Estimation of reactive mineral surface area during water–rock interaction using fluid chemical data

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Geochimica et Cosmochimica Acta 74 (2010) 6996–7007 www.elsevier.com/locate/gca

Estimation of reactive mineral surface area during water–rock interaction using fluid chemical data Alexandro Scislewski a, Pierpaolo Zuddas a,b,⇑ b

a Institut de Physique du Globe de Paris, 4 Place Jussieu, 75005 Paris Cedex 05, France Institut Ge´nie de l’Environnement Ecodeveloppement and De´partement Sciences de la Terre, UMR 5125, Universite´ Claude Bernard Lyon1, Campus de la Doua, 2, rue Dubois, F69622, Villeurbanne Cedex, France

Received 8 February 2010; accepted in revised form 7 September 2010; available online 17 September 2010

Abstract Mineral dissolution and precipitation reactions actively participate to control fluid chemistry during water–rock interaction. However, it is difficult to estimate and normalize bulk reaction rates if the mineral surface area effectively participating in the reactions is unknown. In this study, we evaluated the changing of the reactive mineral surface area during the interaction between CO2-rich fluids and albitite rock reacting under flow-through conditions. Our methodology, adopting an inverse modelling approach, is based on the measured chemical fluid composition as raw data. We estimated the rates of dissolution and the reactive surface areas of the different minerals by reconstructing the chemical evolution of the interacting fluids. This was done by a reaction process schema that was defined by a fractional degree of advance of the irreversible mass-transfer process and by attaining the continuum limit during the water–rock interaction. Calculations were carried out for albite, microcline, biotite and calcite assuming that the ion activity of dissolved silica and aluminium ions was limited by the equilibrium with quartz and kaolinite. We found that the absolute dissolution rate of albite, microcline, biotite and calcite remains essentially constant as a function of time, and the calcite dissolution rate is orders of magnitude higher than silicate minerals. On the contrary, the reactive surface area of the parent minerals varied by more than two orders of magnitude during the observed reaction time, especially for albite. We propose that the reactive surface area depends mainly on the stability of the secondary mineral coating that may passivate the effective reactive surface area of the parent minerals. Ó 2010 Elsevier Ltd. All rights reserved.

1. INTRODUCTION The quantification of the parameters controlling water– rock interaction is a prerequisite for understanding several fundamental and applied Earth processes. This is particularly important in understanding the transport and fate of pollutants in groundwater and surface water systems as well as the feedback mechanisms controlling carbon dioxide lev⇑ Corresponding author at: Institut Ge´nie de l’Environnement

Ecodeveloppement and De´partement Sciences de la Terre, UMR 5125, Universite´ Claude Bernard Lyon1, Campus de la Doua, 2, rue Dubois, F69622, Villeurbanne Cedex, France. Tel.: +33 472448202. E-mail address: [email protected] (P. Zuddas). 0016-7037/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.gca.2010.09.015

els in the atmosphere (Appelo and Postma, 2007; Brantley et al., 2008; Merkel and Planer-Friedrich, 2008). That is why, over the past 30 years, silicate and carbonate mineral dissolution rates have been thoroughly investigated through both laboratory experiments and studies on the watershed scale (White and Brantley, 1995; Brantley et al., 2008 and references in therein). The studies produced significantly different results, depending on whether the estimates were made under laboratory conditions or in the field. One of the reasons is that under controlled experimental conditions the surface area cannot be readily reconciled with the contact surface between minerals and the percolating waters in soils and rocks (Brantley et al., 2008). Moreover, the dissolution process is not homogeneous and the reactive surface area, i.e. the portion of the mineral surface area exposed to

