Abstract: INTRODUCTION

Transcription

1 HYDROLOGICAL PROCESSES Hydrol. Process. 22, (2008) Published online 10 September 2008 in Wiley InterScience ( A kinetic approach for simulating redox-controlled fringe and core biodegradation processes in groundwater: model development and application to a landfill site in Piedmont, Italy Massimo Rolle, 1 * T. Prabhakar Clement, 2 Rajandrea Sethi 1 and Antonio Di Molfetta 1 1 Dipartimento del Territorio, dell Ambiente e delle Geotecnologie, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Torino, Italy 2 Department of Civil Engineering, 212 Harbert Engineering Center, Auburn University, AL , USA Abstract: A three-dimensional model for predicting redox controlled, multi-species reactive transport processes in groundwater systems is presented. The model equations were fully integrated within a MODFLOW-family reactive transport code, RT3D. The model can simulate organic compound biodegradation coupled to different terminal electron acceptor processes. A computational approach, which uses the spatial and temporal distribution of the rates of different redox reactions, is proposed to map redox zones. The method allows one to quantify and visualize the biological degradation reactions occurring in three distinct patterns involving fringe, pseudo-core and core processes. The capabilities of the numerical model are demonstrated using two hypothetical examples: a batch problem and a simplified two-dimensional reactive transport problem. The model is then applied to an unconfined aquifer underlying a leaking landfill located near the city of Turin, in Piedmont (Italy). At this site, high organic load from the landfill leachate activates different biogeochemical processes, including aerobic degradation, denitrification, manganese reduction, iron reduction, sulfate reduction and methanogenesis. The model was able to describe and quantify these complex biogeochemical processes. The proposed model offers a rational framework for simulating coupled reactive transport processes occurring beneath a landfill site. Copyright 2008 John Wiley & Sons, Ltd. KEY WORDS redox zonation; TEAPs; reaction rates; reactive transport modelling; landfill; leachate Received 31 October 2007; Accepted 18 June 2008 INTRODUCTION The release of organic pollutants into the subsurface can activate multiple biogeochemical reaction processes such as sorption, ion exchange, precipitation/dissolution and redox reactions. The most important biochemical processes that control the fate and transport of pollutants in groundwater are the microbially mediated redox reactions. Microorganisms can degrade an organic pollutant through different types of terminal electron acceptor processes (TEAPs) such as aerobic respiration, denitrification, Mn(IV) reduction, Fe(III) reduction, sulfate reduction and methanogenesis. These redox processes occur in sequential order, which is controlled by the level of free energy generated during the electron acceptor consumption reaction (Table I). However, the spatial distribution of these reactions would not only depend on the free energy level, but also on the availability of appropriate microbes, organic substrates, nutrients and electron acceptors, and on the kinetics of the degradation reactions. * Correspondence to: Massimo Rolle, University of Tuebingen, Centre for Applied Geoscience, Sigwartsrtasse 10, D-72076, Tuebingen, Germany. massimo.rolle@uni-tuebingen.de A succession of redox zones (as shown in Figure 1) is commonly observed in many sites contaminated by oxidizable organic compounds (Baedecker and Back, 1979; Chapelle et al., 1995, 2002; Christensen et al., 2001; Cozzarelli et al., 2001; Brun et al., 2002; Van Breukelen et al., 2004). Unique biogeochemical conditions available within these zones may selectively favour biodegradation of the contaminant and make a significant contribution to the overall rate of degradation. At the plume fringe, processes involving soluble electron donors and acceptors are typically active (Cirpka et al., 1999; Lerner et al., 2000; Maier and Grathwohl, 2006). These reactions are primarily limited by the diffusive flux driven by transverse dispersion, where soluble electron acceptors such as O 2,NO 3 and SO 4 2 diffuse inwards, from the surrounding groundwater, and are made available for bacteria to support the degradation process. On the other hand, at the plume core, various anaerobic degradation processes such as iron reduction, manganese reduction, and methanogenesis are active (Christensen et al., 2001; Cozzarelli et al., 2001; Chapelle et al., 2002; Schreiber et al., 2004). The efficiency and distribution pattern of these biodegradation reactions are often determined by the availability of the electron donors or acceptors that are originally present or are released from the solid aquifer matrix. Copyright 2008 John Wiley & Sons, Ltd.

2 4906 M. ROLLE ET AL. Table I. Redox reactions in aquifers contaminated by oxidizable organic compounds. The formula CH 2 O represents the organic material; the values for the standard Gibbs free energy at ph D 7 were taken from Christensen et al. (2001) Process Redox reaction 1G (kcal mol 1 ) Aerobic respiration CH 2 O C O 2! CO 2 C H 2 O 120 Denitrification 5CH 2 O C 4NO 3 C 4H C! 5CO 2 C 2N 2 C 7H 2 O 114 Manganese reduction CH 2 O C 2MnO 2 C 4H C! CO 2 C 2Mn 2C C 3H 2 O 81 Iron reduction CH 2 O C 4Fe(OH) 3 C 8H C! CO 2 C 4Fe 2C C 11H 2 O 28 Sulfate reduction 2CH 2 O C SO 2 4 C H C! 2CO 2 C HS C 2H 2 O 25 Methanogenesis 2CH 2 O C CO 2! CH 4 C 2CO 2 22 Figure 1. Conceptual model for groundwater redox zonation Multi-species reactive transport models that can simulate coupled biogeochemical processes are useful tools for describing the complex subsurface environments and for designing remediation systems (Clement et al., 2000, 2002, 2004; Barry et al., 2002; Prommer et al., 2003, 2006; Thullner et al., 2005; Kim, 2005; Lim et al., 2007; Radu et al., 2008). In this study, a comprehensive kinetic model for predicting the transient evolution patterns of redox zones in a contaminated aquifer is presented. We also propose an approach that uses the TEAPs reaction rates, instead of the dominant redox species concentrations, to delineate the spatial and temporal variations of the redox zonation. The model is then applied to simulate the fate and transport of organics contaminants released into a shallow aquifer underlying a leaking landfill located near the city of Turin, in Piedmont (Italy). MATHEMATICAL MODEL A kinetic model, named Kin REDOX, was developed using the user-defined reaction module framework of the reactive transport code RT3D (Clement, 1997; Clement 1998). The general macroscopic equations describing the fate and transport of aqueous- and solid-phase species in a multi-dimensional aquifer can be written as (Clement, 1997): C k t D ( x i D ij Ð C k x j where k D 1, 2,...m ) x i v i Ð C k C q s C s k C r c 1 QC l DQr c where l D 1, 2,...n m 2 t with n total number of species m total number of aqueous phase (mobile) species n m total number of solid or immobile species C k aqueous phase concentration of the kth species [ML 3 ] QC l solid phase concentration of the lth species [MM 1 ] D ij hydrodynamic dispersive tensor [L 2 T 1 ] v i pore velocity in the ith direction [LT 1 ] volumetric flux of water per unit volume of aquifer representing sources and sinks [T 1 ] C sk source/sink concentration of the kth species [ML 3 ] q s effective porosity r c reaction rate in the aqueous phase [ML 3 T 1 ] Qr c reaction rate in the solid phase [MM 1 T 1 ] The Kin REDOX module describes the reactive transport of 10 different species that include eight mobile and two immobile species. The dissolved, mobile species are the organic substrate (CH 2 O), the electron acceptors

