Modeling the Effects of Microbial Competition and Hydrodynamics

Domain. To explore the general sensitivity of NAPL dissolution to microbial competition, a saturated porous medium (Table 1) with one-dimensional flow...
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Environ. Sci. Technol. 2009, 43, 870–877

Modeling the Effects of Microbial Competition and Hydrodynamics on the Dissolution and Detoxification of Dense Nonaqueous Phase Liquid Contaminants J E N N I F E R G . B E C K E R * ,† A N D ERIC A. SEAGREN‡ Departments of Environmental Science and Technology and Civil and Environmental Engineering, University of Maryland, College Park, Maryland 20742

Received June 12, 2008. Revised manuscript received November 3, 2008. Accepted November 10, 2008.

The real significance and engineering potential for bioenhanced dissolution of chlorinated ethene dense nonaqueous phase liquid (DNAPL) contaminants are currently not well understood, in part because they can be influenced by a complex set of factors, including microbial competition for growth substrates. Mathematical simulations were performed to evaluate the effects of competition between Dehalococcoides ethenogenes and Desulfuromonas michiganensis for the electron acceptor tetrachloroethene (PCE) on the distribution of dehalorespirers, PCE dissolution, and the extent of PCE detoxification. The modeling results demonstrate that the outcomeofcompetitionbetweenpopulationsforgrowthsubstrates can have a significant impact on bioenhancement and, thus, on DNAPL source zone longevity and identify the key factors in determining the outcome of competition and its effects on DNAPL dissolution. The potential for bioenhancement is greatest at lower groundwater velocities. At higher velocities, kinetic properties play a key role in determining which population dominates and where, and the amount of bioenhancement that is realized. Engineered bioremediation techniques that maintain multiple dehalorespiring populations may offer the best approach for optimizing the twin cleanup goals of reduced source zone longevity and complete detoxification while maximizing the utilization of added electron donors.

Introduction The common groundwater contaminants tetrachloroethene (PCE) and trichloroethene (TCE) were released into the subsurface at many sites in the form of dense nonaqueous phase liquids (DNAPLs). A promising in situ technology for remediating DNAPL source zones is NAPL dissolution bioenhancement (1), which occurs primarily because biodegradation acts as a reaction sink for the dissolved contaminant. As a result, the contaminant concentration gradient at the interface and, thus, the driving force for NAPL dissolution increases. Bioenhanced NAPL dissolution has been examined theoretically (2-7) and demonstrated in laboratory (8-15) and field studies (16, 17). * Corresponding author phone: (301)405-1179; fax: (301)314-9023; e-mail: [email protected]. † Department of Environmental Science and Technology. ‡ Department of Civil and Environmental Engineering. 870

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Nevertheless, the real significance of this bioenhancement effect and the potential for engineering the phenomenon are not yet fully understood (18). Theoretical analyses predict that a number of interrelated physicochemical (e.g., advection, dispersion, NAPL composition, and abiotic dissolution rate, reactive zone length) and biological (e.g., biokinetics, electron donor supply) factors may influence the extent to which NAPL dissolution can be bioenhanced by an increased concentration gradient (2-4). For example, if the biodegradation rate is relatively slow compared to the rate of dissolution or advection, the bioenhancement effect may be minor (2, 3). Biodegradation kinetics may be controlled by a number of factors. In particular, the biodegradation rate is a function of the contaminant concentration near the NAPL source (12). Low concentrations could be caused by a high rate of groundwater flow or multicomponent NAPL mixtures and result in relatively slow biokinetics and a small bioenhancement effect. In DNAPL source zones, chlorinated ethene concentrations may approach saturation levels. Bioenhanced dissolution of PCE DNAPLs has been observed under these conditions (10, 11, 13, 15). However, PCE dechlorination by some pure dehalorespiring cultures is inhibited at high concentrations of the contaminant, e.g., ref 19. The impact of biodegradation on dissolution could potentially be limited if this inhibitory effect of PCE on biodegradation kinetics is also observed in the field (5, 12). The kinetic characteristics of different chlorinated ethenerespiring bacteria also vary. For example, members of the genus Dehalococcoides (such as Dhc. ethenogenes strain 195) are thought to be key to achieving complete detoxification of PCE to ethene at contaminated sites (20). However, Dehalococcoides strains appear to utilize chlorinated ethenes more slowly compared with other dehalorespirers that transform PCE to TCE or dichloroethenes (DCEs) (21). Thus, different dehalorespiring populations could potentially bioenhance dissolution to varying degrees if biokinetics are the rate-limiting process. Multiple dehalorespiring populations, including Dehalococcoides strains and/or PCE-to-DCE-dechlorinating populations such as Desulfuromonas michiganensis, may be indigenous or added to many contaminated sites through bioaugmentation, e.g., refs 22, 23. Becker (21) demonstrated that under biostimulation conditions, competition for limiting amounts of electron acceptors (chlorinated ethenes) among multiple dehalorespirers in a continuous-flow stirred tank reactor (CSTR) could cause them to function as PCEto-DCE or DCE-dechlorinating specialists. In a contaminated aquifer, such specialization could result in spatial separation of dehalorespiring populations. Competition for H2 or other electron donors can also occur among dehalorespirers or between dehalorespirers and other populations (24). If competition for electron donors (5) or electron acceptors influences the activities of different dehalorespirers at the NAPL-water interface, then it could potentially be a key factor in determining how much bioenhancement can be achieved. The underlying hypothesis of this study is that competitive interactions among dehalorespiring populations can affect their biomass and distribution in contaminant plumes containing DNAPL source zones and their abilities to bioenhance dissolution and detoxify aqueous contaminants. Mathematical simulations demonstrate that competitive interactions between key PCE-respiring populations may impact DNAPL dissolution and contaminant detoxification, but the magnitude of these effects is influenced by site hydrodynamics and substrate availability. The potential for bioenhancement is greatest at lower groundwater velocities. 10.1021/es801616f CCC: $40.75