Reactive mineral surface area during water–rock interaction

the aqueous solution and actively participating in the reaction, may be much lower than the total surface area (Helgeson et al., 1984). Given that fluid-mineral interactions occur primarily at selected sites of the available mineral surface area (White and Peterson, 1990; Gaus et al., 2005; Xu et al., 2005; Brantley et al., 2008 Gaus et al., 2008), many authors recognize that the reactive surface area in heterogeneous reactions involving simultaneous dissolution of several minerals is difficult to quantify (Hochella and Banfield, 1995; White and Brantley, 1995; Oelkers, 1996; Lichtner, 1996, 1998). The mineral surface area can be estimated, under experimental conditions, assuming particles have smooth and regular surfaces and a uniform geometry (Hodson, 2006; Brantley et al., 2008) or by the isotherm adsorption of inert gases like N2 or Ar (B.E.T method) (Brantley et al., 2008). Theoretically, an evaluation of the different energetic sites at the crystal surface, their densities and their distribution reactivity may allow an estimation of the reactive mineral surface area (Brantley et al., 2008). However, the estimation of the reactive surface area during water–rock interaction may be further complicated by the fact that precipitation of newly formed mineral phases may coat the dissolving mineral surface and modify the theoretical estimations (Xu et al., 2005, 2007; Gaus et al., 2008). Moreover, it is generally considered that the total available surface area is between one and three orders of magnitude larger than the actual reactive surface area (Gaus et al., 2005; Xu et al., 2007) with variations of several orders of magnitude during the overall reaction time (Brantley et al., 2008). However, because of the lack of a quantitative estimation, this parameter is often assumed to be a constant, especially at the watershed scale (Brantley et al., 2008). The aim of this study is to investigate the possibility of reconstructing the effective reactive surface area of the mineral participating in the dissolution process during water– rock interaction by the evolution of the water’s chemical composition. We carried out an original laboratory controlled experiment under flow-through dynamic conditions in which an albitite rock reacted with CO2 rich fluids. 2. EXPERIMENTAL METHODS The albite rock used in this study was obtained from a research watershed in Caetite´ (Bahia State, Brazil). The selected sample is composed of 70% albite and 30% mafic minerals. The paragenesis is made by orthoclase (originally perthitic) that is progressively replaced by intermediate and cross-hatched, twinned microcline (Sobrinho et al., 1980; Prates and Fuzikawa, 1982; Lobato et al., 1983; Oliveira et al., 1983; Maruejol, 1989). In our sample, albititic exsolutions are recrystallized into individual crystals of albite (An51) without the mixing of perthitic feldspar into the microcline and plagioclase. This results in polygonal granoblastic textures with K-feldspar between the quartz and albite grains. Quartz abundance does not exceed 10% of the mass. Accessory, mafic minerals and opaques are generally biotite, calcite, magnetite, titanite and uraninite. Calcite, often localized in plagioclase, results from the process of albitization (Sobrinho et al., 1980; Prates and

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Fuzikawa, 1982; Lobato et al., 1983) while biotite, generated from amphibole alteration, has variable Fe/Mg ratio (Maruejol, 1989). Muscovite is rare and is associated with biotite and potassic feldspar while magnetite, which originates from ilmenite destabilization and amphibole dehydration (Sobrinho et al., 1980; Prates and Fuzikawa, 1982; Lobato et al., 1983; Oliveira et al., 1983; Maruejol, 1989), appears in small grains and is <1% of the mass. The modal mineral composition of the selected albititerock, reconstructed after total chemical analysis by X-ray fluorescence and petrographical analysis observations, consists of albite (75%), microcline (10%), quartz (5%), biotite (5%), calcite (3%) and muscovite (<1%), and accessory minerals (garnet, epidote, magnetite, titanite, apatite) are less than 2% of the composition. Mineralogical and petrographic analyses were made by optical microscopie observations under polarized light in thin sections, and chemical composition mapping of the minerals was determined by a JEOL 8900 Scanning Electron Microscope (SEM). For the experiments, the rock sample was processed and sieved into 0.35–0.80 mm grain size fractions corresponding to the textural properties of the rock, and 444.4 grams were separated and introduced into the reactor. The reactor consisted of one glass column where the flow of the input solution proceeded from the bottom to the top of the column. A schematic representation of the experiment is shown in Fig. 1. The temperature of the experiment was kept constant at 22° ± 1 °C. The input solution consisted of deionized water saturated with a 5% CO2 – 95% air mixture which stabilized the pH close to 4.56. The input solution was introduced into the reactor by a micro pump that allowed a continuous mean flow of 10 ml/h. The total effluent volume that passed through the column ranged between 10 and 12 l. The effluent discharged from the top of the column was periodically sampled, filtered through 0.45 lm filter and stored in Falcon tubes in a refrigerator at the temperature of 1 °C. Samples for cation analysis were acidified with HNO3 suprapur (Merck) to a pH close to 2. The pH was measured before filtering using a METTLER TOLEDO MP125 pH meter and an Ingold combined glass electrode previously calibrated with NIST-traceable buffer solutions (pH 4.07; 7.00; 9.00 at 25 °C). Cations (Na+, K+, Ca2+, Mg2+, Altot) were analyzed by flame or flameless atomic absorption spectrometry (HitechiÒ 180–70 and GBCÒ 902). SiO2 was measured by automatic microcolorimetry, and anions (SO42, Cl) were measured by anionic chromatography using non-acidified samples. The carbonate alkalinity of the output solution was analyzed by titration with HCl using the GRAN (1952) method. 3. RESULTS 3.1. Chemical composition of the output fluids The evolution of the effluent solution composition is reported in Figs. 2–6. We found that the pH decreased from an initial value of 8 to a final value of 6.5. Since in our experiment the pH of the input fluids had a constant value of 4.56, the rock’s capacity to neutralize the fluid’s acidity is

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Fig. 1. Schematic representation of the flow-through experimental apparatus.

