Transport of Nano Sized Zero Valent Iron Colloids during

Heft 215 Cjestmir Volkert de Boer

Transport of Nano Sized Zero ValentIron Colloids during Injection into theSubsurface

Transport of Nano Sized Zero Valent Iron Colloids during Injection into the Subsurface

Von der Fakultät Bau- und Umweltingenieurwissenschaften der Universität Stuttgart zur Erlangung der Würde eines Doktor-Ingenieurs (Dr.-Ing.) genehmigte Abhandlung

Vorgelegt von Cjestmir Volkert de Boer

aus Langedijke, Königreich der Niederlande

Hauptberichter: Prof. Dr.-Ing. Rainer Helmig Mitberichter: Prof. Dr. Ruud Schotting Prof. Dr. Rajandrea Sethi Tag der mündlichen Prüfung: 19. Juli 2012

Institut für Wasser- und Umweltsystemmodellierung der Universität Stuttgart

2012

Heft 215 Transport of Nano Sized Zero Valent Iron Colloids during Injection into the Subsurface

von Dr.-Ing. Cjestmir Volkert de Boer

Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart

D93 Transport of Nano Sized Zero Valent Iron Colloids during Injection into the Subsurface

Bibliografische Information der Deutschen Nationalbibliothek Die Deutsche Nationalbibliothek verzeichnet diese Publikation in der Deutschen Nationalbibliografie; detaillierte bibliografische Daten sind im Internet über http://www.d-nb.de abrufbar

de Boer, Cjestmir Volkert: Transport of Nano Sized Zero Valent Iron Colloids during Injection into the

Subsurface von Cjestmir Volkert de Boer. Institut für Wasser- und Umweltsystemmodellierung, Universität Stuttgart. - Stuttgart: Institut für Wasser- und Umweltsystemmodellierung, 2012

(Mitteilungen Institut für Wasser- und Umweltsystemmodellierung, Universität

Stuttgart: H. 215) Zugl.: Stuttgart, Univ., Diss., 2012 ISBN 978-3-942036-19-1 NE: Institut für Wasser- und Umweltsystemmodellierung <Stuttgart>: Mitteilungen

Gegen Vervielfältigung und Übersetzung bestehen keine Einwände, es wird lediglich um Quellenangabe gebeten. Herausgegeben 2012 vom Eigenverlag des Instituts für Wasser- und Umwelt-systemmodellierung Druck: Document Center S. Kästl, Ostfildern

“Muad’Dib could indeed see the Future, but you must understand the limits

of this power. Think of sight. You have eyes, yet cannot see without light. If

you are on the floor of a valley, you cannot see beyond your valley. Just so,

Muad’Dib could not always choose to look across the mysterious terrain. He

tells us that a single obscure decision of prophecy, perhaps the choice of one

word over another, could change the entire aspect of the future. He tells us,

‘The vision of time is broad, but when you pass through it, time becomes a

narrow door.’

And always, he fought the temptation to choose a clear, safe course,

warning, ‘That path leads ever down into stagnation.’

-from ‘Arrakis Awakening’ by the Princess Irulan”

Frank Herbert - Dune - 1965

Acknowledgments

I sincerely thank professors Rainer Helmig, Ruud Schotting and Rajandrea Sethi for their

continuous support, constructive feedback and above all their patience. I enjoyed the nu-

merous discussions I had in the beginning with Ruud and Rainer about how to extract

a dissertation from the results of my work at VEGAS and later the in-detail discussions

about my work with Rajandrea. Beside that, during several visits to Utrecht there was

often time to join the great group activities and while staying in Torino Rajandrea even

introduced me to the local cuisine and wine tasting traditions. More than once I had

serious doubts about finishing this dissertation, but each time I found support and mo-

tivation from the talks I had with each one of you, which motivated me to continue and

finish this work.

I thank all the colleagues from VEGAS for these wonderful years and great working

experience. Special thanks go out to my supervisors Jurgen Braun and Norbert Klaas,

and also Oliver, Steffen, Ralf, Bojan, Hubert, Henning and Tanja for their great help in

working out experimental ideas. I learned a lot from you all and I am confident that this

knowledge will continue to help me in my future work.

During the two projects after finishing my Masters, I had the chance to supervise

several Diplom, Masters and Bachelors students, which helped to keep the fundamental

research going while I was working on the more applied side to reach the project goals.

The dynamic interaction with Stefan, Weining, Willem-Bart, Rein and Dave has helped

me keeping hold of my motivation for being a researcher at the university. It is to a large

extent due to them that I decided to choose for a career in science.

I would like to thank my parents Joke and Gerrit for their unconditional confidence in

me and their support in keeping me on the job of finishing this work. Throughout my

research and especially in the final phase of writing, I have loved the mental support from

Flora, who at the same time was writing her dissertation in Geneva. Thank you for being

such a great friend throughout all these years!

I am very grateful to Tobias for his help with the German summary and being such a

supportive and good friend.

Special picture credits go out to Andre Buchau (2.4, 2.5, 2.8), Bojan Skodic (4.6),

David Estrella (4.23), Flora Boekhout (4.1a), Hua Li (2.12-2.15, 2.19, 2.23) and Stefan

Steiert (2.24, 3.9)

The presented research was performed within three projects at the Research Facility

for Subsurface Remediation (VEGAS ), University of Stuttgart, Germany. I gratefully

I

thank Jurgen Braun for letting me work on these projects and all the effort he has put

into getting these grants. Two projects were funded by the State of Baden-Wurttemberg,

Germany, the first through BW-PLUS under the project number BWR25001, the sec-

ond under the project number 111-047588.6 / 973.049977.9, BUT 013. And one by

the European Commission through the 7th Research Framework Programme: FP7 ENV

2008.3.1.1.1., AQUAREHAB.

Finally, I know I would not have finished my dissertation without the mental support

from my friends and family, “Thank You All!”

Cjestmir de BoerOctober 2012, London (ON), Canada

II

Contents

Acknowledgments I

List of Figures VI

List of Tables IX

Notation IX

Abstract XVI

Kurzfassung XVII

1 Introduction 11.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.2 Remediation Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2.1 Ex-Situ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2.2 In-Situ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.2.3 Nanotechnology for Groundwater Remediation . . . . . . . . . . . . 3

1.2.4 Chemical Reactions and the Chemical Composition of nZVI . . . . 6

1.2.5 Field Application of nZVI . . . . . . . . . . . . . . . . . . . . . . . 8

1.2.6 Detection and Concentration Measurement of nZVI in the Subsurface 10

1.3 Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

1.4 Structure of the Dissertation . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2 Detection and Concentration Measurement of nZVI in the Subsurface 132.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.2 Susceptibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.3 Measurement of nZVI Concentration Profiles in a Column . . . . . . . . . 15

2.3.1 Experimental Set Up . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.3.2 Concentration Profiles and Calibration . . . . . . . . . . . . . . . . 16

2.3.3 About the Metal Detector . . . . . . . . . . . . . . . . . . . . . . . 19

2.4 Measuring Iron Break Through Curves in the Container Experiment . . . . 20

2.4.1 Data Analysis and Post Processing Algorithms . . . . . . . . . . . . 22

2.4.2 Sensor Design and Data Acquisition . . . . . . . . . . . . . . . . . . 24

III

2.4.3 Experimental Verification . . . . . . . . . . . . . . . . . . . . . . . 28

2.5 Measuring Iron Break Through Curves in the Field . . . . . . . . . . . . . 30

2.5.1 Sensor Design and Data Acquisition . . . . . . . . . . . . . . . . . . 31

2.5.2 Measuring Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

2.5.3 Post-Processing Algorithms . . . . . . . . . . . . . . . . . . . . . . 35

2.5.4 Sensor Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

2.5.5 Sensor Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

2.6 Chemical Measurement of nZVI in Soil & Suspension . . . . . . . . . . . . 43

2.6.1 Materials & Methods . . . . . . . . . . . . . . . . . . . . . . . . . . 44

3 Fundamentals of Transport of Nano Sized Zero Valent Iron Colloids 473.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

3.2 Colloid Transport & Filtration in Porous Media . . . . . . . . . . . . . . . 47

3.2.1 Colloid Filtration Theory . . . . . . . . . . . . . . . . . . . . . . . . 48

3.2.2 Attachment Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . 49

3.2.3 Sensitivity of Colloid Filtration Theory Parameters . . . . . . . . . 50

3.3 Characteristics of the nZVI Suspension . . . . . . . . . . . . . . . . . . . . 54

3.3.1 nZVI Suspension . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

3.3.2 Aging of nZVI During Storage . . . . . . . . . . . . . . . . . . . . . 55

3.3.3 Aging of nZVI after Dilution . . . . . . . . . . . . . . . . . . . . . . 57

3.3.4 Size of nZVI in Suspension using Stokes’ Law . . . . . . . . . . . . 57

3.3.5 Size of nZVI in Suspension using a Laser Detector . . . . . . . . . . 60

3.4 Conceptual Model for Transport of nZVI . . . . . . . . . . . . . . . . . . . 61

3.5 Mathematical Model for Transport of nZVI . . . . . . . . . . . . . . . . . . 64

3.5.1 Groundwater Flow and Transport . . . . . . . . . . . . . . . . . . . 64

3.5.2 Transport and Kinetic Removal . . . . . . . . . . . . . . . . . . . . 65

3.5.3 nZVI Removal in Porous Media . . . . . . . . . . . . . . . . . . . . 65

3.6 Transport Experiments (1D) . . . . . . . . . . . . . . . . . . . . . . . . . . 67

3.6.1 Materials and Methods . . . . . . . . . . . . . . . . . . . . . . . . . 68

3.6.2 Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

3.6.3 Results & Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 73

3.7 Numerical Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

3.7.1 Numerical Simulation with Fitting on Transient Column Data . . . 80

3.8 Summarizing the Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

4 Colloid Transport in a Radial Flow Field 854.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

4.2 Flow and Transport in Radial Systems . . . . . . . . . . . . . . . . . . . . 86

4.2.1 Concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

4.2.2 Mathematical Description . . . . . . . . . . . . . . . . . . . . . . . 86

IV

4.3 Container Experiments with a Radial Flow Field . . . . . . . . . . . . . . . 88

4.3.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

4.3.2 Material & Methods . . . . . . . . . . . . . . . . . . . . . . . . . . 89

4.3.3 Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

4.3.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . 97

4.4 Discretized Radial Flow Field Reproduced with Columns . . . . . . . . . . 106

4.4.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

4.4.2 Concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

4.4.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

4.4.4 Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

4.4.5 Results & Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 115

4.5 Numerical Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119

4.5.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119

4.5.2 Solver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120

4.5.3 FEniCS vs. Matlab . . . . . . . . . . . . . . . . . . . . . . . . . . . 124

4.5.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

4.5.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130

4.6 Comparison of Radial Flow Simulations Methods . . . . . . . . . . . . . . 131

5 Feasibility of Injecting nZVI into the Subsurface 1335.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133

5.2 Prerequisites for Success . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133

5.3 Determination of Necessary Amount of nZVI . . . . . . . . . . . . . . . . . 137

5.4 Application of Feasibility Test Methods . . . . . . . . . . . . . . . . . . . . 138

5.5 Application of Methods in the Field . . . . . . . . . . . . . . . . . . . . . . 141

Conclusion 143

Outlook 145

Bibliography 147

V

List of Figures

1.1 NAPL Distributions in the Subsurface . . . . . . . . . . . . . . . . . . . . 2

1.2 From Meter to Nanometer . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.3 Conceptual Injection Field . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

1.4 Dissertation Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

2.1 Photo of the Metal Detector used for Column Experiments . . . . . . . . . 18

2.2 Calibration Set Up and Data from the Metal Detector . . . . . . . . . . . . 19

2.3 Calibration Curve of the Metal Detector . . . . . . . . . . . . . . . . . . . 20

2.4 Magnetic Field Strength of a Cylindrical Coil . . . . . . . . . . . . . . . . 21

2.5 Equivalent Network of the Container Sensor . . . . . . . . . . . . . . . . . 23

2.6 Coil winding machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

2.7 Container Sensor Development . . . . . . . . . . . . . . . . . . . . . . . . . 26

2.8 Iso Surface of the Magnetic Field Strength of the Primary Coil . . . . . . . 27

2.9 Container nZVI Detection Electronics . . . . . . . . . . . . . . . . . . . . . 28

2.10 Influence of Fluid Chemistry on Dual Coil Sensor . . . . . . . . . . . . . . 29

2.11 Schematic Overview of an In-Situ Application of nZVI . . . . . . . . . . . 30

2.12 nZVI Field Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

2.13 Equivalent Network of the Field Sensor . . . . . . . . . . . . . . . . . . . . 32

2.14 Cross Section of the Field Sensor . . . . . . . . . . . . . . . . . . . . . . . 33

2.15 Response of the Field Sensor on nZVI at Increasing Distance . . . . . . . . 33

2.16 Field Sensor Development . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

2.17 Field nZVI Measurement System Overview . . . . . . . . . . . . . . . . . . 36

2.18 Calibration Set Up for the Field Sensor . . . . . . . . . . . . . . . . . . . . 40

2.19 Susceptibility of nZVI at Different Concentrations . . . . . . . . . . . . . . 40

2.20 Field Sensor Test Set Up . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

2.21 Field Measuring Electronics . . . . . . . . . . . . . . . . . . . . . . . . . . 42

2.22 Propagation of nZVI Inside a Small Container . . . . . . . . . . . . . . . . 42

2.23 Concentration and Temperature During the Injection . . . . . . . . . . . . 43

2.24 Measuring Set Up for Analytical ZVI Measurement . . . . . . . . . . . . . 45

3.1 Transport Mechanisms of Particle Filtration . . . . . . . . . . . . . . . . . 48

3.2 Contact Efficiencies as a Function of Different Parameters . . . . . . . . . 52

3.3 Fe0 Reduction of Stored nZVI . . . . . . . . . . . . . . . . . . . . . . . . . 56

VI

3.4 Oxidation of nZVI Suspensions after Dilution . . . . . . . . . . . . . . . . 57

3.5 Sedimentation Curves of nZVI Suspensions . . . . . . . . . . . . . . . . . . 59

3.6 Size of Nano-Fraction of nZVI in Suspension . . . . . . . . . . . . . . . . . 61

3.7 Conceptual Model for nZVI Transport . . . . . . . . . . . . . . . . . . . . 63

3.8 Set Up of the Column Experiment . . . . . . . . . . . . . . . . . . . . . . . 67

3.9 Column Tracer Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . 70

3.10 Mixer and Disperser . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

3.11 Schematic Overview of the 1-D Experiments . . . . . . . . . . . . . . . . . 72

3.12 Photos of the Propagation of nZVI in a Column Experiment . . . . . . . . 74

3.13 Transient Concentration Profiles of Column Experiments . . . . . . . . . . 75

3.14 Pressure Gradient Development . . . . . . . . . . . . . . . . . . . . . . . . 76

3.15 Water Flushing After Injection . . . . . . . . . . . . . . . . . . . . . . . . 77

3.16 nZVI Breakthrough at 50 cm from Column Inlet . . . . . . . . . . . . . . . 78

3.17 Normalized Transport Distance . . . . . . . . . . . . . . . . . . . . . . . . 79

3.18 Numerically Fitted Model on Column Data . . . . . . . . . . . . . . . . . . 81

3.19 Fitting Parameter S0max in Relation to C0 . . . . . . . . . . . . . . . . . . . 83

4.1 Hyperbolically Decreasing Seepage Velocity Around a Well . . . . . . . . . 86

4.2 Photo of the Container Experiment . . . . . . . . . . . . . . . . . . . . . . 89

4.3 Schematic Overview of the Container Experiment Set Up . . . . . . . . . . 90

4.4 Filter Screens of the Container Experiment . . . . . . . . . . . . . . . . . . 91

4.5 Two Different Types of Pumps Used . . . . . . . . . . . . . . . . . . . . . 92

4.6 3-D Graphical Overview of the Container Experiment . . . . . . . . . . . . 93

4.7 View into the Container During Filling . . . . . . . . . . . . . . . . . . . . 94

4.8 Samples Taken for Chemical Analysis . . . . . . . . . . . . . . . . . . . . . 95

4.9 Reynolds Number in the Container Experiments . . . . . . . . . . . . . . . 98

4.10 nZVI Propagation in the Container . . . . . . . . . . . . . . . . . . . . . . 99

4.11 Magnetic Susceptibility Measured During Container Exp. 1 . . . . . . . . . 100

4.12 Photos of Container Experiment Results at 1000 l/h . . . . . . . . . . . . 102

4.13 Chemically Analyzed nZVI from Container Exp. 1 & 4 . . . . . . . . . . . 102

4.14 Photos of Container Experiment Results at 500 & 1000 l/h . . . . . . . . . 104


4.16 Photos of Container Experiment Results with Different Pumps . . . . . . . 105


4.18 Graphical Overview of all Notation for Radial Flow Discretization . . . . . 108

4.19 Discretization of a Radial Flow Field into Three Sections . . . . . . . . . . 112

4.20 Results of Column Set 1 for Container Exp. 1 . . . . . . . . . . . . . . . . 116

4.21 Results of Column Set 3 for Container Exp. 3 . . . . . . . . . . . . . . . . 116

4.22 Manual Correction of Recorded Data . . . . . . . . . . . . . . . . . . . . . 119

4.23 Example Mesh for Radial Flow Simulation . . . . . . . . . . . . . . . . . . 123

VII

4.24 Comparison of the Matlab and FEniCS models . . . . . . . . . . . . . . . 124

4.25 Hydraulic Head Distribution for Container Exp. 1 & 4 Simulation . . . . . 125

4.26 nZVI Distribution from Simulation of Container Exp. 1 . . . . . . . . . . . 126

4.27 Simulation and Container Exp. 1 Data . . . . . . . . . . . . . . . . . . . . 126

4.28 Hydraulic Head Distribution for Container Exp. 3 Simulation . . . . . . . 127





5.1 Injection Wells and Sensor Locations . . . . . . . . . . . . . . . . . . . . . 136

5.2 Differently Possible Distributions of nZVI . . . . . . . . . . . . . . . . . . . 138

5.3 Decision Chart for Using nZVI . . . . . . . . . . . . . . . . . . . . . . . . . 140

5.4 Drawing of Funnel Shaped nZVI Reservoir . . . . . . . . . . . . . . . . . . 141

VIII

List of Tables

1.1 Pollutants that can be Remediated by nZVI . . . . . . . . . . . . . . . . . 6

2.1 Susceptibilities Measured and Calculated . . . . . . . . . . . . . . . . . . . 39

3.1 Filtration Sensitivity Analysis Constants . . . . . . . . . . . . . . . . . . . 50

3.2 Filtration Sensitivity Analysis Variables . . . . . . . . . . . . . . . . . . . . 51

3.3 nZVI Aging of Different Lots . . . . . . . . . . . . . . . . . . . . . . . . . . 55

3.4 Conditions Used for the Column Experiments . . . . . . . . . . . . . . . . 72

3.5 Normalized Transport Distances of the Column Experiments . . . . . . . . 79

3.6 Parameters of the Column Experiment Simulations . . . . . . . . . . . . . 82

4.1 Conditions of the Container Experiments . . . . . . . . . . . . . . . . . . . 92

4.2 Parameters of the Container Experiments . . . . . . . . . . . . . . . . . . . 96

4.3 Parameters for Column Set 1 . . . . . . . . . . . . . . . . . . . . . . . . . 114

4.4 Parameters for Column Set 3 . . . . . . . . . . . . . . . . . . . . . . . . . 114

4.5 Measured Input and Effluent Concentrations . . . . . . . . . . . . . . . . . 115

4.6 Mass Balance Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . 118

4.7 Parameters Used for Model Comparison . . . . . . . . . . . . . . . . . . . 124

IX

Notation

Abbreviation Definition

1-D one dimensional

2-D two dimensional

3-D three dimensional

A/D analog digital

AC alternating current

ADC analog to digital converter

CHC chlorinated hydrocarbons

DNAPL dense non aqueous phase liquid

GSM global system for mobile communications

ID inner diameter

L, W, H length, width, height

L, T , M dimensions: Length, Time, Mass

LNAPL light non aqueous phase liquid

MTBE Methyl-tert-butyl-ether

PCE Tetrachloroethylene

PDE differential equation

Pe Peclet number

PEN project on emerging nanotechnologies

PP Polypropylene

PRB permeable reactive barrier

PTFE Polytetrafluoroethylene (Teflon)

PV pore volume

Re Reynolds number

RMS root mean square

RMSE root mean square error

RNIP reactive nano iron particle

TCE Trichloroethylene

TTL transistor-transistor logic

UV ultra violet

X

Abbreviation Definition

ZVI zero valent iron

modem modulator-demodulator

nZVI nano sized zero valent iron

µZVI micro sized zero valent iron

nr. number

Symbol Definition Dimensionor SI Unit

α empirical attachment efficiency [−]

αagg empirical attachment efficiency of aggregates [−]

αk fitting coefficient for the geometry factor [−]

αl dispersion length [L]

χD average susceptibility measured [−]

χ observed susceptibility [−]

χm susceptibility in accessible domain [−]

χnZV I susceptibility of nZVI [−]

η effective single-collector contact efficiency [−]

ηD single-collector contact efficiency for Brown-

ian diffusion

[−]

ηD single-collector contact efficiency for gravita-

tional effects

[−]

ηI single-collector contact efficiency for inter-

ception

[−]

ηagg0 summed single-collector contact efficiency of

aggregates

[−]

η0 summed single-collector contact efficiency of

colloids

[−]

µ absolute fluid viscosity [ML−1T−1]

µ0 permeability of vacuum [−] (TmA−1)

Ω domain [−]

Φ magnetic flux [−] (Tm2)

ρsand sand density [ML−3]

ρbulk = ρb sand bulk density (porosity included) [ML−3]

XI


ρf fluid density [ML−3]

θ cylindrical coordinate (angle) [−] (Rad)

εr electromotive force [−] (V Volt)

ξ velocity ratio between two discretization sec-

tions

[−]

A Hamaker constant [−] (J = kg·m2·s−2)

Acolumn cross-sectional area of the column [L2]

Ai cross-sectional area of the boundary at ri in

a cylinder

[L2]

AM sum of the measured data points [−]

B magnetic flux density [−] (T Tesla)

b base height of confined aquifer or container [−]

bcolumn number of data points [−]

C generic constant [−]

C concentration [ML−3]

Cmax maximum concentration [ML−3]

CnZV I concentration of nZVI [ML−3]

Ct concentration of nZVI in suspension at time

step t

[−]

Ceffluent output (effluent) concentration [ML−3]

CFe0 weight percentage of zero-valent iron in total

iron

[w%]

Cinput = C0 input concentration [ML−3]

C(in,out)i input, effluent concentration of the boundary

at radial distance ri

[ML−3]

C1 capacitance of the primary coil [−] (F Farad)

C11 capacitance of the primary reference coil [−] (F Farad)

C21 capacitance of the primary detection coil [−] (F Farad)

Ck capacitance of a cable [−] (F Farad)

cM constant [−]

c1,2,3,4 integration constants [−]

D hydrodynamic dispersion (tensor) [L2T−1]

Dl longitudinal hydrodynamic dispersion [L2T−1]

Dinf diffusion in an infinite medium [−]

XII


dp particle (colloid) diameter [L]

daggp aggregate of colloids diameter [L]

dc collector (sand grain) diameter [L]

d10 grain size that exceeds the size (diameter) of

10 % of the material by weight

[L]

d50 grain size that exceeds the size (diameter) of

50 % of the material by weight

[L]

Fetotal total iron (summed Fe0, Fe2+ & Fe3+) [M ]

F mass fraction [−]

fn flux for the Neumann boundary condition [L2T−1]

f frequency [−] (Hz)

f (′) frequency at χ = 0 [−] (Hz)

f ′a,b frequency at two calibration measurements a

& b at χ = 0

[−] (Hz)

g gravitational acceleration [LT−2]

H magnetic field strength [−] (Am−1 Ampere-

turn per meter)

h piezometric head [L]

IC1 current through the primary (generating)

reference coil

[−] (A Ampere)

IC2 current through the primary (generating) de-

tection coil

[−] (A Ampere)

I1 electric current towards the primary (gener-

ating) coil

[−] (A Ampere)

J(i) mass flux density (at boundary ri) [MT−1L−2]

k Boltzmann constant [−] (J · K−1 = kg ·m2 · s−2 ·K−1)

K hydraulic conductivity [LT−1]

K average hydraulic conductivity [LT−1]

kaging nZVI aging coefficient [−]

kcolatt attachment coefficient of colloids [−]

kaggatt attachment coefficient of aggregates [−]

kd detachment coefficient [−]

kexp experimental geometry factor [−]

XIII


kFe conversion ratio from measured data point

into concentration of nZVI

[−]

ksim simulation geometry factor [−]

L characteristic filtration length [−]

L1,2 inductance of coil 1,2 [−] (H Henry)

MFe total injected nZVI [M ]

MFe molecular mass of iron [M ]

Mmi1,2 mutual inductance of the dual (primary and

secondary) coil system, 1 for reference and 2

for detection

[−] (H Henry)

Mt value of measured data point [−]

M0 value of measured background data point [−]

M(i) mass flux of injected nZVI (in section i) [MT−1]

∆M total injected nZVI in time ∆t [M ]

msand total mass of sand [M ]

mtracer mass of tracer [M ]

N number of discretization sections [−]

nH2 amount of H2 molecules [−]

n porosity [−]

P pressure [ML−1T−2]

Q discharge, flow rate or injection rate [L3T−1]

q Darcy velocity (vector) [LT−1]

q Darcy velocity [LT−1]

qi Darcy velocity at the radial distance ri [LT−1]

qi average Darcy velocity over section i [LT−1]

R1 resistance [−] (Ω Ohm)

r cylindrical coordinate (radial distance from

injection well)

[L]

ri radial distance of the boundary of section i [L]

Smax maximum mass of nZVI per unit mass of dry

soil

[MM−1]

S0max maximum mass of colloids per unit mass of

dry soil

[MM−1]

Sr mass of aggregates per unit mass of dry soil [MM−1]

Sc mass of colloids per unit mass of dry soil [MM−1]

XIV


Sb surface [−]

Stotal = S mass of attached and suspended nZVI per

mass of dry soil

[MM−1]

Stotal|wet mass of nZVI per mass of wet soil [MM−1]

T temperature [−] (K Kelvin)

t time [T ]

∆t period of time or time step [T ]

U(′)1 electric voltage over the resistor R1 at the

primary coil, (′) for voltage at χ = 0

[−] (V Volt)

U(′)2 induced voltage at the secondary coil, (′) for

voltage at χ = 0

[−] (V Volt)

U ′1,2|a,b voltages at two calibration measurements a

& b at χ = 0

[−] (V Volt)

U(′)12 induced voltage at the secondary reference

coil, (′) for voltage at χ = 0

[−] (V Volt)

U(′)22 induced voltage at the secondary detection

coil, (′) for voltage at χ = 0

[−] (V Volt)

U(′)3 induced voltage at the secondary coil (com-

bined), (′) for voltage at χ = 0

[−] (V Volt)

V volume [L3]

VnZV I volume occupied by nZVI [L3]

vp particle settling velocity [LT−1]

v seepage velocity [LT−1]

Vi volume flux in section i [L3T−1]

w number of windings on a coil [−]

ω test function [−]

XF normalized travel distance of mass fraction

F

[−]

xF travel distance of a mass fraction F [L]

∆x element size [L]

ZC1 impedance of a coil [−] (V A−1

Volt Ampere−1)

XV

Abstract

One of the recent In-Situ groundwater remediation techniques under development uses

reactive zero valent iron (ZVI) to turn highly toxic chlorinated hydrocarbons (CHCs) into

harmless compounds. CHCs are non miscible and characterized by a low solubility which

determines their slow dissolution (over decades or centuries) into groundwater, forming

plumes that can target drinking water wells, rivers and lakes. Injection of nano sized zero

valent iron (nZVI) suspension into the subsurface could target the contaminants directly

in the source zone. The high reactivity of nZVI together with the injection into the source

fastens the depletion of the contaminant and interrupts the plume generation.

The presented work focused on the transport of nZVI during the injection. To make

quantitative descriptions of transport possible, an effective detection technique was de-

veloped. Exact concentrations of nZVI inside the porous medium was measured through

changes in susceptibility detected with electromagnetic induction sensors. Mobility tests

with different suspension concentrations were performed in a 1-D horizontally orientated

two meter long column. Continuous concentration measurements were performed over

the whole length of the column. In a near field scale container experiment a confined

aquifer with a radial flow field over a radius of almost two meters was simulated. Differ-

ent injection rates and pumping techniques were tested inside this experimental set up.

A discretization method to represent all effects of a radial flow field using sets of columns

was developed. The method could be verified successfully by comparing the concentration

profiles to the results obtained from the container experiments. A mathematical model,

developed by starting from the classic colloid filtration theory and by considering the

transport of primary colloids and aggregates separately, was able to be fitted on the 1-D

results. After implementation in a numerical solver, the model was furthermore capa-

ble of providing a very good fit on the results of the radial geometry tests while using

exclusively the fitted parameters obtained from the 1-D tests.

Throughout the work a better understanding of the transport of nZVI during the in-

jection was developed. It was demonstrated that transport of nZVI without modification

was possible over a distance of two meters in both 1-D and radial geometry flow fields.

An extrapolation of the work for field application was furthermore described. By ap-

plying the methods developed in this work the necessary suspension concentration, the

volume of suspension and the injection rate could be determined in advance. The pre-

sented work showed promising results and could be a sound scientific basis for further

investigations and case studies on nZVI based remediation.

XVI

Kurzfassung

Einleitung

Hintergrund

Die Wahrnahme der Gefahren, die von verunreinigten Standorten ausgehen, hat in den

letzten paar Jahrzehnten stark zugenommen. Viele dieser Standorte wurden kontaminiert

mit chlorierten Kohlenwasserstoffen (CKW’s), welche bereits in niedrigsten Konzentratio-

nen außerst toxisch und umweltschadlich sind und von denen einige sogar krebserregend

fur den Menschen sind. Flussige CKW’s haben eine hohere Dichte als Wasser, wodurch

Sie bis auf große Tiefen im Untergrund versickern konnen. Ihre Loslichkeit im vorbeistro-

menden Grundwasser ist sehr gering, weshalb die CKW’s den Aquifer im unterstromigen

Bereich fur mehrere Jahrhunderte verunreinigen konnen.

In den letzten Jahrzehnten wurden die unterschiedlichsten Methoden entwickelt, um

diese Verunreinigungen zu beseitigen. Eine von den neuesten und vielversprechendsten

Methoden ist die Sanierung mittels nullwertigem Eisen in nanoskaliger, kolloidaler Form.

Diese sogenannten Nano-Eisen-Kolloide haben durch ihre geringe Große eine sehr große

Oberflache und damit eine sehr hohe Reaktivitat. Neben CKW’s kann ein ganzes Spek-

trum von Schadstoffen mit ihrer Hilfe abgebaut und somit unschadlich gemacht werden.

Bis vor Kurzem wurde hauptsachlich die Reaktivitat von Nano-Eisen erforscht. Durch

die geringe Partikelgroße wurde angenommen, dass sich die Kolloide einwandfrei in den

Untergrund einbringen ließen. Leider musste jedoch bei mehreren Pilotanwendungen

[Muller et al., 2006a,b] und Vorversuchen im Labor [de Boer, 2007; Koch, 2007] festgestellt

werden, dass sich die Kolloide deutlich schlechter im Untergrund verteilen als erwartet.

Forschungsfragen

Um ein besseres Verstandnis vom Transport nanoskaliger Eisenkolloide im Untergrund

zu bekommen und deren Anwendbarkeit fur die Sanierung von Schadensfallen besser

abschatzen zu konnen, wurden im Rahmen dieser Arbeit die folgenden Forschungsfragen

aufgestellt.

(a) Ist es moglich, Nano-Eisen direkt im Untergrund zu messen?

(b) Welche Faktoren bedingen die niedrige Transportfahigkeit im porosen Medium und

wie kann der Transport optimiert werden?

XVII

(c) Welche Reichweite kann in einem radialen Stromungsfeld erreicht werden?

(d) Wie lasst sich die Machbarkeit der Injektion an einem Standort feststellen?

Detektion von Nano-Eisen und Konzentrationsmessung

im Untergrund

Die Messung von Nano-Eisen im Untergrund ist mit den gangigen Messtechniken nicht

ohne weiteres moglich, weshalb im Rahmen dieser Arbeit ein neues Messverfahren speziell

fur die Messung von Nano-Eisen entwickelt wurde. Das Messverfahren wurde sukzessive

fur drei verschiedene Skalen angepasst. Zunachst wurde die Messung von Konzentra-

tionsprofilen entlang einer Saule realisiert. Danach folgte die Aufnahme von Durchbruch-

skurven in einem großskaligen Containerversuch mittels stationarer, durchstromter Son-

den. Schlussendlich wurde die Technik dann bis zur Feldtauglichkeit weiterentwickelt.

Messprinzip

Das neue Messverfahren basiert auf den ferromagnetischen Eigenschaften von nullwer-

tigem Eisen. Durch den Ferromagnetismus haben die Kolloide eine messbare Suszeptibil-

itat. Die Suszeptibilitat ist das Verhaltnis aus der Magnetisierung in einer Substanz und

der daraus resultierenden magnetischen Kraft. Die Auswahl eines Messverfahrens, das

die Anderung der magnetischen Suszeptibilitat im Boden erfassen kann, liegt also nahe.

Die Anderung der Suszeptibilitat im Boden ist direkt proportional zur Suszeptibilitat

von Nano-Eisen und damit dessen Konzentration am Ort der Messung.

Messtechnik fur Saulenversuchen

Zur Bestimmung der Transporteigenschaften von Nano-Eisen wurde ein Saulenversuchs-

stand aufgebaut. Um Konzentrationsprofile entlang der Saule messen zu konnen, wurde

zunachst eine modifizierte Version eines kommerzielles verfugbaren Minensuchdetek-

tor (FX2FD, Minex, Reutlingen) genutzt. Der Detektor wurde an einen Rechner

angeschlossen, sodass die Rohdaten ausgelesen werden konnten. Zur Aufnahme von

Konzentrationsprofilen wurde das Minensuchgerat auf einem fahrbaren Wagen montiert,

der mittels eines Schrittmotors entlang der Saule verfahren werden konnte.

Vor der Injektion wurde eine Hintergrundmessung durchgefuhrt. Dann wurde wahrend

der Injektion alle zehn Minuten ein Profil gemessen und die Hintergrunddaten abgezogen.

Um die Rohdaten in reale Konzentrationen umzusetzen, wurde die Gesammtmasse an in-

jiziertem Nano-Eisen zum Zeitpunkt der Messung bestimmt und mit der Integralsumme

der gemessenen Masse uber alle Messpunkte gleichgesetzt. Somit wurde ein Faktor fur

XVIII

jeden Messpunkt ermittelt , der zur Umrechung aller Rohdaten eines Versuchs in Konzen-

trationsprofile herangezogen wurde.

Messtechnik fur die großskaligen Containerversuche

Das bei den Saulenversuchen verwendete Messgerat war nicht fur den Einsatz im großskali-

gen Containerversuch geeignet. Die Messtechnik musste direkt im Boden eingegraben

werden. Die dafur notigen Messsensoren sowie die dazu gehorige Messelektronik wurden

eigens entwickelt.

Es wurde eine lange, zylinderformige Spule gewickelt, um ein elektromagnetisches Feld

aufzubauen (Erregerspule). Um diese Spule wurde eine kurze Spule gewickelt, in der

durch Induktion eine Spannung erzeugt wurde (Messspule). Die Messsensoren wurde

wahrend des Einbaus in den Container mit Bodenmaterial gefullt und so angeordnet,

dass die Grundwasser-Stromungslinien genau mittig durch die Spule verliefen. Wenn nun

die Nano-Eisen Suspension durch die Spulen stromt, andert sich die Suszeptibilitat im

Inneren der Spule, die Spannung der Messspule steigt in der Folge an und der Strom in

der Erregerspule sinkt ab.

Die Anderung der induzierten Spannung und der durch die Erregerspule fließende Strom

wurden mittels einer elektronischen Schaltung erfasst und die Daten auf einem Rechner

gespeichert.

Zur Umrechnung der Daten in reale Konzentrationen, wurden nach Ablauf des Ver-

suches Bodenproben aus den Spulen entnommen und mittels chemischer Analyse die

Konzentration an Nano-Eisen bestimmt. Diese Konzentration wurde dann mit dem let-

zten gemessenen Wert des Sensors gleichgesetzt und die wahrend der gesamten Injek-

tionsdauer gemessenen Konzentrationen entsprechend korrigiert.

Messtechnik furs Feld

Im nachsten Schritt wurde die Messtechnik fur den Feldeinsatz angepasst. Im Feld sollen

die Sensoren in einen Brunnen oder mittels anderer Sondierungsverfahren in der Tiefe

angebracht werden. Dabei ist die parallele Ausrichtung der Sensoren zu den Stromungslin-

ien nicht immer gewahrleistet und die Spulen werden unter Umstanden nicht immer gleich

durchstromt.

Aus diesem Grund wurde ein Spulenpaar entwickelt, bei dem das elektromagnetische

Feld nach außen gerichtet ist. Die Sensitivitat der Messung wurde aber hierdurch deutlich

reduziert, was eine Neuentwicklung der Elektronik erforderlich machte. Die Elektronik

wurde außerdem um die Moglichkeit erweitert, die Daten direkt im Messgerat zu speichern

und uber ein Master-Slave-Verfahren abzurufen. Fur jede Messlanze mit mehreren uber

die Tiefe verteilten Sensoren wurde ein Slave eingesetzt und zentral uber einen Master

abgerufen.

XIX

Da uber chemische Verfahren keine genaue Konzentration im Untergrund zu bestim-

men ist, wurde außerdem eine Methode entwickelt, die Sensoren bereits im Vorfeld zu

kalibrieren.

Diese Methode wurde vor dem Einsatz im Feld mittels eines kleinen Containerversuchs

uberpruft.

Messung von nullwertigem Eisen in Boden- und Flussigproben

Um die Bodenproben vom großskaligen Containerversuch aber auch den Anteil an nullw-

ertigem Eisen in den Nano-Eisen-Partikeln bestimmen zu konnen, wurde ein Messstand

aufgebaut wie z.B. in Elion and Elion [1933] beschrieben. Die Messung beruht darauf,

dass bei einer Reaktion von nullwertigem Eisen mit Salzsaure ein genau definiertes Volu-

men an Wasserstoff freigesetzt wird. Der gebildete Wasserstoff kann somit sehr genau in

die Masse an nullwertigem Eisen umgerechnet werden, die zum Zeitpunkt der Messung

in der Probe enthalten war.

Grundlagen zum Transport von Nano-Eisen-Kolloiden

Hintergrund

Das Hauptziel der Arbeit ist ein besseres Verstandis des Transports kolloidaler Nano-

Eisen-Partikel wahrend der Injektion in den Untergrund. Hierzu wurden zuerst beste-

hende Theorien zur Filtration von Kolloiden im Detail betrachtet. Anschließend wurde

die zu verwendende Nano-Eisen Suspension charakteriziert und ein konzeptionelles Modell

entwickelt. Auf Basis dieses Modells konnte dann ein mathematisches Modell hergeleitet

werden welche dann mittels eines numerischen Modells und eindimensionaler Saulenver-

suche uberpruft wurde.

Kolloidfiltrationstheorie

In porosen Medien wird der Transport von Kolloiden gehemmt durch Filtrationseffekte.

Die Filtration fuhrt dazu, dass die Kolloide aus der Suspension entfernt werden. Die am

haufigste eingesetzte Filtrationstheorie ist die Theorie von Tufenkji and Elimelech [2004].

Der Theorie beschreibt die Filtration auf Basis von drei verschiedenen Filtrationsmech-

anismen: Festsetzung am porosen Medium durch Interzeption, Gravitationseffekte und

Brownsche Diffusion. Das Zusammenspiel der drei Mechanismen ergibt die Kontaktef-

fizienz.

Da mit der Theorie nicht alle Effekte vollstandig beschrieben werden konnen, wird ein

Kontaktseffizienz Koeffizient eingesetzt, welche experimentell zu bestimmen ist. Uber

XX

eine Sensitivitatsanalyse wurde festgestellt, dass die Kolloidgroße den großten Einfluss

auf die Kontakteffizienz hat.

