Biodegradation of petroleum hydrocarbon vapors: laboratory studies on rates and kinetics in unsaturated alluvial sand

Biodegradation of petroleum hydrocarbon vapors:

laboratory studies on rates and kinetics in

unsaturated alluvial sand

Patrick Hohener*, Celine Duwig1, Gabriele Pasteris,Karin Kaufmann, Nathalie Dakhel2, Hauke Harms

Swiss Federal Institute of Technology (EPFL), ENAC-ISTE-LPE, CH-1015 Lausanne, Switzerland

Received 17 May 2002; accepted 7 January 2003

Abstract

Predictions of natural attenuation of volatile organic compounds (VOCs) in the unsaturated zone

rely critically on information about microbial biodegradation kinetics. This study aims at

determining kinetic rate laws for the aerobic biodegradation of a mixture of 12 volatile petroleum

hydrocarbons and methyl tert-butyl ether (MTBE) in unsaturated alluvial sand. Laboratory column

and batch experiments were performed at room temperature under aerobic conditions, and a reactive

transport model for VOC vapors in soil gas coupled to Monod-type degradation kinetics was used

for data interpretation. In the column experiment, an acclimatization of 23 days took place before

steady-state diffusive vapor transport through the horizontal column was achieved. Monod kinetic

parameters Ks and vmax could be derived from the concentration profiles of toluene, m-xylene, n-

octane, and n-hexane, because substrate saturation was approached with these compounds under the

experimental conditions. The removal of cyclic alkanes, isooctane, and 1,2,4-trimethylbenzene

followed first-order kinetics over the whole concentration range applied. MTBE, n-pentane, and

chlorofluorocarbons (CFCs) were not visibly degraded. Batch experiments suggested first-order

disappearance rate laws for all VOCs except n-octane, which decreased following zero-order

kinetics in live batch experiments. For many compounds including MTBE, disappearance rates in

abiotic batch experiments were as high as in live batches indicating sorption. It was concluded that

0169-7722/03/$ - see front matter D 2003 Elsevier Science B.V. All rights reserved.

doi:10.1016/S0169-7722(03)00005-6

* Corresponding author. Tel.: +41-21-693-57-50; fax: +41-21-693-28-59.

E-mail address: [email protected] (P. Hohener).1 Present address: Laboratoire d’etude des transferts en hydrologie et environnement, UMR 5564 (CNRS,

INPG, IRD, UJF), PB 53, 38041, Grenoble cedex 9, France.2 Present address: Ecole d’ingenieurs de Changins, CH-1260 Nyon, Switzerland.

www.elsevier.com/locate/jconhyd

Journal of Contaminant Hydrology 66 (2003) 93–115

the column approach is preferable for determining biodegradation rate parameters to be used in risk

assessment models.

D 2003 Elsevier Science B.V. All rights reserved.

Keywords: Petroleum hydrocarbons; Natural attenuation; Vadose zone; Bioremediation

1. Introduction

Due to the widespread use of fuels, fuel components such as petroleum hydrocarbons

and methyl tert-butyl ether (MTBE) are among the most frequent groundwater contam-

inants (Baehr et al., 1999). Accidental release of fuel to the subsurface results in residual

pools retained in the unsaturated zone (Mercer and Cohen, 1990). This residual fuel can

generate organic vapors in the soil gas phase that can migrate through the unsaturated zone

by diffusion and advection (Scanlon et al., 2000). Gaseous transport of volatile organic

compounds (VOCs) through the unsaturated zone has been identified as a serious threat for

groundwater quality (Baehr et al., 1999; Pasteris et al., 2002). VOC vapors may also

volatilize into the atmosphere, thereby creating a potential health threat to individuals

living in the vicinity of emission sources (Jin et al., 1994). However, the unsaturated zone

is a porous filter layer in which microbiological degradation naturally attenuates pollu-

tants. It has been observed that, under favorable conditions, some petroleum hydrocarbons

are rapidly and completely biodegraded in the unsaturated zone (Ostendorf and Kampbell,

1991; Hinchee and Ong, 1992; Lahvis et al., 1999). Vapor transport is also influenced by

partitioning between liquid and gas phases, and by sorption onto soil particles (Jin et al.,

1994; Li and Voudrias, 1994a,b; Baehr et al., 1999; Kim et al., 2001). Improved

knowledge of the different processes operating in the soil and governing reactive gas

transport is essential to estimate the migration of VOC vapors from contaminated sites

through the unsaturated zone.

Several mathematical models have been proposed to describe the reactive transport of

VOCs in the unsaturated zone (Jury et al., 1983; Jin et al., 1994; Baehr and Baker, 1995;

Baehr et al., 1999). These models include typically first-order kinetics to represent

biodegradation. First-order reactions are popular because of simplicity. They assume

constant biomass, but do not reflect biological phenomena such as dependence on

substrate concentration, inhibition or preferential substrate utilization (Schirmer et al.,

1999). These factors can, however, be incorporated in the Monod equation (Monod, 1949).

Monod kinetic parameters have been determined for various microorganisms growing in

liquid cultures on VOCs such as BTEX (Robertson and Button, 1987; Alvarez et al., 1991;

Chang et al., 1993; Duetz et al., 1997; Schirmer et al., 1999) or n-alkanes (Button, 1985).

Also, the effects of substrate interactions on the Monod kinetic parameters have been

described (Bielefeldt and Stensel, 1999a,b; Reardon et al., 2000). All this work was based

on microorganisms that have been isolated from aquatic ecosystems such as, e.g., sewage

or aquifer sediments and were cultivated in the laboratory, usually in liquid media at

relatively high carbon substrate concentrations. The transfer of these results to micro-

organisms in unsaturated soil is therefore not easily achieved. Autochthonous micro-

organisms have to cope with carbon limitation, exhibit moderate to low specific activity,

P. Hohener et al. / Journal of Contaminant Hydrology 66 (2003) 93–11594

and may comprise a large number of inactive (dormant) cells (Dobbins et al., 1992; Haack

and Bekins, 2000). Moreover, in the unsaturated zone, microbial populations generally

live attached to surfaces, which may result in drastically reduced substrate availability

(Harms and Zehnder, 1994; Simoni et al., 2001).

