it was necessary to collectively test the
competitive binding of metal ions to the PAAG-PAM hydrogel before it was used for
practical DGT analysis. Table 4.2 shows that the binding selectivity order was Cu2+ >>
87
Chapter 4
Cd2+ >> K+ ≈ Mg2+ ≈ Na+ ≈ Ca2+ when all the metal ions were present at the same
normality. These results indicated a much higher selectivity of the gel for Cu2+ (1.3 µmole
cm-2), compared to the other ions tested under competitive binding, including Cd2+ (0.17
µmole cm-2). This result was generally supported by the observations made of the change
in the metal binding capacity with increasing ionic strength (section 4.3.3.5). However, it
seems that the Cd2+ interaction is greatly reduced when Cu2+ is also present. The binding
capacity for Cu2+ was comparable to the capacities reported for the Chelex 100 binding
gel 16 previously used with the DGT technique.
4.3.3.3. Binding Rate
Cd
The metal uptake curves for the non-competitive binding of Cu2+ and Cd2+ are shown in
Figure 4.4. The initial concentrations of the metal ions in the aqueous phase were 1.0
mM. For both metals, a rapid initial rate of uptake was observed in the first two hours.
The linear rate of uptake during this time was 2.64 µmoles cm-2 h-1 for both the Cu2+ and
2+. The binding capacities were effectively reached within 6 h for each metal ion. The
binding rate observed here was approximately equivalent to the experimental data for the
binding kinetics of heavy metal ions by various sorbent systems in membrane or
microsphere forms (about 6 h) 216.
There were also several parameters which determined the binding rate, such as sorbent
structural properties (e.g. size, porosity, surface area), amount of sorbent, metal ion
properties (e.g. hydrated ionic radius), and initial concentration of metal ions 223. In the
case of a single disk of gel immersed in a solution, the binding rate also depended upon
how well the solution was stirred. However, the binding rate obtained with the PAAG
88
Chapter 4
PAM gel was deemed to be satisfactory for the application with DGT, as is confirmed in
section 4.3.4.
Upt
ake
(µm
ole
cm-2
) 6
5
4
3
2
1
0
Cu Cd
0 10 20 30
Time (h)
Figure 4.4 Uptake of Cu2+ and Cd2+ by the PAAG-PAM hydrogel at various times; temperature 23oC, pH 7.0. The metal uptake curves for the non-competitive binding of Cu2+ and Cd2+ are shown in Figure 4.4. The curve shown here represents one set of the experiments. The curves obtained from different experiments showed the same trend
4.3.3.4. Effect of pH on the Binding Capacity of Cu2+ and Cd2+
A change in the pH can influence the uptake of a metal by a complexing agent. In deed
the pH influences the transition metal speciation and solubility and the charge of the
binding functional groups 216, 224, 225. The proportion of the basic form of the glycolic acid
groups, the main binding site, also increases with an increase of pH. Figure 4.5 shows that
the binding capacity of ions first increased with increasing pH, due to a change in the ratio
between the basic and acidic form of the glycolic acid groups. Interestingly the pH 89
Chapter 4
influenced the uptake of Cd2+ and Cu2+ in different ways, with the Cu2+ taken up at lower
pH values (1.5-4.0) and the Cd2+ at slightly higher values (2.5-5.0). This binding
preference is further evidence for the selectivity of the PAAG-PAM hydrogel for Cu2+.
The binding capacities increased slightly at pH values > 5, until the uptake decreased, due
Upt
ake
(µm
ole
cm-2
) to metal hydroxide insolubility at pH > 9.
6
4
2
0 0 5 10
pH
Cu Cd
Figure 4.5 Effect of pH on the binding capacity of the PAAG-PAM hydrogel; temperature 23oC, time 24 h.
4.3.3.5. Effect of Electrolyte Concentration on the Binding Capacity of
Cu2+ and Cd2+
As natural waters have a range of ionic strengths, the binding behaviour of the PAAG
PAM gel to Cu2+ and Cd2+ was studied in aqueous solutions with NaNO3 concentrations
ranging from 10 µM to 0.10 M. Figure 4.6 shows that the binding of Cu2+ to the gel was
slightly stronger than that of Cd2+ at all electrolyte concentrations. In both cases, as
expected, the binding capacity decreased with an increase in ionic strength. Even at a
90
Chapter 4
concentration of 0.1 M NaNO3, the binding capacities obtained were still appropriate for
DGT applications.
6 U
ptak
e (µ
mol
e cm
-2)
4
2
0 -6 -4 -2 0
Cu Cd
Log [NaNO3]
Figure 4.6 Effect of electrolyte concentration on the binding capacity of the gel for Cu2+
and Cd2+. Temperature 23oC, pH 7.0, time 24 h.
4.3.4. Validation of Poly(AAGA-co AAm) as a Binding Phase for DGT Use
Figure 4.7 showed mass-time DGT curve. The data shown were values drawn from one
set of experimental data. Determination of the slope of DGT curve in such way is highly
reproducible and reliable The PAAG-PAM hydrogel was tested as a binding phase with
DGT for Cu2+, based on its selectivity for Cu2+ from the metal binding experiments above.
When the DGT assemblies were deployed, for time periods up to 150 h, the measured
mass (M) of Cu2+ in the gel increased linearly (R2 = 0.975) with time (t).
91
Chapter 4
This linear relationship indicates that the PAAG-PAM binding phase was capable of
reducing the Cu2+ ion concentration to zero at the interface between the binding and
diffusive layers. In addition, the data agreed well with the theoretical line calculated from
the DGT equation using the known concentration of Cu2+ in the experiment (0.79 µM in
synthetic lake water (Windermere)). A recovery of close to 100% was measured this way,
indicating that the diffusion coefficient (D) used was appropriate. For application in more
complex systems, with a range of species present, for each analyte, and each with their
own diffusion coefficient, the results can be interpreted as a flux or as an indicative
concentration value. This interpretation is an area requiring additional research.
µg)
R2
0
1
2
3
4
5
Mas
s (
= 0.9754
0 50 100 150 Time (h)
Figure 4.7 Accumulation mass vs. time response of DGT uptake for Cu2+ ion and theoretical response calculated from standard DGT equation using the solution concentration and other known parameters; ∆g = 0.36 mm, [Cu2+] =
20.79 µM, A = 4.9 cm2, D = 2.2×10-6 cm s-1 at 23 oC.
92
Chapter 4
The two positive outcomes, above, confirm that the PAAG-PAM hydrogel is suitable for
use as a binding phase for Cu2+ ions using the DGT technique. Indeed the results indicate
that the analyte concentration on the interface between the diffusion gel and the binding
gel phase was effectively reduced to zero during the deployment, a condition of applying
the DGT equation. The fact that the gel binding functional groups were evenly distributed
on the three dimensional hydrogel backbone, and the contact between the diffusion gels
and the binding phase would have been close to an ideal two dimensional phase, also
make it ideal for application to DGT.
4.4. CONCLUSIONS
A new copolymer PAAG-PAM was prepared with a 7:2 ratio of AAGA monomer units to
AAm monomer units. This polymer was found to bind Cu2+ ions selectively with a
binding capacity of 5.3 µmole.cm-2 for non-competitive uptake and 1.30 µmole.cm-2 for
competitive uptake with other metal ions. This binding capacity combined with rapid
uptake kinetics made the polymer suitable for use as a binding phase with the DGT
technique. This suitability was confirmed when a linear response was obtained for the
accumulated mass vs. the uptake time of the Cu2+ and a 95 - 100% recovery with the DGT
uptake experiment.
Similar swelling properties of this gel to PAM-PAA gel as described in Chapter 3 were
observed. When the gel contains a high percentage of water, it becomes fragile. Thus the
gel needs to be stored in a NaNO3 solution with similar ionic strength to the water solution
in which the DGT devices are going to be deployed, to minimise the degree to which the
gel size changes.
93
Chapter 5
Chapter 5 Application of a Cellulose Phosphate
Ion Exchange Membrane as a Binding Phase in the
Diffusive Gradients in Thin Films Technique
94
Chapter 5
5.1. INTRODUCTION
The development and evaluation of hydrogels, with homogeneous distribution of
functional groups as binding phases for DGT, are described in the previous two chapters.
Although some advantages of the gels were identified, there are still some limitations in
the use of these gel-based binding phases, due to the nature of the hydrogels. The gels can
be fragile and there is a need for them to be stored in solutions, such as NaNO3, to
minimise their tendency to swell. These features make handling the gels and the assembly
of the DGT devices more difficult. In addition, the gel-based binding phases are not
reusable, because the polyacrylamide degrades during the elution process.
In this chapter, a commercially available, solid-state ion-exchange membrane is proposed
as an alternative to the binding phases currently used with the DGT for the measurement
of trace metal species. There are many such membranes currently available, which made
by the addition of electrophilic functional groups (such as phosphoric acid 226, carboxyl
227, amidoxime 228, hydroxamic acid 229 and sulphonate and triazine 175, 230), to a backbone
membrane structure, such as cellulose. Cellulose phosphate membranes, in particular,
have been used for the binding metal ions and for the separation of trace metals 231, 232.
This material has excellent ion exchange properties, combined with a desirable
hydrophilic nature. The binding functional groups, which are chemically immobilised on
the cellulose backbone, provide good chemical stability and uniformity of coverage on all
surfaces of the membrane. The excellent mechanical strength and flexibility of the
material also makes it convenient for the handling and the preparation of the DGT
assembly. Furthermore, the ion-exchange properties of the membrane can be easily
regenerated under acidic conditions to allow for the reuse of the material as a binding
phase 233, 234 .
95
Chapter 5
A commercially available Whatman P81 cellulose phosphate ion exchange membrane
(P81) was selected as a test case to demonstrate the feasibility of the solid-state DGT
binding phase concept. The binding properties of the Whatman P81 cellulose phosphate
ion exchange membrane, for a range of metal ions under various conditions, were
systematically investigated. The performance of this new solid-state binding phase for
DGT applications was also evaluated.
5.2. EXPERIMENTAL
5.2.1. Cellulose Phosphate Membrane Pre-treatment
The cellulose phosphate membranes (P81), with a 25 mm diameter and a 0.20 mm
thickness, were purchased from Whatman International Ltd., UK and were used as the
binding phase for DGT. The Whatman P81 membrane is a strong cation exchange
membrane with a high ion exchange capacity of 18.0 µEq/cm2 (Whatman catalogue book).
The functional group responsible for binding metal ions is the ester-linked
orthophosphoric acid group 233 with Na+ counterions. In order to minimise any trace metal
ion contamination, the membranes used for all experiments were immersed in 10% HNO3
for 24 h before being thoroughly rinsed with, and stored in, deionised water (Milli-Q).
This process also served to pre-wet the membrane providing a desirable hydrophilic
surface to facilitate the construction of the DGT assembly.
5.2.2. Preparation of the Polyacrylamide Hydrogel
Polyacrylamide (PAM) was employed as the hydrogel diffusive layer in the DGT
assemblies and was prepared according to previously described procedures 147 (Chapter 2).
96
Chapter 5
5.2.3. Binding of Metal Ions to Cellulose Phosphate Membrane
The non-competitive binding capacities of a range of individual metal ions, including
Cu2+, Cd2+, Zn2+, Mn2+, Ni2+, K+, Na+, Ca2+ and Mg2+, were examined by immersing
cellulose phosphate membranes in a solution containing 1.1 mN of metal ions at pH 7.0
for 24 h with a constant rate of stirring. The competitive binding capacities of the same
ions were also measured by immersing the membranes in a solution containing 0.054 mN
for each of the above metal ions for 24 h with a constant rate of stirring. In both cases, the
metal ion concentrations of the solutions were measured against immersion time, using
flame atomic absorption spectrometry (FAAS) (SpectrAA-200, Varian). The mass uptake
by the membrane was also measured by FAAS after elution (as described below).
The effect of the initial metal ion concentration on the uptake was investigated by
immersing membranes in solutions ranging from 0.018 to 1.1 mM for Cd2+, and from
0.016 to 0.94 mM for Cu2+, with an immersion time of 24 h with stirring. The influence of
pH on the binding capacity was tested in the pH range of 0.5 to 12.1 for Cd2+ and 1.0 to
12.2 for Cu2+ respectively. The effect of ionic strength on the binding capacity was
carried out in solutions containing various concentrations of NaNO3 ranging from 1.0×10-5
to 1.0 M.
5.2.4. Elution and Analysis of Metal Ions
The elution of the metals from the cellulose phosphate was carried out in 5.0 ml of 2.0 M
HNO3 for 24 h, after which the elution solution was diluted to an appropriate
concentration with deionised water (Milli-Q). The metal ion concentrations were
97
Chapter 5
determined by FAAS, according to the guidelines of the manufacturer. The metal
concentrations of the various test solutions were also measured by FAAS after
preservation with HNO3 to pH < 2.
5.2.5. Assembly of DGT Devices
The DGT devices were assembled according to previously reported procedures 14, 16 with
cellulose phosphate membranes (P81) used as the binding phase (Chapter 2). The DGT
device consists of a backing support and a front cap with a 2.0 cm diameter window. The
binding phase was placed on the support (it does not matter which side is facing up) and
the polyacrylamide diffusive layer was placed on top of the membrane followed by the
cellulose nitrate covering layer. The DGT device was then sealed.
5.2.6. DGT Validation Experiments
From the DGT equation 3.1, a linear relationship between M and t was expected for any
given solution, with Cb and the other parameters kept constant. Confirmation of this
relationship has been used as a test for the feasibility of the new DGT devices. Indeed the
DGT devices were deployed in well-stirred sample solutions containing 0.80 µM Cu2+ or
0.45 µM Cd2+. The matrix for these experiments was synthetic lake water (Windermere,
Lake District, UK) (Chapter 2) 152. The masses of Cu2+ or Cd2+, accumulated by the
binding phase, were measured after elution, according to the procedure described above.
The concentrations of Cu2+ or Cd2+ in the deployment solution, before and after exposure
to the DGT devices, were also measured.
98
Chapter 5
5.2.7. Reuse of Binding Phase
The DGT validation experiments for the Cu2+ and Cd2+ were repeated with the binding
phases re-used up to four times. After each DGT experiment was completed, the binding
membrane was washed thoroughly with deionised water and then immersed in 2.0 M
HNO3 for 24 h to remove the un-eluted metal ions (if any) from the previous experiment.
The membrane was then soaked in deionised water for 24 h, with three changes of water
prior to reuse.
5.3. RESULTS AND DISCUSSION
5.3.1. Metal Ion Binding Properties
Zn
The metal ion uptake vs. time curves for Cd2+, Cu2+, Na+ and Mg2+ in Figure 5.1 show that
the amount of metal ion uptake increased rapidly, initially, before levelling off, indicating
that saturation had occurred. The saturation time observed was approximately 8 h for all
four metal ions shown in Figure 5.1. Similar behaviour was also observed for other metal
ions tested (i.e. Zn2+, Mn2+, Ni2+, K+ and Ca2+), with the maximum metal uptake values
(binding capacities) for all metals being derived from these curves (Table 5.1). These
binding capacities are comparable to the binding capacities of the Chelex 100-impregnated
polyacrylamide gel 16 widely used for metal measurements with DGT 14, 21, 22, 24. Indeed
the binding capacities for the metal ions investigated were, in order of decreasing strength,
2+ > Cu2+ > Cd2+ > Mn2+ > Ni2+ > Mg2+ > Ca2+ > K+ > Na+, indicating that the binding
capacities of the Whatman P81 membrane, for transition metal ions, were higher than that
for the alkali earth metal ions. It should also be noted that the binding capacities of all the
doubly charged metal ions were greater than were those of the singly charged ions, such as
K+ and Na+. This result is particularly interesting since the binding capacity of an ion
99
Chapter 5
exchange membrane is usually related to the number of available ion-exchange sites. For
this reason, the ion-exchange capacity of the membrane for a singly charged species
should be higher than that of a doubly charged species. The capacity trend obtained here
may be due to the fact that the affinity between the doubly charged ions and the membrane
is better than the singly charged alkali ions. In other words, the membrane binds the
doubly charged ions stronger than does the singly charged alkali ions. This preference
was demonstrated when the competitive ions were introduced.
µmol
e cm
-2 )
0
1
2
3
4
Cd Cu Na M g
Upt
ake
(
0 10 20 30 Time (h)
Figure 5.1 Effect of immersion time on the metal ion uptake by the Whatman P81 membrane binding phase at pH 7.0 for Cd2+, Cd2+, Na+ and Mg2+. Concentration of metal ions: 1.1 mN; Temperature: 23oC.
Table 5.2 shows the binding capacities obtained when all of the test ions were present in
the solution with the same concentration of 0.054 mN. Despite the fact that the binding
capacities of all ions were decreased under the competitive conditions, the selectivity
between the transition metal and the alkali metal ions, or between the alkali earth and the
alkali metal ions indicate that the binding strength was in the order of: transition metal
100
Chapter 5
ions > alkali earth ions > alkali ions. This order becomes more obvious with a comparison
of the capacity ratios shown in Table 5.1 with the selectivity data shown in Table 5.2.
Table 5.1 Binding capacity of P81membrane to various ions
Cu2+ Cd2+ Zn2+ Mn2+ Ni2+ Ca2+ Mg2+ K+ Na+
Uptake (µmole cm -2)
3.22 3.07 4.21 2.73 2.58 1.75 1.93 1.37 1.11
Capacity Ratio 1.00 0.95 1.3 0.85 0.80 0.54 0.60 0.43 0.35
Note: Capacity ratio was calculated based on the uptake value of Cu.
Table 5.2 The binding capacity of the Whatman P81 membrane for various metal ions under the competitive conditions
Cu2+ Cd2+ Zn2+ Mn2+ Ni2+ Ca2+ Mg2+ K+ Na+
Capacity (µmole cm -2)
0.88 0.88 0.86 0.82 0.35 0.20 0.20 0.071 0.069
Selectivity 1.0 1.0 0.98 0.93 0.40 0.23 0.23 0.081 0.078
Note: Selectivity was calculated based on the binding capacity of Cu.
The order of the selectivity and binding capacities suggests that the coordination (inner
sphere complexation) bonding between the transition metals and the membrane was the
dominant interaction for the ion exchange membrane. Further, the order of selectivity for
the transition metal ions did not conform exactly to the hard-soft acid-base theory or the
Irving-Williams series, suggesting a number of parameters were important, including the
morphologies of the gel 235. All the doubly charged metal ions had greater selectivity than
the singly charged metal ions (i.e. K+ and Na+) indicating that the classical ion exchange
interactions, where a charge was the most important factor, were not significant 235.
101
Chapter 5
The uptake of Cu2+ and Cd2+ ions were also investigated further. Figure 5.2 shows the
effect of the concentration on the uptake of Cu2+ and Cd2+. With a deployment time of 24
h, the amount of metal ion uptake increased, with an increase in concentration up to 0.50
mM. Above this concentration, the metal ion uptake levelled off and was almost C
apac
ity (µ
mol
e cm
-2)
independent of the metal ion concentration, indicating the maximum binding capacity of
the membrane.
4
3
2
1
0
Cd Cu
0 0.25 0.5 0.75 1 1.25
Concentration (mM)
Figure 5.2 Effect of Cd2+ and Cu2+ concentration on the binding capacity of the Whatman P81 membrane at pH 7.0. Deployment time: 24 h; Temperature: 23oC.
The pH of the solution also appeared to affect the chemical forms of both the test metal
ions and the functional groups of the ion exchange membrane. Indeed the phosphate
functional group can have a charge of 0, -1, -2 or -3, or some fractional value in between,
depending upon the solution pH. Figure 5.3 shows that at very low pH (pH < 1.8 for Cu2+
and pH < 1.0 for Cd2+), the membrane lost its ability to bind these metal ions. This
decrease of capacity was because at such a low pH the orthophosphoric acid (the major
102
Chapter 5
binding functional group of the membrane) existed predominantly in its acid form, which
is less capable of binding metal ions. As the pH increased, the binding capacity increased
and then saturated when the pH was greater than 4.0. This increase of capacity was due to
the increase in the basic forms of orthophosphoric acid in the membrane. This is probably C
apac
ity (µ
mol
e cm
-2)
the reason behind the preference for binding doubly charged metal ions (Table 5.1) by
complexation. A further increase to pH > 9 resulted in a decrease in the binding capacity
for both Cd2+ and Cu2+. This decrease of capacity was due to significant changes in the
speciation of the metal ions from the free metal ions to the metal hydroxide species, which
are much less soluble 216. The optimum solution pH range of the Whatman P81
membrane for binding metal ions was 4.0 < pH < 9.0, making it suitable for DGT
applications in natural waters.
3.5
2.5
1.5
0.5
-0.5 0 2 4 6 8 10 12
pH
Cd Cu
Figure 5.3 Effect of pH on the binding capacity of the Whatman P81 membrane for Cd2+
and Cu2+. Concentration of metal ion: 1.1 mN; Deployment time: 24 h; Temperature: 23oC.
103
Chapter 5
0
1
2
3
4
Cd Cu
(µm
ole
cm-2
)C
apac
ity
-6 -5 -4 -3 -2 -1 0 1
Log [NaNO3]
Figure 5.4 Effect of ionic strength on the binding capacity of the Whatman P81 membrane for Cd2+ and Cu2+ at pH 7.0. Concentration of metal ion: 1.1 mN; Deployment time: 24 h; Temperature: 23oC.
As natural waters have varying concentrations of major ions, the effect of the ionic
strength on the binding capacity was investigated (Figure 5.4). The ionic strength of the
solution was adjusted using NaNO3, with the concentrations ranging from 1.0 × 10-5 M to
1.0 M. The binding capacities of Cd2+ and Cu2+ decreased as the concentration of the
NaNO3 increased. When the concentration of the NaNO3 was below 10-4 M, the effect of
the ionic strength on the binding capacity was slight. At 10-2 M NaNO3, the binding
capacities of Cd2+ and Cu2+ decreased to 2.52 and 2.76 µmole cm-2, respectively. At
NaNO3 concentrations of 0.5 M, the binding capacities for Cu2+ and Cd2+ were 1.1 µmole
cm-2 and 1.90 µmole cm-2, respectively. These capacity values were still adequate for the
DGT applications in natural waters, given the low analyte concentrations typically present.
The binding capacity for Cu2+ decreased to 0.31 µmole cm-2 at a very high ionic strength
(1.0 M), but more than 60% of its maximum binding capacity for Cd2+ (1.8 µmole cm-2)
104
Chapter 5
was maintained. This result suggests that the application of the binding phase in DGT for
the measurement of Cd in seawater would be feasible. Consequently, the measurement of
copper and other elements in seawater should be further investigated.
5.3.2. Elution and Regeneration
Elution is an important step in the DGT measurement. In order to ensure the accuracy of
the measurement, high elution efficiency is required for the removal of analyte ions from
the binding phase. As demonstrated in Figure 5.3, the Whatman P81 membrane lost all its
binding capability at pH < 2. This property was utilised to elute the metal ions from the
membrane in a 2.0 M HNO3 solution, with high elution efficiencies being obtained under
these conditions (Table 5.3).
In order to evaluate whether the membrane binding phase was reusable, the effect of the
membrane regeneration (Section 5.2.8) on the binding capacity was investigated (Figure
5.5). It was found that less than 15% capacity was lost for both Cu2+ and Cd2+ after five
successive uses. The relatively high binding capacity observed after five successive uses
was considerably above the binding capacity required in most DGT applications which,
despite long deployment times, typically involve the determination of very low metal ion
concentrations 14. These data therefore suggest the possibility of the reuse of the binding
phase in DGT applications (Section 5.3.3).
Table 5.3 Elution efficiency of various metal ions
Cu2+ Cd2+ Zn2+ Mn2+ Ni2+ Ca2+ Mg2+ K+ Na+
Elution efficiency 97.8 101 97.9 100 101 97.1 96.9 98.5 97.3(%)
105
Chapter 5
3.5
3
2.5
2
Cap
acity
(µm
ole
cm-2
)
1.5
1
0.5
0 1 2 3 4 5
Number of Uses
Cd Cu
Figure 5.5 Effect of consecutive membrane regeneration on the binding capacity of Cd2+
and Cu2+ at pH 7.0. Concentration of metal ion: 1.1 mN; Deployment time: 24 h; Temperature: 23oC.
5.3.3. Evaluation for Use as a Binding Phase with DGT
The use of the cellulose phosphate membrane as a DGT binding phase was evaluated
using Cu2+ and Cd2+ as the test species in a synthetic lake (Windermere, UK) water 152.
Figure 5.6 shows the relationship between the mass of metal ions accumulated by the
binding phase (M) and the deployment time (t). Significant coefficients of the
determination, r2, were obtained from the regression lines for Cu2+ (r2 = 1.00, p = 0.000)
and Cd2+ (r2 = 0.985, p = 0.000). These results strongly validate the use of the Whatman
P81 membrane as a binding phase for DGT. Indeed the regression (solid) lines also
indicate high recoveries (103% for Cu2+ and 97% for Cd2+) when compared with the
theoretical (dashed) lines calculated from the DGT equation using the known experimental
parameters.
106
Chapter 5
0
2
4
6
(µg)
Mas
s C
d
0 50 100 150 200
(a)
Mas
s C
u (µ
g)
6
4
2
0
0 50 100 150 200
Time (h) (b)
Figure 5.6 Accumulated mass vs. deployment time curves for (a) Cd2+ and (b) Cu2+ in a well-stirred synthetic lake water (Windermere) at 23oC. The solid and the dashed lines represent respectively the regression line for the experimental data and the theoretical line estimated from the following parameters: Cb = 0.45 µmol/L of Cd2+ or 0.80 µmol/L of Cu2+; ∆g = 0.040 cm; D (Cd) =
2 22.1×10-6 cm s-1; D (Cu) = 2.2×10-6 cm s-1; A = 3.14 cm2.
