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Modelling Biological Cr(VI) Reduction in Aquifer Microcosm Column Systems Pulane E. Molokwane* and Evans M. N. Chirwa Environmental Engineering Group, Department of Chemical Engineering, University of Pretoria, Pretoria 0002. Tel. +27(12)420-5894, Fax +27(12)362-5089, Email: *[email protected] Abstract Several chrome processing facilities in South Africa release Cr(VI) into groundwater resources. Pumpand-treat remediation processes have been implemented at some of the sites but have not been successful in reducing contamination levels. The current study is aimed at developing an environmentally friendly, cost effective and self-sustained biological method to curb the spread of chromium at the contaminated sites. An indigenous Cr(VI) reducing mixed-culture of bacteria was demonstrated to reduce high levels of Cr(VI) in laboratory samples. The effect of Cr(VI) on the removal rate was evaluated at concentrations up to 400 mg/L. Following the detailed evaluation of fundamental processes for biological Cr (VI) reduction, a predictive model for Cr(VI) breakthrough through aquifer microcosm reactors was developed. The reaction rate in batch followed noncompetitive rate kinetics with a Cr(VI) inhibition threshold concentration of approximately 99 mg/L. This study evaluates the application of the kinetic parameters determined in the batch reactors to the continuous flow process. The model developed from advection-reaction rate kinetics in a porous media fitted best the effluent Cr(VI) concentration. The model was also used to elucidate the logistic nature of biomass growth in the reactor systems. Keywords: microcosm reactor, aquifer media, reaction inhibition, advection-reaction, in situ bioremediation. INTRODUCTION Chromium is a common contaminant in surface water and groundwater resulting from numerous industrial, agricultural and military activities (Ehrlich, 1996; Reid et al., 1994; Nriagu and Nieboer, 1988). Hexavalent chromium is known to be both carcinogenic and mutagenic to a wide range of living organisms including mammals (U.S.EPA, 1978). The common treatment method for Cr(VI) contaminated groundwater is usually the pump-and-treat method usually accompanied by precipitation of Cr(VI) using chemical agents. This method proves costly and slow in removing Cr(VI) from the aquifer media. At heavily contaminated sites, it may take up to 30 years to flash out single spill pollution in the order of 3000 kg (Molokwane et al., 2008). Alternatively, biological treatment methods using aquatic biomass and/or Cr(VI) reducing bacteria have been proposed (Wang et al., 1989; Ohtake et al., 1990; Ganguli and Tripathi, 2002 and others). These methods may be applied ex situ (Colica et al., 2010; Zakaria et al., 2007) or in situ in biological barriers (Molokwane and Chirwa, 2009). When applied in situ, it is desirable to use bacteria from the same or nearby environments to avoid the problem of transfer of alien organisms across country or regional boundaries. Permeable reactive barriers have been used mainly for removal of toxic organic compounds using specialised species of bateria. A typical design for the latter purpose comprises of a double-zone barrier system with an aeration zone followed by the bioremediation zone. One such system was evaluated against the removal of methyl-tert-butyl-ether (MTBE) contaminated groundwater (Liu et al, 2006). Another documented application is the treatment of petrochemical pollutants (i.e., benzene, toluene, ethylbenzene, xylene and polyaromatic hydrocarbons), heavy metals (i.e., lead, arsenic etc), and cyanide in the system designed by Doherty et al (2006) using a modified ash system. The latter biological permeable reactive barriers (BPRB) system was implemented at an abandoned gas manufacturing plant. Specific application of the biological permeable reactive barrier (BPRB) system for the removal of Cr(VI) in groundwater has only been attempted lately (Jeyasingh at al., 2011). This slow advancement towards full application has been both due to the unavailability of microorganisms capable of growing under nutrient deficient conditions and lack of information on the speciation and mobility of chromium species in the soil. In this study, operation of an inoculated permeable barrier is mathematically simulated using a dispersion-reaction model using Cr(VI) reducing microorganisms