Modeling colloid transport for performance assessment

Journal of Contaminant Hydrology 47 Ž2001. 323–333 www.elsevier.comrlocaterjconhyd

Modeling colloid transport for performance assessment J.S. Contardi a,) , D.R. Turner b, T.M. Ahn c a

US Nuclear Regulatory Commission, MS T-7F27, RockÕille, MD 20852, USA Center for Nuclear Waste Regulatory Analyses, San Antonio, TX 78238, USA c US Nuclear Regulatory Commission, MS T-7C6, RockÕille, MD 20852, USA

b

Received 20 August 1999; received in revised form 25 February 2000; accepted 31 March 2000

Abstract The natural system is expected to contribute to isolation at the proposed high-level nuclear waste ŽHLW. geologic repository at Yucca Mountain, NV ŽYM.. In developing performance assessment ŽPA. computer models to simulate long-term behavior at YM, colloidal transport of radionuclides has been proposed as a critical factor because of the possible reduced interaction with the geologic media. Site-specific information on the chemistry and natural colloid concentration of saturated zone groundwaters in the vicinity of YM is combined with a surface complexation sorption model to evaluate the impact of natural colloids on calculated retardation factors Ž R F . for several radioelements of concern in PA. Inclusion of colloids into the conceptual model can reduce the calculated effective retardation significantly. Strongly sorbed radionuclides such as americium and thorium are most affected by pseudocolloid formation and transport, with a potential reduction in R F of several orders of magnitude. Radioelements that are less strongly sorbed under YM conditions, such as uranium and neptunium, are not affected significantly by colloid transport, and transport of plutonium in the q5 valence state is only moderately enhanced. Model results showed no increase in the peak mean annual total effective dose equivalent ŽTEDE. within a compliance period of 10,000 years, although this is strongly dependent on container life in the base case scenario. At longer times, simulated container failures increase and the TEDE from the colloidal models increased by a factor of 60 from the base case. By using mechanistic models and sensitivity analyses to determine what parameters and transport processes affect the TEDE, colloidal transport in future versions of the TPA code can be represented more accurately. q 2001 Elsevier Science B.V. All rights reserved. Keywords: Colloid transport; HLW; Performance assessment

)

Corresponding author. Tel.: q1-301-415-5399; fax: q1-301-415-6680. E-mail address: [email protected] ŽJ.S. Contardi..

0169-7722r01r$ - see front matter q 2001 Elsevier Science B.V. All rights reserved. PII: S 0 1 6 9 - 7 7 2 2 Ž 0 0 . 0 0 1 6 0 - 1

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1. Introduction The US Department of Energy ŽDOE. has proposed to permanently dispose of spent nuclear fuel as well as defense related high-level nuclear waste ŽHLW. at the Yucca Mountain ŽYM. deep geologic repository in Nevada. Yucca Mountain is located approximately 100 miles northwest of Las Vegas, NV adjacent to the Nevada Test Site ŽNTS.. The climate at the site is generally arid to semiarid, and the potential repository would be located in volcanic tuff about 300 m above the groundwater table. Both DOE and the Nuclear Regulatory Commission ŽNRC. continue to develop performance assessment ŽPA. computer models to help predict the anticipated radiological effects from the potential disposal of HLW at the YM site ŽJarzemba et al., 1999.. Thus, far several factors have been identified by NRC and DOE that may reduce the performance of the YM site. Among these is the possibility of increased radionuclide mobility resulting from colloidal transport. Because of a high specific surface area and reduced reactivity with the wall rock, the transport of radionuclides may be enhanced when attached to colloids. For example, due to large sorption coefficients Ž K D . in the saturated zone groundwater chemistry anticipated at YM, plutonium would not be expected to migrate far from the waste site. By attaching to inorganic colloidal material the effective retardation of plutonium and other radionuclides may be reduced. Several radionuclides are expected to be present and move via colloids in a deep geologic repository ŽKim, 1986.. Due to its high radiological toxicity, enhanced plutonium transport by colloids has received significant attention. Few occurrences of plutonium colloidal transport have been documented. Recently, Kersting et al. Ž1999. have reported relatively fast transport times from the Benham nuclear test cavity on the NTS for plutonium associated with colloids, but further research is needed to confirm these findings. Penrose et al. Ž1990. have also reported that rapid transport of plutonium at the Mortandad Canyon at Los Alamos National Laboratory may have resulted from colloids. Marty et al. Ž1997., however, noted that the rapid plutonium transport at Mortandad Canyon may result from surface water runoff that filtered down into uncapped sampling wells, and not from colloidal transport as originally proposed by Penrose et al. Ž1990.. Even in situations where plutonium transport has been documented it is often difficult to determine what mechanism was responsible.