Fig. 2. Evolution of pH in the output fluids as a function of time.

Fig. 4. Evolution of sodium concentration in the output solution as a function of time.

Fig. 3. Evolution of alkalinity in the output fluids as a function of time.

Fig. 5. Evolution of the concentration of magnesium, potassium, and calcium in the output fluids as a function of time.

potentially active throughout the investigation. However, alkalinity decreasing as a function of time indicates a possible decline in the rock’s capacity to neutralize the acidity of the input fluid.

During the investigated time, sodium decreased by two orders of magnitude (Fig. 4) while potassium, calcium, magnesium and aluminium decreased by a factor of only 2–3 (Fig. 5). The total dissolved aluminium concentration

Reactive mineral surface area during water–rock interaction

Fig. 6. Evolution of kaolinite and quartz saturation index (SI) of the output fluids as a function of time.

was lower than 1 lmol/l during the time of the investigation, which is in agreement with the low solubility of this trace element in weakly acidic to neutral pH conditions (Appelo and Postma, 2007). Since albite is the main mineral composing the rock that also contains sodium, the dissolved sodium is primarily related to albite dissolution, while potassium will be in the following calculation assumed to be related to the dissolution of microcline. Calcium and magnesium will be associated with calcite and biotite dissolution, respectively. 3.2. Fluid equilibria thermodynamics The thermodynamic relationships needed to evaluate the irreversible water–rock mass that is transferred during water–rock interaction were initially described by Helgeson (1968). We estimated the output fluid’s saturation state by the geochemical code PHREEQCi (Parkhust and Appelo, 1999) using the wateq4f.dat thermodynamic database (Dzombak and Morel, 1990) under oxidizing conditions. We found that the output fluids were saturated with respect to quartz and kaolinite, and they were constantly undersaturated with respect to calcite (saturation index varying from 1.10 to 3.0) and the other main parent rock minerals (Fig. 6). We also estimated the pCO2 partial pressure at equilibrium with the output solution. In the first stage, we found that pCO2 decreased by two orders of magnitude compared to the pCO2 at equilibrium with the initial fluid. Later, pCO2 is less than one order of magnitude lower than the input fluid (Fig. 7). Our experimental investigation showed that, during the advance of the irreversible process and over only two months of interaction, the rock mineral’s capability to neutralize the acidity of the input fluids significantly decreased. 3.3. Neogenic phase formation SEM determinations carried out at the end of the reaction time revealed the presence of newly formed minerals coating the surface of the parent rock minerals. Fig. 8

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Fig. 7. Evolution of the calculated pCO2 partial pressure of the output fluids as a function of time.

shows the occurence of sheets of phyllosilicate-like minerals and iron hydroxides on the surface of albite, biotite and quartz. It appears that coatings may produce a thin layer over the surface of all minerals, or isolated grains with less than 1 lm of diameter and/or agglomerates with saccaroidal texture. The formation of secondary minerals, iron hydroxides and clay minerals with Al/Si ratio close to one, observed in our experiment is the result of the induced weathering reactions of silicate minerals. The relative frequency of iron hydroxides can be related to the dissolution of biotite and magnetite as observed in several field scale works on granitic rocks (van der Perk, 2006; Appelo and Postma, 2007; Brantley et al., 2008). The SEM observations confirm the results obtained from the saturation calculation and show the presence of other neogenic phase coatings on the parent mineral surfaces. 4. ESTIMATION OF THE REACTIVE SURFACE AREA 4.1. Calculating the irreversible mass transfer The evolution of the fluid composition found in the experimental interaction reflects the presence of several dissolution and precipitation reactions. In this section we propose an estimation of the mass transfer processes by introducing the fractional overall progress variable f. The system will be described by a series of mass balance equations for the relevant mineral phases in relation to their absolute reaction rates. As previously described by Sciuto and Ottonello (1995), Lasaga (1998) and Marini et al. (2000), the system can be defined by a matrix containing Ntot species and Nr reactions: I

dn ¼vR dt

ð1Þ

where I represents the identity matrix (dimensions Ntot  Ntot), n refers to the vector of solute concentration (length Ntot), v is the stoichiometric reaction matrix (dimensions Ntot  Nr), t stands for time and R is the reaction rate vector (length Nr) representing the variation of element concentration as a function of time.

