contaminant transport

In: Horizons in Earth Science Research. Volume 6 Editors: Benjamin Veress and Jozsi Szigethy

ISBN: 978-1-61470-462-1 © 2012 Nova Science Publishers, Inc.

The exclusive license for this PDF is limited to personal website use only. No part of this digital document may be reproduced, stored in a retrieval system or transmitted commercially in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services.

Chapter 3

CONTAMINANT TRANSPORT AND FLUID FLOW IN SOILS Franco M. Francisca1,2*, Magali E. Carro Perez1, Daniel A. Glatstein1 and Marcos A. Montoro1 1

Grupo de Investigación en Medios Porosos y Agua Subterránea Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), and Universidad Nacional de Córdoba (UNC) Córdoba, Argentina. 2 Facultad de Ciencias Exactas, Físicas y Naturales (UNC) Departamento de Construcciones Civiles Av. Velez Sarsfield 1611, CP. 5016, Córdoba, Argentina

ABSTRACT Presence of organic and inorganic contaminants in soils affects soil and groundwater quality. The hydraulic conductivity of porous media controls the displacement of liquids in the soil pores and affects the fate and transport of contaminants in the environment. In this chapter we present the influence of relevant soil and permeating liquid properties on fluid displacement and mass transport in soils, including diffusion, advection, retardation, reaction, solubilization and immiscible flow. Then, we address the relevance of microheterogeneities on the displacement and generation of ganglia during the simultaneous flow of water and non-aqueous phase liquids (NAPL). Finally, we discuss the importance of soil hydraulic conductivity and mass transport mechanisms in relation to geoenvironmental applications such as permeable reactive barriers (PRB), soil liners (SL) and smart permeable reactive barriers (SPRB).

*

E-mail address: [email protected]

98

F. M. Francisca, M. E. Carro Perez, D. A. Glatstein et al.

1. INTRODUCTION Organic and inorganic compounds are frequently encountered as contaminants in soils and groundwater. Their displacement inside soil pores is of special interest in several fields including groundwater contamination and remediation studies (Fetter 1993). This phenomenon is mainly controlled by the hydraulic conductivity of the porous media (e.g. soils and rocks) and the geological conditions of the site (Freeze and Cherry 1979). Most significant soil properties controlling fluid displacement and mass transport include effective porosity, degree of saturation, particle size distribution, soil fabric, pore structure and specific surface (Vucković and Soro 1992, Shackelford and Benson 1995). Significant fluid properties include density, viscosity and water miscibility (Mercer and Cohen 1990). Particle-fluid interaction (PFI) mechanisms and/or contaminant transformation may occur during mass transport. This interaction between the solid phase and liquids inside the pores is responsible for ion exchange mechanisms and the development of the diffuse double layer around soil particles, which affects soil fabric and hydraulic conductivity (Montoro and Francisca 2010). In addition, hydraulic conductivity can also be influenced by bacterial growth within pores (Rockhold et al. 2002), spatial variability of porosity (Francisca and Arduino 2007) and the interaction between immiscible liquids in the pores, such as air-water or hydrocarbon-water (Corey 1986). Behavior of immiscible contaminants inside the pores is governed by micro-scale soil properties including pore size distribution, anisotropy and spatial variability of porosity. Capillary, viscous and gravity forces control the instability of interfaces and ganglia generation which are responsible for the residual oil saturation during the remediation of contaminated sites. The presence of contaminants decrease soil and groundwater quality. Their interaction with the porous media is a dynamic process that includes diffusion, advection, occlusion, precipitation/dissolution, and degradation. Consequently, these substances may pollute groundwater reservoirs immediately or as a long term source; or may also be chemically or biologically altered depending on existing subsurface conditions (Sharma and Reddy 2004). These processes have significant influence on remediation techniques during the removal of organic and inorganic contaminants from soils and groundwater (Suthersan 1997). In this chapter, we present all soil and liquid properties that are relevant to understand contaminant movement in soils, considering the transport of dissolved and immiscible contaminants in porous media. For dissolved contaminants, the generalized advectiondiffusion model from mass equilibrium is discussed to address the relevance of mechanical dispersion, sorption and biodegradation of pollutants during mass transport mechanisms. In the case of immiscible pollutants, the displacement of liquids is analyzed by considering the influence of viscosity ratio, specific surface of particles, soil fabric and PFI on hydraulic conductivity. Finally, we present some practical aspects related to the relevance of hydraulic conductivity on several geoenvironmental problems, including permeable reactive barriers, landfills and surface impoundments and the possibility of designing smart permeable reactive barriers (SPRB) by controlling soil hydraulic conductivity with the aid of bacteria. The last gives the possibility of developing new site remediation techniques and improving waste and leachate containment in landfills.

Contaminant Transport and Fluid Flow in Soils

99

2. PHYSICOCHEMICAL PROPERTIES OF SOILS 2.1. Particles and Pore Water Porous media are mixtures of liquid, gaseous and solid phases. Soil grains are formed by weathering and alteration of rocks. Then, size and mineralogy of soil grains depend on parent rock properties, environmental conditions and physicochemical processes during soil formation. The liquid phase is in general water, sometimes with dissolved chemical compounds, or non-aqueous phase liquids (NAPL). The water phase is of fundamental importance for soil behavior given that it controls relevant engineering and geological properties such as plasticity, shrinkage, flow and stress-strain behavior of soils (Freeze and Cherry 1979). Pore water can be found as adsorbed, funicular/capillary or free water. Given that water is a polar molecule, it has the ability to hydrate ions which interact with the electrical surface charges of mineral particles. This effect becomes of relevance in the case of fine particle soils (Santamarina et al. 2001). Capillary water is under negative pressure and is relevant for the liquid and mass transport in partially saturated soils in the vadose zone. At higher water contents, in the case of saturated soils, water is mainly controlled by gravity.

2.2. Double layer And Soil Fabric Electrical surface charges of soil particles are relevant for the mechanical and hydraulic behavior of fine soils, while gravity effect prevails in coarse soils. Relevance of electrical forces is frequently associated to geomaterials with high specific surface or soil particles with a high surface-to-mass ratio. Then, unbalanced electric surface charges, which are pH dependent, control the behavior of electrical charges and dipoles near the surface (e.g. hydrated ions and water molecules). The electric field generated by soil particles attracts and repulses the hydrated cations and anions which are distributed in the space forming the diffuse double layer (Mitchell and Soga 2005). Water molecules and ions are strongly attracted to the surface at short distances from mineral particles forming the Stern layer. Outside this layer orientation of water molecules and ion distribution are affected by the electric field in a region known as diffuse layer. The double layer thickness, [m], also known as Debye-Hückel length, is related to the liquid properties as follows (Adamson and Gast 1997): ϑ=

ε 0 Rκ ′ T 2F 2 c 0 z 2

.

(1)

Where R (= 8.314 J/(Kmol)) is the universal gas constant, F (= 9.648 x 104 C/m) is Faraday‟s constant, 0 (= 8.85 x10-12 F/m) is the vacuum dielectric permittivity, T [K] is the absolute temperature, c0 [mol/m3] is the bulk electrolyte concentration, ´ is the real relative permittivity, and z the ion valence.


Repulsion

100

low c 0

dispersed fabric

Attraction

medium c 0

Distance high c 0

flocculated fabric

Figure 1. Influence of distance and ion concentration on the net force between particles.

Electrical forces related to the surface charge and presence of ions in the diffuse double layer regulate soil fabric (Palomino and Santamarina 2005). Soil particles and their double layers interact with each other generating particle repulsion, while van der Waals forces produce an attraction effect. The balance between repulsive and attractive forces gives the net force which depends on the distance between particles and ionic concentration in the pore fluid (Figure 1).

3. LIQUIDS DISPLACEMENT IN POROUS MEDIA 3.1. Water Flow Fluid flow through soil pores can be described by Darcy‟s law (equation (2)). This equation relates the “apparent” or Darcy velocity v [m/s] of the fluid flowing through the porous media to the hydraulic gradient (ih) and the feasibility of the liquid to pass through the soil, known as hydraulic conductivity k [m/s]. ∂H

v = k ih = k ∂x .

(2)

Where H [m] is the head pressure and x [m] is the length of the flow path. Then, hydraulic conductivity is the flow velocity when the hydraulic gradient is equal to one. The linear relationship between seepage velocity and hydraulic gradient indicates that the flow remains laminar. However, at higher hydraulic gradients water displacement starts to be turbulent as velocity increases. Also, non-linear behavior is observed at very low hydraulic gradients, or low velocities, because under this condition water behaves as a non-newtonian fluid (Mitchell and Soga 2005) and bacterial growth can partially clog soil pores (Rockhold et al. 2002). It can be noticed that v is an apparent velocity because Darcy‟s law computes flow per unit area, but the liquid can displace only by the area occupied by pores. Then, a new


101

parameter known as effective velocity (ve) is defined by dividing Darcy‟s velocity by the effective porosity (ne): v

ve = n .

(3)

e

Hydraulic conductivity is the most important parameter to be determined for each situation involving flow processes. This parameter depends on soil porosity, grain size and grain size distribution, soil mineralogy, fluid saturation, fluid viscosity, chemical properties of the fluid and soil fabric (Shackelford and Benson 1995). Hydraulic conductivity decreases when grain size, porosity or degree of saturation decrease, and soil gradation, fine particle content and activity of the fine fraction increase (Fredlund and Rahardjo 1993, Mitchell and Soga 2005). Given that hydraulic conductivity depends on the permeating liquid properties, the seepage velocity may be affected by dissolved ions and fluid viscosity. Conversely, permeability K [m2] is not affected by fluid properties and can be considered as a porous media property. The relationship between permeability and hydraulic conductivity is: k=

Kρg μ

.

(4)

Where g [m/s2] is the acceleration due to gravity, ρ [kg/m3] is the density of the fluid and µ [kg/(ms)] is the dynamic viscosity of the liquid phase. There is not a direct method to determine soil permeability. Then, it must be computed from the liquid properties and hydraulic conductivity measurements. For this reason, the accuracy of hydraulic conductivity measurement is the most important task, given that this parameter varies approximately ten orders of magnitude from 1 m/s for coarse sand or gravels to 10-10 m/s for clays such as smectites (Lambe and Whitman 1969). These measurements can be performed either in laboratory or in situ. Hydraulic conductivity measurements are money and time consuming and are affected by sampling effect and the spatial variability of soil properties. Then, several empirical and theoretical models had been developed with the purpose of relating hydraulic conductivity and permeability with other soil properties such as particle size, particle size distribution or Atterberg Limits (Nagaraj et al. 1993, Boadu 2000, Dolinar 2009). Available models usually consider that soil permeability can be computed as (Vucković and Soro 1992): K = Cφ n d2e .

