Laboratory, Field, and Modeling Studies of Bioaugmentation Of

Advances in Water Resources 30 (2007) 1528–1546 www.elsevier.com/locate/advwatres

Laboratory, ﬁeld, and modeling studies of bioaugmentation of butane-utilizing microorganisms for the in situ cometabolic treatment of 1,1-dichloroethene, 1,1-dichloroethane, and 1,1,1-trichloroethane

Lewis Semprini a,*, Mark E. Dolan a, Maureen A. Mathias a, Gary D. Hopkins b, Perry L. McCarty b a Department of Civil, Construction and Environmental Engineering, Oregon State University, Apperson Hall 202, Corvallis, OR 97331-2302, United States b Department of Civil and Environmental Engineering, Stanford University, United States

Received 29 July 2005; received in revised form 10 April 2006; accepted 5 May 2006 Available online 18 September 2006

Abstract

A series of laboratory, field, and modeling studies were performed evaluating the potential for in situ aerobic cometabolism of chlorinated aliphatic hydrocarbon (CAH) mixtures, including 1,1,1-trichloroethane (1,1,1-TCA), 1,1-dichloroethane (1,1-DCA) and 1,1- dichloroethene (1,1-DCE) by bioaugmented microorganisms that grew on butane. A butane-grown bioaugmentation culture, primarily comprised of a Rhodococcus sp., was developed that effectively transformed mixtures of the three CAHs, under subsurface nutrient conditions. Microcosm experiments and modeling studies showed rapid transformation of 1,1-DCE with high transformation product toxicity and weak inhibition by butane, while 1,1,1-TCA was much more slowly transformed and strongly inhibited by butane. Field studies were conducted in the saturated zone at the Moffett Field In-Situ Test Facility in California. In the bioaugmented test leg, 1,1-DCE was most effectively transformed, followed by 1,1-DCA, and 1,1,1-TCA, consistent with the results from the laboratory studies. A 1-D reactive/transport code simulated the field responses during the early stages of testing (first 20 days), with the following extents of removal achieved at the first monitoring well; 1,1-DCE (97%), 1,1-DCA (77%), and 1,1,1-TCA (36%), with little or no CAH transformation observed beyond the first monitoring well. As time proceeded, decreased performance was observed. The modeling analysis indicated that this loss of performance may have been associated with 1,1-DCE transformation toxicity combined with the limited addition of butane as a growth substrate with longer pulse cycles. When shorter pulse cycles were reinitiated after 40 days of operation, 1,1-DCE transformation was restored and the following transformation extents were achieved; 1,1-DCE (94%), 1,1-DCA (8%), and 1,1,1- TCA (0%), with some CAH transformation occurring past the first monitoring well. Modeling analysis of this period indicated that the bioaugmented culture was likely not the dominant butane-utilizing microorganism present. This was consistent with observations in the indigenous leg during this period that showed effective butane utilization and the following extents of transformation: 1,1- DCE (86 %), 1,1-DCA (5%), and 1,1,1-TCA (0%). The combination of lab and field scale studies and supporting modeling provide a means of evaluating the performance of bioaugmentation and the cometabolic treatment of CAH mixtures. 2006 Elsevier Ltd. All rights reserved.

Keywords: Cometabolism; Modeling; Field tests; Bioaugmentation; Butane; 1,1-Dichloroethene, 1,1-Dichloroethane; 1,1,1-Trichloroethane; Inhibition; Transformation toxicity; CAH mixtures

1. Introduction

In situ aerobic cometabolism has been shown to be a method for reducing groundwater contamination with * Corresponding author. Fax: +1 541 7373099. chlorinated aliphatic hydrocarbons (CAHs) [26,12,21]. E-mail address: [email protected] (L. Semprini). Cometabolic transformation results from non-speciﬁc

Nomenclature

Parameter Definition X cell concentration on a pore volume basis (mg/L) KIc,DCE,BUT competitive inhibition constant of 1,1-DCE X0 initial cell concentration on a pore volume basis on butane (mg/L) (mg/L) KIc,DCA,BUT competitive inhibition constant of 1,1- Y cell yield (mg cells/mg butane) DCA on butane (mg/L) b cell decay coefficient (d1) KIc,TCA,BUT competitive inhibition constant of 1,1,1- Fa stoichiometric ratio of oxygen to butane for bio- TCA on butane (mg/L) mass synthesis (mg O2/mg butane) KIc,DCE,DCA competitive inhibition constant of 1,1-DCE VL liquid volume (L) on 1,1-DCA (mg/L) VG gas volume (L) 1 KIc,DCE,TCA competitive inhibition constant of 1,1-DCE Kla overall gas/liquid mass transfer coefficient (d ) on 1,1,1-TCA (mg/L) km DCE maximum transformation rate of 1,1-DCE (mg KIc,DCA,DCE competitive inhibition constant of 1,1- 1,1-DCE/mg cells-d) DCA on 1,1-DCE (mg/L) km DCA maximum transformation rate of 1,1-DCA (mg KIc,DCA,TCA competitive inhibition constant of 1,1- 1,1-DCA/mg cells-d) DCA on 1,1,1-TCA (mg/L) km TCA maximum transformation rate of 1,1,1-TCA KIc,TCA,DCE competitive inhibition constant of 1,1,1- (mg 1,1,1-TCA/mg cells-d) TCA on 1,1-DCE (mg/L) km BUT maximum utilization rate of butane (mg butane/ KIc,TCA,DCA competitive inhibition constant of 1,1,1- mg cell-d) TCA on 1,1-DCA (mg/L) C aqueous substrate concentration (mg/L) KIc,BUT,DCE competitive inhibition constant of butane Ks DCE half-saturation constant of 1,1-DCE (mg/L) on 1,1-DCE (mg/L) Ks DCA half-saturation constant of 1,1-DCA (mg/L) KIc,BUT,DCA competitive inhibition constant of butane Ks TCA half-saturation constant of 1,1,1-TCA (mg/L) on 1,1-DCA (mg/L) Ks BUT half-saturation constant of butane (mg/L) KIc,BUT,TCA competitive inhibition constant of butane Tc DCE transformation capacity of 1,1-DCE (mg 1,1- on 1,1,1-TCA (mg/L) DCE/mg cells) KIu,BUT,DCE non-competitive inhibition constant of bu- Tc DCA transformation capacity of 1,1-DCA (mg 1,1- tane on 1,1-DCE (mg/L) DCA/mg cells) KIu,BUT,DCA non-competitive inhibition constant of bu- Tc TCA transformation capacity of 1,1,1-TCA (mg tane on 1,1-DCA (mg/L) 1,1,1-TCA/mg cells) * KIu,BUT,TCA non-competitive inhibition constant of bu- C sorbed phase substrate concentration (mg sub- tane on 1,1,1-TCA (mg/L) strate/kg soil) 2 Hcc,DCE dimensionless Henrys constant for 1,1-DCE Dh hydrodynamic dispersion coefficient (m /d) 1 Hcc,DCA dimensionless Henrys constant for 1,1-DCA Fk mass transfer rate coefficient for sorption (d ) Hcc,TCA dimensionless Henrys constant for 1,1,1-TCA v average linear groundwater velocity (m/d) Hcc,BUT dimensionless Henrys constant for butane Kd partition coefficient for sorption (L/kg) fd fraction of cells that are biodegradable (mg/mg) U porosity dc cell decay oxygen demand (mg O2/mg cell) qb bulk density of the aquifer solids (kg/L)