As noted by Jin et al. (1994), the experimental basis to understand biodegradation

kinetics of VOC vapors in the unsaturated zone is still limited. A number of previous

studies was based on laboratory batch microcosm experiments (English and Loehr, 1991;

Allen-King et al., 1994a; Zhou and Crawford, 1995; Freijer et al., 1996; Ostendorf et al.,

2000; Baker et al., 2000). Zhou and Crawford (1995) determined Monod kinetic

parameters with total petroleum hydrocarbon in batch experiments with soils that were

acclimated for 1.5 months to gasoline vapors. Drawbacks of batch techniques include the

disruption of soil aggregates, changing boundary conditions (e.g. O2), and the need to

apply much higher contaminant-to-soil ratios than observed in natural soil. Laboratory soil

column experiments can avoid some of these limitations and can account for transport and

degradation. Unsaturated laboratory column experiments have been performed with vapor

transport being solely diffusive (Baehr and Baker, 1995) or advective and diffusive (Jin et

al., 1994; Moyer et al., 1996). Other experiments included also aqueous transport in

unsaturated laboratory columns (Allen-King et al., 1994b, 1996). Conflicting findings

were obtained with unsaturated experimental systems, as first-order (Allen-King et al.,

1994a; Jin et al., 1994; Moyer et al., 1996; Lahvis et al., 1999) as well as zero-order

biodegradation kinetics (Baehr and Baker, 1995; Freijer et al., 1996; Baker et al., 2000)

were reported for various compounds.

We report here on laboratory column and batch experiments to study the biodegradation

kinetics of fuel VOCs in homogeneous unsaturated alluvial sand. The contaminant was a

mixture of 13 VOCs typical for gasoline or kerosene with two recalcitrant fluorinated

tracers. Kinetic parameters for individual compounds degraded from the mixture are

reported. An outdoor lysimeter study was previously conducted with the same sand and

contaminant source (Pasteris et al., 2002). In that study, first-order biodegradation rates

were estimated from concentration vs. depth profiles of VOC vapors. However, the

analytical certainty and the spatial and temporal resolution of data in that experiment were

insufficient to gain detailed insight into biodegradation kinetics. This manuscript aims to

determine biodegradation kinetic constants under well-defined conditions in the labora-

tory, as part of a larger European project developing an experimental base, models, and

guidelines for groundwater risk assessment at contaminated sites (GRACOS).

2. Materials and methods

2.1. Fuel compound mixture

A mixture of 13 typical fuel compounds (Johnson et al., 1990; Cline et al., 1991; Potter

and Simmons, 1998) and 2 chlorofluorocarbons (CFCs) as volatile organic tracers (Table

1) was prepared from products of >99% purity obtained from Fluka (Buchs, Switzerland).

Trichlorofluoromethane (CFC-11) and 1,1,2-trichloro-1,2,2-trifluoroethane (CFC-113)

were chosen because of their persistence under aerobic conditions (Hohener et al.,

P. Hohener et al. / Journal of Contaminant Hydrology 66 (2003) 93–115 95

2003). The same mixture without CFC-113 was used by Pasteris et al. (2002), where the

relevant physico-chemical characteristics of the compounds are reported.

2.2. Characterization of the sand

The alluvial sand used in this study was extracted from Lake Geneva near the Rhone

river delta, de-watered, and sieved < 4 mm. No microorganisms were added before or

during the experiments. Characteristics of the sand were reported previously (Pasteris et

al., 2002).

2.3. Exposure experiment to quantify biomass changes during exposure to VOCs

Small glass dishes filled with 20 g of sand were incubated for 1–38 days in a closed

glass jar containing humidified air and an open vial with 50 ml of the VOC mixture. The

air phase was thus saturated with VOC vapors (see Table 1 for vapor concentrations). O2

partial pressure was always >20%. Total microbial cell numbers were determined after

extraction from the sand fraction < 2 mm by shaking 10 g soil and 5 g glass beads (F= 3

mm) in 50 ml distilled, cell-free water on a rotary shaker for 30 min. Extracts were stained

with 1:10,000 diluted fluorescent dye Sybr Green II (Molecular Probes, Eugene, US).

Twenty microliters of extract were filtered through a white polycarbonate filter (0.2 Am,

Sartorius, Gottingen, Germany) and stepwise dried with ethanol (50%, 80%, and 96%).

Table 1

Composition of fuel, initial vapor pressure of each compound in the mixture governed by Raoult’s law, and

partitioning coefficients used for calculation of capacity factors Ra

Compound Formula Weight in

mixture

(%)

Initial vapor

concentration Ca,oa

(20 jC) (g m� 3)

Henry’s law

constant at 25 jCb

(mol/lgas)/(mol/lwater)

Calculated Kdb

(l kg� 1)

n-Pentane C5H12 3 74.7 50.65 4.4

n-Hexane C6H14 6.9 48.1 68.38 11.1

n-Octane C8H18 7.9 5.14 120.7 84

n-Decane C10H22 16.8 1.27 198c 630

n-Dodecane C12H26 8.9 0.09 293 4105

Methylcyclopentane C6H12 5.9 37.4 14.65 1.7

Methylcyclohexane C7H14 9.9 18.7 17.6c 4.3

Cyclohexane C6H12 5.9 26.1 7.33 3.1

Isooctane

(2,2,4-trimethylpentane)

C8H18 14.9 30.3 132.4 10.7

Toluene C7H8 3 3.74 0.26 0.8

m-Xylene C8H10 5 1.81 0.26 1.8

1,2,4-Trimethylbenzene C9H12 5.9 0.57 0.27 4.7

MTBE C5H12O 5 60.1 0.03 0.03

CFC-113 C2Cl3F3 1 15.9 14.2 1.85

CFC-11 CCl3F 0.01 0.39 3.73 0.6

a Calculated as Ca,0 =Ca,pX with Ca,p = saturated vapor concentration of pure compound (Pasteris et al., 2002)

and X =molar fraction in mixture.b For references and calculations, see Pasteris et al. (2002).c Yaws and Young (1992).


