Rate of Contaminant Bioavailability inArtificial Soil-Water Column Experiments
Yves Dudal, Rejean Samson,and Louise Deschenes
NSERC Industrial Chair for Site Remediationand Management, Chem. Engrg. Dept., EcolePolytechnique de Montreal, Montreal (Quebec),Canada
Bioavailability of organic contaminants isa key parameter in estimating the fateand transport of contaminants in the en-vironment. Its quantification is necessary
for assessing the bioremediation poten-tial of a contaminated site or for eval-uating the hazard associated with thepresence of the contaminant. However,there is a lack of methods that quan-tify biovailability under flow-through con-ditions. Therefore, a method was devel-oped based on mass-balance analysisof contaminant breakthrough curves toquantify a bioavailability rate. The methodwas performed on an eight-column studywhere pentachlorophenol (PCP) was in-jected through saturated columns packedwith a blend of sterile or inoculated sandand PCP-sorbing resin. Columns variedin sorption capacity, pore-water velocityand biodegradation activity. Breakthroughcurves were modeled using a classic ap-proach that includes advection-dispersion,equilibrium and first-order sorption, as wellas biodegradation. Results showed thatthe bioavailability rates (non-dimensionalnumbers ranging from 0.02 for a sorptivecolumn to 0.32 for a non-sorptive one) weredirectly related to the limiting kinetic mech-anism. It was also demonstrated that thecontaminant aqueous phase concentrationdoes not adequately represent its bioavail-ability under flow-through conditions.
Address correspondence to Louise Deschenes, NSERC Industrial Chair for Site Remediation and Manage-ment, Chem. Engrg. Dept., Ecole Polytechnique de Montreal, Montreal (Quebec) H3C 3A7, Canada. E-mail:[email protected]
T HE fate and transport of organic contaminants found in soil and ground waterare governed by a number of physical-chemical and microbiological inter-
actions that take place between the contaminant and its surrounding environment(subsurface solid matrix, aqueous and gaseous phases). Contaminant sorption andits biodegradation by indigenous microorganisms modifies the advective-dispersivesolute transport. These microorganisms, which are usually fixed onto the solid ma-trix, have access only to a certain fraction of the total contamination, mainly due tocontaminant sorption (Luthy et al., 1997). The extent of access depends uponthe contaminant characteristics (hydrophobicity, biodegradability, etc.) and uponthe capacity of the microflora to obtain its substrate (Harms and Zehnder, 1995). Theterm “bioavailability” is often used to describe this partial access that microorgan-isms have to the contaminant. However, bioavailability has been defined in manydifferent ways in various fields. In environmental toxicology and for risk assessmentstudies, bioavailability represents the fraction of the total contamination to whichthe target organism is exposed (Hamelink et al., 1994; Hrudey et al., 1996). Whenapplied to bioremediation processes, bioavailability is expressed as the amount ofcontaminant that can be accessed by the contaminant-degrading microorganismspresent in soil and groundwater. This study will use the term bioavailability tospecifically describe the extent of the degrading microorganisms’ access to thecontaminant. The contaminant bioavailability is the result of physical, chemicaland microbiological interactions occurring between the contaminant and its envi-ronment. This parameter has great implications when assessing the capacity of acontaminated site to be bioremediated (Hatzinger and Alexander, 1995). Not onlydo the microorganisms need to be present and active, but they also need to obtain thecontaminant to proceed with its biotransformation. In the different fields where theterm “bioavailability” is used, it appears to be dependent on the organisms used toassess it. Faced with similar physical-chemical limitations, different organisms willnot be equally exposed to the contaminant. This has been shown for contaminantavailability to microbes (Guerin and Boyd, 1992) and for bioavailability leading totoxicity (Davies et al., 1999).