107
Chapter 5
The laboratory conditions, where free ionic species dominate, are also a desirable
condition for the evaluation of DGT. The reproducibility was tested with nine replicate
measurements (Table 5.4). A relative standard deviation (rsd) of 4.9% and an average
recovery of 102% were found for Cu2+ and an rsd of 5.5% and an average recovery of
104% were found for Cd2+. The slightly high recoveries are likely due to a small error in
the diffusion coefficients estimated for the calculations. Nevertheless these results
confirm that the membrane meets the requirements of a DGT binding phase.
Table 5.4 Reproducibility and recovery data from DGT experiments
Experimental Trial
Cu2+
(µM)
Average Concentration (µM)
RSD
Recovery(%)
Cd2+
(µM)
Average Concentration (µM)
Relative Standard Deviation
Recovery (%)
1# 2# 3# 4# 5# 6# 7# 8# 9#
0.88 0.84 0.82 0.79 0.84 0.76 0.80 0.82 0.80
0.82
4.9%
110 105 103 99 105 95 100 103 100
0.46 0.51 0.50 0.48 0.47 0.47 0.47 0.46 0.43
0.47
5.5%
102 113 111 107 104 104 104 102 96
Note: The actual concentration (added concentration) was 0.80 µM for Cu2+ and 0.45 µM for Cd2+. The experiments were conducted at room temperature of 23°C.
The DGT performance, with the regenerated binding phases, was also investigated.
Figure 5.7 shows the M vs. t relationship for five consecutive uses of the binding phases at
different deployment times for the measurements of Cu2+ and Cd2+. It is readily apparent
that there was little or no degradation of the performance. The r2 values for Cu2+ were
108
Chapter 5
between 0.976 - 1.00 and for Cd2+ were between 0.979 - 0.993, all were significant (p <
0.05). A comparison of the regression with the theoretical lines gave average recoveries
of about 101% for Cu2+ and 98% for Cd2+. Therefore, the capability to reuse the Whatman
P81 membrane binding phases for at least four deployments was established. This reuse
of a DGT binding phase had not been reported before and this finding may lead to a
reduction in the costs of the measurements.
Other advantages of the cellulose phosphate membrane were observed during this study.
The binding phase was easy to use even by inexperienced analysts, overcoming some of
the problems highlighted in Chapter 1. The surface coverage of the orthophosphate
binding groups appears to be both even and high, probably due to the chemical preparation
of the membrane 233, when compared with the physical process used with DGT to date.
Consequently, analysts can obtain very good reproducibility of measurements (≤ 5%).
Additionally, there is no chance of gross errors of the sort outlined in Chapter 1 because
both surfaces of the membrane contain the binding functional groups. Further, the
membrane is mechanically more robust than the hydrogel based binding phases previously
used in DGT, making the handling and the assembly of DGT devices much easier.
Apart from its application for routine monitoring, this new binding phase will be a great
benefit to the application of DGT in sediment, especially where measurements are made at
high resolution 21, 151 and the binding phase handling becomes very problematical.
109
Chapter 5
6
5
4 M
ass
Cu
(µg)
M
ass
Cd
(µg)
3
2
1
0 0 50 100 150 200
Time (h)
5th 4th 3rd 2nd 1st
(a)
7
6
5
4
3
2
1
0
5th 4th 3rd 2nd 1st
0 50 100 150 200 Time (h)
(b)
Figure 5.7 Accumulated mass vs. deployment time curves with consecutively regenerated cellulose phosphate as the binding phase for (a) Cd2+ and (b) Cu2+ in a well-stirred synthetic lake water (Windermere) at 23oC. The solid lines represent the regression the theoretical lines estimated from the following parameters: Cb = 0.45 µmol/L of Cd2+ or 0.80 µmol/L of Cu2+; ∆g = 0.040 cm; D (Cd) =
2 22.1×10-6 cm s-1; D (Cu) = 2.2×10-6 cm s-1; A = 3.14 cm2.
110
Chapter 5
5.4. CONCLUSIONS
The Whatman P81 cellulose phosphate ion exchange membrane has been successfully
used as the binding phase for DGT applications. The performance of this new DGT
binding phase was demonstrated in the determination of Cu2+ and Cd2+ in a synthetic lake
water matrix, with high recovery. The ion exchange activity of the new binding phase can
be regenerated and, therefore, reuse of the binding phase in DGT applications is possible.
This reuse of the binding phase will lower the cost of DGT applications. The
polyacrylamide gel is expensive to make, due to the expense of the agarose derived cross
linker. The new binding phase exhibited excellent mechanical properties and overcame
many of the problems of the hydrogel based binding phases. Those problems include
fragility, caused handling difficulty; swelling or shrinking with the changes of pH or ionic
strength conditions, caused breakage of the diffusive gel or the incomplete coverage of
upper layers.
Perhaps the most significant aspect of this work is that it opens up the possibility of
employing a new range of binding phases in DGT analysis, i.e. binding phases not limited
to gel-based systems. There are also a myriad of other solid ion exchange membranes and
other binding materials available. This work has shown the feasibility of employing such
materials in the DGT technique. Minor limitations of this binding membrane may
include: limited capacity in some applications; the roughness of the solid surfaces making
an impact contact between the surfaces; and the need for elution procedures. In the next
chapter, the deployment of a liquid binding phase is introduced, which overcomes these
limitations.
111
Chapter 6
Chapter 6 Development of a New Generation
DGT Device Using a Solid Membrane Diffusive
Layer with a Liquid Binding Phase
112
Chapter 6
6.1. INTRODUCTION
This chapter describes the development of a binding phase, for use with DGT to measure
trace metals, according to the fourth strategy outlined in Section 3.1: the development of a
solution binding phase. Most binding phases described previously have used particles of a
solid binding material dispersed throughout a polyacrylamide hydrogel to accumulate the
analyte. In previous chapters (Chapters 3 and 4) the use of functionalised hydrogel
copolymers were described while Chapter 5 demonstrated the use of a solid state
membrane binding phase. Each of these binding phases was able to be used with the usual
polyacrylamide diffusive layer 15. However, the use of a solution binding phase has
required the development of a new diffusive layer.
A possible combination is the use of the water soluble poly(4-styrenesulfonate) (PSS) as
the binding material and a dialysis membrane as the diffusive layer. These materials have
been described previously for use in ultrafiltration to remove heavy metal ions from
aqueous solutions 236, 237 and the separation of ionic metal species from metals associated
with colloids 238. A dialysis membrane is capable of retaining the soluble PSS polymer as
well as metals complexed to the PSS. Free metal ions, simple inorganic complexes and
small complexes with soluble organic matter are able to pass through the dialysis
240 membrane 239, . These factors suggest that these materials would be able to be
combined to form a new type of DGT device.
The metal binding properties of the PSS solution were investigated as functions of ionic
strength, pH and electrolyte concentration. The stability constant for the binding of Cu2+
and Cd2+ was measured to determine the binding mechanism. The diffusional properties
of the dialysis membrane were also investigated, particularly with respect to the diffusion
113
Chapter 6
coefficients of metal ions within the membrane under various conditions. The new DGT
device was validated for use in DGT applications with particular emphasis on ensuring
that the assumptions of the DGT equation (as described in Chapter 1) were met.
6.2. EXPERIMENTAL
6.2.1. The DGT Device Using a Solution Binding Phase
Figure 6.1 is a cross-sectional schematic of the DGT device developed for use with a
solution-based binding phase. It consists of a polyethylene tube (1.4 cm diameter)
containing 2.0 ml of 0.020 M PSS solution. The tube is covered and clamped with a 5.0
cm diameter pretreated dialysis membrane acting as the diffusion layer. The device is
deployed with the dialysis membrane down to ensure appropriate contact with the binding
solution. Sections 6.2.2 and 6.2.4 describe the preparation and pre-treatment of the PSS
solution and the dialysis membrane.
Polypropylene Tube
PSS Aqueous Solution
Rubber Gasket
Clamp (Perspex)
Dialysis Membrane
Figure 6.1 Schematic representation of the new DGT device for use with the PSS solution binding phase.
114
Chapter 6
6.2.2. Preparation of the Dialysis Membrane
Cellulose acetate dialysis membranes (Sigma, Mw ca.12,000 or greater retain) were pre
treated by soaking in deionised water (Milli-Q) for 4 h to remove glycerin. They were
then washed with a 0.3% (w/v) solution of sodium sulfide (Sigma, Analytical grade,
98.0%) at 80oC for one minute, and washed again with hot deionised water (60oC) for 2
minutes; this process was followed by acidification with a 0.2% (v/v) solution of sulfuric
acid (BDH, Analytical grade, 98.0%) to remove the sulfur compounds. After a final rinse
with hot deionised water to remove the acid, the membranes were stored in deionised
water. After this process, the thickness of the dialysis membrane increased reproducibly
from 20 µm to 50 µm, as measured by an optical microscope.
6.2.3. Interaction of Cd2+ and Cu2+ with the Cellulose Dialysis Membrane
When considering whether the cellulose dialysis membrane was an appropriate material
for use as a diffusive layer in DGT, there was a need to ensure that there was a minimal
interaction between the ions of interest and the membrane itself. The interaction
experiment was carried out according to the following procedures: a 100 cm2 sheet of 50
µm thick pre-treated cellulose dialysis membrane was exposed to a stirred solution
containing 2.0 µM Cd2+ and Cu2+ for 24 h to accumulate the metal ions. The membrane
was then equilibrated with 1.0 ml of 1.0 M HNO3 (Suprapur, Merck) for 12 h (under
stirring) to elute the accumulated metal ions into solution. The concentration of the metal
ions in the elution solution was determined by FAAS. The concentrations of Cd2+ and
Cu2+ in the membrane were calculated, based on the metal ion concentration in the elution
solution. The experiments were performed in solutions of varying ionic strengths ranging
from 10 µM to 1.0 M NaNO3.
115
Chapter 6
6.2.4. Purification of Poly(4-styrenesulfonate)
The poly(4-styrenesulfonate) (PSS) employed had an average Mw ca. 70,000 (Aldrich).
51.5 g of PSS was dissolved in 200 mL deionised water by ultrasonication. The solution
was then transferred into a cellulose acetate dialysis bag (prepared as described in Section
6.2.2) and placed in deionised water for 72 h with the water frequently replenished. This
process effectively removed all of the low molecular weight PSS that could pass through
the dialysis membrane. The dialysed PSS was then filtered through a 0.45 µm pore size
cellulose nitrate filter membrane to remove any undissolved particles. After purification
the concentration of PSS was determined gravimetrically and a PSS stock solution of 0.50
M (concentration of sulfonate groups) was prepared.
6.2.5. Determination of Metal-PSS Concentrations
The concentrations of the metal and metal PSS complex solutions (after dilution) were
determined by flame atomic absorption spectrometry (FAAS) (SpectrAA-200, Varian),
after appropriate dilutions. The calibration solutions for the measurement of the metal-
PSS complexes were matrix-matched to the dilution factor 192. The method detection
limits were 5.3 × 10-7 mole l-1 for Cu and 8.1 × 10-8 mole l-1 for Cd.
For the FAAS instrument used to measure the metal concentrations in the PSS solution the
detection limit for DGT after 100 h of deployments was 3.1×10-9 mol l-1 for Cu and
9.0×10-10 mol l-1 for Cd when 5 ml PSS solutions were used for the FAAS analysis.
6.2.6. Optimisation of PSS Solution Concentration
The PSS concentration used in the binding phase was optimized using the same diffusion
cell as that used for the measurement of the diffusion coefficients. The experimental
116
Chapter 6
procedures are the same as detailed in section 2.3.5. Compartment B initially contained
50.0 ml of PSS solution, with concentrations varying from 0.0050 to 0.050 M, in synthetic
Windermere Lake water matrix. Compartment A contained 50.0 ml of 10 ppm Cd2+ or
Cu2+ in synthetic Windermere Lake water solution. The mass (M) of the metal that
diffused through the membrane of the exposed area (A), from compartment A to
compartment B, was measured by FAAS, being sampled at certain time intervals (t) from
both compartments. The fluxes (J) were calculated according to the equation J = M 23.At
Masses were calculated from concentrations measured according to Section 6.2.5.
6.2.7. Metal Binding Properties of the Poly(4-styrenesulfonate) Solution
The metal binding properties of PSS were investigated using the new DGT device shown
in Figure 6.1. A concentration series experiment was undertaken to determine that the
binding phase reached its capacity within 24 h. Concentrations above 2.0 mM were
required for both Cu2+ and Cd2+. Non-competitive binding experiments were carried out
in 2.5 meq l-1 solutions of Cd2+, Cu2+, Ca2+, Mg2+, K+ or Na+ (individually) at pH 7.0 for
24 h. All the salts used were of an analytical grade and were supplied by Sigma.
Competitive binding studies were undertaken in a solution containing all of the above
metal ions at 18 µeq l-1 concentration at pH = 7.0. The effects of the varying pH (0.2 to
11) and electrolyte concentration (10 µM to 1 M as NaNO3), on the binding of Cd2+ and
Cu2+ to 0.020 M PSS, were studied.
6.2.8. Determination of Stability Constant
The stability constants of the complexation reaction between PSS and Cd2+ and Cu2+ were
also estimated using the modified DGT devices. 2.0 mL of 0.10 mM PSS solutions were
placed within the DGT device and suspended in solutions of 0.0010, 0.0020, 0.0050,
117
Chapter 6
0.010, 0.020, 0.040 mM Cd2+ or Cu2+ solutions in 1 mM NaNO3 for 48 h to allow the
devices to reach equilibrium. The metal concentrations in the PSS solution, and those
remaining in the original solution, were measured. The stability constants and the
coordination numbers were calculated by the ultrafiltration approach, according to
procedures used by Juang et al. 241 and Samadfam et al. 242.
6.2.9. Measurement of Metal Diffusion Coefficients in the Dialysis Membrane
The diffusion coefficients, Dm, of Cd2+ and Cu2+ ions in the dialysis membrane were
determined using the specially designed diffusion cell with a disc of pretreated cellulose
dialysis membrane fitted between the compartments (Chapter 2, Figure 2.2).
Compartment B of the diffusion cell was filled with 50.0 ml receiving solution containing
0.020 M PSS in synthetic Windermere Lake water matrix. Compartment A of the
diffusion cell was filled with 50.0 ml of source solution containing 10.0 ppm Cd2+ or Cu2+
in synthetic Windermere Lake water matrix. The samples were taken from both the
compartments and were measured by FAAS (Section 6.2.5). The diffusion coefficients
were to be calculated according to the method described in Chapter 2.
6.2.10. Effect of Stirring Conditions on the DBL Layer
The diffusion cell used was the same as that used for the determination of the diffusion
coefficients. Compartment B of the cell was filled with 65.0 ml receiving solution
containing 0.020 M PSS and 0.10 M NaNO3. Compartment A of the diffusion cell was
filled with 65.0 ml source solution containing 10.0 ppm Cd2+ and 0.10 M NaNO3. Both
compartments were stirred using the same over head motor with the same speed (Figure
6.2). The samples were taken from both compartments within a 3 h time interval and the
Cd2+ concentrations were measured by FAAS (Section 6.2.5).
118
Chapter 6
12 mm
φ =8 mm
φ =1.5 mm
+ -
Figure 6.2 Schematic diagram of the over head motor used.
6.2.11. Validation of the New DGT Device
The DGT devices (Figure 6.1) were deployed in triplicate in a well-stirred solution of Cd2+
(0.40 µM) and Cu2+ (0.70 µM) over periods of time from 3 to 200 h in synthetic lake
water (Windermere) (Section 2.2.2.3). A sufficient volume of the sample solution was
used to ensure that the depletion of Cd2+ and Cu2+, by the DGT devices, was negligible.
The Cu2+ and Cd2+ uptake by DGT was also validated, in this way, in solutions ranging
from 0 to 1.0 M NaNO3. The devices were also deployed in a solution containing natural
freshwater (Parkwood Pond) as the matrix, spiked with 0.70 µM Cu2+, for the same
deployment times and replication.
6.3. RESULTS AND DISCUSSION
6.3.1. Dialysis Membrane Diffusive Layer
An important aspect of this work was to demonstrate that the new DGT devices,
employing a dialysis membrane diffusive layer, met the same set of assumptions as the
conventional DGT system and could be used within the existing theoretical framework 14,
16 . In particular, the use of a dialysis membrane as the diffusive layer had to meet the
119
Chapter 6
assumptions that there were no detectable interactions between the analyte species and the
diffusive layer membrane, and that the diffusion boundary layer (DBL), formed at the
interface between the diffusive layer and the bulk solution, was not a significant influence
on the mass transport into and across the diffusive layer (Figure 6.3). The DBL effects
were investigated under well mixed conditions using the usual DGT validation
experiments (Section 6.3.6) and under various flow conditions (Section 6.3.5).
Diffusive Layer
SampleSolution
Cb
Binding
Con
cent
ratio
n
PSS
(PSS
) n M
2+
δ
M2+
0
DB
L
Cm
C ’
∆g
Layer
Distance
Figure 6.3 Schematic representation of the concentration gradients of free ionic species in a DGT device consists a solid membrane diffusive layer and a liquid binding phase.
An essential pre-requisite of the DGT analysis was that there was very little interaction
between the dialysis membrane diffusive layer and the measured solute. If this condition
was true, then, when a membrane was immersed in a solution, the concentration of the
solute in the membrane should, at equilibrium, be the same as the concentration in the
solution. Figure 6.4 shows the ratio of Cd2+ or Cu2+ concentration in the membrane
(Cmembrane) and in the solutions (Csolution) after a 100 cm2 sheet of 50 µm thick pre-treated
cellulose dialysis membrane was exposed to a well-stirred solution containing 2.0 µM 120
Chapter 6
Cd2+ and Cu2+ for 24 h in solutions of varying ionic strength (10–5 M – 1.0 M NaNO3).
The ratio of the membrane metal concentration to the solution metal concentration was in
the range 0.98-1.05 after 24 h exposure. This indicates that there was little or no
interaction between the dialysis membrane and the Cd2+ and Cu2+ ions. This means that
the concentration of these ions in the diffusive layer will not gradually increase and the
assumption required by the DGT equation holds.
0
20
40
60
80
100
120
Cd CuC
/C (%
)m
embr
ane
solu
tion
-6 -4 -2 0
Log [NaNO3]
Figure 6.4 The interaction between the cellulose dialysis membrane (100 cm2 × 50 µm) and metal ions (2.0 µM) under different ionic strengths for 24 h. The ratio (%) was defined as the ratio of Cd2+ or Cu2+ concentration in the membrane (Cmembrane) to that in the solutions (Csolution).
6.3.2. Optimization of PSS Solution Concentration
One of the most important assumptions made for the DGT equation was that the free metal
ion concentration, C’, at the internal membrane interface was zero (Figure 6.3) at which
point the maximum flux can be achieved. In order to satisfy this condition, the metal ions
must be taken up rapidly by the PSS binding phase. The PSS concentration thus needed to
121
Chapter 6
be as high as possible to make this rapid uptake likely, but as low as possibly to minimise
matrix effects during analysis. Therefore, the PSS concentration was optimised.
Figure 6.5 shows the effect of the PSS concentration on the fluxes of Cd2+ or Cu2+ across
the membrane (fluxes were calculated according to procedures in Section 6.2.6). Figure
6.5 shows that the maximum fluxes were observed for both Cd2+ and Cu2+ when the PSS
concentration was 0.015 M or greater. 0.020 M of PSS was chosen as the binding solution
to ensure that it was sufficient to reduce the interfacial concentration (C’) to, effectively,
zero, even when dilution of the solution occurred due to osmotic pressure. Considering
that the concentration of metal ions used in these experiments were very high in
comparison with real deployment conditions, this PSS concentration would probably be
sufficient for most, if not all, deployment conditions.
Flux
(µg
cm-2
s -1
)
0
Cd Cu0.1
0.2
0.3
0.4
0.5
0.6
0.7
0 0.01 0.02 0.03 0.04 0.05 0.06
PSS Concentration (M)
Figure 6.5 Effect of PSS solution concentration on fluxes through the diffusive membrane (see Section 6.2.8 for experimental details).
122
Chapter 6
6.3.3. Metal Ion Binding Properties of Poly(4-styrenesulfonate)
Figure 6.6 shows the effect of concentration on the amount of metal ion uptake by the
binding phase under non-competitive conditions. It was found that for both Cd2+ and
Cu2+, the amount of metal ion uptake increased with concentrations up to about 2 mM
before saturation occurred. The maximum uptake (saturation) values for Cd2+ and Cu2+
were 13.5 µmole cm-2 and 13.0 µmole cm-2, respectively. The non-competitive binding
capacities for other metal ions were obtained in the same way. The results are
summarised in Table 6.1. The binding capacities of the monovalent ions doubled those of
the divalent ones, suggesting that the interactions with the PSS were largely ion exchange
interactions with the sulfonate groups of PSS.
µmol
e cm
-2 )
0
2
4
6
8
10
12
14
16
Cd Cu
Upt
ake
(
0 1 2 3 4
Concentration (mM)
Figure 6.6 Effect of initial metal ion concentrations in the sample solutions on the uptake by PSS liquid binding phase. The DGT devices were immersed in various concentrations of metal ion solutions for 24 h at pH~6.
The metal binding capacities under competitive conditions were also investigated (Table
6.1). The test solution contained Cd2+, Cu2+ and all the alkali and alkali earth metals used
123
Chapter 6
Cu
in the non-competitive study. The results showed that the binding capacities obtained
under competitive conditions for all metal ions decreased compared with the non
competitive conditions, as expected (Table 6.1). The competitive binding capacities were
shown to be in the order Cd2+ > Cu2+ >> alkali earth metals > alkali metals. This order
indicates that the PSS can be used to selectively bind heavy metal ions such as Cd2+ and
2+. The results in Table 6.1 also show that the total metal binding capacities of PSS
were approximately the same under both competitive and non-competitive conditions (the
competitive capacities add up to 20.5 µmole ml-1 counting the divalent ions twice). This
result further suggests that the interactions between PSS and the metal ions are dominated
by cation exchange. The order of selectivity for competitive binding indicates a stronger
preference for Cd2+ and Cu2+ than for the other metals that were used. This preference
suggests that some complexation may occur (see next section).
Table 6.1 Non-competitive and competitive binding of various metals by a 2.0 ml 0.020 M PSS solution
Cd2+ Cu2+ Ca2+ Mg2+ K+ Na+
a Non-competitive (µmole cm-2) 13.5 13.0 12.9 13.3 25.6 26.1
a Non-competitive (µmole ml-1) 10.4 10.0 9.9 10.2 19.7 20.1
b Competitive (µmole cm-2) 7.8 3.3 0.94 1.1 0.49 0.35
b Competitive (µmole ml-1) 6.0 2.5 0.72 0.82 0.37 0.27
a A liquid binding phase DGT device was immersed in a 50 ml solution containing individual metal ion of 2.5 mN. b A liquid binding phase DGT device was immersed in a 1000 ml solution containing all the above metal ions of individual metal ion of 18 µN. c.The binding capacities were expressed by number moles of metal bound in the binding solution per unit volume and per unit exposed area of membrane.
124
Chapter 6
The binding capacity of the 0.020 M PSS solution was given in terms of both µmole cm-2
(for comparison with other DGT binding phases) and µmole ml-1 (for comparison with the
concentration of the PSS solution). This volume characteristic highlights an important
advantage of this DGT approach, compared with the use of a solid state binding phase16
i.e. the capacity of the PSS solution was considerably higher than the solid state binding
phases and could be increased further simply by increasing the volume of binding solution
(see section 8.3.2 for a detailed comparison).
6.3.3.1. Stability Constants of the Polymer Metal Complexes
Stability constant values were calculated to further characterise the PSS binding
interaction. Several methods used to determine the stability constants and the
corresponding average coordination numbers of metal ions in polymeric solutions have
been reported previously 241-245. These methods include the potentiometric or pH titration
methods 243, spectroscopic methods 244 and the equilibrium dialysis method 241, 245. In this
work, the stability constants of PSS with Cd2+ and Cu2+ were determined according to the
242dialysis method proposed by Juang et al. 241 and Samadfam et al. . To calculate the
stability constant, the following assumptions were made: (a) there was no interaction
between the free metal ions and the membrane; (b) the rejection coefficient of PSS was the
same as that of the metal-PSS complex; (c) the complex reaction was in equilibrium in the
polymer phase; and (d) at equilibrium, the free ion concentration in the sample solution
phase was the same as that in the polymer phase.
When a DGT device was immersed in the metal solutions of various concentrations, PSS
and metal-PSS complex were accumulated within the binding phase of the DGT device
until equilibrium was achieved. At equilibrium, the concentrations of free metal ions in
125
Chapter 6
solution were considered to be the same as those in the DGT devices. Once this
assumption is made the following theory can be used.
The stability constant K, for the binding reaction, can be written as (charges are omitted
for all equations below):
K = [ M( PSS ) ] (6.1)n n[ M ] × [ PSS ]
At equilibrium, the free metal concentration, [ M] , can be expressed by subtracting the
concentration of the metal-PSS complex from the initial free metal ion concentration:
[M] = ([M]0⋅ Vs − [M(PSS)n]⋅Vb)/Vs,
where [M]0 is the initial free metal ion concentration; [ M(PSS)n] is the concentration of
metal PSS-complex; and Vs and Vb are the volumes of the sample and the binding phase
solutions.