 2009 American Chemical Society

Published on Web 01/06/2009

TABLE 1. Aquifera and DNAPL Parameter Values for the Cells-in-Series Model Simulations value

reference

Aquifer Property Darcy velocity, qx porosity, n dispersivity, Rx lateral extent of contaminated region, L diameter of contaminated region, d initial residual saturation of PCE, Sn0

0.00033 or 0.033 m/h 0.381 0.06 m 30 cm 2.5 cm 0.13

assumed 26 assumed 11 11 27

PCE Property aqueous diffusion coefficient, D0 solubility, As b mass transfer coefficient correlation

9.0 × 10-6 cm2/s 150 mg/L Supporting Information eq S-1

calculated using the Wilke-Chang equation (38) 39 27

a Aquifer properties reported here and in the Supporting Information are based on Wagner soil mix no. 1 from the Fort Wayne moraine (26). b The aqueous solubilities of the lesser chlorinated ethenes were also obtained from ref 39.

FIGURE 1. Schematic of spill scenario and model domain. At higher velocities, the biodegradation kinetics of the dominant population at the NAPL-water interface strongly influence the amount of bioenhancement that occurs. In general, maintenance of multiple dehalorespiring populations may offer optimal bioenhancement of DNAPL dissolution, detoxification of aqueous contaminants, and electron donor utilization.

Modeling Approach Domain. To explore the general sensitivity of NAPL dissolution to microbial competition, a saturated porous medium (Table 1) with one-dimensional flow was used to approximate the concentration profiles in a remediation scheme, such as illustrated in Figure 1. The DNAPL is initially PCE and present as a residual saturation (Sn0 ) 0.13) of uniformly distributed immobilized blobs (25-28). Conceptual Model of Competition. In the selected competition scenario, Dhc. ethenogenes competes with a Dsm. michiganensis strain for the electron acceptors PCE and TCE (see Supporting Information Figure S-1). Dsm. michiganensis strains and a related organism can dehalorespire chlorinated ethenes using acetate, but not H2, as the electron donor (29, 30). Therefore, Dhc. ethenogenes and Dsm. michiganensis do not compete for the electron donor. This competition scenario could be quite common because H2 and acetate are both produced from the fermentation of lactate and other organic substrates, which are often added to contaminant plumes as part of an engineered bioremediation approach. Model. The advection-dispersion-reaction (ADR) equation can be used to develop a modeling framework for understanding the complex interactions between microbial competition and NAPL dissolution bioenhancement. For the

model domain described above, the transport of dissolved chlorinated ethenes in saturated, isotropic porous media can be described using the following nonsteady-state form of the one-dimensional ADR equation for a homogeneous medium with steady flow in the x direction: ∂2Ai ∂Ai ∂Ai P - Ai) ) Dx 2 - vx + Kl,i(Xn,iAeq,i ∂t ∂x ∂x Si qmaxX KS,i + Si

(

)(

Ai KA,i + Ai

)