Accurate quantification of bioavailability is still problematic. The aqueous phaseconcentration of the contaminant (external dose) is often used as a first estimate ofthe microbial availability based on the fact that water is the exchange phase for thecontaminant between the solid matrix and the microorganisms. Considering thatthe microbes can immediately take up the desorbing contaminant, an aqueous phaseconcentration below the detection limit does not mean a zero availability. In soils,this concentration is evaluated using the contaminant distribution coefficient (K D),between the solid matrix and the soil solution, which is based on the contaminanthydrophobicity (KOW) (Karickhoff et al., 1979; Schwarzenbach et al., 1993). Var-ious methods have been developed to measure this distribution coefficient, usingdifferent solvents or extracting devices. Solid-phase micro extraction using C18columns (Hsieh and Dorsey, 1995) and various solvent extractions (Loibner et al.,
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SSC TJ881-05 November 17, 2003 11:40
1997) have been tested. However, the parameters obtained by these methods arethermodynamic and relate to an equilibrium state, rarely reached in the environment.Bioluminescent probes have been used, which relate the biodegradation activity ofthe microbe-probe to a luminescent signal (Paton et al., 1995), but these experi-ments were performed under batch conditions. Flow-through conditions are morerelevant to real-world situations, but the bioavailability of the contaminant in thesesystems has not yet been addressed, other than by measuring the aqueous phaseconcentration. However, this concentration is questionable as far as a representa-tion of the actual microbial availability of the contaminant, even more than in batchconditions. Therefore, the aims of this paper are: i) to understand the bioavailabil-ity of an organic contaminant under flow-through conditions, and ii) to develop amethod that quantifies this bioavailability under such conditions. To do so, a seriesof experiments with 8 columns was carried out where an organic contaminant, pen-tachlorophenol (PCP), was injected through different blends of reactive materials(sorbing and biodegrading) to represent various environmental conditions, and thenmonitored at the exit of the columns. PCP has been used for several decades as afungicide, algaecide and insecticide in wood treatment (McAllister et al., 1996)and is on the U.S. Environmental Protection Agency’s priority pollutant list. It isan ionizable compound, its hydrophobicity is pH-dependent, and at a neutral pH isfound as a charged species (Kaiser and Valdmanis, 1982). Also, PCP was shownto migrate through the non-saturated zone and reach the groundwater at varioussites (Valo et al., 1984). Furthermore, bioaugmentation of a PCP-contaminated soilwith an acclimated microbial consortium (aerobic biodegradation) is a promisingapproach (Barbeau et al., 1997). PCP-dechlorinating enrichment cultures were iso-lated in an anaerobic fluidized-bed reactor (Magar et al., 2000) and a fluidized-bedreactor was used to enrich an aerobic PCP-degrading microbial culture (Melin et al.,1997).
MATERIAL AND METHODS
Model Aquifer Materials
The aim of the experimental set-up was to produce PCP breakthrough curves forvarious environmental conditions presumed to affect bioavailability, namely thesorption capacity, water flow velocity, and biodegradation capacity of the medium.The column experimental set-up, the model aquifer materials (Figure 1), and thevarious conditions of each experiment (Table 1) were selected to recreate suchenvironments.
All the columns were saturated using a mineral salt medium (MSM; Greer andShelton, 1992) based on a phosphate buffer (pH 7.15). Pentachlorophenolate sodium(NaPCP) was added to the MSM as its sodium salt (Sigma, 98% pure). StandardOttawa sand (Anachemia, Montreal), consisting of clean silica sand of homogenousgranulometry (500 µm diameter), was used as the main component of the solidphase with the PCP-retaining resin Amberlite XAD-4 (Sigma). This resin will
Half flow rate C7column Inoculated silica sand after experiment C4
No resin0.5 mL min−1
Higher microbial C8population Inoculated silica sand after experiment C7column No resin
1 mL min−1
∗Amberlite XAD-4 (Sigma), which retains hydrophobic molecules.
FIGURE 1
Scheme of the experimental system.
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SSC TJ881-05 November 17, 2003 11:40
specifically retain hydrophobic molecules from aqueous media. Its grain size issimilar to the sand grain size, with a specific area of 715 m2 g−1 and an averageinside pore diameter of 50