enzymes fortuitously catalyzing these reactions. Because Microorganisms that grow on butane have the ability to these reactions do not provide energy or carbon, a primary cometabolize a broad range of CAHs [9,8,15,14]. Microor- growth substrate must be supplied to stimulate the neces- ganisms stimulated on butane are capable of transform- sary population of cometabolizing microorganisms. In oxi- ing 1,1-dichloroethene (1,1-DCE), 1,1-dichloroethane dative cometabolism, the enzymes use the primary growth (1,1-DCA), and 1,1,1-trichloroethane (1,1,1-TCA) [17]. substrate as an electron donor and oxygen as an electron Kim et al. [16,17] performed detailed kinetic and inhibition acceptor. studies on the cometabolic transformation of these three The performance of cultures capable of cometabolic oxi- CAHs with a butane-grown enrichment culture. 1,1-DCE dative dechlorination has been studied for a variety of con- was observed to have the fastest transformation kinetics, taminants and primary growth substrates as reviewed by followed by 1,1-DCA, and 1,1,1-TCA. Inhibition models Arp et al. [4] and Alvarez-Cohen and Speitel [2]. Examples were also determined for butane inhibition on CAH trans- of monooxygenase-inducing substrates include methane, formation, CAH inhibition on butane utilization, and propane, ammonia, toluene, and phenol [9,8,3,5]. CAH inhibition on each others’ transformation. These 1530 L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546 inhibitions play an important role in application of comet- substrate, PR1301 did not maintain TCE degradative ability abolic transformations and are incorporated into our for long periods. model development. A microcosm study with the butane-enrichment culture Glotz et al. [7] reviewed models for cometabolism, of Kim et al. [16] was conducted by Jitnuyanont et al. [13] including transport models and the use of models in the to study the transformation of 1,1,1-TCA in bioaugmented design of remediation systems. The modeling of cometab- and non-augmented microcosms. The augmented micro- olism both in batch systems and transport codes involves cosms required less time to start utilization of butane than the incorporation of processes including microbial growth non-augmented microcosms and initially were more effec- and decay, substrate utilization as an electron donor, oxy- tive in transforming 1,1,1-TCA, but their transformation gen utilization as an electron acceptor, and the transfor- ability decreased with prolonged incubation. mation of the CAHs of interest. The multi-species The objectives of our study were to: (1) develop a culture reactive transport models must also include key cometa- for bioaugmentation from a parent culture that had been bolic processes including the kinetics of different inhibi- kinetically well characterized by Kim et al. [16,17]; (2) eval- tions, as well as transformation product toxicity that uate the culture’s ability to transform 1,1-DCE, 1,1-DCA, can result from the transformation of the CAHs. Such and 1,1,1-TCA in batch kinetic studies performed in both models have been used to evaluate the results of field scale media and groundwater microcosms; (3) simulate the tests experiments [27,28,6]. of the media and microcosm studies using a cometabolic Few studies have been performed, where cometabolic transformation model, using as many independently models have been applied at different scales, including derived parameters as possible; (4) perform a field scale batch kinetic laboratory studies in media or soil/groundwa- bioaugmentation experiment using the culture, and evalu- ter microcosm studies, column studies and field scale tests. ate the transformation of the CAH mixture; and (5) simu- Gandhi et al. [6] performed two-dimensional time-variant late the results of the field experiment using a reactive model simulations of a full-scale recirculation system at transport model that includes cometabolic kinetics, using Edwards Field, California, to evaluate in situ cometabolic kinetic parameters that were independently determined in treatment of trichloroethene (TCE) with microorganisms laboratory studies. For simulating the results of the field stimulated on toluene. Models simulations were performed test, a multi-species reactive transport model was adapted using estimated kinetic parameters and those determined from that presented by Semprini and McCarty [27,28],to directly from microcosm studies using site groundwater include terms of transformation product toxicity and com- and aquifer solids. The parameters included the growth petitive and mixed inhibition of butane and the chlorinated yield, the endogenous decay coefficient, the maximum spe- solvent, as described by Kim et al. [16,17]. cific primary substrate utilization rate, TCE transforma- The ultimate goal of the study was to evaluate bioaug- tion rate, TCE transformation product toxicity, and mentation at the field scale. The Moffett Field test facility competitive inhibition between toluene and TCE. TCE had been previously used for field scale evaluation of removals based on model simulations closely simulated in situ cometabolism of TCE, c-DCE, trans-dichloroethene those observed in the field demonstration. (t-DCE), and VC with methane [25], phenol [11] and tolu- In our study we evaluated the potential for bioaugmen- ene [12] added as cometabolic substrates. Methane utilizers tation of a butane-utilizing culture to achieve effective effectively transformed VC, and t-DCE, but were less effec- transformation of mixtures of 1,1-DCE, 1,1-DCA, and tive in transforming c-DCE, and TCE. Phenol utilizers and 1,1,1-TCA. The goal of this approach is to achieve pro- toluene utilizers effectively transformed TCE, c-DCE, and longed survival and growth of the added organisms that VC, and were less effective at transforming 1,1-DCE and are more effective than the indigenous microorganisms in t-DCE. 1,1,1-TCA present as a background contaminant transforming the target contaminants. In situ bioaugmen- was not effectively transformed by any of these cometabolic tation with specialized cometabolizing microorganisms systems. In addition, 1,1-DCE strongly inhibited the trans- has been previously evaluated. Burkholderia cepacia formation of TCE by microorganisms grown on toluene ENV435, a toluene-utilizing microorganism, was bioaug- [12]. mented into groundwater contaminated with 1000–2500 Our study investigated the transformation of 1,1-DCA, lg/L of TCE, 1,2-cis-dichloroethene (c-DCE), and vinyl 1,1-DCE and 1,1,1-TCA – three CAHs that are frequently chloride (VC). The total mass of CAHs in the treated area found together due to biotic and abiotic transformation of was reduced by as much as 78% within 2 days, after inject- the latter into the former two, respectively [30]. Kim et al. ing the organisms [29]. A genetically modified strain of B. [16,17] conducted detailed kinetic studies with a butane- cepacia G4, PR1301, that can degrade TCE effectively while utilizing enrichment, which was the parent culture for this growing on simple substrates such as lactate, instead of study. Inhibition types were determined and kinetic para- phenol or toluene, was bioaugmented into small scale lab- meters for butane utilization, 1,1,1-TCA, 1,1-DCE, and oratory columns [23,22]. The results indicated that the 1,1-DCA transformation, and inhibition constants were biaugmented organisms were present in column effluents developed. Table 1 presents the maximum utilization rate as long as bioaugmentation continued, but not when it constants (km) and half-saturation constants (Ks) that were was discontinued. When lactate was used as a primary determined. The culture transformed 1,1-DCE at the high- L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546 1531

Table 1 Input parameters for modeling biotransformation in media, microcosm and field experiments Parameter Units Value Parameter Units Value a d KIc,DCA,BUT mg/L 39.9 X0 mg/L 85 e X0 mg/L Varied c X0 mg/L Varied a a KIc,DCA,DCE mg/L 1.8 Y mg/mg 0.79 a 1 a KIc,DCA,TCA mg/L 1.6 b d 0.038 b d1 0.084b a 1 c KIc,DCE,BUT mg/L 0.84 b d 0.1 c Fa mg/mg 4.0 a d KIc,DCE,DCA mg/L 0.35 VL L 0.017 a d KIc,DCE,TCA mg/L 0.11 VG L 0.010 e VL L 0.40 e VG L 0.27 1 e Kla d 0.72 a KIc,TCA,BUT mg/L 41.8 km BUT mg/mg-d 3.49 a a KIc,TCA,DCA mg/L 1.3 km DCA mg/mg-d 1.16 a a KIc,TCA,DCE mg/L 2.3 km DCE mg/mg-d 6.52 a km TCA mg/mg-d 0.64 a KIu,BUT,DCA mg/L 0.20 b a 0.023 Ks BUT mg/L 1.11 a a KIu,BUT,DCE mg/L 0.40 Ks DCA mg/L 1.90 a a KIu,BUT,TCA mg/L 0.03 Ks DCE mg/L 0.14 a Ks TCA mg/L 1.63 a KIc,BUT,DCE mg/L 0.02 a Tc DCA mg/mg 0.197 a Hcc DCA – 0.18 Tc DCE mg/mg 0.050 b Hcc DCE – 0.86 0.017 b Hcc TCA – 0.55 Tc TCA mg/mg 0.069 b Hcc BUT –38 0.110 c fd mg/mg 0.8 c dc mg/mg 1.42 a Value from [17] and used to model media, microcosm, and field tests unless specified otherwise. b Value adjusted to better fit media reactor data and used to model microcosm and field tests. c Value used in reactive transport model. d Value used for media reactors. e Value used for simulations of microcosms with aquifer solids. est rate, followed by 1,1-DCA, and 1,1,1-TCA. The Kim et al. [16,17] determined the types of inhibition dur- Ks value for 1,1-DCE was also much lower than for ing cometabolism by the butane-enrichment culture that 1,1-DCA, and 1,1,1-TCA, which also resulted in more was the parent culture tested in this study. Competitive, rapid transformation at lower concentrations, and less non-competitive, and mixed inhibition, was observed. inhibition of transformation by butane and the other Competitive inhibition among the CAHs when mixtures CAHs. The culture had a higher km value for 1,1-DCE were present is represented by, and a lower Ks value than cultures that grew on methane dC XkmC or ammonia, indicating it was much more effective at ¼ ð1Þ dt K ðÞþ1 þ I =K C 1,1-DCE transformation [17]. The transformation capacity s c Ic (Tc DCE) of 1,1-DCE, which is the amount of CAH trans- where C is the aqueous concentration of the substrate (mg/ formed for the amount cells present, was also shown to be L), Ic is the aqueous concentration of inhibitor (mg/L); KIc is high for this culture [15]. the constant for competitive inhibition (mg inhibitor/L); km is the substrate maximum specific utilization rate (mg sub- 2. Model development strate/mg cells/day); and Ks is the substrate half-saturation constant (mg substrate/L). Kim et al. [17] found that the An aerobic cometabolism model was developed that measured Ks values for transformation of the CAHs, repre- includes substrate and CAH inhibition models for the sented the inhibition constant, Ic, well for the inhibition by butane-enrichment culture along with transformation one CAH on the transformation of another CAH or butane. product toxicity, as described by Kim et al. [17]. For labo- Non-competitive inhibition more specifically influences the maximum utilization rate, ratory batch reactor studies, the series of equations for ! microbial growth and decay, butane utilization, and trans- dC Xk C formation of CAHs was solved using Stella software ¼ m ð2Þ Ks dt 1 þ Iu=KIu (High Performance System Inc., Hanover, NH). 1þIu=KIuþC 1532 L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546