as biocatalysts. The general performance of the system and the analysis of the behaviour or microorganisms is presented in the earlier articles (Molokwane and Chirwa, 2009). MATERIALS AND METHODS Microbial Cultures The mixed culture of bacteria was obtained from dried sludge collected from sand drying beds at the Brits Wastewater Treatment Works (North West Province, South Africa). The treatment plant receives periodic flows from a nearby abandoned sodium dichromate processing facility reported to discharge high levels of Cr(VI) in the sewerage works, thus the bacteria at the treatment plant is expected to be acclimated to Cr(VI) toxicity. Microbial cultures from the sludge were used to inoculate the columns directly by feeding source organisms before running the sterile experimental feed into the reactors. Microcosm Reactor Systems Soil columns extracted from the aquifer (below the water table) were installed in a continuous dose experiment. Eight microcosm columns were installed with the first acting as the control, Reactor HR2 was used to evaluate the sludge bacteria acting alone, and Reactors HR3 and HR4 were used to evaluate the native soil bacteria acting alone (in duplicate). The main experiments comprised (in duplicate) HR5 and HR6 with both sludge bacteria and native soil bacteria but operated without carbon source, and HR7 and HR8 with soil bacteria and sludge bacteria operated with added carbon source. The carbon source in HR7 and HR8 consisted of a natural matrix of organics leached from saw dust. This was intended to simulate humic organics leaching from stems of dead plants in the veldt. The experimental plan for the detailed evaluation of the performance of aquifer microcosm reactors is summarised in Table 1. Table 1: Conditions for the aquifer microcosm range of experiments. Reactor(s) Experiment Reactor HR1 Sterilised (killed native bacteria) + no inoculation Reactor HR2 Sterilised (killed native bacteria) + inoculated (sludge bacteria) Reactors HR3 and HR4 Live native soil bacteria (non-sterile) + no inoculation Reactors HR5 and HR6 Live native soil bacteria (non-sterile) + inoculated (sludge bacteria) Reactors HR7 and HR8 Live native soil bacteria (non-sterile) +inoculated + carbon source Cr(VI) and Total Cr Measurement Cr(VI) was measured using a UV/Vis spectrophotometer (WPA, Light Wave II, Labotech, South Africa). The measurement was carried out at a wavelength of 540 nm (10 mm light path) after acidification of 0.2ml samples with 1N H2SO4 and reaction with 1,5-diphenyl carbazide to produce a purple colour (APHA, 2005). Total Cr was measured at a wavelength of 359.9 nm using a Varian AA-1275 Series Atomic Adsorption Spectrophotometer (AAS) (Varian, Palo Alto, CA (USA)) equipped with a 3 mA chromium hollow cathode lamp. Cr(III) was determined as the difference between total Cr and Cr(VI) concentration. Cr(VI) Reduction Kinetics The following simple Monod-type enzymatically based kinetic model derived earlier by Shen and Wang (1994) was utilised in this study to simulate Cr(VI) reduction in batch systems: r d (C ) k mc C X dt C Kc (1) where kmc = maximum specific Cr(VI) reduction rate coefficient (T-1), Kc = half velocity concentration (ML-3), C = Cr(VI) concentration (ML-3), and X = concentration of viable cells (ML-3) at any time t (T). When non-competitive inhibition, maximum Cr(VI) reduction capacity of cells, and toxicity threshold is taken into consideration, the model is revised as shown by Molokwane (2010) as follows: k C C C dC X 0 0 1-Cr C0mc dt Rc K K c C (2) where Xo = initial concentration of viable cells (ML-3), Co = initial concentration of Cr(VI) (ML-3), Rc = Cr(VI) reduction capacity of the cells (g Cr(VI) reduced/g cells inactivated), K = noncompetitive inhibition rate coefficient (ML-3), and Cr = toxicity threshold concentration of Cr(VI) (ML-3). Simulation of Cr(VI) Removal Across Column A dispersion-reaction model was used to determine kinetic and dynamic parameters for the microbial barrier system. The microcosm reactors were modelled as plug flow reactors with the Cr(VI) removal influenced by the following internal processes: (1) advection influenced by the interstitual velocity u (LT-1), (2) mass transport into media particles governed by mass transport rate coefficient kL (LT-1), (3) adsorption rate governed by mass transport and surface reaction, (4) Cr(VI) reduction governed by the kinetics described