(1)

in which the parameters are defined as listed in the Notation section of the Supporting Information. The processes on the right-hand side of eq 1 represent longitudinal macropore dispersion, advection, rate-limited NAPL dissolution, and biodegradation. NAPL dissolution is represented by a singleresistance model with a linear driving force, e.g., ref 28. The rates of reductive dehalogenation of chlorinated ethenes are assumed to follow dual Monod kinetics, e.g., ref 31, the bacteria are assumed to be immobilized, and the biokinetics are a function of the macroscopic biomass and bulk-fluid substrate concentrations (32). To complete the description of the system, eq 1 is coupled with mass-balance equations for the electron donor and biomass (including microbial growth and decay), which are not shown in the interest of brevity. Equation 1 can be transformed to a nondimensional form (2, 3) using the dimensionless numbers defined in Table 2 and by defining t* ) (tvx)/Lx; x* ) x/Lx; A* ) Ai/Aeq,i; S* ) * * ) KS,i/S0; and KA,i ) KA,i/Aeq,i, where Lx Si/S0; X* ) X/X0; KS,i ) domain length in the x-direction [L], Aeq,i ) aqueous concentration of component i at thermodynamic equilibrium VOL. 43, NO. 3, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 2. Definition and Significance of the Dimensionless Numbers significance with respect to rate-limiting process symbol dimensionless numbers comparing mass transfer rates

a

advection is slower than dispersion

dispersion is slower than advection

mass-transfer (dissolution) is slower than advection

advection is slower than dissolution from NAPL

Da2 (Damko¨hler no. 2)

biodegradation rate/ advection rate ) (qmaxX0Lx)/(Aeq,ivx)

slow advection of substrate limits biodegradation

Da3 (Damko¨hler no. 3)

biodegradation rate/ NAPL dissolution rate ) (qmaxX0)/(Kl,iAeq,i)

biodegradation is slower than advection (little potential for bioenhancement) biodegradation is slower than dissolution (little potential for bioenhancement)

slow dissolution of contaminant from NAPL limits biodegradation

From ref 40.

FIGURE 2. Total PCE dissolution across the domain in simulations 1 (qx ) 0.00033 m/h, abiotic) and 5 (qx ) 0.00033 m/ h, biostimulation with both populations active) and total biodegradation of PCE across the domain by Dhc. ethenogenes and Dsm. michiganensis in simulation 5. with the NAPL [MsoluteL-3], S0 ) influent electron donor concentration [ML-3], and X0 ) the initial biomass concentration [MbiomassL-3], giving, ∗

2 ∗

∗

(

∗

1 ∂A ∂A S ∂A ) + St(1 - A∗) - Da2X∗ ∗ ∂t∗ Pe ∂x∗2 ∂x∗ KS,i + S∗

(

)

∗

)

A (2) ∗ KA,i + A∗

The dimensionless parameters in Table 2 are useful because they can be used to quantitatively compare the relative rates of key phenomena affecting bioenhanced dissolution, e.g., refs 2, 3. For example, Da3 represents the ratio of the biodegradation rate to the NAPL dissolution rate. If Da3 > 1, it means that biodegradation is relatively fast compared to NAPL dissolution and, thus, the potential for biodegradation of aqueous-phase contaminants to bioenhance NAPL dissolution is high. If Da3 < 1, it indicates that the biodegradation rate is slower than the rate at which the NAPL-phase contaminant dissolves and the potential for bioenhancement is limited. The dimensionless parameter values are calculated using the kinetic parameters for PCE (Supporting Information Table S-1). As defined in Table 2, the dimensionless numbers are based on initial conditions, 872

dimensionless number > 1

advection rate/ dispersion rate ) vxLx/Dx mass-transfer rate/ advection rate ) Kl,iLx/vxa

St (Stanton no.)

dimensionless numbers comparing biodegradation and mass transfer rates

dimensionless number < 1

definition

Pe (Peclet no.)