❛
A. 3H-H20 (Sigma, 1 mCi mL−1) was diluted in MSMfor performing the tracer tests.
PCP-degrading microorganisms were grown from a PCP-contaminated soil sam-ple by sequential addition of NaPCP in a fed-batch slurry bioreactor using MSMat pH 7.15 (Becaert et al., 1999). This slurry was filtered through 8 µm-Whatmanfilter paper to obtain a suspension of microorganisms. The suspension was mixedwith sterile standard sand (1/3 vol/w) in a fed-batch aerated and agitated (200 rpm)bioreactor and enriched by sequential addition of NaPCP at concentrations in-creasing from 5 to 100 mg L−1. A parallel study, using molecular biology tech-niques such as SSCP (Single-Strand Conformation Polymorphism) performed onthe consortium, showed that the microflora primarily consisted of PCP degraderssuch as Sphingomonas sp. (Beaulieu et al., 2000). PCP monitoring was carriedout on a daily basis. Aqueous samples were centrifuged at 10000 g for 10 min,the supernatant was filtered through 0.45 µm filter paper (Millipore), and the UVabsorbance at 319 nm was read in a spectrophotometer (Varian model DMR90).When the biodegradation rate was nitrogen limited (due to constant addition ofcarbon substrate to MSM but not of nitrogen substrate), the aqueous phase con-taining a fraction of all the microorganisms was separated from the inoculatedsand. This inoculated sand was used to pack the biotic columns (C4 to C8 inTable 1).
Experimental Set-Up
The eight columns used for the experiments (Table 1) were pre-chromatographyChromaflexTM columns (VWR Canlab) made of KimaxTM borosilicate glass andpolytetrafluoroethylene (PTFE). The columns were 15 cm long with a 4.8-cm in-side diameter. Both ends included a 20-µm PTFE filter and a PTFE grid for bedsupport and accurate flow distribution. Model solids used for column packing con-sisted of silica sand (either sterile for abiotic elution or inoculated) and AmberliteXAD-4 resin. Columns C1, C2 and C3 were packed with 490 g of sterile stan-dard sand and with 0, 0.5 or 1 g of resin, respectively and were used under abioticconditions. Columns C4, C5 and C6 were packed with the same composition, butinoculated sand was used for packing the columns. For all eight columns, PCP wascontinuously injected during the course of the experiment (1.5 pore volumes ofstep injection). Elution on column C4 was monitored for the same time period asthe other columns (1.5 pore volumes) but it was performed until the concentrationat the exit of the column was brought down to a non-detectable level. This columnwas flushed for 10 pore volumes using MSM and a new experiment designatedC7 (PCP injection during 1.5 pore volumes) was performed at half the flow rate(0.5 mL min−1). Injection of PCP on this column was performed until the PCPlevel in the effluent was brought to a non-detectable level, the column was flushed
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for 10 pore volumes and a third experiment designated C8 (1 mL min−1) wasperformed.
All columns were packed with their composition of model solids by sedimenta-tion of the solids in MSM (2-cm section at a time until complete saturation of thecolumn). At the end of each experiment, column materials were dried and weighedfor saturation calculations. All experiments were performed with a water saturationof 99 ± 0.5% (v/v) and evaluated by weighing empty and saturated columns, as wellas, dry materials. Hydrodynamic characterisation of each column was performedusing a step tracer test with 3H-H2O based MSM. Fractions were collected at theexit of the column and counts per minute (CPM) were monitored using a liquidscintillation counter (Wallac, 1409).
Abiotic solute curves were obtained by performing upward step elution of PCP(13 mg L−1 in MSM) on the columns containing abiotic materials (columns C1, C2and C3). The PCP solution was fed at a rate of 1 mL min−1 using a Cole-Parmerperistaltic pump set up with a special PTFE tubing head. Fractions (4 mL) were col-lected at the exit of the columns and were used to monitor PCP concentration. Eachfraction was filtered through a 0.45 µm filter (Millipore) and PCP concentrationwas monitored by measuring absorbance at 319 nm. To avoid any limitations bydissolved oxygen (around 8.5 mg L−1 at 22◦C in the MSM) in the biotic columns,PCP was used at a concentration of 13 mg L−1 (requiring 7 mg L−1 of dissolvedoxygen), allowing stoichiometric biodegradation.
The same protocol was used for the biotic columns (C4, C5, C6, C7 and C8).These columns were packed with the same blends of sand and resin, but the sand hadbeen previously inoculated. Prior to the contaminant injection, two pore volumesof MSM were eluted through the biotic columns to discard non-attached cells(Herman et al., 1997). Biomass was monitored in the column effluent during thisflush by protein analysis using the micro-BCA (bicinchoninic acid) method (PierceChemicals, Rockford, IL). Samples were centrifuged (10000 g for 10 min) andthe pellet was washed with MSM to avoid interference between the reagent andPCP. After a second identical centrifugation, bacteria were lysed using 1%-tritonin water (Union Carbide, Danbury, CT), which is compatible with the methodreagent.