by preliminary batch modelling and (5) cell replacement rate with the cells acting as the catalyst in the Cr(VI) reduction process. The predominant processes in the reactor are thus limited to advection, reduction, mass transport and cell growth. These processes were used in the mass balance for Cr(VI) removal across the bulk liquid phase in the microcosm reactor: l Li d (C V ) A uCin C jc .ai qc rc V dt l 0 (3) in which for each segment of reactor of length L (L), V = change in reactor volume (L3), the interstitial velocity u (LT-1) is assumed to be constant throughout the entire reactor, ai = surface area in the segment (L2). The adsorption rate, qc (ML-3T-1) approaches zero as the reactor is operated for 6 to 10 hours (this study). The Cr(VI) reduction rate, rc (ML-3T-1), is a function of viable biomass in the reactor (Equations 1 & 2). The above fundamental processes in the reactor during transient state operation were represented by the Equations 4 to 8 below: dV uA dt (4) dC k L aC C s jc dt (5) dC k ad C eq C q c dt (6) k C C C dC X 0 0 rc 1-Cr C0mc dt Rc K K c C (7) k S dX Y ms k d X dt Ks S (8) where Cs and Ceq = are the particle surface and equilibrium surface concentration for the adsorptive process (ML-3), the coefficient kL = mass transport rate coefficient (LT-1), a = total surface area in the reactor (L2), kad = adsorption rate coefficient (T-1), Y = cell yield coefficient (MM-1), kms = specific substrate utilisation rate coefficient (T-1), Ks = half velocity substrate concentration (ML-3), S = the concentration of carbon sources (ML-3) at time t, and kd = cell death rate coefficient (T-1). The interstitial space A in the microcosm was estimated as the volume of the mobile phase (bulk liquid) minus entrained water determined as the difference between the weight of the wet nonflowing reactor and a dry reactor. And process terms are defined as follows: jc = mass transport rate (ML-2T-1), qc = adsorption rate (ML-3T-1), and rc = Cr(VI) reduction rate (ML-3T-1). The substrates S and viable biomass could not be measured accurately with current methods. Thus, for the time being, these are generated as model outputs from an empirical logistic biomass term (Equation 9 below): X X0 X max t 1 t0 b (9) with Xo = the initial viable biomass (ML-3) in the reactor, Xmax = maximum achievable biomass (ML-3) due to toxicity and space limitations, t0 = x-intercept for the logistic curve, and b = pitch factor (dimensionless) determining the amplitude of the biomass curve. The predicted concentrations were calculated using the Computer Programme for Simulation of Aquatic Systems (AQUASIM 2.0) (Reichert, 1998). RESULTS AND DISCUSSION Cr(VI) Reduction in a Control Column The operation of the sterilised reactor without added biomass showed a characteristic rise following the effluent tracer line for the clean-bed reactor system (Figure 1). The characteristic exponential rise suggests that adsorption processes were insignificant, i.e., the column reached equilibrium with respect to adsorption during the 45 days of operation. The extended controls Reactors (HR2, HR3 and HR4) show that soil bacteria and activated sludge bacteria acting alone in these conditions did not reduce Cr(VI). The reason why the soil bacteria could not reduce Cr(VI) is most certainly because there were no Cr(VI) reducing bacterial species in the soil. However, it is not known why the sludge bacteria did not reduce Cr(VI) after inoculating a sterile column. One suggestion is that the Cr(VI) reducing bacteria from the sludge required some biochemical metabolites or cofactors produced by the soil bacteria. Cr(VI) concentration, mg/L 60 50 40 30 Tracer line Influent Cr(VI) Effluent Cr(VI) 20 10 0 0 10 20 30 40 50 Time, days Figure 1: Performance of a non-inoculated sterile column showing a characteristic exponential rise in effluent Cr(VI) comparable to the tracer. In the abiotic system, the effluent concentration will reach influent levels after 4.5 bed volumes. Cr(VI) Reduction in a Column without Carbon Source The performance of live cultures from both sources (soil and sludge) working together was evaluated in system HR5 (Figure 2). The Reactor HR5 represents the operation on only inorganic carbon sources from soil. Simulation of the system showed that cell growth is possible within the constraints of the model, from an approximate initial concentration of 8.5 g/m3 to a maximum value