Speciation in the iron(II)-iron(III)-sulfate-water system at 25.degree.C

iron-sulfate waters. Model Development. The equilibrium speciation model uses known solution composition as input into mass balance equations and mass...
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Environ. Sci. Technol. 1990, 24, 699-706

Speciation in the Fe(I1)-Fe(II1)-SO,-H,O System at 25 Sensitivity of an Equilibrium Model to Uncertainties

O C

and Low pH:

Susan L. Stipp" Department of Earth Sciences, University of Waterloo, Ontario, Canada N2L-3Gl

This work demonstrates a method for verifying a specific set of equilibrium constants that are intended for inclusion into a large geochemical model. A series of solutions with known concentrations of Fe(II), Fe(III), and SO4 were prepared to simulate the chemical composition and pH range commonly encountered in acid mine waters: I(Fe)T I I(SO,), I10-1 m, 1 z pH 5 4 , and m, ionic strength KSO; + K" + 50:Fe(OH)zt + Fe3+ + OHFe(OH)2t = Fe3" + 20HFeS0,O * Fez+ + SO:-

+

FeS04+* Fe9+ SO:-

pK (model)b

pK

pK'"

13.997 f 0.003* 1.99 f 0.01* 0.85 f 0.05* 11.81 f 0.02' 22.3 f 0.1* 2.2 f 0.1' 2.3 2.21 2.75 2.11 2.2

1.1 1.7 1.0

4.04 f 0.1' 4.18 4.00 4.05 3.85 3.86 4.04

3.02 1.98 2.03 2.36 2.23 2.02 2.43 2.21 2.07 2.62 2.39 2.12

3.95 4.15 4.15 4.26 4.08

1.98 1.83 1.93 2.31 2.30 2.32 2.24 2.06 2.66 1.92

4.42 1.93 3.92 5.38 f 1.0*

FeHS0:"

5.26 4.20 3.34 4.17 5.34

+ HSO;

1.08*

+ HSO;

2.48

+ Fe3+

Fe(0H)SOt * Fe(OHI2" + SO-: Fe(OH)2SO; + Fe(OH)2t + SO-: FeClO," + Fez+ + C10; FeC1O4*" + Fe3+ + ClO,

soln and ionic strength

T,"C

0 0 0

25.0 25.0 25.0 25.0 25.0 25.0 25.0 30.5

0

3.85 3.87 2.82

FeHS04+= Fez+

Oca

2.00 0.97 0.55 0.94 2.11 0.29 0.61 2.47 0.6 f 0.11 1.0 f 0.5 0.8 f 0.05

2.3 0.8 0.9 1.15 1.28 Eissumed no pairing

0 0 0 1 M NaC10, 2.2 M H2S04 1 M NaClO, 0 0 0.066 M NaClO, 1 M HClO, 1 M HClO, 0.15 M NaClO, 1.23 M NaClO; 1 M Na2L (variable) I = 0.25 I = 0.75 I = 1.53 0 I = 0.1 (variable) I = 0.2 (variable) I = 0.4 (variable) I = 0.69 (variable) I = 1.0 (variable) I = 1.0 (variable) 0.5 M NaClO, 0.5 M NaClO,

1 M NaClO, 1.2 M NaC10, 0.1 M HN03 2.67 M (variable) 0 3.00 M (variable) 0 0 1.2 M NaC10, 1 M HClO, 0.3 M Na2S0, 1 M NaClO, I = 1 (variable) 0 4 M NaClO, variable 0 I = 0.15 M Ba(C104)2 2.67 M 0.3 M NaCl 1.2 M NaClO, 0 0 variable 0

methodC 1 1 1 1 1 1

4 5 2

25.0 25.0 25.0 18.0 28.0 27.0 19.0 25.0 25.0 25.0 25.0 25.0 20.0 20.0 20.0 20.0 20.0 20.0 30.0 25.0 25.0 25.0 25.0 20.0 20.0 25.0 25.0 25.0 25.0 25.0 25.0 28.0 25.0 25.0 25.0 25.0 25.0 25.0 19.0 25.0 var 25.0 25.0 25.0 25.0 19.0

5 6 1

5 2 3 3 3 7 7 7 7 3 3 3 3 3 3 3 3 5 7 3 3 3 3 7 7 1 1

3 2 7 3 7 4 5 2 5 3 317 7 3 8 8 2 1 3

ref 3 3 4 5 5 3 6 7 8 9 10 3 11 12 12 13 14, 15 16 16 16 16 17 17 17 17 17 17 17 18 19 19 20 21 22 23 24 25 26 3 14, 15 12 16 20 25 27 9 8 27 13 23 25 14, 15 14, 15 14, 15 8 3 13 23

Reported apparent stability constants (pK? were converted to thermodynamic constants (pK) by using activity coefficients estimated by the mean salt method (2) for solutions with ionic strength, I > 0.1 m and by the Truesdell-Jones (35) model for I 5 0.1 m. bValues recommended for incorporation into geochemical models for acid high iron-sulfate waters are indicated *. 1, literature review; 2, ion exchange; 3, spectrophotometry; 4, calculations based on charge, radius, and polarizability; 5, rate constant data; 6, calorimetry; 7, potentiometry; 8, estimated by comparison with other metal-hydroxide complexes.

species were not included in the original model, but were added, one at a time, in order to test each one's effect on speciation. The results of these tests will be discussed below. The effect of C104- pairing with iron was found to be negligible when the speciation model was tested with pK = 0.9 for the dissociation of FeC104+(8) and pK = 1.15 for FeC10d2+(3). Accordingly, these constants were neither included in the model, nor was the effect of their uncertainty tested further. The ferric hydroxide pairs Fe(OH),O 700

Environ. Sci. Technol., Vol. 24, No. 5, 1990

and Fe(OH),- are present only in waters where pH > 4, and the ferrous hydroxide species Fe(OH)+, Fe(OH),O, Fe(OH) 9. The ferric dimer Fe2(OH),4+and trimer Fe3(0H)45+ are present only in solutions with high concentrations of oxidized iron. Inclusion of constants for these species had no effect on the model-calculated species concentrations, so they were not considered further. The computational procedure applies the iterative continuous fraction technique of Wigley (28)to a set of linearly

Table 11. Parameter of Closest Approach, A, for Species of Interest in This Study (36,37)'

K+

H+

3

9

Fez+ 6

Fe3+ 9

OH-

Fe(OHP+ 5' Fe(OH)2+

3.5

4'

SO4-

KS04-

4

3'

HS043.51

FeSOl0 30

FeS04+ 30 Fe(SOJ230

c1043.5

Estimates, based on comparison of species with similar size and charge, are indicated (e).