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Fig. 8. Images obtained by scanning electron microscopy (SEM) showing the occurence of sheets of phylosilicate-like minerals and iron hydroxides on the surface of (a) albite, (b) biotite and (c) quartz.

If all reactions are described with kinetic rate laws, the equation system can be theoretically solved in a time-mode by substituting rate laws in the reaction vector R. However, in the time-mode, the obligation to assign a surface area to each solid mineral reactant significantly hinders its practical resolution. In effect, for every single-mineral kinetic rate law, we may write: Ri ¼ S i Ri

ð2Þ

 i is the absolute mineral dissolution rate per unit of where R reactive surface area (usually in mol m2 s1) and Si is the reactive surface area (m2) of the ith mineral phase. The dissolved species are related to a set of homogeneous and heterogeneous reactions that, in our case, are: Ca+, Mg2+, Na+, K+, H+, SiO2(aq), Al3+ (or Al(OH)4), H2CO3, HCO3, CO32 and H+ (Table 1). Since in our

experimental conditions the output fluids are always close to saturation with respect to quartz and kaolinite, silica and aluminium concentrations can be assumed to be controlled by the two respective equilibria. We assume that muscovite does not significantly participate in the evolution of the fluid composition, as it occurs in very small amounts (<1% in the rock) and is located inside biotite crystals. We therefore can conclude that only Ca+, Mg2+, Na+, K+, HCO3 and H+ participate in mineral dissolution reactions. For every relative mineral involved in the ith reaction, the dissolution reaction rate, ri, representing the amount of matter released as a function of the degree of advancement of the reaction, can be expressed as a function of the fractional overall progress variable (f) as: dNaþ ¼ r1 ; df

ð3aÞ

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Table 1 Equations of the chemical reactions assumed in the modelling.

Albite NaAlSi3 O8 þ 4Hþ $ Naþ þ Al3þ þ 3SiO2ðaqÞ þ 2H2 O

ð1Þ

Microcline KAlSi3 O8 þ 4Hþ $ Kþ þ Al3þ þ 3SiO2ðaqÞ þ 2H2 O

ð2Þ

Calcite CaCO3 $ Ca

2þ

þ

CO2 3

ð3Þ þ

þ

Biotite KðMg; FeÞ3 ðAlSi3 O10 ÞðOHÞ2 þ 10H $ K þ 3Mg

2þ

þ Al

3þ

þ 3SiO2ðaqÞ þ

6H2 O Quartz SiO2 $ SiO2ðaqÞ

ð5Þ þ

Kaolinite Al2 Si2 O5 ðOHÞ4 þ 6H $ 2Al þ

þ

3þþ

þ 2SiO2ðaqÞ þ 5H2 O

ð6Þ

3þ

ð7Þ

Anorthite CaAl2 Si2 O8 þ 8H $ Ca þ 2Al þ

þ 2SiO2ðaqÞ þ 4H2 O

þ

Muscovite KAl3 Si3 O10 ðOHÞ2 þ 10H $ K þ 3Al 2 þ HCO 3 $ H þ CO3

H2 CO03

þ

ð4Þ

3þ

þ 3SiO2ðaqÞ þ 6H2 O

ð8Þ ð9Þ

HCO 3 

$H þ H2 O $ Hþ þ OH

ð10Þ ð11Þ

H2 O þ CO2ðgÞ $ H2 CO03

ð12Þ

dKþ ¼ r2 ; df

ð3bÞ

dCa2þ ¼ r3 ; df

ð3cÞ

dMgþ2 ¼ r4 ; ð3dÞ df The fluid’s composition trend ni,j (molality) has been reconstructed as a function of the fractional overall progress variable (f) through a sequence of discrete points representing the reversible and irreversible mass exchanges of the jth aqueous specie in the ith reaction (Prigogine, 1967; Sciuto and Ottonello, 1995; Marini et al., 2000):  Z f¼1  @nj;i nj;n  nj;n1 ¼ df ð4Þ ri @fi f¼0 where : 0 6 f 6 1