of approximately 45.5 g/m3. The biomass was simulated empirically at this point by the logistic function (Equation 9). The cell viability was reflected in the increased Cr(VI) reduction removal rate after 6 bed volumes (day 6). The characteristic flattening of the curve suggests an approach to the maximum cell growth and Cr(VI) reduction capacity of the reactor. Cr(VI) Reduction in a Column with Carbon Source The best performance was observed in Reactor HR7 operated under carbon source (Figure 3). In this reactor, the simulated viable biomass continually increased with time and this was reflected in the ever increasing rate of Cr(VI) reduction until the termination of the experiment at day 45. The improved performance under carbon source was also demonstrated by the ever-increasing cumulative Cr(VI) reduction in the reactor HR7 (data not shown). The trend in biomass from day 6 to 45 shows no sign of levelling off. This indicates a relaxation in the pitch factor, b (Equation 9), showing that the full capacity was not reached in the reactor operated under carbon sources. 70 60 50 50 40 40 30 30 20 20 Measured influent Cr(VI) Measured effluent Cr(VI) Simulated effluent Cr(VI) Simulated biomass Xin 10 Viable cell conc. X, g/m3 Cr(VI) concentration, mg/L 60 10 0 0 0 10 20 30 40 50 Time, days Figure 2: Performance and simulation of the live soil culture microcosm inoculated with live cultures from sludge and operated without carbon source (Reactor HR5). 70 60 50 50 40 40 30 Measured Influent BR7 Measured Effluent BR7 Simulated effluent Cr(VI) Simulated biomass Xin 20 30 20 10 Viable cell conc. X, g/m3 Cr(VI) concentration, mg/L 60 10 0 0 0 10 20 30 40 50 Time, days Figure 3: Model simulation of the live soil culture microcosm inoculated with live cultures from sludge and operated with carbon source (Reactor HR7). In this simulation, the system performed well regardless of having started with the lowest initial biomass value, Xin = 4.5 g/m3. The biomass in the reactor increased to approximately 65.5 mg/L, a value more than 1.5 times higher than the maximum achievable cell concentration under no carbon source (Reactor HR5). The logistic time constant t0 almost doubled to 10.4 days as X continued to increase. The pitch factor, b, and interstitial velocity, u, remained the same as under the other simulations conditions at 5.03 and 6.24 10-4 m/d, respectively. The increase in biomass with time in the reactor was accompanied by increasing Cr(VI) reduction which continued until the experiment was terminated at 45 days. Effect of Toxicity Inhibition The Cr(VI) reducing culture used in this experiment is more sensitive to Cr(VI) toxicity compared to batch cultures grown aerobically. This is due to low access to the organic carbon sources generally, and specifically (Reactor HR5) due to growth under autotrophic conditions. The model was modified for toxicity sensitivity by introducing the Cr(VI) inhibition term and the Cr(VI) toxicity threshold and the cell inactivation term X0Rc in the Monod-like equation (NkhalambayausiChirwa and Wang, 2004). A reasonable accuracy was achieved in the final optimised parameters as shown in the Figures 2 and 3 simulated effluent model line. The optimum parameters in the final simulation are shown in Table 2. Table 2: Final parameter values from the application and optimisation in the microcosm reactors. Parameters Associated Process Optimum Value Units kmc Kc Rc K Cr t0 X0 Xmax D A Cr(VI) reduction rate Cr(VI) reduction rate Cr(VI) reduction rate Cr(VI) reduction rate Cr(VI) reduction rate Cell growth Cell growth Cell growth Column properties Column properties 1.385 2.450 0.533 0.50 99 10.4-20.4 4.5-23.5 (HR7-HR4) 3.5-65.3 (HR4-HR7) 98.4 1/d mg/L mg/mg mg/L mg/L d g/m3 g/m3 m2/h m2 3.65-4.65 10-4 Conclusion Model simulation confirms the effect of inhibition (inhibition threshold Cr) and direct toxicity (cell inactivation coefficient Rc) as the dual mechanisms limiting the extent of Cr(VI) reduction in the aquifer media. The accurate determination of these parameters is critical in the future development of a pilot scale system for Cr(VI) reduction and immobilization using a microbial permeable barrier system. Other parameters of importance are the interstitial velocity u and the diffusivity of Cr(VI) in the soil media which was determined to be slower than the value in water. 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