Flgure 1. Plot of pe calculated by the speciation model versus measured pe for all data. Calculations were made with single-ion activity coefficients estimated by the TruesdellJones equation, pH measurements that had been adjusted for drift and liquid junction potential, and the equilibrium constants listed In Table I, column 2. The line of best fit for these data is not significantly different from the 1:l line. The 95% confidence limits are shown by dashed lines (f0.27pe unit or 16 mV). The points encircled A and B represent solutions containing only iron and perchloric acid: sulfate was absent.

independent equations for mass balance and mass action. The known variables include the experimental concentrations for Fe(II), Fe(III), SO4,K, and C104,measured pH, the dissociation constants for all the aqueous complexes, and the equilibrium constants for the acid/base reactions. Ionic strength is estimated, activity coefficients (yi)are calculated, and then both parameters (1 and y i ) are subsequently refined until convergence is attained. Convergence is assumed when the change in ionic strength is minimal, or when

(n

this study are low enough, the ion-association methods of Debye-Huckel(38), Davies (34),and Truesdell and Jones (35) were tested. The modeling results indicate that the assumptions about the ionic strength are valid (discussed later). The Debye-Huckel equation is

where 1 represents ionic strength; zi, the charge on species i; Ai, the parameter of closest approach (Table 11); and A and B are parameters dependent on temperature and pressure (38). The Davies equation

(fi

- 0.31)

log yi = -A%?

l+&

includes an arithmetic ion-interaction term, 0.31. A further modification, as suggested by Truesdell and Jones (35) in WATEQ, log yi = -Azi2

( +fi 1

For all solutions of this study, it was attained in less than 10 iterations. One aim of this work is to test the effect on the speciation results due to uncertainty in the equilibrium constants for the various aqueous species. In order to do this, a method for calculating the single-ion activity coefficients for each species is required, but additional uncertainty associated with the activity correction enters the model. Speciation was tested by using three methods for estimating single-ion activity coefficients. The purpose of using different models was not to discover the best one for simulating the experimental data, but rather the purpose was to observe the difference in speciation calculations resulting from the different models, and in this way, to demonstrate the degree of uncertainty in a model that is related to attempting to estimate single-ion activity coefficients. The Pitzer method of activity correction for solutions where 1 > 0.1 m (29,301 is becoming popular in geochemical modeling. It is particularly useful in application to waters with moderate to high pH (32,32). The model has recently been applied to the Fe(II)-S04-H20 system (33), but no comprehensive Pitzer formulation has yet been developed for modeling systems where ferric iron species are present. Because the ionic strengths of solutions in

(3)

BAi&

-

biz)

(4)

incorporates both Ai and a species-dependent, ion-interaction term, biz. The values for the bi term for a few species have been presented (35), but for most of the species of this study, estimates would be required. In order not to complicate the sensitivity analysis with another source of uncertainty, bi was assigned the value 0.3 for all i. For the ionic strengths of this study, the value chosen for bi has little effect on the speciation results. In the speciation model, the dissociation constants for all reactions and the total concentrations of all dissolved constituents are specified. Speciation by the model is influenced by the choice for y estimation, by uncertainties in the equilibrium constants, and by uncertainties in the input concentrations. Charge balance is determined from the calculated species concentrations and provides a check on the validity of the pH measurement. The pH could be independently calculated, but consistent with field methods and with measured pH as input, the free Fe2+and Fe3+ concentrations could be calculated and pe predicted from [Fe3+]/ [Fez+],where square brackets denote activity (m). For this system (at 298.15 K and 1 bar), the Nearnst equation (34) has the form [Fe3+] pe = 13.0 log (5) [Fez+] A comparison can then be made of calculated (pe,) and measured (pe,) values over the entire set of data, for one

+

Environ. Sci. Technol., Vol. 24, No. 5, 1990 701

specific set of chemical conditions, by using a parameter called the deviation factor

where DF represents the degrees of freedom for the population. If correlation is ideal, uf = 0. Increased discrepancy between calculations and measurements increases

13.00

12.50

-

12.00

-

w

e ~

Of.

1

W

I-

U

Experimental Methods The solutions for this study were prepared with total iron concentration ranging from (0.56 ppm) to m (558 ppm) with Fe(III)/Fe(II) ratio of 1. The pH ranged from 1 to a limit determined by Fe(OH),,,, saturation: pH = 4 for the low iron samples, and pH = 2 for higher iron. Sulfate concentration varied from (96 ppm) to lo-' m (9600 ppm). Although acid mine drainage has been found to contain more than 170oO ppm total iron, 3 times as much sulfate, and pH as low as 0.55 (I,39), most ground and surface waters from mine sites fall in the concentration range of the experimental solutions (40,411. Fe(III)/Fe(II) stock solutions were prepared with iron perchlorate salts in distilled-deionized water and HC104 and were stored in the dark, with N2 sparging. Fe(I1) and total iron concentrations (after reduction by granular silver) were determined (fl%) by titration with K2Cr207 and potassium diphenylaminesulfonate as the indicator (42). Fe(II1) concentration (k2%) was calculated by difference. A sulfate stock solution (0.5 m f 1%)was prepared with oven-dried K2S04. The concentrations of the acid stock (0.05,0.5,and 5.0 m HC104)were verified ( f l % ) by potentiometric titration against Na2C03. All solutions were stored, and the experiments performed, in sealed vessels and bubbled with high-purity, humidified N2 that has been purged of COPand 02. The pH and Eh electrodes, buffers, and test solutions were maintained at 25 (*0.1) "C in a water bath. The Orion-Ross combination glass electrode with 3.0 M KC1 filling solution was stored in 4.01 NBS buffer (0.05 m potassium hydrogen phthalate) and calibrated before and after each series of measurements with the pH 4.01 buffer and a standardized pH 2.096 H2S04solution, and checked with pH 1.68 0.05 m potassium tetraoxalate and pH 1.00 HCl + KC1 buffers. The Markson 1202 Eh combination platinum and Ag-AgC1 electrode had a 3.5 M KCl filling solution and a sleeve-type liquid junction surrounding a platinum billet. The billet was polished periodically with very fine emery paper to remove surface alteration products (43).The electrode was calibrated in ZoBell solution (44).All measurements were corrected for drift of electrode potential with time, and for liquid junction potentials using the Henderson equation by the procedure of Plummer and Busenberg (45).In all cases, the magnitude of the corrections was small: well within the range of experimental error. Reproducibility for pH readings was k0.02 pH unit and for Eh was better than f1.48 mV (f0.025 pe unit) except for samples where iron concentration was less than m. After calibration of the electrodes, a measured volume of distilled water was sealed in the 700-mL reaction vessel, bubbled with nitrogen, stirred with a Teflon-coated magnetic stirring bar, and allowed to equilibrate to 25 "C. Acid was added first to prevent ferric hydroxide precipitation, and iron and sulfate aliquots were added next. Volumes of each stock solution were injected by plastic syringes that had been calibrated by weighing volumes of distilled water. Densities of stock solutions were determined and used to 702