The concentration of PSS, [PSS], can be obtained according to: [PSS] = [PSS]0 −
[M(PSS)n], where [PSS]0 is the initial concentration of PSS.
Assuming that the formation of the metal hydroxides were negligible, at pH 7 for the
given metal ion concentrations 246, and only two forms of metals, free metal ion and its
PSS complex, existed in the solution and polymer phase. Thus, equation 6.1 can be
rewritten as (charges are omitted):
K = [ M( PSS ) ]n
[ M ] × V − [ M( PSS ) ] × Vb × PSS ([ ] − [ M( PSS ) ])n (6.2)
V 0 s n
0 n s
Rearranging equation 6.2, we have:
Vb0− Log( [ M ]
− ) = LogK + PSS ([ nLog ] − [ M( PSS ) ])[ M( PSS ) ] V 0 n
n s
126
Chapter 6
0let Y − = Log( [ M ] −
Vb ) ; X = PSS ([ Log ] − [ M( PSS ) ]) , then:[ M( PSS ) ] V 0 n
n s
Y = LogK + nX (6.3)
16.8
16.4
16
15.6
15.2
R2y = 1.80x + 8.11
= 0.980
4 4.2 4.4 4.6 4.8
X
Figure 6.7 Plot of Y against X for determination of the stability constant and coordination number of PSS-Cu2+ complex reaction at pH~6, in 1 mM NaNO3 solution.
Plotting Y against X obtained for Cu2+ gives Figure 6.7. The stability constant, LogKCu =
8.1, and the coordination number, n = 1.8 (in 1 mM NaNO3), were obtained from the Y
intercept and the slope of the curve, respectively. The stability constant, logKCd = 9.0, and
the coordination number, n = 2.2 for Cd2+ were obtained by the same means. The binding
stoichiometry formed here is very close to that determined in Section 6.3.3. Therefore,
cation exchange processes seem to dominate, although transition metals seem to exhibit
the strongest interactions with the PSS, which makes it ideal for DGT applications. These
logK stability constants also confirm that the stability constants for Cd2+ and Cu2+ were
high enough for their strong binding to the PSS polyelectrolyte.
127
Chapter 6
6.3.3.2. Effect of pH on the Binding Capacity
The change in binding capacity for Cd2+ and Cu2+ with the 0.020 M PSS solution with U
ptak
e (µ
mol
e cm
-2)
solution pH is shown in Figure 6.8. The binding capacity increased rapidly from pH 1 to
3, probably due to the increase in the proportion of the base form of the sulfonic acid
groups in the PSS solution. From pH 4 to 8 the binding capacity remained quite constant
for both metal ions. At pH>8 the binding of Cu2+ decreased rapidly, due to the formation
of insoluble hydroxides. The Cd2+ binding decreased rapidly at pH>10. The fact that the
sulfonic acid groups have a low pKa value 247, 248 (in fact it may be a strong acid functional
group) allows them to function as a binding phase for metal ions over a wide pH range
compared with weaker acid groups, such as carboxylic acid (pKa about 4.8) 210 and Chelex
100 (pKa about 3.5) 249.
16
14
12
10
8
6
4
2
0
Cd Cu
0 5 10 pH
Figure 6.8 Effect of sample solution pH on the metal ion uptake by the PSS liquid binding phase.
128
Chapter 6
6.3.3.3. Effect of Ionic Strength on the Binding Capacity
The change in the binding capacity of 0.020 M PSS for Cd2+ and Cu2+ with increasing
ionic concentrations is shown in Figure 6.9. The binding capacity of PSS for Cd2+
decreased from 13.5 µmole cm-2 to 3.3 µmole cm-2 as the ionic concentration (as NaNO3)
increased from 10-5 M to 1.0 M. The binding of Cu2+ decreased from 13.0 µmole cm-2 to
2.5 µmole cm-2 over the same increase in NaNO3 concentration. This decrease in binding
capacity was due to increased competition from Na+, which was the least competitive ion
tested here (but which is important in seawater deployments, Section 6.2.11).
µmol
e cm
-2 )
0
2
4
6
8
10
12
14
16
Cd Cu
Upt
ake
(
-6 -4 -2 0
Log [NaNO3]
Figure 6.9 Effect of ionic strength presented as NaNO3 concentrations in the sample solutions on the metal ion uptake by the PSS liquid binding phase.
Even at 1 M NaNO3 the binding capacities of Cd2+ and Cu2+ were comparable with those
for the solid phase binding agents used previously for DGT at lower ionic strengths. At
lower ionic strengths they were substantially higher: Chelex 100 resin gel, 1.1 µmole cm-2
for Cd 16; polyacrylamide/polyacrylic acid copolymer hydrogel, 1.56 µmole cm-2 for Cd2+,
129
Chapter 6
1.59 µmole cm-2 for Cu2+ (Chapter 3); poly(acrylamidoglycolic acid-co-acrylamide), 5.2
µmole cm-2 for Cd2+, 5.4 µmole cm-2 for Cu2+ (Chapter 4); cellulose phosphate membrane,
3.07 µmole cm-2 for Cd2+, 3.22 µmole cm-2 for Cu2+ (Chapter 5).
6.3.4. Diffusion of Cd2+ and Cu2+ in the Cellulose Dialysis Membrane
The diffusion coefficients of metal species within the diffusive layer need to be known (or
measured) for DGT to be used to estimate analyte concentrations. This is how the DGT
technique is calibrated. In order to ensure the applicability of the measured diffusion
coefficients, the conditions employed for the measurements had to be similar to the DGT
deployment conditions. The diffusion cell was set up as described in Section 2.3.5, with
0.020 M PSS in the receiving solution and 10.0 ppm free metal ions in the source solution.
The experimental procedures are explained in Chapter 2. The transport process involved
in the diffusion coefficient measurement was an active one because the following reaction
occurred at the interface with the diffusion cell (or binding phase in the case of DGT).
M(PSS)n(aq) M2+(aq) + nPSS(aq)
The concentration of PSS used was sufficient to reduce the free metal ion concentration at
the membrane/PSS solution interface to, efficiently, zero through the above reaction
(Sections 6.3.2 and 6.3.3 for supporting evidence). Under this condition, the
concentration difference across the membrane equalled the bulk solution concentration
provided that the effect of a DBL in the source solution is negligible. The measurement of
diffusion coefficients can then be carried out according to the DGT equation,
mM = AC D b t . Plotting M versus the product of Cb and t gives a slope value (ADm/∆g),∆g
which allows the calculation of Dm, since A and ∆g are known constants (Figure 6.10).
130
Chapter 6
(µg)
R2
0
10
20
30
40
Mas
s C
d
y = 0.0535x - 0.406 = 0.997
0 200 400 600 800
(µg) R2
0
10
20
30
40
Mas
s C
u
y = 0.0400x + 0.649 = 0.992
0 200 400 600 800
Ci×t (ppm min.)
Figure 6.10 Plots of mass vs C×t for Cd2+ and Cu2+ (10.0 ppm) in synthetic lake water solution (Windermere). The curves were drawn with mass (µg) transported to compartment B versus the product of time (t, min.) and average metal ion concentrations (Ci, ppm) of each diffusion period in compartment A.
Table 6.2 shows the diffusion coefficients of Cd2+ and Cu2+ in the cellulose dialysis
membrane measured under different ionic strengths (NaNO3 concentrations). The results
indicate that when the NaNO3 concentration was varied from 0 to 0.010 M, a dramatic
2 2decrease in the Dm values for both Cd2+ and Cu2+(5.1×10-6 cm s-1 to 7.8×10-7 cm s-1 and
131
Chapter 6
2 24.2×10-6 cm s-1 to 6.8×10-7 cm s-1) was observed. However, the effect of the NaNO3
2 2 -1concentration on the Dm values was less significant (7.8×10-7 cm s-1 to 2.8×10-7 cm s
2 2and 6.8×10-7 cm s-1 to 2.1×10-7 cm s-1) in the more concentrated NaNO3 solutions (from
0.010 M to 1.0 M). When 90 µM Cd2+ or 160 µM Cu2+ was used, within the NaNO3
(10-6
-1)
Dm
cm
2 s
concentration range from 0.01 M to 1.0 M, non-linear curve fitting indicated that the
relationships between the Dm and NaNO3 concentrations (CI) could be expressed as Dm =
0.279 CI -0.230 for Cd2+ and Dm = 0.196 CI
-0.258 for Cu2+ (Figure 6.11). These results are
quite interesting in that they indicate that there is little change in the Dm at high ionic
strengths. This relatively constant value of Dm will be an advantage in the DGT
deployments in estuarine and other coastal waters. The Dm values for Cd2+ and Cu2+ in
synthetic lake water matrix (Windermere, Lake District, UK) were determined as 2.5×10-6
2 2cm s-1 and 1.9×10-6 cm s-1, respectively.
1
0.8
0.6
0.4
0.2
0
Cd
Cu
Dm CI
Dm CI
= 0.279 -0.230
= 0.196 -0.258
0 0.2 0.4 0.6 0.8 1
[NaNO3] (M)
Figure 6.11 Diffusion coefficients of Cd2+ and Cu2+ in dialysis membrane in various concentrations of NaNO3 (0.010 M-1.0 M).
132
Chapter 6
2Table 6.2 Diffusion coefficients of Cd2+ and Cu2+ (10-6 cm s-1) in cellulose dialysis membrane under various concentrations of NaNO3 (M) (pH~6)
[NaNO3] 1.0 0.10 0.050 0.010 0.0050 0.0023 0
D(Cd2+) 0.28 0.47 0.59 0.78 1.2 2.9 5.1
D(Cu2+) 0.21 0.32 0.43 0.68 0.94 2.2 4.2
As Torre 22 noted, in order to satisfy the condition of electroneutrality in a medium where
ions are co-diffusing, the effective diffusion coefficient of a given ion (Di,eff), should be
described by:
⎡ ⎤∑n =j 1 D z ( dC / dx ) dC /( / dx )j j j iD eff , i =Di − C z D i i i (6.4)⎢
⎢⎣ × ⎥
⎥⎦∑n j=
2 C D z 1 j j j
where Di and zi are the tracer diffusion coefficient and charge, respectively of ion "i".
Equation 6.4 shows that the diffusion coefficient of an ion is influenced by the
concentrations, concentration gradients and diffusion coefficients of all "j" ions, including
the ion "i" of interest; the second term on the right hand side of equation 6.4 refers to the
coulombic or electrical component of Di,eff. When the DGT devices are deployed in
natural waters, there are numerous cations present. Equation 6.4 therefore indicates that
the nature of the matrix can also have a significant influence on the diffusion coefficient of
analyte metals. Therefore, diffusion coefficient should be measured in water of similar
composition (synthetic) to that in which DGT device is being deployed (Chapter 7).
6.3.5. Effect of Stirring Conditions on the DBL Layer
Another important assumption made in the derivation of the DGT equation was that the
double boundary layer (DBL), developed during the DGT deployment, must be
insignificant in comparison with the thickness of the diffusive layer.
133
Chapter 6
Zhang and Davison have described an approach to minimise the influence of a substantial
DBL being formed in poorly mixed waters, in which the DBL thickness becomes
significant compared with the diffusive layer thickness 150. The need to consider DBL
effects arises because the diffusion coefficients of metal ions in the bulk solution are
similar to the diffusion coefficients in the polyacrylamide gels 154. Additionally, the
diffusive gradient within the DBL can also limit the overall mass transport. The approach
by Zhang and Davison to overcome DBL effects involved deployment of two DGT
devices with hydrogel diffusive layers of different thicknesses, which effectively allows
the value of an average DBL to be subtracted from the estimation of the accumulated
metal ions, M, assuming that the DBL thicknesses in the two DGT devices were the
150same .
With the dialysis membrane diffusive layer described here, it was thought that the DBL
might not have a significant effect on the concentration measurement. This is because of
the differences in the diffusion coefficients in solution with those in the membrane.
2 2Diffusion coefficients of 5.55×10-6 cm s-1 for Cd2+ and 5.67×10-6 cm s-1 for Cu2+ in
seawater (Dw) at 16 °C have been previously reported 250. Dw is the diffusion coefficient
of metal ion in water solution. These values increase slightly with a decrease in ionic
strength; an 8% increase in deionised water compared with seawater was also reported 16.
On the other hand, diffusion coefficients of metal ions in the dialysis membrane (Dm)
2 2 2varied from 5.1×10-6 cm s-1 to 0.28×10-6 cm s-1 for Cd2+ and 4.2×10-6 cm s-1 to 0.21×10-
6 2cm s-1 for Cu2+, as the ionic concentration increased from 0 to 1.0 M (as NaNO3) (Table
6.2). The diffusion coefficients decreased dramatically in the lower ionic strength range
(<0.1 M) but changed little in the higher ionic strength range (0.1-1.0 M) (Figure 6.11).
These data indicate that the diffusion across the dialysis membrane in high ionic strength
134
Chapter 6
natural waters under most hydrodynamic conditions would be the rate-limiting step of the
overall transport process (due to the diffusion coefficient in bulk solution being nearly 20
× greater than the diffusion coefficient in the membrane). In low ionic strength waters the
DBL could become much more significant as there is less difference between the diffusion
coefficients in the water and in the membrane. As the DBL is dependent upon the solution
hydrodynamics 148, experiments were undertaken to investigate this phenomenon.
Figure 6.12 shows the effect of the stirring rate on the mass of Cd2+ transported across the
membrane. The negative Y-intercepts reflect the time taken for the concentration
gradients to develop, which decreased as the stirring rates increased. For all cases, a linear
relationship between the mass and the time were obtained (R2 = 0.994 - 1) indicating that
the DBL was fixed during the deployments under each hydrodynamic condition (equation
6.5). It was also found that the rate of transport increased as the stirring rate increased
from 0 to 200 RPM (the slopes of the lines in Figure 6.12 represents the rates of transport)
due to the decrease of the DBL thickness (equation 6.5). A further increase in the stirring
rate above 200 RPM showed no significant effect on the rate of transport because the
minimum DBL thickness was achieved. Under these conditions the flux through the
membrane is the rate-limiting step. At the RPM below 200, however, the flux in the DBL
became rate limiting. As these experiments were carried out in 0.1 M NaNO3 solution, for
which there will be a large difference between Dm and Dw, the DBL definitely needs to be
considered.
The DGT equation has been modified to include the DBL contribution. Considering the
m b mflux through the DBL ( J = D ( C − C ) ) equals the flux through the diffusive layer
δ
m m( J = D ( C − 'C ) , Figure 6.3), we have:
∆g
135
Chapter 6
J = M
= D ( C − C ) D ( C − 'C ) , m b m m m=
At δ ∆ g
where Dm and Dw, are diffusion coefficients (cm2 s-1) of the solute in the membrane and in
the bulk solution, respectively; ∆ g and δ represent the thickness of the diffusion layer and
the DBL layer, respectively; C', Cm and Cb are the solute concentrations (mol l-1) at the
internal membrane surface (the membrane/binding phase interface), the external
membrane surface (the membrane/DBL interface) and the bulk solution.
0
10
20
30
40
50
µ g)
Mas
s (
0 5 10 15
Time (h) 1000 RPM M = 4.06t - 0.33 R2 = 0.994 200 RPM M = 4.08t - 0.33 R2 = 1 100 RPM M = 3.82t - 0.77 R2 = 1 50 RPM M = 3.49t - 0.61 R2 = 0.999 0 RPM M = 2.97t - 1.47 R2 = 1
Figure 6.12 Effect of stirring rate on the mass transport across the dialysis membrane in 0.10 M NaNO3 solution.
When the PSS concentration in the receiving solution is sufficient to reduce C’ to zero, the
DGT equation can be obtained:
w mM = C D AD b ⋅ t (6.5)δ D ∆ + gDm w
136
Chapter 6
Equation 6.5 gives the relationship between the mass (M), the DBL thickness (δ) or the
deployment time (t) for a given DGT device and bulk solution concentration. Under the
condition of δDm << ∆gDw, the maximum rate of transport, ADmCb/∆g, can be achieved
∆and Equation 6.5 becomes the normal DGT equation, C = g M . More importantly, the b AtDm
effect of DBL can be experimentally quantified according to the relationship given by the
equation.
Table 6.3 Effect of double boundary layer (δ) at stirring rate on the accumulated mass
Stirring Rate (RPM) Mass transport rate (µg/h) DBL increase (cm) ∆C/C (%)
1000 4.06 0 0
200 4.08 0 0
100 3.82 0.0038 6
50 3.49 0.010 17
0 2.97 0.022 34
Note: the membrane area is 1.2 cm2, thickness (∆g) 0.005 cm, diffusion coefficient in the membrane (Dm) = 4.7 × 10–7 cm s-1, concentration of Cd2+ 10 ppm.
The thickness of DBL and the measurement errors caused by DBL under different stirring
conditions can be estimated based on the experimental data shown in Figure 6.12 using
equation 6.5 (Table 6.3). It was found that the DBL thickness obtained under the
quiescent condition had increased by 0.022 cm, which is more than 4 times the thickness
of the diffusive layer used. Under such conditions, without correction for the DBL effect,
the DGT measurement will underestimate the concentration by 34%. Actually, this also
means that DBL effects at this ionic strength will lead to an error of no more than 34%.
The thickness of DBL decreased rapidly as the rate of stirring was increased. When the
rotation rate was greater than 200 RPM, the thickness of DBL achieved its minimum value
and maintained. At 100 RPM, the measurement error caused by the development of DBL 137
Chapter 6
was 6%, which is acceptable for most environmental analysis. These results became more
significant for low ionic strength waters, which are poorly mixed.
Vibrating
DGT Device
Wave Action
Diffusive Layer
DBL Development Direction
Figure 6.13 Schematic diagram of wave action effect on the dialysis membrane diffusive layer vibration.
It should be mentioned that the convective condition generated by the stirrer used for this
experiment (Figure 6.2) should be quite gentle even with 200 RPM rotation rate.
Although we could not quantitatively relate the stirring rate used in this experiment to the
hydrodynamic conditions in natural environments, we believe the convective condition
generated by the wave action in the real field deployment should be much stronger than
the convection generated under 200 RPM in the laboratory. This is due to the fact that the
thickness of DBL depends on not only the surface flow rate but also the direction of the
flow. The wave action can cause the diffusive layer vibrating in the direction against the
direction of DBL developed (Figure 6.13). Therefore, it is unlikely that the significant
thickness of DBL can be developed under such conditions. By considering this, and the
observation from Figure 6.12 that a constant transport rate can be obtained under each
given hydrodynamic condition, we have good reason to believe that the development of a
DBL would have only a minor impact on the accuracy of the DGT measurement in real
138
Chapter 6
environmental conditions. The DBL effect can be further minimised by measuring the
diffusion coefficient under the imitated hydrodynamic conditions of natural waters where
the DGT devices will be deployed.
6.3.6. Validation of the PSS/dialysis DGT Device
The test of whether a new DGT method meets the assumptions required by the DGT
equation is to investigate the mass vs. time relationship. If this plot is linear and passes
through the origin then the assumptions are likely to hold. The new DGT assemblies were
validated by testing this relationship between the mass of analyte accumulated in the
binding phase (M) and the deployment time (t) with a solution of known concentration 16.
Figure 6.14 shows the M vs. t relationship for Cd2+ and Cu2+ in a well stirred synthetic
Windermere lake water. The mass of metal ions (µg) increased linearly with time over the
deployment periods used for Cd2+ (r2 = 0.969) and Cu2+ (r2 = 0.980). The solid lines in
Figure 6.14 are lines of best fit for the experimental data; the dashed lines are the
theoretical lines calculated using the DGT equation.
The theoretical lines are virtually identical to the lines of best fit for both Cd2+ and Cu2+.
These two results, along with those described above, confirm that the new DGT device
meets the criteria for application of the DGT equation. Similar coefficients of
determination for the experimental results and recoveries (when compared with the
theoretical lines) were obtained for the validation experiments in a NaNO3 solutions
ranging from 0 to 1.0 M. These results support the conceptual model described above in
which diffusion through the membrane is the rate-limiting step under the conditions
investigated. If this model were not true, then such high coefficients of determination and
recoveries of about 100% would not have been obtained.
139
Chapter 6
30
20
Mas
s C
u (µ
g)
Mas
s C
d ( µ
g)
10
0 0 50 100 150
30
20
10
0 0 50 100 150 200
Time (h)
Figure 6.14 The mass of the metals accumulated by the PSS liquid phase in DGT devices as a function of time. DGT devices were suspended in a well-stirred solution containing known concentrations for different time periods. The solid lines are the lines of best fit for the experimental data. The dashed lines are predicted relationships calculated from known deployment conditions and the DGT equation. For ∆: C = 0.40 µM Cd2+ in synthetic Windermere lake
2water, D = 2.5×10-6 cm s-1; for O: C = 0.70 µM Cu2+ in synthetic 2Windermere lake water, D = 1.9×10-6 cm s-1; and for : C = 0.70 µM Cu2+
2 -1added to Parkwood Pond water, D = 0.94×10-6 cm s ; ∆g = 50 µm, A = 1.54 cm2.
140
Chapter 6
The reproducibility of these DGT devices was also tested and found to be satisfactory
(5.4% rsd, n = 9, for Cd2+ and 5.6% rsd, n = 15 for Cu2+). These data suggest that the
configuration of this DGT device is close to ideal, as described by the DGT equation. In
addition, the nature of the interface between the diffusive layer and binding phase (with a
100%, even coverage of the binding sites at this interface) combined with a well-defined
and reproducible diffusive layer are ideal for DGT applications. The ease of handling
means only minimal user experience is required. Furthermore, there is no requirement to
elute the metals from the binding phase, thus removing the need for estimation and
correction of the elution efficiency. However, the matrix does need to be matched during
analysis.
The pre-concentration factor is defined as the ratio between the concentration of metal ion
bound in the PSS solution and in the synthetic bulk solution 16. This factor increased as
deployment time increased (indicated in the bracket): 94 (50 h), 188 (100 h), 281 (150 h)
for Cd2+ and 71 (50 h), 140 (100 h) 209 (150 h) and 278 (200 h) for Cu2+. For a 30 day
field deployment, a concentration factor of 1120 was observed for Cu.
Validation of the new DGT device was also carried out by spiking a natural freshwater
(Parkwood Pond) with Cu2+. The results are also shown in Figure 6.14. A linear
relationship was observed between the accumulated mass and time (r2 = 0.981), indicating
that the assumptions required for DGT were valid. The recovery was only 46%. This low
recovery resulted from the presence of humic substances, which would have complexed a
significant fraction of the added Cu2+. The work presented in the next chapter focuses on
metal speciation information such as this when employing this new DGT device.
141
Chapter 6
6.4. CONCLUSIONS
This chapter demonstrates the potential for a new type of DGT device, using a poly(4-
styrenesulfonate) (PSS) solution binding phase, and a dialysis membrane diffusive layer.
The diffusion properties of the dialysis membrane and the binding properties of the PSS
solution were characterised and found to be suitable for use with DGT. The double
boundary layer effect was investigated in detail with results suggesting that the effect may
be minimal. A new DGT device was designed and validated by demonstrating a linear
mass vs. time relationship for Cd2+ and Cu2+ in synthetic waters and in the Cu2+ spiked
Parkwood Pond matrix solution. The lower recovery in the Parkwood Pond solution
indicated that the measurement of metals by this DGT device did not include the humic
substances complexed fractions of metals, i.e. only inorganic metals were measured.
The advantages of this approach to DGT include theoretically ideal mass transport and
accumulation due to the mobility of the binding solution and the ideal interface with the
diffusive layer, with consequent good reproducibility; a well-defined, reproducible
diffusive layer (commercially available), which overcomes the fragility and swelling
problems of the gel based binding phases. In addition, there is no need for elution
corrections, which are required for all solid binding phases that do not elute 100%. The
only drawback was the need to dilute and matrix match standards to the PSS solution for
instrumental analysis. This drawback could be overcome through further method
development.
142
Chapter 7
Chapter 7 Characterisation of the Dialysis
Membrane/PSS DGT Device for Trace Metal
Speciation Measurements
143
Chapter 7
7.1. INTRODUCTION
In Chapter 6, a new DGT device, employing poly(4-styrenesulfonate) (PSS) aqueous
solution as a binding phase and a dialysis membrane as a diffusive layer, was validated
under laboratory and natural water conditions. This chapter describes a detailed
investigation into the trace metal speciation characteristics of this new DGT device.
Natural waters contain various ligands that can form complexes with trace metal ions, as
described in Section 1.2 184, 251. Consequently, free metal ions are usually a minor
component of the total metal species present. These numerous complexes have very
different physical properties, such as charge, size and diffusion coefficient, compared with
free metal ions. A DGT device employing a small pore size diffusive layer, such as the
dialysis membrane 202 and an appropriate binding phase (i.e. PSS), has the ability to make
use of these physical differences to achieve selective measurement of species. This
process occurs because the mass transport in DGT analysis is an active process in which a
diffusive flux is maintained by continual binding of the labile species. Only species which
are small enough (not excluded by the diffusive membrane), and which can be bound
strongly by PSS, are measured. Species can also be differentiated on the basis of their
diffusion coefficients, which influence the fluxes through the diffusion layer.
The purpose of this chapter is to investigate the effect of ligands of various types on the
amount of trace metals measured by the PSS DGT device. In order to correctly interpret
the DGT speciation measurement it is vital to characterise the difference between the
diffusion coefficient of the organic complexes and those of the inorganic metal species.
One ligand for which the complexing properties have been well established is EDTA.
