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Colloid Transport in the Subsurface

Past, Present, and Future Challenges

Department of Earth and Planetary Sciences, 306 Earth and Planetary Sciences Bldg., University of Tennessee, Knoxville, TN 37996-1410

View larger version (12K): [in a new window]   Fig. 1. The main result of the Grimsel Colloid Exercise interlaboratory comparison of the cumulative size distribution of colloidal particles recovered at the Grimsel Test Site. Laboratories that contributed to this exercise included: Atomic Energy of Canada, Limited (AECL); British Geological Survey (BGS); Commissariat de l'Energie Atomique (CEA); Paul Scherrer Institute (PSI); Harwell Laboratory Nuclear Physics Division (UKNP); and the University of Norway (UNOS). Techniques used to characterize colloids includes gravimetry (GRAV), scanning electron microscopy (SEM), single-particle counting (PC), and transmission electron microscopy (TEM). The cumulative contribution of different sized particles to the total colloid concentration in Grimsel groundwater (particles [pt] L–1) is indicated. The cumulative size distribution follows Pareto's power law: logCn = 15.8(±0.4) – 3.2(±0.2) log(d), where Cn is the cumulative particle concentration for sizes ranging from 25000 nm to d (Degueldre et al., 1989).

View larger version (41K): [in a new window]   Fig. 2. Influence of patchwise heterogeneity on colloid transport. (a) Zeta potential as a function of solution pH for clean sand grains (filled circles), aminosilane-modified sand grains (filled triangles), and various mixtures of aminosilane-modified and clean sand grains (open symbols). Zeta potentials were calculated from measured streaming potentials. Experiments were conducted with 10–3 M NaCl as a background electrolyte at a temperature of 21°C. (b) Colloid transport in chemically heterogeneous granular porous medium at pH 5.6 to 5.8 and solution ionic strength of 10–3 M. Colloid breakthrough curves are expressed as normalized colloid concentration at the column effluent as a function of pore volume for various mixtures of aminosilane-modified and clean sand grains (ranging from clean sand, 0%, for the top curve to 100% for the bottom curve) (Elimelech et al., 2000).

View larger version (21K): [in a new window]   Fig. 3. Transport of four sizes of colloids through a saprolite monolith using input solutions of varying cation charge and ionic strengths. (a) The recovery of different sized microspheres is plotted as a function of the concentration of Na1+ (dotted lines) or Ca2+ (solid lines) in the influent tracer solution. The open symbols represent the percentage of recovery of microspheres in a replicate experiment conducted at the end of the series of injection experiments. (b) The concentration of monovalent (Na and K) and divalent (Ca and Mg) cations in the effluent of the monolith is plotted as a function of the concentration of Na+1 (bottom axis) or Ca+2 (top axis). The effluent concentrations of mono- and divalent cations during the experiments with Na+1 input solutions is shown on the left axis, while the effluent concentration of divalent cations during the experiments with Ca+2 input solutions is shown on the right axis. (c) The recovery of microspheres is plotted as a function of the concentration of divalent cations (sum of Ca2+ and Mg2+) in the column effluent (McCarthy et al., 2002).

View larger version (113K): [in a new window]   Fig. 4. Photograph of an exposure of a typical clay till overlying the Danien limestone in Denmark. The yellow staining results from infiltration along fractures through the till to the aquifer. For scale, the shovel at the bottom of the profile is 1.2 m long (source: Knud Erik Klint, Danish Geological Survey, GEUS).

View larger version (80K): [in a new window]   Fig. 5. Moisture content visualization of finger formation and persistence in a sand slab (Glass et al., 1989).