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High-resolution single-particle quantification of colloid transport processes [Elektronische Ressource] / Laura Gérard

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Published 01 January 2011
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Technische Universitat Munchen
High-Resolution Single-Particle
Quanti cation of Colloid Transport
Processes
Laura Gerard
Institut fur Wasserchemie und Chemische Balneologie
Lehrstuhl fur Analytische Chemie TECHNISCHE UNIVERSITAT MUNCHEN
Institut fur Wasserchemie und Chemische Balneologie
Lehrstuhl fur Analytische Chemie
High-Resolution Single-Particle
Quanti cation of Colloid Transport
Processes
Laura Gerard
Vollst andiger Abdruck der von der Fakult at fur Chemie
der Technischen Universit at Munc hen zur Erlangung des akademischen Grades
eines Doktors der Naturwissenschaften
genehmigten Dissertation.
Vorsitzender: Univ. -Prof. Dr. M. Schuster
Prufer der Dissertation:
1. Univ. -Prof. Dr. R. Nie ner
2. Univ. -Prof. Dr. K. -O Hinrichsen
Die Dissertation wurde am 08.12.2010 bei der Technischen Universit at
Munc hen eingereicht und durch die Fakult at fur Chemie
am 10.03.2011 angenommen.Part of this thesis has been published in Water Research, volume 44 (2010), pp. 1246-
1254.Abstract
The objectives of this thesis were to determine what physical and chemical factors e ect
colloid dispersion and to observe and quantify this on the pore scale in a micro uidic
system, which mimics the pore topology of an aquifer. The trajectories of carboxy-
lated polystyrene microspheres were collected during transport experiments in silicon
micromodels with three pore topologies. The trajectories revealed the ow path of indi-
vidual colloids. More than a thousand trajectories were evaluated for each experiment
to obtain the dispersivity of the colloids for ow distances between 10 and 1000 m.
All experiments were run at high Peclet numbers. The pore scale dispersivity was de-
pendent on the heterogeneity of the pore topology and was on the order of 8-30% of
the ow distance with pure water. The physical and chemical parameters studied were
the e ects in the pore topology (Heterogeneous:porosity = 0.36, Diamond:porosity =
0.27, and Ellipsoid:porosity = 0.26), the e ects in the velocity (0.5-5 m/d), the e ects
9 11in colloid size (1m, 0.5m), the e ects in colloid concentration (2.7 x 10 - 2.7 x 10
particles/L), the change in ionic strength (0 - 0.01 M NaCl), and the change in surface
functionalities (using 2 mg/L and 20 mg/L of humic acid). The highest dispersion values
were found in the Heterogeneous micromodel and the lowest values were found in the
Ellipsoid and Diamond models. It was determined that by decreasing the ow rate to 5
L/h increased dispersivity by 15 % (Diamond and Heterogeneous) to 27 % (Ellipsoid).
Due to di usion, decreasing the colloid size by a factor of two, dramatically
increased the observed dispersivity by over 100% in the Ellipsoid micromodel, over 200%
in the Heterogeneous model and 5% in the Diamond micromodel. The higher the con-
centration of colloids the more colloid-colloid interactions took place, thus increasing
the concentration by a factor of 100, increased the chance of colloids deviating from the
path line. With increasing ionic strength, the interaction of colloids with one another
and the porous matrix increased. There was a 50 % increase of dispersivity when the
ionic strength increased from pure water to 0.01 M NaCl in the Ellipsoid micromodel.
Finally, adding humic acids to the micromodel and to the colloid suspensions stabilised
the colloids and prevented attachment and increased colloid dispersivity.
The dispersivity studies used Particle Tracking and a new range of programs created in
R. This provided an opportunity to accurately calculate particle dispersivity, velocity,
etc. Trajectories were counted accurately 95 % of the time and it was possible to count
thousands of trajectories at once. This study provides insight into the scale dependency
of colloid dispersion on the pore scale.Acknowledgements
I would like to thank my supervisor, Thomas Baumann, whose guidance and support
from the initial to the nal level enabled me to develop an understanding of the sub-
ject, and who was behind the R programming, without which I would have had much
di culty. My research was funded by the DFG project, Ba 1592/3-1. I would also
like to thank Reinhard Niessner; my colleagues and coworkers Carsten Kykal, Clemens
Helmbrecht, Sebastian Wiesemann, Birgit Apel, Joachim Langer, Christina Mayr, Su-
sanne Huckele and Jimena Sauceda-Friebe; Charles Werth and Thomas Willingham for
providing the micromodels used during the project.
Lastly, I o er my regards and blessings to all of those who supported me in any respect
during the completion of the project. My parents, Tim and Connie Toops who always
provided an encouraging word and always believed in me. My husband, Franck Gerard
for providing a listening ear.
