Journal of Environmental Quality 30:1523-1527 (2001)
© 2001 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America
TECHNICAL REPORT
Bioremediation and Biodegradation
Kinetic Modeling of Bioavailability for Sorbed-Phase 2,4-Dichlorophenoxyacetic Acid
Jeong-Hun Parka,
Denise Kayb,
Xianda Zhaoa,
Stephen A. Boydb and
Thomas C. Voice*,a
a Dep. of Civil and Environ. Eng., Michigan State Univ., East Lansing, MI 48824
b Dep. of Crop and Soil Science, Michigan State Univ., East Lansing, MI 48824
* Corresponding author (voice{at}msu.edu)
Received for publication September 22, 2000.
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ABSTRACT
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The degradation rate of 2,4-dichlorophenoxyacetic acid (2,4-D) was studied in silica–slurry systems to evaluate the bioavailability of sorbed-phase contaminant. After the silica particles were saturated with 2,4-D, the system was inoculated with the 2,4-D–degrading microorganism Flavorbacterium sp. strain FB4. The disappearance rate of 2,4-D was found to be greater than the rate predicted based upon liquid-phase 2,4-D concentrations. A kinetic formulation, termed the enhanced bioavailability model, was developed to describe the desorption and biodegradation processes in this batch system. The approach assumes that 2,4-D resides in both the liquid and solid phases and degradation occurs via both suspended and attached biomass. All biomass can degrade liquid-phase 2,4-D at one rate, while only attached biomass can degrade sorbed 2,4-D at another rate. An enhanced transformation factor (Ef) was introduced to express the increased biodegradation rate over that expected from the liquid phase only. This approach was able to account for the increased degradation rates observed experimentally. The results provide evidence that desorption to the bulk solution is not prerequisite to degradation, and that sorbed substrate may be available for degradation.
Abbreviations: MSM, minimal salts media • PBS, phosphate buffered saline • 2,4-D, 2,4-dichlorophenoxyacetic acid • FB4, Flavobacterium sp. FB4 • EDTA, ethylenediaminetetraacetic acid • EB, enhanced bioavailability
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INTRODUCTION
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BIOAVAILABILITY of sorbed contaminants in soils and sediments affects the clean-up time, cost, and end-point of bioremediation processes. Published results suggest that bioavailability varies with the sorbent (Geerdink et al., 1996), substrate (Griffith and Fletcher, 1991), and organisms (Guerin and Boyd, 1992). Rigorous interpretation of such results requires formulation of a conceptual model describing the component processes, conducting experiments to allow quantification of individual process rates, and mathematical analysis of experimental bioavailability data to evaluate the validity of the model formulation. Potential interactions between processes must also be assessed. One critical issue that arises in this approach is whether desorption is prerequisite to biodegradation, or expressed alternatively, whether degradation can occur without contaminant release to the bulk liquid phase. Some researchers have reported that sorbed contaminant is not directly available to attached or suspended cells (Steen et al., 1980; Ogram et al., 1985; Shimp and Young, 1988; Smith et al., 1992; Weissenfels et al., 1992; Shelton and Doherty, 1997), whereas others concluded that sorbed substrate can be directly utilized by attached cells (Guerin and Boyd, 1992, 1993, 1997; Crocker et al., 1995; Calvillo and Alexander, 1996; Ortega-Calvo and Saiz-Jimenez, 1998; Tang et al., 1998; Lahlou and Ortega-Calvo, 1999; Laor et al., 1999; Feng et al., 2000). While these conflicting interpretations may reflect differences related to the characteristics of the sorbents, substrates, and organisms employed, they may also result from inadequate experimental and mathematical resolution of individual processes and the factors affecting them. For example, none of the above studies reporting direct sorbed-phase degradation fully described desorption kinetics, resulting in uncertainty in the substrate concentration driving degradation.
The purpose of this study was to develop an experimental and mathematical approach to evaluate bioavailability, and specifically whether desorption and degradation are strictly sequential or independent processes. To do this, desorption rates were measured in the absence of organisms and biodegradation rates were measured in the absence of solids. Combined desorption/biodegradation experiments were then performed, and the results were analyzed using a mathematical model incorporating three processes: desorption, liquid-phase degradation, and sorbed-phase degradation. Using this approach, we were able to determine whether a sorbed-phase degradation mechanism is consistent with the bioavailability data and the rate of this process. Experimentally, we used 2,4-dichlorophenoxyacetic acid (2,4-D) as the sorbate and substrate, silica as the sorbent, and a 2,4-D–degrading organism, Flavobacterium sp. FB4. The herbicide 2,4-D is widely used on wheat (Triticum aestivum L.), corn (Zea mays L.), and sorghum [Sorghum bicolor (L.) Moench] to control broad-leaf weeds and is a potential pollutant of ground water (Sannino et al., 1997).
