Geochemical transport modelling of drainage from experimental mine tailings cells covered by capillary barriers

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Applied Geochemistry Applied Geochemistry 23 (2008) 1–24 www.elsevier.com/locate/apgeochem

Geochemical transport modelling of drainage from experimental mine tailings cells covered by capillary barriers J. Molson a

a,*

, M. Aubertin

a,c

, B. Bussie`re

b,c

, M. Benzaazoua

b

Department of Civil, Geological and Mining Engineering, E´cole Polytechnique, Montre´al, C.P. 6079 succ. Centre-ville, Montre´al, Que´bec, Canada H3C 3A7 b Department of Applied Sciences, Universite´ du Que´bec en Abitibi-Te´miscamingue, 445 Universite´ Blvd, Rouyn-Noranda, Que´bec, Canada J9X 5E4 c Industrial NSERC-Polytechnique-UQAT Chair, Environment and Mine Wastes Management, Canada Received 23 February 2007; accepted 9 August 2007 Editorial handling by M. Kersten Available online 11 September 2007

Abstract The use of covers with capillary barrier effects (CCBEs) for reducing acid mine drainage (AMD) from sulphidic mine tailings is simulated using the MIN3P finite volume model for coupled groundwater flow, O2 diffusion and multi-component reactive transport. The model is applied to simulate five pilot-scale in situ test cells containing reactive tailings from the Manitou mine site, Val d’Or, Que., Canada. Four of the cells were constructed with CCBEs over the tailings, while the fifth tailings cell was left uncovered. Observed and simulated discharge from the base of each cell showed that the capillary barrier covers significantly reduced sulphide oxidation and AMD. Compared to acidic discharge from the uncovered cell, discharge from the four CCBE-covered cells had neutral pH levels and 1–7 orders of magnitude lower concentrations of SO4, Fe, Zn, Cu and Al. The simulations showed that the moisture retaining layer of the CCBEs reduced AMD by inhibiting O2 diffusion into the underlying reactive wastes. Provided the moisture-retention layer of the CCBE remains close to saturation, its thickness had a relatively minor effect. Under such near-saturated conditions, O2 availability is limited by its diffusion rate through the bulk porous medium and not by the diffusion rate through the oxidized grain shells. The model is providing important new insights for comparing design alternatives for reducing or controlling AMD.  2007 Elsevier Ltd. All rights reserved.

1. Introduction Acid mine drainage (AMD) from sulphidic waste rock piles and mine tailings can be a significant source of environmental contamination due to potentially high concentrations of SO4, Fe and dis*

Corresponding author. Fax: +1 514 340 4477. E-mail address: [email protected] (J. Molson).

solved metals (e.g., Jambor, 1994; Sracek et al., 2003; Smuda et al., 2007). The environmental impact is of critical concern in the mining industry, with potentially several billion dollars of liability in Canada alone (Tremblay and Hargreaves, 1999). Research is advancing on characterizing these types of mine wastes, understanding the reactive processes responsible for AMD as well as developing new methods of prevention and remediation (Lefebvre

0883-2927/$ - see front matter  2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.apgeochem.2007.08.004

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J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

et al., 2001; Schneider et al., 2002; Aubertin et al., 2002; Blowes et al., 2003a; Price, 2003; Schippers et al., 2007). The generation of AMD from reactive mine wastes is often controlled by the diffusive flux of O2, which decreases as the pore water content increases (e.g., Mbonimpa et al., 2003; Aachib et al., 2004). Several strategies for reducing AMD are therefore based on maintaining a high water content within the mine wastes or within mine waste covers. Three possible approaches involve flooding the wastes with water (e.g., Malmstro¨m et al., 2006), maintaining an elevated water table within the waste (Aubertin et al., 2002; Dagenais et al., 2006), and applying various cover systems including covers with capillary barrier effects (CCBEs; Aubertin et al., 1995, 1996, 1999; Bussie`re et al., 2003). The behaviour of CCBEs depends on the contrast in water retention characteristics between a fine-grained and underlying coarse-grained porous material. In a wet or temperate climate setting, a fine-grained layer is typically sandwiched between two coarser grained layers. Under negative pressure (in unsaturated conditions), the coarse layers typically drain rapidly (often to a residual water content) while the fine layer remains close to saturation due to water retention associated with capillary barrier effects (Nicholson et al., 1989; Aubertin et al., 1999; Bussie`re et al., 2003). Emplaced at the surface of AMD-generating tailings, a cover with capillary barrier effects can reduce the rate of O2 diffusion, thereby reducing the rate of sulphide oxidation. Capillary barriers have also been proposed to reduce O2 diffusion through waste rock piles, and can be used to control surface and internal fluid flow (Bussie`re et al., 2003; Molson et al., 2005; Aubertin et al., 2006). Designing efficient CCBEs can be difficult because of variable climatic conditions and layer geometry, and complex behaviour of the unsaturated materials. Most previous research has focussed on laboratory experiments, while field scale and pilot studies have been relatively rare. Numerical simulation models are often the most versatile tools for assessing and predicting the hydraulic behaviour of CCBEs (e.g., Akindunni et al., 1991; Oldenburg and Pruess, 1993; Bussie`re, 1999; Fala et al., 2005) and other cover types such as water covers and composite caps (e.g., Romano et al., 2003; Kim and Benson, 2004). Models can also be used for predicting reactive transport through mine waste systems (Nicholson et al., 2003; Molson et al., 2005;

Linklater et al., 2005). For example, Lefebvre et al. (2001) adapted the TOUGH model (Pruess, 1991) to simulate flow, O2 transport and pyrite oxidation within waste rock piles. They considered the special cases of low permeability boundary membranes and layered co-mingling and studied their effect on the internal moisture distribution, O2 flux, temperature, and oxidation rates. Romano et al. (2003) applied the PYROX model (Wunderly et al., 1996), linked to the unsaturated flow model WAVES (Dawes and Short, 1993) to simulate AMD from 1D waste columns constructed with various cover scenarios. They considered full water covers, O2 diffusion barriers made of CFT (cassiterite float tails) and combined water/CFT covers. They concluded that combined water/CFT covers were most efficient, although a water cover alone was almost equally effective. In the Lefebvre et al. (2001) and Romano et al. (2003) models, only the direct oxidation products (H+, Fe2+ and SO2 4 Þ were simulated; the full geochemical system including geochemical speciation and pH buffering by solid minerals was not considered. Mayer et al. (2003) provide an overview of the latest developments in reactive transport models for mine waste applications. In this paper, the numerical model MIN3P (Mayer et al., 2002) is used to gain insight into the application of capillary barrier covers for reducing AMD from reactive tailings. The model is applied to simulate a series of four experimental in situ field cells in which CCBEs were emplaced over reactive (pyritic) but unoxidized tailings from the Manitou mine site, Val d’Or, Quebec (Fig. 1). The results are compared to a fifth control tailings cell without

Fig. 1. Site location map of the Manitou mine site near Val d’Or, Que., Canada.

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

a CCBE. The modelling study also investigates the behaviour of CCBEs over long time scales, and assesses parameter sensitivity. Construction of the experimental field cells and their hydraulic behaviour is described in detail by Aubertin et al. (1999) and Bussie`re et al. (2007). Only a brief overview will be presented below. The focus of this paper is on the coupled hydraulic-geochemical behaviour of the CCBE-covered tailings and the aqueous geochemistry of the discharge water from each cell. The objectives of the paper are to illustrate how a reactive transport model can be used to help interpret the observed performance of the field cell CCBEs and for predicting their long term geochemical behaviour. This is a critical step for preparing a monitoring system for existing large-scale CCBE covers (e.g., at the LTA site, see Bussie`re et al., 2006), and for improving the design of proposed CCBEs. The study will also be useful as a case study for illustrating the advantages and limitations of advanced reactive transport modelling. 2. Field experiment set-up During the summer of 1995, five pilot-scale experimental field cells were installed at ITEC Mineral Inc.’s Norebec-Manitou mine site near Val d’Or, Que., Canada (Aubertin et al., 1997; Bussie`re, 1999; Bussie`re and Aubertin, 1999; Bussie`re et al., 2001). The emplaced cells were the shape of inverted pyramids, each measuring about 11 · 11 m at the surface and 3 m deep at the centre (the configuration of Cell 1, typical of all cells, is shown in Fig. 2). Each cell was underlain by an impervious geomembrane (COEX 30 mil) which channelled

Cell 1

2.8

Elevation (m)

2.4

sand

1.2 0.8

drainage water to a subdrain. The top surface of each cell was open to natural infiltration and the geochemistry of the drainage water was monitored over a 4-a period. The base of each experimental cell was filled with 1.5 m of fresh sulphidic tailings from the Manitou mine. In cells 1–4, the tailings were overlain by 0.4 m of non-reactive sand, followed by a finegrained moisture-retaining layer (MRL), then covered at the surface by a final 0.3 m layer of sand. Cell 5 was a control cell containing only the 1.5 m of reactive tailings, without a cover. The moisture retaining layer of the CCBE in cells 1–4 was composed of various combinations and thicknesses of low-sulphide fine-grained milling residue (from the Sigma mine, Quebec) or natural till (Fig. 3). The covers were instrumented at various depths for monitoring water content (hw) and suction (w), and leachate from the subdrain was collected for analysis. Further information on the instrumentation and monitoring of the cells is provided in Bussie`re et al. (2007). Cell 4

q

q

Cell 5

sand q

sand sand

Sigma

Sigma

Natural silt till

Sigma

sand

sand

sand

sand

Manitou sulphidic tailings

Manitou sulphidic tailings

Manitou sulphidic tailings

Manitou sulphidic tailings

2 1.6

Fig. 2. Structural model of the CCBE in situ test Cell #1. Cells 2–4 were conceptually similar, with different materials or thicknesses for the moisture retaining layer; the tailings in Cell 5 were left uncovered.

Cell 3

Cell 2 q

3

q Manitou sulphidic tailings

0.4 0 Discharge

Fig. 3. Structure of the five experimental cells as simulated by the numerical model in 1D. Cell #5 is a control cell, constructed without a CCBE. The ‘‘Sigma’’ layer represents the CCBE moisture-retention material made of low-sulphide tailings from the Sigma mine.