3 REDOX-CONTROLLED FRINGE AND CORE BIODEGRADATION PROCESSES IN GROUNDWATER 4907 (O 2,NO 3,SO 4 2 ), the metabolic by-products (Mn 2C, Fe 2C,CH 4 ) and a conservative tracer. The solid immobile species are pyrolusite (MnO 2 ) and amorphous iron hydroxide (Fe(OH) 3 ). The kinetics of various biodegradation reactions that use different TEAPs are assumed to be first-order with respect to the organic substrate (CH 2 O). Monod terms were used to account for different electron acceptor limitations. By assuming firstorder kinetics with respect to the organic compound, we assume that saturation with respect to the substrate is never reached or, in other words, that the microbial population mediating the biodegradation process is always available and would continue to respond to any increases in the supply of the organic substrate. Another important assumption used in the model is that the organic contaminant is treated as a single electron donor (CH 2 O). This approach ignores different fractions of organic material that may be characterized by different levels of biodegradability. The model allows biodegradation only when the organic contaminant and the electron acceptor are in direct contact; this is expressed in the mathematical formulation by incorporating the simultaneous dependence of electron donor and electron acceptor in all the reaction rate equations. An inhibition model was used to describe sequentially active metabolic pathways. The general framework of the model is similar to the one presented by Lu et al. (1999), which was applied to simulate the natural attenuation of BTEX compounds. However, in the Lu et al. (1999) model, iron reduction and methanogenic reactions are described using an empirical approach. In this work, we use a more fundamental approach to model these reactions by tracking the reactive minerals present in the sediment matrix (Heron et. al., 1994). The measured concentrations of solid electron acceptors can be used directly in the kinetic formulation of the proposed model. Biodegradation processes are described by writing the reaction rate terms in the governing transport Equations (1) and (2) as: [O 2 ] r CH2 O/O 2 D k O2 [CH 2 O] K O2 C [O 2 ] [NO 3 ] r CH2 O/NO 3 D k NO3 [CH 2 O] K NO3 C [NO 3 ] K i,o2 K i,o2 C [O 2 ] [MnO 2 ] r CH2 O/Mn D k Mn [CH 2 O] K MnO2 C [MnO 2 ] K i,o2 K i,no3 K i,o2 C [O 2 ] K i,no3 C [NO 3 ] [Fe OH 3 ] r CH2 O/Fe D k Fe [CH 2 O] K Fe OH 3 C [Fe OH 3 ] K i,o2 K i,no3 K i,o2 C [O 2 ] K i,no3 C [NO 3 ] K i,mno2 K i,mno2 C [MnO 2 ] [SO 4 ] r CH2 O/SO 4 D k SO4 [CH 2 O] K 2 SO4 C [SO 4 ] K i,o2 K i,no3 K i,o2 C [O 2 ] K i,no3 C [NO 3 ] K i,mno2 K i,mno2 C [MnO 2 ] K i,fe OH 3 K i,fe OH 3 C [Fe OH 3 ] K i,o2 r CH2 O/CH 4 D k CH4 [CH 2 O] K i,o2 C [O 2 ] K i,no3 K i,mno2 6 7 K i,no3 C [NO 3 ] K i,mno2 C [MnO 2 ] K i,fe OH 3 K i,fe OH 3 C [Fe OH 3 ] K i,so4 K i,so4 C [SO 4 ] 8 where r CH2O/EAi are the kinetics of degradation of CH 2 Ofollowing the different TEAPs [ML 3 T 1 ] k EAi are the degradation constants [T 1 ] K EAi are the half-saturation Monod constants [ML 3 ] K i,eai are the inhibition coefficients [ML 3 ]. The overall degradation kinetic of the organic material via the six different metabolic pathways can be expressed by the equation: r CH2 O,TOT D d[ch 2O] D r CH2 O/O 2 C r CH2 O/NO 3 C r CH2 O/Mn C r CH2 O/Fe C r CH2 O/SO 4 C r CH2 O/CH 4 9 The consumption of electron acceptors and the formation of metabolic by-products can be expressed by multiplying the CH 2 O degradation kinetics by appropriate stoichiometric yield coefficients (Y): r O2 D d[o 2] D Y O2 /CH 2 O Ð r CH2 O/O 2 10 r NO3 D d[no 3] D Y NO3 /CH 2 O Ð r CH2 O/NO 3 11 r Mn 2C D d[mn2c ] D Y Mn /CH 2 O Ð r CH2 O/Mn 12 r Fe 2C D d[fe2c ] D Y Fe /CH 2 O Ð r CH2 O/Fe 13 r SO4 D d[so 4] D Y SO4 /CH 2 O Ð r CH2 O/SO 4 14 r CH4 D d[ch 4] D Y CH4 /CH 2 O Ð r CH2 O/CH 4 r Tracer D d[tracer] D