Charakterisierung der Nano-Eisen Suspension

Die ausgewahlte Suspension war RNIP 10-E von Toda Kogyo, Japan. Die Suspension

wird vom Hersteller als sehr hoch konzentrierter Schlamm geliefert, der vor der Verwen-

dung verdunnt werden muss. Uber Vorversuche [de Boer, 2007] wurde festgestellt, dass

die Kolloide im Schlamm stark aggregiert sind, jedoch mittels hoher Scherkrafte von einen

Dispergiergerat wieder aufgebrochen werden konnen. Ein weiteres Ergebnis der Vorun-

tersuchungen war, dass sich eine Suspensionskonzentration von etwa 10 g/l am besten im

porosen Medium transportieren lasst.

Es stellte sich heraus, dass der Schlamm wahrend der Lagerung altert und der Anteil an

nullwertigem Eisen mit der Zeit abnimmt. Hierzu wurden Langzeitmessungen uber mehr

als funf Jahre durchgefuhrt, woraus Alterungsgleichungen hergeleitet werden konnten.

Aus der in Sedimentationsversuchen bestimmten Absatzkurve konnte festgestellt wer-

den, dass auch nach der Dispergierung noch Aggregate mit einem mittleren Durchmesser

von 4, 4 µm vorlagen. Mit Hilfe von Messungen mit einem Partikelgroßenmessgerat, das

auf der Streuung von einem Helium-Laser basiert, konnten jedoch auch die primaren

Nano-Eisen-Kolloide mit einer Große zwischen 60nm und 120nm nachgewiesen werden.

Konzeptionelles Transportmodell

Auf Basis der Charakterisierung und der Filtrationstheorie konnte ein konzeptionelles

Modell aufgesetzt werden. Das Modell lasst sich zusammenfassen in vier Punkte:

Die Suspension besteht aus nanoskaligen Kolloiden und mikroskaligen, kolloidalen Ag-

gregaten.

Die Kolloide binding an der Kornoberflache, wobei die verfugbaren Bindungsplatze

begrenzt sind.

Aggregate werden durch Gravitationseffekte und auf Basis ihrer Große aus der Suspen-

sion entfernt. Hierzu gibt es kein Maximum außer dem verfugbaren Porenvolumen, was

aber hier vernachlassigt wird.

Die Filtrationstheorie von Tufenkji and Elimelech [2004] kann sowohl die Entfernung

der Kolloide als Aggregate beschreiben, gegeben Sie werden getrennt betrachtet.

1-D Transport Modell

Fur das konzeptionelle Modell wurde eine mathematische Beziehung hergeleitet. Diese

Transportgleichung wurde dann in ein numerisches Modell (in Matlab) integriert, mit

Hilfe dessen der Transport berechnet werden konnte. Anschließend wurden Saulenver-

suche durchgefuhrt. Da in der Filtrationstheorie die Suspensionskonzentration nicht

XXI

berucksichtigt wird, musste zunachst festgestellt werden, ob die Transportgleichung fur

unterschiedliche Eingangskonzentrationen gleichermaßen gilt oder ob dazu zusatzliche

Konstitutivbeziehungen notig sind.

Die Saulenversuche wurden sodann mit verschiedenen Eingangskonzentrationen

durchgefuhrt und dabei jeweils Konzentrationsprofile zu verschiedenen Zeitpunkten

aufgezeichnet.

Das numerische Modell wurde dann mit drei Parametern iterativ an die Daten

angepasst. Die Parameter waren die Kontaktseffizienz Koeffizient fur die Kolloide und

die Aggregate, und die Maximalkonzentration der gebundene Kolloide. Mit Hilfe der

Experimente konnte festgestellt werden, dass die Filtrationstheorie fur die Kolloide eine

sehr gute Vorhersage lieferte. Einzig der Kontaktseffizienz Koeffizient fur die Aggregate

musste recht niedrig eingestellt werden, um eine gute Ubereinstimmung mit den experi-

mentellen Daten zu erreichen. Beide Koeffizienten wiesen keine erkennbare Abhangigkeit

von der Kolloidkonzentration auf. Die Maximalkonzentration der Kolloide war jedoch

konzentrationsabhangig, wozu eine lineare Beziehung aufgestellt werden konnte.

Transport von Nano-Eisen-Kolloiden im radialen

Stromungsfeld

Hintergrund

Saulenversuche konnen nur bedingt die Transportfahigkeit von Nano-Eisen darstellen,

da Sie nur ein sehr einfaches, eindimensionales Stromungsfeld besitzen. Um das Trans-

portverhalten von Nano-Eisen wahrend der Injektion im Untergrund richtig beschreiben

zu konnen, muß das Stromungsfeld mindest radialsymmetrisch gewahlt werden. In einem

radialsymmetrischen Stromungsfeld weist unter anderem die Fließgeschwindigkeit eine hy-

perbolische Abnahme mit zunehmender Entfernung von der Injektionsstelle auf. Dieser

Effekt lasst sich mittels standard Saulenversuchen nicht darstellen.

Im Rahmen dieser Arbeit wurden drei verschiedene Methoden entwickelt, um den

Transport in einem radialsymmetrischen Stromungsfeld nachbilden bzw. vorhersagen zu

konnen.

Großskalige Containerversuche

Zur Erstellung eines hyperbolisch abnehmenden Fließgeschwindigkeitsprofils wurde ein

Container in Form eines gleichseitigen Dreiecks zur Annaherung an ein Zylindersegment

aufgebaut (Lange = 2 m, Hohe = 60 cm, Winkel = 60). Ein Dreieck wurde ausgewahlt,

da dies annahernd die gleichen Stromungseffekte wie ein kompletter Zylinder nachweist

aber nur ein Sechstel an Bodenmaterial und Suspension benotigt. Ein Dreiecksschenkel

XXII

wurde mit einer Glasscheibe versehen, um die Ausbreitung der Kolloide auch visuell

beobachten zu konnen. In der Spitze wurde ein Injektionsbrunnen eingebracht und ent-

lang des gegenuberliegenden Dreiecksschenkels wurden Drainagerohre installiert, die an

einen Auslaufbehalter mit Festpotential angeschlossen wurden. Der Behalter wurde ho-

mogen mit Sand befullt und mit einem festen Deckel verschlossen, sodass ein gespannter

Aquifer gebildet war. Im Container wurden verschiedene Versuche durchgefuhrt. So kon-

nte gezeigt werden, dass eine kontinuierliche Pumprate bei der Injektion besser ist als eine

pulsierende. Auch wurde festgestellt, dass eine Halbierung der Injektionsrate nur einen

geringen Effekt auf den Ausbreitungsradius hatte.

Bei den Versuchen war es moglich, das Nano-Eisen uber eine Distanz von etwa zwei

Metern zu transportieren, wenn etwa drei Porenvolumina uber eine Injektionsdauer von

einer Stunde injiziert wurden.

Abbildung eines radialen Stromungsfeldes mittels Saulenversuchen

Da die großskaligen Containerversuche sehr arbeitsintensiv waren, viel Vorbereitungszeit

brauchten und sehr große Mengen an Suspension benotigten, wurde nach einer einfacheren

und schnelleren Methode gesucht, um den Transport in einem radialen Stromungsfeld

darzustellen.

Hierzu wurde zunachst mathematisch das Stromungsfeld aufgeteilt in kleinere Kreis-

segmente. Dann wurde die Fließrate in jedem Segment auf eine Saule gleicher Lange

ubertragen. Bei der Injektion der Suspension in eine der jeweils ein Segment represen-

tierenden Saulen wurde der Auslauf gesammelt, sodass er als Eingangssuspension fur die

nachste Saule genutzt werden konnte. Somit wurde eine Versuchsmethode entwickelt, um

das radiale Stromungsfeld diskretisiert darzustellen.

Es wurden zwei Versuche mit jeweils drei Segmenten durchgefuhrt. Die Ergebnisse

wurden sodann mit denen von zwei großskaligen Containerversuchen verglichen. Hierzu

wurde von jeder einzelnen Saule das Konzentrationsprofil aufgezeichnet. In der graphis-

chen Darstellung wurden sodann die einzelnen Profile entsprechend der Position der Saule

im Gesamtablauf aneinandergehangt. Es konnte somit nachgewiesen werden, dass die

Methode in der Lage ist, die Realitat akzeptabel bis gut zu reprasentieren.

Ein Hauptproblem bei der Durchfuhrung war die genaue Einstellung der Ein-

gangskonzentration durch Verdunnung aus dem Nano-Eisen-Schlamm. Da die Trans-

porteigenschaften der Suspension stark von deren Einganskonzentration abhangig sind,

ist es schwierig, verschiedene Falle zu vergleichen oder Vorhersagen bezuglich des Trans-

portverhaltens in einem bestimmten System zu treffen, wenn auch nur geringfugig veran-

derte Eingangskonzentrationen vorliegen.

XXIII

Numerische Simulation

Als dritte Methode wurde die hergeleitete Transportgleichung in ein numerisches Model

mit mehrere Dimensionen umgesetzt. Um die Robustheit vom Modell zu steigern und

die Moglichkeiten der Anwendbarkeit zu vergroßern, wurde der Finite-Elemente-Solver

FEniCS [Logg et al., 2011] gewahlt. Auch hier wurde das Modell getestet gegen die Resul-

tate der großskaligen Containerversuche, wobei die Eingangsparameter entsprechend dem

großskaligen Containerversuche gewahlt wurden. Dazu wurden die Kontaktseffizienz Ko-

effizienten fur die Kolloide und die Aggregate und die Gleichung fur die Maximalkonzen-

tration der Kolloide eingesetzt, die aus den Saulenversuchen bestimmt wurden. Das Re-

sultat wurde dann vergleichend mit den Endresultaten vom großskaligen Containerversuch

graphisch dargestellt. Auffallig war, dass die Ergebnisse der numerischen Simulation fast

genau durch die Mittelwerte der gemessenen Konzentrationen gingen.

Durch den Einsatz der Transportgleichung in einer numerischen Simulation konnte also

eine sehr gute Vorhersage des Transports im radialen Stromungsfeld getroffen werden.

Machbarkeitsanalyse zum Einsatz von Nano-Eisen im

Feld

Hintergrund

Die bisher in dieser Arbeit prasentierten Erkenntnisse sind weitgehend als Grundlagen-

forschung anzusehen und stellen die Basis fur ein vertieftes Prozessverstandnis zum

Transport von injizierten Nano-Eisen-Partikeln im Untergrund. Uber die rein wis-

senschaftlichen Aspekte hinaus konnen die entwickelten Methoden und hergeleiteten

Beziehungen auch zur Einschatzung der Machbarkeit einer Injektion im Feld herange-

zogen werden.

Einschrankend lasst sich nochmals darauf hinweisen, dass alle hier beschriebenen Meth-

oden auf der Annahme basieren, dass Stromung und Transport im Untergrund nur mittels

Permeation im porosen Medium stattfinden und nicht durch hydraulisch erzeugte Klufte.

Außerdem wurden fur die Beweisfuhrung nur dispergierte, verdunnte Nano-Eisen Suspen-

sionen eingesetzt. Die Ubertragbarkeit auf Suspensionen mit anderen Eigenschaften ist

daher vorher im Einzelfall zu uberprufen.

Voraussetzungen fur einen erfolgreichen Einsatz

Bevor Nano-Eisen zur Grundwassersanierung eingesetzt werden kann, muss bekannt sein,

ob ein Einsatz mit einer hinreichend hohen Wahrscheinlichkeit zum Erfolg fuhrt. Hierzu

sollten bereits in einem fruhen Stadium der Planung einige grundlegende Fragen beant-

wortet werden, um die grundsatzliche Machbarkeit einer Injektion einschatzen zu konnen.

XXIV

Befindet sich zum Beispiel der Schadensherd hauptsachlich in der ungesattigten Zone, ist

der Einsatz von Nano-Eisen nicht sinnvoll, da es sofort durch den hohen Sauerstoffge-

halt oxidieren wurde. Ein weiteres Ausschlusskriterium ist die hydraulische Leitfahigkeit

des Untergrundes. Ist diese zu niedrig, kann hochstwahrscheinlich kein Transport uber

Permeation stattfinden. Falls alle sonstigen Kriterien aber fur den Einsatz von Nano-

Eisen sprechen, sollten Laborversuche durchgefuhrt werden, um die Machbarkeit naher

zu untersuchen.

Zunachst sollte festgestellt werden, wie im Einzellfall ein Erfolg definiert ist und wie

dieser nachzuweisen ist. Hauptsachlich sollte bewiesen werden, dass die erforderliche Aus-

breitung der Partikel wahrend der Injektion erreicht wurde. Dazu kann beispielsweise die

im Rahmen dieser Arbeit entwickelte Feldmesstechnik eingesetzt werden. Die Sensoren

werden dazu idealerweise direkt zwischen zwei Injektionspunkten installiert. Des Weit-

eren sollte die Reduktion der unterstromigen Schadstofffracht nachgewiesen werden. Zu

beachten ist dabei, dass bei der Injektion von Nano-Eisen-Suspension zumeist auch viel

sauberes Wasser injiziert wird. Bevor aus der Abnahme der Schadstofffracht Schlussfol-

gerungen gezogen werden konnen, muss gewahrleistet werden, dass diese Injektionsflus-

sigkeit vor der Beprobung komplett ausgespult wurde. Des Weiteren konnen vor und

nach der Injektion durchgefuhrte Tracerversuche dabei helfen, die in die Frachtberech-

nung eingehende Grundwasserfließgeschwindigkeit moglichst genau zu bestimmen

Anwendung von Entwickelte Machbarkeitstests

Die in dieser Arbeit beschriebenen Methoden zur Vorhersage der Ausbreitung von Nano-

Eisen-Suspension im radialen Stromungsfeld konnen dazu eingesetzt werden, sowohl die

Eingangskonzentration als auch die Injektionsrate fur einen Feldeinsatz zu bemessen.

Gegebenenfalls kann zusatzlich noch die Distanz zwischen den Injektionsbrunnen op-

timiert werden, wobei fur deren Lage jedoch haufig andere Faktoren (z.B. Bebauung)

ausschlaggebend sind.

Ziel einer Auslegung sollte es sein, eine Kombination von Eingangskonzentration und

Injektionsrate zu finden, mit der eine zuvor bestimmte Mindestkonzentration an Nano-

Eisen in moglichst großen Bereichen des zu sanierenden Untergrundes erreicht werden

kann. Die benotigte Menge an Nano-Eisen kann somit minimiert werden.

Schlußfolgerungen

Der Einsatz von Nano-Eisen ist ein vielversprechendes Verfahren zur Sanierung von verun-

reinigten Aquiferen. Das Ziel eines solchen Einsatzes ist die Entfernung des Schaden-

sherdes in-situ, also direkt im Untergrund. Das Transportverhalten von Nano-Eisen

wahrend der Injektion wurde in dieser Arbeit im Detail untersucht und es konnte ein

deutlicher Fortschritt im Verstandnis des Transportverhaltens verzeichnet werden. Die

XXV

chemische Machbarkeit einer Sanierung mit Nano-Eisen wurde in dieser Arbeit nicht be-

trachtet. Abschließend soll nun auf die eingangs gestellten vier Forschungsfragen einge-

gangen werden, welche alle vier eindeutig beantwortet werden konnten:

(a) Ist es moglich Nano-Eisen direkt im Untergrund zu messen?

Es gab bis zum Anfang der Arbeit noch keinen verfugbaren Messtechnik. Deshalb

wurde im Rahmen der Arbeit eine neue Messtechnik entwickelt mit Hilfe derer die

Nano-Eisen-Konzentration zerstorungsfrei gemessen werden kann.

(b) Welche Faktoren bedingen die niedrige Transportfahigkeit im porosen Medium und

wie kann der Transport optimiert werden?

Die Große der Kolloide wurde als Hauptfaktor fur den Transport bestimmt. Beim be-

trachteten Nano-Eisen-Material (RNIP 10-E, Toda Kogyo, Japan) wurde festgestellt,

dass die Kolloide zur Bildung von Aggregaten neigen und der angelieferte Schlamm fur

eine direkte Einbringung in den Untergrund zu hoch konzentriert ist. Ein vorrangiges

Ziel dieser Arbeit war es, die minimal notige Vorbehandlung der Suspension fur eine

erfolgreiche Injektion zu ermitteln. Die kolloidalen Aggregate konnen unter Einsatz

hoher Scherkrafte mittels eines Dispergiergerates in kleinere Aggregate aufgebrochen

werden. Die Primarkolloide konnen aber selbst damit nur bedingt wiederhergestellt

werden. Zusatzlich muss der angelieferte Schlamm runterverdunnt werden, um den

Transport im Untergrund moglich zu machen.

(c) Welche Reichweite kann in einem radialen Stromungsfeld erreicht werden?

In dieser Arbeit wurde erstmalig ein Transport von fast zwei Metern in einem radialen

Stromungsfeld nachgewiesen.

(d) Wie lasst sich die Machbarkeit der Injektion an einem Standort feststellen?

Es wurde ein Fließschema erstellt, um bei der Einschatzung der Machbarkeit einer

Injektion zu helfen. Es wurden zwei alternative Methoden entwickelt, um den Trans-

port im radialen Stromungsfeld vorhersagen zu konnen. Der Einsatz einer dieser

Methoden kann in der Planungsphase helfen, die richtigen Entscheidungen zu treffen

und die benotigten Ablaufbedingungen festzulegen.

Die Ergebnisse dieser Arbeit sind vielversprechend und stellen eine gute Basis fur

weitere Forschung bezuglich des Einsatzes von Nano-Eisen bei der Sanierung von kon-

taminierten Aquiferen dar. Des Weiteren konnen die hier vorgestellten Ergebnisse bei der

Beurteilung von entsprechend gelagerten Fallbeispielen helfen.

XXVI

1 Introduction

1.1 Background

The awareness of the dangers of contaminated sites and the resulting contamination in

groundwater has been increasing over the last decades. The number of sites that have

been recognized for the need to be treated is large, in the European Union there are over

three million sites contaminated [Swartjes, 2011]. In Germany 350 000 sites are potentially

contaminated and are a danger for the environment and the groundwater [Hahn, 2006].

A major separation of contaminant types is made based on their density (Figure 1.1).

Contaminants that have a higher density than water are called dense nonaqueous phase

liquids (DNAPL), if their density is lower than water they are light nonaqueous phase

liquids (LNAPL). Among the sites in Germany, 35% are contaminated by chlorinated

hydrocarbons (CHCs), these are very toxic and many of them are carcinogenic. CHCs like

Tetrachloroethylene (PCE) and Trichloroethylene (TCE) are non flammable solvents for

organic materials and were thus used in many industrial areas, mainly to degrease metal

parts. Furthermore, PCE was also applied in many dry-cleaning facilities, which were

often situated in urban areas. Liquid CHCs like PCE and TCE are DNAPLs. If spilled

in large volumes, due to their high density, they can penetrate deep into the subsurface,

moving through the unsaturated zone and pass the groundwater table into the saturated

zone, leaving a trail of residual NAPL (ganglia) behind, until a less permeable layer like

a clay layer or an aquitard (typically the bedrock formation), holds them from moving

further downward, where a highly saturated pool forms. DNAPLs like PCE and TCE

dissolve (albeit, very slowly) into the groundwater passing through the zone of ganglias

and pool (source zone), the formed contaminated groundwater plume in turn often ends

up in drinking water wells, rivers and lakes. Due to the high toxicity of these CHCs, even

very low concentrations in the groundwater can form a risk for human health and the

environment. Furthermore, because CHC phase is so persistent, downstream groundwater

can end up to be polluted for several centuries.

1

1. Introduction

Figure 1.1: LNAPL and DNAPL spill distributions in the subsurface, after Godeke [2011]

1.2 Remediation Technologies

At present, many different types of remediation techniques exist. They can be classified

in: Ex-Situ methods that remove the contaminant from the subsurface to treat it on the

surface, both on-site and off-site and In-Situ techniques to remediate a contamination

in the subsurface without bringing the contaminant to the surface.

1.2.1 Ex-Situ

For sites with near surface pollution (often these are LNAPL spills), excavation is the

most common applied method. Though effective in achieving a full clean up, the main

disadvantages of this technique are the ecologically ineffectiveness due to the high en-

ergy consumption for excavation, transport and off-site treatment as well as the rather

unsuitability for residential areas and saturated aquifers [Fetter, 1999]. In case of a sat-

urated aquifer or for deeper contaminations the pump-and-treat remediation is currently

the most applied method for treatment. With pump-and-treat the groundwater with the

2

1.2. Remediation Technologies

dissolved contaminant is pumped out of the ground and treated on the surface, for ex-

ample by using activated-carbon filters. With this technique it often takes many years or

even decades to remediate a site if NAPL phase or sorbed contaminants is present [Fetter,

1999].

1.2.2 In-Situ

Different In-Situ techniques have been developed to remove CHCs from the groundwater

and source zone. Some methods involve only a single action after which chemical reactions

or biology removes the contaminants or when the natural conditions are suitable to remove

the contaminants it might even involve no action beside close observation and monitoring

of the contaminants in the downstream groundwater.

Contaminant plumes downstream of the source zone can be cut off by placing permeable

reactive barriers (PRBs) or they can be treated by enhanced natural attenuation (ENA).

ENA is mainly the controlled and enhanced biodegradation by bacteria or plants (e.g.

Ferguson and Pietari [2000]; Yang et al. [2009]).

The PRB method was proposed by Gillham and O’Hannesin [1992], these barriers are in

principle trenches where the aquifer material has been replaced by reactive material, the

exactly chosen chemical substance can differ for each pollution origin. Once the polluted

groundwater flows through the PRB, the reactive components of the PRB transform the

pollutants into harmless or immobile end products.

One of the materials often used (e.g. Vogan et al. [1999] or VanStone et al. [2005]) in

PRBs is zero valent iron (also denoted as “elementary iron” or “Fe0”). Zero valent iron is

capable of remediating several types of pollutants, the most common target pollutions of

PRBs are chlorinated hydrocarbons. Most of them can be dechlorinated by zero-valent

iron.

1.2.3 Nanotechnology for Groundwater Remediation

In an interview in The Progressive [Higgs, 2009], David Rejiski of the Project on Emerging

Nanotechnologies (PEN) states that products that include nano-sized particles are boom-

ing with 212 different products in March 2006 up to 1015 products in August 2009. This

organization also notes a 50% increase in the number of organizations that are involved

in nanotechnology between 2006 and 2008.

Nanotechnology takes place at a scale of one to several billionths of a meter. For

comparison, the diameter of a human hair varies between 17 000 and 181 000 nanometer

3

1. Introduction

1m 10−1m 10−2m 10−3m 10−4m 10−5m 10−6m 10−7m 10−8m 10−9m 10−10m

(1 cm) (1 mm) (1 µm) (100 nm) (1 nm)

Soccer BallDiameter ≈ 22 cm

Human Hair, diameter 17− 181 µmMicro Fe-Colloids, diameter 1− 15 µm

Credit: BASF, Germany

nZVI ParticlesDiameter: ≈ 60− 120 nmCredit: Li, Elliot and Zhang [2006]

Carbon 60Diameter ≈ 0.7 nm

10m

Micro Iron ParticlesDiameter ≈ 30− 100 µm

Credit: Hoganas, Sweden

1

Figure 1.2: Overview of different sizes

[Ley, 2010]. A meter scale is given in Figure 1.2 to give an overview of the different size

scales. Since science and industry are now able to work on these incredibly small scales,

all sorts of intriguing possibilities come within reach.

Also for the groundwater remediation field it is nano-technology that appears to provide

very promising possibilities. Different types of nanoparticles are being created to treat

specific contaminants. Nanotitaniumoxide particles (TiO2) were found capable of immo-

bilizing pertechnetate anions in situ [Mattigod et al., 2005]. TiO2 particles (∼ 20 nm)

doped with gold nanoparticles (∼ 2 nm) were found to be highly effective to perform

a photocatalytic clean-up of methyl-tert-butyl-ether (MTBE) and 4-chlorophenol con-

taminated groundwater [Orlov et al., 2007]. A nanosensor was developed based on a

semiconductor film of ZnO (∼ 27 nm) which was found to quench emitting visible light

when chlorinated phenols were present in the water on top of the film. The quenching

was quantitative to the concentration and could be used to detect concentration as low as

1 ppm. Furthermore these semiconductors were able to completely degrade the organic

contaminants when radiated with UV-light [Kamat et al., 2002].

4


Based on the success of zero valent iron used in PRBs, an In-Situ method was proposed

by Cantrell and Kaplan [1997]. Instead of an excavated trench filled with ZVI filings, they

proposed the injection of a zero valent iron colloid suspension into the subsurface using

wells. This method forms a reactive permeable zone which is no longer bound to limited

depths and plume treatment, but can also be used directly in the contaminant source zone.

By treating the source directly, the contaminant removal time is significantly reduced. The

ZVI removes the contaminant from the water in the direct vicinity of the contaminant

phase, thus increasing the dissolution rate. Furthermore, the contaminant plume is cut off

and no new plume can develop. In the first tests, Cantrell and Kaplan [1997] used iron of

micrometer scale. These particles were rather heavy and gravitational settling occurred

during injection, limiting the transport and feasibility of this method. Due to the recent

developments in the nano technology branche, it has become possible to create zero-

valent iron particles at the nanometer scale. Some of the currently commercially available

nano-sized zero-valent iron (nZVI) colloids are between 10 and 100 nm in diameter (e.g.

RNIP, Toda Kogyo, Japan or NANOFER 25, NanoIron, Czech Republic). These are

provided suspended in water (with additives like surfactants and/or polymers) as a highly

concentrated slurry.

Common aquifer pore diameters range from 200 nm for a silty aquifer to 100 000 nm in

a gravel aquifer. Thus nZVI colloids are small enough to be transported through the finer

pore spaces of the porous media where micro sized particles would be filtered out [Elliott

and Zhang, 2001]. Considering the small size of nZVI, filtration effects and the chance of

clogging the aquifer are reduced and also they will have a lower settling velocity, which

should make it possible to transport them farther away from the injection well. Still

though, Tratnyek and Johnson [2006] describe that the transport distance in an aquifer

is expected to be limited based on the deep-bed filtration theory. Transport of larger

colloids is reduced mainly due to gravitational forces and straining effects (trapping in

pore throats that are too small to allow passage), whereas smaller colloids will filter out

of suspension mainly due to Van der Waals forces and Brownian diffusion [Tufenkji and

Elimelech, 2004].

While several field tests have been performed with nZVI, the delivery of the particles

to the desired location often was unsuccessful or at least disputable [Schrick et al., 2004]

or the transported distance was very small resulting in a very narrow grid of boreholes

needed for the injection (e.g. Muller et al. [2006b]).

5

1. Introduction

1.2.4 Chemical Reactions and the Chemical Composition of nZVI

The reactivity of nZVI colloids is mainly controlled by their specific surface, a higher

specific surface resulting in a higher reactivity [Bradford and Torkzaban, 2008]. The

specific surface of nZVI colloids is approximately 33.5 m2/g [Elliott and Zhang, 2001], in

comparison, for micro iron particles 0.1 − 1 m2/g [Nurmi et al., 2005] and for granular

iron filings approximately 0.004 m2/g [Huang et al., 2003], although the latter can due to

surface roughness and angularity reach a specific surface of approximately 0.5 m2/g. The

high reactivity makes the nZVI colloids reactive towards many contaminants (Table 1.1)

and facilitate to deplete a source zone with high concentrations of the contaminant and

stop the generation of a pollution plume. The chemical reaction that takes place between

nZVI and contaminants (e.g. CHCs) is well understood and has been described by several

authors in detail [Bartzas et al., 2006; Lien and Zhang, 2001; Liu et al., 2005; Steiert,

2008; Zhang, 2003].

Table 1.1: Pollutants that can be remediated by nZVI. After Muller et al. [2006a]; Zhang [2003]

Chlorinated methanes Chlorinated benzenes Pesticides

Carbon tetrachloride (CCl4) Hexachlorobenzene (C6Cl6) DDT (C14H9Cl5)

Chloroform (CHCl3) Pentachlorobenzene (C6HCl5) Lindane (C6H6Cl6)

Dichloromethane (CH2Cl2) Tetrachlorobenzenes (C6H2Cl4) Organic dyes

Chloromethane (CH3Cl) Trichlorobenzenes (C6H3Cl3) Orange II (C16H11N2NaO4S)

Dichlorobenzenes (C6H4Cl2) Chrysoidine (C12H13ClN4)

Chlorobenzene (C6H5Cl) Tropaeolin O (C12H9N2NaO5S)

Heavy metal ions Trihalomethanes Chlorinated ethenes

Mercury (Hg2+) Bromoform (CHBr3) Tetrachloroethene (C2Cl4)

Nickel (Ni2+) Dibromochloromethane (CHBr2Cl) Trichloroethene (C2HCl3)

Silver (Ag+) Dichlorobromomethane (CHBrCl2) cis-Dichloroethene (C2H2Cl2)

Cadmium (Cd2+) trans-Dichloroethene (C2H2Cl2)

Cobalt (Co2+) 1,1-Dichloroethene (C2H2Cl2)

Tin (Sn2+) Vinyl chloride (C2H3Cl)

Lead (Pb2+)

Copper (Cu2+)

Polychlorinated hydrocarbons Other organic contaminants Inorganic anions

PCB’s N-nitrosodimethylamine (NDMA) Dichromate (Cr2O2−7 )

Dioxins (C4H10N2O) Arsenic (AsO3−4 )

Pentachlorophenol (C6HCl5O) TNT (C7H5N3O6) Perchlorate (ClO−4 )

Nitrate (NO−3 )

6


Though, the colloids are not only more reactive towards the contaminants, they are also

strongly affected by undesired side reactions. The main side reaction is the tendency

to quickly corrode. Dry nZVI colloids would even self ignite due to the reaction with

oxygen in the air. Aerobic corrosion also occurs in suspension with the dissolved oxygen

(Equation 1.1). Hence, the colloids are unsuitable for the remediation of pollutants in

the unsaturated zone, whereas fully saturated aquifers are in general completely anaerobe

and thus provide a suitable environment.

2Fe0(s) + 4H+

(aq) +O2(aq) → 2Fe2+(aq) + 2H2O(l) (1.1)

An other side reaction is anaerobic corrosion (Equation 1.2), this reaction though is much

slower and strongly pH dependent [Bartzas et al., 2006]. During storage the colloids are in

an anaerobic environment, in which, even tough no free oxygen is present, they can thus

still corrode. The anaerobe corrosion is in a closed environment self inhibiting because

the corrosion sets hydrogen and hydroxide free which increases the pH and consequently

reduces the corrosion rate.

Fe0(s) + 2H2O(aq) → Fe2+

(aq) +H2(g) + 2OH−(aq) (1.2)

The amount of zero valent iron inside a colloid therefore reduces with residence time in

water. Anaerobe corrosion sets hydrogen gas free (Equation 1.2) which could clog the

porous media.

To minimize the corrosion problem, nZVI colloids are often covered with a thin

shell that shields the zero valent iron from direct contact with water. The nZVI col-

loids as presented by Wang and Zhang [1997] were produced with a palladium acetate

([Pd](C2H3O2)2]3) that reacts with a small outer part of the zero-valent iron colloid, cre-

ating a small shield against corrosion and will function as a catalyst. Towards several

contaminants additional metals like the palladium acetate can function as a catalyst as

well, other metals that can be used with the same purposes are for example platinum

(Fe/Pt), silver (Fe/Ag), nickel (Fe/Ni), cobalt (Fe/Co) and copper (Fe/Cu). The

particles of Toda Kogyo (Japan) and Nano Iron (Czech republic) are shielded with crys-

talline magnetite (Fe3O4) (Fe/Fe) [Wang and Zhang, 1997]. So far only the last type

has shown to be producible in larger amounts for a fairly acceptable price.

The chemical feasibility of the remediation technique has been worked out in detail with

Steiert [2008]. Within his research it was furthermore discovered that the production of

hydrogen gas and with that the clogging of the porous media can be significantly reduced

7

1. Introduction

by adding burned chalk (Ca(OH)2) in granular form to the suspension before injection.

This technique has been filed for patenting [Klaas et al., 2010b].

Though very small, nZVI colloids are still ferro magnetic and contain a positive and

negative pole (i.e. they are bipolar). The colloids thus tend to get attracted to each

other and form aggregates. The aggregation and gelation (the building of a network

of aggregates) can easily result in pore plugging and gravity settling, strongly reducing

transportability [Saleh et al., 2006]. To avoid aggregation, a nZVI suspension can be

stabilized through the following repelling mechanisms:

Electrostatic repulsion, which is the mutual repulsion of like electrical charges, influ-

enced by the pH value of suspension [Hong et al., 2009]; Steric repulsion, adsorbed long

polymers (e.g. guar gum) on the particle surface, which prevents particles to get close

[Tiraferri et al., 2008]; Electrosteric repulsion, which is the combination of both using

long steric repelling polymers [Phenrat et al., 2008]. Unfortunately, it was also found

that the addition of electrosteric polymers significantly reduced the reactivity because

the obstructed contact between the contaminant and the colloid [Phenrat et al., 2009,

2007].

1.2.5 Field Application of nZVI

The injection of a nZVI suspension in the field could be performed using a simple screened

well, with packers to inject over a small height, by using a short filter screen at the tip

of a direct push rod, or hydro fracturing (either by using a concrete lined well, or direct

push). The injections using filter screens result generally in a near radially symmetrical

flow field around the injection well. Spherical flow fields will be less profound since most

aquifers show a horizontal layered structure with a large anisotropy. A radial flow field

results in a hyperbolically reducing seepage velocity with increasing distance from the

well screen. When hydro fracturing is applied, the main transport takes place in large

fractures and there is negligible porous media flow (permeation) thus this technique falls

beyond the scope of this research.

In a general sense, there are two different possible application concepts for injectable

nZVI, source zone- and plume treatment.

F To prevent the migration of a plume, or to secure an area (e.g. residential- or water-

protection area) from an approaching plume a barrier can be formed with injectable nZVI

(similar to a PRB). The concentrations in a downstream plume are much lower than the

concentrations in a source zone. The removal of the contaminant in the plume will not

8


Figure 1.3: Conceptual concentration distribution of an injection field

affect the dissolution rate of the contaminant in the source zone. This application type

is thus mainly useful in case of an unknown, unreachable or already removed source. To

make sure that the whole contaminant is in contact with the injected barrier, it should

be guaranteed that the nZVI is spread between injection wells without voids where the

groundwater could pass through. This can be achieved by placing the wells in triangular

positions. The concentration of nZVI is expected to decrease with increasing distance

from the injection well. Hence, a possible concentration profile could look like the one

presented in Figure 1.3. The injected barrier has to be reactive for a long period and a full

consumption of the reactive iron is likely to occur before the source zone stops emitting.

Injectable nZVI can then make it possible to re-inject fresh reactive iron at the moment

that the previous dose has been consumed.

F To apply source zone treatment, the location of the source inside the subsurface

needs to be well known. The nZVI has then to be injected, such that it gets very close

to the contaminant phase. Once in place, the dissolved contaminant concentration in the

direct vicinity of the contaminant phase is being reduced, this in response will increase

the dissolution rate of the contaminant phase. The downstream plume will be cut off but

will not be removed. By natural attenuation or by applying a pump and treat method

the plume could be removed if necessary.

9

1. Introduction

1.2.6 Detection and Concentration Measurement of nZVI in the

Subsurface

To do a source zone treatment, as for most methods targeting the source zone, it is

essential that the exact location of the source is well known. This is far from trivial and

puts a high demand on the measuring techniques used for the field characterization. Once

the site has been characterized and the contaminant source localized, the nZVI has to

be transported to these locations. Hence, an accurate detection technique is necessary

to determine the location of nZVI during and after the injection. Since the reaction in

this active zone is expected to be fast, nZVI will be consumed rapidly as the reaction

proceeds. An accurate monitoring technique would thus be preferable to determine when

the nZVI has been consumed and a renewal is needed.

So far several measuring techniques have been applied during pilot tests to proof the

effectiveness of injected nZVI. Muller et al. [2006b] used geophysical measurements, like

ground penetrating radar, geomagnetic and geoelectric mapping. Glazier et al. [2003]

and Zhang [2003] used in their field test measurements of flow rate, water level, oxidation

reduction potential (ORP), dissolved oxygen (DO), pH, specific conductance, tempera-

ture and the contaminant concentration reduction to show the radius of influence of the

injection and the location of nZVI during and after the injection. Elliott and Zhang [2001]

monitored the total iron and dissolved iron concentrations in combination with the pH

and ORP values at monitoring wells throughout the injection to determine the migration

of nZVI. Quinn et al. [2005] used soil samples from cores taken at different times after the

injection of emulsified zero valent iron and compared the TCE content in the samples to

samples from cores taken prior to the injection. They also measured the TCE concentra-

tions in ground water samples at different times after the injection and compared them

with samples taken prior to the injection.

The aforementioned measuring techniques all share some common problems. The meth-

ods based on ground water sampling are not conclusive since during the injection a large

amount of clean water (used as carrier fluid for nZVI) was injected, pushing away the

dissolved contaminants. It takes time before the contaminants again dissolve into the

fresh water up to the old concentration and also the groundwater flow velocity through

the contaminated zone might be reduced due to the presence of the nZVI and possibly

hydrogen gas. Using cores from different locations to compare samples after the injection

with samples taken prior to the injection will likely be inconclusive even if the cores are

taken close to each other since the subsurface is heterogeneous. Therefore, geogenic iron

10

1.3. Research Questions

background values are likely to differ more than the additional iron added due to injection

of nZVI from one location to another.

To quantitatively and conclusively measure the nZVI presence in the subsurface during

and after the injection, a new technique able to monitor directly iron concentrations

without background interference is desirable.

1.3 Research Questions

In the previous sections it has been emphasized that the treatment of contaminations in

the groundwater with injectable nZVI is promising. Nevertheless, there are still questions

to be answered and technical problems to be overcome before the method can be applied.

The goal of this doctoral research is to get a better description and understanding of

the transport behavior of nZVI during the injection into the subsurface which led to the

following research questions:

(a) Is it possible to detect In-Situ the concentration of iron and determine the transport

distance?

(b) Which conditions have the largest effect on mobility and how can they be opti-

mized?

(c) What is the transport distance in a radial flow field?

(d) Which method can test the feasibility of injection into the subsurface?

1.4 Structure of the Dissertation

To obtain a better description and understanding of the transport behavior of nZVI in

porous media the research started at the fundamental of colloid filtration and worked

this out through 1-D and 2-D experiments and numerical simulations to recommenda-

tions for the field, covering a wide range of scales. For this need, it was found that no

non-destructive and direct measuring technique was available and thus first had to be

developed to describe and understand the transport behavior (Figure 1.4).

This work distinguishes four main chapters after this introduction. Chapter 2 presents

the developed quantitative non-destructive measuring and detection techniques based on

the ferro magnetic property of nZVI to measure the nZVI concentration in the porous

medium at the column, container and field scale. A chemical (destructive) analysis

method was furthermore developed to provide a chemical verification method of the non-

destructive measurements as well as to characterize nZVI suspensions. Chapter ??

11

1. Introduction

Figure 1.4: Dissertation research structure

provides a description of colloid transport and constitutive relationships derived from the

colloid filtration theory, column experiments and numerical simulations of the column

experiments. Chapter 4 focuses on the transport in a radial flow field. A large scale

container experiment is presented. The results of this experiment were used to verify a

quick screening column experiment and a numerical predictive model. Chapter 5 shows

how the experiments and the numerical simulations provide a method to test the injec-

tion feasibility and can be used to design a field application. Recommendations and the

preferred approach for the optimized design are presented. At the end of the work the

answers on the research questions are summarized in the conclusion and an outlook

provides further research topics that could be performed.