(5)

Where C is a fitting parameter which depends on soil fabric, grain shape and mineralogy; φ(n) is a porosity function and de is a representative grain size diameter. The most known model is the theoretical equation developed by Kozeny and Carman which relates k, K and relevant soil and fluid properties as follows (Mitchell and Soga 2005): K=k

μ ρg

=k

1 2 2 0 T0 S 0

e3 1+e

S3 .

(6)

102


Where T0 is the tortuosity, k0 is a pore shape factor, S0 [m-1] is the wetted surface area per unit volume of particles, e is the void ratio and S the degree of saturation. Kozeny-Carman´s equation provides fairly good results for coarse soils such as sand or coarse silts. However, in the case of fine silts and clays, predicted and measured hydraulic conductivities may show differences of up to three orders of magnitude given that this equation ignores the effect of double layer on soil structure (Freeze and Cherry 1979). In coarse soils and when soil fabric has negligible effects on hydraulic conductivity, soil porosity (or void ratio) controls the displacement of fluids inside the pores. The effect of porosity is considered by the porosity function included in equation (5) which may justify very important differences in computed permeabilities (Figure 2). This is strongly related to pore sizes and different particle arrangements. For example, coarse spherical particles with simple-cubic and tetrahedral packing have porosities n=0.476 and n=0.26, respectively. According to Figure 2 and equation (5), the expected higher permeability will be 39 times the lower predicted value for the simple-cubic packing, and 83 times for the tetrahedral packing according to Slichter´s and Hazen´s models, respectively (the upper and lower bounds for this range of porosities in Figure 2). 1000

Zamarín -Kozeny Carman (1953) Hazen (1892) Slichter (1898) Terzaghi (1925) Sauerbrei -Kozeny (1953) Krüeger (1953) Zunker (1930)

100

 (n)

10 1 0.1 0.01 0.001 0.0001 0

0.2

0.4

n

0.6

0.8

1

Figure 2. Porosity function of equation 5. Models compiled in Vukovic and Soro (2002).

Flocculated soil fabric has larger pore sizes than dispersed fabric, and therefore soils with dispersed microstructure are less permeable than those with flocculated particle arrangements (Mitchell and Younger 1967). Any of the liquid properties included in equation (1), capable of modifying the double layer thickness and the attraction/repulsion forces between particles, will affect soil hydraulic conductivity (Petrov and Rowe 1997, Jo et al. 2001).


103

3.2. Contaminant Transport 3.2.1. Inert Pollutants Inert chemical compounds do not decompose nor increase the mass of the porous media by chemical, physical or biological deposition. This means that they are conservative and that the contaminant neither change nor is retained by the media. Even this represents only ideal situations, it is the starting point to study the displacement of chemical substances through porous media. Contaminants that do not interact with the media are transported by concentration and hydraulic gradients. In the first case, dissolved contaminants displace from high concentration to low concentration areas due to thermal vibrations related to their inner thermal energy. This random movement is called molecular diffusion. In the second case, the different total pressure between two points induces liquid movement transporting dissolved contaminants by advection. Diffusive transport can take place without water movement or even in the opposite direction to the hydraulic flow. Then, diffusion will only cease when concentration gradients are null. Fick‟s first law relates the concentration gradient with the contaminant mass flow as follows (1D-flow): Fd = −D∗

∂C ∂x

.

(7)

Where Fd [kg/(m2s)] is the diffusive mass flow per unit area and time, D* [m2/s] is the effective diffusion coefficient and dC/dx [kgm-3/m] is the concentration gradient. The effective diffusion coefficient is related to the molecular diffusion coefficient D0 [m2/s] by the following relation: D∗ = ωD0 .

(8)

Where  is a coefficient related to the effective porosity and tortuosity of the porous media. According to Perkins and Johnston (1963), ≈ 0.7 for sands, whereas Freeze and Cherry (1979) suggests values between 0.5 and 0.01 for different geomaterials. In general  is highly variable and should be experimentally determined for each soil condition (Rowe et al. 1988). The molecular diffusion coefficient varies according to the nature and size of the diffusive element, the solvent type and the temperature. Mass transport by advection depends on the contaminant concentration and inflow rate (1D-flow - Sharma and Reddy 2004): Fa = vC = ne ve C .

(9)

Where Fa [kg/m2s] is the advective mass flow, and C [kg/m3] is the contaminant concentration. Longitudinal and transverse mechanical dispersion occurs during mass transport due to differences in flow path lengths, spatial variability of pore sizes and friction between fluid and soil particles. These mechanisms affect the advancing solute front and produce mechanical dispersion which can be computed as:

104

F. M. Francisca, M. E. Carro Perez, D. A. Glatstein et al. DL = αL ve ,

(10)

DT = αT ve .

(11)

Where DL and DT are the longitudinal and transverse mechanical dispersion coefficients, respectively, and L and T are the longitudinal and transverse dispersivities. In general, molecular diffusion and mechanical dispersion take place simultaneously; for this reason their effects are considered as cumulative: D∗L = αL vs + D∗ ,

(12)

D∗T = αT vs + D∗ .

(13)

Where DL* and DT* are the hydrodynamic dispersion coefficients or mixing coefficients. The transport equation for non-reactive solutes considers all three processes mentioned previously, and it is based on the works of Ogata (1970), Bear (1972) and Freeze and Cherry (1979). Assuming homogeneous and isotropic media, saturated with a fluid that follows Darcy‟s law, and considering one-directional flow; the total mass transport per unit area is described by: ∂C

F = ne ve C − ne D∗L ∂x .

(14)

Then, from mass conservation in a representative elementary volume: ∂F ∂x

= −ne

∂C ∂t

.

(15)

Where t [s] is time. Then, replacing F from the total mass transport equation (14) in the mass conservation equation (15), it is obtained the partial differential equation that dominates the solute transport in porous media which is known as advection-diffusion model: D∗L

∂2 C ∂x 2

− ve

∂C ∂x

=

∂C ∂t

.

(16)

3.2.2. Reactive Contaminants Chemical reactions occurring in groundwater may act as sources or sinks for different substances. Depending on the generated or consumed substance, these processes could be detrimental or favorable for the environment. In both cases, if the contaminant concentration changes with time, a rate of mass production/consumption given by the kinetic model of reaction (r) must be included in the advection-diffusion equation as follows: D∗L

∂2 C ∂x 2

− ve

∂C ∂x



r ne

=

∂C ∂t

.

(17)


105

If sorption is the mass transfer processes taking place during the contaminant transport, the mass adsorbed on soil particles (C*) is related to the contaminant concentration (C) through any adsorption isotherm (linear, Freundlich, Langmuir, etc.). In this case, the rate of mass production/consumption becomes: r = γd

∂C ∗ ∂t

.

(18)

Where d is the dry unit weight of porous media. Adsorption delays contaminant percolation and transport. The time, or pore volume of flow, needed by the center of mass of the contaminant to pass through a soil column or reactive barrier, respect to the time or volume expected for non-reactive transport (diffusion + advection) defines a retardation factor (R). This retardation factor can be directly incorporated in equation (16) resulting (Sharma and Reddy 2004): D ∗L ∂ 2 C R ∂x 2

−

v e ∂C R ∂x

=

∂C ∂t

.

(19)

The retardation factor can be experimentally determined or estimated from calibrated isotherm adsorption models. Although direct measurements are preferred; they are only practical in the case of retardation factors lower than 10; otherwise extremely larger experimental times are required for its determination. Other chemical processes that may change the contaminant concentration with time are: a) precipitation and dissolution, b) complex reactions, c) volatilization, d) hydrolysis, e) acidbase reactions, and f) reduction-oxidation (redox) reactions. The first three processes completely modify the contaminant phase, decreasing their mobility; whereas the last three alter the chemical composition, changing the structure or modifying the contaminant speciation and toxicity. Precipitation produces the deposition of dissolved contaminant substances, preventing mass transportation. Conversely, dissolution is the mechanism responsible for the lixiviation of chemical compounds from the minerals to solutions. The formation of solid complexes usually modifies the compound solubility and, in most cases, reduces its bioavailability. During volatilization, the contaminant evaporates from the aqueous phase and is released to the atmosphere. Hydrolysis, acid-base and redox reactions modify the chemical structure of the contaminant (e.g. sulfide converts to sulfate, arsenite converts to arsenate). Hydrolysis reactions are the most important among dissolved organic compounds. During hydrolysis reactions, contaminants split into two parts by the addition of a water molecule (H2O) which is also divided in two fragments (H+ and OH−) that combine with each part of the original pollutant, as follows: RX + H2 O ⟺ ROH + HX .

(20)

Acid-base equilibrium plays a fundamental role on mineral dissolution (e.g. carbonates); and redox reactions are mostly significant in heavy metal contamination. The latter involves the transfer of electrons from one compound to another, changing the molecule speciation, which modifies its solubility and/or its toxicity. These types of reactions occur naturally, although their intensity can be manipulated.

106


In general, contaminant transport models consider that the previous reactions follow a first-order kinetic. This means that the concentration rate due to chemical reactions is given by the following relation: 𝜕𝐶 𝜕𝑡 𝑟𝑥𝑛

= −C ,

(21)

where  [1/s] is the velocity or first-order reaction constant, which is related to the contaminant half-life. The contaminant half-life is the time required to achieve a decrease on concentration to a half of the initial value. Then, can be computed as: =

ln 2 t 1/2

.

(22)

And, the rate of mass production/consumption r in equation (17) results: r =  𝑛e C .

(23)

When diffusion, advection and adsorption effects are negligible, and the chemical reaction follows a first-order kinetic, the concentration change with time is: 𝐶 = C0 e− t .

(24)

3.3. Biologically-enhanced Degradation Degradation is the process by which an organic molecule breaks into smaller molecules, either due to chemical or biological action (Fetter 1993). In the case of biodegradation, specific microorganisms use organic molecules as carbon source, producing methane or carbon dioxide and water, depending on the metabolic pathway that they follow. Biodegradation can either be aerobic or anaerobic. In the first case, molecular oxygen acts as electron acceptor, while in the second one other compounds must be used for this role. For this reason, biological processes affect the life cycle of several chemical elements, including nitrogen, sulfur, iron and manganese. Due to the wide variety of reactions, it is possible to treat hydrocarbon spills, nitrate contamination in agricultural runoff, and sulfate contamination in acid mine drainage, being necessary the addition of an organic carbon source as nutrient in the last two cases. If the required conditions are reached, the contaminant concentration will decrease due to microbiological action, and the evolution of relative concentrations with time will be as shown in Figure 3.

3.4. Immiscible Flow Immiscible flow takes place when at least two different fluids flow simultaneously as independent phases (e.g. water and air, water and oil, oil and gas). Typical immiscible

107


displacement phenomena include water displacement in unsaturated soils, and simultaneous flow of oil and water. The distribution of fluid phases inside the pores depends on fluids and porous media properties. Relevant fluid properties include viscosity, density and saturation degree of each fluid phase; while porosity, pore size distribution, spatial variability of porosity and wettability are relevant properties of the porous media (Mercer and Cohen 1990). Two or more fluid phases within soil pores are separated by interfaces that induce nonlinearities on the macroscopic behavior of fluid displacement (Lenormand 1990, Sahimi 1993). In the case of saturated media, the solid phase is in contact with water or NAPLs. Soils or rocks that are preferentially in contact with water are water-wet or hydrophilic, otherwise they are considered as oil-wet or hydrophobic. Then, the affinity of the mineral surfaces to be wetted by water or NAPL defines its wettability. Continuous Injection Reactor

Contaminant Plug

1

t1

t2

t3

t4

C/C0

C/C0

1

0.5

0

t3

1

t1

t2

t3

t4

C/C0

C/C0

Advection Dispersion

t2

0

1

0.5

0

t1 0.5

Advection Dispersion Sorption

t2 t3

0

1

1

t1

t2

t3

t4

C/C0

C/C0

t1 0.5

0.5

Advection Dispersion Sorption Biodegradation

t1 0.5

t2 0

L

0

t3

x

(a)

(b)

Figure 3: Effects of various processes on the breakthrough curve for (a) continuous injection and (b) plug injection of contaminant.

Interfacial tensions and wettability determine the shape of macroscopic drops of liquids in contact with a solid flat surface as predicted by Young‟s model (Figure 4) (Adamson and Gast 1997): cos θ =

γ nws −γ ws γ nww

.

(25)

Where, nws [N/m] is the oil-solid interfacial tension, nww [N/m] is the oil-water interfacial tension and ws [N/m] is the water-solid interfacial tension. By convention, contact angle is

108


always measured through the aqueous phase, and materials with  < 75º are considered as water-wet (Anderson 1987). nww

Non-wetting phase  Wetting 

nws

ws

phase

Figure 4. Contact angle.

Interfacial tensions can be reduced by accumulation of electrical charges at the liquidsolid interface (Rosslee and Abbott 2000, Francisca et al. 2008) or due to the presence of surface active agents (Shaw 1992). In porous media, wetting fluids usually form a film over the mineral surface or particles and occupies the smaller pores, while the non-wetting fluid resides in larger pore throats and in the central part of pore bodies. The opposite situation is only possible in oil-wet porous media usually associated to the adsorption of water repellent organic radicals to the mineral surface. The affinity between different minerals and water in presence of oil controls the removal of the oil phase from the solid surface (Francisca et al. 2003). At a pore scale level, wettability controls the amount of ganglia that generates and determines the residual saturation of the oil phase (Caruana and Dawe 1996, O‟Carrol et al. 2004, Al-Raoush 2009). The pressure necessary to displace ganglia or the interface between the wetting and nonwetting liquids inside the pores must surpass the capillary pressure Pc [N/m2] (Dullien 1992): Pc = Pnw − Pw =

2 γ nww cos θ rp

.

(26)

Where Pnw and Pw are the pressures in the non-wetting and wetting phases, respectively, and rp [m] is the radius of the capillaries in the porous media. Capillary pressure depends on fluid saturation which is of fundamental importance for the displacement of immiscible fluids in porous media (Corey 1986, Mercer and Cohen 1990, Fagerlund et al. 2006). This dependence is known as soil water characteristic curve or oilwater retention curve depending on the type of fluids present in the soil or rock pores. Capillary pressure – saturation curves depend on which fluid is being displaced (water or oil), on porous media properties (e.g. pore sizes distribution) and on fluid type (Figure 5). Soil water characteristic curves and oil-water retention curves can be experimentally obtained by either steady state or unsteady state methods (Dullien 1992). These methods were originally developed for air-water systems and then adopted for oil-water systems (Donaldson et al. 1985). Table 1 summarizes frequently used pressure-saturation models.

109

Contaminant Transport and Fluid Flow in Soils Snw

Snwr 0

Residual saturation of nonwetting fluid

Capillary Pressure

Irreducible wetting saturation

1

Drainage

Pd Imbibition

0

Swirr

1

Sw

Figure 5. Capillary pressure curves for drainage and imbibitions processes. Snwr = residual saturation of the non-wetting fluid, Swirr = irreducible saturation of wetting fluid, and Pd = bubbling or imbibition pressure.

Table 1. Capillary pressure – saturation models Model

Equation

n = 1 + qPca Pd λ = Pc

Gardner (1958)

SeN

Brooks and Corey (1964)

SeN

van Genuchten (1980)

SeN = 1 + αvg Pc ln Pc = a + b × ln nS ln Pm − ln Pc SeN = Fn σn

Williams et al. (1983) Lognormal (Kosugi, 1994)

n vg −m vg

P cmax

Fredlund and Xing (1994)

S Pc = n

f Pc

2γcosθ 2γcosθ dPc Pc Pc2

Note: Pc is the capillary pressure, Pd is the bubbling pressure, SeN (= (SN - SrN )/(1 - SrN)) is the effective saturation of the N phase, SrN is the residual saturation of the phase N, λ is Corey‟s pore size distribution index, mvg, nvg (= 1/(1-mVG), and vg are van Genuchten‟s fitting parameters, Fn is the lognormal probability distribution function, σn is the standard deviation of pore sizes distribution, Pm is the capillary pressure associated to the mean pore radius, a and b are fitting parameters, q is the Gardner‟s model fitting parameter, n is the porosity,  is the interfacial tension and  is the contact angle.

110


Immiscible fluid flow depends on the interplay between gravity, capillary and viscous effects. Capillary forces are related to the presence of interfaces, viscous forces become of relevance during seepage, and gravity forces arises due to the difference in mass density between the fluid phases. In all cases, flow must satisfy mass conservation for each phase: ∂ nρ i S i ∂t

= −∇ · ρi vi + si .

(27)

Where the subscript “i” refers to either oil or water, and si accounts for sources and sinks. Then, the flow equation for each fluid phase is obtained from a generalized Darcy‟s law and the corresponding relative permeability Kri as follows (Bear 1972): vi = −

1 μi

K ri K ∇Pi − ρi g ∇x .

(28)

The relative permeability represents the influence of the simultaneous presence of two immiscible phases on permeability. This parameter ranges from 0 to 1, depending on the degree of saturation of each fluid phase (Figure 6) and can be determined by either steady state or unsteady state laboratory methods (Corey 1986). Table 2 summarizes the most frequently used relative permeability - saturation model equations. Note that relative permeability models can be combined with capillary pressure–saturation relationships in order to obtain explicit dependence between relative permeability and fluid saturation (Chen et al. 1999). Equations (27) and (28) have to be solved together to explain the immiscible flow in porous media. The differential flow equations can be solved analytically for simple boundary conditions or by means of numerical methods such as finite differences, finite element or algorithms specifically developed for oil production problems (Chen et al. 2006). In all cases, the presence of ganglia or trapped oil difficults the modeling. There are different alternatives to consider this effect. Among them, Kaluarachchi and Parker (1992) integrate the equations by considering a modified capillary pressure–saturation curve which includes the free and trapped non–aqueous phase liquid; Valavanides et al. (1998) and Panfilov and Panfilova (2005) include the entrapment mechanisms on the constitutive relationships; and van Duijn et al. (2007) use the fractional flow conception including contaminant entrapment and heterogeneous porous media. Flow equations (27) and (28) consider soils and rocks as homogenous media at macroscale, even in most cases they are heterogeneous at microscale (Sahimi 1993). Then, flow equations are capable of predicting the evolution of saturation but cannot capture microscopic aspects such as the size and distribution of ganglia and movement of interfaces during the immiscible displacement. Pore networks and cellular automata models allow accurate simulations of immiscible displacement by emulating the porous media as nodes connected by capillaries tubes (Figure 7). Relevant information that can be obtained from pore network models include: a) the effect of pore size anisotropy on ganglia generation (Mani and Mohanty 1999, Francisca and Arduino 2007), b) capillary pressure–saturation curves (Jerauld and Salter 1990, Beliaev and Hassanizadeh 2001, Ahrenholz et al. 2008), c) evolution of relative permeabilities (Maximenko and Kadet 2000, Blunt et al. 2002, Karaman and Demiral 2004), and d) the

111


influence of capillary and viscous forces (Lenormand et al. 1988, Berkowitz and Ewing 1998).

Snw 1

0.8

0.6

0.2 Snwr 0

0.4

0.8

Kr

0.6

0.4

nw

Krw Krnw

Residual nonwetting saturation

Irreducible water saturation

1

w

I

III

0.2 II 0 0

Swirr

0.2

0.4

0.6

0.8

1

Sw Figure 6. Influence of water saturation (Sw) on relative permeability respect to water (Krw) and nonwetting fluid (Krnw). Region “I” has high non-wetting fluid saturation and water remain as discontinuous phase. Region “III” has high water saturation and non-wetting fluid is forming ganglia. In the region “II” oil and water saturations are fairly similar with each other and both phases flow simultaneously. The experimental data correspond to medium sand permeated with water and paraffin oil.

3.5. Partially Miscible Flow Partially miscible flow is an intermediate situation between the transport mechanisms governed by advection-diffusion and the immiscible flow discussed previously. Most immiscible contaminants have very low solubility with water and constitute a long term source of pollution due to the mass transfer from the non–aqueous liquid phase to pore water. The mass transfer rate for non-aqueous phase liquids dissolution usually follows a first order reaction or solubility equation: ρnw n

∂S nw ∂t

= k 𝑑𝑖𝑠𝑠 a Cnw − Cs .

(29)

Where Cnw [Kg/m³] is the NAPL concentration in the aqueous phase, Cs [Kg/m³] is NAPL solubility limit, kdiss [m/s] is the NAPL dissolution coefficient, a [m-1] is the specific

112


interfacial area between the NAPL and water, ρnw [Kg/m³] is the NAPL density, and Snw is NAPL saturation.

Figure 7. Typical result obtained with a pore network model showing the evolution of the advancing front during an imbibitions process (black = water, white = paraffin oil).

Once in solution, the mass transport can be analyzed by the advection-diffusion equation (equation 16) in conjunction with the solubility equation. The most important soil and liquid properties that affect partially miscible flow are grain size distribution, particle wettability, flow velocity, and dissolution rate (Powers et al. 1994, Khachikian and Harmon 2000). Most trapped oil forms multipore ganglia (Powers et al. 1992), which sizes decrease with the evolution of the flow process, increasing the specific interfacial area of the oil blobs. Thereafter, the specific surface area of ganglia starts to decrease because of dissolution and the resulting less amount of NAPL trapped in the pores. Properties of ganglia (e.g. specific surface changes), needed to solve equations (16) and (29), can be determined from light visual transmission, x-ray tomography or nuclear magnetic resonance imaging (Werth et al. 2010). Pore network models also provide very useful information about partially miscible flow in porous media (Jia et al. 1999). However, there are still difficulties scaling up results from the laboratory to the field (Khachikian and Harmon 2000).

113

Contaminant Transport and Fluid Flow in Soils Table 2. Relative permeability models Author Fatt-Dykstra (1951)

Equation K rw =

SedSe 0 P3 c 1d S e 0 P3 c

SedSe 0 P3 c 1d S e 0 P3 c SedSe 0 P2 c 2 1d S e 2 0 Pc

K rnw = 1 − Sew SedSe 0 P2 c 1d S e 2 0 Pc

Burdine (1953)

K rw =

Pirson (1958)

0.5 3 K rw = Swe Sw

K rnw =

4 K rw = Swe

K ro = 2

4 K rw = Swe

2 K rnw = 1 − Swe 1 − Swe

NaarHenderson (1961) Brooks and Corey (1964) Mualem (1976) Timmerman (1982)

K rw =

2 Sew

η Sew

K rw = Sw

SedSe 0 Pc 1d S e 0 Pc Se dSe 0 P2 c 1d S e 0 P2 c

Honarpur et al. (1982)

1−S wirr −S nwr 1−2 S w +S wirr 1−S wirr

1.5 −

η

K rnw = 1 − Sew 2.5

S w −S wirr

S nw 1−S wirr

−S nwr

−0.010874

2.5

SedSe 0 Pc 1d S e 0 Pc

S w −S wirr

0.5

1−S wirr

2 2

2.9

1−S wirr −S or

1.8

1−S nwr

+2.6318 n 1 − Snwr

Se dSe 0 P2 c 1d S e 0 P2 c

1.5

1−2 S w +S wirr

2

1−S wirr −S or Sw 3.6 Sw − Swirr

K ro = 0.76067

2

1−S w −S nw

K rnw = S0

K rw = 0.035388 +0.56556

K rnw = 1 − Sew

S nw −S nwr

2

1−S wirr −S nwr

Snw − Snwr

1.25875−0.070812 ln μw /μnw /γ

Fulcher et al. (1985)

K rw = 0.6135 Swe

1.28610−0.09187 ln γ

K rnw = 1.33874 Senw

μw μo

0.08528

4. HYDRAULIC CONDUCTIVITY AND GEOENVIRONMENTAL PROBLEMS 4.1. Reactive Porous Media: In-situ Barriers 4.1.1. Inorganic Pollutants Inorganic substances in soils or groundwater with concentrations higher than those recommended by current regulations are defined as inorganic contaminants or toxic inorganic chemicals. Some common inorganic pollutants include metals like lead (Pb), chromium (Cr), zinc (Zn), cadmium (Cd), copper (Cu), nickel (Ni), and mercury (Hg) and metalloids like arsenic (As) and selenium (Se) (Ott 2000).

114


High concentrations of inorganic pollutants are frequently related to anthropogenic sources and climate and geological reasons. Anthropogenic sources of contamination include leakage of underground tanks and pipes, accidental spills and industrial discharges, while natural causes include geochemical processes controlled by water-minerals interactions in aquifers (See case study 1).

Case study 1 Drinking water containing high concentrations of inorganic arsenic produces serious health problems including different types of cancer and skin alterations such as hyperkeratosis and hyperpigmentation. In the central part of Argentina most aquifers contain arsenic with concentrations that exceed the value suggested by current regulations, restricting the use of groundwater as a source of drinking water. The problem is also complicated due to the relevant temporal and spatial variability (horizontal and vertical) of arsenic concentrations in the aquifer system (Figure 8). The origin of arsenic is related to the mineralogical composition of local soil given that in contact with water, arsenic will lixiviate from the dissolution of volcanic glass (Smedley et al. 2002, García et al. 2004, Francisca and Carro Perez 2009). Affected zone covers very large areas of the northeastern Argentine and concerns partially to rural and dispersed population with only this source of water.

La t itu

de

de itu ng o L

Figure 8. Spatial variability of the difference between the maximum and minimum arsenic concentrations detected in groundwater (mg/l) in Cordoba Province in the center of Argentine.

Inorganic elements can be found in soils as dissolved in pore water, adsorbed, precipitated, associated with organic matter and in the mineral structure. Dissolved chemicals have high mobility while compounds linked to the solid phase through any known mechanism have relative less mobility. In this case, mobility depends on the chemical structure and speciation of the chemical compound and on the physicochemical properties of the soil.


115

Permeable reactive barriers (PRB) are reactive porous media where adsorption, ionic exchange, redox reactions or precipitation take place (USEPA 1999, Morrison et al. 2002, Cravotta and Watzlaf 2002). These barriers are frequently used as a groundwater remediation technique given they are permeable to water and, at the same time, retain chemical pollutants. Then PRB can be used for the removal of organic and inorganic contaminants from groundwater. PRBs contain solid materials such as activated carbon, resins, zeolites and lateritic soils with high adsorption capacity, and therefore, mass transport is significantly affected due to the retardation effect described previously (equation (19)). The barrier is designed to reduce the initial concentration C0, to effluent concentrations Cf. The thickness of the wall will depends on the flow velocity, given that advection controls the mass transport through PRB, and on the residence time required to reach the target concentration (Sharma and Reddy 2004) 1

t res =  ln

C0 Cf

.

(30)

Where  is related to the contaminant half-life (t1/2) in presence of reactive media (equation (22)). Common inorganic pollutants treated with PRBs include uranium, chromium and arsenic. These contaminants can be removed by sorption on zeolites or lateritic soils and by precipitation after reduction with zero valent iron (ZVI) or permanganate (Morrison et al. 2002). Also, PRBs can be used to treat acid mine drainage, by incorporating limestone as buffer material which raises the pH and causes metal precipitation.

4.1.2. Organic Pollutants Organic compounds frequently encountered as air, soil and groundwater contaminants involve hydrocarbons, phenols, dioxins, PCBs, chlorinated solvents and pesticides, among many others. In all cases the chemical structure of the organic molecule is of fundamental importance given that controls its toxicity, density, solubility, persistence, etc. There are two ways to divide organic contaminants: a) considering their relative density respect to water, and b) as a function of their persistence. According to their relative density, they are classified as Dense Non-Aqueous Phase Liquids (DNAPLs), if they are denser than water, and Light Non-Aqueous Phase Liquids (LNAPLs), when they are lighter than water. Most common DNAPLs are chlorinated solvents (e.g. PCE, TCE), pesticides, coal tars, creosote, PCBs and PAHs (Suthersan 1997). LNAPLs cover oil subproducts, some of them being soluble in water as Methyl Ethyl Ketone, other having low solubility as BTEXs, and finally others that are practically insoluble, such as gasoline or fuel oil. In addition, organic compounds are divided according to their persistence in the environment. Oil byproducts that contain linear and relatively short carbon chains are considered to be reactive, whereas when aromatic rings and halogens substitutions increase, or saturation degree decreases, the reactivity of the compound decreases. Persistent organic pollutants (POP) are those capable of resisting photolytic, chemical or microbiological action, and include aldrin, chlordane, DDT, dieldrin, endrin, heptachlor, hexachlorobenzene, mirex, polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins (dioxins), polychlorinated dibenzofurans (furans), toxaphene, polycyclic aromatic hydrocarbons (PAHs) and some organometallic compounds (e.g. tirbutyltin) (Ritter 1996).

116


In general, contamination by organic compounds includes four different phases: nonaqueous or free phase, dissolved phase, adsorbed phase and vapor phase depending on their solubility and vapor pressure. For example, in a gasoline spill of 8000 liters in medium sand, 62% is found as free phase, 33% is adsorbed, between 1-5% was dissolved in water and less than 1% is found as vapor; however, in the total volume of contaminated soil and water (930500 m3), the free phase occupies a 1%, the adsorbed phase a 20%, and the dissolved phase a 79% (Suthersan 1997). This explains the importance of a rapid removal of the free phase to avoid groundwater contamination. There are several remediation techniques for the removal of organic substances, which depend on the hydrogeologic properties of the site (soil type and degree of saturation). The decontamination strategy is in general constrained by the physicochemical properties of the compound to be remediated. Available alternatives include pump and treat technologies, soil vapor extraction, air sparging, reactive barriers, electrokinetic, bio- and fito-remediation, etc. (Sharma and Reddy 2004). In situ barriers are an innovative method for the treatment of contaminated soil and groundwater, acting as a sorbent or reactive media. This technology was first used in 1993 to treat a TCE contaminant plume in Ontario, Canada, and nowadays more than a hundred barriers can be found installed mostly in USA and Europe (Ott 2000). Most used sorbent media are surfactant modified zeolites (SMZ), organobentonites and granular activated carbon (GAC) (Vidic and Pohland 1996). Zeolites are used in ionic exchange applications given their high cation exchange capacity, bentonites are useful for liners construction and ionic exchange applications due to their high specific surface and swelling capacity, and GAC is used in adsorption barriers due to its high specific surface. Organic and inorganic compounds sorb to the solid surface by physical processes, which are fast, unspecific and reversible; or less commonly by chemical reactions (chemisorption) which are more specific, take longer and might be irreversible (Suthersan 1997). Zeolite and bentonite cannot adsorb large amounts of organic compounds given that they are hydrophilic by nature. To improve the adsorption of organic molecules they are treated with surfactants that generate a non-polar layer around solid particles enhancing the reaction between organic molecules and the surfactant modified solid surface (Bowman 2003, Cruz-Guzmán et al. 2005, Yoo et al. 2004). Chemical degradation is other possible reaction that takes place in the porous barrier. There are two possible mechanisms for the degradation of organic molecules: a) chemical reduction and b) biomediated remediation. ZVI is widely used for the chemical reduction of organic compounds due to its low cost and their capacity of reducing hydrocarbons. Successful results were also obtained by using bimetallic compounds which consists on ZVI pellets covered by palladium (Pd) (Wang et al. 2009, Nagpal et al. 2010), aluminum (Al) (Chen et al. 2008), nickel, copper (Fennelly and Roberts 1998), or even other compounds which do not have iron such as the copper/aluminum media (Lien and Zhang 2002). In these cases, the covering metal acts as a catalyst or as part of a galvanic couple increasing the degradation rate (Ott 2000). Alternatively, decontamination by means of biomediated processes incorporates microorganisms capable of attacking specific compounds by natural means decreasing the contaminant concentration (Choi et al. 2007, Farhadian et al. 2008, Yeh et al. 2010). During the process organic molecules are used by bacteria as energy and carbon source.

117


18.0

17.0

High compaction ef f ort

Low compaction ef f ort

16.0

15.0

1.0E-04

1.0E-05

1.0E-06

1.0E-07

5

7

9

11

13

15

17

19

21

23

Hydraulic conductivity, k [cm/s]

Dry unit weight,  d [kN/m3]

19.0

1.0E-08 25

Water content, w [%]

Figure 9. Influence of moisture content and compaction energy on the saturated hydraulic conductivity of loessical silts.

4.2. Landfills and Surface Impoundments 4.2.1. Soil Microstructure Soil microstructure is the most fundamental soil property to be considered in the construction of earthen liners to contain contaminated water or groundwater. There are many configurations of these barriers depending on the properties and source of the contaminated liquid. Soil liners must have low hydraulic conductivity and in many cases a high retention capacity of contaminants is also preferred (Shackelford and Benson 1995). To prevent fluid displacement and contaminant transport through the soil liner its hydraulic conductivity must be as low as possible. Fine particle soils are frequently used as construction material for earthen liners and, if needed, different types of clays or polymers can be added to local soil to reach the hydraulic conductivity specified by current regulations. In this type of soil, particle-fluid interaction (PFI) mechanisms become of relevance and may control the hydraulic properties of the soil (Mitchell and Soga 2005, Montoro and Francisca 2010). These mechanisms are in most cases associated with the behavior of expandable materials which behavior is governed by pore fluid properties and electrical forces. The magnitudes of these forces determine particle association and flocculation (van Olphen 1977).

118


Compaction method, energy and molding water content also play important roles in determining the soil structure (Lambe 1958, Mitchell et al. 1965). The molding water content of compacted soils is usually lower than that required for the complete development of the double layer around particles. Even though flocculated microstructure is expected when the molding water content is lower than the optimum determined in the compaction test. Otherwise, a dispersed microstructure is obtained if the soil is compacted in the wet-side of the compaction curve resulting in a higher degree of particle orientation (Seed and Chan 1959). This affects significantly the obtained hydraulic conductivity as shown in Figure 9. In general, in the wet-side of optimum the soil has a dispersed microstructure and lower hydraulic conductivity than in the dry-side of optimum, even for different compaction efforts (Figure 9). The pH of the permeating liquid must also be considered given that it affects the surface charge of soil particles, as well as the expected electrostatic repulsion forces which modify the hydraulic conductivity of soils (Ruhl and Daniel 1997, Jo et al. 2001).

dth

Hydraulic conductivity, k

I u k0 kl0

II

III

A

Upper limit

B

Lower limit

D C

u k∞

E

F

k ∞l

Dry unit weight,  d Figure 10. Identified zones and soil behavior.

The microstructure of the compacted soil determines upper and lower bounds of hydraulic conductivity (Figure 10). Three zones with different soil microstructure are observed depending on the dry unit weight of the soil. Zone I is characterized by a small decrease of hydraulic conductivity when dry unit weight increases. Regardless the dry unit weight, all samples have relatively flocculated structure within this zone (points A and D). Samples represented by point D have lower hydraulic conductivity and a less flocculated structure than those corresponding to point A. After the threshold, within the zone II, very significant reductions of hydraulic conductivity are observed as a result of important changes in soil microstructure. Specimens represented by points B and E have more dispersed microstructures than those of points A and D, respectively. Finally, zone III gathers specimens with dispersed structure, where the small decrease of k can be explained by the

119


influence of the soil unit weight. In this zone, specimens F have a more dispersed structure than specimens C (See case study 2).

Case study 2 Nieva and Francisca (2007) collected and analyzed hydraulic conductivity results for the loessical silts of the center of Argentine. They observed that the maximum and minimum expected hydraulic conductivity differ in approximately one order of magnitude for dry unit weights from 11.55 to 18.15 kN/m3 (Figure 11). In addition, all undisturbed specimens always have hydraulic conductivities that fall within zone I, while values within zones II and III are only attained in compacted soil specimens. 1.0E-02

Hydraulic conductivity, k [cm/s]

1.0E-03 Zone I

Zone II

Zone III

1.0E-04

1.0E-05

1.0E-06

1.0E-07

1.0E-08 11.55

13.20

14.85

16.50

18.15

Dry unit weight,  d [kN/m3] Figure 11. Influence of soil structure and dry unit weight on the hydraulic conductivity of Argentinean loessical silts.

The presence of ions in the permeating liquid is of fundamental importance for geoenvironmental applications. Several authors have shown that hydraulic conductivity increases when ion concentration increases in coincidence with the effect of ions on the decrease of the DDL thickness (Petrov and Rowe 1997, Jo et al. 2001). In general, this effect can be associated to swelling/shrinkage mechanisms of expandable clay minerals. However, the most important fact is that in addition to the initial dry density of the soil and ionic concentration (or soil fabric), the feasibility of ion exchange must also be considered. For example, two soil specimens having the same dry unit weight may have different hydraulic conductivity as shown in Figures 9 and 10. This confirms the inadequacy of dry unit weight or void ratio to predict the hydraulic conductivity of compacted clays (Mitchell et al. 1965). Similarly, one specimen of compacted soil can develop different hydraulic conductivities for

120


the same permeating liquid depending on the current and past ionic concentration and valence of the dissolved contaminant in the permeating liquid which control the exchangeability of ions in the diffuse double layer around soil particles (Montoro and Francisca 2010). This observation confirms that hydraulic conductivity cannot be accurately predicted in terms of the changes in soil structure.

4.2.2. Clay Content Landfills for non-hazardous solid waste must have liners with hydraulic conductivities lower than 1x10-9 m/s and a minimum thickness that depends on local regulations. Bentonite is usually added to soil when the hydraulic conductivity of compacted specimens is higher than this value (Daniel 1993). The bentonite type must also be considered. Natural Nabentonites have greater swelling capacity and achieve lower hydraulic conductivities, but are less common than Ca-bentonites. Sometimes these bentonites are also treated with polymers or converted to organoclays to improve their performance when they are in contact with saline, low pH or organic liquids. Even the clay fraction may control the hydraulic conductivity of sediment-clay mixtures, the final value also depends on the size of the coarser fraction (Sivapullaiah et al. 2000) and chemical properties of the permeating liquid. However, the clay fraction dominates the hydraulic behavior of the mixture when its content is higher than 5% - 7% (Santamarina et al. 2001). Below this value, the coarse fraction and degree of bentonation are the two main factors controlling the hydraulic conductivity of soil-bentonite mixtures (Abichou et al. 2004). Table 3 presents several models to account for the influence of clay on the hydraulic conductivity of soils. These models provide only approximate hydraulic conductivities given the difficulty in reproducing test conditions and the physical properties of the soils used in the developing of the prediction models.

4.3. Smart Permeable Reactive Barriers (SPRB) 4.3.1. Physical and Biological Clogging Most permeable reactive barriers for the treatment of inorganic contaminants are designed with the purpose of promoting precipitation, sorption or complexation reactions, which tends to gradually decrease their hydraulic conductivity. Precipitation reduces the effective porosity and hydraulic conductivity of porous media and permeable reactive barriers (the opposite effect is observed when fine particles are washed off or in the case of particle dissolution). Clogging mechanisms can be divided in three categories: (a) physical, (b) chemical and (c) biological, although in most cases these processes develop altogether. Physical clogging is the phenomenon caused by the retention of inert suspended material that agglomerates in soil pores and reduces progressively the flow channels. Physical clogging associated to fine migration has been widely studied in drainage layers for landfills (Mitchell and Makram 1990, Ng and Lo 2010), roads (Lee and Bourdeau 2006), agriculture (Nia et al. 2010) and underground structures (Reddi et al. 2000).

Table 3. Hydraulic conductivity models for soil-clay and rock-clay mixtures Dependency Void ratio Void ratio Atterberg limits Atterberg limits Dry density Cation exchange capacity

Hydraulic conductivity k = e4 10−13.7 1 e log k = − 2.28 0.233 eL e − 0.0535 wL − 5.286 log k = 0.0063 wL + 0.2516 0.0174 e − 0.027 wL − 0.24 PI /PI k= 1+e log k = −4.07 ρd − 6.13 1 k= EXCi k i CEC with

Swelling Clay content Clay content Clay content and void ratio

ki =

γ aw 12 μaw

2 di

2

i

k = 2.230710−6 εsv 1.6245 k = A CB 6.3110−7 0.234 k= e2.66 PI −8.74 C PI − 8.74 C 3.03 eb C ρbs ke = kc , e = ec + 1 1 + eb b 1 − C ρcs

Limitation Pure bentonite Normally consolidated clays

References Sällfors and Öberg-Högsta (2002)

Sand-bentonite mixtures

Sivappullaiah et al. (2000)

Remolded clays

Carrier and Beckman (1984)

Pure bentonite

Cho et al. (2010)

Bentonite-based buffer and backfill materials

Komine (2008)

Bentonite in backfill voids Clay-sand mixtures

Komine (2004) Shevnin et al. (2006)

Clay-soil mixtures

Dolinar (2009)

Crushed rock and bentonite

Börgesson et al. (2003)

Nagaraj et al. (1993)

4.29

δ2p 1−φ m Fiction (Kozeny-CarmanNa-bentonite Liu (2010) log k = log + log like equation) 4Ck φn Note: k is hydraulic conductivity, e is void ratio, eL is void ratio at liquid limit, wL is liquid limit, d is dry density, CEC [meq/g] is the cation exchange capacity of bentonite, EXCi [meq/g] is the exchange capacity of the exchangeable cation i, k i is the hydraulic conductivity of two montmorillonite parallel-plate layers at the exchangeable cation i, aw and μaw are the density and dynamic viscosity of interlayer water between two montmorillonite parallel-plate layers, and di [m] is half the distance between two montmorillonite layers, sv [%] is the swelling specific strain, C is clay content, A and B are fitting parameters, PI is plastic index, Ck is a scaled pore-shape factor,  is the volume fraction of the solids, p is the particle thickness, m and n are constants, ke is the expected hydraulic conductivity, kc is the hydraulic conductivity of the clay, eb is the ballast void ratio, bs and cs are density of ballast solids and clay solids, respectively.

122


Chemical clogging is associated with precipitation and dissolution reactions that develop in the pore water. Three different cases are frequently observed: a) calcium carbonate (CaCO3) precipitation, b) calcium and magnesium salts precipitation (as chlorides or sulfates), and c) precipitation of metals, in the form of hydroxides, fluorides, phosphates, sulfates or sulfides (Custodio and Llamas 2001). The potential for CaCO3 precipitation is related to several processes, in particular fine sediments formation in the near sea floor (Mitchell and Santamarina 2005), chemical reactions with landfill leachate (van Gulck et al. 2003), and groundwater remediation with permeable reactive barriers (Wantanaphong et al. 2006). Precipitation of calcium and magnesium salts is dominated by hydrogeological conditions and the contribution of different contaminant sources (e.g. leaking of septic tanks). Metals precipitation is associated to PRBs when using ZVI as reactive porous material (Ott 2000). This chemical clogging of PRBs can be spontaneous, as the one caused by the interaction between a contaminant plume and the ZVI (Powell et al. 1998); or biomediated, as in the case of a bioreduction from sulfate to sulfide and the consequent precipitation of metal sulfides (USEPA 1999, Guo and Blowes 2009). 1.0E+01

Hydraulic conductivity with biomass Initial hydraulic conductivity

Thullner et al. (2002) (colonies) Thullner et al. (2002) (biof ilm)

Vandevivere (1995)

1.0E+00

Clement et al. (1996) Seki et al. (2001)

1.0E-01

1.0E-02

1.0E-03

1.0E-04

0

0.2

0.4

0.6

0.8

1

Porosity fraction occupied by biomass Figure 12. Influence of biomass accumulation in the pore space on the hydraulic conductivity of porous media.

Bioclogging is related to the presence and growth of bacteria inside soil pores. There are several mechanisms proposed to describe the accumulation of biomass, which consider bacterial growth, chemical precipitation and fine entrapment, all of them embedded in an exopolysaccharides (EPS) matrix. Possible mechanisms responsible for porosity reduction due to bacteria assumes the growth as either discrete colonies in the pores (Dupin et al. 2001) or as a biofilm surrounding soil particles (Vandevivere 1995, Clement et al. 1996, Francisca and Glatstein 2010). In all cases, biomass causes porosity reductions that decrease significantly the hydraulic conductivity of the media (Figure 12).

123


4.3.2. Flow rate and bacterial growth Flow displacement in porous media can be controlled by manipulating biomass growth, which gives the possibility of creating smart permeable reactive barriers (SPRB). The growing pattern of bacteria requires specific conditions of oxygen and moisture content, temperature, nutrients content, pressure and inhibiting substances. The hydraulic conductivity of porous media can be significantly reduced by favoring the development of bacteria (Figure 12). Conversely, this biomass growth could be diminished if higher flow rate and system performance are needed. The minimum thickness W [m] of PRB needed to reduce contaminant concentrations from C0 to Cf depends on flow velocity and residence time (Sharma and Reddy 2004). W = ve t res .

(31)

Where ve and tres are defined by equations (3) and (30), respectively. SPRB are then essentially similar to PRB with the distinctive attribute that ve is manipulated by controlling bacterial growth. 2000 Pure ZVI Commercial ZVI

Ct [ g/l]

1600 1200

tres(C)

t res(P)

800

400 Cf = 70

0

0

60

120

180

240

300

t [hr]

Figure 13. cDCE decay in a PRB with pure and commercial ZVI as reactive materials.

Example Problem a) An auto parts company uses cDCE as degreaser. An accidental spill of cDCE generated a contaminant plume affecting groundwater. A consultant GeoEngineer suggested the use of a SPRB for the aquifer remediation. The aquifer has an effective porosity of 35%, hydraulic gradient of 0.01, a hydraulic conductivity of 1x10-3 cm/s. The initial cDCE concentration in groundwater is 2000 g/l, and half lives for cDCE in pure and commercial ZVI are 19.7 and 47.6 hours respectively. Find the time needed to reduce the cDCE concentration to Cf =70 g/l after the permeable wall. Solution: Reaction rate constants for pure and commercial ZVI are computed from equation (22) resulting  0.035 hour-1 and  0.015 hour-1 for pure and commercial ZVI, respectively. Then, the residence time in the barrier can be computed from equation (30) with  C0=2000 g/l and Cf =70 g/l. Figure 13 shows the influence of time on the decay of cDCE in pure and commercial ZVI.

124


b) Consider that the hydraulic conductivity of the barrier can be reduced one order of magnitude with the addition of bacteria. Find the SPRB widths for cDCE concentrations ranging from 100 g/l to 5000 g/l. Solution: Replacing equations (3) and (30) in equation (31) we can find the thickness for different barriers and requirements. Modifying the hydraulic conductivity we can evaluate the effect of bioclogging on the remediation. Figure 14 shows the barrier thickness needed to achieve Cf =70 g/l by using commercial and pure ZVI with and without the inoculation of bacteria. Lower barrier thicknesses are required for pure ZVI in comparison to commercial ZVI as reactive materials. Also, the addition of bacteria reduces the required barrier thickness to lower the contaminant level to the target values. 35 PRB

Barrier width, W [cm]

30 25

Pure ZVI without bacteria Pure ZVI with bacteria Commercial ZVI without bacteria Commercial ZVI with bacteria

20

15 PRB

10 5

SPRB SPRB

0 0

1000

2000 3000 4000 Initial Concentration, C0 [ g/l]

5000

6000

Figure 14. Influence of the initial cDCE concentration on the minimum barrier thickness of PRB and SPRB.

REFERENCES Abichou T., Benson C.H., Edil T.B. (2004). “Network model for hydraulic conductivity of sand-bentonite mixtures”. Can. Geotech. J. 41 (4): 698-712. Adamson A.W., Gast A.P. (1997). Physical Chemistry of Surfaces. 6th Ed. Wiley Interscience, New York. Ahrenholz B., Tolke J., Lehmann P., Peters A., Kaestner A., Krafczyk M., Durner W. (2008). “Prediction of Capillary Hysteresis in a Porous Material Using Lattice-Boltzmann Methods and Comparison to Experimental Data and a Morphological Pore Network Model”. Advances in Water Resources 31 (9): 1253-1268. Al-Raoush R.I. (2009). ”Impact of Wettability on Pore-Scale Characteristics of Residual Nonaqueous Phase Liquids”. Environ. Sci. and Technol 43: 4796-4801.


125

Anderson W.G. (1987). “Wettability Litterature Survey – Part 2: Wettability Measurement”. Journal of Petroleoum Technology 38: 1246-1262. Bear J. (1972). Dynamics of Fluids in Porous Media. Dover Publications Inc. New York. Beliaev A.Y, Hassanizadeh S.M. (2001). “A Theoretical Model of Hysteresis and Dynamic Effects in the Capillary Relation for Two-Phase Flow in Porous Media”. Transport in Porous Media 43: 487-510. Berkowitz B., Ewing R.P. (1998). “ Percolation theory and network modeling applications in soil physics”. Surveys in Geophysics 19 (1): 23-72. Blunt M.J., Jackson M.D., Piri M., Valvatne P.H. (2002). “Detailed Physics, Predictive Capabilities, and Macroscopic Consequences for Pore Network Models of Multiphase Flow”. Advances in Water Resources 25: 1069-1089. Boadu F.K. (2000). “Hydraulic Conductivity of Soils from Grain Size Distribution: New Models”. Journal of Geotechnical and Geoenvironmental Engineering 126 (8): 739-746. Börgesson L., Johannesson L.E, Gunnarsson D. (2003). “Influence of soil structure heterogeneities on the behaviour of backfill materials based on mixtures of bentonite and crushed rock”. Applied Clay Science 23 (1-4): 121-131. Bowman R.S. (2003). “Applications of surfactant-modified zeolites to environmental remediation”. Microporous and Mesoporous Materials. 61: 43–56. Brooks R.H., Corey A.T. (1964). “Hydraulic Properties of Porous Medium”. Colorado State University (Fort Collins). Hydrology Paper. No 3. Burdine N.T. (1953). “Relative Permeability Calculations from Pore Size Distribution Data”. American Institute of Mining and Metallurgical Engineering 198. Carrier W.D. Beckman J.F. (1984). “Correlations between index tests and the properties of remoulded clays”. Geotechnique 34 (2): 211. Caruana A., Dawe R.A. (1996). “Flow Behavior in the Presence of Wettability Heterogeneities”. Transport in Porous Media 25: 217-233. Chen J., Hopmans J.W., Grismer M.E. (1999). “Parameter Estimation of Two-Fluid Capillary Pressure-Saturation and Permeability Functions”. Advances in Water Resources 27 (5): 479-493. Chen Z., Huan G., Ma Y. (2006). Computacional Methods for Multiphase Flow in Porous Media. SIAM. Philadelphia. Chen L.H., Huang C.C., Lien H.L. (2008). “Bimetallic iron aluminum particles for dechlorination of carbon tetrachloride”. Chemosphere 73: 692-697. Cho W.J., Lee J.O, Kwon S. (2010). “Analysis of thermo-hydro-mechanical process in the engineered barrier system of a high-level waste repository”. Nuclear Engineering and Design 240: 1688–1698. Choi J.H., Kim Y.H., Choi S.J. (2007). “Reductive dechlorination and biodegradation of 2,4,6 trichlorophenol using sequential permeable reactive barriers: Laboratory studies”. Chemosphere 67: 1551-1557. Clement T.P., Hooker B.S., Skeen R.S. (1996). “Macroscopic models for predicting changes in saturated porous media properties caused by microbial growth”. Groundwater 34 (5): 934-942. Corey A.T. (1986). Mechanics of Immiscible Fluids in Porous Media. Water Resources Publications. Littleton, Colorado. Cravotta C.A., Watzlaf G.R. (2002). “Chapter 2: Design and Performance of Limestone Drains to Increase pH and Remove Metals from Acidic Mine Drainage”. Handbook of

126


groundwater remediation using permeable reactive barriers: applications to radionuclides, trace metals, and nutrients. Naftz D.L., Morrison S.J., Fuller C.C. (Eds.). Academic Press, Orlando, Florida. pp. 19-66. Cruz-Guzmán M., Celis R., Hermosín M.C., Koskinen W.C., Cornejo J. (2005) “Adsorption of Pesticides from Water by Functionalized Organobentonites”. J. Agric. Food Chem 53: 7502-7511. Custodio E., Llamas M.R. (2001). Hidrología subterránea, 2nd Edition. Ed. Omega S.A., Barcelona, 2350 pp. Daniel D.E. (1993). Geotechnical practice for waste disposal. Chapman & Hall, London. 695 pp Dolinar B. (2009). “Predicting the Hydraulic Conductivity of Saturated Clays Using Plasticity – value Correlations”. Applied Clay Science 45: 90-94. Donaldson E.C., Chilingarian G.V., Yen T.F. (1985). Enhanced Oil Recovery, I: Fundamentals and Analyses. Elsevier. New York. Dullien F.A.L. (1992). Porous Media: Fluid Transport and Porous Structure. 2nd Edition. Academic Press. San Diego. Dupin H.J., Kitanidis P.K., McCarty P.L. (2001). “Pore-scale modeling of biological clogging due to aggregate expansion: A material mechanics approach”. Water Resources Research 37 (12): 2965-2979. Fagerlund F.F., Niemi A., Oden M. (2006). “Comparison of Relative Permeability – Fluid Saturation – Capillary Pressure Relations in Modeling of Non-Aqueous Phase Liquid Infiltration in Variably Saturated, Layered Media”. Advances in Water Resources 29 (11): 1705-1730. Farhadian M., Vachelard C., Duchez D., Larroche C. (2008). “In situ bioremediation of monoaromatic pollutants in groundwater: A review”. Bioresource Technology 99: 52965308. Fatt I., Dykstra H. (1951). “Relative Permeability Studies”. American Institute of Mining and Metallurgical Engineering 192: 249-256. Fennelly J.P., Roberts A.L. (1998). “Reaction of 1,1,1 Trichloroethane with Zero Valent Metals and Bimetallic Reductants”. Environ. Sci. Technol. 32: 1980-1988. Fetter C.W. (1993). Contaminant Hydrogeology. 2nd Edition. Prentice Hall, Upper Saddle River. Francisca F.M., Arduino P. (2007). “Cellular Automata Model for Immiscible Flow in Porous Media”. ASCE International Journal of Geomechanics 7 (4): 11-17. Francisca F.M., Carro Pérez M.E. (2009). “Assessment of natural arsenic in groundwater in Cordoba State (Argentina)”. Environmental Geochemistry and Health 31 (6): 673-682. Francisca F.M., Fratta D.O., Wang, H. (2008). “Electrowetting on Mineral and Rock Surfaces”. Geophysical Research Letters 35. Francisca F.M., Glatstein D.A. (2010). “Long Term Hydraulic Conductivity of Compacted Soils Permeated With Landfill Leachate”. Applied Clay Science 49: 187-193. Francisca F.M., Rinaldi V.A., Santamarina J.C. (2003). “Instability of Hydrocarbon Films over Mineral Surfaces: Microscales Experimental Studies”. Journal of Environmental Engineering 129 (12): 1120-1128. Fredlund D.G., Rahardjo H. (1993). Soil Mechanics for Unsaturated Soils. John Wiley and Sons Inc. Hoboken.


127

Fredlund D.G., Xing A. (1994). “Equations for the Soil Water Characterisitic Curve”. Canadian Geotechnical Journal 31: 521-532. Freeze R.A., Cherry J.A. (1979). Groundwater. Prentice Hall, Inc., Englewood Cliffs, New Jersey, 604 pp. Fulcher R.A.. Ertekin T., Stahl C.D. (1985). “Effect of Capillary Number and Its Constituents on Two-Phase Relative Permeabilities Curves”. Journal of Petroleoum Technology 37 (2): 249-260. García M.G., Hidalgo M. del V., Litter M.I., Blesa M.A. (2004). “As removal by SORAS in Los Pereyra, Province of Tucumán, Argentina”. Solar Light Assisted Arsenic Removal in Rural Communities of Latin America, Litter M.I., Mansilla H.D. (Eds.) Digital Graphic, La Plata, Argentina. Gardner W.R. (1958). “Some steady-state solutions of the unsaturated moisture flow equation with application to evaporation from a water table”. Soil Science 85 (4): 228-232. Guo Q., Blowes D.W. (2009). “Biogeochemistry of two types of permeable reactive barriers, organic carbon and iron-bearing organic carbon for mine drainage treatment: Column experiments”. Journal of Contaminant Hydrology 107: 128-139. Honarpur M., Koederitz L., Harvey A.H. (1982). “Empirical Equations for Estimating TwoPhase Relative Permeability in Consolidated Rock”. Journal of Petroleoum Technology 34 (12): 2905-2908. Jerauld G.R., Salter S.J. (1990). “The Effect of Pore Structure on Hysteresis in Relative Permeability and Capillary Pressure: Pore Level Modeling”. Transport in Porous Media 5: 103-151. Jia C., Shing K., Yortsos Y.C. (1999). “Visualization and Simulation of Non-Aqueous Phase Liquids Solubilization in Pore Networks”. Journal of Contaminant Hydrology 35: 363387. Jo H.Y., Katsumi T., Benson C.H., Edil T.B. (2001). “Hydraulic Conductivity and Swelling of Nonprehydrated GCLs Permeated with Single-Species Salt Solutions”. Journal of Geotechnical and Geoenvironmental Engineering 127 (7): 557-567. Kaluarachchi J.J., Parker J.C. (1992). “Multiphase Flow with a Simplified Model for Oil Entrapment”. Transport in Porous Media 7: 1-14. Karaman T., Demiral B.M.R. (2004). “Determination of Two and Three Phase Relative Values by Using a Pore Network Model”. Energy Sources 26: 685-696. Khachikian C., Harmon T.C. (2000). “Nonaqueous Phase Liquid Dissolution in Porous Media: Current State of Knowledge and Research Needs”. Transport in Porous Media 38: 3-28. Komine H. (2004). “Simplified evaluation on hydraulic conductivities of sand–bentonite mixture backfill”. Applied Clay Science 26 (1-4): 13-19. Komine H. (2008). “Theoretical Equations on Hydraulic Conductivities of Bentonite-Based Buffer and Backfill for Underground Disposal of Radioactive Wastes”. Journal of Geotechnical and Geoenvironmental Engineering 134 (4): 497-508. Kosugi K. (1994). “Three-Parameter Lognormal Distribution Model for Soil-Water Retention”. Water Resources Research 30 (4): 891-901. Lambe T.W. (1958). “The structure of compacted clay”. Journal of the Soil Mechanics and Foundation Division 84 (SM2), 1654-1-1654-34. Lambe T.W., Whitman R.V. (1969). Soil Mechanics. John Wiley & Sons, New York.

128


Lee S., Bourdeau P.L. (2006). “Filter Performance and Design for Highway Drains”. Joint Transportation Research Program. Paper 266. Lenormand R., Toublo E., Zarcone C. (1988). “Numerical Models and Experiments on Immiscible Displacement in Porous Media”. J. Fluid Mech. 189: 165-187. Lenormand R. (1990). “Liquids in Porous Media”. Phys. Condens. Matter 2: SA79-SA88. Lien H.L., Zhang W. (2002). “Enhanced dehalogenation of halogenated methanes by bimetallic Cu/Al”. Chemosphere 49: 371-378. Liu L. (2010). “Permeability and expansibility of sodium bentonite in dilute solutions”. Colloids and Surfaces A: Physicochem. Eng. Aspects 358: 68–78. Mani V., Mohanty K.K. (1999). “Effect of Pore-Space Spatial Correlations on Two-Phase Flow in Porous Media”. Journal of Petroleum Science and Engineering 23: 173-188. Maximenko A., Kadet V.V. (2000). “Determination of Relative Permeabilities Using the Network Models of Porous Media”. Journal of Petroleum Science and Engineering 28: 145-152. Mercer J.W., Cohen R.M. (1990). “A Review of Immiscible Fluids in the Subsurface: Properties, Models, Characterization and Remediation”. Journal of Contaminant Hydrology 29: 319-346. Mitchell J.K., Hooper R., Campanella R. (1965). “Permeability of compacted clay”. Journal of Soil Mechanics and Foundation Division 91 (4): 41-65. Mitchell J.K., Makram J. (1990). “Factors controlling the long-term properties of clay liners”. Geotechnical Special Publication 26: 84-105. Mitchell J.K., Santamarina J.C. (2005). “Biological Considerations in Geotechnical Engineering”. J. Geotech., Geoenvir. Engrg. 131(10): 1222-1233. Mitchell J.K., Soga K. (2005). Fundamentals of Soil Behavior. 3rd Ed. John Wiley & Sons, Hoboken, New Jersey. Mitchell J.K., Younger J.S. (1967). “Abnormalities in Hydraulic Flow Through Fine-Grained Soils”. Permeability and Capillarity of Soils, STP 417: 106-139. Montoro M.A., Francisca F.M. (2010). “Soil permeability controlled by particle-fluid interaction”. Geotechnical and Geological Engineering 28: 851-864. Morrison S.J., Naftz D.L., Davis J.A., Fuller C.C. (2002). “Chapter 1: Introduction to Groundwater Remediation of Metals, Radionuclides, and Nutrients with Permeable Reactive Barriers”. Handbook of groundwater remediation using permeable reactive barriers: applications to radionuclides, trace metals, and nutrients. Naftz D.L., Morrison S.J., Fuller C.C. (Eds.). Academic Press, Orlando, Florida. pp. 1-15. Mualem Y. (1976) “New Model for Predicting the Hydraulic Conductivity of Unsaturated Porous Media”. Water Resources Research 12 (3): 513-522. Naar J., Henderson H. (1961). “An Imbibition Model – Its Application to flow Behavior, and the Prediction of Oil Recovery”. SPEJ 6: 61-70. Nagaraj T.S., Pandian N.S., Narasimha Taju P.S.R. (1993). “Stress State – Permeability Relationships for Fine – Grained Soils”. Geotechnique 43 (29): 333-336. Nagpal V., Bokare A.D., Chikate R.C., Rode C.V., Paknikar K.M. (2010). “Reductive dechlorination of -hexachlorocyclohexane using Fe/Pd bimetallic nanoparticles”. Journal of Hazardous Materials 175: 680-687. Ng K.T.W., Lo I.M.C. (2010). “Fines migration from soil daily covers in Hong Kong landfills”. Waste Management 30: 2047-2057.


129

Nia M.G., Rahimi H., Sohrabi T., Naseri A., Tofighi H. (2010). “Potential risk of calcium carbonate precipitation in agricultural drain envelopes in arid and semi-arid areas”. Agricultural Water Management 97: 1602-1608. Nieva P.M., Francisca F.M. (2007). “On the permeability of compacted and stabilized loessical silts in relation to liner system regulations”. International Congress on Development, Environment and Natural Resources: Multi-level and Multi-scale Sustainability, Cochabamba, Bolivia. O‟Carrol D.M., Bradford S.A., Abriola L.M. (2004). “Infiltration of PCE in a System Containing Spatial Wettability Variations”. Journal of Contaminant Hydrology 73: 3963. Ogata A. (1970). “Theory of dispersion in a granular medium”. US Geological Survey Professional Papers 411–I, 34. Ott N. (2000). Permeable Reactive Barriers for Inorganics. USEPA, Washington DC. Palomino A.M., Santamarina J.C. (2005). “Fabric Map for Kaolinite: Effect of pH and Ionic Concentration on Behavior”. Clays and Clay minerals 53 (3): 211-223. Panfilov M., Panfilova I. (2005). “Phenomenological Meniscus Model for Two-Phase Flows in Porous Media”. Transport in Porous Media 58: 87-119. Perkins T.K., Johnston O.C. (1963). “A review of diffusion and dispersion in porous media”. SPE Journal 3 (195): 70-84. Petrov R., Rowe R. (1997). “Geosynthetic Clay Liner (GCL) – Chemical Compatibility by Hydraulic Conductivity Testing and Factors Impacting its Performance.” Canadian Geotechnical Journal 34: 863-885. Pirson S.J. (1958). Oil Reservoir Engineering. McGraw Hill. New York. Powell R.M., Blowes D.W., Gillham R.W., Schultz D., Sivavec T., Puls R.W., Vogan J.L., Powell P.D., Landis R. (1998). “Permeable Reactive Barrier Technologies for Contaminant Remediation”. US EPA, Washington. Powers S.E., Abriola L.M., Dunkin J.S., Weber W.J. (1994). “Phenomenological Models for Transient NAPL – Water Mass – Transfer Processes”. Journal of Contaminant Hydrology 16: 1-33. Powers S.E., Abriola L.M., Weber W.J. (1992). “An Experimental Investigation of NonAqueous Phase Liquids Dissolution in Saturated Subsurface Systems: Steady State Mass Transfer Rates”. Water Resources Research 28 (10): 2691-2705. Reddi L.N., Xiao M., Hajra M.G., Lee I.M. (2000). “Permeability reduction of soil filters due to physical clogging”. Journal of Geotechnical and Geoenvironmental Engineering 126 (3): 236-246. Ritter L., Solomon K.R., Forget J., Stemeroff M., O'Leary C. (1996). Persistent Organic Pollutants. International Program on Chemical Safety. Rockhold M.L., Yarwood R.R., Niemet M.R., Bottomley P.J., Selker J.S. (2002). “Considerations for Modelling Bacterial-Induced Changes in Hydraulic properties of Variable Saturated Porous Media”. Advances in Water Resources 25: 477-495 Rosslee C., Abbott N.L. (2000). “Active Control of Interfacial Properties”. Curr. Opinion Colloid Interface Sci. 5: 81-87. Rowe R.K., Caers C.J. and Barone F. (1988). “Laboratory determination of diffusion and distribution coefficients of contaminants using undisturbed clayey soil”. Canadian Geotechnical Journal 25: 108-118.

130


Ruhl J.L and Daniel D.E. (1997). “Geosynthetic Clay Liners Permeated with Chemical Solutions and Leachates”. J. Geotech. and Geoenvir. Engrg. 123 (4): 369-381. Sällfors G., Öberg-Högsta A. (2002). “Determination of hydraulic conductivity of sandbentonite mixtures for engineering purposes”. Geotechnical and Geological Engineering 20 (1): 65-80. Sahimi M. (1993). “Flow phenomena in rocks: from continuum models to fractals, percolation, cellular automata, and simulated annealing”. Review of Modern Physics. 65 (4): 1393-1537. Santamarina J.C., Klein K.A., Fam M.A. (2001). Soils and Waves. John Wiley & Sons, West Sussex. Seed H.B., Chan C.K. (1959). “Structure and strength characteristics of compacted clays”. Journal of the Soil Mechanics and Foundation Division 85 (SM5): 87-128. Seki K., Miyazaki T. (2001). “A mathematical model for biological clogging of uniform porous media”. Water Resources Research. 37 (12): 2995–2999. Shackelford C.D., Benson C.H. (1995). Soil Liners and Covers for Landfills. Lectures Notes for Caterpillar Hemispheric Series of Short Courses. Universidad de Puerto Rico. Sharma H.D., Reddy K.R. (2004). Geoenvironmental Engineering. John Wiley and Sons. Hoboken. Shaw D. (1992). Introduction to Colloid and Surface Chemistry. Butterworth and Co, Oxford. Shevnin V., Delgado-Rodríguez O., Mousatov A., Ryjov A. (2006). “Estimation of hydraulic conductivity on clay content in soil determined from resistivity data”. Geofísica Internacional 45 (3): 195-207. Sivapullaiah P.V., Sridharan A., Stalin V.K. (2000). “Hydraulic conductivity of bentonite– sand mixtures”. Canadian Geotechnical Journal 37 (2): 406-413. Smedley P.L., icolli H.B., Macdonald D.M.J., Barros A.J., Tullio J.O. (2002). “Hydrogeochemistry of Arsenic and other inorganic constituents in groundwaters from La Pampa, Argentina”. Appl. Geochem. 17 (2): 259-284. Suthersan S.S. (1997). Remediation Engineering, Design Concepts. CRC. Press. Boca Raton. Thullner M., Zeyer J., Kinzelbach W. (2002). “Influence of microbial growth on hydraulic properties of pore networks”. Transport in Porous Media 49: 99-122. Timmerman, E. H. (1982). Practical Reservoir Engineering. Part I. Penn Well Books, Tulsa. USEPA (1999). “Field Applications of In Situ Remediation Technologies: Permeable Reactive Barriers”. Washington DC. Valavanides M.S., Constantinides G.N., Payatakes A.C. (1998). “Mechanistic Model of Steady-State Two-Phase Flow in Porous Media Based on Ganglion Dynamics”. Transport in Porous Media 30: 267-299. van Duijn C.J., Eichel H., Helmig R., Pop I.S. (2007). “Effective Equations for Two-Phase Flow in Porous Media: The Effect of Trapping on the Microscale”. Transport in Porous Media 69: 411-428. Vandevivere P. (1995). “Bacterial clogging of porous media: A new modeling approach”. Biofouling 8: 281-291. van Genuchten M.T. (1980). “A Closed-Form Equation for Predicting the Hydraulic of Unsaturated Soils”. Soil Science Society of America Journal 44: 892-898. van Olphen H. (1977). Clay colloid chemistry: for clay technologists, geologists, and soil scientists, 2nd Ed., Wiley-Interscience, New York.


131

van Gulck J.F., Rowe R.K., Rittmann B.E., Cooke A.J. (2003). “Predicting biogeochemical calcium precipitation in landfill leachate collection systems”. Biodegradation 14: 331346. Vidic R.D., Pohland F.G. (1996). Treatment Walls. GWRTAC, Pittsburgh. Vuković M., Soro A. (1992). Determination of Hydraulic Conductivity of Porous Media from Grain Size Distribution. Water Resources Publications. Littleton, Colorado. Wang X., Chen C., Chang Y., Liu H. (2009). “Dechlorination of chlorinated methanes by Pd/Fe bimetallic nanoparticles”. Journal of Hazardous Materials. 161: 815-823. Wantanaphong J., Mooney S.J., Bailey E.H. (2006). “Quantification of pore clogging characteristics in potential permeable reactive barrier (PRB) substrates using image analysis”. Journal of Contaminant Hydrology 86: 299-320. Werth C.J., Zang C., Brusseau M.L., Oostrom M., Bauman, T. (2010). “A Review of NonInvasive Imaging Methods and Aplications in Contaminant Hydrogeology Research”. Journal of Contaminant Hydrology 113: 1-24. Williams J., Prebble R.E., Williams W.T., Hignett C.T. (1983). “The Influence of Texture, Structure and Clay Mineralogy on the Soil Moisture Characteristic”. Australian Journal of Soil Research 21: 15-32. Yeh C.H., Lin C.W., Wu C.H. (2010). “A permeable reactive barrier for the bioremediation of BTEX contaminated groundwater: Microbial community distribution and removal efficiencies” Journal of Hazardous Materials 178: 74-80. Yoo J.Y., Choi J., Lee T., Park J.W. (2004). “Organobentonite for sorption and degradation of phenol in the presence of heavy metals”. Water, Air, and Soil Pollution 154: 225-237.