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J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

Laboratory column experiments with the same reactive tailings and covers were also run prior to and concurrent with the field trials (Aubertin et al., 1995, 1997, 1999; Joanes, 1999). The complete laboratory experiment included a series of plexiglass columns with heights ranging from about 1.5 to 2.0 m depending on the cover scenario. Since the laboratory results were consistent with those obtained from the field, this paper will focus on the field experiments and numerical modelling.

where Srw is the residual water saturation (m3 m3), w is the pressure head (m), av, nv and mv are the van Genuchten (1980) parameters determined from the moisture-retention data (with mv = 1  1/nv) and k is a parameter representing the degree of pore connectivity (k = 0.5 is used here). In Eq. (3), Sew is the effective volumetric water saturation given by S ew ¼

S w  S rw : 1  S rw

ð4Þ

3. Numerical model 3.2. Transport equation In this study, the numerical finite volume model MIN3P (Mayer, 1999; Mayer et al., 2002) is applied to simulate flow and reactive transport through the experimental field cells. The 3D code has been previously verified and applied to a variety of mine waste systems including laboratory and large-scale mine impact studies (Mayer et al., 1999; Bain et al., 2001; Amos et al., 2004).

The transport equation for advective–dispersive transport of the dissolved phase components is written as: i o h i oh S w /  T wj þ ½S g /  T gj  þ r qw T wj ot ot h i    r S w /  Dw rT wj  r S g /  Dg rT gj w;ext  Qw;w  Qw;s  Qg;ext j j j  Qj

3.1. Flow equation

¼ 0 j ¼ 1 to N c ; The MIN3P model solves the governing equation for Darcy-type fluid flow in a variably saturated porous medium. Neglecting convective O2 flow and assuming a passive air phase, the mass conservation equation for the water phase can be written as: SwSs

oh oS w þ/  r  ½k rw Krh  Qw ¼ 0; ot ot

ð1Þ

where Sw is the volumetric water saturation (m3 m3), Ss is the specific storage coefficient (m1), h is the hydraulic head (m), t is time (s), u is the porosity (m3 m3), Qw is a source–sink term (s1), krw is the relative permeability of the porous medium with respect to the water phase (dimensionless), and K is the saturated hydraulic conductivity tensor (m s1). The nonlinear functions defining the water retention curves (Sw–w) and relative permeability functions (krw–w) are given by van Genuchten (1980) and Wo¨sten and van Genuchten (1988), according to:  mv 1  S rw ð2Þ S w ¼ S rw þ n 1 þ ðav wÞ v and  2 v mv k rw ¼ S lew 1  ð1  S 1=m ; ew Þ

ð3Þ

ð5Þ

where Sg is the gas phase saturation (m3 m3), T wj and T gj ðkg m3 H2 O Þ are the total water and gas phase concentrations of component j, respectively, qw (m s1) is the Darcy fluid flux and Dw and Dg (m2 s1) are the dispersion tensors for the water and gas phase components, respectively (including hydrodynamic dispersion and diffusion in the water phase and diffusion in the gas phase). The source– sink terms Qw;w and Qw;s represent contributions to j j w Tj from intra-aqueous and precipitation– dissolution reactions, respectively. Similarly, Qw;ext and Qg;ext represent external source–sinks for j j the aqueous and gas phases, respectively. The conservation law for the change in mineral mass is given by: ouk ¼ V mk  Rmk ; k ¼ 1 to N m ; ð6Þ ot where uk is the volume fraction of the mineral m (m3min m3 is the mineral molar volume bulk Þ, V k 1 (L min mol ), Rmk is the overall reaction rate for 1 the mineral ðmol L3 bulk s Þ, which controls precipitation/dissolution reactions, and Nm is the number of minerals. Chemical reactions in MIN3P can be equilibrium-controlled using the law of mass action, or they can be kinetically-controlled. For kinetic reactions, the reaction rate Rmk in Eq. (6) is user-defined

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

and can take many forms (see Mayer et al., 2002). In this paper, the two formulations for surface-controlled reactions are expressed as: ½1  IAPk =K k  Rmk ¼ k m;eff k

ð7Þ

and Rmk ¼ S k k mk ½T i n ;

ð8Þ

where k m;eff k 1 ðmol L3 bulk s Þ,

is an effective rate coefficient IAPk is the ion-activity product, Kk is the equilibrium constant, k mk is the specific rate 1 constant ðmol1n LnH2 O m2 mineral s Þ, Sk is the reactive 2 surface area of the grains ðmmin L1 bulk Þ and Ti is the aqueous phase concentration ðmol L3 H2 O Þ of the rate-controlling component i. The mineral reactivity can be assumed constant or can be made a function of the time-dependent mineral volume fraction according to Mayer et al. (2002):  t n u k teff ¼ k 0eff ; ð9Þ u0

where u0 and ut are the mineral volume fractions at t = 0 and t, respectively, and n is an exponent which can take the value n = 2/3 (‘‘two-third’’ model) or n = 0 (constant rate). A rate which decreases with the mineral volume fraction could be used, for example, to account for a decreasing reactive surface area, or for build-up of non-reactive surface coatings on the mineral grains. Other reactions can be described in MIN3P as being transport (diffusion)-controlled, in which the overall rate is dependent on the diffusion rate of a reactant through a mineral coating. The shrinkingcore model, for example, which assumes spherical grain geometry, is often used to simulate local (grain) scale O2 diffusion-controlled sulphide mineral oxidation (Davis and Ritchie, 1986). Transport of O2 through the partially saturated porous medium is governed in MIN3P by advection–dispersion in the aqueous phase, and by diffusion in the gas phase using the saturation-dependent tortuosity formulation of Millington (1959). Equilibrium exchange between each phase is also accounted for. For this study, MIN3P was modified to incorporate the saturation-dependent diffusion formulation developed by Aachib et al. (2004), which can be expressed for each phase as: 1  Dp ¼ 2 D0p  h3:4 ; ð10Þ p / where p is the phase (water or gas), D0p is the O2 diffusion coefficient in phase p (m2 s1) and hp is the

5

phase-filled porosity [dimensionless] (i.e., the volumetric water or gas content). Eq. (10) is analogous to the effective diffusion coefficient of Aachib et al. (2004) in the special case where O2 advection in the aqueous phase is negligible. Using the shrinking core model as a basis, the sulphide oxidation rate can be written as (Mayer, 1999):     rpi ½O2 w 3 Rk ¼ 10 S k Dk  ; ð11Þ ðrpi  rri Þ  rri tk where Dk is the diffusion coefficient (m2 s1) through the oxidized particle rim, rpi is the radius of the grain (m), rri is the radius of the unoxidized grain core (m), [O2](aq) is the concentration of O2 in water at the grain surface (calculated from the O2 diffusion equation through the bulk porous medium), and tk is the stoichiometric coefficient of O2 in the sulphide oxidation reaction. MIN3P uses a control volume, global implicit solution method which is locally mass conservative. Newton iteration is employed to linearize both the flow and transport equations. An isothermal system and uniform fluid density is assumed for all simulations. Further details on the numerical solution approach and handling of ion-exchange and mineral precipitation–dissolution reactions are given in Mayer (1999) and Mayer et al. (2002). 4. Physical properties and hydro-geochemical system of the Manitou experimental cells Each experimental field cell is here considered as a vertical 1D column, discretized uniformly using 1 0 1 control volumes. Using the hydrogeological monitoring data, a similar 1D approach was previously validated for modelling unsaturated water flow within the CCBE-covered cells (Bussie`re, 1999; Bussie`re et al., 2007). Five cover scenarios will be considered (Fig. 3). Each case includes 1.5 m of sulphidic tailings at the base overlain by various configurations of CCBE covers. As installed in the field, Cell 5 included only the 1.5 m of Manitou tailings, without a cover. Three porous materials are considered in each of the simulated CCBE cells: the reactive Manitou tailings, the fine-grained material of the moisture-retention layer (made of low-sulphide, non-acid generating tailings from the Sigma mine for Cells 1, 3 and 4 and a natural till for Cell 2), and a sulphide-free sand material used to sandwich the moisture-retention layer. Material properties affecting

6

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

Table 1 Physical material properties for the field experimental cells (after Aubertin et al., 1999; Bussie`re et al., 2007) Material

/

Sand Sigma low-S tailings Sigma 1bd Natural Till Manitou tailings

0.32 0.41 0.41 0.41 0.43

Srw 0.03 0.08 0.08 0.08 0.07

DHa (mm) 0.74 0.01 0.01 0.008 0.04

Kz(sat) (m s1) 5

7.2 · 10 1.5 · 106 1.5 · 106 2.0 · 107 2.7 · 105

av, nvb (m1) (dimensionless)

AEVc (m)

2.9, 10.2 0.13, 2.6 0.30, 2.4 0.15, 2.6 0.61, 2.6

0.28 2.75 2.75 2.75 2.65

The ‘‘Sigma’’ and ‘‘Natural Till’’ materials were used as the moisture-retaining layer in the CCBEs; the Manitou unit formed the reactive tailings (see also Fig. 2). a Equivalent surface area grain diameter (see Eq. (13)). b van Genuchten (1980) parameters (‘ = 0.5 for all materials). c AEV, air entry value. d Sigma 1b used in the sensitivity case.

the hydrogeological behaviour for each layer are provided in Table 1; the water retention and hydraulic conductivity curves are shown in Fig. 4. All simulations considered 16 aqueous components, 2 redox pairs, 40 secondary species, 2 gases and 15 minerals (Table 2). All intra-aqueous reactions are considered equilibrium-controlled, using equilibrium constants from the MIN3P data base (which originate from the WATEQ4F and MINTEQ/A2 data bases; see Ball and Nordstrom, 1991; and Allison et al., 1991, respectively). All reac-

0

(b) Sigma low-S Tailings water-retention layer Cell 1 (base case)

0.4 0.2

Cell 1b

0

(c) Natural Till water-retention layer

0.4 0.2 0

(d) Manitou Reactive Tailings 0.4 0.2 0 1 10

2

10 10 Suction (cm water)

3

k (cm/s)