EDTA forms strong complexes with Cu2+ and Cd2+ in a 1.0:1.0 ratio, so will be an ideal
144
Chapter 7
case study to measure the diffusion coefficient of a metal complex. The experiment can
be set up so that there is effectively no free or inorganic metal ions present in solution; in
other words the diffusion coefficient of the complex can be measured without interference
from the free metal ions. Being able to measure the diffusion coefficient of one complex
will allow a full characterisation of the DGT speciation measurement of a known solution
containing that complex. General trends may then also be made concerning the
measurability of other metal complexes, for which diffusion coefficients are less readily
characterised.
The fraction of metal species measured by DGT was then compared with a theoretical free
metal ion fraction, where available, for various ligands commonly found in natural waters,
including ethylenediaminetetraacetic acid (EDTA), humic acid (HA), tannic acid (TA),
glucose (GL) and dodecylbenzenesulfonic acid (DBS). Several ratios of the ligand to the
metal ion were investigated to see how the DGT-labile measurement varied in response.
This comparison will help determine the general speciation properties of the PSS DGT
device. In addition, the DGT-labile fraction of metal ions was measured by the DGT
device in various natural water sites with varying levels of organic contents.
Description of the Properties of the Ligands Chosen
The ligands chosen all have some environmental significance. Ethylenediaminetetraacetic
acid (EDTA), which can form very stable complexes with a wide range of metal ions 246,
is one of the examples of aminopolycarboxylic acids. Aminopolycarboxylic acids are
widely used in industrial processes, and in particular, are used as substitutes for
phosphates in detergents. After their release into the environment, these chelating agents
may affect the speciation distribution of metals within the aquatic ecosystems 252.
145
Chapter 7
Humic acids (HA) are a major class of humic substances present in natural waters. Humic
acids are defined operationally as the fraction of humic substances that precipitate upon
acidification. These substances are present in soil, water and sediments, in both soluble
and insoluble forms 253. Humic acids have complex structures including a substantial
proportion of condensed aromatic rings with a large number of –OH and –COOH
functional groups 134, 254, 255. HA are often the ligands present at the highest levels and
therefore play a crucial role in the speciation, transportation and deposition of metal ions
256, 257 .
Tannic acid (TA), a type of tannin polyphenolic substance 258, resulting from the leaching
of bark and leaf litter 259, was also selected for the study. It has properties similar to those
of humic substances in regard to complex formation, absorbability and colour, but it has a
smaller molecular weight 213.
ions
Dissolved carbohydrates are ca. 10 - 40% of the dissolved organic matter in natural water
and play an important role in the aquatic ecosystem 260. Polyhydroxy compounds have
long been known to act as ligands in the formation of coordination complexes of metal
261, 262. For these reasons, D-glucose (GL) was selected as an example to represent
the polyhydroxy compounds. GL compound with –OH function groups on the molecular
structure interacts with metal ions in a complicated way, such as forming a strong sugar
H-bonding network or other interactions 263. However, the interaction was weaker than
the complexes formation of HA or TA 264.
The wide use of synthetic surfactants in domestic and industrial applications and the
inflow of heavy metal ions into aquatic systems have intensified investigations concerning
ecological problems of natural and waste waters 265. Dodecylbenzenesulfonic acid (DBS)
146
Chapter 7
was selected for this study to represent this group of ligands. It is well known that DBS is
able to form complexes with a wide range of metal ions by means of ion-exchange or
electrostatic interaction, however these complexes are often unstable 184, 266.
7.2. EXPERIMENTAL
7.2.1. Measurement of Diffusion Coefficients of EDTA-Metal Complexes
Diffusion coefficients of metal-EDTA complexes in the dialysis membrane were
measured using the diffusion cell described in Chapter 2. One compartment contained
0.40 mM EDTA (Aldrich) and 0.090 mM Cd2+ or 0.16 mM Cu2+ in a 50 ml synthetic lake
water matrix (Windermere, UK). The other compartment was filled with 0.020 M PSS in
a 50 ml solution of the same matrix. Samples were taken from both compartments and
measured by FAAS at specific time intervals for 16 h. The diffusion coefficients were
calculated according to the method described in Chapter 2.
7.2.2. Measurement of DGT-labile Fractions
Two solutions of synthetic Windermere water (Chapter 2, pH = 6.8) containing: (i) 0.70
µM Cu2+ and (ii) 0.40 µM Cd2+ were spiked with various ligands at molar ratios of
1.8:1.0, 1.0:1.0 and 1.0:1.8 with the metal ions. These solutions were mixed over night at
23°C, to allow equilibration of the complexation reactions, before nine DGT devices were
deployed. Three devices were taken for FAAS measurement every twelve hours, while
the solution metal concentrations were measured at the same time by FAAS. The ligands
used were humic acid (HA) (Aldrich), tannic acid (TA) (Aldrich), glucose (GL) (Chem-
Supply, Australia), EDTA (Aldrich), and dodecylbenzenesulfonic acid (DBS) (Sigma).
The DGT-labile metal ion concentration was measured and calculated in the same way as
the normal DGT deployment according to the DGT equation. The total metal ion
147
Chapter 7
concentration was obtained using ICP-MS. The DGT-labile fraction of metal ions (β) was
calculated using the following equation:
ionconcentrat ion metal labile DGT β = .ionconcentrat ion metal Total
7.2.3. Theoretical Calculation of Free Cu and Cd Fractions
βtheoretical is defined as free metal ion concentration over total metal concentration, which
was calculated, for a given ligand, using the speciation function of the IUPAC Stability
Constants Database (SC-database model, Academic Software) 267. This calculation
requires inputs of known parameters, e.g. stability constants of the metal-ligand
complexes, dissociation constants of the ligands, concentrations of the ligands and metal
ion, pH of the solution, as outlined in Table 7.1.
Table 7.1 Constants used for theoretical calculation
NO3-EDTA 246 HA 268 TA 258 Cl- SO4
2-
18.9 7.99 5.4 0.98 269 0.1 270 1.54 271LogβCu1
- - 9.1 0.69LogβCu2
16.5 7.18 - 1.57 272 0.46 273 0.72 274LogβCd1
- - - 2.42 0.17 0.84LogβCd2
pKa1 1.99 - 8.68 -
pKa2 2.67 - - - 1.92 246
pKa3 6.16 - - -
pKa4 10.26 - - -
Molar mass 336.2 13,000 1701 35.5 62.0 96.1
Note: All constants are for 25°C; the solution pH was 6.8; the total concentrations of Cd2+
and Cu2+ were 0.40 µM and 0.70 µM respectively. Logβ: logarithm cumulative stability constant; pKa: negative logarithm acid dissociation constant. EDTA: ethylenediaminetetraacetic acid; HA: humic acid; TA: tannic acid.
148
Chapter 7
7.2.4. Field Deployments of PSS DGT Devices
Each deployment consisted of nine PSS DGT devices mounted on a foam buoy (Figure
7.1). The devices were deployed in various natural water sites (Figure 7.2) by being
anchored to a jetty for specific periods of time.
Anchor
Foam buoy
DGT devices
O-ring
Figure 7.1 Solution based DGT holders were fixed on a square shape foam buoy, floating on waters.
Two seawater sites were chosen: the first was a jetty within Runaway Bay Marina (Figure
7.3) (which had previously been shown to have high trace metal concentrations,
particularly Cu) 275; the second was on a canal site in Biggera Waters (with relatively
lower boat traffic) (Figure 7.4). Two freshwater sites were also chosen: one with
relatively high concentrations of natural organic matter (NOM), Parkwood Pond (Figure
7.5); and the other with less NOM, Loders Creek (Figure 7.5). All the DGT devices were
rinsed thoroughly with deionised water after collection, to minimise contamination.
149
Chapter 7
Grab water samples were also collected for each site, at the beginning, middle and end of
the DGT deployment period, in polyethylene sample containers (Nalgene), pre-cleaned
with 10% nitric acid solution. The samples were filtered immediately on site through 0.45
µm pore size cellulose nitrate (Whatman) membranes and acidified with 65% suprapur
nitric acid (Merck) (2 ml acid per litre of sample) to pH < 2.
Temperature, pH and salinity were also measured on site for the purpose of estimating
diffusion coefficients. The dissolved organic carbon concentrations (DOC) were measured
using a Dohrmann DC-190 TOC analyser. Cu and Cd concentrations were measured by
ICPMS (Agilent Technologies, 7500 Series, Germany) to obtain the dissolved trace metal
concentrations (Section 7.2.5).
Gold Coast
N
Runaway Bay Marina
Biggera Waters
Loder Creek
Parkwood Pond
Figure 7.2 DGT deployment site locations on the Gold Coast in Australia.
150
Chapter 7
N
Figure 7.3 The red circle shows the DGT deployment site at the Runaway Bay Marina (Runaway Bay Marina).
N
Figure 7.4 The red circle shows the DGT deployment site on Back Street in Biggera Waters.
151
Chapter 7
N
A
B
Figure 7.5 The red circle shows the DGT deployment site on Parkwood Pond (A) and Loders Creek (B).
7.2.5. Measurement of PSS DGT-labile and 0.45-filtered Cu and Cd
Concentrations
The concentrations of Cu and Cd accumulated by the PSS in the DGT devices were
measured by ICP-MS after a five-fold dilution. Standards were matrix-matched with PSS
diluted accordingly (as per Chapter 2). The detection limits of this method were 5.5×10-9
mole l-1 for Cu and 1.7×10-9 mole l-1 for Cd.
The 0.45 µm filtered Cu and Cd concentrations of grab samples were analysed by ICPMS
(Agilent Technologies, 7500 Series, Germany). Standard solutions were matrix-matched
with NaCl and MgCl2 diluted accordingly. The detection limits of this method were 1.4 ×
10-8 mol l-1 for Cu and 5.7 × 10-8 mol l-1 for Cd in saline waters; 4.3 × 10-9 mol l-1 for Cu
and 3.2 × 10-9 mol l-1 for Cd in fresh waters.
152
Chapter 7
7.3. RESULTS AND DISCUSSION
7.3.1. Diffusion of EDTA-Cu and EDTA-Cd in the Dialysis Membrane Diffusive
Layer
The DGT analysis is dependent on the rate of diffusion of trace metal species across the
diffusive layer. The accumulation of metal ions in the binding phase arises from all labile
metal ions, including free metal ions, inorganic complexes and organic complexes. The
mass deriving from each species is proportional to the flux of that species across the
diffusive layer, as described by equation 1.5. According to Fick’s law of diffusion
(equation 1.1), the flux depends upon both the diffusive coefficient and the concentration
gradient of that species in the measured water.
The diffusion coefficients of Cd2+ and Cu2+ in the dialysis membrane were determined in
Chapter 6. It would be very useful to compare these diffusion coefficients values with
those of metal-complexes. To measure the diffusion coefficient of a complex requires the
complex to be the only form of metal ion present. Many natural ligands do not bind metal
ions strongly enough or at a stoichiometric ratio sufficient to ensure this condition. As
described earlier, one ligand that does meet this condition is EDTA, which binds Cu2+ and
Cd2+ strongly at a 1:1 molar ratio. The diffusion of the metal-complex can therefore be
measured in isolation from free metal ion diffusion.
Since an excess amount of EDTA was used in the source solution, all metal ions were
complexed. In addition, during the experiment (up to 16 h), the source solution
concentration change, caused by transport of EDTA-metal complex to the receiving
153
Chapter 7
solution, was negligible (<< 1%). The concentration measured in the receiving solution
was below the detection limit of FAAS within 16 h. The diffusion coefficients of EDTA
2metal complexes can be estimated to be less than 4.6 × 10-9 cm s-1 for Cd and 8.5 × 10-9
2cm s-1 for Cu respectively (calculated based on the method in Chapter 2). These diffusion
coefficients were over two orders of magnitude lower compared with the inorganic metal
2ion diffusion coefficients under the same conditions (2.5 × 10-6 cm s-1 for Cd2+ and 1.9 ×
210-6 cm s-1 for Cu2+). These results indicate that, with this dialysis membrane/PSS DGT
device, the accumulation of free metal ions could be more than 200 times faster than the
accumulation of their complexes, assuming they were present at similar concentrations.
Even if the metal-EDTA complex was present at concentrations 10 times higher than the
inorganic metal ions, it would be underestimated considerably.
This result allows conclusions to be made concerning the likely role of diffusion
coefficients of other metal complexes, which can not be measured so readily, on the PSS
DGT measurement. EDTA has either a comparable or a smaller molecular mass
compared with other likely ligands, such as those discussed in section 7.1. As diffusion
coefficients generally decrease in proportion to molecular mass 134 (although other factors
such as shape are also important) metal complexes that form with these other ligands are
likely to have diffusion coefficients that are similar or even lower when compared with the
metal-EDTA complexes. Therefore, it is likely that DGT will measure largely inorganic
and free metal ions, in preference to even small complexes with organic ligands.
However, in natural waters the speciation of trace metal ions is very complex, with a great
range of inorganic and organic ligands present. The complexes that form from each of
these ligands will have their own concentrations and diffusion coefficients, and therefore
their own fluxes. In many natural waters, most (sometimes > 90%) of the trace metals are
154
Chapter 7
complexed to natural organic matter (as described in Chapter 1). The next section
discusses experiments that investigated the amount of a trace metal solution measured by
the PSS-dialysis membrane DGT device in the presence of different complexing agents at
various proportions.
7.3.2. Measurement of Labile Metal Ions in the Presence of Ligands
The mass of a particular metal ion, measured in the PSS solution, is the sum of all forms
of the metal that are DGT-labile. This can occur via several mechanisms:
(1) Exclusion of species larger than the pore size or molecular weight cut-off
(MWCO).
(2) Retardation of species flux (i.e. low diffusion coefficient).
(3) The ability of the binding phase functional group to remove the metal ions from a
complex. If this does not happen then the DGT equation does not apply and the
accumulation in the binding phase occurs by equilibration instead of a maintained
concentration gradient. The former will be a much slower process and
concentration of the metal ions will not occur.
(4) Exchange of the ligand within the time frame required for the species to diffuse
across the diffusive layer. This means that inorganic and organic species can be
interchangeable. This is possible for ligands that form weak complexes or
occasionally even for strong ligands 149.
The following sections describe the results of experiments in which the effect of various
ligands, present at differing ratios with the metal ions, on the DGT-labile measurement
was studied. The DGT labile metal fractions measured reflected the mechanisms as
described in the earlier section of this chapter: 1. the membrane effectively distinguishes
155
Chapter 7
the metal species through size and diffusion differences; 2. different binding properties of
the binding phases also distinguish the metal species; 3. some weak bound metal species
can dissociate in the diffusion layer due to the concentration gradients. This comparison
was used to indicate which speciation mechanism was dominant. Mechanism (1) was not
relevant in these laboratory solutions. Mechanism (2) was likely to always be occurring to
some extent. If the DGT-labile fraction was found to be the same as the theoretical
estimation then it was likely that diffusional selectivity was the dominant mechanism.
This is because the complexed species would have diffused through the dialysis
membrane much more slowly and effectively be insignificant to the DGT measurement
compared with the inorganic metal species which diffuse through much more quickly. In
other words only the inorganic fraction is DGT-labile.
Mechanism (3) will only become important for species which are not selected against
significantly by mechanism (2) (i.e. have fluxes greater than 1% of the fluxes of the
inorganic metal species) and which also bind the metal ions more strongly than the PSS
solution. The laboratory experiment will not be able to examine this mechanism. It is
possible that no such species exist when using the dialysis membrane diffusive layer, for
which mechanism (2) becomes more important than for the polyacrylamide diffusive gels.
Zhang and Davison 154 have measured the diffusion coefficients of fulvic and humic acids
in water and in several types of diffusive gels. In their work the diffusion coefficient was
retarded by one order of magnitude at most, whereas the diffusion coefficients of large
molecules/complexes through the dialysis membrane is likely to be retarded to a much
greater extent. It has been reported that even 1000 Dalton molecules can not pass through
the 10,000 MWCO membrane 276.
156
Chapter 7
The final potential mechanism, based on dissociation of complexes at the time scale of
diffusion through the dialysis membrane, can be considered to be a modifier to both
mechanism (2) and mechanism (3), with the former being more important. If a significant
fraction of metal ions dissociates this will effectively speed up the mass transport slightly
and act to maintain the concentration gradient. This would have the effect of increasing
the DGT-labile fraction when compared with the theoretical estimation of the inorganic
metal fraction.
These predictions will be discussed with respect to the experimental results obtained.
However it is important to remember that other factors could be responsible for a
difference in the DGT-labile fraction and the theoretically estimated inorganic fraction.
The main one is an actual difference in the stability constant of the complexes in the
experimental solution and that used in the speciation software. The humic substance
ligands have a great variety of forms that occur in nature and any particular sample will
have binding sites with a range of stability constants present 134, 277. For some ligands
stability constants may not have been calculated while for others such as EDTA there will
be a high degree of certainty. The precision of the DGT technique will also be a factor in
establishing which mechanism is predominant. If the DGT-labile fraction is statistically
equivalent to the theoretical inorganic fraction (α = 0.05) then mechanism (2) should be
considered to dominate.
7.3.2.1. Speciation Measurement of Labile Metals in the Presence of EDTA
EDTA was the first ligand investigated. Figure 7.6 shows the effect of metal ion/EDTA
molar ratio on the DGT labile metal ion concentration. It was found that, as the molar
ratio of metal ion/EDTA decreased, the DGT-labile metal fractions dramatically
157
Chapter 7
decreased. Both βCd and βCu became virtually 0 at 1:1 molar ratio and lower. Therefore,
as expected, with EDTA as the complexing ligand, the free metal ion concentration is
effectively equal to the metal ion concentration minus the EDTA concentration. The fact
that no Cu and Cd were measured in solutions with metal/EDTA ratios ≤ 1 indicates that
DG
T La
bile
Met
al F
ract
ion β
(%)
the complexes are being selected against due to mechanism (2); i.e. slow diffusion through
the dialysis membrane.
100
90
80
70
60
50
40
30
20
10
0
3.0:1.0 1.8:1.0 1.0:1.0 1.0:1.8
Cd Cu
Molar Ratios of Metal Ions and EDTA
Figure 7.6 Ratios of measured DGT labile metal ions (β) in solutions containing various molar ratios of metal ion and EDTA. Molar ratios between metal ions and EDTA are: 3.0:1.0, 1.8:1.0, 1.0:1.0 and 1.0:1.8, as shown in the Figure.
The theoretical free metal ion fractions at a different molar ratio of EDTA/metal ions were
calculated (Table 7.2). The results revealed that both the DGT labile metal fractions and
the theoretical free metal ion fractions were very similar and followed the same trend
when the molar ratio of metal ion/EDTA was changed. The βCd values were 55.0% and
36.1%, the same as the theoretical value for 3:1 and 1.8:1 Cd/EDTA molar ratios
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Chapter 7
respectively. The βCu values were 66.7% and 43.5%, the same as the theoretical value for
the 3:1 and 1.8:1 Cu/EDTA molar ratios respectively (Table 7.2). The agreements
between DGT measurement and theoretical calculation indicate that DGT measured free
metal ion concentration in the EDTA solution.
Table 7.2 Effect of EDTA to metal ion molar ratio on the DGT labile metal ion fraction and free metal ion fraction calculated by SC-database model
Molar Ratio of Metal Ion/EDTA
3.0:1.0 1.8:1.0 1.0:1.0 1.0:1.8
βCd (%) 55.0±3 36.1±2 0 0
βCd,theoretical (%) 56.1 37.4 0 0
βCu (%) 66.7±2 43.5±1 0 0
βCu,theoretical (%) 65.3 44.4 0 0
Note: βCd and βCd are the DGT labile fraction of Cd and Cu. The values shown here were the averages of 7 replicate experiments. βCd,theoretical and βCu,theoretical are the free metal ion fraction of Cd and Cu calculated by SC-database model 267.
7.3.2.2. Speciation Measurement of Labile Metal in the Presence of Humic Acid
Figure 7.7 shows the effect of varying the ratio between the metal ion and the HA in the
sample solution on the DGT-labile fraction for Cd and Cu (βcd and βcu). It was found that
both βCd and βCu decreased as the ligand to the metal ion ratio increased. When the metal
ion/HA molar ratio increased from 1.0:1.8 to 1.0:1.0, to 1.8:1.0, the percentages of the
DGT labile metal ion, measured, increased from 18.7% to 32.8% to 51.0% for Cd and
1.2% to 10.1% to 42.4% for Cu. The DGT-labile fractions are compared to the theoretical
inorganic fractions in Table 7.3.
From Table 7.3 it is apparent that the values of βCd and βCu obtained were very close to the
theoretical values. The βCd values were 51.0%, 32.8 and 18.7%, close to the theoretical
values for the 1.8:1.0, 1.0:1.0 and 1.0:1.8 Cd/HA molar ratio respectively. The βCu values
159
Chapter 7
were 42.4%, 10.1% and 1.2%, the same as the theoretical value for the 1.8:1.0, 1.0:1.0 and
1.0:1.8 Cu/HA molar ratios respectively (Table 7.3). It is more likely that, at 1.0:1.8
metal/HA molar ratio, the measured DGT labile metal ion fractions may be from the
dissociation of the complexed metals (mechanism 4).
DG
T La
bile
Met
al F
ract
ion β
(%)
100
90
80
70
60
50
40
30
20
10
0
1.8:1.0 1.0:1.0 1.0:1.8
Cd Cu Molar Ratios of Metal Ions and HA
Figure 7.7 Ratios of measured DGT labile metal ions (β) in solutions containing various molar ratios of metal ion and humic acid (HA). β is defined as the concentration of DGT labile metal ions over total metal ion concentration (%) in the solution. Molar ratios between metal ions and HA are: 1.8:1.0, 1.0:1.0 and 1.0:1.8, as shown in the Figure.
Table 7.3 Effect of humic acid to metal ion molar ratio on the DGT labile metal ion fraction and free metal ion fraction calculated by SC-database model
Molar Ratio of Metal Ion/Humic Acid 1.8:1.0 1.0:1.0 1.0:1.8
βCd (%) 51.0±2 32.8±4 18.7±3 βCd,theoretical (%) 56.5 33.2 14.8
βCu (%) 42.4±4 10.1±3 1.2±1 βCu,theoretical (%) 46.1 11.4 1.81
Note: βCd and βCu are the DGT labile fraction of Cd and Cu. The values shown here were the averages of 7 replicate experiments. βCd,theoretical and βCu,theoretical are the free metal ion fraction of Cd and Cu calculated by SC-database model 267.
160
Chapter 7
It was also found that, for a given HA/metal ion molar ratio, the DGT labile metal
fractions obtained for Cd2+ were always greater than that for Cu2+. This result can be
explained by the stability constant for each metal complex (Table 7.1). The stability
constant of HA-Cd (LogK = 7.18) was smaller than that of HA-Cu (LogK = 7.99).
7.3.2.3. Speciation Measurement of Labile Metals in the Presence of Tannic Acid
Figure 7.8 shows the effect of the molar ratio of TA/metal ion on the ratio of DGT-labile
concentration to the total concentration for Cd and Cu (βcd and βcu). It was found that both
βcd and βcu decreased as the molar ratio of TA/metal ion increased, which was expected.
When the metal ion/TA molar ratio increased from 1.0:1.8 to 1.0:1.0 to 1.8:1.0, the
percentages of the DGT labile metal ion, measured, increased from 38.8% to 47.5% to
64.3% for Cd and 58.4% to 66.7% to 70.1% to for Cu.
Table 7.4 shows the DGT-labile metal fractions compared with the theoretical inorganic
fractions. It was found that the DGT-labile Cu fractions, βCu, were substantially less than
the theoretical values for all molar ratios used. The most likely reason for this was a
difference between the stability constant used in the speciation software and that of the
sample of tannic acid used. However, these results may be explained by the complicated
interactions between the metal ions and the tannic acid. Possible physical and chemical
absorptions of the metal ions to the tannic acid may keep some metal ions as “bound”
ions258. It is not possible to suggest a likely mechanism for speciation of the TA
complexes based on this data. However, given the results obtained for the HA and EDTA
complexes in the previous sections, the mechanism based on retarded diffusion of the
complexes compared with the inorganic metal ions is most likely.
161
Chapter 7
DG
T La
bile
Met
al F
ract
ion β
(%)
100
90
80
70
60
50
40
30
20
10
0
1.8:1.0 1.0:1.0 1.0:1.8
Cd Cu Molar Ratios of Metal Ions and TA
Figure 7.8 Ratios of measured DGT labile metal ions (β) in solutions containing various molar ratios of metal ion and tannic acid (TA). β is defined as the concentration of DGT labile metal ions over total metal ion concentration (%) in the solution. Molar ratios between metal ions and TA are: 1.8:1.0, 1.0:1.0 and 1.0:1.8, as shown in the Figure.
Table 7.4 Effect of tannic acid to metal ion molar ratio on the DGT labile metal ion fraction and free metal ion fraction calculated by SC-database model
Molar Ratio of Metal Ion/Tannic Acid
1.8:1.0 1.0:1.0 1.0:1.8
βCd (%) 64.3±2 47.5±3 38.8±2
βCd,theoretical (%) - - -
βCu (%) 70.1±1 66.7±3 58.4±4
βCu,theoretical (%) 92.2 86.7 78.9
Note: βCd and βCd are the DGT labile fraction of Cd and Cu. The values shown here were the averages of 7 replicate experiments. βCd,theoretical and βCu,theoretical are the free metal ion fraction of Cd and Cu calculated by SC-database model 267.