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but their values were subject to change as biomass concentrations and NAPL saturation and composition evolved temporally. A cells-in-series model was used to simulate the transient one-dimensional contaminant transport described by eqs 1 and 2. This approach has been used to model transport of dissolved material in groundwater flow and other systems, e.g.. ref 33. It involves dividing the model domain into a network of completely mixed cells through which water and dissolved constituents are transported. A cells-in-series approach was adopted in this study because it allowed us to readily adapt and expand an existing model that described biodegradation of dissolved chlorinated ethenes in a CSTR (21). However, it is important to note that when utilizing and interpreting the predictions of a cells-in-series model, it is particularly critical to evaluate the ability of the model to accurately describe key mass transfer and transport processes. A series of checks that was conducted to verify the performance of the model used in this study is described in Section S-IV of the Supporting Information. An alternative modeling approach is to numerically solve eq 1 and the conservation of mass equations for biomass and electron donors (not shown) simultaneously. In this study, advective contaminant transport through the cells was described by assuming a constant Darcy velocity, qx [LT-1], and calculating the average pore water velocity, vx[LT-1], as follows: vx )

qx nSw

(3)

where n ) porosity; Sw ) water saturation ) 1 - Sn. It was necessary to account for Sw because not all of the pore volume was available for water flow due to the NAPL blobs. As Sn changed with NAPL blob dissolution, Sw and vx changed accordingly. Dispersive transport was incorporated via the “implicit dispersion” inherent in the cells-in-series model (34). The relative magnitude of dispersion compared to advection is characterized by Pe (Table 2). Based on a comparison of the variance of the nonreactive tracer output curve with a pulse tracer input for the cells-in-series model (i.e., equal cells without exchange flow) and the advection/dispersion model, Levenspiel (35) developed a reactor performance criterion to describe the relationship between the number, j, of equally sized, perfectly mixed cells and the Pe of a dispersed flow reactor, which can be approximated as (34) Pe ) 2j - 1

(4)

The model developed by Becker (21) was adapted to simulate competition between two PCE-respirers, Dhc. ethenogenes

TABLE 3. Conditions Used in the Model Simulations model conditions simulation

treatment scenario

a

Darcy velocity, qx, (m/h)

electron donor level

populations present

none 5 µM acetate 5 µM H2 5000 µM acetate 5000 µM H2 5000 µM acetate 5000 µM H2 none 5 µM acetate 5 µM H2 5000 µM acetate 5000 µM H2 5000 µM acetate 5000 µM H2

none Dsm. michiganensis Dhc. ethenogenes Dsm. michiganensis Dhc. ethenogenes Dsm. michiganensis Dhc. ethenogenes none Dsm. michiganensis Dhc. ethenogenes Dsm. michiganensis Dhc. ethenogenes Dsm. michiganensis Dhc. ethenogenes

1 2

abiotic intrinsic

0.00033 0.00033

3 4 5

biostimulation biostimulation biostimulation

0.00033 0.00033 0.00033

6 7

abiotic intrinsic

0.033 0.033

8 9 10

biostimulation biostimulation biostimulation

0.033 0.033 0.033

and Dsm. michiganensis, as described above. Reductive dehalogenation is modeled using dual-Monod kinetics (eq 1). Dsm. michiganensis was recently shown to be inhibited at PCE concentrations >560 µM (19). However, bioenhanced dissolution has been observed at PCE concentrations at or near saturation in several relevant studies involving mixed cultures in columns or tanks (10, 11, 13, 15). Growth of Dehalococcoides strains close to a PCE DNAPL has also been observed (13). Therefore, inhibition terms were not included for the chlorinated ethenes, following the approach used successfully in several studies, e.g., ref 31. The net biomass growth terms incorporate decay (21, 31). Dehalogenation of PCE and TCE contributes to the growth of both organisms. Dhc. ethenogenes also uses DCE as a growth substrate, but not vinyl chloride (VC), which it cometabolizes (36). To simulate a completely mixed biofilm reactor, only growth and decay of biofilm biomass within each cell were incorporated. Advection of biomass between cells was not allowed. To model dissolution of the entrapped DNAPL blob source term and repartitioning of chlorinated ethenes back into the DNAPL, the NAPL dissolution source term in eq 1 was adapted according to, P - Ai) R ) VwKl,j(Xn,iAeq,i

(5)

where R ) the DNAPL source dissolution rate [MsoluteT-1], and Vw ) the reactor pore-water volume [L3]. Unless noted otherwise, Kl,i was calculated within each cell by applying a general correlation for transient NAPL dissolution rates (27), as described in Section S-III of the Supporting Information. Changes in NAPL composition were incorporated by allowing partitioning of chlorinated ethenes back into DNAPL, and changes in interfacial area were modeled by tracking changes in the volumetric fraction of NAPL and incorporating the value into the transient mass-transfer coefficient correlation. The bioenhancement of DNAPL dissolution represented in eq 5 can be quantified using a bioenhancement factor, E, similar to that defined by Seagren et al. (3). Here, E is the ratio of the DNAPL source dissolution rate with biodegradation, Rbiotic, to the dissolution rate without biodegradation, Rabiotic: E)