0.2

-2

10 10-3 -4 10 -5 10 -6 10 -7 10

k (cm/s)

0.6

0.4

10 -3 10 -4 10 -5 10 -6 10 -7 10

-2

10 -3 10 -4 10 -5 10 -6 10 -7 10

k (cm/s)

Water Content

0.6

-2

water content hydraulic conductivity

-2

10 -3 10 -4 10 -5 10 -6 10 -7 10

k (cm/s)

Water Content Water Content

0.6

Water Content

(a) Sand 0.6

Fig. 4. Water retention and hydraulic conductivity curves for each of the cell materials used in the model. Curves are defined by Eqs. (2) and (3), using parameters from Table 1. Cell 1b curve in Fig. 4b is used in the sensitivity case (see Fig. 13).

tions except for sulphide mineral oxidation and dissolution of anorthite, albite and muscovite were considered reversible. Similar conceptual and numerical models of acid mine drainage can be found in Blowes et al. (2003b), Salmon and Malmstrom (2004), Ouangrawa (2007) and Ouangrawa et al. (2007). Preliminary simulations of the Manitou cells using a simplified mineralogy were presented by Molson et al. (2004). The mineralogical analyses of the Manitou sulphide-bearing tailings by X-ray diffraction (XRD; using a Bruker AXS Inc. Model D8 Advance using a Co anticathode, followed by a Rietveld quantification), showed an abundance of quartz (66%vol.; Vmineral/Vsolids · 100), as well as chlorite (12%), muscovite (10%), pyrite (7%), anorthite (5%), gypsum (0.2%) and K-jarosite (0.1%). Traces of carbonates (calcite, dolomite) were also found (<1%). The XRD-derived mineralogical composition of the Sigma low-sulphide tailings, which formed the moisture-retention layer in Cells 1, 3 and 4, was dominated by quartz (43%vol.), albite (20%), muscovite (12%), chlorite (8%), calcite (6%), goethite (2%), gypsum (1%), anorthite (1%), K-feldspar (1%) and K-jarosite (0.8%), as well as pyrite (4%) and trace amounts of sphalerite and chalcopyrite (<1%). XRD data were not available for the natural till unit, however a previous optical microscopy analysis showed an abundance of quartz (45%), albite (25%), K-feldspar (10%), biotite/muscovite (10%), chlorite (5%) and anorthite (5%). No XRD data were available for the sand, therefore a simplified mineralogy was assumed, composed of quartz (55%), 10% each for K-feldspar, anorthite, albite and muscovite, and small amounts of calcite, siderite and gibbsite (Table 3; the sand was from a local source used for making cement, thus was relatively inert).

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

7

Table 2 Reaction stoichiometry and mineral equilibrium constants K mk assumed in the modelling of the Manitou experimental test cells Mineral

log K m k

Reaction 2SO2 4

2þ

þ

a

Pyrite Sphalerite Chalcopyrite Calcite Siderite Gibbsite Gypsum Ferrihydrite Jarosite K-feldspar Anorthite Albite Muscovite Chlorite Silica

FeS2 þ 7=2O2 þ H2 O ) Fe þ þ 2H ZnS þ 2O2 ) Zn2þ þ 2SO2 4 CuFeS2 þ 4O2 ) Cu2þ þ Fe2þ þ 2SO2 4 CaCO3 () Ca2þ þ CO2 3 2 2þ FeCO3 () Fe þ CO3 Al(OH)3 + 3H+ () Al3+ + 3H2O CaSO4  2H2 O () Ca2þ þ SO2 4 þ 2H2 O Fe(OH)3 + 3H+ () Fe3+ + 3H2O KFe3 ðSO4 Þ2 ðOHÞ6 þ 6Hþ () Kþ þ 3Fe3þ þ 2SO2 4 þ 6H2 O (KAl)Si3O8 + 4H+ + 4H2O ) K+ + Al3+ + 3H4SiO4 CaAl2Si2O8 + 8H+ ) Ca2+ + 2Al3+ + 2H4SiO4 (NaAl)Si3O8 + 4H+ + 4H2O ) Na+ + Al3+ + 3H4SiO4 KAl2(AlSi3O10)(OH)2 + 10H+ ) K+ + 3Al3+ + 3H4SiO4(aq) (Mg2Fe3Al2)Si3O10(OH)8 + 16H+ ) 2Mg2+ + 3Fe2+ + 2Al3+ + 3H4SiO4 + 6H2O SiO2(am) + 2H2O () H4SiO4

Redox couples Fe2+/Fe3+  SO2 4 /HS

Fe2+ + 1/4 O2(aq) + H+ () Fe3+ + 1/2 H2O þ HS þ 2O2 ðaqÞ () SO2 4 þH

8.5 138.5

Gas partitioning O2(g)/O2(aq) CO2(g)/CO2(aq)

O2(g) () O2(aq) + CO2(g) + H2O () CO2 3 + 2H

2.9 18.1

a a

8.5 10.5 8.1 4.6 4.9 9.2 0.08b a a a

13.0b 3.98

(am), amorphous. Equilibrium constants from the MIN3P database (Mayer et al., 2002). a Irreversible reaction. b Irreversible reaction, log K control.

Table 3 Mineralogical composition for each cell material in the base case simulations (m3mineral m3 solids  100%; converted in MIN3P to mineral volume fractions (fv) in m3mineral m3 bulk Þ Mineral Pyrite Sphalerite Chalcopyrite Calcite Siderite Gibbsite Gypsum Ferrihydrite K-jarosite K-feldspar Anorthite Albite Muscovite Chlorite Quartz Total

Manitou tailings 6.0 0.2 0.4 1.2 0.00 0.00 0.23 0.00 0.18 0.0 5.2 0.0 9.0 12.0 66. 100

Sigma low-S tailings 1.7 105 0.00 8.5 0.34 0.0 1.0 1.7 0.8 1.0 1.0 20.0 12. 8.5 43.0 100

Natural till 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 10.0 5.0 25.0 10.0 5.0 45.0 100

Sand 0.0 0.0 0.0 3.0 1.5 0.7 0.0 0.0 0.0 10.0 10.0 10.0 10.0 0.00 55.0 100

Values derived from Bernier (1998), Aubertin et al. (1999) and Benzaazoua (2006), allowing for uncertainty in the mineralogical analysis. See Fig. 5 for graphical profiles in Cell 1.

The XRD analyses, while precise for the selected samples, do not reflect inherent uncertainty due to material heterogeneity. A comparison with a previ-

ous microscopic analysis (Aubertin et al., 1999; Joanes, 1999) suggests that some mineral fractions could be significantly different among samples. In

8

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

the Manitou tailings, for example, Aubertin et al. (1999) give a volume fraction for gypsum of 3%, and pyrite volume fractions ranging from 2.8% to 6.5%. Similarly, for the Sigma tailings, microscopic analysis suggested a chlorite fraction of 22% and sulphides of 1%. Some allowance was therefore given during model calibration for choosing the model-input volume fractions, while maintaining the total solid fraction as determined from the sample porosity. The final mineralogical composition of each material in the numerical model was consistent with the observed data (Table 3). In the numerical model, the primary sulphide mineral in the Manitou mine tailings is assumed to be pyrite, with the overall oxidation reaction stoichiometry given by: FeS2ðsÞ þ 7=2O2 þ H2 O þ ! Fe2þ þ 2SO2 4 þ 2H

ð12Þ

Pyrite is assumed to be uniformly distributed within the Manitou tailings at an initial volume fraction (fv) of 6% (Vmineral/Vsolids). The initial (unoxidized) grain diameter for this unit is derived from the equivalent grain diameter (DH) of a uniform material which has the same surface area as the real heterogeneous mixture. The equivalent grain diameter is expressed as (Aubertin et al., 1998) DH ¼ ½1 þ 1:7  logðD60 =D10 Þ  D10 ;

ð13Þ

where D60 and D10 are, respectively, the 60% and 10% passing fractions on the grain size curve. Using the grain size data for the Manitou tailings (Aubertin et al., 1999), a DH value of 0.04 mm was obtained (Table 1). Trace amounts of sphalerite (fv = 0.2%) and chalcopyrite (fv = 0.4%) were also included in the simulated tailings as sources of Zn and Cu, respectively (see Table 3). Within the Manitou tailings, siderite, gibbsite and ferrihydrite were assumed initially not present but were allowed to precipitate as secondary minerals. The rate expressions and calibrated rate coefficients for each reaction are provided in Table 4. The 1D model columns are open at the top and bottom, and the sides are impermeable. A steady recharge of 360 mm a1 is applied at the top inflow boundary, which is applied for 8 months of each year (April–November). During the remaining 4 months (December–March), the cells are assumed frozen with no recharge. The recharge water chemistry is assigned a typical chemical composition of rainwater which has been equilibrated with atmospheric O2 and CO2 at 10 C (P O2 ¼ 0:21 atm; P CO2 ¼ 103:5 atm, see Table 5). The equilibrated recharge has a pH = 5.6 which is consistent with observed values for the Abitibi region, Que., Canada. At the base of each simulated column, the water pressure is fixed at 0.0 m, allowing free drainage.