162
Chapter 7
No βCd,theoretical was given in Table 7.4 because of the lack of a stability constant for TA-
Cd. It has been reported previously that no significant complexation occurs between
between Cd2+ and TA 258. However, our results do not support this, as the βCd, values
obtained were even smaller than that of βCu, for each given molar ratio of TA/metal ion.
This means that Cd2+ was bound more tightly to our sample of tannic acid than Cu2+ was.
Comparing the results shown in Tables 7.2 and 7.3, it can be seen that the DGT labile
metal fractions, in the presence of TA, were higher than that in the presence of HA,
especially for Cu. This result indicates that the interactions between TA and metal ions
were not as strong as that of HA. This result agrees with Ross’s results 278 where it was
reported that TA belongs to the category of weaker natural binding ligands compared to
the HA ligand, which is rich in both primary amines and carbohydrates.
7.3.2.4. Speciation Measurement of Labile Metals in the Presence of Glucose
Figure 7.9 shows that the DGT-labile metal fractions for both Cd and Cu (βCd and βCu)
decreased as the molar ratios of metal ion/glucose decreased. The 1.8:1.0 ratio for both
metals and the 1.0:1.0 ratio for Cu gave DGT-labile fractions close to 100%. The
strongest binding, 1.0:1.8 for Cd, gave a DGT-labile fraction of only about 80%. These
observations demonstrate that glucose weakly binds the metal ions in a way to make them
non-DGT-labile. This effect was larger for Cd2+ than for Cu2+. For a given molar ratio,
the DGT-labile metal fractions, obtained for both Cd and Cu in the presence of GL, were
much higher than that obtained in the presence of HA, TA or EDTA, due to the weaker
interactions between the metal ions and the GL 264, 279. Although there is no theoretical
calculation for comparison, given that the metal glucose species are likely to diffuse much
more slowly through the dialysis membrane than the inorganic species, it is again likely
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Chapter 7
that the DGT-labile fractions measured here largely represents the inorganic metal ion
fraction 263. It is possible that mechanism (4), dissociation of the complex during
diffusion through the dialysis membrane, is important here given the weak complex
formed with the glucose ligands.
DG
T La
bile
Met
al F
ract
ion β
(%)
100
90
80
70
60
50
40
30
20
10
0
1.8:1.0 1.0:1.0 1.0:1.8
Cd Cu
Molar Ratios of Metal Ions and GL
Figure 7.9 Ratios of measured DGT labile metal ions (β) in solutions containing various molar ratios of metal ion and glucose (GL). β is defined as the concentration of DGT labile metal ions over total metal ion concentration (%) in the solution. Molar ratios between metal ions and GL are: 1.8:1.0, 1.0:1.0 and 1.0:1.8, as shown in the Figure.
7.3.2.5. Speciation Measurement of Labile Metals in the Presence of
Dodecylbenzenesulfonic Acid
The effect of the molar ratio of metal ion/DBS on the DGT-labile metal fraction is given
in Figure 7.10. It can be seen that the DGT-labile metal fractions for both Cd (βcd values
are 81.5%, 64.8% and 52.8% for Cd/DBS molar ratios of 1.8:1.0, 1.0:1.0 and 1.0:1.8) and
Cu (βcu values are 96.0%, 84.3% and 75.7% for Cu/DBS molar ratios of 1.8:1.0, 1.0:1.0
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Chapter 7
and 1.0:1.8) decreased as the molar ratios of metal ion/DBS decreased, particularly for Cd.
This indicated mid-strength binding for Cd2+ and somewhat weaker binding for Cu2+. The
binding strength for both Cd and Cu seemed to be between that for the TA and glucose
ligands. Like the TA case, it seems that the most likely mechanism responsible for
speciation of the metal-DBS complex is slow diffusion through the dialysis membrane,
although there may be some dissociation occurring as well.
DG
T La
bile
Met
al F
ract
ion β
(%)
100
80
60
40
20
0
Cd Cu Molar Ratios of Metal Ions and DBS
1.8:1.0 1.0:1.0 1.0:1.8
Figure 7.10 Ratios of measured DGT labile metal ions (β) in solutions containing various molar ratios of metal ion and (DBS). β is defined as the concentration of DGT labile metal ions over total metal ion concentration (%) in the solution. Molar ratios between metal ions and DBS are: 1.8:1.0, 1.0:1.0 and 1.0:1.8, as shown in the Figure.
Based on this work, the PSS-DGT device seems to largely measure the inorganic fractions
of metal ions in solutions only. Metal complexes with EDTA, HA and TA are non-DGT-
labile while complexes with glucose and DBS also seem likely to not be measured,
although this has not been confirmed here. For binding ligands with greater stability
constants, such as EDTA, the non-complexed fraction was a lot lower and therefore so
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Chapter 7
was the DGT-labile fraction. The order of increasing DGT-lability of the complexes was
EDTA < HA < TA < DBS < glucose for both Cu and Cd. This speciation is influenced
largely by retardation of the flux of the complex through the dialysis membrane.
The following section describes the results of field deployments of the PSS DGT device in
natural waters, where a complicated mixture of ligands can potentially influence the DGT-
labile measurements. The only previous field study to investigate the speciation of the
DGT-measurements used the conventional Chelex 100 DGT devices and found that 55.2%
of the Cu complexes with organic matter were DGT-labile 23. These results suggest that
with the PSS DGT device this is likely to be much lower, if not zero.
7.3.3. Field Deployments
The newly developed PSS DGT devices were deployed at several sites for in situ trace
metal ion speciation. Both fresh (Parkwood Pond and Loders Creek) and saline water
(Runaway Bay Marina and Biggera Waters) sites were chosen. Detail experiment
procedures were given in the experimental section 7.2.4 of this chapter.
In order to obtain the diffusion coefficients for inorganic Cu2+ and Cd2+, the matrices of
each site were first determined. The composition of these matrices is given in Table 7.5.
Synthetic solutions were then prepared matching the major cation composition of the
water at each site. The diffusion coefficients of Cd2+ and Cu2+ for each test site were
measured in these synthetic solutions according to the previously described method
(Section 2.3.5) and are shown in Table 7.6. The magnitude of diffusion coefficients
obtained was dependent on total ionic strength. The value of diffusion coefficients
obtained from the salty waters (Runaway Bay Marina and Biggera Waters) were much
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Chapter 7
smaller than those obtained from fresh waters (Parkwood Pond and Loders Creek) due to
the high ionic strength of the former.
lTable 7.5 Major cation concentrations (mM), dissolved organic carbon (DOC, mgC
-1), salinity, pH and water temperature (oC) on the DGT deployment sites
Measured Parameters
Test Sites [K+] (mM)
[Na+] (mM)
[Ca2+] (mM)
[Mg2+] (mM)
DOC (mgC l-1)
pH Salinity (ppm)
Temp (oC)
Runaway Bay 13.2 530 32.1 43.6 0.93 8.1 34.3 26.2 Marina
Biggera 14.7 524 26.3 72.2 1.1 7.9 35.7 25.7 Waters
Parkwood 0.56 1.1 0.41 1.9 12 5.2 0.23 28.3 Pond
Loder Creek 0.080 0.87 1.4 0.18 7.5 6.5 0.31 25.3
Note: cation concentrations were measured by AAS after appropriate dilutions. Other parameters were measured at the beginning, middle and the end of the DGT deployment and averaged.
Table 7.6 Diffusion coefficient of metal ions in different test sites
Diffusion Coefficient
Test Sites Dm (Cd2+) (cm2s-1)
Dm (Cu2+) (cm2s-1)
Runaway Bay Marina 0.30×10-6 0.22×10-6
Biggera Waters 0.30×10-6 0.21×10-6
Parkwood Pond 1.0×10-6 0.89×10-6
Loders Creek 1.4×10-6 1.0×10-6
Note: diffusion coefficients of Cd2+ and Cu2+ in the membrane in the tested sites were determined by the measurements of mass diffused through the membrane in solutions containing NaCl and MgCl2 of concentrations equivalent to the ionic strengths of the sites using the diffusion cell in Chapter 2.
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Chapter 7
The results obtained from the field deployment are summarised in Table 7.7 for Cu and
Table 7.8 for Cd. For the seawater sites, the 0.45 µm-filterable Cu components
determined by ICP-MS were found to be very similar: 1.20 ppb for the Biggera Waters
site and 1.30 ppb for the Runaway Bay Marina site. The DGT-labile Cu concentrations
were 0.55 ppb for both the Biggera Waters site and the Runaway Bay Marina site. These
data represent 46% and 42% of the 0.45 µm-filterable Cu, respectively. These
percentages are effectively the same when experimental uncertainties are taken into
consideration, probably because the sites are part of the one well-flushed and mixed
coastal lagoon (Gold Coast Broad Water).
Table 7.7 DGT labile and 0.45 µm-filterable concentrations of Cu
Test Sites CDGT * (ppb) CF
* (ppb) β **(%)
Biggera Waters 0.55±0.04 1.20 46
Runaway Bay Marina 0.55±0.03 1.30 42
Parkwood Pond 0.050±0.002 0.61 8.2
Loder Creek 0.025±0.004 0.51 4.9
*Note: CDGT and CTF are the DGT labile metal ion concentration and the total filterable metal ion concentration measured by ICPMS respectively. Data presented here are the mean values of three replicates. **β is defined as the DGT labile metal ion concentration (CDGT ) divided by the total filterable metal ion concentration (CF).
For the seawater sites, both the 0.45 µm-filterable and DGT-labile Cd concentrations were
much lower when compared to the Cu. The 0.45 µm-filterable Cd components for the
Biggera Waters and the Runaway Bay Marina sites were found to be below the detection
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Chapter 7
limits. The DGT labile Cd ion concentrations were 0.043 ppb for the Biggera Waters site
and 0.039 ppb for the Runaway Bay Marina.
Table 7.8 DGT labile and 0.45 µm-filterable concentrations of Cd
Test Sites CDGT * (ppb) CF
* (ppb) β** (%)
Biggera Waters 0.043±0.01 <0.6 -
Runaway Bay Marina 0.039±0.004 <0.6 -
Parkwood Pond 0.019±0.008 <0.4 -
Loder Creek 0.014±0.002 <0.4 -
Note: *CDGT and CTF are the DGT labile metal ion concentration and the total filterable metal ion concentration measured by ICPMS respectively. Data presented here are the mean values of three replicates. **β is defined as the DGT labile metal ion concentration (CDGT ) divided by the total filterable metal ion concentration (CF).
For the freshwater sites, the 0.45 µm-filterable Cu and Cd were much lower than in the
seawater sites. The DGT-labile Cu concentrations obtained from the fresh water sites
were 0.050 ppb for Parkwood Pond and 0.025 ppb for Loders Creek. The DGT-labile Cd
concentrations obtained from the freshwater sites were 0.019 ppb for Parkwood Pond and
0.014 ppb for Loders Creek. These DGT-labile metal concentrations were much lower
than those at the seawater sites.
The freshwater sites had higher DOC levels and also had lower DGT-labile concentrations
compared with the seawater sites (Tables 7.5 and 7.7). DOC has been used as an indicator
of the amount of complexation with organic matter that is likely to occur 280, 281. Given the
results in the previous sections of this chapter, it is likely that the low DGT-labile
measurements are due to a higher proportion of the Cu and Cd being complexed to organic
matter and therefore becoming non-labile to the PSS DGT device. Of course this should
be studied in much more detail as part of future studies. 169
Chapter 7
7.4. CONCLUSIONS
It was demonstrated that the dialysis membrane/PSS DGT device was capable of
measuring DGT labile fraction of metal ions. The measurement in solutions containing
various complexing ligands showed good agreement with SC-database model calculations.
The measured DGT labile metal ion fractions were determined by the four mechanisms as
described in Section 7.3.2.
The application of the DGT technique in natural waters validated its speciation ability.
The site at the Runaway Bay Marina showed higher concentrations of copper because of
the release of antifouling paints from boats berthing at the site. At the site with high lever
of DOC, the Parkwood Pond site, low DGT labile metal ion fraction was measured due to
the complexation of metals to humic substances. Both the experiments in laboratory and
in natural waters showed the potential of using this DGT device as a tool for speciation
analysis of trace metals in waters.
170
Chapter 8
Chapter 8 Evaluation of the New Binding Phases
Developed for Use in the Diffusive Gradients in
Thin Films Technique
171
Chapter 8
8.1. INTRODUCTION
In the previous chapters, various new DGT binding phases were developed and validated
for trace metal measurements. These are the first new DGT binding phases reported for
trace metals since the Chelex 100 polyacrylamide gel was first described 14, 15. This
chapter will compare the trace metal speciation characteristics of DGT using these new
binding phases with Chelex 100 DGT devices. The methods used to characterise the PSS
binding solution in Chapter 7 will be used. Comparison of the different binding phases
was also carried out in field deployments. The known properties of each of the binding
phases developed in this thesis are also compared.
8.2. EXPERIMENTAL
8.2.1. Diffusion Layer Preparation
Both polyacrylamide diffusive gel and the cellulose dialysis membrane diffusive layer
were prepared according to the methods described in Chapters 2 and 6.
8.2.2. Binding Phase Preparation
Poly(acrylamide-co-acrylic acid) (PAM-PAA) gel, poly(acrylamidoglycolic acid-co-
acrylamide) (PAAG-PAM) gel, Whatman P81 cellulose phosphate ion exchange
membrane (P81), poly(4-styrenesulfonate) (PSS) solution and Chelex 100 polyacrylamide
gel (Chelex 100) were employed as binding phases for this study. These binding phases
were prepared in the same manner as described in previous chapters.
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Chapter 8
8.2.3. DGT Measurements in Laboratory
DGT devices employing solid binding phases (Chelex 100, PAM-PAA, PAAG-PAM and
P81) were assembled using the conventional piston design 16 (Figure 2.1) by placing
polyacrylamide gel diffusive layers (thickness, 0.08 cm and exposure area, 4.9 cm2) on top
of each binding phases. The solution binding phase DGT devices were prepared using a
special design by clamping a diffusive membrane on a plastic tube filled with 2.0 ml 0.020
M PSS solution and deployed in solutions in the way of the membrane side facing down
(Figure 6.1). The thickness and exposure area of the diffusive membrane were 0.0050 cm
and 4.5 cm2 respectively.
Nine replicates of each of the above DGT devices were immersed in solutions containing
0.40 µM Cd2+ with varying EDTA concentrations (0.13 µM, 0.22 µM and 0.40 µM,
making metal:ligand ratios of 3.0:1.0, 1.8:1.0 and 1.0:1.0) or varying humic acid
concentrations (0.22 µM, 0.40 µM and 0.70 µM, making ratios of 1.8:1.0, 1.0:1.0 and
1.0:1.8). The replicates were deployed in groups of three with each group removed after
10, 24 and 36 hours. The same measurements were made on solutions of 0.70 µM Cu2+
with EDTA or humic acid concentrations varied to produce the same ratios. These
solutions were prepared in 25 L volume to ensure that the depletion of metal ions by DGT
devices was negligible and appropriate percentages of bound and unbound metal ions
were close to equilibrium.
Metals accumulated in the solid/gel binding phases were measured by FAAS after elution
of the solid binding phases in 10% HNO3 solution, whereas metals in PSS solution were
directly measured by FAAS with PSS matrix matched calibration standards (as described
in Section 6.2.7). The accumulated mass was calculated and then plotted vs time with the
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Chapter 8
slope used to calculate C, given that all the other parameters were known. β was
calculated as described in Chapter 7.
8.2.4. DGT Field Deployment
Each of the DGT devices were deployed in triplicate, using the field deployment apparatus
shown in Figure 8.1, for 24 hours on each day over a 6 day period at Runaway Bay
Marina (Figure 7.3) and Parkwood Pond (Figure 7.5). All DGT devices were rinsed with
deionised water thoroughly before disassembly to prevent contamination. Blanks were
also analysed together with the deployed DGT devices as in Chapters 6 and 7.
Anchor
Foam buoy
DGT devices
Figure 8.1 Gel based DGT holders were fixed on a square shape foam buoy, floating on waters.
174
Chapter 8
Water samples were also collected from each site in acid-washed LDPE containers
(Nalgene) at the beginning, middle, and end of the DGT deployment. These samples were
filtered immediately on-site through 0.45 µm cellulose nitrate membranes, acidified with
65% suprapur nitric acid (Merck) (2.0 ml acid per litre of sample) to pH ≈ 2, and analysed
by ICP-MS (Agilent Technologies, 7500 Series, Germany) to obtain total dissolved trace
metal concentrations (Chapter 2). Samples taken from seawater were analysed after
appropriate dilution with matrix matching to minimise background interference. The
detection limits were as described in 7.2.5.
To measure the diffusion coefficients of the Cu and Cd in the diffusive layers (i.e.
polyacrylamide gel and cellulose nitrate dialysis membranes) in the natural waters
investigated, the major ion compositions were measured and an artificial solution created.
For Runaway Bay Marina water 1.16 g KCl, 33.3 g NaCl, 2.8 g CaCO3 8.3 g and MgCl2
6H2O were dissolved in 800 ml of deionised water. For the Parkwood Pond water 0.036 g
KCl, 0.088 g NaCl, 0.071 g CaCO3 and 0.35 g MgCl2 6H2O were dissolved in 800 ml
deionised water. 10.0 ml of 1000 ppm Cd2+ or Cu2+ was added to the solutions before
they were diluted to one litre total volume. The diffusion coefficients of the metal ions in
the two diffusive layer for each water were measured using these synthetic solutions
according to the previously described method in Chapter 2.
8.3. RESULTS AND DISCUSSION
8.3.1. Measurement of DGT Labile Metal Ions in the Presence of Ligands
In this section, the effect of the presence of ligands in the sample solution on the
measurement of the DGT labile metal fraction (β) by different DGT binding phases was
investigated.
175
267
Chapter 8
8.3.1.1. Measurement of DGT Labile Metal Ions in the Presence of EDTA
The effect of the presence of EDTA on the DGT-labile metal fraction for the different
binding phases is described here. EDTA is a good ligand to study because the
thermodynamic properties of EDTA-metal ion complexes are well characterised and they
are very strong complexes (Chapter 7). This makes it possible for us to accurately
calculate the inorganic metal concentrations with varying metal/EDTA ratios. The DGT-
labile metal fractions experimentally obtained from different binding phases were
compared with the theoretical free metal ion fractions calculated by SC-database model
. The results are given in Tables 8.1 and 8.2 for Cd and Cu, respectively.
Table 8.1 Effect of molar ratio Cd2+ to EDTA on the DGT labile metal ion fraction measured by binding phases and free metal ion fraction calculated by SC-database model
Molar Ratio of Cd2+ to EDTA
Fraction (%) 3.0:1.0 1.8:1.0 1.0:1.0
βtheoretical 56.1 37.4 0
βChelex 100 54.5±3 35.6±3 0
βPAM-PAA 52.6±2 34.1±4 0
βPAAG-PAM - - -
βP81 53.8±4 35.9±5 0
βPSS 55.0±3 36.1±2 0
See note below.
Table 8.1 shows the comparison of the theoretical free metal ion fractions (βtheoretical) with
DGT-labile fractions of Cd2+ for each binding phase. Except for PAAG-PAM binding
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Chapter 8
phase, which does not bind Cd2+, as mentioned previously, the DGT-labile fractions
obtained from all the binding phases were not significantly different (α=0.125, n=3, t-test)
to the theoretical free metal ion fraction, βtheoretical for each ratio investigated. This
indicates that the DGT-labile fractions obtained were the same as the inorganic metal
fraction. The contribution to the DGT-labile fraction by the metal ions that result from
dissociation of the EDTA-Cd2+ complex were negligible, as demonstrated by the results
for the 1:1 experiment.
Table 8.2 Effect of molar ratio Cu2+ to EDTA on the DGT labile metal ion fraction measured by binding phases and free metal ion fraction calculated by SC-database model
Molar Ratio of Cu2+ to EDTA
Fraction (%) 3.0:1.0 1.8:1.0 1.0:1.0
βtheoretical 66.7 44.4 <LOD
βChelex 100 65.1±5 43.0±6 <LOD
βPAM-PAA 62.2±3 42.0±4 <LOD
βPAAG-PAM 60.6±4 41.5±2 <LOD
βP81 64.3±2 42.3±3 <LOD
βPSS 66.1±2 43.5±1 <LOD
Note: βChelex 100, βP81, βPAM-PAA, and βPSS are the DGT-labile fractions of Cu and Cd measured by binding phases as described. The values shown here were the averages of 3 replicate experiments. βtheoretical is the free Cu2+ or Cd2+ fraction of calculated by SC-database model 267.
Table 8.2 shows the comparison of βtheoretical to DGT-labile fractions of Cu2+ for each
binding phase. Once again, the DGT-labile fractions measured by each binding phase,
including PAAG-PAM, were not significantly different to βtheoretical for each molar ratio
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Chapter 8
(p<0.125, n=3 means only, t-test). This again suggests that the DGT-labile fractions
obtained were the inorganic Cu fractions.
These results were interesting. Two factors largely determine the measurement of metal-
EDTA complexes: diffusion coefficients relative to the inorganic metal species and the
ability of the binding functional group to remove metal ions from the complex with
EDTA. It has been established, in the previous chapter, that metal-EDTA complexes are
not labile with the PSS DGT device because the complexes diffuse so slowly through the
dialysis membrane (>500x more slowly than inorganic metal species). However, previous
measurements of diffusion coefficients of metal complexes through the polyacrylamide
diffusive gel have found the diffusion of even metal-humic acid complexes occur at only
10x less than the free ionic species 149. Given that metal-EDTA complexes should have a
higher diffusion coefficient than the HA complexes (as they have much lower molecular
masses) it might be expected that diffusion retardation would not be a large enough
discriminating effect (perhaps 2-3x only) to explain the results obtained. However, this
flux retardation effect in combination with the apparent inability of binding agents to
remove metal ions from the EDTA complex could explain these results. Only the Chelex
and PSS binding layers have stability constants likely to allow competition with the EDTA
ligands, however, as no β value is higher than the theoretical value (which would happen
if the complexes were labile), it seems as if this removal of the metal ions does not occur
to a significant extent at all. If the binding layer can not remove the metal ions from the
complex then the diffusive gradient will not be maintained. Consequently, the technique
will not operate in a kinetic mode but in an equilibrium mode instead, which will reduce
the flux even further. A combination of these effects is likely to be the reason why no
difference was observed between the DGT-labile fractions for any of the binding layers
used, given the range of RSD values observed for the DGT measurements (up to 14%).
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Consequently, only inorganic metal species were DGT-labile for each binding layer
investigated.
8.3.1.2. Measurement of DGT Labile Metal Ions in the Presence of Humic Acid
The effect of the presence of humic acid on the DGT-labile metal fraction for the different
DGT binding phases was investigated and compared with the theoretical free metal ion
fractions calculated by SC-database model 267. The results for Cd with the PSS binding
phase are taken from Chapter 7. Humic acids are a major category of natural organic
matter and have been reported to readily bind trace metals like Cd and Cu. The results are
given in Tables 8.3 and 8.4 for Cd and Cu, respectively.
Table 8.3 Effect of molar ratio Cd2+ to humic acid on the DGT-labile metal fraction measured by various binding phases and the theoretical free metal fraction.
Fraction (%)
βtheoretical 56.5 33.2 14.8
βChelex 100 47.2±6 32.7±4 13.8±3
βPAM-PAA 50.6±3+ 31.1±4 11.1±3
βPAAG-PAM - - -
βP81 48.6±3 30.8±4 12.9±2
βPSS 51.0±2 32.8±4 18.7±3
Molar Ratio of Cd2+ to Humic Acid
1.8:1.0 1.0:1.0 1.0:1.8
See note below.
An increase in the molar ratio of Cd2+/HA and Cu2+/HA lead to an increase in βtheoretical,
calculated by the SC-database model, as expected (see Chapter 7). A very similar trend
was observed for the DGT-labile metal fractions for all binding phases, except for PAAG179
Chapter 8
PAM with Cd which was previously found to be incapable of binding Cd2+ (Chapter 4).
Furthermore, the DGT-labile fractions were not significantly different (p<0.125, n=3
means only, t-test) to the theoretical values. However, in some cases the DGT
measurements were all either higher or lower than the theoretical value. Therefore, this
should be evaluated again with more replication so that a more powerful statistical
comparison can be utilised. The fact that the DGT-labile fractions are not significantly
higher than the theoretical fractions suggests that the metal-HA complexes are not
measured significantly for any of the DGT devices, with either the polyacrylamide or
dialysis membrane diffusive layer.
Table 8.4 Effect of molar ratio Cu2+ to humic acid on the DGT-labile metal fraction measured by various binding phases and the theoretical free metal fraction.
Fraction (%)
βtheoretical 46.1 11.8 1.8
βChelex 100 44.3±4 15.2±5 <2.6
βPAM-PAA 42.5±3 9.2±4 <1.4
βPAAG-PAM 40.2±6 11.0±2 <1.4
βP81 41.1±3 10.6±4 <1.9
βPSS 45.4±4 14.1±3 <1.0
Molar Ratio of Cu2+ to Humic Acid
1.8:1.0 1.0:1.0 1.0:1.8
Note: βChelex 100, βP81, βPAM-PAA, and βPSS are the DGT-labile fractions of Cu and Cd measured by binding phases as described. The values shown here were the averages of 3 replicate experiments.
βtheoretical is the free Cu2+ or Cd2+ fraction of calculated by SC-database model 267.
These results are likely to come about largely due to the flux of humic acid complexes
being considerably slower than that of the inorganic metal species (>10x for the
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polyacrylamide diffusive layer and >500x for the dialysis membrane diffusive layer).