4 4908 M. ROLLE ET AL. Table II. Stoichiometric yield coefficients for the oxidation of CH 2 O under different TEAPs. The values are expressed as mass ratio between electron acceptor (and/or metabolic product) and electron donor Process Aerobic respiration Denitrification Manganese reduction Iron reduction Sulfate reduction Methanogenesis Stoichiometric yield coefficient Y O2/CH2O D 1Ð07 Y NO3/CH2O D 1Ð65 Y Mn2C/CH2O D 3Ð67 Y MnO2/CH2O D 5Ð8 Y Fe2C/CH2O D 7Ð47 Y Fe OH 3/CH2O D 14Ð27 Y SO4/CH2O D 1Ð6 Y CH4/CH2O D 0Ð27 r MnO2 D d[mno 2] D Y MnO2 /CH 2 O Ð r CH2 O/Mn r Fe OH 3 D d[fe OH 3] D Y Fe OH 3 /CH 2 O Ð r CH2 O/Fe Assuming that the dissolved organic compound can be expressed by the general formula CH 2 O and that the microbial populations that carry out the degradation reactions are at steady state conditions, the stoichiometric yield coefficients can be calculated (Table II) from the redox reactions given in Table I. RESULTS AND DISCUSSION The kinetic model described above was coded in FOR- TRAN and was implemented as a user-defined module within the multi-species reactive transport code RT3D. The resulting code was used to simulate different types of scenarios. In the following sections results are presented for (1) a batch (zero dimension) problem, (2) a two-dimensional problem, and (3) a field problem. Batch simulation results The hypothetical batch problem considers biodegradationof20mgl 1 of an organic compound in a reactor containing natural sediments that support all the TEAPs described by the model. The simulations were completed using the kinetic parameters and the initial conditions summarized in Table III. The upper plot of Figure 2 shows the concentration profiles of the reactive species from time zero through 50 days. The decreasing trend of the organic contaminant concentration results from biodegradation with the sequential utilization of the different electron acceptors. As shown in Figure 2a, in this system, oxygen is depleted first followed by nitrate and then by the solid species MnO 2 and Fe(OH) 3, which produce dissolved Mn 2C and Fe 2C, respectively. Later, sulfate started to be consumed and finally methane was produced under the most reducing (methanogenic) conditions. The conservative tracer did not undergo any Table III. Baseline input parameters used in the batch simulation Model parameters Kinetic parameters Aerobic degradation constant, k O2 Denitrification degradation constant, k NO3 Mn-reduction degradation constant, k Mn Fe-reduction degradation constant, k Fe Sulfate reduction degradation constant, k SO4 Methanogenesis degradation constant, k CH4 Oxygen half-saturation constant, K O2 Nitrate half-saturation constant, K NO3 Manganese half-saturation constant, K MnO2 Iron half-saturation constant, K Fe OH 3 Sulfate half-saturation constant, K SO4 Methane half-saturation constant, K CH4 Oxygen inhibition constant, K i,o2 Nitrate inhibition constant, K i,no3 Manganes inhibition constant, K i,mno2 Iron inhibition constant, K i,fe OH 3 Sulfate inhibition constant, K i,so4 Initial Conditions CH 2 O O 2 NO 3 Mn 2C Fe 2C 2 SO 4 CH 4 Tracer MnO 2 Fe(OH) 3 0Ð15 d 1 0Ð12 d 1 0Ð11 d 1 0Ð10 d 1a 0Ð09 d 1 0Ð08 d 1 0Ð01 mg L 1 0Ð01 mg L 1 0Ð01 mg L 1 0Ð01 mg L 1b 0Ð01 mg L 1c 20 mg L 1 3mgL 1 8mgL 1 0Ð1 mgl 1 0Ð1 mgl 1 5mgL 1 0Ð01 mg L 1 10 mg L 1 14Ð24 mg L 1d 38Ð21 mg L 1d a Set to 0Ð03 d 1 to generate Figure 3b b Set to 100 mg/l to generate Figure 3a c Set to 0Ð5 mg/l to generate Figure 3b d Calculated from matrix concentration of Mn(IV) D 1Ð59 mg kg 1 and Fe(III) D 3Ð53 mg kg 1, assuming a bulk density D 1700 kgm 3 and a porosity D 0Ð3. reaction and remained constant at the initial concentration level throughout the simulation. A data processing method was developed to calculate the transient reaction rates which can be used to visualize the time sequence of the redox reactions. The results shown in Figure 2b illustrate the succession of TEAPs, which were coded in a sequential order based on their thermodynamic energetic yields. At the beginning of the simulation, aerobic degradation was the predominant redox process. When the available dissolved oxygen was depleted, nitrate reduction occurred. The sequential degradation of the organic compounds through the TEAPs proceeded up to methanogenesis reaction, which was dominant at higher simulation times when all other electron acceptors were fully consumed. Figure 3 shows the results of two sets of additional batch simulations that were used to illustrate the versatility of the kinetic model developed in this study. Figure 3a shows the concentration profiles and the reaction rates for a batch simulation in which the processes of iron