12

2 Detection and Concentration

Measurement of nZVI in the

Subsurface

2.1 Motivation

Research on the transport of nZVI is only possible with accurate methods to determine

the concentration inside porous media. So far most research was based on break through

curves of columns (e.g. Baumann and Werth [2005]; Bradford and Bettahar [2006]), some-

times supported by a destructive chemical analysis of the column contents after the exper-

iments were finished (e.g. Tufenkji and Elimelech [2005b]). Break through curves can be

useful and through a combination with numerical simulations [Tosco et al., 2009], many

transport parameters can be determined by fitting. The exact distribution inside the

porous medium though is far from sure to be realistic, many different scenarios can lead

to the same break through curve. Visual observation can not provide quantitative con-

centrations, since the iron already colors the sand black at very low concentrations, only

the front of the iron can be determined and further no separation between low and high

concentrations is possible. In a chemical determination the natural presence (geogenic)

of iron in the sand will create a large unknown factor in the determination. Because even

the geogenic iron content of sand packed in a column or container is not homogeneously

spread, it is not possible to make a fully reliable difference measurement based on chem-

ical iron detection. Furthermore, a chemical analysis can first be performed after the

experiment is finished because sand samples have to be taken.

To facilitate a quantitative measurement of the nano sized zero valent iron (nZVI)

concentration during and after the injection into a column, a container or an aquifer,

a new measuring technique has been developed. The method has been produced in

different stages for different uses. The first stage was the adaptation of existing hardware

to measure concentrations inside a column. The second phase was the development of a

13

2. Detection and Concentration Measurement of nZVI in the Subsurface

sensor and the accompanying electronics to measure break through curves within a large

container experiment. The final stage was the development of sensors and electronics to

measure concentrations in an aquifer for a field application. All three different types of

sensors and accompanying electronics have been tested in the lab. The following sections

separately describe the measuring techniques for all three uses.

Collaborations

The container and field sensor development was performed in collaboration with Andre

Buchau and Hua Li of the Institute of Theoretic Electrical Engineering (ITE), Univer-

sity of Stuttgart. They performed numerical simulations of the electromagnetic fields

of different types of sensors to optimize the sensors for the container and the field and

developed post processing algorithms. The coordination, design of the sensor production

techniques, production and experimental testing of all the sensors and implementation of

the post processing algorithms into data analysis software were performed by the author.

The electronics for the container and field sensors was developed in collaboration with

Hubert Hermes from Hermes Messtechnik, Stuttgart, Germany. The building and testing

of all the electronics based on the electrical layouts were performed by the author.

2.2 Susceptibility

Susceptibility is the ratio of the magnetization in a substance to the corresponding mag-

netizing force, iron has a significant susceptibility [Getzlaff, 2008]. Simple experiments

on nZVI showed that this material property is still observable [de Boer, 2007]. Hence, a

measurement system that detects changes in susceptibility of the monitored subsurface

is possible. The system should be designed in a way that the magnetic field strength

is small enough to neglect the non-linear behavior of susceptibility of iron. Then, the

magnetic flux density B is simply connected to the magnetic field strength H by

B = µ0(1 + χnZV I)H (2.1)

where χnZV I is the susceptibility of nZVI and µ0 is the permeability of vacuum [Getzlaff,

2008]. The volume of nZVI (VnZV I), which is injected into an aquifer, is very small.

Furthermore, it is assumed that the nZVI near the sensor is approximately homogeneously

distributed in the aquifer. Then, the observed susceptibility χ is expected to be in the

14

2.3. Measurement of nZVI Concentration Profiles in a Column

range of:

χ ' VnZV IχnZV I (2.2)

The measured susceptibility in Equation 2.2 depends both on the concentration of nZVI

and on its susceptibility [Bregar and Pavlin, 2004]. If the susceptibility of nZVI is con-

stant, the resulting susceptibility depends only on the concentration of nZVI. Non-linear

behaviour of nZVI is excluded by small magnetic fields to ensure the recommended con-

stant susceptibility of nZVI. By using an alternating magnetic field (e.g. between 1 kHz

and 20 kHz), there is no chance of polarizing the nZVI nor is there any magnetic attrac-

tion or repelling. Starting from the statement in Equation 2.2, the concentration of nZVI

in the porous medium (CnZV I) can be related to the total susceptibility

CnZV I = s (χ) (2.3)

The function s (χ) can be obtained from posteriori chemical analysis (e.g. using the

method described in Elion and Elion [1933] or Liu and Lowry [2006]), or a priori cal-

ibration of the sensor. The calibration of the column experiments was performed by

calculating the total injected mass of iron present inside the column at the moment the

susceptibility was measured along the column. The posteriori chemical analysis method

has been used for the container experiments and is described in more detail in Section 2.6,

for the field measurement a method to calibrate the sensors before installation has been

developed and is presented in Section 2.5.4. Since the total susceptibility χ is very small, a

high sensitivity and precision of the electronics was necessary for a reliable measurement.

In the following three sections the measurement of the susceptibility at three different

scales is presented.

2.3 Measurement of nZVI Concentration Profiles in a

Column

A column experiment was set up to investigate the transportability of nZVI. To measure

the particle concentration and determine transport characteristics in porous media, a

commercially available metal detector was adopted. Institute Dr. Foerster (Reutlingen,

Germany) provided one of their research and development devices (Minex FX2FD) which

could be connected to a computer to store all the raw data internally produced by the

15


detector.

2.3.1 Experimental Set Up

To prevent interference of metal on the detection, the framework to hold the column was

made completely from wood and contained no metal parts. Due to the framework, the

column was situated 1.5 m above the steel reinforced concrete floor and the metal track

which was used to move a wooden metal detector carrier at a constant velocity along the

column. Within one of the sensor openings of the metal detector the column was placed

(Figure 2.1). In basics, the detector consists of an oscillator producing an alternating

current at 19.2 kHz that passes through a coil producing an alternating electromagnetic

field. Another coil is used to measure the electromagnetic field through an alternating

voltage induced in that coil. This voltage changes when the susceptibility within the

electromagnetic field changes. The coils of the Minex FX2FD are 8-shaped and placed

on top of each other, creating roughly one electromagnetic field within each of the loops

which both point in opposing directions [Auslander et al., 1991]. This is useful when

searching small metal parts in the soil to determine if they are located closer to the one

or other opening of the sensor. Though, for the column experiment this functionality is

not necessary and is not used by placing the column inside only one of the loops.

The digital output of the detector is linearly proportional to the magnetic susceptibility

(detailed testing provided in the following section). The susceptibility in turn is directly

proportional to the iron concentration [Bregar and Pavlin, 2004; Buchau et al., 2010].

2.3.2 Concentration Profiles and Calibration

During the injection the concentration profile inside the column was measured approxi-

mately every ten minutes. A high accuracy of the nZVI content change inside the column

due to the injection was reached because geogenic iron occurrences in the sand and back-

ground metal presences were removed by subtracting a background measurement. The

carrier moved with 10 mm/s and the metal detector registered 25 readings per second,

resulting in a resolution of 0.4 mm. To convert the measured signal profile into a real

concentration profile, one measured profile of each experiment was used with a clear

distribution of iron inside the column. The total injected nZVI MFe at the moment

of the recording was calculated based on the injection rate Q, duration t and the sus-

pension input concentration Cinput (i.e. MFe = QCinputt). The concentration Cinput was

determined using the phenanthroline colorimetric method and a photometer (Lambda 12,

16


Perkin Elmer, Germany), this method provides a measurement of the total iron (Fetotal)

in suspension. All the iron inside the suspension was dissolved into solution by using

nitric acid (H2SO4). Preferably no iron break through at the outlet was reached. When

such reading was not available, the difference between the injected concentration and the

effluent concentration (Ceffluent) was used to determine the total iron inside the column:

MFe(t) = CinputQt− Ceffluent(Qt− PV ) (2.4)

where PV denotes one pore volume of the column. The measured value Mt minus the

background value M0 were then integrated over the length of the column (Equation 2.6),

from this sum AM and the total injected iron MFe a conversion ratio kFe was calculated

(Equation 2.6), which was used to convert the rest of the measurements into concentration

profiles.

AM =∑

0→bcolumn

(Mt −M0) (2.5)

kFe =MFe

AM

(bcolumnmsand

)(2.6)

where bcolumn is the number of data points along the length of the column and msand

the total mass of sand inside the column. Since the metal detector can not distinguish

between colloids in suspension and colloids attached to the porous medium, the concen-

tration profiles always present the summed concentration of the attached mass of nZVI

on the porous medium and the mass of nZVI in suspension, this summed concentration

is presented in the rest of this work as Stotal to present the total mass of nZVI per mass

of dry soil (Equation 2.7) in each data point.

Stotal = kFe (Mt −M0) (2.7)

when the concentration as a function of wet soil would be needed, Stotal|wet could be

calculated following:

Stotal|wet = kFe (Mt −M0)

(ρsand(1− n)

ρsand(1− n) + ρf (n)

)(2.8)

where ρsand is the density of sand [ML−3], ρf the density of water [ML−3] and n the

porosity [−].

17


Figure 2.1: Setup of the metal detector to non-destructively measure concentration profilesalong the column. The metal detector was placed on a wooden frame which could move over a

rails. The column was placed inside the lower opening of the metal detector ring

2.3.2.1 Linearity of the Detector

To show the linear response of the metal detector to the concentration of iron, different

amounts of dry iron powder were mixed with sand. The iron powder was each time

completely mixed with 140 g sand, this filled a section of 10 cm in the column. In the

column the iron sand mixtures were separated by a section with 10 cm clean sand for the

low concentrations and a section with 15 cm clean sand for the higher concentrations (see

top of Figure 2.2). The whole column was measured by moving the detector at a rate of

10 mm/s along the column.

The signal of the metal detector responded to the iron content in the vicinity of the

location of the measuring coil (Figure 2.2). Thus the signal was already changing in the

clean sand area when it got close to the section containing iron. In the middle of each

iron filled section, the signal was at a maximum because on both sides of the measuring

coil an equal amount of metal was present.

To determine the maximum value for each metal containing section, over a length of

10 mm around the maximum value (12 data points in each direction plus the center point,

giving 25 data points in total), the sum of the response frequency was taken. This integral

value was divided by the amount of data point in 10 mm to get an average response for

1 mm of column length. Figure 2.3 shows the determined values for each integrated

section.

18


Figure 2.2: Calibration setup and the recorded RAW data of the detector. The upper valuesabove the column present the iron mass (g) per mass of sand (kg), the lower values present the

iron mass (mg) per mm of column length. Each iron containing section was separated by asection containing no iron

2.3.3 About the Metal Detector

A small noise was observed in the recorded signal, present when the detector moved

and when it stood still. The movement of the metal detector on the rails was nearly

constant, but small vibrations in the direction of travel at the measure coil was observed.

The difference between a recording with the detector standing still and moving though

showed negligible difference in the noise, indicating that the vibrations could be neglected,

especially when higher concentration changes are to be measured.

Because the metal detector mainly responds to zero valent iron, and the calibration is

performed with analytically determined values of the total iron in suspension (Fetotal),

the concentration of zero valent iron inside the colloids has an influence on the calibration

19


100

1000

10000

100000

1e+06

1e+07

1e+08

1e-05 0.0001 0.001 0.01 0.1 1

RA

W d

ata

in

teg

rate

d o

ve

r 1

mm

[-]

Stotal [g/mm]

Calibration valuesf(Stotal)=9.18⋅10

7Stotal (+/- 1.137 %)

Figure 2.3: Calibration curve of the metal detector. The measured RAW data was integratedover 1 mm and set out against the average iron content in 1 mm column length. The linear

fitted relation is: f(Stotal) = 9.18 · 107 Stotal with R2 = 0.9986

coefficient. Therefore the calibration has to be performed for each experiment when the

concentration of zero valent iron inside the colloids has changed. This happens with time

for all nZVI colloids used for this research (Section 2.6).

2.4 Measuring Iron Break Through Curves in the

Container Experiment

A large container experiment was developed to determine transport behavior of nZVI in

a near field scale radial flow regime. Since the container simulates a confined aquifer of

60 cm thickness, no metal detector could be conveniently moved along the radial distance

of the container to obtain transient concentration profiles, like in the column experiment

set up. Therefore, a fixed sensor system was thought of, installing several sensors at

different locations within the container during filling it with sand.

The magnetic field of a cylindrical coil (Figure 2.4) is large near the coil. Hence,

changes of susceptibility are mainly detected in the near-field of the coil. Then, an

optimal configuration for the measurement of changes in susceptibility is obtained if the

20

2.4. Measuring Iron Break Through Curves in the Container Experiment

Figure 2.4: Streamlines of the magnetic field strength of a cylindrical coil; energy density ofthe magnetic field in a cutting plane

axis of the coil is parallel to the flow direction of nZVI and if this flow goes through the

coil.

A fairly standard technique in the context of iron detection is to use two coils for

the measurement of the magnetic flux density. One coil measures the magnetic flux

density of the examined material and the second coil is used for a reference measurement

without magnetic material. Both coils are oppositely connected and only a difference

signal is obtained. An advantage of such a configuration is that unbalances are eliminated

at low-level in hardware. Though, here, a reference measurement is impossible. The

measurement coils are buried and a domain without nZVI is not available while the

experiment runs, and cannot be created at justifiable costs. For that reason, a post-

processing of the measured signals was used instead of the reference coil [Klaas et al.,

2010a].

Since the measured susceptibility of nZVI in the subsurface was unknown but was

expected to be very small, the measurement system had to be as sensitive as possible.

Therefore a configuration of the coils where the flow of nZVI goes through the coils was

chosen. Furthermore, a coil design that concentrates the magnetic energy very close to the

coil was used, because in such a measurement system the influence between neighboring

coils is negligible. This fact is important, since several coils have to be used at the same

time to monitor the spatial distribution of nZVI.

21


2.4.1 Data Analysis and Post Processing Algorithms

Sensitivity of the measurement method depends mainly on the accuracy of the measured

input current and the output voltage of the measuring coil sensor. A post-processing,

which is described in the following in detail, reduces errors of the measuring components

and eliminates inherent deviations of the measurement system.

The magnetic field strength H is proportional to the electric current I in the first coil

H = CI (2.9)

C is a constant that depends on the location of the point, in which the magnetic field is

calculated, but is independent of susceptibility and electric current. This approximation

is valid, if susceptibility is constant near the coil.

Since it is very difficult to keep I1 constant during an experiment, I1 is determined and

logged measuring the voltage U1 at the resistor R1 , which is connected in series to the

coil (Figure 2.5):

I1 =U1

R1

(2.10)

The electric current in the first coil is time-harmonic (with a frequency of 10 kHz).

Hence, a voltage U2 is induced in the second coil. The induced voltage depends on the

magnetic flux density B, described by the frequency, susceptibility and current in the

first coil:

U2 = c2f (χ+ 1)U1 (2.11)

The constant c2 is the result of the flux computation through the second coil.

In practice, the voltages U1 and U2 are measured with a circuit, which converts the

voltage into a digital signal for post processing on a computer (Figure 2.5). Tolerances

in the circuits are eliminated by calibration of each measuring channel. For instance,

voltage is precisely measured and the corresponding digital signal is stored in a look-up

table. Hence, even small non-linearities of the circuit are eliminated.

The easiest way to determine the constant c2 is to perform a reference measurement

with vanishing susceptibility χ = 0, all parameters measured without nZVI (χ = 0) are

indicated with a prime (′).

U ′2 = c2f′U ′1 (2.12)

22


Figure 2.5: Equivalent network of the first coil, which is used to determine the electric currentin the coil IC1 from the measured current I1; measured signals are sent to a PC

where the prime denotes the measurement at χ = 0. Note, the voltage U2 in Equation 2.11

and U ′2 in Equation 2.12 depend directly on the frequencies f and f ′. Since the frequency

produced by a signal generator is generally not stable enough for the desired accuracy,

f is recorded during the measurement by performing a TTL-conversion of the sine wave.

Finally, susceptibility is obtained from:

χ =U2f

′U ′1U ′2fU1

− 1 (2.13)

Experimental data showed, however, that an analysis purely based on Equation 2.13 is

not accurate enough in practice. The voltage U2 changed when water was injected into

the container, even though water with a zero nZVI concentration has no susceptibility.

An important quantity is the capacitance of the coil, which is caused by the electric

field between the windings of the coil. The capacitance of a coil is proportional to the

permittivity, which can be influenced by salts and surfactants in the water. Surfactants

are necessary for the transport of nZVI and the injected water was a degassed tap water,

without further treatment to remove salts. The flow of water could thus cause a change

in the permittivity and with that influence U2 due to salts and surfactants in the water.

The equivalent network of the first coil is depicted in Figure 2.5, the electric current I1,

which is measured with help of the voltage U1, it is not equal to the current IC1 through

the first coil, though preferred, it is impossible to measure IC1 directly. A solution to

avoid this problem, would be to decrease the frequency of the system. Though, that

23


would also significantly decrease the measured voltage at the second coil and with that

the sensitivity of the system. Hence, a solution, which avoids the influence of permittivity

change, was preferred. By covering the coils completely in an epoxy resin the water can

not get in between the wires and the capacitance of the coils stays unchanged.

A transfer function between the voltage at the primary coil and the voltage at the

secondary coil was obtained by an analysis of the equivalent network (Figure 2.5) and the

basic ideas of Equation 2.10 and Equation 2.11. Small terms in the transfer function are

neglected, to simplify the equation:

U2 =c3f (1 + χ)U1

1− c4(εr)f 2(1 + χ)(2.14)

where c3 and c4 are two integration constants, εr is the electromotive force, the voltage

generated around a closed loop in an electromagnetic field. Two calibration measurements

(subscripts a and b) with non-magnetic matter (χ = 0) but slightly different frequency

are to be performed. Then, the constants c3 and c4 are given by:

c3 =U ′2bfbU ′1b

(1− f ′af

′bU′1aU

′2b − (f ′b)

2U ′1bU′2a

f ′bf′aU′1aU

′2b − (f ′a)

2U ′1bU′2a

)(2.15)

and

c4 =f ′aU

′1aU

′2b − f ′bU ′1bU ′2a

(f ′b)2f ′aU

′1aU

′2b − (f ′a)

2f ′bU′1bU

′2a

(2.16)

The susceptibility χ is finally obtained from

χ =

(U2

c3fU1

)(1− c4f

2)− 1

1 +(

U2

c4fU1

)c2f 2

(2.17)

2.4.2 Sensor Design and Data Acquisition

Numerical simulations of the magnetic fields of the dual coil sensor were applied to find

a suitable design of the coils. Further prerequisites were that the coils should be small

enough to measure the local concentration of nZVI, but should still be large enough not

to disturb the flow of nZVI in the aquifer.

A cylindrical coil with a length of 108 mm and an inner diameter of 35 mm was found

most suitable for generating the magnetic field in the first coil. A copper wire with a

24


Figure 2.6: Coil winding machine

diameter of 0.6 m (0.674 mm with a varnish) was wound in four layers of 160 windings

each. The thickness of these four layers was 2.4 mm in total. For the experiment, a

self-supporting coil was obtained by a varnish coated copper wire, which melts because

of heating during winding and which consolidates afterwards (Figure 2.6). The second

coil surrounds this first coil. The length of the second coil is 14 mm. It consists of

four layers of each 40 windings. The diameter of the copper wire is 0.3 mm (0.354 mm

including varnish) and the thickness of these four layers is 1.4 mm (Figure 2.7). An

iso-surface was computed for the value of the magnetic field strength, which is 0.1% of

the maximum value of the magnetic field strength (Figure 2.8). The color indicates the

distance to the center of the coil and ranges between 200 mm in the radial direction and

300 mm in the axial direction. The streamlines of the magnetic field are cut at this iso

surface. The minimum distance between two neighboring coils in an experiment can be

derived by analyzing the magnetic field. If a neighboring coil lies outside the iso surface,

the error, which is caused in the neighboring coil, is kept lower than 0.1%. The first coil

is excited by a time harmonic electric current. Frequency and amplitude of this current

are given. Here, a frequency of 10 kHz was found to be most suitable. The voltage,

25


(a) Tools to wind cylindrical coils on (b) Uncoated dual coil sensors

(c) Tool to coat the dual coil sensor withepoxy resin

(d) Coated with epoxy resin dual coil sensor

Figure 2.7: Dual coil sensor development

which is measured at the second coil, is proportional to the magnetic flux density and the

unknown susceptibility, respectively.

The first experiments were performed using the bare coils, later experiments were per-

formed with coils completely covered by an epoxy resin. A special tool was developed

to cover the coils with the resin (Epoxy Resin L, R&G Faserverbundwerkstoffe GmbH,

Germany) (Figure 2.7c)

During the first two experiments in the container the signal of the metal detection

sensors was strongly influenced by the water chemistry (mainly due to surfactants in the

water used to inhibit the aggregation of iron colloids). For the third transport experiments

in the large container (2-D radial symmetric flow container) the sensors were coated with

an epoxy resin to avoid the influence of water chemistry on the measured signal. The

26


Figure 2.8: Iso surface of 0.1% of the maximum of the magnetic field strength of the first coilof the dual coil sensor

coated sensors only show a change in the measured signal when ferromagnetic material

is nearby. Unfortunately, however, the resin layer also reduced the magnitude of the

signal and, hence, significantly decreased the sensitivity of the measuring system. The

electronics developed for these sensors had thus to be optimized after the sensors were

coated. Furthermore the above presented method of performing measurements at different

frequencies had to be made possible. A new controller unit was designed to make it

possible to measure quickly after each other at two different frequencies. This made the

external sine wave generator (Figure 2.9c) obsolete. The electronics was found to be highly

sensitive to sudden temperature changes in the lab (e.g. direct sunlight on the electronics

or opening and closing of the building door) and daily temperature changes of day and

night, the latter made it almost impossible to calibrate the system in the morning and

perform measurements in the afternoon, therefore the electronics were all placed inside

an isolated box in which the temperature was maintained constant (Figure 2.9d). Also,

the measuring device showed fluctuations due to a 50 Hz background noise from the

27


(a) Amplifier card of the measuringdevice

(b) Sallen key low pass filter extension

(c) First set up of the electronicswith an external sine wave

generator

(d) Final set up of the electronics inside an isolated box.The front lid is opened

Figure 2.9: Container measuring electronics

electricity net. Sallen key low pass filters [Texas Instruments, 2002] between the peak

detectors and the A/D converter were added to remove this artifact (Figure 2.9b).

2.4.3 Experimental Verification

Two small column experiments were performed to verify the previously mentioned influ-

ence of surfactants on the measured magnetic susceptibility. Two dual coil sensors, one

uncoated and one coated with epoxy resin (Figure 2.7), were each placed inside a glass

column (ID: 10 cm, L: 20 cm) and filled with sand (Dorsilit, nr. 8, 0.3 − 0.8 mm).

First the columns were filled with degassed tap water, next two pore volumes of nZVI

28


1

1.0005

1.001

1.0015

1.002

1.0025

1.003

1.0035

1.004

0 1 2 3 4 5 1

1.02

1.04

1.06

1.08

1.1

1.12

χco

ated

(-)

χun

coat

ed (-

)

Pore Volumes

uncoated coilcoated coil

(a) magnetic susceptibility curves for the coated anduncoated sensor; both have their own y-axis

(b) Two test columns filled withsand, the coated and uncoated

sensors are inside. The left columnis being injected with nZVI

suspension

Figure 2.10: Experiment to verify that a coated sensor is not influenced by the injection fluidchemistry

suspension (RNIP 10 E, Toda Kogyo, Japan), diluted to 10 g/l, dispersed with a T25

Ultra Turrax (IKA, Germany) without further treatment were injected, the effluent was

circulated for another pore volume (Figure 2.10b). Afterwards the columns were flushed

with degassed tap water for three pore volumes. At the start of each experiment U ′1, U ′2,

and the frequency were measured, during the experiments U1, U2, and the frequency were

continuously measured. Next, the data was processed using the post processing algo-

rithms previously described. The nZVI suspension was injected and spread through the

whole column, after flushing with fresh water most of the nZVI particles stayed inside the

column. The resulting magnetic susceptibility curves of both sensors (Figure 2.10a) show

that the uncoated sensor increased strongly during the presence of surfactants whereas

the coated sensor shows no increased apparent susceptibility because of the surfactants

in the fluid. The uncoated shows an increased magnetic susceptibility (right y-axis) in

the column after the removal of the surfactants, which is because of the presence of nZVI

in and around the sensor. The coated sensor shows a much smaller increase in suscepti-

bility (left y-axis), but the change is still clearly visible. The larger apparent magnetic

susceptibility of the uncoated sensor after flushing with fresh water indicates that there

are still some remnants of the surfactants present.

29


2.5 Measuring Iron Break Through Curves in the Field

The next stage was the development of sensors, electronics and accompanying installa-

tion techniques to measure nZVI concentrations in an aquifer during a field application

(Figure 2.11).

The aim of the sensor is to measure a low concentration of nZVI over a relatively large

measuring range around the sensor. The sensor developed for the container experiment,

was designed such that most of the magnetic field strength was focused in the center of

the coil, because the nZVI could flow through the center of the sensor. By installing

a sensor in the subsurface it can no longer be guaranteed that nZVI will flow exactly

through the sensor and thus the sensor has to measure the change in susceptibility in the

area outside of the sensor. At the ITE a numerical simulation was performed to design

and optimize the shape and dimensions of the coils by computing the magnetic field with

the finite element method in COMSOL Multiphysics [Li et al., 2012].

Figure 2.11: Schematic overview of an in-situ application of nZVI including monitoring

30

2.5. Measuring Iron Break Through Curves in the Field

2.5.1 Sensor Design and Data Acquisition

Compared to other shapes the sharply edged so-called racetrack coil has the widest out-

wards oriented magnetic field. Moreover, there is no need to consider the orientation

of the coil, since the magnetic field penetrates a circular domain around the well when

installed such that the axial orientation is vertically aligned with the well (Figure 2.12).

The inductive sensor presented here is composed of two identical sets of two racetrack

coils. The second set of coils is connected in series to the first coil as reference. The

potential difference between a region with nZVI and without nZVI is measured instead

of an absolute value. The susceptibility of the considered domain in the aquifer, which

is related to the concentration of nZVI, is calculated according to this voltage. The

advantage of a series circuit in the primary coils is that two primary coils have the same

current and generate the same magnetic field. Both of the secondary coils are oppositely

connected so that the potential difference can be measured directly. This offers the

possibility to measure very small changes in susceptibility and thus the electronics can

be kept fairly simple. The influence of a long cable between the coils can be significant,

because the resistance and capacitance of the cable increase with the length of the cable.

However, the inductance of a long cable is small enough to be neglected (Figure 2.13).

It is important to consider the accuracy of the measuring device, so that the device

can detect the smallest change of potential difference successfully. Taking all factors into

account the dimensions of the racetrack coil were obtained by a parameter sweep.

An optimized design of the set of two racetrack coils was found to be able to measure

1 g/kg of nZVI at a measuring range of 10 cm, considering that a change in voltage of

Figure 2.12: Dual racetrack coil sensor. The primary racetrack coil generates the magneticfield and the secondary racetrack coil measures the magnetic flux density

31


12

22

3

Figure 2.13: Equivalent network of the inductive dual coil measurement system with areference sensor

10 µV can be detected by the measuring electronics.

The optimized dimensions of the primary racetrack coil are 52×10×100 mm. The

secondary coil, which fits within the primary coil, is 36×37×80 mm. The primary coil

uses a copper wire with 0.3 mm diameter and has 513 windings. The secondary coil wire

has a diameter of 0.2 mm and 4228 windings. Due to the higher amount of windings

in the secondary coil, the induced voltage due to nZVI presence is amplified. A display

version of the designed sensor with a transparent plastic casing is shown in Figure 2.16d.

The measuring range of the sensor was determined by simulating rings of 1 cm with

an inner diameter varying from 8.5 cm to 18.5 cm (Figure 2.14). The inner diameter of

the well is 7.5 cm and the induced voltage by each 1 cm ring was calculated from the

simulation results (Figure 2.15).

A suitable magnetic field to measure nZVI is generated with an input current density of

0.125 · 106 A/m2. The optimal frequency was determined to be 2 kHz. At this frequency

the skin effect in the coil can be neglected and the presence of nZVI still provides a

measurable effect in the secondary coil.

The coils were again wound on the winding machine using two special tools (Fig-

ure 2.16a). To be able to install the sensor at a field site a special casing was designed.

32


Figure 2.14: Horizontal plane cross section view of the sensor in the well and its measuringdomain with nZVI

Figure 2.15: Induced voltage of a ring-shaped volume of 1 cm width containing nZVI at aconcentration of 1 g/kg positioned at different measuring distances

33


The plastic casing was made out of two halves, each with a space removed where the two

coils could be placed in and positioned (Figure 2.16b). On both halves, half of a channel

was cut out through which, when the halves were screwed together, an epoxy resin could

be injected with a syringe. In total 45 ml of resin was needed to fill up the complete in-

terior of the casing, the air and excess resin could come out on the top through the cable

channel. The epoxy resin protects and fixates the coils inside, but is mainly meant to

coat the coils against water chemistry. On the bottom and top a male and female thread

was placed, this way the sensor could be connected to standard one inch pipes which are

commonly used to build observation wells. Several sensors could be connected together

with different lengths of pipe between them, to reach the desired distance between the

sensors and depth of installation (Figure 2.16c). The installation would preferably be

performed by using a hollow pipe direct push method (e.g. using a 3.25′′ outer diameter

Geoprobe) or a hollow auger drilling technique. The hollow pipe would then be pushed

down with a lost tip at the bottom, closing off the pipe. The sensors will have to be a

(a) Tools to wind angular coils on (b) Coils for the dual coil field sensor

(c) Field sensors connected on a one inch pipe which can be connected to thethreads on the top and bottom to provide an easy installation of the sensor at

larger depths

(d) Look-throughversion

Figure 2.16: Field sensor development

34


certain distance away from this metal tip, preferably a blind pipe of one meter would be

connected to the bottom of the deepest sensors. Once down, the sensors connected to

the pipe with all cables bound to the pipe, could be inserted. Afterwards the hollow pipe

would be removed with the tip left below and the aquifer material falls back towards the

sensors and pipe. By placing bentonite plugs or a socking filled with bentonite pellets,

cross connections and preferential flow paths along the installation could be avoided. Be-

side the sensor other measuring techniques could be installed as well together on the same

pipe, creating a multi functional observation well. These could be temperature sensors,

fluorescence sensors (glass fiber cables) and small liquid sampling ports.

2.5.2 Measuring Device

Since the detection of nZVI is needed at different wells and depths, the measurement

system is set up modular, and can thus consist of several amplifier cards. Each amplifier

card holds a sine generator with an audio power amplifier. This generates the excitation

AC voltage of approximately 14 V RMS at a frequency of 2 kHz. This voltage is sent

through both primary coils of the detection and reference system, which are intercon-

nected as described above. The current through the excitation coils is measured by a

shunt resistor with an adjacent RMS detector and 24 bit analog digital converter (ADC).

An operational amplifier is used to amplify the few µV RMS (root mean square) differ-

ence of the voltages induced in the secondary coils. The signal then is also led to an RMS

voltage amplitude detector and an ADC. In this way a small change can be measured.

Due to geometrical and electrical differences of the coils, there is a signal offset to be

expected, even without the presence of iron. The more similar the two sets of coils are,

the lower this offset will be. With the produced coils used here, this difference was around

100 mV .

The data should be collected at a central point to access all the data at once and make

remote control through a GSM modem possible. Therefore, the whole system is set up

as a master-slave system (Figure 2.17). The slaves, on request, will start measuring and

send their data to the central master. Each slave is positioned at a well and can have up

to 16 amplifier cards for sensors at 16 different depths.

2.5.3 Post-Processing Algorithms

The equivalent circuit diagram of two windings of primary coil is composed of the dis-

tributed capacitance between these windings, which is parallel to resistance and induc-

35


tance connected in series.

However, it is difficult to measure the distributed capacitance of the coil directly by

using a simple measurement. Instead, an equivalent capacitance C1 is used for the equiv-

alent circuit diagram of the coil (Figure 2.13).

The voltages and currents of the primary coil at different frequencies are measured

by the measuring device. Though it is difficult to measure the capacitance of the coil,

the impedance ZC1 of the coil, which is also related to the frequency, can be calculated

according to Ohm’s law:

ZC1 =U11

IC1

(2.18)

where ZC1 is the impedance of the coil, U11 the measured voltage at the coil, IC1 is the

measured current in the coil. From the equivalent circuit diagram of the coil (Figure 2.13),

the impedance ZC1 of the coil is:

ZC1 =R1 + j2πfL1

(1− (2πf)2)L1C1 + j2πfR1C1

(2.19)

Figure 2.17: Measuring device and the measurement system overview for application in thefield

36


where j indicates the imaginary part, R1 the resistance, L1 the inductance and C1 the

capacitance of the first reference coil.

The values of R1, L1 and C1, were determined by performing a measurement where

the frequency f was varied from 100 Hz to 3 kHz. The lower and upper bounds of

R1, L1 were estimated by a measuring device, the bounds of C1 were computed by the

simulation. The measured impedance ZC1 was imported and plotted in the curve fitting

tool of MATLAB, to fit Equation 2.19 to the measured data by varying C1.

The current in the primary coil decreases because of the increased inductance, when

nZVI is in the measuring domain of the sensor. The symbols of I ′1, I ′C1, I ′C2 and U ′12, U ′22,

U ′3 in Figure 2.13 are the currents and voltages without nZVI (χ = 0). The following

symbols of I1, IC1, IC2 and U11, U12, U22 are the currents and voltages with nZVI χ 6= 0.

The currents I1, I ′1 and the voltages U12, U ′12, U22, U ′22 can be measured by the measuring

device. The currents in the primary coils are

IC1, (I′C1) =

∣∣((1− (2πf)2L1C1) + j2πfR1C1

)−1∣∣I1, (I′1) (2.20)

IC2, (I′C2) =

∣∣((1− (2πf)2L2(C2 + Ck)) + j2πfR2(C2 + Ck))−1∣∣I1, (I

′1) (2.21)

where C1 is the capacitance and L1 the inductance and I(′)1 the current of the primary

reference coil, and Ck is the capacitance of the cable, C2 the capacitance and L2 the

inductance of the primary detection coil. Hence, if there is no nZVI around the coil, the

induced voltages U ′12 und U ′22 in each secondary coil are

U ′12, (U′22) = j2πfMmi1I

′C1, (j2πfMmi2I

′C2) (2.22)

where Mmi1 and Mmi2 are the mutual inductances of the dual coil system (reference and

detection respectively). Which can be calculated according to the induced voltage U12,22

and the current IC1,C2, which are measured in the circuit by the measuring device. If

there is nZVI around the sensor, the induced voltages U12 and U22 are

U12 = j2πfMmi1IC1 (2.23)

U22 = j2πf

(1 +

χmkexp

)Mmi2IC2 (2.24)

where kexp is the measured geometry factor as defined in Equation 2.34), and χm the

measured susceptibility. Since the two dual coil systems are connected in series, the

37


potential difference of the secondary coils from the reference and detection sensor is:

U ′3 = U ′22 − U ′12 (2.25)

U ′3 = j2πf(Mmi2I

′C2 −Mmi1I

′C1

)(2.26)

U3 = U22 − U12 (2.27)

U3 = j2πf

((1 +

χmkexp

)Mmi2I

′C2 −Mmi1I

′C1

)(2.28)

Finally, the susceptibility is obtained from

χm = kexp

∣∣U3

∣∣−∣∣U ′3∣∣2πf

−Mmi1(I ′C1 − IC1)

Mmi2IC2

+I ′C2

IC2

− 1

(2.29)

where U3(′) is the potential difference of the reference and detection sensors’ secondary

coils. The plastic casing of the sensor obstructs the nZVI from getting too close or within

the coil center. The average susceptibility measured χD thus consists of two domains,

one where nZVI can enter χm and one where it cannot (Figure 2.14). To calculate only

the susceptibility in the area around the sensor where nZVI can be present, a geometry

factor ksim has to be calculated. It is obtained through the following equations:

Φ = wMmiI1 (2.30)

Mmi = (1 + χD)cM (2.31)

χD =Φ

wI1

cM − 1 (2.32)

ksim =χmχD

(2.33)

kexp = αkksim (2.34)

where Φ is the magnetic flux in the secondary coil, w is the windings, Mmi is the mutual

inductance between two coils and cM is the constant term of it. The average susceptibility

χD in the measuring domain can be calculated according to the above equations and the

susceptibility of nZVI χm can be obtained from the simulation. Therefore, the geometry

factor ksim is 4.5. The calibration coefficient αk is determined experimentally.

38


2.5.4 Sensor Calibration

A validation of the inductive sensor between simulation and measurement was performed.

Also this experiment was used to determine the calibration coefficient αk.

A hollow cylinder box divided in quarters was filled with a mixture of sand and nZVI

(Figure 2.18). The compartments were filled each time with a different nZVI concentration

and the compartments were arranged around the sensor to fit the numerical simulation.

A sine wave generator (DG2021A, Rigol, China) was connected to the reference and

measuring coil as described in the previous section. The induced voltage in the secondary

coils and the current flowing through the primary coils was measured with a high precision

multi meter (DM3064, Rigol, China) and the shape of the AC voltage sine wave was

observed with a hand-held oscilloscope (123, Fluke, USA). Based on the measured data,

the susceptibility could then be calculated by using the post-processing algorithms. A

calibration of the numerical simulation and the post-processing algorithms was performed

based on the data and known concentration of nZVI.

The result of measurement with the hollow cylinder box showed that the concentration

of nZVI was indeed proportional to its susceptibility (Figure 2.19). The inductive sensor

can clearly measure a low concentration of nZVI of 1 g/kg over a radius of 10 cm. With

the well known concentration of nZVI the coefficient to calibrate the geometry factor ksim

was determined (αk = 0.813), thus the geometry factor kexp is 3.658. The post-processing

algorithms could be validated within acceptable limits by comparing the measured data

to the simulation results (Table 2.1). The larger error for the lowest concentration is

acceptable because the assumption that the nZVI is spread exactly homogeneously inside

the compartments is experimentally difficult to hold, which will result in a larger error

for lower concentrations.

Table 2.1: Susceptibilities measured and calculated through simulation, and the error betweenboth

Concentration Susceptibility Susceptibility Error

of nZVI [g/kg] of Simulation [−] of Measurement [−] [%]

1 0.00035 0.00026 25.7

2 0.00070 0.00065 6.5

5 0.00175 0.00190 9.9

10 0.00350 0.00349 0.3

39


Figure 2.18: Measurement of a hollow cylinder box filled with 10 g/kg nZVI, the measuresensor is placed in the center of the hollow cylinder box. In the background, a sine wave

generator and a multi meter. In the foreground a portable oscilloscope and the reference sensor

0

0.001

0.002

0.003

0.004

0.005

0 1 2 5 10

χ [−

]

Stotal [g/kg]

χ(Stotal) = 0.00045·Stotal

MeasurementsLinear fit

Figure 2.19: Susceptibility of nZVI at a concentration of 1, 2, 5 and 10 g/kg

2.5.5 Sensor Test

The second experiment was performed to verify the measuring technique under field

realistic conditions. The measuring sensor was placed inside a container filled with sand,

after which a nZVI suspension was injected into the container. During the injection, the

response of the sensor was recorded. The post processing algorithms described above were

40


Figure 2.20: Placement of sensor inside the container during sand packing. Metal plates wereused to separate the coarse filter sand from the fine sand filling and are removed after packing

was completed

used to calculate the concentration of nZVI inside the container throughout the injection.

A Plexiglas container (L×W×H: 50×40×40 cm) was filled with sand (Dorsilit #8,

0.2 − 0.8 mm, Dorfner, Germany), a coarse sand was used to make a 2 cm thick filter

screen on the inlet and outlet side of the container. After closing the container with

swelling clay and a silicon sealed lid, the container was flushed with degassed tap water.

In a reservoir the nZVI suspension (RNIP 10E, Toda Kogyo, Japan) was prepared and

dispersed at 10 g/l. The suspension was injected into the container using a constant flux

dosing pump (Seepex, Germany) such that the container was flushed at one pore volume

in 10 minutes, resulting in a seepage velocity of 8.3 · 10−4 m/s.

The measuring sensor was installed at the center inside the container while packing it

with sand (Figure 2.20). The reference sensor was placed at a location with no iron in a

vicinity of 50 cm. The coils of both the measuring and reference sensor were placed inside

a plastic mold which was filled with an epoxy resin to avoid water contact with the coils

and to stabilize the sensor.