Bacteria were counted in 16 randomly selected fields of 0.0001 cm2 per sample with a

microscope equipped for epifluorescence (Olympus BX-60, Olympus Optical, Tokyo,

Japan). The variance (1r) is reported for counts of three samples from one extraction. Total

protein in the sand was determined using the Bradford assay as described in Hess et al.

(1996). Microbial biomass was calculated from the protein content using a conversion

factor of 0.55 g protein g� 1 cells.

2.4. Laboratory column experiment

A one-dimensional horizontal column experiment was carried out during 51 days at room

temperature (23F 2 jC). The laboratory column (Fig. 1) of 120 cm length and 8.1 cm

internal diameter made of acrylic glass was homogeneously packed with sand to a soil

density of 1.49 g cm� 3. Voids of 3 cm length remained on both ends of the column. Tight

packing and constant moisture self-stabilized the sand–air interface. The sand had

previously been moistened with distilled water to the volumetric water content of 0.118

m3 m� 3. This water content corresponds to 28% of the total porosity (ntot = 0.42) and is

above the water retention capacity (0.03 m3 m� 3) for this coarse-textured sand. Due to the

horizontal position of the column, no hydraulic gradient causing water advection along the

column axis was present. A small hydraulic gradient that established across the column

diameter was assumed to be of limited influence, as vapor transport was studied in the center

of the column. The sand and its indigenous microbial community were left undisturbed

during 20 days to acclimatize after column packing. After that period, designated day 0, the

columnwas connected to a reservoir containing 10ml of VOCmixture (Fig. 1), in a way that

one end of the sand column was in direct contact with the fuel headspace. Fresh fuel was

added on days 9 and 28, since by then some of the very volatile compounds were slightly

depleted. The void space on the other end of the column was purged with a water-saturated

airflow at a rate of 5F 1 ml min� 1, in order to chase the fuel vapor without drying the sand.

Fluxes of VOC vapors escaping from the column were quantified by multiplying vapor

concentrations with the air flow rate. Periodical weighing of the column showed that loss of

water was negligible. The column was equipped with 13 sampling ports positioned every 10

Fig. 1. Schematic drawing of the column experimental set-up.


cm (Fig. 1). These ports were made with GC septa (Injection rubber plugs, Part No. 201-

35584, Shimadzu, Kyoto, Japan) fitted into a hole of 4.8 mm diameter. Two ports allowed

measurements of gas concentrations in the air at both ends outside of the sand and the others

were for sampling of the gas phase in the sand. Gas samples were taken with gas-tight

syringes equipped with a two-way valve and stainless steel hypodermic needles (length 50

mm; i.d. 0.15 mm).

2.5. Laboratory batch microcosm experiments

Bottles of 63 ml volume (H�F= 90� 35 mm) closed with Teflon MininertR valves

(Supelco, Buchs, Switzerland) were used for microcosm experiments. After bringing the

sand to the desired moisture content, it was filled into the bottle with a spoon and packed to a

total porosity of 0.42F 0.02 without leaving any headspace in the bottle. Before adding the

VOCs, the microcosms were stored at 25 jC for 24 h. Then, 2 ml of the VOC-saturated

headspace of a bottle containing the fuel mixture at 25 jC were injected by using a stainless

steel hypodermic needle (50 mm length) fitted to a gas-tight syringe. The injection was

directed at the center of the bottle in the sand. Diffusion was the process responsible for the

homogenization of vapor concentrations in the microcosm. Since diffusion is fast over short

distances, homogeneous distribution was expected within a few minutes after vapor

addition. Abiotic controls were prepared by autoclaving the sand three times at 120 jCfor 20 min at intervals of 24 h and adding thereafter 0.2 g of NaN3 per 100 g of sand. The

sand used in this study was also separated into sieve fractions of 150–200 and 500–1000

Am. These fractions were treated separately as abiotic controls and abiotic losses were

studied therein. Further controls were performed by injection of 10 ml of VOC vapor into

empty bottles to account for gas leaks and sorption to glass and stoppers.

2.6. Analytical methods

Gas concentrations of volatile organic compounds were analyzed by injecting 50 Al ofgas into an HP-6890 Series gas chromatograph (Agilent Technologies, USA) using gas-

tight syringes with Teflon plungers. The GC method and detection limits were reported

previously (Pasteris et al., 2002). The GC was calibrated by diluting the fuel mixture in

cyclohexane, whereas calibration for cyclohexane was performed by diluting it in toluene.

Partial pressures of CO2 and O2 were analyzed by injecting 100 Al of gas into a GC-8AIT

gas chromatograph (Shimadzu) equipped with two PORAPAK Q columns (3 m� 1.6 mm)

and a thermal conductivity detector operated at 55 jC, using N2 as carrier gas. Dilutions of

pure gases of CO2 and O2 were used for calibration.

3. Theory

3.1. Biodegradation kinetics

The basic assumptions underlying this work are that microorganisms are living in the

aqueous phase of the unsaturated zone, that VOC vapors need to dissolve in the aqueous


phase before biodegradation can occur, and that biodegradation follows Monod kinetics.