1 where Iu is the aqueous concentration of non-competitive coefficient (day ); CBUT is the aqueous concentration of inhibitor (mg/L); and KIu is the constant for non-competi- butane as the electron donor (mg/L); CO2 is the aqueous tive inhibition (mg inhibitor/L). Kim et al. [16,17] found concentration of electron acceptor oxygen (mg/L); km BUT that butane inhibition of CAH transformation followed a is the maximum substrate utilization rate of butane (mg bu- mixed inhibition pattern, which is a combination of compet- tane/mg cells/day); Ks BUT is the half-saturation constant of itive and non-competitive inhibition. Mixed inhibition can butane (mg butane/L); KsO2 is the half-saturation constant be represented by a combination of Eqs. (1) and (2) to give of oxygen (mg/L). Tc,TCA is the transformation capacity of !1,1,1-TCA as a non-growth substrate (mg TCA/ mg cells). dC Xkm C ¼ ð3Þ Tc is specific for a CAH and the culture exposed to it. Prod- Ks dt 1 þ Iu=KIu ðÞþ1 þ Ic=KIc C 1þIu=KIu uct toxicity from several non-growth, or cometabolic, substrates may be incorporated by adding a T term for each When several inhibitors are present, inhibition is repre- c CAH [1]. sented by the combination of the appropriate inhibition The field tests were simulated using a modified form of equations. For example, transformation of 1,1,1-TCA the combined biotransformation/transport model presented may be inhibited by the presence of butane, 1,1-DCE, by Semprini and McCarty [27,28]. The model includes and 1,1-DCA through mixed and competitive fashions, competitive inhibition of CAHs on CAH transformation; respectively,

dC Xk C TCA ¼ mTCA O2 dt 1 þ C =K K þ C BUT Iu;BUT;TCA sO2 O2 ! C TCA ð4Þ KsTCA ðÞ1 þ CBUT=KIc;BUT;TCA þ CDCE=KIc;DCE;TCA þ CDCA=KIc;DCA;TCA þCTCA 1þCBUT=KIu;BUT;TCA

where C is the aqueous concentration of substrate (mg/L); competitive inhibition of the CAHs on butane utilization, km is the maximum specific utilization rate of 1,1,1-TCA mixed inhibition of butane on CAH transformation, and (mg TCA/mg cells/day); Ks TCA is the half-saturation con- transformation product toxicity. The transport equation stant of 1,1,1-TCA (mg TCA/L); KIu,BUT,TCA is the con- includes 1-D advective/dispersive transport and non- stant for non-competitive inhibition of 1,1,1-TCA by equilibrium sorption. Cyclic pulsing of electron donor and butane (mg butane/L); and KIc,DCA,TCA is the constant electron acceptor is permitted at the inlet boundary. for competitive inhibition of 1,1,1-TCA by butane (mg The transport of dissolved butane (electron donor), dis- butane/L). KIc,DCE,TCAand KIc,DCA,TCA are the competitive solved oxygen (electron acceptor), and the CAHs of inter- inhibition constants for 1,1-DCE and 1,1-DCA on 1,1,1- est are represented in a 1-D advection/dispersion multi- TCA, respectively. The subscript BUT stands for butane species transport model. Non-equilibrium sorption for and the subscript O2 represents the electron acceptor, oxy- the 1-D transport code was defined in our model as a gen in this case. first-order rate process as previously described by Semprini Cometabolic transformations result in a drain of energy and McCarty [28]: from cells as well as transformation product toxicity. Alva- o2 rez-Cohen and Speitel [2] reviewed and discussed these pro- dC C dC qb ¼ Dh v F kðÞKdC C rCT ð6Þ cesses and the models used to represent them. One of the dt ox2 dx / simplest approaches to represent transformation product dC ¼ F kðKdC C Þð7Þ toxicity is to include a transformation capacity term (Tc), dt that represents cell loss resulting from the cometabolic where C* is the sorbed-phase concentration of substrate transformation of a substrate [1], into the equation for cell (mg substrate/kg soil); C is the aqueous concentration growth and decay. The differential equation for cell growth of substrate (mg/L); Fk is the rate coefficient for mass concentration used in the model for the case of 1,1,1-TCA 1 transfer between aqueous and sorbed phases (d ); Dh is transformation toxicity is represented by, 2 the hydrodynamic dispersion coefficient (m /d); v is the dX CBUT average linear groundwater velocity (m/d); qb is the bulk ¼ XYkmBUT density of the aquifer solids (kg/L); K is the partition dt KsBUTðÞ1 þCTCA=KIc;TCA þCBUT d coefficient of sorbed substrate (L/kg); and / is the aquifer 1 dCTCA CO bX 2 ð5Þ porosity. This form was chosen to provide a simple, non- T dt K þ C c;TCA sO2 O2 equilibrium sorption process. Equilibrium sorption condi- where X is the cell concentration (mg/L); Y is the yield tions may be simulated by assigning a very high value to coefficient (mg cells/mg growth substrate); b is the decay the mass transfer rate coefficient (Fk). The reaction terms, L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546 1533 rCT, for the cometabolic transformations are provided in The highly enriched culture used to bioaugment the detail in Table 2 for each CAH. The transformation of microcosms and field site was obtained as described in Li 1,1,1-TCA by other processes, such as anaerobic degrada- [18], and is briefly described here. The aliquoted mixed cul- tion and abiotic transformation are not included, since ture was thawed, diluted and inoculated onto agar plates our tests were aerobic and abiotic transformation rates containing mineral salts media and incubated in a chamber would be negligible. with a 3% butane-in-air headspace. Individual colonies The cometabolic transformation and transport models were serially streaked through four generations before presented above were combined to create equations for being reintroduced to liquid media and grown for harvest- tracking the aqueous concentrations of the electron donor ing, storage in liquid nitrogen, and molecular analysis. Two (butane), electron acceptor (oxygen), and CAHs (1,1-DCE, highly enriched cultures were developed and one, referred 1,1-DCA, and 1,1,1-TCA). Eqs. (6) and (7), for example, to here as the bioaugmentation culture, was chosen for field were combined with Eq. (4), to represent 1,1,1-TCA trans- use based on butane and CAH transformation kinetics, the port and transformation. Sorption was not included for the culture’s butane and CAH transformation kinetics, its dis- combined equations for the electron donor (butane) and persed rather than agglomerated growth, and because the acceptor (oxygen). The resulting series of equations pro- dominant organism in the culture was not found present vided in Table 2, were solved numerically as described by when using T-RFLP analyses of the field site aquifer solids Semprini and McCarty [27,28]. The solutions involve finite and groundwater. The dominant morphology was short difference approximations of the terms on the right-hand rods approximately 1 lm wide by 1.5 lm long, often side of the equations and numerical integration in time grouped in pairs. T-RFLP analysis of the 16S rDNA of using the Runge–Kutta method, resulting in a sequential the bioaugmentation culture showed >93% of the total iterative approach to solving the series of non-linear peak area was associated with an organism with a terminal equations. fragment length of 183 bp when restricted with the MnlI The numerical solution with simpler kinetic expressions restriction endonuclease and which was found to be a Rho- was previously verified by Semprini and McCarty [27,28] dococcus sp., based on 16S-rDNA sequencing (data not using analytical solutions to the advection/dispersion equa- shown). In contrast, T-RFLP analysis of the parent culture tion and other methods. To verify the modified code with revealed a more diverse community with >13 discernable more complex kinetic expressions, the numerical code peaks with the largest (T-RFFL of 118 bp) accounting was compared with solutions obtained using Stella soft- for 31% of the total peak area. The parent culture did ware for a batch reactor kinetics that were programmed not contain a peak at 183 bp, which corresponded to the with the same kinetic expressions. In order to model batch dominant organism in the bioaugmentation culture. kinetics in the transport model, flow was set to zero. Excel- In order to grow enough culture for kinetic studies and lent agreement was obtained between the transport code for bioaugmentation at the field site multiple (48–72) batch and Stella software simulations. reactors were used. The cells stored in liquid nitrogen were thawed and inoculated into autoclaved, 707 mL clear glass 3. Batch kinetic studies bottles containing 300 mL of growth media, with the remaining volume headspace (air), and capped with gray 3.1. Culture description butyl rubber septa (Wheaton Glass Co., Millville, NJ). The bottles were inoculated with 15–30 mL of butane and The butane-utilizing culture used in this study was incubated at 20 C while shaken at approximately developed from the parent enrichment culture used in the 200 rpm. Cells were harvested when optical densities at kinetic studies of Kim et al. [16,17]. The parent culture 600 nm reached approximately 1.0. was enriched from aquifer sediments from the Hanford DOE site, Washington, and the kinetics and inhibitory 3.2. Batch transformation tests in media and microcosms interactions of butane utilization and CAH cometabolic transformation were determined. Initially, the parent cul- The culture’s ability to cometabolize 1,1-DCE, ture was added to microcosms containing aquifer solids 1,1-DCA, and 1,1,1-TCA while utilizing butane was mea- and groundwater from Moffett Federal Airfield, California, sured both in growth media and in soil/groundwater to select for microorganisms that grew well under the geo- microcosms. Media biotransformation experiments were chemical conditions of the site. A mixed culture sample was conducted in 27 mL batch reactor vials containing 10 mL harvested from a microcosm that exhibited effective 1,1,1- of growth media and 17 mL of air headspace, and were TCA transformation and was grown to an optical density inoculated with approximately 0.85 mg cells measured by (OD600) of about 1.0 in a 3% butane-in-air headspace. dry weight. The cells were exposed to approximately The culture was harvested, aliquoted into 250–1 mL cryo- 100 lg/L 1,1-DCE, 200 lg/L 1,1-DCA, 200 lg/L genic tubes and stored at 80 C for further use. This cul- 1,1,1-TCA, and 4% butane by volume in the headspace. ture was then further enriched in an effort to obtain isolates The reactors were incubated at 20 C and shaken at capable of CAH transformation for bioaugmentation at 200 rpm to ensure rapid mass transfer between the aqueous the field site. and gas phases. The tests were performed in triplicate. 1534

Table 2 Equations used in the reactive transport model simulations 2 Electron donor dCBUT CO CBUT o CBUT dCBUT ¼Xk 2 þ D v mBUT h o 2 (Butane) dt KsO2 þ CO2 KsBUTðÞ1 þ CDCE=KIc;DCE;BUT þ CDCA=KIc;DCA; BUT þ CTCA=KIc;TCA;BUT x dx Electron acceptor dC C C O2 ¼F Xk O2 BUT (oxygen) dt a mBUT K þ C K ð1 þ C =K þ C =K þ C =K þ C =K ÞþC sO2 O2 sBUT BUT HAL DCE Ic;DCE;BUT DCA Ic; DCA;BUT TCA Ic;TCA;BUT BUT o2 CO2 CO2 dCO2 d f bX þ D v 1528–1546 (2007) 30 Resources Water in Advances / al. et Semprini L. c d h o 2 KsO2 þ CO2 x dx