Rbiotic Rabiotic

(6)

Model Application. Experimental results (25, 26) and an analytical solution (2) were used to verify the model results under steady-state and transient conditions, with and without biological activity, as described in Section S-IV of the Supporting Information. Application of the full model for quantifying the effect of competitive interactions on the

bioenhancement of DNAPL dissolution was performed using the porous media and contaminant properties in Table 1 and the biokinetic parameters given in the Supporting Information Table S-1. The advection rate corresponding to these parameters was relatively fast compared to the dispersion rate, as indicated by a Pe of 5. Based on this Pe and eq 4, j ) 3 cells were used. The initial concentration of each population was assumed to be 0.015 mg volatile suspended solids (VSS)/L (37). H2 and acetate are common intermediates of anaerobic metabolism and were provided as electron donors in equimolar amounts. Ten different scenarios were simulated (Table 3) under transient conditions to evaluate the effects of biological activity on DNAPL dissolution under two sets of hydrodynamic conditions. To assess the effects of microbial competition on the bioenhancement of DNAPL dissolution, the scenarios with biological activity differed with respect to the populations of dehalorespirers that were present. Further, the competition effects were evaluated with low and high influent electron donor concentrations, reflecting conditions in intrinsic bioremediation and biostimulation scenarios, respectively. In addition, application of the model was demonstrated through comparison with the experimental results of Yang and McCarty (11) using the parameters given in Section S-V of the Supporting Information.

Results and Discussion Cells-in-Series Model Analysis at Low qx (0.0033 m/h). Under abiotic conditions at the low velocity (simulation 1, Table 3), the NAPL dissolution rate was relatively fast compared to advection, as indicated by the St of 76, based on the Kl,PCE value of 0.25 h-1 predicted by the transient mass transfer coefficient correlation (eq S-1, Supporting Information). Under these conditions, the aqueous PCE concentration increased very rapidly along the domain, and essentially reached equilibrium conditions by cell 2 (Supporting Information, Figure S-3). Correspondingly, the PCE dissolution rate rapidly stabilized at a relatively low value (Figure 2). Therefore, most of the dissolution occurred at the upstream end of the domain in cell 1. Even so, Sn changed less than 0.5% after 780 h in cell 1. When biodegradation of chlorinated ethenes was incorporated into the model, the degree of bioenhancement of the PCE dissolution rate depended on the magnitude of the biodegradation rate compared to the advection rate, as reflected by Da2, and the magnitude of the biodegradation rate compared to the dissolution rate, as reflected by Da3. At the low velocity and intrinsic (low) electron donor levels, biodegradation was the overall rate-limiting process for both populations (as indicated by Da2 and Da3), and we expected VOL. 43, NO. 3, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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biodegradation to have little or no effect on the dissolution rate (2). Specifically, Da2 and Da3 were both initially on the order of 10-2 or less for Dhc. ethenogenes and Dsm. michiganensis, assuming an Aeq,i equal to the PCE solubility for the initial conditions. Furthermore, under intrinsic conditions, Dsm. michiganensis and Dhc. ethenogenes are very electron donor-limited. Correspondingly, the PCE dissolution rates predicted under intrinsic bioremediation conditions (simulation 2; data not shown) were very similar to the abiotic dissolution rate presented in Figure 2 (simulation 1). After a brief initial bioenhancement of only about 4%, approximately 90% of the acetate and essentially all of the H2 were consumed, and after a short period of growth, the Dsm. michiganensis and Dhc. ethenogenes biomass decreased due to net decay in cells 2 and 3. Growth of both organisms continued in cell 1, but resulted in only 1% bioenhancement due to the limited availability of electron donors. Under biostimulation conditions with both populations active (simulation 5), the bioenhancement of the DNAPL dissolution rate was much greater than under intrinsic conditions because the higher electron donor concentrations resulted in faster biomass growth and PCE removal rates for both organisms (Figure 2). Initially, Dsm. michiganensis out competed Dhc. ethenogenes for most of the PCE and TCE because of its faster substrate utilization kinetics, resulting in rapid increases in the Dsm. michiganensis biomass (Figure 3) and the rates of PCE and TCE dechlorination rates by Dsm. michiganensis in all three cells. By 120 h, the total PCE dissolution rate reached a maximum (corresponding to 75fold bioenhancement; Figure 2) and started becoming mass transfer-limited, as indicated by Da2 and Da3 for Dsm. michiganensis exceeding 100 and 1, respectively, in all three cells. The high Dsm. michiganensis biomass concentration (Figure 3) rapidly depleted all of the acetate in each of the cells, causing the rates of PCE and TCE dechlorination by Dsm. michiganensis to decline. During the same simulation, Dhc. ethenogenes initially mediated only low levels of chlorinated ethene dechlorination in the three cells. However, as the Dsm. michiganensis biomass and PCE and TCE removal rates in cell 1 declined, Dhc. ethenogenes began out competing Dsm. michiganensis for the chlorinated ethenes (as shown for PCE in Figure 3) and became the dominant population. The large Dhc. ethenogenes population rapidly depleted H2 within cell 1. Subsequently, Dhc. ethenogenes activity was limited to cell 1 and controlled by the input of H2 into the domain. The results of the low velocity simulations highlight the important role that competition can play in determining how much dissolution bioenhancement can occur. Greater sustained levels of bioenhancement of the PCE dissolution rate were observed under biostimulation conditions when both populations were present (simulation 5) compared with PCE dissolution in the presence of either Dsm. michiganensis alone (simulation 3) or Dhc. ethenogenes alone (simulation 4). Figure 4A provides a snapshot comparison of the total PCE dissolution rate throughout the domain at the low velocity under the abiotic condition, with either Dhc. ethenogenes or Dsm. michiganensis present, and with the two dehalorespiring populations competing for PCE and TCE, during a period when mass transfer and biodegradation processes were at a pseudosteady-state. Analysis of the dimensionless parameters indicates that conditions were suitable for bioenhancement because biodegradation was limited by advection (i.e., electron donor supply), as indicated by Da2 . 1, and dissolution (i.e., electron acceptor supply), which is manifested in Da3 > 1. Specifically, at 708 h, Da2 ) 343 and Da3 ) 4.6 for Dsm. michiganensis in cell 2, and Da2 ) 626 and Da3 ) 8.9 for Dhc. ethenogenes in cell 1. The amount of bioenhancement achieved by each population acting individually was similar (E ) 22-25) because each population 874