2. Mechanistic sorption model: effect of colloids on radionuclide transport In both DOE and NRC PA’s, transport velocity of dissolved radionuclides Ž VRN . relative to the groundwater flow velocity Ž Vwater . is modeled using a retardation factor Ž R F . defined by the equation ŽFreeze and Cherry, 1979.: RF s

Vwater VRN

s1q

Ž1yf . r f

KD

Ž 1.

where r Žgrcm3 . is the density, f Žcm3rcm3 . is the porosity of the medium, and K D Žmlrg. is the sorption coefficient for the radionuclide of interest. Vilks et al. Ž1998.

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proposed a means of modifying Eq. Ž1. as a way to evaluate the effect of the formation of pseudocolloids on radionuclide transport in saturated aquifers. Vilks et al. Ž1998. based this approach on the assumptions that the sorption of radionuclides onto natural colloids is reversible, and that the partitioning of radionuclides into a colloid phase is preferred over complexation with the geologic media and dissolved ligands. As developed by Vilks et al. Ž1998., the effect of colloids on transport is represented by an effective retardation factor R F,eff such that: R F ,eff s 1 q

Ž1yf . rKD f Ž 1 q CFK D .

Ž 2.

where C is the colloid concentration Žmgrl., and F is an empirical partitioning factor such that: K D , colloid s FK D , geologic medium

Ž 3.

For a colloid concentrations 0, Eq. Ž2. reduces to Eq. Ž1., and R F,eff s R F . Recent studies ŽBertetti et al., 1998; Pabalan et al., 1998. suggest that the pH dependence and magnitude of actinide sorption behavior is similar for different minerals when normalized to an effective surface area AX Žm2rg. such that: K AX s K D rAX

Ž 4.

Assuming that actinide sorption on colloids expressed in terms of K AX is the same as that on the geologic medium Ži.e., K AX , colloid s K AX , geologic medium ., from Eqs. Ž3. and Ž4. can be expressed as: F s AXcolloidrAXgeologic medium

Ž 5.

The major difference in the sorptive capacity between colloids and the geologic medium, assuming similar mineralogies, is therefore the greater specific surface area of the colloid phase. Site-specific information is necessary to bound the parameters given in Eqs. Ž1. – Ž5. and apply the approach of Vilks et al. Ž1998. to evaluate potential pseudocolloid transport from the proposed repository at YM. Information on colloid concentrations and water chemistry in 23 springs ŽTable 1. in the NTS area has been reported by Kingston and Whitbeck Ž1991. and can be used to constrain parameter C in Eq. Ž2.. It is important to remember that these data represent colloid chemistry at the sampling points, and do not necessarily represent changes in hydrochemistry along flowpaths. It is also important to note that the modeling approach of Vilks et al. Ž1998. was developed for saturated aquifers and may not be applicable to the unsaturated zone at YM. As opposed to assuming a constant sorption coefficient, a diffuse-layer ŽDLM. surface complexation modeling approach was used in combination with the geochemical speciation code MINTEQA2, Version 3.11 to calculate chemistry-dependent sorption for AmŽIII., ThŽIV., PuŽV., UŽVI., and NpŽV. under the chemical conditions presented in Table 1. Specifics on the modeling approach and model parameters are provided

326 Table 1 Colloid Concentration Ž C in mgrl. and hydrochemistry from Kingston and Whitbeck Ž1991.. All major ions reported in mgrl. Laboratory and field pH reported in standard pH units Location Location Aquifer UTM Žnorth. UTM Žeast.