1,1,1-TCA dC k C TCA ¼X mTCA O2 dt 1 þ C =K K þ C BUT Iu;BUT; TCA sO2 O2 ! C TCA KsTCA ðÞ1 þ CBUT=KIc;BUT;TCA þ CDCE=KIc;DCE; TCA þ CDCA=KIc;DCA;TCA þ CTCA 1þCBUT=KIU;BUT;TCA o2C dC q þ D TCA v TCA b F K C C h ox2 dx / kTCA dTCA TCA TCA dC k C DCE ¼X mDCE O2 1,1-DCE dt 1 þ C =K K þ C BUT Iu;BUT; DCE sO2 O2 ! C DCE KsDCE ðÞ1 þ CBUT=KIu;BUT;DCE þ CTCA=KIc;TCA; DCE þ CDCA=KIc;DCA;DCE þCDCE 1þCBUT=KIu;BUT; DCE o2C dC q þ D DCE v DCE b F K C C h ox2 dx / kDCE dDCE DCE DCE

1,1-DCA dCDCA kmDCA CO ¼X 2 dt 1 þ C =K K þ C BUT Iu;BUT; DCA sO2 O2 ! C DCA KsDCA ðÞ1 þ CBUT=KIu;BUT;DCA þ CTCA=KIc;TCA; DCA þ CDCE=KIc;DCE;DCA þCDCA 1þCBUT=KIu;BUT; DCA o2C dC q þ D DCA v DCA b F K C C h ox2 dx / kDCA dDCA DCA DCA

dX CO2 CBUT CO2 dCDCE 1 dCDCA 1 dCTCA 1 Biomass* ¼ XYkmBUT bX þ þ dt KsO2 þ CO2 KsBUTðÞ1 þ CDCE=KIc;DCE;BUT þ CDCA=KIc;DCA; BUT þ CTCA=KIc;TCA;BUT þCBUT KsO2 þ CO2 dt T cDCE dt T cDCA dt T cTCA

* dCDCE dCDCA dCTCA The dt ; dt and dt terms are of the form given in Eq. (4). L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546 1535

Microcosm experiments were performed in 707 mL 4. Field tests autoclaved, clear-glass bottles containing approximately 100 mL of Moffett Field soils (approximately 120 g), Field studies were conducted at the Moffett Test facil- 400 mL of Moffett Field groundwater and capped with ity, which has been used in past studies of in situ aerobic gray butyl rubber septa. Reactor tests were conducted in cometabolism [25,11,12]. The test legs were located in a triplicate. Details of the construction are provided by shallow confined aquifer composed of poorly sorted mate- Mathias [20]. Approximately 0.43 mg of the bioaugmenta- rials. Details of the site hydrogeology are provided by tion culture was inoculated into each microcosm at the Roberts et al. [24]. Two experimental test legs were beginning of the test. The microcosms were incubated at installed (Fig. 1). One leg served as the control test leg 20 C, and in initial tests were shaken at 100 rpm. After (West Leg), where indigenous butane utilizers were stimu- mass transfer limitations were indicated, the speed of shak- lated, and the other served as the bioaugmented test leg ing was increased to 150 rpm. 1,1-DCE, 1,1-DCA, and (East Leg). Each test leg consisted of an injection well 1,1,1-TCA (99%, >99%, 99.5%, respectively, Aldrich Chem- and an extraction well located about 7 m apart with mon- ical Co., Milwaukee, WI) were added to the media reactors itoring wells in between. Tests were conducted using pro- and microcosms as saturated solutions (CAH in 25 mL tocols described in previous studies [24,25]. Induced deionized water). Butane was added directly as a gas. Oxy- gradient conditions for each experimental test leg were gen was added to the reactors according to stochiometric created by injecting groundwater at 1.5 L/min and extract- oxygen demand for butane consumption (4 mol O2:1 mol ing at approximately 8 L/min. The extracted groundwater butane). was amended with the chemicals of interest and re- injected. 1,1-DCE, 1,1-DCA, and 1,1,1-TCA were contin- 3.3. Analytical methods uously injected to the test leg at concentrations ranging from 50 to 200 lg/L. During the biostimulation and bio- Headspace samples were taken periodically using a transformation studies, butane or oxygen were dissolved 100 lL gas-tight syringe, and gaseous concentrations of in the extracted groundwater, and injected in alternating butane and the CAHs were measured by gas chromatogra- pulses to help prevent bioclogging of the injection well, phy. Butane, 1,1-DCE, and 1,1-DCA concentrations were as described by Semprini et al. [25]. The concentrations determined using a Hewlett–Packard (Wilmington, DE) of CAHs, dissolved butane and oxygen were measured 6890 gas chromatograph equipped with a flame ionization on-site using an automated data acquisition system detector (FID) and photo ionization detector (PID) described by McCarty et al. [21]. connected in series. The PID was used to determine 1,1-DCE concentration. Chromatographic separation was 5. Results achieved using a GS-Q 30 m · 0.53 mm PLOT column (J&W Scientific, Folsom, CA). 1,1,1-TCA was measured 5.1. Transformation of CAH mixtures in batch reactors with using a Hewlett–Packard (Wilmington, DE) 5890 gas chro- growth media matograph equipped with a 63Ni electron capture detector (ECD). Chromatographic separation was achieved Transformation experiments conducted in growth using a HP-624 capillary, 30 m · 0.25 mm · 1.4 mm film media showed that the bioaugmentation culture was capa- thickness. ble of butane utilization and biotransformation of the Reactor mass balances were performed using the mea- CAH mixture. Fig. 2 presents experimental results and sured gaseous concentrations, published Henry’s constants model simulations. Results from triplicate reactors were [19,7], and gas and liquid volumes. Sorption of the CAHs nearly identical. 1,1-DCE was quickly transformed in the to the aquifer solids was assumed minimal based on the presence of butane, followed by 1,1-DCA, and 1,1,1- low organic carbon of the aquifer material of 0.1% [24], TCA transformation once butane concentrations were and the low solids to liquid volume ration in the micro- lowered. Butane was also rapidly utilized, but since a much cosms. At equilibrium, the mass of CAH in the reactor is greater mass of butane was present it was transformed given by, over a longer period. The order of the transformations are consistent with the k and K values given in Table M ¼ C ðV þ V =H Þð8Þ m s G G L cc 1, and the expected inhibition of butane on 1,1,1-TCA where M is the total mass (mg), CG is the measured gas transformation. phase concentration, VG and VL are the volumes of the li- Biotransformation observed in the media reactors was quid and the gas phase, respectively, and Hcc is the dimen- simulated using the equations shown in Table 2, without sionless Henry’s Coefficient. The Stella model for solving the transport, sorption, and dispersion terms included. the equations presented in Table 2, without transport and The kinetic parameter values determined by Kim et al. dispersion, provides for equilibrium partitioning between [16,17] for the parent culture from which the bioaugmenta- the liquid and gas phases, as well as for a mass transfer, tion culture was developed were used for the initial simula- based on two-film theory, with a liquid overall mass trans- tions (Table 1, Fig. 2). The model, using the independently 1 fer coefficient, Kla (d ), included. derived kinetic parameters and inhibitions constants, did a 1536 L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546

Indigenous Bioaugmented

Extraction Wells (8 L/min)

Groundwater S3 S3 Monitoring Points 7 m

S2 S2 FP Wells Regional With Solid Groundwater Support Media Gradient S1 S1

Injection Wells 4.5 m (1.5 L/min)

Fig. 1. Layout of the indigenous, or West, and the bioaugmented, or East, well legs at the Moﬀett Field test site. Groundwater monitoring points S1, S2, and S3 were placed approximately 1 m, 2 m, and 4 m from their respective injection wells.

good job capturing the overall response observed in the 1,1-DCE Data 1,1-DCE Model 1,1-DCA Data 1,1-DCA Model batch reactors. However, model prediction of 1,1-DCA 5 1,1,1-TCA Data 1,1,1-TCA Model 1600 transformation was more rapid than was observed in the Butane Data Butane Model media reactors. The bioaugmentation culture was an 4

1200 g) enrichment of the parent culture with a Rhodococcus sp. μ g)

μ dominating the population. It is possible that other 3 1,1-DCA cometabolizing organisms, or possibly organisms 800 2 able to utilize 1,1-DCA for energy, may have been present in the parent culture, but eliminated during the bioaugmen-

CAH Mass ( 400

1 Butane Mass ( tation culture enrichment. Fig. 2b shows the results of model simulations after sev- 0 0 eral parameters were heuristically adjusted to achieve a bet- 0 5 10 15 20 25 30 Time (hrs) ter ﬁt, especially to the 1,1-DCA results. The decay constant b, the transformation capacities of 1,1,1-TCA

1,1-DCE Data 1,1-DCE Model (Tc TCA) and 1,1-DCE (Tc DCE) and the constant for non- 1,1-DCA Data 1,1-DCA Model competitive inhibition of 1,1-DCA by butane (KIu,BUT,DCA) 5 1,1,1-TCA Data 1,1,1-TCA Model 1600 were adjusted (Table 1). The higher decay value (0.0035/h; Butane Data Butane Model 0.084/d) is in the range of values used by Semprini and 4 1200 g) McCarty [27]. The constant for non-competitive butane μ g)

μ inhibition on 1,1-DCA transformation was decreased from 3 l l 800 3.5 mol/L to 0.4 mol/L, making butane a stronger inhib- 2 itor of 1,1-DCA transformation. The transformation capacity of 1,1-DCE was decreased by a factor of 3, while