Before the injection started a background measurement was performed. During the

injection the response of the sensor to the injected nZVI suspension was recorded every

41


Figure 2.21: Master unit with laptop connected to directly visualize the measured data

4 seconds (Figure 2.21). Parallel to the measurement of the susceptibility, the temper-

ature was recorded as well. The transport and final distribution of nZVI as resulted

from the experiment was a close resemblance of what would be expected in a real field

situation. The nZVI front was moving slower than the injection fluid. Furthermore, a

concentration gradient inside the porous media along the length of the container was

visually observed (Figure 2.22), and the nZVI distribution was not equal over the whole

height of the container. The susceptibility clearly increased during the injection of nZVI

into the container. The temperature increased before the susceptibility started to rise

(Figure 2.23). This showed that the temperature can be used to prove that the injection

fluid arrived at the sensor, it furthermore indicated the velocity difference between wa-

ter and nZVI. The susceptibility measured in this experiment is different from the one

obtained from the previous experiment, because the sensor is in direct contact with the

porous medium. Thus a new geometry factor was determined (kexp = 2.573), which will

Figure 2.22: Three photos showing the propagation of nZVI inside the small container, withthe time indicated as injected pore volumes

42

2.6. Chemical Measurement of nZVI in Soil & Suspension

0

0.5

1

1.5

2

0 0.2 0.4 0.6 0.8 1

20

22

24

26

28

30

32S

tota

l [g/

kg]

Tem

pera

ture

[°C

]

Duration [PV]

StotalTemperature

Figure 2.23: Concentration and temperatue during the injection

be the same for a field application. The calibration factor (αk = 0.813) obtained from

the calibration experiment was used to simulate the new situation. The average concen-

tration at a radius of 10 cm around the sensor inside the container was then derived from

the simulation (Figure 2.23).

2.6 Chemical Measurement of nZVI in Soil & Suspension

An important factor in the characterization of nZVI is the percentage of zero valent iron

present in the colloids. The nZVI colloids used in this research consist of a zero valent iron

core and a shell of iron oxides (Magnetite, Fe3O4) [Nurmi et al., 2005]. The percentage

of zero valent iron in a particle furthermore determines the reactivity of the particle [Liu

and Lowry, 2006]. According to Equation 1.2 the core of zero valent iron corrodes when

the colloids get in contact with water and thus the core becomes smaller and the shell

thicker. Because the colloids even corrode during storage the exact amount of zero valent

iron in a suspension is changing over time. The exact amount of zero valent iron available

in a suspension is important when determining the amount of base suspension necessary

for an application.

A simple and robust gas volumetric based method has been used to develop a set up

to measure the zero valent iron content of stored nZVI samples. The setup furthermore

43


was developed such that soil samples could be analyzed as well. The latter was mainly

applied on samples taken from the large scale container experiments.

2.6.1 Materials & Methods

The nZVI testing material was RNIP-10E (Toda Kogyo, Japan) which is a commercially

available nZVI suspension. In a glass vial 4 ml nZVI suspension was injected with a

pipette and deep-fried immediately. The vial was weighted (BP 210 S, Satorius, Germany,

accuracy 0.1 mg) before and after adding the suspension. Afterwards the vials were dried

by sublimation in an Alpha 1-2 (Christ, Germany). Afterwards the vacuum chamber was

aerated with technical argon gas (Westfalen, Germany) and a 3 mm septum (Pharma

Fix Septum) with an aluminum cap was placed on the vial. The septum and cap were

weighted before and the freeze dried sample in the vial with cap was weighted as a total.

The air pressure and temperature was measured with a digital barometer (GTD 1100,

Greisinger, Germany, accuracy: pressure ± 1.5 mbar, temperature ± 1%). Based on

the method described by Elion and Elion [1933], the gas volumetric setup was build.

The functional scheme is given in Figure 2.24a and Figure 2.24b shows the final set up.

The vial was placed in the setup and 3 ml of 32% (10 molar) HCl (Merck, Germany)

solution was added to the vial through a Sterican (B-Braun, Germany) needle with a

10 ml plastic syringe (VWR, Germany). To avoid foam from building up due to the

presence of surfactant in RNIP-10E, which would enter the tubing of the setup or clog

the needle, 90 µl of anti-foaming agent (Drewplus L-674, Ashland, USA) was added with

a 100 µl glass syringe (Hamilton, Switzerland).

From the volume of water displaced by the hydrogen gas the total moles of zero valent

iron can be calculated. The displaced water volume is assumed to be equal to the produced

H2 gas volume [Elion and Elion, 1933].

Fe0 + 2H+ → Fe2+ +H2 (2.35)

Equation 2.35 shows the production of H2 due to the reaction with an acid, it shows

that the total number of H2 molecules produced is equal the number of Fe0 molecules

consumed. By using the ideal gas law, the amount of H2 molecules can be calculated

from the displaced volume:

nH2 =P · VR · T (2.36)

44

2.6. Chemical Measurement of nZVI in Soil & Suspension

(a) Schematic overview of gas volumetricmeasuring set up, after Elion and Elion

[1933]. A is the main water reservoirconnected through G to B, which is open

to the air. C is the water outflowreservoir, pressure between C and A isbuild up due to hydrogen gas produced

at E. After the reaction valve D isopened and the water is collected in F

(b) Photograph of the hydrogen measurement setup. A, B, C, D, F and G are as described in (a), Eis a three way valve to switch between E1 and E2,where E1 is the sample vial and E2 is a 1 l bottlefor large samples or soil samples. Central on the

board a barometric pressure and temperaturemeasuring device is positioned

Figure 2.24: Measuring set up to chemically determine the amount of zero valent iron inside asample

where nH2 is the amount of molecules, P the pressure, V the displaced volume, R the gas

constant (8.312 Jmol−1K−1) and T the temperature. Since the amount of H2 molecules

is equal to the amount of Fe0 molecules, the mass of elementary iron (mFe0) in the sample

is given by:

mFe0 = MFe · nH2 (2.37)

where MFe is here the molecular weight of iron (55.845 g/mol). From the mass of elemen-

tary iron in the dried suspension the weight ratio of nZVI to total iron was calculated.

From this ratio the real concentration of zero valent iron in the suspension can be deter-

mined.

The zero valent iron content in a soil sample is determined slightly different. The soil

45


sample is filled into a 1 l glass bottle (Duran, Germany), which is weighted before and

after filling. To prevent oxidation of Fe0 to air, the head space is flushed with Argon

gas. This allows the sample to be stored for a short period. The bottle is placed in the

measuring set up (location E2 in Figure 2.24b), through the three-way valve above the

bottle acid (HCl, 32 %) is added with a syringe and a stainless steel needle. The three-

way valve is turned such that the bottle is open towards E, and the bottle is shaken by

hand to get a good mixing of the acid and the soil sample. If the content in the bottle are

still black from the iron, new acid is added. This is repeated until the water level in A no

longer moves down. The produced gas volume is again used to calculate the content of

Fe0 in the sample using Equations 2.35-2.37. When the Fe0 content of the colloids of the

injected suspension was determined prior to the injection, the determined concentration

of Fe0 in the soil sample can also be converted into a Fetotal concentration

46

3 Fundamentals of Transport of Nano

Sized Zero Valent Iron Colloids

3.1 Motivation

The main goal of this work is to get a better understanding and description of the trans-

port of nZVI colloids during the injection into the subsurface. This chapter presents a

conceptual transport model based on ideas obtained from the filtration theory and the

characterization of the nZVI suspension. Furthermore a method is presented to obtain

quantitative measures of transport from column experiments by combining transient con-

centration profiles, transport equations, an adapted application of the classical filtration

theory and numerical modeling. Constitutive relations were sought by looking at the

filtration theory, transient concentration profiles of the column experiments and fitting

parameters for a numerical model of these experiments.

3.2 Colloid Transport & Filtration in Porous Media

In a porous medium, transport of particles is limited due to filtration effects. Filtration

causes particles to be removed from the liquid phase.

In this section the filtration theory as described by Tufenkji and Elimelech [2004] is

presented. It is based upon Happel’s sphere-in-cell model [Happel, 1958] to describe the

fluid flow in a porous media and Prieve & Ruckenstein’s theory [Prieve and Ruckenstein,

1974] which concludes that all individual contributions from transport mechanisms can

be summed to calculate the total deposition rate. Many scientist have used this filtration

theory (e.g. [Long and Hilpert, 2009; Schrick et al., 2004; Wang et al., 2008; Zhan et al.,

2008]).

47

3. Fundamentals of Transport of Nano Sized Zero Valent Iron Colloids

3.2.1 Colloid Filtration Theory

The filtration theory describes the retention of particles through a single-collector ef-

ficiency coefficient. This is the rate of particle deposition onto the collector divided by

the convective transport of particles towards the collector. The collector is assumed to

be a spherical sand grain as is the approaching colloid or particle.

The filtration is described by looking at a single spherical grain (collector) and a single

colloid (particle) in a porous medium and describing all the interactions between the

collector and the particle in detail. There are several models available for the description

of flow around packed spherical collectors (e.g. [Brinkman, 1947; Happel, 1958]). Happel’s

sphere-in-cell model is used to describe the flow around the collector in the single-collector

contact efficiency correlation equation derived by Tufenkji and Elimelech [2004]. Based on

the work of Prieve and Ruckenstein [1974], the correlation equation assumes that particle

deposition rates can be calculated by a summation of the individual contributions from

each transport mechanism to this deposition. The transport contributions accounted

for are: ηD, Brownian diffusion which is the filtration of particles not moving along

regular flow lines but move by Brownian motion; ηI , the contribution due to interception

which occurs when particles move along the sand grain so nearby that they get attracted

(mainly Van der Waals forces) and ηG, the removal of particles due to gravitational effects

(Figure 3.1, Equation 3.1).

η0 = ηD + ηI + ηG (3.1)

Figure 3.1: Basic transport mechanisms of particle filtration, after Yao et al. [1971]

48

3.2. Colloid Transport & Filtration in Porous Media

With As being the porosity-dependent parameter from Happel’s flow model [Happel,

1958], and by means of the dimensionless parameters for the aspect ratio NR, the Peclet

number Pe, the Van der Waals number NV dW , the attraction number NA, and the gravi-

tational number NG, the combined contribution can be rewritten as one equation to define

the single collector efficiency η0:

η0 = 2.4A13sN

−0.081R N−0.715

Pe N0.052V dW + 0.55AsN

1.675R N0.125

A (3.2)

+0.22N−0.24R N1.11

G N0.053V dW

with:

As =2(1− γ5)

2− 3γ + 3γ5 − 2γ6with: γ = (1− n)

13

NR =dpdc

NA =A

3πµd2pv

NG =d2p(ρp − ρf )g

18µv

NV dW =AkT

NPe =vdcDinf

with: Dinf =kT

3πµdp

where dp is the particle diameter, dc the collector (grain) diameter, Dinf the diffusion

in an infinite medium, A is the Hamaker constant, k is the Boltzmann constant, T is

the absolute temperature of the fluid, µ is the absolute viscosity of the fluid, g is the

gravitational constant, ρp is the particle density, and ρf is the fluid density.

3.2.2 Attachment Efficiency

The filtration theory predicts with η0 the attachment of the colloids on the sand grain sur-

face at ideal conditions. The theory does not take the real concentration of the suspension

or soil chemistry into account.

In most natural systems the contact efficiency calculated in Equation 3.2 will provide

an overestimation because of repulsive colloidal interactions between particles but also

between particles and the collector. These can be influenced by ionic strengths, surfac-

tants and surface charge, where equally signed charges will repel each other. Therefore

an empirical attachment efficiency factor α was added:

η = αη0 (3.3)

The attachment efficiency factor (α) can be determined in laboratory column experi-

49


ments from the transport distance of particles into the porous medium or the concentra-

tion of particles in suspension at a specific distance [Tufenkji and Elimelech, 2004]. This

follows from the assumption that the particle concentration decreases exponentially with

the filter depth in a 1-D flow field [Iwasaki, 1937; Tien, 1989]:

Ceffluent = Cinpute− katt

vL (3.4)

katt =3(1− n)αη0v

2dc(3.5)

α = − 2dc3(1− n)η0L

ln

(CeffluentCinput

)(3.6)

where Ceffluent is the effluent concentration [ML−3], Cinput the inflow concentration

[ML−3], katt the attachment coefficient (also denoted as particle deposition rate coeffi-

cient) [−] and L is the characteristic filtration length [L]. In column experiments, L is

the length of the column, α can be determined fastest by looking at the effluent concen-

tration, the break through curve will show a constant but lower effluent concentration

than the input concentration with time (e.g. after 2 PV [Tufenkji and Elimelech, 2005a]).

With the calculated η0, the collector diameter dc and the porosity n, the attachment

efficiency can be determined.

3.2.3 Sensitivity of Colloid Filtration Theory Parameters

To determine which are affecting the filtration at most and in which way, a parame-

ter sensitivity analysis on different boundary conditions was performed. The constants

presented in Table 3.1 were used to perform the sensitivity analysis.

The parameters were varied over a range of field realistic values (Table 3.2). The base

case value of a parameter was used as constants when another parameter was changed.

The base case values were related to the conditions used in the column experiments and

large scale container experiments. For each of these parameters the contact efficiency

Table 3.1: Constants for the sensitivity analysis [after Schrick et al., 2004].

Constant Abr. Value Unit

Liquid Density ρf 1.010 kg · l−1

Hamaker Constant A 1 · 10−20 J = kg ·m2 · s−2

Boltzmann Constant k 1.3805 · 10−23 J ·K−1 = kg ·m2 · s−2 ·K−1

Gravitational Acceleration g 9.81 m · s−2

Porosity n 0.34 −

50


Table 3.2: Base case values and ranges of varied parameters for the sensitivity analysis

Varied Parameter Abr. Base Case Min Max Unit

Particle Diameter dp 0.070 0.001 1000 µm

Collector Diameter dc 476 1 1 · 105 µm

Particle Densisty ρp 6.7 1 10 kg · l−1

Viscosity µ 1.003 1 10 10−3kg ·m−1 · s−1

Seepage Velocity v 1.618 0.003 10 10−3m · s−1

Attachment Factor α 1.0 0.0001 1 −

Temperature T 288 275 315 K

(equations 3.2 & 3.3) was calculated using Scilab (INRIA, France).

Low contact efficiencies indicate a low tendency to retain particles in the porous

medium. Contact efficiencies were calculated as a function of various parameters by

changing one boundary condition at a time (Figures 3.2a - 3.2g). The plots all show

the same range for the contact efficiency for a better comparison of the influence of each

of the parameters on the total contact efficiency. The base case contact efficiency was

calculated to be η = 4.409 · 10−3 and has been plotted in each figure.

dp From the change in contact efficiency by varying the independent parameters it be-

comes clear that the particle diameter has a strong non-linear effect on the filtration

(Figure 3.2c). Especially the increased filtration for smaller particles is an interesting

effect. The minimum contact efficiency for the particle diameter indicates that for each

set of boundary conditions there is an ideal particle size to be expected.

ρp The particle density of nano sized colloids shows to have an insignificant effect on the

contact efficiency (Figure 3.2f).

α Changing α has the expected linear effect. Since α operates directly on the contact

efficiency, the contact efficiency is maximum for α = 1 and zero for α = 0. In some

studies α was found to be larger than one. This could be due to extra attracting forces

like an extra strong opposing surface charge [Lecoanet et al., 2004].

dc The collector size has a non linear effect on the contact efficiency, though the general

trend is the reduction of the contact efficiency with increasing grain sizes.

µ An increased viscosity reduces the contact efficiency. It is intuitive that the chance

that the particle will deviate from the flow path is hemmed due to the increased viscosity.

v The seepage velovity has a non-linear semi-hyperbolical relation to contact efficiency.

For the presented calculation, the relation η0(v) = 8.4 ·10−5 +4.2 ·10−5/v0.72 gives a near

perfect fit. Especially very low seepage velocities result in a high contact efficiency while

increasing higher seepage velocities results in minimal changes of the contact efficiency.

51


0.001

0.01

0.1

1

0.01 0.1 1

Con

tact

Effi

cien

cy η

[−]

Attachment Efficiency α [−]

η

base case

(a)

0.001

0.01

0.1

1

1e−07 1e−06 1e−05 0.0001 0.001 0.01 0.1

Con

tact

Effi

cien

cy η

[−]

Collector Size dc [m]

η

base case

(b)

0.001

0.01

0.1

1

1e−09 1e−08 1e−07 1e−06 1e−05 0.0001 0.001

Con

tact

Effi

cien

cy η

[−]

Particle Size dp [m]

η

base case

(c)

0.001

0.01

0.1

1

0.001 0.01

Con

tact

Effi

cien

cy η

[−]

Viscosity µ [kg/m.s]

η base case

(d)

Figure 3.2: Contact efficiencies as a function of parameters α, dc, dp and µ calculated bychanging one boundary condition at a time (Tables 3.1 & 3.2). The base case solution of

η = 4.409 · 10−3 is shown in each graph. Continues on next page. . .

T Temperature differences are expected to be small, between 10 and 40 C, the contact

efficiency shows no significant change.

↓ vs. → The presented colloid filtration theory was derived for deep bed filtration,

where the general velocity component is vertical and points in the same direction as the

gravitation. It has been assumed that this is transferable to horizontal flow in porous

media as well. In which case, the gravitation component stands perpendicular to the

flow component and in a one-dimensional system thus has no influence on the particle.

The sensitivity of the gravitation component in the semi-analytical solution was looked

into by comparing the variation of particle sizes with and without the gravity acting on

the particles.

The gravity number NG was found to have a negligible influence on the contact efficiency

52


0.001

0.01

0.1

1

0.0001 0.001 0.01

Con

tact

Effi

cien

cy η

[−]

Seepage Velocity v [m/s]

η

base case

(e)

0.001

0.01

0.1

1

1000 2000 3000 4000 7000 10000

Con

tact

Effi

cien

cy η

[−]

Particle Density ρ [kg/m3]

η

base case

(f)

0.001

0.01

0.1

1

275 285 295 305 315

Con

tact

Effi

cien

cy η

[−]

Temperature T [K]

η

base case

(g)

0.001

0.01

0.1

1

1e−09 1e−08 1e−07 1e−06 1e−05 0.0001 0.001

Con

tact

Effi

cien

cy η

[−]

Particle Size dp [m]

η

base caseη, NG=0

base case, NG=0

(h)

Figure 3.2: Continued. . . Contact efficiencies as a function of parameters v, ρp and Tcalculated by changing one boundary condition at a time (Tables 3.1 & 3.2). 3.2h shows the

contact efficiency with and without gravity. The base case solution of η = 4.409 · 10−3 is shownin each graph

number for colloids smaller than 0.5 µm (Figure 3.2h).

The nano sized colloids used for this study are thus not expected to be influenced by

gravity. Attachment of nano sized colloids thus mainly takes place due to interception,

Van der Waals forces and Brownian diffusion.

The sensitivity analysis on the contact efficiency can be a useful tool to investigate the

effect of a certain parameter on the filtration of particles during the injection into a porous

medium.

The sensitivity analysis can furthermore be useful to investigate an ideal (though sim-

plified) scenario for injection. This can be used when approached from different point-

53


of-views. (I) One approach would be to find out which particle size would be most

suitable for a given aquifer. This is a valuable tool that can be taken into account

while designing a field application. (II) To indicate the range of porous media types

or injection conditions that are most suitable for a given particle. This for example is

useful when the chemical behavior of a certain given particle is preferred but it is not

possible to change the size of that particle.

To be able to predict the transport distance of particles during an injection in the

field a non-linear numerical transport model should be used to be able to account for the

suspension concentration and non-constant seepage velocity around the injection well.

3.3 Characteristics of the nZVI Suspension

Classic filtration theories and most classic research on colloid transport focuses on other

colloids than nZVI. Bacteriophages [Schijven et al., 2002], viruses [Schijven and Has-

sanizadeh, 2002], latex particles [Tosco et al., 2009] and many more have all been reason-

ably described using the classic filtration theory by approaching them as single colloids in

suspension. Furthermore, most descriptions focus on suspensions with very low particle

concentrations. The colloids used here are very dense (approximately seven times the

density of water), are ferromagnetic and are applied in very high concentrations. During

preliminary research [de Boer, 2007], it was also found that a freshly received suspension

behaves different from an older one, which can be approached as an aging effect. There-

fore, it was necessary to focus also on characterizing the colloidal suspension itself when

looking for a good description of the transport behavior. This helps to understand the

behavior of the colloids in suspension, and could lead to verification or extension of the

available theories to account for the behavior observed.

3.3.1 nZVI Suspension

For this research the nano sized zero valent iron colloids (nZVI, RNIP 10E) were obtained

from Toda Kogyo Corp., Japan. It was delivered as slurry with a concentration of 214 g/l.

The colloids contained according to the data sheet 60% zero valent iron (Fe0) and 40%

Magnetite (Fe3O4). For the experiments the slurry was diluted with degassed tap water

(dissolved O2 . 1 mg/l, Total Organic Carbon: 0.4 g/l, pH: 8.0, Electrical Conductivity:

∼ 8.9 S/m) to the desired suspension concentration. To break up aggregated colloids after

the suspension was taken from storage, a disperser with a flow through chamber (UTL25

54

3.3. Characteristics of the nZVI Suspension

Ultra Turrax with S25-IL, IKA, Germany) was used.

3.3.2 Aging of nZVI During Storage

The aging aspect (longevity) due to anaerobic corrosion (Equation 1.2) is a strong criterion

for the feasibility of using nZVI for In-Situ remediation. Furthermore, it impacts the

conversion factor to convert the measured susceptibility into a concentration of the total

iron, because the zero valent iron content is responsible for the high susceptibility of the

suspension.

Measurements were performed monthly over a period of five years to get real long term

data sets. The aging was determined by measuring the zero valent iron weight percentage

of the total-iron mass in the sample (Section 2.6.1). Since these measurements started,

similar work has been published (e.g. Liu and Lowry [2006]).

For the presented measurements three different lots were used (Figure 3.3), each lot was

produced in a different year, 2006, 2007 and 2008. The first measurement was performed

in 2008 for all three charges.

The iron was stored in a fridge at 8 C, was not in contact with any other reactants

beside water and this water was not refreshed during the period of observation. After each

sampling the containers were aerated with nitrogen gas to remove all oxygen in the gas

atmosphere. The following exponential equation was fitted to the measurement results:

CFe0(t) = CFe0(0) · e−kaging ·t (3.7)

where CFe0 is the Fe0 weight percentage of the total Fe mass, kaging the aging coefficient

and t the days of storage. Table 3.3 shows fitted the constants of Equation 3.7 for the three

lots and the three combined, assuming that initial Fe0 weight percentage was variable

instead of the 65% presented on the data sheets of the lots.

Based on these equations the content of zero valent iron inside the colloids could be de-

termined for all the experiments when the total iron was determined using a photometer.

Table 3.3: Aging coefficient and initial concentration of the different RNIP lots. According toEquation 3.7

Production Year CFe0 (0) [w%] kaging

2006 77.1 1.08 · 10−3

2007 59.3 1.21 · 10−3

2008 56.9 9.42 · 10−4

Combined 55.6 9.40 · 10−4

55


0

10

20

30

40

50

60

70

80

0 500 1000 1500 2000

Fe0 C

onte

nt o

f Col

loid

s [w

%]

Days of Storage

RNIP−10E 2006 (storage at pH 12.2)RNIP−10E 2007 (storage at pH 12.2)RNIP−10E 2008 (storage at pH 12.2)

fitted curve on all data2006 fitted curve2007 fitted curve2008 fitted curve

Figure 3.3: Fe0 weight percentage in the stored samples, starting concentration fitted

By using this equation, it was also possible to determine the total mass of iron based on

the hydrogen production in soil samples, as described in 2.6.1.

Although the reduction exponent kaging is approximately the same for all three lots,

the charges all show an offset. The following arguments for the discrepancy could be

reasoned, the first being most likely, the last less: (I) The lots are differently reactive.

Particle size, surface area, amount of surfactants in the suspension or a Monday morn-

ing production could be some of the reasons. (II) The lots were delivered in different

packaging. The 2006 lot is packed from the factory in a small PP-bottle (0.5 l) and the

2007 lot in a large one (1.5 l), whereas the 2008 lot was delivered in a PP-bag (10 l).

The bag might let more oxygen through, oxygen diffusion could cause aerobic corrosion

additionally to the anaerobic corrosion. Inside the bottle also a higher pressure built up

due to hydrogen production can occur, which could cause the pH of the 2006 lot to be

slightly higher, reducing the corrosion rate. (III) The nitrogen flushing before closing

the bottle and bag could be more effective in removing the air from the bottle. (IV) The

initial Fe0 of the lots were different. There are no measurements or exact data available

of the initial state before shipping except for the information on the data sheet. (V) The

production date provided in the data sheet was erroneous.

56


3.3.3 Aging of nZVI after Dilution

Diluted suspensions quickly (< 24h) turn into a dark brown suspension (Figure 3.4),

indicating rapid oxidation and high iron concentrations in solution. Even in degassed

water the oxygen level is still higher than in the storage water. Degassed tap water

furthermore has a neutral pH of approximately 7, whereas the storage water is around

pH12, causing a significant increase in the oxidation rate.

Figure 3.4: Oxidation effect on nZVI suspensions after dilution. Left: fresh suspension, clear,Right: older suspension with dark oxidized water color. Both vials were closed and left

untouched to let all nZVI settle out of suspension

3.3.4 Size of nZVI in Suspension using Stokes’ Law

During preliminary transport experiments, it was shown that older suspensions clogged

the pores quicker and there appeared to be more and larger aggregates in the suspension.

It was also found out that by applying mechanically high shear forces with a dispersing

unit the older suspension behaved from a transport point of view again very similar to

a very fresh sample [de Boer, 2007]. Similar results were presented by Phenrat et al.

[2007], though, they used ultrasonification instead. The size of the particles (or aggre-

gates) in suspension before and after dispersion was determined through a sedimentation

experiment.

57


In order to determine the particle size, first the sedimentation rate was determined

using a hydrometer (VWR NFB 35511, BS 718, ISO 649), according to the method of

[Dunford and Lorentz, 1994, Ch. 3.3]. From Stokes’ law, the settling velocity (or terminal

velocity) for a specific particle size can be calculated (Equation 3.8) or the particle size

can be derived for a given settling velocity (Equation 3.9). Stokes derived an expression

for the frictional force exerted on spherical objects with very small Reynolds numbers

(e.g. nano or micro sized particles) in a continuous viscous fluid. Stokes’ law assumes

that: (I) The terminal velocity is attained as soon as settling begins, (II) settling

and resistance are entirely due to viscosity of the fluid, (III) particles are smooth and

spherical and (IV) there is no interaction between individual particles in the solution

[Cengel and Cimbala, 2006; Dunford and Lorentz, 1994].

vp =g(ρp − ρf )

18µd2p (3.8)

dp =

√18µvp

g(ρp − ρf )(3.9)

where vp is the particle settling velocity, g is the gravitational acceleration, ρp the density

of the particle, ρf is the density of the fluid, dp the diameter of the particle and µ the

fluid viscosity. From Equation 3.8 it follows that for a nZVI colloid of 70 nm and using

g = 9.81 m/s2, ρp = 6700 kg/m3, ρf = 1010 kg/m3 and µ = 1.003 · 10−3 kg/m · s,the settling velocity is: vp = 1.51 · 10−8 m/s.

The glass vessel used for the sedimentation test was 0.5 l with a diameter of 50 mm

and a height of 250 mm. During the experiment at different stages of the sedimentation,

the density was measured. The sedimentation curve was constructed by plotting the

normalized concentration against time.

Both a dispersed suspension and a non-treated only stirred suspension of 40 g/l were

tested.

The concentration of the stirred suspension decreased very rapid (Figure 3.5a). Within

20 minutes almost all the nZVI was settled out. The dispersed suspension took 2 hours

to reach its minimum value. Comparable sedimentation curves were also presented by

Saleh et al. [2006].

To determine the observed settling velocity, the height of the glass vessel (250 mm)

was divided by the time it took the normalized concentration to go from 1 to 0 (Fig-

ure 3.5a). The observed settling velocity for the only stirred suspension was approximately

58


0

0.2

0.4

0.6

0.8

1

0 0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5

C/C

0 [-]

Time [h]

Stirred: f(x) = -3.3 x + 1Dispersed: g(x) = -0.49 x + 1

Stirred: vp = 2.32e-04 m/sDispersed: vp = 3.39e-05 m/s

Stirred: dp = 8.7 µmDispersed: dp = 3.3 µm

Stirred: ∆t = 0.2994 hDispersed: ∆t = 2.05 h

Stirred nZVIDispersed nZVI

Stirred fitDispersed fit

(a)

0

0.2

0.4

0.6

0.8

1

0 2 4 6

C/C

0 [-]

Time [h]

I: f(x) = -0.0092 x + 1II: g(x) = -0.86 x + 1.3

III: h(x) = -0.26 x + 0.61I: vp = 6.42e-07 m/s

II: vp = 5.96e-05 m/sIII: vp = 1.78e-05 m/s

I: ∆t = 108.2 hII: ∆t = 1.165 h

III: ∆t = 3.901 h

I: dp = 0.46 µmII: dp = 4.4 µmIII: dp = 2.4 µm

Dispersed nZVIIII

III

(b)

Figure 3.5: Concentration change due to sedimentation of nZVI. Both suspensions had aninitial concentration of 40 g/l

vstirredobs = 2.32 · 10−4 m/s and for the dispersed suspension vdispobs = 3.39 · 10−5 m/s.

These observed fall velocities are not even close to the calculated one. The assumption

that the colloids fall as single colloids has thus to be declined. With the assumption

that the colloids attach to each other while in suspension and colloid-colloid interaction

thus results in the formation of aggregates [Phenrat et al., 2007], an approximation

of the aggregate size can be made based on the observed fall velocity.

The determined velocities were used as the settling velocity in Stokes’ Law, to es-

timate the diameter of the aggregates (Equation 3.9). For the non-dispersed suspen-

sion this is: dstirredp = 8.7 · 10−6 m = 8.7 µm, and for the dispersed suspension:

ddispp = 3.3 · 10−6 m = 3.3 µm. This would mean that mean diameter of the aggre-

gates is approximately 50− 100 times the diameter of the primary colloids.

The above calculated diameters were based on the average sedimentation time. The

sedimentation curve of the dispersed suspension though shows three phases (Fig-

ure 3.5a) of sedimentation. (I) The first half hour shows almost no change in the

concentration, (II) then a rapid change occurs for about 40 minutes, (III) followed by

a slower change.

It can be reasoned that the differences are caused by aggregation effects and this aggre-

59


gation is not instantaneous. (I) In the first stage there are mainly single colloids or

very small aggregates which are very stable, (II) in the second phase large aggregates

form and settle out quickly and (III) in the last phase there are only intermediate sized

aggregates and single colloids left, or as proposed and observed by Phenrat et al. [2007],

interconnected aggregates have formed networks (gelation) which results in a network

fluid which can hold its shape under motionless conditions [Witten and Pincus, 2004].

Since the observed third phase here is not completely stable and still sedimentation oc-

curs, it could be assumed that either there are still single aggregates present which settle

out or that the minimal vibrations in the room were enough to induce motion.

On the sedimentation curve of the dispersed suspension three different lines were fitted

to the three phases (Figure 3.5b). The time it took the normalized concentration to go

from 1 to 0 was determined by assuming that the fitted line was valid for a suspension of

equally sized particles without aging effect. The lines were then extrapolated to C/C0 = 1

and the ∆t between this intersection and the intersection with C/C0 = 0 was calculated.

Next the height of the vessel 250 mm was divided by the calculated ∆t to determine the

fall velocity and subsequent the aggregate (or colloid) diameter.

Under the assumption that each phase represents a different aggregation stage with

differently sized aggregates, the estimated average colloid and aggregate sizes of each

phase are: dIp = 0.46 µm, dIIp = 4.4 µm and dIIIp = 2.4 µm. The assumption that

in the first half hour after dispersion the aggregates are fully disintegrated into single

colloids does not hold by this determination. The hydrometer reading though is not

extremely accurate and the first 20 minutes no hydrometer change was observed, which

would result in a fully horizontal tangent, and thus in zero-sized colloids. Therefore,

the first reading with a difference was included for the fitting of the first tangent. The

assumption that dispersion breaks up the aggregates into single particles might still hold,

though the aggregation is quick and the single particles are present only shortly. An

aggregate diameter of 460 nm still is a very small colloid and could stay in suspension

with the absence of further aggregation, as calculated for over 100 hours. The diameters

of the second and third phase do not differ that much, though already show a distinctly

different sedimentation velocity.

3.3.5 Size of nZVI in Suspension using a Laser Detector

From the data sheet as well as from some publications an average diameter of the primary

colloids was determined at 70 nm [e.g. Nurmi et al., 2005].

60

3.4. Conceptual Model for Transport of nZVI

0

0.1

0.2

0.3

0.4

0.5

0.6

0 50 100 150 200 250

Par

ticle

siz

e co

unt [

%]

Particle size [nm]

topupper middlelower middle

bottom

Figure 3.6: RNIP 10-E nano particles measured with the Mastersizer 2000 (measured 3.5 yearsafter production)

The method after Stokes law showed to be fairly unsuitable to determine the size of the

primary particles of the nZVI suspension because the primary particles aggregate quickly

after the measurement started and a high concentration of these primary particles are

needed for the test. Therefore the suspension was analyzed through Mie scattering of a

Helium neon laser (Mastersizer 2000 with Hydro G, Malvern, United Kingdom).

A diluted suspension of 40 g/l of nZVI was prepared and dispersed. After preparation

it was set to rest in a 40 cm high 1 l vessel to let all aggregates settle out of suspension.

After three hours the (visually clear) suspension above the settled out nZVI was sampled

by taking samples of 160 ml at a time. The particle size counts in percents are given

for four different levels in Figure 3.6 for the nano range. The measurement showed that

nano sized particles are still in suspension, even though the concentration of stable nano

particles is very low. Most iron settled out of suspension. The sample taken from the

bottom shows no nano sized particles, indicating that all settled iron must have been in

aggregated form or at least has aggregated once it settled out.

3.4 Conceptual Model for Transport of nZVI

Based on the characterization of the suspension and the colloid filtration theory a con-

ceptual model for the transport of nZVI in porous media could be constructed.

From the aging effects, it can be concluded that the suspension of nZVI does not

behave as a typical colloid suspension for which classical deep bed filtration theories were

derived, nor can Stokes’ law be easily applied to determine particle sizes. Aggregation

61


of nZVI colloids due to magnetic attraction is expected to be the main cause for the

discrepancy. Collisions between colloids result in clustering and continuously increasing

size of aggregates. Therefore, the suspension is under continuous change and particles of

different sizes are present within the suspension.

The dispersed suspension clearly showed to contain a mixture of nano sized colloids

and micro sized aggregates, both behave quite differently according to the filtration

theory, this has to be regarded to get a good description of the transport behavior.

Roughly the suspension can be accounted to consist of particles of two different sizes,

nano sized colloids and micro sized aggregates. According to the filtration theory, nano

sized colloids are not influenced by gravity and are mainly filtered out of suspension due

to interception, Van der Waals forces and Brownian diffusion. Micro sized aggregates

on the other had are under the influence of gravity, which causes them to sediment and

due to their size can result in straining at narrow pore throats.

The proposed conceptual model assumes that the suspension consists of particles of two

different sizes which can be determined from the sedimentation tests for the aggregates

and particle size detector for the nano sized colloids. The aging effect causing increasing

aggregate sizes with time is not taken into account because the injection duration is fairly

short and in contrast to the undisturbed sedimentation experiments the suspension before

the injection is kept mechanically in continuous disturbance and during the flow in the

porous media is in movement as well.

The removal of nZVI from the suspension and the deposition onto the porous medium

affects both the colloidal and aggregated form of nZVI. The concept assumes that the

removal of the colloids is fully described by the filtration theory and can only take

place for as long there is enough available space on the grain surfaces. The removal

of aggregates is mainly a sedimentation process which can also be described by the

filtration theory. Removal of aggregates is not limited by the available surface area

because the removal from the suspension is almost purely due to gravitation and the

aggregates will mainly occupy low velocity corners in the porous media and the bottom

of pores. A maximum removal of aggregates would be the available pore space, this

though is not taken into account because of the short injection durations.

The removed aggregates are assumed to have no influence on the maximum at-

tached colloids on the surface of the sand grains. The nano sized colloids are expected

to reach the grain surface before the aggregates do and the aggregates mainly occupy dif-

ferent portions of the pore space. Furthermore, for relatively short injection durations,

the removal is assumed to have no influence on the porosity of the porous medium

62

3.4. Conceptual Model for Transport of nZVI

1 cm

meso scale

macro scale

1 m

micro scale

100 µm

Figure 3.7: Conceptual model for the transport and retention of nZVI during the injection

63


and the associated seepage velocity.

The conceptual model is graphically depicted in Figure 3.7, the model can be summa-

rized following:⊙Two sizes of particles: nano colloids, micro aggregates⊙Grain surface attachment of nano colloids, with a maximum due to availability of

surface area⊙Sedimentation and straining of micro aggregates, no maximum amount of ag-

gregates retained in porous media⊙The filtration theory of Tufenkji and Elimelech [2004] can describe the removal of

both the colloids and aggregates if regarded separately

3.5 Mathematical Model for Transport of nZVI

In the search for a good description of the transport of nZVI in porous media a robust

mathematical description of the transport is preferred. A robust mathematical description

in 1-D can easily be verified and fitted to column data and could provide the basis for

the prediction of nZVI transport in more dimensions and larger scales.

The presented mathematical model here describes the removal of nZVI from the sus-

pension in colloidal and aggregated form and its deposition onto the porous medium. The

approach assumes that the concentration of removed aggregates is a continuous addition

to the total concentration of nZVI removed from the suspension. The removed aggregates

are assumed to have no influence on the maximum attached colloids on the surface of the

sand grains. Therefore, the removed aggregates are added to the maximum attachable

colloid concentration, and thus, there is no maximum of nZVI in the porous media. This

limits the applicability of the model to relatively short injection durations (or respectively

small removal rates) since a prolonged injection (or high removal rate) would induce so

much solid phase to the system that the alteration of the porous medium would no longer

be negligible.

3.5.1 Groundwater Flow and Transport

The conservative transport of mass in a porous medium can be described by the governing

equation of mass transport combined with a continuity equation including hydrodynamic

64

3.5. Mathematical Model for Transport of nZVI

dispersion and advection:

n∂C

∂t+ C∇ · q + q∇C −∇ · (nD∇C) = 0 (3.10)

where C is the concentration of nZVI in suspension [ML−3], q the Darcy velocity vector

[LT−1], t time [T ], n porosity [−] and D the hydrodynamic dispersion tensor [L2T−1].

Taking into account only the component in the x-direction the conservative advection

dispersion equation becomes:

∂C

∂t+ v

∂C

∂x−Dl

∂2C

∂x2= 0 (3.11)

where v is the seepage velocity [LT−1] and Dl the longitudinal hydrodynamic dispersion

coefficient [L2T−1].

3.5.2 Transport and Kinetic Removal

Non-conservative transport of mass in a porous medium can be described by the mass

balance equation for the liquid phase (including hydrodynamic dispersion, advection and

a sink term) combined with the mass balance equation for the solid phase, that describes

the sink term of the first one. Assuming that the porosity is constant and the transport

only occurs in the direction of flow, the equation becomes:

∂C

∂t+ v

∂C

∂x−Dl

∂2C

∂x2= −ρb

n

∂S

∂t(3.12)

where S is the mass of nZVI per dry unit weight of sand [MM−1] and ρb the bulk density

(ρb = (1− n)ρs, with n the porosity and ρs the density of the sand).

3.5.3 nZVI Removal in Porous Media

The removal of colloids from the suspension, and with that the associated concentration

of colloids at the solid phase S, is here treated to be not only caused by the attachment on

the grain surface but also by the gravitational settling and straining effects of the colloids

and aggregates in the porous medium during transport.