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FIGURE 3. Dsm. michiganensis and Dhc. ethenogenes biomass and PCE dechlorination rates in simulation 5 (qx ) 0.00033 m/h, biostimulation with both populations active) in (A) cell 1, (B) cell 2, and (C) cell 3 as a function of time. was limited by electron donor availability. Interestingly, the greater bioenhancement effect observed in simulation 5 was not due to Dhc. ethenogenes activity, despite the fact that it became the dominant population in cell 1. Instead, it resulted from a change in the distribution of Dsm. michiganensis in the domain. After Dsm. michiganensis was out competed for PCE and TCE in the upgradient region (cell 1), acetate became available for downgradient biodegradation and enhanced dissolution of PCE by Dsm. michiganensis in cell 2. As a result, Dsm. michiganensis biomass levels rebounded after 275 h in cell 2 (Figure 3). Eventually the Dsm. michiganensis biomass in cell 2 approached a plateau, as did the total PCE dissolution rate (Figure 2). During this plateau, mass transfer processes were rate-limiting. These results suggest that, when applied to DNAPL source zones, biostimulation and bioaugmentation strategies should focus on increasing the abundance of heterotrophic PCErespiring populations like Dsm. michiganensis, as well as Dehalococcoides species. Becker (21) noted that Dsm. michiganensis and other organisms that specialize in the dechlorination of PCE to DCE (or TCE) can be beneficial because they generally have faster kinetics compared with Dehalo-