CAH Mass ( 400 1 Butane Mass ( 1,1,1-TCA was increased by a factor of 1.6, based on the modeling of microcosm tests, discussed later. 1,1-DCE 0 0 has a much lower transformation capacity than 1,1-DCA, 0 5 10 15 20 25 30 and 1,1,1-TCA, indicating that it is much more toxic to Time (hrs) the cells. Adjustment of only a few parameters was Fig. 2. Experimental results and model simulations of bioaugmentation required to achieve a very good fit to the concentration his- culture transformation of butane, 1,1-DCE, 1,1-DCA, and 1,1,1-TCA in tories of butane and the three CAHs. media bottles: (a) simulation using model parameters developed by Kim et al. [17] for the parent culture from which the bioaugmentation culture The experimental results showed that 1,1-DCE was rap- was developed and (b) simulation using the adjusted model parameters idly transformed, while 1,1-DCA and 1,1,1-TCA were developed in this study. more slowly transformed. This was accounted for in the L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546 1537 model by non-competitive butane inhibition of CAH trans- over time (data not shown). The results illustrated the formation and lower km and higher Ks values for 1,1-DCA ability of the bioaugmentation inoculum to grow in the and 1,1,1-TCA. The lower constants for non-competitive presence of CAH contamination and, with repeated butane inhibition of 1,1-DCA and 1,1,1-TCA (0.4 and butane additions, to increase rates of butane utilization 0.5 lmol/L) reflect greater inhibition of their transfor- and CAH cometabolism. Effective transformation of the mation by butane compared to 1,1-DCE. As butane was CAH mixture was maintained over a period of 100 days. consumed and concentrations became lower, the transfor- However, unlike the field tests discussed later, there did mation of 1,1-DCA and 1,1,1-TCA increased, due to less not appear to be a native population of butane-utilizers inhibition and an increase in the butane-utilizing microbial to compete with the bioaugmentation culture as noted population. by the lack of butane utilization over 100 days in the non-bioaugmented microcosms. 5.2. Transformation of CAH mixtures in groundwater/ The results of studies in media and the resulting model aquifer solids microcosms simulations indicated that the product toxicity of 1,1-DCE was greater than that reported by Kim et al. Microcosm studies using site groundwater and aquifer [15]. Kim reported a 1,1-DCE transformation capacity material were performed to evaluate the transformation (Tc DCE) value of 0.52 lmol DCE/mg cells (0.05 mg/mg), of CAH mixtures upon inoculation with the bioaugmenta- while our simulations (Fig. 2) indicated that a value of tion culture. The purpose of the experiment was to deter- 0.175 lmol DCE/mg cells (0.017 mg/mg) more adequately mine if the bioaugmentation culture could be introduced fit our laboratory data. Upon completion of the microcosm in a small dose to a contaminated environment with similar tests described above, three of the bioaugmented micro- geochemical conditions as that of the field site and respond cosms were used to determine the transformation capacity with robust growth to produce effective CAH transforma- of 1,1-DCE. Since the actual biomass concentration in the tion over an extended period of time. Microcosms were microcosms was not known, the cell mass at the start of the inoculated with approximately 0.43 mg of the bioaugmen- tests was estimated by measuring butane consumption tation culture at the beginning of the test. The dose was rates in the absence of CAHs. The microcosms were stim- small in comparison with that used in the growth media ulated in the absence of the CAHs, through repeated addi- experiments (0.85 mg in an aqueous volume of 10 mL) tions of butane with the rotary shaker speed increased to and was used to better approximate the relative volumes 150 rpm to eliminate mass transfer limitations. Butane uti- of expected bioaugmentation dose and active aquifer treat- lization profiles were recorded and simulated using the ment zone volume expected at the field site. The micro- model to determine approximate active cell mass within cosms were subjected to repeated additions of butane and the microcosms. The model provided a good fit to the data the CAH mixture, and were operated for a period of 100 gathered from the three microcosms and showed the inde- days (2400 h). pendently measured Ks value provided an appropriate The bioaugmentation culture was capable of butane shaped concentration response (data not shown). Based utilization and biotransformation of the CAH mixture on these simulations, an active cell mass of 123 mg/L was under the geochemical conditions of the groundwater/ estimated for the 1,1-DCE product toxicity tests, which aquifer solids microcosms (Fig. 3). 1,1-DCE was rapidly corresponded to a total cell mass of 41 mg within the transformed, and butane consumption accelerated once microcosms. 1,1-DCE was removed to lower concentrations. Butane The transformation capacity tests were conducted as strongly inhibited the transformation of 1,1,1-TCA. The resting cell tests, with no butane present. Based on the esti- time for complete removal of all compounds decreased mated cell mass, the microcosms should be able to trans- with repeated additions of butane, indicating growth of form about 720 lg/L of 1,1-DCE, if the transformation the butane-utilizing, CAH-cometabolizing population. capacity was 0.02 lg DCE/mg of cells (0.20-lmol DCE/ For example, with the first addition of butane and CAHs, mg cell). 1,1-DCE (1200 lg) and 110 lg 1,1,1-TCA were it took over 400 h to completely utilize the butane and added to the microcosms to initiate the test. completely remove 1,1-DCA, and some 1,1,1-TCA still Fig. 4 shows the results of the batch microcosm equili- remained after 500 h of incubation. By the fifth addition brations with 1,1-DCE and model simulations. Simulations of butane and CAHs, it only took 30 h for complete are shown for both the higher and lower TcDCE values. butane and 1,1-DCA removal and 1,1,1-TCA was com- Input parameter values for the simulations are provided pletely removed within 40 h. Triplicate microcosms in Table 1. 1,1,1-TCA and 1,1-DCE remained in the micro- showed very similar results, with some minor differences cosms at the end of transformation test. The data were very that may have resulted from slight variations in the bio- reproducible in the three microcosms with 1,1-DCE rapidly augmentation inoculum doses. In contrast, microcosms transformed during the first 5–6 h of these experiments, that were not bioaugmented did not utilize butane or after which transformation activity ceased. 1,1,1-TCA transform any of the CAHs over a period of 100 days transformation was not observed. Model simulations indi- (data not shown). Microcosms containing the mercury- cated that 1,1-DCE transformation inactivated the cells, killed bioaugmented culture also showed negligible losses preventing 1,1,1-TCA from being transformed, although 1538 L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546

1,1-DCE Data 1,1-DCE Model 1,1-DCA Data 1,1-DCA Model 1,1,1-TCA Data 1,1,1-TCA Model 90 12000 Butane Data Butane Model g) g) 75 μ

μ 9000 60 45 6000 30 3000

CAH Mass ( 15 0 0 Butane Mass ( 0 100 200 300 400 500 600 Time (hrs)

90 12000 g) μ g) 75

μ 9000 60 45 6000 30 3000

CAH Mass ( 15 Butane Mass ( 0 0 1200 1300 1400 1500 1600 1700 Time (hrs)

90 12000 g) μ

g) 75

μ 9000 60 45 6000 30 3000

CAH Mass ( 15 Butane Mass ( 0 0 1900 1920 1940 1960 1980 2000 Time (hrs)

90 12000 g) μ g) 75

μ 9000 60 45 6000 30 3000

CAH Mass ( 15 Butane Mass ( 0 0 2200 2220 2240 2260 2280 2300 Time (hrs)

Fig. 3. Experimental data and model simulation for microcosm M2B during ﬁve consecutive additions of butane and the CAH mixture. Note that the time scale changes on the panels with decreasing time required for complete transformation with each subsequent butane addition. The model parameter values provide a good match to experimental data over a period of almost 100 days covering microbial concentrations ranging from less than 1 mg/L to over 20 mg/L.

the model predicted faster 1,1-DCE transformation than (Kla,). Model parameters used for simulating the micro- 1 was observed in the microcosms. The model simulations cosm results, including the Kla (0.72 d ) are provided in with the lower Tc DCE value (0.175 lmol/mg = 0.017 Table 1. Details for the Kla determinations are provided mg/mg) better described 1,1-DCE transformation product by Mathias [20]. toxicity for the bioaugmentation culture. Simulations of the microcosm tests with repeated butane Mass transfer limitations were observed in the micro- and CAH mixture additions were performed using the cosm tests when the bottles were shaken at 100 rpm. A ser- lower value of Tc DCE and incorporated mass transfer lim- ies of microcosm tests, performed at shaking speeds of 100, itations for butane (Fig. 3). Simulations show 1,1-DCE to 150, 200 rpm (data not shown), indicated that there was be rapidly transformed, followed by 1,1-DCA and 1,1,1- liquid/gas mass transfer limitation for butane occurring TCA transformation. Butane showed inhibitory effects, at the shaking speed of 100 rpm, the rate used for the especially on 1,1,1-TCA with faster transformation occur- microcosm tests [20]. Rate limited mass transfer between ring after butane concentrations were reduced. Consistent the gas and liquid phases was incorporated in the model, with the microcosm data, the simulations of the first incu- using an overall liquid phase mass transfer coefficient bation show 1,1-DCE concentrations initially decreasing L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546 1539

1500 between 300 and 500 h. The simulated biomass of butane- M2B utilizing microorganisms illustrates what was occurring 1200 M3A (Fig. 5). The bioaugmented biomass was approximately g) M3B μ 4 mg/L. 1,1-DCE transformation product toxicity greatly TcDCE = 0.175 900 TcDCE = 0.52 reduced the biomass (0–200 h) as it was rapidly transformed, and this resulted in the decreased rate of 600 1,1-DCE transformation. Butane was very slowly transformed during the ﬁrst 300 h, while 1,1-DCE remained in 1,1-DCE Mass ( 300 the microcosm, and continued to cause toxicity as it was transformed. After 1,1-DCE was essentially completely 0 transformed, rates of butane utilization increased, resulting 0 5 10 15 20 Time (hrs) in an increase in biomass. The biomass then slowly decreased as a result of microbial decay after about 150 450 h. 1,1,1-TCA was not completely transformed, while model simulations predicted essentially complete transfor- 120 mation. One possibility is that the enzymes did not remain g) μ induced for 1,1,1-TCA transformation long after butane was consumed. 90 M2B M3A Reasonable matches were obtained to the second and 60 M3B third simulations of 1200–1700 h (Fig. 3). In order to TcDCE = 0.175 achieve these matches the biomass at the start of the simu- TcDCE = 0.52 lation had to be adjusted. The adjustments required an