UE19c NTS Water Well 20 NTS Well 8 NTS Whiterock Spring NTS UE16d NTS Well A NTS Topopah Spring NTS Well C-1 NTS Well 4 NTS Cane Spring NTS Beatty Well 2 Lower Indian Spring Indian Spring Well Lathrop Wells Fairbanks Spring Crystal Pool Indian Springs Cold Creek Spring Ash Springs Pahroc Spring Sidehill Spring Peavine Ranch Well Peavine Cyn Campground Spring

4124714.9 4122709.2 4113271.2 4117486.6 4103823.5 4099201.6 4088169.4 4086098.9 4084575.7 4073116.9 4084343.0 4088589.4 4089540.4 4055243.0 4036314.5 4030638.4 4047366.5 4030080.5 4142240.3 4171198.8 4234070.9 4269535.0 4274168.1

560341.1 550624.3 563111.8 577107.5 663087.1 585700.0 564956.8 588233.0 586961.8 584427.0 521529.3 519045.2 517064.5 553809.5 561668.0 560762.2 619311.5 612699.9 659956.9 678370.8 527123.0 476674.2 473592.3

C

Ca2q

Mg 2q Naq

Volcanic 0.69 13.00 0.10 Volcanic 0.48 6.18 0.28 Volcanic 0.73 7.91 1.15 Volcanic 145.81 100.00 31.00 Carbonate 0.36 75.70 22.90 Alluvium 0.31 22.30 6.82 Volcanic 25.19 6.90 1.50 Carbonate 0.54 75.40 29.70 Volcanic 0.72 23.00 7.75 Volcanic 0.36 31.30 9.60 Alluvium 6.48 29.70 4.41 Volcanic 0.66 6.65 0.69 Volcanic 1.36 3.62 0.40 Alluvium 0.54 13.90 0.87 Carbonate 0.39 51.00 18.00 Carbonate 0.35 40.00 20.00 Carbonate 0.59 46.30 24.40 Carbonate 0.87 69.10 17.00 Carbonate 0.47 39.00 18.00 Volcanic 1.30 30.90 8.28 Volcanic 0.82 25.50 4.34 Volcanic 0.51 30.80 7.82 Volcanic 0.28 27.80 6.81

Kq

Cly

SO42y

HCOy SiO 2 3

pH pH Temp Žfield. Žlab. Ž8C.

141.00 0.20 7.70 0.10 400.00 30.00 7.90 59.40 1.78 11.80 82.60 111.00 51.00 8.23 30.30 8.39 7.60 15.80 78.10 48.00 – 8.40 1.80 16.00 180.00 201.00 13.00 7.00 36.80 6.77 10.60 58.80 370.00 31.00 – 48.30 9.25 6.40 20.00 209.00 78.00 – 11.70 6.56 2.40 6.60 57.40 56.00 – 127.00 14.00 83.60 65.50 587.00 30.00 – 50.20 4.99 11.90 41.60 161.00 60.00 – 38.30 7.88 19.60 28.00 181.00 65.00 – 227.00 9.72 77.10 174.00 376.00 63.00 7.75 60.70 1.39 14.90 19.40 134.00 53.00 6.90 58.50 2.12 14.00 23.70 111.00 46.00 8.66 96.30 4.16 18.40 92.00 150.00 41.00 8.13 71.00 8.00 22.00 80.00 300.00 20.00 7.30 72.00 8.60 22.00 81.00 278.00 25.00 8.20 4.50 1.22 3.80 16.40 281.00 13.00 8.21 1.90 0.58 1.60 8.50 294.00 7.00 – 32.00 6.80 9.70 3.40 231.00 31.00 8.10 12.30 5.63 11.70 11.40 135.00 59.00 7.60 24.90 5.22 9.90 14.10 136.00 48.00 6.90 16.40 1.66 6.40 26.80 127.00 38.00 6.89 15.60 1.47 5.20 19.60 125.00 33.00 6.94

– 8.03 7.72 7.70 7.65 7.79 6.94 6.58 8.05 7.54 8.19 7.84 8.38 8.20 – – 8.05 8.12 – 7.90 7.80 7.75 7.81

31.1 27.0 26.8 25.0 23.0 26.9 16.0 36.4 38.0 16.0 23.0 22.0 30.0 26.0 27.0 33.0 25.2 10.0 31.0 16.0 18.0 12.0 11.0

J.S. Contardi et al.r Journal of Contaminant Hydrology 47 (2001) 323–333

Sample name

WellrSpring location

K AX — Am Žmlrm2 .