Table 4 Mineral reaction rate expressions and kinetic rate coefficients used in the Base Case model of the five Manitou experimental cells Mineral

Rate expression

Dk (m2 s1)

k m;eff k 1 ðmol L1 pm s Þ

km k n2 1 ðmol1n Lwm s Þ

S k ðm2min L1 pm Þ

Rate update modelc

Pyrite Sphalerite Chalcopyrite Calcite Siderite Gibbsite Gypsum Ferrihydrite Jarosite K-feldspar Anorthite Albite Muscovite

Shrinking core da 0:5 Rd = S k k m k ½O2aq  d m R = S k k k ½O2aq 0:5 ½1  IAP=K R ¼ k m;eff k ½1  IAP=K R ¼ k m;eff k R ¼ k m;eff ½1  IAP=K k R ¼ k m;eff ½1  IAP=K k R ¼ k m;eff ½1  IAP=K k ½1  IAP=K R ¼ k m;eff k Rd = k m;eff ½1  IAP=K k þ 1:12 Rdb = S k k m k ½H  þ 1:12 ½H  Rdb = S k k m k db m þ 0:1 R = S k ðk k1 ½Hþ þ0:08 þ k m Þ k2 ½H 

2.4 · 1014 – – – – – – – – – – – –

– – – 1.0 · 106 1.0 · 108 1.0 · 108 1.0 · 108 1.0 · 108 1.0 · 108 5.0 · 1011 – – –

– 100 200 – – – – – – – 10 100 100

a

Chlorite Silica

Rd = k m;eff ½1  IAP=K k ½1  IAP=K Rd = k m;eff k

– –

1.0 · 1011 1.0 · 108

– 1.0 · 1010 1.0 · 1010 – – – – – – – 1.0 · 105.9 1.0 · 1011 kk1 = 1.0 · 1012.6 kk2 = 1.0 · 1013.5 – –

– –

0 0

a b c d

See Eq. (11) (this paper) as well as Molson et al. (2005), and Mayer et al. (2002); assuming D0w =2.4e  9 m2 s1. After Mayer et al. (2002, and references therein). Exponent n for volume fraction-dependent rate term (see Eq. (9)). Irreversible dissolution.

2/3 2/3 0 0 0 0 0 0 0 0 0 0

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24 Table 5 Recharge water composition for simulated test cells (after Molson et al., 2005, and consistent with Mayer et al., 2002, and Appelo and Postma, 1993) Component

Recharge water conc. (mol L1)

Ca Mg Na K Cl SO4 Fe(II) Fe(III) H4SiO4 Al Zn Cu [O2]aq pO2 pCO2 pH

2.0e  05 2.0e  05 7.0e  05 5.0e  06 1.0e  05 7.4e  05 2.2e  16 1.0e  08 1.0e  08 1.0e  10 1.0e  10 1.0e  10 10.5 mg L1 (10 C) 0.21 atm 103.5 atm 5.6

The simulated columns are assumed initially water saturated and O2-free. For the 8 unfrozen months of each year, the cell temperature is assumed uniform at 10 C. During the 4-month winter period, the experimental cells are assumed completely frozen, with no recharge, mass transport or geochemical reactions allowed to occur. The longitudinal dispersivity for each material was assumed to be 0.5 mm, which is consistent with the system scale (Gelhar et al., 1992). The assumed free diffusion coefficient for each aqueous component was 2.4 · 109 m2 s1 and for O2 and CO2 in air was 2.0 · 105 m2 s1 (Glinski and Stepniewski, 1985; as used by Mayer et al. (2002)). In addition to the base case calibration simulation for each of the five cells, two additional sensitivity scenarios are presented: the first addresses the impact of the water retention characteristics of the moisture-retaining layer of Cell 1 and the second tests the sensitivity of the oxidized rim diffusion coefficients (Dk) in the tailings of Cell 5. Additional base case (Cell 1) scenarios were also run including a simulation with different grain diameters (1/10th and 10 times the base case value), a CCBE 10 times more permeable to water, a higher background temperature of 20 C and a simulation with periodic (1-week) recharge/no-flow conditions across the top boundary. In all these cases, O2 diffusion to the reactive tailings layer was inhibited by the CCBE, thus they showed essentially the same geochemical response and are therefore not presented.

9

5. Experimental and numerical results The base case simulations for all cells were run for a 100-a period, beginning after cell emplacement on September 1, 1995. Execution times were typically on the order of 60–120 min on a Pentium IV, 2 GHz machine. Calibration was performed over the first 1200-day monitoring period by making small adjustments to the mineralogical composition (allowing for uncertainty in the mineralogical analyses; see Table 3), and by adjusting the reaction rates and mineral surface areas (Table 4). The flow system variables, including the hydraulic conductivity and van Genuchten (1980) parameters (obtained independently from lab tests), were not modified during calibration. The base case (calibrated) simulations are provided in Figs. 5 and 7–10 for Cells 1–5. In each case, the transient response is shown for water saturation, O2 concentration, pH and the selected aqueous component and sulphide mineral volume fractions (fv), focussing on the first 1200-day observation period. Fig. 11 compares the evolution of pH, SO4, Fe, Cu, Zn and Al in the CCBE-covered Cell 1 with that of the uncovered Cell 5 and with the observed data. 5.1. Cell 1 The transient results for Cell 1, with 0.6 m of low-sulphide tailings as the moisture-retention layer (between 1.9 and 2.5 m), are shown in Fig. 5. The water saturation profile shows that although water drains rapidly from the sand, the moisture-retention layer remains close to saturation (Sw  0.94). The steady-state saturation within the reactive Manitou tailings (0.30–0.43) is above that of the two sand layers (0.1), but remains significantly less than the saturation of the moisture-retention layer. Differences in water content between the sand units and the moisture-retention layer of Cell 1 are highlighted in Fig. 6, which shows the simulated and observed data during the last year of monitoring (1998). The simulated steady-state water content for the moisture-retention layer of the CCBE is a good match to the average observed values, although the simulated water content for the sand units was somewhat less than that observed, possibly due to an underestimated residual moisture content. The fit was not adjusted in order to keep all flow parameters independent. Furthermore, since the lower simulated water content would favour O2 diffusion, this would lead to a worst-case scenario

10

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

Cell 1: 0.6m Sigma low-S tailings water saturation 2.8

1d

oxygen

1h

10h

1d 10h 60d 60d 1200d 25y, 100y

2.4 Elevation (m)

oxidation dissolved aqueous sulphides products metals cpds.

pH

2.0 2d

FeS2 SO4 FeS2 0 100y

1.6 1.2 10d

ZnS 1h

0.8

CuFeS2

10h

0.4

Zn

2-

ZnS

2+

Al3+

2+

Fe

K

2+

Cu

+

2+

Ca

3+

Fe

2-

CO3

1200d

60d

0.0

0

0.5 Sw

1

calcite

Elevation (m)

2.8

siderite

gibbsite gypsum ferrihydrite jarosite

0d

0.8

0d

-3

0

1

2

10 10 10 mg/L

3

porosity 0d

0d

100y

25y

1200d

25y

25y 100y

100y

10

k-feldspar

anorthite

10

-2

fV

-6

1200d

1200d

25y

25y

0 -3 -2 -1 10 10 10 fV

0d

100y

1200d

1200d 25y

-4

-3

10 10 mg/L

0d 1200d

-4

10 10 10 fV

-2

-4

10 10 fV

-2

10

-4

10

13y -2

10

fV

-4

10

-2

fV

albite muscovite chlorite

0.3 0.4 θ

quartz

0d

0d

0d 0d

0d

2.4 Elevation (m)

3

1200d

0.4

2.8

0

10 10 10 mg/L

0d

1200d

1.6 1.2

4 8 pH

-2

0

0d

2.4 100y 2

-4

10 10 fV

0 0.2 [O2] (mg/L)

0d

2 1.6 100y 100y

100y

1.2

100y 100y

0.8

100y

0.4 0 -4 -2 10 10 fV

0

0.05 fV

0

0.1 fV

0

0.05 fV

0

0.05 fV

0

0.4 fV

Fig. 5. MIN3P simulated geochemical profiles for Cell 1 with a 0.6 m layer of Sigma low-sulphide tailings as the capillary barrier. Observed water saturation data for this and other cell profiles (square symbols) represent the 1998 average (see Fig. 6 in Bussie`re et al., 2007). Mineral volume fractions (fv) in Vsolid/Vbulk; results at 1200 days if not otherwise shown.

for assessing performance of the CCBE. The simulated water saturation results are consistent with those obtained by Joanes (1999), Bussie`re (1999) and Bussie`re et al. (2007) using the SEEP/W flow model (Geoslope Inc.). The O2 profile of Fig. 5 shows that within 1 day of the start of drainage of Cell 1, the O2 front has advanced about 0.3 m into the sand at the top surface, but as the front enters the nearly saturated moisture-retention layer, the diffusive flux is significantly reduced. After 1200 days, the front has only

advanced 0.6 m from the top surface. The high degree of saturation in the Sigma moisture-retention layer has thus significantly limited the flux of O2 into the cell. Pyrite and sphalerite oxidation within the Sigma layer is also consuming some of the O2. The result is that after 1200 days, the pH within the Manitou tailings remains neutral at about 6.8, there is no visible pyrite-oxidation front, and the volume fractions of sphalerite and chalcopyrite within the Manitou tailings have remained essentially unchanged.

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24 May

June

July

Aug.

Sept.

Oct.

11

Nov.

Volumetric Water Content (%)

60

C2-2

50 40 30

C2-1

20

C1-2

C3-1

10 0 0

30

60

90 120 Time (days)

150

180

210

Fig. 6. Simulated vs. observed water content in Cell 1 during the last year of monitoring (1998); observed data after Bussie`re et al., 2007). Monitors C2-1 and C2-2 were located in the moisture retaining layer, C1-2 in the lower sand, and C3-1 in the upper sand layer; horizontal dashed lines show corresponding simulated values.