The hyperbolic function proposed by Monod (1949) to describe microbial growth as a

function of the aqueous substrate concentration was modified by Lawrence and McCarthy

(1970) to describe the removal rate of a growth limiting substrate as a function of the

substrate concentration:

rwðCwÞ ¼ vmaxXCw

ðKs þ CwÞð1Þ

where rw(Cw) (g substrate m� 3 day� 1) is the reaction rate in the aqueous phase, vmax (g

substrate g� 1 cells day� 1) is the maximum specific substrate utilization rate at infinite

substrate concentration, X (g cells m� 3) is the biomass in the aqueous phase, Cw (g m� 3)

is the carbon substrate (VOC) concentration in the aqueous phase, and Ks (g m� 3) is the

half-saturation constant in the aqueous phase. Note that use of Cw in Eq. (1) assumes that

carbon is the limiting element and that other elements such as oxygen, nitrogen, or

phosphorus are assumed to be present in excess.

Concentrations of VOCs in soil water are difficult to measure directly. However, it can

be assumed that Cw is proportional to the concentration in soil air Ca (g m� 3) via

Ca ¼ HCw ð2Þ

where H is the dimensionless form of Henry’s law constant (g m� 3 air/g m� 3 water).

Combining and transforming Eqs. (1) and (2) gives the biodegradation rate in the

aqueous phase as a function of the concentration in soil gas:

rwðCaÞ ¼ vmaxXCa

ðHKs þ CaÞð3Þ

Eq. (3) assumes instantaneous equilibration of VOC between soil air and water. It

furthermore regards reaction rates observed with constant biomass X. Growth was not

regarded in this study but can be accounted for by the Monod-with-growth model

(Simkins and Alexander, 1984; Kelly et al., 1996).

3.2. Coupling biodegradation, sorption, and diffusive transport

The transport model used in this study is a modified form of the diffusive reactive

transport model used by Jin et al. (1994). In addition of the assumptions regarding the

biodegradation processes, the following further assumptions were made: (1) diffusion is

the dominant transport process and Fick’s law applies, (2) all solid surfaces are wetted, i.e.,

air/solid interfaces are absent, (3) sorption is linear and reversible, (4) volatilization obeys

Henry’s law (Eq. (2)), (5) diffusion in soil water is very slow as compared to diffusion in

soil air and thus negligible, and (6) the diffusion coefficient in soil air, as opposed to air, is

reduced by a tortuosity factor sa as given by Millington and Quirk (1961):

sa ¼ h2:33a =n2tot ð4Þ

Here, ha (m3 air m� 3 total) is the volumetric soil air content and ntot is the total porosity.

Modifications from Jin et al. (1994) are assumption 5 and the omission of decay in the


sorbed phase. With these assumptions, the reactive transport of VOC vapors in soil can be

expressed in terms of the soil air concentration Ca as:

Ra

BCa

Bt¼ D

B2Ca

Bz2� hwrwðCaÞ ð5aÞ

where the capacity (or retardation) factor Ra (m3 air m� 3 total) and the diffusion

coefficient in soil D (m2 day� 1) are defined as follows:

Ra ¼ ðqbKd þ hw þ haHÞ=H ð5bÞ

D ¼ hasaDa ð5cÞ

where qb (g m� 3) is the soil bulk density, Kd (m3 g� 1) is the distribution coefficient

between dissolved and solid phase, D (m2 day� 1) is the effective diffusion coefficient of a

fuel compound in soil air, Da (m2 day� 1) is the molecular diffusion coefficient in air

calculated according to the method of Fuller as outlined in Schwarzenbach et al. (1993),

and hw (m3 water m� 3 total) is the volumetric soil water content.

3.3. Solutions applying to the column experiments

3.3.1. First-order

Due to the non-linearity of the Monod equation, analytical solutions of Eq. (5a)

generally cannot be found. However, solutions for first-order and zero-order kinetics are

available. At steady state, the left-hand side of Eq. (5a) is zero and the capacity factor Ra

has no influence. When HKsHCa, Eq. (3) becomes a first-order rate law. For the column

experiment, an analytical solution describing the special case of first-order biodegradation

at steady-state was published by Wilson (1997) for the boundary conditions

Ca ¼ Ca;0 at z ¼ 0 ð6aÞ

Ca ¼ 0 at z ¼ L ð6bÞ

Ca ¼ Ca;0

sinh

ffiffiffiffil1c

D

qðL� zÞ

� �

sinh

ffiffiffiffil1c

D

qL

� � ð6cÞ

l1c ¼

vmaxhwXHKs

ð6dÞ

Here, lc1 (day� 1) is a lumped first-order rate coefficient applying to the column

experimental setup, Ca,0 is the concentration in the source headspace, and L (m) is the

length of the soil column. Note that hwX is the biomass per unit volume of the column

(g cells m� 3). lc1 can be determined for each compound in this study by fitting this

solution to the measured Ca(z) profiles.


3.3.2. Zero-order

When HKsbCa, Eq. (3) becomes a zero-order rate law. An analytical solution for Eqs.

(5a)–(5c) and zero-order kinetics at steady-state is available (Eweis et al., 1998) for the

boundary conditions:

Ca ¼ Ca;0 at z ¼ 0 ð7aÞ

dCa=dz ! 0 at z ! k; with k ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffi2Ca;0D

l0c

sð7bÞ

Ca ¼ Ca;0 1þ z2 � 2zk

k2

� �ð7cÞ

l0c ¼ vmaxhwX ð7dÞ

Here, lc0 (g substrate m� 3 day� 1) is a lumped zero-order rate coefficient applying to

the column experimental setup. Note that the k (Eq. (7b)) corresponds to the penetration

depth of VOC vapors into the column (Eweis et al., 1998). Note also that the assumption

of zero-order kinetics is violated near this penetration depth where Ca becomes small.