K AX — Np Žmlrm2 .

K AX — Pu Žmlrm2 .

K AX — Th Žmlrm2 .

K AX — U Žmlrm2 .

Surface area Žm2 rl.

Surface area Žm 2 rg.

F

UE19c NTS Water Well 20 NTS Well 8 NTS Whiterock Spring NTS UE16d NTS Well A NTS Topopah Spring NTS Well C-1 NTS Well 4 NTS Cane Spring NTS Beatty Well 2 Lower Indian Spring Indian Spring Well Lathrop Wells Fairbanks Spring Crystal Pool Indian Springs Cold Creek Spring Ash Springs Pahroc Spring Sidehill Spring Peavine Ranch Well Peavine Canyon Campground Spring

3783 4814 6151 130778 3133 3809 240688 1226 7186 3641 709492 2185 882276 4733 2481 3734 4052 18239 4654 5469 3048 2243 1787

4.7 13.8 7.5 1.9 5.1 6.7 1.7 0.8 6.3 5.4 5.6 1.5 16.8 11.2 3.0 5.9 9.4 14.2 7.4 6.2 1.6 1.5 1.7

384.5 1133.2 735.7 164.4 372.7 553.7 174.5 62.1 713.3 468.6 402.6 148.9 1454.4 892.0 256.6 566.9 636.2 765.1 637.3 563.0 149.5 147.2 164.8

329.4 352.3 376.2 4410.1 435.1 371.1 3462.2 427.4 259.9 521.1 1497.2 474.1 349.7 369.6 411.4 294.7 373.7 644.8 320.1 530.8 570.5 613.2 568.6

0.2 4.3 16.9 4.4 0.4 1.6 48.9 0.6 1.5 4.9 0.3 12.7 2.3 2.2 1.2 0.3 0.4 0.6 0.7 9.4 14.9 20.9 21.3

0.27 0.23 0.34 3.66 0.21 0.24 2.84 0.22 0.37 0.23 2.64 0.22 0.70 0.23 0.20 0.20 0.21 0.45 0.26 0.32 0.37 0.17 0.01

1184.34 1184.34 1184.34 1182.07 1162.40 1255.40 153.77 1162.40 1184.34 1184.34 1255.40 1184.34 1184.34 1255.40 1162.40 1162.40 1162.40 1162.40 1162.40 1184.34 1184.34 1184.34 153.77

592.17 592.17 592.17 591.04 581.20 627.70 76.89 581.20 592.17 592.17 627.70 592.17 592.17 627.70 581.20 581.20 581.20 581.20 581.20 592.17 592.17 592.17 76.89

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Table 2 Estimated sorption parameters for AmŽIII., NpŽV., PuŽV., ThŽIV., and UŽVI.. Calculated for site-specific water chemistries given in Table 1 using the DLM with parameters given in Turner Ž1995., Pabalan and Turner Ž1997., and Turner et al., Ž1998.