Environ. Sci. Technol., Vol. 24, No. 5, 1990

_I

3

u

10.50

y 10.50

I 11.00

I

I

I 12.50

't;.2h~~~d~.P"i

1 13.00

Flgure 2. Comparison of calculated pe with measured pe for a series of solutions with (Fe), = lo-* m and varying sulfate concentrations. The difference between Calculated and measured pe increases with decreasing pH because of problems measuring pH at values less than 1.7. Some pH measurements appear as small numbers beside the data points. See Appendix for complete tabulation of solution chemistry.

convert concentrations to molality (m).Reproducibility of injected volumes was determined to be better than f0.5%. Eh and pH were measured after the addition of each acid aliquot until a final pH near 1 was reached.

Results All data for calculated pe are plotted as a function of measured pe on Figure 1. The Appendix contains the full data set. The pe calculations were made with Truesdell-Jones y estimates and the equilibrium constants listed in Table I, column 2. For ideal correlation, the line of best fit would have a coefficient of determination (1.2) and slope (0)of 1.0, and a y intercept ( C Y ) and deviation factor (uf) of 0. For the actual data, r2 was 0.94 for a population size ( n )of 130 points; p = 0.97 was not significantly different from 1.0 at the 95% confidence limit; CY was 0.45; u was 0.74. The significant correlation of the data and the closeness of the line of best fit to the ideal line demonstrate the effectiveness of the conventional model in describing speciation in acid mine waters, even with ionic strength as high as 0.35 m and many pH measurements below 2.0. Speciation calculations indicate that iron hydroxide complexes always play a minor role in these solutions where pH < 4.0. These species are most abundant where sulfate concentration is low, and pH > 2. With increased sulfate concentration, there is an increase in the percentage of ferric-sulfate pairs and a drop in pe occurs. At lower pH, free Fe3+and Fez+are more abundant. Higher pe is observed in low-pH samples due to the greater proportion of Fe3+with respect to Fe2+. For samples with pH < 1.7, pH was consistently measured too high because of electrode conditioning problems, and calculated pe was likewise in error. Discussion Although the model predicts pe without significant deviation at the 95% confidence limit, systematic differences in the data do exist (See Figures 1 and 2). The degree of discrepancy varies, depending on the pH and the composition of the test solution. These differences are attributed to the following sources: (1) uncertainties in

electrode measurement, (2) uncertainties in the estimated single-ion activity coefficients, and (3) uncertainties in the equilibrium constants and/or the existence of ion pairs not accounted for in the speciation model. The relative effects of these sources of uncertainty are evaluated and discussed in the following paragraphs. Electrode Response. The uncertainty in the electrode measurements was evaluated by an analysis of pH measurement error and by a test of the importance of the liquid junction potential correction for both pH and Eh electrodes. The charge balance error showed an increase in anion excess when pH decreased below 2.00. The input concentrations of all major constituents except H+ were known with less than 2 % uncertainty so could not account for these high charge differences. The H+ concentrations, however, were derived from measured pH. The logarithmic nature of pH and the dominance of H+ as a cation in acid solutions result in magnification of the uncertainties derived from errors in the pH electrode readings. For this study, the pH electrode was stored in pH 4.01 NBS buffer, calibrated with 4.01 buffer and pH 2.096 H2S04solution. Measurements were reproducible (f0.02 pH unit), but where pH was less than 1.7, slight and prolonged downward drift of potential was observed. In a separate experiment, the electrode was first conditioned in the pH 2.096 H2S04solution for several hours and then calibrated with the pH 4.01 and 1.00 HCl and KC1 buffers. pH measurements in various strengths of H2S04ranging from 0.05 to 5 M were again reproducible, but the readings were consistently and remarkably stable. For example, a stable pH of 0.10 was recorded for 0.9345 M H2S04after 3.5 min. During the next 28 min, the fluctuation in potential was only 0.2 mV, and this fluctuation was accompanied by a temperature variation of 0.25 "C. The measurements agreed with the pH calculated by the speciation model with y approximations made with the TruesdellJones equation for pH 1 0.7 and with the Pitzer model for pH ranging as low as 0. It can be concluded that error in the pH measurements below 1.7 results mostly from the method of storage and calibration of the electrode. Readings for the Fe-S04-H20 test solutions with pH < 1.7 were adjusted by -0.1 pH unit to partially compensate for the memory effect and reentered into the model. This time, the maximum charge balance error was reduced to h570 and the calculated pe was much closer to the experimental data; that is, ar improved from 0.74 to 0.37 (Table 111). To minimize the memory effect for general pH measurements where pH is less than -2, it is recommended that electrodes be conditioned for several hours before use and calibrated with a buffer of acid similar in composition and pH to the solution being measured. Liquid junction potential corrections were made for all pH and Eh measurements of this study. Comparison to calculations made without adjustment for this systematic error indicated that the correction significantly improved the correlation with experimental data (Table 111),but the magnitude of the correction (less than 0.03 pe or pH unit or 2 mV) is within the reproducibility of the readings and need not be considered in routine field measurements. Activity Coefficients. Single-ion activity coefficients form one set of speciation model parameters. Substantially different values result, depending on which estimation method is chosen. Figure 3 shows activity coefficients calculated by the Davies and the Truesdell-Jones models, plotted with ionic strength. At ionic strength of 0.05 m, the y for the bi- and trivalent species vary one from another by -15% and as much as loo%, respectively. A t the maximum ionic strength of the study solutions ( I =