3.3.3. Determination of Monod parameters

Following Suidan and Wang (1985) as described in Ostendorf and Kampbell (1991),

Monod kinetic parameters can be obtained from VOC fluxes inferred from hydrocarbon

concentration profiles. Therefore, concentration versus distance profiles have to be

transformed to flux versus distance profiles. Diffusive fluxes F (g m2 day� 1) of hydro-

carbon vapors through the soil column are calculated using Fick’s law:

F ¼ �DBCa

Bzð8Þ

Fluxes for each compound are calculated from Ca(z) profiles from the concentration

gradient at two adjacent sampling ports. By coupling Eqs. (3), (5a)–(5c), and (8) and

derivating F2 as a function of a dimensionless concentration, the following equation can be

written (Ostendorf and Kampbell, 1991):

BðF2ÞBCa*

¼ 2DvmaxHKshwXCa*

ð1þ Ca*Þð9Þ

where Ca* =Ca/HKs is a dimensionless form of the VOC concentration.

Following Ostendorf and Kampbell (1991), the variables in Eq. (9) can be separated

and integrated:

F ¼ ½2DvmaxhwXHKsðCa*� lnð1þ Ca*ÞÞ1=2 ð10Þ

When D, H, and hwX are known, Ks and vmax can be derived by fitting Eq. (10) to (F, Ca*),

using the solver modules provided by commercially available software. In this study,

Excel (Microsoft) and Kaleidagraph (Abelbeck) yielded the same results.


3.4. Solutions applying to batch experiments

For batch experiments, the solutions of Eqs. (5a)–(5c) for first-order and zero-order

case are

First � order : Ca ¼ Ca;0expf�l1c t=Rag ð11aÞ

Zero� order : Ca ¼ Ca;0 � l0c t=Ra ð11bÞ

where Ca,0 is the concentration in the soil gas after initial homogenization of vapors. It

should be noted that, for the batch experiments, the capacity factor Ra accounts for abiotic

losses of VOC vapor. The first-order exponential loss rate in a batch equals lc1/Ra and the

zero-order loss rate equals lc0/Ra.

4. Results

4.1. Biomass formation in sand upon exposure to VOCs

Before exposure to VOC vapors, the sand used for all experiments contained

3F 0.6� 108 cells g� 1 dry sand (n = 6). This corresponded to 0.24F 0.05 mg protein

g� 1. During exposure to VOC vapor in the closed jar, cell numbers rose without

significant lag (Fig. 2) and reached 8.8F 0.8� 108 cells g� 1 and 0.71F 0.18 mg protein

g� 1 on day 38.

Fig. 2. Microbial cell numbers in sand as a function of exposure time to VOC vapors, measured during the

exposure experiment in the closed glass jar.


Fig. 3. Evolution of concentration profiles of selected VOC compounds in the column. Solid squares: day 1, open

triangles: day 7, solid circles: day 23.


4.2. Column experiment

The evolution of longitudinal VOC concentration profiles in the column was monitored

during 56 days. Profiles of four selected compounds obtained after 1, 7, and 23 days are

shown (Fig. 3). The concentration of CFC-113 decreased linearly after 1 day. No

significant changes were observed thereafter. MTBE profiles were curved on day 1 and

to a lesser extent on day 7 with concentrations below detection limit at the column end. On

day 23 and thereafter, the profile was linear. Concentration profiles of n-octane and m-

xylene remained curved throughout the experiments with no compound entering the

columns further than approximately 50 cm.

Fig. 4. Evolution of the partial pressures of carbon dioxide (CO2) and oxygen (O2) between 3 days before and 44

days after contamination. ( w ) day � 3, (n) day 1, (E) day 7, (�) day 21, (5) day 32, (

b

) day 44.


The corresponding partial pressures of CO2 and O2 are given in Fig. 4. Three days

before exposure to fuel vapor, the CO2 partial pressure was in the range of 0.3%. During

exposure to fuel vapor, it rose steadily and reached a maximum of 4.6% close to the fuel

inlet on day 21 before decreasing again. Partial pressures of O2 were recorded from day 21

on. They showed the corresponding inverse trend with lowest concentrations of 13.3% on

day 21 at the fuel inlet of the column (Fig. 4). The volumetric water and soil air contents

remained constant at hw = 0.118 and ha = 0.302 throughout the experiment.

On day 56, the protein content in a sand sample taken at 0.53 m distance from column

end was 0.78F 0.58 mg protein g� 1 dry sand. Assuming a bulk density of 1480 kg dry

sand m� 3 and a conversion factor of 0.55 g protein g� 1 microbial cells, the microbial cell

mass per unit volume in the column (equalling hwX) is estimated to be 0.30F 0.05 g cells

m� 3 before contamination and 0.96F 0.71 g cells m� 3 on day 56.

Fig. 5. VOC profiles along the column after 23 days. Symbols: measured concentrations. Solid lines: first-order

model (Eqs. (6a)– (6d)). Broken line: zero-order model (Eqs. (7a–7d); n-octane only).