5 REDOX-CONTROLLED FRINGE AND CORE BIODEGRADATION PROCESSES IN GROUNDWATER 4909 Figure 2. Batch results: (a) concentration and (b) reaction-rate profiles computed using Kin REDOX reduction and sulfate reduction are allowed to overlap. The model input used in this simulation was identical to the previous simulation (Table III), except the iron inhibition constant was set to a significantly higher value (100 mg L 1 instead of 0Ð01 mg L 1 ). This allowed the two TEAPs to occur simultaneously. Figure 3b illustrates the result of another simulation with slower iron reduction kinetics and partial overlapping between sulfate reduction and methanogenesis. The parameters modified in this simulation were the kinetic rate constant for iron reduction (k Fe D 0Ð03 d 1 instead of 0Ð1 d 1 ) and the sulfate inhibition constant (K i,so4 D instead of 0Ð01 mg L 1 ). The slower Fe(III)- reduction rate caused slower degradation of the organic compound and also slower consumption of the solid electron acceptor, as can be observed from the concentration profiles shown in the upper plot of the figure. Moreover, production of methane started before the complete utilization of sulfate. Two-dimensional transport simulation results The two-dimensional example simulates the redox zone segregation pattern in a shallow aquifer after the release of an organic contaminant from a point source. Figure 4 shows the problem geometry and boundary conditions. The flow field was simulated with MODFLOW (Harbaugh et al., 2000) and the RT3D code with the new Kin REDOX package was used to simulate the reactive transport. The flow and transport parameters for the problem are summarized in Table IV. The kinetic parameters used were identical to those used in the batch problem (Table III), except the degradation constants were set to 0Ð18, 0Ð11, 0Ð07, 0Ð01, 0Ð01, 0Ð009 d 1 for aerobic degradation, denitrification, manganese reduction, iron reduction, sulfate reduction and methanogenesis, respectively. Figure 5 shows the model simulation results after2 years of reactive transport. The results indicate that the simulated biodegradation processes clearly limit the down-gradient migration of the organic contaminant plume; this can be inferred by comparing the dimensions of the contaminant plume with the tracer plume. The figures also show that down-gradient from the source, the soluble electron acceptors (O 2,NO 3 and SO 4 2 ) are depleted in a sequential manner. Furthermore, reaction product plumes of Mn 2C,Fe 2C and CH 4 are also formed and transported in the down-gradient direction. The Mn 2C and Fe 2C species formed from the depletion

6 4910 M. ROLLE ET AL. Figure 3. Batch simulations with overlapping TEAP profiles: (a) iron inhibition constant (K i,fe OH 3 ) set to 100 mg L 1 ; (b) iron reduction degradation constant (k Fe )setto0ð03 d 1 and sulfate inhibition constant (K i,so4 )setto Figure 4. Geometry and boundary conditions for the 2D test problem of mineral species MnO 2 and Fe(OH) 3, respectively, form an interesting double-ellipse pattern. These patterns are generated due to the down-gradient transport of dissolved Mn(II) and Fe(II) species by advection. The traditional approach for delineating redox zones by means of reactive transport codes is based on the simulated distribution of the reactive species concentrations (Essaid et al, 1995; Abrams 2000a, b; Brun et al., 2002). This approach can be problematic for manganese, iron reduction and methanogenic systems, where the predominant reaction products such as Mn 2C,Fe 2C or CH 4 can be transported downstream by advection. Therefore, the presence of these reaction products in a node point may not be a good indicator for the status of the active TEAP at that location. We propose an alternative approach where one should map the reaction rates of various TEAPs to track the evolution patterns of the redox zones. The relative values of the reaction rates for a

7 REDOX-CONTROLLED FRINGE AND CORE BIODEGRADATION PROCESSES IN GROUNDWATER 4911 certain TEAP indicate the level of activity of the process at a certain space and time. The reaction rate expressions (Equations (3) (8)) were coded into a post-processing routine to estimate directly the reaction rates from the transient concentration dataset output by the RT3D code. The spatial variations in the reaction rates allowed delineation of the redox zones over the entire two-dimensional domain. Direct use of these rate values is an alternative and improved approach to compute the spatial extent of different reaction zones. The delineated extent of the redox zones for the example problem (after 2 years of transport) are shown in Figure 6. The zones indicate distinct patterns that are the result of the three distinct types of mixing processes identified in this study: fringe, core, and pseudo-core processes. We use fringe process to designate reactions which require mixing of an electron acceptor and an electron donor (e.g. aerobic degradation); this reaction is facilitated by dispersion induced mixing and will occur primarily at the fringe of the contaminant plume. We use core process to designate reactions which does not require mixing between electron acceptor and donor (e.g. methonogenic reaction); this reaction will occur in the core without the aid of any physical transport mechanisms. Finally, the term pseudo-core process is used to designate processes which are aided by advection to allow electron donor to come into contact with a solid-phase electron acceptor (e.g. reactions with iron and manganese oxides). Fringe processes. It can be observed in Figure 6 that the TEAPs related to aerobic degradation, denitrification, and sulfate-reduction reactions occur within a relatively thin fringe surrounding the core of the contaminant plume; therefore, they are designated as fringe processes. The presence of highly bioactive zones at the fringes of organic contaminant plumes has been observed both in the laboratory (Bauer et al., 2008) as well as in the field (Lerner et al., 2000; Maier and Grathwohl, 2006; Prommer et al., 2006). In these zones, the oxidizable contaminant (CH 2 O) and the soluble electron acceptors such as O 2,NO 3 and SO 4 2 are brought into contact through diffusion/dispersion controlled mixing processes. The fluxes of oxidants and reductants are transported in opposite directions and are mixed within the fringe to facilitate the reactions which occurin a sequential manner with the aerobic fringe enveloping the denitrification fringe, and the denitrification fringe in turn enveloping the sulfate reduction fringe. In the example problem (Figure 6), all these three processes are highly active at the left boundary of the plume (close to the source zone) since there is a sufficient supply of electron acceptors in this region transported by the regional groundwater flux advected from the left boundary. Core and pseudo-core processes. The manganese and iron reaction zones presented in Figure 6c and 6d also show fringe-type patterns. However, in this case, the mixing between the electron acceptor (manganese and iron oxides) and donor (carbon) is not controlled by Table IV. Model parameters used in the two-dimensional example problem Spatial and temporal discretization Model area Cells dimensions Simulation time Flow and transport parameters Saturated thickness Hydraulic conductivity Porosity Constant head (left BC) Constant head (right BC) Longitudinal dispersivity, x Transversal dispersivity, y Transport boundary conditions 510 m ð 310 m 1Ð25 m ð 1Ð25 m 1000 d 10 m 50 m d 1 0Ð3 100 m 99 m 10 m 0Ð3 x m Inlet: constant concentration Outlet: concentration gradient D 0 CH 2 O 0 mg L 1 O 2 3mgL 1 NO 3 8mgL 1 Mn 2C 0Ð1 mgl 1 Fe 2C 0Ð1 mgl 1 2 SO 4 5mgL 1 CH 4 0Ð01 mg L 1 Tracer 0 mg L 1 Initial conditions CH 2 O O 2 NO 3 Mn 2C Fe 2C 2 SO 4 CH 4 Tracer MnO 2 Fe(OH) 3 Contamination source 0 mg L 1 3mgL 1 8mgL 1 0Ð1 mgl 1 0Ð1 mgl 1 5mgL 1 0Ð01 mg L 1 0 mg L 1 14Ð24 mg L 1 38Ð21 mg L 1 Flow rate 2 m 3 d 1 CH 2 O concentration 1000 mg L 1 Tracer concentration 1000 mg L 1 dispersive processes at the fringe. Instead the mixing naturally occurs when the plume transverses over the electron acceptor rich minerals. A closer inspection of the shape of manganese and iron reaction zones indicates that most of the reduction of oxidized iron and manganese takes place at the right boundary of the plume (i.e. at the plume front which is far away from the source zone) where the organic contaminant contacts the aquifer portion rich with solid-phase electron acceptors, assumed to be present in the form of bioavailable manganese dioxide and iron hydroxide. If a system has a limited amount of bioavailable solid-phase electron acceptors then most of the reaction is expected to occur downgradient where the plume will come into contact with