Breakthrough Curve Modeling
Breakthrough curves were mathematically modeled using the dual compartmentmodel developed by Angley et al. (1992). This model allows the contaminant topartition itself onto the sorbing material and to be reversibly absorbed into the ma-terial with a first-order rate-limited sorption. Biodegradation of the contaminant ismodeled as a first-order kinetic. This assumption, based on a no-growth hypothesis,is valid considering the short time during which the elution takes place (2.5 h) andthe rather low concentration of PCP in the influent solution compared to the adaptedconsortium used in the bioreactor. The dimensional form of the model is presented
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SSC TJ881-05 November 17, 2003 11:40
in Equations 1 and 2,
∂C
∂t+ F
ρ
θK D
∂C
∂t+ (1 − F)
ρ
θ
∂S
∂t= D
∂2C
∂z2− v
∂C
∂z− kbioC (1)
∂S
∂t= k[(1 − F)K DC − S] (2)
where C is the contaminant concentration in the aqueous phase (mg L−1), S is thePCP concentration in the sorbed phase (mg kg−1), t is the time (s), z is the axialdistance (cm), ρ is the medium bulk density (kg L−1), θ is the medium porosity,F is the fraction of sorbed contaminant for which sorption is instantaneous, K D
is the contaminant partition coefficient between the resin and the aqueous phase(L kg−1), D is the axial dispersion coefficient (cm2 s−1), v is the pore water velocity(cm s−1), kbio is the first-order biodegradation constant (s−1), and k is the first-orderreversible sorption rate (s−1).
The dual-compartment model was chosen because of the structure of the resin:large specific area for partition and small pore size for kinetically limited absorption.Due to the resin pore size (50
❛
A), the contaminant has access to the pores butthe microorganisms (average size of 1 µm) do not. The numerical solution wasobtained using the finite difference method on this set of distributed parameterEquations 1 and 2 followed by the resolution of the discretized equations usingthe Euler method. The initial and border conditions used on C and S are presented inEquations 3, 4, and 5.
C(z = 0, t ≥ 0) = C0 (3)
C(z ≥ 0, t = 0) = S(z ≥ 0, t = 0) = 0 (4)
∂C
∂z(z → ∞) = 0 (5)
Curve fitting for parameter estimation from experimental data was carried outusing a non-linear least-square method based on the Marcquardt-Levenberg algo-rithm. This step was performed independently for the hydrodynamic tracer test(estimation of D), for the abiotic elution (estimation of F, K D and k) and for thebiotic elution (estimation of kbio).
RESULTS AND DISCUSSION
The hydrodynamics for the eight columns, obtained from the column weight analy-sis, were characterized by an average porosity of 0.35 ± 0.01, an average hydraulicconductivity of 2.21 × 10−3 ± 0.09 × 10−3 cm s−1 and an average mean residencetime of 105.0 ± 7.4 min. Moreover, curve fitting performed on tracer tests for eachcolumn gave an average axial dispersion of 1.30 × 10−4 ± 0.36 × 10−4 cm2 s−1.
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SSC TJ881-05 November 17, 2003 11:40
FIGURE 2
Experimental (dotted lines) and model-fitted (solid lines) breakthrough curves obtained forthe columns performed under abiotic conditions.
These parameters show a strong plug-flow type hydrodynamic behavior, with lowdispersion. The small standard deviations for these parameters in the eight columnsallowed comparisons to be made between each column.
In order to decouple biotic from abiotic mechanisms, a first step in the break-through curve analysis consisted of understanding and quantifying the PCP sorptionbehavior onto the resin (Figure 2). When no resin was present (C1), a sharp break-through identical to the non-reactive tracer test was observed, showing that thesterile silica sand does not retain PCP. However, when resin was added (C2 andC3), the initial breakthrough was still observed but at a smaller level. The resinretained part of the PCP eluting through the columns, allowing approximately 50and 30% (C2 and C3, respectively) of the total PCP to breakthrough. The dualcompartment model accurately described the experimental results on the three abi-otic columns and allowed the estimation of the sorption parameters F , K D and k(Table 2). The very small values of F (fraction, between 0 and 1, of sorbed contam-inant for which sorption is instantaneous) clearly indicate that most of the sorbedcontaminants (99.97 and 99.94% for the columns 2 and 3 respectively) are notsorbed instantaneously and are therefore located within the pores of the resin (50
❛
Adiameter) where the absorption kinetic is the limiting mechanism. Despite the highsolubility of PCP at experimental pH 7.15 and the small amount of resin used in thecolumns, a K D of 3.93 L kg−1 and 6.56 L kg−1 for columns C2 and C3, respectively,indicated a clear uptake of the contaminant from the aqueous solution. Consideringthe fraction of resin used in the column, these values give an overall K D for PCPon the Amberlite XAD-4 resin of 3700 L kg−1. This value is in the same order of
842
SSC TJ881-05 November 17, 2003 11:40
TAB
LE2
Mod
elPa
ram
eter
sfo
rth
eEig
htC
olum
nsan
dB
ioav
aila
bilit
yR
ates
τ BA
Col
umns
KH
(s−1
)F
KD
(L·kg
−1)
k(s
−1)
k bio
(s−1
)(a
t1.5
pore
volu
mes
)
C1
(ste
rile
sand
)1.