Table 2

Summary of rate laws and rate constants obtained for column and batch experiments

Compound Column on day 23 Batch Lysimeter

Rate law

giving best fit

First-order rate

lc1 (day� 1)

Capacity

factor a, Ra

Flux at

column

outlet (gm� 2

day� 1)

Rate law

giving best

fit in live

sand

Liveb lc1/Ra

(day� 1)

Abioticb

(day� 1)

Difference

live–abiotic

(day� 1)

First-order rate

(Pasteris et al.,

2002) (day� 1)

n-Pentane – < 0.01 0.43 0.20 first-order 0.42F 0.31 0.29F 0.26 – c < 0.05

n-Hexane Monodd 0.26 0.54 0.22 first-order 0.92F 0.27 0.27F 0.22 0.65F 0.35 0.4

n-Octane Monodd 5.0 1.33 0 zero-order 10.6F 2.8e 0.15F 0.14 10.4F 2.8e 6.7F 1.7

n-Decane first-order 13.5 5.08 0 – – – – 5

Methylcyclopentane first-order 0.1 0.48 0.50 first-order 0.52F 0.29 0.24F 0.29 – c 0.15

Methylcyclohexane first-order 0.16 0.67 0.50 first-order 0.55F 0.33 0.13F 0.13 – c 0.8F 0.4

Cyclohexane first-order 0.07 0.95 0.28 first-order 0.43F 0.32 0.20F 0.24 – c 0.5F 0.3

Isooctane

(2,2,4-trimethylpentane)

first-order 0.09 0.42 1.05 first-order 0.36F 0.43 0.17F 0.17 – c 0.12F 0.03

Toluene Monodd 1.31 5.09 0 first-order 2.86F 0.08 0.91F 0.52 1.95F 0.53 3.2

m-Xylene Monodd 3.28 11.1 0 first-order 4.42F 0.94 0.74F 0.77 3.68F 1.21 –

1,2,4-Trimethyl-benzene first-order 4.98 26.3 0 – – – – –

MTBE – < 0.01 5.60 0.91 first-order – – – c < 0.05

CFC-113 – < 0.01 0.44 0.17 first-order 0.26F 0.35 0.32F 0.18 – c –

CFC-11 – < 0.01 0.56 0.12 first-order 0.25F 0.35 0.31F 0.39 – c < 0.05

– : data could not be fitted with any model.a Calculated with Eq. (5b) using qb = 1.48 kg l� 1, ha = 0.302, hw = 0.118, and Kd values taken from Pasteris et al. (2002).b MeanF standard deviation of two live and five abiotic batch experiments.c Rate in live sand not significantly different from rate in abiotic sand.d Data shown in Table 3.e Better fit: zero-order rate in live batches 1.68F 0.24 g m� 3 day� 1.

P.Hohener

etal./JournalofContaminantHydrology66(2003)93–115

106

Concentration versus distance profiles of all VOCs are shown for day 23 (Fig. 5). This

day was chosen because CO2 and O2 partial pressures (Fig. 4) indicated maximum

biodegradation and VOC migration data (Fig. 3) indicated the establishment of a steady

state of substrate VOC transport and consumption. Besides linear profiles of CFC-113 and

MTBE, and n-dodecane concentrations below detection limit at all sampling ports, all

other VOC profiles were curved. Most of these profiles were reasonably well explained by

the reactive transport model with first-order biodegradation (Eqs. (6a)–(6d)). Vapors of six

compounds (toluene, n-octane, n-decane, n-dodecane, m-xylene, and 1,2,4-trimethylben-

zene) did not extend to the column outlet on days 23 (Fig. 5) and 44 (data not shown).

Hence, fluxes of these compounds across the sand–air interface at the outlet were zero.

For all the other VOCs, fluxes at the column outlet could be determined (Table 2). The

total flux of all VOCs at the column inlet on day 21 was 3.9F 0.8 g m� 2 day� 1. The

corresponding flux of CO2 was 3.0F 0.6 g C m� 2 day� 1, while the flux of O2 into the

column was 12.4F 2.5 g m� 2 day� 1.

All concentration profiles except those of CFC-11 and n-dodecane were transformed

into flux versus concentration profiles using Eqs. (8) and (9) (data not shown). The

parameters Ks and vmax were estimated from such profiles by curve fitting using Eq. (10).

Monod kinetic parameters for toluene, m-xylene, n-octane, and n-hexane could be

obtained this way and compiled with literature data (Table 3). For the other compounds,

the flux was constant indicating no degradation activity (CFC-113, MTBE, and n-

pentane), or flux versus concentration profiles were linear indicating first-order kinetics

over the entire range of concentrations (cyclic alkanes, isooctane, and 1,2,4-trimethylben-

zene), or they had too few data points to be interpreted (n-decane). Monod parameters

could not be obtained in any of these cases.

Table 3

Comparison of Monod coefficients obtained in this study with selected literature values

VOC Experimental system Temperature

(jC)Ks (g m� 3) vmax (g g� 1

cells day� 1)

References

m-Xylene saturated batch,

pristine sandy aquifer

10 0.79 7.9F 2.3a Schirmer et al., 1999

p-Xylene batch, gasoline-

contaminated soil

16 6.2b Goldsmith and

Balderson, 1988

Xylene batch, creosote-

contaminated soil

24–26 1.17F 0.38 15.8F 2.6b Kelly et al., 1996

m-Xylene alluvial sand column 23F 2 1.04F 0.70 0.96F 0.39 this study

Toluene batch, creosote-

contaminated soil

24–26 0.039 2.2b Kelly et al., 1996

Toluene saturated sandy aquifer 25 17.4 9.9 Alvarez et al., 1991

Toluene alluvial sand column 23F 2 < 0.3 0.29F 0.05 this study

n-Octane P. putida (oleovorans)

GPo1

0.0008 22b,c Lageveen, 1986

n-Octane alluvial sand column 23F 2 0.004F 0.001 2.45F 0.45 this study

n-Hexane alluvial sand column 23F 2 0.005F 0.002 0.21F 0.16 this study

a Using reported cell yield to convert from lmax.b Assuming a cell yield of 0.5 g cells g� 1 substrate degraded.c vmax obtained in pure culture studies may not be comparable to vmax in mixed cultures.