8 4912 M. ROLLE ET AL. Figure 5. Concentration (mg L 1 ) maps of mobile and immobile species (T D 730 days) the pristine aquifer rich in solid electron acceptors. This leads to the development of a fringe-type reaction zone, although the actual reaction is a core process. The scenario changes dramatically when the plume is migrating into an aquifer with excess amount of solid electron acceptors. Under these conditions, the active iron reduction zone assumes the shape of a true inner core process. This concept is clearly illustrated in Figure 7, which shows the simulated reaction rates with low (3Ð53 mg kg 1 Fe(III) as reported in Table III) and very high (1000 times) solid iron hydroxides. The upper plots show the two-dimensional distribution of the reaction rates, while the lower plots show the profiles of iron reduction rates along the plume centreline. Note, not only is the shape of the active iron zones different between the two simulated scenarios, but also the absolute reaction rates are different and their values are considerably higher when iron concentrations are high.

9 REDOX-CONTROLLED FRINGE AND CORE BIODEGRADATION PROCESSES IN GROUNDWATER 4913 Figure 6. Computed redox zones; the reaction rates of the different TEAPs are calculated after a simulation time of 730 days and the rates are expressed in mg L 1 d 1 Figure 6f shows the extent of methanogenic reaction zone, which is a purely core process. The anaerobic degradation of organic compounds to methane can follow different pathways (Conrad, 1999). In this study it is assumed that the process can be described by a fermentation pathway and therefore the microorganisms mediating the process do not require an external electron acceptor. The mathematical description used in Kin REDOX assumes that the rate of methanogenesis depends only on the concentration of the organic compound (Equation (8)). In contaminated aquifers methanogenesis requires highly reducing conditions and hence can occur only within the plume core where the other competing electron acceptors are fully depleted. Furthermore, this process does not require any type of transport or mixing. The main product of methanogenesis (CH 4 ) is quite stable in anaerobic environments and hence can be transported down-gradient away from the methanogenic zone. The computed methanogenic region, mapped based on the reaction rates (Figure 6f), show that the process is active close to the contamination source where high concentrations of organic contaminant are available and the competing TEAPs are fully depleted. Figure 8 compares the delineated redox zones and the reaction product distribution for iron-reduction and methonogenic processes, which are mediated by core reactions. This comparison illustrates the benefits of using reaction rate values to delineate the location of the redox zones, instead of using the reaction by-products (such as Fe 2C and methane) as surrogate measures. We use a hypothetical observation well OW1 (shown in Figure 8) to further illustrate the importance of mapping the reaction zones. If one were to use a standard natural attenuation protocol, such as the one described in Wiedemeier et al. (1999), then the measured high concentrations of dissolved Fe(II) at the observation well OW1 would erroneously lead to a conclusion that iron reduction is active at that point. By computing the actual reaction rates of the iron reduction process

10 4914 M. ROLLE ET AL. Figure 7. Patterns of Fe-reduction. Reaction rate (mg L 1 d 1 ) maps and the corresponding centreline rate profiles at T D 730 days for low solid Fe(III) concentrations (pseudo-inner core process) and high solid Fe(III) concentrations (inner core process) Figure 8. Redox zones: comparison between computed concentrations (mg L 1 ) and reaction rates (mg L 1 d 1 ) it can be concluded that the active Fe(III)-reductive zone is located up-gradient of OW1. A similar argument can also be made for methanogenesis; the observed high methane concentration at the well OW2 does not indicate the presence of methanogenic activity near the well. The computation of the methanogenesis reaction rates allowed us to locate the active methanogenic zone, which is located up-gradient away from OW2. In both cases, the advection process transported the degradation by-products Fe 2C and methane towards the monitoring well, which was located away from the actual reaction zone. Therefore, we hypothesize that the