ð4aÞ

Eq. (4a) results from the estimation of f obtained introducing the non-fractional overall variable e (by the relationship en = nNa+ + nK+ + nCa2+ + nMg+2). For each fluid sample f is obtained by dividing en by the eend (e for the last fluid sample), for which f is equal to 1. Stemming from the relationship between pH and f, the activity, molality and time trends for each of the solutes are derived by fitting analytical data (Table 2) in the fractional reaction progress mode. The non-component species (e.g. Si, Al) are also described because their values operate within the activity terms of dissolution rates and within the estimation of the ion activity product terms for the various hydrolysis reactions. The vector of solute concentrations is then obtained by the partial derivatives in df of the equations in Table 2. Fig. 9 shows that the calculated fluid composition trend is in agreement with the measured chemical composition of the fluid. Correlation analysis, ranging between 0.9 and 0.7 for Na and Mg, respec-

tively, indicates that the composition reconstruction is in agreement with the direct chemical composition measurements and shows the robustness of our model calculation. 4.2. Determining the reactive surface area of the mineral Mineral dissolution and precipitation rates have generally been described as a function of thermodynamic affinity (Aagaard and Helgeson, 1982; Ottonello, 1997; Lasaga, 1998). In a rock, where several reactions of mineral dissolution/precipitation occur concomitantly, the single mineral  i , can be expressed by (Denbigh, absolute dissolution rate, R 1971; Aagaard and Helgeson, 1982; Marini et al., 2000; Appelo and Postma, 2007; Brantley et al., 2008):    Ai ð5Þ Rl ¼ k i 1  exp gRT where, ki is the mineral dissolution rate constant in the ith reaction, g is the Temkin’s average stoichiometric number of the ith reaction, R is the perfect gas constant, T is the absolute temperature and Ai is the thermodynamic affinity of the ith reaction usually defined as (Prigogine, 1967):   Q Ai ¼ RTln i ð6Þ Ki where, Qi is the ion activity product and Ki is the solubility constant. Since mineral dissolution rates are pH-dependent, the silicate rate constants (ki) can be estimated using the empirical single mineral rate constant (kemp,i) and the semi-logarithmic pH function of Marini et al. (2000):   ð7Þ log k i ¼ log k emp;i þ bemp pH i  pH emp where, kemp,i values (Table 3a) of the minerals were obtained at the every empirical fixed pH (pHemp,). pHi is the logarithmic proton activity of the outlet solution at a given

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A. Scislewski, P. Zuddas / Geochimica et Cosmochimica Acta 74 (2010) 6996–7007 Table 2 Polynomial expressions relating the thermodynamic activity of solutes, ai, and molality, ni, to the fractional overall progress variable of the process, f. Time = 73488493.6676 f4 + 162204841.6662 f3  117917543.5184 f2 + 36719524.0066 f  3246353.6043 log nCa = 4.5143 f4  7.7076 f3 + 2.0949 f2 + 1.3406 f  4.4458 log aCa = 3.3345 f3  7.2488 f2 + 4.5009 f  4.8413 log nMg = 12.048 f4  30.1807 f3 + 25.4235 f2  8.2458 f  2.9685 log aMg = 0.81077 f3 + 0.69452 f2  0.0021604 f  3.8649 log nNa = 19.1081 f4 + 47.3955 f3  35.9111 f2 + 5.5319 f  3.1034 log aNa = 19.2591 f4 + 47.7783 f3  36.2516 f2 + 5.6631 f  3.1376 log nK = 5.4793 f4  11.1246 f3 + 6.3803 f2  0.87083 f  4.3225 log aK = 5.3244 f4  10.7319 f3 + 6.0307 f2  0.73609 f  4.3574 log nAl = 1.9199e  015 f  8 log aAl = 1.2029 f4 + 3.0452 f3  2.7042 f2 + 1.0419 f  8.2821 log nHCO3 = 4.7734 f4  12.6166 f3 + 11.9308 f2  5.3357 f  2.2112 log aHCO3 = 4.6225 f4  12.2339 f3 + 11.5902 f2  5.2044 f  2.2455 log nH = 17.1103 f4 + 33.5567 f3  21.2513 f2 + 6.8087 f  8.514 log aH = 8.0638 f3 + 13.6806 f2  4.7245 f  7.3925

Fig. 9. Relationship between calculated and measured fluid composition.

time, and bemp is the slope of the linear function between the log kemp,i and pHemp. The rate constants for the reaction of calcite dissolution were estimated by the Chou et al. study (1989) and are reported in Table 3b.