4.3. Batch experiments

In control experiments using bottles without sand, gaseous concentrations of all VOCs

except n-dodecane (data not shown) stayed within F 10% of the initial concentrations for

15 days (Fig. 6). In abiotic controls, concentrations of all VOCs decreased between 0.5

Fig. 6. Results of batch experiments: open circles: empty control bottles, open triangles: abiotic sand control

(hw = 0.096), closed squares: live (biotic) sand (hw = 0.13).


and 5.5 h after VOC injection following first-order rate law (Fig. 6) with rate constants

ranging between 0.13F 0.13 day� 1 for methylcyclohexane and 0.91F 0.52 day� 1 for

toluene (Table 2). The gaseous concentrations of n-dodecane and to a lesser extent also of

n-decane and 1,2,4-trimethylbenzene (data not shown) decreased in an erratic manner,

suggesting condensation and sorption. No CO2 production or O2 consumption (data not

shown) was found. Total losses in sterile sand within 14 days ranged between 5% for

CFC-11 (Fig. 6) and 90% for m-xylene. In live sand, all compounds except n-octane and

MTBE decreased with first-order kinetics between 0.5 and 5.5 h after injection. First-order

rate constants evaluated from data points after 0.5 h in live sand are shown in Table 2. n-

Octane disappearance in live sand appeared to be fitted slightly better with a zero-order

than with a first-order rate law (Fig. 6), although the last data point may indicate that the

degradation rate declined slightly at a concentration below 0.03 g m� 3. MTBE decreased

for 2.5 h with neither a zero- nor a first-order law and was constant thereafter. CO2

production and O2 consumption within 5.5 h in live batch experiments were below

detection limit.

5. Discussion

5.1. Biomass formation with VOC vapors

An exposure experiment was carried out to follow changes in microbial biomass in

sand as a function of exposure to VOC vapors. A two-fold increase in microbial numbers

occurred within only 5 days of exposure (Fig. 2), suggesting that growth initially is not

limited by nutrients and that toxicity is not a major problem. As a consequence, batch

degradation experiments conducted to infer degradation kinetic parameters should be

significantly shorter to avoid influences of changing biomass. During longer exposure to

VOC vapors, the microbial numbers rose more slowly and the assumption of constant

biomass for exposure times of a few weeks may be justified.

5.2. Column experiment

A column experiment was conducted to study steady state VOC degradation after a

period of acclimatization dominated by sorption and air–water partitioning of VOC,

which is accounted for by the capacity factor Ra. During this period, some bacterial growth

took place as was seen from protein measurements in the column. Values for Ra were

calculated according to Pasteris et al. (2002) (Table 2). High Ra values are a result of a

strong tendency for of the compounds partitioning either into the aqueous phase (hydro-

philic compounds such as MTBE) or into the solid phase (hydrophobic compounds such

as n-dodecane). The time needed to reach steady state is linearly related to Ra. CFC-113

(Ra = 0.44) and MTBE (Ra = 5.6) reached linear concentration profiles after 1 and 21 days,

respectively (Fig. 3). The steady state is characterized by stable VOC concentration

profiles indicating that the sum of biomass production and specific degradation activity

and abiotic removal rate is constant and equals the mass-transfer rate. At steady state, the

Monod-no-growth model was applied to infer kinetic constants from instantaneous


concentration versus distance profiles, provided that certain assumptions (listed in the

theory section) are fulfilled. Some of these assumptions could be verified. An independent

gas tracer experiment performed in the column as described in Werner and Hohener (2002)

allowed the calculation of a tortuosity factor of 0.37F 0.02, which is in good agreement

with a value of 0.35 obtained using the Millington–Quirk relationship (Eq. (4)). The

dominance of diffusion as the transport process for VOCs was demonstrated by consistent

fluxes of the two inert compounds CFC-113 and MTBE through the column with respect

to Fick’s law. On day 21, fluxes of 0.17 and 0.91 g m� 2 day� 1 were measured at the

column outlet (Table 2), which were in agreement with calculated diffusion fluxes of 0.13

and 1.17 g m� 2 day� 1 for CFC-113 and MTBE, respectively.

VOC profiles along the column were compared with the analytical solution (Eqs. (6a)–

(6d)) of the coupled transport biodegradation model using first-order kinetics for

biodegradation (solid lines in Fig. 5). The good match of most profiles suggests that the

reactive transport model with first-order degradation is a useful approximation. Recalci-

trant or slowly biodegraded VOCs such as CFC-113 and MTBE exhibited linear profiles

with distance, in accordance to lc1 values < 0.01 day� 1 (Fig. 5). Easily biodegraded VOCs

such as n-octane and toluene exhibited strongly curved profiles with lc1 values larger than

one per day (see Table 2). A calculated n-octane profile obeying zero-order kinetics (Eqs.

(7a)–(7d)) was compared with the measured profile (Fig. 5) since n-octane degradation

had followed zero-order kinetics in batch experiments. However, the first-order model fit

measured data slightly better than the zero-order model (Fig. 5).

The biodegradation rates of n-octane, n-hexane, toluene, and m-xylene and compounds

deviated from first-order kinetics (Fig. 5) near the column inlet, thus allowing the

calculation of Monod kinetic constants. Fitting the data with the Ostendorf and Kampbell

(1991) approach (Eq. (10)) yields the lumped parameters HKs and vmaxDXhw from which

Ks and vmax were obtained by dividing by known H (Table 1) or estimates of DXhw,respectively. Table 3 compares the values obtained with those collected by a number of

other investigators using various experimental setups. There is considerable variability in

the data for each compound, which may be due to the kind of microbial community or the

experimental conditions. Nevertheless, a few general trends can be observed. For n-octane

and n-hexane, lower Ks values are reported than for BTX. Among the BTX, Ks values for

toluene are frequently smaller than for xylenes (Table 3). The results for the n-alkanes,

toluene, and m-xylene in this study show the same trend. The somewhat lower vmax for the

xylenes compared to toluene and n-octane may be explained by substrate toxicity at high

concentrations (Kelly et al., 1996). It should be noted that vmax express substrate utilization

rate on a basis of total cells, but, in studies with mixed substrates, not all cells may be

involved in the degradation of one specific substrate. This explains the relatively low vmax

obtained in our study and other mixed culture studies compared to values from pure

cultures growing on one substrate.