It is here proposed to build up the removal of nZVI from the liquid phase in two parts,

kcolatt for the attachment on the grain surface due to colloid filtration of single colloids and

kaggatt to account for the removal of aggregates from the suspension. The sink term from

65


Equation 3.12) is described by a kinetic version of the Langmuir sorption isotherm for the

removal of colloids due to filtration and a term to account for the continuous filtration of

the aggregates. This results in the following definition of the sink term:

∂S

∂t=

n

ρbkcolatt

(1− S

Smax

)C +

n

ρbkaggatt C − kdS (3.13)

where kcolatt and kaggatt represent the attachment- and kd the detachment coefficients [−] and

Smax the maximum amount of nZVI that can be attached at the solid phase [MM−1]. The

aggregates removed from the suspension are assumed to have no effect on the maximum

of colloids that can be attached on the grain surface, thus they were chosen to be added

to Smax, which was therefore defined by:

Smax = S0max + Sr (3.14)

where Sr represents the removed aggregates from the suspension (i.e. Sr = nρb−1kaggatt C).

Once these equations are substituted into Equation 3.13, it becomes clear that the total

mass of removed colloids will show an asymptotic behavior. Concentrations taking in

more space than available by the pore space are in theory possible. Though, it is assumed

that the injection duration is relatively short or the removal rates are respectively small,

avoiding the system to ever reach concentrations which could significantly fill up the pore

space. The removal of aggregates is proposed to also be described by using the contact

efficiency coefficient:

kaggatt =3(1− n)αaggηagg0 v

2dc(3.15)

where, ηagg0 is the contact efficiency coefficient calculated for the aggregates and αagg is

the aggregate removal efficiency. Since the aggregates are much bigger, the removal will

be mainly caused by sedimentation and straining and thus the available surface area of

the sand grains is less of importance, hence, a Langmuir isotherm is not expected to be

necessary for the removal of the aggregates.

It is assumed that furthermore for the transport of nZVI colloids, the desorption is

negligibly small and thus further has not to be taken into account. Together these

equations form the following flow, transport and kinetic removal equation:

66

3.6. Transport Experiments (1D)

∂C

∂t= −v∂C

∂x+Dl

∂2C

∂x2−(

3(1− n)αη0v

2dc

)(1− S

S0max + Sr

)C −(

3(1− n)αaggηagg0 v

2dc

)C (3.16)

This mathematical description takes all the assumptions of the conceptual model into

account. Whether this transport equation and the filtration theory are capable of fully

describing the removal of both colloids and aggregates can only be verified by combining

experimental with numerical work.

3.6 Transport Experiments (1D)

Transport experiments in columns were performed to increase the understanding of the

occurring transport phenomena during the injection of a nZVI suspension into porous

media. The column experiments were performed in horizontal two meter long columns to

have transport conditions which are closer to those of a field scale injection (Figure 3.8).

Figure 3.8: Column experiment set up

67


The raw data of the column experiments presented here was obtained through the work

of Xu [2009] and Steiert [2008].

Both descriptive and quantitative methods were applied to compare column experi-

ments of different condition with each other and obtain a way of identifying conditions

resulting in better or poorer transport.

The measuring technique as described in section 2.3 was used to measure transient con-

centration profiles from which the information was obtained to compare the experiments

among each other. Furthermore, these datasets were to be used as fitting input of the

transport equation in a numerical model.

Because the filtration theory does not directly take the concentration of the suspension

into account, the set of experiments presented here was performed with different input

concentrations of the injected suspension. It was sought if the transport is independent

of the concentration, or if there is a dependency and if so, if a constitutive relationship

could be obtained from these experiments.

3.6.1 Materials and Methods

Porous Medium

For the porous medium a quartz sand (Dorsilit nr. 8, d10 = 0.3 mm, d50 = 0.47 mm,

d90 = 0.8 mm, Dorfner GmbH, Germany) was used. This quartz sand was delivered fire

dried and had a very low iron content (< 1 mg/kg).

The used columns consisted of transparent Plexiglas (Acrylglas XT, Ernst Kienzle

GmbH, Germany) and were 2 m long and had a 36 mm inner-diameter. The in- and

outlet plugs (IWS, University of Stuttgart, Germany) were made of PTFE and were placed

inside the column. A PTFE gauze (Sefar Nytal, PA5-HD225, mesh-opening 225 µm) was

pulled over the front of the plugs to create a good contact with the porous medium. The

screws, valves, tube-nipples and other accessories were made of various plastics.

The column filling was done by dry packing using a sand raining construction with two

wire gauzes placed on a 45 angle to each other, according to Rad and Tumay [1985].

After filling, the top side was closed with the outlet plug. From bottom to top CO2

gas was pushed through (6 pore volumes), which replaced the air. Next the column was

saturated and flushed with 6 pore volumes from bottom to top with degassed tap water

(∼ 1 mg O2/l).

Placed horizontally in the framework, the hydraulic conductivity of the column was

determined by attaching two constant head containers (the one at the inlet side placed

68


approximately 90 cm higher then the one at the outlet) and measuring the discharge

through the column by weighting the outflow on a scale.

The average packing density was 1.55 g/cm3 and the porosity was 0.34. The hydraulic

conductivity was on average 1.28 · 10−3 m/s.

Tracer break through curves were analyzed to further characterize the porous medium

in the column. The conservative tracer Uranine (C20H10O5Na2) which gives a green

solution was injected and measured at the outlet of the column with a flow through cell

(Hellma, 175.000 − QS) inside a photometer (Lambda 20, Perkin Elmer, Germany) the

extinction at 490 nm. A Uranine pulse of 10 ml (assumed to represent a Dirac pulse)

with a concentration of 8.1 mg/l in degassed tap water was injected with a syringe at the

inlet of the column. A flux of 70 ml/h was applied with a peristaltic pump (Ismatec IPC

8, Novodirect, Germany).

The longitudinal dispersion length αl which is a seepage velocity independent charac-

teristic of the porous medium was determined from the break through curve according to

the following equation [Bear, 1972]:

Cmax(t) =mtracer

2Acolumnn√πDlt

exp

(−(x− x)2

4Dlt

)(3.17)

where Cmax is the maximum concentration [ML−3] at time t [T ], mtracer the mass of

tracer [M ], Acolumn the cross-sectional area of the column [L2], n the porosity [−], Dl

the longitudinal dispersion coefficient [L2T−1], x is the observation point seen from the

column inlet [L] and x the transported distance of the center of the pulse [L]. Because a

conservative tracer is used and the arrival time of the center of the pulse is equal to the

duration of one pore volume, x = x, Equation 3.17 can be following rewritten to determine

the longitudinal dispersion coefficient Dl and the associated longitudinal dispersion length

αl:

Dl =

(m

AnCmax,t

)21

4πt(3.18)

αl =Dl

v(3.19)

where v is the seepage velocity [LT−1] and αl the dispersion length [L].

A maximum concentration of 0.594mg/l was measured after 614.5 minutes (Figure 3.9),

thus the longitudinal dispersion length is αl = 5.18 ·10−4 m. The determined longitudinal

dispersion length is very close to the d50 of the sand used (4.7 · 10−4m). This supports a

69


0

0.1

0.2

0.3

0.4

0.5

0.6

500 600 700 800 900 1000 0

20

40

60

80

100C

Ura

nine

[mg/

l]

Cum

ulat

ive

[%]

Time [min]

Breakthrough curveCumulative mass

Breakthrough of 50%

Figure 3.9: Tracer experiment data to determine the longitudinal hydrodynamic dispersioncoefficient

common rule of thumb that for a sand with a very steep sieve curve d50 can be used as

the longitudinal dispersion length.

Suspension

The nZVI base suspension for all column experiments was RNIP 10-E (2007 lot, Toda

Kogyo, Japan). A detailed characterization of the suspension is described in section 3.3.1.

The diluted suspension was dispersed mechanically by applying high shear forces. The

Dispersing unit circulated the mixed suspension inside the reservoir while breaking up

the aggregates (Figure 3.10). At the start of the injection, the disperser was switched off

and the mixer was kept on to keep the colloids in suspension.

Experimental Set Up

An overview of the set up is given in Figure 3.11. The whole setup of the experiment

including the column and plugs was constructed without any metal parts within 1 m

distance from the column to avoid interference on the metal detector reading. The frame-

work holding the column was made of wood and placed the column 1.5 m above the metal

reinforced concrete floor.

70


Figure 3.10: Disperser connected to the nZVI reservoir with mixer

The constant head container at the outflow side was kept connected during the trans-

port experiment, the constant head at the inlet side was disconnected to connect a peri-

staltic pump (Watson Marlow 323, pump heads 318MC and 314X) for the injection of

the nZVI suspension. This pump could deliver a constant flux until a pressure of approx-

imately 0.2 bar (i.e. a gradient of 1 in this system). At higher pressures the discharge

reduces and eventually stops. To know the exact discharge throughout the experiment

the outflow was collected and weighted on a scale. The pressure was measured at the

inlet and outlet side with pressure sensors (DRTR 0−1.6 bar, HYGROSENS, Germany).

The hydraulic conductivity of the column could be measured by selecting the constant

head instead of the pump at the inlet using the 3-way valve. To inject the suspension

from the nZVI reservoir the 3-way valve was turned towards the pump. The water at

the outlet was collected and continuously weighed using a balance (DE 12K1A, Kern,

Germany) to know the exact discharge during the hydraulic conductivity measurement

and the injection.

The pressure sensors (PS1 and PS2) were connected in the vicinity of the in- and outlet

plugs.

71


Constant Head Tank (outlet)Metall Detector

Column

PumpDisperser

Mixer

PS 1

Constant Head Tank (inlet)

3-WayValve

PS 2

Figure 3.11: Schematic overview of the column experiment set up

The total-iron concentration of each suspension prepared for injection was after disso-

lution with HCl determined using the phenanthroline colorimetric method and a photo

meter (Lambda 12, Perkin Elmer, Germany).

3.6.2 Conditions

The column experiments were performed with different suspension concentrations while

maintaining the seepage velocity inside the column constant. The total injected nZVI

mass was not kept constant, but the injected pore volumes were adjusted to get the total

injected mass closer together.

The conditions that were kept constant throughout all the column experiments were:

porosity n = 0.34, hydraulic conductivity K = 1.3 · 10−3 m/s, porous media length

L = 1.9 m, mass of sand msand = 3.2 kg, pore volume 1PV = 6.86 · 10−4 m3. The varied

input conditions that were measured just before or during each experiment are given

in Table 3.4. The average seepage velocity is presented in Table 3.4. The initially set

Table 3.4: Conditions used for the column experiments. Provided are: the suspensionconcentration (C0), amount of injected pore volumes (PV ), volume of injected nZVI

suspension (VFe), injection duration (t), total mass of injected nZVI (MFe) and the averageseepage velocity (v)

C0(g/l) PV (−) VFe(l) t(min) MFe(g) v(·10−3m/s)

0.08 20.35 39.21 500 1.07 1.28

0.81 10.17 20.23 240 5.55 1.38

1.50 9.88 19.66 240 10.00 1.34

5.53 6.95 12.39 200 23.24 1.01

9.26 7.27 14.38 250 45.20 0.94

11.26 4.45 3.00 150 33.69 0.96

72


seepage velocity for all experiment was 1.6 · 10−3m/s, nevertheless, the peristaltic pump

could not provide a very constant flux and thus the seepage velocity was obtained from

the measured discharge.

3.6.3 Results & Discussion

For one experiment successive photos with a 10 min interval are shown in Figure 3.12

Transient concentration profiles are shown in Figure 3.13 of column experiments per-

formed with different input concentrations. The plots present subsequent concentration

profiles along the column, the time in the plots is presented by injected pore volumes.

The time interval between each of the measurements was ten minutes which accounts for

approximately half a pore volume.

Beside the presented experiments in these plots more experiments (some as duplicates)

were performed and used for the further analysis of the transport behavior. The first

measurement has the lowest concentrations (bottom left corner of each plot), the last

measurement is always the outside profile with the highest concentrations. During the

injection the lateral transport progressed while the concentration of retained col-

loids inside the porous medium continuously increased. In none of the experiments a

maximum concentration was observed.

In non of the experiments a concentration of iron occupying a volume close to that of the

pore space was reached. The maximum measured volume ratio occupied by the iron was

3%. Nevertheless, the pressure gradient did change during the injection (Figure 3.14).

Especially for the experiments with the highest concentrations the gradient increased

significantly. This indicates that the hydraulic conductivity changed during the injection.

The hydraulic conductivity of the whole system though can be lowered by a reduced

conductivity at a single place. Bridging effects [Bradford and Torkzaban, 2008; de Zwart,

2007] and filter cake building [Al-Abduwani et al., 2005] directly at the inlet filter or first

few sand grains after the filter would be the most likely cause of the significant hydraulic

conductivity reduction, while the rest of the column was not affected. For the lower

injected concentrations no significant change in the pressure gradient was observed.

73


(a) 0 min

(b) 2 min

(c) 12 min

(d) 22 min

(e) 32 min, 1 PV

(f) 42 min

(g) 52 min

(h) 62 min, 2 PV

(i) 72 min

(j) 82 min

(k) 92 min, 3 PV

(l) 102 min

(m) 112 min

(n) 122 min, 4 PV

Figure 3.12: Injection on nZVI into a column. A small volume of dyed water was injected firstto show the injection front propagation (the dark color on the right end of the column is a

lightning artifact)

74


0

0.5

1

1.5

2

0 500 1000 1500 2000

Sto

tal [

g/kg

]

C0: 0.08 g/l0.451.001.552.082.583.093.584.054.524.98

5.445.896.316.717.137.547.958.358.759.15

9.559.94

10.3310.7211.1111.4911.8712.2512.6313.00

13.3713.7114.0414.4214.7915.1415.4815.8316.2116.59

16.9617.3417.7218.0918.4718.8519.2219.6019.9820.35

0 1 2 3 4 5 6

0 500 1000 1500 2000

Sto

tal [

g/kg

]

C0: 0.81 g/l0.480.961.461.932.362.813.263.71

4.154.574.995.405.816.226.637.04

7.447.828.198.558.909.239.569.88

0 5

10 15 20 25 30

0 500 1000 1500 2000

Sto

tal [

g/kg

]

C0: 5.53 g/l0.350.711.071.441.812.172.532.893.243.60

3.954.294.634.975.315.655.976.306.626.95

0 5

10 15 20 25 30

0 500 1000 1500 2000

Sto

tal [

g/kg

]

Distance from inlet [mm]

C0: 11.26 g/l0.330.651.011.351.692.022.332.63

2.923.193.463.723.974.214.45

Figure 3.13: Concentration profiles for nZVI (Stotal, retained and in suspension combined)along the column with 10 minutes interval, the legend shows the injected pore volumes [PV ]

75


0

0.2

0.4

0.6

0.8

1

0 1 2 3 4 5 6 7 8

Pre

ssur

e gr

adie

nt [-

]

Injected pore volumes [PV]

0.08 g/l0.81 g/l5.53 g/l

11.26 g/l

Figure 3.14: Pressure gradient development during the injection. The gradient is the pressureat the inlet divided by the porous media length

Water Flushing

For several experiments the effect of water flushing after the injection of iron was tested.

In Figure 3.15 the difference of the iron distribution inside a column is shown for an

experiment where after the injection of iron the column was flushed with fresh water

at the same injection rate. The pump was kept on running during the switching of

the reservoirs, with two valves the reservoir switch can be performed without pressure

pulses. The removal of colloids showed to be nearly irreversible under the applied flow

conditions from these measurements. The flushing applied to the other experiments (not

presented here), showed comparable results. These measurements support the choice of

an irreversible sink term and the negligence of the detachment coefficient in the transport

equation (Equation 3.16). It can further be assumed based on these observations that the

colloids will not remobilize after the injection has finished. Once after the injection, the

natural ground water again flows through the injected nZVI, the natural ground water

velocities are orders of magnitude smaller than the flow velocities induced during the

injection, which will further minimize the chance of remobilization.

76


-1

0

1

2

3

4

5

6

7

8

0 500 1000 1500 2000

Sto

tal [

g/kg

]

Distance from the inlet [mm]

End of 5 PVs Fe InjectionAfter 1 PV H2O Flushing

Difference

Figure 3.15: Concentration change within the column after a water flushing of 1 pore volume.The discharge was not interrupted between the nZVI injection and H2O flushing

Column Data Analysis

Quantitative methods to describe and compare the column experiments were developed

based on the datasets of the transient concentration profiles.

To evaluate the concentration change within the column, the concentration at several

locations within the column were plotted against the time. For a selection of the ex-

periments these are presented for 50 cm from the inlet in Figure 3.16. The curves show

that no steady state was reached during the injection duration, since the concentrations

continuously increased throughout the whole injection time.

From the transient concentration profiles, the distances of different mass fractions (e.g.

25, 50 or 95%) of the injected iron were determined by first integrating the concentration

profile and then finding the distance where the cumulative mass reaches the searched

mass fraction. To compare these transport distances with each other over time, but

also from one experiment to the other, the travel distance (xF ) was normalized by the

displacement of the advective front, where only the representative fraction of the advective

front displacement was taken into account (Equation 3.20).

XF (t) =xF (t)

F · v · t (3.20)

77


0

5

10

15

20

25

0 1 2 3 4 5 6 7 8

Sto

tal a

t 50

cm [g

/kg]


0.08 g/l0.81 g/l5.53 g/l

11.26 g/l

Figure 3.16: Breakthrough curves within the column at 50 cm during the injection. Shown areexperiments with different suspension concentrations

here XF (t) is the normalized travel distance of the mass fraction [−], F is the mass

fraction (e.g. 0.5 for the center of mass or 0.95 for the 2σ position) of the total injected

nZVI mass [−] and xf (t) the distance where the cumulative concentration reaches the

mass fraction [L]. It follows that the advective front (F · v · t) can be fictive when it

becomes larger than the porous media length. This procedure is similar to the procedure

used for calculating the retardation factor as applied in solvent transport. For solvent

transport, the retardation describes a process of adsorption and desorption [Fetter, 1999],

whereas here colloids attach and do not detach, and beside the attachment of colloids a

general removal of the aggregates takes place. The retardation factor in solvent transport

is applied on the concentration in the liquid phase, here the normalized travel distance

describes the mass distribution at the solid phase and liquid phase combined. For the

application of nZVI as in-situ remediation technique, the mass of iron in the non-mobile

phase is of main interest, hence the quality of transport was chosen to be at best described

by the here presented normalized transport distance. The normalized travel distance of

the 50% mass fraction (center of mass) as a function of time is presented in Figure 3.17, the

50%, 75% and 98% mass fraction values at 2 pore volumes are given in Table 3.5. Values

closer to 1 represent better transport, for conservative transport X50, X75 and X98 would

all be equal to 1. From these values it can be seen that the normalized transport distance

78


Table 3.5: Transport results of the 1-D flow experiments. X50 and X98 are the normalizedtransport distances at 2 pore volumes

C0 X50 X75 X98

0.08 0.024 0.025 0.029

0.81 0.075 0.093 0.38

1.50 0.077 0.11 0.47

5.53 0.087 0.096 0.14

9.26 0.15 0.16 0.18

11.26 0.12 0.13 0.14

presents a quick method to compare different experiments with very different conditions

to each other. The overall normalized travel distances are largest for the experiments

around 10 g/l. Experiments at higher concentrations were initially also performed but

are not presented here because they showed serious clogging effects (pressure gradient

larger than 1) before one pore volume could be injected.

A general transport behavior becomes visible from Figures 3.17 and 3.16. The trans-

port shows two phases in the transport, first a phase of quick movement along

with the injection fluid is seen, followed by a phase during which the iron is being further

0

0.05

0.1

0.15

0.2

0.25

0.3

0 1 2 3 4 5 6 7 8

Nor

mal

ized

tran

spor

t dis

tanc

e [-]


0.08 g/l0.81 g/l5.53 g/l

11.26 g/l

Figure 3.17: Normalized transport distances as a function of injected pore volumes for 50 % ofthe injected nZVI mass (center of mass). Presented are experiments with different suspension

concentrations

79


deposited over the distance of this first transport phase. During the second phase only

minimal transport in the lateral direction was taking place. This effect was also visu-

ally observed during these and other (e.g. de Boer [2007]) experiments. In Figure 3.16

this is clearly observed for the 11.26 g/l injection through the two different inclina-

tions of the concentration change over time. The normalized transport distance shows

a more smooth change (Figure 3.17), though the normalized transport distance shows a

fast reduction in the beginning followed by a slow continuous reduction during the rest

of the injection.

When aiming for an injection to result in high concentration (e.g. 25 g/kg) without

clogging the porous medium, from this data analysis the injections performed at a con-

centration around 10 g/l performed best. If much larger distances are aimed and the

concentration of nZVI retained in the porous medium does not have to be that high (e.g.

1 ∼ 2 g/kg) an injection around 1 g/l should be applied based on these results. To reach

the larger distances off course also much larger injection volumes have to be applied.

3.7 Numerical Model

The transport was modeled using the presented transport equation (Equation 3.16) in a

numerical finite elements code in MATLAB (the Mathworks, Novi, MI), the finite element

base of the code and the fitting algorithm were provided by D.M. O’Carrol (RESTORE,

UWO, Canada), which was also used in Liu et al. [2009]. In their application the model

was fitted to the break through curves of the effluent concentration of the columns. In the

work presented here the model was adapted to produce the concentration profiles for the

total of attached and suspended iron along the full length of the column. The flow and

transport equation was replaced by the proposed one, and the model was also adjusted to

produce real concentrations instead of normalized concentrations. The model was then

applied for inverse fitting to the measured data over S0max, α and αagg on three successive

concentration profiles of each injection experiment.

3.7.1 Numerical Simulation with Fitting on Transient Column Data

The flow and transport equation was solved in the 1-D finite elements code and inversely

fitted on the transient concentration profiles of the column experiments. In Figure 3.18 the

measured concentration profiles and their model results are presented for four successive

concentration profiles of each experiment.

80

3.7. Numerical Model

0

0.5

1

1.5

2

0 500 1000 1500 2000

Sto

tal [

g/kg

]

C0: 0.08 g/lData

Simulation

0 1 2 3 4 5 6

0 500 1000 1500 2000

Sto

tal [

g/kg

]

C0: 0.81 g/lData

Simulation

0 5

10 15 20 25 30

0 500 1000 1500 2000

Sto

tal [

g/kg

]

C0: 5.53 g/lData

Simulation

0 5

10 15 20 25 30

0 500 1000 1500 2000

Sto

tal [

g/kg

]

Distance from inlet [mm]

C0: 11.26 g/lData

Simulation

Figure 3.18: Data and numerical simulation for four concentration profiles of four selectedexperiments with different input concentrations. Fitted was on three profiles, the fourth (most

outer) profile is always the forward model result

81


Table 3.6: Calculated (η0, ηagg0 ) and fitted (α, S0max, αagg) values of the simulations.

C0(g/l) η0(−) α(−) S0max(g/kg) ηagg0 (−) αagg(−)

0.08 5.30 · 10−3 1.0 6.08 · 10−4 2.77 · 10−2 0.038

0.81 5.00 · 10−3 0.9 2.53 · 10−3 2.56 · 10−2 0.016

1.50 5.10 · 10−3 0.3 4.13 · 10−3 2.66 · 10−2 0.010

5.53 6.20 · 10−3 1.0 8.00 · 10−3 3.46 · 10−2 0.019

9.26 6.70 · 10−3 1.0 5.00 · 10−3 3.92 · 10−2 0.018

11.26 6.50 · 10−3 1.0 1.29 · 10−2 3.71 · 10−2 0.010

Averages 0.0058 0.86 Equation 3.21 0.0318 0.018

The fitting was performed on three of these concentration profiles, the fitting routine

searches the minimum of the normalized summed root mean square error (RMSE) of

the calculated three concentration profiles and the measured concentration profiles. The

fourth profile shown in each plot was not included for the inverse fitting but is a continued

calculation to see how well the model predicts the further progress of the experiment. In

Table 3.6 the fitting results are presented for all experiments performed at different input

concentrations.

The transport including the observed continuous increase of the concentration inside

the column could be accurately described due to the addition of the separate aggregate

removal term (kaggatt ) and the continuous addition of these removed aggregates to the

denominator of the Langmuir weighting term (Equation 3.16).

S0max increases with higher input concentration (C0) (Figure 3.19, Table 3.6), the

amount of colloids attachable on the grain surface thus showed to be a function of the

input concentration. A linear constitutive relationship could be reasonably fitted to this

dependency:

S0max(C0) = 7.81 · 10−4C0 + 1.83 · 10−3 (3.21)

For α and αagg there does not seem to be any relationship towards the input concen-

tration, they both are almost identical for all experiments and an average value should

be capable of describing the transport independent of the input concentration.

ηagg0 was strongly over predicted by the filtration theory which results in a correction

of 0.018 via the attachment efficiency factor αagg. The most likely causes for the dis-

crepancy would be the non-spherical shape of the aggregates which results in different

behavior and a lower density of the aggregates. Aggregates thus clearly get much better

transported than would be expected from the sedimentation experiments and filtration

theory alone. Another reason could be that the aggregates were more than 0.5 µm, in

82

3.8. Summarizing the Findings

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0 2 4 6 8 10 12 14 16

S0 m

ax [

g/kg

]

C0 [g/l]

S0max(C0) = a C0 + b

a =7.81e-04

b =1.83e-03

S0max

S0max(C0)

Figure 3.19: S0max fitted for experiments with different input concentrations

Section 3.2.3 it was already mentioned that the assumption of horizontal flow instead of

vertical would probably not hold for colloids larger than 0.5 µm. The larger aggregates

thus will be influenced by gravity and the filtration theory assumes that the flow direction

is in the same direction as gravity, which is actually not the case for the horizontal column

experiments.

3.8 Summarizing the Findings

Through a sensitivity analysis of a filtration theory and the characterization of the nZVI

suspension a better understanding of the expected transport behavior of nZVI could be

constructed. The result is a conceptual model that describes the transport of nZVI by

approaching the suspension to be consisted of two main particle sizes (nano sized colloids

and micro sized aggregates) of which the size can be determined through sedimentation

experiments for the aggregates and a commercial particle size detector for the nano sized

colloids. A transport equation was derived to fully describe the concept. This transport

equation was verified and where necessary fitted in a numerical model to transient con-

centration profiles of column experiments. The transport equation, measured parameters

characterizing the suspension and the fitted parameters of the numerical code will be used

for the upscaling and prediction of transport in more dimensions in the following chapter.

83


84

4 Colloid Transport in a Radial Flow

Field

4.1 Motivation

Column experiments as described in Section 3.6 give an indication on how nZVI is being

transported in a 1-D geometry. They cannot be directly used to predict field conditions

or to design a pilot or full remediation. Therefore, research of two and three dimensional

transport behavior at a near field scale would be preferable.

So far, in the literature, most of the research, has been done on column experiments,

and transport was characterized in only one dimension. Less research has been done

into the two and three dimensional description of transport of nZVI. Most of the studies

involving two or three dimensions, use small scale flume experiments [Kanel et al., 2008;

Phenrat et al., 2010, 2011]. Although the basic transport mechanisms of nZVI transport

in porous media must be understood before accurate predictions of transport can be made,

one dimensional models and experiments are insufficient to describe the rapid decrease

of the seepage velocity in a radial flow field around an injection well. Furthermore,

flume experiments at small scales do not sufficiently reproduce the results of field scale

injections.

Here, three different methods were developed to get a better description and prediction

possibility of nZVI transport in radial full scale flow fields. (I) Large near field scale con-

tainer experiments, (II) experiments using multiple columns and boundary conditions to

experimentally discretize a radial flow field, and (III) the transfer of calibrated parameters

from the 1-D model (Section 3.7) to run forward simulations of radial flow.

85

4. Colloid Transport in a Radial Flow Field

4.2 Flow and Transport in Radial Systems

4.2.1 Concept

During injection into a well, the injected fluid has to flow through a continuously grow-

ing cross sectional area (Figure 4.1a) The seepage velocity around the well is therefore

no longer constant (as in a column experiment) but decreases hyperbolically (for con-

fined, fully screened and homogeneous conditions) with increasing distance from the well

(Figure 4.1b).

(a) After Payne et al. [2008]

0

1

2

3

4

5

6

7

8

0 500 1000 1500 2000

See

page

vel

ocity

[mm

/s]

Radial distance [mm]

(b)

Figure 4.1: (a) The cross sectional area increases while the injection fluid progresses fartherfrom the injection well. (b) Hyperbolically decreasing seepage velocity around a fully screened

well in a confined aquifer of 0.6 m thick with an injection rate of 6000 l/h

4.2.2 Mathematical Description

The groundwater flow and transport equations have been presented in the previous chap-

ter in detail for 1-D flow fields. Here, the equations will be presented for radial flow fields,

which occur around a fully screened well over the height of a confined aquifer.

Steady State Groundwater Flow Equation

Steady state groundwater flow can be presented in two different ways in cylindrical coor-

dinates when assuming there is no influence of the vertical z-direction. (I) As a function

of the hydraulic conductivity and the change in hydraulic head in all directions

[Schwartz and Zhang, 2003]. The discharge per unit width of aquifer is then given by the

86

4.2. Flow and Transport in Radial Systems

Darcy velocity:

q = K∇h with: K =1

b

∫ b

0

K(z)dz (4.1)

q = K

(1

r

∂h

∂θ+∂h

∂r

)(4.2)

where θ and r are the cylindrical coordinates and q is the Darcy velocity [LT−1], K the

average hydraulic conductivity over the thickness of the aquifer [LT−1], b the base height

of the confined aquifer [L] in the z direction and h the hydraulic head [L]. This can be

further simplified when assuming that there is no change of the hydraulic head over θ and

the hydraulic conductivity is everywhere the same in the whole domain:

q = K∂h

∂r(4.3)

with K being the hydraulic conductivity.

(II) The Darcy velocity can furthermore be calculated from the pumping rate at the

well, using cylindrical coordinates:

q =Q

2πbr(4.4)

where Q is flow rate [L3T−1] and r is radius [L]. The Darcy velocity can then be divided

by porosity, to obtain the seepage velocity:

v =Q

2πnbr(4.5)

where v is the seepage velocity [LT−1] and n the porosity [−].

Groundwater Flow, Transport and Filtration

The flow and transport equation for an incompressible fluid (Equation 3.10) was extended

with kinetic removal:

n∂C

∂t+ C∇ · q + q∇C −∇ · (nD∇C) = −ρb

∂S

∂t(4.6)

Following the procedure described by equations 3.13-3.16, but taking into account that

the velocity (v), the hydrodynamic dispersion (D), the collector efficiency for colloids (η0)

and the collector efficiency for aggregates (ηagg0 ) are no longer constants, but vary over

87


space and have to be kept in the equation as a tensor, the kinetic removal term is defined

following:

∂S

∂t=

(3(1− n)αη0v

ρb2dc

)(1− S

S0max + Sr

)C −

(3(1− n)αaggηagg0 v

ρb2dc

)C (4.7)

Assuming that the porosity is constant, the following partial differential equation can

be defined:

∂C

∂t= −C∇ · v − v∇C +∇ · (D∇C)−(

3(1− n)αη0v

2dc

)(1− S

S0max + Sr

)C −(

3(1− n)αaggηagg0 v

2dc

)C (4.8)

4.3 Container Experiments with a Radial Flow Field

4.3.1 Motivation

The Darcy velocity, as well as other quantities and variables such as mass flux density,

decrease hyperbolically with distance from the well, which cannot be represented by a

single column experiment. Before field trials are started, the effect of this type of flow

field was to be investigated. To be able to get a better understanding of the transferability

of the description derived from batch and column experiments and filtration theory into

the field scale a large scale experiment was developed. At this large scale it also became

possible to test real pumping techniques and the preparation of large volumes suspension.

The experiment consisted of a triangular container which represents a 60° segment of a

full cylinder. Assuming radially symmetrical flow, the 60° segment can represent a full

cylinder without loss of generalization. Moreover, a window installed along the side wall

of the tank allows for a visual observation of flow and transport along a stream line

(Figure 4.2).

The main questions to be answered with the four experiments presented here were:

Which transport distances are possible for nZVI colloids under field realistic condi-

tions?

Are the results reproducible?

What is the influence of injection rate on the transport distance?

Which pumping mechanism is better for the transport; pulsating or continuous flux?

88

4.3. Container Experiments with a Radial Flow Field

Figure 4.2: Overview photo of the container experiment set up

4.3.2 Material & Methods

ZVI Suspensions

For the experiments presented here, nZVI colloids (RNIP 10E, Lot 2008, Toda Kogyo

Corp., Japan) were used. Detailed specifications are provided in sections 3.3 & 3.6.1

The delivered slurry was diluted with degassed tap water to achieve the desired sus-

pension concentration for each experiment. The suspension was prepared using a mixing

and dispersing unit (Figure 3.10) at a high concentration (∼ 75 g/l), and was then

pumped into a large 1000 liter reservoir for further dilution. A circular mixing unit in the

reservoir was also used to keep the colloids in suspension throughout the duration of the

experiment. The IKA UTL25 Ultra Turrax was used for the first three experiments, be-

cause in total 1000 liters of suspension needed to be prepared for each experiment, it was

replaced by a larger dispersing unit. The new dispersing unit (DK40, CAT, Germany)

could process up to 6000 l/h, versus 600 l/h for the IKA UTL25.

The desired suspension concentration was 10 g/l, the measured concentrations varied

between 8.3 and 12.7 g/l.

89


Porous Medium

For all experiments the same quartz sand as described in Section 3.6.1 was used. The

pore volume of the porous medium between the filter screens was approximately 300 liters.

Porosity in the column experiments was approximately 0.35, and approximately 0.4 in

the container experiments, due to different packing methods. There is also a difference

in anisotropy when comparing the porous medium of the columns to containers. The

columns were filled perpendicular to the direction of the flow, whereas the container was

filled parallel to the direction of flow.

The container was filled with sand using buckets and spreading the sand with a rake.

The sand (∼ 5 cm layer) was compacted with a heavy pestle.

During packing, the sensors for measuring the nZVI break through were installed. The

sensors were first filled with sand and then placed horizontally in line with the direction

of flow.

A constant head boundary condition was implemented with a constant head tank at a

height of 68 cm that collects the outflow from the outer edge of the porous medium.

Experimental Set Up

The container constructed to simulate the radial symmetrically flow field inside a confined

aquifer was chosen to be triangularly shaped. The triangle represents a 60° segment of a

full cylinder to make it possible to get a cross-sectional view of the experiment through a

glass plate (40 mm security glass, Sudwest Glas, Germany) as well as to reduce the total

size. By using only a segment of the full cylinder, this scales the aquifer volume, necessary

suspension volume and injection rate but not the concentration and seepage velocity and

Figure 4.3: Schematic overview of the container experiment set up

90


thus the transport behavior. The segment represents one sixth of a full cylinder, therefore,

an injection of 1000 l/h into the container is equivalent to an injection of 6000 l/h at a

full 360° system. The dimensions of the container (inside: b = 0.6 m, r = 1.78 m) were

chosen to be comparable to a real field situation. Sand was packed into the container to

create the porous medium as describe above. A reinforced lid provided an upper seal of

the container. To ensure confined conditions and to prevent preferential flow along the lid

a swelling bentonite (QSM200, Eijkelkamp, The Netherlands) clay layer was packed on

top of the sand. Additionally the lid was air tight closed with silicon (Ottoseal S10, Otto-

Chemie, Germany). The whole container was built from Polypropylene (PP) and no iron

was used within at least 50 cm from the container wall to reduce the background magnetic

susceptibility and thus avoid interference of the container material on the electromagnetic

measurement system (Section 2.4). The injection well (∅ = 2.5 cm) was installed inside

another well screen (∅ = 12 cm), to allow for the emplacement of filter sand (Dorsilit, nr.

3, 2 − 3.5 mm, Dorfner, Germany) to guarantee a good transfer from the well into the

porous medium and to avoid the finer porous media sand to enter the well (Figure 4.4a).

At the outflow side drainage pipes (∅ = 10 cm, DIY store) were placed to create a filter

screen. Around the drainage pipes filter sand was placed to prevent the washing out of

sand grains, to avoid during the filling mixing of the sand and filter sand a bended metal

plate of 10 cm height was pulled up 5 cm after each sand layer was packed (Figure 4.4b).

(a) Top view of the double injection filter screenwith the coarse filter sand around the inner

injection filter. Photo taken after the injection,nZVI clearly seen in sand outside of second filter

screen, and filter sand is almost clean

(b) Top: drainage pipes used for the outflow filterscreen. Metal bended plate was moved up duringfilling to fill the area around the drainage pipeswith filter sand. Bottom: top view of the filter

sand when the whole container was filled

Figure 4.4: Injection filter and outlet filter of the container experiment

91


Table 4.1: Set up of the container experiments 1, 2, 3 and 4, which represent a 60° wedge froma confined fully saturated aquifer

Experiment 1 2 3 4

Distance between filter screens [m] 1.78 1.78 1.78 1.78

Well radius [m] 0.065 0.065 0.065 0.065

Base height [m] 0.6 0.6 0.6 0.6

Volume of sand [l] 833 833 833 833

Porosity [−] 0.4 0.4 0.4 0.4

1 PV [l] 333 333 333 333

The outflow of the drainage pipes was connected to a constant head tank (Figure 4.3).

The suspension was injected into the container using two in parallel connected dosing

pumps (Seepex, Germany) for all experiments except one, which used a piston-diaphragm

pump (Figure 4.5, Grundfos Alldos). The pumping rates were kept constant throughout

the experiment, creating a constant flux boundary condition at the injection well.

Soil samples were taken from the interior of each nZVI sensor and a representative

sample was taken at the same distance but at an angle of 45 from the glass plate where

no nZVI sensors were placed. The samples were analyzed by using the method described in

Section 2.6 and the nZVI concentration was calculated based on the age of the suspension

and Equation 3.7.

Figure 4.5: Two different types of pumps used. Left: two parallel connected continuous fluxdosing pumps. Right: pulsating flux piston-diaphragm pump

92


Installed Measuring Techniques

In total 27 nZVI sensors (see Section 2.4) were installed to measure the concentration

of iron at different locations within the container during the injection. The sensors were

placed at five different locations along the radial direction (measured from the center of

the injection well: 0.2, 0.4, 0.8, 1.1 and 1.5 m), at two angular directions (seen from

the glass plate at 5 and 30) and at three different levels (10, 30 and 50 cm). At the

distance of 0.2 m only one sensor at each level was placed, because the space at this

distance from the injection well was small for placing two sensors next to each other.

They were buried in the sand during the container filling and placed in line with the flow

field (Figure 4.6 & 4.7). Each sensor was connected through two coaxial cables (RG 58)

with a corresponding channel of the electronic measurement system.

The measured voltages were digitalized and logged by a computer. Finally, the data

was evaluated to obtain the change in magnetic susceptibility, which is directly related

Figure 4.6: 3-D Overview of sensor locations inside the container

93


Figure 4.7: View into the triangular container during filling. Sensors of the first layer are inplace. The injection well is located in the center end (blue) and the filter pipes are located in

the front (yellow) for the constant head boundary (clearly shown in Figure 4.6). The total flowdistance between injection (blue) and extraction (yellow) is 1.8 m, the inside height is 0.6 m

and the angle is 60°

to the nZVI concentration, as described in Section 2.4. In order to convert this magnetic

susceptibility into iron concentration the system needed to be calibrated retrospectively

after the experiment was excavated and the iron concentration within the coils were

determined analytically (Figure 4.8 and Section 2.6).

For the third and fourth transport experiment in the container the sensors installed

were coated with an epoxy resin (Figure 2.7) to avoid the influence of water chemistry on

the measured signal. During the first two tests in the container the signal of the metal

detection sensors was strongly influenced by the water chemistry (mainly the surfactants

inside the water which were added by the producer to prevent the iron colloids from

strong aggregation).

Several preliminary tests were performed as described in Section 2.4.3, these showed

that the influence of the water chemistry was completely removed due to the coating. The

coated sensor only showed a change in the measured signal when ferromagnetic material

was inside the sensor.

94


Figure 4.8: Samples taken out of the sensors for chemical analysis

4.3.3 Conditions

To answer the four questions posed in the motivation above, four experiments were per-

formed and compared to each other.

(Exp. 1) To determine the possible transport distance under field realistic conditions,

the field trial description of Muller et al. [2006a] was used as basis. An injection

rate of 1000 l/h in the container experiment results in approximately the seepage

velocities of their field trial.

(Exp. 1 & 4) The first experiment was repeated to test the reproducibility of the exper-

iments.