1, 1-TCA Mass ( 30 increase at 1220 h and a decrease at 1480 h. The results indicate that longer term decay between butane feedings 0 0 5 10 15 20 may not be accurately simulated. Less biomass adjustment Time (hrs) was required for the third, fourth, and fifth additions, as operation achieved a higher biomass concentration, and Fig. 4. Results of 1,1-DCE transformation capacity experiments in three there was less of a time interval between additions. For microcosms and model simulations using different values for Tc DCE. Note the model prediction of complete 1,1-DCE and 1,1,1-TCA transformation the final two additions (1920 and 2210 h) the responses when using the higher Tc DCE value and the experimental data that support are very similar, 1,1-DCE is rapidly degraded and the rate the use of a lower Tc DCE value. does not slow, since a higher biomass is maintained in the microcosms. Longer times are predicted to reduce butane rapidly in the first 50 h and then more slowly from 100 to and 1,1,1-TCA to lower concentrations. Strong inhibition 400 h of incubation. Butane consumption is also fairly well of butane on 1,1,1-TCA transformation affects the 1,1,1- simulated and shows that most of the butane is consumed TCA response. The model generally does a reasonable

2 Cell Conc (mg/L) 0 0 200 400 600 800 1000 1200 Time (hrs)

Cell Conc (mg/L) 5

0 1200 1400 1600 1800 2000 2200 2400 Time (hrs)

Fig. 5. Cell concentrations calculated by the Stella model for microcosm M2B (Fig. 3). Cell concentrations were adjusted at 1220, 1480, 1920, and 2210 h to obtain better simulation fits to the microcosm results. 1540 L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546 job predicting the microcosm performance. 1,1-DCE prod- Table 3 uct toxicity is shown to be an important factor that Injection concentrations and processes studied during the field bioaug- strongly influences the systems response. The model does mentation demonstration a good job capturing this toxicity as well as the inhibition Duration Chemicals Average Process studied of butane on 1,1,1-TCA transformation. The simulations injected concentration show that effectively modeling butane concentrations is 10/22–11/28/02 Bromide 150 mg/L Transport characteristics important, since the transformation of 1,1,1-TCA is of the experimental legs strongly inhibited by butane. 12/26–1/3/02 Bromide 150 mg/L 1,1,1-TCA, 1,1-DCA, (0–9 days) 1,1,1-TCA 140 lg/L 1,1-DCE transport and 1,1-DCA 130 lg/L transformation prior to 5.3. Field experiments and model simulations 1,1-DCE 50 lg/L biostimulation

The field testing focused on inoculation of the treatment 1/3/–1/23/02 Bromide 150 mg/L Bioaugmentation east and (9–20 days) Oxygen 20 mg/La biostimulation of both zone with the bioaugmentation culture and biostimulation Butane 8.75 mg/La legs with short pulse through injection of butane and dissolved oxygen. The 1,1,1-TCA 140 lg/L cycles for transformation cometabolism of 1,1,1-TCA, 1,1-DCE, and 1,1-DCA was 1,1-DCA 200 lg/L of the CAH mixture evaluated by continuously injecting known concentrations 1,1-DCE 65 lg/L into the test leg, and monitoring the temporal concentra- 1/23–2/12/02 Bromide 150 mg/L Long term tion responses at monitoring wells. The East experimental (20–40) Oxygen 20 mg/La biotransformation with a leg (Fig. 1) was bioaugmented with the bioaugmentation Butane 3.5 mg/L long pulse cycles of 1,1,1-TCA 195 lg/L butane and oxygen culture, while in the West leg indigenous butane-utilizing 1,1-DCA 100 lg/L microorganisms were stimulated. Both experimental legs 1,1-DCE 65 lg/L were operated under similar induced gradient conditions 2/12–3/17/02 Oxygen 20 mg/La Biotransformation of injection and extraction and essentially the same injec- (40–70) Butane 8.75 mg/La achieved upon returning tion concentrations of dissolved butane and oxygen, and 1,1,1-TCA 175 lg/L to short total pulse cycles CAHs of interest. 1,1-DCA 175 lg/L with more butane The field tests were performed in the following sequence: 1,1-DCE 65 lg/L addition (1) tracer tests where bromide was added under induced a Time-averaged concentrations – the concentration expected if the total gradient conditions to study transport characteristics of mass of oxygen or butane was delivered continuously rather than applied the test zone and to determine if cross contamination of in pulses. injected groundwater occurred between the experimental legs; (2) addition of 1,1,1-TCA, 1,1-DCA, and 1,1-DCE Table 4 prior to biostimulation and bioaugmentation to determine Butane and oxygen injection pulsing durations and concentrations used in their transport characteristics and to evaluate if transfor- model simulation of field experiments mation occurred in the absence of biostimulation; (3) addi- Duration Concentration tion of the bioaugmentation culture to the East Leg and Days 9–20: 15/45 min BUT/O2 Days 9–20: 35/25 mg/L BUT/O2 biostimulation of both the East and West legs through Days 20–30: 2/22 h BUT/O2 Days 20–23: 35/25 mg/L BUT/O2 the addition of butane and oxygen in short alternating Days 30–40: 1/23 h BUT/O2 Days 23–30: 35/5 mg/L BUT/O2 pulses; (4) long term biostimulation of both experimental Days 40–75: 15/45 min BUT/O2 Days 30–40: 35/18 mg/L BUT/O2 Days 40–75: 20/25 mg/L BUT/O legs through the addition of butane and oxygen with long 2 pulse cycles and the evaluation of the transformation of Pulsing durations are read as from day 9 to day 20, butane was injected for 15 min, followed by 45 min of oxygen. Pulsing concentrations are read as the CAH mixture in both experimental legs; and (5) evalu- from day 9 to day 20, butane was injected at 35 mg/L and oxygen was ation of short term pulsing of butane and oxygen to supply injected at 25 mg/L. more butane to the test legs and to restore CAH transformation activity. Table 3 presents the conditions of the field tests and out- Table 5 lines the sequence of tests described above. The CAHs were 1,1-DCE, 1,1-DCA, and 1,1,1-TCA injection concentrations used in model simulations of field experiments continuously injected into the test zone at concentrations ranging from about 50 lg/L for 1,1-DCE to 140 lg/L for 1,1-DCE injection 1,1-DCA injection 1,1,1-TCA injection 1,1,1-TCA. During the biostimulation and biotransforma- Days 0–9: 50 lg/L Days 0–9: 130 lg/L Days 0–9: 140 lg/L tion tests, butane and oxygen were added in alternating Days 9–75: 65 lg/L Days 9–20: 200 lg/L Days 9–30: 140 lg/L Days 20–35: 100 lg/L Days 30–75: 175 lg/L pulses. The concentrations presented in Table 3 repre- Days 35–60: 175 lg/L sent time-averaged concentrations, or the concentration Days 60–75: 150 lg/L expected if the total mass of butane delivered was continuously applied rather than applied in pulses. Presented in Table 4 is more detailed information on the pulse fre- injection concentrations of the CAHs over the course of quency of the butane and oxygen, their concentration, the experiments that were used in model simulations are and when the pulse cycle was changed. Changes in the presented in Table 5. L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546 1541

Bromide tracer test breakthrough curves at the S1 and BROMIDE at S1 S3 monitoring wells, located 1 m and 3.0 m from the injec- v = 2.0 m/day tion well, were simulated using the transport code without 300 S1 Data transformation. Flow velocities and dispersion coefficients 250 S1 Model were varied heuristically to obtain fits to the breakthrough 200 curves. The 1-D modeling approach did a reasonable job 150 simulating the combined effects of injection, extraction, and regional flow along the experimental test leg, as dis- 100 cussed by Semprini and McCarty [27]. 50 Bromide Conc (mg/L) Transport values used for the simulations are provided 0 in Table 6. Simulations with an average linear groundwater 0 2 4 6 8 10 velocity 2.0 m/d for transport to well S1 and 3.0 m/d to Time (days) well S3 are presented in Fig. 6. Note that there is a good BROMIDE at S3 match for bromide breakthrough, however different flow v= 3.0 m/day velocities were required to achieve this fit. Observations 250 at S1 showed some perturbations in bromide concentra- S3 Data 200 tion, resulting in high injection concentrations (days 1.3– S3 Model 2.6). The different groundwater velocities likely result from 150 aquifer heterogeneities and the monitoring wells being par- 100 tially penetrating. Similar observations were made by Semprini and McCarty [27] for bromide tracer tests con- 50 ducted on another test leg at the site. Bromide Conc (mg/L) 0 Before bioaugmentation and biostimulation, 1,1-DCE, 0 2 4 6 8 10 1,1,1-TCA, and 1,1-DCA were injected into the aquifer Time (days) to develop breakthrough curves for each compound. The Fig. 6. Observed bromide breakthrough at the S1 and S3 monitoring wells transport of the CAHs was retarded due to sorption and model simulations. (Fig. 7). The simulations used flows and dispersion coefficients determined from the bromide tracer tests, and sorption coefficients (Kd) and first-order rate parameters were mon et al. [10]. Simulations of earlier transformation estimated to achieve fit to the breakthrough curves. Esti- experiments by Semprini and McCarty [28] indicated that mates of the Kd values were based on retardation factors including rate limited sorption permits evaluation of determined from times to achieve the 50% breakthrough responses to inhibition that result from the dynamic puls- 1 of bromide and the CAHs at the S1 observation well. ing of butane and oxygen. A Fk value of 2.0 d , however, The estimated retardation factors for 1,1-DCE, 1,1-DCA, was used for modeling the field responses to biostimulation and 1,1,1-TCA were 4.3. 3.4, and 3.4, respectively, which and biotransformation, which damped responses to pulsing resulted in Kd values of 0.69, 0.50, and 0.50 L/kg, respec- and inhibition, in order to observe more general trends in tively. The first-order mass transfer rate coefficients (Fk) the concentration responses. were determined by fitting the CAH breakthrough curves. Fig. 7 presents the S1 breakthrough curves and simulations 5.4. Bioaugmentation and biostimulation tests 1 with Fk values of 0.2 and 2.0 d , representing non- equilibrium sorption and equilibrium cases, respectively. The field tests were simulated using rate parameter val- 1 The Fk value of 0.2 d gave a better fit to the break- ues determined from the laboratory experiments and the through data, indicating rate-limited sorption is occurring aquifer transport parameters defined above. A summary under the transport conditions of Moffett Field test zone, of the biotransformation input values is listed in Table 1, consistent with the modeling analysis performed by Har- while transport input parameters are provided in Table 6.