5.3. Batch experiments

The batch experiments in this study were designed to keep the ratio of soil to soil air as

close as possible to that in real soils, reducing the influence of sorption to stopper or to

glass, which was reported to be significant over long time scales (Ostendorf et al., 2000).


The duration of all experiments involving live sand was kept shorter than 0.3 days in order

to avoid also significant bacterial growth. As in the column experiment, vapor concen-

trations were monitored instead of aqueous concentrations. Occasional leaks in stoppers

were identified using the CFC data. Analytical problems were encountered for the three

compounds with the highest boiling temperatures, n-dodecane (216 jC), n-decane (174

jC), and 1,2,4-trimethylbenzene (169 jC), probably due to condensation of the vapors in

batch bottles and syringes used for sampling. It is concluded that the batch experimental

technique in this study can be applied only to VOCs with boiling temperatures smaller

than about 160–170 jC.After the initial addition of VOC vapors to sand, 0.5 h (2.5 h for MTBE) were needed

for diffusive mixing of the vapors in the bottle. The concentration versus time profiles

obtained thereafter were generally too inaccurate to distinguish unambiguously between

zero- or first-order kinetic rate laws for degradation (Fig. 6). However, the interpretation of

batch experimental data in terms of kinetic constants was seriously complicated by the fact

that only four VOCs had disappearance rates in live sand which were significantly larger

than disappearance rates in abiotic controls (Table 2). The use of large soil air (headspace)

to soil volumes ratios as, e.g., in the experiments by Allen-King et al. (1994a) or Zhou and

Crawford (1995) would minimize the importance of abiotic loss as compared to

biodegradation, but require much longer incubation, thereby increasing the probability

of bacterial growth or toxic effects.

For most compounds, two phases of disappearance were observed. Rapid abiotic losses

due to sorption and partitioning took place during the first 30 min after addition. They

were followed by slower sorption as can be seen from the abiotic controls and

biodegradation. Even for the recalcitrant CFCs, abiotic disappearance rates of 0.3 day� 1

were measured (Table 2). The slow ongoing sorption in abiotic batches may be interpreted

as intraparticle diffusion-limited approach of equilibrium between soil water and soil

particles. A characteristic of intraparticle diffusion is its dependency on the particle radius

a with faster sorption kinetics obtained with coarser materials (Grathwohl and Reinhard,

1993). In order to test this, abiotic batch experiments were performed using sieved sand

fractions (Fig. 7). Again rapid initial decline occurred within the first 0.5 h. Thereafter,

abiotic losses were more pronounced in the fraction 500 < a < 1000 Am and followed first-

order kinetics (Fig. 7), whereas in the sieve fraction 150 < a < 200 Am sorption obviously

nearly reached equilibrium within the first 30 min. Intraparticle diffusion is thus a likely

mechanism for abiotic loss of VOCs during short-term batch experiments. In a similar

batch experiment with poisoned sandy soil (Allen-King et al., 1994a), toluene vapor

concentration was found to decrease rapidly during the first hour, then more slowly during

the next 60 h and finally stayed constant during 600 h.

5.4. Comparison of data from column and batch experiments

The kinetic data obtained from both experimental approaches cannot be compared

directly due to the different nature of the experiments. Acclimatization of the sand in the

column led to growth of microorganisms and to a closer approach to sorption equilibrium.

At steady-state conditions in the column, a lumped first-order rate coefficient lc1

independent of sorption, partitioning, and retardation can be calculated. To estimate


first-order rates in the column approach, only the knowledge of diffusion coefficients is

needed. In batch experiments, VOC disappearance depends on Ra (Eqs. (11a) and (11b))

and the parameters therein (H, Kd, qb ha, hw). Estimation of the biodegradation rate in

batch experiments requires thus that all these parameters are accurately known. Further-

more, the gaseous concentrations in the column experiment at the column inlet (Fig. 5)

were about 10 times higher than the initial gaseous concentrations in the live batch

experiments (Fig. 6). At low concentrations, first-order rate laws are more likely to be

expected. All this makes it a priori difficult to compare kinetic rate data obtained with

these experiments. The first-order rate constants obtained in the column experiment can,

however, be compared with those obtained in the field lysimeter experiment (Pasteris et

al., 2002). A good correlation of first-order rate constants for all compounds is found for

those two experiments (Table 2).

6. Conclusions

Kinetic rate laws of VOC biodegradation in unsaturated alluvial sand were determined

in column and batch laboratory experiments. First-order kinetics was a good approxima-

tion for most of the compounds in both experimental systems, with n-octane as the only

exception out of 10 VOCs that were biodegraded. Only the column approach allowed us to

Fig. 7. Control batch experiment with abiotic sand: closed circles: sieve fractions 150–200 Am (hw = 0.042), opencircles: sieve fraction 500–1000 Am (hw = 0.056).


measure Monod kinetic parameters. The correct interpretation of kinetic biodegradation

parameters in unsaturated batch experiments remains a difficult task. Abiotic losses pose

problems when working in short incubations with large soil/headspace ratios and changes

in microbial communities pose problems when working in long-term incubations with low

soil/headspace ratios. The study confirms furthermore the recalcitrance of MTBE vapors.

Unlike, e.g., toluene or m-xylene vapors, MTBE vapors are not attenuated within 1.14 m

of homogeneous unsaturated alluvial sand.

Acknowledgements

This project is part of the European project Groundwater risk assessment at

contaminated sites GRACOS, EVK1-CT-1999-00029. Financial support was from the

Swiss Federal Office for Education and Science (BBW No. 99.0412). We thank David

Werner, Marjorie Aelion, and Robert Borden for helpful comments on the manuscript.

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