The sulphide mineral profiles in Fig. 5 confirm that oxidation of pyrite, sphalerite and chalcopyrite within the Manitou tailings has been prevented by the CCBE. Although almost half the sphalerite within the Sigma cover layer has been oxidized by 1200 days, there is no visible oxidation front of any of the sulphide minerals within the Manitou layer, or of pyrite in either layer. Indeed, after 100 a, there is still no pyrite oxidation front, and only a trace of sphalerite and chalcopyrite oxidation within the Manitou tailings. After 1200 days, the concentrations of Fe2+ and SO2 4 within the reactive Manitou tailings layer of Cell 1 are, respectively, about 8 and 2000 mg/L (Fig. 5). Aqueous Fe is dominated by Fe3+ above the O2 diffusion front (0.6 m depth at 1200 days) and by Fe2+ below it. Peak sulphate and FeTOT concentrations are each about 2 orders of magnitude higher than background values in the upper sand. At 1200 days, the Fe2+ front coincides with the sphalerite oxidation front in the middle of the Sigma layer, while the SO2 4 front coincides with the gypsum dissolution front. Some limited pyrite oxidation at the top edge of the Sigma layer, and jarosite dissolution somewhat deeper, also contribute minor amounts of SO2 4 . The confirmed low oxidation rates in this CCBE covered cell have also kept the dissolved metal concentrations relatively low. Due to sphalerite dissolution, Zn2+ concentrations rise within the Sigma layer to about 10 mg/L, while Al3+ and Cu2+ concentrations remain around 3 10 mg L1. The Al3+ concentration decreases from the inflow concentration due to gibbsite

precipitation and concentrations remain low due to slow dissolution of the alumino-silicates in this neutral pH environment. Concentrations of K+ increase within the Sigma layer due to dissolution of jarosite and limited dissolution of K-feldspar and muscovite, while Ca2+ and CO2 3 concentrations increase primarily due to calcite and siderite dissolution, and limited anorthite dissolution. The solid mineral profiles are consistent with the aqueous profiles, showing precipitation of gibbsite and ferrihydrite (initially absent in the tailings) due to equilibration with Al and Fe, and dissolution of calcite, siderite, gypsum and jarosite. Because of the neutral pH within the covered tailings of Cell 1, the distribution of calcite at 1200 days has remained essentially unchanged from its initial volume fractions (see Table 3), while siderite has completely dissolved within the upper sand and throughout half of the Sigma moisture-retention layer of the CCBE. Siderite is undersaturated in this upper area of the cell where Fe2+ concentrations are very low, while ferrihydrite has precipitated in the siderite-depleted, O2-rich zone. Note that as gypsum dissolves at its leading (upgradient) front, some is re-precipitated as it migrates further down the column. After 100 a, all silicate profiles remain essentially unchanged from their initial profiles. However, the sum of all mineral volume changes induces a net mineral volume loss which results in a maximum porosity increase within the Sigma layer of about 5% (assuming a constant total volume), and virtually no change elsewhere.

12

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

The O2 diffusion profiles in Cell 2 are also similar to those of Cell 1, but since the natural till layer contained no pyrite or sphalerite, oxidation-induced consumption of O2 is eliminated which allows O2 to diffuse into this unit more rapidly than in Cell 1. A steady-state diffusion profile through the till is reached after only 60 days, compared to 1200 days in Cell 1. As in Cell 1, however, O2 is prevented from advancing significantly further due to the high water saturation of the till. Within the first 1200 days, there is again no significant oxidation front for pyrite, sphalerite or chalcopyrite. However, at later time, an oxidation front develops for the latter two minerals which advances about 0.1 m after 100 a. Because sphalerite, gypsum and jarosite are not present within the till layer of Cell 2, Zn2+ and SO2 concentrations have dropped, respectively, 4 compared to Cell 1. The correspondence in Cell 2 between the SO2 4 front and the gypsum dissolution front at 1200 days (1.0 m elev.), and the similar peak SO2 concentrations with those of Cell 1 4 (2000 mg L1), confirms that in both cells, most

5.2. Cell 2 Cell 2 had an identical geometry to that of Cell 1, but the moisture-retaining layer of the CCBE was constructed with a natural till which had a different mineralogical composition, lower saturated hydraulic conductivity and a finer mean grain size (see Tables 1 and 3 and Fig. 4). In particular, the natural till unit contained only silicate minerals, with no sulphides, carbonates, sulphates or hydroxides. The simulated geochemical behaviour of Cell 2 is shown in Fig. 7. The simulated water saturation profile of Cell 2 is virtually identical to that of Cell 1, although the match with the observed data is less convincing due to possible transient effects or material heterogeneities. However, a better fit was not attempted since the fit with the observed data from Cell 1 was good, and both the Sigma and natural till units had fairly similar physical properties. In addition, the generally lower predicted saturations in Cell 2 would tend to overestimate oxidation rates and would thus be conservative.

Cell 2: 0.6m Natural Till water saturation 2.8

1h

2d

Elevation (m)

1d

10h 60d

2-

SO4

10d 60d 1200d

2.0 2d

1.6

oxidation dissolved aqueous sulphides products metals cpds.

pH

10h

2d

2.4

100y ZnS

1.2 10d 1h

0.8

0.0

0

0.5 Sw

1200d

1

calcite 2.8

Al3+

FeS2 0 100y

Ca2+

2+

Cu Zn2+

Fe3+

CO23

2+

10h

0.4 60d

Elevation (m)

oxygen

Fe CuFeS2 -4

10 10 fV

0 0.2 [O2] (mg/L)

0

siderite

gibbsite gypsum ferrihydrite jarosite

0d

0d

4 8 pH

+

K -2

10-3 100 103 mg/L

0d

100y

25y

25y

0d

0.8

1200d

25y 100y

10 fV

-2

-6

-4

10 10 10 fV

-2

-4

10 10 fV

100d 300d

1200d 25y 100y

0.4 -4

0d 100y

1200d

10

porosity 0d

1200d

1.2

0 10-3 10-2 10-1 fV

101 102 103 mg/L

0d

2.4 100y 1200d 1200d 2 1.6 25y

10-3 100 mg/L

-2

10

-4

fV

10

-2

600d

10

-4

fV

10

-2

0.3 0.4 θ

Fig. 7. MIN3P numerical simulation showing vertical geochemical profiles for Cell 2: 0.6 m layer of Natural Till as the moisture-retaining layer of the capillary barrier. Mineral volume fractions (fv) in Vsolid/Vbulk; results at 1200 days if not otherwise shown.

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

of the SO2 originated from gypsum dissolution, 4 not from sulphide oxidation. Similarly, the correspondence between the Fe2+ front at 1200 days (1.9 m elev.) with the siderite dissolution front, and the absence of any other changes in Fe2+ (or SO2 4 Þ concentrations, confirms that there is no significant sulphide oxidation occurring within the Manitou reactive tailings layer. As in Cell 1, the simulated silicate profiles of Cell 2 remained essentially unchanged and are therefore not shown in this case.

13

barrier. Because of the limited O2 flux, sulphide oxidation in the Manitou reactive tailings and in the Sigma moisture-retaining layer is again inhibited and the pH profiles remain neutral. However, even this limited amount of O2 is sufficient to completely oxidize the sphalerite in the moisture-retaining layer within 1200 days (depletion is also rapid since the mass of sphalerite is lower in the thinner moistureretention layer). Thus, with sphalerite depleted from the moisture-retaining layer, and insignificant input from the O2-free Manitou tailings, Zn2+ concentrations within the profile are also less relative to Cell 1. The remaining geochemical profiles behave similarly to those in Cell 1.

5.3. Cell 3 The simulated profiles for Cell 3, with a thinner moisture-retention layer (Sigma material; 1/2 thickness of Cell 1), are shown in Fig. 8. The general behaviour of the water saturation profile is similar to that of Cell 1, but the extent of the high-saturation zone corresponding to the moisture-retention layer has now been reduced. Nevertheless, the O2 diffusion front remains highly attenuated, indicating that the CCBE is still functioning efficiently as an O2

5.4. Cell 4 The simulated profiles for Cell 4, with a thicker moisture-retention layer (0.9 m of Sigma low-sulphide tailings), are shown in Fig. 9. In this case, the zone of high water saturation is more extensive, corresponding to the thicker moisture-retention layer and the flux of O2 is again significantly

Cell 3: 0.3m Sigma low-S tailings water saturation 2.8

Elevation (m)

10h 1d 60d 60d 600d 1200d, 25y 10h

2.0 2d

1.6

FeS2 ZnS

100y

0.8

0.0

60d

0

1200d

0.5 Sw

1

calcite

0 0.10.20.3 0 [O2] (mg/L)

siderite

+

Al

Fe2+

0 100y

ZnS

1h 10h

SO24

FeS2

1.2 10d

0.4

oxidation dissolved aqueous sulphides products metals cpds.

pH

1h

1d

2.4

oxygen

Cu

Fe3+

Ca2+

2+

Zn2+

CuFeS2

10-4 10-2 fV

4 8 pH

K

3+

10-3 100 103 mg/L

10-3 100 mg/L

CO23

101 102 103 mg/L

gibbsite gypsum ferrihydrite jarosite

porosity

2.8 0d

Elevation (m)

2.4 2 100y

0d

0.8

1200d

25y 0d

100y

1200d

25y 100y

1200d

1200d 25y

0d

25y 1200d

25y

1200d 25y 100y

0.4 0 10-3 10-2 10-1 fV

0d

0d

0d

25y

1.6 1.2

0d

1200d

100y -6

10-4 fV

-4

10-2 10 10 10 fV

-2

-4

10 10 fV

-2

10

-4

fV

10

-2

10

-4

fV

10

-2

0.3 0.4 θ

Fig. 8. MIN3P numerical simulation showing vertical geochemical profiles for Cell 3: 0.3 m layer of Sigma low-sulphide tailings as the moisture-retaining layer of the capillary barrier. Mineral volume fractions (fv) in Vsolid/Vbulk; results at 1200 days if not otherwise shown.