Since the thermodynamic activity of solutes is described as a polynomial in f (Table 2), the values of Qi, chemical affinities (Ai) and activity terms can be computed at each discrete value of f. The corresponding mineral absolute

Reactive mineral surface area during water–rock interaction Table 3 Kinetic parameters used in the modelling, where log k0+,i is in mol cm2 s1. Table (a) from Nagy et al. (1995) and Marini et al. (2000); Table (b) from Chou et al. (1989). Phase

Component

log k0+,i

bi

pH0

(a) Plagioclase K-feldspar Biotitea

NaAlSi3O8 KAlSi3O8 K(Mg,Fe)3(AlSi3O10)(OH)2

16.75 17.00 17.00

0.3 0.3 0.3

6.0 6.0 6.0

Phase

Component k1

(b) Calciteb CaCO3

k2

k3

tion under natural conditions (Zhu, 2005) these dissolution rates are between three and five orders of magnitude higher. The water–rock system can now be described in the reaction progress mode using the advancement degree functions. Thus, Eq. (1) can then be rewritten as: I

dn ¼ v Rf df

Rf;i ¼ S i Rl

a

The respective values were defined for muscovite, but according to Nagy (1995), the biotite pH dependence is similar to that observed for muscovite. b Reaction rate of calcite.

reaction rate per unit of surface area was obtained for every value of f using Eqs. (5), (6) and (7). A routine procedure, based on the experimental flow-through data (temperature, pH, solute concentration), was developed to estimate the mineral absolute reaction rate. The procedure takes into account charge balance error, ionic strength, activity and activity coefficients, Debye–Huckel variables and the polynomial data fittings describing the relationship between the components and the variable f. We found that the absolute dissolution rates of albite, microcline, biotite and calcite remained constant throughout the investigation at pH 6–7.5 (Fig. 10). As expected, we also found that the calcite dissolution rate is two and six orders of magnitude higher than biotite and feldspar, respectively. Our dissolution rate estimations are in agreement with several results of single-mineral dissolution experiments reported in the literature for pH 4–8 (Busenberg and Clemency, 1976; Chou and Wollast, 1984; Knauss and Wolery, 1986; Schweda, 1989; Acker and Bricker, 1992; White and Brantley, 1995) and with the isotopic rate estimation of Seimbille et al. (1998), which validates our model calculation. However, when compared to the rate estima-

Fig. 10. Evolution of the absolute dissolution rates of albite, microcline, biotite and calcite as a function of time.

ð8Þ

where Rf is the transposed reaction rate vector:

k4

8.9  105 5.0  108 6.5  1011 1.9  102

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dt df

ð9Þ

 i is the absolute reaction rate previously estimated where R and Si is the reactive surface area of the ith mineral. Introducing absolute reaction rates for each discrete value of f, the reactive surface area can be now estimated for every dissolving mineral phase. The results reported in Table 4 and Figs. 11–14 show that the reactive surface area changes by more than three orders of magnitude, especially for the albite dissolution reaction. We found that the evolution of the reactive surface area is not monotonous and that albite, microcline and calcite have a silimar trend. Three main temporal stages correspond to the first 12 h of reaction time, 12 and 47 h of reaction time and beyond 47 h of reaction time. In the first stage, the reactive surface area of albite, microcline and calcite increases by more than one order of magnitude indicating the prevalency of the dissolution reaction. The increase of the reactive surface area in the first stage found in our study can be explained by a possible formation of an etch pit at the mineral surface. Previous studies (Hodson, 2006; Appelo and Postma, 2007; Brantley et al., 2008) showed that the formation of surface etch pits may be responsible for increasing the geometric mineral surface because dissolution reactions are controlled by surface mechanisms (Lasaga and Blum, 1986; Lasaga and Lu¨ttge, 2001; Lu¨ttge, 2005). Our results indicate that the predominancy of the dissolution reaction is potentially able to increase the surface area of the minerals. In the second stage, the reactive surface area decreases by more than three orders of magnitude for albite and by one to two orders of magnitude for microcline and calcite. At this stage of the interaction, solutions are oversaturated with respect to kaolinite and quartz and new minerals may precipitate. Actually, phyllosilicate-like minerals and/or amourphous silica and iron hydroxides coating the mineral surface are potentially responsible for the observed decrease of the reactive surface area as they may reduce the contact area between the parent mineral surfaces and the fluids (Nugent et al., 1998; Xu et al., 2005; Xu et al., 2007; Gaus et al., 2008). In the third stage of the interaction, the reactive surface area increases again, especially with respect to albite dissolution. This enhancement occurs when the pH of the output solution decreases. We suspect that an eventual dissolution of an earlier precipitated coating is unstable in the more acidic conditions and that this may explain the later enhancement of the reactive surface area of the parent minerals. The reactive surface area of biotite does not change monotonously as a function of time as did feldspars and calcite; it displays an oscillating trend. In biotite and other

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Table 4  i , mol m2 s1) of dissolution–precipitation computed at various Surface areas of the mineral phases (Si, m2 per 1 kgw), absolute rates (R values of the fractional overall degree of advancement of the process (f) during the albitite–water interaction. f