(Exp. 3 & 4) An other experiment was performed at half the injection rate (Exp. 3) to

see the influence of the injection rate on the transport distance. As mentioned be-

fore, in a radial flow field the seepage velocity decreases hyperbolically with distance

to the injection well. Due to that the seepage velocity drops fast in the direct vicin-

ity of the well. Recall that from the analysis of the filtration theory it was shown

that the relation between the collector efficiency and the seepage velocity was non

linear and could be described by a semi-hyperbolic function (Section 3.2.3). It

was hypothesized that the injection rate might have only a minimal effect on the

transport distance in a radial flow field. When changing the flow rate, the absolute

difference in seepage velocity close to the well is large, while further from the injec-

tion well the absolute difference is much smaller. Experiment 3 was performed at

500 l/h and experiment 4 at 1000 l/h (Table 4.2), both experiments used the same

95


continuous flux dosing pump and the total amount of nZVI suspension injected was

the same for both experiments.

(Exp. 2 & 3) For a field application different types of pumps can be used. Two extremes

were compared here, a pump providing a very stable and continuous flux (Exp. 3)

through a rotor stator technique and one that provides a pulsating discontinuous

flux (Exp. 2) through a large single diaphragm (Table 4.2). Both pumps are shown

in Figure 4.5. Both experiments were performed at 500 l/h. The comparison of the

two pumping techniques should give an indication if the pulsating effect provides

a better or worse transport. The fluctuations in shear rate as a result of pulsation

could improve the transport of the colloids since colloids that attach to a sand grain

can potentially be remobilized by the high shear rates exited by the high flow rate

at the beginning of each pulse. It would though be worse if the increased flow rate

at the beginning of each pulse is not high enough to remobilize the colloids and

the lower flow rates (down to zero-flux) would result in a stronger removal of colloids.

Each of the experiments consisted of three injection phases. (I) Five liters of tracer

solution (Uranine, 0.5 g/l) were injected followed by (II) 900 liters of nZVI suspension.

The aimed suspension concentration was for all four experiments 10 g/l. (III) An in-

jection of 900 liters of degassed tap water (DO: ∼ 1 mg/l, pH: 7.0).The conditions of

the four experiments are presented in Table 4.2. Experiments 1 and 4 were performed

as duplicates, experiments 2 and 3 were performed at half the injection rate, and 2 was

performed with a different pump.

Table 4.2: The parameters used in the container experiments 1, 2, 3 and 4, which represent a60° wedge from a confined fully saturated aquifer

Experiment 1 2 3 4

Experiment Injection Rate [l/h] 1000 500 500 1000

Pump type Continuous Pulsating Continuous Continuous

Number of PVs injected [−] 2.7 2.7 2.7 2.7

Duration of injection [min] 55 110 110 55

nZVI age [days] 184 338 556 921

Cinput set [g/l] 10 10 10 10

Cinput measured [g/l] 8.3 9.9 10.5 12.7

96


4.3.4 Results and Discussion

In total four experiments were carried out to test the transport of nZVI colloids in a

confined aquifer using the container setup. Only the results of the nZVI sensors from

experiment 1 are shown, the strong influence of the water chemistry on the measurement

resulted the measurements of experiment 2 to go off scale. For experiments 3 and 4 the

coated nZVI sensors were installed, unfortunately, due to the resin around the sensors the

total signal was also reduced and during experiment 3 the sensitivity of the measuring

system was not enough anymore to get representative iron break through curves, this was

solved for experiment 4 but there the datafile unfortunately got corrupted during saving.

Each of the injections of nZVI was followed by an equal volume of fresh water, visually

no change in the distribution could be observed (compare Figures 4.10d and 4.10e), also

in the measurements with the nZVI sensors during the water flushing no change was

observed (Figure 4.11a). The presence of the surfactants in the suspension (although the

concentration of surfactants is low in the strongly diluted suspension) could enhance the

transport during the suspension injection and the lack of these surfactants during the

water flushing would then stop the transport.

For the container experiments the Reynolds number (Re) was calculated to test the

validity of assuming laminar flow throughout the whole container and thus the applica-

bility of Darcy’s Law to describe the flow field in the container. Reynolds Number is a

dimensionless indicator for the type of flow, the exact boundaries of the flow types laminar

and turbulent are case specific and also depend on the exact choice of the characteristic

length, Bear [1972] describes four different characteristic lengths and states that all of

them result in an upper limit for laminar flow at a value of Re between 1 and 10. Thus,

for Re values below 1−10 there correlation between pressure and Darcy velocity is linear

and for Re values between 1 − 10 and 100 a transition from laminar to turbulent flow

takes place because inertial forces start to predominate the flow. Reynolds number is

calculated by:

Re =ρfqL

µ(4.9)

where ρf is the fluid density [ML−3], q the Darcy velocity (or specific discharge) [LT−1],

L the characteristic length (often taken to be the representative grain diameter for the

porous medium, d50) [L] and µ the viscosity [ML−1T−1] [Bear, 1972]. Figure 4.9 shows

the resulting function for L = d50 = 0.6 mm. In the experiment the filter screens were

positioned at 6.5 cm and 184.4 cm from the center of the injection well which are indicated

97


0.1

1

10

0 0.5 1 1.5 2

Rey

nold

s nu

mbe

r [-]

Distance from injection well center [m]

6 m3/h3 m3/h

Figure 4.9: Dependency of Reynolds number on r between the two filter screens of thecontainer. Used parameters were:

d50 = 6 · 10−4 m, b = 0.6 m,n = 0.4, ρf = 1 kg/l, µ = 1.003 g/m · s,Q1 = 6 m3/h,Q2 = 3 m3/h,which represent container experiments 1 and 4 for Q1, and 2 and 3 for Q2

by the blue and yellow vertical lines in Figure 4.9. The graph shows that for both injection

rates the Reynolds number is below 10 in the whole domain, although close to the well

the injection rate of 1000 l/h is only just below 10. 60 cm from the injection well screen

it is below 1 for the injection at 1000 l/h and for the injection rate of 500 l/h this is

already after 27 cm.

Injection at 1000 l/h (Exp. 1)

During experiment 1 (Table 4.2) it was possible to get the iron colloids transported over

the full length of the container (Figure 4.10). While visually the window was black

throughout, the sensors showed a large gradient in concentration along the flow path. Vi-

sual observation through the glass plate showed significant retention of nZVI compared to

the injection front which was highlighted by a conservative tracer (Uranine, Figure 4.10b).

The iron front visibly arrived at the outlet side after three pore volumes of suspension

were injected.

98


(a) t = 3 min, Uranine front (green) directly in front of nZVI front(black)

(b) t = 1 PV , Uranine front (green) at outlet, nZVI front (black)progressing slower

(c) t = 2 PV , nZVI front (black) halfway

(d) t = 3 PV , nZVI front (black) close to outflow

(e) t = 3 PV nZV I + 3 PV H2O, nZVI front (black) very stableduring water flush

Figure 4.10: Uranine and nZVI front during the injection at different time intervals. Shown isexperiment 1 at 1000 l/h

99


In Figure 4.11a the magnetic susceptibility is shown as a function of the injection time

for five successive locations inside the container. It shows that at each location the mag-

netic susceptibility initially increases strongly followed by a slight, steady increase until

the injection of the nZVI suspension stopped. This steady increase shows the real break

through curve of nZVI. After the injection with nZVI, the suspension fluid was chased

by degassed tap water, resulting in a drop of the magnetic susceptibility. This drop was

caused due to an influence of the surfactants on the capacity of the coils (Section 2.4.3).

As mentioned before, later the coils were covered with an epoxy resin, which prevents

this jump and drop in the signal. The susceptibility during the water flushing stage re-

mained stable, indicating that the colloids no longer moved and, hence, that the iron

concentration inside the container did not change any more. The magnetic susceptibility

is directly linearly related to the nZVI concentration, as can be seen by comparing the

final magnetic susceptibility after water flushing (Figure 4.11a) with the average of the

measured concentrations through chemical analysis (Figure 4.11b). Therefore, it is also

possible to plot the breakthrough curves directly in concentrations, which was presented

in theory in Section 2.2. It was chosen not to present this for this data set because the

measured susceptibility was biased due to the water chemistry and the concentrations

calculated would easily lead to misinterpretation of the plot.

1

1.01

1.02

1.03

1.04

1.05

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

χ [-

]

Time [h]

r=0.24 mr=0.43 mr=0.80 mr=1.17 mr=1.54 m

(a)

0

5

10

15

20

25

30

0 0.5 1 1.5 2

Sto

tal,

[g/k

g]

Distance from the injection well [m]

r=0.24 mr=0.43 mr=0.80 mr=1.17 mr=1.54 m

(b)

Figure 4.11: (a) Magnetic susceptibility changes during the injection of nZVI (0− 1 h) andwater flushing (1− 2 h, not all shown) of experiment 1. Each coil pair responded differently tothe surfactants, after the water flushing the sensors showed the actual susceptibility withoutinfluence from water chemistry. (b) nZVI concentration inside the coils obtained by chemicalanalysis. From left to right the values represent the sensors at different distances; the final

susceptibilities are directly related to the average values of the chemical analysis

100


Reproducibility of the container experiments (Exp. 1 & 4)

The conditions of experiment 4 were chosen identical to the conditions of experiment 1

to test the reproducibility of the experiments. The boundary conditions of both experi-

ments were not exactly the same, it is with experimental investigations nearly impossible

to perform an experiment twice with exactly the same boundary conditions. The main

deviations determined for these experiments were the dispersing unit and the input con-

centration of the nZVI suspension.

In a visual comparison (Figure 4.12), the transport distances of both experiments are

similar but not identical, experiment 4 shows higher concentrations and a sharper front.

Unfortunately, a comparison of the break through curves of the inductive iron detectors

could not be performed because the datasets were corrupted during saving.

A comparison of the concentrations obtained in the chemical analysis of the soil sam-

ples taken during excavation is shown in Figure 4.13. Looking at the average of these

measurements, it can be seen that the transport of experiment 4 to a large extend repli-

cated the results of experiment 1. The measured values all are on average a little higher,

this is mainly due to the higher concentration of nZVI injected. During experiment 1, the

dispersing was done using the much smaller IKA machine as compared to the large CAT

machine used in experiment 4. In experiment 4 the concentration at three different levels

inside the filter sand of the injection well was measured additionally. Even though some

iron is located inside the filter sand, the concentration is low compared to the concen-

trations at 20 cm from the injection well. A risk of well clogging is based on these data

minimal for this material, and the filter sand worked well to provide a good connection

between the injection well and the porous medium.

It can be seen that the measuring technique to analytically determine the nZVI con-

centrations inside the soil samples (Figure 4.13) has been improved significantly since

the first experiment, the measured concentrations for each location have a much smaller

deviation. During the first experiment this measuring set up was still in a testing state,

whereas from experiment 2 on the set up was replaced by the one described in Section 2.6.

Influence of Different Injection Rates (Exp. 3 & 4)

Experiments 3 and 4 are here compared to discuss the influence of the injection rate on

the transport in a radial flow field. In Figure 4.14 the final iron distribution can be seen

for both experiments. In experiment 4 (1000 l/h) the iron is transported slightly further.

101


Figure 4.12: Final transport results of the two container experiments performed at 1000 l/h,top: experiment 1, bottom: experiment 4

0

5

10

15

20

25

30

0 0.5 1 1.5 2

Sto

tal [

g/kg

]

Distance from injection well [m]

Exp. 1: 1000 l/hExp. 4: 1000 l/h

Figure 4.13: Chemically analyzed iron concentrations at different locations in the containerobtained from soil samples taken during excavation

102


Looking at the chemically analyzed soil samples (Figure 4.15) the injection at experi-

ment 3 (500 l/h) shows higher concentrations closer to the well. Further from the well,

the concentrations are very similar.

The differences in concentrations close to the well are in accordance with the hypothesis

that the transport of nZVI is mainly influenced in this region. Nevertheless, since the

concentrations in experiment 4 (1000 l/h) are lower in the vicinity of the well and thus

the danger of clogging is reduced, this higher injection rate has to be preferred.

Pulsating Flux Pump vs. Continuous Flux Pump (Exp. 2 & 3)

The flow rate in experiment 2 was discontinuous and the pressure relaxed from 10 to

0 bar during each pulse, therefore the flow rate of each pulse was higher at the beginning

of the pulse and lower at the end. This resulted in a very erratic flow regime. Although

the high pressure that was induced at each pulse of the membrane pump (∼ 10 bar) was

higher than the designed limit of the container (1 bar), this pressure only existed for a

very short time at the beginning of each pulse and no leakage problems arose.

In both the photographs in Figure 4.16 and the chemical measurements presented in

Figure 4.17 it can be seen that the pulsating injection provided a poorer transport result.

From the pulsating flux pump (Exp. 2), nZVI was mainly retained close to the well and

there was a fairly sharp front. Applying the continuous flux pump (Exp. 3), the transport

of nZVI was better and the front was less sharp.

From these results it can be concluded that the pulsating pumping technique did not

provide the improved transport of nZVI as was hypothesized. A possible cause could be

that in the interval between the pulses the colloids can sediment out of the suspension

faster due to the lack of shear forces and that the increased shear rate at the beginning

of each pulse was not high enough to remobilize the attached or sedimented colloids.

Summarizing the Findings

The comparison of experimental results was difficult because beside the desired change of

one boundary always other boundary conditions changed as well. The main discrepancy

was the inconsistency of the input concentrations, which was expected to have affected the

final results significantly. The injections showed that transport over a distance of nearly

two meters was possible. Each of the injections of nZVI was followed by an equal volume

of fresh water, visually no change in the distribution could be observed, further research

could possibly provide a more conclusive statement with respect to the exact reason for

103


Figure 4.14: Comparison of the final transport result of the container experiments performedat 500 l/h (Exp. 3) and 1000 l/h (Exp. 4)

0

5

10

15

20

25

30

35

40

0 0.5 1 1.5 2

Sto

tal [

g/k

g]


Exp. 3: 500 l/hExp. 4:1000 l/h

Figure 4.15: Chemically analyzed final nZVI concentration distribution of two differentinjection rates

104


Figure 4.16: Comparison of the final result after three pore volumes of injected suspension inthe container experiments with the pulsating membrane pump and the continuous flux pump.

Both performed at 500 l/h

0

5

10

15

20

25

30

35

40

45

0 0.5 1 1.5 2

Sto

tal [

g/kg

]


Exp. 2: PulsatingExp. 3: Continuous

Figure 4.17: Chemically analysed final nZVI concentration distribution of two differentpumping techniques

105


the immobilization of nZVI during water flushing. It was also shown that a continuous

flux is preferable over a pulsating flux for injection. The influence of the injection rate is

less pronounced in the large scale experiments than in the column experiments due to the

hyperbolically decreasing seepage velocity in a radial flow field. Nevertheless the injection

at the higher injection rate performed slightly better. Especially the concentrations close

to the well were lower, avoiding the risk of clogging.

4.4 Discretized Radial Flow Field Reproduced with

Columns

4.4.1 Motivation

The container experiment is a very useful tool to provide insight into the impact of real

field scale methods like pumps used and large suspension volumes preparation on the

transport of nZVI. The experiments on the other hand are also very labor intense and

costly. For a quick screening of applicability of a certain nZVI, porous medium or injection

rate, the container experiment would simply take too much time and effort. Therefore

simplified quick screening methods were developed.

The first to be developed was an experimental method to approximate the results

of full scale radial nZVI injections by discretizing the full radial flow field into hollow

cylinder segments and representing each of these with 1-D column experiments using sets

of multiple subsequent column experiments with the appropriate boundary conditions

[de Boer et al., 2008; Estrella, 2011a]. The measured concentration profile from each

column was assumed to represent the concentration profile of that section of the radial

flow field. This would allow for the quick approximation of a nZVI injection using only

column experiments. The method was tested and validated against the results of two

of the near field scale container experiments performed with the continuous flux dosing

pump described before (experiments 1 and 3).

4.4.2 Concept

Equations were derived to discretize a two dimensional radial flow field into a series of

sections (as presented in Figure 4.18). These equations were derived so that the boundary

conditions from a full scale radial flow system could be applied to a discretization with

any number of columns.

106

4.4. Discretized Radial Flow Field Reproduced with Columns

To implement the boundary conditions of radial flow to one dimensional columns, a set

of equations was set up. These apply the average Darcy velocity across sections of the

flow field to columns of the same length as the distance between the two radii of each

section (as presented in Figure 4.19).

Derivation

An injection well is chosen to be fully screened over the thickness of a confined aquifer

and therefore the velocity decreases by 1r

with increasing distance r from the injection

point, resulting in a radial flow field, as follows from continuity (Equation 4.4). The

derivation is graphically depicted including the nomenclature of all the notations used in

Figure 4.18.

The 2-D flow field was discretized in ring-shaped sections (Figure 4.18). It was chosen

to do this such that the average velocity over each section maintains the same ratio, ξ, to

the velocity of the next section (the ratio ξ does not have to be a constant, refinements

of the discretization are for example possible but not aimed for in this derivation).

qi = ξ qi+1 (4.10)

Where i refers to one section and i + 1 refers to the next one (away from the injection

well). The average velocity in each section can be calculated as an arithmetic mean of

the integrated continuity equation (eq. 4.4).

qi =1

ri+1 − ri

∫ ri+1

ri

q(r) dr (4.11)

the radii ri+1 refers to the boundary between adjacent segments i and i+ 1.

To describe the transport of nZVI the mass flux, M , is considered:

M =∆M

∆t(4.12)

where ∆M is the total mass transported in time ∆t.

Mass flux can also be described as a function of concentration and volume flux:

Mi = Ci Vi (4.13)

where Ci is the concentration of the suspension at the boundary ri and Vi the volume

flux through the boundary at ri.

107


µ

µ

µ

- - -

µ

µ

R

R

R

Vi+1

Vi

Cini

Couti

Cini+1

Couti+1

CinN

qi

qi+1

qN

Mi Mi+1MN

ri

ri+1

rN

∆ Mi

∆ ti

∆ Mi+1

∆ ti+1

-

- --

-

- -

--

Cini

Cini+1 Cin

N

Mi Mi+1 MN

qi qi+1 qN

Couti+1Cout

i

Vi Vi+1

∆Mi

∆ti

∆Mi+1

∆ti+1

ri ri+1 rN

r0

6

6

Ji

Ji+1

r0

--

- - -JNJi+1Ji

1

Figure 4.18: Graphical overview of the nomenclature of all the notations used for thediscretization of transport in a radial flow field. The rectangle shows the cross section of the

top view, relation of both figures is 1:1

108


The volume flux can also be rewritten in terms of the Darcy velocity due to continuity:

Mi = Ci Q (4.14)

Mi = Ci qi Ai (4.15)

where Ai is the cross-sectional area of the boundary at ri.

Although the mass flux is a constant throughout the system, the mass flux density (J)

is not. Mass flux density can be described as follows:

J =M

A(4.16)

The ratio of the mass flux density from one radius to the next can be derived as follows:

Mi = Mi+1 (4.17)

JiAi = Ji+1Ai+1 (4.18)

Ji+1 =AiAi+1

Ji (4.19)

Ji+1 =2πbri

2πbri+1

Ji (4.20)

Ji+1 =riri+1

Ji (4.21)

Because the mass flux density (Equation 4.16) can also be described by the Darcy velocity:

J =CQ

A= Cq (4.22)

Equation 4.21 can be rewritten as (for this derivation it was assumed that the mass flux

is conservative, otherwise sink terms would have to be added to this set of equations):

Ji+1 =riri+1

Ji (4.23)

Cqi+1 =riri+1

Cqi (4.24)

qi+1 =riri+1

qi (4.25)

qi =ri+1

riqi+1 (4.26)

109


The ratio, ξ, as introduced in Equation 4.10 is thus given by:

ξ =ri+1

ri(4.27)

Experimental Application

Calculation of the appropriate experimental conditions is necessary to accurately dis-

cretize a radial flow field of a field application or a large scale radial flow experiment into

1-D column experiments.

Equation 4.4 was used to calculated the average Darcy velocity between two radii as

follows:

qi =1

ri+1 − ri

∫ ri+1

ri

Q

2πrbdr

=Q

2πb(ri+1 − ri)

∫ ri+1

ri

1

rdr

=Q

2πb(ri+1 − ri)[ln |r|

]ri+1

ri

=Q

2πb(ri+1 − ri)ln |ri+1

ri|

=Q

2πb(ri+1 − ri)ln |ξ| (4.28)

An example of the average Darcy velocity over three different sections in a radial flow

field is also given in Figure 4.19a.

The radii for each column can now be calculated such that the ratio ξ, is consistent

throughout the entire domain. Given the well radius r0 (thus r0 > 0), the outer radius

of the full domain rN and the desired number of discretization sections or columns N , ξ

can be calculated. From the definition of Equation 4.27, the following definition of ξ can

be derived using r0, rN and N , to explain, first r0, r1 and r2 are substituted:

r0

r1

= ξ

r1 =r0

ξ

r2 =r1

ξ=

r0ξ

ξ=r0

ξ2(4.29)

110


thus:

rN =r0

ξNand:

ξ =( r0

rN

) 1N

(4.30)

Using Equation 4.28 and the radii, r0 . . . rN , the average Darcy velocity in each column

can be determined. To determine the required flow rate for each column, Qcolumni , the

average Darcy velocity must be multiplied by the cross sectional area of the column,

Acolumn:

Qcolumni = qiAcolumn (4.31)

The volume of the solution injected into the full radial system is determined by the

number of pore volumes. The time for one pore volume (PV ) to be injected at the given

flow rate Q is calculated as follows:

V1PV

Q= t1PV (4.32)

Where V1PV is the pore volume of the full system (from r0 to rN), and t1PV is the time

required for the injection of one full system pore volume.

The total time of injection for the first segment is determined by multiplying the time

for one pore volume by the desired number of pore volumes. Each subsequent segment

will have a shorter injection duration, the duration of the previous segment minus the

residence time of that previous segment. Time for subsequent segments can thus be

calculated as follows:

ti+1 = ti −V1PVi

Q(4.33)

where ti is injection time for segment i and ti+1 that of the subsequent segment and V1PVi

the pore volume of segment i.

The injection volumes for each column that represents a segment can be calculated by

combining Equation 4.31 to calculate the injection rate of each column and Equation 4.33

to calculate the injection duration for each column:

Vi = Qcolumni · ti (4.34)

111


where Vi is the suspension volume to be injected into column i.

Either the initial concentration of the first column or the effluent concentration of the

previous column should be used as the input concentration. This then replicates the

concentration reduction over a given radius and satisfies mass conservation throughout

the system.

4.4.3 Methods

The porous medium description and suspension preparation of Section 3.6.1 are applicable

for these experiments as well. The column experiment set up was identical to set up

described in Section 3.6.1, except for the lengths of the columns which were changed

to fit the length of each of the discretized sections (Figure 4.19b). The first column

of a set was injected for the full duration of a full radial injection, each subsequent

column injection was shorter according to Equation 4.33. To satisfy the mass balance,

the correct suspension concentration must be injected into each column in the set, the

volume necessary for each subsequent column is smaller though. When thinking about

the discretization, the total mass of nZVI in the effluent of each segment goes into the

next segment. Therefore, the effluent of a column was collected and well mixed, to get

a homogeneous suspension of which the necessary volume for the next column in the set

was taken. Liquid samples were taken for chemical analysis prior to injection at the inlet

of the first column and after each column injection from the homogenized effluent.

The radial flow container experiment is a 60° wedge of a full radial flow system, and

0

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Dar

cy v

eloc

ity [m

/s]

Distance from the injectionwell [m]

Darcy velocityAverage Darcy velocities

(a) (b)

Figure 4.19: (a)Darcy velocity in a radial flow field and the average Darcy velocities in adiscretization into 3 sections. (b)Three columns of different length

112


therefore the injected flow rate is only 16th of a full size injection. When using the

presented equations to replicate the radial flow experiment, the full size flow rate Q, must

be used for calculation of the proper Darcy velocity instead of the experiment size flow

rate Qexp, thus: 6 ·Qexp = Q.

While packing the column experiments and container experiment with exactly the same

sand, the two different packing methods result in differences in porosity. The packing

method for the columns has provided very consistent porosities in the columns of 0.35,

the porosity in the radial flow container experiment is less consistent though with 0.40 on

average a bit higher. This means that with equal Darcy velocities, the seepage velocity will

be different in both experimental set ups. Because the filtration theory showed that the

transport of nZVI depends on the seepage velocity (Section 3.2.3), the Darcy velocities in

the column experiments must be calculated such that the seepage velocities are the same

as those of the container experiment. The average Darcy velocity within one segment is

calculated according to Equation 4.28, next this value is divided by the porosity of the

container and multiplied by the porosity of the column (Equation 4.35), the rest of the

equations use the new adjusted Darcy velocity.

qcolumn =qcontainerncontainer

ncolumn (4.35)

The metal detector, as described in Section 2.3, was used to record the concentration

profiles of each of the columns in the set.

4.4.4 Conditions

In preliminary tests it was determined that a discretization of three columns provided

the most accurate representation. Experiments with more columns (up to seven in one

set was tested) introduce too many boundary effect at the column in- and outlet, and the

experimental duration becomes too long. Because each column needs to be injected for the

same duration, the experimental duration becomes as many times the full scale duration,

and it can no longer be assumed that the suspension is fresh in the last columns. Using

only one column was also tested to represent the whole full scale system, this showed to

be non mass conservative and provided a high overestimation of the transport distances.

Therefore the comparison of the discretized column experiments were performed using

sets of three columns.

The boundary and initial conditions of radial flow container experiments 1 and 3 were

used as previously described in Section 4.3, with all the conditions in Table 4.2. The

113


parameters of each of the column sets to represent the container experiments are given

in Tables 4.3 and 4.4.

Table 4.3: Parameters for column set 1 (number of discretization segments: N = 3)representing container experiment 1 with Qexp = 1000 l/h

Column number 1a 1b 1c

Start radius [m] r0 = 0.065 r1 = 0.196 r2 = 0.591

End radius [m] r1 = 0.196 r2 = 0.591 r3 = 1.780

Column length [m] 0.131 0.395 1.189

Average seepage velocity [m/s] v1 = 9.31 · 10−3 v2 = 3.09 · 10−3 v3 = 1.03 · 10−3

Average Darcy velocity column [m/s] qcolumn1 = 3.26 · 10−3 qcolumn

2 = 1.08 · 10−3 qcolumn3 = 3.59 · 10−4

Average Darcy velocity container [m/s] qcontainer1 = 3.73 · 10−3 qcontainer2 1.24 · 10−4 qcontainer3 4.10 · 10−4

Column flow rate [ml/min] Qcolumn1 = 227.5 Qcolumn

2 = 75.5 Qcolumn3 = 25.0

Injection time [min] t1 = 56.4 t2 = 56.1 t3 = 54.0

Injection volume [l] V1 = 11.22 V2 = 3.71 V3 = 1.18

Pore volume of column [l] 0.05 0.14 0.42

Number of pore volumes injected [−] 240.59 26.37 2.79

Porosity of column [−] 0.35 0.35 0.35

Table 4.4: Parameters for column set 3 (number of discretization segments: N = 3)representing container experiment 3 with Qexp = 500 l/h

Column number 3a 3b 3c

Start radius [m] r0 = 0.065 r1 = 0.196 r2 = 0.591

End radius [m] r1 = 0.196 r2 = 0.591 r3 = 1.780

Column length [m] 0.131 0.395 1.189

Average seepage velocity [m/s] v1 = 4.66 · 10−3 v2 = 1.55 · 10−3 v3 = 5.13 · 10−4

Average Darcy velocity column [m/s] qcolumn1 = 1.63 · 10−3 qcolumn

2 = 5.41 · 10−4 qcolumn3 = 1.79 · 10−4

Average Darcy velocity container [m/s] qcontainer1 = 1.86 · 10−3 qcontainer2 = 6.18 · 10−4 qcontainer3 = 2.05 · 10−4

Column flow rate [ml/min] Qcolumn1 = 99.55 Qcolumn

2 = 33.03 Qcolumn3 = 10.96

Injection time [min] t1 = 112.7 t2 = 112.3 t3 = 108.0

Injection volume [l] V1 = 11.22 V2 = 3.71 V3 = 1.18

Pore volume of column [l] 0.05 0.14 0.42

Number of pore volumes injected [−] 240.59 26.37 2.79

Porosity of column [−] 0.35 0.35 0.35

114


4.4.5 Results & Discussion

The results of both the radial flow experiments and the columns experiments are displayed

in Figures 4.20 and 4.21. The values from the container experiments are the average values

of the measurements taken at each radius analyzed using the hydrogen production method

(Section 2.6). The error bars represent the minimum and maximum values measured at

each point.

The inflow concentrations of the suspensions injected into the container and the first

column of each set are also provided in these plots, because the inflow concentrations were

not always successfully matched (Table 4.5). Mainly this was related to the concentration

of the base suspension, which was subject to heterogeneities and uneven distribution

during storage. The measured iron content (Stotal) was nevertheless chosen to be shown

instead of normalized values because normalized plots would not show the predictive

capacity of the method.

The iron concentration profiles were reasonably close to those of the container, although

not exact or always fully within the standard deviation of the measured values. The most

likely cause for these discrepancies would be the differences in the input concentrations.

This effect is clearly observed when comparing the results of the last columns from both

sets. In column set 1 the input concentration was higher than in the container, as was

the profile of the last column, whereas in column set 3 the input concentration was lower,

and lower values were observed.

Table 4.5: Chemically measured input and effluent concentrations of the container and columnexperiments

Experiment Cinput [g/l] Ceffluent [g/l]

Container 1 8.3 N.N.

Column 1a 10.12 9.97

Column 1b 9.97 8.83

Column 1c 8.83 0.21

Container 3 10.5 N.N.

Column 3a 8.00 5.69

Column 3b 5.69 2.71

Column 3c 2.71 0.20

115


0

5

10

15

20

25

30

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Sto

tal [

g/kg

]

Distance from the injection well [mm]

3 Column Experiment (Cinput = 10.1 g/l)Container Exp. 1 (Cinput = 8.3 g/l)

Figure 4.20: nZVI concentration profiles from column set 1 compared to measurements fromradial flow experiment 1. Both experiments simulated a field injection rate of 6000 l/h using

RNIP nZVI suspensions into a confined aquifer. From left to right: column 1a, 1b and 1c

0

5

10

15

20

25

30

35

40

45

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Sto

tal [

g/kg

]


3 Column Experiment (Cinput = 8.0 g/l)Container Exp. 3 (Cinput = 10.5 g/l)

Figure 4.21: nZVI concentration profiles from column set 3 compared to measurements fromradial flow experiment 3. Both experiments simulated a field injection rate of 3000 l/h using

RNIP nZVI suspensions into a confined aquifer. From left to right: column 3a, 3b and 3c

116


Conservation of Mass

To prove that the discretization method is valid, it is necessary to show that the system

is mass conservative and the storage and transport value represent accurately the ratios

in an actual radial flow system. The total mass in an actual radial system was calculated

two different ways: using the metal detector measurements and using the chemical data.

First the mass in each column was calculated using the volumes and concentrations

of the in- and outflow. This total mass was then divided by the dry mass of soil within

the column to obtain a ratio in grams of iron to kilograms of soil. This ratio was then

multiplied by the mass of soil in that section of a 0.6 m thick radial system. This yields

the total iron storage within a full radial system. Volume and concentration of the outflow

were then used to calculate the total mass of iron to leave the system. The storage and

outflow mass were then summed and compared to the injected mass, or the injected

volume of 6000 l multiplied by the measured input concentration.

The same method was used a second time, but the iron to dry soil ratio was calculated

from the average metal detector reading in that section. It should be noted that this cal-

culation is still partially dependent on the chemical analysis because it uses the measured

input concentration and the effluent concentration to close the system.

The calculation of M inputtotal iron was performed by multiplying the input concentration by

the theoretical full scale injection volume minus the mass lost in the effluent.

M inputtotal iron = (Cinput − Ceffluent)Qfull scalet (4.36)

where The calculations of M storedtotal iron were performed by multiplying the total measured

iron content with respect to the column volume by the total volume in a full radial system.

M storedtotal iron = πb

(rN

2 − r02) ∑

1→N

(∑bcolumn,i

Stotalρbπ4d2

column∆xπ4d2

columnLcolumn,i

)(4.37)

where N is the number of columns, dcolumn the diameter of the column and Lcolumn,i is the

length of column i, bcolumn,i is the total number of data points of the concentration profile

along column i, and ∆x the distance between two data points. The coefficient to convert

the metal detector readings to iron content was the same for all experiments, therefore

the measured iron content is not dependent on the measured liquid concentrations and

these two values can be compared.

The results of the mass balance calculations confirm that the iron content profiles

117


satisfy mass balance when converted to a full radial system (Table 4.6).

Table 4.6: Mass balance calculations compared the calculated mass storage in a full radialsystem from both the liquid concentrations of the in and outflow, and the metal detector

readings

Column Set M inputtotal iron [g] Mstored

total iron [g] Percent Error

from inflow - outflow from Stotal

1 53526 53606 0.10%

3 42186 41838 -0.80%

Errors in the Concentration Profiles

Measurements of the iron concentration profiles with the metal detector result in some

errors, especially associated with the boundaries of columns, which for short columns

are much more prominent and can unfortunately dominate the measurement. The most

prominent error is (I) the peak in nZVI concentration in the direct vicinity of the

inlet, as opposed to directly at the inlet, where the peak concentration would be expected.

As the metal detector moves from the filter to the porous media, it detects nZVI only

on one side, therefore the reading will be lower than when it is one or two centimeters

farther and is completely surrounded by sand that contains iron. This is most prominent

with very short columns where the first two centimeters accord to a significant portion of

the column, in columns of one meter or more this effect is negligible. So far no reliable

methods were found to automatically and scientifically acceptable convert the recordings

in the vicinity of the inlet and outlet. Therefore it was chosen to keep the data as it was

recorded. For long columns the induced error is negligible, only with very short column

this measuring artefact can induce a significant error. For short columns it could be

discussed if manual adjustment of the recordings as shown in Figure 4.22 is justifiable.

The metal detector reading was (II) transformed using data from the chemical anal-

yses for each experiment, errors in the chemical analysis thus directly transfer into the

concentration profiles and mass balances. The transformation factor was calculated from

the input and effluent concentration of the second column of each set and this factor was

then applied to all columns of the set, which for these two experiments was identical.

The chemical analysis using the photometer is highly accurate, though, the method

as a whole does have some error associated with it. The photometer itself (given it is

correctly calibrated) has negligible error, but the method has some error associated with

118

4.5. Numerical Simulations

0

10

20

30

40

50

60

0 50 100 150 200 250

Sto

tal [

g/kg

]


3 Column Experiment (Cinput = 8.0 g/l)Adjusted 3 Column Experiment (Cinput = 8.0 g/l)

Container Exp. 3 (Cinput = 10.5 g/l)

Figure 4.22: Manual adjustment of the recording at the vicinity of the inlet and outlet of thefirst column of set 3. Both profiles represent the same total mass

it because very small volumes from the original sample (100µl) can only be tested in

the photometer. The difficulty of this method thus lays in taking a fully representable

sample. This error is even more prevalent in samples with higher concentrations, such as

the samples from the base solution, since they have to be diluted in several steps, each

step with an error associated due to the difficulty of taking a representative sample. For

samples with lower concentrations, such as those of the effluent, the method would thus

be best suited.

4.5 Numerical Simulations

4.5.1 Motivation

The third method is a combination of numerical simulations and column experiments to

determine the transport distance and concentration profile in a radial flow field.

The transfer of the numerical model with fitting parameters from the column experi-

ments of Section 3.7 into a radial flow system was therefore explored [de Boer et al., 2008;

Estrella, 2011b]. The basis of the new injection model for a radial flow field was the trans-

port description in 1-D as described in Section 3.5, combined with the fitted parameters

and relationships obtained from fitting the 1-D finite difference model (implemented in

119


Matlab) on the concentration profiles of column experiments. The Matlab model used

three fitting parameters to produce the transient nZVI concentration profiles along the

two meter long columns.

4.5.2 Solver

In order to broaden the application and robustness of the mathematical model and to

obtain more stable solutions in a more complex geometry the 1-D finite elements Matlab

model used for the calibration of column experiments was transferred to a solver which

can deal with 2-D and 3-D geometries. The solver also uses the finite element method

and can deal very well with curves and grid refinements in the more critical areas and

therefore provides stable solutions in a radial flow field. Furthermore the transfer into

this solver provides to possibility to run the numerical model on much more complex

geometries or hydraulic conductivity fields.

For the implementation of this mathematical model, FEniCS was selected. The FEniCS

Project focusses on the solution of differential equations by the finite element methods

[Logg et al., 2011].

Implementation in FEniCS

In general, implementation of a mathematical problem in FEniCS can be performed by

the following steps [Logg et al., 2011]: (I) Define the partial differential equation (PDE)

and the appropriate boundary conditions. (II) Reformulate the PDE as a variational

problem. (III) Define all initial and boundary conditions, and a mesh for the domain

Ω. (IV) Add any necessary statements for the solution of the variational problem and

calculate all necessary information for presentation. (V) Graphically represent the results

using ParaView and Gnuplot.

Definition of the PDE and Boundary Conditions

There are two PDEs that must be solved for this problem: (I) the flow problem with

the appropriate boundary conditions, and (II) the transport problem using the velocity

calculated from the flow problem.(I) The flow problem is defined by equation 4.1. Two

boundary conditions were implemented for the flow problem. The first is a Neumann,

constant flux, boundary condition applied at the injection well using the Darcy velocity

at the well screen (6.5 cm from the center of the well) corresponding to the given flow

120


rate. A Dirichlet, constant head, boundary condition was applied to the outer edge of

the domain at a radial distance of 1.78 m from the well screen.

(II) Next the PDE for nZVI transport was defined after Equation 4.8. The only differ-

ence is that in this case the seepage velocity v, is calculated from the gradient of h, the

solution of the flow problem.

∂C

∂t= −C∇ ·

(K

n∇h)−(K

n∇h)∇C +∇ · (D∇C)−(

3(1− n)αη0(Kn∇h)

2dc

)(1− S

S0max + Sr

)C −(

3(1− n)αaggηagg0

(Kn∇h)

2dc

)C (4.38)

The boundary condition at the injection well screen applied to this problem was a

Dirichlet, constant concentration:

C(t)|r0 = Cinput (4.39)

The boundary condition at the outer boundary was Neumann, zero normal derivative of

the concentration:

∇C · n = 0 (4.40)

where n is a normal positive outward unit vector.

Reformulation of the PDEs as Variational Problems

The general method for reformulating a PDE into a variational problem consists of the

following steps [Donea and Huerta, 2003; Logg et al., 2011]: (I) Multiply the whole

PDE by the test function, here denoted by ω. (II) Integrate the PDE over the

domain Ω (III) Perform integration by parts on terms with second order derivatives

The new condition defined for the variational formulation was the Neumann boundary

condition of prescribed flux fn, which is defined as a piecewise function on the domain

boundary (fn = fn(r, θ, z)) which was integrated over the surface of the boundary (Sb).

The variational formulations are given in equations 4.41 and 4.42. Equation 4.41 was

121


solved as a steady state problem, so there is no time dependency.∫Ω

ωK∇h dΩ =

∫Sb

ωfn dSb (4.41)

Equation 4.42 is time dependent, therefore the solution of C is defined for both the

current and previous time steps as Ct and Ct−1

∫Ω

ωCt−1dΩ =

∫Ω

ωCt dΩ +

∫Ω

ω

(K

n∇h)· ∇Ct dΩ

−∫

Ω

∇ω · (D∇Ct) dΩ

+

∫Ω

ω3(1− n)αη0

(Kn∇h)

2dc

(1− St−1

S0max + St−1

r

)Ct dΩ

+

∫Ω

ω3(1− n)αaggηagg0

(Kn∇h)

2dcCt dΩ (4.42)

Additional Equations and Statements

Several additional calculations are made within the model, both for the solving of the

PDE, as well as presentation of the results. At each time step and location within the

domain, the values of S and Sr are calculated based on the removal of nZVI during the

previous time step. Sr is now calculated following:

Sr =n

ρbkaggatt C

t−1dt+ St−1r (4.43)

where ρb is the bulk density of the soil [ML−3], and kaggatt is the removal coefficients of the

aggregates [−] as presented in Equation 3.15. The calculation of S is calculated similarly

such that the removal of iron due to the constant removal and colloid terms are combined,

yielding equation 4.44.