FIGURE 4. (A) Total PCE dissolution rate across the domain. Bioenhancement factors are given above the columns for scenarios with active dehalorespiring populations. (B) Distribution of chlorinated ethenes exiting the domain for abiotic dissolution scenarios and biostimulation scenarios with one or two active dehalorespiring populations. Simulation numbers are given in parentheses in x-axes labels. Values were recorded at a single point in time (at 708 h for qx ) 0.00033 m/h and at 492 h for qx ) 0.033 m/h). coccoides strains. Maintenance of dehalorespiring heterotrophs like Dsm. michiganensis may also be helpful because their ability to use acetate as an electron donor in regions where H2 levels are depleted will bioenhance PCE dissolution in a larger portion of the DNAPL source zone. Of course achieving PCE detoxification is also an important treatment goal when remediating DNAPL source zones. As shown in Figure 4B, nontoxic ethene was the dominant dechlorination product when bioremediation strategies that support active Dehalococcoides strains were used. DCE was the dominant product when Dsm. michiganensis was present alone, although this is not apparent in Figure 4B because some of the DCE partitioned back into the DNAPL where it could serve as a long-term contamination source. Thus, maintenance of multiple dehalorespiring populations that can utilize H2 and organic electron donors is also advantageous because it is most efficient in terms of utilizing the reducing equivalents from fermentable organic substrates and results in greater reductive dechlorination of aqueous chlorinated ethenes. Previous laboratory studies performed in columns or tanks at relatively slow average pore water velocities with mixed microbial cultures have shown a 2- to 13-fold bioenhancement of PCE DNAPL dissolution (10, 11, 13-15). These levels of bioenhancement are smaller than predicted in this study, probably due to three key factors. First, the simulations presented here did not include competition for electron donors by other acetotrophic and hydrogenotrophic organisms, which could potentially reduce the observed bioenhancement. Second, the biokinetics used here may not be relevant to the experimental conditions in previous studies. Finally, inhibition effects on chlorinated ethene biodegradation were not included in the simulations presented here but could conceivably have limited bioenhancement in the laboratory experiments. Importantly, the cells-in-series model simulations capture key trends in the dissolution rate of the DNAPL-contaminated column experiments of Yang and McCarty (10, 11), which were performed under conditions similar to those modeled here. For example, the effluent PCE concentration approached equilibrium concentrations in a steady-state control reactor and during the lag period in the electron donor-

supplied columns of Yang and McCarty (11). Equilibration of PCE in the NAPL and water phases is expected under these conditions (2) because in the absence of biodegradation, the rate of dissolution is rapid compared to the rates of PCE advection and dispersion in the column. This is reflected in the corresponding Pe and St values (87 and 80, respectively), which we determined using the parameters reported in Section S-V of the Supporting Information. Subsequently, the rate of dissolution in the electron donor-supplied columns increased relatively rapidly above the abiotic rate observed during the lag period to a maximum value before leveling off or slowly declining. The same trends in the bioenhancement effect were observed in simulations of the model domain used in the current study at the low qx, as shown by the simulation 5 dissolution rate in Figure 2. Our analysis of the dimensionless numbers indicates that the rapid increase in the amount of bioenhancement and its subsequent plateau predicted for both the columns of Yang and McCarty (11) and the model domain used in the current study, were due to a shift from a dissolution rate limited by biodegradation kinetics to one limited by mass-transfer processes. Correspondingly, the Da2 and Da3 values calculated for the columns of Yang and McCarty (11) increased from 0.3 and 0.004, respectively, to values that were greater than 1 (based on the assumptions reported in Section S-V of the Supporting Information). The simulations of the model domain used in this study also were consistent with the distribution of chlorinated ethenes measured by Yang and McCarty (11). PCE and DCE were the dominant chlorinated ethenes in the effluents of the columns inoculated with PCE-to-DCE dehalorespirers and Dehalococcoides (11, 14) and, along with ethene, were predominant in simulation 5, in which both Dsm. michiganensis and Dhc. ethenogenes were active. Cells-in-Series Model Analysis at High qx (0.033 m/h). At a qx of 0.033 m/h (representing higher velocity conditions that either occur naturally, due to pumping, or as a result of an aquifer flushing remedial scheme), the abiotic NAPL dissolution rate was still relatively fast compared to advection, as indicated by an initial St of 12.0 (based on Kl,PCE ) 4.0 h-1). However, the mass transfer rate under these conditions was not large enough relative to advection to achieve equilibrium VOL. 43, NO. 3, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 5. Total PCE dissolution rate across the domain as a function of time for scenarios 6s10 at qx ) 0.033 m/h. The model predictions for simulations 6 (abiotic) and 7 (intrinsic conditions) overlap and are indistinguishable. Additional information about the trends shown in this figure is provided in the text of the Supporting Information and Supporting Information Figure S-5. at any point in the domain. The abiotic dissolution rate was approximately 100 times larger than for the low qx case because the lower aqueous concentration created a greater driving force for dissolution (compare simulation 1 in Figure 2 with simulation 6 in Figure 5). Substantial changes in Sn resulted throughout the domain. When sufficient DNAPL blob source material was depleted, the dissolution rate declined with time. This effect was particularly noticeable under biostimulation conditions when both populations consumed aqueous PCE and further increased the dissolution rate (simulation 10; Figure 5). After leveling off between 180 and 228 h, the PCE dissolution rate declined with DNAPL depletion as Sn decreased more than 12% in all cells. The decrease in the dissolved electron acceptor concentration at the high qx also decreases the rate of biodegradation (eq 1). As a result, the biodegradation kinetics are slower relative to advection and mass transfer in comparison to the low qx case. For example, under intrinsic conditions (simulation 7, Table 3), the initial Da2 and Da3 were very small (∼10-6-10-4) for both organisms, assuming that Aeq,i equaled PCE solubility. The decrease in the rate of biodegradation limits its potential to enhance the dissolution rate. There was no substantial bioenhancement effect under intrinsic bioremediation conditions (simulation 7) compared with the abiotic case (simulation 6), as illustrated in Figure 5. As shown in Figure 4A, even under conditions that are optimal for bioenhancementsbiostimulation with both populations active (simulation 10)sthe bioenhancement during a period of pseudosteady-state was approximately 4.8 times the abiotic dissolution rate, compared with a bioenhancement effect of approximately 33-fold under the low velocity conditions (simulation 5). The trend of greater bioenhancement at lower qx for a given biomass concentration and biokinetic characteristics is consistent with the steady-state model predictions of Seagren et al. (2) and the experimental results of Glover et al. (15) for PCE at residual saturations (Sn) of 0.25 and 0.55. At the high qx, the magnitude of the bioenhancement effect depends on the biodegradation rate. This is evident in Figure 4A. The largest bioenhancement effects were observed in the presence of Dsm michiganensis, which utilizes PCE at a higher rate than Dhc. ethenogenes (21). Dsm. michiganensis primarily controlled the bioenhancement of dissolution in the presence of Dhc. ethenogenes (simulation 10), largely 876