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MATERIALS AND METHODS
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The Flavobacterium sp. strain FB4 used in this study is a proteobacterium that is able to internally metabolize 2,4-D as a sole C and energy source (Ogram et al., 1985). No degradation of 2,4-D by extracellular enzymes was observed in cell culture supernatants. Cells were grown in batch culture until early stationary phase in minimal salts media ([MSM] 1419.6 mg Na2HPO4, 1360.9 mg KH4PO4, 0.3 mg (NH4)2SO4, 50 mg MgSO4·7H2O, 5.88 mg CaCl2·2H2O, 3.2 mg EDTA disodium salt, 2.78 mg FeSO4·7H2O, 1.15 mg ZnSO4·7H2O, 1.69 mg MnSO4·H2O, 0.375 mg CuSO4·5H2O, 0.233 mg Co(NO3)2·6H2O, and 0.1236 mg (NH4)6Mo7O24·4H2O L-1 of distilled water) that initially contained 2,4-D at 400 mg L-1. These cells were harvested by centrifugation, rinsed in phosphate buffered saline (PBS), centrifuged again, and resuspended in PBS before being used as inoculum.
Sterile stock solutions of radio-labeled 2,4-D (Sigma St. Louis, MO., 96% radiochemical purity, specific activity, 3.84 x 108 Bq mmol-1) were prepared in PBS. The solutions contained approximately 2.4 x 10-6 Bq mL-1 (200000 dpm mL-1) ring-U-[14C] 2,4-D with a final concentration of 10 mg L-1. The solutions were filter sterilized and stored in five 100-mL portions in light-shielded bottles at 4°C.
Uncoated silica was obtained from the J.T. Baker company. The irregular-shaped particles have an average size of 40 µm with 60-angstrom pores. To create the silica slurries, 2.5 g silica were weighed into sterile, 10-mL Falcon tubes and 9 mL PBS were carefully layered on top of the silica. The tubes were placed in a Speed Vac, which applies gentle centrifugation and vacuum simultaneously, for 1 min. A disposable sterile loop was used to resuspend the silica. The silica was rinsed with 200 mL of PBS in 10-mL aliquots in a 25-mL glass column with a glass frit. After rinsing, the silica was transferred to a 20-mL serum vial. The solution from the last rinse was used as the supernatant control.
Sorption kinetics were evaluated to determine the silica–liquid contact time necessary to reach apparent steady state in batch experiments. Phosphate buffered saline and stock solutions containing 14C-labeled 2,4-D were added to serum vials containing silica to achieve the appropriate slurry density and contaminant concentration. The vials were placed on a platform rocker set at 60 cycles min-1. This mixed the slurries well enough to prevent the silica from settling. The slurries were sampled at prearranged time intervals and the samples were immediately centrifuged at 11750 x g in a centrifuge filter vial (Pall Gelman, Nanosep MF Microconcentrators, 0.2-µm pore size) to separate the silica from the solution. After centrifugation the filter cup was separated from the vial and the cap was cut off. The filter cup and vial were dropped into separate scintillation vials containing 10 mL of scintillation cocktail fluid. Activity was counted on a liquid scintillation analyzer.
Desorption kinetics were measured by first equilibrating silica and 2,4-D for 45 min, diluting the supernatant with 2,4-D-free PBS, and resuspending the particles. Liquid-phase and sorbed-phase concentrations were measured over time as described above.
Biodegradation in the presence or absence of the sorbent was measured in similar batch systems. After the system reached sorption steady state, it was sampled as previously described to determine the sorbed and liquid-phase contaminant concentrations. The slurry was then inoculated with a pure bacterial culture (FB4) at a cell density of approximately 1 x 108 CFU mL-1. Depletion of liquid phase 2,4-D was monitored over time. Acid, 40 µL 2 M HCl, at the bottom of the microconcentrator tube was used to effectively drive off any CO2 remaining in solution. Cell-free control vials were also prepared and monitored to examine abiotic losses in the batch system. The liquid-phase degradation rate for 2,4-D was also determined in the supernatant control solutions.
In the proposed model, shown schematically in Fig. 1, the contaminant can reside in two phases, solid and liquid, and degradation occurs via both suspended and attached biomass. Distribution of 2,4-D between the two phases is described by an equilibrium distribution coefficient, as the kinetic experiments indicated that this process is rapid and reversible. All of the biomass in the system can degrade liquid-phase contaminant at one rate, while only an attached fraction degrades sorbed-phase contaminant at another rate. This model system does not intend to account for all of the factors controlling biodegradation rates in natural systems.
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Fig. 1. Conceptive model for disappearance of 2,4-D in slurry systems, where S and C are sorbed and liquid phase concentration, respectively, fs is attached cell fraction, Kd is the sorbent-water distribution coefficient, and kl and ks are the liquid and sorbed phase degradation rate coefficients, respectively.