Table 111. Statistics from Speciation Model Testing Test for e f f e c t of: pH Measurerent Error (calculations used l i s t e d pK's and T-J -del for 1 ) Liquid Junction Potential ( U P ) corrections oads for pH and Eh measurementi

0.94

0.97

0.45

0.74

b)

U P corrections omitted

0.95

0.96

0.41

1.32

c)

- 0 . 1 adjustneat =de to pH measurements less than 1.7 t o correct for aystamtic errora

0.94

0.98

0.29

0.37

0.94 0.94 0.93

0.97 0.82 0.88

0.45 2.15 1.45

0.74 1.75 2.09

a)

Model for 'I Estimation (PH corrected for U P and l i s t e d pK's)

a)

Truesdell-Jones Davies Debye-HUckel

b)

c)

Uncertainty (pil correci Species

Bquilibri for WP ar

Conatanti

'-J f o r I)

pKb

MJuitment

13.997

-0.003

0.94

0.97

0.45

0.74

1.99 0.85

-0.02 -0.02

0.94 0.94

0.97 0.97

0.49 0.48

0.70 0.71

Fe( 0 0 ) z+

11.81

Fe(0H)f

22.3

-0.02 -0.1

0.94 0.94

0.97 0.97

0.43 0.43

0.74 0.74

FeSOe

2.2

-0.1

0.94

1.0

0.09

0.49 1.03

HSOi KS0;

M.1

Peso:

4.04

-0.1 M.1

0.94 0.94

0.94 1.0

0.87 0.00

1.49 0.00

5.38

-1.0 -0.1

0.93 0.94

0.90 0.95

1.34 0.67

0.84

1.18

FeHSOt

0

0.95 0.94

0.96 0.97

0.53 0.40

0.20

c1.5 FeHSOZ+

0

+2.47 +1.5

0.95 0.94

0.97 0.97

0.36 0.44

0.69 0.57

Fe (OH)SOg

0

0

C2.3 M.8

0.94 0.94

0.98

Fe(0H)ZSOi

0.28 0.45

0.73 0.74

+I * 08

0.97

2.83

OMaximum charge balance error improved from f40 to *5?& with this change. *pKs are all for dissociation reactions, Le., Fe(OH)SOdoe Fe(OH)2++ SOA2-.

1.0

-

%

0.8

-

0.6

-

0.4

-

Y

0.2-

I

0.001

I

0.01

I'

I

I

0.I

I. 0

Figure 3. Single-ion activity coefficients versus ionic strength for H+, OH-, Fe2+,S O:-, and Fe3+, estimated by TruesdellJones and Davies (DA) equations.

0.35 m),y varies by 20% for the monovalent species and as much as 133% for Fe3+. This uncertainty in activity coefficient estimation contributes significantly to the uncertainty of the model results. The ability of the model to simulate the experimental data was tested by using each of the three methods for estimating single-ion activity coefficients. The statistics are presented in Table 111. Estimations made with the Debye-Huckel equation do not include a correction for the ion-interaction effect, so y uncertainty increases with ionic strength. As a result, the calculated pe for solutions with high sulfate, high iron, or low pH are consistently higher Environ. Sci. Technol., Vol. 24, No. 5, 1990

703

Table IV pB

le11

PeIII

SO4

K

C104

pm

pe,

I(=)

CB(2)

12.16 12.37 12.53 12.64 12.67

0.008 10.20 0.015 10.07 0.041 -12.93 0.119 -28.91 0.155 -33.23

2.487 2.488 2.321 1.944 1.390 0.877 0.725

12.27 11.95 12.13 12.31 12.39 12.26 12.32

12.23 11.99 12.16 12.37 12.S3 12.64 12.67

0.005 9.34 0.006 8.32 0.008 9.06 0.015 8.50 0.041 -14.81 0.119 -28.85 0.160 -38.S6

2.487 2.489 2.322 1.945 1.389 0.877 0.752

12.34 11.70 11.86 12.07 12.24 12.30 12.28

12.23 0.005 11.76 0.012 11.86 -0.013 12.06 0.019 12.28 0.044 12.50 0.122 12.54 0.157

9.93 5.88 6.37 10.34 -10.62 -26.76 -33.07

2.487 2.495 2.326 1.?46 :.-09 0.882

12.32 11.38 11.52 11.69 12.08

12.23 11.50 11.56 11.68 i;.?i 12.21

0.004 0.030 0.031 0.035 5.056 0.131

8.75 2.12 2.69 5.78 -i.65 -22.80

2.487 2.515 2.339 1.951 1.392 0.877

12.29 11.02 11.17 11.30 11.46 11.68

12.22 11.26 11.31 11.37 11.56 11.83

0.004 7.58 0.087 0.62 0.086 0.96 2.60 0.086 0.100 5.40 0.165 -14.31

2.487 0.696 2.582 0.698 2.382 0.703 1.968 0.706 1.396 0.713 0.878 0.724 0.577

12.24 10.63 10.80 10.92 10.98 11.19 11.32

12.22 11.01 11.05 11.09 11.16 11.37 11.56

0.004 0.242 0.242 0.238

1.456 12.60 1.457 12.53 1.206 12.51 0.792 12.36

12.64 12.57 12.63 12.69

0.055 10.64 0.053 10.83 -2.h4 0.079 0.164 -21.70

1.456 1.459 1.207 0.793

12.64 12.40 12.41 12.35

12.64 12.38 12.47 12.58

0.054 0.050 0.076 0.161

8.45 8.48 -4.26 -23.63

1.067 1.476 1.214 0.796

12.59 11.91 12.02 12.15

12.64 11.90 12.06 12.30

0.053 0.056

10.75 10.19 -2.02 -19.33

1.466 1.496 1.224 0.801 0.642

12.62 11.44 11.54 11.72 11.78

12.63 11.43 11.55 11.82 12.01

0.053 0.104

1.466 1.569 1.264 0.818 0.634

12.56 10.94 11.06 11.25 11.36

8.71 12.63 0.053 11.08 0.260 0.95 -1.24 11.14 0.264 11.34 0.300 -9.74 11.46 0.346 -16.95