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because Dsm. michiganensis′ faster PCE degradation kinetics allowed it to become the dominant population. The trends in the predicted dissolution rates over time at the high qx were similar to those observed in the low qx model simulations and in the laboratory experiments of Yang and McCarty (11). Mass transfer processes eventually limited the dissolution rate in simulations 8 and 10. For example, when the maximum dissolution rates were reached (at ∼200 h), Da2 exceeded 10 and Da3 exceeded 1 for Dsm. michiganensis. The presence of a Dehalococcoides strain was also beneficial under these conditions because it improved the fate of aqueous PCE by carrying out dechlorination of DCE and VC (Figure 4B). Thus, while its effects on the bioenhancement of DNAPL dissolution at high qx are relatively modest, the use of biostimulation may still be beneficial under these conditions because of its potential to positively impact the fate of aqueous PCE. At sites where DNAPL is present, engineered bioremediation strategies should endeavor to promote the growth of dehalorespirers like Dsm. michiganensis with fast PCE utilization kinetics to maximize bioenhanced DNAPL dissolution while sustaining Dehalococcoides to detoxify the lesser chlorinated ethenes. The results of these preliminary simulations demonstrate that the outcome of competition between populations for electron acceptor growth substrates can significantly impact the degree of bioenhancement and, thus, DNAPL source zone longevity, as well as affect the extent of detoxification. Hydrodynamics affect the outcome of competition. Organisms with relatively fast biokinetics appear to have a competitive advantage under higher velocity conditions. The modeling results at different qx also highlight the need to balance the effects of changing qx, biomass concentrations, and biokinetics, e.g., via pumping, biostimulation, and/or bioaugmentation as suggested by Seagren et al. (2). The modeling results presented here are also important because they show that biostimulation may be a less effective bioremediation strategy for enhancing DNAPL dissolution at high qx than at low qx. Although these simulations do not incorporate all of the complexity of actual field systems, they are useful for identifying the parameters that determine the outcome of competition and its impact on DNAPL dissolution. This information is needed to understand how biostimulation and bioaugmentation affect bioenhancement by stimulating different populations and develop bioremediation strategies that incorporate these treatment technologies while balancing the twin cleanup goals of reduced source longevity and complete detoxification.

Acknowledgments This research was supported by the National Science Foundation (NSF) through a PECASE award to J.G.B. under Grant No. 0134433 and a CAREER award to E.A.S. under Grant No. 0093857.

Supporting Information Available A figure depicting the conceptual model of competition; details on implementation of the cells-in-series model and the general correlation used to calculate transient NAPL dissolution rates; evaluations of the cells-in-series model performance through comparison with experimental data and an analytical solution; parameters used for application of the model to analyze the experimental results of Yang and McCarty (11); additional information on the model analysis at high qx; a summary of the biokinetic parameter values used in mathematical simulations; and the notation of the symbols used in the main text and/or the Supporting Information. This material is available free of charge via the Internet at http://pubs.acs.org.

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