Table 6 Transport parameter values for simulating ﬁeld data Average lineara groundwater Average lineara groundwater Porosity, U (–) Bulk density, Dispersion a velocity, v to well S1 (m/d) velocity, v to well S3 (m/d) qb (kg/L) coeﬃcient , 2 Dh(m /d) 2.0 3.0 0.33 1.6 0.31

b b 1 Sorption coefficient , Kd (L/kg) Mass transfer rate coefficient , Fk (d ) 1,1-DCE 1,1-DCA 1,1,1-TCA 1,1-DCE 1,1-DCA 1,1,1-TCA 0.69 0.50 0.50 2.0 2.0 2.0 a Defined from bromide tracer tests. b Defined from CAH breakthrough tests. 1542 L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546

1 1,1-DCE Data Cell decay was increased to a value of 0.1 d , which was 80 DCE Model, Fk = 2.0 used previously to simulate tests at Moﬀett Field [27]. DCE Model, Fk = 0.2 60 The fraction of degradable cells (fd) and the oxygen g/L) μ demand for cell decay (dc) were values of Semprini and 40 McCarty [27], while the stoichiometry between butane and oxygen utilization (F ) was determined using reaction 20 a

1,1- DCE ( mass balances. The lower transformation capacity of 0 1,1-DCE (Tc DCE) determined in the microcosm experi- 02468 10ments was also used. The initial biomass was assumed to Time (days) be non-uniformly distributed, with most of the microbes existing within 1 m of the injection well. The initial distri- 1,1-DCA Data 200 DCA Model, Fk = 2.0 bution of biomass concentration was estimated to be DCA Model, Fk = 0.2 consistent with the 5 g of cells that were bioaugmented. 150 g/L) Injection concentrations and pulsing durations used as μ 100 model input are listed in Tables 4 and 5. Field observations and model simulations of butane and 50 dissolved oxygen concentrations, and 1,1-DCE, 1,1,1- 1,1-DCA ( TCA, and 1,1-DCA at the S1 monitoring well are provided 0 0246810in Figs. 8 and 9. Butane and oxygen addition were started Time (days) on day 9, when the bioaugmentation culture was added into the test leg with the injected groundwater. During 1,1,1-TCA Data the early stages of the test (10–20 days) butane concentra- 250 TCA Model, Fk = 2.0 TCA Model, Fk = 0.2 tions at the monitoring well ﬂuctuated greatly, which was 200

g/L) likely caused from unstable delivery of oxygen and butane μ 150 pulses. The model predicts more rapid decreases in butane and oxygen than was observed. We did not try to simulate 100 the unknown and random additions of butane and oxygen 50

1,1,1-TCA ( that were likely occurring. Around day 20, both the model 0 and the field observations show effective decreases in 0426810 Time (days) butane and oxygen concentration. Concentrations may have been reduced earlier; however, from days 17 to 19, Fig. 7. 1,1-DCE, 1,1-DCA, and 1,1,1-TCA breakthroughs at the S1 there appeared to be a large slug addition of butane that monitoring well in the East well leg and transport simulations with high was not effectively transformed. and low rates of mass transfer.

Field Data 8 Model Output 6

2 Butane (mg/L) 0 0 1020 3040506070 Time (days)

Field Data 30 Model Output

10 D.O. (mg/L)

0 0 10203040506070 Time (days)

Fig. 8. Field data and model simulations of butane and dissolved oxygen concentrations at the S1 monitoring well in the bioaugmented well leg, 1 m from the injection well. Oxygen and butane addition began shortly before bioaugmentation on day 9. Butane and oxygen pulse lengths were increased on day 20, which resulted in a higher butane residual at the S1 well, which corresponded to a loss of CAH removal eﬃciency (Fig. 9). The pulse lengths were shortened on day 40, and after two to three weeks, eﬃcient butane utilization was re-established. L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546 1543

80 g/L)

μ 60

20 1,1-DCE Conc ( 0 0 10203040506070 Time (days)

250

g/L) 200 μ

150

100

50 1,1-DCA Conc ( 0 0 10203040506070 Time (days)

250

g/L) 200 μ

150

100

50 1,1-TCA Conc ( 0 0 10203040506070 Time (days)

Fig. 9. Field data and model simulations of 1,1-DCE, 1,1-DCA, and 1,1,1-TCA concentrations in the bioaugmented well leg. The thin dashed lines represent measured injection concentrations; the thin solid lines represent measured concentrations in the S1 monitoring well 1 m from the injection well; the thick solid lines represent model simulations at the S1 well. The culture was bioaugmented on day 9 and maximum CAH removal occurred around day 20. The butane and oxygen pulse lengths were increased on day 20, which resulted in a loss of CAH removal eﬃciency. The pulse lengths were shortened on day 40 and 1,1-DCE removal increased, but there was no recovery of 1,1-DCA or 1,1,1-TCA removal.

On day 20 of the test, the pulse cycles were lengthened to The field observations of 1,1-DCE, 1,1-DCA, and,1,1,1- 2 h (butane) and 22 h (oxygen), a great increase over the TCA show consistent trends with the laboratory results earlier cycle of time of about 1 h (Table 4). Both field with respect to the rates and extent of removal (Fig. 9). observations and model simulations show an increase and 1,1-DCE was the most rapidly transformed and was greater fluctuations in butane concentration. Around 30 removed to the greatest extent followed by 1,1-DCA. days, the duration of the butane pulse interval was 1,1,1-TCA was the least effectively transformed. This is decreased to 1 hr (butane) and 22 h (oxygen), which best illustrated by the initial removals achieved, from 18 resulted in lower and less fluctuations in butane concentra- to 21 days. Simulations and field observations at the S1 tion, and an increase in the dissolved oxygen concentra- monitoring well show 1,1-DCE, 1,1-DCA, and 1,1,1-TCA tion. The model simulations provide similar responses as maximum removals of 97 %, 77%, and 36%, respectively the field observations. At 40 days, the total pulse duration (Table 7). was decreased to that of the start of the test, less that 1 hr. The simulations show a similar response to the increase This resulted in a greater delivery of butane to the test leg. in pulse cycle length at around 20 days, with increases in all Simulated butane concentrations increased over the period three CAHs occurring. This partly results from butane not of 40–48 days. Field observations show a more delayed being effectively consumed with the longer pulse cycle, increase in butane, which may indicate butane transport which results in inhibition of CAH transformation. Simula- was retarded, which was not included in the model simulations also indicate a decrease in the biomass, as a result of tions. A decrease in butane and oxygen concentrations, at 1,1-DCE transformation toxicity and less butane addition, 50–60 days, indicates a restimulation of butane-utilizing may be responsible for the loss in cometabolic treatment. microorganisms. Over the period of 60–70 days, stable, Upon the initiation of the short pulse cycles at 40 days, low concentrations of butane were observed and simulated. and restimulation of butane utilizers, cometabolic 1544 L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546