1.456 1.558 1.259 0.946 0.663

12.60 10.97 11.09 11.29 11.41

12.63 11.08 11.14 11.34 11.49

K

2.999 3.005 3.007 3.015 3.018

2.698 2.704 2.706 2.714 2.717

-

-

2.998 2.999 3.005 3.007 3.015 3.019

2.697 2.698 2.704 2.706 2.714 2.718

PeII

ClO'

1.531 2.044 1.549 1.093

5.317 5.323 5.325 5.332 5.334 5.342

5.306 5.312 5.314 5.320 5.323 5.331

2.962 2.968 2.970 2.977 2.979 2.987

2.661 2.667 2.669 2.676 2.678 2.686

3.478 2.991 2.481 1.979 1.374 0.848

11.26 11.67 11.93 12.17 12.24 12.05

11.35 11.81 12.07 12.28 12.48 12.62

0.004 0.004 0.006 0.013 0.000 0.120

3.335 3.032 2.526 2.034 1.556 1.093

5.319 5.323 5.325 5.332 5.334 5.342

5.308 5.312 5.314 5.320 5.323 5.331

2.964 2.663 2.968 2.667 2.970 2.669 2.977 2.676 2.979 2.678 2.987 2.686

3.295 2.991 2.481 1.979 1.374 2.868

11.72 11.91 12.15 12.32 12.41 12.32

11.57 11.81 12.07 12.28 12.48 12.62

0.003 0.004 0.006 0.013 0.039 0.120

1.57 1.94 2.20 0.88 -25.03 -38.79

,804 .E47 .545 .043

3.344 3.345 3.346 3.352 .550 3.354 .Os6 3.362 1.975 3.366

3.325 3.326 3.327 3.333 3.335 3.342 3.347

4.093 3.188 3.087 2.584 2.073 1.568 1.101

5.317 5.323 5.325 5.327 5.334 5.336 5.344

5.306 5.312 5.314 5.316 5.322 5.325 5.333

2.460 2.466 2.468 2.470 2.476 2.479 2.487

2.159 2.165 2.167 2.169 2.175 2.178 2.186

3.972 3.096 2.994 2.482 1.979 1.373 0.847

10.86 11.57 11.63 11.83 12.00 12.14 12.12

10.58 11.58 11.63 11.80 11.97 12.22 12.46

0.010 0.011 0.011 0.012 0.018 0.044 0.124

0.25 1.03 1.13 1.05 0.72 -22.07 -38.06

.799 3.344 '.E95 3.347 .593 3.348 8.051 3.356 -. . .. .550 3.356 .086 3.363 1.985 3.367

3.325 3.328 3.329 3.337 3.344 3.348

2.497 2.498 2.504 2.5~ 2.513 2.517

3.684 3.192 2.680 2.160 1.624 1.127

5.326 5.332 5.334 5.340 5.342 5.350

5.314 5.320 5.322 5.329 5.331 5.339

1.963 1.969 1.971 1.977 1.979 1.987

1.662 1.668 1.670 1.676 1.h71 1.686

3.490 2.995 2.482 1.979

10.84 11.13 11.38 11.55 11.67

11.70

!.SO9 1.031 !.709 !.149 ..575 ,103

3.344 3.353 3.354 3.360 3.362 3.369

3.325 3.334 3.335 3.341 3.343 3.350

-

1.37'3

0.031 0.27 0.031 0.54 0.98 0.032 0.035 1.22 0.053 -17.25 0.134 -35.51

-

0.847

11.15 11.62 11.53 11.64 ?!.a5 12.17

1.997 1.998 2.004 2.006 2.013

1.696 1.697 1.703 1.705 1.712

3.339 2.827 2.306 1.734 1.170 1.031

5.353 5.355 5.361 5.363 5.371 5.376

5.341 5.343 5.350 5.352 5.360 5.364

1.472 1.171 1.473 1.172 1.480 1.179 1.482 1.181 1.490 1.189 1.495 1.193

2.995 2.483 1.980 1.374 0.848 0.704

11.15 11.26 11.33 11.44 11.63 11.63

11.21 0.091 11.29 0.091 11.35 0.091 11.49 0.104 11.78 0.170 11.88 0.210

0.31 0.76 1.68 -7.14 -24.07 -31.27

l.819 1.228 l.887 L.321 L.624 1.137

3.344 3.372 3.373 3.379 3.381 3.389

3.325 3.353 3.354 3.360 3.362 3.369

-

-

1.698 1.499 1.505 1.507 1.515

1.197 1.198 1.206 1.206 1.214

3.306 2.959 2.508 1.976 1.354

5.431 5.433 5.439 5.442 5.449

5.420 5.422 5.428 5.430 5.438

0.982 0.984 0.990 0.992 1.000

0.681 0.683 0.689 0.691 0.699

2.774 2.409 1.963 1.378 0.856

10.94 10.99 11.03 11.02 11.05

11.02 0.250 11.04 0.248 11.07 0.285 11.14 0.248 11.34 0.282

0.28 0.47 1.00 -2.30 -12.04

3.001 2.516 2.029 1.540 1.084

4.325 4.326 4.333 4.335 4.343

4.313 4.315 4.321

7.671

7.900

I?.(?!