11 REDOX-CONTROLLED FRINGE AND CORE BIODEGRADATION PROCESSES IN GROUNDWATER 4915 measured concentrations of reaction by-products such as Fe 2C and methane may have little use in delineating the extent of the redox zone where the actual reaction occurred. Model application to a landfill site Site description. A landfill leachate plume present in a shallow unconfined aquifer was selected for the case study. The site is located in an agricultural area in the Piedmont region close to the city of Turin (Italy). It spreads over a m 2 area and includes a wide landfill area of about m 2. The site was a former sand and gravel pit and since the early 1970s it has been used for uncontrolled waste disposal activities. The landfill received a wide variety of wastes of both municipal and industrial origin. Because of the lack of any clay or HDPE liner, the contaminants migrated vertically from the landfill and impacted the underlying groundwater. The site is located in the western portion of the alluvial plane of the river Po. The shallow groundwater flows through the gravelly-sandy fluvial sediments and the depth to the water table ranges from m BGS. The shallow unconfined aquifer has a thickness of approximately m and is underlain by a silty-clay lens located at a depth of m. This impermeable layer, found at most of the sampling points, divides the shallow aquifer from the deep groundwater systems below the landfill area. The direction of groundwater flow below the landfill is from north-west to south-east. Groundwater levels measured in January 2003 are shown in the water table elevation map (Figure 9) together with the main source area located in the central zone of the site. The average hydraulic conductivity of the shallow aquifer is 6Ð9 ð 10 4 ms 1 and the groundwater velocity 1Ð2 ð 10 5 ms 1. Below the source zone a plume of dissolved organic contaminants developed and migrated down-gradient for an estimated length of approximately 400 m. The values of the principal geochemical parameters measured (during May 2003 survey) in the groundwater at a number of monitoring points located along the flow direction are shown in Figure 10. Analysis of the spatial variation of geochemical parameters clearly shows important redox processes occuring in the groundwater below the landfill. As the background aerobic groundwater (indicated by well-p3s data) flows through the site, considerable depletion of dissolved oxygen occurs. Hence, anaerobic conditions characterize the subsurface environment directly below the landfill and farther downgradient. Also, other dissolved electron acceptors, such as NO 3 and SO 2 4, show a decreasing trend. In particular, depletion of nitrate is clearly noticeable. The concentrations of NO 3 below the landfill are significantly lower than the background values. Metabolic by-products such as dissolved manganese, iron and methane are present in the contaminated groundwater. Dissolved iron concentrations dramatically increase in the central zone of the site, where high values are reached (as indicated by the value of 15Ð35 mg L 1 in SP17); then the concentration decreases to low values, as indicated by the measurement made in the down-gradient well PZE6. On the contrary, dissolved manganese concentrations show a more gradual increase, starting from very low background values. However, once high concentration levels are reached the levels appear to be maintained in the down-gradient direction. Modelling study. A two-dimensional modelling study was carried out with the aim of simulating the migration patterns of the contaminant plume and the redox zonation processes observed at the landfill site. The domain was discretized into rectangular cells, with uniform longitudinal and transversal cell spacings of 10 and 8Ð5 m, respectively. In the vertical direction, the shallow aquifer was considered as a single layer. The steady state simulations of the groundwater flow field were performed using the finite difference code MODFLOW (Harbaugh et al., 2000). Transport simulations were carried out using RT3D with the Kin REDOX module. The background groundwater chemistry, measured in the monitoring well P3S, was selected as the initial condition and was also used to represent the incoming clean groundwater (left boundary condition). Sediment samples collected up-gradient of the contamination source showed average values of Fe(III) and Mn(IV) as 1Ð9 mgg 1 and 0Ð4 mgg 1, respectively. These values were used as initial concentrations of the reactive minerals available in the aquifer. Continuous release of pollutants from the landfill was assumed to have started in the mid 1970s, when the site was used for uncontrolled waste disposal activities. It was estimated that the contamination event lasted for 25 years, which is the total simulation time used in this study. The release of organic compounds was represented by a recharge concentration condition with a flow of 200 mm year 1 over the entire simulation domain and a constant concentration of 5000 mg L 1 in the source area located in the middle of the landfill. A summary of other model parameters used in the simulations is given in Table V. The complex mixture of organic contaminants (i.e. volatile fatty acids, aliphatic hydrocarbons, mono- and polycyclic aromatic hydrocarbons, chlorinated aliphatic compounds and phenols) leaching from the landfill was represented in the numerical simulations as a generic carbon species CH 2 O, the electron acceptors and the metabolic products of the primary TEAPs were computed using the kinetic formulation described within Kin REDOX. A simplified first-order sink term was used to describe the complex suite of secondary removal reactions involving redox transformations, acid-base reactions, homogeneous complexation reactions, sorption, dissolution, precipitation of mineral phases, and abiotic transformation that affect the transport of the products of the primary TEAPs (Hunter et al., 1998). In order to account for the loss of the reaction products Mn 2C,Fe 2C and methane via one (or a combination) of these secondary removal mechanisms, the reaction terms in the kinetic equations for dissolved

12 4916 M. ROLLE ET AL. Figure 9. Site map, groundwater contours (m MSL) and lithological cross-section along the transect A A 0 manganese, iron and methane (Equations (11), (12) and (15)) were modified as: r Mn 2C D d[mn2c ] D Y Mn 2C /CH 2 O Ð r CH2 O/Mn k Mn 2C [Mn 2C ] r Fe 2C D d[fe2c ] D Y Fe 2C /CH 2 O Ð r CH2 O/Fe k Fe 2C [Fe 2C ] r CH4 D d[ch 4] D Y CH4 /CH 2 O Ð r CH2 O/CH 4 k CH4 [CH 4 ] where, in each equation, the first term expresses the production of the reduced species coupled to the oxidative degradation of the organic contaminant (primary TEAP) and the second term describes the first-order removal rate of the reduced species. The most important processes described by these sink terms are the removal of dissolved metals by precipitation under different mineral forms (e.g. iron sulfides precipitation when dissolved iron and sulfide, produced by the primary redox processes, come into contact) and volatilization and/or degradation of methane. The kinetic constants of these overall sink terms are determined by calibrating the model to the observed concentrations of the reduced species along the flow path. Note that the model does not account for the secondary demand for oxidants (e.g. oxygen for the re-oxidation of reduced metals and methane) and the contribution of these processes to the restoration of the oxidation capacity of the aquifer. A large number of transport simulations were performed and a trial and error calibration process was carried out to simultaneously match a set of measured concentrations for the organic contaminant (CH 2 O) and the geochemical parameters. The principal calibration parameters were the kinetic constants for different TEAPs, the inhibition constants and the decay rates of the metabolic by-products. Other parameters, such as the electron acceptors half-saturation constants were set to