14

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

Cell 4: 0.9m Sigma low-S tailings water saturation 1d

1h

2.8

oxygen 1d

Elevation (m)

FeS2

60d Zn ZnS

2d

1.6

100y

0.4 0.0

1h 10h

1200d

60d

0

0.5 Sw

1

calcite

0 0.1 0.2 0.3 0 [O2] (mg/L)

siderite

100y

1200d

2.4

Cu

Ca2+ 2-

-4

10 10 fV

4 8 pH

-2

10-3 100 103 mg/L

10-3 100 mg/L

101 102 103 mg/L

gibbsite gypsum ferrihydrite jarosite 0d

porosity

0d

0d

0d 1200d

1200d

13y

1200d

1200d

25y 25y

100y

1200d

1.2 25y

0d

25y 100y

0.4 100y -6

fV

100y

0d

13y

25y

10-4

0d

1200d

1200d

0.8

0 10-3 10-2 10-1 fV

2+

CO3

25y

2 1.6

3+

Fe

K+

CuFeS2

0d

0d

2.8

0 100y

ZnS

Al3+

Fe2+

FeS2

1.2 10d

2+

SO24

2.0

0.8

Elevation (m)

10h

10h

60d 600d 1200d

2.4

oxidation dissolved aqueous sulphides products metals cpds.

pH

-4

10-2 10 10 10 fV

-2

-4

10 10 fV

-2

10

-4

fV

10

-2

10

-4

fV

10

-2

0.3 0.4 θ

Fig. 9. MIN3P numerical simulation showing vertical geochemical profiles for Cell 4:0.9 m layer of Sigma low-sulphide tailings as the moisture-retaining layer of the capillary barrier. Mineral volume fractions (fv) in Vsolid/Vbulk; results at 1200 days if not otherwise shown.

restricted through the CCBE. In fact after 1200 days, the O2 diffusion front has not yet reached the base of the moisture-retention layer, as it had in Cells 1–3. With a low O2 flux, the pH again remains neutral and the geochemical behaviour of all major components remains similar to that of Cell 1. 5.5. Cell 5 Control Cell 5 had no CCBE and the reactive tailings were left exposed; the simulated results are provided in Fig. 10. The water saturation profiles show that the water saturation with the tailings decreases rapidly, reaching a steady-state profile by about 10 days during which time the saturations decline from the initial saturated state to about Sw = 0.3 at the top and Sw = 0.45 at the base. As the uncovered tailings drain and the water content decreases, O2 diffuses rapidly inwards from the tailings surface and begins to be consumed by oxidation of pyrite, sphalerite and chalcopyrite. Although the rate of advance of the O2 diffusion

front decreases in time due to O2 consumption and an increasing moisture content with depth, O2 continues to advance over time, suggesting that diffusion is rapid enough in this case to overcome depletion from sulphide mineral oxidation. After 60 days, the O2 diffusion front has reached the base of the tailings 1.5 m below the surface, and has essentially reached a steady-state distribution after 75 a. As the sulphide minerals in Cell 5 are oxidized, a low-pH zone develops which correlates with the O2 diffusion front. This low-pH water is carried downwards with the natural infiltration, and the low-pH zone is gradually enlarged, although its advance is somewhat retarded due to mineral buffering reactions. The low-pH front reaches a depth into the tailings of about 0.3 m after 60 days, and about 1.1 m after 200 days (Fig. 10). The lower pH plateau is also maintained by ferrihydrite precipitation but is buffered by aluminosilicate dissolution (primarily anorthite). Similar patterns of sequential mineral buffering with several intermediate plateaus have been observed and simu-

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

15

Cell 5: Uncovered Tailings water saturation

oxygen

pH

oxidation oxidation chalcopy. products products

pyrite sphalerite

2.8

FeS2

ZnS

SO24

CuFeS2

Fe3+

Elevation (m)

2.4 2.0 60d 600d

1.2 0.8 0.4 0.0

50y 0

100y

1.6

10h

10h

0

13y 75y

10h

0.5 Sw

1

2.8 Zn2+

oxidation products Cu

4 pH

25y -4

10 10 fV

8

-2

dissolved metals calcite

2+

Al

200d 1200d

13y

1200d

0

60d

50y

100y

50y

200d

0 0.2 [O2] (mg/L)

oxidation products

1200d

20y

1200d

1h

200d 1200d 25y

0d

25y

10d

60d

0d

1200d

60d

0d 1200d

-4

10 10 fV

-2

-4

-2

10 10 fV

gibbsite

gypsum

100 102 104 mg/L

100 102 104 mg/L

ferrihydrite porosity

3+

Elevation (m)

2.4 2.0

0d

1.6 1.2 0.8 0.4 0.0

0d

60d

60d

1200d

1200d

20y 25y

100 103 mg/L

100d

10d

50y 60d

100y 100d

200d 100d

13y

0d

1200d

1d

50y

10d

100y

25y 0

1200d 200d

10 100 103 10 mg/L mg/L

3

100y 1200d 100y

300d -6

-4

-4 -3 -2 10 10 10 10 10 10 fV fV

-2

50y

100d

200d

20y

1200d

10

-4

10 fV

-2

10

-4

fV

10

-2

0.4 0.5 θ

Fig. 10. MIN3P numerical simulation showing vertical geochemical profiles for Cell 5:uncovered control cell. Mineral volume fractions (fv) in Vsolid/Vbulk; results at 1200 days if not otherwise shown.

lated by Johnson et al. (2000), Jurjovec et al. (2002), and Bain et al. (2000). In the uncovered cell, the minimum simulated pH within the column dropped to about 2.8 which correlates well with the observed minimum in the discharge water (pH  2–3; see also next section showing drainage water chemistry). Differences in pH may be due to an incomplete background mineralogy assumed in the model, preferential flow paths through the exposed tailings, or variable climatic conditions and three-dimensional effects which are not considered in the model. As O2 diffuses into the uncovered tailings of Cell 5, pyrite, sphalerite and chalcopyrite become depleted throughout the 1.5 m of reactive tailings; the most extensive depletion occurs at shallow depths which have been exposed to higher O2 concentrations for longer times. Sharper sulphide oxidation fronts would be expected for cases in which the sulphide oxidation rate is significantly higher, and limited by the O2 diffusion rate. With the higher sulphide oxidation rates of Cell 3+ 5, peak concentrations of SO2 and Al3+ are 4 , Fe

all much higher than in the CCBE covered cells. The concentrations of these three components generally increase with depth in the tailings, reaching peak levels between 200 and 1200 days (see also discharge curves in Fig. 11), and decrease thereafter. Maximum concentrations reach about 1 20,000 mg[Fe3+] L1 and 110; 000 mg½SO2 4 L , 15,000 mg[Al3+] L1. These concentrations are, respectively, about 102, 103 and 106 times higher than in the CCBE covered Cell 1. Note that Al3+ originates solely from dissolution of aluminosilicates (in this case mostly from anorthite) since gibbsite is initially absent from the tailings. Within the low-pH environment of the Manitou reactive tailings in Cell 5, the initial calcite rapidly dissolves and is flushed from the tailings in 300– 400 days, while the tailings water remains undersaturated with respect to siderite (which was initially absent). Gibbsite (also initially absent) precipitates as discrete pulses at the leading edge of the highconcentration Al3+ front as shown in the profiles from 60 to 300 days. Gibbsite is depleted above these pulses because of the low pH, and below them

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24 (a) pH

8 6 4 2 0

pH

8 6 4 2 0

Cell 5

[SO4 ]

2

3

4

10 10 10 10

5

(b) [SO ]

Cell 1

(c) Fe (total)

10-2100 102 104

Fe (total)

Cu

-3

0

10 10 10

3

(d) Cu

(e) Zn

Zn

10-2 100 102 104

10-2 100 102 104

[Zn] mg/L

CCBE-covered Cell 1

uncovered Cell 5

[SO4] mg/L [FeTOT ] mg/L [Cu] mg/L 2 3 4 5 -2 0 2 4 10-3 100 103 10 10 10 10 10 10 10 10

pH

16

Al

103 10-3

[Al] mg/L

(f) Al

0

300 600 900 Time (days)

1200

0

25

50 75 Time (years)

100

Fig. 11. Evolution of discharge water over time for the CCBE-covered Cell 1 and uncovered Cell 5. The simulated results (lines) and observed data (symbols) show the evolution of (a) pH, (b) SO4, (c) Fe, (d) Cu, (e) Zn and (f) Al concentrations (observed data unavailable for Al). Left column time scale 0–1200 days, right column 0–100 a.

because of lower Al3+ concentrations. By the 50 and 100 a profiles, however, gibbsite has reappeared in the column following the recovery to more neutral pH conditions. Gypsum, initially present at a volume fraction fv = 0.0013 (Vmineral/Vbulk), increases throughout the column within the first 1200 days to fv = 0.026 due to elevated concentrations of SO2 from sul4 phide oxidation. As the sulphide minerals become depleted and the SO2 concentrations decrease, 4 and as Ca2+ concentrations decrease because of calcite dissolution and flushing, gypsum begins dissolving from the upgradient region and is re-precipitated downgradient. Thus while continuously dissolving from the inflow end, gypsum’s local volume fraction progressively increases with time. As in Cells 1–4, elevated concentrations of Fe3+ cause ferrihydrite precipitation. Anorthite (not shown) dissolves slowly due to the low pH and is completely

dissolved by 100 a. Muscovite, chlorite and silica remain relatively unchanged. 6. Discharge water chemistry and sulphide mineral oxidation rates 2+ and Zn2+ The simulated pH, SO2 4 , FeTOT, Cu concentrations in the water discharging from the base of Cell 1 and 5 are compared to the observed data in Fig. 11. The reader is reminded that identical initial conditions, boundary conditions and tailings mineralogy were used for both cells, the only difference being the absence of the CCBE in Cell 5. The simulated pH of the drainage water from the covered Cell 1 remained at relatively neutral levels of about 6.5–7 for the 1200 days monitoring period, which was in very good agreement with the observed data (Fig. 11a). The pH remains neutral because of the CCBE which limits sulphide oxida-

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

tion, and because of the presence of carbonate buffers. In the exposed Cell 5, the simulated pH of the effluent water follows two plateaus which are linked to the arrival of the O2 diffusion front and to pH buffering minerals, as explained above in reference to the vertical profiles. During the first 350 days, the pH remains at a neutral plateau of between 6.4 and 6.6, where the pH is buffered primarily by calcite dissolution. At about 360 days, the simulated pH of the effluent water drops rapidly to the second plateau of about 2.8, buffered by jarosite and aluminosilicate dissolution. The siderite and gibbsite buffer plateaus, as described in the conceptual models of Al et al. (2000), Jurjovec et al. (2002) and Blowes et al. (2003b), were either non-existent or rapidly passed due to the rapid decline in pH and a limited amounts of these minerals. The observed data did not show any evidence for intermediate pH plateaus. 2+ The simulated SO2 and Zn2+ con4 , FeTOT, Cu centrations in Cells 1 and 5 were also consistent with the observed data (Fig. 11b–e). In the CCBE-covered Cell 1, the simulated SO2 concentrations 4 showed a slight downward trend from about 2500 mg L1 at early time to about 1700 mg L1 after 1200 days, matching the observed data well (Fig. 11b). In the uncovered Cell 5, the predicted SO2 4 concentrations were initially stable, increasing moderately from about 2600 to 5000 mg L1 during the first 350 days, then increasing rapidly to about 110,000 mg L1 by 420 days. During the remaining 780 day period, the simulated SO2 4 concentrations showed a slight decreasing trend to about 75,000 mg L1, a level which correlates well with the observed data. The simulated dissolved Fe trends (Fig. 11c) were similar to those of SO2 4 . In the CCBE covered Cell 1, the simulated Fe concentrations, which were dominated by Fe2+, remained at about 8 mg L1 throughout the experiment, agreeing well with the observed data. In the uncovered Cell 5, the simulated Fe concentrations, dominated by Fe3+ in this more O2-rich environment, were about 0.04 mg L1 for the first 350 days, rapidly increasing to 16,000 mg L1 then declining slowly to about 7500 mg L1 after 1200 days, matching the observed concentrations. The rapid rise in Fe3+ at 350 days occurred at the same time as the rise in SO2 4 and the drop in pH. The simulated Cu2+ concentrations in the CCBE covered Cell 1 reached a plateau of about