S = Sc + Sr (4.44)

where

Sc = St−1c +

n

ρb

(3(1− n)αη0v

2dc

)(1− St−1

c + St−1r

S0max + St−1

r

)Ct−1dt (4.45)

122


These equations are formulated in this manner because S0max corresponds to the maximum

possible removal due to the colloid removal term acting on the colloids. A conditional

statement was then implemented to limit the value of Sc at S0max.

For the presentation of the final iron content profiles, C was converted into gironkgdrysoil

and added to S. This was necessary because the results of the column and container

experiments, the total iron, including that of the liquid phase, was measured. Therefore,

Stotal is calculated as shown in Equation 4.46.

Stotal =

(n

ρbC + S

)1000 (4.46)

where the factor 1000 accounts for the conversion form kg to g.

Definition of the Mesh

The mesh (grid) was defined according to the dimensions of the porous medium in the

container experiment. Divisions were made in the radial and angular directions. An

example of the layout of the mesh is displayed in Figure 4.23, this mesh shows 25 divisions

with respect to radius and 10 with respect to angle. All simulations were performed on a

mesh of 500 divisions in the radial direction and 50 in the angular.

Figure 4.23: Example mesh with 25 divisions in the r direction and 10 in the θ direction, thecalculations were performed at a much finer discretization (500 in r, 50 in θ)

123


4.5.3 FEniCS vs. Matlab

Before the FEniCS model was applied to radial flow around an injection well, simulations

were run with a constant velocity in 1-D in order to compare, while using the same input

parameters, the results from the FEniCS model to those of the Matlab model. Using the

parameters in Table 4.7, simulations were performed with both models and the results are

plotted against each other in Figure 4.24. This proves that the solution in both models

are the same within reasonable error, while using very different numerical solvers.

Table 4.7: Parameters used for the comparison simulation of the models in Matlab and FEniCS

Parameter Value

Input concentration [g/l] 11.25

Column length [mm] 2000

Grid size [mm] 1

Porosity [−] 0.34

Seepage Velocity [m/s] 1.43 · 10−3

S0max [g/kg] 1.06 · 10−2

α [−] 8.63 · 10−1

αagg [−] 1.8 · 10−2

∆t [s] 30

0

5

10

15

20

25

30

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Sto

tal [

g/kg

]


FEniCs Simulation, t=3000s, t=6000s, t=9000sMatlab Simulation, t=3000s, t=6000s, t=9000s

19.9

20

20.1

800 805 810

Figure 4.24: Comparison between three transient nZVI concentration profiles of the Matlaband FEniCS models, with an inset zooming in on the results

124


4.5.4 Results

Using the FEniCS model, forward simulations were run with the initial parameters and

boundary conditions of container experiments 1, 3 and 4. Container experiment 2 was

not simulated because that was performed with a pulsating flux pump.

Container Experiment 1

The input parameters for experiment 1 can be found in Table 4.2. These parameters were

then set in the FEniCS model in order to compare the forward simulation results to those

of the container experiment.

As previously discussed, the FEniCS model uses both a flow and transport equation.

The flow equation was solved for head distribution, then the vector field of the gradient

of h was used in the advective term of the transport equation. This head distribution

can be found in Figure 4.25. The result of the final nZVI distribution can be found in

Figure 4.26.

In order to compare the results shown in Figure 4.26 to the container experiment, Stotal

was plotted with respect to radial distance from the center of the well (Figure 4.27).

The results with respect to radial distance are plotted with the average, minimum, and

maximum values of measured nZVI concentrations from container experiment 1.

Based on the comparison in figure 4.27, the FEniCS simulation fits very well within

the measurements. The largest residuals seem to be between the values at 800 mm, but

the simulation results still lie well within the measured values. It is also to important to

note that the final transport distance seems to be very close to the observed values.

Figure 4.25: Head distribution from FEniCS simulation of container experiment 1

125


Figure 4.26: nZVI distribution from FEniCS simulation of container experiment 1

0

5

10

15

20

25

30

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Sto

tal [

g/kg

]


FEniCs SimulationContainer Experiment

Figure 4.27: FEniCS simulation and results from container experiment 1

126



The input parameters for experiment 3 can be found in Table 4.2. These parameters were

then set in the FEniCS model in order to compare the forward simulation results to those

of the container experiment.

The head distribution calculated by FEniCS can be found in Figure 4.28. The result

of the final nZVI distribution can be found in Figure 4.29.

In order to compare the results shown in Figure 4.29, Stotal was plotted with respect to

radial distance from the center of the well. In Figure 4.30, these results with respect to

radial distance are plotted with the average, minimum, and maximum values of measured

nZVI concentrations from container experiment 3.

The FEniCS simulation fits the observed data for experiment 3 very well The largest

discrepancy is located at 400 mm. The results from the other measuring points in com-

parison to the model are very close to each other. The final transport distance calculated

appears to be a bit shorter since around 1200 mm the measurements from the container

still showed to contain iron where the model already is almost at zero. A slight underes-

timation of the front progression thus occurred in this simulation.

Figure 4.28: Head distribution from FEniCS simulation of container experiment 3

127



0

5

10

15

20

25

30

35

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Sto

tal [

g/kg

]



Figure 4.30: Fenics simulation and results from container experiment 3

128



0

5

10

15

20

25

30

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Sto

tal [

g/kg

]



Figure 4.32: FEniCS simulation and results from container experiment 4

129



The input parameters for experiment 4 can again be found in Table 4.2.

The head distribution calculated by FEniCS was identical to the head distribution of

container experiment 1, and can thus be found in Figure 4.25. The result of the final

nZVI distribution can be found in Figure 4.31.

The results from the simulation of experiment 4 are very close to the observed values.

The largest residuals are located at around 200 mm and 400 mm, but they are still within

the error limits of the chemical measurements. At all other points of the simulation

data not only fit within the maximum and minimum values, but intersect the average

measurement values.

4.5.5 Discussion

The implementation of the governing nZVI transport equation into FEniCS was success-

ful, and the comparison of the results to the calculations from the Matlab model clearly

demonstrated that the solution calculated by both solvers was identical. The subsequent

transfer of the FEniCS model to two dimensions assumes that the calibrated parameters

hold true as the flow properties change. This assumption is also supported by the lack

of any clear correlations between the fitting parameters and seepage velocity. This indi-

cated that changes in velocity are accurately accounted for by the function for collector

efficiency, η0 and ηagg. Based on the good correlations between the forward FEniCS sim-

ulations and the measured data from the container experiments, it can be stated that

these calibrated parameters are indeed transferable to different conditions.

Another important point of discussion is the further application of these calibration

parameters to other materials. These calibrations were performed only with one combi-

nation of sand and iron particles. Some of the soil and iron suspension properties, such

as particle size, density, and viscosity, are accounted for in the equation for single particle

collector efficiency, η0 and ηagg, but the effects of these changes on the calibration param-

eters is not known. Future research with different nZVI suspensions and soils would have

to determine the dependence of these fitting parameters on the nZVI-soil combinations.

This does not mean that this model cannot be used for other materials; it means only

that these parameters may need to be derived from a set of column experiments, where

parameter correlations can be investigated. Information for a specific soil-nZVI combina-

tion can be obtained by 3−6 two meter column experiments with concentrations ranging

from 1− 30 g/l.

130

4.6. Comparison of Radial Flow Simulations Methods

4.6 Comparison of Radial Flow Simulations Methods

All three techniques presented in this chapter have their pros and cons.

The final transport distance is one of the most important pieces of information because,

in application of nZVI as a remediation technique, it determines the required distance to

the next well while maintaining a minimum nZVI concentration in the soil. The apparent

accuracy of the transport distance of all methods is promising for the application of such

techniques for a field application design.

Radial Flow Field Container

The simulation of a full scale radial system using the large scale container experiments is

an exclusive and useful method. Real field scale techniques like the pumps and volume

of suspension used can be tested with this method, which is otherwise only possible in

a field pilot test. The big advantage of the container experiment is in the possibility to

emplace sensors for direct measurement of different parameters. The sensors developed in

this work could be used to get In-Situ live break trough curves of nZVI. Sensors for tracer

detection could aid in characterizing the hydraulic conductivity of the system and pressure

sensors could be used to show whether clogging occurs at specific locations. Sample points

could be installed to measure nZVI concentrations or colloid and aggregate sizes in liquid

samples. Furthermore, the container experiments showed to be a perfect tool to provide

near field scale data to compare the other simulation techniques to.

Sets of Columns Representing Radial Flow

The experimental approximation method for injected nZVI transport showed adequate

accuracy in comparison to the measured data from the radial flow container experiments,

but it does not quantify transport properties. Mass balance conditions for experiments

of three columns were satisfied within reasonable error in all cases.

Simulations using column experiments showed to be difficult because the aimed input

concentration was never without error. Comparison of the results from columns between

each other is difficult due to the differences in input concentration, but also the prediction

of a full radial system based on column experiments is only valid when the same input

concentration in the full system is matched. Comparison of column experiments between

each other with differences in other conditions like the injection rate is furthermore diffi-

cult because in most cases not only the injection rate will be changed but also the input

concentration.

131


Nevertheless, the discretization using column experiments to represent the radial flow

field can be a useful and quick tool to do qualitative screening of differences in several

conditions (e.g. porous medium material, suspension chemistry, nZVI pretreatment or

ZVI type), given that more care is taken into getting the aimed input concentration

to make the experiments comparable. This could be done by chemically analyzing the

suspension before the injection is started, the chemical analysis is not very quick so the

suspension would age already a bit before the experiment is started. When nZVI would be

dried (e.g. through sublimation) and exact masses could be weighted under an anaerobic

environment (glove box) or when µZVI would be used which is air stable, the exact aimed

input concentration could be accurately set. Furthermore, this technique can be used to

test the transport behavior of other nano materials in a radial flow field. The metal

detector might then not be usable (e.g. when not using ferro-magnetic materials), but

still the outflow concentrations of each of the columns in a set will be able to show the

transport distance.

Numerical Simulations of Transport in Radial Flow Fields

Numerical aided predictions proved to work best when compared to the observed ex-

perimental data. Though, it is the most elaborate method and knowledge of both the

experimental work as well as numerics is needed. The big advantage is that there is no

problem with the input concentration and discharge in the column experiments performed

to find the fitting parameters. A range of different input concentrations are needed, but

the exact concentration of the individual column experiments is of no importance. Fur-

thermore the boundary effects that occur with the short columns are insignificant with the

two meter long columns used for the model fitting. Given the relationships determined

with the column experiments many different injection scenarios could be simulated.

This method could further reduce the amount of experimental work when investigating

injection parameters, and broaden the application of these parameters to a wider range

of systems and boundary conditions. The total amount of resources used for injection

optimization would be greatly reduced.

132

5 Feasibility of Injecting nZVI into the

Subsurface

5.1 Motivation

The results presented in the previous chapters provide a better scientific understanding

of the transport of nano sized zero valent iron (nZVI) during the injection into the sub-

surface. It was shown that the transport of nZVI is limited by filtration of primary and

aggregated particles, therefore the progression of the nZVI front is much slower than the

injection front. The study is not just theoretical but the developed relationships and

models can also be used in order to understand the fate of nZVI in the field. It was

shown that given the right conditions, nZVI can be transported in a radial flow field over

a distance of almost two meters. Long term measurements showed that after five years in

storage the material still contains the reactive zero valent iron (ZVI), though significantly

less than in the beginning. In the field, dilution and continuous contact with fresh water

will further reduce the longevity.

The main impact will be the methods developed in this work which can be used for test-

ing the feasibility and expected success of using nZVI for the remediation of contaminated

aquifers.

In the following the assumption was again made that transport of nZVI has to be

due to permeation and the carrier liquid is a near newtonian fluid. Other techniques like

fracturing the subsurface, addition of chemical colloid stabilizing compounds or using non-

newtonian carrier fluids were not taken into account in this work, and thus no predictions

can be made for those techniques.

5.2 Prerequisites for Success

Before starting to use nZVI for the remediation of a contaminated aquifer, it should be

know if the application is likely to lead to a successful remediation. In order to decide if

133

5. Feasibility of Injecting nZVI into the Subsurface

the remediation using nZVI will be successful, several questions will have to be answered

first. The questions of main importance are listed and discussed below.

(a) At which depth is the source located, and is it located in the saturated or unsaturated

zone?

(b) Is the source of contamination concentrated in one point, is the source smeared over

a large area and/or depth or is generally little known about the exact location, shape

and dimension of the source?

(c) Which type of aquifer material is present. Porous or fractured aquifer; consolidated

or unconsolidated sediments; coarse or fine material; heterogeneous or homogeneous;

lenses of fine or coarse material present?

(d) Is nZVI capable of remediating the contaminant under consideration?

(e) What is the average hydraulic conductivity of the aquifer and what is the average

seepage velocity of the groundwater through the contaminated area (hydraulic head

gradient)?

(f) What is the aim of remediation and how will this result be tested?

(g) Which amount of injection points is possible or affordable?

(h) Which concentrations in the subsurface (in suspension and attached to the aquifer

material, i.e. Stotal) are required to emplace the necessary total mass of nZVI. Is this

technically possible to reach with a single injection?

Already based on these questions a decision on using nZVI or not can be made. The

following discussion points with respect to the open questions will have to be taken into

account for that decision.

(a) The application of nZVI in the unsaturated zone is not possible, nZVI corrodes rapidly

when in contact with free oxygen. The depth will provide an indication of the injection

pressures that can be build up before fracturing or daylighting is expected to occur.

(b) With a contamination spread of a very large aquifer volume at a fairly low concen-

tration, the use of nZVI is likely to become very costly because many injection points

and especially at many levels will be needed, furthermore, the consumption on nZVI

due to the reaction with other compounds will be too abundant.

(c) If the aquifer material is consolidated, very fine, or the contaminants are mainly

located inside fine sand lenses, the injection of nZVI is unlikely to be successful.

Injection into consolidated or very fine material will likely results in fracturing and

when lenses with fine material are present, nZVI will be transported around these

lenses. In these situations, nZVI won’t be able to reach the contaminant source.

134

5.2. Prerequisites for Success

(d) Many contaminants can be remediated by nZVI, though some better than others,

preliminary batch experiments might therefore be necessary.

(e) With an unconsolidated fairly coarse sand with good hydraulic conductivity

(K > ∼ 1 · 10−4 m/s) the injection of nZVI is possible. Lower hydraulic con-

ductivities could be feasible but experimental proof first has to be obtained. Other

stabilizing agents are likely to be necessary for lower hydraulic conductivities, which

was not investigated in this study. The average groundwater seepage velocity through

the source zone will indicate if the contact time is long enough for the nZVI to fully

reduce the contaminant. Also, at too high flow rates the side reactions (e.g. anaerobic

corrosion) are likely to become too abundant resulting in significant reduction of the

longevity of nZVI.

(f) Required fast remediation (e.g. less than two years) in combination with the right

subsurface conditions would make nZVI a suitable technique. Caution must be taken

when testing the success, the techniques used should suitable for testing the success of

the remediation due to nZVI. Consumption of nZVI could for example be monitored

by measuring the susceptibility change throughout the whole remediation process. A

mass flux calculation based on a large cross section down stream can also be used

to show that the contaminant flux reduces, this measuring net should then be set

up abundantly long early before the injection of nZVI takes place and operated long

enough afterwards to make sure all dilution effects due to the injection of the carrier

fluid are gone. The seepage velocity through the source zone is likely to be lower

once nZVI has been injected because the hydraulic conductivity is slightly reduced.

Therefore, tracer tests before and after the injection are necessary to determine the

dilution effect caused by more groundwater flowing around the source zone than

through it.

(g) The minimum or maximum distance between the injection points is needed, these

might be restricted due to on-site building constructions or infrastructure (above-

and underground). The necessary transport distance of nZVI will be bounded by the

size of the treatment volume and distances between injection wells.

(h) The minimal concentration of nZVI necessary in the subsurface (Stotal|minimal) can

be calculated based on stoichiometric mass balance, but an extra amount of nZVI

is needed to cover the loss of nZVI due to side reactions. With high groundwater

flow rates, side reactions are likely to become more abundant. It might be necessary

to perform multiple injections if the concentration can not be reached with a single

injection or the longevity of nZVI is not enough for the expected remediation duration.

135


Next it is necessary to determine what is needed to be able to speak about a successful

field injection and site remediation. The main issues to be taken care of are: (I) Proof

of transport distance. A successful injection can only be proven by using the correct

detection method. In the introduction several currently used methods are described, these

all have their limits and possible lack of conclusiveness. The electromagnetic measurement

of the susceptibility change in the subsurface is the chosen method to provide a conclusive

statement about the transport distance in the subsurface.

The installation of the detection sensors has to be done at those locations that are

thought of to be critical. The amount of injection points determines the minimal trans-

port distance that nZVI should reach. Furthermore, a certain concentration needs to be

reached to ensure that the reactivity will not diminish before accomplishing the degrada-

tion of the contaminant. Emplacement of the sensors at the center between two injection

wells (Figure 5.1) will show whether the nZVI concentration is high enough at these

critical locations.

When first a pilot trial injection is performed, the amount of sensors around the injec-

tion well should be increased, then a better understanding of the flow field and transport

distances can be obtained. (II) Proof of removal of contaminants. Before starting

sampling, the dilution effect due to the injection of the nZVI carrier fluid has first to be

taken into account. Hence, enough time must be allowed to pass before the concentration

measurements are taken. (III) Proof of consumption of nZVI due to reaction with

contaminants. The electromagnetic sensors will be able to show the reduction of nZVI in

the subsurface. This alone is not yet enough to prove that nZVI is reducing the contami-

nant concentration. Therefore, also other reaction end products will have to be measured,

for example Ethane which is an end product of PCE when remediated by nZVI.

Sensor

Well

Figure 5.1: Overview of minimal amount of sensor locations in an injection field with multipleinjection wells to prove the continuity of nZVI between the injection wells

136

5.3. Determination of Necessary Amount of nZVI

5.3 Determination of Necessary Amount of nZVI

Given that the previous questions lead to the choice of using nZVI for the remediation, a

more precise prediction of the feasibility can be made.

First the chemical applicability of the technique has to be verified. In order to decide

if the contaminants can be targeted with the specific nZVI available, batch experiments

need to be performed. Reactivity testing methods were not described in this work, but

can be found in literature (among many others e.g.: Lien and Zhang [2001]; Liu and

Lowry [2006]; Steiert [2008]; Zhang et al. [2009]). Furthermore the necessary mass of ZVI

should be determined based on stoichiometry and results from the reactivity tests. The

use of site own aquifer material and ground water compared to tests using clean quartz

sand and demineralized water can help to determine the amount of ZVI loss due to side

reactions.

For example, based on Equation 5.1 [Lien and Zhang, 2001], where the transfer from

PCE into Ethane is described, the necessary stoichiometric mass of zero valent iron can

be determined. According to Equation 5.1, and the molecular masses, the mass ratio is

approximately 1:1, so for each unit mass of PCE one unit mass of ZVI is needed.

C2Cl4 + 5Fe0 + 6H+ → C2H6 + 5Fe+ + 4Cl− (5.1)

Adding to this the fraction of ZVI lost due to the side reactions determined from the

batch (or column) experiments, a minimal mass ratio of ZVI can be calculated.

Mass of ZVI

Unit mass PCE=

Stoichiometric mass of ZVI

Unit mass PCE+

Mass of ZVI for side reactions

Unit mass PCE(5.2)

Using the nZVI concentration storage equation (Equation 3.7), the mass of ZVI can be

transfered into the actual mass of nZVI.

Mass of nZVI

Unit mass PCE=

Mass of ZVI

Unit mass PCE× 1

CFe0(t)(5.3)

recall from Equation 3.7 that CFe0(t) is the mass ratio of ZVI in nZVI at age t. Given the

contaminated volume of aquifer, and the total mass of contaminants inside this volume,

the minimal nZVI concentration at the porous medium (Stotal) can be calculated. Because

the actual total mass and exact distribution of contaminants in the subsurface is never

completely known, a two-fold safety factor for the total mass should at least be taken

137


into account.

Stotal|minimal = 2×Mass of nZVI

Unit mass PCE× Total mass of PCE

ρbulk × Volume of contaminated aquifer(5.4)

5.4 Application of Feasibility Test Methods

The next step is to determine how to reach this minimal concentration of nZVI

(Stotal|minimal) best over the whole source zone. Since nZVI does not move with the

same velocity as the injected carrier fluid, a gradient of nZVI concentration at the porous

medium (Stotal) will develop around the injection well. The aimed concentration though

has to be reached over a certain distance (i.e. half of the aimed distance between injection

wells, raimed). The total nZVI necessary will thus be higher due to the higher concentra-

tions close to the injection well. The final Stotal distribution shape can result in different

amounts of excess nZVI, compare the Stotal distributions in the graphs in Figure 5.2.

Excesses close to the well are less significant when compared to excesses at a large radial

distance, since the latter affects a much larger aquifer volume.

The minimum of excess nZVI necessary to reach Stotal|minimal at the aimed radial dis-

tance thus has to be found. Using one of the methods described in the previous chapters

the input concentration and injection rate can be determined to reach this. Based on the

time and funding available but also the complexity of the subsurface conditions, one or

more of the presented methods can be chosen.

The first and simplest method is the prediction based on (I) the discretization of the

full scale flow field using sets of column experiments (Section 4.4). This method is

ideal for fairly simple aquifer conditions (i.e. there should be no large heterogeneities), the

experiments could be performed with real aquifer material obtained from core samples.

Not much material is needed, one liter of aquifer material is already enough to perform

Figure 5.2: Three differently possible Stotal distributions resulting in different amounts ofexcess mass

138

5.4. Application of Feasibility Test Methods

one set with three columns. Between three and six experiment sets will be needed to be

able to determine the optimal combination of input concentration and injection rate for

reaching the aimed concentration of nZVI at a specific distance.

With more complex aquifer conditions and the desire to present full complexity predic-

tions of the final nZVI distribution over the source zone, (II) a computer simulation

aided prediction is to be chosen (Sections 3.6, 3.7 & 4.5). This method is more elab-

orate and complex and therefor will need more time, but it provides a better prediction

and higher flexibility. The nZVI to be used will have to be characterized to determine the

size distribution of the primary colloids and the aggregates, although, when RNIP (Toda

Kogyo, Japan) is to be used, the parameters from this research can be used. Also here

the use of real aquifer material is possible. Between four and seven horizontal two meter

long column experiments are to be performed, each with a different input concentration,

varying between 0.1 and 10 g/l. The injection rate should be tried to keep constant

between the experiments, but this is not very critical since the model can compensate

the velocity effects, given that the exact discharge of each experiment is recorded. The

injection rate should be chosen such that the seepage velocity is slower than the for-

ward velocity of the wagon carrying the metal detector (which for this research moved

at 10 mm/s). For a good numerical fit, at least three transient concentration profiles

should have been recorded before the nZVI front passes the outflow filter of the column.

The fitting parameters, obtained from the numerical fitting algorithm on the transient

concentration profiles, can be used for the prediction of the nZVI distribution in a full

radial flow field. Depending on the amount of data available from the field site, different

scenarios or computations with measured hydraulic conductivity fields can be performed.

Again the aim is to find the right injection rate and input concentration that results in the

least consumption of nZVI while the minimal necessary concentration (Stotal) is reached

at the largest possible (or desired) distance from the injection well.

139


Contaminated Site

Contaminantsto treat are in the saturated zone ?

Don't use nZVISearch for other method

No

Contaminants are located deep (> 10 m), or

Infrastructure obstructs excavation method ?

nZVI could be used,but more cost efficient

methods might be avaiable

No

Continue ?

Aquifer material has a high hydraulic conductivity

(K > 1e-04 m/s) ? &Contaminants are not located in

low conductivity zones (e.g. clay lenses) ?

Yes

Yes

Yes

No

No

Yes

Unwise to use nZVILab tests necessary if continuing

Continue ?

No

Aquifer material is well sorted ?& nZVI already characterized ?

Yes

No

Columndiscretizationof radial flow

field

Quick

Computer aided simulations with

column data input

Flexible

Large scalecontainer

experiments

Real data

Choose experimental technique

GoodTransport

BadTransport

Charcterization with sedimentation testsand particle size detector:

size of aggregates and colloids

Run horizontal column tests (L > 1 m)at least 5 experiments, C varied: 0.1 - 10 g/l

Numerical fitting algorithm on column data

Use previous or new column experiment results.Run 2-D model to determine Cinput based on

aimed S_total and associated transport distance (well separation)

Calculate volume of suspension and C needed for field,based on extrapolation of column discretization

or numerical simulations

Start on-site FieldPhase

Yes

Figure 5.3: Decision chart to determine the applicability of nZVI

140

5.5. Application of Methods in the Field

The third experimental method provided in this work is (III) the large scale container

experiment, which is likely to be too labor intensive to be used for a feasibility study on

itself. Like with the discretized column sets approach, between three and six experiments

would be necessary to determine the optimal combination of input concentration and

injection rate. This results in something between six and twelve months of non-stop work

on the container experiments. Therefore it is here suggested that this method is optionally

added to either one of the two other methods, to verify if the found combination of input

concentration and injection rate indeed provide the predicted result. This method can

furthermore ideally be used to test the pumping technique, different types of sensors,

sampling systems, suspension preparation technique, among other techniques that would

otherwise need a much more expensive and less controlled field trial.

A flow chart was drawn (Figure 5.3) to help guiding the decision making of whether to

use nZVI and if so, which feasibility testing methods should be used.

5.5 Application of Methods in the Field

In the presented work also technical problems had to be overcome, of which several

resulting techniques are useful and recommended to be used in the field as well.

Agglomeration is a not to be overlooked problem of nZVI, (I) dispersing nZVI using

mechanically induced high shear forces was found to be an effective method to partly undo

the aggregation. In-line dispersers were found to be best suited. The in-line operation

avoids the introduction of air (free oxygen leads to corrosion) into the suspension.

When performing the small flume experiment at the end of the research (Section 2.5.5)

it was chosen to use (II) a funnel shaped nZVI reservoir (Figure 5.4). The outlet at the

bottom first went through the dispersing unit and then into a small flow-through reservoir

Pump

Disperser

nZVIReservoir

Floater

Ventilation

Figure 5.4: Drawing of a funnel shaped nZVI reservoir with the connected disperser and pump

141


from which the dosing pump took the suspension, all surplus suspension automatically

went back into the top op the funnel shaped reservoir. By using a floater, the well

dispersed suspension was injected just under the water table, providing a very good and

homogeneous suspension inside the reservoir. It is highly recommended that a similar set

up be used for field applications.

One of the tests performed in the container experiments was to determine which type of

pump performed better for an injection. (III) The continuous flux dosing pump was

found to be best suitable. This type of pump can provide a very continuous flux and can

build up high pressures while maintaining the same flux. Also for the column experiments

a small version of such a dosing pump could be used to maintain a continuous flux, also

at higher injection pressures.

(IV) The susceptibility based monitoring technique to observe the transport

during injection should be installed to make sure that nZVI arrived at the calculated

concentration at the desired distance from the injection well. For long term observation

of the consumption of nZVI it is advisable to keep the sensors and electronics installed.

While installing the electro magnetic sensors, this can easily be (V) combined with

the installation of a whole range of other sensors and sampling ports to support the

monitoring during and after the injection.

142

Conclusion

Application of nano sized zero valent iron (nZVI) to remediate contaminated aquifers is a

promising method. By applying nZVI in the source zone and reduce the concentration of

contaminants directly in-situ, the remediation duration and expenses are expected to be

significantly reduced. The main goal of this work was to get a better understanding and

description of the transport of nZVI during the injection into the subsurface. Chemical

feasibility was in the context of this work assumed to be granted and was not further

investigated. Four research questions were set up which could all be answered throughout

this work.

(a) Is it possible to detect In-Situ the concentration of iron and determine the transport

distance?

The first problem faced was the lack of available measuring techniques to determine

non-destructively the concentration of nZVI inside the porous medium. A measuring

technique based on the magnetic susceptibility of zero valent iron inside nZVI col-

loids was developed. The technique was at first worked out for column experiments,

making it possible to measure transient concentration profiles along the full length of

a column. Next the technique was further developed to make in-situ measurements of

nZVI breakthrough possible in a large scale container experiment. This technique was

then further upscaled to a field ready technique, which could be installed in boreholes

at a pilot test or full scale field application.

(b) Which conditions have the largest effect on mobility and how can they be optimized?

By looking into a classic filtration theory in detail, it was determined that the colloid

size is the main factor affecting the transport of nZVI. Through characterization of

the chosen nZVI material in this study (RNIP 10-E, Toda Kogyo, Japan), it was

found out that colloidal aggregation is very abundant, which following the filtration

theory significantly reduces the transport. In order to undo the aggregation, mechan-

ically induced high shear forces were applied by using an in-line dispersing unit, the

aggregation was found not be fully undone, and smaller aggregates maintained.

Column experiments with different input suspension concentrations were performed

143

Conclusion

because the colloid filtration theory does not take the suspension concentration into

account. It was found out that the suspension concentration was a further factor that

significantly influences the transport of nZVI.

Based on these finding, the minimal alterations that had to be applied to the sup-

plied nZVI suspension were dilution and dispersion. Further methods of optimizing

the suspension were not investigated because the aim was to use the commercially

available material with as little changes as possible.

(c) What is the transport distance in a radial flow field?

The transport in a radial flow field was investigated first by performing transport

experiments in a large triangular shaped container, representing a wedge out of a full

cylinder. nZVI was transported over a distance of almost two meters (distance of

one pore volume) after injecting three pore volumes of suspension at 10 g/l, at an

injection duration of one hour. A transport distance of two meters is a very reasonable

distance for field applications.

(d) Which method can test the feasibility of injection into the subsurface?

Two methods were developed to predict the transport of nZVI in a radial flow field

with a high accuracy. A computer simulation aided prediction based on input from

column experiments, and a discretization of the radial flow field into segments that

could be represented by a set of column experiments of various length. An extended

transport and filtration equation was derived and used in the numerical simulations,

both for the column and container experiments. The results of both predictive meth-

ods were compared to the results obtained from the container experiment.

An overview on how to decide in favor of using nZVI and how the predictive methods

can help to design a field application has finally been presented.

The results of this work are very promising and are a sound scientific basis for further

investigations and case studies on nZVI based remediation of contaminated aquifers.

144

Outlook

Already the methods developed here showed to be very useful and the understanding of

the transport of nZVI was significantly improved. Nevertheless, more research could be

performed to further improve the methods and to make the extrapolation to real field

situations solid. The following research items could be taken into account:

Further improve the field sensor to make measurements without reference sensor pos-

sible, as was the case with the sensor developed for the container.

Record breakthrough curves during the container experiments with the container sen-

sors but using the much more sensitive electronics that were developed for the field

sensors. The breakthrough curves could then be used to verify the transient results of

the numerical simulations.

Transient concentration profiles in the container based on photo series from the con-

tainer experiments calibrated on the final measured nZVI distribution might be possi-

ble. This could then also be used to test the transient results of the numerical simula-

tions instead of just the final results.

Identify the mechanisms responsible for the fairly low attachment efficiency of the

aggregates when predicted by the filtration theory.

Improve the filtration theory, which is based on deep bed filtration, because the flow

direction is not only equal to the vertical gravity force component during an injection

in the subsurface.

Perform simulations in a radial flow field by using hydraulic conductivity fields obtained

from tracer breakthrough curves of the container experiments.

Test the simulation with other hydraulic conductivities, include lenses with a lower

or higher hydraulic conductivity, extend the model to full 3-D, include variation in

hydraulic conductivity in the z-direction and simulate multiple injection wells.

Run the numerical simulation for different flow fields, e.g. using an injection-extraction

configuration of wells (e.g. 2-spot or 5-spot).

Testing of characterization and prediction methods on other nZVI products and other

soil material.

145

Outlook

Use a real field site as a case study to determine the input concentration and injection

rate by using the methods developed in this work.

146

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155

Curriculum Vitae

Cjestmir Volkert de Boer, M.Sc.

Personal Details

Gender: Male

Date of birth: 27th of July, 1980

Place of birth: Langedijke, Ooststellingwerf, The Netherlands

Citizenship: Dutch

Email: [email protected]

Language Knowledge

Dutch: native English: fluent German: fluent

Education

09/2000–06/2007 Bachelor-/ Master study in Earth Sciences with specialization in En-

vironmental Hydrogeology at the department of Geo Sciences of the

Utrecht University, The Netherlands

09/1992–07/1999 High-school (Atheneum) at Stellingwerf College in Oosterwolde, Fries-

land, The Netherlands

Working Experience

04/2007–03/2012 Research assistant at VEGAS research facility, department of Hy-

draulic Engineering, Stuttgart University, Germany (full-time)

09/2003–08/2004 Help desk assistance at the Faculty ICT Service, Earth Sciences,

Utrecht University (part-time)

04/2003–09/2009 First-line help desk Technical Supporter for YourName Webhosting,

Nijmegen, The Netherlands (part-time)

05/2000–09/2000 Lock-keeper in Friesland, Provinsje Fryslan, The Netherlands (full-

time)

02/2000–05/2000 Assemblage worker at Aludon, Donkerbroek, The Netherlands (full-

time)

Research Projects

05/2009–03/2012 Development of rehabilitation technologies and approaches for multi-

pressured degraded waters and the integration of their impact on river

basin management. Funded by the European Commission through

the 7th Research Framework Programme: FP7 ENV 2008.3.1.1.1,

AQUAREHAB

08/2007–12/2008 Injection of Nano-Scale Iron for the In-Situ Remediation of Chlo-

rinated Hydrocarbons in Soil and Groundwater (Investigations on

Transport in large-scale Experiments and in Field Applications).

Funded by the State of Baden-Wurttemberg, Germany under the

project number 111-047588.6 / 973.049977.9, BUT 013

05/2007–08/2007 Surfactant Flushing in Column and Flume Experiments for the Re-

moval of Residual Chloronaphthaline.

10/2005–05/2007 Feasibility Study on the In-Situ Application of Reactive Nano-Sized

Iron Particles to Remediate CHC-Contaminations. Funded by the

State of Baden-Wurttemberg, Germany through BW-PLUS under the

project number BWR25001

Institut für Wasser- und Umweltsystemmodellierung Universität Stuttgart

Pfaffenwaldring 61 70569 Stuttgart (Vaihingen) Telefon (0711) 685 - 64717/64749/64752/64679 Telefax (0711) 685 - 67020 o. 64746 o. 64681 E-Mail: [email protected] http://www.iws.uni-stuttgart.de

Direktoren Prof. Dr. rer. nat. Dr.-Ing. András Bárdossy Prof. Dr.-Ing. Rainer Helmig Prof. Dr.-Ing. Silke Wieprecht Vorstand (Stand 01.04.2009) Prof. Dr. rer. nat. Dr.-Ing. A. Bárdossy Prof. Dr.-Ing. R. Helmig Prof. Dr.-Ing. S. Wieprecht Jürgen Braun, PhD Dr.-Ing. H. Class Dr.-Ing. S. Hartmann Dr.-Ing. H.-P. Koschitzky PD Dr.-Ing. W. Marx Dr. rer. nat. J. Seidel Emeriti Prof. Dr.-Ing. habil. Dr.-Ing. E.h. Jürgen Giesecke Prof. Dr.h.c. Dr.-Ing. E.h. Helmut Kobus, PhD

Lehrstuhl für Wasserbau und Wassermengenwirtschaft Leiter: Prof. Dr.-Ing. Silke Wieprecht Stellv.: PD Dr.-Ing. Walter Marx, AOR Versuchsanstalt für Wasserbau Leiter: Dr.-Ing. Sven Hartmann, AOR Lehrstuhl für Hydromechanik und Hydrosystemmodellierung Leiter: Prof. Dr.-Ing. Rainer Helmig Stellv.: Dr.-Ing. Holger Class, AOR Lehrstuhl für Hydrologie und Geohydrologie Leiter: Prof. Dr. rer. nat. Dr.-Ing. András Bárdossy Stellv.: Dr. rer. nat. Jochen Seidel VEGAS, Versuchseinrichtung zur Grundwasser- und Altlastensanierung Leitung: Jürgen Braun, PhD Dr.-Ing. Hans-Peter Koschitzky, AD

Verzeichnis der Mitteilungshefte

1 Röhnisch, Arthur: Die Bemühungen um eine Wasserbauliche Versuchsanstalt an

der Technischen Hochschule Stuttgart, und Fattah Abouleid, Abdel: Beitrag zur Berechnung einer in lockeren Sand geramm-ten, zweifach verankerten Spundwand, 1963

2 Marotz, Günter: Beitrag zur Frage der Standfestigkeit von dichten Asphaltbelägen

im Großwasserbau, 1964 3 Gurr, Siegfried: Beitrag zur Berechnung zusammengesetzter ebener Flächen-

tragwerke unter besonderer Berücksichtigung ebener Stauwände, mit Hilfe von Randwert- und Lastwertmatrizen, 1965

4 Plica, Peter: Ein Beitrag zur Anwendung von Schalenkonstruktionen im Stahlwas-

serbau, und Petrikat, Kurt: Möglichkeiten und Grenzen des wasserbaulichen Ver-suchswesens, 1966

2 Institut für Wasser- und Umweltsystemmodellierung * Universität Stuttgart * IWS 5 Plate, Erich: Beitrag zur Bestimmung der Windgeschwindigkeitsverteilung in der

durch eine Wand gestörten bodennahen Luftschicht, und Röhnisch, Arthur; Marotz, Günter: Neue Baustoffe und Bauausführungen für den Schutz der Böschungen und der Sohle von Kanälen, Flüssen und Häfen; Geste-hungskosten und jeweilige Vorteile, sowie Unny, T.E.: Schwingungs-untersuchungen am Kegelstrahlschieber, 1967

6 Seiler, Erich: Die Ermittlung des Anlagenwertes der bundeseigenen Bin-

nenschiffahrtsstraßen und Talsperren und des Anteils der Binnenschiffahrt an die-sem Wert, 1967

7 Sonderheft anläßlich des 65. Geburtstages von Prof. Arthur Röhnisch mit Beiträ-

gen von Benk, Dieter; Breitling, J.; Gurr, Siegfried; Haberhauer, Robert; Hone-kamp, Hermann; Kuz, Klaus Dieter; Marotz, Günter; Mayer-Vorfelder, Hans-Jörg; Miller, Rudolf; Plate, Erich J.; Radomski, Helge; Schwarz, Helmut; Vollmer, Ernst; Wildenhahn, Eberhard; 1967

8 Jumikis, Alfred: Beitrag zur experimentellen Untersuchung des Wassernachschubs

in einem gefrierenden Boden und die Beurteilung der Ergebnisse, 1968 9 Marotz, Günter: Technische Grundlagen einer Wasserspeicherung im natürlichen

Untergrund, 1968 10 Radomski, Helge: Untersuchungen über den Einfluß der Querschnittsform wellen-

förmiger Spundwände auf die statischen und rammtechnischen Eigenschaften, 1968

11 Schwarz, Helmut: Die Grenztragfähigkeit des Baugrundes bei Einwirkung vertikal

gezogener Ankerplatten als zweidimensionales Bruchproblem, 1969 12 Erbel, Klaus: Ein Beitrag zur Untersuchung der Metamorphose von Mittelgebirgs-

schneedecken unter besonderer Berücksichtigung eines Verfahrens zur Bestim-mung der thermischen Schneequalität, 1969

13 Westhaus, Karl-Heinz: Der Strukturwandel in der Binnenschiffahrt und sein Einfluß

auf den Ausbau der Binnenschiffskanäle, 1969 14 Mayer-Vorfelder, Hans-Jörg: Ein Beitrag zur Berechnung des Erdwiderstandes un-

ter Ansatz der logarithmischen Spirale als Gleitflächenfunktion, 1970 15 Schulz, Manfred: Berechnung des räumlichen Erddruckes auf die Wandung kreis-

zylindrischer Körper, 1970 16 Mobasseri, Manoutschehr: Die Rippenstützmauer. Konstruktion und Grenzen ihrer

Standsicherheit, 1970 17 Benk, Dieter: Ein Beitrag zum Betrieb und zur Bemessung von Hochwasser-

rückhaltebecken, 1970

Verzeichnis der Mitteilungshefte 3 18 Gàl, Attila: Bestimmung der mitschwingenden Wassermasse bei überströmten