71×
10−4
00
00
N.A
.C
2(+
0.5
gre
sin)
1.61
×10
−46.
4×
10−4
3.93
6.51
×10
−60
N.A
.C
3(+
1g
resi
n)1.
71×
10−4
3.4
×10
−46.
566.
82×
10−6
0N
.A.
C4
(ino
cula
ted
sand
)1.
81×
10−4
00
01.
15×
10−5
0.07
0C
5(+
0.5
gre
sin)
1.71
×10
−46.
4×
10−4
3.93
6.51
×10
−61.
15×
10−5
0.02
3C
6(+
1g
resi
n)1.
75×
10−4
3.4
×10
−46.
566.
82×
10−6
1.15
×10
−50.
020
C7
(C4,
half
flow
rate
)9.
0×
10−5
00
04.
18×
10−5
0.32
C8
(C4,
high
erm
icro
bial
activ
ity)
1.80
×10
−40
00
5.06
×10
−50.
18
KH
:red
uced
hydr
aulic
cond
uctiv
ity.
F:f
ract
ion
ofco
ntam
inan
tsor
bed
unde
req
uilib
rium
.K
D:d
istr
ibut
ion
coef
ficie
nt.
k:fir
st-o
rder
reve
rsib
leso
rptio
nki
netic
cons
tant
.k b
io:fi
rst-
orde
rbi
odeg
rada
tion
kine
ticco
nsta
nt.
τ BA
:bio
avai
labi
lity
rate
.
843
SSC TJ881-05 November 17, 2003 11:40
FIGURE 3
Experimental (dotted lines) and model-fitted (solid lines) breakthrough curves for the columnsperformed under biotic conditions.
magnitude as values obtained in other studies using such resins (Guerin and Boyd,1997). The absorption kinetic constants (k) were similar for the columns C2 andC3 (6.51 × 10−6 and 6.82 × 10−6 s−1), which is in agreement with the fact thatthe resin used in the two columns allowed similar diffusion rates within the pores.The main difference between the two columns resides in the surface area availableto partition the contaminant.
These results were confirmed in the biotic experiments (Figure 3). Columns C4,C5 and C6 were the biotic equivalents to columns C1, C2 and C3. The differencein amplitude between columns C1 and C4 (Figure 4) shows that biodegradationoccurred to a low extent (5%) during PCP transport during the 1.5 pore volumesof the experiments. The same observation was made for the sorptive columns (C2vs. C5 and C3 vs. C6; Figure 4). Column C4 was injected with PCP until theeffluent concentration was brought down to non-detectable levels. This first elu-tion lasted 100 pore volumes. During that time, the biodegradation activity wasable to increase from the available substrate, which led to a more active col-umn. This same column was used for a second experiment (C7) performed athalf the flow rate and, subsequently, for a third experiment at the initial flow rate(C8). These two breakthrough curves (Figure 3) clearly show the sharp increasein biodegradation capacity. From 5% degradation in column C4, biodegradationwent up to 40% and 25% for columns C7 (combination of increased activity andhalf flow-rate) and C8, respectively. The biodegradation is also increased whenthe residence time is increased (half flow-rate in column C7). Exposure of the
844
SSC TJ881-05 November 17, 2003 11:40
FIGURE 4
Comparisons of breakthrough curves for the non-reactive tracer test (similar to C1) and forthe columns performed under abiotic (C1, C2 and C3) and biotic (C4, C5 and C6 respectively)conditions.
microbes to the contaminant is time-dependent and a major influencing factor forbioavailability is residence time (Wick et al., 2001). Thus, three factors affect theavailability of PCP to microorganisms: sorption, biomass activity and residencetime.