Time (days)

RAlb

RKfeld

Rcal

RBiot

SAlb

SKfeld

SCal

SBiot

0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95

1.37 6.49 9.39 10.89 11.72 12.44 13.50 15.24 17.84 21.38 25.79 30.90 36.37 41.78 46.55 50.00 51.28

6.25E-13 6.40E-13 6.36E-13 6.15E-13 5.82E-13 5.41E-13 4.96E-13 4.50E-13 4.06E-13 3.66E-13 3.31E-13 3.02E-13 2.78E-13 2.60E-13 2.48E-13 2.42E-13 2.42E-13

3.52E-13 3.60E-13 3.58E-13 3.46E-13 3.27E-13 3.04E-13 2.79E-13 2.53E-13 2.28E-13 2.06E-13 1.86E-13 1.70E-13 1.56E-13 1.46E-13 1.40E-13 1.36E-13 1.36E-13

6.23E-07 6.44E-07 6.56E-07 6.65E-07 6.74E-07 6.85E-07 6.99E-07 7.18E-07 7.45E-07 7.82E-07 8.33E-07 9.02E-07 9.91E-07 1.09E-06 1.18E-06 1.22E-06 1.17E-06

9.91E-09 1.01E-08 1.01E-08 9.75E-09 9.22E-09 8.57E-09 7.85E-09 7.13E-09 6.44E-09 5.80E-09 5.25E-09 4.78E-09 4.41E-09 4.13E-09 3.93E-09 3.83E-09 3.83E-09

4.39E+02 1.23E+03 2.01E+03 2.76E+03 3.15E+03 2.09E+03 7.95E+02 2.76E+02 1.06E+02 4.59E+01 2.20E+01 1.11E+01 5.38E+00 1.82E+00 8.61E-01 3.32E+00 6.84E+00

4.89E+00 1.52E+01 3.53E+01 7.62E+01 1.38E+02 1.34E+02 5.60E+01 1.67E+00 2.70E+01 4.30E+01 5.22E+01 5.72E+01 5.92E+01 5.94E+01 5.87E+01 5.90E+01 7.18E+01

2.18E-05 3.86E-05 7.09E-05 1.31E-04 2.09E-04 1.79E-04 6.74E-05 6.14E-06 1.73E-05 2.46E-05 2.49E-05 2.24E-05 1.89E-05 1.57E-05 1.34E-05 1.24E-05 1.50E-05

1.18E-02 8.07E-03 5.57E-03 1.46E-03 8.70E-03 1.96E-02 1.76E-02 1.16E-02 6.66E-03 2.63E-03 7.50E-04 3.58E-03 5.84E-03 7.56E-03 8.92E-03 1.06E-02 1.79E-02

Fig. 11. Evolution of the reactive surface area of albite as a function of time.

Fig. 13. Evolution of the reactive surface area of biotite as a function of time.

Fig. 12. Evolution of the reactive surface area of microcline as a function of time.

Fig. 14. Evolution of the reactive surface area of calcite as a function of time.

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mica-like minerals, the edges are considered to dissolve faster than basal (0 0 1) surfaces (Hodson, 2006) and determine the evolution of the reactive surface area. Because of rock history and genesis, biotite has a variable Fe/Mg ratio with a potentially heterogenous behavior during the dissolution process. Dissolved iron coming from biotite and/or magnetite dissolution may precipitate as easily formed iron hydroxide coatings under our experimental pH conditions. This process might reduce the reactive surface area of biotite (Turpault and Trotignon, 1994; Malmstro¨m and Banwart, 1997; Murakami et al., 2003). We suspect that coatings of iron hydroxide may form rapidly because of magnetite rapid alteration (Faivre et al., 2004). The change in biotite reactive surface area in the later stages of the interactions is reminiscent of that observed for albite, microcline and calcite. The results of our experimental study show that a mineral’s reactive surface area changes significantly during dissolution and that this kinetic parameter is a variable and not a constant of the water–rock interaction as is often assumed in predictive modelling. In our experiments, the reactive surface area of albite presented the greatest variations. These variations can be related to highly abundant and homogeneous grain size distribution within the rock. In this study we propose a quantification of this kinetic parameter in a system where several minerals dissolve simultaneously and new solids are generated as is found in natural situations (Appelo and Postma, 2007; Merkel and Planer-Friedrich, 2008). Comparing the results of our study to the theoretical surface reactive sites estimated by mineral structural properties (Parks, 1990; Kulik, 2009), we found that the reactive surface area of the minerals can be two orders of magnitude lower because of an early coating formation. Coating abundance and distribution can be even larger in natural systems (Nugent et al., 2001), and reactive mineral surface area may be also lower. The results of this study show that with the advancement of the overall process, a mineral’s ability to neutralize a fluid’s acidity decreases, resulting in a lower system ability to neutralize the dissolved CO2. The initial dissolution of parent minerals and the precipitation of phyllosicate-like minerals and iron hydroxides controls the proportion of the effective reactive surface area available to participate to the CO2-rich fluid mineralization.