17

0.001 mg L1 after 1200 days, which was about a factor of 10 less than the peak observed concentrations of 0.01 mg L1 (Fig. 11d). However, this difference is relatively minor when compared to the observed and simulated Cu2+ concentrations in the uncovered Cell 5 which reached a peak over 5 orders of magnitude higher, or about 1000 mg L1. The simulated Zn2+ concentrations in Cell 1 and Cell 5 after 1200 days, reached concentrations of about 10 and 1000 mg L1, respectively, which closely matched the observed data (Fig. 11e). Although observed data were unavailable for Al3+, the trend was similar to those of the other metals, with the difference in effluent concentrations between the CCBE-covered Cell 1 and the uncovered Cell 5 being on the order of 107 (Fig. 11f). In Cell 5, Al3+ originates from low-pH enhanced dissolution of the aluminosilicate minerals. The overall fit between the simulated and observed data is considered very good, considering the complex array of reactions and the inherent simplifications and assumptions in the modelling. The good agreement suggests the model assumptions are valid and provides confidence for using the model to make longer-term predictions of effluent characteristics for both the covered and uncovered tailings. The long-term (100 a) simulated results are shown alongside the 1200-day monitoring period results in Fig. 11. In the uncovered Cell 5, the 100-a simulation shows a pH recovery to neutral values after about 58 a, coinciding with a sudden drop in SO2 4 and Fe. This pH recovery is due to pyrite depletion and flushing of the cells by clean recharge water. As pyrite becomes depleted, the oxidation rate also declines due to the decreasing reactive surface areas of the unoxidized grain cores. Copper and Zn2+ concentrations in Cell 5 fall rapidly at about 20 and 30–35 a, respectively, coinciding with chalcopyrite and sphalerite depletion from the tailings. The concentration of Al3+ drops to background levels at about 58 a, also coinciding with the pH recovery. The effect of the CCBE on depletion rates of the sulphide minerals is more clearly illustrated in the sulphide mass plot of Fig. 12. In the CCBE-covered Cell 1, the proportions of pyrite, chalcopyrite and sphalerite remained essentially constant throughout the 100-a simulation time. In the uncovered Cell 5, however, pyrite is completely oxidized (>99.9%) by about 58 a, sphalerite within 30 a, and chalcopyrite within 20 a. These depletion times correspond to

18

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

7.1. Water retention function

Sulphide Mass

Mass (kg) 0 2 10 10

FeS2 CuFeS 2 ZnS

10

-2

Cell 1 Cell 5

0

25

50 75 Time (years)

100

Fig. 12. Mass plot showing the mass of sulphide minerals vs. time, for the CCBE-covered Cell 1 and the uncovered Cell 5.

bulk mineral oxidation rates of 4.9 kgPyrite m2 a1, 0.64 kgChalcopy. m2 a1 and 0.2 kgSphalerite m2 a1 for pyrite, chalcopyrite and sphalerite, respectively. These calculated rates are in agreement with the range of oxidation consumption rates measured in the cell (reported in Aubertin et al. (1999)), as obtained with the technique proposed by Elberling et al. (1993). On the other hand, the corresponding 100-a average oxidation rates for the CCBE-covered Cell 1 are 2–4 orders of magnitude less, being: 1.2 · 104 kgPyrite m2 a1, 7.7 · 103 kgChalcopy. 2 1 3 m a , and 3.8 · 10 kgSphalerite m2 a1. Thus, the observed and simulated discharge water chemistry as well as the calculated mineral oxidation rates clearly show that the CCBEs in Cells 1–4 were efficient at preventing significant oxidation of the sulphide minerals. After 1200 days, concentrations of the oxidation products SO2 and Fe3+ in the effluent were lower in the 4 CCBE-covered Cell 1 by factors of about 50· and 1000·, respectively, compared to the uncovered cell. In the case of Zn2+, Cu2+ and Al3+, the concentrations were 2, 5 and 7 orders of magnitude less, respectively. Differences between the observed and simulated results could be attributed to several factors including incongruent mineral dissolution (which is not considered in the MIN3P model), 3D effects in the field cell not accounted for in the 1D modelling approach, neglecting full transient recharge (e.g. daily or seasonal variations), material heterogeneity, and limitations in the mineralogical analysis on which the simulated mineralogy was based. 7. Sensitivity analysis In order to gain further insight into the hydrogeochemical behaviour of CCBE systems, and to address parameter uncertainty, several additional simulation scenarios were run using Cell 1 and Cell 5 as the base case models.

The base case Cell 1 simulation is here repeated using the same geometry and mineralogy, but with a modified water retention curve for the Sigma moisture retaining layer as shown in Fig. 4b (referred to as Cell 1b). The modification had the effect of reducing the water retention capacity of the moisture retaining layer. The comparison against the base case Cell 1 is shown in Fig. 13. The simulation with the modified water retention curve shows a reduced steady state water saturation within the Sigma unit to about 0.7 (Fig. 13), compared to 0.94 in the base case Cell 1 (Fig. 5), thus allowing more rapid O2 diffusion. The higher O2 concentrations have increased the oxidation rate of sphalerite and chalcopyrite, as shown by the sulphide mineral dissolution fronts which have advanced about 0.6 m into the tailings. Pyrite has not yet been significantly affected because of its lower intrinsic oxidation rate, and preferential O2 consumption by the other sulphide minerals. Like2+ wise, the dissolved SO2 and Cu2+ concentra4 , Zn tions have increased by factors of about 10, 103 and 106, respectively, while Fe2+ has been almost completely oxidized to Fe3+. Thus, the results show that such a reduced water retention capacity would significantly limit the effectiveness of the CCBE for preventing sulphide mineral oxidation. 7.2. Grain diffusion coefficient Dk In the base case simulation described above, all parameters were derived from independent laboratory or literature sources, with the exception of the mineral reaction rates (kk, see Table 4) and the O2 diffusion coefficient through the oxidized grain rims of the shrinking core model for pyrite oxidation (Dk; see Eq. (11)). While the reaction rates were based largely on previously published values, the diffusion coefficients were unknown and had to be calibrated. The model is used here to investigate the effect of uncertainty in Dk, i.e., to assess a possible range which would still yield a reasonable fit to the observed geochemical data. In the CCBE-covered Cell 1, the simulated AMD composition was not sensitive to variations in Dk since the sulphide oxidation rates were limited by the very low rate of O2 diffusion through the CCBE, and not through the mineral grains. The sensitivity of the model to a higher and lower Dk is therefore only shown for the uncovered Cell 5.

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

19

Cell 1 vs. Cell 1b: 0.6m Sigma low-S tailings water saturation oxygen 2.8

pH

FeS2

CuFeS2

oxidation products

ZnS

dissolved metals

Cell 1

Cell 1

2.4

Cell 1

Zn2+

Elevation (m)

Cell 1b

2.0

Cell 1b

Cell 1b

Cell 1

Cell 1

1.6 1.2

SO24 Fe3+

Cell 1b

Cell 1b

0.8

0.0

Cu2+

Fe2+

0.4 0

0.5 Sw

1

0 0 0.2 [O2] (mg/L)

4 8 pH

10-4 10-2 fV

10-4 10-2 fV

10-4 10-2 fV

10-3100103 mg/L

Zn2+ Cu2+

10-3100 103 mg/L

(a) pH

8 6 4 2 0

5 Dk

Dk /10

8 6 4 2 0

Dk

pH Dk /10 5 Dk

5

[SO4 ]

2

3

4

10 10 10 10

2

3

4

10 10 10 10

[SO4] mg/L

Dk /5

(b) [SO4 ]

5

pH

Fig. 13. Comparison of geochemical behaviour of Cell 1 (base case) vs. Cell 1b (with modified water retention curve – see Fig. 4). Results shown at 1200 days. Dashed lines show Cell 1b response.

Fe (total) 4

0

-2

0

2

10 10 10 10

4 -2

0

2

10 10 10 10

[FeTOT ] mg/L

(c) Fe (total)

300 600 900 Time (days)

1200

10

-1

0

1

10 10 Time (years)

10

2

Fig. 14. Sensitivity scenarios, uncovered Cell 5: simulated evolution of column effluent for pH, SO4 and total Fe (mostly Fe3+) showing effect on discharge of the diffusion coefficient within the oxidized rim of the shrinking core model. Values are relative to the base case Dk value of 2.4 · 1014 m2 s1. Left column 0–1200 days linear scale, right column 0.1–100 a, log scale. Observed data points also shown.