327

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elsewhere ŽTurner, 1995; Pabalan and Turner, 1997; Turner et al., 1998; Turner and Pabalan, in press.. The two most important chemical parameters controlling actinide sorption behavior are pH and carbonate concentration ŽTurner et al., 1998.. Calculated values for K AX are given in Table 2. For the site-specific colloid fraction relative to the geologic medium, AX was estimated by assuming spherical colloidal particles with a radius at the midpoint of a given filter size fraction in Kingston and Whitbeck Ž1991. Žfour sizes from 30 nm to ) 1 mm.. Colloid density was assumed to be related to the lithology of the aquifer such that r volcanic s 2.65 grcm3 , rcarbonate s 2.7 grcm3, and ralluvium s 2.5 grcm3 ŽMohanty and McCartin, 1998.. The final column of Table 2 is the F factor in Eq. Ž5., calculated assuming a constant surface area of 2 m2rg for the geologic medium. This value is at the lower limit of the range Ž2 to 10 m2rg. reported for the volcanic tuffs at YM ŽTriay et al., 1997., and from the point of view of the effects of colloid transport, can be considered to be conservative Ži.e., higher values of F would result in greater impacts of colloid transport.. A value for the porosity, f , of 0.5 cm3rcm 3 was assumed to minimize the effective retardation coefficient Ža conservative approach.. Using Eq. Ž2., a general reference model was drawn for F s 590 Žsimilar to most of the values in Table 2 and represented by lines in Fig. 1.. It can be noted that for C s 0 mgrl, the model produces a straight line that is

Fig. 1. Effective retardation factors calculated using Eq. Ž2.. Reference model Žlines. is for F s 590. Symbols represent site-specific calculations using colloid concentrations in Table 1 and sorption parameters given in Table 2.

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the standard R F given in Eq. Ž1.. As colloid concentration increases, R F,eff decreases. As K D increases, the effect is more pronounced, but for a given colloid concentration, R F,eff becomes insensitive to K D above a threshold value. The value of R F,eff was calculated for each sample of Kingston and Whitbeck Ž1991. using the radionuclide sorption coefficient calculated for the reported water chemistry, the measured colloid concentration, and the empirical parameter F assuming spherical particles. Where data were reported, field pH was used in preference to lab pH. Water temperatures were used to model aqueous speciation, but due to uncertainties in temperature effects, DLM parameters for T s 258C were used for sorption reactions. The results are superimposed on the reference model as symbols in Fig. 1. It is important to note that the reference model was calculated using a constant value of F s 590, so the comparison to the site-specific calculations is not direct. The effect of colloids is calculated to be most significant for the highly sorbing radionuclides AmŽIII. and ThŽIV., reducing R F,eff by as much as five orders of magnitude over the colloid-free case. The effect is somewhat less pronounced for PuŽV., and almost nonexistent for poorly sorbing radionuclides such as NpŽV. and UŽVI., except at the very highest reported colloid concentrations, C s 145 mgrl, where reduction is at most half an order of magnitude. It is important to note that this study considers colloidal transport of PuŽV. rather than the more strongly sorbing PuŽIV..

3. Sensitivity analyses with TPA version 3.2 Mechanistic models of colloidal transport predict a reduction in radionuclide R F . Sensitivity analyses can be used to determine the effect of these reductions on repository performance. The NRC and the Center for Nuclear Waste Regulatory Analyses ŽCNWRA. have developed the total-system performance assessment ŽTPA. computer code version 3.2 1 for the deep geologic repository at YM ŽMohanty and McCartin, 1998.. Fig. 2 represents the TPA version 3.2 computer model flow diagram for YM. Currently colloidal transport is not modeled in the TPA code. To quantify and evaluate the potential dose contributed by colloidal transport at the YM site, two sensitivity trials were conducted. The first trial consisted of plutonium, 239 Pu and 240 Pu, alone. The second trial simulated colloidal transport of plutonium and americium with the other radionuclides tracked in TPA version 3.2. Both trials were compared against the base case scenario. To simulate colloid transport, the TPA version 3.2 model was modified such that no retardation was assumed for plutonium and americium in the saturated zone such that these radioelements were considered as non-sorbing and non-diffusing solutes. Also in keeping with the base case scenario, predominantly fracture flow was assumed for the unsaturated zone, and fracture flow was assumed in the saturated zone except for approximately 10 km of alluvium ŽMohanty and McCartin, 1998.. A conservative solubility limit for plutonium was simulated with a uniform probability distribution 1

Use of a particular approach, model, or parameter in TPA 3.2 should NOT be construed as regulatory acceptance.