The curve-fitting procedure carried out on the biotic columns was as follows.First, experiments C4 (inoculated sand), C5 (+0.5 g resin) and C6 (+1 g resin)were carried out simultaneously to assess the influence of the retention capacityof the medium on bioavailability and the biodegradation kinetic parameters fromcolumn C4 were used to model the biotic counterparts C5 and C6. Accordingly,sorption parameters obtained from columns C2 (abiotic sand +0.5 g resin) and C3(abiotic sand + 1 g resin) were used to model biotic columns C5 and C6. Thus,the dual-compartment model was validated for columns C5 and C6. The good fitof the model to the experiments (Figure 3) indicates that the pre-estimated param-eters (sorption and biodegradation) were valid for these two experiments and thatno detectable interactions occurred between the microflora and the resin (Table 2).Furthermore, the biodegradation kinetic constant on the inoculated sand was com-parable for columns C4, C5 and C6, showing the reproducibility of the columnsused.
By comparing the biodegradation kinetics obtained in the bioactive columns C4,C7 and C8, the influence of microorganisms on contaminant availability is assessed.
845
SSC TJ881-05 November 17, 2003 11:40
The freshly packed, inoculated sand gave an estimated first-order biodegradationconstant, kbio, of 1.15 × 10−5 s−1 (Table 2). For the second experiment on the samecolumn at half the flow-rate (C7), the kbio increased to 4.18 × 10−5 s−1 and to 5.06 ×10−5 s−1 for the third experiment (C8). This clearly indicates that, while there is nosignificant growth during the elution (1.5 pore volumes), constant feeding of thecolumn led to higher microbial activity and resulted in a higher biodegradation ratefor columns C7 and C8 versus column C4 as expected. Subsequently, results wereused for quantification of the bioavailability. Moreover, no signs of microorganismsleaching out of the columns was observed through protein analysis of the effluent.To assess the influence of pore water velocity, columns C7 and C8 were compared.Figure 3 shows that a longer exposure time for microorganisms to PCP results inmore PCP biodegradation.
Quantification of Contaminant Bioavailability
For all the columns studied, three tests were performed: a non-reactive tracer test,a PCP abiotic (sterile sand) test and a PCP biotic test (inoculated sand). The ex-perimental breakthrough curves were non-dimensionalized and plotted as relativeconcentration versus number of pore volumes (Figures 2 and 3). This enabledthe comparison between the results of the different tests. The area under each ofthe solute curves (AUCs) was calculated using the trapeze method. These AUCswere used to perform the mass balance over the column. The area under the curvecorresponding to the reference non-reactive tracer test (AUCref) represents the totalamount of solute injected in the column over the length of the experiment. The areaunder the abiotic solute curve (AUCabio) represents the amount of solute that wasnot sorbed by the solid matrix and was able to migrate through the column over thecourse of the experiment. Finally, the area under the biotic solute curve (AUCbio)represents the amount of solute that was neither sorbed nor biodegraded throughoutthe course of the experiment.
Bioavailability can be quantified as the total amount of contaminant taken upby the microflora during the course of the experiment. The bioavailable fraction(BA) of the total solute injected (AUCref) was calculated throughout the course ofthe experiment as the amount injected minus the amount sorbed minus the amountthat migrated out, according to Equation 6.
BA = AUCref − (AUCref − AUCabio) − AUCbio
AUCref= AUCabio − AUCbio
AUCref(6)
It took various times for the contaminant to migrate through each column andto generate a solute curve. The available fractions obtained for each column canbe compared either at a similar time or after being reduced to a characteristicexperimental time. This step leads to the definition of a bioavailability rate (τBA),according to Equation 7, which represents the reality of the contaminant availability
846
SSC TJ881-05 November 17, 2003 11:40
to the microbes in a flow-through system that cannot be a simple fraction of thetotal contaminant concentration.
τBA = BA
T(7)
In order to facilitate the comparison between the eight columns, the characteristictime (T) was set as the mean residence time and defined as the ratio between thearea under the first moment curve (AUMCbio) and the area under the biotic solutecurve (AUCbio) according to Equation 8.