Fischbauchklappen mit kreiszylindrischem Staublech, 1971, 19 Kuz, Klaus Dieter: Ein Beitrag zur Frage des Einsetzens von Kavitationserschei-

nungen in einer Düsenströmung bei Berücksichtigung der im Wasser gelösten Ga-se, 1971,

20 Schaak, Hartmut: Verteilleitungen von Wasserkraftanlagen, 1971 21 Sonderheft zur Eröffnung der neuen Versuchsanstalt des Instituts für Wasserbau

der Universität Stuttgart mit Beiträgen von Brombach, Hansjörg; Dirksen, Wolfram; Gàl, Attila; Gerlach, Reinhard; Giesecke, Jürgen; Holthoff, Franz-Josef; Kuz, Klaus Dieter; Marotz, Günter; Minor, Hans-Erwin; Petrikat, Kurt; Röhnisch, Arthur; Rueff, Helge; Schwarz, Helmut; Vollmer, Ernst; Wildenhahn, Eberhard; 1972

22 Wang, Chung-su: Ein Beitrag zur Berechnung der Schwingungen an Kegelstrahl-

schiebern, 1972 23 Mayer-Vorfelder, Hans-Jörg: Erdwiderstandsbeiwerte nach dem Ohde-

Variationsverfahren, 1972 24 Minor, Hans-Erwin: Beitrag zur Bestimmung der Schwingungsanfachungs-

funktionen überströmter Stauklappen, 1972, 25 Brombach, Hansjörg: Untersuchung strömungsmechanischer Elemente (Fluidik)

und die Möglichkeit der Anwendung von Wirbelkammerelementen im Wasserbau, 1972,

26 Wildenhahn, Eberhard: Beitrag zur Berechnung von Horizontalfilterbrunnen, 1972 27 Steinlein, Helmut: Die Eliminierung der Schwebstoffe aus Flußwasser zum Zweck

der unterirdischen Wasserspeicherung, gezeigt am Beispiel der Iller, 1972 28 Holthoff, Franz Josef: Die Überwindung großer Hubhöhen in der Binnenschiffahrt

durch Schwimmerhebewerke, 1973 29 Röder, Karl: Einwirkungen aus Baugrundbewegungen auf trog- und kastenförmige

Konstruktionen des Wasser- und Tunnelbaues, 1973 30 Kretschmer, Heinz: Die Bemessung von Bogenstaumauern in Abhängigkeit von

der Talform, 1973 31 Honekamp, Hermann: Beitrag zur Berechnung der Montage von Unterwasserpipe-

lines, 1973 32 Giesecke, Jürgen: Die Wirbelkammertriode als neuartiges Steuerorgan im Was-

serbau, und Brombach, Hansjörg: Entwicklung, Bauformen, Wirkungsweise und Steuereigenschaften von Wirbelkammerverstärkern, 1974

4 Institut für Wasser- und Umweltsystemmodellierung * Universität Stuttgart * IWS 33 Rueff, Helge: Untersuchung der schwingungserregenden Kräfte an zwei hinterein-

ander angeordneten Tiefschützen unter besonderer Berücksichtigung von Kavita-tion, 1974

34 Röhnisch, Arthur: Einpreßversuche mit Zementmörtel für Spannbeton - Vergleich

der Ergebnisse von Modellversuchen mit Ausführungen in Hüllwellrohren, 1975 35 Sonderheft anläßlich des 65. Geburtstages von Prof. Dr.-Ing. Kurt Petrikat mit Bei-

trägen von: Brombach, Hansjörg; Erbel, Klaus; Flinspach, Dieter; Fischer jr., Ri-chard; Gàl, Attila; Gerlach, Reinhard; Giesecke, Jürgen; Haberhauer, Robert; Haf-ner Edzard; Hausenblas, Bernhard; Horlacher, Hans-Burkhard; Hutarew, Andreas; Knoll, Manfred; Krummet, Ralph; Marotz, Günter; Merkle, Theodor; Miller, Chris-toph; Minor, Hans-Erwin; Neumayer, Hans; Rao, Syamala; Rath, Paul; Rueff, Hel-ge; Ruppert, Jürgen; Schwarz, Wolfgang; Topal-Gökceli, Mehmet; Vollmer, Ernst; Wang, Chung-su; Weber, Hans-Georg; 1975

36 Berger, Jochum: Beitrag zur Berechnung des Spannungszustandes in rotations-

symmetrisch belasteten Kugelschalen veränderlicher Wandstärke unter Gas- und Flüssigkeitsdruck durch Integration schwach singulärer Differentialgleichungen, 1975

37 Dirksen, Wolfram: Berechnung instationärer Abflußvorgänge in gestauten Gerin-

nen mittels Differenzenverfahren und die Anwendung auf Hochwasserrückhalte-becken, 1976

38 Horlacher, Hans-Burkhard: Berechnung instationärer Temperatur- und Wärme-

spannungsfelder in langen mehrschichtigen Hohlzylindern, 1976 39 Hafner, Edzard: Untersuchung der hydrodynamischen Kräfte auf Baukörper im

Tiefwasserbereich des Meeres, 1977, ISBN 3-921694-39-6 40 Ruppert, Jürgen: Über den Axialwirbelkammerverstärker für den Einsatz im Was-

serbau, 1977, ISBN 3-921694-40-X 41 Hutarew, Andreas: Beitrag zur Beeinflußbarkeit des Sauerstoffgehalts in Fließge-

wässern an Abstürzen und Wehren, 1977, ISBN 3-921694-41-8, 42 Miller, Christoph: Ein Beitrag zur Bestimmung der schwingungserregenden Kräfte

an unterströmten Wehren, 1977, ISBN 3-921694-42-6 43 Schwarz, Wolfgang: Druckstoßberechnung unter Berücksichtigung der Radial- und

Längsverschiebungen der Rohrwandung, 1978, ISBN 3-921694-43-4 44 Kinzelbach, Wolfgang: Numerische Untersuchungen über den optimalen Einsatz

variabler Kühlsysteme einer Kraftwerkskette am Beispiel Oberrhein, 1978, ISBN 3-921694-44-2

45 Barczewski, Baldur: Neue Meßmethoden für Wasser-Luftgemische und deren An-

wendung auf zweiphasige Auftriebsstrahlen, 1979, ISBN 3-921694-45-0

Verzeichnis der Mitteilungshefte 5 46 Neumayer, Hans: Untersuchung der Strömungsvorgänge in radialen Wirbelkam-

merverstärkern, 1979, ISBN 3-921694-46-9 47 Elalfy, Youssef-Elhassan: Untersuchung der Strömungsvorgänge in Wirbelkam-

merdioden und -drosseln, 1979, ISBN 3-921694-47-7 48 Brombach, Hansjörg: Automatisierung der Bewirtschaftung von Wasserspeichern,

1981, ISBN 3-921694-48-5 49 Geldner, Peter: Deterministische und stochastische Methoden zur Bestimmung der

Selbstdichtung von Gewässern, 1981, ISBN 3-921694-49-3, 50 Mehlhorn, Hans: Temperaturveränderungen im Grundwasser durch Brauchwas-

sereinleitungen, 1982, ISBN 3-921694-50-7, 51 Hafner, Edzard: Rohrleitungen und Behälter im Meer, 1983, ISBN 3-921694-51-5 52 Rinnert, Bernd: Hydrodynamische Dispersion in porösen Medien: Einfluß von Dich-

teunterschieden auf die Vertikalvermischung in horizontaler Strömung, 1983, ISBN 3-921694-52-3,

53 Lindner, Wulf: Steuerung von Grundwasserentnahmen unter Einhaltung ökologi-

scher Kriterien, 1983, ISBN 3-921694-53-1, 54 Herr, Michael; Herzer, Jörg; Kinzelbach, Wolfgang; Kobus, Helmut; Rinnert, Bernd:

Methoden zur rechnerischen Erfassung und hydraulischen Sanierung von Grund-wasserkontaminationen, 1983, ISBN 3-921694-54-X

55 Schmitt, Paul: Wege zur Automatisierung der Niederschlagsermittlung, 1984, ISBN

3-921694-55-8, 56 Müller, Peter: Transport und selektive Sedimentation von Schwebstoffen bei ge-

stautem Abfluß, 1985, ISBN 3-921694-56-6 57 El-Qawasmeh, Fuad: Möglichkeiten und Grenzen der Tropfbewässerung unter be-

sonderer Berücksichtigung der Verstopfungsanfälligkeit der Tropfelemente, 1985, ISBN 3-921694-57-4,

58 Kirchenbaur, Klaus: Mikroprozessorgesteuerte Erfassung instationärer Druckfelder

am Beispiel seegangsbelasteter Baukörper, 1985, ISBN 3-921694-58-2 59 Kobus, Helmut (Hrsg.): Modellierung des großräumigen Wärme- und Schadstoff-

transports im Grundwasser, Tätigkeitsbericht 1984/85 (DFG-Forschergruppe an den Universitäten Hohenheim, Karlsruhe und Stuttgart), 1985, ISBN 3-921694-59-0,

60 Spitz, Karlheinz: Dispersion in porösen Medien: Einfluß von Inhomogenitäten und

Dichteunterschieden, 1985, ISBN 3-921694-60-4, 61 Kobus, Helmut: An Introduction to Air-Water Flows in Hydraulics, 1985,

ISBN 3-921694-61-2

6 Institut für Wasser- und Umweltsystemmodellierung * Universität Stuttgart * IWS 62 Kaleris, Vassilios: Erfassung des Austausches von Oberflächen- und Grundwasser

in horizontalebenen Grundwassermodellen, 1986, ISBN 3-921694-62-0 63 Herr, Michael: Grundlagen der hydraulischen Sanierung verunreinigter Poren-

grundwasserleiter, 1987, ISBN 3-921694-63-9 64 Marx, Walter: Berechnung von Temperatur und Spannung in Massenbeton infolge

Hydratation, 1987, ISBN 3-921694-64-7 65 Koschitzky, Hans-Peter: Dimensionierungskonzept für Sohlbelüfter in Schußrinnen

zur Vermeidung von Kavitationsschäden, 1987, ISBN 3-921694-65-5 66 Kobus, Helmut (Hrsg.): Modellierung des großräumigen Wärme- und Schadstoff-

transports im Grundwasser, Tätigkeitsbericht 1986/87 (DFG-Forschergruppe an den Universitäten Hohenheim, Karlsruhe und Stuttgart) 1987, ISBN 3-921694-66-3

67 Söll, Thomas: Berechnungsverfahren zur Abschätzung anthropogener Tempera-

turanomalien im Grundwasser, 1988, ISBN 3-921694-67-1 68 Dittrich, Andreas; Westrich, Bernd: Bodenseeufererosion, Bestandsaufnahme und

Bewertung, 1988, ISBN 3-921694-68-X, 69 Huwe, Bernd; van der Ploeg, Rienk R.: Modelle zur Simulation des Stickstoffhaus-

haltes von Standorten mit unterschiedlicher landwirtschaftlicher Nutzung, 1988, ISBN 3-921694-69-8,

70 Stephan, Karl: Integration elliptischer Funktionen, 1988, ISBN 3-921694-70-1 71 Kobus, Helmut; Zilliox, Lothaire (Hrsg.): Nitratbelastung des Grundwassers, Aus-

wirkungen der Landwirtschaft auf die Grundwasser- und Rohwasserbeschaffenheit und Maßnahmen zum Schutz des Grundwassers. Vorträge des deutsch-franzö-sischen Kolloquiums am 6. Oktober 1988, Universitäten Stuttgart und Louis Pas-teur Strasbourg (Vorträge in deutsch oder französisch, Kurzfassungen zwei-sprachig), 1988, ISBN 3-921694-71-X

72 Soyeaux, Renald: Unterströmung von Stauanlagen auf klüftigem Untergrund unter

Berücksichtigung laminarer und turbulenter Fließzustände,1991, ISBN 3-921694-72-8

73 Kohane, Roberto: Berechnungsmethoden für Hochwasserabfluß in Fließgewäs-

sern mit überströmten Vorländern, 1991, ISBN 3-921694-73-6 74 Hassinger, Reinhard: Beitrag zur Hydraulik und Bemessung von Blocksteinrampen

in flexibler Bauweise, 1991, ISBN 3-921694-74-4, 75 Schäfer, Gerhard: Einfluß von Schichtenstrukturen und lokalen Einlagerungen auf

die Längsdispersion in Porengrundwasserleitern, 1991, ISBN 3-921694-75-2 76 Giesecke, Jürgen: Vorträge, Wasserwirtschaft in stark besiedelten Regionen; Um-

weltforschung mit Schwerpunkt Wasserwirtschaft, 1991, ISBN 3-921694-76-0

Verzeichnis der Mitteilungshefte 7 77 Huwe, Bernd: Deterministische und stochastische Ansätze zur Modellierung des

Stickstoffhaushalts landwirtschaftlich genutzter Flächen auf unterschiedlichem Skalenniveau, 1992, ISBN 3-921694-77-9,

78 Rommel, Michael: Verwendung von Kluftdaten zur realitätsnahen Generierung von

Kluftnetzen mit anschließender laminar-turbulenter Strömungsberechnung, 1993, ISBN 3-92 1694-78-7

79 Marschall, Paul: Die Ermittlung lokaler Stofffrachten im Grundwasser mit Hilfe von

Einbohrloch-Meßverfahren, 1993, ISBN 3-921694-79-5, 80 Ptak, Thomas: Stofftransport in heterogenen Porenaquiferen: Felduntersuchungen

und stochastische Modellierung, 1993, ISBN 3-921694-80-9, 81 Haakh, Frieder: Transientes Strömungsverhalten in Wirbelkammern, 1993,

ISBN 3-921694-81-7 82 Kobus, Helmut; Cirpka, Olaf; Barczewski, Baldur; Koschitzky, Hans-Peter: Ver-

sucheinrichtung zur Grundwasser und Altlastensanierung VEGAS, Konzeption und Programmrahmen, 1993, ISBN 3-921694-82-5

83 Zang, Weidong: Optimaler Echtzeit-Betrieb eines Speichers mit aktueller Abflußre-

generierung, 1994, ISBN 3-921694-83-3, 84 Franke, Hans-Jörg: Stochastische Modellierung eines flächenhaften Stoffeintrages

und Transports in Grundwasser am Beispiel der Pflanzenschutzmittelproblematik, 1995, ISBN 3-921694-84-1

85 Lang, Ulrich: Simulation regionaler Strömungs- und Transportvorgänge in Karst-

aquiferen mit Hilfe des Doppelkontinuum-Ansatzes: Methodenentwicklung und Pa-rameteridentifikation, 1995, ISBN 3-921694-85-X,

86 Helmig, Rainer: Einführung in die Numerischen Methoden der Hydromechanik,

1996, ISBN 3-921694-86-8, 87 Cirpka, Olaf: CONTRACT: A Numerical Tool for Contaminant Transport and

Chemical Transformations - Theory and Program Documentation -, 1996, ISBN 3-921694-87-6

88 Haberlandt, Uwe: Stochastische Synthese und Regionalisierung des Niederschla-

ges für Schmutzfrachtberechnungen, 1996, ISBN 3-921694-88-4 89 Croisé, Jean: Extraktion von flüchtigen Chemikalien aus natürlichen Lockergestei-

nen mittels erzwungener Luftströmung, 1996, ISBN 3-921694-89-2, 90 Jorde, Klaus: Ökologisch begründete, dynamische Mindestwasserregelungen bei

Ausleitungskraftwerken, 1997, ISBN 3-921694-90-6, 91 Helmig, Rainer: Gekoppelte Strömungs- und Transportprozesse im Untergrund -

Ein Beitrag zur Hydrosystemmodellierung-, 1998, ISBN 3-921694-91-4,

8 Institut für Wasser- und Umweltsystemmodellierung * Universität Stuttgart * IWS 92 Emmert, Martin: Numerische Modellierung nichtisothermer Gas-Wasser Systeme

in porösen Medien, 1997, ISBN 3-921694-92-2 93 Kern, Ulrich: Transport von Schweb- und Schadstoffen in staugeregelten Fließge-

wässern am Beispiel des Neckars, 1997, ISBN 3-921694-93-0, 94 Förster, Georg: Druckstoßdämpfung durch große Luftblasen in Hochpunkten von

Rohrleitungen 1997, ISBN 3-921694-94-9 95 Cirpka, Olaf: Numerische Methoden zur Simulation des reaktiven Mehrkomponen-

tentransports im Grundwasser, 1997, ISBN 3-921694-95-7, 96 Färber, Arne: Wärmetransport in der ungesättigten Bodenzone: Entwicklung einer

thermischen In-situ-Sanierungstechnologie, 1997, ISBN 3-921694-96-5 97 Betz, Christoph: Wasserdampfdestillation von Schadstoffen im porösen Medium:

Entwicklung einer thermischen In-situ-Sanierungstechnologie, 1998, ISBN 3-921694-97-3

98 Xu, Yichun: Numerical Modeling of Suspended Sediment Transport in Rivers,

1998, ISBN 3-921694-98-1, 99 Wüst, Wolfgang: Geochemische Untersuchungen zur Sanierung CKW-

kontaminierter Aquifere mit Fe(0)-Reaktionswänden, 2000, ISBN 3-933761-02-2 100 Sheta, Hussam: Simulation von Mehrphasenvorgängen in porösen Medien unter

Einbeziehung von Hysterese-Effekten, 2000, ISBN 3-933761-03-4 101 Ayros, Edwin: Regionalisierung extremer Abflüsse auf der Grundlage statistischer

Verfahren, 2000, ISBN 3-933761-04-2, 102 Huber, Ralf: Compositional Multiphase Flow and Transport in Heterogeneous Po-

rous Media, 2000, ISBN 3-933761-05-0 103 Braun, Christopherus: Ein Upscaling-Verfahren für Mehrphasenströmungen in po-

rösen Medien, 2000, ISBN 3-933761-06-9 104 Hofmann, Bernd: Entwicklung eines rechnergestützten Managementsystems zur

Beurteilung von Grundwasserschadensfällen, 2000, ISBN 3-933761-07-7 105 Class, Holger: Theorie und numerische Modellierung nichtisothermer Mehrphasen-

prozesse in NAPL-kontaminierten porösen Medien, 2001, ISBN 3-933761-08-5

106 Schmidt, Reinhard: Wasserdampf- und Heißluftinjektion zur thermischen Sanie-

rung kontaminierter Standorte, 2001, ISBN 3-933761-09-3 107 Josef, Reinhold:, Schadstoffextraktion mit hydraulischen Sanierungsverfahren un-

ter Anwendung von grenzflächenaktiven Stoffen, 2001, ISBN 3-933761-10-7

Verzeichnis der Mitteilungshefte 9 108 Schneider, Matthias: Habitat- und Abflussmodellierung für Fließgewässer mit un-

scharfen Berechnungsansätzen, 2001, ISBN 3-933761-11-5 109 Rathgeb, Andreas: Hydrodynamische Bemessungsgrundlagen für Lockerdeckwer-

ke an überströmbaren Erddämmen, 2001, ISBN 3-933761-12-3 110 Lang, Stefan: Parallele numerische Simulation instätionärer Probleme mit adapti-

ven Methoden auf unstrukturierten Gittern, 2001, ISBN 3-933761-13-1 111 Appt, Jochen; Stumpp Simone: Die Bodensee-Messkampagne 2001, IWS/CWR

Lake Constance Measurement Program 2001, 2002, ISBN 3-933761-14-X 112 Heimerl, Stephan: Systematische Beurteilung von Wasserkraftprojekten, 2002,

ISBN 3-933761-15-8, 113 Iqbal, Amin: On the Management and Salinity Control of Drip Irrigation, 2002, ISBN

3-933761-16-6 114 Silberhorn-Hemminger, Annette: Modellierung von Kluftaquifersystemen: Geosta-

tistische Analyse und deterministisch-stochastische Kluftgenerierung, 2002, ISBN 3-933761-17-4

115 Winkler, Angela: Prozesse des Wärme- und Stofftransports bei der In-situ-

Sanierung mit festen Wärmequellen, 2003, ISBN 3-933761-18-2 116 Marx, Walter: Wasserkraft, Bewässerung, Umwelt - Planungs- und Bewertungs-

schwerpunkte der Wasserbewirtschaftung, 2003, ISBN 3-933761-19-0 117 Hinkelmann, Reinhard: Efficient Numerical Methods and Information-Processing

Techniques in Environment Water, 2003, ISBN 3-933761-20-4 118 Samaniego-Eguiguren, Luis Eduardo: Hydrological Consequences of Land Use /

Land Cover and Climatic Changes in Mesoscale Catchments, 2003, ISBN 3-933761-21-2

119 Neunhäuserer, Lina: Diskretisierungsansätze zur Modellierung von Strömungs-

und Transportprozessen in geklüftet-porösen Medien, 2003, ISBN 3-933761-22-0 120 Paul, Maren: Simulation of Two-Phase Flow in Heterogeneous Poros Media with

Adaptive Methods, 2003, ISBN 3-933761-23-9 121 Ehret, Uwe: Rainfall and Flood Nowcasting in Small Catchments using Weather

Radar, 2003, ISBN 3-933761-24-7 122 Haag, Ingo: Der Sauerstoffhaushalt staugeregelter Flüsse am Beispiel des Ne-

ckars - Analysen, Experimente, Simulationen -, 2003, ISBN 3-933761-25-5 123 Appt, Jochen: Analysis of Basin-Scale Internal Waves in Upper Lake Constance,

2003, ISBN 3-933761-26-3

10 Institut für Wasser- und Umweltsystemmodellierung * Universität Stuttgart * IWS 124 Hrsg.: Schrenk, Volker; Batereau, Katrin; Barczewski, Baldur; Weber, Karolin und

Koschitzky, Hans-Peter: Symposium Ressource Fläche und VEGAS - Statuskol-loquium 2003, 30. September und 1. Oktober 2003, 2003, ISBN 3-933761-27-1

125 Omar Khalil Ouda: Optimisation of Agricultural Water Use: A Decision Support

System for the Gaza Strip, 2003, ISBN 3-933761-28-0 126 Batereau, Katrin: Sensorbasierte Bodenluftmessung zur Vor-Ort-Erkundung von

Schadensherden im Untergrund, 2004, ISBN 3-933761-29-8 127 Witt, Oliver: Erosionsstabilität von Gewässersedimenten mit Auswirkung auf den

Stofftransport bei Hochwasser am Beispiel ausgewählter Stauhaltungen des Ober-rheins, 2004, ISBN 3-933761-30-1

128 Jakobs, Hartmut: Simulation nicht-isothermer Gas-Wasser-Prozesse in komplexen

Kluft-Matrix-Systemen, 2004, ISBN 3-933761-31-X 129 Li, Chen-Chien: Deterministisch-stochastisches Berechnungskonzept zur Beurtei-

lung der Auswirkungen erosiver Hochwasserereignisse in Flussstauhaltungen, 2004, ISBN 3-933761-32-8

130 Reichenberger, Volker; Helmig, Rainer; Jakobs, Hartmut; Bastian, Peter; Niessner,

Jennifer: Complex Gas-Water Processes in Discrete Fracture-Matrix Systems: Up-scaling, Mass-Conservative Discretization and Efficient Multilevel Solution, 2004, ISBN 3-933761-33-6

131 Hrsg.: Barczewski, Baldur; Koschitzky, Hans-Peter; Weber, Karolin; Wege, Ralf:

VEGAS - Statuskolloquium 2004, Tagungsband zur Veranstaltung am 05. Oktober 2004 an der Universität Stuttgart, Campus Stuttgart-Vaihingen, 2004, ISBN 3-933761-34-4

132 Asie, Kemal Jabir: Finite Volume Models for Multiphase Multicomponent Flow

through Porous Media. 2005, ISBN 3-933761-35-2 133 Jacoub, George: Development of a 2-D Numerical Module for Particulate Con-

taminant Transport in Flood Retention Reservoirs and Impounded Rivers, 2004, ISBN 3-933761-36-0

134 Nowak, Wolfgang: Geostatistical Methods for the Identification of Flow and Trans-

port Parameters in the Subsurface, 2005, ISBN 3-933761-37-9 135 Süß, Mia: Analysis of the influence of structures and boundaries on flow and

transport processes in fractured porous media, 2005, ISBN 3-933761-38-7 136 Jose, Surabhin Chackiath: Experimental Investigations on Longitudinal Dispersive

Mixing in Heterogeneous Aquifers, 2005, ISBN: 3-933761-39-5 137 Filiz, Fulya: Linking Large-Scale Meteorological Conditions to Floods in Mesoscale

Catchments, 2005, ISBN 3-933761-40-9

Verzeichnis der Mitteilungshefte 11 138 Qin, Minghao: Wirklichkeitsnahe und recheneffiziente Ermittlung von Temperatur

und Spannungen bei großen RCC-Staumauern, 2005, ISBN 3-933761-41-7 139 Kobayashi, Kenichiro: Optimization Methods for Multiphase Systems in the Sub-

surface - Application to Methane Migration in Coal Mining Areas, 2005, ISBN 3-933761-42-5

140 Rahman, Md. Arifur: Experimental Investigations on Transverse Dispersive Mixing

in Heterogeneous Porous Media, 2005, ISBN 3-933761-43-3 141 Schrenk, Volker: Ökobilanzen zur Bewertung von Altlastensanierungsmaßnahmen,

2005, ISBN 3-933761-44-1 142 Hundecha, Hirpa Yeshewatesfa: Regionalization of Parameters of a Conceptual

Rainfall-Runoff Model, 2005, ISBN: 3-933761-45-X 143 Wege, Ralf: Untersuchungs- und Überwachungsmethoden für die Beurteilung na-

türlicher Selbstreinigungsprozesse im Grundwasser, 2005, ISBN 3-933761-46-8 144 Breiting, Thomas: Techniken und Methoden der Hydroinformatik - Modellierung

von komplexen Hydrosystemen im Untergrund, 2006, 3-933761-47-6 145 Hrsg.: Braun, Jürgen; Koschitzky, Hans-Peter; Müller, Martin: Ressource Unter-

grund: 10 Jahre VEGAS: Forschung und Technologieentwicklung zum Schutz von Grundwasser und Boden, Tagungsband zur Veranstaltung am 28. und 29. Sep-tember 2005 an der Universität Stuttgart, Campus Stuttgart-Vaihingen, 2005, ISBN 3-933761-48-4

146 Rojanschi, Vlad: Abflusskonzentration in mesoskaligen Einzugsgebieten unter

Berücksichtigung des Sickerraumes, 2006, ISBN 3-933761-49-2 147 Winkler, Nina Simone: Optimierung der Steuerung von Hochwasserrückhaltebe-

cken-systemen, 2006, ISBN 3-933761-50-6 148 Wolf, Jens: Räumlich differenzierte Modellierung der Grundwasserströmung allu-

vialer Aquifere für mesoskalige Einzugsgebiete, 2006, ISBN: 3-933761-51-4 149 Kohler, Beate: Externe Effekte der Laufwasserkraftnutzung, 2006,

ISBN 3-933761-52-2 150 Hrsg.: Braun, Jürgen; Koschitzky, Hans-Peter; Stuhrmann, Matthias: VEGAS-

Statuskolloquium 2006, Tagungsband zur Veranstaltung am 28. September 2006 an der Universität Stuttgart, Campus Stuttgart-Vaihingen, 2006, ISBN 3-933761-53-0

151 Niessner, Jennifer: Multi-Scale Modeling of Multi-Phase - Multi-Component Pro-

cesses in Heterogeneous Porous Media, 2006, ISBN 3-933761-54-9 152 Fischer, Markus: Beanspruchung eingeerdeter Rohrleitungen infolge Austrocknung

bindiger Böden, 2006, ISBN 3-933761-55-7

12 Institut für Wasser- und Umweltsystemmodellierung * Universität Stuttgart * IWS 153 Schneck, Alexander: Optimierung der Grundwasserbewirtschaftung unter Berück-

sichtigung der Belange der Wasserversorgung, der Landwirtschaft und des Natur-schutzes, 2006, ISBN 3-933761-56-5

154 Das, Tapash: The Impact of Spatial Variability of Precipitation on the Predictive

Uncertainty of Hydrological Models, 2006, ISBN 3-933761-57-3 155 Bielinski, Andreas: Numerical Simulation of CO2 sequestration in geological forma-

tions, 2007, ISBN 3-933761-58-1 156 Mödinger, Jens: Entwicklung eines Bewertungs- und Entscheidungsunterstüt-

zungssystems für eine nachhaltige regionale Grundwasserbewirtschaftung, 2006, ISBN 3-933761-60-3

157 Manthey, Sabine: Two-phase flow processes with dynamic effects in porous

media - parameter estimation and simulation, 2007, ISBN 3-933761-61-1 158 Pozos Estrada, Oscar: Investigation on the Effects of Entrained Air in Pipelines,

2007, ISBN 3-933761-62-X 159 Ochs, Steffen Oliver: Steam injection into saturated porous media – process

analysis including experimental and numerical investigations, 2007, ISBN 3-933761-63-8

160 Marx, Andreas: Einsatz gekoppelter Modelle und Wetterradar zur Abschätzung

von Niederschlagsintensitäten und zur Abflussvorhersage, 2007, ISBN 3-933761-64-6

161 Hartmann, Gabriele Maria: Investigation of Evapotranspiration Concepts in Hydro-

logical Modelling for Climate Change Impact Assessment, 2007, ISBN 3-933761-65-4

162 Kebede Gurmessa, Tesfaye: Numerical Investigation on Flow and Transport Char-

acteristics to Improve Long-Term Simulation of Reservoir Sedimentation, 2007, ISBN 3-933761-66-2

163 Trifković, Aleksandar: Multi-objective and Risk-based Modelling Methodology for

Planning, Design and Operation of Water Supply Systems, 2007, ISBN 3-933761-67-0

164 Götzinger, Jens: Distributed Conceptual Hydrological Modelling - Simulation of

Climate, Land Use Change Impact and Uncertainty Analysis, 2007, ISBN 3-933761-68-9

165 Hrsg.: Braun, Jürgen; Koschitzky, Hans-Peter; Stuhrmann, Matthias: VEGAS –

Kolloquium 2007, Tagungsband zur Veranstaltung am 26. September 2007 an der Universität Stuttgart, Campus Stuttgart-Vaihingen, 2007, ISBN 3-933761-69-7

166 Freeman, Beau: Modernization Criteria Assessment for Water Resources Plan-

ning; Klamath Irrigation Project, U.S., 2008, ISBN 3-933761-70-0

Verzeichnis der Mitteilungshefte 13 167 Dreher, Thomas: Selektive Sedimentation von Feinstschwebstoffen in Wechselwir-

kung mit wandnahen turbulenten Strömungsbedingungen, 2008, ISBN 3-933761-71-9

168 Yang, Wei: Discrete-Continuous Downscaling Model for Generating Daily Precipi-

tation Time Series, 2008, ISBN 3-933761-72-7 169 Kopecki, Ianina: Calculational Approach to FST-Hemispheres for Multiparametrical

Benthos Habitat Modelling, 2008, ISBN 3-933761-73-5 170 Brommundt, Jürgen: Stochastische Generierung räumlich zusammenhängender

Niederschlagszeitreihen, 2008, ISBN 3-933761-74-3 171 Papafotiou, Alexandros: Numerical Investigations of the Role of Hysteresis in Het-

erogeneous Two-Phase Flow Systems, 2008, ISBN 3-933761-75-1 172 He, Yi: Application of a Non-Parametric Classification Scheme to Catchment Hy-

drology, 2008, ISBN 978-3-933761-76-7 173 Wagner, Sven: Water Balance in a Poorly Gauged Basin in West Africa Using At-

mospheric Modelling and Remote Sensing Information, 2008, ISBN 978-3-933761-77-4

174 Hrsg.: Braun, Jürgen; Koschitzky, Hans-Peter; Stuhrmann, Matthias; Schrenk, Vol-

ker: VEGAS-Kolloquium 2008 Ressource Fläche III, Tagungsband zur Veranstal-tung am 01. Oktober 2008 an der Universität Stuttgart, Campus Stuttgart-Vaihingen, 2008, ISBN 978-3-933761-78-1

175 Patil, Sachin: Regionalization of an Event Based Nash Cascade Model for Flood

Predictions in Ungauged Basins, 2008, ISBN 978-3-933761-79-8 176 Assteerawatt, Anongnart: Flow and Transport Modelling of Fractured Aquifers

based on a Geostatistical Approach, 2008, ISBN 978-3-933761-80-4 177 Karnahl, Joachim Alexander: 2D numerische Modellierung von multifraktionalem

Schwebstoff- und Schadstofftransport in Flüssen, 2008, ISBN 978-3-933761-81-1 178 Hiester, Uwe: Technologieentwicklung zur In-situ-Sanierung der ungesättigten Bo-

denzone mit festen Wärmequellen, 2009, ISBN 978-3-933761-82-8 179 Laux, Patrick: Statistical Modeling of Precipitation for Agricultural Planning in the

Volta Basin of West Africa, 2009, ISBN 978-3-933761-83-5 180 Ehsan, Saqib: Evaluation of Life Safety Risks Related to Severe Flooding, 2009,

ISBN 978-3-933761-84-2 181 Prohaska, Sandra: Development and Application of a 1D Multi-Strip Fine Sedi-

ment Transport Model for Regulated Rivers, 2009, ISBN 978-3-933761-85-9

14 Institut für Wasser- und Umweltsystemmodellierung * Universität Stuttgart * IWS 182 Kopp, Andreas: Evaluation of CO2 Injection Processes in Geological Formations

for Site Screening, 2009, ISBN 978-3-933761-86-6 183 Ebigbo, Anozie: Modelling of biofilm growth and its influence on CO2 and water

(two-phase) flow in porous media, 2009, ISBN 978-3-933761-87-3 184 Freiboth, Sandra: A phenomenological model for the numerical simulation of

multiphase multicomponent processes considering structural alterations of po-rous media, 2009, ISBN 978-3-933761-88-0

185 Zöllner, Frank: Implementierung und Anwendung netzfreier Methoden im Kon-

struktiven Wasserbau und in der Hydromechanik, 2009, ISBN 978-3-933761-89-7

186 Vasin, Milos: Influence of the soil structure and property contrast on flow and

transport in the unsaturated zone, 2010, ISBN 978-3-933761-90-3 187 Li, Jing: Application of Copulas as a New Geostatistical Tool, 2010, ISBN 978-3-

933761-91-0 188 AghaKouchak, Amir: Simulation of Remotely Sensed Rainfall Fields Using Copu-

las, 2010, ISBN 978-3-933761-92-7 189 Thapa, Pawan Kumar: Physically-based spatially distributed rainfall runoff model-

ling for soil erosion estimation, 2010, ISBN 978-3-933761-93-4 190 Wurms, Sven: Numerische Modellierung der Sedimentationsprozesse in Retenti-

onsanlagen zur Steuerung von Stoffströmen bei extremen Hochwasserabflusser-eignissen, 2011, ISBN 978-3-933761-94-1

191 Merkel, Uwe: Unsicherheitsanalyse hydraulischer Einwirkungen auf Hochwasser-

schutzdeiche und Steigerung der Leistungsfähigkeit durch adaptive Strömungs-modellierung, 2011, ISBN 978-3-933761-95-8

192 Fritz, Jochen: A Decoupled Model for Compositional Non-Isothermal Multiphase

Flow in Porous Media and Multiphysics Approaches for Two-Phase Flow, 2010, ISBN 978-3-933761-96-5

193 Weber, Karolin (Hrsg.): 12. Treffen junger WissenschaftlerInnen an Wasserbauin-

stituten, 2010, ISBN 978-3-933761-97-2 194 Bliefernicht, Jan-Geert: Probability Forecasts of Daily Areal Precipitation for Small

River Basins, 2011, ISBN 978-3-933761-98-9 195 Hrsg.: Koschitzky, Hans-Peter; Braun, Jürgen: VEGAS-Kolloquium 2010 In-situ-

Sanierung - Stand und Entwicklung Nano und ISCO -, Tagungsband zur Veran-staltung am 07. Oktober 2010 an der Universität Stuttgart, Campus Stuttgart-Vaihingen, 2010, ISBN 978-3-933761-99-6

Verzeichnis der Mitteilungshefte 15 196 Gafurov, Abror: Water Balance Modeling Using Remote Sensing Information - Fo-

cus on Central Asia, 2010, ISBN 978-3-942036-00-9 197 Mackenberg, Sylvia: Die Quellstärke in der Sickerwasserprognose:

Möglichkeiten und Grenzen von Labor- und Freilanduntersuchungen, 2010, ISBN 978-3-942036-01-6

198 Singh, Shailesh Kumar: Robust Parameter Estimation in Gauged and Ungauged

Basins, 2010, ISBN 978-3-942036-02-3 199 Doğan, Mehmet Onur: Coupling of porous media flow with pipe flow, 2011,

ISBN 978-3-942036-03-0 200 Liu, Min: Study of Topographic Effects on Hydrological Patterns and the Implica-

tion on Hydrological Modeling and Data Interpolation, 2011, ISBN 978-3-942036-04-7

201 Geleta, Habtamu Itefa: Watershed Sediment Yield Modeling for Data Scarce Ar-

eas, 2011, ISBN 978-3-942036-05-4 202 Franke, Jörg: Einfluss der Überwachung auf die Versagenswahrscheinlichkeit von

Staustufen, 2011, ISBN 978-3-942036-06-1 203 Bakimchandra, Oinam: Integrated Fuzzy-GIS approach for assessing regional soil

erosion risks, 2011, ISBN 978-3-942036-07-8 204 Alam, Muhammad Mahboob: Statistical Downscaling of Extremes of Precipita-

tion in Mesoscale Catchments from Different RCMs and Their Effects on Local Hydrology, 2011, ISBN 978-3-942036-08-5

205 Hrsg.: Koschitzky, Hans-Peter; Braun, Jürgen: VEGAS-Kolloquium 2011 Flache

Geothermie - Perspektiven und Risiken, Tagungsband zur Veranstaltung am 06. Oktober 2011 an der Universität Stuttgart, Campus Stuttgart-Vaihingen, 2011, ISBN 978-3-933761-09-2

206 Haslauer, Claus: Analysis of Real-World Spatial Dependence of Subsurface

Hydraulic Properties Using Copulas with a Focus on Solute Transport Behav-iour, 2011, ISBN 978-3-942036-10-8

207 Dung, Nguyen Viet: Multi-objective automatic calibration of hydrodynamic mod-

els – development of the concept and an application in the Mekong Delta, 2011, ISBN 978-3-942036-11-5

208 Hung, Nguyen Nghia: Sediment dynamics in the floodplain of the

Mekong Delta, Vietnam, 2011, ISBN 978-3-942036-12-2 209 Kuhlmann, Anna: Influence of soil structure and root water uptake on flow in the

unsaturated zone, 2012, ISBN 978-3-942036-13-9

16 Institut für Wasser- und Umweltsystemmodellierung * Universität Stuttgart * IWS 210 Tuhtan, Jeffrey Andrew: Including the Second Law Inequality in Aquatic Ecody-

namics: A Modeling Approach for Alpine Rivers Impacted by Hydropeaking, 2012, ISBN 978-3-942036-14-6

211 Tolossa, Habtamu: Sediment Transport Computation Using a Data-Driven Adap-

tive Neuro-Fuzzy Modelling Approach, 2012, ISBN 978-3-942036-15-3 212 Tatomir, Alexandru-Bodgan: From Discrete to Continuum Concepts of Flow in

Fractured Porous Media, 2012, ISBN 978-3-942036-16-0 213 Erbertseder, Karin: A Multi-Scale Model for Describing Cancer-Therapeutic Trans-

port in the Human Lung, 2012, ISBN 978-3-942036-17-7 214 Noack, Markus: Modelling Approach for Interstitial Sediment Dynamics and Repro-

duction of Gravel Spawning Fish, 2012, ISBN 978-3-942036-18-4 215 De Boer, Cjestmir Volkert: Transport of Nano Sized Zero Valent Iron Colloids dur-

ing Injection into the Subsurface, 2012, ISBN 978-3-942036-19-1 Die Mitteilungshefte ab der Nr. 134 (Jg. 2005) stehen als pdf-Datei über die Homepage des Instituts: www.iws.uni-stuttgart.de zur Verfügung.

Documents

Transport of Nano Sized Zero Valent Iron Colloids during