The simulation results for the sensitivity analysis on Dk are shown in Fig. 14. The base case value of D0k ¼ 2:4  1014 m2 s1 was used for comparison against three other cases: Dk ¼ 5  D0k ; D0k =5 and D0k =10 (note that the rates for sphalerite and chalcopyrite are not affected by Dk since the shrinking core model was not used for these minerals). The pH, SO2 4 and FeTOT profiles show that while early time observed data are scarce, the calibrated base case rate is a somewhat better overall fit, and is consistent with values used by Wunderly et al. (1996), Gerke et al. (1998) and Mayer et al. (2002). In the context of CCBEs, these simulation results show that the diffusion coefficient Dk (through the oxidized grain rims) would play an important role

only in cases where a cover may experience significant long-term desaturation. In covers which remain close to fully saturated, and hence where oxidation is limited by the bulk diffusion rate through the porous medium, the use of published Dk values for similar material would be justified. 8. Discussion This reactive modelling study has brought to light several issues which should be considered when interpreting the results, and to help improve future efforts in reactive transport modelling. One of the most critical issues is inherent uncertainty in the mineralogical analysis of the reactive tailings and

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J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

the cover material. Because of complexity in the existing mineralogy, as well as the many unknown secondary minerals which may appear at later times, various conceptual models and simulation results are possible. Uncertainty in the mineralogy can arise, for example, from sample heterogeneity as well as from limitations in the equipment (e.g., precision, especially for low fraction minerals, and differentiation of structurally similar but chemically distinct minerals). Furthermore, an XRD analysis of the sand was not available. Possible alteration of the tailings mineralogy before cell emplacement (e.g., some pre-oxidation) is another source of uncertainty. The presence of both calcite and jarosite in the XRD analysis of the Manitou tailings, for example, is difficult to explain and may be indicative of some localized pre-oxidation or heterogeneity. Because the observed mineralogy plays such an important role in development of the geochemical conceptual model, extra care must be made to ensure it accurately represents the field conditions. A second issue related to mineralogical uncertainty pertains to silicate weathering. In this study, silicate weathering rates were based primarily on published values, and may be non-unique. Also, anorthite is the primary source of dissolved Al3+ from the aluminosilicate minerals whereas muscovite and chlorite may also be important sources of Al3+ (and of Fe2+ and Mg2+ from chlorite). Without post-experiment mineralogical data, their relative contribution and true weathering rates cannot be verified. However, Al was not of primary concern in this study (and was therefore not measured in the effluent) and uncertainty in its origin would not be expected to have a significant effect on the general results. Differences between the observed and simulated data may also be due to simplifying the true climatic conditions experienced by the field cells. Although winter freezing was accounted for, surface temperature variations during the rest of the year, and temperature variations with depth within the columns, could have affected the equilibrium constants and reaction rates (including microbial activity) and transient recharge would have affected the water saturation and O2 diffusion rates. In order to simplify the system and to facilitate interpreting the geochemical reactions, the numerical simulations assumed a constant surface recharge (360 mm a-1) and temperature (10 C) for 8 months of each year, and were assumed frozen 4 months per year. Although the simulations did not account for

extended dry or wet periods, the uniform recharge rate was not considered a significant limitation since Bussie`re et al. (2007) showed that the moistureretention layer of the CCBEs remained near saturation even during relatively dry periods. The oxidation of the sulphide minerals in this study was assumed to be limited to the supply of O2. Under some conditions (e.g., low pH; see Bonnissel-Gissinger et al., 1998), sulphide oxidation can also proceed with Fe3+ as the electron acceptor according to the following reaction (e.g., Blowes et al., 2003b): FeS2ðsÞ þ 14Fe3þ þ 8H2 O þ ! 15Fe2þ þ 2SO2 4 þ 16H

ð14Þ

for which Fe3+ is supplied from the oxidation of Fe2+. However, this reaction is not always significant and in the test cell modelling presented here, it was not required to match the observed pH levels. Also, the supply of Fe3+ in Eq. (14), which is produced mostly by oxidation of Fe2+ by O2, can itself be limited by the availability of O2. Therefore, to keep the conceptual model as simple as possible, this reaction was not included and pyrite was assumed oxidized only through Eq. (12). Direct bacteriological-mediated reactions are also not considered, but are indirectly included through the effective reaction rates. Furthermore, the shrinking core model for pyrite oxidation assumes spherical grains and requires the diffusion coefficient through the oxidized mineral coating (Dk). To the authors’ knowledge, this diffusion coefficient has never been independently measured for mine tailings material, and must therefore be derived from calibration of a numerical model as in the case here. Thus, the approach is physically based, but relies on what is essentially a fitting parameter which introduces additional uncertainty. An independently measured Dk would significantly reduce this uncertainty (work is in progress in this regard). The suitability of the shrinking core model itself is also uncertain. In microscopic analyses of the Manitou tailings, for example, Aubertin et al. (1999) found evidence for individual pyrite grains with fractured surfaces which would likely not behave according to the conceptual spherical grain model. Another possible limitation of the modelling was the geometric simplification of the 3D field cells to the 1D numerical models. Neglecting dimensionality effects in the 1D models would be expected to underestimate the discharge rate from

J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

the base of the cells (because of flow focussing) and would underestimate event times such as the arrival times of the low-pH front and time to complete dissolution (because of somewhat longer travel distances for each flow line in the real 3D system). However, assuming that the increased water flow rate towards the bottom of the real 3D cells does not alter the intrinsic reaction rates, the 1D geometrical simplification should not have significantly altered the general geochemical behaviour. Note that a 1D model would be fully justified to simulate a spatially extensive and relatively flat cover anywhere except perhaps near the edges of an impoundment. 9. Conclusions The numerical simulations presented here have helped to illustrate how coupled hydro-geochemical modelling can be used to assess the response of covered and exposed reactive tailings with respect to the generation of acid mine drainage. The results specifically show the effect of covers with capillary barrier effects on reducing O2 diffusion and sulphide mineral oxidation within potentially acid-generating mine wastes. The model has proven to be a very useful tool to quantify the coupled and nonlinear effects of groundwater flow and moisture-retention on the reactive geochemistry responsible for acid mine drainage. In these 1D simulations, discharge from the capillary barrier covered cells was maintained at nearneutral pH, consistent with that observed. Without a CCBE cover, the pH in the effluent dropped to about 2.8 within the tailings effluent. In all simulated cover scenarios, concentrations of the primary oxidation products and dissolved metals were consistent with the observed effluent data, with concentrations reduced by the following factors with 3 respect to the uncovered cell: SO2 4 50, FeTOT 10 , 2+ 2 2+ 5 3+ 7 Zn 10 , Cu 10 and Al 10 . Oxidation rates in the CCBE covered Cell 1 were 1.2 · 104 kgPyrite m2 a1, 7.7 · 103 kgChalcopy. m2 a1 and 3.8 · 103 kgSphalerite m2 a1, which were 2–4 orders of magnitude less than in the uncovered control Cell 5. Variations in the thickness and non-sulphide mineralogy of the CCBE moisture-retention layer, as well as the grain size and diffusion coefficient within the oxidized grain shell had relatively less effect on the geochemical behaviour of the CCBE-covered cells. In these cases, the sulphide

21

oxidation rate was limited by the bulk, moisturecontent dependent diffusion rate of O2 through the column. This limited diffusion rate led to essentially identical reductions in AMD from the thinner 0.3 m CCBE cover of Cell 3 compared to AMD from the thicker 0.6 and 0.9 m covers of Cell 1 and 5. The simulations also suggest that a low fraction of sulphide minerals can be beneficial in a moisture-retaining layer (at least temporarily) by increasing the consumption of O2, allowing less to diffuse into the underlying more sulphide rich tailings. Provided the CCBE moisture-retention layer remains nearly saturated, the rate of O2 diffusion through the cover, and therefore the rate of sulphide oxidation in the tailings, will be significantly reduced relative to uncovered tailings. The primary limitations of the model as applied in this study include the effect of neglecting seasonal recharge variations, and the uncertainty in the background mineralogy. Carbonate mineralogy, for example, plays a major role in AMD evolution, particularly with respect to pH buffering reactions. More accurate reproduction of field trends will require more thorough and quantitative mineralogical analyses. Nevertheless, the good correlation between the simulated results and observed data are very encouraging (see Fig. 11), especially since most system parameters (including all flow parameters) were obtained independently. The use of the model for future prediction and design of CCBE systems can therefore be justified, if all assumptions are acknowledged. Acknowledgements The authors thank Dr. Uli Mayer of the Dept. of Earth and Ocean Sciences at the University of British Columbia for generously providing the MIN3P code and for his helpful advice and comments for improving the manuscript. Funding for this research was provided in part by ITEC Mineral Inc., the Quebec Ministry of Natural Resources, the Canada Centre for Mineral and Energy Technology (CANMET), and the Natural Sciences and Engineering Research Council of Canada through the Industrial NSERC Polytechnique-UQAT Chair in Environment and Mine Wastes Management. The Chair is supported by various industrial and government partners who are listed on the Chair website: http://www.envirogeremi.polymtl.ca/.

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J. Molson et al. / Applied Geochemistry 23 (2008) 1–24

Appendix A List of symbols De effective diffusion coefficient through the bulk porous medium (m2 s1) 0 0 Dw , Dg diffusion coefficients in the water and gas phases (m2 s1) Dk diffusion coefficient through oxidized grain rim (m2 s1) D60 grain diameter at 60% passing on grain size curve (m) D10 grain diameter at 10% passing on grain size curve (m) DH surface-area equivalent grain diameter for a heterogeneous mixture (m) h hydraulic head (m) K saturated hydraulic conductivity tensor (m s1) m;eff 1 kk effective rate coefficient ðmol L3 bulk s Þ m kk specific rate constant 1 (mol1n LnH2 O m2 mineral s ) krw relative permeability to water (dimensionless) Kz(sat) vertical saturated hydraulic conductivity (m s1) Kk equilibrium constant (dimensionless) Nc number of dissolved components Nm number of minerals qw Darcy flux in water phase (m s1) Qw reactive source/sink for water phase (s1) p ri initial particle radius (m) rri radius of unoxidized core (m) Rm reaction rate (mol L3 s1) k Sg volumetric gas phase saturation (m3 m3) Sw volumetric water saturation (m3 m3) Srw residual volumetric water saturation (m3 m3) Sew effective volumetric water saturation (m3 m3) reactive surface area (m2 L1) Sk SS specific storage (m1) t time (s) Tj total component concentration (kg m3 H2 O ) spatial coordinate i = x, y, z (m) xi Vm mineral molar volume (Lmin mol1) k Greek symbols / porosity (dimensionless) /p phase-filled porosity (dimensionless) av, mv, nv van Genuchten (1980) soil function parameters w water pressure head (m) uk mineral volume fraction (m3 m3) t stoichiometric coefficient for O2

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