iiiContents
Abstract ii
Acknowledgements iii
List of Figures vi
List of Tables vii
1 Background 1
1.1 Colloid Transport Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Factors Governing Colloidal Transport . . . . . . . . . . . . . . . . . . . . 3
1.2.1 Advection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.2 Dispersion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.2.3 Colloid-Colloid and Colloid-Matrix Interactions . . . . . . . . . . . 8
1.2.4 E ects of DOM on Colloid Transport . . . . . . . . . . . . . . . . 14
1.3 Quanti cation of Colloidal Transport Processes . . . . . . . . . . . . . . . 15
1.3.1 Field Scale Experiments/Column Experiments . . . . . . . . . . . 15
1.3.2 Pore Scale Expts . . . . . . . . . . . . . . . . . . . . . . . . 17
1.3.3 Image Processing and Evaluation . . . . . . . . . . . . . . . . . . . 19
2 Materials and Methods 21
2.1 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.2.1 Colloid Characterisation . . . . . . . . . . . . . . . . . . . . . . . . 23
2.2.2 Micromodel Experiments . . . . . . . . . . . . . . . . . . . . . . . 24
2.2.3 Modi cation of Colloids and Matrix Surfaces . . . . . . . . . . . . 25
2.2.4 Image Acquisition and Processing . . . . . . . . . . . . . . . . . . 26
2.2.5 Image Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3 Results and Discussion 32
3.1 Development of an Automated Colloid Tracking Procedure . . . . . . . . 32
3.1.1 Image Preprocessing . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.1.2 Results with PIV . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.1.3 Optimization of PT . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.1.4 Validation of PT . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
ivContents v
3.2 Quanti cation of Colloid Dispersion on the Pore Scale . . . . . . . . . . . 38
3.2.1 E ects of Average Linear Velocity . . . . . . . . . . . . . . . . . . 38
3.2.2 E ects of Pore Topology . . . . . . . . . . . . . . . . . . . . . . . . 42
3.2.3 E ect of Colloid Size . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.2.4 E ects of Colloid-Colloid and Colloid-Matrix Interactions . . . . . 45
3.2.5 Change in Colloid Concentration . . . . . . . . . . . . . . . . . . . 47
3.2.6 of Ionic Strength . . . . . . . . . . . . . . . . . . . . . . . 49
3.2.7 E ects of Surface Functionality . . . . . . . . . . . . . . . . . . . . 51
3.2.7.1 The In uence of Humic Acids on Colloid Stability/At-
tachment . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.3 Colloid Residence Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
4 Summary 62
A Chemicals List 64
B Abbreviations and Symbols List 66
B.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
B.2 Symbols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
Bibliography 68List of Figures
1.1 Transport behavior of colloids in porous media - Fetter, 2001. . . . . . . . 4
1.2 The spreading e ect of a colloid suspension in the subsurface environment
due to advection and dispersion. . . . . . . . . . . . . . . . . . . . . . . . 6
1.3 Transport and spreading of a colloidal suspension. . . . . . . . . . . . . . 7
1.4 Filtration theory (Baumann, 2002) . . . . . . . . . . . . . . . . . . . . . . 9
1.5 E ect of ionic strength on the dispersion of colloids. . . . . . . . . . . . . 13
2.1 Silicon-etched micromodels: Ellipsoid, Diamond and Heterogeneous. . . . 22
2.2 Schematic ofdel setup. . . . . . . . . . . . . . . . . . . . . . . . . 22
2.3 Zetaphoremeter IV. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.4 Image processing - colloid shape homogenizing and center of mass. . . . . 27
2.5 The image process from start to nish. . . . . . . . . . . . . . . . . . . . . 27
2.6 Coordinate list with time stamp. . . . . . . . . . . . . . . . . . . . . . . . 28
2.7 PIV tracking the movement of a single particle. . . . . . . . . . . . . . . . 28
2.8 Example trajectories in the Ellipsoid, Diamond, and Heterogeneous mi-
cromodels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.1 PIV Output. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.2 PT tracking errors - 1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.3 PT tracking errors - 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.4 Histogram of average trajectory lengths. . . . . . . . . . . . . . . . . . . . 37
3.5 Hand-tracked vs. computer-tracked particles. . . . . . . . . . . . . . . . . 39
3.6 Variance of the trajectories’ velocity in the Ellipsoid and Diamond micro-
models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.7 Variance of trajectories’ velocity in the Heterogeneous micromodel . . . . 41
3.8 The e ect of pore topology on colloid dispersivity? . . . . . . . . . . . . . 42
3.9 View of trajectories in half of a micromodel . . . . . . . . . . . . . . . . . 43
3.10 Breakdown of the dispersivity graph. . . . . . . . . . . . . . . . . . . . . . 44
3.11 Brownian motion in the Heterogeneous micromodel with 0.2 m colloids. 45
3.12 Interaction energies for colloid-matrix/colloid-colloid. . . . . . . . . . . . . 46
3.13 Bar chart showing number of particles crossing over into other pathways. 47
3.14 Crossover points taken from high concentration tests. . . . . . . . . . . . . 48
3.15 E ect of humic acid on the colloids’ zeta potential. . . . . . . . . . . . . . 51
3.16 DLVO curve for pH bu ers . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.17 E ect of humic acid on colloid attachment e ciency at di erent pH values
and ionic strengths. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.18 Plot of how the emission of uorescence increases as the pH increases. . . 55
3.19 A residence image from the Diamond micromodel. . . . . . . . . . . . . . 56
viList of Tables vii
3.20 Change in residence time for micromodels. . . . . . . . . . . . . . . . . . . 57
3.21 Comparison of frame lengths for each micromodel. . . . . . . . . . . . . . 59
3.22 Frame lengths for ow rate and ionic strength. . . . . . . . . . . . . . . . 60List of Tables
2.1 Image resolution for the CCD camera. . . . . . . . . . . . . . . . . . . . . 26
3.1 Ionic strength for bu er solutions used, calculated from the Zetaphoreme-
TMter IV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
viii