0.997 0.999 1.004 1.007 1.016 1.025

12.27 12.47

1.R83

2.313

i.ilira

-

0.122

1.507 1.047

2.316 2.324

2.294 2.295 2.297 2.305

-

2.314

12.56

2.75 2.89 1.52 -22.07 -37.00

3.325 3.420 3.421 3.427 3.429 3.437 3.:47

2.673 2 . 6 5 1 2.679 1.969 2.5'1 !.371 2.689 0.846

11.84 i2.09 12.29 12.49 12.62

3.344 3.439 3.441 3.446 3.449 3.456 3.L67

4.326 4.332

2.972 2.971 2.980 2.982 2.990

2.819 ).481 3.120 2.547 1.966 1.318 1.954

2.964 2.966 2.974

2.663 2.665 2.673

3.057 2.564 2.058 1.559 1.093

4.327 4.329 4.335 4.337 4.345

4.315 4.317 4.323 4.326 4.334

2.467 2.166 2.469 2.168 2.475 2.174 2.478 2.177 2.486 2.185

2.901 2.450 1.969 1.370 0.846

11.71 11.90 12.07 12.28 12.38

11.64 0.011 11.81 0.013 11.98 0.018 12.22 0.044 12.46 0.125

1.48 2.13 2.65 -20.40 -36.42

1.902 1.931 1.530 1.064

2.313 2.316 2.318 2.326

2.294 2.297 2.299 2.307

-

-

2.463 2.465 2.473

2.162 2.164 2.172

2.981 2.600 2.120 1.605 i1.127

4.337 4.326 4.339 4.328 4.345 6.334 4.348 4.337 4.356 6.344

1.972 1.671 1.974 1.673 1.980 1.679 1.983 1.682 1.991 1.690

2.761 2.399 1.955 1.370 0.849

11.46 11.55 11.66 11.88 12.11

11.48 0.031 11.55 0.032 11.65 0.036 11.87 0.058 12.17 0.133

1.21 1.69 2.95 -14.90 -35.04

1.888 1,961 1.554 1.064

2.323 2.311 2.332 2.321 2.334 2.323 2.342 2.331

-

-

1.963 1.965 1.973

1.662 1.664 1.672

4.344 4.347 4.351 4.354 4.356 4.364 4.366

1.473 1.475 1.479 1.682 1.185 1.492 1.495

1.172 2.455 1.174 2.190 1.178 1.972 1.181 1.854 1.183 1.312 1.191 0.840 1.194 0.751

11.27 11.31 11.35 11.38 11.49 11.74 11.80

11.29 0.091 11.32 0.091 11.35 0.091 11.18 0.091 1 1 . ~ 1 0.105 11.79 0.172 11.86 0.197

0.97 1.56 2.00 2.76 -5.17 -24.25 -26.06

2.323 2.353 2.355 2.363 2.368

2.311 2.341 2.344 2.351 2.357

-

4.356 4.358 4.362 4.365 4.367 4.375 4.378

1.907 2.162 1.716 1.172 0.875

-

2.807 2.526 2.296 2.157 1.680 1.161 1.056

1.464 1.466 1.474 1.480

1.163 1.165 1.173 1.179

4.417 0.977 4.423 0.983 4.425 0.986 4.433 0.991 4.442 1.702

0.676 2.166 0.682 1.978 0.685 1.383

11.03 11.07 ~1.14 11.33 11.48

1.!01

2.311 2.414 2.416 2.424 2.430

-

4.428 4.434 4.437 4.444 4.453

2.323 2.425 2.427 2.435 2.441

-

3.045 2.533 1.986 1.353 1.089

1.907 2.515 2.004 1.352

0.968 0.667 0.970 0.669 0.978 0.677 0.985 0.684

2.799 2.837

3.344 3.345

3.325 3.326

1.927 2.5:5 2.109 1.359 1.047

2.310 2.412 2.414 2.419 2.427

2.298 2.400 0.969 2.402 0.971 2.407 0.976 2.415 0.984

3.532

3.042

~

-

2.998

12.59

~~

(?.E04 O.Wb

0.013 0.O.iO

0.252 0.248 0.251 0.285 0.349

0.692

0.854

10.96 11.04 11.11 :1.29

0.70:

0.630

i:.~',

-

2.487

12.30 12.23 0.005 11.95 12.00 0.006

2.69i

:.:a8

0.37 9.96 -2.13 -!:.a4

-23.15 3.93 9.11

than the measurements. With Davies estimations, calcu-

3.335 .

-

-

m(x)

pac

12.15 12.34 12.44 12.38 12.35

SO6

3.327 3.333 3.335 3.342 3.346

pH

I(=)

pe,

2.321 1.940 1.390 0.876 0.751

PeIII

.535 3.346 .034 3.352 .541 3.354 ,086 3.362 1.977 3.365

0.89 1.17 1.47 -1.10 -23.94 -38.79

2.196 2.197 2.203 2.205 2.212 2.216

-

0.668 0.670 0.675 0.683

11.88

0.240

0.274 5.357

0.080

0.165

7.58 0.22 0.38 1.28 -0.60 -7.10 -18.b3

8.71 4.65 -2.90 0.188 -20.87 0.257 -11.09 0.118

0.054 0.260 0.263 0.281 0.343

6.50 0.73 -1.53 4.95 -7.62

constant for each species was adjusted by its uncertainty; the effects on speciation are reflected by the statistics of Table 111. The small uncertainties for dissociation constants of species from systems that have been well-studied have little effect on the results, as for example, for the iron-hydroxide pairs. On Figure 1,the circles labeled A and B represent data for waters with only iron and acid present; sulfate is absent. Their position with respect to the ideal line indicates that the uncertainty in the thermodynamic data for the Fe-H20-K-C104 system is minimal. More pK uncertainty, for example, f1.0 for Fe(S04)2-,leads to a larger effect. In some cases, however, when the relative abundance of a species is high, such as for FeS04+,small uncertainty (*0.1) can have a considerable effect on the speciation results. The model was tested for sensitivity to the inclusion of the uncertain pK for Fe(OH)SO,O, Fe-

(OH)2S0c, FeHS04+, and FeHSOZ'. Calculated concentrations were not significantly affected by the constants for the ferric hydroxide-sulfate complexes. Inclusion of constants for the iron-bisulfate pairs slightly improved the relationship between measured and calculated pe. The equilibrium constants and their uncertainties, listed in Table I and marked by an asterisk, are recommended for incorporation in geochemical models for speciation of acid, iron-sulfate waters.