13 REDOX-CONTROLLED FRINGE AND CORE BIODEGRADATION PROCESSES IN GROUNDWATER 4917 Figure 10. Geochemical parameters observed (May 2003) along the principal groundwater flow direction a constant value (0Ð5 mg L 1 ) and were not modified during model calibration. The results of the calibrated model are presented in Figure 11, as concentration profiles of the different reactive species, along the direction of groundwater flow (note, transect B B 0 shown in Figure 10). The computed profiles were calibrated using the concentrations of dissolved species measured in monitoring wells P3S, SP14, SP17, PZ8, PZ9 and PZE6. Besides the qualitative assessment of calibration by visual comparison of model output and measured data, a quantitative analysis of the goodness-of-fit was also completed. A dimensionless indicator, the coefficient of efficiency (Nash and Sutcliffe, 1970), and an absolute error indicator, the mean absolute error (MAE; Legates and McCabe, 1999) were calculated for each reactive species and the results are reported in Table VI. The results show that the model could reproduce the pattern of CH 2 O, with high concentration levels below the source zone and progressively decreasing values moving down-gradient (Figure 11a). Also, the computed oxygen consumption in the highly reducing zone was in good agreement with the measured data (MAE D 0Ð20 mg L 1 and E D 0Ð993), whereas the consumption of nitrate in the field appeared to start more up-gradient of the simulated profile. In order to match the observed Mn 2C concentrations (Figure 11d) a low value for the kinetic coefficient of the secondary sink term was used (k Mn2C D 0Ð001 d 1, in Equation (19)). Major problems were encountered when we attempted to calibrate dissolved iron data. Although iron reduction was active at the site, as indicated by the high concentration values of dissolved iron below the source, Fe 2C did not migrate significantly down-gradient (low concentration in PZE6) because of the presence of active iron sinks (e.g. mineral precipitation). By using a fairly high value of the overall first-order decay term for Fe 2C (k Fe2C D 0Ð03 d 1 in Equation (20)) the observed trend of dissolved iron could be reproduced but just qualitatively as shown by the quantitative measurement of the goodness of fit (Table VI). The observed concentrations appear to be shifted upgradient compared with the model results (Figure 11e). Very high concentrations of Fe(II) in monitoring wells located close to the contamination source have been reported in other studies (Essaid et al., 1995; Jakobsen and Postma, 1999, Chapelle et al., 2002; Schreiber et al., 2004). Schreiber et al. (2004) suggested that these findings can be attributed either to the simultaneous occurrence of Fe(III)-reduction with other less thermodynamically favourable TEAPs (e.g. methanogenesis) or to other processes affecting the fate of metabolic byproducts (e.g. adsorption of Fe(II) onto aquifer solids, heterogeneity in Fe(III) concentrations, etc.). Finally, to reproduce the observed trends in methane concentrations, a high value for methanogenic rates had to be used. Probably, the amount of methanogenesis occurring in the contaminated aquifer is overestimated by the model since a fraction of the dissolved methane observed in groundwater is likely to be produced by methanogenic processes occurring within the core of the disposed wastes and then transported to the water table by infiltrating water and by diffusion from the soil air.

14 4918 M. ROLLE ET AL. Table V. Model parameters used for simulating the field problem TableV.(Continued) Model parameters Spatial and temporal discretization Model area Cell dimensions Simulation time Kinetic parameters Aerobic degradation constant, k O2 Denitrification degradation constant, k NO3 Manganese reduction degradation constant, k Mn Iron reduction degradation constant, k Fe Sulfate reduction degradation constant, k SO4 Methanogenesis degradation constant, k CH4 Oxygen half-saturation constant, K O2 Nitrate half-saturation constant, K NO3 Manganese half-saturation constant, K MnO2 Iron half-saturation constant, K Fe OH 3 Sulfate half-saturation constant, K SO4 Methane half-saturation constant, K CH4 Oxygen inhibition constant, K i,o2 Nitrate inhibition constant, K i,no3 Manganes inhibition constant, K i,mno2 Iron inhibition constant, K i,fe OH 3 Sulfate inhibition constant, K i,so4 Mn 2C decay rate constant, k Mn2C Fe 2C decay rate constant, k Fe2C CH 4 decay rate constant, k CH4 Flow and transport parameters 2000 m ð 1500 m 10 m ð 8Ð5 m 9125 d 0Ð08 d 1 0Ð01 d 1 0Ð008 d 1 0Ð011 d 1 0Ð12 d 1 0Ð6 d 1 1 mg L 1 10 mg L mg L mg L mg L 1 0Ð001 d 1 0Ð03 d 1 0Ð01 d 1 Unconfined aquifer Saturated thickness 15 m Hydraulic conductivity 6Ð9 ð 10 4 m s 1 Recharge 200 mm year 1 Porosity 0Ð2 Constant head (left boundary) 259Ð7 m Constant head (right boundary) 251Ð25 m Longitudinal dispersivity, x 30 m Transverse dispersivity, y 0Ð1 x m Transport boundary conditions Inlet: constant concentration Outlet: concentration gradient D 0 CH 2 O 0 mg/l O 2 7Ð5 mg/l NO 3 47 mg/l Mn 2C 0Ð01 mg/l Fe 2C 0Ð1 mg/l 2 SO 4 28 mg/l CH 4 0mg/L Tracer 0 mg/l Initial conditions CH 2 O O 2 0 mg L 1 7Ð5 mgl 1 Initial conditions NO 3 Mn 2C Fe 2C 2 SO 4 CH 4 Tracer MnO 2 Fe(OH) 3 Contamination Source CH 2 O concentration Tracer concentration 47 mg L 1 0Ð01 mg L 1 0Ð1 mgl 1 28 mg L 1 0mgL 1 0 mg L mg L mg L mg L mg L 1 The kinetic reaction rates of the different redox processes were computed with the aim of delineating the redox zones in the contaminated groundwater. Figure 12 shows the longitudinal (B B 0 ) and transverse (at PZ8) reaction rates profiles of the different redox processes. Aerobic degradation and nitrate reduction are active at the outer edges of the plume. These reactions appear to be particularly effective at the up-gradient boundary of the plume where the incoming pristine groundwater, rich in dissolved oxygen and nitrate, contacts the oxidizable organic compounds released by the leaking landfill. The other primary TEAPs observed in the contaminated aquifer (manganese reduction, iron reduction, sulfate reduction and methanogenesis) occur within the organic plume, closer to the contamination source. Unlike the results presented for the hypothetical, 2D test problem (presented earlier), in the field example problem it was not possible to clearly distinguish the differences between the different types of core processes. In fact, directly beneath the landfill, all core processes appear to overlap. Such an overlap has been observed in other studies (Postma and Jakobsen, 1996; Ludvigsen et al., 1998; Christensen et al., 2001; Schreiber et al., 2004). Processes that are more thermodynamically favourable, such as Mn- and Fe-reduction, are probably kinetic limited and hence tend to overlap with less favourable reactions such as sulfate reduction and methanogenesis. The slow kinetics of iron and manganese reduction reactions and the availability of different minerals may result in only partial consumption of the solid electron acceptors and hence iron and manganese reduction can be active even in mature, steady-state plumes. SUMMARY AND CONCLUSIONS Details of a kinetic reaction model, which can be used to simulate the reactive transport of microbially mediated organic pollutant degradation processes occurring in a groundwater aquifer, is presented. The model has been coded as a reaction package (named Kin REDOX) and integrated with the MODFLOW-family reactive transport code RT3D. Ten reactive species were considered in