T = AUMCbio
AUCbio=
∫ t0 Ctdt∫ t
0 Cdt(8)
This bioavailability rate was calculated for each column and was a time-independent and non-dimensional measure of the microorganisms’ exposure tothe contaminant, which allowed inter-column comparisons. Factors affecting avail-ability (degree of sorption, pore water velocity and biodegradation capacity) weregiven different values in the study and the bioavailability (BA) rates (τBA) werecomputed according to the method developed. These were compared and analyzed.The τBA for the five columns performed under biotic conditions (C4 to C8) werecomputed (Table 2) and reflect the different situations assessed. The increasingretention capacity assessed in columns C4, C5 and C6 led to a decrease in theτBA (0.07, 0.023 and 0.02, respectively). This observation is in agreement withthe general knowledge that contaminant sorption decreases its accessibility by mi-croorganisms (Luthy et al., 1997), but is new for flow-through systems. Guo et al.(1999) have shown significant differences between biodegradation rates measuredin the liquid and in the sorbed phases under flow-through conditions, but havenot assessed the influence of an increase in the sorption capacity on bioavailabil-ity. The activity of the microorganisms towards the contaminant showed a greatinfluence on the τBA. While initial results for column C4 (first elution on the inocu-lated sand) led to a rate of 0.07, the second elution performed on the same columnled to a value of 0.18. Finally, the pore water velocity showed a great influence onbioavailability that increased from 0.18 to 0.32 by decreasing the flow rate from 1 to0.5 mL min−1.
The influence of different factors (sorption, biodegradation activity and waterflow) on BA can be seen as a kinetic competition for the contaminant. On onehand, the flow carries the contaminant along, leaving a short exposure time be-tween the contaminant and the resin. On the other hand, the biological receptoris in competition for the same contaminant. This competition is quantitativelyexplained when looking at the magnitude of the kinetic constants for the dif-ferent mechanisms (Table 2). The reduced hydraulic conductivity (reported tothe length of the column) is larger than the values describing the other mecha-nisms and is thus the dominant factor, except for column C7 (half flow rate). In
847
SSC TJ881-05 November 17, 2003 11:40
column C7, the lowered hydraulic conductivity (K H of 9.0 × 10−5 s−1 for C7 ver-sus 1.81 × 10−4 s−1 for C4) allowed the biodegradation kinetic to compete (kbio
of 4.18 × 10−5 s−1, with the same order of magnitude as K H of 9.0 × 10−5 s−1).Bioavailability appears to be controlled by the limiting kinetic mechanism takingplace within the system: hydrodynamics, rate-limited sorption and biodegrada-tion. Bosma et al. (1997) reported a similar conclusion for bioavailability in staticsystems, where it was quantified as the ratio between rate-limited sorption andbiodegradation kinetics. However, hydrodynamics cannot be considered in staticsystems. Nevertheless, when the different kinetics of the system are known, thecontaminant availability to the microbes can be assessed. The four parametersnecessary (distribution coefficient, hydraulic conductivity, first-order sorption rateand first-order biodegradation rate) are frequently assessed for contaminated sites,can be found in the literature, or can be assessed in lab studies with sampledmaterial.
This study used only one contaminant, pentachlorophenol. Further studies per-formed with various organic contaminants need to be carried out in order to validatethe method. Furthermore, the direct estimation of a bioavailability rate from on-site experiments requires an abiotic test, which is not always possible on site. Thislimitation could be overcome by performing the abiotic test in a lab column usingsampled material.
CONCLUSION
The method presented here to estimate the bioavailability rate of an organic con-taminant to the microorganisms in a flow-through system can be applied eitherdirectly from abiotic and biotic column results or by indirect estimation using thekinetic parameters of the system. It has proven useful in distinguishing the aqueousphase concentration of the contaminant from the microbial uptake concentration,which takes into account the kinetic competition between the different mechanismstaking place in a flow-through system. Finally, the kinetic aspect of bioavailabilityis taken into account by defining an τBA instead of measuring a concentration notrelevant in a dynamic system.
ACKNOWLEDGMENTS
The authors acknowledge the financial support from the industrial Chair partners:Alcan, Bell Canada, Cambior, Canadian Pacific Railway, CEAEQ, Hydro-Quebec,Natural Science and Engineering Research Council (NSERC), Gaz de France-Electricite de France, Ministere de la Metropole et des affaires municipales duQuebec, Petro-Canada, Solvay, Total-Fina-ELF, Ville de Montreal. The authorsthank Dr Sherri Dudal for reviewing this manuscript.
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