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Fig. 2. Flow Diagram for Total-System Performance Assessment ŽTPA. Version 3.2 Code ŽMohanty and McCartin, 1998..

function ranging from 2.4 = 10y3 to 2.4 = 10y1 mgrml ŽMohanty and McCartin, 1998; TRW Environmental Safety Systems, 1995.. Therefore, the sensitivity trials did not have an explicit colloid model but instead allowed the entire released amount of plutonium and americium to travel unretarded at the velocity of the groundwater.

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Fig. 3. The effect of plutonium and americium colloidal transport peak mean annual TEDE at Yucca Mountain, simulated using TPA version 3.2 Žsolid line.. Transport modeled assuming non-sorbing and non-diffusing solute with complete suite of base case scenario radionuclides. All other parameters consistent with base case scenario ŽMohanty and McCartin, 1998.. Peak mean annual TEDE from only plutonium colloidal transport Ždashed line.. The base case results shown with the short dashed line.

For a compliance period of 10,000 years the sensitivity trials revealed that plutonium and americium colloidal transport contributed less than 0.1 mremryear peak mean total effective dose equivalent ŽTEDE.. This contribution of dose during the compliance period is indistinguishable from the base case scenario. For the case with plutonium alone, the TEDE rises rapidly to a maximum of 69.0 mremryear at 46,400 years ŽFig. 3. as container failures increase at longer times.2 For the case with both americium and plutonium the TEDE continues to rise and levels off at approximately 73.8 mremryear at 44,700 years. At these peak values the colloidal contribution to dose from americium and plutonium raises the mean peak TEDE relative to the base case by a factor of 60 ŽFig. 3.. Comparison of the results from the two trials reveals that plutonium will dominate the dose contribution from colloidal transport of americium and plutonium.

2

Insights and assertions are preliminary, parameter and model refinement is continuing, and preliminary outputs are based on limited analysis.

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These sensitivity trials were performed to provide a conservative bound for colloidal transport at YM. Although colloid transport faster than the mean groundwater velocity have been experimentally measured ŽReimus et al., 1995., this hydrodynamic chromatographic effect was not taken into account. Typically when colloids travel faster than the mean groundwater velocity the colloids are large and remain in the center of fractures and flowpaths. The larger colloids will therefore have a larger filtration rate compared to smaller colloids, and a lower fraction of radionuclides attached due to the lower specific surface area. Since filtration was neglected for the trials, the inclusion of plutonium and americium transport velocities greater than the average flow velocity might be overly conservative. The sensitivity trials were performed to bound the dose effects of colloidal movement at the YM site. The results indicate that, relative to the TPA version 3.2 base case, there is no dose impact within a 10,000 years compliance period using a conservative Ano retardationB Ž R F s 1. approach to modeling colloidal transport. Mechanistic modeling using site-specific information on chemistry and natural colloid concentration of groundwaters in the vicinity of YM suggest that although radionuclide retardation is reduced by colloid transport, retardation is still significant compared to the conservative values assumed in the PA sensitivity analysis. Further sensitivity trials using insights from the mechanistic modeling could provide a more realistic assessment of the potential impact of colloids on repository performance.

4. Conclusions Abstraction of mechanistic modeling results based on site-specific data suggest that R F values used to model radionuclide transport may be reduced by several orders of magnitude by reversible sorption onto transported colloid particles. The radionuclides most affected by colloid transport were strongly sorbing radionuclides such as americium and thorium. Weakly sorbing radionuclides like uranium and neptunium showed little effect on transport. Sensitivity analyses using the current TPA code suggest that transport of nonsorbing, nondiffusing colloids of plutonium and americium does not affect peak mean TEDE relative to the base case over a compliance period of 10,000 years, although this is sensitive to container life predicted in the base case scenario. At longer time periods there may be a 60-fold increase in peak mean TEDE due to colloid transport. Additional modeling studies are necessary to evaluate the effects on performance of enhanced radionuclide transport by colloids, and the effect of irreversible radionuclide sorption onto colloidal material.

Acknowledgements This paper does not necessarily reflect the position or views of the Nuclear Regulatory Commission. The authors would like to thank Budhi Sagar, Roberto Pabalan, and Bret Leslie for their careful reviews of this manuscript.

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