Conclusions Equilibria in the aqueous acid iron-sulfate system at 25 "C can reliably be simulated by using a speciation program that incorporates presently accepted equilibrium constants. Values recommended for incorporation into geochemical models are presented in Table I. If the pH and solute concentrations are known, the model is effective in calculating pe within h0.25 pe unit (f15 mV) at the 95% confidence level, over the typical range of composition for acid mine and tailings water, even with ionic strength as high as 0.35 m. Uncertainties in the speciation calculations result from error associated with pH electrode measurements and from uncertainty in the two main sets of model parameters: single-ion activity coefficients and the equilibrium constants. For solutions where pH is less than 1.7, large measurement error can result from the technique adopted for conditioning and calibrating the pH electrode. The model calculations are only slightly sensitive to the correction for the liquid junction potential for all measurements with the Ehand pH electrodes. Speciation is somewhat sensitive to uncertainties in the estimates for activity coefficients. Of the three methods used, the Truesdell-Jones equation produced the least difference between measured and calculated pe values for solutions in this system. The model results are not sensitive to changes in pK for any of the iron-hydroxide complexes. They are sensitive to uncertainties in equilibrium constants for iron-sulfate pairs, particularly FeS04+. Simulations are slightly improved by inclusion in the model of approximated constants for FeHS04+ and FeHSOZ+. In summary, the equilibrium speciation model for the aqueous acid iron sulfate system, as outlined in this paper, is satisfactory for simulating species concentrations at ionic strengths up to 0.35 m in the pH range of 1-4. The constants listed in Table I, column 2 (and marked *), are recommended for incorporation into geochemical models for iron sulfate waters. To ensure accurate calculations for solutions where pH is measured to be less than 2.0, care must be taken to condition and calibrate the pH electrode in a buffer of acid similar in pH and composition to the unknown. Aside from the difficulty associated with H+ concentration for solutions with pH below 2.0, the greatest source of uncertainty in model simulations lies with the method of calculating single-ion activity coefficients. Uncertainties in the equilibrium constants of the species involved appear to be of secondary importance.

Acknowledgments I gratefully acknowledge the guidance provided by Eric Reardon in the first part of this work, and thank Kirk Nordstrom, Jim Leckie and George Parks for encouragement and discussion. Appendix

Data for the experimental solutions are given in Table IV. pH has been corrected for the liquid junction potential and time-dependent drift. Derived parameters (pet,

I, and CB) were calculated with the speciation model by using the equilibrium constants listed in Table I and the Truesdell-Jones equation for estimating single-ion activity coefficients. Component concentrations are expressed as -log of molal concentration; pe, represents measured pe and pec, calculated pe; I is ionic strength; and CB is charge balance error, which indicates error in pH measurement. Registry No. Fe(II), 7439-89-6; K, 7440-09-7.

Literature Cited Nordstrom, D. K.; Jenne, E. A.; Ball, J. W. Chemical Modeling in Aqueous Systems; Jenne, E. A., Ed.; ACS Symposium Series 93; American Chemical Society: Washington, DC, 1979; pp 51-79. Robinson, R. A.; Stokes, R. H. Electrolyte Solutions; Butterworths: London, 1970. Smith, R. M.; Martell, A. E. Critical Stability Constants; Plenum: New York, 1976. Reardon, E. J. J. Phys. Chem. 1975, 79,422-425. Baes, C. F., Jr.; Mesmer, R. E. The Hydrolysis of Cations; Wiley: New York, 1976. Yatsimirskii, K. B. J. Gen. Chem. USSR (Engl. Transl. 1954,24, 1498-1503 (1485-1491). Huffman, R. E.; Davidson, N. J. Am. Chem. SOC.1956, 78, 4836-4842. Beukenkamp, J.; Herrington, K. D. J. Am. Chem.SOC.1960, 82, 3022-3025. Wells, C. F.; Salam, M. A. J. Chem. SOC.A 1968,308-315. Izatt, R. M.; Eatough, D.; Christensen,J. J.; Bartholomew, C. H. J. Chem. SOC.A 1969,45-53. Sykes, K. W. J. Chem. SOC.1952, 124-129. Whiteker, R. A.; Davidson, N. Am. J. Chem. SOC.1953, 75, 3081-3085. Sykes, K. W. Spec. Publa-Chem. SOC.1954, I, 64-74. Lister, M. W.; Rivington, D. E. Can. J . Chem. 1955, 33, 1572-1590. Lister, M. W.; Rivington, D. E. Can. J . Chem. 1955, 33, 1591-1602. M a t h , B. N. Z. Phys. Chem. Neue Folge 1959,19,156-167. Kumai, T. J. Chem. SOC.Jpn. 1960,81, 1687-1695. Davis, G. G.; Smith, W. M. Can. J . Chem. 1962, 40, 1836-1845. Willix, R. L. S. Trans. Faraday SOC.1963,59,1315-1324. Bachmann, K.; Leiser, K. H. Ber Bunsenges. Phys. Chem. 1963,67,802-809. Maslowska, J. Roezniki Chem. 1967,41, 1857. Babko, A. K.; Markova, L. V. Ukr. Khim. Zh. (Russ. Ed.) 1959, 25, 363. Sapieszko, R. S.; Patel, R. C.; Matijevic, E. J. Phys. Chem. 1977, 81, 1061-1068. Nikolaeva, N. M.; Tsvelobud, L. D. Russ. J. Inorg. Chem. (Engl. Transl.) 1975, 20, 1677-1680. Nikol'skii, B. P.; Pal'chevskii, V. V.; Pang, F. T. Dokl. Akad. Nauk. SSSR 1973,209,624-627 (253-255). Wagman, D. D.; Evans, W. H.; Parker, V. B.; Halow, I.; Bailey, S. M.; Schumm, R. H. Selected values of chemical thermodynamic properties. Tables for elements 35 through 53 in the standard order of arrangement. NBS Tech. Note (U.S.) 1969, NO.270-4. Mattigod, S. V.; Sposito, G. Soil Sci. SOC.Am. J. 1977,41, 1092-1097. Wigley, T. L. M. Tech. Bull.-Br. Geomorphol.Res. Group 1977, NO.20, 1-48. Harvie, C. E.; Weare, J. H. Geochim. Cosmochim. Acta 1980, 44, 981-988. Harvie, C. E.; Moeller, N.; Weare, J. H. Geochim. Cosmochim. Acta 1984, 48, 723-751. Monnin, C.; Schott, J. Geochim. Cosmochim. Acta 1984, 48, 571-581. Felmy, A. R.; Weare, J. H. Geochim. Cosmochim. Acta 1986, 50, 2771-2784. Reardon, E. J.; Beckie, R. D. Geochim. Cosmochim. Acta 1987,51, 2355-2368. Stu", W.; Morgan, J. J. Aquatic Chemistry;Wiley: New York, 1981. Environ. Sci. Technol., Vol. 24, No. 5, 1990