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The linear sorption distribution coefficient (Kd) decribes the relationship between the sorbed-phase (Se), and liquid-phase (Ce) concentrations at equilibrium.
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The overall mass balance equation of contaminant in the batch system is expressed as:
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where C is the liquid-phase concentration of contaminant (µg L-1), t is time (min), kl is the first-order liquid-phase degradation rate coefficient (min-1) determined from the biodegradation assay, fs is the fraction of attached biomass in the system (unitless); ks is the first-order sorbed-phase degradation rate coefficient (min-1), m is the sorbent mass (g), and Vl is liquid volume (mL).
Under the sorption–desorption equilibrium assumption, the rate of change in the sorbed phase can be calculated from the change in liquid-phase concentration:
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Rearranging Eq. [2] and [3], the liquid-phase contaminant disappearance rate can be expressed as:
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where, Ef is the enhanced transformation factor (unitless),
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Bf is the bioavailability factor (Zhang et al., 1998),
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and Rsl is solid/liquid ratio (g mL-1).
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Integrating Eq. [4], the liquid-phase contaminant concentration is expressed as
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where C0 is the initial liquid-phase concentration. We designated this approach as the Enhanced Bioavailability (EB) model.
The solid–liquid distribution coefficient, Kd, was determined from the sorption isotherm experiments. The liquid-phase degradation rate coefficient, kl, was determined from the silica-free biodegradation experiment using Eq. [4] when Ef and Bf are set to one. The fraction of attached biomass, fs, was determined by comparison of the cell plate counts from the initial inoculant and the liquid phase of the silica slurry. The solid/liquid ratio, Rsl, was calculated from the silica weight and liquid volume. The bioavailability factor, Bf, was calculated from Eq. [6]. The enhanced transformation factor, Ef, was determined from the change in liquid-phase concentration of contaminant in the bioavailability assay using Eq. [8]. The sorbed-phase degradation rate coefficient, ks, was calculated after Ef was determined using Eq. [5].
If there is no sorbed-phase degradation by the attached biomass, ks is zero and Ef is one. The equation reduces to the bioavailability equation (Bf model) that assumes sorption–desorption equilibrium and only liquid-phase degradation (Zhang et al., 1998). Values of Bf varies between 0 and 1, with a value of 1 corresponding to a system with no sorbent. Values of Ef > 1 indicate a 2,4-D biodegradation rate faster than that expected based on liquid-phase concentrations, whereas values <1 indicate slower rates. In the later case, the value of ks will be negative.
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RESULTS
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The 2,4-D sorption isotherm was linear over the concentration range employed in this study. Steady-state conditions were reached within 5 min and the sorption distribution coefficient (Kd) was 3.3 (±0.1) L kg-1. Desorption was also rapid, with the system reaching the value predicted by the sorption Kd by the first time point at 30 s (Fig. 2). Three consecutive dilution desorption experiments were performed and no desorption hysteresis was observed. It was therefore concluded that sorption/desorption could be described as completely reversible and instantaneous for this study.
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Fig. 2. 2,4-D desorption from silica following a single dilution of the solution phase. Time points represent single measurements.
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Two sets of experiments were completed to evaluate the bioavailability of sorbed 2,4-D in slurry systems. In the first set, the silica/liquid ratio, Rsl, was varied while the amounts of 2,4-D were held constant. In the second set of experiments, the initial 2,4-D amount was varied while Rsl was held constant. Since the experiments were performed using cells harvested from independent cultures, cell activity varied slightly. Biokinetic parameters were evaluated from silica-free controls and normalized for each set of experiments.
Four silica/liquid ratios, 0.12, 0.19, 0.29, and 0.43 g mL-1, were used in the first experiment (Table 1). The amount of 2,4-D and volume of solution remained constant. As a result, the initial liquid-phase 2,4-D concentrations for biodegradation were between 750 and 360 µg L-1 for the four ratios. An example of the concentration data and prediction by the Bf model are shown in Fig. 3. The Bf model consistently overpredicted liquid-phase concentrations (i.e., underpredicted 2,4-D depletion), suggesting the need for an additional or enhanced rate process. The enhanced transformation factor (Ef) was determined from the 2,4-D concentration-time profile using Eq. [8]. It can be seen that the added degradation described by this term results in a fit consistent with the data. The enhanced transformation factors (Ef) were >1 for all silica/liquid ratios and increased linearly with this ratio (Fig. 4).
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Table 1. Analysis of experimental results for a range of solid/liquid ratios Rsl = 0.12 to 0.43, cell density of 1.2 x 107 CFU mL-1, and kl = 0.006 min-1.
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Fig. 3. 2,4-D liquid-phase concentration versus incubation time. The two depicted lines were plotted using following values: Rsl (0.19), kl (0.0060), ks (0.032), and fs (0.28). Inoculum density was 1.2 x 107 CFU mL-1.