Given the RSD values typical of the DGT measurements (>6%) it is unlikely that a 1 in 10
increase will result in a significantly different measurement. This will be the case even if
the binding agents are able to remove the metal ions from the HA complexes, which
should happen to some extent. It remains to be seen whether these different binding
phases measure different fractions in natural waters, which have a much more complex
speciation characteristics than the laboratory solutions.
8.3.2. Field Deployments
In order to compare the performance characteristics of DGT devices with different binding
phases all measurements were performed at the same time for each site. In practice, for a
given test site, all DGT deployments were carried out within the same time period of 6
days. For each binding phase, three DGT devices were removed every 24 hours for the
purpose of constructing a mass vs. time curve, for which the average concentration for the
deployment period was calculated by using the known values of A and ∆g (from slope =
CDA/∆g). However, the diffusion coefficients for Cu2+ and Cd2+ through each diffusion
layer were measured in synthetic solutions similar to those at each deployment site (see
section below). The concentrations obtained are described in section 8.3.2.2.
8.3.2.1. Measurement of Diffusion Coefficients
The diffusion coefficients used for DGT calculation depend on the type of diffusive layer
employed and the sample matrices. The composition of the waters at both the sites used
were analysed with the results summarised in Table 8.5. Synthetic solutions were created
to match the major ion compositions (i.e. no organic complexes). The diffusion
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coefficients of the metal ions in each diffusive layer were measured using the synthetic
matrices (Table 8.6).
lTable 8.5 Concentrations of major cations (mM), dissolved organic carbon (DOC, mgC
-1), pH and water temperature (oC) at Runaway Bay Marina and Parkwood Pond on the Gold Coast.
Measured Parameters
Test Sites K+
(mM)
Na+
(mM)
Ca2+
(mM)
Mg2+
(mM)
DOC
(mgC l-1) pH Salinity
(ppm)
Temp.
(oC)
Runaway Bay Marina 15.5 570 28.0 41.1 0.84 8.2 35.0 22
Parkwood Pond 0.49 1.5 0.71 1.7 9.2 6.1 0.25 25
Table 8.6 Diffusion coefficients of Cd2+ and Cu2+ of the polyacrylamide and the dialysis membrane diffusive layers at different test sites.
Test Sites
Runaway Bay Marina
Parkwood Pond
Diffusion Coefficient
Dg (Cd2+) Dg (Cu2+) Dm (Cd2+) Dm (Cu2+) 2 -1) 2 -1)(cm s (cm2s-1) (cm2s-1) (cm s
1.4×10-6 1.6×10-6 0.30×10-6 0.21×10-6
2.0×10-6 2.1×10-6 0.92×10-6 0.81×10-6
Note: Dg and Dm are the diffusion coefficients of Cd2+ and Cu2+ in the polyacrylamide gel and the dialysis membrane respectively.
It was found that the magnitude of diffusion coefficients decreased as the total ionic
strength increased for both the polyacrylamide gel and the dialysis membrane diffusive
layers. Therefore, the diffusion coefficients obtained for the Runaway Bay Marina were
smaller than those obtained for Parkwood Pond. For a given matrix, it was found that the 182
Chapter 8
diffusion coefficients in dialysis membrane were significantly smaller than those in
polyacrylamide gel, although the difference was much greater in the saline waters. Given
these diffusion coefficients, the average DGT-labile concentrations for Cu and Cd for each
binding phase at both sites were able to be calculated.
8.3.2.2. Measurement of DGT-Labile Metal Concentration and Fraction
Runaway Bay Marina
Table 8.7 contains a summary of the DGT-labile concentrations and fractions (if possible)
of Cd2+ and Cu2+ obtained using the various binding phases in Runaway Bay Marina.
95% confidence interval (95% CI) values and detection limits for each binding phase were
also shown, as well as the 0.45 µm-filterable concentration.
For Cd the DGT-labile concentrations measured using the various binding phases, except
PAAG-PAM, which does not bind Cd2+, were from 0.015 to 0.026 µg l-1. A Oneway
ANOVA with a Least Squares Difference post-hoc analysis (df = 84) determined that the
measurements obtained with the various binding layers were not all the same. Chelex was
significantly different from the P81 binding layer (p=0.046) and was highly significantly
different from the PAM-PAA binding layer (p<0.000). The P81 layer was also
significantly different from the PAM-PAA (p=0.048). The PAM-PAA binding layer was
also significantly different from the PSS binding phase (p=0.004). This means that there
were essentially three different fractions of DGT-labile Cd: Chelex, P81 and PAM-PAA.
The PSS binding phase was not significantly different from the Chelex and P81 binding
layers, meaning that it was an intermediate DGT-labile fraction between the different
Chelex and P81 fractions. The 0.45 µm-filterable Cd2+ concentration was not able to be
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Chapter 8
estimated because it was below the detection limit. Therefore, the DGT-labile fractions
were not able to be estimated as a percentage of the 0.45 µm-filterable fraction.
Table 8.7 DGT labile Cd2+ and Cu2+ fractions measured using various DGT binding phases and their total filterable concentrations (TFC) measured by ICP-MS in Runaway Bay Marina on the Gold Coast.
Specifications
CCd (ppb)
95% CI
LODCd,(ppb)#
FCCd (ppb)
βCd (%)
CCu (ppb)
95% CI
LODCu (ppb)#
FCCu (ppb)
βCu (%)
Binding Phases
Chelex 100 PAM-PAA PAAG-PAM P81 PSS
0.026±0.010 0.015±0.010 - 0.020±0.010* 0.023±0.011*
0.021-0.030 0.013-0.018 - 0.017-0.024 0.018-0.028
0.010 0.010 - 0.010 0.010
<0.6 µg l-1
nc nc nc nc nc
0.25±0.11 0.18±0.09 0.14±0.08 0.23±0.09 0.23±0.07
0.20-0.30 0.14-0.21 0.11-0.18 0.19-0.27 0.20-0.26
0.05 0.05 0.05 0.05 0.05
<0.9 µg l-1
nc nc nc nc nc
Note: CCd,and CCu,are DGT labile concentration of Cd2+ and Cu2+. FCCd and FCCu are 0.45 µm membrane filterable concentration of Cd2+ and Cu2+ (ppb). βCd and βCd are the DGT labile fraction of Cd2+ and Cu2+ measured. The values shown here were the averages of 3 replicate experiments. 95% CI is 95% confidence interval. nc means not able to be calculated # the detection limits were conservatively set at these levels even though some were actually lower * one extreme outlier was excluded from analysis and attributed to contamination
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Interpretation of these results is quite difficult, given the knowledge currently available.
There was a very high power (df = 84) in this statistical analysis, so these results are likely
to be accurate. The discussion of the mechanisms responsible for producing the
laboratory results (in section 8.3.1) is not sufficient to explain the field results. It was
concluded previously that the PSS DGT device was unlikely to measure organic
complexes because the diffusion coefficients are considerably lower than the diffusion
coefficients for the inorganic species. A consequence of this conclusion is that PSS DGT
devices will only measure inorganic species. If this conclusion is correct then the Chelex
DGT devices may be measuring some of the metal complexed by organic matter (given
that the mean was slightly higher although not significantly so) which has been reported
previously 282. However, this also means that the PAM-PAA binding layer (which gave a
significantly different and lower concentration) does not measure all of the inorganic Cd
species present. This would be a surprising result, if correct. One possible explanation is
that the PAM-PAA functional groups do not bind some inorganic Cd species, present in
seawater, strongly enough. The SC-database calculates 1.57% CdCl+ and 6.35% CdCl2 as
the main inorganic complexes present apart from aqua complexes. No certain conclusion
can be made based on these results; further research is clearly required to fully determine
the reasons for the different DGT-labile fractions measured.
For Cu, the DGT-labile concentrations measured using the different binding phases were
found to be in the range of 0.144 to 0.246 µg l-1. The 0.45 µm-filterable concentrations
were below the detection limit, therefore the DGT-labile fractions were not able to be
estimated. A Oneway ANOVA with a Least Squares Difference post-hoc analysis (df =
106) determined that the measurements obtained with the various binding layers were
again not all the same. The Chelex binding layer was highly significantly different from
the PAAG-PAM layer (p<0.000) and significantly different from PAM-PAA (p=0.008).
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Likewise, the P81 binding layer was significantly different from the PAAG-PAM
(p=0.001) and PAM-PAA (p=0.039) layers. Finally, the PSS binding phase was also
significantly different from the PAAG-PAM (p=0.002) and PAM-PAA (p=0.045) binding
layers. Therefore there were two categories of results: the DGT-labile concentrations
obtained with the Chelex, P81 and PSS binding phases were effectively the same and
different from the DGT-labile concentrations of the PAAG-PAM and PAA binding layers,
while the latter two gave the same results.
Therefore, we have observed the same issues noted with the Cd measurements. The
Chelex, PSS and P81 were once again similar, even more so than observed for the Cd
measurements. The PAAG-PAM and PAM-PAA DGT devices give lower DGT-labile
concentrations than do the PSS DGT devices. This means that either the PSS DGT
devices do not measure only inorganic species, at least in seawaters, or the PAAG-PAM
and PAM-PAA DGT devices do not measure all of the inorganic fractions. This
phenomenon may be restricted to seawater measurements where the concentrations of
inorganic ligands are very high. More research is also required for Cu DGT
measurements.
Parkwood Pond
Table 8.8 summarises the DGT-labile concentrations and fractions (if possible) of Cd2+
and Cu2+ obtained using the various binding phases at Parkwood Pond. 95% confidence
interval (95% CI) values and detection limits for each binding phase were also shown.
The 0.45 µm-filterable concentration of Cd was below the detection limit but Cu was
measured.
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For Cd, the DGT-labile concentrations measured using the various binding phases, except
PAAG-PAM, which does not bind Cd2+, were from 0.014 to 0.023 µg l-1. A Oneway
ANOVA with a Least Squares Difference post-hoc analysis (df = 85) determined that the
measurements obtained with the various binding layers were not all the same. The PSS
DGT devices gave the highest concentration and were significantly greater than the
concentration measured by the Chelex (p=0.034) and PAM-PAA (0.001) binding layers.
The P81 binding layers were significantly different to only the PAA (p= 0.003) binding
layers. This means that the binding layers were not clearly delineated according to the
results obtained. The PSS binding layer formed one category and the PAM-PAA binding
layer was very different. However, the P81 and Chelex binding layers appeared to be
intermediate, with P81 not being significantly different from the PSS or Chelex layers, but
was significantly different to the PAM-PAA layer, whereas the Chelex layer was only
significantly different to the PSS layer.
For Cu, the DGT-labile concentrations measured using the various binding phases ranged
from 0.023 to 0.030 µg l-1. A Oneway ANOVA with a Least Squares Difference post-hoc
analysis (df = 106) determined that the measurements obtained with the various binding
layers were not all the same. The PAAG-PAM DGT device gave the highest
concentration and were significantly greater than the concentration measured by the PAM
PAA (0.012) binding layers. The P81 binding layers were also significantly greater than
the PAA (p= 0.025) binding layers. The PSS and Chelex binding layers formed an
intermediate group that were not significantly different from any other binding phases.
Once again these results are difficult to explain given our current understanding of the
speciation mechanisms.
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Table 8.8 DGT labile Cd2+ and Cu2+ fractions measured using various DGT binding phases and their total filterable concentrations (TFC) measured by ICP-MS in Parkwood Pond on the Gold Coast.
Binding Phases
Specifications Chelex 100 PAM-PAA PAAG- P81 PSS PAM
0.018±0.010 0.014±0.010 - 0.022±0.010 0.023±0.011CCd (ppb)
0.013-0.022 0.011-0.017 - 0.019-0.025 0.018-0.028 95% CI
0.010 0.010 - 0.010 0.010 LODCd,(ppb)#
FCCd (ppb) <0.4 µg l-1
nc nc - nc ncβCd (%)
0.025±0.011* 0.023±0.011 0.030±0.010 0.030±0.010 0.027±0.011CCu (ppb)
0.0193-0.030 0.018-0.027 0.026-0.035 0.026-0.035 0.0224-0.0322 95% CI
0.015 0.015 0.015 0.015 0.015 LODCu (ppb)#
FCCu (ppb) 0.4±0.0 µg l-1 (LOD = 0.3 µg l-1)
6.3 6.3 7.5 7.5 6.8βCu (%)
Note: CCd,and CCu,are DGT labile concentration of Cd2+ and Cu2+. FCCd and FCCu are 0.45 µm membrane filterable concentration of Cd2+ and Cu2+ (ppb). βCd and βCd are the DGT labile fraction of Cd2+ and Cu2+ measured. The values shown here were the averages of 3 replicate experiments. 95% CI is 95% confidence interval. nc means not able to be calculated # the detection limits were conservatively set at these levels even though some were actually lower * one extreme outlier was excluded from analysis and attributed to contamination
The DGT-labile fraction of the 0.45 µm-filterable concentration was only able to be
estimated for Cu in Parkwood Pond and was found to be 6.3-7.5%. This is lower than
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Chapter 8
many of the fractions reported in the literature. This is probably because Parkwood Pond
has a dissolved organic carbon concentration of 9.2 mg l-1, which is quite high. Given that
the DOC concentration is about 23,000 times higher than the 0.45 µm-filterable
concentration it is obvious that most of the Cu has been complexed by natural organic
matter. This supports the notion that most organically complexed metals are not DGT-
labile.
Overall Assessment
There are few trends apparent in the results discussed, even when compared with the
results from the Runaway Bay Marina deployment. About the only clear one is that the
PAM-PAA DGT devices generally give lower concentrations than the other binding
layers; although it does not always give the numerically lowest concentration, it has
consistently been part of a statistically equivalent group that has given the lowest
concentrations. The conclusion made in the previous chapter, concerning the PSS DGT
devices measurement of inorganic species only, has not been supported by these results in
this chapter. All organic complexes will diffuse through the polyacrylamide layer more
quickly than through the dialysis membrane, so some other explanation needs to be sought
to explain data where the other binding agents provide a concentration that is lower than
the PSS value. The most likely explanation is based on the strength of the binding phase
(stability constant). Only the stability constant of the PSS for Cd and Cu is known so we
can not predict the order or binding strength a priori. Nor do the experimental results
described here provide a clear comparison. We do know that Chelex 100 binds strongly to
transition metals, so it would seem very improbable that any of the other binding agents
that have a polyacrylamide diffusive layer would give concentrations higher than Chelex
DGT devices.
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The most likely explanation is therefore that this statistical analysis has produced Type I
errors, where a difference between data has been found where none actually exists. The
probability of this is equal to α, which was 5%. If α is set at the much more stringent
value of 0.001 instead, many of the differences found no longer become significant. Even
where these highly significant differences do exist, there are usually intermediate groups
that are not significantly different from the groups with the highest and lowest values.
The only result where a clear trend is apparent is Cu at Runaway Bay Marina. However,
this clear delineation is not apparent at α= 0.001. The Cu measurements at Parkwood
Pond also have no significant relationships at α= 0.001. The small range of the DGT-
labile concentrations as a percentage of the 0.45 µm-filterable concentration (6.3-7.5%)
obtained for this site, suggest that Type I errors have occurred here. Clearly further
studies are required to determine whether these various binding phases do give
significantly different results in different waterways. In particular, the possibility that the
PSS DGT devices are capable of measuring metal complexes with natural organic matter
needs to be explored. On the other hand, investigation of the possibility that apparently
weaker binding agents like PAM-PAA do not measure all of the inorganic metal species
may be a simpler experiment to perform using synthetic solutions.
8.4. COMPARISON OF IMPORTANT PROPERTIES OF THE NEW BINDING
PHASES DEVELOPED IN THIS STUDY
This chapter has been devoted to comparison of the binding phases developed in this study
with the Chelex 100 binding phase. Therefore, a summary and general comparison is
included here of all of the major findings and properties of the new binding phases
developed for measurement of Cu and Cd by the DGT technique. Table 8.9 contains a
simple comparison of all the binding phases for important properties that influence the
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operation of DGT. These properties are described in much more detail in the following
sections.
Table 8.9 Properties of binding phases that can adversely effect DGT measurements: means there are problems with this binding layer, means that this binding layer is close to ideal, ) means that there are some minor problems only.
Binding Phase Interface Swelling Biofouling Elution Reusability between
binding and diffusive layer
Chelex 100 )
PAM-PAA
PAAG-PAM
P81
PSS ) *
*There is no elution with PSS, but there are matrix issues for analysis.
8.4.1. Assembly of DGT Devices and the Interface between the Binding and
Diffusive Layers
Assembly of the DGT device should be undertaken in a convenient, reproducible manner.
Likewise, the results obtained with the method should also be reproducible and accurate.
The conventional DGT binding phase is Chelex 100 ion-exchange resin embedded
polyacrylamide gel 14, 15. This binding gel was the first developed DGT binding phase and
has been widely used since 14, 22, 165, 283-285. Assembly of a DGT device with Chelex 100
binding gel is not a trivial task. Users have to identify which surface of the binding gel is
that which the Chelex resin has settled towards during polymerization, and that needs to
be in contact with the diffusive gel 16. If the binding gel is assembled up-side down in the 191
Chapter 8
DGT device then the results will have a large bias towards underestimation of the
concentration. The Chelex binding gel also does not form an ideal interface with the
diffusive layer because the binding functional groups are not aligned continuously at the
surface; the interface has an actual thickness, which in theory should produce a small bias
towards underestimation. These problems will be more important for inexperienced users.
The newly developed gel-based DGT binding phases, PAM-PAA gel and PAAG-PAM
gel, are homogeneous binding phases. The binding sites are spread evenly through out the
binding phases, unlike the Chelex 100 binding gel. Orientation in a particular direction is
therefore not necessary. Furthermore, the interface between the diffusive and binding
phase is ideal, with a continuous coverage of binding functional groups, which is what is
assumed with calculation using the DGT equation. However, other problems concerning
the assembly of DGT device that Chelex 100 binding gel experienced also exist for other
gel-based binding phases (see below).
The cellulose phosphate P81 ion-exchange membrane DGT binding phase is a
commercially available membrane. This membrane has much better mechanical strength
than that of gel based binding phases described above. The strong mechanical strength of
the membrane makes assembly of the DGT device much easier than for gel based binding
phases. Since the binding functional groups are homogenously distributed across the
membrane, orientation is not something that has to be considered.
The PSS liquid binding phase provides a perfectly homogeneous interface with the
diffusive layer. It overcomes the swelling and fragility problems of gel-based binding
phase and eliminates elution steps needed for all solid binding phases. It also minimises
the biofouling effects during DGT deployments. However, this DGT device requires
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Chapter 8
special preparation of the PSS polymer and the dialysis membrane. It also requires a
unique DGT probe.
8.4.2. Swelling Effects
Swelling is another important property of binding phases that affects the handling and ease
of use of the DGT technique. The P81 membrane binding phase does not swell or shrink
under any experimental conditions investigated. The PSS liquid binding phase increases
its volume slightly when the DGT device is deployed in waters due to osmotic pressure
between the binding solution and the sample solution. This change of the binding phase
volume does not affect its application because the PSS solution is diluted to an appropriate
volume after deployment and the binding solution concentration change does not affect its
binding property (the actually used PSS solution concentration is higher than its optimum
binding concentration, Chapter 6). The volume of Chelex 100 gel binding phase changes
a little (10-20%) for the pH range from 2 to 9 where the swelling is constant at ionic
concentrations ranging from 10-5 M - 1.0 M (as NaNO3). However, the volume of PAM
PAA gel and PAAG-PAM gel binding phases depends on the solution pH and ionic
strength. PAM-PAA and PAAG-PAM gel binding phases swell rapidly at pH ~ 3 and 2
respectively. This was due to the transformation of the acidic form of the carboxylate
functional groups to the basic form, which interact with water differently due to a change
in the surface charges. The basic form has a negative charge and thereby interacts with
water more strongly which produces the swelling.
The highest degree of swelling was achieved at pH 6 for PAM-PAA gel and pH 5.4
PAAG-PAM gel. For PAM-PAA gel, the degree of swelling was essentially constant
when the pH > 6 due to the completion of the conversion of acidic form of the gel to basic
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form, while PAAG-PAM gel shrunk rapidly when pH > 5.4 due to the increase of ionic
strength attributed by the addition of NaOH. The degree of swelling for PAM-PAA gel
and PAAG-PAM gel decreased rapidly as NaNO3 concentration increased due to a strong
charge screening effect on the gel network, in which the electrostatic repulsion between
adjacent strands of polymer are minimised, causing the strands to move closer together
resulting in a polymer that has less capacity to absorb water 211. The degree of swelling of
these two gel based binding phases needs to be stabilised before DGT assembly by
keeping the gels in NaNO3 solutions whose ionic strength and pH are similar to those of
the deployment sites. This equilibration needs to be undertaken for at least 24 h 154.
8.4.3. Biofouling Effects
Biofouling will occur in all waters, where organisms adhere to and grow on the membrane
that covers the diffusive layer, or is the diffusive layer. Figure 8.2 shows the biofouling
growth on filter membrane after 1, 3 and 7 weeks 275. After a three week deployment in
Runaway Bay Marina serious biofouling had occurred. Biofouling has two detrimental
effects. Firstly, the presence of layers of organisms changes the diffusional properties of
the DGT device by increasing the diffusive path-length. Secondly, some of the organisms
will adsorb some of the metal ions, effectively removing them from solution and making
them non-measurable by DGT.
Figure 8.2 Filter membrane biofouling in Runaway Bay Marina. 1, 3 and 7 week deployments from left to right, respectively.
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Figure 8.3 shows the biofouling that occurs on the cellulose nitrate dialysis membrane
used in the PSS DGT device. Clearly after 3 weeks the biofouling is much less severe
compared with that shown in Figure 8.2. This is because the dialysis membrane is more
hydrophilic 286 and has been treated to become resistant to biofouling 287. Furthermore, in
long deployments, this problem was solved by replacing the membrane weekly by a fresh
membrane. This can be done without disturbing the PSS solution. This allows
considerable extension of the deployment period, which will be useful for ultra-trace
measurements.
Figure 8.3 Dialysis membrane biofouling. 1, 3 and 7 week deployments from left to right, respectively.
8.4.4. Reusability
Theoretically, all gel based binding phases and P81 membrane binding phase can be
regenerated and reused. However, only the P81 membrane binding phase has been
demonstrated to be practically reusable. This is because gel based binding phases are too
fragile and physical damage can not be avoided during the disassembly and elution
processes. The P81 membrane binding phase can be practically regenerated and reused
due to its excellent mechanical strength and sharply pH dependent metal binding
properties (Section 5.3.1).
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8.4.5. Elution
All solid binding phase DGT devices require elution steps before the measurement of
analyte mass accumulated in the phases, which can be achieved by immersing the binding
phases in a strong acidic solution. The elution factor is defined as the ratio of the eluted
metal mass to the mass bound in the binding phase. The value was used for the
calculation of metal concentrations in a tested sample solution 16. Therefore, the accuracy
of DGT measurements depends on the elution efficiency.
Unlike the solid binding phases, the liquid binding phase does not require an elution step
since the metal in the liquid can be analysed directly by FAAS or ICP-MS methods, which
meets the requirement of rapid and accurate in situ analysis. However, to measure the
metal-PSS concentrations in the binding phase, a series of PSS matrix matched standard
metal solutions are required for calibration. The solutions also have to be diluted to an
appropriate level as the matrix has not been diluted by an elution step.
8.4.6. Valid Deployment Conditions and Metal Binding Properties
This section compares the important properties of the binding phases developed as part of
this study with those of the Chelex 100 gel at pH ~7 and low ionic strength (NaNO3
concentration of 1.0 × 10-5 M). The maximum binding capacities (µmole cm-2) of the
binding phases under non-competitive conditions are listed in Table 8.10. The order of
decreasing binding capacity is: PSS (13.5 for Cd and 13.0 for Cu) > PAAG-PAM gel (5.1
for Cd and 5.3 for Cu) > P81 (3.1 for Cd and 3.2 for Cu) > PAM-PAA gel (1.6 for Cd and
Cu) > Chelex 100 gel (1.1 for Cd). This same order of capacity between the various
phases was observed under different conditions of pH and ionic strength. The PSS has the
196
Chapter 8
highest binding capacities because it is a solution phase which mobile, and so a functional
group at the interface with the diffusive layer can bind a metal ion and then diffuse away
to be replaced with another functional group. The Chelex 100 binding layer has the
lowest capacity because the functional groups that accumulate the metal ion are not
continuous at the surface. The other three solid binding phases do have continuous layer
of functional groups at their surfaces.
Table 8.10 Binding capacities of binding phases
Binding Phase
Maximum Capacity (Cd, µmole cm-2)
Maximum Capacity (Cu, µmole cm-2)
Chelex 100 P81 PAM-PAA PAAG-PAM PSS*
1.1 16 3.1 1.6 5.1 13.5*
- 3.2 1.6 5.3 13.0*
*Binding capacity of a 2.0 ml 0.020 M PSS solution
It is required that DGT binding phases accumulate metals over a wide range of conditions
of pH and ionic strength in natural waters. Ionic strength affects the binding of metal ions
to the binding phases. At higher ionic strength solutions, the binding metal capacities of
the binding phases are lower due to the competition accumulation of matrix ions.
Table 8.11 shows that the studied binding phases are applicable in ionic strength
equivalent to NaNO3 concentration range of 1.0 × 10-5 to 1.0 M. Most natural waters are
within this range. The pH of solutions also affects the accumulation properties of the
binding phases. At lower pH range, the major binding functional groups of the binding
phases are in acidic forms, which are neutral and thus will not bind metals. As reported by
Zhang 16 and investigated in previous chapters, the optimal working pH ranges of the
binding phases for Cd measurement were 5.0 – 8.3 for Chelex 100 gel, 5.0 – 10 for PAM
197
Chapter 8
PAA, 4.2 – 10 for PAAG-PAM, 3.9 – 8.2 for P81 and 2.0 – 10 for PSS; pH ranges for Cu
measurement were 5.0 – 9.0 for PAM-PAA, 3.0 – 9.0 for PAAG-PAM, 3.9 – 8.2 for P81
and 3.0 – 8.7 for PSS.
Table 8.11 Valid deployment conditions
Binding Phase pH Range for Cd pH Range for Cu Ionic Strength (NaNO3, M)
Chelex 100 5.0-8.3 - 10-5-1.0
PAM-PAA 5.0-10 5.0-9.0 10-5-1.0
PAAG-PAM 4.2-10 3.0-9.0 10-5-1.0
P81 3.9-8.2 3.9-8.2 10-5-1.0
PSS 2.0-10 3.0-8.7 10-5-1.0
8.5. CONCLUSIONS
The speciation characteristics of the varying binding phase DGT devices were evaluated.
This evaluation provided important directions for their applications. With comparison to
SC-database model it was found that the measured DGT labile fractions of metals by
varying DGT systems in solutions containing EDTA were inorganic fractions. In
solutions containing humic acid, it was suggested that the metal-HA complexes were not
significantly measured by the various DGT systems with either polyacrylamide or dialysis
membrane diffusive layer. The results from field deployment of the DGT devices were
explained by comparing the various binding phase DGT measurements with the PSS
measurements. Other properties of the binding phases were also evaluated. The
advantages of using P81 ion exchange membrane over gel based binding phases were its
reusability without significant lost of its binding metal properties (five times) and its
198
Chapter 8
constant volume and mechanical strength irrespective of pH and ionic strength. The use
of PSS liquid binding phase provided a mobile, high binding capacity and broad pH
working range (3.0 – 8.7) for DGT. There is no need for elution steps for PSS binding
phase DGT system which is required for solid binding phase DGT. This simplification
increased the accuracy of DGT analysis. The use of dialysis membrane diffusive layer
and PSS binding phase minimised biofouling effects on DGT, which was a serious
problem for solid binding phase DGT 161, 275 when using 0.45 µm filter membrane as a
protect layer and polyacrylamide gel as a diffusive layer. The applicable pH and ionic
strength range of the binding phases were compared, which gave information on
deployment in natural waters.
199
Chapter 9
Chapter 9 General Conclusions
200
Chapter 9
This thesis describes the development and applications of the diffusive gradients in thin
films (DGT) technique for in situ measurements of labile metal species in waters. The key
elements of the technique are the efficient and selective binding of the analytes to a
binding phase and effective diffusion in a well-defined diffusion layer (Chapter 1).
Throughout the course of this work, we have demonstrated that for a DGT sensor, the
performance of the system can be further improved by employing the series of
homogeneous binding phases: binding hydrogels, binding membrane, and polymeric
binding solution. The use of these new binding phases has lead to the developments of the
DGT technique in terms of speciation ability, reproducibility, and processibility.
Firstly, a novel poly(acrylamide-co-acrylic acid) copolymer hydrogel (PAM-PAA) was
synthesised and found to be capable of selective binding of the transition metals such as
Cu2+ and Cd2+ over alkali and alkaline earth metals (Chapter 3). This gel based binding
phase was used with the diffusive gradients in thin-films technique (DGT) for trace metal
analysis in natural waters. The gel was prepared by the controlled hydrolysis of
polyacrylamide hydrogel in alkali solution. FTIR and elemental analysis indicated that the
composition of the copolymer was approximately two units of acrylic acid for every unit
of acrylamide in a syndiotactic-rich structure. The pKa was found to be 4.5. At pH above
5, the carboxylic acid groups were in the salt form and had a greater capacity to bind the
transition metals Cu2+ (1.59 µmoles cm-2) and Cd2+ (1.56 µmoles cm-2). The degree of
swelling (qw) of the gel under equilibrium conditions increased to 120 times that of its
dried state at pH > 6, and was relatively stable when pH > 6. The degree of swelling was
also found to be influenced by ionic strength. This swelling property limited its
application in DGT. Dramatic increase or decrease of the gel volume may cause the
breakage of upper layer of the DGT device, or incomplete coverage of the diffusive layer.
Because of these swelling properties the gels were needed to be stored in appropriate
201
Chapter 9
conditions, similar to those of deployment, before being used with DGT. The optimum
deployment conditions were at pH above 6 and under conditions of relatively stable ionic
strength.
Secondly, a new copolymer poly(acrylamidoglycolic acid-co-acrylamide) (PAAG-PAM)
hydrogel was prepared with a 3:1 ratio of AAGA monomer units to AAm monomer units
(Chapter 4). This gel was found to bind Cu2+ ions selectively with a binding capacity of
5.3 µmole.cm-2 for non-competitive uptake and 1.30 µmole.cm-2 for competitive uptake
with other metal ions. The suitability of using this gel as a binding phase with the DGT
technique was confirmed by obtaining a linear response between the accumulated mass
and the metal uptake time. 95 - 100% recovery with a DGT uptake experiment was also
observed. Similar swelling properties of this gel to PAM-PAA gel as described in Chapter
3 were observed. When the gel contains high percentage of water it becomes fragile. It
also needs to be stored in a NaNO3 solution with similar ionic strength to the water
solution in which the DGT devices are going to be deployed, to minimise the degree of the
gel size changing. To overcome the limitations of this gel, binding phase with more stable
shape to the change of pH and ionic strength are required.
Thirdly, the Whatman P81 cellulose phosphate ion exchange membrane (P81) has been
successfully used as the binding phase for DGT applications (Chapter 5). The
performance of this new DGT binding phase was investigated for analysis of Cu2+ and
Cd2+ in a synthetic lake water matrix. The ion exchange activity of the new binding phase
can be regenerated and, therefore, reused in DGT application. This reuse of the phase
lowered the cost of DGT analysis since the conventional binding phase in DGT, Chelex
100/polyacrylamide gel, was expensive to make due to the agarose derived cross linker
expense. The new binding phase exhibited excellent mechanical properties and overcame
202
Chapter 9
many of the problems of the hydrogel based binding phases. Those problems included
fragility caused handling difficulty, swelling or shrinking with the changes of pH or ionic
strength conditions caused breakage of the diffusive gel or incomplete coverage of the
upper layer. Perhaps the most significant aspect of this work is that it opens up the
possibility of employing a new range of binding phases in DGT analysis, i.e. binding
phases not limited to gel-based systems. There are a myriad of other solid ion exchange
membranes and other binding materials available. This work has shown the feasibility of
employing such materials in DGT technique. The limitations of this binding membrane
may be the roughness of the solid surfaces causing that the contact between the diffusive
and binding phases is not perfect, and the need for elution procedures.
Fourthly, a new style of DGT device has been designed using a poly(4-styrenesulfonate)
(PSS) solution binding phase, and a dialysis membrane diffusive layer (Chapter 6). The
diffusion properties of the dialysis membrane and the binding properties of the PSS
solution were characterised and found to be suitable for use with DGT. A new DGT
device was designed and validated by demonstrating a linear mass vs. time relationship for
Cd and Cu in synthetic waters and spiked natural waters (Cu only).
The major advantages of this DGT device include a theoretically ideal mass transport by
the well-defined diffusive layer available from massive production and mass accumulation
by the mobile binding solution. The fragility and swelling problems of gel based binding
phases were overcome. In addition, the DGT procedures were simplified by removal of
elution steps, which were required for all solid binding phases. This simplification
resulted in the increase of analytical accuracy. One of the important features of DGT,
long-term integrative measurement, was implemented using this device, due to its better
203
Chapter 9
antifouling property, allowing it to be deployed for longer time. The only drawback is the
need for matrix-matched calibrations for instrumental analysis.
The speciation capability and field deployment of this new DGT device were investigated
in details in Chapter 7. The comparison of DGT results with computer modelling
calculations showed that both methods give similar trends of information on labile
fractions of metal concentrations. These results confirmed the validation of using the PSS
liquid binding phase and cellulose dialysis membrane diffusive layer. The deployment of
the DGT device in natural waters further validated its speciation ability. The site on
Marine Stadium showed higher concentration of copper because of the release of
antifouling paints from boats berthing. On the site with much abundant humic substances,
Parkwood Pond, less percentage of DGT labile metal was measured due to the complexing
reactions between the humic substances and metals.
Finally, the newly developed binding phases and the Chelex 100 gel were evaluated for
trace metal speciation measurement both in laboratory and in natural water conditions
(Chapter 8). With comparison to SC-database model it was found that the measured DGT
labile fractions of metals by varying DGT systems in solutions containing EDTA were
inorganic fractions. In solutions containing humic acid, it was suggested that the metal-
HA complexes were not significantly measured by the various DGT systems with either
polyacrylamide or dialysis membrane diffusive layer. The results from field deployment
of the DGT devices were explained by comparing the various binding phase DGT
measurements with the PSS measurements. Other properties of the binding phases were
also evaluated. The advantages of using P81 ion exchange membrane over gel based
binding phases were its reusability without significant lost of its binding metal properties
(five times) and its constant volume and mechanical strength irrespective of pH and ionic
204
Chapter 9
strength. The use of PSS liquid binding phase provided a mobile, high binding capacity
and broad pH working range (3.0 – 8.7) for DGT. There is no need for elution steps for
PSS binding phase DGT system which is required for solid binding phase DGT. This
simplification increased the accuracy of DGT analysis. The use of dialysis membrane
diffusive layer and PSS binding phase minimised biofouling effects on DGT, which was a
serious problem for solid binding phase DGT when using 0.45 µm filter membrane as a
protect layer and polyacrylamide gel as a diffusive layer. The applicable pH and ionic
strength range of the binding phases were compared, which gave information on
deployment in natural waters.
There is a wide area of continuing research in this study. The syntheses of new polymers
for selective and sensitive binding of metals for DGT applications may result in various
fractions of DGT measurements. The solution binding phase, in particular, provided
opportunities to develop the DGT technique in a wider view, due to its inherent features.
Clearly, the development of these series of binding phases has opened doors to further
development of the DGT technique.
Although extensive investigations on the development of new generation DGT technique
have been carried out in this work, some aspects of the newly developed DGT systems
need to be explored further. This research has highlighted a number of areas for future
studies.
(i) Application of these newly developed DGT systems to different types of
environmental samples under various conditions, which will gain better
understanding on the applicability and usefulness of the developed method.
205
Chapter 9
(ii) Investigation of more binding phases, especially, the investigation of other types of
liquid binding phases, which will lead to the improvement of DGT performance in
terms of number of detectable species, selectivity, speciation capacity and
applicability.
(iii) Current DGT system has to be coupled with an appropriate analytical method to
provide the analytical data. In this regard, it is essentially an in situ sampling
device. More effort should be devoted to develop the third generation DGT system
that capable of in situ detection by incorporating an analytical method into the DGT
device. With our newly developed liquid binding phase DGT system we believe
this is highly feasible.
206
References
REFERENCES
(1) Ure, A. M.; Davidson, C. M.; (Eds) Chemical Speciation in the Environment; Blackie
Academic & Proffessional: London, 1995.
(2) Buffle, J.; Horvai, G. In Situ Monitoring of Aquatic Systems Chemical Analysis and
Speciation; John Wiley & Sons Ltd: Chichester, 2000.
(3) Tessier, A.; Turner, D. R.; (Eds) Metal Speciation and Bioavailability in Aquatic
Systems; Wiley: New York, 1995.
(4) Buffle, J.; De Vitre, R. R.; (Eds) Chemical and Biological Regulation of Aquatic
Systems; Lews: London, 1994.
(5) Tessier, A.; Turner, D. R.; (Eds) Metal Speciation and Bioavailability in Aquatic
Systems; Wiley: Chichester, 1995.
(6) Tercier, M.-L.; Buffle, J.; Graziottin, F. Electroanalysis 1998, 10, 355-363.
(7) Donat, J. R.; Bruland, K. W. Trace Elem. Nat. Waters 1995, 247-281.
(8) Salbu, B.; Steinnes, E.; (Eds) Trace Elements in Natural Waters; CRC Press: London,
1995.
(9) Braungardt, C.; Achterberg, E. P.; Nimmo, M. Analytica Chimica Acta 1998, 377,
205-215.
(10) Paucot, H.; Wollast, R. Marine Chemistry 1997, 58, 229-244.
(11) Khan, H.; Brush, G. S. Estuaries 1994, 17, 345-360.
(12) Vale, C. Science of the Total Environment 1990, 97-98, 137-154.
(13) Florence, T. M. Talanta 1982, 29, 345-364.
(14) Davison, W.; Fones, G.; Harper, M.; Teasdale, P.; Zhang, H. In Situ Monitoring of
Aquatic Systems Chemical Analysis and Speciation; John Wiley & Sons Ltd:
Chichester, 2000.
(15) Davison, W.; Zhang, H. Nature (London) 1994, 367, 546-548.
(16) Zhang, H.; Davison, W. Anal. Chem. 1995, 67, 3391-3400.
(17) Dunn, R. J. K. Evaluation of DGT (Diffusive Gradients in Thin Films) against
Traditional Methods for Heavy Metal Measurements: Case Studies in the Gold Coast
Broadwater, Honours Thesis; Griffith University: Gold Coast, 2002.
(18) Buffle, J.; Wilkinson, K. J.; Tercier, M.-L.; Parthasarathy, N. Ann. Chim. (Rome)
1997, 87, 67-82. 207
References
(19) Struempler, A. W. Analytical Chemistry 1973, 45, 2251-2254.
(20) Truitt, R. E.; Weber, J. H. Analytical Chemistry 1979, 51, 2057-2059.
(21) Zhang, H.; Davison, W.; Miller, S.; Tych, W. Geochim. Cosmochim. Acta 1995, 59,
4181-4192.
(22) Torre, M. C. A.-D. l.; Beaulieu, P.-Y.; Tessier, A. Analytica Chimica Acta 2000, 418,
53-68.
(23) Zhang, H.; Davison, W. Anal. Chem. 2000, 72, 4447-4457.
(24) Denney, S.; Sherwood, J.; Leyden, J. Sci. Total Environ. 1999, 239, 71-80.
(25) Twiss, M. R.; Moffett, J. W. Environmental Science & Technology 2002, 36, 1061
1068.
(26) Campell, P. G. C. Metal Speciation and Bioavailability in Aquatic Systems; Wiley:
New York, 1995.
(27) Stumm, W.; Morgan, J. J. Aquatic Chemistry; John Wiley & Sons: New York, 1981.
(28) Buffle, J. Complexation Reactions in Aquatic Chemistry; John Wiley & Sons:
Chichester, UK, 1988.
(29) Mantoura, R. F. C. Elsevier Oceanogr. Ser. (Amsterdam) 1981, 31, 179-223.
(30) Lund, W. NATO ASI Ser., Ser. G 1990, 23, 43-56.
(31) Cosovic, B. Aqueous surface chemistry: assessment of adsorption characteristics of
organic solutes by electrochemical methods; John Wiley & Sons: New York, 1985.
(32) Wetzel, R. G. Limnology; Saunders: Philadelphia, 1983.
(33) Hering, J. G.; Morel, F. M. M. Environ. Sci. Technol. 1988, 22, 1234-1237.
(34) Beveridge, A.; Pickering, W. F. Water, Air, Soil Pollut. 1980, 14, 171-185.
(35) Ortego, L. S.; Benson, W. H. Environ. Toxicol. Chem. 1992, 11, 261-265.
(36) Ma, H.; Kim, S. D.; Cha, D. K.; Allen, H. E. Environ. Toxicol. Chem. 1999, 18, 828
837.
(37) Florence, T. M.; Batley, G. E. CRC Crit. Rev. Anal. Chem. 1980, 9, 219-296.
(38) Noller, B. N. Chemistry in Australia 1992, 59, 403-405.
(39) Gordon, A. S.; Dyer, B. J.; Kango, R. A.; Donat, J. R. Marine Chemistry 1996, 53,
163-172.
(40) Donat, J. R.; Lao, K. A.; Bruland, K. W. Analytica Chimica Acta 1994, 284, 547-571.
(41) Capodaglio, G.; Coale, K. H.; Bruland, K. W. Mar. Chem. 1990, 29, 221-233.
208
References
(42) Capodaglio, G.; Toscano, G.; Scarponi, G.; Cescon, P. Ann. Chim. (Rome) 1989,
79, 543-559.
(43) Batley, G. E.; Gardner, D. Estuarine and Coastal Marine Science 1978, 7, 59-70.
(44) Apte, S. C.; Gardner, M. J.; Ravenscroft, J. E.; Turrell, J. A. Anal. Chim. Acta 1990,
235, 287-297.
(45) Hanson, A. K., Jr.; Sakamoto-Arnold, C. M.; Huizenga, D. L.; Kester, D. R. Mar.
Chem. 1988, 23, 181-203.
(46) Van den Berg, C. M. G.; Rebello, A. d. L. Sci. Total Environ. 1986, 58, 37-45.
(47) Donat, J. R.; Bruland, K. W. Mar. Chem. 1990, 28, 301-323.
(48) Bruland, K. W. Limnol. Oceanogr. 1989, 34, 269-285.
(49) Coale, K. H.; Bruland, K. W. Limnology and Oceanography 1988, 33, 1084-1101.
(50) Salomons, W.; Foerstner, U. Metals in the Hydrocycle; Springer-Verlag: Berlin, Fed.
Rep. Ger., 1984.
(51) Horne, R. A. Marine Chemistry, the Structure of Water and the Chemistry of the
Hydrosphere; Wiley-Interscience: New York, 1969.
(52) Aster, S. R. Chemical Oceanography; Academic Press: London, 1978.
(53) Hammond, L.; Synnot, R.; (Eds) Marine Biology; longman Cheshire Pty Ltd: Sydney,
1994.
(54) Florence, T. M.; Batley, G. E. Critical Reviews in Analytical Chemistry 1980, 9, 219
296.
(55) Waite, T. D.; Morel, F. M. M. Environmental Science and Technology 1984, 18, 860
868.
(56) Cunningham, K. M.; Goldberg, M. C.; Weiner, E. R. Environmental Science and
Technology 1988, 22, 1090-1097.
(57) Gilmour, C. C.; Riedel, G. S. Water, Air, and Soil Pollution 1995, 80, 747-756.
(58) Watras, C. J.; Bloom, N. S.; Claas, S. A.; Morrison, K. A.; Gilmour, C. C.; Craig, S.
R. Water, Air, and Soil Pollution 1995, 80, 735-745.
(59) Rudd, J. W. M. Water, Air, and Soil Pollution 1995, 80, 697-713.
(60) Guimaraes, J. R. D.; Meili, M.; Malm, O.; de Souza Brito, E. M. Science of the Total
Environment 1998, 213, 165-175.
(61) Clark, E. A.; Sterritt, R. M.; Lester, J. N. Environmental Science and Technology
1988, 22, 600-604.
209
References
(62) Seligman, P. F.; Valkirs, A. O.; Lee, R. F. Environmental Science and Technology
1986, 20, 1229-1235.
(63) Kumaresan, M.; Riyazuddin, P. Research Journal of Chemistry and Environment
1999, 3, 59-79.
(64) Williams, D. R. Coordination Chemistry Reviews 1999, 185-186, 177-188.
(65) Kramer, J. R.; Allen, H. E.; Davison, W.; Godtfredsen, K. L.; Meyer, J. S.; Perdue, E.
M.; Tipping, E.; Van de Meent, D.; Westall, J. C. Reassessment of Metals Criteria for
Aquatic Life Protection: Priorities for Research and Implementation, Proceedings of
the Pellston Workshop on Reassessment of Metals Criteria for Aquatic Life
Protection, 26th, Pensacola, Fla., Feb. 10-14, 1996 1997, 57-70.
(66) Koplik, R.; Curdova, E.; Mestek, O. Chemicke Listy 1997, 91, 38-47.
(67) Donard, O. F. X.; Caruso, J. A. Spectrochimica Acta, Part B: Atomic Spectroscopy
1998, 53B, 157-163.
(68) Witters, H. E. Ecotoxicology and Environmental Safety 1998, 41, 90-95.
(69) Nelson, H.; Benoit, D.; Erickson, R.; Mattson, V.; Lindberg, J.; Environ. Res.
Lab.,Duluth,MN,USA. FIELD URL:, 1986, pp 121.
(70) Roast, S. D.; Widdows, J.; Jones, M. B. Environmental Toxicology and Chemistry
2001, 20, 1078-1084.
(71) Banaszak, J. E.; Rittmann, B. E.; Reed, D. T. Journal of Radioanalytical and Nuclear
Chemistry 1999, 241, 385-435.
(72) Mandal, R.; Hassan, N. M.; Murimboh, J.; Chakrabarti, C. L.; Back, M. H.; Rahayu,
U.; Lean, D. R. S. Environmental Science and Technology 2002, 36, 1477-1484.
(73) Gustafsson, O.; Gschwend, P. M. Limnology and Oceanography 1997, 42, 519-528.
(74) Garruto, R. M.; Flaten, T. P.; Wakayama, I. Mineral and Metal Neurotoxicology
1997, 27-34.
(75) Robinson, J. W.; Deano, P. M. Am. Lab. (Fairfield, Conn.) 1986, 18, 17-20, 22, 24
16.
(76) Mandal, B. K.; Suzuki, K. T. Talanta 2002, 58, 201-235.
(77) Kaise, T.; Watanabe, S.; Itoh, K. Chemosphere 1985, 14, 1327-1332.
(78) Cannavale, V.; Chiusano, A. Giornale di Medicina Militare 1992, 142, 161-163.
(79) Leeuwangh, P.; Nijman, W.; Visser, H.; Kolar, Z.; De Goey, J. J. M. Meded. Fac.
Landbouwwet., Rijksuniv. Gent 1976, 41, 1483-1490.
210
References
(80) Zielinski, W.; Brzezinski, J. Rocz. Panstw. Zakl. Hig. 1983, 34, 95-102.
(81) Mertz, W.; Cornatzer, W. E. Newer Trace Elements in Nutrition; Dekker: New York,
1971.
(82) Cooley, T. N.; Martin, D. F. Journal of Inorganic and Nuclear Chemistry 1980, 42,
151-153.
(83) Driscoll, C. T., Jr.; Baker, J. P.; Bisogni, J. J., Jr.; Schofield, C. L. Nature (London,
United Kingdom) 1980, 284, 161-164.
(84) Florence, T. M.; Belew, W. L. Journal of Electroanalytical Chemistry and Interfacial
Electrochemistry 1969, 21, 157-167.
(85) Whitfield, M.; Turner, D. R. Chemical Modelling in Aqueous Systems; American
Chemical Society: Washington D. C., 1979.
(86) Magnuson, V. R.; Harriss, D. K.; Sun, M. S.; Taylor, D. K.; Glass, G. E. Chemical
Modelling in Aqueous Systems; American Chemical Society: Washington D.C.,
1979.
(87) Naimo, T. J. Ecotoxicology 1995, 4, 341-362.
(88) Santschi, P. H.; Adler, D. M.; Amdurer, M. NATO Conference Series IV: Marine
Sciences 1983, 9, 331-349.
(89) Chen, Z.; Mayer, L. M. Marine Ecology: Progress Series 1999, 176, 139-151.
(90) Canterford, G. S.; Canterford, D. R. J. Mar. Biol. Assoc. U. K. 1980, 60, 227-242.
(91) Morel, F. M. M. Principles of Aquatic Chemistry; Wiley-Interscience: New York,
1983.
(92) Kaiser, K. L. E. Can. J. Fish. Aquat. Sci 1980, 37, 211-218.
(93) Urbanowski, J. L.; Piper, R. C. Journal of Biological Chemistry 1999, 274, 38061
38070.
(94) Satofuka, H.; Fukui, T.; Takagi, M.; Atomi, H.; Imanaka, T. Journal of Inorganic
Biochemistry 2001, 86, 595-602.
(95) Williams, R. J. Philos. Trans. R. Soc. London B, 1981, 294, 57-74.
(96) Luoma, S. N. Sci. Total Environ. 1983, 28, 1-22.
(97) Turner, D. R. Elsevier Oceanogr. Ser. (Amsterdam) 1986, 43, 191-200.
(98) Simkiss, K.; Taylor, M. G. Rev. Aquat. Sci. 1989, 1, 173-188.
(99) Rudakova, E. V.; Karakis, K. D.; Sidorshina, T. N. Fiziol. Biokhim. Kul't. Rast. 1988,
20, 3-12.
211
References
(100) Kinter, W. B.; Pritchard, J. B., Bethesda, Md 1977.
(101) Di Toro, D. M.; Allen, H. E.; Bergman, H. L.; Meyer, J. S.; Paquin, P. R.; Santore, R.
C. Environmental Toxicology and Chemistry 2001, 20, 2383-2396.
(102) Paquin, P. R.; Zoltay, V.; Winfield, R. P.; Wu, K. B.; Mathew, R.; Santore, R. C.; Di
Toro, D. M. Comparative Biochemistry and Physiology, Part C: Toxicology &
Pharmacology 2002, 133C, 305-343.
(103) Santore, R. C.; Di Toro, D. M.; Paquin, P. R.; Allen, H. E.; Meyer, J. S.
Environmental Toxicology and Chemistry 2001, 20, 2397-2402.