705

Environ. Sci. Technol. 1990, 2 4 , 706-712

Truesdell, A. H.; Jones, B. F. J . Res. U S . Geol. Sum. 1974, 2, 233-248. Butler, J. N. Ionic Equilibrium; Addison Wesley: Don Mills, Ontario, 1964. Kielland, J. J. Am. Chem. SOC.1937, 59, 1675-1678. Helgeson, H. C.; Kirkham, D. H. Am. J . Sci. 1974, 274, 1199-1261. Nordstrom, D. K. Proceedings of the Hazardous Materials Management Conference/ West, Long Beach, Calif. Dec. 3-5, 1985. Bonner, A. J., Ed.; 1986; pp 453-457. Dubrovsky, N. M. Ph.D. Thesis, University of Waterloo, 1986. Dubrovsky, N. M.; Cherry, J. A.; Reardon, E. J.; Vivyurka, A. J. Can. Geotech. J . 1985,22, 110-128.

(42) Waser, J. Quantitative Chemistry; Benjamin: New York, 1966. (43) Whitfield, M. Ion Selective Electrodes for the Analysis of Natural Waters; Australian Marine Science Association: Sydney, Australia 1971; Handbook 2. (44) Nordstrom, D. K. Geochim. Cosmochim. Acta 1977, 41, 1835-1941. (45) Plummer, L. N.; Busenberg, E. Geochim. Cosmochim. Acta 1982, 46, 1011-1040. Received for review February 28,1989. Accepted December 27, 1989. Financial support was provided by the Natural Sciences and Engineering Research Council of Canada.

Colloidal Behavior of Actinides in an Oligotrophic Lake K. A. Orlandini,*~fW. R. Penrose,+,'B. R. Harvey,§M. B. Lovett,§and M. W. Findlay+,'

Environmental Research Division, Argonne National Laboratory, Argonne, Illinois 60439, and Ministry of Agriculture, Fisheries, and Food, Directorate of Fisheries Research, Lowestoft, Suffolk NR330HT, United Kingdom Understanding the speciation of low levels of actinides from fallout and from local sources in freshwater systems is important if we are to predict their distributions in the environment. Since these materials make excellent tracers for determining sedimentation rates and other environmental parameters, it is important to determine their physical and chemical properties in relatively pristine systems. Reported here are the results of actinide analyses in an artificial, oligotrophic lake in northwest Wales, United Kingdom, which is used as a source of cooling water for a nuclear power plant. The concentrations of the actinide elements plutonium, americium, thorium, and curium, and their distributions among different colloidal sizes were determined. Actinide concentrations in the dissolved fraction (10.45 pm) were as follows: 2397240Pu, 6.4-12.5 fCi/L; 241Am,2.5-18.2 fCi/L; 232Th,0.11-1.09 fCi/L; and W m , 0.3-1.4 fCi/L. The majority of the actinides in the lake were retained by hollow-fiber ultrafilters of 5-nm (nominal 1OOOOO MW) or 100-nm pore sizes; the actinides appeared to be bound reversibly to colloidal material of unknown composition. The two environmentally stable oxidation states of plutonium, IV and V, could be separated by ultrafiltration. These results indicate that submicron colloidal material can dominate the aqueous properties of actinides. Introduction

Numerous environmental studies in water and sediments have made use of trace metals to determine environmental impact, as well as act as indicators of geochemical parameters, e.g., sedimentation rates. Of particular use are actinide markers that can occur from fallout or from local sources. Some of the more useful of these markers include isotopes of plutonium, thorium, americium, and curium, which can be used as indicators of regional and locally sourced materials. The fate of many trace metal or organic pollutants in natural waters is controlled by their binding to particulate matter. The phase separation resulting from such binding, followed by sedimentation, is an important mechanism by

'Argonne National Laboratory. * Present address: Transducer Research, Inc., Naperville, IL

60540.

$Directorate of Fisheries Research. 706

Environ. Sci. Technol., Vol. 24, No. 5, 1990

which particle-reactive pollutants and trace metals can be removed from bulk water. The actinide elements have a strong affinity for particulates, but this affinity is modified by pH, inorganic ions, oxidation state, and the presence of colloidal organic matter. Depending on the circumstances, one or another of these parameters might predominate (1). For example, carbonate can form complexes with U(V1) that bind poorly to particulates. Actinides in the V oxidation state, such as Pu(V) and Np(V), are only weakly particle-reactive, and Am(III), Pu(IV), and Th(1V) are strongly reactive. Colloidal organic matter can strongly complex trivalent and tetravalent actinides at concentrations commonly encountered in the environment. Nelson et al. (2) demonstrated that concentrations of organic matter existing in many natural waters (1-20 mg/L) can compete with suspended particulates for the available actinides. The binding of actinides to particles (i.e., 10.45 pm) can be reduced by orders of magnitude by the presence of smaller colloidal organic matter. Other forms of colloidal material, such as clays and iron and manganese hydroxides, are also encountered in natural waters, but their roles are less well understood than that of organic colloids. Recent studies of natural colloidal systems by Santschi and others (3-5) have led to a renewed appreciation of the dynamic nature of these systems. Aside from the binding of ions to particulates and colloids, these materials seem to participate in equilibria involving aggregation and disaggregation as well. We have investigated the distribution of actinides among natural colloidal particles of various sizes. This study was done in an artificial oligotrophic lake located in northwest Wales, United Kingdom, which contains measurable traces of some important actinides. Methods

Study Site. Lake Trawsfynydd (Figure 1) is located in northwest Wales, United Kingdom. It is an artificial impoundment created in 1926 to supply a small hydroelectric station in the village of Maentwrog. Since 1965 the lake has been under the control of the Central Electricity Generating Board (CEGB). A Magnox-type twin 500-MW nuclear power reactor uses the lake as a source of cooling water to condense steam from the turbines (6). Spent fuel rods are cooled in a small pond that is scrubbed with ion-exchange resins. The washes from resin recycling,

0013-936X/90/0924-0706$02.50/0

0 1990 American Chemical Society