the mineral surface area considered to be involved in masstransfer phenomena. When applying this theoretical framework to natural situations, we may take into account that minerals constituting the rock may be mixtures of various end-members and not pure phases. This is partially the case in our experimental conditions as orthoclase (original perthitic) is partially replaced by intermediate and cross-hatched, twinned microcline and plagioclase is not pure albite. The activity term must be thus introduced into the reaction quotient Qi of Eq. (6) to derive the new chemical affinity. Since the newly calculated surface area is the surface of a mixture (valid for all components in the mixture), the variance of the system does not change but compositional constraints related the reaction kinetics of the phases must be introduced. Based on the existing experimental data on single-mineral dissolution experiments (Holdren and Berner, 1979; Fleer, 1982; Chou and Wollast, 1984; Knauss and Wolery, 1986; Sverdrup, 1990; Marini et al., 2000), we assumed that the parametric constant, log, ki, of plagioclase and alkali feldspar (Eq. (7)) varies linearly with the mineral chemistry. This compositional effect on the reaction kinetics of the solid exerts profound theoretical effects on the computed surface areas. If in our experiment the albite molar fraction in plagioclase is 0.95, the progressive of the surface area of K-feldspar obtained through inverse modelling as an albitization process is affected. The significance of the surface area obtained by the computing model proposed in this study should be regarded as a general trend when applied to real geological situations. The actual mineral modal composition of the rock, its grain size and hydraulic properties must be take into account to compare laboratory estimations to field evaluations of the reactive surface area. When comparing a computed surface area to estimates based on intergranular porosity and modal mineralogy in natural situations, fracture-driven fluid flow is another key parameter. Further kinetic models quantifying water– rock interactions and the chemistry of CO2 rich fluids may take into account the dissolution reaction kinetics of parent minerals, the effect of precipitation and redissolution of newly formed minerals coating mineral surface as well as an evaluation of the fracture systems that short circuit fluid flow.

4.3. Geological implications

In this work, an inverse modelling approach based on the measured chemical fluid composition allowed an estimation of the reactive mineral surface area during albitite CO2-fluid interaction. We found that the reactive surface area of the rock’s parent minerals is not constant during time but rather changes by several orders of magnitude during only two months of interaction. Under our experimental flow-through conditions, the albite reactive surface area changed by 3–4 orders of magnitude while microcline, calcite and biotite changed by 1–2 orders of magnitude. The variation of the reactive surface area of the mineral was found not to be monotonous. We propose that parent mineral chemical heterogeneity, and particularly neogenic phase formation, may explain the observed variation of the reactive surface area of the minerals. The formation

The rates of dissolution of silicate and carbonate minerals, investigated over the last 20 years both by means of laboratory experiments and on the watershed scale, have major discrepancies because the surface area under the controlled experimental conditions in the laboratory cannot be readily reconciled with the contact surface between the minerals and the percolating waters in rocks and soils. In addition, the dissolution process is not homogeneous and the effective surface area, which represents the area of the active sites exposed to the aqueous solution, may be different from the total surface area. The inverse modelling proposed in this experimental work, using the chemical data from a series of time related solution samples, allows an estimation of

5. CONCLUSION

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of coatings at the dissolving mineral surfaces significantly reduced the amount of surface area available to react with CO2-rich fluids. This work has implications on the ability of a rock to neutralize CO2 acidic fluids. At the initial stage of the interaction, when parent minerals dissolve abundantly, CO2 can be easily captured in the form of bicarbonate ions, but when coatings form at the mineral surface, the rock’s capacity to neutralize the acidity of the fluid decreases significantly. Predictive modelling of CO2 sequestration under geological conditions should take into account the inhibiting role of surface coating formation. ACKNOWLEDGMENTS This work was partially financed by the GRASP (Greenhousegas Removal Apprenticeship and Student Program) European network (contract MRTN-CT-2006-036868). We also thank the three anonymous reviewers and Dr. C. Daughney (associate editor) for their important contributions that significantly improved the quality of the manuscript as well as Robin Silver for her assistance in English-language editing.

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