15 REDOX-CONTROLLED FRINGE AND CORE BIODEGRADATION PROCESSES IN GROUNDWATER 4919 Figure 11. Calibrated profiles along the flow direction, after 25 years of simulation Table VI. Goodness of fit of the multi-species reactive transport simulations at the landfill site CH 2 O O 2 NO 3 Mn 2C Fe 2C SO 4 2 CH 4 Mean absolute error (mg L 1 ) Coefficient of Efficiency MAE D n 1 n jobs i sim i j 0Ð44 0Ð20 9Ð65 0Ð96 8Ð59 2Ð97 0Ð26 id1 n obs i sim i 2 E D 1 id1 0Ð998 0Ð993 0Ð025 0Ð885 1Ð46 0Ð203 0Ð903 n obs i obs 2 id1 obs i D observed data, sim i D model results and obs D mean of observed data

16 4920 M. ROLLE ET AL. Figure 12. Reaction rate profiles after 25 years of simulation: (a) longitudinal profile along the groundwater flow direction; (b) transversal profile at PZ8 the model; the species include an organic compound, dissolved and solid mineral electron acceptors, metabolic by-products, and a conservative tracer. The numerical model can simulate both spatial and temporal distribution of the TEAPs, which determine the degradation patterns of degradable organic materials, such as landfill leachates. The reaction rates predicted by the model were used directly to estimate both temporal and spatial variations in redox reactions. This method allowed us to delineate the zones where the different geochemical reactions occurred. The method was able to map the characteristics of three distinct types of biodegradation mechanisms involving fringe, pseudo-core, and core processes. The proposed approach offers a more realistic alternative for identifying the active reaction zones, in particular for those involving immobile TEAPs such as iron and manganese reduction or strictly anaerobic processes such as methanogenesis, which are traditionally (often incorrectly) characterized using the measured values of dissolved metabolic by-products that can be biased by advection. The kinetic approach used in this study is a flexible method that can be used to simulate overlapping redox processes by appropriately adjusting the inhibition coefficients and the reaction rates. This capability was demonstrated using two hypothetical example problems, and a field study example. The field study demonstrated the capability of the model to simulate the degradation patterns of the high concentration (>30 mg L 1 )oforganic matter present beneath the landfill, complete consumption of electron acceptors oxygen and nitrate (from the background concentrations of 7Ð6 mg L 1 and 49 mg L 1, respectively), and the production and transport of metabolic by-products such as dissolved iron (15 mg L 1 ), manganese (7Ð3 mg L 1 ) and methane (3Ð2 mg L 1 ). The model results were calibrated by comparing the results with field observations. The outcomes of the calibration step were assessed using both visual comparison between measured and simulated concentration profiles, and also by quantitative estimates of the goodness of fit. The proposed model has some limitations. For example, it is important to recognize that landfill leachates are heterogeneous mixtures of various types of organic contaminants and this mixture was represented in our model as a simple organic species. Moreover, the uncertainty associated with the lack of information about source location and historic data on leachate release rates add complexities to the field problem. Uncertainty of source is a common problem encountered by several field studies (Clement et al., 2000) and future research should focus on developing source zone models that are capable of quantifying this uncertainty. Finally, the proposed model includes several adjustable reaction parameters and currently we have very little information about scaling characteristics of these parameters and their expected values at different scales. Despite these limitations, the proposed model offers a rational approach for integrating a wide variety of biogeochemical data with hydrogeological data within a mathematical framework that can be used to explain observed conditions, recreate past conditions, and forecast future conditions beneath a landfill site. ACKNOWLEDGEMENTS M. Rolle acknowledges the support of the Progetto Lagrange - Fondazione C.R.T. He also acknowledges the support provided by the Department of Civil Engineering, Auburn University during his tenure as an exchange student at Auburn for 9 months. Dr Clement served as an overseas supervisor of Rolle s PhD dissertation work. The RT3D model development efforts completed at Auburn University were, in part, supported by the Office of Science (BER), US Department of Energy Grant no. DE-FG02-06ER This work was also supported by the Sustainable Water Resources Research Center of 21st Century Frontier Research Program (code#3-4-3). REFERENCES Abrams RH, Loague K. 2000a. A compartmentalized solute transport model for redox zones in contaminated aquifers 1. Theory and development. Water Resources Research 36: Abrams RH, Loague K. 2000b. A compartmentalized solute transport model for redox zones in contaminated aquifers 2. Field-scale simulations. Water Resources Research 36: Baedecker MJ, Back W Hydrogeological processes and chemical reactions at a landfill. Ground Water 17: Barry DA, Prommer H, Miller CT, Engesgaard P, Brun A, Zheng C Modelling the fate of oxidisable organic contaminants in groundwater. Advances in Water Resources 25: