Hydraulic Conductivity of Compacted Soil Liners Permeated with Coal Combustion Product Leachates

Benson, Craig H.; Chen, Jiannan N.; Edil, Tuncer B.; Likos, William J.

doi:10.1061/(ASCE)GT.1943-5606.0001855

Open access

Technical Papers

Jan 30, 2018

Hydraulic Conductivity of Compacted Soil Liners Permeated with Coal Combustion Product Leachates

Authors: Craig H. Benson, F.ASCE [email protected], Jiannan N. Chen, A.M.ASCE [email protected], Tuncer B. Edil, Dist.M.ASCE [email protected], and William J. Likos, M.ASCE [email protected]Author Affiliations

Publication: Journal of Geotechnical and Geoenvironmental Engineering

Volume 144, Issue 4

https://doi.org/10.1061/(ASCE)GT.1943-5606.0001855

PDF

Abstract

Tests were conducted on eight soils to determine how coal combustion product (CCP) leachates may affect the hydraulic conductivity of compacted soil liners (CSLs) used for CCP disposal facilities. The soils represent a broad range of particle-size distributions, Atterberg limits, and mineralogy, and meet minimum compositional recommendations for CSLs. Hydraulic conductivity tests were conducted with five characteristic CCP leachates from the Electric Power Research Institute (EPRI) database of CCP leachates. The testing confirmed that seven of the soils are suitable for a CSL. Five of the seven suitable soils have hydraulic

conductivity < 1 \times 10^{- 9} m / s

when permeated with any of the CCP leachates at 28 kPa effective stress (disposal facility with first lift of CCP placed), as do all but one soil when the effective stress is 450 kPa. Larger increases in hydraulic conductivity are associated with soils having lower hydraulic conductivity to deionized water and significant montmorillonite content. Soils exhibiting the smallest increases in hydraulic conductivity have little to no montmorillonite. Hydraulic conductivity to CCP leachate is not related systematically to any of the primary index properties, indicating that mineralogy is a better indicator of sensitivity to CCP leachates than index properties. Increasing the effective stress from 28 to 450 kPa (

\approx 2

to 30 m CCP depth) results in an average reduction hydraulic conductivity of

10 \times

. The average reduction is

2 \times

at 100 kPa and

5 \times

at 250 kPa.

Introduction

Federal regulations in the United States require that waste containment facilities for disposal of coal combustion products (CCPs) use a composite liner consisting of a geomembrane at least 0.75 mm thick placed directly on top of a soil liner at least 0.6 m thick. The soil liner is required to have a hydraulic conductivity of no more than

1 \times 10^{- 9} m / s

(Federal Register 2015). Soil liners are commonly constructed with compacted finer-grained soil that may or may not classify as clay in the Unified Soil Classification System (USCS) (ASTM 2011a). For this reason, this paper uses the nomenclature compacted soil liner (CSL) to describe the soil liner component instead of the more common term compacted clay liner.

Previous studies have evaluated how the hydraulic conductivity of CSL soils is affected by permeation with organic liquids and leachates containing organic compounds (e.g., Brown and Anderson 1983; Fernandez and Quigley 1985, 1988; Evans and Fang 1986; Bowders and Daniel 1987; Broderick and Daniel 1990; Shackelford 1994), municipal solid waste leachates (Yanful et al. 1990), and inorganic industrial solutions such as wastewater effluent and mine tailings drainage (Edil et al. 1987; Yanful et al. 1995; Alston et al. 1997). These studies have generally shown that the hydraulic conductivity of CSL soils is influenced by chemical changes that alter the thickness of the bound water layer, with higher hydraulic conductivity generally associated with conditions that compress the bound layer: higher ionic strength (

I

), higher valence of cations, higher fraction of organic compound reducing the dielectric constant. Permeation with inorganic solutions that are very dilute, have lower cation valence than the original pore water, or contain suspended solids can result in lower hydraulic conductivity due to an increase in thickness of the bound water layer or deposition of solids (Yanful et al. 1990; Bradshaw and Benson 2013; Setz et al. 2017).

No systematic studies have been conducted to evaluate how CCP leachates affect the hydraulic conductivity of CSL soils. Coal combustion product leachates have been shown to affect the hydraulic conductivity of geosynthetic clay liners (GCLs) adversely under some circumstances, particularly when the leachate has higher ionic strength or a preponderance of divalent cations (Ruhl and Daniel 1997; Benson et al. 2014; Chen et al. 2015, 2018). Coal combustion product leachates suppress swelling of the montmorillonite component, resulting in larger pores and GCLs with higher hydraulic conductivity. Coal combustion product leachates may also impact the hydraulic conductivity of CSLs adversely, especially CSLs constructed from finer-grained materials with a substantial fraction of montmorillonite.

This study evaluated the impact of CCP leachates on the hydraulic conductivity of CSLs. Hydraulic conductivity tests were conducted on eight soils that have been used to construct barrier layers at waste containment facilities throughout North America. Tests were conducted using five synthetic CCP leachates having chemistry representative of leachates encountered in CCP disposal facilities in the United States (Benson et al. 2014). The eight soils were selected to represent a broad range of natural soils used to construct CSLs that have composition meeting recommendations in the literature (Daniel 1990; Benson et al. 1994). Hydraulic conductivity to the CCP leachates was measured over a range of effective stresses to evaluate how the hydraulic conductivity may change as a CCP disposal facility is filled.

Materials

Soil Liners

The CSL soils used in this study were selected from the University of Wisconsin-Madison (UW) Soil Bank, which contains finer-grained barrier soils from more than 40 containment facilities in North America (Benson and Gurdal 2013). These soils have a wide range of physical and chemical properties and come from a broad range of geological environments. The soils include glacial tills and glaciofluvial clays from the Midwest and Northeast United States, residual soils from the Southeast, marine clays from the Gulf Coast, alluvial clays from the intermountain range and West Coast, and eolian soils from the Northwest. The plasticity chart in Fig. 1 illustrates the range of soils in the Soil Bank along with the eight soils selected for the study. Soil classifications, compaction properties, and index properties of the soils are summarized in Table 1. Each soil was assigned an alphanumeric identifier with the first two letters corresponding to the symbolic designation in the USCS and the digits corresponding to the plasticity index (PI) of the

- 40

fraction.

Fig. 1. Casagrande plasticity chart showing soils selected for this study along with other clay liner soils in the University of Wisconsin-Madison Soil Bank

Table 1. Classification, Compaction Properties, and Source of Soils Used in Study

Soil identifier	USCS group symbol	Standard Proctor compaction		Atterberg limits		Particle size fractions (%)				Activity (A)	Specific gravity ( $G_{s}$ )
Soil identifier	USCS group symbol	$w_{opt}$ (%)	$γ_{d \max}$ ( $kN / m^{3}$ )	LL	PI	Gravel	Sand	Fines	2-μm clay	Activity (A)	Specific gravity ( $G_{s}$ )
CL7	CL-ML	18.5	16.6	28	7	0.3	7.6	92.1	16.0	0.44	2.53
CL25	CL	19.6	16.4	42	25	0.0	1.1	98.9	31.4	0.80	2.65
CL28	CL	18.3	17.4	49	28	1.0	15.0	84.0	30.0	0.93	2.68
CH38	CH	24.1	15.4	70	38	0.0	6.0	94.0	65.0	0.58	2.80
ML14	MH	22.5	15.5	50	14	0.0	36.0	64.0	23.0	0.61	2.75
SC10	SC	13.4	18.6	27	10	11.8	57.7	30.5	14.1	0.71	2.68
SC17	SC	18.0	16.3	32	18	31.5	28.1	41.4	16.3	1.07	2.68
SC18	SC	13.0	18.7	31	18	6.1	60.7	33.2	19.6	0.92	2.76

Note: LL = liquid limit; PI = plasticity index; $w_{opt}$ = optimum water content; $γ_{d \max}$ = maximum dry unit weight. Particle size fractions defined in ASTM D422.

Seven of the soils meet the minimum compositional requirements for clay liners stipulated by Daniel (1990) and Benson et al. (1994): liquid limit

(LL) > 20

, plasticity index

(PI) > 7

, fines

content > 30 %

, 2-μm clay

content > 10 %

, and gravel

content < 30 %

. Soil SC17 is an exception, with slightly more gravel than would normally be considered acceptable (Benson et al. 1994). These CSL soils have a wide range of 2-μm clay content (14–65%) and represent a range of potential reactivity with CCP leachate. The soils were organized into three groups based on fines content:

> 50 %

fines, 40–50% fines, and 30–40% fines. Table 2 summarizes the mineralogical composition of the eight soils, measured by X-ray diffraction (XRD) using the methods in Moore and Reynolds (1989) and Scalia et al. (2014). All of the soils contain a considerable quartz fraction. The fine-grained soils with higher PI (CL25, CL28, and CH38) tend to have a greater fraction of montmorillonite or mixed-layer illite-smectite, whereas the fine-grained soils with lower PI (CL7 and ML14) have a greater fraction of illite or kaolinite. The more plastic clayey sands (SC17 and SC18) typically have lower PI (

< 18

) and have mixed-layer illite-smectite in the clay fraction with trace amounts of kaolinite and illite.

Table 2. Mineralogy of Soils Used in Study Obtained by X-Ray Diffraction

Mineral constituents	CL7	CL25	ML14	CL28	CH38	SC17	SC10	SC18
Quartz	43	38	15	54	29	39	59	34
Albite feldspar	8	15	1	9	Trace	7	17	18
Orthoclase feldspar	7	8	—	5	Trace	6	14	10
Microcline feldspar	—	—	6	—	—	—	—	—
Calcite	7	$< 0.5$	1	—	—	—	—	—
Dolomite	1	1	$< 0.5$	—	—	3	4	2
Siderite	1	—	—	—	—	—	—	—
Hematite	1	1	3	—	—	2	—	1
Akaganeite	—	—	—	—	—	—	1	1
Pargasite	—	—	3	—	—	—	—	—
Hornblende	—	—	—	—	—	—	—	$< 0.5$
Kaolinite	1	4	69	1	37	3	2	2
Chlorite	5	—	—	—	4	1	0	1
Illite/mica	20	3	—	2	2	1	2	3
Montmorillonite	—	30	—	—	22	—	—	—
Mixed-layered illite/smectite	6	—	2	29	6	38	1	28

Note: Dash indicates no measurable quantity.

Table 3 summarizes cation exchange capacity (CEC) and mole fractions of the major bound cations in the exchange complex (i.e., collection of cations bound to the mineral surface) of the eight soils, measured in accordance with ASTM D7503 (ASTM 2010) (labeled Pretest). The CEC spans a broad range for CSL soils (Benson and Trast 1995), from 3.6 to

30.8 {cmol}^{+} / kg

, which reflects differences in mineralogy between the soils. Soils with a greater montmorillonite fraction or mixed-layer illite-smectite fraction have higher CEC.

{Ca}^{2 +}

and

{Mg}^{2 +}

are the predominant cations for each soil, composing nearly the entire exchange complex, as is common in surficial soils in natural environments in North America (Meer and Benson 2007; Scalia and Benson 2011).

Table 3. Mole Fraction of Bound Cations in Exchange Complex and Cation Exchange Capacity of Each Soil Prior to Permeation and after Permeation with DI Water and CCP Leachate

Soil	Permeant solution	Mole fraction of bound cations				CEC ( ${cmol}^{+} / kg$ )
Soil	Permeant solution	Na	K	Ca	Mg	CEC ( ${cmol}^{+} / kg$ )
CL7	Pretest	0.01	0.00	0.94	0.05	$7.3 \pm 0.8$
	DI water	0.01	0.00	0.95	0.04
	Typical CCP	0.01	0.01	0.95	0.03
	Low RMD	0.01	0.00	0.95	0.04
	FGD	0.02	0.01	0.92	0.05
	High strength	0.08	0.01	0.87	0.04
	Trona	0.13	0.01	0.84	0.02
CL25	Pretest	0.00	0.02	0.84	0.14	$27.6 \pm 1.3$
	DI water	0.00	0.01	0.87	0.11
	Typical CCP	0.00	0.03	0.85	0.12
	Low RMD	0.00	0.03	0.84	0.13
	FGD	0.01	0.03	0.82	0.14
	High strength	0.02	0.03	0.82	0.13
	Trona	0.22	0.03	0.70	0.05
CL28	Pretest	0.00	0.00	0.82	0.18	$25.8 \pm 2.2$
	DI water	0.00	0.00	0.83	0.17
	Typical CCP	0.00	0.01	0.82	0.17
	Low RMD	0.00	0.00	0.83	0.17
	FGD	0.02	0.01	0.81	0.16
	High strength	0.07	0.01	0.75	0.17
	Trona	0.11	0.00	0.79	0.10
CH38	Pretest	0.00	0.01	0.93	0.06	$30.8 \pm 2.1$
	DI water	0.00	0.01	0.91	0.08
	Typical CCP	0.00	0.02	0.94	0.04
	Low RMD	0.00	0.01	0.94	0.05
	FGD	0.02	0.02	0.88	0.05
	High strength	0.07	0.02	0.86	0.05
	Trona	0.10	0.02	0.82	0.06
ML14	Pretest	0.00	0.00	0.46	0.53	$15.8 \pm 2.0$
	DI water	0.00	0.00	0.48	0.51
	Typical CCP	0.00	0.00	0.46	0.51
	Low RMD	0.00	0.01	0.47	0.51
	FGD	0.01	0.01	0.44	0.53
	High strength	0.07	0.01	0.39	0.52
	Trona	0.12	0.00	0.42	0.45
SC10	Pretest	0.00	0.00	0.60	0.41	$3.6 \pm 0.6$
	DI water	0.00	0.00	0.72	0.24
	Typical CCP	0.00	0.01	0.61	0.39
	Low RMD	0.00	0.01	0.60	0.40
	FGD	0.01	0.01	0.58	0.41
	High strength	0.02	0.01	0.58	0.40
	Trona	0.05	0.00	0.62	0.30
SC17	Pretest	0.00	0.00	0.58	0.42	$22.1 \pm 2.0$
	DI water	0.00	0.00	0.61	0.38
	Typical CCP	0.00	0.01	0.59	0.40
	Low RMD	0.00	0.01	0.58	0.41
	FGD	0.01	0.01	0.56	0.42
	High strength	0.07	0.01	0.52	0.40
	Trona	0.12	0.00	0.60	0.26
SC18	Pretest	0.01	0.00	0.93	0.06	$15.0 \pm 0.7$
	DI water	0.02	0.00	0.94	0.04
	Typical CCP	0.01	0.01	0.94	0.04
	Low RMD	0.01	0.00	0.94	0.05
	FGD	0.02	0.01	0.91	0.06
	High strength	0.08	0.01	0.86	0.05
	Trona	0.13	0.00	0.85	0.01

Note: CEC shown with two standard deviations based on seven measurements.

Leachates

The synthetic leachates used in this study were identified by Benson et al. (2014) through analysis of a database compiled by the Electric Power Research Institute (EPRI) containing leachate data from 33 CCP disposal facilities. The database includes concentrations of major cations and anions, ionic strength, relative abundance of monovalent and polyvalent cations, pH, and electrical conductivity (EC). Ionic strength is a measure of the total concentration of ions in a solution and is defined as

I = \frac{1}{2} \sum_{i = 1}^{n} c_{i} z_{i}^{2}

(1)

where

c_{i}

= molar concentration of the

i

th ionic species in the solution; and

z_{i}

= valence of the

i

th ion. Fig. 2 shows the relative abundance of monovalent and polyvalent cations in the leachates in terms of the parameter RMD (Kolstad et al. 2004)

RMD = \frac{M_{M}}{\sqrt{M_{D}}}

(2)

where

M_{M}

= total molar concentration of monovalent cations in the leachate and

M_{D}

= total molar concentration of polyvalent cations. Benson et al. (2014) identified five characteristic leachates representing different CCP disposal conditions: typical CCP leachate (geometric mean of leachate chemistry for all CCP leachates), low-RMD leachate, flue gas desulfurization (FGD) leachate, high ionic strength leachate, and trona ash leachate. Table 4 summarizes the ionic composition of the five leachates.

Fig. 2. RMD versus I for leachate data in the EPRI CCP leachate database along with synthetic test leachates defined by Benson et al. (2014); MSW leachate data from Bradshaw and Benson (2013) shown for comparison

Table 4. Composition and Chemical Properties of Synthetic Leachates

Property	Typical CCP	Low RMD	High ionic strength	Typical FGD	Trona
${Ca}^{2 +}$ ( $mg / L$ )	311	616	512	542	500
${Na}^{+}$ ( $mg / L$ )	254	28.8	2,500	968	14,800
${Mg}^{2 +}$ ( $mg / L$ )	29.4	24.3	140	73.1	150
$K^{+}$ ( $mg / L$ )	72.2	10.6	22.2	49.9	200
${Cl}^{-}$ ( $mg / L$ )	70.7	23.2	1,720	784	—
${SO}_{4}^{2 -}$ ( $mg / L$ )	1,390	1,620	4,720	2,620	33,000
pH	$8.0 \pm 0.5$	$8.0 \pm 0.5$	$8.0 \pm 0.5$	$8.0 \pm 0.5$	$11.0 \pm 0.5$
Ionic strength (mM)	41.7	54.3	174	94.0	746
RMD ( $M^{1 / 2}$ )	0.16	0.012	0.98	0.40	6.86

Fig. 2 shows the ionic strength of the five leachates along with the EPRI data and comparable data for municipal solid waste leachate reported by Bradshaw and Benson (2013). Trona leachate has the highest ionic strength and RMD due to the prevalence of

{Na}^{+}

in the soluble sodium carbonate produced when trona mineral is injected into flue gas to remove sulfur trioxide (Nolan 2000). The FGD and high ionic strength leachates also have higher ionic strength and greater predominance of monovalent cations (higher RMD) (Fig. 2), reflecting greater concentrations of

{Na}^{+}

and

{Cl}^{-}

in these leachates relative to typical CCP leachate (Table 4). The low-RMD leachate has a greater fraction of divalent cations (Table 2) relative to all of the other leachates, and falls along the lower bound of the band in Fig. 2. Four of the leachates are slightly alkaline (pH 8). Trona leachate is highly alkaline (pH 11) (Table 4).

Methods

Specimen Preparation

All test specimens were prepared using the procedure in Benson and Yesiller (2016), which was developed for a study regarding the repeatability of hydraulic conductivity measurements for the Institute for Standards Research of ASTM International. These methods have been demonstrated to create reproducible specimens, with a coefficient of variation (COV) for water content less than 1% and a COV for dry unit weight less than 0.5%. The intent was to create nearly identical specimens so that the effect of leachate chemistry would be isolated in the testing program.

Each soil was initially air dried and crushed past a No. 4 sieve (4.75 mm) as required by ASTM D698 (ASTM 2012b). The crushed and sieved soils were moistened with tap water (

pH = 7.5

,

EC = 0.06 S / m

at 20°C) using a spray bottle to 1% wet of optimum water content per standard Proctor to represent typical clay liner construction practice in North America (Benson et al. 1994, 1999; Benson and Trast 1995). The soils were thoroughly blended with a trowel during moistening and subsequently sealed in plastic bags to equilibrate for at least 24 h.

After the equilibration period, the soils were compacted in half-height steel compaction molds (102-mm inside

diameter \times 58 - mm

height) using the standard Proctor procedures described in ASTM D698, with the number of blows adjusted for the shorter height of the mold. This resulted in specimens compacted wet of the line of optimums. Compacted specimens were extruded using a hydraulic jack, wrapped in two layers of plastic sheet, encased in two evacuated resealable plastic bags, and stored in a 100% humidity room prior to testing. All specimens were set up in a permeameter within 48 h of compaction.

Hydraulic Conductivity Testing

Hydraulic conductivity tests were conducted on the compacted soil specimens in flexible-wall permeameters following the methods in ASTM D7100 (ASTM 2011b) and ASTM D5084 (ASTM 2016). The falling headwater–constant tailwater method was used with an average hydraulic gradient of 20. All tests were initially conducted at an average effective stress of 28 kPa to simulate the stress in a disposal facility with the first lift of CCPs placed. No backpressure was applied to simulate field conditions and to minimize alterations in geochemistry. All specimens were determined to meet the saturation requirements in ASTM D5084 by weight-volume calculations conducted on conclusion of testing. Table 5 summarizes the water content, dry unit weight, and degree of saturation before and after permeation.

Table 5. Initial and Final Water Content, Dry Unit Weight, and Degree of Saturation

Soil	Permeant liquid	Initial properties			Final properties
Soil	Permeant liquid	Water content (%)	Dry unit weight ( $kN / m^{3}$ )	Degree of saturation (%)	Water content (%)	Dry unit weight ( $kN / m^{3}$ )	Degree of saturation (%)
CL7	DI	19.5	16.3	86.0	19.9	16.8	98.7
	Typical CCP				19.6	16.7	96.2
	Low RMD				19.6	16.7	96.2
	FGD				19.7	16.7	96.7
	High strength				19.6	16.8	97.7
	Trona				20.8	16.6	95.6
CL25	DI	20.6	16.2	81.7	19.9	17.5	97.3
	Typical CCP				23.1	16.5	97.5
	Low RMD				23.3	16.5	98.4
	FGD				23.5	16.6	97.4
	High strength				23.3	16.6	96.6
	Trona				23.0	16.5	96.2
ML14	DI	25.1	15.2	81.4	25.1	16.4	107.0
	Typical CCP				25.3	16.4	107.9
	Low RMD				25.6	16.4	109.2
	FGD				24.9	16.4	106.2
	High strength				24.1	16.5	104.4
	Trona				26.1	16.4	111.3
CL28	DI	19.3	17.2	88.3	14.1	17.7	98.8
	Typical CCP				11.8	18.5	97.7
	Low RMD				11.7	18.6	99.1
	FGD				11.9	18.5	98.5
	High strength				11.6	18.5	97.3
	Trona				12.4	18.4	99.8
CH38	DI	25.1	15.2	80.1	19.6	18.1	95.3
	Typical CCP				19.5	18.3	97.8
	Low RMD				19.7	18.2	98.2
	FGD				19.5	18.2	97.2
	High strength				19.4	18.2	96.7
	Trona				19.6	18.3	97.9
SC17	DI	19.0	16.0	73.0	21.2	17.3	99.8
	Typical CCP				20.7	17.3	97.5
	Low RMD				20.7	17.2	96.0
	FGD				21.0	17.2	97.4
	High strength				20.6	17.2	95.5
	Trona				21.7	17.2	101.8
SC10	DI	14.4	18.2	79.1	15.9	19.1	105.1
SC10	Trona	14.4	18.2	79.1	16.6	18.9	105.9
SC18	DI	14.0	18.3	75.9	13.4	19.9	96.6
	Typical CCP				14.3	19.8	99.5
	Low RMD				14.3	19.7	98.7
	FGD				13.9	19.7	95.5
	High strength				13.5	19.9	96.5
	Trona				14.1	19.7	97.5

Tests were conducted on each soil with deionized (DI) and five synthetic CCP leachates as permeant liquids. Each specimen was permeated with only one permeant liquid. Deionized water was used in lieu of the more traditional tap water or 0.01 M

{CaCl}_{2}

solution suggested in ASTM D5084 to ensure that the water entering the specimen had no ionic species that might alter the hydraulic conductivity. Specimens were consolidated to the initial effective stress for at least 48 h with the permeant liquid applied on the influent end and with the effluent line closed (i.e., no flow).

All tests conducted with synthetic leachates were coninued until the hydraulic conductivity was steady as defined in D7100 and D5084, the flow ratio (incremental

outflow \div inflow

volume) was steady and fell within

1.0 \pm 0.25

, and the pH ratio (effluent

pH \div influent

pH), cation concentration ratios (effluent

concentration \div influent

concentration), and electrical conductivity ratio (effluent

EC \div influent

EC) were within

1.0 \pm 0.1

(i.e., 10%). Electrical conductivity and pH were used as indicators of chemical equilibrium, as described by Stern and Shackelford (1998), Shackelford et al. (1999, 2000), and Jo et al. (2001, 2005). After these conditions were met, the specimens were consolidated to an average effective stress of 100 kPa and then permeated again until hydraulic equilibrium was established (steady hydraulic conductivity, and steady flow ratio of

1.0 \pm 0.25

). This consolidation and permeation procedure was repeated at 250 and 450 kPa. The initial effective stress (28 kPa) was selected to replicate the stress applied by the leachate collection system and the initial lift of waste (i.e., stress applied when the liner first is contacted by leachate). The higher effective stresses represent greater depths of CCPs placed in a disposal facility, with the highest effective stress (450 kPa) corresponding to a CCP depth of approximately 30 m (Edil et al. 1987).

Intrinsic permeability (

k

) was computed from the steady-state hydraulic conductivity using the kinematic viscosity of the permeant liquid and the gravitational acceleration (Mitchell 1976). Intrinsic permeability represents the geometry of the pore space (size, shape, and tortuosity) independent of the hydrodynamic properties of the permeant liquid, which change as the chemistry changes. Kinematic viscosity of each permeant liquid was measured using a Cannon-Fenske viscometer (Cannon Instrument, State College, Pennsylvania) following ASTM D445 (ASTM 2015). Density was measured using a bicapillary pycnometer following ASTM D3505 (ASTM 2012a). Changes in intrinsic permeability between different permeant liquids are indicative of changes in the geometry of the pore space, whereas changes in hydraulic conductivity represent changes in the pore space and changes in the hydrodynamic properties of the permeant liquid (Fernandez and Quigley 1988).

Permeant Liquids and Chemical Analysis

Synthetic leachates representing the five CCP leachates were created by dissolving reagent-grade

Ca {SO}_{4}

,

{Na}_{2} {SO}_{4}

,

Mg {SO}_{4}

,

K_{2} {SO}_{4}

, NaCl, and

{CaCl}_{2}

in ASTM Type II DI water (ASTM D1193) using the methodology of Benson et al. (2014). All leachates were stored in flexible plastic containers with zero headspace at 4°C prior to use. Fresh solutions were prepared monthly or more frequently if the pH or EC of the solution indicated a change in geochemistry.

Samples of the influent and effluent from each specimen were analyzed for pH and EC immediately after collection using a benchtop pH and EC meter (Orion 5-STAR, Thermo Scientific, Madison, Wisconsin). Each sample was filtered using 0.45-μm filter paper, preserved with nitric acid to

pH < 2

, and stored at 4°C. Concentrations of the major cations (i.e.,

{Na}^{+}

,

K^{+}

,

{Ca}^{2 +}

, and

{Mg}^{2 +}

) in the influent and effluent were determined using inductively coupled plasma optical emission spectrometry (ICP-OES) (770ES, Varian, Palo Alto, California) following USEPA Method 6010C (USEPA 1996).

Results and Discussion

Table 6 summarizes the hydraulic conductivities that were measured along with the effective stress applied during testing, the cumulative pore volumes of flow (PVFs) through each specimen, and the total test duration. All soils except SC10 were permeated with each of the synthetic leachates and DI water. Tests were only conducted on SC10 with DI water and with trona leachate because the high hydraulic conductivity (

> 1 \times 10^{- 7} m / s

) to DI water was unrealistic for a CSL.