(104) Janssen, C. R.; Heijerick, D. G.; De Schamphelaere, K. A. C.; Allen, H. E.
Environment International 2003, 28, 793-800.
(105) Pagenkopf, G. K. Environmental Science and Technology 1983, 17, 342-347.
(106) Tipping, E. Computers & Geosciences 1994, 20, 973-1023.
(107) Santore, R. C.; Driscoll, C. T. SSSA Special Publication 1995, 42, 357-375.
(108) Erickson, R. J.; Benoit, D. A.; Mattson, V. R.; Nelson, H. P., Jr.; Leonard, E. N.
Environmental Toxicology and Chemistry 1996, 15, 181-193.
(109) Diamond, J. M.; Gerardi, C.; Leppo, E.; Miorelli, T. Environmental Toxicology and
Chemistry 1997, 16, 1480-1487.
(110) Bury, N. R.; Galvez, F.; Wood, C. M. Environmental Toxicology and Chemistry
1999, 18, 56-62.
(111) Karen, D. J.; Ownby, D. R.; Forsythe, B. L.; Bills, T. P.; La Point, T. W.; Cobb, G.
B.; Klaine, S. J. Environmental Toxicology and Chemistry 1999, 18, 63-70.
(112) Karapanagiotis, N. K.; Sterritt, R. M.; Lester, J. N. Environmental Pollution (Oxford,
United Kingdom) 1990, 67, 259-278.
(113) Buffle, J.; Leppard, G. G. Environ. Sci. Technol. 1995, 29, 2169-2175.
(114) Buffle, J.; Leppard, G. G. Environ. Sci. Technol. 1995, 29, 2176-2184.
(115) Andersen, M. K.; Raulund-Rasmussen, K.; Strobel, B. W.; Hansen, H. C. B. Journal
of Environmental Quality 2002, 31, 168-175.
(116) Buffle, J.; Wilkinson, K. J.; Tercier, M.-L.; Parthasarathy, N. Annali di Chimica
(Rome) 1997, 87, 67-82.
(117) Branica, M. Kemija u Industriji 2001, 50, 493-499.
(118) Mevius, W. Neue DELIWA-Zeitschrift 1988, 39, 82-87.
(119) Chen, Y.-W.; Buffle, J. Water Res. 1996, 30, 2185-2192.
212
References
(120) Chen, Y.-W.; Buffle, J. Water Res. 1996, 30, 2178-2184.
(121) Mota, A. M.; Correia dos, M. M. Metal Speciation and Bioavailability in Aquatic
Systems; Wiley: New York, 1999.
(122) Kramer, K. J. M. Tidal Estuaries : Manual of Sampling and Analytical Procedures;
A.A. Balkema for the European Commission: Rotterdam, 1994.
(123) Gamo, T. Bunseki 1998, 832-839.
(124) Beichert, J. K.; Kanitz, J. Gewaesserschutz, Wasser, Abwasser 1993, 135, 647-660.
(125) Bufflap, S. E.; Allen, H. E. Water Res. 1995, 29, 165-177.
(126) Koryta, J.; Stulik, K. Ion-Selective Electrodes. 2nd Ed; Cambridge University Press:
Cambridge, UK, 1983.
(127) Moody, G. J.; Thomas, J. D. R. Selective Ion-Sensitive Electrodes (Merrow Technical
Library; Practical Science); Merrow: Watford, Engl., 1971.
(128) Pineros, M. A.; Shaff, J. E.; Kochian, L. V. Plant Physiology 1998, 116, 1393-1401.
(129) Midorikawa, T.; Tanoue, E.; Sugimura, Y. Analytical Chemistry 1990, 62, 1737
1746.
(130) Buffle, J.; Tercier-Waeber, M.-L. In Situ Monitoring of Aquatic Systems Chemical
Analysis and Speciation; John Wiley & Sons Ltd: Chichester, 2000.
(131) Henze, G. NATO ASI Ser., Ser. G 1990, 23, 391-408.
(132) Mizuike, A. Pure Appl. Chem. 1987, 59, 555-564.
(133) Heyrowsky, J.; Kuta, J. Principles of Polarography; Academic Press: London, 1966.
(134) Buffle, J. Complexation Reactions in Aquatic Systems: An Analytical Approach;
Ellis Horwood Ltd.: Chichester, UK, 1988.
(135) Buffle, J.; Wilkinson, K. J.; Stoll, S.; Filella, M.; Zhang, J. Environmental Science
and Technology 1998, 32, 2887-2899.
(136) Pavillon, J. F.; Menesria, R.; Lacaze, J. C. J. Rech. Oceanogr. 1992, 17, 12-16.
(137) Mayer, L. M. Limnol. Oceanogr. 1976, 21, 909-912.
(138) Batley, G. E. Trace Element Speciation: Analytical Methods and Problems; CRC
Press: Boca Raton, Fla., 1989.
(139) Buffle, J.; Perret, D.; Newman, M. Environ. Part. 1992, 1, 171-230.
(140) Carignan, R.; Rapin, F.; Tessier, A. Geochim. Cosmochim. Acta 1985, 49, 2493
2497.
213
References
(141) Shuttleworth, S. M.; Davison, W.; Hamilton-Taylor, J. Environ. Sci. Technol. 1999,
33, 4169-4175.
(142) Cox, J. A.; Bhatnagar, A.; Francis Robert W, Jr. Talanta 1986, 33, 713-716.
(143) Danesi, P. R. Separation Science and Technology 1984, 19, 857-894.
(144) Knutsson, M.; Nilve, G.; Mathiasson, L.; Joensson, J. A. Journal of Agricultural and
Food Chemistry 1992, 40, 2413-2417.
(145) Malcus, F.; Djane, N. K.; Mathiasson, L.; Johansson, G. Analytica Chimica Acta
1996, 327, 295-300.
(146) Davison, W.; Grime, G. W.; Morgan, J. A. W.; Clarke, K. Nature (London) 1991,
352, 323-325.
(147) Chang, L.-Y.; Davison, W.; Zhang, H.; Kelly, M. Anal. Chim. Acta 1998, 368, 243
253.
(148) Snodgrass, W. J. Sediments and Water Interactions; Springer: New York, 1986.
(149) Scally, S.; Davison, W.; Zhang, H. Environmental Science and Technology 2003, 37,
1379-1384.
(150) Zhang, H.; Davison, W.; Gadi, R.; Kobayashi, T. Anal. Chim. Acta 1998, 370, 29-38.
(151) Davison, W.; Fones, G. R.; Grime, G. W. Nature (London) 1997, 387, 885-888.
(152) Chang, L.-Y. Development and Application of Diffusive Gradients in Thin-films
(DGT) for the Measurement of Stable and Radioactive Caesium and Strontium in
Surface Waters, Ph.D Thesis; Lancaster University: Lancaster, UK, 1998.
(153) Zhang, H.; Davison, W.; Grime, G. W. ASTM Spec. Tech. Publ. 1995, STP 1293,
170-181.
(154) Zhang, H.; Davison, W. Anal. Chim. Acta 1999, 398, 329-340.
(155) Davison, W.; Zhang, H.; Grime, G. W. Environ. Sci. Technol. 1994, 28, 1623-1632.
(156) Teasdale, P. R.; Hayward, S.; Davison, W. Anal. Chem. 1999, 71, 2186-2191.
(157) Hudson, R. J. M. Science of the Total Environment 1998, 219, 95-115.
(158) Mirimanoff, N.; Wilkinson, K. J. Environmental Science and Technology 2000, 34,
616-622.
(159) Van Leeuwen, H. P. Environmental Science and Technology 1999, 33, 3743-3748.
(160) Davison, W. J. Electroanal. Chem. Interfacial Electrochem. 1978, 87, 395-404.
(161) Webb, J. A.; Keough, M. J. Marine Pollution Bulletin 2002, 44, 222-229.
214
References
(162) Beaulieu, P. Y. Verification d'une Methode DGT Pour Mesurer Les Metaux Traces et
Son Utilisation In Situ Comparee a La Dialyse In Situ, M.Sc Thesis; Univerite du
Quebec: Sainte-Foy, Canada, 1999.
(163) Dunn, R. J. K.; Teasdale, P. R.; Warnken, J.; Schleich, R. R. Environmental Science
and Technology 2003, 37, 2794-2800.
(164) Teasdale, P. Unpublished results.
(165) Munksgaard, N. C.; Parry, D. L. Journal of Environmental Monitoring 2003, 5, 145
149.
(166) Sangi, M. R.; Halstead, M. J.; Hunter, K. A. Analytica Chimica Acta 2002, 456, 241
251.
(167) Fones, G. R.; Moffett, J. W. Abstracts of Papers, 224th ACS National Meeting,
Boston, MA, United States, August 18-22, 2002 2002, GEOC-018.
(168) Pesavento, M.; Biesuz, R.; Gnecco, C.; Magi, E. Analytica Chimica Acta 2001, 449,
23-33.
(169) Warshawsky, A. Synthesis and Separation Using Functional Polymers; Wiley: New
York, 1988.
(170) Klein, E. J. Membr. Sci. 2000, 179, 1-27.
(171) Kremer, M.; Pothmann, E.; Roessler, T.; Baker, J.; Yee, A.; Blanch, H.; Prausnitz, J.
M. Macromolecules 1994, 27, 2965-2973.
(172) Dusek, K.; Janacek, J. Journal of Applied Polymer Science 1975, 19, 3061-3075.
(173) Yao, K.-J.; Zhou, W.-J. Journal of Applied Polymer Science 1994, 53, 1533-1538.
(174) Baker, J. P.; Hong, L. H.; Blanch, H. W.; Prausnitz, J. M. Macromolecules 1994, 27,
1446-1454.
(175) Denizli, A.; Salih, B.; Arica, M. Y.; Kesenci, K.; Hasirci, V.; Piskin, E. J.
Chromatogr., A 1997, 758, 217-226.
(176) Denizli, A.; Kesenci, K.; Arica, M. Y.; Salih, B.; Hasirci, V.; Piskin, E. Talanta 1998,
46, 551-558.
(177) Shah, R.; Devi, S. React. Funct. Polym. 1996, 31, 1-9.
(178) Uludag, Y.; Ozbelge, H. O.; Yilmaz, L. Journal of Membrane Science 1997, 129, 93
99.
(179) Sasaki, K. J.; Burnett, S. L.; Christian, S. D.; Tucker, E. E.; Scamehorn, J. F.
Langmuir 1989, 5, 363-369.
215
References
(180) Muslehiddinoglu, J.; Uludag, Y.; Ozbelge, H. O.; Yilmaz, L. Journal of Membrane
Science 1998, 140, 251-266.
(181) Rivas, B. L.; Martinez, E.; Pereira, E.; Geckeler, K. E. Polymer International 2001,
50, 456-462.
(182) Rivas, B. L.; Pooley, S. A.; Luna, M. Macromolecular Rapid Communications 2001,
22, 418-421.
(183) Rivas, B. L.; Pereira, E. D.; Moreno-Villoslada, I. Progress in Polymer Science 2002,
28, 173-208.
(184) Rivas, B. L.; Moreno-Villoslada, I. J. Phys. Chem. B 1998, 102, 6994-6999.
(185) Yin, X.-q.; Zhang, Q.; Yu, W.-x.; Yang, L.-c.; Lin, Q. Wuji Huaxue Xuebao 2002, 18,
87-90.
(186) Kurpiel-Gorgol, R.; Brzyska, W. Journal of Thermal Analysis and Calorimetry 2003,
71, 539-548.
(187) Teasdale, P. Personal Communication.
(188) Sutcliffe, D. W.; Carrick, T. R. Freshwater Biol. 1983, 13, 323-352.
(189) Harris, D. C. Quantitative Chemical Analysis. 2nd Ed; W. H. Freeman and Co.: New
York, N. Y., 1995.
(190) Skoog, D. A.; West, D. M. Analytical Chemistry: An Introduction. 7th Ed; Saunders
College Publishing: Fort Worth, 1996.
(191) Wilson, A. L. The Chemical Analysis of Water. General Principles and Techniques;
Chem. Soc.: London, Engl., 1978.
(192) Muslehiddinoglu, J.; Uludag, Y.; Ozbelge, H. O.; Yilmaz, L. Talanta 1998, 46, 1557
1565.
(193) Chanda, M.; Rempel, G. L. React. Polym. 1993, 19, 213-223.
(194) Kabay, N.; Katakai, A.; Sugo, T.; Egawa, H. J. Appl. Polym. Sci. 1993, 49, 599-597.
(195) Montembault, V.; Folliot, V.; Soutif, J. C.; Brosse, J. C. React. Polym. 1994, 22, 81
89.
(196) Alexandratos, S. D.; Trochimczuk, A. W.; Crick, D. W.; Horwitz, E. P.; Gatrone, R.
C.; Chiarizia, R. Macromolecules 1996, 29, 1021-1026.
(197) Kulkarni, R. A.; Gundiah, S. Makromol. Chem. 1984, 185, 957-967.
(198) March, J. Advanced Organic Chemistry: Reactions, Mechanisms, and Structure,
Fourth Edition; Wiley: New York, N. Y., 1992.
216
References
(199) Durmaz, S.; Okay, O. Polymer 2000, 41, 3693-3704.
(200) Hummel, D. O. Infrared Analysis of Polymers, Resins and Additives, An Atlas; Wiley
Interscience: New York, 1969.
(201) Ahn, J. S.; Choi, H. K.; Cho, C. S. Biomaterials 2001, 22, 923-928.
(202) Nikaido, H.; Rosenberg, E. Y. J. Gen. Physiol. 1981, 77, 121-135.
(203) Molyneux, P. Water-Soluble Synthetic Polymers: Properties and Behavior; CRC
Press: Boca Raton, Fla., 1984.
(204) Osada, Y.; Okuzaki, H.; Gong, J. P. Trends Polym. Sci. (Cambridge, U. K.) 1994, 2,
61-66.
(205) Brazel, C. S.; Peppas, N. A. Macromolecules 1995, 28, 8016-8020.
(206) Cohen, Y.; Ramon, O.; Kopelman, I. J.; Mizrahi, S. J. Polym. Sci., Part B: Polym.
Phys. 1992, 30, 1055-1067.
(207) Shibayama, M.; Mizutani, S.-y.; Nomura, S. Macromolecules 1996, 29, 2019-2024.
(208) Shibayama, M.; Uesaka, M.; Shiwa, Y. J. Chem. Phys. 1996, 105, 4350-4357.
(209) Ravichandran, P.; Shantha, K. L.; Rao, K. P. International Journal of Pharmaceutics
1997, 154, 89-94.
(210) Yoo, M. K.; Sung, Y. K.; Lee, Y. M.; Cho, C. S. Polymer 2000, 41, 5713-5719.
(211) Baker, J. P.; Blanch, H. W.; Prausnitz, J. M. Polymer 1995, 36, 1061-1069.
(212) Rivas, B. L.; Pooley, S. A.; Soto, M.; Geckeler, K. E. J. Polym. Sci., Part A: Polym.
Chem. 1997, 35, 2461-2467.
(213) Stumm, W.; Morgan, J. J. Aquatic Chemistry; Wiley: New York, N. Y., 1996.
(214) Mandal, R.; Sekaly, A. L. R.; Murimboh, J.; Hassan, N. M.; Chakrabarti, C. L.; Back,
M. H.; Gregoire, D. C.; Schroeder, W. H. Anal. Chim. Acta 1999, 395, 323-334.
(215) Marinsky, J. A.; Anspach, W. M. J. Phys. Chem. 1975, 79, 439-444.
(216) Reed, B. E.; Matsumoto, M. R. Sep. Sci. Technol. 1993, 28, 2179-2195.
(217) Yang, Z.; Zhang, Y.; Markland, P.; Yang, V. C. Journal of Biomedical Materials
Research 2002, 62, 14-21.
(218) Bhadani, S. N.; Prasad, Y. K. Makromol. Chem. 1977, 178, 1841-1851.
(219) Seymour, R. B.; Carraher, C. E., Jr. Polymer Chemistry. An Introduction; Dekker:
New York, N. Y., 1981.
(220) Yan, L.; Qian, F.; Zhu, Q. Polymer International 2001, 50, 1370-1374.
217
References
(221) Yazdani-Pedram, M.; Retuert, J.; Quijada, R. Macromolecular Chemistry and
Physics 2000, 201, 923-930.
(222) Silverstein, R. M.; Webster, F. X. Spectrometric identification of organic compounds;
John Wiley & Sons, Inc.: New York, 1997.
(223) Denizli, A.; Salih, B.; Piskin, E. J. Chromatogr., A 1997, 773, 169-178.
(224) Kantipuly, C.; Katragadda, S.; Chow, A.; Gesser, H. D. Talanta 1990, 37, 491-517.
(225) Egawa, H.; Nakayama, M.; Nonaka, T.; Sugihara, E. J. Appl. Polym. Sci. 1987, 33,
1993-2005.
(226) Choi, S.-H.; Han Jeong, Y.; Jeong Ryoo, J.; Lee, K.-P. Radiation Physics and
Chemistry 2001, 60, 503-511.
(227) Wen, O. H.; Kuroda, S.-i.; Kubota, H. European Polymer Journal 2001, 37, 807-813.
(228) Saito, K.; Yamada, S.; Furusaki, S.; Sugo, T.; Okamoto, J. Journal of Membrane
Science 1987, 34, 307-315.
(229) Fischer, H. J.; Lieser, K. H. Angew. Makromol. Chem. 1993, 208, 133-150.
(230) Denizli, A.; Tanyolac, D.; Salih, B.; Aydinlar, E.; Ozdural, A.; Piskin, E. J. Membr.
Sci. 1997, 137, 1-8.
(231) Brajter, K.; Slonawska, K. Anal. Chim. Acta 1986, 185, 271-277.
(232) Schmitt, D. H.; Fritz, J. S. Talanta 1968, 15, 515-524.
(233) Kabay, N.; Demircioglu, M.; Yayli, S.; Yuksel, M.; Saglam, M.; Levison, P. R. Sep.
Sci. Technol. 1999, 34, 41-51.
(234) Dorfner, K. Ion Exchangers; Ann Arbor Science Publishers Inc.: Michigan, 1972.
(235) Stumm, W.; Sigg, L.; Sulzberger, B. The Role of Coordination at the Surface of
Aquatic Particles in Chemical and Biological Regulation of Aquatic Systems; Lewis
Publishers, USA, 1994.
(236) Volchek, K.; Krentsel, E.; Zhilin, Y.; Shtereva, G.; Dytnersky, Y. Journal of
Membrane Science 1993, 79, 253-272.
(237) Kichik, V. A.; Yagodin, G. A.; Kuleshov, N. F.; Svitsov, A. A. At. Energ. 1985, 58,
272-273.
(238) Pickering, W. F. Chemical speciation in the environment; Blackie Academic &
Proffessional: London, 1995.
(239) Apte, S. C.; Gardner, M. J.; Hunt, D. T. E. Environ. Technol. Lett. 1989, 10, 201
212.
218
References
(240) Benes, P.; Steinnes, E. Water Res. 1974, 8, 947-953.
(241) Juang, R.-S.; Liang, J.-F. Journal of Membrane Science 1993, 82, 163-174.
(242) Samadfam, M.; Jintoku, T.; Sato, S.; Ohashi, H. Journal of Nuclear Science and
Technology 1998, 35, 579-583.
(243) Gregor, H. P.; Luttinger, L. B.; Loebl, E. M. J. Phys. Chem. 1955, 59, 34-39.
(244) Leyte, J. C.; Zuiderweg, L. H.; Van Reisen, M. J. Phys. Chem. 1968, 72, 1127-1132.
(245) Yamaoka, K.; Masujima, T. Bull. Chem. Soc. Jpn. 1979, 52, 1819-1827.
(246) Lange, N. A. Lange's Handbook of Chemistry; McGraw-Hill Book Company: New
York, 1985.
(247) Kotin, L.; Nagasawa, M. J. Am. Chem. Soc. 1961, 83, 1026-1028.
(248) Lapanje, S.; Rice, S. A. J. Am. Chem. Soc. 1961, 83, 496-497.
(249) Pesavento, M.; Biesuz, R. Analytica Chimica Acta 1997, 346, 381-391.
(250) Li, Y.-H.; Gregory, S. Geochim. Cosmochim. Acta 1974, 38, 703-714.
(251) Rivas, B. L.; Moreno-Villoslada, I. J. Appl. Polym. Sci. 1998, 70, 219-225.
(252) Buchberger, W.; Haddad, P. R.; Alexander, P. W. J. Chromatogr. 1991, 558, 181
186.
(253) McKnight, D. M.; Aiken, G. R. Ecological Studies 1998, 133, 9-39.
(254) Perminova, I. V.; Grechishcheva, N. Y.; Petrosyan, V. S. Environmental Science and
Technology 1999, 33, 3781-3787.
(255) Stevenson, F. J. Humus Chemistry: Genesis, Composition and Reactions; Wiley: New
York, 1994.
(256) MacCarthy, P. Adv. Chem. Ser. 1989, 219, xvii-xxx.
(257) Livens, F. R. Environ. Pollut. 1991, 70, 183-208.
(258) Cruz, B. H.; Diaz-Cruz, J. M.; Arino, C.; Esteban, M. Electroanalysis 2000, 12, 1130
1137.
(259) Brezonic, P. L. Chemical Kinetics and Process Dynamics in Aquatic Systems; Lewis
Publish: Boca Raton, 1994.
(260) Ochiai, M. Journal of Chromatography A 1980, 194, 224-227.
(261) Rendleman, J. A., Jr. Adv. Carbohydr. Chem. 1966, 21, 209-271.
(262) Bourne, E. J.; Nery, R.; Weigel, H. Chem. & Ind. (London) 1959, 998-999.
(263) Tajmir-Riahi, H. A. Carbohydr. Res. 1988, 183, 35-46.
219
References
(264) Briggs, J.; Finch, P.; Matulewicz, M. C.; Weigel, H. Carbohydr. Res. 1981, 97, 181
188.
(265) Turner, A. H.; Houston, J. H. Industrial Applications of Surfactants III. (The
Proceedings of a Symposium Organized by the North West Region of the Industrial
Division of the Royal Society of Chemistry, University of Salford, 16-18th
September 1991.) [In: Spec. Publ. - R. Soc. Chem., 1992; 107]; Royal Soc. Chem.:
Cambridge, UK, 1992.
(266) Crisp, P. T.; Eckert, J. M.; Gibson, N. A. J. Chem. Educ. 1983, 60, 236-238.
(267) Pettit, G.; Pettit, L. D. IUPAC Stability Constants Database; Academic Software,
1999.
(268) Relan, P. S.; Khanna, S. S.; Chand, T.; Kumari, R. J. Indian Soc. Soil Sci. 1986, 34,
250-256.
(269) Morris, D. F. C.; Short, E. L. Journal of the Chemical Society, Abstracts 1962, 2672
2675.
(270) Lazarev, A. N.; Makashev, Y. A.; Mironov, V. E.; Lobov, B. I. Zhurnal Fizicheskoi
Khimii 1975, 49, 2258-2262.
(271) Ashurst, K. G.; Hancock, R. D. Journal of the Chemical Society, Dalton Transactions:
Inorganic Chemistry (1972-1999) 1977, 1701-1707.
(272) Zelic, M.; Branica, M. Electroanalysis 1992, 4, 701-706.
(273) Fedorov, V. A.; Robov, A. M.; Plekhanov, V. P.; Kudruk, V. V.; Kuznechikhina, M.
A.; Chernikova, G. E. Zhurnal Neorganicheskoi Khimii 1974, 19, 1225-1229.
(274) Fedorov, V. A.; Chernikova, G. E.; Kuznechikhina, M. A.; Kuznetsova, T. I. Zhurnal
Neorganicheskoi Khimii 1975, 20, 2912-2915.
(275) Schleich; R., R. Measuring Copper Release from Antifouling Paints Using Diffusive
Gradients in Thin Films (DGT), Honours Thesis; Griffith University: Gold Coast,
Australia, 2001.
(276) Marty, J.; Persin, M.; Sarrazin, J. Journal of Membrane Science 2000, 167, 291-297.
(277) Aiken, G. Humic Substances in Soil, Sediment, and Water; Geochemistry, Isolation,
and Characterization; John Wiley and Sons: New York, N. Y, 1985.
(278) Ross, A. R. S.; Ikonomou, M. G.; Orians, K. J. Analytica Chimica Acta 2000, 411,
91-102.
(279) Bourne, E. J.; Searle, F.; Weigel, H. Carbohydrate Research 1971, 16, 185-187.
220
References
(280) Jordan, R. N.; Yonge, D. R.; Hathhorn, W. E. Journal of Contaminant Hydrology
1997, 29, 59-80.
(281) Hsu, J.-H.; Lo, S.-L. Journal of Environmental Quality 2000, 29, 447-453.
(282) Tusseau-Vuillemin, M.-H.; Gilbin, R.; Taillefert, M. Environmental Science and
Technology 2003, 37, 1645-1652.
(283) DeVries, C. R.; Wang, F. Environmental Science and Technology 2003, 37, 792-797.
(284) Odzak, N.; Kistler, D.; Xue, H.; Sigg, L. Aquatic Sciences 2002, 64, 292-299.
(285) Garmo, O. A.; Royset, O.; Steinnes, E.; Flaten, T. P. Analytical Chemistry, ACS
ASAP.
(286) Bitter, J. G. A. Transport Mechanisms in Membrane Separation Processes; Plenum
Press: New York, 1991.
(287) Wallace, R. A.; Gable, R. J. J. Appl. Polym. Sci. 1973, 17, 3549-3552.
221
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