Table 7 CAH removal efficienciesa during different periodsb of the bioaugmentation demonstration at wells S1 and S3 Bioaugmented 1,1,1-TCA % 1,1-DCA % 1,1-DCE % Indigenous 1,1,1-TCA % 1,1-DCA % 1,1-DCE % East Leg removal removal removal West Leg removal removal removal Well S1 20 days 36 77 97 20 days 0 0 0 38 days 0 0 3 38 days 0 0 0 65 days 0 0 80 65 days 0 0 76 Well S3 20 days 31 63 81 30 days 0 0 0 38 days 0 0 14 38 days 0 0 0 65 days 2 8 94 65 days 0 5 86 a Removal efficiencies were calculated after adjusting monitoring well CAH concentrations by the relative amount of bromide tracer capture at the same well. b The three time points chosen for comparison correspond to: (1) 20 days – the point of maximum CAH transformation in the bioaugmented leg, (2) 38 days – a time when CAH treatment in the bioagmented leg was lost and complete butane utilization in the indigenous leg had not yet been achieved, (3) 65 days – after pulse lengths were shortened and complete butane utilization and 1,1-DCE transformation were observed in both well legs. treatment of 1,1-DCE was achieved (50–70 days) in tation culture that showed 1,1-DCE was the most rapidly response to effective butane utilization. The model, how- transformed, followed by 1,1-DCA, and 1,1,1-TCA. The ever, over-predicts the amount of 1,1-DCA and 1,1,1- results are also consistent with the results of laboratory TCA removal. A likely explanation of the poorer removal studies which showed that 1,1-DCA and 1,1,1-TCA trans- is that the bioaugmented microorganisms were no longer a formations were inhibited by the presence of butane, and dominant population in the test zone. Upon restimulation removal of butane to low concentrations was required for at later time, an indigenous butane-utilizing population effective transformation to be achieved. was likely responsible for much of the butane consumption The effective transformation of CAHs that was achieved and 1,1-DCE transformation. in the bioaugmented leg early in the tests was lost during a Observations from the indigenous biostimulated leg period when long terms pulses of butane (1–2 h) and oxy- (data not shown) support our hypothesis that indigenous gen (23 h) were initiated. Results of a modeling analysis butane utilizers and not the bioaugmented culture were of the results of these tests indicated that less butane was dominant in both experimental legs in the latter stages of introduced during the longer pulse cycles, and this was the tests. During the initial stages of the biostimuation tests partly the reason for the loss in activity, combined with (0–40 days) there was little evidence of butane consumption 1,1-DCE transformation toxicity. The bioaugmented pop- or any CAH transformation in the indigenous leg. After 50 ulation may also have been established close to the injec- days of butane and oxygen addition, butane and oxygen uti- tion well. Thus, the change to the long pulse cycle may lization became apparent. By the end of the test (60–70 have limited the oxygen and butane required for their days), some transformation of 1,1-DCE was observed and maintenance. Thirty-eight days into the test, the CAH rem- about 80% removal was achieved, in the indigenous leg. ovals were greatly decreased in the bioaugmented leg, with Table 7 presents a summary of the percent removals that essentially no removal of 1,1,1-TCA being achieved, and were achieved in the bioaugmented and indigenous treat- with very limited removal of 1,1-DCA and 1,1-DCE. Of ment legs. Estimates are based on observations at the S1 the three CAHs, 1,1-DCE was removed to the most signif- and S3 monitoring wells. In the bioaugmented leg, all three icant extent. In contrast, little removal of CAHs was CAHs were being removed 20 days into the test (11 days achieved on the West indigenous leg over the same time after bioaugmentation), to different extents. 1,1-DCE was period. removed to the greatest extent, followed by 1,1-DCA and The initiation of the short pulse cycles after 40 days of some 1,1,1-TCA. All the removal was essentially achieved operation resulted in 1,1-DCE removal in both the bioaug- within 1 m of travel, consistent with butane removal. This mented and indigenous legs. The results demonstrated that combined with the short pulse interval resulted in essen- indigenous butane utilizers were present in the aquifer that tially all the transformation occurring within 1 meter of were capable of 1,1-DCE transformation. 1,1-DCE was travel. In contrast, no removal of the CAHs occurred in more effectively transformed along the bioaugmented leg the indigenous West Leg over the same period. The results than the indigenous leg (Table 7). 1,1-DCA and 1,1,1- are consistent with butane and oxygen concentrations TCA were not removed along the indigenous leg, and lim- along the leg, which showed little removal at early time. ited removal was observed along the bioaugmented leg. The results show that the bioaugmentation culture was Butane and CAH removal differed spatially along the bio- effective in decreasing lag times for biostimulation as augmented leg during the later period of short pulses (40– well as in promoting the biotransformation of 1,1-DCE, 70 days) compared to the earlier period (10–20 days). 1,1-DCA, and 1,1,1-TCA. The results are also consistent Butane uptake and CAH removal was more distributed with the results of laboratory studies with the bioaugmen- along the test zone during the latter period. For example, L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546 1545 in the latter stages of the test 1,1-DCA and 1,1-DCE rem- field, such as the loss in transformation that was observed. ovals increased from the S1 to the S3 wells. The results 1,1-DCE transformation product toxicity, represented by indicate more distributed biostimulation of the test zone, the low Tc DCE value, was required to simulate the micro- likely with indigenous butane-utilizing microorganisms cosm responses and was also required to match the field that have limited ability to transform 1,1-DCA and 1,1,1- observations. Model simulations also indicated that less TCA. butane was added to the field during the periods of longer pulse cycles, and butane utilization decreased during this 6. Discussion period (days 20–40). Higher residual butane concentrations were associated with a lower butane-utilizing biomass and The combination of laboratory, field, and modeling a loss of CAH transformation. Since butane was added in analysis provides a means of investigating the cometabo- short pulses cycles in the field test, it was difficult to time lism of mixtures of CAHs at the field scale. The potential sampling of the injection stream to determine the exact for bioaugmentation of a culture was also evaluated. amounts of butane that were added. We therefore used Microcosm tests demonstrated effective bioaugmentation field oxygen concentrations to provide a guide to the of the culture and using the kinetic, inhibition, and prod- amount of butane added, and adjusted butane addition uct toxicity values defined by Kim et al. [16,17] with some to match oxygen levels observed in the field tests. adjustments, model simulations matched butane utiliza- The model predicted significantly more 1,1-DCA trans- tion and CAH transformation well in batch reactors with formation for the latter period of the simulations (days 60– media and in microcosm tests. The similarities included 70) than was indicated by field data. It also predicted that the order of transformation (1,1-DCE transformed first, slightly more 1,1,1-TCA should be transformed. These dif- followed by 1,1-DCA and then 1,1,1-TCA), the strong ferences were possibly due to changes in the microbial com- inhibition of butane on 1,1,1-TCA transformation, and munity within the test zone. It is likely that an indigenous the high product toxicity of 1,1-DCE. The laboratory population was eventually stimulated and the bioaug- experiments and the model simulations illustrated the mented population diminished. This was supported by model’s ability to capture such trends using primarily observations from a non-bioaugmented control test leg independently determined parameter values. These values which had been treated in the same manner as the aug- were then used to simulate the results of the field exper- mented leg. In the control leg, butane utilization was iments. Butane inhibition of CAH transformation and observed and 1,1-DCE was transformed at a later time, 1,1-DCE transformation product toxicity were shown to while 1,1,1-TCA and 1,1-DCA were not transformed. This be important factors. is consistent with reports of other butane-utilizing cultures Field responses and simulations indicated that bioaug- described by Hamamura et al. [8], an enrichment culture mentation and biostimulation of the test leg was initially (CF8) and a pure culture of Psuedomonas butanovora, that successful, decreasing the lag time for biostimulation and could not effectively transform 1,1,1-TCA. Based on this providing a culture that transformed the CAH mixture. information, the modeling results would suggest that the After bioaugmentation (days 9–20) there was good trans- indigenous microorganisms predominated at the later time. formation of 1,1-DCE, 1,1-DCA, and 1,1,1-TCA, with We do not know if this change would have occurred with- the latter two lagging behind until significant butane had out the change to the long pulse cycles, combined with lim- been consumed and reduced to low concentrations. This ited butane addition, and prolonged exposure of 1,1-DCE. followed the observations from the laboratory experiments, More complicated models that would include multiple where 1,1-DCE was quickly transformed (due to its high microbial populations with different kinetic parameters transformation rate) and 1,1-DCA and 1,1,1-TCA were would be needed to try to simulate such changes, which inhibited by butane. Transformation of all three CAHs are beyond our current understanding of the microbial was lost when butane and oxygen pulsing cycles were elon- community dynamics. The use of molecular microbial anal- gated (days 20–40). 1,1-DCE transformation returned ysis methods would help demonstrate that changes in the when pulsing was shortened again (days 40–75). 1,1-DCE microbial community did occur. Despite these limitations, concentrations oscillated over the period of 60–70 days. the modeling approach was useful and simulated expected We do not know if these oscillations resulted from compet- transformation responses to bioaugmentation and biosti- itive inhibition due to the pulsing of butane. The model mulation. The strong inhibition by butane required accu- 1 employed equilibrium sorption (Fk = 2.0 d ), compared rate modeling of the butane responses, since CAH 1 to lower first-order mass transfer kinetics (Fk = 0.2 d ), transformation was so tied to butane biomass and butane which likely resulted in a dampening of concentration oscil- concentrations. The processes of inhibition and transfor- lations due to inhibition by butane. mation product toxicity were shown to be important fac- The modeling analysis of the field tests indicated poten- tors that needed to be considered. tial reasons for the loss in activity and recovery later in the The modeling effort, despite such complexities as tests. The modeling analysis also helped explore how oper- inhibition and product toxicity and other factors, simu- ating factors, such as longer pulse cycles and less butane lated trends observed in the field. The model analysis addition may have affected the responses observed in the permitted complex interactions of transport, sorption, 1546 L. Semprini et al. / Advances in Water Resources 30 (2007) 1528–1546 biostimulation, and cometabolic transformation kinetics, trichloroethane in groundwater microcosms. Biodegradation 2001;12: including inhibition, to be simulated. This permitted us 11–22. to evaluate how well laboratory derived kinetic parameters [14] Kim Y, Semprini L, Arp D. Aerobic cometabolism of chloroform and 1,1,1-trichloroethane by butane-grown microorganisms. Bioremedia- simulated field responses, and how changes such as pulse tion J 1997;1(2):135–48. duration, and butane addition potentially affected the over- [15] Kim Y, Arp DJ, Semprini L. Chlorinated solvent cometabolism by all performance observed in the field. butane-grown mixed culture. J Environ Eng 2000;126:934–42. [16] Kim Y, Arp D, Semprini L. A combined method for determining inhibition type, kinetic parameters, and inhibition coefficients for Acknowledgements aerobic cometabolism of 1,1,1-trichloroethane by a butane-grown mixed culture. Biotechnol Bioeng 2002;77(5):564–76. This research was funded by the Department of Defense [17] Kim Y, Arp DJ, Semprini L. Kinetic and inhibition studies for the Strategic Environmental Research Development Program aerobic cometabolism of 1,1,1-trichloroethane, 1,1-dichloroethylene, and 1,1- dichloroethane by a butane-grown mixed culture. Biotechnol (SERDP) as Project CU-1127. This paper has not been re- Bioeng 2002;80:498–508. viewed by this agency, and official endorsement should be [18] Li J. Molecular analysis of bacterial community dynamics during inferred. bioaugmentation studies in a soil column and at a field test site. Masters Thesis, Department of Civil, Construction, and Environ- mental Engineering, Oregon State University; 2004. References [19] Mackey D, Shui WY. Review of Henry’s law constants for chemicals of environmental interest. J Phys Chem Ref. Data 1981;10(4): [1] Alvarez-Cohen L, McCarty PL. Product toxicity and cometabolic 1175–99. competitive inhibition modeling of chloroform and trichloroethylene [20] Mathias M. 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