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Fig. 4. Enhanced transformation factor versus the ratio of silica to liquid. The estimated line was plotted using average values of kl (0.0060), ks (0.027), and fs (0.28). Inoculum density was 1.2 x 107 CFU mL-1.
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In the second experiment, four different 2,4-D amounts were used with a constant silica/liquid ratio (Rsl = 0.25) (Table 2). This resulted in initial concentrations for biodegradation between 70 to 550 µg L-1. Again, the Bf model significantly underestimated initial 2,4-D depletion rates while the EB model consistently fit the results (Fig. 5). The average value of the enhanced transformation factor (Ef) was 1.70 ± 0.15.
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Table 2. Analysis of experimental results for different initial 2,4-D concentrations, and with a constant solid/liquid ratio Rsl = 0.25, a cell density of 5.6 x 106 CFU mL-1, and kl = 0.0045 min-1.
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Fig. 5. Initial depletion rate vs. initial equilibrium concentration at a constant silica/liquid ratio. Inoculum density was 5.5 x 106 CFU mL-1. Values used for model were: kl (0.0045), ks (0.014), and fs (0.28).
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DISCUSSION
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The proposed approach for assessing bioavailability defines a combination of experimental and mathematical tools that can be used to describe biodegradation in the presence of a sorbent. We have accounted for the dependence and the effect of both desorption and biodegradation on liquid-phase concentration. By doing this we are able to evaluate whether desorption and degradation are sequential processes, with degradation dependent only on liquid-phase concentration. In our experimental system, this was not the case. In all experiments, degradation proceeded at a rate faster than would be expected based on the liquid concentration alone. This result deviates from the previous study of Ogram et al. (1985), who concluded that only dissolved 2,4-D in soil slurries was available to both suspended and attached biomass. Our simplified model system, while not fully representative of natural soil systems, allowed investigation of bioavailability without the complications of desorption rate limitation, and reduced the potential impact of other variables such as alternate carbon sources. In practice, instantaneous desorption of organic contaminants is unlikely to occur in soil slurries, because most soils have multiple sites with different kinetic behaviors (Kan et al., 1998).
The EB model presented in this study was developed using formulations for reversible and instantaneous sorption–desorption processes and first-order biodegradation reactions in both liquid and solid phases, and the assumption that the liquid-phase degradation rate coefficient is not affected by the presence of solids. Since desorption can never be truly instantaneous, the validity of this formulation rests on whether it is significantly faster than degradation. As shown in Fig. 6, if the ratio of the desorption rate coefficient to the degradation rate coefficient is larger than 10, the concentration error would be <2%. A desorption rate coefficient, 
(min-1), was estimated using the following equation
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and found to be at least 30 min-1 for the data shown in Fig. 2. Because the liquid-phase degradation rate coefficients were <0.006 min-1, the rate ratio was >1000. Thus, the error is expected to be insignificant.
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Fig. 6. The ratio effect of desorption rate coefficient to degradation rate coefficient on liquid-phase concentration over incubation time. Ceq is calculated using EB model with Ef value of one. Cd is calculated using Eq. [2] (overall mass balance equation with ks value of zero) and Eq. [9] (first-order desorption-rate equation). The Kd value is assumed 3.3. Rsl is 0.1. and kl is 0.006 min-1.
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To describe the enhanced 2,4-D disappearance rate in the silica slurry system, the enhanced transformation factor (Ef) was introduced to the previously published Bf model. When the Ef value is >1, as in all cases from this study, degradation is faster than expected based on liquid-phase concentrations. We see four possible mechanistic interpretations of Ef values greater than one. First, attached biomass accessing adjacent elevated concentrations of contaminant before complete dilution in the liquid phase. Second, increased bacterial metabolic rates resulting from the presence of the sorbent. Third, enhanced desorption due to a higher gradient at the cell–sorbent interface. Fourth, degradation of sorbed substrate by extracellular enzymes released by cells attached to the sorbent. Of these, the latter two seem unlikely because 2,4-D desorption into bulk solution occurs much more rapidly than degradation. In addition, our cell-free supernatant solutions did not show any 2,4-D degradation activity consistent with earlier reports (Ogram et al., 1985) that FB4 metabolizes 2,4-D internally. When considering the practical implication, the important conclusion is that bacterial degradation in the presence of a sorbent may be faster than described by the independent processes of desorption and liquid-phase degradation.
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ACKNOWLEDGMENTS
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This work was supported by the USDA National Research Initiative Competitive Grants Program, the Center for Microbial Ecology (National Science Foundation, Grant DEB-9120006), and by the Great Lakes and Mid-Atlantic Center for Hazardous Substance Research (Environmental Protection Agency, Michigan Department of Environmental Quality).
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ABSTRACT
INTRODUCTION