Table 6. Summary of Hydraulic Conductivity Test Conditions and Outcomes

Soil	Permeant liquid	Effective stress (kPa)	Hydraulic conductivity ( $m / s$ )	Pore volumes of flow	Cumulative test duration (d)
CL7	DI	28	$4.1 \times 10^{- 10}$	2.0	59.1
		100	$3.9 \times 10^{- 10}$	5.6	159.3
		250	$7.1 \times 10^{- 11}$	5.6	167.4
		450	$5.4 \times 10^{- 12}$	5.7	219.2
	Typical CCP	28	$5.7 \times 10^{- 10}$	2.6	60.9
		100	$4.1 \times 10^{- 10}$	3.1	100.4
		250	$2.4 \times 10^{- 10}$	3.2	109.7
		450	$2.0 \times 10^{- 10}$	3.3	114.6
	Low RMD	28	$8.9 \times 10^{- 10}$	3.6	81.7
		100	$8.3 \times 10^{- 10}$	5.0	122.5
		250	$3.9 \times 10^{- 10}$	5.9	167.5
		450	$1.5 \times 10^{- 10}$	6.1	181.2
	FGD	28	$4.2 \times 10^{- 10}$	3.9	105.6
		100	$4.4 \times 10^{- 10}$	4.7	122.5
		250	$2.4 \times 10^{- 10}$	4.9	157.8
		450	$1.4 \times 10^{- 10}$	5.0	172.4
	High strength	28	$9.0 \times 10^{- 10}$	5.2	112.8
		100	$6.7 \times 10^{- 10}$	6.1	125.6
		250	$6.8 \times 10^{- 12}$	6.3	171.4
		450	$4.9 \times 10^{- 12}$	6.4	184.6
	Trona	28	$1.6 \times 10^{- 9}$	9.8	147.8
		100	$1.3 \times 10^{- 9}$	12.4	189.7
		250	$1.2 \times 10^{- 9}$	15.6	219.7
		450	$1.1 \times 10^{- 9}$	18.0	252.8
CL25	DI	28	$1.3 \times 10^{- 11}$	2.3	364.1
		100	$1.3 \times 10^{- 11}$	2.4	402.2
		250	$1.0 \times 10^{- 11}$	2.5	421.8
		450	$9.2 \times 10^{- 12}$	2.6	428.7
	Typical CCP	28	$2.5 \times 10^{- 10}$	2.7	84.8
		100	$2.3 \times 10^{- 10}$	3.0	127.5
		250	$2.3 \times 10^{- 10}$	3.1	138.3
		450	$4.1 \times 10^{- 11}$	3.2	145.2
	Low RMD	28	$3.9 \times 10^{- 11}$	1.3	64.8
		100	$3.4 \times 10^{- 11}$	1.4	94.7
		250	$2.1 \times 10^{- 11}$	1.6	116.7
		450	$2.0 \times 10^{- 11}$	1.7	122.8
	FGD	28	$1.3 \times 10^{- 10}$	1.3	65.0
		100	$6.0 \times 10^{- 11}$	1.4	92.4
		250	$5.2 \times 10^{- 11}$	1.5	106.3
		450	$4.1 \times 10^{- 11}$	1.6	112.6
	High strength	28	$2.4 \times 10^{- 10}$	1.1	48.2
		100	$6.6 \times 10^{- 11}$	1.4	92.3
		250	$5.0 \times 10^{- 11}$	1.5	95.3
		450	$4.3 \times 10^{- 11}$	1.6	102.1
	Trona	28	$7.6 \times 10^{- 11}$	2.5	358.8
		100	$5.2 \times 10^{- 11}$	2.7	399.5
		250	$5.0 \times 10^{- 11}$	2.8	411.4
		450	$1.2 \times 10^{- 11}$	2.9	418.3
ML14	DI	28	$9.3 \times 10^{- 10}$	2.7	55.0
		100	$6.5 \times 10^{- 10}$	4.8	106.8
		250	$4.1 \times 10^{- 10}$	5.4	127.8
		450	$2.7 \times 10^{- 10}$	6.2	163.7
	Typical CCP	28	$1.1 \times 10^{- 9}$	8.7	122.5
		100	$1.1 \times 10^{- 9}$	9.3	135.3
		250	$1.6 \times 10^{- 10}$	9.7	178.4
		450	$1.0 \times 10^{- 10}$	9.8	182.5
	Low RMD	28	$3.0 \times 10^{- 9}$	9.0	105.5
		100	$1.1 \times 10^{- 9}$	10.0	122.4
		250	$3.8 \times 10^{- 11}$	10.3	167.5
		450	$1.8 \times 10^{- 11}$	10.4	174.6
	FGD	28	$5.1 \times 10^{- 10}$	6.5	157.7
		100	$3.4 \times 10^{- 10}$	7.7	174.5
		250	$2.3 \times 10^{- 10}$	7.9	186.9
		450	$1.2 \times 10^{- 10}$	8.0	197.9
	High strength	28	$3.2 \times 10^{- 10}$	4.7	157.6
		100	$3.0 \times 10^{- 10}$	4.9	174.5
		250	$1.2 \times 10^{- 10}$	5.2	215.7
		450	$7.8 \times 10^{- 11}$	5.3	224.4
	Trona	28	$3.0 \times 10^{- 9}$	4.4	62.6
		100	$1.6 \times 10^{- 9}$	6.6	103.7
		250	$5.2 \times 10^{- 10}$	7.9	136.7
		450	$2.6 \times 10^{- 10}$	8.7	177.7
CL28	DI	28	$9.4 \times 10^{- 10}$	5.0	62.0
		100	$6.8 \times 10^{- 10}$	6.4	90.2
		250	$5.3 \times 10^{- 10}$	8.9	128.9
		450	$2.9 \times 10^{- 10}$	9.7	147.0
	Typical CCP	28	$5.3 \times 10^{- 10}$	4.1	84.9
		100	$1.6 \times 10^{- 10}$	4.2	101.7
		250	$4.9 \times 10^{- 11}$	4.4	157.4
		450	$1.8 \times 10^{- 11}$	4.5	164.6
	Low RMD	28	$7.9 \times 10^{- 10}$	5.5	101.7
		100	$5.5 \times 10^{- 10}$	5.6	115.6
		250	$6.5 \times 10^{- 11}$	5.8	145.6
		450	$8.0 \times 10^{- 12}$	5.9	158.7
	FGD	28	$9.3 \times 10^{- 10}$	4.7	88.9
		100	$8.5 \times 10^{- 10}$	6.0	101.7
		250	$3.1 \times 10^{- 11}$	6.3	157.4
		450	$1.1 \times 10^{- 11}$	6.4	168.6
	High strength	28	$3.1 \times 10^{- 10}$	3.6	84.9
		100	$1.0 \times 10^{- 10}$	3.9	101.7
		250	$1.0 \times 10^{- 11}$	4.0	157.3
		450	$5.2 \times 10^{- 12}$	4.1	174.5
	Trona	28	$1.4 \times 10^{- 9}$	2.7	32.9
		100	$1.2 \times 10^{- 9}$	5.2	56.6
		250	$5.8 \times 10^{- 10}$	8.3	118.6
		450	$4.7 \times 10^{- 10}$	10.3	147.5
CH38	DI	28	$8.8 \times 10^{- 11}$	3.2	369.2
		100	$2.5 \times 10^{- 11}$	3.3	415.5
		250	$2.0 \times 10^{- 11}$	3.4	428.9
		450	$1.8 \times 10^{- 11}$	3.4	428.9
	Typical CCP	28	$7.5 \times 10^{- 10}$	4.4	115.0
		100	$1.9 \times 10^{- 10}$	4.5	127.8
		250	$6.8 \times 10^{- 11}$	4.6	138.6
		450	$6.8 \times 10^{- 11}$	4.6	138.6
	Low RMD	28	$4.5 \times 10^{- 10}$	3.4	129.2
		100	$1.2 \times 10^{- 10}$	3.5	142.0
		250	$7.7 \times 10^{- 11}$	3.6	158.8
		450	$5.1 \times 10^{- 11}$	3.7	164.9
	FGD	28	$3.1 \times 10^{- 10}$	2.6	216.7
		100	$5.4 \times 10^{- 11}$	2.9	264.3
		250	$5.0 \times 10^{- 11}$	3.0	283.4
		450	$3.8 \times 10^{- 11}$	3.1	291.6
	High strength	28	$4.1 \times 10^{- 10}$	3.9	123.1
		100	$3.6 \times 10^{- 10}$	4.9	139.9
		250	$1.1 \times 10^{- 10}$	5.3	154.3
		450	$6.1 \times 10^{- 11}$	5.4	196.5
	Trona	28	$4.2 \times 10^{- 11}$	2.2	381.1
		100	$1.8 \times 10^{- 11}$	2.4	432.8
		250	$1.1 \times 10^{- 11}$	2.5	451.7
		450	$1.0 \times 10^{- 11}$	2.5	457.4
SC17	DI	28	$1.4 \times 10^{- 10}$	1.5	193.8
		100	$1.3 \times 10^{- 10}$	1.7	224.6
		250	$8.7 \times 10^{- 11}$	1.8	236.7
		450	$5.8 \times 10^{- 11}$	1.9	242.8
	Typical CCP	28	$5.5 \times 10^{- 10}$	4.0	128.8
		100	$2.7 \times 10^{- 10}$	4.3	141.6
		250	$1.1 \times 10^{- 10}$	4.4	167.4
		450	$5.9 \times 10^{- 11}$	4.6	206.4
	Low RMD	28	$6.0 \times 10^{- 10}$	6.8	140.0
		100	$3.4 \times 10^{- 10}$	7.3	156.8
		250	$6.5 \times 10^{- 11}$	7.8	184.9
		450	$2.0 \times 10^{- 11}$	8.0	225.7
	FGD	28	$3.0 \times 10^{- 10}$	7.3	161.6
		100	$2.1 \times 10^{- 10}$	7.5	174.5
		250	$6.6 \times 10^{- 11}$	7.9	223.8
		450	$2.0 \times 10^{- 11}$	8.0	239.4
	High strength	28	$3.6 \times 10^{- 10}$	4.1	148.4
		100	$1.3 \times 10^{- 10}$	4.5	165.2
		250	$3.9 \times 10^{- 11}$	4.6	214.3
		450	$2.5 \times 10^{- 11}$	4.8	215.2
	Trona	28	$2.4 \times 10^{- 10}$	1.5	132.9
		100	$9.2 \times 10^{- 11}$	1.7	149.7
		250	$2.8 \times 10^{- 11}$	1.8	127.8
		450	$1.8 \times 10^{- 11}$	1.9	147.6
SC10	DI	28	$1.7 \times 10^{- 7}$	2.5	0.2
		100	$1.7 \times 10^{- 7}$	6.6	0.3
		250	$1.8 \times 10^{- 7}$	8.4	0.5
		450	$1.4 \times 10^{- 7}$	9.9	0.6
	Trona	28	$8.1 \times 10^{- 7}$	3.4	0.1
		100	$8.1 \times 10^{- 7}$	6.5	0.2
		250	$7.2 \times 10^{- 7}$	7.6	0.2
		450	$7.9 \times 10^{- 7}$	9.1	0.2
SC18	DI	28	$1.5 \times 10^{- 9}$	6.8	1.5
		100	$4.9 \times 10^{- 10}$	4.3	40.7
		250	$5.6 \times 10^{- 11}$	5.0	57.6
		450	$5.5 \times 10^{- 11}$	5.1	84.2
	Typical CCP	28	$4.3 \times 10^{- 10}$	1.5	123.7
		100	$7.6 \times 10^{- 11}$	1.6	178.6
		250	$4.2 \times 10^{- 11}$	1.7	196.7
		450	$1.1 \times 10^{- 11}$	1.8	202.5
	Low RMD	28	$3.8 \times 10^{- 10}$	2.4	76.1
		100	$1.2 \times 10^{- 10}$	2.6	92.9
		250	$5.8 \times 10^{- 11}$	4.3	115.6
		450	$1.9 \times 10^{- 11}$	4.4	146.7
	FGD	28	$1.5 \times 10^{- 10}$	1.5	92.8
		100	$8.9 \times 10^{- 11}$	1.7	143.4
		250	$8.0 \times 10^{- 11}$	1.8	160.3
		450	$3.5 \times 10^{- 11}$	1.9	167.2
	High strength	28	$3.6 \times 10^{- 10}$	2.0	80.1
		100	$3.6 \times 10^{- 11}$	2.2	92.9
		250	$1.3 \times 10^{- 11}$	2.3	123.4
		450	$7.8 \times 10^{- 12}$	2.5	157.8
	Trona	28	$4.9 \times 10^{- 10}$	2.7	173.2
		100	$1.5 \times 10^{- 10}$	3.1	193.0
		250	$5.3 \times 10^{- 11}$	4.8	254.6
		450	$4.6 \times 10^{- 11}$	4.9	283.8

Figs. 3 and 4 show typical data records from a hydraulic conductivity test in terms of PVF for Soil CH38 permeated with high ionic strength leachate. Benson et al. (2016) includes similar graphs for all other tests. Hydraulic conductivity of this specimen increased initially during permeation, and then leveled off [Fig. 3(a)]. The increase in hydraulic conductivity was concomitant with elution of

{Ca}^{2 +}

and

{Mg}^{2 +}

[Figs. 4(d and e)] from the exchange complex, which apparently was replaced by

{Na}^{+}

and

K^{+}

in the leachate [Figs. 4(c and f)].

{Na}^{+}

replaced

{Ca}^{2 +}

and

{Mg}^{2 +}

, despite the preference for the latter in the lyotropic series, due to mass action effects associated with the high

{Na}^{+}

concentration in the leachate relative to other cations.

K^{+}

in the leachate replaced other ions in the exchange complex because

K^{+}

was absent in the original exchange complex.

Fig. 3. (a) Hydraulic conductivity; (b) flow ratio ( $Q_{out} / Q_{in}$ ) versus PVF for Soil CH38 permeated with high ionic strength leachate at an effective stress of 28 kPa

Fig. 4. pH, EC, and cation concentrations in effluent relative to the influent versus PVF for Soil CH38 permeated with high ionic strength leachate at an effective stress of 28 kPa: (a) pH; (b) EC; (c) ${Na}^{+}$ ; (d) ${Ca}^{2 +}$ ; (e) ${Mg}^{2 +}$ ; (f) $K^{+}$

Hydraulic and chemical equilibrium were established in less than 10 PVFs in nearly all cases (Table 6) and often in less than 5 PVFs (Figs. 3 and 4). Tests with DI water were an exception, which never reached chemical equilibrium during the testing program due to the very slow elution of salts from the pore space, as observed when permeating GCLs with DI water (Jo et al. 2005). The PVF reported in Table 6 for specimens permeated with DI water represents the PVF at the time the hydraulic conductivity was determined. All tests with DI water met the hydraulic equilibrium criteria in ASTM D5084 at the time the hydraulic conductivity was determined.

Substantially fewer PVFs were required to reach chemical equilibrium for the compacted soils than is common when conducting tests with GCLs, which usually require 40 PVFs or more to reach equilibrium (Jo et al. 2005; Benson et al. 2014; Bradshaw et al. 2015; Tian et al. 2016). Fewer PVFs are required to reach equilibrium for compacted soils because different mechanisms control the rate of mass transfer between ions in the pore water and those bound to the mineral surface. Ion exchange occurs very slowly in bentonite in GCLs because diffusion controls the rate at which ions migrate into and out of the interlayer. In contrast, exchange occurs relatively rapidly on the exterior surfaces of nonexpansive clay minerals (Jo et al. 2006). In addition, the exchange complex in most compacted soils, including those used in this study, is dominated by

{Ca}^{2 +}

and

{Mg}^{2 +}

(Table 3), which can preclude expansion of the interlayer of the montmorillonite fraction and limit cation exchange to exterior surfaces of the solids that are readily accessed. Even after permeation to equilibrium with the sodic FGD, high ionic strength, and trona leachates, the exchange complex in all soils was predominantly

{Ca}^{2 +}

and

{Mg}^{2 +}

(Table 3), presumably due to the preference of these divalent cations in the lyotropic series (Mitchell 1976). Only modest enrichment in

{Na}^{+}

occurred in the exchange complex during permeation with these leachates (Table 3).

Hydraulic Conductivity to DI Water

The soils CL-7, CL-25, CL-28, CH-38, M-14, and SC-17 all had hydraulic

conductivity \leq 1 \times 10^{- 9} m / s

to DI water at 28 kPa effective stress (Table 6), which was anticipated based on the recommendations of Daniel (1990) and Benson et al. (1994). Each of these generally would be considered a suitable clay liner soil. The hydraulic conductivity of SC18 to DI water was

1.5 \times 10^{- 9} m / s

at 28 kPa effective stress. This soil would be considered a marginal clay liner soil because the hydraulic conductivity exceeded

1 \times 10^{- 9} m / s

, but would be acceptable in some cases because the hydraulic conductivity was less than

1 \times 10^{- 9} m / s

at higher stresses representative of conditions after filling.

Soil SC10 had hydraulic conductivity to DI water in excess of

1 \times 10^{- 7} m / s

, i.e., more than 100 times higher than the maximum permissible hydraulic conductivity of

1 \times 10^{- 9} m / s

. This soil would not be considered suitable for a clay liner material based on hydraulic conductivity, even though the soil meets the minimum compositional requirements for a clay liner described by Daniel (1990) and Benson et al. (1994). The effect of CCP leachate on the hydraulic conductivity of SC10 was evaluated using trona leachate to ascertain whether precipitation of solids from this high ionic strength leachate might reduce the hydraulic conductivity. However, high hydraulic conductivity was obtained with both DI water and trona leachate, and therefore no additional tests were conducted on SC10.

Fig. 5 shows the hydraulic conductivity of the soils to DI water at 28 kPa as a function of percent fines, percent 2-μm clay, liquid limit (LL), plasticity index (PI), and activity (A), which are the compositional variables that have the greatest influence on the hydraulic conductivity of compacted finer-grained soils to water (Benson et al. 1994). Hydraulic conductivity of the soils generally decreases with increasing fines content, 2-μm clay content, LL, PI, and activity when all other factors are equal. This reflects narrower and more-tortuous pore spaces in soils with a greater fraction of fine particles and clay particles with greater bound water blocking flow paths. Similar trends were reported by Benson et al. (1994) for compacted soil barrier materials and by Lee et al. (2005) for geosynthetic clay liners. Significant scatter exists for each relationship even though each soil was compacted under similar conditions (1% wet of optimum water content with standard Proctor effort), because none of the compositional variables has a unique influence on the attributes of the pore network controlling flow. Benson et al. (1994) report similar scatter.

Fig. 5. Hydraulic conductivity of CSL soils to DI water as a function of (a) percent fines; (b) 2-μm clay content; (c) liquid limit; (d) plasticity index; (e) activity

Hydraulic Conductivity to CCP Leachate

Fig. 6 compares the hydraulic conductivities of the compacted soils to the CCP leachates at 28 kPa with the hydraulic conductivity to DI water. Fig. 6 does not include data for SC10 because this soil is not a representative CSL soil.

For six of the soils, the hydraulic conductivity to CCP leachates (

K_{CCP}

) was within a factor of ten times higher than the hydraulic conductivity to DI water (

K_{DI}

) (Fig. 6). The more plastic CL25 was the exception, having a hydraulic conductivity to CCP leachate as much as 19 times higher than the hydraulic conductivity to DI water. For five soils, the hydraulic conductivity to CCP leachate and to DI water differed by less than a factor of five and for three soils (CL28, ML14, and SC18) the hydraulic conductivity to some of the CCP leachates was lower than the hydraulic conductivity to DI water. For example, hydraulic conductivities of Soil SC18 to all CCP leachates were lower than to DI water, and for FGD leachate the hydraulic conductivity was 10 times lower.

Although hydraulic conductivities to CCP leachates at 28 kPa were higher than for DI water in the majority (24 of 35) of the specimens (Soil SC10 excluded due to high hydraulic conductivity to DI water), only five specimens permeated with CCP leachate had hydraulic conductivity exceeding

1 \times 10^{- 9} m / s

, the U.S. regulatory standard for CCP disposal facilities (Fig. 6). Three specimens of ML14 and one specimen each of CL7 and CL28 had hydraulic conductivity exceeding

1 \times 10^{- 9} m / s

, with three of the five associated with the trona leachate, one associated with low RMD leachate (ML14), and one associated with typical CCP leachate (ML14).

Seven of the 11 tests for which lower hydraulic conductivity was obtained with CCP leachate than with DI water correspond to less-conventional soils for CSLs, SC18 (all five leachates), and ML14 (FGD and high-strength leachates) (Fig. 6). Moreover, SC18 would be considered marginal when permeated with DI water (hydraulic

conductivity = 1.5 \times 10^{- 9} m / s

at 28 kPa), but acceptable when permeated with CCP leachate. Thus permeation with CCP leachate may not be detrimental to a CSL, and may be beneficial in some cases, especially for some soils that might be considered marginal for use as a soil barrier in terms of conventional recommendations for CSLs. The sensitivity of the hydraulic conductivity to chemistry of the permeant liquid illustrates that a site-specific assessment may be necessary for cases in which the hydraulic conductivity is close to

1 \times 10^{- 9} m / s

.

Mineralogy

Hydraulic conductivities to CCP leachates were largest relative to DI water for CL25, which had the lowest hydraulic conductivity to DI water [Fig. 6(b)]. Soil CH38 had the next highest hydraulic conductivities to CCP leachate relative to DI water. These soils also had the highest fraction of montmorillonite (30% for CL25 and 22% for CH38) as well as the highest fines content and clay content. The larger increases in hydraulic conductivity for these soils is consistent with other studies assessing how changes in the pore space alter hydraulic conductivity. Soils with very low hydraulic conductivity to DI water have the smallest pores, and increases in the size of these pores result in larger increases in hydraulic conductivity (e.g., Othman et al. 1994; Albrecht and Benson 2001; Benson et al. 2007, 2011). This is particularly true for montmorillonite-rich soils such as bentonite. For example, Chen et al. (2015, 2018) show that the hydraulic conductivity of bentonite is sensitive to permeation by CCP leachates, with increases in hydraulic conductivity of a factor of 10–1,000 as the ionic strength of the leachate increases. Soil CL25 had the highest montmorillonite fraction of the soils evaluated, and therefore should behave more like bentonite relative to the others soils. Soil CH38 had the next-largest increases in hydraulic conductivity relative to DI water, and the second-highest montmorillonite content of the soils evaluated. This observation is consistent with the findings of Lee and Shackelford (2005), in which GCLs with a higher percentage of montmorillonite had lower hydraulic conductivity to water, and were more susceptible to alterations in hydraulic conductivity when permeated with leachate.

Similarly, hydraulic conductivities to CCP leachates were lowest relative to DI water for the soils with the highest hydraulic conductivity to DI water (ML14 and SC18). Soils ML14 and SC18 had hydraulic conductivities close to

1 \times 10^{- 9} m / s

and no measurable montmorillonite content. The predominant minerals in these soils are kaolinite (ML14), a nonexpansive clay mineral, and quartz (SC18). Soil CL7 also was relatively insensitive to the CCP leachates, with the largest increase in hydraulic conductivity less than a factor of four (with trona leachate, highest ionic strength of CCP leachates). Nonexpansive illite and mica are the predominant clay minerals in CL7, and the quartz fraction is 43%.

Intrinsic Permeability

Fig. 7 illustrates the impact of the CCP leachates on the pore space in terms of the ratio of the intrinsic permeability of each soil to CCP leachate (

K_{CCP}

) relative to the intrinsic permeability to DI water (

K_{DI}

). Table 7 summarizes the intrinsic permeabilities for the soils at an effective stress of 28 kPa. Cases in which

K_{CCP} / K_{DI} > 1

correspond to opening of the pore space (larger pores, less-tortuous pore space), permitting fluid to flow more readily. Conversely,

K_{CCP} / K_{DI} < 1

corresponds to closing of the pore space (smaller pores, more-tortuous pore space), restricting fluid flow. Soils CL25 and CH38, which had the lowest hydraulic conductivity to DI water, had the largest

K_{CCP} / K_{DI}

, indicating that CCP leachates opened the pore space of these soils significantly. Conversely, SC18 had

K_{CCP} / K_{DI} < 1

and the lowest

K_{CCP} / K_{DI}

for all soils and leachates, indicating that CCP leachates closed the pore space of this soil relative to DI water more than the other soils. Closure of the pore space occurs through expansion of the bound layer or deposition of precipitates. Soil ML14 had

K_{CCP} / K_{DI} > 1

for the typical CCP, low-RMD, and trona leachates, and

K_{CCP} / K_{DI} < 1

for the typical FGD and high-strength leachates, indicating opening or closing of the pore space depending on the permeant liquid. All other soils had

K_{CCP} / K_{DI}

just above 1, indicating that CCP leachate opened the pore space relative to DI water.

Fig. 7. Ratio of intrinsic permeability of soil permeated with CCP leachate to intrinsic permeability of soil permeated with DI water

Table 7. Intrinsic Permeability of Soils at Effective Stress of 28 kPa (

m^{2}

)

Soil	Intrinsic permeability ( $m^{2}$ )
Soil	DI water	Typical CCP	Low RMD	FGD	High strength	Trona
CL7	$3.6 \times 10^{- 17}$	$4.8 \times 10^{- 17}$	$4.3 \times 10^{- 17}$	$3.5 \times 10^{- 17}$	$8.1 \times 10^{- 17}$	$1.4 \times 10^{- 16}$
CL25	$9.5 \times 10^{- 19}$	$3.6 \times 10^{- 17}$	$9.8 \times 10^{- 19}$	$1.3 \times 10^{- 17}$	$2.4 \times 10^{- 17}$	$7.8 \times 10^{- 18}$
ML14	$8.3 \times 10^{- 17}$	$9.2 \times 10^{- 17}$	$2.6 \times 10^{- 16}$	$4.2 \times 10^{- 17}$	$2.9 \times 10^{- 17}$	$2.7 \times 10^{- 16}$
CL28	$2.6 \times 10^{- 17}$	$3.6 \times 10^{- 17}$	$4.5 \times 10^{- 17}$	$7.6 \times 10^{- 17}$	$2.8 \times 10^{- 17}$	$4.4 \times 10^{- 17}$
CH38	$7.8 \times 10^{- 18}$	$6.5 \times 10^{- 17}$	$3.8 \times 10^{- 17}$	$2.2 \times 10^{- 17}$	$3.1 \times 10^{- 17}$	$3.6 \times 10^{- 18}$
SC17	$1.3 \times 10^{- 17}$	$2.5 \times 10^{- 17}$	$4.8 \times 10^{- 17}$	$4.2 \times 10^{- 17}$	$3.0 \times 10^{- 17}$	$1.9 \times 10^{- 17}$
SC10	$1.5 \times 10^{- 14}$	—	—	—	—	$7.4 \times 10^{- 17}$
SC18	$9.3 \times 10^{- 17}$	$3.6 \times 10^{- 17}$	$3.3 \times 10^{- 17}$	$1.5 \times 10^{- 17}$	$3.2 \times 10^{- 17}$	$4.5 \times 10^{- 17}$

Note: Kinematic $viscosity \times 10^{- 7} m^{2} / s$ : DI $water = 8.7$ , $FGD = 8.1$ , high $strength = 8.8$ , low $RMD = 8.3$ , $trona = 9.0$ , typical $CCP = 8.2$ ; density ( $g / mL$ ): DI $water = 1.00$ , $FGD = 1.05$ , high $strength = 1.12$ , low $RMD = 1.04$ , $trona = 1.64$ , typical $CCP = 81.03$ .

Index Properties

Fig. 8 shows the hydraulic conductivity to CCP leachate relative to the hydraulic conductivity to DI water (

K_{CCP} / K_{DI}

) versus the primary soil index properties used to identify suitable CSL materials. Definitive trends did not exist between

K_{CCP} / K_{DI}

and any of these index properties. Only fines content exhibited some trend, with the largest

K_{CCP} / K_{DI}

corresponding to soils with the highest fines content (

> 90 %

) and the lowest

K_{CCP} / K_{DI}

corresponding to soils with the lowest fines content (

< 40 %

). No other trends existed between

K_{CCP} / K_{DI}

and the primary index properties. Thus, reliable inferences regarding the impacts of CCP leachate on hydraulic conductivity may not be practical with index properties that have been considered indicative of sensitivity to leachate interactions (Dunn and Mitchell 1984; Bowders et al. 1985). Based on the aforementioned discussion, mineralogy is a more effective indicator, with soils richer in montmorillonite being more sensitive to CCP leachates.

Fig. 8. Ratio of hydraulic conductivity to CCP leachate to the hydraulic conductivity to DI water ( $K_{CCP} / K_{DI}$ ) as a function of (a) fines content; (b) 2-μm clay content; (c) plasticity index; (d) liquid limit; (e) activity

Impact of Effective Stress

Table 6 summarizes the hydraulic conductivities obtained at higher effective stresses. In all but one case, increasing the effective stress to 450 kPa (corresponding to a CCP disposal facility with a depth of approximately 30 m) resulted in hydraulic

conductivity < 1 \times 10^{- 9} m / s

for all leachates (Soil SC10 excluded due to high hydraulic conductivity to DI water). Soil CL7 was an exception, having hydraulic conductivity to trona leachate of

1.1 \times 10^{- 9} m / s

at 450 kPa.

Fig. 9 shows the relationship between hydraulic conductivity and effective stress for all soils in terms of the ratio of hydraulic conductivity at an effective stress of 28 kPa (

K_{28}

) to the hydraulic conductivity at a specified effective

stress > 28 kPa

(

K_{σ^{'}}

). When

K_{28} / K_{σ^{'}} > 1

, the hydraulic conductivity at effective stress

σ^{'}

is lower relative to the hydraulic conductivity obtained at 28 kPa. The upper and lower dashed lines in Fig. 9 represent the range of

K_{28} / K_{σ^{'}}

for a given effective stress. Increasing the effective stress from 28 to 450 kPa resulted in a decrease in hydraulic conductivity of more than two orders of magnitude, but the impact of effective stress was specific to the soil and leachate used for permeation. For example,

K_{28} / K_{σ^{'}}

varied from less than a factor of 2 for Soil CL25 as the effective stress increased from 28 kPa to 450 kPa to more than a factor of 100 for Soil ML14. A tenfold reduction in hydraulic conductivity was typical, as illustrated by the regression line in Fig. 9, which was obtained by nonlinear least-squares regression on all the data in Table 6 (except that for Soil SC10). The regression line corresponds to

K_{σ^{'}} = K_{28} \exp {- 0.34 In R_{s} - 0.18 {(In R_{s})}^{2}}

(3)

where

R_{s}

= ratio of the applied effective stress (

σ^{'}

) to 28 kPa (

R_{s} = σ^{'} / 28

); and the coefficient of determination

(R^{2}) = 0.71

.

Fig. 9. Hydraulic conductivity at 28 kPa effective stress realtive to hydraulic conductivity at a specified effective stress as a function of the effective stress for CSL specimens permeated with DI water and synthetic leachates

No systematic effect of CCP leachate was evident in the data. However, the sensitivity to effective stress was influenced by the hydraulic conductivity at low effective stress. The largest reductions in hydraulic conductivity occurred for soils that had higher hydraulic conductivity at 28 kPa (CL28, ML14, and SC18), the smallest reductions occurred for the soils with the lowest hydraulic conductivity at 28 kPa (CL25 and CH38), and intermediate reductions in hydraulic conductivity occurred for the soils with intermediate hydraulic conductivity at 28 kPa (CL7 and SC17). This sensitivity indicates that increasing the effective stress has a greater impact on the pore space for soils with larger and/or more connected pores at 28 kPa.

Summary and Conclusions

Tests were conducted on eight finer-grained soils to evaluate how coal combustion product leachates may affect the hydraulic conductivity of compacted soil liners used for CCP disposal facilities. All eight soils are used as soil barriers at waste containment facilities in North America. They represent a broad range of particle size distribution, Atterberg limits, and mineralogy, and meet the minimum compositional recommendations by Daniel (1990) and Benson et al. (1994) for acceptable CSL materials. Hydraulic conductivity tests were conducted with the five characteristic CCP leachates identified by Benson et al. (2014) from the Electric Power Research Institute database of CCP leachates.

Tests with DI water indicated that seven of the eight soils used in the study would be considered suitable for a CSL. Hydraulic conductivity tests were conducted on these seven soils to chemical equilibrium (as defined in ASTM D7100) at an effective stress of 28 kPa with each of the characteristic CCP leachates (one leachate per specimen). After chemical equilibrium was established at 28 kPa, the specimens were successively consolidated and permeated to hydraulic equilibrium (as defined in ASTM D5084) to average effective stresses of 100, 250, and 450 kPa to evaluate how the hydraulic conductivity could change as a CCP disposal facility is filled.

The findings indicate that a broad range of soils are suitable for CSLs for CCP disposal facilities. Five of the seven soils had hydraulic

conductivity < 1 \times 10^{- 9} m / s

when permeated with any of the CCP leachates at 28 kPa effective stress (disposal facility with first lift of CCP placed), and lower hydraulic conductivity at higher effective stress. The hydraulic conductivity to CCP leachate was less than five times the hydraulic conductivity to DI water for five of the soils, and a large increase in hydraulic conductivity was obtained for only one soil (19 times hydraulic conductivity to DI water). For three soils, the hydraulic conductivity to some CCP leachates was lower than the hydraulic conductivity to DI water.

Larger increases in hydraulic conductivity were associated with soils having lower hydraulic conductivity to DI water and are attributed to opening of the pore space due to chemical interactions with the CCP leachate, as illustrated by comparing the intrinsic permeability obtained with CCP leachate with the intrinsic permeability obtained with DI water. Soils exhibiting the largest increases in hydraulic conductivity relative to DI water typically had the greatest fines content (

> 90 %

) and significant montmorillonite content. Soils exhibiting the smallest increases in hydraulic conductivity had the lowest fines content (

< 40 %

) and contained little to no montmorillonite. Hydraulic conductivity to CCP leachate was not related systematically to any of the other primary index properties, although the soils exhibiting the largest increase in hydraulic conductivity had the highest fines content. These findings indicate that mineralogy is a better indicator of sensitivity to CCP leachates than are index properties, with greater potential for alterations in hydraulic conductivity anticipated for soils with higher montmorillonite content. For all soils, however, sensitivity to chemical interactions depended on the characteristics of the leachate. Leachate-specific testing should be considered when evaluating CSL materials for CCP leachates that differ appreciably from the leachates used in this study.

Increasing the effective stress from 28 to 450 kPa resulted in a reduction in hydraulic conductivity (one order of magnitude, on average), the latter stress corresponding to a disposal facility with CCP depth of approximately 30 m. All but one of the soils evaluated had hydraulic conductivity less than

1 \times 10^{- 9} cm / s

for all CCP leachates at an effective stress of 450 kPa, illustrating the importance of evaluating the hydraulic conductivity at the appropriate effective stress when assessing suitability of a CSL soil for CCPs.

Acknowledgments

Financial support for this study was provided by the Electric Power Research Institute (EPRI). The findings in this report are those of the authors, and may not reflect the policies or opinions of EPRI. Ken Ladwig and Bruce Hensel of EPRI provided assistance during the study.

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Published In

Journal of Geotechnical and Geoenvironmental Engineering

Volume 144 • Issue 4 • April 2018

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This work is made available under the terms of the Creative Commons Attribution 4.0 International license, http://creativecommons.org/licenses/by/4.0/.

History

Received: Jan 3, 2017

Accepted: Sep 27, 2017

Published online: Jan 30, 2018

Published in print: Apr 1, 2018

Discussion open until: Jun 30, 2018

Authors

Affiliations

Craig H. Benson, F.ASCE [email protected]

Dean, School of Engineering, Univ. of Virginia, Charlottesville, VA 22903 (corresponding author). E-mail: [email protected]

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Jiannan N. Chen, A.M.ASCE [email protected]

Assistant Professor, School of Geoscience and Environmental Engineering, Southwest Jiaotong Univ., Chengdu 611756, China. E-mail: [email protected]

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Tuncer B. Edil, Dist.M.ASCE [email protected]

Professor Emeritus, Geological Engineering, Civil and Environmental Engineering, Univ. of Wisconsin-Madison, Madison, WI 53706. E-mail: [email protected]

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William J. Likos, M.ASCE [email protected]

Gary and Rosemarie Wendt Professor, Geological Engineering, Civil and Environmental Engineering, Univ. of Wisconsin-Madison, Madison, WI 53706. E-mail: [email protected]

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Abstract

Introduction

Materials

Soil Liners

Leachates

Methods

Specimen Preparation

Hydraulic Conductivity Testing

Permeant Liquids and Chemical Analysis

Results and Discussion

Hydraulic Conductivity to DI Water

Hydraulic Conductivity to CCP Leachate

Mineralogy

Intrinsic Permeability

Index Properties

Impact of Effective Stress

Summary and Conclusions

Acknowledgments

References

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